summaryrefslogtreecommitdiffhomepage
path: root/tracker-pt/module/point_extractor.cpp
blob: 1208da4e3e7085b4aab0a332385a592ba06d9ddd (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
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
207
208
209
210
211
212
213
214
215
216
217
218
219
220
221
222
223
224
225
226
227
228
229
230
231
232
233
234
235
236
237
238
239
240
241
242
243
244
245
246
247
248
249
250
251
252
253
254
255
256
257
258
259
260
261
262
263
264
265
266
267
268
269
270
271
272
273
274
275
276
277
278
279
280
281
282
283
284
285
286
287
288
289
290
291
292
293
294
295
296
297
298
299
300
301
302
303
304
305
306
307
308
309
310
311
312
313
314
315
316
317
318
319
320
321
322
323
324
325
326
327
328
329
330
331
332
333
334
335
336
337
338
339
340
341
342
343
344
345
346
347
348
349
350
351
352
353
354
355
356
357
358
359
360
361
362
363
364
365
366
367
368
369
370
371
372
373
374
375
376
377
378
/* Copyright (c) 2012 Patrick Ruoff
 * Copyright (c) 2015-2017 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 "point_tracker.h"
#include "frame.hpp"

#include "cv/numeric.hpp"
#include "compat/math.hpp"

#include <opencv2/videoio.hpp>

#undef PREVIEW
//#define PREVIEW

#if defined PREVIEW
#   include <opencv2/highgui.hpp>
#endif

#include <cmath>
#include <algorithm>
#include <cinttypes>
#include <memory>

#include <QDebug>

using namespace types;
using namespace pt_module;

/*
http://en.wikipedia.org/wiki/Mean-shift
In this application the idea, is to eliminate any bias of the point estimate 
which is introduced by the rather arbitrary thresholded area. One must recognize
that the thresholded area can only move in one pixel increments since it is
binary. Thus, its center of mass might make "jumps" as pixels are added/removed
from the thresholded area.
With mean-shift, a moving "window" or kernel is multiplied with the gray-scale
image, and the COM is calculated of the result. This is iterated where the
kernel center is set the previously computed COM. Thus, peaks in the image intensity
distribution "pull" the kernel towards themselves. Eventually it stops moving, i.e.
then the computed COM coincides with the kernel center. We hope that the 
corresponding location is a good candidate for the extracted point.
The idea similar to the window scaling suggested in  Berglund et al. "Fast, bias-free 
algorithm for tracking single particles with variable size and shape." (2008).
*/
static cv::Vec2d MeanShiftIteration(const cv::Mat &frame_gray, const vec2 &current_center, f filter_width)
{
    // Most amazingly this function runs faster with doubles than with floats.
    const f s = 1.0 / filter_width;

    f m = 0;
    vec2 com { 0, 0  };
    for (int i = 0; i < frame_gray.rows; i++)
    {
        auto frame_ptr = (uint8_t const* __restrict)frame_gray.ptr(i);
        for (int j = 0; j < frame_gray.cols; j++)
        {
            f val = frame_ptr[j];
            val = val * val; // taking the square wights brighter parts of the image stronger.
            {
                f dx = (j - current_center[0])*s;
                f dy = (i - current_center[1])*s;
                f f = std::fmax(0, 1 - dx*dx - dy*dy);
                val *= f;
            }
            m += val;
            com[0] += j * val;
            com[1] += i * val;
        }
    }
    if (m > f(.1))
    {
        com *= f(1) / m;
        return com;
    }
    else
        return current_center;
}

PointExtractor::PointExtractor(const QString& module_name) : s(module_name)
{
    blobs.reserve(max_blobs);
}

void PointExtractor::ensure_channel_buffers(const cv::Mat& orig_frame)
{
    if (ch[0].rows != orig_frame.rows || ch[0].cols != orig_frame.cols)
        for (unsigned k = 0; k < 3; k++)
            ch[k] = cv::Mat1b(orig_frame.rows, orig_frame.cols);
}

void PointExtractor::ensure_buffers(const cv::Mat& frame)
{
    const int W = frame.cols, H = frame.rows;

    if (frame_gray.rows != W || frame_gray.cols != H)
    {
        frame_gray = cv::Mat1b(H, W);
        frame_bin = cv::Mat1b(H, W);
        frame_gray_unmasked = cv::Mat1b(H, W);
    }
}

