Train an OCR classifier by the input of regions.
The operator traind_ocr_class_box trains the classifier directly via the input of regions in an image. Any number of regions of an image can be passed. For each character (region) in Character the corresponding name (class) Class must be specified. The gray values are passed in Image. When the procedure has finished the parameter AvgConfidence provides information about the success of the training: It contains the average confidence of the trained characters measured by a re-classification. The confidence of mismatched characters is set to 0 (thus, the average confidence will be decreased significantly).
|
Character (input_object) |
region(-array) -> object |
| Characters to be trained. | |
|
Image (input_object) |
image -> object : byte |
| Gray values for the characters. | |
|
OcrHandle (input_control) |
ocr -> integer |
| ID of the desired OCR-classifier. | |
|
Class (input_control) |
string(-array) -> string |
| Class (name) of the characters. | |
| Default value: ''a'' | |
|
AvgConfidence (output_control) |
real -> real |
| Average confidence during a re-classification of the trained characters. | |
If the parameters are correct, the operator traind_ocr_class_box returns the value 2 (H_MSG_TRUE). Otherwise an exception will be raised.
traind_ocr_class_box is processed completely exclusively without parallelization.
create_ocr_class_box, read_ocr
traind_ocr_class_box, write_ocr, do_ocr_multi, do_ocr_single
Optical character recognition
