001// 002// This file is auto-generated. Please don't modify it! 003// 004package org.opencv.imgproc; 005 006import org.opencv.core.Algorithm; 007import org.opencv.core.Mat; 008import org.opencv.core.Size; 009 010// C++: class LineSegmentDetector 011/** 012 * Line segment detector class 013 * 014 * following the algorithm described at CITE: Rafael12 . 015 * 016 * <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. 017 * restored again after [Computation of a NFA](https://github.com/rafael-grompone-von-gioi/binomial_nfa) code published under the MIT license. 018 */ 019public class LineSegmentDetector extends Algorithm { 020 021 protected LineSegmentDetector(long addr) { super(addr); } 022 023 // internal usage only 024 public static LineSegmentDetector __fromPtr__(long addr) { return new LineSegmentDetector(addr); } 025 026 // 027 // C++: void cv::LineSegmentDetector::detect(Mat image, Mat& lines, Mat& width = Mat(), Mat& prec = Mat(), Mat& nfa = Mat()) 028 // 029 030 /** 031 * Finds lines in the input image. 032 * 033 * This is the output of the default parameters of the algorithm on the above shown image. 034 * 035 *  036 * 037 * @param image A grayscale (CV_8UC1) input image. If only a roi needs to be selected, use: 038 * {@code lsd_ptr->detect(image(roi), lines, ...); lines += Scalar(roi.x, roi.y, roi.x, roi.y);} 039 * @param lines A vector of Vec4f elements specifying the beginning and ending point of a line. Where 040 * Vec4f is (x1, y1, x2, y2), point 1 is the start, point 2 - end. Returned lines are strictly 041 * oriented depending on the gradient. 042 * @param width Vector of widths of the regions, where the lines are found. E.g. Width of line. 043 * @param prec Vector of precisions with which the lines are found. 044 * @param nfa Vector containing number of false alarms in the line region, with precision of 10%. The 045 * bigger the value, logarithmically better the detection. 046 * <ul> 047 * <li> 048 * -1 corresponds to 10 mean false alarms 049 * </li> 050 * <li> 051 * 0 corresponds to 1 mean false alarm 052 * </li> 053 * <li> 054 * 1 corresponds to 0.1 mean false alarms 055 * This vector will be calculated only when the objects type is #LSD_REFINE_ADV. 056 * </li> 057 * </ul> 058 */ 059 public void detect(Mat image, Mat lines, Mat width, Mat prec, Mat nfa) { 060 detect_0(nativeObj, image.nativeObj, lines.nativeObj, width.nativeObj, prec.nativeObj, nfa.nativeObj); 061 } 062 063 /** 064 * Finds lines in the input image. 065 * 066 * This is the output of the default parameters of the algorithm on the above shown image. 067 * 068 *  069 * 070 * @param image A grayscale (CV_8UC1) input image. If only a roi needs to be selected, use: 071 * {@code lsd_ptr->detect(image(roi), lines, ...); lines += Scalar(roi.x, roi.y, roi.x, roi.y);} 072 * @param lines A vector of Vec4f elements specifying the beginning and ending point of a line. Where 073 * Vec4f is (x1, y1, x2, y2), point 1 is the start, point 2 - end. Returned lines are strictly 074 * oriented depending on the gradient. 075 * @param width Vector of widths of the regions, where the lines are found. E.g. Width of line. 076 * @param prec Vector of precisions with which the lines are found. 077 * bigger the value, logarithmically better the detection. 078 * <ul> 079 * <li> 080 * -1 corresponds to 10 mean false alarms 081 * </li> 082 * <li> 083 * 0 corresponds to 1 mean false alarm 084 * </li> 085 * <li> 086 * 1 corresponds to 0.1 mean false alarms 087 * This vector will be calculated only when the objects type is #LSD_REFINE_ADV. 088 * </li> 089 * </ul> 090 */ 091 public void detect(Mat image, Mat lines, Mat width, Mat prec) { 092 detect_1(nativeObj, image.nativeObj, lines.nativeObj, width.nativeObj, prec.nativeObj); 093 } 094 095 /** 096 * Finds lines in the input image. 097 * 098 * This is the output of the default parameters of the algorithm on the above shown image. 099 * 100 *  101 * 102 * @param image A grayscale (CV_8UC1) input image. If only a roi needs to be selected, use: 103 * {@code lsd_ptr->detect(image(roi), lines, ...); lines += Scalar(roi.x, roi.y, roi.x, roi.y);} 104 * @param lines A vector of Vec4f elements specifying the beginning and ending point of a line. Where 105 * Vec4f is (x1, y1, x2, y2), point 1 is the start, point 2 - end. Returned lines are strictly 106 * oriented depending on the gradient. 107 * @param width Vector of widths of the regions, where the lines are found. E.g. Width of line. 108 * bigger the value, logarithmically better the detection. 109 * <ul> 110 * <li> 111 * -1 corresponds to 10 mean false alarms 112 * </li> 113 * <li> 114 * 0 corresponds to 1 mean false alarm 115 * </li> 116 * <li> 117 * 1 corresponds to 0.1 mean false alarms 118 * This vector will be calculated only when the objects type is #LSD_REFINE_ADV. 119 * </li> 120 * </ul> 121 */ 122 public void detect(Mat image, Mat lines, Mat width) { 123 detect_2(nativeObj, image.nativeObj, lines.nativeObj, width.nativeObj); 124 } 125 126 /** 127 * Finds lines in the input image. 