{"nbformat":4,"nbformat_minor":0,"metadata":{"colab":{"provenance":[],"gpuType":"T4"},"kernelspec":{"name":"python3","display_name":"Python 3"},"language_info":{"name":"python"},"accelerator":"GPU"},"cells":[{"cell_type":"markdown","source":["## 1. 掛載雲端硬碟"],"metadata":{"id":"JvFnrA5V65pO"}},{"cell_type":"code","source":["from google.colab import drive\n","drive.mount('/content/drive')"],"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"vu6SEPk764ES","executionInfo":{"status":"ok","timestamp":1718263954899,"user_tz":-480,"elapsed":26444,"user":{"displayName":"黃致宇","userId":"05257376044901631491"}},"outputId":"9f1d7a68-f087-4b87-ec1d-47413057c232"},"execution_count":2,"outputs":[{"output_type":"stream","name":"stdout","text":["Mounted at /content/drive\n"]}]},{"cell_type":"markdown","source":["## 2. 安裝套件"],"metadata":{"id":"eOlb0q627EZI"}},{"cell_type":"code","source":["!pip install --upgrade pyyaml==5.3.1"],"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"5SCKBEDB7EFG","executionInfo":{"status":"ok","timestamp":1718263957162,"user_tz":-480,"elapsed":2268,"user":{"displayName":"黃致宇","userId":"05257376044901631491"}},"outputId":"d7c7230a-0d22-4348-9de4-9e1ee4d39b30"},"execution_count":3,"outputs":[{"output_type":"stream","name":"stdout","text":["Collecting pyyaml==5.3.1\n","  Downloading PyYAML-5.3.1.tar.gz (269 kB)\n","\u001b[?25l     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m0.0/269.4 kB\u001b[0m \u001b[31m?\u001b[0m eta \u001b[36m-:--:--\u001b[0m\r\u001b[2K     \u001b[91m━━━━━━━━━━━━━\u001b[0m\u001b[91m╸\u001b[0m\u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m92.2/269.4 kB\u001b[0m \u001b[31m2.6 MB/s\u001b[0m eta \u001b[36m0:00:01\u001b[0m\r\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m269.4/269.4 kB\u001b[0m \u001b[31m5.1 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n","\u001b[?25h  \u001b[1;31merror\u001b[0m: \u001b[1msubprocess-exited-with-error\u001b[0m\n","  \n","  \u001b[31m×\u001b[0m \u001b[32mpython setup.py egg_info\u001b[0m did not run successfully.\n","  \u001b[31m│\u001b[0m exit code: \u001b[1;36m1\u001b[0m\n","  \u001b[31m╰─>\u001b[0m See above for output.\n","  \n","  \u001b[1;35mnote\u001b[0m: This error originates from a subprocess, and is likely not a problem with pip.\n","  Preparing metadata (setup.py) ... \u001b[?25l\u001b[?25herror\n","\u001b[1;31merror\u001b[0m: \u001b[1mmetadata-generation-failed\u001b[0m\n","\n","\u001b[31m×\u001b[0m Encountered error while generating package metadata.\n","\u001b[31m╰─>\u001b[0m See above for output.\n","\n","\u001b[1;35mnote\u001b[0m: This is an issue with the package mentioned above, not pip.\n","\u001b[1;36mhint\u001b[0m: See above for details.\n"]}]},{"cell_type":"markdown","source":["## 3. 下載程式碼"],"metadata":{"id":"ngH7Q6Kx6f7m"}},{"cell_type":"code","execution_count":4,"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"QA5CaOZY6aMM","executionInfo":{"status":"ok","timestamp":1718263957163,"user_tz":-480,"elapsed":22,"user":{"displayName":"黃致宇","userId":"05257376044901631491"}},"outputId":"5043cf2d-c098-4711-fe52-8c1573dc315c"},"outputs":[{"output_type":"stream","name":"stdout","text":["/content\n","/content/drive/MyDrive/data3\n"]}],"source":["#顯示當前目錄\n","!pwd\n","\n","#切換目錄\n","%cd /content/drive/MyDrive/data3"]},{"cell_type":"code","source":["# 從git上面下載程式碼(只要執行一次)\n","!git clone https://github.com/WongKinYiu/yolov7.git"],"metadata":{"id":"VGe25V0bVkdb","colab":{"base_uri":"https://localhost:8080/"},"executionInfo":{"status":"ok","timestamp":1718263957163,"user_tz":-480,"elapsed":19,"user":{"displayName":"黃致宇","userId":"05257376044901631491"}},"outputId":"61428a98-5a00-4ee8-c5b5-aa86c68e337a"},"execution_count":5,"outputs":[{"output_type":"stream","name":"stdout","text":["fatal: destination path 'yolov7' already exists and is not an empty directory.\n"]}]},{"cell_type":"markdown","source":["## 4. 下載已經使用coco dataset預先訓練好的權重\n","* 從 https://github.com/WongKinYiu/yolov7.git 上面去尋找連結"],"metadata":{"id":"zdM561AuAUZc"}},{"cell_type":"code","source":["!wget https://github.com/WongKinYiu/yolov7/releases/download/v0.1/yolov7.pt"],"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"ffh4H-2E6eEo","executionInfo":{"status":"ok","timestamp":1718263960458,"user_tz":-480,"elapsed":3312,"user":{"displayName":"黃致宇","userId":"05257376044901631491"}},"outputId":"fa564d2c-0ce8-492e-9888-96413319d8b3"},"execution_count":6,"outputs":[{"output_type":"stream","name":"stdout","text":["--2024-06-13 07:32:36--  https://github.com/WongKinYiu/yolov7/releases/download/v0.1/yolov7.pt\n","Resolving github.com (github.com)... 20.205.243.166\n","Connecting to github.com (github.com)|20.205.243.166|:443... connected.\n","HTTP request sent, awaiting response... 302 Found\n","Location: https://objects.githubusercontent.com/github-production-release-asset-2e65be/511187726/b0243edf-9fb0-4337-95e1-42555f1b37cf?X-Amz-Algorithm=AWS4-HMAC-SHA256&X-Amz-Credential=releaseassetproduction%2F20240613%2Fus-east-1%2Fs3%2Faws4_request&X-Amz-Date=20240613T073236Z&X-Amz-Expires=300&X-Amz-Signature=fedc5bb14cb442783ac47bd5c56b16a49c0532d5acaf9a495b8c19e615cf1cb2&X-Amz-SignedHeaders=host&actor_id=0&key_id=0&repo_id=511187726&response-content-disposition=attachment%3B%20filename%3Dyolov7.pt&response-content-type=application%2Foctet-stream [following]\n","--2024-06-13 07:32:36--  https://objects.githubusercontent.com/github-production-release-asset-2e65be/511187726/b0243edf-9fb0-4337-95e1-42555f1b37cf?X-Amz-Algorithm=AWS4-HMAC-SHA256&X-Amz-Credential=releaseassetproduction%2F20240613%2Fus-east-1%2Fs3%2Faws4_request&X-Amz-Date=20240613T073236Z&X-Amz-Expires=300&X-Amz-Signature=fedc5bb14cb442783ac47bd5c56b16a49c0532d5acaf9a495b8c19e615cf1cb2&X-Amz-SignedHeaders=host&actor_id=0&key_id=0&repo_id=511187726&response-content-disposition=attachment%3B%20filename%3Dyolov7.pt&response-content-type=application%2Foctet-stream\n","Resolving objects.githubusercontent.com (objects.githubusercontent.com)... 185.199.108.133, 185.199.109.133, 185.199.110.133, ...\n","Connecting to objects.githubusercontent.com (objects.githubusercontent.com)|185.199.108.133|:443... connected.\n","HTTP request sent, awaiting response... 200 OK\n","Length: 75587165 (72M) [application/octet-stream]\n","Saving to: ‘yolov7.pt.2’\n","\n","yolov7.pt.2         100%[===================>]  72.08M  39.1MB/s    in 1.8s    \n","\n","2024-06-13 07:32:39 (39.1 MB/s) - ‘yolov7.pt.2’ saved [75587165/75587165]\n","\n"]}]},{"cell_type":"markdown","source":["## 5. 上傳資料與新增設定檔"],"metadata":{"id":"usnmC9u8AtTw"}},{"cell_type":"code","source":["#切換目錄到剛下載的git專案\n","%cd yolov7"],"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"0FaLnNRP6eB9","executionInfo":{"status":"ok","timestamp":1718263960458,"user_tz":-480,"elapsed":5,"user":{"displayName":"黃致宇","userId":"05257376044901631491"}},"outputId":"dcd37812-f866-40bb-ec2e-7610153e6aa0"},"execution_count":7,"outputs":[{"output_type":"stream","name":"stdout","text":["/content/drive/MyDrive/data3/yolov7\n"]}]},{"cell_type":"markdown","source":["## 6-1. 在./yolo/data/目錄底下手動建立資料夾 [project名稱]\n","## 6-2. 上傳訓練資料到./yolo/data/train跟 ./yolo/data/val/\n","## 6-3. 複製data目錄底下的coco.yaml, 改名為[project名稱].yaml\n","## 6-4. 編輯[project名稱].yaml裡面的參數\n","* train: ./data/[project名稱]/train\n","* val: ./data/[project名稱]/val\n","* test: ./data/[project名稱]/test\n","* nc: [總共有多少類別]\n","* names: [每個類別代表的英文名稱]\n","\n","## 6-5. 複製cfg/training目錄底下的yolov7.yaml 並改名為yolov7_[project名稱].yaml\n","## 6-6. 編輯yolov7_[project名稱].yaml\n","* nc: [總共有多少類別]"],"metadata":{"id":"px5Ui1z691Gf"}},{"cell_type":"markdown","source":["## 7. 訓練模型"],"metadata":{"id":"o1qlx6w0BIY4"}},{"cell_type":"code","source":["!pwd\n","\n","%cd /content/drive/MyDrive/data3/yolov7"],"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"Z-vgRl_mVUGk","executionInfo":{"status":"ok","timestamp":1718263961320,"user_tz":-480,"elapsed":865,"user":{"displayName":"黃致宇","userId":"05257376044901631491"}},"outputId":"2c7c4bf2-a7b6-415c-f4e5-fe7c02d623ff"},"execution_count":8,"outputs":[{"output_type":"stream","name":"stdout","text":["/content/drive/MyDrive/data3/yolov7\n","/content/drive/MyDrive/data3/yolov7\n"]}]},{"cell_type":"code","source":["!python train.py --device 0 --batch-size 16 --epochs 100 --data /content/drive/MyDrive/data3/data.yaml --img 640 640 --hyp data/hyp.scratch.custom.yaml --cfg /content/drive/MyDrive/data3/yolov7/cfg/training/triffict.yaml --weights 'yolov7.pt' --name yolov7-fish"],"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"TtHOAGy56c2Q","outputId":"ee71429e-56bd-496d-c370-3db0b973adbc","executionInfo":{"status":"ok","timestamp":1718267228144,"user_tz":-480,"elapsed":3266826,"user":{"displayName":"黃致宇","userId":"05257376044901631491"}}},"execution_count":9,"outputs":[{"output_type":"stream","name":"stdout","text":["2024-06-13 07:32:45.970999: E external/local_xla/xla/stream_executor/cuda/cuda_dnn.cc:9261] Unable to register cuDNN factory: Attempting to register factory for plugin cuDNN when one has already been registered\n","2024-06-13 07:32:45.971073: E external/local_xla/xla/stream_executor/cuda/cuda_fft.cc:607] Unable to register cuFFT factory: Attempting to register factory for plugin cuFFT when one has already been registered\n","2024-06-13 07:32:45.972920: E external/local_xla/xla/stream_executor/cuda/cuda_blas.cc:1515] Unable to register cuBLAS factory: Attempting to register factory for plugin cuBLAS when one has already been registered\n","2024-06-13 07:32:45.983169: I tensorflow/core/platform/cpu_feature_guard.cc:182] This TensorFlow binary is optimized to use available CPU instructions in performance-critical operations.