Yolov5.ipynb

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  "metadata": {
    "colab": {
      "provenance": []
    },
    "kernelspec": {
      "name": "python3",
      "display_name": "Python 3"
    },
    "language_info": {
      "name": "python"
    },
    "accelerator": "GPU"
  },
  "cells": [
    {
      "cell_type": "code",
      "execution_count": 10,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "s8u25a7_2TPs",
        "outputId": "19cf9efe-b4db-43b6-d297-4539c869fc21"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Cloning into 'yolov5'...\n",
            "remote: Enumerating objects: 11182, done.\u001b[K\n",
            "remote: Counting objects: 100% (75/75), done.\u001b[K\n",
            "remote: Compressing objects: 100% (74/74), done.\u001b[K\n",
            "remote: Total 11182 (delta 0), reused 73 (delta 0), pack-reused 11107\u001b[K\n",
            "Receiving objects: 100% (11182/11182), 18.05 MiB | 22.63 MiB/s, done.\n",
            "Resolving deltas: 100% (7396/7396), done.\n",
            "/content/yolov5/yolov5/yolov5\n"
          ]
        }
      ],
      "source": [
        "!git clone https://github.com/AJITKUMAR130012/yolov5.git # clone\n",
        "%cd yolov5\n"
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "!pwd"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "64pvzXFe2Xq6",
        "outputId": "d3af2f37-3927-4faa-dbc4-34d959d4d5da"
      },
      "execution_count": 2,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "/content/yolov5\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "%cd yolov5"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "hT3orw2_2zLx",
        "outputId": "7e9d84ee-1fdf-4d08-eee5-70dd5cbbef4b"
      },
      "execution_count": 3,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "/content/yolov5/yolov5\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "%pip install -qr requirements.txt  # install\n",
        "\n",
        "import torch\n",
        "import utils\n",
        "display = utils.notebook_init() "
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "L1Kiyql1221t",
        "outputId": "3354bba4-f525-4869-d2a4-42ad88db9643"
      },
      "execution_count": 4,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "YOLOv5 🚀 2022-10-22 Python-3.7.15 torch-1.12.1+cu113 CUDA:0 (Tesla T4, 15110MiB)\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Setup complete ✅ (2 CPUs, 12.7 GB RAM, 38.8/78.2 GB disk)\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# Train YOLOv5s on COCO128 for 3 epochs\n",
        "!python train.py --img 640 --batch 16 --epochs 60 --data custom_coco128.yaml --weights yolov5s.pt --cache"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "kl5axZtz27L7",
        "outputId": "08c2f3d0-181c-4fdc-8cc1-79e5f8e98cfd"
      },
      "execution_count": 5,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "\u001b[34m\u001b[1mtrain: \u001b[0mweights=yolov5s.pt, cfg=, data=custom_coco128.yaml, hyp=data/hyps/hyp.scratch-low.yaml, epochs=60, batch_size=16, imgsz=640, rect=False, resume=False, nosave=False, noval=False, noautoanchor=False, noplots=False, evolve=None, bucket=, cache=ram, image_weights=False, device=, multi_scale=False, single_cls=False, optimizer=SGD, sync_bn=False, workers=8, project=runs/train, name=exp, 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[0mskipping check (not a git repository), for updates see https://github.com/ultralytics/yolov5\n",
            "YOLOv5 🚀 2022-10-22 Python-3.7.15 torch-1.12.1+cu113 CUDA:0 (Tesla T4, 15110MiB)\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[1mClearML: \u001b[0mrun 'pip install clearml' to automatically track, visualize and remotely train YOLOv5 🚀 in ClearML\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://github.com/ultralytics/yolov5/releases/download/v6.2/yolov5s.pt to yolov5s.pt...\n",
            "100% 14.1M/14.1M [00:00<00:00, 212MB/s]\n",
            "\n",
            "Overriding model.yaml nc=80 with nc=3\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     21576  models.yolo.Detect                      [3, [[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, 7027720 parameters, 7027720 gradients, 16.0 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/yolov5/datasets/train_data/labels/train' images and labels...51 found, 0 missing, 0 empty, 0 corrupt: 100% 51/51 [00:00<00:00, 1748.13it/s]\n",
            "\u001b[34m\u001b[1mtrain: \u001b[0mNew cache created: /content/yolov5/datasets/train_data/labels/train.cache\n",
            "\u001b[34m\u001b[1mtrain: \u001b[0mCaching images (0.0GB ram): 100% 51/51 [00:00<00:00, 73.42it/s]\n",
