Remove dublicated SIFT-Dectector instance in feature matching (#1053)

Summary:
It seems to me that the SIFT detector is instantiated, but then not used, because the object is created again in the following while loop. This merge request removes the unnecessary code.
I have also made the missing parameters of the OpenCV-Sift implementation configurable.

Pull Request resolved: #1053

Reviewed By: paulinus

Differential Revision: D57765783

Pulled By: fabianschenk

fbshipit-source-id: 59a24bbbc60f55c1cb5e1f81a9896ec13f82e5d8

opensfm/config.py

@@ -42,6 +42,12 @@ class OpenSfMConfig:
     sift_peak_threshold: float = 0.1
     # See OpenCV doc
     sift_edge_threshold: int = 10
+    # See OpenCV doc
+    sift_nfeatures: int = 0
+    # See OpenCV doc
+    sift_octave_layers: int = 3
+    # See OpenCV doc
+    sift_sigma: float = 1.6
 
     ##################################
     # Params for SURF

opensfm/features.py

@@ -353,45 +353,36 @@ def extract_features_sift(
 ) -> Tuple[np.ndarray, np.ndarray]:
     sift_edge_threshold = config["sift_edge_threshold"]
     sift_peak_threshold = float(config["sift_peak_threshold"])
-    # SIFT support is in cv2 main from version 4.4.0
-    if context.OPENCV44 or context.OPENCV5:
-        # OpenCV versions concerned /** 3.4.11, >= 4.4.0 **/  ==> Sift became free since March 2020
-        detector = cv2.SIFT_create(
-            edgeThreshold=sift_edge_threshold, contrastThreshold=sift_peak_threshold
-        )
-        descriptor = detector
-    elif context.OPENCV3 or context.OPENCV4:
-        try:
-            # OpenCV versions concerned /** 3.2.x, 3.3.x, 3.4.0, 3.4.1, 3.4.2, 3.4.10, 4.3.0, 4.4.0 **/
-            detector = cv2.xfeatures2d.SIFT_create(
-                edgeThreshold=sift_edge_threshold, contrastThreshold=sift_peak_threshold
-            )
-        except AttributeError as ae:
-            # OpenCV versions concerned /** 3.4.3, 3.4.4, 3.4.5, 3.4.6, 3.4.7, 3.4.8, 3.4.9, 4.0.x, 4.1.x, 4.2.x **/
-            if "no attribute 'xfeatures2d'" in str(ae):
-                logger.error(
-                    "OpenCV Contrib modules are required to extract SIFT features"
-                )
-            raise
-        descriptor = detector
-    else:
-        detector = cv2.FeatureDetector_create("SIFT")
-        descriptor = cv2.DescriptorExtractor_create("SIFT")
-        detector.setDouble("edgeThreshold", sift_edge_threshold)
+    sift_nfeatures = config["sift_nfeatures"]
+    sift_octave_layers = config["sift_octave_layers"]
+    sift_sigma = float(config["sift_sigma"])
     while True:
         logger.debug("Computing sift with threshold {0}".format(sift_peak_threshold))
         t = time.time()
         # SIFT support is in cv2 main from version 4.4.0
         if context.OPENCV44 or context.OPENCV5:
             detector = cv2.SIFT_create(
-                edgeThreshold=sift_edge_threshold, contrastThreshold=sift_peak_threshold
+                nfeatures=sift_nfeatures,
+                nOctaveLayers=sift_octave_layers,
+                contrastThreshold=sift_peak_threshold,
+                edgeThreshold=sift_edge_threshold,
+                sigma=sift_sigma,
             )
+            descriptor = detector
         elif context.OPENCV3:
             detector = cv2.xfeatures2d.SIFT_create(
-                edgeThreshold=sift_edge_threshold, contrastThreshold=sift_peak_threshold
+                nfeatures=sift_nfeatures,
+                nOctaveLayers=sift_octave_layers,
+                contrastThreshold=sift_peak_threshold,
+                edgeThreshold=sift_edge_threshold,
+                sigma=sift_sigma,
             )
+            descriptor = detector
         else:
-            detector.setDouble("contrastThreshold", sift_peak_threshold)
+            detector = cv2.FeatureDetector_create("SIFT")
+            descriptor = cv2.DescriptorExtractor_create("SIFT")
+            detector.setDouble("edgeThreshold", sift_edge_threshold)
+
         points = detector.detect(image)
         logger.debug("Found {0} points in {1}s".format(len(points), time.time() - t))
         if len(points) < features_count and sift_peak_threshold > 0.0001:
@@ -400,6 +391,7 @@ def extract_features_sift(
         else:
             logger.debug("done")
             break
+
     points, desc = descriptor.compute(image, points)
 
     if desc is not None: