44 lines
1.4 KiB
Python
44 lines
1.4 KiB
Python
import cv2
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import numpy as np
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def angle_cos(p0, p1, p2):
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d1, d2 = (p0-p1).astype('float'), (p2-p1).astype('float')
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return abs( np.dot(d1, d2) / np.sqrt( np.dot(d1, d1)*np.dot(d2, d2) ) )
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def find_squares(img):
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squares = []
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gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
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# cv2.imshow("gray", gray)
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gaussian = cv2.GaussianBlur(gray, (5, 5), 0)
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thresh = cv2.adaptiveThreshold(gaussian, 255, 1, 1, 11, 2)
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#temp,bin = cv2.threshold(gaussian, 80, 255, cv2.THRESH_BINARY)
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cv2.imshow("thresh", thresh)
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contours, hierarchy = cv2.findContours(thresh, cv2.RETR_TREE, cv2.CHAIN_APPROX_SIMPLE)
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cv2.drawContours( gray, contours, -1, (0, 255, 0), 3 )
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#cv2.imshow('contours', gray)
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for cnt in contours:
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cnt_len = cv2.arcLength(cnt, True)
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cnt = cv2.approxPolyDP(cnt, 0.02*cnt_len, True)
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if cv2.contourArea(cnt) > 1000 :
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#cnt = cnt.reshape(-1, 2)
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#max_cos = np.max([angle_cos( cnt[i], cnt[(i+1) % 4], cnt[(i+2) % 4] ) for i in range(4)])
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#if max_cos < 0.1:
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squares.append(cnt)
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return squares
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if __name__ == '__main__':
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img = cv2.imread('equip/main_screen.jpg')
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#cv2.imshow("origin", img)
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squares = find_squares(img)
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print("Find %d squres" % len(squares))
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cv2.drawContours( img, squares, -1, (0, 255, 0), 3 )
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cv2.imshow('squares', img)
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cv2.waitKey() |