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{
  "cells": [
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "rymoKnbpwtLs",
        "outputId": "fa54be62-5f73-49b9-d4c8-b406f8cf0373"
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "Requirement already satisfied: pip in /usr/local/lib/python3.10/dist-packages (24.0)\n",
            "Requirement already satisfied: setuptools in /usr/local/lib/python3.10/dist-packages (69.5.1)\n",
            "\u001b[33mWARNING: Running pip as the 'root' user can result in broken permissions and conflicting behaviour with the system package manager. It is recommended to use a virtual environment instead: https://pip.pypa.io/warnings/venv\u001b[0m\u001b[33m\n",
            "\u001b[0m"
          ]
        }
      ],
      "source": [
        "!pip install --upgrade pip setuptools"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "kZ9-Fb95_7Z8",
        "outputId": "40ef73fe-989b-4eb8-a576-3db6fd271ed0"
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "Requirement already satisfied: fastai in /usr/local/lib/python3.10/dist-packages (2.7.15)\n",
            "Requirement already satisfied: pip in /usr/local/lib/python3.10/dist-packages (from fastai) (24.0)\n",
            "Requirement already satisfied: packaging in /usr/local/lib/python3.10/dist-packages (from fastai) (24.0)\n",
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            "Requirement already satisfied: fastcore<1.6,>=1.5.29 in /usr/local/lib/python3.10/dist-packages (from fastai) (1.5.33)\n",
            "Requirement already satisfied: torchvision>=0.11 in /usr/local/lib/python3.10/dist-packages (from fastai) (0.17.1+cu121)\n",
            "Requirement already satisfied: matplotlib in /usr/local/lib/python3.10/dist-packages (from fastai) (3.7.1)\n",
            "Requirement already satisfied: pandas in /usr/local/lib/python3.10/dist-packages (from fastai) (2.0.3)\n",
            "Requirement already satisfied: requests in /usr/local/lib/python3.10/dist-packages (from fastai) (2.31.0)\n",
            "Requirement already satisfied: pyyaml in /usr/local/lib/python3.10/dist-packages (from fastai) (6.0.1)\n",
            "Requirement already satisfied: fastprogress>=0.2.4 in /usr/local/lib/python3.10/dist-packages (from fastai) (1.0.3)\n",
            "Requirement already satisfied: pillow>=9.0.0 in /usr/local/lib/python3.10/dist-packages (from fastai) (9.4.0)\n",
            "Requirement already satisfied: scikit-learn in /usr/local/lib/python3.10/dist-packages (from fastai) (1.2.2)\n",
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            "Requirement already satisfied: spacy<4 in /usr/local/lib/python3.10/dist-packages (from fastai) (3.7.4)\n",
            "Requirement already satisfied: torch<2.4,>=1.10 in /usr/local/lib/python3.10/dist-packages (from fastai) (2.2.1+cu121)\n",
            "Requirement already satisfied: spacy-legacy<3.1.0,>=3.0.11 in /usr/local/lib/python3.10/dist-packages (from spacy<4->fastai) (3.0.12)\n",
            "Requirement already satisfied: spacy-loggers<2.0.0,>=1.0.0 in /usr/local/lib/python3.10/dist-packages (from spacy<4->fastai) (1.0.5)\n",
            "Requirement already satisfied: murmurhash<1.1.0,>=0.28.0 in /usr/local/lib/python3.10/dist-packages (from spacy<4->fastai) (1.0.10)\n",
            "Requirement already satisfied: cymem<2.1.0,>=2.0.2 in /usr/local/lib/python3.10/dist-packages (from spacy<4->fastai) (2.0.8)\n",
            "Requirement already satisfied: preshed<3.1.0,>=3.0.2 in /usr/local/lib/python3.10/dist-packages (from spacy<4->fastai) (3.0.9)\n",
            "Requirement already satisfied: thinc<8.3.0,>=8.2.2 in /usr/local/lib/python3.10/dist-packages (from spacy<4->fastai) (8.2.3)\n",
            "Requirement already satisfied: wasabi<1.2.0,>=0.9.1 in /usr/local/lib/python3.10/dist-packages (from spacy<4->fastai) (1.1.2)\n",
            "Requirement already satisfied: srsly<3.0.0,>=2.4.3 in /usr/local/lib/python3.10/dist-packages (from spacy<4->fastai) (2.4.8)\n",
            "Requirement already satisfied: catalogue<2.1.0,>=2.0.6 in /usr/local/lib/python3.10/dist-packages (from spacy<4->fastai) (2.0.10)\n",
