Electrical Board Detection YOLOV8.ipynb

{
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  "metadata": {
    "colab": {
      "provenance": [],
      "gpuType": "T4"
    },
    "kernelspec": {
      "name": "python3",
      "display_name": "Python 3"
    },
    "language_info": {
      "name": "python"
    },
    "accelerator": "GPU"
  },
  "cells": [
    {
      "cell_type": "code",
      "source": [
        "ROOT_DIR = '/content/drive/MyDrive/DL_projects_colab/yolov8'"
      ],
      "metadata": {
        "id": "Yo-Fit1ftvln"
      },
      "execution_count": 1,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "%cd {ROOT_DIR}"
      ],
      "metadata": {
        "id": "iyQgileLtyxm"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "!git clone https://github.com/ultralytics/ultralytics.git"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "5cURr23Yt0Yn",
        "outputId": "0674ded0-93ea-464b-9c50-3ece4b7da0e7"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Cloning into 'ultralytics'...\n",
            "remote: Enumerating objects: 16457, done.\u001b[K\n",
            "remote: Counting objects: 100% (172/172), done.\u001b[K\n",
            "remote: Compressing objects: 100% (150/150), done.\u001b[K\n",
            "remote: Total 16457 (delta 85), reused 75 (delta 22), pack-reused 16285\u001b[K\n",
            "Receiving objects: 100% (16457/16457), 8.83 MiB | 10.14 MiB/s, done.\n",
            "Resolving deltas: 100% (11395/11395), done.\n",
            "Updating files: 100% (445/445), done.\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "%cd ultralytics"
      ],
      "metadata": {
        "id": "sgM0KUwmt2jG"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "!pip install -r requirements.txt"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "f7nqRgglt3-9",
        "outputId": "5d8ea1ca-c213-4c23-cce2-97740a74597b"
      },
      "execution_count": 4,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "\u001b[31mERROR: Could not open requirements file: [Errno 2] No such file or directory: 'requirements.txt'\u001b[0m\u001b[31m\n",
            "\u001b[0m"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "!pip install ultralytics"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "0WsaZ6Y6t6q1",
        "outputId": "544993eb-9f35-4fd6-c186-fe9253db944a"
      },
      "execution_count": 5,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Collecting ultralytics\n",
            "  Downloading ultralytics-8.0.200-py3-none-any.whl (644 kB)\n",
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            "\u001b[?25hRequirement already satisfied: matplotlib>=3.3.0 in /usr/local/lib/python3.10/dist-packages (from ultralytics) (3.7.1)\n",
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            "Collecting thop>=0.1.1 (from ultralytics)\n",
            "  Downloading thop-0.1.1.post2209072238-py3-none-any.whl (15 kB)\n",
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            "Installing collected packages: thop, ultralytics\n",
            "Successfully installed thop-0.1.1.post2209072238 ultralytics-8.0.200\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "%cd {ROOT_DIR}"
      ],
      "metadata": {
        "id": "TMAr3K0gt9L-"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "import matplotlib.pyplot as plt\n",
        "from IPython.display import Image as imgshow\n",
        "import os"
      ],
      "metadata": {
        "id": "IE7lvtsSuCk2"
      },
      "execution_count": 8,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "!pip install roboflow\n"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 1000
        },
        "id": "2OLYqnQ0uH5u",
        "outputId": "1720fd40-e87b-4c89-f999-65e9956ac517"
      },
      "execution_count": 9,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Collecting roboflow\n",
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            "Installing collected packages: python-dotenv, pyparsing, opencv-python-headless, idna, cycler, chardet, certifi, supervision, requests-toolbelt, roboflow\n",
            "  Attempting uninstall: pyparsing\n",
            "    Found existing installation: pyparsing 3.1.1\n",
            "    Uninstalling pyparsing-3.1.1:\n",
            "      Successfully uninstalled pyparsing-3.1.1\n",
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            "    Found existing installation: opencv-python-headless 4.8.1.78\n",
            "    Uninstalling opencv-python-headless-4.8.1.78:\n",
            "      Successfully uninstalled opencv-python-headless-4.8.1.78\n",
            "  Attempting uninstall: idna\n",
            "    Found existing installation: idna 3.4\n",
            "    Uninstalling idna-3.4:\n",
            "      Successfully uninstalled idna-3.4\n",
            "  Attempting uninstall: cycler\n",
            "    Found existing installation: cycler 0.12.1\n",
            "    Uninstalling cycler-0.12.1:\n",
            "      Successfully uninstalled cycler-0.12.1\n",
            "  Attempting uninstall: chardet\n",
            "    Found existing installation: chardet 5.2.0\n",
            "    Uninstalling chardet-5.2.0:\n",
            "      Successfully uninstalled chardet-5.2.0\n",
            "  Attempting uninstall: certifi\n",
            "    Found existing installation: certifi 2023.7.22\n",
            "    Uninstalling certifi-2023.7.22:\n",
            "      Successfully uninstalled certifi-2023.7.22\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",
            "lida 0.0.10 requires fastapi, which is not installed.\n",
            "lida 0.0.10 requires kaleido, which is not installed.\n",
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            "\u001b[0mSuccessfully installed certifi-2022.12.7 chardet-4.0.0 cycler-0.10.0 idna-2.10 opencv-python-headless-4.8.0.74 pyparsing-2.4.7 python-dotenv-1.0.0 requests-toolbelt-1.0.0 roboflow-1.1.7 supervision-0.16.0\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "application/vnd.colab-display-data+json": {
              "pip_warning": {
                "packages": [
                  "certifi",
                  "cycler",
                  "pyparsing"
                ]
              }
            }
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "from roboflow import Roboflow\n",
        "rf = Roboflow(api_key=\"aqKa81zmRnWwsWVUZWA1\")\n",
