| """Read frame WebDatasets using each dataset's manifest.""" |
| import json |
| import io |
| from pathlib import Path |
|
|
| import numpy as np |
| from PIL import Image |
| import webdataset as wds |
|
|
|
|
| def decode_sample(sample): |
| result = dict(sample) |
| meta = json.loads(sample['json']) |
| result['json'] = meta |
| for modality, field in meta['components'].items(): |
| if field is None: |
| continue |
| data = io.BytesIO(sample[field]) |
| if field.endswith('.npy'): |
| result[field] = np.load(data, allow_pickle=False) |
| elif modality == 'depth': |
| |
| with Image.open(data) as image: |
| result[field] = np.array(image) |
| else: |
| with Image.open(data) as image: |
| result[field] = image.convert('RGB') |
| return result |
|
|
|
|
| def dataset(directory, split='train', decode=True): |
| directory = Path(directory) |
| manifest = json.loads((directory / 'manifest.json').read_text()) |
| if manifest['status'] != 'complete': |
| raise RuntimeError(f'Dataset is not complete: {manifest["status"]}') |
| shards = [str(directory / s['path']) for s in manifest['shards'] |
| if s['path'].split('/')[1] == split] |
| if not shards: |
| raise ValueError(f'No shards for split {split!r}') |
| result = wds.WebDataset(shards, shardshuffle=False) |
| return result.map(decode_sample) if decode else result |
|
|
|
|
| if __name__ == '__main__': |
| import argparse |
| p = argparse.ArgumentParser() |
| p.add_argument('directory') |
| p.add_argument('--split', default='train') |
| args = p.parse_args() |
| sample = next(iter(dataset(args.directory, args.split))) |
| meta = sample['json'] |
| print('Fields:', list(sample)) |
| print('Dataset:', meta['dataset'], 'scene:', meta['scene_id'], 'frame:', meta['frame_id']) |
|
|
