02. YOLO_training.ipynb

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  "metadata": {
    "colab": {
      "provenance": [],
      "machine_shape": "hm",
      "gpuType": "V100"
    },
    "kernelspec": {
      "name": "python3",
      "display_name": "Python 3"
    },
    "language_info": {
      "name": "python"
    },
    "accelerator": "GPU"
  },
  "cells": [
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "KolA9715COx1"
      },
      "outputs": [],
      "source": [
        "import os"
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# Change the current working directory to the specified path\n",
        "os.chdir(\"/content/drive/MyDrive/yolo_training\")"
      ],
      "metadata": {
        "id": "aFyvwyEUDu_R"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "!ls"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "Fv5SuyfgD16v",
        "outputId": "d7dc6683-d81d-48bf-f53a-25ebee41a917"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "yolo_training.ipynb  yolov5\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "#💠  Clone the YOLOv5 repository from GitHub to the current working Directory"
      ],
      "metadata": {
        "id": "lMPOO3r_BMWT"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "🔄**git clone command** : to clone (copy) the YOLOv5 repository from GitHub into the current working directory. By executing this command, you are downloading all the files and the entire version history of the YOLOv5 repository maintained by Ultralytics."
      ],
      "metadata": {
        "id": "EBcbvLpGAmZz"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "# Clone the YOLOv5 repository from GitHub to the current working directory\n",
        "!git clone https://github.com/ultralytics/yolov5.git"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "S1OjvMCFEOSP",
        "outputId": "4e554276-304e-419a-be44-d2f919a5522c"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "fatal: destination path 'yolov5' already exists and is not an empty directory.\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# Change the current working directory to the 'yolov5' directory\n",
        "os.chdir('yolov5')"
      ],
      "metadata": {
        "id": "iD-Kat77GC6l"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "!ls"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "3ZRAFn-pGHhl",
        "outputId": "1046e2b5-ad47-4ef2-ebc5-23ebb71fd6bd"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            " benchmarks.py\t   data_images\t models\t\t    setup.cfg\n",
            " CITATION.cff\t   data.yaml\t __pycache__\t    train.py\n",
            " classify\t   detect.py\t README.md\t    tutorial.ipynb\n",
            " CONTRIBUTING.md   export.py\t README.zh-CN.md    utils\n",
            " data\t\t   hubconf.py\t requirements.txt   val.py\n",
            "'data (1).yaml'    LICENSE\t segment\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "#💠 install all required packeges from requirement.txt"
      ],
      "metadata": {
        "id": "K00Hd0ODHBkj"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        " the **requirements.txt** file contains the specific libraries and versions needed to run the YOLOv5 code. By executing this command, you are setting up the environment with all the necessary dependencies, ensuring that the code will run as intended."
      ],
      "metadata": {
        "id": "MF639TC0CZR7"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "# Install the required packages and dependencies listed in the 'requirements.txt' file\n",
        "# This file is part of the YOLOv5 repository and specifies the versions and packages needed to run the code\n",
        "!pip install -r requirements.txt"
      ],
      "metadata": {
        "id": "qCg5LAHZHSPc",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "0227d248-418e-4d39-bcad-bef69146cbd7"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
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            "Installing collected packages: smmap, gitdb, gitpython, ultralytics, thop\n",
            "Successfully installed gitdb-4.0.10 gitpython-3.1.32 smmap-5.0.0 thop-0.1.1.post2209072238 ultralytics-8.0.145\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "#💠 Training YOLO V5 Model"
      ],
      "metadata": {
        "id": "9y-UnAVUMiah"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "In this step, we train the YOLOv5 object detection model using the command below:"
      ],
      "metadata": {
        "id": "DvMC4dijEe9a"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "✅ **Here's a breakdown of the command-line arguments used:**\n",
        "\n",
        "* data data.yaml: Specifies the configuration file (data.yaml) containing information about the dataset, including paths to training and validation data.\n",
        "\n",
        "* weights yolov5s.pt: Indicates the pre-trained weights file (yolov5s.pt) to initialize the model, providing a starting point for training.\n",
        "* --batch-size 8: Sets the batch size to 8, determining how many training samples are processed simultaneously.\n",
        "* --name Model: Assigns the name 'Model' to the trained model, allowing for easy identification later.\n",
        "* --img 640: Defines the image size as 640 pixels, controlling the dimensions to which input images are resized during training.\n",
        "* --epochs 150: Specifies the number of training epochs as 150, defining how many complete passes through the training data the model will make.\n",
        "\n",
        "🔄 This command initiates the training process, utilizing the specified parameters to train the model according to the project's requirements."
      ],
      "metadata": {
        "id": "6N8yhOKwEhvo"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "# Train the YOLOv5 model using the specified parameters\n",
        "# Data configuration: 'data.yaml'\n",
        "# Pre-trained weights: 'yolov5s.pt'\n",
        "# Batch size: 8\n",
        "# Model name: 'Model'\n",
        "# Image size: 640\n",
        "# Number of epochs: 150\n",
        "\n",
        "!python train.py --data data.yaml --weights yolov5s.pt --batch-size 8 --name Model --img 640 --epochs 150"
      ],
      "metadata": {
        "id": "kdZPqBXEMnwZ",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "8cdae62b-ad2a-4fa9-d022-77fd903097e0"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "\u001b[34m\u001b[1mtrain: \u001b[0mweights=yolov5s.pt, cfg=, data=data.yaml, hyp=data/hyps/hyp.scratch-low.yaml, epochs=150, batch_size=8, imgsz=640, 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 🚀 v7.0-198-g34c2187 Python-3.10.6 torch-2.0.1+cu118 CUDA:0 (Tesla V100-SXM2-16GB, 16151MiB)\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, 24.3MB/s]\n",
            "Downloading https://github.com/ultralytics/yolov5/releases/download/v7.0/yolov5s.pt to yolov5s.pt...\n",
            "100% 14.1M/14.1M [00:00<00:00, 85.6MB/s]\n",
            "\n",
            "Overriding model.yaml nc=80 with nc=20\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     67425  models.yolo.Detect                      [20, [[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, 7073569 parameters, 7073569 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... 4010 images, 0 backgrounds, 0 corrupt: 100% 4010/4010 [01:41<00:00, 39.44it/s] \n",
            "\u001b[34m\u001b[1mtrain: \u001b[0mNew cache created: /content/drive/MyDrive/yolo_training/yolov5/data_images/train.cache\n",
            "\u001b[34m\u001b[1mval: \u001b[0mScanning /content/drive/MyDrive/yolo_training/yolov5/data_images/test... 1002 images, 0 backgrounds, 0 corrupt: 100% 1002/1002 [00:29<00:00, 33.66it/s]\n",
            "\u001b[34m\u001b[1mval: \u001b[0mNew cache created: /content/drive/MyDrive/yolo_training/yolov5/data_images/test.cache\n",
            "\n",
            "\u001b[34m\u001b[1mAutoAnchor: \u001b[0m4.25 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 640 train, 640 val\n",
            "Using 4 dataloader workers\n",
            "Logging results to \u001b[1mruns/train/Model\u001b[0m\n",
            "Starting training for 150 epochs...\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   obj_loss   cls_loss  Instances       Size\n",
            "      0/149      1.76G    0.07668    0.04442    0.06208         18        640: 100% 502/502 [01:19<00:00,  6.32it/s]\n",
            "                 Class     Images  Instances          P          R      mAP50   mAP50-95: 100% 63/63 [00:11<00:00,  5.56it/s]\n",
            "                   all       1002       3172      0.471      0.348      0.352      0.176\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   obj_loss   cls_loss  Instances       Size\n",
            "      1/149       2.9G    0.05499     0.0386    0.03276         23        640: 100% 502/502 [01:15<00:00,  6.69it/s]\n",
            "                 Class     Images  Instances          P          R      mAP50   mAP50-95: 100% 63/63 [00:08<00:00,  7.16it/s]\n",
            "                   all       1002       3172      0.579      0.578      0.576      0.289\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   obj_loss   cls_loss  Instances       Size\n",
            "      2/149       2.9G    0.05391    0.03769    0.02493         15        640: 100% 502/502 [01:14<00:00,  6.76it/s]\n",
            "                 Class     Images  Instances          P          R      mAP50   mAP50-95: 100% 63/63 [00:08<00:00,  7.18it/s]\n",
            "                   all       1002       3172      0.519      0.555      0.529      0.272\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   obj_loss   cls_loss  Instances       Size\n",
            "      3/149       2.9G    0.05088    0.04046    0.02404         13        640: 100% 502/502 [01:15<00:00,  6.63it/s]\n",
            "                 Class     Images  Instances          P          R      mAP50   mAP50-95: 100% 63/63 [00:08<00:00,  7.20it/s]\n",
            "                   all       1002       3172      0.607      0.506      0.557      0.276\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   obj_loss   cls_loss  Instances       Size\n",
            "      4/149       2.9G    0.04883     0.0411    0.02337         11        640: 100% 502/502 [01:14<00:00,  6.75it/s]\n",
            "                 Class     Images  Instances          P          R      mAP50   mAP50-95: 100% 63/63 [00:08<00:00,  7.35it/s]\n",
            "                   all       1002       3172      0.558        0.5      0.514       0.26\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   obj_loss   cls_loss  Instances       Size\n",
            "      5/149       2.9G    0.04792    0.04164    0.02219         16        640: 100% 502/502 [01:12<00:00,  6.90it/s]\n",
            "                 Class     Images  Instances          P          R      mAP50   mAP50-95: 100% 63/63 [00:08<00:00,  7.23it/s]\n",
            "                   all       1002       3172      0.596      0.518       0.55      0.292\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   obj_loss   cls_loss  Instances       Size\n",
            "      6/149       2.9G     0.0466     0.0418    0.02169         25        640: 100% 502/502 [01:11<00:00,  7.02it/s]\n",
            "                 Class     Images  Instances          P          R      mAP50   mAP50-95: 100% 63/63 [00:08<00:00,  7.35it/s]\n",
