std::vector<cv::Rect> hogDetection(cv::Mat sequence, cv::HOGDescriptor hog)
{
std::vector<cv::Rect> found;
hog.detectMultiScale(sequence, found, 0, cv::Size(8,8), cv::Size(32,32), 1.05, 2);
return found;
}
int process_image(cv::Mat & input_img) {
std::vector<cv::Rect> found_rectangles;
hog.detectMultiScale(input_img, found_rectangles);
for (unsigned int rec_idx = 0; rec_idx < found_rectangles.size(); ++rec_idx)
cv::rectangle(input_img, found_rectangles[rec_idx], CV_RGB(255,0,0), 2);
cv::imwrite("input_img.png", input_img);
cv::imshow("input_img", input_img);
} // end process_image()
void peopleDetectApp::update()
{
if( getElapsedFrames() % 30 == 0 )
{
if(stillSurface) {
//cv::Mat newFrame = toOcv( Channel( capture.getSurface() )); // capture the frame
cv::Mat newFrame = toOcv( Channel(stillSurface));
vector<cv::Rect> found, found_filtered;
// run the detector with default parameters. to get a higher hit-rate
// (and more false alarms, respectively), decrease the hitThreshold and
// groupThreshold (set groupThreshold to 0 to turn off the grouping completely).
//hog.detectMultiScale(newFrame, foundLocations, 0, cv::Size(8,8), cv::Size(32,32), 1.05, 2);
hog.detectMultiScale(newFrame, foundLocations, 0, cv::Size(8,8), cv::Size(32,32), 1.05, 2);
int i,j;
for( i = 0; i < foundLocations.size(); i++ )
{
cv::Rect r = foundLocations[i];
for( j = 0; j < foundLocations.size(); j++ ) {
if( j != i && (r & foundLocations[j]) == r)
break;
if( j == foundLocations.size() )
found_filtered.push_back(r);
}
}
console() << " found # " << foundLocations.size() << " filtered to " << found_filtered.size() << endl;
ciPeople.clear();
for( i = 0; i < foundLocations.size(); i++ ) {
cv::Rect r = foundLocations[i];
// the HOG detector returns slightly larger rectangles than the real objects.
// so we slightly shrink the rectangles to get a nicer output.
r.x += cvRound(r.width*0.1);
r.width = cvRound(r.width*0.8);
r.y += cvRound(r.height*0.07);
r.height = cvRound(r.height*0.8);
ciPeople.push_back(fromOcv(r));
}
}
}
}
void detect(shared_data& in_data)
{
std::vector<cv::Rect> temp_boxes;
for (auto i: in_data.im_data.im_ROI) {
temp_resize.create(in_data.im_data.image(i).rows*opt.scale, in_data.im_data.image(i).cols*opt.scale, CV_64FC3);
cv::resize(in_data.im_data.image(i), temp_resize, temp_resize.size());
//these magic numbers are from opencv
if (temp_resize.rows > 128 && temp_resize.cols > 64) {
temp_boxes.clear();
hog.detectMultiScale(temp_resize,
temp_boxes,
0,
cv::Size(8, 8),
cv::Size(0, 0),
1.05);
for (auto j: temp_boxes) {
i.x -= center_x;
i.y -= center_y;
i.x = opt.scale*i.x+scenter_x;
i.y = opt.scale*i.y+scenter_y;
j.x += i.x;
j.y += i.y;
j.x -= scenter_x;
j.y -= scenter_y;
j.x = 1.0/opt.scale*j.x+center_x;
j.y = 1.0/opt.scale*j.y+center_y;
j.height/=opt.scale;
j.width/=opt.scale;
box_safe(j, 0, 0, in_data.im_data.image.cols-1, in_data.im_data.image.rows-1);
shared_data::bbox temp;
temp = j;
temp.type_label = TYPE_PERSON;
in_data.im_boxes.push_back(temp);
}
}
}
}
void ocvOpticalFlowApp::findPeople(cv::Mat curImg)
{
cv::Mat monoImg;
cv::cvtColor(curImg, monoImg, CV_BGR2GRAY);
hog.detectMultiScale(monoImg, mFoundPeople);
}