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""" |
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Add height/width columns to nastol-images-full dataset |
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""" |
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import argparse |
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import os |
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import logging |
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import sys |
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from pathlib import Path |
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logging.basicConfig( |
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level=logging.INFO, |
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format='[%(asctime)s] %(levelname)s: %(message)s', |
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datefmt='%Y-%m-%d %H:%M:%S', |
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stream=sys.stdout, |
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force=True |
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) |
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logger = logging.getLogger(__name__) |
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from datasets import load_dataset |
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from huggingface_hub import HfApi |
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import pyarrow as pa |
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import pyarrow.parquet as pq |
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def main(): |
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ap = argparse.ArgumentParser() |
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ap.add_argument('--input-dataset', type=str, default='vlordier/nastol-images-full') |
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ap.add_argument('--output-dataset', type=str, default='vlordier/nastol-images-full') |
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ap.add_argument('--split', type=str, default='train') |
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ap.add_argument('--shard-index', type=int, default=0) |
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ap.add_argument('--num-shards', type=int, default=1) |
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ap.add_argument('--batch-size', type=int, default=1000) |
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args = ap.parse_args() |
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logger.info("="*60) |
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logger.info("Add Height/Width Columns to Dataset") |
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logger.info("="*60) |
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logger.info(f"Arguments: {vars(args)}") |
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token = os.environ.get('HF_TOKEN') |
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api = HfApi(token=token) |
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logger.info(f"Loading {args.input_dataset}...") |
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ds = load_dataset(args.input_dataset, split=args.split, streaming=True) |
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if args.num_shards > 1: |
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ds = ds.shard(num_shards=args.num_shards, index=args.shard_index) |
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logger.info(f"Processing shard {args.shard_index+1}/{args.num_shards}") |
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buffer = [] |
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batch_count = 0 |
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upload_count = 0 |
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def flush_buffer(): |
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nonlocal buffer, upload_count |
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if not buffer: |
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return |
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image_paths = [b['image_path'] for b in buffer] |
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images_bytes = [b['image'] for b in buffer] |
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heights = [b['height'] for b in buffer] |
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widths = [b['width'] for b in buffer] |
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table = pa.table({ |
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'image_path': image_paths, |
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'image': images_bytes, |
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'height': heights, |
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'width': widths |
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}) |
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local_dir = Path('dimension_batches') |
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local_dir.mkdir(parents=True, exist_ok=True) |
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file_name = f"shard-{args.shard_index:03d}-batch-{upload_count:04d}.parquet" |
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local_path = local_dir / file_name |
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pq.write_table(table, local_path) |
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path_in_repo = f"data/{file_name}" |
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logger.info(f"Uploading batch {upload_count} with {len(buffer)} images -> {path_in_repo}") |
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try: |
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api.upload_file( |
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path_or_fileobj=str(local_path), |
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path_in_repo=path_in_repo, |
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repo_id=args.output_dataset, |
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repo_type='dataset', |
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token=token |
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) |
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logger.info("✓ Uploaded") |
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except Exception as e: |
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logger.error(f"Upload failed: {e}") |
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buffer.clear() |
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upload_count += 1 |
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logger.info("Processing images...") |
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for idx, sample in enumerate(ds): |
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image = sample['image'] |
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image_path = sample.get('image_path', f'img_{idx:06d}') |
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width, height = image.size |
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import io |
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buf = io.BytesIO() |
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image.save(buf, format='PNG') |
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image_bytes = buf.getvalue() |
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buffer.append({ |
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'image_path': image_path, |
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'image': image_bytes, |
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'height': height, |
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'width': width |
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}) |
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if len(buffer) >= args.batch_size: |
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flush_buffer() |
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batch_count += 1 |
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logger.info(f"Processed {batch_count * args.batch_size} images") |
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flush_buffer() |
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logger.info(f"✓ Completed shard {args.shard_index}: {batch_count * args.batch_size + len(buffer)} images") |
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if __name__ == '__main__': |
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main() |
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