Merge pull request #20797 from sturkmen72:restore_LSD

modules/imgproc/include/opencv2/imgproc.hpp

@@ -1220,12 +1220,17 @@ protected:
 //! @addtogroup imgproc_feature
 //! @{
 
+/** @example samples/cpp/lsd_lines.cpp
+An example using the LineSegmentDetector
+\image html building_lsd.png "Sample output image" width=434 height=300
+*/
+
 /** @brief Line segment detector class
 
 following the algorithm described at @cite Rafael12 .
 
-@note Implementation has been removed due original code license conflict
-
+@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.
 */
 class CV_EXPORTS_W LineSegmentDetector : public Algorithm
 {
@@ -1239,8 +1244,8 @@ public:
 
     @param image A grayscale (CV_8UC1) input image. If only a roi needs to be selected, use:
     `lsd_ptr-\>detect(image(roi), lines, ...); lines += Scalar(roi.x, roi.y, roi.x, roi.y);`
-    @param lines A vector of Vec4i or Vec4f elements specifying the beginning and ending point of a line. Where
-    Vec4i/Vec4f is (x1, y1, x2, y2), point 1 is the start, point 2 - end. Returned lines are strictly
+    @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.
@@ -1288,8 +1293,6 @@ to edit those, as to tailor it for their own application.
 @param log_eps Detection threshold: -log10(NFA) \> log_eps. Used only when advance refinement is chosen.
 @param density_th Minimal density of aligned region points in the enclosing rectangle.
 @param n_bins Number of bins in pseudo-ordering of gradient modulus.
-
-@note Implementation has been removed due original code license conflict
  */
 CV_EXPORTS_W Ptr<LineSegmentDetector> createLineSegmentDetector(
     int refine = LSD_REFINE_STD, double scale = 0.8,

modules/imgproc/test/test_lsd.cpp

@@ -5,8 +5,6 @@
 
 namespace opencv_test { namespace {
 
-#if 0  // LSD implementation has been removed due original code license issues
-
 const Size img_size(640, 480);
 const int LSD_TEST_SEED = 0x134679;
 const int EPOCHS = 20;
@@ -404,6 +402,4 @@ TEST_F(Imgproc_LSD_Common, compareSegmentsVec4i)
     ASSERT_EQ(result2, 11);
 }
 
-#endif
-
 }} // namespace

samples/cpp/lsd_lines.cpp

+#include "opencv2/imgproc.hpp"
+#include "opencv2/imgcodecs.hpp"
+#include "opencv2/highgui.hpp"
+#include <iostream>
+
+using namespace std;
+using namespace cv;
+
+int main(int argc, char** argv)
+{
+    cv::CommandLineParser parser(argc, argv,
+                                 "{input   i|building.jpg|input image}"
+                                 "{refine  r|false|if true use LSD_REFINE_STD method, if false use LSD_REFINE_NONE method}"
+                                 "{canny   c|false|use Canny edge detector}"
+                                 "{overlay o|false|show result on input image}"
+                                 "{help    h|false|show help message}");
+
+    if (parser.get<bool>("help"))
+    {
+        parser.printMessage();
+        return 0;
+    }
+
+    parser.printMessage();
+
+    String filename = samples::findFile(parser.get<String>("input"));
+    bool useRefine = parser.get<bool>("refine");
+    bool useCanny = parser.get<bool>("canny");
+    bool overlay = parser.get<bool>("overlay");
+
+    Mat image = imread(filename, IMREAD_GRAYSCALE);
+
+    if( image.empty() )
+    {
+        cout << "Unable to load " << filename;
+        return 1;
+    }
+
+    imshow("Source Image", image);
+
+    if (useCanny)
+    {
+        Canny(image, image, 50, 200, 3); // Apply Canny edge detector
+    }
+
+    // Create and LSD detector with standard or no refinement.
+    Ptr<LineSegmentDetector> ls = useRefine ? createLineSegmentDetector(LSD_REFINE_STD) : createLineSegmentDetector(LSD_REFINE_NONE);
+
+    double start = double(getTickCount());
+    vector<Vec4f> lines_std;
+
+    // Detect the lines
+    ls->detect(image, lines_std);
+
+    double duration_ms = (double(getTickCount()) - start) * 1000 / getTickFrequency();
+    std::cout << "It took " << duration_ms << " ms." << std::endl;
+
+    // Show found lines
+    if (!overlay || useCanny)
+    {
+        image = Scalar(0, 0, 0);
+    }
+
+    ls->drawSegments(image, lines_std);
+
+    String window_name = useRefine ? "Result - standard refinement" : "Result - no refinement";
+    window_name += useCanny ? " - Canny edge detector used" : "";
+
+    imshow(window_name, image);
+
+    waitKey();
+    return 0;
+}