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/*M///////////////////////////////////////////////////////////////////////////////////////
//
// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
//
// By downloading, copying, installing or using the software you agree to this license.
// If you do not agree to this license, do not download, install,
// copy or use the software.
//
//
// License Agreement
// For Open Source Computer Vision Library
//
// Copyright (C) 2013, OpenCV Foundation, all rights reserved.
// Third party copyrights are property of their respective owners.
//
// Redistribution and use in source and binary forms, with or without modification,
// are permitted provided that the following conditions are met:
//
// * Redistributions of source code must retain the above copyright notice,
// this list of conditions and the following disclaimer.
//
// * Redistributions in binary form must reproduce the above copyright notice,
// this list of conditions and the following disclaimer in the documentation
// and/or other materials provided with the distribution.
//
// * The name of the copyright holders may not be used to endorse or promote products
// derived from this software without specific prior written permission.
//
// This software is provided by the copyright holders and contributors "as is" and
// any express or implied warranties, including, but not limited to, the implied
// warranties of merchantability and fitness for a particular purpose are disclaimed.
// In no event shall the Intel Corporation or contributors be liable for any direct,
// indirect, incidental, special, exemplary, or consequential damages
// (including, but not limited to, procurement of substitute goods or services;
// loss of use, data, or profits; or business interruption) however caused
// and on any theory of liability, whether in contract, strict liability,
// or tort (including negligence or otherwise) arising in any way out of
// the use of this software, even if advised of the possibility of such damage.
//
//M*/
#include "precomp.hpp"
#include <vector>
#if defined(_MSC_VER)
# pragma warning(disable:4702) // unreachable code
#endif
namespace cv {
class LineSegmentDetectorImpl CV_FINAL : public LineSegmentDetector
{
public:
/**
* Create a LineSegmentDetectorImpl object. Specifying scale, number of subdivisions for the image, should the lines be refined and other constants as follows:
*
* @param _refine How should the lines found be refined?
* LSD_REFINE_NONE - No refinement applied.
* LSD_REFINE_STD - Standard refinement is applied. E.g. breaking arches into smaller line approximations.
* LSD_REFINE_ADV - Advanced refinement. Number of false alarms is calculated,
* lines are refined through increase of precision, decrement in size, etc.
* @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 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
* @param _density_th Minimal density of aligned region points in rectangle.
* @param _n_bins Number of bins in pseudo-ordering of gradient modulus.
*/
LineSegmentDetectorImpl(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);
/**
* Detect lines in the input image.
*
* @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 Return: 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 Return: Vector of widths of the regions, where the lines are found. E.g. Width of line.
* @param prec Return: Vector of precisions with which the lines are found.
* @param nfa Return: 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 REFINE_ADV
*/
void detect(InputArray _image, OutputArray _lines,
OutputArray width = noArray(), OutputArray prec = noArray(),
OutputArray nfa = noArray()) CV_OVERRIDE;
/**
* Draw lines on the given canvas.
*
* @param image The image, where lines will be drawn.
* Should have the size of the image, where the lines were found
* @param lines The lines that need to be drawn
*/
void drawSegments(InputOutputArray _image, InputArray lines) CV_OVERRIDE;
/**
* Draw both vectors on the image canvas. Uses blue for lines 1 and red for lines 2.
*
* @param size The size of the image, where lines1 and lines2 were found.
* @param lines1 The first lines that need to be drawn. Color - Blue.
* @param lines2 The second lines that need to be drawn. Color - Red.
* @param image An optional image, where lines will be drawn.
* Should have the size of the image, where the lines were found
* @return The number of mismatching pixels between lines1 and lines2.
