import cv2
import numpy as np
from matplotlib import pyplot as plt


def auto_canny(image, sigma=0.33):
    median = np.median(image)
    lower = int(max(0, (1.0 - sigma) * median))
    upper = int(min(255, (1.0 + sigma) * median))
    edged = cv2.Canny(image, lower, upper, L2gradient=True)
    return edged

def findPlane(pic):
    img = cv2.imread(pic,0) #0 -w odc szarosci
    edges = cv2.GaussianBlur(img, (3, 3), 0)  #filtr gaussowski
    edges = auto_canny(edges)                  #canny
    edges = cv2.blur(edges, (5, 5))             #blur
    image, contours, hierarchy = cv2.findContours(edges, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)   #pobieram krawedzie
    edges = cv2.drawContours(edges, contours, -1, (255, 255, 255), cv2.FILLED)  #nakladam wypelnione krawedzie
    edges = auto_canny(edges)
    cv2.imwrite("edged-" + pic, edges)  #zapis obrazka
    return edges

pics = ['samolot17.jpg','samolot07.jpg','samolot08.jpg','samolot09.jpg','samolot10.jpg','samolot14.jpg']

fig = plt.figure(1)
fig.subplots_adjust(wspace=0, hspace=0, top=1, bottom=0, left=0, right=1)
for each in pics:
    ax = fig.add_subplot(3, 2, pics.index(each) + 1)
    new_pic = findPlane(each)
    height, width = new_pic.shape[:2]     #skalowanie dla lepszego rysowania
    max_height = 200
    max_width = 300
    scaling_factor = max_height / float(height)
    new_pic = cv2.resize(new_pic, None, fx=scaling_factor, fy=scaling_factor, interpolation=cv2.INTER_AREA)
    ax.imshow(new_pic, cmap="gray", aspect='auto')


plt.show()
key = cv2.waitKey()