CustomTrained_Model.ipynb

{
  "nbformat": 4,
  "nbformat_minor": 0,
  "metadata": {
    "colab": {
      "provenance": [],
      "gpuType": "T4",
      "authorship_tag": "ABX9TyOwH/NcQCVgIqzufLqztbBu",
      "include_colab_link": true
    },
    "kernelspec": {
      "name": "python3",
      "display_name": "Python 3"
    },
    "language_info": {
      "name": "python"
    },
    "accelerator": "GPU"
  },
  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "view-in-github",
        "colab_type": "text"
      },
      "source": [
        "<a href=\"https://colab.research.google.com/github/harshit4311/Pepsi-Coke-LogoDetection/blob/main/CustomTrained_Model.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "collapsed": true,
        "id": "1OvDVqMerVpy",
        "outputId": "1c8b55cb-8b20-4c62-e436-5912307afd2b"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Collecting roboflow\n",
            "  Downloading roboflow-1.1.34-py3-none-any.whl (76 kB)\n",
            "\u001b[?25l     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m0.0/76.2 kB\u001b[0m \u001b[31m?\u001b[0m eta \u001b[36m-:--:--\u001b[0m\r\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m76.2/76.2 kB\u001b[0m \u001b[31m2.4 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[?25hRequirement already satisfied: certifi in /usr/local/lib/python3.10/dist-packages (from roboflow) (2024.7.4)\n",
            "Collecting chardet==4.0.0 (from roboflow)\n",
            "  Downloading chardet-4.0.0-py2.py3-none-any.whl (178 kB)\n",
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            "Requirement already satisfied: python-dateutil in /usr/local/lib/python3.10/dist-packages (from roboflow) (2.8.2)\n",
            "Collecting python-dotenv (from roboflow)\n",
            "  Downloading python_dotenv-1.0.1-py3-none-any.whl (19 kB)\n",
            "Requirement already satisfied: requests in /usr/local/lib/python3.10/dist-packages (from roboflow) (2.31.0)\n",
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            "Requirement already satisfied: urllib3>=1.26.6 in /usr/local/lib/python3.10/dist-packages (from roboflow) (2.0.7)\n",
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            "Requirement already satisfied: PyYAML>=5.3.1 in /usr/local/lib/python3.10/dist-packages (from roboflow) (6.0.1)\n",
            "Collecting requests-toolbelt (from roboflow)\n",
            "  Downloading requests_toolbelt-1.0.0-py2.py3-none-any.whl (54 kB)\n",
            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m54.5/54.5 kB\u001b[0m \u001b[31m8.9 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[?25hCollecting python-magic (from roboflow)\n",
            "  Downloading python_magic-0.4.27-py2.py3-none-any.whl (13 kB)\n",
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            "Requirement already satisfied: charset-normalizer<4,>=2 in /usr/local/lib/python3.10/dist-packages (from requests->roboflow) (3.3.2)\n",
            "Installing collected packages: python-magic, python-dotenv, chardet, requests-toolbelt, roboflow\n",
            "  Attempting uninstall: chardet\n",
            "    Found existing installation: chardet 5.2.0\n",
            "    Uninstalling chardet-5.2.0:\n",
            "      Successfully uninstalled chardet-5.2.0\n",
            "Successfully installed chardet-4.0.0 python-dotenv-1.0.1 python-magic-0.4.27 requests-toolbelt-1.0.0 roboflow-1.1.34\n",
            "loading Roboflow workspace...\n",
            "loading Roboflow project...\n",
            "[WARNING] we noticed you are downloading a `yolov8` datasets but you don't have `ultralytics` installed. Roboflow `.deploy` supports only models trained with `ultralytics==8.0.196`, to intall it `pip install ultralytics==8.0.196`.\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "Downloading Dataset Version Zip in Pepsi-Logo-Detection-1 to yolov8:: 100%|██████████| 249870/249870 [00:04<00:00, 58414.88it/s]"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "\n",
            "Extracting Dataset Version Zip to Pepsi-Logo-Detection-1 in yolov8:: 100%|██████████| 3127/3127 [00:01<00:00, 1703.79it/s]\n"
          ]
        }
      ],
      "source": [
        "!pip install roboflow\n",
        "\n",
        "# Pepsi datset\n",
        "from roboflow import Roboflow\n",
        "rf = Roboflow(api_key=\"sTc6rzGcJ1amfsX6qUia\")\n",
        "project = rf.workspace(\"detectionanas\").project(\"pepsi-logo-detection\")\n",
        "version = project.version(1)\n",
        "dataset = version.download(\"yolov8\")\n"
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# Coke dataset\n",
        "from roboflow import Roboflow\n",
        "rf = Roboflow(api_key=\"sTc6rzGcJ1amfsX6qUia\")\n",
        "project = rf.workspace(\"test01-fr735\").project(\"brands-qv6fs\")\n",
        "version = project.version(1)\n",
        "dataset = version.download(\"yolov8\")\n"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "collapsed": true,
        "id": "B9kfzPSMrkCO",
        "outputId": "580b7e77-bca8-481e-c117-3124f12a4963"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "loading Roboflow workspace...\n",
            "loading Roboflow project...\n",
            "[WARNING] we noticed you are downloading a `yolov8` datasets but you don't have `ultralytics` installed. Roboflow `.deploy` supports only models trained with `ultralytics==8.0.196`, to intall it `pip install ultralytics==8.0.196`.\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "Downloading Dataset Version Zip in Brands-1 to yolov8:: 100%|██████████| 36391/36391 [00:01<00:00, 33059.16it/s]"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "\n",
            "Extracting Dataset Version Zip to Brands-1 in yolov8:: 100%|██████████| 1348/1348 [00:00<00:00, 6917.18it/s]\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "!pip install av ultralytics\n",
        "\n",
        "from ultralytics import YOLO\n"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "collapsed": true,
        "id": "pNjc6dcxrsW_",
        "outputId": "fde30d57-dc54-4e35-d8d1-780628fdfbc9"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Collecting av\n",
            "  Downloading av-12.2.0-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (34.3 MB)\n",
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            "\u001b[?25hCollecting ultralytics\n",
            "  Downloading ultralytics-8.2.58-py3-none-any.whl (802 kB)\n",
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            "Collecting ultralytics-thop>=2.0.0 (from ultralytics)\n",
            "  Downloading ultralytics_thop-2.0.0-py3-none-any.whl (25 kB)\n",
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            "Requirement already satisfied: fsspec in /usr/local/lib/python3.10/dist-packages (from torch>=1.8.0->ultralytics) (2023.6.0)\n",
            "Collecting nvidia-cuda-nvrtc-cu12==12.1.105 (from torch>=1.8.0->ultralytics)\n",
            "  Using cached nvidia_cuda_nvrtc_cu12-12.1.105-py3-none-manylinux1_x86_64.whl (23.7 MB)\n",
            "Collecting nvidia-cuda-runtime-cu12==12.1.105 (from torch>=1.8.0->ultralytics)\n",
            "  Using cached nvidia_cuda_runtime_cu12-12.1.105-py3-none-manylinux1_x86_64.whl (823 kB)\n",
            "Collecting nvidia-cuda-cupti-cu12==12.1.105 (from torch>=1.8.0->ultralytics)\n",
            "  Using cached nvidia_cuda_cupti_cu12-12.1.105-py3-none-manylinux1_x86_64.whl (14.1 MB)\n",
            "Collecting nvidia-cudnn-cu12==8.9.2.26 (from torch>=1.8.0->ultralytics)\n",
            "  Using cached nvidia_cudnn_cu12-8.9.2.26-py3-none-manylinux1_x86_64.whl (731.7 MB)\n",
            "Collecting nvidia-cublas-cu12==12.1.3.1 (from torch>=1.8.0->ultralytics)\n",
            "  Using cached nvidia_cublas_cu12-12.1.3.1-py3-none-manylinux1_x86_64.whl (410.6 MB)\n",
            "Collecting nvidia-cufft-cu12==11.0.2.54 (from torch>=1.8.0->ultralytics)\n",
            "  Using cached nvidia_cufft_cu12-11.0.2.54-py3-none-manylinux1_x86_64.whl (121.6 MB)\n",
            "Collecting nvidia-curand-cu12==10.3.2.106 (from torch>=1.8.0->ultralytics)\n",
            "  Using cached nvidia_curand_cu12-10.3.2.106-py3-none-manylinux1_x86_64.whl (56.5 MB)\n",
            "Collecting nvidia-cusolver-cu12==11.4.5.107 (from torch>=1.8.0->ultralytics)\n",
            "  Using cached nvidia_cusolver_cu12-11.4.5.107-py3-none-manylinux1_x86_64.whl (124.2 MB)\n",
            "Collecting nvidia-cusparse-cu12==12.1.0.106 (from torch>=1.8.0->ultralytics)\n",
            "  Using cached nvidia_cusparse_cu12-12.1.0.106-py3-none-manylinux1_x86_64.whl (196.0 MB)\n",
            "Collecting nvidia-nccl-cu12==2.20.5 (from torch>=1.8.0->ultralytics)\n",
            "  Using cached nvidia_nccl_cu12-2.20.5-py3-none-manylinux2014_x86_64.whl (176.2 MB)\n",
