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lordofthejars/trainingpassports.ipynb

Created May 26, 2024 06:01
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trainingpassports.ipynb
{
"nbformat": 4,
"nbformat_minor": 0,
"metadata": {
"colab": {
"provenance": []
},
"kernelspec": {
"name": "python3",
"display_name": "Python 3"
},
"language_info": {
"name": "python"
}
},
"cells": [
{
"cell_type": "markdown",
"source": [
"Install YOLO 8"
],
"metadata": {
"id": "OOSM_yYz73R0"
}
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/"
},
"id": "QE28CkwI7F_a",
"outputId": "9dc280e3-e7e8-48ab-e08a-56d9e8b25bda"
},
"outputs": [
{
"output_type": "stream",
"name": "stdout",
"text": [
"Collecting ultralytics\n",
" Downloading ultralytics-8.2.22-py3-none-any.whl (778 kB)\n",
"\u001b[2K \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m778.4/778.4 kB\u001b[0m \u001b[31m5.6 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
"\u001b[?25hRequirement already satisfied: matplotlib>=3.3.0 in /usr/local/lib/python3.10/dist-packages (from ultralytics) (3.7.1)\n",
"Requirement already satisfied: opencv-python>=4.6.0 in /usr/local/lib/python3.10/dist-packages (from ultralytics) (4.8.0.76)\n",
"Requirement already satisfied: pillow>=7.1.2 in /usr/local/lib/python3.10/dist-packages (from ultralytics) (9.4.0)\n",
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"Requirement already satisfied: requests>=2.23.0 in /usr/local/lib/python3.10/dist-packages (from ultralytics) (2.31.0)\n",
"Requirement already satisfied: scipy>=1.4.1 in /usr/local/lib/python3.10/dist-packages (from ultralytics) (1.11.4)\n",
"Requirement already satisfied: torch>=1.8.0 in /usr/local/lib/python3.10/dist-packages (from ultralytics) (2.3.0+cu121)\n",
"Requirement already satisfied: torchvision>=0.9.0 in /usr/local/lib/python3.10/dist-packages (from ultralytics) (0.18.0+cu121)\n",
"Requirement already satisfied: tqdm>=4.64.0 in /usr/local/lib/python3.10/dist-packages (from ultralytics) (4.66.4)\n",
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"Requirement already satisfied: py-cpuinfo in /usr/local/lib/python3.10/dist-packages (from ultralytics) (9.0.0)\n",
"Collecting thop>=0.1.1 (from ultralytics)\n",
" Downloading thop-0.1.1.post2209072238-py3-none-any.whl (15 kB)\n",
"Requirement already satisfied: pandas>=1.1.4 in /usr/local/lib/python3.10/dist-packages (from ultralytics) (2.0.3)\n",
"Requirement already satisfied: seaborn>=0.11.0 in /usr/local/lib/python3.10/dist-packages (from ultralytics) (0.13.1)\n",
"Requirement already satisfied: contourpy>=1.0.1 in /usr/local/lib/python3.10/dist-packages (from matplotlib>=3.3.0->ultralytics) (1.2.1)\n",
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"Requirement already satisfied: fonttools>=4.22.0 in /usr/local/lib/python3.10/dist-packages (from matplotlib>=3.3.0->ultralytics) (4.51.0)\n",
"Requirement already satisfied: kiwisolver>=1.0.1 in /usr/local/lib/python3.10/dist-packages (from matplotlib>=3.3.0->ultralytics) (1.4.5)\n",
"Requirement already satisfied: numpy>=1.20 in /usr/local/lib/python3.10/dist-packages (from matplotlib>=3.3.0->ultralytics) (1.25.2)\n",
"Requirement already satisfied: packaging>=20.0 in /usr/local/lib/python3.10/dist-packages (from matplotlib>=3.3.0->ultralytics) (24.0)\n",
"Requirement already satisfied: pyparsing>=2.3.1 in /usr/local/lib/python3.10/dist-packages (from matplotlib>=3.3.0->ultralytics) (3.1.2)\n",
"Requirement already satisfied: python-dateutil>=2.7 in /usr/local/lib/python3.10/dist-packages (from matplotlib>=3.3.0->ultralytics) (2.8.2)\n",
"Requirement already satisfied: pytz>=2020.1 in /usr/local/lib/python3.10/dist-packages (from pandas>=1.1.4->ultralytics) (2023.4)\n",
"Requirement already satisfied: tzdata>=2022.1 in /usr/local/lib/python3.10/dist-packages (from pandas>=1.1.4->ultralytics) (2024.1)\n",
"Requirement already satisfied: charset-normalizer<4,>=2 in /usr/local/lib/python3.10/dist-packages (from requests>=2.23.0->ultralytics) (3.3.2)\n",
"Requirement already satisfied: idna<4,>=2.5 in /usr/local/lib/python3.10/dist-packages (from requests>=2.23.0->ultralytics) (3.7)\n",
"Requirement already satisfied: urllib3<3,>=1.21.1 in /usr/local/lib/python3.10/dist-packages (from requests>=2.23.0->ultralytics) (2.0.7)\n",
