S13/EVA4S13_Part2.ipynb

{
  "nbformat": 4,
  "nbformat_minor": 0,
  "metadata": {
    "colab": {
      "name": "EVA4S13_Part2.ipynb",
      "provenance": [],
      "collapsed_sections": [],
      "toc_visible": true
    },
    "kernelspec": {
      "name": "python3",
      "display_name": "Python 3"
    },
    "accelerator": "GPU"
  },
  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "9R4rCg3BvSzN",
        "colab_type": "text"
      },
      "source": [
        "# YoloV3 - Object Detection\n",
        "Implements object detection using pretrained YOLO V3 architecture"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "SHkbo8GC1ujs",
        "colab_type": "text"
      },
      "source": [
        "## Load Weights\n",
        "\n",
        "- Download the [weights](https://drive.google.com/open?id=1LezFG5g3BCW6iYaV89B2i64cqEUZD7e0) from the file named `yolov3-spp-ultralytics.pt`.\n",
        "- Create a folder weights in YoloV3 and place `yolov3-spp-ultralytics.pt` file in the that folder."
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "_hKQZ_Pd56xq",
        "colab_type": "text"
      },
      "source": [
        "## Loading Files with Google Drive (works only on Google Colab)\n",
        "Upload all the files and pre-trained model weights to the root folder of your Google Drive and run the cell below.\n",
        "\n",
        "**Note**: Run the cell below only if you are running the notebook on Google Colab."
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "Dm2pvUNCzEY9",
        "colab_type": "code",
        "outputId": "d19d2077-ff8f-4aea-d16c-4d102498768b",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 121
        }
      },
      "source": [
        "from google.colab import drive\n",
        "drive.mount('/content/gdrive')"
      ],
      "execution_count": 0,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Go to this URL in a browser: https://accounts.google.com/o/oauth2/auth?client_id=947318989803-6bn6qk8qdgf4n4g3pfee6491hc0brc4i.apps.googleusercontent.com&redirect_uri=urn%3aietf%3awg%3aoauth%3a2.0%3aoob&response_type=code&scope=email%20https%3a%2f%2fwww.googleapis.com%2fauth%2fdocs.test%20https%3a%2f%2fwww.googleapis.com%2fauth%2fdrive%20https%3a%2f%2fwww.googleapis.com%2fauth%2fdrive.photos.readonly%20https%3a%2f%2fwww.googleapis.com%2fauth%2fpeopleapi.readonly\n",
            "\n",
            "Enter your authorization code:\n",
            "··········\n",
            "Mounted at /content/gdrive\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "vwr71NGe95zW",
        "colab_type": "text"
      },
      "source": [
        "## Imports"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "oJWPCDSv0gw3",
        "colab_type": "code",
        "outputId": "ed298f87-97ca-4236-af40-985714e1cbf1",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 34
        }
      },
      "source": [
        "import time\n",
        "import glob\n",
        "import torch\n",
        "\n",
        "import os\n",
        "\n",
        "from IPython.display import Image, clear_output \n",
        "print('PyTorch %s %s' % (torch.__version__, torch.cuda.get_device_properties(0) if torch.cuda.is_available() else 'CPU'))"
      ],
      "execution_count": 0,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "PyTorch 1.4.0 _CudaDeviceProperties(name='Tesla K80', major=3, minor=7, total_memory=11441MB, multi_processor_count=13)\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "TZl6HQqX985V",
        "colab_type": "text"
      },
      "source": [
        "## Path of YoloV3\n",
        "\n",
        "**Note**: Run the cell below only if you are running the notebook on Google Colab."
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "04WxrIQ51BMn",
        "colab_type": "code",
        "outputId": "b259f919-4981-42f0-d26d-040783525ff7",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 34
        }
      },
      "source": [
        "cd gdrive/My Drive/YoloV3/"
      ],
      "execution_count": 0,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "/content/gdrive/My Drive/YoloV3\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "OQj9RKol-k3y",
        "colab_type": "text"
      },
      "source": [
        "**Note**: Run the cell below only if you are running locally."
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "WTBafLfy1JUS",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "cd YoloV3"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "iyCioigJAZJ2",
        "colab_type": "text"
      },
      "source": [
        "## Model Training"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "ElYu4RG01NVw",
        "colab_type": "code",
        "outputId": "1d6ca627-d510-4352-c36e-58583c6c55d8",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 1000
        }
      },
      "source": [
        "!python train.py --batch 10 --cache --epochs 300 --nosave"
      ],
      "execution_count": 0,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Namespace(accumulate=4, adam=False, batch_size=10, bucket='', cache_images=True, cfg='cfg/yolov3-batman.cfg', data='data/train/batman.data', device='', epochs=300, evolve=False, img_size=[512], multi_scale=False, name='', nosave=True, notest=False, rect=False, resume=False, single_cls=False, weights='weights/yolov3-spp-ultralytics.pt')\n",
            "Using CUDA device0 _CudaDeviceProperties(name='Tesla P100-PCIE-16GB', total_memory=16280MB)\n",
            "\n",
            "2020-04-24 05:37:33.675122: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudart.so.10.1\n",
            "Run 'tensorboard --logdir=runs' to view tensorboard at http://localhost:6006/\n",
            "Model Summary: 225 layers, 6.25733e+07 parameters, 6.25733e+07 gradients\n",
            "Caching labels (500 found, 0 missing, 0 empty, 0 duplicate, for 500 images): 100% 500/500 [02:52<00:00,  2.89it/s]\n",
            "Caching images (0.2GB): 100% 500/500 [03:17<00:00,  2.54it/s]\n",
            "Caching labels (500 found, 0 missing, 0 empty, 0 duplicate, for 500 images): 100% 500/500 [00:00<00:00, 1076.22it/s]\n",
            "Caching images (0.2GB): 100% 500/500 [00:08<00:00, 59.30it/s]\n",
            "Image sizes 512 - 512 train, 512 test\n",
            "Using 2 dataloader workers\n",
            "Starting training for 300 epochs...\n",
            "\n",
            "     Epoch   gpu_mem      GIoU       obj       cls     total   targets  img_size\n",
            "     0/299     7.38G      5.28      3.61         0      8.89        21       512: 100% 50/50 [00:36<00:00,  1.36it/s]\n",
            "               Class    Images   Targets         P         R   mAP@0.5        F1: 100% 50/50 [00:20<00:00,  2.42it/s]\n",
            "                 all       500       500         0         0    0.0369         0\n",
            "\n",
            "     Epoch   gpu_mem      GIoU       obj       cls     total   targets  img_size\n",
            "     1/299     11.8G      3.76      2.03         0      5.79        21       512: 100% 50/50 [00:33<00:00,  1.50it/s]\n",
            "               Class    Images   Targets         P         R   mAP@0.5        F1: 100% 50/50 [00:08<00:00,  6.05it/s]\n",
            "                 all       500       500     0.643     0.608     0.644     0.625\n",
            "\n",
            "     Epoch   gpu_mem      GIoU       obj       cls     total   targets  img_size\n",
            "     2/299     11.8G      4.09      1.25         0      5.35        19       512: 100% 50/50 [00:33<00:00,  1.50it/s]\n",
            "               Class    Images   Targets         P         R   mAP@0.5        F1: 100% 50/50 [00:07<00:00,  6.44it/s]\n",
            "                 all       500       500     0.365     0.814     0.676     0.504\n",
            "\n",
            "     Epoch   gpu_mem      GIoU       obj       cls     total   targets  img_size\n",
            "     3/299     11.8G      3.54      1.05         0      4.58        21       512: 100% 50/50 [00:33<00:00,  1.50it/s]\n",
            "               Class    Images   Targets         P         R   mAP@0.5        F1: 100% 50/50 [00:07<00:00,  6.84it/s]\n",
            "                 all       500       500     0.554      0.86     0.696     0.674\n",
            "\n",
            "     Epoch   gpu_mem      GIoU       obj       cls     total   targets  img_size\n",
            "     4/299     11.8G      3.52      0.93         0      4.45        24       512: 100% 50/50 [00:33<00:00,  1.50it/s]\n",
            "               Class    Images   Targets         P         R   mAP@0.5        F1: 100% 50/50 [00:07<00:00,  6.30it/s]\n",
            "                 all       500       500     0.867     0.872     0.922      0.87\n",
            "\n",
            "     Epoch   gpu_mem      GIoU       obj       cls     total   targets  img_size\n",
            "     5/299     11.8G      3.18     0.848         0      4.03        20       512: 100% 50/50 [00:33<00:00,  1.50it/s]\n",
            "               Class    Images   Targets         P         R   mAP@0.5        F1: 100% 50/50 [00:07<00:00,  6.55it/s]\n",
            "                 all       500       500     0.697     0.948     0.928     0.803\n",
            "\n",
            "     Epoch   gpu_mem      GIoU       obj       cls     total   targets  img_size\n",
            "     6/299     11.8G      3.16     0.761         0      3.92        17       512: 100% 50/50 [00:33<00:00,  1.50it/s]\n",
            "               Class    Images   Targets         P         R   mAP@0.5        F1: 100% 50/50 [00:07<00:00,  6.91it/s]\n",
            "                 all       500       500     0.504     0.972     0.918     0.664\n",
            "\n",
            "     Epoch   gpu_mem      GIoU       obj       cls     total   targets  img_size\n",
            "     7/299     11.8G      2.96     0.711         0      3.67        20       512: 100% 50/50 [00:33<00:00,  1.49it/s]\n",
            "               Class    Images   Targets         P         R   mAP@0.5        F1: 100% 50/50 [00:07<00:00,  6.87it/s]\n",
            "                 all       500       500     0.785      0.97     0.968     0.868\n",
            "\n",
            "     Epoch   gpu_mem      GIoU       obj       cls     total   targets  img_size\n",
            "     8/299     11.8G      2.67     0.664         0      3.34        22       512: 100% 50/50 [00:33<00:00,  1.50it/s]\n",
            "               Class    Images   Targets         P         R   mAP@0.5        F1: 100% 50/50 [00:07<00:00,  7.02it/s]\n",
            "                 all       500       500     0.794     0.968     0.965     0.872\n",
            "\n",
            "     Epoch   gpu_mem      GIoU       obj       cls     total   targets  img_size\n",
            "     9/299     11.8G      2.72     0.629         0      3.35        21       512: 100% 50/50 [00:33<00:00,  1.50it/s]\n",
            "               Class    Images   Targets         P         R   mAP@0.5        F1: 100% 50/50 [00:06<00:00,  7.62it/s]\n",
            "                 all       500       500     0.668     0.018    0.0522    0.0351\n",
            "\n",
            "     Epoch   gpu_mem      GIoU       obj       cls     total   targets  img_size\n",
            "  0% 0/50 [00:00<?, ?it/s]\n",
            "Model Bias Summary:    layer        regression        objectness    classification\n",
            "                          89      -0.12+/-0.22      -5.07+/-0.44       4.11+/-0.01 \n",
            "                         101       0.14+/-0.22      -5.78+/-0.46       4.13+/-0.00 \n",
            "                         113       0.16+/-0.18      -6.14+/-0.26       4.09+/-0.01 \n",
            "    10/299     11.8G      2.56     0.628         0      3.18        16       512: 100% 50/50 [00:33<00:00,  1.50it/s]\n",
            "               Class    Images   Targets         P         R   mAP@0.5        F1: 100% 50/50 [00:06<00:00,  7.60it/s]\n",
            "                 all       500       500     0.334     0.004    0.0255   0.00791\n",
            "\n",
            "     Epoch   gpu_mem      GIoU       obj       cls     total   targets  img_size\n",
            "    11/299     11.8G      2.31     0.566         0      2.88        20       512: 100% 50/50 [00:33<00:00,  1.50it/s]\n",
            "               Class    Images   Targets         P         R   mAP@0.5        F1: 100% 50/50 [00:06<00:00,  7.61it/s]\n",
            "                 all       500       500     0.727     0.974     0.975     0.833\n",
            "\n",
            "     Epoch   gpu_mem      GIoU       obj       cls     total   targets  img_size\n",
            "    12/299     11.8G       2.5     0.524         0      3.02        20       512: 100% 50/50 [00:33<00:00,  1.49it/s]\n",
            "               Class    Images   Targets         P         R   mAP@0.5        F1: 100% 50/50 [00:06<00:00,  7.56it/s]\n",
            "                 all       500       500     0.873      0.98     0.983     0.923\n",
            "\n",
            "     Epoch   gpu_mem      GIoU       obj       cls     total   targets  img_size\n",
            "    13/299     11.8G      2.15     0.536         0      2.69        20       512: 100% 50/50 [00:33<00:00,  1.49it/s]\n",
            "               Class    Images   Targets         P         R   mAP@0.5        F1: 100% 50/50 [00:06<00:00,  7.55it/s]\n",
            "                 all       500       500     0.862     0.978      0.98     0.916\n",
            "\n",
            "     Epoch   gpu_mem      GIoU       obj       cls     total   targets  img_size\n",
            "    14/299     11.8G       2.4     0.522         0      2.92        19       512: 100% 50/50 [00:33<00:00,  1.50it/s]\n",
            "               Class    Images   Targets         P         R   mAP@0.5        F1: 100% 50/50 [00:06<00:00,  7.28it/s]\n",
            "                 all       500       500     0.733     0.976     0.974     0.837\n",
            "\n",
            "     Epoch   gpu_mem      GIoU       obj       cls     total   targets  img_size\n",
            "    15/299     11.8G      2.05     0.505         0      2.55        18       512: 100% 50/50 [00:33<00:00,  1.50it/s]\n",
            "               Class    Images   Targets         P         R   mAP@0.5        F1: 100% 50/50 [00:06<00:00,  7.36it/s]\n",
            "                 all       500       500     0.803     0.978     0.974     0.882\n",
            "\n",
            "     Epoch   gpu_mem      GIoU       obj       cls     total   targets  img_size\n",
            "    16/299     11.8G      2.04     0.514         0      2.55        21       512: 100% 50/50 [00:33<00:00,  1.50it/s]\n",
            "               Class    Images   Targets         P         R   mAP@0.5        F1: 100% 50/50 [00:06<00:00,  7.53it/s]\n",
            "                 all       500       500     0.882     0.978     0.978     0.928\n",
            "\n",
            "     Epoch   gpu_mem      GIoU       obj       cls     total   targets  img_size\n",
            "    17/299     11.8G       2.1     0.496         0      2.59        20       512: 100% 50/50 [00:33<00:00,  1.49it/s]\n",
            "               Class    Images   Targets         P         R   mAP@0.5        F1: 100% 50/50 [00:06<00:00,  7.57it/s]\n",
            "                 all       500       500     0.917     0.982     0.983     0.948\n",
            "\n",
            "     Epoch   gpu_mem      GIoU       obj       cls     total   targets  img_size\n",
            "    18/299     11.8G      1.88     0.464         0      2.34        22       512: 100% 50/50 [00:33<00:00,  1.49it/s]\n",
            "               Class    Images   Targets         P         R   mAP@0.5        F1: 100% 50/50 [00:06<00:00,  7.60it/s]\n",
            "                 all       500       500     0.902      0.98     0.984     0.939\n",
            "\n",
            "     Epoch   gpu_mem      GIoU       obj       cls     total   targets  img_size\n",
            "    19/299     11.8G      1.82     0.453         0      2.28        20       512: 100% 50/50 [00:33<00:00,  1.50it/s]\n",
            "               Class    Images   Targets         P         R   mAP@0.5        F1: 100% 50/50 [00:06<00:00,  7.50it/s]\n",
            "                 all       500       500     0.879      0.98     0.985     0.927\n",
            "\n",
            "     Epoch   gpu_mem      GIoU       obj       cls     total   targets  img_size\n",
            "    20/299     11.8G      1.88     0.457         0      2.34        19       512: 100% 50/50 [00:33<00:00,  1.50it/s]\n",
            "               Class    Images   Targets         P         R   mAP@0.5        F1: 100% 50/50 [00:06<00:00,  7.53it/s]\n",
            "                 all       500       500     0.934     0.982     0.985     0.957\n",
            "\n",
            "     Epoch   gpu_mem      GIoU       obj       cls     total   targets  img_size\n",
            "    21/299     11.8G      1.78     0.409         0      2.19        19       512: 100% 50/50 [00:33<00:00,  1.50it/s]\n",
            "               Class    Images   Targets         P         R   mAP@0.5        F1: 100% 50/50 [00:06<00:00,  7.55it/s]\n",
            "                 all       500       500     0.957      0.98     0.984     0.968\n",
            "\n",
            "     Epoch   gpu_mem      GIoU       obj       cls     total   targets  img_size\n",
            "    22/299     11.8G      1.65     0.427         0      2.08        21       512: 100% 50/50 [00:33<00:00,  1.50it/s]\n",
            "               Class    Images   Targets         P         R   mAP@0.5        F1: 100% 50/50 [00:06<00:00,  7.55it/s]\n",
            "                 all       500       500     0.964     0.984     0.988     0.974\n",
            "\n",
            "     Epoch   gpu_mem      GIoU       obj       cls     total   targets  img_size\n",
            "    23/299     11.8G      1.81     0.441         0      2.25        19       512: 100% 50/50 [00:33<00:00,  1.50it/s]\n",
            "               Class    Images   Targets         P         R   mAP@0.5        F1: 100% 50/50 [00:06<00:00,  7.58it/s]\n",
            "                 all       500       500     0.831      0.98     0.984     0.899\n",
            "\n",
            "     Epoch   gpu_mem      GIoU       obj       cls     total   targets  img_size\n",
            "    24/299     11.8G       1.6     0.435         0      2.04        17       512: 100% 50/50 [00:33<00:00,  1.50it/s]\n",
            "               Class    Images   Targets         P         R   mAP@0.5        F1: 100% 50/50 [00:06<00:00,  7.61it/s]\n",
            "                 all       500       500     0.864     0.986     0.987     0.921\n",
            "\n",
            "     Epoch   gpu_mem      GIoU       obj       cls     total   targets  img_size\n",
            "    25/299     11.8G      1.56     0.452         0      2.01        20       512: 100% 50/50 [00:33<00:00,  1.50it/s]\n",
            "               Class    Images   Targets         P         R   mAP@0.5        F1: 100% 50/50 [00:06<00:00,  7.60it/s]\n",
            "                 all       500       500     0.871     0.982     0.986     0.923\n",
            "\n",
            "     Epoch   gpu_mem      GIoU       obj       cls     total   targets  img_size\n",
            "    26/299     11.8G      1.93      0.44         0      2.37        24       512: 100% 50/50 [00:33<00:00,  1.49it/s]\n",
            "               Class    Images   Targets         P         R   mAP@0.5        F1: 100% 50/50 [00:06<00:00,  7.53it/s]\n",
            "                 all       500       500     0.941      0.98     0.989      0.96\n",
            "\n",
            "     Epoch   gpu_mem      GIoU       obj       cls     total   targets  img_size\n",
            "    27/299     11.8G      1.66      0.43         0      2.09        21       512: 100% 50/50 [00:33<00:00,  1.50it/s]\n",
            "               Class    Images   Targets         P         R   mAP@0.5        F1: 100% 50/50 [00:06<00:00,  7.58it/s]\n",
            "                 all       500       500     0.951     0.984     0.994     0.967\n",
            "\n",
            "     Epoch   gpu_mem      GIoU       obj       cls     total   targets  img_size\n",
            "    28/299     11.8G      1.79     0.427         0      2.22        20       512: 100% 50/50 [00:33<00:00,  1.50it/s]\n",
            "               Class    Images   Targets         P         R   mAP@0.5        F1: 100% 50/50 [00:06<00:00,  7.56it/s]\n",
            "                 all       500       500     0.888     0.988     0.991     0.935\n",
            "\n",
            "     Epoch   gpu_mem      GIoU       obj       cls     total   targets  img_size\n",
            "    29/299     11.8G      1.64     0.395         0      2.04        20       512: 100% 50/50 [00:33<00:00,  1.50it/s]\n",
            "               Class    Images   Targets         P         R   mAP@0.5        F1: 100% 50/50 [00:06<00:00,  7.59it/s]\n",
            "                 all       500       500     0.934      0.99     0.993     0.961\n",
            "\n",
            "     Epoch   gpu_mem      GIoU       obj       cls     total   targets  img_size\n",
            "    30/299     11.8G      1.73     0.397         0      2.13        17       512: 100% 50/50 [00:33<00:00,  1.50it/s]\n",
            "               Class    Images   Targets         P         R   mAP@0.5        F1: 100% 50/50 [00:06<00:00,  7.56it/s]\n",
            "                 all       500       500     0.942     0.984     0.991     0.962\n",
            "\n",
            "     Epoch   gpu_mem      GIoU       obj       cls     total   targets  img_size\n",
            "    31/299     11.8G      1.74     0.405         0      2.14        20       512: 100% 50/50 [00:33<00:00,  1.50it/s]\n",
            "               Class    Images   Targets         P         R   mAP@0.5        F1: 100% 50/50 [00:06<00:00,  7.55it/s]\n",
            "                 all       500       500     0.967     0.986     0.994     0.976\n",
            "\n",
            "     Epoch   gpu_mem      GIoU       obj       cls     total   targets  img_size\n",
            "    32/299     11.8G      1.57     0.378         0      1.94        20       512: 100% 50/50 [00:33<00:00,  1.49it/s]\n",
            "               Class    Images   Targets         P         R   mAP@0.5        F1: 100% 50/50 [00:06<00:00,  7.60it/s]\n",
            "                 all       500       500     0.944     0.994     0.993     0.968\n",
            "\n",
            "     Epoch   gpu_mem      GIoU       obj       cls     total   targets  img_size\n",
            "    33/299     11.8G      1.57     0.386         0      1.95        18       512: 100% 50/50 [00:33<00:00,  1.50it/s]\n",
            "               Class    Images   Targets         P         R   mAP@0.5        F1: 100% 50/50 [00:06<00:00,  7.53it/s]\n",
            "                 all       500       500     0.907     0.994     0.994     0.949\n",
            "\n",
            "     Epoch   gpu_mem      GIoU       obj       cls     total   targets  img_size\n",
            "    34/299     11.8G      1.53     0.378         0      1.91        20       512: 100% 50/50 [00:33<00:00,  1.50it/s]\n",
            "               Class    Images   Targets         P         R   mAP@0.5        F1: 100% 50/50 [00:06<00:00,  7.54it/s]\n",
            "                 all       500       500     0.952     0.994     0.995     0.972\n",
            "\n",
            "     Epoch   gpu_mem      GIoU       obj       cls     total   targets  img_size\n",
            "    35/299     11.8G      1.48     0.368         0      1.85        18       512: 100% 50/50 [00:33<00:00,  1.50it/s]\n",
            "               Class    Images   Targets         P         R   mAP@0.5        F1: 100% 50/50 [00:06<00:00,  7.58it/s]\n",
            "                 all       500       500     0.938     0.998     0.994     0.967\n",
            "\n",
            "     Epoch   gpu_mem      GIoU       obj       cls     total   targets  img_size\n",
            "    36/299     11.8G       1.5     0.386         0      1.88        22       512: 100% 50/50 [00:33<00:00,  1.50it/s]\n",
            "               Class    Images   Targets         P         R   mAP@0.5        F1: 100% 50/50 [00:06<00:00,  7.55it/s]\n",
            "                 all       500       500     0.917     0.984      0.99     0.949\n",
            "\n",
            "     Epoch   gpu_mem      GIoU       obj       cls     total   targets  img_size\n",
            "    37/299     11.8G      1.51     0.387         0       1.9        17       512: 100% 50/50 [00:33<00:00,  1.49it/s]\n",
            "               Class    Images   Targets         P         R   mAP@0.5        F1: 100% 50/50 [00:06<00:00,  7.54it/s]\n",
            "                 all       500       500     0.933     0.986      0.99     0.959\n",
            "\n",
            "     Epoch   gpu_mem      GIoU       obj       cls     total   targets  img_size\n",
            "    38/299     11.8G      1.45     0.353         0      1.81        19       512: 100% 50/50 [00:33<00:00,  1.50it/s]\n",
            "               Class    Images   Targets         P         R   mAP@0.5        F1: 100% 50/50 [00:07<00:00,  6.28it/s]\n",
            "                 all       500       500     0.945     0.984     0.991     0.964\n",
            "\n",
            "     Epoch   gpu_mem      GIoU       obj       cls     total   targets  img_size\n",
            "    39/299     11.8G      1.47      0.36         0      1.83        20       512: 100% 50/50 [00:33<00:00,  1.50it/s]\n",
            "               Class    Images   Targets         P         R   mAP@0.5        F1: 100% 50/50 [00:06<00:00,  7.57it/s]\n",
            "                 all       500       500     0.908     0.984     0.993     0.945\n",
            "\n",
            "     Epoch   gpu_mem      GIoU       obj       cls     total   targets  img_size\n",
            "    40/299     11.8G      1.53     0.355         0      1.88        19       512: 100% 50/50 [00:33<00:00,  1.50it/s]\n",
            "               Class    Images   Targets         P         R   mAP@0.5        F1: 100% 50/50 [00:06<00:00,  7.58it/s]\n",
            "                 all       500       500     0.971     0.994     0.995     0.983\n",
            "\n",
            "     Epoch   gpu_mem      GIoU       obj       cls     total   targets  img_size\n",
            "    41/299     11.8G      1.43     0.353         0      1.79        19       512: 100% 50/50 [00:33<00:00,  1.50it/s]\n",
            "               Class    Images   Targets         P         R   mAP@0.5        F1: 100% 50/50 [00:06<00:00,  7.58it/s]\n",
            "                 all       500       500     0.956     0.998     0.995     0.977\n",
            "\n",
            "     Epoch   gpu_mem      GIoU       obj       cls     total   targets  img_size\n",
            "    42/299     11.8G      1.49     0.345         0      1.84        19       512: 100% 50/50 [00:33<00:00,  1.50it/s]\n",
            "               Class    Images   Targets         P         R   mAP@0.5        F1: 100% 50/50 [00:06<00:00,  7.66it/s]\n",
            "                 all       500       500     0.956         1     0.995     0.978\n",
            "\n",
            "     Epoch   gpu_mem      GIoU       obj       cls     total   targets  img_size\n",
            "    43/299     11.8G      1.55      0.33         0      1.88        19       512: 100% 50/50 [00:33<00:00,  1.50it/s]\n",
            "               Class    Images   Targets         P         R   mAP@0.5        F1: 100% 50/50 [00:06<00:00,  7.60it/s]\n",
            "                 all       500       500     0.945         1     0.995     0.972\n",
            "\n",
            "     Epoch   gpu_mem      GIoU       obj       cls     total   targets  img_size\n",
            "    44/299     11.8G      1.44     0.349         0      1.79        19       512: 100% 50/50 [00:33<00:00,  1.50it/s]\n",
            "               Class    Images   Targets         P         R   mAP@0.5        F1: 100% 50/50 [00:06<00:00,  7.62it/s]\n",
            "                 all       500       500     0.963     0.994     0.995     0.978\n",
            "\n",
            "     Epoch   gpu_mem      GIoU       obj       cls     total   targets  img_size\n",
            "    45/299     11.8G      1.38     0.362         0      1.74        19       512: 100% 50/50 [00:33<00:00,  1.50it/s]\n",
            "               Class    Images   Targets         P         R   mAP@0.5        F1: 100% 50/50 [00:06<00:00,  7.57it/s]\n",
            "                 all       500       500     0.951     0.992     0.994     0.971\n",
            "\n",
            "     Epoch   gpu_mem      GIoU       obj       cls     total   targets  img_size\n",
