Train_YoloV3_.ipynb

{
  "nbformat": 4,
  "nbformat_minor": 0,
  "metadata": {
    "colab": {
      "name": "Train_YoloV3 .ipynb",
      "provenance": [],
      "collapsed_sections": []
    },
    "kernelspec": {
      "name": "python3",
      "display_name": "Python 3"
    },
    "accelerator": "GPU"
  },
  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "wHBQcQzjD6HJ",
        "colab_type": "text"
      },
      "source": [
        "**Connect google drive**"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "bwp6NIrsZZFP",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 306
        },
        "outputId": "69fcbdd0-5ccc-4486-b5c5-7a2cdf1c9c69"
      },
      "source": [
        "# Check if NVIDIA GPU is enabled\n",
        "!nvidia-smi"
      ],
      "execution_count": 1,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Fri May  1 07:12:22 2020       \n",
            "+-----------------------------------------------------------------------------+\n",
            "| NVIDIA-SMI 440.64.00    Driver Version: 418.67       CUDA Version: 10.1     |\n",
            "|-------------------------------+----------------------+----------------------+\n",
            "| GPU  Name        Persistence-M| Bus-Id        Disp.A | Volatile Uncorr. ECC |\n",
            "| Fan  Temp  Perf  Pwr:Usage/Cap|         Memory-Usage | GPU-Util  Compute M. |\n",
            "|===============================+======================+======================|\n",
            "|   0  Tesla T4            Off  | 00000000:00:04.0 Off |                    0 |\n",
            "| N/A   61C    P8    11W /  70W |      0MiB / 15079MiB |      0%      Default |\n",
            "+-------------------------------+----------------------+----------------------+\n",
            "                                                                               \n",
            "+-----------------------------------------------------------------------------+\n",
            "| Processes:                                                       GPU Memory |\n",
            "|  GPU       PID   Type   Process name                             Usage      |\n",
            "|=============================================================================|\n",
            "|  No running processes found                                                 |\n",
            "+-----------------------------------------------------------------------------+\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "9e9ZW3sqMEPO",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 258
        },
        "outputId": "b9ed4ee2-eed2-4e70-f724-7ffa89136ed9"
      },
      "source": [
        "from google.colab import drive\n",
        "drive.mount('/content/gdrive')\n",
        "!ln -s /content/gdrive/My\\ Drive/ /mydrive\n",
        "!ls /mydrive"
      ],
      "execution_count": 2,
      "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",
            "'AJAX with Django 3.x.gslides'\t model-ICNet-trained-model.h5\n",
            " certificate.JPG\t\t'NANDINI BANSAL.pdf'\n",
            "'Colab Notebooks'\t\t Nandini_Resume_2020.pdf\n",
            " Companies_ML_DL_DS.gsheet\t siamese-text-similarity.zip\n",
            " dev.csv\t\t\t train.csv\n",
            "'Getting started.pdf'\t\t'Untitled Diagram (1).drawio'\n",
            " glove.6B.50d.txt\t\t'Untitled Diagram.drawio'\n",
            "'HUSE Implementation'\t\t yolov3\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "t7utW4in4azV",
        "colab_type": "text"
      },
      "source": [
        "**1) Clone the Darknet**\n",
        "\n"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "e03U7Zi-qMr2",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 102
        },
        "outputId": "1ccd4b0e-c4de-4c9d-a725-589fce0a93e2"
      },
      "source": [
        "!git clone https://github.com/AlexeyAB/darknet"
      ],
      "execution_count": 3,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Cloning into 'darknet'...\n",
            "remote: Enumerating objects: 13221, done.\u001b[K\n",
            "remote: Total 13221 (delta 0), reused 0 (delta 0), pack-reused 13221\u001b[K\n",
            "Receiving objects: 100% (13221/13221), 11.91 MiB | 12.12 MiB/s, done.\n",
            "Resolving deltas: 100% (9041/9041), done.\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "7gDOF3mU-TAn",
        "colab_type": "text"
      },
      "source": [
        "**2) Compile Darknet using Nvidia GPU**\n"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "5H-Taj06Tw1c",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 1000
        },
        "outputId": "8c6ee447-ba5e-4f25-878f-b03aa76c2542"
      },
      "source": [
        "# change makefile to have GPU and OPENCV enabled\n",
        "%cd darknet\n",
        "!sed -i 's/OPENCV=0/OPENCV=1/' Makefile\n",
        "!sed -i 's/GPU=0/GPU=1/' Makefile\n",
        "!sed -i 's/CUDNN=0/CUDNN=1/' Makefile\n",
        "!make"
      ],
      "execution_count": 4,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "/content/darknet\n",
            "mkdir -p ./obj/\n",
            "mkdir -p backup\n",
            "chmod +x *.sh\n",
            "g++ -std=c++11 -std=c++11 -Iinclude/ -I3rdparty/stb/include -DOPENCV `pkg-config --cflags opencv4 2> /dev/null || pkg-config --cflags opencv` -DGPU -I/usr/local/cuda/include/ -DCUDNN -Wall -Wfatal-errors -Wno-unused-result -Wno-unknown-pragmas -fPIC -Ofast -DOPENCV -DGPU -DCUDNN -I/usr/local/cudnn/include -c ./src/image_opencv.cpp -o obj/image_opencv.o\n",
            "\u001b[01m\u001b[K./src/image_opencv.cpp:\u001b[m\u001b[K In function ‘\u001b[01m\u001b[Kvoid draw_detections_cv_v3(void**, detection*, int, float, char**, image**, int, int)\u001b[m\u001b[K’:\n",
            "\u001b[01m\u001b[K./src/image_opencv.cpp:910:23:\u001b[m\u001b[K \u001b[01;35m\u001b[Kwarning: \u001b[m\u001b[Kvariable ‘\u001b[01m\u001b[Krgb\u001b[m\u001b[K’ set but not used [\u001b[01;35m\u001b[K-Wunused-but-set-variable\u001b[m\u001b[K]\n",
            "                 float \u001b[01;35m\u001b[Krgb\u001b[m\u001b[K[3];\n",
            "                       \u001b[01;35m\u001b[K^~~\u001b[m\u001b[K\n",
            "\u001b[01m\u001b[K./src/image_opencv.cpp:\u001b[m\u001b[K In function ‘\u001b[01m\u001b[Kvoid cv_draw_object(image, float*, int, int, int*, float*, int*, int, char**)\u001b[m\u001b[K’:\n",
            "\u001b[01m\u001b[K./src/image_opencv.cpp:1391:14:\u001b[m\u001b[K \u001b[01;35m\u001b[Kwarning: \u001b[m\u001b[Kunused variable ‘\u001b[01m\u001b[Kbuff\u001b[m\u001b[K’ [\u001b[01;35m\u001b[K-Wunused-variable\u001b[m\u001b[K]\n",
            "         char \u001b[01;35m\u001b[Kbuff\u001b[m\u001b[K[100];\n",
            "              \u001b[01;35m\u001b[K^~~~\u001b[m\u001b[K\n",
            "\u001b[01m\u001b[K./src/image_opencv.cpp:1367:9:\u001b[m\u001b[K \u001b[01;35m\u001b[Kwarning: \u001b[m\u001b[Kunused variable ‘\u001b[01m\u001b[Kit_tb_res\u001b[m\u001b[K’ [\u001b[01;35m\u001b[K-Wunused-variable\u001b[m\u001b[K]\n",
            "     int \u001b[01;35m\u001b[Kit_tb_res\u001b[m\u001b[K = cv::createTrackbar(it_trackbar_name, window_name, &it_trackbar_value, 1000);\n",
            "         \u001b[01;35m\u001b[K^~~~~~~~~\u001b[m\u001b[K\n",
            "\u001b[01m\u001b[K./src/image_opencv.cpp:1371:9:\u001b[m\u001b[K \u001b[01;35m\u001b[Kwarning: \u001b[m\u001b[Kunused variable ‘\u001b[01m\u001b[Klr_tb_res\u001b[m\u001b[K’ [\u001b[01;35m\u001b[K-Wunused-variable\u001b[m\u001b[K]\n",
            "     int \u001b[01;35m\u001b[Klr_tb_res\u001b[m\u001b[K = cv::createTrackbar(lr_trackbar_name, window_name, &lr_trackbar_value, 20);\n",
            "         \u001b[01;35m\u001b[K^~~~~~~~~\u001b[m\u001b[K\n",
            "\u001b[01m\u001b[K./src/image_opencv.cpp:1375:9:\u001b[m\u001b[K \u001b[01;35m\u001b[Kwarning: \u001b[m\u001b[Kunused variable ‘\u001b[01m\u001b[Kcl_tb_res\u001b[m\u001b[K’ [\u001b[01;35m\u001b[K-Wunused-variable\u001b[m\u001b[K]\n",
            "     int \u001b[01;35m\u001b[Kcl_tb_res\u001b[m\u001b[K = cv::createTrackbar(cl_trackbar_name, window_name, &cl_trackbar_value, classes-1);\n",
            "         \u001b[01;35m\u001b[K^~~~~~~~~\u001b[m\u001b[K\n",
            "\u001b[01m\u001b[K./src/image_opencv.cpp:1378:9:\u001b[m\u001b[K \u001b[01;35m\u001b[Kwarning: \u001b[m\u001b[Kunused variable ‘\u001b[01m\u001b[Kbo_tb_res\u001b[m\u001b[K’ [\u001b[01;35m\u001b[K-Wunused-variable\u001b[m\u001b[K]\n",
            "     int \u001b[01;35m\u001b[Kbo_tb_res\u001b[m\u001b[K = cv::createTrackbar(bo_trackbar_name, window_name, boxonly, 1);\n",
            "         \u001b[01;35m\u001b[K^~~~~~~~~\u001b[m\u001b[K\n",
            "g++ -std=c++11 -std=c++11 -Iinclude/ -I3rdparty/stb/include -DOPENCV `pkg-config --cflags opencv4 2> /dev/null || pkg-config --cflags opencv` -DGPU -I/usr/local/cuda/include/ -DCUDNN -Wall -Wfatal-errors -Wno-unused-result -Wno-unknown-pragmas -fPIC -Ofast -DOPENCV -DGPU -DCUDNN -I/usr/local/cudnn/include -c ./src/http_stream.cpp -o obj/http_stream.o\n",
            "In file included from \u001b[01m\u001b[K./src/http_stream.cpp:580:0\u001b[m\u001b[K:\n",
            "\u001b[01m\u001b[K./src/httplib.h:129:0:\u001b[m\u001b[K \u001b[01;35m\u001b[Kwarning: \u001b[m\u001b[K\"INVALID_SOCKET\" redefined\n",
            " #define INVALID_SOCKET (-1)\n",
            " \n",
            "\u001b[01m\u001b[K./src/http_stream.cpp:73:0:\u001b[m\u001b[K \u001b[01;36m\u001b[Knote: \u001b[m\u001b[Kthis is the location of the previous definition\n",
            " #define INVALID_SOCKET -1\n",
            " \n",
            "\u001b[01m\u001b[K./src/http_stream.cpp:\u001b[m\u001b[K In member function ‘\u001b[01m\u001b[Kbool JSON_sender::write(const char*)\u001b[m\u001b[K’:\n",
            "\u001b[01m\u001b[K./src/http_stream.cpp:249:21:\u001b[m\u001b[K \u001b[01;35m\u001b[Kwarning: \u001b[m\u001b[Kunused variable ‘\u001b[01m\u001b[Kn\u001b[m\u001b[K’ [\u001b[01;35m\u001b[K-Wunused-variable\u001b[m\u001b[K]\n",
            "                 int \u001b[01;35m\u001b[Kn\u001b[m\u001b[K = _write(client, outputbuf, outlen);\n",
            "                     \u001b[01;35m\u001b[K^\u001b[m\u001b[K\n",
            "\u001b[01m\u001b[K./src/http_stream.cpp:\u001b[m\u001b[K In member function ‘\u001b[01m\u001b[Kbool MJPG_sender::write(const cv::Mat&)\u001b[m\u001b[K’:\n",
            "\u001b[01m\u001b[K./src/http_stream.cpp:507:113:\u001b[m\u001b[K \u001b[01;35m\u001b[Kwarning: \u001b[m\u001b[Kformat ‘\u001b[01m\u001b[K%zu\u001b[m\u001b[K’ expects argument of type ‘\u001b[01m\u001b[Ksize_t\u001b[m\u001b[K’, but argument 3 has type ‘\u001b[01m\u001b[Kint\u001b[m\u001b[K’ [\u001b[01;35m\u001b[K-Wformat=\u001b[m\u001b[K]\n",
            "                 sprintf(head, \"--mjpegstream\\r\\nContent-Type: image/jpeg\\r\\nContent-Length: %zu\\r\\n\\r\\n\", outlen\u001b[01;35m\u001b[K)\u001b[m\u001b[K;\n",
            "                                                                                                                 \u001b[01;35m\u001b[K^\u001b[m\u001b[K\n",
            "gcc -Iinclude/ -I3rdparty/stb/include -DOPENCV `pkg-config --cflags opencv4 2> /dev/null || pkg-config --cflags opencv` -DGPU -I/usr/local/cuda/include/ -DCUDNN -Wall -Wfatal-errors -Wno-unused-result -Wno-unknown-pragmas -fPIC -Ofast -DOPENCV -DGPU -DCUDNN -I/usr/local/cudnn/include -c ./src/gemm.c -o obj/gemm.o\n",
            "\u001b[01m\u001b[K./src/gemm.c:\u001b[m\u001b[K In function ‘\u001b[01m\u001b[Kconvolution_2d\u001b[m\u001b[K’:\n",
            "\u001b[01m\u001b[K./src/gemm.c:2039:15:\u001b[m\u001b[K \u001b[01;35m\u001b[Kwarning: \u001b[m\u001b[Kunused variable ‘\u001b[01m\u001b[Kout_w\u001b[m\u001b[K’ [\u001b[01;35m\u001b[K-Wunused-variable\u001b[m\u001b[K]\n",
            "     const int \u001b[01;35m\u001b[Kout_w\u001b[m\u001b[K = (w + 2 * pad - ksize) / stride + 1;    // output_width=input_width for stride=1 and pad=1\n",
            "               \u001b[01;35m\u001b[K^~~~~\u001b[m\u001b[K\n",
            "\u001b[01m\u001b[K./src/gemm.c:2038:15:\u001b[m\u001b[K \u001b[01;35m\u001b[Kwarning: \u001b[m\u001b[Kunused variable ‘\u001b[01m\u001b[Kout_h\u001b[m\u001b[K’ [\u001b[01;35m\u001b[K-Wunused-variable\u001b[m\u001b[K]\n",
            "     const int \u001b[01;35m\u001b[Kout_h\u001b[m\u001b[K = (h + 2 * pad - ksize) / stride + 1;    // output_height=input_height for stride=1 and pad=1\n",
            "               \u001b[01;35m\u001b[K^~~~~\u001b[m\u001b[K\n",
            "gcc -Iinclude/ -I3rdparty/stb/include -DOPENCV `pkg-config --cflags opencv4 2> /dev/null || pkg-config --cflags opencv` -DGPU -I/usr/local/cuda/include/ -DCUDNN -Wall -Wfatal-errors -Wno-unused-result -Wno-unknown-pragmas -fPIC -Ofast -DOPENCV -DGPU -DCUDNN -I/usr/local/cudnn/include -c ./src/utils.c -o obj/utils.o\n",
            "gcc -Iinclude/ -I3rdparty/stb/include -DOPENCV `pkg-config --cflags opencv4 2> /dev/null || pkg-config --cflags opencv` -DGPU -I/usr/local/cuda/include/ -DCUDNN -Wall -Wfatal-errors -Wno-unused-result -Wno-unknown-pragmas -fPIC -Ofast -DOPENCV -DGPU -DCUDNN -I/usr/local/cudnn/include -c ./src/dark_cuda.c -o obj/dark_cuda.o\n",
            "\u001b[01m\u001b[K./src/dark_cuda.c:\u001b[m\u001b[K In function ‘\u001b[01m\u001b[Kcudnn_check_error_extended\u001b[m\u001b[K’:\n",
            "\u001b[01m\u001b[K./src/dark_cuda.c:224:20:\u001b[m\u001b[K \u001b[01;35m\u001b[Kwarning: \u001b[m\u001b[Kcomparison between ‘\u001b[01m\u001b[KcudaError_t {aka enum cudaError}\u001b[m\u001b[K’ and ‘\u001b[01m\u001b[Kenum <anonymous>\u001b[m\u001b[K’ [\u001b[01;35m\u001b[K-Wenum-compare\u001b[m\u001b[K]\n",
            "         if (status \u001b[01;35m\u001b[K!=\u001b[m\u001b[K CUDNN_STATUS_SUCCESS)\n",
            "                    \u001b[01;35m\u001b[K^~\u001b[m\u001b[K\n",
            "\u001b[01m\u001b[K./src/dark_cuda.c:\u001b[m\u001b[K In function ‘\u001b[01m\u001b[Kpre_allocate_pinned_memory\u001b[m\u001b[K’:\n",
            "\u001b[01m\u001b[K./src/dark_cuda.c:276:40:\u001b[m\u001b[K \u001b[01;35m\u001b[Kwarning: \u001b[m\u001b[Kformat ‘\u001b[01m\u001b[K%u\u001b[m\u001b[K’ expects argument of type ‘\u001b[01m\u001b[Kunsigned int\u001b[m\u001b[K’, but argument 2 has type ‘\u001b[01m\u001b[Klong unsigned int\u001b[m\u001b[K’ [\u001b[01;35m\u001b[K-Wformat=\u001b[m\u001b[K]\n",
            "         printf(\"pre_allocate: size = \u001b[01;35m\u001b[K%Iu\u001b[m\u001b[K MB, num_of_blocks = %Iu, block_size = %Iu MB \\n\",\n",
            "                                      \u001b[01;35m\u001b[K~~^\u001b[m\u001b[K\n",
            "                                      \u001b[32m\u001b[K%Ilu\u001b[m\u001b[K\n",
            "             \u001b[32m\u001b[Ksize / (1024*1024)\u001b[m\u001b[K, num_of_blocks, pinned_block_size / (1024 * 1024));\n",
            "             \u001b[32m\u001b[K~~~~~~~~~~~~~~~~~~\u001b[m\u001b[K          \n",
            "\u001b[01m\u001b[K./src/dark_cuda.c:276:64:\u001b[m\u001b[K \u001b[01;35m\u001b[Kwarning: \u001b[m\u001b[Kformat ‘\u001b[01m\u001b[K%u\u001b[m\u001b[K’ expects argument of type ‘\u001b[01m\u001b[Kunsigned int\u001b[m\u001b[K’, but argument 3 has type ‘\u001b[01m\u001b[Ksize_t {aka const long unsigned int}\u001b[m\u001b[K’ [\u001b[01;35m\u001b[K-Wformat=\u001b[m\u001b[K]\n",
            "         printf(\"pre_allocate: size = %Iu MB, num_of_blocks = \u001b[01;35m\u001b[K%Iu\u001b[m\u001b[K, block_size = %Iu MB \\n\",\n",
            "                                                              \u001b[01;35m\u001b[K~~^\u001b[m\u001b[K\n",
            "                                                              \u001b[32m\u001b[K%Ilu\u001b[m\u001b[K\n",
            "\u001b[01m\u001b[K./src/dark_cuda.c:276:82:\u001b[m\u001b[K \u001b[01;35m\u001b[Kwarning: \u001b[m\u001b[Kformat ‘\u001b[01m\u001b[K%u\u001b[m\u001b[K’ expects argument of type ‘\u001b[01m\u001b[Kunsigned int\u001b[m\u001b[K’, but argument 4 has type ‘\u001b[01m\u001b[Klong unsigned int\u001b[m\u001b[K’ [\u001b[01;35m\u001b[K-Wformat=\u001b[m\u001b[K]\n",
            "         printf(\"pre_allocate: size = %Iu MB, num_of_blocks = %Iu, block_size = \u001b[01;35m\u001b[K%Iu\u001b[m\u001b[K MB \\n\",\n",
            "                                                                                \u001b[01;35m\u001b[K~~^\u001b[m\u001b[K\n",
            "                                                                                \u001b[32m\u001b[K%Ilu\u001b[m\u001b[K\n",
            "\u001b[01m\u001b[K./src/dark_cuda.c:286:37:\u001b[m\u001b[K \u001b[01;35m\u001b[Kwarning: \u001b[m\u001b[Kformat ‘\u001b[01m\u001b[K%d\u001b[m\u001b[K’ expects argument of type ‘\u001b[01m\u001b[Kint\u001b[m\u001b[K’, but argument 2 has type ‘\u001b[01m\u001b[Ksize_t {aka const long unsigned int}\u001b[m\u001b[K’ [\u001b[01;35m\u001b[K-Wformat=\u001b[m\u001b[K]\n",
            "                 printf(\" Allocated \u001b[01;35m\u001b[K%d\u001b[m\u001b[K pinned block \\n\", pinned_block_size);\n",
            "                                    \u001b[01;35m\u001b[K~^\u001b[m\u001b[K\n",
            "                                    \u001b[32m\u001b[K%ld\u001b[m\u001b[K\n",
            "\u001b[01m\u001b[K./src/dark_cuda.c:\u001b[m\u001b[K In function ‘\u001b[01m\u001b[Kcuda_make_array_pinned_preallocated\u001b[m\u001b[K’:\n",
            "\u001b[01m\u001b[K./src/dark_cuda.c:307:43:\u001b[m\u001b[K \u001b[01;35m\u001b[Kwarning: \u001b[m\u001b[Kformat ‘\u001b[01m\u001b[K%d\u001b[m\u001b[K’ expects argument of type ‘\u001b[01m\u001b[Kint\u001b[m\u001b[K’, but argument 2 has type ‘\u001b[01m\u001b[Ksize_t {aka long unsigned int}\u001b[m\u001b[K’ [\u001b[01;35m\u001b[K-Wformat=\u001b[m\u001b[K]\n",
            "             printf(\"\\n Pinned block_id = \u001b[01;35m\u001b[K%d\u001b[m\u001b[K, filled = %f %% \\n\", pinned_block_id, filled);\n",
            "                                          \u001b[01;35m\u001b[K~^\u001b[m\u001b[K\n",
            "                                          \u001b[32m\u001b[K%ld\u001b[m\u001b[K\n",
            "\u001b[01m\u001b[K./src/dark_cuda.c:322:64:\u001b[m\u001b[K \u001b[01;35m\u001b[Kwarning: \u001b[m\u001b[Kformat ‘\u001b[01m\u001b[K%d\u001b[m\u001b[K’ expects argument of type ‘\u001b[01m\u001b[Kint\u001b[m\u001b[K’, but argument 2 has type ‘\u001b[01m\u001b[Klong unsigned int\u001b[m\u001b[K’ [\u001b[01;35m\u001b[K-Wformat=\u001b[m\u001b[K]\n",
            "             printf(\"Try to allocate new pinned memory, size = \u001b[01;35m\u001b[K%d\u001b[m\u001b[K MB \\n\", \u001b[32m\u001b[Ksize / (1024 * 1024)\u001b[m\u001b[K);\n",
            "                                                               \u001b[01;35m\u001b[K~^\u001b[m\u001b[K         \u001b[32m\u001b[K~~~~~~~~~~~~~~~~~~~~\u001b[m\u001b[K\n",
            "                                                               \u001b[32m\u001b[K%ld\u001b[m\u001b[K\n",
            "\u001b[01m\u001b[K./src/dark_cuda.c:328:63:\u001b[m\u001b[K \u001b[01;35m\u001b[Kwarning: \u001b[m\u001b[Kformat ‘\u001b[01m\u001b[K%d\u001b[m\u001b[K’ expects argument of type ‘\u001b[01m\u001b[Kint\u001b[m\u001b[K’, but argument 2 has type ‘\u001b[01m\u001b[Klong unsigned int\u001b[m\u001b[K’ [\u001b[01;35m\u001b[K-Wformat=\u001b[m\u001b[K]\n",
