mirror of https://github.com/opencv/opencv.git
Open Source Computer Vision Library
https://opencv.org/
You can not select more than 25 topics
Topics must start with a letter or number, can include dashes ('-') and can be up to 35 characters long.
308 lines
10 KiB
308 lines
10 KiB
/*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. |
|
// |
|
// |
|
// Intel License Agreement |
|
// For Open Source Computer Vision Library |
|
// |
|
// Copyright (C) 2000, Intel Corporation, 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: |
|
// |
|
// * Redistribution's of source code must retain the above copyright notice, |
|
// this list of conditions and the following disclaimer. |
|
// |
|
// * Redistribution's 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 Intel Corporation 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 "test_precomp.hpp" |
|
|
|
using namespace cv; |
|
using namespace std; |
|
|
|
class CV_CannyTest : public cvtest::ArrayTest |
|
{ |
|
public: |
|
CV_CannyTest(bool custom_deriv = false); |
|
|
|
protected: |
|
void get_test_array_types_and_sizes( int test_case_idx, vector<vector<Size> >& sizes, vector<vector<int> >& types ); |
|
double get_success_error_level( int test_case_idx, int i, int j ); |
|
int prepare_test_case( int test_case_idx ); |
|
void run_func(); |
|
void prepare_to_validation( int ); |
|
int validate_test_results( int /*test_case_idx*/ ); |
|
|
|
int aperture_size; |
|
bool use_true_gradient; |
|
double threshold1, threshold2; |
|
bool test_cpp; |
|
bool test_custom_deriv; |
|
}; |
|
|
|
|
|
CV_CannyTest::CV_CannyTest(bool custom_deriv) |
|
{ |
|
test_array[INPUT].push_back(NULL); |
|
test_array[OUTPUT].push_back(NULL); |
|
test_array[REF_OUTPUT].push_back(NULL); |
|
element_wise_relative_error = true; |
|
aperture_size = 0; |
|
use_true_gradient = false; |
|
threshold1 = threshold2 = 0; |
|
|
|
test_cpp = false; |
|
test_custom_deriv = custom_deriv; |
|
} |
|
|
|
|
|
void CV_CannyTest::get_test_array_types_and_sizes( int test_case_idx, |
|
vector<vector<Size> >& sizes, |
|
vector<vector<int> >& types ) |
|
{ |
|
RNG& rng = ts->get_rng(); |
|
double thresh_range; |
|
|
|
cvtest::ArrayTest::get_test_array_types_and_sizes( test_case_idx, sizes, types ); |
|
types[INPUT][0] = types[OUTPUT][0] = types[REF_OUTPUT][0] = CV_8U; |
|
|
|
aperture_size = cvtest::randInt(rng) % 2 ? 5 : 3; |
|
thresh_range = aperture_size == 3 ? 300 : 1000; |
|
|
|
threshold1 = cvtest::randReal(rng)*thresh_range; |
|
threshold2 = cvtest::randReal(rng)*thresh_range*0.3; |
|
|
|
if( cvtest::randInt(rng) % 2 ) |
|
CV_SWAP( threshold1, threshold2, thresh_range ); |
|
|
|
use_true_gradient = cvtest::randInt(rng) % 2 != 0; |
|
test_cpp = (cvtest::randInt(rng) & 256) == 0; |
|
|
|
ts->printf(cvtest::TS::LOG, "Canny(size = %d x %d, aperture_size = %d, threshold1 = %g, threshold2 = %g, L2 = %s) test_cpp = %s (test case #%d)\n", |
|
sizes[0][0].width, sizes[0][0].height, aperture_size, threshold1, threshold2, use_true_gradient ? "TRUE" : "FALSE", test_cpp ? "TRUE" : "FALSE", test_case_idx); |
