diff --git "a/ComVis_Tech_Assessment_Verihubs.ipynb" "b/ComVis_Tech_Assessment_Verihubs.ipynb"
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+++ "b/ComVis_Tech_Assessment_Verihubs.ipynb"
@@ -0,0 +1,7601 @@
+{
+  "cells": [
+    {
+      "cell_type": "code",
+      "execution_count": 1,
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/"
+        },
+        "id": "hLUuW5pTJuPT",
+        "outputId": "42b83dd7-f75c-48da-cdc9-bd76ebd7512c"
+      },
+      "outputs": [
+        {
+          "output_type": "stream",
+          "name": "stdout",
+          "text": [
+            "Requirement already satisfied: roboflow in /usr/local/lib/python3.10/dist-packages (1.1.29)\n",
+            "Requirement already satisfied: certifi==2023.7.22 in /usr/local/lib/python3.10/dist-packages (from roboflow) (2023.7.22)\n",
+            "Requirement already satisfied: chardet==4.0.0 in /usr/local/lib/python3.10/dist-packages (from roboflow) (4.0.0)\n",
+            "Requirement already satisfied: cycler==0.10.0 in /usr/local/lib/python3.10/dist-packages (from roboflow) (0.10.0)\n",
+            "Requirement already satisfied: idna==2.10 in /usr/local/lib/python3.10/dist-packages (from roboflow) (2.10)\n",
+            "Requirement already satisfied: kiwisolver>=1.3.1 in /usr/local/lib/python3.10/dist-packages (from roboflow) (1.4.5)\n",
+            "Requirement already satisfied: matplotlib in /usr/local/lib/python3.10/dist-packages (from roboflow) (3.7.1)\n",
+            "Requirement already satisfied: numpy>=1.18.5 in /usr/local/lib/python3.10/dist-packages (from roboflow) (1.25.2)\n",
+            "Requirement already satisfied: opencv-python-headless==4.8.0.74 in /usr/local/lib/python3.10/dist-packages (from roboflow) (4.8.0.74)\n",
+            "Requirement already satisfied: Pillow>=7.1.2 in /usr/local/lib/python3.10/dist-packages (from roboflow) (9.4.0)\n",
+            "Requirement already satisfied: python-dateutil in /usr/local/lib/python3.10/dist-packages (from roboflow) (2.8.2)\n",
+            "Requirement already satisfied: python-dotenv in /usr/local/lib/python3.10/dist-packages (from roboflow) (1.0.1)\n",
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+            "Requirement already satisfied: six in /usr/local/lib/python3.10/dist-packages (from roboflow) (1.16.0)\n",
+            "Requirement already satisfied: urllib3>=1.26.6 in /usr/local/lib/python3.10/dist-packages (from roboflow) (2.0.7)\n",
+            "Requirement already satisfied: tqdm>=4.41.0 in /usr/local/lib/python3.10/dist-packages (from roboflow) (4.66.4)\n",
+            "Requirement already satisfied: PyYAML>=5.3.1 in /usr/local/lib/python3.10/dist-packages (from roboflow) (6.0.1)\n",
+            "Requirement already satisfied: requests-toolbelt in /usr/local/lib/python3.10/dist-packages (from roboflow) (1.0.0)\n",
+            "Requirement already satisfied: python-magic in /usr/local/lib/python3.10/dist-packages (from roboflow) (0.4.27)\n",
+            "Requirement already satisfied: contourpy>=1.0.1 in /usr/local/lib/python3.10/dist-packages (from matplotlib->roboflow) (1.2.1)\n",
+            "Requirement already satisfied: fonttools>=4.22.0 in /usr/local/lib/python3.10/dist-packages (from matplotlib->roboflow) (4.51.0)\n",
+            "Requirement already satisfied: packaging>=20.0 in /usr/local/lib/python3.10/dist-packages (from matplotlib->roboflow) (24.0)\n",
+            "Requirement already satisfied: pyparsing>=2.3.1 in /usr/local/lib/python3.10/dist-packages (from matplotlib->roboflow) (3.1.2)\n",
+            "Requirement already satisfied: charset-normalizer<4,>=2 in /usr/local/lib/python3.10/dist-packages (from requests->roboflow) (3.3.2)\n",
+            "Collecting wandb==0.15.12\n",
+            "  Using cached wandb-0.15.12-py3-none-any.whl (2.1 MB)\n",
+            "Requirement already satisfied: Click!=8.0.0,>=7.1 in /usr/local/lib/python3.10/dist-packages (from wandb==0.15.12) (8.1.7)\n",
+            "Collecting GitPython!=3.1.29,>=1.0.0 (from wandb==0.15.12)\n",
+            "  Using cached GitPython-3.1.43-py3-none-any.whl (207 kB)\n",
+            "Requirement already satisfied: requests<3,>=2.0.0 in /usr/local/lib/python3.10/dist-packages (from wandb==0.15.12) (2.31.0)\n",
+            "Requirement already satisfied: psutil>=5.0.0 in /usr/local/lib/python3.10/dist-packages (from wandb==0.15.12) (5.9.5)\n",
+            "Collecting sentry-sdk>=1.0.0 (from wandb==0.15.12)\n",
+            "  Downloading sentry_sdk-2.2.1-py2.py3-none-any.whl (281 kB)\n",
+            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m281.6/281.6 kB\u001b[0m \u001b[31m4.2 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
+            "\u001b[?25hCollecting docker-pycreds>=0.4.0 (from wandb==0.15.12)\n",
+            "  Downloading docker_pycreds-0.4.0-py2.py3-none-any.whl (9.0 kB)\n",
+            "Requirement already satisfied: PyYAML in /usr/local/lib/python3.10/dist-packages (from wandb==0.15.12) (6.0.1)\n",
+            "Collecting pathtools (from wandb==0.15.12)\n",
+            "  Downloading pathtools-0.1.2.tar.gz (11 kB)\n",
+            "  Preparing metadata (setup.py) ... \u001b[?25l\u001b[?25hdone\n",
+            "Collecting setproctitle (from wandb==0.15.12)\n",
+            "  Downloading setproctitle-1.3.3-cp310-cp310-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl (30 kB)\n",
+            "Requirement already satisfied: setuptools in /usr/local/lib/python3.10/dist-packages (from wandb==0.15.12) (67.7.2)\n",
+            "Requirement already satisfied: appdirs>=1.4.3 in /usr/local/lib/python3.10/dist-packages (from wandb==0.15.12) (1.4.4)\n",
+            "Requirement already satisfied: protobuf!=4.21.0,<5,>=3.19.0 in /usr/local/lib/python3.10/dist-packages (from wandb==0.15.12) (3.20.3)\n",
+            "Requirement already satisfied: six>=1.4.0 in /usr/local/lib/python3.10/dist-packages (from docker-pycreds>=0.4.0->wandb==0.15.12) (1.16.0)\n",
+            "Collecting gitdb<5,>=4.0.1 (from GitPython!=3.1.29,>=1.0.0->wandb==0.15.12)\n",
+            "  Downloading gitdb-4.0.11-py3-none-any.whl (62 kB)\n",
+            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m62.7/62.7 kB\u001b[0m \u001b[31m7.3 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
+            "\u001b[?25hRequirement already satisfied: charset-normalizer<4,>=2 in /usr/local/lib/python3.10/dist-packages (from requests<3,>=2.0.0->wandb==0.15.12) (3.3.2)\n",
+            "Requirement already satisfied: idna<4,>=2.5 in /usr/local/lib/python3.10/dist-packages (from requests<3,>=2.0.0->wandb==0.15.12) (2.10)\n",
+            "Requirement already satisfied: urllib3<3,>=1.21.1 in /usr/local/lib/python3.10/dist-packages (from requests<3,>=2.0.0->wandb==0.15.12) (2.0.7)\n",
+            "Requirement already satisfied: certifi>=2017.4.17 in /usr/local/lib/python3.10/dist-packages (from requests<3,>=2.0.0->wandb==0.15.12) (2023.7.22)\n",
+            "Collecting smmap<6,>=3.0.1 (from gitdb<5,>=4.0.1->GitPython!=3.1.29,>=1.0.0->wandb==0.15.12)\n",
+            "  Downloading smmap-5.0.1-py3-none-any.whl (24 kB)\n",
+            "Building wheels for collected packages: pathtools\n",
+            "  Building wheel for pathtools (setup.py) ... \u001b[?25l\u001b[?25hdone\n",
+            "  Created wheel for pathtools: filename=pathtools-0.1.2-py3-none-any.whl size=8791 sha256=64de6a66e8b36654f7a0eedc926778646639da9d0872a196c03ba200aab96057\n",
+            "  Stored in directory: /root/.cache/pip/wheels/e7/f3/22/152153d6eb222ee7a56ff8617d80ee5207207a8c00a7aab794\n",
+            "Successfully built pathtools\n",
+            "Installing collected packages: pathtools, smmap, setproctitle, sentry-sdk, docker-pycreds, gitdb, GitPython, wandb\n",
+            "Successfully installed GitPython-3.1.43 docker-pycreds-0.4.0 gitdb-4.0.11 pathtools-0.1.2 sentry-sdk-2.2.1 setproctitle-1.3.3 smmap-5.0.1 wandb-0.15.12\n",
+            "Collecting ultralytics==8.0.186\n",
+            "  Using cached ultralytics-8.0.186-py3-none-any.whl (618 kB)\n",
+            "Requirement already satisfied: matplotlib>=3.3.0 in /usr/local/lib/python3.10/dist-packages (from ultralytics==8.0.186) (3.7.1)\n",
+            "Requirement already satisfied: numpy>=1.22.2 in /usr/local/lib/python3.10/dist-packages (from ultralytics==8.0.186) (1.25.2)\n",
+            "Requirement already satisfied: opencv-python>=4.6.0 in /usr/local/lib/python3.10/dist-packages (from ultralytics==8.0.186) (4.8.0.76)\n",
+            "Requirement already satisfied: pillow>=7.1.2 in /usr/local/lib/python3.10/dist-packages (from ultralytics==8.0.186) (9.4.0)\n",
+            "Requirement already satisfied: pyyaml>=5.3.1 in /usr/local/lib/python3.10/dist-packages (from ultralytics==8.0.186) (6.0.1)\n",
+            "Requirement already satisfied: requests>=2.23.0 in /usr/local/lib/python3.10/dist-packages (from ultralytics==8.0.186) (2.31.0)\n",
+            "Requirement already satisfied: scipy>=1.4.1 in /usr/local/lib/python3.10/dist-packages (from ultralytics==8.0.186) (1.11.4)\n",
+            "Requirement already satisfied: torch>=1.8.0 in /usr/local/lib/python3.10/dist-packages (from ultralytics==8.0.186) (2.3.0+cu121)\n",
+            "Requirement already satisfied: torchvision>=0.9.0 in /usr/local/lib/python3.10/dist-packages (from ultralytics==8.0.186) (0.18.0+cu121)\n",
+            "Requirement already satisfied: tqdm>=4.64.0 in /usr/local/lib/python3.10/dist-packages (from ultralytics==8.0.186) (4.66.4)\n",
+            "Requirement already satisfied: pandas>=1.1.4 in /usr/local/lib/python3.10/dist-packages (from ultralytics==8.0.186) (2.0.3)\n",
+            "Requirement already satisfied: seaborn>=0.11.0 in /usr/local/lib/python3.10/dist-packages (from ultralytics==8.0.186) (0.13.1)\n",
+            "Requirement already satisfied: psutil in /usr/local/lib/python3.10/dist-packages (from ultralytics==8.0.186) (5.9.5)\n",
+            "Requirement already satisfied: py-cpuinfo in /usr/local/lib/python3.10/dist-packages (from ultralytics==8.0.186) (9.0.0)\n",
+            "Requirement already satisfied: contourpy>=1.0.1 in /usr/local/lib/python3.10/dist-packages (from matplotlib>=3.3.0->ultralytics==8.0.186) (1.2.1)\n",
+            "Requirement already satisfied: cycler>=0.10 in /usr/local/lib/python3.10/dist-packages (from matplotlib>=3.3.0->ultralytics==8.0.186) (0.10.0)\n",
+            "Requirement already satisfied: fonttools>=4.22.0 in /usr/local/lib/python3.10/dist-packages (from matplotlib>=3.3.0->ultralytics==8.0.186) (4.51.0)\n",
+            "Requirement already satisfied: kiwisolver>=1.0.1 in /usr/local/lib/python3.10/dist-packages (from matplotlib>=3.3.0->ultralytics==8.0.186) (1.4.5)\n",
+            "Requirement already satisfied: packaging>=20.0 in /usr/local/lib/python3.10/dist-packages (from matplotlib>=3.3.0->ultralytics==8.0.186) (24.0)\n",
+            "Requirement already satisfied: pyparsing>=2.3.1 in /usr/local/lib/python3.10/dist-packages (from matplotlib>=3.3.0->ultralytics==8.0.186) (3.1.2)\n",
+            "Requirement already satisfied: python-dateutil>=2.7 in /usr/local/lib/python3.10/dist-packages (from matplotlib>=3.3.0->ultralytics==8.0.186) (2.8.2)\n",
+            "Requirement already satisfied: pytz>=2020.1 in /usr/local/lib/python3.10/dist-packages (from pandas>=1.1.4->ultralytics==8.0.186) (2023.4)\n",
+            "Requirement already satisfied: tzdata>=2022.1 in /usr/local/lib/python3.10/dist-packages (from pandas>=1.1.4->ultralytics==8.0.186) (2024.1)\n",
+            "Requirement already satisfied: charset-normalizer<4,>=2 in /usr/local/lib/python3.10/dist-packages (from requests>=2.23.0->ultralytics==8.0.186) (3.3.2)\n",
+            "Requirement already satisfied: idna<4,>=2.5 in /usr/local/lib/python3.10/dist-packages (from requests>=2.23.0->ultralytics==8.0.186) (2.10)\n",
+            "Requirement already satisfied: urllib3<3,>=1.21.1 in /usr/local/lib/python3.10/dist-packages (from requests>=2.23.0->ultralytics==8.0.186) (2.0.7)\n",
+            "Requirement already satisfied: certifi>=2017.4.17 in /usr/local/lib/python3.10/dist-packages (from requests>=2.23.0->ultralytics==8.0.186) (2023.7.22)\n",
+            "Requirement already satisfied: filelock in /usr/local/lib/python3.10/dist-packages (from torch>=1.8.0->ultralytics==8.0.186) (3.14.0)\n",
+            "Requirement already satisfied: typing-extensions>=4.8.0 in /usr/local/lib/python3.10/dist-packages (from torch>=1.8.0->ultralytics==8.0.186) (4.11.0)\n",
+            "Requirement already satisfied: sympy in /usr/local/lib/python3.10/dist-packages (from torch>=1.8.0->ultralytics==8.0.186) (1.12)\n",
+            "Requirement already satisfied: networkx in /usr/local/lib/python3.10/dist-packages (from torch>=1.8.0->ultralytics==8.0.186) (3.3)\n",
+            "Requirement already satisfied: jinja2 in /usr/local/lib/python3.10/dist-packages (from torch>=1.8.0->ultralytics==8.0.186) (3.1.4)\n",
+            "Requirement already satisfied: fsspec in /usr/local/lib/python3.10/dist-packages (from torch>=1.8.0->ultralytics==8.0.186) (2023.6.0)\n",
+            "Collecting nvidia-cuda-nvrtc-cu12==12.1.105 (from torch>=1.8.0->ultralytics==8.0.186)\n",
+            "  Using cached nvidia_cuda_nvrtc_cu12-12.1.105-py3-none-manylinux1_x86_64.whl (23.7 MB)\n",
+            "Collecting nvidia-cuda-runtime-cu12==12.1.105 (from torch>=1.8.0->ultralytics==8.0.186)\n",
+            "  Using cached nvidia_cuda_runtime_cu12-12.1.105-py3-none-manylinux1_x86_64.whl (823 kB)\n",
+            "Collecting nvidia-cuda-cupti-cu12==12.1.105 (from torch>=1.8.0->ultralytics==8.0.186)\n",
+            "  Using cached nvidia_cuda_cupti_cu12-12.1.105-py3-none-manylinux1_x86_64.whl (14.1 MB)\n",
+            "Collecting nvidia-cudnn-cu12==8.9.2.26 (from torch>=1.8.0->ultralytics==8.0.186)\n",
+            "  Using cached nvidia_cudnn_cu12-8.9.2.26-py3-none-manylinux1_x86_64.whl (731.7 MB)\n",
+            "Collecting nvidia-cublas-cu12==12.1.3.1 (from torch>=1.8.0->ultralytics==8.0.186)\n",
+            "  Using cached nvidia_cublas_cu12-12.1.3.1-py3-none-manylinux1_x86_64.whl (410.6 MB)\n",
+            "Collecting nvidia-cufft-cu12==11.0.2.54 (from torch>=1.8.0->ultralytics==8.0.186)\n",
+            "  Using cached nvidia_cufft_cu12-11.0.2.54-py3-none-manylinux1_x86_64.whl (121.6 MB)\n",
+            "Collecting nvidia-curand-cu12==10.3.2.106 (from torch>=1.8.0->ultralytics==8.0.186)\n",
+            "  Using cached nvidia_curand_cu12-10.3.2.106-py3-none-manylinux1_x86_64.whl (56.5 MB)\n",
+            "Collecting nvidia-cusolver-cu12==11.4.5.107 (from torch>=1.8.0->ultralytics==8.0.186)\n",
+            "  Using cached nvidia_cusolver_cu12-11.4.5.107-py3-none-manylinux1_x86_64.whl (124.2 MB)\n",
+            "Collecting nvidia-cusparse-cu12==12.1.0.106 (from torch>=1.8.0->ultralytics==8.0.186)\n",
+            "  Using cached nvidia_cusparse_cu12-12.1.0.106-py3-none-manylinux1_x86_64.whl (196.0 MB)\n",
+            "Collecting nvidia-nccl-cu12==2.20.5 (from torch>=1.8.0->ultralytics==8.0.186)\n",
+            "  Using cached nvidia_nccl_cu12-2.20.5-py3-none-manylinux2014_x86_64.whl (176.2 MB)\n",
+            "Collecting nvidia-nvtx-cu12==12.1.105 (from torch>=1.8.0->ultralytics==8.0.186)\n",
+            "  Using cached nvidia_nvtx_cu12-12.1.105-py3-none-manylinux1_x86_64.whl (99 kB)\n",
+            "Requirement already satisfied: triton==2.3.0 in /usr/local/lib/python3.10/dist-packages (from torch>=1.8.0->ultralytics==8.0.186) (2.3.0)\n",
+            "Collecting nvidia-nvjitlink-cu12 (from nvidia-cusolver-cu12==11.4.5.107->torch>=1.8.0->ultralytics==8.0.186)\n",
+            "  Using cached nvidia_nvjitlink_cu12-12.5.40-py3-none-manylinux2014_x86_64.whl (21.3 MB)\n",
+            "Requirement already satisfied: six in /usr/local/lib/python3.10/dist-packages (from cycler>=0.10->matplotlib>=3.3.0->ultralytics==8.0.186) (1.16.0)\n",
+            "Requirement already satisfied: MarkupSafe>=2.0 in /usr/local/lib/python3.10/dist-packages (from jinja2->torch>=1.8.0->ultralytics==8.0.186) (2.1.5)\n",
+            "Requirement already satisfied: mpmath>=0.19 in /usr/local/lib/python3.10/dist-packages (from sympy->torch>=1.8.0->ultralytics==8.0.186) (1.3.0)\n",
+            "Installing collected packages: nvidia-nvtx-cu12, nvidia-nvjitlink-cu12, nvidia-nccl-cu12, nvidia-curand-cu12, nvidia-cufft-cu12, nvidia-cuda-runtime-cu12, nvidia-cuda-nvrtc-cu12, nvidia-cuda-cupti-cu12, nvidia-cublas-cu12, nvidia-cusparse-cu12, nvidia-cudnn-cu12, nvidia-cusolver-cu12, ultralytics\n",
+            "Successfully installed nvidia-cublas-cu12-12.1.3.1 nvidia-cuda-cupti-cu12-12.1.105 nvidia-cuda-nvrtc-cu12-12.1.105 nvidia-cuda-runtime-cu12-12.1.105 nvidia-cudnn-cu12-8.9.2.26 nvidia-cufft-cu12-11.0.2.54 nvidia-curand-cu12-10.3.2.106 nvidia-cusolver-cu12-11.4.5.107 nvidia-cusparse-cu12-12.1.0.106 nvidia-nccl-cu12-2.20.5 nvidia-nvjitlink-cu12-12.5.40 nvidia-nvtx-cu12-12.1.105 ultralytics-8.0.186\n"
+          ]
+        }
+      ],
+      "source": [
+        "!pip install roboflow\n",
+        "!pip install wandb==0.15.12\n",
+        "!pip install ultralytics==8.0.186"
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {
+        "id": "W4bpYoXPdICN"
+      },
+      "source": [
+        "# Download Dataset"
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {
+        "id": "k2a4POcLdKPd"
+      },
+      "source": [
+        " I downloaded the dataset from Kaggle, and re-upload it to Roboflow. This dataset contains 807 images with 3,856 bounding boxes of 3 classes:\n",
+        "* `mask_weared_incorrect`\n",
+        "* `with_mask`\n",
+        "* `without_mask`\n",
+        "\n",
+        "After augmentations, the adataset are multiplied 3x into a total of 1,937 images.\n",
+        "\n",
+        "**Note**: You need to insert your Roboflow API key to run the cell below."
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 2,
+      "metadata": {
+        "id": "hK2DcESMHFwD",
+        "colab": {
+          "base_uri": "https://localhost:8080/"
+        },
+        "outputId": "55b5b3ab-c530-4b69-d4eb-1a21a25f7ffc"
+      },
+      "outputs": [
+        {
+          "output_type": "stream",
+          "name": "stdout",
+          "text": [
+            "··········\n",
+            "loading Roboflow workspace...\n",
+            "loading Roboflow project...\n",
+            "Dependency ultralytics==8.0.196 is required but found version=8.0.186, to fix: `pip install ultralytics==8.0.196`\n"
+          ]
+        },
+        {
+          "output_type": "stream",
+          "name": "stderr",
+          "text": [
+            "Downloading Dataset Version Zip in Face-Mask-Detection-1 to yolov8:: 100%|██████████| 122925/122925 [00:07<00:00, 15438.04it/s]"
+          ]
+        },
+        {
+          "output_type": "stream",
+          "name": "stdout",
+          "text": [
+            "\n"
+          ]
+        },
+        {
+          "output_type": "stream",
+          "name": "stderr",
+          "text": [
+            "\n",
+            "Extracting Dataset Version Zip to Face-Mask-Detection-1 in yolov8:: 100%|██████████| 3886/3886 [00:01<00:00, 2398.11it/s]\n"
+          ]
+        }
+      ],
+      "source": [
+        "from getpass import getpass\n",
+        "from roboflow import Roboflow\n",
+        "\n",
+        "rf = Roboflow(api_key=getpass())\n",
+        "project = rf.workspace(\"manfred-michael\").project(\"face-mask-detection-4zoki\")\n",
+        "version = project.version(1)\n",
+        "dataset = version.download(\"yolov8\")"
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {
+        "id": "VAvLch8RecBl"
+      },
+      "source": [
+        "The dataset would be splitted into 3 parts when we download it."
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {
+        "id": "9j2UItKteX5Q"
+      },
+      "source": [
+        "![image.png](data:image/png;base64,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)"
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {
+        "id": "SofVDqFBw5Oq"
+      },
+      "source": [
+        "All images in this dataset are already resized into 640x640 and it also includes augmented samples. So, I don't need to do any data preparation. Roboflow handled everything for me.\n"
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {
+        "id": "zO5bJpTMw5Oo"
+      },
+      "source": [
+        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)"
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {
+        "id": "JCYjNpydw5Os"
+      },
+      "source": [
+        "# Model Training"
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {
+        "id": "9eJha2Kyw5Os"
+      },
+      "source": [
+        "I will use ultralytics to train YOLOv8, and WandB to monitor the training process. This wandb tracking implementation includes some advanced features that we will see shortly."
+      ]
+    },
+    {
+      "cell_type": "code",
+      "source": [
+        "# !pip install wandb"
+      ],
+      "metadata": {
+        "id": "bOs6W9wX763m"
+      },
+      "execution_count": null,
+      "outputs": []
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 3,
+      "metadata": {
+        "id": "A79lfQaaQxY4",
+        "colab": {
+          "base_uri": "https://localhost:8080/"
+        },
+        "outputId": "ca66bfda-aef9-4865-ee23-646227e0d39e"
+      },
+      "outputs": [
+        {
+          "output_type": "stream",
+          "name": "stderr",
+          "text": [
+            "WARNING ⚠️ 'ultralytics.yolo.v8' is deprecated since '8.0.136' and will be removed in '8.1.0'. Please use 'ultralytics.models.yolo' instead.\n",
+            "WARNING ⚠️ 'ultralytics.yolo.utils' is deprecated since '8.0.136' and will be removed in '8.1.0'. Please use 'ultralytics.utils' instead.\n",
+            "Note this warning may be related to loading older models. You can update your model to current structure with:\n",
+            "    import torch\n",
+            "    ckpt = torch.load(\"model.pt\")  # applies to both official and custom models\n",
+            "    torch.save(ckpt, \"updated-model.pt\")\n",
+            "\n"
+          ]
+        }
+      ],
+      "source": [
+        "import wandb\n",
+        "from wandb.integration.ultralytics import add_wandb_callback\n",
+        "from PIL import Image\n",
+        "\n",
+        "from ultralytics import YOLO"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 310,
+          "referenced_widgets": [
+            "2146f10769064170acce6e7e8335cebd",
+            "be657624c5ea43c199921c4382f7a958",
+            "ae90885359d24008a3fd13e846a22246",
+            "9b71788bd91f46269093c90e8fb71c0c",
+            "fd1ba992d244494c972f0f97b775a0a7",
+            "f9879c9d97704b37b8d6c1fff1677d97",
+            "be3b792ad0714dfda173bd1a08979f74",
+            "86eaffd1aa4c47c0ba920352eb4551a5"
+          ]
+        },
+        "id": "mZzOItry66VU",
+        "outputId": "75f83701-6ed4-4760-e822-03eae536adce"
+      },
+      "outputs": [
+        {
+          "output_type": "display_data",
+          "data": {
+            "text/plain": [
+              "<IPython.core.display.HTML object>"
+            ],
+            "text/html": [
+              "Finishing last run (ID:bw243key) before initializing another..."
+            ]
+          },
+          "metadata": {}
+        },
+        {
+          "output_type": "display_data",
+          "data": {
+            "text/plain": [
+              "<IPython.core.display.HTML object>"
+            ],
+            "text/html": [
+              "Waiting for W&B process to finish... <strong style=\"color:green\">(success).</strong>"
+            ]
+          },
+          "metadata": {}
+        },
+        {
+          "output_type": "display_data",
+          "data": {
+            "text/plain": [
+              "VBox(children=(Label(value='0.001 MB of 0.004 MB uploaded (0.000 MB deduped)\\r'), FloatProgress(value=0.327454…"
+            ],
+            "application/vnd.jupyter.widget-view+json": {
+              "version_major": 2,
+              "version_minor": 0,
+              "model_id": "2146f10769064170acce6e7e8335cebd"
+            }
+          },
+          "metadata": {}
+        },
+        {
+          "output_type": "display_data",
+          "data": {
+            "text/plain": [
+              "<IPython.core.display.HTML object>"
+            ],
+            "text/html": [
+              " View run <strong style=\"color:#cdcd00\">copper-oath-3</strong> at: <a href='https://wandb.ai/anakbangkit/verihubs-tech-assessment/runs/bw243key' target=\"_blank\">https://wandb.ai/anakbangkit/verihubs-tech-assessment/runs/bw243key</a><br/>Synced 5 W&B file(s), 0 media file(s), 0 artifact file(s) and 0 other file(s)"
+            ]
+          },
+          "metadata": {}
+        },
+        {
+          "output_type": "display_data",
+          "data": {
+            "text/plain": [
+              "<IPython.core.display.HTML object>"
+            ],
+            "text/html": [
+              "Find logs at: <code>./wandb/run-20240522_071908-bw243key/logs</code>"
+            ]
+          },
+          "metadata": {}
+        },
+        {
+          "output_type": "display_data",
+          "data": {
+            "text/plain": [
+              "<IPython.core.display.HTML object>"
+            ],
+            "text/html": [
+              "Successfully finished last run (ID:bw243key). Initializing new run:<br/>"
+            ]
+          },
+          "metadata": {}
+        },
+        {
+          "output_type": "display_data",
+          "data": {
+            "text/plain": [
+              "<IPython.core.display.HTML object>"
+            ],
+            "text/html": [
+              "wandb version 0.17.0 is available!  To upgrade, please run:\n",
+              " $ pip install wandb --upgrade"
+            ]
+          },
+          "metadata": {}
+        },
+        {
+          "output_type": "display_data",
+          "data": {
+            "text/plain": [
+              "<IPython.core.display.HTML object>"
+            ],
+            "text/html": [
+              "Tracking run with wandb version 0.15.12"
+            ]
+          },
+          "metadata": {}
+        },
+        {
+          "output_type": "display_data",
+          "data": {
+            "text/plain": [
+              "<IPython.core.display.HTML object>"
+            ],
+            "text/html": [
+              "Run data is saved locally in <code>/content/wandb/run-20240522_071941-p127dd66</code>"
+            ]
+          },
+          "metadata": {}
+        },
+        {
+          "output_type": "display_data",
+          "data": {
+            "text/plain": [
+              "<IPython.core.display.HTML object>"
+            ],
+            "text/html": [
+              "Syncing run <strong><a href='https://wandb.ai/anakbangkit/verihubs-tech-assessment/runs/p127dd66' target=\"_blank\">ethereal-grass-4</a></strong> to <a href='https://wandb.ai/anakbangkit/verihubs-tech-assessment' target=\"_blank\">Weights & Biases</a> (<a href='https://wandb.me/run' target=\"_blank\">docs</a>)<br/>"
+            ]
+          },
+          "metadata": {}
+        },
+        {
+          "output_type": "display_data",
+          "data": {
+            "text/plain": [
+              "<IPython.core.display.HTML object>"
+            ],
+            "text/html": [
+              " View project at <a href='https://wandb.ai/anakbangkit/verihubs-tech-assessment' target=\"_blank\">https://wandb.ai/anakbangkit/verihubs-tech-assessment</a>"
+            ]
+          },
+          "metadata": {}
+        },
+        {
+          "output_type": "display_data",
+          "data": {
+            "text/plain": [
+              "<IPython.core.display.HTML object>"
+            ],
+            "text/html": [
+              " View run at <a href='https://wandb.ai/anakbangkit/verihubs-tech-assessment/runs/p127dd66' target=\"_blank\">https://wandb.ai/anakbangkit/verihubs-tech-assessment/runs/p127dd66</a>"
+            ]
+          },
+          "metadata": {}
+        },
+        {
+          "output_type": "execute_result",
+          "data": {
+            "text/html": [
+              "<button onClick=\"this.nextSibling.style.display='block';this.style.display='none';\">Display W&B run</button><iframe src='https://wandb.ai/anakbangkit/verihubs-tech-assessment/runs/p127dd66?jupyter=true' style='border:none;width:100%;height:420px;display:none;'></iframe>"
+            ],
+            "text/plain": [
+              "<wandb.sdk.wandb_run.Run at 0x7c5cf0437730>"
+            ]
+          },
+          "metadata": {},
+          "execution_count": 8
+        }
+      ],
+      "source": [
+        "wandb.init(project=\"verihubs-tech-assessment\", job_type=\"training\")"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/"
+        },
+        "id": "3QhRD12ABwT3",
+        "outputId": "b7597b66-87a1-4d14-9fa7-888085361f27"
+      },
+      "outputs": [
+        {
+          "output_type": "stream",
+          "name": "stderr",
+          "text": [
+            "Ultralytics YOLOv8.0.186 🚀 Python-3.10.12 torch-2.3.0+cu121 CUDA:0 (Tesla T4, 15102MiB)\n",
+            "Setup complete ✅ (2 CPUs, 12.7 GB RAM, 30.2/78.2 GB disk)\n"
+          ]
+        }
+      ],
+      "source": [
+        "import ultralytics\n",
+        "ultralytics.checks()"
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {
+        "id": "OjpabMQqw5Ot"
+      },
+      "source": [
+        "I trained YOLOv8 for 10 epochs."