            "             printf(\"Try to allocate new pinned BLOCK, size = \u001b[01;35m\u001b[K%d\u001b[m\u001b[K MB \\n\", \u001b[32m\u001b[Ksize / (1024 * 1024)\u001b[m\u001b[K);\n",
            "                                                              \u001b[01;35m\u001b[K~^\u001b[m\u001b[K         \u001b[32m\u001b[K~~~~~~~~~~~~~~~~~~~~\u001b[m\u001b[K\n",
            "                                                              \u001b[32m\u001b[K%ld\u001b[m\u001b[K\n",
            "gcc -Iinclude/ -I3rdparty/stb/include -DOPENCV `pkg-config --cflags opencv4 2> /dev/null || pkg-config --cflags opencv` -DGPU -I/usr/local/cuda/include/ -DCUDNN -Wall -Wfatal-errors -Wno-unused-result -Wno-unknown-pragmas -fPIC -Ofast -DOPENCV -DGPU -DCUDNN -I/usr/local/cudnn/include -c ./src/convolutional_layer.c -o obj/convolutional_layer.o\n",
            "\u001b[01m\u001b[K./src/convolutional_layer.c:\u001b[m\u001b[K In function ‘\u001b[01m\u001b[Kforward_convolutional_layer\u001b[m\u001b[K’:\n",
            "\u001b[01m\u001b[K./src/convolutional_layer.c:1204:32:\u001b[m\u001b[K \u001b[01;35m\u001b[Kwarning: \u001b[m\u001b[Kunused variable ‘\u001b[01m\u001b[Kt_intput_size\u001b[m\u001b[K’ [\u001b[01;35m\u001b[K-Wunused-variable\u001b[m\u001b[K]\n",
            "                         size_t \u001b[01;35m\u001b[Kt_intput_size\u001b[m\u001b[K = binary_transpose_align_input(k, n, state.workspace, &l.t_bit_input, ldb_align, l.bit_align);\n",
            "                                \u001b[01;35m\u001b[K^~~~~~~~~~~~~\u001b[m\u001b[K\n",
            "gcc -Iinclude/ -I3rdparty/stb/include -DOPENCV `pkg-config --cflags opencv4 2> /dev/null || pkg-config --cflags opencv` -DGPU -I/usr/local/cuda/include/ -DCUDNN -Wall -Wfatal-errors -Wno-unused-result -Wno-unknown-pragmas -fPIC -Ofast -DOPENCV -DGPU -DCUDNN -I/usr/local/cudnn/include -c ./src/list.c -o obj/list.o\n",
            "gcc -Iinclude/ -I3rdparty/stb/include -DOPENCV `pkg-config --cflags opencv4 2> /dev/null || pkg-config --cflags opencv` -DGPU -I/usr/local/cuda/include/ -DCUDNN -Wall -Wfatal-errors -Wno-unused-result -Wno-unknown-pragmas -fPIC -Ofast -DOPENCV -DGPU -DCUDNN -I/usr/local/cudnn/include -c ./src/image.c -o obj/image.o\n",
            "gcc -Iinclude/ -I3rdparty/stb/include -DOPENCV `pkg-config --cflags opencv4 2> /dev/null || pkg-config --cflags opencv` -DGPU -I/usr/local/cuda/include/ -DCUDNN -Wall -Wfatal-errors -Wno-unused-result -Wno-unknown-pragmas -fPIC -Ofast -DOPENCV -DGPU -DCUDNN -I/usr/local/cudnn/include -c ./src/activations.c -o obj/activations.o\n",
            "\u001b[01m\u001b[K./src/activations.c:\u001b[m\u001b[K In function ‘\u001b[01m\u001b[Kactivate\u001b[m\u001b[K’:\n",
            "\u001b[01m\u001b[K./src/activations.c:77:5:\u001b[m\u001b[K \u001b[01;35m\u001b[Kwarning: \u001b[m\u001b[Kenumeration value ‘\u001b[01m\u001b[KRELU6\u001b[m\u001b[K’ not handled in switch [\u001b[01;35m\u001b[K-Wswitch\u001b[m\u001b[K]\n",
            "     \u001b[01;35m\u001b[Kswitch\u001b[m\u001b[K(a){\n",
            "     \u001b[01;35m\u001b[K^~~~~~\u001b[m\u001b[K\n",
            "\u001b[01m\u001b[K./src/activations.c:77:5:\u001b[m\u001b[K \u001b[01;35m\u001b[Kwarning: \u001b[m\u001b[Kenumeration value ‘\u001b[01m\u001b[KSWISH\u001b[m\u001b[K’ not handled in switch [\u001b[01;35m\u001b[K-Wswitch\u001b[m\u001b[K]\n",
            "\u001b[01m\u001b[K./src/activations.c:77:5:\u001b[m\u001b[K \u001b[01;35m\u001b[Kwarning: \u001b[m\u001b[Kenumeration value ‘\u001b[01m\u001b[KMISH\u001b[m\u001b[K’ not handled in switch [\u001b[01;35m\u001b[K-Wswitch\u001b[m\u001b[K]\n",
            "\u001b[01m\u001b[K./src/activations.c:77:5:\u001b[m\u001b[K \u001b[01;35m\u001b[Kwarning: \u001b[m\u001b[Kenumeration value ‘\u001b[01m\u001b[KNORM_CHAN\u001b[m\u001b[K’ not handled in switch [\u001b[01;35m\u001b[K-Wswitch\u001b[m\u001b[K]\n",
            "\u001b[01m\u001b[K./src/activations.c:77:5:\u001b[m\u001b[K \u001b[01;35m\u001b[Kwarning: \u001b[m\u001b[Kenumeration value ‘\u001b[01m\u001b[KNORM_CHAN_SOFTMAX\u001b[m\u001b[K’ not handled in switch [\u001b[01;35m\u001b[K-Wswitch\u001b[m\u001b[K]\n",
            "\u001b[01m\u001b[K./src/activations.c:77:5:\u001b[m\u001b[K \u001b[01;35m\u001b[Kwarning: \u001b[m\u001b[Kenumeration value ‘\u001b[01m\u001b[KNORM_CHAN_SOFTMAX_MAXVAL\u001b[m\u001b[K’ not handled in switch [\u001b[01;35m\u001b[K-Wswitch\u001b[m\u001b[K]\n",
            "\u001b[01m\u001b[K./src/activations.c:\u001b[m\u001b[K In function ‘\u001b[01m\u001b[Kgradient\u001b[m\u001b[K’:\n",
            "\u001b[01m\u001b[K./src/activations.c:287:5:\u001b[m\u001b[K \u001b[01;35m\u001b[Kwarning: \u001b[m\u001b[Kenumeration value ‘\u001b[01m\u001b[KSWISH\u001b[m\u001b[K’ not handled in switch [\u001b[01;35m\u001b[K-Wswitch\u001b[m\u001b[K]\n",
            "     \u001b[01;35m\u001b[Kswitch\u001b[m\u001b[K(a){\n",
            "     \u001b[01;35m\u001b[K^~~~~~\u001b[m\u001b[K\n",
            "\u001b[01m\u001b[K./src/activations.c:287:5:\u001b[m\u001b[K \u001b[01;35m\u001b[Kwarning: \u001b[m\u001b[Kenumeration value ‘\u001b[01m\u001b[KMISH\u001b[m\u001b[K’ not handled in switch [\u001b[01;35m\u001b[K-Wswitch\u001b[m\u001b[K]\n",
            "gcc -Iinclude/ -I3rdparty/stb/include -DOPENCV `pkg-config --cflags opencv4 2> /dev/null || pkg-config --cflags opencv` -DGPU -I/usr/local/cuda/include/ -DCUDNN -Wall -Wfatal-errors -Wno-unused-result -Wno-unknown-pragmas -fPIC -Ofast -DOPENCV -DGPU -DCUDNN -I/usr/local/cudnn/include -c ./src/im2col.c -o obj/im2col.o\n",
            "gcc -Iinclude/ -I3rdparty/stb/include -DOPENCV `pkg-config --cflags opencv4 2> /dev/null || pkg-config --cflags opencv` -DGPU -I/usr/local/cuda/include/ -DCUDNN -Wall -Wfatal-errors -Wno-unused-result -Wno-unknown-pragmas -fPIC -Ofast -DOPENCV -DGPU -DCUDNN -I/usr/local/cudnn/include -c ./src/col2im.c -o obj/col2im.o\n",
            "gcc -Iinclude/ -I3rdparty/stb/include -DOPENCV `pkg-config --cflags opencv4 2> /dev/null || pkg-config --cflags opencv` -DGPU -I/usr/local/cuda/include/ -DCUDNN -Wall -Wfatal-errors -Wno-unused-result -Wno-unknown-pragmas -fPIC -Ofast -DOPENCV -DGPU -DCUDNN -I/usr/local/cudnn/include -c ./src/blas.c -o obj/blas.o\n",
            "\u001b[01m\u001b[K./src/blas.c:\u001b[m\u001b[K In function ‘\u001b[01m\u001b[Kbackward_shortcut_multilayer_cpu\u001b[m\u001b[K’:\n",
            "\u001b[01m\u001b[K./src/blas.c:207:21:\u001b[m\u001b[K \u001b[01;35m\u001b[Kwarning: \u001b[m\u001b[Kunused variable ‘\u001b[01m\u001b[Kout_index\u001b[m\u001b[K’ [\u001b[01;35m\u001b[K-Wunused-variable\u001b[m\u001b[K]\n",
            "                 int \u001b[01;35m\u001b[Kout_index\u001b[m\u001b[K = id;\n",
            "                     \u001b[01;35m\u001b[K^~~~~~~~~\u001b[m\u001b[K\n",
            "gcc -Iinclude/ -I3rdparty/stb/include -DOPENCV `pkg-config --cflags opencv4 2> /dev/null || pkg-config --cflags opencv` -DGPU -I/usr/local/cuda/include/ -DCUDNN -Wall -Wfatal-errors -Wno-unused-result -Wno-unknown-pragmas -fPIC -Ofast -DOPENCV -DGPU -DCUDNN -I/usr/local/cudnn/include -c ./src/crop_layer.c -o obj/crop_layer.o\n",
            "gcc -Iinclude/ -I3rdparty/stb/include -DOPENCV `pkg-config --cflags opencv4 2> /dev/null || pkg-config --cflags opencv` -DGPU -I/usr/local/cuda/include/ -DCUDNN -Wall -Wfatal-errors -Wno-unused-result -Wno-unknown-pragmas -fPIC -Ofast -DOPENCV -DGPU -DCUDNN -I/usr/local/cudnn/include -c ./src/dropout_layer.c -o obj/dropout_layer.o\n",
            "gcc -Iinclude/ -I3rdparty/stb/include -DOPENCV `pkg-config --cflags opencv4 2> /dev/null || pkg-config --cflags opencv` -DGPU -I/usr/local/cuda/include/ -DCUDNN -Wall -Wfatal-errors -Wno-unused-result -Wno-unknown-pragmas -fPIC -Ofast -DOPENCV -DGPU -DCUDNN -I/usr/local/cudnn/include -c ./src/maxpool_layer.c -o obj/maxpool_layer.o\n",
            "gcc -Iinclude/ -I3rdparty/stb/include -DOPENCV `pkg-config --cflags opencv4 2> /dev/null || pkg-config --cflags opencv` -DGPU -I/usr/local/cuda/include/ -DCUDNN -Wall -Wfatal-errors -Wno-unused-result -Wno-unknown-pragmas -fPIC -Ofast -DOPENCV -DGPU -DCUDNN -I/usr/local/cudnn/include -c ./src/softmax_layer.c -o obj/softmax_layer.o\n",
            "gcc -Iinclude/ -I3rdparty/stb/include -DOPENCV `pkg-config --cflags opencv4 2> /dev/null || pkg-config --cflags opencv` -DGPU -I/usr/local/cuda/include/ -DCUDNN -Wall -Wfatal-errors -Wno-unused-result -Wno-unknown-pragmas -fPIC -Ofast -DOPENCV -DGPU -DCUDNN -I/usr/local/cudnn/include -c ./src/data.c -o obj/data.o\n",
            "\u001b[01m\u001b[K./src/data.c:\u001b[m\u001b[K In function ‘\u001b[01m\u001b[Kload_data_detection\u001b[m\u001b[K’:\n",
            "\u001b[01m\u001b[K./src/data.c:1134:24:\u001b[m\u001b[K \u001b[01;35m\u001b[Kwarning: \u001b[m\u001b[Kunused variable ‘\u001b[01m\u001b[Kx\u001b[m\u001b[K’ [\u001b[01;35m\u001b[K-Wunused-variable\u001b[m\u001b[K]\n",
            "                 int k, \u001b[01;35m\u001b[Kx\u001b[m\u001b[K, y;\n",
            "                        \u001b[01;35m\u001b[K^\u001b[m\u001b[K\n",
            "\u001b[01m\u001b[K./src/data.c:984:43:\u001b[m\u001b[K \u001b[01;35m\u001b[Kwarning: \u001b[m\u001b[Kvariable ‘\u001b[01m\u001b[Kr_scale\u001b[m\u001b[K’ set but not used [\u001b[01;35m\u001b[K-Wunused-but-set-variable\u001b[m\u001b[K]\n",
            "     float r1 = 0, r2 = 0, r3 = 0, r4 = 0, \u001b[01;35m\u001b[Kr_scale\u001b[m\u001b[K = 0;\n",
            "                                           \u001b[01;35m\u001b[K^~~~~~~\u001b[m\u001b[K\n",
            "gcc -Iinclude/ -I3rdparty/stb/include -DOPENCV `pkg-config --cflags opencv4 2> /dev/null || pkg-config --cflags opencv` -DGPU -I/usr/local/cuda/include/ -DCUDNN -Wall -Wfatal-errors -Wno-unused-result -Wno-unknown-pragmas -fPIC -Ofast -DOPENCV -DGPU -DCUDNN -I/usr/local/cudnn/include -c ./src/matrix.c -o obj/matrix.o\n",
            "gcc -Iinclude/ -I3rdparty/stb/include -DOPENCV `pkg-config --cflags opencv4 2> /dev/null || pkg-config --cflags opencv` -DGPU -I/usr/local/cuda/include/ -DCUDNN -Wall -Wfatal-errors -Wno-unused-result -Wno-unknown-pragmas -fPIC -Ofast -DOPENCV -DGPU -DCUDNN -I/usr/local/cudnn/include -c ./src/network.c -o obj/network.o\n",
            "\u001b[01m\u001b[K./src/network.c:\u001b[m\u001b[K In function ‘\u001b[01m\u001b[Kresize_network\u001b[m\u001b[K’:\n",
            "\u001b[01m\u001b[K./src/network.c:610:42:\u001b[m\u001b[K \u001b[01;35m\u001b[Kwarning: \u001b[m\u001b[Kpassing argument 1 of ‘\u001b[01m\u001b[KcudaHostAlloc\u001b[m\u001b[K’ from incompatible pointer type [\u001b[01;35m\u001b[K-Wincompatible-pointer-types\u001b[m\u001b[K]\n",
            "         if (cudaSuccess == cudaHostAlloc(\u001b[01;35m\u001b[K&\u001b[m\u001b[Knet->input_pinned_cpu, size * sizeof(float), cudaHostRegisterMapped))\n",
            "                                          \u001b[01;35m\u001b[K^\u001b[m\u001b[K\n",
            "In file included from \u001b[01m\u001b[K/usr/local/cuda/include/cuda_runtime.h:96:0\u001b[m\u001b[K,\n",
            "                 from \u001b[01m\u001b[Kinclude/darknet.h:41\u001b[m\u001b[K,\n",
            "                 from \u001b[01m\u001b[K./src/network.c:1\u001b[m\u001b[K:\n",
            "\u001b[01m\u001b[K/usr/local/cuda/include/cuda_runtime_api.h:4391:39:\u001b[m\u001b[K \u001b[01;36m\u001b[Knote: \u001b[m\u001b[Kexpected ‘\u001b[01m\u001b[Kvoid **\u001b[m\u001b[K’ but argument is of type ‘\u001b[01m\u001b[Kfloat **\u001b[m\u001b[K’\n",
            " extern __host__ cudaError_t CUDARTAPI \u001b[01;36m\u001b[KcudaHostAlloc\u001b[m\u001b[K(void **pHost, size_t size, unsigned int flags);\n",
            "                                       \u001b[01;36m\u001b[K^~~~~~~~~~~~~\u001b[m\u001b[K\n",
            "gcc -Iinclude/ -I3rdparty/stb/include -DOPENCV `pkg-config --cflags opencv4 2> /dev/null || pkg-config --cflags opencv` -DGPU -I/usr/local/cuda/include/ -DCUDNN -Wall -Wfatal-errors -Wno-unused-result -Wno-unknown-pragmas -fPIC -Ofast -DOPENCV -DGPU -DCUDNN -I/usr/local/cudnn/include -c ./src/connected_layer.c -o obj/connected_layer.o\n",
            "\u001b[01m\u001b[K./src/connected_layer.c:\u001b[m\u001b[K In function ‘\u001b[01m\u001b[Kforward_connected_layer_gpu\u001b[m\u001b[K’:\n",
            "\u001b[01m\u001b[K./src/connected_layer.c:346:11:\u001b[m\u001b[K \u001b[01;35m\u001b[Kwarning: \u001b[m\u001b[Kunused variable ‘\u001b[01m\u001b[Kone\u001b[m\u001b[K’ [\u001b[01;35m\u001b[K-Wunused-variable\u001b[m\u001b[K]\n",
            "     float \u001b[01;35m\u001b[Kone\u001b[m\u001b[K = 1;    // alpha[0], beta[0]\n",
            "           \u001b[01;35m\u001b[K^~~\u001b[m\u001b[K\n",
            "\u001b[01m\u001b[K./src/connected_layer.c:344:13:\u001b[m\u001b[K \u001b[01;35m\u001b[Kwarning: \u001b[m\u001b[Kunused variable ‘\u001b[01m\u001b[Kc\u001b[m\u001b[K’ [\u001b[01;35m\u001b[K-Wunused-variable\u001b[m\u001b[K]\n",
            "     float * \u001b[01;35m\u001b[Kc\u001b[m\u001b[K = l.output_gpu;\n",
            "             \u001b[01;35m\u001b[K^\u001b[m\u001b[K\n",
            "\u001b[01m\u001b[K./src/connected_layer.c:343:13:\u001b[m\u001b[K \u001b[01;35m\u001b[Kwarning: \u001b[m\u001b[Kunused variable ‘\u001b[01m\u001b[Kb\u001b[m\u001b[K’ [\u001b[01;35m\u001b[K-Wunused-variable\u001b[m\u001b[K]\n",
            "     float * \u001b[01;35m\u001b[Kb\u001b[m\u001b[K = l.weights_gpu;\n",
            "             \u001b[01;35m\u001b[K^\u001b[m\u001b[K\n",
            "\u001b[01m\u001b[K./src/connected_layer.c:342:13:\u001b[m\u001b[K \u001b[01;35m\u001b[Kwarning: \u001b[m\u001b[Kunused variable ‘\u001b[01m\u001b[Ka\u001b[m\u001b[K’ [\u001b[01;35m\u001b[K-Wunused-variable\u001b[m\u001b[K]\n",
            "     float * \u001b[01;35m\u001b[Ka\u001b[m\u001b[K = state.input;\n",
            "             \u001b[01;35m\u001b[K^\u001b[m\u001b[K\n",
            "\u001b[01m\u001b[K./src/connected_layer.c:341:9:\u001b[m\u001b[K \u001b[01;35m\u001b[Kwarning: \u001b[m\u001b[Kunused variable ‘\u001b[01m\u001b[Kn\u001b[m\u001b[K’ [\u001b[01;35m\u001b[K-Wunused-variable\u001b[m\u001b[K]\n",
            "     int \u001b[01;35m\u001b[Kn\u001b[m\u001b[K = l.outputs;\n",
            "         \u001b[01;35m\u001b[K^\u001b[m\u001b[K\n",
            "\u001b[01m\u001b[K./src/connected_layer.c:340:9:\u001b[m\u001b[K \u001b[01;35m\u001b[Kwarning: \u001b[m\u001b[Kunused variable ‘\u001b[01m\u001b[Kk\u001b[m\u001b[K’ [\u001b[01;35m\u001b[K-Wunused-variable\u001b[m\u001b[K]\n",
            "     int \u001b[01;35m\u001b[Kk\u001b[m\u001b[K = l.inputs;\n",
            "         \u001b[01;35m\u001b[K^\u001b[m\u001b[K\n",
            "\u001b[01m\u001b[K./src/connected_layer.c:339:9:\u001b[m\u001b[K \u001b[01;35m\u001b[Kwarning: \u001b[m\u001b[Kunused variable ‘\u001b[01m\u001b[Km\u001b[m\u001b[K’ [\u001b[01;35m\u001b[K-Wunused-variable\u001b[m\u001b[K]\n",
            "     int \u001b[01;35m\u001b[Km\u001b[m\u001b[K = l.batch;\n",
            "         \u001b[01;35m\u001b[K^\u001b[m\u001b[K\n",
            "gcc -Iinclude/ -I3rdparty/stb/include -DOPENCV `pkg-config --cflags opencv4 2> /dev/null || pkg-config --cflags opencv` -DGPU -I/usr/local/cuda/include/ -DCUDNN -Wall -Wfatal-errors -Wno-unused-result -Wno-unknown-pragmas -fPIC -Ofast -DOPENCV -DGPU -DCUDNN -I/usr/local/cudnn/include -c ./src/cost_layer.c -o obj/cost_layer.o\n",
            "gcc -Iinclude/ -I3rdparty/stb/include -DOPENCV `pkg-config --cflags opencv4 2> /dev/null || pkg-config --cflags opencv` -DGPU -I/usr/local/cuda/include/ -DCUDNN -Wall -Wfatal-errors -Wno-unused-result -Wno-unknown-pragmas -fPIC -Ofast -DOPENCV -DGPU -DCUDNN -I/usr/local/cudnn/include -c ./src/parser.c -o obj/parser.o\n",
            "\u001b[01m\u001b[K./src/parser.c:\u001b[m\u001b[K In function ‘\u001b[01m\u001b[Kparse_network_cfg_custom\u001b[m\u001b[K’:\n",
            "\u001b[01m\u001b[K./src/parser.c:1573:42:\u001b[m\u001b[K \u001b[01;35m\u001b[Kwarning: \u001b[m\u001b[Kpassing argument 1 of ‘\u001b[01m\u001b[KcudaHostAlloc\u001b[m\u001b[K’ from incompatible pointer type [\u001b[01;35m\u001b[K-Wincompatible-pointer-types\u001b[m\u001b[K]\n",
            "         if (cudaSuccess == cudaHostAlloc(\u001b[01;35m\u001b[K&\u001b[m\u001b[Knet.input_pinned_cpu, size * sizeof(float), cudaHostRegisterMapped)) net.input_pinned_cpu_flag = 1;\n",
            "                                          \u001b[01;35m\u001b[K^\u001b[m\u001b[K\n",
            "In file included from \u001b[01m\u001b[K/usr/local/cuda/include/cuda_runtime.h:96:0\u001b[m\u001b[K,\n",
            "                 from \u001b[01m\u001b[Kinclude/darknet.h:41\u001b[m\u001b[K,\n",
            "                 from \u001b[01m\u001b[K./src/activations.h:3\u001b[m\u001b[K,\n",
            "                 from \u001b[01m\u001b[K./src/activation_layer.h:4\u001b[m\u001b[K,\n",
            "                 from \u001b[01m\u001b[K./src/parser.c:6\u001b[m\u001b[K:\n",
            "\u001b[01m\u001b[K/usr/local/cuda/include/cuda_runtime_api.h:4391:39:\u001b[m\u001b[K \u001b[01;36m\u001b[Knote: \u001b[m\u001b[Kexpected ‘\u001b[01m\u001b[Kvoid **\u001b[m\u001b[K’ but argument is of type ‘\u001b[01m\u001b[Kfloat **\u001b[m\u001b[K’\n",
            " extern __host__ cudaError_t CUDARTAPI \u001b[01;36m\u001b[KcudaHostAlloc\u001b[m\u001b[K(void **pHost, size_t size, unsigned int flags);\n",
            "                                       \u001b[01;36m\u001b[K^~~~~~~~~~~~~\u001b[m\u001b[K\n",
            "gcc -Iinclude/ -I3rdparty/stb/include -DOPENCV `pkg-config --cflags opencv4 2> /dev/null || pkg-config --cflags opencv` -DGPU -I/usr/local/cuda/include/ -DCUDNN -Wall -Wfatal-errors -Wno-unused-result -Wno-unknown-pragmas -fPIC -Ofast -DOPENCV -DGPU -DCUDNN -I/usr/local/cudnn/include -c ./src/option_list.c -o obj/option_list.o\n",
            "gcc -Iinclude/ -I3rdparty/stb/include -DOPENCV `pkg-config --cflags opencv4 2> /dev/null || pkg-config --cflags opencv` -DGPU -I/usr/local/cuda/include/ -DCUDNN -Wall -Wfatal-errors -Wno-unused-result -Wno-unknown-pragmas -fPIC -Ofast -DOPENCV -DGPU -DCUDNN -I/usr/local/cudnn/include -c ./src/darknet.c -o obj/darknet.o\n",
            "gcc -Iinclude/ -I3rdparty/stb/include -DOPENCV `pkg-config --cflags opencv4 2> /dev/null || pkg-config --cflags opencv` -DGPU -I/usr/local/cuda/include/ -DCUDNN -Wall -Wfatal-errors -Wno-unused-result -Wno-unknown-pragmas -fPIC -Ofast -DOPENCV -DGPU -DCUDNN -I/usr/local/cudnn/include -c ./src/detection_layer.c -o obj/detection_layer.o\n",
            "gcc -Iinclude/ -I3rdparty/stb/include -DOPENCV `pkg-config --cflags opencv4 2> /dev/null || pkg-config --cflags opencv` -DGPU -I/usr/local/cuda/include/ -DCUDNN -Wall -Wfatal-errors -Wno-unused-result -Wno-unknown-pragmas -fPIC -Ofast -DOPENCV -DGPU -DCUDNN -I/usr/local/cudnn/include -c ./src/captcha.c -o obj/captcha.o\n",
            "gcc -Iinclude/ -I3rdparty/stb/include -DOPENCV `pkg-config --cflags opencv4 2> /dev/null || pkg-config --cflags opencv` -DGPU -I/usr/local/cuda/include/ -DCUDNN -Wall -Wfatal-errors -Wno-unused-result -Wno-unknown-pragmas -fPIC -Ofast -DOPENCV -DGPU -DCUDNN -I/usr/local/cudnn/include -c ./src/route_layer.c -o obj/route_layer.o\n",
