{
  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "colab_type": "text",
        "id": "view-in-github"
      },
      "source": [
        "<a href=\"https://colab.research.google.com/github/yasirfaizahmed/ML_Notebooks/blob/master/NumberPlate_detection_using_YOLOv8.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "WvRyifGfTQQ2"
      },
      "source": [
        "# license plate object detection using YOLOv8"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {},
      "source": [
        "#### dataset : https://huggingface.co/datasets/keremberke/license-plate-object-detection\n"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 1,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "yVFdjWeRS8jh",
        "outputId": "6a9c0a99-5dc3-4705-aa8b-14ea3db5c04c"
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "Collecting datasets\n",
            "  Downloading datasets-3.2.0-py3-none-any.whl.metadata (20 kB)\n",
            "Collecting ultralytics\n",
            "  Downloading ultralytics-8.3.68-py3-none-any.whl.metadata (35 kB)\n",
            "Requirement already satisfied: filelock in /usr/local/lib/python3.11/dist-packages (from datasets) (3.17.0)\n",
            "Requirement already satisfied: numpy>=1.17 in /usr/local/lib/python3.11/dist-packages (from datasets) (1.26.4)\n",
            "Requirement already satisfied: pyarrow>=15.0.0 in /usr/local/lib/python3.11/dist-packages (from datasets) (17.0.0)\n",
            "Collecting dill<0.3.9,>=0.3.0 (from datasets)\n",
            "  Downloading dill-0.3.8-py3-none-any.whl.metadata (10 kB)\n",
            "Requirement already satisfied: pandas in /usr/local/lib/python3.11/dist-packages (from datasets) (2.2.2)\n",
            "Requirement already satisfied: requests>=2.32.2 in /usr/local/lib/python3.11/dist-packages (from datasets) (2.32.3)\n",
            "Requirement already satisfied: tqdm>=4.66.3 in /usr/local/lib/python3.11/dist-packages (from datasets) (4.67.1)\n",
            "Collecting xxhash (from datasets)\n",
            "  Downloading xxhash-3.5.0-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.metadata (12 kB)\n",
            "Collecting multiprocess<0.70.17 (from datasets)\n",
            "  Downloading multiprocess-0.70.16-py311-none-any.whl.metadata (7.2 kB)\n",
            "Collecting fsspec<=2024.9.0,>=2023.1.0 (from fsspec[http]<=2024.9.0,>=2023.1.0->datasets)\n",
            "  Downloading fsspec-2024.9.0-py3-none-any.whl.metadata (11 kB)\n",
            "Requirement already satisfied: aiohttp in /usr/local/lib/python3.11/dist-packages (from datasets) (3.11.11)\n",
            "Requirement already satisfied: huggingface-hub>=0.23.0 in /usr/local/lib/python3.11/dist-packages (from datasets) (0.27.1)\n",
            "Requirement already satisfied: packaging in /usr/local/lib/python3.11/dist-packages (from datasets) (24.2)\n",
            "Requirement already satisfied: pyyaml>=5.1 in /usr/local/lib/python3.11/dist-packages (from datasets) (6.0.2)\n",
            "Requirement already satisfied: matplotlib>=3.3.0 in /usr/local/lib/python3.11/dist-packages (from ultralytics) (3.10.0)\n",
            "Requirement already satisfied: opencv-python>=4.6.0 in /usr/local/lib/python3.11/dist-packages (from ultralytics) (4.10.0.84)\n",
            "Requirement already satisfied: pillow>=7.1.2 in /usr/local/lib/python3.11/dist-packages (from ultralytics) (11.1.0)\n",
            "Requirement already satisfied: scipy>=1.4.1 in /usr/local/lib/python3.11/dist-packages (from ultralytics) (1.13.1)\n",
            "Requirement already satisfied: torch>=1.8.0 in /usr/local/lib/python3.11/dist-packages (from ultralytics) (2.5.1+cu121)\n",
            "Requirement already satisfied: torchvision>=0.9.0 in /usr/local/lib/python3.11/dist-packages (from ultralytics) (0.20.1+cu121)\n",
            "Requirement already satisfied: psutil in /usr/local/lib/python3.11/dist-packages (from ultralytics) (5.9.5)\n",
            "Requirement already satisfied: py-cpuinfo in /usr/local/lib/python3.11/dist-packages (from ultralytics) (9.0.0)\n",
            "Requirement already satisfied: seaborn>=0.11.0 in /usr/local/lib/python3.11/dist-packages (from ultralytics) (0.13.2)\n",
            "Collecting ultralytics-thop>=2.0.0 (from ultralytics)\n",
            "  Downloading ultralytics_thop-2.0.14-py3-none-any.whl.metadata (9.4 kB)\n",
            "Requirement already satisfied: aiohappyeyeballs>=2.3.0 in /usr/local/lib/python3.11/dist-packages (from aiohttp->datasets) (2.4.4)\n",
            "Requirement already satisfied: aiosignal>=1.1.2 in /usr/local/lib/python3.11/dist-packages (from aiohttp->datasets) (1.3.2)\n",
            "Requirement already satisfied: attrs>=17.3.0 in /usr/local/lib/python3.11/dist-packages (from aiohttp->datasets) (24.3.0)\n",
            "Requirement already satisfied: frozenlist>=1.1.1 in /usr/local/lib/python3.11/dist-packages (from aiohttp->datasets) (1.5.0)\n",
            "Requirement already satisfied: multidict<7.0,>=4.5 in /usr/local/lib/python3.11/dist-packages (from aiohttp->datasets) (6.1.0)\n",
            "Requirement already satisfied: propcache>=0.2.0 in /usr/local/lib/python3.11/dist-packages (from aiohttp->datasets) (0.2.1)\n",
            "Requirement already satisfied: yarl<2.0,>=1.17.0 in /usr/local/lib/python3.11/dist-packages (from aiohttp->datasets) (1.18.3)\n",
            "Requirement already satisfied: typing-extensions>=3.7.4.3 in /usr/local/lib/python3.11/dist-packages (from huggingface-hub>=0.23.0->datasets) (4.12.2)\n",
            "Requirement already satisfied: contourpy>=1.0.1 in /usr/local/lib/python3.11/dist-packages (from matplotlib>=3.3.0->ultralytics) (1.3.1)\n",
            "Requirement already satisfied: cycler>=0.10 in /usr/local/lib/python3.11/dist-packages (from matplotlib>=3.3.0->ultralytics) (0.12.1)\n",
            "Requirement already satisfied: fonttools>=4.22.0 in /usr/local/lib/python3.11/dist-packages (from matplotlib>=3.3.0->ultralytics) (4.55.5)\n",
            "Requirement already satisfied: kiwisolver>=1.3.1 in /usr/local/lib/python3.11/dist-packages (from matplotlib>=3.3.0->ultralytics) (1.4.8)\n",
            "Requirement already satisfied: pyparsing>=2.3.1 in /usr/local/lib/python3.11/dist-packages (from matplotlib>=3.3.0->ultralytics) (3.2.1)\n",
            "Requirement already satisfied: python-dateutil>=2.7 in /usr/local/lib/python3.11/dist-packages (from matplotlib>=3.3.0->ultralytics) (2.8.2)\n",
            "Requirement already satisfied: pytz>=2020.1 in /usr/local/lib/python3.11/dist-packages (from pandas->datasets) (2024.2)\n",
            "Requirement already satisfied: tzdata>=2022.7 in /usr/local/lib/python3.11/dist-packages (from pandas->datasets) (2025.1)\n",
            "Requirement already satisfied: charset-normalizer<4,>=2 in /usr/local/lib/python3.11/dist-packages (from requests>=2.32.2->datasets) (3.4.1)\n",
            "Requirement already satisfied: idna<4,>=2.5 in /usr/local/lib/python3.11/dist-packages (from requests>=2.32.2->datasets) (3.10)\n",
            "Requirement already satisfied: urllib3<3,>=1.21.1 in /usr/local/lib/python3.11/dist-packages (from requests>=2.32.2->datasets) (2.3.0)\n",
            "Requirement already satisfied: certifi>=2017.4.17 in /usr/local/lib/python3.11/dist-packages (from requests>=2.32.2->datasets) (2024.12.14)\n",
            "Requirement already satisfied: networkx in /usr/local/lib/python3.11/dist-packages (from torch>=1.8.0->ultralytics) (3.4.2)\n",
            "Requirement already satisfied: jinja2 in /usr/local/lib/python3.11/dist-packages (from torch>=1.8.0->ultralytics) (3.1.5)\n",
            "Requirement already satisfied: nvidia-cuda-nvrtc-cu12==12.1.105 in /usr/local/lib/python3.11/dist-packages (from torch>=1.8.0->ultralytics) (12.1.105)\n",
            "Requirement already satisfied: nvidia-cuda-runtime-cu12==12.1.105 in /usr/local/lib/python3.11/dist-packages (from torch>=1.8.0->ultralytics) (12.1.105)\n",
            "Requirement already satisfied: nvidia-cuda-cupti-cu12==12.1.105 in /usr/local/lib/python3.11/dist-packages (from torch>=1.8.0->ultralytics) (12.1.105)\n",
            "Requirement already satisfied: nvidia-cudnn-cu12==9.1.0.70 in /usr/local/lib/python3.11/dist-packages (from torch>=1.8.0->ultralytics) (9.1.0.70)\n",
            "Requirement already satisfied: nvidia-cublas-cu12==12.1.3.1 in /usr/local/lib/python3.11/dist-packages (from torch>=1.8.0->ultralytics) (12.1.3.1)\n",
            "Requirement already satisfied: nvidia-cufft-cu12==11.0.2.54 in /usr/local/lib/python3.11/dist-packages (from torch>=1.8.0->ultralytics) (11.0.2.54)\n",
            "Requirement already satisfied: nvidia-curand-cu12==10.3.2.106 in /usr/local/lib/python3.11/dist-packages (from torch>=1.8.0->ultralytics) (10.3.2.106)\n",
            "Requirement already satisfied: nvidia-cusolver-cu12==11.4.5.107 in /usr/local/lib/python3.11/dist-packages (from torch>=1.8.0->ultralytics) (11.4.5.107)\n",
            "Requirement already satisfied: nvidia-cusparse-cu12==12.1.0.106 in /usr/local/lib/python3.11/dist-packages (from torch>=1.8.0->ultralytics) (12.1.0.106)\n",
            "Requirement already satisfied: nvidia-nccl-cu12==2.21.5 in /usr/local/lib/python3.11/dist-packages (from torch>=1.8.0->ultralytics) (2.21.5)\n",
            "Requirement already satisfied: nvidia-nvtx-cu12==12.1.105 in /usr/local/lib/python3.11/dist-packages (from torch>=1.8.0->ultralytics) (12.1.105)\n",
            "Requirement already satisfied: triton==3.1.0 in /usr/local/lib/python3.11/dist-packages (from torch>=1.8.0->ultralytics) (3.1.0)\n",
            "Requirement already satisfied: sympy==1.13.1 in /usr/local/lib/python3.11/dist-packages (from torch>=1.8.0->ultralytics) (1.13.1)\n",
            "Requirement already satisfied: nvidia-nvjitlink-cu12 in /usr/local/lib/python3.11/dist-packages (from nvidia-cusolver-cu12==11.4.5.107->torch>=1.8.0->ultralytics) (12.6.85)\n",
            "Requirement already satisfied: mpmath<1.4,>=1.1.0 in /usr/local/lib/python3.11/dist-packages (from sympy==1.13.1->torch>=1.8.0->ultralytics) (1.3.0)\n",
            "Requirement already satisfied: six>=1.5 in /usr/local/lib/python3.11/dist-packages (from python-dateutil>=2.7->matplotlib>=3.3.0->ultralytics) (1.17.0)\n",
            "Requirement already satisfied: MarkupSafe>=2.0 in /usr/local/lib/python3.11/dist-packages (from jinja2->torch>=1.8.0->ultralytics) (3.0.2)\n",
            "Downloading datasets-3.2.0-py3-none-any.whl (480 kB)\n",
            "\u001b[2K   \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m480.6/480.6 kB\u001b[0m \u001b[31m9.3 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[?25hDownloading ultralytics-8.3.68-py3-none-any.whl (913 kB)\n",
            "\u001b[2K   \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m913.6/913.6 kB\u001b[0m \u001b[31m34.1 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[?25hDownloading dill-0.3.8-py3-none-any.whl (116 kB)\n",
            "\u001b[2K   \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m116.3/116.3 kB\u001b[0m \u001b[31m9.2 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[?25hDownloading fsspec-2024.9.0-py3-none-any.whl (179 kB)\n",
            "\u001b[2K   \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m179.3/179.3 kB\u001b[0m \u001b[31m14.7 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[?25hDownloading multiprocess-0.70.16-py311-none-any.whl (143 kB)\n",
            "\u001b[2K   \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m143.5/143.5 kB\u001b[0m \u001b[31m11.9 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[?25hDownloading ultralytics_thop-2.0.14-py3-none-any.whl (26 kB)\n",
            "Downloading xxhash-3.5.0-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (194 kB)\n",
            "\u001b[2K   \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m194.8/194.8 kB\u001b[0m \u001b[31m15.4 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[?25hInstalling collected packages: xxhash, fsspec, dill, multiprocess, ultralytics-thop, datasets, ultralytics\n",
            "  Attempting uninstall: fsspec\n",
            "    Found existing installation: fsspec 2024.10.0\n",
