yolo_training.ipynb

{
  "nbformat": 4,
  "nbformat_minor": 0,
  "metadata": {
    "colab": {
      "provenance": [],
      "machine_shape": "hm",
      "gpuType": "T4"
    },
    "kernelspec": {
      "name": "python3",
      "display_name": "Python 3"
    },
    "language_info": {
      "name": "python"
    },
    "accelerator": "GPU"
  },
  "cells": [
    {
      "cell_type": "code",
      "execution_count": 1,
      "metadata": {
        "id": "emnOGViyuu3C"
      },
      "outputs": [],
      "source": [
        "import os\n",
        "os.chdir('/content/drive/MyDrive/yolo_training')"
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "ls"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "fAasrJ3dvU7Y",
        "outputId": "d705fc1c-e656-403c-9eff-00e6f62f8c98"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "yolo_training_2.ipynb\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "!git clone https://github.com/ultralytics/yolov5.git"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "ezT_b2O6vWOt",
        "outputId": "bd67f21c-2ca9-4457-c5eb-e45df97ab467"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Cloning into 'yolov5'...\n",
            "remote: Enumerating objects: 16057, done.\u001b[K\n",
            "remote: Total 16057 (delta 0), reused 0 (delta 0), pack-reused 16057\u001b[K\n",
            "Receiving objects: 100% (16057/16057), 14.68 MiB | 14.76 MiB/s, done.\n",
            "Resolving deltas: 100% (11032/11032), done.\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "os.chdir('yolov5')"
      ],
      "metadata": {
        "id": "f_swrXxcveyh"
      },
      "execution_count": 2,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "ls"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "T51Fd2FzSA8o",
        "outputId": "898d2f0b-a56e-44d2-dd74-4168afe583eb"
      },
      "execution_count": 3,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "benchmarks.py    \u001b[0m\u001b[01;34mdata\u001b[0m/         export.py   \u001b[01;34m__pycache__\u001b[0m/      \u001b[01;34mruns\u001b[0m/      tutorial.ipynb\n",
            "CITATION.cff     \u001b[01;34mdata_images\u001b[0m/  hubconf.py  README.md         \u001b[01;34msegment\u001b[0m/   \u001b[01;34mutils\u001b[0m/\n",
            "\u001b[01;34mclassify\u001b[0m/        data.yaml     LICENSE     README.zh-CN.md   setup.cfg  val.py\n",
            "CONTRIBUTING.md  detect.py     \u001b[01;34mmodels\u001b[0m/     requirements.txt  train.py   yolov5s.pt\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "!pip install -r requirements.txt"
      ],
      "metadata": {
        "id": "g2arp2FuSBOm"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "!python train.py --data data.yaml --weights yolov5s.pt --img 512 --batch-size 8 --name Model --epochs 1"
      ],
      "metadata": {
        "id": "cnaUuG34SauS",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "78b52ac3-89f6-47eb-e2e5-58f109792be2"
      },
      "execution_count": 4,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "2023-11-15 23:45:59.348911: E tensorflow/compiler/xla/stream_executor/cuda/cuda_dnn.cc:9342] Unable to register cuDNN factory: Attempting to register factory for plugin cuDNN when one has already been registered\n",
            "2023-11-15 23:45:59.348970: E tensorflow/compiler/xla/stream_executor/cuda/cuda_fft.cc:609] Unable to register cuFFT factory: Attempting to register factory for plugin cuFFT when one has already been registered\n",
            "2023-11-15 23:45:59.348998: E tensorflow/compiler/xla/stream_executor/cuda/cuda_blas.cc:1518] Unable to register cuBLAS factory: Attempting to register factory for plugin cuBLAS when one has already been registered\n",
            "\u001b[34m\u001b[1mtrain: \u001b[0mweights=yolov5s.pt, cfg=, data=data.yaml, hyp=data/hyps/hyp.scratch-low.yaml, epochs=1, batch_size=8, imgsz=512, rect=False, resume=False, nosave=False, noval=False, noautoanchor=False, noplots=False, evolve=None, bucket=, cache=None, image_weights=False, device=, multi_scale=False, single_cls=False, optimizer=SGD, sync_bn=False, workers=8, project=runs/train, name=Model, exist_ok=False, quad=False, cos_lr=False, label_smoothing=0.0, patience=100, freeze=[0], save_period=-1, seed=0, local_rank=-1, entity=None, upload_dataset=False, bbox_interval=-1, artifact_alias=latest\n",
            "Command 'git fetch origin' timed out after 5 seconds\n",
            "YOLOv5 🚀 v7.0-240-g84ec8b5 Python-3.10.12 torch-2.1.0+cu118 CUDA:0 (Tesla T4, 15102MiB)\n",
            "\n",
            "\u001b[34m\u001b[1mhyperparameters: \u001b[0mlr0=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=0.05, cls=0.5, cls_pw=1.0, obj=1.0, obj_pw=1.0, iou_t=0.2, anchor_t=4.0, fl_gamma=0.0, hsv_h=0.015, hsv_s=0.7, hsv_v=0.4, degrees=0.0, translate=0.1, scale=0.5, shear=0.0, perspective=0.0, flipud=0.0, fliplr=0.5, mosaic=1.0, mixup=0.0, copy_paste=0.0\n",
            "\u001b[34m\u001b[1mComet: \u001b[0mrun 'pip install comet_ml' to automatically track and visualize YOLOv5 🚀 runs in Comet\n",
            "\u001b[34m\u001b[1mTensorBoard: \u001b[0mStart with 'tensorboard --logdir runs/train', view at http://localhost:6006/\n",
            "Downloading https://ultralytics.com/assets/Arial.ttf to /root/.config/Ultralytics/Arial.ttf...\n",
            "100% 755k/755k [00:00<00:00, 86.6MB/s]\n",
            "Overriding model.yaml nc=80 with nc=21\n",
            "\n",
            "                 from  n    params  module                                  arguments                     \n",
            "  0                -1  1      3520  models.common.Conv                      [3, 32, 6, 2, 2]              \n",
            "  1                -1  1     18560  models.common.Conv                      [32, 64, 3, 2]                \n",
            "  2                -1  1     18816  models.common.C3                        [64, 64, 1]                   \n",
            "  3                -1  1     73984  models.common.Conv                      [64, 128, 3, 2]               \n",
            "  4                -1  2    115712  models.common.C3                        [128, 128, 2]                 \n",
            "  5                -1  1    295424  models.common.Conv                      [128, 256, 3, 2]              \n",
            "  6                -1  3    625152  models.common.C3                        [256, 256, 3]                 \n",
            "  7                -1  1   1180672  models.common.Conv                      [256, 512, 3, 2]              \n",
            "  8                -1  1   1182720  models.common.C3                        [512, 512, 1]                 \n",
            "  9                -1  1    656896  models.common.SPPF                      [512, 512, 5]                 \n",
            " 10                -1  1    131584  models.common.Conv                      [512, 256, 1, 1]              \n",
            " 11                -1  1         0  torch.nn.modules.upsampling.Upsample    [None, 2, 'nearest']          \n",
            " 12           [-1, 6]  1         0  models.common.Concat                    [1]                           \n",
            " 13                -1  1    361984  models.common.C3                        [512, 256, 1, False]          \n",
            " 14                -1  1     33024  models.common.Conv                      [256, 128, 1, 1]              \n",
            " 15                -1  1         0  torch.nn.modules.upsampling.Upsample    [None, 2, 'nearest']          \n",
            " 16           [-1, 4]  1         0  models.common.Concat                    [1]                           \n",
            " 17                -1  1     90880  models.common.C3                        [256, 128, 1, False]          \n",
            " 18                -1  1    147712  models.common.Conv                      [128, 128, 3, 2]              \n",
            " 19          [-1, 14]  1         0  models.common.Concat                    [1]                           \n",
            " 20                -1  1    296448  models.common.C3                        [256, 256, 1, False]          \n",
            " 21                -1  1    590336  models.common.Conv                      [256, 256, 3, 2]              \n",
            " 22          [-1, 10]  1         0  models.common.Concat                    [1]                           \n",
            " 23                -1  1   1182720  models.common.C3                        [512, 512, 1, False]          \n",
            " 24      [17, 20, 23]  1     70122  models.yolo.Detect                      [21, [[10, 13, 16, 30, 33, 23], [30, 61, 62, 45, 59, 119], [116, 90, 156, 198, 373, 326]], [128, 256, 512]]\n",
            "Model summary: 214 layers, 7076266 parameters, 7076266 gradients, 16.1 GFLOPs\n",
            "\n",
            "Transferred 343/349 items from yolov5s.pt\n",
            "\u001b[34m\u001b[1mAMP: \u001b[0mchecks passed ✅\n",
            "\u001b[34m\u001b[1moptimizer:\u001b[0m SGD(lr=0.01) with parameter groups 57 weight(decay=0.0), 60 weight(decay=0.0005), 60 bias\n",
            "\u001b[34m\u001b[1malbumentations: \u001b[0mBlur(p=0.01, blur_limit=(3, 7)), MedianBlur(p=0.01, blur_limit=(3, 7)), ToGray(p=0.01), CLAHE(p=0.01, clip_limit=(1, 4.0), tile_grid_size=(8, 8))\n",
            "\u001b[34m\u001b[1mtrain: \u001b[0mScanning /content/drive/MyDrive/yolo_training/yolov5/data_images/train_yolo... 7388 images, 3 backgrounds, 0 corrupt: 100% 7391/7391 [03:29<00:00, 35.36it/s] \n",
            "\u001b[34m\u001b[1mtrain: \u001b[0mNew cache created: /content/drive/MyDrive/yolo_training/yolov5/data_images/train_yolo.cache\n",
            "\u001b[34m\u001b[1mval: \u001b[0mScanning /content/drive/MyDrive/yolo_training/yolov5/data_images/test_yolo... 1847 images, 0 backgrounds, 0 corrupt: 100% 1847/1847 [00:54<00:00, 34.08it/s] \n",
