Datasets:
Download tools/load_sample.py from diffusion-gif/trick-prediction-simulation-data: direct link, hf CLI and curl.
- Browser
- Download file 1.97 kB
-
https://huggingface.co/datasets/diffusion-gif/trick-prediction-simulation-data/resolve/main/tools/load_sample.py
- Command line
-
hf download hf://datasets/diffusion-gif/trick-prediction-simulation-data/tools/load_sample.py
-
curl -L -o load_sample.py https://huggingface.co/datasets/diffusion-gif/trick-prediction-simulation-data/resolve/main/tools/load_sample.py
1.97 kB
| #!/usr/bin/env python3 | |
| """Load one public eight-frame simulation observation, without model/GPU usage.""" | |
| import argparse,hashlib,io,json,tarfile | |
| from pathlib import Path | |
| import numpy as np | |
| from PIL import Image | |
| from schema import validate | |
| def load(root,row): | |
| validate(row);root=Path(root) | |
| with tarfile.open(root/row['media_archive'],'r:') as archive: | |
| member=archive.getmember(row['media_member']) | |
| if not member.isfile() or member.name!=row['media_member']:raise ValueError('Unsafe tar member') | |
| data=archive.extractfile(member).read() | |
| if hashlib.sha256(data).hexdigest()!=row['media_sha256']:raise ValueError('Media SHA256 mismatch') | |
| with np.load(io.BytesIO(data),allow_pickle=False) as arrays: | |
| if set(arrays.files)!={f'f{i}' for i in range(8)}:raise ValueError('Unknown NPZ fields') | |
| frames=[] | |
| for i in range(8): | |
| a=arrays[f'f{i}'] | |
| if a.dtype!=np.uint8 or a.ndim!=1:raise ValueError('Unexpected encoded frame') | |
| im=Image.open(io.BytesIO(a.tobytes()));im.load() | |
| if list(reversed(im.size))!=row['hw']:raise ValueError('Frame dimensions differ') | |
| frames.append(im.convert('RGB')) | |
| return frames,row | |
| def main(): | |
| p=argparse.ArgumentParser(description=__doc__);p.add_argument('--root',type=Path,default=Path(__file__).resolve().parents[1]);p.add_argument('--split',choices=('train','heldout'),default='train');p.add_argument('--index',type=int,default=0);p.add_argument('--gif',type=Path);a=p.parse_args() | |
| with (a.root/'data'/(a.split+'.jsonl')).open() as f: | |
| row=next(json.loads(line) for n,line in enumerate(f) if n==a.index) | |
| frames,row=load(a.root,row) | |
| if a.gif: | |
| if a.gif.exists():raise ValueError('Will not overwrite an existing user file') | |
| frames[0].save(a.gif,save_all=True,append_images=frames[1:],duration=180,loop=0) | |
| print(json.dumps({'sample_id':row['sample_id'],'frames':len(frames),'source':row['source_dataset'],'task':row['task'],'image_size':frames[0].size,'model_loaded':False},indent=2)) | |
| if __name__=='__main__':main() | |