Update findContours parameter type

samples/python/tutorial_code/ImgTrans/distance_transformation/imageSegmentation.py

@@ -91,7 +91,7 @@ cv.imshow('Peaks', dist)
 dist_8u = dist.astype('uint8')
 
 # Find total markers
-_, contours, _ = cv.findContours(dist_8u, cv.RETR_EXTERNAL, cv.CHAIN_APPROX_SIMPLE)
+contours, _ = cv.findContours(dist_8u, cv.RETR_EXTERNAL, cv.CHAIN_APPROX_SIMPLE)
 
 # Create the marker image for the watershed algorithm
 markers = np.zeros(dist.shape, dtype=np.int32)

samples/python/tutorial_code/ShapeDescriptors/bounding_rects_circles/generalContours_demo1.py

@@ -16,7 +16,7 @@ def thresh_callback(val):
 
     ## [findContours]
     # Find contours
-    _, contours, _ = cv.findContours(canny_output, cv.RETR_TREE, cv.CHAIN_APPROX_SIMPLE)
+    contours, _ = cv.findContours(canny_output, cv.RETR_TREE, cv.CHAIN_APPROX_SIMPLE)
     ## [findContours]
 
     ## [allthework]

samples/python/tutorial_code/ShapeDescriptors/bounding_rotated_ellipses/generalContours_demo2.py

@@ -16,7 +16,7 @@ def thresh_callback(val):
 
     ## [findContours]
     # Find contours
-    _, contours, _ = cv.findContours(canny_output, cv.RETR_TREE, cv.CHAIN_APPROX_SIMPLE)
+    contours, _ = cv.findContours(canny_output, cv.RETR_TREE, cv.CHAIN_APPROX_SIMPLE)
     ## [findContours]
 
     # Find the rotated rectangles and ellipses for each contour

samples/python/tutorial_code/ShapeDescriptors/find_contours/findContours_demo.py

@@ -13,7 +13,7 @@ def thresh_callback(val):
     canny_output = cv.Canny(src_gray, threshold, threshold * 2)
 
     # Find contours
-    _, contours, hierarchy = cv.findContours(canny_output, cv.RETR_TREE, cv.CHAIN_APPROX_SIMPLE)
+    contours, hierarchy = cv.findContours(canny_output, cv.RETR_TREE, cv.CHAIN_APPROX_SIMPLE)
 
     # Draw contours
     drawing = np.zeros((canny_output.shape[0], canny_output.shape[1], 3), dtype=np.uint8)

samples/python/tutorial_code/ShapeDescriptors/hull/hull_demo.py

@@ -13,7 +13,7 @@ def thresh_callback(val):
     canny_output = cv.Canny(src_gray, threshold, threshold * 2)
 
     # Find contours
-    _, contours, _ = cv.findContours(canny_output, cv.RETR_TREE, cv.CHAIN_APPROX_SIMPLE)
+    contours, _ = cv.findContours(canny_output, cv.RETR_TREE, cv.CHAIN_APPROX_SIMPLE)
 
     # Find the convex hull object for each contour
     hull_list = []

samples/python/tutorial_code/ShapeDescriptors/moments/moments_demo.py

@@ -17,7 +17,7 @@ def thresh_callback(val):
 
     ## [findContours]
     # Find contours
-    _, contours, _ = cv.findContours(canny_output, cv.RETR_TREE, cv.CHAIN_APPROX_SIMPLE)
+    contours, _ = cv.findContours(canny_output, cv.RETR_TREE, cv.CHAIN_APPROX_SIMPLE)
     ## [findContours]
 
     # Get the moments

samples/python/tutorial_code/ShapeDescriptors/point_polygon_test/pointPolygonTest_demo.py

@@ -21,7 +21,7 @@ for i in range(6):
     cv.line(src, vert[i],  vert[(i+1)%6], ( 255 ), 3)
 
 # Get the contours
-_, contours, _ = cv.findContours(src, cv.RETR_TREE, cv.CHAIN_APPROX_SIMPLE)
+contours, _ = cv.findContours(src, cv.RETR_TREE, cv.CHAIN_APPROX_SIMPLE)
 
 # Calculate the distances to the contour
 raw_dist = np.empty(src.shape, dtype=np.float32)

samples/python/tutorial_code/ml/introduction_to_pca/introduction_to_pca.py

@@ -81,7 +81,7 @@ _, bw = cv.threshold(gray, 50, 255, cv.THRESH_BINARY | cv.THRESH_OTSU)
 
 ## [contours]
 # Find all the contours in the thresholded image
-_, contours, _ = cv.findContours(bw, cv.RETR_LIST, cv.CHAIN_APPROX_NONE)
+contours, _ = cv.findContours(bw, cv.RETR_LIST, cv.CHAIN_APPROX_NONE)
 
 for i, c in enumerate(contours):
     # Calculate the area of each contour