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Merge pull request #25424 from mshabunin:fix-features2d-test

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features2d: reduce accuracy test avg memory consumption #25424

**Merge with contrib**: https://github.com/opencv/opencv_contrib/pull/3722

I've observed high memory consumption in the `opencv_test_features2d` (x86_64, Ubuntu 22.04, Debug):

![image](https://github.com/opencv/opencv/assets/3304494/419d65d9-d727-4d1e-bdec-dbde6681c188)
It's always more than 180 MiB with peak at 535 MiB

This was caused by pointers to the algorithm object instances stored in the tests parameters. I've replaced them with factory functions/lambdas with the following result:

![image](https://github.com/opencv/opencv/assets/3304494/bd4ff0ea-3db4-4ab8-8e6d-192a3826e99c)
Now peak is at 355 MiB and permanent consumption level is ~ 1-2 MiB


**Note:** current peak is caused by KAZE features allocating 8x image size utility buffers. Not sure if we can or should do anything about it: 66fb5021e9/modules/features2d/src/kaze/KAZEFeatures.cpp (L61-L68)
This commit is contained in:
Maksim Shabunin 2024-04-17 14:19:05 +03:00 committed by GitHub
parent 577ad0a5ad
commit f9e9567870
No known key found for this signature in database
GPG Key ID: B5690EEEBB952194
5 changed files with 38 additions and 28 deletions
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9
modules/features2d/test/ocl/test_feature2d.cpp
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@ -5,6 +5,7 @@
#include "../test_precomp.hpp"
#include "cvconfig.h"
#include "opencv2/ts/ocl_test.hpp"
#include <functional>
#ifdef HAVE_OPENCL
@ -16,7 +17,7 @@ namespace ocl {
"../stitching/a3.png", \
"../stitching/s2.jpg")
PARAM_TEST_CASE(Feature2DFixture, Ptr<Feature2D>, std::string)
PARAM_TEST_CASE(Feature2DFixture, std::function<Ptr<Feature2D>()>, std::string)
{
std::string filename;
Mat image, descriptors;
@ -27,7 +28,7 @@ PARAM_TEST_CASE(Feature2DFixture, Ptr<Feature2D>, std::string)
virtual void SetUp()
{
feature = GET_PARAM(0);
feature = GET_PARAM(0)();
filename = GET_PARAM(1);
image = readImage(filename);
@ -61,10 +62,10 @@ OCL_TEST_P(Feature2DFixture, DescriptorsSame)
}
OCL_INSTANTIATE_TEST_CASE_P(AKAZE, Feature2DFixture,
testing::Combine(testing::Values(AKAZE::create()), TEST_IMAGES));
testing::Combine(testing::Values([]() { return AKAZE::create(); }), TEST_IMAGES));
OCL_INSTANTIATE_TEST_CASE_P(AKAZE_DESCRIPTOR_KAZE, Feature2DFixture,
testing::Combine(testing::Values(AKAZE::create(AKAZE::DESCRIPTOR_KAZE)), TEST_IMAGES));
testing::Combine(testing::Values([]() { return AKAZE::create(AKAZE::DESCRIPTOR_KAZE); }), TEST_IMAGES));
}//ocl
}//cvtest