        "project = rf.workspace(\"rcdat\").project(\"electrical-board-detection\")\n",
        "dataset = project.version(1).download(\"yolov8\")\n"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "DKlPmzkOuMS_",
        "outputId": "d92a4046-aca4-4503-c74d-f51671885b69"
      },
      "execution_count": 1,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "loading Roboflow workspace...\n",
            "loading Roboflow project...\n",
            "Dependency ultralytics==8.0.134 is required but found version=8.0.200, to fix: `pip install ultralytics==8.0.134`\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "Downloading Dataset Version Zip in Electrical-Board-Detection-1 to yolov8:: 100%|██████████| 63288/63288 [00:03<00:00, 19152.51it/s]"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "\n",
            "Extracting Dataset Version Zip to Electrical-Board-Detection-1 in yolov8:: 100%|██████████| 1495/1495 [00:00<00:00, 5221.91it/s]\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "{dataset.location}"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "cdz00zuNuQct",
        "outputId": "e8164974-183d-4a6c-8119-896e0dbabae8"
      },
      "execution_count": 2,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "{'/content/Electrical-Board-Detection-1'}"
            ]
          },
          "metadata": {},
          "execution_count": 2
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "import yaml\n",
        "\n",
        "data_yaml_path = '/content/Electrical-Board-Detection-1/data.yaml'\n",
        "with open(data_yaml_path, 'r') as file:\n",
        "    data_yaml = yaml.safe_load(file)\n",
        "\n",
        "data_yaml['train'] = '/content/Electrical-Board-Detection-1/train/images'\n",
        "data_yaml['val'] = '/content/Electrical-Board-Detection-1/valid/images'\n",
        "data_yaml['test'] = '/content/Electrical-Board-Detection-1/test/images'\n",
        "\n",
        "with open(data_yaml_path, 'w') as file:\n",
        "    yaml.safe_dump(data_yaml, file)\n"
      ],
      "metadata": {
        "id": "5lngQkEnqC_A"
      },
      "execution_count": 3,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "!yolo task=detect mode=train model=yolov8n.pt data={dataset.location}/data.yaml epochs=80 imgsz=608"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "Dv8ETOTBuXpF",
        "outputId": "67c452d8-18ff-49a0-ea03-fabd9c576b9c"
      },
      "execution_count": 5,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Downloading https://github.com/ultralytics/assets/releases/download/v0.0.0/yolov8n.pt to 'yolov8n.pt'...\n",
            "100% 6.23M/6.23M [00:00<00:00, 117MB/s]\n",
            "Ultralytics YOLOv8.0.200 🚀 Python-3.10.12 torch-2.1.0+cu118 CUDA:0 (Tesla T4, 15102MiB)\n",
            "\u001b[34m\u001b[1mengine/trainer: \u001b[0mtask=detect, mode=train, model=yolov8n.pt, data=/content/Electrical-Board-Detection-1/data.yaml, epochs=80, patience=50, batch=16, imgsz=608, save=True, save_period=-1, cache=False, device=None, workers=8, project=None, name=train, exist_ok=False, pretrained=True, optimizer=auto, verbose=True, seed=0, deterministic=True, single_cls=False, rect=False, cos_lr=False, close_mosaic=10, resume=False, amp=True, fraction=1.0, profile=False, freeze=None, overlap_mask=True, mask_ratio=4, dropout=0.0, val=True, split=val, save_json=False, save_hybrid=False, conf=None, iou=0.7, max_det=300, half=False, dnn=False, plots=True, source=None, show=False, save_txt=False, save_conf=False, save_crop=False, show_labels=True, show_conf=True, vid_stride=1, stream_buffer=False, line_width=None, visualize=False, augment=False, agnostic_nms=False, classes=None, retina_masks=False, boxes=True, format=torchscript, keras=False, optimize=False, int8=False, dynamic=False, simplify=False, opset=None, workspace=4, nms=False, lr0=0.01, lrf=0.01, momentum=0.937, weight_decay=0.0005, warmup_epochs=3.0, warmup_momentum=0.8, warmup_bias_lr=0.1, box=7.5, cls=0.5, dfl=1.5, pose=12.0, kobj=1.0, label_smoothing=0.0, nbs=64, hsv_h=0.015, hsv_s=0.7, hsv_v=0.4, degrees=0.0, translate=0.1, 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, cfg=None, tracker=botsort.yaml, save_dir=runs/detect/train\n",
            "Downloading https://ultralytics.com/assets/Arial.ttf to '/root/.config/Ultralytics/Arial.ttf'...\n",
            "100% 755k/755k [00:00<00:00, 21.3MB/s]\n",
            "Overriding model.yaml nc=80 with nc=1\n",
            "\n",
            "                   from  n    params  module                                       arguments                     \n",
            "  0                  -1  1       464  ultralytics.nn.modules.conv.Conv             [3, 16, 3, 2]                 \n",
            "  1                  -1  1      4672  ultralytics.nn.modules.conv.Conv             [16, 32, 3, 2]                \n",
            "  2                  -1  1      7360  ultralytics.nn.modules.block.C2f             [32, 32, 1, True]             \n",
            "  3                  -1  1     18560  ultralytics.nn.modules.conv.Conv             [32, 64, 3, 2]                \n",
            "  4                  -1  2     49664  ultralytics.nn.modules.block.C2f             [64, 64, 2, True]             \n",
            "  5                  -1  1     73984  ultralytics.nn.modules.conv.Conv             [64, 128, 3, 2]               \n",
            "  6                  -1  2    197632  ultralytics.nn.modules.block.C2f             [128, 128, 2, True]           \n",
            "  7                  -1  1    295424  ultralytics.nn.modules.conv.Conv             [128, 256, 3, 2]              \n",
            "  8                  -1  1    460288  ultralytics.nn.modules.block.C2f             [256, 256, 1, True]           \n",
            "  9                  -1  1    164608  ultralytics.nn.modules.block.SPPF            [256, 256, 5]                 \n",
            " 10                  -1  1         0  torch.nn.modules.upsampling.Upsample         [None, 2, 'nearest']          \n",
            " 11             [-1, 6]  1         0  ultralytics.nn.modules.conv.Concat           [1]                           \n",
            " 12                  -1  1    148224  ultralytics.nn.modules.block.C2f             [384, 128, 1]                 \n",
            " 13                  -1  1         0  torch.nn.modules.upsampling.Upsample         [None, 2, 'nearest']          \n",
