Resize rectangular image to square, keeping ratio and fill background with black

Question

I'm trying to resize a batch of grayscale images that are 256 x N pixels (N varies, but is always ≤256).

My intention is to downscale the images.

The resize would have to output a square (1:1) image, with:

• resized image centered vertically
• aspect ratio maintained
• remaining pixels rendered black

Visually this would be the desired result:

I have tried creating a numpy zeroes matrix with the target size (e.g. 200 x 200) but have not been able to paste the resized image into its vertical center.

Any suggestions using cv2, PIL or numpy are welcome.

Answer 1

You can use Pillow to accomplish that:

Code:

from PIL import Image  def make_square(im, min_size=256, fill_color=(0, 0, 0, 0)):     x, y = im.size     size = max(min_size, x, y)     new_im = Image.new('RGBA', (size, size), fill_color)     new_im.paste(im, (int((size - x) / 2), int((size - y) / 2)))     return new_im 

Test Code:

test_image = Image.open('hLarp.png') new_image = make_square(test_image) new_image.show() 

For a white background you can do:

new_image = make_square(test_image, fill_color=(255, 255, 255, 0)) 

Result:

Answer 2

Here is a code that solve your question with OPENCV module (using NUMPY module too)

#Importing modules opencv + numpy import cv2 import numpy as np  #Reading an image (you can use PNG or JPG) img = cv2.imread("image.png")  #Getting the bigger side of the image s = max(img.shape[0:2])  #Creating a dark square with NUMPY   f = np.zeros((s,s,3),np.uint8)  #Getting the centering position ax,ay = (s - img.shape[1])//2,(s - img.shape[0])//2  #Pasting the 'image' in a centering position f[ay:img.shape[0]+ay,ax:ax+img.shape[1]] = img  #Showing results (just in case)  cv2.imshow("IMG",f) #A pause, waiting for any press in keyboard cv2.waitKey(0)  #Saving the image cv2.imwrite("img2square.png",f) cv2.destroyAllWindows()