            "    46/299     11.8G      1.32     0.335         0      1.66        21       512: 100% 50/50 [00:33<00:00,  1.50it/s]\n",
            "               Class    Images   Targets         P         R   mAP@0.5        F1: 100% 50/50 [00:06<00:00,  7.60it/s]\n",
            "                 all       500       500     0.943     0.996     0.994     0.969\n",
            "\n",
            "     Epoch   gpu_mem      GIoU       obj       cls     total   targets  img_size\n",
            "    47/299     11.8G      1.36     0.325         0      1.69        22       512: 100% 50/50 [00:33<00:00,  1.50it/s]\n",
            "               Class    Images   Targets         P         R   mAP@0.5        F1: 100% 50/50 [00:06<00:00,  7.56it/s]\n",
            "                 all       500       500     0.941         1     0.994     0.969\n",
            "\n",
            "     Epoch   gpu_mem      GIoU       obj       cls     total   targets  img_size\n",
            "    48/299     11.8G      1.38     0.328         0      1.71        20       512: 100% 50/50 [00:33<00:00,  1.49it/s]\n",
            "               Class    Images   Targets         P         R   mAP@0.5        F1: 100% 50/50 [00:06<00:00,  7.58it/s]\n",
            "                 all       500       500     0.979     0.998     0.995     0.988\n",
            "\n",
            "     Epoch   gpu_mem      GIoU       obj       cls     total   targets  img_size\n",
            "    49/299     11.8G      1.33     0.337         0      1.67        20       512: 100% 50/50 [00:33<00:00,  1.50it/s]\n",
            "               Class    Images   Targets         P         R   mAP@0.5        F1: 100% 50/50 [00:06<00:00,  7.50it/s]\n",
            "                 all       500       500     0.986     0.999     0.995     0.993\n",
            "\n",
            "     Epoch   gpu_mem      GIoU       obj       cls     total   targets  img_size\n",
            "    50/299     11.8G       1.4     0.354         0      1.75        19       512: 100% 50/50 [00:33<00:00,  1.49it/s]\n",
            "               Class    Images   Targets         P         R   mAP@0.5        F1: 100% 50/50 [00:06<00:00,  7.42it/s]\n",
            "                 all       500       500     0.923     0.998     0.995     0.959\n",
            "\n",
            "     Epoch   gpu_mem      GIoU       obj       cls     total   targets  img_size\n",
            "    51/299     11.8G      1.33     0.332         0      1.66        21       512: 100% 50/50 [00:33<00:00,  1.49it/s]\n",
            "               Class    Images   Targets         P         R   mAP@0.5        F1: 100% 50/50 [00:06<00:00,  7.49it/s]\n",
            "                 all       500       500     0.978     0.986     0.994     0.982\n",
            "\n",
            "     Epoch   gpu_mem      GIoU       obj       cls     total   targets  img_size\n",
            "    52/299     11.8G      1.34     0.329         0      1.67        21       512: 100% 50/50 [00:33<00:00,  1.49it/s]\n",
            "               Class    Images   Targets         P         R   mAP@0.5        F1: 100% 50/50 [00:06<00:00,  7.49it/s]\n",
            "                 all       500       500     0.954     0.986     0.994      0.97\n",
            "\n",
            "     Epoch   gpu_mem      GIoU       obj       cls     total   targets  img_size\n",
            "    53/299     11.8G      1.32     0.308         0      1.63        17       512: 100% 50/50 [00:33<00:00,  1.50it/s]\n",
            "               Class    Images   Targets         P         R   mAP@0.5        F1: 100% 50/50 [00:06<00:00,  7.52it/s]\n",
            "                 all       500       500     0.987     0.986     0.995     0.986\n",
            "\n",
            "     Epoch   gpu_mem      GIoU       obj       cls     total   targets  img_size\n",
            "    54/299     11.8G      1.38     0.318         0       1.7        19       512: 100% 50/50 [00:33<00:00,  1.50it/s]\n",
            "               Class    Images   Targets         P         R   mAP@0.5        F1: 100% 50/50 [00:06<00:00,  7.46it/s]\n",
            "                 all       500       500     0.976     0.996     0.995     0.986\n",
            "\n",
            "     Epoch   gpu_mem      GIoU       obj       cls     total   targets  img_size\n",
            "    55/299     11.8G      1.32     0.325         0      1.64        19       512: 100% 50/50 [00:33<00:00,  1.50it/s]\n",
            "               Class    Images   Targets         P         R   mAP@0.5        F1: 100% 50/50 [00:06<00:00,  7.48it/s]\n",
            "                 all       500       500      0.95     0.998     0.994     0.974\n",
            "\n",
            "     Epoch   gpu_mem      GIoU       obj       cls     total   targets  img_size\n",
            "    56/299     11.8G      1.36     0.316         0      1.68        23       512: 100% 50/50 [00:33<00:00,  1.50it/s]\n",
            "               Class    Images   Targets         P         R   mAP@0.5        F1: 100% 50/50 [00:06<00:00,  7.49it/s]\n",
            "                 all       500       500     0.971     0.996     0.994     0.983\n",
            "\n",
            "     Epoch   gpu_mem      GIoU       obj       cls     total   targets  img_size\n",
            "    57/299     11.8G      1.17     0.328         0       1.5        18       512: 100% 50/50 [00:33<00:00,  1.50it/s]\n",
            "               Class    Images   Targets         P         R   mAP@0.5        F1: 100% 50/50 [00:06<00:00,  7.52it/s]\n",
            "                 all       500       500     0.958     0.998     0.994     0.978\n",
            "\n",
            "     Epoch   gpu_mem      GIoU       obj       cls     total   targets  img_size\n",
            "    58/299     11.8G      1.34       0.3         0      1.64        21       512: 100% 50/50 [00:33<00:00,  1.50it/s]\n",
            "               Class    Images   Targets         P         R   mAP@0.5        F1: 100% 50/50 [00:06<00:00,  7.57it/s]\n",
            "                 all       500       500     0.956         1     0.994     0.978\n",
            "\n",
            "     Epoch   gpu_mem      GIoU       obj       cls     total   targets  img_size\n",
            "    59/299     11.8G      1.34     0.319         0      1.66        20       512: 100% 50/50 [00:33<00:00,  1.49it/s]\n",
            "               Class    Images   Targets         P         R   mAP@0.5        F1: 100% 50/50 [00:06<00:00,  7.45it/s]\n",
            "                 all       500       500     0.971     0.996     0.994     0.983\n",
            "\n",
            "     Epoch   gpu_mem      GIoU       obj       cls     total   targets  img_size\n",
            "    60/299     11.8G      1.23     0.306         0      1.53        20       512: 100% 50/50 [00:33<00:00,  1.49it/s]\n",
            "               Class    Images   Targets         P         R   mAP@0.5        F1: 100% 50/50 [00:06<00:00,  7.58it/s]\n",
            "                 all       500       500     0.977         1     0.995     0.988\n",
            "\n",
            "     Epoch   gpu_mem      GIoU       obj       cls     total   targets  img_size\n",
            "    61/299     11.8G      1.32     0.317         0      1.64        19       512: 100% 50/50 [00:33<00:00,  1.50it/s]\n",
            "               Class    Images   Targets         P         R   mAP@0.5        F1: 100% 50/50 [00:06<00:00,  7.49it/s]\n",
            "                 all       500       500     0.969         1     0.995     0.984\n",
            "\n",
            "     Epoch   gpu_mem      GIoU       obj       cls     total   targets  img_size\n",
            "    62/299     11.8G      1.36     0.305         0      1.66        21       512: 100% 50/50 [00:33<00:00,  1.50it/s]\n",
            "               Class    Images   Targets         P         R   mAP@0.5        F1: 100% 50/50 [00:06<00:00,  7.53it/s]\n",
            "                 all       500       500     0.978         1     0.995     0.989\n",
            "\n",
            "     Epoch   gpu_mem      GIoU       obj       cls     total   targets  img_size\n",
            "    63/299     11.8G      1.29     0.312         0       1.6        20       512: 100% 50/50 [00:33<00:00,  1.50it/s]\n",
            "               Class    Images   Targets         P         R   mAP@0.5        F1: 100% 50/50 [00:06<00:00,  7.66it/s]\n",
            "                 all       500       500     0.985         1     0.995     0.992\n",
            "\n",
            "     Epoch   gpu_mem      GIoU       obj       cls     total   targets  img_size\n",
            "    64/299     11.8G      1.27      0.33         0       1.6        18       512: 100% 50/50 [00:33<00:00,  1.50it/s]\n",
            "               Class    Images   Targets         P         R   mAP@0.5        F1: 100% 50/50 [00:06<00:00,  7.66it/s]\n",
            "                 all       500       500     0.951         1     0.995     0.975\n",
            "\n",
            "     Epoch   gpu_mem      GIoU       obj       cls     total   targets  img_size\n",
            "    65/299     11.8G      1.37     0.313         0      1.69        23       512: 100% 50/50 [00:33<00:00,  1.50it/s]\n",
            "               Class    Images   Targets         P         R   mAP@0.5        F1: 100% 50/50 [00:06<00:00,  7.69it/s]\n",
            "                 all       500       500     0.952     0.992     0.994     0.972\n",
            "\n",
            "     Epoch   gpu_mem      GIoU       obj       cls     total   targets  img_size\n",
            "    66/299     11.8G      1.29     0.306         0       1.6        26       512: 100% 50/50 [00:33<00:00,  1.50it/s]\n",
            "               Class    Images   Targets         P         R   mAP@0.5        F1: 100% 50/50 [00:06<00:00,  7.63it/s]\n",
            "                 all       500       500     0.953     0.998     0.994     0.975\n",
            "\n",
            "     Epoch   gpu_mem      GIoU       obj       cls     total   targets  img_size\n",
            "    67/299     11.8G      1.08     0.281         0      1.36        16       512: 100% 50/50 [00:33<00:00,  1.50it/s]\n",
            "               Class    Images   Targets         P         R   mAP@0.5        F1: 100% 50/50 [00:07<00:00,  6.33it/s]\n",
            "                 all       500       500     0.962     0.998     0.995      0.98\n",
            "\n",
            "     Epoch   gpu_mem      GIoU       obj       cls     total   targets  img_size\n",
            "    68/299     11.8G      1.21     0.295         0      1.51        16       512: 100% 50/50 [00:33<00:00,  1.50it/s]\n",
            "               Class    Images   Targets         P         R   mAP@0.5        F1: 100% 50/50 [00:06<00:00,  7.64it/s]\n",
            "                 all       500       500     0.982         1     0.995     0.991\n",
            "\n",
            "     Epoch   gpu_mem      GIoU       obj       cls     total   targets  img_size\n",
            "    69/299     11.8G      1.26     0.296         0      1.56        20       512: 100% 50/50 [00:33<00:00,  1.50it/s]\n",
            "               Class    Images   Targets         P         R   mAP@0.5        F1: 100% 50/50 [00:06<00:00,  7.64it/s]\n",
            "                 all       500       500     0.967         1     0.994     0.983\n",
            "\n",
            "     Epoch   gpu_mem      GIoU       obj       cls     total   targets  img_size\n",
            "    70/299     11.8G      1.21     0.303         0      1.52        19       512: 100% 50/50 [00:33<00:00,  1.50it/s]\n",
            "               Class    Images   Targets         P         R   mAP@0.5        F1: 100% 50/50 [00:06<00:00,  7.61it/s]\n",
            "                 all       500       500     0.968         1     0.995     0.984\n",
            "\n",
            "     Epoch   gpu_mem      GIoU       obj       cls     total   targets  img_size\n",
            "    71/299     11.8G      1.22     0.301         0      1.52        21       512: 100% 50/50 [00:33<00:00,  1.50it/s]\n",
            "               Class    Images   Targets         P         R   mAP@0.5        F1: 100% 50/50 [00:06<00:00,  7.63it/s]\n",
            "                 all       500       500     0.976         1     0.995     0.988\n",
            "\n",
            "     Epoch   gpu_mem      GIoU       obj       cls     total   targets  img_size\n",
            "    72/299     11.8G      1.09     0.307         0       1.4        19       512: 100% 50/50 [00:33<00:00,  1.50it/s]\n",
            "               Class    Images   Targets         P         R   mAP@0.5        F1: 100% 50/50 [00:06<00:00,  7.60it/s]\n",
            "                 all       500       500     0.981         1     0.995     0.991\n",
            "\n",
            "     Epoch   gpu_mem      GIoU       obj       cls     total   targets  img_size\n",
            "    73/299     11.8G      1.16     0.274         0      1.43        18       512: 100% 50/50 [00:33<00:00,  1.49it/s]\n",
            "               Class    Images   Targets         P         R   mAP@0.5        F1: 100% 50/50 [00:06<00:00,  7.57it/s]\n",
            "                 all       500       500     0.986     0.998     0.995     0.992\n",
            "\n",
            "     Epoch   gpu_mem      GIoU       obj       cls     total   targets  img_size\n",
            "    74/299     11.8G      1.18     0.268         0      1.45        21       512: 100% 50/50 [00:33<00:00,  1.49it/s]\n",
            "               Class    Images   Targets         P         R   mAP@0.5        F1: 100% 50/50 [00:06<00:00,  7.59it/s]\n",
            "                 all       500       500     0.962     0.998     0.995      0.98\n",
            "\n",
            "     Epoch   gpu_mem      GIoU       obj       cls     total   targets  img_size\n",
            "    75/299     11.8G      1.39     0.298         0      1.69        17       512: 100% 50/50 [00:33<00:00,  1.50it/s]\n",
            "               Class    Images   Targets         P         R   mAP@0.5        F1: 100% 50/50 [00:06<00:00,  7.57it/s]\n",
            "                 all       500       500     0.972     0.998     0.995     0.985\n",
            "\n",
            "     Epoch   gpu_mem      GIoU       obj       cls     total   targets  img_size\n",
            "    76/299     11.8G      1.28     0.293         0      1.57        17       512: 100% 50/50 [00:33<00:00,  1.49it/s]\n",
            "               Class    Images   Targets         P         R   mAP@0.5        F1: 100% 50/50 [00:06<00:00,  7.62it/s]\n",
            "                 all       500       500     0.946     0.998     0.994     0.971\n",
            "\n",
            "     Epoch   gpu_mem      GIoU       obj       cls     total   targets  img_size\n",
            "    77/299     11.8G      1.14     0.301         0      1.44        15       512: 100% 50/50 [00:33<00:00,  1.50it/s]\n",
            "               Class    Images   Targets         P         R   mAP@0.5        F1: 100% 50/50 [00:06<00:00,  7.60it/s]\n",
            "                 all       500       500     0.949     0.998     0.995     0.973\n",
            "\n",
            "     Epoch   gpu_mem      GIoU       obj       cls     total   targets  img_size\n",
            "    78/299     11.8G      1.17     0.296         0      1.47        23       512: 100% 50/50 [00:33<00:00,  1.50it/s]\n",
            "               Class    Images   Targets         P         R   mAP@0.5        F1: 100% 50/50 [00:06<00:00,  7.56it/s]\n",
            "                 all       500       500     0.963     0.998     0.995      0.98\n",
            "\n",
            "     Epoch   gpu_mem      GIoU       obj       cls     total   targets  img_size\n",
            "    79/299     11.8G      1.16     0.287         0      1.44        23       512: 100% 50/50 [00:33<00:00,  1.50it/s]\n",
            "               Class    Images   Targets         P         R   mAP@0.5        F1: 100% 50/50 [00:06<00:00,  7.69it/s]\n",
            "                 all       500       500     0.949     0.998     0.995     0.973\n",
            "\n",
            "     Epoch   gpu_mem      GIoU       obj       cls     total   targets  img_size\n",
            "    80/299     11.8G      1.18     0.299         0      1.48        22       512: 100% 50/50 [00:33<00:00,  1.50it/s]\n",
            "               Class    Images   Targets         P         R   mAP@0.5        F1: 100% 50/50 [00:06<00:00,  7.65it/s]\n",
            "                 all       500       500     0.941         1     0.995      0.97\n",
            "\n",
            "     Epoch   gpu_mem      GIoU       obj       cls     total   targets  img_size\n",
            "    81/299     11.8G      1.06      0.29         0      1.35        22       512: 100% 50/50 [00:33<00:00,  1.50it/s]\n",
            "               Class    Images   Targets         P         R   mAP@0.5        F1: 100% 50/50 [00:06<00:00,  7.58it/s]\n",
            "                 all       500       500      0.95         1     0.995     0.974\n",
            "\n",
            "     Epoch   gpu_mem      GIoU       obj       cls     total   targets  img_size\n",
            "    82/299     11.8G      1.25     0.282         0      1.54        19       512: 100% 50/50 [00:33<00:00,  1.50it/s]\n",
            "               Class    Images   Targets         P         R   mAP@0.5        F1: 100% 50/50 [00:06<00:00,  7.70it/s]\n",
            "                 all       500       500     0.985     0.998     0.995     0.991\n",
            "\n",
            "     Epoch   gpu_mem      GIoU       obj       cls     total   targets  img_size\n",
            "    83/299     11.8G      1.14     0.294         0      1.43        15       512: 100% 50/50 [00:33<00:00,  1.50it/s]\n",
            "               Class    Images   Targets         P         R   mAP@0.5        F1: 100% 50/50 [00:06<00:00,  7.66it/s]\n",
            "                 all       500       500     0.972         1     0.995     0.986\n",
            "\n",
            "     Epoch   gpu_mem      GIoU       obj       cls     total   targets  img_size\n",
            "    84/299     11.8G      1.13     0.277         0      1.41        20       512: 100% 50/50 [00:33<00:00,  1.50it/s]\n",
            "               Class    Images   Targets         P         R   mAP@0.5        F1: 100% 50/50 [00:06<00:00,  7.65it/s]\n",
            "                 all       500       500     0.966         1     0.995     0.983\n",
            "\n",
            "     Epoch   gpu_mem      GIoU       obj       cls     total   targets  img_size\n",
            "    85/299     11.8G      1.06     0.273         0      1.33        19       512: 100% 50/50 [00:33<00:00,  1.50it/s]\n",
            "               Class    Images   Targets         P         R   mAP@0.5        F1: 100% 50/50 [00:06<00:00,  7.67it/s]\n",
            "                 all       500       500     0.977         1     0.995     0.988\n",
            "\n",
            "     Epoch   gpu_mem      GIoU       obj       cls     total   targets  img_size\n",
            "    86/299     11.8G      1.15     0.246         0       1.4        23       512: 100% 50/50 [00:33<00:00,  1.50it/s]\n",
            "               Class    Images   Targets         P         R   mAP@0.5        F1: 100% 50/50 [00:06<00:00,  7.60it/s]\n",
            "                 all       500       500     0.977         1     0.995     0.989\n",
            "\n",
            "     Epoch   gpu_mem      GIoU       obj       cls     total   targets  img_size\n",
            "    87/299     11.8G      1.02     0.266         0      1.28        19       512: 100% 50/50 [00:33<00:00,  1.50it/s]\n",
            "               Class    Images   Targets         P         R   mAP@0.5        F1: 100% 50/50 [00:06<00:00,  7.64it/s]\n",
            "                 all       500       500     0.965         1     0.995     0.982\n",
            "\n",
            "     Epoch   gpu_mem      GIoU       obj       cls     total   targets  img_size\n",
            "    88/299     11.8G      1.06     0.301         0      1.36        24       512: 100% 50/50 [00:33<00:00,  1.50it/s]\n",
            "               Class    Images   Targets         P         R   mAP@0.5        F1: 100% 50/50 [00:06<00:00,  7.64it/s]\n",
            "                 all       500       500     0.966         1     0.995     0.983\n",
            "\n",
            "     Epoch   gpu_mem      GIoU       obj       cls     total   targets  img_size\n",
            "    89/299     11.8G      1.21     0.262         0      1.47        19       512: 100% 50/50 [00:33<00:00,  1.50it/s]\n",
            "               Class    Images   Targets         P         R   mAP@0.5        F1: 100% 50/50 [00:06<00:00,  7.64it/s]\n",
            "                 all       500       500      0.97     0.998     0.995     0.984\n",
            "\n",
            "     Epoch   gpu_mem      GIoU       obj       cls     total   targets  img_size\n",
            "    90/299     11.8G      1.11     0.262         0      1.37        19       512: 100% 50/50 [00:33<00:00,  1.50it/s]\n",
            "               Class    Images   Targets         P         R   mAP@0.5        F1: 100% 50/50 [00:06<00:00,  7.64it/s]\n",
            "                 all       500       500     0.979         1     0.995     0.989\n",
            "\n",
            "     Epoch   gpu_mem      GIoU       obj       cls     total   targets  img_size\n",
            "    91/299     11.8G     0.994     0.267         0      1.26        20       512: 100% 50/50 [00:33<00:00,  1.50it/s]\n",
            "               Class    Images   Targets         P         R   mAP@0.5        F1: 100% 50/50 [00:06<00:00,  7.65it/s]\n",
            "                 all       500       500     0.978         1     0.995     0.989\n",
            "\n",
            "     Epoch   gpu_mem      GIoU       obj       cls     total   targets  img_size\n",
            "    92/299     11.8G     0.934      0.27         0       1.2        23       512: 100% 50/50 [00:33<00:00,  1.50it/s]\n",
            "               Class    Images   Targets         P         R   mAP@0.5        F1: 100% 50/50 [00:06<00:00,  7.62it/s]\n",
            "                 all       500       500     0.972         1     0.995     0.986\n",
            "\n",
            "     Epoch   gpu_mem      GIoU       obj       cls     total   targets  img_size\n",
            "    93/299     11.8G      1.14     0.255         0       1.4        20       512: 100% 50/50 [00:33<00:00,  1.50it/s]\n",
            "               Class    Images   Targets         P         R   mAP@0.5        F1: 100% 50/50 [00:06<00:00,  7.60it/s]\n",
            "                 all       500       500     0.984         1     0.995     0.992\n",
            "\n",
            "     Epoch   gpu_mem      GIoU       obj       cls     total   targets  img_size\n",
            "    94/299     11.8G     0.979     0.255         0      1.23        19       512: 100% 50/50 [00:33<00:00,  1.50it/s]\n",
            "               Class    Images   Targets         P         R   mAP@0.5        F1: 100% 50/50 [00:06<00:00,  7.64it/s]\n",
            "                 all       500       500     0.989         1     0.995     0.995\n",
            "\n",
            "     Epoch   gpu_mem      GIoU       obj       cls     total   targets  img_size\n",
            "    95/299     11.8G      1.11     0.268         0      1.38        19       512: 100% 50/50 [00:33<00:00,  1.50it/s]\n",
            "               Class    Images   Targets         P         R   mAP@0.5        F1: 100% 50/50 [00:06<00:00,  7.63it/s]\n",
            "                 all       500       500     0.984         1     0.995     0.992\n",
            "\n",
            "     Epoch   gpu_mem      GIoU       obj       cls     total   targets  img_size\n",
            "    96/299     11.8G      1.14     0.273         0      1.42        20       512: 100% 50/50 [00:33<00:00,  1.50it/s]\n",
            "               Class    Images   Targets         P         R   mAP@0.5        F1: 100% 50/50 [00:08<00:00,  6.22it/s]\n",
            "                 all       500       500     0.974         1     0.995     0.987\n",
            "\n",
            "     Epoch   gpu_mem      GIoU       obj       cls     total   targets  img_size\n",
            "    97/299     11.8G      1.19     0.286         0      1.47        17       512: 100% 50/50 [00:33<00:00,  1.50it/s]\n",
            "               Class    Images   Targets         P         R   mAP@0.5        F1: 100% 50/50 [00:06<00:00,  7.62it/s]\n",
            "                 all       500       500     0.958         1     0.995     0.979\n",
            "\n",
            "     Epoch   gpu_mem      GIoU       obj       cls     total   targets  img_size\n",
            "    98/299     11.8G      1.09     0.254         0      1.35        19       512: 100% 50/50 [00:33<00:00,  1.50it/s]\n",
            "               Class    Images   Targets         P         R   mAP@0.5        F1: 100% 50/50 [00:06<00:00,  7.64it/s]\n",
            "                 all       500       500     0.943         1     0.995     0.971\n",
            "\n",
            "     Epoch   gpu_mem      GIoU       obj       cls     total   targets  img_size\n",
            "    99/299     11.8G      1.09     0.269         0      1.36        22       512: 100% 50/50 [00:33<00:00,  1.49it/s]\n",
            "               Class    Images   Targets         P         R   mAP@0.5        F1: 100% 50/50 [00:06<00:00,  7.63it/s]\n",
            "                 all       500       500     0.959         1     0.995     0.979\n",
            "\n",
            "     Epoch   gpu_mem      GIoU       obj       cls     total   targets  img_size\n",
            "   100/299     11.8G      1.15     0.262         0      1.42        20       512: 100% 50/50 [00:33<00:00,  1.50it/s]\n",
            "               Class    Images   Targets         P         R   mAP@0.5        F1: 100% 50/50 [00:06<00:00,  7.60it/s]\n",
            "                 all       500       500     0.974         1     0.995     0.987\n",
            "\n",
            "     Epoch   gpu_mem      GIoU       obj       cls     total   targets  img_size\n",
            "   101/299     11.8G      1.02     0.259         0      1.28        21       512: 100% 50/50 [00:33<00:00,  1.50it/s]\n",
            "               Class    Images   Targets         P         R   mAP@0.5        F1: 100% 50/50 [00:06<00:00,  7.63it/s]\n",
            "                 all       500       500     0.966         1     0.995     0.983\n",
            "\n",
            "     Epoch   gpu_mem      GIoU       obj       cls     total   targets  img_size\n",
            "   102/299     11.8G      1.19     0.246         0      1.43        17       512: 100% 50/50 [00:33<00:00,  1.50it/s]\n",
            "               Class    Images   Targets         P         R   mAP@0.5        F1: 100% 50/50 [00:06<00:00,  7.65it/s]\n",
            "                 all       500       500     0.961         1     0.995      0.98\n",
            "\n",
            "     Epoch   gpu_mem      GIoU       obj       cls     total   targets  img_size\n",
            "   103/299     11.8G      1.07     0.252         0      1.32        24       512: 100% 50/50 [00:33<00:00,  1.50it/s]\n",
            "               Class    Images   Targets         P         R   mAP@0.5        F1: 100% 50/50 [00:06<00:00,  7.59it/s]\n",
            "                 all       500       500     0.968         1     0.995     0.984\n",
            "\n",
            "     Epoch   gpu_mem      GIoU       obj       cls     total   targets  img_size\n",
            "   104/299     11.8G      1.04     0.238         0      1.28        21       512: 100% 50/50 [00:33<00:00,  1.49it/s]\n",
            "               Class    Images   Targets         P         R   mAP@0.5        F1: 100% 50/50 [00:06<00:00,  7.55it/s]\n",
            "                 all       500       500     0.973         1     0.995     0.986\n",
            "\n",
            "     Epoch   gpu_mem      GIoU       obj       cls     total   targets  img_size\n",
            "   105/299     11.8G      1.18     0.242         0      1.42        19       512: 100% 50/50 [00:33<00:00,  1.50it/s]\n",
            "               Class    Images   Targets         P         R   mAP@0.5        F1: 100% 50/50 [00:06<00:00,  7.61it/s]\n",
            "                 all       500       500     0.978         1     0.995     0.989\n",
            "\n",
            "     Epoch   gpu_mem      GIoU       obj       cls     total   targets  img_size\n",
            "   106/299     11.8G      1.16     0.271         0      1.43        18       512: 100% 50/50 [00:33<00:00,  1.50it/s]\n",
            "               Class    Images   Targets         P         R   mAP@0.5        F1: 100% 50/50 [00:06<00:00,  7.63it/s]\n",
