Question

I’m trying to use matplotlib to read in an RGB image and convert it to grayscale.

In matlab I use this:

img = rgb2gray(imread('image.png'));

In the matplotlib tutorial they don’t cover it. They just read in the image

import matplotlib.image as mpimg
img = mpimg.imread('image.png')

and then they slice the array, but that’s not the same thing as converting RGB to grayscale from what I understand.

lum_img = img[:,:,0]

I find it hard to believe that numpy or matplotlib doesn’t have a built-in function to convert from rgb to gray. Isn’t this a common operation in image processing?

I wrote a very simple function that works with the image imported using imread in 5 minutes. It’s horribly inefficient, but that’s why I was hoping for a professional implementation built-in.

Sebastian has improved my function, but I’m still hoping to find the built-in one.

matlab’s (NTSC/PAL) implementation:

import numpy as np

def rgb2gray(rgb):

    r, g, b = rgb[:,:,0], rgb[:,:,1], rgb[:,:,2]
    gray = 0.2989 * r + 0.5870 * g + 0.1140 * b

    return gray

Answer 1

How about doing it with Pillow:

from PIL import Image
img = Image.open('image.png').convert('L')
img.save('greyscale.png')

---

If an alpha (transparency) channel is present in the input image and should be preserved, use mode LA:

img = Image.open('image.png').convert('LA')

---

Using matplotlib and the formula

Y' = 0.2989 R + 0.5870 G + 0.1140 B 

you could do:

import numpy as np
import matplotlib.pyplot as plt
import matplotlib.image as mpimg

def rgb2gray(rgb):
    return np.dot(rgb[...,:3], [0.2989, 0.5870, 0.1140])

img = mpimg.imread('image.png')     
gray = rgb2gray(img)    
plt.imshow(gray, cmap=plt.get_cmap('gray'), vmin=0, vmax=1)
plt.show()