16
modules/features2d/test/test_descriptors_invariance.cpp
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@ -18,31 +18,31 @@ const static std::string IMAGE_BIKES = "detectors_descriptors_evaluation/images_
*/
INSTANTIATE_TEST_CASE_P(SIFT, DescriptorRotationInvariance,
Value(IMAGE_TSUKUBA, SIFT::create(), SIFT::create(), 0.98f));
Value(IMAGE_TSUKUBA, []() { return SIFT::create(); }, []() { return SIFT::create(); }, 0.98f));
INSTANTIATE_TEST_CASE_P(BRISK, DescriptorRotationInvariance,
Value(IMAGE_TSUKUBA, BRISK::create(), BRISK::create(), 0.99f));
Value(IMAGE_TSUKUBA, []() { return BRISK::create(); }, []() { return BRISK::create(); }, 0.99f));
INSTANTIATE_TEST_CASE_P(ORB, DescriptorRotationInvariance,
Value(IMAGE_TSUKUBA, ORB::create(), ORB::create(), 0.99f));
Value(IMAGE_TSUKUBA, []() { return ORB::create(); }, []() { return ORB::create(); }, 0.99f));
INSTANTIATE_TEST_CASE_P(AKAZE, DescriptorRotationInvariance,
Value(IMAGE_TSUKUBA, AKAZE::create(), AKAZE::create(), 0.99f));
Value(IMAGE_TSUKUBA, []() { return AKAZE::create(); }, []() { return AKAZE::create(); }, 0.99f));
INSTANTIATE_TEST_CASE_P(AKAZE_DESCRIPTOR_KAZE, DescriptorRotationInvariance,
Value(IMAGE_TSUKUBA, AKAZE::create(AKAZE::DESCRIPTOR_KAZE), AKAZE::create(AKAZE::DESCRIPTOR_KAZE), 0.99f));
Value(IMAGE_TSUKUBA, []() { return AKAZE::create(AKAZE::DESCRIPTOR_KAZE); }, []() { return AKAZE::create(AKAZE::DESCRIPTOR_KAZE); }, 0.99f));
/*
* Descriptor's scale invariance check
*/
INSTANTIATE_TEST_CASE_P(SIFT, DescriptorScaleInvariance,
Value(IMAGE_BIKES, SIFT::create(0, 3, 0.09), SIFT::create(0, 3, 0.09), 0.78f));
Value(IMAGE_BIKES, []() { return SIFT::create(0, 3, 0.09); }, []() { return SIFT::create(0, 3, 0.09); }, 0.78f));
INSTANTIATE_TEST_CASE_P(AKAZE, DescriptorScaleInvariance,
Value(IMAGE_BIKES, AKAZE::create(), AKAZE::create(), 0.6f));
Value(IMAGE_BIKES, []() { return AKAZE::create(); }, []() { return AKAZE::create(); }, 0.6f));
INSTANTIATE_TEST_CASE_P(AKAZE_DESCRIPTOR_KAZE, DescriptorScaleInvariance,
Value(IMAGE_BIKES, AKAZE::create(AKAZE::DESCRIPTOR_KAZE), AKAZE::create(AKAZE::DESCRIPTOR_KAZE), 0.55f));
Value(IMAGE_BIKES, []() { return AKAZE::create(AKAZE::DESCRIPTOR_KAZE); }, []() { return AKAZE::create(AKAZE::DESCRIPTOR_KAZE); }, 0.55f));
}} // namespace

11
modules/features2d/test/test_descriptors_invariance.impl.hpp
View File

@ -3,12 +3,17 @@
// of this distribution and at http://opencv.org/license.html
#include "test_invariance_utils.hpp"
#include <functional>
namespace opencv_test { namespace {
#define SHOW_DEBUG_LOG 1
typedef tuple<std::string, Ptr<FeatureDetector>, Ptr<DescriptorExtractor>, float>
// NOTE: using factory function (function<Ptr<Type>()>) instead of object instance (Ptr<Type>) as a
// test parameter, because parameters exist during whole test program run and consume a lot of memory
typedef std::function<cv::Ptr<cv::FeatureDetector>()> DetectorFactory;
typedef std::function<cv::Ptr<cv::DescriptorExtractor>()> ExtractorFactory;
typedef tuple<std::string, DetectorFactory, ExtractorFactory, float>
String_FeatureDetector_DescriptorExtractor_Float_t;
@ -61,8 +66,8 @@ protected:
image0 = imread(filename);
ASSERT_FALSE(image0.empty()) << "couldn't read input image";
featureDetector = get<1>(GetParam());
descriptorExtractor = get<2>(GetParam());
featureDetector = get<1>(GetParam())();
descriptorExtractor = get<2>(GetParam())();
minInliersRatio = get<3>(GetParam());
}

