1. import cv2
2. import numpy as np
3. from matplotlib import pyplot as plt
4.  
5.  
6. def auto_canny(image, sigma=0.33):
7.     median = np.median(image)
8.     lower = int(max(0, (1.0 - sigma) * median))
9.     upper = int(min(255, (1.0 + sigma) * median))
10.     edged = cv2.Canny(image, lower, upper, L2gradient=True)
11.     return edged
12.  
13. def findPlane(pic):
14.     img = cv2.imread(pic,0) #0 -w odc szarosci
15.     edges = cv2.GaussianBlur(img, (3, 3), 0)  #filtr gaussowski
16.     edges = auto_canny(edges)                  #canny
17.     edges = cv2.blur(edges, (5, 5))             #blur
18.     image, contours, hierarchy = cv2.findContours(edges, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)   #pobieram krawedzie
19.     edges = cv2.drawContours(edges, contours, -1, (255, 255, 255), cv2.FILLED)  #nakladam wypelnione krawedzie
20.     edges = auto_canny(edges)
21.     cv2.imwrite("edged-" + pic, edges)  #zapis obrazka
22.     return edges
23.  
24. pics = ['samolot17.jpg','samolot07.jpg','samolot08.jpg','samolot09.jpg','samolot10.jpg','samolot14.jpg']
25.  
26. fig = plt.figure(1)
27. fig.subplots_adjust(wspace=0, hspace=0, top=1, bottom=0, left=0, right=1)
28. for each in pics:
29.     ax = fig.add_subplot(3, 2, pics.index(each) + 1)
30.     new_pic = findPlane(each)
31.     height, width = new_pic.shape[:2]     #skalowanie dla lepszego rysowania
32.     max_height = 200
33.     max_width = 300
34.     scaling_factor = max_height / float(height)
35.     new_pic = cv2.resize(new_pic, None, fx=scaling_factor, fy=scaling_factor, interpolation=cv2.INTER_AREA)
36.     ax.imshow(new_pic, cmap="gray", aspect='auto')
37.  
38.  
39. plt.show()
40. key = cv2.waitKey()