"Requirement already satisfied: certifi>=2017.4.17 in /usr/local/lib/python3.10/dist-packages (from requests>=2.23.0->ultralytics) (2024.2.2)\n",
"Requirement already satisfied: filelock in /usr/local/lib/python3.10/dist-packages (from torch>=1.8.0->ultralytics) (3.14.0)\n",
"Requirement already satisfied: typing-extensions>=4.8.0 in /usr/local/lib/python3.10/dist-packages (from torch>=1.8.0->ultralytics) (4.11.0)\n",
"Requirement already satisfied: sympy in /usr/local/lib/python3.10/dist-packages (from torch>=1.8.0->ultralytics) (1.12)\n",
"Requirement already satisfied: networkx in /usr/local/lib/python3.10/dist-packages (from torch>=1.8.0->ultralytics) (3.3)\n",
"Requirement already satisfied: jinja2 in /usr/local/lib/python3.10/dist-packages (from torch>=1.8.0->ultralytics) (3.1.4)\n",
"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_cu12-12.5.40-py3-none-manylinux2014_x86_64.whl (21.3 MB)\n",
"\u001b[2K \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m21.3/21.3 MB\u001b[0m \u001b[31m43.5 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
"\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>=0.19 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, nvidia-cusparse-cu12, nvidia-cudnn-cu12, nvidia-cusolver-cu12, thop, ultralytics\n",
"Successfully installed nvidia-cublas-cu12-12.1.3.1 nvidia-cuda-cupti-cu12-12.1.105 nvidia-cuda-nvrtc-cu12-12.1.105 nvidia-cuda-runtime-cu12-12.1.105 nvidia-cudnn-cu12-8.9.2.26 nvidia-cufft-cu12-11.0.2.54 nvidia-curand-cu12-10.3.2.106 nvidia-cusolver-cu12-11.4.5.107 nvidia-cusparse-cu12-12.1.0.106 nvidia-nccl-cu12-2.20.5 nvidia-nvjitlink-cu12-12.5.40 nvidia-nvtx-cu12-12.1.105 thop-0.1.1.post2209072238 ultralytics-8.2.22\n"
]
}
],
"source": [
"!pip install ultralytics\n"
]
},
{
"cell_type": "markdown",
"source": [
"Extract Dataset YOLOv8 format with labels"
],
"metadata": {
"id": "tLdZfhj7DrT0"
}
},
{
"cell_type": "code",
"source": [
"!unzip PassportEntityDetection.yolov8.zip -d \"dataset\""
],
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/"
},
"collapsed": true,
"id": "m1BfUKREDMTh",
"outputId": "06c17936-0df2-4bdd-b391-e8b2d188b7e5"
},
"execution_count": null,
"outputs": [
{
"output_type": "stream",
"name": "stdout",
"text": [
"Archive: PassportEntityDetection.yolov8.zip\n",
" extracting: dataset/README.dataset.txt \n",
" extracting: dataset/README.roboflow.txt \n",
" extracting: dataset/data.yaml \n",
" creating: dataset/train/\n",
" creating: dataset/train/images/\n",
" extracting: dataset/train/images/img10_jpeg_jpg.rf.0eea45ce9c02e8df3a0512efed846ab8.jpg \n",
" extracting: dataset/train/images/img10_jpeg_jpg.rf.197a7d41ec33d4f19f8136c1d39612fa.jpg \n",
" extracting: dataset/train/images/img10_jpeg_jpg.rf.cf3e3cc45996d0c3f49d22ba8b2009a3.jpg \n",
" extracting: dataset/train/images/img11_jpeg_jpg.rf.1a405954e55fa8711892e53012d8a4ec.jpg \n",
" extracting: dataset/train/images/img11_jpeg_jpg.rf.ab59c419a9088524a3e8dc51364572c8.jpg \n",
" extracting: dataset/train/images/img11_jpeg_jpg.rf.b5cab6ea05b7357a215db89f4f996e1a.jpg \n",
" extracting: dataset/train/images/img12_jpeg_jpg.rf.79bc14aae96250eb9dc49636a7fe49c6.jpg \n",
" extracting: dataset/train/images/img12_jpeg_jpg.rf.8ce715c3beea94ed8ca191c58d095d6f.jpg \n",
" extracting: dataset/train/images/img12_jpeg_jpg.rf.8e4a67a3d3b5836dcbec1a159f0af82e.jpg \n",
" extracting: dataset/train/images/img13_jpeg_jpg.rf.67a52a8a9c4c90356e9d1be54315201d.jpg \n",
" extracting: dataset/train/images/img13_jpeg_jpg.rf.883c988bed612575f6bf80074d75198a.jpg \n",
" extracting: dataset/train/images/img13_jpeg_jpg.rf.8c8d3c5ddf61ddc9d12f6da5c53e80c7.jpg \n",
" extracting: dataset/train/images/img14_jpeg_jpg.rf.42edaae0f7d67d11f59f9334e7b9170f.jpg \n",
" extracting: dataset/train/images/img14_jpeg_jpg.rf.cdb9da99eef51b1985c1f7d2d8eb6418.jpg \n",
" extracting: dataset/train/images/img14_jpeg_jpg.rf.ffc6ba69815f42a27e684197cb9ab3ed.jpg \n",
" extracting: dataset/train/images/img15_jpeg_jpg.rf.4647e07f52b9bae97dbb7ae819407115.jpg \n",
" extracting: dataset/train/images/img15_jpeg_jpg.rf.695176ba3eb2884f159827aad823fb66.jpg \n",
" extracting: dataset/train/images/img15_jpeg_jpg.rf.c8b592a5c7c3ff4e9ccb3a349edfac34.jpg \n",
