Datasets:
File size: 1,739 Bytes
0760102 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 | from __future__ import annotations
import argparse
from pathlib import Path
import pyarrow.parquet as pq
from datasets import load_dataset
from datasets.table import embed_table_storage
def main() -> int:
parser = argparse.ArgumentParser(description="Build a viewer-friendly Parquet split with embedded images")
parser.add_argument("--root", type=Path, default=Path(__file__).resolve().parents[1])
parser.add_argument("--out", type=Path, default=None, help="Output parquet path")
parser.add_argument("--row-group-size", type=int, default=100)
args = parser.parse_args()
root = args.root.resolve()
out = args.out or (root / "data" / "train-00000-of-00001.parquet")
out.parent.mkdir(parents=True, exist_ok=True)
dataset = load_dataset(str(root), split="train")
ordered = ["image"] + [name for name in dataset.column_names if name != "image"]
dataset = dataset.select_columns(ordered)
table = dataset.with_format("arrow")[:]
table = embed_table_storage(table)
writer = pq.ParquetWriter(str(out), table.schema)
try:
for batch in table.to_batches(max_chunksize=args.row_group_size):
writer.write_batch(batch, row_group_size=args.row_group_size)
finally:
writer.close()
check = pq.read_table(str(out))
first = check.column("image")[0].as_py()
embedded = isinstance(first, dict) and first.get("bytes") is not None
print(
f"wrote {out} ({out.stat().st_size / 1024**2:.2f} MiB, {check.num_rows} rows, "
f"{check.metadata.num_row_groups if hasattr(check, 'metadata') else 'n/a'}); "
f"images_embedded={embedded}"
)
return 0 if embedded else 1
if __name__ == "__main__":
raise SystemExit(main())
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