amogusDither.py

##CC0 Kaelygon 2025
import math
import numpy as np
from PIL import Image
from dataclasses import dataclass, field

class ImgConverter:
    #amogus matrix
    amogus = np.array([
        [0,1,1,1,0],
        [1,1,0,0,0],
        [1,1,1,1,0],
        [0,1,0,1,0],
        [0,0,0,0,0],
    ])
    amogus = (amogus/(np.max(amogus)+1))**2.0 #gamma correct
    dither_width = 1.0
    amogus*=dither_width

    pixels = None #Don't mutate this after init
    pixels_output = None #copy of pixels that can be modified
    size = None

    def __init__(self, input_path):
        self.imgToOkPixels(input_path)

    #private
    def _limitDepth(self, colors: np.ndarray, color_depth: np.array):
        return np.round(colors*color_depth)/color_depth

    #public
    def imgToOkPixels(self, img_path: str):
        in_img = Image.open(img_path).convert("RGBA")
        rgba = np.array(in_img, dtype=np.float64) / 255.0
        self.pixels = rgba.reshape(-1, 4)
        self.pixels_output = self.pixels
        self.size = in_img.size

    def saveImage(self, output_path: str, color_depth: np.array):
        rgba = self.pixels_output
        rgba = self._limitDepth(rgba, color_depth)
        rgba = np.clip(np.round(rgba * 255), 0, 255).astype(np.uint8)
        rgba = rgba.reshape((self.size[1], self.size[0], 4))
        img = Image.fromarray(rgba, "RGBA")
        img.save(output_path)

    def ditherAmogus(self, color_depth: [float]*3):
        #palettize
        color_depth_rgb = color_depth[:3]
        pixels = self.pixels_output[...,:3].copy()

        y_idxs, x_idxs = np.divmod(np.arange(len(pixels)), self.size[0])
        m_h, m_w = self.amogus.shape
        thresholds = self.amogus[y_idxs % m_h, x_idxs % m_w]
        pixel_gaps=1.0/np.array(color_depth_rgb)

        #apply mask
        new_cols = pixels + thresholds[:,None] * pixel_gaps
        new_cols = self._limitDepth(new_cols, color_depth_rgb)

        alpha = self.pixels_output[..., 3].copy()
        self.pixels_output = np.concatenate([new_cols, alpha[:, None]], axis=1)


@dataclass
class ConvertPreset:
    image: str #file names
    output: str
    color_depth: np.array #number of axis steps [R,G,B,A]

def palettizeImage(preset: ConvertPreset):
    image_ok = ImgConverter(preset.image)
    image_ok.ditherAmogus(preset.color_depth)
    image_ok.saveImage(preset.output, preset.color_depth)


if __name__ == '__main__':

    preset_list = [
        ConvertPreset(
            image           = "./testImg/KaelygonSeawing.png",
            output      = "./output/palettizedImg.png",
            color_depth = [6,6,7,8] #r,g,b,a
        )
    ]

    palettizeImage( preset_list[0]  )