inline
void place_cell_generator::setFiringRate()
{
// rate is in Hz, dt in ms, so we have to convert from s to ms
double sim_dt = Time::get_resolution().get_ms();
poisson_dev_.set_lambda(sim_dt * P_.rate * 1e-3 * gaussianFunction());
}
std::vector<BoundingBox> PedestrianDetector::detectWCandidates(std::vector<BoundingBox> &candidates,
const std::vector<cv::Mat> &pyramid_images,
const std::vector<float> &pyramid_scales,
const float hit_threshold) {
std::vector<BoundingBox> detections;
// for all the levels of the pyramid ...
for (int l=0; l<pyramid_images.size(); ++l) {
// ... search for candidates at this level and put them on search locations.
std::cout << "LEVEL: " << l;
std::cout << " pyramid_scales[l]: " << pyramid_scales[l] << std::endl;
// TODO: obviously I could order them by scale and reduce the complexity of this.
std::vector<cv::Point> search_locations;
for (int i=0; i<candidates.size(); ++i) {
if (l == candidates[i].pyramid_level) {
// see if the bounding box of at this level will correspond to a
// good approximation of the bounding box in the candidate
float det_size_scale = det_size.height/pyramid_scales[l];
// std::cout << "level in pyramid " << l << std::endl;
// std::cout << "det at this scale representation height: " << det_size_scale << std::endl;
// std::cout << "bb height " << candidates[i].bb.height << std::endl;
// add candidate to search_location (top-left point)
cv::Point pt = candidates[i].bb.tl()*pyramid_scales[l];
search_locations.push_back(pt);
}
}
std::cout << "search_locations size" << search_locations.size() << std::endl;
if (search_locations.size() > 0) {
// detect in this level.
std::vector<cv::Point> found;
std::vector<double> weights;
hog.detect(pyramid_images[l], found, weights, hit_threshold, cv::Size(), cv::Size(), search_locations);
// std::cout << std::endl << "Search: ";
// for (int i=0; i<search_locations.size(); ++i) {
// std::cout << search_locations[i] << " ";
// }
// std::cout << std::endl << "Found: ";
cv::Size det_size_l(det_size); // size of detector in this level
det_size_l.width /= pyramid_scales[l];
det_size_l.height /= pyramid_scales[l];
for (int i = 0; i < found.size(); ++i) {
BoundingBox bb;
// find candidate to compute the score using gaussian weighthing
for (int j=0; j<candidates.size(); ++j) {
if (found[i] == candidates[j].bb.tl()*pyramid_scales[l]) {
// add weight for non max suppression.
double new_score = weights[i]*gaussianFunction(1.800, 0.300, candidates[j].world_height);
bb.score = new_score;
//std::cout << "det " << i << "score "<< new_score << std::endl;
}
}
// bb.score = weights[i];
cv::Point f = found[i];
f.x /= pyramid_scales[l];
f.y /= pyramid_scales[l];
bb.bb = cv::Rect(f, det_size_l);
detections.push_back(bb);
}
}
}
return detections;
}