create-new-weight.ipynb

{
  "nbformat": 4,
  "nbformat_minor": 0,
  "metadata": {
    "accelerator": "GPU",
    "colab": {
      "name": "새로운weight만들기.ipynb의 사본",
      "provenance": [],
      "collapsed_sections": [],
      "include_colab_link": true
    },
    "kernelspec": {
      "display_name": "Python 3",
      "name": "python3"
    },
    "language_info": {
      "name": "python"
    }
  },
  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "view-in-github",
        "colab_type": "text"
      },
      "source": [
        "<a href=\"https://colab.research.google.com/github/jung-youjin/dip-pillow/blob/main/create-new-weight.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "nbJY-_LA_2l0",
        "outputId": "3565cd12-835a-4b75-f5a0-013533a9eb10"
      },
      "source": [
        "# clone darknet repo\n",
        "!git clone /~https://github.com/AlexeyAB/darknet"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "fatal: destination path 'darknet' already exists and is not an empty directory.\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "Vnv26DoZ_9sN",
        "outputId": "9685a4b5-cdda-4bb6-c2b6-e4b3d83ce6be"
      },
      "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",
        "!sed -i 's/CUDNN_HALF=0/CUDNN_HALF=1/' Makefile"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "/content/darknet\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "UYH20IFz_94m",
        "outputId": "c15f11d0-7f72-4649-c596-3328b6cde150"
      },
      "source": [
        "# verify CUDA\n",
        "!/usr/local/cuda/bin/nvcc --version"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "nvcc: NVIDIA (R) Cuda compiler driver\n",
            "Copyright (c) 2005-2020 NVIDIA Corporation\n",
            "Built on Wed_Jul_22_19:09:09_PDT_2020\n",
            "Cuda compilation tools, release 11.0, V11.0.221\n",
            "Build cuda_11.0_bu.TC445_37.28845127_0\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "7E8ggHxZ_977",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "c6eb483b-0992-4229-a1a6-599962b661fa"
      },
      "source": [
        "# make darknet (builds darknet so that you can then use the darknet executable file to run or train object detectors)\n",
        "!make"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "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 -DCUDNN_HALF -Wall -Wfatal-errors -Wno-unused-result -Wno-unknown-pragmas -fPIC -Ofast -DOPENCV -DGPU -DCUDNN -I/usr/local/cudnn/include -DCUDNN_HALF -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:935:23:\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 draw_train_loss(char*, void**, int, float, float, int, int, float, int, char*, float, int, int, double)\u001b[m\u001b[K’:\n",
            "\u001b[01m\u001b[K./src/image_opencv.cpp:1136:13:\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 (iteration_old == 0)\n",
            "             \u001b[01;35m\u001b[K^~\u001b[m\u001b[K\n",
            "\u001b[01m\u001b[K./src/image_opencv.cpp:1139:10:\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",
            "          \u001b[01;36m\u001b[Kif\u001b[m\u001b[K (iteration_old != 0){\n",
            "          \u001b[01;36m\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:1433:14:\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:1409:9:\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:1413:9:\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:1417:9:\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:1420:9:\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 -DCUDNN_HALF -Wall -Wfatal-errors -Wno-unused-result -Wno-unknown-pragmas -fPIC -Ofast -DOPENCV -DGPU -DCUDNN -I/usr/local/cudnn/include -DCUDNN_HALF -c ./src/http_stream.cpp -o obj/http_stream.o\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:253:21:\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:511:113:\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",
            "\u001b[01m\u001b[K./src/http_stream.cpp:\u001b[m\u001b[K In function ‘\u001b[01m\u001b[Kvoid set_track_id(detection*, int, float, float, float, int, int, int)\u001b[m\u001b[K’:\n",
            "\u001b[01m\u001b[K./src/http_stream.cpp:867:27:\u001b[m\u001b[K \u001b[01;35m\u001b[Kwarning: \u001b[m\u001b[Kcomparison between signed and unsigned integer expressions [\u001b[01;35m\u001b[K-Wsign-compare\u001b[m\u001b[K]\n",
            "         for (int i = 0; \u001b[01;35m\u001b[Ki < v.size()\u001b[m\u001b[K; ++i) {\n",
            "                         \u001b[01;35m\u001b[K~~^~~~~~~~~~\u001b[m\u001b[K\n",
            "\u001b[01m\u001b[K./src/http_stream.cpp:875:33:\u001b[m\u001b[K \u001b[01;35m\u001b[Kwarning: \u001b[m\u001b[Kcomparison between signed and unsigned integer expressions [\u001b[01;35m\u001b[K-Wsign-compare\u001b[m\u001b[K]\n",
            "     for (int old_id = 0; \u001b[01;35m\u001b[Kold_id < old_dets.size()\u001b[m\u001b[K; ++old_id) {\n",
            "                          \u001b[01;35m\u001b[K~~~~~~~^~~~~~~~~~~~~~~~~\u001b[m\u001b[K\n",
            "\u001b[01m\u001b[K./src/http_stream.cpp:894:31:\u001b[m\u001b[K \u001b[01;35m\u001b[Kwarning: \u001b[m\u001b[Kcomparison between signed and unsigned integer expressions [\u001b[01;35m\u001b[K-Wsign-compare\u001b[m\u001b[K]\n",
            "     for (int index = 0; \u001b[01;35m\u001b[Kindex < new_dets_num*old_dets.size()\u001b[m\u001b[K; ++index) {\n",
            "                         \u001b[01;35m\u001b[K~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~\u001b[m\u001b[K\n",
            "\u001b[01m\u001b[K./src/http_stream.cpp:930:28:\u001b[m\u001b[K \u001b[01;35m\u001b[Kwarning: \u001b[m\u001b[Kcomparison between signed and unsigned integer expressions [\u001b[01;35m\u001b[K-Wsign-compare\u001b[m\u001b[K]\n",
            "     if (\u001b[01;35m\u001b[Kold_dets_dq.size() > deque_size\u001b[m\u001b[K) old_dets_dq.pop_front();\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 -DCUDNN_HALF -Wall -Wfatal-errors -Wno-unused-result -Wno-unknown-pragmas -fPIC -Ofast -DOPENCV -DGPU -DCUDNN -I/usr/local/cudnn/include -DCUDNN_HALF -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:2044:15:\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:2043:15:\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 -DCUDNN_HALF -Wall -Wfatal-errors -Wno-unused-result -Wno-unknown-pragmas -fPIC -Ofast -DOPENCV -DGPU -DCUDNN -I/usr/local/cudnn/include -DCUDNN_HALF -c ./src/utils.c -o obj/utils.o\n",
            "\u001b[01m\u001b[K./src/utils.c:\u001b[m\u001b[K In function ‘\u001b[01m\u001b[Kcustom_hash\u001b[m\u001b[K’:\n",
            "\u001b[01m\u001b[K./src/utils.c:1045:12:\u001b[m\u001b[K \u001b[01;35m\u001b[Kwarning: \u001b[m\u001b[Ksuggest parentheses around assignment used as truth value [\u001b[01;35m\u001b[K-Wparentheses\u001b[m\u001b[K]\n",
            "     while (\u001b[01;35m\u001b[Kc\u001b[m\u001b[K = *str++)\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 -DCUDNN_HALF -Wall -Wfatal-errors -Wno-unused-result -Wno-unknown-pragmas -fPIC -Ofast -DOPENCV -DGPU -DCUDNN -I/usr/local/cudnn/include -DCUDNN_HALF -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:231:20:\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[Kcublas_check_error_extended\u001b[m\u001b[K’:\n",