            "\u001b[34m\u001b[1mval: \u001b[0mScanning '/content/yolov5/datasets/train_data/labels/val' images and labels...16 found, 1 missing, 0 empty, 0 corrupt: 100% 17/17 [00:00<00:00, 545.17it/s]\n",
            "\u001b[34m\u001b[1mval: \u001b[0mNew cache created: /content/yolov5/datasets/train_data/labels/val.cache\n",
            "\u001b[34m\u001b[1mval: \u001b[0mCaching images (0.0GB ram): 100% 17/17 [00:00<00:00, 29.29it/s]\n",
            "\n",
            "\u001b[34m\u001b[1mAutoAnchor: \u001b[0m4.01 anchors/target, 1.000 Best Possible Recall (BPR). Current anchors are a good fit to dataset ✅\n",
            "Plotting labels to runs/train/exp2/labels.jpg... \n",
            "Image sizes 640 train, 640 val\n",
            "Using 2 dataloader workers\n",
            "Logging results to \u001b[1mruns/train/exp2\u001b[0m\n",
            "Starting training for 60 epochs...\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   obj_loss   cls_loss  Instances       Size\n",
            "       0/59      3.74G     0.1182    0.03862     0.0399         17        640: 100% 4/4 [00:04<00:00,  1.12s/it]\n",
            "                 Class     Images  Instances          P          R      mAP50   mAP50-95: 100% 1/1 [00:01<00:00,  1.81s/it]\n",
            "                   all         17         46   0.000608     0.0625   0.000553   6.64e-05\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   obj_loss   cls_loss  Instances       Size\n",
            "       1/59      3.74G     0.1168    0.03804    0.04064         15        640: 100% 4/4 [00:01<00:00,  3.53it/s]\n",
            "                 Class     Images  Instances          P          R      mAP50   mAP50-95: 100% 1/1 [00:00<00:00,  2.32it/s]\n",
            "                   all         17         46   0.000635     0.0625   0.000641   0.000149\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   obj_loss   cls_loss  Instances       Size\n",
            "       2/59      3.74G     0.1138    0.03672    0.04011         19        640: 100% 4/4 [00:01<00:00,  3.96it/s]\n",
            "                 Class     Images  Instances          P          R      mAP50   mAP50-95: 100% 1/1 [00:00<00:00,  2.98it/s]\n",
            "                   all         17         46   0.000992     0.0833   0.000718   0.000116\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   obj_loss   cls_loss  Instances       Size\n",
            "       3/59      3.74G     0.1086    0.03931    0.03853         16        640: 100% 4/4 [00:00<00:00,  4.16it/s]\n",
            "                 Class     Images  Instances          P          R      mAP50   mAP50-95: 100% 1/1 [00:00<00:00,  4.02it/s]\n",
            "                   all         17         46   0.000622     0.0625   0.000375   7.03e-05\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   obj_loss   cls_loss  Instances       Size\n",
            "       4/59      3.74G     0.1079    0.03721    0.03757         15        640: 100% 4/4 [00:00<00:00,  4.28it/s]\n",
            "                 Class     Images  Instances          P          R      mAP50   mAP50-95: 100% 1/1 [00:00<00:00,  4.22it/s]\n",
            "                   all         17         46   0.000966     0.0833   0.000631   0.000145\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   obj_loss   cls_loss  Instances       Size\n",
            "       5/59      3.74G     0.1018    0.03501    0.03608          6        640: 100% 4/4 [00:00<00:00,  4.43it/s]\n",
            "                 Class     Images  Instances          P          R      mAP50   mAP50-95: 100% 1/1 [00:00<00:00,  4.62it/s]\n",
            "                   all         17         46    0.00179      0.125    0.00162   0.000255\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   obj_loss   cls_loss  Instances       Size\n",
            "       6/59      3.74G     0.1025    0.03625    0.03628         16        640: 100% 4/4 [00:00<00:00,  4.26it/s]\n",
            "                 Class     Images  Instances          P          R      mAP50   mAP50-95: 100% 1/1 [00:00<00:00,  4.87it/s]\n",
            "                   all         17         46    0.00195      0.193    0.00211   0.000427\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   obj_loss   cls_loss  Instances       Size\n",
            "       7/59      3.74G    0.09933     0.0377    0.03487         16        640: 100% 4/4 [00:00<00:00,  4.33it/s]\n",
            "                 Class     Images  Instances          P          R      mAP50   mAP50-95: 100% 1/1 [00:00<00:00,  4.97it/s]\n",