void PointExtractor::extract_single_channel(const cv::Mat& orig_frame, int idx, cv::Mat& dest)
{
    ensure_channel_buffers(orig_frame);

    const int from_to[] = {
        idx, 0,
    };

    cv::mixChannels(&orig_frame, 1, &dest, 1, from_to, 1);
}

void PointExtractor::extract_channels(const cv::Mat& orig_frame, const int* order, int order_npairs)
{
    ensure_channel_buffers(orig_frame);

    cv::mixChannels(&orig_frame, 1, (cv::Mat*) ch, order_npairs, order, order_npairs);
}

void PointExtractor::color_to_grayscale(const cv::Mat& frame, cv::Mat1b& output)
{
    switch (s.blob_color)
    {
    case pt_color_blue_only:
    {
        extract_single_channel(frame, 0, output);
        break;
    }
    case pt_color_red_only:
    {
        extract_single_channel(frame, 2, output);
        break;
    }
    case pt_color_average:
    {
        const int W = frame.cols, H = frame.rows;
        const cv::Mat tmp = frame.reshape(1, W * H);
        cv::Mat output_ = output.reshape(1, W * H);
        cv::reduce(tmp, output_, 1, cv::REDUCE_AVG);
        break;
    }
    default:
        once_only(qDebug() << "wrong pt_color_type enum value" << int(s.blob_color));
        /*FALLTHROUGH*/
    case pt_color_natural:
        cv::cvtColor(frame, output, cv::COLOR_BGR2GRAY);
        break;
    }
}

void PointExtractor::threshold_image(const cv::Mat& frame_gray, cv::Mat1b& output)
{
    const int threshold_slider_value = s.threshold_slider.to<int>();

    if (!s.auto_threshold)
    {
        cv::threshold(frame_gray, output, threshold_slider_value, 255, cv::THRESH_BINARY);
    }
    else
    {
        const int hist_size = 256;
        const float ranges_[] = { 0, 256 };
        float const* ranges = (const float*) ranges_;

        cv::calcHist(&frame_gray,
                     1,
                     nullptr,
                     cv::noArray(),
                     hist,
                     1,
                     (int const*) &hist_size,
                     &ranges);

        const f radius = (f) threshold_radius_value(frame_gray.cols, frame_gray.rows, threshold_slider_value);

        float const* const __restrict ptr = hist.ptr<float>(0);
        const unsigned area = uround(3 * M_PI * radius*radius);
        const unsigned sz = unsigned(hist.cols * hist.rows);
        unsigned thres = 32;
        for (unsigned i = sz-1, cnt = 0; i > 32; i--)
        {
            cnt += ptr[i];
            if (cnt >= area)
                break;
            thres = i;
        }

        cv::threshold(frame_gray, output, thres, 255, cv::THRESH_BINARY);
    }
}

void PointExtractor::extract_points(const pt_frame& frame_, pt_preview& preview_frame_, std::vector<vec2>& points)
{
    const cv::Mat& frame = frame_.as_const<Frame>()->mat;
    cv::Mat& preview_frame = *preview_frame_.as<Preview>();

    ensure_buffers(frame);
    color_to_grayscale(frame, frame_gray_unmasked);

#if defined PREVIEW
    cv::imshow("capture", frame_gray);
    cv::waitKey(1);
#endif

    threshold_image(frame_gray_unmasked, frame_bin);
    frame_gray_unmasked.copyTo(frame_gray, frame_bin);

    const f region_size_min = s.min_point_size;
    const f region_size_max = s.max_point_size;

    unsigned idx = 0;

    blobs.clear();

    for (int y=0; y < frame_bin.rows; y++)
    {
        const unsigned char* ptr_bin = frame_bin.ptr(y);
        for (int x=0; x < frame_bin.cols; x++)
        {
            if (ptr_bin[x] != 255)
                continue;
            idx = blobs.size() + 1;

            cv::Rect rect;
            cv::floodFill(frame_bin,
                          cv::Point(x,y),
                          cv::Scalar(idx),
                          &rect,
                          cv::Scalar(0),
                          cv::Scalar(0),
                          4 | cv::FLOODFILL_FIXED_RANGE);

            unsigned cnt = 0;
            unsigned norm = 0;

            const int ymax = rect.y+rect.height,
                      xmax = rect.x+rect.width;

            for (int i=rect.y; i < ymax; i++)
            {
                unsigned char const* const __restrict ptr_blobs = frame_bin.ptr(i);
                unsigned char const* const __restrict ptr_gray = frame_gray.ptr(i);
                for (int j=rect.x; j < xmax; j++)
                {
                    if (ptr_blobs[j] != idx)
                        continue;