            "\u001b[01m\u001b[K./src/dark_cuda.c:265:18:\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 cudaError_enum\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 CUDA_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:396:40:\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:396:64:\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:396:82:\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:406:37:\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:427:43:\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:442:64:\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:448:63:\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",
            "At top level:\n",
            "\u001b[01m\u001b[K./src/dark_cuda.c:288:23:\u001b[m\u001b[K \u001b[01;35m\u001b[Kwarning: \u001b[m\u001b[K‘\u001b[01m\u001b[KswitchBlasHandle\u001b[m\u001b[K’ defined but not used [\u001b[01;35m\u001b[K-Wunused-variable\u001b[m\u001b[K]\n",
            " static cublasHandle_t \u001b[01;35m\u001b[KswitchBlasHandle\u001b[m\u001b[K[16];\n",
            "                       \u001b[01;35m\u001b[K^~~~~~~~~~~~~~~~\u001b[m\u001b[K\n",
            "\u001b[01m\u001b[K./src/dark_cuda.c:287:12:\u001b[m\u001b[K \u001b[01;35m\u001b[Kwarning: \u001b[m\u001b[K‘\u001b[01m\u001b[KswitchBlasInit\u001b[m\u001b[K’ defined but not used [\u001b[01;35m\u001b[K-Wunused-variable\u001b[m\u001b[K]\n",
            " static int \u001b[01;35m\u001b[KswitchBlasInit\u001b[m\u001b[K[16] = { 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 -DCUDNN_HALF -Wall -Wfatal-errors -Wno-unused-result -Wno-unknown-pragmas -fPIC -Ofast -DOPENCV -DGPU -DCUDNN -I/usr/local/cudnn/include -DCUDNN_HALF -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:1341:32:\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 -DCUDNN_HALF -Wall -Wfatal-errors -Wno-unused-result -Wno-unknown-pragmas -fPIC -Ofast -DOPENCV -DGPU -DCUDNN -I/usr/local/cudnn/include -DCUDNN_HALF -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 -DCUDNN_HALF -Wall -Wfatal-errors -Wno-unused-result -Wno-unknown-pragmas -fPIC -Ofast -DOPENCV -DGPU -DCUDNN -I/usr/local/cudnn/include -DCUDNN_HALF -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 -DCUDNN_HALF -Wall -Wfatal-errors -Wno-unused-result -Wno-unknown-pragmas -fPIC -Ofast -DOPENCV -DGPU -DCUDNN -I/usr/local/cudnn/include -DCUDNN_HALF -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:79:5:\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:79:5:\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:79:5:\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:79:5:\u001b[m\u001b[K \u001b[01;35m\u001b[Kwarning: \u001b[m\u001b[Kenumeration value ‘\u001b[01m\u001b[KHARD_MISH\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:79:5:\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:79:5:\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:79:5:\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:310:5:\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:310:5:\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:310:5:\u001b[m\u001b[K \u001b[01;35m\u001b[Kwarning: \u001b[m\u001b[Kenumeration value ‘\u001b[01m\u001b[KHARD_MISH\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 -DCUDNN_HALF -Wall -Wfatal-errors -Wno-unused-result -Wno-unknown-pragmas -fPIC -Ofast -DOPENCV -DGPU -DCUDNN -I/usr/local/cudnn/include -DCUDNN_HALF -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 -DCUDNN_HALF -Wall -Wfatal-errors -Wno-unused-result -Wno-unknown-pragmas -fPIC -Ofast -DOPENCV -DGPU -DCUDNN -I/usr/local/cudnn/include -DCUDNN_HALF -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 -DCUDNN_HALF -Wall -Wfatal-errors -Wno-unused-result -Wno-unknown-pragmas -fPIC -Ofast -DOPENCV -DGPU -DCUDNN -I/usr/local/cudnn/include -DCUDNN_HALF -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",
            "\u001b[01m\u001b[K./src/blas.c:\u001b[m\u001b[K In function ‘\u001b[01m\u001b[Kfind_sim\u001b[m\u001b[K’:\n",
            "\u001b[01m\u001b[K./src/blas.c:597:59:\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(\" Error: find_sim(): sim isn't found: i = \u001b[01;35m\u001b[K%d\u001b[m\u001b[K, j = %d, z = %d \\n\", i, j, z);\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/blas.c:597:67:\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 3 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(\" Error: find_sim(): sim isn't found: i = %d, j = \u001b[01;35m\u001b[K%d\u001b[m\u001b[K, z = %d \\n\", i, j, z);\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/blas.c:597:75:\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 4 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(\" Error: find_sim(): sim isn't found: i = %d, j = %d, z = \u001b[01;35m\u001b[K%d\u001b[m\u001b[K \\n\", i, j, z);\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/blas.c:\u001b[m\u001b[K In function ‘\u001b[01m\u001b[Kfind_P_constrastive\u001b[m\u001b[K’:\n",
            "\u001b[01m\u001b[K./src/blas.c:611:68:\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(\" Error: find_P_constrastive(): P isn't found: i = \u001b[01;35m\u001b[K%d\u001b[m\u001b[K, j = %d, z = %d \\n\", i, j, z);\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/blas.c:611:76:\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 3 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(\" Error: find_P_constrastive(): P isn't found: i = %d, j = \u001b[01;35m\u001b[K%d\u001b[m\u001b[K, z = %d \\n\", i, j, z);\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/blas.c:611:84:\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 4 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(\" Error: find_P_constrastive(): P isn't found: i = %d, j = %d, z = \u001b[01;35m\u001b[K%d\u001b[m\u001b[K \\n\", i, j, z);\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/blas.c:\u001b[m\u001b[K In function ‘\u001b[01m\u001b[KP_constrastive_f\u001b[m\u001b[K’:\n",
            "\u001b[01m\u001b[K./src/blas.c:651:79:\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 3 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",
            "         fprintf(stderr, \" Error: in P_constrastive must be i != l, while i = \u001b[01;35m\u001b[K%d\u001b[m\u001b[K, l = %d \\n\", i, l);\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/blas.c:651:87:\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 4 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",
            "         fprintf(stderr, \" Error: in P_constrastive must be i != l, while i = %d, l = \u001b[01;35m\u001b[K%d\u001b[m\u001b[K \\n\", i, l);\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/blas.c:\u001b[m\u001b[K In function ‘\u001b[01m\u001b[KP_constrastive\u001b[m\u001b[K’:\n",
            "\u001b[01m\u001b[K./src/blas.c:785:79:\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 3 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",
            "         fprintf(stderr, \" Error: in P_constrastive must be i != l, while i = \u001b[01;35m\u001b[K%d\u001b[m\u001b[K, l = %d \\n\", i, l);\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/blas.c:785:87:\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 4 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",
