import numpy as np
import cv2

from PIL import Image


def HWC3(x):
    assert x.dtype == np.uint8
    if x.ndim == 2:
        x = x[:, :, None]
    assert x.ndim == 3
    H, W, C = x.shape
    assert C == 1 or C == 3 or C == 4
    if C == 3:
        return x
    if C == 1:
        return np.concatenate([x, x, x], axis=2)
    if C == 4:
        color = x[:, :, 0:3].astype(np.float32)
        alpha = x[:, :, 3:4].astype(np.float32) / 255.0 # normalization
        y = color * alpha + 255.0 * (1.0 - alpha)
        y = y.clip(0, 255).astype(np.uint8)
        return y


def resize_image(input_image, resolution):
    H, W, C = input_image.shape
    H = float(H)
    W = float(W)
    k = float(resolution) / min(H, W)
    H *= k
    W *= k
    H = int(np.round(H / 64.0)) * 64
    W = int(np.round(W / 64.0)) * 64
    img = cv2.resize(input_image, (W, H), interpolation=cv2.INTER_LANCZOS4 if k > 1 else cv2.INTER_AREA)
    return img

# if __name__ == "__main__":
#     image_path = "/data/lh/docker/project/HieraFashDiff/3.jpeg"
#     input_image = Image.open(image_path).convert("RGB")
#     input_image = np.array(input_image)  # Convert PIL Image to NumPy array
#     input_image = HWC3(input_image)

#     img = resize_image(input_image, 512)
#     H, W, C = img.shape
#     filename = "result.jpg"
#     Image.fromarray(img).save(filename)