您可以做的是围绕两个黑色数字创建边界矩形,然后从最左侧的矩形进行迭代,并将该矩形中的所有轮廓发送到您的CNN。如果你把这个作为一个例子,从顶部去下,你将有两个独立的矩形:
该链接的示例代码:
contours, hier = cv2.findContours(gray,cv2.RETR_LIST,cv2.CHAIN_APPROX_SIMPLE)
for cnt in contours:
if 200<cv2.contourArea(cnt)<5000:
cv2.drawContours(img,[cnt],0,(0,255,0),2)
cv2.drawContours(mask,[cnt],0,255,-1)
然后,当您具有一组轮廓时,可以按顺序对它们进行排序:
import numpy as np
c = np.load(r"rect.npy")
contours = list(c)
# Example - contours = [(287, 117, 13, 46), (102, 117, 34, 47), (513, 116, 36, 49), (454, 116, 32, 49), (395, 116, 28, 48), (334, 116, 31, 49), (168, 116, 26, 49), (43, 116, 30, 48), (224, 115, 33, 50), (211, 33, 34, 47), ( 45, 33, 13, 46), (514, 32, 32, 49), (455, 32, 31, 49), (396, 32, 29, 48), (275, 32, 28, 48), (156, 32, 26, 49), (91, 32, 30, 48), (333, 31, 33, 50)]
max_width = np.sum(c[::, (0, 2)], axis=1).max()
max_height = np.max(c[::, 3])
nearest = max_height * 1.4
contours.sort(key=lambda r: (int(nearest * round(float(r[1])/nearest)) * max_width + r[0]))
for x, y, w, h in contours:
print "{:4} {:4} {:4} {:4}".format(x, y, w, h)
取自-这里
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