// // This file is auto-generated. Please don't modify it! // package org.opencv.text; import org.opencv.core.Mat; import org.opencv.text.BaseOCR; import org.opencv.text.OCRBeamSearchDecoder; import org.opencv.text.OCRBeamSearchDecoder_ClassifierCallback; // C++: class OCRBeamSearchDecoder /** * OCRBeamSearchDecoder class provides an interface for OCR using Beam Search algorithm. * * Note: * */ public class OCRBeamSearchDecoder extends BaseOCR { protected OCRBeamSearchDecoder(long addr) { super(addr); } // internal usage only public static OCRBeamSearchDecoder __fromPtr__(long addr) { return new OCRBeamSearchDecoder(addr); } // // C++: String cv::text::OCRBeamSearchDecoder::run(Mat image, int min_confidence, int component_level = 0) // /** * 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. * * @param 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). * * @param component_level Only OCR_LEVEL_WORD is supported. * @param min_confidence automatically generated * @return automatically generated */ public String run(Mat image, int min_confidence, int component_level) { return run_0(nativeObj, image.nativeObj, 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. * * @param 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). * * @param min_confidence automatically generated * @return automatically generated */ public String run(Mat image, int min_confidence) { return run_1(nativeObj, image.nativeObj, min_confidence); } // // C++: String cv::text::OCRBeamSearchDecoder::run(Mat image, Mat mask, int min_confidence, int component_level = 0) // public String run(Mat image, Mat mask, int min_confidence, int component_level) { return run_2(nativeObj, image.nativeObj, mask.nativeObj, min_confidence, component_level); } public String run(Mat image, Mat mask, int min_confidence) { return run_3(nativeObj, image.nativeObj, mask.nativeObj, min_confidence); } // // C++: static Ptr_OCRBeamSearchDecoder cv::text::OCRBeamSearchDecoder::create(Ptr_OCRBeamSearchDecoder_ClassifierCallback classifier, string vocabulary, Mat transition_probabilities_table, Mat emission_probabilities_table, text_decoder_mode mode = OCR_DECODER_VITERBI, int beam_size = 500) // /** * Creates an instance of the OCRBeamSearchDecoder class. Initializes HMMDecoder. * * @param classifier The character classifier with built in feature extractor. * * @param vocabulary The language vocabulary (chars when ASCII English text). vocabulary.size() * must be equal to the number of classes of the classifier. * * @param transition_probabilities_table Table with transition probabilities between character * pairs. cols == rows == vocabulary.size(). * * @param emission_probabilities_table Table with observation emission probabilities. cols == * rows == vocabulary.size(). * * @param mode HMM Decoding algorithm. Only OCR_DECODER_VITERBI is available for the moment * (<http://en.wikipedia.org/wiki/Viterbi_algorithm>). * * @param beam_size Size of the beam in Beam Search algorithm. * @return automatically generated */ public static OCRBeamSearchDecoder create(OCRBeamSearchDecoder_ClassifierCallback classifier, String vocabulary, Mat transition_probabilities_table, Mat emission_probabilities_table, int mode, int beam_size) { return OCRBeamSearchDecoder.__fromPtr__(create_0(classifier.getNativeObjAddr(), vocabulary, transition_probabilities_table.nativeObj, emission_probabilities_table.nativeObj, mode, beam_size)); } /** * Creates an instance of the OCRBeamSearchDecoder class. Initializes HMMDecoder. * * @param classifier The character classifier with built in feature extractor. * * @param vocabulary The language vocabulary (chars when ASCII English text). vocabulary.size() * must be equal to the number of classes of the classifier. * * @param transition_probabilities_table Table with transition probabilities between character * pairs. cols == rows == vocabulary.size(). * * @param emission_probabilities_table Table with observation emission probabilities. cols == * rows == vocabulary.size(). * * @param mode HMM Decoding algorithm. Only OCR_DECODER_VITERBI is available for the moment * (<http://en.wikipedia.org/wiki/Viterbi_algorithm>). * * @return automatically generated */ public static OCRBeamSearchDecoder create(OCRBeamSearchDecoder_ClassifierCallback classifier, String vocabulary, Mat transition_probabilities_table, Mat emission_probabilities_table, int mode) { return OCRBeamSearchDecoder.__fromPtr__(create_1(classifier.getNativeObjAddr(), vocabulary, transition_probabilities_table.nativeObj, emission_probabilities_table.nativeObj, mode)); } /** * Creates an instance of the OCRBeamSearchDecoder class. Initializes HMMDecoder. * * @param classifier The character classifier with built in feature extractor. * * @param vocabulary The language vocabulary (chars when ASCII English text). vocabulary.size() * must be equal to the number of classes of the classifier. * * @param transition_probabilities_table Table with transition probabilities between character * pairs. cols == rows == vocabulary.size(). * * @param emission_probabilities_table Table with observation emission probabilities. cols == * rows == vocabulary.size(). * * (<http://en.wikipedia.org/wiki/Viterbi_algorithm>). * * @return automatically generated */ public static OCRBeamSearchDecoder create(OCRBeamSearchDecoder_ClassifierCallback classifier, String vocabulary, Mat transition_probabilities_table, Mat emission_probabilities_table) { return OCRBeamSearchDecoder.__fromPtr__(create_2(classifier.getNativeObjAddr(), vocabulary, transition_probabilities_table.nativeObj, emission_probabilities_table.nativeObj)); } @Override protected void finalize() throws Throwable { delete(nativeObj); } // C++: String cv::text::OCRBeamSearchDecoder::run(Mat image, int min_confidence, int component_level = 0) private static native String run_0(long nativeObj, long image_nativeObj, int min_confidence, int component_level); private static native String run_1(long nativeObj, long image_nativeObj, int min_confidence); // C++: String cv::text::OCRBeamSearchDecoder::run(Mat image, Mat mask, int min_confidence, int component_level = 0) private static native String run_2(long nativeObj, long image_nativeObj, long mask_nativeObj, int min_confidence, int component_level); private static native String run_3(long nativeObj, long image_nativeObj, long mask_nativeObj, int min_confidence); // C++: static Ptr_OCRBeamSearchDecoder cv::text::OCRBeamSearchDecoder::create(Ptr_OCRBeamSearchDecoder_ClassifierCallback classifier, string vocabulary, Mat transition_probabilities_table, Mat emission_probabilities_table, text_decoder_mode mode = OCR_DECODER_VITERBI, int beam_size = 500) private static native long create_0(long classifier_nativeObj, String vocabulary, long transition_probabilities_table_nativeObj, long emission_probabilities_table_nativeObj, int mode, int beam_size); private static native long create_1(long classifier_nativeObj, String vocabulary, long transition_probabilities_table_nativeObj, long emission_probabilities_table_nativeObj, int mode); private static native long create_2(long classifier_nativeObj, String vocabulary, long transition_probabilities_table_nativeObj, long emission_probabilities_table_nativeObj); // native support for java finalize() private static native void delete(long nativeObj); }