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There is no (built-in) PathLike. Various applications and libraries roll their own with a Union. If we were to abide by the protocol of the inner open() call, then a union of a Path and a str is incorrect, because it can also take a file-like:

But I consider all of that to be a bit much for this application, and would constrain it to Path for simplicity and clarity.

from pathlib import Path

import PIL.Image
import numpy as np


CHARSET = (
    "@$B%8&WM#*oahkbdpqwm"
    "ZO0QLCJUYXzcvunxrjft"
    "/\|()1{}[]?-_+~<>i!l"
    "I;:,\"^`'. "
)


def resize(image: PIL.Image.Image, new_width: int = 300) -> PIL.Image.Image:
    width, height = image.size
    new_height = new_width * height / width / 2.5
    return image.resize((round(new_width), round(new_height)))


def pixel_to_ascii(pixels: np.ndarray, light_mode: bool = True) -> str:
    direction = 1 if light_mode else -1
    charset_str = CHARSET[::direction]
    charset = np.array(tuple(charset_str), dtype='U1')

    minp = pixels.min()
    maxp = pixels.max()
    scaled = (pixels - minp) / (maxp - minp) * (len(CHARSET) - 1)
    indices = np.around(scaled).astype(int)

    ascii_array = charset[indices]
    rows = ascii_array.view(f'U{pixels.shape[1]}')[:, 0]
    return '\n'.join(rows)


def convert(path: Path) -> str:
    greyscale_image = resize(PIL.Image.open(path).convert('F'))
    return pixel_to_ascii(np.array(greyscale_image))


def main() -> None:
    ascii_img = convert(Path('archived/image2l.png'))
    print(ascii_img)


if __name__ == '__main__':
    main()

You can use os.PathLike. However, if we were to abide by the protocol of the inner open() call, then a PathLike is incorrect, because it can also take a file-like:

But I consider all of that to be a bit much for this application, and would constrain it to PathLike for simplicity and clarity.

from os import PathLike
from pathlib import Path

import PIL.Image
import numpy as np


CHARSET = (
    "@$B%8&WM#*oahkbdpqwm"
    "ZO0QLCJUYXzcvunxrjft"
    "/\|()1{}[]?-_+~<>i!l"
    "I;:,\"^`'. "
)


def resize(image: PIL.Image.Image, new_width: int = 300) -> PIL.Image.Image:
    width, height = image.size
    new_height = new_width * height / width / 2.5
    return image.resize((round(new_width), round(new_height)))


def pixel_to_ascii(pixels: np.ndarray, light_mode: bool = True) -> str:
    direction = 1 if light_mode else -1
    charset_str = CHARSET[::direction]
    charset = np.array(tuple(charset_str), dtype='U1')

    minp = pixels.min()
    maxp = pixels.max()
    scaled = (pixels - minp) / (maxp - minp) * (len(CHARSET) - 1)
    indices = np.around(scaled).astype(int)

    ascii_array = charset[indices]
    rows = ascii_array.view(f'U{pixels.shape[1]}')[:, 0]
    return '\n'.join(rows)


def convert(path: PathLike) -> str:
    greyscale_image = resize(PIL.Image.open(path).convert('F'))
    return pixel_to_ascii(np.array(greyscale_image))


def main() -> None:
    ascii_img = convert('archived/image2l.png')
    print(ascii_img)


if __name__ == '__main__':
    main()

I don't think you need to bisect. You can simply load the image in 'F' mode (32-bit floating-point), scale to your min and max, round to the nearest index and then index into your charset:

from pathlib import Path

import PIL.Image
import numpy as np


CHARSET = (
    "@$B%8&WM#*oahkbdpqwm"
    "ZO0QLCJUYXzcvunxrjft"
    "/\|()1{}[]?-_+~<>i!l"
    "I;:,\"^`'. "
)


def resize(image: PIL.Image.Image, new_width: int = 300) -> PIL.Image.Image:
    width, height = image.size
    new_height = new_width * height / width / 2.5
    return image.resize((round(new_width), round(new_height)))