            "    Uninstalling fsspec-2024.10.0:\n",
            "      Successfully uninstalled fsspec-2024.10.0\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",
            "gcsfs 2024.10.0 requires fsspec==2024.10.0, but you have fsspec 2024.9.0 which is incompatible.\u001b[0m\u001b[31m\n",
            "\u001b[0mSuccessfully installed datasets-3.2.0 dill-0.3.8 fsspec-2024.9.0 multiprocess-0.70.16 ultralytics-8.3.68 ultralytics-thop-2.0.14 xxhash-3.5.0\n"
          ]
        }
      ],
      "source": [
        "! pip install datasets ultralytics"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 2,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 402,
          "referenced_widgets": [
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        },
        "id": "jnJT1oEGVV6d",
        "outputId": "2f509f0a-4f9c-4c05-855f-4caa059f23b6"
      },
      "outputs": [
        {
          "name": "stderr",
          "output_type": "stream",
          "text": [
            "/usr/local/lib/python3.11/dist-packages/huggingface_hub/utils/_auth.py:94: UserWarning: \n",
            "The secret `HF_TOKEN` does not exist in your Colab secrets.\n",
            "To authenticate with the Hugging Face Hub, create a token in your settings tab (https://huggingface.co/settings/tokens), set it as secret in your Google Colab and restart your session.\n",
            "You will be able to reuse this secret in all of your notebooks.\n",
            "Please note that authentication is recommended but still optional to access public models or datasets.\n",
            "  warnings.warn(\n"
          ]
        },
        {
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            ]
          },
          "metadata": {},
          "output_type": "display_data"
        },
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            ]
          },
          "metadata": {},
          "output_type": "display_data"
        },
        {
          "data": {
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        },
        {
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        },
        {
          "data": {
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              "model_id": "031ad2790ce14930a576fbb5a70aa6ac",
              "version_major": 2,
              "version_minor": 0
            },
            "text/plain": [
              "Generating train split:   0%|          | 0/6176 [00:00<?, ? examples/s]"
            ]
          },
          "metadata": {},
          "output_type": "display_data"
        },
        {
          "data": {
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            "text/plain": [
              "Generating validation split:   0%|          | 0/1765 [00:00<?, ? examples/s]"
            ]
          },
          "metadata": {},
          "output_type": "display_data"
        },
        {
          "data": {
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              "model_id": "6e8a5580a981464e842c56ee88fdc29d",
              "version_major": 2,
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            },
            "text/plain": [
              "Generating test split:   0%|          | 0/882 [00:00<?, ? examples/s]"
            ]
          },
          "metadata": {},
          "output_type": "display_data"
        }
      ],
      "source": [
        "from datasets import load_dataset\n",
        "\n",
        "ds = load_dataset(\"keremberke/license-plate-object-detection\", \"full\")"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 3,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "haIMLABdXUmZ",
        "outputId": "b26a0d7c-6b83-4c8f-db80-df9f900f0b2f"
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "Creating new Ultralytics Settings v0.0.6 file ✅ \n",
            "View Ultralytics Settings with 'yolo settings' or at '/root/.config/Ultralytics/settings.json'\n",
            "Update Settings with 'yolo settings key=value', i.e. 'yolo settings runs_dir=path/to/dir'. For help see https://docs.ultralytics.com/quickstart/#ultralytics-settings.\n"
          ]
        }
      ],
      "source": [
        "import pandas as pd\n",
        "from matplotlib import pyplot as plt\n",
        "import numpy as np\n",
        "import cv2\n",
        "from ultralytics import YOLO"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 4,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 425
        },
        "id": "xEqD51f1Xmce",
        "outputId": "6382a9b0-ab55-422f-ca8f-b1e52cb18009"
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "<class 'pandas.core.frame.DataFrame'>\n",
            "RangeIndex: 6176 entries, 0 to 6175\n",
            "Data columns (total 5 columns):\n",
            " #   Column    Non-Null Count  Dtype \n",
            "---  ------    --------------  ----- \n",
            " 0   image_id  6176 non-null   int64 \n",
            " 1   image     6176 non-null   object\n",
            " 2   width     6176 non-null   int32 \n",
            " 3   height    6176 non-null   int32 \n",
            " 4   objects   6176 non-null   object\n",
            "dtypes: int32(2), int64(1), object(2)\n",
            "memory usage: 193.1+ KB\n"
          ]
        },
        {
          "data": {
            "application/vnd.google.colaboratory.intrinsic+json": {
              "summary": "{\n  \"name\": \"df_train\",\n  \"rows\": 6176,\n  \"fields\": [\n    {\n      \"column\": \"image_id\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 1783,\n        \"min\": 0,\n        \"max\": 6175,\n        \"num_unique_values\": 6176,\n        \"samples\": [\n          2669,\n          2934,\n          5218\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"image\",\n      \"properties\": {\n        \"dtype\": \"object\",\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"width\",\n      \"properties\": {\n        \"dtype\": \"int32\",\n        \"num_unique_values\": 80,\n        \"samples\": [\n          300,\n          472,\n          370\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"height\",\n      \"properties\": {\n        \"dtype\": \"int32\",\n        \"num_unique_values\": 205,\n        \"samples\": [\n          342,\n          427,\n          512\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"objects\",\n      \"properties\": {\n        \"dtype\": \"object\",\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    }\n  ]\n}",
              "type": "dataframe",
              "variable_name": "df_train"
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              "      display:flex;\n",
              "      gap: 12px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert {\n",
              "      background-color: #E8F0FE;\n",
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              "      buttonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
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              "        const element = document.querySelector('#df-b250277b-1fd0-4ee9-b28a-84369bc4b472');\n",
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              "          await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                    [key], {});\n",
              "        if (!dataTable) return;\n",
              "\n",
              "        const docLinkHtml = 'Like what you see? Visit the ' +\n",
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              "\n",
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              "      --bg-color: #E8F0FE;\n",
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              "      --hover-bg-color: #E2EBFA;\n",
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              "      --disabled-fill-color: #AAA;\n",
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              "  }\n",
              "\n",
              "  [theme=dark] .colab-df-quickchart {\n",
              "      --bg-color: #3B4455;\n",
              "      --fill-color: #D2E3FC;\n",
              "      --hover-bg-color: #434B5C;\n",
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              "      --disabled-fill-color: #666;\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart {\n",
              "    background-color: var(--bg-color);\n",
              "    border: none;\n",
              "    border-radius: 50%;\n",
              "    cursor: pointer;\n",
              "    display: none;\n",
              "    fill: var(--fill-color);\n",
              "    height: 32px;\n",
              "    padding: 0;\n",
              "    width: 32px;\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart:hover {\n",
              "    background-color: var(--hover-bg-color);\n",
              "    box-shadow: 0 1px 2px rgba(60, 64, 67, 0.3), 0 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "    fill: var(--button-hover-fill-color);\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart-complete:disabled,\n",
              "  .colab-df-quickchart-complete:disabled:hover {\n",
              "    background-color: var(--disabled-bg-color);\n",
              "    fill: var(--disabled-fill-color);\n",
              "    box-shadow: none;\n",
              "  }\n",
              "\n",
              "  .colab-df-spinner {\n",
              "    border: 2px solid var(--fill-color);\n",
              "    border-color: transparent;\n",
              "    border-bottom-color: var(--fill-color);\n",
              "    animation:\n",
              "      spin 1s steps(1) infinite;\n",
              "  }\n",
              "\n",
              "  @keyframes spin {\n",
              "    0% {\n",
              "      border-color: transparent;\n",
              "      border-bottom-color: var(--fill-color);\n",
              "      border-left-color: var(--fill-color);\n",
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              "    20% {\n",
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              "      border-color: transparent;\n",
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              "    }\n",
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              "      border-color: transparent;\n",
              "      border-bottom-color: var(--fill-color);\n",
              "    }\n",
              "  }\n",
              "</style>\n",
              "\n",
              "  <script>\n",
              "    async function quickchart(key) {\n",
              "      const quickchartButtonEl =\n",
              "        document.querySelector('#' + key + ' button');\n",
              "      quickchartButtonEl.disabled = true;  // To prevent multiple clicks.\n",
              "      quickchartButtonEl.classList.add('colab-df-spinner');\n",
              "      try {\n",
              "        const charts = await google.colab.kernel.invokeFunction(\n",
              "            'suggestCharts', [key], {});\n",
              "      } catch (error) {\n",
              "        console.error('Error during call to suggestCharts:', error);\n",
              "      }\n",
              "      quickchartButtonEl.classList.remove('colab-df-spinner');\n",
              "      quickchartButtonEl.classList.add('colab-df-quickchart-complete');\n",
              "    }\n",
              "    (() => {\n",
              "      let quickchartButtonEl =\n",
              "        document.querySelector('#df-63930fe7-2b7d-4db3-9aa6-d8efecad41fa button');\n",
              "      quickchartButtonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "    })();\n",
              "  </script>\n",
              "</div>\n",
              "\n",
              "    </div>\n",
              "  </div>\n"
            ],
            "text/plain": [
              "   image_id                                              image  width  height  \\\n",
              "0      6152  {'bytes': b'\\xff\\xd8\\xff\\xe0\\x00\\x10JFIF\\x00\\x...    472     303   \n",
              "1      5500  {'bytes': b'\\xff\\xd8\\xff\\xe0\\x00\\x10JFIF\\x00\\x...    472     303   \n",
              "2      1188  {'bytes': b'\\xff\\xd8\\xff\\xe0\\x00\\x10JFIF\\x00\\x...    400     240   \n",
              "3      3524  {'bytes': b'\\xff\\xd8\\xff\\xe0\\x00\\x10JFIF\\x00\\x...    540     405   \n",