            "                 all       500       500     0.976         1     0.995     0.988\n",
            "\n",
            "     Epoch   gpu_mem      GIoU       obj       cls     total   targets  img_size\n",
            "   107/299     11.8G      1.06     0.257         0      1.31        20       512: 100% 50/50 [00:33<00:00,  1.50it/s]\n",
            "               Class    Images   Targets         P         R   mAP@0.5        F1: 100% 50/50 [00:06<00:00,  7.59it/s]\n",
            "                 all       500       500     0.986         1     0.995     0.993\n",
            "\n",
            "     Epoch   gpu_mem      GIoU       obj       cls     total   targets  img_size\n",
            "   108/299     11.8G     0.955     0.239         0      1.19        19       512: 100% 50/50 [00:33<00:00,  1.50it/s]\n",
            "               Class    Images   Targets         P         R   mAP@0.5        F1: 100% 50/50 [00:06<00:00,  7.63it/s]\n",
            "                 all       500       500     0.978         1     0.995     0.989\n",
            "\n",
            "     Epoch   gpu_mem      GIoU       obj       cls     total   targets  img_size\n",
            "   109/299     11.8G      1.13     0.268         0       1.4        22       512: 100% 50/50 [00:33<00:00,  1.50it/s]\n",
            "               Class    Images   Targets         P         R   mAP@0.5        F1: 100% 50/50 [00:06<00:00,  7.62it/s]\n",
            "                 all       500       500     0.973         1     0.995     0.986\n",
            "\n",
            "     Epoch   gpu_mem      GIoU       obj       cls     total   targets  img_size\n",
            "   110/299     11.8G     0.897     0.244         0      1.14        18       512: 100% 50/50 [00:33<00:00,  1.50it/s]\n",
            "               Class    Images   Targets         P         R   mAP@0.5        F1: 100% 50/50 [00:06<00:00,  7.61it/s]\n",
            "                 all       500       500     0.977         1     0.995     0.988\n",
            "\n",
            "     Epoch   gpu_mem      GIoU       obj       cls     total   targets  img_size\n",
            "   111/299     11.8G     0.959     0.255         0      1.21        21       512: 100% 50/50 [00:33<00:00,  1.50it/s]\n",
            "               Class    Images   Targets         P         R   mAP@0.5        F1: 100% 50/50 [00:06<00:00,  7.60it/s]\n",
            "                 all       500       500     0.974         1     0.995     0.987\n",
            "\n",
            "     Epoch   gpu_mem      GIoU       obj       cls     total   targets  img_size\n",
            "   112/299     11.8G     0.889     0.241         0      1.13        22       512: 100% 50/50 [00:33<00:00,  1.50it/s]\n",
            "               Class    Images   Targets         P         R   mAP@0.5        F1: 100% 50/50 [00:06<00:00,  7.66it/s]\n",
            "                 all       500       500     0.977         1     0.995     0.989\n",
            "\n",
            "     Epoch   gpu_mem      GIoU       obj       cls     total   targets  img_size\n",
            "   113/299     11.8G     0.987      0.24         0      1.23        19       512: 100% 50/50 [00:33<00:00,  1.50it/s]\n",
            "               Class    Images   Targets         P         R   mAP@0.5        F1: 100% 50/50 [00:06<00:00,  7.64it/s]\n",
            "                 all       500       500     0.972         1     0.995     0.986\n",
            "\n",
            "     Epoch   gpu_mem      GIoU       obj       cls     total   targets  img_size\n",
            "   114/299     11.8G     0.975     0.259         0      1.23        17       512: 100% 50/50 [00:33<00:00,  1.49it/s]\n",
            "               Class    Images   Targets         P         R   mAP@0.5        F1: 100% 50/50 [00:06<00:00,  7.54it/s]\n",
            "                 all       500       500     0.985         1     0.995     0.992\n",
            "\n",
            "     Epoch   gpu_mem      GIoU       obj       cls     total   targets  img_size\n",
            "   115/299     11.8G     0.951     0.252         0       1.2        21       512: 100% 50/50 [00:33<00:00,  1.49it/s]\n",
            "               Class    Images   Targets         P         R   mAP@0.5        F1: 100% 50/50 [00:06<00:00,  7.68it/s]\n",
            "                 all       500       500     0.991         1     0.995     0.995\n",
            "\n",
            "     Epoch   gpu_mem      GIoU       obj       cls     total   targets  img_size\n",
            "   116/299     11.8G      0.93     0.224         0      1.15        17       512: 100% 50/50 [00:33<00:00,  1.50it/s]\n",
            "               Class    Images   Targets         P         R   mAP@0.5        F1: 100% 50/50 [00:06<00:00,  7.62it/s]\n",
            "                 all       500       500     0.997         1     0.995     0.998\n",
            "\n",
            "     Epoch   gpu_mem      GIoU       obj       cls     total   targets  img_size\n",
            "   117/299     11.8G      1.12     0.256         0      1.38        20       512: 100% 50/50 [00:33<00:00,  1.50it/s]\n",
            "               Class    Images   Targets         P         R   mAP@0.5        F1: 100% 50/50 [00:06<00:00,  7.63it/s]\n",
            "                 all       500       500         1     0.993     0.995     0.996\n",
            "\n",
            "     Epoch   gpu_mem      GIoU       obj       cls     total   targets  img_size\n",
            "   118/299     11.8G      1.03     0.243         0      1.27        16       512: 100% 50/50 [00:33<00:00,  1.50it/s]\n",
            "               Class    Images   Targets         P         R   mAP@0.5        F1: 100% 50/50 [00:06<00:00,  7.58it/s]\n",
            "                 all       500       500     0.994      0.99     0.995     0.992\n",
            "\n",
            "     Epoch   gpu_mem      GIoU       obj       cls     total   targets  img_size\n",
            "   119/299     11.8G      1.06     0.258         0      1.32        19       512: 100% 50/50 [00:33<00:00,  1.50it/s]\n",
            "               Class    Images   Targets         P         R   mAP@0.5        F1: 100% 50/50 [00:06<00:00,  7.68it/s]\n",
            "                 all       500       500     0.998         1     0.995     0.999\n",
            "\n",
            "     Epoch   gpu_mem      GIoU       obj       cls     total   targets  img_size\n",
            "   120/299     11.8G      1.03     0.241         0      1.27        23       512: 100% 50/50 [00:33<00:00,  1.49it/s]\n",
            "               Class    Images   Targets         P         R   mAP@0.5        F1: 100% 50/50 [00:06<00:00,  7.65it/s]\n",
            "                 all       500       500      0.97         1     0.995     0.985\n",
            "\n",
            "     Epoch   gpu_mem      GIoU       obj       cls     total   targets  img_size\n",
            "   121/299     11.8G      1.02     0.246         0      1.26        23       512: 100% 50/50 [00:33<00:00,  1.50it/s]\n",
            "               Class    Images   Targets         P         R   mAP@0.5        F1: 100% 50/50 [00:06<00:00,  7.71it/s]\n",
            "                 all       500       500     0.983         1     0.995     0.991\n",
            "\n",
            "     Epoch   gpu_mem      GIoU       obj       cls     total   targets  img_size\n",
            "   122/299     11.8G     0.926      0.25         0      1.18        18       512: 100% 50/50 [00:33<00:00,  1.50it/s]\n",
            "               Class    Images   Targets         P         R   mAP@0.5        F1: 100% 50/50 [00:06<00:00,  7.66it/s]\n",
            "                 all       500       500     0.991         1     0.995     0.995\n",
            "\n",
            "     Epoch   gpu_mem      GIoU       obj       cls     total   targets  img_size\n",
            "   123/299     11.8G         1     0.243         0      1.25        23       512: 100% 50/50 [00:33<00:00,  1.50it/s]\n",
            "               Class    Images   Targets         P         R   mAP@0.5        F1: 100% 50/50 [00:06<00:00,  7.65it/s]\n",
            "                 all       500       500     0.983     0.998     0.995      0.99\n",
            "\n",
            "     Epoch   gpu_mem      GIoU       obj       cls     total   targets  img_size\n",
            "   124/299     11.8G      1.01     0.237         0      1.25        20       512: 100% 50/50 [00:33<00:00,  1.50it/s]\n",
            "               Class    Images   Targets         P         R   mAP@0.5        F1: 100% 50/50 [00:06<00:00,  7.67it/s]\n",
            "                 all       500       500     0.983         1     0.995     0.992\n",
            "\n",
            "     Epoch   gpu_mem      GIoU       obj       cls     total   targets  img_size\n",
            "   125/299     11.8G      0.92     0.238         0      1.16        24       512: 100% 50/50 [00:33<00:00,  1.50it/s]\n",
            "               Class    Images   Targets         P         R   mAP@0.5        F1: 100% 50/50 [00:06<00:00,  7.61it/s]\n",
            "                 all       500       500     0.977         1     0.995     0.989\n",
            "\n",
            "     Epoch   gpu_mem      GIoU       obj       cls     total   targets  img_size\n",
            "   126/299     11.8G     0.979     0.235         0      1.21        18       512: 100% 50/50 [00:33<00:00,  1.50it/s]\n",
            "               Class    Images   Targets         P         R   mAP@0.5        F1: 100% 50/50 [00:06<00:00,  7.67it/s]\n",
            "                 all       500       500     0.984         1     0.995     0.992\n",
            "\n",
            "     Epoch   gpu_mem      GIoU       obj       cls     total   targets  img_size\n",
            "   127/299     11.8G      1.03     0.243         0      1.28        23       512: 100% 50/50 [00:33<00:00,  1.50it/s]\n",
            "               Class    Images   Targets         P         R   mAP@0.5        F1: 100% 50/50 [00:06<00:00,  7.64it/s]\n",
            "                 all       500       500     0.986         1     0.995     0.993\n",
            "\n",
            "     Epoch   gpu_mem      GIoU       obj       cls     total   targets  img_size\n",
            "   128/299     11.8G     0.855     0.224         0      1.08        17       512: 100% 50/50 [00:33<00:00,  1.50it/s]\n",
            "               Class    Images   Targets         P         R   mAP@0.5        F1: 100% 50/50 [00:06<00:00,  7.66it/s]\n",
            "                 all       500       500     0.988         1     0.995     0.994\n",
            "\n",
            "     Epoch   gpu_mem      GIoU       obj       cls     total   targets  img_size\n",
            "   129/299     11.8G     0.926     0.231         0      1.16        23       512: 100% 50/50 [00:33<00:00,  1.50it/s]\n",
            "               Class    Images   Targets         P         R   mAP@0.5        F1: 100% 50/50 [00:06<00:00,  7.64it/s]\n",
            "                 all       500       500     0.984         1     0.995     0.992\n",
            "\n",
            "     Epoch   gpu_mem      GIoU       obj       cls     total   targets  img_size\n",
            "   130/299     11.8G      0.86     0.248         0      1.11        16       512: 100% 50/50 [00:33<00:00,  1.50it/s]\n",
            "               Class    Images   Targets         P         R   mAP@0.5        F1: 100% 50/50 [00:06<00:00,  7.63it/s]\n",
            "                 all       500       500     0.985         1     0.995     0.993\n",
            "\n",
            "     Epoch   gpu_mem      GIoU       obj       cls     total   targets  img_size\n",
            "   131/299     11.8G     0.836     0.235         0      1.07        19       512: 100% 50/50 [00:33<00:00,  1.50it/s]\n",
            "               Class    Images   Targets         P         R   mAP@0.5        F1: 100% 50/50 [00:06<00:00,  7.63it/s]\n",
            "                 all       500       500     0.992         1     0.995     0.996\n",
            "\n",
            "     Epoch   gpu_mem      GIoU       obj       cls     total   targets  img_size\n",
            "   132/299     11.8G     0.876     0.243         0      1.12        19       512: 100% 50/50 [00:33<00:00,  1.50it/s]\n",
            "               Class    Images   Targets         P         R   mAP@0.5        F1: 100% 50/50 [00:06<00:00,  7.63it/s]\n",
            "                 all       500       500     0.983         1     0.995     0.991\n",
            "\n",
            "     Epoch   gpu_mem      GIoU       obj       cls     total   targets  img_size\n",
            "   133/299     11.8G      1.01     0.225         0      1.23        21       512: 100% 50/50 [00:33<00:00,  1.50it/s]\n",
            "               Class    Images   Targets         P         R   mAP@0.5        F1: 100% 50/50 [00:06<00:00,  7.65it/s]\n",
            "                 all       500       500     0.983         1     0.995     0.992\n",
            "\n",
            "     Epoch   gpu_mem      GIoU       obj       cls     total   targets  img_size\n",
            "   134/299     11.8G     0.914     0.249         0      1.16        17       512: 100% 50/50 [00:33<00:00,  1.50it/s]\n",
            "               Class    Images   Targets         P         R   mAP@0.5        F1: 100% 50/50 [00:06<00:00,  7.64it/s]\n",
            "                 all       500       500     0.987         1     0.995     0.993\n",
            "\n",
            "     Epoch   gpu_mem      GIoU       obj       cls     total   targets  img_size\n",
            "   135/299     11.8G     0.921     0.225         0      1.15        19       512: 100% 50/50 [00:33<00:00,  1.50it/s]\n",
            "               Class    Images   Targets         P         R   mAP@0.5        F1: 100% 50/50 [00:06<00:00,  7.64it/s]\n",
            "                 all       500       500     0.987         1     0.995     0.993\n",
            "\n",
            "     Epoch   gpu_mem      GIoU       obj       cls     total   targets  img_size\n",
            "   136/299     11.8G     0.862     0.221         0      1.08        17       512: 100% 50/50 [00:33<00:00,  1.50it/s]\n",
            "               Class    Images   Targets         P         R   mAP@0.5        F1: 100% 50/50 [00:06<00:00,  7.64it/s]\n",
            "                 all       500       500     0.986         1     0.995     0.993\n",
            "\n",
            "     Epoch   gpu_mem      GIoU       obj       cls     total   targets  img_size\n",
            "   137/299     11.8G      0.85     0.226         0      1.08        21       512: 100% 50/50 [00:33<00:00,  1.50it/s]\n",
            "               Class    Images   Targets         P         R   mAP@0.5        F1: 100% 50/50 [00:06<00:00,  7.64it/s]\n",
            "                 all       500       500     0.985         1     0.995     0.993\n",
            "\n",
            "     Epoch   gpu_mem      GIoU       obj       cls     total   targets  img_size\n",
            "   138/299     11.8G     0.814     0.211         0      1.02        17       512: 100% 50/50 [00:33<00:00,  1.50it/s]\n",
            "               Class    Images   Targets         P         R   mAP@0.5        F1: 100% 50/50 [00:06<00:00,  7.62it/s]\n",
            "                 all       500       500     0.988         1     0.995     0.994\n",
            "\n",
            "     Epoch   gpu_mem      GIoU       obj       cls     total   targets  img_size\n",
            "   139/299     11.8G     0.777     0.218         0     0.994        21       512: 100% 50/50 [00:33<00:00,  1.50it/s]\n",
            "               Class    Images   Targets         P         R   mAP@0.5        F1: 100% 50/50 [00:06<00:00,  7.64it/s]\n",
            "                 all       500       500     0.977         1     0.995     0.988\n",
            "\n",
            "     Epoch   gpu_mem      GIoU       obj       cls     total   targets  img_size\n",
            "   140/299     11.8G     0.765     0.219         0     0.983        20       512: 100% 50/50 [00:33<00:00,  1.50it/s]\n",
            "               Class    Images   Targets         P         R   mAP@0.5        F1: 100% 50/50 [00:06<00:00,  7.63it/s]\n",
            "                 all       500       500     0.987         1     0.995     0.994\n",
            "\n",
            "     Epoch   gpu_mem      GIoU       obj       cls     total   targets  img_size\n",
            "   141/299     11.8G     0.879     0.231         0      1.11        21       512: 100% 50/50 [00:33<00:00,  1.50it/s]\n",
            "               Class    Images   Targets         P         R   mAP@0.5        F1: 100% 50/50 [00:06<00:00,  7.61it/s]\n",
            "                 all       500       500     0.983         1     0.995     0.991\n",
            "\n",
            "     Epoch   gpu_mem      GIoU       obj       cls     total   targets  img_size\n",
            "   142/299     11.8G     0.891     0.228         0      1.12        17       512: 100% 50/50 [00:33<00:00,  1.50it/s]\n",
            "               Class    Images   Targets         P         R   mAP@0.5        F1: 100% 50/50 [00:06<00:00,  7.62it/s]\n",
            "                 all       500       500     0.971         1     0.995     0.985\n",
            "\n",
            "     Epoch   gpu_mem      GIoU       obj       cls     total   targets  img_size\n",
            "   143/299     11.8G     0.789     0.215         0         1        17       512: 100% 50/50 [00:33<00:00,  1.49it/s]\n",
            "               Class    Images   Targets         P         R   mAP@0.5        F1: 100% 50/50 [00:06<00:00,  7.63it/s]\n",
            "                 all       500       500     0.981         1     0.995      0.99\n",
            "\n",
            "     Epoch   gpu_mem      GIoU       obj       cls     total   targets  img_size\n",
            "   144/299     11.8G     0.795      0.21         0      1.01        20       512: 100% 50/50 [00:33<00:00,  1.50it/s]\n",
            "               Class    Images   Targets         P         R   mAP@0.5        F1: 100% 50/50 [00:06<00:00,  7.65it/s]\n",
            "                 all       500       500     0.978         1     0.995     0.989\n",
            "\n",
            "     Epoch   gpu_mem      GIoU       obj       cls     total   targets  img_size\n",
            "   145/299     11.8G     0.807     0.224         0      1.03        22       512: 100% 50/50 [00:33<00:00,  1.50it/s]\n",
            "               Class    Images   Targets         P         R   mAP@0.5        F1: 100% 50/50 [00:06<00:00,  7.60it/s]\n",
            "                 all       500       500     0.981         1     0.995      0.99\n",
            "\n",
            "     Epoch   gpu_mem      GIoU       obj       cls     total   targets  img_size\n",
            "   146/299     11.8G     0.814     0.224         0      1.04        19       512: 100% 50/50 [00:33<00:00,  1.50it/s]\n",
            "               Class    Images   Targets         P         R   mAP@0.5        F1: 100% 50/50 [00:06<00:00,  7.61it/s]\n",
            "                 all       500       500      0.98         1     0.995      0.99\n",
            "\n",
            "     Epoch   gpu_mem      GIoU       obj       cls     total   targets  img_size\n",
            "   147/299     11.8G     0.872     0.218         0      1.09        17       512: 100% 50/50 [00:33<00:00,  1.50it/s]\n",
            "               Class    Images   Targets         P         R   mAP@0.5        F1: 100% 50/50 [00:06<00:00,  7.64it/s]\n",
            "                 all       500       500     0.985         1     0.995     0.992\n",
            "\n",
            "     Epoch   gpu_mem      GIoU       obj       cls     total   targets  img_size\n",
            "   148/299     11.8G     0.785     0.224         0      1.01        21       512: 100% 50/50 [00:33<00:00,  1.50it/s]\n",
            "               Class    Images   Targets         P         R   mAP@0.5        F1: 100% 50/50 [00:06<00:00,  7.67it/s]\n",
            "                 all       500       500     0.981         1     0.995     0.991\n",
            "\n",
            "     Epoch   gpu_mem      GIoU       obj       cls     total   targets  img_size\n",
            "   149/299     11.8G     0.746     0.207         0     0.953        17       512: 100% 50/50 [00:33<00:00,  1.50it/s]\n",
            "               Class    Images   Targets         P         R   mAP@0.5        F1: 100% 50/50 [00:06<00:00,  7.67it/s]\n",
            "                 all       500       500      0.99         1     0.995     0.995\n",
            "\n",
            "     Epoch   gpu_mem      GIoU       obj       cls     total   targets  img_size\n",
            "   150/299     11.8G     0.836     0.205         0      1.04        22       512: 100% 50/50 [00:33<00:00,  1.50it/s]\n",
            "               Class    Images   Targets         P         R   mAP@0.5        F1: 100% 50/50 [00:06<00:00,  7.65it/s]\n",
            "                 all       500       500     0.993         1     0.995     0.996\n",
            "\n",
            "     Epoch   gpu_mem      GIoU       obj       cls     total   targets  img_size\n",
            "   151/299     11.8G     0.825      0.23         0      1.05        17       512: 100% 50/50 [00:33<00:00,  1.50it/s]\n",
            "               Class    Images   Targets         P         R   mAP@0.5        F1: 100% 50/50 [00:06<00:00,  7.64it/s]\n",
            "                 all       500       500     0.992         1     0.995     0.996\n",
            "\n",
            "     Epoch   gpu_mem      GIoU       obj       cls     total   targets  img_size\n",
            "   152/299     11.8G     0.742     0.207         0     0.949        21       512: 100% 50/50 [00:33<00:00,  1.50it/s]\n",
            "               Class    Images   Targets         P         R   mAP@0.5        F1: 100% 50/50 [00:06<00:00,  7.69it/s]\n",
            "                 all       500       500     0.989         1     0.995     0.994\n",
            "\n",
            "     Epoch   gpu_mem      GIoU       obj       cls     total   targets  img_size\n",
            "   153/299     11.8G     0.792     0.207         0     0.999        21       512: 100% 50/50 [00:33<00:00,  1.50it/s]\n",
            "               Class    Images   Targets         P         R   mAP@0.5        F1: 100% 50/50 [00:06<00:00,  7.67it/s]\n",
            "                 all       500       500     0.991         1     0.995     0.996\n",
            "\n",
            "     Epoch   gpu_mem      GIoU       obj       cls     total   targets  img_size\n",
            "   154/299     11.8G      0.86     0.212         0      1.07        16       512: 100% 50/50 [00:33<00:00,  1.50it/s]\n",
            "               Class    Images   Targets         P         R   mAP@0.5        F1: 100% 50/50 [00:06<00:00,  7.66it/s]\n",
            "                 all       500       500     0.998         1     0.995     0.999\n",
            "\n",
            "     Epoch   gpu_mem      GIoU       obj       cls     total   targets  img_size\n",
            "   155/299     11.8G     0.853     0.225         0      1.08        19       512: 100% 50/50 [00:33<00:00,  1.50it/s]\n",
            "               Class    Images   Targets         P         R   mAP@0.5        F1: 100% 50/50 [00:06<00:00,  7.62it/s]\n",
            "                 all       500       500     0.993         1     0.995     0.997\n",
            "\n",
            "     Epoch   gpu_mem      GIoU       obj       cls     total   targets  img_size\n",
            "   156/299     11.8G     0.804     0.207         0      1.01        20       512: 100% 50/50 [00:33<00:00,  1.50it/s]\n",
            "               Class    Images   Targets         P         R   mAP@0.5        F1: 100% 50/50 [00:06<00:00,  7.66it/s]\n",
            "                 all       500       500      0.99         1     0.995     0.995\n",
            "\n",
            "     Epoch   gpu_mem      GIoU       obj       cls     total   targets  img_size\n",
            "   157/299     11.8G     0.876     0.214         0      1.09        22       512: 100% 50/50 [00:33<00:00,  1.50it/s]\n",
            "               Class    Images   Targets         P         R   mAP@0.5        F1: 100% 50/50 [00:06<00:00,  7.68it/s]\n",
            "                 all       500       500     0.997         1     0.995     0.998\n",
            "\n",
            "     Epoch   gpu_mem      GIoU       obj       cls     total   targets  img_size\n",
            "   158/299     11.8G     0.825     0.209         0      1.03        17       512: 100% 50/50 [00:33<00:00,  1.50it/s]\n",
            "               Class    Images   Targets         P         R   mAP@0.5        F1: 100% 50/50 [00:06<00:00,  7.64it/s]\n",
            "                 all       500       500     0.988         1     0.995     0.994\n",
            "\n",
            "     Epoch   gpu_mem      GIoU       obj       cls     total   targets  img_size\n",
            "   159/299     11.8G     0.739     0.198         0     0.937        19       512: 100% 50/50 [00:33<00:00,  1.50it/s]\n",
            "               Class    Images   Targets         P         R   mAP@0.5        F1: 100% 50/50 [00:06<00:00,  7.65it/s]\n",
            "                 all       500       500     0.987         1     0.995     0.994\n",
            "\n",
            "     Epoch   gpu_mem      GIoU       obj       cls     total   targets  img_size\n",
            "   160/299     11.8G     0.784     0.209         0     0.992        19       512: 100% 50/50 [00:33<00:00,  1.50it/s]\n",
            "               Class    Images   Targets         P         R   mAP@0.5        F1: 100% 50/50 [00:06<00:00,  7.67it/s]\n",
            "                 all       500       500     0.985         1     0.995     0.992\n",
            "\n",
            "     Epoch   gpu_mem      GIoU       obj       cls     total   targets  img_size\n",
            "   161/299     11.8G      0.75     0.198         0     0.948        19       512: 100% 50/50 [00:33<00:00,  1.50it/s]\n",
            "               Class    Images   Targets         P         R   mAP@0.5        F1: 100% 50/50 [00:06<00:00,  7.68it/s]\n",
            "                 all       500       500     0.986         1     0.995     0.993\n",
            "\n",
            "     Epoch   gpu_mem      GIoU       obj       cls     total   targets  img_size\n",
            "   162/299     11.8G     0.733     0.217         0     0.951        19       512: 100% 50/50 [00:33<00:00,  1.50it/s]\n",
            "               Class    Images   Targets         P         R   mAP@0.5        F1: 100% 50/50 [00:06<00:00,  7.63it/s]\n",
            "                 all       500       500     0.984         1     0.995     0.992\n",
            "\n",
            "     Epoch   gpu_mem      GIoU       obj       cls     total   targets  img_size\n",
            "   163/299     11.8G     0.687     0.191         0     0.878        19       512: 100% 50/50 [00:33<00:00,  1.50it/s]\n",
            "               Class    Images   Targets         P         R   mAP@0.5        F1: 100% 50/50 [00:06<00:00,  7.67it/s]\n",
            "                 all       500       500     0.988         1     0.995     0.994\n",
            "\n",
            "     Epoch   gpu_mem      GIoU       obj       cls     total   targets  img_size\n",
            "   164/299     11.8G     0.773     0.218         0     0.991        22       512: 100% 50/50 [00:33<00:00,  1.50it/s]\n",
            "               Class    Images   Targets         P         R   mAP@0.5        F1: 100% 50/50 [00:06<00:00,  7.63it/s]\n",
            "                 all       500       500     0.982         1     0.995     0.991\n",
            "\n",
            "     Epoch   gpu_mem      GIoU       obj       cls     total   targets  img_size\n",
            "   165/299     11.8G     0.794     0.207         0         1        18       512: 100% 50/50 [00:33<00:00,  1.50it/s]\n",
            "               Class    Images   Targets         P         R   mAP@0.5        F1: 100% 50/50 [00:06<00:00,  7.65it/s]\n",
            "                 all       500       500      0.98         1     0.995      0.99\n",
            "\n",
            "     Epoch   gpu_mem      GIoU       obj       cls     total   targets  img_size\n",
            "   166/299     11.8G     0.834     0.205         0      1.04        24       512: 100% 50/50 [00:33<00:00,  1.50it/s]\n",
            "               Class    Images   Targets         P         R   mAP@0.5        F1: 100% 50/50 [00:06<00:00,  7.62it/s]\n",
            "                 all       500       500     0.985         1     0.995     0.993\n",
            "\n",
