File size: 5,662 Bytes
985fb0e | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 | 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()
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