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/"
+        },
+        "id": "2iFRJbtnQ6f8",
+        "outputId": "335d9641-7335-4439-f15d-9278d4bc527f"
+      },
+      "outputs": [
+        {
+          "output_type": "stream",
+          "name": "stderr",
+          "text": [
+            "\u001b[1;30;43mOutput streaming akan dipotong hingga 5000 baris terakhir.\u001b[0m\n",
+            "      28/80      8.54G       1.09      0.576      1.107         71        640: 100%|██████████| 106/106 [00:59<00:00,  1.79it/s]\n",
+            "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100%|██████████| 6/6 [00:02<00:00,  2.25it/s]\n",
+            "                   all        161        861      0.842      0.769      0.808      0.518\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss301_png.rf.79b160619414ca6a470bd5ea8b30ef4a.jpg: 640x640 22 with_masks, 5 without_masks, 47.9ms\n",
+            "Speed: 1.7ms preprocess, 47.9ms inference, 2.6ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss303_png.rf.f00ae35b4058b933e066d1d2a4d88c17.jpg: 640x640 4 with_masks, 37.2ms\n",
+            "Speed: 2.0ms preprocess, 37.2ms inference, 2.8ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss258_png.rf.fc7b4f2f14e1d199dce55985695d1120.jpg: 640x640 1 mask_weared_incorrect, 2 with_masks, 37.2ms\n",
+            "Speed: 1.7ms preprocess, 37.2ms inference, 2.0ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss304_png.rf.9df48cf93de57fa41d0a2b59de78a62c.jpg: 640x640 2 with_masks, 2 without_masks, 37.2ms\n",
+            "Speed: 1.8ms preprocess, 37.2ms inference, 2.0ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss224_png.rf.4539ed1dc0a709e4e01077ecf7bc2b22.jpg: 640x640 3 with_masks, 37.1ms\n",
+            "Speed: 1.8ms preprocess, 37.1ms inference, 2.2ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss20_png.rf.ca394d629ffaba1fdb13e432a79a5eb9.jpg: 640x640 1 with_mask, 7 without_masks, 37.1ms\n",
+            "Speed: 1.9ms preprocess, 37.1ms inference, 2.1ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss109_png.rf.3c26f7537566830dffb39c47f71e574e.jpg: 640x640 1 with_mask, 37.1ms\n",
+            "Speed: 1.8ms preprocess, 37.1ms inference, 2.0ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss114_png.rf.c087c8382ac2542ac89314fa0bbeb4f6.jpg: 640x640 1 with_mask, 3 without_masks, 37.1ms\n",
+            "Speed: 1.5ms preprocess, 37.1ms inference, 2.0ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss127_png.rf.1baab62c26cbf4478f2a8d99e1cf68de.jpg: 640x640 1 with_mask, 1 without_mask, 37.2ms\n",
+            "Speed: 1.8ms preprocess, 37.2ms inference, 2.0ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss146_png.rf.ec0da30308aa466d39bae79b0cc0e2bf.jpg: 640x640 4 with_masks, 2 without_masks, 37.2ms\n",
+            "Speed: 1.7ms preprocess, 37.2ms inference, 3.0ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss152_png.rf.c66bb39b29efc7503239890f834100dc.jpg: 640x640 7 with_masks, 37.1ms\n",
+            "Speed: 1.9ms preprocess, 37.1ms inference, 2.1ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss154_png.rf.7512e06f4e0bd3a2185ec1867603cc8a.jpg: 640x640 1 with_mask, 1 without_mask, 37.1ms\n",
+            "Speed: 1.8ms preprocess, 37.1ms inference, 2.4ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss168_png.rf.3b19cb741e672eef23c3f091fd204d52.jpg: 640x640 4 with_masks, 6 without_masks, 37.2ms\n",
+            "Speed: 1.7ms preprocess, 37.2ms inference, 2.0ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss217_png.rf.c4e305ead91154374bba4fc48e0e3b99.jpg: 640x640 1 with_mask, 1 without_mask, 37.1ms\n",
+            "Speed: 1.4ms preprocess, 37.1ms inference, 2.1ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss169_png.rf.49a3d702f1cd1ce83aa6cd01599e3644.jpg: 640x640 1 with_mask, 37.2ms\n",
+            "Speed: 2.1ms preprocess, 37.2ms inference, 2.2ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss174_png.rf.ba1760e663e246482b26e587332650b0.jpg: 640x640 4 with_masks, 37.2ms\n",
+            "Speed: 1.7ms preprocess, 37.2ms inference, 2.1ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss178_png.rf.2fd8857c96b9bed1982f78b55798a334.jpg: 640x640 2 with_masks, 2 without_masks, 37.3ms\n",
+            "Speed: 2.1ms preprocess, 37.3ms inference, 2.0ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss194_png.rf.77ed2eca9fe5235cf2496449dd156996.jpg: 640x640 3 with_masks, 37.1ms\n",
+            "Speed: 2.1ms preprocess, 37.1ms inference, 2.0ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss197_png.rf.cd0c6b120a0fae906bb417f825daf6a1.jpg: 640x640 1 with_mask, 37.1ms\n",
+            "Speed: 1.6ms preprocess, 37.1ms inference, 2.1ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss1_png.rf.e41f0052ad0e49cab0887d6e50e5a7eb.jpg: 640x640 8 with_masks, 1 without_mask, 37.3ms\n",
+            "Speed: 2.3ms preprocess, 37.3ms inference, 2.1ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss203_png.rf.eba7307a461c6b2098593e82d2cccecc.jpg: 640x640 5 with_masks, 37.2ms\n",
+            "Speed: 1.8ms preprocess, 37.2ms inference, 2.0ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss206_png.rf.68794173883f5ae26e2382a3087aac0b.jpg: 640x640 12 with_masks, 3 without_masks, 37.2ms\n",
+            "Speed: 1.7ms preprocess, 37.2ms inference, 2.2ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss172_png.rf.13bb93a8bf5266e0d73bab43f62e0376.jpg: 640x640 1 with_mask, 1 without_mask, 37.1ms\n",
+            "Speed: 1.6ms preprocess, 37.1ms inference, 2.2ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss306_png.rf.52a38aff8eebcfb7d90d0c7cac38fdec.jpg: 640x640 2 with_masks, 37.1ms\n",
+            "Speed: 2.2ms preprocess, 37.1ms inference, 2.2ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss307_png.rf.93b21e5a88a625f2a9284ff6253bd417.jpg: 640x640 1 mask_weared_incorrect, 1 with_mask, 5 without_masks, 37.2ms\n",
+            "Speed: 2.0ms preprocess, 37.2ms inference, 2.3ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss308_png.rf.61a249cc68e67a9cf66c2393f61080f2.jpg: 640x640 4 with_masks, 37.1ms\n",
+            "Speed: 1.7ms preprocess, 37.1ms inference, 2.3ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss402_png.rf.adb70e16aac43aa519466a4364f99311.jpg: 640x640 1 with_mask, 1 without_mask, 37.1ms\n",
+            "Speed: 1.8ms preprocess, 37.1ms inference, 2.0ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss408_png.rf.bb077fd8dd6090c8f22b2dfe4fb0b2dc.jpg: 640x640 8 with_masks, 2 without_masks, 37.1ms\n",
+            "Speed: 1.7ms preprocess, 37.1ms inference, 2.2ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss409_png.rf.a1da634820d49e7be38ce59f5f5887bb.jpg: 640x640 1 with_mask, 4 without_masks, 37.1ms\n",
+            "Speed: 2.0ms preprocess, 37.1ms inference, 2.1ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss410_png.rf.eaad04d3f7e7468f6a0a3d017306d6da.jpg: 640x640 1 mask_weared_incorrect, 25 with_masks, 4 without_masks, 37.1ms\n",
+            "Speed: 1.7ms preprocess, 37.1ms inference, 2.2ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss418_png.rf.432d10d262677cb69e95be55ca0c9125.jpg: 640x640 2 with_masks, 37.2ms\n",
+            "Speed: 1.9ms preprocess, 37.2ms inference, 2.2ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss421_png.rf.7ecb66f6ba285fd631717a3635a7dd71.jpg: 640x640 5 with_masks, 1 without_mask, 37.3ms\n",
+            "Speed: 1.9ms preprocess, 37.3ms inference, 2.1ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n",
+            "      29/80       8.6G      1.077     0.5726      1.101        103        640: 100%|██████████| 106/106 [00:58<00:00,  1.82it/s]\n",
+            "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100%|██████████| 6/6 [00:03<00:00,  1.83it/s]\n",
+            "                   all        161        861      0.881      0.753      0.825      0.539\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss425_png.rf.b69c6da9a6c99fd8edfdad09f10582d2.jpg: 640x640 1 with_mask, 38.3ms\n",
+            "Speed: 5.0ms preprocess, 38.3ms inference, 9.6ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss400_png.rf.63c84ce5e3e0391c9509f77d2244755c.jpg: 640x640 5 with_masks, 37.2ms\n",
+            "Speed: 1.8ms preprocess, 37.2ms inference, 3.3ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss429_png.rf.0f9bc0b4f072650f40e985eefdce87df.jpg: 640x640 4 with_masks, 37.1ms\n",
+            "Speed: 1.6ms preprocess, 37.1ms inference, 2.1ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss438_png.rf.85978160d8cedb7d56a26e0d06e41f87.jpg: 640x640 4 with_masks, 37.1ms\n",
+            "Speed: 2.4ms preprocess, 37.1ms inference, 2.1ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss440_png.rf.641564d43589f6344bacc5d05d51da53.jpg: 640x640 2 mask_weared_incorrects, 10 with_masks, 2 without_masks, 37.1ms\n",
+            "Speed: 2.0ms preprocess, 37.1ms inference, 2.2ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss44_png.rf.b6697a646548922305672e657697750b.jpg: 640x640 4 with_masks, 37.1ms\n",
+            "Speed: 1.7ms preprocess, 37.1ms inference, 2.2ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss450_png.rf.8f5e0ff6c7228f1180f985685beb20d5.jpg: 640x640 4 with_masks, 37.2ms\n",
+            "Speed: 1.9ms preprocess, 37.2ms inference, 2.2ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss457_png.rf.60b3bf773c197a83826aae38a0cf2387.jpg: 640x640 4 with_masks, 1 without_mask, 37.2ms\n",
+            "Speed: 1.7ms preprocess, 37.2ms inference, 2.5ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss459_png.rf.73bd4ff56e948804a4c7d5cc9e2f98ef.jpg: 640x640 2 mask_weared_incorrects, 2 with_masks, 1 without_mask, 37.1ms\n",
+            "Speed: 2.5ms preprocess, 37.1ms inference, 2.1ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss45_png.rf.3b160c8afb75253926e1abf7b4972504.jpg: 640x640 1 with_mask, 1 without_mask, 37.2ms\n",
+            "Speed: 1.9ms preprocess, 37.2ms inference, 2.4ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss431_png.rf.c5e66fbd5f544edca4f20973ce5ecf08.jpg: 640x640 1 mask_weared_incorrect, 21 with_masks, 37.1ms\n",
+            "Speed: 1.9ms preprocess, 37.1ms inference, 2.1ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss395_png.rf.d0fd9e7ac741d7df48a86b7f291e9b49.jpg: 640x640 1 with_mask, 37.2ms\n",
+            "Speed: 1.8ms preprocess, 37.2ms inference, 2.0ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss389_png.rf.11956fb49c814dab304f0006b9075f71.jpg: 640x640 14 with_masks, 1 without_mask, 37.1ms\n",
+            "Speed: 1.8ms preprocess, 37.1ms inference, 2.1ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss388_png.rf.4847bd339895b2496b21a16876aca440.jpg: 640x640 1 mask_weared_incorrect, 10 with_masks, 9 without_masks, 37.3ms\n",
+            "Speed: 2.0ms preprocess, 37.3ms inference, 2.3ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss311_png.rf.8d4e3cc30ab76d6699d7f220a26286dd.jpg: 640x640 5 with_masks, 37.1ms\n",
+            "Speed: 1.8ms preprocess, 37.1ms inference, 2.1ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss313_png.rf.0d2ede745cca1bbc73883747763be4cb.jpg: 640x640 1 with_mask, 37.1ms\n",
+            "Speed: 1.7ms preprocess, 37.1ms inference, 2.0ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss315_png.rf.bdcb0e2cde8b888d72849bbf232bc644.jpg: 640x640 2 with_masks, 37.4ms\n",
+            "Speed: 2.0ms preprocess, 37.4ms inference, 2.3ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss31_png.rf.f71dabc8b32a5181ae4a7ec0724d169e.jpg: 640x640 2 with_masks, 37.1ms\n",
+            "Speed: 1.8ms preprocess, 37.1ms inference, 2.2ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss321_png.rf.d5ca9ccecbb235c5551003b177cd1d46.jpg: 640x640 1 mask_weared_incorrect, 2 with_masks, 1 without_mask, 37.2ms\n",
+            "Speed: 1.9ms preprocess, 37.2ms inference, 2.4ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss330_png.rf.ca2fe4eca45ae4b2bc6bb9fde6d39dff.jpg: 640x640 4 with_masks, 37.1ms\n",
+            "Speed: 1.7ms preprocess, 37.1ms inference, 2.0ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss338_png.rf.669c284dd81181d71654743a3ca9aeb3.jpg: 640x640 10 with_masks, 37.1ms\n",
+            "Speed: 2.0ms preprocess, 37.1ms inference, 2.1ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss339_png.rf.d26efdd756cada62599cd227994bbf56.jpg: 640x640 1 with_mask, 37.1ms\n",
+            "Speed: 1.7ms preprocess, 37.1ms inference, 2.0ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss343_png.rf.1c5c7bbcb828a1cf9d4d2584972083cb.jpg: 640x640 1 with_mask, 1 without_mask, 37.2ms\n",
+            "Speed: 1.9ms preprocess, 37.2ms inference, 2.3ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss351_png.rf.15436d1eb7080d7bae2e79d554a4d3cb.jpg: 640x640 1 with_mask, 37.2ms\n",
+            "Speed: 1.6ms preprocess, 37.2ms inference, 2.0ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss364_png.rf.74e470c60f166ba4ec1a268b153fa240.jpg: 640x640 3 with_masks, 37.2ms\n",
+            "Speed: 1.8ms preprocess, 37.2ms inference, 2.5ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss366_png.rf.433ea8f6b4fcab0d951b52116611c1be.jpg: 640x640 2 with_masks, 37.1ms\n",
+            "Speed: 1.8ms preprocess, 37.1ms inference, 2.3ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss368_png.rf.1d14fe4224d1b152c5e272d889fe3d45.jpg: 640x640 9 with_masks, 37.4ms\n",
+            "Speed: 2.0ms preprocess, 37.4ms inference, 2.3ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss374_png.rf.b51c420d86fc3a474ed557b5a230b51e.jpg: 640x640 5 with_masks, 1 without_mask, 37.1ms\n",
+            "Speed: 2.1ms preprocess, 37.1ms inference, 2.0ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss376_png.rf.ca418b2ffccc242892a1ab14657e8349.jpg: 640x640 7 with_masks, 37.1ms\n",
+            "Speed: 1.7ms preprocess, 37.1ms inference, 2.2ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss37_png.rf.60ce2ff44ae089a01d8f07ff2e0f00ad.jpg: 640x640 1 with_mask, 37.1ms\n",
+            "Speed: 1.8ms preprocess, 37.1ms inference, 2.0ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss387_png.rf.6d027b3075e33a4414cc245ec7435fcc.jpg: 640x640 1 mask_weared_incorrect, 5 with_masks, 1 without_mask, 37.1ms\n",
+            "Speed: 1.7ms preprocess, 37.1ms inference, 2.0ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss464_png.rf.b7d07a0f6aabc271e6bfbe039246786b.jpg: 640x640 6 with_masks, 37.1ms\n",
+            "Speed: 1.7ms preprocess, 37.1ms inference, 2.1ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n",
+            "      30/80      8.64G      1.076     0.5669      1.098         86        640: 100%|██████████| 106/106 [01:00<00:00,  1.76it/s]\n",
+            "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100%|██████████| 6/6 [00:03<00:00,  1.73it/s]\n",
+            "                   all        161        861      0.902      0.709      0.812      0.525\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss90_png.rf.bb3401c96e9aba7db607a9a5ac8d8f51.jpg: 640x640 10 with_masks, 41.6ms\n",
+            "Speed: 7.2ms preprocess, 41.6ms inference, 2.7ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n",
+            "      31/80      8.72G      1.071     0.5658      1.102        115        640: 100%|██████████| 106/106 [00:59<00:00,  1.79it/s]\n",
+            "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100%|██████████| 6/6 [00:03<00:00,  1.53it/s]\n",
+            "                   all        161        861      0.799      0.751      0.786      0.497\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss107_png.rf.285757ad3a789f0d69380282b3bdb846.jpg: 640x640 1 with_mask, 38.5ms\n",
+            "Speed: 3.9ms preprocess, 38.5ms inference, 11.3ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss569_png.rf.245d020288f15a704c2742a49eb1ca63.jpg: 640x640 1 with_mask, 37.4ms\n",
+            "Speed: 1.9ms preprocess, 37.4ms inference, 5.2ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss56_png.rf.ffec370c63bb3ee301d05f9ce072e3fa.jpg: 640x640 1 with_mask, 37.1ms\n",
+            "Speed: 1.9ms preprocess, 37.1ms inference, 2.1ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss577_png.rf.99d8deb18d344f24bb95f02394713470.jpg: 640x640 15 with_masks, 1 without_mask, 37.2ms\n",
+            "Speed: 1.7ms preprocess, 37.2ms inference, 2.5ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss585_png.rf.16b40d54481e86f0a1434d30bc6d9c64.jpg: 640x640 4 with_masks, 3 without_masks, 37.2ms\n",
+            "Speed: 2.1ms preprocess, 37.2ms inference, 2.1ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss595_png.rf.f3a260412881f24273c64d6bd6e1966b.jpg: 640x640 6 with_masks, 37.3ms\n",
+            "Speed: 1.8ms preprocess, 37.3ms inference, 2.1ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss596_png.rf.9bf29752ebe873bc099ff9b64ddef6d1.jpg: 640x640 1 with_mask, 37.2ms\n",
+            "Speed: 1.8ms preprocess, 37.2ms inference, 2.1ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss603_png.rf.0d06c5299fd1cf3136e68b97a2afa4fd.jpg: 640x640 108 with_masks, 23 without_masks, 37.2ms\n",
+            "Speed: 2.0ms preprocess, 37.2ms inference, 2.2ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss568_png.rf.a4d4a4e139954b5194617ef2e9ffc81c.jpg: 640x640 1 with_mask, 37.2ms\n",
+            "Speed: 2.1ms preprocess, 37.2ms inference, 2.3ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss608_png.rf.4806b67fedacda192a8448bcf3b53d64.jpg: 640x640 1 with_mask, 37.1ms\n",
+            "Speed: 1.9ms preprocess, 37.1ms inference, 2.0ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss623_png.rf.19a2c6b529d5478510934f467949c887.jpg: 640x640 2 mask_weared_incorrects, 21 with_masks, 3 without_masks, 37.1ms\n",
+            "Speed: 1.7ms preprocess, 37.1ms inference, 2.1ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss626_png.rf.4a2f1a57a893fdcef400930251142f52.jpg: 640x640 1 with_mask, 37.1ms\n",
+            "Speed: 1.5ms preprocess, 37.1ms inference, 2.4ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss627_png.rf.81b096f6b0f9e897cc64f59880e630e0.jpg: 640x640 3 mask_weared_incorrects, 10 with_masks, 6 without_masks, 37.2ms\n",
+            "Speed: 1.8ms preprocess, 37.2ms inference, 2.1ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss630_png.rf.d1ecd7de587fb5c2571563293babff62.jpg: 640x640 1 with_mask, 37.1ms\n",
+            "Speed: 1.8ms preprocess, 37.1ms inference, 2.1ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss631_png.rf.418be1a60a0224818dc54e0d2281c6f4.jpg: 640x640 11 with_masks, 37.1ms\n",
+            "Speed: 2.0ms preprocess, 37.1ms inference, 2.2ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss636_png.rf.e6889a20be3cb52fa81b195fdef01b58.jpg: 640x640 7 with_masks, 2 without_masks, 37.2ms\n",
+            "Speed: 2.0ms preprocess, 37.2ms inference, 2.2ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss645_png.rf.d577b2fbdae8c09e7cb396b9c14f18d7.jpg: 640x640 1 with_mask, 37.3ms\n",
+            "Speed: 1.7ms preprocess, 37.3ms inference, 2.0ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss619_png.rf.bc1dcbfae2f9104ce082afe801399f54.jpg: 640x640 3 with_masks, 1 without_mask, 37.1ms\n",
+            "Speed: 1.7ms preprocess, 37.1ms inference, 2.1ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss646_png.rf.a434ddc2569b34a89bbb07a259996497.jpg: 640x640 1 with_mask, 37.2ms\n",
+            "Speed: 2.1ms preprocess, 37.2ms inference, 2.1ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss563_png.rf.dc088c07f08e5fba01fd6bddeceb27e2.jpg: 640x640 2 with_masks, 37.1ms\n",
+            "Speed: 2.2ms preprocess, 37.1ms inference, 2.1ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss554_png.rf.ba664c8fdc34b11faff3a128d06dbe9a.jpg: 640x640 5 with_masks, 37.2ms\n",
+            "Speed: 2.0ms preprocess, 37.2ms inference, 2.1ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss473_png.rf.6de35811442245ad013a2676e2bcaa0a.jpg: 640x640 4 with_masks, 1 without_mask, 37.2ms\n",
+            "Speed: 1.9ms preprocess, 37.2ms inference, 2.1ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss477_png.rf.0e319d347398d08b8a52fb6a152de44e.jpg: 640x640 8 with_masks, 7 without_masks, 37.2ms\n",
+            "Speed: 1.8ms preprocess, 37.2ms inference, 2.1ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss481_png.rf.6682292ffe5179b26d46c8515797446e.jpg: 640x640 7 with_masks, 37.1ms\n",
+            "Speed: 1.7ms preprocess, 37.1ms inference, 2.1ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss483_png.rf.4c059c2770f996153e3487a7f52f771c.jpg: 640x640 3 with_masks, 2 without_masks, 37.2ms\n",
+            "Speed: 1.8ms preprocess, 37.2ms inference, 2.9ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss484_png.rf.a57bfdb112b858aa9ed93bf36306ac61.jpg: 640x640 1 mask_weared_incorrect, 1 with_mask, 37.2ms\n",
+            "Speed: 3.0ms preprocess, 37.2ms inference, 2.0ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss498_png.rf.095899d089070e7a5a7697113b108f8a.jpg: 640x640 9 with_masks, 4 without_masks, 37.1ms\n",
+            "Speed: 1.8ms preprocess, 37.1ms inference, 2.1ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss499_png.rf.611bdf8f03aea1d86028c7b5d7d494ec.jpg: 640x640 1 with_mask, 2 without_masks, 37.1ms\n",
+            "Speed: 1.9ms preprocess, 37.1ms inference, 3.1ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss560_png.rf.bc8e65e2733e0f7b723391d33c380fe0.jpg: 640x640 2 with_masks, 1 without_mask, 38.2ms\n",
+            "Speed: 1.8ms preprocess, 38.2ms inference, 2.6ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss49_png.rf.d4077078d124ff3d3d699fc94bd06150.jpg: 640x640 8 with_masks, 3 without_masks, 37.2ms\n",
+            "Speed: 1.8ms preprocess, 37.2ms inference, 2.6ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss509_png.rf.6470c0dd2a6a4b05117cca6aad267087.jpg: 640x640 (no detections), 37.2ms\n",
+            "Speed: 1.8ms preprocess, 37.2ms inference, 1.6ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss512_png.rf.8dbd72e69a164fdcdad2e220bcd0c467.jpg: 640x640 8 with_masks, 37.1ms\n",
+            "Speed: 1.8ms preprocess, 37.1ms inference, 2.6ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n",
+            "      32/80      8.79G      1.071     0.5651      1.096        106        640: 100%|██████████| 106/106 [01:00<00:00,  1.76it/s]\n",
+            "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100%|██████████| 6/6 [00:02<00:00,  2.22it/s]\n",
+            "                   all        161        861      0.836      0.805      0.828      0.527\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss515_png.rf.9b8d660e9368ee9ccfeb977e609167ed.jpg: 640x640 1 with_mask, 38.5ms\n",
+            "Speed: 1.7ms preprocess, 38.5ms inference, 2.8ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss529_png.rf.6ae323861cb838fc945c80ee31070c4c.jpg: 640x640 6 with_masks, 1 without_mask, 37.2ms\n",
+            "Speed: 2.3ms preprocess, 37.2ms inference, 3.6ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss532_png.rf.03aa559343f932efbfa3753190291fa7.jpg: 640x640 1 with_mask, 37.2ms\n",
+            "Speed: 1.8ms preprocess, 37.2ms inference, 2.2ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss537_png.rf.f22f4997ea93880ebfa2cb19a893caad.jpg: 640x640 1 without_mask, 37.1ms\n",
+            "Speed: 1.7ms preprocess, 37.1ms inference, 2.1ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss551_png.rf.010062fb38326dac49ecca8d9322953f.jpg: 640x640 5 with_masks, 37.2ms\n",
+            "Speed: 2.0ms preprocess, 37.2ms inference, 2.3ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss501_png.rf.125122fa5a318ec6d0e27d632764f840.jpg: 640x640 8 with_masks, 1 without_mask, 37.2ms\n",
+            "Speed: 2.0ms preprocess, 37.2ms inference, 2.2ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss649_png.rf.5540865cd8826940d55b3b48c045183c.jpg: 640x640 1 with_mask, 37.1ms\n",
+            "Speed: 2.0ms preprocess, 37.1ms inference, 2.3ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss64_png.rf.4b8ca34d17365fb62029fdbee94cb0aa.jpg: 640x640 3 with_masks, 37.2ms\n",
+            "Speed: 1.7ms preprocess, 37.2ms inference, 2.2ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss653_png.rf.22cf40d34bad20f7f9b542b6a0a89e2f.jpg: 640x640 2 with_masks, 37.2ms\n",
+            "Speed: 1.8ms preprocess, 37.2ms inference, 2.1ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss787_png.rf.a7e026e8082789734a57252cf6df81e5.jpg: 640x640 8 with_masks, 2 without_masks, 37.2ms\n",
+            "Speed: 1.9ms preprocess, 37.2ms inference, 2.4ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss793_png.rf.dd2be948b6231ceb68a6af8371f2329c.jpg: 640x640 2 with_masks, 37.1ms\n",
+            "Speed: 1.8ms preprocess, 37.1ms inference, 2.1ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss797_png.rf.5ead12df141e267f928b7b34c73dfb1a.jpg: 640x640 10 with_masks, 2 without_masks, 37.2ms\n",
+            "Speed: 1.7ms preprocess, 37.2ms inference, 2.1ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss79_png.rf.e12280d9bd602d3e52504b83921437d6.jpg: 640x640 5 with_masks, 37.2ms\n",
+            "Speed: 1.8ms preprocess, 37.2ms inference, 2.2ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss806_png.rf.504dc192775390a4b3f7d6b85bc58636.jpg: 640x640 8 with_masks, 2 without_masks, 37.1ms\n",
+            "Speed: 1.7ms preprocess, 37.1ms inference, 2.3ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss808_png.rf.b2e534caaaf701b8674add21e64fd528.jpg: 640x640 1 with_mask, 37.1ms\n",
+            "Speed: 1.9ms preprocess, 37.1ms inference, 2.1ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss822_png.rf.8601f2a416cbe3f239fde9934f5f66d2.jpg: 640x640 16 with_masks, 5 without_masks, 37.1ms\n",
+            "Speed: 1.5ms preprocess, 37.1ms inference, 2.3ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss784_png.rf.b95afb3096062e72503f25dfdaf53f52.jpg: 640x640 8 with_masks, 1 without_mask, 37.2ms\n",
+            "Speed: 1.6ms preprocess, 37.2ms inference, 2.2ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss828_png.rf.ef40e6fb83c895f7c4ca491dadbcecb1.jpg: 640x640 1 with_mask, 37.2ms\n",
+            "Speed: 2.5ms preprocess, 37.2ms inference, 2.0ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss832_png.rf.fd2d4b0fa4b62433e71f92aa8f1bc067.jpg: 640x640 1 mask_weared_incorrect, 2 without_masks, 37.2ms\n",
+            "Speed: 2.0ms preprocess, 37.2ms inference, 2.3ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss834_png.rf.c14acf559bb5531c92d3cf19a5193aa2.jpg: 640x640 5 with_masks, 37.1ms\n",
+            "Speed: 1.8ms preprocess, 37.1ms inference, 2.1ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss835_png.rf.b8a44eb8c868a51999b450873338a62a.jpg: 640x640 1 with_mask, 37.1ms\n",
+            "Speed: 1.5ms preprocess, 37.1ms inference, 2.0ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss840_png.rf.78c778f16a6a87f204473b70c7e735b1.jpg: 640x640 2 with_masks, 37.2ms\n",
+            "Speed: 2.4ms preprocess, 37.2ms inference, 3.2ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss844_png.rf.98f015b79733ae45cfff40da2c6eb85c.jpg: 640x640 2 with_masks, 38.1ms\n",
+            "Speed: 1.8ms preprocess, 38.1ms inference, 3.2ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss846_png.rf.f600f86418cd50b99d7116344abfe0df.jpg: 640x640 1 with_mask, 37.3ms\n",
+            "Speed: 1.9ms preprocess, 37.3ms inference, 2.7ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss848_png.rf.a1793122f2a5ab2b5a3d7be92157ea6b.jpg: 640x640 3 with_masks, 37.2ms\n",
+            "Speed: 4.1ms preprocess, 37.2ms inference, 2.6ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss830_png.rf.c8684a6a7e69bd43d4d35d54f2004fd7.jpg: 640x640 1 mask_weared_incorrect, 1 with_mask, 37.2ms\n",
+            "Speed: 1.9ms preprocess, 37.2ms inference, 2.9ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss761_png.rf.666e2aaecaf296dc7fe39031d857300a.jpg: 640x640 1 mask_weared_incorrect, 1 with_mask, 37.2ms\n",
+            "Speed: 1.9ms preprocess, 37.2ms inference, 3.0ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss751_png.rf.dad3bdfd78335be99b02ca0f7f0a6679.jpg: 640x640 4 with_masks, 1 without_mask, 37.2ms\n",
+            "Speed: 1.8ms preprocess, 37.2ms inference, 3.0ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss748_png.rf.75b65aa87d1ab4b31a47b7e3f80a43c3.jpg: 640x640 1 mask_weared_incorrect, 1 without_mask, 37.2ms\n",
+            "Speed: 1.9ms preprocess, 37.2ms inference, 2.9ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss658_png.rf.18a299a86c94f8a6784af81f2f6b6c89.jpg: 640x640 1 mask_weared_incorrect, 1 with_mask, 38.3ms\n",
+            "Speed: 2.1ms preprocess, 38.3ms inference, 2.9ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss65_png.rf.f3dacea8ddea2ac8019c39c83bcec5c4.jpg: 640x640 1 mask_weared_incorrect, 2 with_masks, 1 without_mask, 37.2ms\n",
+            "Speed: 1.9ms preprocess, 37.2ms inference, 2.9ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss662_png.rf.0dec50b3c2f682da13df8167851159b8.jpg: 640x640 4 with_masks, 37.2ms\n",
+            "Speed: 1.7ms preprocess, 37.2ms inference, 3.1ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n",
+            "      33/80      8.85G      1.046     0.5498      1.083         93        640: 100%|██████████| 106/106 [01:00<00:00,  1.75it/s]\n",
+            "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100%|██████████| 6/6 [00:02<00:00,  2.02it/s]\n",
+            "                   all        161        861       0.87       0.79      0.824      0.519\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss664_png.rf.d7257f69f379e30582c9d5854e4bb093.jpg: 640x640 2 with_masks, 44.8ms\n",
+            "Speed: 1.7ms preprocess, 44.8ms inference, 2.6ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss674_png.rf.7848cd9439fa5dc0f5b03471912cdd27.jpg: 640x640 21 with_masks, 1 without_mask, 37.2ms\n",
+            "Speed: 2.0ms preprocess, 37.2ms inference, 2.7ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss680_png.rf.6430e43e329f2bd17482dab5d188875a.jpg: 640x640 3 mask_weared_incorrects, 10 with_masks, 3 without_masks, 37.2ms\n",
+            "Speed: 1.7ms preprocess, 37.2ms inference, 2.2ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss691_png.rf.68076bbedb2a9c8ce1c37ba0bc259d8c.jpg: 640x640 1 mask_weared_incorrect, 14 with_masks, 37.1ms\n",
+            "Speed: 1.6ms preprocess, 37.1ms inference, 2.1ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss694_png.rf.92b3468ed6b2d74d6e8e47c151e871a0.jpg: 640x640 9 with_masks, 37.1ms\n",
+            "Speed: 2.0ms preprocess, 37.1ms inference, 2.2ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss708_png.rf.0b01c6531d4980ea30cfde314a37ac52.jpg: 640x640 7 with_masks, 1 without_mask, 37.1ms\n",
+            "Speed: 1.9ms preprocess, 37.1ms inference, 2.9ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss714_png.rf.c59ce90ae182b29cc037c99b47028dd2.jpg: 640x640 4 with_masks, 37.1ms\n",
+            "Speed: 2.0ms preprocess, 37.1ms inference, 2.1ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss723_png.rf.4f8f04c5a74149652aaa8862ac9acb2a.jpg: 640x640 8 with_masks, 6 without_masks, 37.1ms\n",
+            "Speed: 2.5ms preprocess, 37.1ms inference, 2.2ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss725_png.rf.24ef1eeec5e346d219ce1633e649949c.jpg: 640x640 1 with_mask, 37.2ms\n",
+            "Speed: 1.9ms preprocess, 37.2ms inference, 2.2ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss72_png.rf.b94af68c76d704d083fc9720d480ef93.jpg: 640x640 1 without_mask, 37.2ms\n",
+            "Speed: 2.1ms preprocess, 37.2ms inference, 2.3ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss733_png.rf.bde25a6afb7d3fef880a5c9723c5c30d.jpg: 640x640 1 with_mask, 37.1ms\n",
+            "Speed: 1.6ms preprocess, 37.1ms inference, 2.8ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss73_png.rf.4f856521249c200a0dac653cddd51e50.jpg: 640x640 1 mask_weared_incorrect, 4 with_masks, 37.1ms\n",
+            "Speed: 1.7ms preprocess, 37.1ms inference, 2.1ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss744_png.rf.a8b60de6dbbfeb80df902a739b90f925.jpg: 640x640 2 with_masks, 2 without_masks, 37.1ms\n",
+            "Speed: 1.9ms preprocess, 37.1ms inference, 2.1ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss747_png.rf.09f39fbe610327e3092119f0e0a091ff.jpg: 640x640 1 with_mask, 37.2ms\n",
+            "Speed: 1.7ms preprocess, 37.2ms inference, 2.3ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss471_png.rf.c52f488eaed280f80c7d3e439c0c4e2a.jpg: 640x640 5 with_masks, 3 without_masks, 37.2ms\n",
+            "Speed: 1.9ms preprocess, 37.2ms inference, 2.2ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss89_png.rf.0459d0e0116e154559a89c1975734728.jpg: 640x640 1 mask_weared_incorrect, 43 with_masks, 6 without_masks, 37.2ms\n",
+            "Speed: 1.7ms preprocess, 37.2ms inference, 2.1ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss470_png.rf.3fca085941c9a6dbd4e79ea151f97079.jpg: 640x640 5 with_masks, 37.2ms\n",
+            "Speed: 2.4ms preprocess, 37.2ms inference, 2.3ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss461_png.rf.6316f0f312cd4c8c93c77f83f5484af9.jpg: 640x640 8 with_masks, 37.1ms\n",
+            "Speed: 1.8ms preprocess, 37.1ms inference, 2.5ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss230_png.rf.1fe3136ab2b6bffc7cd0b6e65101870c.jpg: 640x640 5 with_masks, 37.4ms\n",
+            "Speed: 2.2ms preprocess, 37.4ms inference, 2.4ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss236_png.rf.ea526bb945fec0e07973f2cd052ef688.jpg: 640x640 1 without_mask, 37.1ms\n",
+            "Speed: 1.7ms preprocess, 37.1ms inference, 2.1ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss241_png.rf.01c103b7f1b42f6eaaa3f4c67d5e063a.jpg: 640x640 1 with_mask, 37.2ms\n",
+            "Speed: 2.2ms preprocess, 37.2ms inference, 2.1ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss242_png.rf.048ddfefd131055beb8263c92bbb62a8.jpg: 640x640 1 with_mask, 37.2ms\n",
+            "Speed: 2.2ms preprocess, 37.2ms inference, 2.1ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss244_png.rf.f9240dd571e5670cad3b769290bbd680.jpg: 640x640 1 with_mask, 3 without_masks, 37.1ms\n",
+            "Speed: 2.6ms preprocess, 37.1ms inference, 2.1ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss247_png.rf.f67e30adf66e59df979a1db74326bd5b.jpg: 640x640 13 with_masks, 1 without_mask, 37.2ms\n",
+            "Speed: 2.0ms preprocess, 37.2ms inference, 2.2ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss248_png.rf.c19d9460b893693e4b637a1f7df7008a.jpg: 640x640 1 without_mask, 37.2ms\n",
+            "Speed: 1.9ms preprocess, 37.2ms inference, 2.0ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss229_png.rf.45ba617a90c78bc0e8e547bffedbe3c3.jpg: 640x640 15 with_masks, 37.2ms\n",
+            "Speed: 2.2ms preprocess, 37.2ms inference, 2.1ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss253_png.rf.93b13ca348adf361296ed659d6acfe75.jpg: 640x640 1 mask_weared_incorrect, 9 with_masks, 5 without_masks, 37.2ms\n",
+            "Speed: 1.6ms preprocess, 37.2ms inference, 2.5ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss264_png.rf.7018fdf357ffc35189a710fdfc752b52.jpg: 640x640 7 with_masks, 37.1ms\n",
+            "Speed: 1.9ms preprocess, 37.1ms inference, 2.1ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss271_png.rf.cc2239f13f1ebcc7519a1b37fc36376a.jpg: 640x640 1 with_mask, 37.2ms\n",
+            "Speed: 1.9ms preprocess, 37.2ms inference, 2.2ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss277_png.rf.12d1ae22a19b53135a7172821eaf2559.jpg: 640x640 9 with_masks, 37.2ms\n",
+            "Speed: 1.8ms preprocess, 37.2ms inference, 2.2ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss282_png.rf.32d06bf0012896891f681325fa56166d.jpg: 640x640 11 with_masks, 2 without_masks, 37.1ms\n",
+            "Speed: 1.6ms preprocess, 37.1ms inference, 2.2ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss289_png.rf.fee0ba4040ee03de9c67793e8127c627.jpg: 640x640 2 without_masks, 37.1ms\n",
+            "Speed: 1.8ms preprocess, 37.1ms inference, 2.1ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n",
+            "      34/80      8.86G      1.049     0.5441      1.084        131        640: 100%|██████████| 106/106 [01:00<00:00,  1.75it/s]\n",
+            "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100%|██████████| 6/6 [00:02<00:00,  2.17it/s]\n",
+            "                   all        161        861      0.821      0.718      0.785      0.507\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss301_png.rf.79b160619414ca6a470bd5ea8b30ef4a.jpg: 640x640 20 with_masks, 2 without_masks, 51.5ms\n",
+            "Speed: 1.9ms preprocess, 51.5ms inference, 2.8ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss303_png.rf.f00ae35b4058b933e066d1d2a4d88c17.jpg: 640x640 2 with_masks, 40.8ms\n",
+            "Speed: 3.9ms preprocess, 40.8ms inference, 3.2ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss258_png.rf.fc7b4f2f14e1d199dce55985695d1120.jpg: 640x640 1 mask_weared_incorrect, 2 with_masks, 37.7ms\n",
+            "Speed: 1.9ms preprocess, 37.7ms inference, 3.1ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss304_png.rf.9df48cf93de57fa41d0a2b59de78a62c.jpg: 640x640 2 with_masks, 37.2ms\n",
+            "Speed: 1.9ms preprocess, 37.2ms inference, 3.0ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss224_png.rf.4539ed1dc0a709e4e01077ecf7bc2b22.jpg: 640x640 2 with_masks, 37.2ms\n",
+            "Speed: 1.9ms preprocess, 37.2ms inference, 3.0ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss20_png.rf.ca394d629ffaba1fdb13e432a79a5eb9.jpg: 640x640 3 with_masks, 37.2ms\n",
+            "Speed: 1.9ms preprocess, 37.2ms inference, 2.9ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss109_png.rf.3c26f7537566830dffb39c47f71e574e.jpg: 640x640 1 with_mask, 37.2ms\n",
+            "Speed: 1.8ms preprocess, 37.2ms inference, 2.9ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss114_png.rf.c087c8382ac2542ac89314fa0bbeb4f6.jpg: 640x640 2 with_masks, 1 without_mask, 37.2ms\n",
+            "Speed: 1.9ms preprocess, 37.2ms inference, 3.0ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss127_png.rf.1baab62c26cbf4478f2a8d99e1cf68de.jpg: 640x640 1 with_mask, 37.3ms\n",
+            "Speed: 2.1ms preprocess, 37.3ms inference, 2.7ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss146_png.rf.ec0da30308aa466d39bae79b0cc0e2bf.jpg: 640x640 3 with_masks, 38.1ms\n",
+            "Speed: 1.9ms preprocess, 38.1ms inference, 3.6ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss152_png.rf.c66bb39b29efc7503239890f834100dc.jpg: 640x640 7 with_masks, 37.2ms\n",
+            "Speed: 2.2ms preprocess, 37.2ms inference, 3.1ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss154_png.rf.7512e06f4e0bd3a2185ec1867603cc8a.jpg: 640x640 1 without_mask, 37.2ms\n",
+            "Speed: 2.0ms preprocess, 37.2ms inference, 2.8ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss168_png.rf.3b19cb741e672eef23c3f091fd204d52.jpg: 640x640 4 with_masks, 2 without_masks, 38.9ms\n",
+            "Speed: 2.0ms preprocess, 38.9ms inference, 2.9ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss217_png.rf.c4e305ead91154374bba4fc48e0e3b99.jpg: 640x640 1 without_mask, 37.1ms\n",
+            "Speed: 1.8ms preprocess, 37.1ms inference, 3.0ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss169_png.rf.49a3d702f1cd1ce83aa6cd01599e3644.jpg: 640x640 1 with_mask, 37.2ms\n",
+            "Speed: 1.9ms preprocess, 37.2ms inference, 2.8ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss174_png.rf.ba1760e663e246482b26e587332650b0.jpg: 640x640 4 with_masks, 37.2ms\n",
+            "Speed: 2.7ms preprocess, 37.2ms inference, 3.4ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss178_png.rf.2fd8857c96b9bed1982f78b55798a334.jpg: 640x640 2 with_masks, 1 without_mask, 40.9ms\n",
+            "Speed: 1.8ms preprocess, 40.9ms inference, 3.4ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss194_png.rf.77ed2eca9fe5235cf2496449dd156996.jpg: 640x640 2 with_masks, 37.1ms\n",
+            "Speed: 2.0ms preprocess, 37.1ms inference, 2.3ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss197_png.rf.cd0c6b120a0fae906bb417f825daf6a1.jpg: 640x640 1 with_mask, 37.2ms\n",
+            "Speed: 2.2ms preprocess, 37.2ms inference, 2.1ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss1_png.rf.e41f0052ad0e49cab0887d6e50e5a7eb.jpg: 640x640 6 with_masks, 1 without_mask, 38.0ms\n",
+            "Speed: 3.5ms preprocess, 38.0ms inference, 2.3ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss203_png.rf.eba7307a461c6b2098593e82d2cccecc.jpg: 640x640 4 with_masks, 1 without_mask, 37.1ms\n",
+            "Speed: 2.6ms preprocess, 37.1ms inference, 2.3ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss206_png.rf.68794173883f5ae26e2382a3087aac0b.jpg: 640x640 7 with_masks, 1 without_mask, 37.1ms\n",
+            "Speed: 2.1ms preprocess, 37.1ms inference, 2.2ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss172_png.rf.13bb93a8bf5266e0d73bab43f62e0376.jpg: 640x640 1 without_mask, 37.2ms\n",
+            "Speed: 1.9ms preprocess, 37.2ms inference, 2.0ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss306_png.rf.52a38aff8eebcfb7d90d0c7cac38fdec.jpg: 640x640 1 with_mask, 37.2ms\n",
+            "Speed: 2.0ms preprocess, 37.2ms inference, 2.4ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss307_png.rf.93b21e5a88a625f2a9284ff6253bd417.jpg: 640x640 1 mask_weared_incorrect, 1 with_mask, 3 without_masks, 37.2ms\n",
+            "Speed: 2.0ms preprocess, 37.2ms inference, 2.2ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss308_png.rf.61a249cc68e67a9cf66c2393f61080f2.jpg: 640x640 3 with_masks, 37.1ms\n",
+            "Speed: 2.4ms preprocess, 37.1ms inference, 2.2ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss402_png.rf.adb70e16aac43aa519466a4364f99311.jpg: 640x640 1 without_mask, 37.2ms\n",
+            "Speed: 1.8ms preprocess, 37.2ms inference, 2.2ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss408_png.rf.bb077fd8dd6090c8f22b2dfe4fb0b2dc.jpg: 640x640 8 with_masks, 2 without_masks, 37.1ms\n",
+            "Speed: 3.0ms preprocess, 37.1ms inference, 2.3ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss409_png.rf.a1da634820d49e7be38ce59f5f5887bb.jpg: 640x640 1 with_mask, 37.2ms\n",
+            "Speed: 1.8ms preprocess, 37.2ms inference, 2.1ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss410_png.rf.eaad04d3f7e7468f6a0a3d017306d6da.jpg: 640x640 19 with_masks, 37.2ms\n",
+            "Speed: 1.9ms preprocess, 37.2ms inference, 2.6ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss418_png.rf.432d10d262677cb69e95be55ca0c9125.jpg: 640x640 2 with_masks, 37.1ms\n",
+            "Speed: 1.8ms preprocess, 37.1ms inference, 2.1ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss421_png.rf.7ecb66f6ba285fd631717a3635a7dd71.jpg: 640x640 5 with_masks, 37.2ms\n",
+            "Speed: 1.8ms preprocess, 37.2ms inference, 2.3ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n",
+            "      35/80       8.9G       1.02     0.5384      1.081         56        640: 100%|██████████| 106/106 [00:59<00:00,  1.78it/s]\n",
+            "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100%|██████████| 6/6 [00:03<00:00,  1.87it/s]\n",
+            "                   all        161        861       0.84      0.787      0.827      0.518\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss425_png.rf.b69c6da9a6c99fd8edfdad09f10582d2.jpg: 640x640 2 with_masks, 38.6ms\n",
+            "Speed: 1.7ms preprocess, 38.6ms inference, 2.9ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss400_png.rf.63c84ce5e3e0391c9509f77d2244755c.jpg: 640x640 3 with_masks, 37.2ms\n",
+            "Speed: 2.0ms preprocess, 37.2ms inference, 3.8ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss429_png.rf.0f9bc0b4f072650f40e985eefdce87df.jpg: 640x640 4 with_masks, 37.2ms\n",
+            "Speed: 1.9ms preprocess, 37.2ms inference, 2.2ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss438_png.rf.85978160d8cedb7d56a26e0d06e41f87.jpg: 640x640 4 with_masks, 37.2ms\n",
+            "Speed: 2.1ms preprocess, 37.2ms inference, 12.1ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss440_png.rf.641564d43589f6344bacc5d05d51da53.jpg: 640x640 1 mask_weared_incorrect, 9 with_masks, 1 without_mask, 37.4ms\n",
+            "Speed: 2.2ms preprocess, 37.4ms inference, 2.2ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss44_png.rf.b6697a646548922305672e657697750b.jpg: 640x640 3 with_masks, 1 without_mask, 37.2ms\n",
+            "Speed: 1.8ms preprocess, 37.2ms inference, 2.2ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss450_png.rf.8f5e0ff6c7228f1180f985685beb20d5.jpg: 640x640 4 with_masks, 37.1ms\n",
+            "Speed: 2.1ms preprocess, 37.1ms inference, 2.1ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss457_png.rf.60b3bf773c197a83826aae38a0cf2387.jpg: 640x640 4 with_masks, 1 without_mask, 37.2ms\n",
+            "Speed: 4.0ms preprocess, 37.2ms inference, 2.3ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss459_png.rf.73bd4ff56e948804a4c7d5cc9e2f98ef.jpg: 640x640 1 mask_weared_incorrect, 1 with_mask, 1 without_mask, 37.1ms\n",
+            "Speed: 2.1ms preprocess, 37.1ms inference, 2.2ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss45_png.rf.3b160c8afb75253926e1abf7b4972504.jpg: 640x640 2 with_masks, 1 without_mask, 37.4ms\n",
+            "Speed: 1.9ms preprocess, 37.4ms inference, 2.3ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss431_png.rf.c5e66fbd5f544edca4f20973ce5ecf08.jpg: 640x640 1 mask_weared_incorrect, 17 with_masks, 37.2ms\n",
+            "Speed: 2.1ms preprocess, 37.2ms inference, 3.4ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss395_png.rf.d0fd9e7ac741d7df48a86b7f291e9b49.jpg: 640x640 1 with_mask, 37.2ms\n",
+            "Speed: 3.2ms preprocess, 37.2ms inference, 4.5ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss389_png.rf.11956fb49c814dab304f0006b9075f71.jpg: 640x640 1 mask_weared_incorrect, 11 with_masks, 2 without_masks, 37.2ms\n",
+            "Speed: 2.2ms preprocess, 37.2ms inference, 2.9ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss388_png.rf.4847bd339895b2496b21a16876aca440.jpg: 640x640 11 with_masks, 10 without_masks, 37.1ms\n",
+            "Speed: 2.2ms preprocess, 37.1ms inference, 2.8ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss311_png.rf.8d4e3cc30ab76d6699d7f220a26286dd.jpg: 640x640 5 with_masks, 37.2ms\n",
+            "Speed: 1.8ms preprocess, 37.2ms inference, 2.6ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss313_png.rf.0d2ede745cca1bbc73883747763be4cb.jpg: 640x640 1 with_mask, 37.2ms\n",
+            "Speed: 1.8ms preprocess, 37.2ms inference, 3.1ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss315_png.rf.bdcb0e2cde8b888d72849bbf232bc644.jpg: 640x640 2 with_masks, 37.2ms\n",
+            "Speed: 2.0ms preprocess, 37.2ms inference, 2.9ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss31_png.rf.f71dabc8b32a5181ae4a7ec0724d169e.jpg: 640x640 2 with_masks, 37.2ms\n",
+            "Speed: 2.0ms preprocess, 37.2ms inference, 3.3ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss321_png.rf.d5ca9ccecbb235c5551003b177cd1d46.jpg: 640x640 1 mask_weared_incorrect, 1 with_mask, 1 without_mask, 37.2ms\n",
+            "Speed: 2.1ms preprocess, 37.2ms inference, 2.8ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss330_png.rf.ca2fe4eca45ae4b2bc6bb9fde6d39dff.jpg: 640x640 4 with_masks, 37.2ms\n",
+            "Speed: 1.7ms preprocess, 37.2ms inference, 4.6ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss338_png.rf.669c284dd81181d71654743a3ca9aeb3.jpg: 640x640 9 with_masks, 37.2ms\n",
+            "Speed: 1.9ms preprocess, 37.2ms inference, 3.0ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss339_png.rf.d26efdd756cada62599cd227994bbf56.jpg: 640x640 1 with_mask, 37.2ms\n",
+            "Speed: 1.9ms preprocess, 37.2ms inference, 2.8ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss343_png.rf.1c5c7bbcb828a1cf9d4d2584972083cb.jpg: 640x640 1 without_mask, 37.1ms\n",
+            "Speed: 1.8ms preprocess, 37.1ms inference, 2.7ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss351_png.rf.15436d1eb7080d7bae2e79d554a4d3cb.jpg: 640x640 1 with_mask, 39.2ms\n",
+            "Speed: 1.7ms preprocess, 39.2ms inference, 2.8ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss364_png.rf.74e470c60f166ba4ec1a268b153fa240.jpg: 640x640 3 with_masks, 37.2ms\n",
+            "Speed: 1.9ms preprocess, 37.2ms inference, 2.9ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss366_png.rf.433ea8f6b4fcab0d951b52116611c1be.jpg: 640x640 3 with_masks, 37.2ms\n",
+            "Speed: 4.8ms preprocess, 37.2ms inference, 2.9ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss368_png.rf.1d14fe4224d1b152c5e272d889fe3d45.jpg: 640x640 10 with_masks, 39.0ms\n",
+            "Speed: 1.9ms preprocess, 39.0ms inference, 2.9ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss374_png.rf.b51c420d86fc3a474ed557b5a230b51e.jpg: 640x640 4 with_masks, 1 without_mask, 37.2ms\n",
+            "Speed: 1.8ms preprocess, 37.2ms inference, 3.0ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss376_png.rf.ca418b2ffccc242892a1ab14657e8349.jpg: 640x640 7 with_masks, 37.1ms\n",
+            "Speed: 4.9ms preprocess, 37.1ms inference, 3.2ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss37_png.rf.60ce2ff44ae089a01d8f07ff2e0f00ad.jpg: 640x640 1 with_mask, 37.2ms\n",
+            "Speed: 2.1ms preprocess, 37.2ms inference, 2.7ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss387_png.rf.6d027b3075e33a4414cc245ec7435fcc.jpg: 640x640 1 mask_weared_incorrect, 4 with_masks, 1 without_mask, 37.1ms\n",
+            "Speed: 1.8ms preprocess, 37.1ms inference, 2.7ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss464_png.rf.b7d07a0f6aabc271e6bfbe039246786b.jpg: 640x640 7 with_masks, 37.2ms\n",
+            "Speed: 2.0ms preprocess, 37.2ms inference, 3.2ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n",
+            "      36/80      9.03G      1.026     0.5305      1.074        122        640: 100%|██████████| 106/106 [01:00<00:00,  1.76it/s]\n",
+            "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100%|██████████| 6/6 [00:02<00:00,  2.19it/s]\n",
+            "                   all        161        861      0.785      0.767      0.797      0.497\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss90_png.rf.bb3401c96e9aba7db607a9a5ac8d8f51.jpg: 640x640 14 with_masks, 49.0ms\n",
+            "Speed: 2.9ms preprocess, 49.0ms inference, 2.8ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n",
+            "      37/80      9.07G      1.014     0.5258      1.072         91        640: 100%|██████████| 106/106 [00:59<00:00,  1.77it/s]\n",
+            "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100%|██████████| 6/6 [00:02<00:00,  2.35it/s]\n",
+            "                   all        161        861      0.855      0.808      0.845      0.534\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss107_png.rf.285757ad3a789f0d69380282b3bdb846.jpg: 640x640 1 with_mask, 45.7ms\n",
+            "Speed: 2.0ms preprocess, 45.7ms inference, 2.8ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss569_png.rf.245d020288f15a704c2742a49eb1ca63.jpg: 640x640 1 with_mask, 37.2ms\n",
+            "Speed: 1.8ms preprocess, 37.2ms inference, 2.7ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss56_png.rf.ffec370c63bb3ee301d05f9ce072e3fa.jpg: 640x640 1 with_mask, 37.2ms\n",
+            "Speed: 1.9ms preprocess, 37.2ms inference, 2.2ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss577_png.rf.99d8deb18d344f24bb95f02394713470.jpg: 640x640 14 with_masks, 37.1ms\n",
+            "Speed: 2.3ms preprocess, 37.1ms inference, 2.2ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss585_png.rf.16b40d54481e86f0a1434d30bc6d9c64.jpg: 640x640 4 with_masks, 3 without_masks, 37.1ms\n",
+            "Speed: 2.3ms preprocess, 37.1ms inference, 2.1ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss595_png.rf.f3a260412881f24273c64d6bd6e1966b.jpg: 640x640 6 with_masks, 37.2ms\n",
+            "Speed: 2.1ms preprocess, 37.2ms inference, 2.1ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss596_png.rf.9bf29752ebe873bc099ff9b64ddef6d1.jpg: 640x640 1 with_mask, 37.2ms\n",
+            "Speed: 1.8ms preprocess, 37.2ms inference, 2.2ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss603_png.rf.0d06c5299fd1cf3136e68b97a2afa4fd.jpg: 640x640 102 with_masks, 16 without_masks, 37.2ms\n",
+            "Speed: 1.7ms preprocess, 37.2ms inference, 2.3ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss568_png.rf.a4d4a4e139954b5194617ef2e9ffc81c.jpg: 640x640 1 with_mask, 37.2ms\n",
+            "Speed: 1.9ms preprocess, 37.2ms inference, 2.0ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss608_png.rf.4806b67fedacda192a8448bcf3b53d64.jpg: 640x640 1 with_mask, 37.1ms\n",
+            "Speed: 1.9ms preprocess, 37.1ms inference, 2.0ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss623_png.rf.19a2c6b529d5478510934f467949c887.jpg: 640x640 1 mask_weared_incorrect, 20 with_masks, 3 without_masks, 37.1ms\n",
+            "Speed: 1.7ms preprocess, 37.1ms inference, 2.3ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss626_png.rf.4a2f1a57a893fdcef400930251142f52.jpg: 640x640 2 with_masks, 37.2ms\n",
+            "Speed: 3.1ms preprocess, 37.2ms inference, 2.8ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss627_png.rf.81b096f6b0f9e897cc64f59880e630e0.jpg: 640x640 3 mask_weared_incorrects, 7 with_masks, 7 without_masks, 37.2ms\n",
+            "Speed: 1.8ms preprocess, 37.2ms inference, 3.2ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss630_png.rf.d1ecd7de587fb5c2571563293babff62.jpg: 640x640 1 with_mask, 37.2ms\n",
+            "Speed: 1.8ms preprocess, 37.2ms inference, 2.5ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss631_png.rf.418be1a60a0224818dc54e0d2281c6f4.jpg: 640x640 11 with_masks, 37.2ms\n",
+            "Speed: 1.8ms preprocess, 37.2ms inference, 3.1ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss636_png.rf.e6889a20be3cb52fa81b195fdef01b58.jpg: 640x640 6 with_masks, 2 without_masks, 37.1ms\n",
+            "Speed: 1.9ms preprocess, 37.1ms inference, 2.7ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss645_png.rf.d577b2fbdae8c09e7cb396b9c14f18d7.jpg: 640x640 1 with_mask, 37.2ms\n",
+            "Speed: 2.3ms preprocess, 37.2ms inference, 3.1ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss619_png.rf.bc1dcbfae2f9104ce082afe801399f54.jpg: 640x640 2 with_masks, 37.2ms\n",
+            "Speed: 1.9ms preprocess, 37.2ms inference, 3.1ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss646_png.rf.a434ddc2569b34a89bbb07a259996497.jpg: 640x640 1 with_mask, 37.2ms\n",
+            "Speed: 1.9ms preprocess, 37.2ms inference, 2.8ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss563_png.rf.dc088c07f08e5fba01fd6bddeceb27e2.jpg: 640x640 3 with_masks, 37.2ms\n",
+            "Speed: 1.9ms preprocess, 37.2ms inference, 2.9ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss554_png.rf.ba664c8fdc34b11faff3a128d06dbe9a.jpg: 640x640 4 with_masks, 37.2ms\n",
+            "Speed: 4.0ms preprocess, 37.2ms inference, 3.0ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss473_png.rf.6de35811442245ad013a2676e2bcaa0a.jpg: 640x640 4 with_masks, 1 without_mask, 37.2ms\n",
+            "Speed: 1.7ms preprocess, 37.2ms inference, 2.9ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss477_png.rf.0e319d347398d08b8a52fb6a152de44e.jpg: 640x640 6 with_masks, 6 without_masks, 37.2ms\n",
+            "Speed: 1.8ms preprocess, 37.2ms inference, 2.9ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss481_png.rf.6682292ffe5179b26d46c8515797446e.jpg: 640x640 5 with_masks, 37.2ms\n",
+            "Speed: 1.8ms preprocess, 37.2ms inference, 3.0ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss483_png.rf.4c059c2770f996153e3487a7f52f771c.jpg: 640x640 3 with_masks, 1 without_mask, 37.1ms\n",
+            "Speed: 1.9ms preprocess, 37.1ms inference, 2.9ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss484_png.rf.a57bfdb112b858aa9ed93bf36306ac61.jpg: 640x640 1 mask_weared_incorrect, 1 with_mask, 37.1ms\n",
+            "Speed: 1.9ms preprocess, 37.1ms inference, 2.8ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss498_png.rf.095899d089070e7a5a7697113b108f8a.jpg: 640x640 11 with_masks, 2 without_masks, 37.2ms\n",
+            "Speed: 1.9ms preprocess, 37.2ms inference, 3.1ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss499_png.rf.611bdf8f03aea1d86028c7b5d7d494ec.jpg: 640x640 1 with_mask, 1 without_mask, 37.1ms\n",
+            "Speed: 1.9ms preprocess, 37.1ms inference, 2.9ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss560_png.rf.bc8e65e2733e0f7b723391d33c380fe0.jpg: 640x640 1 with_mask, 37.2ms\n",
+            "Speed: 1.9ms preprocess, 37.2ms inference, 2.7ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss49_png.rf.d4077078d124ff3d3d699fc94bd06150.jpg: 640x640 8 with_masks, 3 without_masks, 37.2ms\n",
+            "Speed: 1.7ms preprocess, 37.2ms inference, 2.9ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss509_png.rf.6470c0dd2a6a4b05117cca6aad267087.jpg: 640x640 1 with_mask, 37.2ms\n",
+            "Speed: 1.8ms preprocess, 37.2ms inference, 2.9ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss512_png.rf.8dbd72e69a164fdcdad2e220bcd0c467.jpg: 640x640 8 with_masks, 37.2ms\n",
+            "Speed: 2.7ms preprocess, 37.2ms inference, 2.8ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n",
+            "      38/80      9.11G      1.018     0.5264      1.065        132        640: 100%|██████████| 106/106 [00:59<00:00,  1.78it/s]\n",
+            "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100%|██████████| 6/6 [00:02<00:00,  2.27it/s]\n",
+            "                   all        161        861      0.875      0.756       0.82       0.51\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss515_png.rf.9b8d660e9368ee9ccfeb977e609167ed.jpg: 640x640 1 with_mask, 39.4ms\n",
+            "Speed: 4.1ms preprocess, 39.4ms inference, 3.0ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss529_png.rf.6ae323861cb838fc945c80ee31070c4c.jpg: 640x640 4 with_masks, 1 without_mask, 37.1ms\n",
+            "Speed: 2.2ms preprocess, 37.1ms inference, 3.3ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss532_png.rf.03aa559343f932efbfa3753190291fa7.jpg: 640x640 1 with_mask, 37.6ms\n",
+            "Speed: 2.7ms preprocess, 37.6ms inference, 2.2ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss537_png.rf.f22f4997ea93880ebfa2cb19a893caad.jpg: 640x640 1 without_mask, 37.1ms\n",
+            "Speed: 1.9ms preprocess, 37.1ms inference, 2.2ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss551_png.rf.010062fb38326dac49ecca8d9322953f.jpg: 640x640 5 with_masks, 37.1ms\n",
+            "Speed: 1.8ms preprocess, 37.1ms inference, 2.2ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss501_png.rf.125122fa5a318ec6d0e27d632764f840.jpg: 640x640 8 with_masks, 37.2ms\n",
+            "Speed: 1.7ms preprocess, 37.2ms inference, 2.2ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss649_png.rf.5540865cd8826940d55b3b48c045183c.jpg: 640x640 1 with_mask, 37.2ms\n",
+            "Speed: 1.8ms preprocess, 37.2ms inference, 2.1ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss64_png.rf.4b8ca34d17365fb62029fdbee94cb0aa.jpg: 640x640 3 with_masks, 37.2ms\n",
+            "Speed: 1.8ms preprocess, 37.2ms inference, 2.3ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss653_png.rf.22cf40d34bad20f7f9b542b6a0a89e2f.jpg: 640x640 2 with_masks, 37.1ms\n",
+            "Speed: 1.9ms preprocess, 37.1ms inference, 2.1ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss787_png.rf.a7e026e8082789734a57252cf6df81e5.jpg: 640x640 8 with_masks, 2 without_masks, 37.1ms\n",
+            "Speed: 1.8ms preprocess, 37.1ms inference, 2.2ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss793_png.rf.dd2be948b6231ceb68a6af8371f2329c.jpg: 640x640 2 with_masks, 37.2ms\n",
+            "Speed: 1.8ms preprocess, 37.2ms inference, 2.2ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss797_png.rf.5ead12df141e267f928b7b34c73dfb1a.jpg: 640x640 9 with_masks, 1 without_mask, 37.1ms\n",
+            "Speed: 1.8ms preprocess, 37.1ms inference, 2.2ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss79_png.rf.e12280d9bd602d3e52504b83921437d6.jpg: 640x640 5 with_masks, 39.4ms\n",
+            "Speed: 1.9ms preprocess, 39.4ms inference, 3.1ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss806_png.rf.504dc192775390a4b3f7d6b85bc58636.jpg: 640x640 6 with_masks, 37.3ms\n",
+            "Speed: 2.2ms preprocess, 37.3ms inference, 3.2ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss808_png.rf.b2e534caaaf701b8674add21e64fd528.jpg: 640x640 1 with_mask, 37.2ms\n",
+            "Speed: 5.0ms preprocess, 37.2ms inference, 2.8ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss822_png.rf.8601f2a416cbe3f239fde9934f5f66d2.jpg: 640x640 10 with_masks, 5 without_masks, 37.2ms\n",
+            "Speed: 5.8ms preprocess, 37.2ms inference, 3.4ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss784_png.rf.b95afb3096062e72503f25dfdaf53f52.jpg: 640x640 8 with_masks, 1 without_mask, 37.2ms\n",
+            "Speed: 2.0ms preprocess, 37.2ms inference, 2.7ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss828_png.rf.ef40e6fb83c895f7c4ca491dadbcecb1.jpg: 640x640 1 with_mask, 37.2ms\n",
+            "Speed: 2.0ms preprocess, 37.2ms inference, 3.0ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss832_png.rf.fd2d4b0fa4b62433e71f92aa8f1bc067.jpg: 640x640 1 mask_weared_incorrect, 1 with_mask, 37.2ms\n",
+            "Speed: 2.0ms preprocess, 37.2ms inference, 3.1ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss834_png.rf.c14acf559bb5531c92d3cf19a5193aa2.jpg: 640x640 6 with_masks, 1 without_mask, 37.2ms\n",
+            "Speed: 2.2ms preprocess, 37.2ms inference, 3.2ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss835_png.rf.b8a44eb8c868a51999b450873338a62a.jpg: 640x640 1 mask_weared_incorrect, 2 with_masks, 37.2ms\n",
+            "Speed: 1.9ms preprocess, 37.2ms inference, 3.1ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss840_png.rf.78c778f16a6a87f204473b70c7e735b1.jpg: 640x640 2 with_masks, 38.7ms\n",
+            "Speed: 2.0ms preprocess, 38.7ms inference, 3.0ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss844_png.rf.98f015b79733ae45cfff40da2c6eb85c.jpg: 640x640 2 with_masks, 37.2ms\n",
+            "Speed: 1.8ms preprocess, 37.2ms inference, 2.9ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss846_png.rf.f600f86418cd50b99d7116344abfe0df.jpg: 640x640 1 with_mask, 37.2ms\n",
+            "Speed: 1.8ms preprocess, 37.2ms inference, 2.8ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss848_png.rf.a1793122f2a5ab2b5a3d7be92157ea6b.jpg: 640x640 3 with_masks, 38.8ms\n",
+            "Speed: 2.0ms preprocess, 38.8ms inference, 3.2ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss830_png.rf.c8684a6a7e69bd43d4d35d54f2004fd7.jpg: 640x640 1 with_mask, 37.2ms\n",
+            "Speed: 1.9ms preprocess, 37.2ms inference, 2.8ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss761_png.rf.666e2aaecaf296dc7fe39031d857300a.jpg: 640x640 1 mask_weared_incorrect, 1 with_mask, 37.2ms\n",
+            "Speed: 2.1ms preprocess, 37.2ms inference, 3.0ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss751_png.rf.dad3bdfd78335be99b02ca0f7f0a6679.jpg: 640x640 3 with_masks, 37.2ms\n",
+            "Speed: 1.9ms preprocess, 37.2ms inference, 2.9ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss748_png.rf.75b65aa87d1ab4b31a47b7e3f80a43c3.jpg: 640x640 1 mask_weared_incorrect, 37.2ms\n",
+            "Speed: 1.8ms preprocess, 37.2ms inference, 2.7ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss658_png.rf.18a299a86c94f8a6784af81f2f6b6c89.jpg: 640x640 1 mask_weared_incorrect, 37.2ms\n",
+            "Speed: 1.8ms preprocess, 37.2ms inference, 2.9ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss65_png.rf.f3dacea8ddea2ac8019c39c83bcec5c4.jpg: 640x640 2 with_masks, 1 without_mask, 37.2ms\n",
+            "Speed: 1.9ms preprocess, 37.2ms inference, 2.9ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss662_png.rf.0dec50b3c2f682da13df8167851159b8.jpg: 640x640 4 with_masks, 37.2ms\n",
+            "Speed: 1.7ms preprocess, 37.2ms inference, 2.7ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n",
+            "      39/80      9.19G      1.001     0.5244      1.059         87        640: 100%|██████████| 106/106 [00:59<00:00,  1.78it/s]\n",
+            "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100%|██████████| 6/6 [00:02<00:00,  2.21it/s]\n",
+            "                   all        161        861      0.886      0.748      0.812      0.516\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss664_png.rf.d7257f69f379e30582c9d5854e4bb093.jpg: 640x640 1 with_mask, 43.6ms\n",
+            "Speed: 1.7ms preprocess, 43.6ms inference, 6.9ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss674_png.rf.7848cd9439fa5dc0f5b03471912cdd27.jpg: 640x640 19 with_masks, 1 without_mask, 44.9ms\n",
+            "Speed: 1.8ms preprocess, 44.9ms inference, 10.1ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss680_png.rf.6430e43e329f2bd17482dab5d188875a.jpg: 640x640 1 mask_weared_incorrect, 9 with_masks, 2 without_masks, 37.2ms\n",
+            "Speed: 1.8ms preprocess, 37.2ms inference, 3.5ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss691_png.rf.68076bbedb2a9c8ce1c37ba0bc259d8c.jpg: 640x640 11 with_masks, 37.1ms\n",
+            "Speed: 1.8ms preprocess, 37.1ms inference, 2.8ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss694_png.rf.92b3468ed6b2d74d6e8e47c151e871a0.jpg: 640x640 6 with_masks, 37.2ms\n",
+            "Speed: 1.8ms preprocess, 37.2ms inference, 2.8ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss708_png.rf.0b01c6531d4980ea30cfde314a37ac52.jpg: 640x640 3 with_masks, 1 without_mask, 37.1ms\n",
+            "Speed: 1.8ms preprocess, 37.1ms inference, 2.7ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss714_png.rf.c59ce90ae182b29cc037c99b47028dd2.jpg: 640x640 5 with_masks, 37.2ms\n",
+            "Speed: 1.9ms preprocess, 37.2ms inference, 2.9ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss723_png.rf.4f8f04c5a74149652aaa8862ac9acb2a.jpg: 640x640 8 with_masks, 7 without_masks, 37.1ms\n",
+            "Speed: 1.8ms preprocess, 37.1ms inference, 2.9ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss725_png.rf.24ef1eeec5e346d219ce1633e649949c.jpg: 640x640 1 with_mask, 37.1ms\n",
+            "Speed: 1.9ms preprocess, 37.1ms inference, 2.7ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss72_png.rf.b94af68c76d704d083fc9720d480ef93.jpg: 640x640 1 without_mask, 37.1ms\n",
+            "Speed: 2.0ms preprocess, 37.1ms inference, 2.8ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss733_png.rf.bde25a6afb7d3fef880a5c9723c5c30d.jpg: 640x640 1 with_mask, 37.2ms\n",
+            "Speed: 1.9ms preprocess, 37.2ms inference, 3.2ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss73_png.rf.4f856521249c200a0dac653cddd51e50.jpg: 640x640 2 mask_weared_incorrects, 2 with_masks, 37.2ms\n",
+            "Speed: 1.8ms preprocess, 37.2ms inference, 3.0ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss744_png.rf.a8b60de6dbbfeb80df902a739b90f925.jpg: 640x640 2 with_masks, 1 without_mask, 37.2ms\n",
+            "Speed: 1.8ms preprocess, 37.2ms inference, 3.0ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss747_png.rf.09f39fbe610327e3092119f0e0a091ff.jpg: 640x640 1 with_mask, 37.4ms\n",
+            "Speed: 2.0ms preprocess, 37.4ms inference, 3.2ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss471_png.rf.c52f488eaed280f80c7d3e439c0c4e2a.jpg: 640x640 5 with_masks, 4 without_masks, 37.2ms\n",
+            "Speed: 2.3ms preprocess, 37.2ms inference, 3.5ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss89_png.rf.0459d0e0116e154559a89c1975734728.jpg: 640x640 51 with_masks, 2 without_masks, 37.5ms\n",
+            "Speed: 2.1ms preprocess, 37.5ms inference, 2.2ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss470_png.rf.3fca085941c9a6dbd4e79ea151f97079.jpg: 640x640 5 with_masks, 37.1ms\n",
+            "Speed: 1.9ms preprocess, 37.1ms inference, 2.1ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss461_png.rf.6316f0f312cd4c8c93c77f83f5484af9.jpg: 640x640 8 with_masks, 39.7ms\n",
+            "Speed: 2.0ms preprocess, 39.7ms inference, 2.3ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss230_png.rf.1fe3136ab2b6bffc7cd0b6e65101870c.jpg: 640x640 5 with_masks, 37.1ms\n",
+            "Speed: 2.1ms preprocess, 37.1ms inference, 2.2ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss236_png.rf.ea526bb945fec0e07973f2cd052ef688.jpg: 640x640 1 without_mask, 37.1ms\n",
+            "Speed: 2.0ms preprocess, 37.1ms inference, 2.3ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss241_png.rf.01c103b7f1b42f6eaaa3f4c67d5e063a.jpg: 640x640 1 with_mask, 37.2ms\n",
+            "Speed: 2.0ms preprocess, 37.2ms inference, 2.0ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss242_png.rf.048ddfefd131055beb8263c92bbb62a8.jpg: 640x640 1 with_mask, 37.1ms\n",
+            "Speed: 1.7ms preprocess, 37.1ms inference, 2.0ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss244_png.rf.f9240dd571e5670cad3b769290bbd680.jpg: 640x640 1 with_mask, 3 without_masks, 37.1ms\n",
+            "Speed: 1.8ms preprocess, 37.1ms inference, 2.3ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss247_png.rf.f67e30adf66e59df979a1db74326bd5b.jpg: 640x640 13 with_masks, 37.2ms\n",
+            "Speed: 1.9ms preprocess, 37.2ms inference, 2.1ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss248_png.rf.c19d9460b893693e4b637a1f7df7008a.jpg: 640x640 1 with_mask, 1 without_mask, 37.2ms\n",
+            "Speed: 1.8ms preprocess, 37.2ms inference, 2.1ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss229_png.rf.45ba617a90c78bc0e8e547bffedbe3c3.jpg: 640x640 15 with_masks, 37.2ms\n",
+            "Speed: 1.7ms preprocess, 37.2ms inference, 2.1ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss253_png.rf.93b13ca348adf361296ed659d6acfe75.jpg: 640x640 7 with_masks, 4 without_masks, 37.2ms\n",
+            "Speed: 2.2ms preprocess, 37.2ms inference, 2.1ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss264_png.rf.7018fdf357ffc35189a710fdfc752b52.jpg: 640x640 7 with_masks, 37.2ms\n",
+            "Speed: 1.8ms preprocess, 37.2ms inference, 2.2ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss271_png.rf.cc2239f13f1ebcc7519a1b37fc36376a.jpg: 640x640 1 with_mask, 37.1ms\n",
+            "Speed: 1.7ms preprocess, 37.1ms inference, 2.0ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss277_png.rf.12d1ae22a19b53135a7172821eaf2559.jpg: 640x640 10 with_masks, 37.1ms\n",
+            "Speed: 1.8ms preprocess, 37.1ms inference, 2.0ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss282_png.rf.32d06bf0012896891f681325fa56166d.jpg: 640x640 1 mask_weared_incorrect, 10 with_masks, 1 without_mask, 37.1ms\n",
+            "Speed: 1.8ms preprocess, 37.1ms inference, 2.1ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss289_png.rf.fee0ba4040ee03de9c67793e8127c627.jpg: 640x640 2 without_masks, 37.1ms\n",
+            "Speed: 1.7ms preprocess, 37.1ms inference, 2.1ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n",
+            "      40/80      9.34G     0.9872     0.5144      1.056        121        640: 100%|██████████| 106/106 [00:59<00:00,  1.77it/s]\n",
+            "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100%|██████████| 6/6 [00:02<00:00,  2.23it/s]\n",
+            "                   all        161        861      0.836      0.754      0.819      0.532\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss301_png.rf.79b160619414ca6a470bd5ea8b30ef4a.jpg: 640x640 16 with_masks, 1 without_mask, 38.6ms\n",
+            "Speed: 1.7ms preprocess, 38.6ms inference, 2.8ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss303_png.rf.f00ae35b4058b933e066d1d2a4d88c17.jpg: 640x640 2 with_masks, 42.6ms\n",
+            "Speed: 3.0ms preprocess, 42.6ms inference, 3.2ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss258_png.rf.fc7b4f2f14e1d199dce55985695d1120.jpg: 640x640 1 mask_weared_incorrect, 2 with_masks, 37.2ms\n",
+            "Speed: 1.8ms preprocess, 37.2ms inference, 3.4ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss304_png.rf.9df48cf93de57fa41d0a2b59de78a62c.jpg: 640x640 2 with_masks, 37.1ms\n",
+            "Speed: 1.6ms preprocess, 37.1ms inference, 2.3ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss224_png.rf.4539ed1dc0a709e4e01077ecf7bc2b22.jpg: 640x640 2 with_masks, 40.6ms\n",
+            "Speed: 1.8ms preprocess, 40.6ms inference, 2.2ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss20_png.rf.ca394d629ffaba1fdb13e432a79a5eb9.jpg: 640x640 3 with_masks, 37.1ms\n",
+            "Speed: 2.9ms preprocess, 37.1ms inference, 2.1ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss109_png.rf.3c26f7537566830dffb39c47f71e574e.jpg: 640x640 5 with_masks, 37.2ms\n",
+            "Speed: 2.8ms preprocess, 37.2ms inference, 2.1ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss114_png.rf.c087c8382ac2542ac89314fa0bbeb4f6.jpg: 640x640 1 mask_weared_incorrect, 1 with_mask, 1 without_mask, 37.4ms\n",
+            "Speed: 1.8ms preprocess, 37.4ms inference, 2.1ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss127_png.rf.1baab62c26cbf4478f2a8d99e1cf68de.jpg: 640x640 1 with_mask, 37.1ms\n",
+            "Speed: 2.2ms preprocess, 37.1ms inference, 2.2ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss146_png.rf.ec0da30308aa466d39bae79b0cc0e2bf.jpg: 640x640 3 with_masks, 37.2ms\n",
+            "Speed: 1.8ms preprocess, 37.2ms inference, 2.2ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss152_png.rf.c66bb39b29efc7503239890f834100dc.jpg: 640x640 7 with_masks, 37.1ms\n",
+            "Speed: 2.2ms preprocess, 37.1ms inference, 2.2ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss154_png.rf.7512e06f4e0bd3a2185ec1867603cc8a.jpg: 640x640 1 without_mask, 37.1ms\n",
+            "Speed: 2.7ms preprocess, 37.1ms inference, 2.0ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss168_png.rf.3b19cb741e672eef23c3f091fd204d52.jpg: 640x640 3 with_masks, 4 without_masks, 41.2ms\n",
+            "Speed: 1.8ms preprocess, 41.2ms inference, 2.2ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss217_png.rf.c4e305ead91154374bba4fc48e0e3b99.jpg: 640x640 1 without_mask, 37.2ms\n",
+            "Speed: 2.0ms preprocess, 37.2ms inference, 2.3ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss169_png.rf.49a3d702f1cd1ce83aa6cd01599e3644.jpg: 640x640 1 with_mask, 37.1ms\n",
+            "Speed: 1.8ms preprocess, 37.1ms inference, 2.1ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss174_png.rf.ba1760e663e246482b26e587332650b0.jpg: 640x640 4 with_masks, 37.1ms\n",
+            "Speed: 1.9ms preprocess, 37.1ms inference, 2.1ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss178_png.rf.2fd8857c96b9bed1982f78b55798a334.jpg: 640x640 2 with_masks, 1 without_mask, 37.2ms\n",
+            "Speed: 1.8ms preprocess, 37.2ms inference, 2.1ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss194_png.rf.77ed2eca9fe5235cf2496449dd156996.jpg: 640x640 2 with_masks, 37.3ms\n",
+            "Speed: 2.1ms preprocess, 37.3ms inference, 3.5ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss197_png.rf.cd0c6b120a0fae906bb417f825daf6a1.jpg: 640x640 1 with_mask, 37.1ms\n",
+            "Speed: 2.6ms preprocess, 37.1ms inference, 2.1ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss1_png.rf.e41f0052ad0e49cab0887d6e50e5a7eb.jpg: 640x640 7 with_masks, 1 without_mask, 37.1ms\n",
+            "Speed: 2.4ms preprocess, 37.1ms inference, 2.1ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss203_png.rf.eba7307a461c6b2098593e82d2cccecc.jpg: 640x640 4 with_masks, 37.2ms\n",
+            "Speed: 1.8ms preprocess, 37.2ms inference, 2.2ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss206_png.rf.68794173883f5ae26e2382a3087aac0b.jpg: 640x640 6 with_masks, 1 without_mask, 37.2ms\n",
+            "Speed: 1.8ms preprocess, 37.2ms inference, 2.3ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss172_png.rf.13bb93a8bf5266e0d73bab43f62e0376.jpg: 640x640 1 without_mask, 37.1ms\n",
+            "Speed: 4.6ms preprocess, 37.1ms inference, 2.1ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss306_png.rf.52a38aff8eebcfb7d90d0c7cac38fdec.jpg: 640x640 1 with_mask, 37.3ms\n",
+            "Speed: 2.3ms preprocess, 37.3ms inference, 2.5ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss307_png.rf.93b21e5a88a625f2a9284ff6253bd417.jpg: 640x640 1 mask_weared_incorrect, 1 with_mask, 1 without_mask, 37.3ms\n",
+            "Speed: 2.8ms preprocess, 37.3ms inference, 2.6ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss308_png.rf.61a249cc68e67a9cf66c2393f61080f2.jpg: 640x640 2 with_masks, 37.2ms\n",
+            "Speed: 2.0ms preprocess, 37.2ms inference, 2.7ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss402_png.rf.adb70e16aac43aa519466a4364f99311.jpg: 640x640 1 without_mask, 37.2ms\n",
+            "Speed: 2.4ms preprocess, 37.2ms inference, 2.6ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss408_png.rf.bb077fd8dd6090c8f22b2dfe4fb0b2dc.jpg: 640x640 8 with_masks, 3 without_masks, 37.1ms\n",
+            "Speed: 1.8ms preprocess, 37.1ms inference, 2.7ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss409_png.rf.a1da634820d49e7be38ce59f5f5887bb.jpg: 640x640 1 with_mask, 37.2ms\n",
+            "Speed: 6.9ms preprocess, 37.2ms inference, 3.0ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss410_png.rf.eaad04d3f7e7468f6a0a3d017306d6da.jpg: 640x640 1 mask_weared_incorrect, 19 with_masks, 37.4ms\n",
+            "Speed: 1.8ms preprocess, 37.4ms inference, 3.6ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss418_png.rf.432d10d262677cb69e95be55ca0c9125.jpg: 640x640 2 with_masks, 37.2ms\n",
+            "Speed: 1.8ms preprocess, 37.2ms inference, 3.1ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss421_png.rf.7ecb66f6ba285fd631717a3635a7dd71.jpg: 640x640 5 with_masks, 37.2ms\n",
+            "Speed: 1.9ms preprocess, 37.2ms inference, 3.1ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n",
+            "      41/80      9.29G     0.9788      0.513      1.053         77        640: 100%|██████████| 106/106 [00:59<00:00,  1.77it/s]\n",
+            "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100%|██████████| 6/6 [00:03<00:00,  1.89it/s]\n",
+            "                   all        161        861      0.877      0.731      0.824      0.537\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss425_png.rf.b69c6da9a6c99fd8edfdad09f10582d2.jpg: 640x640 3 with_masks, 44.6ms\n",
+            "Speed: 7.4ms preprocess, 44.6ms inference, 9.8ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss400_png.rf.63c84ce5e3e0391c9509f77d2244755c.jpg: 640x640 4 with_masks, 45.3ms\n",
+            "Speed: 3.0ms preprocess, 45.3ms inference, 2.9ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss429_png.rf.0f9bc0b4f072650f40e985eefdce87df.jpg: 640x640 5 with_masks, 37.2ms\n",
+            "Speed: 6.5ms preprocess, 37.2ms inference, 2.9ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss438_png.rf.85978160d8cedb7d56a26e0d06e41f87.jpg: 640x640 4 with_masks, 37.2ms\n",
+            "Speed: 2.0ms preprocess, 37.2ms inference, 2.8ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss440_png.rf.641564d43589f6344bacc5d05d51da53.jpg: 640x640 2 mask_weared_incorrects, 8 with_masks, 37.2ms\n",
+            "Speed: 2.2ms preprocess, 37.2ms inference, 7.2ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss44_png.rf.b6697a646548922305672e657697750b.jpg: 640x640 3 with_masks, 1 without_mask, 37.2ms\n",
+            "Speed: 1.8ms preprocess, 37.2ms inference, 2.2ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss450_png.rf.8f5e0ff6c7228f1180f985685beb20d5.jpg: 640x640 4 with_masks, 37.2ms\n",
+            "Speed: 2.1ms preprocess, 37.2ms inference, 2.2ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss457_png.rf.60b3bf773c197a83826aae38a0cf2387.jpg: 640x640 5 with_masks, 1 without_mask, 37.2ms\n",
+            "Speed: 1.8ms preprocess, 37.2ms inference, 2.4ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss459_png.rf.73bd4ff56e948804a4c7d5cc9e2f98ef.jpg: 640x640 2 mask_weared_incorrects, 3 with_masks, 1 without_mask, 37.2ms\n",
+            "Speed: 1.7ms preprocess, 37.2ms inference, 2.1ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss45_png.rf.3b160c8afb75253926e1abf7b4972504.jpg: 640x640 1 with_mask, 2 without_masks, 37.2ms\n",
+            "Speed: 1.7ms preprocess, 37.2ms inference, 2.1ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss431_png.rf.c5e66fbd5f544edca4f20973ce5ecf08.jpg: 640x640 1 mask_weared_incorrect, 18 with_masks, 37.1ms\n",
+            "Speed: 1.9ms preprocess, 37.1ms inference, 2.3ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss395_png.rf.d0fd9e7ac741d7df48a86b7f291e9b49.jpg: 640x640 1 with_mask, 37.2ms\n",
+            "Speed: 1.9ms preprocess, 37.2ms inference, 2.0ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss389_png.rf.11956fb49c814dab304f0006b9075f71.jpg: 640x640 9 with_masks, 2 without_masks, 37.1ms\n",
+            "Speed: 1.8ms preprocess, 37.1ms inference, 2.2ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss388_png.rf.4847bd339895b2496b21a16876aca440.jpg: 640x640 1 mask_weared_incorrect, 10 with_masks, 8 without_masks, 37.2ms\n",
+            "Speed: 2.0ms preprocess, 37.2ms inference, 2.5ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss311_png.rf.8d4e3cc30ab76d6699d7f220a26286dd.jpg: 640x640 6 with_masks, 37.3ms\n",
+            "Speed: 2.7ms preprocess, 37.3ms inference, 2.2ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss313_png.rf.0d2ede745cca1bbc73883747763be4cb.jpg: 640x640 3 with_masks, 37.2ms\n",
+            "Speed: 2.0ms preprocess, 37.2ms inference, 2.3ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss315_png.rf.bdcb0e2cde8b888d72849bbf232bc644.jpg: 640x640 5 with_masks, 37.8ms\n",
+            "Speed: 2.2ms preprocess, 37.8ms inference, 2.2ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss31_png.rf.f71dabc8b32a5181ae4a7ec0724d169e.jpg: 640x640 2 with_masks, 37.2ms\n",
+            "Speed: 2.0ms preprocess, 37.2ms inference, 2.1ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss321_png.rf.d5ca9ccecbb235c5551003b177cd1d46.jpg: 640x640 1 mask_weared_incorrect, 3 with_masks, 1 without_mask, 37.2ms\n",
+            "Speed: 1.8ms preprocess, 37.2ms inference, 2.2ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss330_png.rf.ca2fe4eca45ae4b2bc6bb9fde6d39dff.jpg: 640x640 5 with_masks, 37.2ms\n",
+            "Speed: 1.8ms preprocess, 37.2ms inference, 2.1ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss338_png.rf.669c284dd81181d71654743a3ca9aeb3.jpg: 640x640 7 with_masks, 37.2ms\n",
+            "Speed: 2.0ms preprocess, 37.2ms inference, 2.1ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss339_png.rf.d26efdd756cada62599cd227994bbf56.jpg: 640x640 2 with_masks, 37.5ms\n",
+            "Speed: 2.1ms preprocess, 37.5ms inference, 2.1ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss343_png.rf.1c5c7bbcb828a1cf9d4d2584972083cb.jpg: 640x640 1 without_mask, 37.1ms\n",
+            "Speed: 2.1ms preprocess, 37.1ms inference, 2.0ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss351_png.rf.15436d1eb7080d7bae2e79d554a4d3cb.jpg: 640x640 1 with_mask, 37.2ms\n",
+            "Speed: 1.9ms preprocess, 37.2ms inference, 2.1ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss364_png.rf.74e470c60f166ba4ec1a268b153fa240.jpg: 640x640 4 with_masks, 37.1ms\n",
+            "Speed: 2.7ms preprocess, 37.1ms inference, 2.1ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss366_png.rf.433ea8f6b4fcab0d951b52116611c1be.jpg: 640x640 2 with_masks, 37.1ms\n",
+            "Speed: 1.8ms preprocess, 37.1ms inference, 2.4ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss368_png.rf.1d14fe4224d1b152c5e272d889fe3d45.jpg: 640x640 9 with_masks, 37.1ms\n",
+            "Speed: 2.0ms preprocess, 37.1ms inference, 2.4ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss374_png.rf.b51c420d86fc3a474ed557b5a230b51e.jpg: 640x640 4 with_masks, 1 without_mask, 37.3ms\n",
+            "Speed: 1.9ms preprocess, 37.3ms inference, 2.2ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss376_png.rf.ca418b2ffccc242892a1ab14657e8349.jpg: 640x640 7 with_masks, 37.2ms\n",