            "gcc -Iinclude/ -I3rdparty/stb/include -DOPENCV `pkg-config --cflags opencv4 2> /dev/null || pkg-config --cflags opencv` -DGPU -I/usr/local/cuda/include/ -DCUDNN -Wall -Wfatal-errors -Wno-unused-result -Wno-unknown-pragmas -fPIC -Ofast -DOPENCV -DGPU -DCUDNN -I/usr/local/cudnn/include -c ./src/writing.c -o obj/writing.o\n",
            "gcc -Iinclude/ -I3rdparty/stb/include -DOPENCV `pkg-config --cflags opencv4 2> /dev/null || pkg-config --cflags opencv` -DGPU -I/usr/local/cuda/include/ -DCUDNN -Wall -Wfatal-errors -Wno-unused-result -Wno-unknown-pragmas -fPIC -Ofast -DOPENCV -DGPU -DCUDNN -I/usr/local/cudnn/include -c ./src/box.c -o obj/box.o\n",
            "\u001b[01m\u001b[K./src/box.c:\u001b[m\u001b[K In function ‘\u001b[01m\u001b[Kbox_iou_kind\u001b[m\u001b[K’:\n",
            "\u001b[01m\u001b[K./src/box.c:154:5:\u001b[m\u001b[K \u001b[01;35m\u001b[Kwarning: \u001b[m\u001b[Kenumeration value ‘\u001b[01m\u001b[KMSE\u001b[m\u001b[K’ not handled in switch [\u001b[01;35m\u001b[K-Wswitch\u001b[m\u001b[K]\n",
            "     \u001b[01;35m\u001b[Kswitch\u001b[m\u001b[K(iou_kind) {\n",
            "     \u001b[01;35m\u001b[K^~~~~~\u001b[m\u001b[K\n",
            "\u001b[01m\u001b[K./src/box.c:\u001b[m\u001b[K In function ‘\u001b[01m\u001b[Kdiounms_sort\u001b[m\u001b[K’:\n",
            "\u001b[01m\u001b[K./src/box.c:898:27:\u001b[m\u001b[K \u001b[01;35m\u001b[Kwarning: \u001b[m\u001b[Kunused variable ‘\u001b[01m\u001b[Kbeta_prob\u001b[m\u001b[K’ [\u001b[01;35m\u001b[K-Wunused-variable\u001b[m\u001b[K]\n",
            "                     float \u001b[01;35m\u001b[Kbeta_prob\u001b[m\u001b[K = pow(dets[j].prob[k], 2) / sum_prob;\n",
            "                           \u001b[01;35m\u001b[K^~~~~~~~~\u001b[m\u001b[K\n",
            "\u001b[01m\u001b[K./src/box.c:897:27:\u001b[m\u001b[K \u001b[01;35m\u001b[Kwarning: \u001b[m\u001b[Kunused variable ‘\u001b[01m\u001b[Kalpha_prob\u001b[m\u001b[K’ [\u001b[01;35m\u001b[K-Wunused-variable\u001b[m\u001b[K]\n",
            "                     float \u001b[01;35m\u001b[Kalpha_prob\u001b[m\u001b[K = pow(dets[i].prob[k], 2) / sum_prob;\n",
            "                           \u001b[01;35m\u001b[K^~~~~~~~~~\u001b[m\u001b[K\n",
            "gcc -Iinclude/ -I3rdparty/stb/include -DOPENCV `pkg-config --cflags opencv4 2> /dev/null || pkg-config --cflags opencv` -DGPU -I/usr/local/cuda/include/ -DCUDNN -Wall -Wfatal-errors -Wno-unused-result -Wno-unknown-pragmas -fPIC -Ofast -DOPENCV -DGPU -DCUDNN -I/usr/local/cudnn/include -c ./src/nightmare.c -o obj/nightmare.o\n",
            "gcc -Iinclude/ -I3rdparty/stb/include -DOPENCV `pkg-config --cflags opencv4 2> /dev/null || pkg-config --cflags opencv` -DGPU -I/usr/local/cuda/include/ -DCUDNN -Wall -Wfatal-errors -Wno-unused-result -Wno-unknown-pragmas -fPIC -Ofast -DOPENCV -DGPU -DCUDNN -I/usr/local/cudnn/include -c ./src/normalization_layer.c -o obj/normalization_layer.o\n",
            "gcc -Iinclude/ -I3rdparty/stb/include -DOPENCV `pkg-config --cflags opencv4 2> /dev/null || pkg-config --cflags opencv` -DGPU -I/usr/local/cuda/include/ -DCUDNN -Wall -Wfatal-errors -Wno-unused-result -Wno-unknown-pragmas -fPIC -Ofast -DOPENCV -DGPU -DCUDNN -I/usr/local/cudnn/include -c ./src/avgpool_layer.c -o obj/avgpool_layer.o\n",
            "gcc -Iinclude/ -I3rdparty/stb/include -DOPENCV `pkg-config --cflags opencv4 2> /dev/null || pkg-config --cflags opencv` -DGPU -I/usr/local/cuda/include/ -DCUDNN -Wall -Wfatal-errors -Wno-unused-result -Wno-unknown-pragmas -fPIC -Ofast -DOPENCV -DGPU -DCUDNN -I/usr/local/cudnn/include -c ./src/coco.c -o obj/coco.o\n",
            "\u001b[01m\u001b[K./src/coco.c:\u001b[m\u001b[K In function ‘\u001b[01m\u001b[Kvalidate_coco_recall\u001b[m\u001b[K’:\n",
            "\u001b[01m\u001b[K./src/coco.c:248:11:\u001b[m\u001b[K \u001b[01;35m\u001b[Kwarning: \u001b[m\u001b[Kunused variable ‘\u001b[01m\u001b[Kbase\u001b[m\u001b[K’ [\u001b[01;35m\u001b[K-Wunused-variable\u001b[m\u001b[K]\n",
            "     char *\u001b[01;35m\u001b[Kbase\u001b[m\u001b[K = \"results/comp4_det_test_\";\n",
            "           \u001b[01;35m\u001b[K^~~~\u001b[m\u001b[K\n",
            "gcc -Iinclude/ -I3rdparty/stb/include -DOPENCV `pkg-config --cflags opencv4 2> /dev/null || pkg-config --cflags opencv` -DGPU -I/usr/local/cuda/include/ -DCUDNN -Wall -Wfatal-errors -Wno-unused-result -Wno-unknown-pragmas -fPIC -Ofast -DOPENCV -DGPU -DCUDNN -I/usr/local/cudnn/include -c ./src/dice.c -o obj/dice.o\n",
            "gcc -Iinclude/ -I3rdparty/stb/include -DOPENCV `pkg-config --cflags opencv4 2> /dev/null || pkg-config --cflags opencv` -DGPU -I/usr/local/cuda/include/ -DCUDNN -Wall -Wfatal-errors -Wno-unused-result -Wno-unknown-pragmas -fPIC -Ofast -DOPENCV -DGPU -DCUDNN -I/usr/local/cudnn/include -c ./src/yolo.c -o obj/yolo.o\n",
            "gcc -Iinclude/ -I3rdparty/stb/include -DOPENCV `pkg-config --cflags opencv4 2> /dev/null || pkg-config --cflags opencv` -DGPU -I/usr/local/cuda/include/ -DCUDNN -Wall -Wfatal-errors -Wno-unused-result -Wno-unknown-pragmas -fPIC -Ofast -DOPENCV -DGPU -DCUDNN -I/usr/local/cudnn/include -c ./src/detector.c -o obj/detector.o\n",
            "\u001b[01m\u001b[K./src/detector.c:\u001b[m\u001b[K In function ‘\u001b[01m\u001b[Kprint_cocos\u001b[m\u001b[K’:\n",
            "\u001b[01m\u001b[K./src/detector.c:451:29:\u001b[m\u001b[K \u001b[01;35m\u001b[Kwarning: \u001b[m\u001b[Kformat not a string literal and no format arguments [\u001b[01;35m\u001b[K-Wformat-security\u001b[m\u001b[K]\n",
            "                 fprintf(fp, \u001b[01;35m\u001b[Kbuff\u001b[m\u001b[K);\n",
            "                             \u001b[01;35m\u001b[K^~~~\u001b[m\u001b[K\n",
            "\u001b[01m\u001b[K./src/detector.c:\u001b[m\u001b[K In function ‘\u001b[01m\u001b[Keliminate_bdd\u001b[m\u001b[K’:\n",
            "\u001b[01m\u001b[K./src/detector.c:544:21:\u001b[m\u001b[K \u001b[01;35m\u001b[Kwarning: \u001b[m\u001b[Kstatement with no effect [\u001b[01;35m\u001b[K-Wunused-value\u001b[m\u001b[K]\n",
            "                     \u001b[01;35m\u001b[Kfor\u001b[m\u001b[K (k; buf[k + n] != '\\0'; k++)\n",
            "                     \u001b[01;35m\u001b[K^~~\u001b[m\u001b[K\n",
            "\u001b[01m\u001b[K./src/detector.c:\u001b[m\u001b[K In function ‘\u001b[01m\u001b[Kvalidate_detector\u001b[m\u001b[K’:\n",
            "\u001b[01m\u001b[K./src/detector.c:657:13:\u001b[m\u001b[K \u001b[01;35m\u001b[Kwarning: \u001b[m\u001b[Kunused variable ‘\u001b[01m\u001b[Kmkd2\u001b[m\u001b[K’ [\u001b[01;35m\u001b[K-Wunused-variable\u001b[m\u001b[K]\n",
            "         int \u001b[01;35m\u001b[Kmkd2\u001b[m\u001b[K = make_directory(buff2, 0777);\n",
            "             \u001b[01;35m\u001b[K^~~~\u001b[m\u001b[K\n",
            "\u001b[01m\u001b[K./src/detector.c:655:13:\u001b[m\u001b[K \u001b[01;35m\u001b[Kwarning: \u001b[m\u001b[Kunused variable ‘\u001b[01m\u001b[Kmkd\u001b[m\u001b[K’ [\u001b[01;35m\u001b[K-Wunused-variable\u001b[m\u001b[K]\n",
            "         int \u001b[01;35m\u001b[Kmkd\u001b[m\u001b[K = make_directory(buff, 0777);\n",
            "             \u001b[01;35m\u001b[K^~~\u001b[m\u001b[K\n",
            "\u001b[01m\u001b[K./src/detector.c:\u001b[m\u001b[K In function ‘\u001b[01m\u001b[Kvalidate_detector_map\u001b[m\u001b[K’:\n",
            "\u001b[01m\u001b[K./src/detector.c:1276:15:\u001b[m\u001b[K \u001b[01;35m\u001b[Kwarning: \u001b[m\u001b[Kunused variable ‘\u001b[01m\u001b[Kclass_recall\u001b[m\u001b[K’ [\u001b[01;35m\u001b[K-Wunused-variable\u001b[m\u001b[K]\n",
            "         float \u001b[01;35m\u001b[Kclass_recall\u001b[m\u001b[K = (float)tp_for_thresh_per_class[i] / ((float)tp_for_thresh_per_class[i] + (float)(truth_classes_count[i] - tp_for_thresh_per_class[i]));\n",
            "               \u001b[01;35m\u001b[K^~~~~~~~~~~~\u001b[m\u001b[K\n",
            "\u001b[01m\u001b[K./src/detector.c:1275:15:\u001b[m\u001b[K \u001b[01;35m\u001b[Kwarning: \u001b[m\u001b[Kunused variable ‘\u001b[01m\u001b[Kclass_precision\u001b[m\u001b[K’ [\u001b[01;35m\u001b[K-Wunused-variable\u001b[m\u001b[K]\n",
            "         float \u001b[01;35m\u001b[Kclass_precision\u001b[m\u001b[K = (float)tp_for_thresh_per_class[i] / ((float)tp_for_thresh_per_class[i] + (float)fp_for_thresh_per_class[i]);\n",
            "               \u001b[01;35m\u001b[K^~~~~~~~~~~~~~~\u001b[m\u001b[K\n",
            "\u001b[01m\u001b[K./src/detector.c:\u001b[m\u001b[K In function ‘\u001b[01m\u001b[Kdraw_object\u001b[m\u001b[K’:\n",
            "\u001b[01m\u001b[K./src/detector.c:1792:19:\u001b[m\u001b[K \u001b[01;35m\u001b[Kwarning: \u001b[m\u001b[Kunused variable ‘\u001b[01m\u001b[Kinv_loss\u001b[m\u001b[K’ [\u001b[01;35m\u001b[K-Wunused-variable\u001b[m\u001b[K]\n",
            "             float \u001b[01;35m\u001b[Kinv_loss\u001b[m\u001b[K = 1.0 / max_val_cmp(0.01, avg_loss);\n",
            "                   \u001b[01;35m\u001b[K^~~~~~~~\u001b[m\u001b[K\n",
            "gcc -Iinclude/ -I3rdparty/stb/include -DOPENCV `pkg-config --cflags opencv4 2> /dev/null || pkg-config --cflags opencv` -DGPU -I/usr/local/cuda/include/ -DCUDNN -Wall -Wfatal-errors -Wno-unused-result -Wno-unknown-pragmas -fPIC -Ofast -DOPENCV -DGPU -DCUDNN -I/usr/local/cudnn/include -c ./src/layer.c -o obj/layer.o\n",
            "\u001b[01m\u001b[K./src/layer.c:\u001b[m\u001b[K In function ‘\u001b[01m\u001b[Kfree_layer_custom\u001b[m\u001b[K’:\n",
            "\u001b[01m\u001b[K./src/layer.c:191:9:\u001b[m\u001b[K \u001b[01;35m\u001b[Kwarning: \u001b[m\u001b[Kthis ‘\u001b[01m\u001b[Kif\u001b[m\u001b[K’ clause does not guard... [\u001b[01;35m\u001b[K-Wmisleading-indentation\u001b[m\u001b[K]\n",
            "         \u001b[01;35m\u001b[Kif\u001b[m\u001b[K (l.x_gpu)                   cuda_free(l.x_gpu);  l.x_gpu = NULL;\n",
            "         \u001b[01;35m\u001b[K^~\u001b[m\u001b[K\n",
            "\u001b[01m\u001b[K./src/layer.c:191:61:\u001b[m\u001b[K \u001b[01;36m\u001b[Knote: \u001b[m\u001b[K...this statement, but the latter is misleadingly indented as if it were guarded by the ‘\u001b[01m\u001b[Kif\u001b[m\u001b[K’\n",
            "         if (l.x_gpu)                   cuda_free(l.x_gpu);  \u001b[01;36m\u001b[Kl\u001b[m\u001b[K.x_gpu = NULL;\n",
            "                                                             \u001b[01;36m\u001b[K^\u001b[m\u001b[K\n",
            "gcc -Iinclude/ -I3rdparty/stb/include -DOPENCV `pkg-config --cflags opencv4 2> /dev/null || pkg-config --cflags opencv` -DGPU -I/usr/local/cuda/include/ -DCUDNN -Wall -Wfatal-errors -Wno-unused-result -Wno-unknown-pragmas -fPIC -Ofast -DOPENCV -DGPU -DCUDNN -I/usr/local/cudnn/include -c ./src/compare.c -o obj/compare.o\n",
            "gcc -Iinclude/ -I3rdparty/stb/include -DOPENCV `pkg-config --cflags opencv4 2> /dev/null || pkg-config --cflags opencv` -DGPU -I/usr/local/cuda/include/ -DCUDNN -Wall -Wfatal-errors -Wno-unused-result -Wno-unknown-pragmas -fPIC -Ofast -DOPENCV -DGPU -DCUDNN -I/usr/local/cudnn/include -c ./src/classifier.c -o obj/classifier.o\n",
            "\u001b[01m\u001b[K./src/classifier.c:\u001b[m\u001b[K In function ‘\u001b[01m\u001b[Ktrain_classifier\u001b[m\u001b[K’:\n",
            "\u001b[01m\u001b[K./src/classifier.c:138:9:\u001b[m\u001b[K \u001b[01;35m\u001b[Kwarning: \u001b[m\u001b[Kunused variable ‘\u001b[01m\u001b[Kcount\u001b[m\u001b[K’ [\u001b[01;35m\u001b[K-Wunused-variable\u001b[m\u001b[K]\n",
            "     int \u001b[01;35m\u001b[Kcount\u001b[m\u001b[K = 0;\n",
            "         \u001b[01;35m\u001b[K^~~~~\u001b[m\u001b[K\n",
            "\u001b[01m\u001b[K./src/classifier.c:\u001b[m\u001b[K In function ‘\u001b[01m\u001b[Kpredict_classifier\u001b[m\u001b[K’:\n",
            "\u001b[01m\u001b[K./src/classifier.c:831:13:\u001b[m\u001b[K \u001b[01;35m\u001b[Kwarning: \u001b[m\u001b[Kunused variable ‘\u001b[01m\u001b[Ktime\u001b[m\u001b[K’ [\u001b[01;35m\u001b[K-Wunused-variable\u001b[m\u001b[K]\n",
            "     clock_t \u001b[01;35m\u001b[Ktime\u001b[m\u001b[K;\n",
            "             \u001b[01;35m\u001b[K^~~~\u001b[m\u001b[K\n",
            "\u001b[01m\u001b[K./src/classifier.c:\u001b[m\u001b[K In function ‘\u001b[01m\u001b[Kdemo_classifier\u001b[m\u001b[K’:\n",
            "\u001b[01m\u001b[K./src/classifier.c:1261:49:\u001b[m\u001b[K \u001b[01;35m\u001b[Kwarning: \u001b[m\u001b[Kunused variable ‘\u001b[01m\u001b[Ktval_result\u001b[m\u001b[K’ [\u001b[01;35m\u001b[K-Wunused-variable\u001b[m\u001b[K]\n",
            "         struct timeval tval_before, tval_after, \u001b[01;35m\u001b[Ktval_result\u001b[m\u001b[K;\n",
            "                                                 \u001b[01;35m\u001b[K^~~~~~~~~~~\u001b[m\u001b[K\n",
            "\u001b[01m\u001b[K./src/classifier.c:1261:37:\u001b[m\u001b[K \u001b[01;35m\u001b[Kwarning: \u001b[m\u001b[Kunused variable ‘\u001b[01m\u001b[Ktval_after\u001b[m\u001b[K’ [\u001b[01;35m\u001b[K-Wunused-variable\u001b[m\u001b[K]\n",
            "         struct timeval tval_before, \u001b[01;35m\u001b[Ktval_after\u001b[m\u001b[K, tval_result;\n",
            "                                     \u001b[01;35m\u001b[K^~~~~~~~~~\u001b[m\u001b[K\n",
            "gcc -Iinclude/ -I3rdparty/stb/include -DOPENCV `pkg-config --cflags opencv4 2> /dev/null || pkg-config --cflags opencv` -DGPU -I/usr/local/cuda/include/ -DCUDNN -Wall -Wfatal-errors -Wno-unused-result -Wno-unknown-pragmas -fPIC -Ofast -DOPENCV -DGPU -DCUDNN -I/usr/local/cudnn/include -c ./src/local_layer.c -o obj/local_layer.o\n",
            "gcc -Iinclude/ -I3rdparty/stb/include -DOPENCV `pkg-config --cflags opencv4 2> /dev/null || pkg-config --cflags opencv` -DGPU -I/usr/local/cuda/include/ -DCUDNN -Wall -Wfatal-errors -Wno-unused-result -Wno-unknown-pragmas -fPIC -Ofast -DOPENCV -DGPU -DCUDNN -I/usr/local/cudnn/include -c ./src/swag.c -o obj/swag.o\n",
            "gcc -Iinclude/ -I3rdparty/stb/include -DOPENCV `pkg-config --cflags opencv4 2> /dev/null || pkg-config --cflags opencv` -DGPU -I/usr/local/cuda/include/ -DCUDNN -Wall -Wfatal-errors -Wno-unused-result -Wno-unknown-pragmas -fPIC -Ofast -DOPENCV -DGPU -DCUDNN -I/usr/local/cudnn/include -c ./src/shortcut_layer.c -o obj/shortcut_layer.o\n",
            "\u001b[01m\u001b[K./src/shortcut_layer.c:\u001b[m\u001b[K In function ‘\u001b[01m\u001b[Kmake_shortcut_layer\u001b[m\u001b[K’:\n",
            "\u001b[01m\u001b[K./src/shortcut_layer.c:55:15:\u001b[m\u001b[K \u001b[01;35m\u001b[Kwarning: \u001b[m\u001b[Kunused variable ‘\u001b[01m\u001b[Kscale\u001b[m\u001b[K’ [\u001b[01;35m\u001b[K-Wunused-variable\u001b[m\u001b[K]\n",
            "         float \u001b[01;35m\u001b[Kscale\u001b[m\u001b[K = sqrt(2. / l.nweights);\n",
            "               \u001b[01;35m\u001b[K^~~~~\u001b[m\u001b[K\n",
            "gcc -Iinclude/ -I3rdparty/stb/include -DOPENCV `pkg-config --cflags opencv4 2> /dev/null || pkg-config --cflags opencv` -DGPU -I/usr/local/cuda/include/ -DCUDNN -Wall -Wfatal-errors -Wno-unused-result -Wno-unknown-pragmas -fPIC -Ofast -DOPENCV -DGPU -DCUDNN -I/usr/local/cudnn/include -c ./src/activation_layer.c -o obj/activation_layer.o\n",
            "gcc -Iinclude/ -I3rdparty/stb/include -DOPENCV `pkg-config --cflags opencv4 2> /dev/null || pkg-config --cflags opencv` -DGPU -I/usr/local/cuda/include/ -DCUDNN -Wall -Wfatal-errors -Wno-unused-result -Wno-unknown-pragmas -fPIC -Ofast -DOPENCV -DGPU -DCUDNN -I/usr/local/cudnn/include -c ./src/rnn_layer.c -o obj/rnn_layer.o\n",
            "gcc -Iinclude/ -I3rdparty/stb/include -DOPENCV `pkg-config --cflags opencv4 2> /dev/null || pkg-config --cflags opencv` -DGPU -I/usr/local/cuda/include/ -DCUDNN -Wall -Wfatal-errors -Wno-unused-result -Wno-unknown-pragmas -fPIC -Ofast -DOPENCV -DGPU -DCUDNN -I/usr/local/cudnn/include -c ./src/gru_layer.c -o obj/gru_layer.o\n",
            "gcc -Iinclude/ -I3rdparty/stb/include -DOPENCV `pkg-config --cflags opencv4 2> /dev/null || pkg-config --cflags opencv` -DGPU -I/usr/local/cuda/include/ -DCUDNN -Wall -Wfatal-errors -Wno-unused-result -Wno-unknown-pragmas -fPIC -Ofast -DOPENCV -DGPU -DCUDNN -I/usr/local/cudnn/include -c ./src/rnn.c -o obj/rnn.o\n",
            "gcc -Iinclude/ -I3rdparty/stb/include -DOPENCV `pkg-config --cflags opencv4 2> /dev/null || pkg-config --cflags opencv` -DGPU -I/usr/local/cuda/include/ -DCUDNN -Wall -Wfatal-errors -Wno-unused-result -Wno-unknown-pragmas -fPIC -Ofast -DOPENCV -DGPU -DCUDNN -I/usr/local/cudnn/include -c ./src/rnn_vid.c -o obj/rnn_vid.o\n",
            "gcc -Iinclude/ -I3rdparty/stb/include -DOPENCV `pkg-config --cflags opencv4 2> /dev/null || pkg-config --cflags opencv` -DGPU -I/usr/local/cuda/include/ -DCUDNN -Wall -Wfatal-errors -Wno-unused-result -Wno-unknown-pragmas -fPIC -Ofast -DOPENCV -DGPU -DCUDNN -I/usr/local/cudnn/include -c ./src/crnn_layer.c -o obj/crnn_layer.o\n",
            "gcc -Iinclude/ -I3rdparty/stb/include -DOPENCV `pkg-config --cflags opencv4 2> /dev/null || pkg-config --cflags opencv` -DGPU -I/usr/local/cuda/include/ -DCUDNN -Wall -Wfatal-errors -Wno-unused-result -Wno-unknown-pragmas -fPIC -Ofast -DOPENCV -DGPU -DCUDNN -I/usr/local/cudnn/include -c ./src/demo.c -o obj/demo.o\n",
            "gcc -Iinclude/ -I3rdparty/stb/include -DOPENCV `pkg-config --cflags opencv4 2> /dev/null || pkg-config --cflags opencv` -DGPU -I/usr/local/cuda/include/ -DCUDNN -Wall -Wfatal-errors -Wno-unused-result -Wno-unknown-pragmas -fPIC -Ofast -DOPENCV -DGPU -DCUDNN -I/usr/local/cudnn/include -c ./src/tag.c -o obj/tag.o\n",
            "gcc -Iinclude/ -I3rdparty/stb/include -DOPENCV `pkg-config --cflags opencv4 2> /dev/null || pkg-config --cflags opencv` -DGPU -I/usr/local/cuda/include/ -DCUDNN -Wall -Wfatal-errors -Wno-unused-result -Wno-unknown-pragmas -fPIC -Ofast -DOPENCV -DGPU -DCUDNN -I/usr/local/cudnn/include -c ./src/cifar.c -o obj/cifar.o\n",
            "gcc -Iinclude/ -I3rdparty/stb/include -DOPENCV `pkg-config --cflags opencv4 2> /dev/null || pkg-config --cflags opencv` -DGPU -I/usr/local/cuda/include/ -DCUDNN -Wall -Wfatal-errors -Wno-unused-result -Wno-unknown-pragmas -fPIC -Ofast -DOPENCV -DGPU -DCUDNN -I/usr/local/cudnn/include -c ./src/go.c -o obj/go.o\n",
            "gcc -Iinclude/ -I3rdparty/stb/include -DOPENCV `pkg-config --cflags opencv4 2> /dev/null || pkg-config --cflags opencv` -DGPU -I/usr/local/cuda/include/ -DCUDNN -Wall -Wfatal-errors -Wno-unused-result -Wno-unknown-pragmas -fPIC -Ofast -DOPENCV -DGPU -DCUDNN -I/usr/local/cudnn/include -c ./src/batchnorm_layer.c -o obj/batchnorm_layer.o\n",
            "gcc -Iinclude/ -I3rdparty/stb/include -DOPENCV `pkg-config --cflags opencv4 2> /dev/null || pkg-config --cflags opencv` -DGPU -I/usr/local/cuda/include/ -DCUDNN -Wall -Wfatal-errors -Wno-unused-result -Wno-unknown-pragmas -fPIC -Ofast -DOPENCV -DGPU -DCUDNN -I/usr/local/cudnn/include -c ./src/art.c -o obj/art.o\n",
            "gcc -Iinclude/ -I3rdparty/stb/include -DOPENCV `pkg-config --cflags opencv4 2> /dev/null || pkg-config --cflags opencv` -DGPU -I/usr/local/cuda/include/ -DCUDNN -Wall -Wfatal-errors -Wno-unused-result -Wno-unknown-pragmas -fPIC -Ofast -DOPENCV -DGPU -DCUDNN -I/usr/local/cudnn/include -c ./src/region_layer.c -o obj/region_layer.o\n",