              "4      5049  {'bytes': b'\\xff\\xd8\\xff\\xe0\\x00\\x10JFIF\\x00\\x...    472     303   \n",
              "\n",
              "                                             objects  \n",
              "0  {'id': [6388], 'area': [2604], 'bbox': [[261.0...  \n",
              "1  {'id': [5719], 'area': [742], 'bbox': [[263.0,...  \n",
              "2  {'id': [1231], 'area': [2701], 'bbox': [[147.0...  \n",
              "3  {'id': [3651], 'area': [800], 'bbox': [[217.0,...  \n",
              "4  {'id': [5242], 'area': [2112], 'bbox': [[145.0...  "
            ]
          },
          "execution_count": 4,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "df_train = ds['train'].to_pandas()\n",
        "df_val = ds['validation'].to_pandas()\n",
        "df_test = ds['test'].to_pandas()\n",
        "df_train.info()\n",
        "df_train.head()"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 5,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "5gxgevPxZU26",
        "outputId": "58a58ccb-985c-4098-ab72-a9ac4b57e566"
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "Downloading https://github.com/ultralytics/assets/releases/download/v8.3.0/yolov8n.pt to 'yolov8n.pt'...\n"
          ]
        },
        {
          "name": "stderr",
          "output_type": "stream",
          "text": [
            "100%|██████████| 6.25M/6.25M [00:00<00:00, 76.2MB/s]\n"
          ]
        }
      ],
      "source": [
        "# Load a pre-trained YOLOv8 model\n",
        "model = YOLO('yolov8n.pt')  # 'yolov8n.pt' is a small model, you can choose others like 'yolov8"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 6,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "SORMPYhvZb4Z",
        "outputId": "365feb67-da37-4a29-afe1-3155667a1bbe"
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "{'id': array([6388]), 'area': array([2604]), 'bbox': array([array([        261,         203,          93,          28], dtype=float32)], dtype=object), 'category': array([0])}\n"
          ]
        }
      ],
      "source": [
        "import os\n",
        "import cv2\n",
        "print(df_train[\"objects\"][0])\n"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 7,
      "metadata": {
        "id": "3Hff3i23bPE4"
      },
      "outputs": [],
      "source": [
        "# Output directories\n",
        "image_dir = 'dataset/images/train'\n",
        "label_dir = 'dataset/labels/train'\n",
        "os.makedirs(image_dir, exist_ok=True)\n",
        "os.makedirs(label_dir, exist_ok=True)\n",
        "\n",
        "for idx, row in df_train.iterrows():\n",
        "    # Convert byte string to image\n",
        "    image = np.frombuffer(row['image'].get('bytes'), dtype=np.uint8)\n",
        "    image = cv2.imdecode(image, cv2.IMREAD_COLOR)\n",
        "\n",
        "    if image is not None:\n",
        "      image_height, image_width = image.shape[:2]\n",
        "    else:\n",
        "      continue\n",
        "\n",
        "    # Save image\n",
        "    image_path = os.path.join(image_dir, f'image_{idx}.jpg')\n",
        "    cv2.imwrite(image_path, image)\n",
        "\n",
        "    # Convert bbox to YOLO format\n",
        "    # Extract bounding box and class ID\n",
        "    bbox = row['objects'].get(\"bbox\")  # [x_min, y_min, width, height]\n",
        "    class_id = 0 # Class ID\n",
        "\n",
        "    # Normalize bbox coordinates\n",
        "    x_min, y_min, width, height = bbox[0]\n",
        "    x_center = (x_min + width / 2) / image_width\n",
        "    y_center = (y_min + height / 2) / image_height\n",
        "    bbox_width = width / image_width\n",
        "    bbox_height = height / image_height\n",
        "\n",
        "    # Save label file\n",
        "    label_path = os.path.join(label_dir, f'image_{idx}.txt')\n",
        "    with open(label_path, 'w') as f:\n",
        "        f.write(f'{class_id} {x_center} {y_center} {bbox_width} {bbox_height}\\n')"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 8,
      "metadata": {
        "id": "f_J9xp_hpenL"
      },
      "outputs": [],
      "source": [
        "# Output directories\n",
        "image_dir = 'dataset/images/val'\n",
        "label_dir = 'dataset/labels/val'\n",
        "os.makedirs(image_dir, exist_ok=True)\n",
        "os.makedirs(label_dir, exist_ok=True)\n",
        "\n",
        "for idx, row in df_val.iterrows():\n",
        "    # Convert byte string to image\n",
        "    image = np.frombuffer(row['image'].get('bytes'), dtype=np.uint8)\n",
        "    image = cv2.imdecode(image, cv2.IMREAD_COLOR)\n",
        "\n",
        "    if image is not None:\n",
        "      image_height, image_width = image.shape[:2]\n",
        "    else:\n",
        "      continue\n",
        "\n",
        "    # Save image\n",
        "    image_path = os.path.join(image_dir, f'image_{idx}.jpg')\n",
        "    cv2.imwrite(image_path, image)\n",
        "\n",
        "    # Convert bbox to YOLO format\n",
        "    # Extract bounding box and class ID\n",
        "    bbox = row['objects'].get(\"bbox\")  # [x_min, y_min, width, height]\n",
        "    class_id = 0  # Class ID\n",
        "\n",
        "\n",
        "    # Normalize bbox coordinates\n",
        "    x_min, y_min, width, height = bbox[0]\n",
        "    x_center = (x_min + width / 2) / image_width\n",
        "    y_center = (y_min + height / 2) / image_height\n",
        "    bbox_width = width / image_width\n",
        "    bbox_height = height / image_height\n",
        "\n",
        "    # Save label file\n",
        "    label_path = os.path.join(label_dir, f'image_{idx}.txt')\n",
        "    with open(label_path, 'w') as f:\n",
        "        f.write(f'{class_id} {x_center} {y_center} {bbox_width} {bbox_height}\\n')"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 11,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "UpfV5l2Dom3t",
        "outputId": "78e0a3c8-34cc-4f92-f31d-62b4b06a132a"
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "Ultralytics 8.3.68 🚀 Python-3.11.11 torch-2.5.1+cu121 CUDA:0 (NVIDIA A100-SXM4-40GB, 40514MiB)\n",
            "\u001b[34m\u001b[1mengine/trainer: \u001b[0mtask=detect, mode=train, model=yolov8n.pt, data=dataset.yaml, epochs=75, time=None, patience=100, batch=16, imgsz=640, save=True, save_period=-1, cache=False, device=None, workers=8, project=None, name=train3, 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, multi_scale=False, 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, vid_stride=1, stream_buffer=False, visualize=False, augment=False, agnostic_nms=False, classes=None, retina_masks=False, embed=None, show=False, save_frames=False, save_txt=False, save_conf=False, save_crop=False, show_labels=True, show_conf=True, show_boxes=True, line_width=None, format=torchscript, keras=False, optimize=False, int8=False, dynamic=False, simplify=True, opset=None, workspace=None, 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, 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, bgr=0.0, mosaic=1.0, mixup=0.0, copy_paste=0.0, copy_paste_mode=flip, auto_augment=randaugment, erasing=0.4, crop_fraction=1.0, cfg=None, tracker=botsort.yaml, save_dir=runs/detect/train3\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, 3,011,043 parameters, 3,011,027 gradients, 8.2 GFLOPs\n",
            "\n",
            "Transferred 355/355 items from pretrained weights\n",
            "\u001b[34m\u001b[1mTensorBoard: \u001b[0mStart with 'tensorboard --logdir runs/detect/train3', 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...\n",
            "\u001b[34m\u001b[1mAMP: \u001b[0mchecks passed ✅\n"
          ]
        },
        {
          "name": "stderr",
          "output_type": "stream",
          "text": [
            "\u001b[34m\u001b[1mtrain: \u001b[0mScanning /content/dataset/labels/train.cache... 6176 images, 0 backgrounds, 0 corrupt: 100%|██████████| 6176/6176 [00:00<?, ?it/s]"
          ]
        },
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "\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, num_output_channels=3, method='weighted_average'), CLAHE(p=0.01, clip_limit=(1.0, 4.0), tile_grid_size=(8, 8))\n"
          ]
        },
        {
          "name": "stderr",
          "output_type": "stream",
          "text": [
            "\n",
            "\u001b[34m\u001b[1mval: \u001b[0mScanning /content/dataset/labels/val.cache... 1765 images, 0 backgrounds, 0 corrupt: 100%|██████████| 1765/1765 [00:00<?, ?it/s]\n"
          ]
        },
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "Plotting labels to runs/detect/train3/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",
            "\u001b[34m\u001b[1mTensorBoard: \u001b[0mmodel graph visualization added ✅\n",
            "Image sizes 640 train, 640 val\n",
            "Using 8 dataloader workers\n",
            "Logging results to \u001b[1mruns/detect/train3\u001b[0m\n",
            "Starting training for 75 epochs...\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n"
          ]
        },
        {
          "name": "stderr",
          "output_type": "stream",
          "text": [
            "       1/75      3.87G      1.143      0.681      1.065         31        640: 100%|██████████| 386/386 [00:38<00:00,  9.98it/s]\n",
            "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100%|██████████| 56/56 [00:06<00:00,  8.89it/s]"
          ]
        },
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "                   all       1765       1765      0.975       0.95      0.975      0.641\n"
          ]
        },
        {
          "name": "stderr",
          "output_type": "stream",
          "text": [
            "\n"
          ]
        },
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "\n",
            "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n"
          ]
        },
        {
          "name": "stderr",
          "output_type": "stream",
          "text": [
            "       2/75      4.01G      1.186     0.6815      1.092         28        640: 100%|██████████| 386/386 [00:36<00:00, 10.45it/s]\n",
            "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100%|██████████| 56/56 [00:06<00:00,  8.84it/s]"
          ]
        },
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "                   all       1765       1765      0.913      0.932      0.962      0.649\n"
          ]
        },
        {
          "name": "stderr",
          "output_type": "stream",
          "text": [
            "\n"
          ]
        },
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "\n",
            "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n"
          ]
        },
        {
          "name": "stderr",
          "output_type": "stream",
          "text": [
            "       3/75      4.01G      1.206     0.6668      1.097         31        640: 100%|██████████| 386/386 [00:35<00:00, 10.85it/s]\n",
            "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100%|██████████| 56/56 [00:06<00:00,  9.00it/s]"
          ]
        },
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "                   all       1765       1765      0.955      0.952      0.979      0.668\n"
          ]
        },
        {
          "name": "stderr",
          "output_type": "stream",
          "text": [
            "\n"
          ]
        },
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "\n",
            "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n"
          ]
        },
        {
          "name": "stderr",
          "output_type": "stream",
          "text": [
            "       4/75      4.01G      1.196     0.6361      1.095         32        640: 100%|██████████| 386/386 [00:35<00:00, 11.01it/s]\n",
            "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100%|██████████| 56/56 [00:06<00:00,  9.12it/s]"
          ]
        },
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "                   all       1765       1765      0.974      0.959      0.981      0.684\n"
          ]
        },
        {
          "name": "stderr",
