Package org.opencv.text
Class OCRBeamSearchDecoder
- java.lang.Object
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- org.opencv.text.BaseOCR
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- org.opencv.text.OCRBeamSearchDecoder
 
 
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 public class OCRBeamSearchDecoder extends BaseOCR OCRBeamSearchDecoder class provides an interface for OCR using Beam Search algorithm. Note:- (C++) An example on using OCRBeamSearchDecoder recognition combined with scene text detection can be found at the demo sample: <https://github.com/opencv/opencv_contrib/blob/master/modules/text/samples/word_recognition.cpp>
 
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Constructor SummaryConstructors Modifier Constructor Description protectedOCRBeamSearchDecoder(long addr)
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Method SummaryAll Methods Static Methods Instance Methods Concrete Methods Modifier and Type Method Description static OCRBeamSearchDecoder__fromPtr__(long addr)static OCRBeamSearchDecodercreate(OCRBeamSearchDecoder_ClassifierCallback classifier, String vocabulary, Mat transition_probabilities_table, Mat emission_probabilities_table)Creates an instance of the OCRBeamSearchDecoder class.static OCRBeamSearchDecodercreate(OCRBeamSearchDecoder_ClassifierCallback classifier, String vocabulary, Mat transition_probabilities_table, Mat emission_probabilities_table, int mode)Creates an instance of the OCRBeamSearchDecoder class.static OCRBeamSearchDecodercreate(OCRBeamSearchDecoder_ClassifierCallback classifier, String vocabulary, Mat transition_probabilities_table, Mat emission_probabilities_table, int mode, int beam_size)Creates an instance of the OCRBeamSearchDecoder class.protected voidfinalize()Stringrun(Mat image, int min_confidence)Recognize text using Beam Search.Stringrun(Mat image, int min_confidence, int component_level)Recognize text using Beam Search.Stringrun(Mat image, Mat mask, int min_confidence)Stringrun(Mat image, Mat mask, int min_confidence, int component_level)- 
Methods inherited from class org.opencv.text.BaseOCRgetNativeObjAddr
 
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Method Detail- 
__fromPtr__public static OCRBeamSearchDecoder __fromPtr__(long addr) 
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runpublic String run(Mat image, int min_confidence, int component_level) Recognize text using Beam Search. Takes image on input and returns recognized text in the output_text parameter. Optionally provides also the Rects for individual text elements found (e.g. words), and the list of those text elements with their confidence values.- Parameters:
- image- Input binary image CV_8UC1 with a single text line (or word). text elements found (e.g. words). recognition of individual text elements found (e.g. words). for the recognition of individual text elements found (e.g. words).
- component_level- Only OCR_LEVEL_WORD is supported.
- min_confidence- automatically generated
- Returns:
- automatically generated
 
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runpublic String run(Mat image, int min_confidence) Recognize text using Beam Search. Takes image on input and returns recognized text in the output_text parameter. Optionally provides also the Rects for individual text elements found (e.g. words), and the list of those text elements with their confidence values.- Parameters:
- image- Input binary image CV_8UC1 with a single text line (or word). text elements found (e.g. words). recognition of individual text elements found (e.g. words). for the recognition of individual text elements found (e.g. words).
- min_confidence- automatically generated
- Returns:
- automatically generated
 
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createpublic static OCRBeamSearchDecoder create(OCRBeamSearchDecoder_ClassifierCallback classifier, String vocabulary, Mat transition_probabilities_table, Mat emission_probabilities_table, int mode, int beam_size) Creates an instance of the OCRBeamSearchDecoder class. Initializes HMMDecoder.- Parameters:
- classifier- The character classifier with built in feature extractor.
- vocabulary- The language vocabulary (chars when ASCII English text). vocabulary.size() must be equal to the number of classes of the classifier.
- transition_probabilities_table- Table with transition probabilities between character pairs. cols == rows == vocabulary.size().
- emission_probabilities_table- Table with observation emission probabilities. cols == rows == vocabulary.size().
- mode- HMM Decoding algorithm. Only OCR_DECODER_VITERBI is available for the moment (<http://en.wikipedia.org/wiki/Viterbi_algorithm>).
- beam_size- Size of the beam in Beam Search algorithm.
- Returns:
- automatically generated
 
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createpublic static OCRBeamSearchDecoder create(OCRBeamSearchDecoder_ClassifierCallback classifier, String vocabulary, Mat transition_probabilities_table, Mat emission_probabilities_table, int mode) Creates an instance of the OCRBeamSearchDecoder class. Initializes HMMDecoder.- Parameters:
- classifier- The character classifier with built in feature extractor.
- vocabulary- The language vocabulary (chars when ASCII English text). vocabulary.size() must be equal to the number of classes of the classifier.
- transition_probabilities_table- Table with transition probabilities between character pairs. cols == rows == vocabulary.size().
- emission_probabilities_table- Table with observation emission probabilities. cols == rows == vocabulary.size().
- mode- HMM Decoding algorithm. Only OCR_DECODER_VITERBI is available for the moment (<http://en.wikipedia.org/wiki/Viterbi_algorithm>).
- Returns:
- automatically generated
 
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createpublic static OCRBeamSearchDecoder create(OCRBeamSearchDecoder_ClassifierCallback classifier, String vocabulary, Mat transition_probabilities_table, Mat emission_probabilities_table) Creates an instance of the OCRBeamSearchDecoder class. Initializes HMMDecoder.- Parameters:
- classifier- The character classifier with built in feature extractor.
- vocabulary- The language vocabulary (chars when ASCII English text). vocabulary.size() must be equal to the number of classes of the classifier.
- transition_probabilities_table- Table with transition probabilities between character pairs. cols == rows == vocabulary.size().
- emission_probabilities_table- Table with observation emission probabilities. cols == rows == vocabulary.size(). (<http://en.wikipedia.org/wiki/Viterbi_algorithm>).
- Returns:
- automatically generated
 
 
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