diff --git "a/training/model_training.ipynb" "b/training/model_training.ipynb" new file mode 100644--- /dev/null +++ "b/training/model_training.ipynb" @@ -0,0 +1,3678 @@ +{ + "nbformat": 4, + "nbformat_minor": 0, + "metadata": { + "colab": { + "provenance": [], + "gpuType": "T4" + }, + "kernelspec": { + "name": "python3", + "display_name": "Python 3" + }, + "language_info": { + "name": "python" + }, + "accelerator": "GPU" + }, + "cells": [ + { + "cell_type": "code", + "execution_count": 1, + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/" + }, + "id": "DD0FS3tEVrbt", + "outputId": "34b81e30-c2a6-4ac2-dc2d-757fda2ef2b3" + }, + "outputs": [ + { + "output_type": "stream", + "name": "stdout", + "text": [ + "Collecting ultralytics\n", + " Downloading ultralytics-8.3.144-py3-none-any.whl.metadata (37 kB)\n", + "Requirement already satisfied: numpy>=1.23.0 in /usr/local/lib/python3.11/dist-packages (from ultralytics) (2.0.2)\n", + "Requirement already satisfied: 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" Found existing installation: nvidia-curand-cu12 10.3.6.82\n", + " Uninstalling nvidia-curand-cu12-10.3.6.82:\n", + " Successfully uninstalled nvidia-curand-cu12-10.3.6.82\n", + " Attempting uninstall: nvidia-cufft-cu12\n", + " Found existing installation: nvidia-cufft-cu12 11.2.3.61\n", + " Uninstalling nvidia-cufft-cu12-11.2.3.61:\n", + " Successfully uninstalled nvidia-cufft-cu12-11.2.3.61\n", + " Attempting uninstall: nvidia-cuda-runtime-cu12\n", + " Found existing installation: nvidia-cuda-runtime-cu12 12.5.82\n", + " Uninstalling nvidia-cuda-runtime-cu12-12.5.82:\n", + " Successfully uninstalled nvidia-cuda-runtime-cu12-12.5.82\n", + " Attempting uninstall: nvidia-cuda-nvrtc-cu12\n", + " Found existing installation: nvidia-cuda-nvrtc-cu12 12.5.82\n", + " Uninstalling nvidia-cuda-nvrtc-cu12-12.5.82:\n", + " Successfully uninstalled nvidia-cuda-nvrtc-cu12-12.5.82\n", + " Attempting uninstall: nvidia-cuda-cupti-cu12\n", + " Found existing installation: nvidia-cuda-cupti-cu12 12.5.82\n", + " Uninstalling nvidia-cuda-cupti-cu12-12.5.82:\n", + " Successfully uninstalled nvidia-cuda-cupti-cu12-12.5.82\n", + " Attempting uninstall: nvidia-cublas-cu12\n", + " Found existing installation: nvidia-cublas-cu12 12.5.3.2\n", + " Uninstalling nvidia-cublas-cu12-12.5.3.2:\n", + " Successfully uninstalled nvidia-cublas-cu12-12.5.3.2\n", + " Attempting uninstall: nvidia-cusparse-cu12\n", + " Found existing installation: nvidia-cusparse-cu12 12.5.1.3\n", + " Uninstalling nvidia-cusparse-cu12-12.5.1.3:\n", + " Successfully uninstalled nvidia-cusparse-cu12-12.5.1.3\n", + " Attempting uninstall: nvidia-cudnn-cu12\n", + " Found existing installation: nvidia-cudnn-cu12 9.3.0.75\n", + " Uninstalling nvidia-cudnn-cu12-9.3.0.75:\n", + " Successfully uninstalled nvidia-cudnn-cu12-9.3.0.75\n", + " Attempting uninstall: nvidia-cusolver-cu12\n", + " Found existing installation: nvidia-cusolver-cu12 11.6.3.83\n", + " Uninstalling nvidia-cusolver-cu12-11.6.3.83:\n", + " Successfully uninstalled nvidia-cusolver-cu12-11.6.3.83\n", + "Successfully installed nvidia-cublas-cu12-12.4.5.8 nvidia-cuda-cupti-cu12-12.4.127 nvidia-cuda-nvrtc-cu12-12.4.127 nvidia-cuda-runtime-cu12-12.4.127 nvidia-cudnn-cu12-9.1.0.70 nvidia-cufft-cu12-11.2.1.3 nvidia-curand-cu12-10.3.5.147 nvidia-cusolver-cu12-11.6.1.9 nvidia-cusparse-cu12-12.3.1.170 nvidia-nvjitlink-cu12-12.4.127 ultralytics-8.3.144 ultralytics-thop-2.0.14\n", + "Sat May 24 11:15:03 2025 \n", + "+-----------------------------------------------------------------------------------------+\n", + "| NVIDIA-SMI 550.54.15 Driver Version: 550.54.15 CUDA Version: 12.4 |\n", + "|-----------------------------------------+------------------------+----------------------+\n", + "| GPU Name Persistence-M | Bus-Id Disp.A | Volatile Uncorr. ECC |\n", + "| Fan Temp Perf Pwr:Usage/Cap | Memory-Usage | GPU-Util Compute M. |\n", + "| | | MIG M. |\n", + "|=========================================+========================+======================|\n", + "| 0 Tesla T4 Off | 00000000:00:04.0 Off | 0 |\n", + "| N/A 58C P8 12W / 70W | 0MiB / 15360MiB | 0% Default |\n", + "| | | N/A |\n", + "+-----------------------------------------+------------------------+----------------------+\n", + " \n", + "+-----------------------------------------------------------------------------------------+\n", + "| Processes: |\n", + "| GPU GI CI PID Type Process name GPU Memory |\n", + "| ID ID Usage |\n", + "|=========================================================================================|\n", + "| No running processes found |\n", + "+-----------------------------------------------------------------------------------------+\n" + ] + } + ], + "source": [ + "!pip install ultralytics --upgrade\n", + "!nvidia-smi # Check for GPU support" + ] + }, + { + "cell_type": "code", + "source": [ + "!unzip /content/dataset.zip" + ], + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/" + }, + "id": "pOMe4cXhWlF2", + "outputId": "7429c2a0-f0e5-4cc8-b957-d65a8292340a" + }, + "execution_count": 2, + "outputs": [ + { + "output_type": "stream", + "name": "stdout", + "text": [ + "Archive: /content/dataset.zip\n", + " creating: dataset/\n", + " creating: dataset/images/\n", + " creating: dataset/images/test/\n", + " inflating: dataset/images/test/fork_000.png \n", + " inflating: dataset/images/test/fork_001.png \n", + " inflating: dataset/images/test/fork_002.png \n", + " inflating: dataset/images/test/fork_003.png \n", + " inflating: dataset/images/test/fork_004.png \n", + " inflating: dataset/images/test/fork_005.png \n", + " inflating: dataset/images/test/fork_006.png \n", + " inflating: dataset/images/test/fork_007.png \n", + " inflating: dataset/images/test/fork_008.png \n", + " inflating: dataset/images/test/fork_009.png \n", + " inflating: dataset/images/test/glass_000.png \n", + " inflating: dataset/images/test/glass_001.png \n", + " inflating: dataset/images/test/glass_002.png \n", + " inflating: dataset/images/test/glass_003.png \n", + " inflating: dataset/images/test/glass_004.png \n", + " inflating: dataset/images/test/glass_005.png \n", + " inflating: dataset/images/test/glass_006.png \n", + " inflating: dataset/images/test/glass_007.png \n", + " inflating: dataset/images/test/glass_008.png \n", + " inflating: dataset/images/test/glass_009.png \n", + " inflating: dataset/images/test/plate_000.png \n", + " inflating: dataset/images/test/plate_001.png \n", + " inflating: dataset/images/test/plate_002.png \n", + " inflating: dataset/images/test/plate_003.png \n", + " inflating: dataset/images/test/plate_004.png \n", + " inflating: dataset/images/test/plate_005.png \n", + " inflating: dataset/images/test/plate_006.png \n", + " inflating: dataset/images/test/plate_007.png \n", + " inflating: dataset/images/test/plate_008.png \n", + " inflating: dataset/images/test/plate_009.png \n", + " inflating: dataset/images/test/spoon_000.png \n", + " inflating: dataset/images/test/spoon_001.png \n", + " inflating: dataset/images/test/spoon_002.png \n", + " inflating: dataset/images/test/spoon_003.png \n", + " inflating: dataset/images/test/spoon_004.png \n", + " inflating: dataset/images/test/spoon_005.png \n", + " inflating: dataset/images/test/spoon_006.png \n", + " inflating: dataset/images/test/spoon_007.png \n", + " inflating: dataset/images/test/spoon_008.png \n", + " inflating: dataset/images/test/spoon_009.png \n", + " creating: dataset/images/train/\n", + " inflating: dataset/images/train/fork_000.png \n", + " inflating: dataset/images/train/fork_001.png \n", + " inflating: dataset/images/train/fork_002.png \n", + " inflating: dataset/images/train/fork_003.png \n", + " inflating: dataset/images/train/fork_004.png \n", + " inflating: dataset/images/train/fork_005.png \n", + " inflating: dataset/images/train/fork_006.png \n", + " inflating: dataset/images/train/fork_007.png \n", + " inflating: dataset/images/train/fork_008.png \n", + " inflating: dataset/images/train/fork_009.png \n", + " inflating: dataset/images/train/fork_010.png \n", + " inflating: dataset/images/train/fork_011.png \n", + " inflating: dataset/images/train/fork_012.png \n", + " inflating: dataset/images/train/fork_013.png \n", + " inflating: dataset/images/train/fork_014.png \n", + " inflating: dataset/images/train/fork_015.png \n", + " inflating: dataset/images/train/fork_016.png \n", + " inflating: dataset/images/train/fork_017.png \n", + " inflating: dataset/images/train/fork_018.png \n", + " inflating: dataset/images/train/fork_019.png \n", + " inflating: dataset/images/train/fork_020.png \n", + " inflating: dataset/images/train/fork_021.png \n", + " inflating: dataset/images/train/fork_022.png \n", + " inflating: dataset/images/train/fork_023.png \n", + " inflating: dataset/images/train/fork_024.png \n", + " inflating: dataset/images/train/fork_025.png \n", + " inflating: dataset/images/train/fork_026.png \n", + " inflating: dataset/images/train/fork_027.png \n", + " inflating: dataset/images/train/fork_028.png \n", + " inflating: dataset/images/train/fork_029.png \n", + " inflating: dataset/images/train/fork_030.png \n", + " inflating: dataset/images/train/fork_031.png \n", + " inflating: dataset/images/train/fork_032.png \n", + " inflating: dataset/images/train/fork_033.png \n", + " inflating: dataset/images/train/fork_034.png \n", + " inflating: dataset/images/train/fork_035.png \n", + " inflating: dataset/images/train/fork_036.png \n", + " inflating: dataset/images/train/fork_037.png \n", + " inflating: dataset/images/train/fork_038.png \n", + " inflating: dataset/images/train/fork_039.png \n", + " inflating: dataset/images/train/glass_000.png \n", + " inflating: dataset/images/train/glass_001.png \n", + " inflating: dataset/images/train/glass_002.png \n", + " inflating: dataset/images/train/glass_003.png \n", + " inflating: dataset/images/train/glass_004.png \n", + " inflating: dataset/images/train/glass_005.png \n", + " inflating: dataset/images/train/glass_006.png \n", + " inflating: dataset/images/train/glass_007.png \n", + " inflating: dataset/images/train/glass_008.png \n", + " inflating: dataset/images/train/glass_009.png \n", + " inflating: dataset/images/train/glass_010.png \n", + " inflating: dataset/images/train/glass_011.png \n", + " inflating: dataset/images/train/glass_012.png \n", + " inflating: dataset/images/train/glass_013.png \n", + " inflating: dataset/images/train/glass_014.png \n", + " inflating: dataset/images/train/glass_015.png \n", + " inflating: dataset/images/train/glass_016.png \n", + " inflating: dataset/images/train/glass_017.png \n", + " inflating: dataset/images/train/glass_018.png \n", + " inflating: dataset/images/train/glass_019.png \n", + " inflating: dataset/images/train/glass_020.png \n", + " inflating: dataset/images/train/glass_021.png \n", + " inflating: dataset/images/train/glass_022.png \n", + " inflating: dataset/images/train/glass_023.png \n", + " inflating: dataset/images/train/glass_024.png \n", + " inflating: dataset/images/train/glass_025.png \n", + " inflating: dataset/images/train/glass_026.png \n", + " inflating: dataset/images/train/glass_027.png \n", + " inflating: dataset/images/train/glass_028.png \n", + " inflating: dataset/images/train/glass_029.png \n", + " inflating: dataset/images/train/glass_030.png \n", + " inflating: dataset/images/train/glass_031.png \n", + " inflating: dataset/images/train/glass_032.png \n", + " inflating: dataset/images/train/glass_033.png \n", + " inflating: dataset/images/train/glass_034.png \n", + " inflating: dataset/images/train/glass_035.png \n", + " inflating: dataset/images/train/glass_036.png \n", + " inflating: dataset/images/train/glass_037.png \n", + " inflating: dataset/images/train/glass_038.png \n", + " inflating: dataset/images/train/glass_039.png \n", + " inflating: dataset/images/train/plate_000.png \n", + " inflating: dataset/images/train/plate_001.png \n", + " inflating: dataset/images/train/plate_002.png \n", + " inflating: dataset/images/train/plate_003.png \n", + " inflating: dataset/images/train/plate_004.png \n", + " inflating: dataset/images/train/plate_005.png \n", + " inflating: dataset/images/train/plate_006.png \n", + " inflating: dataset/images/train/plate_007.png \n", + " inflating: dataset/images/train/plate_008.png \n", + " inflating: dataset/images/train/plate_009.png \n", + " inflating: dataset/images/train/plate_010.png \n", + " inflating: dataset/images/train/plate_011.png \n", + " inflating: dataset/images/train/plate_012.png \n", + " inflating: dataset/images/train/plate_013.png \n", + " inflating: dataset/images/train/plate_014.png \n", + " inflating: dataset/images/train/plate_015.png \n", + " inflating: dataset/images/train/plate_016.png \n", + " inflating: dataset/images/train/plate_017.png \n", + " inflating: dataset/images/train/plate_018.png \n", + " inflating: dataset/images/train/plate_019.png \n", + " inflating: dataset/images/train/plate_020.png \n", + " inflating: dataset/images/train/plate_021.png \n", + " inflating: dataset/images/train/plate_022.png \n", + " inflating: dataset/images/train/plate_023.png \n", + " inflating: dataset/images/train/plate_024.png \n", + " inflating: dataset/images/train/plate_025.png \n", + " inflating: dataset/images/train/plate_026.png \n", + " inflating: dataset/images/train/plate_027.png \n", + " inflating: dataset/images/train/plate_028.png \n", + " inflating: dataset/images/train/plate_029.png \n", + " inflating: dataset/images/train/plate_030.png \n", + " inflating: dataset/images/train/plate_031.png \n", + " inflating: dataset/images/train/plate_032.png \n", + " inflating: dataset/images/train/plate_033.png \n", + " inflating: dataset/images/train/plate_034.png \n", + " inflating: dataset/images/train/plate_035.png \n", + " inflating: dataset/images/train/plate_036.png \n", + " inflating: dataset/images/train/plate_037.png \n", + " inflating: dataset/images/train/plate_038.png \n", + " inflating: dataset/images/train/plate_039.png \n", + " inflating: dataset/images/train/spoon_000.png \n", + " inflating: dataset/images/train/spoon_001.png \n", + " inflating: dataset/images/train/spoon_002.png \n", + " inflating: dataset/images/train/spoon_003.png \n", + " inflating: dataset/images/train/spoon_004.png \n", + " inflating: dataset/images/train/spoon_005.png \n", + " inflating: dataset/images/train/spoon_006.png \n", + " inflating: dataset/images/train/spoon_007.png \n", + " inflating: dataset/images/train/spoon_008.png \n", + " inflating: dataset/images/train/spoon_009.png \n", + " inflating: dataset/images/train/spoon_010.png \n", + " inflating: dataset/images/train/spoon_011.png \n", + " inflating: dataset/images/train/spoon_012.png \n", + " inflating: dataset/images/train/spoon_013.png \n", + " inflating: dataset/images/train/spoon_014.png \n", + " inflating: dataset/images/train/spoon_015.png \n", + " inflating: dataset/images/train/spoon_016.png \n", + " inflating: dataset/images/train/spoon_017.png \n", + " inflating: dataset/images/train/spoon_018.png \n", + " inflating: dataset/images/train/spoon_019.png \n", + " inflating: dataset/images/train/spoon_020.png \n", + " inflating: dataset/images/train/spoon_021.png \n", + " inflating: dataset/images/train/spoon_022.png \n", + " inflating: dataset/images/train/spoon_023.png \n", + " inflating: dataset/images/train/spoon_024.png \n", + " inflating: dataset/images/train/spoon_025.png \n", + " inflating: dataset/images/train/spoon_026.png \n", + " inflating: dataset/images/train/spoon_027.png \n", + " inflating: dataset/images/train/spoon_028.png \n", + " inflating: dataset/images/train/spoon_029.png \n", + " inflating: dataset/images/train/spoon_030.png \n", + " inflating: dataset/images/train/spoon_031.png \n", + " inflating: dataset/images/train/spoon_032.png \n", + " inflating: dataset/images/train/spoon_033.png \n", + " inflating: dataset/images/train/spoon_034.png \n", + " inflating: dataset/images/train/spoon_035.png \n", + " inflating: dataset/images/train/spoon_036.png \n", + " inflating: dataset/images/train/spoon_037.png \n", + " inflating: dataset/images/train/spoon_038.png \n", + " inflating: dataset/images/train/spoon_039.png \n", + " creating: dataset/labels/\n", + " creating: dataset/labels/test/\n", + " inflating: dataset/labels/test/classes.txt \n", + " inflating: dataset/labels/test/fork_000.txt \n", + " inflating: dataset/labels/test/fork_001.txt \n", + " inflating: dataset/labels/test/fork_002.txt \n", + " inflating: dataset/labels/test/fork_003.txt \n", + " inflating: dataset/labels/test/fork_004.txt \n", + " inflating: dataset/labels/test/fork_005.txt \n", + " inflating: dataset/labels/test/fork_006.txt \n", + " inflating: dataset/labels/test/fork_007.txt \n", + " inflating: dataset/labels/test/fork_008.txt \n", + " inflating: dataset/labels/test/fork_009.txt \n", + " inflating: dataset/labels/test/glass_000.txt \n", + " inflating: dataset/labels/test/glass_001.txt \n", + " inflating: dataset/labels/test/glass_002.txt \n", + " inflating: dataset/labels/test/glass_003.txt \n", + " inflating: dataset/labels/test/glass_004.txt \n", + " inflating: dataset/labels/test/glass_005.txt \n", + " inflating: dataset/labels/test/glass_006.txt \n", + " inflating: dataset/labels/test/glass_007.txt \n", + " inflating: dataset/labels/test/glass_008.txt \n", + " inflating: dataset/labels/test/glass_009.txt \n", + " inflating: dataset/labels/test/plate_000.txt \n", + " inflating: dataset/labels/test/plate_001.txt \n", + " inflating: dataset/labels/test/plate_002.txt \n", + " inflating: dataset/labels/test/plate_003.txt \n", + " inflating: dataset/labels/test/plate_004.txt \n", + " inflating: dataset/labels/test/plate_005.txt \n", + " inflating: dataset/labels/test/plate_006.txt \n", + " inflating: dataset/labels/test/plate_007.txt \n", + " inflating: dataset/labels/test/plate_008.txt \n", + " inflating: dataset/labels/test/plate_009.txt \n", + " inflating: dataset/labels/test/spoon_000.txt \n", + " inflating: dataset/labels/test/spoon_001.txt \n", + " inflating: dataset/labels/test/spoon_002.txt \n", + " inflating: dataset/labels/test/spoon_003.txt \n", + " inflating: dataset/labels/test/spoon_004.txt \n", + " inflating: dataset/labels/test/spoon_005.txt \n", + " inflating: dataset/labels/test/spoon_006.txt \n", + " inflating: dataset/labels/test/spoon_007.txt \n", + " inflating: dataset/labels/test/spoon_008.txt \n", + " inflating: dataset/labels/test/spoon_009.txt \n", + " creating: dataset/labels/train/\n", + " inflating: dataset/labels/train/classes.txt \n", + " inflating: dataset/labels/train/fork_000.txt \n", + " inflating: dataset/labels/train/fork_001.txt \n", + " inflating: dataset/labels/train/fork_002.txt \n", + " inflating: dataset/labels/train/fork_003.txt \n", + " inflating: dataset/labels/train/fork_004.txt \n", + " inflating: dataset/labels/train/fork_005.txt \n", + " inflating: dataset/labels/train/fork_006.txt \n", + " inflating: dataset/labels/train/fork_007.txt \n", + " inflating: dataset/labels/train/fork_008.txt \n", + " inflating: dataset/labels/train/fork_009.txt \n", + " inflating: dataset/labels/train/fork_010.txt \n", + " inflating: dataset/labels/train/fork_011.txt \n", + " inflating: dataset/labels/train/fork_012.txt \n", + " inflating: dataset/labels/train/fork_013.txt \n", + " inflating: dataset/labels/train/fork_014.txt \n", + " inflating: dataset/labels/train/fork_015.txt \n", + " inflating: dataset/labels/train/fork_016.txt \n", + " inflating: dataset/labels/train/fork_017.txt \n", + " inflating: dataset/labels/train/fork_018.txt \n", + " inflating: dataset/labels/train/fork_019.txt \n", + " inflating: dataset/labels/train/fork_020.txt \n", + " inflating: dataset/labels/train/fork_021.txt \n", + " inflating: dataset/labels/train/fork_022.txt \n", + " inflating: dataset/labels/train/fork_023.txt \n", + " inflating: dataset/labels/train/fork_024.txt \n", + " inflating: dataset/labels/train/fork_025.txt \n", + " inflating: dataset/labels/train/fork_026.txt \n", + " inflating: dataset/labels/train/fork_027.txt \n", + " inflating: dataset/labels/train/fork_028.txt \n", + " inflating: dataset/labels/train/fork_029.txt \n", + " inflating: dataset/labels/train/fork_030.txt \n", + " inflating: dataset/labels/train/fork_031.txt \n", + " inflating: dataset/labels/train/fork_032.txt \n", + " inflating: dataset/labels/train/fork_033.txt \n", + " inflating: dataset/labels/train/fork_034.txt \n", + " inflating: dataset/labels/train/fork_035.txt \n", + " inflating: dataset/labels/train/fork_036.txt \n", + " inflating: dataset/labels/train/fork_037.txt \n", + " inflating: dataset/labels/train/fork_038.txt \n", + " inflating: dataset/labels/train/fork_039.txt \n", + " inflating: dataset/labels/train/glass_000.txt \n", + " inflating: dataset/labels/train/glass_001.txt \n", + " inflating: dataset/labels/train/glass_002.txt \n", + " inflating: dataset/labels/train/glass_003.txt \n", + " inflating: dataset/labels/train/glass_004.txt \n", + " inflating: dataset/labels/train/glass_005.txt \n", + " inflating: dataset/labels/train/glass_006.txt \n", + " inflating: dataset/labels/train/glass_007.txt \n", + " inflating: dataset/labels/train/glass_008.txt \n", + " inflating: dataset/labels/train/glass_009.txt \n", + " inflating: dataset/labels/train/glass_010.txt \n", + " inflating: dataset/labels/train/glass_011.txt \n", + " inflating: dataset/labels/train/glass_012.txt \n", + " inflating: dataset/labels/train/glass_013.txt \n", + " inflating: dataset/labels/train/glass_014.txt \n", + " inflating: dataset/labels/train/glass_015.txt \n", + " inflating: dataset/labels/train/glass_016.txt \n", + " inflating: dataset/labels/train/glass_017.txt \n", + " inflating: dataset/labels/train/glass_018.txt \n", + " inflating: dataset/labels/train/glass_019.txt \n", + " inflating: dataset/labels/train/glass_020.txt \n", + " inflating: dataset/labels/train/glass_021.txt \n", + " inflating: dataset/labels/train/glass_022.txt \n", + " inflating: dataset/labels/train/glass_023.txt \n", + " inflating: dataset/labels/train/glass_024.txt \n", + " inflating: dataset/labels/train/glass_025.txt \n", + " inflating: dataset/labels/train/glass_026.txt \n", + " inflating: dataset/labels/train/glass_027.txt \n", + " inflating: dataset/labels/train/glass_028.txt \n", + " inflating: dataset/labels/train/glass_029.txt \n", + " inflating: dataset/labels/train/glass_030.txt \n", + " inflating: dataset/labels/train/glass_031.txt \n", + " inflating: dataset/labels/train/glass_032.txt \n", + " inflating: dataset/labels/train/glass_033.txt \n", + " inflating: dataset/labels/train/glass_034.txt \n", + " inflating: dataset/labels/train/glass_035.txt \n", + " inflating: dataset/labels/train/glass_036.txt \n", + " inflating: dataset/labels/train/glass_037.txt \n", + " inflating: dataset/labels/train/glass_038.txt \n", + " inflating: dataset/labels/train/glass_039.txt \n", + " inflating: dataset/labels/train/plate_000.txt \n", + " inflating: dataset/labels/train/plate_001.txt \n", + " inflating: dataset/labels/train/plate_002.txt \n", + " inflating: dataset/labels/train/plate_003.txt \n", + " inflating: dataset/labels/train/plate_004.txt \n", + " inflating: dataset/labels/train/plate_005.txt \n", + " inflating: dataset/labels/train/plate_006.txt \n", + " inflating: dataset/labels/train/plate_007.txt \n", + " inflating: dataset/labels/train/plate_008.txt \n", + " inflating: dataset/labels/train/plate_009.txt \n", + " inflating: dataset/labels/train/plate_010.txt \n", + " inflating: dataset/labels/train/plate_011.txt \n", + " inflating: dataset/labels/train/plate_012.txt \n", + " inflating: dataset/labels/train/plate_013.txt \n", + " inflating: dataset/labels/train/plate_014.txt \n", + " inflating: dataset/labels/train/plate_015.txt \n", + " inflating: dataset/labels/train/plate_016.txt \n", + " inflating: dataset/labels/train/plate_017.txt \n", + " inflating: dataset/labels/train/plate_018.txt \n", + " inflating: dataset/labels/train/plate_019.txt \n", + " inflating: dataset/labels/train/plate_020.txt \n", + " inflating: dataset/labels/train/plate_021.txt \n", + " inflating: dataset/labels/train/plate_022.txt \n", + " inflating: dataset/labels/train/plate_023.txt \n", + " inflating: dataset/labels/train/plate_024.txt \n", + " inflating: dataset/labels/train/plate_025.txt \n", + " inflating: dataset/labels/train/plate_026.txt \n", + " inflating: dataset/labels/train/plate_027.txt \n", + " inflating: dataset/labels/train/plate_028.txt \n", + " inflating: dataset/labels/train/plate_029.txt \n", + " inflating: dataset/labels/train/plate_030.txt \n", + " inflating: dataset/labels/train/plate_031.txt \n", + " inflating: dataset/labels/train/plate_032.txt \n", + " inflating: dataset/labels/train/plate_033.txt \n", + " inflating: dataset/labels/train/plate_034.txt \n", + " inflating: dataset/labels/train/plate_035.txt \n", + " inflating: dataset/labels/train/plate_036.txt \n", + " inflating: dataset/labels/train/plate_037.txt \n", + " inflating: dataset/labels/train/plate_038.txt \n", + " inflating: dataset/labels/train/plate_039.txt \n", + " inflating: dataset/labels/train/spoon_000.txt \n", + " inflating: dataset/labels/train/spoon_001.txt \n", + " inflating: dataset/labels/train/spoon_002.txt \n", + " inflating: dataset/labels/train/spoon_003.txt \n", + " inflating: dataset/labels/train/spoon_004.txt \n", + " inflating: dataset/labels/train/spoon_005.txt \n", + " inflating: dataset/labels/train/spoon_006.txt \n", + " inflating: dataset/labels/train/spoon_007.txt \n", + " inflating: dataset/labels/train/spoon_008.txt \n", + " inflating: dataset/labels/train/spoon_009.txt \n", + " inflating: dataset/labels/train/spoon_010.txt \n", + " inflating: dataset/labels/train/spoon_011.txt \n", + " inflating: dataset/labels/train/spoon_012.txt \n", + " inflating: dataset/labels/train/spoon_013.txt \n", + " inflating: dataset/labels/train/spoon_014.txt \n", + " inflating: dataset/labels/train/spoon_015.txt \n", + " inflating: dataset/labels/train/spoon_016.txt \n", + " inflating: dataset/labels/train/spoon_017.txt \n", + " inflating: dataset/labels/train/spoon_018.txt \n", + " inflating: dataset/labels/train/spoon_019.txt \n", + " inflating: dataset/labels/train/spoon_020.txt \n", + " inflating: dataset/labels/train/spoon_021.txt \n", + " inflating: dataset/labels/train/spoon_022.txt \n", + " inflating: dataset/labels/train/spoon_023.txt \n", + " inflating: dataset/labels/train/spoon_024.txt \n", + " inflating: dataset/labels/train/spoon_025.txt \n", + " inflating: dataset/labels/train/spoon_026.txt \n", + " inflating: dataset/labels/train/spoon_027.txt \n", + " inflating: dataset/labels/train/spoon_028.txt \n", + " inflating: dataset/labels/train/spoon_029.txt \n", + " inflating: dataset/labels/train/spoon_030.txt \n", + " inflating: dataset/labels/train/spoon_031.txt \n", + " inflating: dataset/labels/train/spoon_032.txt \n", + " inflating: dataset/labels/train/spoon_033.txt \n", + " inflating: dataset/labels/train/spoon_034.txt \n", + " inflating: dataset/labels/train/spoon_035.txt \n", + " inflating: dataset/labels/train/spoon_036.txt \n", + " inflating: dataset/labels/train/spoon_037.txt \n", + " inflating: dataset/labels/train/spoon_038.txt \n", + " inflating: dataset/labels/train/spoon_039.txt \n" + ] + } + ] + }, + { + "cell_type": "code", + "source": [ + "import os\n", + "\n", + "# 🔧 Set this to your actual labels directory\n", + "label_dir = \"/content/dataset/labels/train\" # Change if needed\n", + "\n", + "# Loop through each file in the label directory\n", + "for fname in os.listdir(label_dir):\n", + " if fname.endswith(\".txt\"):\n", + " fpath = os.path.join(label_dir, fname)\n", + " with open(fpath, \"r\") as f:\n", + " lines = f.readlines()\n", + "\n", + " updated_lines = []\n", + " changed = False\n", + "\n", + " for line in lines:\n", + " parts = line.strip().split()\n", + " if len(parts) >= 5:\n", + " class_id = parts[0]\n", + " if class_id == \"15\":\n", + " parts[0] = \"0\" # Replace 15 with 0\n", + " changed = True\n", + " updated_lines.append(\" \".join(parts))\n", + "\n", + " # Overwrite file only if changes were made\n", + " if changed:\n", + " with open(fpath, \"w\") as f:\n", + " f.write(\"\\n\".join(updated_lines))\n", + "\n", + "print(\"Finished replacing class ID 15 with 0.\")\n" + ], + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/" + }, + "id": "dWnY5q74VzxD", + "outputId": "f1871a1e-6b05-4320-fc9e-6ad0a44bed24" + }, + "execution_count": null, + "outputs": [ + { + "output_type": "stream", + "name": "stdout", + "text": [ + "Finished replacing class ID 15 with 0.\n" + ] + } + ] + }, + { + "cell_type": "code", + "source": [ + "from ultralytics import YOLO\n", + "\n", + "model = YOLO(\"yolov8s.pt\") # Medium-sized model\n", + "\n", + "results = model.train(\n", + " data=\"data.yaml\",\n", + " epochs=35,\n", + " patience=20,\n", + " imgsz=512,\n", + " batch=8, # Adjust based on GPU RAM\n", + " conf=0.35,\n", + " name=\"object-detector\",\n", + " augment=True,\n", + " auto_augment=\"randaugment\",\n", + " lr0=0.001,\n", + " cos_lr=True,\n", + " save=True,\n", + " save_period=10,\n", + " pretrained=True,\n", + " # Optional tweaks:\n", + " weight_decay=0.0005,\n", + " fliplr=0.5, # Helps with small objects\n", + " mosaic=1.0, # Improves small-object detection\n", + " amp=True, # Enable if GPU supports it\n", + ")" + ], + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/" + }, + "id": "ZpDGBwYTWj3f", + "outputId": "eb324f60-8e46-4655-c301-72e5665f6899" + }, + "execution_count": 3, + "outputs": [ + { + "output_type": "stream", + "name": "stdout", + "text": [ + "Creating new Ultralytics Settings v0.0.6 file ✅ \n", + "View Ultralytics Settings with 'yolo settings' or at '/root/.config/Ultralytics/settings.json'\n", + "Update Settings with 'yolo settings key=value', i.e. 'yolo settings runs_dir=path/to/dir'. For help see https://docs.ultralytics.com/quickstart/#ultralytics-settings.\n", + "Downloading https://github.com/ultralytics/assets/releases/download/v8.3.0/yolov8s.pt to 'yolov8s.pt'...\n" + ] + }, + { + "output_type": "stream", + "name": "stderr", + "text": [ + "100%|██████████| 21.5M/21.5M [00:00<00:00, 269MB/s]\n" + ] + }, + { + "output_type": "stream", + "name": "stdout", + "text": [ + "Ultralytics 8.3.144 🚀 Python-3.11.12 torch-2.6.0+cu124 CUDA:0 (Tesla T4, 15095MiB)\n", + "\u001b[34m\u001b[1mengine/trainer: \u001b[0magnostic_nms=False, amp=True, augment=True, auto_augment=randaugment, batch=8, bgr=0.0, box=7.5, cache=False, cfg=None, classes=None, close_mosaic=10, cls=0.5, conf=0.35, copy_paste=0.0, copy_paste_mode=flip, cos_lr=True, cutmix=0.0, data=data.yaml, degrees=0.0, deterministic=True, device=None, dfl=1.5, dnn=False, dropout=0.0, dynamic=False, embed=None, epochs=35, erasing=0.4, exist_ok=False, fliplr=0.5, flipud=0.0, format=torchscript, fraction=1.0, freeze=None, half=False, hsv_h=0.015, hsv_s=0.7, hsv_v=0.4, imgsz=512, int8=False, iou=0.7, keras=False, kobj=1.0, line_width=None, lr0=0.001, lrf=0.01, mask_ratio=4, max_det=300, mixup=0.0, mode=train, model=yolov8s.pt, momentum=0.937, mosaic=1.0, multi_scale=False, name=object-detector, nbs=64, nms=False, opset=None, optimize=False, optimizer=auto, overlap_mask=True, patience=20, perspective=0.0, plots=True, pose=12.0, pretrained=True, profile=False, project=None, rect=False, resume=False, retina_masks=False, save=True, save_conf=False, save_crop=False, save_dir=runs/detect/object-detector, save_frames=False, save_json=False, save_period=10, save_txt=False, scale=0.5, seed=0, shear=0.0, show=False, show_boxes=True, show_conf=True, show_labels=True, simplify=True, single_cls=False, source=None, split=val, stream_buffer=False, task=detect, time=None, tracker=botsort.yaml, translate=0.1, val=True, verbose=True, vid_stride=1, visualize=False, warmup_bias_lr=0.1, warmup_epochs=3.0, warmup_momentum=0.8, weight_decay=0.0005, workers=8, workspace=None\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, 