          "output_type": "stream",
          "text": [
            "\n"
          ]
        },
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "\n",
            "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n"
          ]
        },
        {
          "name": "stderr",
          "output_type": "stream",
          "text": [
            "       5/75      4.01G      1.189     0.6285      1.099         30        640: 100%|██████████| 386/386 [00:34<00:00, 11.05it/s]\n",
            "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100%|██████████| 56/56 [00:06<00:00,  9.06it/s]"
          ]
        },
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "                   all       1765       1765      0.971      0.954      0.981       0.68\n"
          ]
        },
        {
          "name": "stderr",
          "output_type": "stream",
          "text": [
            "\n"
          ]
        },
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "\n",
            "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n"
          ]
        },
        {
          "name": "stderr",
          "output_type": "stream",
          "text": [
            "       6/75      4.01G      1.161     0.6001      1.081         25        640: 100%|██████████| 386/386 [00:35<00:00, 11.03it/s]\n",
            "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100%|██████████| 56/56 [00:06<00:00,  9.05it/s]"
          ]
        },
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "                   all       1765       1765      0.974      0.969      0.989      0.689\n"
          ]
        },
        {
          "name": "stderr",
          "output_type": "stream",
          "text": [
            "\n"
          ]
        },
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "\n",
            "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n"
          ]
        },
        {
          "name": "stderr",
          "output_type": "stream",
          "text": [
            "       7/75      4.01G      1.145     0.5798      1.073         24        640: 100%|██████████| 386/386 [00:35<00:00, 10.88it/s]\n",
            "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100%|██████████| 56/56 [00:06<00:00,  9.14it/s]"
          ]
        },
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "                   all       1765       1765      0.974      0.967      0.989      0.691\n"
          ]
        },
        {
          "name": "stderr",
          "output_type": "stream",
          "text": [
            "\n"
          ]
        },
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "\n",
            "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n"
          ]
        },
        {
          "name": "stderr",
          "output_type": "stream",
          "text": [
            "       8/75      4.01G      1.147     0.5732      1.073         32        640: 100%|██████████| 386/386 [00:35<00:00, 10.98it/s]\n",
            "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100%|██████████| 56/56 [00:06<00:00,  8.95it/s]"
          ]
        },
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "                   all       1765       1765      0.968      0.967      0.987      0.689\n"
          ]
        },
        {
          "name": "stderr",
          "output_type": "stream",
          "text": [
            "\n"
          ]
        },
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "\n",
            "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n"
          ]
        },
        {
          "name": "stderr",
          "output_type": "stream",
          "text": [
            "       9/75      4.01G      1.126     0.5606      1.068         24        640: 100%|██████████| 386/386 [00:34<00:00, 11.04it/s]\n",
            "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100%|██████████| 56/56 [00:06<00:00,  9.09it/s]"
          ]
        },
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "                   all       1765       1765      0.975      0.961      0.983      0.694\n"
          ]
        },
        {
          "name": "stderr",
          "output_type": "stream",
          "text": [
            "\n"
          ]
        },
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "\n",
            "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n"
          ]
        },
        {
          "name": "stderr",
          "output_type": "stream",
          "text": [
            "      10/75      4.01G      1.119     0.5514      1.062         28        640: 100%|██████████| 386/386 [00:34<00:00, 11.05it/s]\n",
            "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100%|██████████| 56/56 [00:06<00:00,  8.71it/s]"
          ]
        },
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "                   all       1765       1765      0.972      0.955      0.985      0.697\n"
          ]
        },
        {
          "name": "stderr",
          "output_type": "stream",
          "text": [
            "\n"
          ]
        },
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "\n",
            "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n"
          ]
        },
        {
          "name": "stderr",
          "output_type": "stream",
          "text": [
            "      11/75      4.01G      1.124     0.5437      1.063         29        640: 100%|██████████| 386/386 [00:34<00:00, 11.04it/s]\n",
            "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100%|██████████| 56/56 [00:06<00:00,  9.03it/s]"
          ]
        },
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "                   all       1765       1765      0.973      0.967      0.988       0.69\n"
          ]
        },
        {
          "name": "stderr",
          "output_type": "stream",
          "text": [
            "\n"
          ]
        },
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "\n",
            "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n"
          ]
        },
        {
          "name": "stderr",
          "output_type": "stream",
          "text": [
            "      12/75      4.01G      1.124     0.5377      1.062         28        640: 100%|██████████| 386/386 [00:35<00:00, 10.92it/s]\n",
            "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100%|██████████| 56/56 [00:06<00:00,  8.90it/s]"
          ]
        },
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "                   all       1765       1765      0.983      0.968      0.985      0.702\n"
          ]
        },
        {
          "name": "stderr",
          "output_type": "stream",
          "text": [
            "\n"
          ]
        },
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "\n",
            "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n"
          ]
        },
        {
          "name": "stderr",
          "output_type": "stream",
          "text": [
            "      13/75      4.01G      1.112     0.5336      1.061         42        640: 100%|██████████| 386/386 [00:35<00:00, 10.96it/s]\n",
            "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100%|██████████| 56/56 [00:06<00:00,  9.07it/s]"
          ]
        },
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "                   all       1765       1765      0.969      0.972      0.988      0.692\n"
          ]
        },
        {
          "name": "stderr",
          "output_type": "stream",
          "text": [
            "\n"
          ]
        },
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "\n",
            "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n"
          ]
        },
        {
          "name": "stderr",
          "output_type": "stream",
          "text": [
            "      14/75      4.01G      1.109     0.5251      1.051         27        640: 100%|██████████| 386/386 [00:34<00:00, 11.10it/s]\n",
            "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100%|██████████| 56/56 [00:06<00:00,  8.81it/s]"
          ]
        },
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "                   all       1765       1765      0.979      0.968      0.987       0.71\n"
          ]
        },
        {
          "name": "stderr",
          "output_type": "stream",
          "text": [
            "\n"
          ]
        },
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "\n",
            "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n"
          ]
        },
        {
          "name": "stderr",
          "output_type": "stream",
          "text": [
            "      15/75      4.01G      1.109     0.5195      1.056         34        640: 100%|██████████| 386/386 [00:34<00:00, 11.09it/s]\n",
            "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100%|██████████| 56/56 [00:06<00:00,  9.32it/s]"
          ]
        },
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "                   all       1765       1765      0.977      0.969      0.988      0.717\n"
          ]
        },
        {
          "name": "stderr",
          "output_type": "stream",
          "text": [
            "\n"
          ]
        },
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "\n",
            "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n"
          ]
        },
        {
          "name": "stderr",
          "output_type": "stream",
          "text": [
            "      16/75      4.01G      1.099     0.5134      1.055         28        640: 100%|██████████| 386/386 [00:34<00:00, 11.05it/s]\n",
            "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100%|██████████| 56/56 [00:06<00:00,  9.05it/s]"
          ]
        },
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "                   all       1765       1765      0.982      0.967      0.988      0.705\n"
          ]
        },
        {
          "name": "stderr",
          "output_type": "stream",
          "text": [
            "\n"
          ]
        },
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "\n",
            "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n"
          ]
        },
        {
          "name": "stderr",
          "output_type": "stream",
          "text": [
            "      17/75      4.01G      1.095     0.5061      1.055         31        640: 100%|██████████| 386/386 [00:34<00:00, 11.04it/s]\n",
            "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100%|██████████| 56/56 [00:06<00:00,  9.03it/s]"
          ]
        },
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "                   all       1765       1765      0.975      0.973      0.989       0.71\n"
          ]
        },
        {
          "name": "stderr",
          "output_type": "stream",
          "text": [
            "\n"
          ]
        },
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "\n",
            "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n"
          ]
        },
        {
          "name": "stderr",
          "output_type": "stream",
          "text": [
            "      18/75      4.01G      1.092     0.5071      1.053         30        640: 100%|██████████| 386/386 [00:35<00:00, 11.02it/s]\n",
            "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100%|██████████| 56/56 [00:06<00:00,  8.84it/s]"
          ]
        },
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "                   all       1765       1765      0.979      0.966      0.985      0.707\n"
          ]
        },
        {
          "name": "stderr",
          "output_type": "stream",
          "text": [
            "\n"
          ]
        },
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "\n",
            "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n"
          ]
        },
        {
          "name": "stderr",
          "output_type": "stream",
          "text": [
            "      19/75      4.01G      1.081     0.5001      1.048         31        640: 100%|██████████| 386/386 [00:35<00:00, 10.80it/s]\n",
            "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100%|██████████| 56/56 [00:06<00:00,  9.17it/s]"