            " 14             [-1, 4]  1         0  ultralytics.nn.modules.conv.Concat           [1]                           \n",
            " 15                  -1  1     37248  ultralytics.nn.modules.block.C2f             [192, 64, 1]                  \n",
            " 16                  -1  1     36992  ultralytics.nn.modules.conv.Conv             [64, 64, 3, 2]                \n",
            " 17            [-1, 12]  1         0  ultralytics.nn.modules.conv.Concat           [1]                           \n",
            " 18                  -1  1    123648  ultralytics.nn.modules.block.C2f             [192, 128, 1]                 \n",
            " 19                  -1  1    147712  ultralytics.nn.modules.conv.Conv             [128, 128, 3, 2]              \n",
            " 20             [-1, 9]  1         0  ultralytics.nn.modules.conv.Concat           [1]                           \n",
            " 21                  -1  1    493056  ultralytics.nn.modules.block.C2f             [384, 256, 1]                 \n",
            " 22        [15, 18, 21]  1    751507  ultralytics.nn.modules.head.Detect           [1, [64, 128, 256]]           \n",
            "Model summary: 225 layers, 3011043 parameters, 3011027 gradients, 8.2 GFLOPs\n",
            "\n",
            "Transferred 319/355 items from pretrained weights\n",
            "\u001b[34m\u001b[1mTensorBoard: \u001b[0mStart with 'tensorboard --logdir runs/detect/train', view at http://localhost:6006/\n",
            "Freezing layer 'model.22.dfl.conv.weight'\n",
            "\u001b[34m\u001b[1mAMP: \u001b[0mrunning Automatic Mixed Precision (AMP) checks with YOLOv8n...\n",
            "\u001b[34m\u001b[1mAMP: \u001b[0mchecks passed ✅\n",
            "\u001b[34m\u001b[1mtrain: \u001b[0mScanning /content/Electrical-Board-Detection-1/train/labels... 519 images, 0 backgrounds, 0 corrupt: 100% 519/519 [00:00<00:00, 2184.02it/s]\n",
            "\u001b[34m\u001b[1mtrain: \u001b[0mNew cache created: /content/Electrical-Board-Detection-1/train/labels.cache\n",
            "WARNING ⚠️ Box and segment counts should be equal, but got len(segments) = 23, len(boxes) = 540. To resolve this only boxes will be used and all segments will be removed. To avoid this please supply either a detect or segment dataset, not a detect-segment mixed dataset.\n",
            "\u001b[34m\u001b[1malbumentations: \u001b[0mBlur(p=0.01, blur_limit=(3, 7)), MedianBlur(p=0.01, blur_limit=(3, 7)), ToGray(p=0.01), CLAHE(p=0.01, clip_limit=(1, 4.0), tile_grid_size=(8, 8))\n",
            "\u001b[34m\u001b[1mval: \u001b[0mScanning /content/Electrical-Board-Detection-1/valid/labels... 149 images, 0 backgrounds, 0 corrupt: 100% 149/149 [00:00<00:00, 799.22it/s]\n",
            "\u001b[34m\u001b[1mval: \u001b[0mNew cache created: /content/Electrical-Board-Detection-1/valid/labels.cache\n",
            "WARNING ⚠️ Box and segment counts should be equal, but got len(segments) = 1, len(boxes) = 151. To resolve this only boxes will be used and all segments will be removed. To avoid this please supply either a detect or segment dataset, not a detect-segment mixed dataset.\n",
            "Plotting labels to runs/detect/train/labels.jpg... \n",
            "\u001b[34m\u001b[1moptimizer:\u001b[0m 'optimizer=auto' found, ignoring 'lr0=0.01' and 'momentum=0.937' and determining best 'optimizer', 'lr0' and 'momentum' automatically... \n",
            "\u001b[34m\u001b[1moptimizer:\u001b[0m AdamW(lr=0.002, momentum=0.9) with parameter groups 57 weight(decay=0.0), 64 weight(decay=0.0005), 63 bias(decay=0.0)\n",
            "Image sizes 608 train, 608 val\n",
            "Using 2 dataloader workers\n",
            "Logging results to \u001b[1mruns/detect/train\u001b[0m\n",
            "Starting training for 80 epochs...\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n",
            "       1/80      2.17G     0.6948      1.569      1.299         22        608: 100% 33/33 [00:13<00:00,  2.39it/s]\n",
            "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100% 5/5 [00:02<00:00,  1.79it/s]\n",
            "                   all        149        151       0.94      0.954      0.973      0.693\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n",
            "       2/80      2.05G     0.6425      1.003      1.251         14        608: 100% 33/33 [00:10<00:00,  3.24it/s]\n",
            "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100% 5/5 [00:01<00:00,  2.69it/s]\n",
            "                   all        149        151      0.929      0.952      0.976      0.555\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n",
            "       3/80      2.07G     0.6542     0.9119      1.242         24        608: 100% 33/33 [00:10<00:00,  3.09it/s]\n",
            "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100% 5/5 [00:01<00:00,  2.58it/s]\n",
            "                   all        149        151      0.924      0.884      0.949      0.739\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n",
            "       4/80      2.07G     0.6781     0.8388      1.263         13        608: 100% 33/33 [00:10<00:00,  3.14it/s]\n",
            "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100% 5/5 [00:01<00:00,  2.88it/s]\n",
            "                   all        149        151       0.97       0.96      0.981      0.707\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n",
            "       5/80      2.05G     0.6583     0.7474      1.254         23        608: 100% 33/33 [00:10<00:00,  3.19it/s]\n",
            "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100% 5/5 [00:01<00:00,  2.63it/s]\n",
            "                   all        149        151      0.555      0.748      0.588      0.228\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n",
            "       6/80      2.04G     0.6279     0.7068      1.225         22        608: 100% 33/33 [00:10<00:00,  3.08it/s]\n",
            "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100% 5/5 [00:01<00:00,  2.76it/s]\n",
            "                   all        149        151      0.841      0.839      0.928      0.673\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n",
            "       7/80      2.05G     0.6501     0.6706      1.247         19        608: 100% 33/33 [00:10<00:00,  3.17it/s]\n",