" extracting: dataset/train/images/img16_jpeg_jpg.rf.461d76d1cd01c7cb09437417f623016a.jpg \n",
" extracting: dataset/train/images/img16_jpeg_jpg.rf.8be4aea647bf306bb0e7cd40139eac8f.jpg \n",
" extracting: dataset/train/images/img16_jpeg_jpg.rf.8eba7f5ccfa014d259b0ea744c05e209.jpg \n",
" extracting: dataset/train/images/img17_jpeg_jpg.rf.23254b4d4658af1b59fd1175d766c154.jpg \n",
" extracting: dataset/train/images/img17_jpeg_jpg.rf.6a674a28bcc76bc2cd7df8523b919b4f.jpg \n",
" extracting: dataset/train/images/img17_jpeg_jpg.rf.a44ed607d0113846e4152bc8ceafa226.jpg \n",
" extracting: dataset/train/images/img18_jpeg_jpg.rf.2d014199e911d4bee27d2d1f4e6fd443.jpg \n",
" extracting: dataset/train/images/img18_jpeg_jpg.rf.e45a5459350bb72326631ccd99cf1cb0.jpg \n",
" extracting: dataset/train/images/img18_jpeg_jpg.rf.eead794638e93fdc2075f3f3400c1ffe.jpg \n",
" extracting: dataset/train/images/img19_jpeg_jpg.rf.045f7ed2c4b65d05150b3d379b8473a3.jpg \n",
" extracting: dataset/train/images/img19_jpeg_jpg.rf.9fe07b8a6e9d73303ab07b43753036b4.jpg \n",
" extracting: dataset/train/images/img19_jpeg_jpg.rf.ddfe6ac4e97879d24703283417abc5bb.jpg \n",
" extracting: dataset/train/images/img1_jpeg_jpg.rf.1eb3975eb5f2f47756f963261dae4d8e.jpg \n",
" extracting: dataset/train/images/img1_jpeg_jpg.rf.7f365354e8e0da9bc868e8509c23e6b9.jpg \n",
" extracting: dataset/train/images/img1_jpeg_jpg.rf.d6ffddf37be055acfadef363264a9e9b.jpg \n",
" extracting: dataset/train/images/img20_jpeg_jpg.rf.797573010d9a5ae37ab76be2ceebdb36.jpg \n",
" extracting: dataset/train/images/img20_jpeg_jpg.rf.c757c6fb5f72be180c76cbaa11b9fbb6.jpg \n",
" extracting: dataset/train/images/img20_jpeg_jpg.rf.d6114546d5e0abbb7492854a16ae3c1c.jpg \n",
" extracting: dataset/train/images/img23_jpeg_jpg.rf.11c9790a48297a11092cec60a33f849d.jpg \n",
" extracting: dataset/train/images/img23_jpeg_jpg.rf.6f595c098c8f7298fe8dd6cab397660d.jpg \n",
" extracting: dataset/train/images/img23_jpeg_jpg.rf.975874fe0216cd71434deb4a3bce99cd.jpg \n",
" extracting: dataset/train/images/img26_jpeg_jpg.rf.751c0fccb8df609e261f4300dec0afde.jpg \n",
" extracting: dataset/train/images/img26_jpeg_jpg.rf.9a0369b5de87e11184f4642e842632b0.jpg \n",
" extracting: dataset/train/images/img26_jpeg_jpg.rf.c4c2c3baa1336940844b94f91eeb6b9d.jpg \n",
" extracting: dataset/train/images/img27_jpeg_jpg.rf.1538cb12a53a4f16f658421e6f40b0df.jpg \n",
" extracting: dataset/train/images/img27_jpeg_jpg.rf.62fe452daca350387589924f86cd02e0.jpg \n",
" extracting: dataset/train/images/img27_jpeg_jpg.rf.a95ba5d1fc9d1f3a305e574e5d438093.jpg \n",
" extracting: dataset/train/images/img28_jpeg_jpg.rf.2039f7dd1fd3bc6329d8aef0da6e5c65.jpg \n",
" extracting: dataset/train/images/img28_jpeg_jpg.rf.707d61d899e69bf9fd7a96dabb73a8c2.jpg \n",
" extracting: dataset/train/images/img28_jpeg_jpg.rf.ae4b990b975b81ee9f371647f0c349d1.jpg \n",
" extracting: dataset/train/images/img29_jpeg_jpg.rf.43d71b193e7af5542ace1a2eb5a98ece.jpg \n",
" extracting: dataset/train/images/img29_jpeg_jpg.rf.73ff60f6b395f513db7aa2cbc7beaa85.jpg \n",
" extracting: dataset/train/images/img29_jpeg_jpg.rf.eb5aa9738214f2ae793e36f95adc996f.jpg \n",
" extracting: dataset/train/images/img2_jpeg_jpg.rf.372f5239b526564df8dce2c61ad6e2c8.jpg \n",
" extracting: dataset/train/images/img2_jpeg_jpg.rf.c3a9c75fd8fc51626189f1ddbde50147.jpg \n",
" extracting: dataset/train/images/img2_jpeg_jpg.rf.c6d6a85170ea278c226948b73a891971.jpg \n",
" extracting: dataset/train/images/img3_jpeg_jpg.rf.247a0d52eed039949a255194a38be169.jpg \n",
" extracting: dataset/train/images/img3_jpeg_jpg.rf.6bb16c85fa5f34e55676f055ae8e05a1.jpg \n",
" extracting: dataset/train/images/img3_jpeg_jpg.rf.ea94d7d95cacff0fe167f5a61e272cc7.jpg \n",
" extracting: dataset/train/images/img4_jpeg_jpg.rf.3a5a27a9b03f82af18f0af8f5bfc8e63.jpg \n",
" extracting: dataset/train/images/img4_jpeg_jpg.rf.99f30280c9db4208b170c73cae0a8500.jpg \n",
" extracting: dataset/train/images/img4_jpeg_jpg.rf.f264971ede3111f06f4ed749ff36a642.jpg \n",
" extracting: dataset/train/images/img5_jpeg_jpg.rf.2311dd0173f55c14e7fe7b333a0eb641.jpg \n",
" extracting: dataset/train/images/img5_jpeg_jpg.rf.4aceec12eb842a31bd3be60442808c88.jpg \n",
" extracting: dataset/train/images/img5_jpeg_jpg.rf.b00774a767cf15d76f733ed8ca37d2da.jpg \n",
