448 lines
13 KiB
C++
448 lines
13 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/ocl/ocl.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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class App
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{
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public:
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App(CommandLineParser& cmd);
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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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// This function test if gpu_rst matches cpu_rst.
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// If the two vectors are not equal, it will return the difference in vector size
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// Else if will return
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// (total diff of each cpu and gpu rects covered pixels)/(total cpu rects covered pixels)
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double checkRectSimilarity(Size sz,
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std::vector<Rect>& cpu_rst,
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std::vector<Rect>& gpu_rst);
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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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double resize_scale;
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int win_width;
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int win_stride_width, win_stride_height;
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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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string img_source;
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string vdo_source;
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string output;
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int camera_id;
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bool write_once;
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};
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int main(int argc, char** argv)
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{
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const char* keys =
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"{ h | help | false | print help message }"
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"{ i | input | | specify input image}"
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"{ c | camera | -1 | enable camera capturing }"
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"{ v | video | | use video as input }"
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"{ g | gray | false | convert image to gray one or not}"
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"{ s | scale | 1.0 | resize the image before detect}"
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"{ l |larger_win| false | use 64x128 window}"
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"{ o | output | | specify output path when input is images}";
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CommandLineParser cmd(argc, argv, keys);
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if (cmd.get<bool>("help"))
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{
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cout << "Usage : hog [options]" << endl;
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cout << "Available options:" << endl;
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cmd.printParams();
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return EXIT_SUCCESS;
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}
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App app(cmd);
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try
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{
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app.run();
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}
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catch (const Exception& e)
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{
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return cout << "error: " << e.what() << endl, 1;
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}
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catch (const exception& e)
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{
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return cout << "error: " << e.what() << endl, 1;
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}
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catch(...)
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{
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return cout << "unknown exception" << endl, 1;
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}
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return EXIT_SUCCESS;
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}
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App::App(CommandLineParser& cmd)
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{
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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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<< "\to - save output image once, or switch on/off video save\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 = cmd.get<bool>("g");
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resize_scale = cmd.get<double>("s");
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win_width = cmd.get<bool>("l") == true ? 64 : 48;
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vdo_source = cmd.get<string>("v");
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img_source = cmd.get<string>("i");
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output = cmd.get<string>("o");
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camera_id = cmd.get<int>("c");
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win_stride_width = 8;
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win_stride_height = 8;
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gr_threshold = 8;
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nlevels = 13;
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hit_threshold = win_width == 48 ? 1.4 : 0.;
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scale = 1.05;
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gamma_corr = true;
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write_once = false;
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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: " << win_width << endl;
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cout << "Win stride: (" << win_stride_width << ", " << 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::run()
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{
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running = true;
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VideoWriter video_writer;
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Size win_size(win_width, win_width * 2);
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Size win_stride(win_stride_width, win_stride_height);
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// Create HOG descriptors and detectors here
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vector<float> detector;
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if (win_size == Size(64, 128))
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detector = ocl::HOGDescriptor::getPeopleDetector64x128();
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else
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detector = ocl::HOGDescriptor::getPeopleDetector48x96();
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ocl::HOGDescriptor gpu_hog(win_size, Size(16, 16), Size(8, 8), Size(8, 8), 9,
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ocl::HOGDescriptor::DEFAULT_WIN_SIGMA, 0.2, gamma_corr,
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ocl::HOGDescriptor::DEFAULT_NLEVELS);
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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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gpu_hog.setSVMDetector(detector);
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cpu_hog.setSVMDetector(detector);
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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 (vdo_source!="")
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{
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vc.open(vdo_source.c_str());
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if (!vc.isOpened())
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throw runtime_error(string("can't open video file: " + vdo_source));
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vc >> frame;
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}
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else if (camera_id != -1)
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{
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vc.open(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: " << 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(img_source);
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if (frame.empty())
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throw runtime_error(string("can't open image file: " + img_source));
