from pathlib import Path

import numpy as np
from PIL import Image
from skimage import exposure


def normalize_image(
    src: Path,
    dst: Path,
    target_size=(512, 512),
    png_low: int = 16,
    png_high: int = 238,
) -> None:
    """Convert JPEG to grayscale, resize, and match PNG intensity distribution."""
    img = Image.open(src).convert("L")
    img = img.resize(target_size, Image.Resampling.BICUBIC)

    arr = np.array(img, dtype=np.float32)
    arr = exposure.rescale_intensity(
        arr, in_range="image", out_range=(png_low, png_high)
    )
    arr = np.clip(arr, png_low, png_high)
    arr = ((arr - png_low) / (png_high - png_low) * 255.0).astype(np.uint8)

    dst.parent.mkdir(parents=True, exist_ok=True)
    Image.fromarray(arr, mode="L").save(dst)


if __name__ == "__main__":
    src = Path("/Users/fatemehtahavori/Downloads/atk1/K-1.jpg")
    dst = Path("normalized_outputs") / f"{src.stem}_normalized.png"

    normalize_image(src, dst)
    print(f"Saved normalized frame to {dst.resolve()}")