" extracting: dataset/train/images/img6_jpeg_jpg.rf.5cc6cb22474da3939db687a566bdad7b.jpg \n",
" extracting: dataset/train/images/img6_jpeg_jpg.rf.708ac8cabd59c512609692030e64d536.jpg \n",
" extracting: dataset/train/images/img6_jpeg_jpg.rf.db2a39198c0ab0273dfa4f251c47b901.jpg \n",
" extracting: dataset/train/images/img7_jpeg_jpg.rf.01b84c422661ab4a5e7c36c0ab8c2f7d.jpg \n",
" extracting: dataset/train/images/img7_jpeg_jpg.rf.6d7af7b6997a87f3480035e0c101be9d.jpg \n",
" extracting: dataset/train/images/img7_jpeg_jpg.rf.ce0578e816ea09e044f415ededd1996a.jpg \n",
" extracting: dataset/train/images/img8_jpeg_jpg.rf.3b5e065021085b69e4c44ef818ee6120.jpg \n",
" extracting: dataset/train/images/img8_jpeg_jpg.rf.4e2c8e61747cf2f23453d5c290f03da3.jpg \n",
" extracting: dataset/train/images/img8_jpeg_jpg.rf.92c02164f16c6f97e1b1d92d8b18a0a4.jpg \n",
" extracting: dataset/train/images/img9_jpeg_jpg.rf.7e57699e50d4c546d52ee8adb15915c0.jpg \n",
" extracting: dataset/train/images/img9_jpeg_jpg.rf.a05a761a27d9c44e12b86b57f34f818e.jpg \n",
" extracting: dataset/train/images/img9_jpeg_jpg.rf.f88887fec96d28a1e926de84cb78e636.jpg \n",
" creating: dataset/train/labels/\n",
" extracting: dataset/train/labels/img10_jpeg_jpg.rf.0eea45ce9c02e8df3a0512efed846ab8.txt \n",
" extracting: dataset/train/labels/img10_jpeg_jpg.rf.197a7d41ec33d4f19f8136c1d39612fa.txt \n",
" extracting: dataset/train/labels/img10_jpeg_jpg.rf.cf3e3cc45996d0c3f49d22ba8b2009a3.txt \n",
" extracting: dataset/train/labels/img11_jpeg_jpg.rf.1a405954e55fa8711892e53012d8a4ec.txt \n",
" extracting: dataset/train/labels/img11_jpeg_jpg.rf.ab59c419a9088524a3e8dc51364572c8.txt \n",
" extracting: dataset/train/labels/img11_jpeg_jpg.rf.b5cab6ea05b7357a215db89f4f996e1a.txt \n",
" extracting: dataset/train/labels/img12_jpeg_jpg.rf.79bc14aae96250eb9dc49636a7fe49c6.txt \n",
" extracting: dataset/train/labels/img12_jpeg_jpg.rf.8ce715c3beea94ed8ca191c58d095d6f.txt \n",
" extracting: dataset/train/labels/img12_jpeg_jpg.rf.8e4a67a3d3b5836dcbec1a159f0af82e.txt \n",
" extracting: dataset/train/labels/img13_jpeg_jpg.rf.67a52a8a9c4c90356e9d1be54315201d.txt \n",
" extracting: dataset/train/labels/img13_jpeg_jpg.rf.883c988bed612575f6bf80074d75198a.txt \n",
" extracting: dataset/train/labels/img13_jpeg_jpg.rf.8c8d3c5ddf61ddc9d12f6da5c53e80c7.txt \n",
" extracting: dataset/train/labels/img14_jpeg_jpg.rf.42edaae0f7d67d11f59f9334e7b9170f.txt \n",
" extracting: dataset/train/labels/img14_jpeg_jpg.rf.cdb9da99eef51b1985c1f7d2d8eb6418.txt \n",
" extracting: dataset/train/labels/img14_jpeg_jpg.rf.ffc6ba69815f42a27e684197cb9ab3ed.txt \n",
" extracting: dataset/train/labels/img15_jpeg_jpg.rf.4647e07f52b9bae97dbb7ae819407115.txt \n",
" extracting: dataset/train/labels/img15_jpeg_jpg.rf.695176ba3eb2884f159827aad823fb66.txt \n",
" extracting: dataset/train/labels/img15_jpeg_jpg.rf.c8b592a5c7c3ff4e9ccb3a349edfac34.txt \n",
" extracting: dataset/train/labels/img16_jpeg_jpg.rf.461d76d1cd01c7cb09437417f623016a.txt \n",
" extracting: dataset/train/labels/img16_jpeg_jpg.rf.8be4aea647bf306bb0e7cd40139eac8f.txt \n",
" extracting: dataset/train/labels/img16_jpeg_jpg.rf.8eba7f5ccfa014d259b0ea744c05e209.txt \n",
" extracting: dataset/train/labels/img17_jpeg_jpg.rf.23254b4d4658af1b59fd1175d766c154.txt \n",
" extracting: dataset/train/labels/img17_jpeg_jpg.rf.6a674a28bcc76bc2cd7df8523b919b4f.txt \n",
" extracting: dataset/train/labels/img17_jpeg_jpg.rf.a44ed607d0113846e4152bc8ceafa226.txt \n",
" extracting: dataset/train/labels/img18_jpeg_jpg.rf.2d014199e911d4bee27d2d1f4e6fd443.txt \n",
" extracting: dataset/train/labels/img18_jpeg_jpg.rf.e45a5459350bb72326631ccd99cf1cb0.txt \n",
" extracting: dataset/train/labels/img18_jpeg_jpg.rf.eead794638e93fdc2075f3f3400c1ffe.txt \n",
" extracting: dataset/train/labels/img19_jpeg_jpg.rf.045f7ed2c4b65d05150b3d379b8473a3.txt \n",
" extracting: dataset/train/labels/img19_jpeg_jpg.rf.9fe07b8a6e9d73303ab07b43753036b4.txt \n",
" extracting: dataset/train/labels/img19_jpeg_jpg.rf.ddfe6ac4e97879d24703283417abc5bb.txt \n",
" extracting: dataset/train/labels/img1_jpeg_jpg.rf.1eb3975eb5f2f47756f963261dae4d8e.txt \n",
" extracting: dataset/train/labels/img1_jpeg_jpg.rf.7f365354e8e0da9bc868e8509c23e6b9.txt \n",
" extracting: dataset/train/labels/img1_jpeg_jpg.rf.d6ffddf37be055acfadef363264a9e9b.txt \n",
