dithering.py

from PIL import Image
import numpy as np
import sys

image = Image.open(sys.argv[1])
image_data = np.asarray(image)

for i in range(image_data.shape[0]):
	for j in range(image_data.shape[1]):
		oldpixel = image_data[i][j]
		newpixel = find_closest_palette_color(oldpixel[:3])
		image_data[i][j][:3] = newpixel
		
		if oldpixel.shape[0] < 4 or oldpixel[3] > 0:
			quant_error = oldpixel[:3] - newpixel
			quant_error = quant_error/16
			j_not_out_of_bounds = (j < image_data.shape[1] -1)
			if i < image_data.shape[0] -1:
				image_data[i + 1][j    ][:3] = image_data[i + 1][j    ][:3] + quant_error * 5 
				if j > 0:
					image_data[i + 1][j - 1][:3] = image_data[i + 1][j - 1][:3] + quant_error * 3 
				if j_not_out_of_bounds:
					image_data[i + 1][j + 1][:3] = image_data[i + 1][j + 1][:3] + quant_error 
			if j_not_out_of_bounds:
				image_data[i    ][j + 1][:3] = image_data[i    ][j + 1][:3] + quant_error * 7 
				
#taking only 3 values and leaving fourth the same so this works for RGBA images like .png

old_image = np.asarray(image)
output_image = Image.fromarray(image_data)
output_image.save(sys.argv[2])