            "Requirement already satisfied: weasel<0.4.0,>=0.1.0 in /usr/local/lib/python3.10/dist-packages (from spacy<4->fastai) (0.3.4)\n",
            "Requirement already satisfied: typer<0.10.0,>=0.3.0 in /usr/local/lib/python3.10/dist-packages (from spacy<4->fastai) (0.9.4)\n",
            "Requirement already satisfied: smart-open<7.0.0,>=5.2.1 in /usr/local/lib/python3.10/dist-packages (from spacy<4->fastai) (6.4.0)\n",
            "Requirement already satisfied: tqdm<5.0.0,>=4.38.0 in /usr/local/lib/python3.10/dist-packages (from spacy<4->fastai) (4.66.4)\n",
            "Requirement already satisfied: pydantic!=1.8,!=1.8.1,<3.0.0,>=1.7.4 in /usr/local/lib/python3.10/dist-packages (from spacy<4->fastai) (2.7.1)\n",
            "Requirement already satisfied: jinja2 in /usr/local/lib/python3.10/dist-packages (from spacy<4->fastai) (3.1.4)\n",
            "Requirement already satisfied: setuptools in /usr/local/lib/python3.10/dist-packages (from spacy<4->fastai) (69.5.1)\n",
            "Requirement already satisfied: langcodes<4.0.0,>=3.2.0 in /usr/local/lib/python3.10/dist-packages (from spacy<4->fastai) (3.4.0)\n",
            "Requirement already satisfied: numpy>=1.19.0 in /usr/local/lib/python3.10/dist-packages (from spacy<4->fastai) (1.25.2)\n",
            "Requirement already satisfied: charset-normalizer<4,>=2 in /usr/local/lib/python3.10/dist-packages (from requests->fastai) (3.3.2)\n",
            "Requirement already satisfied: idna<4,>=2.5 in /usr/local/lib/python3.10/dist-packages (from requests->fastai) (3.7)\n",
            "Requirement already satisfied: urllib3<3,>=1.21.1 in /usr/local/lib/python3.10/dist-packages (from requests->fastai) (2.0.7)\n",
            "Requirement already satisfied: certifi>=2017.4.17 in /usr/local/lib/python3.10/dist-packages (from requests->fastai) (2024.2.2)\n",
            "Requirement already satisfied: filelock in /usr/local/lib/python3.10/dist-packages (from torch<2.4,>=1.10->fastai) (3.14.0)\n",
            "Requirement already satisfied: typing-extensions>=4.8.0 in /usr/local/lib/python3.10/dist-packages (from torch<2.4,>=1.10->fastai) (4.11.0)\n",
            "Requirement already satisfied: sympy in /usr/local/lib/python3.10/dist-packages (from torch<2.4,>=1.10->fastai) (1.12)\n",
            "Requirement already satisfied: networkx in /usr/local/lib/python3.10/dist-packages (from torch<2.4,>=1.10->fastai) (3.3)\n",
            "Requirement already satisfied: fsspec in /usr/local/lib/python3.10/dist-packages (from torch<2.4,>=1.10->fastai) (2023.6.0)\n",
            "Collecting nvidia-cuda-nvrtc-cu12==12.1.105 (from torch<2.4,>=1.10->fastai)\n",
            "  Downloading nvidia_cuda_nvrtc_cu12-12.1.105-py3-none-manylinux1_x86_64.whl.metadata (1.5 kB)\n",
            "Collecting nvidia-cuda-runtime-cu12==12.1.105 (from torch<2.4,>=1.10->fastai)\n",
            "  Downloading nvidia_cuda_runtime_cu12-12.1.105-py3-none-manylinux1_x86_64.whl.metadata (1.5 kB)\n",
            "Collecting nvidia-cuda-cupti-cu12==12.1.105 (from torch<2.4,>=1.10->fastai)\n",
            "  Downloading nvidia_cuda_cupti_cu12-12.1.105-py3-none-manylinux1_x86_64.whl.metadata (1.6 kB)\n",
            "Collecting nvidia-cudnn-cu12==8.9.2.26 (from torch<2.4,>=1.10->fastai)\n",
            "  Downloading nvidia_cudnn_cu12-8.9.2.26-py3-none-manylinux1_x86_64.whl.metadata (1.6 kB)\n",
            "Collecting nvidia-cublas-cu12==12.1.3.1 (from torch<2.4,>=1.10->fastai)\n",
            "  Downloading nvidia_cublas_cu12-12.1.3.1-py3-none-manylinux1_x86_64.whl.metadata (1.5 kB)\n",
            "Collecting nvidia-cufft-cu12==11.0.2.54 (from torch<2.4,>=1.10->fastai)\n",
            "  Downloading nvidia_cufft_cu12-11.0.2.54-py3-none-manylinux1_x86_64.whl.metadata (1.5 kB)\n",
            "Collecting nvidia-curand-cu12==10.3.2.106 (from torch<2.4,>=1.10->fastai)\n",
            "  Downloading nvidia_curand_cu12-10.3.2.106-py3-none-manylinux1_x86_64.whl.metadata (1.5 kB)\n",
            "Collecting nvidia-cusolver-cu12==11.4.5.107 (from torch<2.4,>=1.10->fastai)\n",
            "  Downloading nvidia_cusolver_cu12-11.4.5.107-py3-none-manylinux1_x86_64.whl.metadata (1.6 kB)\n",