" extracting: dataset/train/labels/img20_jpeg_jpg.rf.797573010d9a5ae37ab76be2ceebdb36.txt \n",
" extracting: dataset/train/labels/img20_jpeg_jpg.rf.c757c6fb5f72be180c76cbaa11b9fbb6.txt \n",
" extracting: dataset/train/labels/img20_jpeg_jpg.rf.d6114546d5e0abbb7492854a16ae3c1c.txt \n",
" extracting: dataset/train/labels/img23_jpeg_jpg.rf.11c9790a48297a11092cec60a33f849d.txt \n",
" extracting: dataset/train/labels/img23_jpeg_jpg.rf.6f595c098c8f7298fe8dd6cab397660d.txt \n",
" extracting: dataset/train/labels/img23_jpeg_jpg.rf.975874fe0216cd71434deb4a3bce99cd.txt \n",
" extracting: dataset/train/labels/img26_jpeg_jpg.rf.751c0fccb8df609e261f4300dec0afde.txt \n",
" extracting: dataset/train/labels/img26_jpeg_jpg.rf.9a0369b5de87e11184f4642e842632b0.txt \n",
" extracting: dataset/train/labels/img26_jpeg_jpg.rf.c4c2c3baa1336940844b94f91eeb6b9d.txt \n",
" extracting: dataset/train/labels/img27_jpeg_jpg.rf.1538cb12a53a4f16f658421e6f40b0df.txt \n",
" extracting: dataset/train/labels/img27_jpeg_jpg.rf.62fe452daca350387589924f86cd02e0.txt \n",
" extracting: dataset/train/labels/img27_jpeg_jpg.rf.a95ba5d1fc9d1f3a305e574e5d438093.txt \n",
" extracting: dataset/train/labels/img28_jpeg_jpg.rf.2039f7dd1fd3bc6329d8aef0da6e5c65.txt \n",
" extracting: dataset/train/labels/img28_jpeg_jpg.rf.707d61d899e69bf9fd7a96dabb73a8c2.txt \n",
" extracting: dataset/train/labels/img28_jpeg_jpg.rf.ae4b990b975b81ee9f371647f0c349d1.txt \n",
" extracting: dataset/train/labels/img29_jpeg_jpg.rf.43d71b193e7af5542ace1a2eb5a98ece.txt \n",
" extracting: dataset/train/labels/img29_jpeg_jpg.rf.73ff60f6b395f513db7aa2cbc7beaa85.txt \n",
" extracting: dataset/train/labels/img29_jpeg_jpg.rf.eb5aa9738214f2ae793e36f95adc996f.txt \n",
" extracting: dataset/train/labels/img2_jpeg_jpg.rf.372f5239b526564df8dce2c61ad6e2c8.txt \n",
" extracting: dataset/train/labels/img2_jpeg_jpg.rf.c3a9c75fd8fc51626189f1ddbde50147.txt \n",
" extracting: dataset/train/labels/img2_jpeg_jpg.rf.c6d6a85170ea278c226948b73a891971.txt \n",
" extracting: dataset/train/labels/img3_jpeg_jpg.rf.247a0d52eed039949a255194a38be169.txt \n",
" extracting: dataset/train/labels/img3_jpeg_jpg.rf.6bb16c85fa5f34e55676f055ae8e05a1.txt \n",
" extracting: dataset/train/labels/img3_jpeg_jpg.rf.ea94d7d95cacff0fe167f5a61e272cc7.txt \n",
" extracting: dataset/train/labels/img4_jpeg_jpg.rf.3a5a27a9b03f82af18f0af8f5bfc8e63.txt \n",
" extracting: dataset/train/labels/img4_jpeg_jpg.rf.99f30280c9db4208b170c73cae0a8500.txt \n",
" extracting: dataset/train/labels/img4_jpeg_jpg.rf.f264971ede3111f06f4ed749ff36a642.txt \n",
" extracting: dataset/train/labels/img5_jpeg_jpg.rf.2311dd0173f55c14e7fe7b333a0eb641.txt \n",
" extracting: dataset/train/labels/img5_jpeg_jpg.rf.4aceec12eb842a31bd3be60442808c88.txt \n",
" extracting: dataset/train/labels/img5_jpeg_jpg.rf.b00774a767cf15d76f733ed8ca37d2da.txt \n",
" extracting: dataset/train/labels/img6_jpeg_jpg.rf.5cc6cb22474da3939db687a566bdad7b.txt \n",
" extracting: dataset/train/labels/img6_jpeg_jpg.rf.708ac8cabd59c512609692030e64d536.txt \n",
" extracting: dataset/train/labels/img6_jpeg_jpg.rf.db2a39198c0ab0273dfa4f251c47b901.txt \n",
" extracting: dataset/train/labels/img7_jpeg_jpg.rf.01b84c422661ab4a5e7c36c0ab8c2f7d.txt \n",
" extracting: dataset/train/labels/img7_jpeg_jpg.rf.6d7af7b6997a87f3480035e0c101be9d.txt \n",
" extracting: dataset/train/labels/img7_jpeg_jpg.rf.ce0578e816ea09e044f415ededd1996a.txt \n",
" extracting: dataset/train/labels/img8_jpeg_jpg.rf.3b5e065021085b69e4c44ef818ee6120.txt \n",
" extracting: dataset/train/labels/img8_jpeg_jpg.rf.4e2c8e61747cf2f23453d5c290f03da3.txt \n",
" extracting: dataset/train/labels/img8_jpeg_jpg.rf.92c02164f16c6f97e1b1d92d8b18a0a4.txt \n",
" extracting: dataset/train/labels/img9_jpeg_jpg.rf.7e57699e50d4c546d52ee8adb15915c0.txt \n",
" extracting: dataset/train/labels/img9_jpeg_jpg.rf.a05a761a27d9c44e12b86b57f34f818e.txt \n",
" extracting: dataset/train/labels/img9_jpeg_jpg.rf.f88887fec96d28a1e926de84cb78e636.txt \n",
" creating: dataset/valid/\n",
" creating: dataset/valid/images/\n",
" extracting: dataset/valid/images/img21_jpeg_jpg.rf.e40081019927a2d2d9d61756f1d2c21e.jpg \n",
" extracting: dataset/valid/images/img24_jpeg_jpg.rf.47b927d6a89bd804b05e67b01e17ac1b.jpg \n",
