Commit 45f7c83d authored by Roman Donchenko's avatar Roman Donchenko Committed by OpenCV Buildbot

Merge pull request #1119 from 23pointsNorth:lsd

parents b2d359b6 ae93a3e6
...@@ -191,6 +191,12 @@ enum { HOUGH_STANDARD = 0, ...@@ -191,6 +191,12 @@ enum { HOUGH_STANDARD = 0,
HOUGH_GRADIENT = 3 HOUGH_GRADIENT = 3
}; };
//! Variants of Line Segment Detector
enum { LSD_REFINE_NONE = 0,
LSD_REFINE_STD = 1,
LSD_REFINE_ADV = 2
};
//! Histogram comparison methods //! Histogram comparison methods
enum { HISTCMP_CORREL = 0, enum { HISTCMP_CORREL = 0,
HISTCMP_CHISQR = 1, HISTCMP_CHISQR = 1,
...@@ -829,7 +835,62 @@ protected: ...@@ -829,7 +835,62 @@ protected:
Point2f bottomRight; Point2f bottomRight;
}; };
class LineSegmentDetector : public Algorithm
{
public:
/**
* Detect lines in the input image with the specified ROI.
*
* @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 elements specifying the beginning and ending point of a line.
* Where Vec4i is (x1, y1, x2, y2), point 1 is the start, point 2 - end.
* Returned lines are strictly oriented depending on the gradient.
* @param _roi Return: ROI of the image, where lines are to be found. If specified, the returning
* lines coordinates are image wise.
* @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
*/
virtual void detect(const InputArray _image, OutputArray _lines,
OutputArray width = noArray(), OutputArray prec = noArray(),
OutputArray nfa = noArray()) = 0;
/**
* 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
*/
virtual void drawSegments(InputOutputArray image, const InputArray lines) = 0;
/**
* Draw both vectors on the image canvas. Uses blue for lines 1 and red for lines 2.
*
* @param image The image, where lines will be drawn.
* Should have the size of the image, where the lines 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.
* @return The number of mismatching pixels between lines1 and lines2.
*/
virtual int compareSegments(const Size& size, const InputArray lines1, const InputArray lines2, Mat* image = 0) = 0;
virtual ~LineSegmentDetector() {};
};
//! Returns a pointer to a LineSegmentDetector class.
CV_EXPORTS Ptr<LineSegmentDetector> createLineSegmentDetectorPtr(
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);
//! returns type (one of KERNEL_*) of 1D or 2D kernel specified by its coefficients. //! returns type (one of KERNEL_*) of 1D or 2D kernel specified by its coefficients.
CV_EXPORTS int getKernelType(InputArray kernel, Point anchor); CV_EXPORTS int getKernelType(InputArray kernel, Point anchor);
......
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#include "test_precomp.hpp"
#include <vector>
using namespace cv;
using namespace std;
const Size img_size(640, 480);
const int LSD_TEST_SEED = 0x134679;
const int EPOCHS = 20;
class LSDBase : public testing::Test
{
public:
LSDBase() {};
protected:
Mat test_image;
vector<Vec4i> lines;
RNG rng;
int passedtests;
void GenerateWhiteNoise(Mat& image);
void GenerateConstColor(Mat& image);
void GenerateLines(Mat& image, const unsigned int numLines);
void GenerateRotatedRect(Mat& image);
virtual void SetUp();
};
class Imgproc_LSD_ADV: public LSDBase
{
public:
Imgproc_LSD_ADV() {};
