1
0
mirror of https://github.com/opencv/opencv.git synced 2026-07-30 15:53:03 +04:00

Merge pull request #25842 from mshabunin:cpp-imgproc-test-4.x

imgproc: remove C-API usage from tests #25842

Final cleanup will be done in 5.x after regular merge.

Some tests have been reworked, some required only slight modifications.
This commit is contained in:
Maksim Shabunin
2024-07-04 16:29:08 +03:00
committed by GitHub
parent efbc9f0b66
commit 94b7a2d320
7 changed files with 831 additions and 2435 deletions
+71 -162
View File
@@ -43,130 +43,7 @@
namespace opencv_test { namespace {
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;
Mat img;
};
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_custom_deriv = custom_deriv;
const char imgPath[] = "shared/fruits.png";
img = cv::imread(cvtest::TS::ptr()->get_data_path() + imgPath, IMREAD_GRAYSCALE);
}
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 )
{
RNG& rng = ts->get_rng();
Mat& src = test_mat[INPUT][0];
//GaussianBlur(src, src, Size(11, 11), 5, 5);
if(src.cols > img.cols || src.rows > img.rows)
resize(img, src, src.size(), 0, 0, INTER_LINEAR_EXACT);
else
img(
Rect(
cvtest::randInt(rng) % (img.cols-src.cols),
cvtest::randInt(rng) % (img.rows-src.rows),
src.cols,
src.rows
)
).copyTo(src);
GaussianBlur(src, src, Size(5, 5), 0);
}
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
{
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);
}
}
static void
cannyFollow( int x, int y, float lowThreshold, const Mat& mag, Mat& dst )
static void Canny_reference_follow( 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;
@@ -181,16 +58,15 @@ cannyFollow( int x, int y, float lowThreshold, const Mat& mag, Mat& dst )
(unsigned)y1 < (unsigned)mag.rows &&
mag.at<float>(y1, x1) > lowThreshold &&
!dst.at<uchar>(y1, x1) )
cannyFollow( x1, y1, lowThreshold, mag, dst );
Canny_reference_follow( x1, y1, lowThreshold, mag, dst );
}
}
static void
test_Canny( const Mat& src, Mat& dst,
static void Canny_reference( const Mat& src, Mat& dst,
double threshold1, double threshold2,
int aperture_size, bool use_true_gradient )
{
dst.create(src.size(), src.type());
int m = aperture_size;
Point anchor(m/2, m/2);
const double tan_pi_8 = tan(CV_PI/8.);
@@ -273,47 +149,80 @@ test_Canny( const Mat& src, Mat& dst,
{
for( x = 0; x < width; x++ )
if( mag.at<float>(y, x) > highThreshold && !dst.at<uchar>(y, x) )
cannyFollow( x, y, lowThreshold, mag, dst );
Canny_reference_follow( x, y, lowThreshold, mag, dst );
}
}
//==============================================================================
void CV_CannyTest::prepare_to_validation( int )
// aperture, true gradient
typedef testing::TestWithParam<testing::tuple<int, bool>> Canny_Modes;
TEST_P(Canny_Modes, accuracy)
{
Mat src = test_mat[INPUT][0], dst = test_mat[REF_OUTPUT][0];
test_Canny( src, dst, threshold1, threshold2, aperture_size, use_true_gradient );
const int aperture = get<0>(GetParam());
const bool trueGradient = get<1>(GetParam());
const double range = aperture == 3 ? 300. : 1000.;
RNG & rng = TS::ptr()->get_rng();
for (int ITER = 0; ITER < 20; ++ITER)
{
SCOPED_TRACE(cv::format("iteration %d", ITER));
const std::string fname = cvtest::findDataFile("shared/fruits.png");
const Mat original = cv::imread(fname, IMREAD_GRAYSCALE);
const double thresh1 = rng.uniform(0., range);
const double thresh2 = rng.uniform(0., range * 0.3);
const Size sz(rng.uniform(127, 800), rng.uniform(127, 600));
const Size osz = original.size();
// preparation
Mat img;
if (sz.width >= osz.width || sz.height >= osz.height)
{
// larger image -> scale
resize(original, img, sz, 0, 0, INTER_LINEAR_EXACT);
}
else
{
// smaller image -> crop
Point origin(rng.uniform(0, osz.width - sz.width), rng.uniform(0, osz.height - sz.height));
Rect roi(origin, sz);
original(roi).copyTo(img);
}
GaussianBlur(img, img, Size(5, 5), 0);
// regular function
Mat result;
{
cv::Canny(img, result, thresh1, thresh2, aperture, trueGradient);
}
// custom derivatives
Mat customResult;
{
Mat dxkernel = cvtest::calcSobelKernel2D(1, 0, aperture, 0);
Mat dykernel = cvtest::calcSobelKernel2D(0, 1, aperture, 0);
Point anchor(aperture / 2, aperture / 2);
cv::Mat dx, dy;
cvtest::filter2D(img, dx, CV_16S, dxkernel, anchor, 0, BORDER_REPLICATE);
cvtest::filter2D(img, dy, CV_16S, dykernel, anchor, 0, BORDER_REPLICATE);
cv::Canny(dx, dy, customResult, thresh1, thresh2, trueGradient);
}
Mat reference;
Canny_reference(img, reference, thresh1, thresh2, aperture, trueGradient);
EXPECT_MAT_NEAR(result, reference, 0);
EXPECT_MAT_NEAR(customResult, reference, 0);
}
}
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(); }
INSTANTIATE_TEST_CASE_P(/**/, Canny_Modes,
testing::Combine(
testing::Values(3, 5),
testing::Values(true, false)));
/*