#include
#include
#include
#include
#include
#include
#include "opencv2/gpu/gpu.hpp"
#include "opencv2/highgui/highgui.hpp"
using namespace std;
using namespace cv;
/** Contains all properties of application (including those which can be
changed by user in runtime) */
class Settings
{
public:
/** Sets default values */
Settings();
/** Reads settings from command args */
static Settings Read(int argc, char** argv);
string src;
bool src_is_video;
bool make_gray;
bool resize_src;
double resize_src_scale;
double scale;
int nlevels;
int gr_threshold;
double hit_threshold;
int win_width;
int win_stride_width;
int win_stride_height;
bool gamma_corr;
};
/** Describes aplication logic */
class App
{
public:
/** Initializes application */
App(const Settings& s);
/** Runs demo using OpenCV highgui module for GUI building */
void RunOpencvGui();
/** Processes user keybord input */
void HandleKey(char key);
void HogWorkBegin();
void HogWorkEnd();
double HogWorkFps() const;
void WorkBegin();
void WorkEnd();
double WorkFps() const;
const string GetPerformanceSummary() const;
private:
App operator=(App&);
Settings settings;
bool running;
bool use_gpu;
bool make_gray;
double scale;
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;
};
int main(int argc, char** argv)
{
try
{
if (argc {
cout /n"
] # says to interp. src as img or as video/n"
] # convert image to gray one or not/n"
] # do resize of the source image or not/n"
] # preprocessing image scale factor/n"
] # classifying plane dist. threshold (0.0 usually)/n"
] # HOG window scale factor/n"
] # max number of HOG window scales/n"
] # width of the window (48 or 64)/n"
] # distance by OX axis between neighbour wins/n"
] # distance by OY axis between neighbour wins/n"
] # merging similar rects constant/n"
] # do gamma correction or not/n";
return 1;
}
App app(Settings::Read(argc, argv));
app.RunOpencvGui();
}
catch (const Exception& e) { return cout catch (const exception& e) { return cout catch(...) { return cout return 0;
}
Settings::Settings()
{
src_is_video = false;
make_gray = false;
resize_src = true;
resize_src_scale = 1.5;
scale = 1.05;
nlevels = 13;
gr_threshold = 8;
hit_threshold = 1.4;
win_width = 48;
win_stride_width = 8;
win_stride_height = 8;
gamma_corr = true;
}
Settings Settings::Read(int argc, char** argv)
{
cout
Settings settings;
for (int i = 1; i {
string key = argv[i];
string val = argv[i + 1];
if (key == "-src") settings.src = val;
else if (key == "-src_is_video") settings.src_is_video = (val == "true");
else if (key == "-make_gray") settings.make_gray = (val == "true");
else if (key == "-resize_src") settings.resize_src = (val == "true");
else if (key == "-resize_src_scale") settings.resize_src_scale = atof(val.c_str());
else if (key == "-hit_threshold") settings.hit_threshold = atof(val.c_str());
else if (key == "-scale") settings.scale = atof(val.c_str());
else if (key == "-nlevels") settings.nlevels = atoi(val.c_str());
else if (key == "-win_width") settings.win_width = atoi(val.c_str());
else if (key == "-win_stride_width") settings.win_stride_width = atoi(val.c_str());
else if (key == "-win_stride_height") settings.win_stride_height = atoi(val.c_str());
else if (key == "-gr_threshold") settings.gr_threshold = atoi(val.c_str());
else if (key == "-gamma_corr") settings.gamma_corr = atoi(val.c_str()) != 0;
else throw runtime_error((string("Unknown key: ") + key));
}
cout return settings;
}
App::App(const Settings &s)
{
settings = s;
cout CPU/n"
use_gpu = true;
make_gray = settings.make_gray;
scale = settings.scale;
gr_threshold = settings.gr_threshold;
nlevels = settings.nlevels;
