org.opencv.text.OCRHMMDecoder Maven / Gradle / Ivy
//
// 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.OCRHMMDecoder;
// C++: class OCRHMMDecoder
/**
* OCRHMMDecoder class provides an interface for OCR using Hidden Markov Models.
*
* Note:
*
* -
* (C++) An example on using OCRHMMDecoder recognition combined with scene text detection can
* be found at the webcam_demo sample:
* <https://github.com/opencv/opencv_contrib/blob/master/modules/text/samples/webcam_demo.cpp>
*
*
*/
public class OCRHMMDecoder extends BaseOCR {
protected OCRHMMDecoder(long addr) { super(addr); }
// internal usage only
public static OCRHMMDecoder __fromPtr__(long addr) { return new OCRHMMDecoder(addr); }
//
// C++: static Ptr_OCRHMMDecoder cv::text::OCRHMMDecoder::create(Ptr_OCRHMMDecoder_ClassifierCallback classifier, String vocabulary, Mat transition_probabilities_table, Mat emission_probabilities_table, int mode = OCR_DECODER_VITERBI)
//
// Unknown type 'Ptr_OCRHMMDecoder_ClassifierCallback' (I), skipping the function
//
// C++: static Ptr_OCRHMMDecoder cv::text::OCRHMMDecoder::create(String filename, String vocabulary, Mat transition_probabilities_table, Mat emission_probabilities_table, int mode = OCR_DECODER_VITERBI, int classifier = OCR_KNN_CLASSIFIER)
//
/**
* Creates an instance of the OCRHMMDecoder class. Loads and initializes HMMDecoder from the specified path
*
*
* @param filename automatically generated
* @param vocabulary automatically generated
* @param transition_probabilities_table automatically generated
* @param emission_probabilities_table automatically generated
* @param mode automatically generated
* @param classifier automatically generated
* @return automatically generated
*/
public static OCRHMMDecoder create(String filename, String vocabulary, Mat transition_probabilities_table, Mat emission_probabilities_table, int mode, int classifier) {
return OCRHMMDecoder.__fromPtr__(create_0(filename, vocabulary, transition_probabilities_table.nativeObj, emission_probabilities_table.nativeObj, mode, classifier));
}
/**
* Creates an instance of the OCRHMMDecoder class. Loads and initializes HMMDecoder from the specified path
*
*
* @param filename automatically generated
* @param vocabulary automatically generated
* @param transition_probabilities_table automatically generated
* @param emission_probabilities_table automatically generated
* @param mode automatically generated
* @return automatically generated
*/
public static OCRHMMDecoder create(String filename, String vocabulary, Mat transition_probabilities_table, Mat emission_probabilities_table, int mode) {
return OCRHMMDecoder.__fromPtr__(create_1(filename, vocabulary, transition_probabilities_table.nativeObj, emission_probabilities_table.nativeObj, mode));
}
/**
* Creates an instance of the OCRHMMDecoder class. Loads and initializes HMMDecoder from the specified path
*
*
* @param filename automatically generated
* @param vocabulary automatically generated
* @param transition_probabilities_table automatically generated
* @param emission_probabilities_table automatically generated
* @return automatically generated
*/
public static OCRHMMDecoder create(String filename, String vocabulary, Mat transition_probabilities_table, Mat emission_probabilities_table) {
return OCRHMMDecoder.__fromPtr__(create_2(filename, vocabulary, transition_probabilities_table.nativeObj, emission_probabilities_table.nativeObj));
}
//
// C++: String cv::text::OCRHMMDecoder::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_0(nativeObj, image.nativeObj, mask.nativeObj, min_confidence, component_level);
}
public String run(Mat image, Mat mask, int min_confidence) {
return run_1(nativeObj, image.nativeObj, mask.nativeObj, min_confidence);
}
//
// C++: String cv::text::OCRHMMDecoder::run(Mat image, int min_confidence, int component_level = 0)
//
/**
* Recognize text using HMM.
*
* Takes an image and a mask (where each connected component corresponds to a segmented character)
* 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 image CV_8UC1 or CV_8UC3 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_2(nativeObj, image.nativeObj, min_confidence, component_level);
}
/**
* Recognize text using HMM.
*
* Takes an image and a mask (where each connected component corresponds to a segmented character)
* 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 image CV_8UC1 or CV_8UC3 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_3(nativeObj, image.nativeObj, min_confidence);
}
@Override
protected void finalize() throws Throwable {
delete(nativeObj);
}
// C++: static Ptr_OCRHMMDecoder cv::text::OCRHMMDecoder::create(String filename, String vocabulary, Mat transition_probabilities_table, Mat emission_probabilities_table, int mode = OCR_DECODER_VITERBI, int classifier = OCR_KNN_CLASSIFIER)
private static native long create_0(String filename, String vocabulary, long transition_probabilities_table_nativeObj, long emission_probabilities_table_nativeObj, int mode, int classifier);
private static native long create_1(String filename, String vocabulary, long transition_probabilities_table_nativeObj, long emission_probabilities_table_nativeObj, int mode);
private static native long create_2(String filename, String vocabulary, long transition_probabilities_table_nativeObj, long emission_probabilities_table_nativeObj);
// C++: String cv::text::OCRHMMDecoder::run(Mat image, Mat mask, int min_confidence, int component_level = 0)
private static native String run_0(long nativeObj, long image_nativeObj, long mask_nativeObj, int min_confidence, int component_level);
private static native String run_1(long nativeObj, long image_nativeObj, long mask_nativeObj, int min_confidence);
// C++: String cv::text::OCRHMMDecoder::run(Mat image, int min_confidence, int component_level = 0)
private static native String run_2(long nativeObj, long image_nativeObj, int min_confidence, int component_level);
private static native String run_3(long nativeObj, long image_nativeObj, int min_confidence);
// native support for java finalize()
private static native void delete(long nativeObj);
}
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