summaryrefslogtreecommitdiffhomepage
path: root/tracker-pt/point_extractor.cpp
blob: 655e1412559459faa8e7bddb48a86f6d78067bbb (plain)
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
/* 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()
{
}

const std::vector<cv::Vec2f>& PointExtractor::extract_points(cv::Mat& frame)
{
    const int W = frame.cols;
    const int H = frame.rows;
    
    if (frame_gray.rows != frame.rows || frame_gray.cols != frame.cols)
    {
        frame_gray = cv::Mat(frame.rows, frame.cols, CV_8U);
        frame_bin = cv::Mat(frame.rows, frame.cols, CV_8U);;
    }

    // convert to grayscale
    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::threshold(frame_gray, frame_bin, thres, 255, cv::THRESH_BINARY);
        cv::findContours(frame_bin, contours, CV_RETR_LIST, CV_CHAIN_APPROX_SIMPLE);
    }
    else
    {
        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.cols * hist.rows;
        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.);
        auto ptr = reinterpret_cast<const float*>(hist.ptr(0));
        for (int i = sz-1; i >= 0; i--)
        {
            cnt += ptr[i];
            if (cnt >= pixels_to_include)
            {
                val = i;
                break;
            }
        }
        val *= hist_c;
        val *= 240./256.;
        //qDebug() << "val" << val;

        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));
    }
    
    using b = const blob;
    std::sort(blobs.begin(), blobs.end(), [](b& b1, b& b2) {return b1.confid > b2.confid;});
    
    points.reserve(blobs.size());
    
    QMutexLocker l(&mtx);
    
    points.clear();
    
    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;
}