            "\u001b[34m\u001b[1mval: \u001b[0mNew cache created: /content/drive/MyDrive/yolo_training/yolov5/data_images/test_yolo.cache\n",
            "\n",
            "\u001b[34m\u001b[1mAutoAnchor: \u001b[0m4.57 anchors/target, 1.000 Best Possible Recall (BPR). Current anchors are a good fit to dataset ✅\n",
            "Plotting labels to runs/train/Model/labels.jpg... \n",
            "Image sizes 512 train, 512 val\n",
            "Using 8 dataloader workers\n",
            "Logging results to \u001b[1mruns/train/Model\u001b[0m\n",
            "Starting training for 1 epochs...\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   obj_loss   cls_loss  Instances       Size\n",
            "        0/0      1.28G    0.05548     0.0342    0.07242         25        512: 100% 924/924 [01:30<00:00, 10.18it/s]\n",
            "                 Class     Images  Instances          P          R      mAP50   mAP50-95: 100% 116/116 [00:19<00:00,  5.86it/s]\n",
            "                   all       1847       3134      0.347      0.129     0.0918     0.0608\n",
            "\n",
            "1 epochs completed in 0.031 hours.\n",
            "Optimizer stripped from runs/train/Model/weights/last.pt, 14.4MB\n",
            "Optimizer stripped from runs/train/Model/weights/best.pt, 14.4MB\n",
            "\n",
            "Validating runs/train/Model/weights/best.pt...\n",
            "Fusing layers... \n",
            "Model summary: 157 layers, 7066762 parameters, 0 gradients, 15.9 GFLOPs\n",
            "                 Class     Images  Instances          P          R      mAP50   mAP50-95: 100% 116/116 [00:18<00:00,  6.24it/s]\n",
            "                   all       1847       3134      0.347      0.129     0.0918     0.0609\n",
            "                 Pants       1847        206      0.135       0.35      0.127     0.0824\n",
            "              Handbags       1847        198          1          0     0.0218     0.0142\n",
            "                Shirts       1847        208      0.268    0.00386     0.0296       0.02\n",
            "                 Shoes       1847        186          0          0     0.0168     0.0102\n",
            "               Scarves       1847        211          0          0     0.0459     0.0333\n",
            "               Jewelry       1847        209          0          0     0.0188     0.0121\n",
            "                Skirts       1847        189          0          0     0.0482     0.0309\n",
            "                 Coats       1847        204     0.0657     0.0245     0.0571     0.0415\n",
            "                  Hats       1847        195      0.135    0.00513     0.0752     0.0587\n",
            "               Dresses       1847        199      0.139      0.663      0.243      0.161\n",
            "                Shorts       1847        210          1          0      0.115     0.0797\n",
            "               Watches       1847        183      0.268       0.94      0.616      0.385\n",
            "            Sunglasses       1847        189      0.274      0.725       0.37      0.258\n",
            "             Jumpsuits       1847         60          1          0     0.0231      0.014\n",
            "                 Socks       1847        153          0          0     0.0277     0.0175\n",
            "                 Rings       1847        113          0          0     0.0197      0.013\n",
            "                 Belts       1847        139          0          0     0.0571     0.0369\n",
            "                Gloves       1847         14          1          0    0.00164    0.00119\n",
            "              Swimwear       1847         40          1          0    0.00699    0.00473\n",
            "             Stockings       1847         24          0          0    0.00774    0.00469\n",
            "              Neckties       1847          4          1          0    0.00053   0.000409\n",
            "Results saved to \u001b[1mruns/train/Model\u001b[0m\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "!python train.py --data data.yaml --weights runs/train/Model/weights/best.pt --img 512 --batch-size 8 --name Model --epochs 100"
      ],
      "metadata": {
        "id": "72UnojGZT0Bk",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "90f028fd-0ffa-45b9-c7a3-542a16ec61f5"
      },
      "execution_count": 5,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "2023-11-15 23:55:11.554983: E tensorflow/compiler/xla/stream_executor/cuda/cuda_dnn.cc:9342] Unable to register cuDNN factory: Attempting to register factory for plugin cuDNN when one has already been registered\n",
            "2023-11-15 23:55:11.555031: E tensorflow/compiler/xla/stream_executor/cuda/cuda_fft.cc:609] Unable to register cuFFT factory: Attempting to register factory for plugin cuFFT when one has already been registered\n",
            "2023-11-15 23:55:11.555064: E tensorflow/compiler/xla/stream_executor/cuda/cuda_blas.cc:1518] Unable to register cuBLAS factory: Attempting to register factory for plugin cuBLAS when one has already been registered\n",
            "\u001b[34m\u001b[1mtrain: \u001b[0mweights=runs/train/Model/weights/best.pt, cfg=, data=data.yaml, hyp=data/hyps/hyp.scratch-low.yaml, epochs=100, batch_size=8, imgsz=512, rect=False, resume=False, nosave=False, noval=False, noautoanchor=False, noplots=False, evolve=None, bucket=, cache=None, image_weights=False, device=, multi_scale=False, single_cls=False, optimizer=SGD, sync_bn=False, workers=8, project=runs/train, name=Model, exist_ok=False, quad=False, cos_lr=False, label_smoothing=0.0, patience=100, freeze=[0], save_period=-1, seed=0, local_rank=-1, entity=None, upload_dataset=False, bbox_interval=-1, artifact_alias=latest\n",
            "\u001b[34m\u001b[1mgithub: \u001b[0mup to date with https://github.com/ultralytics/yolov5 ✅\n",
            "YOLOv5 🚀 v7.0-240-g84ec8b5 Python-3.10.12 torch-2.1.0+cu118 CUDA:0 (Tesla T4, 15102MiB)\n",
            "\n",
            "\u001b[34m\u001b[1mhyperparameters: \u001b[0mlr0=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=0.05, cls=0.5, cls_pw=1.0, obj=1.0, obj_pw=1.0, iou_t=0.2, anchor_t=4.0, fl_gamma=0.0, hsv_h=0.015, hsv_s=0.7, hsv_v=0.4, degrees=0.0, translate=0.1, scale=0.5, shear=0.0, perspective=0.0, flipud=0.0, fliplr=0.5, mosaic=1.0, mixup=0.0, copy_paste=0.0\n",
            "\u001b[34m\u001b[1mComet: \u001b[0mrun 'pip install comet_ml' to automatically track and visualize YOLOv5 🚀 runs in Comet\n",
            "\u001b[34m\u001b[1mTensorBoard: \u001b[0mStart with 'tensorboard --logdir runs/train', view at http://localhost:6006/\n",
            "\n",
            "                 from  n    params  module                                  arguments                     \n",
            "  0                -1  1      3520  models.common.Conv                      [3, 32, 6, 2, 2]              \n",
            "  1                -1  1     18560  models.common.Conv                      [32, 64, 3, 2]                \n",
            "  2                -1  1     18816  models.common.C3                        [64, 64, 1]                   \n",
            "  3                -1  1     73984  models.common.Conv                      [64, 128, 3, 2]               \n",
            "  4                -1  2    115712  models.common.C3                        [128, 128, 2]                 \n",
            "  5                -1  1    295424  models.common.Conv                      [128, 256, 3, 2]              \n",
            "  6                -1  3    625152  models.common.C3                        [256, 256, 3]                 \n",
            "  7                -1  1   1180672  models.common.Conv                      [256, 512, 3, 2]              \n",
            "  8                -1  1   1182720  models.common.C3                        [512, 512, 1]                 \n",
            "  9                -1  1    656896  models.common.SPPF                      [512, 512, 5]                 \n",
            " 10                -1  1    131584  models.common.Conv                      [512, 256, 1, 1]              \n",
            " 11                -1  1         0  torch.nn.modules.upsampling.Upsample    [None, 2, 'nearest']          \n",
            " 12           [-1, 6]  1         0  models.common.Concat                    [1]                           \n",
            " 13                -1  1    361984  models.common.C3                        [512, 256, 1, False]          \n",
            " 14                -1  1     33024  models.common.Conv                      [256, 128, 1, 1]              \n",
            " 15                -1  1         0  torch.nn.modules.upsampling.Upsample    [None, 2, 'nearest']          \n",
            " 16           [-1, 4]  1         0  models.common.Concat                    [1]                           \n",
            " 17                -1  1     90880  models.common.C3                        [256, 128, 1, False]          \n",
            " 18                -1  1    147712  models.common.Conv                      [128, 128, 3, 2]              \n",
            " 19          [-1, 14]  1         0  models.common.Concat                    [1]                           \n",
            " 20                -1  1    296448  models.common.C3                        [256, 256, 1, False]          \n",
            " 21                -1  1    590336  models.common.Conv                      [256, 256, 3, 2]              \n",
            " 22          [-1, 10]  1         0  models.common.Concat                    [1]                           \n",
            " 23                -1  1   1182720  models.common.C3                        [512, 512, 1, False]          \n",
