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
379
380
381
382
383
384
385
386
387
388
389
390
391
392
393
394
395
396
397
398
/*****************************************************************************/
/* Latent SVM prediction API */
/*****************************************************************************/
#ifndef _LATENTSVM_H_
#define _LATENTSVM_H_
#include <stdio.h>
#include "_lsvm_types.h"
#include "_lsvm_error.h"
#include "_lsvm_routine.h"
//////////////////////////////////////////////////////////////
// Building feature pyramid
// (pyramid constructed both contrast and non-contrast image)
//////////////////////////////////////////////////////////////
/*
// Getting feature pyramid
//
// API
// int getFeaturePyramid(IplImage * image, const filterObject **all_F,
const int n_f,
const int lambda, const int k,
const int startX, const int startY,
const int W, const int H, featurePyramid **maps);
// INPUT
// image - image
// lambda - resize scale
// k - size of cells
// startX - X coordinate of the image rectangle to search
// startY - Y coordinate of the image rectangle to search
// W - width of the image rectangle to search
// H - height of the image rectangle to search
// OUTPUT
// maps - feature maps for all levels
// RESULT
// Error status
*/
int getFeaturePyramid(IplImage * image, CvLSVMFeaturePyramid **maps);
/*
// Getting feature map for the selected subimage
//
// API
// int getFeatureMaps(const IplImage * image, const int k, featureMap **map);
// INPUT
// image - selected subimage
// k - size of cells
// OUTPUT
// map - feature map
// RESULT
// Error status
*/
int getFeatureMaps(const IplImage * image, const int k, CvLSVMFeatureMap **map);
/*
// Feature map Normalization and Truncation
//
// API
// int normalizationAndTruncationFeatureMaps(featureMap *map, const float alfa);
// INPUT
// map - feature map
// alfa - truncation threshold
// OUTPUT
// map - truncated and normalized feature map
// RESULT
// Error status
*/
int normalizeAndTruncate(CvLSVMFeatureMap *map, const float alfa);
/*
// Feature map reduction
// In each cell we reduce dimension of the feature vector
// according to original paper special procedure
//
// API
// int PCAFeatureMaps(featureMap *map)
// INPUT
// map - feature map
// OUTPUT
// map - feature map
// RESULT
// Error status
*/
int PCAFeatureMaps(CvLSVMFeatureMap *map);
//////////////////////////////////////////////////////////////
// search object
//////////////////////////////////////////////////////////////
/*
// Transformation filter displacement from the block space
// to the space of pixels at the initial image
//
// API
// int convertPoints(int countLevel, int lambda,
int initialImageLevel,
CvPoint *points, int *levels,
CvPoint **partsDisplacement, int kPoints, int n,
int maxXBorder,
int maxYBorder);
// INPUT
// countLevel - the number of levels in the feature pyramid
// lambda - method parameter
// initialImageLevel - level of feature pyramid that contains feature map
for initial image
// points - the set of root filter positions (in the block space)
// levels - the set of levels
// partsDisplacement - displacement of part filters (in the block space)
// kPoints - number of root filter positions
// n - number of part filters
// maxXBorder - the largest root filter size (X-direction)
// maxYBorder - the largest root filter size (Y-direction)
// OUTPUT
// points - the set of root filter positions (in the space of pixels)
// partsDisplacement - displacement of part filters (in the space of pixels)
// RESULT
// Error status
*/
int convertPoints(int countLevel, int lambda,
int initialImageLevel,
CvPoint *points, int *levels,
CvPoint **partsDisplacement, int kPoints, int n,
int maxXBorder,
int maxYBorder);
/*
// Elimination boxes that are outside the image boudaries
//
// API
// int clippingBoxes(int width, int height,
CvPoint *points, int kPoints);
// INPUT
// width - image wediht
// height - image heigth
// points - a set of points (coordinates of top left or
bottom right corners)
// kPoints - points number
// OUTPUT
// points - updated points (if coordinates less than zero then
set zero coordinate, if coordinates more than image
size then set coordinates equal image size)
// RESULT
// Error status
*/
#ifdef __cplusplus
extern "C"
#endif
int clippingBoxes(int width, int height,
CvPoint *points, int kPoints);
/*
// Creation feature pyramid with nullable border
//
// API
// featurePyramid* createFeaturePyramidWithBorder(const IplImage *image,
int maxXBorder, int maxYBorder);
// INPUT
// image - initial image
// maxXBorder - the largest root filter size (X-direction)
// maxYBorder - the largest root filter size (Y-direction)
// OUTPUT
// RESULT
// Feature pyramid with nullable border
*/
#ifdef __cplusplus
extern "C"
#endif
CvLSVMFeaturePyramid* createFeaturePyramidWithBorder(IplImage *image,
int maxXBorder, int maxYBorder);
/*
// Computation of the root filter displacement and values of score function
//
// API
// int searchObject(const featurePyramid *H, const filterObject **all_F, int n,
float b,
int maxXBorder,
int maxYBorder,
CvPoint **points, int **levels, int *kPoints, float *score,
CvPoint ***partsDisplacement);
// INPUT
// H - feature pyramid
// all_F - the set of filters (the first element is root filter,
other elements - part filters)
// n - the number of part filters
// b - linear term of the score function
// maxXBorder - the largest root filter size (X-direction)
// maxYBorder - the largest root filter size (Y-direction)
// OUTPUT
// points - positions (x, y) of the upper-left corner
of root filter frame
// levels - levels that correspond to each position
// kPoints - number of positions
