//
// This file is auto-generated. Please don't modify it!
//
package org.opencv.imgproc;
import org.opencv.core.Algorithm;
import org.opencv.core.Mat;
import org.opencv.core.Size;
// C++: class LineSegmentDetector
/**
* Line segment detector class
*
* following the algorithm described at CITE: Rafael12 .
*
* <b>Note:</b> Implementation has been removed from OpenCV version 3.4.6 to 3.4.15 and version 4.1.0 to 4.5.3 due original code license conflict.
* restored again after [Computation of a NFA](https://github.com/rafael-grompone-von-gioi/binomial_nfa) code published under the MIT license.
*/
public class LineSegmentDetector extends Algorithm {
protected LineSegmentDetector(long addr) { super(addr); }
// internal usage only
public static LineSegmentDetector __fromPtr__(long addr) { return new LineSegmentDetector(addr); }
//
// C++: void cv::LineSegmentDetector::detect(Mat image, Mat& lines, Mat& width = Mat(), Mat& prec = Mat(), Mat& nfa = Mat())
//
/**
* Finds lines in the input image.
*
* This is the output of the default parameters of the algorithm on the above shown image.
*
* 
*
* @param image A grayscale (CV_8UC1) input image. If only a roi needs to be selected, use:
* {@code lsd_ptr->detect(image(roi), lines, ...); lines += Scalar(roi.x, roi.y, roi.x, roi.y);}
* @param lines A vector of Vec4f elements specifying the beginning and ending point of a line. Where
* Vec4f is (x1, y1, x2, y2), point 1 is the start, point 2 - end. Returned lines are strictly
* oriented depending on the gradient.
* @param width Vector of widths of the regions, where the lines are found. E.g. Width of line.
* @param prec Vector of precisions with which the lines are found.
* @param nfa Vector containing number of false alarms in the line region, with precision of 10%. The
* bigger the value, logarithmically better the detection.
* <ul>
* <li>
* -1 corresponds to 10 mean false alarms
* </li>
* <li>
* 0 corresponds to 1 mean false alarm
* </li>
* <li>
* 1 corresponds to 0.1 mean false alarms
* This vector will be calculated only when the objects type is #LSD_REFINE_ADV.
* </li>
* </ul>
*/
public void detect(Mat image, Mat lines, Mat width, Mat prec, Mat nfa) {
detect_0(nativeObj, image.nativeObj, lines.nativeObj, width.nativeObj, prec.nativeObj, nfa.nativeObj);
}
/**
* Finds lines in the input image.
*
* This is the output of the default parameters of the algorithm on the above shown image.
*
* 
*
* @param image A grayscale (CV_8UC1) input image. If only a roi needs to be selected, use:
* {@code lsd_ptr->detect(image(roi), lines, ...); lines += Scalar(roi.x, roi.y, roi.x, roi.y);}
* @param lines A vector of Vec4f elements specifying the beginning and ending point of a line. Where
* Vec4f is (x1, y1, x2, y2), point 1 is the start, point 2 - end. Returned lines are strictly
* oriented depending on the gradient.
* @param width Vector of widths of the regions, where the lines are found. E.g. Width of line.
* @param prec Vector of precisions with which the lines are found.
* bigger the value, logarithmically better the detection.
* <ul>
* <li>
* -1 corresponds to 10 mean false alarms
* </li>
* <li>
* 0 corresponds to 1 mean false alarm
* </li>
* <li>
* 1 corresponds to 0.1 mean false alarms
* This vector will be calculated only when the objects type is #LSD_REFINE_ADV.
* </li>
* </ul>
*/
public void detect(Mat image, Mat lines, Mat width, Mat prec) {
detect_1(nativeObj, image.nativeObj, lines.nativeObj, width.nativeObj, prec.nativeObj);
}
/**
* Finds lines in the input image.
*
* This is the output of the default parameters of the algorithm on the above shown image.
*
* 
*
* @param image A grayscale (CV_8UC1) input image. If only a roi needs to be selected, use:
* {@code lsd_ptr->detect(image(roi), lines, ...); lines += Scalar(roi.x, roi.y, roi.x, roi.y);}
* @param lines A vector of Vec4f elements specifying the beginning and ending point of a line. Where
* Vec4f is (x1, y1, x2, y2), point 1 is the start, point 2 - end. Returned lines are strictly
* oriented depending on the gradient.
* @param width Vector of widths of the regions, where the lines are found. E.g. Width of line.
* bigger the value, logarithmically better the detection.
* <ul>
* <li>
* -1 corresponds to 10 mean false alarms
* </li>
* <li>
* 0 corresponds to 1 mean false alarm
* </li>
* <li>
* 1 corresponds to 0.1 mean false alarms
* This vector will be calculated only when the objects type is #LSD_REFINE_ADV.