            "Collecting nvidia-nvtx-cu12==12.1.105 (from torch>=1.8.0->ultralytics)\n",
            "  Using cached nvidia_nvtx_cu12-12.1.105-py3-none-manylinux1_x86_64.whl (99 kB)\n",
            "Requirement already satisfied: triton==2.3.0 in /usr/local/lib/python3.10/dist-packages (from torch>=1.8.0->ultralytics) (2.3.0)\n",
            "Collecting nvidia-nvjitlink-cu12 (from nvidia-cusolver-cu12==11.4.5.107->torch>=1.8.0->ultralytics)\n",
            "  Downloading nvidia_nvjitlink_cu12-12.5.82-py3-none-manylinux2014_x86_64.whl (21.3 MB)\n",
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            "\u001b[?25hRequirement already satisfied: six>=1.5 in /usr/local/lib/python3.10/dist-packages (from python-dateutil>=2.7->matplotlib>=3.3.0->ultralytics) (1.16.0)\n",
            "Requirement already satisfied: MarkupSafe>=2.0 in /usr/local/lib/python3.10/dist-packages (from jinja2->torch>=1.8.0->ultralytics) (2.1.5)\n",
            "Requirement already satisfied: mpmath<1.4,>=1.1.0 in /usr/local/lib/python3.10/dist-packages (from sympy->torch>=1.8.0->ultralytics) (1.3.0)\n",
            "Installing collected packages: nvidia-nvtx-cu12, nvidia-nvjitlink-cu12, nvidia-nccl-cu12, nvidia-curand-cu12, nvidia-cufft-cu12, nvidia-cuda-runtime-cu12, nvidia-cuda-nvrtc-cu12, nvidia-cuda-cupti-cu12, nvidia-cublas-cu12, av, nvidia-cusparse-cu12, nvidia-cudnn-cu12, nvidia-cusolver-cu12, ultralytics-thop, ultralytics\n",
            "Successfully installed av-12.2.0 nvidia-cublas-cu12-12.1.3.1 nvidia-cuda-cupti-cu12-12.1.105 nvidia-cuda-nvrtc-cu12-12.1.105 nvidia-cuda-runtime-cu12-12.1.105 nvidia-cudnn-cu12-8.9.2.26 nvidia-cufft-cu12-11.0.2.54 nvidia-curand-cu12-10.3.2.106 nvidia-cusolver-cu12-11.4.5.107 nvidia-cusparse-cu12-12.1.0.106 nvidia-nccl-cu12-2.20.5 nvidia-nvjitlink-cu12-12.5.82 nvidia-nvtx-cu12-12.1.105 ultralytics-8.2.58 ultralytics-thop-2.0.0\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "import os\n",
        "\n",
        "# Path to your coke dataset directory\n",
        "dataset_dir = '/content/coke-dataset/valid/labels'\n",
        "\n",
        "# List all label files in the dataset directory\n",
        "label_files = [file for file in os.listdir(dataset_dir) if file.endswith('.txt')]\n",
        "\n",
        "# Iterate through each label file and replace label 0 with label 1\n",
        "for label_file in label_files:\n",
        "    file_path = os.path.join(dataset_dir, label_file)\n",
        "    with open(file_path, 'r+') as f:\n",
        "        lines = f.readlines()\n",
        "        f.seek(0)\n",
        "        for line in lines:\n",
        "            parts = line.strip().split()\n",
        "            if len(parts) > 0:\n",
        "                label = int(parts[0])\n",
        "                if label == 0:\n",
        "                    parts[0] = '1'\n",
        "                f.write(' '.join(parts) + '\\n')\n",
        "        f.truncate()\n",
        "    print(f\"Updated labels in {label_file}\")\n",
        "\n",
        "print(\"Label update complete.\")\n"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "collapsed": true,
        "id": "3ohts3disDl8",
        "outputId": "76d9cc50-e05f-4441-9259-34e11e9469e0"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Updated labels in owen-vangioni-EJ74C9h8oSw-unsplash_jpg.rf.fb7612c118e26c58f501929e098d421a.txt\n",
            "Updated labels in maximilian-zahn-iYkr_NigI_A-unsplash_jpg.rf.7fc70429fd7a018d7ab3872af7f62bf8.txt\n",
            "Updated labels in Image_114_jpg.rf.a55dea670b529475ff8dfb4d2f6456ea.txt\n",
            "Updated labels in Image_29_jpg.rf.e8adb94b7c339a43e97e3d7250e9af7b.txt\n",
            "Updated labels in Image_79_jpg.rf.eb099f22bf19c2541358486f08bf82db.txt\n",
            "Updated labels in Image_104_jpeg.rf.c802069080e87d218d3ede1152189f01.txt\n",
            "Updated labels in Image_68_jpg.rf.6efa24f28e9240cd15406335b21ea5d6.txt\n",
            "Updated labels in Image_142_jpg.rf.05a8e7474f1ac26b01625280c9921903.txt\n",
            "Updated labels in Image_76_jpg.rf.8037a3db082a9abb6341d5d36b2bb1dd.txt\n",
            "Updated labels in Image_23_jpg.rf.a5076ab3068125f7840214367bd63d3b.txt\n",
            "Updated labels in Image_72_jpg.rf.c339a73eb0908c86c6e9afba9fec4a04.txt\n",
            "Updated labels in Image_21_jpg.rf.3774ab5dab556ddb225a5489f2860982.txt\n",
            "Updated labels in Image_43_jpg.rf.2035f274ad6719c4e7dad892ee23a6aa.txt\n",
            "Updated labels in Image_80_jpg.rf.1953c3eb295fb0b156faaa02ec96539d.txt\n",
            "Updated labels in Image_131_jpg.rf.55759d1fa30e7ad16755e39a59891cbc.txt\n",
            "Updated labels in sarang-pande-Y7uX3gjsiT4-unsplash_jpg.rf.fb9412ee8ff14921fcc2fccc462e16a8.txt\n",
            "Updated labels in Image_3_jpg.rf.85bb5229f934583c1535a520e514bb67.txt\n",
            "Updated labels in vaea-garrido-NvRJVdmNKf4-unsplash_jpg.rf.cb92a9440bf76692e83b7f30d5938109.txt\n",
            "Updated labels in Image_80_jpg.rf.f365839ad425332c209fc9f41c8d2e09.txt\n",
            "Updated labels in Screenshot-2024-02-20-at-9-26-52-PM_png.rf.5faee9226830a6521343d02648a0203c.txt\n",
            "Updated labels in sue-hughes-GHFsy_rnrP8-unsplash_jpg.rf.4e55363867b88298a439284b2efe92af.txt\n",
            "Updated labels in Image_196_jpg.rf.53d420beefb394d30dc01b778192b49d.txt\n",
            "Updated labels in Image_56_jpg.rf.553a7ede7f5adfd4fff5371734a4cccc.txt\n",
            "Updated labels in andrea-leopardi-u8NQockJPwg-unsplash_jpg.rf.3f34f252b6d2525c66f04721f44c01b5.txt\n",
            "Updated labels in Image_43_jpg.rf.fc2d23ae1c913451c496c78c13e24236.txt\n",
            "Updated labels in Image_50_jpg.rf.23d26a26c3a4f0e96516b4bd0279d50e.txt\n",
            "Updated labels in Image_127_jpg.rf.0bdfc5461fdef21237f36cad908774aa.txt\n",
            "Updated labels in Image_1_jpg.rf.88ac9465322290eb25f9423a3c1b2d05.txt\n",
            "Updated labels in Image_16_jpg.rf.43f0a324755063a153806c6359045a08.txt\n",
            "Updated labels in Image_75_jpg.rf.5f54f725a214f14b56657ff8496c517c.txt\n",
            "Updated labels in Image_66_png.rf.0e3f92219beb30f1d9678029a317df8a.txt\n",
            "Updated labels in Image_31_jpg.rf.04eb078903a131d41c344231727caf4e.txt\n",
            "Updated labels in Image_120_jpg.rf.7d59c9e233b35b69e6718254a9839a56.txt\n",
            "Updated labels in Image_71_jpg.rf.23ec44f7903ee3191f7040047dc3564d.txt\n",
            "Updated labels in hamish-weir-SUi9mYSVTyc-unsplash_jpg.rf.453ea005ca0b37896c3c4143d6f9c60c.txt\n",
            "Updated labels in Image_126_jpg.rf.f3dd0ae1e92825ac31d4f065447d67ad.txt\n",
            "Updated labels in Image_74_jpg.rf.d9fdcba4b865c61e463d9fb74aecc567.txt\n",
            "Updated labels in Image_15_jpg.rf.9ae763900c2ec6e7b8ee9623c32e4b65.txt\n",
            "Updated labels in Image_106_jpg.rf.af1a79118f8ffac69b78bf885b7c09d9.txt\n",
            "Updated labels in Image_41_jpg.rf.5a3d57650802c3137f67a0f7988e4de8.txt\n",
            "Updated labels in Image_177_jpg.rf.03120ac99788b7b4b3dc3600d5f34b86.txt\n",
            "Updated labels in Image_75_jpg.rf.fa4d6460fae0a76da7a2f8ce452b296a.txt\n",
            "Updated labels in Image_67_jpg.rf.b2a203f82587be7a01c1ea1a35b70760.txt\n",
            "Updated labels in Image_101_jpg.rf.6988c42856746484336c6d488e6081f4.txt\n",
            "Updated labels in sajjad-salehi-d53OiWlgWO4-unsplash_jpg.rf.7fe08bed275c57f754f8c245125c3abf.txt\n",
            "Updated labels in Image_50_jpg.rf.e2e6c0a9971033ff9f7514a92d63b20f.txt\n",
            "Updated labels in Image_76_jpg.rf.e20364211b476f37ef689d144daa3ee7.txt\n",
            "Updated labels in fox-60CpKQ7u-yE-unsplash_jpg.rf.99825f0a3537c2655d9b230e9aef5a25.txt\n",
            "Updated labels in Image_82_jpg.rf.f505d9c9eea254ee09ef8c1504000978.txt\n",
            "Updated labels in james-yarema-wQFmDhrvVSs-unsplash_jpg.rf.4a3281df5da53b8269a6dc785755c326.txt\n",
            "Updated labels in Image_13_jpg.rf.680cd517f4cd4c7d5b920acb8f82d195.txt\n",
            "Updated labels in Image_38_jpg.rf.ed82804e71da807130a02a094b55adcf.txt\n",
            "Updated labels in Image_36_jpg.rf.e564494ea4a031187f3459bd47990e32.txt\n",
            "Updated labels in Image_6_jpg.rf.98f99c43a47d562dc379b98a40f66da5.txt\n",
            "Updated labels in Image_42_JPG.rf.aa9f6a90c42b772c2e6f3ec59610076b.txt\n",
            "Updated labels in Image_66_jpeg.rf.b1ac09339cb2b3a46615ac015c775955.txt\n",
            "Updated labels in donald-teel-ymEc-M3Z1y4-unsplash_jpg.rf.b22076e0cce8f3a0935e0855ad1eb162.txt\n",
            "Updated labels in Image_119_jpg.rf.2fe03a161764b9edb8f43c79f7943e86.txt\n",
            "Updated labels in Image_47_jpg.rf.293ddb9f5e964736f8f7fe96b9b9c41a.txt\n",