+            "Speed: 1.7ms preprocess, 37.2ms inference, 2.3ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss37_png.rf.60ce2ff44ae089a01d8f07ff2e0f00ad.jpg: 640x640 1 with_mask, 37.1ms\n",
+            "Speed: 2.0ms preprocess, 37.1ms inference, 2.0ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss387_png.rf.6d027b3075e33a4414cc245ec7435fcc.jpg: 640x640 1 mask_weared_incorrect, 4 with_masks, 37.2ms\n",
+            "Speed: 2.2ms preprocess, 37.2ms inference, 2.1ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss464_png.rf.b7d07a0f6aabc271e6bfbe039246786b.jpg: 640x640 7 with_masks, 37.2ms\n",
+            "Speed: 1.7ms preprocess, 37.2ms inference, 2.1ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n",
+            "      42/80      9.42G     0.9645     0.4966      1.044        115        640: 100%|██████████| 106/106 [01:00<00:00,  1.75it/s]\n",
+            "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100%|██████████| 6/6 [00:02<00:00,  2.22it/s]\n",
+            "                   all        161        861      0.849      0.726      0.806      0.525\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss90_png.rf.bb3401c96e9aba7db607a9a5ac8d8f51.jpg: 640x640 10 with_masks, 38.7ms\n",
+            "Speed: 1.8ms preprocess, 38.7ms inference, 2.9ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n",
+            "      43/80      9.44G     0.9858     0.4992      1.045         84        640: 100%|██████████| 106/106 [01:01<00:00,  1.73it/s]\n",
+            "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100%|██████████| 6/6 [00:02<00:00,  2.14it/s]\n",
+            "                   all        161        861       0.89      0.773      0.825      0.544\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss107_png.rf.285757ad3a789f0d69380282b3bdb846.jpg: 640x640 1 with_mask, 38.7ms\n",
+            "Speed: 13.3ms preprocess, 38.7ms inference, 2.8ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss569_png.rf.245d020288f15a704c2742a49eb1ca63.jpg: 640x640 1 with_mask, 37.2ms\n",
+            "Speed: 1.9ms preprocess, 37.2ms inference, 3.1ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss56_png.rf.ffec370c63bb3ee301d05f9ce072e3fa.jpg: 640x640 1 with_mask, 45.6ms\n",
+            "Speed: 5.4ms preprocess, 45.6ms inference, 7.5ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss577_png.rf.99d8deb18d344f24bb95f02394713470.jpg: 640x640 16 with_masks, 1 without_mask, 37.2ms\n",
+            "Speed: 2.1ms preprocess, 37.2ms inference, 2.9ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss585_png.rf.16b40d54481e86f0a1434d30bc6d9c64.jpg: 640x640 4 with_masks, 2 without_masks, 37.1ms\n",
+            "Speed: 1.9ms preprocess, 37.1ms inference, 2.2ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss595_png.rf.f3a260412881f24273c64d6bd6e1966b.jpg: 640x640 6 with_masks, 37.2ms\n",
+            "Speed: 1.8ms preprocess, 37.2ms inference, 2.2ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss596_png.rf.9bf29752ebe873bc099ff9b64ddef6d1.jpg: 640x640 1 with_mask, 37.1ms\n",
+            "Speed: 1.8ms preprocess, 37.1ms inference, 2.0ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss603_png.rf.0d06c5299fd1cf3136e68b97a2afa4fd.jpg: 640x640 1 mask_weared_incorrect, 102 with_masks, 25 without_masks, 37.1ms\n",
+            "Speed: 1.7ms preprocess, 37.1ms inference, 2.1ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss568_png.rf.a4d4a4e139954b5194617ef2e9ffc81c.jpg: 640x640 1 with_mask, 37.1ms\n",
+            "Speed: 1.6ms preprocess, 37.1ms inference, 2.0ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss608_png.rf.4806b67fedacda192a8448bcf3b53d64.jpg: 640x640 1 with_mask, 37.1ms\n",
+            "Speed: 1.8ms preprocess, 37.1ms inference, 2.2ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss623_png.rf.19a2c6b529d5478510934f467949c887.jpg: 640x640 1 mask_weared_incorrect, 22 with_masks, 3 without_masks, 37.1ms\n",
+            "Speed: 1.7ms preprocess, 37.1ms inference, 2.3ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss626_png.rf.4a2f1a57a893fdcef400930251142f52.jpg: 640x640 1 with_mask, 37.1ms\n",
+            "Speed: 1.7ms preprocess, 37.1ms inference, 2.1ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss627_png.rf.81b096f6b0f9e897cc64f59880e630e0.jpg: 640x640 3 mask_weared_incorrects, 6 with_masks, 7 without_masks, 37.1ms\n",
+            "Speed: 4.5ms preprocess, 37.1ms inference, 2.1ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss630_png.rf.d1ecd7de587fb5c2571563293babff62.jpg: 640x640 1 with_mask, 37.1ms\n",
+            "Speed: 1.5ms preprocess, 37.1ms inference, 2.1ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss631_png.rf.418be1a60a0224818dc54e0d2281c6f4.jpg: 640x640 11 with_masks, 37.1ms\n",
+            "Speed: 1.8ms preprocess, 37.1ms inference, 2.2ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss636_png.rf.e6889a20be3cb52fa81b195fdef01b58.jpg: 640x640 6 with_masks, 2 without_masks, 37.1ms\n",
+            "Speed: 1.8ms preprocess, 37.1ms inference, 2.2ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss645_png.rf.d577b2fbdae8c09e7cb396b9c14f18d7.jpg: 640x640 1 with_mask, 37.2ms\n",
+            "Speed: 2.1ms preprocess, 37.2ms inference, 2.0ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss619_png.rf.bc1dcbfae2f9104ce082afe801399f54.jpg: 640x640 2 with_masks, 1 without_mask, 37.2ms\n",
+            "Speed: 1.8ms preprocess, 37.2ms inference, 2.2ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss646_png.rf.a434ddc2569b34a89bbb07a259996497.jpg: 640x640 1 with_mask, 37.1ms\n",
+            "Speed: 1.6ms preprocess, 37.1ms inference, 2.0ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss563_png.rf.dc088c07f08e5fba01fd6bddeceb27e2.jpg: 640x640 1 with_mask, 37.1ms\n",
+            "Speed: 2.0ms preprocess, 37.1ms inference, 2.0ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss554_png.rf.ba664c8fdc34b11faff3a128d06dbe9a.jpg: 640x640 1 mask_weared_incorrect, 5 with_masks, 37.2ms\n",
+            "Speed: 1.9ms preprocess, 37.2ms inference, 2.1ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss473_png.rf.6de35811442245ad013a2676e2bcaa0a.jpg: 640x640 3 with_masks, 1 without_mask, 37.1ms\n",
+            "Speed: 1.7ms preprocess, 37.1ms inference, 2.0ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss477_png.rf.0e319d347398d08b8a52fb6a152de44e.jpg: 640x640 7 with_masks, 7 without_masks, 37.1ms\n",
+            "Speed: 1.7ms preprocess, 37.1ms inference, 2.2ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss481_png.rf.6682292ffe5179b26d46c8515797446e.jpg: 640x640 10 with_masks, 37.2ms\n",
+            "Speed: 1.5ms preprocess, 37.2ms inference, 2.1ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss483_png.rf.4c059c2770f996153e3487a7f52f771c.jpg: 640x640 4 with_masks, 1 without_mask, 37.1ms\n",
+            "Speed: 1.5ms preprocess, 37.1ms inference, 2.1ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss484_png.rf.a57bfdb112b858aa9ed93bf36306ac61.jpg: 640x640 2 mask_weared_incorrects, 37.1ms\n",
+            "Speed: 1.5ms preprocess, 37.1ms inference, 2.1ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss498_png.rf.095899d089070e7a5a7697113b108f8a.jpg: 640x640 9 with_masks, 3 without_masks, 37.1ms\n",
+            "Speed: 1.9ms preprocess, 37.1ms inference, 2.2ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss499_png.rf.611bdf8f03aea1d86028c7b5d7d494ec.jpg: 640x640 1 with_mask, 1 without_mask, 37.1ms\n",
+            "Speed: 1.6ms preprocess, 37.1ms inference, 2.0ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss560_png.rf.bc8e65e2733e0f7b723391d33c380fe0.jpg: 640x640 1 with_mask, 37.1ms\n",
+            "Speed: 1.8ms preprocess, 37.1ms inference, 2.1ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss49_png.rf.d4077078d124ff3d3d699fc94bd06150.jpg: 640x640 7 with_masks, 3 without_masks, 37.2ms\n",
+            "Speed: 1.9ms preprocess, 37.2ms inference, 2.1ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss509_png.rf.6470c0dd2a6a4b05117cca6aad267087.jpg: 640x640 1 with_mask, 37.1ms\n",
+            "Speed: 2.0ms preprocess, 37.1ms inference, 2.0ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss512_png.rf.8dbd72e69a164fdcdad2e220bcd0c467.jpg: 640x640 8 with_masks, 37.1ms\n",
+            "Speed: 2.4ms preprocess, 37.1ms inference, 2.1ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n",
+            "      44/80      9.47G     0.9401     0.4742      1.035        100        640: 100%|██████████| 106/106 [01:00<00:00,  1.77it/s]\n",
+            "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100%|██████████| 6/6 [00:02<00:00,  2.15it/s]\n",
+            "                   all        161        861      0.872      0.744      0.806      0.518\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss515_png.rf.9b8d660e9368ee9ccfeb977e609167ed.jpg: 640x640 1 with_mask, 38.6ms\n",
+            "Speed: 1.7ms preprocess, 38.6ms inference, 2.9ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss529_png.rf.6ae323861cb838fc945c80ee31070c4c.jpg: 640x640 7 with_masks, 2 without_masks, 37.2ms\n",
+            "Speed: 1.8ms preprocess, 37.2ms inference, 2.1ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss532_png.rf.03aa559343f932efbfa3753190291fa7.jpg: 640x640 1 with_mask, 37.1ms\n",
+            "Speed: 2.0ms preprocess, 37.1ms inference, 2.2ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss537_png.rf.f22f4997ea93880ebfa2cb19a893caad.jpg: 640x640 1 without_mask, 37.2ms\n",
+            "Speed: 2.0ms preprocess, 37.2ms inference, 2.1ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss551_png.rf.010062fb38326dac49ecca8d9322953f.jpg: 640x640 5 with_masks, 37.1ms\n",
+            "Speed: 1.8ms preprocess, 37.1ms inference, 2.1ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss501_png.rf.125122fa5a318ec6d0e27d632764f840.jpg: 640x640 8 with_masks, 37.1ms\n",
+            "Speed: 2.7ms preprocess, 37.1ms inference, 2.2ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss649_png.rf.5540865cd8826940d55b3b48c045183c.jpg: 640x640 1 with_mask, 37.1ms\n",
+            "Speed: 1.8ms preprocess, 37.1ms inference, 2.2ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss64_png.rf.4b8ca34d17365fb62029fdbee94cb0aa.jpg: 640x640 3 with_masks, 37.2ms\n",
+            "Speed: 1.7ms preprocess, 37.2ms inference, 2.1ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss653_png.rf.22cf40d34bad20f7f9b542b6a0a89e2f.jpg: 640x640 2 with_masks, 37.2ms\n",
+            "Speed: 1.8ms preprocess, 37.2ms inference, 2.0ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss787_png.rf.a7e026e8082789734a57252cf6df81e5.jpg: 640x640 8 with_masks, 2 without_masks, 37.2ms\n",
+            "Speed: 1.9ms preprocess, 37.2ms inference, 3.4ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss793_png.rf.dd2be948b6231ceb68a6af8371f2329c.jpg: 640x640 1 with_mask, 37.2ms\n",
+            "Speed: 2.1ms preprocess, 37.2ms inference, 3.0ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss797_png.rf.5ead12df141e267f928b7b34c73dfb1a.jpg: 640x640 6 with_masks, 3 without_masks, 37.2ms\n",
+            "Speed: 1.7ms preprocess, 37.2ms inference, 2.6ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss79_png.rf.e12280d9bd602d3e52504b83921437d6.jpg: 640x640 5 with_masks, 37.1ms\n",
+            "Speed: 1.8ms preprocess, 37.1ms inference, 2.6ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss806_png.rf.504dc192775390a4b3f7d6b85bc58636.jpg: 640x640 6 with_masks, 37.2ms\n",
+            "Speed: 1.9ms preprocess, 37.2ms inference, 2.5ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss808_png.rf.b2e534caaaf701b8674add21e64fd528.jpg: 640x640 1 with_mask, 37.2ms\n",
+            "Speed: 1.9ms preprocess, 37.2ms inference, 2.5ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss822_png.rf.8601f2a416cbe3f239fde9934f5f66d2.jpg: 640x640 11 with_masks, 5 without_masks, 37.7ms\n",
+            "Speed: 1.8ms preprocess, 37.7ms inference, 3.0ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss784_png.rf.b95afb3096062e72503f25dfdaf53f52.jpg: 640x640 8 with_masks, 1 without_mask, 37.2ms\n",
+            "Speed: 1.9ms preprocess, 37.2ms inference, 2.7ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss828_png.rf.ef40e6fb83c895f7c4ca491dadbcecb1.jpg: 640x640 1 with_mask, 37.6ms\n",
+            "Speed: 1.9ms preprocess, 37.6ms inference, 2.8ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss832_png.rf.fd2d4b0fa4b62433e71f92aa8f1bc067.jpg: 640x640 1 mask_weared_incorrect, 1 with_mask, 1 without_mask, 37.2ms\n",
+            "Speed: 2.1ms preprocess, 37.2ms inference, 3.2ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss834_png.rf.c14acf559bb5531c92d3cf19a5193aa2.jpg: 640x640 6 with_masks, 37.1ms\n",
+            "Speed: 2.2ms preprocess, 37.1ms inference, 2.9ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss835_png.rf.b8a44eb8c868a51999b450873338a62a.jpg: 640x640 1 mask_weared_incorrect, 1 with_mask, 37.2ms\n",
+            "Speed: 2.0ms preprocess, 37.2ms inference, 3.0ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss840_png.rf.78c778f16a6a87f204473b70c7e735b1.jpg: 640x640 2 with_masks, 37.2ms\n",
+            "Speed: 2.0ms preprocess, 37.2ms inference, 3.1ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss844_png.rf.98f015b79733ae45cfff40da2c6eb85c.jpg: 640x640 2 with_masks, 37.2ms\n",
+            "Speed: 1.9ms preprocess, 37.2ms inference, 3.2ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss846_png.rf.f600f86418cd50b99d7116344abfe0df.jpg: 640x640 2 with_masks, 37.2ms\n",
+            "Speed: 1.8ms preprocess, 37.2ms inference, 2.9ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss848_png.rf.a1793122f2a5ab2b5a3d7be92157ea6b.jpg: 640x640 3 with_masks, 37.2ms\n",
+            "Speed: 4.3ms preprocess, 37.2ms inference, 2.8ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss830_png.rf.c8684a6a7e69bd43d4d35d54f2004fd7.jpg: 640x640 1 mask_weared_incorrect, 1 with_mask, 37.2ms\n",
+            "Speed: 1.9ms preprocess, 37.2ms inference, 3.0ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss761_png.rf.666e2aaecaf296dc7fe39031d857300a.jpg: 640x640 1 mask_weared_incorrect, 37.2ms\n",
+            "Speed: 1.8ms preprocess, 37.2ms inference, 2.9ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss751_png.rf.dad3bdfd78335be99b02ca0f7f0a6679.jpg: 640x640 1 mask_weared_incorrect, 5 with_masks, 37.2ms\n",
+            "Speed: 1.9ms preprocess, 37.2ms inference, 3.0ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss748_png.rf.75b65aa87d1ab4b31a47b7e3f80a43c3.jpg: 640x640 1 mask_weared_incorrect, 37.2ms\n",
+            "Speed: 1.8ms preprocess, 37.2ms inference, 2.8ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss658_png.rf.18a299a86c94f8a6784af81f2f6b6c89.jpg: 640x640 1 mask_weared_incorrect, 1 with_mask, 37.2ms\n",
+            "Speed: 1.8ms preprocess, 37.2ms inference, 2.9ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss65_png.rf.f3dacea8ddea2ac8019c39c83bcec5c4.jpg: 640x640 2 with_masks, 1 without_mask, 37.2ms\n",
+            "Speed: 1.9ms preprocess, 37.2ms inference, 2.9ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss662_png.rf.0dec50b3c2f682da13df8167851159b8.jpg: 640x640 4 with_masks, 37.2ms\n",
+            "Speed: 1.8ms preprocess, 37.2ms inference, 2.9ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n",
+            "      45/80      9.59G     0.9338     0.4761      1.031         96        640: 100%|██████████| 106/106 [01:01<00:00,  1.74it/s]\n",
+            "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100%|██████████| 6/6 [00:02<00:00,  2.19it/s]\n",
+            "                   all        161        861      0.892      0.786      0.824      0.533\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss664_png.rf.d7257f69f379e30582c9d5854e4bb093.jpg: 640x640 1 with_mask, 46.7ms\n",
+            "Speed: 1.9ms preprocess, 46.7ms inference, 2.5ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss674_png.rf.7848cd9439fa5dc0f5b03471912cdd27.jpg: 640x640 20 with_masks, 1 without_mask, 37.2ms\n",
+            "Speed: 1.9ms preprocess, 37.2ms inference, 3.2ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss680_png.rf.6430e43e329f2bd17482dab5d188875a.jpg: 640x640 1 mask_weared_incorrect, 9 with_masks, 1 without_mask, 37.1ms\n",
+            "Speed: 1.8ms preprocess, 37.1ms inference, 2.2ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss691_png.rf.68076bbedb2a9c8ce1c37ba0bc259d8c.jpg: 640x640 18 with_masks, 37.2ms\n",
+            "Speed: 1.7ms preprocess, 37.2ms inference, 2.1ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss694_png.rf.92b3468ed6b2d74d6e8e47c151e871a0.jpg: 640x640 6 with_masks, 37.1ms\n",
+            "Speed: 1.8ms preprocess, 37.1ms inference, 2.1ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss708_png.rf.0b01c6531d4980ea30cfde314a37ac52.jpg: 640x640 5 with_masks, 37.1ms\n",
+            "Speed: 2.2ms preprocess, 37.1ms inference, 2.1ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss714_png.rf.c59ce90ae182b29cc037c99b47028dd2.jpg: 640x640 4 with_masks, 38.2ms\n",
+            "Speed: 1.8ms preprocess, 38.2ms inference, 2.1ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss723_png.rf.4f8f04c5a74149652aaa8862ac9acb2a.jpg: 640x640 9 with_masks, 7 without_masks, 37.1ms\n",
+            "Speed: 1.7ms preprocess, 37.1ms inference, 2.3ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss725_png.rf.24ef1eeec5e346d219ce1633e649949c.jpg: 640x640 1 with_mask, 37.2ms\n",
+            "Speed: 1.8ms preprocess, 37.2ms inference, 2.2ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss72_png.rf.b94af68c76d704d083fc9720d480ef93.jpg: 640x640 1 without_mask, 37.2ms\n",
+            "Speed: 1.8ms preprocess, 37.2ms inference, 2.1ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss733_png.rf.bde25a6afb7d3fef880a5c9723c5c30d.jpg: 640x640 1 with_mask, 37.1ms\n",
+            "Speed: 1.9ms preprocess, 37.1ms inference, 2.2ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss73_png.rf.4f856521249c200a0dac653cddd51e50.jpg: 640x640 4 with_masks, 37.2ms\n",
+            "Speed: 1.7ms preprocess, 37.2ms inference, 2.2ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss744_png.rf.a8b60de6dbbfeb80df902a739b90f925.jpg: 640x640 2 with_masks, 1 without_mask, 37.1ms\n",
+            "Speed: 1.7ms preprocess, 37.1ms inference, 2.2ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss747_png.rf.09f39fbe610327e3092119f0e0a091ff.jpg: 640x640 1 with_mask, 37.2ms\n",
+            "Speed: 3.0ms preprocess, 37.2ms inference, 2.2ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss471_png.rf.c52f488eaed280f80c7d3e439c0c4e2a.jpg: 640x640 5 with_masks, 2 without_masks, 37.1ms\n",
+            "Speed: 1.9ms preprocess, 37.1ms inference, 2.4ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss89_png.rf.0459d0e0116e154559a89c1975734728.jpg: 640x640 42 with_masks, 2 without_masks, 37.1ms\n",
+            "Speed: 1.9ms preprocess, 37.1ms inference, 2.4ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss470_png.rf.3fca085941c9a6dbd4e79ea151f97079.jpg: 640x640 5 with_masks, 37.2ms\n",
+            "Speed: 1.9ms preprocess, 37.2ms inference, 3.2ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss461_png.rf.6316f0f312cd4c8c93c77f83f5484af9.jpg: 640x640 8 with_masks, 37.2ms\n",
+            "Speed: 2.0ms preprocess, 37.2ms inference, 3.2ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss230_png.rf.1fe3136ab2b6bffc7cd0b6e65101870c.jpg: 640x640 5 with_masks, 1 without_mask, 37.2ms\n",
+            "Speed: 1.8ms preprocess, 37.2ms inference, 2.7ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss236_png.rf.ea526bb945fec0e07973f2cd052ef688.jpg: 640x640 1 without_mask, 37.2ms\n",
+            "Speed: 2.3ms preprocess, 37.2ms inference, 2.5ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss241_png.rf.01c103b7f1b42f6eaaa3f4c67d5e063a.jpg: 640x640 2 with_masks, 37.1ms\n",
+            "Speed: 1.8ms preprocess, 37.1ms inference, 2.7ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss242_png.rf.048ddfefd131055beb8263c92bbb62a8.jpg: 640x640 1 with_mask, 37.2ms\n",
+            "Speed: 1.7ms preprocess, 37.2ms inference, 2.7ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss244_png.rf.f9240dd571e5670cad3b769290bbd680.jpg: 640x640 1 with_mask, 2 without_masks, 38.0ms\n",
+            "Speed: 2.2ms preprocess, 38.0ms inference, 2.7ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss247_png.rf.f67e30adf66e59df979a1db74326bd5b.jpg: 640x640 13 with_masks, 37.2ms\n",
+            "Speed: 2.0ms preprocess, 37.2ms inference, 3.5ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss248_png.rf.c19d9460b893693e4b637a1f7df7008a.jpg: 640x640 1 without_mask, 37.1ms\n",
+            "Speed: 2.0ms preprocess, 37.1ms inference, 2.8ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss229_png.rf.45ba617a90c78bc0e8e547bffedbe3c3.jpg: 640x640 14 with_masks, 37.2ms\n",
+            "Speed: 1.8ms preprocess, 37.2ms inference, 2.9ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss253_png.rf.93b13ca348adf361296ed659d6acfe75.jpg: 640x640 7 with_masks, 4 without_masks, 37.1ms\n",
+            "Speed: 1.9ms preprocess, 37.1ms inference, 2.9ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss264_png.rf.7018fdf357ffc35189a710fdfc752b52.jpg: 640x640 7 with_masks, 37.1ms\n",
+            "Speed: 3.7ms preprocess, 37.1ms inference, 2.8ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss271_png.rf.cc2239f13f1ebcc7519a1b37fc36376a.jpg: 640x640 1 with_mask, 37.1ms\n",
+            "Speed: 1.8ms preprocess, 37.1ms inference, 2.7ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss277_png.rf.12d1ae22a19b53135a7172821eaf2559.jpg: 640x640 8 with_masks, 37.2ms\n",
+            "Speed: 1.7ms preprocess, 37.2ms inference, 5.0ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss282_png.rf.32d06bf0012896891f681325fa56166d.jpg: 640x640 9 with_masks, 1 without_mask, 37.1ms\n",
+            "Speed: 2.0ms preprocess, 37.1ms inference, 2.8ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss289_png.rf.fee0ba4040ee03de9c67793e8127c627.jpg: 640x640 3 without_masks, 37.2ms\n",
+            "Speed: 1.7ms preprocess, 37.2ms inference, 2.8ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n",
+            "      46/80      9.62G     0.9246     0.4633      1.025         88        640: 100%|██████████| 106/106 [01:03<00:00,  1.66it/s]\n",
+            "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100%|██████████| 6/6 [00:03<00:00,  1.93it/s]\n",
+            "                   all        161        861      0.894      0.784      0.829      0.529\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss301_png.rf.79b160619414ca6a470bd5ea8b30ef4a.jpg: 640x640 17 with_masks, 1 without_mask, 47.0ms\n",
+            "Speed: 1.9ms preprocess, 47.0ms inference, 7.3ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss303_png.rf.f00ae35b4058b933e066d1d2a4d88c17.jpg: 640x640 2 with_masks, 37.2ms\n",
+            "Speed: 2.2ms preprocess, 37.2ms inference, 3.3ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss258_png.rf.fc7b4f2f14e1d199dce55985695d1120.jpg: 640x640 1 with_mask, 37.3ms\n",
+            "Speed: 2.4ms preprocess, 37.3ms inference, 2.1ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss304_png.rf.9df48cf93de57fa41d0a2b59de78a62c.jpg: 640x640 2 with_masks, 37.2ms\n",
+            "Speed: 1.8ms preprocess, 37.2ms inference, 2.2ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss224_png.rf.4539ed1dc0a709e4e01077ecf7bc2b22.jpg: 640x640 2 with_masks, 37.4ms\n",
+            "Speed: 2.1ms preprocess, 37.4ms inference, 2.1ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss20_png.rf.ca394d629ffaba1fdb13e432a79a5eb9.jpg: 640x640 1 with_mask, 37.2ms\n",
+            "Speed: 2.0ms preprocess, 37.2ms inference, 2.4ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss109_png.rf.3c26f7537566830dffb39c47f71e574e.jpg: 640x640 1 with_mask, 37.2ms\n",
+            "Speed: 2.1ms preprocess, 37.2ms inference, 2.2ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss114_png.rf.c087c8382ac2542ac89314fa0bbeb4f6.jpg: 640x640 1 with_mask, 1 without_mask, 37.1ms\n",
+            "Speed: 1.9ms preprocess, 37.1ms inference, 2.5ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss127_png.rf.1baab62c26cbf4478f2a8d99e1cf68de.jpg: 640x640 1 with_mask, 37.1ms\n",
+            "Speed: 1.8ms preprocess, 37.1ms inference, 2.4ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss146_png.rf.ec0da30308aa466d39bae79b0cc0e2bf.jpg: 640x640 3 with_masks, 37.1ms\n",
+            "Speed: 1.5ms preprocess, 37.1ms inference, 2.2ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss152_png.rf.c66bb39b29efc7503239890f834100dc.jpg: 640x640 8 with_masks, 37.1ms\n",
+            "Speed: 2.2ms preprocess, 37.1ms inference, 3.5ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss154_png.rf.7512e06f4e0bd3a2185ec1867603cc8a.jpg: 640x640 1 without_mask, 37.2ms\n",
+            "Speed: 1.8ms preprocess, 37.2ms inference, 2.2ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss168_png.rf.3b19cb741e672eef23c3f091fd204d52.jpg: 640x640 3 with_masks, 3 without_masks, 37.2ms\n",
+            "Speed: 2.0ms preprocess, 37.2ms inference, 2.2ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss217_png.rf.c4e305ead91154374bba4fc48e0e3b99.jpg: 640x640 1 without_mask, 37.2ms\n",
+            "Speed: 1.8ms preprocess, 37.2ms inference, 2.3ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss169_png.rf.49a3d702f1cd1ce83aa6cd01599e3644.jpg: 640x640 1 with_mask, 37.2ms\n",
+            "Speed: 1.9ms preprocess, 37.2ms inference, 2.1ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss174_png.rf.ba1760e663e246482b26e587332650b0.jpg: 640x640 4 with_masks, 37.1ms\n",
+            "Speed: 1.8ms preprocess, 37.1ms inference, 2.3ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss178_png.rf.2fd8857c96b9bed1982f78b55798a334.jpg: 640x640 2 with_masks, 1 without_mask, 37.1ms\n",
+            "Speed: 1.9ms preprocess, 37.1ms inference, 2.2ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss194_png.rf.77ed2eca9fe5235cf2496449dd156996.jpg: 640x640 2 with_masks, 37.2ms\n",
+            "Speed: 2.2ms preprocess, 37.2ms inference, 2.2ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss197_png.rf.cd0c6b120a0fae906bb417f825daf6a1.jpg: 640x640 2 with_masks, 37.2ms\n",
+            "Speed: 2.6ms preprocess, 37.2ms inference, 2.2ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss1_png.rf.e41f0052ad0e49cab0887d6e50e5a7eb.jpg: 640x640 7 with_masks, 1 without_mask, 37.1ms\n",
+            "Speed: 1.9ms preprocess, 37.1ms inference, 2.4ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss203_png.rf.eba7307a461c6b2098593e82d2cccecc.jpg: 640x640 4 with_masks, 37.2ms\n",
+            "Speed: 1.7ms preprocess, 37.2ms inference, 2.5ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss206_png.rf.68794173883f5ae26e2382a3087aac0b.jpg: 640x640 7 with_masks, 2 without_masks, 37.2ms\n",
+            "Speed: 1.8ms preprocess, 37.2ms inference, 2.4ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss172_png.rf.13bb93a8bf5266e0d73bab43f62e0376.jpg: 640x640 1 without_mask, 37.2ms\n",
+            "Speed: 2.0ms preprocess, 37.2ms inference, 2.2ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss306_png.rf.52a38aff8eebcfb7d90d0c7cac38fdec.jpg: 640x640 1 with_mask, 37.2ms\n",
+            "Speed: 2.1ms preprocess, 37.2ms inference, 2.2ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss307_png.rf.93b21e5a88a625f2a9284ff6253bd417.jpg: 640x640 1 mask_weared_incorrect, 1 with_mask, 37.2ms\n",
+            "Speed: 2.0ms preprocess, 37.2ms inference, 2.8ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss308_png.rf.61a249cc68e67a9cf66c2393f61080f2.jpg: 640x640 2 with_masks, 37.4ms\n",
+            "Speed: 1.8ms preprocess, 37.4ms inference, 3.3ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss402_png.rf.adb70e16aac43aa519466a4364f99311.jpg: 640x640 1 without_mask, 37.3ms\n",
+            "Speed: 2.0ms preprocess, 37.3ms inference, 2.7ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss408_png.rf.bb077fd8dd6090c8f22b2dfe4fb0b2dc.jpg: 640x640 8 with_masks, 3 without_masks, 37.2ms\n",
+            "Speed: 1.8ms preprocess, 37.2ms inference, 2.8ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss409_png.rf.a1da634820d49e7be38ce59f5f5887bb.jpg: 640x640 1 with_mask, 37.1ms\n",
+            "Speed: 1.9ms preprocess, 37.1ms inference, 2.8ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss410_png.rf.eaad04d3f7e7468f6a0a3d017306d6da.jpg: 640x640 1 mask_weared_incorrect, 20 with_masks, 2 without_masks, 37.2ms\n",
+            "Speed: 1.7ms preprocess, 37.2ms inference, 2.7ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss418_png.rf.432d10d262677cb69e95be55ca0c9125.jpg: 640x640 3 with_masks, 37.1ms\n",
+            "Speed: 1.9ms preprocess, 37.1ms inference, 3.0ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss421_png.rf.7ecb66f6ba285fd631717a3635a7dd71.jpg: 640x640 5 with_masks, 37.3ms\n",
+            "Speed: 1.7ms preprocess, 37.3ms inference, 2.7ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n",
+            "      47/80      9.57G     0.9267     0.4664      1.031        118        640: 100%|██████████| 106/106 [01:02<00:00,  1.71it/s]\n",
+            "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100%|██████████| 6/6 [00:02<00:00,  2.25it/s]\n",
+            "                   all        161        861      0.876      0.819      0.845      0.552\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss425_png.rf.b69c6da9a6c99fd8edfdad09f10582d2.jpg: 640x640 1 with_mask, 48.9ms\n",
+            "Speed: 5.5ms preprocess, 48.9ms inference, 3.0ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss400_png.rf.63c84ce5e3e0391c9509f77d2244755c.jpg: 640x640 3 with_masks, 39.8ms\n",
+            "Speed: 1.9ms preprocess, 39.8ms inference, 3.4ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss429_png.rf.0f9bc0b4f072650f40e985eefdce87df.jpg: 640x640 4 with_masks, 37.2ms\n",
+            "Speed: 2.0ms preprocess, 37.2ms inference, 3.4ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss438_png.rf.85978160d8cedb7d56a26e0d06e41f87.jpg: 640x640 4 with_masks, 37.3ms\n",
+            "Speed: 2.0ms preprocess, 37.3ms inference, 2.3ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss440_png.rf.641564d43589f6344bacc5d05d51da53.jpg: 640x640 1 mask_weared_incorrect, 7 with_masks, 37.1ms\n",
+            "Speed: 2.2ms preprocess, 37.1ms inference, 2.2ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss44_png.rf.b6697a646548922305672e657697750b.jpg: 640x640 4 with_masks, 1 without_mask, 37.2ms\n",
+            "Speed: 1.8ms preprocess, 37.2ms inference, 2.4ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss450_png.rf.8f5e0ff6c7228f1180f985685beb20d5.jpg: 640x640 4 with_masks, 37.2ms\n",
+            "Speed: 2.0ms preprocess, 37.2ms inference, 2.4ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss457_png.rf.60b3bf773c197a83826aae38a0cf2387.jpg: 640x640 5 with_masks, 1 without_mask, 37.2ms\n",
+            "Speed: 2.1ms preprocess, 37.2ms inference, 2.3ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss459_png.rf.73bd4ff56e948804a4c7d5cc9e2f98ef.jpg: 640x640 1 with_mask, 1 without_mask, 37.3ms\n",
+            "Speed: 2.7ms preprocess, 37.3ms inference, 2.5ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss45_png.rf.3b160c8afb75253926e1abf7b4972504.jpg: 640x640 1 with_mask, 1 without_mask, 37.1ms\n",
+            "Speed: 1.6ms preprocess, 37.1ms inference, 3.4ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss431_png.rf.c5e66fbd5f544edca4f20973ce5ecf08.jpg: 640x640 1 mask_weared_incorrect, 18 with_masks, 37.2ms\n",
+            "Speed: 2.3ms preprocess, 37.2ms inference, 2.2ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss395_png.rf.d0fd9e7ac741d7df48a86b7f291e9b49.jpg: 640x640 2 with_masks, 37.2ms\n",
+            "Speed: 2.4ms preprocess, 37.2ms inference, 2.2ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss389_png.rf.11956fb49c814dab304f0006b9075f71.jpg: 640x640 10 with_masks, 1 without_mask, 37.2ms\n",
+            "Speed: 1.8ms preprocess, 37.2ms inference, 2.3ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss388_png.rf.4847bd339895b2496b21a16876aca440.jpg: 640x640 12 with_masks, 8 without_masks, 37.2ms\n",
+            "Speed: 1.6ms preprocess, 37.2ms inference, 2.2ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss311_png.rf.8d4e3cc30ab76d6699d7f220a26286dd.jpg: 640x640 5 with_masks, 37.1ms\n",
+            "Speed: 1.9ms preprocess, 37.1ms inference, 2.4ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss313_png.rf.0d2ede745cca1bbc73883747763be4cb.jpg: 640x640 1 with_mask, 37.2ms\n",
+            "Speed: 1.9ms preprocess, 37.2ms inference, 2.8ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss315_png.rf.bdcb0e2cde8b888d72849bbf232bc644.jpg: 640x640 2 with_masks, 37.2ms\n",
+            "Speed: 1.9ms preprocess, 37.2ms inference, 5.0ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss31_png.rf.f71dabc8b32a5181ae4a7ec0724d169e.jpg: 640x640 2 with_masks, 37.2ms\n",
+            "Speed: 1.8ms preprocess, 37.2ms inference, 2.7ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss321_png.rf.d5ca9ccecbb235c5551003b177cd1d46.jpg: 640x640 1 mask_weared_incorrect, 2 with_masks, 1 without_mask, 37.2ms\n",
+            "Speed: 2.1ms preprocess, 37.2ms inference, 2.9ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss330_png.rf.ca2fe4eca45ae4b2bc6bb9fde6d39dff.jpg: 640x640 4 with_masks, 37.2ms\n",
+            "Speed: 1.8ms preprocess, 37.2ms inference, 2.6ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss338_png.rf.669c284dd81181d71654743a3ca9aeb3.jpg: 640x640 8 with_masks, 37.3ms\n",
+            "Speed: 2.0ms preprocess, 37.3ms inference, 3.9ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss339_png.rf.d26efdd756cada62599cd227994bbf56.jpg: 640x640 1 with_mask, 37.2ms\n",
+            "Speed: 2.1ms preprocess, 37.2ms inference, 4.2ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss343_png.rf.1c5c7bbcb828a1cf9d4d2584972083cb.jpg: 640x640 1 without_mask, 37.2ms\n",
+            "Speed: 2.0ms preprocess, 37.2ms inference, 3.1ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss351_png.rf.15436d1eb7080d7bae2e79d554a4d3cb.jpg: 640x640 1 with_mask, 37.2ms\n",
+            "Speed: 1.8ms preprocess, 37.2ms inference, 2.9ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss364_png.rf.74e470c60f166ba4ec1a268b153fa240.jpg: 640x640 3 with_masks, 37.2ms\n",
+            "Speed: 1.9ms preprocess, 37.2ms inference, 2.8ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss366_png.rf.433ea8f6b4fcab0d951b52116611c1be.jpg: 640x640 2 with_masks, 37.1ms\n",
+            "Speed: 1.8ms preprocess, 37.1ms inference, 2.8ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss368_png.rf.1d14fe4224d1b152c5e272d889fe3d45.jpg: 640x640 9 with_masks, 37.2ms\n",
+            "Speed: 1.9ms preprocess, 37.2ms inference, 3.1ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss374_png.rf.b51c420d86fc3a474ed557b5a230b51e.jpg: 640x640 4 with_masks, 1 without_mask, 37.2ms\n",
+            "Speed: 1.9ms preprocess, 37.2ms inference, 2.8ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss376_png.rf.ca418b2ffccc242892a1ab14657e8349.jpg: 640x640 8 with_masks, 37.2ms\n",
+            "Speed: 2.2ms preprocess, 37.2ms inference, 3.0ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss37_png.rf.60ce2ff44ae089a01d8f07ff2e0f00ad.jpg: 640x640 1 with_mask, 37.2ms\n",
+            "Speed: 2.1ms preprocess, 37.2ms inference, 3.1ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss387_png.rf.6d027b3075e33a4414cc245ec7435fcc.jpg: 640x640 1 mask_weared_incorrect, 3 with_masks, 37.2ms\n",
+            "Speed: 6.6ms preprocess, 37.2ms inference, 3.2ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss464_png.rf.b7d07a0f6aabc271e6bfbe039246786b.jpg: 640x640 9 with_masks, 37.2ms\n",
+            "Speed: 1.9ms preprocess, 37.2ms inference, 3.1ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n",
+            "      48/80      9.73G     0.9063      0.461      1.019        164        640: 100%|██████████| 106/106 [01:06<00:00,  1.60it/s]\n",
+            "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100%|██████████| 6/6 [00:03<00:00,  1.82it/s]\n",
+            "                   all        161        861      0.891      0.762      0.832      0.534\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss90_png.rf.bb3401c96e9aba7db607a9a5ac8d8f51.jpg: 640x640 13 with_masks, 40.0ms\n",
+            "Speed: 4.0ms preprocess, 40.0ms inference, 15.5ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n",
+            "      49/80      9.67G     0.8964     0.4531      1.017         86        640: 100%|██████████| 106/106 [01:10<00:00,  1.50it/s]\n",
+            "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100%|██████████| 6/6 [00:03<00:00,  1.91it/s]\n",
+            "                   all        161        861      0.915      0.764      0.846       0.54\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss107_png.rf.285757ad3a789f0d69380282b3bdb846.jpg: 640x640 1 with_mask, 38.8ms\n",
+            "Speed: 5.5ms preprocess, 38.8ms inference, 11.2ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss569_png.rf.245d020288f15a704c2742a49eb1ca63.jpg: 640x640 2 with_masks, 37.4ms\n",
+            "Speed: 5.1ms preprocess, 37.4ms inference, 2.9ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss56_png.rf.ffec370c63bb3ee301d05f9ce072e3fa.jpg: 640x640 1 with_mask, 37.9ms\n",
+            "Speed: 1.8ms preprocess, 37.9ms inference, 2.8ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss577_png.rf.99d8deb18d344f24bb95f02394713470.jpg: 640x640 11 with_masks, 37.2ms\n",
+            "Speed: 2.0ms preprocess, 37.2ms inference, 3.0ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss585_png.rf.16b40d54481e86f0a1434d30bc6d9c64.jpg: 640x640 4 with_masks, 2 without_masks, 37.2ms\n",
+            "Speed: 1.9ms preprocess, 37.2ms inference, 3.0ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss595_png.rf.f3a260412881f24273c64d6bd6e1966b.jpg: 640x640 6 with_masks, 37.2ms\n",
+            "Speed: 1.9ms preprocess, 37.2ms inference, 2.9ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss596_png.rf.9bf29752ebe873bc099ff9b64ddef6d1.jpg: 640x640 1 with_mask, 37.2ms\n",
+            "Speed: 1.9ms preprocess, 37.2ms inference, 3.6ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss603_png.rf.0d06c5299fd1cf3136e68b97a2afa4fd.jpg: 640x640 101 with_masks, 20 without_masks, 37.2ms\n",
+            "Speed: 1.8ms preprocess, 37.2ms inference, 3.1ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss568_png.rf.a4d4a4e139954b5194617ef2e9ffc81c.jpg: 640x640 1 with_mask, 37.2ms\n",
+            "Speed: 1.9ms preprocess, 37.2ms inference, 2.8ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss608_png.rf.4806b67fedacda192a8448bcf3b53d64.jpg: 640x640 1 with_mask, 37.2ms\n",
+            "Speed: 1.8ms preprocess, 37.2ms inference, 2.9ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss623_png.rf.19a2c6b529d5478510934f467949c887.jpg: 640x640 1 mask_weared_incorrect, 20 with_masks, 3 without_masks, 37.1ms\n",
+            "Speed: 1.8ms preprocess, 37.1ms inference, 2.9ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss626_png.rf.4a2f1a57a893fdcef400930251142f52.jpg: 640x640 1 with_mask, 37.1ms\n",
+            "Speed: 4.2ms preprocess, 37.1ms inference, 2.8ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss627_png.rf.81b096f6b0f9e897cc64f59880e630e0.jpg: 640x640 2 mask_weared_incorrects, 6 with_masks, 8 without_masks, 37.2ms\n",
+            "Speed: 2.1ms preprocess, 37.2ms inference, 2.8ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss630_png.rf.d1ecd7de587fb5c2571563293babff62.jpg: 640x640 1 with_mask, 37.2ms\n",
+            "Speed: 2.0ms preprocess, 37.2ms inference, 2.8ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss631_png.rf.418be1a60a0224818dc54e0d2281c6f4.jpg: 640x640 11 with_masks, 37.2ms\n",
+            "Speed: 1.8ms preprocess, 37.2ms inference, 2.9ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss636_png.rf.e6889a20be3cb52fa81b195fdef01b58.jpg: 640x640 6 with_masks, 2 without_masks, 37.2ms\n",
+            "Speed: 1.9ms preprocess, 37.2ms inference, 3.6ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss645_png.rf.d577b2fbdae8c09e7cb396b9c14f18d7.jpg: 640x640 1 with_mask, 37.3ms\n",
+            "Speed: 5.4ms preprocess, 37.3ms inference, 3.7ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss619_png.rf.bc1dcbfae2f9104ce082afe801399f54.jpg: 640x640 2 with_masks, 1 without_mask, 37.2ms\n",
+            "Speed: 2.1ms preprocess, 37.2ms inference, 2.2ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss646_png.rf.a434ddc2569b34a89bbb07a259996497.jpg: 640x640 1 with_mask, 37.1ms\n",
+            "Speed: 1.6ms preprocess, 37.1ms inference, 2.2ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss563_png.rf.dc088c07f08e5fba01fd6bddeceb27e2.jpg: 640x640 1 with_mask, 37.1ms\n",
+            "Speed: 1.9ms preprocess, 37.1ms inference, 2.1ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss554_png.rf.ba664c8fdc34b11faff3a128d06dbe9a.jpg: 640x640 5 with_masks, 37.1ms\n",
+            "Speed: 2.3ms preprocess, 37.1ms inference, 2.1ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss473_png.rf.6de35811442245ad013a2676e2bcaa0a.jpg: 640x640 3 with_masks, 1 without_mask, 37.2ms\n",
+            "Speed: 1.9ms preprocess, 37.2ms inference, 2.2ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss477_png.rf.0e319d347398d08b8a52fb6a152de44e.jpg: 640x640 1 mask_weared_incorrect, 7 with_masks, 7 without_masks, 37.1ms\n",
+            "Speed: 1.9ms preprocess, 37.1ms inference, 2.2ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss481_png.rf.6682292ffe5179b26d46c8515797446e.jpg: 640x640 8 with_masks, 37.2ms\n",
+            "Speed: 2.2ms preprocess, 37.2ms inference, 2.2ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss483_png.rf.4c059c2770f996153e3487a7f52f771c.jpg: 640x640 3 with_masks, 1 without_mask, 37.2ms\n",
+            "Speed: 2.1ms preprocess, 37.2ms inference, 2.3ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss484_png.rf.a57bfdb112b858aa9ed93bf36306ac61.jpg: 640x640 1 mask_weared_incorrect, 1 with_mask, 37.1ms\n",
