ClassesClassesClassesClasses | | | | Operators

trainf_ocr_class_mlpT_trainf_ocr_class_mlpTrainfOcrClassMlptrainf_ocr_class_mlpTrainfOcrClassMlpTrainfOcrClassMlp (Operator)

Name

trainf_ocr_class_mlpT_trainf_ocr_class_mlpTrainfOcrClassMlptrainf_ocr_class_mlpTrainfOcrClassMlpTrainfOcrClassMlp — Train an OCR classifier.

Signature

trainf_ocr_class_mlp( : : OCRHandle, TrainingFile, MaxIterations, WeightTolerance, ErrorTolerance : Error, ErrorLog)

Herror T_trainf_ocr_class_mlp(const Htuple OCRHandle, const Htuple TrainingFile, const Htuple MaxIterations, const Htuple WeightTolerance, const Htuple ErrorTolerance, Htuple* Error, Htuple* ErrorLog)

Herror trainf_ocr_class_mlp(const HTuple& OCRHandle, const HTuple& TrainingFile, const HTuple& MaxIterations, const HTuple& WeightTolerance, const HTuple& ErrorTolerance, HTuple* Error, HTuple* ErrorLog)

double HOCRMlp::TrainfOcrClassMlp(const HTuple& TrainingFile, const HTuple& MaxIterations, const HTuple& WeightTolerance, const HTuple& ErrorTolerance, HTuple* ErrorLog) const

void TrainfOcrClassMlp(const HTuple& OCRHandle, const HTuple& TrainingFile, const HTuple& MaxIterations, const HTuple& WeightTolerance, const HTuple& ErrorTolerance, HTuple* Error, HTuple* ErrorLog)

double HOCRMlp::TrainfOcrClassMlp(const HTuple& TrainingFile, Hlong MaxIterations, double WeightTolerance, double ErrorTolerance, HTuple* ErrorLog) const

double HOCRMlp::TrainfOcrClassMlp(const HString& TrainingFile, Hlong MaxIterations, double WeightTolerance, double ErrorTolerance, HTuple* ErrorLog) const

double HOCRMlp::TrainfOcrClassMlp(const char* TrainingFile, Hlong MaxIterations, double WeightTolerance, double ErrorTolerance, HTuple* ErrorLog) const

void HOperatorSetX.TrainfOcrClassMlp(
[in] VARIANT OCRHandle, [in] VARIANT TrainingFile, [in] VARIANT MaxIterations, [in] VARIANT WeightTolerance, [in] VARIANT ErrorTolerance, [out] VARIANT* Error, [out] VARIANT* ErrorLog)

double HOCRMlpX.TrainfOcrClassMlp(
[in] VARIANT TrainingFile, [in] Hlong MaxIterations, [in] double WeightTolerance, [in] double ErrorTolerance, [out] VARIANT* ErrorLog)

static void HOperatorSet.TrainfOcrClassMlp(HTuple OCRHandle, HTuple trainingFile, HTuple maxIterations, HTuple weightTolerance, HTuple errorTolerance, out HTuple error, out HTuple errorLog)

double HOCRMlp.TrainfOcrClassMlp(HTuple trainingFile, int maxIterations, double weightTolerance, double errorTolerance, out HTuple errorLog)

double HOCRMlp.TrainfOcrClassMlp(string trainingFile, int maxIterations, double weightTolerance, double errorTolerance, out HTuple errorLog)

Description

trainf_ocr_class_mlptrainf_ocr_class_mlpTrainfOcrClassMlptrainf_ocr_class_mlpTrainfOcrClassMlpTrainfOcrClassMlp trains the OCR classifier OCRHandleOCRHandleOCRHandleOCRHandleOCRHandleOCRHandle with the training characters stored in the OCR training files given by TrainingFileTrainingFileTrainingFileTrainingFileTrainingFiletrainingFile. The training files must have been created, e.g., using write_ocr_trainfwrite_ocr_trainfWriteOcrTrainfwrite_ocr_trainfWriteOcrTrainfWriteOcrTrainf, before calling trainf_ocr_class_mlptrainf_ocr_class_mlpTrainfOcrClassMlptrainf_ocr_class_mlpTrainfOcrClassMlpTrainfOcrClassMlp. The remaining parameters have the same meaning as in train_class_mlptrain_class_mlpTrainClassMlptrain_class_mlpTrainClassMlpTrainClassMlp and are described in detail with train_class_mlptrain_class_mlpTrainClassMlptrain_class_mlpTrainClassMlpTrainClassMlp. Please, note that training characters that have no corresponding class in the classifier OCRHandleOCRHandleOCRHandleOCRHandleOCRHandleOCRHandle are discarded.

Parallelization

Parameters

OCRHandleOCRHandleOCRHandleOCRHandleOCRHandleOCRHandle (input_control)  ocr_mlp HOCRMlp, HTupleHTupleHOCRMlp, HTupleHOCRMlpX, VARIANTHtuple (integer) (IntPtr) (Hlong) (Hlong) (Hlong) (Hlong)

Handle of the OCR classifier.

TrainingFileTrainingFileTrainingFileTrainingFileTrainingFiletrainingFile (input_control)  filename.read(-array) HTupleHTupleHTupleVARIANTHtuple (string) (string) (HString) (char*) (BSTR) (char*)

Names of the training files.

