update for zhihu TUTR_edge_detection

Author: Yonv1943

Demo/TUTR_edge_detection.py

@@ -2,7 +2,10 @@
 import numpy as np
 
 '''REFER: https://hub.packtpub.com/opencv-detecting-edges-lines-shapes/'''
-'''Yonv1943 2018-06-30 23:00:14'''
+'''Yonv1943 2018-06-30 '''
+'''Yonv1943 2018-07-01 comment to test.png'''
+'''Yonv1943 2018-07-01 gray in threshold, hierarchy'''
+'''Yonv1943 2018-07-01 draw_approx_hull_polygon() no [for loop]'''
 
 
 def draw_contours(img, cnts):  # conts = contours
@@ -13,6 +16,7 @@ def draw_contours(img, cnts):  # conts = contours
 
 def draw_min_rect_circle(img, cnts):  # conts = contours
     img = np.copy(img)
+
     for cnt in cnts:
         x, y, w, h = cv2.boundingRect(cnt)
         cv2.rectangle(img, (x, y), (x + w, y + h), (255, 0, 0), 2)  # blue
@@ -30,31 +34,44 @@ def draw_min_rect_circle(img, cnts):  # conts = contours
 def draw_approx_hull_polygon(img, cnts):
     # img = np.copy(img)
     img = np.zeros(img.shape, dtype=np.uint8)
-    for cnt in cnts:
-        img = cv2.drawContours(img, cnts, -1, (255, 0, 0), 2)  # blue
 
-        epsilon = 0.02 * cv2.arcLength(cnt, True)
-        approx = cv2.approxPolyDP(cnt, epsilon, True)
-        cv2.polylines(img, [approx, ], True, (0, 255, 0), 2)  # green
+    cv2.drawContours(img, cnts, -1, (255, 0, 0), 2)  # blue
+
+    epsilion = img.shape[0]/32
+    approxes = [cv2.approxPolyDP(cnt, epsilion, True) for cnt in cnts]
+    cv2.polylines(img, approxes, True, (0, 255, 0), 2)  # green
+
+    hulls = [cv2.convexHull(cnt) for cnt in cnts]
+    cv2.polylines(img, hulls, True, (0, 0, 255), 2)  # red
 
-        hull = cv2.convexHull(cnt)
-        cv2.polylines(img, [hull, ], True, (0, 0, 255), 2)  # red
+    # for cnt in cnts:
+    #     cv2.drawContours(img, [cnt, ], -1, (255, 0, 0), 2)  # blue
+    #
+    #     epsilon = 0.02 * cv2.arcLength(cnt, True)
+    #     approx = cv2.approxPolyDP(cnt, epsilon, True)
+    #     cv2.polylines(img, [approx, ], True, (0, 255, 0), 2)  # green
+    #
+    #     hull = cv2.convexHull(cnt)
+    #     cv2.polylines(img, [hull, ], True, (0, 0, 255), 2)  # red
     return img
 
 
 def run():
-    image = cv2.imread('test.png')
+    image = cv2.imread('test.png')  # a black objects on white image is better
 
-    # ret, thresh = cv2.threshold(cv2.cvtColor(image.copy(), cv2.COLOR_BGR2GRAY), 127, 255, cv2.THRESH_BINARY)
+    # gray = cv2.cvtColor(image.copy(), cv2.COLOR_BGR2GRAY)
+    # ret, thresh = cv2.threshold(gray, 127, 255, cv2.THRESH_BINARY)
     thresh = cv2.Canny(image, 128, 256)
 
     thresh, contours, hierarchy = cv2.findContours(thresh, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)
+    # print(hierarchy, ":hierarchy")
     """
-    print("hierarchy:", hierarchy)
-    hierarchy: [[[1, -1, -1, -1],
-                 [2,  0, -1, -1],
-                 [3,  1, -1, -1],
-                 [-1, 2, -1, -1],]]
+    [[[-1 -1 -1 -1]]] :hierarchy  # cv2.Canny()
+    
+    [[[ 1 -1 -1 -1]
+      [ 2  0 -1 -1]
+      [ 3  1 -1 -1]
+      [-1  2 -1 -1]]] :hierarchy  # cv2.threshold()
     """
 
     imgs = [
@@ -64,9 +81,9 @@ def run():
     ]
 
     for img in imgs:
-        cv2.imwrite("%s.jpg" % id(img), img)
+        # cv2.imwrite("%s.jpg" % id(img), img)
         cv2.imshow("contours", img)
-        cv2.waitKey(1234)
+        cv2.waitKey(1943)
 
 
 if __name__ == '__main__':