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Open Source Computer Vision Library
https://opencv.org/
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419 lines
12 KiB
419 lines
12 KiB
#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/gpu/gpu.hpp" |
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#include "opencv2/highgui/highgui.hpp" |
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using namespace std; |
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using namespace cv; |
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//#define WRITE_VIDEO |
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/** Contains all properties of application (including those which can be |
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changed by user in runtime) */ |
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class Settings |
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{ |
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public: |
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/** Sets default values */ |
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Settings(); |
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/** Reads settings from command args */ |
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static Settings Read(int argc, char** argv); |
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string src; |
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bool src_is_video; |
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bool make_gray; |
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bool resize_src; |
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double resize_src_scale; |
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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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int win_width; |
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int win_stride_width; |
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int win_stride_height; |
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bool gamma_corr; |
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}; |
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/** Describes aplication logic */ |
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class App |
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{ |
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public: |
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/** Initializes application */ |
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App(const Settings& s); |
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/** Runs demo using OpenCV highgui module for GUI building */ |
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void RunOpencvGui(); |
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/** Processes user keybord input */ |
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void HandleKey(char key); |
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void HogWorkBegin(); |
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void HogWorkEnd(); |
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double HogWorkFps() const; |
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void WorkBegin(); |
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void WorkEnd(); |
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double WorkFps() const; |
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const string GetPerformanceSummary() const; |
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private: |
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App operator=(App&); |
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Settings settings; |
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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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int main(int argc, char** argv) |
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{ |
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try |
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{ |
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if (argc < 2) |
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{ |
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cout << "Usage:\nhog_gpu\n" |
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<< " -src <path_to_the_source>\n" |
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<< " [-src_is_video <true/false>] # says to interp. src as img or as video\n" |
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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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<< " [-resize_src_scale <double>] # preprocessing image scale factor\n" |
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<< " [-hit_threshold <double>] # classifying plane dist. 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 (48 or 64)\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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<< " [-gr_threshold <int>] # merging similar rects constant\n" |
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<< " [-gamma_corr <int>] # do gamma correction or not\n"; |
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return 1; |
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} |
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App app(Settings::Read(argc, argv)); |
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app.RunOpencvGui(); |
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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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Settings::Settings() |
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{ |
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src_is_video = false; |
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make_gray = false; |
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resize_src = true; |
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resize_src_scale = 1.5; |
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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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win_width = 48; |
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win_stride_width = 8; |
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win_stride_height = 8; |
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gamma_corr = true; |
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} |
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Settings Settings::Read(int argc, char** argv) |
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{ |
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cout << "Parsing command args" << endl; |
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Settings settings; |
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for (int i = 1; i < argc - 1; i += 2) |
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{ |
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string key = argv[i]; |
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string val = argv[i + 1]; |
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if (key == "-src") settings.src = val; |
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else if (key == "-src_is_video") settings.src_is_video = (val == "true"); |
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else if (key == "-make_gray") settings.make_gray = (val == "true"); |
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else if (key == "-resize_src") settings.resize_src = (val == "true"); |
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else if (key == "-resize_src_scale") settings.resize_src_scale = atof(val.c_str()); |
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else if (key == "-hit_threshold") settings.hit_threshold = atof(val.c_str()); |
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else if (key == "-scale") settings.scale = atof(val.c_str()); |
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else if (key == "-nlevels") settings.nlevels = atoi(val.c_str()); |
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else if (key == "-win_width") settings.win_width = atoi(val.c_str()); |
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else if (key == "-win_stride_width") settings.win_stride_width = atoi(val.c_str()); |
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else if (key == "-win_stride_height") settings.win_stride_height = atoi(val.c_str()); |
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else if (key == "-gr_threshold") settings.gr_threshold = atoi(val.c_str()); |
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else if (key == "-gamma_corr") settings.gamma_corr = atoi(val.c_str()) != 0; |
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else throw runtime_error((string("Unknown key: ") + key)); |
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} |
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cout << "Command args are parsed\n"; |
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return settings; |
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} |
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App::App(const Settings &s) |
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{ |
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settings = 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 = settings.make_gray; |
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scale = settings.scale; |
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gr_threshold = settings.gr_threshold; |
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nlevels = settings.nlevels; |
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hit_threshold = settings.hit_threshold; |
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gamma_corr = settings.gamma_corr; |
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if (settings.win_width != 64 && settings.win_width != 48) |
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settings.win_width = 64; |
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cout << "Scale: " << scale << endl; |
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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 width: " << settings.win_width << endl; |
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cout << "Win stride: (" << settings.win_stride_width << ", " << settings.win_stride_height << ")\n"; |
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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::RunOpencvGui() |
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{ |
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running = true; |
