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added different win_stride values feature into gpu HOG, refactored gpu HOG sample

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This commit is contained in:
Alexey Spizhevoy
2010-11-17 14:11:30 +00:00
parent 27542529a5
commit 2d01558479
3 changed files with 48 additions and 31 deletions
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34
samples/gpu/gpu_hog.cpp
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@@ -31,6 +31,8 @@ public:
int gr_threshold;
double hit_threshold;
int win_width;
int win_stride_width;
int win_stride_height;
};
@@ -94,6 +96,8 @@ int main(int argc, char** argv)
<< " [-scale <double>] # HOG window scale factor\n"
<< " [-nlevels <int>] # max number of HOG window scales\n"
<< " [-win_width <int>] # width of the window (48 or 64)\n"
<< " [-win_stride_width <int>] # distance by OX axis between neighbour wins\n"
<< " [-win_stride_height <int>] # distance by OY axis between neighbour wins\n"
<< " [-gr_threshold <int>] # merging similar rects constant\n";
return 1;
}
@@ -118,6 +122,8 @@ Settings::Settings()
gr_threshold = 8;
hit_threshold = 1.4;
win_width = 48;
win_stride_width = 8;
win_stride_height = 8;
}
@@ -139,6 +145,8 @@ Settings Settings::Read(int argc, char** argv)
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 throw exception((string("Unknown key: ") + key).c_str());
}
@@ -152,13 +160,13 @@ App::App(const Settings &s)
{
settings = s;
cout << "\nControls:\n"
<< "ESC - exit\n"
<< "m - change mode GPU <-> CPU\n"
<< "g - convert image to gray or not\n"
<< "1/q - increase/decrease HOG scale\n"
<< "2/w - increase/decrease levels count\n"
<< "3/e - increase/decrease HOG group threshold\n"
<< "4/r - increase/decrease hit threshold\n"
<< "\tESC - exit\n"
<< "\tm - change mode GPU <-> CPU\n"
<< "\tg - convert image to gray or not\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;
use_gpu = true;
@@ -171,10 +179,11 @@ App::App(const Settings &s)
if (settings.win_width != 64 && settings.win_width != 48)
settings.win_width = 64;
cout << endl << "Scale: " << scale << endl;
cout << "Scale: " << scale << endl;
cout << "Group threshold: " << gr_threshold << endl;
cout << "Levels number: " << nlevels << endl;
cout << "Win width: " << settings.win_width << endl;
cout << "Win stride: (" << settings.win_stride_width << ", " << settings.win_stride_height << ")\n";
cout << "Hit threshold: " << hit_threshold << endl;
cout << endl;
}
@@ -185,10 +194,11 @@ 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<float> detector;
if (win_size == Size(64,128))
if (win_size == Size(64, 128))
detector = cv::gpu::HOGDescriptor::getPeopleDetector_64x128();
else
detector = cv::gpu::HOGDescriptor::getPeopleDetector_48x96();
@@ -198,7 +208,7 @@ void App::RunOpencvGui()
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, true, HOGDescriptor::DEFAULT_NLEVELS);
cv::HOGDescriptor cpu_hog(win_size, Size(16, 16), Size(8, 8), Size(8, 8), 9, 1, -1, HOGDescriptor::L2Hys, 0.2, true, HOGDescriptor::DEFAULT_NLEVELS);
cpu_hog.setSVMDetector(detector);
// Make endless cycle from video (if src is video)
@@ -250,10 +260,10 @@ void App::RunOpencvGui()
if (use_gpu)
{
gpu_img = img;
gpu_hog.detectMultiScale(gpu_img, found, hit_threshold, Size(8, 8), Size(0, 0), scale, gr_threshold);
gpu_hog.detectMultiScale(gpu_img, found, hit_threshold, win_stride, Size(0, 0), scale, gr_threshold);
}
else
cpu_hog.detectMultiScale(img, found, hit_threshold, Size(8, 8), Size(0, 0), scale, gr_threshold);
cpu_hog.detectMultiScale(img, found, hit_threshold, win_stride, Size(0, 0), scale, gr_threshold);
HogWorkEnd();
// Draw positive classified windows