imgproc: drop LineSegmentDetector stubs

modules/imgproc/include/opencv2/imgproc.hpp

@@ -480,14 +480,6 @@ enum HoughModes {
     HOUGH_GRADIENT_ALT  = 4, //!< variation of HOUGH_GRADIENT to get better accuracy
 };
 
-//! Variants of Line Segment %Detector
-enum LineSegmentDetectorModes {
-    LSD_REFINE_NONE = 0, //!< No refinement applied
-    LSD_REFINE_STD  = 1, //!< Standard refinement is applied. E.g. breaking arches into smaller straighter line approximations.
-    LSD_REFINE_ADV  = 2  //!< Advanced refinement. Number of false alarms is calculated, lines are
-                         //!< refined through increase of precision, decrement in size, etc.
-};
-
 //! @} imgproc_feature
 
 /** Histogram comparison methods
@@ -1251,88 +1243,6 @@ protected:
 
 //! @} imgproc_subdiv2d
 
-//! @addtogroup imgproc_feature
-//! @{
-
-/** @brief Line segment detector class
-
-following the algorithm described at @cite Rafael12 .
-
-@note Implementation has been removed due original code license conflict
-
-*/
-class CV_EXPORTS_W LineSegmentDetector : public Algorithm
-{
-public:
-
-    /** @brief 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:
-    `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
-    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.
-    */
-    CV_WRAP virtual void detect(InputArray _image, OutputArray _lines,
-                        OutputArray width = noArray(), OutputArray prec = noArray(),
-                        OutputArray nfa = noArray()) = 0;
-
-    /** @brief 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.
-     */
-    CV_WRAP virtual void drawSegments(InputOutputArray _image, InputArray lines) = 0;
-
-    /** @brief 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.
-     */
-    CV_WRAP virtual int compareSegments(const Size& size, InputArray lines1, InputArray lines2, InputOutputArray _image = noArray()) = 0;
-
-    virtual ~LineSegmentDetector() { }
-};
-
-/** @brief Creates a smart pointer to a LineSegmentDetector object and initializes it.
-
-The LineSegmentDetector algorithm is defined using the standard values. Only advanced users may want
-to edit those, as to tailor it for their own application.
-
-@param _refine The way found lines will be refined, see #LineSegmentDetectorModes
-@param _scale The scale of the image that will be used to find the lines. Range (0..1].
-@param _sigma_scale Sigma for Gaussian filter. It is computed as sigma = _sigma_scale/_scale.
-@param _quant Bound to the quantization error on the gradient norm.
-@param _ang_th Gradient angle tolerance in degrees.
-@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,
-    double _sigma_scale = 0.6, double _quant = 2.0, double _ang_th = 22.5,
-    double _log_eps = 0, double _density_th = 0.7, int _n_bins = 1024);
-
-//! @} imgproc_feature
-
 //! @addtogroup imgproc_filter
 //! @{