            " 24      [17, 20, 23]  1     70122  models.yolo.Detect                      [21, [[10, 13, 16, 30, 33, 23], [30, 61, 62, 45, 59, 119], [116, 90, 156, 198, 373, 326]], [128, 256, 512]]\n",
            "Model summary: 214 layers, 7076266 parameters, 7076266 gradients, 16.1 GFLOPs\n",
            "\n",
            "Transferred 349/349 items from runs/train/Model/weights/best.pt\n",
            "\u001b[34m\u001b[1mAMP: \u001b[0mchecks passed ✅\n",
            "\u001b[34m\u001b[1moptimizer:\u001b[0m SGD(lr=0.01) with parameter groups 57 weight(decay=0.0), 60 weight(decay=0.0005), 60 bias\n",
            "\u001b[34m\u001b[1malbumentations: \u001b[0mBlur(p=0.01, blur_limit=(3, 7)), MedianBlur(p=0.01, blur_limit=(3, 7)), ToGray(p=0.01), CLAHE(p=0.01, clip_limit=(1, 4.0), tile_grid_size=(8, 8))\n",
            "\u001b[34m\u001b[1mtrain: \u001b[0mScanning /content/drive/MyDrive/yolo_training/yolov5/data_images/train_yolo.cache... 7388 images, 3 backgrounds, 0 corrupt: 100% 7391/7391 [00:00<?, ?it/s]\n",
            "\u001b[34m\u001b[1mval: \u001b[0mScanning /content/drive/MyDrive/yolo_training/yolov5/data_images/test_yolo.cache... 1847 images, 0 backgrounds, 0 corrupt: 100% 1847/1847 [00:00<?, ?it/s]\n",
            "\n",
            "\u001b[34m\u001b[1mAutoAnchor: \u001b[0m4.57 anchors/target, 1.000 Best Possible Recall (BPR). Current anchors are a good fit to dataset ✅\n",
            "Plotting labels to runs/train/Model2/labels.jpg... \n",
            "Image sizes 512 train, 512 val\n",
            "Using 8 dataloader workers\n",
            "Logging results to \u001b[1mruns/train/Model2\u001b[0m\n",
            "Starting training for 100 epochs...\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   obj_loss   cls_loss  Instances       Size\n",
            "       0/99      1.28G    0.03015    0.03175    0.05952         25        512: 100% 924/924 [01:29<00:00, 10.32it/s]\n",
            "                 Class     Images  Instances          P          R      mAP50   mAP50-95: 100% 116/116 [00:18<00:00,  6.34it/s]\n",
            "                   all       1847       3134       0.42      0.218       0.15      0.104\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   obj_loss   cls_loss  Instances       Size\n",
            "       1/99      1.28G    0.03515    0.02958    0.04763         28        512: 100% 924/924 [01:25<00:00, 10.77it/s]\n",
            "                 Class     Images  Instances          P          R      mAP50   mAP50-95: 100% 116/116 [00:16<00:00,  6.96it/s]\n",
            "                   all       1847       3134      0.498      0.378      0.283       0.19\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   obj_loss   cls_loss  Instances       Size\n",
            "       2/99      1.28G    0.03503    0.02883    0.03694         20        512: 100% 924/924 [01:24<00:00, 10.95it/s]\n",
            "                 Class     Images  Instances          P          R      mAP50   mAP50-95: 100% 116/116 [00:16<00:00,  6.88it/s]\n",
            "                   all       1847       3134      0.481      0.464      0.325      0.213\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   obj_loss   cls_loss  Instances       Size\n",
            "       3/99      1.28G    0.03266    0.02944    0.03304         16        512: 100% 924/924 [01:24<00:00, 10.99it/s]\n",
            "                 Class     Images  Instances          P          R      mAP50   mAP50-95: 100% 116/116 [00:16<00:00,  6.98it/s]\n",
            "                   all       1847       3134      0.517      0.495      0.346      0.242\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   obj_loss   cls_loss  Instances       Size\n",
            "       4/99      1.28G    0.03058    0.02969     0.0305         15        512: 100% 924/924 [01:24<00:00, 11.00it/s]\n",
            "                 Class     Images  Instances          P          R      mAP50   mAP50-95: 100% 116/116 [00:16<00:00,  6.99it/s]\n",
            "                   all       1847       3134      0.509      0.503      0.392      0.277\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   obj_loss   cls_loss  Instances       Size\n",
            "       5/99      1.28G    0.02896    0.02901    0.02855         30        512: 100% 924/924 [01:23<00:00, 11.11it/s]\n",
            "                 Class     Images  Instances          P          R      mAP50   mAP50-95: 100% 116/116 [00:16<00:00,  7.16it/s]\n",
            "                   all       1847       3134      0.415      0.628      0.417      0.307\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   obj_loss   cls_loss  Instances       Size\n",
            "       6/99      1.28G    0.02783    0.02888    0.02712         30        512: 100% 924/924 [01:22<00:00, 11.16it/s]\n",
            "                 Class     Images  Instances          P          R      mAP50   mAP50-95: 100% 116/116 [00:15<00:00,  7.28it/s]\n",
            "                   all       1847       3134      0.477      0.578       0.43      0.318\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   obj_loss   cls_loss  Instances       Size\n",
            "       7/99      1.28G    0.02723    0.02876    0.02531         20        512: 100% 924/924 [01:23<00:00, 11.12it/s]\n",
            "                 Class     Images  Instances          P          R      mAP50   mAP50-95: 100% 116/116 [00:15<00:00,  7.25it/s]\n",
            "                   all       1847       3134      0.456      0.603      0.455      0.338\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   obj_loss   cls_loss  Instances       Size\n",
            "       8/99      1.28G    0.02701    0.02881    0.02486         12        512: 100% 924/924 [01:23<00:00, 11.12it/s]\n",
            "                 Class     Images  Instances          P          R      mAP50   mAP50-95: 100% 116/116 [00:16<00:00,  7.24it/s]\n",
            "                   all       1847       3134      0.468      0.601      0.472      0.356\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   obj_loss   cls_loss  Instances       Size\n",
            "       9/99      1.28G    0.02627    0.02855    0.02474         22        512: 100% 924/924 [01:23<00:00, 11.10it/s]\n",
            "                 Class     Images  Instances          P          R      mAP50   mAP50-95: 100% 116/116 [00:16<00:00,  7.20it/s]\n",
            "                   all       1847       3134      0.522      0.583      0.468      0.352\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   obj_loss   cls_loss  Instances       Size\n",
            "      10/99      1.28G    0.02577    0.02827    0.02283         36        512: 100% 924/924 [01:22<00:00, 11.16it/s]\n",
            "                 Class     Images  Instances          P          R      mAP50   mAP50-95: 100% 116/116 [00:16<00:00,  7.19it/s]\n",
            "                   all       1847       3134      0.518      0.618      0.494      0.372\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   obj_loss   cls_loss  Instances       Size\n",
            "      11/99      1.28G    0.02522    0.02811    0.02222         18        512: 100% 924/924 [01:22<00:00, 11.16it/s]\n",
            "                 Class     Images  Instances          P          R      mAP50   mAP50-95: 100% 116/116 [00:15<00:00,  7.27it/s]\n",
            "                   all       1847       3134      0.479      0.618      0.477       0.36\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   obj_loss   cls_loss  Instances       Size\n",
            "      12/99      1.28G    0.02469    0.02744    0.02123         26        512: 100% 924/924 [01:22<00:00, 11.14it/s]\n",
            "                 Class     Images  Instances          P          R      mAP50   mAP50-95: 100% 116/116 [00:15<00:00,  7.41it/s]\n",
            "                   all       1847       3134      0.499      0.633      0.511      0.392\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   obj_loss   cls_loss  Instances       Size\n",
            "      13/99      1.28G    0.02458    0.02765    0.02104         19        512: 100% 924/924 [01:23<00:00, 11.09it/s]\n",
            "                 Class     Images  Instances          P          R      mAP50   mAP50-95: 100% 116/116 [00:16<00:00,  7.24it/s]\n",
            "                   all       1847       3134      0.492      0.643      0.509      0.398\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   obj_loss   cls_loss  Instances       Size\n",
            "      14/99      1.28G    0.02441     0.0282    0.02051         24        512: 100% 924/924 [01:23<00:00, 11.11it/s]\n",
            "                 Class     Images  Instances          P          R      mAP50   mAP50-95: 100% 116/116 [00:15<00:00,  7.32it/s]\n",
            "                   all       1847       3134      0.485      0.634      0.506      0.392\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   obj_loss   cls_loss  Instances       Size\n",
            "      15/99      1.28G    0.02415    0.02747    0.02033         29        512: 100% 924/924 [01:22<00:00, 11.17it/s]\n",
            "                 Class     Images  Instances          P          R      mAP50   mAP50-95: 100% 116/116 [00:15<00:00,  7.31it/s]\n",
            "                   all       1847       3134      0.532      0.606      0.518       0.41\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   obj_loss   cls_loss  Instances       Size\n",
            "      16/99      1.28G    0.02379    0.02747    0.01909         23        512: 100% 924/924 [01:23<00:00, 11.11it/s]\n",
            "                 Class     Images  Instances          P          R      mAP50   mAP50-95: 100% 116/116 [00:15<00:00,  7.35it/s]\n",