\n","To enable the following instructions: AVX2 AVX512F FMA, in other operations, rebuild TensorFlow with the appropriate compiler flags.\n","2024-06-13 07:32:47.516969: W tensorflow/compiler/tf2tensorrt/utils/py_utils.cc:38] TF-TRT Warning: Could not find TensorRT\n","YOLOR 🚀 v0.1-128-ga207844 torch 2.3.0+cu121 CUDA:0 (Tesla T4, 15102.0625MB)\n","\n","Namespace(weights='yolov7.pt', cfg='/content/drive/MyDrive/data3/yolov7/cfg/training/triffict.yaml', data='/content/drive/MyDrive/data3/data.yaml', hyp='data/hyp.scratch.custom.yaml', epochs=100, batch_size=16, img_size=[640, 640], rect=False, resume=False, nosave=False, notest=False, noautoanchor=False, evolve=False, bucket='', cache_images=False, image_weights=False, device='0', multi_scale=False, single_cls=False, adam=False, sync_bn=False, local_rank=-1, workers=8, project='runs/train', entity=None, name='yolov7-fish', exist_ok=False, quad=False, linear_lr=False, label_smoothing=0.0, upload_dataset=False, bbox_interval=-1, save_period=-1, artifact_alias='latest', freeze=[0], v5_metric=False, world_size=1, global_rank=-1, save_dir='runs/train/yolov7-fish3', total_batch_size=16)\n","\u001b[34m\u001b[1mtensorboard: \u001b[0mStart with 'tensorboard --logdir runs/train', view at http://localhost:6006/\n","\u001b[34m\u001b[1mhyperparameters: \u001b[0mlr0=0.01, lrf=0.1, momentum=0.937, weight_decay=0.0005, warmup_epochs=3.0, warmup_momentum=0.8, warmup_bias_lr=0.1, box=0.05, cls=0.3, cls_pw=1.0, obj=0.7, obj_pw=1.0, iou_t=0.2, anchor_t=4.0, fl_gamma=0.0, hsv_h=0.015, hsv_s=0.7, hsv_v=0.4, degrees=0.0, translate=0.2, scale=0.5, shear=0.0, perspective=0.0, flipud=0.0, fliplr=0.5, mosaic=1.0, mixup=0.0, copy_paste=0.0, paste_in=0.0, loss_ota=1\n","\u001b[34m\u001b[1mwandb: \u001b[0mInstall Weights & Biases for YOLOR logging with 'pip install wandb' (recommended)\n","\n","                 from  n    params  module                                  arguments                     \n","  0                -1  1       928  models.common.Conv                      [3, 32, 3, 1]                 \n","  1                -1  1     18560  models.common.Conv                      [32, 64, 3, 2]                \n","  2                -1  1     36992  models.common.Conv                      [64, 64, 3, 1]                \n","  3                -1  1     73984  models.common.Conv                      [64, 128, 3, 2]               \n","  4                -1  1      8320  models.common.Conv                      [128, 64, 1, 1]               \n","  5                -2  1      8320  models.common.Conv                      [128, 64, 1, 1]               \n","  6                -1  1     36992  models.common.Conv                      [64, 64, 3, 1]                \n","  7                -1  1     36992  models.common.Conv                      [64, 64, 3, 1]                \n","  8                -1  1     36992  models.common.Conv                      [64, 64, 3, 1]                \n","  9                -1  1     36992  models.common.Conv                      [64, 64, 3, 1]                \n"," 10  [-1, -3, -5, -6]  1         0  models.common.Concat                    [1]                           \n"," 11                -1  1     66048  models.common.Conv                      [256, 256, 1, 1]              \n"," 12                -1  1         0  models.common.MP                        []                            \n"," 13                -1  1     33024  models.common.Conv                      [256, 128, 1, 1]              \n"," 14                -3  1     33024  models.common.Conv                      [256, 128, 1, 1]              \n"," 15                -1  1    147712  models.common.Conv                      [128, 128, 3, 2]              \n"," 16          [-1, -3]  1         0  models.common.Concat                    [1]                           \n"," 17                -1  1     33024  models.common.Conv                      [256, 128, 1, 1]              \n"," 18                -2  1     33024  models.common.Conv                      [256, 128, 1, 1]              \n"," 19                -1  1    147712  models.common.Conv                      [128, 128, 3, 1]              \n"," 20                -1  1    147712  models.common.Conv                      [128, 128, 3, 1]              \n"," 21                -1  1    147712  models.common.Conv                      [128, 128, 3, 1]              \n"," 22                -1  1    147712  models.common.Conv                      [128, 128, 3, 1]              \n"," 23  [-1, -3, -5, -6]  1         0  models.common.Concat                    [1]                           \n"," 24                -1  1    263168  models.common.Conv                      [512, 512, 1, 1]              \n"," 25                -1  1         0  models.common.MP                        []                            \n"," 26                -1  1    131584  models.common.Conv                      [512, 256, 1, 1]              \n"," 27                -3  1    131584  models.common.Conv                      [512, 256, 1, 1]              \n"," 28                -1  1    590336  models.common.Conv                      [256, 256, 3, 2]              \n"," 29          [-1, -3]  1         0  models.common.Concat                    [1]                           \n"," 30                -1  1    131584  models.common.Conv                      [512, 256, 1, 1]              \n"," 31                -2  1    131584  models.common.Conv                      [512, 256, 1, 1]              \n"," 32                -1  1    590336  models.common.Conv                      [256, 256, 3, 1]              \n"," 33                -1  1    590336  models.common.Conv                      [256, 256, 3, 1]              \n"," 34                -1  1    590336  models.common.Conv                      [256, 256, 3, 1]              \n"," 35                -1  1    590336  models.common.Conv                      [256, 256, 3, 1]              \n"," 36  [-1, -3, -5, -6]  1         0  models.common.Concat                    [1]                           \n"," 37                -1  1   1050624  models.common.Conv                      [1024, 1024, 1, 1]            \n"," 38                -1  1         0  models.common.MP                        []                            \n"," 39                -1  1    525312  models.common.Conv                      [1024, 512, 1, 1]             \n"," 40                -3  1    525312  models.common.Conv                      [1024, 512, 1, 1]             \n"," 41                -1  1   2360320  models.common.Conv                      [512, 512, 3, 2]              \n"," 42          [-1, -3]  1         0  models.common.Concat                    [1]                           \n"," 43                -1  1    262656  models.common.Conv                      [1024, 256, 1, 1]             \n"," 44                -2  1    262656  models.common.Conv                      [1024, 256, 1, 1]             \n"," 45                -1  1    590336  models.common.Conv                      [256, 256, 3, 1]              \n"," 46                -1  1    590336  models.common.Conv                      [256, 256, 3, 1]              \n"," 47                -1  1    590336  models.common.Conv                      [256, 256, 3, 1]              \n"," 48                -1  1    590336  models.common.Conv                      [256, 256, 3, 1]              \n"," 49  [-1, -3, -5, -6]  1         0  models.common.Concat                    [1]                           \n"," 50                -1  1   1050624  models.common.Conv                      [1024, 1024, 1, 1]            \n"," 51                -1  1   7609344  models.common.SPPCSPC                   [1024, 512, 1]                \n"," 52                -1  1    131584  models.common.Conv                      [512, 256, 1, 1]              \n"," 53                -1  1         0  torch.nn.modules.upsampling.Upsample    [None, 2, 'nearest']          \n"," 54                37  1    262656  models.common.Conv                      [1024, 256, 1, 1]             \n"," 55          [-1, -2]  1         0  models.common.Concat                    [1]                           \n"," 56                -1  1    131584  models.common.Conv                      [512, 256, 1, 1]              \n"," 57                -2  1    131584  models.common.Conv                      [512, 256, 1, 1]              \n"," 58                -1  1    295168  models.common.Conv                      [256, 128, 3, 1]              \n"," 59                -1  1    147712  models.common.Conv                      [128, 128, 3, 1]              \n"," 60                -1  1    147712  models.common.Conv                      [128, 128, 3, 1]              \n"," 61                -1  1    147712  models.common.Conv                      [128, 128, 3, 1]              \n"," 62[-1, -2, -3, -4, -5, -6]  1         0  models.common.Concat                    [1]                           \n"," 63                -1  1    262656  models.common.Conv                      [1024, 256, 1, 1]             \n"," 64                -1  1     33024  models.common.Conv                      [256, 128, 1, 1]              \n"," 65                -1  1         0  torch.nn.modules.upsampling.Upsample    [None, 2, 'nearest']          \n"," 66                24  1     65792  models.common.Conv                      [512, 128, 1, 1]              \n"," 67          [-1, -2]  1         0  models.common.Concat                    [1]                           \n"," 68                -1  1     33024  models.common.Conv                      [256, 128, 1, 1]              \n"," 69                -2  1     33024  models.common.Conv                      [256, 128, 1, 1]              \n"," 70                -1  1     73856  models.common.Conv                      [128, 64, 3, 1]               \n"," 71                -1  1     36992  models.common.Conv                      [64, 64, 3, 1]                \n"," 72                -1  1     36992  models.common.Conv                      [64, 64, 3, 1]                \n"," 73                -1  1     36992  models.common.Conv                      [64, 64, 3, 1]                \n"," 74[-1, -2, -3, -4, -5, -6]  1         0  models.common.Concat                    [1]                           \n"," 75                -1  1     65792  models.common.Conv                      [512, 128, 1, 1]              \n"," 76                -1  1         0  models.common.MP                        []                            \n"," 77                -1  1     16640  models.common.Conv                      [128, 128, 1, 1]              \n"," 78                -3  1     16640  models.common.Conv                      [128, 128, 1, 1]              \n"," 79                -1  1    147712  models.common.Conv                      [128, 128, 3, 2]              \n"," 80      [-1, -3, 63]  1         0  models.common.Concat                    [1]                           \n"," 81                -1  1    131584  models.common.Conv                      [512, 256, 1, 1]              \n"," 82                -2  1    131584  models.common.Conv                      [512, 256, 1, 1]              \n"," 83                -1  1    295168  models.common.Conv                      [256, 128, 3, 1]              \n"," 84                -1  1    147712  models.common.Conv                      [128, 128, 3, 1]              \n"," 85                -1  1    147712  models.common.Conv                      [128, 128, 3, 1]              \n"," 86                -1  1    147712  models.common.Conv                      [128, 128, 3, 1]              \n"," 87[-1, -2, -3, -4, -5, -6]  1         0  models.common.Concat                    [1]                           \n"," 88                -1  1    262656  models.common.Conv                      [1024, 256, 1, 1]             \n"," 89                -1  1         0  models.common.MP                        []                            \n"," 90                -1  1     66048  models.common.Conv                      [256, 256, 1, 1]              \n"," 91                -3  1     66048  models.common.Conv                      [256, 256, 1, 1]              \n"," 92                -1  1    590336  models.common.Conv                      [256, 256, 3, 2]              \n"," 93      [-1, -3, 51]  1         0  models.common.Concat                    [1]                           \n"," 94                -1  1    525312  models.common.Conv                      [1024, 512, 1, 1]             \n"," 95                -2  1    525312  models.common.Conv                      [1024, 512, 1, 1]             \n"," 96                -1  1   1180160  models.common.Conv                      [512, 256, 3, 1]              \n"," 97                -1  1    590336  models.common.Conv                      [256, 256, 3, 1]              \n"," 98                -1  1    590336  models.common.Conv                      [256, 256, 3, 1]              \n"," 99                -1  1    590336  models.common.Conv                      [256, 256, 3, 1]              \n","100[-1, -2, -3, -4, -5, -6]  1         0  models.common.Concat                    [1]                           \n","101                -1  1   1049600  models.common.Conv                      [2048, 512, 1, 1]             \n","102                75  1    328704  models.common.RepConv                   [128, 256, 3, 1]              \n","103                88  1   1312768  models.common.RepConv                   [256, 512, 3, 1]              \n","104               101  1   5246976  models.common.RepConv                   [512, 1024, 3, 1]             \n","105   [102, 103, 104]  1     61126  models.yolo.IDetect                     [6, [[12, 16, 19, 36, 40, 28], [36, 75, 76, 55, 72, 146], [142, 110, 192, 243, 459, 401]], [256, 512, 1024]]\n","Model Summary: 415 layers, 37223526 parameters, 37223526 gradients\n","\n","Transferred 552/566 items from yolov7.pt\n","Scaled weight_decay = 0.0005\n","Optimizer groups: 95 .bias, 95 conv.weight, 98 other\n","\u001b[34m\u001b[1mtrain: \u001b[0mScanning '/content/drive/MyDrive/data3/train/labels.cache' images and labels... 338 found, 0 missing, 0 empty, 0 corrupted: 100% 338/338 [00:00<?, ?it/s]\n","/usr/lib/python3.10/multiprocessing/popen_fork.py:66: RuntimeWarning: os.fork() was called. os.fork() is incompatible with multithreaded code, and JAX is multithreaded, so this will likely lead to a deadlock.\n","  self.pid = os.fork()\n","\u001b[34m\u001b[1mval: \u001b[0mScanning '/content/drive/MyDrive/data3/valid/labels.cache' images and labels... 100 found, 0 missing, 0 empty, 0 corrupted: 100% 100/100 [00:00<?, ?it/s]\n","\n","\u001b[34m\u001b[1mautoanchor: \u001b[0mAnalyzing anchors... anchors/target = 4.11, Best Possible Recall (BPR) = 1.0000\n","Image sizes 640 train, 640 test\n","Using 2 dataloader workers\n","Logging results to runs/train/yolov7-fish3\n","Starting training for 100 epochs...\n","\n","     Epoch   gpu_mem       box       obj       cls     total    labels  img_size\n","      0/99     1.12G   0.07343   0.01657   0.03208    0.1221         5       640: 100% 22/22 [01:11<00:00,  3.26s/it]\n","               Class      Images      Labels           P           R      mAP@.5  mAP@.5:.95:   0% 0/4 [00:00<?, ?it/s]/usr/local/lib/python3.10/dist-packages/torch/functional.py:512: UserWarning: torch.meshgrid: in an upcoming release, it will be required to pass the indexing argument. (Triggered internally at ../aten/src/ATen/native/TensorShape.cpp:3587.)\n","  return _VF.meshgrid(tensors, **kwargs)  # type: ignore[attr-defined]\n","               Class      Images      Labels           P           R      mAP@.5  mAP@.5:.95: 100% 4/4 [00:10<00:00,  2.61s/it]\n","                 all         100         288     0.00314      0.0332    0.000673    0.000163\n","\n","     Epoch   gpu_mem       box       obj       cls     total    labels  img_size\n","      1/99     12.5G   0.06626   0.01606   0.02921    0.1115        10       640: 100% 22/22 [00:26<00:00,  1.20s/it]\n","               Class      Images      Labels           P           R      mAP@.5  mAP@.5:.95: 100% 4/4 [00:05<00:00,  1.26s/it]\n","                 all         100         288      0.0134      0.0245     0.00623     0.00101\n","\n","     Epoch   gpu_mem       box       obj       cls     total    labels  img_size\n","      2/99     11.1G   0.05859   0.01656   0.02625    0.1014        11       640: 100% 22/22 [00:24<00:00,  1.09s/it]\n","               Class      Images      Labels           P           R      mAP@.5  mAP@.5:.95: 100% 4/4 [00:03<00:00,  1.03it/s]\n","                 all         100         288       0.862      0.0633      0.0484      0.0138\n","\n","     Epoch   gpu_mem       box       obj       cls     total    labels  img_size\n","      3/99     11.1G    0.0537   0.01596   0.02283   0.09249         9       640: 100% 22/22 [00:25<00:00,  1.15s/it]\n","               Class      Images      Labels           P           R      mAP@.5  mAP@.5:.95: 100% 4/4 [00:04<00:00,  1.21s/it]\n","                 all         100         288        0.88      0.0691      0.0716       0.024\n","\n","     Epoch   gpu_mem       box       obj       cls     total    labels  img_size\n","      4/99     11.1G   0.05165   0.01497   0.02024   0.08686         9       640: 100% 22/22 [00:24<00:00,  1.13s/it]\n","               Class      Images      Labels           P           R      mAP@.5  mAP@.5:.95: 100% 4/4 [00:02<00:00,  1.46it/s]\n","                 all         100         288       0.918      0.0949       0.119      0.0374\n","\n","     Epoch   gpu_mem       box       obj       cls     total    labels  img_size\n","      5/99     11.1G   0.04925    0.0137   0.01858   0.08153         4       640: 100% 22/22 [00:26<00:00,  1.21s/it]\n","               Class      Images      Labels           P           R      mAP@.5  mAP@.5:.95: 100% 4/4 [00:04<00:00,  1.12s/it]\n","                 all         100         288       0.918       0.102       0.154      0.0492\n","\n","     Epoch   gpu_mem       box       obj       cls     total    labels  img_size\n","      6/99     11.1G   0.04989   0.01371   0.01779    0.0814        17       640: 100% 22/22 [00:25<00:00,  1.15s/it]\n","               Class      Images      Labels           P           R      mAP@.5  mAP@.5:.95: 100% 4/4 [00:02<00:00,  1.55it/s]\n","                 all         100         288       0.361       0.433       0.177      0.0493\n","\n","     Epoch   gpu_mem       box       obj       cls     total    labels  img_size\n","      7/99     11.1G   0.04817   0.01208   0.01614   0.07639         2       640: 100% 22/22 [00:26<00:00,  1.21s/it]\n","               Class      Images      Labels           P           R      mAP@.5  mAP@.5:.95: 100% 4/4 [00:02<00:00,  1.43it/s]\n","                 all         100         288       0.384       0.281       0.202      0.0494\n","\n","     Epoch   gpu_mem       box       obj       cls     total    labels  img_size\n","      8/99     11.1G   0.05058   0.01266   0.01611   0.07935        14       640: 100% 22/22 [00:25<00:00,  1.18s/it]\n","               Class      Images      Labels           P           R      mAP@.5  mAP@.5:.95: 100% 4/4 [00:04<00:00,  1.16s/it]\n","                 all         100         288       0.436       0.446       0.306       0.104\n","\n","     Epoch   gpu_mem       box       obj       cls     total    labels  img_size\n","      9/99     11.1G   0.04952   0.01155   0.01434    0.0754         2       640: 100% 22/22 [00:24<00:00,  1.12s/it]\n","               Class      Images      Labels           P           R      mAP@.5  mAP@.5:.95: 100% 4/4 [00:03<00:00,  1.29it/s]\n","                 all         100         288       0.651       0.226       0.213      0.0692\n","\n","     Epoch   gpu_mem       box       obj       cls     total    labels  img_size\n","     10/99     11.1G   0.05071   0.01238   0.01597   0.07907        12       640: 100% 22/22 [00:24<00:00,  1.13s/it]\n","               Class      Images      Labels           P           R      mAP@.5  mAP@.5:.95: 100% 4/4 [00:02<00:00,  1.40it/s]\n","                 all         100         288       0.533       0.423        0.34       0.129\n","\n","     Epoch   gpu_mem       box       obj       cls     total    labels  img_size\n","     11/99     11.1G   0.04892   0.01149   0.01567   0.07607         6       640: 100% 22/22 [00:27<00:00,  1.26s/it]\n","               Class      Images      Labels           P           R      mAP@.5  mAP@.5:.95: 100% 4/4 [00:03<00:00,  1.13it/s]\n","                 all         100         288        0.72       0.304       0.308       0.127\n","\n","     Epoch   gpu_mem       box       obj       cls     total    labels  img_size\n","     12/99     11.1G   0.05012   0.01233   0.01369   0.07614         9       640: 100% 22/22 [00:23<00:00,  1.08s/it]\n","               Class      Images      Labels           P           R      mAP@.5  mAP@.5:.95: 100% 4/4 [00:03<00:00,  1.04it/s]\n","                 all         100         288       0.657       0.354       0.367       0.155\n","\n","     Epoch   gpu_mem       box       obj       cls     total    labels  img_size\n","     13/99     11.1G   0.05234   0.01163   0.01401   0.07798         7       640: 100% 22/22 [00:24<00:00,  1.12s/it]\n","               Class      Images      Labels           P           R      mAP@.5  mAP@.5:.95: 100% 4/4 [00:02<00:00,  1.43it/s]\n","                 all         100         288       0.781       0.408       0.404       0.155\n","\n","     Epoch   gpu_mem       box       obj       cls     total    labels  img_size\n","     14/99     11.1G   0.04692   0.01152   0.01176    0.0702         3       640: 100% 22/22 [00:29<00:00,  1.35s/it]\n","               Class      Images      Labels           P           R      mAP@.5  mAP@.5:.95: 100% 4/4 [00:02<00:00,  1.45it/s]\n","                 all         100         288       0.588       0.352       0.278      0.0931\n","\n","     Epoch   gpu_mem       box       obj       cls     total    labels  img_size\n","     15/99     11.1G   0.05109    0.0118   0.01345   0.07634         6       640: 100% 22/22 [00:24<00:00,  1.09s/it]\n","               Class      Images      Labels           P           R      mAP@.5  mAP@.5:.95: 100% 4/4 [00:03<00:00,  1.07it/s]\n","                 all         100         288       0.604       0.441       0.336       0.136\n","\n","     Epoch   gpu_mem       box       obj       cls     total    labels  img_size\n","     16/99     11.1G   0.04412     0.012   0.01314   0.06925        10       640: 100% 22/22 [00:25<00:00,  1.14s/it]\n","               Class      Images      Labels           P           R      mAP@.5  mAP@.5:.95: 100% 4/4 [00:02<00:00,  1.43it/s]\n","                 all         100         288       0.495        0.27       0.205      0.0824\n","\n","     Epoch   gpu_mem       box       obj       cls     total    labels  img_size\n","     17/99     11.1G   0.04513   0.01139   0.01171   0.06823        10       640: 100% 22/22 [00:24<00:00,  1.13s/it]\n","               Class      Images      Labels           P           R      mAP@.5  mAP@.5:.95: 100% 4/4 [00:04<00:00,  1.14s/it]\n","                 all         100         288       0.661       0.345       0.348        0.13\n","\n","     Epoch   gpu_mem       box       obj       cls     total    labels  img_size\n","     18/99     11.1G   0.04013   0.01212   0.01091   0.06316         6       640: 100% 22/22 [00:23<00:00,  1.08s/it]\n","               Class      Images      Labels           P           R      mAP@.5  mAP@.5:.95: 100% 4/4 [00:02<00:00,  1.38it/s]\n","                 all         100         288       0.287       0.235      0.0476      0.0158\n","\n","     Epoch   gpu_mem       box       obj       cls     total    labels  img_size\n","     19/99     11.1G   0.04957   0.01165   0.01278     0.074        14       640: 100% 22/22 [00:25<00:00,  1.17s/it]\n","               Class      Images      Labels           P           R      mAP@.5  mAP@.5:.95: 100% 4/4 [00:02<00:00,  1.52it/s]\n","                 all         100         288       0.552       0.201        0.16      0.0534\n","\n","     Epoch   gpu_mem       box       obj       cls     total    labels  img_size\n","     20/99     11.1G    0.0432   0.01099   0.01003   0.06421         6       640: 100% 22/22 [00:23<00:00,  1.07s/it]\n","               Class      Images      Labels           P           R      mAP@.5  mAP@.5:.95: 100% 4/4 [00:03<00:00,  1.03it/s]\n","                 all         100         288       0.742       0.425       0.436       0.172\n","\n","     Epoch   gpu_mem       box       obj       cls     total    labels  img_size\n","     21/99     11.1G   0.04771   0.01147   0.01063   0.06981         7       640: 100% 22/22 [00:24<00:00,  1.12s/it]\n","               Class      Images      Labels           P           R      mAP@.5  mAP@.5:.95: 100% 4/4 [00:03<00:00,  1.21it/s]\n","                 all         100         288       0.652       0.393       0.377       0.151\n","\n","     Epoch   gpu_mem       box       obj       cls     total    labels  img_size\n","     22/99     11.1G   0.04425   0.01208   0.01183   0.06816         5       640: 100% 22/22 [00:25<00:00,  1.15s/it]\n","               Class      Images      Labels           P           R      mAP@.5  mAP@.5:.95: 100% 4/4 [00:03<00:00,  1.32it/s]\n","                 all         100         288         0.5       0.259       0.167      0.0529\n","\n","     Epoch   gpu_mem       box       obj       cls     total    labels  img_size\n","     23/99     11.1G     0.048   0.01277   0.01482   0.07559         7       640: 100% 22/22 [00:23<00:00,  1.08s/it]\n","               Class      Images      Labels           P           R      mAP@.5  mAP@.5:.95: 100% 4/4 [00:04<00:00,  1.04s/it]\n","                 all         100         288       0.246      0.0255      0.0052    0.000953\n","\n","     Epoch   gpu_mem       box       obj       cls     total    labels  img_size\n","     24/99     12.5G   0.04232   0.01214   0.01148   0.06595         3       640: 100% 22/22 [00:24<00:00,  1.10s/it]\n","               Class      Images      Labels           P           R      mAP@.5  mAP@.5:.95: 100% 4/4 [00:02<00:00,  1.65it/s]\n","                 