144MB/s]" + ] + }, + { + "output_type": "stream", + "name": "stdout", + "text": [ + "Overriding model.yaml nc=80 with nc=4\n", + "\n", + " from n params module arguments \n", + " 0 -1 1 928 ultralytics.nn.modules.conv.Conv [3, 32, 3, 2] \n", + " 1 -1 1 18560 ultralytics.nn.modules.conv.Conv [32, 64, 3, 2] \n", + " 2 -1 1 29056 ultralytics.nn.modules.block.C2f [64, 64, 1, True] \n", + " 3 -1 1 73984 ultralytics.nn.modules.conv.Conv [64, 128, 3, 2] \n", + " 4 -1 2 197632 ultralytics.nn.modules.block.C2f [128, 128, 2, True] \n", + " 5 -1 1 295424 ultralytics.nn.modules.conv.Conv [128, 256, 3, 2] \n", + " 6 -1 2 788480 ultralytics.nn.modules.block.C2f [256, 256, 2, True] \n", + " 7 -1 1 1180672 ultralytics.nn.modules.conv.Conv [256, 512, 3, 2] \n", + " 8 -1 1 1838080 ultralytics.nn.modules.block.C2f [512, 512, 1, True] \n", + " 9 -1 1 656896 ultralytics.nn.modules.block.SPPF [512, 512, 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 591360 ultralytics.nn.modules.block.C2f [768, 256, 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 148224 ultralytics.nn.modules.block.C2f [384, 128, 1] \n", + " 16 -1 1 147712 ultralytics.nn.modules.conv.Conv [128, 128, 3, 2] \n", + " 17 [-1, 12] 1 0 ultralytics.nn.modules.conv.Concat [1] \n", + " 18 -1 1 493056 ultralytics.nn.modules.block.C2f [384, 256, 1] \n", + " 19 -1 1 590336 ultralytics.nn.modules.conv.Conv [256, 256, 3, 2] \n", + " 20 [-1, 9] 1 0 ultralytics.nn.modules.conv.Concat [1] \n", + " 21 -1 1 1969152 ultralytics.nn.modules.block.C2f [768, 512, 1] \n", + " 22 [15, 18, 21] 1 2117596 ultralytics.nn.modules.head.Detect [4, [128, 256, 512]] \n" + ] + }, + { + "output_type": "stream", + "name": "stderr", + "text": [ + "\n" + ] + }, + { + "output_type": "stream", + "name": "stdout", + "text": [ + "Model summary: 129 layers, 11,137,148 parameters, 11,137,132 gradients, 28.7 GFLOPs\n", + "\n", + "Transferred 349/355 items from pretrained weights\n", + "Freezing layer 'model.22.dfl.conv.weight'\n", + "\u001b[34m\u001b[1mAMP: \u001b[0mrunning Automatic Mixed Precision (AMP) checks...\n", + "Downloading https://github.com/ultralytics/assets/releases/download/v8.3.0/yolo11n.pt to 'yolo11n.pt'...\n" + ] + }, + { + "output_type": "stream", + "name": "stderr", + "text": [ + "100%|██████████| 5.35M/5.35M [00:00<00:00, 265MB/s]\n" + ] + }, + { + "output_type": "stream", + "name": "stdout", + "text": [ + "\u001b[34m\u001b[1mAMP: \u001b[0mchecks passed ✅\n", + "\u001b[34m\u001b[1mtrain: \u001b[0mFast image access ✅ (ping: 0.1±0.1 ms, read: 2040.5±1215.5 MB/s, size: 339.8 KB)\n" + ] + }, + { + "output_type": "stream", + "name": "stderr", + "text": [ + "\u001b[34m\u001b[1mtrain: \u001b[0mScanning /content/dataset/labels/train... 160 images, 0 backgrounds, 0 corrupt: 100%|██████████| 160/160 [00:00<00:00, 1297.84it/s]" + ] + }, + { + "output_type": "stream", + "name": "stdout", + "text": [ + "\u001b[34m\u001b[1mtrain: \u001b[0mNew cache created: /content/dataset/labels/train.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, method='weighted_average', num_output_channels=3), CLAHE(p=0.01, clip_limit=(1.0, 4.0), tile_grid_size=(8, 8))\n", + "\u001b[34m\u001b[1mval: \u001b[0mFast image access ✅ (ping: 0.1±0.1 ms, read: 1514.1±1162.7 MB/s, size: 313.5 KB)\n" + ] + }, + { + "output_type": "stream", + "name": "stderr", + "text": [ + "\u001b[34m\u001b[1mval: \u001b[0mScanning /content/dataset/labels/test... 40 images, 0 backgrounds, 0 corrupt: 100%|██████████| 40/40 [00:00<00:00, 1095.69it/s]" + ] + }, + { + "output_type": "stream", + "name": "stdout", + "text": [ + "\u001b[34m\u001b[1mval: \u001b[0mNew cache created: /content/dataset/labels/test.cache\n" + ] + }, + { + "output_type": "stream", + "name": "stderr", + "text": [ + "\n" + ] + }, + { + "output_type": "stream", + "name": "stdout", + "text": [ + "Plotting labels to runs/detect/object-detector/labels.jpg... \n", + "\u001b[34m\u001b[1moptimizer:\u001b[0m 'optimizer=auto' found, ignoring 'lr0=0.001' and 'momentum=0.937' and determining best 'optimizer', 'lr0' and 'momentum' automatically... \n", + "\u001b[34m\u001b[1moptimizer:\u001b[0m AdamW(lr=0.00125, momentum=0.9) with parameter groups 57 weight(decay=0.0), 64 weight(decay=0.0005), 63 bias(decay=0.0)\n", + "Image sizes 512 train, 512 val\n", + "Using 2 dataloader workers\n", + "Logging results to \u001b[1mruns/detect/object-detector\u001b[0m\n", + "Starting training for 35 epochs...\n", + "\n", + " Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size\n" + ] + }, + { + "output_type": "stream", + "name": "stderr", + "text": [ + " 1/35 1.3G 1.835 3.163 1.825 14 512: 100%|██████████| 20/20 [00:05<00:00, 3.56it/s]\n", + " Class Images Instances Box(P R mAP50 mAP50-95): 100%|██████████| 3/3 [00:01<00:00, 2.05it/s]" + ] + }, + { + "output_type": "stream", + "name": "stdout", + "text": [ + " all 40 40 0.594 0.512 0.593 0.332\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": [ + " 2/35 1.59G 1.73 2.513 1.656 18 512: 100%|██████████| 20/20 [00:03<00:00, 6.41it/s]\n", + " Class Images Instances Box(P R mAP50 mAP50-95): 100%|██████████| 3/3 [00:00<00:00, 7.91it/s]" + ] + }, + { + "output_type": "stream", + "name": "stdout", + "text": [ + " all 40 40 0.489 0.522 0.516 0.243\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": [ + " 3/35 1.63G 1.714 2.167 1.644 15 512: 100%|██████████| 20/20 [00:04<00:00, 4.80it/s]\n", + " Class Images Instances Box(P R mAP50 mAP50-95): 100%|██████████| 3/3 [00:00<00:00, 8.03it/s]" + ] + }, + { + "output_type": "stream", + "name": "stdout", + "text": [ + " all 40 40 0.285 0.5 0.335 0.172\n" + ] + }, + { + "output_type": "stream", + "name": "stderr", + "text": [ + "\n" + ] + }, + { + "output_type": "stream", + "name": "stdout", + "text": [ + "\n", + " Epoch GPU_mem box_loss cls_loss 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+ ] + }, + { + "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": [ + " 6/35 1.73G 1.794 2.073 1.662 18 512: 100%|██████████| 20/20 [00:03<00:00, 5.49it/s]\n", + " Class Images Instances Box(P R mAP50 mAP50-95): 100%|██████████| 3/3 [00:00<00:00, 6.57it/s]" + ] + }, + { + "output_type": "stream", + "name": "stdout", + "text": [ + " all 40 40 0.473 0.3 0.323 0.152\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": [ + " 7/35 1.88G 1.705 1.864 1.631 19 512: 100%|██████████| 20/20 [00:03<00:00, 6.55it/s]\n", + " Class Images 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" Class Images Instances Box(P R mAP50 mAP50-95): 100%|██████████| 3/3 [00:00<00:00, 7.94it/s]" + ] + }, + { + "output_type": "stream", + "name": "stdout", + "text": [ + " all 40 40 0.894 0.85 0.901 0.594\n" + ] + }, + { + "output_type": "stream", + "name": "stderr", + "text": [ + "\n" + ] + }, + { + "output_type": "stream", + "name": "stdout", + "text": [ + "\n", + "35 epochs completed in 0.043 hours.