            "                   all       1847       3134      0.494      0.648      0.515      0.409\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   obj_loss   cls_loss  Instances       Size\n",
            "      17/99      1.28G     0.0237    0.02708    0.01976         39        512: 100% 924/924 [01:23<00:00, 11.12it/s]\n",
            "                 Class     Images  Instances          P          R      mAP50   mAP50-95: 100% 116/116 [00:15<00:00,  7.39it/s]\n",
            "                   all       1847       3134      0.514      0.629      0.507      0.391\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   obj_loss   cls_loss  Instances       Size\n",
            "      18/99      1.28G    0.02315    0.02745    0.01895         30        512: 100% 924/924 [01:22<00:00, 11.14it/s]\n",
            "                 Class     Images  Instances          P          R      mAP50   mAP50-95: 100% 116/116 [00:15<00:00,  7.42it/s]\n",
            "                   all       1847       3134      0.506      0.638      0.526      0.408\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   obj_loss   cls_loss  Instances       Size\n",
            "      19/99      1.28G    0.02316    0.02703     0.0187         17        512: 100% 924/924 [01:22<00:00, 11.13it/s]\n",
            "                 Class     Images  Instances          P          R      mAP50   mAP50-95: 100% 116/116 [00:15<00:00,  7.30it/s]\n",
            "                   all       1847       3134      0.507      0.651      0.532      0.416\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   obj_loss   cls_loss  Instances       Size\n",
            "      20/99      1.28G    0.02279    0.02723    0.01741         23        512: 100% 924/924 [01:22<00:00, 11.15it/s]\n",
            "                 Class     Images  Instances          P          R      mAP50   mAP50-95: 100% 116/116 [00:15<00:00,  7.35it/s]\n",
            "                   all       1847       3134      0.504      0.652      0.524      0.419\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   obj_loss   cls_loss  Instances       Size\n",
            "      21/99      1.28G    0.02275    0.02711    0.01723         20        512: 100% 924/924 [01:23<00:00, 11.12it/s]\n",
            "                 Class     Images  Instances          P          R      mAP50   mAP50-95: 100% 116/116 [00:16<00:00,  7.14it/s]\n",
            "                   all       1847       3134      0.541      0.636      0.536      0.423\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   obj_loss   cls_loss  Instances       Size\n",
            "      22/99      1.28G    0.02296    0.02676    0.01824         26        512: 100% 924/924 [01:23<00:00, 11.02it/s]\n",
            "                 Class     Images  Instances          P          R      mAP50   mAP50-95: 100% 116/116 [00:15<00:00,  7.27it/s]\n",
            "                   all       1847       3134      0.507      0.639      0.534      0.426\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   obj_loss   cls_loss  Instances       Size\n",
            "      23/99      1.28G    0.02257     0.0271    0.01751         18        512: 100% 924/924 [01:23<00:00, 11.13it/s]\n",
            "                 Class     Images  Instances          P          R      mAP50   mAP50-95: 100% 116/116 [00:15<00:00,  7.39it/s]\n",
            "                   all       1847       3134       0.52      0.647      0.541      0.431\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   obj_loss   cls_loss  Instances       Size\n",
            "      24/99      1.28G    0.02246    0.02713    0.01666         19        512: 100% 924/924 [01:23<00:00, 11.02it/s]\n",
            "                 Class     Images  Instances          P          R      mAP50   mAP50-95: 100% 116/116 [00:15<00:00,  7.27it/s]\n",
            "                   all       1847       3134      0.512      0.659      0.539      0.429\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   obj_loss   cls_loss  Instances       Size\n",
            "      25/99      1.28G    0.02241    0.02674      0.017         24        512: 100% 924/924 [01:23<00:00, 11.13it/s]\n",
            "                 Class     Images  Instances          P          R      mAP50   mAP50-95: 100% 116/116 [00:16<00:00,  7.20it/s]\n",
            "                   all       1847       3134      0.491      0.667       0.54      0.432\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   obj_loss   cls_loss  Instances       Size\n",
            "      26/99      1.28G    0.02214    0.02673    0.01681         39        512: 100% 924/924 [01:23<00:00, 11.11it/s]\n",
            "                 Class     Images  Instances          P          R      mAP50   mAP50-95: 100% 116/116 [00:15<00:00,  7.36it/s]\n",
            "                   all       1847       3134      0.529      0.627      0.547      0.438\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   obj_loss   cls_loss  Instances       Size\n",
            "      27/99      1.28G    0.02204    0.02667      0.016         18        512: 100% 924/924 [01:23<00:00, 11.05it/s]\n",
            "                 Class     Images  Instances          P          R      mAP50   mAP50-95: 100% 116/116 [00:15<00:00,  7.41it/s]\n",
            "                   all       1847       3134      0.539      0.643      0.561      0.453\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   obj_loss   cls_loss  Instances       Size\n",
            "      28/99      1.28G      0.022    0.02645    0.01638         22        512: 100% 924/924 [01:22<00:00, 11.19it/s]\n",
            "                 Class     Images  Instances          P          R      mAP50   mAP50-95: 100% 116/116 [00:15<00:00,  7.33it/s]\n",
            "                   all       1847       3134      0.518      0.646      0.551      0.441\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   obj_loss   cls_loss  Instances       Size\n",
            "      29/99      1.28G     0.0216    0.02636    0.01609         31        512: 100% 924/924 [01:22<00:00, 11.14it/s]\n",
            "                 Class     Images  Instances          P          R      mAP50   mAP50-95: 100% 116/116 [00:15<00:00,  7.37it/s]\n",
            "                   all       1847       3134      0.518      0.671      0.554      0.446\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   obj_loss   cls_loss  Instances       Size\n",
            "      30/99      1.28G     0.0217    0.02652    0.01548         12        512: 100% 924/924 [01:23<00:00, 11.12it/s]\n",
            "                 Class     Images  Instances          P          R      mAP50   mAP50-95: 100% 116/116 [00:15<00:00,  7.34it/s]\n",
            "                   all       1847       3134      0.533      0.645      0.554      0.446\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   obj_loss   cls_loss  Instances       Size\n",
            "      31/99      1.28G    0.02151    0.02679    0.01534         28        512: 100% 924/924 [01:22<00:00, 11.14it/s]\n",
            "                 Class     Images  Instances          P          R      mAP50   mAP50-95: 100% 116/116 [00:15<00:00,  7.35it/s]\n",
            "                   all       1847       3134      0.521      0.656      0.553      0.445\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   obj_loss   cls_loss  Instances       Size\n",
            "      32/99      1.28G    0.02178    0.02642    0.01521         23        512: 100% 924/924 [01:22<00:00, 11.14it/s]\n",
            "                 Class     Images  Instances          P          R      mAP50   mAP50-95: 100% 116/116 [00:15<00:00,  7.37it/s]\n",
            "                   all       1847       3134      0.523      0.667      0.553      0.449\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   obj_loss   cls_loss  Instances       Size\n",
            "      33/99      1.28G    0.02142    0.02642    0.01459         27        512: 100% 924/924 [01:23<00:00, 11.07it/s]\n",
            "                 Class     Images  Instances          P          R      mAP50   mAP50-95: 100% 116/116 [00:15<00:00,  7.38it/s]\n",
            "                   all       1847       3134       0.53      0.639      0.556      0.452\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   obj_loss   cls_loss  Instances       Size\n",
            "      34/99      1.28G    0.02115    0.02639    0.01454         15        512: 100% 924/924 [01:23<00:00, 11.09it/s]\n",
            "                 Class     Images  Instances          P          R      mAP50   mAP50-95: 100% 116/116 [00:15<00:00,  7.40it/s]\n",
            "                   all       1847       3134      0.538      0.634      0.562      0.452\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   obj_loss   cls_loss  Instances       Size\n",
            "      35/99      1.28G    0.02109    0.02624    0.01471         22        512: 100% 924/924 [01:22<00:00, 11.13it/s]\n",
            "                 Class     Images  Instances          P          R      mAP50   mAP50-95: 100% 116/116 [00:15<00:00,  7.44it/s]\n",
            "                   all       1847       3134      0.508      0.694       0.57      0.462\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   obj_loss   cls_loss  Instances       Size\n",
            "      36/99      1.28G    0.02105    0.02596    0.01421         26        512: 100% 924/924 [01:23<00:00, 11.05it/s]\n",
            "                 Class     Images  Instances          P          R      mAP50   mAP50-95: 100% 116/116 [00:15<00:00,  7.28it/s]\n",
            "                   all       1847       3134      0.563      0.604      0.565      0.456\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   obj_loss   cls_loss  Instances       Size\n",