            "                   all         17         46    0.00337      0.318    0.00471    0.00123\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   obj_loss   cls_loss  Instances       Size\n",
            "       8/59      3.74G    0.09657    0.03584    0.03302         11        640: 100% 4/4 [00:00<00:00,  4.36it/s]\n",
            "                 Class     Images  Instances          P          R      mAP50   mAP50-95: 100% 1/1 [00:00<00:00,  4.74it/s]\n",
            "                   all         17         46    0.00456      0.426    0.00508     0.0018\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   obj_loss   cls_loss  Instances       Size\n",
            "       9/59      3.74G    0.09793    0.03859    0.03315         12        640: 100% 4/4 [00:00<00:00,  4.32it/s]\n",
            "                 Class     Images  Instances          P          R      mAP50   mAP50-95: 100% 1/1 [00:00<00:00,  4.86it/s]\n",
            "                   all         17         46    0.00424      0.387    0.00557     0.0015\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   obj_loss   cls_loss  Instances       Size\n",
            "      10/59      3.74G    0.09454    0.03692    0.03225         14        640: 100% 4/4 [00:00<00:00,  4.37it/s]\n",
            "                 Class     Images  Instances          P          R      mAP50   mAP50-95: 100% 1/1 [00:00<00:00,  5.45it/s]\n",
            "                   all         17         46    0.00544      0.443    0.00569    0.00103\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   obj_loss   cls_loss  Instances       Size\n",
            "      11/59      3.74G    0.09118    0.04557    0.03073         25        640: 100% 4/4 [00:00<00:00,  4.28it/s]\n",
            "                 Class     Images  Instances          P          R      mAP50   mAP50-95: 100% 1/1 [00:00<00:00,  5.62it/s]\n",
            "                   all         17         46    0.00536      0.551     0.0187    0.00588\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   obj_loss   cls_loss  Instances       Size\n",
            "      12/59      3.74G    0.08877    0.03846    0.02851         18        640: 100% 4/4 [00:00<00:00,  4.45it/s]\n",
            "                 Class     Images  Instances          P          R      mAP50   mAP50-95: 100% 1/1 [00:00<00:00,  5.00it/s]\n",
            "                   all         17         46    0.00589      0.592     0.0296    0.00851\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   obj_loss   cls_loss  Instances       Size\n",
            "      13/59      3.74G    0.08402    0.03785    0.02743         11        640: 100% 4/4 [00:00<00:00,  4.13it/s]\n",
            "                 Class     Images  Instances          P          R      mAP50   mAP50-95: 100% 1/1 [00:00<00:00,  5.45it/s]\n",
            "                   all         17         46    0.00506      0.518    0.00642    0.00149\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   obj_loss   cls_loss  Instances       Size\n",
            "      14/59      3.74G    0.08738    0.04657    0.02627         23        640: 100% 4/4 [00:00<00:00,  4.24it/s]\n",
            "                 Class     Images  Instances          P          R      mAP50   mAP50-95: 100% 1/1 [00:00<00:00,  5.14it/s]\n",
            "                   all         17         46     0.0203      0.167     0.0293     0.0054\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   obj_loss   cls_loss  Instances       Size\n",
            "      15/59      3.74G    0.08197    0.03693    0.02677         10        640: 100% 4/4 [00:00<00:00,  4.34it/s]\n",
            "                 Class     Images  Instances          P          R      mAP50   mAP50-95: 100% 1/1 [00:00<00:00,  5.20it/s]\n",
            "                   all         17         46     0.0208       0.25     0.0315    0.00543\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   obj_loss   cls_loss  Instances       Size\n",
            "      16/59      3.74G    0.08161    0.04747    0.02519         21        640: 100% 4/4 [00:01<00:00,  3.75it/s]\n",
            "                 Class     Images  Instances          P          R      mAP50   mAP50-95: 100% 1/1 [00:00<00:00,  5.11it/s]\n",
            "                   all         17         46      0.351      0.208     0.0175    0.00438\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   obj_loss   cls_loss  Instances       Size\n",