            "\u001b[01m\u001b[K./src/region_layer.c:\u001b[m\u001b[K In function ‘\u001b[01m\u001b[Kresize_region_layer\u001b[m\u001b[K’:\n",
            "\u001b[01m\u001b[K./src/region_layer.c:58:9:\u001b[m\u001b[K \u001b[01;35m\u001b[Kwarning: \u001b[m\u001b[Kunused variable ‘\u001b[01m\u001b[Kold_h\u001b[m\u001b[K’ [\u001b[01;35m\u001b[K-Wunused-variable\u001b[m\u001b[K]\n",
            "     int \u001b[01;35m\u001b[Kold_h\u001b[m\u001b[K = l->h;\n",
            "         \u001b[01;35m\u001b[K^~~~~\u001b[m\u001b[K\n",
            "\u001b[01m\u001b[K./src/region_layer.c:57:9:\u001b[m\u001b[K \u001b[01;35m\u001b[Kwarning: \u001b[m\u001b[Kunused variable ‘\u001b[01m\u001b[Kold_w\u001b[m\u001b[K’ [\u001b[01;35m\u001b[K-Wunused-variable\u001b[m\u001b[K]\n",
            "     int \u001b[01;35m\u001b[Kold_w\u001b[m\u001b[K = l->w;\n",
            "         \u001b[01;35m\u001b[K^~~~~\u001b[m\u001b[K\n",
            "gcc -Iinclude/ -I3rdparty/stb/include -DOPENCV `pkg-config --cflags opencv4 2> /dev/null || pkg-config --cflags opencv` -DGPU -I/usr/local/cuda/include/ -DCUDNN -Wall -Wfatal-errors -Wno-unused-result -Wno-unknown-pragmas -fPIC -Ofast -DOPENCV -DGPU -DCUDNN -I/usr/local/cudnn/include -c ./src/reorg_layer.c -o obj/reorg_layer.o\n",
            "gcc -Iinclude/ -I3rdparty/stb/include -DOPENCV `pkg-config --cflags opencv4 2> /dev/null || pkg-config --cflags opencv` -DGPU -I/usr/local/cuda/include/ -DCUDNN -Wall -Wfatal-errors -Wno-unused-result -Wno-unknown-pragmas -fPIC -Ofast -DOPENCV -DGPU -DCUDNN -I/usr/local/cudnn/include -c ./src/reorg_old_layer.c -o obj/reorg_old_layer.o\n",
            "gcc -Iinclude/ -I3rdparty/stb/include -DOPENCV `pkg-config --cflags opencv4 2> /dev/null || pkg-config --cflags opencv` -DGPU -I/usr/local/cuda/include/ -DCUDNN -Wall -Wfatal-errors -Wno-unused-result -Wno-unknown-pragmas -fPIC -Ofast -DOPENCV -DGPU -DCUDNN -I/usr/local/cudnn/include -c ./src/super.c -o obj/super.o\n",
            "gcc -Iinclude/ -I3rdparty/stb/include -DOPENCV `pkg-config --cflags opencv4 2> /dev/null || pkg-config --cflags opencv` -DGPU -I/usr/local/cuda/include/ -DCUDNN -Wall -Wfatal-errors -Wno-unused-result -Wno-unknown-pragmas -fPIC -Ofast -DOPENCV -DGPU -DCUDNN -I/usr/local/cudnn/include -c ./src/voxel.c -o obj/voxel.o\n",
            "gcc -Iinclude/ -I3rdparty/stb/include -DOPENCV `pkg-config --cflags opencv4 2> /dev/null || pkg-config --cflags opencv` -DGPU -I/usr/local/cuda/include/ -DCUDNN -Wall -Wfatal-errors -Wno-unused-result -Wno-unknown-pragmas -fPIC -Ofast -DOPENCV -DGPU -DCUDNN -I/usr/local/cudnn/include -c ./src/tree.c -o obj/tree.o\n",
            "gcc -Iinclude/ -I3rdparty/stb/include -DOPENCV `pkg-config --cflags opencv4 2> /dev/null || pkg-config --cflags opencv` -DGPU -I/usr/local/cuda/include/ -DCUDNN -Wall -Wfatal-errors -Wno-unused-result -Wno-unknown-pragmas -fPIC -Ofast -DOPENCV -DGPU -DCUDNN -I/usr/local/cudnn/include -c ./src/yolo_layer.c -o obj/yolo_layer.o\n",
            "\u001b[01m\u001b[K./src/yolo_layer.c:\u001b[m\u001b[K In function ‘\u001b[01m\u001b[Kmake_yolo_layer\u001b[m\u001b[K’:\n",
            "\u001b[01m\u001b[K./src/yolo_layer.c:61:38:\u001b[m\u001b[K \u001b[01;35m\u001b[Kwarning: \u001b[m\u001b[Kpassing argument 1 of ‘\u001b[01m\u001b[KcudaHostAlloc\u001b[m\u001b[K’ from incompatible pointer type [\u001b[01;35m\u001b[K-Wincompatible-pointer-types\u001b[m\u001b[K]\n",
            "     if (cudaSuccess == cudaHostAlloc(\u001b[01;35m\u001b[K&\u001b[m\u001b[Kl.output, batch*l.outputs*sizeof(float), cudaHostRegisterMapped)) l.output_pinned = 1;\n",
            "                                      \u001b[01;35m\u001b[K^\u001b[m\u001b[K\n",
            "In file included from \u001b[01m\u001b[K/usr/local/cuda/include/cuda_runtime.h:96:0\u001b[m\u001b[K,\n",
            "                 from \u001b[01m\u001b[Kinclude/darknet.h:41\u001b[m\u001b[K,\n",
            "                 from \u001b[01m\u001b[K./src/activations.h:3\u001b[m\u001b[K,\n",
            "                 from \u001b[01m\u001b[K./src/layer.h:4\u001b[m\u001b[K,\n",
            "                 from \u001b[01m\u001b[K./src/yolo_layer.h:5\u001b[m\u001b[K,\n",
            "                 from \u001b[01m\u001b[K./src/yolo_layer.c:1\u001b[m\u001b[K:\n",
            "\u001b[01m\u001b[K/usr/local/cuda/include/cuda_runtime_api.h:4391:39:\u001b[m\u001b[K \u001b[01;36m\u001b[Knote: \u001b[m\u001b[Kexpected ‘\u001b[01m\u001b[Kvoid **\u001b[m\u001b[K’ but argument is of type ‘\u001b[01m\u001b[Kfloat **\u001b[m\u001b[K’\n",
            " extern __host__ cudaError_t CUDARTAPI \u001b[01;36m\u001b[KcudaHostAlloc\u001b[m\u001b[K(void **pHost, size_t size, unsigned int flags);\n",
            "                                       \u001b[01;36m\u001b[K^~~~~~~~~~~~~\u001b[m\u001b[K\n",
            "\u001b[01m\u001b[K./src/yolo_layer.c:68:38:\u001b[m\u001b[K \u001b[01;35m\u001b[Kwarning: \u001b[m\u001b[Kpassing argument 1 of ‘\u001b[01m\u001b[KcudaHostAlloc\u001b[m\u001b[K’ from incompatible pointer type [\u001b[01;35m\u001b[K-Wincompatible-pointer-types\u001b[m\u001b[K]\n",
            "     if (cudaSuccess == cudaHostAlloc(\u001b[01;35m\u001b[K&\u001b[m\u001b[Kl.delta, batch*l.outputs*sizeof(float), cudaHostRegisterMapped)) l.delta_pinned = 1;\n",
            "                                      \u001b[01;35m\u001b[K^\u001b[m\u001b[K\n",
            "In file included from \u001b[01m\u001b[K/usr/local/cuda/include/cuda_runtime.h:96:0\u001b[m\u001b[K,\n",
            "                 from \u001b[01m\u001b[Kinclude/darknet.h:41\u001b[m\u001b[K,\n",
            "                 from \u001b[01m\u001b[K./src/activations.h:3\u001b[m\u001b[K,\n",
            "                 from \u001b[01m\u001b[K./src/layer.h:4\u001b[m\u001b[K,\n",
            "                 from \u001b[01m\u001b[K./src/yolo_layer.h:5\u001b[m\u001b[K,\n",
            "                 from \u001b[01m\u001b[K./src/yolo_layer.c:1\u001b[m\u001b[K:\n",
            "\u001b[01m\u001b[K/usr/local/cuda/include/cuda_runtime_api.h:4391:39:\u001b[m\u001b[K \u001b[01;36m\u001b[Knote: \u001b[m\u001b[Kexpected ‘\u001b[01m\u001b[Kvoid **\u001b[m\u001b[K’ but argument is of type ‘\u001b[01m\u001b[Kfloat **\u001b[m\u001b[K’\n",
            " extern __host__ cudaError_t CUDARTAPI \u001b[01;36m\u001b[KcudaHostAlloc\u001b[m\u001b[K(void **pHost, size_t size, unsigned int flags);\n",
            "                                       \u001b[01;36m\u001b[K^~~~~~~~~~~~~\u001b[m\u001b[K\n",
            "\u001b[01m\u001b[K./src/yolo_layer.c:\u001b[m\u001b[K In function ‘\u001b[01m\u001b[Kresize_yolo_layer\u001b[m\u001b[K’:\n",
            "\u001b[01m\u001b[K./src/yolo_layer.c:95:42:\u001b[m\u001b[K \u001b[01;35m\u001b[Kwarning: \u001b[m\u001b[Kpassing argument 1 of ‘\u001b[01m\u001b[KcudaHostAlloc\u001b[m\u001b[K’ from incompatible pointer type [\u001b[01;35m\u001b[K-Wincompatible-pointer-types\u001b[m\u001b[K]\n",
            "         if (cudaSuccess != cudaHostAlloc(\u001b[01;35m\u001b[K&\u001b[m\u001b[Kl->output, l->batch*l->outputs * sizeof(float), cudaHostRegisterMapped)) {\n",
            "                                          \u001b[01;35m\u001b[K^\u001b[m\u001b[K\n",
            "In file included from \u001b[01m\u001b[K/usr/local/cuda/include/cuda_runtime.h:96:0\u001b[m\u001b[K,\n",
            "                 from \u001b[01m\u001b[Kinclude/darknet.h:41\u001b[m\u001b[K,\n",
            "                 from \u001b[01m\u001b[K./src/activations.h:3\u001b[m\u001b[K,\n",
            "                 from \u001b[01m\u001b[K./src/layer.h:4\u001b[m\u001b[K,\n",
            "                 from \u001b[01m\u001b[K./src/yolo_layer.h:5\u001b[m\u001b[K,\n",
            "                 from \u001b[01m\u001b[K./src/yolo_layer.c:1\u001b[m\u001b[K:\n",
            "\u001b[01m\u001b[K/usr/local/cuda/include/cuda_runtime_api.h:4391:39:\u001b[m\u001b[K \u001b[01;36m\u001b[Knote: \u001b[m\u001b[Kexpected ‘\u001b[01m\u001b[Kvoid **\u001b[m\u001b[K’ but argument is of type ‘\u001b[01m\u001b[Kfloat **\u001b[m\u001b[K’\n",
            " extern __host__ cudaError_t CUDARTAPI \u001b[01;36m\u001b[KcudaHostAlloc\u001b[m\u001b[K(void **pHost, size_t size, unsigned int flags);\n",
            "                                       \u001b[01;36m\u001b[K^~~~~~~~~~~~~\u001b[m\u001b[K\n",
            "\u001b[01m\u001b[K./src/yolo_layer.c:104:42:\u001b[m\u001b[K \u001b[01;35m\u001b[Kwarning: \u001b[m\u001b[Kpassing argument 1 of ‘\u001b[01m\u001b[KcudaHostAlloc\u001b[m\u001b[K’ from incompatible pointer type [\u001b[01;35m\u001b[K-Wincompatible-pointer-types\u001b[m\u001b[K]\n",
            "         if (cudaSuccess != cudaHostAlloc(\u001b[01;35m\u001b[K&\u001b[m\u001b[Kl->delta, l->batch*l->outputs * sizeof(float), cudaHostRegisterMapped)) {\n",
            "                                          \u001b[01;35m\u001b[K^\u001b[m\u001b[K\n",
            "In file included from \u001b[01m\u001b[K/usr/local/cuda/include/cuda_runtime.h:96:0\u001b[m\u001b[K,\n",
            "                 from \u001b[01m\u001b[Kinclude/darknet.h:41\u001b[m\u001b[K,\n",
            "                 from \u001b[01m\u001b[K./src/activations.h:3\u001b[m\u001b[K,\n",
            "                 from \u001b[01m\u001b[K./src/layer.h:4\u001b[m\u001b[K,\n",
            "                 from \u001b[01m\u001b[K./src/yolo_layer.h:5\u001b[m\u001b[K,\n",
            "                 from \u001b[01m\u001b[K./src/yolo_layer.c:1\u001b[m\u001b[K:\n",
            "\u001b[01m\u001b[K/usr/local/cuda/include/cuda_runtime_api.h:4391:39:\u001b[m\u001b[K \u001b[01;36m\u001b[Knote: \u001b[m\u001b[Kexpected ‘\u001b[01m\u001b[Kvoid **\u001b[m\u001b[K’ but argument is of type ‘\u001b[01m\u001b[Kfloat **\u001b[m\u001b[K’\n",
            " extern __host__ cudaError_t CUDARTAPI \u001b[01;36m\u001b[KcudaHostAlloc\u001b[m\u001b[K(void **pHost, size_t size, unsigned int flags);\n",
            "                                       \u001b[01;36m\u001b[K^~~~~~~~~~~~~\u001b[m\u001b[K\n",
            "\u001b[01m\u001b[K./src/yolo_layer.c:\u001b[m\u001b[K In function ‘\u001b[01m\u001b[Kforward_yolo_layer\u001b[m\u001b[K’:\n",
            "\u001b[01m\u001b[K./src/yolo_layer.c:371:25:\u001b[m\u001b[K \u001b[01;35m\u001b[Kwarning: \u001b[m\u001b[Kvariable ‘\u001b[01m\u001b[Kbest_match_t\u001b[m\u001b[K’ set but not used [\u001b[01;35m\u001b[K-Wunused-but-set-variable\u001b[m\u001b[K]\n",
            "                     int \u001b[01;35m\u001b[Kbest_match_t\u001b[m\u001b[K = 0;\n",
            "                         \u001b[01;35m\u001b[K^~~~~~~~~~~~\u001b[m\u001b[K\n",
            "gcc -Iinclude/ -I3rdparty/stb/include -DOPENCV `pkg-config --cflags opencv4 2> /dev/null || pkg-config --cflags opencv` -DGPU -I/usr/local/cuda/include/ -DCUDNN -Wall -Wfatal-errors -Wno-unused-result -Wno-unknown-pragmas -fPIC -Ofast -DOPENCV -DGPU -DCUDNN -I/usr/local/cudnn/include -c ./src/gaussian_yolo_layer.c -o obj/gaussian_yolo_layer.o\n",
            "\u001b[01m\u001b[K./src/gaussian_yolo_layer.c:\u001b[m\u001b[K In function ‘\u001b[01m\u001b[Kmake_gaussian_yolo_layer\u001b[m\u001b[K’:\n",
            "\u001b[01m\u001b[K./src/gaussian_yolo_layer.c:71:38:\u001b[m\u001b[K \u001b[01;35m\u001b[Kwarning: \u001b[m\u001b[Kpassing argument 1 of ‘\u001b[01m\u001b[KcudaHostAlloc\u001b[m\u001b[K’ from incompatible pointer type [\u001b[01;35m\u001b[K-Wincompatible-pointer-types\u001b[m\u001b[K]\n",
            "     if (cudaSuccess == cudaHostAlloc(\u001b[01;35m\u001b[K&\u001b[m\u001b[Kl.output, batch*l.outputs * sizeof(float), cudaHostRegisterMapped)) l.output_pinned = 1;\n",
            "                                      \u001b[01;35m\u001b[K^\u001b[m\u001b[K\n",
            "In file included from \u001b[01m\u001b[K/usr/local/cuda/include/cuda_runtime.h:96:0\u001b[m\u001b[K,\n",
            "                 from \u001b[01m\u001b[Kinclude/darknet.h:41\u001b[m\u001b[K,\n",
            "                 from \u001b[01m\u001b[K./src/gaussian_yolo_layer.h:5\u001b[m\u001b[K,\n",
            "                 from \u001b[01m\u001b[K./src/gaussian_yolo_layer.c:7\u001b[m\u001b[K:\n",
            "\u001b[01m\u001b[K/usr/local/cuda/include/cuda_runtime_api.h:4391:39:\u001b[m\u001b[K \u001b[01;36m\u001b[Knote: \u001b[m\u001b[Kexpected ‘\u001b[01m\u001b[Kvoid **\u001b[m\u001b[K’ but argument is of type ‘\u001b[01m\u001b[Kfloat **\u001b[m\u001b[K’\n",
            " extern __host__ cudaError_t CUDARTAPI \u001b[01;36m\u001b[KcudaHostAlloc\u001b[m\u001b[K(void **pHost, size_t size, unsigned int flags);\n",
            "                                       \u001b[01;36m\u001b[K^~~~~~~~~~~~~\u001b[m\u001b[K\n",
            "\u001b[01m\u001b[K./src/gaussian_yolo_layer.c:78:38:\u001b[m\u001b[K \u001b[01;35m\u001b[Kwarning: \u001b[m\u001b[Kpassing argument 1 of ‘\u001b[01m\u001b[KcudaHostAlloc\u001b[m\u001b[K’ from incompatible pointer type [\u001b[01;35m\u001b[K-Wincompatible-pointer-types\u001b[m\u001b[K]\n",
            "     if (cudaSuccess == cudaHostAlloc(\u001b[01;35m\u001b[K&\u001b[m\u001b[Kl.delta, batch*l.outputs * sizeof(float), cudaHostRegisterMapped)) l.delta_pinned = 1;\n",
            "                                      \u001b[01;35m\u001b[K^\u001b[m\u001b[K\n",
            "In file included from \u001b[01m\u001b[K/usr/local/cuda/include/cuda_runtime.h:96:0\u001b[m\u001b[K,\n",
            "                 from \u001b[01m\u001b[Kinclude/darknet.h:41\u001b[m\u001b[K,\n",
            "                 from \u001b[01m\u001b[K./src/gaussian_yolo_layer.h:5\u001b[m\u001b[K,\n",
            "                 from \u001b[01m\u001b[K./src/gaussian_yolo_layer.c:7\u001b[m\u001b[K:\n",
            "\u001b[01m\u001b[K/usr/local/cuda/include/cuda_runtime_api.h:4391:39:\u001b[m\u001b[K \u001b[01;36m\u001b[Knote: \u001b[m\u001b[Kexpected ‘\u001b[01m\u001b[Kvoid **\u001b[m\u001b[K’ but argument is of type ‘\u001b[01m\u001b[Kfloat **\u001b[m\u001b[K’\n",
            " extern __host__ cudaError_t CUDARTAPI \u001b[01;36m\u001b[KcudaHostAlloc\u001b[m\u001b[K(void **pHost, size_t size, unsigned int flags);\n",
            "                                       \u001b[01;36m\u001b[K^~~~~~~~~~~~~\u001b[m\u001b[K\n",
            "\u001b[01m\u001b[K./src/gaussian_yolo_layer.c:\u001b[m\u001b[K In function ‘\u001b[01m\u001b[Kresize_gaussian_yolo_layer\u001b[m\u001b[K’:\n",
            "\u001b[01m\u001b[K./src/gaussian_yolo_layer.c:110:42:\u001b[m\u001b[K \u001b[01;35m\u001b[Kwarning: \u001b[m\u001b[Kpassing argument 1 of ‘\u001b[01m\u001b[KcudaHostAlloc\u001b[m\u001b[K’ from incompatible pointer type [\u001b[01;35m\u001b[K-Wincompatible-pointer-types\u001b[m\u001b[K]\n",
            "         if (cudaSuccess != cudaHostAlloc(\u001b[01;35m\u001b[K&\u001b[m\u001b[Kl->output, l->batch*l->outputs * sizeof(float), cudaHostRegisterMapped)) {\n",
            "                                          \u001b[01;35m\u001b[K^\u001b[m\u001b[K\n",
            "In file included from \u001b[01m\u001b[K/usr/local/cuda/include/cuda_runtime.h:96:0\u001b[m\u001b[K,\n",
            "                 from \u001b[01m\u001b[Kinclude/darknet.h:41\u001b[m\u001b[K,\n",
            "                 from \u001b[01m\u001b[K./src/gaussian_yolo_layer.h:5\u001b[m\u001b[K,\n",
            "                 from \u001b[01m\u001b[K./src/gaussian_yolo_layer.c:7\u001b[m\u001b[K:\n",
            "\u001b[01m\u001b[K/usr/local/cuda/include/cuda_runtime_api.h:4391:39:\u001b[m\u001b[K \u001b[01;36m\u001b[Knote: \u001b[m\u001b[Kexpected ‘\u001b[01m\u001b[Kvoid **\u001b[m\u001b[K’ but argument is of type ‘\u001b[01m\u001b[Kfloat **\u001b[m\u001b[K’\n",
            " extern __host__ cudaError_t CUDARTAPI \u001b[01;36m\u001b[KcudaHostAlloc\u001b[m\u001b[K(void **pHost, size_t size, unsigned int flags);\n",
            "                                       \u001b[01;36m\u001b[K^~~~~~~~~~~~~\u001b[m\u001b[K\n",
            "\u001b[01m\u001b[K./src/gaussian_yolo_layer.c:119:42:\u001b[m\u001b[K \u001b[01;35m\u001b[Kwarning: \u001b[m\u001b[Kpassing argument 1 of ‘\u001b[01m\u001b[KcudaHostAlloc\u001b[m\u001b[K’ from incompatible pointer type [\u001b[01;35m\u001b[K-Wincompatible-pointer-types\u001b[m\u001b[K]\n",
            "         if (cudaSuccess != cudaHostAlloc(\u001b[01;35m\u001b[K&\u001b[m\u001b[Kl->delta, l->batch*l->outputs * sizeof(float), cudaHostRegisterMapped)) {\n",
            "                                          \u001b[01;35m\u001b[K^\u001b[m\u001b[K\n",
            "In file included from \u001b[01m\u001b[K/usr/local/cuda/include/cuda_runtime.h:96:0\u001b[m\u001b[K,\n",
            "                 from \u001b[01m\u001b[Kinclude/darknet.h:41\u001b[m\u001b[K,\n",
            "                 from \u001b[01m\u001b[K./src/gaussian_yolo_layer.h:5\u001b[m\u001b[K,\n",
            "                 from \u001b[01m\u001b[K./src/gaussian_yolo_layer.c:7\u001b[m\u001b[K:\n",
            "\u001b[01m\u001b[K/usr/local/cuda/include/cuda_runtime_api.h:4391:39:\u001b[m\u001b[K \u001b[01;36m\u001b[Knote: \u001b[m\u001b[Kexpected ‘\u001b[01m\u001b[Kvoid **\u001b[m\u001b[K’ but argument is of type ‘\u001b[01m\u001b[Kfloat **\u001b[m\u001b[K’\n",
            " extern __host__ cudaError_t CUDARTAPI \u001b[01;36m\u001b[KcudaHostAlloc\u001b[m\u001b[K(void **pHost, size_t size, unsigned int flags);\n",
            "                                       \u001b[01;36m\u001b[K^~~~~~~~~~~~~\u001b[m\u001b[K\n",
            "\u001b[01m\u001b[K./src/gaussian_yolo_layer.c:\u001b[m\u001b[K In function ‘\u001b[01m\u001b[Kforward_gaussian_yolo_layer\u001b[m\u001b[K’:\n",
            "\u001b[01m\u001b[K./src/gaussian_yolo_layer.c:460:25:\u001b[m\u001b[K \u001b[01;35m\u001b[Kwarning: \u001b[m\u001b[Kvariable ‘\u001b[01m\u001b[Kbest_match_t\u001b[m\u001b[K’ set but not used [\u001b[01;35m\u001b[K-Wunused-but-set-variable\u001b[m\u001b[K]\n",
            "                     int \u001b[01;35m\u001b[Kbest_match_t\u001b[m\u001b[K = 0;\n",
            "                         \u001b[01;35m\u001b[K^~~~~~~~~~~~\u001b[m\u001b[K\n",
            "gcc -Iinclude/ -I3rdparty/stb/include -DOPENCV `pkg-config --cflags opencv4 2> /dev/null || pkg-config --cflags opencv` -DGPU -I/usr/local/cuda/include/ -DCUDNN -Wall -Wfatal-errors -Wno-unused-result -Wno-unknown-pragmas -fPIC -Ofast -DOPENCV -DGPU -DCUDNN -I/usr/local/cudnn/include -c ./src/upsample_layer.c -o obj/upsample_layer.o\n",
            "gcc -Iinclude/ -I3rdparty/stb/include -DOPENCV `pkg-config --cflags opencv4 2> /dev/null || pkg-config --cflags opencv` -DGPU -I/usr/local/cuda/include/ -DCUDNN -Wall -Wfatal-errors -Wno-unused-result -Wno-unknown-pragmas -fPIC -Ofast -DOPENCV -DGPU -DCUDNN -I/usr/local/cudnn/include -c ./src/lstm_layer.c -o obj/lstm_layer.o\n",
            "gcc -Iinclude/ -I3rdparty/stb/include -DOPENCV `pkg-config --cflags opencv4 2> /dev/null || pkg-config --cflags opencv` -DGPU -I/usr/local/cuda/include/ -DCUDNN -Wall -Wfatal-errors -Wno-unused-result -Wno-unknown-pragmas -fPIC -Ofast -DOPENCV -DGPU -DCUDNN -I/usr/local/cudnn/include -c ./src/conv_lstm_layer.c -o obj/conv_lstm_layer.o\n",