            "         fprintf(stderr, \" Error: in P_constrastive must be i != l, while i = %d, l = \u001b[01;35m\u001b[K%d\u001b[m\u001b[K \\n\", i, l);\n",
            "                                                                                      \u001b[01;35m\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 -DCUDNN_HALF -Wall -Wfatal-errors -Wno-unused-result -Wno-unknown-pragmas -fPIC -Ofast -DOPENCV -DGPU -DCUDNN -I/usr/local/cudnn/include -DCUDNN_HALF -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 -DCUDNN_HALF -Wall -Wfatal-errors -Wno-unused-result -Wno-unknown-pragmas -fPIC -Ofast -DOPENCV -DGPU -DCUDNN -I/usr/local/cudnn/include -DCUDNN_HALF -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 -DCUDNN_HALF -Wall -Wfatal-errors -Wno-unused-result -Wno-unknown-pragmas -fPIC -Ofast -DOPENCV -DGPU -DCUDNN -I/usr/local/cudnn/include -DCUDNN_HALF -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 -DCUDNN_HALF -Wall -Wfatal-errors -Wno-unused-result -Wno-unknown-pragmas -fPIC -Ofast -DOPENCV -DGPU -DCUDNN -I/usr/local/cudnn/include -DCUDNN_HALF -c ./src/softmax_layer.c -o obj/softmax_layer.o\n",
            "\u001b[01m\u001b[K./src/softmax_layer.c:\u001b[m\u001b[K In function ‘\u001b[01m\u001b[Kmake_contrastive_layer\u001b[m\u001b[K’:\n",
            "\u001b[01m\u001b[K./src/softmax_layer.c:203:101:\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 9 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",
            "     fprintf(stderr, \"contrastive %4d x%4d x%4d x emb_size %4d x batch: %4d  classes = %4d, step = \u001b[01;35m\u001b[K%4d\u001b[m\u001b[K \\n\", w, h, l.n, l.embedding_size, batch, l.classes, step);\n",
            "                                                                                                   \u001b[01;35m\u001b[K~~^\u001b[m\u001b[K\n",
            "                                                                                                   \u001b[32m\u001b[K%4ld\u001b[m\u001b[K\n",
            "\u001b[01m\u001b[K./src/softmax_layer.c:\u001b[m\u001b[K In function ‘\u001b[01m\u001b[Kforward_contrastive_layer\u001b[m\u001b[K’:\n",
            "\u001b[01m\u001b[K./src/softmax_layer.c:244:27:\u001b[m\u001b[K \u001b[01;35m\u001b[Kwarning: \u001b[m\u001b[Kvariable ‘\u001b[01m\u001b[Kmax_truth\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[Kmax_truth\u001b[m\u001b[K = 0;\n",
            "                           \u001b[01;35m\u001b[K^~~~~~~~~\u001b[m\u001b[K\n",
            "\u001b[01m\u001b[K./src/softmax_layer.c:423:71:\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(\" Error: too large number of bboxes: contr_size = \u001b[01;35m\u001b[K%d\u001b[m\u001b[K > max_contr_size  = %d \\n\", contr_size, max_contr_size);\n",
            "                                                                      \u001b[01;35m\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 -DCUDNN_HALF -Wall -Wfatal-errors -Wno-unused-result -Wno-unknown-pragmas -fPIC -Ofast -DOPENCV -DGPU -DCUDNN -I/usr/local/cudnn/include -DCUDNN_HALF -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:1297:24:\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:1090:43:\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 -DCUDNN_HALF -Wall -Wfatal-errors -Wno-unused-result -Wno-unknown-pragmas -fPIC -Ofast -DOPENCV -DGPU -DCUDNN -I/usr/local/cudnn/include -DCUDNN_HALF -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 -DCUDNN_HALF -Wall -Wfatal-errors -Wno-unused-result -Wno-unknown-pragmas -fPIC -Ofast -DOPENCV -DGPU -DCUDNN -I/usr/local/cudnn/include -DCUDNN_HALF -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[Ktrain_network_waitkey\u001b[m\u001b[K’:\n",
            "\u001b[01m\u001b[K./src/network.c:434:13:\u001b[m\u001b[K \u001b[01;35m\u001b[Kwarning: \u001b[m\u001b[Kunused variable ‘\u001b[01m\u001b[Kema_period\u001b[m\u001b[K’ [\u001b[01;35m\u001b[K-Wunused-variable\u001b[m\u001b[K]\n",
            "         int \u001b[01;35m\u001b[Kema_period\u001b[m\u001b[K = (net.max_batches - ema_start_point - 1000) * (1.0 - net.ema_alpha);\n",
            "             \u001b[01;35m\u001b[K^~~~~~~~~~\u001b[m\u001b[K\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:659:42:\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:4707:39:\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 -DCUDNN_HALF -Wall -Wfatal-errors -Wno-unused-result -Wno-unknown-pragmas -fPIC -Ofast -DOPENCV -DGPU -DCUDNN -I/usr/local/cudnn/include -DCUDNN_HALF -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 -DCUDNN_HALF -Wall -Wfatal-errors -Wno-unused-result -Wno-unknown-pragmas -fPIC -Ofast -DOPENCV -DGPU -DCUDNN -I/usr/local/cudnn/include -DCUDNN_HALF -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 -DCUDNN_HALF -Wall -Wfatal-errors -Wno-unused-result -Wno-unknown-pragmas -fPIC -Ofast -DOPENCV -DGPU -DCUDNN -I/usr/local/cudnn/include -DCUDNN_HALF -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:1719:42:\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:4707:39:\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/parser.c:\u001b[m\u001b[K In function ‘\u001b[01m\u001b[Ksave_implicit_weights\u001b[m\u001b[K’:\n",
            "\u001b[01m\u001b[K./src/parser.c:1851:9:\u001b[m\u001b[K \u001b[01;35m\u001b[Kwarning: \u001b[m\u001b[Kunused variable ‘\u001b[01m\u001b[Ki\u001b[m\u001b[K’ [\u001b[01;35m\u001b[K-Wunused-variable\u001b[m\u001b[K]\n",
            "     int \u001b[01;35m\u001b[Ki\u001b[m\u001b[K;\n",
            "         \u001b[01;35m\u001b[K^\u001b[m\u001b[K\n",
            "\u001b[01m\u001b[K./src/parser.c:\u001b[m\u001b[K In function ‘\u001b[01m\u001b[Kget_classes_multipliers\u001b[m\u001b[K’:\n",
            "\u001b[01m\u001b[K./src/parser.c:438:29:\u001b[m\u001b[K \u001b[01;35m\u001b[Kwarning: \u001b[m\u001b[Kargument 1 range [18446744071562067968, 18446744073709551615] exceeds maximum object size 9223372036854775807 [\u001b[01;35m\u001b[K-Walloc-size-larger-than=\u001b[m\u001b[K]\n",
            "         \u001b[01;35m\u001b[Kclasses_multipliers = (float *)calloc(classes_counters, sizeof(float))\u001b[m\u001b[K;\n",
            "         \u001b[01;35m\u001b[K~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~\u001b[m\u001b[K\n",
            "In file included from \u001b[01m\u001b[K./src/parser.c:3:0\u001b[m\u001b[K:\n",
            "\u001b[01m\u001b[K/usr/include/stdlib.h:541:14:\u001b[m\u001b[K \u001b[01;36m\u001b[Knote: \u001b[m\u001b[Kin a call to allocation function ‘\u001b[01m\u001b[Kcalloc\u001b[m\u001b[K’ declared here\n",
