Merge pull request #17618 from Yosshi999:gsoc_sift-better-test

Added/Fixed testcases for SIFT

* merge perf_sift into conventional perf tests

* Fix disabled SIFT scale invariance tests

allows trainIdx duplication in matching scaled keypoints

modules/features2d/include/opencv2/features2d.hpp

@@ -261,6 +261,10 @@ public:
     @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.
 
+    @note The contrast threshold will be divided by nOctaveLayers when the filtering is applied. When
+    nOctaveLayers is set to default and if you want to use the value used in D. Lowe paper, 0.03, set
+    this argument to 0.09.
+
     @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).
@@ -271,6 +275,8 @@ public:
     CV_WRAP static Ptr<SIFT> create(int nfeatures = 0, int nOctaveLayers = 3,
         double contrastThreshold = 0.04, double edgeThreshold = 10,
         double sigma = 1.6);
+
+    CV_WRAP virtual String getDefaultName() const CV_OVERRIDE;
 };
 
 typedef SIFT SiftFeatureDetector;

modules/features2d/perf/perf_feature2d.hpp

@@ -21,7 +21,8 @@ namespace opencv_test
     ORB_DEFAULT, ORB_1500_13_1,                                                         \
     AKAZE_DEFAULT, AKAZE_DESCRIPTOR_KAZE,                                               \
     BRISK_DEFAULT,                                                                      \
-    KAZE_DEFAULT
+    KAZE_DEFAULT,                                                                       \
+    SIFT_DEFAULT
 
 #define CV_ENUM_EXPAND(name, ...) CV_ENUM(name, __VA_ARGS__)
 
@@ -77,6 +78,8 @@ static inline Ptr<Feature2D> getFeature2D(Feature2DType type)
         return KAZE::create();
     case MSER_DEFAULT:
         return MSER::create();
+    case SIFT_DEFAULT:
+        return SIFT::create();
     default:
         return Ptr<Feature2D>();
     }

modules/features2d/perf/perf_sift.cpp

@@ -1,85 +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_detect;
-typedef perf::TestBaseWithParam<std::string> SIFT_extract;
-typedef perf::TestBaseWithParam<std::string> SIFT_full;
-
-#define SIFT_IMAGES \
-    "cv/detectors_descriptors_evaluation/images_datasets/leuven/img1.png",\
-    "stitching/a3.png"
-
-PERF_TEST_P_(SIFT_detect, SIFT)
-{
-    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, SIFT)
-{
-    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, SIFT)
-{
-    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();
-}
-
-
-INSTANTIATE_TEST_CASE_P(/*nothing*/, SIFT_detect,
-    testing::Values(SIFT_IMAGES)
-);
-INSTANTIATE_TEST_CASE_P(/*nothing*/, SIFT_extract,
-    testing::Values(SIFT_IMAGES)
-);
-INSTANTIATE_TEST_CASE_P(/*nothing*/, SIFT_full,
-    testing::Values(SIFT_IMAGES)
-);
-
-}} // namespace

modules/features2d/src/sift.dispatch.cpp

@@ -126,6 +126,11 @@ Ptr<SIFT> SIFT::create( int _nfeatures, int _nOctaveLayers,
     return makePtr<SIFT_Impl>(_nfeatures, _nOctaveLayers, _contrastThreshold, _edgeThreshold, _sigma);
 }
 
+String SIFT::getDefaultName() const
+{
+    return (Feature2D::getDefaultName() + ".SIFT");
+}
+
 static inline void
 unpackOctave(const KeyPoint& kpt, int& octave, int& layer, float& scale)
 {

modules/features2d/test/test_descriptors_invariance.cpp

@@ -15,6 +15,26 @@ const static std::string IMAGE_TSUKUBA = "features2d/tsukuba.png";
 const static std::string IMAGE_BIKES = "detectors_descriptors_evaluation/images_datasets/bikes/img1.png";
 #define Value(...) Values(String_FeatureDetector_DescriptorExtractor_Float_t(__VA_ARGS__))
 
+static
+void SetSuitableSIFTOctave(vector<KeyPoint>& keypoints,
+                             int firstOctave = -1, int nOctaveLayers = 3, double sigma = 1.6)
+{
+    for (size_t i = 0; i < keypoints.size(); i++ )
+    {
+        int octv, layer;
+        KeyPoint& kpt = keypoints[i];
+        double octv_layer = std::log(kpt.size / sigma) / std::log(2.) - 1;
+        octv = cvFloor(octv_layer);
+        layer = cvRound( (octv_layer - octv) * nOctaveLayers );
+        if (octv < firstOctave)
+        {
+            octv = firstOctave;
+            layer = 0;
+        }
+        kpt.octave = (layer << 8) | (octv & 255);
+    }
+}
+
 static
 void rotateKeyPoints(const vector<KeyPoint>& src, const Mat& H, float angle, vector<KeyPoint>& dst)
 {
@@ -132,6 +152,10 @@ TEST_P(DescriptorScaleInvariance, scale)
 
         vector<KeyPoint> keypoints1;
         scaleKeyPoints(keypoints0, keypoints1, 1.0f/scale);
+        if (featureDetector->getDefaultName() == "Feature2D.SIFT")
+        {
+            SetSuitableSIFTOctave(keypoints1);
+        }
         Mat descriptors1;
         descriptorExtractor->compute(image1, keypoints1, descriptors1);
 
@@ -186,9 +210,8 @@ INSTANTIATE_TEST_CASE_P(AKAZE_DESCRIPTOR_KAZE, DescriptorRotationInvariance,
  * Descriptor's scale invariance check
  */
 
-// TODO: Expected: (descInliersRatio) >= (minInliersRatio), actual: 0.330378 vs 0.78
+INSTANTIATE_TEST_CASE_P(SIFT, DescriptorScaleInvariance,
-INSTANTIATE_TEST_CASE_P(DISABLED_SIFT, DescriptorScaleInvariance,
+                        Value(IMAGE_BIKES, SIFT::create(0, 3, 0.09), SIFT::create(0, 3, 0.09), 0.78f));
-                        Value(IMAGE_BIKES, SIFT::create(), SIFT::create(), 0.78f));
 
 INSTANTIATE_TEST_CASE_P(AKAZE, DescriptorScaleInvariance,
                         Value(IMAGE_BIKES, AKAZE::create(), AKAZE::create(), 0.6f));

modules/features2d/test/test_detectors_invariance.cpp

@@ -29,7 +29,6 @@ void matchKeyPoints(const vector<KeyPoint>& keypoints0, const Mat& H,
         perspectiveTransform(Mat(points0), points0t, H);
 
     matches.clear();
-    vector<uchar> usedMask(keypoints1.size(), 0);
     for(int i0 = 0; i0 < static_cast<int>(keypoints0.size()); i0++)
     {
         int nearestPointIndex = -1;
@@ -37,8 +36,6 @@ void matchKeyPoints(const vector<KeyPoint>& keypoints0, const Mat& H,
         const float r0 =  0.5f * keypoints0[i0].size;
         for(size_t i1 = 0; i1 < keypoints1.size(); i1++)
         {
-            if(nearestPointIndex >= 0 && usedMask[i1])
-                continue;
 
             float r1 = 0.5f * keypoints1[i1].size;
             float intersectRatio = calcIntersectRatio(points0t.at<Point2f>(i0), r0,
@@ -51,8 +48,6 @@ void matchKeyPoints(const vector<KeyPoint>& keypoints0, const Mat& H,
         }
 
         matches.push_back(DMatch(i0, nearestPointIndex, maxIntersectRatio));
-        if(nearestPointIndex >= 0)
-            usedMask[nearestPointIndex] = 1;
     }
 }
 
@@ -239,9 +234,8 @@ INSTANTIATE_TEST_CASE_P(AKAZE_DESCRIPTOR_KAZE, DetectorRotationInvariance,
  * Detector's scale invariance check
  */
 
-// TODO: Expected: (keyPointMatchesRatio) >= (minKeyPointMatchesRatio), actual: 0.596752 vs 0.69
+INSTANTIATE_TEST_CASE_P(SIFT, DetectorScaleInvariance,
-INSTANTIATE_TEST_CASE_P(DISABLED_SIFT, DetectorScaleInvariance,
+                        Value(IMAGE_BIKES, SIFT::create(0, 3, 0.09), 0.69f, 0.98f));
-                        Value(IMAGE_BIKES, SIFT::create(), 0.69f, 0.98f));
 
 INSTANTIATE_TEST_CASE_P(BRISK, DetectorScaleInvariance,
                         Value(IMAGE_BIKES, BRISK::create(), 0.08f, 0.49f));