            "                   all       1002       3172      0.614      0.512      0.557      0.295\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   obj_loss   cls_loss  Instances       Size\n",
            "      7/149       2.9G    0.04647    0.04172    0.02181         28        640: 100% 502/502 [01:11<00:00,  7.00it/s]\n",
            "                 Class     Images  Instances          P          R      mAP50   mAP50-95: 100% 63/63 [00:08<00:00,  7.40it/s]\n",
            "                   all       1002       3172      0.598      0.539      0.576      0.311\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   obj_loss   cls_loss  Instances       Size\n",
            "      8/149       2.9G    0.04548    0.04138    0.02048          4        640: 100% 502/502 [01:11<00:00,  7.01it/s]\n",
            "                 Class     Images  Instances          P          R      mAP50   mAP50-95: 100% 63/63 [00:08<00:00,  7.53it/s]\n",
            "                   all       1002       3172      0.613      0.538       0.57      0.308\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   obj_loss   cls_loss  Instances       Size\n",
            "      9/149       2.9G    0.04523    0.04134    0.01952          4        640: 100% 502/502 [01:13<00:00,  6.81it/s]\n",
            "                 Class     Images  Instances          P          R      mAP50   mAP50-95: 100% 63/63 [00:08<00:00,  7.65it/s]\n",
            "                   all       1002       3172      0.648      0.543      0.589      0.326\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   obj_loss   cls_loss  Instances       Size\n",
            "     10/149       2.9G    0.04473    0.04025    0.01868         10        640: 100% 502/502 [01:12<00:00,  6.90it/s]\n",
            "                 Class     Images  Instances          P          R      mAP50   mAP50-95: 100% 63/63 [00:08<00:00,  7.74it/s]\n",
            "                   all       1002       3172      0.624      0.531      0.578      0.309\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   obj_loss   cls_loss  Instances       Size\n",
            "     11/149       2.9G    0.04365    0.03959    0.01865         11        640: 100% 502/502 [01:12<00:00,  6.97it/s]\n",
            "                 Class     Images  Instances          P          R      mAP50   mAP50-95: 100% 63/63 [00:08<00:00,  7.16it/s]\n",
            "                   all       1002       3172      0.634      0.556      0.587      0.319\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   obj_loss   cls_loss  Instances       Size\n",
            "     12/149       2.9G    0.04378    0.03991    0.01838         11        640: 100% 502/502 [01:11<00:00,  6.99it/s]\n",
            "                 Class     Images  Instances          P          R      mAP50   mAP50-95: 100% 63/63 [00:08<00:00,  7.49it/s]\n",
            "                   all       1002       3172      0.656      0.539      0.582      0.318\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   obj_loss   cls_loss  Instances       Size\n",
            "     13/149       2.9G    0.04366    0.04007    0.01761         16        640: 100% 502/502 [01:11<00:00,  7.00it/s]\n",
            "                 Class     Images  Instances          P          R      mAP50   mAP50-95: 100% 63/63 [00:08<00:00,  7.45it/s]\n",
            "                   all       1002       3172      0.672      0.571      0.624      0.349\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   obj_loss   cls_loss  Instances       Size\n",
            "     14/149       2.9G    0.04277    0.03978    0.01626         24        640: 100% 502/502 [01:12<00:00,  6.96it/s]\n",
            "                 Class     Images  Instances          P          R      mAP50   mAP50-95: 100% 63/63 [00:08<00:00,  7.34it/s]\n",
            "                   all       1002       3172      0.659      0.557      0.602      0.337\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   obj_loss   cls_loss  Instances       Size\n",
            "     15/149       2.9G    0.04265    0.03946    0.01646          7        640: 100% 502/502 [01:12<00:00,  6.95it/s]\n",
            "                 Class     Images  Instances          P          R      mAP50   mAP50-95: 100% 63/63 [00:08<00:00,  7.57it/s]\n",
            "                   all       1002       3172      0.648      0.572      0.612      0.341\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   obj_loss   cls_loss  Instances       Size\n",
            "     16/149       2.9G    0.04241    0.03912    0.01649          5        640: 100% 502/502 [01:13<00:00,  6.79it/s]\n",
            "                 Class     Images  Instances          P          R      mAP50   mAP50-95: 100% 63/63 [00:08<00:00,  7.36it/s]\n",
            "                   all       1002       3172      0.653      0.547      0.594      0.335\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   obj_loss   cls_loss  Instances       Size\n",
            "     17/149       2.9G     0.0419    0.03872    0.01648         14        640: 100% 502/502 [01:12<00:00,  6.95it/s]\n",
            "                 Class     Images  Instances          P          R      mAP50   mAP50-95: 100% 63/63 [00:08<00:00,  7.37it/s]\n",
            "                   all       1002       3172      0.688      0.544      0.613      0.342\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   obj_loss   cls_loss  Instances       Size\n",
            "     18/149       2.9G    0.04133    0.03879    0.01588          6        640: 100% 502/502 [01:11<00:00,  7.04it/s]\n",
            "                 Class     Images  Instances          P          R      mAP50   mAP50-95: 100% 63/63 [00:08<00:00,  7.66it/s]\n",
            "                   all       1002       3172      0.642      0.566      0.606      0.351\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   obj_loss   cls_loss  Instances       Size\n",
            "     19/149       2.9G    0.04161    0.03851    0.01494         16        640: 100% 502/502 [01:12<00:00,  6.95it/s]\n",
            "                 Class     Images  Instances          P          R      mAP50   mAP50-95: 100% 63/63 [00:08<00:00,  7.71it/s]\n",
            "                   all       1002       3172      0.668      0.597      0.628      0.356\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   obj_loss   cls_loss  Instances       Size\n",
            "     20/149       2.9G    0.04088    0.03847    0.01497         12        640: 100% 502/502 [01:11<00:00,  6.98it/s]\n",
            "                 Class     Images  Instances          P          R      mAP50   mAP50-95: 100% 63/63 [00:08<00:00,  7.85it/s]\n",
            "                   all       1002       3172      0.646      0.581       0.62      0.353\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   obj_loss   cls_loss  Instances       Size\n",
            "     21/149       2.9G    0.04066    0.03766    0.01412          6        640: 100% 502/502 [01:12<00:00,  6.92it/s]\n",
            "                 Class     Images  Instances          P          R      mAP50   mAP50-95: 100% 63/63 [00:08<00:00,  7.42it/s]\n",
            "                   all       1002       3172      0.692      0.553      0.624      0.358\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   obj_loss   cls_loss  Instances       Size\n",
            "     22/149       2.9G    0.04066    0.03818    0.01381          6        640: 100% 502/502 [01:12<00:00,  6.94it/s]\n",
            "                 Class     Images  Instances          P          R      mAP50   mAP50-95: 100% 63/63 [00:08<00:00,  7.30it/s]\n",
            "                   all       1002       3172      0.689      0.576      0.636      0.373\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   obj_loss   cls_loss  Instances       Size\n",
            "     23/149       2.9G     0.0397    0.03721    0.01374         17        640: 100% 502/502 [01:12<00:00,  6.94it/s]\n",
            "                 Class     Images  Instances          P          R      mAP50   mAP50-95: 100% 63/63 [00:08<00:00,  7.45it/s]\n",
            "                   all       1002       3172      0.667      0.587      0.627      0.364\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   obj_loss   cls_loss  Instances       Size\n",
            "     24/149       2.9G    0.03982    0.03815    0.01408         12        640: 100% 502/502 [01:12<00:00,  6.96it/s]\n",
            "                 Class     Images  Instances          P          R      mAP50   mAP50-95: 100% 63/63 [00:08<00:00,  7.58it/s]\n",
            "                   all       1002       3172      0.664       0.57      0.609       0.35\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   obj_loss   cls_loss  Instances       Size\n",
            "     25/149       2.9G    0.03958    0.03741    0.01343          7        640: 100% 502/502 [01:13<00:00,  6.84it/s]\n",
            "                 Class     Images  Instances          P          R      mAP50   mAP50-95: 100% 63/63 [00:08<00:00,  7.42it/s]\n",
            "                   all       1002       3172      0.683      0.586      0.642       0.37\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   obj_loss   cls_loss  Instances       Size\n",
            "     26/149       2.9G     0.0395    0.03697    0.01338         16        640: 100% 502/502 [01:13<00:00,  6.85it/s]\n",
            "                 Class     Images  Instances          P          R      mAP50   mAP50-95: 100% 63/63 [00:08<00:00,  7.76it/s]\n",
            "                   all       1002       3172      0.707      0.585      0.659      0.386\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   obj_loss   cls_loss  Instances       Size\n",
            "     27/149       2.9G    0.03911    0.03643    0.01261         21        640: 100% 502/502 [01:12<00:00,  6.90it/s]\n",
            "                 Class     Images  Instances          P          R      mAP50   mAP50-95: 100% 63/63 [00:08<00:00,  7.55it/s]\n",
            "                   all       1002       3172      0.722      0.593      0.654      0.384\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   obj_loss   cls_loss  Instances       Size\n",
            "     28/149       2.9G    0.03874    0.03646    0.01294          6        640: 100% 502/502 [01:13<00:00,  6.80it/s]\n",
            "                 Class     Images  Instances          P          R      mAP50   mAP50-95: 100% 63/63 [00:08<00:00,  7.23it/s]\n",
            "                   all       1002       3172      0.688      0.586      0.631      0.373\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   obj_loss   cls_loss  Instances       Size\n",
            "     29/149       2.9G    0.03879     0.0367    0.01297         38        640: 100% 502/502 [01:12<00:00,  6.93it/s]\n",
            "                 Class     Images  Instances          P          R      mAP50   mAP50-95: 100% 63/63 [00:08<00:00,  7.45it/s]\n",
            "                   all       1002       3172      0.684      0.603       0.65      0.373\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   obj_loss   cls_loss  Instances       Size\n",
            "     30/149       2.9G    0.03872    0.03689    0.01181         17        640: 100% 502/502 [01:12<00:00,  6.90it/s]\n",
            "                 Class     Images  Instances          P          R      mAP50   mAP50-95: 100% 63/63 [00:08<00:00,  7.53it/s]\n",