            " extern void *\u001b[01;36m\u001b[Kcalloc\u001b[m\u001b[K (size_t __nmemb, size_t __size)\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 -DCUDNN_HALF -Wall -Wfatal-errors -Wno-unused-result -Wno-unknown-pragmas -fPIC -Ofast -DOPENCV -DGPU -DCUDNN -I/usr/local/cudnn/include -DCUDNN_HALF -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 -DCUDNN_HALF -Wall -Wfatal-errors -Wno-unused-result -Wno-unknown-pragmas -fPIC -Ofast -DOPENCV -DGPU -DCUDNN -I/usr/local/cudnn/include -DCUDNN_HALF -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 -DCUDNN_HALF -Wall -Wfatal-errors -Wno-unused-result -Wno-unknown-pragmas -fPIC -Ofast -DOPENCV -DGPU -DCUDNN -I/usr/local/cudnn/include -DCUDNN_HALF -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 -DCUDNN_HALF -Wall -Wfatal-errors -Wno-unused-result -Wno-unknown-pragmas -fPIC -Ofast -DOPENCV -DGPU -DCUDNN -I/usr/local/cudnn/include -DCUDNN_HALF -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 -DCUDNN_HALF -Wall -Wfatal-errors -Wno-unused-result -Wno-unknown-pragmas -fPIC -Ofast -DOPENCV -DGPU -DCUDNN -I/usr/local/cudnn/include -DCUDNN_HALF -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 -DCUDNN_HALF -Wall -Wfatal-errors -Wno-unused-result -Wno-unknown-pragmas -fPIC -Ofast -DOPENCV -DGPU -DCUDNN -I/usr/local/cudnn/include -DCUDNN_HALF -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 -DCUDNN_HALF -Wall -Wfatal-errors -Wno-unused-result -Wno-unknown-pragmas -fPIC -Ofast -DOPENCV -DGPU -DCUDNN -I/usr/local/cudnn/include -DCUDNN_HALF -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 -DCUDNN_HALF -Wall -Wfatal-errors -Wno-unused-result -Wno-unknown-pragmas -fPIC -Ofast -DOPENCV -DGPU -DCUDNN -I/usr/local/cudnn/include -DCUDNN_HALF -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 -DCUDNN_HALF -Wall -Wfatal-errors -Wno-unused-result -Wno-unknown-pragmas -fPIC -Ofast -DOPENCV -DGPU -DCUDNN -I/usr/local/cudnn/include -DCUDNN_HALF -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 -DCUDNN_HALF -Wall -Wfatal-errors -Wno-unused-result -Wno-unknown-pragmas -fPIC -Ofast -DOPENCV -DGPU -DCUDNN -I/usr/local/cudnn/include -DCUDNN_HALF -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 -DCUDNN_HALF -Wall -Wfatal-errors -Wno-unused-result -Wno-unknown-pragmas -fPIC -Ofast -DOPENCV -DGPU -DCUDNN -I/usr/local/cudnn/include -DCUDNN_HALF -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 -DCUDNN_HALF -Wall -Wfatal-errors -Wno-unused-result -Wno-unknown-pragmas -fPIC -Ofast -DOPENCV -DGPU -DCUDNN -I/usr/local/cudnn/include -DCUDNN_HALF -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 -DCUDNN_HALF -Wall -Wfatal-errors -Wno-unused-result -Wno-unknown-pragmas -fPIC -Ofast -DOPENCV -DGPU -DCUDNN -I/usr/local/cudnn/include -DCUDNN_HALF -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 -DCUDNN_HALF -Wall -Wfatal-errors -Wno-unused-result -Wno-unknown-pragmas -fPIC -Ofast -DOPENCV -DGPU -DCUDNN -I/usr/local/cudnn/include -DCUDNN_HALF -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[Ktrain_detector\u001b[m\u001b[K’:\n",
            "\u001b[01m\u001b[K./src/detector.c:386:72:\u001b[m\u001b[K \u001b[01;35m\u001b[Kwarning: \u001b[m\u001b[Ksuggest parentheses around ‘\u001b[01m\u001b[K&&\u001b[m\u001b[K’ within ‘\u001b[01m\u001b[K||\u001b[m\u001b[K’ [\u001b[01;35m\u001b[K-Wparentheses\u001b[m\u001b[K]\n",
            "             \u001b[01;35m\u001b[K(iteration >= (iter_save + 1000) || iteration % 1000 == 0) && net.max_batches < 10000\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[Kprint_cocos\u001b[m\u001b[K’:\n",
            "\u001b[01m\u001b[K./src/detector.c:486:29:\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:579:21:\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:700:13:\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:698:13:\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:1332:15:\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:1331:15:\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:1867:19:\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 -DCUDNN_HALF -Wall -Wfatal-errors -Wno-unused-result -Wno-unknown-pragmas -fPIC -Ofast -DOPENCV -DGPU -DCUDNN -I/usr/local/cudnn/include -DCUDNN_HALF -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:208:68:\u001b[m\u001b[K \u001b[01;35m\u001b[Kwarning: \u001b[m\u001b[Ksuggest parentheses around ‘\u001b[01m\u001b[K&&\u001b[m\u001b[K’ within ‘\u001b[01m\u001b[K||\u001b[m\u001b[K’ [\u001b[01;35m\u001b[K-Wparentheses\u001b[m\u001b[K]\n",
            "     if (l.delta_gpu && (l.optimized_memory < 1 || \u001b[01;35m\u001b[Kl.keep_delta_gpu && l.optimized_memory < 3\u001b[m\u001b[K)) cuda_free(l.delta_gpu), l.delta_gpu = NULL;\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 -DCUDNN_HALF -Wall -Wfatal-errors -Wno-unused-result -Wno-unknown-pragmas -fPIC -Ofast -DOPENCV -DGPU -DCUDNN -I/usr/local/cudnn/include -DCUDNN_HALF -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 -DCUDNN_HALF -Wall -Wfatal-errors -Wno-unused-result -Wno-unknown-pragmas -fPIC -Ofast -DOPENCV -DGPU -DCUDNN -I/usr/local/cudnn/include -DCUDNN_HALF -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:146:9:\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:855:13:\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:1287:49:\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:1287:37:\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 -DCUDNN_HALF -Wall -Wfatal-errors -Wno-unused-result -Wno-unknown-pragmas -fPIC -Ofast -DOPENCV -DGPU -DCUDNN -I/usr/local/cudnn/include -DCUDNN_HALF -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 -DCUDNN_HALF -Wall -Wfatal-errors -Wno-unused-result -Wno-unknown-pragmas -fPIC -Ofast -DOPENCV -DGPU -DCUDNN -I/usr/local/cudnn/include -DCUDNN_HALF -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 -DCUDNN_HALF -Wall -Wfatal-errors -Wno-unused-result -Wno-unknown-pragmas -fPIC -Ofast -DOPENCV -DGPU -DCUDNN -I/usr/local/cudnn/include -DCUDNN_HALF -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 -DCUDNN_HALF -Wall -Wfatal-errors -Wno-unused-result -Wno-unknown-pragmas -fPIC -Ofast -DOPENCV -DGPU -DCUDNN -I/usr/local/cudnn/include -DCUDNN_HALF -c ./src/representation_layer.c -o obj/representation_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 -DCUDNN_HALF -Wall -Wfatal-errors -Wno-unused-result -Wno-unknown-pragmas -fPIC -Ofast -DOPENCV -DGPU -DCUDNN -I/usr/local/cudnn/include -DCUDNN_HALF -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 -DCUDNN_HALF -Wall -Wfatal-errors -Wno-unused-result -Wno-unknown-pragmas -fPIC -Ofast -DOPENCV -DGPU -DCUDNN -I/usr/local/cudnn/include -DCUDNN_HALF -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 -DCUDNN_HALF -Wall -Wfatal-errors -Wno-unused-result -Wno-unknown-pragmas -fPIC -Ofast -DOPENCV -DGPU -DCUDNN -I/usr/local/cudnn/include -DCUDNN_HALF -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 -DCUDNN_HALF -Wall -Wfatal-errors -Wno-unused-result -Wno-unknown-pragmas -fPIC -Ofast -DOPENCV -DGPU -DCUDNN -I/usr/local/cudnn/include -DCUDNN_HALF -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 -DCUDNN_HALF -Wall -Wfatal-errors -Wno-unused-result -Wno-unknown-pragmas -fPIC -Ofast -DOPENCV -DGPU -DCUDNN -I/usr/local/cudnn/include -DCUDNN_HALF -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 -DCUDNN_HALF -Wall -Wfatal-errors -Wno-unused-result -Wno-unknown-pragmas -fPIC -Ofast -DOPENCV -DGPU -DCUDNN -I/usr/local/cudnn/include -DCUDNN_HALF -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 -DCUDNN_HALF -Wall -Wfatal-errors -Wno-unused-result -Wno-unknown-pragmas -fPIC -Ofast -DOPENCV -DGPU -DCUDNN -I/usr/local/cudnn/include -DCUDNN_HALF -c ./src/demo.c -o obj/demo.o\n",
            "\u001b[01m\u001b[K./src/demo.c:\u001b[m\u001b[K In function ‘\u001b[01m\u001b[Kdetect_in_thread\u001b[m\u001b[K’:\n",
