| """Read local or public-Hub WebDataset shards without extracting image files.""" |
| import argparse |
| import io |
| import json |
| import tarfile |
| from pathlib import Path |
| from urllib.request import urlopen |
| from PIL import Image |
|
|
| def samples(fileobj): |
| """Yield (PIL image, metadata, text) while retaining only one sample in RAM.""" |
| with tarfile.open(fileobj=fileobj, mode='r|*') as archive: |
| pending = {} |
| current = None |
| for member in archive: |
| key, extension = member.name.rsplit('.', 1) |
| if current is not None and key != current: |
| if set(pending) != {'png', 'json', 'txt'}: |
| raise ValueError('Incomplete WebDataset sample: ' + current) |
| metadata = json.loads(pending['json']) |
| with Image.open(io.BytesIO(pending['png'])) as im: |
| yield im.convert('RGB'), metadata, pending['txt'].decode() |
| pending = {} |
| current = key |
| if extension in pending: |
| raise ValueError('Repeated member: ' + member.name) |
| pending[extension] = archive.extractfile(member).read() |
| if pending: |
| if set(pending) != {'png', 'json', 'txt'}: |
| raise ValueError('Incomplete WebDataset sample: ' + current) |
| with Image.open(io.BytesIO(pending['png'])) as im: |
| yield im.convert('RGB'), json.loads(pending['json']), pending['txt'].decode() |
|
|
| if __name__ == '__main__': |
| p=argparse.ArgumentParser() |
| p.add_argument('shard',help='Local TAR path, https URL, or shard filename in --repo') |
| p.add_argument('--repo',default='laion/Anim-E-Ghibli-Backgrounds-FLUX-9B') |
| p.add_argument('--revision',default='main') |
| p.add_argument('--prefix',default='data',help='Repository shard directory, e.g. city-data or extension-data') |
| p.add_argument('--limit',type=int,default=5) |
| a=p.parse_args() |
| if Path(a.shard).is_file(): |
| source=open(a.shard,'rb') |
| else: |
| url=a.shard if a.shard.startswith('https://') else f'https://huggingface.co/datasets/{a.repo}/resolve/{a.revision}/{a.prefix}/{a.shard}' |
| source=urlopen(url,timeout=90) |
| with source: |
| for i,(image,metadata,text) in enumerate(samples(source)): |
| print(json.dumps(dict(id=metadata['id'],size=image.size,primary_class=metadata.get('primary_class'), |
| subcategory=metadata.get('subcategory'),personality_id=metadata.get('personality_id'), |
| emotion=metadata.get('emotion'),seed=metadata['seed'],prompt=text),ensure_ascii=False)) |
| if i+1>=a.limit: break |
|
|