            "                   all       1002       3172      0.666      0.614       0.66      0.385\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   obj_loss   cls_loss  Instances       Size\n",
            "     31/149       2.9G    0.03821    0.03672    0.01194          7        640: 100% 502/502 [01:13<00:00,  6.86it/s]\n",
            "                 Class     Images  Instances          P          R      mAP50   mAP50-95: 100% 63/63 [00:08<00:00,  7.55it/s]\n",
            "                   all       1002       3172      0.644      0.604      0.633      0.367\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   obj_loss   cls_loss  Instances       Size\n",
            "     32/149       2.9G    0.03782     0.0364    0.01195         22        640: 100% 502/502 [01:13<00:00,  6.80it/s]\n",
            "                 Class     Images  Instances          P          R      mAP50   mAP50-95: 100% 63/63 [00:08<00:00,  7.53it/s]\n",
            "                   all       1002       3172      0.677      0.597      0.638      0.378\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   obj_loss   cls_loss  Instances       Size\n",
            "     33/149       2.9G    0.03755    0.03593    0.01212          5        640: 100% 502/502 [01:12<00:00,  6.88it/s]\n",
            "                 Class     Images  Instances          P          R      mAP50   mAP50-95: 100% 63/63 [00:08<00:00,  7.69it/s]\n",
            "                   all       1002       3172      0.671      0.609      0.655      0.391\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   obj_loss   cls_loss  Instances       Size\n",
            "     34/149       2.9G    0.03753    0.03603    0.01152          9        640: 100% 502/502 [01:13<00:00,  6.82it/s]\n",
            "                 Class     Images  Instances          P          R      mAP50   mAP50-95: 100% 63/63 [00:08<00:00,  7.81it/s]\n",
            "                   all       1002       3172      0.717      0.626      0.669      0.396\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   obj_loss   cls_loss  Instances       Size\n",
            "     35/149       2.9G    0.03733    0.03588    0.01125         14        640: 100% 502/502 [01:14<00:00,  6.76it/s]\n",
            "                 Class     Images  Instances          P          R      mAP50   mAP50-95: 100% 63/63 [00:08<00:00,  7.64it/s]\n",
            "                   all       1002       3172      0.694      0.611      0.651      0.381\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   obj_loss   cls_loss  Instances       Size\n",
            "     36/149       2.9G    0.03685    0.03508    0.01154          8        640: 100% 502/502 [01:12<00:00,  6.95it/s]\n",
            "                 Class     Images  Instances          P          R      mAP50   mAP50-95: 100% 63/63 [00:08<00:00,  7.35it/s]\n",
            "                   all       1002       3172      0.704      0.602      0.649      0.384\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   obj_loss   cls_loss  Instances       Size\n",
            "     37/149       2.9G    0.03678    0.03494    0.01138         18        640: 100% 502/502 [01:12<00:00,  6.92it/s]\n",
            "                 Class     Images  Instances          P          R      mAP50   mAP50-95: 100% 63/63 [00:08<00:00,  7.44it/s]\n",
            "                   all       1002       3172      0.696      0.614      0.661      0.396\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   obj_loss   cls_loss  Instances       Size\n",
            "     38/149       2.9G    0.03672    0.03482    0.01107         10        640: 100% 502/502 [01:12<00:00,  6.88it/s]\n",
            "                 Class     Images  Instances          P          R      mAP50   mAP50-95: 100% 63/63 [00:08<00:00,  7.55it/s]\n",
            "                   all       1002       3172      0.709      0.608       0.66      0.395\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   obj_loss   cls_loss  Instances       Size\n",
            "     39/149       2.9G    0.03757    0.03479    0.01111          5        640: 100% 502/502 [01:14<00:00,  6.73it/s]\n",
            "                 Class     Images  Instances          P          R      mAP50   mAP50-95: 100% 63/63 [00:08<00:00,  7.47it/s]\n",
            "                   all       1002       3172      0.686      0.595      0.654      0.387\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   obj_loss   cls_loss  Instances       Size\n",
            "     40/149       2.9G    0.03662    0.03486    0.01062         20        640: 100% 502/502 [01:12<00:00,  6.88it/s]\n",
            "                 Class     Images  Instances          P          R      mAP50   mAP50-95: 100% 63/63 [00:08<00:00,  7.69it/s]\n",
            "                   all       1002       3172      0.689      0.597      0.647      0.393\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   obj_loss   cls_loss  Instances       Size\n",
            "     41/149       2.9G    0.03645    0.03465    0.01055         22        640: 100% 502/502 [01:13<00:00,  6.86it/s]\n",
            "                 Class     Images  Instances          P          R      mAP50   mAP50-95: 100% 63/63 [00:08<00:00,  7.74it/s]\n",
            "                   all       1002       3172      0.717      0.615      0.664      0.398\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   obj_loss   cls_loss  Instances       Size\n",
            "     42/149       2.9G    0.03625    0.03414    0.01018         10        640: 100% 502/502 [01:15<00:00,  6.66it/s]\n",
            "                 Class     Images  Instances          P          R      mAP50   mAP50-95: 100% 63/63 [00:08<00:00,  7.38it/s]\n",
            "                   all       1002       3172      0.693      0.613      0.663      0.399\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   obj_loss   cls_loss  Instances       Size\n",
            "     43/149       2.9G    0.03634    0.03497    0.01041          9        640: 100% 502/502 [01:13<00:00,  6.81it/s]\n",
            "                 Class     Images  Instances          P          R      mAP50   mAP50-95: 100% 63/63 [00:08<00:00,  7.64it/s]\n",
            "                   all       1002       3172      0.718      0.602      0.664      0.399\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   obj_loss   cls_loss  Instances       Size\n",
            "     44/149       2.9G    0.03634     0.0343    0.01013         13        640: 100% 502/502 [01:12<00:00,  6.91it/s]\n",
            "                 Class     Images  Instances          P          R      mAP50   mAP50-95: 100% 63/63 [00:08<00:00,  7.30it/s]\n",
            "                   all       1002       3172      0.716      0.595      0.663      0.405\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   obj_loss   cls_loss  Instances       Size\n",
            "     45/149       2.9G    0.03568    0.03418   0.009689          7        640: 100% 502/502 [01:12<00:00,  6.91it/s]\n",
            "                 Class     Images  Instances          P          R      mAP50   mAP50-95: 100% 63/63 [00:08<00:00,  7.54it/s]\n",
            "                   all       1002       3172      0.699      0.614      0.661        0.4\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   obj_loss   cls_loss  Instances       Size\n",
            "     46/149       2.9G    0.03539    0.03342    0.00994          8        640: 100% 502/502 [01:12<00:00,  6.92it/s]\n",
            "                 Class     Images  Instances          P          R      mAP50   mAP50-95: 100% 63/63 [00:08<00:00,  7.53it/s]\n",
            "                   all       1002       3172       0.72       0.63      0.672      0.403\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   obj_loss   cls_loss  Instances       Size\n",
            "     47/149       2.9G    0.03545    0.03283   0.009641          7        640: 100% 502/502 [01:12<00:00,  6.90it/s]\n",
            "                 Class     Images  Instances          P          R      mAP50   mAP50-95: 100% 63/63 [00:08<00:00,  7.76it/s]\n",
            "                   all       1002       3172      0.707      0.625      0.677      0.412\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   obj_loss   cls_loss  Instances       Size\n",
            "     48/149       2.9G    0.03541    0.03385   0.009505         11        640: 100% 502/502 [01:14<00:00,  6.77it/s]\n",
            "                 Class     Images  Instances          P          R      mAP50   mAP50-95: 100% 63/63 [00:07<00:00,  7.91it/s]\n",
            "                   all       1002       3172      0.743      0.606      0.681      0.416\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   obj_loss   cls_loss  Instances       Size\n",
            "     49/149       2.9G     0.0351    0.03333   0.009672          9        640: 100% 502/502 [01:13<00:00,  6.86it/s]\n",
            "                 Class     Images  Instances          P          R      mAP50   mAP50-95: 100% 63/63 [00:07<00:00,  7.91it/s]\n",
            "                   all       1002       3172      0.731      0.604      0.673      0.411\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   obj_loss   cls_loss  Instances       Size\n",
            "     50/149       2.9G    0.03498    0.03384   0.009509         15        640: 100% 502/502 [01:12<00:00,  6.90it/s]\n",
            "                 Class     Images  Instances          P          R      mAP50   mAP50-95: 100% 63/63 [00:08<00:00,  7.42it/s]\n",
            "                   all       1002       3172       0.73      0.629       0.68      0.413\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   obj_loss   cls_loss  Instances       Size\n",
            "     51/149       2.9G    0.03505    0.03348   0.008996          3        640: 100% 502/502 [01:12<00:00,  6.96it/s]\n",
            "                 Class     Images  Instances          P          R      mAP50   mAP50-95: 100% 63/63 [00:08<00:00,  7.51it/s]\n",
            "                   all       1002       3172      0.668      0.621      0.663      0.403\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   obj_loss   cls_loss  Instances       Size\n",
            "     52/149       2.9G    0.03469    0.03336   0.009002          6        640: 100% 502/502 [01:12<00:00,  6.92it/s]\n",
            "                 Class     Images  Instances          P          R      mAP50   mAP50-95: 100% 63/63 [00:08<00:00,  7.18it/s]\n",
            "                   all       1002       3172      0.745      0.616      0.686      0.409\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   obj_loss   cls_loss  Instances       Size\n",
            "     53/149       2.9G    0.03474     0.0331     0.0089          5        640: 100% 502/502 [01:14<00:00,  6.77it/s]\n",
            "                 Class     Images  Instances          P          R      mAP50   mAP50-95: 100% 63/63 [00:08<00:00,  7.40it/s]\n",
            "                   all       1002       3172      0.728      0.628      0.687      0.414\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   obj_loss   cls_loss  Instances       Size\n",
            "     54/149       2.9G    0.03456    0.03315   0.009148          4        640: 100% 502/502 [01:14<00:00,  6.73it/s]\n",
            "                 Class     Images  Instances          P          R      mAP50   mAP50-95: 100% 63/63 [00:08<00:00,  7.30it/s]\n",