hit_threshold = settings.hit_threshold;
gamma_corr = settings.gamma_corr;
if (settings.win_width != 64 && settings.win_width != 48)
settings.win_width = 64;
cout cout cout cout cout cout cout cout }
void App::RunOpencvGui()
{
running = true;
Size win_size(settings.win_width, settings.win_width * 2); //(64, 128) or (48, 96)
Size win_stride(settings.win_stride_width, settings.win_stride_height);
vector
if (win_size == Size(64, 128))
detector = cv::gpu::HOGDescriptor::getPeopleDetector_64x128();
else
detector = cv::gpu::HOGDescriptor::getPeopleDetector_48x96();
// GPU's HOG classifier
cv::gpu::HOGDescriptor gpu_hog(win_size, Size(16, 16), Size(8, 8), Size(8, 8), 9,
cv::gpu::HOGDescriptor::DEFAULT_WIN_SIGMA, 0.2, gamma_corr,
cv::gpu::HOGDescriptor::DEFAULT_NLEVELS);
gpu_hog.setSVMDetector(detector);
// CPU's HOG classifier
cv::HOGDescriptor cpu_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);
cpu_hog.setSVMDetector(detector);
// Make endless cycle from video (if src is video)
while (running)
{
VideoCapture vc;
Mat frame;
if (settings.src_is_video)
{
vc.open(settings.src.c_str());
if (!vc.isOpened())
throw runtime_error(string("Can't open video file: " + settings.src));
vc >> frame;
}
else
{
frame = imread(settings.src);
if (frame.empty())
throw runtime_error(string("Can't open image file: " + settings.src));
}
Mat img_aux, img, img_to_show;
gpu::GpuMat gpu_img;
// Iterate over all frames
while (running && !frame.empty())
{
WorkBegin();
vector
// Change format of the image (input must be 8UC3)
if (make_gray)
cvtColor(frame, img_aux, CV_BGR2GRAY);
else if (use_gpu)
cvtColor(frame, img_aux, CV_BGR2BGRA);
else
img_aux = frame;
// Resize image
if (settings.resize_src)
resize(img_aux, img, Size(int(frame.cols * settings.resize_src_scale), int(frame.rows * settings.resize_src_scale)));
else
img = img_aux;
img_to_show = img;
gpu_hog.nlevels = nlevels;
cpu_hog.nlevels = nlevels;
// Perform HOG classification
HogWorkBegin();
if (use_gpu)
{
gpu_img = img;
gpu_hog.detectMultiScale(gpu_img, found, hit_threshold, win_stride, Size(0, 0), scale, gr_threshold);
}
else
cpu_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 {
Rect r = found[i];
rectangle(img_to_show, r.tl(), r.br(), CV_RGB(0, 255, 0), 3);
}
WorkEnd();
// Show results
putText(img_to_show, GetPerformanceSummary(), Point(5, 25), FONT_HERSHEY_SIMPLEX, 1.0, Scalar(0, 0, 255), 2);
imshow("opencv_gpu_hog", img_to_show);
HandleKey((char)waitKey(3));
if (settings.src_is_video)
{
vc >> frame;
}
}
}
}
void App::HandleKey(char key)
{
switch (key)
{
case 27:
running = false;
break;
case 'm':
case 'M':
use_gpu = !use_gpu;
cout break;
case 'g':
case 'G':
make_gray = !make_gray;
cout break;
case '1':
scale *= 1.05;
cout break;
case 'q':
case 'Q':
scale /= 1.05;
cout break;
case '2':
nlevels++;
cout break;
case 'w':
case 'W':
nlevels = max(nlevels - 1, 1);
cout break;
case '3':
gr_threshold++;
cout break;
case 'e':
case 'E':
gr_threshold = max(0, gr_threshold - 1);
cout break;
case '4':
hit_threshold+=0.25;
cout break;
case 'r':
case 'R':
hit_threshold = max(0.0, hit_threshold - 0.25);
cout break;
case 'c':
case 'C':
gamma_corr = !gamma_corr;
cout 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 double App::HogWorkFps() const { return hog_work_fps; }
inline void App::WorkBegin() { work_begin = getTickCount(); }
inline void App::WorkEnd()
{
int64 delta = getTickCount() - work_begin;
double freq = getTickFrequency();
work_fps = freq / delta;
}
inline double App::WorkFps() const { return work_fps; }
inline const string App::GetPerformanceSummary() const
{
stringstream ss;
ss setw(7) return ss.str();
}