// score - value of the score function
// partsDisplacement - part filters displacement for each position
of the root filter
// RESULT
// Error status
*/
int searchObject(const CvLSVMFeaturePyramid *H, const CvLSVMFilterObject **all_F, int n,
float b,
int maxXBorder,
int maxYBorder,
CvPoint **points, int **levels, int *kPoints, float *score,
CvPoint ***partsDisplacement);
/*
// Computation of the root filter displacement and values of score function
//
// API
// int searchObjectThreshold(const featurePyramid *H,
const filterObject **all_F, int n,
float b,
int maxXBorder, int maxYBorder,
float scoreThreshold,
CvPoint **points, int **levels, int *kPoints,
float **score, CvPoint ***partsDisplacement);
// INPUT
// H - feature pyramid
// all_F - the set of filters (the first element is root filter,
other elements - part filters)
// n - the number of part filters
// b - linear term of the score function
// maxXBorder - the largest root filter size (X-direction)
// maxYBorder - the largest root filter size (Y-direction)
// scoreThreshold - score threshold
// OUTPUT
// points - positions (x, y) of the upper-left corner
of root filter frame
// levels - levels that correspond to each position
// kPoints - number of positions
// score - values of the score function
// partsDisplacement - part filters displacement for each position
of the root filter
// RESULT
// Error status
*/
int searchObjectThreshold(const CvLSVMFeaturePyramid *H,
const CvLSVMFilterObject **all_F, int n,
float b,
int maxXBorder, int maxYBorder,
float scoreThreshold,
CvPoint **points, int **levels, int *kPoints,
float **score, CvPoint ***partsDisplacement,
int numThreads CV_DEFAULT(-1));
/*
// Computation root filters displacement and values of score function
//
// API
// int searchObjectThresholdSomeComponents(const featurePyramid *H,
const filterObject **filters,
int kComponents, const int *kPartFilters,
const float *b, float scoreThreshold,
CvPoint **points, CvPoint **oppPoints,
float **score, int *kPoints);
// INPUT
// H - feature pyramid
// filters - filters (root filter then it's part filters, etc.)
// kComponents - root filters number
// kPartFilters - array of part filters number for each component
// b - array of linear terms
// scoreThreshold - score threshold
// OUTPUT
// points - root filters displacement (top left corners)
// oppPoints - root filters displacement (bottom right corners)
// score - array of score values
// kPoints - number of boxes
// RESULT
// Error status
*/
#ifdef __cplusplus
extern "C"
#endif
int searchObjectThresholdSomeComponents(const CvLSVMFeaturePyramid *H,
const CvLSVMFilterObject **filters,
int kComponents, const int *kPartFilters,
const float *b, float scoreThreshold,
CvPoint **points, CvPoint **oppPoints,
float **score, int *kPoints, int numThreads);
/*
// Compute opposite point for filter box
//
// API
// int getOppositePoint(CvPoint point,
int sizeX, int sizeY,
float step, int degree,
CvPoint *oppositePoint);
// INPUT
// point - coordinates of filter top left corner
(in the space of pixels)
// (sizeX, sizeY) - filter dimension in the block space
// step - scaling factor
// degree - degree of the scaling factor
// OUTPUT
// oppositePoint - coordinates of filter bottom corner
(in the space of pixels)
// RESULT
// Error status
*/
int getOppositePoint(CvPoint point,
int sizeX, int sizeY,
float step, int degree,
CvPoint *oppositePoint);
/*
// Drawing root filter boxes
//
// API
// int showRootFilterBoxes(const IplImage *image,
const filterObject *filter,
CvPoint *points, int *levels, int kPoints,
CvScalar color, int thickness,
int line_type, int shift);
// INPUT
// image - initial image
// filter - root filter object
// points - a set of points
// levels - levels of feature pyramid
// kPoints - number of points
// color - line color for each box
// thickness - line thickness
// line_type - line type
// shift - shift
// OUTPUT
// window contained initial image and filter boxes
// RESULT
// Error status
*/
int showRootFilterBoxes(IplImage *image,
const CvLSVMFilterObject *filter,
CvPoint *points, int *levels, int kPoints,
CvScalar color, int thickness,
int line_type, int shift);
/*
// Drawing part filter boxes
//
// API
// int showPartFilterBoxes(const IplImage *image,
const filterObject *filter,
CvPoint *points, int *levels, int kPoints,
CvScalar color, int thickness,
int line_type, int shift);
// INPUT
// image - initial image
// filters - a set of part filters
// n - number of part filters
// partsDisplacement - a set of points
// levels - levels of feature pyramid
// kPoints - number of foot filter positions
// color - line color for each box
// thickness - line thickness
// line_type - line type
// shift - shift
// OUTPUT
// window contained initial image and filter boxes
// RESULT
// Error status
*/
int showPartFilterBoxes(IplImage *image,
const CvLSVMFilterObject **filters,
int n, CvPoint **partsDisplacement,
int *levels, int kPoints,
CvScalar color, int thickness,
int line_type, int shift);
/*
// Drawing boxes
//
// API
// int showBoxes(const IplImage *img,
const CvPoint *points, const CvPoint *oppositePoints, int kPoints,
CvScalar color, int thickness, int line_type, int shift);
// INPUT
// img - initial image
// points - top left corner coordinates
// oppositePoints - right bottom corner coordinates
// kPoints - points number
// color - line color for each box
// thickness - line thickness
// line_type - line type
// shift - shift
// OUTPUT
// RESULT
// Error status
*/
int showBoxes(IplImage *img,
const CvPoint *points, const CvPoint *oppositePoints, int kPoints,
CvScalar color, int thickness, int line_type, int shift);
#endif