-
Notifications
You must be signed in to change notification settings - Fork 486
/
line2Dup.h
336 lines (269 loc) · 10 KB
/
line2Dup.h
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
#ifndef CXXLINEMOD_H
#define CXXLINEMOD_H
#include <opencv2/core/core.hpp>
#include <opencv2/imgproc.hpp>
#include <opencv2/highgui/highgui.hpp>
#include <map>
#include "mipp.h" // for SIMD in different platforms
namespace line2Dup
{
struct Feature
{
int x;
int y;
int label;
float theta;
void read(const cv::FileNode &fn);
void write(cv::FileStorage &fs) const;
Feature() : x(0), y(0), label(0) {}
Feature(int x, int y, int label);
};
inline Feature::Feature(int _x, int _y, int _label) : x(_x), y(_y), label(_label) {}
struct Template
{
int width;
int height;
int tl_x;
int tl_y;
int pyramid_level;
std::vector<Feature> features;
void read(const cv::FileNode &fn);
void write(cv::FileStorage &fs) const;
};
class ColorGradientPyramid
{
public:
ColorGradientPyramid(const cv::Mat &src, const cv::Mat &mask,
float weak_threshold, size_t num_features,
float strong_threshold);
void quantize(cv::Mat &dst) const;
bool extractTemplate(Template &templ) const;
void pyrDown();
public:
void update();
/// Candidate feature with a score
struct Candidate
{
Candidate(int x, int y, int label, float score);
/// Sort candidates with high score to the front
bool operator<(const Candidate &rhs) const
{
return score > rhs.score;
}
Feature f;
float score;
};
cv::Mat src;
cv::Mat mask;
int pyramid_level;
cv::Mat angle;
cv::Mat magnitude;
cv::Mat angle_ori;
float weak_threshold;
size_t num_features;
float strong_threshold;
static bool selectScatteredFeatures(const std::vector<Candidate> &candidates,
std::vector<Feature> &features,
size_t num_features, float distance);
};
inline ColorGradientPyramid::Candidate::Candidate(int x, int y, int label, float _score) : f(x, y, label), score(_score) {}
class ColorGradient
{
public:
ColorGradient();
ColorGradient(float weak_threshold, size_t num_features, float strong_threshold);
std::string name() const;
float weak_threshold;
size_t num_features;
float strong_threshold;
void read(const cv::FileNode &fn);
void write(cv::FileStorage &fs) const;
cv::Ptr<ColorGradientPyramid> process(const cv::Mat src, const cv::Mat &mask = cv::Mat()) const
{
return cv::makePtr<ColorGradientPyramid>(src, mask, weak_threshold, num_features, strong_threshold);
}
};
struct Match
{
Match()
{
}
Match(int x, int y, float similarity, const std::string &class_id, int template_id);
/// Sort matches with high similarity to the front
bool operator<(const Match &rhs) const
{
// Secondarily sort on template_id for the sake of duplicate removal
if (similarity != rhs.similarity)
return similarity > rhs.similarity;
else
return template_id < rhs.template_id;
}
bool operator==(const Match &rhs) const
{
return x == rhs.x && y == rhs.y && similarity == rhs.similarity && class_id == rhs.class_id;
}
int x;
int y;
float similarity;
std::string class_id;
int template_id;
};
inline Match::Match(int _x, int _y, float _similarity, const std::string &_class_id, int _template_id)
: x(_x), y(_y), similarity(_similarity), class_id(_class_id), template_id(_template_id)
{
}
class Detector
{
public:
/**
* \brief Empty constructor, initialize with read().