all         100         288       0.203      0.0129    0.000624    0.000163\n","\n","     Epoch   gpu_mem       box       obj       cls     total    labels  img_size\n","     25/99     12.5G   0.04772   0.01205   0.01165   0.07142         8       640: 100% 22/22 [00:25<00:00,  1.18s/it]\n","               Class      Images      Labels           P           R      mAP@.5  mAP@.5:.95: 100% 4/4 [00:03<00:00,  1.06it/s]\n","                 all         100         288       0.222      0.0632      0.0099     0.00151\n","\n","     Epoch   gpu_mem       box       obj       cls     total    labels  img_size\n","     26/99     12.5G   0.04478   0.01225   0.01105   0.06808        16       640: 100% 22/22 [00:24<00:00,  1.10s/it]\n","               Class      Images      Labels           P           R      mAP@.5  mAP@.5:.95: 100% 4/4 [00:02<00:00,  1.36it/s]\n","                 all         100         288      0.0144      0.0585     0.00311    0.000925\n","\n","     Epoch   gpu_mem       box       obj       cls     total    labels  img_size\n","     27/99     12.5G   0.04159   0.01187   0.01049   0.06394         8       640: 100% 22/22 [00:24<00:00,  1.13s/it]\n","               Class      Images      Labels           P           R      mAP@.5  mAP@.5:.95: 100% 4/4 [00:02<00:00,  1.36it/s]\n","                 all         100         288       0.669       0.333       0.331       0.131\n","\n","     Epoch   gpu_mem       box       obj       cls     total    labels  img_size\n","     28/99     12.5G   0.04176    0.0119  0.009673   0.06334        15       640: 100% 22/22 [00:23<00:00,  1.07s/it]\n","               Class      Images      Labels           P           R      mAP@.5  mAP@.5:.95: 100% 4/4 [00:02<00:00,  1.45it/s]\n","                 all         100         288        0.66       0.331       0.325       0.123\n","\n","     Epoch   gpu_mem       box       obj       cls     total    labels  img_size\n","     29/99     12.5G   0.03409   0.01088  0.007783   0.05274         5       640: 100% 22/22 [00:25<00:00,  1.17s/it]\n","               Class      Images      Labels           P           R      mAP@.5  mAP@.5:.95: 100% 4/4 [00:02<00:00,  1.35it/s]\n","                 all         100         288       0.608       0.396       0.366       0.156\n","\n","     Epoch   gpu_mem       box       obj       cls     total    labels  img_size\n","     30/99     12.5G    0.0388    0.0115  0.009283   0.05958        10       640: 100% 22/22 [00:22<00:00,  1.03s/it]\n","               Class      Images      Labels           P           R      mAP@.5  mAP@.5:.95: 100% 4/4 [00:03<00:00,  1.08it/s]\n","                 all         100         288       0.709       0.431       0.439       0.178\n","\n","     Epoch   gpu_mem       box       obj       cls     total    labels  img_size\n","     31/99     12.5G    0.0423   0.01166  0.009611   0.06357        11       640: 100% 22/22 [00:23<00:00,  1.07s/it]\n","               Class      Images      Labels           P           R      mAP@.5  mAP@.5:.95: 100% 4/4 [00:03<00:00,  1.26it/s]\n","                 all         100         288       0.615       0.448        0.36       0.115\n","\n","     Epoch   gpu_mem       box       obj       cls     total    labels  img_size\n","     32/99     12.5G   0.04047   0.01151  0.008159   0.06014         5       640: 100% 22/22 [00:25<00:00,  1.16s/it]\n","               Class      Images      Labels           P           R      mAP@.5  mAP@.5:.95: 100% 4/4 [00:03<00:00,  1.26it/s]\n","                 all         100         288       0.719       0.509       0.491        0.21\n","\n","     Epoch   gpu_mem       box       obj       cls     total    labels  img_size\n","     33/99     12.5G   0.03315   0.01125  0.006074   0.05048         7       640: 100% 22/22 [00:26<00:00,  1.22s/it]\n","               Class      Images      Labels           P           R      mAP@.5  mAP@.5:.95: 100% 4/4 [00:04<00:00,  1.09s/it]\n","                 all         100         288       0.752       0.462       0.484       0.197\n","\n","     Epoch   gpu_mem       box       obj       cls     total    labels  img_size\n","     34/99     12.5G   0.03997   0.01078   0.00829   0.05904         5       640: 100% 22/22 [00:23<00:00,  1.08s/it]\n","               Class      Images      Labels           P           R      mAP@.5  mAP@.5:.95: 100% 4/4 [00:02<00:00,  1.45it/s]\n","                 all         100         288       0.754       0.488       0.485       0.194\n","\n","     Epoch   gpu_mem       box       obj       cls     total    labels  img_size\n","     35/99     12.5G   0.03453   0.01095  0.006492   0.05196         3       640: 100% 22/22 [00:23<00:00,  1.08s/it]\n","               Class      Images      Labels           P           R      mAP@.5  mAP@.5:.95: 100% 4/4 [00:05<00:00,  1.29s/it]\n","                 all         100         288       0.693       0.508        0.48       0.196\n","\n","     Epoch   gpu_mem       box       obj       cls     total    labels  img_size\n","     36/99     12.5G   0.03006   0.01114  0.005025   0.04622        10       640: 100% 22/22 [00:22<00:00,  1.03s/it]\n","               Class      Images      Labels           P           R      mAP@.5  mAP@.5:.95: 100% 4/4 [00:02<00:00,  1.53it/s]\n","                 all         100         288       0.782        0.58       0.562       0.238\n","\n","     Epoch   gpu_mem       box       obj       cls     total    labels  img_size\n","     37/99     12.5G   0.03526   0.01159  0.005378   0.05223        13       640: 100% 22/22 [00:25<00:00,  1.17s/it]\n","               Class      Images      Labels           P           R      mAP@.5  mAP@.5:.95: 100% 4/4 [00:03<00:00,  1.05it/s]\n","                 all         100         288       0.787       0.553       0.565       0.245\n","\n","     Epoch   gpu_mem       box       obj       cls     total    labels  img_size\n","     38/99     12.5G   0.03932   0.01064  0.007064   0.05703         2       640: 100% 22/22 [00:23<00:00,  1.07s/it]\n","               Class      Images      Labels           P           R      mAP@.5  mAP@.5:.95: 100% 4/4 [00:03<00:00,  1.08it/s]\n","                 all         100         288       0.762       0.522       0.522       0.219\n","\n","     Epoch   gpu_mem       box       obj       cls     total    labels  img_size\n","     39/99     12.5G   0.03437   0.01116  0.007261    0.0528         8       640: 100% 22/22 [00:23<00:00,  1.06s/it]\n","               Class      Images      Labels           P           R      mAP@.5  mAP@.5:.95: 100% 4/4 [00:02<00:00,  1.48it/s]\n","                 all         100         288       0.661       0.425       0.393       0.157\n","\n","     Epoch   gpu_mem       box       obj       cls     total    labels  img_size\n","     40/99     12.5G   0.03686   0.01142  0.007929   0.05621         7       640: 100% 22/22 [00:23<00:00,  1.07s/it]\n","               Class      Images      Labels           P           R      mAP@.5  mAP@.5:.95: 100% 4/4 [00:04<00:00,  1.18s/it]\n","                 all         100         288       0.682       0.435       0.424       0.181\n","\n","     Epoch   gpu_mem       box       obj       cls     total    labels  img_size\n","     41/99     12.5G   0.03994   0.01121  0.008274   0.05943         7       640: 100% 22/22 [00:23<00:00,  1.08s/it]\n","               Class      Images      Labels           P           R      mAP@.5  mAP@.5:.95: 100% 4/4 [00:02<00:00,  1.44it/s]\n","                 all         100         288       0.547       0.378       0.307       0.108\n","\n","     Epoch   gpu_mem       box       obj       cls     total    labels  img_size\n","     42/99     12.5G   0.04126   0.01123   0.00747   0.05996        17       640: 100% 22/22 [00:29<00:00,  1.34s/it]\n","               Class      Images      Labels           P           R      mAP@.5  mAP@.5:.95: 100% 4/4 [00:02<00:00,  1.45it/s]\n","                 all         100         288       0.618       0.512       0.418       0.167\n","\n","     Epoch   gpu_mem       box       obj       cls     total    labels  img_size\n","     43/99     12.5G    0.0383   0.01129  0.008437   0.05802         7       640: 100% 22/22 [00:23<00:00,  1.05s/it]\n","               Class      Images      Labels           P           R      mAP@.5  mAP@.5:.95: 100% 4/4 [00:03<00:00,  1.15it/s]\n","                 all         100         288       0.635       0.365       0.341       0.155\n","\n","     Epoch   gpu_mem       box       obj       cls     total    labels  img_size\n","     44/99     12.5G   0.03607   0.01165  0.008139   0.05586        17       640: 100% 22/22 [00:23<00:00,  1.06s/it]\n","               Class      Images      Labels           P           R      mAP@.5  mAP@.5:.95: 100% 4/4 [00:02<00:00,  1.57it/s]\n","                 all         100         288       0.617       0.429       0.388        0.15\n","\n","     Epoch   gpu_mem       box       obj       cls     total    labels  