|
} |
|
|
|
|
|
int CV_CannyTest::prepare_test_case( int test_case_idx ) |
|
{ |
|
int code = cvtest::ArrayTest::prepare_test_case( test_case_idx ); |
|
if( code > 0 ) |
|
{ |
|
Mat& src = test_mat[INPUT][0]; |
|
GaussianBlur(src, src, Size(11, 11), 5, 5); |
|
} |
|
|
|
return code; |
|
} |
|
|
|
|
|
double CV_CannyTest::get_success_error_level( int /*test_case_idx*/, int /*i*/, int /*j*/ ) |
|
{ |
|
return 0; |
|
} |
|
|
|
|
|
void CV_CannyTest::run_func() |
|
{ |
|
if (test_custom_deriv) |
|
{ |
|
cv::Mat _out = cv::cvarrToMat(test_array[OUTPUT][0]); |
|
cv::Mat src = cv::cvarrToMat(test_array[INPUT][0]); |
|
cv::Mat dx, dy; |
|
int m = aperture_size; |
|
Point anchor(m/2, m/2); |
|
Mat dxkernel = cvtest::calcSobelKernel2D( 1, 0, m, 0 ); |
|
Mat dykernel = cvtest::calcSobelKernel2D( 0, 1, m, 0 ); |
|
cvtest::filter2D(src, dx, CV_16S, dxkernel, anchor, 0, BORDER_REPLICATE); |
|
cvtest::filter2D(src, dy, CV_16S, dykernel, anchor, 0, BORDER_REPLICATE); |
|
cv::Canny(dx, dy, _out, threshold1, threshold2, use_true_gradient); |
|
} |
|
else if(!test_cpp) |
|
{ |
|
cvCanny( test_array[INPUT][0], test_array[OUTPUT][0], threshold1, threshold2, |
|
aperture_size + (use_true_gradient ? CV_CANNY_L2_GRADIENT : 0)); |
|
} |
|
else |
|
{ |
|
cv::Mat _out = cv::cvarrToMat(test_array[OUTPUT][0]); |
|
cv::Canny(cv::cvarrToMat(test_array[INPUT][0]), _out, threshold1, threshold2, |
|
aperture_size + (use_true_gradient ? CV_CANNY_L2_GRADIENT : 0)); |
|
} |
|
} |
|
|
|
|
|
static void |
|
cannyFollow( int x, int y, float lowThreshold, const Mat& mag, Mat& dst ) |
|
{ |
|
static const int ofs[][2] = {{1,0},{1,-1},{0,-1},{-1,-1},{-1,0},{-1,1},{0,1},{1,1}}; |
|
int i; |
|
|
|
dst.at<uchar>(y, x) = (uchar)255; |
|
|
|
for( i = 0; i < 8; i++ ) |
|
{ |
|
int x1 = x + ofs[i][0]; |
|
int y1 = y + ofs[i][1]; |
|
if( (unsigned)x1 < (unsigned)mag.cols && |
|
(unsigned)y1 < (unsigned)mag.rows && |
|
mag.at<float>(y1, x1) > lowThreshold && |
|
!dst.at<uchar>(y1, x1) ) |
|
cannyFollow( x1, y1, lowThreshold, mag, dst ); |
|
} |
|
} |
|
|
|
|
|
static void |
|
test_Canny( const Mat& src, Mat& dst, |
|
double threshold1, double threshold2, |
|
int aperture_size, bool use_true_gradient ) |
|
{ |
|
int m = aperture_size; |
|
Point anchor(m/2, m/2); |
|
const double tan_pi_8 = tan(CV_PI/8.); |
|
const double tan_3pi_8 = tan(CV_PI*3/8); |
|
float lowThreshold = (float)MIN(threshold1, threshold2); |
|
float highThreshold = (float)MAX(threshold1, threshold2); |
|
|
|
int x, y, width = src.cols, height = src.rows; |
|
|
|
Mat dxkernel = cvtest::calcSobelKernel2D( 1, 0, m, 0 ); |
|
Mat dykernel = cvtest::calcSobelKernel2D( 0, 1, m, 0 ); |
|
Mat dx, dy, mag(height, width, CV_32F); |
|
cvtest::filter2D(src, dx, CV_16S, dxkernel, anchor, 0, BORDER_REPLICATE); |
|
cvtest::filter2D(src, dy, CV_16S, dykernel, anchor, 0, BORDER_REPLICATE); |
|
|
|
// calc gradient magnitude |
|
for( y = 0; y < height; y++ ) |
|
{ |
|
for( x = 0; x < width; x++ ) |
|
{ |
|