22
modules/features2d/test/test_detectors_invariance.cpp
View File

@ -18,40 +18,40 @@ const static std::string IMAGE_BIKES = "detectors_descriptors_evaluation/images_
*/
INSTANTIATE_TEST_CASE_P(SIFT, DetectorRotationInvariance,
Value(IMAGE_TSUKUBA, SIFT::create(), 0.45f, 0.70f));
Value(IMAGE_TSUKUBA, []() { return SIFT::create(); }, 0.45f, 0.70f));
INSTANTIATE_TEST_CASE_P(BRISK, DetectorRotationInvariance,
Value(IMAGE_TSUKUBA, BRISK::create(), 0.45f, 0.76f));
Value(IMAGE_TSUKUBA, []() { return BRISK::create(); }, 0.45f, 0.76f));
INSTANTIATE_TEST_CASE_P(ORB, DetectorRotationInvariance,
Value(IMAGE_TSUKUBA, ORB::create(), 0.5f, 0.76f));
Value(IMAGE_TSUKUBA, []() { return ORB::create(); }, 0.5f, 0.76f));
INSTANTIATE_TEST_CASE_P(AKAZE, DetectorRotationInvariance,
Value(IMAGE_TSUKUBA, AKAZE::create(), 0.5f, 0.71f));
Value(IMAGE_TSUKUBA, []() { return AKAZE::create(); }, 0.5f, 0.71f));
INSTANTIATE_TEST_CASE_P(AKAZE_DESCRIPTOR_KAZE, DetectorRotationInvariance,
Value(IMAGE_TSUKUBA, AKAZE::create(AKAZE::DESCRIPTOR_KAZE), 0.5f, 0.71f));
Value(IMAGE_TSUKUBA, []() { return AKAZE::create(AKAZE::DESCRIPTOR_KAZE); }, 0.5f, 0.71f));
/*
* Detector's scale invariance check
*/
INSTANTIATE_TEST_CASE_P(SIFT, DetectorScaleInvariance,
Value(IMAGE_BIKES, SIFT::create(0, 3, 0.09), 0.60f, 0.98f));
Value(IMAGE_BIKES, []() { return SIFT::create(0, 3, 0.09); }, 0.60f, 0.98f));
INSTANTIATE_TEST_CASE_P(BRISK, DetectorScaleInvariance,
Value(IMAGE_BIKES, BRISK::create(), 0.08f, 0.49f));
Value(IMAGE_BIKES, []() { return BRISK::create(); }, 0.08f, 0.49f));
INSTANTIATE_TEST_CASE_P(ORB, DetectorScaleInvariance,
Value(IMAGE_BIKES, ORB::create(), 0.08f, 0.49f));
Value(IMAGE_BIKES, []() { return ORB::create(); }, 0.08f, 0.49f));
INSTANTIATE_TEST_CASE_P(KAZE, DetectorScaleInvariance,
Value(IMAGE_BIKES, KAZE::create(), 0.08f, 0.49f));
Value(IMAGE_BIKES, []() { return KAZE::create(); }, 0.08f, 0.49f));
INSTANTIATE_TEST_CASE_P(AKAZE, DetectorScaleInvariance,
Value(IMAGE_BIKES, AKAZE::create(), 0.08f, 0.49f));
Value(IMAGE_BIKES, []() { return AKAZE::create(); }, 0.08f, 0.49f));
INSTANTIATE_TEST_CASE_P(AKAZE_DESCRIPTOR_KAZE, DetectorScaleInvariance,
Value(IMAGE_BIKES, AKAZE::create(AKAZE::DESCRIPTOR_KAZE), 0.08f, 0.49f));
Value(IMAGE_BIKES, []() { return AKAZE::create(AKAZE::DESCRIPTOR_KAZE); }, 0.08f, 0.49f));
}} // namespace

8
modules/features2d/test/test_detectors_invariance.impl.hpp
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@ -3,12 +3,16 @@
// of this distribution and at http://opencv.org/license.html
#include "test_invariance_utils.hpp"
#include <functional>
namespace opencv_test { namespace {
#define SHOW_DEBUG_LOG 1
typedef tuple<std::string, Ptr<FeatureDetector>, float, float> String_FeatureDetector_Float_Float_t;
// NOTE: using factory function (function<Ptr<Type>()>) instead of object instance (Ptr<Type>) as a
// test parameter, because parameters exist during whole test program run and consume a lot of memory
typedef std::function<cv::Ptr<cv::FeatureDetector>()> DetectorFactory;
typedef tuple<std::string, DetectorFactory, float, float> String_FeatureDetector_Float_Float_t;
static
@ -56,7 +60,7 @@ protected:
image0 = imread(filename);
ASSERT_FALSE(image0.empty()) << "couldn't read input image";
featureDetector = get<1>(GetParam());
featureDetector = get<1>(GetParam())();
minKeyPointMatchesRatio = get<2>(GetParam());
minInliersRatio = get<3>(GetParam());
}