File size: 2,360 Bytes
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Prepare dataset for Flux fine-tuning.
Combines images + captions into WebDataset format (tar shards).
"""
import json
import io
import argparse
from pathlib import Path
import webdataset as wds
from PIL import Image
from tqdm import tqdm
IMAGE_DIR = Path("/home/adminuser/chungcat/data/raw/unsplash")
CAPTION_DIR = Path("/home/adminuser/chungcat/data/captions")
OUTPUT_DIR = Path("/home/adminuser/chungcat/data/processed/flux_train")
def create_webdataset(image_dir, caption_dir, output_dir, shard_size=1000):
output_dir.mkdir(parents=True, exist_ok=True)
pattern = str(output_dir / "shard-%06d.tar")
captions = list(caption_dir.glob("*.json"))
print(f"Found {len(captions)} captions")
with wds.ShardWriter(pattern, maxcount=shard_size) as sink:
written = 0
for cap_path in tqdm(captions):
meta = json.loads(cap_path.read_text())
stem = cap_path.stem
img_path = image_dir / f"{stem}.jpg"
if not img_path.exists():
img_path = image_dir / f"{stem}.png"
if not img_path.exists():
continue
try:
img = Image.open(img_path).convert("RGB")
img = img.resize((1024, 1024), Image.LANCZOS)
img_bytes = io.BytesIO()
img.save(img_bytes, format="JPEG", quality=95)
img_bytes = img_bytes.getvalue()
sample = {
"__key__": stem,
"jpg": img_bytes,
"txt": meta["caption"],
"json": json.dumps(meta).encode(),
}
sink.write(sample)
written += 1
except Exception as e:
print(f"Error {stem}: {e}")
print(f"Done! Written {written} samples to {output_dir}")
if __name__ == "__main__":
parser = argparse.ArgumentParser(description="Prepare WebDataset for Flux training")
parser.add_argument("--image-dir", type=Path, default=IMAGE_DIR)
parser.add_argument("--caption-dir", type=Path, default=CAPTION_DIR)
parser.add_argument("--output-dir", type=Path, default=OUTPUT_DIR)
parser.add_argument("--shard-size", type=int, default=1000)
args = parser.parse_args()
create_webdataset(args.image_dir, args.caption_dir, args.output_dir, args.shard_size)
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