            "Updated labels in randy-fath-Yi_ntljEuz0-unsplash_jpg.rf.9ee8dacf6445bb99120526dac0225b28.txt\n",
            "Updated labels in Image_110_jpg.rf.2aacbaa1c9755867c836dc09b5b42987.txt\n",
            "Updated labels in Image_22_jpg.rf.c2cbfc98737bc65f4fb73498f783b719.txt\n",
            "Updated labels in taras-chernus-MTTrsZIWDgw-unsplash_jpg.rf.d985f32eca3b285e16a4d9d4a7a54ccb.txt\n",
            "Updated labels in Image_12_jpg.rf.348eb8786c2500401434030b8eb514b2.txt\n",
            "Updated labels in Image_50_jpg.rf.aa42fc1e301d6a0523a1da75ae76455f.txt\n",
            "Updated labels in Image_153_jpg.rf.5ba0b38f10a3fef6acceff6867d4b1d3.txt\n",
            "Updated labels in Image_17_jpg.rf.8c72fd65a8ec77cfdf6e3ceed151541f.txt\n",
            "Updated labels in mariah-hewines-WXDsxWzbdG4-unsplash_jpg.rf.2ab0724e619bdfc0b079ae897809f6c5.txt\n",
            "Updated labels in spencer-davis-qIionkVllq0-unsplash_jpg.rf.2cc3669554870158d41e51b459c2ebd0.txt\n",
            "Updated labels in Image_41_jpg.rf.c8e01792558524eec4c265994f8cc317.txt\n",
            "Updated labels in Image_123_jpg.rf.fd8cc998a77fd41805dcbed5c17c660f.txt\n",
            "Updated labels in panos-sakalakis-hAIe6BO3f6c-unsplash_jpg.rf.e58e601b62f326decce6baa5d0055721.txt\n",
            "Updated labels in Screenshot-2024-02-20-at-9-22-25-PM_png.rf.0b79e1ebf2be80a948a1eb032160db05.txt\n",
            "Updated labels in ravi-sharma-nWCmjC7dmdo-unsplash_jpg.rf.58b760e4142839dd372efe70f8b41f55.txt\n",
            "Updated labels in Image_109_jpg.rf.2c1ed3c018a5cc2c6a98fcb8458046b2.txt\n",
            "Updated labels in Image_134_jpg.rf.edcfdb05837f577d51b8505f023a823e.txt\n",
            "Updated labels in Image_41_jpg.rf.8a080f01e7bcd889b6aa8f942c963e3e.txt\n",
            "Updated labels in Image_120_jpg.rf.b8bbf12a091f6cfcba5d39d54db5d4f1.txt\n",
            "Updated labels in taras-chernus-Q5s2cNLxPOw-unsplash_jpg.rf.71e4ff302a3827ec0638cac7fdae380a.txt\n",
            "Updated labels in Image_116_jpg.rf.66b088358e8f300bde1d444ba57d5606.txt\n",
            "Updated labels in taylor-rooney-YELGXc05QOw-unsplash_jpg.rf.239510fcfb9bfda5a82d909d9fd81cb3.txt\n",
            "Updated labels in Image_117_jpg.rf.213fb81228bdc10db2a48d9cd652d131.txt\n",
            "Updated labels in __-drz-__-UtbFfsFYVMQ-unsplash_jpg.rf.6d7ca212aa03b066b5a6d3071b8aa267.txt\n",
            "Updated labels in Image_41_jpg.rf.be4ba86f6442e9476cfe47eb6e245404.txt\n",
            "Updated labels in Image_37_jpeg.rf.2e478d712039cfb9d180375c772df060.txt\n",
            "Updated labels in Image_53_jpg.rf.0885ed3ce29650c9a1971217b42568ec.txt\n",
            "Updated labels in Image_38_jpg.rf.d575e5665a0058ea9efa951c95762c94.txt\n",
            "Updated labels in Image_67_jpg.rf.49d9bb7f870beb302f878cb311570d90.txt\n",
            "Updated labels in salman-sidheek-MOuMUQ-I6_Q-unsplash_jpg.rf.bcf6ccf9a4369e93fba8c3de2444e437.txt\n",
            "Updated labels in louis-hansel-M-4_S-SsDFw-unsplash_jpg.rf.7caf54e1f33873205f52a89dc685a411.txt\n",
            "Updated labels in amanda-vick-egXEwHvp90g-unsplash_jpg.rf.4e0b3082466b9911f081d889e658e849.txt\n",
            "Updated labels in Image_51_jpg.rf.15c2122a6666269e2259a3cdcd7af16e.txt\n",
            "Updated labels in Image_124_jpg.rf.34a1ad167cbe4b77b8a937d7e4029f45.txt\n",
            "Updated labels in Screenshot-2024-02-20-at-9-25-07-PM_png.rf.719316c2213036bdea96c5487aca2b07.txt\n",
            "Updated labels in mateusz-d-3S8jWSbPmtA-unsplash_jpg.rf.d9739da224b8a64415839c80f19dd024.txt\n",
            "Updated labels in Image_61_jpg.rf.e9406f48eae81ed16624a5d0a69a79a8.txt\n",
            "Updated labels in Image_4_jpg.rf.a2639fbae438b1dda00c4d4eeb834e8a.txt\n",
            "Updated labels in Image_121_jpg.rf.052c90cdb7effcc36ad4e2cefa34976d.txt\n",
            "Updated labels in Image_36_jpg.rf.db96704211be79b86795883f7f171e3d.txt\n",
            "Updated labels in arys-scott-FH8pGzYN6gs-unsplash_jpg.rf.988d0f83620bea39703d231d227a7fa3.txt\n",
            "Label update complete.\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "import os\n",
        "import shutil\n",
        "\n",
        "# Define paths to your datasets\n",
        "source_dataset_dir = '/content/coke-dataset'   # Path to coke-dataset\n",
        "destination_dataset_dir = '/content/pepsi-dataset'   # Path to pepsi-dataset\n",
        "\n",
        "# Ensure the destination directory exists, create it if it doesn't\n",
        "os.makedirs(destination_dataset_dir, exist_ok=True)\n",
        "\n",
        "# Function to copy all files from source to destination\n",
        "def copy_dataset(source_dir, destination_dir):\n",
        "    for root, dirs, files in os.walk(source_dir):\n",
        "        for file in files:\n",
        "            source_file = os.path.join(root, file)\n",
        "            dest_file = os.path.join(destination_dir, os.path.relpath(source_file, source_dir))\n",
        "            dest_dir = os.path.dirname(dest_file)\n",
        "            os.makedirs(dest_dir, exist_ok=True)\n",
        "            shutil.copyfile(source_file, dest_file)\n",
        "\n",
        "# Copy the dataset\n",
        "copy_dataset(source_dataset_dir, destination_dataset_dir)\n",
        "\n",
        "print(\"Dataset copied successfully from coke-dataset to pepsi-dataset.\")\n"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "collapsed": true,
        "id": "AHoBbJWZsNw9",
        "outputId": "f031a482-cd87-46bc-cfa6-6fd814b1f001"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Dataset copied successfully from coke-dataset to pepsi-dataset.\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "%ls"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "P6ZzCkEzsaKP",
        "outputId": "8aaff3f2-a4e1-4016-ffaf-9b67b72d0b20"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "\u001b[0m\u001b[01;34mcoke-dataset\u001b[0m/  \u001b[01;34mpepsi-dataset\u001b[0m/  \u001b[01;34msample_data\u001b[0m/\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "%cd pepsi-dataset/"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "collapsed": true,
        "id": "mOLE2Z9kscRh",
        "outputId": "6ec5071a-eb0c-464c-9f8a-c934d0d04d72"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "/content/pepsi-dataset\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "!yolo task=detect mode=train model=yolov8n.pt data=data.yaml epochs=100"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "collapsed": true,
        "id": "vHE7oJYEsh5M",
        "outputId": "6360cda2-f32d-42de-808f-dbb4e28c25ad"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Downloading https://github.com/ultralytics/assets/releases/download/v8.2.0/yolov8n.pt to 'yolov8n.pt'...\n",
            "100% 6.25M/6.25M [00:00<00:00, 102MB/s]\n",
            "Ultralytics YOLOv8.2.58 🚀 Python-3.10.12 torch-2.3.0+cu121 CUDA:0 (Tesla T4, 15102MiB)\n",
            "\u001b[34m\u001b[1mengine/trainer: \u001b[0mtask=detect, mode=train, model=yolov8n.pt, data=data.yaml, epochs=100, time=None, patience=100, batch=16, imgsz=640, save=True, save_period=-1, cache=False, device=None, workers=8, project=None, name=train, exist_ok=False, pretrained=True, optimizer=auto, verbose=True, seed=0, deterministic=True, single_cls=False, rect=False, cos_lr=False, close_mosaic=10, resume=False, amp=True, fraction=1.0, profile=False, freeze=None, 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=False, opset=None, workspace=4, nms=False, lr0=0.01, lrf=0.01, momentum=0.937, weight_decay=0.0005, warmup_epochs=3.0, warmup_momentum=0.8, warmup_bias_lr=0.1, box=7.5, cls=0.5, dfl=1.5, pose=12.0, kobj=1.0, label_smoothing=0.0, nbs=64, hsv_h=0.015, hsv_s=0.7, hsv_v=0.4, degrees=0.0, translate=0.1, scale=0.5, shear=0.0, perspective=0.0, flipud=0.0, fliplr=0.5, bgr=0.0, mosaic=1.0, mixup=0.0, copy_paste=0.0, auto_augment=randaugment, erasing=0.4, crop_fraction=1.0, cfg=None, tracker=botsort.yaml, save_dir=runs/detect/train\n",
            "Downloading https://ultralytics.com/assets/Arial.ttf to '/root/.config/Ultralytics/Arial.ttf'...\n",
            "100% 755k/755k [00:00<00:00, 22.8MB/s]\n",
            "Overriding model.yaml nc=80 with nc=2\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    751702  ultralytics.nn.modules.head.Detect           [2, [64, 128, 256]]           \n",
            "Model summary: 225 layers, 3,011,238 parameters, 3,011,222 gradients, 8.2 GFLOPs\n",
            "\n",
            "Transferred 319/355 items from pretrained weights\n",
            "\u001b[34m\u001b[1mTensorBoard: \u001b[0mStart with 'tensorboard --logdir runs/detect/train', view at http://localhost:6006/\n",
            "Freezing layer 'model.22.dfl.conv.weight'\n",
            "\u001b[34m\u001b[1mAMP: \u001b[0mrunning Automatic Mixed Precision (AMP) checks with YOLOv8n...\n",
            "/usr/local/lib/python3.10/dist-packages/torch/nn/modules/conv.py:456: UserWarning: Plan failed with a cudnnException: CUDNN_BACKEND_EXECUTION_PLAN_DESCRIPTOR: cudnnFinalize Descriptor Failed cudnn_status: CUDNN_STATUS_NOT_SUPPORTED (Triggered internally at ../aten/src/ATen/native/cudnn/Conv_v8.cpp:919.)\n",
            "  return F.conv2d(input, weight, bias, self.stride,\n",
            "\u001b[34m\u001b[1mAMP: \u001b[0mchecks passed ✅\n",
            "\u001b[34m\u001b[1mtrain: \u001b[0mScanning /content/datasets/train/labels... 1706 images, 236 backgrounds, 0 corrupt: 100% 1706/1706 [00:02<00:00, 584.38it/s]\n",
            "\u001b[34m\u001b[1mtrain: \u001b[0mNew cache created: /content/datasets/train/labels.cache\n",
            "\u001b[34m\u001b[1malbumentations: \u001b[0mBlur(p=0.01, blur_limit=(3, 7)), MedianBlur(p=0.01, blur_limit=(3, 7)), ToGray(p=0.01), CLAHE(p=0.01, clip_limit=(1, 4.0), tile_grid_size=(8, 8))\n",
            "/usr/lib/python3.10/multiprocessing/popen_fork.py:66: RuntimeWarning: os.fork() was called. os.fork() is incompatible with multithreaded code, and JAX is multithreaded, so this will likely lead to a deadlock.\n",
            "  self.pid = os.fork()\n",
            "\u001b[34m\u001b[1mval: \u001b[0mScanning /content/datasets/valid/labels... 418 images, 68 backgrounds, 0 corrupt: 100% 418/418 [00:00<00:00, 552.32it/s]\n",
            "\u001b[34m\u001b[1mval: \u001b[0mNew cache created: /content/datasets/valid/labels.cache\n",
            "Plotting labels to runs/detect/train/labels.jpg... \n",
            "\u001b[34m\u001b[1moptimizer:\u001b[0m 'optimizer=auto' found, ignoring 'lr0=0.01' and 'momentum=0.937' and determining best 'optimizer', 'lr0' and 'momentum' automatically... \n",
            "\u001b[34m\u001b[1moptimizer:\u001b[0m AdamW(lr=0.001667, 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 2 dataloader workers\n",
            "Logging results to \u001b[1mruns/detect/train\u001b[0m\n",
            "Starting training for 100 epochs...\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n",
            "      1/100      2.46G      1.256      2.502      1.208         17        640: 100% 107/107 [01:02<00:00,  1.73it/s]\n",
            "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95):  93% 13/14 [00:09<00:00,  1.45it/s]/usr/local/lib/python3.10/dist-packages/torch/nn/modules/conv.py:456: UserWarning: Plan failed with a cudnnException: CUDNN_BACKEND_EXECUTION_PLAN_DESCRIPTOR: cudnnFinalize Descriptor Failed cudnn_status: CUDNN_STATUS_NOT_SUPPORTED (Triggered internally at ../aten/src/ATen/native/cudnn/Conv_v8.cpp:919.)\n",
            "  return F.conv2d(input, weight, bias, self.stride,\n",
            "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100% 14/14 [00:09<00:00,  1.42it/s]\n",
            "                   all        418        716      0.559      0.524      0.566      0.351\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n",
            "      2/100       2.3G       1.26      1.713       1.21         24        640: 100% 107/107 [00:54<00:00,  1.97it/s]\n",
            "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100% 14/14 [00:11<00:00,  1.18it/s]\n",
            "                   all        418        716      0.492      0.607      0.494      0.296\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n",
            "      3/100      2.27G      1.299      1.526      1.241         24        640: 100% 107/107 [00:55<00:00,  1.91it/s]\n",
            "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100% 14/14 [00:07<00:00,  1.91it/s]\n",
            "                   all        418        716      0.635      0.451      0.505      0.301\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n",
            "      4/100      2.31G      1.314      1.413      1.263         41        640: 100% 107/107 [00:56<00:00,  1.89it/s]\n",
            "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100% 14/14 [00:08<00:00,  1.65it/s]\n",
            "                   all        418        716      0.721      0.629       0.68      0.428\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n",
            "      5/100      2.31G      1.258      1.237      1.227         19        640: 100% 107/107 [00:52<00:00,  2.05it/s]\n",
            "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100% 14/14 [00:12<00:00,  1.14it/s]\n",
            "                   all        418        716      0.769      0.679      0.731      0.449\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n",
            "      6/100      2.26G      1.242      1.165      1.221         42        640: 100% 107/107 [00:53<00:00,  1.99it/s]\n",
            "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100% 14/14 [00:09<00:00,  1.53it/s]\n",
            "                   all        418        716      0.721      0.714       0.75      0.476\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n",
            "      7/100      2.29G      1.206      1.083      1.182         34        640: 100% 107/107 [00:56<00:00,  1.89it/s]\n",
            "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100% 14/14 [00:07<00:00,  1.98it/s]\n",
            "                   all        418        716      0.781      0.677      0.735      0.467\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n",
            "      8/100      2.26G      1.206      1.062      1.184         28        640: 100% 107/107 [00:55<00:00,  1.92it/s]\n",
            "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100% 14/14 [00:10<00:00,  1.37it/s]\n",
            "                   all        418        716      0.797      0.689      0.752       0.48\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n",
            "      9/100      2.26G      1.178       1.01      1.169         48        640: 100% 107/107 [00:52<00:00,  2.04it/s]\n",
            "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100% 14/14 [00:11<00:00,  1.19it/s]\n",
            "                   all        418        716      0.713      0.726       0.75       0.47\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n",
            "     10/100      2.26G      1.199     0.9959      1.176         40        640: 100% 107/107 [00:54<00:00,  1.95it/s]\n",
            "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100% 14/14 [00:07<00:00,  1.77it/s]\n",
            "                   all        418        716      0.842      0.723      0.808      0.536\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n",
            "     11/100      2.29G      1.162     0.9518       1.15         21        640: 100% 107/107 [00:55<00:00,  1.92it/s]\n",
            "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100% 14/14 [00:07<00:00,  1.81it/s]\n",
            "                   all        418        716      0.787      0.684      0.757      0.491\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n",
            "     12/100       2.3G       1.16     0.9509      1.155         29        640: 100% 107/107 [00:53<00:00,  1.99it/s]\n",
            "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100% 14/14 [00:11<00:00,  1.23it/s]\n",
            "                   all        418        716      0.804      0.748      0.789      0.517\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n",
            "     13/100      2.28G      1.138     0.9265      1.142         26        640: 100% 107/107 [00:55<00:00,  1.93it/s]\n",
            "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100% 14/14 [00:08<00:00,  1.57it/s]\n",
            "                   all        418        716      0.796      0.709      0.786      0.524\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n",
            "     14/100      2.26G      1.139     0.9182      1.138         33        640: 100% 107/107 [00:56<00:00,  1.90it/s]\n",
            "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100% 14/14 [00:07<00:00,  1.96it/s]\n",
            "                   all        418        716      0.749      0.749      0.812      0.525\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n",
            "     15/100      2.29G      1.127     0.8974      1.125         26        640: 100% 107/107 [00:54<00:00,  1.95it/s]\n",
            "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100% 14/14 [00:10<00:00,  1.40it/s]\n",
            "                   all        418        716      0.745      0.774      0.771      0.507\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n",
            "     16/100      2.26G      1.129     0.8931       1.13         49        640: 100% 107/107 [00:51<00:00,  2.06it/s]\n",
            "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100% 14/14 [00:10<00:00,  1.32it/s]\n",
            "                   all        418        716      0.778      0.772      0.811      0.526\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n",
            "     17/100      2.26G      1.099     0.8585      1.121         31        640: 100% 107/107 [00:55<00:00,  1.94it/s]\n",
            "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100% 14/14 [00:07<00:00,  1.96it/s]\n",
            "                   all        418        716      0.801      0.745      0.814      0.555\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n",
            "     18/100       2.3G      1.085     0.8479      1.112         15        640: 100% 107/107 [00:55<00:00,  1.92it/s]\n",
            "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100% 14/14 [00:07<00:00,  1.84it/s]\n",
            "                   all        418        716      0.795      0.751      0.806      0.554\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n",
            "     19/100      2.27G       1.09     0.8596      1.113         20        640: 100% 107/107 [00:54<00:00,  1.97it/s]\n",
            "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100% 14/14 [00:10<00:00,  1.35it/s]\n",
            "                   all        418        716      0.836      0.751      0.828      0.554\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n",
            "     20/100      2.26G      1.104     0.8295      1.123         21        640: 100% 107/107 [00:51<00:00,  2.06it/s]\n",
            "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100% 14/14 [00:10<00:00,  1.37it/s]\n",
            "                   all        418        716      0.843      0.756      0.832      0.559\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n",
            "     21/100      2.28G      1.098     0.8581      1.122         25        640: 100% 107/107 [00:55<00:00,  1.92it/s]\n",
            "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100% 14/14 [00:07<00:00,  1.85it/s]\n",
            "                   all        418        716       0.81      0.733      0.797      0.534\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n",
            "     22/100      2.26G      1.085     0.8305      1.113         11        640: 100% 107/107 [00:55<00:00,  1.91it/s]\n",
            "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100% 14/14 [00:06<00:00,  2.08it/s]\n",
            "                   all        418        716      0.741      0.845      0.836      0.566\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n",
            "     23/100       2.3G      1.068     0.8084      1.095         13        640: 100% 107/107 [00:55<00:00,  1.94it/s]\n",
            "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100% 14/14 [00:09<00:00,  1.46it/s]\n",
            "                   all        418        716      0.803      0.781       0.83      0.546\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n",
            "     24/100       2.3G       1.08      0.813      1.103         35        640: 100% 107/107 [00:52<00:00,  2.03it/s]\n",
            "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100% 14/14 [00:10<00:00,  1.28it/s]\n",
            "                   all        418        716      0.852      0.779       0.85      0.567\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n",
            "     25/100      2.28G      1.051      0.777      1.086         21        640: 100% 107/107 [00:54<00:00,  1.95it/s]\n",
            "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100% 14/14 [00:08<00:00,  1.58it/s]\n",
            "                   all        418        716      0.792      0.823      0.853      0.571\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n",
            "     26/100      2.26G      1.059     0.7834      1.089         26        640: 100% 107/107 [00:56<00:00,  1.89it/s]\n",
            "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100% 14/14 [00:07<00:00,  2.00it/s]\n",
            "                   all        418        716      0.818       0.81      0.857      0.567\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n",
            "     27/100      2.25G      1.068      0.775      1.089         19        640: 100% 107/107 [00:55<00:00,  1.91it/s]\n",
            "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100% 14/14 [00:09<00:00,  1.55it/s]\n",
            "                   all        418        716      0.805      0.826      0.866      0.587\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n",
            "     28/100      2.26G      1.031     0.7532      1.085         22        640: 100% 107/107 [00:52<00:00,  2.06it/s]\n",
            "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100% 14/14 [00:12<00:00,  1.17it/s]\n",
            "                   all        418        716      0.792       0.79      0.826      0.554\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n",
            "     29/100      2.28G      1.057     0.7844      1.095         27        640: 100% 107/107 [00:55<00:00,  1.94it/s]\n",
            "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100% 14/14 [00:08<00:00,  1.72it/s]\n",
            "                   all        418        716      0.765      0.825       0.85       0.57\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n",
            "     30/100      2.28G      1.027     0.7203      1.083         34        640: 100% 107/107 [00:54<00:00,  1.96it/s]\n",
            "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100% 14/14 [00:07<00:00,  1.83it/s]\n",
            "                   all        418        716      0.802       0.81      0.859       0.58\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n",
            "     31/100      2.27G      1.042     0.7446      1.088         37        640: 100% 107/107 [00:55<00:00,  1.94it/s]\n",
            "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100% 14/14 [00:10<00:00,  1.29it/s]\n",
            "                   all        418        716      0.814      0.802      0.847      0.578\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n",
            "     32/100      2.26G      1.022     0.7501      1.084         32        640: 100% 107/107 [00:51<00:00,  2.10it/s]\n",
            "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100% 14/14 [00:08<00:00,  1.57it/s]\n",
            "                   all        418        716       0.81      0.797      0.844      0.557\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n",
            "     33/100       2.3G      1.029     0.7392      1.076         23        640: 100% 107/107 [00:56<00:00,  1.90it/s]\n",
            "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100% 14/14 [00:07<00:00,  1.86it/s]\n",
            "                   all        418        716      0.857      0.781      0.863      0.588\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n",
            "     34/100      2.28G      1.035     0.7511       1.08         21        640: 100% 107/107 [00:55<00:00,  1.94it/s]\n",
            "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100% 14/14 [00:09<00:00,  1.47it/s]\n",
            "                   all        418        716      0.857      0.786      0.837      0.554\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n",
            "     35/100      2.27G      1.028     0.7205      1.074         25        640: 100% 107/107 [00:51<00:00,  2.08it/s]\n",
            "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100% 14/14 [00:11<00:00,  1.19it/s]\n",
            "                   all        418        716      0.821      0.839      0.861       0.59\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n",
            "     36/100      2.26G      1.031      0.733      1.066         14        640: 100% 107/107 [00:54<00:00,  1.97it/s]\n",
            "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100% 14/14 [00:08<00:00,  1.56it/s]\n",
            "                   all        418        716      0.775      0.842      0.858      0.591\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n",
            "     37/100      2.31G     0.9997     0.7134      1.055         20        640: 100% 107/107 [00:55<00:00,  1.93it/s]\n",
            "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100% 14/14 [00:07<00:00,  1.94it/s]\n",
            "                   all        418        716      0.851      0.802      0.874      0.576\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n",
            "     38/100       2.3G      1.017     0.7042       1.08         16        640: 100% 107/107 [00:56<00:00,  1.91it/s]\n",
            "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100% 14/14 [00:09<00:00,  1.51it/s]\n",
            "                   all        418        716      0.824      0.809      0.864      0.573\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n",
            "     39/100      2.27G      1.004      0.694      1.068         15        640: 100% 107/107 [00:52<00:00,  2.04it/s]\n",
            "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100% 14/14 [00:11<00:00,  1.23it/s]\n",
            "                   all        418        716      0.827      0.793       0.85      0.575\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n",
            "     40/100       2.3G     0.9961     0.6932      1.058         21        640: 100% 107/107 [00:54<00:00,  1.98it/s]\n",
            "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100% 14/14 [00:08<00:00,  1.64it/s]\n",
            "                   all        418        716      0.774      0.836      0.842      0.583\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n",
            "     41/100       2.3G     0.9959     0.7046      1.056         22        640: 100% 107/107 [00:55<00:00,  1.92it/s]\n",
            "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100% 14/14 [00:07<00:00,  1.95it/s]\n",
            "                   all        418        716      0.819      0.805      0.856      0.573\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n",
            "     42/100      2.26G      0.982      0.676      1.055         23        640: 100% 107/107 [00:55<00:00,  1.91it/s]\n",
            "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100% 14/14 [00:09<00:00,  1.54it/s]\n",
            "                   all        418        716      0.809       0.81      0.851      0.586\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n",
            "     43/100      2.29G      0.976      0.671      1.053         13        640: 100% 107/107 [00:52<00:00,  2.02it/s]\n",
            "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100% 14/14 [00:11<00:00,  1.22it/s]\n",
            "                   all        418        716      0.805      0.808      0.855      0.586\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n",
            "     44/100      2.26G     0.9759     0.6729      1.052         25        640: 100% 107/107 [00:53<00:00,  2.02it/s]\n",
            "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100% 14/14 [00:09<00:00,  1.42it/s]\n",
            "                   all        418        716      0.829      0.801      0.868      0.595\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n",
            "     45/100      2.18G     0.9822     0.6868      1.052         31        640: 100% 107/107 [00:55<00:00,  1.94it/s]\n",
            "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100% 14/14 [00:06<00:00,  2.01it/s]\n",
            "                   all        418        716      0.839      0.804      0.867      0.602\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n",
            "     46/100      2.28G     0.9759     0.6764      1.052         27        640: 100% 107/107 [00:55<00:00,  1.93it/s]\n",
            "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100% 14/14 [00:07<00:00,  1.91it/s]\n",
            "                   all        418        716      0.823      0.835      0.883      0.607\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n",
            "     47/100      2.29G     0.9803     0.6624      1.044         25        640: 100% 107/107 [00:55<00:00,  1.93it/s]\n",
            "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100% 14/14 [00:09<00:00,  1.47it/s]\n",
            "                   all        418        716      0.784      0.815      0.849      0.596\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n",
            "     48/100      2.26G     0.9502     0.6511      1.034         20        640: 100% 107/107 [00:52<00:00,  2.05it/s]\n",
            "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100% 14/14 [00:09<00:00,  1.40it/s]\n",
            "                   all        418        716      0.792       0.85       0.89      0.609\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n",
            "     49/100      2.26G     0.9671     0.6516       1.04         21        640: 100% 107/107 [00:55<00:00,  1.93it/s]\n",
            "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100% 14/14 [00:07<00:00,  1.89it/s]\n",
            "                   all        418        716      0.845      0.808      0.866        0.6\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n",
            "     50/100       2.3G     0.9656     0.6415      1.033         28        640: 100% 107/107 [00:55<00:00,  1.94it/s]\n",
            "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100% 14/14 [00:07<00:00,  1.99it/s]\n",
            "                   all        418        716      0.833      0.807      0.868      0.611\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n",
            "     51/100      2.25G     0.9675     0.6528      1.039         20        640: 100% 107/107 [00:55<00:00,  1.92it/s]\n",
            "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100% 14/14 [00:10<00:00,  1.39it/s]\n",
            "                   all        418        716      0.845      0.819      0.866      0.595\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n",
            "     52/100       2.3G     0.9475     0.6413      1.037         13        640: 100% 107/107 [00:51<00:00,  2.09it/s]\n",
            "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100% 14/14 [00:11<00:00,  1.20it/s]\n",
            "                   all        418        716      0.826      0.819      0.874      0.598\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n",
            "     53/100       2.3G     0.9559     0.6268      1.032         22        640: 100% 107/107 [00:53<00:00,  1.99it/s]\n",
            "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100% 14/14 [00:09<00:00,  1.55it/s]\n",
            "                   all        418        716      0.826      0.844      0.872      0.593\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n",
            "     54/100      2.26G     0.9429     0.6277      1.031         23        640: 100% 107/107 [00:54<00:00,  1.97it/s]\n",
            "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100% 14/14 [00:07<00:00,  1.98it/s]\n",
            "                   all        418        716      0.809      0.826      0.873      0.591\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n",
            "     55/100      2.27G     0.9417     0.6173      1.027         27        640: 100% 107/107 [00:55<00:00,  1.92it/s]\n",
            "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100% 14/14 [00:08<00:00,  1.70it/s]\n",
            "                   all        418        716      0.829      0.849      0.889      0.622\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n",
            "     56/100      2.28G     0.9274      0.615      1.027         26        640: 100% 107/107 [00:55<00:00,  1.94it/s]\n",
            "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100% 14/14 [00:11<00:00,  1.21it/s]\n",
            "                   all        418        716      0.826      0.848      0.871        0.6\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n",
            "     57/100      2.26G     0.9383      0.615      1.025         20        640: 100% 107/107 [00:53<00:00,  1.99it/s]\n",
            "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100% 14/14 [00:09<00:00,  1.40it/s]\n",
            "                   all        418        716      0.828      0.854      0.891      0.609\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n",
            "     58/100      2.26G     0.9228     0.6102      1.018         32        640: 100% 107/107 [00:56<00:00,  1.90it/s]\n",
            "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100% 14/14 [00:07<00:00,  1.99it/s]\n",
            "                   all        418        716       0.81      0.861      0.882      0.614\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n",
            "     59/100      2.27G     0.9424     0.6163       1.03         20        640: 100% 107/107 [00:55<00:00,  1.92it/s]\n",
            "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100% 14/14 [00:08<00:00,  1.71it/s]\n",
            "                   all        418        716      0.829      0.833      0.876      0.617\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n",
            "     60/100      2.26G     0.9175      0.604      1.015         34        640: 100% 107/107 [00:55<00:00,  1.94it/s]\n",
            "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100% 14/14 [00:11<00:00,  1.27it/s]\n",
            "                   all        418        716      0.835      0.834      0.889      0.614\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n",
