Replace cv with cv2

GlacioHack · Oct 17, 2022 · c1fe496 · c1fe496
1 parent 86ee17e
commit c1fe496
Showing 1 changed file with 4 additions and 4 deletions.
diff --git a/xdem/filters.py b/xdem/filters.py
@@ -4,7 +4,7 @@
 import warnings
 
 try:
-    import cv2 as cv
+    import cv2
 
     _has_cv2 = True
 except ImportError:
@@ -88,7 +88,7 @@ def gaussian_filter_cv(array: NDArrayf, sigma: float) -> NDArrayf:
     # In case array does not contain NaNs, use OpenCV's gaussian filter directly
     # With kernel size (0, 0), i.e. set to default, and borderType=BORDER_REFLECT, the output is equivalent to scipy
     if np.count_nonzero(np.isnan(array)) == 0:
-        gauss = cv.GaussianBlur(array, (0, 0), sigmaX=sigma, borderType=cv.BORDER_REFLECT)
+        gauss = cv2.GaussianBlur(array, (0, 0), sigmaX=sigma, borderType=cv2.BORDER_REFLECT)
 
     # If array contain NaNs, need a more sophisticated approach
     # Inspired by https://stackoverflow.com/a/36307291
@@ -97,13 +97,13 @@ def gaussian_filter_cv(array: NDArrayf, sigma: float) -> NDArrayf:
         # Run filter on a copy with NaNs set to 0
         array_no_nan = array.copy()
         array_no_nan[np.isnan(array)] = 0
-        gauss_no_nan = cv.GaussianBlur(array_no_nan, (0, 0), sigmaX=sigma, borderType=cv.BORDER_REFLECT)
+        gauss_no_nan = cv2.GaussianBlur(array_no_nan, (0, 0), sigmaX=sigma, borderType=cv2.BORDER_REFLECT)
         del array_no_nan
 
         # Mask of NaN values
         nan_mask = 0 * array.copy() + 1
         nan_mask[np.isnan(array)] = 0
-        gauss_mask = cv.GaussianBlur(nan_mask, (0, 0), sigmaX=sigma, borderType=cv.BORDER_REFLECT)
+        gauss_mask = cv2.GaussianBlur(nan_mask, (0, 0), sigmaX=sigma, borderType=cv2.BORDER_REFLECT)
         del nan_mask
 
         with warnings.catch_warnings():