            "                   all       1002       3172      0.719      0.624      0.675      0.409\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   obj_loss   cls_loss  Instances       Size\n",
            "     55/149       2.9G     0.0344    0.03258   0.009207         15        640: 100% 502/502 [01:15<00:00,  6.62it/s]\n",
            "                 Class     Images  Instances          P          R      mAP50   mAP50-95: 100% 63/63 [00:08<00:00,  7.37it/s]\n",
            "                   all       1002       3172      0.729      0.627      0.683      0.417\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   obj_loss   cls_loss  Instances       Size\n",
            "     56/149       2.9G    0.03445    0.03241   0.008677          6        640: 100% 502/502 [01:12<00:00,  6.89it/s]\n",
            "                 Class     Images  Instances          P          R      mAP50   mAP50-95: 100% 63/63 [00:08<00:00,  7.69it/s]\n",
            "                   all       1002       3172      0.694      0.625      0.677      0.415\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   obj_loss   cls_loss  Instances       Size\n",
            "     57/149       2.9G     0.0338    0.03223   0.008536         14        640: 100% 502/502 [01:12<00:00,  6.89it/s]\n",
            "                 Class     Images  Instances          P          R      mAP50   mAP50-95: 100% 63/63 [00:08<00:00,  7.75it/s]\n",
            "                   all       1002       3172       0.73      0.621      0.677      0.416\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   obj_loss   cls_loss  Instances       Size\n",
            "     58/149       2.9G    0.03391    0.03259   0.008712         29        640: 100% 502/502 [01:14<00:00,  6.71it/s]\n",
            "                 Class     Images  Instances          P          R      mAP50   mAP50-95: 100% 63/63 [00:08<00:00,  7.77it/s]\n",
            "                   all       1002       3172      0.704      0.632      0.679      0.419\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   obj_loss   cls_loss  Instances       Size\n",
            "     59/149       2.9G    0.03395    0.03259   0.008685         11        640: 100% 502/502 [01:12<00:00,  6.93it/s]\n",
            "                 Class     Images  Instances          P          R      mAP50   mAP50-95: 100% 63/63 [00:08<00:00,  7.49it/s]\n",
            "                   all       1002       3172      0.746      0.634      0.686      0.422\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   obj_loss   cls_loss  Instances       Size\n",
            "     60/149       2.9G    0.03378    0.03236   0.008498          8        640: 100% 502/502 [01:11<00:00,  6.98it/s]\n",
            "                 Class     Images  Instances          P          R      mAP50   mAP50-95: 100% 63/63 [00:08<00:00,  7.43it/s]\n",
            "                   all       1002       3172      0.716      0.638      0.684      0.418\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   obj_loss   cls_loss  Instances       Size\n",
            "     61/149       2.9G    0.03345     0.0317   0.008396         20        640: 100% 502/502 [01:12<00:00,  6.95it/s]\n",
            "                 Class     Images  Instances          P          R      mAP50   mAP50-95: 100% 63/63 [00:08<00:00,  7.58it/s]\n",
            "                   all       1002       3172      0.715      0.642      0.679      0.419\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   obj_loss   cls_loss  Instances       Size\n",
            "     62/149       2.9G    0.03311    0.03199   0.008054         19        640: 100% 502/502 [01:13<00:00,  6.82it/s]\n",
            "                 Class     Images  Instances          P          R      mAP50   mAP50-95: 100% 63/63 [00:08<00:00,  7.74it/s]\n",
            "                   all       1002       3172      0.713      0.639       0.68      0.418\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   obj_loss   cls_loss  Instances       Size\n",
            "     63/149       2.9G    0.03338    0.03205   0.008458         11        640: 100% 502/502 [01:13<00:00,  6.87it/s]\n",
            "                 Class     Images  Instances          P          R      mAP50   mAP50-95: 100% 63/63 [00:08<00:00,  7.70it/s]\n",
            "                   all       1002       3172      0.738       0.64       0.69      0.425\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   obj_loss   cls_loss  Instances       Size\n",
            "     64/149       2.9G    0.03343    0.03139    0.00862         12        640: 100% 502/502 [01:13<00:00,  6.85it/s]\n",
            "                 Class     Images  Instances          P          R      mAP50   mAP50-95: 100% 63/63 [00:08<00:00,  7.67it/s]\n",
            "                   all       1002       3172      0.732      0.648      0.687      0.428\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   obj_loss   cls_loss  Instances       Size\n",
            "     65/149       2.9G     0.0332    0.03191   0.007748         13        640: 100% 502/502 [01:13<00:00,  6.84it/s]\n",
            "                 Class     Images  Instances          P          R      mAP50   mAP50-95: 100% 63/63 [00:08<00:00,  7.32it/s]\n",
            "                   all       1002       3172      0.724      0.644       0.69      0.428\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   obj_loss   cls_loss  Instances       Size\n",
            "     66/149       2.9G    0.03293     0.0319   0.008059         12        640: 100% 502/502 [01:14<00:00,  6.74it/s]\n",
            "                 Class     Images  Instances          P          R      mAP50   mAP50-95: 100% 63/63 [00:08<00:00,  7.25it/s]\n",
            "                   all       1002       3172      0.711      0.645      0.689      0.427\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   obj_loss   cls_loss  Instances       Size\n",
            "     67/149       2.9G    0.03251    0.03157   0.007758         12        640: 100% 502/502 [01:13<00:00,  6.87it/s]\n",
            "                 Class     Images  Instances          P          R      mAP50   mAP50-95: 100% 63/63 [00:08<00:00,  7.61it/s]\n",
            "                   all       1002       3172      0.726      0.653      0.691      0.432\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   obj_loss   cls_loss  Instances       Size\n",
            "     68/149       2.9G    0.03276    0.03123   0.007741          5        640: 100% 502/502 [01:12<00:00,  6.90it/s]\n",
            "                 Class     Images  Instances          P          R      mAP50   mAP50-95: 100% 63/63 [00:08<00:00,  7.46it/s]\n",
            "                   all       1002       3172      0.718      0.641      0.685      0.431\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   obj_loss   cls_loss  Instances       Size\n",
            "     69/149       2.9G    0.03258    0.03106   0.007866         10        640: 100% 502/502 [01:13<00:00,  6.83it/s]\n",
            "                 Class     Images  Instances          P          R      mAP50   mAP50-95: 100% 63/63 [00:08<00:00,  7.25it/s]\n",
            "                   all       1002       3172      0.748      0.628      0.686      0.427\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   obj_loss   cls_loss  Instances       Size\n",
            "     70/149       2.9G    0.03264    0.03122     0.0081          8        640: 100% 502/502 [01:12<00:00,  6.89it/s]\n",
            "                 Class     Images  Instances          P          R      mAP50   mAP50-95: 100% 63/63 [00:08<00:00,  7.65it/s]\n",
            "                   all       1002       3172      0.733      0.633      0.685      0.424\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   obj_loss   cls_loss  Instances       Size\n",
            "     71/149       2.9G    0.03217    0.03112    0.00798         13        640: 100% 502/502 [01:12<00:00,  6.92it/s]\n",
            "                 Class     Images  Instances          P          R      mAP50   mAP50-95: 100% 63/63 [00:08<00:00,  7.52it/s]\n",
            "                   all       1002       3172      0.736      0.623      0.682      0.429\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   obj_loss   cls_loss  Instances       Size\n",
            "     72/149       2.9G    0.03237    0.03075   0.007752         16        640: 100% 502/502 [01:12<00:00,  6.91it/s]\n",
            "                 Class     Images  Instances          P          R      mAP50   mAP50-95: 100% 63/63 [00:08<00:00,  7.40it/s]\n",
            "                   all       1002       3172      0.745      0.619      0.683      0.429\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   obj_loss   cls_loss  Instances       Size\n",
            "     73/149       2.9G    0.03212    0.03101   0.007857          9        640: 100% 502/502 [01:13<00:00,  6.80it/s]\n",
            "                 Class     Images  Instances          P          R      mAP50   mAP50-95: 100% 63/63 [00:08<00:00,  7.39it/s]\n",
            "                   all       1002       3172      0.755      0.636      0.692      0.433\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   obj_loss   cls_loss  Instances       Size\n",
            "     74/149       2.9G    0.03222    0.03121   0.007884          8        640: 100% 502/502 [01:14<00:00,  6.71it/s]\n",
            "                 Class     Images  Instances          P          R      mAP50   mAP50-95: 100% 63/63 [00:08<00:00,  7.41it/s]\n",
            "                   all       1002       3172      0.744      0.625      0.686      0.428\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   obj_loss   cls_loss  Instances       Size\n",
            "     75/149       2.9G    0.03178    0.03047   0.007644         13        640: 100% 502/502 [01:13<00:00,  6.85it/s]\n",
            "                 Class     Images  Instances          P          R      mAP50   mAP50-95: 100% 63/63 [00:08<00:00,  7.55it/s]\n",
            "                   all       1002       3172      0.741      0.621      0.684      0.431\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   obj_loss   cls_loss  Instances       Size\n",
            "     76/149       2.9G    0.03186    0.03057   0.007358         17        640: 100% 502/502 [01:12<00:00,  6.88it/s]\n",
            "                 Class     Images  Instances          P          R      mAP50   mAP50-95: 100% 63/63 [00:08<00:00,  7.35it/s]\n",
            "                   all       1002       3172      0.715      0.639      0.682      0.429\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   obj_loss   cls_loss  Instances       Size\n",
            "     77/149       2.9G    0.03175    0.03029   0.007384          4        640: 100% 502/502 [01:14<00:00,  6.77it/s]\n",
            "                 Class     Images  Instances          P          R      mAP50   mAP50-95: 100% 63/63 [00:08<00:00,  7.50it/s]\n",
            "                   all       1002       3172      0.742      0.629      0.687      0.434\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   obj_loss   cls_loss  Instances       Size\n",
            "     78/149       2.9G    0.03142    0.03027   0.007343          6        640: 100% 502/502 [01:12<00:00,  6.92it/s]\n",
            "                 Class     Images  Instances          P          R      mAP50   mAP50-95: 100% 63/63 [00:08<00:00,  7.64it/s]\n",