            "gcc -Iinclude/ -I3rdparty/stb/include -DOPENCV `pkg-config --cflags opencv4 2> /dev/null || pkg-config --cflags opencv` -DGPU -I/usr/local/cuda/include/ -DCUDNN -Wall -Wfatal-errors -Wno-unused-result -Wno-unknown-pragmas -fPIC -Ofast -DOPENCV -DGPU -DCUDNN -I/usr/local/cudnn/include -c ./src/scale_channels_layer.c -o obj/scale_channels_layer.o\n",
            "gcc -Iinclude/ -I3rdparty/stb/include -DOPENCV `pkg-config --cflags opencv4 2> /dev/null || pkg-config --cflags opencv` -DGPU -I/usr/local/cuda/include/ -DCUDNN -Wall -Wfatal-errors -Wno-unused-result -Wno-unknown-pragmas -fPIC -Ofast -DOPENCV -DGPU -DCUDNN -I/usr/local/cudnn/include -c ./src/sam_layer.c -o obj/sam_layer.o\n",
            "nvcc -gencode arch=compute_30,code=sm_30 -gencode arch=compute_35,code=sm_35 -gencode arch=compute_50,code=[sm_50,compute_50] -gencode arch=compute_52,code=[sm_52,compute_52] -gencode arch=compute_61,code=[sm_61,compute_61] -Iinclude/ -I3rdparty/stb/include -DOPENCV `pkg-config --cflags opencv4 2> /dev/null || pkg-config --cflags opencv` -DGPU -I/usr/local/cuda/include/ -DCUDNN --compiler-options \"-Wall -Wfatal-errors -Wno-unused-result -Wno-unknown-pragmas -fPIC -Ofast -DOPENCV -DGPU -DCUDNN -I/usr/local/cudnn/include\" -c ./src/convolutional_kernels.cu -o obj/convolutional_kernels.o\n",
            "nvcc -gencode arch=compute_30,code=sm_30 -gencode arch=compute_35,code=sm_35 -gencode arch=compute_50,code=[sm_50,compute_50] -gencode arch=compute_52,code=[sm_52,compute_52] -gencode arch=compute_61,code=[sm_61,compute_61] -Iinclude/ -I3rdparty/stb/include -DOPENCV `pkg-config --cflags opencv4 2> /dev/null || pkg-config --cflags opencv` -DGPU -I/usr/local/cuda/include/ -DCUDNN --compiler-options \"-Wall -Wfatal-errors -Wno-unused-result -Wno-unknown-pragmas -fPIC -Ofast -DOPENCV -DGPU -DCUDNN -I/usr/local/cudnn/include\" -c ./src/activation_kernels.cu -o obj/activation_kernels.o\n",
            "nvcc -gencode arch=compute_30,code=sm_30 -gencode arch=compute_35,code=sm_35 -gencode arch=compute_50,code=[sm_50,compute_50] -gencode arch=compute_52,code=[sm_52,compute_52] -gencode arch=compute_61,code=[sm_61,compute_61] -Iinclude/ -I3rdparty/stb/include -DOPENCV `pkg-config --cflags opencv4 2> /dev/null || pkg-config --cflags opencv` -DGPU -I/usr/local/cuda/include/ -DCUDNN --compiler-options \"-Wall -Wfatal-errors -Wno-unused-result -Wno-unknown-pragmas -fPIC -Ofast -DOPENCV -DGPU -DCUDNN -I/usr/local/cudnn/include\" -c ./src/im2col_kernels.cu -o obj/im2col_kernels.o\n",
            "\u001b[01m\u001b[K./src/im2col_kernels.cu:125:18:\u001b[m\u001b[K \u001b[01;35m\u001b[Kwarning: \u001b[m\u001b[K\"/*\" within comment [\u001b[01;35m\u001b[K-Wcomment\u001b[m\u001b[K]\n",
            "                 //*data_col_ptr = (h >= 0 && w >= 0 && h < height && w < width) ?\n",
            "                   \n",
            "\u001b[01m\u001b[K./src/im2col_kernels.cu:1178:6:\u001b[m\u001b[K \u001b[01;35m\u001b[Kwarning: \u001b[m\u001b[K\"/*\" within comment [\u001b[01;35m\u001b[K-Wcomment\u001b[m\u001b[K]\n",
            "     //*((uint64_t *)(A_s + (local_i*lda + k) / 8)) = *((uint64_t *)(A + (i_cur*lda + k) / 8));    // weights\n",
            "       \n",
            "\u001b[01m\u001b[K./src/im2col_kernels.cu:125:18:\u001b[m\u001b[K \u001b[01;35m\u001b[Kwarning: \u001b[m\u001b[K\"/*\" within comment [\u001b[01;35m\u001b[K-Wcomment\u001b[m\u001b[K]\n",
            "                 //*data_col_ptr = (h >= 0 && w >= 0 && h < height && w < width) ?\n",
            "                   \n",
            "\u001b[01m\u001b[K./src/im2col_kernels.cu:1178:6:\u001b[m\u001b[K \u001b[01;35m\u001b[Kwarning: \u001b[m\u001b[K\"/*\" within comment [\u001b[01;35m\u001b[K-Wcomment\u001b[m\u001b[K]\n",
            "     //*((uint64_t *)(A_s + (local_i*lda + k) / 8)) = *((uint64_t *)(A + (i_cur*lda + k) / 8));    // weights\n",
            "       \n",
            "\u001b[01m\u001b[K./src/im2col_kernels.cu:125:18:\u001b[m\u001b[K \u001b[01;35m\u001b[Kwarning: \u001b[m\u001b[K\"/*\" within comment [\u001b[01;35m\u001b[K-Wcomment\u001b[m\u001b[K]\n",
            "                 //*data_col_ptr = (h >= 0 && w >= 0 && h < height && w < width) ?\n",
            "                   \n",
            "\u001b[01m\u001b[K./src/im2col_kernels.cu:1178:6:\u001b[m\u001b[K \u001b[01;35m\u001b[Kwarning: \u001b[m\u001b[K\"/*\" within comment [\u001b[01;35m\u001b[K-Wcomment\u001b[m\u001b[K]\n",
            "     //*((uint64_t *)(A_s + (local_i*lda + k) / 8)) = *((uint64_t *)(A + (i_cur*lda + k) / 8));    // weights\n",
            "       \n",
            "\u001b[01m\u001b[K./src/im2col_kernels.cu:125:18:\u001b[m\u001b[K \u001b[01;35m\u001b[Kwarning: \u001b[m\u001b[K\"/*\" within comment [\u001b[01;35m\u001b[K-Wcomment\u001b[m\u001b[K]\n",
            "                 //*data_col_ptr = (h >= 0 && w >= 0 && h < height && w < width) ?\n",
            "                   \n",
            "\u001b[01m\u001b[K./src/im2col_kernels.cu:1178:6:\u001b[m\u001b[K \u001b[01;35m\u001b[Kwarning: \u001b[m\u001b[K\"/*\" within comment [\u001b[01;35m\u001b[K-Wcomment\u001b[m\u001b[K]\n",
            "     //*((uint64_t *)(A_s + (local_i*lda + k) / 8)) = *((uint64_t *)(A + (i_cur*lda + k) / 8));    // weights\n",
            "       \n",
            "\u001b[01m\u001b[K./src/im2col_kernels.cu:125:18:\u001b[m\u001b[K \u001b[01;35m\u001b[Kwarning: \u001b[m\u001b[K\"/*\" within comment [\u001b[01;35m\u001b[K-Wcomment\u001b[m\u001b[K]\n",
            "                 //*data_col_ptr = (h >= 0 && w >= 0 && h < height && w < width) ?\n",
            "                   \n",
            "\u001b[01m\u001b[K./src/im2col_kernels.cu:1178:6:\u001b[m\u001b[K \u001b[01;35m\u001b[Kwarning: \u001b[m\u001b[K\"/*\" within comment [\u001b[01;35m\u001b[K-Wcomment\u001b[m\u001b[K]\n",
            "     //*((uint64_t *)(A_s + (local_i*lda + k) / 8)) = *((uint64_t *)(A + (i_cur*lda + k) / 8));    // weights\n",
            "       \n",
            "\u001b[01m\u001b[K./src/im2col_kernels.cu:125:18:\u001b[m\u001b[K \u001b[01;35m\u001b[Kwarning: \u001b[m\u001b[K\"/*\" within comment [\u001b[01;35m\u001b[K-Wcomment\u001b[m\u001b[K]\n",
            "                 //*data_col_ptr = (h >= 0 && w >= 0 && h < height && w < width) ?\n",
            "                   \n",
            "\u001b[01m\u001b[K./src/im2col_kernels.cu:1178:6:\u001b[m\u001b[K \u001b[01;35m\u001b[Kwarning: \u001b[m\u001b[K\"/*\" within comment [\u001b[01;35m\u001b[K-Wcomment\u001b[m\u001b[K]\n",
            "     //*((uint64_t *)(A_s + (local_i*lda + k) / 8)) = *((uint64_t *)(A + (i_cur*lda + k) / 8));    // weights\n",
            "       \n",
            "nvcc -gencode arch=compute_30,code=sm_30 -gencode arch=compute_35,code=sm_35 -gencode arch=compute_50,code=[sm_50,compute_50] -gencode arch=compute_52,code=[sm_52,compute_52] -gencode arch=compute_61,code=[sm_61,compute_61] -Iinclude/ -I3rdparty/stb/include -DOPENCV `pkg-config --cflags opencv4 2> /dev/null || pkg-config --cflags opencv` -DGPU -I/usr/local/cuda/include/ -DCUDNN --compiler-options \"-Wall -Wfatal-errors -Wno-unused-result -Wno-unknown-pragmas -fPIC -Ofast -DOPENCV -DGPU -DCUDNN -I/usr/local/cudnn/include\" -c ./src/col2im_kernels.cu -o obj/col2im_kernels.o\n",
            "nvcc -gencode arch=compute_30,code=sm_30 -gencode arch=compute_35,code=sm_35 -gencode arch=compute_50,code=[sm_50,compute_50] -gencode arch=compute_52,code=[sm_52,compute_52] -gencode arch=compute_61,code=[sm_61,compute_61] -Iinclude/ -I3rdparty/stb/include -DOPENCV `pkg-config --cflags opencv4 2> /dev/null || pkg-config --cflags opencv` -DGPU -I/usr/local/cuda/include/ -DCUDNN --compiler-options \"-Wall -Wfatal-errors -Wno-unused-result -Wno-unknown-pragmas -fPIC -Ofast -DOPENCV -DGPU -DCUDNN -I/usr/local/cudnn/include\" -c ./src/blas_kernels.cu -o obj/blas_kernels.o\n",
            "./src/blas_kernels.cu(1038): warning: variable \"out_index\" was declared but never referenced\n",
            "\n",
            "./src/blas_kernels.cu(1082): warning: variable \"step\" was set but never used\n",
            "\n",
            "./src/blas_kernels.cu(1686): warning: variable \"stage_id\" was declared but never referenced\n",
            "\n",
            "./src/blas_kernels.cu(1038): warning: variable \"out_index\" was declared but never referenced\n",
            "\n",
            "./src/blas_kernels.cu(1082): warning: variable \"step\" was set but never used\n",
            "\n",
            "./src/blas_kernels.cu(1686): warning: variable \"stage_id\" was declared but never referenced\n",
            "\n",
            "./src/blas_kernels.cu(1038): warning: variable \"out_index\" was declared but never referenced\n",
            "\n",
            "./src/blas_kernels.cu(1082): warning: variable \"step\" was set but never used\n",
            "\n",
            "./src/blas_kernels.cu(1686): warning: variable \"stage_id\" was declared but never referenced\n",
            "\n",
            "./src/blas_kernels.cu(1038): warning: variable \"out_index\" was declared but never referenced\n",
            "\n",
            "./src/blas_kernels.cu(1082): warning: variable \"step\" was set but never used\n",
            "\n",
            "./src/blas_kernels.cu(1686): warning: variable \"stage_id\" was declared but never referenced\n",
            "\n",
            "./src/blas_kernels.cu(1038): warning: variable \"out_index\" was declared but never referenced\n",
            "\n",
            "./src/blas_kernels.cu(1082): warning: variable \"step\" was set but never used\n",
            "\n",
            "./src/blas_kernels.cu(1686): warning: variable \"stage_id\" was declared but never referenced\n",
            "\n",
            "\u001b[01m\u001b[K./src/blas_kernels.cu:\u001b[m\u001b[K In function ‘\u001b[01m\u001b[Kvoid backward_shortcut_multilayer_gpu(int, int, int, int*, float**, float*, float*, float*, float*, int, float*, float**, WEIGHTS_NORMALIZATION_T)\u001b[m\u001b[K’:\n",
            "\u001b[01m\u001b[K./src/blas_kernels.cu:1082:5:\u001b[m\u001b[K \u001b[01;35m\u001b[Kwarning: \u001b[m\u001b[Kvariable ‘\u001b[01m\u001b[Kstep\u001b[m\u001b[K’ set but not used [\u001b[01;35m\u001b[K-Wunused-but-set-variable\u001b[m\u001b[K]\n",
            "     \u001b[01;35m\u001b[Kint \u001b[m\u001b[Kstep = 0;\n",
            "     \u001b[01;35m\u001b[K^~~~\u001b[m\u001b[K\n",
            "nvcc -gencode arch=compute_30,code=sm_30 -gencode arch=compute_35,code=sm_35 -gencode arch=compute_50,code=[sm_50,compute_50] -gencode arch=compute_52,code=[sm_52,compute_52] -gencode arch=compute_61,code=[sm_61,compute_61] -Iinclude/ -I3rdparty/stb/include -DOPENCV `pkg-config --cflags opencv4 2> /dev/null || pkg-config --cflags opencv` -DGPU -I/usr/local/cuda/include/ -DCUDNN --compiler-options \"-Wall -Wfatal-errors -Wno-unused-result -Wno-unknown-pragmas -fPIC -Ofast -DOPENCV -DGPU -DCUDNN -I/usr/local/cudnn/include\" -c ./src/crop_layer_kernels.cu -o obj/crop_layer_kernels.o\n",
            "nvcc -gencode arch=compute_30,code=sm_30 -gencode arch=compute_35,code=sm_35 -gencode arch=compute_50,code=[sm_50,compute_50] -gencode arch=compute_52,code=[sm_52,compute_52] -gencode arch=compute_61,code=[sm_61,compute_61] -Iinclude/ -I3rdparty/stb/include -DOPENCV `pkg-config --cflags opencv4 2> /dev/null || pkg-config --cflags opencv` -DGPU -I/usr/local/cuda/include/ -DCUDNN --compiler-options \"-Wall -Wfatal-errors -Wno-unused-result -Wno-unknown-pragmas -fPIC -Ofast -DOPENCV -DGPU -DCUDNN -I/usr/local/cudnn/include\" -c ./src/dropout_layer_kernels.cu -o obj/dropout_layer_kernels.o\n",
            "./src/dropout_layer_kernels.cu(140): warning: variable \"cur_scale\" was declared but never referenced\n",
            "\n",
            "./src/dropout_layer_kernels.cu(245): warning: variable \"cur_scale\" was declared but never referenced\n",
            "\n",
            "./src/dropout_layer_kernels.cu(262): warning: variable \"block_prob\" was declared but never referenced\n",
            "\n",
            "./src/dropout_layer_kernels.cu(140): warning: variable \"cur_scale\" was declared but never referenced\n",
            "\n",
            "./src/dropout_layer_kernels.cu(245): warning: variable \"cur_scale\" was declared but never referenced\n",
            "\n",
            "./src/dropout_layer_kernels.cu(262): warning: variable \"block_prob\" was declared but never referenced\n",
            "\n",
            "./src/dropout_layer_kernels.cu(140): warning: variable \"cur_scale\" was declared but never referenced\n",
            "\n",
            "./src/dropout_layer_kernels.cu(245): warning: variable \"cur_scale\" was declared but never referenced\n",
            "\n",
            "./src/dropout_layer_kernels.cu(262): warning: variable \"block_prob\" was declared but never referenced\n",
            "\n",
            "./src/dropout_layer_kernels.cu(140): warning: variable \"cur_scale\" was declared but never referenced\n",
            "\n",
            "./src/dropout_layer_kernels.cu(245): warning: variable \"cur_scale\" was declared but never referenced\n",
            "\n",
            "./src/dropout_layer_kernels.cu(262): warning: variable \"block_prob\" was declared but never referenced\n",
            "\n",
            "./src/dropout_layer_kernels.cu(140): warning: variable \"cur_scale\" was declared but never referenced\n",
            "\n",
            "./src/dropout_layer_kernels.cu(245): warning: variable \"cur_scale\" was declared but never referenced\n",
            "\n",
            "./src/dropout_layer_kernels.cu(262): warning: variable \"block_prob\" was declared but never referenced\n",
            "\n",
            "nvcc -gencode arch=compute_30,code=sm_30 -gencode arch=compute_35,code=sm_35 -gencode arch=compute_50,code=[sm_50,compute_50] -gencode arch=compute_52,code=[sm_52,compute_52] -gencode arch=compute_61,code=[sm_61,compute_61] -Iinclude/ -I3rdparty/stb/include -DOPENCV `pkg-config --cflags opencv4 2> /dev/null || pkg-config --cflags opencv` -DGPU -I/usr/local/cuda/include/ -DCUDNN --compiler-options \"-Wall -Wfatal-errors -Wno-unused-result -Wno-unknown-pragmas -fPIC -Ofast -DOPENCV -DGPU -DCUDNN -I/usr/local/cudnn/include\" -c ./src/maxpool_layer_kernels.cu -o obj/maxpool_layer_kernels.o\n",
            "nvcc -gencode arch=compute_30,code=sm_30 -gencode arch=compute_35,code=sm_35 -gencode arch=compute_50,code=[sm_50,compute_50] -gencode arch=compute_52,code=[sm_52,compute_52] -gencode arch=compute_61,code=[sm_61,compute_61] -Iinclude/ -I3rdparty/stb/include -DOPENCV `pkg-config --cflags opencv4 2> /dev/null || pkg-config --cflags opencv` -DGPU -I/usr/local/cuda/include/ -DCUDNN --compiler-options \"-Wall -Wfatal-errors -Wno-unused-result -Wno-unknown-pragmas -fPIC -Ofast -DOPENCV -DGPU -DCUDNN -I/usr/local/cudnn/include\" -c ./src/network_kernels.cu -o obj/network_kernels.o\n",
            "./src/network_kernels.cu(359): warning: variable \"l\" was declared but never referenced\n",
            "\n",
            "./src/network_kernels.cu(368): warning: variable \"im\" was set but never used\n",
            "\n",
            "./src/network_kernels.cu(359): warning: variable \"l\" was declared but never referenced\n",
            "\n",
            "./src/network_kernels.cu(368): warning: variable \"im\" was set but never used\n",
            "\n",
            "./src/network_kernels.cu(359): warning: variable \"l\" was declared but never referenced\n",
            "\n",
            "./src/network_kernels.cu(368): warning: variable \"im\" was set but never used\n",
            "\n",
            "./src/network_kernels.cu(359): warning: variable \"l\" was declared but never referenced\n",
            "\n",
            "./src/network_kernels.cu(368): warning: variable \"im\" was set but never used\n",
            "\n",
            "./src/network_kernels.cu(359): warning: variable \"l\" was declared but never referenced\n",
            "\n",
            "./src/network_kernels.cu(368): warning: variable \"im\" was set but never used\n",
            "\n",
            "\u001b[01m\u001b[K./src/network_kernels.cu:\u001b[m\u001b[K In function ‘\u001b[01m\u001b[Kfloat train_network_datum_gpu(network, float*, float*)\u001b[m\u001b[K’:\n",
            "\u001b[01m\u001b[K./src/network_kernels.cu:359:7:\u001b[m\u001b[K \u001b[01;35m\u001b[Kwarning: \u001b[m\u001b[Kvariable ‘\u001b[01m\u001b[Kl\u001b[m\u001b[K’ set but not used [\u001b[01;35m\u001b[K-Wunused-but-set-variable\u001b[m\u001b[K]\n",
            "       \u001b[01;35m\u001b[K \u001b[m\u001b[K layer l = net.layers[net.n - 1];\n",
            "       \u001b[01;35m\u001b[K^\u001b[m\u001b[K\n",
            "\u001b[01m\u001b[K./src/network_kernels.cu:368:7:\u001b[m\u001b[K \u001b[01;35m\u001b[Kwarning: \u001b[m\u001b[Kvariable ‘\u001b[01m\u001b[Kim\u001b[m\u001b[K’ set but not used [\u001b[01;35m\u001b[K-Wunused-but-set-variable\u001b[m\u001b[K]\n",
            "       \u001b[01;35m\u001b[K  \u001b[m\u001b[Kimage im;\n",
            "       \u001b[01;35m\u001b[K^\u001b[m\u001b[K \n",
            "nvcc -gencode arch=compute_30,code=sm_30 -gencode arch=compute_35,code=sm_35 -gencode arch=compute_50,code=[sm_50,compute_50] -gencode arch=compute_52,code=[sm_52,compute_52] -gencode arch=compute_61,code=[sm_61,compute_61] -Iinclude/ -I3rdparty/stb/include -DOPENCV `pkg-config --cflags opencv4 2> /dev/null || pkg-config --cflags opencv` -DGPU -I/usr/local/cuda/include/ -DCUDNN --compiler-options \"-Wall -Wfatal-errors -Wno-unused-result -Wno-unknown-pragmas -fPIC -Ofast -DOPENCV -DGPU -DCUDNN -I/usr/local/cudnn/include\" -c ./src/avgpool_layer_kernels.cu -o obj/avgpool_layer_kernels.o\n",
            "g++ -std=c++11 -std=c++11 -Iinclude/ -I3rdparty/stb/include -DOPENCV `pkg-config --cflags opencv4 2> /dev/null || pkg-config --cflags opencv` -DGPU -I/usr/local/cuda/include/ -DCUDNN -Wall -Wfatal-errors -Wno-unused-result -Wno-unknown-pragmas -fPIC -Ofast -DOPENCV -DGPU -DCUDNN -I/usr/local/cudnn/include obj/image_opencv.o obj/http_stream.o obj/gemm.o obj/utils.o obj/dark_cuda.o obj/convolutional_layer.o obj/list.o obj/image.o obj/activations.o obj/im2col.o obj/col2im.o obj/blas.o obj/crop_layer.o obj/dropout_layer.o obj/maxpool_layer.o obj/softmax_layer.o obj/data.o obj/matrix.o obj/network.o obj/connected_layer.o obj/cost_layer.o obj/parser.o obj/option_list.o obj/darknet.o obj/detection_layer.o obj/captcha.o obj/route_layer.o obj/writing.o obj/box.o obj/nightmare.o obj/normalization_layer.o obj/avgpool_layer.o obj/coco.o obj/dice.o obj/yolo.o obj/detector.o obj/layer.o obj/compare.o obj/classifier.o obj/local_layer.o obj/swag.o obj/shortcut_layer.o obj/activation_layer.o obj/rnn_layer.o obj/gru_layer.o obj/rnn.o obj/rnn_vid.o obj/crnn_layer.o obj/demo.o obj/tag.o obj/cifar.o obj/go.o obj/batchnorm_layer.o obj/art.o obj/region_layer.o obj/reorg_layer.o obj/reorg_old_layer.o obj/super.o obj/voxel.o obj/tree.o obj/yolo_layer.o obj/gaussian_yolo_layer.o obj/upsample_layer.o obj/lstm_layer.o obj/conv_lstm_layer.o obj/scale_channels_layer.o obj/sam_layer.o obj/convolutional_kernels.o obj/activation_kernels.o obj/im2col_kernels.o obj/col2im_kernels.o obj/blas_kernels.o obj/crop_layer_kernels.o obj/dropout_layer_kernels.o obj/maxpool_layer_kernels.o obj/network_kernels.o obj/avgpool_layer_kernels.o -o darknet -lm -pthread `pkg-config --libs opencv4 2> /dev/null || pkg-config --libs opencv` -L/usr/local/cuda/lib64 -lcuda -lcudart -lcublas -lcurand -L/usr/local/cudnn/lib64 -lcudnn -lstdc++ \n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "gAOLtA_qI9vF",