            "     61/100      2.28G     0.9071     0.5919      1.009         40        640: 100% 107/107 [00:53<00:00,  2.01it/s]\n",
            "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100% 14/14 [00:10<00:00,  1.33it/s]\n",
            "                   all        418        716      0.844      0.827      0.885      0.622\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n",
            "     62/100      2.26G     0.8989     0.5914      1.015         20        640: 100% 107/107 [00:56<00:00,  1.89it/s]\n",
            "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100% 14/14 [00:06<00:00,  2.03it/s]\n",
            "                   all        418        716      0.826      0.859      0.894      0.623\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n",
            "     63/100      2.25G     0.9201     0.5924      1.018         20        640: 100% 107/107 [00:57<00:00,  1.87it/s]\n",
            "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100% 14/14 [00:07<00:00,  1.91it/s]\n",
            "                   all        418        716      0.855      0.839      0.889      0.616\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n",
            "     64/100      2.26G     0.9149     0.5853      1.011         31        640: 100% 107/107 [00:55<00:00,  1.94it/s]\n",
            "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100% 14/14 [00:10<00:00,  1.28it/s]\n",
            "                   all        418        716      0.815      0.861      0.886      0.615\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n",
            "     65/100      2.28G     0.9066     0.5853      1.015         18        640: 100% 107/107 [00:52<00:00,  2.04it/s]\n",
            "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100% 14/14 [00:10<00:00,  1.33it/s]\n",
            "                   all        418        716       0.84       0.83      0.876      0.605\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n",
            "     66/100      2.26G     0.9171     0.5934      1.013         27        640: 100% 107/107 [00:56<00:00,  1.91it/s]\n",
            "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100% 14/14 [00:07<00:00,  1.90it/s]\n",
            "                   all        418        716      0.817      0.854      0.884      0.622\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n",
            "     67/100      2.29G     0.9018     0.5763      1.007         25        640: 100% 107/107 [00:54<00:00,  1.96it/s]\n",
            "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100% 14/14 [00:08<00:00,  1.61it/s]\n",
            "                   all        418        716      0.836      0.853      0.888      0.618\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n",
            "     68/100       2.3G     0.8935     0.5765      1.004         20        640: 100% 107/107 [00:52<00:00,  2.02it/s]\n",
            "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100% 14/14 [00:11<00:00,  1.25it/s]\n",
            "                   all        418        716       0.83      0.867      0.885      0.617\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n",
            "     69/100      2.31G     0.8891     0.5676     0.9991         17        640: 100% 107/107 [00:53<00:00,  2.02it/s]\n",
            "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100% 14/14 [00:09<00:00,  1.51it/s]\n",
            "                   all        418        716      0.843      0.841      0.885      0.618\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n",
            "     70/100      2.28G     0.8879     0.5578      1.006         35        640: 100% 107/107 [00:55<00:00,  1.93it/s]\n",
            "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100% 14/14 [00:07<00:00,  1.92it/s]\n",
            "                   all        418        716      0.846       0.83      0.879      0.619\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n",
            "     71/100      2.29G     0.8867     0.5644      0.997         23        640: 100% 107/107 [00:54<00:00,  1.96it/s]\n",
            "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100% 14/14 [00:09<00:00,  1.41it/s]\n",
            "                   all        418        716      0.836      0.864      0.894      0.629\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n",
            "     72/100      2.31G     0.9016     0.5683      1.002         21        640: 100% 107/107 [00:52<00:00,  2.05it/s]\n",
            "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100% 14/14 [00:10<00:00,  1.27it/s]\n",
            "                   all        418        716      0.816      0.872      0.886       0.62\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n",
            "     73/100      2.26G     0.8746     0.5568      1.002         29        640: 100% 107/107 [00:54<00:00,  1.96it/s]\n",
            "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100% 14/14 [00:08<00:00,  1.71it/s]\n",
            "                   all        418        716       0.84      0.837      0.888      0.622\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n",
            "     74/100       2.3G     0.8762     0.5445     0.9967         20        640: 100% 107/107 [00:55<00:00,  1.92it/s]\n",
            "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100% 14/14 [00:07<00:00,  2.00it/s]\n",
            "                   all        418        716      0.797      0.847      0.873      0.616\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n",
            "     75/100      2.27G     0.8585     0.5563      1.004         24        640: 100% 107/107 [00:56<00:00,  1.90it/s]\n",
            "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100% 14/14 [00:08<00:00,  1.67it/s]\n",
            "                   all        418        716      0.835      0.832      0.886      0.633\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n",
            "     76/100      2.28G      0.859     0.5411     0.9908         20        640: 100% 107/107 [00:56<00:00,  1.89it/s]\n",
            "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100% 14/14 [00:13<00:00,  1.05it/s]\n",
            "                   all        418        716       0.83      0.828       0.88      0.622\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n",
            "     77/100       2.3G     0.8746     0.5449      1.001         17        640: 100% 107/107 [00:53<00:00,  2.02it/s]\n",
            "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100% 14/14 [00:08<00:00,  1.67it/s]\n",
            "                   all        418        716      0.851      0.826      0.889      0.633\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n",
            "     78/100      2.31G     0.8572     0.5281     0.9958         15        640: 100% 107/107 [00:56<00:00,  1.90it/s]\n",
            "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100% 14/14 [00:06<00:00,  2.03it/s]\n",
            "                   all        418        716      0.852      0.831       0.89      0.629\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n",
            "     79/100      2.27G      0.853     0.5196     0.9885         26        640: 100% 107/107 [00:54<00:00,  1.95it/s]\n",
            "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100% 14/14 [00:10<00:00,  1.38it/s]\n",
            "                   all        418        716       0.81      0.876      0.885      0.615\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n",
            "     80/100       2.3G     0.8642     0.5311     0.9829         34        640: 100% 107/107 [00:53<00:00,  2.01it/s]\n",
            "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100% 14/14 [00:11<00:00,  1.26it/s]\n",
            "                   all        418        716      0.837      0.852       0.89      0.632\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n",
            "     81/100      2.28G     0.8454     0.5223     0.9786         15        640: 100% 107/107 [00:54<00:00,  1.95it/s]\n",
            "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100% 14/14 [00:09<00:00,  1.49it/s]\n",
            "                   all        418        716      0.805      0.873      0.885       0.61\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n",
            "     82/100       2.3G     0.8511     0.5261     0.9807         16        640: 100% 107/107 [00:56<00:00,  1.90it/s]\n",
            "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100% 14/14 [00:06<00:00,  2.01it/s]\n",
            "                   all        418        716      0.844      0.837      0.882      0.627\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n",
