xfeatures2d: move SIFT to main repository

modules/README.md

@@ -64,7 +64,7 @@ $ cmake -D OPENCV_EXTRA_MODULES_PATH=<opencv_contrib>/modules -D BUILD_opencv_<r
 
 - **tracking**: Vision Based Object Tracking -- Use and/or evaluate one of 5 different visual object tracking techniques.
 
-- **xfeatures2d**: Features2D extra -- Extra 2D Features Framework containing experimental and non-free 2D feature detector/descriptor algorithms. SURF, SIFT, BRIEF, Censure, Freak, LUCID, Daisy, Self-similar.
+- **xfeatures2d**: Features2D extra -- Extra 2D Features Framework containing experimental and non-free 2D feature detector/descriptor algorithms. SURF, BRIEF, Censure, Freak, LUCID, Daisy, Self-similar.
 
 - **ximgproc**: Extended Image Processing -- Structured Forests / Domain Transform Filter / Guided Filter / Adaptive Manifold Filter / Joint Bilateral Filter / Superpixels / Ridge Detection Filter.
 

modules/xfeatures2d/README.md

@@ -5,4 +5,4 @@ Extra 2D Features Framework
 2. Non-free 2D feature algorithms
 
 Extra 2D Features Framework containing experimental and non-free 2D feature detector/descriptor algorithms:
- SURF, SIFT, BRIEF, Censure, Freak, LUCID, Daisy, Self-similar.
+ SURF, BRIEF, Censure, Freak, LUCID, Daisy, Self-similar.

modules/xfeatures2d/doc/xfeatures2d.bib

@@ -60,17 +60,6 @@
   year = {2016}
 }
 
-@article{Lowe04,
-  title = {Distinctive image features from scale-invariant keypoints},
-  author = {Lowe, David G},
-  journal = {International journal of computer vision},
-  volume = {60},
-  number = {2},
-  pages = {91--110},
-  year = {2004},
-  publisher = {Kluwer Academic Publishers}
-}
-
 @article{Mikolajczyk2004,
   title = {Scale \& affine invariant interest point detectors},
   author = {Mikolajczyk, Krystian and Schmid, Cordelia},

modules/xfeatures2d/include/opencv2/xfeatures2d.hpp

@@ -65,39 +65,6 @@ namespace cv
 namespace xfeatures2d
 {
 
-
-/** @brief Class for extracting keypoints and computing descriptors using the Scale Invariant Feature Transform
-(SIFT) algorithm by D. Lowe @cite Lowe04 .
-*/
-class CV_EXPORTS_W SIFT : public Feature2D
-{
-public:
-    /**
-    @param nfeatures The number of best features to retain. The features are ranked by their scores
-    (measured in SIFT algorithm as the local contrast)
-
-    @param nOctaveLayers The number of layers in each octave. 3 is the value used in D. Lowe paper. The
-    number of octaves is computed automatically from the image resolution.
-
-    @param contrastThreshold The contrast threshold used to filter out weak features in semi-uniform
-    (low-contrast) regions. The larger the threshold, the less features are produced by the detector.
-
-    @param edgeThreshold The threshold used to filter out edge-like features. Note that the its meaning
-    is different from the contrastThreshold, i.e. the larger the edgeThreshold, the less features are
-    filtered out (more features are retained).
-
-    @param sigma The sigma of the Gaussian applied to the input image at the octave \#0. If your image
-    is captured with a weak camera with soft lenses, you might want to reduce the number.
-    */
-    CV_WRAP static Ptr<SIFT> create(int nfeatures = 0, int nOctaveLayers = 3,
-        double contrastThreshold = 0.04, double edgeThreshold = 10,
-        double sigma = 1.6);
-};
-
-typedef SIFT SiftFeatureDetector;
-typedef SIFT SiftDescriptorExtractor;
-
-
 //! @addtogroup xfeatures2d_experiment
 //! @{
 

modules/xfeatures2d/perf/perf_sift.cpp

@@ -1,72 +0,0 @@
-// 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 "perf_precomp.hpp"
-
-namespace opencv_test { namespace {
-
-typedef perf::TestBaseWithParam<std::string> sift;
-
-#define SIFT_IMAGES \
-    "cv/detectors_descriptors_evaluation/images_datasets/leuven/img1.png",\
-    "stitching/a3.png"
-
-PERF_TEST_P(sift, detect, testing::Values(SIFT_IMAGES))
-{
-    string filename = getDataPath(GetParam());
-    Mat frame = imread(filename, IMREAD_GRAYSCALE);
-    ASSERT_FALSE(frame.empty()) << "Unable to load source image " << filename;
-
-    Mat mask;
-    declare.in(frame).time(90);
-    Ptr<SIFT> detector = SIFT::create();
-    vector<KeyPoint> points;
-
-    PERF_SAMPLE_BEGIN();
-        detector->detect(frame, points, mask);
-    PERF_SAMPLE_END();
-
-    SANITY_CHECK_NOTHING();
-}
-
-PERF_TEST_P(sift, extract, testing::Values(SIFT_IMAGES))
-{
-    string filename = getDataPath(GetParam());
-    Mat frame = imread(filename, IMREAD_GRAYSCALE);
-    ASSERT_FALSE(frame.empty()) << "Unable to load source image " << filename;
-
-    Mat mask;
-    declare.in(frame).time(90);
-
-    Ptr<SIFT> detector = SIFT::create();
-    vector<KeyPoint> points;
-    Mat descriptors;
-    detector->detect(frame, points, mask);
-
-    PERF_SAMPLE_BEGIN();
-        detector->compute(frame, points, descriptors);
-    PERF_SAMPLE_END();
-
-    SANITY_CHECK_NOTHING();
-}
-
-PERF_TEST_P(sift, full, testing::Values(SIFT_IMAGES))
-{
-    string filename = getDataPath(GetParam());
-    Mat frame = imread(filename, IMREAD_GRAYSCALE);
-    ASSERT_FALSE(frame.empty()) << "Unable to load source image " << filename;
-
-    Mat mask;
-    declare.in(frame).time(90);
-    Ptr<SIFT> detector = SIFT::create();
-    vector<KeyPoint> points;
-    Mat descriptors;
-
-    PERF_SAMPLE_BEGIN();
-        detector->detectAndCompute(frame, mask, points, descriptors, false);
-    PERF_SAMPLE_END();
-
-    SANITY_CHECK_NOTHING();
-}
-
-}} // namespace