            "Collecting nvidia-cusparse-cu12==12.1.0.106 (from torch<2.4,>=1.10->fastai)\n",
            "  Downloading nvidia_cusparse_cu12-12.1.0.106-py3-none-manylinux1_x86_64.whl.metadata (1.6 kB)\n",
            "Collecting nvidia-nccl-cu12==2.19.3 (from torch<2.4,>=1.10->fastai)\n",
            "  Downloading nvidia_nccl_cu12-2.19.3-py3-none-manylinux1_x86_64.whl.metadata (1.8 kB)\n",
            "Collecting nvidia-nvtx-cu12==12.1.105 (from torch<2.4,>=1.10->fastai)\n",
            "  Downloading nvidia_nvtx_cu12-12.1.105-py3-none-manylinux1_x86_64.whl.metadata (1.7 kB)\n",
            "Requirement already satisfied: triton==2.2.0 in /usr/local/lib/python3.10/dist-packages (from torch<2.4,>=1.10->fastai) (2.2.0)\n",
            "Collecting nvidia-nvjitlink-cu12 (from nvidia-cusolver-cu12==11.4.5.107->torch<2.4,>=1.10->fastai)\n",
            "  Downloading nvidia_nvjitlink_cu12-12.4.127-py3-none-manylinux2014_x86_64.whl.metadata (1.5 kB)\n",
            "Requirement already satisfied: contourpy>=1.0.1 in /usr/local/lib/python3.10/dist-packages (from matplotlib->fastai) (1.2.1)\n",
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            "Requirement already satisfied: joblib>=1.1.1 in /usr/local/lib/python3.10/dist-packages (from scikit-learn->fastai) (1.4.2)\n",
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            "Requirement already satisfied: annotated-types>=0.4.0 in /usr/local/lib/python3.10/dist-packages (from pydantic!=1.8,!=1.8.1,<3.0.0,>=1.7.4->spacy<4->fastai) (0.6.0)\n",
            "Requirement already satisfied: pydantic-core==2.18.2 in /usr/local/lib/python3.10/dist-packages (from pydantic!=1.8,!=1.8.1,<3.0.0,>=1.7.4->spacy<4->fastai) (2.18.2)\n",
            "Requirement already satisfied: six>=1.5 in /usr/local/lib/python3.10/dist-packages (from python-dateutil>=2.7->matplotlib->fastai) (1.16.0)\n",
            "Requirement already satisfied: blis<0.8.0,>=0.7.8 in /usr/local/lib/python3.10/dist-packages (from thinc<8.3.0,>=8.2.2->spacy<4->fastai) (0.7.11)\n",
            "Requirement already satisfied: confection<1.0.0,>=0.0.1 in /usr/local/lib/python3.10/dist-packages (from thinc<8.3.0,>=8.2.2->spacy<4->fastai) (0.1.4)\n",
            "Requirement already satisfied: click<9.0.0,>=7.1.1 in /usr/local/lib/python3.10/dist-packages (from typer<0.10.0,>=0.3.0->spacy<4->fastai) (8.1.7)\n",
            "Requirement already satisfied: cloudpathlib<0.17.0,>=0.7.0 in /usr/local/lib/python3.10/dist-packages (from weasel<0.4.0,>=0.1.0->spacy<4->fastai) (0.16.0)\n",
            "Requirement already satisfied: MarkupSafe>=2.0 in /usr/local/lib/python3.10/dist-packages (from jinja2->spacy<4->fastai) (2.1.5)\n",
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            "Downloading nvidia_cublas_cu12-12.1.3.1-py3-none-manylinux1_x86_64.whl (410.6 MB)\n",
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            "\u001b[?25hInstalling 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\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-cu12-2.19.3 nvidia-nvjitlink-cu12-12.4.127 nvidia-nvtx-cu12-12.1.105\n",
            "\u001b[33mWARNING: Running pip as the 'root' user can result in broken permissions and conflicting behaviour with the system package manager. It is recommended to use a virtual environment instead: https://pip.pypa.io/warnings/venv\u001b[0m\u001b[33m\n",
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            "\u001b[?25hBuilding wheels for collected packages: ffmpy\n",
            "  Building wheel for ffmpy (setup.py) ... \u001b[?25l\u001b[?25hdone\n",
            "  Created wheel for ffmpy: filename=ffmpy-0.3.2-py3-none-any.whl size=5584 sha256=a82dd8a6813395ac66dc30dd749e872dcde8138d5e13b278e5331d16079abc9a\n",
            "  Stored in directory: /root/.cache/pip/wheels/bd/65/9a/671fc6dcde07d4418df0c592f8df512b26d7a0029c2a23dd81\n",
            "Successfully built ffmpy\n",
            "Installing collected packages: pydub, ffmpy, websockets, uvloop, ujson, tomlkit, shellingham, semantic-version, ruff, python-multipart, python-dotenv, orjson, httptools, h11, dnspython, aiofiles, watchfiles, uvicorn, starlette, httpcore, email_validator, typer, httpx, gradio-client, fastapi-cli, fastapi, gradio\n",
            "  Attempting uninstall: typer\n",
            "    Found existing installation: typer 0.9.4\n",
            "    Uninstalling typer-0.9.4:\n",
            "      Successfully uninstalled typer-0.9.4\n",
            "\u001b[31mERROR: pip's dependency resolver does not currently take into account all the packages that are installed. This behaviour is the source of the following dependency conflicts.\n",
            "spacy 3.7.4 requires typer<0.10.0,>=0.3.0, but you have typer 0.12.3 which is incompatible.\n",
            "weasel 0.3.4 requires typer<0.10.0,>=0.3.0, but you have typer 0.12.3 which is incompatible.\u001b[0m\u001b[31m\n",
            "\u001b[0mSuccessfully installed aiofiles-23.2.1 dnspython-2.6.1 email_validator-2.1.1 fastapi-0.111.0 fastapi-cli-0.0.3 ffmpy-0.3.2 gradio-4.31.0 gradio-client-0.16.2 h11-0.14.0 httpcore-1.0.5 httptools-0.6.1 httpx-0.27.0 orjson-3.10.3 pydub-0.25.1 python-dotenv-1.0.1 python-multipart-0.0.9 ruff-0.4.4 semantic-version-2.10.0 shellingham-1.5.4 starlette-0.37.2 tomlkit-0.12.0 typer-0.12.3 ujson-5.9.0 uvicorn-0.29.0 uvloop-0.19.0 watchfiles-0.21.0 websockets-11.0.3\n",
            "\u001b[33mWARNING: Running pip as the 'root' user can result in broken permissions and conflicting behaviour with the system package manager. It is recommended to use a virtual environment instead: https://pip.pypa.io/warnings/venv\u001b[0m\u001b[33m\n",
            "\u001b[0m"
          ]
        }
      ],
      "source": [
        "!pip install -U fastai\n",
        "!pip install -U gradio\n",
        "!pip install gradio_client"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "pt5sekV0AP3B"
      },
      "outputs": [],
      "source": [
        "from fastai.vision.all import load_learner\n",
        "import gradio as gr"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "6tOiOdb1ARmS",
        "outputId": "245be524-6b03-4136-dd3e-f0740d2520eb"
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "Mounted at /content/drive\n"
          ]
        }
      ],
      "source": [
        "from google.colab import drive\n",
        "drive.mount('/content/drive')"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "RmvqWys4Ahb7",
        "outputId": "e3a93d90-edda-474d-eb37-c29686203b73"
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "/content/drive/MyDrive/Art Style Recognizer\n"
          ]
        }
      ],
      "source": [
        "%cd /content/drive/MyDrive/Art Style Recognizer"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "h9ECj9D9AtZf"
      },
      "outputs": [],
      "source": [
        "model = load_learner('/content/drive/MyDrive/Art Style Recognizer/models/artStyle_recognizer-v5.pk1')"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "AeLgBlSzCfjl"
      },
      "outputs": [],
      "source": [
        "art_labels= [\n",
        "    \"Art Nouveau\",\n",
        "    \"Constructivism Art\",\n",
        "    \"Cubism Art\",\n",
        "    \"Dadaism Art\",\n",
        "    \"Fauvism Art\",\n",
        "    \"Gothic Art\",\n",
        "    \"Minimalism Art\",\n",
        "    \"Pointillism Art\",\n",
        "    \"Pop Art\",\n",
        "    \"Prehistoric Art\"\n",
        "\n",
        "]"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "nJc157VHCX-1"
      },
      "outputs": [],
      "source": [
        "def recognize_image(image):\n",
        "    pred, idx, probs = model.predict(image)\n",
        "    return dict(zip(art_labels, map(float, probs)))"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 185
        },
        "id": "M92kwbSrC_XG",
        "outputId": "9a931c24-c12f-4484-d9e8-85d8e1ce348a"
      },
      "outputs": [
        {
          "data": {
            "image/png": 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",
            "text/plain": [
              "<PIL.JpegImagePlugin.JpegImageFile image mode=RGB size=224x168>"
            ]
          },
          "execution_count": 18,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "from PIL import Image\n",