                    //ptr_blobs[j] = 0;
                    norm += ptr_gray[j];
                    cnt++;
                }
            }

            const double radius = std::sqrt(cnt / M_PI);
            if (radius > region_size_max || radius < region_size_min)
                continue;

            blobs.emplace_back(radius,
                               vec2(rect.width/2., rect.height/2.),
                               std::pow(f(norm), f(1.1))/cnt,
                               rect);

            if (idx >= max_blobs)
                goto end;

            // XXX we could go to the next scanline unless the points are really small.
            // i'd expect each point being present on at least one unique scanline
            // but it turns out some people are using 2px points -sh 20180110
#if BROKEN && 0
            break;
#endif
        }
    }
end:

    const int W = frame_gray.cols;
    const int H = frame_gray.rows;

    const unsigned sz = blobs.size();

    std::sort(blobs.begin(), blobs.end(), [](const blob& b1, const blob& b2) { return b2.brightness < b1.brightness; });

    for (idx = 0; idx < sz; ++idx)
    {
        blob &b = blobs[idx];
        cv::Rect rect = b.rect;

        rect.x -= rect.width / 2;
        rect.y -= rect.height / 2;
        rect.width *= 2;
        rect.height *= 2;
        rect &= cv::Rect(0, 0, W, H);  // crop at frame boundaries

        cv::Mat frame_roi = frame_gray(rect);

        // smaller values mean more changes. 1 makes too many changes while 1.5 makes about .1
        static constexpr f radius_c = f(1.75);

        const f kernel_radius = b.radius * radius_c;
        vec2 pos(rect.width/2., rect.height/2.); // position relative to ROI.

        for (int iter = 0; iter < 10; ++iter)
        {
            vec2 com_new = MeanShiftIteration(frame_roi, pos, kernel_radius);
            vec2 delta = com_new - pos;
            pos = com_new;
            if (delta.dot(delta) < 1e-2)
                break;
        }

        b.pos[0] = pos[0] + rect.x;
        b.pos[1] = pos[1] + rect.y;
    }

    for (unsigned k = 0; k < blobs.size(); k++)
    {
        blob& b = blobs[k];

        const f dpi = preview_frame.cols / f(320);
        const f offx = 10 * dpi, offy = 7.5 * dpi;

        const f cx = preview_frame.cols / f(frame.cols),
                cy = preview_frame.rows / f(frame.rows),
                c_ = (cx+cy)/2;

        static constexpr unsigned fract_bits = 16;
        static constexpr double c_fract(1 << fract_bits);

        cv::Point p(iround(b.pos[0] * cx * c_fract), iround(b.pos[1] * cy * c_fract));

        auto circle_color = k >= PointModel::N_POINTS
                            ? cv::Scalar(192, 192, 192)
                            : cv::Scalar(255, 255, 0);

        const f overlay_size = dpi > 1.5 ? 2 : 1;

        cv::circle(preview_frame, p, iround((b.radius + 3.3) * c_ * c_fract), circle_color, overlay_size, cv::LINE_AA, fract_bits);

        char buf[16];
        buf[sizeof(buf)-1] = '\0';
        std::snprintf(buf, sizeof(buf) - 1, "%.2fpx", b.radius);

        auto text_color = k >= PointModel::N_POINTS
                          ? cv::Scalar(160, 160, 160)
                          : cv::Scalar(0, 0, 255);

        cv::Point pos(iround(b.pos[0]*cx+offx), iround(b.pos[1]*cy+offy));
        cv::putText(preview_frame, buf, pos,
                    cv::FONT_HERSHEY_PLAIN, overlay_size, text_color,
                    1);
    }

    // End of mean shift code. At this point, blob positions are updated with hopefully less noisy less biased values.
    points.reserve(max_blobs);
    points.clear();

    for (const auto& b : blobs)
    {
        // note: H/W is equal to fx/fy

        vec2 p;
        std::tie(p[0], p[1]) = to_screen_pos(b.pos[0], b.pos[1], W, H);
        points.push_back(p);
    }
}

blob::blob(f radius, const vec2& pos, f brightness, const cv::Rect& rect) :
    radius(radius), brightness(brightness), pos(pos), rect(rect)
{
    //qDebug() << "radius" << radius << "pos" << pos[0] << pos[1];
}