            "      37/99      1.28G    0.02101    0.02614    0.01466         19        512: 100% 924/924 [01:23<00:00, 11.06it/s]\n",
            "                 Class     Images  Instances          P          R      mAP50   mAP50-95: 100% 116/116 [00:15<00:00,  7.41it/s]\n",
            "                   all       1847       3134      0.475      0.725      0.574      0.464\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   obj_loss   cls_loss  Instances       Size\n",
            "      38/99      1.28G    0.02097    0.02625    0.01401         18        512: 100% 924/924 [01:22<00:00, 11.14it/s]\n",
            "                 Class     Images  Instances          P          R      mAP50   mAP50-95: 100% 116/116 [00:15<00:00,  7.38it/s]\n",
            "                   all       1847       3134      0.501      0.686      0.577      0.468\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   obj_loss   cls_loss  Instances       Size\n",
            "      39/99      1.28G    0.02089    0.02612    0.01438         24        512: 100% 924/924 [01:22<00:00, 11.16it/s]\n",
            "                 Class     Images  Instances          P          R      mAP50   mAP50-95: 100% 116/116 [00:15<00:00,  7.33it/s]\n",
            "                   all       1847       3134      0.481      0.674      0.575      0.467\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   obj_loss   cls_loss  Instances       Size\n",
            "      40/99      1.28G    0.02084    0.02574    0.01356         33        512: 100% 924/924 [01:22<00:00, 11.16it/s]\n",
            "                 Class     Images  Instances          P          R      mAP50   mAP50-95: 100% 116/116 [00:15<00:00,  7.42it/s]\n",
            "                   all       1847       3134      0.512       0.69      0.586      0.475\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   obj_loss   cls_loss  Instances       Size\n",
            "      41/99      1.28G    0.02078    0.02581    0.01362         18        512: 100% 924/924 [01:22<00:00, 11.17it/s]\n",
            "                 Class     Images  Instances          P          R      mAP50   mAP50-95: 100% 116/116 [00:15<00:00,  7.45it/s]\n",
            "                   all       1847       3134      0.507      0.692      0.586      0.476\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   obj_loss   cls_loss  Instances       Size\n",
            "      42/99      1.28G    0.02066    0.02583    0.01338         19        512: 100% 924/924 [01:23<00:00, 11.03it/s]\n",
            "                 Class     Images  Instances          P          R      mAP50   mAP50-95: 100% 116/116 [00:15<00:00,  7.35it/s]\n",
            "                   all       1847       3134      0.492      0.668      0.576      0.468\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   obj_loss   cls_loss  Instances       Size\n",
            "      43/99      1.28G    0.02039    0.02586    0.01315         34        512: 100% 924/924 [01:22<00:00, 11.16it/s]\n",
            "                 Class     Images  Instances          P          R      mAP50   mAP50-95: 100% 116/116 [00:15<00:00,  7.29it/s]\n",
            "                   all       1847       3134      0.541      0.641      0.575       0.47\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   obj_loss   cls_loss  Instances       Size\n",
            "      44/99      1.28G    0.02051    0.02564    0.01368         23        512: 100% 924/924 [01:23<00:00, 11.08it/s]\n",
            "                 Class     Images  Instances          P          R      mAP50   mAP50-95: 100% 116/116 [00:15<00:00,  7.48it/s]\n",
            "                   all       1847       3134      0.485      0.694      0.581      0.475\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   obj_loss   cls_loss  Instances       Size\n",
            "      45/99      1.28G    0.02038    0.02553     0.0132         23        512: 100% 924/924 [01:22<00:00, 11.18it/s]\n",
            "                 Class     Images  Instances          P          R      mAP50   mAP50-95: 100% 116/116 [00:15<00:00,  7.44it/s]\n",
            "                   all       1847       3134      0.521      0.649      0.586      0.481\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   obj_loss   cls_loss  Instances       Size\n",
            "      46/99      1.28G    0.02031    0.02555     0.0127         25        512: 100% 924/924 [01:22<00:00, 11.16it/s]\n",
            "                 Class     Images  Instances          P          R      mAP50   mAP50-95: 100% 116/116 [00:15<00:00,  7.40it/s]\n",
            "                   all       1847       3134      0.519       0.66       0.59      0.485\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   obj_loss   cls_loss  Instances       Size\n",
            "      47/99      1.28G    0.02024    0.02557    0.01256         30        512: 100% 924/924 [01:24<00:00, 10.99it/s]\n",
            "                 Class     Images  Instances          P          R      mAP50   mAP50-95: 100% 116/116 [00:15<00:00,  7.35it/s]\n",
            "                   all       1847       3134      0.528      0.659      0.587      0.481\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   obj_loss   cls_loss  Instances       Size\n",
            "      48/99      1.28G    0.01989    0.02537    0.01279         20        512: 100% 924/924 [01:23<00:00, 11.10it/s]\n",
            "                 Class     Images  Instances          P          R      mAP50   mAP50-95: 100% 116/116 [00:15<00:00,  7.38it/s]\n",
            "                   all       1847       3134      0.516      0.678      0.592      0.486\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   obj_loss   cls_loss  Instances       Size\n",
            "      49/99      1.28G    0.02004    0.02534    0.01243         20        512: 100% 924/924 [01:23<00:00, 11.06it/s]\n",
            "                 Class     Images  Instances          P          R      mAP50   mAP50-95: 100% 116/116 [00:15<00:00,  7.31it/s]\n",
            "                   all       1847       3134      0.516      0.664      0.595      0.487\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   obj_loss   cls_loss  Instances       Size\n",
            "      50/99      1.28G       0.02    0.02544    0.01261         28        512: 100% 924/924 [01:24<00:00, 10.96it/s]\n",
            "                 Class     Images  Instances          P          R      mAP50   mAP50-95: 100% 116/116 [00:16<00:00,  7.23it/s]\n",
            "                   all       1847       3134      0.519      0.664      0.598      0.489\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   obj_loss   cls_loss  Instances       Size\n",
            "      51/99      1.28G    0.01996    0.02491    0.01237         18        512: 100% 924/924 [01:23<00:00, 11.00it/s]\n",
            "                 Class     Images  Instances          P          R      mAP50   mAP50-95: 100% 116/116 [00:15<00:00,  7.39it/s]\n",
            "                   all       1847       3134      0.515      0.664       0.58      0.476\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   obj_loss   cls_loss  Instances       Size\n",
            "      52/99      1.28G    0.01958    0.02537    0.01231         18        512: 100% 924/924 [01:23<00:00, 11.11it/s]\n",
            "                 Class     Images  Instances          P          R      mAP50   mAP50-95: 100% 116/116 [00:15<00:00,  7.45it/s]\n",
            "                   all       1847       3134      0.538      0.666      0.594      0.485\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   obj_loss   cls_loss  Instances       Size\n",
            "      53/99      1.28G    0.01956    0.02495    0.01172         18        512: 100% 924/924 [01:23<00:00, 11.13it/s]\n",
            "                 Class     Images  Instances          P          R      mAP50   mAP50-95: 100% 116/116 [00:15<00:00,  7.42it/s]\n",
            "                   all       1847       3134      0.538      0.667      0.598      0.493\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   obj_loss   cls_loss  Instances       Size\n",
            "      54/99      1.28G    0.01963    0.02481     0.0119         18        512: 100% 924/924 [01:23<00:00, 11.11it/s]\n",
            "                 Class     Images  Instances          P          R      mAP50   mAP50-95: 100% 116/116 [00:15<00:00,  7.39it/s]\n",
            "                   all       1847       3134      0.526      0.679      0.585      0.483\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   obj_loss   cls_loss  Instances       Size\n",
            "      55/99      1.28G    0.01982    0.02502    0.01242         18        512: 100% 924/924 [01:22<00:00, 11.15it/s]\n",
            "                 Class     Images  Instances          P          R      mAP50   mAP50-95: 100% 116/116 [00:15<00:00,  7.45it/s]\n",
            "                   all       1847       3134      0.543      0.647      0.586      0.484\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   obj_loss   cls_loss  Instances       Size\n",
            "      56/99      1.28G    0.01969    0.02516     0.0119         25        512: 100% 924/924 [01:22<00:00, 11.17it/s]\n",
            "                 Class     Images  Instances          P          R      mAP50   mAP50-95: 100% 116/116 [00:15<00:00,  7.32it/s]\n",
            "                   all       1847       3134       0.52      0.695      0.586      0.484\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   obj_loss   cls_loss  Instances       Size\n",
            "      57/99      1.28G    0.01947    0.02491    0.01157         14        512: 100% 924/924 [01:22<00:00, 11.17it/s]\n",