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}
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Mat img_aux, img, img_to_show;
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ocl::oclMat gpu_img;
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// Iterate over all frames
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bool verify = false;
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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, CV_BGR2GRAY);
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else if (use_gpu) cvtColor(frame, img_aux, CV_BGR2BGRA);
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else frame.copyTo(img_aux);
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// Resize image
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if (abs(scale-1.0)>0.001)
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{
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Size sz((int)((double)img_aux.cols/resize_scale), (int)((double)img_aux.rows/resize_scale));
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resize(img_aux, img, sz);
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}
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else 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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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.detectMultiScale(gpu_img, found, hit_threshold, win_stride,
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Size(0, 0), scale, gr_threshold);
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if (!verify)
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{
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// verify if GPU output same objects with CPU at 1st run
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verify = true;
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vector<Rect> ref_rst;
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cvtColor(img, img, CV_BGRA2BGR);
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cpu_hog.detectMultiScale(img, ref_rst, hit_threshold, win_stride,
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Size(0, 0), scale, gr_threshold-2);
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double accuracy = checkRectSimilarity(img.size(), ref_rst, found);
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cout << "\naccuracy value: " << accuracy << endl;
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}
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}
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else cpu_hog.detectMultiScale(img, found, hit_threshold, win_stride,
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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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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 only): " + 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 (vdo_source!="" || camera_id!=-1) vc >> frame;
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workEnd();
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if (output!="" && write_once)
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{
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if (img_source!="") // wirte image
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{
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write_once = false;
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imwrite(output, img_to_show);
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}
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else //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(output, CV_FOURCC('x','v','i','d'), 24,
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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, CV_GRAY2BGR);
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else cvtColor(img_to_show, img, CV_BGRA2BGR);
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video_writer << img;
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}
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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':
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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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case 'o':
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case 'O':
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write_once = !write_once;
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break;
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}
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}
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inline void App::hogWorkBegin()
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{
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hog_work_begin = getTickCount();
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}
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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 string App::hogWorkFps() const
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{
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stringstream ss;
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ss << hog_work_fps;
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return ss.str();
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}
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inline void App::workBegin()
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{
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work_begin = getTickCount();
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}
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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 string App::workFps() const
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{
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stringstream ss;
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ss << work_fps;
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return ss.str();
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}
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double App::checkRectSimilarity(Size sz,
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std::vector<Rect>& ob1,
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std::vector<Rect>& ob2)
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{
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double final_test_result = 0.0;
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size_t sz1 = ob1.size();
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size_t sz2 = ob2.size();
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if(sz1 != sz2)
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{
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return sz1 > sz2 ? (double)(sz1 - sz2) : (double)(sz2 - sz1);
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}
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else
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{
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if(sz1==0 && sz2==0)
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return 0;
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cv::Mat cpu_result(sz, CV_8UC1);
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cpu_result.setTo(0);
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for(vector<Rect>::const_iterator r = ob1.begin(); r != ob1.end(); r++)
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{
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cv::Mat cpu_result_roi(cpu_result, *r);
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cpu_result_roi.setTo(1);
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cpu_result.copyTo(cpu_result);
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}
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int cpu_area = cv::countNonZero(cpu_result > 0);
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cv::Mat gpu_result(sz, CV_8UC1);
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gpu_result.setTo(0);
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for(vector<Rect>::const_iterator r2 = ob2.begin(); r2 != ob2.end(); r2++)
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{
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cv::Mat gpu_result_roi(gpu_result, *r2);
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gpu_result_roi.setTo(1);
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gpu_result.copyTo(gpu_result);
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}
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cv::Mat result_;
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multiply(cpu_result, gpu_result, result_);
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int result = cv::countNonZero(result_ > 0);
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if(cpu_area!=0 && result!=0)
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final_test_result = 1.0 - (double)result/(double)cpu_area;
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else if(cpu_area==0 && result!=0)
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final_test_result = -1;
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}
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return final_test_result;
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}
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