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Merge pull request #26907 from asmorkalov:as/openvx_hal_features2d
Migrate remaning OpenVX integrations to OpenVX HAL (features2d)
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@@ -49,8 +49,6 @@ The references are:
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#include "opencv2/core/hal/intrin.hpp"
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#include "opencv2/core/utils/buffer_area.private.hpp"
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#include "opencv2/core/openvx/ovx_defs.hpp"
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namespace cv
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{
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@@ -370,72 +368,6 @@ static bool ocl_FAST( InputArray _img, std::vector<KeyPoint>& keypoints,
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}
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#endif
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#ifdef HAVE_OPENVX
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namespace ovx {
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template <> inline bool skipSmallImages<VX_KERNEL_FAST_CORNERS>(int w, int h) { return w*h < 800 * 600; }
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}
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static bool openvx_FAST(InputArray _img, std::vector<KeyPoint>& keypoints,
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int _threshold, bool nonmaxSuppression, int type)
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{
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using namespace ivx;
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// Nonmax suppression is done differently in OpenCV than in OpenVX
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// 9/16 is the only supported mode in OpenVX
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if(nonmaxSuppression || type != FastFeatureDetector::TYPE_9_16)
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return false;
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Mat imgMat = _img.getMat();
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if(imgMat.empty() || imgMat.type() != CV_8UC1)
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return false;
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if (ovx::skipSmallImages<VX_KERNEL_FAST_CORNERS>(imgMat.cols, imgMat.rows))
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return false;
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try
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{
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Context context = ovx::getOpenVXContext();
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Image img = Image::createFromHandle(context, Image::matTypeToFormat(imgMat.type()),
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Image::createAddressing(imgMat), (void*)imgMat.data);
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ivx::Scalar threshold = ivx::Scalar::create<VX_TYPE_FLOAT32>(context, _threshold);
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vx_size capacity = imgMat.cols * imgMat.rows;
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Array corners = Array::create(context, VX_TYPE_KEYPOINT, capacity);
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ivx::Scalar numCorners = ivx::Scalar::create<VX_TYPE_SIZE>(context, 0);
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IVX_CHECK_STATUS(vxuFastCorners(context, img, threshold, (vx_bool)nonmaxSuppression, corners, numCorners));
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size_t nPoints = numCorners.getValue<vx_size>();
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keypoints.clear(); keypoints.reserve(nPoints);
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std::vector<vx_keypoint_t> vxCorners;
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corners.copyTo(vxCorners);
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for(size_t i = 0; i < nPoints; i++)
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{
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vx_keypoint_t kp = vxCorners[i];
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//if nonmaxSuppression is false, kp.strength is undefined
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keypoints.push_back(KeyPoint((float)kp.x, (float)kp.y, 7.f, -1, kp.strength));
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}
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#ifdef VX_VERSION_1_1
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//we should take user memory back before release
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//(it's not done automatically according to standard)
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img.swapHandle();
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#endif
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}
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catch (const RuntimeError & e)
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{
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VX_DbgThrow(e.what());
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}
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catch (const WrapperError & e)
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{
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VX_DbgThrow(e.what());
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}
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return true;
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}
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#endif
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static inline int hal_FAST(cv::Mat& src, std::vector<KeyPoint>& keypoints, int threshold, bool nonmax_suppression, FastFeatureDetector::DetectorType type)
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{
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if (threshold > 20)
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@@ -503,13 +435,12 @@ void FAST(InputArray _img, std::vector<KeyPoint>& keypoints, int threshold, bool
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cv::Mat img = _img.getMat();
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CALL_HAL(fast_dense, hal_FAST, img, keypoints, threshold, nonmax_suppression, type);
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size_t keypoints_count;
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size_t keypoints_count = 10000;
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keypoints.clear();
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keypoints.resize(keypoints_count);
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CALL_HAL(fast, cv_hal_FAST, img.data, img.step, img.cols, img.rows,
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(uchar*)(keypoints.data()), &keypoints_count, threshold, nonmax_suppression, type);
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CV_OVX_RUN(true,
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openvx_FAST(_img, keypoints, threshold, nonmax_suppression, type))
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switch(type) {
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case FastFeatureDetector::TYPE_5_8:
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FAST_t<8>(_img, keypoints, threshold, nonmax_suppression);
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@@ -118,8 +118,8 @@ void CV_FastTest::run( int )
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read( fs["exp_kps2"], exp_kps2, Mat() );
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fs.release();
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if ( exp_kps1.size != kps1.size || 0 != cvtest::norm(exp_kps1, kps1, NORM_L2) ||
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exp_kps2.size != kps2.size || 0 != cvtest::norm(exp_kps2, kps2, NORM_L2))
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if ( exp_kps1.size != kps1.size || 0 != cvtest::norm(exp_kps1, kps1, NORM_L2) ||
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exp_kps2.size != kps2.size || 0 != cvtest::norm(exp_kps2, kps2, NORM_L2))
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{
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ts->set_failed_test_info(cvtest::TS::FAIL_MISMATCH);
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return;
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@@ -135,4 +135,34 @@ void CV_FastTest::run( int )
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TEST(Features2d_FAST, regression) { CV_FastTest test; test.safe_run(); }
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// #define DUMP_TEST_DATA
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TEST(Features2d_FAST, noNMS)
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{
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Mat img = imread(string(cvtest::TS::ptr()->get_data_path()) + "inpaint/orig.png", cv::IMREAD_GRAYSCALE);
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string xml = string(cvtest::TS::ptr()->get_data_path()) + "fast/result_no_nonmax.xml";
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vector<KeyPoint> keypoints;
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FAST(img, keypoints, 100, false, FastFeatureDetector::DetectorType::TYPE_9_16);
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Mat kps(1, (int)(keypoints.size() * sizeof(KeyPoint)), CV_8U, &keypoints[0]);
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Mat gt_kps;
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FileStorage fs(xml, FileStorage::READ);
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#ifdef DUMP_TEST_DATA
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if (!fs.isOpened())
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{
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fs.open(xml, FileStorage::WRITE);
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fs << "exp_kps" << kps;
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fs.release();
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fs.open(xml, FileStorage::READ);
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}
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#endif
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ASSERT_TRUE(fs.isOpened());
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fs["exp_kps"] >> gt_kps;
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fs.release();
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ASSERT_GT(gt_kps.total(), size_t(0));
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ASSERT_EQ( 0, cvtest::norm(gt_kps, kps, NORM_L2));
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}
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}} // namespace
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