do_ocr_single_class_mlpT_do_ocr_single_class_mlpDoOcrSingleClassMlpDoOcrSingleClassMlpdo_ocr_single_class_mlp (算子)
名称
do_ocr_single_class_mlpT_do_ocr_single_class_mlpDoOcrSingleClassMlpDoOcrSingleClassMlpdo_ocr_single_class_mlp — 使用 OCR 分类器对单个字符进行分类。
签名
void DoOcrSingleClassMlp(const HObject& Character, const HObject& Image, const HTuple& OCRHandle, const HTuple& Num, HTuple* Class, HTuple* Confidence)
HTuple HRegion::DoOcrSingleClassMlp(const HImage& Image, const HOCRMlp& OCRHandle, const HTuple& Num, HTuple* Confidence) const
HString HRegion::DoOcrSingleClassMlp(const HImage& Image, const HOCRMlp& OCRHandle, const HTuple& Num, double* Confidence) const
HTuple HOCRMlp::DoOcrSingleClassMlp(const HRegion& Character, const HImage& Image, const HTuple& Num, HTuple* Confidence) const
HString HOCRMlp::DoOcrSingleClassMlp(const HRegion& Character, const HImage& Image, const HTuple& Num, double* Confidence) const
static void HOperatorSet.DoOcrSingleClassMlp(HObject character, HObject image, HTuple OCRHandle, HTuple num, out HTuple classVal, out HTuple confidence)
HTuple HRegion.DoOcrSingleClassMlp(HImage image, HOCRMlp OCRHandle, HTuple num, out HTuple confidence)
string HRegion.DoOcrSingleClassMlp(HImage image, HOCRMlp OCRHandle, HTuple num, out double confidence)
HTuple HOCRMlp.DoOcrSingleClassMlp(HRegion character, HImage image, HTuple num, out HTuple confidence)
string HOCRMlp.DoOcrSingleClassMlp(HRegion character, HImage image, HTuple num, out double confidence)
def do_ocr_single_class_mlp(character: HObject, image: HObject, ocrhandle: HHandle, num: Sequence[int]) -> Tuple[Sequence[str], Sequence[float]]
def do_ocr_single_class_mlp_s(character: HObject, image: HObject, ocrhandle: HHandle, num: Sequence[int]) -> Tuple[str, float]
描述
do_ocr_single_class_mlpdo_ocr_single_class_mlpDoOcrSingleClassMlpDoOcrSingleClassMlpDoOcrSingleClassMlpdo_ocr_single_class_mlp computes the best NumNumNumNumnumnum
classes of the character given by the region CharacterCharacterCharacterCharactercharactercharacter and
the gray values ImageImageImageImageimageimage with the OCR classifier
OCRHandleOCRHandleOCRHandleOCRHandleOCRHandleocrhandle and returns the classes in ClassClassClassClassclassValclass and the
corresponding confidences (probabilities) of the classes in
ConfidenceConfidenceConfidenceConfidenceconfidenceconfidence. Because multiple classes may be returned by
do_ocr_single_class_mlpdo_ocr_single_class_mlpDoOcrSingleClassMlpDoOcrSingleClassMlpDoOcrSingleClassMlpdo_ocr_single_class_mlp, CharacterCharacterCharacterCharactercharactercharacter may only contain
a single region (a single character). If multiple characters should
be classified in a single call, do_ocr_multi_class_mlpdo_ocr_multi_class_mlpDoOcrMultiClassMlpDoOcrMultiClassMlpDoOcrMultiClassMlpdo_ocr_multi_class_mlp must
be used. Because do_ocr_multi_class_mlpdo_ocr_multi_class_mlpDoOcrMultiClassMlpDoOcrMultiClassMlpDoOcrMultiClassMlpdo_ocr_multi_class_mlp typically is faster
than a loop with do_ocr_single_class_mlpdo_ocr_single_class_mlpDoOcrSingleClassMlpDoOcrSingleClassMlpDoOcrSingleClassMlpdo_ocr_single_class_mlp and because the
confidences can be interpreted as probabilities (see
classify_class_mlpclassify_class_mlpClassifyClassMlpClassifyClassMlpClassifyClassMlpclassify_class_mlp and evaluate_class_mlpevaluate_class_mlpEvaluateClassMlpEvaluateClassMlpEvaluateClassMlpevaluate_class_mlp), and it
is therefore easy to check whether a character has been classified
with too much uncertainty, in most cases
do_ocr_multi_class_mlpdo_ocr_multi_class_mlpDoOcrMultiClassMlpDoOcrMultiClassMlpDoOcrMultiClassMlpdo_ocr_multi_class_mlp should be used, unless the
second-best class should be examined explicitly.
