trainf_ocr_class_svm🔗
Short description🔗
trainf_ocr_class_svm — Train an OCR classifier.
Signature🔗
trainf_ocr_class_svm( ocr_svm OCRHandle, filename.read TrainingFile, real Epsilon, number TrainMode )
Description🔗
trainf_ocr_class_svm trains the OCR classifier
OCRHandle with the training characters stored in the OCR
training files given by TrainingFile. The training files
must have been created, e.g., using write_ocr_trainf, before
calling trainf_ocr_class_svm. The parameters
Epsilon and TrainMode have the same meaning as in
train_class_svm. Please, note that training characters that have
no corresponding class in the classifier OCRHandle are discarded.
Execution information🔗
Execution information
-
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:
During execution of this operator, access to the value of this parameter must be synchronized if it is used across multiple threads.
Parameters🔗
OCRHandle (input_control, state is modified) ocr_svm → (handle)
Handle of the OCR classifier.
TrainingFile (input_control) filename.read(-array) → (string)
Names of the training files.
Default: 'ocr.trf'
File extension: .trf, .otr
Epsilon (input_control) real → (real)
Stop parameter for training.
Default: 0.001
Suggested values: 0.00001, 0.0001, 0.001, 0.01, 0.1
TrainMode (input_control) number → (string / integer)
Mode of training.
Default: 'default'
List of values: 'add_sv_to_train_set', 'default'
Example🔗
(HDevelop)
* Train an OCR classifier
read_ocr_trainf_names ('ocr.trf', CharacterNames, CharacterCount)
create_ocr_class_svm (8, 10, 'constant', 'default', CharacterNames, \
'rbf', 0.01, 0.01, 'one-versus-one', \
'normalization', 81, OCRHandle)
trainf_ocr_class_svm (OCRHandle, 'ocr.trf', 0.001, 'default')
write_ocr_class_svm (OCRHandle, 'ocr.osc')
Result🔗
If the parameters are valid the operator
trainf_ocr_class_svm returns the value 2 (H_MSG_TRUE). If necessary,
an exception is raised.
trainf_ocr_class_svm may return the error 9211 (Matrix is
not positive definite) if Preprocessing \(=\)
'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'. Another solution can be to add more
training samples.
Combinations with other operators🔗
Combinations
Possible predecessors
create_ocr_class_svm, write_ocr_trainf, append_ocr_trainf, write_ocr_trainf_image
Possible successors
do_ocr_single_class_svm, do_ocr_multi_class_svm, write_ocr_class_svm
Alternatives
See also
Module🔗
OCR/OCV