vendor: OpenCV 5.0.0 snapshot at 755e50675d97db9b7d449d8bd6b09888646f6c6e
This commit is contained in:
@@ -0,0 +1,131 @@
|
||||
// This file is part of OpenCV project.
|
||||
// It is subject to the license terms in the LICENSE file found in the top-level directory
|
||||
// of this distribution and at http://opencv.org/license.html.
|
||||
#ifndef OPENCV_TEST_PRECOMP_HPP
|
||||
#define OPENCV_TEST_PRECOMP_HPP
|
||||
|
||||
#include <chrono>
|
||||
#include <opencv2/core.hpp>
|
||||
#include <opencv2/ts.hpp>
|
||||
#include <opencv2/ts/ocl_test.hpp> // OCL_ON, OCL_OFF
|
||||
#include <opencv2/imgcodecs.hpp>
|
||||
#include <opencv2/quality.hpp>
|
||||
#include <opencv2/quality/quality_utils.hpp>
|
||||
|
||||
namespace opencv_test
|
||||
{
|
||||
namespace quality_test
|
||||
{
|
||||
|
||||
const cv::String
|
||||
dataDir = "cv/optflow/"
|
||||
, testfile1a = dataDir + "rock_1.bmp"
|
||||
, testfile1b = dataDir + "rock_2.bmp"
|
||||
, testfile2a = dataDir + "RubberWhale1.png"
|
||||
, testfile2b = dataDir + "RubberWhale2.png"
|
||||
;
|
||||
|
||||
const cv::Scalar
|
||||
MSE_EXPECTED_1 = { 2136.0525 } // matlab: immse('rock_1.bmp', 'rock_2.bmp') == 2.136052552083333e+03
|
||||
, MSE_EXPECTED_2 = { 92.8235, 109.4104, 121.4 } // matlab: immse('rubberwhale1.png', 'rubberwhale2.png') == {92.8235, 109.4104, 121.4}
|
||||
;
|
||||
|
||||
inline cv::Mat get_testfile(const cv::String& path, int flags = IMREAD_UNCHANGED )
|
||||
{
|
||||
auto full_path = TS::ptr()->get_data_path() + path;
|
||||
auto result = cv::imread( full_path, flags );
|
||||
if (result.empty())
|
||||
CV_Error(cv::Error::StsObjectNotFound, "Cannot find file: " + full_path );
|
||||
return result;
|
||||
}
|
||||
|
||||
inline cv::Mat get_testfile_1a() { return get_testfile(testfile1a, IMREAD_GRAYSCALE); }
|
||||
inline cv::Mat get_testfile_1b() { return get_testfile(testfile1b, IMREAD_GRAYSCALE); }
|
||||
inline cv::Mat get_testfile_2a() { return get_testfile(testfile2a); }
|
||||
inline cv::Mat get_testfile_2b() { return get_testfile(testfile2b); }
|
||||
|
||||
const double QUALITY_ERR_TOLERANCE = .002 // allowed margin of error
|
||||
;
|
||||
|
||||
inline void quality_expect_near( const cv::Scalar& a, const cv::Scalar& b, double err_tolerance = QUALITY_ERR_TOLERANCE)
|
||||
{
|
||||
for (int i = 0; i < a.rows; ++i)
|
||||
{
|
||||
if (std::isinf(a(i)))
|
||||
EXPECT_EQ(a(i), b(i));
|
||||
else
|
||||
EXPECT_NEAR(a(i), b(i), err_tolerance);
|
||||
}
|
||||
}
|
||||
|
||||
template <typename TMat>
|
||||
inline void check_quality_map( const TMat& mat, const bool expect_empty = false )
|
||||
{
|
||||
EXPECT_EQ( mat.empty(), expect_empty );
|
||||
if ( !expect_empty )
|
||||
{
|
||||
EXPECT_GT(mat.rows, 0);
|
||||
EXPECT_GT(mat.cols, 0);
|
||||
}
|
||||
}
|
||||
|
||||
// execute quality test for a pair of images
|
||||
template <typename TMat>
|
||||
inline void quality_test(cv::Ptr<quality::QualityBase> ptr, const TMat& cmp, const Scalar& expected, const bool quality_map_expected = true, const bool empty_expected = false )
|
||||
{
|
||||
cv::Mat qMat = {};
|
||||
cv::UMat qUMat = {};
|
||||
|
||||
// quality map should return empty in initial state
|
||||
ptr->getQualityMap(qMat);
|
||||
EXPECT_TRUE( qMat.empty() );
|
||||
|
||||
// compute quality, check result
|
||||
quality_expect_near( expected, ptr->compute(cmp));
|
||||
|
||||
if (empty_expected)
|
||||
EXPECT_TRUE(ptr->empty());
|
||||
else
|
||||
EXPECT_FALSE(ptr->empty());
|
||||
|
||||
// getQualityMap to Mat, UMat
|
||||
ptr->getQualityMap(qMat);
|
||||
ptr->getQualityMap(qUMat);
|
||||
|
||||
// check them
|
||||
check_quality_map(qMat, !quality_map_expected);
|
||||
check_quality_map(qUMat, !quality_map_expected);
|
||||
|
||||
// reset algorithm, should now be empty
|
||||
ptr->clear();
|
||||
EXPECT_TRUE(ptr->empty());
|
||||
}
|
||||
|
||||
/* A/B test benchmarking for development purposes */
|
||||
/*
|
||||
template <typename Fn>
|
||||
inline void quality_performance_test( const char* name, Fn&& op )
|
||||
{
|
||||
const auto exec_test = [&]()
|
||||
{
|
||||
const int NRUNS = 100;
|
||||
const auto start_t = std::chrono::high_resolution_clock::now();
|
||||
for (int i = 0; i < NRUNS; ++i)
|
||||
op();
|
||||
|
||||
const auto end_t = std::chrono::high_resolution_clock::now();
|
||||
std::cout << name << " performance (OCL=" << cv::ocl::useOpenCL() << "): " << (double)(std::chrono::duration_cast<std::chrono::milliseconds>(end_t - start_t).count()) / (double)NRUNS << "ms\n";
|
||||
};
|
||||
|
||||
// only run tests in NDEBUG mode
|
||||
#ifdef NDEBUG
|
||||
OCL_OFF(exec_test());
|
||||
OCL_ON(exec_test());
|
||||
#endif
|
||||
}
|
||||
*/
|
||||
|
||||
}
|
||||
}
|
||||
|
||||
#endif
|
||||
Reference in New Issue
Block a user