edge_detection.py

import cv2;
import numpy as np;

img = cv2.imread("test.jpg", 0);
h, w = img.shape[:2]
kernel = np.ones((15,15),np.uint8)

e = cv2.erode(img,kernel,iterations = 2)
d = cv2.dilate(e,kernel,iterations = 1)
ret, th = cv2.threshold(d, 150, 255, cv2.THRESH_BINARY_INV)

mask = np.zeros((h+2, w+2), np.uint8)
cv2.floodFill(th, mask, (200,200), 255); # position = (200,200)
out = cv2.bitwise_not(th)
out= cv2.dilate(out,kernel,iterations = 3)
img, cnt, h = cv2.findContours(out,cv2.RETR_TREE,cv2.CHAIN_APPROX_SIMPLE)
for i in range(len(cnt)):
            # print("hi")
            area = cv2.contourArea(cnt[i])
            if(area>1000 and area<10000000):
                  mask = np.zeros_like(img)
                  cv2.drawContours(mask, cnt, i, 255, -1)
                  x,y,w,h = cv2.boundingRect(cnt[i])
                  crop= img[ y:h+y,x:w+x]
                  cv2.imshow("snip",img )
                  if(cv2.waitKey(0))==27:break

cv2.destroyAllWindows()