Crop black edges with OpenCV

Question

I think it should be a very simple problem, but I cannot find a solution or an effective keyword for search.

I just have this image.

The black edges are useless so that I want to cut them, only leaving the Windows icon (and the blue background).

I do not want to calculate the coordinate and the size of the Windows icon. GIMP and Photoshop have sort of autocrop function. OpenCV does not have one?

Answer 1

I am not sure whether all your images are like this. But for this image, below is a simple python-opencv code to crop it.

first import libraries :

import cv2 import numpy as np 

Read the image, convert it into grayscale, and make in binary image for threshold value of 1.

img = cv2.imread('sofwin.png') gray = cv2.cvtColor(img,cv2.COLOR_BGR2GRAY) _,thresh = cv2.threshold(gray,1,255,cv2.THRESH_BINARY) 

Now find contours in it. There will be only one object, so find bounding rectangle for it.

contours,hierarchy = cv2.findContours(thresh,cv2.RETR_EXTERNAL,cv2.CHAIN_APPROX_SIMPLE) cnt = contours[0] x,y,w,h = cv2.boundingRect(cnt) 

Now crop the image, and save it into another file.

crop = img[y:y+h,x:x+w] cv2.imwrite('sofwinres.png',crop) 

Below is the result :

Answer 2

import numpy as np  def autocrop(image, threshold=0):     """Crops any edges below or equal to threshold      Crops blank image to 1x1.      Returns cropped image.      """     if len(image.shape) == 3:         flatImage = np.max(image, 2)     else:         flatImage = image     assert len(flatImage.shape) == 2      rows = np.where(np.max(flatImage, 0) > threshold)[0]     if rows.size:         cols = np.where(np.max(flatImage, 1) > threshold)[0]         image = image[cols[0]: cols[-1] + 1, rows[0]: rows[-1] + 1]     else:         image = image[:1, :1]      return image