            "     83/100      2.29G     0.8281     0.5144     0.9899         19        640: 100% 107/107 [00:56<00:00,  1.88it/s]\n",
            "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100% 14/14 [00:07<00:00,  1.76it/s]\n",
            "                   all        418        716      0.827      0.856       0.88      0.622\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n",
            "     84/100      2.28G     0.8388     0.5082     0.9838         23        640: 100% 107/107 [00:53<00:00,  2.00it/s]\n",
            "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100% 14/14 [00:10<00:00,  1.29it/s]\n",
            "                   all        418        716      0.829      0.863      0.887      0.632\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n",
            "     85/100      2.28G     0.8309     0.5092     0.9813         27        640: 100% 107/107 [00:52<00:00,  2.04it/s]\n",
            "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100% 14/14 [00:09<00:00,  1.49it/s]\n",
            "                   all        418        716       0.84      0.839      0.878       0.62\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n",
            "     86/100       2.3G     0.8386      0.513     0.9825         14        640: 100% 107/107 [00:57<00:00,  1.86it/s]\n",
            "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100% 14/14 [00:07<00:00,  1.98it/s]\n",
            "                   all        418        716      0.806      0.883      0.882       0.62\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n",
            "     87/100      2.25G     0.8235     0.5169     0.9799         23        640: 100% 107/107 [00:56<00:00,  1.90it/s]\n",
            "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100% 14/14 [00:07<00:00,  1.89it/s]\n",
            "                   all        418        716      0.828      0.864      0.881      0.618\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n",
            "     88/100      2.28G     0.8151     0.4958     0.9753         40        640: 100% 107/107 [00:55<00:00,  1.93it/s]\n",
            "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100% 14/14 [00:10<00:00,  1.33it/s]\n",
            "                   all        418        716      0.797      0.855      0.881      0.623\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n",
            "     89/100       2.3G     0.8174     0.5007     0.9725         23        640: 100% 107/107 [00:52<00:00,  2.05it/s]\n",
            "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100% 14/14 [00:11<00:00,  1.21it/s]\n",
            "                   all        418        716      0.818      0.848      0.884      0.626\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n",
            "     90/100      2.26G     0.8273     0.5025     0.9759         20        640: 100% 107/107 [00:55<00:00,  1.93it/s]\n",
            "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100% 14/14 [00:08<00:00,  1.68it/s]\n",
            "                   all        418        716      0.821      0.849      0.885      0.625\n",
            "Closing dataloader mosaic\n",
            "\u001b[34m\u001b[1malbumentations: \u001b[0mBlur(p=0.01, blur_limit=(3, 7)), MedianBlur(p=0.01, blur_limit=(3, 7)), ToGray(p=0.01), CLAHE(p=0.01, clip_limit=(1, 4.0), tile_grid_size=(8, 8))\n",
            "/usr/lib/python3.10/multiprocessing/popen_fork.py:66: RuntimeWarning: os.fork() was called. os.fork() is incompatible with multithreaded code, and JAX is multithreaded, so this will likely lead to a deadlock.\n",
            "  self.pid = os.fork()\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n",
            "     91/100      2.42G     0.7979     0.4513     0.9627         11        640: 100% 107/107 [00:56<00:00,  1.88it/s]\n",
            "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100% 14/14 [00:08<00:00,  1.70it/s]\n",
            "                   all        418        716      0.833      0.857      0.896      0.633\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n",
            "     92/100      2.28G     0.7717     0.4238     0.9443         10        640: 100% 107/107 [00:52<00:00,  2.06it/s]\n",
            "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100% 14/14 [00:10<00:00,  1.28it/s]\n",
            "                   all        418        716      0.844      0.825      0.891      0.628\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n",
            "     93/100      2.26G      0.776     0.4251     0.9475         17        640: 100% 107/107 [00:51<00:00,  2.09it/s]\n",
            "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100% 14/14 [00:10<00:00,  1.29it/s]\n",
            "                   all        418        716      0.828      0.847      0.888      0.629\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n",
            "     94/100      2.26G     0.7758     0.4199     0.9425         27        640: 100% 107/107 [00:52<00:00,  2.05it/s]\n",
            "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100% 14/14 [00:09<00:00,  1.50it/s]\n",
            "                   all        418        716      0.853      0.829      0.894      0.629\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n",
            "     95/100      2.25G      0.773     0.4362     0.9479         14        640: 100% 107/107 [00:55<00:00,  1.93it/s]\n",
            "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100% 14/14 [00:08<00:00,  1.71it/s]\n",
            "                   all        418        716      0.843      0.849      0.894      0.636\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n",
            "     96/100      2.26G     0.7711     0.4176     0.9456         27        640: 100% 107/107 [00:56<00:00,  1.91it/s]\n",
            "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100% 14/14 [00:07<00:00,  1.96it/s]\n",
            "                   all        418        716      0.843      0.853      0.888      0.627\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n",
            "     97/100      2.26G     0.7647     0.4217     0.9476         18        640: 100% 107/107 [00:54<00:00,  1.95it/s]\n",
            "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100% 14/14 [00:07<00:00,  1.97it/s]\n",
            "                   all        418        716       0.83      0.857      0.888      0.622\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n",
            "     98/100      2.28G     0.7534     0.4163     0.9351         16        640: 100% 107/107 [00:54<00:00,  1.96it/s]\n",
            "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100% 14/14 [00:08<00:00,  1.62it/s]\n",
            "                   all        418        716      0.859      0.826      0.886      0.625\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n",
            "     99/100      2.25G     0.7513     0.4119     0.9284         31        640: 100% 107/107 [00:51<00:00,  2.06it/s]\n",
            "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100% 14/14 [00:11<00:00,  1.20it/s]\n",
            "                   all        418        716      0.864      0.822      0.887      0.626\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n",
            "    100/100      2.26G     0.7452     0.4031     0.9314         39        640: 100% 107/107 [00:51<00:00,  2.09it/s]\n",
            "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100% 14/14 [00:10<00:00,  1.28it/s]\n",
            "                   all        418        716      0.844      0.845      0.888      0.628\n",
            "\n",
            "100 epochs completed in 1.820 hours.\n",
            "Optimizer stripped from runs/detect/train/weights/last.pt, 6.3MB\n",
            "Optimizer stripped from runs/detect/train/weights/best.pt, 6.3MB\n",
            "\n",
            "Validating runs/detect/train/weights/best.pt...\n",
            "Ultralytics YOLOv8.2.58 🚀 Python-3.10.12 torch-2.3.0+cu121 CUDA:0 (Tesla T4, 15102MiB)\n",
            "Model summary (fused): 168 layers, 3,006,038 parameters, 0 gradients, 8.1 GFLOPs\n",
            "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100% 14/14 [00:12<00:00,  1.11it/s]\n",
            "                   all        418        716      0.836      0.856      0.893      0.636\n",
            "             coca-cola        250        508      0.822      0.917      0.923      0.695\n",
            "                 pepsi        100        208      0.851      0.794      0.864      0.577\n",
            "Speed: 0.6ms preprocess, 3.5ms inference, 0.0ms loss, 5.0ms postprocess per image\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "💡 Learn more at https://docs.ultralytics.com/modes/train\n"
          ]
        }
      ]
    }
  ]
}