\n", + "Optimizer stripped from runs/detect/object-detector/weights/last.pt, 22.5MB\n", + "Optimizer stripped from runs/detect/object-detector/weights/best.pt, 22.5MB\n", + "\n", + "Validating runs/detect/object-detector/weights/best.pt...\n", + "Ultralytics 8.3.144 🚀 Python-3.11.12 torch-2.6.0+cu124 CUDA:0 (Tesla T4, 15095MiB)\n", + "Model summary (fused): 72 layers, 11,127,132 parameters, 0 gradients, 28.4 GFLOPs\n" + ] + }, + { + "output_type": "stream", + "name": "stderr", + "text": [ + " Class Images Instances Box(P R mAP50 mAP50-95): 100%|██████████| 3/3 [00:01<00:00, 1.95it/s]\n" + ] + }, + { + "output_type": "stream", + "name": "stdout", + "text": [ + " all 40 40 0.841 0.721 0.806 0.541\n", + " fork 10 10 1 0.383 0.516 0.276\n", + " spoon 10 10 0.572 0.8 0.813 0.437\n", + " plate 10 10 1 1 0.995 0.774\n", + " glass 10 10 0.793 0.7 0.9 0.678\n", + "Speed: 0.3ms preprocess, 31.3ms inference, 0.0ms loss, 1.8ms postprocess per image\n", + "Results saved to \u001b[1mruns/detect/object-detector\u001b[0m\n" + ] + } + ] + }, + { + "cell_type": "code", + "source": [ + "from ultralytics import YOLO\n", + "\n", + "# Load base model\n", + "model = YOLO(\"yolov8m.pt\") # ⬅️ Upgrade from 'yolov8n.pt' to 'yolov8s.pt' for better accuracy\n", + "\n", + "# Train\n", + "model.train(\n", + " data=\"data.yaml\", # path to your dataset YAML file\n", + " epochs=45, # increased to allow better convergence\n", + " patience=20, # early stopping if no val improvement\n", + " imgsz=640, # image size\n", + " batch=8, # adjust if Colab RAM allows (16–32 is ideal)\n", + " conf=0.25, # initial confidence threshold\n", + " name=\"detector\", # new project name\n", + " augment=True, # enables data augmentation\n", + " auto_augment='randaugment',# advanced augmentation strategy\n", + " lr0=0.001, # initial learning rate (optional tweak)\n", + " cos_lr=True, # cosine learning rate schedule (smoother training)\n", + " save=True, # save all checkpoints\n", + " save_period=10, # save weights every 10 epochs\n", + " pretrained=True # use pretrained weights (not training from scratch)\n", + ")" + ], + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/" + }, + "id": "gRn_bJapEbqM", + "outputId": "dcf7273c-fc64-4e28-b3b8-ab2340ae7e9d" + }, + "execution_count": 1, + "outputs": [ + { + "output_type": "stream", + "name": "stdout", + "text": [ + "Downloading https://github.com/ultralytics/assets/releases/download/v8.3.0/yolov8m.pt to 'yolov8m.pt'...\n" + ] + }, + { + "output_type": "stream", + "name": "stderr", + "text": [ + "100%|██████████| 49.7M/49.7M [00:00<00:00, 400MB/s]\n" + ] + }, + { + "output_type": "stream", + "name": "stdout", + "text": [ + "Ultralytics 8.3.144 🚀 Python-3.11.12 torch-2.6.0+cu124 CUDA:0 (Tesla T4, 15095MiB)\n", + "\u001b[34m\u001b[1mengine/trainer: \u001b[0magnostic_nms=False, amp=True, augment=True, auto_augment=randaugment, batch=8, bgr=0.0, box=7.5, cache=False, cfg=None, classes=None, close_mosaic=10, cls=0.5, conf=0.25, copy_paste=0.0, copy_paste_mode=flip, cos_lr=True, cutmix=0.0, data=data.yaml, degrees=0.0, deterministic=True, device=None, dfl=1.5, dnn=False, dropout=0.0, dynamic=False, embed=None, epochs=45, erasing=0.4, exist_ok=False, fliplr=0.5, flipud=0.0, format=torchscript, fraction=1.0, freeze=None, half=False, hsv_h=0.015, hsv_s=0.7, hsv_v=0.4, imgsz=640, int8=False, iou=0.7, keras=False, kobj=1.0, line_width=None, lr0=0.001, lrf=0.01, mask_ratio=4, max_det=300, mixup=0.0, mode=train, model=yolov8m.pt, momentum=0.937, mosaic=1.0, multi_scale=False, name=detector2, nbs=64, nms=False, opset=None, optimize=False, optimizer=auto, overlap_mask=True, patience=20, perspective=0.0, plots=True, pose=12.0, pretrained=True, profile=False, project=None, rect=False, resume=False, retina_masks=False, save=True, save_conf=False, save_crop=False, save_dir=runs/detect/detector2, save_frames=False, save_json=False, save_period=10, save_txt=False, scale=0.5, seed=0, shear=0.0, show=False, show_boxes=True, show_conf=True, show_labels=True, simplify=True, single_cls=False, source=None, split=val, stream_buffer=False, task=detect, time=None, tracker=botsort.yaml, translate=0.1, val=True, verbose=True, vid_stride=1, visualize=False, warmup_bias_lr=0.1, warmup_epochs=3.0, warmup_momentum=0.8, weight_decay=0.0005, workers=8, workspace=None\n", + "Overriding model.yaml nc=80 with nc=4\n", + "\n", + " from n params module arguments \n", + " 0 -1 1 1392 ultralytics.nn.modules.conv.Conv [3, 48, 3, 2] \n", + " 1 -1 1 41664 ultralytics.nn.modules.conv.Conv [48, 96, 3, 2] \n", + " 2 -1 2 111360 ultralytics.nn.modules.block.C2f [96, 96, 2, True] \n", + " 3 -1 1 166272 ultralytics.nn.modules.conv.Conv [96, 192, 3, 2] \n", + " 4 -1 4 813312 ultralytics.nn.modules.block.C2f [192, 192, 4, True] \n", + " 5 -1 1 664320 ultralytics.nn.modules.conv.Conv [192, 384, 3, 2] \n", + " 6 -1 4 3248640 ultralytics.nn.modules.block.C2f [384, 384, 4, True] \n", + " 7 -1 1 1991808 ultralytics.nn.modules.conv.Conv [384, 576, 3, 2] \n", + " 8 -1 2 3985920 ultralytics.nn.modules.block.C2f [576, 576, 2, True] \n", + " 9 -1 1 831168 ultralytics.nn.modules.block.SPPF [576, 576, 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 2 1993728 ultralytics.nn.modules.block.C2f [960, 384, 2] \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 2 517632 ultralytics.nn.modules.block.C2f [576, 192, 2] \n", + " 16 -1 1 332160 ultralytics.nn.modules.conv.Conv [192, 192, 3, 2] \n", + " 17 [-1, 12] 1 0 ultralytics.nn.modules.conv.Concat [1] \n", + " 18 -1 2 1846272 ultralytics.nn.modules.block.C2f [576, 384, 2] \n", + " 19 -1 1 1327872 ultralytics.nn.modules.conv.Conv [384, 384, 3, 2] \n", + " 20 [-1, 9] 1 0 ultralytics.nn.modules.conv.Concat [1] \n", + " 21 -1 2 4207104 ultralytics.nn.modules.block.C2f [960, 576, 2] \n", + " 22 [15, 18, 21] 1 3778012 ultralytics.nn.modules.head.Detect [4, [192, 384, 576]] \n", + "Model summary: 169 layers, 25,858,636 parameters, 25,858,620 gradients, 79.1 GFLOPs\n", + "\n", + "Transferred 469/475 items from pretrained weights\n", + "Freezing layer 'model.22.dfl.conv.weight'\n", + "\u001b[34m\u001b[1mAMP: \u001b[0mrunning Automatic Mixed Precision (AMP) checks...\n", + "\u001b[34m\u001b[1mAMP: \u001b[0mchecks passed ✅\n", + "\u001b[34m\u001b[1mtrain: \u001b[0mFast image access ✅ (ping: 0.0±0.0 ms, read: 2182.5±922.2 MB/s, size: 339.8 KB)\n" + ] + }, + { + "output_type": "stream", + "name": "stderr", + "text": [ + "\u001b[34m\u001b[1mtrain: \u001b[0mScanning /content/dataset/labels/train... 160 images, 0 backgrounds, 0 corrupt: 100%|██████████| 160/160 [00:00<00:00, 1274.37it/s]" + ] + }, + { + "output_type": "stream", + "name": "stdout", + "text": [ + "\u001b[34m\u001b[1mtrain: \u001b[0mNew cache created: /content/dataset/labels/train.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, method='weighted_average', num_output_channels=3), CLAHE(p=0.01, clip_limit=(1.0, 4.0), tile_grid_size=(8, 8))\n", + "\u001b[34m\u001b[1mval: \u001b[0mFast image access ✅ (ping: 0.0±0.0 ms, read: 1791.1±1377.6 MB/s, size: 313.5 KB)\n" + ] + }, + { + "output_type": "stream", + "name": "stderr", + "text": [ + "\u001b[34m\u001b[1mval: \u001b[0mScanning /content/dataset/labels/test... 40 images, 0 backgrounds, 0 corrupt: 100%|██████████| 40/40 [00:00<00:00, 483.50it/s]" + ] + }, + { + "output_type": "stream", + "name": "stdout", + "text": [ + "\u001b[34m\u001b[1mval: \u001b[0mNew cache created: /content/dataset/labels/test.cache\n" + ] + }, + { + "output_type": "stream", + "name": "stderr", + "text": [ + "\n" + ] + }, + { + "output_type": "stream", + "name": "stdout", + "text": [ + "Plotting labels to runs/detect/detector2/labels.jpg... \n", + "\u001b[34m\u001b[1moptimizer:\u001b[0m 'optimizer=auto' found, ignoring 'lr0=0.001' and 'momentum=0.937' and determining best 'optimizer', 'lr0' and 'momentum' automatically... \n", + "\u001b[34m\u001b[1moptimizer:\u001b[0m AdamW(lr=0.00125, momentum=0.9) with parameter groups 77 weight(decay=0.0), 84 weight(decay=0.0005), 83 bias(decay=0.0)\n", + "Image sizes 640 train, 640 val\n", + "Using 2 dataloader workers\n", + "Logging results to 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[00:00<00:00, 5.10it/s]" + ] + }, + { + "output_type": "stream", + "name": "stdout", + "text": [ + " all 40 40 0.105 0.2 0.066 0.0279\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": [ + " 3/45 3.96G 1.947 2.69 1.951 15 640: 100%|██████████| 20/20 [00:06<00:00, 3.30it/s]\n", + " Class Images Instances Box(P R mAP50 mAP50-95): 100%|██████████| 3/3 [00:00<00:00, 5.24it/s]" + ] + }, + { + "output_type": "stream", + "name": "stdout", + "text": [ + " all 40 40 0.016 0.05 0.0131 0.00572\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", + 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1.278 1.64 8 640: 100%|██████████| 20/20 [00:05<00:00, 3.64it/s]\n", + " Class Images Instances Box(P R mAP50 mAP50-95): 100%|██████████| 3/3 [00:00<00:00, 4.95it/s]" + ] + }, + { + "output_type": "stream", + "name": "stdout", + "text": [ + " all 40 40 0.86 0.675 0.796 0.503\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": [ + " 45/45 6.04G 1.377 1.288 1.615 8 640: 100%|██████████| 20/20 [00:05<00:00, 3.45it/s]\n", + " Class Images Instances Box(P R mAP50 mAP50-95): 100%|██████████| 3/3 [00:00<00:00, 4.90it/s]" + ] + }, + { + "output_type": "stream", + "name": "stdout", + "text": [ + " all 40 40 0.855 0.675 0.78 0.508\n" + ] + }, + { + "output_type": "stream", + "name": "stderr", + "text": [ + "\n" + ] + }, + { + "output_type": "stream", + "name": "stdout", + "text": [ + "\n", + "45 epochs completed in 0.111 hours.\n", + "Optimizer stripped from runs/detect/detector2/weights/last.pt, 52.0MB\n", + "Optimizer stripped from runs/detect/detector2/weights/best.pt, 52.0MB\n", + "\n", + "Validating runs/detect/detector2/weights/best.pt...\n", + "Ultralytics 8.3.144 🚀 Python-3.11.12 torch-2.6.0+cu124 CUDA:0 (Tesla T4, 15095MiB)\n", + "Model summary (fused): 92 layers, 25,842,076 parameters, 0 gradients, 78.7 GFLOPs\n" + ] + }, + { + "output_type": "stream", + "name": "stderr", + "text": [ + " Class Images Instances Box(P R mAP50 mAP50-95): 100%|██████████| 3/3 [00:02<00:00, 1.48it/s]\n" + ] + }, + { + "output_type": "stream", + "name": "stdout", + "text": [ + " all 40 40 0.681 0.725 0.731 0.468\n", + " fork 10 10 0.338 0.2 0.265 0.113\n", + " glass 10 10 0.643 0.9 0.888 0.432\n", + " plate 10 10 1 1 0.995 0.833\n", + " spoon 10 10 0.744 0.8 0.776 0.496\n", + "Speed: 1.5ms preprocess, 39.2ms inference, 0.0ms loss, 3.2ms postprocess per image\n", + "Results saved to \u001b[1mruns/detect/detector2\u001b[0m\n" + ] + }, + { + "output_type": "execute_result", + "data": { + "text/plain": [ + "ultralytics.utils.metrics.DetMetrics object with attributes:\n", + "\n", + "ap_class_index: array([0, 1, 2, 3])\n", + "box: ultralytics.utils.metrics.Metric object\n", + "confusion_matrix: \n", + "curves: ['Precision-Recall(B)', 'F1-Confidence(B)', 'Precision-Confidence(B)', 'Recall-Confidence(B)']\n", + "curves_results: [[array([ 0, 0.001001, 0.002002, 0.003003, 0.004004, 0.005005, 0.006006, 0.007007, 0.008008, 0.009009, 0.01001, 0.011011, 0.012012, 0.013013, 0.014014, 0.015015, 0.016016, 0.017017, 0.018018, 0.019019, 0.02002, 0.021021, 0.022022, 0.023023,\n", + " 0.024024, 0.025025, 0.026026, 0.027027, 0.028028, 0.029029, 0.03003, 0.031031, 0.032032, 0.033033, 0.034034, 0.035035, 0.036036, 0.037037, 0.038038, 0.039039, 0.04004, 0.041041, 0.042042, 0.043043, 0.044044, 0.045045, 0.046046, 0.047047,\n", + " 0.048048, 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"names: {0: 'fork', 1: 'glass', 2: 'plate', 3: 'spoon'}\n", + "plot: True\n", + "results_dict: {'metrics/precision(B)': np.float64(0.6812832632376996), 'metrics/recall(B)': np.float64(0.7250000000000001), 'metrics/mAP50(B)': np.float64(0.7312101093351093), 'metrics/mAP50-95(B)': np.float64(0.4684609515484516), 'fitness': np.float64(0.49473586732711733)}\n", + "save_dir: PosixPath('runs/detect/detector2')\n", + "speed: {'preprocess': 1.4666298250062937, 'inference': 39.15243917499538, 'loss': 0.000886350017026416, 'postprocess': 3.1747297000151775}\n", + "task: 'detect'" + ] + }, + "metadata": {}, + "execution_count": 1 + } + ] + }, + { + "cell_type": "code", + "source": [ + "\n" + ], + "metadata": { + "id": "6Woe2o0hGbu9" + }, + "execution_count": null, + "outputs": [] + } + ] +} \ No newline at end of file