            "      17/59      3.74G    0.07918    0.03703    0.02233          8        640: 100% 4/4 [00:00<00:00,  4.14it/s]\n",
            "                 Class     Images  Instances          P          R      mAP50   mAP50-95: 100% 1/1 [00:00<00:00,  4.76it/s]\n",
            "                   all         17         46      0.341     0.0417    0.00976    0.00288\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   obj_loss   cls_loss  Instances       Size\n",
            "      18/59      3.74G    0.07964    0.03745    0.02104          9        640: 100% 4/4 [00:00<00:00,  4.36it/s]\n",
            "                 Class     Images  Instances          P          R      mAP50   mAP50-95: 100% 1/1 [00:00<00:00,  4.70it/s]\n",
            "                   all         17         46      0.382      0.188     0.0537     0.0117\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   obj_loss   cls_loss  Instances       Size\n",
            "      19/59      3.74G    0.07886    0.03921    0.02033          9        640: 100% 4/4 [00:00<00:00,  4.35it/s]\n",
            "                 Class     Images  Instances          P          R      mAP50   mAP50-95: 100% 1/1 [00:00<00:00,  4.26it/s]\n",
            "                   all         17         46      0.414       0.12     0.0597     0.0156\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   obj_loss   cls_loss  Instances       Size\n",
            "      20/59      3.74G    0.07665    0.04124    0.02216         16        640: 100% 4/4 [00:00<00:00,  4.06it/s]\n",
            "                 Class     Images  Instances          P          R      mAP50   mAP50-95: 100% 1/1 [00:00<00:00,  4.49it/s]\n",
            "                   all         17         46      0.397      0.188     0.0719     0.0262\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   obj_loss   cls_loss  Instances       Size\n",
            "      21/59      3.74G    0.07116    0.04412    0.01969         15        640: 100% 4/4 [00:00<00:00,  4.27it/s]\n",
            "                 Class     Images  Instances          P          R      mAP50   mAP50-95: 100% 1/1 [00:00<00:00,  4.67it/s]\n",
            "                   all         17         46      0.406      0.146     0.0404     0.0138\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   obj_loss   cls_loss  Instances       Size\n",
            "      22/59      3.74G    0.07974    0.04194    0.01911         20        640: 100% 4/4 [00:00<00:00,  4.24it/s]\n",
            "                 Class     Images  Instances          P          R      mAP50   mAP50-95: 100% 1/1 [00:00<00:00,  4.52it/s]\n",
            "                   all         17         46      0.421      0.104     0.0775     0.0139\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   obj_loss   cls_loss  Instances       Size\n",
            "      23/59      3.74G    0.07686    0.03843    0.01708         16        640: 100% 4/4 [00:00<00:00,  4.28it/s]\n",
            "                 Class     Images  Instances          P          R      mAP50   mAP50-95: 100% 1/1 [00:00<00:00,  4.44it/s]\n",
            "                   all         17         46      0.373      0.146      0.026     0.0053\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   obj_loss   cls_loss  Instances       Size\n",
            "      24/59      3.74G    0.07812    0.03696    0.01646         15        640: 100% 4/4 [00:00<00:00,  4.18it/s]\n",
            "                 Class     Images  Instances          P          R      mAP50   mAP50-95: 100% 1/1 [00:00<00:00,  4.72it/s]\n",
            "                   all         17         46      0.478      0.208      0.137     0.0226\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   obj_loss   cls_loss  Instances       Size\n",
            "      25/59      3.74G     0.0727    0.03542    0.01619          8        640: 100% 4/4 [00:00<00:00,  4.46it/s]\n",
            "                 Class     Images  Instances          P          R      mAP50   mAP50-95: 100% 1/1 [00:00<00:00,  4.88it/s]\n",
            "                   all         17         46      0.352     0.0625     0.0126    0.00327\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   obj_loss   cls_loss  Instances       Size\n",
            "      26/59      3.74G    0.07747    0.03414    0.01679         11        640: 100% 4/4 [00:00<00:00,  4.25it/s]\n",
            "                 Class     Images  Instances          P          R      mAP50   mAP50-95: 100% 1/1 [00:00<00:00,  4.88it/s]\n",
            "                   all         17         46      0.567      0.229      0.202     0.0568\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   obj_loss   cls_loss  Instances       Size\n",