            "\u001b[01m\u001b[K./src/demo.c:101:15:\u001b[m\u001b[K \u001b[01;35m\u001b[Kwarning: \u001b[m\u001b[Kunused variable ‘\u001b[01m\u001b[Kl\u001b[m\u001b[K’ [\u001b[01;35m\u001b[K-Wunused-variable\u001b[m\u001b[K]\n",
            "         layer \u001b[01;35m\u001b[Kl\u001b[m\u001b[K = net.layers[net.n - 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 -DCUDNN_HALF -Wall -Wfatal-errors -Wno-unused-result -Wno-unknown-pragmas -fPIC -Ofast -DOPENCV -DGPU -DCUDNN -I/usr/local/cudnn/include -DCUDNN_HALF -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 -DCUDNN_HALF -Wall -Wfatal-errors -Wno-unused-result -Wno-unknown-pragmas -fPIC -Ofast -DOPENCV -DGPU -DCUDNN -I/usr/local/cudnn/include -DCUDNN_HALF -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 -DCUDNN_HALF -Wall -Wfatal-errors -Wno-unused-result -Wno-unknown-pragmas -fPIC -Ofast -DOPENCV -DGPU -DCUDNN -I/usr/local/cudnn/include -DCUDNN_HALF -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 -DCUDNN_HALF -Wall -Wfatal-errors -Wno-unused-result -Wno-unknown-pragmas -fPIC -Ofast -DOPENCV -DGPU -DCUDNN -I/usr/local/cudnn/include -DCUDNN_HALF -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 -DCUDNN_HALF -Wall -Wfatal-errors -Wno-unused-result -Wno-unknown-pragmas -fPIC -Ofast -DOPENCV -DGPU -DCUDNN -I/usr/local/cudnn/include -DCUDNN_HALF -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 -DCUDNN_HALF -Wall -Wfatal-errors -Wno-unused-result -Wno-unknown-pragmas -fPIC -Ofast -DOPENCV -DGPU -DCUDNN -I/usr/local/cudnn/include -DCUDNN_HALF -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:63:9:\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:62:9:\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 -DCUDNN_HALF -Wall -Wfatal-errors -Wno-unused-result -Wno-unknown-pragmas -fPIC -Ofast -DOPENCV -DGPU -DCUDNN -I/usr/local/cudnn/include -DCUDNN_HALF -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 -DCUDNN_HALF -Wall -Wfatal-errors -Wno-unused-result -Wno-unknown-pragmas -fPIC -Ofast -DOPENCV -DGPU -DCUDNN -I/usr/local/cudnn/include -DCUDNN_HALF -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 -DCUDNN_HALF -Wall -Wfatal-errors -Wno-unused-result -Wno-unknown-pragmas -fPIC -Ofast -DOPENCV -DGPU -DCUDNN -I/usr/local/cudnn/include -DCUDNN_HALF -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 -DCUDNN_HALF -Wall -Wfatal-errors -Wno-unused-result -Wno-unknown-pragmas -fPIC -Ofast -DOPENCV -DGPU -DCUDNN -I/usr/local/cudnn/include -DCUDNN_HALF -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 -DCUDNN_HALF -Wall -Wfatal-errors -Wno-unused-result -Wno-unknown-pragmas -fPIC -Ofast -DOPENCV -DGPU -DCUDNN -I/usr/local/cudnn/include -DCUDNN_HALF -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 -DCUDNN_HALF -Wall -Wfatal-errors -Wno-unused-result -Wno-unknown-pragmas -fPIC -Ofast -DOPENCV -DGPU -DCUDNN -I/usr/local/cudnn/include -DCUDNN_HALF -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: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.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:4707:39:\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:75:38:\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:4707:39:\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:106:42:\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:4707:39:\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:115:42:\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:4707:39:\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[Kprocess_batch\u001b[m\u001b[K’:\n",
            "\u001b[01m\u001b[K./src/yolo_layer.c:426:25:\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",
            "\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:707:11:\u001b[m\u001b[K \u001b[01;35m\u001b[Kwarning: \u001b[m\u001b[Kunused variable ‘\u001b[01m\u001b[Kavg_anyobj\u001b[m\u001b[K’ [\u001b[01;35m\u001b[K-Wunused-variable\u001b[m\u001b[K]\n",
            "     float \u001b[01;35m\u001b[Kavg_anyobj\u001b[m\u001b[K = 0;\n",
            "           \u001b[01;35m\u001b[K^~~~~~~~~~\u001b[m\u001b[K\n",
            "\u001b[01m\u001b[K./src/yolo_layer.c:706:11:\u001b[m\u001b[K \u001b[01;35m\u001b[Kwarning: \u001b[m\u001b[Kunused variable ‘\u001b[01m\u001b[Kavg_obj\u001b[m\u001b[K’ [\u001b[01;35m\u001b[K-Wunused-variable\u001b[m\u001b[K]\n",
            "     float \u001b[01;35m\u001b[Kavg_obj\u001b[m\u001b[K = 0;\n",
            "           \u001b[01;35m\u001b[K^~~~~~~\u001b[m\u001b[K\n",
            "\u001b[01m\u001b[K./src/yolo_layer.c:705:11:\u001b[m\u001b[K \u001b[01;35m\u001b[Kwarning: \u001b[m\u001b[Kunused variable ‘\u001b[01m\u001b[Kavg_cat\u001b[m\u001b[K’ [\u001b[01;35m\u001b[K-Wunused-variable\u001b[m\u001b[K]\n",
            "     float \u001b[01;35m\u001b[Kavg_cat\u001b[m\u001b[K = 0;\n",
            "           \u001b[01;35m\u001b[K^~~~~~~\u001b[m\u001b[K\n",
            "\u001b[01m\u001b[K./src/yolo_layer.c:704:11:\u001b[m\u001b[K \u001b[01;35m\u001b[Kwarning: \u001b[m\u001b[Kunused variable ‘\u001b[01m\u001b[Krecall75\u001b[m\u001b[K’ [\u001b[01;35m\u001b[K-Wunused-variable\u001b[m\u001b[K]\n",
            "     float \u001b[01;35m\u001b[Krecall75\u001b[m\u001b[K = 0;\n",
            "           \u001b[01;35m\u001b[K^~~~~~~~\u001b[m\u001b[K\n",
            "\u001b[01m\u001b[K./src/yolo_layer.c:703:11:\u001b[m\u001b[K \u001b[01;35m\u001b[Kwarning: \u001b[m\u001b[Kunused variable ‘\u001b[01m\u001b[Krecall\u001b[m\u001b[K’ [\u001b[01;35m\u001b[K-Wunused-variable\u001b[m\u001b[K]\n",
            "     float \u001b[01;35m\u001b[Krecall\u001b[m\u001b[K = 0;\n",
            "           \u001b[01;35m\u001b[K^~~~~~\u001b[m\u001b[K\n",
            "\u001b[01m\u001b[K./src/yolo_layer.c:702:11:\u001b[m\u001b[K \u001b[01;35m\u001b[Kwarning: \u001b[m\u001b[Kunused variable ‘\u001b[01m\u001b[Ktot_ciou_loss\u001b[m\u001b[K’ [\u001b[01;35m\u001b[K-Wunused-variable\u001b[m\u001b[K]\n",
            "     float \u001b[01;35m\u001b[Ktot_ciou_loss\u001b[m\u001b[K = 0;\n",
            "           \u001b[01;35m\u001b[K^~~~~~~~~~~~~\u001b[m\u001b[K\n",
            "\u001b[01m\u001b[K./src/yolo_layer.c:701:11:\u001b[m\u001b[K \u001b[01;35m\u001b[Kwarning: \u001b[m\u001b[Kunused variable ‘\u001b[01m\u001b[Ktot_diou_loss\u001b[m\u001b[K’ [\u001b[01;35m\u001b[K-Wunused-variable\u001b[m\u001b[K]\n",
            "     float \u001b[01;35m\u001b[Ktot_diou_loss\u001b[m\u001b[K = 0;\n",
            "           \u001b[01;35m\u001b[K^~~~~~~~~~~~~\u001b[m\u001b[K\n",
            "\u001b[01m\u001b[K./src/yolo_layer.c:698:11:\u001b[m\u001b[K \u001b[01;35m\u001b[Kwarning: \u001b[m\u001b[Kunused variable ‘\u001b[01m\u001b[Ktot_ciou\u001b[m\u001b[K’ [\u001b[01;35m\u001b[K-Wunused-variable\u001b[m\u001b[K]\n",
            "     float \u001b[01;35m\u001b[Ktot_ciou\u001b[m\u001b[K = 0;\n",
            "           \u001b[01;35m\u001b[K^~~~~~~~\u001b[m\u001b[K\n",
            "\u001b[01m\u001b[K./src/yolo_layer.c:697:11:\u001b[m\u001b[K \u001b[01;35m\u001b[Kwarning: \u001b[m\u001b[Kunused variable ‘\u001b[01m\u001b[Ktot_diou\u001b[m\u001b[K’ [\u001b[01;35m\u001b[K-Wunused-variable\u001b[m\u001b[K]\n",
            "     float \u001b[01;35m\u001b[Ktot_diou\u001b[m\u001b[K = 0;\n",
            "           \u001b[01;35m\u001b[K^~~~~~~~\u001b[m\u001b[K\n",
