using OpenCVForUnity.CoreModule;
using OpenCVForUnity.UtilsModule;
using System;
using System.Collections.Generic;
using System.Runtime.InteropServices;
namespace OpenCVForUnity.ImgprocModule
{
// C++: class LineSegmentDetector
/**
* Line segment detector class
*
* following the algorithm described at CITE: Rafael12 .
*
* Note: 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 : Algorithm
{
protected override void Dispose(bool disposing)
{
try
{
if (disposing)
{
}
if (IsEnabledDispose)
{
if (nativeObj != IntPtr.Zero)
imgproc_LineSegmentDetector_delete(nativeObj);
nativeObj = IntPtr.Zero;
}
}
finally
{
base.Dispose(disposing);
}
}
protected internal LineSegmentDetector(IntPtr addr) : base(addr) { }
// internal usage only
public static new LineSegmentDetector __fromPtr__(IntPtr 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.
*
* ![image](pics/building_lsd.png)
*
* 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.
*
* -
* -1 corresponds to 10 mean false alarms
*
* -
* 0 corresponds to 1 mean false alarm
*
* -
* 1 corresponds to 0.1 mean false alarms
* This vector will be calculated only when the objects type is #LSD_REFINE_ADV.
*
*
*/
public void detect(Mat image, Mat lines, Mat width, Mat prec, Mat nfa)
{
ThrowIfDisposed();
if (image != null) image.ThrowIfDisposed();
if (lines != null) lines.ThrowIfDisposed();
if (width != null) width.ThrowIfDisposed();
if (prec != null) prec.ThrowIfDisposed();
if (nfa != null) nfa.ThrowIfDisposed();
imgproc_LineSegmentDetector_detect_10(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.
*
* ![image](pics/building_lsd.png)
*
* 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.
*
* -
* -1 corresponds to 10 mean false alarms
*
* -
* 0 corresponds to 1 mean false alarm
*
* -
* 1 corresponds to 0.1 mean false alarms
* This vector will be calculated only when the objects type is #LSD_REFINE_ADV.
*
*
*/
public void detect(Mat image, Mat lines, Mat width, Mat prec)
{
ThrowIfDisposed();
if (image != null) image.ThrowIfDisposed();
if (lines != null) lines.ThrowIfDisposed();
if (width != null) width.ThrowIfDisposed();
if (prec != null) prec.ThrowIfDisposed();
imgproc_LineSegmentDetector_detect_11(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.
*
* ![image](pics/building_lsd.png)
*
* 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.
*
* -
* -1 corresponds to 10 mean false alarms
*
* -
* 0 corresponds to 1 mean false alarm
*
* -
* 1 corresponds to 0.1 mean false alarms
* This vector will be calculated only when the objects type is #LSD_REFINE_ADV.
*
*
*/
public void detect(Mat image, Mat lines, Mat width)
{
ThrowIfDisposed();
if (image != null) image.ThrowIfDisposed();
if (lines != null) lines.ThrowIfDisposed();
if (width != null) width.ThrowIfDisposed();
imgproc_LineSegmentDetector_detect_12(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.
*
* ![image](pics/building_lsd.png)
*
* 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.
*
* -
* -1 corresponds to 10 mean false alarms
*
* -
* 0 corresponds to 1 mean false alarm
*
* -
* 1 corresponds to 0.1 mean false alarms
* This vector will be calculated only when the objects type is #LSD_REFINE_ADV.
*
*
*/
public void detect(Mat image, Mat lines)
{
ThrowIfDisposed();
if (image != null) image.ThrowIfDisposed();
if (lines != null) lines.ThrowIfDisposed();
imgproc_LineSegmentDetector_detect_13(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)
{
ThrowIfDisposed();
if (image != null) image.ThrowIfDisposed();
if (lines != null) lines.ThrowIfDisposed();
imgproc_LineSegmentDetector_drawSegments_10(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)
{
ThrowIfDisposed();
if (lines1 != null) lines1.ThrowIfDisposed();
if (lines2 != null) lines2.ThrowIfDisposed();
if (image != null) image.ThrowIfDisposed();
return imgproc_LineSegmentDetector_compareSegments_10(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)
{
ThrowIfDisposed();
if (lines1 != null) lines1.ThrowIfDisposed();
if (lines2 != null) lines2.ThrowIfDisposed();
return imgproc_LineSegmentDetector_compareSegments_11(nativeObj, size.width, size.height, lines1.nativeObj, lines2.nativeObj);
}
#if (UNITY_IOS || UNITY_WEBGL) && !UNITY_EDITOR
const string LIBNAME = "__Internal";
#else
const string LIBNAME = "opencvforunity";
#endif
// C++: void cv::LineSegmentDetector::detect(Mat image, Mat& lines, Mat& width = Mat(), Mat& prec = Mat(), Mat& nfa = Mat())
[DllImport(LIBNAME)]
private static extern void imgproc_LineSegmentDetector_detect_10(IntPtr nativeObj, IntPtr image_nativeObj, IntPtr lines_nativeObj, IntPtr width_nativeObj, IntPtr prec_nativeObj, IntPtr nfa_nativeObj);
[DllImport(LIBNAME)]
private static extern void imgproc_LineSegmentDetector_detect_11(IntPtr nativeObj, IntPtr image_nativeObj, IntPtr lines_nativeObj, IntPtr width_nativeObj, IntPtr prec_nativeObj);
[DllImport(LIBNAME)]
private static extern void imgproc_LineSegmentDetector_detect_12(IntPtr nativeObj, IntPtr image_nativeObj, IntPtr lines_nativeObj, IntPtr width_nativeObj);
[DllImport(LIBNAME)]
private static extern void imgproc_LineSegmentDetector_detect_13(IntPtr nativeObj, IntPtr image_nativeObj, IntPtr lines_nativeObj);
// C++: void cv::LineSegmentDetector::drawSegments(Mat& image, Mat lines)
[DllImport(LIBNAME)]
private static extern void imgproc_LineSegmentDetector_drawSegments_10(IntPtr nativeObj, IntPtr image_nativeObj, IntPtr lines_nativeObj);
// C++: int cv::LineSegmentDetector::compareSegments(Size size, Mat lines1, Mat lines2, Mat& image = Mat())
[DllImport(LIBNAME)]
private static extern int imgproc_LineSegmentDetector_compareSegments_10(IntPtr nativeObj, double size_width, double size_height, IntPtr lines1_nativeObj, IntPtr lines2_nativeObj, IntPtr image_nativeObj);
[DllImport(LIBNAME)]
private static extern int imgproc_LineSegmentDetector_compareSegments_11(IntPtr nativeObj, double size_width, double size_height, IntPtr lines1_nativeObj, IntPtr lines2_nativeObj);
// native support for java finalize()
[DllImport(LIBNAME)]
private static extern void imgproc_LineSegmentDetector_delete(IntPtr nativeObj);
}
}