int dxval = dx.at<short>(y, x), dyval = dy.at<short>(y, x); |
|
mag.at<float>(y, x) = use_true_gradient ? |
|
(float)sqrt((double)(dxval*dxval + dyval*dyval)) : |
|
(float)(fabs((double)dxval) + fabs((double)dyval)); |
|
} |
|
} |
|
|
|
// calc gradient direction, do nonmaxima suppression |
|
for( y = 0; y < height; y++ ) |
|
{ |
|
for( x = 0; x < width; x++ ) |
|
{ |
|
|
|
float a = mag.at<float>(y, x), b = 0, c = 0; |
|
int y1 = 0, y2 = 0, x1 = 0, x2 = 0; |
|
|
|
if( a <= lowThreshold ) |
|
continue; |
|
|
|
int dxval = dx.at<short>(y, x); |
|
int dyval = dy.at<short>(y, x); |
|
|
|
double tg = dxval ? (double)dyval/dxval : DBL_MAX*CV_SIGN(dyval); |
|
|
|
if( fabs(tg) < tan_pi_8 ) |
|
{ |
|
y1 = y2 = y; x1 = x + 1; x2 = x - 1; |
|
} |
|
else if( tan_pi_8 <= tg && tg <= tan_3pi_8 ) |
|
{ |
|
y1 = y + 1; y2 = y - 1; x1 = x + 1; x2 = x - 1; |
|
} |
|
else if( -tan_3pi_8 <= tg && tg <= -tan_pi_8 ) |
|
{ |
|
y1 = y - 1; y2 = y + 1; x1 = x + 1; x2 = x - 1; |
|
} |
|
else |
|
{ |
|
assert( fabs(tg) > tan_3pi_8 ); |
|
x1 = x2 = x; y1 = y + 1; y2 = y - 1; |
|
} |
|
|
|
if( (unsigned)y1 < (unsigned)height && (unsigned)x1 < (unsigned)width ) |
|
b = (float)fabs(mag.at<float>(y1, x1)); |
|
|
|
if( (unsigned)y2 < (unsigned)height && (unsigned)x2 < (unsigned)width ) |
|
c = (float)fabs(mag.at<float>(y2, x2)); |
|
|
|
if( (a > b || (a == b && ((x1 == x+1 && y1 == y) || (x1 == x && y1 == y+1)))) && a > c ) |
|
; |
|
else |
|
mag.at<float>(y, x) = -a; |
|
} |
|
} |
|
|
|
dst = Scalar::all(0); |
|
|
|
// hysteresis threshold |
|
for( y = 0; y < height; y++ ) |
|
{ |
|
for( x = 0; x < width; x++ ) |
|
if( mag.at<float>(y, x) > highThreshold && !dst.at<uchar>(y, x) ) |
|
cannyFollow( x, y, lowThreshold, mag, dst ); |
|
} |
|
} |
|
|
|
|
|
void CV_CannyTest::prepare_to_validation( int ) |
|
{ |
|
Mat src = test_mat[INPUT][0], dst = test_mat[REF_OUTPUT][0]; |
|
test_Canny( src, dst, threshold1, threshold2, aperture_size, use_true_gradient ); |
|
} |
|
|
|
|
|
int CV_CannyTest::validate_test_results( int test_case_idx ) |
|
{ |
|
int code = cvtest::TS::OK, nz0; |
|
prepare_to_validation(test_case_idx); |
|
|
|
double err = cvtest::norm(test_mat[OUTPUT][0], test_mat[REF_OUTPUT][0], CV_L1); |
|
if( err == 0 ) |
|
return code; |
|
|
|
if( err != cvRound(err) || cvRound(err)%255 != 0 ) |
|
{ |
|
ts->printf( cvtest::TS::LOG, "Some of the pixels, produced by Canny, are not 0's or 255's; the difference is %g\n", err ); |
|
ts->set_failed_test_info( cvtest::TS::FAIL_INVALID_OUTPUT ); |
|
return code; |
|
} |
|
|
|
nz0 = cvRound(cvtest::norm(test_mat[REF_OUTPUT][0], CV_L1)/255); |
|
err = (err/255/MAX(nz0,100))*100; |
|
if( err > 1 ) |
|
{ |
|
ts->printf( cvtest::TS::LOG, "Too high percentage of non-matching edge pixels = %g%%\n", err); |
|
ts->set_failed_test_info( cvtest::TS::FAIL_BAD_ACCURACY ); |
|
} |
|
|
|
return code; |
|
} |
|
|
|
TEST(Imgproc_Canny, accuracy) { CV_CannyTest test; test.safe_run(); } |
|
TEST(Imgproc_Canny, accuracy_deriv) { CV_CannyTest test(true); test.safe_run(); } |
|
|
|
/* End of file. */
|
|
|