Package org.opencv.dnn
Class TextRecognitionModel
- java.lang.Object
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- org.opencv.dnn.Model
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- org.opencv.dnn.TextRecognitionModel
 
 
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 public class TextRecognitionModel extends Model This class represents high-level API for text recognition networks. TextRecognitionModel allows to set params for preprocessing input image. TextRecognitionModel creates net from file with trained weights and config, sets preprocessing input, runs forward pass and return recognition result. For TextRecognitionModel, CRNN-CTC is supported.
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Constructor SummaryConstructors Modifier Constructor Description protectedTextRecognitionModel(long addr)TextRecognitionModel(java.lang.String model)Create text recognition model from network represented in one of the supported formats Call setDecodeType() and setVocabulary() after constructor to initialize the decoding methodTextRecognitionModel(java.lang.String model, java.lang.String config)Create text recognition model from network represented in one of the supported formats Call setDecodeType() and setVocabulary() after constructor to initialize the decoding methodTextRecognitionModel(Net network)Create Text Recognition model from deep learning network Call setDecodeType() and setVocabulary() after constructor to initialize the decoding method
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Method SummaryAll Methods Static Methods Instance Methods Concrete Methods Modifier and Type Method Description static TextRecognitionModel__fromPtr__(long addr)protected voidfinalize()java.lang.StringgetDecodeType()Get the decoding methodjava.util.List<java.lang.String>getVocabulary()Get the vocabulary for recognition.java.lang.Stringrecognize(Mat frame)Given theinputframe, create input blob, run net and return recognition resultvoidrecognize(Mat frame, java.util.List<Mat> roiRects, java.util.List<java.lang.String> results)Given theinputframe, create input blob, run net and return recognition resultTextRecognitionModelsetDecodeOptsCTCPrefixBeamSearch(int beamSize)Set the decoding method options for"CTC-prefix-beam-search"decode usageTextRecognitionModelsetDecodeOptsCTCPrefixBeamSearch(int beamSize, int vocPruneSize)Set the decoding method options for"CTC-prefix-beam-search"decode usageTextRecognitionModelsetDecodeType(java.lang.String decodeType)Set the decoding method of translating the network output into stringTextRecognitionModelsetVocabulary(java.util.List<java.lang.String> vocabulary)Set the vocabulary for recognition.- 
Methods inherited from class org.opencv.dnn.ModelenableWinograd, getNativeObjAddr, predict, setInputCrop, setInputMean, setInputParams, setInputParams, setInputParams, setInputParams, setInputParams, setInputParams, setInputScale, setInputSize, setInputSize, setInputSwapRB, setPreferableBackend, setPreferableTarget
 
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Constructor Detail- 
TextRecognitionModelprotected TextRecognitionModel(long addr) 
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TextRecognitionModelpublic TextRecognitionModel(Net network) Create Text Recognition model from deep learning network Call setDecodeType() and setVocabulary() after constructor to initialize the decoding method- Parameters:
- network- Net object
 
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TextRecognitionModelpublic TextRecognitionModel(java.lang.String model, java.lang.String config)Create text recognition model from network represented in one of the supported formats Call setDecodeType() and setVocabulary() after constructor to initialize the decoding method- Parameters:
- model- Binary file contains trained weights
- config- Text file contains network configuration
 
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TextRecognitionModelpublic TextRecognitionModel(java.lang.String model) Create text recognition model from network represented in one of the supported formats Call setDecodeType() and setVocabulary() after constructor to initialize the decoding method- Parameters:
- model- Binary file contains trained weights
 
 
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Method Detail- 
__fromPtr__public static TextRecognitionModel __fromPtr__(long addr) 
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setDecodeTypepublic TextRecognitionModel setDecodeType(java.lang.String decodeType) Set the decoding method of translating the network output into string- Parameters:
- decodeType- The decoding method of translating the network output into string, currently supported type: -- "CTC-greedy"greedy decoding for the output of CTC-based methods -- "CTC-prefix-beam-search"Prefix beam search decoding for the output of CTC-based methods
- Returns:
- automatically generated
 
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getDecodeTypepublic java.lang.String getDecodeType() Get the decoding method- Returns:
- the decoding method
 
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setDecodeOptsCTCPrefixBeamSearchpublic TextRecognitionModel setDecodeOptsCTCPrefixBeamSearch(int beamSize, int vocPruneSize) Set the decoding method options for"CTC-prefix-beam-search"decode usage- Parameters:
- beamSize- Beam size for search
- vocPruneSize- Parameter to optimize big vocabulary search, only take top- vocPruneSizetokens in each search step,- vocPruneSize<= 0 stands for disable this prune.
- Returns:
- automatically generated
 
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setDecodeOptsCTCPrefixBeamSearchpublic TextRecognitionModel setDecodeOptsCTCPrefixBeamSearch(int beamSize) Set the decoding method options for"CTC-prefix-beam-search"decode usage- Parameters:
- beamSize- Beam size for search only take top- vocPruneSizetokens in each search step,- vocPruneSize<= 0 stands for disable this prune.
- Returns:
- automatically generated
 
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setVocabularypublic TextRecognitionModel setVocabulary(java.util.List<java.lang.String> vocabulary) Set the vocabulary for recognition.- Parameters:
- vocabulary- the associated vocabulary of the network.
- Returns:
- automatically generated
 
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getVocabularypublic java.util.List<java.lang.String> getVocabulary() Get the vocabulary for recognition.- Returns:
- vocabulary the associated vocabulary
 
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recognizepublic java.lang.String recognize(Mat frame) Given theinputframe, create input blob, run net and return recognition result- Parameters:
- frame- The input image
- Returns:
- The text recognition result
 
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recognizepublic void recognize(Mat frame, java.util.List<Mat> roiRects, java.util.List<java.lang.String> results) Given theinputframe, create input blob, run net and return recognition result- Parameters:
- frame- The input image
- roiRects- List of text detection regions of interest (cv::Rect, CV_32SC4). ROIs is be cropped as the network inputs
- results- A set of text recognition results.
 
 
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