+            "Speed: 1.7ms preprocess, 37.1ms inference, 2.1ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss498_png.rf.095899d089070e7a5a7697113b108f8a.jpg: 640x640 9 with_masks, 4 without_masks, 37.1ms\n",
+            "Speed: 1.7ms preprocess, 37.1ms inference, 2.2ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss499_png.rf.611bdf8f03aea1d86028c7b5d7d494ec.jpg: 640x640 1 with_mask, 1 without_mask, 37.1ms\n",
+            "Speed: 1.6ms preprocess, 37.1ms inference, 2.3ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss560_png.rf.bc8e65e2733e0f7b723391d33c380fe0.jpg: 640x640 1 with_mask, 1 without_mask, 37.2ms\n",
+            "Speed: 1.8ms preprocess, 37.2ms inference, 2.1ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss49_png.rf.d4077078d124ff3d3d699fc94bd06150.jpg: 640x640 7 with_masks, 3 without_masks, 37.2ms\n",
+            "Speed: 2.6ms preprocess, 37.2ms inference, 2.3ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss509_png.rf.6470c0dd2a6a4b05117cca6aad267087.jpg: 640x640 1 with_mask, 37.2ms\n",
+            "Speed: 1.8ms preprocess, 37.2ms inference, 2.4ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss512_png.rf.8dbd72e69a164fdcdad2e220bcd0c467.jpg: 640x640 8 with_masks, 41.5ms\n",
+            "Speed: 1.9ms preprocess, 41.5ms inference, 2.4ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n",
+            "      50/80      9.77G     0.8982     0.4541      1.022         55        640: 100%|██████████| 106/106 [01:06<00:00,  1.59it/s]\n",
+            "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100%|██████████| 6/6 [00:03<00:00,  1.87it/s]\n",
+            "                   all        161        861      0.851      0.805      0.842      0.541\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss515_png.rf.9b8d660e9368ee9ccfeb977e609167ed.jpg: 640x640 1 with_mask, 38.5ms\n",
+            "Speed: 1.6ms preprocess, 38.5ms inference, 2.8ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss529_png.rf.6ae323861cb838fc945c80ee31070c4c.jpg: 640x640 8 with_masks, 1 without_mask, 37.1ms\n",
+            "Speed: 2.1ms preprocess, 37.1ms inference, 2.1ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss532_png.rf.03aa559343f932efbfa3753190291fa7.jpg: 640x640 1 with_mask, 37.1ms\n",
+            "Speed: 1.8ms preprocess, 37.1ms inference, 2.0ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss537_png.rf.f22f4997ea93880ebfa2cb19a893caad.jpg: 640x640 1 without_mask, 37.1ms\n",
+            "Speed: 1.9ms preprocess, 37.1ms inference, 2.1ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss551_png.rf.010062fb38326dac49ecca8d9322953f.jpg: 640x640 5 with_masks, 37.1ms\n",
+            "Speed: 1.9ms preprocess, 37.1ms inference, 3.2ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss501_png.rf.125122fa5a318ec6d0e27d632764f840.jpg: 640x640 7 with_masks, 37.1ms\n",
+            "Speed: 1.6ms preprocess, 37.1ms inference, 2.6ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss649_png.rf.5540865cd8826940d55b3b48c045183c.jpg: 640x640 1 with_mask, 37.2ms\n",
+            "Speed: 2.8ms preprocess, 37.2ms inference, 2.1ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss64_png.rf.4b8ca34d17365fb62029fdbee94cb0aa.jpg: 640x640 3 with_masks, 37.1ms\n",
+            "Speed: 2.1ms preprocess, 37.1ms inference, 2.1ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss653_png.rf.22cf40d34bad20f7f9b542b6a0a89e2f.jpg: 640x640 2 with_masks, 37.1ms\n",
+            "Speed: 1.8ms preprocess, 37.1ms inference, 2.3ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss787_png.rf.a7e026e8082789734a57252cf6df81e5.jpg: 640x640 8 with_masks, 2 without_masks, 37.2ms\n",
+            "Speed: 1.8ms preprocess, 37.2ms inference, 2.2ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss793_png.rf.dd2be948b6231ceb68a6af8371f2329c.jpg: 640x640 1 with_mask, 37.1ms\n",
+            "Speed: 2.0ms preprocess, 37.1ms inference, 2.3ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss797_png.rf.5ead12df141e267f928b7b34c73dfb1a.jpg: 640x640 8 with_masks, 1 without_mask, 37.2ms\n",
+            "Speed: 1.7ms preprocess, 37.2ms inference, 2.1ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss79_png.rf.e12280d9bd602d3e52504b83921437d6.jpg: 640x640 5 with_masks, 37.1ms\n",
+            "Speed: 1.8ms preprocess, 37.1ms inference, 2.6ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss806_png.rf.504dc192775390a4b3f7d6b85bc58636.jpg: 640x640 6 with_masks, 37.2ms\n",
+            "Speed: 1.8ms preprocess, 37.2ms inference, 3.1ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss808_png.rf.b2e534caaaf701b8674add21e64fd528.jpg: 640x640 1 with_mask, 37.2ms\n",
+            "Speed: 1.9ms preprocess, 37.2ms inference, 2.5ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss822_png.rf.8601f2a416cbe3f239fde9934f5f66d2.jpg: 640x640 13 with_masks, 4 without_masks, 37.2ms\n",
+            "Speed: 3.7ms preprocess, 37.2ms inference, 2.8ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss784_png.rf.b95afb3096062e72503f25dfdaf53f52.jpg: 640x640 11 with_masks, 1 without_mask, 37.2ms\n",
+            "Speed: 1.8ms preprocess, 37.2ms inference, 2.6ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss828_png.rf.ef40e6fb83c895f7c4ca491dadbcecb1.jpg: 640x640 1 with_mask, 1 without_mask, 37.2ms\n",
+            "Speed: 1.9ms preprocess, 37.2ms inference, 2.5ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss832_png.rf.fd2d4b0fa4b62433e71f92aa8f1bc067.jpg: 640x640 1 mask_weared_incorrect, 1 with_mask, 1 without_mask, 37.2ms\n",
+            "Speed: 1.9ms preprocess, 37.2ms inference, 2.7ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss834_png.rf.c14acf559bb5531c92d3cf19a5193aa2.jpg: 640x640 6 with_masks, 37.2ms\n",
+            "Speed: 1.8ms preprocess, 37.2ms inference, 3.1ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss835_png.rf.b8a44eb8c868a51999b450873338a62a.jpg: 640x640 1 mask_weared_incorrect, 3 with_masks, 37.2ms\n",
+            "Speed: 1.7ms preprocess, 37.2ms inference, 2.8ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss840_png.rf.78c778f16a6a87f204473b70c7e735b1.jpg: 640x640 2 with_masks, 37.2ms\n",
+            "Speed: 1.8ms preprocess, 37.2ms inference, 2.8ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss844_png.rf.98f015b79733ae45cfff40da2c6eb85c.jpg: 640x640 2 with_masks, 37.2ms\n",
+            "Speed: 1.8ms preprocess, 37.2ms inference, 2.8ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss846_png.rf.f600f86418cd50b99d7116344abfe0df.jpg: 640x640 1 with_mask, 37.2ms\n",
+            "Speed: 1.8ms preprocess, 37.2ms inference, 2.9ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss848_png.rf.a1793122f2a5ab2b5a3d7be92157ea6b.jpg: 640x640 3 with_masks, 37.2ms\n",
+            "Speed: 1.9ms preprocess, 37.2ms inference, 3.0ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss830_png.rf.c8684a6a7e69bd43d4d35d54f2004fd7.jpg: 640x640 1 mask_weared_incorrect, 1 with_mask, 37.2ms\n",
+            "Speed: 4.8ms preprocess, 37.2ms inference, 6.1ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss761_png.rf.666e2aaecaf296dc7fe39031d857300a.jpg: 640x640 1 mask_weared_incorrect, 1 with_mask, 37.2ms\n",
+            "Speed: 2.0ms preprocess, 37.2ms inference, 2.9ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss751_png.rf.dad3bdfd78335be99b02ca0f7f0a6679.jpg: 640x640 4 with_masks, 1 without_mask, 37.1ms\n",
+            "Speed: 1.8ms preprocess, 37.1ms inference, 2.8ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss748_png.rf.75b65aa87d1ab4b31a47b7e3f80a43c3.jpg: 640x640 1 mask_weared_incorrect, 37.2ms\n",
+            "Speed: 1.8ms preprocess, 37.2ms inference, 2.7ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss658_png.rf.18a299a86c94f8a6784af81f2f6b6c89.jpg: 640x640 1 mask_weared_incorrect, 37.2ms\n",
+            "Speed: 1.8ms preprocess, 37.2ms inference, 2.7ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss65_png.rf.f3dacea8ddea2ac8019c39c83bcec5c4.jpg: 640x640 2 with_masks, 1 without_mask, 37.2ms\n",
+            "Speed: 2.0ms preprocess, 37.2ms inference, 2.9ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss662_png.rf.0dec50b3c2f682da13df8167851159b8.jpg: 640x640 4 with_masks, 37.2ms\n",
+            "Speed: 1.8ms preprocess, 37.2ms inference, 3.0ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n",
+            "      51/80      9.85G     0.8893     0.4496      1.017        135        640: 100%|██████████| 106/106 [01:00<00:00,  1.76it/s]\n",
+            "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100%|██████████| 6/6 [00:02<00:00,  2.22it/s]\n",
+            "                   all        161        861      0.875      0.763      0.812      0.525\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss664_png.rf.d7257f69f379e30582c9d5854e4bb093.jpg: 640x640 1 with_mask, 50.9ms\n",
+            "Speed: 7.3ms preprocess, 50.9ms inference, 2.7ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss674_png.rf.7848cd9439fa5dc0f5b03471912cdd27.jpg: 640x640 18 with_masks, 1 without_mask, 37.3ms\n",
+            "Speed: 4.9ms preprocess, 37.3ms inference, 3.8ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss680_png.rf.6430e43e329f2bd17482dab5d188875a.jpg: 640x640 4 mask_weared_incorrects, 9 with_masks, 2 without_masks, 37.1ms\n",
+            "Speed: 1.8ms preprocess, 37.1ms inference, 3.4ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss691_png.rf.68076bbedb2a9c8ce1c37ba0bc259d8c.jpg: 640x640 14 with_masks, 37.2ms\n",
+            "Speed: 1.8ms preprocess, 37.2ms inference, 2.8ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss694_png.rf.92b3468ed6b2d74d6e8e47c151e871a0.jpg: 640x640 5 with_masks, 37.3ms\n",
+            "Speed: 1.8ms preprocess, 37.3ms inference, 2.7ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss708_png.rf.0b01c6531d4980ea30cfde314a37ac52.jpg: 640x640 4 with_masks, 37.2ms\n",
+            "Speed: 1.9ms preprocess, 37.2ms inference, 3.6ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss714_png.rf.c59ce90ae182b29cc037c99b47028dd2.jpg: 640x640 4 with_masks, 37.1ms\n",
+            "Speed: 1.8ms preprocess, 37.1ms inference, 2.8ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss723_png.rf.4f8f04c5a74149652aaa8862ac9acb2a.jpg: 640x640 8 with_masks, 7 without_masks, 37.1ms\n",
+            "Speed: 1.8ms preprocess, 37.1ms inference, 2.8ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss725_png.rf.24ef1eeec5e346d219ce1633e649949c.jpg: 640x640 2 with_masks, 37.2ms\n",
+            "Speed: 1.9ms preprocess, 37.2ms inference, 3.1ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss72_png.rf.b94af68c76d704d083fc9720d480ef93.jpg: 640x640 1 without_mask, 37.2ms\n",
+            "Speed: 1.7ms preprocess, 37.2ms inference, 2.7ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss733_png.rf.bde25a6afb7d3fef880a5c9723c5c30d.jpg: 640x640 1 with_mask, 37.2ms\n",
+            "Speed: 1.8ms preprocess, 37.2ms inference, 2.8ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss73_png.rf.4f856521249c200a0dac653cddd51e50.jpg: 640x640 3 with_masks, 37.6ms\n",
+            "Speed: 3.9ms preprocess, 37.6ms inference, 3.0ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss744_png.rf.a8b60de6dbbfeb80df902a739b90f925.jpg: 640x640 2 with_masks, 1 without_mask, 37.2ms\n",
+            "Speed: 1.8ms preprocess, 37.2ms inference, 2.8ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss747_png.rf.09f39fbe610327e3092119f0e0a091ff.jpg: 640x640 1 with_mask, 37.2ms\n",
+            "Speed: 1.8ms preprocess, 37.2ms inference, 2.7ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss471_png.rf.c52f488eaed280f80c7d3e439c0c4e2a.jpg: 640x640 5 with_masks, 2 without_masks, 37.1ms\n",
+            "Speed: 1.9ms preprocess, 37.1ms inference, 3.0ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss89_png.rf.0459d0e0116e154559a89c1975734728.jpg: 640x640 42 with_masks, 2 without_masks, 37.2ms\n",
+            "Speed: 1.9ms preprocess, 37.2ms inference, 2.9ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss470_png.rf.3fca085941c9a6dbd4e79ea151f97079.jpg: 640x640 5 with_masks, 37.2ms\n",
+            "Speed: 1.8ms preprocess, 37.2ms inference, 2.8ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss461_png.rf.6316f0f312cd4c8c93c77f83f5484af9.jpg: 640x640 8 with_masks, 37.1ms\n",
+            "Speed: 1.7ms preprocess, 37.1ms inference, 4.2ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss230_png.rf.1fe3136ab2b6bffc7cd0b6e65101870c.jpg: 640x640 5 with_masks, 37.2ms\n",
+            "Speed: 1.8ms preprocess, 37.2ms inference, 3.3ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss236_png.rf.ea526bb945fec0e07973f2cd052ef688.jpg: 640x640 1 without_mask, 37.2ms\n",
+            "Speed: 2.0ms preprocess, 37.2ms inference, 3.1ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss241_png.rf.01c103b7f1b42f6eaaa3f4c67d5e063a.jpg: 640x640 1 with_mask, 37.1ms\n",
+            "Speed: 1.9ms preprocess, 37.1ms inference, 2.2ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss242_png.rf.048ddfefd131055beb8263c92bbb62a8.jpg: 640x640 1 with_mask, 37.1ms\n",
+            "Speed: 2.7ms preprocess, 37.1ms inference, 2.2ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss244_png.rf.f9240dd571e5670cad3b769290bbd680.jpg: 640x640 1 with_mask, 3 without_masks, 37.2ms\n",
+            "Speed: 1.9ms preprocess, 37.2ms inference, 2.2ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss247_png.rf.f67e30adf66e59df979a1db74326bd5b.jpg: 640x640 14 with_masks, 37.4ms\n",
+            "Speed: 1.9ms preprocess, 37.4ms inference, 2.2ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss248_png.rf.c19d9460b893693e4b637a1f7df7008a.jpg: 640x640 1 without_mask, 37.2ms\n",
+            "Speed: 2.0ms preprocess, 37.2ms inference, 2.1ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss229_png.rf.45ba617a90c78bc0e8e547bffedbe3c3.jpg: 640x640 15 with_masks, 37.3ms\n",
+            "Speed: 2.9ms preprocess, 37.3ms inference, 2.2ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss253_png.rf.93b13ca348adf361296ed659d6acfe75.jpg: 640x640 1 mask_weared_incorrect, 7 with_masks, 4 without_masks, 37.2ms\n",
+            "Speed: 1.9ms preprocess, 37.2ms inference, 2.2ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss264_png.rf.7018fdf357ffc35189a710fdfc752b52.jpg: 640x640 8 with_masks, 37.2ms\n",
+            "Speed: 1.8ms preprocess, 37.2ms inference, 2.1ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss271_png.rf.cc2239f13f1ebcc7519a1b37fc36376a.jpg: 640x640 1 with_mask, 37.2ms\n",
+            "Speed: 2.2ms preprocess, 37.2ms inference, 2.0ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss277_png.rf.12d1ae22a19b53135a7172821eaf2559.jpg: 640x640 8 with_masks, 37.1ms\n",
+            "Speed: 1.8ms preprocess, 37.1ms inference, 2.1ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss282_png.rf.32d06bf0012896891f681325fa56166d.jpg: 640x640 10 with_masks, 2 without_masks, 37.2ms\n",
+            "Speed: 1.8ms preprocess, 37.2ms inference, 2.1ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss289_png.rf.fee0ba4040ee03de9c67793e8127c627.jpg: 640x640 2 without_masks, 37.2ms\n",
+            "Speed: 2.6ms preprocess, 37.2ms inference, 2.1ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n",
+            "      52/80      9.87G     0.8786     0.4452      1.011        154        640: 100%|██████████| 106/106 [01:04<00:00,  1.65it/s]\n",
+            "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100%|██████████| 6/6 [00:03<00:00,  1.70it/s]\n",
+            "                   all        161        861      0.829      0.775      0.825      0.526\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss301_png.rf.79b160619414ca6a470bd5ea8b30ef4a.jpg: 640x640 19 with_masks, 1 without_mask, 65.3ms\n",
+            "Speed: 1.8ms preprocess, 65.3ms inference, 3.0ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss303_png.rf.f00ae35b4058b933e066d1d2a4d88c17.jpg: 640x640 2 with_masks, 38.5ms\n",
+            "Speed: 1.9ms preprocess, 38.5ms inference, 2.9ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss258_png.rf.fc7b4f2f14e1d199dce55985695d1120.jpg: 640x640 2 with_masks, 37.8ms\n",
+            "Speed: 6.6ms preprocess, 37.8ms inference, 2.6ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss304_png.rf.9df48cf93de57fa41d0a2b59de78a62c.jpg: 640x640 2 with_masks, 37.2ms\n",
+            "Speed: 1.7ms preprocess, 37.2ms inference, 3.9ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss224_png.rf.4539ed1dc0a709e4e01077ecf7bc2b22.jpg: 640x640 3 with_masks, 39.4ms\n",
+            "Speed: 1.8ms preprocess, 39.4ms inference, 7.9ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss20_png.rf.ca394d629ffaba1fdb13e432a79a5eb9.jpg: 640x640 2 with_masks, 37.1ms\n",
+            "Speed: 1.8ms preprocess, 37.1ms inference, 2.9ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss109_png.rf.3c26f7537566830dffb39c47f71e574e.jpg: 640x640 1 with_mask, 37.2ms\n",
+            "Speed: 1.9ms preprocess, 37.2ms inference, 2.7ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss114_png.rf.c087c8382ac2542ac89314fa0bbeb4f6.jpg: 640x640 2 with_masks, 1 without_mask, 37.1ms\n",
+            "Speed: 1.7ms preprocess, 37.1ms inference, 3.9ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss127_png.rf.1baab62c26cbf4478f2a8d99e1cf68de.jpg: 640x640 1 with_mask, 37.2ms\n",
+            "Speed: 4.1ms preprocess, 37.2ms inference, 3.1ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss146_png.rf.ec0da30308aa466d39bae79b0cc0e2bf.jpg: 640x640 3 with_masks, 37.2ms\n",
+            "Speed: 1.8ms preprocess, 37.2ms inference, 3.1ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss152_png.rf.c66bb39b29efc7503239890f834100dc.jpg: 640x640 7 with_masks, 37.2ms\n",
+            "Speed: 1.9ms preprocess, 37.2ms inference, 2.3ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss154_png.rf.7512e06f4e0bd3a2185ec1867603cc8a.jpg: 640x640 1 without_mask, 37.1ms\n",
+            "Speed: 1.7ms preprocess, 37.1ms inference, 2.1ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss168_png.rf.3b19cb741e672eef23c3f091fd204d52.jpg: 640x640 4 with_masks, 2 without_masks, 37.2ms\n",
+            "Speed: 2.0ms preprocess, 37.2ms inference, 2.1ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss217_png.rf.c4e305ead91154374bba4fc48e0e3b99.jpg: 640x640 1 without_mask, 37.1ms\n",
+            "Speed: 1.8ms preprocess, 37.1ms inference, 2.0ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss169_png.rf.49a3d702f1cd1ce83aa6cd01599e3644.jpg: 640x640 1 with_mask, 37.2ms\n",
+            "Speed: 2.1ms preprocess, 37.2ms inference, 2.1ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss174_png.rf.ba1760e663e246482b26e587332650b0.jpg: 640x640 4 with_masks, 37.2ms\n",
+            "Speed: 2.0ms preprocess, 37.2ms inference, 2.1ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss178_png.rf.2fd8857c96b9bed1982f78b55798a334.jpg: 640x640 1 mask_weared_incorrect, 2 with_masks, 1 without_mask, 37.1ms\n",
+            "Speed: 2.5ms preprocess, 37.1ms inference, 2.1ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss194_png.rf.77ed2eca9fe5235cf2496449dd156996.jpg: 640x640 2 with_masks, 37.1ms\n",
+            "Speed: 1.7ms preprocess, 37.1ms inference, 2.4ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss197_png.rf.cd0c6b120a0fae906bb417f825daf6a1.jpg: 640x640 3 with_masks, 37.2ms\n",
+            "Speed: 2.2ms preprocess, 37.2ms inference, 2.4ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss1_png.rf.e41f0052ad0e49cab0887d6e50e5a7eb.jpg: 640x640 5 with_masks, 1 without_mask, 37.4ms\n",
+            "Speed: 2.4ms preprocess, 37.4ms inference, 2.1ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss203_png.rf.eba7307a461c6b2098593e82d2cccecc.jpg: 640x640 4 with_masks, 37.8ms\n",
+            "Speed: 1.8ms preprocess, 37.8ms inference, 2.1ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss206_png.rf.68794173883f5ae26e2382a3087aac0b.jpg: 640x640 7 with_masks, 1 without_mask, 37.2ms\n",
+            "Speed: 2.0ms preprocess, 37.2ms inference, 2.1ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss172_png.rf.13bb93a8bf5266e0d73bab43f62e0376.jpg: 640x640 1 without_mask, 37.1ms\n",
+            "Speed: 2.1ms preprocess, 37.1ms inference, 2.1ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss306_png.rf.52a38aff8eebcfb7d90d0c7cac38fdec.jpg: 640x640 1 with_mask, 37.3ms\n",
+            "Speed: 2.5ms preprocess, 37.3ms inference, 2.0ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss307_png.rf.93b21e5a88a625f2a9284ff6253bd417.jpg: 640x640 1 mask_weared_incorrect, 1 with_mask, 2 without_masks, 37.1ms\n",
+            "Speed: 2.3ms preprocess, 37.1ms inference, 2.1ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss308_png.rf.61a249cc68e67a9cf66c2393f61080f2.jpg: 640x640 3 with_masks, 37.1ms\n",
+            "Speed: 1.7ms preprocess, 37.1ms inference, 2.4ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss402_png.rf.adb70e16aac43aa519466a4364f99311.jpg: 640x640 1 without_mask, 37.2ms\n",
+            "Speed: 1.8ms preprocess, 37.2ms inference, 2.2ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss408_png.rf.bb077fd8dd6090c8f22b2dfe4fb0b2dc.jpg: 640x640 7 with_masks, 2 without_masks, 37.2ms\n",
+            "Speed: 1.8ms preprocess, 37.2ms inference, 2.3ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss409_png.rf.a1da634820d49e7be38ce59f5f5887bb.jpg: 640x640 1 with_mask, 37.2ms\n",
+            "Speed: 4.0ms preprocess, 37.2ms inference, 2.2ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss410_png.rf.eaad04d3f7e7468f6a0a3d017306d6da.jpg: 640x640 1 mask_weared_incorrect, 23 with_masks, 37.1ms\n",
+            "Speed: 1.6ms preprocess, 37.1ms inference, 2.1ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss418_png.rf.432d10d262677cb69e95be55ca0c9125.jpg: 640x640 2 with_masks, 1 without_mask, 37.3ms\n",
+            "Speed: 2.0ms preprocess, 37.3ms inference, 2.2ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss421_png.rf.7ecb66f6ba285fd631717a3635a7dd71.jpg: 640x640 5 with_masks, 37.4ms\n",
+            "Speed: 2.0ms preprocess, 37.4ms inference, 2.1ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n",
+            "      53/80      9.99G     0.8738     0.4471      1.004        112        640: 100%|██████████| 106/106 [01:00<00:00,  1.74it/s]\n",
+            "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100%|██████████| 6/6 [00:02<00:00,  2.19it/s]\n",
+            "                   all        161        861      0.824       0.78      0.823      0.532\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss425_png.rf.b69c6da9a6c99fd8edfdad09f10582d2.jpg: 640x640 1 with_mask, 48.8ms\n",
+            "Speed: 2.2ms preprocess, 48.8ms inference, 2.5ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss400_png.rf.63c84ce5e3e0391c9509f77d2244755c.jpg: 640x640 5 with_masks, 37.3ms\n",
+            "Speed: 1.9ms preprocess, 37.3ms inference, 3.1ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss429_png.rf.0f9bc0b4f072650f40e985eefdce87df.jpg: 640x640 5 with_masks, 37.4ms\n",
+            "Speed: 2.8ms preprocess, 37.4ms inference, 2.2ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss438_png.rf.85978160d8cedb7d56a26e0d06e41f87.jpg: 640x640 4 with_masks, 37.1ms\n",
+            "Speed: 1.7ms preprocess, 37.1ms inference, 2.1ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss440_png.rf.641564d43589f6344bacc5d05d51da53.jpg: 640x640 1 mask_weared_incorrect, 10 with_masks, 37.1ms\n",
+            "Speed: 2.3ms preprocess, 37.1ms inference, 2.2ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss44_png.rf.b6697a646548922305672e657697750b.jpg: 640x640 4 with_masks, 1 without_mask, 37.2ms\n",
+            "Speed: 1.8ms preprocess, 37.2ms inference, 2.4ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss450_png.rf.8f5e0ff6c7228f1180f985685beb20d5.jpg: 640x640 4 with_masks, 37.2ms\n",
+            "Speed: 1.8ms preprocess, 37.2ms inference, 2.4ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss457_png.rf.60b3bf773c197a83826aae38a0cf2387.jpg: 640x640 5 with_masks, 1 without_mask, 37.6ms\n",
+            "Speed: 1.8ms preprocess, 37.6ms inference, 2.1ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss459_png.rf.73bd4ff56e948804a4c7d5cc9e2f98ef.jpg: 640x640 1 with_mask, 1 without_mask, 38.6ms\n",
+            "Speed: 1.8ms preprocess, 38.6ms inference, 3.4ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss45_png.rf.3b160c8afb75253926e1abf7b4972504.jpg: 640x640 4 with_masks, 2 without_masks, 37.2ms\n",
+            "Speed: 2.0ms preprocess, 37.2ms inference, 3.1ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss431_png.rf.c5e66fbd5f544edca4f20973ce5ecf08.jpg: 640x640 1 mask_weared_incorrect, 19 with_masks, 37.1ms\n",
+            "Speed: 1.8ms preprocess, 37.1ms inference, 2.9ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss395_png.rf.d0fd9e7ac741d7df48a86b7f291e9b49.jpg: 640x640 1 with_mask, 37.2ms\n",
+            "Speed: 2.0ms preprocess, 37.2ms inference, 2.5ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss389_png.rf.11956fb49c814dab304f0006b9075f71.jpg: 640x640 1 mask_weared_incorrect, 12 with_masks, 2 without_masks, 37.1ms\n",
+            "Speed: 1.8ms preprocess, 37.1ms inference, 2.7ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss388_png.rf.4847bd339895b2496b21a16876aca440.jpg: 640x640 1 mask_weared_incorrect, 12 with_masks, 8 without_masks, 37.2ms\n",
+            "Speed: 1.9ms preprocess, 37.2ms inference, 3.0ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss311_png.rf.8d4e3cc30ab76d6699d7f220a26286dd.jpg: 640x640 5 with_masks, 37.3ms\n",
+            "Speed: 2.1ms preprocess, 37.3ms inference, 3.1ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss313_png.rf.0d2ede745cca1bbc73883747763be4cb.jpg: 640x640 2 with_masks, 37.2ms\n",
+            "Speed: 1.9ms preprocess, 37.2ms inference, 2.8ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss315_png.rf.bdcb0e2cde8b888d72849bbf232bc644.jpg: 640x640 2 with_masks, 37.1ms\n",
+            "Speed: 1.8ms preprocess, 37.1ms inference, 2.8ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss31_png.rf.f71dabc8b32a5181ae4a7ec0724d169e.jpg: 640x640 2 with_masks, 37.2ms\n",
+            "Speed: 2.0ms preprocess, 37.2ms inference, 2.8ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss321_png.rf.d5ca9ccecbb235c5551003b177cd1d46.jpg: 640x640 1 mask_weared_incorrect, 1 with_mask, 1 without_mask, 37.2ms\n",
+            "Speed: 1.9ms preprocess, 37.2ms inference, 3.0ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss330_png.rf.ca2fe4eca45ae4b2bc6bb9fde6d39dff.jpg: 640x640 4 with_masks, 37.2ms\n",
+            "Speed: 1.7ms preprocess, 37.2ms inference, 3.0ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss338_png.rf.669c284dd81181d71654743a3ca9aeb3.jpg: 640x640 10 with_masks, 37.2ms\n",
+            "Speed: 1.8ms preprocess, 37.2ms inference, 2.9ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss339_png.rf.d26efdd756cada62599cd227994bbf56.jpg: 640x640 1 with_mask, 37.1ms\n",
+            "Speed: 1.8ms preprocess, 37.1ms inference, 2.7ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss343_png.rf.1c5c7bbcb828a1cf9d4d2584972083cb.jpg: 640x640 1 without_mask, 37.1ms\n",
+            "Speed: 1.7ms preprocess, 37.1ms inference, 2.6ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss351_png.rf.15436d1eb7080d7bae2e79d554a4d3cb.jpg: 640x640 1 with_mask, 37.2ms\n",
+            "Speed: 2.3ms preprocess, 37.2ms inference, 2.7ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss364_png.rf.74e470c60f166ba4ec1a268b153fa240.jpg: 640x640 3 with_masks, 37.2ms\n",
+            "Speed: 1.8ms preprocess, 37.2ms inference, 2.9ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss366_png.rf.433ea8f6b4fcab0d951b52116611c1be.jpg: 640x640 2 with_masks, 39.9ms\n",
+            "Speed: 1.9ms preprocess, 39.9ms inference, 2.8ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss368_png.rf.1d14fe4224d1b152c5e272d889fe3d45.jpg: 640x640 9 with_masks, 37.2ms\n",
+            "Speed: 1.8ms preprocess, 37.2ms inference, 3.1ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss374_png.rf.b51c420d86fc3a474ed557b5a230b51e.jpg: 640x640 4 with_masks, 1 without_mask, 37.2ms\n",
+            "Speed: 1.7ms preprocess, 37.2ms inference, 2.8ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss376_png.rf.ca418b2ffccc242892a1ab14657e8349.jpg: 640x640 7 with_masks, 37.1ms\n",
+            "Speed: 1.8ms preprocess, 37.1ms inference, 2.9ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss37_png.rf.60ce2ff44ae089a01d8f07ff2e0f00ad.jpg: 640x640 1 with_mask, 37.2ms\n",
+            "Speed: 1.8ms preprocess, 37.2ms inference, 2.8ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss387_png.rf.6d027b3075e33a4414cc245ec7435fcc.jpg: 640x640 1 mask_weared_incorrect, 3 with_masks, 1 without_mask, 37.1ms\n",
+            "Speed: 1.8ms preprocess, 37.1ms inference, 2.9ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss464_png.rf.b7d07a0f6aabc271e6bfbe039246786b.jpg: 640x640 8 with_masks, 37.1ms\n",
+            "Speed: 1.8ms preprocess, 37.1ms inference, 2.9ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n",
+            "      54/80        10G     0.8735     0.4425      1.002        120        640: 100%|██████████| 106/106 [01:05<00:00,  1.63it/s]\n",
+            "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100%|██████████| 6/6 [00:03<00:00,  1.60it/s]\n",
+            "                   all        161        861      0.867      0.773      0.826      0.542\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss90_png.rf.bb3401c96e9aba7db607a9a5ac8d8f51.jpg: 640x640 11 with_masks, 42.7ms\n",
+            "Speed: 8.2ms preprocess, 42.7ms inference, 2.8ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n",
+            "      55/80        10G     0.8592     0.4363     0.9941         89        640: 100%|██████████| 106/106 [01:08<00:00,  1.55it/s]\n",
+            "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100%|██████████| 6/6 [00:02<00:00,  2.08it/s]\n",
+            "                   all        161        861      0.829      0.807      0.816      0.531\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss107_png.rf.285757ad3a789f0d69380282b3bdb846.jpg: 640x640 1 with_mask, 48.0ms\n",
+            "Speed: 7.0ms preprocess, 48.0ms inference, 3.2ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss569_png.rf.245d020288f15a704c2742a49eb1ca63.jpg: 640x640 1 with_mask, 37.2ms\n",
+            "Speed: 2.6ms preprocess, 37.2ms inference, 2.8ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss56_png.rf.ffec370c63bb3ee301d05f9ce072e3fa.jpg: 640x640 1 with_mask, 37.1ms\n",
+            "Speed: 2.1ms preprocess, 37.1ms inference, 2.1ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss577_png.rf.99d8deb18d344f24bb95f02394713470.jpg: 640x640 13 with_masks, 37.1ms\n",
+            "Speed: 1.8ms preprocess, 37.1ms inference, 2.2ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss585_png.rf.16b40d54481e86f0a1434d30bc6d9c64.jpg: 640x640 4 with_masks, 2 without_masks, 37.2ms\n",
+            "Speed: 8.1ms preprocess, 37.2ms inference, 2.2ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss595_png.rf.f3a260412881f24273c64d6bd6e1966b.jpg: 640x640 6 with_masks, 37.1ms\n",
+            "Speed: 2.2ms preprocess, 37.1ms inference, 2.2ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss596_png.rf.9bf29752ebe873bc099ff9b64ddef6d1.jpg: 640x640 1 with_mask, 37.3ms\n",
+            "Speed: 2.5ms preprocess, 37.3ms inference, 2.2ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss603_png.rf.0d06c5299fd1cf3136e68b97a2afa4fd.jpg: 640x640 104 with_masks, 15 without_masks, 37.2ms\n",
+            "Speed: 1.9ms preprocess, 37.2ms inference, 2.7ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss568_png.rf.a4d4a4e139954b5194617ef2e9ffc81c.jpg: 640x640 1 with_mask, 37.2ms\n",
+            "Speed: 2.0ms preprocess, 37.2ms inference, 2.5ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss608_png.rf.4806b67fedacda192a8448bcf3b53d64.jpg: 640x640 1 with_mask, 37.4ms\n",
+            "Speed: 1.9ms preprocess, 37.4ms inference, 2.3ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss623_png.rf.19a2c6b529d5478510934f467949c887.jpg: 640x640 1 mask_weared_incorrect, 21 with_masks, 3 without_masks, 37.2ms\n",
+            "Speed: 1.9ms preprocess, 37.2ms inference, 2.9ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss626_png.rf.4a2f1a57a893fdcef400930251142f52.jpg: 640x640 1 with_mask, 37.2ms\n",
+            "Speed: 2.1ms preprocess, 37.2ms inference, 2.3ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss627_png.rf.81b096f6b0f9e897cc64f59880e630e0.jpg: 640x640 3 mask_weared_incorrects, 6 with_masks, 8 without_masks, 37.1ms\n",
+            "Speed: 2.4ms preprocess, 37.1ms inference, 2.2ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss630_png.rf.d1ecd7de587fb5c2571563293babff62.jpg: 640x640 1 with_mask, 37.1ms\n",
+            "Speed: 3.1ms preprocess, 37.1ms inference, 2.1ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss631_png.rf.418be1a60a0224818dc54e0d2281c6f4.jpg: 640x640 11 with_masks, 37.2ms\n",
+            "Speed: 3.1ms preprocess, 37.2ms inference, 3.3ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss636_png.rf.e6889a20be3cb52fa81b195fdef01b58.jpg: 640x640 6 with_masks, 2 without_masks, 37.3ms\n",
+            "Speed: 2.0ms preprocess, 37.3ms inference, 2.2ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss645_png.rf.d577b2fbdae8c09e7cb396b9c14f18d7.jpg: 640x640 1 with_mask, 37.1ms\n",
+            "Speed: 1.9ms preprocess, 37.1ms inference, 2.3ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss619_png.rf.bc1dcbfae2f9104ce082afe801399f54.jpg: 640x640 2 with_masks, 1 without_mask, 37.2ms\n",
+            "Speed: 1.8ms preprocess, 37.2ms inference, 2.2ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss646_png.rf.a434ddc2569b34a89bbb07a259996497.jpg: 640x640 1 with_mask, 37.1ms\n",
+            "Speed: 2.7ms preprocess, 37.1ms inference, 2.1ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss563_png.rf.dc088c07f08e5fba01fd6bddeceb27e2.jpg: 640x640 1 with_mask, 37.1ms\n",
+            "Speed: 1.9ms preprocess, 37.1ms inference, 2.2ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss554_png.rf.ba664c8fdc34b11faff3a128d06dbe9a.jpg: 640x640 4 with_masks, 37.2ms\n",
+            "Speed: 1.8ms preprocess, 37.2ms inference, 2.4ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss473_png.rf.6de35811442245ad013a2676e2bcaa0a.jpg: 640x640 3 with_masks, 1 without_mask, 37.2ms\n",
+            "Speed: 1.9ms preprocess, 37.2ms inference, 2.4ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss477_png.rf.0e319d347398d08b8a52fb6a152de44e.jpg: 640x640 7 with_masks, 7 without_masks, 37.1ms\n",
+            "Speed: 2.1ms preprocess, 37.1ms inference, 2.2ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss481_png.rf.6682292ffe5179b26d46c8515797446e.jpg: 640x640 8 with_masks, 38.0ms\n",
+            "Speed: 1.9ms preprocess, 38.0ms inference, 2.2ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss483_png.rf.4c059c2770f996153e3487a7f52f771c.jpg: 640x640 3 with_masks, 1 without_mask, 37.1ms\n",
+            "Speed: 2.4ms preprocess, 37.1ms inference, 2.2ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss484_png.rf.a57bfdb112b858aa9ed93bf36306ac61.jpg: 640x640 1 mask_weared_incorrect, 1 with_mask, 37.1ms\n",
+            "Speed: 1.9ms preprocess, 37.1ms inference, 2.6ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss498_png.rf.095899d089070e7a5a7697113b108f8a.jpg: 640x640 10 with_masks, 2 without_masks, 37.2ms\n",
+            "Speed: 1.9ms preprocess, 37.2ms inference, 2.3ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss499_png.rf.611bdf8f03aea1d86028c7b5d7d494ec.jpg: 640x640 1 with_mask, 1 without_mask, 37.2ms\n",
+            "Speed: 1.8ms preprocess, 37.2ms inference, 2.7ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss560_png.rf.bc8e65e2733e0f7b723391d33c380fe0.jpg: 640x640 1 with_mask, 37.2ms\n",
+            "Speed: 1.9ms preprocess, 37.2ms inference, 2.3ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss49_png.rf.d4077078d124ff3d3d699fc94bd06150.jpg: 640x640 7 with_masks, 3 without_masks, 37.2ms\n",
+            "Speed: 2.2ms preprocess, 37.2ms inference, 2.2ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss509_png.rf.6470c0dd2a6a4b05117cca6aad267087.jpg: 640x640 2 with_masks, 37.2ms\n",
+            "Speed: 1.9ms preprocess, 37.2ms inference, 2.3ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss512_png.rf.8dbd72e69a164fdcdad2e220bcd0c467.jpg: 640x640 7 with_masks, 37.2ms\n",
+            "Speed: 2.0ms preprocess, 37.2ms inference, 2.2ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n",
+            "      56/80      10.1G     0.8384     0.4295     0.9918         90        640: 100%|██████████| 106/106 [01:11<00:00,  1.49it/s]\n",
+            "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100%|██████████| 6/6 [00:03<00:00,  1.83it/s]\n",
+            "                   all        161        861      0.893      0.781      0.841      0.551\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss515_png.rf.9b8d660e9368ee9ccfeb977e609167ed.jpg: 640x640 1 with_mask, 38.6ms\n",
+            "Speed: 1.9ms preprocess, 38.6ms inference, 2.7ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss529_png.rf.6ae323861cb838fc945c80ee31070c4c.jpg: 640x640 7 with_masks, 1 without_mask, 37.2ms\n",
+            "Speed: 1.9ms preprocess, 37.2ms inference, 2.2ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss532_png.rf.03aa559343f932efbfa3753190291fa7.jpg: 640x640 1 with_mask, 37.1ms\n",
+            "Speed: 1.8ms preprocess, 37.1ms inference, 2.0ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss537_png.rf.f22f4997ea93880ebfa2cb19a893caad.jpg: 640x640 1 without_mask, 37.2ms\n",
+            "Speed: 1.8ms preprocess, 37.2ms inference, 2.4ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss551_png.rf.010062fb38326dac49ecca8d9322953f.jpg: 640x640 5 with_masks, 37.2ms\n",
+            "Speed: 2.7ms preprocess, 37.2ms inference, 2.2ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss501_png.rf.125122fa5a318ec6d0e27d632764f840.jpg: 640x640 7 with_masks, 37.1ms\n",
+            "Speed: 1.8ms preprocess, 37.1ms inference, 2.1ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss649_png.rf.5540865cd8826940d55b3b48c045183c.jpg: 640x640 1 with_mask, 37.2ms\n",
+            "Speed: 2.2ms preprocess, 37.2ms inference, 2.3ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss64_png.rf.4b8ca34d17365fb62029fdbee94cb0aa.jpg: 640x640 3 with_masks, 37.3ms\n",
+            "Speed: 2.5ms preprocess, 37.3ms inference, 2.2ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss653_png.rf.22cf40d34bad20f7f9b542b6a0a89e2f.jpg: 640x640 2 with_masks, 37.2ms\n",
+            "Speed: 1.8ms preprocess, 37.2ms inference, 2.2ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss787_png.rf.a7e026e8082789734a57252cf6df81e5.jpg: 640x640 8 with_masks, 2 without_masks, 37.2ms\n",
+            "Speed: 2.1ms preprocess, 37.2ms inference, 2.2ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss793_png.rf.dd2be948b6231ceb68a6af8371f2329c.jpg: 640x640 1 with_mask, 37.2ms\n",
+            "Speed: 1.9ms preprocess, 37.2ms inference, 2.2ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss797_png.rf.5ead12df141e267f928b7b34c73dfb1a.jpg: 640x640 1 mask_weared_incorrect, 11 with_masks, 1 without_mask, 37.2ms\n",
+            "Speed: 2.3ms preprocess, 37.2ms inference, 2.3ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss79_png.rf.e12280d9bd602d3e52504b83921437d6.jpg: 640x640 5 with_masks, 37.2ms\n",
+            "Speed: 1.8ms preprocess, 37.2ms inference, 3.3ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss806_png.rf.504dc192775390a4b3f7d6b85bc58636.jpg: 640x640 9 with_masks, 2 without_masks, 37.3ms\n",
+            "Speed: 2.0ms preprocess, 37.3ms inference, 3.2ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss808_png.rf.b2e534caaaf701b8674add21e64fd528.jpg: 640x640 1 with_mask, 37.2ms\n",
+            "Speed: 2.0ms preprocess, 37.2ms inference, 2.6ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss822_png.rf.8601f2a416cbe3f239fde9934f5f66d2.jpg: 640x640 10 with_masks, 4 without_masks, 37.2ms\n",
+            "Speed: 1.8ms preprocess, 37.2ms inference, 2.8ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss784_png.rf.b95afb3096062e72503f25dfdaf53f52.jpg: 640x640 9 with_masks, 1 without_mask, 37.1ms\n",
+            "Speed: 1.8ms preprocess, 37.1ms inference, 2.7ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss828_png.rf.ef40e6fb83c895f7c4ca491dadbcecb1.jpg: 640x640 1 with_mask, 37.1ms\n",
+            "Speed: 1.9ms preprocess, 37.1ms inference, 2.5ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss832_png.rf.fd2d4b0fa4b62433e71f92aa8f1bc067.jpg: 640x640 1 mask_weared_incorrect, 1 without_mask, 37.2ms\n",
+            "Speed: 1.8ms preprocess, 37.2ms inference, 3.1ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss834_png.rf.c14acf559bb5531c92d3cf19a5193aa2.jpg: 640x640 5 with_masks, 37.2ms\n",
+            "Speed: 2.2ms preprocess, 37.2ms inference, 4.9ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss835_png.rf.b8a44eb8c868a51999b450873338a62a.jpg: 640x640 1 mask_weared_incorrect, 1 with_mask, 37.2ms\n",
+            "Speed: 2.1ms preprocess, 37.2ms inference, 2.9ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss840_png.rf.78c778f16a6a87f204473b70c7e735b1.jpg: 640x640 3 with_masks, 37.2ms\n",
+            "Speed: 1.9ms preprocess, 37.2ms inference, 2.9ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss844_png.rf.98f015b79733ae45cfff40da2c6eb85c.jpg: 640x640 2 with_masks, 37.2ms\n",
+            "Speed: 1.9ms preprocess, 37.2ms inference, 3.0ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss846_png.rf.f600f86418cd50b99d7116344abfe0df.jpg: 640x640 3 with_masks, 37.2ms\n",
+            "Speed: 1.8ms preprocess, 37.2ms inference, 2.9ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss848_png.rf.a1793122f2a5ab2b5a3d7be92157ea6b.jpg: 640x640 3 with_masks, 37.2ms\n",
+            "Speed: 1.8ms preprocess, 37.2ms inference, 4.8ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss830_png.rf.c8684a6a7e69bd43d4d35d54f2004fd7.jpg: 640x640 1 mask_weared_incorrect, 1 with_mask, 37.2ms\n",
+            "Speed: 1.9ms preprocess, 37.2ms inference, 3.0ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss761_png.rf.666e2aaecaf296dc7fe39031d857300a.jpg: 640x640 2 mask_weared_incorrects, 37.2ms\n",
+            "Speed: 6.9ms preprocess, 37.2ms inference, 2.9ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss751_png.rf.dad3bdfd78335be99b02ca0f7f0a6679.jpg: 640x640 6 with_masks, 1 without_mask, 37.6ms\n",
+            "Speed: 1.9ms preprocess, 37.6ms inference, 3.2ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss748_png.rf.75b65aa87d1ab4b31a47b7e3f80a43c3.jpg: 640x640 1 mask_weared_incorrect, 1 without_mask, 37.1ms\n",
+            "Speed: 2.0ms preprocess, 37.1ms inference, 2.9ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss658_png.rf.18a299a86c94f8a6784af81f2f6b6c89.jpg: 640x640 1 mask_weared_incorrect, 37.2ms\n",
+            "Speed: 1.9ms preprocess, 37.2ms inference, 5.6ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss65_png.rf.f3dacea8ddea2ac8019c39c83bcec5c4.jpg: 640x640 2 with_masks, 1 without_mask, 37.2ms\n",
+            "Speed: 1.9ms preprocess, 37.2ms inference, 2.8ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss662_png.rf.0dec50b3c2f682da13df8167851159b8.jpg: 640x640 4 with_masks, 37.2ms\n",
+            "Speed: 1.9ms preprocess, 37.2ms inference, 2.9ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n",
+            "      57/80      10.2G     0.8435     0.4276      0.991         72        640: 100%|██████████| 106/106 [01:09<00:00,  1.53it/s]\n",
+            "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100%|██████████| 6/6 [00:03<00:00,  1.79it/s]\n",
+            "                   all        161        861      0.856      0.799      0.813      0.525\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss664_png.rf.d7257f69f379e30582c9d5854e4bb093.jpg: 640x640 2 with_masks, 40.5ms\n",
+            "Speed: 2.1ms preprocess, 40.5ms inference, 2.9ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss674_png.rf.7848cd9439fa5dc0f5b03471912cdd27.jpg: 640x640 19 with_masks, 1 without_mask, 39.4ms\n",
+            "Speed: 2.5ms preprocess, 39.4ms inference, 3.6ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss680_png.rf.6430e43e329f2bd17482dab5d188875a.jpg: 640x640 3 mask_weared_incorrects, 8 with_masks, 2 without_masks, 38.5ms\n",
+            "Speed: 2.5ms preprocess, 38.5ms inference, 6.2ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss691_png.rf.68076bbedb2a9c8ce1c37ba0bc259d8c.jpg: 640x640 9 with_masks, 37.2ms\n",
+            "Speed: 1.8ms preprocess, 37.2ms inference, 2.4ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss694_png.rf.92b3468ed6b2d74d6e8e47c151e871a0.jpg: 640x640 6 with_masks, 37.3ms\n",
+            "Speed: 2.2ms preprocess, 37.3ms inference, 2.3ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss708_png.rf.0b01c6531d4980ea30cfde314a37ac52.jpg: 640x640 3 with_masks, 37.2ms\n",
+            "Speed: 1.8ms preprocess, 37.2ms inference, 2.2ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss714_png.rf.c59ce90ae182b29cc037c99b47028dd2.jpg: 640x640 4 with_masks, 37.2ms\n",
+            "Speed: 1.8ms preprocess, 37.2ms inference, 2.1ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss723_png.rf.4f8f04c5a74149652aaa8862ac9acb2a.jpg: 640x640 9 with_masks, 6 without_masks, 37.2ms\n",
+            "Speed: 2.1ms preprocess, 37.2ms inference, 2.4ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss725_png.rf.24ef1eeec5e346d219ce1633e649949c.jpg: 640x640 1 with_mask, 37.2ms\n",
+            "Speed: 1.8ms preprocess, 37.2ms inference, 2.7ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss72_png.rf.b94af68c76d704d083fc9720d480ef93.jpg: 640x640 1 without_mask, 37.2ms\n",
+            "Speed: 1.8ms preprocess, 37.2ms inference, 2.1ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss733_png.rf.bde25a6afb7d3fef880a5c9723c5c30d.jpg: 640x640 1 with_mask, 37.2ms\n",
+            "Speed: 2.6ms preprocess, 37.2ms inference, 2.1ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss73_png.rf.4f856521249c200a0dac653cddd51e50.jpg: 640x640 3 with_masks, 37.2ms\n",
+            "Speed: 1.7ms preprocess, 37.2ms inference, 2.2ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss744_png.rf.a8b60de6dbbfeb80df902a739b90f925.jpg: 640x640 2 with_masks, 2 without_masks, 37.2ms\n",
+            "Speed: 1.9ms preprocess, 37.2ms inference, 2.8ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss747_png.rf.09f39fbe610327e3092119f0e0a091ff.jpg: 640x640 1 with_mask, 37.2ms\n",
+            "Speed: 2.0ms preprocess, 37.2ms inference, 2.0ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss471_png.rf.c52f488eaed280f80c7d3e439c0c4e2a.jpg: 640x640 5 with_masks, 2 without_masks, 37.2ms\n",
+            "Speed: 1.8ms preprocess, 37.2ms inference, 2.1ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss89_png.rf.0459d0e0116e154559a89c1975734728.jpg: 640x640 41 with_masks, 2 without_masks, 37.1ms\n",
+            "Speed: 1.6ms preprocess, 37.1ms inference, 2.2ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss470_png.rf.3fca085941c9a6dbd4e79ea151f97079.jpg: 640x640 6 with_masks, 37.2ms\n",
+            "Speed: 1.9ms preprocess, 37.2ms inference, 2.6ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss461_png.rf.6316f0f312cd4c8c93c77f83f5484af9.jpg: 640x640 8 with_masks, 37.2ms\n",
+            "Speed: 2.1ms preprocess, 37.2ms inference, 2.4ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss230_png.rf.1fe3136ab2b6bffc7cd0b6e65101870c.jpg: 640x640 5 with_masks, 37.2ms\n",
+            "Speed: 2.1ms preprocess, 37.2ms inference, 2.3ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss236_png.rf.ea526bb945fec0e07973f2cd052ef688.jpg: 640x640 1 without_mask, 37.2ms\n",
+            "Speed: 2.1ms preprocess, 37.2ms inference, 2.3ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss241_png.rf.01c103b7f1b42f6eaaa3f4c67d5e063a.jpg: 640x640 1 with_mask, 39.7ms\n",
+            "Speed: 2.1ms preprocess, 39.7ms inference, 2.6ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss242_png.rf.048ddfefd131055beb8263c92bbb62a8.jpg: 640x640 3 with_masks, 37.4ms\n",
+            "Speed: 2.2ms preprocess, 37.4ms inference, 2.5ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss244_png.rf.f9240dd571e5670cad3b769290bbd680.jpg: 640x640 1 with_mask, 3 without_masks, 37.1ms\n",
+            "Speed: 2.0ms preprocess, 37.1ms inference, 2.5ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss247_png.rf.f67e30adf66e59df979a1db74326bd5b.jpg: 640x640 13 with_masks, 37.1ms\n",
+            "Speed: 2.2ms preprocess, 37.1ms inference, 2.2ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss248_png.rf.c19d9460b893693e4b637a1f7df7008a.jpg: 640x640 1 without_mask, 37.2ms\n",
+            "Speed: 1.9ms preprocess, 37.2ms inference, 2.5ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss229_png.rf.45ba617a90c78bc0e8e547bffedbe3c3.jpg: 640x640 14 with_masks, 37.1ms\n",
+            "Speed: 1.9ms preprocess, 37.1ms inference, 2.2ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss253_png.rf.93b13ca348adf361296ed659d6acfe75.jpg: 640x640 1 mask_weared_incorrect, 7 with_masks, 5 without_masks, 37.2ms\n",
+            "Speed: 2.5ms preprocess, 37.2ms inference, 2.2ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss264_png.rf.7018fdf357ffc35189a710fdfc752b52.jpg: 640x640 7 with_masks, 37.2ms\n",
+            "Speed: 1.8ms preprocess, 37.2ms inference, 2.2ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss271_png.rf.cc2239f13f1ebcc7519a1b37fc36376a.jpg: 640x640 1 with_mask, 37.2ms\n",
+            "Speed: 1.9ms preprocess, 37.2ms inference, 2.0ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss277_png.rf.12d1ae22a19b53135a7172821eaf2559.jpg: 640x640 9 with_masks, 37.2ms\n",
+            "Speed: 2.1ms preprocess, 37.2ms inference, 2.1ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss282_png.rf.32d06bf0012896891f681325fa56166d.jpg: 640x640 9 with_masks, 37.2ms\n",
+            "Speed: 4.1ms preprocess, 37.2ms inference, 2.2ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss289_png.rf.fee0ba4040ee03de9c67793e8127c627.jpg: 640x640 2 without_masks, 37.2ms\n",
+            "Speed: 3.9ms preprocess, 37.2ms inference, 3.1ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n",
+            "      58/80      10.2G     0.8201     0.4239     0.9837         99        640: 100%|██████████| 106/106 [01:04<00:00,  1.64it/s]\n",
+            "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100%|██████████| 6/6 [00:02<00:00,  2.26it/s]\n",
+            "                   all        161        861      0.874      0.774      0.819      0.536\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss301_png.rf.79b160619414ca6a470bd5ea8b30ef4a.jpg: 640x640 1 mask_weared_incorrect, 18 with_masks, 2 without_masks, 38.6ms\n",
+            "Speed: 1.7ms preprocess, 38.6ms inference, 3.1ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss303_png.rf.f00ae35b4058b933e066d1d2a4d88c17.jpg: 640x640 2 with_masks, 37.2ms\n",
+            "Speed: 2.0ms preprocess, 37.2ms inference, 2.1ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss258_png.rf.fc7b4f2f14e1d199dce55985695d1120.jpg: 640x640 1 mask_weared_incorrect, 1 with_mask, 37.1ms\n",
+            "Speed: 1.9ms preprocess, 37.1ms inference, 2.1ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss304_png.rf.9df48cf93de57fa41d0a2b59de78a62c.jpg: 640x640 2 with_masks, 37.1ms\n",
+            "Speed: 2.2ms preprocess, 37.1ms inference, 2.4ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss224_png.rf.4539ed1dc0a709e4e01077ecf7bc2b22.jpg: 640x640 2 with_masks, 37.2ms\n",
+            "Speed: 2.0ms preprocess, 37.2ms inference, 2.2ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss20_png.rf.ca394d629ffaba1fdb13e432a79a5eb9.jpg: 640x640 1 with_mask, 37.1ms\n",
+            "Speed: 1.6ms preprocess, 37.1ms inference, 2.7ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss109_png.rf.3c26f7537566830dffb39c47f71e574e.jpg: 640x640 1 with_mask, 37.4ms\n",
+            "Speed: 1.9ms preprocess, 37.4ms inference, 2.0ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss114_png.rf.c087c8382ac2542ac89314fa0bbeb4f6.jpg: 640x640 1 with_mask, 1 without_mask, 37.1ms\n",
+            "Speed: 2.3ms preprocess, 37.1ms inference, 2.1ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss127_png.rf.1baab62c26cbf4478f2a8d99e1cf68de.jpg: 640x640 1 with_mask, 37.1ms\n",
+            "Speed: 1.8ms preprocess, 37.1ms inference, 2.3ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss146_png.rf.ec0da30308aa466d39bae79b0cc0e2bf.jpg: 640x640 3 with_masks, 37.2ms\n",
+            "Speed: 1.7ms preprocess, 37.2ms inference, 2.2ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss152_png.rf.c66bb39b29efc7503239890f834100dc.jpg: 640x640 7 with_masks, 37.1ms\n",
+            "Speed: 2.2ms preprocess, 37.1ms inference, 2.1ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss154_png.rf.7512e06f4e0bd3a2185ec1867603cc8a.jpg: 640x640 1 without_mask, 37.2ms\n",
+            "Speed: 3.1ms preprocess, 37.2ms inference, 2.1ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss168_png.rf.3b19cb741e672eef23c3f091fd204d52.jpg: 640x640 3 with_masks, 2 without_masks, 37.2ms\n",
+            "Speed: 1.8ms preprocess, 37.2ms inference, 2.3ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss217_png.rf.c4e305ead91154374bba4fc48e0e3b99.jpg: 640x640 1 without_mask, 37.2ms\n",
+            "Speed: 2.1ms preprocess, 37.2ms inference, 2.1ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss169_png.rf.49a3d702f1cd1ce83aa6cd01599e3644.jpg: 640x640 1 with_mask, 37.4ms\n",
+            "Speed: 1.9ms preprocess, 37.4ms inference, 2.1ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss174_png.rf.ba1760e663e246482b26e587332650b0.jpg: 640x640 4 with_masks, 37.1ms\n",
+            "Speed: 1.8ms preprocess, 37.1ms inference, 2.0ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss178_png.rf.2fd8857c96b9bed1982f78b55798a334.jpg: 640x640 2 with_masks, 1 without_mask, 37.1ms\n",
+            "Speed: 2.8ms preprocess, 37.1ms inference, 2.2ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss194_png.rf.77ed2eca9fe5235cf2496449dd156996.jpg: 640x640 2 with_masks, 37.1ms\n",
+            "Speed: 1.7ms preprocess, 37.1ms inference, 2.2ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss197_png.rf.cd0c6b120a0fae906bb417f825daf6a1.jpg: 640x640 1 with_mask, 37.2ms\n",
+            "Speed: 1.8ms preprocess, 37.2ms inference, 2.0ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss1_png.rf.e41f0052ad0e49cab0887d6e50e5a7eb.jpg: 640x640 7 with_masks, 1 without_mask, 37.1ms\n",
+            "Speed: 1.7ms preprocess, 37.1ms inference, 2.1ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss203_png.rf.eba7307a461c6b2098593e82d2cccecc.jpg: 640x640 4 with_masks, 37.2ms\n",
+            "Speed: 2.4ms preprocess, 37.2ms inference, 2.2ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss206_png.rf.68794173883f5ae26e2382a3087aac0b.jpg: 640x640 7 with_masks, 2 without_masks, 37.2ms\n",
+            "Speed: 1.8ms preprocess, 37.2ms inference, 2.3ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss172_png.rf.13bb93a8bf5266e0d73bab43f62e0376.jpg: 640x640 1 without_mask, 37.1ms\n",
+            "Speed: 1.9ms preprocess, 37.1ms inference, 2.0ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss306_png.rf.52a38aff8eebcfb7d90d0c7cac38fdec.jpg: 640x640 1 with_mask, 37.2ms\n",
+            "Speed: 1.9ms preprocess, 37.2ms inference, 2.1ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss307_png.rf.93b21e5a88a625f2a9284ff6253bd417.jpg: 640x640 1 mask_weared_incorrect, 3 with_masks, 2 without_masks, 37.2ms\n",
+            "Speed: 1.8ms preprocess, 37.2ms inference, 2.1ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss308_png.rf.61a249cc68e67a9cf66c2393f61080f2.jpg: 640x640 2 with_masks, 37.2ms\n",
+            "Speed: 1.8ms preprocess, 37.2ms inference, 2.1ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss402_png.rf.adb70e16aac43aa519466a4364f99311.jpg: 640x640 1 without_mask, 37.1ms\n",
+            "Speed: 2.6ms preprocess, 37.1ms inference, 2.0ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss408_png.rf.bb077fd8dd6090c8f22b2dfe4fb0b2dc.jpg: 640x640 8 with_masks, 2 without_masks, 37.1ms\n",
+            "Speed: 1.6ms preprocess, 37.1ms inference, 2.1ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss409_png.rf.a1da634820d49e7be38ce59f5f5887bb.jpg: 640x640 1 with_mask, 37.2ms\n",
+            "Speed: 2.3ms preprocess, 37.2ms inference, 2.0ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss410_png.rf.eaad04d3f7e7468f6a0a3d017306d6da.jpg: 640x640 1 mask_weared_incorrect, 22 with_masks, 3 without_masks, 37.1ms\n",
+            "Speed: 1.6ms preprocess, 37.1ms inference, 2.2ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss418_png.rf.432d10d262677cb69e95be55ca0c9125.jpg: 640x640 2 with_masks, 2 without_masks, 40.6ms\n",
+            "Speed: 1.9ms preprocess, 40.6ms inference, 2.1ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss421_png.rf.7ecb66f6ba285fd631717a3635a7dd71.jpg: 640x640 5 with_masks, 37.2ms\n",
+            "Speed: 1.8ms preprocess, 37.2ms inference, 2.6ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n",
+            "      59/80      10.3G     0.8283     0.4195     0.9829        104        640: 100%|██████████| 106/106 [01:01<00:00,  1.71it/s]\n",
+            "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100%|██████████| 6/6 [00:03<00:00,  1.64it/s]\n",
+            "                   all        161        861      0.856      0.786      0.829      0.536\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss425_png.rf.b69c6da9a6c99fd8edfdad09f10582d2.jpg: 640x640 2 with_masks, 46.1ms\n",
+            "Speed: 1.8ms preprocess, 46.1ms inference, 9.2ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss400_png.rf.63c84ce5e3e0391c9509f77d2244755c.jpg: 640x640 3 with_masks, 37.6ms\n",
+            "Speed: 9.7ms preprocess, 37.6ms inference, 3.2ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss429_png.rf.0f9bc0b4f072650f40e985eefdce87df.jpg: 640x640 5 with_masks, 37.1ms\n",
+            "Speed: 1.8ms preprocess, 37.1ms inference, 2.6ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss438_png.rf.85978160d8cedb7d56a26e0d06e41f87.jpg: 640x640 4 with_masks, 37.1ms\n",
+            "Speed: 1.7ms preprocess, 37.1ms inference, 2.5ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss440_png.rf.641564d43589f6344bacc5d05d51da53.jpg: 640x640 1 mask_weared_incorrect, 10 with_masks, 37.1ms\n",
+            "Speed: 6.1ms preprocess, 37.1ms inference, 6.3ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss44_png.rf.b6697a646548922305672e657697750b.jpg: 640x640 5 with_masks, 1 without_mask, 37.1ms\n",
+            "Speed: 1.8ms preprocess, 37.1ms inference, 5.1ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss450_png.rf.8f5e0ff6c7228f1180f985685beb20d5.jpg: 640x640 5 with_masks, 37.2ms\n",
+            "Speed: 2.0ms preprocess, 37.2ms inference, 2.9ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss457_png.rf.60b3bf773c197a83826aae38a0cf2387.jpg: 640x640 5 with_masks, 1 without_mask, 37.2ms\n",
+            "Speed: 1.9ms preprocess, 37.2ms inference, 3.0ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss459_png.rf.73bd4ff56e948804a4c7d5cc9e2f98ef.jpg: 640x640 1 with_mask, 1 without_mask, 37.2ms\n",
+            "Speed: 5.2ms preprocess, 37.2ms inference, 2.9ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss45_png.rf.3b160c8afb75253926e1abf7b4972504.jpg: 640x640 1 with_mask, 1 without_mask, 40.2ms\n",
+            "Speed: 1.7ms preprocess, 40.2ms inference, 2.8ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss431_png.rf.c5e66fbd5f544edca4f20973ce5ecf08.jpg: 640x640 1 mask_weared_incorrect, 17 with_masks, 37.2ms\n",
+            "Speed: 2.1ms preprocess, 37.2ms inference, 2.9ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss395_png.rf.d0fd9e7ac741d7df48a86b7f291e9b49.jpg: 640x640 1 with_mask, 37.2ms\n",
+            "Speed: 3.1ms preprocess, 37.2ms inference, 2.8ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss389_png.rf.11956fb49c814dab304f0006b9075f71.jpg: 640x640 11 with_masks, 2 without_masks, 37.1ms\n",
+            "Speed: 3.9ms preprocess, 37.1ms inference, 3.0ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss388_png.rf.4847bd339895b2496b21a16876aca440.jpg: 640x640 1 mask_weared_incorrect, 10 with_masks, 8 without_masks, 37.1ms\n",
+            "Speed: 1.8ms preprocess, 37.1ms inference, 2.8ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss311_png.rf.8d4e3cc30ab76d6699d7f220a26286dd.jpg: 640x640 5 with_masks, 37.2ms\n",
+            "Speed: 2.3ms preprocess, 37.2ms inference, 3.6ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss313_png.rf.0d2ede745cca1bbc73883747763be4cb.jpg: 640x640 3 with_masks, 37.2ms\n",
+            "Speed: 1.8ms preprocess, 37.2ms inference, 2.9ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss315_png.rf.bdcb0e2cde8b888d72849bbf232bc644.jpg: 640x640 2 with_masks, 37.2ms\n",
+            "Speed: 2.2ms preprocess, 37.2ms inference, 3.0ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss31_png.rf.f71dabc8b32a5181ae4a7ec0724d169e.jpg: 640x640 2 with_masks, 37.2ms\n",
+            "Speed: 1.8ms preprocess, 37.2ms inference, 3.1ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss321_png.rf.d5ca9ccecbb235c5551003b177cd1d46.jpg: 640x640 1 mask_weared_incorrect, 1 with_mask, 1 without_mask, 37.1ms\n",
+            "Speed: 1.9ms preprocess, 37.1ms inference, 2.9ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss330_png.rf.ca2fe4eca45ae4b2bc6bb9fde6d39dff.jpg: 640x640 4 with_masks, 37.2ms\n",
+            "Speed: 2.1ms preprocess, 37.2ms inference, 2.9ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss338_png.rf.669c284dd81181d71654743a3ca9aeb3.jpg: 640x640 7 with_masks, 37.2ms\n",
+            "Speed: 1.9ms preprocess, 37.2ms inference, 3.0ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss339_png.rf.d26efdd756cada62599cd227994bbf56.jpg: 640x640 1 with_mask, 37.2ms\n",
+            "Speed: 2.0ms preprocess, 37.2ms inference, 3.1ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss343_png.rf.1c5c7bbcb828a1cf9d4d2584972083cb.jpg: 640x640 1 without_mask, 37.2ms\n",
+            "Speed: 1.8ms preprocess, 37.2ms inference, 2.8ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss351_png.rf.15436d1eb7080d7bae2e79d554a4d3cb.jpg: 640x640 1 with_mask, 37.9ms\n",
+            "Speed: 1.9ms preprocess, 37.9ms inference, 2.8ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss364_png.rf.74e470c60f166ba4ec1a268b153fa240.jpg: 640x640 3 with_masks, 37.1ms\n",
+            "Speed: 1.8ms preprocess, 37.1ms inference, 2.8ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss366_png.rf.433ea8f6b4fcab0d951b52116611c1be.jpg: 640x640 3 with_masks, 37.2ms\n",
+            "Speed: 1.7ms preprocess, 37.2ms inference, 2.8ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss368_png.rf.1d14fe4224d1b152c5e272d889fe3d45.jpg: 640x640 9 with_masks, 37.2ms\n",
+            "Speed: 1.9ms preprocess, 37.2ms inference, 2.9ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss374_png.rf.b51c420d86fc3a474ed557b5a230b51e.jpg: 640x640 4 with_masks, 1 without_mask, 37.2ms\n",
+            "Speed: 1.8ms preprocess, 37.2ms inference, 3.9ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss376_png.rf.ca418b2ffccc242892a1ab14657e8349.jpg: 640x640 8 with_masks, 37.1ms\n",
+            "Speed: 2.0ms preprocess, 37.1ms inference, 3.2ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss37_png.rf.60ce2ff44ae089a01d8f07ff2e0f00ad.jpg: 640x640 1 with_mask, 37.2ms\n",
+            "Speed: 1.7ms preprocess, 37.2ms inference, 2.6ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss387_png.rf.6d027b3075e33a4414cc245ec7435fcc.jpg: 640x640 1 mask_weared_incorrect, 3 with_masks, 37.3ms\n",
+            "Speed: 1.9ms preprocess, 37.3ms inference, 3.1ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss464_png.rf.b7d07a0f6aabc271e6bfbe039246786b.jpg: 640x640 8 with_masks, 37.2ms\n",
+            "Speed: 1.9ms preprocess, 37.2ms inference, 3.1ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n",
+            "      60/80      10.4G     0.8154      0.416     0.9786        102        640: 100%|██���███████| 106/106 [00:59<00:00,  1.77it/s]\n",
+            "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100%|██████████| 6/6 [00:02<00:00,  2.26it/s]\n",
+            "                   all        161        861      0.922      0.767      0.843      0.542\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss90_png.rf.bb3401c96e9aba7db607a9a5ac8d8f51.jpg: 640x640 12 with_masks, 44.3ms\n",
+            "Speed: 1.6ms preprocess, 44.3ms inference, 2.9ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n",
+            "      61/80      10.4G     0.7983     0.4074     0.9735        109        640: 100%|██████████| 106/106 [00:59<00:00,  1.77it/s]\n",
+            "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100%|██████████| 6/6 [00:02<00:00,  2.33it/s]\n",
+            "                   all        161        861      0.882      0.765      0.836       0.54\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss107_png.rf.285757ad3a789f0d69380282b3bdb846.jpg: 640x640 1 with_mask, 44.3ms\n",
+            "Speed: 4.7ms preprocess, 44.3ms inference, 2.6ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss569_png.rf.245d020288f15a704c2742a49eb1ca63.jpg: 640x640 1 with_mask, 37.1ms\n",
+            "Speed: 1.9ms preprocess, 37.1ms inference, 2.1ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss56_png.rf.ffec370c63bb3ee301d05f9ce072e3fa.jpg: 640x640 1 with_mask, 37.2ms\n",
+            "Speed: 1.9ms preprocess, 37.2ms inference, 2.4ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss577_png.rf.99d8deb18d344f24bb95f02394713470.jpg: 640x640 12 with_masks, 37.3ms\n",
+            "Speed: 2.1ms preprocess, 37.3ms inference, 2.4ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss585_png.rf.16b40d54481e86f0a1434d30bc6d9c64.jpg: 640x640 3 with_masks, 2 without_masks, 37.2ms\n",
+            "Speed: 1.8ms preprocess, 37.2ms inference, 2.7ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss595_png.rf.f3a260412881f24273c64d6bd6e1966b.jpg: 640x640 6 with_masks, 37.2ms\n",
+            "Speed: 2.2ms preprocess, 37.2ms inference, 2.1ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss596_png.rf.9bf29752ebe873bc099ff9b64ddef6d1.jpg: 640x640 1 with_mask, 37.1ms\n",
+            "Speed: 2.6ms preprocess, 37.1ms inference, 2.0ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss603_png.rf.0d06c5299fd1cf3136e68b97a2afa4fd.jpg: 640x640 94 with_masks, 20 without_masks, 37.1ms\n",
+            "Speed: 1.9ms preprocess, 37.1ms inference, 2.3ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss568_png.rf.a4d4a4e139954b5194617ef2e9ffc81c.jpg: 640x640 1 with_mask, 37.2ms\n",
+            "Speed: 2.8ms preprocess, 37.2ms inference, 2.3ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss608_png.rf.4806b67fedacda192a8448bcf3b53d64.jpg: 640x640 1 with_mask, 37.2ms\n",
+            "Speed: 1.9ms preprocess, 37.2ms inference, 2.3ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss623_png.rf.19a2c6b529d5478510934f467949c887.jpg: 640x640 1 mask_weared_incorrect, 20 with_masks, 3 without_masks, 37.2ms\n",
+            "Speed: 1.8ms preprocess, 37.2ms inference, 2.3ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss626_png.rf.4a2f1a57a893fdcef400930251142f52.jpg: 640x640 1 with_mask, 37.3ms\n",
+            "Speed: 2.0ms preprocess, 37.3ms inference, 2.6ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss627_png.rf.81b096f6b0f9e897cc64f59880e630e0.jpg: 640x640 2 mask_weared_incorrects, 6 with_masks, 7 without_masks, 37.2ms\n",
+            "Speed: 1.8ms preprocess, 37.2ms inference, 2.2ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss630_png.rf.d1ecd7de587fb5c2571563293babff62.jpg: 640x640 1 with_mask, 37.1ms\n",
+            "Speed: 1.9ms preprocess, 37.1ms inference, 2.1ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss631_png.rf.418be1a60a0224818dc54e0d2281c6f4.jpg: 640x640 11 with_masks, 37.2ms\n",
+            "Speed: 2.0ms preprocess, 37.2ms inference, 2.2ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss636_png.rf.e6889a20be3cb52fa81b195fdef01b58.jpg: 640x640 6 with_masks, 2 without_masks, 37.3ms\n",
+            "Speed: 2.1ms preprocess, 37.3ms inference, 2.3ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss645_png.rf.d577b2fbdae8c09e7cb396b9c14f18d7.jpg: 640x640 1 with_mask, 37.2ms\n",
+            "Speed: 1.9ms preprocess, 37.2ms inference, 2.1ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss619_png.rf.bc1dcbfae2f9104ce082afe801399f54.jpg: 640x640 2 with_masks, 1 without_mask, 37.2ms\n",
+            "Speed: 1.8ms preprocess, 37.2ms inference, 2.1ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss646_png.rf.a434ddc2569b34a89bbb07a259996497.jpg: 640x640 1 with_mask, 37.4ms\n",
+            "Speed: 1.9ms preprocess, 37.4ms inference, 2.0ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss563_png.rf.dc088c07f08e5fba01fd6bddeceb27e2.jpg: 640x640 2 with_masks, 37.2ms\n",
+            "Speed: 2.0ms preprocess, 37.2ms inference, 2.2ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss554_png.rf.ba664c8fdc34b11faff3a128d06dbe9a.jpg: 640x640 4 with_masks, 37.4ms\n",
+            "Speed: 2.1ms preprocess, 37.4ms inference, 2.2ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss473_png.rf.6de35811442245ad013a2676e2bcaa0a.jpg: 640x640 3 with_masks, 1 without_mask, 37.4ms\n",
+            "Speed: 1.9ms preprocess, 37.4ms inference, 2.1ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss477_png.rf.0e319d347398d08b8a52fb6a152de44e.jpg: 640x640 7 with_masks, 7 without_masks, 37.1ms\n",
+            "Speed: 2.2ms preprocess, 37.1ms inference, 2.3ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss481_png.rf.6682292ffe5179b26d46c8515797446e.jpg: 640x640 7 with_masks, 37.2ms\n",
+            "Speed: 2.3ms preprocess, 37.2ms inference, 2.2ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss483_png.rf.4c059c2770f996153e3487a7f52f771c.jpg: 640x640 3 with_masks, 1 without_mask, 37.1ms\n",
+            "Speed: 1.8ms preprocess, 37.1ms inference, 2.2ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss484_png.rf.a57bfdb112b858aa9ed93bf36306ac61.jpg: 640x640 2 mask_weared_incorrects, 1 with_mask, 37.1ms\n",
+            "Speed: 1.8ms preprocess, 37.1ms inference, 2.1ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss498_png.rf.095899d089070e7a5a7697113b108f8a.jpg: 640x640 9 with_masks, 2 without_masks, 37.2ms\n",
+            "Speed: 1.9ms preprocess, 37.2ms inference, 2.7ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss499_png.rf.611bdf8f03aea1d86028c7b5d7d494ec.jpg: 640x640 1 with_mask, 1 without_mask, 37.2ms\n",
+            "Speed: 1.9ms preprocess, 37.2ms inference, 2.6ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss560_png.rf.bc8e65e2733e0f7b723391d33c380fe0.jpg: 640x640 1 with_mask, 37.2ms\n",
+            "Speed: 5.9ms preprocess, 37.2ms inference, 2.7ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss49_png.rf.d4077078d124ff3d3d699fc94bd06150.jpg: 640x640 7 with_masks, 2 without_masks, 37.1ms\n",
+            "Speed: 1.8ms preprocess, 37.1ms inference, 2.6ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss509_png.rf.6470c0dd2a6a4b05117cca6aad267087.jpg: 640x640 1 with_mask, 37.2ms\n",
+            "Speed: 1.8ms preprocess, 37.2ms inference, 2.5ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss512_png.rf.8dbd72e69a164fdcdad2e220bcd0c467.jpg: 640x640 8 with_masks, 37.2ms\n",
+            "Speed: 2.0ms preprocess, 37.2ms inference, 2.7ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n",
+            "      62/80      10.5G     0.7956      0.405     0.9638         74        640: 100%|██████████| 106/106 [01:01<00:00,  1.73it/s]\n",
+            "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100%|██████████| 6/6 [00:02<00:00,  2.26it/s]\n",
+            "                   all        161        861      0.895      0.738      0.819      0.527\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss515_png.rf.9b8d660e9368ee9ccfeb977e609167ed.jpg: 640x640 1 with_mask, 40.1ms\n",
+            "Speed: 1.9ms preprocess, 40.1ms inference, 9.3ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss529_png.rf.6ae323861cb838fc945c80ee31070c4c.jpg: 640x640 8 with_masks, 1 without_mask, 37.2ms\n",
+            "Speed: 1.8ms preprocess, 37.2ms inference, 2.2ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss532_png.rf.03aa559343f932efbfa3753190291fa7.jpg: 640x640 1 with_mask, 37.2ms\n",
+            "Speed: 2.0ms preprocess, 37.2ms inference, 2.6ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss537_png.rf.f22f4997ea93880ebfa2cb19a893caad.jpg: 640x640 1 without_mask, 37.1ms\n",
+            "Speed: 1.9ms preprocess, 37.1ms inference, 2.1ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss551_png.rf.010062fb38326dac49ecca8d9322953f.jpg: 640x640 5 with_masks, 37.2ms\n",
+            "Speed: 1.8ms preprocess, 37.2ms inference, 2.2ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss501_png.rf.125122fa5a318ec6d0e27d632764f840.jpg: 640x640 8 with_masks, 1 without_mask, 37.1ms\n",
+            "Speed: 1.9ms preprocess, 37.1ms inference, 3.5ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss649_png.rf.5540865cd8826940d55b3b48c045183c.jpg: 640x640 1 with_mask, 37.1ms\n",
+            "Speed: 1.6ms preprocess, 37.1ms inference, 2.1ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss64_png.rf.4b8ca34d17365fb62029fdbee94cb0aa.jpg: 640x640 3 with_masks, 37.2ms\n",
+            "Speed: 1.9ms preprocess, 37.2ms inference, 2.5ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss653_png.rf.22cf40d34bad20f7f9b542b6a0a89e2f.jpg: 640x640 2 with_masks, 37.2ms\n",
+            "Speed: 1.8ms preprocess, 37.2ms inference, 2.5ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss787_png.rf.a7e026e8082789734a57252cf6df81e5.jpg: 640x640 8 with_masks, 2 without_masks, 37.1ms\n",
+            "Speed: 1.9ms preprocess, 37.1ms inference, 2.4ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss793_png.rf.dd2be948b6231ceb68a6af8371f2329c.jpg: 640x640 1 with_mask, 37.4ms\n",
+            "Speed: 2.7ms preprocess, 37.4ms inference, 2.2ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss797_png.rf.5ead12df141e267f928b7b34c73dfb1a.jpg: 640x640 8 with_masks, 37.2ms\n",
+            "Speed: 1.9ms preprocess, 37.2ms inference, 2.2ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss79_png.rf.e12280d9bd602d3e52504b83921437d6.jpg: 640x640 5 with_masks, 37.3ms\n",
+            "Speed: 1.8ms preprocess, 37.3ms inference, 2.3ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss806_png.rf.504dc192775390a4b3f7d6b85bc58636.jpg: 640x640 7 with_masks, 1 without_mask, 37.2ms\n",
+            "Speed: 2.0ms preprocess, 37.2ms inference, 2.2ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss808_png.rf.b2e534caaaf701b8674add21e64fd528.jpg: 640x640 1 with_mask, 37.2ms\n",
+            "Speed: 2.6ms preprocess, 37.2ms inference, 2.2ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss822_png.rf.8601f2a416cbe3f239fde9934f5f66d2.jpg: 640x640 10 with_masks, 6 without_masks, 37.3ms\n",
+            "Speed: 2.0ms preprocess, 37.3ms inference, 2.2ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss784_png.rf.b95afb3096062e72503f25dfdaf53f52.jpg: 640x640 11 with_masks, 2 without_masks, 37.2ms\n",
+            "Speed: 1.9ms preprocess, 37.2ms inference, 2.3ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss828_png.rf.ef40e6fb83c895f7c4ca491dadbcecb1.jpg: 640x640 1 with_mask, 37.3ms\n",
+            "Speed: 1.8ms preprocess, 37.3ms inference, 2.9ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss832_png.rf.fd2d4b0fa4b62433e71f92aa8f1bc067.jpg: 640x640 1 mask_weared_incorrect, 1 without_mask, 37.2ms\n",
+            "Speed: 1.9ms preprocess, 37.2ms inference, 3.4ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss834_png.rf.c14acf559bb5531c92d3cf19a5193aa2.jpg: 640x640 6 with_masks, 37.2ms\n",
+            "Speed: 5.1ms preprocess, 37.2ms inference, 2.7ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss835_png.rf.b8a44eb8c868a51999b450873338a62a.jpg: 640x640 1 mask_weared_incorrect, 2 with_masks, 37.2ms\n",
+            "Speed: 2.0ms preprocess, 37.2ms inference, 2.5ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss840_png.rf.78c778f16a6a87f204473b70c7e735b1.jpg: 640x640 2 with_masks, 37.1ms\n",
+            "Speed: 1.7ms preprocess, 37.1ms inference, 2.7ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss844_png.rf.98f015b79733ae45cfff40da2c6eb85c.jpg: 640x640 2 with_masks, 37.2ms\n",
+            "Speed: 1.9ms preprocess, 37.2ms inference, 2.8ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss846_png.rf.f600f86418cd50b99d7116344abfe0df.jpg: 640x640 2 with_masks, 37.2ms\n",
+            "Speed: 1.9ms preprocess, 37.2ms inference, 2.7ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss848_png.rf.a1793122f2a5ab2b5a3d7be92157ea6b.jpg: 640x640 3 with_masks, 37.2ms\n",
+            "Speed: 2.0ms preprocess, 37.2ms inference, 3.0ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss830_png.rf.c8684a6a7e69bd43d4d35d54f2004fd7.jpg: 640x640 1 mask_weared_incorrect, 1 with_mask, 39.8ms\n",
+            "Speed: 1.8ms preprocess, 39.8ms inference, 2.9ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss761_png.rf.666e2aaecaf296dc7fe39031d857300a.jpg: 640x640 1 mask_weared_incorrect, 1 with_mask, 37.2ms\n",
+            "Speed: 1.9ms preprocess, 37.2ms inference, 3.0ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss751_png.rf.dad3bdfd78335be99b02ca0f7f0a6679.jpg: 640x640 4 with_masks, 37.2ms\n",
+            "Speed: 1.8ms preprocess, 37.2ms inference, 2.9ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss748_png.rf.75b65aa87d1ab4b31a47b7e3f80a43c3.jpg: 640x640 1 mask_weared_incorrect, 1 without_mask, 37.4ms\n",
+            "Speed: 2.2ms preprocess, 37.4ms inference, 2.9ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss658_png.rf.18a299a86c94f8a6784af81f2f6b6c89.jpg: 640x640 1 mask_weared_incorrect, 1 without_mask, 37.2ms\n",
+            "Speed: 1.9ms preprocess, 37.2ms inference, 3.0ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss65_png.rf.f3dacea8ddea2ac8019c39c83bcec5c4.jpg: 640x640 3 with_masks, 1 without_mask, 37.2ms\n",
+            "Speed: 1.9ms preprocess, 37.2ms inference, 2.8ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss662_png.rf.0dec50b3c2f682da13df8167851159b8.jpg: 640x640 4 with_masks, 37.2ms\n",
+            "Speed: 1.8ms preprocess, 37.2ms inference, 2.8ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n",
+            "      63/80      10.5G     0.7792     0.3974     0.9639        100        640: 100%|██████████| 106/106 [01:00<00:00,  1.77it/s]\n",
+            "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100%|██████████| 6/6 [00:03<00:00,  1.78it/s]\n",
+            "                   all        161        861      0.923      0.769      0.856      0.557\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss664_png.rf.d7257f69f379e30582c9d5854e4bb093.jpg: 640x640 1 with_mask, 44.6ms\n",
+            "Speed: 1.8ms preprocess, 44.6ms inference, 2.6ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss674_png.rf.7848cd9439fa5dc0f5b03471912cdd27.jpg: 640x640 19 with_masks, 1 without_mask, 37.2ms\n",
+            "Speed: 2.0ms preprocess, 37.2ms inference, 3.2ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss680_png.rf.6430e43e329f2bd17482dab5d188875a.jpg: 640x640 2 mask_weared_incorrects, 8 with_masks, 1 without_mask, 37.1ms\n",
+            "Speed: 2.5ms preprocess, 37.1ms inference, 2.2ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss691_png.rf.68076bbedb2a9c8ce1c37ba0bc259d8c.jpg: 640x640 12 with_masks, 1 without_mask, 37.1ms\n",
+            "Speed: 1.7ms preprocess, 37.1ms inference, 2.4ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss694_png.rf.92b3468ed6b2d74d6e8e47c151e871a0.jpg: 640x640 5 with_masks, 37.2ms\n",
+            "Speed: 1.9ms preprocess, 37.2ms inference, 2.2ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss708_png.rf.0b01c6531d4980ea30cfde314a37ac52.jpg: 640x640 4 with_masks, 1 without_mask, 37.2ms\n",
+            "Speed: 1.9ms preprocess, 37.2ms inference, 2.2ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss714_png.rf.c59ce90ae182b29cc037c99b47028dd2.jpg: 640x640 5 with_masks, 37.2ms\n",
+            "Speed: 1.9ms preprocess, 37.2ms inference, 3.0ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss723_png.rf.4f8f04c5a74149652aaa8862ac9acb2a.jpg: 640x640 8 with_masks, 6 without_masks, 37.1ms\n",
+            "Speed: 2.8ms preprocess, 37.1ms inference, 2.2ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss725_png.rf.24ef1eeec5e346d219ce1633e649949c.jpg: 640x640 1 with_mask, 37.2ms\n",
+            "Speed: 2.0ms preprocess, 37.2ms inference, 2.1ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss72_png.rf.b94af68c76d704d083fc9720d480ef93.jpg: 640x640 1 without_mask, 37.2ms\n",
+            "Speed: 2.0ms preprocess, 37.2ms inference, 2.2ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss733_png.rf.bde25a6afb7d3fef880a5c9723c5c30d.jpg: 640x640 1 with_mask, 37.2ms\n",
+            "Speed: 2.1ms preprocess, 37.2ms inference, 2.2ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss73_png.rf.4f856521249c200a0dac653cddd51e50.jpg: 640x640 2 mask_weared_incorrects, 3 with_masks, 37.1ms\n",
+            "Speed: 1.6ms preprocess, 37.1ms inference, 2.3ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss744_png.rf.a8b60de6dbbfeb80df902a739b90f925.jpg: 640x640 2 with_masks, 37.2ms\n",
+            "Speed: 3.1ms preprocess, 37.2ms inference, 2.7ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss747_png.rf.09f39fbe610327e3092119f0e0a091ff.jpg: 640x640 1 with_mask, 37.1ms\n",
+            "Speed: 1.8ms preprocess, 37.1ms inference, 2.1ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss471_png.rf.c52f488eaed280f80c7d3e439c0c4e2a.jpg: 640x640 5 with_masks, 2 without_masks, 37.1ms\n",
+            "Speed: 1.7ms preprocess, 37.1ms inference, 2.4ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss89_png.rf.0459d0e0116e154559a89c1975734728.jpg: 640x640 41 with_masks, 37.2ms\n",
+            "Speed: 2.4ms preprocess, 37.2ms inference, 3.3ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss470_png.rf.3fca085941c9a6dbd4e79ea151f97079.jpg: 640x640 6 with_masks, 1 without_mask, 37.2ms\n",
+            "Speed: 6.1ms preprocess, 37.2ms inference, 2.7ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss461_png.rf.6316f0f312cd4c8c93c77f83f5484af9.jpg: 640x640 8 with_masks, 37.9ms\n",
+            "Speed: 1.8ms preprocess, 37.9ms inference, 2.6ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss230_png.rf.1fe3136ab2b6bffc7cd0b6e65101870c.jpg: 640x640 6 with_masks, 37.2ms\n",
+            "Speed: 3.8ms preprocess, 37.2ms inference, 5.9ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss236_png.rf.ea526bb945fec0e07973f2cd052ef688.jpg: 640x640 1 without_mask, 37.2ms\n",
+            "Speed: 2.3ms preprocess, 37.2ms inference, 2.7ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss241_png.rf.01c103b7f1b42f6eaaa3f4c67d5e063a.jpg: 640x640 1 with_mask, 37.1ms\n",
+            "Speed: 1.8ms preprocess, 37.1ms inference, 3.2ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss242_png.rf.048ddfefd131055beb8263c92bbb62a8.jpg: 640x640 1 with_mask, 37.2ms\n",
+            "Speed: 2.1ms preprocess, 37.2ms inference, 3.4ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss244_png.rf.f9240dd571e5670cad3b769290bbd680.jpg: 640x640 1 with_mask, 2 without_masks, 37.1ms\n",
+            "Speed: 2.3ms preprocess, 37.1ms inference, 2.9ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss247_png.rf.f67e30adf66e59df979a1db74326bd5b.jpg: 640x640 14 with_masks, 37.2ms\n",
+            "Speed: 2.9ms preprocess, 37.2ms inference, 3.0ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss248_png.rf.c19d9460b893693e4b637a1f7df7008a.jpg: 640x640 1 without_mask, 37.4ms\n",