            "                   all       1002       3172      0.723      0.636      0.686      0.438\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   obj_loss   cls_loss  Instances       Size\n",
            "     79/149       2.9G    0.03145    0.02986   0.007444         15        640: 100% 502/502 [01:13<00:00,  6.84it/s]\n",
            "                 Class     Images  Instances          P          R      mAP50   mAP50-95: 100% 63/63 [00:08<00:00,  7.69it/s]\n",
            "                   all       1002       3172      0.778      0.602      0.683      0.435\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   obj_loss   cls_loss  Instances       Size\n",
            "     80/149       2.9G    0.03133    0.02983   0.007695         16        640: 100% 502/502 [01:14<00:00,  6.78it/s]\n",
            "                 Class     Images  Instances          P          R      mAP50   mAP50-95: 100% 63/63 [00:08<00:00,  7.66it/s]\n",
            "                   all       1002       3172      0.753      0.627      0.689      0.436\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   obj_loss   cls_loss  Instances       Size\n",
            "     81/149       2.9G    0.03121    0.03015   0.007313          6        640: 100% 502/502 [01:12<00:00,  6.89it/s]\n",
            "                 Class     Images  Instances          P          R      mAP50   mAP50-95: 100% 63/63 [00:08<00:00,  7.24it/s]\n",
            "                   all       1002       3172      0.763      0.623      0.694       0.44\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   obj_loss   cls_loss  Instances       Size\n",
            "     82/149       2.9G     0.0312    0.03018   0.007432         26        640: 100% 502/502 [01:14<00:00,  6.73it/s]\n",
            "                 Class     Images  Instances          P          R      mAP50   mAP50-95: 100% 63/63 [00:08<00:00,  7.42it/s]\n",
            "                   all       1002       3172      0.749      0.636      0.695       0.44\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   obj_loss   cls_loss  Instances       Size\n",
            "     83/149       2.9G    0.03154    0.03001   0.007192         11        640: 100% 502/502 [01:13<00:00,  6.87it/s]\n",
            "                 Class     Images  Instances          P          R      mAP50   mAP50-95: 100% 63/63 [00:08<00:00,  7.61it/s]\n",
            "                   all       1002       3172      0.751      0.623      0.685      0.434\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   obj_loss   cls_loss  Instances       Size\n",
            "     84/149       2.9G    0.03073    0.03028   0.007059         14        640: 100% 502/502 [01:14<00:00,  6.75it/s]\n",
            "                 Class     Images  Instances          P          R      mAP50   mAP50-95: 100% 63/63 [00:09<00:00,  6.90it/s]\n",
            "                   all       1002       3172      0.739      0.641      0.694      0.439\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   obj_loss   cls_loss  Instances       Size\n",
            "     85/149       2.9G    0.03094    0.03002   0.006818         15        640: 100% 502/502 [01:16<00:00,  6.58it/s]\n",
            "                 Class     Images  Instances          P          R      mAP50   mAP50-95: 100% 63/63 [00:08<00:00,  7.33it/s]\n",
            "                   all       1002       3172      0.738      0.649      0.698      0.441\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   obj_loss   cls_loss  Instances       Size\n",
            "     86/149       2.9G    0.03083    0.02941    0.00706         21        640: 100% 502/502 [01:13<00:00,  6.85it/s]\n",
            "                 Class     Images  Instances          P          R      mAP50   mAP50-95: 100% 63/63 [00:08<00:00,  7.47it/s]\n",
            "                   all       1002       3172      0.768       0.64      0.703      0.446\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   obj_loss   cls_loss  Instances       Size\n",
            "     87/149       2.9G    0.03074    0.02956   0.007101          4        640: 100% 502/502 [01:13<00:00,  6.87it/s]\n",
            "                 Class     Images  Instances          P          R      mAP50   mAP50-95: 100% 63/63 [00:08<00:00,  7.46it/s]\n",
            "                   all       1002       3172      0.723      0.659      0.695      0.441\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   obj_loss   cls_loss  Instances       Size\n",
            "     88/149       2.9G    0.03048    0.02971   0.006839         25        640: 100% 502/502 [01:15<00:00,  6.68it/s]\n",
            "                 Class     Images  Instances          P          R      mAP50   mAP50-95: 100% 63/63 [00:08<00:00,  7.61it/s]\n",
            "                   all       1002       3172      0.754       0.65      0.707      0.448\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   obj_loss   cls_loss  Instances       Size\n",
            "     89/149       2.9G    0.03055    0.02946   0.006886          8        640: 100% 502/502 [01:14<00:00,  6.72it/s]\n",
            "                 Class     Images  Instances          P          R      mAP50   mAP50-95: 100% 63/63 [00:08<00:00,  7.77it/s]\n",
            "                   all       1002       3172      0.751      0.642      0.698      0.444\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   obj_loss   cls_loss  Instances       Size\n",
            "     90/149       2.9G    0.03038    0.02966   0.006768         34        640: 100% 502/502 [01:14<00:00,  6.70it/s]\n",
            "                 Class     Images  Instances          P          R      mAP50   mAP50-95: 100% 63/63 [00:08<00:00,  7.74it/s]\n",
            "                   all       1002       3172       0.74      0.644      0.694      0.442\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   obj_loss   cls_loss  Instances       Size\n",
            "     91/149       2.9G    0.03029    0.02912   0.006829         17        640: 100% 502/502 [01:16<00:00,  6.56it/s]\n",
            "                 Class     Images  Instances          P          R      mAP50   mAP50-95: 100% 63/63 [00:08<00:00,  7.73it/s]\n",
            "                   all       1002       3172      0.759       0.65        0.7      0.449\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   obj_loss   cls_loss  Instances       Size\n",
            "     92/149       2.9G     0.0304    0.02889   0.006689          9        640: 100% 502/502 [01:14<00:00,  6.76it/s]\n",
            "                 Class     Images  Instances          P          R      mAP50   mAP50-95: 100% 63/63 [00:08<00:00,  7.61it/s]\n",
            "                   all       1002       3172       0.76      0.632      0.698      0.444\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   obj_loss   cls_loss  Instances       Size\n",
            "     93/149       2.9G       0.03    0.02929   0.006485         10        640: 100% 502/502 [01:13<00:00,  6.79it/s]\n",
            "                 Class     Images  Instances          P          R      mAP50   mAP50-95: 100% 63/63 [00:08<00:00,  7.31it/s]\n",
            "                   all       1002       3172      0.738       0.65      0.698      0.442\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   obj_loss   cls_loss  Instances       Size\n",
            "     94/149       2.9G    0.02979    0.02877   0.006547         12        640: 100% 502/502 [01:14<00:00,  6.71it/s]\n",
            "                 Class     Images  Instances          P          R      mAP50   mAP50-95: 100% 63/63 [00:08<00:00,  7.50it/s]\n",
            "                   all       1002       3172      0.751      0.635      0.695      0.446\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   obj_loss   cls_loss  Instances       Size\n",
            "     95/149       2.9G     0.0302    0.02935     0.0064         12        640: 100% 502/502 [01:14<00:00,  6.77it/s]\n",
            "                 Class     Images  Instances          P          R      mAP50   mAP50-95: 100% 63/63 [00:08<00:00,  7.35it/s]\n",
            "                   all       1002       3172      0.751      0.643      0.693      0.443\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   obj_loss   cls_loss  Instances       Size\n",
            "     96/149       2.9G    0.02993    0.02911   0.006246         16        640: 100% 502/502 [01:13<00:00,  6.81it/s]\n",
            "                 Class     Images  Instances          P          R      mAP50   mAP50-95: 100% 63/63 [00:08<00:00,  7.44it/s]\n",
            "                   all       1002       3172      0.746      0.649      0.693      0.441\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   obj_loss   cls_loss  Instances       Size\n",
            "     97/149       2.9G    0.02941    0.02884   0.006479         14        640: 100% 502/502 [01:13<00:00,  6.83it/s]\n",
            "                 Class     Images  Instances          P          R      mAP50   mAP50-95: 100% 63/63 [00:09<00:00,  6.89it/s]\n",
            "                   all       1002       3172      0.727      0.656      0.692      0.447\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   obj_loss   cls_loss  Instances       Size\n",
            "     98/149       2.9G    0.02948    0.02873   0.006201          8        640: 100% 502/502 [01:14<00:00,  6.75it/s]\n",
            "                 Class     Images  Instances          P          R      mAP50   mAP50-95: 100% 63/63 [00:08<00:00,  7.58it/s]\n",
            "                   all       1002       3172       0.75      0.649        0.7       0.45\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   obj_loss   cls_loss  Instances       Size\n",
            "     99/149       2.9G    0.02919    0.02802   0.006247         18        640: 100% 502/502 [01:14<00:00,  6.72it/s]\n",
            "                 Class     Images  Instances          P          R      mAP50   mAP50-95: 100% 63/63 [00:08<00:00,  7.48it/s]\n",
            "                   all       1002       3172      0.744      0.644      0.694      0.447\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   obj_loss   cls_loss  Instances       Size\n",
            "    100/149       2.9G    0.02898    0.02799   0.006656         33        640: 100% 502/502 [01:14<00:00,  6.78it/s]\n",
            "                 Class     Images  Instances          P          R      mAP50   mAP50-95: 100% 63/63 [00:08<00:00,  7.56it/s]\n",
            "                   all       1002       3172      0.741      0.656      0.696      0.446\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   obj_loss   cls_loss  Instances       Size\n",
            "    101/149       2.9G    0.02919    0.02771   0.006448          5        640: 100% 502/502 [01:15<00:00,  6.69it/s]\n",
            "                 Class     Images  Instances          P          R      mAP50   mAP50-95: 100% 63/63 [00:08<00:00,  7.60it/s]\n",
            "                   all       1002       3172      0.735      0.642      0.689       0.44\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   obj_loss   cls_loss  Instances       Size\n",
            "    102/149       2.9G    0.02938    0.02877   0.006161         10        640: 100% 502/502 [01:14<00:00,  6.76it/s]\n",
            "                 Class     Images  Instances          P          R      mAP50   mAP50-95: 100% 63/63 [00:08<00:00,  7.59it/s]\n",
