potok/opencv
1
0
Fork 0
mirror of https://github.com/opencv/opencv.git synced 2026-07-30 07:43:03 +04:00
Code Packages Releases Wiki Activity

Merge remote-tracking branch 'upstream/3.4' into merge-3.4

Browse Source
This commit is contained in:
Alexander Alekhin
2023-01-21 18:19:39 +00:00
parent 3085fc6345 b71a168937
commit 18cbfa4a4f
74 changed files with 249 additions and 228 deletions
Download Patch File Download Diff File Expand all files Collapse all files
modules/calib3d/test/test_calibration_hand_eye.cpp
+4 -4
View File
@@ -427,9 +427,9 @@ public:
eps_rvec_noise[CALIB_HAND_EYE_ANDREFF] = 1.0e-2;
eps_rvec_noise[CALIB_HAND_EYE_DANIILIDIS] = 1.0e-2;
eps_tvec_noise[CALIB_HAND_EYE_TSAI] = 5.0e-2;
eps_tvec_noise[CALIB_HAND_EYE_PARK] = 5.0e-2;
eps_tvec_noise[CALIB_HAND_EYE_HORAUD] = 5.0e-2;
eps_tvec_noise[CALIB_HAND_EYE_TSAI] = 7.0e-2;
eps_tvec_noise[CALIB_HAND_EYE_PARK] = 7.0e-2;
eps_tvec_noise[CALIB_HAND_EYE_HORAUD] = 7.0e-2;
if (eyeToHandConfig)
{
eps_tvec_noise[CALIB_HAND_EYE_ANDREFF] = 7.0e-2;
@@ -454,7 +454,7 @@ void CV_CalibrateHandEyeTest::run(int)
{
ts->set_failed_test_info(cvtest::TS::OK);
RNG& rng = ts->get_rng();
RNG& rng = cv::theRNG();
std::vector<std::vector<double> > vec_rvec_diff(5);
std::vector<std::vector<double> > vec_tvec_diff(5);
modules/calib3d/test/test_chesscorners.cpp
+1 -1
View File
@@ -224,7 +224,7 @@ void CV_ChessboardDetectorTest::run_batch( const string& filename )
/* read the image */
String img_file = board_list[idx * 2];
Mat gray = imread( folder + img_file, 0);
Mat gray = imread( folder + img_file, IMREAD_GRAYSCALE);
if( gray.empty() )
{
modules/calib3d/test/test_homography.cpp
+26 -57
View File
@@ -73,60 +73,27 @@ int METHOD[METHODS_COUNT] = {0, cv::RANSAC, cv::LMEDS, cv::RHO};
using namespace cv;
using namespace std;
class CV_HomographyTest: public cvtest::ArrayTest
{
public:
CV_HomographyTest();
~CV_HomographyTest();
void run (int);
namespace HomographyTestUtils {
protected:
static const float max_diff = 0.032f;
static const float max_2diff = 0.020f;
static const int image_size = 100;
static const double reproj_threshold = 3.0;
static const double sigma = 0.01;
int method;
int image_size;
double reproj_threshold;
double sigma;
private:
float max_diff, max_2diff;
bool check_matrix_size(const cv::Mat& H);
bool check_matrix_diff(const cv::Mat& original, const cv::Mat& found, const int norm_type, double &diff);
int check_ransac_mask_1(const Mat& src, const Mat& mask);
int check_ransac_mask_2(const Mat& original_mask, const Mat& found_mask);
void print_information_1(int j, int N, int method, const Mat& H);
void print_information_2(int j, int N, int method, const Mat& H, const Mat& H_res, int k, double diff);
void print_information_3(int method, int j, int N, const Mat& mask);
void print_information_4(int method, int j, int N, int k, int l, double diff);
void print_information_5(int method, int j, int N, int l, double diff);
void print_information_6(int method, int j, int N, int k, double diff, bool value);
void print_information_7(int method, int j, int N, int k, double diff, bool original_value, bool found_value);
void print_information_8(int method, int j, int N, int k, int l, double diff);
};
CV_HomographyTest::CV_HomographyTest() : max_diff(1e-2f), max_2diff(2e-2f)
{
method = 0;
image_size = 100;
reproj_threshold = 3.0;
sigma = 0.01;
}
CV_HomographyTest::~CV_HomographyTest() {}
bool CV_HomographyTest::check_matrix_size(const cv::Mat& H)
static bool check_matrix_size(const cv::Mat& H)
{
return (H.rows == 3) && (H.cols == 3);
}
bool CV_HomographyTest::check_matrix_diff(const cv::Mat& original, const cv::Mat& found, const int norm_type, double &diff)
static bool check_matrix_diff(const cv::Mat& original, const cv::Mat& found, const int norm_type, double &diff)