            "\u001b[01m\u001b[K./src/yolo_layer.c:696:11:\u001b[m\u001b[K \u001b[01;35m\u001b[Kwarning: \u001b[m\u001b[Kunused variable ‘\u001b[01m\u001b[Ktot_giou\u001b[m\u001b[K’ [\u001b[01;35m\u001b[K-Wunused-variable\u001b[m\u001b[K]\n",
            "     float \u001b[01;35m\u001b[Ktot_giou\u001b[m\u001b[K = 0;\n",
            "           \u001b[01;35m\u001b[K^~~~~~~~\u001b[m\u001b[K\n",
            "\u001b[01m\u001b[K./src/yolo_layer.c:668:12:\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 b, \u001b[01;35m\u001b[Kn\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 -DCUDNN_HALF -Wall -Wfatal-errors -Wno-unused-result -Wno-unknown-pragmas -fPIC -Ofast -DOPENCV -DGPU -DCUDNN -I/usr/local/cudnn/include -DCUDNN_HALF -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:72:38:\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:4707:39:\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:79:38:\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:4707:39:\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:111:42:\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:4707:39:\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:120:42:\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:4707:39:\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 -DCUDNN_HALF -Wall -Wfatal-errors -Wno-unused-result -Wno-unknown-pragmas -fPIC -Ofast -DOPENCV -DGPU -DCUDNN -I/usr/local/cudnn/include -DCUDNN_HALF -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 -DCUDNN_HALF -Wall -Wfatal-errors -Wno-unused-result -Wno-unknown-pragmas -fPIC -Ofast -DOPENCV -DGPU -DCUDNN -I/usr/local/cudnn/include -DCUDNN_HALF -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 -DCUDNN_HALF -Wall -Wfatal-errors -Wno-unused-result -Wno-unknown-pragmas -fPIC -Ofast -DOPENCV -DGPU -DCUDNN -I/usr/local/cudnn/include -DCUDNN_HALF -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 -DCUDNN_HALF -Wall -Wfatal-errors -Wno-unused-result -Wno-unknown-pragmas -fPIC -Ofast -DOPENCV -DGPU -DCUDNN -I/usr/local/cudnn/include -DCUDNN_HALF -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 -DCUDNN_HALF -Wall -Wfatal-errors -Wno-unused-result -Wno-unknown-pragmas -fPIC -Ofast -DOPENCV -DGPU -DCUDNN -I/usr/local/cudnn/include -DCUDNN_HALF -c ./src/sam_layer.c -o obj/sam_layer.o\n",
            "nvcc -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] -gencode arch=compute_70,code=[sm_70,compute_70] -Iinclude/ -I3rdparty/stb/include -DOPENCV `pkg-config --cflags opencv4 2> /dev/null || pkg-config --cflags opencv` -DGPU -I/usr/local/cuda/include/ -DCUDNN -DCUDNN_HALF --compiler-options \"-Wall -Wfatal-errors -Wno-unused-result -Wno-unknown-pragmas -fPIC -Ofast -DOPENCV -DGPU -DCUDNN -I/usr/local/cudnn/include -DCUDNN_HALF\" -c ./src/convolutional_kernels.cu -o obj/convolutional_kernels.o\n",
            "nvcc warning : The 'compute_35', 'compute_37', 'compute_50', 'sm_35', 'sm_37' and 'sm_50' architectures are deprecated, and may be removed in a future release (Use -Wno-deprecated-gpu-targets to suppress warning).\n",
            "nvcc -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] -gencode arch=compute_70,code=[sm_70,compute_70] -Iinclude/ -I3rdparty/stb/include -DOPENCV `pkg-config --cflags opencv4 2> /dev/null || pkg-config --cflags opencv` -DGPU -I/usr/local/cuda/include/ -DCUDNN -DCUDNN_HALF --compiler-options \"-Wall -Wfatal-errors -Wno-unused-result -Wno-unknown-pragmas -fPIC -Ofast -DOPENCV -DGPU -DCUDNN -I/usr/local/cudnn/include -DCUDNN_HALF\" -c ./src/activation_kernels.cu -o obj/activation_kernels.o\n",
            "nvcc warning : The 'compute_35', 'compute_37', 'compute_50', 'sm_35', 'sm_37' and 'sm_50' architectures are deprecated, and may be removed in a future release (Use -Wno-deprecated-gpu-targets to suppress warning).\n",
            "./src/activation_kernels.cu(263): warning: variable \"MISH_THRESHOLD\" was declared but never referenced\n",
            "\n",
            "./src/activation_kernels.cu(263): warning: variable \"MISH_THRESHOLD\" was declared but never referenced\n",
            "\n",
            "./src/activation_kernels.cu(263): warning: variable \"MISH_THRESHOLD\" was declared but never referenced\n",
            "\n",
            "./src/activation_kernels.cu(263): warning: variable \"MISH_THRESHOLD\" was declared but never referenced\n",
            "\n",
            "./src/activation_kernels.cu(263): warning: variable \"MISH_THRESHOLD\" was declared but never referenced\n",
            "\n",
            "nvcc -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] -gencode arch=compute_70,code=[sm_70,compute_70] -Iinclude/ -I3rdparty/stb/include -DOPENCV `pkg-config --cflags opencv4 2> /dev/null || pkg-config --cflags opencv` -DGPU -I/usr/local/cuda/include/ -DCUDNN -DCUDNN_HALF --compiler-options \"-Wall -Wfatal-errors -Wno-unused-result -Wno-unknown-pragmas -fPIC -Ofast -DOPENCV -DGPU -DCUDNN -I/usr/local/cudnn/include -DCUDNN_HALF\" -c ./src/im2col_kernels.cu -o obj/im2col_kernels.o\n",
            "nvcc warning : The 'compute_35', 'compute_37', 'compute_50', 'sm_35', 'sm_37' and 'sm_50' architectures are deprecated, and may be removed in a future release (Use -Wno-deprecated-gpu-targets to suppress warning).\n",
            "nvcc -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] -gencode arch=compute_70,code=[sm_70,compute_70] -Iinclude/ -I3rdparty/stb/include -DOPENCV `pkg-config --cflags opencv4 2> /dev/null || pkg-config --cflags opencv` -DGPU -I/usr/local/cuda/include/ -DCUDNN -DCUDNN_HALF --compiler-options \"-Wall -Wfatal-errors -Wno-unused-result -Wno-unknown-pragmas -fPIC -Ofast -DOPENCV -DGPU -DCUDNN -I/usr/local/cudnn/include -DCUDNN_HALF\" -c ./src/col2im_kernels.cu -o obj/col2im_kernels.o\n",
            "nvcc warning : The 'compute_35', 'compute_37', 'compute_50', 'sm_35', 'sm_37' and 'sm_50' architectures are deprecated, and may be removed in a future release (Use -Wno-deprecated-gpu-targets to suppress warning).\n",
            "nvcc -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] -gencode arch=compute_70,code=[sm_70,compute_70] -Iinclude/ -I3rdparty/stb/include -DOPENCV `pkg-config --cflags opencv4 2> /dev/null || pkg-config --cflags opencv` -DGPU -I/usr/local/cuda/include/ -DCUDNN -DCUDNN_HALF --compiler-options \"-Wall -Wfatal-errors -Wno-unused-result -Wno-unknown-pragmas -fPIC -Ofast -DOPENCV -DGPU -DCUDNN -I/usr/local/cudnn/include -DCUDNN_HALF\" -c ./src/blas_kernels.cu -o obj/blas_kernels.o\n",
            "nvcc warning : The 'compute_35', 'compute_37', 'compute_50', 'sm_35', 'sm_37' and 'sm_50' architectures are deprecated, and may be removed in a future release (Use -Wno-deprecated-gpu-targets to suppress warning).\n",
            "./src/blas_kernels.cu(1086): warning: variable \"out_index\" was declared but never referenced\n",
            "\n",
            "./src/blas_kernels.cu(1130): warning: variable \"step\" was set but never used\n",
            "\n",
            "./src/blas_kernels.cu(1736): warning: variable \"stage_id\" was declared but never referenced\n",
            "\n",
            "./src/blas_kernels.cu(1086): warning: variable \"out_index\" was declared but never referenced\n",
            "\n",
            "./src/blas_kernels.cu(1130): warning: variable \"step\" was set but never used\n",