Default value: 'ocr.trf' "ocr.trf" "ocr.trf" "ocr.trf" "ocr.trf" "ocr.trf"

File extension: .trf, .otr

MaxIterationsMaxIterationsMaxIterationsMaxIterationsMaxIterationsmaxIterations (input_control)  integer HTupleHTupleHTupleVARIANTHtuple (integer) (int / long) (Hlong) (Hlong) (Hlong) (Hlong)

Maximum number of iterations of the optimization algorithm.

Default value: 200

Suggested values: 20, 40, 60, 80, 100, 120, 140, 160, 180, 200, 220, 240, 260, 280, 300

WeightToleranceWeightToleranceWeightToleranceWeightToleranceWeightToleranceweightTolerance (input_control)  real HTupleHTupleHTupleVARIANTHtuple (real) (double) (double) (double) (double) (double)

Threshold for the difference of the weights of the MLP between two iterations of the optimization algorithm.

Default value: 1.0

Suggested values: 1.0, 0.1, 0.01, 0.001, 0.0001, 0.00001

Restriction: WeightTolerance >= 1.0e-8

ErrorToleranceErrorToleranceErrorToleranceErrorToleranceErrorToleranceerrorTolerance (input_control)  real HTupleHTupleHTupleVARIANTHtuple (real) (double) (double) (double) (double) (double)

Threshold for the difference of the mean error of the MLP on the training data between two iterations of the optimization algorithm.

Default value: 0.01

Suggested values: 1.0, 0.1, 0.01, 0.001, 0.0001, 0.00001

Restriction: ErrorTolerance >= 1.0e-8

ErrorErrorErrorErrorErrorerror (output_control)  real HTupleHTupleHTupleVARIANTHtuple (real) (double) (double) (double) (double) (double)

Mean error of the MLP on the training data.

ErrorLogErrorLogErrorLogErrorLogErrorLogerrorLog (output_control)  real-array HTupleHTupleHTupleVARIANTHtuple (real) (double) (double) (double) (double) (double)

Mean error of the MLP on the training data as a function of the number of iterations of the optimization algorithm.

Example (HDevelop)

* Train an OCR classifier
read_ocr_trainf_names ('ocr.trf', CharacterNames, CharacterCount)
create_ocr_class_mlp (8, 10, 'constant', 'default', CharacterNames, 80, \
                      'none', 81, 42, OCRHandle)
trainf_ocr_class_mlp (OCRHandle, 'ocr.trf', 100, 1, 0.01, Error, ErrorLog)
write_ocr_class_mlp (OCRHandle, 'ocr.omc')
clear_ocr_class_mlp (OCRHandle)

Result

If the parameters are valid, the operator trainf_ocr_class_mlptrainf_ocr_class_mlpTrainfOcrClassMlptrainf_ocr_class_mlpTrainfOcrClassMlpTrainfOcrClassMlp returns the value 2 (H_MSG_TRUE). If necessary, an exception is raised.

trainf_ocr_class_mlptrainf_ocr_class_mlpTrainfOcrClassMlptrainf_ocr_class_mlpTrainfOcrClassMlpTrainfOcrClassMlp may return the error 9211 (Matrix is not positive definite) if Preprocessing = 'canonical_variates'"canonical_variates""canonical_variates""canonical_variates""canonical_variates""canonical_variates" is used. This typically indicates that not enough training samples have been stored for each class. In this case we recommend to change Preprocessing to 'normalization'"normalization""normalization""normalization""normalization""normalization". Another solution can be to add more training samples.

Possible Predecessors

create_ocr_class_mlpcreate_ocr_class_mlpCreateOcrClassMlpcreate_ocr_class_mlpCreateOcrClassMlpCreateOcrClassMlp, write_ocr_trainfwrite_ocr_trainfWriteOcrTrainfwrite_ocr_trainfWriteOcrTrainfWriteOcrTrainf, append_ocr_trainfappend_ocr_trainfAppendOcrTrainfappend_ocr_trainfAppendOcrTrainfAppendOcrTrainf, write_ocr_trainf_imagewrite_ocr_trainf_imageWriteOcrTrainfImagewrite_ocr_trainf_imageWriteOcrTrainfImageWriteOcrTrainfImage

Possible Successors

do_ocr_single_class_mlpdo_ocr_single_class_mlpDoOcrSingleClassMlpdo_ocr_single_class_mlpDoOcrSingleClassMlpDoOcrSingleClassMlp, do_ocr_multi_class_mlpdo_ocr_multi_class_mlpDoOcrMultiClassMlpdo_ocr_multi_class_mlpDoOcrMultiClassMlpDoOcrMultiClassMlp, write_ocr_class_mlpwrite_ocr_class_mlpWriteOcrClassMlpwrite_ocr_class_mlpWriteOcrClassMlpWriteOcrClassMlp

Alternatives

read_ocr_class_mlpread_ocr_class_mlpReadOcrClassMlpread_ocr_class_mlpReadOcrClassMlpReadOcrClassMlp

See also

train_class_mlptrain_class_mlpTrainClassMlptrain_class_mlpTrainClassMlpTrainClassMlp

Module

OCR/OCV


ClassesClassesClassesClasses | | | | Operators