modules/xfeatures2d/src/precomp.hpp

@@ -61,6 +61,4 @@
 
 #include "opencv2/core/private.hpp"
 
-#define USE_AVX2  (cv::checkHardwareSupport(CV_CPU_AVX2))
-
 #endif

modules/xfeatures2d/test/test_features2d.cpp

@@ -987,12 +987,6 @@ void CV_DescriptorMatcherTest::run( int )
  * Detectors
  */
 
-TEST( Features2d_Detector_SIFT, regression )
-{
-    CV_FeatureDetectorTest test( "detector-sift", SIFT::create() );
-    test.safe_run();
-}
-
 #ifdef OPENCV_ENABLE_NONFREE
 TEST( Features2d_Detector_SURF, regression )
 {
@@ -1028,12 +1022,6 @@ TEST( Features2d_Detector_Harris_Laplace_Affine, regression )
 /*
  * Descriptors
  */
-TEST( Features2d_DescriptorExtractor_SIFT, regression )
-{
-    CV_DescriptorExtractorTest<L1<float> > test( "descriptor-sift", 1.0f,
-                                                SIFT::create() );
-    test.safe_run();
-}
 
 #ifdef OPENCV_ENABLE_NONFREE
 TEST( Features2d_DescriptorExtractor_SURF, regression )
@@ -1413,34 +1401,6 @@ TEST(DISABLED_Features2d_SURF_using_mask, regression)
     FeatureDetectorUsingMaskTest test(SURF::create());
     test.safe_run();
 }
-
-TEST( XFeatures2d_DescriptorExtractor, batch )
-{
-    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, 0);
-        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);
-    }
-}
 #endif // NONFREE
 
 }} // namespace

modules/xfeatures2d/test/test_keypoints.cpp

@@ -121,12 +121,6 @@ TEST(Features2d_Detector_Keypoints_SURF, validation)
     CV_FeatureDetectorKeypointsTest test(xfeatures2d::SURF::create());
     test.safe_run();
 }
-
-TEST(Features2d_Detector_Keypoints_SIFT, validation)
-{
-    CV_FeatureDetectorKeypointsTest test(xfeatures2d::SIFT::create());
-    test.safe_run();
-}
 #endif // NONFREE
 
 

modules/xfeatures2d/test/test_rotation_and_scale_invariance.cpp

@@ -610,14 +610,6 @@ TEST(Features2d_RotationInvariance_Detector_SURF, regression)
     test.safe_run();
 }
 
-TEST(Features2d_RotationInvariance_Detector_SIFT, DISABLED_regression)
-{
-    DetectorRotationInvarianceTest test(SIFT::create(),
-                                        0.45f,
-                                        0.70f);
-    test.safe_run();
-}
-
 /*
  * Descriptors's rotation invariance check
  */
@@ -629,15 +621,7 @@ TEST(Features2d_RotationInvariance_Descriptor_SURF, regression)
                                           0.83f);
     test.safe_run();
 }
-
+#endif // NONFREE
-TEST(Features2d_RotationInvariance_Descriptor_SIFT, regression)
-{
-    DescriptorRotationInvarianceTest test(SIFT::create(),
-                                          SIFT::create(),
-                                          NORM_L1,
-                                          0.98f);
-    test.safe_run();
-}
 
 TEST(Features2d_RotationInvariance_Descriptor_LATCH, regression)
 {
@@ -647,7 +631,6 @@ TEST(Features2d_RotationInvariance_Descriptor_LATCH, regression)
                                           0.98f);
     test.safe_run();
 }
-#endif // NONFREE
 
 TEST(DISABLED_Features2d_RotationInvariance_Descriptor_DAISY, regression)
 {
@@ -806,14 +789,6 @@ TEST(Features2d_ScaleInvariance_Detector_SURF, regression)
     test.safe_run();
 }
 
-TEST(Features2d_ScaleInvariance_Detector_SIFT, regression)
-{
-    DetectorScaleInvarianceTest test(SIFT::create(),
-                                     0.69f,
-                                     0.98f);
-    test.safe_run();
-}
-
 /*
  * Descriptor's scale invariance check
  */
@@ -826,16 +801,6 @@ TEST(Features2d_ScaleInvariance_Descriptor_SURF, regression)
     test.safe_run();
 }
 
-TEST(Features2d_ScaleInvariance_Descriptor_SIFT, regression)
-{
-    DescriptorScaleInvarianceTest test(SIFT::create(),
-                                       SIFT::create(),
-                                       NORM_L1,
-                                       0.78f);
-    test.safe_run();
-}
-
-
 TEST(Features2d_RotationInvariance2_Detector_SURF, regression)
 {
     Mat cross(100, 100, CV_8UC1, Scalar(255));