LBPHFaceRecognizer.h 13 KB

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  1. //
  2. // This file is auto-generated. Please don't modify it!
  3. //
  4. #pragma once
  5. #ifdef __cplusplus
  6. //#import "opencv.hpp"
  7. #import "opencv2/face.hpp"
  8. #import "opencv2/face/facerec.hpp"
  9. #else
  10. #define CV_EXPORTS
  11. #endif
  12. #import <Foundation/Foundation.h>
  13. #import "FaceRecognizer.h"
  14. @class Mat;
  15. NS_ASSUME_NONNULL_BEGIN
  16. // C++: class LBPHFaceRecognizer
  17. /**
  18. * The LBPHFaceRecognizer module
  19. *
  20. * Member of `Face`
  21. */
  22. CV_EXPORTS @interface LBPHFaceRecognizer : FaceRecognizer
  23. #ifdef __cplusplus
  24. @property(readonly)cv::Ptr<cv::face::LBPHFaceRecognizer> nativePtrLBPHFaceRecognizer;
  25. #endif
  26. #ifdef __cplusplus
  27. - (instancetype)initWithNativePtr:(cv::Ptr<cv::face::LBPHFaceRecognizer>)nativePtr;
  28. + (instancetype)fromNative:(cv::Ptr<cv::face::LBPHFaceRecognizer>)nativePtr;
  29. #endif
  30. #pragma mark - Methods
  31. //
  32. // int cv::face::LBPHFaceRecognizer::getGridX()
  33. //
  34. /**
  35. * @see `-setGridX:`
  36. */
  37. - (int)getGridX NS_SWIFT_NAME(getGridX());
  38. //
  39. // void cv::face::LBPHFaceRecognizer::setGridX(int val)
  40. //
  41. /**
  42. * getGridX @see `-getGridX:`
  43. */
  44. - (void)setGridX:(int)val NS_SWIFT_NAME(setGridX(val:));
  45. //
  46. // int cv::face::LBPHFaceRecognizer::getGridY()
  47. //
  48. /**
  49. * @see `-setGridY:`
  50. */
  51. - (int)getGridY NS_SWIFT_NAME(getGridY());
  52. //
  53. // void cv::face::LBPHFaceRecognizer::setGridY(int val)
  54. //
  55. /**
  56. * getGridY @see `-getGridY:`
  57. */
  58. - (void)setGridY:(int)val NS_SWIFT_NAME(setGridY(val:));
  59. //
  60. // int cv::face::LBPHFaceRecognizer::getRadius()
  61. //
  62. /**
  63. * @see `-setRadius:`
  64. */
  65. - (int)getRadius NS_SWIFT_NAME(getRadius());
  66. //
  67. // void cv::face::LBPHFaceRecognizer::setRadius(int val)
  68. //
  69. /**
  70. * getRadius @see `-getRadius:`
  71. */
  72. - (void)setRadius:(int)val NS_SWIFT_NAME(setRadius(val:));
  73. //
  74. // int cv::face::LBPHFaceRecognizer::getNeighbors()
  75. //
  76. /**
  77. * @see `-setNeighbors:`
  78. */
  79. - (int)getNeighbors NS_SWIFT_NAME(getNeighbors());
  80. //
  81. // void cv::face::LBPHFaceRecognizer::setNeighbors(int val)
  82. //
  83. /**
  84. * getNeighbors @see `-getNeighbors:`
  85. */
  86. - (void)setNeighbors:(int)val NS_SWIFT_NAME(setNeighbors(val:));
  87. //
  88. // double cv::face::LBPHFaceRecognizer::getThreshold()
  89. //
  90. /**
  91. * @see `-setThreshold:`
  92. */
  93. - (double)getThreshold NS_SWIFT_NAME(getThreshold());
  94. //
  95. // void cv::face::LBPHFaceRecognizer::setThreshold(double val)
  96. //
  97. /**
  98. * getThreshold @see `-getThreshold:`
  99. */
  100. - (void)setThreshold:(double)val NS_SWIFT_NAME(setThreshold(val:));
  101. //
  102. // vector_Mat cv::face::LBPHFaceRecognizer::getHistograms()
  103. //
  104. - (NSArray<Mat*>*)getHistograms NS_SWIFT_NAME(getHistograms());
  105. //
  106. // Mat cv::face::LBPHFaceRecognizer::getLabels()
  107. //
  108. - (Mat*)getLabels NS_SWIFT_NAME(getLabels());
  109. //
  110. // static Ptr_LBPHFaceRecognizer cv::face::LBPHFaceRecognizer::create(int radius = 1, int neighbors = 8, int grid_x = 8, int grid_y = 8, double threshold = DBL_MAX)
  111. //
  112. /**
  113. * @param radius The radius used for building the Circular Local Binary Pattern. The greater the
  114. * radius, the smoother the image but more spatial information you can get.
  115. * @param neighbors The number of sample points to build a Circular Local Binary Pattern from. An
  116. * appropriate value is to use `8` sample points. Keep in mind: the more sample points you include,
  117. * the higher the computational cost.
  118. * @param grid_x The number of cells in the horizontal direction, 8 is a common value used in
  119. * publications. The more cells, the finer the grid, the higher the dimensionality of the resulting
  120. * feature vector.
  121. * @param grid_y The number of cells in the vertical direction, 8 is a common value used in
  122. * publications. The more cells, the finer the grid, the higher the dimensionality of the resulting
  123. * feature vector.
  124. * @param threshold The threshold applied in the prediction. If the distance to the nearest neighbor
  125. * is larger than the threshold, this method returns -1.
  126. *
  127. * ### Notes:
  128. *
  129. * - The Circular Local Binary Patterns (used in training and prediction) expect the data given as
  130. * grayscale images, use cvtColor to convert between the color spaces.
  131. * - This model supports updating.
  132. *
  133. * ### Model internal data:
  134. *
  135. * - radius see LBPHFaceRecognizer::create.
  136. * - neighbors see LBPHFaceRecognizer::create.
  137. * - grid_x see LLBPHFaceRecognizer::create.
  138. * - grid_y see LBPHFaceRecognizer::create.
  139. * - threshold see LBPHFaceRecognizer::create.
  140. * - histograms Local Binary Patterns Histograms calculated from the given training data (empty if
  141. * none was given).
  142. * - labels Labels corresponding to the calculated Local Binary Patterns Histograms.
  143. */
  144. + (LBPHFaceRecognizer*)create:(int)radius neighbors:(int)neighbors grid_x:(int)grid_x grid_y:(int)grid_y threshold:(double)threshold NS_SWIFT_NAME(create(radius:neighbors:grid_x:grid_y:threshold:));
  145. /**
  146. * @param radius The radius used for building the Circular Local Binary Pattern. The greater the
  147. * radius, the smoother the image but more spatial information you can get.
  148. * @param neighbors The number of sample points to build a Circular Local Binary Pattern from. An
  149. * appropriate value is to use `8` sample points. Keep in mind: the more sample points you include,
  150. * the higher the computational cost.
  151. * @param grid_x The number of cells in the horizontal direction, 8 is a common value used in
  152. * publications. The more cells, the finer the grid, the higher the dimensionality of the resulting
  153. * feature vector.
  154. * @param grid_y The number of cells in the vertical direction, 8 is a common value used in
  155. * publications. The more cells, the finer the grid, the higher the dimensionality of the resulting
  156. * feature vector.
  157. * is larger than the threshold, this method returns -1.
  158. *
  159. * ### Notes:
  160. *
  161. * - The Circular Local Binary Patterns (used in training and prediction) expect the data given as
  162. * grayscale images, use cvtColor to convert between the color spaces.
  163. * - This model supports updating.
  164. *
  165. * ### Model internal data:
  166. *
  167. * - radius see LBPHFaceRecognizer::create.
  168. * - neighbors see LBPHFaceRecognizer::create.
  169. * - grid_x see LLBPHFaceRecognizer::create.
  170. * - grid_y see LBPHFaceRecognizer::create.
  171. * - threshold see LBPHFaceRecognizer::create.
  172. * - histograms Local Binary Patterns Histograms calculated from the given training data (empty if
  173. * none was given).
  174. * - labels Labels corresponding to the calculated Local Binary Patterns Histograms.
  175. */
  176. + (LBPHFaceRecognizer*)create:(int)radius neighbors:(int)neighbors grid_x:(int)grid_x grid_y:(int)grid_y NS_SWIFT_NAME(create(radius:neighbors:grid_x:grid_y:));
  177. /**
  178. * @param radius The radius used for building the Circular Local Binary Pattern. The greater the
  179. * radius, the smoother the image but more spatial information you can get.
  180. * @param neighbors The number of sample points to build a Circular Local Binary Pattern from. An
  181. * appropriate value is to use `8` sample points. Keep in mind: the more sample points you include,
  182. * the higher the computational cost.
  183. * @param grid_x The number of cells in the horizontal direction, 8 is a common value used in
  184. * publications. The more cells, the finer the grid, the higher the dimensionality of the resulting
  185. * feature vector.
  186. * publications. The more cells, the finer the grid, the higher the dimensionality of the resulting
  187. * feature vector.
  188. * is larger than the threshold, this method returns -1.
  189. *
  190. * ### Notes:
  191. *
  192. * - The Circular Local Binary Patterns (used in training and prediction) expect the data given as
  193. * grayscale images, use cvtColor to convert between the color spaces.
  194. * - This model supports updating.
  195. *
  196. * ### Model internal data:
  197. *
  198. * - radius see LBPHFaceRecognizer::create.
  199. * - neighbors see LBPHFaceRecognizer::create.
  200. * - grid_x see LLBPHFaceRecognizer::create.
  201. * - grid_y see LBPHFaceRecognizer::create.
  202. * - threshold see LBPHFaceRecognizer::create.
