Download scripts/prepare_benchmark_assets.py from ProAudience/agenthoi-eval: direct link, hf CLI and curl.
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https://huggingface.co/datasets/ProAudience/agenthoi-eval/resolve/main/scripts/prepare_benchmark_assets.py
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curl -L -o prepare_benchmark_assets.py https://huggingface.co/datasets/ProAudience/agenthoi-eval/resolve/main/scripts/prepare_benchmark_assets.py
5.27 kB
| #!/usr/bin/env python3 | |
| # -*- coding: utf-8 -*- | |
| """ | |
| Copy ref images from benchmark JSONs into benchmarks/assets/ and write portable JSONs. | |
| Usage (on a machine that can read the paths inside the JSON files): | |
| python scripts/prepare_benchmark_assets.py | |
| python scripts/prepare_benchmark_assets.py --datasets crosstest AC homa | |
| python scripts/prepare_benchmark_assets.py --dry-run | |
| Outputs: | |
| benchmarks/assets/<image_id>/ref_human.png|ref_object.png|ref_pasted.png | |
| benchmarks/datasets_portable/<same basenames as datasets/> | |
| """ | |
| from __future__ import annotations | |
| import argparse | |
| import hashlib | |
| import json | |
| import os | |
| import re | |
| import shutil | |
| from pathlib import Path | |
| EVAL_ROOT = Path(__file__).resolve().parent.parent | |
| DATASET_DIR = EVAL_ROOT / "benchmarks" / "datasets" | |
| PORTABLE_DIR = EVAL_ROOT / "benchmarks" / "datasets_portable" | |
| ASSETS_DIR = EVAL_ROOT / "benchmarks" / "assets" | |
| DATASET_MAP = { | |
| "crosstest": "hoi_crosstest_20251107.json", | |
| "AC": "hoi_AC_test_evalset.json", | |
| "homa": "hoi_selfcollect_homa1_evalset.json", | |
| } | |
| IMAGE_KEYS = ( | |
| ("ref_image_path", "ref_human.png"), | |
| ("ref_obj_image_path", "ref_object.png"), | |
| ("pasted_image", "ref_pasted.png"), | |
| ) | |
| def safe_dir_name(image_id: str) -> str: | |
| s = re.sub(r"[^\w=\-.]", "_", image_id) | |
| return s[:200] if len(s) > 200 else s | |
| def copy_if_exists(src: str, dst: Path, dry_run: bool) -> bool: | |
| if not src or not isinstance(src, str): | |
| return False | |
| if not src.lower().endswith((".png", ".jpg", ".jpeg", ".webp")): | |
| return False | |
| if not os.path.isfile(src): | |
| return False | |
| if dry_run: | |
| return True | |
| dst.parent.mkdir(parents=True, exist_ok=True) | |
| if dst.exists() and dst.stat().st_size == os.path.getsize(src): | |
| return True | |
| shutil.copy2(src, dst) | |
| return True | |
| def portable_path(image_id: str, filename: str) -> str: | |
| return f"benchmarks/assets/{safe_dir_name(image_id)}/{filename}" | |
| def process_dataset( | |
| src_json: Path, | |
| dst_json: Path, | |
| assets_dir: Path, | |
| dry_run: bool, | |
| report: dict, | |
| ) -> None: | |
| with open(src_json, "r", encoding="utf-8") as f: | |
| items = json.load(f) | |
| out_items = [] | |
| for item in items: | |
| image_id = item["image_id"] | |
| subdir = assets_dir / safe_dir_name(image_id) | |
| new_item = dict(item) | |
| for json_key, local_name in IMAGE_KEYS: | |
| src = item.get(json_key) | |
| if not src: | |
| continue | |
| dst_file = subdir / local_name | |
| if copy_if_exists(src, dst_file, dry_run): | |
| new_item[json_key] = portable_path(image_id, local_name) | |
| report["copied"] += 1 | |
| else: | |
| report["missing"] += 1 | |
| if src.lower().endswith((".png", ".jpg", ".jpeg", ".webp")): | |
| report["missing_paths"].append(src) | |
| out_items.append(new_item) | |
| if not dry_run: | |
| dst_json.parent.mkdir(parents=True, exist_ok=True) | |
| with open(dst_json, "w", encoding="utf-8") as f: | |
| json.dump(out_items, f, ensure_ascii=False, indent=2) | |
| report["samples"] = len(out_items) | |
| def main(): | |
| parser = argparse.ArgumentParser(description="Package benchmark ref images for release/HF") | |
| parser.add_argument( | |
| "--datasets", | |
| nargs="+", | |
| default=list(DATASET_MAP.keys()), | |
| choices=list(DATASET_MAP.keys()), | |
| help="Which splits to process", | |
| ) | |
| parser.add_argument("--dry-run", action="store_true") | |
| parser.add_argument( | |
| "--assets-dir", | |
| type=Path, | |
| default=ASSETS_DIR, | |
| ) | |
| parser.add_argument( | |
| "--portable-dir", | |
| type=Path, | |
| default=PORTABLE_DIR, | |
| ) | |
| args = parser.parse_args() | |
| total_report = {"copied": 0, "missing": 0, "missing_paths": [], "samples": 0} | |
| for name in args.datasets: | |
| src = DATASET_DIR / DATASET_MAP[name] | |
| dst = args.portable_dir / DATASET_MAP[name] | |
| report = {"copied": 0, "missing": 0, "missing_paths": [], "samples": 0} | |
| print(f"[{name}] {src.name}") | |
| process_dataset(src, dst, args.assets_dir, args.dry_run, report) | |
| print( | |
| f" samples={report['samples']} copied_fields={report['copied']} " | |
| f"missing_fields={report['missing']}" | |
| ) | |
| for k in ("copied", "missing", "samples"): | |
| total_report[k] += report[k] | |
| total_report["missing_paths"].extend(report["missing_paths"]) | |
| if not args.dry_run and args.assets_dir.exists(): | |
| n_dirs = sum(1 for _ in args.assets_dir.iterdir() if _.is_dir()) | |
| print(f"\nassets: {args.assets_dir} ({n_dirs} sample dirs)") | |
| print(f"portable json: {args.portable_dir}") | |
| missing_unique = sorted(set(total_report["missing_paths"])) | |
| if missing_unique: | |
| miss_log = EVAL_ROOT / "benchmarks" / "assets_missing.txt" | |
| if not args.dry_run: | |
| miss_log.write_text("\n".join(missing_unique) + "\n", encoding="utf-8") | |
| print(f"\n[warn] {len(missing_unique)} unique missing source files") | |
| print(f" log: {miss_log}") | |
| print(" Re-run this script on the dev machine where those paths exist.") | |
| if args.dry_run: | |
| print("\n(dry-run, no files written)") | |
| if __name__ == "__main__": | |
| main() | |