" extracting: dataset/valid/images/img25_jpeg_jpg.rf.9c651ef9c4eeab15cb719f638b8723f4.jpg \n",
" creating: dataset/valid/labels/\n",
" extracting: dataset/valid/labels/img21_jpeg_jpg.rf.e40081019927a2d2d9d61756f1d2c21e.txt \n",
" extracting: dataset/valid/labels/img24_jpeg_jpg.rf.47b927d6a89bd804b05e67b01e17ac1b.txt \n",
" extracting: dataset/valid/labels/img25_jpeg_jpg.rf.9c651ef9c4eeab15cb719f638b8723f4.txt \n"
]
}
]
},
{
"cell_type": "markdown",
"source": [
"Load YOLO"
],
"metadata": {
"id": "lgx5NqVXD46w"
}
},
{
"cell_type": "code",
"source": [
"import os\n",
"import sys\n",
"\n",
"# main code to run YOLO training\n",
"from ultralytics import YOLO\n",
"\n",
"model = YOLO(\"yolov8n.pt\") # load a pretrained model (recommended for training)\n"
],
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/"
},
"id": "-Kjpf3hrD66A",
"outputId": "2358f478-cb2a-44f6-ebaa-651014834450"
},
"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"
]
},
{
"output_type": "stream",
"name": "stderr",
"text": [
"100%|██████████| 6.23M/6.23M [00:00<00:00, 70.6MB/s]\n"
]
}
]
},
{
"cell_type": "markdown",
"source": [
"Train Model"
],
"metadata": {
"id": "J62Y9xv5Ejkd"
}
},
{
"cell_type": "code",
"source": [
"# Use the model\n",
"results = model.train(data=\"./dataset/data.yaml\", epochs=150, pretrained=True, iou=0.5, visualize=True, patience=0) # train the model"
],
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/"
},
"id": "sS5oOhzBElPP",
"outputId": "1836e633-f9e9-45fe-9451-46bdeeda30f8"
},
"execution_count": null,
"outputs": [
{
"output_type": "stream",
"name": "stdout",
"text": [
"Ultralytics YOLOv8.2.22 🚀 Python-3.10.12 torch-2.3.0+cu121 CPU (Intel Xeon 2.20GHz)\n",
"\u001b[34m\u001b[1mengine/trainer: \u001b[0mtask=detect, mode=train, model=yolov8n.pt, data=./dataset/data.yaml, epochs=150, time=None, patience=0, batch=16, imgsz=640, save=True, save_period=-1, cache=False, device=None, workers=8, project=None, name=train9, 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=0.5, max_det=300, half=False, dnn=False, plots=True, source=None, vid_stride=1, stream_buffer=False, visualize=True, 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/train9\n",
"Downloading https://ultralytics.com/assets/Arial.ttf to '/root/.config/Ultralytics/Arial.ttf'...\n"
]
},
{
"output_type": "stream",
"name": "stderr",
"text": [
"100%|██████████| 755k/755k [00:00<00:00, 14.8MB/s]\n"
]
},
{
"output_type": "stream",
"name": "stdout",
"text": [
"Overriding model.yaml nc=80 with nc=15\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 754237 ultralytics.nn.modules.head.Detect [15, [64, 128, 256]] \n",
"Model summary: 225 layers, 3013773 parameters, 3013757 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/train9', view at http://localhost:6006/\n",
"Freezing layer 'model.22.dfl.conv.weight'\n"
]
},
{
"output_type": "stream",
"name": "stderr",
"text": [
"\u001b[34m\u001b[1mtrain: \u001b[0mScanning /content/dataset/train/labels... 75 images, 0 backgrounds, 0 corrupt: 100%|██████████| 75/75 [00:00<00:00, 1054.37it/s]"
]
},
{
"output_type": "stream",
"name": "stdout",
"text": [
"\u001b[34m\u001b[1mtrain: \u001b[0mNew cache created: /content/dataset/train/labels.cache\n"
]
},
{
"output_type": "stream",
"name": "stderr",
"text": [
"\n"
]
},
{
"output_type": "stream",
"name": "stdout",
"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), CLAHE(p=0.01, clip_limit=(1, 4.0), tile_grid_size=(8, 8))\n"
]
},
{
"output_type": "stream",
"name": "stderr",
"text": [
"\u001b[34m\u001b[1mval: \u001b[0mScanning /content/dataset/valid/labels... 3 images, 0 backgrounds, 0 corrupt: 100%|██████████| 3/3 [00:00<00:00, 3420.20it/s]"
]
},
{
"output_type": "stream",
"name": "stdout",
"text": [
"\u001b[34m\u001b[1mval: \u001b[0mNew cache created: /content/dataset/valid/labels.cache\n"
]
},
{
"output_type": "stream",
"name": "stderr",
"text": [
"\n"
]
},
{
"output_type": "stream",
"name": "stdout",
"text": [
"Plotting labels to runs/detect/train9/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=0.000526, 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 0 dataloader workers\n",
"Logging results to \u001b[1mruns/detect/train9\u001b[0m\n",
"Starting training for 150 epochs...\n",
"\n",
" Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size\n"