* </li>
* </ul>
*/
public void detect(Mat image, Mat lines, Mat width) {
detect_2(nativeObj, image.nativeObj, lines.nativeObj, width.nativeObj);
}
/**
* Finds lines in the input image.
*
* This is the output of the default parameters of the algorithm on the above shown image.
*
* 
*
* @param image A grayscale (CV_8UC1) input image. If only a roi needs to be selected, use:
* {@code lsd_ptr->detect(image(roi), lines, ...); lines += Scalar(roi.x, roi.y, roi.x, roi.y);}
* @param lines A vector of Vec4f elements specifying the beginning and ending point of a line. Where
* Vec4f is (x1, y1, x2, y2), point 1 is the start, point 2 - end. Returned lines are strictly
* oriented depending on the gradient.
* bigger the value, logarithmically better the detection.
* <ul>
* <li>
* -1 corresponds to 10 mean false alarms
* </li>
* <li>
* 0 corresponds to 1 mean false alarm
* </li>
* <li>
* 1 corresponds to 0.1 mean false alarms
* This vector will be calculated only when the objects type is #LSD_REFINE_ADV.
* </li>
* </ul>
*/
public void detect(Mat image, Mat lines) {
detect_3(nativeObj, image.nativeObj, lines.nativeObj);
}
//
// C++: void cv::LineSegmentDetector::drawSegments(Mat& image, Mat lines)
//
/**
* Draws the line segments on a given image.
* @param image The image, where the lines will be drawn. Should be bigger or equal to the image,
* where the lines were found.
* @param lines A vector of the lines that needed to be drawn.
*/
public void drawSegments(Mat image, Mat lines) {
drawSegments_0(nativeObj, image.nativeObj, lines.nativeObj);
}
//
// C++: int cv::LineSegmentDetector::compareSegments(Size size, Mat lines1, Mat lines2, Mat& image = Mat())
//
/**
* Draws two groups of lines in blue and red, counting the non overlapping (mismatching) pixels.
*
* @param size The size of the image, where lines1 and lines2 were found.
* @param lines1 The first group of lines that needs to be drawn. It is visualized in blue color.
* @param lines2 The second group of lines. They visualized in red color.
* @param image Optional image, where the lines will be drawn. The image should be color(3-channel)
* in order for lines1 and lines2 to be drawn in the above mentioned colors.
* @return automatically generated
*/
public int compareSegments(Size size, Mat lines1, Mat lines2, Mat image) {
return compareSegments_0(nativeObj, size.width, size.height, lines1.nativeObj, lines2.nativeObj, image.nativeObj);
}
/**
* Draws two groups of lines in blue and red, counting the non overlapping (mismatching) pixels.
*
* @param size The size of the image, where lines1 and lines2 were found.
* @param lines1 The first group of lines that needs to be drawn. It is visualized in blue color.
* @param lines2 The second group of lines. They visualized in red color.
* in order for lines1 and lines2 to be drawn in the above mentioned colors.
* @return automatically generated
*/
public int compareSegments(Size size, Mat lines1, Mat lines2) {
return compareSegments_1(nativeObj, size.width, size.height, lines1.nativeObj, lines2.nativeObj);
}
@Override
protected void finalize() throws Throwable {
delete(nativeObj);
}
// C++: void cv::LineSegmentDetector::detect(Mat image, Mat& lines, Mat& width = Mat(), Mat& prec = Mat(), Mat& nfa = Mat())
private static native void detect_0(long nativeObj, long image_nativeObj, long lines_nativeObj, long width_nativeObj, long prec_nativeObj, long nfa_nativeObj);
private static native void detect_1(long nativeObj, long image_nativeObj, long lines_nativeObj, long width_nativeObj, long prec_nativeObj);
private static native void detect_2(long nativeObj, long image_nativeObj, long lines_nativeObj, long width_nativeObj);
private static native void detect_3(long nativeObj, long image_nativeObj, long lines_nativeObj);
// C++: void cv::LineSegmentDetector::drawSegments(Mat& image, Mat lines)
private static native void drawSegments_0(long nativeObj, long image_nativeObj, long lines_nativeObj);
// C++: int cv::LineSegmentDetector::compareSegments(Size size, Mat lines1, Mat lines2, Mat& image = Mat())
private static native int compareSegments_0(long nativeObj, double size_width, double size_height, long lines1_nativeObj, long lines2_nativeObj, long image_nativeObj);
private static native int compareSegments_1(long nativeObj, double size_width, double size_height, long lines1_nativeObj, long lines2_nativeObj);
// native support for java finalize()
private static native void delete(long nativeObj);
}
