pimage.py

from os import path
from sys import argv
from PIL import Image
from PIL.Image import Resampling
from termcolor import colored
import functions as fun
import settings as sel


if fun.isNotebook():
    (fPath, fName) = (
        '/home/chipdelmal/Documents/Sync/LegoOptimizer/', 
        'marioTanooki.png'
    )
else:
    (fPath, fName) = (argv[1], argv[2])
###############################################################################
# Get user selections from file
###############################################################################
(SIZE, PALETTE) = (sel.USER_SEL['size'], sel.USER_SEL['palette'])
###############################################################################
# Load image
###############################################################################
pth = path.join(fPath, fName)
img = Image.open(pth).convert('RGB')
###############################################################################
# Quantize
#   0: median cut, 1: maximum coverage, 2: fast octree
###############################################################################
if isinstance(PALETTE, int):
    # Provided palette is a number of target quantization colors --------------
    imgQnt = fun.quantizeImage(img, int(PALETTE), method=0)
    print(colored(f'+ Quantizing image to {PALETTE} colors', 'red'))
elif isinstance(PALETTE, tuple) or isinstance(PALETTE, list):
    # Provided palette is a list or tuple of colors with no block qty ---------
    cpal = fun.paletteReshape(PALETTE)
    imgQnt = fun.quantizeImage(
        img, colorPalette=cpal[1], method=0
    )
    print(colored(f'+ Quantizing image to palette with no block QTY', 'red'))
elif isinstance(PALETTE, dict):
    # Provided palette is a dictionary of colors with block qty ---------------
    pal = tuple(PALETTE.keys())
    cpal = fun.paletteReshape(pal)
    imgQnt = fun.quantizeImage(
        img, colorPalette=cpal[1], method=0
    )
    print(colored(f'+ Quantizing image to palette with block QTY', 'red'))
else:
    print(colored("Error in the color palette!", "red"))
###############################################################################
# Downscale
#   NEAREST, BILINEAR, BICUBIC, LANCZOS, NEAREST
###############################################################################
pthDWN = path.join(fPath, fName.split('.png')[0]+'_DWN.png')
imgDwn = imgQnt.resize(SIZE, resample=Resampling.LANCZOS)
imgDwn.save(pthDWN)
imgDwn.close()