        "colab_type": "text"
      },
      "source": [
        "**3) Configure Darknet network for training YOLO V3**"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "s-RpscgU853t",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "!cp cfg/yolov3.cfg cfg/yolov3_training.cfg"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "5ZgVQRop_vwR",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "!sed -i 's/batch=1/batch=64/' cfg/yolov3_training.cfg\n",
        "!sed -i 's/subdivisions=1/subdivisions=16/' cfg/yolov3_training.cfg\n",
        "!sed -i 's/max_batches = 500200/max_batches = 4000/' cfg/yolov3_training.cfg\n",
        "!sed -i '610 s@classes=80@classes=1@' cfg/yolov3_training.cfg\n",
        "!sed -i '696 s@classes=80@classes=1@' cfg/yolov3_training.cfg\n",
        "!sed -i '783 s@classes=80@classes=1@' cfg/yolov3_training.cfg\n",
        "!sed -i '603 s@filters=255@filters=18@' cfg/yolov3_training.cfg\n",
        "!sed -i '689 s@filters=255@filters=18@' cfg/yolov3_training.cfg\n",
        "!sed -i '776 s@filters=255@filters=18@' cfg/yolov3_training.cfg"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "nscRN-X2Mr3d",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 34
        },
        "outputId": "9ab86dbc-77c7-4d33-fbb6-be628d5fa5d9"
      },
      "source": [
        "# Create folder on google drive so that we can save there the weights\n",
        "!mkdir \"/mydrive/yolov3\""
      ],
      "execution_count": 7,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "mkdir: cannot create directory ‘/mydrive/yolov3’: File exists\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "7AIBw_psIclz",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "!echo \"License\" > data/obj.names\n",
        "!echo -e 'classes= 1\\ntrain  = data/train.txt\\nvalid  = data/test.txt\\nnames = data/obj.names\\nbackup = /mydrive/yolov3' > data/obj.data\n",
        "!mkdir data/obj"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "eZlkzFMW7I_N",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 204
        },
        "outputId": "ad1c6cf8-4a5d-4abc-a3dc-99853afa2443"
      },
      "source": [
        "# Download weights darknet model 53\n",
        "!wget https://pjreddie.com/media/files/darknet53.conv.74"
      ],
      "execution_count": 9,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "--2020-05-01 07:17:04--  https://pjreddie.com/media/files/darknet53.conv.74\n",
            "Resolving pjreddie.com (pjreddie.com)... 128.208.4.108\n",
            "Connecting to pjreddie.com (pjreddie.com)|128.208.4.108|:443... connected.\n",
            "HTTP request sent, awaiting response... 200 OK\n",
            "Length: 162482580 (155M) [application/octet-stream]\n",
            "Saving to: ‘darknet53.conv.74’\n",
            "\n",
            "darknet53.conv.74   100%[===================>] 154.96M  2.18MB/s    in 1m 49s  \n",
            "\n",
            "2020-05-01 07:18:54 (1.42 MB/s) - ‘darknet53.conv.74’ saved [162482580/162482580]\n",
            "\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "9RbVKJjoncW2",
        "colab_type": "text"
      },
      "source": [
        "**4) Extract Images**\n",
        "\n",
        "The images need to be inside a zip archive called \"images.zip\" and they need to be inside the folder \"yolov3\" on Google Drive"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "jhb5nZvsQ_96",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 1000
        },
        "outputId": "447fa2f5-9f93-4c06-901b-cd1e12b5044d"
      },
      "source": [
        "!unzip /mydrive/yolov3/images.zip -d data/obj"
      ],
      "execution_count": 10,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Archive:  /mydrive/yolov3/images.zip\n",
            "  inflating: data/obj/20.jpg         \n",
            "  inflating: data/obj/20.txt         \n",
            " extracting: data/obj/22403415607-7d842000e2-b.jpg  \n",
            " extracting: data/obj/22403415607-7d842000e2-b.txt  \n",
            "  inflating: data/obj/7.jpg          \n",
            "  inflating: data/obj/7.txt          \n",
            "  inflating: data/obj/75ad7d9a68b8dbac61cf0210fb5159b6.jpg  \n",
            " extracting: data/obj/75ad7d9a68b8dbac61cf0210fb5159b6.txt  \n",
            "  inflating: data/obj/7dab210d4d37b58c34e17347d57d4d36.jpg  \n",
            " extracting: data/obj/7dab210d4d37b58c34e17347d57d4d36.txt  \n",
            "  inflating: data/obj/car-embossed.jpg  \n",
            "  inflating: data/obj/car-embossed.txt  \n",
            "  inflating: data/obj/Car-Image-with-Indian-Number-Plate.png  \n",
            " extracting: data/obj/Car-Image-with-Indian-Number-Plate.txt  \n",
            "  inflating: data/obj/Car-Number-Plate.jpg  \n",
            "  inflating: data/obj/Car-Number-Plate.txt  \n",
            "  inflating: data/obj/classes.txt    \n",
            "  inflating: data/obj/d2.jpg         \n",
            "  inflating: data/obj/d2.txt         \n",
            "  inflating: data/obj/d4.jpg         \n",
            "  inflating: data/obj/d4.txt         \n",
            "  inflating: data/obj/d7e06425bcb8ae719796190434d1b649.jpg  \n",
            " extracting: data/obj/d7e06425bcb8ae719796190434d1b649.txt  \n",
            "  inflating: data/obj/DbH5xTRXkAAsLoy.jpg  \n",
            "  inflating: data/obj/DbH5xTRXkAAsLoy.txt  \n",
            "  inflating: data/obj/delhi number plate.jpg  \n",
            "  inflating: data/obj/delhi number plate.txt  \n",
            "  inflating: data/obj/Dqrjk2WVsAEuArf.jpg  \n",
            "  inflating: data/obj/Dqrjk2WVsAEuArf.txt  \n",
            "  inflating: data/obj/DSC00161.JPG   \n",
            "  inflating: data/obj/DSC00161.txt   \n",
            "  inflating: data/obj/electric-cars-green-number-plate-827x510-51525929214.jpg  \n",
            "  inflating: data/obj/electric-cars-green-number-plate-827x510-51525929214.txt  \n",
            "  inflating: data/obj/electric-vehicles-india-ev-mandate-ev-green-number-plates-el.jpg  \n",
            "  inflating: data/obj/electric-vehicles-india-ev-mandate-ev-green-number-plates-el.txt  \n",
            "  inflating: data/obj/images_1.jpg   \n",
            "  inflating: data/obj/images_1.txt   \n",
            "  inflating: data/obj/images_10.jpg  \n",
            "  inflating: data/obj/images_10.txt  \n",
            "  inflating: data/obj/images_100.jpg  \n",
            " extracting: data/obj/images_100.txt  \n",
            "  inflating: data/obj/images_101.jpg  \n",
            "  inflating: data/obj/images_102.jpg  \n",
            "  inflating: data/obj/images_103.jpg  \n",
            "  inflating: data/obj/images_103.txt  \n",
            "  inflating: data/obj/images_104.jpg  \n",
            "  inflating: data/obj/images_104.txt  \n",
            " extracting: data/obj/images_105.jpg  \n",
            "  inflating: data/obj/images_106.jpg  \n",
            "  inflating: data/obj/images_106.txt  \n",
            "  inflating: data/obj/images_107.jpg  \n",
            " extracting: data/obj/images_107.txt  \n",
            "  inflating: data/obj/images_109.jpg  \n",
            "  inflating: data/obj/images_109.txt  \n",
            "  inflating: data/obj/images_11.jpg  \n",
            "  inflating: data/obj/images_11.txt  \n",
            "  inflating: data/obj/images_110.jpg  \n",
            "  inflating: data/obj/images_110.txt  \n",
            "  inflating: data/obj/images_111.jpg  \n",
            "  inflating: data/obj/images_111.txt  \n",
            "  inflating: data/obj/images_112.jpg  \n",
            "  inflating: data/obj/images_112.txt  \n",
            "  inflating: data/obj/images_113.jpg  \n",
            "  inflating: data/obj/images_113.txt  \n",
            "  inflating: data/obj/images_114.jpg  \n",
            "  inflating: data/obj/images_114.txt  \n",
            "  inflating: data/obj/images_115.jpg  \n",
            "  inflating: data/obj/images_115.txt  \n",
            "  inflating: data/obj/images_116.jpg  \n",
            "  inflating: data/obj/images_116.txt  \n",
            "  inflating: data/obj/images_117.jpg  \n",
            "  inflating: data/obj/images_117.txt  \n",
            "  inflating: data/obj/images_118.jpg  \n",
            "  inflating: data/obj/images_118.txt  \n",
            "  inflating: data/obj/images_119.jpg  \n",
            "  inflating: data/obj/images_119.txt  \n",
            "  inflating: data/obj/images_12.jpg  \n",
            "  inflating: data/obj/images_12.txt  \n",
            "  inflating: data/obj/images_120.jpg  \n",
            "  inflating: data/obj/images_120.txt  \n",
            "  inflating: data/obj/images_121.jpg  \n",
            "  inflating: data/obj/images_121.txt  \n",
            "  inflating: data/obj/images_122.jpg  \n",
            "  inflating: data/obj/images_122.txt  \n",
            "  inflating: data/obj/images_123.jpg  \n",
            " extracting: data/obj/images_123.txt  \n",
            "  inflating: data/obj/images_124.jpg  \n",
            "  inflating: data/obj/images_124.txt  \n",
            "  inflating: data/obj/images_125.jpg  \n",
            "  inflating: data/obj/images_125.txt  \n",
            "  inflating: data/obj/images_126.jpg  \n",
            " extracting: data/obj/images_126.txt  \n",
            "  inflating: data/obj/images_127.jpg  \n",
            "  inflating: data/obj/images_127.txt  \n",
            "  inflating: data/obj/images_128.jpg  \n",
            " extracting: data/obj/images_128.txt  \n",
            "  inflating: data/obj/images_129.jpg  \n",
            "  inflating: data/obj/images_129.txt  \n",
            "  inflating: data/obj/images_13.jpg  \n",
            "  inflating: data/obj/images_13.txt  \n",
            "  inflating: data/obj/images_130.jpg  \n",
            "  inflating: data/obj/images_130.txt  \n",
            "  inflating: data/obj/images_131.jpg  \n",
            "  inflating: data/obj/images_131.txt  \n",
            "  inflating: data/obj/images_132.jpg  \n",
            "  inflating: data/obj/images_132.txt  \n",
            "  inflating: data/obj/images_133.jpg  \n",
            "  inflating: data/obj/images_133.txt  \n",
            "  inflating: data/obj/images_134.jpg  \n",
            "  inflating: data/obj/images_134.txt  \n",
            "  inflating: data/obj/images_135.jpg  \n",
            "  inflating: data/obj/images_135.txt  \n",
            "  inflating: data/obj/images_137.jpg  \n",
            "  inflating: data/obj/images_137.txt  \n",
            "  inflating: data/obj/images_138.jpg  \n",
            "  inflating: data/obj/images_138.txt  \n",
            "  inflating: data/obj/images_139.jpg  \n",
            "  inflating: data/obj/images_139.txt  \n",
            "  inflating: data/obj/images_14.jpg  \n",
            "  inflating: data/obj/images_14.txt  \n",
            "  inflating: data/obj/images_140.jpg  \n",
            " extracting: data/obj/images_140.txt  \n",
            "  inflating: data/obj/images_141.jpg  \n",
            "  inflating: data/obj/images_141.txt  \n",
            "  inflating: data/obj/images_142.jpg  \n",
            "  inflating: data/obj/images_142.txt  \n",
            "  inflating: data/obj/images_144.jpg  \n",
            " extracting: data/obj/images_144.txt  \n",
            "  inflating: data/obj/images_145.jpg  \n",
            "  inflating: data/obj/images_145.txt  \n",
            "  inflating: data/obj/images_146.jpg  \n",
            "  inflating: data/obj/images_146.txt  \n",
            "  inflating: data/obj/images_147.jpg  \n",
            "  inflating: data/obj/images_147.txt  \n",
            "  inflating: data/obj/images_148.jpg  \n",
            "  inflating: data/obj/images_148.txt  \n",
            "  inflating: data/obj/images_149.jpg  \n",
            " extracting: data/obj/images_149.txt  \n",
            "  inflating: data/obj/images_15.jpg  \n",
            "  inflating: data/obj/images_15.txt  \n",
            "  inflating: data/obj/images_150.jpg  \n",
            " extracting: data/obj/images_150.txt  \n",
            "  inflating: data/obj/images_151.jpg  \n",
            " extracting: data/obj/images_151.txt  \n",
            "  inflating: data/obj/images_152.jpg  \n",
            "  inflating: data/obj/images_152.txt  \n",
            "  inflating: data/obj/images_153.jpg  \n",
            " extracting: data/obj/images_153.txt  \n",
            "  inflating: data/obj/images_154.jpg  \n",
            "  inflating: data/obj/images_154.txt  \n",
            "  inflating: data/obj/images_155.jpg  \n",
            " extracting: data/obj/images_155.txt  \n",
            "  inflating: data/obj/images_156.jpg  \n",
            " extracting: data/obj/images_156.txt  \n",
            "  inflating: data/obj/images_157.jpg  \n",
            "  inflating: data/obj/images_157.txt  \n",
            "  inflating: data/obj/images_158.jpg  \n",
            "  inflating: data/obj/images_158.txt  \n",
            "  inflating: data/obj/images_159.jpg  \n",
            "  inflating: data/obj/images_16.jpg  \n",
            "  inflating: data/obj/images_16.txt  \n",
            " extracting: data/obj/images_160.jpg  \n",
            " extracting: data/obj/images_160.txt  \n",
            " extracting: data/obj/images_161.jpg  \n",
            "  inflating: data/obj/images_161.txt  \n",
            "  inflating: data/obj/images_162.jpg  \n",
            "  inflating: data/obj/images_162.txt  \n",
            "  inflating: data/obj/images_163.jpg  \n",
            "  inflating: data/obj/images_163.txt  \n",
            "  inflating: data/obj/images_164.jpg  \n",
            "  inflating: data/obj/images_164.txt  \n",
            "  inflating: data/obj/images_165.jpg  \n",
            " extracting: data/obj/images_165.txt  \n",
            "  inflating: data/obj/images_166.jpg  \n",
            "  inflating: data/obj/images_167.jpg  \n",
            "  inflating: data/obj/images_168.jpg  \n",
            "  inflating: data/obj/images_168.txt  \n",
            "  inflating: data/obj/images_169.jpg  \n",
            " extracting: data/obj/images_169.txt  \n",
            "  inflating: data/obj/images_17.jpg  \n",
            " extracting: data/obj/images_17.txt  \n",
            "  inflating: data/obj/images_170.jpg  \n",
            "  inflating: data/obj/images_171.jpg  \n",
            "  inflating: data/obj/images_171.txt  \n",
            "  inflating: data/obj/images_172.jpg  \n",
            "  inflating: data/obj/images_173.jpg  \n",
            " extracting: data/obj/images_173.txt  \n",
            "  inflating: data/obj/images_174.jpg  \n",
            "  inflating: data/obj/images_174.txt  \n",
            "  inflating: data/obj/images_175.jpg  \n",
            "  inflating: data/obj/images_175.txt  \n",
            "  inflating: data/obj/images_176.jpg  \n",
            "  inflating: data/obj/images_177.jpg  \n",
            "  inflating: data/obj/images_177.txt  \n",
            "  inflating: data/obj/images_178.jpg  \n",
            "  inflating: data/obj/images_178.txt  \n",
            "  inflating: data/obj/images_179.jpg  \n",
            "  inflating: data/obj/images_179.txt  \n",
            "  inflating: data/obj/images_18.jpg  \n",
            "  inflating: data/obj/images_18.txt  \n",
            "  inflating: data/obj/images_180.jpg  \n",
            " extracting: data/obj/images_180.txt  \n",
            "  inflating: data/obj/images_181.jpg  \n",
            "  inflating: data/obj/images_182.jpg  \n",
            "  inflating: data/obj/images_182.txt  \n",
            " extracting: data/obj/images_183.jpg  \n",
            " extracting: data/obj/images_183.txt  \n",
            "  inflating: data/obj/images_184.jpg  \n",
            " extracting: data/obj/images_184.txt  \n",
            "  inflating: data/obj/images_185.jpg  \n",
            "  inflating: data/obj/images_185.txt  \n",
            "  inflating: data/obj/images_186.jpg  \n",
            " extracting: data/obj/images_186.txt  \n",
            "  inflating: data/obj/images_187.jpg  \n",
            "  inflating: data/obj/images_187.txt  \n",
            "  inflating: data/obj/images_188.jpg  \n",
            "  inflating: data/obj/images_188.txt  \n",
            "  inflating: data/obj/images_189.jpg  \n",
            " extracting: data/obj/images_189.txt  \n",
            "  inflating: data/obj/images_19.jpg  \n",
            "  inflating: data/obj/images_19.txt  \n",
            "  inflating: data/obj/images_190.jpg  \n",
            " extracting: data/obj/images_190.txt  \n",
            "  inflating: data/obj/images_191.jpg  \n",
            "  inflating: data/obj/images_191.txt  \n",
            "  inflating: data/obj/images_192.jpg  \n",
            "  inflating: data/obj/images_192.txt  \n",
            "  inflating: data/obj/images_193.jpg  \n",
            "  inflating: data/obj/images_193.txt  \n",
            "  inflating: data/obj/images_197.jpg  \n",
            "  inflating: data/obj/images_197.txt  \n",
            "  inflating: data/obj/images_198.jpg  \n",
            " extracting: data/obj/images_199.jpg  \n",
            "  inflating: data/obj/images_199.txt  \n",
            "  inflating: data/obj/images_2.jpg   \n",
            "  inflating: data/obj/images_2.txt   \n",
            "  inflating: data/obj/images_20.jpg  \n",
            "  inflating: data/obj/images_20.txt  \n",
            "  inflating: data/obj/images_200.jpg  \n",
            "  inflating: data/obj/images_200.txt  \n",
            "  inflating: data/obj/images_201.jpg  \n",
            "  inflating: data/obj/images_202.jpg  \n",
            " extracting: data/obj/images_202.txt  \n",
            "  inflating: data/obj/images_203.jpg  \n",
            " extracting: data/obj/images_203.txt  \n",
            "  inflating: data/obj/images_204.jpg  \n",
            "  inflating: data/obj/images_204.txt  \n",
            "  inflating: data/obj/images_205.jpg  \n",
            "  inflating: data/obj/images_205.txt  \n",
            "  inflating: data/obj/images_206.jpg  \n",
            "  inflating: data/obj/images_206.txt  \n",
            "  inflating: data/obj/images_207.jpg  \n",
            " extracting: data/obj/images_207.txt  \n",
            "  inflating: data/obj/images_208.jpg  \n",
            " extracting: data/obj/images_208.txt  \n",
            "  inflating: data/obj/images_209.jpg  \n",
            "  inflating: data/obj/images_209.txt  \n",
            "  inflating: data/obj/images_21.jpg  \n",
            "  inflating: data/obj/images_21.txt  \n",
