opencv/modules/stitching/test/test_matchers.cpp
Jiri Horner 1ba7c728a6 Merge pull request #12827 from hrnr:stitching_4
[evolution] Stitching for OpenCV 4.0

* stitching: wrap Stitcher::create for bindings

* provide method for consistent stitcher usage across languages

* samples: add python stitching sample

* port cpp stitching sample to python

* stitching: consolidate Stitcher create methods

* remove Stitcher::createDefault, it returns Stitcher, not Ptr<Stitcher> -> inconsistent API
* deprecate cv::createStitcher and cv::createStitcherScans in favor of Stitcher::create

* stitching: avoid anonymous enum in Stitcher

* ORIG_RESOL should be double
* add documentatiton

* stitching: improve documentation in Stitcher

* stitching: expose estimator in Stitcher

* remove ABI hack

* stitching: drop try_use_gpu flag

* OCL will be used automatically through T-API in OCL-enable paths
* CUDA won't be used unless user sets CUDA-enabled classes manually

* stitching: drop FeaturesFinder

* use Feature2D instead of FeaturesFinder
* interoperability with features2d module
* detach from dependency on xfeatures2d

* features2d: fix compute and detect to work with UMat vectors

* correctly pass UMats as UMats to allow OCL paths
* support vector of UMats as output arg

* stitching: use nearest interpolation for resizing masks

* fix warnings
2018-11-10 19:53:48 +03:00

110 lines
4.2 KiB
C++

/*M///////////////////////////////////////////////////////////////////////////////////////
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#include "test_precomp.hpp"
#include "opencv2/opencv_modules.hpp"
namespace opencv_test { namespace {
#ifdef HAVE_OPENCV_XFEATURES2D
TEST(SurfFeaturesFinder, CanFindInROIs)
{
Ptr<Feature2D> finder = xfeatures2d::SURF::create();
Mat img = imread(string(cvtest::TS::ptr()->get_data_path()) + "cv/shared/lena.png");
vector<Rect> rois;
rois.push_back(Rect(0, 0, img.cols / 2, img.rows / 2));
rois.push_back(Rect(img.cols / 2, img.rows / 2, img.cols - img.cols / 2, img.rows - img.rows / 2));
// construct mask
Mat mask = Mat::zeros(img.size(), CV_8U);
for (const Rect &roi : rois)
{
Mat(mask, roi) = 1;
}
detail::ImageFeatures roi_features;
detail::computeImageFeatures(finder, img, roi_features, mask);
int tl_rect_count = 0, br_rect_count = 0, bad_count = 0;
for (const auto &keypoint : roi_features.keypoints)
{
if (rois[0].contains(keypoint.pt))
tl_rect_count++;
else if (rois[1].contains(keypoint.pt))
br_rect_count++;
else
bad_count++;
}
EXPECT_GT(tl_rect_count, 0);
EXPECT_GT(br_rect_count, 0);
EXPECT_EQ(bad_count, 0);
}
#endif // HAVE_OPENCV_XFEATURES2D
TEST(ParallelFeaturesFinder, IsSameWithSerial)
{
Ptr<Feature2D> para_finder = ORB::create();
Ptr<Feature2D> serial_finder = ORB::create();
Mat img = imread(string(cvtest::TS::ptr()->get_data_path()) + "stitching/a3.png", IMREAD_GRAYSCALE);
vector<Mat> imgs(50, img);
detail::ImageFeatures serial_features;
vector<detail::ImageFeatures> para_features(imgs.size());
detail::computeImageFeatures(serial_finder, img, serial_features);
detail::computeImageFeatures(para_finder, imgs, para_features);
// results must be the same
for(size_t i = 0; i < para_features.size(); ++i)
{
Mat diff_descriptors = serial_features.descriptors.getMat(ACCESS_READ) != para_features[i].descriptors.getMat(ACCESS_READ);
EXPECT_EQ(countNonZero(diff_descriptors), 0);
EXPECT_EQ(serial_features.img_size, para_features[i].img_size);
EXPECT_EQ(serial_features.keypoints.size(), para_features[i].keypoints.size());
}
}
}} // namespace