            "                   all       1002       3172      0.738      0.647      0.694      0.445\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   obj_loss   cls_loss  Instances       Size\n",
            "    103/149       2.9G    0.02875    0.02835   0.005961          4        640: 100% 502/502 [01:15<00:00,  6.66it/s]\n",
            "                 Class     Images  Instances          P          R      mAP50   mAP50-95: 100% 63/63 [00:08<00:00,  7.71it/s]\n",
            "                   all       1002       3172      0.754      0.643      0.697       0.45\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   obj_loss   cls_loss  Instances       Size\n",
            "    104/149       2.9G    0.02897     0.0282   0.005941         19        640: 100% 502/502 [01:15<00:00,  6.66it/s]\n",
            "                 Class     Images  Instances          P          R      mAP50   mAP50-95: 100% 63/63 [00:08<00:00,  7.87it/s]\n",
            "                   all       1002       3172      0.751      0.643      0.697      0.453\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   obj_loss   cls_loss  Instances       Size\n",
            "    105/149       2.9G    0.02868    0.02748   0.005934          6        640: 100% 502/502 [01:14<00:00,  6.71it/s]\n",
            "                 Class     Images  Instances          P          R      mAP50   mAP50-95: 100% 63/63 [00:08<00:00,  7.67it/s]\n",
            "                   all       1002       3172      0.764      0.642      0.701      0.455\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   obj_loss   cls_loss  Instances       Size\n",
            "    106/149       2.9G    0.02881    0.02771   0.005924          9        640: 100% 502/502 [01:14<00:00,  6.73it/s]\n",
            "                 Class     Images  Instances          P          R      mAP50   mAP50-95: 100% 63/63 [00:08<00:00,  7.49it/s]\n",
            "                   all       1002       3172      0.765      0.638      0.694      0.447\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   obj_loss   cls_loss  Instances       Size\n",
            "    107/149       2.9G    0.02869    0.02784   0.005957          7        640: 100% 502/502 [01:13<00:00,  6.79it/s]\n",
            "                 Class     Images  Instances          P          R      mAP50   mAP50-95: 100% 63/63 [00:08<00:00,  7.19it/s]\n",
            "                   all       1002       3172      0.762      0.628      0.692      0.446\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   obj_loss   cls_loss  Instances       Size\n",
            "    108/149       2.9G     0.0287    0.02746   0.005931         25        640: 100% 502/502 [01:14<00:00,  6.77it/s]\n",
            "                 Class     Images  Instances          P          R      mAP50   mAP50-95: 100% 63/63 [00:08<00:00,  7.51it/s]\n",
            "                   all       1002       3172      0.767      0.636      0.691      0.449\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   obj_loss   cls_loss  Instances       Size\n",
            "    109/149       2.9G    0.02848      0.027   0.005832          9        640: 100% 502/502 [01:13<00:00,  6.84it/s]\n",
            "                 Class     Images  Instances          P          R      mAP50   mAP50-95: 100% 63/63 [00:08<00:00,  7.41it/s]\n",
            "                   all       1002       3172      0.759      0.643      0.692      0.448\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   obj_loss   cls_loss  Instances       Size\n",
            "    110/149       2.9G    0.02889    0.02756   0.005962          8        640: 100% 502/502 [01:14<00:00,  6.76it/s]\n",
            "                 Class     Images  Instances          P          R      mAP50   mAP50-95: 100% 63/63 [00:08<00:00,  7.52it/s]\n",
            "                   all       1002       3172      0.768      0.633      0.701      0.452\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   obj_loss   cls_loss  Instances       Size\n",
            "    111/149       2.9G    0.02807    0.02724   0.005618         14        640: 100% 502/502 [01:15<00:00,  6.68it/s]\n",
            "                 Class     Images  Instances          P          R      mAP50   mAP50-95: 100% 63/63 [00:08<00:00,  7.30it/s]\n",
            "                   all       1002       3172      0.757      0.637      0.701      0.451\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   obj_loss   cls_loss  Instances       Size\n",
            "    112/149       2.9G    0.02818    0.02707     0.0054         10        640: 100% 502/502 [01:13<00:00,  6.82it/s]\n",
            "                 Class     Images  Instances          P          R      mAP50   mAP50-95: 100% 63/63 [00:08<00:00,  7.59it/s]\n",
            "                   all       1002       3172      0.754      0.637      0.705      0.454\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   obj_loss   cls_loss  Instances       Size\n",
            "    113/149       2.9G    0.02786    0.02684   0.005605          6        640: 100% 502/502 [01:13<00:00,  6.81it/s]\n",
            "                 Class     Images  Instances          P          R      mAP50   mAP50-95: 100% 63/63 [00:08<00:00,  7.63it/s]\n",
            "                   all       1002       3172      0.762      0.627      0.702      0.451\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   obj_loss   cls_loss  Instances       Size\n",
            "    114/149       2.9G    0.02767    0.02703   0.005478         12        640: 100% 502/502 [01:13<00:00,  6.79it/s]\n",
            "                 Class     Images  Instances          P          R      mAP50   mAP50-95: 100% 63/63 [00:08<00:00,  7.21it/s]\n",
            "                   all       1002       3172      0.772      0.638      0.708      0.458\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   obj_loss   cls_loss  Instances       Size\n",
            "    115/149       2.9G    0.02766    0.02725   0.005574         26        640: 100% 502/502 [01:14<00:00,  6.73it/s]\n",
            "                 Class     Images  Instances          P          R      mAP50   mAP50-95: 100% 63/63 [00:08<00:00,  7.51it/s]\n",
            "                   all       1002       3172      0.748      0.667      0.713      0.462\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   obj_loss   cls_loss  Instances       Size\n",
            "    116/149       2.9G    0.02768    0.02659   0.005535         14        640: 100% 502/502 [01:14<00:00,  6.74it/s]\n",
            "                 Class     Images  Instances          P          R      mAP50   mAP50-95: 100% 63/63 [00:08<00:00,  7.47it/s]\n",
            "                   all       1002       3172      0.765      0.654      0.711      0.461\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   obj_loss   cls_loss  Instances       Size\n",
            "    117/149       2.9G    0.02726    0.02653   0.005378          8        640: 100% 502/502 [01:14<00:00,  6.78it/s]\n",
            "                 Class     Images  Instances          P          R      mAP50   mAP50-95: 100% 63/63 [00:08<00:00,  7.28it/s]\n",
            "                   all       1002       3172      0.754      0.645      0.707      0.459\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   obj_loss   cls_loss  Instances       Size\n",
            "    118/149       2.9G    0.02738    0.02701   0.005212         11        640: 100% 502/502 [01:15<00:00,  6.62it/s]\n",
            "                 Class     Images  Instances          P          R      mAP50   mAP50-95: 100% 63/63 [00:08<00:00,  7.39it/s]\n",
            "                   all       1002       3172      0.766      0.649      0.709      0.462\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   obj_loss   cls_loss  Instances       Size\n",
            "    119/149       2.9G     0.0272    0.02659   0.005221          5        640: 100% 502/502 [01:13<00:00,  6.80it/s]\n",
            "                 Class     Images  Instances          P          R      mAP50   mAP50-95: 100% 63/63 [00:08<00:00,  7.38it/s]\n",
            "                   all       1002       3172       0.78      0.627      0.706      0.459\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   obj_loss   cls_loss  Instances       Size\n",
            "    120/149       2.9G    0.02718    0.02637   0.005379         11        640: 100% 502/502 [01:13<00:00,  6.82it/s]\n",
            "                 Class     Images  Instances          P          R      mAP50   mAP50-95: 100% 63/63 [00:08<00:00,  7.26it/s]\n",
            "                   all       1002       3172      0.777      0.637      0.703      0.458\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   obj_loss   cls_loss  Instances       Size\n",
            "    121/149       2.9G    0.02713    0.02649   0.005329         21        640: 100% 502/502 [01:15<00:00,  6.67it/s]\n",
            "                 Class     Images  Instances          P          R      mAP50   mAP50-95: 100% 63/63 [00:08<00:00,  7.58it/s]\n",
            "                   all       1002       3172       0.77      0.636      0.701      0.454\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   obj_loss   cls_loss  Instances       Size\n",
            "    122/149       2.9G     0.0271    0.02659    0.00506          4        640: 100% 502/502 [01:13<00:00,  6.80it/s]\n",
            "                 Class     Images  Instances          P          R      mAP50   mAP50-95: 100% 63/63 [00:08<00:00,  7.38it/s]\n",
            "                   all       1002       3172      0.755      0.651        0.7      0.457\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   obj_loss   cls_loss  Instances       Size\n",
            "    123/149       2.9G     0.0267    0.02576   0.005069          7        640: 100% 502/502 [01:14<00:00,  6.76it/s]\n",
            "                 Class     Images  Instances          P          R      mAP50   mAP50-95: 100% 63/63 [00:08<00:00,  7.45it/s]\n",
            "                   all       1002       3172      0.745      0.654      0.697      0.456\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   obj_loss   cls_loss  Instances       Size\n",
            "    124/149       2.9G    0.02656    0.02633   0.004947         10        640: 100% 502/502 [01:14<00:00,  6.72it/s]\n",
            "                 Class     Images  Instances          P          R      mAP50   mAP50-95: 100% 63/63 [00:08<00:00,  7.70it/s]\n",
            "                   all       1002       3172      0.762      0.644      0.699      0.456\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   obj_loss   cls_loss  Instances       Size\n",
            "    125/149       2.9G    0.02691     0.0262   0.005004         12        640: 100% 502/502 [01:13<00:00,  6.82it/s]\n",
            "                 Class     Images  Instances          P          R      mAP50   mAP50-95: 100% 63/63 [00:08<00:00,  7.69it/s]\n",
            "                   all       1002       3172       0.76      0.645        0.7       0.46\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   obj_loss   cls_loss  Instances       Size\n",
            "    126/149       2.9G    0.02663    0.02567   0.005104         13        640: 100% 502/502 [01:14<00:00,  6.75it/s]\n",
            "                 Class     Images  Instances          P          R      mAP50   mAP50-95: 100% 63/63 [00:08<00:00,  7.78it/s]\n",
