org.opencv.dnn.TextDetectionModel_DB Maven / Gradle / Ivy
//
// This file is auto-generated. Please don't modify it!
//
package org.opencv.dnn;
import org.opencv.dnn.Net;
import org.opencv.dnn.TextDetectionModel;
import org.opencv.dnn.TextDetectionModel_DB;
// C++: class TextDetectionModel_DB
/**
* This class represents high-level API for text detection DL networks compatible with DB model.
*
* Related publications: CITE: liao2020real
* Paper: https://arxiv.org/abs/1911.08947
* For more information about the hyper-parameters setting, please refer to https://github.com/MhLiao/DB
*
* Configurable parameters:
* - (float) binaryThreshold - The threshold of the binary map. It is usually set to 0.3.
* - (float) polygonThreshold - The threshold of text polygons. It is usually set to 0.5, 0.6, and 0.7. Default is 0.5f
* - (double) unclipRatio - The unclip ratio of the detected text region, which determines the output size. It is usually set to 2.0.
* - (int) maxCandidates - The max number of the output results.
*/
public class TextDetectionModel_DB extends TextDetectionModel {
protected TextDetectionModel_DB(long addr) { super(addr); }
// internal usage only
public static TextDetectionModel_DB __fromPtr__(long addr) { return new TextDetectionModel_DB(addr); }
//
// C++: cv::dnn::TextDetectionModel_DB::TextDetectionModel_DB(Net network)
//
/**
* Create text detection algorithm from deep learning network.
* @param network Net object.
*/
public TextDetectionModel_DB(Net network) {
super(TextDetectionModel_DB_0(network.nativeObj));
}
//
// C++: cv::dnn::TextDetectionModel_DB::TextDetectionModel_DB(string model, string config = "")
//
/**
* Create text detection model from network represented in one of the supported formats.
* An order of {@code model} and {@code config} arguments does not matter.
* @param model Binary file contains trained weights.
* @param config Text file contains network configuration.
*/
public TextDetectionModel_DB(String model, String config) {
super(TextDetectionModel_DB_1(model, config));
}
/**
* Create text detection model from network represented in one of the supported formats.
* An order of {@code model} and {@code config} arguments does not matter.
* @param model Binary file contains trained weights.
*/
public TextDetectionModel_DB(String model) {
super(TextDetectionModel_DB_2(model));
}
//
// C++: TextDetectionModel_DB cv::dnn::TextDetectionModel_DB::setBinaryThreshold(float binaryThreshold)
//
public TextDetectionModel_DB setBinaryThreshold(float binaryThreshold) {
return new TextDetectionModel_DB(setBinaryThreshold_0(nativeObj, binaryThreshold));
}
//
// C++: float cv::dnn::TextDetectionModel_DB::getBinaryThreshold()
//
public float getBinaryThreshold() {
return getBinaryThreshold_0(nativeObj);
}
//
// C++: TextDetectionModel_DB cv::dnn::TextDetectionModel_DB::setPolygonThreshold(float polygonThreshold)
//
public TextDetectionModel_DB setPolygonThreshold(float polygonThreshold) {
return new TextDetectionModel_DB(setPolygonThreshold_0(nativeObj, polygonThreshold));
}
//
// C++: float cv::dnn::TextDetectionModel_DB::getPolygonThreshold()
//
public float getPolygonThreshold() {
return getPolygonThreshold_0(nativeObj);
}
//
// C++: TextDetectionModel_DB cv::dnn::TextDetectionModel_DB::setUnclipRatio(double unclipRatio)
//
public TextDetectionModel_DB setUnclipRatio(double unclipRatio) {
return new TextDetectionModel_DB(setUnclipRatio_0(nativeObj, unclipRatio));
}
//
// C++: double cv::dnn::TextDetectionModel_DB::getUnclipRatio()
//
public double getUnclipRatio() {
return getUnclipRatio_0(nativeObj);
}
//
// C++: TextDetectionModel_DB cv::dnn::TextDetectionModel_DB::setMaxCandidates(int maxCandidates)
//
public TextDetectionModel_DB setMaxCandidates(int maxCandidates) {
return new TextDetectionModel_DB(setMaxCandidates_0(nativeObj, maxCandidates));
}
//
// C++: int cv::dnn::TextDetectionModel_DB::getMaxCandidates()
//
public int getMaxCandidates() {
return getMaxCandidates_0(nativeObj);
}
@Override
protected void finalize() throws Throwable {
delete(nativeObj);
}
// C++: cv::dnn::TextDetectionModel_DB::TextDetectionModel_DB(Net network)
private static native long TextDetectionModel_DB_0(long network_nativeObj);
// C++: cv::dnn::TextDetectionModel_DB::TextDetectionModel_DB(string model, string config = "")
private static native long TextDetectionModel_DB_1(String model, String config);
private static native long TextDetectionModel_DB_2(String model);
// C++: TextDetectionModel_DB cv::dnn::TextDetectionModel_DB::setBinaryThreshold(float binaryThreshold)
private static native long setBinaryThreshold_0(long nativeObj, float binaryThreshold);
// C++: float cv::dnn::TextDetectionModel_DB::getBinaryThreshold()
private static native float getBinaryThreshold_0(long nativeObj);
// C++: TextDetectionModel_DB cv::dnn::TextDetectionModel_DB::setPolygonThreshold(float polygonThreshold)
private static native long setPolygonThreshold_0(long nativeObj, float polygonThreshold);
// C++: float cv::dnn::TextDetectionModel_DB::getPolygonThreshold()
private static native float getPolygonThreshold_0(long nativeObj);
// C++: TextDetectionModel_DB cv::dnn::TextDetectionModel_DB::setUnclipRatio(double unclipRatio)
private static native long setUnclipRatio_0(long nativeObj, double unclipRatio);
// C++: double cv::dnn::TextDetectionModel_DB::getUnclipRatio()
private static native double getUnclipRatio_0(long nativeObj);
// C++: TextDetectionModel_DB cv::dnn::TextDetectionModel_DB::setMaxCandidates(int maxCandidates)
private static native long setMaxCandidates_0(long nativeObj, int maxCandidates);
// C++: int cv::dnn::TextDetectionModel_DB::getMaxCandidates()
private static native int getMaxCandidates_0(long nativeObj);
// native support for java finalize()
private static native void delete(long nativeObj);
}