对于轮廓图像

我认为想要类似

对于打开的数字，例如1，2，5，很容易做到:从整个图像中裁剪，或绘制新图像.对于0，6，8，9之类的闭合数字，需要执行更多步骤.这是5的示例，您将获得.

For opened number such as 1, 2, 5 , it is easy to do: Crop from the whole image, or draw on new image. For closed number such as 0, 6, 8, 9, more steps are needed. Here is example for 5, you will get .

详细信息和描述在代码中.

#!/usr/bin/python3
# 2018.01.14 09:48:15 CST
# 2018.01.14 11:39:03 CST

import numpy as np
import cv2

im = cv2.imread('test.png')
imgray = cv2.cvtColor(im, cv2.COLOR_BGR2GRAY)
ret, thresh = cv2.threshold(imgray, 127, 255, 0)
contours = cv2.findContours(thresh, cv2.RETR_TREE, cv2.CHAIN_APPROX_SIMPLE)[-2]


## this contour is a 3D numpy array
cnt = contours[4]
res = cv2.drawContours(im,[cnt],0,(255,0,0), -1)
cv2.imwrite("contours.png", res)

## Method 1: crop the region
x,y,w,h = cv2.boundingRect(cnt)
croped = res[y:y+h, x:x+w]
cv2.imwrite("croped.png", croped)

## Method 2: draw on blank
# get the 0-indexed coords
offset = cnt.min(axis=0)
cnt = cnt - cnt.min(axis=0)
max_xy = cnt.max(axis=0) + 1
w,h = max_xy[0][0], max_xy[0][1]
# draw on blank
canvas = np.ones((h,w,3), np.uint8)*255
cv2.drawContours(canvas, [cnt], -1, (255,0,0), -1)
cv2.imwrite("canvas.png", canvas)