            "                   all       1002       3172      0.777      0.643      0.705      0.461\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   obj_loss   cls_loss  Instances       Size\n",
            "    127/149       2.9G    0.02635    0.02608    0.00497         31        640: 100% 502/502 [01:15<00:00,  6.65it/s]\n",
            "                 Class     Images  Instances          P          R      mAP50   mAP50-95: 100% 63/63 [00:08<00:00,  7.53it/s]\n",
            "                   all       1002       3172      0.769      0.646      0.702      0.459\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   obj_loss   cls_loss  Instances       Size\n",
            "    128/149       2.9G    0.02636    0.02609   0.005015          6        640: 100% 502/502 [01:13<00:00,  6.81it/s]\n",
            "                 Class     Images  Instances          P          R      mAP50   mAP50-95: 100% 63/63 [00:08<00:00,  7.32it/s]\n",
            "                   all       1002       3172      0.762      0.647      0.705      0.459\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   obj_loss   cls_loss  Instances       Size\n",
            "    129/149       2.9G    0.02649     0.0259   0.004947         10        640: 100% 502/502 [01:13<00:00,  6.86it/s]\n",
            "                 Class     Images  Instances          P          R      mAP50   mAP50-95: 100% 63/63 [00:08<00:00,  7.48it/s]\n",
            "                   all       1002       3172      0.771       0.65      0.705      0.461\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   obj_loss   cls_loss  Instances       Size\n",
            "    130/149       2.9G    0.02604    0.02563   0.004786         12        640: 100% 502/502 [01:14<00:00,  6.72it/s]\n",
            "                 Class     Images  Instances          P          R      mAP50   mAP50-95: 100% 63/63 [00:08<00:00,  7.50it/s]\n",
            "                   all       1002       3172      0.767      0.646        0.7      0.459\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   obj_loss   cls_loss  Instances       Size\n",
            "    131/149       2.9G    0.02644    0.02608   0.005164          9        640: 100% 502/502 [01:14<00:00,  6.76it/s]\n",
            "                 Class     Images  Instances          P          R      mAP50   mAP50-95: 100% 63/63 [00:08<00:00,  7.27it/s]\n",
            "                   all       1002       3172       0.76      0.642      0.698      0.457\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   obj_loss   cls_loss  Instances       Size\n",
            "    132/149       2.9G    0.02599    0.02523   0.004867         10        640: 100% 502/502 [01:13<00:00,  6.83it/s]\n",
            "                 Class     Images  Instances          P          R      mAP50   mAP50-95: 100% 63/63 [00:08<00:00,  7.49it/s]\n",
            "                   all       1002       3172      0.754      0.652        0.7      0.458\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   obj_loss   cls_loss  Instances       Size\n",
            "    133/149       2.9G    0.02577     0.0258    0.00459         11        640: 100% 502/502 [01:14<00:00,  6.74it/s]\n",
            "                 Class     Images  Instances          P          R      mAP50   mAP50-95: 100% 63/63 [00:08<00:00,  7.36it/s]\n",
            "                   all       1002       3172      0.768      0.641      0.698      0.456\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   obj_loss   cls_loss  Instances       Size\n",
            "    134/149       2.9G    0.02604    0.02603   0.004709         11        640: 100% 502/502 [01:13<00:00,  6.79it/s]\n",
            "                 Class     Images  Instances          P          R      mAP50   mAP50-95: 100% 63/63 [00:08<00:00,  7.66it/s]\n",
            "                   all       1002       3172      0.772      0.641      0.698      0.459\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   obj_loss   cls_loss  Instances       Size\n",
            "    135/149       2.9G    0.02589     0.0255   0.004791         19        640: 100% 502/502 [01:14<00:00,  6.78it/s]\n",
            "                 Class     Images  Instances          P          R      mAP50   mAP50-95: 100% 63/63 [00:08<00:00,  7.80it/s]\n",
            "                   all       1002       3172      0.781       0.64        0.7      0.458\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   obj_loss   cls_loss  Instances       Size\n",
            "    136/149       2.9G    0.02586    0.02593   0.004624          7        640: 100% 502/502 [01:16<00:00,  6.58it/s]\n",
            "                 Class     Images  Instances          P          R      mAP50   mAP50-95: 100% 63/63 [00:08<00:00,  7.62it/s]\n",
            "                   all       1002       3172      0.772      0.645      0.703      0.459\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   obj_loss   cls_loss  Instances       Size\n",
            "    137/149       2.9G    0.02563    0.02495   0.004667         18        640: 100% 502/502 [01:14<00:00,  6.70it/s]\n",
            "                 Class     Images  Instances          P          R      mAP50   mAP50-95: 100% 63/63 [00:08<00:00,  7.69it/s]\n",
            "                   all       1002       3172      0.775      0.639      0.702       0.46\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   obj_loss   cls_loss  Instances       Size\n",
            "    138/149       2.9G    0.02567    0.02545   0.004724         17        640: 100% 502/502 [01:14<00:00,  6.76it/s]\n",
            "                 Class     Images  Instances          P          R      mAP50   mAP50-95: 100% 63/63 [00:08<00:00,  7.50it/s]\n",
            "                   all       1002       3172      0.764      0.648      0.704       0.46\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   obj_loss   cls_loss  Instances       Size\n",
            "    139/149       2.9G    0.02517    0.02479   0.004653          6        640: 100% 502/502 [01:14<00:00,  6.75it/s]\n",
            "                 Class     Images  Instances          P          R      mAP50   mAP50-95: 100% 63/63 [00:08<00:00,  7.19it/s]\n",
            "                   all       1002       3172      0.749      0.653      0.703       0.46\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   obj_loss   cls_loss  Instances       Size\n",
            "    140/149       2.9G    0.02562    0.02526   0.004914         11        640: 100% 502/502 [01:15<00:00,  6.68it/s]\n",
            "                 Class     Images  Instances          P          R      mAP50   mAP50-95: 100% 63/63 [00:08<00:00,  7.25it/s]\n",
            "                   all       1002       3172      0.784      0.632      0.703       0.46\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   obj_loss   cls_loss  Instances       Size\n",
            "    141/149       2.9G    0.02527    0.02507   0.004592          9        640: 100% 502/502 [01:14<00:00,  6.70it/s]\n",
            "                 Class     Images  Instances          P          R      mAP50   mAP50-95: 100% 63/63 [00:08<00:00,  7.36it/s]\n",
            "                   all       1002       3172      0.769      0.645      0.703      0.461\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   obj_loss   cls_loss  Instances       Size\n",
            "    142/149       2.9G    0.02515    0.02467   0.004567         15        640: 100% 502/502 [01:14<00:00,  6.76it/s]\n",
            "                 Class     Images  Instances          P          R      mAP50   mAP50-95: 100% 63/63 [00:08<00:00,  7.40it/s]\n",
            "                   all       1002       3172      0.775      0.643      0.703       0.46\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   obj_loss   cls_loss  Instances       Size\n",
            "    143/149       2.9G    0.02501     0.0249   0.004499          4        640: 100% 502/502 [01:15<00:00,  6.65it/s]\n",
            "                 Class     Images  Instances          P          R      mAP50   mAP50-95: 100% 63/63 [00:08<00:00,  7.35it/s]\n",
            "                   all       1002       3172      0.762      0.643      0.701      0.461\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   obj_loss   cls_loss  Instances       Size\n",
            "    144/149       2.9G    0.02514    0.02557   0.004743          4        640: 100% 502/502 [01:14<00:00,  6.74it/s]\n",
            "                 Class     Images  Instances          P          R      mAP50   mAP50-95: 100% 63/63 [00:08<00:00,  7.49it/s]\n",
            "                   all       1002       3172      0.783      0.633        0.7      0.461\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   obj_loss   cls_loss  Instances       Size\n",
            "    145/149       2.9G    0.02475    0.02483   0.004298         28        640: 100% 502/502 [01:14<00:00,  6.77it/s]\n",
            "                 Class     Images  Instances          P          R      mAP50   mAP50-95: 100% 63/63 [00:08<00:00,  7.56it/s]\n",
            "                   all       1002       3172      0.775      0.635      0.698       0.46\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   obj_loss   cls_loss  Instances       Size\n",
            "    146/149       2.9G    0.02497    0.02453   0.004418         18        640: 100% 502/502 [01:15<00:00,  6.67it/s]\n",
            "                 Class     Images  Instances          P          R      mAP50   mAP50-95: 100% 63/63 [00:08<00:00,  7.44it/s]\n",
            "                   all       1002       3172      0.775       0.63      0.698      0.461\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   obj_loss   cls_loss  Instances       Size\n",
            "    147/149       2.9G    0.02479    0.02477   0.004561         11        640: 100% 502/502 [01:14<00:00,  6.77it/s]\n",
            "                 Class     Images  Instances          P          R      mAP50   mAP50-95: 100% 63/63 [00:08<00:00,  7.52it/s]\n",
            "                   all       1002       3172      0.769      0.639      0.698      0.459\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   obj_loss   cls_loss  Instances       Size\n",
            "    148/149       2.9G    0.02459    0.02469   0.004332          9        640: 100% 502/502 [01:14<00:00,  6.74it/s]\n",
            "                 Class     Images  Instances          P          R      mAP50   mAP50-95: 100% 63/63 [00:08<00:00,  7.60it/s]\n",
            "                   all       1002       3172      0.771      0.633      0.697       0.46\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   obj_loss   cls_loss  Instances       Size\n",
            "    149/149       2.9G    0.02486    0.02462   0.004352         23        640: 100% 502/502 [01:15<00:00,  6.68it/s]\n",
            "                 Class     Images  Instances          P          R      mAP50   mAP50-95: 100% 63/63 [00:08<00:00,  7.55it/s]\n",
            "                   all       1002       3172      0.759      0.637      0.697       0.46\n",
            "\n",
            "150 epochs completed in 3.449 hours.\n",
            "Optimizer stripped from runs/train/Model/weights/last.pt, 14.5MB\n",
            "Optimizer stripped from runs/train/Model/weights/best.pt, 14.5MB\n",
            "\n",
            "Validating runs/train/Model/weights/best.pt...\n",
            "Fusing layers... \n",
            "Model summary: 157 layers, 7064065 parameters, 0 gradients, 15.9 GFLOPs\n",
