Operator Reference

HALCON Operator Reference / OCR / Neural Nets

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do_ocr_multi_class_mlpT_do_ocr_multi_class_mlpDoOcrMultiClassMlpDoOcrMultiClassMlpdo_ocr_multi_class_mlp (Operator)

do_ocr_multi_class_mlpT_do_ocr_multi_class_mlpDoOcrMultiClassMlpDoOcrMultiClassMlpdo_ocr_multi_class_mlp — Classify multiple characters with an OCR classifier.

Signature

do_ocr_multi_class_mlp(Character, Image : : OCRHandle : Class, Confidence)

Herror T_do_ocr_multi_class_mlp(const Hobject Character, const Hobject Image, const Htuple OCRHandle, Htuple* Class, Htuple* Confidence)

void DoOcrMultiClassMlp(const HObject& Character, const HObject& Image, const HTuple& OCRHandle, HTuple* Class, HTuple* Confidence)

HTuple HRegion::DoOcrMultiClassMlp(const HImage& Image, const HOCRMlp& OCRHandle, HTuple* Confidence) const

HString HRegion::DoOcrMultiClassMlp(const HImage& Image, const HOCRMlp& OCRHandle, double* Confidence) const

HTuple HOCRMlp::DoOcrMultiClassMlp(const HRegion& Character, const HImage& Image, HTuple* Confidence) const

HString HOCRMlp::DoOcrMultiClassMlp(const HRegion& Character, const HImage& Image, double* Confidence) const

static void HOperatorSet.DoOcrMultiClassMlp(HObject character, HObject image, HTuple OCRHandle, out HTuple classVal, out HTuple confidence)

HTuple HRegion.DoOcrMultiClassMlp(HImage image, HOCRMlp OCRHandle, out HTuple confidence)

string HRegion.DoOcrMultiClassMlp(HImage image, HOCRMlp OCRHandle, out double confidence)

HTuple HOCRMlp.DoOcrMultiClassMlp(HRegion character, HImage image, out HTuple confidence)

string HOCRMlp.DoOcrMultiClassMlp(HRegion character, HImage image, out double confidence)

def do_ocr_multi_class_mlp(character: HObject, image: HObject, ocrhandle: HHandle) -> Tuple[Sequence[str], Sequence[float]]

def do_ocr_multi_class_mlp_s(character: HObject, image: HObject, ocrhandle: HHandle) -> Tuple[str, float]

Description

do_ocr_multi_class_mlpdo_ocr_multi_class_mlpDoOcrMultiClassMlpDoOcrMultiClassMlpdo_ocr_multi_class_mlp computes the best class for each of the characters given by the regions CharacterCharacterCharactercharactercharacter and the gray values ImageImageImageimageimage with the OCR classifier OCRHandleOCRHandleOCRHandleOCRHandleocrhandle and returns the classes in ClassClassClassclassValclass and the corresponding confidences (probabilities) of the classes in ConfidenceConfidenceConfidenceconfidenceconfidence. In contrast to do_ocr_single_class_mlpdo_ocr_single_class_mlpDoOcrSingleClassMlpDoOcrSingleClassMlpdo_ocr_single_class_mlp, do_ocr_multi_class_mlpdo_ocr_multi_class_mlpDoOcrMultiClassMlpDoOcrMultiClassMlpdo_ocr_multi_class_mlp can classify multiple characters in one call, and therefore typically is faster than a loop that uses do_ocr_single_class_mlpdo_ocr_single_class_mlpDoOcrSingleClassMlpDoOcrSingleClassMlpdo_ocr_single_class_mlp to classify single characters. However, do_ocr_multi_class_mlpdo_ocr_multi_class_mlpDoOcrMultiClassMlpDoOcrMultiClassMlpdo_ocr_multi_class_mlp can only return the best class of each character. Because the confidences can be interpreted as probabilities (see classify_class_mlpclassify_class_mlpClassifyClassMlpClassifyClassMlpclassify_class_mlp and evaluate_class_mlpevaluate_class_mlpEvaluateClassMlpEvaluateClassMlpevaluate_class_mlp), and it is therefore easy to check whether a character has been classified with too much uncertainty, this is usually not a disadvantage, except in cases where the classes overlap so much that in many cases the second best class must be examined to be able to decide the class of the character. In these cases, do_ocr_single_class_mlpdo_ocr_single_class_mlpDoOcrSingleClassMlpDoOcrSingleClassMlpdo_ocr_single_class_mlp should be used.

A string of the number (alternatively displayed as ) in ClassClassClassclassValclass signifies that the region has been classified as rejection class.

Before calling do_ocr_multi_class_mlpdo_ocr_multi_class_mlpDoOcrMultiClassMlpDoOcrMultiClassMlpdo_ocr_multi_class_mlp, the classifier must be trained with trainf_ocr_class_mlptrainf_ocr_class_mlpTrainfOcrClassMlpTrainfOcrClassMlptrainf_ocr_class_mlp.

Execution Information

• Multithreading type: reentrant (runs in parallel with non-exclusive operators).
• Multithreading scope: global (may be called from any thread).
• Automatically parallelized on tuple level.

Parameters

CharacterCharacterCharactercharactercharacter (input_object)  region(-array) → objectHRegionHObjectHObjectHobject

Characters to be recognized.

ImageImageImageimageimage (input_object)  singlechannelimage → objectHImageHObjectHObjectHobject (byte / uint2)

Gray values of the characters.

OCRHandleOCRHandleOCRHandleOCRHandleocrhandle (input_control)  ocr_mlp → HOCRMlp, HTupleHHandleHTupleHtuple (handle) (IntPtr) (HHandle) (handle)

Handle of the OCR classifier.

ClassClassClassclassValclass (output_control)  string(-array) → HTupleSequence[str]HTupleHtuple (string) (string) (HString) (char*)

Result of classifying the characters with the MLP.

Number of elements: Class == Character

ConfidenceConfidenceConfidenceconfidenceconfidence (output_control)  real(-array) → HTupleSequence[float]HTupleHtuple (real) (double) (double) (double)

Confidence of the class of the characters.

Number of elements: Confidence == Character

Result

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

Possible Predecessors

trainf_ocr_class_mlptrainf_ocr_class_mlpTrainfOcrClassMlpTrainfOcrClassMlptrainf_ocr_class_mlp, read_ocr_class_mlpread_ocr_class_mlpReadOcrClassMlpReadOcrClassMlpread_ocr_class_mlp

Alternatives

do_ocr_word_mlpdo_ocr_word_mlpDoOcrWordMlpDoOcrWordMlpdo_ocr_word_mlp, do_ocr_single_class_mlpdo_ocr_single_class_mlpDoOcrSingleClassMlpDoOcrSingleClassMlpdo_ocr_single_class_mlp

See also

create_ocr_class_mlpcreate_ocr_class_mlpCreateOcrClassMlpCreateOcrClassMlpcreate_ocr_class_mlp, classify_class_mlpclassify_class_mlpClassifyClassMlpClassifyClassMlpclassify_class_mlp

Module

OCR/OCV

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