cmelevator

cmelevator.py

import PIL.Image

import numpy as np


def remove_buildings(clean: np.ndarray, elevated: np.ndarray) -> np.ndarray:
    xorred = np.bitwise_xor(clean, elevated)

    output = xorred

    return output


def load_image(path: str) -> np.ndarray:
    image = PIL.Image.open(path).convert("RGB")

    array = np.array(image)

    mask = np.all(array == [255, 255, 255], axis=2)

    output = np.zeros_like(array)
    output[mask] = [255, 255, 255]

    return output


def load_font() -> list[np.ndarray]:
    # the image is 50x7
    font = load_image("./font.png")

    return [font[0:7, l:r] for l, r in zip(range(0, 46, 5), range(5, 51, 5))]


def match(tile: np.ndarray, font: list[np.ndarray]) -> int:
    # white_glyph = np.full((7, 5, 3), [255, 255, 255], np.uint8)

    glyph_shape = (7, 5, 3)

    for i in range(len(font)):
        glyph = font[i]

        compared = np.bitwise_and(
            glyph, tile[4 : 4 + glyph_shape[0], 5 : 5 + glyph_shape[1]]
        )

        match = np.all(compared == glyph)

        if match:
            return i

    ones = None
    tens = None

    for i in range(len(font)):
        glyph = font[i]

        l = np.bitwise_and(glyph, tile[4 : 4 + glyph_shape[0], 2 : 2 + glyph_shape[1]])
        r = np.bitwise_and(glyph, tile[4 : 4 + glyph_shape[0], 8 : 8 + glyph_shape[1]])

        l_match = np.all(l == glyph)
        r_match = np.all(r == glyph)

        if l_match:
            tens = i
        if r_match:
            ones = i

    if None not in [tens, ones]:
        value = int(f"{tens}{ones}")
        return value

    return 255


if __name__ == "__main__":
    clean = load_image("./tile-clean.png")
    elevated = load_image("./tile-elevation.png")

    font = load_font()

    tile_x = 16
    tile_y = 16
    m = load_image("./map-elevation.png")

    y_dim = m.shape[0] // tile_y
    x_dim = m.shape[1] // tile_x

    elevations = np.full(m.shape[:2], 255, np.uint8)

    for y in range(y_dim):
        for x in range(x_dim):
            y_start = y * tile_y
            y_stop = y_start + tile_y
            x_start = x * tile_x
            x_stop = x_start + tile_x

            tile = m[y_start:y_stop, x_start:x_stop]

            value = match(tile, font)

            elevations[y][x] = value

    lowest = np.min(elevations)

    cond_list = [elevations < 255]
    choice_list = [elevations]
    elevations = np.select(cond_list, choice_list, 0)

    highest = np.max(elevations)

    top = highest - lowest

    output = np.zeros(m.shape, np.uint8)

    for y in range(y_dim):
        for x in range(x_dim):
            y_start = y * tile_y
            y_stop = y_start + tile_y
            x_start = x * tile_x
            x_stop = x_start + tile_x

            value = elevations[y][x]

            if value > 0:
                color = [255 // top * value] * 3
            else:
                color = [0, 0, 0]

            output[y_start:y_stop, x_start:x_stop] = color

    print(lowest, highest, top)
    print(*output.shape)
    output = PIL.Image.fromarray(output, mode="RGB")
    output.save("./tile-no-buildings.png")