protected:
};
class Imgproc_LSD_STD: public LSDBase
{
public:
Imgproc_LSD_STD() {};
protected:
};
class Imgproc_LSD_NONE: public LSDBase
{
public:
Imgproc_LSD_NONE() {};
protected:
};
void LSDBase::GenerateWhiteNoise(Mat& image)
{
image = Mat(img_size, CV_8UC1);
rng.fill(image, RNG::UNIFORM, 0, 256);
}
void LSDBase::GenerateConstColor(Mat& image)
{
image = Mat(img_size, CV_8UC1, Scalar::all(rng.uniform(0, 256)));
}
void LSDBase::GenerateLines(Mat& image, const unsigned int numLines)
{
image = Mat(img_size, CV_8UC1, Scalar::all(rng.uniform(0, 128)));
for(unsigned int i = 0; i < numLines; ++i)
{
int y = rng.uniform(10, img_size.width - 10);
Point p1(y, 10);
Point p2(y, img_size.height - 10);
line(image, p1, p2, Scalar(255), 3);
}
}
void LSDBase::GenerateRotatedRect(Mat& image)
{
image = Mat::zeros(img_size, CV_8UC1);
Point center(rng.uniform(img_size.width/4, img_size.width*3/4),
rng.uniform(img_size.height/4, img_size.height*3/4));
Size rect_size(rng.uniform(img_size.width/8, img_size.width/6),
rng.uniform(img_size.height/8, img_size.height/6));
float angle = rng.uniform(0.f, 360.f);
Point2f vertices[4];
RotatedRect rRect = RotatedRect(center, rect_size, angle);
rRect.points(vertices);
for (int i = 0; i < 4; i++)
{
line(image, vertices[i], vertices[(i + 1) % 4], Scalar(255), 3);
}
}
void LSDBase::SetUp()
{
lines.clear();
test_image = Mat();
rng = RNG(LSD_TEST_SEED);
passedtests = 0;
}
TEST_F(Imgproc_LSD_ADV, whiteNoise)
{
for (int i = 0; i < EPOCHS; ++i)
{
GenerateWhiteNoise(test_image);
Ptr<LineSegmentDetector> detector = createLineSegmentDetectorPtr(LSD_REFINE_ADV);
detector->detect(test_image, lines);
if(uint(40) >= lines.size()) ++passedtests;
}
ASSERT_EQ(EPOCHS, passedtests);
}
TEST_F(Imgproc_LSD_ADV, constColor)
{
for (int i = 0; i < EPOCHS; ++i)
{
GenerateConstColor(test_image);
Ptr<LineSegmentDetector> detector = createLineSegmentDetectorPtr(LSD_REFINE_ADV);
detector->detect(test_image, lines);
if(uint(0) == lines.size()) ++passedtests;
}
ASSERT_EQ(EPOCHS, passedtests);
}
TEST_F(Imgproc_LSD_ADV, lines)
{
for (int i = 0; i < EPOCHS; ++i)
{
const unsigned int numOfLines = 1;
GenerateLines(test_image, numOfLines);
Ptr<LineSegmentDetector> detector = createLineSegmentDetectorPtr(LSD_REFINE_ADV);
detector->detect(test_image, lines);
if(numOfLines * 2 == lines.size()) ++passedtests; // * 2 because of Gibbs effect
}
ASSERT_EQ(EPOCHS, passedtests);
}
TEST_F(Imgproc_LSD_ADV, rotatedRect)
{
for (int i = 0; i < EPOCHS; ++i)
{
GenerateRotatedRect(test_image);
Ptr<LineSegmentDetector> detector = createLineSegmentDetectorPtr(LSD_REFINE_ADV);
detector->detect(test_image, lines);
if(uint(2) <= lines.size()) ++passedtests;
}
ASSERT_EQ(EPOCHS, passedtests);
}
TEST_F(Imgproc_LSD_STD, whiteNoise)
{
for (int i = 0; i < EPOCHS; ++i)
{
GenerateWhiteNoise(test_image);
Ptr<LineSegmentDetector> detector = createLineSegmentDetectorPtr(LSD_REFINE_STD);
detector->detect(test_image, lines);
if(uint(50) >= lines.size()) ++passedtests;
}
ASSERT_EQ(EPOCHS, passedtests);
}
TEST_F(Imgproc_LSD_STD, constColor)
{
for (int i = 0; i < EPOCHS; ++i)
{
GenerateConstColor(test_image);
Ptr<LineSegmentDetector> detector = createLineSegmentDetectorPtr(LSD_REFINE_STD);