*/
int compareSegments(const Size& size, InputArray lines1, InputArray lines2, InputOutputArray _image = noArray()) CV_OVERRIDE;
private:
LineSegmentDetectorImpl& operator= (const LineSegmentDetectorImpl&); // to quiet MSVC
};
/////////////////////////////////////////////////////////////////////////////////////////
CV_EXPORTS Ptr<LineSegmentDetector> createLineSegmentDetector(
int _refine, double _scale, double _sigma_scale, double _quant, double _ang_th,
double _log_eps, double _density_th, int _n_bins)
{
return makePtr<LineSegmentDetectorImpl>(
_refine, _scale, _sigma_scale, _quant, _ang_th,
_log_eps, _density_th, _n_bins);
}
/////////////////////////////////////////////////////////////////////////////////////////
LineSegmentDetectorImpl::LineSegmentDetectorImpl(int _refine, double _scale, double _sigma_scale, double _quant,
double _ang_th, double _log_eps, double _density_th, int _n_bins)
{
CV_Assert(_scale > 0 && _sigma_scale > 0 && _quant >= 0 &&
_ang_th > 0 && _ang_th < 180 && _density_th >= 0 && _density_th < 1 &&
_n_bins > 0);
CV_UNUSED(_refine); CV_UNUSED(_log_eps);
CV_Error(Error::StsNotImplemented, "Implementation has been removed due original code license issues");
}
void LineSegmentDetectorImpl::detect(InputArray _image, OutputArray _lines,
OutputArray _width, OutputArray _prec, OutputArray _nfa)
{
CV_INSTRUMENT_REGION();
CV_UNUSED(_image); CV_UNUSED(_lines);
CV_UNUSED(_width); CV_UNUSED(_prec); CV_UNUSED(_nfa);
CV_Error(Error::StsNotImplemented, "Implementation has been removed due original code license issues");
}
void LineSegmentDetectorImpl::drawSegments(InputOutputArray _image, InputArray lines)
{
CV_INSTRUMENT_REGION();
CV_Assert(!_image.empty() && (_image.channels() == 1 || _image.channels() == 3));
if (_image.channels() == 1)
{
cvtColor(_image, _image, COLOR_GRAY2BGR);
}
Mat _lines = lines.getMat();
const int N = _lines.checkVector(4);
CV_Assert(_lines.depth() == CV_32F || _lines.depth() == CV_32S);
// Draw segments
if (_lines.depth() == CV_32F)
{
for (int i = 0; i < N; ++i)
{
const Vec4f& v = _lines.at<Vec4f>(i);
const Point2f b(v[0], v[1]);
const Point2f e(v[2], v[3]);
line(_image, b, e, Scalar(0, 0, 255), 1);
}
}
else
{
for (int i = 0; i < N; ++i)
{
const Vec4i& v = _lines.at<Vec4i>(i);
const Point2i b(v[0], v[1]);
const Point2i e(v[2], v[3]);
line(_image, b, e, Scalar(0, 0, 255), 1);
}
}
}
int LineSegmentDetectorImpl::compareSegments(const Size& size, InputArray lines1, InputArray lines2, InputOutputArray _image)
{
CV_INSTRUMENT_REGION();
Size sz = size;
if (_image.needed() && _image.size() != size) sz = _image.size();
CV_Assert(!sz.empty());
Mat_<uchar> I1 = Mat_<uchar>::zeros(sz);
Mat_<uchar> I2 = Mat_<uchar>::zeros(sz);
Mat _lines1 = lines1.getMat();
Mat _lines2 = lines2.getMat();
const int N1 = _lines1.checkVector(4);
const int N2 = _lines2.checkVector(4);
CV_Assert(_lines1.depth() == CV_32F || _lines1.depth() == CV_32S);
CV_Assert(_lines2.depth() == CV_32F || _lines2.depth() == CV_32S);
if (_lines1.depth() == CV_32S)
_lines1.convertTo(_lines1, CV_32F);
if (_lines2.depth() == CV_32S)
_lines2.convertTo(_lines2, CV_32F);
// Draw segments
for(int i = 0; i < N1; ++i)
{
const Point2f b(_lines1.at<Vec4f>(i)[0], _lines1.at<Vec4f>(i)[1]);
const Point2f e(_lines1.at<Vec4f>(i)[2], _lines1.at<Vec4f>(i)[3]);
line(I1, b, e, Scalar::all(255), 1);
}
for(int i = 0; i < N2; ++i)
{
const Point2f b(_lines2.at<Vec4f>(i)[0], _lines2.at<Vec4f>(i)[1]);
const Point2f e(_lines2.at<Vec4f>(i)[2], _lines2.at<Vec4f>(i)[3]);
line(I2, b, e, Scalar::all(255), 1);
}
// Count the pixels that don't agree
Mat Ixor;
bitwise_xor(I1, I2, Ixor);
int N = countNonZero(Ixor);
if (_image.needed())
{
CV_Assert(_image.channels() == 3);
Mat img = _image.getMatRef();
CV_Assert(img.isContinuous() && I1.isContinuous() && I2.isContinuous());
for (unsigned int i = 0; i < I1.total(); ++i)
{
uchar i1 = I1.ptr()[i];
uchar i2 = I2.ptr()[i];
if (i1 || i2)
{
unsigned int base_idx = i * 3;
if (i1) img.ptr()[base_idx] = 255;
else img.ptr()[base_idx] = 0;
img.ptr()[base_idx + 1] = 0;
if (i2) img.ptr()[base_idx + 2] = 255;
else img.ptr()[base_idx + 2] = 0;
}
}
}
return N;
}
} // namespace cv