mirror of
https://github.com/opencv/opencv.git
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553 lines
17 KiB
C++
553 lines
17 KiB
C++
#include <iostream>
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#include <fstream>
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#include <string>
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#include <sstream>
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#include <iomanip>
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#include <stdexcept>
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#include <opencv2/core/utility.hpp>
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#include "opencv2/cudaobjdetect.hpp"
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#include "opencv2/highgui.hpp"
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#include "opencv2/objdetect.hpp"
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#include "opencv2/imgproc.hpp"
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using namespace std;
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using namespace cv;
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bool help_showed = false;
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class Args
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{
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public:
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Args();
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static Args read(int argc, char** argv);
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string src;
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bool src_is_folder;
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bool src_is_video;
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bool src_is_camera;
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int camera_id;
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bool svm_load;
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string svm;
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bool write_video;
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string dst_video;
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double dst_video_fps;
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bool make_gray;
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bool resize_src;
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int width, height;
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double scale;
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int nlevels;
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int gr_threshold;
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double hit_threshold;
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bool hit_threshold_auto;
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int win_width;
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int win_stride_width, win_stride_height;
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int block_width;
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int block_stride_width, block_stride_height;
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int cell_width;
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int nbins;
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bool gamma_corr;
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};
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class App
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{
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public:
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App(const Args& s);
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void run();
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void handleKey(char key);
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void hogWorkBegin();
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void hogWorkEnd();
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string hogWorkFps() const;
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void workBegin();
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void workEnd();
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string workFps() const;
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string message() const;
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private:
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App operator=(App&);
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Args args;
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bool running;
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bool use_gpu;
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bool make_gray;
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double scale;
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int gr_threshold;
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int nlevels;
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double hit_threshold;
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bool gamma_corr;
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int64 hog_work_begin;
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double hog_work_fps;
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int64 work_begin;
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double work_fps;
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};
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static void printHelp()
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{
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cout << "Histogram of Oriented Gradients descriptor and detector sample.\n"
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<< "\nUsage: hog\n"
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<< " (<image>|--video <vide>|--camera <camera_id>) # frames source\n"
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<< " or"
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<< " (--folder <folder_path>) # load images from folder\n"
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<< " [--svm <file> # load svm file"
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<< " [--make_gray <true/false>] # convert image to gray one or not\n"
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<< " [--resize_src <true/false>] # do resize of the source image or not\n"
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<< " [--width <int>] # resized image width\n"
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<< " [--height <int>] # resized image height\n"
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<< " [--hit_threshold <double>] # classifying plane distance threshold (0.0 usually)\n"
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<< " [--scale <double>] # HOG window scale factor\n"
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<< " [--nlevels <int>] # max number of HOG window scales\n"
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<< " [--win_width <int>] # width of the window\n"
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<< " [--win_stride_width <int>] # distance by OX axis between neighbour wins\n"
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<< " [--win_stride_height <int>] # distance by OY axis between neighbour wins\n"
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<< " [--block_width <int>] # width of the block\n"
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<< " [--block_stride_width <int>] # distance by 0X axis between neighbour blocks\n"
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<< " [--block_stride_height <int>] # distance by 0Y axis between neighbour blocks\n"
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<< " [--cell_width <int>] # width of the cell\n"
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<< " [--nbins <int>] # number of bins\n"
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<< " [--gr_threshold <int>] # merging similar rects constant\n"
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<< " [--gamma_correct <int>] # do gamma correction or not\n"
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<< " [--write_video <bool>] # write video or not\n"
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<< " [--dst_video <path>] # output video path\n"
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<< " [--dst_video_fps <double>] # output video fps\n";
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help_showed = true;
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}
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int main(int argc, char** argv)
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{
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try
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{
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Args args;
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if (argc < 2)
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{
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printHelp();
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args.camera_id = 0;