            "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100% 5/5 [00:01<00:00,  2.65it/s]\n",
            "                   all        149        151      0.918      0.894      0.957      0.716\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n",
            "       8/80      2.05G     0.6364     0.6904      1.226         17        608: 100% 33/33 [00:10<00:00,  3.09it/s]\n",
            "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100% 5/5 [00:01<00:00,  2.73it/s]\n",
            "                   all        149        151      0.984      0.947      0.979      0.785\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n",
            "       9/80      2.05G     0.6022     0.5999      1.207         18        608: 100% 33/33 [00:10<00:00,  3.16it/s]\n",
            "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100% 5/5 [00:01<00:00,  2.85it/s]\n",
            "                   all        149        151       0.86      0.954      0.957      0.676\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n",
            "      10/80      2.04G     0.5634     0.5546      1.192         15        608: 100% 33/33 [00:10<00:00,  3.17it/s]\n",
            "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100% 5/5 [00:01<00:00,  2.87it/s]\n",
            "                   all        149        151        0.5      0.702      0.613      0.293\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n",
            "      11/80      2.05G     0.5665     0.5859       1.18         24        608: 100% 33/33 [00:10<00:00,  3.21it/s]\n",
            "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100% 5/5 [00:01<00:00,  2.82it/s]\n",
            "                   all        149        151       0.96      0.964      0.988       0.81\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n",
            "      12/80      2.05G     0.5707     0.5673      1.183         25        608: 100% 33/33 [00:10<00:00,  3.17it/s]\n",
            "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100% 5/5 [00:01<00:00,  3.10it/s]\n",
            "                   all        149        151      0.868      0.915      0.951      0.579\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n",
            "      13/80      2.05G     0.5385     0.5403       1.16         21        608: 100% 33/33 [00:10<00:00,  3.30it/s]\n",
            "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100% 5/5 [00:02<00:00,  2.44it/s]\n",
            "                   all        149        151      0.671      0.809      0.817      0.483\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n",
            "      14/80      2.04G     0.5363      0.519      1.167         19        608: 100% 33/33 [00:09<00:00,  3.59it/s]\n",
            "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100% 5/5 [00:02<00:00,  1.68it/s]\n",
            "                   all        149        151      0.979      0.954      0.984      0.852\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n",
            "      15/80      2.05G     0.5403     0.5277      1.172         17        608: 100% 33/33 [00:08<00:00,  3.68it/s]\n",
            "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100% 5/5 [00:03<00:00,  1.63it/s]\n",
            "                   all        149        151      0.983       0.96      0.979      0.726\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n",
            "      16/80      2.05G     0.5236     0.5016      1.154         21        608: 100% 33/33 [00:08<00:00,  3.68it/s]\n",
            "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100% 5/5 [00:02<00:00,  2.15it/s]\n",
            "                   all        149        151      0.936      0.974      0.982      0.822\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n",
            "      17/80      2.05G     0.5239     0.4867      1.158         22        608: 100% 33/33 [00:09<00:00,  3.59it/s]\n",
            "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100% 5/5 [00:01<00:00,  2.71it/s]\n",
            "                   all        149        151      0.978      0.954      0.992      0.823\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n",
            "      18/80      2.04G     0.5166     0.4787      1.161         18        608: 100% 33/33 [00:09<00:00,  3.44it/s]\n",
            "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100% 5/5 [00:01<00:00,  2.78it/s]\n",
            "                   all        149        151      0.984       0.96      0.992      0.843\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n",
            "      19/80      2.05G     0.5102     0.4913      1.146         17        608: 100% 33/33 [00:10<00:00,  3.23it/s]\n",
            "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100% 5/5 [00:01<00:00,  2.88it/s]\n",
            "                   all        149        151       0.99      0.947      0.991      0.832\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n",
            "      20/80      2.05G     0.4927     0.4715      1.139         22        608: 100% 33/33 [00:10<00:00,  3.19it/s]\n",
            "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100% 5/5 [00:01<00:00,  2.66it/s]\n",
            "                   all        149        151       0.78      0.735      0.822      0.564\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n",
            "      21/80      2.07G     0.4725     0.4528      1.116         19        608: 100% 33/33 [00:10<00:00,  3.22it/s]\n",
            "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100% 5/5 [00:01<00:00,  2.94it/s]\n",
            "                   all        149        151      0.994      0.954      0.994      0.867\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n",
            "      22/80      2.04G      0.474     0.4329      1.121         25        608: 100% 33/33 [00:10<00:00,  3.21it/s]\n",
            "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100% 5/5 [00:01<00:00,  2.74it/s]\n",
            "                   all        149        151      0.965      0.901      0.964      0.654\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n",
            "      23/80      2.05G     0.4938     0.4339      1.137         19        608: 100% 33/33 [00:10<00:00,  3.18it/s]\n",