            "  inflating: data/obj/images_210.jpg  \n",
            " extracting: data/obj/images_210.txt  \n",
            "  inflating: data/obj/images_211.jpg  \n",
            "  inflating: data/obj/images_211.txt  \n",
            "  inflating: data/obj/images_212.jpg  \n",
            "  inflating: data/obj/images_212.txt  \n",
            "  inflating: data/obj/images_213.jpg  \n",
            "  inflating: data/obj/images_213.txt  \n",
            "  inflating: data/obj/images_214.jpg  \n",
            "  inflating: data/obj/images_215.jpg  \n",
            "  inflating: data/obj/images_215.txt  \n",
            "  inflating: data/obj/images_216.jpg  \n",
            " extracting: data/obj/images_216.txt  \n",
            "  inflating: data/obj/images_217.jpg  \n",
            " extracting: data/obj/images_217.txt  \n",
            "  inflating: data/obj/images_218.jpg  \n",
            "  inflating: data/obj/images_218.txt  \n",
            "  inflating: data/obj/images_219.jpg  \n",
            "  inflating: data/obj/images_219.txt  \n",
            "  inflating: data/obj/images_22.jpg  \n",
            " extracting: data/obj/images_22.txt  \n",
            "  inflating: data/obj/images_220.jpg  \n",
            "  inflating: data/obj/images_220.txt  \n",
            "  inflating: data/obj/images_221.jpg  \n",
            " extracting: data/obj/images_221.txt  \n",
            "  inflating: data/obj/images_222.jpg  \n",
            "  inflating: data/obj/images_222.txt  \n",
            "  inflating: data/obj/images_223.jpg  \n",
            " extracting: data/obj/images_223.txt  \n",
            "  inflating: data/obj/images_224.jpg  \n",
            " extracting: data/obj/images_224.txt  \n",
            "  inflating: data/obj/images_225.jpg  \n",
            "  inflating: data/obj/images_225.txt  \n",
            "  inflating: data/obj/images_226.jpg  \n",
            "  inflating: data/obj/images_226.txt  \n",
            "  inflating: data/obj/images_227.jpg  \n",
            " extracting: data/obj/images_227.txt  \n",
            "  inflating: data/obj/images_228.jpg  \n",
            "  inflating: data/obj/images_228.txt  \n",
            "  inflating: data/obj/images_229.jpg  \n",
            "  inflating: data/obj/images_229.txt  \n",
            "  inflating: data/obj/images_23.jpg  \n",
            "  inflating: data/obj/images_23.txt  \n",
            "  inflating: data/obj/images_230.jpg  \n",
            "  inflating: data/obj/images_230.txt  \n",
            "  inflating: data/obj/images_231.jpg  \n",
            " extracting: data/obj/images_231.txt  \n",
            "  inflating: data/obj/images_232.jpg  \n",
            " extracting: data/obj/images_232.txt  \n",
            "  inflating: data/obj/images_233.jpg  \n",
            "  inflating: data/obj/images_233.txt  \n",
            "  inflating: data/obj/images_234.jpg  \n",
            " extracting: data/obj/images_234.txt  \n",
            "  inflating: data/obj/images_235.jpg  \n",
            " extracting: data/obj/images_235.txt  \n",
            " extracting: data/obj/images_236.jpg  \n",
            "  inflating: data/obj/images_236.txt  \n",
            "  inflating: data/obj/images_237.jpg  \n",
            " extracting: data/obj/images_237.txt  \n",
            "  inflating: data/obj/images_24.jpg  \n",
            "  inflating: data/obj/images_24.txt  \n",
            "  inflating: data/obj/images_25.jpg  \n",
            "  inflating: data/obj/images_25.txt  \n",
            "  inflating: data/obj/images_26.jpg  \n",
            "  inflating: data/obj/images_26.txt  \n",
            "  inflating: data/obj/images_27.jpg  \n",
            "  inflating: data/obj/images_27.txt  \n",
            "  inflating: data/obj/images_28.jpg  \n",
            " extracting: data/obj/images_28.txt  \n",
            "  inflating: data/obj/images_29.jpg  \n",
            "  inflating: data/obj/images_29.txt  \n",
            "  inflating: data/obj/images_3.jpg   \n",
            " extracting: data/obj/images_3.txt   \n",
            "  inflating: data/obj/images_30.jpg  \n",
            "  inflating: data/obj/images_30.txt  \n",
            "  inflating: data/obj/images_31.jpg  \n",
            "  inflating: data/obj/images_31.txt  \n",
            "  inflating: data/obj/images_32.jpg  \n",
            "  inflating: data/obj/images_32.txt  \n",
            "  inflating: data/obj/images_33.jpg  \n",
            "  inflating: data/obj/images_33.txt  \n",
            "  inflating: data/obj/images_34.jpg  \n",
            "  inflating: data/obj/images_34.txt  \n",
            "  inflating: data/obj/images_35.jpg  \n",
            " extracting: data/obj/images_35.txt  \n",
            "  inflating: data/obj/images_36.jpg  \n",
            "  inflating: data/obj/images_36.txt  \n",
            "  inflating: data/obj/images_37.jpg  \n",
            "  inflating: data/obj/images_38.jpg  \n",
            "  inflating: data/obj/images_38.txt  \n",
            "  inflating: data/obj/images_39.jpg  \n",
            "  inflating: data/obj/images_39.txt  \n",
            "  inflating: data/obj/images_4.jpg   \n",
            "  inflating: data/obj/images_4.txt   \n",
            "  inflating: data/obj/images_40.jpg  \n",
            "  inflating: data/obj/images_40.txt  \n",
            "  inflating: data/obj/images_41.jpg  \n",
            "  inflating: data/obj/images_41.txt  \n",
            "  inflating: data/obj/images_42.jpg  \n",
            "  inflating: data/obj/images_42.txt  \n",
            "  inflating: data/obj/images_43.jpg  \n",
            "  inflating: data/obj/images_43.txt  \n",
            "  inflating: data/obj/images_44.jpg  \n",
            "  inflating: data/obj/images_44.txt  \n",
            "  inflating: data/obj/images_45.jpg  \n",
            "  inflating: data/obj/images_45.txt  \n",
            "  inflating: data/obj/images_46.jpg  \n",
            "  inflating: data/obj/images_46.txt  \n",
            "  inflating: data/obj/images_47.jpg  \n",
            " extracting: data/obj/images_47.txt  \n",
            "  inflating: data/obj/images_48.jpg  \n",
            "  inflating: data/obj/images_48.txt  \n",
            "  inflating: data/obj/images_49.jpg  \n",
            " extracting: data/obj/images_49.txt  \n",
            "  inflating: data/obj/images_5.jpg   \n",
            "  inflating: data/obj/images_5.txt   \n",
            "  inflating: data/obj/images_50.jpg  \n",
            " extracting: data/obj/images_50.txt  \n",
            "  inflating: data/obj/images_51.jpg  \n",
            " extracting: data/obj/images_51.txt  \n",
            "  inflating: data/obj/images_52.jpg  \n",
            "  inflating: data/obj/images_52.txt  \n",
            "  inflating: data/obj/images_53.jpg  \n",
            " extracting: data/obj/images_53.txt  \n",
            "  inflating: data/obj/images_54.jpg  \n",
            "  inflating: data/obj/images_54.txt  \n",
            "  inflating: data/obj/images_55.jpg  \n",
            "  inflating: data/obj/images_55.txt  \n",
            "  inflating: data/obj/images_56.jpg  \n",
            " extracting: data/obj/images_56.txt  \n",
            "  inflating: data/obj/images_57.jpg  \n",
            " extracting: data/obj/images_58.jpg  \n",
            "  inflating: data/obj/images_58.txt  \n",
            "  inflating: data/obj/images_59.jpg  \n",
            "  inflating: data/obj/images_59.txt  \n",
            "  inflating: data/obj/images_60.jpg  \n",
            " extracting: data/obj/images_60.txt  \n",
            "  inflating: data/obj/images_61.jpg  \n",
            " extracting: data/obj/images_61.txt  \n",
            "  inflating: data/obj/images_62.jpg  \n",
            "  inflating: data/obj/images_62.txt  \n",
            "  inflating: data/obj/images_63.jpg  \n",
            " extracting: data/obj/images_63.txt  \n",
            "  inflating: data/obj/images_64.jpg  \n",
            "  inflating: data/obj/images_64.txt  \n",
            "  inflating: data/obj/images_65.jpg  \n",
            "  inflating: data/obj/images_65.txt  \n",
            "  inflating: data/obj/images_66.jpg  \n",
            "  inflating: data/obj/images_66.txt  \n",
            "  inflating: data/obj/images_67.jpg  \n",
            "  inflating: data/obj/images_67.txt  \n",
            "  inflating: data/obj/images_68.jpg  \n",
            "  inflating: data/obj/images_68.txt  \n",
            "  inflating: data/obj/images_69.jpg  \n",
            "  inflating: data/obj/images_69.txt  \n",
            "  inflating: data/obj/images_7.jpg   \n",
            "  inflating: data/obj/images_7.txt   \n",
            "  inflating: data/obj/images_70.jpg  \n",
            " extracting: data/obj/images_70.txt  \n",
            "  inflating: data/obj/images_71.jpg  \n",
            "  inflating: data/obj/images_71.txt  \n",
            "  inflating: data/obj/images_72.jpg  \n",
            " extracting: data/obj/images_72.txt  \n",
            "  inflating: data/obj/images_73.jpg  \n",
            "  inflating: data/obj/images_73.txt  \n",
            "  inflating: data/obj/images_74.jpg  \n",
            " extracting: data/obj/images_74.txt  \n",
            "  inflating: data/obj/images_75.jpg  \n",
            "  inflating: data/obj/images_75.txt  \n",
            "  inflating: data/obj/images_76.jpg  \n",
            "  inflating: data/obj/images_76.txt  \n",
            "  inflating: data/obj/images_77.jpg  \n",
            "  inflating: data/obj/images_77.txt  \n",
            "  inflating: data/obj/images_78.jpg  \n",
            "  inflating: data/obj/images_78.txt  \n",
            "  inflating: data/obj/images_79.jpg  \n",
            "  inflating: data/obj/images_79.txt  \n",
            "  inflating: data/obj/images_8.jpg   \n",
            "  inflating: data/obj/images_8.txt   \n",
            "  inflating: data/obj/images_80.jpg  \n",
            "  inflating: data/obj/images_80.txt  \n",
            "  inflating: data/obj/images_81.jpg  \n",
            " extracting: data/obj/images_81.txt  \n",
            "  inflating: data/obj/images_82.jpg  \n",
            " extracting: data/obj/images_82.txt  \n",
            "  inflating: data/obj/images_83.jpg  \n",
            "  inflating: data/obj/images_83.txt  \n",
            "  inflating: data/obj/images_84.jpg  \n",
            "  inflating: data/obj/images_84.txt  \n",
            "  inflating: data/obj/images_85.jpg  \n",
            "  inflating: data/obj/images_85.txt  \n",
            "  inflating: data/obj/images_86.jpg  \n",
            " extracting: data/obj/images_86.txt  \n",
            "  inflating: data/obj/images_87.jpg  \n",
            "  inflating: data/obj/images_87.txt  \n",
            "  inflating: data/obj/images_88.jpg  \n",
            "  inflating: data/obj/images_88.txt  \n",
            "  inflating: data/obj/images_89.jpg  \n",
            "  inflating: data/obj/images_9.jpg   \n",
            " extracting: data/obj/images_9.txt   \n",
            "  inflating: data/obj/images_90.jpg  \n",
            "  inflating: data/obj/images_90.txt  \n",
            "  inflating: data/obj/images_91.jpg  \n",
            "  inflating: data/obj/images_91.txt  \n",
            "  inflating: data/obj/images_92.jpg  \n",
            "  inflating: data/obj/images_92.txt  \n",
            "  inflating: data/obj/images_93.jpg  \n",
            "  inflating: data/obj/images_93.txt  \n",
            "  inflating: data/obj/images_94.jpg  \n",
            " extracting: data/obj/images_94.txt  \n",
            "  inflating: data/obj/images_95.jpg  \n",
            "  inflating: data/obj/images_95.txt  \n",
            "  inflating: data/obj/images_96.jpg  \n",
            "  inflating: data/obj/images_96.txt  \n",
            "  inflating: data/obj/images_98.jpg  \n",
            "  inflating: data/obj/images_98.txt  \n",
            "  inflating: data/obj/images_99.jpg  \n",
            "  inflating: data/obj/images_99.txt  \n",
            "  inflating: data/obj/india-skoda-license-plate.jpg  \n",
            "  inflating: data/obj/india-skoda-license-plate.txt  \n",
            "  inflating: data/obj/india-uttarakhand-rishikesh-car-plate-close-up-BK64DW.jpg  \n",
            " extracting: data/obj/india-uttarakhand-rishikesh-car-plate-close-up-BK64DW.txt  \n",
            "  inflating: data/obj/License-plate-india-header-1920x730.jpg  \n",
            "  inflating: data/obj/License-plate-india-header-1920x730.txt  \n",
            "  inflating: data/obj/main-cropped.jpg  \n",
            " extracting: data/obj/main-cropped.txt  \n",
            "  inflating: data/obj/main-qimg-125a65253f383b7209f33bc455463807.jpeg  \n",
            " extracting: data/obj/main-qimg-125a65253f383b7209f33bc455463807.txt  \n",
            "  inflating: data/obj/maxresdefault.jpg  \n",
            "  inflating: data/obj/maxresdefault.txt  \n",
            "  inflating: data/obj/NoPlate.jpg    \n",
            " extracting: data/obj/NoPlate.txt    \n",
            "  inflating: data/obj/number plate.jpg  \n",
            "  inflating: data/obj/number plate.txt  \n",
            "  inflating: data/obj/plate 2.JPG    \n",
            "  inflating: data/obj/plate 2.txt    \n",
            "  inflating: data/obj/Red-Number-Plate.jpg  \n",
            "  inflating: data/obj/Red-Number-Plate.txt  \n",
            "  inflating: data/obj/Samples-of-Characters-for-Recognition-Sample-Indian-Vehicle-.jpg  \n",
            "  inflating: data/obj/Samples-of-Characters-for-Recognition-Sample-Indian-Vehicle-.txt  \n",
            "  inflating: data/obj/skoda-india-front-license-plate.jpg  \n",
            "  inflating: data/obj/skoda-india-front-license-plate.txt  \n",
            "  inflating: data/obj/Skoda-Kodiaq-India-Review-15.jpg  \n",
            "  inflating: data/obj/Skoda-Kodiaq-India-Review-15.txt  \n",
            "  inflating: data/obj/Swift Rear2.JPG  \n",
            "  inflating: data/obj/Swift Rear2.txt  \n",
            "  inflating: data/obj/typesofcarnumberplates-02-01.jpg  \n",
            " extracting: data/obj/typesofcarnumberplates-02-01.txt  \n",
            "  inflating: data/obj/vehicle-with-a-licence-plate-from-the-indian-state-of-sikkim.jpg  \n",
            "  inflating: data/obj/vehicle-with-a-licence-plate-from-the-indian-state-of-sikkim.txt  \n",
            "  inflating: data/obj/vehicles-will-soon-come-fitted-with-number-plates6-155437216.jpg  \n",
            "  inflating: data/obj/vehicles-will-soon-come-fitted-with-number-plates6-155437216.txt  \n",
            "  inflating: data/obj/vehicles-will-soon-come-fitted-with-number-plates8-152447991.jpg  \n",
            "  inflating: data/obj/vehicles-will-soon-come-fitted-with-number-plates8-152447991.txt  \n",
            "  inflating: data/obj/Why-IND-is-written-on-vehicle-number-plates.jpg  \n",
            " extracting: data/obj/Why-IND-is-written-on-vehicle-number-plates.txt  \n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "DGUyXxeYX0IP",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 1000
        },
        "outputId": "d78ab0df-fa04-477c-e04b-178414a86b13"
      },
      "source": [
        "# We're going to convert the class index on the .txt files. As we're working with only one class, it's supposed to be class 0.\n",
        "# If the index is different from 0 then we're going to change it.\n",
        "import glob\n",
        "import os\n",
        "import re\n",
        "\n",
        "txt_file_paths = glob.glob(r\"data/obj/*.txt\")\n",
        "for i, file_path in enumerate(txt_file_paths):\n",
        "    # get image size\n",
        "    with open(file_path, \"r\") as f_o:\n",
        "        lines = f_o.readlines()\n",
        "\n",
        "        text_converted = []\n",
        "        for line in lines:\n",
        "            print(line)\n",
        "            numbers = re.findall(\"[0-9.]+\", line)\n",
        "            print(numbers)\n",
        "            if numbers:\n",
        "\n",
        "                # Define coordinates\n",
        "                text = \"{} {} {} {} {}\".format(0, numbers[1], numbers[2], numbers[3], numbers[4])\n",
        "                text_converted.append(text)\n",
        "                print(i, file_path)\n",
        "                print(text)\n",
        "        # Write file\n",
        "        with open(file_path, 'w') as fp:\n",
        "            for item in text_converted:\n",
        "                fp.writelines(\"%s\\n\" % item)"
      ],
      "execution_count": 11,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
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            "\n",
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            "0 data/obj/images_180.txt\n",
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            "\n",
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            "\n",
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            "['15', '0.494078', '0.520877', '0.338409', '0.102296']\n",
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            "['15', '0.505168', '0.588785', '0.268734', '0.087227']\n",
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            "\n",
            "['15', '0.441406', '0.490972', '0.309375', '0.281944']\n",
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            "\n",
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            "\n",
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            "\n",
            "['15', '0.595052', '0.539062', '0.177083', '0.056641']\n",
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            "\n",
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            "\n",
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            "\n",
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            "\n",
            "['15', '0.458333', '0.461424', '0.253333', '0.103858']\n",
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            "\n",
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            "\n",
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            "\n",
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            "\n",
            "['15', '0.519000', '0.802326', '0.342000', '0.081395']\n",
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            "\n",
            "['15', '0.554688', '0.445312', '0.343750', '0.058594']\n",
            "56 data/obj/images_24.txt\n",
            "0 0.554688 0.445312 0.343750 0.058594\n",
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            "\n",
            "['15', '0.512308', '0.803245', '0.258462', '0.081136']\n",
            "57 data/obj/images_165.txt\n",
            "0 0.512308 0.803245 0.258462 0.081136\n",
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            "\n",
            "['15', '0.460674', '0.565903', '0.575281', '0.335244']\n",
            "58 data/obj/images_81.txt\n",
            "0 0.460674 0.565903 0.575281 0.335244\n",