          ]
        },
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "                   all       1765       1765      0.973       0.98      0.987      0.701\n"
          ]
        },
        {
          "name": "stderr",
          "output_type": "stream",
          "text": [
            "\n"
          ]
        },
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "\n",
            "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n"
          ]
        },
        {
          "name": "stderr",
          "output_type": "stream",
          "text": [
            "      20/75      4.01G      1.073     0.4922      1.045         27        640: 100%|██████████| 386/386 [00:34<00:00, 11.08it/s]\n",
            "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100%|██████████| 56/56 [00:06<00:00,  8.84it/s]"
          ]
        },
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "                   all       1765       1765      0.982       0.97      0.988      0.709\n"
          ]
        },
        {
          "name": "stderr",
          "output_type": "stream",
          "text": [
            "\n"
          ]
        },
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "\n",
            "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n"
          ]
        },
        {
          "name": "stderr",
          "output_type": "stream",
          "text": [
            "      21/75      4.01G      1.084     0.4985      1.047         23        640: 100%|██████████| 386/386 [00:35<00:00, 10.95it/s]\n",
            "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100%|██████████| 56/56 [00:06<00:00,  9.09it/s]"
          ]
        },
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "                   all       1765       1765      0.977      0.968       0.99       0.72\n"
          ]
        },
        {
          "name": "stderr",
          "output_type": "stream",
          "text": [
            "\n"
          ]
        },
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "\n",
            "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n"
          ]
        },
        {
          "name": "stderr",
          "output_type": "stream",
          "text": [
            "      22/75      4.01G      1.064     0.4892      1.037         33        640: 100%|██████████| 386/386 [00:35<00:00, 10.94it/s]\n",
            "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100%|██████████| 56/56 [00:06<00:00,  8.87it/s]"
          ]
        },
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "                   all       1765       1765      0.972      0.973       0.99      0.704\n"
          ]
        },
        {
          "name": "stderr",
          "output_type": "stream",
          "text": [
            "\n"
          ]
        },
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "\n",
            "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n"
          ]
        },
        {
          "name": "stderr",
          "output_type": "stream",
          "text": [
            "      23/75      4.01G      1.078     0.4916      1.041         34        640: 100%|██████████| 386/386 [00:35<00:00, 10.98it/s]\n",
            "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100%|██████████| 56/56 [00:06<00:00,  9.24it/s]"
          ]
        },
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "                   all       1765       1765      0.979      0.971       0.99      0.725\n"
          ]
        },
        {
          "name": "stderr",
          "output_type": "stream",
          "text": [
            "\n"
          ]
        },
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "\n",
            "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n"
          ]
        },
        {
          "name": "stderr",
          "output_type": "stream",
          "text": [
            "      24/75      4.01G      1.062     0.4822      1.037         27        640: 100%|██████████| 386/386 [00:35<00:00, 10.93it/s]\n",
            "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100%|██████████| 56/56 [00:06<00:00,  8.81it/s]"
          ]
        },
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "                   all       1765       1765      0.977      0.973      0.989      0.719\n"
          ]
        },
        {
          "name": "stderr",
          "output_type": "stream",
          "text": [
            "\n"
          ]
        },
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "\n",
            "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n"
          ]
        },
        {
          "name": "stderr",
          "output_type": "stream",
          "text": [
            "      25/75      4.01G       1.07     0.4853      1.041         43        640: 100%|██████████| 386/386 [00:35<00:00, 10.93it/s]\n",
            "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100%|██████████| 56/56 [00:06<00:00,  9.15it/s]"
          ]
        },
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "                   all       1765       1765      0.975      0.976       0.99       0.72\n"
          ]
        },
        {
          "name": "stderr",
          "output_type": "stream",
          "text": [
            "\n"
          ]
        },
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "\n",
            "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n"
          ]
        },
        {
          "name": "stderr",
          "output_type": "stream",
          "text": [
            "      26/75      4.01G      1.061     0.4755      1.032         36        640: 100%|██████████| 386/386 [00:35<00:00, 10.96it/s]\n",
            "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100%|██████████| 56/56 [00:06<00:00,  8.92it/s]\n"
          ]
        },
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "                   all       1765       1765      0.975      0.978      0.991      0.727\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n"
          ]
        },
        {
          "name": "stderr",
          "output_type": "stream",
          "text": [
            "      27/75      4.01G      1.059     0.4759      1.038         29        640: 100%|██████████| 386/386 [00:35<00:00, 11.02it/s]\n",
            "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100%|██████████| 56/56 [00:06<00:00,  9.04it/s]"
          ]
        },
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "                   all       1765       1765      0.981      0.974      0.991      0.726\n"
          ]
        },
        {
          "name": "stderr",
          "output_type": "stream",
          "text": [
            "\n"
          ]
        },
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "\n",
            "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n"
          ]
        },
        {
          "name": "stderr",
          "output_type": "stream",
          "text": [
            "      28/75      4.01G      1.058     0.4687      1.036         22        640: 100%|██████████| 386/386 [00:35<00:00, 10.97it/s]\n",
            "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100%|██████████| 56/56 [00:06<00:00,  9.07it/s]"
          ]
        },
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "                   all       1765       1765      0.977      0.973      0.988      0.718\n"
          ]
        },
        {
          "name": "stderr",
          "output_type": "stream",
          "text": [
            "\n"
          ]
        },
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "\n",
            "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n"
          ]
        },
        {
          "name": "stderr",
          "output_type": "stream",
          "text": [
            "      29/75      4.01G      1.055     0.4652      1.032         26        640: 100%|██████████| 386/386 [00:35<00:00, 10.93it/s]\n",
            "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100%|██████████| 56/56 [00:06<00:00,  9.07it/s]"
          ]
        },
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "                   all       1765       1765      0.982      0.974       0.99      0.725\n"
          ]
        },
        {
          "name": "stderr",
          "output_type": "stream",
          "text": [
            "\n"
          ]
        },
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "\n",
            "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n"
          ]
        },
        {
          "name": "stderr",
          "output_type": "stream",
          "text": [
            "      30/75      4.01G       1.05      0.462      1.034         28        640: 100%|██████████| 386/386 [00:35<00:00, 10.80it/s]\n",
            "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100%|██████████| 56/56 [00:06<00:00,  8.89it/s]"
          ]
        },
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "                   all       1765       1765      0.984      0.976      0.992      0.725\n"
          ]
        },
        {
          "name": "stderr",
          "output_type": "stream",
          "text": [
            "\n"
          ]
        },
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "\n",
            "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n"
          ]
        },
        {
          "name": "stderr",
          "output_type": "stream",
          "text": [
            "      31/75      4.01G      1.038     0.4587      1.033         22        640: 100%|██████████| 386/386 [00:35<00:00, 11.02it/s]\n",
            "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100%|██████████| 56/56 [00:06<00:00,  9.00it/s]"
          ]
        },
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "                   all       1765       1765      0.974      0.981       0.99      0.721\n"
          ]
        },
        {
          "name": "stderr",
          "output_type": "stream",
          "text": [
            "\n"
          ]
        },
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "\n",
            "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n"
          ]
        },
        {
          "name": "stderr",
          "output_type": "stream",
          "text": [
            "      32/75      4.01G      1.043     0.4582       1.03         28        640: 100%|██████████| 386/386 [00:35<00:00, 11.02it/s]\n",
            "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100%|██████████| 56/56 [00:06<00:00,  9.11it/s]"
          ]
        },
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "                   all       1765       1765      0.977      0.973      0.991      0.722\n"
          ]
        },
        {
          "name": "stderr",
          "output_type": "stream",
          "text": [
            "\n"
          ]
        },
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "\n",
            "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n"
          ]
        },
        {
          "name": "stderr",
          "output_type": "stream",
          "text": [
            "      33/75      4.01G      1.041     0.4539      1.022         30        640: 100%|██████████| 386/386 [00:35<00:00, 10.99it/s]\n",
            "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100%|██████████| 56/56 [00:06<00:00,  8.98it/s]"
          ]
        },
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "                   all       1765       1765      0.977      0.979      0.992      0.731\n"
          ]
        },
        {
          "name": "stderr",
          "output_type": "stream",
          "text": [
            "\n"
          ]
        },
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "\n",
            "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n"
          ]
        },
        {
          "name": "stderr",
          "output_type": "stream",
          "text": [
            "      34/75      4.01G      1.044     0.4597      1.026         25        640: 100%|██████████| 386/386 [00:35<00:00, 10.93it/s]\n",
            "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100%|██████████| 56/56 [00:06<00:00,  9.20it/s]"