img_size\n","     45/99     12.5G   0.03057   0.01103  0.006084   0.04768         3       640: 100% 22/22 [00:23<00:00,  1.06s/it]\n","               Class      Images      Labels           P           R      mAP@.5  mAP@.5:.95: 100% 4/4 [00:04<00:00,  1.01s/it]\n","                 all         100         288       0.493       0.256       0.227      0.0803\n","\n","     Epoch   gpu_mem       box       obj       cls     total    labels  img_size\n","     46/99     12.5G   0.03219   0.01143  0.005667   0.04929         8       640: 100% 22/22 [00:23<00:00,  1.06s/it]\n","               Class      Images      Labels           P           R      mAP@.5  mAP@.5:.95: 100% 4/4 [00:02<00:00,  1.53it/s]\n","                 all         100         288       0.516       0.412       0.302        0.12\n","\n","     Epoch   gpu_mem       box       obj       cls     total    labels  img_size\n","     47/99     12.5G   0.03642   0.01104  0.007334   0.05479         8       640: 100% 22/22 [00:23<00:00,  1.08s/it]\n","               Class      Images      Labels           P           R      mAP@.5  mAP@.5:.95: 100% 4/4 [00:04<00:00,  1.16s/it]\n","                 all         100         288       0.447       0.266       0.185      0.0716\n","\n","     Epoch   gpu_mem       box       obj       cls     total    labels  img_size\n","     48/99     12.5G   0.03508   0.01072  0.006626   0.05243         3       640: 100% 22/22 [00:23<00:00,  1.05s/it]\n","               Class      Images      Labels           P           R      mAP@.5  mAP@.5:.95: 100% 4/4 [00:02<00:00,  1.47it/s]\n","                 all         100         288       0.697       0.519       0.491       0.203\n","\n","     Epoch   gpu_mem       box       obj       cls     total    labels  img_size\n","     49/99     12.5G   0.03671   0.01109  0.008408    0.0562         8       640: 100% 22/22 [00:23<00:00,  1.06s/it]\n","               Class      Images      Labels           P           R      mAP@.5  mAP@.5:.95: 100% 4/4 [00:04<00:00,  1.17s/it]\n","                 all         100         288        0.63       0.377       0.355       0.142\n","\n","     Epoch   gpu_mem       box       obj       cls     total    labels  img_size\n","     50/99     12.5G   0.03919   0.01119  0.009259   0.05964         9       640: 100% 22/22 [00:23<00:00,  1.08s/it]\n","               Class      Images      Labels           P           R      mAP@.5  mAP@.5:.95: 100% 4/4 [00:03<00:00,  1.21it/s]\n","                 all         100         288       0.668       0.398        0.36       0.154\n","\n","     Epoch   gpu_mem       box       obj       cls     total    labels  img_size\n","     51/99     12.5G   0.04162    0.0117  0.006991   0.06031         6       640: 100% 22/22 [00:24<00:00,  1.13s/it]\n","               Class      Images      Labels           P           R      mAP@.5  mAP@.5:.95: 100% 4/4 [00:04<00:00,  1.17s/it]\n","                 all         100         288       0.486       0.394       0.299       0.129\n","\n","     Epoch   gpu_mem       box       obj       cls     total    labels  img_size\n","     52/99     12.5G   0.03476   0.01171  0.008199   0.05466         5       640: 100% 22/22 [00:24<00:00,  1.10s/it]\n","               Class      Images      Labels           P           R      mAP@.5  mAP@.5:.95: 100% 4/4 [00:05<00:00,  1.28s/it]\n","                 all         100         288       0.589       0.424       0.381       0.152\n","\n","     Epoch   gpu_mem       box       obj       cls     total    labels  img_size\n","     53/99     12.5G   0.03457     0.012  0.006016   0.05258         8       640: 100% 22/22 [00:23<00:00,  1.07s/it]\n","               Class      Images      Labels           P           R      mAP@.5  mAP@.5:.95: 100% 4/4 [00:02<00:00,  1.44it/s]\n","                 all         100         288       0.636       0.453       0.436        0.19\n","\n","     Epoch   gpu_mem       box       obj       cls     total    labels  img_size\n","     54/99     12.5G   0.03861   0.01102  0.006828   0.05646         6       640: 100% 22/22 [00:25<00:00,  1.15s/it]\n","               Class      Images      Labels           P           R      mAP@.5  mAP@.5:.95: 100% 4/4 [00:03<00:00,  1.32it/s]\n","                 all         100         288       0.727       0.516       0.516       0.232\n","\n","     Epoch   gpu_mem       box       obj       cls     total    labels  img_size\n","     55/99     12.5G   0.03131   0.01063  0.006179   0.04812         9       640: 100% 22/22 [00:23<00:00,  1.07s/it]\n","               Class      Images      Labels           P           R      mAP@.5  mAP@.5:.95: 100% 4/4 [00:03<00:00,  1.20it/s]\n","                 all         100         288       0.707       0.553       0.543       0.246\n","\n","     Epoch   gpu_mem       box       obj       cls     total    labels  img_size\n","     56/99     12.5G   0.03279   0.01064  0.005051   0.04848         7       640: 100% 22/22 [00:24<00:00,  1.12s/it]\n","               Class      Images      Labels           P           R      mAP@.5  mAP@.5:.95: 100% 4/4 [00:02<00:00,  1.39it/s]\n","                 all         100         288       0.706       0.612       0.559       0.255\n","\n","     Epoch   gpu_mem       box       obj       cls     total    labels  img_size\n","     57/99     12.5G   0.03458   0.01118   0.00592   0.05168         7       640: 100% 22/22 [00:24<00:00,  1.11s/it]\n","               Class      Images      Labels           P           R      mAP@.5  mAP@.5:.95: 100% 4/4 [00:03<00:00,  1.04it/s]\n","                 all         100         288       0.748       0.601       0.563       0.265\n","\n","     Epoch   gpu_mem       box       obj       cls     total    labels  img_size\n","     58/99     12.5G   0.03083   0.01102  0.004703   0.04655        14       640: 100% 22/22 [00:25<00:00,  1.14s/it]\n","               Class      Images      Labels           P           R      mAP@.5  mAP@.5:.95: 100% 4/4 [00:03<00:00,  1.14it/s]\n","                 all         100         288       0.793       0.576        0.59       0.278\n","\n","     Epoch   gpu_mem       box       obj       cls     total    labels  img_size\n","     59/99     12.5G    0.0329   0.01115  0.005283   0.04933         7       640: 100% 22/22 [00:24<00:00,  1.11s/it]\n","               Class      Images      Labels           P           R      mAP@.5  mAP@.5:.95: 100% 4/4 [00:02<00:00,  1.45it/s]\n","                 all         100         288       0.768       0.579        0.58       0.281\n","\n","     Epoch   gpu_mem       box       obj       cls     total    labels  img_size\n","     60/99     12.5G   0.03244   0.01114  0.005445   0.04902         5       640: 100% 22/22 [00:27<00:00,  1.27s/it]\n","               Class      Images      Labels           P           R      mAP@.5  mAP@.5:.95: 100% 4/4 [00:04<00:00,  1.10s/it]\n","                 all         100         288        0.76       0.632       0.596       0.283\n","\n","     Epoch   gpu_mem       box       obj       cls     total    labels  img_size\n","     61/99     12.5G   0.02782   0.01129  0.003955   0.04307         6       640: 100% 22/22 [00:24<00:00,  1.10s/it]\n","               Class      Images      Labels           P           R      mAP@.5  mAP@.5:.95: 100% 4/4 [00:03<00:00,  1.27it/s]\n","                 all         100         288       0.768       0.609       0.598       0.291\n","\n","     Epoch   gpu_mem       box       obj       cls     total    labels  img_size\n","     62/99     12.5G   0.03529   0.01113  0.006207   0.05263        13       640: 100% 22/22 [00:23<00:00,  1.09s/it]\n","               Class      Images      Labels           P           R      mAP@.5  mAP@.5:.95: 100% 4/4 [00:02<00:00,  1.46it/s]\n","                 all         100         288       0.789       0.591       0.579       0.283\n","\n","     Epoch   gpu_mem       box       obj       cls     total    labels  img_size\n","     63/99     12.5G    0.0314   0.01119  0.004977   0.04756        11       640: 100% 22/22 [00:24<00:00,  1.09s/it]\n","               Class      Images      Labels           P           R      mAP@.5  mAP@.5:.95: 100% 4/4 [00:04<00:00,  1.12s/it]\n","                 all         100         288       0.801       0.589       0.595       0.288\n","\n","     Epoch   gpu_mem       box       obj       cls     total    labels  img_size\n","     64/99     12.5G   0.02789   0.01062  0.004013   0.04253         6       640: 100% 22/22 [00:23<00:00,  1.05s/it]\n","               Class      Images      Labels           P           R      mAP@.5  mAP@.5:.95: 100% 4/4 [00:02<00:00,  1.51it/s]\n","                 all         100         288       0.824       0.582       0.614        0.31\n","\n","     Epoch   gpu_mem       box       obj       cls     total    labels  img_size\n","     65/99     12.5G   0.02664   0.01145   0.00424   0.04233        10       640: 100% 22/22 [00:25<00:00,  1.16s/it]\n","               Class      Images      