def pixel_to_ascii(pixels: np.ndarray, light_mode: bool = True) -> str:
    direction = 1 if light_mode else -1
    charset = CHARSET[::direction]
    minp = pixels.min()
    maxp = pixels.max()
    scaled = (pixels - minp) / (maxp - minp) * (len(CHARSET) - 1)
    indices = np.around(scaled)
    ascii_str = '\n'.join(
        ''.join(charset[int(i)] for i in row)
        for row in indices
    )
    return ascii_str


def convert(path: Path) -> str:
    greyscale_image = resize(PIL.Image.open(path).convert('F'))
    return pixel_to_ascii(np.array(greyscale_image))


def main() -> None:
    ascii_img = convert(Path('archived/image2l.png'))
    print(ascii_img)


if __name__ == '__main__':
    main()

I don't think you need to bisect. You can simply load the image in 'F' mode (32-bit floating-point), scale to your min and max, round to the nearest index and then index into your charset. You can take the opportunity to improve Numpy vectorisation and eliminate your loops.

from pathlib import Path

import PIL.Image
import numpy as np


CHARSET = (
    "@$B%8&WM#*oahkbdpqwm"
    "ZO0QLCJUYXzcvunxrjft"
    "/\|()1{}[]?-_+~<>i!l"
    "I;:,\"^`'. "
)


def resize(image: PIL.Image.Image, new_width: int = 300) -> PIL.Image.Image:
    width, height = image.size
    new_height = new_width * height / width / 2.5
    return image.resize((round(new_width), round(new_height)))


def pixel_to_ascii(pixels: np.ndarray, light_mode: bool = True) -> str:
    direction = 1 if light_mode else -1
    charset_str = CHARSET[::direction]
    charset = np.array(tuple(charset_str), dtype='U1')

    minp = pixels.min()
    maxp = pixels.max()
    scaled = (pixels - minp) / (maxp - minp) * (len(CHARSET) - 1)
    indices = np.around(scaled).astype(int)

    ascii_array = charset[indices]
    rows = ascii_array.view(f'U{pixels.shape[1]}')[:, 0]
    return '\n'.join(rows)


def convert(path: Path) -> str:
    greyscale_image = resize(PIL.Image.open(path).convert('F'))
    return pixel_to_ascii(np.array(greyscale_image))


def main() -> None:
    ascii_img = convert(Path('archived/image2l.png'))
    print(ascii_img)


if __name__ == '__main__':
    main()

Simplified algorithm

I don't think you need to bisect. You can simply load the image in 'F' mode (32-bit floating-point), scale to your min and max, round to the nearest index and then index into your charset:

from pathlib import Path

import PIL.Image
import numpy as np


CHARSET = (
    "@$B%8&WM#*oahkbdpqwm"
    "ZO0QLCJUYXzcvunxrjft"
    "/\|()1{}[]?-_+~<>i!l"
    "I;:,\"^`'. "
)


def resize(image: PIL.Image.Image, new_width: int = 300) -> PIL.Image.Image:
    width, height = image.size
    new_height = new_width * height / width / 2.5
    return image.resize((round(new_width), round(new_height)))


def pixel_to_ascii(pixels: np.ndarray, light_mode: bool = True) -> str:
    direction = 1 if light_mode else -1
    charset = CHARSET[::direction]
    minp = pixels.min()
    maxp = pixels.max()
    scaled = (pixels - minp) / (maxp - minp) * (len(CHARSET) - 1)
    indices = np.around(scaled)
    ascii_str = '\n'.join(
        ''.join(charset[int(i)] for i in row)
        for row in indices
    )
    return ascii_str


def convert(path: Path) -> str:
    greyscale_image = resize(PIL.Image.open(path).convert('F'))
    return pixel_to_ascii(np.array(greyscale_image))


def main() -> None:
    ascii_img = convert(Path('archived/image2l.png'))
    print(ascii_img)


if __name__ == '__main__':
    main()