A string of the number
'\032'"\032""\032""\032""\032""\032" (alternatively
displayed as '\0x1A'"\0x1A""\0x1A""\0x1A""\0x1A""\0x1A") in
ClassClassClassClassclassValclass signifies that the region has been classified as rejection
class.
Before calling do_ocr_single_class_mlpdo_ocr_single_class_mlpDoOcrSingleClassMlpDoOcrSingleClassMlpDoOcrSingleClassMlpdo_ocr_single_class_mlp, the classifier must be
trained with trainf_ocr_class_mlptrainf_ocr_class_mlpTrainfOcrClassMlpTrainfOcrClassMlpTrainfOcrClassMlptrainf_ocr_class_mlp。
执行信息
- 多线程类型：可重入（与非独占算子并行运行）。
- 多线程作用域：全局（可从任何线程调用）。
- 未采用并行化处理。
参数
CharacterCharacterCharacterCharactercharactercharacter (输入对象) region → objectHRegionHObjectHRegionHobject
Character to be recognized.
ImageImageImageImageimageimage (输入对象) singlechannelimage → objectHImageHObjectHImageHobject (byte / uint2)
Gray values of the character.
OCRHandleOCRHandleOCRHandleOCRHandleOCRHandleocrhandle (输入控制) ocr_mlp → HOCRMlp, HTupleHHandleHTupleHtuple (handle) (IntPtr) (HHandle) (handle)
Handle of the OCR classifier.
NumNumNumNumnumnum (输入控制) integer-array → HTupleSequence[int]HTupleHtuple (integer) (int / long) (Hlong) (Hlong)
Number of best classes to determine.
默认值：
1
建议值：
1, 2, 3, 4, 5
ClassClassClassClassclassValclass (输出控制) string(-array) → HTupleSequence[str]HTupleHtuple (string) (string) (HString) (char*)
Result of classifying the character with the
MLP.
ConfidenceConfidenceConfidenceConfidenceconfidenceconfidence (输出控制) real(-array) → HTupleSequence[float]HTupleHtuple (real) (double) (double) (double)
Confidence(s) of the class(es) of the character.
结果
如果参数有效，算子
do_ocr_single_class_mlpdo_ocr_single_class_mlpDoOcrSingleClassMlpDoOcrSingleClassMlpDoOcrSingleClassMlpdo_ocr_single_class_mlp 返回值 2 ( H_MSG_TRUE )。如有必要，则抛出异常。
可能的前趋
trainf_ocr_class_mlptrainf_ocr_class_mlpTrainfOcrClassMlpTrainfOcrClassMlpTrainfOcrClassMlptrainf_ocr_class_mlp,
read_ocr_class_mlpread_ocr_class_mlpReadOcrClassMlpReadOcrClassMlpReadOcrClassMlpread_ocr_class_mlp
替代
do_ocr_multi_class_mlpdo_ocr_multi_class_mlpDoOcrMultiClassMlpDoOcrMultiClassMlpDoOcrMultiClassMlpdo_ocr_multi_class_mlp
另见
create_ocr_class_mlpcreate_ocr_class_mlpCreateOcrClassMlpCreateOcrClassMlpCreateOcrClassMlpcreate_ocr_class_mlp,
classify_class_mlpclassify_class_mlpClassifyClassMlpClassifyClassMlpClassifyClassMlpclassify_class_mlp
模块
光学字符识别/光学字符验证