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Size win_size(settings.win_width, settings.win_width * 2); //(64, 128) or (48, 96) |
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Size win_stride(settings.win_stride_width, settings.win_stride_height); |
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vector<float> detector; |
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if (win_size == Size(64, 128)) |
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detector = cv::gpu::HOGDescriptor::getPeopleDetector_64x128(); |
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else |
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detector = cv::gpu::HOGDescriptor::getPeopleDetector_48x96(); |
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// GPU's HOG classifier |
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cv::gpu::HOGDescriptor gpu_hog(win_size, Size(16, 16), Size(8, 8), Size(8, 8), 9, |
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cv::gpu::HOGDescriptor::DEFAULT_WIN_SIGMA, 0.2, gamma_corr, |
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cv::gpu::HOGDescriptor::DEFAULT_NLEVELS); |
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gpu_hog.setSVMDetector(detector); |
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// CPU's HOG classifier |
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cv::HOGDescriptor cpu_hog(win_size, Size(16, 16), Size(8, 8), Size(8, 8), 9, 1, -1, |
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HOGDescriptor::L2Hys, 0.2, gamma_corr, cv::HOGDescriptor::DEFAULT_NLEVELS); |
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cpu_hog.setSVMDetector(detector); |
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#ifdef WRITE_VIDEO |
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cv::VideoWriter video_writer; |
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video_writer.open("output.avi", CV_FOURCC('x','v','i','d'), 24., cv::Size(640, 480), 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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#endif |
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// Make endless cycle from video (if src is video) |
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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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if (settings.src_is_video) |
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{ |
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vc.open(settings.src.c_str()); |
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if (!vc.isOpened()) |
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throw runtime_error(string("Can't open video file: " + settings.src)); |
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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(settings.src); |
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if (frame.empty()) |
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throw runtime_error(string("Can't open image file: " + settings.src)); |
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} |
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Mat img_aux, img, img_to_show; |
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gpu::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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vector<Rect> found; |
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// Change format of the image (input must be 8UC3) |
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if (make_gray) |
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cvtColor(frame, img_aux, CV_BGR2GRAY); |
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else if (use_gpu) |
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cvtColor(frame, img_aux, CV_BGR2BGRA); |
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else |
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img_aux = frame; |
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// Resize image |
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if (settings.resize_src) |
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resize(img_aux, img, Size(int(frame.cols * settings.resize_src_scale), int(frame.rows * settings.resize_src_scale))); |
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else |
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img = img_aux; |
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img_to_show = img; |
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gpu_hog.nlevels = nlevels; |
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cpu_hog.nlevels = nlevels; |
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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 = img; |
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gpu_hog.detectMultiScale(gpu_img, found, hit_threshold, win_stride, Size(0, 0), scale, gr_threshold); |
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} |
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else |
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cpu_hog.detectMultiScale(img, found, hit_threshold, win_stride, Size(0, 0), scale, gr_threshold); |
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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(), CV_RGB(0, 255, 0), 3); |
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} |
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// Show results |
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putText(img_to_show, GetPerformanceSummary(), Point(5, 25), FONT_HERSHEY_SIMPLEX, 1.0, Scalar(0, 0, 255), 2); |
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imshow("opencv_gpu_hog", img_to_show); |
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HandleKey((char)waitKey(3)); |
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if (settings.src_is_video) |
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{ |
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vc >> frame; |
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} |
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WorkEnd(); |
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#ifdef WRITE_VIDEO |
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cvtColor(img_to_show, img, CV_BGRA2BGR); |
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video_writer << img; |
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#endif |
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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': |
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nlevels = max(nlevels - 1, 1); |
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cout << "Levels number: " << nlevels << endl; |
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break; |
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case '3': |
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gr_threshold++; |
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cout << "Group threshold: " << gr_threshold << endl; |
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break; |
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case 'e': |
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case 'E': |
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gr_threshold = max(0, gr_threshold - 1); |
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cout << "Group threshold: " << gr_threshold << endl; |
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break; |
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case '4': |
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hit_threshold+=0.25; |
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cout << "Hit threshold: " << hit_threshold << endl; |
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break; |
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case 'r': |
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case 'R': |
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hit_threshold = max(0.0, hit_threshold - 0.25); |
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cout << "Hit threshold: " << hit_threshold << endl; |
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break; |
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case 'c': |
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case 'C': |
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gamma_corr = !gamma_corr; |
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cout << "Gamma correction: " << gamma_corr << endl; |
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break; |
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} |
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} |
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inline void App::HogWorkBegin() { hog_work_begin = getTickCount(); } |
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inline void App::HogWorkEnd() |
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{ |
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int64 delta = getTickCount() - hog_work_begin; |
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double freq = getTickFrequency(); |
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hog_work_fps = freq / delta; |
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} |
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inline double App::HogWorkFps() const { return hog_work_fps; } |
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inline void App::WorkBegin() { work_begin = getTickCount(); } |
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inline void App::WorkEnd() |
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{ |
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int64 delta = getTickCount() - work_begin; |
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double freq = getTickFrequency(); |
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work_fps = freq / delta; |
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} |
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inline double App::WorkFps() const { return work_fps; } |
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inline const string App::GetPerformanceSummary() const |
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{ |
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stringstream ss; |
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ss << (use_gpu ? "GPU" : "CPU") << " HOG FPS: " << setiosflags(ios::left) << setprecision(4) << |
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setw(7) << HogWorkFps() << " Total FPS: " << setprecision(4) << setw(7) << WorkFps(); |
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return ss.str(); |
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}
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