            "      27/59      3.74G     0.0714    0.03691    0.01504         16        640: 100% 4/4 [00:00<00:00,  4.36it/s]\n",
            "                 Class     Images  Instances          P          R      mAP50   mAP50-95: 100% 1/1 [00:00<00:00,  5.04it/s]\n",
            "                   all         17         46      0.385      0.146     0.0514     0.0166\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   obj_loss   cls_loss  Instances       Size\n",
            "      28/59      3.74G    0.07304    0.03974    0.01373         21        640: 100% 4/4 [00:00<00:00,  4.30it/s]\n",
            "                 Class     Images  Instances          P          R      mAP50   mAP50-95: 100% 1/1 [00:00<00:00,  5.23it/s]\n",
            "                   all         17         46      0.513      0.246      0.207     0.0702\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   obj_loss   cls_loss  Instances       Size\n",
            "      29/59      3.74G    0.06913    0.03598    0.01418         12        640: 100% 4/4 [00:00<00:00,  4.51it/s]\n",
            "                 Class     Images  Instances          P          R      mAP50   mAP50-95: 100% 1/1 [00:00<00:00,  4.11it/s]\n",
            "                   all         17         46      0.407       0.25     0.0726     0.0229\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   obj_loss   cls_loss  Instances       Size\n",
            "      30/59      3.74G    0.07142    0.03792    0.01504         19        640: 100% 4/4 [00:00<00:00,  4.39it/s]\n",
            "                 Class     Images  Instances          P          R      mAP50   mAP50-95: 100% 1/1 [00:00<00:00,  5.21it/s]\n",
            "                   all         17         46      0.415      0.333     0.0768     0.0231\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   obj_loss   cls_loss  Instances       Size\n",
            "      31/59      3.74G    0.07088    0.03723    0.01347         15        640: 100% 4/4 [00:00<00:00,  4.23it/s]\n",
            "                 Class     Images  Instances          P          R      mAP50   mAP50-95: 100% 1/1 [00:00<00:00,  4.53it/s]\n",
            "                   all         17         46      0.481      0.312       0.24     0.0706\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   obj_loss   cls_loss  Instances       Size\n",
            "      32/59      3.74G    0.06606     0.0377    0.01398          8        640: 100% 4/4 [00:00<00:00,  4.29it/s]\n",
            "                 Class     Images  Instances          P          R      mAP50   mAP50-95: 100% 1/1 [00:00<00:00,  5.14it/s]\n",
            "                   all         17         46      0.478      0.125      0.115      0.036\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   obj_loss   cls_loss  Instances       Size\n",
            "      33/59      3.74G    0.06991    0.03914    0.01255         15        640: 100% 4/4 [00:00<00:00,  4.34it/s]\n",
            "                 Class     Images  Instances          P          R      mAP50   mAP50-95: 100% 1/1 [00:00<00:00,  5.22it/s]\n",
            "                   all         17         46      0.534      0.208      0.244     0.0739\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   obj_loss   cls_loss  Instances       Size\n",
            "      34/59      3.74G    0.06566    0.03716    0.01371         12        640: 100% 4/4 [00:00<00:00,  4.27it/s]\n",
            "                 Class     Images  Instances          P          R      mAP50   mAP50-95: 100% 1/1 [00:00<00:00,  5.43it/s]\n",
            "                   all         17         46      0.449      0.208      0.104       0.03\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   obj_loss   cls_loss  Instances       Size\n",
            "      35/59      3.74G     0.0633    0.03586    0.01215         11        640: 100% 4/4 [00:00<00:00,  4.62it/s]\n",
            "                 Class     Images  Instances          P          R      mAP50   mAP50-95: 100% 1/1 [00:00<00:00,  4.42it/s]\n",
            "                   all         17         46      0.477      0.208      0.214     0.0597\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   obj_loss   cls_loss  Instances       Size\n",
            "      36/59      3.74G    0.06906    0.03696    0.01034         19        640: 100% 4/4 [00:00<00:00,  4.24it/s]\n",
            "                 Class     Images  Instances          P          R      mAP50   mAP50-95: 100% 1/1 [00:00<00:00,  5.55it/s]\n",