            "15 0.505531 0.602190 0.263274 0.153285\n",
            "\n",
            "['15', '0.505531', '0.602190', '0.263274', '0.153285']\n",
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            "15 0.520000 0.456590 0.673846 0.273013\n",
            "\n",
            "['15', '0.520000', '0.456590', '0.673846', '0.273013']\n",
            "197 data/obj/vehicle-with-a-licence-plate-from-the-indian-state-of-sikkim.txt\n",
            "0 0.520000 0.456590 0.673846 0.273013\n",
            "15 0.522778 0.587917 0.144444 0.064167\n",
            "\n",
            "['15', '0.522778', '0.587917', '0.144444', '0.064167']\n",
            "198 data/obj/images_88.txt\n",
            "0 0.522778 0.587917 0.144444 0.064167\n",
            "15 0.493000 0.524490 0.982000 0.926531\n",
            "\n",
            "['15', '0.493000', '0.524490', '0.982000', '0.926531']\n",
            "199 data/obj/images_63.txt\n",
            "0 0.493000 0.524490 0.982000 0.926531\n",
            "15 0.497000 0.528226 0.306000 0.104839\n",
            "\n",
            "['15', '0.497000', '0.528226', '0.306000', '0.104839']\n",
            "200 data/obj/images_75.txt\n",
            "0 0.497000 0.528226 0.306000 0.104839\n",
            "15 0.541274 0.736948 0.398585 0.140562\n",
            "\n",
            "['15', '0.541274', '0.736948', '0.398585', '0.140562']\n",
            "201 data/obj/images_231.txt\n",
            "0 0.541274 0.736948 0.398585 0.140562\n",
            "15 0.577724 0.433333 0.209936 0.111111\n",
            "\n",
            "['15', '0.577724', '0.433333', '0.209936', '0.111111']\n",
            "202 data/obj/images_26.txt\n",
            "0 0.577724 0.433333 0.209936 0.111111\n",
            "15 0.227500 0.678042 0.145000 0.062315\n",
            "\n",
            "['15', '0.227500', '0.678042', '0.145000', '0.062315']\n",
            "203 data/obj/images_76.txt\n",
            "0 0.227500 0.678042 0.145000 0.062315\n",
            "15 0.783333 0.498516 0.126667 0.071217\n",
            "\n",
            "['15', '0.783333', '0.498516', '0.126667', '0.071217']\n",
            "203 data/obj/images_76.txt\n",
            "0 0.783333 0.498516 0.126667 0.071217\n",
            "15 0.496875 0.423333 0.813750 0.190000\n",
            "\n",
            "['15', '0.496875', '0.423333', '0.813750', '0.190000']\n",
            "204 data/obj/images_112.txt\n",
            "0 0.496875 0.423333 0.813750 0.190000\n",
            "15 0.545703 0.496458 0.549219 0.348288\n",
            "\n",
            "['15', '0.545703', '0.496458', '0.549219', '0.348288']\n",
            "205 data/obj/images_49.txt\n",
            "0 0.545703 0.496458 0.549219 0.348288\n",
            "15 0.657000 0.504274 0.418000 0.282051\n",
            "\n",
            "['15', '0.657000', '0.504274', '0.418000', '0.282051']\n",
            "206 data/obj/images_175.txt\n",
            "0 0.657000 0.504274 0.418000 0.282051\n",
            "15 0.476190 0.661765 0.326531 0.113445\n",
            "\n",
            "['15', '0.476190', '0.661765', '0.326531', '0.113445']\n",
            "207 data/obj/images_47.txt\n",
            "0 0.476190 0.661765 0.326531 0.113445\n",
            "15 0.331832 0.482000 0.417417 0.180000\n",
            "\n",
            "['15', '0.331832', '0.482000', '0.417417', '0.180000']\n",
            "208 data/obj/images_64.txt\n",
            "0 0.331832 0.482000 0.417417 0.180000\n",
            "15 0.509649 0.540541 0.121053 0.094595\n",
            "\n",
            "['15', '0.509649', '0.540541', '0.121053', '0.094595']\n",
            "209 data/obj/images_162.txt\n",
            "0 0.509649 0.540541 0.121053 0.094595\n",
            "15 0.464218 0.585938 0.280603 0.089844\n",
            "\n",
            "['15', '0.464218', '0.585938', '0.280603', '0.089844']\n",
            "210 data/obj/images_197.txt\n",
            "0 0.464218 0.585938 0.280603 0.089844\n",
            "15 0.685090 0.640449 0.208226 0.082397\n",
            "\n",
            "['15', '0.685090', '0.640449', '0.208226', '0.082397']\n",
            "211 data/obj/images_141.txt\n",
            "0 0.685090 0.640449 0.208226 0.082397\n",
            "15 0.466667 0.439502 0.874667 0.434164\n",
            "\n",
            "['15', '0.466667', '0.439502', '0.874667', '0.434164']\n",
            "212 data/obj/images_106.txt\n",
            "0 0.466667 0.439502 0.874667 0.434164\n",
            "15 0.555000 0.523333 0.415000 0.153333\n",
            "\n",
            "['15', '0.555000', '0.523333', '0.415000', '0.153333']\n",
            "213 data/obj/images_125.txt\n",
            "0 0.555000 0.523333 0.415000 0.153333\n",
            "15 0.493557 0.497992 0.311856 0.066934\n",
            "\n",
            "['15', '0.493557', '0.497992', '0.311856', '0.066934']\n",
            "214 data/obj/7dab210d4d37b58c34e17347d57d4d36.txt\n",
            "0 0.493557 0.497992 0.311856 0.066934\n",
            "15 0.363803 0.586996 0.343693 0.199634\n",
            "\n",
            "['15', '0.363803', '0.586996', '0.343693', '0.199634']\n",
            "215 data/obj/images_59.txt\n",
            "0 0.363803 0.586996 0.343693 0.199634\n",
            "15 0.321311 0.560825 0.222951 0.103093\n",
            "\n",
            "['15', '0.321311', '0.560825', '0.222951', '0.103093']\n",
            "216 data/obj/images_33.txt\n",
            "0 0.321311 0.560825 0.222951 0.103093\n",
            "15 0.305648 0.533923 0.219269 0.117994\n",
            "\n",
            "['15', '0.305648', '0.533923', '0.219269', '0.117994']\n",
            "217 data/obj/images_135.txt\n",
            "0 0.305648 0.533923 0.219269 0.117994\n",
            "15 0.424453 0.451025 0.475149 0.473804\n",
            "\n",
            "['15', '0.424453', '0.451025', '0.475149', '0.473804']\n",
            "218 data/obj/images_67.txt\n",
            "0 0.424453 0.451025 0.475149 0.473804\n",
            "15 0.323293 0.602510 0.453815 0.133891\n",
            "\n",
            "['15', '0.323293', '0.602510', '0.453815', '0.133891']\n",
            "219 data/obj/images_232.txt\n",
            "0 0.323293 0.602510 0.453815 0.133891\n",
            "15 0.300680 0.400756 0.198639 0.124764\n",
            "\n",
            "['15', '0.300680', '0.400756', '0.198639', '0.124764']\n",
            "220 data/obj/images_58.txt\n",
            "0 0.300680 0.400756 0.198639 0.124764\n",
            "15 0.751701 0.398866 0.216327 0.200378\n",
            "\n",
            "['15', '0.751701', '0.398866', '0.216327', '0.200378']\n",
            "220 data/obj/images_58.txt\n",
            "0 0.751701 0.398866 0.216327 0.200378\n",
            "15 0.484716 0.489286 0.585153 0.207143\n",
            "\n",
            "['15', '0.484716', '0.489286', '0.585153', '0.207143']\n",
            "221 data/obj/images_225.txt\n",
            "0 0.484716 0.489286 0.585153 0.207143\n",
            "15 0.165347 0.661808 0.243564 0.116618\n",
            "\n",
            "['15', '0.165347', '0.661808', '0.243564', '0.116618']\n",
            "222 data/obj/images_140.txt\n",
            "0 0.165347 0.661808 0.243564 0.116618\n",
            "15 0.605246 0.479367 0.648752 0.469290\n",
            "\n",
            "['15', '0.605246', '0.479367', '0.648752', '0.469290']\n",
            "223 data/obj/typesofcarnumberplates-02-01.txt\n",
            "0 0.605246 0.479367 0.648752 0.469290\n",
            "15 0.207534 0.680284 0.234247 0.085258\n",
            "\n",
            "['15', '0.207534', '0.680284', '0.234247', '0.085258']\n",
            "224 data/obj/images_34.txt\n",
            "0 0.207534 0.680284 0.234247 0.085258\n",
            "15 0.487903 0.646341 0.387097 0.170732\n",
            "\n",
            "['15', '0.487903', '0.646341', '0.387097', '0.170732']\n",
            "225 data/obj/images_121.txt\n",
            "0 0.487903 0.646341 0.387097 0.170732\n",
            "15 0.496377 0.541667 0.345411 0.083333\n",
            "\n",
            "['15', '0.496377', '0.541667', '0.345411', '0.083333']\n",
            "226 data/obj/images_62.txt\n",
            "0 0.496377 0.541667 0.345411 0.083333\n",
            "15 0.820833 0.692708 0.266667 0.102083\n",
            "\n",
            "['15', '0.820833', '0.692708', '0.266667', '0.102083']\n",
            "227 data/obj/images_82.txt\n",
            "0 0.820833 0.692708 0.266667 0.102083\n",
            "15 0.531000 0.603723 0.626000 0.207447\n",
            "\n",
            "['15', '0.531000', '0.603723', '0.626000', '0.207447']\n",
            "228 data/obj/images_145.txt\n",
            "0 0.531000 0.603723 0.626000 0.207447\n",
            "15 0.390000 0.750000 0.265000 0.133929\n",
            "\n",
            "['15', '0.390000', '0.750000', '0.265000', '0.133929']\n",
            "229 data/obj/images_228.txt\n",
            "0 0.390000 0.750000 0.265000 0.133929\n",
            "15 0.315000 0.458155 0.190000 0.100858\n",
            "\n",
            "['15', '0.315000', '0.458155', '0.190000', '0.100858']\n",
            "230 data/obj/images_41.txt\n",
            "0 0.315000 0.458155 0.190000 0.100858\n",
            "15 0.568010 0.734818 0.395466 0.141700\n",
            "\n",
            "['15', '0.568010', '0.734818', '0.395466', '0.141700']\n",
            "231 data/obj/images_220.txt\n",
            "0 0.568010 0.734818 0.395466 0.141700\n",
            "15 0.499196 0.463061 0.901929 0.720317\n",
            "\n",
            "['15', '0.499196', '0.463061', '0.901929', '0.720317']\n",
            "232 data/obj/images_109.txt\n",
            "0 0.499196 0.463061 0.901929 0.720317\n",
            "15 0.279000 0.597744 0.326000 0.218045\n",
            "\n",
            "['15', '0.279000', '0.597744', '0.326000', '0.218045']\n",
            "233 data/obj/images_28.txt\n",
            "0 0.279000 0.597744 0.326000 0.218045\n",
            "15 0.491000 0.802292 0.346000 0.126074\n",
            "\n",
            "['15', '0.491000', '0.802292', '0.346000', '0.126074']\n",
            "234 data/obj/images_72.txt\n",
            "0 0.491000 0.802292 0.346000 0.126074\n",
            "15 0.479000 0.677711 0.238000 0.060241\n",
            "\n",
            "['15', '0.479000', '0.677711', '0.238000', '0.060241']\n",
            "235 data/obj/images_235.txt\n",
            "0 0.479000 0.677711 0.238000 0.060241\n",
            "15 0.251599 0.725917 0.247335 0.094037\n",
            "\n",
            "['15', '0.251599', '0.725917', '0.247335', '0.094037']\n",
            "236 data/obj/images_53.txt\n",
            "0 0.251599 0.725917 0.247335 0.094037\n",
            "15 0.437500 0.884273 0.458333 0.183976\n",
            "\n",
            "['15', '0.437500', '0.884273', '0.458333', '0.183976']\n",
            "237 data/obj/images_149.txt\n",
            "0 0.437500 0.884273 0.458333 0.183976\n",
            "15 0.488333 0.498750 0.183333 0.057500\n",
            "\n",
            "['15', '0.488333', '0.498750', '0.183333', '0.057500']\n",
            "238 data/obj/images_188.txt\n",
            "0 0.488333 0.498750 0.183333 0.057500\n",
            "15 0.464844 0.371875 0.423438 0.156250\n",
            "\n",
            "['15', '0.464844', '0.371875', '0.423438', '0.156250']\n",
            "239 data/obj/Car-Image-with-Indian-Number-Plate.txt\n",
            "0 0.464844 0.371875 0.423438 0.156250\n",
            "15 0.494286 0.591006 0.285714 0.051392\n",
            "\n",
            "['15', '0.494286', '0.591006', '0.285714', '0.051392']\n",
            "240 data/obj/images_153.txt\n",
            "0 0.494286 0.591006 0.285714 0.051392\n",
            "15 0.470350 0.603535 0.374663 0.101010\n",
            "\n",
            "['15', '0.470350', '0.603535', '0.374663', '0.101010']\n",
            "241 data/obj/images_85.txt\n",
            "0 0.470350 0.603535 0.374663 0.101010\n",
            "15 0.539823 0.557895 0.560472 0.265263\n",
            "\n",
            "['15', '0.539823', '0.557895', '0.560472', '0.265263']\n",
            "242 data/obj/images_190.txt\n",
            "0 0.539823 0.557895 0.560472 0.265263\n",
            "15 0.305455 0.513109 0.247273 0.172285\n",
            "\n",
            "['15', '0.305455', '0.513109', '0.247273', '0.172285']\n",
            "243 data/obj/images_14.txt\n",
            "0 0.305455 0.513109 0.247273 0.172285\n",
            "15 0.665833 0.548817 0.265000 0.150888\n",
            "\n",
            "['15', '0.665833', '0.548817', '0.265000', '0.150888']\n",
            "244 data/obj/vehicles-will-soon-come-fitted-with-number-plates8-152447991.txt\n",
            "0 0.665833 0.548817 0.265000 0.150888\n",
            "15 0.438936 0.749020 0.159613 0.133333\n",
            "\n",
            "['15', '0.438936', '0.749020', '0.159613', '0.133333']\n",
            "245 data/obj/electric-cars-green-number-plate-827x510-51525929214.txt\n",
            "0 0.438936 0.749020 0.159613 0.133333\n",
            "15 0.520000 0.617442 0.216667 0.127907\n",
            "\n",
            "['15', '0.520000', '0.617442', '0.216667', '0.127907']\n",
            "246 data/obj/images_204.txt\n",
            "0 0.520000 0.617442 0.216667 0.127907\n",
            "15 0.496614 0.257530 0.875847 0.274096\n",
            "\n",
            "['15', '0.496614', '0.257530', '0.875847', '0.274096']\n",
            "247 data/obj/images_122.txt\n",
            "0 0.496614 0.257530 0.875847 0.274096\n",
            "15 0.502257 0.618976 0.900677 0.286145\n",
            "\n",
            "['15', '0.502257', '0.618976', '0.900677', '0.286145']\n",
            "247 data/obj/images_122.txt\n",
            "0 0.502257 0.618976 0.900677 0.286145\n",
            "15 0.511000 0.391892 0.270000 0.093093\n",
            "\n",
            "['15', '0.511000', '0.391892', '0.270000', '0.093093']\n",
            "248 data/obj/images_126.txt\n",
            "0 0.511000 0.391892 0.270000 0.093093\n",
            "15 0.546000 0.763855 0.264000 0.144578\n",
            "\n",
            "['15', '0.546000', '0.763855', '0.264000', '0.144578']\n",
            "249 data/obj/images_134.txt\n",
            "0 0.546000 0.763855 0.264000 0.144578\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "5I_0ht7ITMUu",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 71
        },
        "outputId": "873af4f5-ecdd-4b0d-9618-f757c94ec9f8"
      },
      "source": [
        "import glob\n",
        "images_list = glob.glob(\"data/obj/*.jpg\")\n",
        "images_list2 = glob.glob(\"data/obj/*.png\")\n",
        "images_list.extend(images_list2)\n",
        "print(images_list)\n",
        "print(len(images_list))"
      ],
      "execution_count": 14,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "['data/obj/DbH5xTRXkAAsLoy.jpg', 'data/obj/images_223.jpg', 'data/obj/images_93.jpg', 'data/obj/images_218.jpg', 'data/obj/images_16.jpg', 'data/obj/images_210.jpg', 'data/obj/images_237.jpg', 'data/obj/images_183.jpg', 'data/obj/Skoda-Kodiaq-India-Review-15.jpg', 'data/obj/images_155.jpg', 'data/obj/images_182.jpg', 'data/obj/images_14.jpg', 'data/obj/images_82.jpg', 'data/obj/images_204.jpg', 'data/obj/india-uttarakhand-rishikesh-car-plate-close-up-BK64DW.jpg', 'data/obj/images_162.jpg', 'data/obj/images_230.jpg', 'data/obj/images_205.jpg', 'data/obj/main-cropped.jpg', 'data/obj/images_31.jpg', 'data/obj/images_211.jpg', 'data/obj/images_132.jpg', 'data/obj/images_163.jpg', 'data/obj/images_157.jpg', 'data/obj/images_7.jpg', 'data/obj/images_209.jpg', 'data/obj/images_141.jpg', 'data/obj/images_207.jpg', 'data/obj/images_123.jpg', 'data/obj/images_169.jpg', 'data/obj/vehicle-with-a-licence-plate-from-the-indian-state-of-sikkim.jpg', 'data/obj/images_173.jpg', 'data/obj/images_106.jpg', 'data/obj/images_50.jpg', 'data/obj/images_90.jpg', 'data/obj/images_73.jpg', 'data/obj/images_38.jpg', 'data/obj/images_47.jpg', 'data/obj/images_131.jpg', 'data/obj/images_3.jpg', 'data/obj/images_104.jpg', 'data/obj/images_186.jpg', 'data/obj/images_188.jpg', 'data/obj/images_140.jpg', 'data/obj/images_68.jpg', 'data/obj/Dqrjk2WVsAEuArf.jpg', 'data/obj/75ad7d9a68b8dbac61cf0210fb5159b6.jpg', 'data/obj/car-embossed.jpg', 'data/obj/images_206.jpg', 'data/obj/images_127.jpg', 'data/obj/images_148.jpg', 'data/obj/images_12.jpg', 'data/obj/images_87.jpg', 'data/obj/License-plate-india-header-1920x730.jpg', 'data/obj/images_134.jpg', 'data/obj/images_49.jpg', 'data/obj/number plate.jpg', 'data/obj/images_20.jpg', 'data/obj/images_88.jpg', 'data/obj/images_26.jpg', 'data/obj/images_35.jpg', 'data/obj/images_79.jpg', 'data/obj/images_234.jpg', 'data/obj/images_67.jpg', 'data/obj/images_86.jpg', 'data/obj/images_77.jpg', 'data/obj/images_61.jpg', 'data/obj/d2.jpg', 'data/obj/images_80.jpg', 'data/obj/images_219.jpg', 'data/obj/images_171.jpg', 'data/obj/images_149.jpg', 'data/obj/images_98.jpg', 'data/obj/images_217.jpg', 'data/obj/NoPlate.jpg', 'data/obj/images_151.jpg', 'data/obj/images_58.jpg', 'data/obj/images_180.jpg', 'data/obj/images_120.jpg', 'data/obj/images_9.jpg', 'data/obj/images_236.jpg', 'data/obj/images_37.jpg', 'data/obj/images_222.jpg', 'data/obj/images_199.jpg', 'data/obj/images_178.jpg', 'data/obj/images_64.jpg', 'data/obj/images_190.jpg', 'data/obj/images_119.jpg', 'data/obj/images_137.jpg', 'data/obj/images_30.jpg', 'data/obj/Samples-of-Characters-for-Recognition-Sample-Indian-Vehicle-.jpg', 'data/obj/images_60.jpg', 'data/obj/images_102.jpg', 'data/obj/images_224.jpg', 'data/obj/images_130.jpg', 'data/obj/vehicles-will-soon-come-fitted-with-number-plates8-152447991.jpg', 'data/obj/20.jpg', 'data/obj/images_4.jpg', 'data/obj/vehicles-will-soon-come-fitted-with-number-plates6-155437216.jpg', 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'data/obj/images_48.jpg', 'data/obj/images_15.jpg', 'data/obj/images_184.jpg', 'data/obj/images_51.jpg', 'data/obj/images_174.jpg', 'data/obj/images_34.jpg', 'data/obj/images_111.jpg', 'data/obj/images_84.jpg', 'data/obj/images_57.jpg', 'data/obj/images_18.jpg', 'data/obj/images_228.jpg', 'data/obj/images_166.jpg', 'data/obj/images_121.jpg', 'data/obj/images_10.jpg', 'data/obj/images_45.jpg', 'data/obj/images_185.jpg', 'data/obj/7dab210d4d37b58c34e17347d57d4d36.jpg', 'data/obj/images_168.jpg', 'data/obj/images_233.jpg', 'data/obj/images_125.jpg', 'data/obj/images_103.jpg', 'data/obj/Car-Image-with-Indian-Number-Plate.png']\n",
            "261\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "EzygoAtMSnon",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "#Create training.txt file\n",
        "file = open(\"data/train.txt\", \"w\") \n",
        "file.write(\"\\n\".join(images_list)) \n",
        "file.close() "
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "CeSiuLrXoAjc",
        "colab_type": "text"
      },
      "source": [
        "**6) Start the training**"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "S3_g3jclUzMm",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "# Start the training\n",
        "!./darknet detector train data/obj.data cfg/yolov3_training.cfg darknet53.conv.74 -dont_show"
      ],
      "execution_count": 0,
      "outputs": []
    }
  ]
}