            "     Epoch   gpu_mem      GIoU       obj       cls     total   targets  img_size\n",
            "   167/299     11.8G      0.71     0.194         0     0.904        19       512: 100% 50/50 [00:33<00:00,  1.50it/s]\n",
            "               Class    Images   Targets         P         R   mAP@0.5        F1: 100% 50/50 [00:06<00:00,  7.65it/s]\n",
            "                 all       500       500     0.985         1     0.995     0.992\n",
            "\n",
            "     Epoch   gpu_mem      GIoU       obj       cls     total   targets  img_size\n",
            "   168/299     11.8G     0.749     0.193         0     0.942        21       512: 100% 50/50 [00:33<00:00,  1.50it/s]\n",
            "               Class    Images   Targets         P         R   mAP@0.5        F1: 100% 50/50 [00:06<00:00,  7.70it/s]\n",
            "                 all       500       500     0.985         1     0.995     0.992\n",
            "\n",
            "     Epoch   gpu_mem      GIoU       obj       cls     total   targets  img_size\n",
            "   169/299     11.8G     0.779     0.207         0     0.986        19       512: 100% 50/50 [00:33<00:00,  1.49it/s]\n",
            "               Class    Images   Targets         P         R   mAP@0.5        F1: 100% 50/50 [00:06<00:00,  7.67it/s]\n",
            "                 all       500       500      0.98         1     0.995      0.99\n",
            "\n",
            "     Epoch   gpu_mem      GIoU       obj       cls     total   targets  img_size\n",
            "   170/299     11.8G     0.686     0.209         0     0.895        19       512: 100% 50/50 [00:33<00:00,  1.50it/s]\n",
            "               Class    Images   Targets         P         R   mAP@0.5        F1: 100% 50/50 [00:06<00:00,  7.67it/s]\n",
            "                 all       500       500     0.979         1     0.995     0.989\n",
            "\n",
            "     Epoch   gpu_mem      GIoU       obj       cls     total   targets  img_size\n",
            "   171/299     11.8G      0.76      0.18         0      0.94        18       512: 100% 50/50 [00:33<00:00,  1.50it/s]\n",
            "               Class    Images   Targets         P         R   mAP@0.5        F1: 100% 50/50 [00:06<00:00,  7.69it/s]\n",
            "                 all       500       500     0.978         1     0.995     0.989\n",
            "\n",
            "     Epoch   gpu_mem      GIoU       obj       cls     total   targets  img_size\n",
            "   172/299     11.8G     0.767     0.197         0     0.964        18       512: 100% 50/50 [00:33<00:00,  1.50it/s]\n",
            "               Class    Images   Targets         P         R   mAP@0.5        F1: 100% 50/50 [00:06<00:00,  7.67it/s]\n",
            "                 all       500       500     0.974         1     0.995     0.987\n",
            "\n",
            "     Epoch   gpu_mem      GIoU       obj       cls     total   targets  img_size\n",
            "   173/299     11.8G     0.784     0.208         0     0.992        19       512: 100% 50/50 [00:33<00:00,  1.50it/s]\n",
            "               Class    Images   Targets         P         R   mAP@0.5        F1: 100% 50/50 [00:06<00:00,  7.67it/s]\n",
            "                 all       500       500     0.979         1     0.995     0.989\n",
            "\n",
            "     Epoch   gpu_mem      GIoU       obj       cls     total   targets  img_size\n",
            "   174/299     11.8G     0.728      0.19         0     0.918        19       512: 100% 50/50 [00:33<00:00,  1.50it/s]\n",
            "               Class    Images   Targets         P         R   mAP@0.5        F1: 100% 50/50 [00:06<00:00,  7.61it/s]\n",
            "                 all       500       500     0.986         1     0.995     0.993\n",
            "\n",
            "     Epoch   gpu_mem      GIoU       obj       cls     total   targets  img_size\n",
            "   175/299     11.8G     0.687      0.18         0     0.867        22       512: 100% 50/50 [00:33<00:00,  1.50it/s]\n",
            "               Class    Images   Targets         P         R   mAP@0.5        F1: 100% 50/50 [00:06<00:00,  7.65it/s]\n",
            "                 all       500       500     0.988         1     0.995     0.994\n",
            "\n",
            "     Epoch   gpu_mem      GIoU       obj       cls     total   targets  img_size\n",
            "   176/299     11.8G     0.637     0.197         0     0.834        18       512: 100% 50/50 [00:33<00:00,  1.50it/s]\n",
            "               Class    Images   Targets         P         R   mAP@0.5        F1: 100% 50/50 [00:06<00:00,  7.66it/s]\n",
            "                 all       500       500     0.985         1     0.995     0.993\n",
            "\n",
            "     Epoch   gpu_mem      GIoU       obj       cls     total   targets  img_size\n",
            "   177/299     11.8G     0.717     0.191         0     0.908        24       512: 100% 50/50 [00:33<00:00,  1.50it/s]\n",
            "               Class    Images   Targets         P         R   mAP@0.5        F1: 100% 50/50 [00:06<00:00,  7.66it/s]\n",
            "                 all       500       500     0.985         1     0.995     0.992\n",
            "\n",
            "     Epoch   gpu_mem      GIoU       obj       cls     total   targets  img_size\n",
            "   178/299     11.8G     0.722     0.207         0     0.929        19       512: 100% 50/50 [00:33<00:00,  1.50it/s]\n",
            "               Class    Images   Targets         P         R   mAP@0.5        F1: 100% 50/50 [00:06<00:00,  7.64it/s]\n",
            "                 all       500       500     0.978         1     0.995     0.989\n",
            "\n",
            "     Epoch   gpu_mem      GIoU       obj       cls     total   targets  img_size\n",
            "   179/299     11.8G     0.715     0.196         0     0.912        16       512: 100% 50/50 [00:33<00:00,  1.50it/s]\n",
            "               Class    Images   Targets         P         R   mAP@0.5        F1: 100% 50/50 [00:06<00:00,  7.66it/s]\n",
            "                 all       500       500     0.971         1     0.995     0.985\n",
            "\n",
            "     Epoch   gpu_mem      GIoU       obj       cls     total   targets  img_size\n",
            "   180/299     11.8G     0.662     0.178         0     0.839        21       512: 100% 50/50 [00:33<00:00,  1.50it/s]\n",
            "               Class    Images   Targets         P         R   mAP@0.5        F1: 100% 50/50 [00:06<00:00,  7.69it/s]\n",
            "                 all       500       500     0.973         1     0.995     0.986\n",
            "\n",
            "     Epoch   gpu_mem      GIoU       obj       cls     total   targets  img_size\n",
            "   181/299     11.8G     0.723     0.186         0     0.908        20       512: 100% 50/50 [00:33<00:00,  1.50it/s]\n",
            "               Class    Images   Targets         P         R   mAP@0.5        F1: 100% 50/50 [00:06<00:00,  7.64it/s]\n",
            "                 all       500       500     0.983         1     0.995     0.991\n",
            "\n",
            "     Epoch   gpu_mem      GIoU       obj       cls     total   targets  img_size\n",
            "   182/299     11.8G     0.634     0.189         0     0.823        19       512: 100% 50/50 [00:33<00:00,  1.50it/s]\n",
            "               Class    Images   Targets         P         R   mAP@0.5        F1: 100% 50/50 [00:06<00:00,  7.63it/s]\n",
            "                 all       500       500     0.981         1     0.995      0.99\n",
            "\n",
            "     Epoch   gpu_mem      GIoU       obj       cls     total   targets  img_size\n",
            "   183/299     11.8G     0.535     0.188         0     0.722        19       512: 100% 50/50 [00:33<00:00,  1.50it/s]\n",
            "               Class    Images   Targets         P         R   mAP@0.5        F1: 100% 50/50 [00:06<00:00,  7.64it/s]\n",
            "                 all       500       500     0.982         1     0.995     0.991\n",
            "\n",
            "     Epoch   gpu_mem      GIoU       obj       cls     total   targets  img_size\n",
            "   184/299     11.8G     0.597      0.18         0     0.777        20       512: 100% 50/50 [00:33<00:00,  1.50it/s]\n",
            "               Class    Images   Targets         P         R   mAP@0.5        F1: 100% 50/50 [00:06<00:00,  7.65it/s]\n",
            "                 all       500       500     0.987         1     0.995     0.993\n",
            "\n",
            "     Epoch   gpu_mem      GIoU       obj       cls     total   targets  img_size\n",
            "   185/299     11.8G     0.785     0.186         0     0.971        20       512: 100% 50/50 [00:33<00:00,  1.50it/s]\n",
            "               Class    Images   Targets         P         R   mAP@0.5        F1: 100% 50/50 [00:06<00:00,  7.63it/s]\n",
            "                 all       500       500     0.987         1     0.995     0.994\n",
            "\n",
            "     Epoch   gpu_mem      GIoU       obj       cls     total   targets  img_size\n",
            "   186/299     11.8G     0.618     0.193         0     0.812        18       512: 100% 50/50 [00:33<00:00,  1.50it/s]\n",
            "               Class    Images   Targets         P         R   mAP@0.5        F1: 100% 50/50 [00:06<00:00,  7.68it/s]\n",
            "                 all       500       500     0.984         1     0.995     0.992\n",
            "\n",
            "     Epoch   gpu_mem      GIoU       obj       cls     total   targets  img_size\n",
            "   187/299     11.8G     0.554     0.185         0     0.739        23       512: 100% 50/50 [00:33<00:00,  1.50it/s]\n",
            "               Class    Images   Targets         P         R   mAP@0.5        F1: 100% 50/50 [00:06<00:00,  7.66it/s]\n",
            "                 all       500       500     0.982         1     0.995     0.991\n",
            "\n",
            "     Epoch   gpu_mem      GIoU       obj       cls     total   targets  img_size\n",
            "   188/299     11.8G     0.649     0.178         0     0.828        23       512: 100% 50/50 [00:33<00:00,  1.50it/s]\n",
            "               Class    Images   Targets         P         R   mAP@0.5        F1: 100% 50/50 [00:06<00:00,  7.68it/s]\n",
            "                 all       500       500     0.983         1     0.995     0.992\n",
            "\n",
            "     Epoch   gpu_mem      GIoU       obj       cls     total   targets  img_size\n",
            "   189/299     11.8G     0.619     0.185         0     0.805        20       512: 100% 50/50 [00:33<00:00,  1.50it/s]\n",
            "               Class    Images   Targets         P         R   mAP@0.5        F1: 100% 50/50 [00:06<00:00,  7.66it/s]\n",
            "                 all       500       500     0.988         1     0.995     0.994\n",
            "\n",
            "     Epoch   gpu_mem      GIoU       obj       cls     total   targets  img_size\n",
            "   190/299     11.8G     0.625     0.182         0     0.808        19       512: 100% 50/50 [00:33<00:00,  1.50it/s]\n",
            "               Class    Images   Targets         P         R   mAP@0.5        F1: 100% 50/50 [00:06<00:00,  7.69it/s]\n",
            "                 all       500       500     0.987         1     0.995     0.993\n",
            "\n",
            "     Epoch   gpu_mem      GIoU       obj       cls     total   targets  img_size\n",
            "   191/299     11.8G     0.568     0.172         0     0.741        19       512: 100% 50/50 [00:33<00:00,  1.50it/s]\n",
            "               Class    Images   Targets         P         R   mAP@0.5        F1: 100% 50/50 [00:06<00:00,  7.70it/s]\n",
            "                 all       500       500     0.983         1     0.995     0.991\n",
            "\n",
            "     Epoch   gpu_mem      GIoU       obj       cls     total   targets  img_size\n",
            "   192/299     11.8G     0.699     0.186         0     0.885        20       512: 100% 50/50 [00:33<00:00,  1.50it/s]\n",
            "               Class    Images   Targets         P         R   mAP@0.5        F1: 100% 50/50 [00:06<00:00,  7.70it/s]\n",
            "                 all       500       500     0.982         1     0.995     0.991\n",
            "\n",
            "     Epoch   gpu_mem      GIoU       obj       cls     total   targets  img_size\n",
            "   193/299     11.8G     0.576     0.172         0     0.748        19       512: 100% 50/50 [00:33<00:00,  1.50it/s]\n",
            "               Class    Images   Targets         P         R   mAP@0.5        F1: 100% 50/50 [00:06<00:00,  7.66it/s]\n",
            "                 all       500       500     0.983         1     0.995     0.991\n",
            "\n",
            "     Epoch   gpu_mem      GIoU       obj       cls     total   targets  img_size\n",
            "   194/299     11.8G     0.687      0.18         0     0.866        20       512: 100% 50/50 [00:33<00:00,  1.50it/s]\n",
            "               Class    Images   Targets         P         R   mAP@0.5        F1: 100% 50/50 [00:06<00:00,  7.68it/s]\n",
            "                 all       500       500     0.985         1     0.995     0.992\n",
            "\n",
            "     Epoch   gpu_mem      GIoU       obj       cls     total   targets  img_size\n",
            "   195/299     11.8G     0.561     0.189         0      0.75        20       512: 100% 50/50 [00:33<00:00,  1.50it/s]\n",
            "               Class    Images   Targets         P         R   mAP@0.5        F1: 100% 50/50 [00:06<00:00,  7.62it/s]\n",
            "                 all       500       500     0.983         1     0.995     0.991\n",
            "\n",
            "     Epoch   gpu_mem      GIoU       obj       cls     total   targets  img_size\n",
            "   196/299     11.8G     0.611     0.181         0     0.793        25       512: 100% 50/50 [00:33<00:00,  1.50it/s]\n",
            "               Class    Images   Targets         P         R   mAP@0.5        F1: 100% 50/50 [00:06<00:00,  7.66it/s]\n",
            "                 all       500       500     0.979         1     0.995      0.99\n",
            "\n",
            "     Epoch   gpu_mem      GIoU       obj       cls     total   targets  img_size\n",
            "   197/299     11.8G     0.647     0.209         0     0.856        19       512: 100% 50/50 [00:33<00:00,  1.50it/s]\n",
            "               Class    Images   Targets         P         R   mAP@0.5        F1: 100% 50/50 [00:06<00:00,  7.63it/s]\n",
            "                 all       500       500     0.984         1     0.995     0.992\n",
            "\n",
            "     Epoch   gpu_mem      GIoU       obj       cls     total   targets  img_size\n",
            "   198/299     11.8G     0.548      0.18         0     0.728        20       512: 100% 50/50 [00:33<00:00,  1.50it/s]\n",
            "               Class    Images   Targets         P         R   mAP@0.5        F1: 100% 50/50 [00:06<00:00,  7.69it/s]\n",
            "                 all       500       500     0.988         1     0.995     0.994\n",
            "\n",
            "     Epoch   gpu_mem      GIoU       obj       cls     total   targets  img_size\n",
            "   199/299     11.8G     0.582     0.158         0      0.74        15       512: 100% 50/50 [00:33<00:00,  1.50it/s]\n",
            "               Class    Images   Targets         P         R   mAP@0.5        F1: 100% 50/50 [00:06<00:00,  7.67it/s]\n",
            "                 all       500       500     0.986         1     0.995     0.993\n",
            "\n",
            "     Epoch   gpu_mem      GIoU       obj       cls     total   targets  img_size\n",
            "   200/299     11.8G     0.645     0.193         0     0.838        17       512: 100% 50/50 [00:33<00:00,  1.50it/s]\n",
            "               Class    Images   Targets         P         R   mAP@0.5        F1: 100% 50/50 [00:06<00:00,  7.66it/s]\n",
            "                 all       500       500     0.986         1     0.995     0.993\n",
            "\n",
            "     Epoch   gpu_mem      GIoU       obj       cls     total   targets  img_size\n",
            "   201/299     11.8G     0.534     0.167         0     0.701        20       512: 100% 50/50 [00:33<00:00,  1.50it/s]\n",
            "               Class    Images   Targets         P         R   mAP@0.5        F1: 100% 50/50 [00:06<00:00,  7.68it/s]\n",
            "                 all       500       500     0.988         1     0.995     0.994\n",
            "\n",
            "     Epoch   gpu_mem      GIoU       obj       cls     total   targets  img_size\n",
            "   202/299     11.8G       0.5     0.195         0     0.695        17       512: 100% 50/50 [00:33<00:00,  1.50it/s]\n",
            "               Class    Images   Targets         P         R   mAP@0.5        F1: 100% 50/50 [00:06<00:00,  7.66it/s]\n",
            "                 all       500       500     0.989         1     0.995     0.995\n",
            "\n",
            "     Epoch   gpu_mem      GIoU       obj       cls     total   targets  img_size\n",
            "   203/299     11.8G     0.628     0.157         0     0.785        13       512: 100% 50/50 [00:33<00:00,  1.50it/s]\n",
            "               Class    Images   Targets         P         R   mAP@0.5        F1: 100% 50/50 [00:06<00:00,  7.65it/s]\n",
            "                 all       500       500     0.987         1     0.995     0.993\n",
            "\n",
            "     Epoch   gpu_mem      GIoU       obj       cls     total   targets  img_size\n",
            "   204/299     11.8G     0.584     0.175         0     0.758        24       512: 100% 50/50 [00:33<00:00,  1.50it/s]\n",
            "               Class    Images   Targets         P         R   mAP@0.5        F1: 100% 50/50 [00:06<00:00,  7.66it/s]\n",
            "                 all       500       500     0.984         1     0.995     0.992\n",
            "\n",
            "     Epoch   gpu_mem      GIoU       obj       cls     total   targets  img_size\n",
            "   205/299     11.8G     0.585     0.155         0     0.741        20       512: 100% 50/50 [00:33<00:00,  1.50it/s]\n",
            "               Class    Images   Targets         P         R   mAP@0.5        F1: 100% 50/50 [00:06<00:00,  7.66it/s]\n",
            "                 all       500       500     0.982         1     0.995     0.991\n",
            "\n",
            "     Epoch   gpu_mem      GIoU       obj       cls     total   targets  img_size\n",
            "   206/299     11.8G     0.534     0.166         0       0.7        16       512: 100% 50/50 [00:33<00:00,  1.50it/s]\n",
            "               Class    Images   Targets         P         R   mAP@0.5        F1: 100% 50/50 [00:06<00:00,  7.68it/s]\n",
            "                 all       500       500     0.982         1     0.995     0.991\n",
            "\n",
            "     Epoch   gpu_mem      GIoU       obj       cls     total   targets  img_size\n",
            "   207/299     11.8G      0.54     0.161         0     0.702        22       512: 100% 50/50 [00:33<00:00,  1.50it/s]\n",
            "               Class    Images   Targets         P         R   mAP@0.5        F1: 100% 50/50 [00:06<00:00,  7.66it/s]\n",
            "                 all       500       500     0.985         1     0.995     0.992\n",
            "\n",
            "     Epoch   gpu_mem      GIoU       obj       cls     total   targets  img_size\n",
            "   208/299     11.8G     0.541      0.17         0     0.711        20       512: 100% 50/50 [00:33<00:00,  1.50it/s]\n",
            "               Class    Images   Targets         P         R   mAP@0.5        F1: 100% 50/50 [00:06<00:00,  7.68it/s]\n",
            "                 all       500       500     0.985         1     0.995     0.992\n",
            "\n",
            "     Epoch   gpu_mem      GIoU       obj       cls     total   targets  img_size\n",
            "   209/299     11.8G     0.542     0.167         0     0.709        23       512: 100% 50/50 [00:33<00:00,  1.50it/s]\n",
            "               Class    Images   Targets         P         R   mAP@0.5        F1: 100% 50/50 [00:06<00:00,  7.62it/s]\n",
            "                 all       500       500     0.985         1     0.995     0.992\n",
            "\n",
            "     Epoch   gpu_mem      GIoU       obj       cls     total   targets  img_size\n",
            "   210/299     11.8G     0.578     0.154         0     0.732        23       512: 100% 50/50 [00:33<00:00,  1.50it/s]\n",
            "               Class    Images   Targets         P         R   mAP@0.5        F1: 100% 50/50 [00:06<00:00,  7.71it/s]\n",
            "                 all       500       500     0.982         1     0.995     0.991\n",
            "\n",
            "     Epoch   gpu_mem      GIoU       obj       cls     total   targets  img_size\n",
            "   211/299     11.8G     0.583     0.174         0     0.757        22       512: 100% 50/50 [00:33<00:00,  1.50it/s]\n",
            "               Class    Images   Targets         P         R   mAP@0.5        F1: 100% 50/50 [00:06<00:00,  7.66it/s]\n",
            "                 all       500       500     0.982         1     0.995     0.991\n",
            "\n",
            "     Epoch   gpu_mem      GIoU       obj       cls     total   targets  img_size\n",
            "   212/299     11.8G     0.554     0.176         0      0.73        23       512: 100% 50/50 [00:33<00:00,  1.50it/s]\n",
            "               Class    Images   Targets         P         R   mAP@0.5        F1: 100% 50/50 [00:06<00:00,  7.66it/s]\n",
            "                 all       500       500     0.981         1     0.995     0.991\n",
            "\n",
            "     Epoch   gpu_mem      GIoU       obj       cls     total   targets  img_size\n",
            "   213/299     11.8G      0.48     0.152         0     0.632        18       512: 100% 50/50 [00:33<00:00,  1.50it/s]\n",
            "               Class    Images   Targets         P         R   mAP@0.5        F1: 100% 50/50 [00:06<00:00,  7.67it/s]\n",
            "                 all       500       500     0.984         1     0.995     0.992\n",
            "\n",
            "     Epoch   gpu_mem      GIoU       obj       cls     total   targets  img_size\n",
            "   214/299     11.8G     0.503     0.156         0      0.66        21       512: 100% 50/50 [00:33<00:00,  1.50it/s]\n",
            "               Class    Images   Targets         P         R   mAP@0.5        F1: 100% 50/50 [00:06<00:00,  7.71it/s]\n",
            "                 all       500       500     0.984         1     0.995     0.992\n",
            "\n",
            "     Epoch   gpu_mem      GIoU       obj       cls     total   targets  img_size\n",
            "   215/299     11.8G     0.606     0.157         0     0.763        19       512: 100% 50/50 [00:33<00:00,  1.50it/s]\n",
            "               Class    Images   Targets         P         R   mAP@0.5        F1: 100% 50/50 [00:06<00:00,  7.68it/s]\n",
            "                 all       500       500     0.987         1     0.995     0.993\n",
            "\n",
            "     Epoch   gpu_mem      GIoU       obj       cls     total   targets  img_size\n",
            "   216/299     11.8G     0.546     0.145         0     0.692        21       512: 100% 50/50 [00:33<00:00,  1.50it/s]\n",
            "               Class    Images   Targets         P         R   mAP@0.5        F1: 100% 50/50 [00:06<00:00,  7.65it/s]\n",
            "                 all       500       500     0.987         1     0.995     0.993\n",
            "\n",
            "     Epoch   gpu_mem      GIoU       obj       cls     total   targets  img_size\n",
            "   217/299     11.8G     0.668     0.175         0     0.844        21       512: 100% 50/50 [00:33<00:00,  1.50it/s]\n",
            "               Class    Images   Targets         P         R   mAP@0.5        F1: 100% 50/50 [00:06<00:00,  7.65it/s]\n",
            "                 all       500       500     0.985         1     0.995     0.993\n",
            "\n",
            "     Epoch   gpu_mem      GIoU       obj       cls     total   targets  img_size\n",
            "   218/299     11.8G     0.605     0.165         0      0.77        20       512: 100% 50/50 [00:33<00:00,  1.50it/s]\n",
            "               Class    Images   Targets         P         R   mAP@0.5        F1: 100% 50/50 [00:06<00:00,  7.63it/s]\n",
            "                 all       500       500     0.988         1     0.995     0.994\n",
            "\n",
            "     Epoch   gpu_mem      GIoU       obj       cls     total   targets  img_size\n",
            "   219/299     11.8G      0.56     0.156         0     0.715        20       512: 100% 50/50 [00:33<00:00,  1.50it/s]\n",
            "               Class    Images   Targets         P         R   mAP@0.5        F1: 100% 50/50 [00:06<00:00,  7.67it/s]\n",
            "                 all       500       500     0.987         1     0.995     0.994\n",
            "\n",
            "     Epoch   gpu_mem      GIoU       obj       cls     total   targets  img_size\n",
            "   220/299     11.8G     0.594      0.16         0     0.753        18       512: 100% 50/50 [00:33<00:00,  1.50it/s]\n",
            "               Class    Images   Targets         P         R   mAP@0.5        F1: 100% 50/50 [00:06<00:00,  7.67it/s]\n",
            "                 all       500       500     0.989         1     0.995     0.994\n",
            "\n",
            "     Epoch   gpu_mem      GIoU       obj       cls     total   targets  img_size\n",
            "   221/299     11.8G     0.485     0.157         0     0.642        21       512: 100% 50/50 [00:33<00:00,  1.50it/s]\n",
            "               Class    Images   Targets         P         R   mAP@0.5        F1: 100% 50/50 [00:06<00:00,  7.68it/s]\n",
            "                 all       500       500     0.983         1     0.995     0.992\n",
            "\n",
            "     Epoch   gpu_mem      GIoU       obj       cls     total   targets  img_size\n",
            "   222/299     11.8G      0.51     0.157         0     0.667        19       512: 100% 50/50 [00:33<00:00,  1.50it/s]\n",
            "               Class    Images   Targets         P         R   mAP@0.5        F1: 100% 50/50 [00:06<00:00,  7.66it/s]\n",
            "                 all       500       500     0.985         1     0.995     0.992\n",
            "\n",
            "     Epoch   gpu_mem      GIoU       obj       cls     total   targets  img_size\n",
            "   223/299     11.8G     0.463     0.154         0     0.617        22       512: 100% 50/50 [00:33<00:00,  1.50it/s]\n",
            "               Class    Images   Targets         P         R   mAP@0.5        F1: 100% 50/50 [00:06<00:00,  7.64it/s]\n",
            "                 all       500       500     0.986         1     0.995     0.993\n",
            "\n",
            "     Epoch   gpu_mem      GIoU       obj       cls     total   targets  img_size\n",
            "   224/299     11.8G     0.558     0.156         0     0.715        18       512: 100% 50/50 [00:33<00:00,  1.50it/s]\n",
            "               Class    Images   Targets         P         R   mAP@0.5        F1: 100% 50/50 [00:06<00:00,  7.65it/s]\n",
            "                 all       500       500     0.985         1     0.995     0.992\n",
            "\n",
            "     Epoch   gpu_mem      GIoU       obj       cls     total   targets  img_size\n",
            "   225/299     11.8G     0.476     0.155         0     0.631        24       512: 100% 50/50 [00:33<00:00,  1.50it/s]\n",
            "               Class    Images   Targets         P         R   mAP@0.5        F1: 100% 50/50 [00:06<00:00,  7.69it/s]\n",
            "                 all       500       500     0.984         1     0.995     0.992\n",
            "\n",
            "     Epoch   gpu_mem      GIoU       obj       cls     total   targets  img_size\n",
            "   226/299     11.8G     0.464     0.145         0     0.608        22       512: 100% 50/50 [00:33<00:00,  1.50it/s]\n",
            "               Class    Images   Targets         P         R   mAP@0.5        F1: 100% 50/50 [00:06<00:00,  7.69it/s]\n",
            "                 all       500       500     0.985         1     0.995     0.992\n",
            "\n",
            "     Epoch   gpu_mem      GIoU       obj       cls     total   targets  img_size\n",
            "   227/299     11.8G     0.551     0.165         0     0.716        23       512: 100% 50/50 [00:33<00:00,  1.50it/s]\n",