          ]
        },
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "                   all       1765       1765      0.978      0.976      0.992      0.729\n"
          ]
        },
        {
          "name": "stderr",
          "output_type": "stream",
          "text": [
            "\n"
          ]
        },
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "\n",
            "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n"
          ]
        },
        {
          "name": "stderr",
          "output_type": "stream",
          "text": [
            "      35/75      4.01G      1.028     0.4473      1.025         35        640: 100%|██████████| 386/386 [00:35<00:00, 11.01it/s]\n",
            "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100%|██████████| 56/56 [00:06<00:00,  8.98it/s]"
          ]
        },
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "                   all       1765       1765      0.982      0.976      0.993       0.73\n"
          ]
        },
        {
          "name": "stderr",
          "output_type": "stream",
          "text": [
            "\n"
          ]
        },
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "\n",
            "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n"
          ]
        },
        {
          "name": "stderr",
          "output_type": "stream",
          "text": [
            "      36/75      4.01G      1.034     0.4504      1.028         30        640: 100%|██████████| 386/386 [00:35<00:00, 10.86it/s]\n",
            "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100%|██████████| 56/56 [00:06<00:00,  9.11it/s]"
          ]
        },
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "                   all       1765       1765      0.983      0.975      0.989      0.725\n"
          ]
        },
        {
          "name": "stderr",
          "output_type": "stream",
          "text": [
            "\n"
          ]
        },
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "\n",
            "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n"
          ]
        },
        {
          "name": "stderr",
          "output_type": "stream",
          "text": [
            "      37/75      4.01G      1.024     0.4418      1.024         27        640: 100%|██████████| 386/386 [00:35<00:00, 10.94it/s]\n",
            "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100%|██████████| 56/56 [00:06<00:00,  8.80it/s]"
          ]
        },
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "                   all       1765       1765      0.983      0.972      0.991      0.727\n"
          ]
        },
        {
          "name": "stderr",
          "output_type": "stream",
          "text": [
            "\n"
          ]
        },
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "\n",
            "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n"
          ]
        },
        {
          "name": "stderr",
          "output_type": "stream",
          "text": [
            "      38/75      4.01G      1.018     0.4412      1.017         35        640: 100%|██████████| 386/386 [00:35<00:00, 10.98it/s]\n",
            "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100%|██████████| 56/56 [00:06<00:00,  9.06it/s]"
          ]
        },
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "                   all       1765       1765      0.979      0.976      0.992      0.724\n"
          ]
        },
        {
          "name": "stderr",
          "output_type": "stream",
          "text": [
            "\n"
          ]
        },
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "\n",
            "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n"
          ]
        },
        {
          "name": "stderr",
          "output_type": "stream",
          "text": [
            "      39/75      4.01G      1.031     0.4443      1.025         33        640: 100%|██████████| 386/386 [00:35<00:00, 10.90it/s]\n",
            "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100%|██████████| 56/56 [00:06<00:00,  8.73it/s]"
          ]
        },
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "                   all       1765       1765      0.977      0.977      0.991      0.728\n"
          ]
        },
        {
          "name": "stderr",
          "output_type": "stream",
          "text": [
            "\n"
          ]
        },
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "\n",
            "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n"
          ]
        },
        {
          "name": "stderr",
          "output_type": "stream",
          "text": [
            "      40/75      4.01G      1.026     0.4408      1.026         27        640: 100%|██████████| 386/386 [00:35<00:00, 10.98it/s]\n",
            "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100%|██████████| 56/56 [00:06<00:00,  9.22it/s]"
          ]
        },
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "                   all       1765       1765      0.976      0.977      0.991       0.73\n"
          ]
        },
        {
          "name": "stderr",
          "output_type": "stream",
          "text": [
            "\n"
          ]
        },
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "\n",
            "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n"
          ]
        },
        {
          "name": "stderr",
          "output_type": "stream",
          "text": [
            "      41/75      4.01G       1.01     0.4325      1.016         38        640: 100%|██████████| 386/386 [00:35<00:00, 10.92it/s]\n",
            "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100%|██████████| 56/56 [00:06<00:00,  8.88it/s]"
          ]
        },
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "                   all       1765       1765      0.979      0.977      0.991      0.734\n"
          ]
        },
        {
          "name": "stderr",
          "output_type": "stream",
          "text": [
            "\n"
          ]
        },
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "\n",
            "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n"
          ]
        },
        {
          "name": "stderr",
          "output_type": "stream",
          "text": [
            "      42/75      4.01G      1.014     0.4312      1.016         27        640: 100%|██████████| 386/386 [00:35<00:00, 10.83it/s]\n",
            "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100%|██████████| 56/56 [00:06<00:00,  9.07it/s]"
          ]
        },
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "                   all       1765       1765      0.984       0.97       0.99      0.737\n"
          ]
        },
        {
          "name": "stderr",
          "output_type": "stream",
          "text": [
            "\n"
          ]
        },
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "\n",
            "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n"
          ]
        },
        {
          "name": "stderr",
          "output_type": "stream",
          "text": [
            "      43/75      4.01G      1.015     0.4328      1.018         26        640: 100%|██████████| 386/386 [00:34<00:00, 11.09it/s]\n",
            "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100%|██████████| 56/56 [00:06<00:00,  8.79it/s]"
          ]
        },
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "                   all       1765       1765      0.984      0.973      0.991      0.737\n"
          ]
        },
        {
          "name": "stderr",
          "output_type": "stream",
          "text": [
            "\n"
          ]
        },
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "\n",
            "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n"
          ]
        },
        {
          "name": "stderr",
          "output_type": "stream",
          "text": [
            "      44/75      4.01G      1.009     0.4306      1.018         26        640: 100%|██████████| 386/386 [00:34<00:00, 11.04it/s]\n",
            "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100%|██████████| 56/56 [00:06<00:00,  9.19it/s]"
          ]
        },
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "                   all       1765       1765      0.982      0.976      0.992      0.734\n"
          ]
        },
        {
          "name": "stderr",
          "output_type": "stream",
          "text": [
            "\n"
          ]
        },
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "\n",
            "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n"
          ]
        },
        {
          "name": "stderr",
          "output_type": "stream",
          "text": [
            "      45/75      4.01G      1.009     0.4255      1.012         26        640: 100%|██████████| 386/386 [00:34<00:00, 11.07it/s]\n",
            "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100%|██████████| 56/56 [00:06<00:00,  8.99it/s]"
          ]
        },
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "                   all       1765       1765      0.983      0.975      0.991      0.737\n"
          ]
        },
        {
          "name": "stderr",
          "output_type": "stream",
          "text": [
            "\n"
          ]
        },
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "\n",
            "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n"
          ]
        },
        {
          "name": "stderr",
          "output_type": "stream",
          "text": [
            "      46/75      4.01G      1.005     0.4262      1.013         32        640: 100%|██████████| 386/386 [00:34<00:00, 11.03it/s]\n",
            "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100%|██████████| 56/56 [00:06<00:00,  9.09it/s]"
          ]
        },
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "                   all       1765       1765      0.983      0.977      0.991      0.734\n"
          ]
        },
        {
          "name": "stderr",
          "output_type": "stream",
          "text": [
            "\n"
          ]
        },
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "\n",
            "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n"
          ]
        },
        {
          "name": "stderr",
          "output_type": "stream",
          "text": [
            "      47/75      4.01G      1.001     0.4223      1.011         30        640: 100%|██████████| 386/386 [00:34<00:00, 11.04it/s]\n",
            "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100%|██████████| 56/56 [00:06<00:00,  8.93it/s]"
          ]
        },
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "                   all       1765       1765      0.982      0.978      0.991      0.744\n"
          ]
        },
        {
          "name": "stderr",
          "output_type": "stream",
          "text": [
            "\n"
          ]
        },
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "\n",
            "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n"
          ]
        },
        {
          "name": "stderr",
          "output_type": "stream",
          "text": [
            "      48/75      4.01G          1     0.4205      1.007         30        640: 100%|██████████| 386/386 [00:35<00:00, 10.82it/s]\n",
            "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100%|██████████| 56/56 [00:06<00:00,  9.20it/s]"
          ]
        },
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "                   all       1765       1765      0.978      0.978      0.991      0.731\n"
          ]
        },
        {
          "name": "stderr",
          "output_type": "stream",
          "text": [
            "\n"
          ]
        },
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "\n",
            "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n"
          ]
        },
        {
          "name": "stderr",
          "output_type": "stream",
          "text": [