*/
Detector();
Detector(std::vector<int> T);
Detector(int num_features, std::vector<int> T, float weak_thresh = 30.0f, float strong_thresh = 60.0f);
std::vector<Match> match(cv::Mat sources, float threshold,
const std::vector<std::string> &class_ids = std::vector<std::string>(),
const cv::Mat masks = cv::Mat()) const;
int addTemplate(const cv::Mat sources, const std::string &class_id,
const cv::Mat &object_mask, int num_features = 0);
int addTemplate_rotate(const std::string &class_id, int zero_id, float theta, cv::Point2f center);
const cv::Ptr<ColorGradient> &getModalities() const { return modality; }
int getT(int pyramid_level) const { return T_at_level[pyramid_level]; }
int pyramidLevels() const { return pyramid_levels; }
const std::vector<Template> &getTemplates(const std::string &class_id, int template_id) const;
int numTemplates() const;
int numTemplates(const std::string &class_id) const;
int numClasses() const { return static_cast<int>(class_templates.size()); }
std::vector<std::string> classIds() const;
void read(const cv::FileNode &fn);
void write(cv::FileStorage &fs) const;
std::string readClass(const cv::FileNode &fn, const std::string &class_id_override = "");
void writeClass(const std::string &class_id, cv::FileStorage &fs) const;
void readClasses(const std::vector<std::string> &class_ids,
const std::string &format = "templates_%s.yml.gz");
void writeClasses(const std::string &format = "templates_%s.yml.gz") const;
protected:
cv::Ptr<ColorGradient> modality;
int pyramid_levels;
std::vector<int> T_at_level;
typedef std::vector<Template> TemplatePyramid;
typedef std::map<std::string, std::vector<TemplatePyramid>> TemplatesMap;
TemplatesMap class_templates;
typedef std::vector<cv::Mat> LinearMemories;
// Indexed as [pyramid level][ColorGradient][quantized label]
typedef std::vector<std::vector<LinearMemories>> LinearMemoryPyramid;
void matchClass(const LinearMemoryPyramid &lm_pyramid,
const std::vector<cv::Size> &sizes,
float threshold, std::vector<Match> &matches,
const std::string &class_id,
const std::vector<TemplatePyramid> &template_pyramids) const;
};
} // namespace line2Dup
namespace shape_based_matching {
class shapeInfo_producer{
public:
cv::Mat src;
cv::Mat mask;
std::vector<float> angle_range;
std::vector<float> scale_range;
float angle_step = 15;
float scale_step = 0.5;
float eps = 0.00001f;
class Info{
public:
float angle;
float scale;
Info(float angle_, float scale_){
angle = angle_;
scale = scale_;
}
};
std::vector<Info> infos;
shapeInfo_producer(cv::Mat src, cv::Mat mask = cv::Mat()){
this->src = src;
if(mask.empty()){
// make sure we have masks
this->mask = cv::Mat(src.size(), CV_8UC1, {255});
}else{
this->mask = mask;
}
}
static cv::Mat transform(cv::Mat src, float angle, float scale){
cv::Mat dst;
cv::Point2f center(src.cols/2.0f, src.rows/2.0f);
cv::Mat rot_mat = cv::getRotationMatrix2D(center, angle, scale);
cv::warpAffine(src, dst, rot_mat, src.size());
return dst;
}
static void save_infos(std::vector<shapeInfo_producer::Info>& infos, std::string path = "infos.yaml"){
cv::FileStorage fs(path, cv::FileStorage::WRITE);
fs << "infos"
<< "[";
for (int i = 0; i < infos.size(); i++)
{
fs << "{";
fs << "angle" << infos[i].angle;
fs << "scale" << infos[i].scale;
fs << "}";
}
fs << "]";
}
static std::vector<Info> load_infos(std::string path = "info.yaml"){
cv::FileStorage fs(path, cv::FileStorage::READ);
std::vector<Info> infos;
cv::FileNode infos_fn = fs["infos"];
cv::FileNodeIterator it = infos_fn.begin(), it_end = infos_fn.end();
for (int i = 0; it != it_end; ++it, i++)
{
infos.emplace_back(float((*it)["angle"]), float((*it)["scale"]));
}
return infos;
}
void produce_infos(){
infos.clear();
assert(angle_range.size() <= 2);
assert(scale_range.size() <= 2);
assert(angle_step > eps*10);
assert(scale_step > eps*10);
// make sure range not empty
if(angle_range.size() == 0){
angle_range.push_back(0);
}
if(scale_range.size() == 0){
scale_range.push_back(1);
}
if(angle_range.size() == 1 && scale_range.size() == 1){
float angle = angle_range[0];
float scale = scale_range[0];
infos.emplace_back(angle, scale);
}else if(angle_range.size() == 1 && scale_range.size() == 2){
assert(scale_range[1] > scale_range[0]);
float angle = angle_range[0];
for(float scale = scale_range[0]; scale <= scale_range[1]+eps; scale += scale_step){
infos.emplace_back(angle, scale);
}
}else if(angle_range.size() == 2 && scale_range.size() == 1){
assert(angle_range[1] > angle_range[0]);
float scale = scale_range[0];
for(float angle = angle_range[0]; angle <= angle_range[1]+eps; angle += angle_step){
infos.emplace_back(angle, scale);
}
}else if(angle_range.size() == 2 && scale_range.size() == 2){
assert(scale_range[1] > scale_range[0]);
assert(angle_range[1] > angle_range[0]);
for(float scale = scale_range[0]; scale <= scale_range[1]+eps; scale += scale_step){
for(float angle = angle_range[0]; angle <= angle_range[1]+eps; angle += angle_step){
infos.emplace_back(angle, scale);
}
}
}
}
cv::Mat src_of(const Info& info){
return transform(src, info.angle, info.scale);
}
cv::Mat mask_of(const Info& info){
return (transform(mask, info.angle, info.scale) > 0);
}
};
}
#endif