How to check whether a jpeg image is color or gray scale using only Python stdlib

Question

I have to write a test case in python to check whether a jpg image is in color or grayscale. Can anyone please let me know if there is any way to do it with out installing e

Answer 1

I faced a similar situation, where I tried the following approaches:

1. Reading using IMREAD_UNCHANGEDand checking for image.shape
2. Splitting B,G,R channels and checking if they are equal

Both of these approaches got me only like 53% accuracy in my dataset. I had to relax the condition for checking pixels in different channels and create a ratio to classify it as grey or color. With this approach, I was able to get 87.3% accuracy on my dataset.

Here is the logic which worked for me:

import cv2
import numpy as np

###test image
img=cv2.imread('test.jpg')

### splitting b,g,r channels
b,g,r=cv2.split(img)

### getting differences between (b,g), (r,g), (b,r) channel pixels
r_g=np.count_nonzero(abs(r-g))
r_b=np.count_nonzero(abs(r-b))
g_b=np.count_nonzero(abs(g-b))

### sum of differences
diff_sum=float(r_g+r_b+g_b)

### finding ratio of diff_sum with respect to size of image
ratio=diff_sum/img.size

if ratio>0.005:
    print("image is color")
else:
    print("image is greyscale")

Answer 2

Can be done as follow:

from scipy.misc import imread, imsave, imresize
image = imread(f_name)
if(len(image.shape)<3):
      print 'gray'
elif len(image.shape)==3:
      print 'Color(RGB)'
else:
      print 'others'

Answer 3

For faster processing, it is better to avoid loops on every pixel, using ImageChops, (but also to be sure that the image is truly grayscale, we need to compare colors on every pixel and cannot just use the sum):

from PIL import Image,ImageChops

def is_greyscale(im):
    """
    Check if image is monochrome (1 channel or 3 identical channels)
    """
    if im.mode not in ("L", "RGB"):
        raise ValueError("Unsuported image mode")

    if im.mode == "RGB":
        rgb = im.split()
        if ImageChops.difference(rgb[0],rgb[1]).getextrema()[1]!=0: 
            return False
        if ImageChops.difference(rgb[0],rgb[2]).getextrema()[1]!=0: 
            return False
    return True