            "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100% 5/5 [00:01<00:00,  2.82it/s]\n",
            "                   all        149        151      0.987      0.987      0.995      0.822\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n",
            "      24/80      2.05G      0.485     0.4483      1.132         26        608: 100% 33/33 [00:10<00:00,  3.17it/s]\n",
            "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100% 5/5 [00:01<00:00,  2.93it/s]\n",
            "                   all        149        151      0.968      0.987      0.992      0.852\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n",
            "      25/80      2.05G     0.4595       0.41      1.108         22        608: 100% 33/33 [00:10<00:00,  3.22it/s]\n",
            "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100% 5/5 [00:01<00:00,  2.68it/s]\n",
            "                   all        149        151      0.979      0.954      0.989      0.847\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n",
            "      26/80      2.04G     0.4649     0.3902      1.107         17        608: 100% 33/33 [00:10<00:00,  3.29it/s]\n",
            "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100% 5/5 [00:01<00:00,  2.62it/s]\n",
            "                   all        149        151       0.98      0.955      0.992      0.823\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n",
            "      27/80      2.07G     0.4795     0.3986      1.125         24        608: 100% 33/33 [00:09<00:00,  3.35it/s]\n",
            "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100% 5/5 [00:02<00:00,  2.35it/s]\n",
            "                   all        149        151      0.953      0.974      0.983      0.832\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n",
            "      28/80      2.05G      0.467     0.4182      1.108         20        608: 100% 33/33 [00:09<00:00,  3.65it/s]\n",
            "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100% 5/5 [00:02<00:00,  1.69it/s]\n",
            "                   all        149        151      0.986      0.939      0.989      0.817\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n",
            "      29/80      2.06G     0.4712     0.4066      1.113         17        608: 100% 33/33 [00:08<00:00,  3.70it/s]\n",
            "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100% 5/5 [00:02<00:00,  2.02it/s]\n",
            "                   all        149        151      0.993       0.98      0.995      0.835\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n",
            "      30/80      2.04G     0.4372     0.4005      1.101         19        608: 100% 33/33 [00:08<00:00,  3.74it/s]\n",
            "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100% 5/5 [00:01<00:00,  2.68it/s]\n",
            "                   all        149        151      0.986      0.974      0.994      0.869\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n",
            "      31/80      2.05G     0.4533     0.3958      1.105         23        608: 100% 33/33 [00:09<00:00,  3.49it/s]\n",
            "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100% 5/5 [00:02<00:00,  2.50it/s]\n",
            "                   all        149        151       0.98      0.979      0.992      0.857\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n",
            "      32/80      2.05G     0.4466     0.3755      1.106         21        608: 100% 33/33 [00:10<00:00,  3.23it/s]\n",
            "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100% 5/5 [00:01<00:00,  2.65it/s]\n",
            "                   all        149        151       0.98      0.963      0.991      0.881\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n",
            "      33/80      2.05G     0.4235     0.3772       1.09         12        608: 100% 33/33 [00:10<00:00,  3.21it/s]\n",
            "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100% 5/5 [00:01<00:00,  2.88it/s]\n",
            "                   all        149        151      0.991       0.98      0.995      0.891\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n",
            "      34/80      2.04G     0.4351     0.3749      1.094         23        608: 100% 33/33 [00:10<00:00,  3.19it/s]\n",
            "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100% 5/5 [00:01<00:00,  2.57it/s]\n",
            "                   all        149        151      0.974      0.992      0.991      0.848\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n",
            "      35/80      2.05G     0.4477     0.3716      1.107         16        608: 100% 33/33 [00:10<00:00,  3.27it/s]\n",
            "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100% 5/5 [00:01<00:00,  2.74it/s]\n",
            "                   all        149        151      0.912      0.887      0.961      0.779\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n",
            "      36/80      2.05G     0.4423     0.3673      1.088         24        608: 100% 33/33 [00:10<00:00,  3.25it/s]\n",
            "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100% 5/5 [00:01<00:00,  2.77it/s]\n",
            "                   all        149        151      0.973      0.954       0.99       0.85\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n",
            "      37/80      2.05G     0.4424     0.3757      1.109         21        608: 100% 33/33 [00:10<00:00,  3.17it/s]\n",
            "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100% 5/5 [00:01<00:00,  2.95it/s]\n",
            "                   all        149        151      0.993      0.973      0.994      0.858\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n",
            "      38/80      2.04G     0.4364     0.3713       1.09         20        608: 100% 33/33 [00:10<00:00,  3.23it/s]\n",
            "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100% 5/5 [00:01<00:00,  2.63it/s]\n",
            "                   all        149        151      0.997       0.98      0.995      0.871\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n",
            "      39/80      2.05G     0.4181     0.3595      1.076         18        608: 100% 33/33 [00:10<00:00,  3.15it/s]\n",
            "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100% 5/5 [00:01<00:00,  2.89it/s]\n",