+            "Speed: 1.9ms preprocess, 37.4ms inference, 2.8ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss229_png.rf.45ba617a90c78bc0e8e547bffedbe3c3.jpg: 640x640 14 with_masks, 37.2ms\n",
+            "Speed: 1.9ms preprocess, 37.2ms inference, 3.0ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss253_png.rf.93b13ca348adf361296ed659d6acfe75.jpg: 640x640 7 with_masks, 4 without_masks, 37.2ms\n",
+            "Speed: 1.9ms preprocess, 37.2ms inference, 2.9ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss264_png.rf.7018fdf357ffc35189a710fdfc752b52.jpg: 640x640 7 with_masks, 37.2ms\n",
+            "Speed: 2.7ms preprocess, 37.2ms inference, 3.8ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss271_png.rf.cc2239f13f1ebcc7519a1b37fc36376a.jpg: 640x640 1 with_mask, 38.7ms\n",
+            "Speed: 1.9ms preprocess, 38.7ms inference, 2.7ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss277_png.rf.12d1ae22a19b53135a7172821eaf2559.jpg: 640x640 9 with_masks, 37.2ms\n",
+            "Speed: 4.1ms preprocess, 37.2ms inference, 2.9ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss282_png.rf.32d06bf0012896891f681325fa56166d.jpg: 640x640 12 with_masks, 1 without_mask, 37.2ms\n",
+            "Speed: 2.7ms preprocess, 37.2ms inference, 2.9ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss289_png.rf.fee0ba4040ee03de9c67793e8127c627.jpg: 640x640 2 without_masks, 37.1ms\n",
+            "Speed: 2.0ms preprocess, 37.1ms inference, 3.0ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n",
+            "      64/80      10.5G      0.773     0.3889     0.9626         59        640: 100%|██████████| 106/106 [01:00<00:00,  1.76it/s]\n",
+            "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100%|██████████| 6/6 [00:03<00:00,  1.91it/s]\n",
+            "                   all        161        861      0.905      0.752      0.827      0.552\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss301_png.rf.79b160619414ca6a470bd5ea8b30ef4a.jpg: 640x640 1 mask_weared_incorrect, 19 with_masks, 3 without_masks, 73.9ms\n",
+            "Speed: 1.8ms preprocess, 73.9ms inference, 4.5ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss303_png.rf.f00ae35b4058b933e066d1d2a4d88c17.jpg: 640x640 2 with_masks, 37.2ms\n",
+            "Speed: 1.7ms preprocess, 37.2ms inference, 2.2ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss258_png.rf.fc7b4f2f14e1d199dce55985695d1120.jpg: 640x640 1 mask_weared_incorrect, 1 with_mask, 37.2ms\n",
+            "Speed: 1.9ms preprocess, 37.2ms inference, 2.2ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss304_png.rf.9df48cf93de57fa41d0a2b59de78a62c.jpg: 640x640 2 with_masks, 37.2ms\n",
+            "Speed: 1.8ms preprocess, 37.2ms inference, 2.2ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss224_png.rf.4539ed1dc0a709e4e01077ecf7bc2b22.jpg: 640x640 2 with_masks, 37.1ms\n",
+            "Speed: 1.7ms preprocess, 37.1ms inference, 2.2ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss20_png.rf.ca394d629ffaba1fdb13e432a79a5eb9.jpg: 640x640 2 with_masks, 37.2ms\n",
+            "Speed: 1.7ms preprocess, 37.2ms inference, 3.3ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss109_png.rf.3c26f7537566830dffb39c47f71e574e.jpg: 640x640 1 with_mask, 37.1ms\n",
+            "Speed: 1.6ms preprocess, 37.1ms inference, 2.1ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss114_png.rf.c087c8382ac2542ac89314fa0bbeb4f6.jpg: 640x640 2 with_masks, 1 without_mask, 37.2ms\n",
+            "Speed: 2.1ms preprocess, 37.2ms inference, 2.2ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss127_png.rf.1baab62c26cbf4478f2a8d99e1cf68de.jpg: 640x640 1 with_mask, 1 without_mask, 37.2ms\n",
+            "Speed: 2.8ms preprocess, 37.2ms inference, 2.3ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss146_png.rf.ec0da30308aa466d39bae79b0cc0e2bf.jpg: 640x640 3 with_masks, 37.1ms\n",
+            "Speed: 2.0ms preprocess, 37.1ms inference, 2.1ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss152_png.rf.c66bb39b29efc7503239890f834100dc.jpg: 640x640 7 with_masks, 37.2ms\n",
+            "Speed: 2.0ms preprocess, 37.2ms inference, 2.3ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss154_png.rf.7512e06f4e0bd3a2185ec1867603cc8a.jpg: 640x640 1 without_mask, 37.1ms\n",
+            "Speed: 1.8ms preprocess, 37.1ms inference, 2.9ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss168_png.rf.3b19cb741e672eef23c3f091fd204d52.jpg: 640x640 3 with_masks, 3 without_masks, 37.1ms\n",
+            "Speed: 1.9ms preprocess, 37.1ms inference, 2.2ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss217_png.rf.c4e305ead91154374bba4fc48e0e3b99.jpg: 640x640 1 without_mask, 37.2ms\n",
+            "Speed: 2.2ms preprocess, 37.2ms inference, 2.4ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss169_png.rf.49a3d702f1cd1ce83aa6cd01599e3644.jpg: 640x640 1 with_mask, 37.2ms\n",
+            "Speed: 2.9ms preprocess, 37.2ms inference, 2.2ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss174_png.rf.ba1760e663e246482b26e587332650b0.jpg: 640x640 4 with_masks, 37.3ms\n",
+            "Speed: 1.8ms preprocess, 37.3ms inference, 2.2ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss178_png.rf.2fd8857c96b9bed1982f78b55798a334.jpg: 640x640 2 with_masks, 1 without_mask, 37.1ms\n",
+            "Speed: 1.9ms preprocess, 37.1ms inference, 2.4ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss194_png.rf.77ed2eca9fe5235cf2496449dd156996.jpg: 640x640 2 with_masks, 37.3ms\n",
+            "Speed: 2.4ms preprocess, 37.3ms inference, 2.1ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss197_png.rf.cd0c6b120a0fae906bb417f825daf6a1.jpg: 640x640 2 with_masks, 37.2ms\n",
+            "Speed: 2.0ms preprocess, 37.2ms inference, 2.1ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss1_png.rf.e41f0052ad0e49cab0887d6e50e5a7eb.jpg: 640x640 6 with_masks, 1 without_mask, 37.1ms\n",
+            "Speed: 1.9ms preprocess, 37.1ms inference, 2.1ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss203_png.rf.eba7307a461c6b2098593e82d2cccecc.jpg: 640x640 4 with_masks, 37.2ms\n",
+            "Speed: 1.9ms preprocess, 37.2ms inference, 2.2ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss206_png.rf.68794173883f5ae26e2382a3087aac0b.jpg: 640x640 7 with_masks, 2 without_masks, 37.1ms\n",
+            "Speed: 1.9ms preprocess, 37.1ms inference, 2.1ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss172_png.rf.13bb93a8bf5266e0d73bab43f62e0376.jpg: 640x640 1 without_mask, 37.1ms\n",
+            "Speed: 1.9ms preprocess, 37.1ms inference, 2.1ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss306_png.rf.52a38aff8eebcfb7d90d0c7cac38fdec.jpg: 640x640 1 with_mask, 37.2ms\n",
+            "Speed: 1.9ms preprocess, 37.2ms inference, 2.1ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss307_png.rf.93b21e5a88a625f2a9284ff6253bd417.jpg: 640x640 1 mask_weared_incorrect, 1 with_mask, 1 without_mask, 37.2ms\n",
+            "Speed: 1.8ms preprocess, 37.2ms inference, 2.2ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss308_png.rf.61a249cc68e67a9cf66c2393f61080f2.jpg: 640x640 2 with_masks, 37.3ms\n",
+            "Speed: 2.3ms preprocess, 37.3ms inference, 2.2ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss402_png.rf.adb70e16aac43aa519466a4364f99311.jpg: 640x640 1 without_mask, 37.1ms\n",
+            "Speed: 1.8ms preprocess, 37.1ms inference, 2.1ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss408_png.rf.bb077fd8dd6090c8f22b2dfe4fb0b2dc.jpg: 640x640 8 with_masks, 3 without_masks, 37.4ms\n",
+            "Speed: 1.8ms preprocess, 37.4ms inference, 2.1ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss409_png.rf.a1da634820d49e7be38ce59f5f5887bb.jpg: 640x640 1 with_mask, 37.2ms\n",
+            "Speed: 1.8ms preprocess, 37.2ms inference, 2.3ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss410_png.rf.eaad04d3f7e7468f6a0a3d017306d6da.jpg: 640x640 1 mask_weared_incorrect, 22 with_masks, 2 without_masks, 37.2ms\n",
+            "Speed: 1.7ms preprocess, 37.2ms inference, 3.1ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss418_png.rf.432d10d262677cb69e95be55ca0c9125.jpg: 640x640 2 with_masks, 1 without_mask, 37.1ms\n",
+            "Speed: 2.4ms preprocess, 37.1ms inference, 2.2ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss421_png.rf.7ecb66f6ba285fd631717a3635a7dd71.jpg: 640x640 5 with_masks, 37.1ms\n",
+            "Speed: 1.5ms preprocess, 37.1ms inference, 2.1ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n",
+            "      65/80      10.6G     0.7668      0.395     0.9549        220        640: 100%|██████████| 106/106 [01:00<00:00,  1.75it/s]\n",
+            "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100%|██████████| 6/6 [00:02<00:00,  2.10it/s]\n",
+            "                   all        161        861      0.901      0.769      0.832      0.551\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss425_png.rf.b69c6da9a6c99fd8edfdad09f10582d2.jpg: 640x640 1 with_mask, 101.1ms\n",
+            "Speed: 1.7ms preprocess, 101.1ms inference, 5.1ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss400_png.rf.63c84ce5e3e0391c9509f77d2244755c.jpg: 640x640 2 with_masks, 39.9ms\n",
+            "Speed: 1.9ms preprocess, 39.9ms inference, 3.0ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss429_png.rf.0f9bc0b4f072650f40e985eefdce87df.jpg: 640x640 4 with_masks, 37.2ms\n",
+            "Speed: 1.8ms preprocess, 37.2ms inference, 2.9ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss438_png.rf.85978160d8cedb7d56a26e0d06e41f87.jpg: 640x640 4 with_masks, 37.3ms\n",
+            "Speed: 1.9ms preprocess, 37.3ms inference, 2.8ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss440_png.rf.641564d43589f6344bacc5d05d51da53.jpg: 640x640 1 mask_weared_incorrect, 9 with_masks, 37.2ms\n",
+            "Speed: 2.8ms preprocess, 37.2ms inference, 2.9ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss44_png.rf.b6697a646548922305672e657697750b.jpg: 640x640 3 with_masks, 1 without_mask, 37.2ms\n",
+            "Speed: 1.8ms preprocess, 37.2ms inference, 3.1ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss450_png.rf.8f5e0ff6c7228f1180f985685beb20d5.jpg: 640x640 4 with_masks, 37.2ms\n",
+            "Speed: 1.8ms preprocess, 37.2ms inference, 2.8ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss457_png.rf.60b3bf773c197a83826aae38a0cf2387.jpg: 640x640 4 with_masks, 1 without_mask, 37.9ms\n",
+            "Speed: 1.9ms preprocess, 37.9ms inference, 2.9ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss459_png.rf.73bd4ff56e948804a4c7d5cc9e2f98ef.jpg: 640x640 1 mask_weared_incorrect, 1 with_mask, 1 without_mask, 37.2ms\n",
+            "Speed: 1.9ms preprocess, 37.2ms inference, 3.1ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss45_png.rf.3b160c8afb75253926e1abf7b4972504.jpg: 640x640 3 with_masks, 1 without_mask, 37.1ms\n",
+            "Speed: 1.8ms preprocess, 37.1ms inference, 3.0ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss431_png.rf.c5e66fbd5f544edca4f20973ce5ecf08.jpg: 640x640 1 mask_weared_incorrect, 19 with_masks, 37.1ms\n",
+            "Speed: 1.8ms preprocess, 37.1ms inference, 3.1ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss395_png.rf.d0fd9e7ac741d7df48a86b7f291e9b49.jpg: 640x640 1 with_mask, 37.2ms\n",
+            "Speed: 1.8ms preprocess, 37.2ms inference, 2.8ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss389_png.rf.11956fb49c814dab304f0006b9075f71.jpg: 640x640 1 mask_weared_incorrect, 10 with_masks, 2 without_masks, 37.2ms\n",
+            "Speed: 1.9ms preprocess, 37.2ms inference, 2.9ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss388_png.rf.4847bd339895b2496b21a16876aca440.jpg: 640x640 1 mask_weared_incorrect, 10 with_masks, 9 without_masks, 37.2ms\n",
+            "Speed: 1.9ms preprocess, 37.2ms inference, 3.1ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss311_png.rf.8d4e3cc30ab76d6699d7f220a26286dd.jpg: 640x640 5 with_masks, 37.2ms\n",
+            "Speed: 1.9ms preprocess, 37.2ms inference, 2.9ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss313_png.rf.0d2ede745cca1bbc73883747763be4cb.jpg: 640x640 1 with_mask, 37.2ms\n",
+            "Speed: 1.9ms preprocess, 37.2ms inference, 3.1ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss315_png.rf.bdcb0e2cde8b888d72849bbf232bc644.jpg: 640x640 2 with_masks, 40.6ms\n",
+            "Speed: 2.0ms preprocess, 40.6ms inference, 3.3ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss31_png.rf.f71dabc8b32a5181ae4a7ec0724d169e.jpg: 640x640 2 with_masks, 37.2ms\n",
+            "Speed: 1.8ms preprocess, 37.2ms inference, 2.1ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss321_png.rf.d5ca9ccecbb235c5551003b177cd1d46.jpg: 640x640 1 mask_weared_incorrect, 1 with_mask, 1 without_mask, 37.2ms\n",
+            "Speed: 1.9ms preprocess, 37.2ms inference, 2.4ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss330_png.rf.ca2fe4eca45ae4b2bc6bb9fde6d39dff.jpg: 640x640 4 with_masks, 37.1ms\n",
+            "Speed: 1.7ms preprocess, 37.1ms inference, 2.2ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss338_png.rf.669c284dd81181d71654743a3ca9aeb3.jpg: 640x640 6 with_masks, 37.1ms\n",
+            "Speed: 2.5ms preprocess, 37.1ms inference, 2.3ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss339_png.rf.d26efdd756cada62599cd227994bbf56.jpg: 640x640 1 with_mask, 37.1ms\n",
+            "Speed: 1.9ms preprocess, 37.1ms inference, 2.3ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss343_png.rf.1c5c7bbcb828a1cf9d4d2584972083cb.jpg: 640x640 1 without_mask, 37.8ms\n",
+            "Speed: 1.9ms preprocess, 37.8ms inference, 2.1ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss351_png.rf.15436d1eb7080d7bae2e79d554a4d3cb.jpg: 640x640 1 with_mask, 37.1ms\n",
+            "Speed: 1.6ms preprocess, 37.1ms inference, 2.3ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss364_png.rf.74e470c60f166ba4ec1a268b153fa240.jpg: 640x640 3 with_masks, 37.2ms\n",
+            "Speed: 2.0ms preprocess, 37.2ms inference, 2.3ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss366_png.rf.433ea8f6b4fcab0d951b52116611c1be.jpg: 640x640 2 with_masks, 37.1ms\n",
+            "Speed: 1.7ms preprocess, 37.1ms inference, 2.1ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss368_png.rf.1d14fe4224d1b152c5e272d889fe3d45.jpg: 640x640 9 with_masks, 37.1ms\n",
+            "Speed: 1.9ms preprocess, 37.1ms inference, 2.8ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss374_png.rf.b51c420d86fc3a474ed557b5a230b51e.jpg: 640x640 4 with_masks, 1 without_mask, 37.1ms\n",
+            "Speed: 1.9ms preprocess, 37.1ms inference, 2.6ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss376_png.rf.ca418b2ffccc242892a1ab14657e8349.jpg: 640x640 7 with_masks, 37.1ms\n",
+            "Speed: 2.2ms preprocess, 37.1ms inference, 2.3ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss37_png.rf.60ce2ff44ae089a01d8f07ff2e0f00ad.jpg: 640x640 1 with_mask, 37.1ms\n",
+            "Speed: 1.9ms preprocess, 37.1ms inference, 3.2ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss387_png.rf.6d027b3075e33a4414cc245ec7435fcc.jpg: 640x640 1 mask_weared_incorrect, 3 with_masks, 1 without_mask, 37.2ms\n",
+            "Speed: 2.1ms preprocess, 37.2ms inference, 2.4ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss464_png.rf.b7d07a0f6aabc271e6bfbe039246786b.jpg: 640x640 9 with_masks, 37.3ms\n",
+            "Speed: 2.0ms preprocess, 37.3ms inference, 2.2ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n",
+            "      66/80      10.6G     0.7636     0.3859     0.9584         89        640: 100%|██████████| 106/106 [01:04<00:00,  1.64it/s]\n",
+            "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100%|██████████| 6/6 [00:04<00:00,  1.47it/s]\n",
+            "                   all        161        861      0.908      0.762      0.829      0.538\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss90_png.rf.bb3401c96e9aba7db607a9a5ac8d8f51.jpg: 640x640 12 with_masks, 87.2ms\n",
+            "Speed: 2.4ms preprocess, 87.2ms inference, 10.4ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n",
+            "      67/80      10.7G     0.7531     0.3801     0.9556         87        640: 100%|██████████| 106/106 [01:01<00:00,  1.73it/s]\n",
+            "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100%|██████████| 6/6 [00:02<00:00,  2.22it/s]\n",
+            "                   all        161        861      0.851      0.792      0.835      0.547\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss107_png.rf.285757ad3a789f0d69380282b3bdb846.jpg: 640x640 1 with_mask, 80.8ms\n",
+            "Speed: 4.1ms preprocess, 80.8ms inference, 10.0ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss569_png.rf.245d020288f15a704c2742a49eb1ca63.jpg: 640x640 1 with_mask, 37.2ms\n",
+            "Speed: 5.0ms preprocess, 37.2ms inference, 8.2ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss56_png.rf.ffec370c63bb3ee301d05f9ce072e3fa.jpg: 640x640 1 with_mask, 37.2ms\n",
+            "Speed: 1.9ms preprocess, 37.2ms inference, 3.5ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss577_png.rf.99d8deb18d344f24bb95f02394713470.jpg: 640x640 13 with_masks, 1 without_mask, 37.2ms\n",
+            "Speed: 2.5ms preprocess, 37.2ms inference, 2.7ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss585_png.rf.16b40d54481e86f0a1434d30bc6d9c64.jpg: 640x640 4 with_masks, 2 without_masks, 37.4ms\n",
+            "Speed: 1.9ms preprocess, 37.4ms inference, 2.8ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss595_png.rf.f3a260412881f24273c64d6bd6e1966b.jpg: 640x640 6 with_masks, 38.3ms\n",
+            "Speed: 1.7ms preprocess, 38.3ms inference, 2.7ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss596_png.rf.9bf29752ebe873bc099ff9b64ddef6d1.jpg: 640x640 1 with_mask, 37.1ms\n",
+            "Speed: 1.8ms preprocess, 37.1ms inference, 2.6ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss603_png.rf.0d06c5299fd1cf3136e68b97a2afa4fd.jpg: 640x640 95 with_masks, 19 without_masks, 37.2ms\n",
+            "Speed: 1.9ms preprocess, 37.2ms inference, 2.7ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss568_png.rf.a4d4a4e139954b5194617ef2e9ffc81c.jpg: 640x640 1 with_mask, 39.7ms\n",
+            "Speed: 1.9ms preprocess, 39.7ms inference, 3.2ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss608_png.rf.4806b67fedacda192a8448bcf3b53d64.jpg: 640x640 1 with_mask, 37.2ms\n",
+            "Speed: 1.8ms preprocess, 37.2ms inference, 3.0ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss623_png.rf.19a2c6b529d5478510934f467949c887.jpg: 640x640 1 mask_weared_incorrect, 21 with_masks, 3 without_masks, 37.2ms\n",
+            "Speed: 1.9ms preprocess, 37.2ms inference, 2.9ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss626_png.rf.4a2f1a57a893fdcef400930251142f52.jpg: 640x640 1 with_mask, 37.7ms\n",
+            "Speed: 1.9ms preprocess, 37.7ms inference, 2.8ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss627_png.rf.81b096f6b0f9e897cc64f59880e630e0.jpg: 640x640 1 mask_weared_incorrect, 6 with_masks, 7 without_masks, 37.2ms\n",
+            "Speed: 1.9ms preprocess, 37.2ms inference, 3.0ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss630_png.rf.d1ecd7de587fb5c2571563293babff62.jpg: 640x640 1 with_mask, 37.2ms\n",
+            "Speed: 1.8ms preprocess, 37.2ms inference, 2.9ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss631_png.rf.418be1a60a0224818dc54e0d2281c6f4.jpg: 640x640 11 with_masks, 1 without_mask, 37.2ms\n",
+            "Speed: 1.9ms preprocess, 37.2ms inference, 2.9ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss636_png.rf.e6889a20be3cb52fa81b195fdef01b58.jpg: 640x640 6 with_masks, 2 without_masks, 37.4ms\n",
+            "Speed: 1.9ms preprocess, 37.4ms inference, 4.0ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss645_png.rf.d577b2fbdae8c09e7cb396b9c14f18d7.jpg: 640x640 1 with_mask, 37.2ms\n",
+            "Speed: 1.9ms preprocess, 37.2ms inference, 2.8ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss619_png.rf.bc1dcbfae2f9104ce082afe801399f54.jpg: 640x640 2 with_masks, 1 without_mask, 37.2ms\n",
+            "Speed: 2.2ms preprocess, 37.2ms inference, 3.0ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss646_png.rf.a434ddc2569b34a89bbb07a259996497.jpg: 640x640 1 with_mask, 37.2ms\n",
+            "Speed: 7.0ms preprocess, 37.2ms inference, 2.9ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss563_png.rf.dc088c07f08e5fba01fd6bddeceb27e2.jpg: 640x640 1 with_mask, 37.2ms\n",
+            "Speed: 3.7ms preprocess, 37.2ms inference, 2.8ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss554_png.rf.ba664c8fdc34b11faff3a128d06dbe9a.jpg: 640x640 5 with_masks, 42.7ms\n",
+            "Speed: 1.9ms preprocess, 42.7ms inference, 4.1ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss473_png.rf.6de35811442245ad013a2676e2bcaa0a.jpg: 640x640 3 with_masks, 1 without_mask, 37.3ms\n",
+            "Speed: 1.8ms preprocess, 37.3ms inference, 5.5ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss477_png.rf.0e319d347398d08b8a52fb6a152de44e.jpg: 640x640 6 with_masks, 7 without_masks, 37.2ms\n",
+            "Speed: 5.0ms preprocess, 37.2ms inference, 2.9ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss481_png.rf.6682292ffe5179b26d46c8515797446e.jpg: 640x640 6 with_masks, 37.1ms\n",
+            "Speed: 1.9ms preprocess, 37.1ms inference, 2.8ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss483_png.rf.4c059c2770f996153e3487a7f52f771c.jpg: 640x640 3 with_masks, 2 without_masks, 40.5ms\n",
+            "Speed: 1.9ms preprocess, 40.5ms inference, 2.9ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss484_png.rf.a57bfdb112b858aa9ed93bf36306ac61.jpg: 640x640 1 mask_weared_incorrect, 1 with_mask, 37.4ms\n",
+            "Speed: 3.2ms preprocess, 37.4ms inference, 3.2ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss498_png.rf.095899d089070e7a5a7697113b108f8a.jpg: 640x640 10 with_masks, 3 without_masks, 37.4ms\n",
+            "Speed: 1.9ms preprocess, 37.4ms inference, 2.2ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss499_png.rf.611bdf8f03aea1d86028c7b5d7d494ec.jpg: 640x640 1 with_mask, 1 without_mask, 37.2ms\n",
+            "Speed: 2.1ms preprocess, 37.2ms inference, 2.3ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss560_png.rf.bc8e65e2733e0f7b723391d33c380fe0.jpg: 640x640 1 with_mask, 1 without_mask, 37.2ms\n",
+            "Speed: 2.2ms preprocess, 37.2ms inference, 2.1ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss49_png.rf.d4077078d124ff3d3d699fc94bd06150.jpg: 640x640 7 with_masks, 2 without_masks, 37.1ms\n",
+            "Speed: 2.0ms preprocess, 37.1ms inference, 2.1ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss509_png.rf.6470c0dd2a6a4b05117cca6aad267087.jpg: 640x640 (no detections), 37.4ms\n",
+            "Speed: 1.9ms preprocess, 37.4ms inference, 1.3ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss512_png.rf.8dbd72e69a164fdcdad2e220bcd0c467.jpg: 640x640 7 with_masks, 37.1ms\n",
+            "Speed: 1.9ms preprocess, 37.1ms inference, 2.2ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n",
+            "      68/80      10.7G     0.7499      0.382     0.9592         66        640: 100%|██████████| 106/106 [01:01<00:00,  1.73it/s]\n",
+            "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100%|██████████| 6/6 [00:02<00:00,  2.11it/s]\n",
+            "                   all        161        861      0.885      0.771      0.829      0.542\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss515_png.rf.9b8d660e9368ee9ccfeb977e609167ed.jpg: 640x640 1 with_mask, 76.5ms\n",
+            "Speed: 1.7ms preprocess, 76.5ms inference, 6.9ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss529_png.rf.6ae323861cb838fc945c80ee31070c4c.jpg: 640x640 1 mask_weared_incorrect, 6 with_masks, 1 without_mask, 37.2ms\n",
+            "Speed: 1.7ms preprocess, 37.2ms inference, 2.1ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss532_png.rf.03aa559343f932efbfa3753190291fa7.jpg: 640x640 1 with_mask, 37.2ms\n",
+            "Speed: 1.9ms preprocess, 37.2ms inference, 2.2ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss537_png.rf.f22f4997ea93880ebfa2cb19a893caad.jpg: 640x640 1 without_mask, 37.3ms\n",
+            "Speed: 1.8ms preprocess, 37.3ms inference, 2.0ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss551_png.rf.010062fb38326dac49ecca8d9322953f.jpg: 640x640 5 with_masks, 37.1ms\n",
+            "Speed: 1.9ms preprocess, 37.1ms inference, 2.2ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss501_png.rf.125122fa5a318ec6d0e27d632764f840.jpg: 640x640 8 with_masks, 37.2ms\n",
+            "Speed: 3.0ms preprocess, 37.2ms inference, 2.2ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss649_png.rf.5540865cd8826940d55b3b48c045183c.jpg: 640x640 1 with_mask, 37.1ms\n",
+            "Speed: 1.5ms preprocess, 37.1ms inference, 2.1ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss64_png.rf.4b8ca34d17365fb62029fdbee94cb0aa.jpg: 640x640 3 with_masks, 37.2ms\n",
+            "Speed: 1.9ms preprocess, 37.2ms inference, 2.1ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss653_png.rf.22cf40d34bad20f7f9b542b6a0a89e2f.jpg: 640x640 3 with_masks, 37.2ms\n",
+            "Speed: 1.8ms preprocess, 37.2ms inference, 2.1ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss787_png.rf.a7e026e8082789734a57252cf6df81e5.jpg: 640x640 8 with_masks, 2 without_masks, 37.2ms\n",
+            "Speed: 2.0ms preprocess, 37.2ms inference, 2.2ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss793_png.rf.dd2be948b6231ceb68a6af8371f2329c.jpg: 640x640 1 with_mask, 37.1ms\n",
+            "Speed: 1.7ms preprocess, 37.1ms inference, 2.1ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss797_png.rf.5ead12df141e267f928b7b34c73dfb1a.jpg: 640x640 8 with_masks, 37.2ms\n",
+            "Speed: 2.0ms preprocess, 37.2ms inference, 2.2ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss79_png.rf.e12280d9bd602d3e52504b83921437d6.jpg: 640x640 5 with_masks, 37.2ms\n",
+            "Speed: 1.7ms preprocess, 37.2ms inference, 2.4ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss806_png.rf.504dc192775390a4b3f7d6b85bc58636.jpg: 640x640 6 with_masks, 1 without_mask, 37.2ms\n",
+            "Speed: 2.1ms preprocess, 37.2ms inference, 2.2ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss808_png.rf.b2e534caaaf701b8674add21e64fd528.jpg: 640x640 1 with_mask, 37.1ms\n",
+            "Speed: 1.8ms preprocess, 37.1ms inference, 2.0ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss822_png.rf.8601f2a416cbe3f239fde9934f5f66d2.jpg: 640x640 1 mask_weared_incorrect, 9 with_masks, 4 without_masks, 37.2ms\n",
+            "Speed: 1.6ms preprocess, 37.2ms inference, 2.3ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss784_png.rf.b95afb3096062e72503f25dfdaf53f52.jpg: 640x640 11 with_masks, 2 without_masks, 37.1ms\n",
+            "Speed: 1.5ms preprocess, 37.1ms inference, 2.2ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss828_png.rf.ef40e6fb83c895f7c4ca491dadbcecb1.jpg: 640x640 1 with_mask, 37.2ms\n",
+            "Speed: 2.8ms preprocess, 37.2ms inference, 2.1ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss832_png.rf.fd2d4b0fa4b62433e71f92aa8f1bc067.jpg: 640x640 1 mask_weared_incorrect, 1 with_mask, 37.1ms\n",
+            "Speed: 1.9ms preprocess, 37.1ms inference, 2.1ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss834_png.rf.c14acf559bb5531c92d3cf19a5193aa2.jpg: 640x640 6 with_masks, 37.2ms\n",
+            "Speed: 2.1ms preprocess, 37.2ms inference, 2.4ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss835_png.rf.b8a44eb8c868a51999b450873338a62a.jpg: 640x640 1 mask_weared_incorrect, 2 with_masks, 37.2ms\n",
+            "Speed: 1.7ms preprocess, 37.2ms inference, 2.1ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss840_png.rf.78c778f16a6a87f204473b70c7e735b1.jpg: 640x640 2 with_masks, 37.2ms\n",
+            "Speed: 2.2ms preprocess, 37.2ms inference, 2.1ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss844_png.rf.98f015b79733ae45cfff40da2c6eb85c.jpg: 640x640 2 with_masks, 37.5ms\n",
+            "Speed: 1.9ms preprocess, 37.5ms inference, 2.7ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss846_png.rf.f600f86418cd50b99d7116344abfe0df.jpg: 640x640 1 with_mask, 37.2ms\n",
+            "Speed: 1.9ms preprocess, 37.2ms inference, 2.1ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss848_png.rf.a1793122f2a5ab2b5a3d7be92157ea6b.jpg: 640x640 3 with_masks, 37.2ms\n",
+            "Speed: 1.8ms preprocess, 37.2ms inference, 2.1ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss830_png.rf.c8684a6a7e69bd43d4d35d54f2004fd7.jpg: 640x640 1 mask_weared_incorrect, 1 with_mask, 37.1ms\n",
+            "Speed: 2.2ms preprocess, 37.1ms inference, 2.2ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss761_png.rf.666e2aaecaf296dc7fe39031d857300a.jpg: 640x640 1 mask_weared_incorrect, 37.2ms\n",
+            "Speed: 2.9ms preprocess, 37.2ms inference, 2.5ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss751_png.rf.dad3bdfd78335be99b02ca0f7f0a6679.jpg: 640x640 5 with_masks, 37.2ms\n",
+            "Speed: 2.0ms preprocess, 37.2ms inference, 2.9ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss748_png.rf.75b65aa87d1ab4b31a47b7e3f80a43c3.jpg: 640x640 1 mask_weared_incorrect, 1 with_mask, 1 without_mask, 37.2ms\n",
+            "Speed: 1.8ms preprocess, 37.2ms inference, 2.8ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss658_png.rf.18a299a86c94f8a6784af81f2f6b6c89.jpg: 640x640 1 mask_weared_incorrect, 1 with_mask, 37.2ms\n",
+            "Speed: 2.0ms preprocess, 37.2ms inference, 2.6ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss65_png.rf.f3dacea8ddea2ac8019c39c83bcec5c4.jpg: 640x640 2 with_masks, 1 without_mask, 40.6ms\n",
+            "Speed: 1.7ms preprocess, 40.6ms inference, 2.6ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss662_png.rf.0dec50b3c2f682da13df8167851159b8.jpg: 640x640 4 with_masks, 37.6ms\n",
+            "Speed: 4.2ms preprocess, 37.6ms inference, 3.0ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n",
+            "      69/80        11G     0.7407     0.3803      0.957        171        640: 100%|██████████| 106/106 [01:02<00:00,  1.68it/s]\n",
+            "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100%|██████████| 6/6 [00:02<00:00,  2.20it/s]\n",
+            "                   all        161        861      0.869      0.767      0.806      0.531\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss664_png.rf.d7257f69f379e30582c9d5854e4bb093.jpg: 640x640 2 with_masks, 50.2ms\n",
+            "Speed: 4.5ms preprocess, 50.2ms inference, 2.9ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss674_png.rf.7848cd9439fa5dc0f5b03471912cdd27.jpg: 640x640 19 with_masks, 1 without_mask, 37.2ms\n",
+            "Speed: 1.8ms preprocess, 37.2ms inference, 3.3ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss680_png.rf.6430e43e329f2bd17482dab5d188875a.jpg: 640x640 3 mask_weared_incorrects, 8 with_masks, 1 without_mask, 37.2ms\n",
+            "Speed: 1.8ms preprocess, 37.2ms inference, 2.1ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss691_png.rf.68076bbedb2a9c8ce1c37ba0bc259d8c.jpg: 640x640 10 with_masks, 37.2ms\n",
+            "Speed: 1.8ms preprocess, 37.2ms inference, 2.1ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss694_png.rf.92b3468ed6b2d74d6e8e47c151e871a0.jpg: 640x640 5 with_masks, 37.2ms\n",
+            "Speed: 1.9ms preprocess, 37.2ms inference, 2.1ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss708_png.rf.0b01c6531d4980ea30cfde314a37ac52.jpg: 640x640 3 with_masks, 37.2ms\n",
+            "Speed: 1.8ms preprocess, 37.2ms inference, 2.1ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss714_png.rf.c59ce90ae182b29cc037c99b47028dd2.jpg: 640x640 4 with_masks, 37.2ms\n",
+            "Speed: 1.9ms preprocess, 37.2ms inference, 2.2ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss723_png.rf.4f8f04c5a74149652aaa8862ac9acb2a.jpg: 640x640 8 with_masks, 6 without_masks, 37.2ms\n",
+            "Speed: 2.4ms preprocess, 37.2ms inference, 2.1ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss725_png.rf.24ef1eeec5e346d219ce1633e649949c.jpg: 640x640 1 with_mask, 37.2ms\n",
+            "Speed: 1.9ms preprocess, 37.2ms inference, 2.6ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss72_png.rf.b94af68c76d704d083fc9720d480ef93.jpg: 640x640 1 without_mask, 37.1ms\n",
+            "Speed: 1.9ms preprocess, 37.1ms inference, 2.2ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss733_png.rf.bde25a6afb7d3fef880a5c9723c5c30d.jpg: 640x640 1 with_mask, 37.2ms\n",
+            "Speed: 2.7ms preprocess, 37.2ms inference, 2.3ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss73_png.rf.4f856521249c200a0dac653cddd51e50.jpg: 640x640 1 mask_weared_incorrect, 3 with_masks, 37.1ms\n",
+            "Speed: 2.0ms preprocess, 37.1ms inference, 2.3ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss744_png.rf.a8b60de6dbbfeb80df902a739b90f925.jpg: 640x640 2 with_masks, 1 without_mask, 37.2ms\n",
+            "Speed: 2.1ms preprocess, 37.2ms inference, 2.1ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss747_png.rf.09f39fbe610327e3092119f0e0a091ff.jpg: 640x640 1 with_mask, 37.2ms\n",
+            "Speed: 1.8ms preprocess, 37.2ms inference, 2.1ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss471_png.rf.c52f488eaed280f80c7d3e439c0c4e2a.jpg: 640x640 6 with_masks, 4 without_masks, 37.2ms\n",
+            "Speed: 1.9ms preprocess, 37.2ms inference, 2.7ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss89_png.rf.0459d0e0116e154559a89c1975734728.jpg: 640x640 36 with_masks, 1 without_mask, 37.1ms\n",
+            "Speed: 1.5ms preprocess, 37.1ms inference, 2.2ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss470_png.rf.3fca085941c9a6dbd4e79ea151f97079.jpg: 640x640 5 with_masks, 37.4ms\n",
+            "Speed: 2.0ms preprocess, 37.4ms inference, 2.3ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss461_png.rf.6316f0f312cd4c8c93c77f83f5484af9.jpg: 640x640 8 with_masks, 37.1ms\n",
+            "Speed: 1.6ms preprocess, 37.1ms inference, 2.8ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss230_png.rf.1fe3136ab2b6bffc7cd0b6e65101870c.jpg: 640x640 5 with_masks, 37.1ms\n",
+            "Speed: 1.7ms preprocess, 37.1ms inference, 2.1ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss236_png.rf.ea526bb945fec0e07973f2cd052ef688.jpg: 640x640 1 without_mask, 37.1ms\n",
+            "Speed: 1.7ms preprocess, 37.1ms inference, 2.2ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss241_png.rf.01c103b7f1b42f6eaaa3f4c67d5e063a.jpg: 640x640 2 with_masks, 37.1ms\n",
+            "Speed: 2.3ms preprocess, 37.1ms inference, 2.1ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss242_png.rf.048ddfefd131055beb8263c92bbb62a8.jpg: 640x640 2 with_masks, 37.2ms\n",
+            "Speed: 1.8ms preprocess, 37.2ms inference, 2.3ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss244_png.rf.f9240dd571e5670cad3b769290bbd680.jpg: 640x640 1 with_mask, 2 without_masks, 37.2ms\n",
+            "Speed: 6.8ms preprocess, 37.2ms inference, 2.4ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss247_png.rf.f67e30adf66e59df979a1db74326bd5b.jpg: 640x640 14 with_masks, 37.2ms\n",
+            "Speed: 2.4ms preprocess, 37.2ms inference, 5.3ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss248_png.rf.c19d9460b893693e4b637a1f7df7008a.jpg: 640x640 1 without_mask, 37.1ms\n",
+            "Speed: 1.8ms preprocess, 37.1ms inference, 2.5ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss229_png.rf.45ba617a90c78bc0e8e547bffedbe3c3.jpg: 640x640 15 with_masks, 1 without_mask, 37.2ms\n",
+            "Speed: 2.0ms preprocess, 37.2ms inference, 2.7ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss253_png.rf.93b13ca348adf361296ed659d6acfe75.jpg: 640x640 7 with_masks, 5 without_masks, 38.7ms\n",
+            "Speed: 1.8ms preprocess, 38.7ms inference, 4.8ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss264_png.rf.7018fdf357ffc35189a710fdfc752b52.jpg: 640x640 7 with_masks, 37.2ms\n",
+            "Speed: 1.9ms preprocess, 37.2ms inference, 3.3ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss271_png.rf.cc2239f13f1ebcc7519a1b37fc36376a.jpg: 640x640 1 with_mask, 37.2ms\n",
+            "Speed: 3.9ms preprocess, 37.2ms inference, 2.3ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss277_png.rf.12d1ae22a19b53135a7172821eaf2559.jpg: 640x640 8 with_masks, 37.2ms\n",
+            "Speed: 1.8ms preprocess, 37.2ms inference, 3.0ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss282_png.rf.32d06bf0012896891f681325fa56166d.jpg: 640x640 11 with_masks, 1 without_mask, 37.1ms\n",
+            "Speed: 6.8ms preprocess, 37.1ms inference, 2.9ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss289_png.rf.fee0ba4040ee03de9c67793e8127c627.jpg: 640x640 2 without_masks, 37.2ms\n",
+            "Speed: 3.9ms preprocess, 37.2ms inference, 2.8ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n",
+            "      70/80      10.9G     0.7398     0.3749     0.9456        107        640: 100%|██████████| 106/106 [01:01<00:00,  1.73it/s]\n",
+            "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100%|██████████| 6/6 [00:02<00:00,  2.18it/s]\n",
+            "                   all        161        861      0.823       0.81      0.835      0.541\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss301_png.rf.79b160619414ca6a470bd5ea8b30ef4a.jpg: 640x640 1 mask_weared_incorrect, 19 with_masks, 3 without_masks, 50.3ms\n",
+            "Speed: 8.7ms preprocess, 50.3ms inference, 6.2ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss303_png.rf.f00ae35b4058b933e066d1d2a4d88c17.jpg: 640x640 2 with_masks, 37.2ms\n",
+            "Speed: 1.8ms preprocess, 37.2ms inference, 3.2ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss258_png.rf.fc7b4f2f14e1d199dce55985695d1120.jpg: 640x640 1 mask_weared_incorrect, 1 with_mask, 37.1ms\n",
+            "Speed: 1.5ms preprocess, 37.1ms inference, 2.2ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss304_png.rf.9df48cf93de57fa41d0a2b59de78a62c.jpg: 640x640 2 with_masks, 37.1ms\n",
+            "Speed: 2.0ms preprocess, 37.1ms inference, 2.2ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss224_png.rf.4539ed1dc0a709e4e01077ecf7bc2b22.jpg: 640x640 2 with_masks, 37.1ms\n",
+            "Speed: 1.8ms preprocess, 37.1ms inference, 2.1ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss20_png.rf.ca394d629ffaba1fdb13e432a79a5eb9.jpg: 640x640 4 with_masks, 37.1ms\n",
+            "Speed: 1.6ms preprocess, 37.1ms inference, 2.2ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss109_png.rf.3c26f7537566830dffb39c47f71e574e.jpg: 640x640 1 with_mask, 37.2ms\n",
+            "Speed: 1.8ms preprocess, 37.2ms inference, 3.3ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss114_png.rf.c087c8382ac2542ac89314fa0bbeb4f6.jpg: 640x640 1 with_mask, 1 without_mask, 37.2ms\n",
+            "Speed: 2.4ms preprocess, 37.2ms inference, 3.0ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss127_png.rf.1baab62c26cbf4478f2a8d99e1cf68de.jpg: 640x640 1 with_mask, 37.2ms\n",
+            "Speed: 2.0ms preprocess, 37.2ms inference, 2.5ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss146_png.rf.ec0da30308aa466d39bae79b0cc0e2bf.jpg: 640x640 3 with_masks, 37.2ms\n",
+            "Speed: 1.8ms preprocess, 37.2ms inference, 2.7ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss152_png.rf.c66bb39b29efc7503239890f834100dc.jpg: 640x640 7 with_masks, 40.8ms\n",
+            "Speed: 7.7ms preprocess, 40.8ms inference, 2.7ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss154_png.rf.7512e06f4e0bd3a2185ec1867603cc8a.jpg: 640x640 1 without_mask, 37.2ms\n",
+            "Speed: 1.9ms preprocess, 37.2ms inference, 3.0ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss168_png.rf.3b19cb741e672eef23c3f091fd204d52.jpg: 640x640 3 with_masks, 3 without_masks, 37.3ms\n",
+            "Speed: 1.9ms preprocess, 37.3ms inference, 3.3ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss217_png.rf.c4e305ead91154374bba4fc48e0e3b99.jpg: 640x640 1 without_mask, 37.2ms\n",
+            "Speed: 1.8ms preprocess, 37.2ms inference, 3.1ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss169_png.rf.49a3d702f1cd1ce83aa6cd01599e3644.jpg: 640x640 1 with_mask, 37.2ms\n",
+            "Speed: 1.8ms preprocess, 37.2ms inference, 2.8ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss174_png.rf.ba1760e663e246482b26e587332650b0.jpg: 640x640 4 with_masks, 37.2ms\n",
+            "Speed: 6.1ms preprocess, 37.2ms inference, 3.4ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss178_png.rf.2fd8857c96b9bed1982f78b55798a334.jpg: 640x640 2 with_masks, 1 without_mask, 37.2ms\n",
+            "Speed: 5.1ms preprocess, 37.2ms inference, 2.9ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss194_png.rf.77ed2eca9fe5235cf2496449dd156996.jpg: 640x640 2 with_masks, 37.3ms\n",
+            "Speed: 2.0ms preprocess, 37.3ms inference, 2.8ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss197_png.rf.cd0c6b120a0fae906bb417f825daf6a1.jpg: 640x640 1 with_mask, 37.2ms\n",
+            "Speed: 1.8ms preprocess, 37.2ms inference, 3.1ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss1_png.rf.e41f0052ad0e49cab0887d6e50e5a7eb.jpg: 640x640 7 with_masks, 1 without_mask, 37.2ms\n",
+            "Speed: 1.8ms preprocess, 37.2ms inference, 2.9ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss203_png.rf.eba7307a461c6b2098593e82d2cccecc.jpg: 640x640 4 with_masks, 37.9ms\n",
+            "Speed: 1.8ms preprocess, 37.9ms inference, 3.0ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss206_png.rf.68794173883f5ae26e2382a3087aac0b.jpg: 640x640 7 with_masks, 1 without_mask, 37.2ms\n",
+            "Speed: 3.0ms preprocess, 37.2ms inference, 2.2ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss172_png.rf.13bb93a8bf5266e0d73bab43f62e0376.jpg: 640x640 1 without_mask, 37.2ms\n",
+            "Speed: 1.8ms preprocess, 37.2ms inference, 2.1ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss306_png.rf.52a38aff8eebcfb7d90d0c7cac38fdec.jpg: 640x640 1 with_mask, 37.1ms\n",