            "\n",
            "./src/blas_kernels.cu(1736): warning: variable \"stage_id\" was declared but never referenced\n",
            "\n",
            "./src/blas_kernels.cu(1086): warning: variable \"out_index\" was declared but never referenced\n",
            "\n",
            "./src/blas_kernels.cu(1130): warning: variable \"step\" was set but never used\n",
            "\n",
            "./src/blas_kernels.cu(1736): warning: variable \"stage_id\" was declared but never referenced\n",
            "\n",
            "./src/blas_kernels.cu(1086): warning: variable \"out_index\" was declared but never referenced\n",
            "\n",
            "./src/blas_kernels.cu(1130): warning: variable \"step\" was set but never used\n",
            "\n",
            "./src/blas_kernels.cu(1736): warning: variable \"stage_id\" was declared but never referenced\n",
            "\n",
            "./src/blas_kernels.cu(1086): warning: variable \"out_index\" was declared but never referenced\n",
            "\n",
            "./src/blas_kernels.cu(1130): warning: variable \"step\" was set but never used\n",
            "\n",
            "./src/blas_kernels.cu(1736): 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:1130:5:\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_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] -gencode arch=compute_70,code=[sm_70,compute_70] -Iinclude/ -I3rdparty/stb/include -DOPENCV `pkg-config --cflags opencv4 2> /dev/null || pkg-config --cflags opencv` -DGPU -I/usr/local/cuda/include/ -DCUDNN -DCUDNN_HALF --compiler-options \"-Wall -Wfatal-errors -Wno-unused-result -Wno-unknown-pragmas -fPIC -Ofast -DOPENCV -DGPU -DCUDNN -I/usr/local/cudnn/include -DCUDNN_HALF\" -c ./src/crop_layer_kernels.cu -o obj/crop_layer_kernels.o\n",
            "nvcc warning : The 'compute_35', 'compute_37', 'compute_50', 'sm_35', 'sm_37' and 'sm_50' architectures are deprecated, and may be removed in a future release (Use -Wno-deprecated-gpu-targets to suppress warning).\n",
            "nvcc -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] -gencode arch=compute_70,code=[sm_70,compute_70] -Iinclude/ -I3rdparty/stb/include -DOPENCV `pkg-config --cflags opencv4 2> /dev/null || pkg-config --cflags opencv` -DGPU -I/usr/local/cuda/include/ -DCUDNN -DCUDNN_HALF --compiler-options \"-Wall -Wfatal-errors -Wno-unused-result -Wno-unknown-pragmas -fPIC -Ofast -DOPENCV -DGPU -DCUDNN -I/usr/local/cudnn/include -DCUDNN_HALF\" -c ./src/dropout_layer_kernels.cu -o obj/dropout_layer_kernels.o\n",
            "nvcc warning : The 'compute_35', 'compute_37', 'compute_50', 'sm_35', 'sm_37' and 'sm_50' architectures are deprecated, and may be removed in a future release (Use -Wno-deprecated-gpu-targets to suppress warning).\n",
            "nvcc -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] -gencode arch=compute_70,code=[sm_70,compute_70] -Iinclude/ -I3rdparty/stb/include -DOPENCV `pkg-config --cflags opencv4 2> /dev/null || pkg-config --cflags opencv` -DGPU -I/usr/local/cuda/include/ -DCUDNN -DCUDNN_HALF --compiler-options \"-Wall -Wfatal-errors -Wno-unused-result -Wno-unknown-pragmas -fPIC -Ofast -DOPENCV -DGPU -DCUDNN -I/usr/local/cudnn/include -DCUDNN_HALF\" -c ./src/maxpool_layer_kernels.cu -o obj/maxpool_layer_kernels.o\n",
            "nvcc warning : The 'compute_35', 'compute_37', 'compute_50', 'sm_35', 'sm_37' and 'sm_50' architectures are deprecated, and may be removed in a future release (Use -Wno-deprecated-gpu-targets to suppress warning).\n",
            "nvcc -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] -gencode arch=compute_70,code=[sm_70,compute_70] -Iinclude/ -I3rdparty/stb/include -DOPENCV `pkg-config --cflags opencv4 2> /dev/null || pkg-config --cflags opencv` -DGPU -I/usr/local/cuda/include/ -DCUDNN -DCUDNN_HALF --compiler-options \"-Wall -Wfatal-errors -Wno-unused-result -Wno-unknown-pragmas -fPIC -Ofast -DOPENCV -DGPU -DCUDNN -I/usr/local/cudnn/include -DCUDNN_HALF\" -c ./src/network_kernels.cu -o obj/network_kernels.o\n",
            "nvcc warning : The 'compute_35', 'compute_37', 'compute_50', 'sm_35', 'sm_37' and 'sm_50' architectures are deprecated, and may be removed in a future release (Use -Wno-deprecated-gpu-targets to suppress warning).\n",
            "./src/network_kernels.cu(364): warning: variable \"l\" was declared but never referenced\n",
            "\n",
            "./src/network_kernels.cu(364): warning: variable \"l\" was declared but never referenced\n",
            "\n",
            "./src/network_kernels.cu(364): warning: variable \"l\" was declared but never referenced\n",
            "\n",
            "./src/network_kernels.cu(364): warning: variable \"l\" was declared but never referenced\n",
            "\n",
            "./src/network_kernels.cu(364): warning: variable \"l\" was declared but never referenced\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:364:7:\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",
            "nvcc -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] -gencode arch=compute_70,code=[sm_70,compute_70] -Iinclude/ -I3rdparty/stb/include -DOPENCV `pkg-config --cflags opencv4 2> /dev/null || pkg-config --cflags opencv` -DGPU -I/usr/local/cuda/include/ -DCUDNN -DCUDNN_HALF --compiler-options \"-Wall -Wfatal-errors -Wno-unused-result -Wno-unknown-pragmas -fPIC -Ofast -DOPENCV -DGPU -DCUDNN -I/usr/local/cudnn/include -DCUDNN_HALF\" -c ./src/avgpool_layer_kernels.cu -o obj/avgpool_layer_kernels.o\n",
            "nvcc warning : The 'compute_35', 'compute_37', 'compute_50', 'sm_35', 'sm_37' and 'sm_50' architectures are deprecated, and may be removed in a future release (Use -Wno-deprecated-gpu-targets to suppress warning).\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 -DCUDNN_HALF -Wall -Wfatal-errors -Wno-unused-result -Wno-unknown-pragmas -fPIC -Ofast -DOPENCV -DGPU -DCUDNN -I/usr/local/cudnn/include -DCUDNN_HALF 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/representation_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": "code",
      "metadata": {
        "id": "2KK6P_yuGK2y"
      },
      "source": [
        "# define helper functions\n",
        "def imShow(path):\n",
        "  import cv2\n",
        "  import matplotlib.pyplot as plt\n",
        "  %matplotlib inline\n",
        "\n",
        "  image = cv2.imread(path)\n",
        "  height, width = image.shape[:2]\n",
        "  resized_image = cv2.resize(image,(3*width, 3*height), interpolation = cv2.INTER_CUBIC)\n",
        "\n",
        "  fig = plt.gcf()\n",
        "  fig.set_size_inches(18, 10)\n",
        "  plt.axis(\"off\")\n",
        "  plt.imshow(cv2.cvtColor(resized_image, cv2.COLOR_BGR2RGB))\n",
        "  plt.show()\n",
        "\n",
        "# use this to upload files\n",
        "def upload():\n",
        "  from google.colab import files\n",
        "  uploaded = files.upload() \n",
        "  for name, data in uploaded.items():\n",
        "    with open(name, 'wb') as f:\n",
        "      f.write(data)\n",
        "      print ('saved file', name)\n",
        "\n",
        "# use this to download a file  \n",
        "def download(path):\n",