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args.src_is_camera = true;
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}
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else
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{
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args = Args::read(argc, argv);
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if (help_showed)
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return -1;
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}
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App app(args);
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app.run();
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}
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catch (const Exception& e) { return cout << "error: " << e.what() << endl, 1; }
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catch (const exception& e) { return cout << "error: " << e.what() << endl, 1; }
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catch(...) { return cout << "unknown exception" << endl, 1; }
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return 0;
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}
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Args::Args()
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{
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src_is_video = false;
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src_is_camera = false;
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src_is_folder = false;
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svm_load = false;
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camera_id = 0;
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write_video = false;
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dst_video_fps = 24.;
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make_gray = false;
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resize_src = false;
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width = 640;
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height = 480;
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scale = 1.05;
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nlevels = 13;
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gr_threshold = 8;
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hit_threshold = 1.4;
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hit_threshold_auto = true;
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win_width = 48;
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win_stride_width = 8;
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win_stride_height = 8;
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block_width = 16;
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block_stride_width = 8;
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block_stride_height = 8;
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cell_width = 8;
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nbins = 9;
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gamma_corr = true;
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}
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Args Args::read(int argc, char** argv)
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{
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Args args;
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for (int i = 1; i < argc; i++)
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{
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if (string(argv[i]) == "--make_gray") args.make_gray = (string(argv[++i]) == "true");
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else if (string(argv[i]) == "--resize_src") args.resize_src = (string(argv[++i]) == "true");
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else if (string(argv[i]) == "--width") args.width = atoi(argv[++i]);
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else if (string(argv[i]) == "--height") args.height = atoi(argv[++i]);
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else if (string(argv[i]) == "--hit_threshold")
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{
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args.hit_threshold = atof(argv[++i]);
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args.hit_threshold_auto = false;
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}
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else if (string(argv[i]) == "--scale") args.scale = atof(argv[++i]);
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else if (string(argv[i]) == "--nlevels") args.nlevels = atoi(argv[++i]);
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else if (string(argv[i]) == "--win_width") args.win_width = atoi(argv[++i]);
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else if (string(argv[i]) == "--win_stride_width") args.win_stride_width = atoi(argv[++i]);
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else if (string(argv[i]) == "--win_stride_height") args.win_stride_height = atoi(argv[++i]);
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else if (string(argv[i]) == "--block_width") args.block_width = atoi(argv[++i]);
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else if (string(argv[i]) == "--block_stride_width") args.block_stride_width = atoi(argv[++i]);
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else if (string(argv[i]) == "--block_stride_height") args.block_stride_height = atoi(argv[++i]);
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else if (string(argv[i]) == "--cell_width") args.cell_width = atoi(argv[++i]);
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else if (string(argv[i]) == "--nbins") args.nbins = atoi(argv[++i]);
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else if (string(argv[i]) == "--gr_threshold") args.gr_threshold = atoi(argv[++i]);
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else if (string(argv[i]) == "--gamma_correct") args.gamma_corr = (string(argv[++i]) == "true");
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else if (string(argv[i]) == "--write_video") args.write_video = (string(argv[++i]) == "true");
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else if (string(argv[i]) == "--dst_video") args.dst_video = argv[++i];
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else if (string(argv[i]) == "--dst_video_fps") args.dst_video_fps = atof(argv[++i]);
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else if (string(argv[i]) == "--help") printHelp();
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else if (string(argv[i]) == "--video") { args.src = argv[++i]; args.src_is_video = true; }
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else if (string(argv[i]) == "--camera") { args.camera_id = atoi(argv[++i]); args.src_is_camera = true; }
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else if (string(argv[i]) == "--folder") { args.src = argv[++i]; args.src_is_folder = true;}
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else if (string(argv[i]) == "--svm") { args.svm = argv[++i]; args.svm_load = true;}
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else if (args.src.empty()) args.src = argv[i];
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else throw runtime_error((string("unknown key: ") + argv[i]));
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}
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return args;
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}
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App::App(const Args& s)
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{
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cv::cuda::printShortCudaDeviceInfo(cv::cuda::getDevice());
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args = s;
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cout << "\nControls:\n"
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<< "\tESC - exit\n"
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<< "\tm - change mode GPU <-> CPU\n"
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<< "\tg - convert image to gray or not\n"
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<< "\t1/q - increase/decrease HOG scale\n"
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<< "\t2/w - increase/decrease levels count\n"
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<< "\t3/e - increase/decrease HOG group threshold\n"
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<< "\t4/r - increase/decrease hit threshold\n"
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<< endl;
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use_gpu = true;
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make_gray = args.make_gray;
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scale = args.scale;
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gr_threshold = args.gr_threshold;
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nlevels = args.nlevels;
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if (args.hit_threshold_auto)
