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
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
206
|
/* 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
//#define DEBUG_SUM_OF_SQUARES
#ifdef DEBUG_SUM_OF_SQUARES
# define SUM_OF_SQUARES_WINNAME "sum-of-squares-debug"
# include <opencv2/highgui.hpp>
#endif
PointExtractor::PointExtractor()
{
#ifdef DEBUG_SUM_OF_SQUARES
cv::namedWindow(SUM_OF_SQUARES_WINNAME);
#endif
blobs.reserve(max_blobs);
points.reserve(max_blobs);
}
PointExtractor::~PointExtractor()
{
#ifdef DEBUG_SUM_OF_SQUARES
cv::destroyWindow(SUM_OF_SQUARES_WINNAME);
#endif
}
void PointExtractor::gray_square_diff(const cv::Mat &frame, cv::Mat &frame_gray)
{
const unsigned nchans = frame.channels();
const int rows = frame.rows;
const int cols = frame.cols;
cv::cvtColor(frame, frame_gray, cv::COLOR_RGB2GRAY);
if (nchans == 1 || !s.auto_threshold)
return;
cv::split(frame, gray_split_channels);
if (nchans > gray_absdiff_channels.size())
gray_absdiff_channels.resize(nchans);
for (unsigned i = 0; i < nchans; i++)
cv::absdiff(frame_gray, gray_split_channels[i], gray_absdiff_channels[i]);
if (frame_gray_tmp.rows != rows || frame_gray_tmp.cols != cols)
frame_gray_tmp = cv::Mat(rows, cols, CV_32FC1);
frame_gray.convertTo(frame_gray_tmp, CV_32FC1);
constexpr float scale = .9;
if (float_absdiff_channel.cols != cols || float_absdiff_channel.rows != rows)
float_absdiff_channel = cv::Mat(rows, cols, CV_32FC1);
for (unsigned i = 0; i < nchans; i++)
{
gray_absdiff_channels[i].convertTo(float_absdiff_channel, CV_32FC1);
frame_gray_tmp -= float_absdiff_channel.mul(float_absdiff_channel, scale);
}
frame_gray_tmp = cv::max(0., frame_gray_tmp);
frame_gray_tmp.convertTo(frame_gray, CV_8UC1);
#ifdef DEBUG_SUM_OF_SQUARES
cv::imshow(SUM_OF_SQUARES_WINNAME, frame_gray);
cv::waitKey(1);
#endif
}
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
gray_square_diff(frame, frame_gray);
const double region_size_min = s.min_point_size;
const double region_size_max = s.max_point_size;
const int thres = s.threshold;
contours.clear();
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);
}
blobs.clear();
for (auto& c : contours)
{
const auto m = cv::moments(cv::Mat(c));
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));
if (blobs.size() == max_blobs)
break;
}
using b = const blob;
std::sort(blobs.begin(), blobs.end(), [](b& b1, b& b2) {return b1.confid > b2.confid;});
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;
}
|