001 002// 003// This file is auto-generated. Please don't modify it! 004// 005package org.opencv.ml; 006 007import org.opencv.core.Mat; 008import org.opencv.core.TermCriteria; 009 010// C++: class ANN_MLP 011//javadoc: ANN_MLP 012public class ANN_MLP extends StatModel { 013 014 protected ANN_MLP(long addr) { super(addr); } 015 016 017 public static final int 018 BACKPROP = 0, 019 RPROP = 1, 020 IDENTITY = 0, 021 SIGMOID_SYM = 1, 022 GAUSSIAN = 2, 023 UPDATE_WEIGHTS = 1, 024 NO_INPUT_SCALE = 2, 025 NO_OUTPUT_SCALE = 4; 026 027 028 // 029 // C++: Mat getLayerSizes() 030 // 031 032 //javadoc: ANN_MLP::getLayerSizes() 033 public Mat getLayerSizes() 034 { 035 036 Mat retVal = new Mat(getLayerSizes_0(nativeObj)); 037 038 return retVal; 039 } 040 041 042 // 043 // C++: Mat getWeights(int layerIdx) 044 // 045 046 //javadoc: ANN_MLP::getWeights(layerIdx) 047 public Mat getWeights(int layerIdx) 048 { 049 050 Mat retVal = new Mat(getWeights_0(nativeObj, layerIdx)); 051 052 return retVal; 053 } 054 055 056 // 057 // C++: static Ptr_ANN_MLP create() 058 // 059 060 //javadoc: ANN_MLP::create() 061 public static ANN_MLP create() 062 { 063 064 ANN_MLP retVal = new ANN_MLP(create_0()); 065 066 return retVal; 067 } 068 069 070 // 071 // C++: TermCriteria getTermCriteria() 072 // 073 074 //javadoc: ANN_MLP::getTermCriteria() 075 public TermCriteria getTermCriteria() 076 { 077 078 TermCriteria retVal = new TermCriteria(getTermCriteria_0(nativeObj)); 079 080 return retVal; 081 } 082 083 084 // 085 // C++: double getBackpropMomentumScale() 086 // 087 088 //javadoc: ANN_MLP::getBackpropMomentumScale() 089 public double getBackpropMomentumScale() 090 { 091 092 double retVal = getBackpropMomentumScale_0(nativeObj); 093 094 return retVal; 095 } 096 097 098 // 099 // C++: double getBackpropWeightScale() 100 // 101 102 //javadoc: ANN_MLP::getBackpropWeightScale() 103 public double getBackpropWeightScale() 104 { 105 106 double retVal = getBackpropWeightScale_0(nativeObj); 107 108 return retVal; 109 } 110 111 112 // 113 // C++: double getRpropDW0() 114 // 115 116 //javadoc: ANN_MLP::getRpropDW0() 117 public double getRpropDW0() 118 { 119 120 double retVal = getRpropDW0_0(nativeObj); 121 122 return retVal; 123 } 124 125 126 // 127 // C++: double getRpropDWMax() 128 // 129 130 //javadoc: ANN_MLP::getRpropDWMax() 131 public double getRpropDWMax() 132 { 133 134 double retVal = getRpropDWMax_0(nativeObj); 135 136 return retVal; 137 } 138 139 140 // 141 // C++: double getRpropDWMin() 142 // 143 144 //javadoc: ANN_MLP::getRpropDWMin() 145 public double getRpropDWMin() 146 { 147 148 double retVal = getRpropDWMin_0(nativeObj); 149 150 return retVal; 151 } 152 153 154 // 155 // C++: double getRpropDWMinus() 156 // 157 158 //javadoc: ANN_MLP::getRpropDWMinus() 159 public double getRpropDWMinus() 160 { 161 162 double retVal = getRpropDWMinus_0(nativeObj); 163 164 return retVal; 165 } 166 167 168 // 169 // C++: double getRpropDWPlus() 170 // 171 172 //javadoc: ANN_MLP::getRpropDWPlus() 173 public double getRpropDWPlus() 174 { 175 176 double retVal = getRpropDWPlus_0(nativeObj); 177 178 return retVal; 179 } 180 181 182 // 183 // C++: int getTrainMethod() 184 // 185 186 //javadoc: ANN_MLP::getTrainMethod() 187 public int getTrainMethod() 188 { 189 190 int retVal = getTrainMethod_0(nativeObj); 191 192 return retVal; 193 } 194 195 196 // 197 // C++: void setActivationFunction(int type, double param1 = 0, double param2 = 0) 198 // 199 200 //javadoc: ANN_MLP::setActivationFunction(type, param1, param2) 201 public void setActivationFunction(int type, double param1, double param2) 202 { 203 204 setActivationFunction_0(nativeObj, type, param1, param2); 205 206 return; 207 } 208 209 //javadoc: ANN_MLP::setActivationFunction(type) 210 public void setActivationFunction(int type) 211 { 212 213 setActivationFunction_1(nativeObj, type); 214 215 return; 216 } 217 218 219 // 220 // C++: void setBackpropMomentumScale(double val) 221 // 222 223 //javadoc: ANN_MLP::setBackpropMomentumScale(val) 224 public void setBackpropMomentumScale(double val) 225 { 226 227 setBackpropMomentumScale_0(nativeObj, val); 228 229 return; 230 } 231 232 233 // 234 // C++: void setBackpropWeightScale(double val) 235 // 236 237 //javadoc: ANN_MLP::setBackpropWeightScale(val) 238 public void setBackpropWeightScale(double val) 239 { 240 241 setBackpropWeightScale_0(nativeObj, val); 242 243 return; 244 } 245 246 247 // 248 // C++: void setLayerSizes(Mat _layer_sizes) 249 // 250 251 //javadoc: ANN_MLP::setLayerSizes(_layer_sizes) 252 public void setLayerSizes(Mat _layer_sizes) 253 { 254 255 setLayerSizes_0(nativeObj, _layer_sizes.nativeObj); 256 257 return; 258 } 259 260 261 // 262 // C++: void setRpropDW0(double val) 263 // 264 265 //javadoc: ANN_MLP::setRpropDW0(val) 266 public void setRpropDW0(double val) 267 { 268 269 setRpropDW0_0(nativeObj, val); 270 271 return; 272 } 273 274 275 // 276 // C++: void setRpropDWMax(double val) 277 // 278 279 //javadoc: ANN_MLP::setRpropDWMax(val) 280 public void setRpropDWMax(double val) 281 { 282 283 setRpropDWMax_0(nativeObj, val); 284 285 return; 286 } 287 288 289 // 290 // C++: void setRpropDWMin(double val) 291 // 292 293 //javadoc: ANN_MLP::setRpropDWMin(val) 294 public void setRpropDWMin(double val) 295 { 296 297 setRpropDWMin_0(nativeObj, val); 298 299 return; 300 } 301 302 303 // 304 // C++: void setRpropDWMinus(double val) 305 // 306 307 //javadoc: ANN_MLP::setRpropDWMinus(val) 308 public void setRpropDWMinus(double val) 309 { 310 311 setRpropDWMinus_0(nativeObj, val); 312 313 return; 314 } 315 316 317 // 318 // C++: void setRpropDWPlus(double val) 319 // 320 321 //javadoc: ANN_MLP::setRpropDWPlus(val) 322 public void setRpropDWPlus(double val) 323 { 324 325 setRpropDWPlus_0(nativeObj, val); 326 327 return; 328 } 329 330 331 // 332 // C++: void setTermCriteria(TermCriteria val) 333 // 334 335 //javadoc: ANN_MLP::setTermCriteria(val) 336 public void setTermCriteria(TermCriteria val) 337 { 338 339 setTermCriteria_0(nativeObj, val.type, val.maxCount, val.epsilon); 340 341 return; 342 } 343 344 345 // 346 // C++: void setTrainMethod(int method, double param1 = 0, double param2 = 0) 347 // 348 349 //javadoc: ANN_MLP::setTrainMethod(method, param1, param2) 350 public void setTrainMethod(int method, double param1, double param2) 351 { 352 353 setTrainMethod_0(nativeObj, method, param1, param2); 354 355 return; 356 } 357 358 //javadoc: ANN_MLP::setTrainMethod(method) 359 public void setTrainMethod(int method) 360 { 361 362 setTrainMethod_1(nativeObj, method); 363 364 return; 365 } 366 367 368 @Override 369 protected void finalize() throws Throwable { 370 delete(nativeObj); 371 } 372 373 374 375 // C++: Mat getLayerSizes() 376 private static native long getLayerSizes_0(long nativeObj); 377 378 // C++: Mat getWeights(int layerIdx) 379 private static native long getWeights_0(long nativeObj, int layerIdx); 380 381 // C++: static Ptr_ANN_MLP create() 382 private static native long create_0(); 383 384 // C++: TermCriteria getTermCriteria() 385 private static native double[] getTermCriteria_0(long nativeObj); 386 387 // C++: double getBackpropMomentumScale() 388 private static native double getBackpropMomentumScale_0(long nativeObj); 389 390 // C++: double getBackpropWeightScale() 391 private static native double getBackpropWeightScale_0(long nativeObj); 392 393 // C++: double getRpropDW0() 394 private static native double getRpropDW0_0(long nativeObj); 395 396 // C++: double getRpropDWMax() 397 private static native double getRpropDWMax_0(long nativeObj); 398 399 // C++: double getRpropDWMin() 400 private static native double getRpropDWMin_0(long nativeObj); 401 402 // C++: double getRpropDWMinus() 403 private static native double getRpropDWMinus_0(long nativeObj); 404 405 // C++: double getRpropDWPlus() 406 private static native double getRpropDWPlus_0(long nativeObj); 407 408 // C++: int getTrainMethod() 409 private static native int getTrainMethod_0(long nativeObj); 410 411 // C++: void setActivationFunction(int type, double param1 = 0, double param2 = 0) 412 private static native void setActivationFunction_0(long nativeObj, int type, double param1, double param2); 413 private static native void setActivationFunction_1(long nativeObj, int type); 414 415 // C++: void setBackpropMomentumScale(double val) 416 private static native void setBackpropMomentumScale_0(long nativeObj, double val); 417 418 // C++: void setBackpropWeightScale(double val) 419 private static native void setBackpropWeightScale_0(long nativeObj, double val); 420 421 // C++: void setLayerSizes(Mat _layer_sizes) 422 private static native void setLayerSizes_0(long nativeObj, long _layer_sizes_nativeObj); 423 424 // C++: void setRpropDW0(double val) 425 private static native void setRpropDW0_0(long nativeObj, double val); 426 427 // C++: void setRpropDWMax(double val) 428 private static native void setRpropDWMax_0(long nativeObj, double val); 429 430 // C++: void setRpropDWMin(double val) 431 private static native void setRpropDWMin_0(long nativeObj, double val); 432 433 // C++: void setRpropDWMinus(double val) 434 private static native void setRpropDWMinus_0(long nativeObj, double val); 435 436 // C++: void setRpropDWPlus(double val) 437 private static native void setRpropDWPlus_0(long nativeObj, double val); 438 439 // C++: void setTermCriteria(TermCriteria val) 440 private static native void setTermCriteria_0(long nativeObj, int val_type, int val_maxCount, double val_epsilon); 441 442 // C++: void setTrainMethod(int method, double param1 = 0, double param2 = 0) 443 private static native void setTrainMethod_0(long nativeObj, int method, double param1, double param2); 444 private static native void setTrainMethod_1(long nativeObj, int method); 445 446 // native support for java finalize() 447 private static native void delete(long nativeObj); 448 449}