Resize an image to a target width and height, while keeping the original height-width ratio. If the original height-width ratio is different from the target height-width ratio, fill the rest of the area with white pixels.

resize-white-fill.py

import argparse
from pathlib import Path

import cv2
import numpy.typing as npt


def resize_white_fill(img: npt.NDArray, w_target: int, h_target: int) -> npt.NDArray:
    """Resize an image to a target width and height, while keeping the original
    height-width ratio. If the original height-width ratio is different from
    the target height-width ratio, fill the rest of the area with white pixels.

    Args:
        img (npt.NDArray): _Input image_
        w_target (int): _The desired width of the output image_
        h_target (int): _The desired height of the output image_

    Returns:
        npt.NDArray: _The resized image with white pixels filling the rest of the area_
    """

    # Get the height-width ratio ("h-w ratio" for short) of the input image
    h, w = img.shape[:2]
    r = h / w

    # If the input image has the identical h-w ratio as desired, simply
    # resize this image as the given height and width, without further operations.
    if r == h_target / w_target:
        return cv2.resize(img, (w_target, h_target))

    # Below are the additional operations in case the input image has a different
    # h-w ratio as desired.

    elif int(w_target * r) < h_target:
        # Suppose we resize the image so that it has the same width as the desired
        # width, then we compare the new height with the desired height. If its
        # height is smaller to the desired height.
        w_new = w_target
        h_new = int(w_new * r)
        resized = cv2.resize(img, (w_new, h_new), interpolation=cv2.INTER_AREA)

        # Fill the rest of the area along the height with white pixels
        pad_height_top = int((h_target - h_new) / 2)
        pad_height_bottom = h_target - h_new - pad_height_top
        return cv2.copyMakeBorder(
            resized,
            top=pad_height_top,
            bottom=pad_height_bottom,
            left=0,
            right=0,
            borderType=cv2.BORDER_CONSTANT,
            value=(255, 255, 255)
        )

    else:
        # If the new height exceeds the desired height, we resize the image so that
        # its height fit into the desired height instead.
        h_new = h_target
        w_new = int(h_new / r)
        resized = cv2.resize(img, (w_new, h_new), interpolation=cv2.INTER_AREA)

        # Fill the rest of the area along the width with white pixels
        pad_width_left = int((w_target - w_new) / 2)
        pad_width_right = w_target - w_new - pad_width_left
        return cv2.copyMakeBorder(
            resized,
            top=0,
            bottom=0,
            left=pad_width_left,
            right=pad_width_right,
            borderType=cv2.BORDER_CONSTANT,
            value=(255, 255, 255)
        )


if __name__ == "__main__":
    parser = argparse.ArgumentParser(description="Resize images to a target width\n"
                                     "and height with white fill.")
    parser.add_argument("--input", "-i", type=str,
                        help="Path to the input image.")
    parser.add_argument("--output", "-o", type=str,
                        help="Path to the output image.")
    parser.add_argument("--width", "-wt", type=int,
                        help="The desired width of the output image.")
    parser.add_argument("--height", "-ht", type=int,
                        help="The desired height of the output image.")
    args = parser.parse_args()

    # Read the input image
    img = cv2.imread(str(Path(args.input).resolve()))

    # Resize the image
    resized_img = resize_white_fill(img, args.width, args.height)

    # Save the resized image
    cv2.imwrite(str(Path(args.output).resolve()), resized_img)