bordercrop.py

import numpy as np
import cv2
import pickle
from shapely.geometry import Polygon
import matplotlib.pyplot as plt

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) ) )

img = cv2.imread('./test2.png')
img = cv2.GaussianBlur(img, (5, 5), 0)
height, width = img.shape[:2]
print(height * width)

squares = []
for gray in cv2.split(img):
    for thrs in range(240, 255, 26):
        _, threshold = cv2.threshold(gray, thrs, 255, cv2.THRESH_BINARY)

        contours, _ = cv2.findContours(
            threshold, cv2.RETR_TREE, 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 range(4)])
                if max_cos < 0.1:
                    squares.append(cnt)
                    print('area: ', cv2.contourArea(cnt), 'mean: ', cv2.minMaxLoc(cnt))
                    print()

cv2.drawContours(img, squares, -1, (0, 255, 0), 5)

plt.figure(figsize=(8, 8))
plt.imshow(img)
plt.show()