368 lines
10 KiB
C++
368 lines
10 KiB
C++
#include <iostream>
|
|
#include <fstream>
|
|
#include <string>
|
|
#include <sstream>
|
|
#include <iomanip>
|
|
#include <stdexcept>
|
|
#include <opencv2/core/ocl.hpp>
|
|
#include <opencv2/core/utility.hpp>
|
|
#include "opencv2/imgcodecs.hpp"
|
|
#include <opencv2/video.hpp>
|
|
#include <opencv2/videoio.hpp>
|
|
#include <opencv2/highgui.hpp>
|
|
#include <opencv2/objdetect.hpp>
|
|
#include <opencv2/imgproc.hpp>
|
|
|
|
using namespace std;
|
|
using namespace cv;
|
|
|
|
class App
|
|
{
|
|
public:
|
|
App(CommandLineParser& cmd);
|
|
void run();
|
|
void handleKey(char key);
|
|
void hogWorkBegin();
|
|
void hogWorkEnd();
|
|
string hogWorkFps() const;
|
|
void workBegin();
|
|
void workEnd();
|
|
string workFps() const;
|
|
string message() const;
|
|
|
|
|
|
// This function test if gpu_rst matches cpu_rst.
|
|
// If the two vectors are not equal, it will return the difference in vector size
|
|
// Else if will return
|
|
// (total diff of each cpu and gpu rects covered pixels)/(total cpu rects covered pixels)
|
|
double checkRectSimilarity(Size sz,
|
|
std::vector<Rect>& cpu_rst,
|
|
std::vector<Rect>& gpu_rst);
|
|
private:
|
|
App operator=(App&);
|
|
|
|
//Args args;
|
|
bool running;
|
|
bool make_gray;
|
|
double scale;
|
|
double resize_scale;
|
|
int win_width;
|
|
int win_stride_width, win_stride_height;
|
|
int gr_threshold;
|
|
int nlevels;
|
|
double hit_threshold;
|
|
bool gamma_corr;
|
|
|
|
int64 hog_work_begin;
|
|
double hog_work_fps;
|
|
int64 work_begin;
|
|
double work_fps;
|
|
|
|
string img_source;
|
|
string vdo_source;
|
|
string output;
|
|
int camera_id;
|
|
bool write_once;
|
|
};
|
|
|
|
int main(int argc, char** argv)
|
|
{
|
|
const char* keys =
|
|
"{ h help | false | print help message }"
|
|
"{ i input | | specify input image}"
|
|
"{ c camera | -1 | enable camera capturing }"
|
|
"{ v video | ../data/768x576.avi | use video as input }"
|
|
"{ g gray | false | convert image to gray one or not}"
|
|
"{ s scale | 1.0 | resize the image before detect}"
|
|
"{ o output | | specify output path when input is images}";
|
|
CommandLineParser cmd(argc, argv, keys);
|
|
if (cmd.has("help"))
|
|
{
|
|
cout << "Usage : hog [options]" << endl;
|
|
cout << "Available options:" << endl;
|
|
cmd.printMessage();
|
|
return EXIT_SUCCESS;
|
|
}
|
|
|
|
App app(cmd);
|
|
try
|
|
{
|
|
app.run();
|
|
}
|
|
catch (const Exception& e)
|
|
{
|
|
return cout << "error: " << e.what() << endl, 1;
|
|
}
|
|
catch (const exception& e)
|
|
{
|
|
return cout << "error: " << e.what() << endl, 1;
|
|
}
|
|
catch(...)
|
|
{
|
|
return cout << "unknown exception" << endl, 1;
|
|
}
|
|
return EXIT_SUCCESS;
|
|
}
|
|
|
|
App::App(CommandLineParser& cmd)
|
|
{
|
|
cout << "\nControls:\n"
|
|
<< "\tESC - exit\n"
|
|
<< "\tm - change mode GPU <-> CPU\n"
|
|
<< "\tg - convert image to gray or not\n"
|
|
<< "\to - save output image once, or switch on/off video save\n"
|
|
<< "\t1/q - increase/decrease HOG scale\n"
|
|
<< "\t2/w - increase/decrease levels count\n"
|
|
<< "\t3/e - increase/decrease HOG group threshold\n"
|
|
<< "\t4/r - increase/decrease hit threshold\n"
|
|
<< endl;
|
|
|
|
make_gray = cmd.has("gray");
|
|
resize_scale = cmd.get<double>("s");
|
|
vdo_source = cmd.get<string>("v");
|
|
img_source = cmd.get<string>("i");
|
|
output = cmd.get<string>("o");
|
|
camera_id = cmd.get<int>("c");
|
|
|
|
win_width = 48;
|
|
win_stride_width = 8;
|
|
win_stride_height = 8;
|
|
gr_threshold = 8;
|
|
nlevels = 13;
|
|
hit_threshold = 1.4;
|
|
scale = 1.05;
|
|
gamma_corr = true;
|
|
write_once = false;
|
|
|
|
cout << "Group threshold: " << gr_threshold << endl;
|
|
cout << "Levels number: " << nlevels << endl;
|
|
cout << "Win width: " << win_width << endl;
|
|
cout << "Win stride: (" << win_stride_width << ", " << win_stride_height << ")\n";
|
|
cout << "Hit threshold: " << hit_threshold << endl;
|
|
cout << "Gamma correction: " << gamma_corr << endl;
|
|
cout << endl;
|
|
}
|
|
|
|
void App::run()
|
|
{
|
|
running = true;
|
|