            "                 Class     Images  Instances          P          R      mAP50   mAP50-95: 100% 116/116 [00:15<00:00,  7.43it/s]\n",
            "                   all       1847       3134       0.53      0.678      0.591       0.49\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   obj_loss   cls_loss  Instances       Size\n",
            "      58/99      1.28G    0.01933    0.02426    0.01181         21        512: 100% 924/924 [01:22<00:00, 11.22it/s]\n",
            "                 Class     Images  Instances          P          R      mAP50   mAP50-95: 100% 116/116 [00:15<00:00,  7.48it/s]\n",
            "                   all       1847       3134      0.523      0.674       0.59      0.487\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   obj_loss   cls_loss  Instances       Size\n",
            "      59/99      1.28G    0.01916    0.02472    0.01124         26        512: 100% 924/924 [01:22<00:00, 11.15it/s]\n",
            "                 Class     Images  Instances          P          R      mAP50   mAP50-95: 100% 116/116 [00:15<00:00,  7.30it/s]\n",
            "                   all       1847       3134       0.53      0.679      0.584      0.484\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   obj_loss   cls_loss  Instances       Size\n",
            "      60/99      1.28G    0.01907    0.02452    0.01123         22        512: 100% 924/924 [01:22<00:00, 11.16it/s]\n",
            "                 Class     Images  Instances          P          R      mAP50   mAP50-95: 100% 116/116 [00:15<00:00,  7.49it/s]\n",
            "                   all       1847       3134      0.542      0.653      0.588      0.486\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   obj_loss   cls_loss  Instances       Size\n",
            "      61/99      1.28G    0.01925    0.02449    0.01119         19        512: 100% 924/924 [01:22<00:00, 11.22it/s]\n",
            "                 Class     Images  Instances          P          R      mAP50   mAP50-95: 100% 116/116 [00:15<00:00,  7.46it/s]\n",
            "                   all       1847       3134       0.53      0.694      0.594      0.492\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   obj_loss   cls_loss  Instances       Size\n",
            "      62/99      1.28G    0.01898    0.02421    0.01105         13        512: 100% 924/924 [01:22<00:00, 11.25it/s]\n",
            "                 Class     Images  Instances          P          R      mAP50   mAP50-95: 100% 116/116 [00:15<00:00,  7.55it/s]\n",
            "                   all       1847       3134      0.556      0.658      0.596      0.493\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   obj_loss   cls_loss  Instances       Size\n",
            "      63/99      1.28G     0.0188    0.02407    0.01068         13        512: 100% 924/924 [01:22<00:00, 11.26it/s]\n",
            "                 Class     Images  Instances          P          R      mAP50   mAP50-95: 100% 116/116 [00:15<00:00,  7.49it/s]\n",
            "                   all       1847       3134      0.542      0.681      0.598      0.496\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   obj_loss   cls_loss  Instances       Size\n",
            "      64/99      1.28G    0.01861    0.02401    0.01053         18        512: 100% 924/924 [01:22<00:00, 11.25it/s]\n",
            "                 Class     Images  Instances          P          R      mAP50   mAP50-95: 100% 116/116 [00:15<00:00,  7.47it/s]\n",
            "                   all       1847       3134       0.54       0.65      0.595      0.492\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   obj_loss   cls_loss  Instances       Size\n",
            "      65/99      1.28G    0.01886    0.02432     0.0108         12        512: 100% 924/924 [01:22<00:00, 11.23it/s]\n",
            "                 Class     Images  Instances          P          R      mAP50   mAP50-95: 100% 116/116 [00:15<00:00,  7.48it/s]\n",
            "                   all       1847       3134      0.527      0.678      0.603      0.498\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   obj_loss   cls_loss  Instances       Size\n",
            "      66/99      1.28G     0.0187    0.02378    0.01061         30        512: 100% 924/924 [01:21<00:00, 11.29it/s]\n",
            "                 Class     Images  Instances          P          R      mAP50   mAP50-95: 100% 116/116 [00:15<00:00,  7.47it/s]\n",
            "                   all       1847       3134      0.547       0.66      0.596      0.495\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   obj_loss   cls_loss  Instances       Size\n",
            "      67/99      1.28G    0.01849    0.02398    0.01055         29        512: 100% 924/924 [01:21<00:00, 11.34it/s]\n",
            "                 Class     Images  Instances          P          R      mAP50   mAP50-95: 100% 116/116 [00:15<00:00,  7.48it/s]\n",
            "                   all       1847       3134      0.548      0.652      0.595      0.494\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   obj_loss   cls_loss  Instances       Size\n",
            "      68/99      1.28G    0.01842    0.02391    0.01018         23        512: 100% 924/924 [01:21<00:00, 11.31it/s]\n",
            "                 Class     Images  Instances          P          R      mAP50   mAP50-95: 100% 116/116 [00:15<00:00,  7.51it/s]\n",
            "                   all       1847       3134      0.545      0.647      0.587      0.488\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   obj_loss   cls_loss  Instances       Size\n",
            "      69/99      1.28G    0.01841    0.02389    0.01009         23        512: 100% 924/924 [01:21<00:00, 11.28it/s]\n",
            "                 Class     Images  Instances          P          R      mAP50   mAP50-95: 100% 116/116 [00:15<00:00,  7.52it/s]\n",
            "                   all       1847       3134      0.545      0.654      0.587      0.488\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   obj_loss   cls_loss  Instances       Size\n",
            "      70/99      1.28G    0.01843    0.02347    0.01009         22        512: 100% 924/924 [01:22<00:00, 11.23it/s]\n",
            "                 Class     Images  Instances          P          R      mAP50   mAP50-95: 100% 116/116 [00:15<00:00,  7.47it/s]\n",
            "                   all       1847       3134      0.552      0.642        0.6      0.497\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   obj_loss   cls_loss  Instances       Size\n",
            "      71/99      1.28G    0.01823    0.02367       0.01         31        512: 100% 924/924 [01:21<00:00, 11.30it/s]\n",
            "                 Class     Images  Instances          P          R      mAP50   mAP50-95: 100% 116/116 [00:15<00:00,  7.57it/s]\n",
            "                   all       1847       3134      0.537      0.664        0.6      0.496\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   obj_loss   cls_loss  Instances       Size\n",
            "      72/99      1.28G    0.01823    0.02342    0.01001         24        512: 100% 924/924 [01:22<00:00, 11.26it/s]\n",
            "                 Class     Images  Instances          P          R      mAP50   mAP50-95: 100% 116/116 [00:15<00:00,  7.40it/s]\n",
            "                   all       1847       3134      0.551      0.653      0.597      0.496\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   obj_loss   cls_loss  Instances       Size\n",
            "      73/99      1.28G    0.01826    0.02342    0.01039         17        512: 100% 924/924 [01:22<00:00, 11.15it/s]\n",
            "                 Class     Images  Instances          P          R      mAP50   mAP50-95: 100% 116/116 [00:15<00:00,  7.45it/s]\n",
            "                   all       1847       3134      0.543      0.659      0.604      0.501\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   obj_loss   cls_loss  Instances       Size\n",
            "      74/99      1.28G    0.01806    0.02324   0.009805         18        512: 100% 924/924 [01:22<00:00, 11.14it/s]\n",
            "                 Class     Images  Instances          P          R      mAP50   mAP50-95: 100% 116/116 [00:15<00:00,  7.44it/s]\n",
            "                   all       1847       3134      0.547      0.643      0.597      0.497\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   obj_loss   cls_loss  Instances       Size\n",
            "      75/99      1.28G    0.01806    0.02299   0.009651         20        512: 100% 924/924 [01:23<00:00, 11.12it/s]\n",
            "                 Class     Images  Instances          P          R      mAP50   mAP50-95: 100% 116/116 [00:15<00:00,  7.39it/s]\n",
            "                   all       1847       3134      0.553       0.64      0.602      0.502\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   obj_loss   cls_loss  Instances       Size\n",
            "      76/99      1.28G    0.01789    0.02303   0.008662         18        512: 100% 924/924 [01:23<00:00, 11.09it/s]\n",
            "                 Class     Images  Instances          P          R      mAP50   mAP50-95: 100% 116/116 [00:15<00:00,  7.42it/s]\n",
            "                   all       1847       3134      0.562      0.625        0.6      0.498\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   obj_loss   cls_loss  Instances       Size\n",
            "      77/99      1.28G    0.01776    0.02302   0.009465         15        512: 100% 924/924 [01:23<00:00, 11.12it/s]\n",
            "                 Class     Images  Instances          P          R      mAP50   mAP50-95: 100% 116/116 [00:15<00:00,  7.39it/s]\n",
