Fix findContours call for recent versions of opencv

Fix baiwenjia#14
BioMeDS · Aug 31, 2022 · f5ab9f6 · f5ab9f6
1 parent da49225
commit f5ab9f6
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Showing 2 changed files with 9 additions and 9 deletions.
diff --git a/common/cardiac_utils.py b/common/cardiac_utils.py
@@ -190,7 +190,7 @@ def determine_aha_coordinate_system(seg_sa, affine_sa):
     rv = get_largest_cc(rv).astype(np.uint8)
 
     # Extract epicardial contour
-    _, contours, _ = cv2.findContours(cv2.inRange(epi, 1, 1), cv2.RETR_TREE, cv2.CHAIN_APPROX_NONE)
+    contours, _ = cv2.findContours(cv2.inRange(epi, 1, 1), cv2.RETR_TREE, cv2.CHAIN_APPROX_NONE)
     epi_contour = contours[0][:, 0, :]
 
     # Find the septum, which is the intersection between LV and RV
@@ -417,11 +417,11 @@ def evaluate_wall_thickness(seg_name, output_name_stem, part=None):
         # Extract endocardial contour
         # Note: cv2 considers an input image as a Y x X array, which is different
         # from nibabel which assumes a X x Y array.
-        _, contours, _ = cv2.findContours(cv2.inRange(endo, 1, 1), cv2.RETR_TREE, cv2.CHAIN_APPROX_NONE)
+        contours, _ = cv2.findContours(cv2.inRange(endo, 1, 1), cv2.RETR_TREE, cv2.CHAIN_APPROX_NONE)
         endo_contour = contours[0][:, 0, :]
 
         # Extract epicardial contour
-        _, contours, _ = cv2.findContours(cv2.inRange(epi, 1, 1), cv2.RETR_TREE, cv2.CHAIN_APPROX_NONE)
+        contours, _ = cv2.findContours(cv2.inRange(epi, 1, 1), cv2.RETR_TREE, cv2.CHAIN_APPROX_NONE)
         epi_contour = contours[0][:, 0, :]
 
         # Smooth the contours
@@ -612,7 +612,7 @@ def extract_myocardial_contour(seg_name, contour_name_stem, part=None, three_sli
         lv_centre = np.dot(affine, np.array([cx, cy, z, 1]))[:3]
 
         # Extract epicardial contour
-        _, contours, _ = cv2.findContours(cv2.inRange(epi, 1, 1), cv2.RETR_TREE, cv2.CHAIN_APPROX_NONE)
+        contours, _ = cv2.findContours(cv2.inRange(epi, 1, 1), cv2.RETR_TREE, cv2.CHAIN_APPROX_NONE)
         epi_contour = contours[0][:, 0, :]
         epi_contour = approximate_contour(epi_contour, periodic=True)
 
@@ -666,7 +666,7 @@ def extract_myocardial_contour(seg_name, contour_name_stem, part=None, three_sli
         # Extract endocardial contour
         # Note: cv2 considers an input image as a Y x X array, which is different
         # from nibabel which assumes a X x Y array.
-        _, contours, _ = cv2.findContours(cv2.inRange(endo, 1, 1), cv2.RETR_TREE, cv2.CHAIN_APPROX_NONE)
+        contours, _ = cv2.findContours(cv2.inRange(endo, 1, 1), cv2.RETR_TREE, cv2.CHAIN_APPROX_NONE)
         endo_contour = contours[0][:, 0, :]
         endo_contour = approximate_contour(endo_contour, periodic=True)
 
@@ -1187,11 +1187,11 @@ def extract_la_myocardial_contour(seg_la_name, seg_sa_name, contour_name):
     # Extract endocardial contour
     # Note: cv2 considers an input image as a Y x X array, which is different
     # from nibabel which assumes a X x Y array.
-    _, contours, _ = cv2.findContours(cv2.inRange(endo, 1, 1), cv2.RETR_TREE, cv2.CHAIN_APPROX_NONE)
+    contours, _ = cv2.findContours(cv2.inRange(endo, 1, 1), cv2.RETR_TREE, cv2.CHAIN_APPROX_NONE)
     endo_contour = contours[0][:, 0, :]
 
     # Extract epicardial contour
-    _, contours, _ = cv2.findContours(cv2.inRange(epi, 1, 1), cv2.RETR_TREE, cv2.CHAIN_APPROX_NONE)
+    contours, _ = cv2.findContours(cv2.inRange(epi, 1, 1), cv2.RETR_TREE, cv2.CHAIN_APPROX_NONE)
     epi_contour = contours[0][:, 0, :]
 
     # Record the points located on the mitral valve plane.

diff --git a/common/image_utils.py b/common/image_utils.py
@@ -192,14 +192,14 @@ def distance_metric(seg_A, seg_B, dx):
         # The distance is defined only when both contours exist on this slice
         if np.sum(slice_A) > 0 and np.sum(slice_B) > 0:
             # Find contours and retrieve all the points
-            _, contours, _ = cv2.findContours(cv2.inRange(slice_A, 1, 1),
+            contours, _ = cv2.findContours(cv2.inRange(slice_A, 1, 1),
                                               cv2.RETR_EXTERNAL,
                                               cv2.CHAIN_APPROX_NONE)
             pts_A = contours[0]
             for i in range(1, len(contours)):
                 pts_A = np.vstack((pts_A, contours[i]))
 
-            _, contours, _ = cv2.findContours(cv2.inRange(slice_B, 1, 1),
+            contours, _ = cv2.findContours(cv2.inRange(slice_B, 1, 1),
                                               cv2.RETR_EXTERNAL,
                                               cv2.CHAIN_APPROX_NONE)
             pts_B = contours[0]