Labels           P           R      mAP@.5  mAP@.5:.95: 100% 4/4 [00:02<00:00,  1.41it/s]\n","                 all         100         288       0.811       0.609       0.612       0.309\n","\n","     Epoch   gpu_mem       box       obj       cls     total    labels  img_size\n","     66/99     12.5G   0.03078   0.01069  0.005281   0.04675        15       640: 100% 22/22 [00:25<00:00,  1.16s/it]\n","               Class      Images      Labels           P           R      mAP@.5  mAP@.5:.95: 100% 4/4 [00:04<00:00,  1.14s/it]\n","                 all         100         288       0.811       0.617       0.622       0.304\n","\n","     Epoch   gpu_mem       box       obj       cls     total    labels  img_size\n","     67/99     12.5G   0.02811   0.01095  0.003605   0.04266         8       640: 100% 22/22 [00:24<00:00,  1.10s/it]\n","               Class      Images      Labels           P           R      mAP@.5  mAP@.5:.95: 100% 4/4 [00:02<00:00,  1.53it/s]\n","                 all         100         288       0.833       0.578       0.599       0.294\n","\n","     Epoch   gpu_mem       box       obj       cls     total    labels  img_size\n","     68/99     12.5G   0.02922   0.01112  0.004176   0.04451        11       640: 100% 22/22 [00:26<00:00,  1.22s/it]\n","               Class      Images      Labels           P           R      mAP@.5  mAP@.5:.95: 100% 4/4 [00:02<00:00,  1.43it/s]\n","                 all         100         288       0.801       0.646       0.617       0.298\n","\n","     Epoch   gpu_mem       box       obj       cls     total    labels  img_size\n","     69/99     12.5G   0.03134    0.0106  0.005991   0.04793         9       640: 100% 22/22 [00:27<00:00,  1.23s/it]\n","               Class      Images      Labels           P           R      mAP@.5  mAP@.5:.95: 100% 4/4 [00:04<00:00,  1.19s/it]\n","                 all         100         288        0.79       0.675        0.62       0.302\n","\n","     Epoch   gpu_mem       box       obj       cls     total    labels  img_size\n","     70/99     14.8G   0.02842   0.01061  0.003721   0.04275         6       640: 100% 22/22 [00:24<00:00,  1.12s/it]\n","               Class      Images      Labels           P           R      mAP@.5  mAP@.5:.95: 100% 4/4 [00:02<00:00,  1.46it/s]\n","                 all         100         288       0.855       0.629       0.628       0.313\n","\n","     Epoch   gpu_mem       box       obj       cls     total    labels  img_size\n","     71/99     14.8G   0.03367   0.01046  0.005545   0.04968         7       640: 100% 22/22 [00:26<00:00,  1.20s/it]\n","               Class      Images      Labels           P           R      mAP@.5  mAP@.5:.95: 100% 4/4 [00:02<00:00,  1.42it/s]\n","                 all         100         288       0.846       0.654       0.629       0.321\n","\n","     Epoch   gpu_mem       box       obj       cls     total    labels  img_size\n","     72/99     14.8G   0.02641   0.01142  0.003645   0.04147        19       640: 100% 22/22 [00:27<00:00,  1.25s/it]\n","               Class      Images      Labels           P           R      mAP@.5  mAP@.5:.95: 100% 4/4 [00:02<00:00,  1.38it/s]\n","                 all         100         288       0.824       0.668       0.632       0.323\n","\n","     Epoch   gpu_mem       box       obj       cls     total    labels  img_size\n","     73/99     14.8G   0.02626   0.01099   0.00332   0.04057        12       640: 100% 22/22 [00:24<00:00,  1.13s/it]\n","               Class      Images      Labels           P           R      mAP@.5  mAP@.5:.95: 100% 4/4 [00:04<00:00,  1.22s/it]\n","                 all         100         288       0.826       0.646       0.633       0.317\n","\n","     Epoch   gpu_mem       box       obj       cls     total    labels  img_size\n","     74/99     14.8G   0.02931   0.01049  0.003847   0.04364         3       640: 100% 22/22 [00:23<00:00,  1.08s/it]\n","               Class      Images      Labels           P           R      mAP@.5  mAP@.5:.95: 100% 4/4 [00:02<00:00,  1.43it/s]\n","                 all         100         288       0.842       0.645       0.632       0.316\n","\n","     Epoch   gpu_mem       box       obj       cls     total    labels  img_size\n","     75/99     14.8G   0.03672   0.01061  0.005893   0.05323        15       640: 100% 22/22 [00:27<00:00,  1.27s/it]\n","               Class      Images      Labels           P           R      mAP@.5  mAP@.5:.95: 100% 4/4 [00:02<00:00,  1.45it/s]\n","                 all         100         288       0.816       0.666       0.631       0.311\n","\n","     Epoch   gpu_mem       box       obj       cls     total    labels  img_size\n","     76/99     14.8G   0.02999   0.01056  0.004733   0.04529        12       640: 100% 22/22 [00:23<00:00,  1.08s/it]\n","               Class      Images      Labels           P           R      mAP@.5  mAP@.5:.95: 100% 4/4 [00:03<00:00,  1.01it/s]\n","                 all         100         288       0.846       0.616       0.639       0.327\n","\n","     Epoch   gpu_mem       box       obj       cls     total    labels  img_size\n","     77/99     14.8G     0.033   0.01089  0.005566   0.04946         8       640: 100% 22/22 [00:26<00:00,  1.21s/it]\n","               Class      Images      Labels           P           R      mAP@.5  mAP@.5:.95: 100% 4/4 [00:03<00:00,  1.06it/s]\n","                 all         100         288       0.807        0.66       0.633       0.314\n","\n","     Epoch   gpu_mem       box       obj       cls     total    labels  img_size\n","     78/99     14.8G   0.02847   0.01014  0.004611   0.04322         2       640: 100% 22/22 [00:23<00:00,  1.08s/it]\n","               Class      Images      Labels           P           R      mAP@.5  mAP@.5:.95: 100% 4/4 [00:02<00:00,  1.47it/s]\n","                 all         100         288       0.803       0.659       0.631       0.322\n","\n","     Epoch   gpu_mem       box       obj       cls     total    labels  img_size\n","     79/99     14.8G   0.02719   0.01045  0.004324   0.04197        11       640: 100% 22/22 [00:23<00:00,  1.05s/it]\n","               Class      Images      Labels           P           R      mAP@.5  mAP@.5:.95: 100% 4/4 [00:04<00:00,  1.22s/it]\n","                 all         100         288       0.839       0.629       0.634       0.321\n","\n","     Epoch   gpu_mem       box       obj       cls     total    labels  img_size\n","     80/99     14.8G   0.02886   0.01071  0.005248   0.04482         7       640: 100% 22/22 [00:23<00:00,  1.06s/it]\n","               Class      Images      Labels           P           R      mAP@.5  mAP@.5:.95: 100% 4/4 [00:02<00:00,  1.62it/s]\n","                 all         100         288       0.857        0.63       0.639       0.314\n","\n","     Epoch   gpu_mem       box       obj       cls     total    labels  img_size\n","     81/99     14.8G    0.0261   0.01059  0.003542   0.04023        11       640: 100% 22/22 [00:24<00:00,  1.10s/it]\n","               Class      Images      Labels           P           R      mAP@.5  mAP@.5:.95: 100% 4/4 [00:03<00:00,  1.01it/s]\n","                 all         100         288       0.848       0.644       0.634       0.316\n","\n","     Epoch   gpu_mem       box       obj       cls     total    labels  img_size\n","     82/99     14.8G   0.03742   0.01067  0.005535   0.05363        10       640: 100% 22/22 [00:23<00:00,  1.08s/it]\n","               Class      Images      Labels           P           R      mAP@.5  mAP@.5:.95: 100% 4/4 [00:02<00:00,  1.53it/s]\n","                 all         100         288       0.845       0.639       0.635       0.323\n","\n","     Epoch   gpu_mem       box       obj       cls     total    labels  img_size\n","     83/99     14.8G   0.02991   0.01021  0.004426   0.04455         3       640: 100% 22/22 [00:25<00:00,  1.14s/it]\n","               Class      Images      Labels           P           R      mAP@.5  mAP@.5:.95: 100% 4/4 [00:03<00:00,  1.20it/s]\n","                 all         100         288       0.831       0.628       0.632       0.318\n","\n","     Epoch   gpu_mem       box       obj       cls     total    labels  img_size\n","     84/99     14.8G   0.02378   0.01066  0.002875   0.03732        12       640: 100% 22/22 [00:23<00:00,  1.06s/it]\n","               Class      Images      Labels           P           R      mAP@.5  mAP@.5:.95: 100% 4/4 [00:02<00:00,  1.52it/s]\n","                 all         100         288       0.827       0.624        0.63       0.317\n","\n","     Epoch   gpu_mem       box       obj       cls     total    labels  img_size\n","     85/99     14.8G   0.03177   0.01046  0.004875   0.04711         6       640: 100% 22/22 [00:25<00:00,  1.15s/it]\n","               Class      Images      Labels           P           R      mAP@.5  mAP@.5:.95: 100% 4/4 [00:03<00:00,  1.33it/s]\n","                 all         100         288       0.836       0.631       