            "      49/75      4.01G     0.9894     0.4139      1.004         28        640: 100%|██████████| 386/386 [00:34<00:00, 11.08it/s]\n",
            "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100%|██████████| 56/56 [00:06<00:00,  8.95it/s]"
          ]
        },
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "                   all       1765       1765      0.984      0.977      0.991      0.737\n"
          ]
        },
        {
          "name": "stderr",
          "output_type": "stream",
          "text": [
            "\n"
          ]
        },
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "\n",
            "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n"
          ]
        },
        {
          "name": "stderr",
          "output_type": "stream",
          "text": [
            "      50/75      4.01G     0.9881     0.4116       1.01         29        640: 100%|██████████| 386/386 [00:34<00:00, 11.03it/s]\n",
            "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100%|██████████| 56/56 [00:06<00:00,  9.12it/s]"
          ]
        },
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "                   all       1765       1765      0.983      0.973      0.991      0.736\n"
          ]
        },
        {
          "name": "stderr",
          "output_type": "stream",
          "text": [
            "\n"
          ]
        },
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "\n",
            "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n"
          ]
        },
        {
          "name": "stderr",
          "output_type": "stream",
          "text": [
            "      51/75      4.01G     0.9787     0.4083      1.007         32        640: 100%|██████████| 386/386 [00:35<00:00, 10.93it/s]\n",
            "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100%|██████████| 56/56 [00:06<00:00,  9.18it/s]"
          ]
        },
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "                   all       1765       1765      0.984      0.972      0.991      0.742\n"
          ]
        },
        {
          "name": "stderr",
          "output_type": "stream",
          "text": [
            "\n"
          ]
        },
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "\n",
            "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n"
          ]
        },
        {
          "name": "stderr",
          "output_type": "stream",
          "text": [
            "      52/75      4.01G     0.9848     0.4058      1.008         36        640: 100%|██████████| 386/386 [00:34<00:00, 11.05it/s]\n",
            "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100%|██████████| 56/56 [00:06<00:00,  8.97it/s]"
          ]
        },
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "                   all       1765       1765      0.983      0.979      0.993      0.739\n"
          ]
        },
        {
          "name": "stderr",
          "output_type": "stream",
          "text": [
            "\n"
          ]
        },
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "\n",
            "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n"
          ]
        },
        {
          "name": "stderr",
          "output_type": "stream",
          "text": [
            "      53/75      4.01G     0.9799     0.4047      1.004         32        640: 100%|██████████| 386/386 [00:35<00:00, 10.99it/s]\n",
            "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100%|██████████| 56/56 [00:06<00:00,  9.13it/s]"
          ]
        },
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "                   all       1765       1765      0.987      0.978      0.991      0.735\n"
          ]
        },
        {
          "name": "stderr",
          "output_type": "stream",
          "text": [
            "\n"
          ]
        },
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "\n",
            "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n"
          ]
        },
        {
          "name": "stderr",
          "output_type": "stream",
          "text": [
            "      54/75      4.01G     0.9871      0.405      1.007         37        640: 100%|██████████| 386/386 [00:35<00:00, 10.79it/s]\n",
            "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100%|██████████| 56/56 [00:06<00:00,  8.94it/s]"
          ]
        },
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "                   all       1765       1765      0.987      0.976      0.992       0.74\n"
          ]
        },
        {
          "name": "stderr",
          "output_type": "stream",
          "text": [
            "\n"
          ]
        },
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "\n",
            "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n"
          ]
        },
        {
          "name": "stderr",
          "output_type": "stream",
          "text": [
            "      55/75      4.01G     0.9756     0.4016      1.001         27        640: 100%|██████████| 386/386 [00:34<00:00, 11.08it/s]\n",
            "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100%|██████████| 56/56 [00:06<00:00,  9.02it/s]"
          ]
        },
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "                   all       1765       1765      0.983      0.978      0.992      0.736\n"
          ]
        },
        {
          "name": "stderr",
          "output_type": "stream",
          "text": [
            "\n"
          ]
        },
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "\n",
            "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n"
          ]
        },
        {
          "name": "stderr",
          "output_type": "stream",
          "text": [
            "      56/75      4.01G     0.9782     0.4004          1         22        640: 100%|██████████| 386/386 [00:35<00:00, 10.99it/s]\n",
            "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100%|██████████| 56/56 [00:06<00:00,  8.97it/s]"
          ]
        },
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "                   all       1765       1765      0.985      0.978      0.992      0.741\n"
          ]
        },
        {
          "name": "stderr",
          "output_type": "stream",
          "text": [
            "\n"
          ]
        },
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "\n",
            "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n"
          ]
        },
        {
          "name": "stderr",
          "output_type": "stream",
          "text": [
            "      57/75      4.01G     0.9762     0.4005     0.9995         40        640: 100%|██████████| 386/386 [00:34<00:00, 11.06it/s]\n",
            "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100%|██████████| 56/56 [00:06<00:00,  9.10it/s]"
          ]
        },
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "                   all       1765       1765      0.988      0.977      0.993      0.739\n"
          ]
        },
        {
          "name": "stderr",
          "output_type": "stream",
          "text": [
            "\n"
          ]
        },
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "\n",
            "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n"
          ]
        },
        {
          "name": "stderr",
          "output_type": "stream",
          "text": [
            "      58/75      4.01G     0.9765     0.3915     0.9991         39        640: 100%|██████████| 386/386 [00:34<00:00, 11.07it/s]\n",
            "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100%|██████████| 56/56 [00:06<00:00,  8.96it/s]"
          ]
        },
        {
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          "output_type": "stream",
          "text": [
            "                   all       1765       1765      0.986      0.977      0.992       0.74\n"
          ]
        },
        {
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          "text": [
            "\n"
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        },
        {
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          "output_type": "stream",
          "text": [
            "\n",
            "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n"
          ]
        },
        {
          "name": "stderr",
          "output_type": "stream",
          "text": [
            "      59/75      4.01G     0.9694     0.3908      0.998         31        640: 100%|██████████| 386/386 [00:35<00:00, 10.99it/s]\n",
            "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100%|██████████| 56/56 [00:06<00:00,  9.19it/s]"
          ]
        },
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "                   all       1765       1765      0.984      0.978      0.992      0.739\n"
          ]
        },
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          "text": [
            "\n"
          ]
        },
        {
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          "output_type": "stream",
          "text": [
            "\n",
            "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n"
          ]
        },
        {
          "name": "stderr",
          "output_type": "stream",
          "text": [
            "      60/75      4.01G     0.9543     0.3885     0.9944         36        640: 100%|██████████| 386/386 [00:35<00:00, 10.87it/s]\n",
            "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100%|██████████| 56/56 [00:06<00:00,  8.94it/s]"
          ]
        },
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "                   all       1765       1765      0.982      0.982      0.992      0.743\n"
          ]
        },
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          "output_type": "stream",
          "text": [
            "\n"
          ]
        },
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "\n",
            "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n"
          ]
        },
        {
          "name": "stderr",
          "output_type": "stream",
          "text": [
            "      61/75      4.01G     0.9681     0.3927     0.9933         28        640: 100%|██████████| 386/386 [00:35<00:00, 11.01it/s]\n",
            "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100%|██████████| 56/56 [00:06<00:00,  9.07it/s]"
          ]
        },
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "                   all       1765       1765      0.983      0.978      0.992      0.741\n"
          ]
        },
        {
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          "text": [
            "\n"
          ]
        },
        {
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          "output_type": "stream",
          "text": [
            "\n",
            "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n"
          ]
        },
        {
          "name": "stderr",
          "output_type": "stream",
          "text": [
            "      62/75      4.01G     0.9578     0.3859     0.9942         26        640: 100%|██████████| 386/386 [00:35<00:00, 10.90it/s]\n",
            "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100%|██████████| 56/56 [00:06<00:00,  8.94it/s]"
          ]
        },
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "                   all       1765       1765      0.985       0.98      0.992       0.74\n"
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        },
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          "output_type": "stream",
          "text": [
            "\n"
          ]
        },
        {
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          "output_type": "stream",
          "text": [
            "\n",
            "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n"
          ]
        },
        {
          "name": "stderr",
          "output_type": "stream",
          "text": [
            "      63/75      4.01G     0.9556      0.383     0.9948         23        640: 100%|██████████| 386/386 [00:35<00:00, 11.01it/s]\n",