            "               Class    Images   Targets         P         R   mAP@0.5        F1: 100% 50/50 [00:06<00:00,  7.69it/s]\n",
            "                 all       500       500     0.986         1     0.995     0.993\n",
            "\n",
            "     Epoch   gpu_mem      GIoU       obj       cls     total   targets  img_size\n",
            "   228/299     11.8G     0.481      0.15         0      0.63        17       512: 100% 50/50 [00:33<00:00,  1.50it/s]\n",
            "               Class    Images   Targets         P         R   mAP@0.5        F1: 100% 50/50 [00:06<00:00,  7.74it/s]\n",
            "                 all       500       500     0.986         1     0.995     0.993\n",
            "\n",
            "     Epoch   gpu_mem      GIoU       obj       cls     total   targets  img_size\n",
            "   229/299     11.8G     0.497     0.134         0     0.631        20       512: 100% 50/50 [00:33<00:00,  1.50it/s]\n",
            "               Class    Images   Targets         P         R   mAP@0.5        F1: 100% 50/50 [00:06<00:00,  7.62it/s]\n",
            "                 all       500       500     0.983         1     0.995     0.991\n",
            "\n",
            "     Epoch   gpu_mem      GIoU       obj       cls     total   targets  img_size\n",
            "   230/299     11.8G     0.476     0.162         0     0.638        23       512: 100% 50/50 [00:33<00:00,  1.50it/s]\n",
            "               Class    Images   Targets         P         R   mAP@0.5        F1: 100% 50/50 [00:06<00:00,  7.64it/s]\n",
            "                 all       500       500     0.985         1     0.995     0.993\n",
            "\n",
            "     Epoch   gpu_mem      GIoU       obj       cls     total   targets  img_size\n",
            "   231/299     11.8G     0.552     0.145         0     0.697        24       512: 100% 50/50 [00:33<00:00,  1.50it/s]\n",
            "               Class    Images   Targets         P         R   mAP@0.5        F1: 100% 50/50 [00:06<00:00,  7.69it/s]\n",
            "                 all       500       500     0.986         1     0.995     0.993\n",
            "\n",
            "     Epoch   gpu_mem      GIoU       obj       cls     total   targets  img_size\n",
            "   232/299     11.8G     0.564     0.149         0     0.713        20       512: 100% 50/50 [00:33<00:00,  1.50it/s]\n",
            "               Class    Images   Targets         P         R   mAP@0.5        F1: 100% 50/50 [00:06<00:00,  7.69it/s]\n",
            "                 all       500       500     0.987         1     0.995     0.993\n",
            "\n",
            "     Epoch   gpu_mem      GIoU       obj       cls     total   targets  img_size\n",
            "   233/299     11.8G     0.462     0.156         0     0.618        21       512: 100% 50/50 [00:33<00:00,  1.50it/s]\n",
            "               Class    Images   Targets         P         R   mAP@0.5        F1: 100% 50/50 [00:06<00:00,  7.60it/s]\n",
            "                 all       500       500     0.986         1     0.995     0.993\n",
            "\n",
            "     Epoch   gpu_mem      GIoU       obj       cls     total   targets  img_size\n",
            "   234/299     11.8G     0.505     0.158         0     0.662        22       512: 100% 50/50 [00:33<00:00,  1.50it/s]\n",
            "               Class    Images   Targets         P         R   mAP@0.5        F1: 100% 50/50 [00:06<00:00,  7.66it/s]\n",
            "                 all       500       500     0.987         1     0.995     0.993\n",
            "\n",
            "     Epoch   gpu_mem      GIoU       obj       cls     total   targets  img_size\n",
            "   235/299     11.8G     0.537     0.157         0     0.693        21       512: 100% 50/50 [00:33<00:00,  1.50it/s]\n",
            "               Class    Images   Targets         P         R   mAP@0.5        F1: 100% 50/50 [00:06<00:00,  7.59it/s]\n",
            "                 all       500       500     0.986         1     0.995     0.993\n",
            "\n",
            "     Epoch   gpu_mem      GIoU       obj       cls     total   targets  img_size\n",
            "   236/299     11.8G     0.519     0.167         0     0.685        26       512: 100% 50/50 [00:33<00:00,  1.50it/s]\n",
            "               Class    Images   Targets         P         R   mAP@0.5        F1: 100% 50/50 [00:06<00:00,  7.66it/s]\n",
            "                 all       500       500     0.984         1     0.995     0.992\n",
            "\n",
            "     Epoch   gpu_mem      GIoU       obj       cls     total   targets  img_size\n",
            "   237/299     11.8G     0.441      0.14         0     0.582        17       512: 100% 50/50 [00:33<00:00,  1.50it/s]\n",
            "               Class    Images   Targets         P         R   mAP@0.5        F1: 100% 50/50 [00:06<00:00,  7.65it/s]\n",
            "                 all       500       500     0.985         1     0.995     0.992\n",
            "\n",
            "     Epoch   gpu_mem      GIoU       obj       cls     total   targets  img_size\n",
            "   238/299     11.8G     0.552     0.154         0     0.707        23       512: 100% 50/50 [00:33<00:00,  1.50it/s]\n",
            "               Class    Images   Targets         P         R   mAP@0.5        F1: 100% 50/50 [00:06<00:00,  7.68it/s]\n",
            "                 all       500       500     0.983         1     0.995     0.991\n",
            "\n",
            "     Epoch   gpu_mem      GIoU       obj       cls     total   targets  img_size\n",
            "   239/299     11.8G     0.505     0.149         0     0.653        20       512: 100% 50/50 [00:33<00:00,  1.50it/s]\n",
            "               Class    Images   Targets         P         R   mAP@0.5        F1: 100% 50/50 [00:06<00:00,  7.60it/s]\n",
            "                 all       500       500     0.983         1     0.995     0.991\n",
            "\n",
            "     Epoch   gpu_mem      GIoU       obj       cls     total   targets  img_size\n",
            "   240/299     11.8G     0.537     0.139         0     0.676        18       512: 100% 50/50 [00:33<00:00,  1.50it/s]\n",
            "               Class    Images   Targets         P         R   mAP@0.5        F1: 100% 50/50 [00:06<00:00,  7.63it/s]\n",
            "                 all       500       500     0.985         1     0.995     0.992\n",
            "\n",
            "     Epoch   gpu_mem      GIoU       obj       cls     total   targets  img_size\n",
            "   241/299     11.8G     0.427     0.155         0     0.582        20       512: 100% 50/50 [00:33<00:00,  1.50it/s]\n",
            "               Class    Images   Targets         P         R   mAP@0.5        F1: 100% 50/50 [00:06<00:00,  7.64it/s]\n",
            "                 all       500       500     0.986         1     0.995     0.993\n",
            "\n",
            "     Epoch   gpu_mem      GIoU       obj       cls     total   targets  img_size\n",
            "   242/299     11.8G     0.551     0.166         0     0.717        15       512: 100% 50/50 [00:33<00:00,  1.50it/s]\n",
            "               Class    Images   Targets         P         R   mAP@0.5        F1: 100% 50/50 [00:06<00:00,  7.62it/s]\n",
            "                 all       500       500     0.987         1     0.995     0.993\n",
            "\n",
            "     Epoch   gpu_mem      GIoU       obj       cls     total   targets  img_size\n",
            "   243/299     11.8G     0.459     0.138         0     0.597        18       512: 100% 50/50 [00:33<00:00,  1.50it/s]\n",
            "               Class    Images   Targets         P         R   mAP@0.5        F1: 100% 50/50 [00:06<00:00,  7.53it/s]\n",
            "                 all       500       500     0.986         1     0.995     0.993\n",
            "\n",
            "     Epoch   gpu_mem      GIoU       obj       cls     total   targets  img_size\n",
            "   244/299     11.8G     0.475      0.15         0     0.625        15       512: 100% 50/50 [00:33<00:00,  1.50it/s]\n",
            "               Class    Images   Targets         P         R   mAP@0.5        F1: 100% 50/50 [00:06<00:00,  7.66it/s]\n",
            "                 all       500       500     0.986         1     0.995     0.993\n",
            "\n",
            "     Epoch   gpu_mem      GIoU       obj       cls     total   targets  img_size\n",
            "   245/299     11.8G     0.521     0.151         0     0.672        23       512: 100% 50/50 [00:33<00:00,  1.50it/s]\n",
            "               Class    Images   Targets         P         R   mAP@0.5        F1: 100% 50/50 [00:06<00:00,  7.62it/s]\n",
            "                 all       500       500     0.985         1     0.995     0.993\n",
            "\n",
            "     Epoch   gpu_mem      GIoU       obj       cls     total   targets  img_size\n",
            "   246/299     11.8G     0.486     0.144         0      0.63        18       512: 100% 50/50 [00:33<00:00,  1.50it/s]\n",
            "               Class    Images   Targets         P         R   mAP@0.5        F1: 100% 50/50 [00:06<00:00,  7.65it/s]\n",
            "                 all       500       500     0.987         1     0.995     0.993\n",
            "\n",
            "     Epoch   gpu_mem      GIoU       obj       cls     total   targets  img_size\n",
            "   247/299     11.8G     0.448      0.16         0     0.608        22       512: 100% 50/50 [00:33<00:00,  1.50it/s]\n",
            "               Class    Images   Targets         P         R   mAP@0.5        F1: 100% 50/50 [00:06<00:00,  7.66it/s]\n",
            "                 all       500       500     0.987         1     0.995     0.993\n",
            "\n",
            "     Epoch   gpu_mem      GIoU       obj       cls     total   targets  img_size\n",
            "   248/299     11.8G     0.423     0.144         0     0.567        18       512: 100% 50/50 [00:33<00:00,  1.50it/s]\n",
            "               Class    Images   Targets         P         R   mAP@0.5        F1: 100% 50/50 [00:06<00:00,  7.63it/s]\n",
            "                 all       500       500     0.985         1     0.995     0.993\n",
            "\n",
            "     Epoch   gpu_mem      GIoU       obj       cls     total   targets  img_size\n",
            "   249/299     11.8G     0.453     0.138         0     0.591        24       512: 100% 50/50 [00:33<00:00,  1.50it/s]\n",
            "               Class    Images   Targets         P         R   mAP@0.5        F1: 100% 50/50 [00:06<00:00,  7.60it/s]\n",
            "                 all       500       500     0.987         1     0.995     0.994\n",
            "\n",
            "     Epoch   gpu_mem      GIoU       obj       cls     total   targets  img_size\n",
            "   250/299     11.8G     0.489     0.134         0     0.623        19       512: 100% 50/50 [00:33<00:00,  1.50it/s]\n",
            "               Class    Images   Targets         P         R   mAP@0.5        F1: 100% 50/50 [00:06<00:00,  7.66it/s]\n",
            "                 all       500       500     0.987         1     0.995     0.994\n",
            "\n",
            "     Epoch   gpu_mem      GIoU       obj       cls     total   targets  img_size\n",
            "   251/299     11.8G     0.488     0.149         0     0.637        17       512: 100% 50/50 [00:33<00:00,  1.50it/s]\n",
            "               Class    Images   Targets         P         R   mAP@0.5        F1: 100% 50/50 [00:06<00:00,  7.67it/s]\n",
            "                 all       500       500     0.989         1     0.995     0.995\n",
            "\n",
            "     Epoch   gpu_mem      GIoU       obj       cls     total   targets  img_size\n",
            "   252/299     11.8G      0.42     0.133         0     0.553        17       512: 100% 50/50 [00:33<00:00,  1.50it/s]\n",
            "               Class    Images   Targets         P         R   mAP@0.5        F1: 100% 50/50 [00:06<00:00,  7.67it/s]\n",
            "                 all       500       500     0.989         1     0.995     0.994\n",
            "\n",
            "     Epoch   gpu_mem      GIoU       obj       cls     total   targets  img_size\n",
            "   253/299     11.8G      0.42     0.138         0     0.559        20       512: 100% 50/50 [00:33<00:00,  1.50it/s]\n",
            "               Class    Images   Targets         P         R   mAP@0.5        F1: 100% 50/50 [00:06<00:00,  7.61it/s]\n",
            "                 all       500       500     0.989         1     0.995     0.994\n",
            "\n",
            "     Epoch   gpu_mem      GIoU       obj       cls     total   targets  img_size\n",
            "   254/299     11.8G     0.455     0.134         0     0.589        27       512: 100% 50/50 [00:33<00:00,  1.50it/s]\n",
            "               Class    Images   Targets         P         R   mAP@0.5        F1: 100% 50/50 [00:06<00:00,  7.50it/s]\n",
            "                 all       500       500     0.987         1     0.995     0.994\n",
            "\n",
            "     Epoch   gpu_mem      GIoU       obj       cls     total   targets  img_size\n",
            "   255/299     11.8G     0.443     0.133         0     0.576        25       512: 100% 50/50 [00:33<00:00,  1.49it/s]\n",
            "               Class    Images   Targets         P         R   mAP@0.5        F1: 100% 50/50 [00:06<00:00,  7.67it/s]\n",
            "                 all       500       500     0.987         1     0.995     0.994\n",
            "\n",
            "     Epoch   gpu_mem      GIoU       obj       cls     total   targets  img_size\n",
            "   256/299     11.8G     0.399     0.132         0     0.531        18       512: 100% 50/50 [00:33<00:00,  1.50it/s]\n",
            "               Class    Images   Targets         P         R   mAP@0.5        F1: 100% 50/50 [00:06<00:00,  7.66it/s]\n",
            "                 all       500       500     0.987         1     0.995     0.994\n",
            "\n",
            "     Epoch   gpu_mem      GIoU       obj       cls     total   targets  img_size\n",
            "   257/299     11.8G     0.428     0.145         0     0.573        22       512: 100% 50/50 [00:33<00:00,  1.50it/s]\n",
            "               Class    Images   Targets         P         R   mAP@0.5        F1: 100% 50/50 [00:06<00:00,  7.66it/s]\n",
            "                 all       500       500     0.987         1     0.995     0.993\n",
            "\n",
            "     Epoch   gpu_mem      GIoU       obj       cls     total   targets  img_size\n",
            "   258/299     11.8G     0.519     0.161         0     0.679        19       512: 100% 50/50 [00:33<00:00,  1.50it/s]\n",
            "               Class    Images   Targets         P         R   mAP@0.5        F1: 100% 50/50 [00:06<00:00,  7.67it/s]\n",
            "                 all       500       500     0.988         1     0.995     0.994\n",
            "\n",
            "     Epoch   gpu_mem      GIoU       obj       cls     total   targets  img_size\n",
            "   259/299     11.8G     0.372     0.129         0     0.501        23       512: 100% 50/50 [00:33<00:00,  1.50it/s]\n",
            "               Class    Images   Targets         P         R   mAP@0.5        F1: 100% 50/50 [00:06<00:00,  7.57it/s]\n",
            "                 all       500       500     0.988         1     0.995     0.994\n",
            "\n",
            "     Epoch   gpu_mem      GIoU       obj       cls     total   targets  img_size\n",
            "   260/299     11.8G     0.443     0.141         0     0.584        19       512: 100% 50/50 [00:33<00:00,  1.50it/s]\n",
            "               Class    Images   Targets         P         R   mAP@0.5        F1: 100% 50/50 [00:06<00:00,  7.60it/s]\n",
            "                 all       500       500     0.988         1     0.995     0.994\n",
            "\n",
            "     Epoch   gpu_mem      GIoU       obj       cls     total   targets  img_size\n",
            "   261/299     11.8G     0.433     0.146         0     0.579        17       512: 100% 50/50 [00:33<00:00,  1.50it/s]\n",
            "               Class    Images   Targets         P         R   mAP@0.5        F1: 100% 50/50 [00:06<00:00,  7.67it/s]\n",
            "                 all       500       500      0.99         1     0.995     0.995\n",
            "\n",
            "     Epoch   gpu_mem      GIoU       obj       cls     total   targets  img_size\n",
            "   262/299     11.8G     0.454     0.146         0       0.6        19       512: 100% 50/50 [00:33<00:00,  1.50it/s]\n",
            "               Class    Images   Targets         P         R   mAP@0.5        F1: 100% 50/50 [00:06<00:00,  7.64it/s]\n",
            "                 all       500       500     0.989         1     0.995     0.995\n",
            "\n",
            "     Epoch   gpu_mem      GIoU       obj       cls     total   targets  img_size\n",
            "   263/299     11.8G     0.411     0.138         0     0.548        18       512: 100% 50/50 [00:33<00:00,  1.50it/s]\n",
            "               Class    Images   Targets         P         R   mAP@0.5        F1: 100% 50/50 [00:06<00:00,  7.65it/s]\n",
            "                 all       500       500     0.987         1     0.995     0.994\n",
            "\n",
            "     Epoch   gpu_mem      GIoU       obj       cls     total   targets  img_size\n",
            "   264/299     11.8G     0.464     0.129         0     0.593        21       512: 100% 50/50 [00:33<00:00,  1.50it/s]\n",
            "               Class    Images   Targets         P         R   mAP@0.5        F1: 100% 50/50 [00:06<00:00,  7.71it/s]\n",
            "                 all       500       500      0.99         1     0.995     0.995\n",
            "\n",
            "     Epoch   gpu_mem      GIoU       obj       cls     total   targets  img_size\n",
            "   265/299     11.8G      0.43     0.134         0     0.564        16       512: 100% 50/50 [00:33<00:00,  1.50it/s]\n",
            "               Class    Images   Targets         P         R   mAP@0.5        F1: 100% 50/50 [00:06<00:00,  7.66it/s]\n",
            "                 all       500       500     0.988         1     0.995     0.994\n",
            "\n",
            "     Epoch   gpu_mem      GIoU       obj       cls     total   targets  img_size\n",
            "   266/299     11.8G     0.408     0.134         0     0.542        21       512: 100% 50/50 [00:33<00:00,  1.50it/s]\n",
            "               Class    Images   Targets         P         R   mAP@0.5        F1: 100% 50/50 [00:06<00:00,  7.70it/s]\n",
            "                 all       500       500     0.987         1     0.995     0.994\n",
            "\n",
            "     Epoch   gpu_mem      GIoU       obj       cls     total   targets  img_size\n",
            "   267/299     11.8G     0.359     0.127         0     0.486        17       512: 100% 50/50 [00:33<00:00,  1.50it/s]\n",
            "               Class    Images   Targets         P         R   mAP@0.5        F1: 100% 50/50 [00:06<00:00,  7.59it/s]\n",
            "                 all       500       500     0.987         1     0.995     0.993\n",
            "\n",
            "     Epoch   gpu_mem      GIoU       obj       cls     total   targets  img_size\n",
            "   268/299     11.8G     0.452     0.134         0     0.586        23       512: 100% 50/50 [00:33<00:00,  1.49it/s]\n",
            "               Class    Images   Targets         P         R   mAP@0.5        F1: 100% 50/50 [00:06<00:00,  7.68it/s]\n",
            "                 all       500       500     0.987         1     0.995     0.993\n",
            "\n",
            "     Epoch   gpu_mem      GIoU       obj       cls     total   targets  img_size\n",
            "   269/299     11.8G     0.468     0.144         0     0.612        22       512: 100% 50/50 [00:33<00:00,  1.50it/s]\n",
            "               Class    Images   Targets         P         R   mAP@0.5        F1: 100% 50/50 [00:06<00:00,  7.67it/s]\n",
            "                 all       500       500     0.987         1     0.995     0.993\n",
            "\n",
            "     Epoch   gpu_mem      GIoU       obj       cls     total   targets  img_size\n",
            "   270/299     11.8G     0.439     0.142         0     0.582        20       512: 100% 50/50 [00:33<00:00,  1.49it/s]\n",
            "               Class    Images   Targets         P         R   mAP@0.5        F1: 100% 50/50 [00:06<00:00,  7.66it/s]\n",
            "                 all       500       500     0.987         1     0.995     0.993\n",
            "\n",
            "     Epoch   gpu_mem      GIoU       obj       cls     total   targets  img_size\n",
            "   271/299     11.8G     0.464      0.14         0     0.604        24       512: 100% 50/50 [00:33<00:00,  1.50it/s]\n",
            "               Class    Images   Targets         P         R   mAP@0.5        F1: 100% 50/50 [00:06<00:00,  7.67it/s]\n",
            "                 all       500       500     0.989         1     0.995     0.994\n",
            "\n",
            "     Epoch   gpu_mem      GIoU       obj       cls     total   targets  img_size\n",
            "   272/299     11.8G     0.462     0.143         0     0.606        18       512: 100% 50/50 [00:33<00:00,  1.50it/s]\n",
            "               Class    Images   Targets         P         R   mAP@0.5        F1: 100% 50/50 [00:06<00:00,  7.63it/s]\n",
            "                 all       500       500     0.989         1     0.995     0.994\n",
            "\n",
            "     Epoch   gpu_mem      GIoU       obj       cls     total   targets  img_size\n",
            "   273/299     11.8G     0.392     0.122         0     0.513        18       512: 100% 50/50 [00:33<00:00,  1.50it/s]\n",
            "               Class    Images   Targets         P         R   mAP@0.5        F1: 100% 50/50 [00:06<00:00,  7.58it/s]\n",
            "                 all       500       500     0.989         1     0.995     0.995\n",
            "\n",
            "     Epoch   gpu_mem      GIoU       obj       cls     total   targets  img_size\n",
            "   274/299     11.8G     0.428      0.15         0     0.577        21       512: 100% 50/50 [00:33<00:00,  1.50it/s]\n",
            "               Class    Images   Targets         P         R   mAP@0.5        F1: 100% 50/50 [00:06<00:00,  7.61it/s]\n",
            "                 all       500       500     0.987         1     0.995     0.994\n",
            "\n",
            "     Epoch   gpu_mem      GIoU       obj       cls     total   targets  img_size\n",
            "   275/299     11.8G     0.434     0.132         0     0.567        19       512: 100% 50/50 [00:33<00:00,  1.50it/s]\n",
            "               Class    Images   Targets         P         R   mAP@0.5        F1: 100% 50/50 [00:06<00:00,  7.64it/s]\n",
            "                 all       500       500     0.987         1     0.995     0.994\n",
            "\n",
            "     Epoch   gpu_mem      GIoU       obj       cls     total   targets  img_size\n",
            "   276/299     11.8G     0.398     0.121         0     0.519        22       512: 100% 50/50 [00:33<00:00,  1.50it/s]\n",
            "               Class    Images   Targets         P         R   mAP@0.5        F1: 100% 50/50 [00:06<00:00,  7.63it/s]\n",
            "                 all       500       500     0.985         1     0.995     0.993\n",
            "\n",
            "     Epoch   gpu_mem      GIoU       obj       cls     total   targets  img_size\n",
            "   277/299     11.8G     0.429      0.14         0     0.569        19       512: 100% 50/50 [00:33<00:00,  1.50it/s]\n",
            "               Class    Images   Targets         P         R   mAP@0.5        F1: 100% 50/50 [00:06<00:00,  7.62it/s]\n",
            "                 all       500       500     0.987         1     0.995     0.994\n",
            "\n",
            "     Epoch   gpu_mem      GIoU       obj       cls     total   targets  img_size\n",
            "   278/299     11.8G     0.372     0.127         0     0.499        22       512: 100% 50/50 [00:33<00:00,  1.50it/s]\n",
            "               Class    Images   Targets         P         R   mAP@0.5        F1: 100% 50/50 [00:06<00:00,  7.68it/s]\n",
            "                 all       500       500     0.989         1     0.995     0.995\n",
            "\n",
            "     Epoch   gpu_mem      GIoU       obj       cls     total   targets  img_size\n",
            "   279/299     11.8G     0.424     0.135         0      0.56        21       512: 100% 50/50 [00:33<00:00,  1.50it/s]\n",
            "               Class    Images   Targets         P         R   mAP@0.5        F1: 100% 50/50 [00:06<00:00,  7.62it/s]\n",
            "                 all       500       500     0.989         1     0.995     0.995\n",
            "\n",
            "     Epoch   gpu_mem      GIoU       obj       cls     total   targets  img_size\n",
            "   280/299     11.8G      0.39     0.138         0     0.527        19       512: 100% 50/50 [00:33<00:00,  1.50it/s]\n",
            "               Class    Images   Targets         P         R   mAP@0.5        F1: 100% 50/50 [00:06<00:00,  7.65it/s]\n",
            "                 all       500       500     0.987         1     0.995     0.994\n",
            "\n",
            "     Epoch   gpu_mem      GIoU       obj       cls     total   targets  img_size\n",
            "   281/299     11.8G      0.39     0.133         0     0.522        22       512: 100% 50/50 [00:33<00:00,  1.50it/s]\n",
            "               Class    Images   Targets         P         R   mAP@0.5        F1: 100% 50/50 [00:06<00:00,  7.62it/s]\n",
            "                 all       500       500     0.989         1     0.995     0.995\n",
            "\n",
            "     Epoch   gpu_mem      GIoU       obj       cls     total   targets  img_size\n",
            "   282/299     11.8G     0.436     0.124         0      0.56        17       512: 100% 50/50 [00:33<00:00,  1.50it/s]\n",
            "               Class    Images   Targets         P         R   mAP@0.5        F1: 100% 50/50 [00:06<00:00,  7.62it/s]\n",
            "                 all       500       500     0.989         1     0.995     0.995\n",
            "\n",
            "     Epoch   gpu_mem      GIoU       obj       cls     total   targets  img_size\n",
            "   283/299     11.8G     0.363     0.136         0       0.5        21       512: 100% 50/50 [00:33<00:00,  1.50it/s]\n",
            "               Class    Images   Targets         P         R   mAP@0.5        F1: 100% 50/50 [00:06<00:00,  7.60it/s]\n",
            "                 all       500       500     0.989         1     0.995     0.995\n",
            "\n",
            "     Epoch   gpu_mem      GIoU       obj       cls     total   targets  img_size\n",
            "   284/299     11.8G     0.417     0.131         0     0.548        21       512: 100% 50/50 [00:33<00:00,  1.50it/s]\n",
            "               Class    Images   Targets         P         R   mAP@0.5        F1: 100% 50/50 [00:06<00:00,  7.61it/s]\n",
            "                 all       500       500     0.989         1     0.995     0.994\n",
            "\n",
            "     Epoch   gpu_mem      GIoU       obj       cls     total   targets  img_size\n",
            "   285/299     11.8G     0.411     0.132         0     0.543        17       512: 100% 50/50 [00:33<00:00,  1.50it/s]\n",
            "               Class    Images   Targets         P         R   mAP@0.5        F1: 100% 50/50 [00:06<00:00,  7.60it/s]\n",
            "                 all       500       500     0.993         1     0.995     0.996\n",
            "\n",
            "     Epoch   gpu_mem      GIoU       obj       cls     total   targets  img_size\n",
            "   286/299     11.8G     0.421     0.145         0     0.566        25       512: 100% 50/50 [00:33<00:00,  1.50it/s]\n",
            "               Class    Images   Targets         P         R   mAP@0.5        F1: 100% 50/50 [00:06<00:00,  7.61it/s]\n",
            "                 all       500       500     0.989         1     0.995     0.994\n",
            "\n",
            "     Epoch   gpu_mem      GIoU       obj       cls     total   targets  img_size\n",
            "   287/299     11.8G     0.416     0.133         0     0.549        22       512: 100% 50/50 [00:33<00:00,  1.50it/s]\n",
            "               Class    Images   Targets         P         R   mAP@0.5        F1: 100% 50/50 [00:06<00:00,  7.65it/s]\n",