            "                   all        149        151      0.973       0.98      0.992      0.874\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n",
            "      40/80      2.05G     0.4337     0.3691      1.093         17        608: 100% 33/33 [00:10<00:00,  3.24it/s]\n",
            "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100% 5/5 [00:01<00:00,  2.70it/s]\n",
            "                   all        149        151      0.987      0.987      0.995      0.893\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n",
            "      41/80      2.05G      0.412     0.3774      1.086         23        608: 100% 33/33 [00:09<00:00,  3.52it/s]\n",
            "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100% 5/5 [00:02<00:00,  1.90it/s]\n",
            "                   all        149        151      0.957      0.947      0.987      0.871\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n",
            "      42/80      2.04G     0.4196     0.3473      1.078         19        608: 100% 33/33 [00:09<00:00,  3.61it/s]\n",
            "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100% 5/5 [00:03<00:00,  1.60it/s]\n",
            "                   all        149        151      0.986      0.958      0.989      0.889\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n",
            "      43/80      2.05G     0.4105     0.3485      1.062         18        608: 100% 33/33 [00:08<00:00,  3.85it/s]\n",
            "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100% 5/5 [00:02<00:00,  1.69it/s]\n",
            "                   all        149        151      0.992       0.98       0.99      0.876\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n",
            "      44/80      2.05G     0.4082     0.3475       1.07         20        608: 100% 33/33 [00:08<00:00,  3.73it/s]\n",
            "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100% 5/5 [00:02<00:00,  2.28it/s]\n",
            "                   all        149        151       0.98      0.983      0.994      0.884\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n",
            "      45/80      2.05G     0.4061     0.3459      1.071         20        608: 100% 33/33 [00:09<00:00,  3.54it/s]\n",
            "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100% 5/5 [00:01<00:00,  2.83it/s]\n",
            "                   all        149        151      0.967      0.971       0.99      0.891\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n",
            "      46/80      2.04G     0.3925     0.3407      1.051         17        608: 100% 33/33 [00:10<00:00,  3.22it/s]\n",
            "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100% 5/5 [00:01<00:00,  2.71it/s]\n",
            "                   all        149        151      0.968      0.987      0.993      0.898\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n",
            "      47/80      2.05G     0.4083     0.3419      1.072         21        608: 100% 33/33 [00:10<00:00,  3.19it/s]\n",
            "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100% 5/5 [00:01<00:00,  3.03it/s]\n",
            "                   all        149        151      0.965      0.974      0.992      0.892\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n",
            "      48/80      2.05G     0.3988     0.3292      1.079         13        608: 100% 33/33 [00:10<00:00,  3.18it/s]\n",
            "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100% 5/5 [00:01<00:00,  2.52it/s]\n",
            "                   all        149        151      0.974      0.984      0.993      0.888\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n",
            "      49/80      2.05G     0.3999     0.3296       1.07         22        608: 100% 33/33 [00:10<00:00,  3.21it/s]\n",
            "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100% 5/5 [00:01<00:00,  3.01it/s]\n",
            "                   all        149        151      0.986      0.987      0.995      0.917\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n",
            "      50/80      2.04G     0.3889     0.3184      1.069         21        608: 100% 33/33 [00:10<00:00,  3.23it/s]\n",
            "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100% 5/5 [00:01<00:00,  2.81it/s]\n",
            "                   all        149        151      0.955      0.974      0.992      0.876\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n",
            "      51/80      2.05G     0.3735     0.3181      1.044         23        608: 100% 33/33 [00:10<00:00,  3.22it/s]\n",
            "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100% 5/5 [00:01<00:00,  2.67it/s]\n",
            "                   all        149        151       0.98      0.983      0.992      0.901\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n",
            "      52/80      2.05G     0.3802      0.318      1.052         19        608: 100% 33/33 [00:10<00:00,  3.19it/s]\n",
            "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100% 5/5 [00:01<00:00,  3.06it/s]\n",
            "                   all        149        151      0.991      0.987      0.995      0.913\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n",
            "      53/80      2.07G      0.385     0.3247      1.059         22        608: 100% 33/33 [00:10<00:00,  3.25it/s]\n",
            "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100% 5/5 [00:01<00:00,  2.65it/s]\n",
            "                   all        149        151      0.986      0.987      0.994      0.898\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n",
            "      54/80      2.04G     0.3699     0.3103       1.05         15        608: 100% 33/33 [00:09<00:00,  3.54it/s]\n",
            "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100% 5/5 [00:02<00:00,  1.84it/s]\n",
            "                   all        149        151      0.992      0.987      0.995      0.919\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n",
            "      55/80      2.05G     0.3569     0.3121      1.039         19        608: 100% 33/33 [00:08<00:00,  3.80it/s]\n",
            "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100% 5/5 [00:03<00:00,  1.58it/s]\n",
            "                   all        149        151       0.96      0.987      0.992      0.896\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n",
