img2asc.py

import argparse
from pathlib import Path

from PIL import Image, ImageDraw, ImageFont


def parse_args() -> argparse.Namespace:
    parser = argparse.ArgumentParser()
    parser.add_argument("-w", "--width", dest="width", type=int, default=80)
    parser.add_argument("-l", "--level", dest="level", type=int, default=16)
    parser.add_argument("-i", "--invert", dest="invert", action="store_true")
    parser.add_argument("filename")
    return parser.parse_args()


def create_char_map(*, level: int = 16, inv: bool = False) -> str:
    cmap: list[tuple[int | float, str]] = []
    filepath = Path(__file__).parent / "CascadiaMono.ttf"
    ft = ImageFont.truetype(filepath.as_posix(), size=12)
    canvas = Image.new("L", (20, 20), color=0)
    ctx = ImageDraw.Draw(canvas)
    for i in range(128):
        c = chr(i)
        if c.isprintable():
            ctx.rectangle((0, 0, 20, 20), 0)
            ctx.text((0, 0), c, font=ft, fill=255)
            val = sum(canvas.getdata())
            cmap.append((val, c))
    m, n = max(cmap)[0], min(cmap)[0]
    cmap = [((v - n) / (m - n) * 255, c) for v, c in cmap]
    result: list[str] = []
    for i in range(level):
        v = i / level * 255
        result.append(min(cmap, key=lambda x: abs(x[0] - v))[1])
    return "".join(result if inv else result[::-1])


def convert(
    img: Image.Image, width: int = 80, level: int = 16, invert: bool = False
) -> str:
    cmaps = create_char_map(level=level, inv=invert)
    W, H = width, int(width / img.width * img.height)
    im_res = img.convert("L").resize((W, H), resample=Image.Resampling.BOX)
    res: list[str] = []
    for y in range(im_res.height):
        line: list[str] = []
        for x in range(im_res.width):
            p = im_res.getpixel((x, y))
            line.append(cmaps[int(p / 256 * level)])
        res.append("".join(line))
    return "\n".join(res)


if __name__ == "__main__":
    args = parse_args()
    im = Image.open(args.filename)
    print(convert(im, args.width, args.level, args.invert))

PIL.Image.BOX will be changed to PIL.Image.Resampling.BOX