OCRBeamSearchDecoder class provides an interface for OCR using Beam Search algorithm.
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#include <opencv2/text/ocr.hpp>
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virtual void | run (Mat &image, std::string &output_text, std::vector< Rect > *component_rects=NULL, std::vector< std::string > *component_texts=NULL, std::vector< float > *component_confidences=NULL, int component_level=0) CV_OVERRIDE |
| Recognize text using Beam Search. More...
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virtual void | run (Mat &image, Mat &mask, std::string &output_text, std::vector< Rect > *component_rects=NULL, std::vector< std::string > *component_texts=NULL, std::vector< float > *component_confidences=NULL, int component_level=0) CV_OVERRIDE |
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String | run (InputArray image, int min_confidence, int component_level=0) |
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String | run (InputArray image, InputArray mask, int min_confidence, int component_level=0) |
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virtual | ~BaseOCR () |
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static Ptr< OCRBeamSearchDecoder > | create (const Ptr< OCRBeamSearchDecoder::ClassifierCallback > classifier, const std::string &vocabulary, InputArray transition_probabilities_table, InputArray emission_probabilities_table, text::decoder_mode mode=OCR_DECODER_VITERBI, int beam_size=500) |
| Creates an instance of the OCRBeamSearchDecoder class. Initializes HMMDecoder. More...
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static Ptr< OCRBeamSearchDecoder > | create (const String &filename, const String &vocabulary, InputArray transition_probabilities_table, InputArray emission_probabilities_table, text::decoder_mode mode=OCR_DECODER_VITERBI, int beam_size=500) |
| Creates an instance of the OCRBeamSearchDecoder class. Initializes HMMDecoder from the specified path. More...
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OCRBeamSearchDecoder class provides an interface for OCR using Beam Search algorithm.
- Note
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◆ create() [1/2]
Python: |
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| retval | = | cv.text.OCRBeamSearchDecoder_create( | classifier, vocabulary, transition_probabilities_table, emission_probabilities_table[, mode[, beam_size]] | ) |
Creates an instance of the OCRBeamSearchDecoder class. Initializes HMMDecoder.
- Parameters
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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. |
◆ create() [2/2]
Python: |
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| retval | = | cv.text.OCRBeamSearchDecoder_create( | classifier, vocabulary, transition_probabilities_table, emission_probabilities_table[, mode[, beam_size]] | ) |
Creates an instance of the OCRBeamSearchDecoder class. Initializes HMMDecoder from the specified path.
This is an overloaded member function, provided for convenience. It differs from the above function only in what argument(s) it accepts.
◆ run() [1/4]
virtual void cv::text::OCRBeamSearchDecoder::run |
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Mat & |
image, |
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std::string & |
output_text, |
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std::vector< Rect > * |
component_rects = NULL , |
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std::vector< std::string > * |
component_texts = NULL , |
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std::vector< float > * |
component_confidences = NULL , |
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int |
component_level = 0 |
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virtual |
Python: |
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| retval | = | cv.text_OCRBeamSearchDecoder.run( | image, min_confidence[, component_level] | ) |
| retval | = | cv.text_OCRBeamSearchDecoder.run( | image, mask, min_confidence[, 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
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image | Input binary image CV_8UC1 with a single text line (or word). |
output_text | Output text. Most likely character sequence found by the HMM decoder. |
component_rects | If provided the method will output a list of Rects for the individual text elements found (e.g. words). |
component_texts | If provided the method will output a list of text strings for the recognition of individual text elements found (e.g. words). |
component_confidences | If provided the method will output a list of confidence values for the recognition of individual text elements found (e.g. words). |
component_level | Only OCR_LEVEL_WORD is supported. |
Implements cv::text::BaseOCR.
◆ run() [2/4]
virtual void cv::text::OCRBeamSearchDecoder::run |
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Mat & |
image, |
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Mat & |
mask, |
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std::string & |
output_text, |
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std::vector< Rect > * |
component_rects = NULL , |
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std::vector< std::string > * |
component_texts = NULL , |
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std::vector< float > * |
component_confidences = NULL , |
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int |
component_level = 0 |
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) |
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virtual |
Python: |
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| retval | = | cv.text_OCRBeamSearchDecoder.run( | image, min_confidence[, component_level] | ) |
| retval | = | cv.text_OCRBeamSearchDecoder.run( | image, mask, min_confidence[, component_level] | ) |
◆ run() [3/4]
String cv::text::OCRBeamSearchDecoder::run |
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InputArray |
image, |
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int |
min_confidence, |
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int |
component_level = 0 |
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Python: |
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| retval | = | cv.text_OCRBeamSearchDecoder.run( | image, min_confidence[, component_level] | ) |
| retval | = | cv.text_OCRBeamSearchDecoder.run( | image, mask, min_confidence[, component_level] | ) |
◆ run() [4/4]
Python: |
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| retval | = | cv.text_OCRBeamSearchDecoder.run( | image, min_confidence[, component_level] | ) |
| retval | = | cv.text_OCRBeamSearchDecoder.run( | image, mask, min_confidence[, component_level] | ) |
◆ beam_size
int cv::text::OCRBeamSearchDecoder::beam_size |
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protected |
◆ classifier
◆ emission_p
Mat cv::text::OCRBeamSearchDecoder::emission_p |
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◆ mode
◆ transition_p
Mat cv::text::OCRBeamSearchDecoder::transition_p |
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◆ vocabulary
std::string cv::text::OCRBeamSearchDecoder::vocabulary |
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protected |
The documentation for this class was generated from the following file: