Tracker: clean up GMC (#8003)

ultralytics/trackers/utils/gmc.py

@@ -97,13 +97,13 @@ class GMC:
         if self.method in ["orb", "sift"]:
             return self.applyFeatures(raw_frame, detections)
         elif self.method == "ecc":
-            return self.applyEcc(raw_frame, detections)
+            return self.applyEcc(raw_frame)
         elif self.method == "sparseOptFlow":
-            return self.applySparseOptFlow(raw_frame, detections)
+            return self.applySparseOptFlow(raw_frame)
         else:
             return np.eye(2, 3)
 
-    def applyEcc(self, raw_frame: np.array, detections: list = None) -> np.array:
+    def applyEcc(self, raw_frame: np.array) -> np.array:
         """
         Apply ECC algorithm to a raw frame.
 
@@ -144,7 +144,7 @@ class GMC:
         # Run the ECC algorithm. The results are stored in warp_matrix.
         # (cc, H) = cv2.findTransformECC(self.prevFrame, frame, H, self.warp_mode, self.criteria)
         try:
-            (cc, H) = cv2.findTransformECC(self.prevFrame, frame, H, self.warp_mode, self.criteria, None, 1)
+            (_, H) = cv2.findTransformECC(self.prevFrame, frame, H, self.warp_mode, self.criteria, None, 1)
         except Exception as e:
             LOGGER.warning(f"WARNING: find transform failed. Set warp as identity {e}")
 
@@ -275,7 +275,7 @@ class GMC:
         #     plt.show()
 
         # Find rigid matrix
-        if (prevPoints.shape[0] > 4) and (prevPoints.shape[0] == prevPoints.shape[0]):
+        if prevPoints.shape[0] > 4:
             H, inliers = cv2.estimateAffinePartial2D(prevPoints, currPoints, cv2.RANSAC)
 
             # Handle downscale
@@ -292,7 +292,7 @@ class GMC:
 
         return H
 
-    def applySparseOptFlow(self, raw_frame: np.array, detections: list = None) -> np.array:
+    def applySparseOptFlow(self, raw_frame: np.array) -> np.array:
         """
         Apply Sparse Optical Flow method to a raw frame.
 
@@ -328,7 +328,7 @@ class GMC:
             return H
 
         # Find correspondences
-        matchedKeypoints, status, err = cv2.calcOpticalFlowPyrLK(self.prevFrame, frame, self.prevKeyPoints, None)
+        matchedKeypoints, status, _ = cv2.calcOpticalFlowPyrLK(self.prevFrame, frame, self.prevKeyPoints, None)
 
         # Leave good correspondences only
         prevPoints = []
@@ -344,7 +344,7 @@ class GMC:
 
         # Find rigid matrix
         if (prevPoints.shape[0] > 4) and (prevPoints.shape[0] == prevPoints.shape[0]):
-            H, inliers = cv2.estimateAffinePartial2D(prevPoints, currPoints, cv2.RANSAC)
+            H, _ = cv2.estimateAffinePartial2D(prevPoints, currPoints, cv2.RANSAC)
 
             if self.downscale > 1.0:
                 H[0, 2] *= self.downscale