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args.hit_threshold = args.win_width == 48 ? 1.4 : 0.;
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hit_threshold = args.hit_threshold;
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gamma_corr = args.gamma_corr;
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cout << "Scale: " << scale << endl;
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if (args.resize_src)
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cout << "Resized source: (" << args.width << ", " << args.height << ")\n";
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cout << "Group threshold: " << gr_threshold << endl;
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cout << "Levels number: " << nlevels << endl;
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cout << "Win size: (" << args.win_width << ", " << args.win_width*2 << ")\n";
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cout << "Win stride: (" << args.win_stride_width << ", " << args.win_stride_height << ")\n";
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cout << "Block size: (" << args.block_width << ", " << args.block_width << ")\n";
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cout << "Block stride: (" << args.block_stride_width << ", " << args.block_stride_height << ")\n";
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cout << "Cell size: (" << args.cell_width << ", " << args.cell_width << ")\n";
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cout << "Bins number: " << args.nbins << endl;
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cout << "Hit threshold: " << hit_threshold << endl;
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cout << "Gamma correction: " << gamma_corr << endl;
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cout << endl;
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}
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void App::run()
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{
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running = true;
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cv::VideoWriter video_writer;
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Size win_stride(args.win_stride_width, args.win_stride_height);
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Size win_size(args.win_width, args.win_width * 2);
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Size block_size(args.block_width, args.block_width);
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Size block_stride(args.block_stride_width, args.block_stride_height);
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Size cell_size(args.cell_width, args.cell_width);
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cv::Ptr<cv::cuda::HOG> gpu_hog = cv::cuda::HOG::create(win_size, block_size, block_stride, cell_size, args.nbins);
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cv::HOGDescriptor cpu_hog(win_size, block_size, block_stride, cell_size, args.nbins);
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if(args.svm_load) {
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std::vector<float> svm_model;
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const std::string model_file_name = args.svm;
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FileStorage ifs(model_file_name, FileStorage::READ);
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if (ifs.isOpened()) {
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ifs["svm_detector"] >> svm_model;
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} else {
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const std::string what =
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"could not load model for hog classifier from file: "
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+ model_file_name;
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throw std::runtime_error(what);
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}
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// check if the variables are initialized
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if (svm_model.empty()) {
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const std::string what =
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"HoG classifier: svm model could not be loaded from file"
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+ model_file_name;
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throw std::runtime_error(what);
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}
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gpu_hog->setSVMDetector(svm_model);
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cpu_hog.setSVMDetector(svm_model);
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} else {
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// Create HOG descriptors and detectors here
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Mat detector = gpu_hog->getDefaultPeopleDetector();
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gpu_hog->setSVMDetector(detector);
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cpu_hog.setSVMDetector(detector);
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}
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cout << "gpusvmDescriptorSize : " << gpu_hog->getDescriptorSize()
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<< endl;
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cout << "cpusvmDescriptorSize : " << cpu_hog.getDescriptorSize()
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<< endl;
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while (running)
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{
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VideoCapture vc;
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Mat frame;
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vector<String> filenames;
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unsigned int count = 1;
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if (args.src_is_video)
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{
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vc.open(args.src.c_str());
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if (!vc.isOpened())
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throw runtime_error(string("can't open video file: " + args.src));
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vc >> frame;
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}
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else if (args.src_is_folder) {
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String folder = args.src;
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cout << folder << endl;
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glob(folder, filenames);
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frame = imread(filenames[count]); // 0 --> .gitignore
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if (!frame.data)
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cerr << "Problem loading image from folder!!!" << endl;
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}
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else if (args.src_is_camera)
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{
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vc.open(args.camera_id);
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if (!vc.isOpened())
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{
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stringstream msg;
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msg << "can't open camera: " << args.camera_id;
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throw runtime_error(msg.str());
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}
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vc >> frame;
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}
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else
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{
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frame = imread(args.src);
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if (frame.empty())
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throw runtime_error(string("can't open image file: " + args.src));
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}
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Mat img_aux, img, img_to_show;
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cuda::GpuMat gpu_img;
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// Iterate over all frames
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while (running && !frame.empty())
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{
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workBegin();
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// Change format of the image
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if (make_gray) cvtColor(frame, img_aux, COLOR_BGR2GRAY);
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else if (use_gpu) cvtColor(frame, img_aux, COLOR_BGR2BGRA);
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else frame.copyTo(img_aux);
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// Resize image
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if (args.resize_src) resize(img_aux, img, Size(args.width, args.height));
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else img = img_aux;
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img_to_show = img;
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vector<Rect> found;
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// Perform HOG classification
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hogWorkBegin();
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if (use_gpu)
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{
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gpu_img.upload(img);
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gpu_hog->setNumLevels(nlevels);
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gpu_hog->setHitThreshold(hit_threshold);
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gpu_hog->setWinStride(win_stride);
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gpu_hog->setScaleFactor(scale);
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gpu_hog->setGroupThreshold(gr_threshold);
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gpu_hog->detectMultiScale(gpu_img, found);
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}
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else
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{
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cpu_hog.nlevels = nlevels;
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cpu_hog.detectMultiScale(img, found, hit_threshold, win_stride,
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Size(0, 0), scale, gr_threshold);
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}
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hogWorkEnd();
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// Draw positive classified windows
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for (size_t i = 0; i < found.size(); i++)
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{
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Rect r = found[i];
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rectangle(img_to_show, r.tl(), r.br(), Scalar(0, 255, 0), 3);
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}
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if (use_gpu)
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putText(img_to_show, "Mode: GPU", Point(5, 25), FONT_HERSHEY_SIMPLEX, 1., Scalar(255, 100, 0), 2);
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else
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putText(img_to_show, "Mode: CPU", Point(5, 25), FONT_HERSHEY_SIMPLEX, 1., Scalar(255, 100, 0), 2);
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putText(img_to_show, "FPS HOG: " + hogWorkFps(), Point(5, 65), FONT_HERSHEY_SIMPLEX, 1., Scalar(255, 100, 0), 2);
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putText(img_to_show, "FPS total: " + workFps(), Point(5, 105), FONT_HERSHEY_SIMPLEX, 1., Scalar(255, 100, 0), 2);
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imshow("opencv_gpu_hog", img_to_show);
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if (args.src_is_video || args.src_is_camera) vc >> frame;
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if (args.src_is_folder) {
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count++;
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if (count < filenames.size()) {
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frame = imread(filenames[count]);
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} else {
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Mat empty;
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frame = empty;
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}
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}
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workEnd();
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if (args.write_video)
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{
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if (!video_writer.isOpened())
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{
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video_writer.open(args.dst_video, VideoWriter::fourcc('x','v','i','d'), args.dst_video_fps,
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img_to_show.size(), true);
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if (!video_writer.isOpened())
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throw std::runtime_error("can't create video writer");
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}
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if (make_gray) cvtColor(img_to_show, img, COLOR_GRAY2BGR);
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else cvtColor(img_to_show, img, COLOR_BGRA2BGR);
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video_writer << img;
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}
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handleKey((char)waitKey(3));
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}
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}
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}
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void App::handleKey(char key)
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{
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switch (key)
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{
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case 27:
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running = false;
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break;
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case 'm':
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case 'M':
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use_gpu = !use_gpu;
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cout << "Switched to " << (use_gpu ? "CUDA" : "CPU") << " mode\n";
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break;
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case 'g':
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case 'G':
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make_gray = !make_gray;
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cout << "Convert image to gray: " << (make_gray ? "YES" : "NO") << endl;
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break;
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case '1':
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scale *= 1.05;
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cout << "Scale: " << scale << endl;
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break;
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case 'q':
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case 'Q':
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scale /= 1.05;
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cout << "Scale: " << scale << endl;
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break;
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case '2':
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nlevels++;
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cout << "Levels number: " << nlevels << endl;
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break;
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case 'w':
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case 'W':
|
|
nlevels = max(nlevels - 1, 1);
|
|
cout << "Levels number: " << nlevels << endl;
|
|
break;
|
|
case '3':
|
|
gr_threshold++;
|
|
cout << "Group threshold: " << gr_threshold << endl;
|
|
break;
|
|
case 'e':
|
|
case 'E':
|
|
gr_threshold = max(0, gr_threshold - 1);
|
|
cout << "Group threshold: " << gr_threshold << endl;
|
|
break;
|
|
case '4':
|
|
hit_threshold+=0.25;
|
|
cout << "Hit threshold: " << hit_threshold << endl;
|
|
break;
|
|
case 'r':
|
|
case 'R':
|
|
hit_threshold = max(0.0, hit_threshold - 0.25);
|
|
cout << "Hit threshold: " << hit_threshold << endl;
|
|
break;
|
|
case 'c':
|
|
case 'C':
|
|
gamma_corr = !gamma_corr;
|
|
cout << "Gamma correction: " << gamma_corr << endl;
|
|
break;
|
|
}
|
|
}
|
|
|
|
|
|
inline void App::hogWorkBegin() { hog_work_begin = getTickCount(); }
|
|
|
|
inline void App::hogWorkEnd()
|
|
{
|
|
int64 delta = getTickCount() - hog_work_begin;
|
|
double freq = getTickFrequency();
|
|
hog_work_fps = freq / delta;
|
|
}
|
|
|
|
inline string App::hogWorkFps() const
|
|
{
|
|
stringstream ss;
|
|
ss << hog_work_fps;
|
|
return ss.str();
|
|
}
|
|
|
|
|
|
inline void App::workBegin() { work_begin = getTickCount(); }
|
|
|
|
inline void App::workEnd()
|
|
{
|
|
int64 delta = getTickCount() - work_begin;
|
|
double freq = getTickFrequency();
|
|
work_fps = freq / delta;
|
|
}
|
|
|
|
inline string App::workFps() const
|
|
{
|
|
stringstream ss;
|
|
ss << work_fps;
|
|
return ss.str();
|
|
}
|