            "                   all         17         46      0.493      0.194      0.153     0.0539\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   obj_loss   cls_loss  Instances       Size\n",
            "      37/59      3.74G    0.06249    0.03813    0.01162         17        640: 100% 4/4 [00:00<00:00,  4.30it/s]\n",
            "                 Class     Images  Instances          P          R      mAP50   mAP50-95: 100% 1/1 [00:00<00:00,  5.29it/s]\n",
            "                   all         17         46      0.517      0.229      0.246     0.0708\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   obj_loss   cls_loss  Instances       Size\n",
            "      38/59      3.74G    0.06162    0.03287   0.008588         17        640: 100% 4/4 [00:00<00:00,  4.38it/s]\n",
            "                 Class     Images  Instances          P          R      mAP50   mAP50-95: 100% 1/1 [00:00<00:00,  5.87it/s]\n",
            "                   all         17         46      0.482      0.278      0.171     0.0575\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   obj_loss   cls_loss  Instances       Size\n",
            "      39/59      3.74G    0.06115    0.03104   0.007951         13        640: 100% 4/4 [00:00<00:00,  4.34it/s]\n",
            "                 Class     Images  Instances          P          R      mAP50   mAP50-95: 100% 1/1 [00:00<00:00,  5.21it/s]\n",
            "                   all         17         46      0.665      0.299      0.389      0.104\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   obj_loss   cls_loss  Instances       Size\n",
            "      40/59      3.74G    0.06269    0.03949   0.009043         21        640: 100% 4/4 [00:00<00:00,  4.41it/s]\n",
            "                 Class     Images  Instances          P          R      mAP50   mAP50-95: 100% 1/1 [00:00<00:00,  5.59it/s]\n",
            "                   all         17         46      0.537      0.254      0.266     0.0883\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   obj_loss   cls_loss  Instances       Size\n",
            "      41/59      3.74G    0.06233    0.03312    0.01179         11        640: 100% 4/4 [00:00<00:00,  4.65it/s]\n",
            "                 Class     Images  Instances          P          R      mAP50   mAP50-95: 100% 1/1 [00:00<00:00,  4.24it/s]\n",
            "                   all         17         46       0.61      0.417      0.409      0.126\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   obj_loss   cls_loss  Instances       Size\n",
            "      42/59      3.74G    0.05964    0.03149   0.007951         12        640: 100% 4/4 [00:00<00:00,  4.25it/s]\n",
            "                 Class     Images  Instances          P          R      mAP50   mAP50-95: 100% 1/1 [00:00<00:00,  4.91it/s]\n",
            "                   all         17         46      0.259      0.595      0.309     0.0997\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   obj_loss   cls_loss  Instances       Size\n",
            "      43/59      3.74G    0.06067    0.03159    0.00742          9        640: 100% 4/4 [00:00<00:00,  4.34it/s]\n",
            "                 Class     Images  Instances          P          R      mAP50   mAP50-95: 100% 1/1 [00:00<00:00,  6.10it/s]\n",
            "                   all         17         46      0.546      0.482      0.469       0.15\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   obj_loss   cls_loss  Instances       Size\n",
            "      44/59      3.74G    0.05891    0.03213   0.008076          8        640: 100% 4/4 [00:01<00:00,  3.98it/s]\n",
            "                 Class     Images  Instances          P          R      mAP50   mAP50-95: 100% 1/1 [00:00<00:00,  5.70it/s]\n",
            "                   all         17         46      0.284      0.443      0.319      0.113\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   obj_loss   cls_loss  Instances       Size\n",
            "      45/59      3.74G    0.05691    0.03679   0.008434         20        640: 100% 4/4 [00:00<00:00,  4.27it/s]\n",
            "                 Class     Images  Instances          P          R      mAP50   mAP50-95: 100% 1/1 [00:00<00:00,  6.03it/s]\n",
            "                   all         17         46      0.502      0.531      0.461      0.155\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   obj_loss   cls_loss  Instances       Size\n",