            "      56/80      2.05G     0.3725     0.3294      1.052         15        608: 100% 33/33 [00:08<00:00,  3.75it/s]\n",
            "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100% 5/5 [00:02<00:00,  2.05it/s]\n",
            "                   all        149        151      0.992      0.947      0.992      0.898\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n",
            "      57/80      2.06G     0.3953     0.3247      1.059         23        608: 100% 33/33 [00:08<00:00,  3.70it/s]\n",
            "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100% 5/5 [00:01<00:00,  2.68it/s]\n",
            "                   all        149        151      0.993      0.953      0.989      0.891\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n",
            "      58/80      2.04G     0.3632     0.3152      1.053         16        608: 100% 33/33 [00:09<00:00,  3.41it/s]\n",
            "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100% 5/5 [00:01<00:00,  2.59it/s]\n",
            "                   all        149        151      0.974      0.967      0.992        0.9\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n",
            "      59/80      2.05G     0.3683     0.2915      1.053         21        608: 100% 33/33 [00:10<00:00,  3.21it/s]\n",
            "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100% 5/5 [00:01<00:00,  3.02it/s]\n",
            "                   all        149        151      0.961       0.98      0.993       0.89\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n",
            "      60/80      2.05G     0.3722     0.3072      1.054         21        608: 100% 33/33 [00:10<00:00,  3.16it/s]\n",
            "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100% 5/5 [00:01<00:00,  3.00it/s]\n",
            "                   all        149        151       0.99       0.96      0.993      0.883\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n",
            "      61/80      2.05G     0.3794     0.3136      1.061         20        608: 100% 33/33 [00:10<00:00,  3.14it/s]\n",
            "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100% 5/5 [00:01<00:00,  2.83it/s]\n",
            "                   all        149        151       0.98      0.975      0.993      0.909\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n",
            "      62/80      2.04G     0.3478     0.2839      1.033         20        608: 100% 33/33 [00:10<00:00,  3.19it/s]\n",
            "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100% 5/5 [00:01<00:00,  2.83it/s]\n",
            "                   all        149        151      0.966      0.987      0.994      0.909\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n",
            "      63/80      2.05G     0.3619     0.2849      1.046         24        608: 100% 33/33 [00:10<00:00,  3.13it/s]\n",
            "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100% 5/5 [00:01<00:00,  2.64it/s]\n",
            "                   all        149        151      0.981       0.98      0.994      0.917\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n",
            "      64/80      2.05G     0.3642     0.3053      1.038         18        608: 100% 33/33 [00:10<00:00,  3.22it/s]\n",
            "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100% 5/5 [00:01<00:00,  2.88it/s]\n",
            "                   all        149        151      0.987      0.986      0.995       0.92\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n",
            "      65/80      2.05G      0.353     0.2764      1.045         20        608: 100% 33/33 [00:10<00:00,  3.25it/s]\n",
            "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100% 5/5 [00:01<00:00,  2.68it/s]\n",
            "                   all        149        151      0.993      0.992      0.995      0.927\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n",
            "      66/80      2.04G      0.372     0.3065      1.056         21        608: 100% 33/33 [00:10<00:00,  3.23it/s]\n",
            "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100% 5/5 [00:01<00:00,  2.64it/s]\n",
            "                   all        149        151      0.987      0.986       0.99       0.92\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n",
            "      67/80      2.05G     0.3316     0.2779      1.033         25        608: 100% 33/33 [00:10<00:00,  3.23it/s]\n",
            "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100% 5/5 [00:01<00:00,  2.87it/s]\n",
            "                   all        149        151      0.986       0.98      0.988      0.914\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n",
            "      68/80      2.05G     0.3339     0.2684      1.035         17        608: 100% 33/33 [00:10<00:00,  3.27it/s]\n",
            "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100% 5/5 [00:02<00:00,  2.34it/s]\n",
            "                   all        149        151      0.979      0.987      0.992      0.915\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n",
            "      69/80      2.07G     0.3522     0.2955      1.041         18        608: 100% 33/33 [00:08<00:00,  3.76it/s]\n",
            "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100% 5/5 [00:03<00:00,  1.56it/s]\n",
            "                   all        149        151      0.987      0.978      0.984      0.916\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n",
            "      70/80      2.04G     0.3388     0.2757       1.02         22        608: 100% 33/33 [00:08<00:00,  3.78it/s]\n",
            "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100% 5/5 [00:02<00:00,  1.91it/s]\n",
            "                   all        149        151      0.985      0.974      0.991      0.919\n",
            "Closing dataloader mosaic\n",
            "\u001b[34m\u001b[1malbumentations: \u001b[0mBlur(p=0.01, blur_limit=(3, 7)), MedianBlur(p=0.01, blur_limit=(3, 7)), ToGray(p=0.01), CLAHE(p=0.01, clip_limit=(1, 4.0), tile_grid_size=(8, 8))\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n",
            "      71/80      2.19G      0.237      0.287      1.025          7        608: 100% 33/33 [00:10<00:00,  3.21it/s]\n",