]
},
{
"output_type": "stream",
"name": "stderr",
"text": [
" 1/150 0G 2.483 4.441 2.039 233 640: 100%|██████████| 5/5 [01:27<00:00, 17.41s/it]\n",
" Class Images Instances Box(P R mAP50 mAP50-95): 100%|██████████| 1/1 [00:01<00:00, 1.14s/it]"
]
},
{
"output_type": "stream",
"name": "stdout",
"text": [
" all 3 45 0 0 0 0\n"
]
},
{
"output_type": "stream",
"name": "stderr",
"text": [
"\n"
]
},
{
"output_type": "stream",
"name": "stdout",
"text": [
"\n",
" Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size\n"
]
},
{
"output_type": "stream",
"name": "stderr",
"text": [
" 2/150 0G 2.371 4.431 1.914 278 640: 100%|██████████| 5/5 [01:08<00:00, 13.68s/it]\n",
" Class Images Instances Box(P R mAP50 mAP50-95): 100%|██████████| 1/1 [00:01<00:00, 1.33s/it]"
]
},
{
"output_type": "stream",
"name": "stdout",
"text": [
" all 3 45 0 0 0 0\n"
]
},
{
"output_type": "stream",
"name": "stderr",
"text": [
"\n"
]
},
{
"output_type": "stream",
"name": "stdout",
"text": [
"\n",
" Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size\n"
]
},
{
"output_type": "stream",
"name": "stderr",
"text": [
" 3/150 0G 2.184 4.341 1.802 270 640: 100%|██████████| 5/5 [01:07<00:00, 13.58s/it]\n",
" Class Images Instances Box(P R mAP50 mAP50-95): 100%|██████████| 1/1 [00:00<00:00, 1.16it/s]"
]
},
{
"output_type": "stream",
"name": "stdout",
"text": [
" all 3 45 0.0267 0.0444 0.0267 0.0173\n"
]
},
{
"output_type": "stream",
"name": "stderr",
"text": [
"\n"
]
},
{
"output_type": "stream",
"name": "stdout",
"text": [
"\n",
" Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size\n"
]
},
{
"output_type": "stream",
"name": "stderr",
"text": [
" 4/150 0G 2.034 4.21 1.69 252 640: 100%|██████████| 5/5 [01:08<00:00, 13.66s/it]\n",
" Class Images Instances Box(P R mAP50 mAP50-95): 100%|██████████| 1/1 [00:01<00:00, 1.41s/it]"
]
},
{
"output_type": "stream",
"name": "stdout",
"text": [
" all 3 45 0.048 0.133 0.0958 0.068\n"
]
},
{
"output_type": "stream",
"name": "stderr",
"text": [
"\n"
]
},
{
"output_type": "stream",
"name": "stdout",
"text": [
"\n",
" Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size\n"
]
},
{
"output_type": "stream",
"name": "stderr",
"text": [
" 5/150 0G 1.967 4.112 1.646 266 640: 100%|██████████| 5/5 [01:05<00:00, 13.18s/it]\n",
" Class Images Instances Box(P R mAP50 mAP50-95): 100%|██████████| 1/1 [00:00<00:00, 1.09it/s]"
]
},
{
"output_type": "stream",
"name": "stdout",
"text": [
" all 3 45 0.0398 0.2 0.144 0.0875\n"
]
},
{
"output_type": "stream",
"name": "stderr",
"text": [
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"output_type": "stream",
"name": "stderr",
"text": [
" 147/150 0G 1.016 0.741 1.084 165 640: 100%|██████████| 5/5 [01:02<00:00, 12.42s/it]\n",
" Class Images Instances Box(P R mAP50 mAP50-95): 100%|██████████| 1/1 [00:00<00:00, 1.18it/s]"
]
},
{
"output_type": "stream",
"name": "stdout",
"text": [
" all 3 45 0.813 0.936 0.962 0.607\n"
]
},
{
"output_type": "stream",
"name": "stderr",
"text": [
"\n"
]
},
{
"output_type": "stream",
"name": "stdout",
"text": [
"\n",
" Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size\n"
]
},
{
"output_type": "stream",
"name": "stderr",
"text": [
" 148/150 0G 1.02 0.747 1.098 165 640: 100%|██████████| 5/5 [01:03<00:00, 12.64s/it]\n",
" Class Images Instances Box(P R mAP50 mAP50-95): 100%|██████████| 1/1 [00:00<00:00, 1.15it/s]"
]
},
{
"output_type": "stream",
"name": "stdout",
"text": [
" all 3 45 0.817 0.935 0.962 0.605\n"
]
},
{
"output_type": "stream",
"name": "stderr",
"text": [
"\n"
]
},
{
"output_type": "stream",
"name": "stdout",
"text": [
"\n",
" Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size\n"
]
},
{
"output_type": "stream",
"name": "stderr",
"text": [
" 149/150 0G 1.036 0.7524 1.121 165 640: 100%|██████████| 5/5 [01:02<00:00, 12.43s/it]\n",
" Class Images Instances Box(P R mAP50 mAP50-95): 100%|██████████| 1/1 [00:01<00:00, 1.02s/it]"
]
},
{
"output_type": "stream",
"name": "stdout",
"text": [
" all 3 45 0.818 0.935 0.966 0.608\n"
]
},
{
"output_type": "stream",
"name": "stderr",
"text": [
"\n"
]
},
{
"output_type": "stream",
"name": "stdout",
"text": [
"\n",
" Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size\n"
]
},
{
"output_type": "stream",
"name": "stderr",
"text": [