  203. * - histograms Local Binary Patterns Histograms calculated from the given training data (empty if
  204. * none was given).
  205. * - labels Labels corresponding to the calculated Local Binary Patterns Histograms.
  206. */
  207. + (LBPHFaceRecognizer*)create:(int)radius neighbors:(int)neighbors grid_x:(int)grid_x NS_SWIFT_NAME(create(radius:neighbors:grid_x:));
  208. /**
  209. * @param radius The radius used for building the Circular Local Binary Pattern. The greater the
  210. * radius, the smoother the image but more spatial information you can get.
  211. * @param neighbors The number of sample points to build a Circular Local Binary Pattern from. An
  212. * appropriate value is to use `8` sample points. Keep in mind: the more sample points you include,
  213. * the higher the computational cost.
  214. * publications. The more cells, the finer the grid, the higher the dimensionality of the resulting
  215. * feature vector.
  216. * publications. The more cells, the finer the grid, the higher the dimensionality of the resulting
  217. * feature vector.
  218. * is larger than the threshold, this method returns -1.
  219. *
  220. * ### Notes:
  221. *
  222. * - The Circular Local Binary Patterns (used in training and prediction) expect the data given as
  223. * grayscale images, use cvtColor to convert between the color spaces.
  224. * - This model supports updating.
  225. *
  226. * ### Model internal data:
  227. *
  228. * - radius see LBPHFaceRecognizer::create.
  229. * - neighbors see LBPHFaceRecognizer::create.
  230. * - grid_x see LLBPHFaceRecognizer::create.
  231. * - grid_y see LBPHFaceRecognizer::create.
  232. * - threshold see LBPHFaceRecognizer::create.
  233. * - histograms Local Binary Patterns Histograms calculated from the given training data (empty if
  234. * none was given).
  235. * - labels Labels corresponding to the calculated Local Binary Patterns Histograms.
  236. */
  237. + (LBPHFaceRecognizer*)create:(int)radius neighbors:(int)neighbors NS_SWIFT_NAME(create(radius:neighbors:));
  238. /**
  239. * @param radius The radius used for building the Circular Local Binary Pattern. The greater the
  240. * radius, the smoother the image but more spatial information you can get.
  241. * appropriate value is to use `8` sample points. Keep in mind: the more sample points you include,
  242. * the higher the computational cost.
  243. * publications. The more cells, the finer the grid, the higher the dimensionality of the resulting
  244. * feature vector.
  245. * publications. The more cells, the finer the grid, the higher the dimensionality of the resulting
  246. * feature vector.
  247. * is larger than the threshold, this method returns -1.
  248. *
  249. * ### Notes:
  250. *
  251. * - The Circular Local Binary Patterns (used in training and prediction) expect the data given as
  252. * grayscale images, use cvtColor to convert between the color spaces.
  253. * - This model supports updating.
  254. *
  255. * ### Model internal data:
  256. *
  257. * - radius see LBPHFaceRecognizer::create.
  258. * - neighbors see LBPHFaceRecognizer::create.
  259. * - grid_x see LLBPHFaceRecognizer::create.
  260. * - grid_y see LBPHFaceRecognizer::create.
  261. * - threshold see LBPHFaceRecognizer::create.
  262. * - histograms Local Binary Patterns Histograms calculated from the given training data (empty if
  263. * none was given).
  264. * - labels Labels corresponding to the calculated Local Binary Patterns Histograms.
  265. */
  266. + (LBPHFaceRecognizer*)create:(int)radius NS_SWIFT_NAME(create(radius:));
  267. /**
  268. * radius, the smoother the image but more spatial information you can get.
  269. * appropriate value is to use `8` sample points. Keep in mind: the more sample points you include,
  270. * the higher the computational cost.
  271. * publications. The more cells, the finer the grid, the higher the dimensionality of the resulting
  272. * feature vector.
  273. * publications. The more cells, the finer the grid, the higher the dimensionality of the resulting
  274. * feature vector.
  275. * is larger than the threshold, this method returns -1.
  276. *
  277. * ### Notes:
  278. *
  279. * - The Circular Local Binary Patterns (used in training and prediction) expect the data given as
  280. * grayscale images, use cvtColor to convert between the color spaces.
  281. * - This model supports updating.
  282. *
  283. * ### Model internal data:
  284. *
  285. * - radius see LBPHFaceRecognizer::create.
  286. * - neighbors see LBPHFaceRecognizer::create.
  287. * - grid_x see LLBPHFaceRecognizer::create.
  288. * - grid_y see LBPHFaceRecognizer::create.
  289. * - threshold see LBPHFaceRecognizer::create.
  290. * - histograms Local Binary Patterns Histograms calculated from the given training data (empty if
  291. * none was given).
  292. * - labels Labels corresponding to the calculated Local Binary Patterns Histograms.
  293. */
  294. + (LBPHFaceRecognizer*)create NS_SWIFT_NAME(create());
  295. @end
  296. NS_ASSUME_NONNULL_END