            "                   all       1847       3134      0.542      0.659      0.601      0.498\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   obj_loss   cls_loss  Instances       Size\n",
            "      78/99      1.28G     0.0178    0.02281   0.009437         18        512: 100% 924/924 [01:22<00:00, 11.15it/s]\n",
            "                 Class     Images  Instances          P          R      mAP50   mAP50-95: 100% 116/116 [00:15<00:00,  7.46it/s]\n",
            "                   all       1847       3134      0.531      0.671      0.603        0.5\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   obj_loss   cls_loss  Instances       Size\n",
            "      79/99      1.28G    0.01758     0.0227   0.009058         18        512: 100% 924/924 [01:22<00:00, 11.14it/s]\n",
            "                 Class     Images  Instances          P          R      mAP50   mAP50-95: 100% 116/116 [00:15<00:00,  7.45it/s]\n",
            "                   all       1847       3134       0.54      0.663      0.603      0.499\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   obj_loss   cls_loss  Instances       Size\n",
            "      80/99      1.28G    0.01746    0.02273   0.008909         31        512: 100% 924/924 [01:22<00:00, 11.16it/s]\n",
            "                 Class     Images  Instances          P          R      mAP50   mAP50-95: 100% 116/116 [00:15<00:00,  7.39it/s]\n",
            "                   all       1847       3134      0.536      0.668      0.604        0.5\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   obj_loss   cls_loss  Instances       Size\n",
            "      81/99      1.28G    0.01738    0.02243   0.008793         36        512: 100% 924/924 [01:22<00:00, 11.22it/s]\n",
            "                 Class     Images  Instances          P          R      mAP50   mAP50-95: 100% 116/116 [00:15<00:00,  7.50it/s]\n",
            "                   all       1847       3134      0.533      0.659      0.606      0.502\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   obj_loss   cls_loss  Instances       Size\n",
            "      82/99      1.28G    0.01744    0.02231   0.008686         20        512: 100% 924/924 [01:22<00:00, 11.26it/s]\n",
            "                 Class     Images  Instances          P          R      mAP50   mAP50-95: 100% 116/116 [00:15<00:00,  7.57it/s]\n",
            "                   all       1847       3134      0.559       0.62      0.603      0.502\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   obj_loss   cls_loss  Instances       Size\n",
            "      83/99      1.28G    0.01721    0.02225   0.008794         27        512: 100% 924/924 [01:22<00:00, 11.25it/s]\n",
            "                 Class     Images  Instances          P          R      mAP50   mAP50-95: 100% 116/116 [00:15<00:00,  7.59it/s]\n",
            "                   all       1847       3134      0.556      0.631      0.608      0.508\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   obj_loss   cls_loss  Instances       Size\n",
            "      84/99      1.28G    0.01734    0.02231   0.008933         19        512: 100% 924/924 [01:22<00:00, 11.26it/s]\n",
            "                 Class     Images  Instances          P          R      mAP50   mAP50-95: 100% 116/116 [00:15<00:00,  7.62it/s]\n",
            "                   all       1847       3134      0.559      0.639      0.608      0.509\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   obj_loss   cls_loss  Instances       Size\n",
            "      85/99      1.28G    0.01707    0.02221   0.008401         12        512: 100% 924/924 [01:21<00:00, 11.32it/s]\n",
            "                 Class     Images  Instances          P          R      mAP50   mAP50-95: 100% 116/116 [00:15<00:00,  7.50it/s]\n",
            "                   all       1847       3134      0.562       0.63       0.61      0.508\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   obj_loss   cls_loss  Instances       Size\n",
            "      86/99      1.28G    0.01697    0.02196   0.008245         23        512: 100% 924/924 [01:21<00:00, 11.29it/s]\n",
            "                 Class     Images  Instances          P          R      mAP50   mAP50-95: 100% 116/116 [00:15<00:00,  7.50it/s]\n",
            "                   all       1847       3134      0.555      0.637      0.609      0.507\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   obj_loss   cls_loss  Instances       Size\n",
            "      87/99      1.28G    0.01696    0.02176    0.00808         16        512: 100% 924/924 [01:22<00:00, 11.25it/s]\n",
            "                 Class     Images  Instances          P          R      mAP50   mAP50-95: 100% 116/116 [00:15<00:00,  7.49it/s]\n",
            "                   all       1847       3134       0.57      0.611      0.606      0.508\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   obj_loss   cls_loss  Instances       Size\n",
            "      88/99      1.28G     0.0168     0.0216   0.008261         16        512: 100% 924/924 [01:22<00:00, 11.21it/s]\n",
            "                 Class     Images  Instances          P          R      mAP50   mAP50-95: 100% 116/116 [00:15<00:00,  7.51it/s]\n",
            "                   all       1847       3134      0.547      0.652      0.604      0.507\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   obj_loss   cls_loss  Instances       Size\n",
            "      89/99      1.28G    0.01673     0.0218   0.007872         22        512: 100% 924/924 [01:22<00:00, 11.24it/s]\n",
            "                 Class     Images  Instances          P          R      mAP50   mAP50-95: 100% 116/116 [00:15<00:00,  7.49it/s]\n",
            "                   all       1847       3134      0.548      0.648       0.61      0.511\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   obj_loss   cls_loss  Instances       Size\n",
            "      90/99      1.28G    0.01653    0.02137   0.007668         12        512: 100% 924/924 [01:21<00:00, 11.31it/s]\n",
            "                 Class     Images  Instances          P          R      mAP50   mAP50-95: 100% 116/116 [00:15<00:00,  7.57it/s]\n",
            "                   all       1847       3134      0.559      0.631      0.604      0.508\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   obj_loss   cls_loss  Instances       Size\n",
            "      91/99      1.28G    0.01651    0.02153   0.007732         20        512: 100% 924/924 [01:22<00:00, 11.23it/s]\n",
            "                 Class     Images  Instances          P          R      mAP50   mAP50-95: 100% 116/116 [00:15<00:00,  7.57it/s]\n",
            "                   all       1847       3134      0.558      0.626      0.608      0.508\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   obj_loss   cls_loss  Instances       Size\n",
            "      92/99      1.28G     0.0166    0.02116   0.008136         35        512: 100% 924/924 [01:22<00:00, 11.25it/s]\n",
            "                 Class     Images  Instances          P          R      mAP50   mAP50-95: 100% 116/116 [00:15<00:00,  7.57it/s]\n",
            "                   all       1847       3134      0.576      0.609      0.607      0.507\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   obj_loss   cls_loss  Instances       Size\n",
            "      93/99      1.28G    0.01656     0.0214   0.007549         25        512: 100% 924/924 [01:21<00:00, 11.29it/s]\n",
            "                 Class     Images  Instances          P          R      mAP50   mAP50-95: 100% 116/116 [00:15<00:00,  7.65it/s]\n",
            "                   all       1847       3134      0.556       0.63      0.607      0.507\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   obj_loss   cls_loss  Instances       Size\n",
            "      94/99      1.28G     0.0164    0.02115   0.007398          5        512: 100% 924/924 [01:21<00:00, 11.29it/s]\n",
            "                 Class     Images  Instances          P          R      mAP50   mAP50-95: 100% 116/116 [00:15<00:00,  7.46it/s]\n",
            "                   all       1847       3134      0.544      0.648      0.607      0.507\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   obj_loss   cls_loss  Instances       Size\n",
            "      95/99      1.28G     0.0163    0.02081    0.00731         22        512: 100% 924/924 [01:22<00:00, 11.26it/s]\n",
            "                 Class     Images  Instances          P          R      mAP50   mAP50-95: 100% 116/116 [00:15<00:00,  7.56it/s]\n",
            "                   all       1847       3134      0.544      0.646      0.608      0.509\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   obj_loss   cls_loss  Instances       Size\n",
            "      96/99      1.28G    0.01633     0.0208   0.007682         25        512: 100% 924/924 [01:21<00:00, 11.27it/s]\n",
            "                 Class     Images  Instances          P          R      mAP50   mAP50-95: 100% 116/116 [00:15<00:00,  7.56it/s]\n",
            "                   all       1847       3134      0.543      0.649      0.608       0.51\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   obj_loss   cls_loss  Instances       Size\n",
            "      97/99      1.28G    0.01608    0.02065   0.007351         24        512: 100% 924/924 [01:21<00:00, 11.32it/s]\n",
            "                 Class     Images  Instances          P          R      mAP50   mAP50-95: 100% 116/116 [00:15<00:00,  7.58it/s]\n",
            "                   all       1847       3134      0.543      0.651      0.607      0.509\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   obj_loss   cls_loss  Instances       Size\n",