            "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100% 5/5 [00:03<00:00,  1.64it/s]\n",
            "                   all        149        151      0.993      0.987      0.991      0.923\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n",
            "      72/80      2.05G     0.2151     0.1905      1.012          7        608: 100% 33/33 [00:08<00:00,  3.69it/s]\n",
            "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100% 5/5 [00:02<00:00,  2.05it/s]\n",
            "                   all        149        151      0.974      0.993      0.994      0.924\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n",
            "      73/80      2.05G     0.2079     0.1781      1.012          7        608: 100% 33/33 [00:08<00:00,  3.85it/s]\n",
            "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100% 5/5 [00:01<00:00,  2.84it/s]\n",
            "                   all        149        151       0.98      0.986      0.989      0.924\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n",
            "      74/80      2.04G     0.2039     0.1706      0.986          7        608: 100% 33/33 [00:09<00:00,  3.42it/s]\n",
            "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100% 5/5 [00:01<00:00,  2.94it/s]\n",
            "                   all        149        151      0.987      0.987      0.988      0.929\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n",
            "      75/80      2.05G     0.1904     0.1641     0.9841          7        608: 100% 33/33 [00:09<00:00,  3.39it/s]\n",
            "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100% 5/5 [00:01<00:00,  2.63it/s]\n",
            "                   all        149        151      0.987      0.987      0.991      0.941\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n",
            "      76/80      2.05G      0.191     0.1537     0.9802          7        608: 100% 33/33 [00:09<00:00,  3.38it/s]\n",
            "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100% 5/5 [00:01<00:00,  2.95it/s]\n",
            "                   all        149        151      0.986      0.987      0.992      0.946\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n",
            "      77/80      2.05G     0.1841     0.1497     0.9762          7        608: 100% 33/33 [00:10<00:00,  3.29it/s]\n",
            "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100% 5/5 [00:01<00:00,  2.88it/s]\n",
            "                   all        149        151      0.986      0.987      0.992      0.948\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n",
            "      78/80      2.04G     0.1835     0.1545     0.9841          7        608: 100% 33/33 [00:10<00:00,  3.17it/s]\n",
            "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100% 5/5 [00:01<00:00,  2.85it/s]\n",
            "                   all        149        151      0.993      0.987      0.992      0.949\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n",
            "      79/80      2.05G     0.1846     0.1513     0.9882          7        608: 100% 33/33 [00:09<00:00,  3.37it/s]\n",
            "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100% 5/5 [00:01<00:00,  2.98it/s]\n",
            "                   all        149        151      0.986      0.987      0.989      0.949\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n",
            "      80/80      2.05G     0.1812     0.1482     0.9639          7        608: 100% 33/33 [00:09<00:00,  3.40it/s]\n",
            "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100% 5/5 [00:01<00:00,  2.53it/s]\n",
            "                   all        149        151      0.986      0.987      0.988       0.95\n",
            "\n",
            "80 epochs completed in 0.281 hours.\n",
            "Optimizer stripped from runs/detect/train/weights/last.pt, 6.2MB\n",
            "Optimizer stripped from runs/detect/train/weights/best.pt, 6.2MB\n",
            "\n",
            "Validating runs/detect/train/weights/best.pt...\n",
            "Ultralytics YOLOv8.0.200 🚀 Python-3.10.12 torch-2.1.0+cu118 CUDA:0 (Tesla T4, 15102MiB)\n",
            "Model summary (fused): 168 layers, 3005843 parameters, 0 gradients, 8.1 GFLOPs\n",
            "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100% 5/5 [00:03<00:00,  1.26it/s]\n",
            "                   all        149        151      0.986      0.987      0.988       0.95\n",
            "Speed: 0.4ms preprocess, 4.4ms inference, 0.0ms loss, 4.5ms postprocess per image\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "💡 Learn more at https://docs.ultralytics.com/modes/train\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "r = '/content/runs'"
      ],
      "metadata": {
        "id": "hfQFF4S4tGx7"
      },
      "execution_count": 6,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "!yolo task=detect mode=val model={r}/detect/train/weights/best.pt data={dataset.location}/data.yaml"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "wj_KBoYrxksu",
        "outputId": "a911fb5e-9dc0-4e84-b360-6d772c34f81d"
      },
      "execution_count": 7,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Ultralytics YOLOv8.0.200 🚀 Python-3.10.12 torch-2.1.0+cu118 CUDA:0 (Tesla T4, 15102MiB)\n",
            "Model summary (fused): 168 layers, 3005843 parameters, 0 gradients, 8.1 GFLOPs\n",
            "\u001b[34m\u001b[1mval: \u001b[0mScanning /content/Electrical-Board-Detection-1/valid/labels.cache... 149 images, 0 backgrounds, 0 corrupt: 100% 149/149 [00:00<?, ?it/s]\n",
            "WARNING ⚠️ Box and segment counts should be equal, but got len(segments) = 1, len(boxes) = 151. To resolve this only boxes will be used and all segments will be removed. To avoid this please supply either a detect or segment dataset, not a detect-segment mixed dataset.\n",
            "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100% 10/10 [00:04<00:00,  2.14it/s]\n",
            "                   all        149        151      0.986      0.987      0.988       0.95\n",
            "Speed: 3.5ms preprocess, 6.8ms inference, 0.0ms loss, 2.1ms postprocess per image\n",
            "Results saved to \u001b[1mruns/detect/val\u001b[0m\n",
            "💡 Learn more at https://docs.ultralytics.com/modes/val\n"
          ]
        }
      ]
    }
  ]
}