import numpy as np
import cv2
blank_image = np.zeros((40,40,3), np.uint8)
blank_image.fill(255)
#cv2.imshow(\'i\', blank_image)
#cv2.waitKey(0)
im = cv2.imread(\'
For contours image
I think want something like
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 .
Details and description are in the code.
#!/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)