Define a second version of the grayscale function, called grayscale2, that uses the allegedly crude method of simply averaging each RGB value to apply grayscale. Test the function by comparing its results with those of the other version discussed earlier.


So far my code is:
from images import Image


def grayscale1(image):
"""Converts an image to grayscale using the
psychologically accurate transformations."""
for y in range(image.getHeight()):
for x in range(image.getWidth()):
(r, g, b) = image.getPixel(x, y)
r = int(r * 0.299)
g = int(g * 0.587)
b = int(b * 0.114)
lum = r + g + b
image.setPixel(x, y, (lum, lum, lum))

def grayscale2(image):
"""Converts an image to grayscale using the crude average
of the r, g, and b"""
pass

def main():
filename = input("Enter the image file name: ")
image = Image(filename)
grayscale2(image)
image.draw()

if __name__ == "__main__":
main()

And its giving me 83% difference