{
diff = cvtest::norm(original, found, norm_type);
return diff <= max_diff;
}
int CV_HomographyTest::check_ransac_mask_1(const Mat& src, const Mat& mask)
static int check_ransac_mask_1(const Mat& src, const Mat& mask)
{
if (!(mask.cols == 1) && (mask.rows == src.cols)) return 1;
if (countNonZero(mask) < mask.rows) return 2;
@@ -134,14 +101,14 @@ int CV_HomographyTest::check_ransac_mask_1(const Mat& src, const Mat& mask)
return 0;
}
int CV_HomographyTest::check_ransac_mask_2(const Mat& original_mask, const Mat& found_mask)
static int check_ransac_mask_2(const Mat& original_mask, const Mat& found_mask)
{
if (!(found_mask.cols == 1) && (found_mask.rows == original_mask.rows)) return 1;
for (int i = 0; i < found_mask.rows; ++i) if (found_mask.at<uchar>(i, 0) > 1) return 2;
return 0;
}
void CV_HomographyTest::print_information_1(int j, int N, int _method, const Mat& H)
static void print_information_1(int j, int N, int _method, const Mat& H)
{
cout << endl; cout << "Checking for homography matrix sizes..." << endl; cout << endl;
cout << "Type of srcPoints: "; if ((j>-1) && (j<2)) cout << "Mat of CV_32FC2"; else cout << "vector <Point2f>";
@@ -153,7 +120,7 @@ void CV_HomographyTest::print_information_1(int j, int N, int _method, const Mat
cout << "Number of rows: " << H.rows << " Number of cols: " << H.cols << endl; cout << endl;
}
void CV_HomographyTest::print_information_2(int j, int N, int _method, const Mat& H, const Mat& H_res, int k, double diff)
static void print_information_2(int j, int N, int _method, const Mat& H, const Mat& H_res, int k, double diff)
{
cout << endl; cout << "Checking for accuracy of homography matrix computing..." << endl; cout << endl;
cout << "Type of srcPoints: "; if ((j>-1) && (j<2)) cout << "Mat of CV_32FC2"; else cout << "vector <Point2f>";
@@ -169,7 +136,7 @@ void CV_HomographyTest::print_information_2(int j, int N, int _method, const Mat
cout << "Maximum allowed difference: " << max_diff << endl; cout << endl;
}
void CV_HomographyTest::print_information_3(int _method, int j, int N, const Mat& mask)
static void print_information_3(int _method, int j, int N, const Mat& mask)
{
cout << endl; cout << "Checking for inliers/outliers mask..." << endl; cout << endl;
cout << "Type of srcPoints: "; if ((j>-1) && (j<2)) cout << "Mat of CV_32FC2"; else cout << "vector <Point2f>";
@@ -181,7 +148,7 @@ void CV_HomographyTest::print_information_3(int _method, int j, int N, const Mat
cout << "Number of rows: " << mask.rows << " Number of cols: " << mask.cols << endl; cout << endl;
}
void CV_HomographyTest::print_information_4(int _method, int j, int N, int k, int l, double diff)
static void print_information_4(int _method, int j, int N, int k, int l, double diff)
{
cout << endl; cout << "Checking for accuracy of reprojection error computing..." << endl; cout << endl;
cout << "Method: "; if (_method == 0) cout << 0 << endl; else cout << "CV_LMEDS" << endl;
@@ -195,7 +162,7 @@ void CV_HomographyTest::print_information_4(int _method, int j, int N, int k, in
cout << "Maximum allowed difference: " << max_2diff << endl; cout << endl;
}
void CV_HomographyTest::print_information_5(int _method, int j, int N, int l, double diff)
static void print_information_5(int _method, int j, int N, int l, double diff)
{
cout << endl; cout << "Checking for accuracy of reprojection error computing..." << endl; cout << endl;
cout << "Method: "; if (_method == 0) cout << 0 << endl; else cout << "CV_LMEDS" << endl;
@@ -208,7 +175,7 @@ void CV_HomographyTest::print_information_5(int _method, int j, int N, int l, do
cout << "Maximum allowed difference: " << max_diff << endl; cout << endl;
}
void CV_HomographyTest::print_information_6(int _method, int j, int N, int k, double diff, bool value)
static void print_information_6(int _method, int j, int N, int k, double diff, bool value)
{
cout << endl; cout << "Checking for inliers/outliers mask..." << endl; cout << endl;
cout << "Method: "; if (_method == RANSAC) cout << "RANSAC" << endl; else if (_method == cv::RHO) cout << "RHO" << endl; else cout << _method << endl;
@@ -221,7 +188,7 @@ void CV_HomographyTest::print_information_6(int _method, int j, int N, int k, do
cout << "Value of found mask: "<< value << endl; cout << endl;
}
void CV_HomographyTest::print_information_7(int _method, int j, int N, int k, double diff, bool original_value, bool found_value)
static void print_information_7(int _method, int j, int N, int k, double diff, bool original_value, bool found_value)
{
cout << endl; cout << "Checking for inliers/outliers mask..." << endl; cout << endl;
cout << "Method: "; if (_method == RANSAC) cout << "RANSAC" << endl; else if (_method == cv::RHO) cout << "RHO" << endl; else cout << _method << endl;
@@ -234,7 +201,7 @@ void CV_HomographyTest::print_information_7(int _method, int j, int N, int k, do
cout << "Value of original mask: "<< original_value << " Value of found mask: " << found_value << endl; cout << endl;
}
void CV_HomographyTest::print_information_8(int _method, int j, int N, int k, int l, double diff)
static void print_information_8(int _method, int j, int N, int k, int l, double diff)
{
cout << endl; cout << "Checking for reprojection error of inlier..." << endl; cout << endl;
cout << "Method: "; if (_method == RANSAC) cout << "RANSAC" << endl; else if (_method == cv::RHO) cout << "RHO" << endl; else cout << _method << endl;
@@ -248,11 +215,15 @@ void CV_HomographyTest::print_information_8(int _method, int j, int N, int k, in
cout << "Maximum allowed difference: " << max_2diff << endl; cout << endl;
}
void CV_HomographyTest::run(int)
} // HomographyTestUtils::
TEST(Calib3d_Homography, accuracy)
{
using namespace HomographyTestUtils;
for (int N = MIN_COUNT_OF_POINTS; N <= MAX_COUNT_OF_POINTS; ++N)
{
RNG& rng = ts->get_rng();
RNG& rng = cv::theRNG();
float *src_data = new float [2*N];
@@ -308,7 +279,7 @@ void CV_HomographyTest::run(int)
for (int i = 0; i < METHODS_COUNT; ++i)
{
method = METHOD[i];
const int method = METHOD[i];
switch (method)
{
case 0:
@@ -411,7 +382,7 @@ void CV_HomographyTest::run(int)
for (int i = 0; i < METHODS_COUNT; ++i)
{
method = METHOD[i];
const int method = METHOD[i];
switch (method)
{
case 0:
@@ -573,8 +544,6 @@ void CV_HomographyTest::run(int)
}
}
TEST(Calib3d_Homography, accuracy) { CV_HomographyTest test; test.safe_run(); }
TEST(Calib3d_Homography, EKcase)
{
float pt1data[] =
modules/calib3d/test/test_stereomatching.cpp
+6 -6
View File
@@ -456,8 +456,8 @@ void CV_StereoMatchingTest::run(int)
string datasetFullDirName = dataPath + DATASETS_DIR + datasetName + "/";
Mat leftImg = imread(datasetFullDirName + LEFT_IMG_NAME);
Mat rightImg = imread(datasetFullDirName + RIGHT_IMG_NAME);
Mat trueLeftDisp = imread(datasetFullDirName + TRUE_LEFT_DISP_NAME, 0);
Mat trueRightDisp = imread(datasetFullDirName + TRUE_RIGHT_DISP_NAME, 0);
Mat trueLeftDisp = imread(datasetFullDirName + TRUE_LEFT_DISP_NAME, IMREAD_GRAYSCALE);
Mat trueRightDisp = imread(datasetFullDirName + TRUE_RIGHT_DISP_NAME, IMREAD_GRAYSCALE);
Rect calcROI;
if( leftImg.empty() || rightImg.empty() || trueLeftDisp.empty() )
@@ -835,9 +835,9 @@ TEST_P(Calib3d_StereoBM_BufferBM, memAllocsTest)
const int SADWindowSize = get<1>(get<1>(GetParam()));
String path = cvtest::TS::ptr()->get_data_path() + "cv/stereomatching/datasets/teddy/";
Mat leftImg = imread(path + "im2.png", 0);
Mat leftImg = imread(path + "im2.png", IMREAD_GRAYSCALE);
ASSERT_FALSE(leftImg.empty());
Mat rightImg = imread(path + "im6.png", 0);
Mat rightImg = imread(path + "im6.png", IMREAD_GRAYSCALE);
ASSERT_FALSE(rightImg.empty());
Mat leftDisp;
{
@@ -923,9 +923,9 @@ TEST(Calib3d_StereoSGBM, regression) { CV_StereoSGBMTest test; test.safe_run();
TEST(Calib3d_StereoSGBM_HH4, regression)
{
String path = cvtest::TS::ptr()->get_data_path() + "cv/stereomatching/datasets/teddy/";
Mat leftImg = imread(path + "im2.png", 0);
Mat leftImg = imread(path + "im2.png", IMREAD_GRAYSCALE);
ASSERT_FALSE(leftImg.empty());
Mat rightImg = imread(path + "im6.png", 0);
Mat rightImg = imread(path + "im6.png", IMREAD_GRAYSCALE);
ASSERT_FALSE(rightImg.empty());
Mat testData = imread(path + "disp2_hh4.png",-1);
ASSERT_FALSE(testData.empty());
modules/core/include/opencv2/core/fast_math.hpp
+1 -1
View File
@@ -306,7 +306,7 @@ CV_INLINE int cvIsInf( double value )
#elif defined(__x86_64__) || defined(_M_X64) || defined(__aarch64__) || defined(_M_ARM64) || defined(__PPC64__) || defined(__loongarch64)
Cv64suf ieee754;
ieee754.f = value;
return (ieee754.u & 0x7fffffff00000000) ==
return (ieee754.u & 0x7fffffffffffffff) ==
0x7ff0000000000000;
#else
Cv64suf ieee754;
modules/core/src/system.cpp
+9
View File
@@ -247,6 +247,7 @@ std::wstring GetTempFileNameWinRT(std::wstring prefix)
#if defined __MACH__ && defined __APPLE__
#include <mach/mach.h>
#include <mach/mach_time.h>
#include <sys/sysctl.h>
#endif
#endif
@@ -635,6 +636,14 @@ struct HWFeatures
#if (defined __ARM_FP && (((__ARM_FP & 0x2) != 0) && defined __ARM_NEON__))
have[CV_CPU_FP16] = true;
#endif
#if (defined __ARM_FEATURE_DOTPROD)
int has_feat_dotprod = 0;
size_t has_feat_dotprod_size = sizeof(has_feat_dotprod);
sysctlbyname("hw.optional.arm.FEAT_DotProd", &has_feat_dotprod, &has_feat_dotprod_size, NULL, 0);
if (has_feat_dotprod) {
have[CV_CPU_NEON_DOTPROD] = true;
}
#endif
#elif (defined __clang__)
#if (defined __ARM_NEON__ || (defined __ARM_NEON && defined __aarch64__))
have[CV_CPU_NEON] = true;
modules/core/test/test_math.cpp
+14
View File
@@ -3992,6 +3992,13 @@ TEST(Core_FastMath, InlineNaN)
EXPECT_EQ( cvIsNaN((double) NAN), 1);
EXPECT_EQ( cvIsNaN((double) -NAN), 1);
EXPECT_EQ( cvIsNaN(0.0), 0);
// Regression: check the +/-Inf cases
Cv64suf suf;
suf.u = 0x7FF0000000000000UL;
EXPECT_EQ( cvIsNaN(suf.f), 0);
suf.u = 0xFFF0000000000000UL;
EXPECT_EQ( cvIsNaN(suf.f), 0);
}
TEST(Core_FastMath, InlineIsInf)
@@ -4003,6 +4010,13 @@ TEST(Core_FastMath, InlineIsInf)
EXPECT_EQ( cvIsInf((double) HUGE_VAL), 1);
EXPECT_EQ( cvIsInf((double) -HUGE_VAL), 1);
EXPECT_EQ( cvIsInf(0.0), 0);
// Regression: check the cases of 0x7FF00000xxxxxxxx
Cv64suf suf;
suf.u = 0x7FF0000000000001UL;
EXPECT_EQ( cvIsInf(suf.f), 0);
suf.u = 0x7FF0000012345678UL;
EXPECT_EQ( cvIsInf(suf.f), 0);
}
}} // namespace
modules/dnn/test/test_int8_layers.cpp
+3
View File
@@ -974,6 +974,9 @@ TEST_P(Test_Int8_nets, opencv_face_detector)
TEST_P(Test_Int8_nets, EfficientDet)
{
if (cvtest::skipUnstableTests)
throw SkipTestException("Skip unstable test"); // detail: https://github.com/opencv/opencv/pull/23167
applyTestTag(CV_TEST_TAG_DEBUG_VERYLONG);
if (target == DNN_TARGET_OPENCL_FP16 && !ocl::Device::getDefault().isIntel())
applyTestTag(CV_TEST_TAG_DNN_SKIP_OPENCL_FP16);
modules/features2d/src/sift.simd.hpp
+8 -2
View File
@@ -960,11 +960,18 @@ if( dstMat.type() == CV_32F )
__dst = v_min(v_max(v_cvt_f32(v_round(__dst * __nrm2)), __min), __max);
v_store(dst + k, __dst);
}
#endif
#if defined(__GNUC__) && __GNUC__ >= 9
#pragma GCC diagnostic push
#pragma GCC diagnostic ignored "-Waggressive-loop-optimizations" // iteration XX invokes undefined behavior
#endif
for( ; k < len; k++ )
{
dst[k] = saturate_cast<uchar>(rawDst[k]*nrm2);
}
#if defined(__GNUC__) && __GNUC__ >= 9
#pragma GCC diagnostic pop
#endif
}
else // CV_8U
{
@@ -984,9 +991,8 @@ else // CV_8U
#endif
#if defined(__GNUC__) && __GNUC__ >= 9
// avoid warning "iteration 7 invokes undefined behavior" on Linux ARM64
#pragma GCC diagnostic push
#pragma GCC diagnostic ignored "-Waggressive-loop-optimizations"
#pragma GCC diagnostic ignored "-Waggressive-loop-optimizations" // iteration XX invokes undefined behavior
#endif
for( ; k < len; k++ )
{
modules/features2d/test/test_descriptors_regression.cpp
+2 -2
View File
@@ -82,7 +82,7 @@ TEST( Features2d_DescriptorExtractor, batch_ORB )
for( i = 0; i < n; i++ )
{
string imgname = format("%s/img%d.png", path.c_str(), i+1);
Mat img = imread(imgname, 0);
Mat img = imread(imgname, IMREAD_GRAYSCALE);
imgs.push_back(img);
}
@@ -110,7 +110,7 @@ TEST( Features2d_DescriptorExtractor, batch_SIFT )
for( i = 0; i < n; i++ )
{
string imgname = format("%s/img%d.png", path.c_str(), i+1);
Mat img = imread(imgname, 0);
Mat img = imread(imgname, IMREAD_GRAYSCALE);
imgs.push_back(img);
}
modules/imgcodecs/misc/java/test/ImgcodecsTest.java
+1 -1
View File
@@ -45,7 +45,7 @@ public class ImgcodecsTest extends OpenCVTestCase {
}
public void testImreadStringInt() {
dst = Imgcodecs.imread(OpenCVTestRunner.LENA_PATH, 0);
dst = Imgcodecs.imread(OpenCVTestRunner.LENA_PATH, Imgcodecs.IMREAD_GRAYSCALE);
assertFalse(dst.empty());
assertEquals(1, dst.channels());
assertTrue(512 == dst.cols());
modules/imgproc/test/test_color.cpp
+2 -2
View File
@@ -1077,7 +1077,7 @@ double CV_ColorLabTest::get_success_error_level( int /*test_case_idx*/, int i, i
{
int depth = test_mat[i][j].depth();
// j == 0 is for forward code, j == 1 is for inverse code
return (depth == CV_8U) ? (srgb ? 32 : 8) :
return (depth == CV_8U) ? (srgb ? 37 : 8) :
//(depth == CV_16U) ? 32 : // 16u is disabled
srgb ? ((j == 0) ? 0.4 : 0.0055) : 1e-3;
}
@@ -1256,7 +1256,7 @@ double CV_ColorLuvTest::get_success_error_level( int /*test_case_idx*/, int i, i
{
int depth = test_mat[i][j].depth();
// j == 0 is for forward code, j == 1 is for inverse code
return (depth == CV_8U) ? (srgb ? 36 : 8) :
return (depth == CV_8U) ? (srgb ? 37 : 8) :
//(depth == CV_16U) ? 32 : // 16u is disabled
5e-2;
}
modules/imgproc/test/test_connectedcomponents.cpp
+1 -1
View File
@@ -81,7 +81,7 @@ void CV_ConnectedComponentsTest::run(int /* start_from */)
int ccltype[] = { cv::CCL_DEFAULT, cv::CCL_WU, cv::CCL_GRANA, cv::CCL_BOLELLI, cv::CCL_SAUF, cv::CCL_BBDT, cv::CCL_SPAGHETTI };
string exp_path = string(ts->get_data_path()) + "connectedcomponents/ccomp_exp.png";
Mat exp = imread(exp_path, 0);
Mat exp = imread(exp_path, IMREAD_GRAYSCALE);
Mat orig = imread(string(ts->get_data_path()) + "connectedcomponents/concentric_circles.png", 0);
if (orig.empty())
modules/imgproc/test/test_convhull.cpp
+1 -1
View File
@@ -180,7 +180,7 @@ cvTsIsPointOnLineSegment(const cv::Point2f &x, const cv::Point2f &a, const cv::P
double d2 = cvTsDist(cvPoint2D32f(x.x, x.y), cvPoint2D32f(b.x, b.y));
double d3 = cvTsDist(cvPoint2D32f(a.x, a.y), cvPoint2D32f(b.x, b.y));
return (abs(d1 + d2 - d3) <= (1E-5));
return (abs(d1 + d2 - d3) <= (1E-4));
}
modules/imgproc/test/test_imgproc_umat.cpp
+1 -1
View File
@@ -53,7 +53,7 @@ protected:
void run(int)
{
string imgpath = string(ts->get_data_path()) + "shared/lena.png";
Mat img = imread(imgpath, 1), gray, smallimg, result;
Mat img = imread(imgpath, IMREAD_COLOR), gray, smallimg, result;
UMat uimg = img.getUMat(ACCESS_READ), ugray, usmallimg, uresult;
cvtColor(img, gray, COLOR_BGR2GRAY);
modules/imgproc/test/test_imgwarp.cpp
-1
View File
@@ -102,7 +102,6 @@ void CV_ImgWarpBaseTest::get_test_array_types_and_sizes( int test_case_idx,
int cn = cvtest::randInt(rng) % 3 + 1;
cvtest::ArrayTest::get_test_array_types_and_sizes( test_case_idx, sizes, types );
depth = depth == 0 ? CV_8U : depth == 1 ? CV_16U : CV_32F;
cn += cn == 2;
types[INPUT][0] = types[INPUT_OUTPUT][0] = types[REF_INPUT_OUTPUT][0] = CV_MAKETYPE(depth, cn);
if( test_array[INPUT].size() > 1 )
modules/imgproc/test/test_imgwarp_strict.cpp
+1 -5
View File
@@ -151,8 +151,6 @@ void CV_ImageWarpBaseTest::generate_test_data()
depth = rng.uniform(0, CV_64F);
int cn = rng.uniform(1, 4);
while (cn == 2)
cn = rng.uniform(1, 4);
src.create(ssize, CV_MAKE_TYPE(depth, cn));
@@ -237,7 +235,7 @@ float CV_ImageWarpBaseTest::get_success_error_level(int _interpolation, int) con
else if (_interpolation == INTER_LANCZOS4)
return 1.0f;
else if (_interpolation == INTER_NEAREST)
return 1.0f;
return 255.0f; // FIXIT: check is not reliable for Black/White (0/255) images
else if (_interpolation == INTER_AREA)
return 2.0f;
else
@@ -430,8 +428,6 @@ void CV_Resize_Test::generate_test_data()
depth = rng.uniform(0, CV_64F);
int cn = rng.uniform(1, 4);
while (cn == 2)
cn = rng.uniform(1, 4);
src.create(ssize, CV_MAKE_TYPE(depth, cn));
modules/imgproc/test/test_watershed.cpp
+1 -1
View File
@@ -60,7 +60,7 @@ CV_WatershedTest::~CV_WatershedTest() {}
void CV_WatershedTest::run( int /* start_from */)
{
string exp_path = string(ts->get_data_path()) + "watershed/wshed_exp.png";
Mat exp = imread(exp_path, 0);
Mat exp = imread(exp_path, IMREAD_GRAYSCALE);
Mat orig = imread(string(ts->get_data_path()) + "inpaint/orig.png");
FileStorage fs(string(ts->get_data_path()) + "watershed/comp.xml", FileStorage::READ);
modules/java/test/android_test/src/org/opencv/test/OpenCVTestCase.java
+1 -1
View File
@@ -149,7 +149,7 @@ public class OpenCVTestCase extends TestCase {
rgba128 = new Mat(matSize, matSize, CvType.CV_8UC4, Scalar.all(128));
rgbLena = Imgcodecs.imread(OpenCVTestRunner.LENA_PATH);
grayChess = Imgcodecs.imread(OpenCVTestRunner.CHESS_PATH, 0);
grayChess = Imgcodecs.imread(OpenCVTestRunner.CHESS_PATH, Imgcodecs.IMREAD_GRAYSCALE);
gray255_32f_3d = new Mat(new int[]{matSize, matSize, matSize}, CvType.CV_32F, new Scalar(255.0));
modules/java/test/pure_test/src/org/opencv/test/OpenCVTestCase.java
+1 -1
View File
@@ -175,7 +175,7 @@ public class OpenCVTestCase extends TestCase {
rgba128 = new Mat(matSize, matSize, CvType.CV_8UC4, Scalar.all(128));
rgbLena = Imgcodecs.imread(OpenCVTestRunner.LENA_PATH);
grayChess = Imgcodecs.imread(OpenCVTestRunner.CHESS_PATH, 0);
grayChess = Imgcodecs.imread(OpenCVTestRunner.CHESS_PATH, Imgcodecs.IMREAD_GRAYSCALE);
gray255_32f_3d = new Mat(new int[]{matSize, matSize, matSize}, CvType.CV_32F, new Scalar(255.0));
modules/objdetect/test/test_cascadeandhog.cpp
+1 -1
View File
@@ -138,7 +138,7 @@ int CV_DetectorTest::prepareData( FileStorage& _fs )
String filename;
it >> filename;
imageFilenames.push_back(filename);
Mat img = imread( dataPath+filename, 1 );
Mat img = imread( dataPath+filename, IMREAD_COLOR );
images.push_back( img );
}
}
modules/photo/include/opencv2/photo.hpp
+4 -4
View File
@@ -201,8 +201,8 @@ CV_EXPORTS_W void fastNlMeansDenoisingColored( InputArray src, OutputArray dst,
/** @brief Modification of fastNlMeansDenoising function for images sequence where consecutive images have been
captured in small period of time. For example video. This version of the function is for grayscale
images or for manual manipulation with colorspaces. For more details see
<http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.131.6394>
images or for manual manipulation with colorspaces. See @cite Buades2005DenoisingIS for more details
(open access [here](https://static.aminer.org/pdf/PDF/000/317/196/spatio_temporal_wiener_filtering_of_image_sequences_using_a_parametric.pdf)).
