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/* Copyright (c) 2012 Patrick Ruoff
* Copyright (c) 2014-2015 Stanislaw Halik <sthalik@misaki.pl>
*
* Permission to use, copy, modify, and/or distribute this software for any
* purpose with or without fee is hereby granted, provided that the above
* copyright notice and this permission notice appear in all copies.
*/
#include "point_extractor.h"
#include <QDebug>
#ifdef DEBUG_EXTRACTION
# include "opentrack-compat/timer.hpp"
#endif
PointExtractor::PointExtractor()
{
}
std::vector<cv::Vec2f> PointExtractor::extract_points(cv::Mat& frame)
{
const int W = frame.cols;
const int H = frame.rows;
// convert to grayscale
cv::Mat frame_gray;
cv::cvtColor(frame, frame_gray, cv::COLOR_RGB2GRAY);
const double region_size_min = s.min_point_size;
const double region_size_max = s.max_point_size;
struct blob
{
double radius;
cv::Vec2d pos;
double confid;
bool taken;
double area;
blob(double radius, const cv::Vec2d& pos, double confid, double area) : radius(radius), pos(pos), confid(confid), taken(false), area(area)
{
//qDebug() << "radius" << radius << "pos" << pos[0] << pos[1] << "confid" << confid;
}
bool inside(const blob& other)
{
cv::Vec2d tmp = pos - other.pos;
return sqrt(tmp.dot(tmp)) < radius;
}
};
// mask for everything that passes the threshold (or: the upper threshold of the hysteresis)
std::vector<blob> blobs;
std::vector<std::vector<cv::Point>> contours;
const int thres = s.threshold;
if (!s.auto_threshold)
{
cv::Mat frame_bin;
cv::threshold(frame_gray, frame_bin, thres, 255, cv::THRESH_BINARY);
cv::findContours(frame_bin, contours, CV_RETR_LIST, CV_CHAIN_APPROX_SIMPLE);
}
else
{
cv::Mat hist;
constexpr int hist_c = 8;
cv::calcHist(std::vector<cv::Mat> { frame_gray },
std::vector<int> { 0 },
cv::Mat(),
hist,
std::vector<int> { 256/hist_c },
std::vector<float> { 0, 256/hist_c },
false);
const int sz = hist.rows*hist.cols;
int val = 0;
int cnt = 0;
constexpr int min_pixels = 250;
const auto pixels_to_include = std::max<int>(0, min_pixels * s.threshold/100.);
for (int i = sz-1; i >= 0; i--)
{
cnt += hist.at<float>(i);
if (cnt >= pixels_to_include)
{
val = i;
break;
}
}
val *= hist_c;
val *= 240./256.;
//qDebug() << "val" << val;
cv::Mat frame_bin;
cv::threshold(frame_gray, frame_bin, val, 255, CV_THRESH_BINARY);
cv::findContours(frame_bin, contours, CV_RETR_LIST, CV_CHAIN_APPROX_SIMPLE);
}
int cnt = 0;
for (auto& c : contours)
{
if (cnt++ > 30)
break;
const auto m = cv::moments(cv::Mat(c));
const double area = m.m00;
if (area == 0.)
continue;
const cv::Vec2d pos(m.m10 / m.m00, m.m01 / m.m00);
double radius;
// following based on OpenCV SimpleBlobDetector
{
std::vector<double> dists;
for (auto& k : c)
{
dists.push_back(cv::norm(pos - cv::Vec2d(k.x, k.y)));
}
std::sort(dists.begin(), dists.end());
radius = (dists[(dists.size() - 1)/2] + dists[dists.size()/2])/2;
}
if (radius < region_size_min || radius > region_size_max)
continue;
double confid = 1;
{
double denominator = std::sqrt(std::pow(2 * m.mu11, 2) + std::pow(m.mu20 - m.mu02, 2));
const double eps = 1e-2;
if (denominator > eps)
{
double cosmin = (m.mu20 - m.mu02) / denominator;
double sinmin = 2 * m.mu11 / denominator;
double cosmax = -cosmin;
double sinmax = -sinmin;
double imin = 0.5 * (m.mu20 + m.mu02) - 0.5 * (m.mu20 - m.mu02) * cosmin - m.mu11 * sinmin;
double imax = 0.5 * (m.mu20 + m.mu02) - 0.5 * (m.mu20 - m.mu02) * cosmax - m.mu11 * sinmax;
confid = imin / imax;
}
}
// end SimpleBlobDetector
{
char buf[64];
sprintf(buf, "%.2fpx %.2fc", radius, confid);
cv::putText(frame, buf, cv::Point(pos[0]+30, pos[1]+20), cv::FONT_HERSHEY_DUPLEX, 1, cv::Scalar(0, 0, 255), 1);
}
blobs.push_back(blob(radius, pos, confid, area));
}
// clear old points
points.clear();
using b = const blob;
std::sort(blobs.begin(), blobs.end(), [](b& b1, b& b2) {return b1.confid > b2.confid;});
for (auto& b : blobs)
{
cv::Vec2f p((b.pos[0] - W/2)/W, -(b.pos[1] - H/2)/W);
points.push_back(p);
}
return points;
}
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