            "                 all       500       500     0.989         1     0.995     0.994\n",
            "\n",
            "     Epoch   gpu_mem      GIoU       obj       cls     total   targets  img_size\n",
            "   288/299     11.8G      0.46     0.134         0     0.594        20       512: 100% 50/50 [00:33<00:00,  1.50it/s]\n",
            "               Class    Images   Targets         P         R   mAP@0.5        F1: 100% 50/50 [00:06<00:00,  7.59it/s]\n",
            "                 all       500       500     0.989         1     0.995     0.994\n",
            "\n",
            "     Epoch   gpu_mem      GIoU       obj       cls     total   targets  img_size\n",
            "   289/299     11.8G     0.469     0.133         0     0.603        25       512: 100% 50/50 [00:33<00:00,  1.50it/s]\n",
            "               Class    Images   Targets         P         R   mAP@0.5        F1: 100% 50/50 [00:06<00:00,  7.63it/s]\n",
            "                 all       500       500     0.989         1     0.995     0.994\n",
            "\n",
            "     Epoch   gpu_mem      GIoU       obj       cls     total   targets  img_size\n",
            "   290/299     11.8G     0.398     0.138         0     0.537        22       512: 100% 50/50 [00:33<00:00,  1.50it/s]\n",
            "               Class    Images   Targets         P         R   mAP@0.5        F1: 100% 50/50 [00:06<00:00,  7.59it/s]\n",
            "                 all       500       500     0.989         1     0.995     0.994\n",
            "\n",
            "     Epoch   gpu_mem      GIoU       obj       cls     total   targets  img_size\n",
            "   291/299     11.8G     0.375     0.125         0       0.5        18       512: 100% 50/50 [00:33<00:00,  1.50it/s]\n",
            "               Class    Images   Targets         P         R   mAP@0.5        F1: 100% 50/50 [00:06<00:00,  7.59it/s]\n",
            "                 all       500       500     0.995         1     0.995     0.997\n",
            "\n",
            "     Epoch   gpu_mem      GIoU       obj       cls     total   targets  img_size\n",
            "   292/299     11.8G     0.385     0.127         0     0.512        20       512: 100% 50/50 [00:33<00:00,  1.50it/s]\n",
            "               Class    Images   Targets         P         R   mAP@0.5        F1: 100% 50/50 [00:06<00:00,  7.65it/s]\n",
            "                 all       500       500     0.989         1     0.995     0.994\n",
            "\n",
            "     Epoch   gpu_mem      GIoU       obj       cls     total   targets  img_size\n",
            "   293/299     11.8G     0.428     0.125         0     0.553        24       512: 100% 50/50 [00:33<00:00,  1.50it/s]\n",
            "               Class    Images   Targets         P         R   mAP@0.5        F1: 100% 50/50 [00:06<00:00,  7.62it/s]\n",
            "                 all       500       500     0.989         1     0.995     0.995\n",
            "\n",
            "     Epoch   gpu_mem      GIoU       obj       cls     total   targets  img_size\n",
            "   294/299     11.8G     0.394     0.131         0     0.524        21       512: 100% 50/50 [00:33<00:00,  1.50it/s]\n",
            "               Class    Images   Targets         P         R   mAP@0.5        F1: 100% 50/50 [00:06<00:00,  7.60it/s]\n",
            "                 all       500       500     0.989         1     0.995     0.995\n",
            "\n",
            "     Epoch   gpu_mem      GIoU       obj       cls     total   targets  img_size\n",
            "   295/299     11.8G     0.405     0.126         0     0.531        20       512: 100% 50/50 [00:33<00:00,  1.50it/s]\n",
            "               Class    Images   Targets         P         R   mAP@0.5        F1: 100% 50/50 [00:06<00:00,  7.53it/s]\n",
            "                 all       500       500     0.989         1     0.995     0.995\n",
            "\n",
            "     Epoch   gpu_mem      GIoU       obj       cls     total   targets  img_size\n",
            "   296/299     11.8G     0.402     0.109         0      0.51        17       512: 100% 50/50 [00:33<00:00,  1.50it/s]\n",
            "               Class    Images   Targets         P         R   mAP@0.5        F1: 100% 50/50 [00:06<00:00,  7.55it/s]\n",
            "                 all       500       500     0.987         1     0.995     0.994\n",
            "\n",
            "     Epoch   gpu_mem      GIoU       obj       cls     total   targets  img_size\n",
            "   297/299     11.8G     0.351     0.127         0     0.478        18       512: 100% 50/50 [00:33<00:00,  1.50it/s]\n",
            "               Class    Images   Targets         P         R   mAP@0.5        F1: 100% 50/50 [00:06<00:00,  7.65it/s]\n",
            "                 all       500       500     0.987         1     0.995     0.994\n",
            "\n",
            "     Epoch   gpu_mem      GIoU       obj       cls     total   targets  img_size\n",
            "   298/299     11.8G       0.4     0.124         0     0.523        20       512: 100% 50/50 [00:33<00:00,  1.50it/s]\n",
            "               Class    Images   Targets         P         R   mAP@0.5        F1: 100% 50/50 [00:06<00:00,  7.58it/s]\n",
            "                 all       500       500     0.989         1     0.995     0.995\n",
            "\n",
            "     Epoch   gpu_mem      GIoU       obj       cls     total   targets  img_size\n",
            "   299/299     11.8G     0.378     0.131         0      0.51        19       512: 100% 50/50 [00:33<00:00,  1.50it/s]\n",
            "               Class    Images   Targets         P         R   mAP@0.5        F1: 100% 50/50 [00:06<00:00,  7.60it/s]\n",
            "                 all       500       500     0.989         1     0.995     0.994\n",
            "300 epochs completed in 3.350 hours.\n",
            "\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "uAQFSGALAhR0",
        "colab_type": "text"
      },
      "source": [
        "## Model Inference"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "31oeHX0u2Vwd",
        "colab_type": "code",
        "outputId": "0a23f231-69ab-40ed-dfe2-654b288a9b31",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 1000
        }
      },
      "source": [
        "!python detect.py --conf-thres 0.1 --output output"
      ],
      "execution_count": 0,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Namespace(agnostic_nms=False, augment=False, cfg='cfg/yolov3-batman.cfg', classes=None, conf_thres=0.1, device='', fourcc='mp4v', half=False, img_size=512, iou_thres=0.6, names='data/batman.names', output='output', save_txt=False, source='data/test', view_img=False, weights='weights/last.pt')\n",
            "Using CUDA device0 _CudaDeviceProperties(name='Tesla K80', total_memory=11441MB)\n",
            "\n",
            "Model Summary: 225 layers, 6.25733e+07 parameters, 6.25733e+07 gradients\n",
            "image 1/1032 data/test/img001.jpg: 256x512 1 batmans, Done. (0.074s)\n",
            "image 2/1032 data/test/img002.jpg: 256x512 1 batmans, Done. (0.072s)\n",
            "image 3/1032 data/test/img003.jpg: 256x512 1 batmans, Done. (0.072s)\n",
            "image 4/1032 data/test/img004.jpg: 256x512 1 batmans, Done. (0.072s)\n",
            "image 5/1032 data/test/img005.jpg: 256x512 1 batmans, Done. (0.073s)\n",
            "image 6/1032 data/test/img006.jpg: 256x512 1 batmans, Done. (0.072s)\n",
            "image 7/1032 data/test/img007.jpg: 256x512 1 batmans, Done. (0.072s)\n",
            "image 8/1032 data/test/img008.jpg: 256x512 1 batmans, Done. (0.073s)\n",
            "image 9/1032 data/test/img009.jpg: 256x512 1 batmans, Done. (0.073s)\n",
            "image 10/1032 data/test/img010.jpg: 256x512 1 batmans, Done. (0.072s)\n",
            "image 11/1032 data/test/img011.jpg: 256x512 1 batmans, Done. (0.073s)\n",
            "image 12/1032 data/test/img012.jpg: 256x512 Done. (0.072s)\n",
            "image 13/1032 data/test/img013.jpg: 256x512 1 batmans, Done. (0.073s)\n",
            "image 14/1032 data/test/img014.jpg: 256x512 1 batmans, Done. (0.073s)\n",
            "image 15/1032 data/test/img015.jpg: 256x512 1 batmans, Done. (0.072s)\n",
            "image 16/1032 data/test/img016.jpg: 256x512 1 batmans, Done. (0.072s)\n",
            "image 17/1032 data/test/img017.jpg: 256x512 1 batmans, Done. (0.073s)\n",
            "image 18/1032 data/test/img018.jpg: 256x512 1 batmans, Done. (0.073s)\n",
            "image 19/1032 data/test/img019.jpg: 256x512 1 batmans, Done. (0.072s)\n",
            "image 20/1032 data/test/img020.jpg: 256x512 1 batmans, Done. (0.072s)\n",
            "image 21/1032 data/test/img021.jpg: 256x512 1 batmans, Done. (0.072s)\n",
            "image 22/1032 data/test/img022.jpg: 256x512 1 batmans, Done. (0.073s)\n",
            "image 23/1032 data/test/img023.jpg: 256x512 1 batmans, Done. (0.073s)\n",
            "image 24/1032 data/test/img024.jpg: 256x512 1 batmans, Done. (0.072s)\n",
            "image 25/1032 data/test/img025.jpg: 256x512 1 batmans, Done. (0.073s)\n",
            "image 26/1032 data/test/img026.jpg: 256x512 1 batmans, Done. (0.072s)\n",
            "image 27/1032 data/test/img027.jpg: 256x512 1 batmans, Done. (0.073s)\n",
            "image 28/1032 data/test/img028.jpg: 256x512 1 batmans, Done. (0.072s)\n",
            "image 29/1032 data/test/img029.jpg: 256x512 1 batmans, Done. (0.072s)\n",
            "image 30/1032 data/test/img030.jpg: 256x512 1 batmans, Done. (0.073s)\n",
            "image 31/1032 data/test/img031.jpg: 256x512 Done. (0.072s)\n",
            "image 32/1032 data/test/img032.jpg: 256x512 Done. (0.072s)\n",
            "image 33/1032 data/test/img033.jpg: 256x512 1 batmans, Done. (0.072s)\n",
            "image 34/1032 data/test/img034.jpg: 256x512 1 batmans, Done. (0.072s)\n",
            "image 35/1032 data/test/img035.jpg: 256x512 1 batmans, Done. (0.072s)\n",
            "image 36/1032 data/test/img036.jpg: 256x512 1 batmans, Done. (0.073s)\n",
            "image 37/1032 data/test/img037.jpg: 256x512 1 batmans, Done. (0.073s)\n",
            "image 38/1032 data/test/img038.jpg: 256x512 1 batmans, Done. (0.072s)\n",
            "image 39/1032 data/test/img039.jpg: 256x512 1 batmans, Done. (0.073s)\n",
            "image 40/1032 data/test/img040.jpg: 256x512 1 batmans, Done. (0.073s)\n",
            "image 41/1032 data/test/img041.jpg: 256x512 1 batmans, Done. (0.073s)\n",
            "image 42/1032 data/test/img042.jpg: 256x512 1 batmans, Done. (0.072s)\n",
            "image 43/1032 data/test/img043.jpg: 256x512 1 batmans, Done. (0.073s)\n",
            "image 44/1032 data/test/img044.jpg: 256x512 1 batmans, Done. (0.073s)\n",
            "image 45/1032 data/test/img045.jpg: 256x512 1 batmans, Done. (0.072s)\n",
            "image 46/1032 data/test/img046.jpg: 256x512 1 batmans, Done. (0.072s)\n",
            "image 47/1032 data/test/img047.jpg: 256x512 1 batmans, Done. (0.073s)\n",
            "image 48/1032 data/test/img048.jpg: 256x512 1 batmans, Done. (0.073s)\n",
            "image 49/1032 data/test/img049.jpg: 256x512 1 batmans, Done. (0.073s)\n",
            "image 50/1032 data/test/img050.jpg: 256x512 1 batmans, Done. (0.072s)\n",
            "image 51/1032 data/test/img051.jpg: 256x512 1 batmans, Done. (0.073s)\n",
            "image 52/1032 data/test/img052.jpg: 256x512 1 batmans, Done. (0.072s)\n",
            "image 53/1032 data/test/img053.jpg: 256x512 1 batmans, Done. (0.073s)\n",
            "image 54/1032 data/test/img054.jpg: 256x512 Done. (0.072s)\n",
            "image 55/1032 data/test/img055.jpg: 256x512 Done. (0.073s)\n",
            "image 56/1032 data/test/img056.jpg: 256x512 1 batmans, Done. (0.073s)\n",
            "image 57/1032 data/test/img057.jpg: 256x512 1 batmans, Done. (0.072s)\n",
            "image 58/1032 data/test/img058.jpg: 256x512 1 batmans, Done. (0.072s)\n",
            "image 59/1032 data/test/img059.jpg: 256x512 1 batmans, Done. (0.073s)\n",
            "image 60/1032 data/test/img060.jpg: 256x512 1 batmans, Done. (0.073s)\n",
            "image 61/1032 data/test/img061.jpg: 256x512 1 batmans, Done. (0.073s)\n",
            "image 62/1032 data/test/img062.jpg: 256x512 1 batmans, Done. (0.072s)\n",
            "image 63/1032 data/test/img063.jpg: 256x512 1 batmans, Done. (0.073s)\n",
            "image 64/1032 data/test/img064.jpg: 256x512 1 batmans, Done. (0.072s)\n",
            "image 65/1032 data/test/img065.jpg: 256x512 1 batmans, Done. (0.073s)\n",
            "image 66/1032 data/test/img066.jpg: 256x512 1 batmans, Done. (0.072s)\n",
            "image 67/1032 data/test/img067.jpg: 256x512 1 batmans, Done. (0.073s)\n",
            "image 68/1032 data/test/img068.jpg: 256x512 1 batmans, Done. (0.073s)\n",
            "image 69/1032 data/test/img069.jpg: 256x512 1 batmans, Done. (0.073s)\n",
            "image 70/1032 data/test/img070.jpg: 256x512 1 batmans, Done. (0.073s)\n",
            "image 71/1032 data/test/img071.jpg: 256x512 1 batmans, Done. (0.073s)\n",
            "image 72/1032 data/test/img072.jpg: 256x512 1 batmans, Done. (0.073s)\n",
            "image 73/1032 data/test/img073.jpg: 256x512 1 batmans, Done. (0.073s)\n",
            "image 74/1032 data/test/img074.jpg: 256x512 1 batmans, Done. (0.072s)\n",
            "image 75/1032 data/test/img075.jpg: 256x512 1 batmans, Done. (0.072s)\n",
            "image 76/1032 data/test/img076.jpg: 256x512 1 batmans, Done. (0.073s)\n",
            "image 77/1032 data/test/img077.jpg: 256x512 1 batmans, Done. (0.072s)\n",
            "image 78/1032 data/test/img078.jpg: 256x512 1 batmans, Done. (0.072s)\n",
            "image 79/1032 data/test/img079.jpg: 256x512 1 batmans, Done. (0.072s)\n",
            "image 80/1032 data/test/img080.jpg: 256x512 1 batmans, Done. (0.073s)\n",
            "image 81/1032 data/test/img081.jpg: 256x512 1 batmans, Done. (0.073s)\n",
            "image 82/1032 data/test/img082.jpg: 256x512 1 batmans, Done. (0.073s)\n",
            "image 83/1032 data/test/img083.jpg: 256x512 1 batmans, Done. (0.073s)\n",
            "image 84/1032 data/test/img084.jpg: 256x512 1 batmans, Done. (0.072s)\n",
            "image 85/1032 data/test/img085.jpg: 256x512 1 batmans, Done. (0.073s)\n",
            "image 86/1032 data/test/img086.jpg: 256x512 1 batmans, Done. (0.072s)\n",
            "image 87/1032 data/test/img087.jpg: 256x512 1 batmans, Done. (0.073s)\n",
            "image 88/1032 data/test/img088.jpg: 256x512 1 batmans, Done. (0.073s)\n",
            "image 89/1032 data/test/img089.jpg: 256x512 1 batmans, Done. (0.073s)\n",
            "image 90/1032 data/test/img090.jpg: 256x512 1 batmans, Done. (0.072s)\n",
            "image 91/1032 data/test/img091.jpg: 256x512 1 batmans, Done. (0.072s)\n",
            "image 92/1032 data/test/img092.jpg: 256x512 1 batmans, Done. (0.073s)\n",
            "image 93/1032 data/test/img093.jpg: 256x512 1 batmans, Done. (0.073s)\n",
            "image 94/1032 data/test/img094.jpg: 256x512 1 batmans, Done. (0.072s)\n",
            "image 95/1032 data/test/img095.jpg: 256x512 1 batmans, Done. (0.072s)\n",
            "image 96/1032 data/test/img096.jpg: 256x512 1 batmans, Done. (0.072s)\n",
            "image 97/1032 data/test/img097.jpg: 256x512 1 batmans, Done. (0.073s)\n",
            "image 98/1032 data/test/img098.jpg: 256x512 1 batmans, Done. (0.072s)\n",
            "image 99/1032 data/test/img099.jpg: 256x512 1 batmans, Done. (0.073s)\n",
            "image 100/1032 data/test/img100.jpg: 256x512 1 batmans, Done. (0.072s)\n",
            "image 101/1032 data/test/img1000.jpg: 256x512 1 batmans, Done. (0.073s)\n",
            "image 102/1032 data/test/img1001.jpg: 256x512 1 batmans, Done. (0.073s)\n",
            "image 103/1032 data/test/img1002.jpg: 256x512 1 batmans, Done. (0.072s)\n",
            "image 104/1032 data/test/img1003.jpg: 256x512 1 batmans, Done. (0.073s)\n",
            "image 105/1032 data/test/img1004.jpg: 256x512 1 batmans, Done. (0.072s)\n",
            "image 106/1032 data/test/img1005.jpg: 256x512 1 batmans, Done. (0.073s)\n",
            "image 107/1032 data/test/img1006.jpg: 256x512 1 batmans, Done. (0.073s)\n",
            "image 108/1032 data/test/img1007.jpg: 256x512 1 batmans, Done. (0.073s)\n",
            "image 109/1032 data/test/img1008.jpg: 256x512 1 batmans, Done. (0.073s)\n",
            "image 110/1032 data/test/img1009.jpg: 256x512 1 batmans, Done. (0.073s)\n",
            "image 111/1032 data/test/img101.jpg: 256x512 1 batmans, Done. (0.073s)\n",
            "image 112/1032 data/test/img1010.jpg: 256x512 1 batmans, Done. (0.073s)\n",
            "image 113/1032 data/test/img1011.jpg: 256x512 1 batmans, Done. (0.073s)\n",
            "image 114/1032 data/test/img1012.jpg: 256x512 1 batmans, Done. (0.073s)\n",
            "image 115/1032 data/test/img1013.jpg: 256x512 1 batmans, Done. (0.072s)\n",
            "image 116/1032 data/test/img1014.jpg: 256x512 1 batmans, Done. (0.073s)\n",
            "image 117/1032 data/test/img1015.jpg: 256x512 1 batmans, Done. (0.073s)\n",
            "image 118/1032 data/test/img1016.jpg: 256x512 1 batmans, Done. (0.073s)\n",
            "image 119/1032 data/test/img1017.jpg: 256x512 1 batmans, Done. (0.073s)\n",
            "image 120/1032 data/test/img1018.jpg: 256x512 1 batmans, Done. (0.072s)\n",
            "image 121/1032 data/test/img1019.jpg: 256x512 1 batmans, Done. (0.073s)\n",
            "image 122/1032 data/test/img102.jpg: 256x512 1 batmans, Done. (0.073s)\n",
            "image 123/1032 data/test/img1020.jpg: 256x512 1 batmans, Done. (0.072s)\n",
            "image 124/1032 data/test/img1021.jpg: 256x512 1 batmans, Done. (0.073s)\n",
            "image 125/1032 data/test/img1022.jpg: 256x512 1 batmans, Done. (0.073s)\n",
            "image 126/1032 data/test/img1023.jpg: 256x512 1 batmans, Done. (0.073s)\n",
            "image 127/1032 data/test/img1024.jpg: 256x512 1 batmans, Done. (0.073s)\n",
            "image 128/1032 data/test/img1025.jpg: 256x512 1 batmans, Done. (0.073s)\n",
            "image 129/1032 data/test/img1026.jpg: 256x512 1 batmans, Done. (0.073s)\n",
            "image 130/1032 data/test/img1027.jpg: 256x512 1 batmans, Done. (0.073s)\n",
            "image 131/1032 data/test/img1028.jpg: 256x512 1 batmans, Done. (0.072s)\n",
            "image 132/1032 data/test/img1029.jpg: 256x512 1 batmans, Done. (0.073s)\n",
            "image 133/1032 data/test/img103.jpg: 256x512 1 batmans, Done. (0.073s)\n",
            "image 134/1032 data/test/img1030.jpg: 256x512 1 batmans, Done. (0.073s)\n",
            "image 135/1032 data/test/img1031.jpg: 256x512 1 batmans, Done. (0.073s)\n",
            "image 136/1032 data/test/img1032.jpg: 256x512 1 batmans, Done. (0.073s)\n",
            "image 137/1032 data/test/img104.jpg: 256x512 1 batmans, Done. (0.073s)\n",
            "image 138/1032 data/test/img105.jpg: 256x512 1 batmans, Done. (0.072s)\n",
            "image 139/1032 data/test/img106.jpg: 256x512 1 batmans, Done. (0.073s)\n",
            "image 140/1032 data/test/img107.jpg: 256x512 1 batmans, Done. (0.073s)\n",
            "image 141/1032 data/test/img108.jpg: 256x512 1 batmans, Done. (0.073s)\n",
            "image 142/1032 data/test/img109.jpg: 256x512 1 batmans, Done. (0.073s)\n",
            "image 143/1032 data/test/img110.jpg: 256x512 1 batmans, Done. (0.073s)\n",
            "image 144/1032 data/test/img111.jpg: 256x512 1 batmans, Done. (0.072s)\n",
            "image 145/1032 data/test/img112.jpg: 256x512 1 batmans, Done. (0.073s)\n",
            "image 146/1032 data/test/img113.jpg: 256x512 1 batmans, Done. (0.073s)\n",
            "image 147/1032 data/test/img114.jpg: 256x512 1 batmans, Done. (0.073s)\n",
            "image 148/1032 data/test/img115.jpg: 256x512 1 batmans, Done. (0.073s)\n",
            "image 149/1032 data/test/img116.jpg: 256x512 1 batmans, Done. (0.073s)\n",
            "image 150/1032 data/test/img117.jpg: 256x512 1 batmans, Done. (0.072s)\n",
            "image 151/1032 data/test/img118.jpg: 256x512 1 batmans, Done. (0.073s)\n",
            "image 152/1032 data/test/img119.jpg: 256x512 1 batmans, Done. (0.073s)\n",
            "image 153/1032 data/test/img120.jpg: 256x512 1 batmans, Done. (0.073s)\n",
            "image 154/1032 data/test/img121.jpg: 256x512 1 batmans, Done. (0.073s)\n",
            "image 155/1032 data/test/img122.jpg: 256x512 1 batmans, Done. (0.073s)\n",
            "image 156/1032 data/test/img123.jpg: 256x512 1 batmans, Done. (0.073s)\n",
            "image 157/1032 data/test/img124.jpg: 256x512 1 batmans, Done. (0.073s)\n",
            "image 158/1032 data/test/img125.jpg: 256x512 1 batmans, Done. (0.073s)\n",
            "image 159/1032 data/test/img126.jpg: 256x512 1 batmans, Done. (0.073s)\n",
            "image 160/1032 data/test/img127.jpg: 256x512 1 batmans, Done. (0.073s)\n",
            "image 161/1032 data/test/img128.jpg: 256x512 1 batmans, Done. (0.073s)\n",
            "image 162/1032 data/test/img129.jpg: 256x512 1 batmans, Done. (0.072s)\n",
            "image 163/1032 data/test/img130.jpg: 256x512 1 batmans, Done. (0.072s)\n",
            "image 164/1032 data/test/img131.jpg: 256x512 1 batmans, Done. (0.072s)\n",
            "image 165/1032 data/test/img132.jpg: 256x512 Done. (0.073s)\n",
            "image 166/1032 data/test/img133.jpg: 256x512 1 batmans, Done. (0.072s)\n",
            "image 167/1032 data/test/img134.jpg: 256x512 1 batmans, Done. (0.072s)\n",
            "image 168/1032 data/test/img135.jpg: 256x512 Done. (0.073s)\n",
            "image 169/1032 data/test/img136.jpg: 256x512 1 batmans, Done. (0.073s)\n",
            "image 170/1032 data/test/img137.jpg: 256x512 1 batmans, Done. (0.073s)\n",
            "image 171/1032 data/test/img138.jpg: 256x512 1 batmans, Done. (0.073s)\n",
            "image 172/1032 data/test/img139.jpg: 256x512 1 batmans, Done. (0.073s)\n",
            "image 173/1032 data/test/img140.jpg: 256x512 1 batmans, Done. (0.073s)\n",
            "image 174/1032 data/test/img141.jpg: 256x512 Done. (0.073s)\n",
            "image 175/1032 data/test/img142.jpg: 256x512 1 batmans, Done. (0.073s)\n",
            "image 176/1032 data/test/img143.jpg: 256x512 Done. (0.073s)\n",
            "image 177/1032 data/test/img144.jpg: 256x512 Done. (0.073s)\n",
            "image 178/1032 data/test/img145.jpg: 256x512 Done. (0.072s)\n",
            "image 179/1032 data/test/img146.jpg: 256x512 Done. (0.073s)\n",
            "image 180/1032 data/test/img147.jpg: 256x512 1 batmans, Done. (0.073s)\n",
            "image 181/1032 data/test/img148.jpg: 256x512 1 batmans, Done. (0.073s)\n",
            "image 182/1032 data/test/img149.jpg: 256x512 1 batmans, Done. (0.072s)\n",
            "image 183/1032 data/test/img150.jpg: 256x512 1 batmans, Done. (0.073s)\n",
            "image 184/1032 data/test/img151.jpg: 256x512 1 batmans, Done. (0.073s)\n",
            "image 185/1032 data/test/img152.jpg: 256x512 1 batmans, Done. (0.073s)\n",
            "image 186/1032 data/test/img153.jpg: 256x512 1 batmans, Done. (0.072s)\n",
            "image 187/1032 data/test/img154.jpg: 256x512 1 batmans, Done. (0.073s)\n",
            "image 188/1032 data/test/img155.jpg: 256x512 1 batmans, Done. (0.073s)\n",
            "image 189/1032 data/test/img156.jpg: 256x512 1 batmans, Done. (0.073s)\n",
            "image 190/1032 data/test/img157.jpg: 256x512 1 batmans, Done. (0.073s)\n",
            "image 191/1032 data/test/img158.jpg: 256x512 1 batmans, Done. (0.073s)\n",
            "image 192/1032 data/test/img159.jpg: 256x512 1 batmans, Done. (0.072s)\n",
            "image 193/1032 data/test/img160.jpg: 256x512 1 batmans, Done. (0.075s)\n",
            "image 194/1032 data/test/img161.jpg: 256x512 1 batmans, Done. (0.072s)\n",
            "image 195/1032 data/test/img162.jpg: 256x512 1 batmans, Done. (0.073s)\n",
            "image 196/1032 data/test/img163.jpg: 256x512 1 batmans, Done. (0.073s)\n",
            "image 197/1032 data/test/img164.jpg: 256x512 1 batmans, Done. (0.073s)\n",
            "image 198/1032 data/test/img165.jpg: 256x512 1 batmans, Done. (0.073s)\n",
            "image 199/1032 data/test/img166.jpg: 256x512 1 batmans, Done. (0.073s)\n",
            "image 200/1032 data/test/img167.jpg: 256x512 1 batmans, Done. (0.073s)\n",
            "image 201/1032 data/test/img168.jpg: 256x512 1 batmans, Done. (0.073s)\n",
            "image 202/1032 data/test/img169.jpg: 256x512 1 batmans, Done. (0.073s)\n",
            "image 203/1032 data/test/img170.jpg: 256x512 1 batmans, Done. (0.073s)\n",
            "image 204/1032 data/test/img171.jpg: 256x512 1 batmans, Done. (0.073s)\n",
            "image 205/1032 data/test/img172.jpg: 256x512 1 batmans, Done. (0.073s)\n",
            "image 206/1032 data/test/img173.jpg: 256x512 1 batmans, Done. (0.072s)\n",
            "image 207/1032 data/test/img174.jpg: 256x512 1 batmans, Done. (0.073s)\n",
            "image 208/1032 data/test/img175.jpg: 256x512 1 batmans, Done. (0.073s)\n",
            "image 209/1032 data/test/img176.jpg: 256x512 1 batmans, Done. (0.073s)\n",
            "image 210/1032 data/test/img177.jpg: 256x512 1 batmans, Done. (0.073s)\n",
            "image 211/1032 data/test/img178.jpg: 256x512 1 batmans, Done. (0.073s)\n",
            "image 212/1032 data/test/img179.jpg: 256x512 1 batmans, Done. (0.073s)\n",
            "image 213/1032 data/test/img180.jpg: 256x512 Done. (0.073s)\n",
            "image 214/1032 data/test/img181.jpg: 256x512 Done. (0.073s)\n",
            "image 215/1032 data/test/img182.jpg: 256x512 Done. (0.072s)\n",
            "image 216/1032 data/test/img183.jpg: 256x512 Done. (0.073s)\n",
            "image 217/1032 data/test/img184.jpg: 256x512 Done. (0.073s)\n",
            "image 218/1032 data/test/img185.jpg: 256x512 Done. (0.073s)\n",
            "image 219/1032 data/test/img186.jpg: 256x512 Done. (0.073s)\n",
            "image 220/1032 data/test/img187.jpg: 256x512 Done. (0.073s)\n",
            "image 221/1032 data/test/img188.jpg: 256x512 Done. (0.073s)\n",
            "image 222/1032 data/test/img189.jpg: 256x512 1 batmans, Done. (0.073s)\n",
            "image 223/1032 data/test/img190.jpg: 256x512 1 batmans, Done. (0.073s)\n",
            "image 224/1032 data/test/img191.jpg: 256x512 1 batmans, Done. (0.073s)\n",
            "image 225/1032 data/test/img192.jpg: 256x512 1 batmans, Done. (0.073s)\n",
            "image 226/1032 data/test/img193.jpg: 256x512 1 batmans, Done. (0.073s)\n",
            "image 227/1032 data/test/img194.jpg: 256x512 1 batmans, Done. (0.073s)\n",
            "image 228/1032 data/test/img195.jpg: 256x512 1 batmans, Done. (0.073s)\n",
            "image 229/1032 data/test/img196.jpg: 256x512 1 batmans, Done. (0.073s)\n",
            "image 230/1032 data/test/img197.jpg: 256x512 1 batmans, Done. (0.073s)\n",
            "image 231/1032 data/test/img198.jpg: 256x512 1 batmans, Done. (0.073s)\n",
            "image 232/1032 data/test/img199.jpg: 256x512 1 batmans, Done. (0.073s)\n",
            "image 233/1032 data/test/img200.jpg: 256x512 1 batmans, Done. (0.073s)\n",
            "image 234/1032 data/test/img201.jpg: 256x512 1 batmans, Done. (0.073s)\n",
            "image 235/1032 data/test/img202.jpg: 256x512 1 batmans, Done. (0.072s)\n",
            "image 236/1032 data/test/img203.jpg: 256x512 1 batmans, Done. (0.073s)\n",
            "image 237/1032 data/test/img204.jpg: 256x512 1 batmans, Done. (0.073s)\n",
            "image 238/1032 data/test/img205.jpg: 256x512 1 batmans, Done. (0.073s)\n",
            "image 239/1032 data/test/img206.jpg: 256x512 1 batmans, Done. (0.073s)\n",
            "image 240/1032 data/test/img207.jpg: 256x512 1 batmans, Done. (0.073s)\n",
            "image 241/1032 data/test/img208.jpg: 256x512 1 batmans, Done. (0.073s)\n",
            "image 242/1032 data/test/img209.jpg: 256x512 1 batmans, Done. (0.073s)\n",
            "image 243/1032 data/test/img210.jpg: 256x512 1 batmans, Done. (0.073s)\n",
            "image 244/1032 data/test/img211.jpg: 256x512 1 batmans, Done. (0.073s)\n",
            "image 245/1032 data/test/img212.jpg: 256x512 Done. (0.073s)\n",
            "image 246/1032 data/test/img213.jpg: 256x512 1 batmans, Done. (0.073s)\n",
            "image 247/1032 data/test/img214.jpg: 256x512 1 batmans, Done. (0.073s)\n",
            "image 248/1032 data/test/img215.jpg: 256x512 1 batmans, Done. (0.073s)\n",
            "image 249/1032 data/test/img216.jpg: 256x512 1 batmans, Done. (0.073s)\n",
            "image 250/1032 data/test/img217.jpg: 256x512 1 batmans, Done. (0.073s)\n",
            "image 251/1032 data/test/img218.jpg: 256x512 Done. (0.073s)\n",
            "image 252/1032 data/test/img219.jpg: 256x512 1 batmans, Done. (0.072s)\n",
            "image 253/1032 data/test/img220.jpg: 256x512 1 batmans, Done. (0.073s)\n",
            "image 254/1032 data/test/img221.jpg: 256x512 1 batmans, Done. (0.073s)\n",
            "image 255/1032 data/test/img222.jpg: 256x512 1 batmans, Done. (0.073s)\n",