+            "Speed: 2.8ms preprocess, 37.1ms inference, 2.1ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss307_png.rf.93b21e5a88a625f2a9284ff6253bd417.jpg: 640x640 2 mask_weared_incorrects, 1 with_mask, 1 without_mask, 37.3ms\n",
+            "Speed: 2.2ms preprocess, 37.3ms inference, 2.3ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss308_png.rf.61a249cc68e67a9cf66c2393f61080f2.jpg: 640x640 2 with_masks, 37.2ms\n",
+            "Speed: 2.1ms preprocess, 37.2ms inference, 2.4ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss402_png.rf.adb70e16aac43aa519466a4364f99311.jpg: 640x640 1 without_mask, 37.1ms\n",
+            "Speed: 1.8ms preprocess, 37.1ms inference, 2.1ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss408_png.rf.bb077fd8dd6090c8f22b2dfe4fb0b2dc.jpg: 640x640 8 with_masks, 3 without_masks, 37.3ms\n",
+            "Speed: 2.5ms preprocess, 37.3ms inference, 2.2ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss409_png.rf.a1da634820d49e7be38ce59f5f5887bb.jpg: 640x640 1 with_mask, 37.1ms\n",
+            "Speed: 1.9ms preprocess, 37.1ms inference, 2.0ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss410_png.rf.eaad04d3f7e7468f6a0a3d017306d6da.jpg: 640x640 1 mask_weared_incorrect, 20 with_masks, 3 without_masks, 37.1ms\n",
+            "Speed: 1.8ms preprocess, 37.1ms inference, 2.2ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss418_png.rf.432d10d262677cb69e95be55ca0c9125.jpg: 640x640 2 with_masks, 1 without_mask, 37.3ms\n",
+            "Speed: 1.8ms preprocess, 37.3ms inference, 2.2ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss421_png.rf.7ecb66f6ba285fd631717a3635a7dd71.jpg: 640x640 6 with_masks, 37.2ms\n",
+            "Speed: 1.8ms preprocess, 37.2ms inference, 2.6ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "Closing dataloader mosaic\n",
+            "\u001b[34m\u001b[1malbumentations: \u001b[0mBlur(p=0.01, blur_limit=(3, 7)), MedianBlur(p=0.01, blur_limit=(3, 7)), ToGray(p=0.01), CLAHE(p=0.01, clip_limit=(1, 4.0), tile_grid_size=(8, 8))\n",
+            "os.fork() was called. os.fork() is incompatible with multithreaded code, and JAX is multithreaded, so this will likely lead to a deadlock.\n",
+            "os.fork() was called. os.fork() is incompatible with multithreaded code, and JAX is multithreaded, so this will likely lead to a deadlock.\n",
+            "\n",
+            "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n",
+            "      71/80      10.9G      0.714     0.3269     0.9362         44        640: 100%|██████████| 106/106 [01:03<00:00,  1.66it/s]\n",
+            "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100%|██████████| 6/6 [00:03<00:00,  1.64it/s]\n",
+            "                   all        161        861        0.9      0.771      0.837      0.546\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss425_png.rf.b69c6da9a6c99fd8edfdad09f10582d2.jpg: 640x640 1 with_mask, 38.6ms\n",
+            "Speed: 2.0ms preprocess, 38.6ms inference, 3.4ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss400_png.rf.63c84ce5e3e0391c9509f77d2244755c.jpg: 640x640 3 with_masks, 37.2ms\n",
+            "Speed: 2.7ms preprocess, 37.2ms inference, 3.4ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss429_png.rf.0f9bc0b4f072650f40e985eefdce87df.jpg: 640x640 4 with_masks, 37.2ms\n",
+            "Speed: 1.9ms preprocess, 37.2ms inference, 3.4ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss438_png.rf.85978160d8cedb7d56a26e0d06e41f87.jpg: 640x640 4 with_masks, 37.2ms\n",
+            "Speed: 1.6ms preprocess, 37.2ms inference, 2.6ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss440_png.rf.641564d43589f6344bacc5d05d51da53.jpg: 640x640 1 mask_weared_incorrect, 9 with_masks, 1 without_mask, 37.1ms\n",
+            "Speed: 1.9ms preprocess, 37.1ms inference, 2.3ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss44_png.rf.b6697a646548922305672e657697750b.jpg: 640x640 4 with_masks, 1 without_mask, 37.2ms\n",
+            "Speed: 2.1ms preprocess, 37.2ms inference, 2.3ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss450_png.rf.8f5e0ff6c7228f1180f985685beb20d5.jpg: 640x640 4 with_masks, 37.1ms\n",
+            "Speed: 1.8ms preprocess, 37.1ms inference, 2.1ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss457_png.rf.60b3bf773c197a83826aae38a0cf2387.jpg: 640x640 4 with_masks, 1 without_mask, 37.1ms\n",
+            "Speed: 1.7ms preprocess, 37.1ms inference, 2.1ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss459_png.rf.73bd4ff56e948804a4c7d5cc9e2f98ef.jpg: 640x640 1 mask_weared_incorrect, 1 with_mask, 1 without_mask, 37.2ms\n",
+            "Speed: 2.5ms preprocess, 37.2ms inference, 2.1ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss45_png.rf.3b160c8afb75253926e1abf7b4972504.jpg: 640x640 1 with_mask, 1 without_mask, 37.1ms\n",
+            "Speed: 1.8ms preprocess, 37.1ms inference, 2.4ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss431_png.rf.c5e66fbd5f544edca4f20973ce5ecf08.jpg: 640x640 1 mask_weared_incorrect, 17 with_masks, 37.1ms\n",
+            "Speed: 1.9ms preprocess, 37.1ms inference, 2.2ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss395_png.rf.d0fd9e7ac741d7df48a86b7f291e9b49.jpg: 640x640 1 with_mask, 37.1ms\n",
+            "Speed: 1.8ms preprocess, 37.1ms inference, 2.0ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss389_png.rf.11956fb49c814dab304f0006b9075f71.jpg: 640x640 9 with_masks, 2 without_masks, 37.2ms\n",
+            "Speed: 1.6ms preprocess, 37.2ms inference, 2.2ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss388_png.rf.4847bd339895b2496b21a16876aca440.jpg: 640x640 1 mask_weared_incorrect, 10 with_masks, 8 without_masks, 37.1ms\n",
+            "Speed: 1.5ms preprocess, 37.1ms inference, 2.2ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss311_png.rf.8d4e3cc30ab76d6699d7f220a26286dd.jpg: 640x640 5 with_masks, 37.1ms\n",
+            "Speed: 1.5ms preprocess, 37.1ms inference, 2.4ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss313_png.rf.0d2ede745cca1bbc73883747763be4cb.jpg: 640x640 1 with_mask, 37.2ms\n",
+            "Speed: 1.8ms preprocess, 37.2ms inference, 2.8ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss315_png.rf.bdcb0e2cde8b888d72849bbf232bc644.jpg: 640x640 2 with_masks, 37.2ms\n",
+            "Speed: 1.9ms preprocess, 37.2ms inference, 2.3ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss31_png.rf.f71dabc8b32a5181ae4a7ec0724d169e.jpg: 640x640 2 with_masks, 37.2ms\n",
+            "Speed: 2.3ms preprocess, 37.2ms inference, 2.3ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss321_png.rf.d5ca9ccecbb235c5551003b177cd1d46.jpg: 640x640 1 mask_weared_incorrect, 1 with_mask, 1 without_mask, 37.1ms\n",
+            "Speed: 1.7ms preprocess, 37.1ms inference, 2.2ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss330_png.rf.ca2fe4eca45ae4b2bc6bb9fde6d39dff.jpg: 640x640 4 with_masks, 37.1ms\n",
+            "Speed: 1.8ms preprocess, 37.1ms inference, 2.3ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss338_png.rf.669c284dd81181d71654743a3ca9aeb3.jpg: 640x640 5 with_masks, 37.1ms\n",
+            "Speed: 2.0ms preprocess, 37.1ms inference, 2.2ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss339_png.rf.d26efdd756cada62599cd227994bbf56.jpg: 640x640 1 with_mask, 37.2ms\n",
+            "Speed: 2.0ms preprocess, 37.2ms inference, 2.1ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss343_png.rf.1c5c7bbcb828a1cf9d4d2584972083cb.jpg: 640x640 1 without_mask, 37.1ms\n",
+            "Speed: 2.1ms preprocess, 37.1ms inference, 2.0ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss351_png.rf.15436d1eb7080d7bae2e79d554a4d3cb.jpg: 640x640 1 with_mask, 37.2ms\n",
+            "Speed: 2.1ms preprocess, 37.2ms inference, 2.2ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss364_png.rf.74e470c60f166ba4ec1a268b153fa240.jpg: 640x640 3 with_masks, 37.2ms\n",
+            "Speed: 5.8ms preprocess, 37.2ms inference, 2.1ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss366_png.rf.433ea8f6b4fcab0d951b52116611c1be.jpg: 640x640 2 with_masks, 37.2ms\n",
+            "Speed: 1.8ms preprocess, 37.2ms inference, 2.4ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss368_png.rf.1d14fe4224d1b152c5e272d889fe3d45.jpg: 640x640 9 with_masks, 37.1ms\n",
+            "Speed: 2.3ms preprocess, 37.1ms inference, 2.2ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss374_png.rf.b51c420d86fc3a474ed557b5a230b51e.jpg: 640x640 4 with_masks, 1 without_mask, 37.1ms\n",
+            "Speed: 1.7ms preprocess, 37.1ms inference, 2.1ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss376_png.rf.ca418b2ffccc242892a1ab14657e8349.jpg: 640x640 8 with_masks, 37.1ms\n",
+            "Speed: 2.3ms preprocess, 37.1ms inference, 2.1ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss37_png.rf.60ce2ff44ae089a01d8f07ff2e0f00ad.jpg: 640x640 1 with_mask, 37.2ms\n",
+            "Speed: 1.9ms preprocess, 37.2ms inference, 2.5ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss387_png.rf.6d027b3075e33a4414cc245ec7435fcc.jpg: 640x640 1 mask_weared_incorrect, 3 with_masks, 37.1ms\n",
+            "Speed: 2.0ms preprocess, 37.1ms inference, 2.8ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss464_png.rf.b7d07a0f6aabc271e6bfbe039246786b.jpg: 640x640 7 with_masks, 37.2ms\n",
+            "Speed: 1.8ms preprocess, 37.2ms inference, 3.0ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n",
+            "      72/80        11G     0.6901     0.3235     0.9268         48        640: 100%|██████████| 106/106 [01:02<00:00,  1.71it/s]\n",
+            "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100%|██████████| 6/6 [00:03<00:00,  1.68it/s]\n",
+            "                   all        161        861       0.87       0.77      0.813      0.529\n",
+            "\n",
+            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss90_png.rf.bb3401c96e9aba7db607a9a5ac8d8f51.jpg: 640x640 11 with_masks, 47.8ms\n",
+            "Speed: 1.8ms preprocess, 47.8ms inference, 6.3ms postprocess per image at shape (1, 3, 640, 640)\n",
+            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
+            "\n",
+            "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n",
+            "      73/80        11G     0.6748      0.318     0.9196        167        640: 100%|██████████| 106/106 [00:59<00:00,  1.78it/s]\n",
+            "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100%|██████████| 6/6 [00:03<00:00,  1.90it/s]\n",
+            "                   all        161        861      0.865      0.776       0.83      0.547\n"
+          ]
+        }
+      ],
+      "source": [
+        "# Initialize YOLO Model\n",
+        "model = YOLO(\"yolov8m.pt\")\n",
+        "\n",
+        "# Add Weights & Biases callback for Ultralytics\n",
+        "add_wandb_callback(model, enable_model_checkpointing=True)\n",
+        "\n",
+        "# Train/fine-tune model\n",
+        "model.train(project=\"verihubs-tech-assessment\", data='/content/Face-Mask-Detection-1/data.yaml', epochs=80, device=[0])\n",
+        "model.val()\n",
+        "\n",
+        "# Finish the W&B run\n",
+        "wandb.finish()"
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {
+        "id": "93eWzFxhw5Ot"
+      },
+      "source": [
+        "# Model Evaluation"
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "source": [
+        "### Evaluate on test set"
+      ],
+      "metadata": {
+        "id": "bh2FD2tj38wQ"
+      }
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 9,
+      "metadata": {
+        "id": "_6Hm3i4Pw5Ot"
+      },
+      "outputs": [],
+      "source": [
+        "model = YOLO('best.pt', task='detect')"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 11,
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/"
+        },
+        "id": "eXetfgvw0gpM",
+        "outputId": "08a10b3d-fd98-46fb-ebab-67ea7c4cf68c"
+      },
+      "outputs": [
+        {
+          "output_type": "stream",
+          "name": "stderr",
+          "text": [
+            "Ultralytics YOLOv8.0.186 🚀 Python-3.10.12 torch-2.3.0+cu121 CUDA:0 (Tesla T4, 15102MiB)\n",
+            "Downloading https://ultralytics.com/assets/Arial.ttf to '/root/.config/Ultralytics/Arial.ttf'...\n",
+            "100%|██████████| 755k/755k [00:00<00:00, 62.4MB/s]\n",
+            "\u001b[34m\u001b[1mval: \u001b[0mScanning /content/Face-Mask-Detection-1/valid/labels... 161 images, 0 backgrounds, 0 corrupt: 100%|██████████| 161/161 [00:00<00:00, 1699.32it/s]\n",
+            "\u001b[34m\u001b[1mval: \u001b[0mNew cache created: /content/Face-Mask-Detection-1/valid/labels.cache\n",
+            "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100%|██████████| 11/11 [00:11<00:00,  1.06s/it]\n",
+            "                   all        161        861        0.9      0.772      0.837      0.547\n",
+            " mask_weared_incorrect        161         28      0.891      0.643      0.735      0.486\n",
+            "             with_mask        161        720      0.935      0.902      0.944      0.648\n",
+            "          without_mask        161        113      0.876       0.77      0.831      0.508\n",
+            "Speed: 5.0ms preprocess, 22.5ms inference, 0.0ms loss, 7.2ms postprocess per image\n",
+            "Results saved to \u001b[1mruns/detect/val2\u001b[0m\n"
+          ]
+        },
+        {
+          "output_type": "execute_result",
+          "data": {
+            "text/plain": [
+              "ultralytics.utils.metrics.DetMetrics object with attributes:\n",
+              "\n",
+              "ap_class_index: array([0, 1, 2])\n",
+              "box: ultralytics.utils.metrics.Metric object\n",
+              "confusion_matrix: <ultralytics.utils.metrics.ConfusionMatrix object at 0x7c0dd57b3550>\n",
+              "fitness: 0.5763262590985345\n",
+              "keys: ['metrics/precision(B)', 'metrics/recall(B)', 'metrics/mAP50(B)', 'metrics/mAP50-95(B)']\n",
+              "maps: array([     0.4858,      0.6481,     0.50819])\n",
+              "names: {0: 'mask_weared_incorrect', 1: 'with_mask', 2: 'without_mask'}\n",
+              "plot: True\n",
+              "results_dict: {'metrics/precision(B)': 0.9004291228691308, 'metrics/recall(B)': 0.7716073384676143, 'metrics/mAP50(B)': 0.8370097832892117, 'metrics/mAP50-95(B)': 0.5473614230773481, 'fitness': 0.5763262590985345}\n",
+              "save_dir: PosixPath('runs/detect/val2')\n",
+              "speed: {'preprocess': 5.027679182727885, 'inference': 22.499906350366818, 'loss': 0.001861441949879901, 'postprocess': 7.183861288224689}"
+            ]
+          },
+          "metadata": {},
+          "execution_count": 11
+        }
+      ],
+      "source": [
+        "model.val()"
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "source": [
+        "When I tested the model on test set, I got 83.7% mAP@50 and 54.7% map@50-95 on all classess.\n",
+        "\n",
+        "\n",
+        "See the inference results here https://wandb.ai/anakbangkit/verihubs-tech-assessment/reports/AI-Engineer-Study-Case-Report-Manfred-Michael--Vmlldzo4MDYxNjkx"
+      ],
+      "metadata": {
+        "id": "N9nch27T3Tox"
+      }
+    },
+    {
+      "cell_type": "markdown",
+      "source": [
+        "> **Note**: From the wandb report above, we could see that the incorrectly weared mask is the hardest to detect."
+      ],
+      "metadata": {
+        "id": "Mj6A1Fbc_w-M"
+      }
+    },
+    {
+      "cell_type": "markdown",
+      "source": [
+        "### WandB Tracking Results"
+      ],
+      "metadata": {
+        "id": "DkmorRd54C86"
+      }
+    },
+    {
+      "cell_type": "markdown",
+      "source": [
+        "You can see the full report here - https://wandb.ai/anakbangkit/verihubs-tech-assessment/reports/AI-Engineer-Study-Case-Report-Manfred-Michael--Vmlldzo4MDYxNjkx"
+      ],
+      "metadata": {
+        "id": "SsH3PZdp7FAb"
+      }
+    },
+    {
+      "cell_type": "markdown",
+      "source": [
+        "#### Confusion Matrix"
+      ],
+      "metadata": {
+        "id": "b3H7GOmG4vpS"
+      }
+    },
+    {
+      "cell_type": "markdown",
+      "source": [
+        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)"
+      ],
+      "metadata": {
+        "id": "iiEppGVg_b-T"
+      }
+    },
+    {
+      "cell_type": "markdown",
+      "source": [
+        "#### mean Average Precision"
+      ],
+      "metadata": {
+        "id": "gqhAfDv45U72"
+      }
+    },
+    {
+      "cell_type": "markdown",
+      "source": [
+        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)"
+      ],
+      "metadata": {
+        "id": "G-rjoAqg5LPW"
+      }
+    },
+    {
+      "cell_type": "markdown",
+      "source": [
+        "# Calculate Inference Speed"
+      ],
+      "metadata": {
+        "id": "q-H53qT45ryn"
+      }
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 24,
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 310,
+          "referenced_widgets": [
+            "99f163adc5d743839dd82733209496c3",
+            "8bf3e79c28314bfe92b1462ca08d65fb",
+            "8edf70b4aa984bc09da31c8be7b9405b",
+            "6d09eff9fa5546b592186984c5bddd86",
+            "3b96f0b655104800bf2ef4504660e9fb",
+            "3d8af422cf854c08b9cabcdc10f63f32",
+            "1af10357ef5d4a6dac6d67277ff093b5",
+            "2733a301ee7e448684399bdcb81eddc2"
+          ]
+        },
+        "id": "9WGkhvfXSijI",
+        "outputId": "dfce0c30-2e08-4d82-9c83-4c6b6930ee1d"
+      },
+      "outputs": [
+        {
+          "output_type": "display_data",
+          "data": {
+            "text/plain": [
+              "<IPython.core.display.HTML object>"
+            ],
+            "text/html": [
+              "Finishing last run (ID:uvj29u8v) before initializing another..."
+            ]
+          },
+          "metadata": {}
+        },
+        {
+          "output_type": "display_data",
+          "data": {
+            "text/plain": [
+              "<IPython.core.display.HTML object>"
+            ],
+            "text/html": [
+              "Waiting for W&B process to finish... <strong style=\"color:green\">(success).</strong>"
+            ]
+          },
+          "metadata": {}
+        },
+        {
+          "output_type": "display_data",
+          "data": {
+            "text/plain": [
+              "VBox(children=(Label(value='0.001 MB of 0.013 MB uploaded (0.000 MB deduped)\\r'), FloatProgress(value=0.094515…"
+            ],
+            "application/vnd.jupyter.widget-view+json": {
+              "version_major": 2,
+              "version_minor": 0,
+              "model_id": "99f163adc5d743839dd82733209496c3"
+            }
+          },
+          "metadata": {}
+        },
+        {
+          "output_type": "display_data",
+          "data": {
+            "text/plain": [
+              "<IPython.core.display.HTML object>"
+            ],
+            "text/html": [
+              " View run <strong style=\"color:#cdcd00\">visionary-eon-7</strong> at: <a href='https://wandb.ai/anakbangkit/verihubs-tech-assessment/runs/uvj29u8v' target=\"_blank\">https://wandb.ai/anakbangkit/verihubs-tech-assessment/runs/uvj29u8v</a><br/>Synced 5 W&B file(s), 0 media file(s), 0 artifact file(s) and 0 other file(s)"
+            ]
+          },
+          "metadata": {}
+        },
+        {
+          "output_type": "display_data",
+          "data": {
+            "text/plain": [
+              "<IPython.core.display.HTML object>"
+            ],
+            "text/html": [
+              "Find logs at: <code>./wandb/run-20240522_235650-uvj29u8v/logs</code>"
+            ]
+          },
+          "metadata": {}
+        },
+        {
+          "output_type": "display_data",
+          "data": {
+            "text/plain": [
+              "<IPython.core.display.HTML object>"
+            ],
+            "text/html": [
+              "Successfully finished last run (ID:uvj29u8v). Initializing new run:<br/>"
+            ]
+          },
+          "metadata": {}
+        },
+        {
+          "output_type": "display_data",
+          "data": {
+            "text/plain": [
+              "<IPython.core.display.HTML object>"
+            ],
+            "text/html": [
+              "wandb version 0.17.0 is available!  To upgrade, please run:\n",
+              " $ pip install wandb --upgrade"
+            ]
+          },
+          "metadata": {}
+        },
+        {
+          "output_type": "display_data",
+          "data": {
+            "text/plain": [
+              "<IPython.core.display.HTML object>"
+            ],
+            "text/html": [
+              "Tracking run with wandb version 0.15.12"
+            ]
+          },
+          "metadata": {}
+        },
+        {
+          "output_type": "display_data",
+          "data": {
+            "text/plain": [
+              "<IPython.core.display.HTML object>"
+            ],
+            "text/html": [
+              "Run data is saved locally in <code>/content/wandb/run-20240523_000329-47wmvauk</code>"
+            ]
+          },
+          "metadata": {}
+        },
+        {
+          "output_type": "display_data",
+          "data": {
+            "text/plain": [
+              "<IPython.core.display.HTML object>"
+            ],
+            "text/html": [
+              "Syncing run <strong><a href='https://wandb.ai/anakbangkit/verihubs-tech-assessment/runs/47wmvauk' target=\"_blank\">fanciful-snowball-8</a></strong> to <a href='https://wandb.ai/anakbangkit/verihubs-tech-assessment' target=\"_blank\">Weights & Biases</a> (<a href='https://wandb.me/run' target=\"_blank\">docs</a>)<br/>"
+            ]
+          },
+          "metadata": {}
+        },
+        {
+          "output_type": "display_data",
+          "data": {
+            "text/plain": [
+              "<IPython.core.display.HTML object>"
+            ],
+            "text/html": [
+              " View project at <a href='https://wandb.ai/anakbangkit/verihubs-tech-assessment' target=\"_blank\">https://wandb.ai/anakbangkit/verihubs-tech-assessment</a>"
+            ]
+          },
+          "metadata": {}
+        },
+        {
+          "output_type": "display_data",
+          "data": {
+            "text/plain": [
+              "<IPython.core.display.HTML object>"
+            ],
+            "text/html": [
+              " View run at <a href='https://wandb.ai/anakbangkit/verihubs-tech-assessment/runs/47wmvauk' target=\"_blank\">https://wandb.ai/anakbangkit/verihubs-tech-assessment/runs/47wmvauk</a>"
+            ]
+          },
+          "metadata": {}
+        },
+        {
+          "output_type": "execute_result",
+          "data": {
+            "text/html": [
+              "<button onClick=\"this.nextSibling.style.display='block';this.style.display='none';\">Display W&B run</button><iframe src='https://wandb.ai/anakbangkit/verihubs-tech-assessment/runs/47wmvauk?jupyter=true' style='border:none;width:100%;height:420px;display:none;'></iframe>"
+            ],
+            "text/plain": [
+              "<wandb.sdk.wandb_run.Run at 0x7c0ccfee1360>"
+            ]
+          },
+          "metadata": {},
+          "execution_count": 24
+        }
+      ],
+      "source": [
+        "wandb.init(project=\"verihubs-tech-assessment\", job_type=\"evaluation\")"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 25,
+      "metadata": {
+        "id": "Y8iCmJYpw5Ou"
+      },
+      "outputs": [],
+      "source": [
+        "model_best = YOLO('/content/best.pt', task='detect')"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 26,
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/"
+        },
+        "id": "5AIYedpzYy6R",
+        "outputId": "d38f2424-7d55-4cd9-b4e1-1b9b5f9aa57a"
+      },
+      "outputs": [
+        {
+          "output_type": "stream",
+          "name": "stderr",
+          "text": [
+            "\n",
+            "0: 640x640 2 with_masks, 1: 640x640 3 with_masks, 2: 640x640 3 with_masks, 1 without_mask, 3: 640x640 1 mask_weared_incorrect, 4: 640x640 5 mask_weared_incorrects, 2 with_masks, 1 without_mask, 157.9ms\n",
+            "Speed: 2.8ms preprocess, 31.6ms inference, 1.4ms postprocess per image at shape (1, 3, 640, 640)\n"
+          ]
+        }
+      ],
+      "source": [
+        "import glob\n",
+        "test_img_paths = glob.glob(\"/content/test-images/*\")\n",
+        "\n",
+        "imgs = [Image.open(path) for path in test_img_paths]\n",
+        "\n",
+        "results = model_best(imgs)"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 27,
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/"
+        },
+        "id": "20yvojD1Y8Qu",
+        "outputId": "beebafab-647b-44f9-8e1f-b07ec4a8068d"
+      },
+      "outputs": [
+        {
+          "output_type": "stream",
+          "name": "stdout",
+          "text": [
+            "/content/test-images/106757648-1603404475911-gettyimages-1281710356-nng_6210_2020102252211420.jpeg\n",
+            "{'preprocess': 2.7736663818359375, 'inference': 31.577253341674805, 'postprocess': 1.3605594635009766}\n",
+            "/content/test-images/download (1).jpg\n",
+            "{'preprocess': 2.7736663818359375, 'inference': 31.577253341674805, 'postprocess': 1.3605594635009766}\n",
+            "/content/test-images/Women-wearing-facemasks-while-walking-outdoors-Milan-Italy-February-2020-coronavirus-COVID-19.webp\n",
+            "{'preprocess': 2.7736663818359375, 'inference': 31.577253341674805, 'postprocess': 1.3605594635009766}\n",
+            "/content/test-images/download (2).jpg\n",
+            "{'preprocess': 2.7736663818359375, 'inference': 31.577253341674805, 'postprocess': 1.3605594635009766}\n",
+            "/content/test-images/images (5).jpg\n",
+            "{'preprocess': 2.7736663818359375, 'inference': 31.577253341674805, 'postprocess': 1.3605594635009766}\n"
+          ]
+        }
+      ],
+      "source": [
+        "for result in results:\n",
+        "    print(result.path)\n",
+        "    print(result.speed)"
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "source": [
+        "Here we get 31ms latency on inference"
+      ],
+      "metadata": {
+        "id": "Gls-sFvR5y0V"
+      }
+    },
+    {
+      "cell_type": "markdown",
+      "source": [
+        "# Reduce Inference Speed"
+      ],
+      "metadata": {
+        "id": "73D6BcSl6lEH"
+      }
+    },
+    {
+      "cell_type": "markdown",
+      "source": [
+        "\n",
+        "### Quantize the model"
+      ],
+      "metadata": {
+        "id": "XECaJUUh7SFq"
+      }
+    },
+    {
+      "cell_type": "markdown",
+      "source": [
+        "In this step, I will export the model with int8 quantization."
+      ],
+      "metadata": {
+        "id": "OCr4aSt66p1N"
+      }
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 28,
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 264
+        },
+        "id": "_Q2VJ0QPZJaA",
+        "outputId": "e91223e7-b1e9-4fbc-bc12-078d5e5a03f2"
+      },
+      "outputs": [
+        {
+          "output_type": "stream",
+          "name": "stderr",
+          "text": [
+            "Ultralytics YOLOv8.0.186 🚀 Python-3.10.12 torch-2.3.0+cu121 CPU (Intel Xeon 2.00GHz)\n",
+            "\n",
+            "\u001b[34m\u001b[1mPyTorch:\u001b[0m starting from '/content/best.pt' with input shape (1, 3, 640, 640) BCHW and output shape(s) (1, 7, 8400) (296.6 MB)\n",
+            "\n",
+            "\u001b[34m\u001b[1mTorchScript:\u001b[0m starting export with torch 2.3.0+cu121...\n",
+            "\u001b[34m\u001b[1mTorchScript:\u001b[0m export success ✅ 8.3s, saved as '/content/best.torchscript' (99.1 MB)\n",
+            "\n",
+            "Export complete (11.5s)\n",
+            "Results saved to \u001b[1m/content\u001b[0m\n",
+            "Predict:         yolo predict task=detect model=/content/best.torchscript imgsz=640 int8 \n",
+            "Validate:        yolo val task=detect model=/content/best.torchscript imgsz=640 data=/content/Face-Mask-Detection-1/data.yaml int8 \n",
+            "Visualize:       https://netron.app\n"
+          ]
+        },
+        {
+          "output_type": "execute_result",
+          "data": {
+            "text/plain": [
+              "'/content/best.torchscript'"
+            ],
+            "application/vnd.google.colaboratory.intrinsic+json": {
+              "type": "string"
+            }
+          },
+          "metadata": {},
+          "execution_count": 28
+        }
+      ],
+      "source": [
+        "model_best.export(format='torchscript', int8=True)"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 29,
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 307,
+          "referenced_widgets": [
+            "87507ff80bed4339b98615f17f631f9a",
+            "a709b4b5e31b492f9faee82fac4e5dcb",
+            "21910808f6224ecf98625a62a2546c2a",
+            "58c3b2fffd5e465fb90ef94386c55316",
+            "565aa378b65f4e4d9c741cf49f74cc93",
+            "5cc53119d8e647b082e65550c5eeed76",
+            "0770f30f33b94ec2a1f035a113229c60",
+            "91a7bdb462134402992cb9035fb92ede"
+          ]
+        },
+        "id": "c-8F6pUjSgMN",
+        "outputId": "5fd253b6-05e5-44d3-ec12-0810a80753bf"
+      },
+      "outputs": [
+        {
+          "output_type": "display_data",
+          "data": {
+            "text/plain": [
+              "<IPython.core.display.HTML object>"
+            ],
+            "text/html": [
+              "Finishing last run (ID:47wmvauk) before initializing another..."
+            ]
+          },
+          "metadata": {}
+        },
+        {
+          "output_type": "display_data",
+          "data": {
+            "text/plain": [
+              "<IPython.core.display.HTML object>"
+            ],
+            "text/html": [
+              "Waiting for W&B process to finish... <strong style=\"color:green\">(success).</strong>"
+            ]
+          },
+          "metadata": {}
+        },
+        {
+          "output_type": "display_data",
+          "data": {
+            "text/plain": [
+              "VBox(children=(Label(value='0.001 MB of 0.001 MB uploaded (0.000 MB deduped)\\r'), FloatProgress(value=1.0, max…"
+            ],
+            "application/vnd.jupyter.widget-view+json": {
+              "version_major": 2,
+              "version_minor": 0,
+              "model_id": "87507ff80bed4339b98615f17f631f9a"
+            }
+          },
+          "metadata": {}
+        },
+        {
+          "output_type": "display_data",
+          "data": {
+            "text/plain": [
+              "<IPython.core.display.HTML object>"
+            ],
+            "text/html": [
+              " View run <strong style=\"color:#cdcd00\">fanciful-snowball-8</strong> at: <a href='https://wandb.ai/anakbangkit/verihubs-tech-assessment/runs/47wmvauk' target=\"_blank\">https://wandb.ai/anakbangkit/verihubs-tech-assessment/runs/47wmvauk</a><br/>Synced 5 W&B file(s), 0 media file(s), 0 artifact file(s) and 0 other file(s)"
+            ]
+          },
+          "metadata": {}
+        },
+        {
+          "output_type": "display_data",
+          "data": {
+            "text/plain": [
+              "<IPython.core.display.HTML object>"
+            ],
+            "text/html": [
+              "Find logs at: <code>./wandb/run-20240523_000329-47wmvauk/logs</code>"
+            ]
+          },
+          "metadata": {}
+        },
+        {
+          "output_type": "display_data",
+          "data": {
+            "text/plain": [
+              "<IPython.core.display.HTML object>"
+            ],
+            "text/html": [
+              "Successfully finished last run (ID:47wmvauk). Initializing new run:<br/>"
+            ]
+          },
+          "metadata": {}
+        },
+        {
+          "output_type": "display_data",
+          "data": {
+            "text/plain": [
+              "<IPython.core.display.HTML object>"
+            ],
+            "text/html": [
+              "wandb version 0.17.0 is available!  To upgrade, please run:\n",
+              " $ pip install wandb --upgrade"
+            ]
+          },
+          "metadata": {}
+        },
+        {
+          "output_type": "display_data",
+          "data": {
+            "text/plain": [
+              "<IPython.core.display.HTML object>"
+            ],
+            "text/html": [
+              "Tracking run with wandb version 0.15.12"
+            ]
+          },
+          "metadata": {}
+        },
+        {
+          "output_type": "display_data",
+          "data": {
+            "text/plain": [
+              "<IPython.core.display.HTML object>"
+            ],
+            "text/html": [
+              "Run data is saved locally in <code>/content/wandb/run-20240523_000806-tv5b30zu</code>"
+            ]
+          },
+          "metadata": {}
+        },
+        {
+          "output_type": "display_data",
+          "data": {
+            "text/plain": [
+              "<IPython.core.display.HTML object>"
+            ],
+            "text/html": [
+              "Syncing run <strong><a href='https://wandb.ai/anakbangkit/verihubs-tech-assessment/runs/tv5b30zu' target=\"_blank\">divine-pond-9</a></strong> to <a href='https://wandb.ai/anakbangkit/verihubs-tech-assessment' target=\"_blank\">Weights & Biases</a> (<a href='https://wandb.me/run' target=\"_blank\">docs</a>)<br/>"
+            ]
+          },
+          "metadata": {}
+        },
+        {
+          "output_type": "display_data",
+          "data": {
+            "text/plain": [
+              "<IPython.core.display.HTML object>"
+            ],
+            "text/html": [
+              " View project at <a href='https://wandb.ai/anakbangkit/verihubs-tech-assessment' target=\"_blank\">https://wandb.ai/anakbangkit/verihubs-tech-assessment</a>"
+            ]
+          },
+          "metadata": {}
+        },
+        {
+          "output_type": "display_data",
+          "data": {
+            "text/plain": [
+              "<IPython.core.display.HTML object>"
+            ],
+            "text/html": [
+              " View run at <a href='https://wandb.ai/anakbangkit/verihubs-tech-assessment/runs/tv5b30zu' target=\"_blank\">https://wandb.ai/anakbangkit/verihubs-tech-assessment/runs/tv5b30zu</a>"
+            ]
+          },
+          "metadata": {}
+        },
+        {
+          "output_type": "execute_result",
+          "data": {
+            "text/plain": [
+              "YOLO()"
+            ]
+          },
+          "metadata": {},
+          "execution_count": 29
+        }
+      ],
+      "source": [
+        "wandb.init(project=\"verihubs-tech-assessment\", job_type=\"evaluation\")\n",
+        "\n",
+        "model_int8 = YOLO('/content/best.torchscript', task='detect')\n",
+        "add_wandb_callback(model_int8, enable_model_checkpointing=True)"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 30,
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 138,
+          "referenced_widgets": [
+            "c699954b34a24c50a28c70361badd803",
+            "baee1aa3f5c741e1a531846fd98ac771",
+            "ab714c6388af49ee8da67cddff061443",
+            "d94d1a3b8f4343bea6ff0f19b0bd4443",
+            "96763df4270946caaf2961a07c699c0a",
+            "c504e93947ae4a2d9ecfe2615e0c9cc6",
+            "1c56b744165b4093b5941feb56a73785",
+            "e4bd657fbd7d40bda45409ea8f17c27a",
+            "d1a8603b2d6d462ea3f977fc8ac6e306",
+            "14199fca456249eaadcec5700d1857d3",
+            "c369e26eeb36461a9a06db2ba7658472"
+          ]
+        },
+        "id": "a7g50M8RaMgG",
+        "outputId": "0f7bf76a-8a7f-4fb4-e3d8-342d0231e1dc"
+      },
+      "outputs": [
+        {
+          "output_type": "stream",
+          "name": "stderr",
+          "text": [
+            "Loading /content/best.torchscript for TorchScript inference...\n",
+            "\n",
+            "0: 640x640 2 with_masks, 1: 640x640 3 with_masks, 2: 640x640 3 with_masks, 1 without_mask, 3: 640x640 1 mask_weared_incorrect, 4: 640x640 5 mask_weared_incorrects, 2 with_masks, 1 without_mask, 109.6ms\n",
+            "Speed: 2.2ms preprocess, 21.9ms inference, 1.2ms postprocess per image at shape (1, 3, 640, 640)\n"
+          ]
+        },
+        {
+          "output_type": "display_data",
+          "data": {
+            "text/plain": [
+              "  0%|          | 0/5 [00:00<?, ?it/s]"
+            ],
+            "application/vnd.jupyter.widget-view+json": {
+              "version_major": 2,
+              "version_minor": 0,
+              "model_id": "c699954b34a24c50a28c70361badd803"
+            }
+          },
+          "metadata": {}
+        }
+      ],
+      "source": [
+        "imgs = [Image.open(path) for path in test_img_paths]\n",
+        "results = model_int8(imgs)"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 31,
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/"
+        },
+        "id": "P2LIaT0rWcos",
+        "outputId": "a94286ba-f875-4cb3-db2c-b5db38dfc0e1"
+      },
+      "outputs": [
+        {
+          "output_type": "stream",
+          "name": "stdout",
+          "text": [
+            "/content/test-images/106757648-1603404475911-gettyimages-1281710356-nng_6210_2020102252211420.jpeg\n",
+            "{'preprocess': 2.2184371948242188, 'inference': 21.917200088500977, 'postprocess': 1.1716365814208984}\n",
+            "/content/test-images/download (1).jpg\n",
+            "{'preprocess': 2.2184371948242188, 'inference': 21.917200088500977, 'postprocess': 1.1716365814208984}\n",
+            "/content/test-images/Women-wearing-facemasks-while-walking-outdoors-Milan-Italy-February-2020-coronavirus-COVID-19.webp\n",
+            "{'preprocess': 2.2184371948242188, 'inference': 21.917200088500977, 'postprocess': 1.1716365814208984}\n",
+            "/content/test-images/download (2).jpg\n",
+            "{'preprocess': 2.2184371948242188, 'inference': 21.917200088500977, 'postprocess': 1.1716365814208984}\n",
+            "/content/test-images/images (5).jpg\n",
+            "{'preprocess': 2.2184371948242188, 'inference': 21.917200088500977, 'postprocess': 1.1716365814208984}\n"
+          ]
+        }
+      ],
+      "source": [
+        "for result in results:\n",
+        "    print(result.path)\n",
+        "    print(result.speed)"
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "source": [
+        "After quantization, we get 21ms on inference. 29% reduction in inference time!"
+      ],
+      "metadata": {
+        "id": "GJ6R3zBfaOF6"
+      }
+    },
+    {
+      "cell_type": "markdown",
+      "source": [
+        "### Evaluate after quantization"
+      ],
+      "metadata": {
+        "id": "8CoxoiUI7PzH"
+      }
+    },
+    {
+      "cell_type": "markdown",
+      "source": [
+        "Now let's test the model after quantizatoin"
+      ],
+      "metadata": {
+        "id": "MYH6jwg87Yhb"
+      }
+    },
+    {
+      "cell_type": "code",
+      "source": [
+        "model_int8 = YOLO('/content/best.torchscript', task='detect')\n",
+        "model_int8.val(data='/content/Face-Mask-Detection-1/data.yaml', imgsz=640)"
+      ],
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/"
+        },
+        "id": "GC23AVk_7XZI",
+        "outputId": "a03a3b1d-9d64-4dab-e15d-4429bd000fef"
+      },
+      "execution_count": 32,
+      "outputs": [
+        {
+          "output_type": "stream",
+          "name": "stderr",
+          "text": [
+            "Ultralytics YOLOv8.0.186 🚀 Python-3.10.12 torch-2.3.0+cu121 CUDA:0 (Tesla T4, 15102MiB)\n",
+            "Loading /content/best.torchscript for TorchScript inference...\n",
+            "\u001b[34m\u001b[1mval: \u001b[0mScanning /content/Face-Mask-Detection-1/valid/labels.cache... 161 images, 0 backgrounds, 0 corrupt: 100%|██████████| 161/161 [00:00<?, ?it/s]\n",
+            "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100%|██████████| 11/11 [00:08<00:00,  1.28it/s]\n",
+            "                   all        161        861      0.847      0.795      0.829      0.543\n",
+            " mask_weared_incorrect        161         28      0.809      0.679      0.722      0.482\n",
+            "             with_mask        161        720      0.912       0.91      0.939      0.639\n",
+            "          without_mask        161        113      0.818      0.796      0.825      0.506\n",
+            "Speed: 4.7ms preprocess, 19.8ms inference, 0.0ms loss, 1.5ms postprocess per image\n",
+            "Results saved to \u001b[1mruns/detect/val3\u001b[0m\n"
+          ]
+        },
+        {
+          "output_type": "execute_result",
+          "data": {
+            "text/plain": [
+              "ultralytics.utils.metrics.DetMetrics object with attributes:\n",
+              "\n",
+              "ap_class_index: array([0, 1, 2])\n",
+              "box: ultralytics.utils.metrics.Metric object\n",
+              "confusion_matrix: <ultralytics.utils.metrics.ConfusionMatrix object at 0x7c0ccecef5b0>\n",
+              "fitness: 0.571245528142035\n",
+              "keys: ['metrics/precision(B)', 'metrics/recall(B)', 'metrics/mAP50(B)', 'metrics/mAP50-95(B)']\n",
+              "maps: array([    0.48219,     0.63923,     0.50649])\n",
+              "names: {0: 'mask_weared_incorrect', 1: 'with_mask', 2: 'without_mask'}\n",
+              "plot: True\n",
+              "results_dict: {'metrics/precision(B)': 0.846657158388935, 'metrics/recall(B)': 0.7949851975707888, 'metrics/mAP50(B)': 0.8287328115265163, 'metrics/mAP50-95(B)': 0.5426358299882038, 'fitness': 0.571245528142035}\n",
+              "save_dir: PosixPath('runs/detect/val3')\n",
+              "speed: {'preprocess': 4.6583658419780845, 'inference': 19.83749052012189, 'loss': 0.03296692178856512, 'postprocess': 1.5373052277179977}"
+            ]
+          },
+          "metadata": {},
+          "execution_count": 32
+        }
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+      "cell_type": "markdown",
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+        "Now we get 82.9% mAP@50 and 54.4% map@50-95. A very similar performance with only 2/3 of the original inference time!"
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