ahmet / Python-for-Data-Science

import numpy as np
import matplotlib.pyplot as plt
from load_image import ft_load


def ft_invert(array) -> np.ndarray:
    """Inverts the color of the image received."""
    inverted = array.copy()
    inverted[:, :, :] = 255 - inverted
    return inverted


def ft_red(array) -> np.ndarray:
    """Keeps only the red channel of the image received."""
    red = array.copy()
    red[:, :, 1] = red[:, :, 1] * 0
    red[:, :, 2] = red[:, :, 2] * 0
    return red


def ft_green(array) -> np.ndarray:
    """Keeps only the green channel of the image received."""
    green = array.copy()
    green[:, :, 0] = green[:, :, 0] - green[:, :, 0]
    green[:, :, 2] = green[:, :, 2] - green[:, :, 2]
    return green


def ft_blue(array) -> np.ndarray:
    """Keeps only the blue channel of the image received."""
    blue = array.copy()
    blue[:, :, 0] = 0
    blue[:, :, 1] = 0
    return blue


def ft_grey(array) -> np.ndarray:
    """Converts the image received to greyscale."""
    grey = array.copy()
    average = array.sum(axis=2) / 3
    grey[:, :, 0] = average
    grey[:, :, 1] = average
    grey[:, :, 2] = average
    return grey


def main() -> None:
    """Load landscape.jpg, apply every filter and display the results."""
    try:
        array = ft_load("../landscape.jpg")
        if array is None:
            return
        print(array)

        images = [
            ("Original", array),
            ("Invert", ft_invert(array)),
            ("Red", ft_red(array)),
            ("Green", ft_green(array)),
            ("Blue", ft_blue(array)),
            ("Grey", ft_grey(array)),
        ]
        figure, axes = plt.subplots(2, 3, figsize=(12, 6))
        for axis, (title, image) in zip(axes.flat, images):
            axis.imshow(image)
            axis.set_title(title)
            axis.axis("off")
        figure.tight_layout()
        plt.show()

        print(ft_invert.__doc__)
    except Exception as error:
        print(f"Error: {error}")


if __name__ == "__main__":
    main()