            "image 256/1032 data/test/img223.jpg: 256x512 1 batmans, Done. (0.073s)\n",
            "image 257/1032 data/test/img224.jpg: 256x512 1 batmans, Done. (0.074s)\n",
            "image 258/1032 data/test/img225.jpg: 256x512 1 batmans, Done. (0.073s)\n",
            "image 259/1032 data/test/img226.jpg: 256x512 1 batmans, Done. (0.073s)\n",
            "image 260/1032 data/test/img227.jpg: 256x512 1 batmans, Done. (0.072s)\n",
            "image 261/1032 data/test/img228.jpg: 256x512 2 batmans, Done. (0.072s)\n",
            "image 262/1032 data/test/img229.jpg: 256x512 1 batmans, Done. (0.073s)\n",
            "image 263/1032 data/test/img230.jpg: 256x512 1 batmans, Done. (0.073s)\n",
            "image 264/1032 data/test/img231.jpg: 256x512 1 batmans, Done. (0.073s)\n",
            "image 265/1032 data/test/img232.jpg: 256x512 1 batmans, Done. (0.073s)\n",
            "image 266/1032 data/test/img233.jpg: 256x512 1 batmans, Done. (0.073s)\n",
            "image 267/1032 data/test/img234.jpg: 256x512 1 batmans, Done. (0.073s)\n",
            "image 268/1032 data/test/img235.jpg: 256x512 1 batmans, Done. (0.073s)\n",
            "image 269/1032 data/test/img236.jpg: 256x512 1 batmans, Done. (0.073s)\n",
            "image 270/1032 data/test/img237.jpg: 256x512 1 batmans, Done. (0.073s)\n",
            "image 271/1032 data/test/img238.jpg: 256x512 1 batmans, Done. (0.073s)\n",
            "image 272/1032 data/test/img239.jpg: 256x512 1 batmans, Done. (0.073s)\n",
            "image 273/1032 data/test/img240.jpg: 256x512 1 batmans, Done. (0.073s)\n",
            "image 274/1032 data/test/img241.jpg: 256x512 1 batmans, Done. (0.073s)\n",
            "image 275/1032 data/test/img242.jpg: 256x512 1 batmans, Done. (0.073s)\n",
            "image 276/1032 data/test/img243.jpg: 256x512 1 batmans, Done. (0.072s)\n",
            "image 277/1032 data/test/img244.jpg: 256x512 1 batmans, Done. (0.073s)\n",
            "image 278/1032 data/test/img245.jpg: 256x512 1 batmans, Done. (0.073s)\n",
            "image 279/1032 data/test/img246.jpg: 256x512 1 batmans, Done. (0.073s)\n",
            "image 280/1032 data/test/img247.jpg: 256x512 1 batmans, Done. (0.072s)\n",
            "image 281/1032 data/test/img248.jpg: 256x512 1 batmans, Done. (0.073s)\n",
            "image 282/1032 data/test/img249.jpg: 256x512 1 batmans, Done. (0.073s)\n",
            "image 283/1032 data/test/img250.jpg: 256x512 1 batmans, Done. (0.072s)\n",
            "image 284/1032 data/test/img251.jpg: 256x512 1 batmans, Done. (0.073s)\n",
            "image 285/1032 data/test/img252.jpg: 256x512 1 batmans, Done. (0.073s)\n",
            "image 286/1032 data/test/img253.jpg: 256x512 1 batmans, Done. (0.073s)\n",
            "image 287/1032 data/test/img254.jpg: 256x512 1 batmans, Done. (0.073s)\n",
            "image 288/1032 data/test/img255.jpg: 256x512 1 batmans, Done. (0.073s)\n",
            "image 289/1032 data/test/img256.jpg: 256x512 1 batmans, Done. (0.073s)\n",
            "image 290/1032 data/test/img257.jpg: 256x512 1 batmans, Done. (0.073s)\n",
            "image 291/1032 data/test/img258.jpg: 256x512 1 batmans, Done. (0.073s)\n",
            "image 292/1032 data/test/img259.jpg: 256x512 1 batmans, Done. (0.073s)\n",
            "image 293/1032 data/test/img260.jpg: 256x512 1 batmans, Done. (0.073s)\n",
            "image 294/1032 data/test/img261.jpg: 256x512 1 batmans, Done. (0.073s)\n",
            "image 295/1032 data/test/img262.jpg: 256x512 Done. (0.073s)\n",
            "image 296/1032 data/test/img263.jpg: 256x512 Done. (0.073s)\n",
            "image 297/1032 data/test/img264.jpg: 256x512 Done. (0.073s)\n",
            "image 298/1032 data/test/img265.jpg: 256x512 Done. (0.073s)\n",
            "image 299/1032 data/test/img266.jpg: 256x512 Done. (0.073s)\n",
            "image 300/1032 data/test/img267.jpg: 256x512 Done. (0.073s)\n",
            "image 301/1032 data/test/img268.jpg: 256x512 1 batmans, Done. (0.073s)\n",
            "image 302/1032 data/test/img269.jpg: 256x512 Done. (0.073s)\n",
            "image 303/1032 data/test/img270.jpg: 256x512 Done. (0.074s)\n",
            "image 304/1032 data/test/img271.jpg: 256x512 Done. (0.073s)\n",
            "image 305/1032 data/test/img272.jpg: 256x512 Done. (0.073s)\n",
            "image 306/1032 data/test/img273.jpg: 256x512 Done. (0.073s)\n",
            "image 307/1032 data/test/img274.jpg: 256x512 Done. (0.073s)\n",
            "image 308/1032 data/test/img275.jpg: 256x512 1 batmans, Done. (0.072s)\n",
            "image 309/1032 data/test/img276.jpg: 256x512 Done. (0.073s)\n",
            "image 310/1032 data/test/img277.jpg: 256x512 Done. (0.073s)\n",
            "image 311/1032 data/test/img278.jpg: 256x512 1 batmans, Done. (0.073s)\n",
            "image 312/1032 data/test/img279.jpg: 256x512 Done. (0.073s)\n",
            "image 313/1032 data/test/img280.jpg: 256x512 Done. (0.073s)\n",
            "image 314/1032 data/test/img281.jpg: 256x512 2 batmans, Done. (0.073s)\n",
            "image 315/1032 data/test/img282.jpg: 256x512 1 batmans, Done. (0.073s)\n",
            "image 316/1032 data/test/img283.jpg: 256x512 1 batmans, Done. (0.073s)\n",
            "image 317/1032 data/test/img284.jpg: 256x512 1 batmans, Done. (0.073s)\n",
            "image 318/1032 data/test/img285.jpg: 256x512 Done. (0.073s)\n",
            "image 319/1032 data/test/img286.jpg: 256x512 1 batmans, Done. (0.073s)\n",
            "image 320/1032 data/test/img287.jpg: 256x512 1 batmans, Done. (0.073s)\n",
            "image 321/1032 data/test/img288.jpg: 256x512 Done. (0.073s)\n",
            "image 322/1032 data/test/img289.jpg: 256x512 1 batmans, Done. (0.073s)\n",
            "image 323/1032 data/test/img290.jpg: 256x512 1 batmans, Done. (0.073s)\n",
            "image 324/1032 data/test/img291.jpg: 256x512 Done. (0.073s)\n",
            "image 325/1032 data/test/img292.jpg: 256x512 Done. (0.073s)\n",
            "image 326/1032 data/test/img293.jpg: 256x512 Done. (0.073s)\n",
            "image 327/1032 data/test/img294.jpg: 256x512 1 batmans, Done. (0.073s)\n",
            "image 328/1032 data/test/img295.jpg: 256x512 Done. (0.073s)\n",
            "image 329/1032 data/test/img296.jpg: 256x512 Done. (0.073s)\n",
            "image 330/1032 data/test/img297.jpg: 256x512 Done. (0.073s)\n",
            "image 331/1032 data/test/img298.jpg: 256x512 Done. (0.073s)\n",
            "image 332/1032 data/test/img299.jpg: 256x512 Done. (0.073s)\n",
            "image 333/1032 data/test/img300.jpg: 256x512 Done. (0.073s)\n",
            "image 334/1032 data/test/img301.jpg: 256x512 2 batmans, Done. (0.073s)\n",
            "image 335/1032 data/test/img302.jpg: 256x512 2 batmans, Done. (0.073s)\n",
            "image 336/1032 data/test/img303.jpg: 256x512 1 batmans, Done. (0.073s)\n",
            "image 337/1032 data/test/img304.jpg: 256x512 1 batmans, Done. (0.073s)\n",
            "image 338/1032 data/test/img305.jpg: 256x512 Done. (0.073s)\n",
            "image 339/1032 data/test/img306.jpg: 256x512 1 batmans, Done. (0.073s)\n",
            "image 340/1032 data/test/img307.jpg: 256x512 Done. (0.073s)\n",
            "image 341/1032 data/test/img308.jpg: 256x512 Done. (0.073s)\n",
            "image 342/1032 data/test/img309.jpg: 256x512 Done. (0.073s)\n",
            "image 343/1032 data/test/img310.jpg: 256x512 Done. (0.073s)\n",
            "image 344/1032 data/test/img311.jpg: 256x512 1 batmans, Done. (0.073s)\n",
            "image 345/1032 data/test/img312.jpg: 256x512 1 batmans, Done. (0.073s)\n",
            "image 346/1032 data/test/img313.jpg: 256x512 Done. (0.073s)\n",
            "image 347/1032 data/test/img314.jpg: 256x512 1 batmans, Done. (0.073s)\n",
            "image 348/1032 data/test/img315.jpg: 256x512 1 batmans, Done. (0.073s)\n",
            "image 349/1032 data/test/img316.jpg: 256x512 1 batmans, Done. (0.073s)\n",
            "image 350/1032 data/test/img317.jpg: 256x512 1 batmans, Done. (0.073s)\n",
            "image 351/1032 data/test/img318.jpg: 256x512 1 batmans, Done. (0.073s)\n",
            "image 352/1032 data/test/img319.jpg: 256x512 1 batmans, Done. (0.073s)\n",
            "image 353/1032 data/test/img320.jpg: 256x512 1 batmans, Done. (0.073s)\n",
            "image 354/1032 data/test/img321.jpg: 256x512 1 batmans, Done. (0.073s)\n",
            "image 355/1032 data/test/img322.jpg: 256x512 1 batmans, Done. (0.073s)\n",
            "image 356/1032 data/test/img323.jpg: 256x512 1 batmans, Done. (0.073s)\n",
            "image 357/1032 data/test/img324.jpg: 256x512 1 batmans, Done. (0.073s)\n",
            "image 358/1032 data/test/img325.jpg: 256x512 1 batmans, Done. (0.073s)\n",
            "image 359/1032 data/test/img326.jpg: 256x512 1 batmans, Done. (0.073s)\n",
            "image 360/1032 data/test/img327.jpg: 256x512 1 batmans, Done. (0.073s)\n",
            "image 361/1032 data/test/img328.jpg: 256x512 1 batmans, Done. (0.073s)\n",
            "image 362/1032 data/test/img329.jpg: 256x512 1 batmans, Done. (0.073s)\n",
            "image 363/1032 data/test/img330.jpg: 256x512 1 batmans, Done. (0.073s)\n",
            "image 364/1032 data/test/img331.jpg: 256x512 1 batmans, Done. (0.073s)\n",
            "image 365/1032 data/test/img332.jpg: 256x512 1 batmans, Done. (0.073s)\n",
            "image 366/1032 data/test/img333.jpg: 256x512 1 batmans, Done. (0.073s)\n",
            "image 367/1032 data/test/img334.jpg: 256x512 1 batmans, Done. (0.074s)\n",
            "image 368/1032 data/test/img335.jpg: 256x512 1 batmans, Done. (0.073s)\n",
            "image 369/1032 data/test/img336.jpg: 256x512 1 batmans, Done. (0.073s)\n",
            "image 370/1032 data/test/img337.jpg: 256x512 1 batmans, Done. (0.073s)\n",
            "image 371/1032 data/test/img338.jpg: 256x512 1 batmans, Done. (0.073s)\n",
            "image 372/1032 data/test/img339.jpg: 256x512 1 batmans, Done. (0.073s)\n",
            "image 373/1032 data/test/img340.jpg: 256x512 1 batmans, Done. (0.073s)\n",
            "image 374/1032 data/test/img341.jpg: 256x512 1 batmans, Done. (0.073s)\n",
            "image 375/1032 data/test/img342.jpg: 256x512 1 batmans, Done. (0.074s)\n",
            "image 376/1032 data/test/img343.jpg: 256x512 1 batmans, Done. (0.073s)\n",
            "image 377/1032 data/test/img344.jpg: 256x512 1 batmans, Done. (0.073s)\n",
            "image 378/1032 data/test/img345.jpg: 256x512 1 batmans, Done. (0.073s)\n",
            "image 379/1032 data/test/img346.jpg: 256x512 1 batmans, Done. (0.073s)\n",
            "image 380/1032 data/test/img347.jpg: 256x512 1 batmans, Done. (0.073s)\n",
            "image 381/1032 data/test/img348.jpg: 256x512 1 batmans, Done. (0.073s)\n",
            "image 382/1032 data/test/img349.jpg: 256x512 1 batmans, Done. (0.073s)\n",
            "image 383/1032 data/test/img350.jpg: 256x512 1 batmans, Done. (0.072s)\n",
            "image 384/1032 data/test/img351.jpg: 256x512 1 batmans, Done. (0.073s)\n",
            "image 385/1032 data/test/img352.jpg: 256x512 1 batmans, Done. (0.073s)\n",
            "image 386/1032 data/test/img353.jpg: 256x512 1 batmans, Done. (0.073s)\n",
            "image 387/1032 data/test/img354.jpg: 256x512 1 batmans, Done. (0.073s)\n",
            "image 388/1032 data/test/img355.jpg: 256x512 1 batmans, Done. (0.073s)\n",
            "image 389/1032 data/test/img356.jpg: 256x512 1 batmans, Done. (0.073s)\n",
            "image 390/1032 data/test/img357.jpg: 256x512 1 batmans, Done. (0.073s)\n",
            "image 391/1032 data/test/img358.jpg: 256x512 1 batmans, Done. (0.073s)\n",
            "image 392/1032 data/test/img359.jpg: 256x512 Done. (0.073s)\n",
            "image 393/1032 data/test/img360.jpg: 256x512 Done. (0.073s)\n",
            "image 394/1032 data/test/img361.jpg: 256x512 Done. (0.073s)\n",
            "image 395/1032 data/test/img362.jpg: 256x512 Done. (0.073s)\n",
            "image 396/1032 data/test/img363.jpg: 256x512 Done. (0.073s)\n",
            "image 397/1032 data/test/img364.jpg: 256x512 Done. (0.073s)\n",
            "image 398/1032 data/test/img365.jpg: 256x512 Done. (0.073s)\n",
            "image 399/1032 data/test/img366.jpg: 256x512 Done. (0.073s)\n",
            "image 400/1032 data/test/img367.jpg: 256x512 Done. (0.073s)\n",
            "image 401/1032 data/test/img368.jpg: 256x512 Done. (0.073s)\n",
            "image 402/1032 data/test/img369.jpg: 256x512 Done. (0.072s)\n",
            "image 403/1032 data/test/img370.jpg: 256x512 Done. (0.073s)\n",
            "image 404/1032 data/test/img371.jpg: 256x512 Done. (0.073s)\n",
            "image 405/1032 data/test/img372.jpg: 256x512 Done. (0.073s)\n",
            "image 406/1032 data/test/img373.jpg: 256x512 Done. (0.073s)\n",
            "image 407/1032 data/test/img374.jpg: 256x512 Done. (0.073s)\n",
            "image 408/1032 data/test/img375.jpg: 256x512 Done. (0.073s)\n",
            "image 409/1032 data/test/img376.jpg: 256x512 Done. (0.072s)\n",
            "image 410/1032 data/test/img377.jpg: 256x512 Done. (0.072s)\n",
            "image 411/1032 data/test/img378.jpg: 256x512 Done. (0.072s)\n",
            "image 412/1032 data/test/img379.jpg: 256x512 Done. (0.073s)\n",
            "image 413/1032 data/test/img380.jpg: 256x512 Done. (0.073s)\n",
            "image 414/1032 data/test/img381.jpg: 256x512 Done. (0.073s)\n",
            "image 415/1032 data/test/img382.jpg: 256x512 Done. (0.073s)\n",
            "image 416/1032 data/test/img383.jpg: 256x512 Done. (0.073s)\n",
            "image 417/1032 data/test/img384.jpg: 256x512 Done. (0.073s)\n",
            "image 418/1032 data/test/img385.jpg: 256x512 Done. (0.073s)\n",
            "image 419/1032 data/test/img386.jpg: 256x512 Done. (0.073s)\n",
            "image 420/1032 data/test/img387.jpg: 256x512 Done. (0.073s)\n",
            "image 421/1032 data/test/img388.jpg: 256x512 Done. (0.073s)\n",
            "image 422/1032 data/test/img389.jpg: 256x512 Done. (0.073s)\n",
            "image 423/1032 data/test/img390.jpg: 256x512 Done. (0.073s)\n",
            "image 424/1032 data/test/img391.jpg: 256x512 Done. (0.073s)\n",
            "image 425/1032 data/test/img392.jpg: 256x512 Done. (0.073s)\n",
            "image 426/1032 data/test/img393.jpg: 256x512 Done. (0.073s)\n",
            "image 427/1032 data/test/img394.jpg: 256x512 Done. (0.073s)\n",
            "image 428/1032 data/test/img395.jpg: 256x512 Done. (0.073s)\n",
            "image 429/1032 data/test/img396.jpg: 256x512 Done. (0.074s)\n",
            "image 430/1032 data/test/img397.jpg: 256x512 Done. (0.073s)\n",
            "image 431/1032 data/test/img398.jpg: 256x512 Done. (0.073s)\n",
            "image 432/1032 data/test/img399.jpg: 256x512 Done. (0.073s)\n",
            "image 433/1032 data/test/img400.jpg: 256x512 Done. (0.073s)\n",
            "image 434/1032 data/test/img401.jpg: 256x512 Done. (0.073s)\n",
            "image 435/1032 data/test/img402.jpg: 256x512 Done. (0.073s)\n",
            "image 436/1032 data/test/img403.jpg: 256x512 Done. (0.073s)\n",
            "image 437/1032 data/test/img404.jpg: 256x512 Done. (0.073s)\n",
            "image 438/1032 data/test/img405.jpg: 256x512 Done. (0.073s)\n",
            "image 439/1032 data/test/img406.jpg: 256x512 Done. (0.073s)\n",
            "image 440/1032 data/test/img407.jpg: 256x512 Done. (0.073s)\n",
            "image 441/1032 data/test/img408.jpg: 256x512 Done. (0.073s)\n",
            "image 442/1032 data/test/img409.jpg: 256x512 Done. (0.073s)\n",
            "image 443/1032 data/test/img410.jpg: 256x512 Done. (0.073s)\n",
            "image 444/1032 data/test/img411.jpg: 256x512 Done. (0.073s)\n",
            "image 445/1032 data/test/img412.jpg: 256x512 Done. (0.073s)\n",
            "image 446/1032 data/test/img413.jpg: 256x512 Done. (0.073s)\n",
            "image 447/1032 data/test/img414.jpg: 256x512 Done. (0.073s)\n",
            "image 448/1032 data/test/img415.jpg: 256x512 Done. (0.073s)\n",
            "image 449/1032 data/test/img416.jpg: 256x512 Done. (0.073s)\n",
            "image 450/1032 data/test/img417.jpg: 256x512 Done. (0.073s)\n",
            "image 451/1032 data/test/img418.jpg: 256x512 Done. (0.073s)\n",
            "image 452/1032 data/test/img419.jpg: 256x512 Done. (0.073s)\n",
            "image 453/1032 data/test/img420.jpg: 256x512 Done. (0.073s)\n",
            "image 454/1032 data/test/img421.jpg: 256x512 Done. (0.073s)\n",
            "image 455/1032 data/test/img422.jpg: 256x512 Done. (0.073s)\n",
            "image 456/1032 data/test/img423.jpg: 256x512 Done. (0.073s)\n",
            "image 457/1032 data/test/img424.jpg: 256x512 Done. (0.073s)\n",
            "image 458/1032 data/test/img425.jpg: 256x512 Done. (0.073s)\n",
            "image 459/1032 data/test/img426.jpg: 256x512 Done. (0.073s)\n",
            "image 460/1032 data/test/img427.jpg: 256x512 Done. (0.073s)\n",
            "image 461/1032 data/test/img428.jpg: 256x512 Done. (0.073s)\n",
            "image 462/1032 data/test/img429.jpg: 256x512 Done. (0.073s)\n",
            "image 463/1032 data/test/img430.jpg: 256x512 Done. (0.073s)\n",
            "image 464/1032 data/test/img431.jpg: 256x512 Done. (0.073s)\n",
            "image 465/1032 data/test/img432.jpg: 256x512 Done. (0.073s)\n",
            "image 466/1032 data/test/img433.jpg: 256x512 Done. (0.073s)\n",
            "image 467/1032 data/test/img434.jpg: 256x512 Done. (0.073s)\n",
            "image 468/1032 data/test/img435.jpg: 256x512 Done. (0.073s)\n",
            "image 469/1032 data/test/img436.jpg: 256x512 Done. (0.073s)\n",
            "image 470/1032 data/test/img437.jpg: 256x512 Done. (0.073s)\n",
            "image 471/1032 data/test/img438.jpg: 256x512 Done. (0.073s)\n",
            "image 472/1032 data/test/img439.jpg: 256x512 Done. (0.073s)\n",
            "image 473/1032 data/test/img440.jpg: 256x512 Done. (0.073s)\n",
            "image 474/1032 data/test/img441.jpg: 256x512 Done. (0.073s)\n",
            "image 475/1032 data/test/img442.jpg: 256x512 Done. (0.073s)\n",
            "image 476/1032 data/test/img443.jpg: 256x512 Done. (0.073s)\n",
            "image 477/1032 data/test/img444.jpg: 256x512 Done. (0.073s)\n",
            "image 478/1032 data/test/img445.jpg: 256x512 Done. (0.073s)\n",
            "image 479/1032 data/test/img446.jpg: 256x512 Done. (0.073s)\n",
            "image 480/1032 data/test/img447.jpg: 256x512 1 batmans, Done. (0.073s)\n",
            "image 481/1032 data/test/img448.jpg: 256x512 1 batmans, Done. (0.073s)\n",
            "image 482/1032 data/test/img449.jpg: 256x512 1 batmans, Done. (0.072s)\n",
            "image 483/1032 data/test/img450.jpg: 256x512 1 batmans, Done. (0.073s)\n",
            "image 484/1032 data/test/img451.jpg: 256x512 1 batmans, Done. (0.073s)\n",
            "image 485/1032 data/test/img452.jpg: 256x512 1 batmans, Done. (0.073s)\n",
            "image 486/1032 data/test/img453.jpg: 256x512 1 batmans, Done. (0.073s)\n",
            "image 487/1032 data/test/img454.jpg: 256x512 1 batmans, Done. (0.073s)\n",
            "image 488/1032 data/test/img455.jpg: 256x512 Done. (0.074s)\n",
            "image 489/1032 data/test/img456.jpg: 256x512 Done. (0.073s)\n",
            "image 490/1032 data/test/img457.jpg: 256x512 Done. (0.072s)\n",
            "image 491/1032 data/test/img458.jpg: 256x512 Done. (0.073s)\n",
            "image 492/1032 data/test/img459.jpg: 256x512 Done. (0.073s)\n",
            "image 493/1032 data/test/img460.jpg: 256x512 Done. (0.073s)\n",
            "image 494/1032 data/test/img461.jpg: 256x512 Done. (0.073s)\n",
            "image 495/1032 data/test/img462.jpg: 256x512 Done. (0.073s)\n",
            "image 496/1032 data/test/img463.jpg: 256x512 Done. (0.074s)\n",
            "image 497/1032 data/test/img464.jpg: 256x512 Done. (0.073s)\n",
            "image 498/1032 data/test/img465.jpg: 256x512 Done. (0.073s)\n",
            "image 499/1032 data/test/img466.jpg: 256x512 Done. (0.073s)\n",
            "image 500/1032 data/test/img467.jpg: 256x512 Done. (0.074s)\n",
            "image 501/1032 data/test/img468.jpg: 256x512 Done. (0.073s)\n",
            "image 502/1032 data/test/img469.jpg: 256x512 Done. (0.073s)\n",
            "image 503/1032 data/test/img470.jpg: 256x512 Done. (0.073s)\n",
            "image 504/1032 data/test/img471.jpg: 256x512 Done. (0.073s)\n",
            "image 505/1032 data/test/img472.jpg: 256x512 Done. (0.073s)\n",
            "image 506/1032 data/test/img473.jpg: 256x512 Done. (0.073s)\n",
            "image 507/1032 data/test/img474.jpg: 256x512 Done. (0.073s)\n",
            "image 508/1032 data/test/img475.jpg: 256x512 Done. (0.073s)\n",
            "image 509/1032 data/test/img476.jpg: 256x512 Done. (0.073s)\n",
            "image 510/1032 data/test/img477.jpg: 256x512 Done. (0.073s)\n",
            "image 511/1032 data/test/img478.jpg: 256x512 Done. (0.073s)\n",
            "image 512/1032 data/test/img479.jpg: 256x512 Done. (0.073s)\n",
            "image 513/1032 data/test/img480.jpg: 256x512 Done. (0.073s)\n",
            "image 514/1032 data/test/img481.jpg: 256x512 Done. (0.073s)\n",
            "image 515/1032 data/test/img482.jpg: 256x512 Done. (0.074s)\n",
            "image 516/1032 data/test/img483.jpg: 256x512 Done. (0.073s)\n",
            "image 517/1032 data/test/img484.jpg: 256x512 Done. (0.073s)\n",
            "image 518/1032 data/test/img485.jpg: 256x512 Done. (0.073s)\n",
            "image 519/1032 data/test/img486.jpg: 256x512 Done. (0.073s)\n",
            "image 520/1032 data/test/img487.jpg: 256x512 Done. (0.074s)\n",
            "image 521/1032 data/test/img488.jpg: 256x512 Done. (0.073s)\n",
            "image 522/1032 data/test/img489.jpg: 256x512 Done. (0.073s)\n",
            "image 523/1032 data/test/img490.jpg: 256x512 Done. (0.073s)\n",
            "image 524/1032 data/test/img491.jpg: 256x512 Done. (0.073s)\n",
            "image 525/1032 data/test/img492.jpg: 256x512 Done. (0.073s)\n",
            "image 526/1032 data/test/img493.jpg: 256x512 Done. (0.073s)\n",
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            "image 529/1032 data/test/img496.jpg: 256x512 Done. (0.073s)\n",
            "image 530/1032 data/test/img497.jpg: 256x512 Done. (0.073s)\n",
            "image 531/1032 data/test/img498.jpg: 256x512 Done. (0.073s)\n",
            "image 532/1032 data/test/img499.jpg: 256x512 Done. (0.073s)\n",
            "image 533/1032 data/test/img500.jpg: 256x512 Done. (0.073s)\n",
            "image 534/1032 data/test/img501.jpg: 256x512 Done. (0.073s)\n",
            "image 535/1032 data/test/img502.jpg: 256x512 Done. (0.073s)\n",
            "image 536/1032 data/test/img503.jpg: 256x512 Done. (0.073s)\n",
            "image 537/1032 data/test/img504.jpg: 256x512 Done. (0.073s)\n",
            "image 538/1032 data/test/img505.jpg: 256x512 Done. (0.073s)\n",
            "image 539/1032 data/test/img506.jpg: 256x512 Done. (0.073s)\n",
            "image 540/1032 data/test/img507.jpg: 256x512 Done. (0.073s)\n",
            "image 541/1032 data/test/img508.jpg: 256x512 Done. (0.073s)\n",
            "image 542/1032 data/test/img509.jpg: 256x512 Done. (0.073s)\n",
            "image 543/1032 data/test/img510.jpg: 256x512 Done. (0.073s)\n",
            "image 544/1032 data/test/img511.jpg: 256x512 Done. (0.073s)\n",
            "image 545/1032 data/test/img512.jpg: 256x512 Done. (0.073s)\n",
            "image 546/1032 data/test/img513.jpg: 256x512 Done. (0.073s)\n",
            "image 547/1032 data/test/img514.jpg: 256x512 Done. (0.073s)\n",
            "image 548/1032 data/test/img515.jpg: 256x512 Done. (0.073s)\n",
            "image 549/1032 data/test/img516.jpg: 256x512 Done. (0.073s)\n",
            "image 550/1032 data/test/img517.jpg: 256x512 Done. (0.073s)\n",
            "image 551/1032 data/test/img518.jpg: 256x512 Done. (0.073s)\n",
            "image 552/1032 data/test/img519.jpg: 256x512 Done. (0.073s)\n",
            "image 553/1032 data/test/img520.jpg: 256x512 Done. (0.073s)\n",
            "image 554/1032 data/test/img521.jpg: 256x512 Done. (0.073s)\n",
            "image 555/1032 data/test/img522.jpg: 256x512 Done. (0.073s)\n",
            "image 556/1032 data/test/img523.jpg: 256x512 Done. (0.073s)\n",
            "image 557/1032 data/test/img524.jpg: 256x512 Done. (0.073s)\n",
            "image 558/1032 data/test/img525.jpg: 256x512 Done. (0.073s)\n",
            "image 559/1032 data/test/img526.jpg: 256x512 Done. (0.073s)\n",
            "image 560/1032 data/test/img527.jpg: 256x512 Done. (0.073s)\n",
            "image 561/1032 data/test/img528.jpg: 256x512 Done. (0.073s)\n",
            "image 562/1032 data/test/img529.jpg: 256x512 Done. (0.073s)\n",
            "image 563/1032 data/test/img530.jpg: 256x512 Done. (0.073s)\n",
            "image 564/1032 data/test/img531.jpg: 256x512 Done. (0.073s)\n",
            "image 565/1032 data/test/img532.jpg: 256x512 Done. (0.073s)\n",
            "image 566/1032 data/test/img533.jpg: 256x512 Done. (0.073s)\n",
            "image 567/1032 data/test/img534.jpg: 256x512 Done. (0.073s)\n",
            "image 568/1032 data/test/img535.jpg: 256x512 Done. (0.074s)\n",
            "image 569/1032 data/test/img536.jpg: 256x512 Done. (0.074s)\n",
            "image 570/1032 data/test/img537.jpg: 256x512 Done. (0.073s)\n",
            "image 571/1032 data/test/img538.jpg: 256x512 Done. (0.073s)\n",
            "image 572/1032 data/test/img539.jpg: 256x512 Done. (0.073s)\n",
            "image 573/1032 data/test/img540.jpg: 256x512 Done. (0.073s)\n",
            "image 574/1032 data/test/img541.jpg: 256x512 Done. (0.073s)\n",
            "image 575/1032 data/test/img542.jpg: 256x512 Done. (0.073s)\n",
            "image 576/1032 data/test/img543.jpg: 256x512 Done. (0.074s)\n",
            "image 577/1032 data/test/img544.jpg: 256x512 Done. (0.073s)\n",
            "image 578/1032 data/test/img545.jpg: 256x512 Done. (0.073s)\n",
            "image 579/1032 data/test/img546.jpg: 256x512 Done. (0.072s)\n",
            "image 580/1032 data/test/img547.jpg: 256x512 Done. (0.073s)\n",
            "image 581/1032 data/test/img548.jpg: 256x512 Done. (0.073s)\n",
            "image 582/1032 data/test/img549.jpg: 256x512 Done. (0.073s)\n",
            "image 583/1032 data/test/img550.jpg: 256x512 Done. (0.073s)\n",
            "image 584/1032 data/test/img551.jpg: 256x512 Done. (0.073s)\n",
            "image 585/1032 data/test/img552.jpg: 256x512 Done. (0.073s)\n",
            "image 586/1032 data/test/img553.jpg: 256x512 Done. (0.073s)\n",
            "image 587/1032 data/test/img554.jpg: 256x512 Done. (0.073s)\n",
            "image 588/1032 data/test/img555.jpg: 256x512 Done. (0.073s)\n",
            "image 589/1032 data/test/img556.jpg: 256x512 Done. (0.073s)\n",
            "image 590/1032 data/test/img557.jpg: 256x512 Done. (0.073s)\n",
            "image 591/1032 data/test/img558.jpg: 256x512 Done. (0.073s)\n",
            "image 592/1032 data/test/img559.jpg: 256x512 Done. (0.073s)\n",
            "image 593/1032 data/test/img560.jpg: 256x512 Done. (0.073s)\n",
            "image 594/1032 data/test/img561.jpg: 256x512 Done. (0.073s)\n",
            "image 595/1032 data/test/img562.jpg: 256x512 Done. (0.073s)\n",
            "image 596/1032 data/test/img563.jpg: 256x512 1 batmans, Done. (0.073s)\n",
            "image 597/1032 data/test/img564.jpg: 256x512 1 batmans, Done. (0.073s)\n",
            "image 598/1032 data/test/img565.jpg: 256x512 Done. (0.073s)\n",
            "image 599/1032 data/test/img566.jpg: 256x512 Done. (0.073s)\n",
            "image 600/1032 data/test/img567.jpg: 256x512 1 batmans, Done. (0.073s)\n",
            "image 601/1032 data/test/img568.jpg: 256x512 Done. (0.073s)\n",
            "image 602/1032 data/test/img569.jpg: 256x512 1 batmans, Done. (0.073s)\n",
            "image 603/1032 data/test/img570.jpg: 256x512 2 batmans, Done. (0.073s)\n",
            "image 604/1032 data/test/img571.jpg: 256x512 1 batmans, Done. (0.073s)\n",
            "image 605/1032 data/test/img572.jpg: 256x512 Done. (0.073s)\n",
            "image 606/1032 data/test/img573.jpg: 256x512 Done. (0.073s)\n",
            "image 607/1032 data/test/img574.jpg: 256x512 Done. (0.073s)\n",
            "image 608/1032 data/test/img575.jpg: 256x512 1 batmans, Done. (0.073s)\n",
            "image 609/1032 data/test/img576.jpg: 256x512 1 batmans, Done. (0.073s)\n",
            "image 610/1032 data/test/img577.jpg: 256x512 1 batmans, Done. (0.073s)\n",
            "image 611/1032 data/test/img578.jpg: 256x512 1 batmans, Done. (0.073s)\n",
            "image 612/1032 data/test/img579.jpg: 256x512 1 batmans, Done. (0.073s)\n",
            "image 613/1032 data/test/img580.jpg: 256x512 1 batmans, Done. (0.073s)\n",
            "image 614/1032 data/test/img581.jpg: 256x512 Done. (0.073s)\n",
            "image 615/1032 data/test/img582.jpg: 256x512 Done. (0.073s)\n",
            "image 616/1032 data/test/img583.jpg: 256x512 Done. (0.073s)\n",
            "image 617/1032 data/test/img584.jpg: 256x512 1 batmans, Done. (0.073s)\n",
            "image 618/1032 data/test/img585.jpg: 256x512 1 batmans, Done. (0.073s)\n",
