#!/usr/bin/env python
'''
    image_example.py
    Jeff Ondich, 28 October 2015

    Using the Python Imaging Library (PIL, https://python-pillow.github.io/)
    to directly modify pixels.

    Over-commented for pedagogical purposes.
'''
import sys
import argparse
from PIL import Image

def main(args):
    # Open the original image's file as an Image object.
    try:
        image = Image.open(args.input_image)
        print >>sys.stderr, 'Original image:', image.format, image.size, image.mode
    except:
        print >>sys.stderr, 'Can\'t open image {0}'.format(args.image)
        exit()

    # Use the load() method to get direct access to the image's pixels.
    pixels = image.load()

    # Create a new image, the same size as the original. Initialize to black
    # and load() the pixels.
    new_image = Image.new('RGB', image.size, (0, 0, 0))
    new_pixels = new_image.load()

    # For each pixel in the original image, convert the RGB values to a gray value
    # and assign the corresponding pixel in the new image that value for R, G, and B.
    # Note that the RGB's range from 0 to 255, so their average does, too.
    for y in xrange(image.height):
        for x in xrange(image.width):
            red = pixels[x, y][0]
            green = pixels[x, y][1]
            blue = pixels[x, y][2]
            gray = (red + green + blue) / 3
            new_pixels[x, y] = (gray, gray, gray)

    # Save the final image to the output file.
    new_image.save(args.output_image)

    # Display both images on screen, if appropriate.
    if args.show:
        image.show()
        new_image.show()

if __name__ == '__main__':
    parser = argparse.ArgumentParser(description='Transforms a color image into a grayscale image.')
    parser.add_argument('input_image', help='The name of the image to carve')
    parser.add_argument('output_image', help='The name of the file in which to save the resulting image')
    parser.add_argument('--show', action='store_true', help='Displays both the original and the transformed image (in addition to saving the transformed image in the output_image file)')
    args = parser.parse_args()
    main(args)