            "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100%|██████████| 56/56 [00:06<00:00,  9.16it/s]"
          ]
        },
        {
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            "                   all       1765       1765      0.985       0.98      0.992      0.743\n"
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        },
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          "text": [
            "\n"
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        },
        {
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          "output_type": "stream",
          "text": [
            "\n",
            "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n"
          ]
        },
        {
          "name": "stderr",
          "output_type": "stream",
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            "      64/75      4.01G     0.9538     0.3849      0.994         36        640: 100%|██████████| 386/386 [00:35<00:00, 11.02it/s]\n",
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          ]
        },
        {
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          ]
        },
        {
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          "output_type": "stream",
          "text": [
            "\n"
          ]
        },
        {
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          "output_type": "stream",
          "text": [
            "\n",
            "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n"
          ]
        },
        {
          "name": "stderr",
          "output_type": "stream",
          "text": [
            "      65/75      4.01G     0.9475     0.3823     0.9894         35        640: 100%|██████████| 386/386 [00:35<00:00, 10.98it/s]\n",
            "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100%|██████████| 56/56 [00:06<00:00,  9.09it/s]"
          ]
        },
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "                   all       1765       1765      0.983      0.978      0.992      0.739\n"
          ]
        },
        {
          "name": "stderr",
          "output_type": "stream",
          "text": [
            "\n"
          ]
        },
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "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, num_output_channels=3, method='weighted_average'), CLAHE(p=0.01, clip_limit=(1.0, 4.0), tile_grid_size=(8, 8))\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n"
          ]
        },
        {
          "name": "stderr",
          "output_type": "stream",
          "text": [
            "      66/75      4.01G     0.9412     0.3463      1.002         16        640: 100%|██████████| 386/386 [00:35<00:00, 10.83it/s]\n",
            "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100%|██████████| 56/56 [00:06<00:00,  8.94it/s]"
          ]
        },
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "                   all       1765       1765      0.985      0.978      0.991      0.737\n"
          ]
        },
        {
          "name": "stderr",
          "output_type": "stream",
          "text": [
            "\n"
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          "output_type": "stream",
          "text": [
            "\n",
            "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n"
          ]
        },
        {
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          "output_type": "stream",
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            "      67/75      4.01G     0.9393     0.3446      1.005         16        640: 100%|██████████| 386/386 [00:34<00:00, 11.16it/s]\n",
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          ]
        },
        {
          "name": "stdout",
          "output_type": "stream",
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            "                   all       1765       1765      0.986      0.976      0.991       0.74\n"
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        },
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            "\n"
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        },
        {
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          "output_type": "stream",
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            "\n",
            "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n"
          ]
        },
        {
          "name": "stderr",
          "output_type": "stream",
          "text": [
            "      68/75      4.01G      0.933     0.3398      1.001         16        640: 100%|██████████| 386/386 [00:34<00:00, 11.25it/s]\n",
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          ]
        },
        {
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          "output_type": "stream",
          "text": [
            "                   all       1765       1765      0.984       0.98      0.991      0.743\n"
          ]
        },
        {
          "name": "stderr",
          "output_type": "stream",
          "text": [
            "\n"
          ]
        },
        {
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          "output_type": "stream",
          "text": [
            "\n",
            "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n"
          ]
        },
        {
          "name": "stderr",
          "output_type": "stream",
          "text": [
            "      69/75      4.01G     0.9288     0.3388     0.9981         16        640: 100%|██████████| 386/386 [00:34<00:00, 11.24it/s]\n",
            "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100%|██████████| 56/56 [00:06<00:00,  8.99it/s]"
          ]
        },
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "                   all       1765       1765      0.988      0.976      0.992      0.741\n"
          ]
        },
        {
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            "\n"
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        },
        {
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          "output_type": "stream",
          "text": [
            "\n",
            "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n"
          ]
        },
        {
          "name": "stderr",
          "output_type": "stream",
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            "      70/75      4.01G     0.9258     0.3363     0.9976         16        640: 100%|██████████| 386/386 [00:34<00:00, 11.24it/s]\n",
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          ]
        },
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
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            "\n"
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        {
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          "output_type": "stream",
          "text": [
            "\n",
            "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n"
          ]
        },
        {
          "name": "stderr",
          "output_type": "stream",
          "text": [
            "      71/75      4.01G     0.9173     0.3323     0.9919         16        640: 100%|██████████| 386/386 [00:34<00:00, 11.24it/s]\n",
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          ]
        },
        {
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            "\n"
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        },
        {
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          "output_type": "stream",
          "text": [
            "\n",
            "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n"
          ]
        },
        {
          "name": "stderr",
          "output_type": "stream",
          "text": [
            "      72/75      4.01G     0.9119     0.3303     0.9896         16        640: 100%|██████████| 386/386 [00:34<00:00, 11.06it/s]\n",
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          ]
        },
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
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        },
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            "\n"
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        },
        {
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          "output_type": "stream",
          "text": [
            "\n",
            "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n"
          ]
        },
        {
          "name": "stderr",
          "output_type": "stream",
          "text": [
            "      73/75      4.01G     0.9126     0.3291     0.9877         16        640: 100%|██████████| 386/386 [00:34<00:00, 11.20it/s]\n",
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          ]
        },
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "                   all       1765       1765       0.99      0.974      0.992      0.744\n"
          ]
        },
        {
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          "output_type": "stream",
          "text": [
            "\n"
          ]
        },
        {
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          "output_type": "stream",
          "text": [
            "\n",
            "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n"
          ]
        },
        {
          "name": "stderr",
          "output_type": "stream",
          "text": [
            "      74/75      4.01G     0.9078     0.3285     0.9853         16        640: 100%|██████████| 386/386 [00:34<00:00, 11.16it/s]\n",
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          ]
        },
        {
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          "output_type": "stream",
          "text": [
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          ]
        },
        {
          "name": "stderr",
          "output_type": "stream",
          "text": [
            "\n"
          ]
        },
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "\n",
            "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n"
          ]
        },
        {
          "name": "stderr",
          "output_type": "stream",
          "text": [
            "      75/75      4.01G     0.9056     0.3249     0.9883         16        640: 100%|██████████| 386/386 [00:34<00:00, 11.22it/s]\n",
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          ]
        },
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "                   all       1765       1765       0.99      0.972      0.991      0.744\n"
          ]
        },
        {
          "name": "stderr",
          "output_type": "stream",
          "text": [
            "\n"
          ]
        },
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "\n",
            "75 epochs completed in 0.876 hours.\n",
            "Optimizer stripped from runs/detect/train3/weights/last.pt, 6.2MB\n",
            "Optimizer stripped from runs/detect/train3/weights/best.pt, 6.2MB\n",
            "\n",
            "Validating runs/detect/train3/weights/best.pt...\n",
            "Ultralytics 8.3.68 🚀 Python-3.11.11 torch-2.5.1+cu121 CUDA:0 (NVIDIA A100-SXM4-40GB, 40514MiB)\n",
            "Model summary (fused): 168 layers, 3,005,843 parameters, 0 gradients, 8.1 GFLOPs\n"
          ]
        },
        {
          "name": "stderr",
          "output_type": "stream",
          "text": [
            "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100%|██████████| 56/56 [00:06<00:00,  8.10it/s]\n"
          ]
        },
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "                   all       1765       1765       0.99      0.974      0.993      0.744\n",
            "Speed: 0.1ms preprocess, 0.4ms inference, 0.0ms loss, 0.8ms postprocess per image\n",
            "Results saved to \u001b[1mruns/detect/train3\u001b[0m\n"
          ]
        }
      ],
      "source": [
        "# Train the model using the YAML file\n",
        "results = model.train(data=\"dataset.yaml\", epochs=75, imgsz=640, batch=16)"
      ]
    }
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