@param srcImgs Input 8-bit 1-channel, 2-channel, 3-channel or
4-channel images sequence. All images should have the same type and
@@ -228,8 +228,8 @@ CV_EXPORTS_W void fastNlMeansDenoisingMulti( InputArrayOfArrays srcImgs, OutputA
/** @brief Modification of fastNlMeansDenoising function for images sequence where consecutive images have been
captured in small period of time. For example video. This version of the function is for grayscale
images or for manual manipulation with colorspaces. For more details see
<http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.131.6394>
images or for manual manipulation with colorspaces. See @cite Buades2005DenoisingIS for more details
(open access [here](https://static.aminer.org/pdf/PDF/000/317/196/spatio_temporal_wiener_filtering_of_image_sequences_using_a_parametric.pdf)).
@param srcImgs Input 8-bit or 16-bit (only with NORM_L1) 1-channel,
2-channel, 3-channel or 4-channel images sequence. All images should
modules/photo/test/test_denoising.cpp
+1 -1
View File
@@ -157,7 +157,7 @@ TEST(Photo_White, issue_2646)
TEST(Photo_Denoising, speed)
{
string imgname = string(cvtest::TS::ptr()->get_data_path()) + "shared/5MP.png";
Mat src = imread(imgname, 0), dst;
Mat src = imread(imgname, IMREAD_GRAYSCALE), dst;
double t = (double)getTickCount();
fastNlMeansDenoising(src, dst, 5, 7, 21);
modules/ts/include/opencv2/ts/ts_perf.hpp
-3
View File
@@ -454,9 +454,6 @@ private:
performance_metrics metrics;
void validateMetrics();
static int64 _timeadjustment;
static int64 _calibrate();
static void warmup_impl(cv::Mat m, WarmUpType wtype);
static int getSizeInBytes(cv::InputArray a);
static cv::Size getSize(cv::InputArray a);
modules/ts/src/cuda_test.cpp
+27 -5
View File
@@ -522,13 +522,35 @@ namespace cvtest
int validCount = 0;
for (size_t i = 0; i < gold.size(); ++i)
if (actual.size() == gold.size())
{
const cv::KeyPoint& p1 = gold[i];
const cv::KeyPoint& p2 = actual[i];
for (size_t i = 0; i < gold.size(); ++i)
{
const cv::KeyPoint& p1 = gold[i];
const cv::KeyPoint& p2 = actual[i];
if (keyPointsEquals(p1, p2))
++validCount;
if (keyPointsEquals(p1, p2))
++validCount;
}
}
else
{
std::vector<cv::KeyPoint>& shorter = gold;
std::vector<cv::KeyPoint>& longer = actual;
if (actual.size() < gold.size())
{
shorter = actual;
longer = gold;
}
for (size_t i = 0; i < shorter.size(); ++i)
{
const cv::KeyPoint& p1 = shorter[i];
const cv::KeyPoint& p2 = longer[i];
const cv::KeyPoint& p3 = longer[i+1];
if (keyPointsEquals(p1, p2) || keyPointsEquals(p1, p3))
++validCount;
}
}
return validCount;
modules/ts/src/ts.cpp
+11 -4
View File
@@ -623,20 +623,27 @@ void TS::set_gtest_status()
void TS::update_context( BaseTest* test, int test_case_idx, bool update_ts_context )
{
CV_UNUSED(update_ts_context);
if( current_test_info.test != test )
{
for( int i = 0; i <= CONSOLE_IDX; i++ )
output_buf[i] = string();
rng = RNG(params.rng_seed);
current_test_info.rng_seed0 = current_test_info.rng_seed = rng.state;
}
if (test_case_idx >= 0)
{
current_test_info.rng_seed = param_seed + test_case_idx;
current_test_info.rng_seed0 = current_test_info.rng_seed;
rng = RNG(current_test_info.rng_seed);
cv::theRNG() = rng;
}
current_test_info.test = test;
current_test_info.test_case_idx = test_case_idx;
current_test_info.code = 0;
cvSetErrStatus( CV_StsOk );
if( update_ts_context )
current_test_info.rng_seed = rng.state;
}
modules/ts/src/ts_perf.cpp
+1 -64
View File
@@ -26,7 +26,6 @@ using namespace perf;
int64 TestBase::timeLimitDefault = 0;
unsigned int TestBase::iterationsLimitDefault = UINT_MAX;
int64 TestBase::_timeadjustment = 0;
// Item [0] will be considered the default implementation.