" 150/150 0G 1.036 0.7506 1.105 165 640: 100%|██████████| 5/5 [01:02<00:00, 12.52s/it]\n",
" Class Images Instances Box(P R mAP50 mAP50-95): 100%|██████████| 1/1 [00:01<00:00, 1.35s/it]"
]
},
{
"output_type": "stream",
"name": "stdout",
"text": [
" all 3 45 0.818 0.936 0.966 0.608\n"
]
},
{
"output_type": "stream",
"name": "stderr",
"text": [
"\n"
]
},
{
"output_type": "stream",
"name": "stdout",
"text": [
"\n",
"150 epochs completed in 2.796 hours.\n",
"Optimizer stripped from runs/detect/train9/weights/last.pt, 6.3MB\n",
"Optimizer stripped from runs/detect/train9/weights/best.pt, 6.3MB\n",
"\n",
"Validating runs/detect/train9/weights/best.pt...\n",
"Ultralytics YOLOv8.2.22 🚀 Python-3.10.12 torch-2.3.0+cu121 CPU (Intel Xeon 2.20GHz)\n",
"Model summary (fused): 168 layers, 3008573 parameters, 0 gradients, 8.1 GFLOPs\n"
]
},
{
"output_type": "stream",
"name": "stderr",
"text": [
" Class Images Instances Box(P R mAP50 mAP50-95): 100%|██████████| 1/1 [00:00<00:00, 1.40it/s]\n"
]
},
{
"output_type": "stream",
"name": "stdout",
"text": [
" all 3 45 0.803 0.941 0.97 0.632\n",
" 0 3 3 0.807 1 0.995 0.754\n",
" 1 3 3 0.814 1 0.995 0.533\n",
" 10 3 3 0.701 1 0.995 0.624\n",
" 11 3 3 0.904 1 0.995 0.404\n",
" 12 3 3 0.799 1 0.995 0.731\n",
" 13 3 3 1 0.459 0.995 0.579\n",
" 14 3 3 0.789 1 0.995 0.732\n",
" 2 3 3 0.804 1 0.995 0.697\n",
" 3 3 3 0.819 1 0.995 0.535\n",
" 4 3 3 0.795 1 0.995 0.814\n",
" 5 3 3 0.521 1 0.913 0.764\n",
" 6 3 3 1 0.982 0.995 0.434\n",
" 7 3 3 0.801 1 0.995 0.572\n",
" 8 3 3 0.796 1 0.995 0.895\n",
" 9 3 3 0.692 0.667 0.703 0.413\n",
"Speed: 2.4ms preprocess, 215.6ms inference, 0.0ms loss, 1.5ms postprocess per image\n",
"Results saved to \u001b[1mruns/detect/train9\u001b[0m\n"
]
}
]
},
{
"cell_type": "markdown",
"source": [
"Export Model"
],
"metadata": {
"id": "YMjMEm3EvQUD"
}
},
{
"cell_type": "code",
"source": [
"model.export(format=\"onnx\")"
],
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/",
"height": 502
},
"id": "ugwvvzq5vSVw",
"outputId": "91d193f3-bb2c-4200-ddc1-31e668fa9053"
},
"execution_count": null,
"outputs": [
{
"output_type": "stream",
"name": "stdout",
"text": [
"Ultralytics YOLOv8.2.22 🚀 Python-3.10.12 torch-2.3.0+cu121 CPU (Intel Xeon 2.20GHz)\n",
"Model summary (fused): 168 layers, 3008573 parameters, 0 gradients, 8.1 GFLOPs\n",
"\n",
"\u001b[34m\u001b[1mPyTorch:\u001b[0m starting from 'runs/detect/train9/weights/best.pt' with input shape (1, 3, 640, 640) BCHW and output shape(s) (1, 19, 8400) (6.0 MB)\n",
"\u001b[31m\u001b[1mrequirements:\u001b[0m Ultralytics requirement ['onnx>=1.12.0'] not found, attempting AutoUpdate...\n",
"Collecting onnx>=1.12.0\n",
" Downloading onnx-1.16.1-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (15.9 MB)\n",
" ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 15.9/15.9 MB 49.9 MB/s eta 0:00:00\n",
"Requirement already satisfied: numpy>=1.20 in /usr/local/lib/python3.10/dist-packages (from onnx>=1.12.0) (1.25.2)\n",
"Requirement already satisfied: protobuf>=3.20.2 in /usr/local/lib/python3.10/dist-packages (from onnx>=1.12.0) (3.20.3)\n",
"Installing collected packages: onnx\n",
"Successfully installed onnx-1.16.1\n",
"\n",
"\u001b[31m\u001b[1mrequirements:\u001b[0m AutoUpdate success ✅ 12.5s, installed 1 package: ['onnx>=1.12.0']\n",
"\u001b[31m\u001b[1mrequirements:\u001b[0m ⚠️ \u001b[1mRestart runtime or rerun command for updates to take effect\u001b[0m\n",
"\n",
"\n",
"\u001b[34m\u001b[1mONNX:\u001b[0m starting export with onnx 1.16.1 opset 17...\n",
"\u001b[34m\u001b[1mONNX:\u001b[0m export success ✅ 13.6s, saved as 'runs/detect/train9/weights/best.onnx' (11.7 MB)\n",
"\n",
"Export complete (15.4s)\n",
"Results saved to \u001b[1m/content/runs/detect/train9/weights\u001b[0m\n",
"Predict: yolo predict task=detect model=runs/detect/train9/weights/best.onnx imgsz=640 \n",
"Validate: yolo val task=detect model=runs/detect/train9/weights/best.onnx imgsz=640 data=./dataset/data.yaml \n",
"Visualize: https://netron.app\n"
]
},
{
"output_type": "execute_result",
"data": {
"text/plain": [
"'runs/detect/train9/weights/best.onnx'"
],
"application/vnd.google.colaboratory.intrinsic+json": {
"type": "string"
}
},
"metadata": {},
"execution_count": 13
}
]
}
]
}
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