128 * 129 * This is the output of the default parameters of the algorithm on the above shown image. 130 * 131 *  132 * 133 * @param image A grayscale (CV_8UC1) input image. If only a roi needs to be selected, use: 134 * {@code lsd_ptr->detect(image(roi), lines, ...); lines += Scalar(roi.x, roi.y, roi.x, roi.y);} 135 * @param lines A vector of Vec4f elements specifying the beginning and ending point of a line. Where 136 * Vec4f is (x1, y1, x2, y2), point 1 is the start, point 2 - end. Returned lines are strictly 137 * oriented depending on the gradient. 138 * bigger the value, logarithmically better the detection. 139 * <ul> 140 * <li> 141 * -1 corresponds to 10 mean false alarms 142 * </li> 143 * <li> 144 * 0 corresponds to 1 mean false alarm 145 * </li> 146 * <li> 147 * 1 corresponds to 0.1 mean false alarms 148 * This vector will be calculated only when the objects type is #LSD_REFINE_ADV. 149 * </li> 150 * </ul> 151 */ 152 public void detect(Mat image, Mat lines) { 153 detect_3(nativeObj, image.nativeObj, lines.nativeObj); 154 } 155 156 157 // 158 // C++: void cv::LineSegmentDetector::drawSegments(Mat& image, Mat lines) 159 // 160 161 /** 162 * Draws the line segments on a given image. 163 * @param image The image, where the lines will be drawn. Should be bigger or equal to the image, 164 * where the lines were found. 165 * @param lines A vector of the lines that needed to be drawn. 166 */ 167 public void drawSegments(Mat image, Mat lines) { 168 drawSegments_0(nativeObj, image.nativeObj, lines.nativeObj); 169 } 170 171 172 // 173 // C++: int cv::LineSegmentDetector::compareSegments(Size size, Mat lines1, Mat lines2, Mat& image = Mat()) 174 // 175 176 /** 177 * Draws two groups of lines in blue and red, counting the non overlapping (mismatching) pixels. 178 * 179 * @param size The size of the image, where lines1 and lines2 were found. 180 * @param lines1 The first group of lines that needs to be drawn. It is visualized in blue color. 181 * @param lines2 The second group of lines. They visualized in red color. 182 * @param image Optional image, where the lines will be drawn. The image should be color(3-channel) 183 * in order for lines1 and lines2 to be drawn in the above mentioned colors. 184 * @return automatically generated 185 */ 186 public int compareSegments(Size size, Mat lines1, Mat lines2, Mat image) { 187 return compareSegments_0(nativeObj, size.width, size.height, lines1.nativeObj, lines2.nativeObj, image.nativeObj); 188 } 189 190 /** 191 * Draws two groups of lines in blue and red, counting the non overlapping (mismatching) pixels. 192 * 193 * @param size The size of the image, where lines1 and lines2 were found. 194 * @param lines1 The first group of lines that needs to be drawn. It is visualized in blue color. 195 * @param lines2 The second group of lines. They visualized in red color. 196 * in order for lines1 and lines2 to be drawn in the above mentioned colors. 197 * @return automatically generated 198 */ 199 public int compareSegments(Size size, Mat lines1, Mat lines2) { 200 return compareSegments_1(nativeObj, size.width, size.height, lines1.nativeObj, lines2.nativeObj); 201 } 202 203 204 @Override 205 protected void finalize() throws Throwable { 206 delete(nativeObj); 207 } 208 209 210 211 // C++: void cv::LineSegmentDetector::detect(Mat image, Mat& lines, Mat& width = Mat(), Mat& prec = Mat(), Mat& nfa = Mat()) 212 private static native void detect_0(long nativeObj, long image_nativeObj, long lines_nativeObj, long width_nativeObj, long prec_nativeObj, long nfa_nativeObj); 213 private static native void detect_1(long nativeObj, long image_nativeObj, long lines_nativeObj, long width_nativeObj, long prec_nativeObj); 214 private static native void detect_2(long nativeObj, long image_nativeObj, long lines_nativeObj, long width_nativeObj); 215 private static native void detect_3(long nativeObj, long image_nativeObj, long lines_nativeObj); 216 217 // C++: void cv::LineSegmentDetector::drawSegments(Mat& image, Mat lines) 218 private static native void drawSegments_0(long nativeObj, long image_nativeObj, long lines_nativeObj); 219 220 // C++: int cv::LineSegmentDetector::compareSegments(Size size, Mat lines1, Mat lines2, Mat& image = Mat()) 221 private static native int compareSegments_0(long nativeObj, double size_width, double size_height, long lines1_nativeObj, long lines2_nativeObj, long image_nativeObj); 222 private static native int compareSegments_1(long nativeObj, double size_width, double size_height, long lines1_nativeObj, long lines2_nativeObj); 223 224 // native support for java finalize() 225 private static native void delete(long nativeObj); 226 227}