            "      98/99      1.28G    0.01593    0.02068   0.007275         16        512: 100% 924/924 [01:21<00:00, 11.29it/s]\n",
            "                 Class     Images  Instances          P          R      mAP50   mAP50-95: 100% 116/116 [00:15<00:00,  7.53it/s]\n",
            "                   all       1847       3134      0.547      0.643      0.606      0.509\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   obj_loss   cls_loss  Instances       Size\n",
            "      99/99      1.28G     0.0159     0.0206   0.007139         20        512: 100% 924/924 [01:21<00:00, 11.30it/s]\n",
            "                 Class     Images  Instances          P          R      mAP50   mAP50-95: 100% 116/116 [00:15<00:00,  7.56it/s]\n",
            "                   all       1847       3134      0.551      0.641      0.607      0.509\n",
            "\n",
            "100 epochs completed in 2.756 hours.\n",
            "Optimizer stripped from runs/train/Model2/weights/last.pt, 14.4MB\n",
            "Optimizer stripped from runs/train/Model2/weights/best.pt, 14.4MB\n",
            "\n",
            "Validating runs/train/Model2/weights/best.pt...\n",
            "Fusing layers... \n",
            "Model summary: 157 layers, 7066762 parameters, 0 gradients, 15.9 GFLOPs\n",
            "                 Class     Images  Instances          P          R      mAP50   mAP50-95: 100% 116/116 [00:17<00:00,  6.67it/s]\n",
            "                   all       1847       3134      0.548      0.648      0.609      0.511\n",
            "                 Pants       1847        206      0.389      0.577       0.45      0.397\n",
            "              Handbags       1847        198      0.174      0.192      0.174      0.146\n",
            "                Shirts       1847        208      0.254      0.317      0.256      0.226\n",
            "                 Shoes       1847        186      0.149      0.183       0.15      0.116\n",
            "               Scarves       1847        211      0.777      0.886      0.867      0.743\n",
            "               Jewelry       1847        209      0.375      0.465      0.338      0.272\n",
            "                Skirts       1847        189      0.604      0.868      0.741      0.651\n",
            "                 Coats       1847        204      0.337      0.515      0.383       0.34\n",
            "                  Hats       1847        195      0.439       0.74      0.559      0.489\n",
            "               Dresses       1847        199      0.476      0.719      0.547      0.477\n",
            "                Shorts       1847        210      0.743      0.895      0.847      0.723\n",
            "               Watches       1847        183      0.656      0.887      0.835      0.705\n",
            "            Sunglasses       1847        189      0.585      0.873      0.716      0.594\n",
            "             Jumpsuits       1847         60       0.69      0.833      0.777      0.662\n",
            "                 Socks       1847        153      0.771      0.804      0.884      0.698\n",
            "                 Rings       1847        113      0.618      0.832      0.738      0.585\n",
            "                 Belts       1847        139      0.716      0.899      0.871      0.691\n",
            "                Gloves       1847         14      0.536      0.429      0.422      0.291\n",
            "              Swimwear       1847         40      0.598      0.775      0.813      0.725\n",
            "             Stockings       1847         24      0.623      0.917      0.919      0.744\n",
            "              Neckties       1847          4          1          0      0.511       0.46\n",
            "Results saved to \u001b[1mruns/train/Model2\u001b[0m\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "!python export.py --weights runs/train/Model2/weights/best.pt --include onnx --simplify --opset 12"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "JKqCmRJJcpAh",
        "outputId": "20acaf4e-a47b-4bca-d6f8-ccfae8ccdf8f"
      },
      "execution_count": 6,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "\u001b[34m\u001b[1mexport: \u001b[0mdata=data/coco128.yaml, weights=['runs/train/Model2/weights/best.pt'], imgsz=[640, 640], batch_size=1, device=cpu, half=False, inplace=False, keras=False, optimize=False, int8=False, dynamic=False, simplify=True, opset=12, verbose=False, workspace=4, nms=False, agnostic_nms=False, topk_per_class=100, topk_all=100, iou_thres=0.45, conf_thres=0.25, include=['onnx']\n",
            "YOLOv5 🚀 v7.0-240-g84ec8b5 Python-3.10.12 torch-2.1.0+cu118 CPU\n",
            "\n",
            "Fusing layers... \n",
            "Model summary: 157 layers, 7066762 parameters, 0 gradients, 15.9 GFLOPs\n",
            "\n",
            "\u001b[34m\u001b[1mPyTorch:\u001b[0m starting from runs/train/Model2/weights/best.pt with output shape (1, 25200, 26) (13.7 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-1.15.0-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (15.7 MB)\n",
            "     ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 15.7/15.7 MB 195.0 MB/s eta 0:00:00\n",
            "Requirement already satisfied: numpy in /usr/local/lib/python3.10/dist-packages (from onnx>=1.12.0) (1.23.5)\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-1.15.0\n",
            "\n",
            "\u001b[31m\u001b[1mrequirements:\u001b[0m AutoUpdate success ✅ 6.4s, 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 1.15.0...\n",
            "\u001b[31m\u001b[1mrequirements:\u001b[0m Ultralytics requirements ['onnxruntime', 'onnx-simplifier>=0.4.1'] not found, attempting AutoUpdate...\n",
            "Collecting onnxruntime\n",
            "  Downloading onnxruntime-1.16.2-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (6.4 MB)\n",
            "     ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 6.4/6.4 MB 51.9 MB/s eta 0:00:00\n",
            "Collecting onnx-simplifier>=0.4.1\n",
            "  Downloading onnx_simplifier-0.4.35-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (2.2 MB)\n",
            "     ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 2.2/2.2 MB 175.3 MB/s eta 0:00:00\n",
            "Collecting coloredlogs (from onnxruntime)\n",
            "  Downloading coloredlogs-15.0.1-py2.py3-none-any.whl (46 kB)\n",
            "     ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 46.0/46.0 kB 252.4 MB/s eta 0:00:00\n",
            "Requirement already satisfied: flatbuffers in /usr/local/lib/python3.10/dist-packages (from onnxruntime) (23.5.26)\n",
            "Requirement already satisfied: numpy>=1.21.6 in /usr/local/lib/python3.10/dist-packages (from onnxruntime) (1.23.5)\n",
            "Requirement already satisfied: packaging in /usr/local/lib/python3.10/dist-packages (from onnxruntime) (23.2)\n",
            "Requirement already satisfied: protobuf in /usr/local/lib/python3.10/dist-packages (from onnxruntime) (3.20.3)\n",
            "Requirement already satisfied: sympy in /usr/local/lib/python3.10/dist-packages (from onnxruntime) (1.12)\n",
            "Requirement already satisfied: onnx in /usr/local/lib/python3.10/dist-packages (from onnx-simplifier>=0.4.1) (1.15.0)\n",
            "Requirement already satisfied: rich in /usr/local/lib/python3.10/dist-packages (from onnx-simplifier>=0.4.1) (13.6.0)\n",
            "Collecting humanfriendly>=9.1 (from coloredlogs->onnxruntime)\n",
            "  Downloading humanfriendly-10.0-py2.py3-none-any.whl (86 kB)\n",
            "     ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 86.8/86.8 kB 307.9 MB/s eta 0:00:00\n",
            "Requirement already satisfied: markdown-it-py>=2.2.0 in /usr/local/lib/python3.10/dist-packages (from rich->onnx-simplifier>=0.4.1) (3.0.0)\n",
            "Requirement already satisfied: pygments<3.0.0,>=2.13.0 in /usr/local/lib/python3.10/dist-packages (from rich->onnx-simplifier>=0.4.1) (2.16.1)\n",
            "Requirement already satisfied: mpmath>=0.19 in /usr/local/lib/python3.10/dist-packages (from sympy->onnxruntime) (1.3.0)\n",
            "Requirement already satisfied: mdurl~=0.1 in /usr/local/lib/python3.10/dist-packages (from markdown-it-py>=2.2.0->rich->onnx-simplifier>=0.4.1) (0.1.2)\n",
            "Installing collected packages: humanfriendly, coloredlogs, onnxruntime, onnx-simplifier\n",
            "Successfully installed coloredlogs-15.0.1 humanfriendly-10.0 onnx-simplifier-0.4.35 onnxruntime-1.16.2\n",
            "\n",
            "\u001b[31m\u001b[1mrequirements:\u001b[0m AutoUpdate success ✅ 5.3s, installed 2 packages: ['onnxruntime', 'onnx-simplifier>=0.4.1']\n",
            "\u001b[31m\u001b[1mrequirements:\u001b[0m ⚠️ \u001b[1mRestart runtime or rerun command for updates to take effect\u001b[0m\n",
            "\n",
            "\u001b[34m\u001b[1mONNX:\u001b[0m simplifying with onnx-simplifier 0.4.35...\n",
            "\u001b[34m\u001b[1mONNX:\u001b[0m export success ✅ 13.0s, saved as runs/train/Model2/weights/best.onnx (27.4 MB)\n",
            "\n",
            "Export complete (13.5s)\n",
            "Results saved to \u001b[1m/content/drive/MyDrive/yolo_training/yolov5/runs/train/Model2/weights\u001b[0m\n",
            "Detect:          python detect.py --weights runs/train/Model2/weights/best.onnx \n",
            "Validate:        python val.py --weights runs/train/Model2/weights/best.onnx \n",
            "PyTorch Hub:     model = torch.hub.load('ultralytics/yolov5', 'custom', 'runs/train/Model2/weights/best.onnx')  \n",
            "Visualize:       https://netron.app\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [],
      "metadata": {
        "id": "a1a2f6X9BTiV"
      },
      "execution_count": null,
      "outputs": []
    }
  ]
}