static std::vector<std::string> available_impls;
@@ -1159,7 +1158,6 @@ void TestBase::Init(const std::vector<std::string> & availableImpls,
timeLimitDefault = param_time_limit == 0.0 ? 1 : (int64)(param_time_limit * cv::getTickFrequency());
iterationsLimitDefault = param_force_samples == 0 ? UINT_MAX : param_force_samples;
_timeadjustment = _calibrate();
}
void TestBase::RecordRunParameters()
@@ -1193,66 +1191,6 @@ enum PERF_STRATEGY TestBase::getCurrentModulePerformanceStrategy()
return strategyForce == PERF_STRATEGY_DEFAULT ? strategyModule : strategyForce;
}
int64 TestBase::_calibrate()
{
CV_TRACE_FUNCTION();
if (iterationsLimitDefault <= 1)
return 0;
class _helper : public ::perf::TestBase
{
public:
_helper() { testStrategy = PERF_STRATEGY_BASE; }
performance_metrics& getMetrics() { return calcMetrics(); }
virtual void TestBody() {}
virtual void PerfTestBody()
{
//the whole system warmup
SetUp();
cv::Mat a(2048, 2048, CV_32S, cv::Scalar(1));
cv::Mat b(2048, 2048, CV_32S, cv::Scalar(2));
declare.time(30);
double s = 0;
declare.iterations(20);
minIters = nIters = 20;
for(; next() && startTimer(); stopTimer())
s+=a.dot(b);
declare.time(s);
//self calibration
SetUp();
declare.iterations(1000);
minIters = nIters = 1000;
for(int iters = 0; next() && startTimer(); iters++, stopTimer()) { /*std::cout << iters << nIters << std::endl;*/ }
}
};
// Initialize ThreadPool
class _dummyParallel : public ParallelLoopBody
{
public:
void operator()(const cv::Range& range) const
{
// nothing
CV_UNUSED(range);
}
};
parallel_for_(cv::Range(0, 1000), _dummyParallel());
_timeadjustment = 0;
_helper h;
h.PerfTestBody();
double compensation = h.getMetrics().min;
if (getCurrentModulePerformanceStrategy() == PERF_STRATEGY_SIMPLE)
{
CV_Assert(compensation < 0.01 * cv::getTickFrequency());
compensation = 0.0f; // simple strategy doesn't require any compensation
}
LOGD("Time compensation is %.0f", compensation);
return (int64)compensation;
}
#ifdef _MSC_VER
# pragma warning(push)
# pragma warning(disable:4355) // 'this' : used in base member initializer list
@@ -1561,9 +1499,8 @@ void TestBase::stopTimer()
if (lastTime == 0)
ADD_FAILURE() << " stopTimer() is called before startTimer()/next()";
lastTime = time - lastTime;
CV_Assert(lastTime >= 0); // TODO: CV_Check* for int64
totalTime += lastTime;
lastTime -= _timeadjustment;
if (lastTime < 0) lastTime = 0;
times.push_back(lastTime);
lastTime = 0;
modules/video/test/test_estimaterigid.cpp
+2 -2
View File
@@ -83,7 +83,7 @@ struct WrapAff2D
bool CV_RigidTransform_Test::testNPoints(int from)
{
cv::RNG rng = ts->get_rng();
cv::RNG rng = cv::theRNG();
int progress = 0;
int k, ntests = 10000;
@@ -181,4 +181,4 @@ void CV_RigidTransform_Test::run( int start_from )
TEST(Video_RigidFlow, accuracy) { CV_RigidTransform_Test test; test.safe_run(); }
}} // namespace
}} // namespace