Normalize line endings and whitespace

samples/python2/squares.py

@@ -1,46 +1,46 @@
-'''
-Simple "Square Detector" program.
-
-Loads several images sequentially and tries to find squares in each image.
-'''
-
-import numpy as np
-import cv2
-
-
-def angle_cos(p0, p1, p2):
-    d1, d2 = (p0-p1).astype('float'), (p2-p1).astype('float')
-    return abs( np.dot(d1, d2) / np.sqrt( np.dot(d1, d1)*np.dot(d2, d2) ) )
-
-def find_squares(img):
-    img = cv2.GaussianBlur(img, (5, 5), 0)
-    squares = []
-    for gray in cv2.split(img):
-        for thrs in xrange(0, 255, 26):
-            if thrs == 0:
-                bin = cv2.Canny(gray, 0, 50, apertureSize=5)
-                bin = cv2.dilate(bin, None)
-            else:
-                retval, bin = cv2.threshold(gray, thrs, 255, cv2.THRESH_BINARY)
-            contours, hierarchy = cv2.findContours(bin, cv2.RETR_LIST, cv2.CHAIN_APPROX_SIMPLE)
-            for cnt in contours:
-                cnt_len = cv2.arcLength(cnt, True)
-                cnt = cv2.approxPolyDP(cnt, 0.02*cnt_len, True)
-                if len(cnt) == 4 and cv2.contourArea(cnt) > 1000 and cv2.isContourConvex(cnt):
-                    cnt = cnt.reshape(-1, 2)
-                    max_cos = np.max([angle_cos( cnt[i], cnt[(i+1) % 4], cnt[(i+2) % 4] ) for i in xrange(4)])
-                    if max_cos < 0.1:
-                        squares.append(cnt)
-    return squares
-
-if __name__ == '__main__':
-    from glob import glob
-    for fn in glob('../cpp/pic*.png'):
-        img = cv2.imread(fn)
-        squares = find_squares(img)
-        cv2.drawContours( img, squares, -1, (0, 255, 0), 3 )
-        cv2.imshow('squares', img)
-        ch = 0xFF & cv2.waitKey()
-        if ch == 27:
-            break
-    cv2.destroyAllWindows() 			
+'''
+Simple "Square Detector" program.
+
+Loads several images sequentially and tries to find squares in each image.
+'''
+
+import numpy as np
+import cv2
+
+
+def angle_cos(p0, p1, p2):
+    d1, d2 = (p0-p1).astype('float'), (p2-p1).astype('float')
+    return abs( np.dot(d1, d2) / np.sqrt( np.dot(d1, d1)*np.dot(d2, d2) ) )
+
+def find_squares(img):
+    img = cv2.GaussianBlur(img, (5, 5), 0)
+    squares = []
+    for gray in cv2.split(img):
+        for thrs in xrange(0, 255, 26):
+            if thrs == 0:
+                bin = cv2.Canny(gray, 0, 50, apertureSize=5)
+                bin = cv2.dilate(bin, None)
+            else:
+                retval, bin = cv2.threshold(gray, thrs, 255, cv2.THRESH_BINARY)
+            contours, hierarchy = cv2.findContours(bin, cv2.RETR_LIST, cv2.CHAIN_APPROX_SIMPLE)
+            for cnt in contours:
+                cnt_len = cv2.arcLength(cnt, True)
+                cnt = cv2.approxPolyDP(cnt, 0.02*cnt_len, True)
+                if len(cnt) == 4 and cv2.contourArea(cnt) > 1000 and cv2.isContourConvex(cnt):
+                    cnt = cnt.reshape(-1, 2)
+                    max_cos = np.max([angle_cos( cnt[i], cnt[(i+1) % 4], cnt[(i+2) % 4] ) for i in xrange(4)])
+                    if max_cos < 0.1:
+                        squares.append(cnt)
+    return squares
+
+if __name__ == '__main__':
+    from glob import glob
+    for fn in glob('../cpp/pic*.png'):
+        img = cv2.imread(fn)
+        squares = find_squares(img)
+        cv2.drawContours( img, squares, -1, (0, 255, 0), 3 )
+        cv2.imshow('squares', img)
+        ch = 0xFF & cv2.waitKey()
+        if ch == 27:
+            break
+    cv2.destroyAllWindows()