0.647       0.329\n","\n","     Epoch   gpu_mem       box       obj       cls     total    labels  img_size\n","     86/99     14.8G    0.0245   0.01024  0.003688   0.03843        10       640: 100% 22/22 [00:24<00:00,  1.11s/it]\n","               Class      Images      Labels           P           R      mAP@.5  mAP@.5:.95: 100% 4/4 [00:03<00:00,  1.06it/s]\n","                 all         100         288       0.807       0.666       0.644       0.331\n","\n","     Epoch   gpu_mem       box       obj       cls     total    labels  img_size\n","     87/99     14.8G   0.03064   0.01092  0.005272   0.04684        13       640: 100% 22/22 [00:26<00:00,  1.18s/it]\n","               Class      Images      Labels           P           R      mAP@.5  mAP@.5:.95: 100% 4/4 [00:02<00:00,  1.39it/s]\n","                 all         100         288        0.81       0.654        0.63       0.325\n","\n","     Epoch   gpu_mem       box       obj       cls     total    labels  img_size\n","     88/99     14.8G   0.02701   0.01033  0.003986   0.04133         7       640: 100% 22/22 [00:25<00:00,  1.15s/it]\n","               Class      Images      Labels           P           R      mAP@.5  mAP@.5:.95: 100% 4/4 [00:02<00:00,  1.60it/s]\n","                 all         100         288       0.834       0.633       0.642       0.328\n","\n","     Epoch   gpu_mem       box       obj       cls     total    labels  img_size\n","     89/99     14.8G   0.02786   0.01021  0.004346   0.04242         3       640: 100% 22/22 [00:22<00:00,  1.04s/it]\n","               Class      Images      Labels           P           R      mAP@.5  mAP@.5:.95: 100% 4/4 [00:02<00:00,  1.39it/s]\n","                 all         100         288       0.831       0.624       0.624       0.319\n","\n","     Epoch   gpu_mem       box       obj       cls     total    labels  img_size\n","     90/99     14.8G     0.031   0.01031  0.004724   0.04604         5       640: 100% 22/22 [00:24<00:00,  1.13s/it]\n","               Class      Images      Labels           P           R      mAP@.5  mAP@.5:.95: 100% 4/4 [00:02<00:00,  1.48it/s]\n","                 all         100         288       0.848       0.644        0.64       0.325\n","\n","     Epoch   gpu_mem       box       obj       cls     total    labels  img_size\n","     91/99     14.8G   0.02931   0.01104  0.004801   0.04515        13       640: 100% 22/22 [00:23<00:00,  1.08s/it]\n","               Class      Images      Labels           P           R      mAP@.5  mAP@.5:.95: 100% 4/4 [00:04<00:00,  1.06s/it]\n","                 all         100         288       0.841       0.653       0.633        0.32\n","\n","     Epoch   gpu_mem       box       obj       cls     total    labels  img_size\n","     92/99     14.8G   0.02845   0.01081  0.005574   0.04484         8       640: 100% 22/22 [00:23<00:00,  1.08s/it]\n","               Class      Images      Labels           P           R      mAP@.5  mAP@.5:.95: 100% 4/4 [00:02<00:00,  1.47it/s]\n","                 all         100         288       0.841       0.636       0.626       0.318\n","\n","     Epoch   gpu_mem       box       obj       cls     total    labels  img_size\n","     93/99     14.8G   0.02426   0.01077  0.003498   0.03853         7       640: 100% 22/22 [00:24<00:00,  1.11s/it]\n","               Class      Images      Labels           P           R      mAP@.5  mAP@.5:.95: 100% 4/4 [00:04<00:00,  1.14s/it]\n","                 all         100         288        0.82       0.668       0.643       0.325\n","\n","     Epoch   gpu_mem       box       obj       cls     total    labels  img_size\n","     94/99     14.8G    0.0277   0.01062  0.004119   0.04245        19       640: 100% 22/22 [00:23<00:00,  1.07s/it]\n","               Class      Images      Labels           P           R      mAP@.5  mAP@.5:.95: 100% 4/4 [00:02<00:00,  1.52it/s]\n","                 all         100         288       0.833       0.673       0.649       0.325\n","\n","     Epoch   gpu_mem       box       obj       cls     total    labels  img_size\n","     95/99     14.8G   0.03311   0.01075  0.005632   0.04949        11       640: 100% 22/22 [00:25<00:00,  1.18s/it]\n","               Class      Images      Labels           P           R      mAP@.5  mAP@.5:.95: 100% 4/4 [00:02<00:00,  1.44it/s]\n","                 all         100         288       0.832       0.665        0.64       0.334\n","\n","     Epoch   gpu_mem       box       obj       cls     total    labels  img_size\n","     96/99     14.8G   0.02373   0.01063  0.003614   0.03798         6       640: 100% 22/22 [00:27<00:00,  1.26s/it]\n","               Class      Images      Labels           P           R      mAP@.5  mAP@.5:.95: 100% 4/4 [00:03<00:00,  1.08it/s]\n","                 all         100         288        0.82       0.678       0.647       0.335\n","\n","     Epoch   gpu_mem       box       obj       cls     total    labels  img_size\n","     97/99     14.8G   0.02934   0.01058  0.005722   0.04564        12       640: 100% 22/22 [00:24<00:00,  1.13s/it]\n","               Class      Images      Labels           P           R      mAP@.5  mAP@.5:.95: 100% 4/4 [00:04<00:00,  1.25s/it]\n","                 all         100         288       0.847       0.651       0.652       0.337\n","\n","     Epoch   gpu_mem       box       obj       cls     total    labels  img_size\n","     98/99     14.8G   0.03193   0.01042  0.005847   0.04819        12       640: 100% 22/22 [00:24<00:00,  1.10s/it]\n","               Class      Images      Labels           P           R      mAP@.5  mAP@.5:.95: 100% 4/4 [00:03<00:00,  1.29it/s]\n","                 all         100         288       0.843       0.644        0.65       0.332\n","\n","     Epoch   gpu_mem       box       obj       cls     total    labels  img_size\n","     99/99     14.8G   0.03232   0.01093  0.006601   0.04985        15       640: 100% 22/22 [00:24<00:00,  1.13s/it]\n","               Class      Images      Labels           P           R      mAP@.5  mAP@.5:.95: 100% 4/4 [00:04<00:00,  1.14s/it]\n","                 all         100         288       0.842       0.644       0.648       0.342\n","        green-lights         100          41       0.836       0.902       0.859       0.459\n","          red-lights         100          64       0.746       0.891        0.81       0.406\n","      traffic-lights         100         139       0.866       0.806       0.861       0.488\n","           turn-left         100           2           1           0           0           0\n","       yellow-lights         100          42       0.764       0.619       0.708       0.357\n","100 epochs completed in 0.889 hours.\n","\n","Optimizer stripped from runs/train/yolov7-fish3/weights/last.pt, 74.9MB\n","Optimizer stripped from runs/train/yolov7-fish3/weights/best.pt, 74.9MB\n"]}]},{"cell_type":"code","source":[],"metadata":{"id":"NQKA4hYUX-CE","executionInfo":{"status":"ok","timestamp":1718267228145,"user_tz":-480,"elapsed":4,"user":{"displayName":"黃致宇","userId":"05257376044901631491"}}},"execution_count":9,"outputs":[]},{"cell_type":"markdown","source":["## 8. 預測影像"],"metadata":{"id":"dAiCCP5SE5TR"}},{"cell_type":"code","source":["!python detect.py --weight /content/drive/MyDrive/data3/yolov7/runs/train/yolov7-fish/weights/best.pt --conf 0.04 --img-size 640 --source /content/drive/MyDrive/OIP.jpg --no-trace"],"metadata":{"id":"fRG73MdTE6zT","colab":{"base_uri":"https://localhost:8080/"},"executionInfo":{"status":"ok","timestamp":1718267455532,"user_tz":-480,"elapsed":9250,"user":{"displayName":"黃致宇","userId":"05257376044901631491"}},"outputId":"41f69cb7-ee36-4806-f60b-6930c78b9406"},"execution_count":11,"outputs":[{"output_type":"stream","name":"stdout","text":["Namespace(weights=['/content/drive/MyDrive/data3/yolov7/runs/train/yolov7-fish/weights/best.pt'], source='/content/drive/MyDrive/OIP.jpg', img_size=640, conf_thres=0.04, iou_thres=0.45, device='', view_img=False, save_txt=False, save_conf=False, nosave=False, classes=None, agnostic_nms=False, augment=False, update=False, project='runs/detect', name='exp', exist_ok=False, no_trace=True)\n","YOLOR 🚀 v0.1-128-ga207844 torch 2.3.0+cu121 CUDA:0 (Tesla T4, 15102.0625MB)\n","\n","Fusing layers... \n","RepConv.fuse_repvgg_block\n","RepConv.fuse_repvgg_block\n","RepConv.fuse_repvgg_block\n","IDetect.fuse\n","Model Summary: 314 layers, 36508742 parameters, 6194944 gradients\n","/usr/local/lib/python3.10/dist-packages/torch/functional.py:512: UserWarning: torch.meshgrid: in an upcoming release, it will be required to pass the indexing argument. (Triggered internally at ../aten/src/ATen/native/TensorShape.cpp:3587.)\n","  return _VF.meshgrid(tensors, **kwargs)  # type: ignore[attr-defined]\n","1 green-lights, 1 red-lights, 3 traffic-lightss, 1 yellow-lights, Done. (15.3ms) Inference, (567.1ms) NMS\n"," The image with the result is saved in: runs/detect/exp4/OIP.jpg\n","Done. (0.854s)\n"]}]}]}