            "image 619/1032 data/test/img586.jpg: 256x512 1 batmans, Done. (0.073s)\n",
            "image 620/1032 data/test/img587.jpg: 256x512 1 batmans, Done. (0.073s)\n",
            "image 621/1032 data/test/img588.jpg: 256x512 Done. (0.073s)\n",
            "image 622/1032 data/test/img589.jpg: 256x512 Done. (0.073s)\n",
            "image 623/1032 data/test/img590.jpg: 256x512 Done. (0.073s)\n",
            "image 624/1032 data/test/img591.jpg: 256x512 Done. (0.073s)\n",
            "image 625/1032 data/test/img592.jpg: 256x512 Done. (0.073s)\n",
            "image 626/1032 data/test/img593.jpg: 256x512 Done. (0.073s)\n",
            "image 627/1032 data/test/img594.jpg: 256x512 Done. (0.073s)\n",
            "image 628/1032 data/test/img595.jpg: 256x512 Done. (0.073s)\n",
            "image 629/1032 data/test/img596.jpg: 256x512 1 batmans, Done. (0.073s)\n",
            "image 630/1032 data/test/img597.jpg: 256x512 Done. (0.073s)\n",
            "image 631/1032 data/test/img598.jpg: 256x512 Done. (0.073s)\n",
            "image 632/1032 data/test/img599.jpg: 256x512 1 batmans, Done. (0.073s)\n",
            "image 633/1032 data/test/img600.jpg: 256x512 1 batmans, Done. (0.073s)\n",
            "image 634/1032 data/test/img601.jpg: 256x512 1 batmans, Done. (0.073s)\n",
            "image 635/1032 data/test/img602.jpg: 256x512 Done. (0.073s)\n",
            "image 636/1032 data/test/img603.jpg: 256x512 Done. (0.073s)\n",
            "image 637/1032 data/test/img604.jpg: 256x512 1 batmans, Done. (0.073s)\n",
            "image 638/1032 data/test/img605.jpg: 256x512 Done. (0.073s)\n",
            "image 639/1032 data/test/img606.jpg: 256x512 1 batmans, Done. (0.073s)\n",
            "image 640/1032 data/test/img607.jpg: 256x512 1 batmans, Done. (0.073s)\n",
            "image 641/1032 data/test/img608.jpg: 256x512 1 batmans, Done. (0.073s)\n",
            "image 642/1032 data/test/img609.jpg: 256x512 Done. (0.073s)\n",
            "image 643/1032 data/test/img610.jpg: 256x512 1 batmans, Done. (0.073s)\n",
            "image 644/1032 data/test/img611.jpg: 256x512 2 batmans, Done. (0.073s)\n",
            "image 645/1032 data/test/img612.jpg: 256x512 2 batmans, Done. (0.073s)\n",
            "image 646/1032 data/test/img613.jpg: 256x512 1 batmans, Done. (0.072s)\n",
            "image 647/1032 data/test/img614.jpg: 256x512 1 batmans, Done. (0.073s)\n",
            "image 648/1032 data/test/img615.jpg: 256x512 1 batmans, Done. (0.074s)\n",
            "image 649/1032 data/test/img616.jpg: 256x512 1 batmans, Done. (0.073s)\n",
            "image 650/1032 data/test/img617.jpg: 256x512 1 batmans, Done. (0.073s)\n",
            "image 651/1032 data/test/img618.jpg: 256x512 1 batmans, Done. (0.073s)\n",
            "image 652/1032 data/test/img619.jpg: 256x512 1 batmans, Done. (0.074s)\n",
            "image 653/1032 data/test/img620.jpg: 256x512 1 batmans, Done. (0.073s)\n",
            "image 654/1032 data/test/img621.jpg: 256x512 1 batmans, Done. (0.073s)\n",
            "image 655/1032 data/test/img622.jpg: 256x512 1 batmans, Done. (0.073s)\n",
            "image 656/1032 data/test/img623.jpg: 256x512 1 batmans, Done. (0.073s)\n",
            "image 657/1032 data/test/img624.jpg: 256x512 1 batmans, Done. (0.073s)\n",
            "image 658/1032 data/test/img625.jpg: 256x512 1 batmans, Done. (0.073s)\n",
            "image 659/1032 data/test/img626.jpg: 256x512 1 batmans, Done. (0.073s)\n",
            "image 660/1032 data/test/img627.jpg: 256x512 1 batmans, Done. (0.073s)\n",
            "image 661/1032 data/test/img628.jpg: 256x512 1 batmans, Done. (0.072s)\n",
            "image 662/1032 data/test/img629.jpg: 256x512 1 batmans, Done. (0.073s)\n",
            "image 663/1032 data/test/img630.jpg: 256x512 1 batmans, Done. (0.073s)\n",
            "image 664/1032 data/test/img631.jpg: 256x512 1 batmans, Done. (0.073s)\n",
            "image 665/1032 data/test/img632.jpg: 256x512 2 batmans, Done. (0.073s)\n",
            "image 666/1032 data/test/img633.jpg: 256x512 1 batmans, Done. (0.073s)\n",
            "image 667/1032 data/test/img634.jpg: 256x512 1 batmans, Done. (0.073s)\n",
            "image 668/1032 data/test/img635.jpg: 256x512 1 batmans, Done. (0.073s)\n",
            "image 669/1032 data/test/img636.jpg: 256x512 Done. (0.073s)\n",
            "image 670/1032 data/test/img637.jpg: 256x512 1 batmans, Done. (0.073s)\n",
            "image 671/1032 data/test/img638.jpg: 256x512 1 batmans, Done. (0.073s)\n",
            "image 672/1032 data/test/img639.jpg: 256x512 1 batmans, Done. (0.073s)\n",
            "image 673/1032 data/test/img640.jpg: 256x512 1 batmans, Done. (0.073s)\n",
            "image 674/1032 data/test/img641.jpg: 256x512 Done. (0.073s)\n",
            "image 675/1032 data/test/img642.jpg: 256x512 1 batmans, Done. (0.073s)\n",
            "image 676/1032 data/test/img643.jpg: 256x512 Done. (0.073s)\n",
            "image 677/1032 data/test/img644.jpg: 256x512 Done. (0.073s)\n",
            "image 678/1032 data/test/img645.jpg: 256x512 Done. (0.073s)\n",
            "image 679/1032 data/test/img646.jpg: 256x512 Done. (0.073s)\n",
            "image 680/1032 data/test/img647.jpg: 256x512 Done. (0.073s)\n",
            "image 681/1032 data/test/img648.jpg: 256x512 Done. (0.073s)\n",
            "image 682/1032 data/test/img649.jpg: 256x512 Done. (0.073s)\n",
            "image 683/1032 data/test/img650.jpg: 256x512 Done. (0.073s)\n",
            "image 684/1032 data/test/img651.jpg: 256x512 Done. (0.073s)\n",
            "image 685/1032 data/test/img652.jpg: 256x512 Done. (0.073s)\n",
            "image 686/1032 data/test/img653.jpg: 256x512 Done. (0.073s)\n",
            "image 687/1032 data/test/img654.jpg: 256x512 Done. (0.073s)\n",
            "image 688/1032 data/test/img655.jpg: 256x512 Done. (0.073s)\n",
            "image 689/1032 data/test/img656.jpg: 256x512 Done. (0.073s)\n",
            "image 690/1032 data/test/img657.jpg: 256x512 Done. (0.073s)\n",
            "image 691/1032 data/test/img658.jpg: 256x512 Done. (0.073s)\n",
            "image 692/1032 data/test/img659.jpg: 256x512 Done. (0.073s)\n",
            "image 693/1032 data/test/img660.jpg: 256x512 Done. (0.073s)\n",
            "image 694/1032 data/test/img661.jpg: 256x512 Done. (0.073s)\n",
            "image 695/1032 data/test/img662.jpg: 256x512 Done. (0.073s)\n",
            "image 696/1032 data/test/img663.jpg: 256x512 Done. (0.073s)\n",
            "image 697/1032 data/test/img664.jpg: 256x512 Done. (0.074s)\n",
            "image 698/1032 data/test/img665.jpg: 256x512 Done. (0.073s)\n",
            "image 699/1032 data/test/img666.jpg: 256x512 Done. (0.073s)\n",
            "image 700/1032 data/test/img667.jpg: 256x512 Done. (0.073s)\n",
            "image 701/1032 data/test/img668.jpg: 256x512 Done. (0.073s)\n",
            "image 702/1032 data/test/img669.jpg: 256x512 Done. (0.073s)\n",
            "image 703/1032 data/test/img670.jpg: 256x512 Done. (0.073s)\n",
            "image 704/1032 data/test/img671.jpg: 256x512 Done. (0.073s)\n",
            "image 705/1032 data/test/img672.jpg: 256x512 Done. (0.073s)\n",
            "image 706/1032 data/test/img673.jpg: 256x512 Done. (0.073s)\n",
            "image 707/1032 data/test/img674.jpg: 256x512 Done. (0.073s)\n",
            "image 708/1032 data/test/img675.jpg: 256x512 Done. (0.073s)\n",
            "image 709/1032 data/test/img676.jpg: 256x512 Done. (0.073s)\n",
            "image 710/1032 data/test/img677.jpg: 256x512 Done. (0.073s)\n",
            "image 711/1032 data/test/img678.jpg: 256x512 Done. (0.073s)\n",
            "image 712/1032 data/test/img679.jpg: 256x512 Done. (0.073s)\n",
            "image 713/1032 data/test/img680.jpg: 256x512 Done. (0.073s)\n",
            "image 714/1032 data/test/img681.jpg: 256x512 Done. (0.073s)\n",
            "image 715/1032 data/test/img682.jpg: 256x512 Done. (0.073s)\n",
            "image 716/1032 data/test/img683.jpg: 256x512 Done. (0.073s)\n",
            "image 717/1032 data/test/img684.jpg: 256x512 Done. (0.073s)\n",
            "image 718/1032 data/test/img685.jpg: 256x512 Done. (0.073s)\n",
            "image 719/1032 data/test/img686.jpg: 256x512 Done. (0.073s)\n",
            "image 720/1032 data/test/img687.jpg: 256x512 Done. (0.073s)\n",
            "image 721/1032 data/test/img688.jpg: 256x512 Done. (0.073s)\n",
            "image 722/1032 data/test/img689.jpg: 256x512 Done. (0.073s)\n",
            "image 723/1032 data/test/img690.jpg: 256x512 Done. (0.074s)\n",
            "image 724/1032 data/test/img691.jpg: 256x512 Done. (0.073s)\n",
            "image 725/1032 data/test/img692.jpg: 256x512 Done. (0.073s)\n",
            "image 726/1032 data/test/img693.jpg: 256x512 Done. (0.073s)\n",
            "image 727/1032 data/test/img694.jpg: 256x512 Done. (0.073s)\n",
            "image 728/1032 data/test/img695.jpg: 256x512 Done. (0.073s)\n",
            "image 729/1032 data/test/img696.jpg: 256x512 Done. (0.073s)\n",
            "image 730/1032 data/test/img697.jpg: 256x512 Done. (0.073s)\n",
            "image 731/1032 data/test/img698.jpg: 256x512 Done. (0.073s)\n",
            "image 732/1032 data/test/img699.jpg: 256x512 Done. (0.073s)\n",
            "image 733/1032 data/test/img700.jpg: 256x512 Done. (0.073s)\n",
            "image 734/1032 data/test/img701.jpg: 256x512 Done. (0.073s)\n",
            "image 735/1032 data/test/img702.jpg: 256x512 Done. (0.073s)\n",
            "image 736/1032 data/test/img703.jpg: 256x512 Done. (0.073s)\n",
            "image 737/1032 data/test/img704.jpg: 256x512 Done. (0.073s)\n",
            "image 738/1032 data/test/img705.jpg: 256x512 Done. (0.073s)\n",
            "image 739/1032 data/test/img706.jpg: 256x512 Done. (0.073s)\n",
            "image 740/1032 data/test/img707.jpg: 256x512 Done. (0.073s)\n",
            "image 741/1032 data/test/img708.jpg: 256x512 Done. (0.073s)\n",
            "image 742/1032 data/test/img709.jpg: 256x512 Done. (0.073s)\n",
            "image 743/1032 data/test/img710.jpg: 256x512 Done. (0.073s)\n",
            "image 744/1032 data/test/img711.jpg: 256x512 1 batmans, Done. (0.073s)\n",
            "image 745/1032 data/test/img712.jpg: 256x512 Done. (0.073s)\n",
            "image 746/1032 data/test/img713.jpg: 256x512 Done. (0.073s)\n",
            "image 747/1032 data/test/img714.jpg: 256x512 1 batmans, Done. (0.073s)\n",
            "image 748/1032 data/test/img715.jpg: 256x512 Done. (0.073s)\n",
            "image 749/1032 data/test/img716.jpg: 256x512 Done. (0.073s)\n",
            "image 750/1032 data/test/img717.jpg: 256x512 Done. (0.073s)\n",
            "image 751/1032 data/test/img718.jpg: 256x512 1 batmans, Done. (0.073s)\n",
            "image 752/1032 data/test/img719.jpg: 256x512 1 batmans, Done. (0.073s)\n",
            "image 753/1032 data/test/img720.jpg: 256x512 Done. (0.073s)\n",
            "image 754/1032 data/test/img721.jpg: 256x512 Done. (0.073s)\n",
            "image 755/1032 data/test/img722.jpg: 256x512 Done. (0.073s)\n",
            "image 756/1032 data/test/img723.jpg: 256x512 Done. (0.073s)\n",
            "image 757/1032 data/test/img724.jpg: 256x512 Done. (0.073s)\n",
            "image 758/1032 data/test/img725.jpg: 256x512 Done. (0.073s)\n",
            "image 759/1032 data/test/img726.jpg: 256x512 Done. (0.073s)\n",
            "image 760/1032 data/test/img727.jpg: 256x512 Done. (0.073s)\n",
            "image 761/1032 data/test/img728.jpg: 256x512 Done. (0.073s)\n",
            "image 762/1032 data/test/img729.jpg: 256x512 Done. (0.073s)\n",
            "image 763/1032 data/test/img730.jpg: 256x512 Done. (0.073s)\n",
            "image 764/1032 data/test/img731.jpg: 256x512 Done. (0.073s)\n",
            "image 765/1032 data/test/img732.jpg: 256x512 Done. (0.073s)\n",
            "image 766/1032 data/test/img733.jpg: 256x512 Done. (0.073s)\n",
            "image 767/1032 data/test/img734.jpg: 256x512 Done. (0.073s)\n",
            "image 768/1032 data/test/img735.jpg: 256x512 Done. (0.073s)\n",
            "image 769/1032 data/test/img736.jpg: 256x512 Done. (0.073s)\n",
            "image 770/1032 data/test/img737.jpg: 256x512 Done. (0.073s)\n",
            "image 771/1032 data/test/img738.jpg: 256x512 Done. (0.073s)\n",
            "image 772/1032 data/test/img739.jpg: 256x512 Done. (0.073s)\n",
            "image 773/1032 data/test/img740.jpg: 256x512 Done. (0.073s)\n",
            "image 774/1032 data/test/img741.jpg: 256x512 Done. (0.073s)\n",
            "image 775/1032 data/test/img742.jpg: 256x512 Done. (0.073s)\n",
            "image 776/1032 data/test/img743.jpg: 256x512 Done. (0.073s)\n",
            "image 777/1032 data/test/img744.jpg: 256x512 Done. (0.073s)\n",
            "image 778/1032 data/test/img745.jpg: 256x512 Done. (0.073s)\n",
            "image 779/1032 data/test/img746.jpg: 256x512 Done. (0.073s)\n",
            "image 780/1032 data/test/img747.jpg: 256x512 Done. (0.073s)\n",
            "image 781/1032 data/test/img748.jpg: 256x512 Done. (0.073s)\n",
            "image 782/1032 data/test/img749.jpg: 256x512 Done. (0.073s)\n",
            "image 783/1032 data/test/img750.jpg: 256x512 Done. (0.073s)\n",
            "image 784/1032 data/test/img751.jpg: 256x512 Done. (0.073s)\n",
            "image 785/1032 data/test/img752.jpg: 256x512 Done. (0.073s)\n",
            "image 786/1032 data/test/img753.jpg: 256x512 Done. (0.073s)\n",
            "image 787/1032 data/test/img754.jpg: 256x512 Done. (0.073s)\n",
            "image 788/1032 data/test/img755.jpg: 256x512 Done. (0.073s)\n",
            "image 789/1032 data/test/img756.jpg: 256x512 Done. (0.073s)\n",
            "image 790/1032 data/test/img757.jpg: 256x512 Done. (0.073s)\n",
            "image 791/1032 data/test/img758.jpg: 256x512 Done. (0.073s)\n",
            "image 792/1032 data/test/img759.jpg: 256x512 Done. (0.073s)\n",
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            "image 794/1032 data/test/img761.jpg: 256x512 Done. (0.073s)\n",
            "image 795/1032 data/test/img762.jpg: 256x512 Done. (0.073s)\n",
            "image 796/1032 data/test/img763.jpg: 256x512 Done. (0.074s)\n",
            "image 797/1032 data/test/img764.jpg: 256x512 Done. (0.073s)\n",
            "image 798/1032 data/test/img765.jpg: 256x512 Done. (0.073s)\n",
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            "image 858/1032 data/test/img825.jpg: 256x512 Done. (0.073s)\n",
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            "image 919/1032 data/test/img886.jpg: 256x512 Done. (0.073s)\n",
            "image 920/1032 data/test/img887.jpg: 256x512 1 batmans, Done. (0.073s)\n",
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            "image 950/1032 data/test/img917.jpg: 256x512 1 batmans, Done. (0.073s)\n",
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            "image 975/1032 data/test/img942.jpg: 256x512 Done. (0.073s)\n",
            "image 976/1032 data/test/img943.jpg: 256x512 1 batmans, Done. (0.073s)\n",
            "image 977/1032 data/test/img944.jpg: 256x512 1 batmans, Done. (0.073s)\n",
            "image 978/1032 data/test/img945.jpg: 256x512 2 batmans, Done. (0.073s)\n",
            "image 979/1032 data/test/img946.jpg: 256x512 1 batmans, Done. (0.073s)\n",
            "image 980/1032 data/test/img947.jpg: 256x512 1 batmans, Done. (0.073s)\n",
            "image 981/1032 data/test/img948.jpg: 256x512 1 batmans, Done. (0.073s)\n",
            "image 982/1032 data/test/img949.jpg: 256x512 1 batmans, Done. (0.073s)\n",
            "image 983/1032 data/test/img950.jpg: 256x512 1 batmans, Done. (0.073s)\n",
            "image 984/1032 data/test/img951.jpg: 256x512 1 batmans, Done. (0.073s)\n",
            "image 985/1032 data/test/img952.jpg: 256x512 1 batmans, Done. (0.073s)\n",
            "image 986/1032 data/test/img953.jpg: 256x512 1 batmans, Done. (0.073s)\n",
            "image 987/1032 data/test/img954.jpg: 256x512 1 batmans, Done. (0.073s)\n",
            "image 988/1032 data/test/img955.jpg: 256x512 1 batmans, Done. (0.073s)\n",
            "image 989/1032 data/test/img956.jpg: 256x512 1 batmans, Done. (0.073s)\n",
            "image 990/1032 data/test/img957.jpg: 256x512 1 batmans, Done. (0.073s)\n",
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            "image 992/1032 data/test/img959.jpg: 256x512 1 batmans, Done. (0.073s)\n",
            "image 993/1032 data/test/img960.jpg: 256x512 1 batmans, Done. (0.073s)\n",
            "image 994/1032 data/test/img961.jpg: 256x512 1 batmans, Done. (0.073s)\n",
            "image 995/1032 data/test/img962.jpg: 256x512 1 batmans, Done. (0.073s)\n",
            "image 996/1032 data/test/img963.jpg: 256x512 1 batmans, Done. (0.073s)\n",
            "image 997/1032 data/test/img964.jpg: 256x512 1 batmans, Done. (0.073s)\n",
            "image 998/1032 data/test/img965.jpg: 256x512 1 batmans, Done. (0.073s)\n",
            "image 999/1032 data/test/img966.jpg: 256x512 1 batmans, Done. (0.073s)\n",
            "image 1000/1032 data/test/img967.jpg: 256x512 1 batmans, Done. (0.073s)\n",
            "image 1001/1032 data/test/img968.jpg: 256x512 1 batmans, Done. (0.073s)\n",
            "image 1002/1032 data/test/img969.jpg: 256x512 1 batmans, Done. (0.073s)\n",
            "image 1003/1032 data/test/img970.jpg: 256x512 1 batmans, Done. (0.073s)\n",
            "image 1004/1032 data/test/img971.jpg: 256x512 1 batmans, Done. (0.073s)\n",
            "image 1005/1032 data/test/img972.jpg: 256x512 1 batmans, Done. (0.073s)\n",
            "image 1006/1032 data/test/img973.jpg: 256x512 1 batmans, Done. (0.073s)\n",
            "image 1007/1032 data/test/img974.jpg: 256x512 1 batmans, Done. (0.073s)\n",
            "image 1008/1032 data/test/img975.jpg: 256x512 1 batmans, Done. (0.072s)\n",
            "image 1009/1032 data/test/img976.jpg: 256x512 1 batmans, Done. (0.073s)\n",
            "image 1010/1032 data/test/img977.jpg: 256x512 1 batmans, Done. (0.073s)\n",
            "image 1011/1032 data/test/img978.jpg: 256x512 1 batmans, Done. (0.073s)\n",
            "image 1012/1032 data/test/img979.jpg: 256x512 1 batmans, Done. (0.073s)\n",
            "image 1013/1032 data/test/img980.jpg: 256x512 1 batmans, Done. (0.072s)\n",
            "image 1014/1032 data/test/img981.jpg: 256x512 1 batmans, Done. (0.073s)\n",
            "image 1015/1032 data/test/img982.jpg: 256x512 1 batmans, Done. (0.073s)\n",
            "image 1016/1032 data/test/img983.jpg: 256x512 1 batmans, Done. (0.073s)\n",
            "image 1017/1032 data/test/img984.jpg: 256x512 1 batmans, Done. (0.073s)\n",
            "image 1018/1032 data/test/img985.jpg: 256x512 1 batmans, Done. (0.073s)\n",
            "image 1019/1032 data/test/img986.jpg: 256x512 1 batmans, Done. (0.073s)\n",
            "image 1020/1032 data/test/img987.jpg: 256x512 1 batmans, Done. (0.073s)\n",
            "image 1021/1032 data/test/img988.jpg: 256x512 1 batmans, Done. (0.073s)\n",
            "image 1022/1032 data/test/img989.jpg: 256x512 1 batmans, Done. (0.073s)\n",
            "image 1023/1032 data/test/img990.jpg: 256x512 1 batmans, Done. (0.073s)\n",
            "image 1024/1032 data/test/img991.jpg: 256x512 1 batmans, Done. (0.073s)\n",
            "image 1025/1032 data/test/img992.jpg: 256x512 1 batmans, Done. (0.072s)\n",
            "image 1026/1032 data/test/img993.jpg: 256x512 1 batmans, Done. (0.073s)\n",
            "image 1027/1032 data/test/img994.jpg: 256x512 1 batmans, Done. (0.073s)\n",
            "image 1028/1032 data/test/img995.jpg: 256x512 1 batmans, Done. (0.073s)\n",
            "image 1029/1032 data/test/img996.jpg: 256x512 1 batmans, Done. (0.073s)\n",
            "image 1030/1032 data/test/img997.jpg: 256x512 1 batmans, Done. (0.074s)\n",
            "image 1031/1032 data/test/img998.jpg: 256x512 1 batmans, Done. (0.074s)\n",
            "image 1032/1032 data/test/img999.jpg: 256x512 1 batmans, Done. (0.073s)\n",
            "Results saved to /content/gdrive/My Drive/YoloV3/output\n",
            "Done. (575.853s)\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "07gv4GI1A4Ax",
        "colab_type": "text"
      },
      "source": [
        "## Output"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "weNdrTVi86Ws",
        "colab_type": "code",
        "outputId": "3cb0c13f-e942-4ff0-da08-dc0617597896",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 267
        }
      },
      "source": [
        "Image(filename='output/img350.jpg', width=600)"
      ],
      "execution_count": 0,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "image/jpeg": 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\n",
            "text/plain": [
              "<IPython.core.display.Image object>"
            ]
          },
          "metadata": {
            "tags": [],
            "image/jpeg": {
              "width": 600
            }
          },
          "execution_count": 19
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "eaSbzlOh3XTB",
        "colab_type": "code",
        "outputId": "fba23e0c-5804-4800-b7d3-724703ab0b58",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 267
        }
      },
      "source": [
        "Image(filename='output/img050.jpg', width=600)"
      ],
      "execution_count": 0,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "image/jpeg": 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\n",
            "text/plain": [
              "<IPython.core.display.Image object>"
            ]
          },
          "metadata": {
            "tags": [],
            "image/jpeg": {
              "width": 600
            }
          },
          "execution_count": 18
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "Qn0bFsKp9WQ8",
        "colab_type": "code",
        "outputId": "2d3c114e-4ea1-464a-db7d-e3f0eaecf676",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 267
        }
      },
      "source": [
        "Image(filename='output/img1010.jpg', width=600)"
      ],
      "execution_count": 0,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "image/jpeg": 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\n",
            "text/plain": [
              "<IPython.core.display.Image object>"
            ]
          },
          "metadata": {
            "tags": [],
            "image/jpeg": {
              "width": 600
            }
          },
          "execution_count": 33
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "F6EiOdQc-JIt",
        "colab_type": "text"
      },
      "source": [
        "### Convert output frames to video"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "IiavdSFA8jvH",
        "colab_type": "code",
        "outputId": "c0d30525-7306-47fa-a9cf-85ea7590495b",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 877
        }
      },
      "source": [
        "!ffmpeg -framerate 24 -i output/img%3d.jpg -r 24 -y batman.mp4"
      ],
      "execution_count": 0,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "ffmpeg version 3.4.6-0ubuntu0.18.04.1 Copyright (c) 2000-2019 the FFmpeg developers\n",
            "  built with gcc 7 (Ubuntu 7.3.0-16ubuntu3)\n",
            "  configuration: --prefix=/usr --extra-version=0ubuntu0.18.04.1 --toolchain=hardened --libdir=/usr/lib/x86_64-linux-gnu --incdir=/usr/include/x86_64-linux-gnu --enable-gpl --disable-stripping --enable-avresample --enable-avisynth --enable-gnutls --enable-ladspa --enable-libass --enable-libbluray --enable-libbs2b --enable-libcaca --enable-libcdio --enable-libflite --enable-libfontconfig --enable-libfreetype --enable-libfribidi --enable-libgme --enable-libgsm --enable-libmp3lame --enable-libmysofa --enable-libopenjpeg --enable-libopenmpt --enable-libopus --enable-libpulse --enable-librubberband --enable-librsvg --enable-libshine --enable-libsnappy --enable-libsoxr --enable-libspeex --enable-libssh --enable-libtheora --enable-libtwolame --enable-libvorbis --enable-libvpx --enable-libwavpack --enable-libwebp --enable-libx265 --enable-libxml2 --enable-libxvid --enable-libzmq --enable-libzvbi --enable-omx --enable-openal --enable-opengl --enable-sdl2 --enable-libdc1394 --enable-libdrm --enable-libiec61883 --enable-chromaprint --enable-frei0r --enable-libopencv --enable-libx264 --enable-shared\n",
            "  libavutil      55. 78.100 / 55. 78.100\n",
            "  libavcodec     57.107.100 / 57.107.100\n",
            "  libavformat    57. 83.100 / 57. 83.100\n",
            "  libavdevice    57. 10.100 / 57. 10.100\n",
            "  libavfilter     6.107.100 /  6.107.100\n",
            "  libavresample   3.  7.  0 /  3.  7.  0\n",
            "  libswscale      4.  8.100 /  4.  8.100\n",
            "  libswresample   2.  9.100 /  2.  9.100\n",
            "  libpostproc    54.  7.100 / 54.  7.100\n",
            "Input #0, image2, from 'output/img%3d.jpg':\n",
            "  Duration: 00:00:43.00, start: 0.000000, bitrate: N/A\n",
            "    Stream #0:0: Video: mjpeg, yuvj420p(pc, bt470bg/unknown/unknown), 1920x800 [SAR 1:1 DAR 12:5], 24 fps, 24 tbr, 24 tbn, 24 tbc\n",
            "Stream mapping:\n",
            "  Stream #0:0 -> #0:0 (mjpeg (native) -> h264 (libx264))\n",
            "Press [q] to stop, [?] for help\n",
            "\u001b[1;36m[libx264 @ 0x555fc474fe00] \u001b[0musing SAR=1/1\n",
            "\u001b[1;36m[libx264 @ 0x555fc474fe00] \u001b[0musing cpu capabilities: MMX2 SSE2Fast SSSE3 SSE4.2 AVX FMA3 BMI2 AVX2\n",
            "\u001b[1;36m[libx264 @ 0x555fc474fe00] \u001b[0mprofile High, level 4.0\n",
            "\u001b[1;36m[libx264 @ 0x555fc474fe00] \u001b[0m264 - core 152 r2854 e9a5903 - H.264/MPEG-4 AVC codec - Copyleft 2003-2017 - http://www.videolan.org/x264.html - options: cabac=1 ref=3 deblock=1:0:0 analyse=0x3:0x113 me=hex subme=7 psy=1 psy_rd=1.00:0.00 mixed_ref=1 me_range=16 chroma_me=1 trellis=1 8x8dct=1 cqm=0 deadzone=21,11 fast_pskip=1 chroma_qp_offset=-2 threads=3 lookahead_threads=1 sliced_threads=0 nr=0 decimate=1 interlaced=0 bluray_compat=0 constrained_intra=0 bframes=3 b_pyramid=2 b_adapt=1 b_bias=0 direct=1 weightb=1 open_gop=0 weightp=2 keyint=250 keyint_min=24 scenecut=40 intra_refresh=0 rc_lookahead=40 rc=crf mbtree=1 crf=23.0 qcomp=0.60 qpmin=0 qpmax=69 qpstep=4 ip_ratio=1.40 aq=1:1.00\n",
            "Output #0, mp4, to 'batman.mp4':\n",
            "  Metadata:\n",
            "    encoder         : Lavf57.83.100\n",
            "    Stream #0:0: Video: h264 (libx264) (avc1 / 0x31637661), yuvj420p(pc), 1920x800 [SAR 1:1 DAR 12:5], q=-1--1, 24 fps, 12288 tbn, 24 tbc\n",
            "    Metadata:\n",
            "      encoder         : Lavc57.107.100 libx264\n",
            "    Side data:\n",
            "      cpb: bitrate max/min/avg: 0/0/0 buffer size: 0 vbv_delay: -1\n",
            "frame= 1032 fps=5.9 q=-1.0 Lsize=   33363kB time=00:00:42.87 bitrate=6374.6kbits/s speed=0.246x    \n",
            "video:33350kB audio:0kB subtitle:0kB other streams:0kB global headers:0kB muxing overhead: 0.037633%\n",
            "\u001b[1;36m[libx264 @ 0x555fc474fe00] \u001b[0mframe I:30    Avg QP:19.75  size: 42268\n",
            "\u001b[1;36m[libx264 @ 0x555fc474fe00] \u001b[0mframe P:382   Avg QP:23.34  size: 35967\n",
            "\u001b[1;36m[libx264 @ 0x555fc474fe00] \u001b[0mframe B:620   Avg QP:24.32  size: 30875\n",
            "\u001b[1;36m[libx264 @ 0x555fc474fe00] \u001b[0mconsecutive B-frames: 14.7% 13.4%  6.4% 65.5%\n",
            "\u001b[1;36m[libx264 @ 0x555fc474fe00] \u001b[0mmb I  I16..4: 57.1% 41.6%  1.3%\n",
            "\u001b[1;36m[libx264 @ 0x555fc474fe00] \u001b[0mmb P  I16..4: 40.4% 49.5%  0.9%  P16..4:  4.0%  1.9%  0.9%  0.0%  0.0%    skip: 2.4%\n",
            "\u001b[1;36m[libx264 @ 0x555fc474fe00] \u001b[0mmb B  I16..4: 19.7% 42.2%  0.5%  B16..8:  9.5%  4.6%  1.6%  direct: 6.2%  skip:15.7%  L0:49.3% L1:41.8% BI: 8.9%\n",
            "\u001b[1;36m[libx264 @ 0x555fc474fe00] \u001b[0m8x8 transform intra:60.7% inter:86.8%\n",
            "\u001b[1;36m[libx264 @ 0x555fc474fe00] \u001b[0mcoded y,uvDC,uvAC intra: 41.3% 85.9% 13.6% inter: 24.7% 46.1% 6.4%\n",
            "\u001b[1;36m[libx264 @ 0x555fc474fe00] \u001b[0mi16 v,h,dc,p: 39% 44% 16%  1%\n",
            "\u001b[1;36m[libx264 @ 0x555fc474fe00] \u001b[0mi8 v,h,dc,ddl,ddr,vr,hd,vl,hu: 18% 23% 47%  3%  1%  1%  1%  1%  6%\n",
            "\u001b[1;36m[libx264 @ 0x555fc474fe00] \u001b[0mi4 v,h,dc,ddl,ddr,vr,hd,vl,hu: 46% 30% 11%  2%  3%  3%  2%  2%  2%\n",
            "\u001b[1;36m[libx264 @ 0x555fc474fe00] \u001b[0mi8c dc,h,v,p: 29% 36% 28%  7%\n",
            "\u001b[1;36m[libx264 @ 0x555fc474fe00] \u001b[0mWeighted P-Frames: Y:13.4% UV:11.8%\n",
            "\u001b[1;36m[libx264 @ 0x555fc474fe00] \u001b[0mref P L0: 49.8% 12.7% 21.7% 13.7%  2.1%\n",
            "\u001b[1;36m[libx264 @ 0x555fc474fe00] \u001b[0mref B L0: 77.2% 17.6%  5.2%\n",
            "\u001b[1;36m[libx264 @ 0x555fc474fe00] \u001b[0mref B L1: 92.0%  8.0%\n",
            "\u001b[1;36m[libx264 @ 0x555fc474fe00] \u001b[0mkb/s:6353.51\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "v1X2_SFkdsjg",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        ""
      ],
      "execution_count": 0,
      "outputs": []
    }
  ]
}