            "                 Class     Images  Instances          P          R      mAP50   mAP50-95: 100% 63/63 [00:11<00:00,  5.67it/s]\n",
            "                   all       1002       3172      0.748      0.668      0.713      0.462\n",
            "                person       1002       1136      0.793      0.747      0.802      0.471\n",
            "                   car       1002        312      0.803      0.792      0.846      0.621\n",
            "                 chair       1002        285       0.69      0.572      0.621      0.367\n",
            "                bottle       1002        120      0.644      0.408      0.503      0.307\n",
            "           pottedplant       1002        136      0.701      0.574      0.583      0.244\n",
            "                  bird       1002        115      0.765      0.595      0.663      0.424\n",
            "                   dog       1002        112       0.76      0.678       0.73      0.506\n",
            "                  sofa       1002         80      0.684      0.562      0.568      0.376\n",
            "               bicycle       1002         79      0.804      0.726      0.793      0.507\n",
            "                 horse       1002         76      0.811      0.855      0.857      0.631\n",
            "                  boat       1002         86      0.639        0.5      0.542      0.271\n",
            "             motorbike       1002         85      0.713        0.8      0.804       0.55\n",
            "                   cat       1002         69      0.785      0.689      0.694      0.494\n",
            "             tvmonitor       1002         78       0.91      0.718      0.807      0.527\n",
            "                   cow       1002         81      0.721      0.556      0.681       0.45\n",
            "                 sheep       1002         76      0.712      0.748      0.783      0.456\n",
            "             aeroplane       1002         74      0.739       0.73      0.759      0.487\n",
            "                 train       1002         53      0.865      0.774      0.826      0.558\n",
            "           diningtable       1002         57      0.622      0.632      0.632      0.399\n",
            "                   bus       1002         62      0.803       0.71      0.767      0.585\n",
            "Results saved to \u001b[1mruns/train/Model\u001b[0m\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "## Resuming Training of the YOLOv5 Model"
      ],
      "metadata": {
        "id": "UDX386sZGJqJ"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "If you wish to resume training the model from a previously saved checkpoint, you can use the following command:"
      ],
      "metadata": {
        "id": "VdGCOpGNGK_Z"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "!python train.py --data data.yaml --weights run/train.Model/weights/best.pt --img 640 --batch-size 8 --name Model --epochs 50"
      ],
      "metadata": {
        "id": "hxqBzeJKFiOB"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "✅ **Here's an explanation of the command-line arguments used for resuming training:**\n",
        "\n",
        "* --data data.yaml: Specifies the same configuration file (data.yaml) used in the initial training, containing dataset information.\n",
        "\n",
        "* --weights run/train.Model/weights/best.pt: Indicates the path to the saved checkpoint weights file (best.pt) from which training will be resumed.\n",
        "\n",
        "* --img 640: Keeps the image size at 640 pixels, consistent with the initial training.\n",
        "\n",
        "* --batch-size 8: Maintains the same batch size of 8 as used earlier.\n",
        "\n",
        "* --name Model: Continues to identify the model with the name 'Model.'\n",
        "\n",
        "* --epochs 50: Specifies the additional number of training epochs as 50, defining how many more passes through the training data will be made.\n",
        "\n",
        "🔄 By using this command, you can continue training the model from where it was left off, allowing for further refinement or adaptation to new data."
      ],
      "metadata": {
        "id": "lshLFJeBGfj3"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "# export Model into ONNX file"
      ],
      "metadata": {
        "id": "i91jRvENTdfg"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "# Import the os module to interact with the operating system\n",
        "import os\n",
        "\n",
        "# Change the current working directory to the specified path\n",
        "os.chdir('/content/drive/MyDrive/yolo_training/yolov5')\n"
      ],
      "metadata": {
        "id": "f8YSXHRWUCnA"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "!ls"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "gShJjpG-UXsW",
        "outputId": "ae8651ab-36f0-43fc-85b9-c7ea6488e921"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "benchmarks.py    data.yaml   \u001b[0m\u001b[01;34m__pycache__\u001b[0m/      setup.cfg\n",
            "CITATION.cff     detect.py   README.md         train.py\n",
            "\u001b[01;34mclassify\u001b[0m/        export.py   README.zh-CN.md   tutorial.ipynb\n",
            "CONTRIBUTING.md  hubconf.py  requirements.txt  \u001b[01;34mutils\u001b[0m/\n",
            "\u001b[01;34mdata\u001b[0m/            LICENSE     \u001b[01;34mruns\u001b[0m/             val.py\n",
            "\u001b[01;34mdata_images\u001b[0m/     \u001b[01;34mmodels\u001b[0m/     \u001b[01;34msegment\u001b[0m/          yolov5s.pt\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "To export the trained YOLOv5 model to the ONNX (Open Neural Network Exchange) format, we use the following command:\n"
      ],
      "metadata": {
        "id": "DDS7eR-xHZck"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "✅ **Here's a breakdown of the command-line arguments:**\n",
        "\n",
        "* **--weights runs/train/Model/weights/best.pt** : Specifies the path to the saved checkpoint weights file (best.pt) that represents the trained model.\n",
        "\n",
        "* **--include onnx** : Indicates that the export format should be ONNX, a popular format for interchange between various deep learning frameworks.\n",
        "\n",
        "* **--simplify** : Enables model simplification, which can optimize the model by removing redundant operations, improving performance.\n",
        "\n",
        "* **--opset 12** : Sets the ONNX Operator Set version to 12, ensuring compatibility with specific versions of ONNX-supporting platforms.\n",
        "\n",
        "🔄 Exporting the model to ONNX format provides greater flexibility, allowing the model to be deployed and used across different platforms and tools that support the ONNX standard."
      ],
      "metadata": {
        "id": "z5xNJN1xHho3"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "!python export.py --weights runs/train/Model/weights/best.pt  --include onnx --simplify --opset 12"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "3Q5327P3Tn-j",
        "outputId": "a7a451d6-d48d-40d6-e03e-956c481beaa3"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "\u001b[34m\u001b[1mexport: \u001b[0mdata=data/coco128.yaml, weights=['runs/train/Model/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 🚀 v7.0-198-g34c2187 Python-3.10.6 torch-2.0.1+cu118 CPU\n",
            "\n",
            "Fusing layers... \n",
            "Model summary: 157 layers, 7064065 parameters, 0 gradients, 15.9 GFLOPs\n",
            "\n",
            "\u001b[34m\u001b[1mPyTorch:\u001b[0m starting from runs/train/Model/weights/best.pt with output shape (1, 25200, 25) (13.8 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-1.14.0-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (14.6 MB)\n",
            "     ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 14.6/14.6 MB 39.1 MB/s eta 0:00:00\n",
            "Requirement already satisfied: numpy in /usr/local/lib/python3.10/dist-packages (from onnx>=1.12.0) (1.22.4)\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",
            "Requirement already satisfied: typing-extensions>=3.6.2.1 in /usr/local/lib/python3.10/dist-packages (from onnx>=1.12.0) (4.7.1)\n",
            "Installing collected packages: onnx\n",
            "Successfully installed onnx-1.14.0\n",
            "\n",
            "\u001b[31m\u001b[1mrequirements:\u001b[0m AutoUpdate success ✅ 6.6s, 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 1.14.0...\n",
            "============= Diagnostic Run torch.onnx.export version 2.0.1+cu118 =============\n",
            "verbose: False, log level: Level.ERROR\n",
            "======================= 0 NONE 0 NOTE 0 WARNING 0 ERROR ========================\n",
            "\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-1.15.1-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (5.9 MB)\n",
            "     ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 5.9/5.9 MB 15.0 MB/s eta 0:00:00\n",
            "Collecting onnx-simplifier>=0.4.1\n",
            "  Downloading onnx_simplifier-0.4.33-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (2.2 MB)\n",
            "     ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 2.2/2.2 MB 34.7 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 171.1 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",
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            "Requirement already satisfied: packaging in /usr/local/lib/python3.10/dist-packages (from onnxruntime) (23.1)\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) (1.11.1)\n",
            "Requirement already satisfied: onnx in /usr/local/lib/python3.10/dist-packages (from onnx-simplifier>=0.4.1) (1.14.0)\n",
            "Requirement already satisfied: rich in /usr/local/lib/python3.10/dist-packages (from onnx-simplifier>=0.4.1) (13.4.2)\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 257.3 MB/s eta 0:00:00\n",
            "Requirement already satisfied: typing-extensions>=3.6.2.1 in /usr/local/lib/python3.10/dist-packages (from onnx->onnx-simplifier>=0.4.1) (4.7.1)\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",
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            "Requirement already satisfied: mpmath>=0.19 in /usr/local/lib/python3.10/dist-packages (from sympy->onnxruntime) (1.3.0)\n",
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            "Installing collected packages: humanfriendly, coloredlogs, onnxruntime, onnx-simplifier\n",
            "Successfully installed coloredlogs-15.0.1 humanfriendly-10.0 onnx-simplifier-0.4.33 onnxruntime-1.15.1\n",
            "\n",
            "\u001b[31m\u001b[1mrequirements:\u001b[0m AutoUpdate success ✅ 5.6s, 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 0.4.33...\n",
            "\u001b[34m\u001b[1mONNX:\u001b[0m export success ✅ 14.5s, saved as runs/train/Model/weights/best.onnx (27.4 MB)\n",
            "\n",
            "Export complete (42.9s)\n",
            "Results saved to \u001b[1m/content/drive/MyDrive/yolo_training/yolov5/runs/train/Model/weights\u001b[0m\n",
            "Detect:          python detect.py --weights runs/train/Model/weights/best.onnx \n",
            "Validate:        python val.py --weights runs/train/Model/weights/best.onnx \n",
            "PyTorch Hub:     model = torch.hub.load('ultralytics/yolov5', 'custom', 'runs/train/Model/weights/best.onnx')  \n",
            "Visualize:       https://netron.app\n"
          ]
        }
      ]
    }
  ]
}