        "  from google.colab import files\n",
        "  files.download(path)"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "9GXXS-CE_-AS",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "113867f2-c7ea-4b8a-fe4c-32c6687be183"
      },
      "source": [
        "%cd ..\n",
        "from google.colab import drive\n",
        "drive.mount('/content/gdrive')"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "/content\n",
            "Drive already mounted at /content/gdrive; to attempt to forcibly remount, call drive.mount(\"/content/gdrive\", force_remount=True).\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "vPVhCC5D_-CX",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "5cda5621-493b-4c88-8869-e8bc06f5e494"
      },
      "source": [
        "# this creates a symbolic link so that now the path /content/gdrive/My\\ Drive/ is equal to /mydrive\n",
        "!ln -s /content/gdrive/MyDrive/ /mydrive\n",
        "!ls /mydrive"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "ln: failed to create symbolic link '/mydrive/MyDrive': File exists\n",
            " 모아놓기\t\t Dip프로젝트\t\t     testImg222.png\n",
            " 안되는약\t\t DIP프로젝트\t\t     testImg25.JPG\n",
            " 2100TEST\t\t'DIP 기술 관련 자료.gdoc'    testImg55555.JPG\n",
            " A분반_7조_lab11.pptx\t 발표_소진_보고서참고.gdoc   testImg555.JPG\n",
            " annotations\t\t imag\t\t\t     testImg5666.JPG\n",
            " chart.png\t\t images\t\t\t     tmpyolov4\n",
            " chart_yolov4-obj.png\t MyDrive\t\t     yolov4\n",
            "'Colab Notebooks'\t'My Drive'\t\t     yolov4.weights\n",
            "'Colab Yolo 정리.gdoc'\t'반도체공학 기말필기.pdf'\n",
            " crop_test\t\t Shareddrives\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "lNu7H7mo6vHi",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "eeed8f22-8caa-421c-c833-ddb78b985a8c"
      },
      "source": [
        "# cd back into the darknet folder to run detections\n",
        "%cd darknet"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "/content/darknet\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "sMdRkiNmAQXl",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "80379096-5b0a-4cae-be90-549daceedbd8"
      },
      "source": [
        "# this is where my datasets are stored within my Google Drive (I created a yolov4 folder to store all important files for custom training) \n",
        "!ls /mydrive/yolov4"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "backup\t\t   generate_test.py   obj.names     test.zip\n",
            "cfg\t\t   generate_train.py  obj.zip\t    yolov4.conv.137\n",
            "filterforocr222.m  kaggle.json\t      parse-xml.py  yolov4-obj.cfg\n",
            "filterforocr.m\t   obj.data\t      testImg\t    yolov4-parse-xml-new.py\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "-MRMMBMlAQcC"
      },
      "source": [
        "# copy over both datasets into the root directory of the Colab VM (comment out test.zip if you are not using a validation dataset)\n",
        "!cp /mydrive/yolov4/obj.zip ../\n",
        "!cp /mydrive/yolov4/test.zip ../"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "-MuZgRT2AQh-",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "05d494a8-cad0-4a95-b25d-02048daa8c4d"
      },
      "source": [
        "# unzip the datasets and their contents so that they are now in /darknet/data/ folder\n",
        "!unzip ../obj.zip -d data\n",
        "!unzip ../test.zip -d data"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Archive:  ../obj.zip\n",
            "replace data/obj/0 (10).jpg? [y]es, [n]o, [A]ll, [N]one, [r]ename: Archive:  ../test.zip\n",
            "replace data/test/0 (1).jpg? [y]es, [n]o, [A]ll, [N]one, [r]ename: "
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "notIpw92AQm5"
      },
      "source": [
        "# upload the custom .cfg back to cloud VM from Google Drive\n",
        "!cp /mydrive/yolov4/yolov4-obj.cfg ./cfg"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "8GPTOYdsAQpl"
      },
      "source": [
        "# upload the obj.names and obj.data files to cloud VM from Google Drive\n",
        "!cp /mydrive/yolov4/obj.names ./data\n",
        "!cp /mydrive/yolov4/obj.data  ./data"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "MxTNEFy3_-Fg"
      },
      "source": [
        "# upload the generate_train.py and generate_test.py script to cloud VM from Google Drive\n",
        "!cp /mydrive/yolov4/generate_train.py ./\n",
        "!cp /mydrive/yolov4/generate_test.py ./"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "NFDyByfJC5EI"
      },
      "source": [
        "!python generate_train.py\n",
        "!python generate_test.py"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "WnSUJV6FC5Iu"
      },
      "source": [
        "# verify that the newly generated train.txt and test.txt can be seen in our darknet/data folder\n",
        "!ls data/"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "TdyETiw-DIKY"
      },
      "source": [
        "!wget /~https://github.com/AlexeyAB/darknet/releases/download/darknet_yolo_v3_optimal/yolov4.conv.137"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "__9cl9wTDIPr"
      },
      "source": [
        "## train code\n",
        "\n",
        "#!./darknet detector train data/obj.data cfg/yolov4-obj.cfg yolov4.conv.137 -dont_show -map | tee output.log"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "dzUopQxYDISL"
      },
      "source": [
        "# kick off training from where it last saved\n",
        "\n",
        "#!./darknet detector train data/obj.data cfg/yolov4-obj.cfg /mydrive/yolov4/backup/yolov4-obj_last.weights -dont_show\n",
        "#!./darknet detector train data/obj.data cfg/yolov4-obj.cfg /mydrive/yolov4/backup/yolov4-obj_last.weights -map | tee results.log"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "TeH61opf_jS_"
      },
      "source": [
        "## test code\n",
        "\n",
        "%cd ..\n",
        "!git clone /~https://github.com/jung-youjin/yolov4-custom-functions.git\n",
        "%cd yolov4-custom-functions/\n",
        "!pip install -r requirements-gpu.txt\n",
        "%cd /content\n",
        "# weight를 /yolov4-custom-functions/data 에 불러오기\n",
        "!cp /mydrive/yolov4/backup/yolov4-obj_last.weights ./yolov4-custom-functions/data\n",
        "%cd /content/yolov4-custom-functions/data/classes\n",
        "!rm coco.names"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "P4DSxHXY_o0L"
      },
      "source": [
        "%cd /content\n",
        "!cp /mydrive/yolov4/obj.names /content/yolov4-custom-functions/data/classes/coco.names\n",
        "%cd /content/yolov4-custom-functions\n",
        "\n",
        "!python save_model.py --weights ./data/yolov4-obj_last.weights --output ./checkpoints/yolov4-416 --input_size 416 --model yolov4 \n",
        "%cd /content/yolov4-custom-functions/\n",
        "\n",
        "## test image\n",
        "!python detect.py --weights ./checkpoints/yolov4-416 --size 416 --model yolov4 --images /mydrive/yolov4/testImg/testset35장/blog21.jpeg\n",
        "\n",
        "# detection 결과는 /content/yolov4-custom-functions/detections/detection1.png 에서 확인할 수 있음"
      ],
      "execution_count": null,
      "outputs": []
    }
  ]
}