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#include "test_precomp.hpp"
using namespace cv;
using namespace std;
class CV_CannyTest : public cvtest::ArrayTest
{
public:
CV_CannyTest();
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;
};
CV_CannyTest::CV_CannyTest()
{
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;
}
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;
}
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_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(); }
/* End of file. */