            "      46/59      3.74G    0.05684    0.03205   0.009044         12        640: 100% 4/4 [00:00<00:00,  4.26it/s]\n",
            "                 Class     Images  Instances          P          R      mAP50   mAP50-95: 100% 1/1 [00:00<00:00,  6.15it/s]\n",
            "                   all         17         46      0.321      0.485      0.334      0.111\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   obj_loss   cls_loss  Instances       Size\n",
            "      47/59      3.74G    0.05827    0.03452   0.008533         16        640: 100% 4/4 [00:00<00:00,  4.26it/s]\n",
            "                 Class     Images  Instances          P          R      mAP50   mAP50-95: 100% 1/1 [00:00<00:00,  6.26it/s]\n",
            "                   all         17         46      0.578      0.515      0.492      0.159\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   obj_loss   cls_loss  Instances       Size\n",
            "      48/59      3.74G    0.05537    0.04177   0.005768         22        640: 100% 4/4 [00:00<00:00,  4.09it/s]\n",
            "                 Class     Images  Instances          P          R      mAP50   mAP50-95: 100% 1/1 [00:00<00:00,  6.09it/s]\n",
            "                   all         17         46      0.375      0.464      0.337      0.123\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   obj_loss   cls_loss  Instances       Size\n",
            "      49/59      3.74G    0.05642    0.03324   0.006612         15        640: 100% 4/4 [00:00<00:00,  4.43it/s]\n",
            "                 Class     Images  Instances          P          R      mAP50   mAP50-95: 100% 1/1 [00:00<00:00,  5.48it/s]\n",
            "                   all         17         46      0.572      0.576      0.506      0.178\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   obj_loss   cls_loss  Instances       Size\n",
            "      50/59      3.74G    0.05423     0.0321   0.008652         12        640: 100% 4/4 [00:01<00:00,  3.91it/s]\n",
            "                 Class     Images  Instances          P          R      mAP50   mAP50-95: 100% 1/1 [00:00<00:00,  4.58it/s]\n",
            "                   all         17         46      0.485       0.52      0.394      0.153\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   obj_loss   cls_loss  Instances       Size\n",
            "      51/59      3.74G    0.05528    0.03352   0.006335         20        640: 100% 4/4 [00:00<00:00,  4.41it/s]\n",
            "                 Class     Images  Instances          P          R      mAP50   mAP50-95: 100% 1/1 [00:00<00:00,  5.94it/s]\n",
            "                   all         17         46      0.532      0.554      0.466      0.153\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   obj_loss   cls_loss  Instances       Size\n",
            "      52/59      3.74G    0.05285    0.03421   0.005444         14        640: 100% 4/4 [00:00<00:00,  4.30it/s]\n",
            "                 Class     Images  Instances          P          R      mAP50   mAP50-95: 100% 1/1 [00:00<00:00,  5.33it/s]\n",
            "                   all         17         46      0.446      0.506      0.397       0.13\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   obj_loss   cls_loss  Instances       Size\n",
            "      53/59      3.74G    0.05406    0.03548   0.005826         18        640: 100% 4/4 [00:00<00:00,  4.19it/s]\n",
            "                 Class     Images  Instances          P          R      mAP50   mAP50-95: 100% 1/1 [00:00<00:00,  6.37it/s]\n",
            "                   all         17         46       0.53      0.491      0.475      0.154\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   obj_loss   cls_loss  Instances       Size\n",
            "      54/59      3.74G    0.05317    0.03671   0.006269         16        640: 100% 4/4 [00:00<00:00,  4.38it/s]\n",
            "                 Class     Images  Instances          P          R      mAP50   mAP50-95: 100% 1/1 [00:00<00:00,  6.00it/s]\n",
            "                   all         17         46      0.526      0.506      0.477      0.167\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   obj_loss   cls_loss  Instances       Size\n",
            "      55/59      3.74G    0.04845    0.02817   0.005164          8        640: 100% 4/4 [00:00<00:00,  4.32it/s]\n",
            "                 Class     Images  Instances          P          R      mAP50   mAP50-95: 100% 1/1 [00:00<00:00,  6.31it/s]\n",
