postprocess_wavelet_folder.py

import argparse
from pathlib import Path

from PIL import Image

from myutils.wavelet_color_fix import wavelet_color_fix


DEFAULT_EXTENSIONS = ".png,.jpg,.jpeg,.JPG,.JPEG"
BICUBIC = Image.Resampling.BICUBIC if hasattr(Image, "Resampling") else Image.BICUBIC


def parse_args():
    parser = argparse.ArgumentParser(
        description="Replace VARSR low frequencies with bicubic-upsampled LR low frequencies.",
        formatter_class=argparse.ArgumentDefaultsHelpFormatter,
    )
    parser.add_argument("--lr_dir", required=True, help="Folder containing the original LR images.")
    parser.add_argument("--varsr_dir", required=True, help="Folder containing existing VARSR HR images.")
    parser.add_argument("--output_dir", required=True, help="Folder for wavelet-corrected images.")
    parser.add_argument("--scale", type=int, default=4, help="Expected VARSR enlargement factor.")
    parser.add_argument(
        "--high_freq_weight",
        type=float,
        default=1.0,
        help="Weight of VARSR high frequencies in the corrected image.",
    )
    parser.add_argument("--levels", type=int, default=5, help="Number of wavelet decomposition levels.")
    parser.add_argument("--extensions", default=DEFAULT_EXTENSIONS, help="Comma-separated image extensions.")
    parser.add_argument("--save_ext", default=".png", help="Output extension; empty keeps the VARSR suffix.")
    parser.add_argument("--limit", type=int, default=0, help="Only process the first N images when greater than 0.")
    parser.add_argument("--overwrite", action="store_true", help="Overwrite existing corrected images.")
    args = parser.parse_args()

    if args.scale <= 0:
        parser.error("--scale must be positive")
    if args.high_freq_weight < 0:
        parser.error("--high_freq_weight must be non-negative")
    if args.levels <= 0:
        parser.error("--levels must be positive")
    return args


def normalize_extensions(raw_extensions):
    extensions = set()
    for raw_extension in raw_extensions.split(","):
        extension = raw_extension.strip().lower()
        if extension:
            extensions.add(extension if extension.startswith(".") else f".{extension}")
    return extensions


def iter_images(root, extensions):
    return sorted(
        path
        for path in root.rglob("*")
        if path.is_file() and path.suffix.lower() in extensions
    )


def relative_stem(path, root):
    return path.relative_to(root).with_suffix("").as_posix().lower()


def index_images(root, extensions):
    image_index = {}
    for image_path in iter_images(root, extensions):
        key = relative_stem(image_path, root)
        if key in image_index:
            raise RuntimeError(f"Duplicate relative image stem in {root}: {key}")
        image_index[key] = image_path
    return image_index


def main():
    args = parse_args()
    lr_dir = Path(args.lr_dir)
    varsr_dir = Path(args.varsr_dir)
    output_dir = Path(args.output_dir)
    extensions = normalize_extensions(args.extensions)

    if not lr_dir.is_dir():
        raise FileNotFoundError(f"LR directory does not exist: {lr_dir}")
    if not varsr_dir.is_dir():
        raise FileNotFoundError(f"VARSR directory does not exist: {varsr_dir}")

    lr_images = index_images(lr_dir, extensions)
    varsr_images = iter_images(varsr_dir, extensions)
    if args.limit > 0:
        varsr_images = varsr_images[: args.limit]
    if not varsr_images:
        raise RuntimeError(f"No VARSR images found in {varsr_dir}")

    print(f"Found {len(varsr_images)} VARSR image(s). Writing to {output_dir}")
    print(
        f"Wavelet settings: scale={args.scale}, levels={args.levels}, "
        f"high_freq_weight={args.high_freq_weight}"
    )

    processed = 0
    for index, varsr_path in enumerate(varsr_images, 1):
        key = relative_stem(varsr_path, varsr_dir)
        lr_path = lr_images.get(key)
        if lr_path is None:
            raise FileNotFoundError(f"No LR image matching relative stem '{key}' in {lr_dir}")

        relative_path = varsr_path.relative_to(varsr_dir)
        suffix = args.save_ext if args.save_ext else relative_path.suffix
        if suffix and not suffix.startswith("."):
            suffix = f".{suffix}"
        output_path = (output_dir / relative_path).with_suffix(suffix)
        if output_path.exists() and not args.overwrite:
            print(f"[{index}/{len(varsr_images)}] skip existing {output_path}")
            continue

        with Image.open(lr_path) as lr_source, Image.open(varsr_path) as varsr_source:
            lr_image = lr_source.convert("RGB")
            varsr_image = varsr_source.convert("RGB")

        expected_size = (lr_image.width * args.scale, lr_image.height * args.scale)
        if varsr_image.size != expected_size:
            raise ValueError(
                f"Size mismatch for {varsr_path}: got {varsr_image.size}, expected {expected_size} "
                f"from LR image {lr_path} and scale {args.scale}"
            )

        lr_reference = lr_image.resize(varsr_image.size, BICUBIC)
        corrected = wavelet_color_fix(
            varsr_image,
            lr_reference,
            levels=args.levels,
            high_freq_weight=args.high_freq_weight,
        )
        output_path.parent.mkdir(parents=True, exist_ok=True)
        save_kwargs = {"quality": 95} if output_path.suffix.lower() in {".jpg", ".jpeg"} else {}
        corrected.save(output_path, **save_kwargs)
        processed += 1
        print(f"[{index}/{len(varsr_images)}] {varsr_path} -> {output_path}")

    print(f"Completed: processed={processed}, total={len(varsr_images)}")


if __name__ == "__main__":
    main()