Package org.opencv.text
Class OCRBeamSearchDecoder
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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 Summary
Constructors Modifier Constructor Description protected
OCRBeamSearchDecoder(long addr)
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Method Summary
All Methods Static Methods Instance Methods Concrete Methods Modifier and Type Method Description static OCRBeamSearchDecoder
__fromPtr__(long addr)
static OCRBeamSearchDecoder
create(OCRBeamSearchDecoder_ClassifierCallback classifier, java.lang.String vocabulary, Mat transition_probabilities_table, Mat emission_probabilities_table)
Creates an instance of the OCRBeamSearchDecoder class.static OCRBeamSearchDecoder
create(OCRBeamSearchDecoder_ClassifierCallback classifier, java.lang.String vocabulary, Mat transition_probabilities_table, Mat emission_probabilities_table, int mode)
Creates an instance of the OCRBeamSearchDecoder class.static OCRBeamSearchDecoder
create(OCRBeamSearchDecoder_ClassifierCallback classifier, java.lang.String vocabulary, Mat transition_probabilities_table, Mat emission_probabilities_table, int mode, int beam_size)
Creates an instance of the OCRBeamSearchDecoder class.protected void
finalize()
java.lang.String
run(Mat image, int min_confidence)
Recognize text using Beam Search.java.lang.String
run(Mat image, int min_confidence, int component_level)
Recognize text using Beam Search.java.lang.String
run(Mat image, Mat mask, int min_confidence)
java.lang.String
run(Mat image, Mat mask, int min_confidence, int component_level)
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Methods inherited from class org.opencv.text.BaseOCR
getNativeObjAddr
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Method Detail
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__fromPtr__
public static OCRBeamSearchDecoder __fromPtr__(long addr)
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run
public java.lang.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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run
public java.lang.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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create
public static OCRBeamSearchDecoder create(OCRBeamSearchDecoder_ClassifierCallback classifier, java.lang.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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create
public static OCRBeamSearchDecoder create(OCRBeamSearchDecoder_ClassifierCallback classifier, java.lang.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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create
public static OCRBeamSearchDecoder create(OCRBeamSearchDecoder_ClassifierCallback classifier, java.lang.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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