detector->detect(test_image, lines);
if(uint(0) == lines.size()) ++passedtests;
}
ASSERT_EQ(EPOCHS, passedtests);
}
TEST_F(Imgproc_LSD_STD, lines)
{
for (int i = 0; i < EPOCHS; ++i)
{
const unsigned int numOfLines = 1;
GenerateLines(test_image, numOfLines);
Ptr<LineSegmentDetector> detector = createLineSegmentDetectorPtr(LSD_REFINE_STD);
detector->detect(test_image, lines);
if(numOfLines * 2 == lines.size()) ++passedtests; // * 2 because of Gibbs effect
}
ASSERT_EQ(EPOCHS, passedtests);
}
TEST_F(Imgproc_LSD_STD, rotatedRect)
{
for (int i = 0; i < EPOCHS; ++i)
{
GenerateRotatedRect(test_image);
Ptr<LineSegmentDetector> detector = createLineSegmentDetectorPtr(LSD_REFINE_STD);
detector->detect(test_image, lines);
if(uint(4) <= lines.size()) ++passedtests;
}
ASSERT_EQ(EPOCHS, passedtests);
}
TEST_F(Imgproc_LSD_NONE, whiteNoise)
{
for (int i = 0; i < EPOCHS; ++i)
{
GenerateWhiteNoise(test_image);
Ptr<LineSegmentDetector> detector = createLineSegmentDetectorPtr(LSD_REFINE_STD);
detector->detect(test_image, lines);
if(uint(50) >= lines.size()) ++passedtests;
}
ASSERT_EQ(EPOCHS, passedtests);
}
TEST_F(Imgproc_LSD_NONE, constColor)
{
for (int i = 0; i < EPOCHS; ++i)
{
GenerateConstColor(test_image);
Ptr<LineSegmentDetector> detector = createLineSegmentDetectorPtr(LSD_REFINE_NONE);
detector->detect(test_image, lines);
if(uint(0) == lines.size()) ++passedtests;
}
ASSERT_EQ(EPOCHS, passedtests);
}
TEST_F(Imgproc_LSD_NONE, lines)
{
for (int i = 0; i < EPOCHS; ++i)
{
const unsigned int numOfLines = 1;
GenerateLines(test_image, numOfLines);
Ptr<LineSegmentDetector> detector = createLineSegmentDetectorPtr(LSD_REFINE_NONE);
detector->detect(test_image, lines);
if(numOfLines * 2 == lines.size()) ++passedtests; // * 2 because of Gibbs effect
}
ASSERT_EQ(EPOCHS, passedtests);
}
TEST_F(Imgproc_LSD_NONE, rotatedRect)
{
for (int i = 0; i < EPOCHS; ++i)
{
GenerateRotatedRect(test_image);
Ptr<LineSegmentDetector> detector = createLineSegmentDetectorPtr(LSD_REFINE_NONE);
detector->detect(test_image, lines);
if(uint(8) <= lines.size()) ++passedtests;
}
ASSERT_EQ(EPOCHS, passedtests);
}
#include <iostream>
#include <string>
#include "opencv2/core/core.hpp"
#include "opencv2/core/utility.hpp"
#include "opencv2/imgproc/imgproc.hpp"
#include "opencv2/highgui/highgui.hpp"
using namespace std;
using namespace cv;
int main(int argc, char** argv)
{
std::string in;
if (argc != 2)
{
std::cout << "Usage: lsd_lines [input image]. Now loading building.jpg" << std::endl;
in = "building.jpg";
}
else
{
in = argv[1];
}
Mat image = imread(in, IMREAD_GRAYSCALE);
#if 0
Canny(image, image, 50, 200, 3); // Apply canny edge
#endif
// Create and LSD detector with standard or no refinement.
#if 1
Ptr<LineSegmentDetector> ls = createLineSegmentDetectorPtr(LSD_REFINE_STD);
#else
Ptr<LineSegmentDetector> ls = createLineSegmentDetectorPtr(LSD_REFINE_NONE);
#endif
double start = double(getTickCount());
vector<Vec4i> 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
Mat drawnLines(image);
ls->drawSegments(drawnLines, lines_std);
imshow("Standard refinement", drawnLines);
waitKey();
return 0;
}
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