Name
trainf_ocr_class_svm_protectedtrainf_ocr_class_svm_protectedTrainfOcrClassSvmProtectedtrainf_ocr_class_svm_protectedTrainfOcrClassSvmProtectedTrainfOcrClassSvmProtected — Train an OCR classifier with data from a (protected) training file.
void TrainfOcrClassSvmProtected(const HTuple& OCRHandle, const HTuple& TrainingFile, const HTuple& Password, const HTuple& Epsilon, const HTuple& TrainMode)
void HOCRSvm::TrainfOcrClassSvmProtected(const HTuple& TrainingFile, const HTuple& Password, double Epsilon, const HTuple& TrainMode) const
void HOCRSvm::TrainfOcrClassSvmProtected(const HString& TrainingFile, const HString& Password, double Epsilon, const HString& TrainMode) const
void HOCRSvm::TrainfOcrClassSvmProtected(const char* TrainingFile, const char* Password, double Epsilon, const char* TrainMode) const
static void HOperatorSet.TrainfOcrClassSvmProtected(HTuple OCRHandle, HTuple trainingFile, HTuple password, HTuple epsilon, HTuple trainMode)
void HOCRSvm.TrainfOcrClassSvmProtected(HTuple trainingFile, HTuple password, double epsilon, HTuple trainMode)
void HOCRSvm.TrainfOcrClassSvmProtected(string trainingFile, string password, double epsilon, string trainMode)
trainf_ocr_class_svm_protectedtrainf_ocr_class_svm_protectedTrainfOcrClassSvmProtectedtrainf_ocr_class_svm_protectedTrainfOcrClassSvmProtectedTrainfOcrClassSvmProtected trains the OCR classifier
OCRHandleOCRHandleOCRHandleOCRHandleOCRHandleOCRHandle with the training data stored in the OCR
training files given by TrainingFileTrainingFileTrainingFileTrainingFileTrainingFiletrainingFile. Its functionality
corresponds to the functionality of trainf_ocr_class_svmtrainf_ocr_class_svmTrainfOcrClassSvmtrainf_ocr_class_svmTrainfOcrClassSvmTrainfOcrClassSvm,
with the addition that trainf_ocr_class_svm_protectedtrainf_ocr_class_svm_protectedTrainfOcrClassSvmProtectedtrainf_ocr_class_svm_protectedTrainfOcrClassSvmProtectedTrainfOcrClassSvmProtected
can process unprotected and protected training files. Protected
training files can be used only with the correct user password
PasswordPasswordPasswordPasswordPasswordpassword. If the number of passwords PasswordPasswordPasswordPasswordPasswordpassword
equals 1, then every input file TrainingFileTrainingFileTrainingFileTrainingFileTrainingFiletrainingFile is checked
with that password, otherwise the number of passwords has to be
equal to the number of input files and the input file at position
n is checked with the password at position n. For unprotected
training files the passwords are ignored.
For a more detailed description of the operator's functionality see
trainf_ocr_class_svmtrainf_ocr_class_svmTrainfOcrClassSvmtrainf_ocr_class_svmTrainfOcrClassSvmTrainfOcrClassSvm. The concept of protecting OCR training
data in HALCON is described in protect_ocr_trainfprotect_ocr_trainfProtectOcrTrainfprotect_ocr_trainfProtectOcrTrainfProtectOcrTrainf.
- Multithreading type: reentrant (runs in parallel with non-exclusive operators).
- Multithreading scope: global (may be called from any thread).
- Processed without parallelization.
This operator modifies the state of the following input parameter:
The value of this parameter may not be shared across multiple threads without external synchronization.
Handle of the OCR classifier.
Names of the training files.
Default value:
'ocr.trf'
"ocr.trf"
"ocr.trf"
"ocr.trf"
"ocr.trf"
"ocr.trf"
File extension: .trf, .otr
Passwords for protected training files.
Stop parameter for training.
Default value: 0.001
Suggested values: 0.00001, 0.0001, 0.001, 0.01, 0.1
Mode of training.
Default value:
'default'
"default"
"default"
"default"
"default"
"default"
List of values: 'add_sv_to_train_set'"add_sv_to_train_set""add_sv_to_train_set""add_sv_to_train_set""add_sv_to_train_set""add_sv_to_train_set", 'default'"default""default""default""default""default"
If the parameters are valid the operator
trainf_ocr_class_svm_protectedtrainf_ocr_class_svm_protectedTrainfOcrClassSvmProtectedtrainf_ocr_class_svm_protectedTrainfOcrClassSvmProtectedTrainfOcrClassSvmProtected returns the value 2 (H_MSG_TRUE). If necessary,
an exception is raised.
trainf_ocr_class_svm_protectedtrainf_ocr_class_svm_protectedTrainfOcrClassSvmProtectedtrainf_ocr_class_svm_protectedTrainfOcrClassSvmProtectedTrainfOcrClassSvmProtected 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.
create_ocr_class_svmcreate_ocr_class_svmCreateOcrClassSvmcreate_ocr_class_svmCreateOcrClassSvmCreateOcrClassSvm,
write_ocr_trainfwrite_ocr_trainfWriteOcrTrainfwrite_ocr_trainfWriteOcrTrainfWriteOcrTrainf,
append_ocr_trainfappend_ocr_trainfAppendOcrTrainfappend_ocr_trainfAppendOcrTrainfAppendOcrTrainf,
write_ocr_trainf_imagewrite_ocr_trainf_imageWriteOcrTrainfImagewrite_ocr_trainf_imageWriteOcrTrainfImageWriteOcrTrainfImage,
protect_ocr_trainfprotect_ocr_trainfProtectOcrTrainfprotect_ocr_trainfProtectOcrTrainfProtectOcrTrainf
do_ocr_single_class_svmdo_ocr_single_class_svmDoOcrSingleClassSvmdo_ocr_single_class_svmDoOcrSingleClassSvmDoOcrSingleClassSvm,
do_ocr_multi_class_svmdo_ocr_multi_class_svmDoOcrMultiClassSvmdo_ocr_multi_class_svmDoOcrMultiClassSvmDoOcrMultiClassSvm,
write_ocr_class_svmwrite_ocr_class_svmWriteOcrClassSvmwrite_ocr_class_svmWriteOcrClassSvmWriteOcrClassSvm
read_ocr_class_svmread_ocr_class_svmReadOcrClassSvmread_ocr_class_svmReadOcrClassSvmReadOcrClassSvm
trainf_ocr_class_svmtrainf_ocr_class_svmTrainfOcrClassSvmtrainf_ocr_class_svmTrainfOcrClassSvmTrainfOcrClassSvm,
train_class_svmtrain_class_svmTrainClassSvmtrain_class_svmTrainClassSvmTrainClassSvm
OCR/OCV