ARMBench-VL / scripts /load_armbench_vl.py
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Add ARMBench-VL annotations and documentation
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"""Small dependency-free loader for a downloaded ARMBench-VL release."""
from __future__ import annotations
import json
import re
from pathlib import Path
from typing import Any, Iterator
def _config(root: Path) -> dict[str, dict[str, Any]]:
return json.loads((root / "dataset_config.json").read_text(encoding="utf-8"))
def load_records(root: str | Path, task: str) -> list[dict[str, Any]]:
root = Path(root)
task_config = _config(root)[task]
annotation_path = root / task_config["annotations"]
with annotation_path.open(encoding="utf-8") as handle:
return [json.loads(line) for line in handle if line.strip()]
def resolve_images(
root: str | Path, task: str, record: dict[str, Any]
) -> list[Path]:
root = Path(root)
resource_root = root / _config(root)[task]["resource_root"]
return [resource_root / image for image in record.get("images", [])]
def iter_document_pages(root: str | Path, doc_id: str) -> Iterator[Path]:
"""Yield individual page images in numeric order, excluding composites."""
root = Path(root)
resource_root = root / _config(root)["multimodal_long_document_qa"][
"resource_root"
]
stem = Path(doc_id).stem
pattern = re.compile(rf"^{re.escape(stem)}_(\d+)\.(?:jpg|jpeg|png|webp)$", re.I)
pages: list[tuple[int, Path]] = []
for path in resource_root.glob(f"{stem}_*"):
match = pattern.match(path.name)
if match:
pages.append((int(match.group(1)), path))
for _, path in sorted(pages):
yield path
if __name__ == "__main__":
import argparse
parser = argparse.ArgumentParser()
parser.add_argument("root", type=Path)
parser.add_argument(
"task",
choices=(
"fine_grained_perception",
"multimodal_long_document_qa",
"multimodal_instruction_following",
),
)
args = parser.parse_args()
records = load_records(args.root, args.task)
print(f"{args.task}: {len(records)} examples")
print("first image(s):", *resolve_images(args.root, args.task, records[0]))