VideoWriter video_writer;
|
|
|
|
Size win_size(win_width, win_width * 2);
|
|
Size win_stride(win_stride_width, win_stride_height);
|
|
|
|
// Create HOG descriptors and detectors here
|
|
|
|
HOGDescriptor hog(win_size, Size(16, 16), Size(8, 8), Size(8, 8), 9, 1, -1,
|
|
HOGDescriptor::L2Hys, 0.2, gamma_corr, cv::HOGDescriptor::DEFAULT_NLEVELS);
|
|
hog.setSVMDetector( HOGDescriptor::getDaimlerPeopleDetector() );
|
|
|
|
while (running)
|
|
{
|
|
VideoCapture vc;
|
|
UMat frame;
|
|
|
|
if (vdo_source!="")
|
|
{
|
|
vc.open(vdo_source.c_str());
|
|
if (!vc.isOpened())
|
|
throw runtime_error(string("can't open video file: " + vdo_source));
|
|
vc >> frame;
|
|
}
|
|
else if (camera_id != -1)
|
|
{
|
|
vc.open(camera_id);
|
|
if (!vc.isOpened())
|
|
{
|
|
stringstream msg;
|
|
msg << "can't open camera: " << camera_id;
|
|
throw runtime_error(msg.str());
|
|
}
|
|
vc >> frame;
|
|
}
|
|
else
|
|
{
|
|
imread(img_source).copyTo(frame);
|
|
if (frame.empty())
|
|
throw runtime_error(string("can't open image file: " + img_source));
|
|
}
|
|
|
|
UMat img_aux, img;
|
|
Mat img_to_show;
|
|
|
|
// Iterate over all frames
|
|
while (running && !frame.empty())
|
|
{
|
|
workBegin();
|
|
|
|
// Change format of the image
|
|
if (make_gray) cvtColor(frame, img_aux, COLOR_BGR2GRAY );
|
|
else frame.copyTo(img_aux);
|
|
|
|
// Resize image
|
|
if (abs(scale-1.0)>0.001)
|
|
{
|
|
Size sz((int)((double)img_aux.cols/resize_scale), (int)((double)img_aux.rows/resize_scale));
|
|
resize(img_aux, img, sz);
|
|
}
|
|
else img = img_aux;
|
|
img.copyTo(img_to_show);
|
|
hog.nlevels = nlevels;
|
|
vector<Rect> found;
|
|
|
|
// Perform HOG classification
|
|
hogWorkBegin();
|
|
|
|
hog.detectMultiScale(img, found, hit_threshold, win_stride,
|
|
Size(0, 0), scale, gr_threshold);
|
|
hogWorkEnd();
|
|
|
|
|
|
// Draw positive classified windows
|
|
for (size_t i = 0; i < found.size(); i++)
|
|
{
|
|
Rect r = found[i];
|
|
rectangle(img_to_show, r.tl(), r.br(), Scalar(0, 255, 0), 3);
|
|
}
|
|
|
|
putText(img_to_show, ocl::useOpenCL() ? "Mode: OpenCL" : "Mode: CPU", Point(5, 25), FONT_HERSHEY_SIMPLEX, 1., Scalar(255, 100, 0), 2);
|
|
putText(img_to_show, "FPS (HOG only): " + hogWorkFps(), Point(5, 65), FONT_HERSHEY_SIMPLEX, 1., Scalar(255, 100, 0), 2);
|
|
putText(img_to_show, "FPS (total): " + workFps(), Point(5, 105), FONT_HERSHEY_SIMPLEX, 1., Scalar(255, 100, 0), 2);
|
|
imshow("opencv_hog", img_to_show);
|
|
if (vdo_source!="" || camera_id!=-1) vc >> frame;
|
|
|
|
workEnd();
|
|
|
|
if (output!="" && write_once)
|
|
{
|
|
if (img_source!="") // wirte image
|
|
{
|
|
write_once = false;
|
|
imwrite(output, img_to_show);
|
|
}
|
|
else //write video
|
|
{
|
|
if (!video_writer.isOpened())
|
|
{
|
|
video_writer.open(output, VideoWriter::fourcc('x','v','i','d'), 24,
|
|
img_to_show.size(), true);
|
|
if (!video_writer.isOpened())
|
|
throw std::runtime_error("can't create video writer");
|
|
}
|
|
|
|
if (make_gray) cvtColor(img_to_show, img, COLOR_GRAY2BGR);
|
|
else cvtColor(img_to_show, img, COLOR_BGRA2BGR);
|
|
|
|
video_writer << img.getMat(ACCESS_READ);
|
|
}
|
|
}
|
|
|
|
handleKey((char)waitKey(3));
|
|
}
|
|
}
|
|
}
|
|
|
|
void App::handleKey(char key)
|
|
{
|
|
switch (key)
|
|
{
|
|
case 27:
|
|
running = false;
|
|
break;
|
|
case 'm':
|
|
case 'M':
|
|
ocl::setUseOpenCL(!cv::ocl::useOpenCL());
|
|
cout << "Switched to " << (ocl::useOpenCL() ? "OpenCL enabled" : "CPU") << " mode\n";
|
|
break;
|
|
case 'g':
|
|
case 'G':
|
|
make_gray = !make_gray;
|
|
cout << "Convert image to gray: " << (make_gray ? "YES" : "NO") << endl;
|
|
break;
|
|
case '1':
|
|
scale *= 1.05;
|
|
cout << "Scale: " << scale << endl;
|
|
break;
|
|
case 'q':
|
|
case 'Q':
|
|
scale /= 1.05;
|
|
cout << "Scale: " << scale << endl;
|
|
break;
|
|
case '2':
|
|
nlevels++;
|
|
cout << "Levels number: " << nlevels << endl;
|
|
break;
|
|
case 'w':
|
|
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;
|
|
case 'o':
|
|
case 'O':
|
|
write_once = !write_once;
|
|
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();
|
|
}
|