Merge pull request #26405 from kaingwade:rename_features2d

Rename features2d #26405 This PR renames the module _features2d_ to _features_ as one of the Big OpenCV Cleanup #25007. Related PR: opencv/opencv_contrib: [#3820](https://github.com/opencv/opencv_contrib/pull/3820) opencv/ci-gha-workflow: [#192](https://github.com/opencv/ci-gha-workflow/pull/192)
2026-07-31 00:03:03 +04:00 · 2024-11-12 16:04:48 +08:00
parent c7a21dc5bf
commit 614e250fd3
260 changed files with 273 additions and 268 deletions
@@ -0,0 +1,162 @@
+// 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
+
+#include "test_precomp.hpp"
+
+namespace opencv_test { namespace {
+const string FEATURES2D_DIR = "features2d";
+const string IMAGE_FILENAME = "tsukuba.png";
+const string DESCRIPTOR_DIR = FEATURES2D_DIR + "/descriptor_extractors";
+}} // namespace
+
+#include "test_descriptors_regression.impl.hpp"
+
+namespace opencv_test { namespace {
+
+/****************************************************************************************\
+*                                Tests registrations                                     *
+\****************************************************************************************/
+
+TEST( Features2d_DescriptorExtractor_SIFT, regression )
+{
+    CV_DescriptorExtractorTest<L1<float> > test( "descriptor-sift", 1.0f,
+                                                SIFT::create() );
+    test.safe_run();
+}
+
+TEST( Features2d_DescriptorExtractor_ORB, regression )
+{
+    // TODO adjust the parameters below
+    CV_DescriptorExtractorTest<Hamming> test( "descriptor-orb",
+#if CV_NEON
+                                              (CV_DescriptorExtractorTest<Hamming>::DistanceType)25.f,
+#else
+                                              (CV_DescriptorExtractorTest<Hamming>::DistanceType)12.f,
+#endif
+                                             ORB::create() );
+    test.safe_run();
+}
+
+TEST( Features2d_DescriptorExtractor, batch_ORB )
+{
+    string path = string(cvtest::TS::ptr()->get_data_path() + "detectors_descriptors_evaluation/images_datasets/graf");
+    vector<Mat> imgs, descriptors;
+    vector<vector<KeyPoint> > keypoints;
+    int i, n = 6;
+    Ptr<ORB> orb = ORB::create();
+
+    for( i = 0; i < n; i++ )
+    {
+        string imgname = format("%s/img%d.png", path.c_str(), i+1);
+        Mat img = imread(imgname, IMREAD_GRAYSCALE);
+        imgs.push_back(img);
+    }
+
+    orb->detect(imgs, keypoints);
+    orb->compute(imgs, keypoints, descriptors);
+
+    ASSERT_EQ((int)keypoints.size(), n);
+    ASSERT_EQ((int)descriptors.size(), n);
+
+    for( i = 0; i < n; i++ )
+    {
+        EXPECT_GT((int)keypoints[i].size(), 100);
+        EXPECT_GT(descriptors[i].rows, 100);
+    }
+}
+
+TEST( Features2d_DescriptorExtractor, batch_SIFT )
+{
+    string path = string(cvtest::TS::ptr()->get_data_path() + "detectors_descriptors_evaluation/images_datasets/graf");
+    vector<Mat> imgs, descriptors;
+    vector<vector<KeyPoint> > keypoints;
+    int i, n = 6;
+    Ptr<SIFT> sift = SIFT::create();
+
+    for( i = 0; i < n; i++ )
+    {
+        string imgname = format("%s/img%d.png", path.c_str(), i+1);
+        Mat img = imread(imgname, IMREAD_GRAYSCALE);
+        imgs.push_back(img);
+    }
+
+    sift->detect(imgs, keypoints);
+    sift->compute(imgs, keypoints, descriptors);
+
+    ASSERT_EQ((int)keypoints.size(), n);
+    ASSERT_EQ((int)descriptors.size(), n);
+
+    for( i = 0; i < n; i++ )
+    {
+        EXPECT_GT((int)keypoints[i].size(), 100);
+        EXPECT_GT(descriptors[i].rows, 100);
+    }
+}
+
+
+class DescriptorImage : public TestWithParam<std::string>
+{
+protected:
+    virtual void SetUp() {
+        pattern = GetParam();
+    }
+
+    std::string pattern;
+};
+
+TEST_P(DescriptorImage, no_crash)
+{
+    vector<String> fnames;
+    glob(cvtest::TS::ptr()->get_data_path() + pattern, fnames, false);
+    std::sort(fnames.begin(), fnames.end());
+
+    Ptr<ORB> orb = ORB::create();
+    size_t n = fnames.size();
+    vector<KeyPoint> keypoints;
+    Mat descriptors;
+    orb->setMaxFeatures(5000);
+
+    for(size_t i = 0; i < n; i++ )
+    {
+        printf("%d. image: %s:\n", (int)i, fnames[i].c_str());
+        if( strstr(fnames[i].c_str(), "MP.png") != 0 )
+        {
+            printf("\tskip\n");
+            continue;
+        }
+        bool checkCount = strstr(fnames[i].c_str(), "templ.png") == 0;
+
+        Mat img = imread(fnames[i], -1);
+
+        printf("\t%dx%d\n", img.cols, img.rows);
+
+#define TEST_DETECTOR(name, descriptor) \
+        keypoints.clear(); descriptors.release(); \
+        printf("\t" name "\n"); fflush(stdout); \
+        descriptor->detectAndCompute(img, noArray(), keypoints, descriptors); \
+        printf("\t\t\t(%d keypoints, descriptor size = %d)\n", (int)keypoints.size(), descriptors.cols); fflush(stdout); \
+        if (checkCount) \
+        { \
+            EXPECT_GT((int)keypoints.size(), 0); \
+        } \
+        ASSERT_EQ(descriptors.rows, (int)keypoints.size());
+
+        TEST_DETECTOR("ORB", orb);
+    }
+}
+
+INSTANTIATE_TEST_CASE_P(Features2d, DescriptorImage,
+        testing::Values(
+            "shared/lena.png",
+            "shared/box*.png",
+            "shared/fruits*.png",
+            "shared/airplane.png",
+            "shared/graffiti.png",
+            "shared/1_itseez-0001*.png",
+            "shared/pic*.png",
+            "shared/templ.png"
+        )
+);
+
+}} // namespace