        "img = Image.open(f'Art Nouveau.jpg')\n",
        "img.thumbnail((224,224))\n",
        "img"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 191
        },
        "id": "HLJyD4T0DZDa",
        "outputId": "876d937f-7465-468f-db2f-49a1952ee1e2"
      },
      "outputs": [
        {
          "data": {
            "text/html": [
              "\n",
              "<style>\n",
              "    /* Turns off some styling */\n",
              "    progress {\n",
              "        /* gets rid of default border in Firefox and Opera. */\n",
              "        border: none;\n",
              "        /* Needs to be in here for Safari polyfill so background images work as expected. */\n",
              "        background-size: auto;\n",
              "    }\n",
              "    progress:not([value]), progress:not([value])::-webkit-progress-bar {\n",
              "        background: repeating-linear-gradient(45deg, #7e7e7e, #7e7e7e 10px, #5c5c5c 10px, #5c5c5c 20px);\n",
              "    }\n",
              "    .progress-bar-interrupted, .progress-bar-interrupted::-webkit-progress-bar {\n",
              "        background: #F44336;\n",
              "    }\n",
              "</style>\n"
            ],
            "text/plain": [
              "<IPython.core.display.HTML object>"
            ]
          },
          "metadata": {},
          "output_type": "display_data"
        },
        {
          "data": {
            "text/html": [],
            "text/plain": [
              "<IPython.core.display.HTML object>"
            ]
          },
          "metadata": {},
          "output_type": "display_data"
        },
        {
          "data": {
            "text/plain": [
              "{'Art Nouveau': 0.999980092048645,\n",
              " 'Constructivism Art': 3.581120111562086e-08,\n",
              " 'Cubism Art': 5.082507868792163e-06,\n",
              " 'Dadaism Art': 8.201993182410661e-07,\n",
              " 'Fauvism Art': 6.737728313055413e-07,\n",
              " 'Gothic Art': 6.75285207307752e-07,\n",
              " 'Minimalism Art': 1.575264718667313e-07,\n",
              " 'Pointillism Art': 2.2495997598070971e-07,\n",
              " 'Pop Art': 1.1605121471802704e-05,\n",
              " 'Prehistoric Art': 6.758876338608388e-07}"
            ]
          },
          "execution_count": 19,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "recognize_image(img)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "WaONDTrJDfF6"
      },
      "outputs": [],
      "source": [
        "image = gr.Image()\n",
        "label = gr.Label()\n",
        "example = [\n",
        "    'Constructivism art.jpg',\n",
        "    'Fauvism art.jpg',\n",
        "    'Gothic art.jpeg',\n",
        "    'Minimalistic art.jpg'\n",
        "]"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "bVn6xSKFD53Z",
        "outputId": "a07dd445-f267-4c97-949e-f25014f6a07e"
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "Setting queue=True in a Colab notebook requires sharing enabled. Setting `share=True` (you can turn this off by setting `share=False` in `launch()` explicitly).\n",
            "\n",
            "Colab notebook detected. To show errors in colab notebook, set debug=True in launch()\n",
            "Running on public URL: https://5b2a41b827ca8bd747.gradio.live\n",
            "\n",
            "This share link expires in 72 hours. For free permanent hosting and GPU upgrades, run `gradio deploy` from Terminal to deploy to Spaces (https://huggingface.co/spaces)\n"
          ]
        },
        {
          "data": {
            "text/plain": []
          },
          "execution_count": 21,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "iface = gr.Interface(fn = recognize_image, inputs = image, outputs = label, examples = example)\n",
        "iface.launch(inline=False)"
      ]
    }
  ],
  "metadata": {
    "colab": {
      "provenance": []
    },
    "kernelspec": {
      "display_name": "Python 3",
      "name": "python3"
    },
    "language_info": {
      "name": "python"
    }
  },
  "nbformat": 4,
  "nbformat_minor": 0
}