import cv2
import numpy as np
import matplotlib.pyplot as plt


def show_image(img):
    """Display an image in PyCharm."""
    img_rgb = cv2.cvtColor(img, cv2.COLOR_BGR2RGB)  # Convert BGR to RGB (if using OpenCV)
    plt.imshow(img_rgb)
    plt.axis("off")  # Hide axes
    plt.show()

def resize_and_pad(image, target_shape):
    h, w = image.shape[:2]
    target_h, target_w = target_shape

    scale = min(target_w / w, target_h / h)
    new_w, new_h = int(w * scale), int(h * scale)
    resized = cv2.resize(image, (new_w, new_h), interpolation=cv2.INTER_AREA)

    canvas = np.zeros((target_h, target_w, 3), dtype=np.uint8)
    top = (target_h - new_h) // 2
    left = (target_w - new_w) // 2
    canvas[top:top + new_h, left:left + new_w] = resized
    return canvas

def create_instance(img1: np.ndarray, img2: np.ndarray, output_shape) -> np.ndarray:

    img1_resized = resize_and_pad(img1, output_shape)
    img2_resized = resize_and_pad(img2, output_shape)

    output = np.dstack((img1_resized, img2_resized))

    return output


# Example

output_shape = (256, 128)

img1 = np.ones((127, 47, 3)) * 128
img2 = np.ones((180, 57, 3)) * 64

out = create_instance(img1, img2, output_shape)

#out has shape 256 x 128 x 6
print(np.shape(out))