            "                   all         17         46      0.461      0.506      0.473      0.154\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   obj_loss   cls_loss  Instances       Size\n",
            "      56/59      3.74G    0.05071    0.03095   0.007683         12        640: 100% 4/4 [00:00<00:00,  4.44it/s]\n",
            "                 Class     Images  Instances          P          R      mAP50   mAP50-95: 100% 1/1 [00:00<00:00,  5.07it/s]\n",
            "                   all         17         46      0.447      0.565      0.448      0.163\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   obj_loss   cls_loss  Instances       Size\n",
            "      57/59      3.74G    0.05156    0.03286   0.007319         11        640: 100% 4/4 [00:00<00:00,  4.43it/s]\n",
            "                 Class     Images  Instances          P          R      mAP50   mAP50-95: 100% 1/1 [00:00<00:00,  6.26it/s]\n",
            "                   all         17         46      0.434      0.575      0.421      0.149\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   obj_loss   cls_loss  Instances       Size\n",
            "      58/59      3.74G    0.05241    0.03135   0.007979         12        640: 100% 4/4 [00:00<00:00,  4.61it/s]\n",
            "                 Class     Images  Instances          P          R      mAP50   mAP50-95: 100% 1/1 [00:00<00:00,  5.37it/s]\n",
            "                   all         17         46      0.419      0.622      0.447      0.155\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   obj_loss   cls_loss  Instances       Size\n",
            "      59/59      3.74G    0.05104      0.033   0.005662         16        640: 100% 4/4 [00:00<00:00,  4.11it/s]\n",
            "                 Class     Images  Instances          P          R      mAP50   mAP50-95: 100% 1/1 [00:00<00:00,  6.39it/s]\n",
            "                   all         17         46      0.421      0.632      0.454      0.163\n",
            "\n",
            "60 epochs completed in 0.027 hours.\n",
            "Optimizer stripped from runs/train/exp2/weights/last.pt, 14.5MB\n",
            "Optimizer stripped from runs/train/exp2/weights/best.pt, 14.5MB\n",
            "\n",
            "Validating runs/train/exp2/weights/best.pt...\n",
            "Fusing layers... \n",
            "Model summary: 157 layers, 7018216 parameters, 0 gradients, 15.8 GFLOPs\n",
            "                 Class     Images  Instances          P          R      mAP50   mAP50-95: 100% 1/1 [00:00<00:00,  4.49it/s]\n",
            "                   all         17         46      0.572      0.573       0.51      0.182\n",
            "              Merchant         17         16      0.457      0.631      0.544      0.208\n",
            "                  Date         17         14          1      0.339      0.471      0.129\n",
            "                 Total         17         16      0.259       0.75      0.515      0.209\n",
            "Results saved to \u001b[1mruns/train/exp2\u001b[0m\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "!python detect.py --weights runs/train/exp2/weights/best.pt --img 640 --conf 0.25 --source /content/1191-receipt.jpg\n",
        "# display.Image(filename='runs/detect/exp/zidane.jpg', width=600)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "EJF3ZfRl3Oz9",
        "outputId": "8f65e933-4a96-4a67-90c2-325e4af815d8"
      },
      "execution_count": 9,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "\u001b[34m\u001b[1mdetect: \u001b[0mweights=['runs/train/exp2/weights/best.pt'], source=/content/1191-receipt.jpg, data=data/coco128.yaml, imgsz=[640, 640], conf_thres=0.25, iou_thres=0.45, max_det=1000, device=, view_img=False, save_txt=False, save_conf=False, save_crop=False, nosave=False, classes=None, agnostic_nms=False, augment=False, visualize=False, update=False, project=runs/detect, name=exp, exist_ok=False, line_thickness=3, hide_labels=False, hide_conf=False, half=False, dnn=False, vid_stride=1\n",
            "YOLOv5 🚀 2022-10-22 Python-3.7.15 torch-1.12.1+cu113 CUDA:0 (Tesla T4, 15110MiB)\n",
            "\n",
            "Fusing layers... \n",
            "Model summary: 157 layers, 7018216 parameters, 0 gradients, 15.8 GFLOPs\n",
            "image 1/1 /content/1191-receipt.jpg: 640x512 5 Totals, 15.5ms\n",
            "Speed: 0.6ms pre-process, 15.5ms inference, 1.3ms NMS per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/exp4\u001b[0m\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [],
      "metadata": {
        "id": "nxGpkKHp3d5B"
      },
      "execution_count": null,
      "outputs": []
    }
  ]
}