| |
| |
| """Generate OBJ-DINO and TVA manifest JSONs from an HOI eval dataset.""" |
| import argparse |
| import json |
| import os |
| import os.path as osp |
|
|
| _EVAL_ROOT = osp.abspath(osp.join(osp.dirname(__file__), "..")) |
| _DEFAULT_DATASET = osp.join( |
| _EVAL_ROOT, "benchmarks/datasets/hoi_crosstest_20251107.json" |
| ) |
| _DEFAULT_OBJ_TABLE = osp.join( |
| _EVAL_ROOT, "benchmarks/datasets/prompt_translated3.json" |
| ) |
|
|
| CAPTION_OBJ_NAME_FALLBACK = { |
| "selfcollect250509_img_1-1": "notebook", |
| "selfcollect250509_img_1-2": "notebook", |
| "selfcollect250509_img_4": "electric guitar", |
| "selfcollect250509_img_5-1": "tablet", |
| "selfcollect250509_img_5-2": "cup", |
| "selfcollect250509_img_7": "container", |
| "selfcollect250509_img_8": "smartphone", |
| "selfcollect250509_img_13": "laptop", |
| "selfcollect250509_img_14": "tablet", |
| "selfcollect250509_img_15": "camera", |
| "selfcollect250509_img_17": "paper cup", |
| "selfcollect250509_img_18": "glass of water", |
| "selfcollect250509_img_23": "shoes", |
| "selfcollect250509_img_25": "smartphone", |
| "selfcollect250509_img_27": "tablet", |
| "selfcollect250509_img_29-1": "handbag", |
| "selfcollect250509_img_29-2": "handbag", |
| "selfcollect250509_img_31-1": "sandal", |
| "selfcollect250509_img_31-2": "loafer", |
| "selfcollect250509_img_32": "jar", |
| "selfcollect250509_img_33": "tablet", |
| "selfcollect250509_img_38": "smartphone", |
| "selfcollect250509_img_42": "cup", |
| "selfcollect250509_img_48": "plastic bag", |
| "selfcollect250509_img_51-1": "compact mirror", |
| "selfcollect250509_img_51-2": "compact mirror", |
| "selfcollect250509_img_53": "acoustic guitar", |
| "selfcollect250509_img_54": "acoustic guitar", |
| "selfcollect250509_img_57": "smartphone", |
| "selfcollect250509_img_62": "electric guitar", |
| "selfcollect250509_img_67": "acoustic guitar", |
| "selfcollect250509_img_70": "water bottle", |
| "selfcollect250509_img_72": "water bottle", |
| "selfcollect250509_img_75": "laptop", |
| "selfcollect250509_img_76": "sneakers", |
| "selfcollect250509_img_81": "smartphone", |
| "selfcollect250509_img_85": "compact mirror", |
| "selfcollect250509_img_92": "smartphone", |
| "selfcollect250509_img_101": "smartphone", |
| "selfcollect250509_img_103": "tablet", |
| } |
|
|
|
|
| def convert_obj_table(obj_data): |
| return {item["id"]: item for item in obj_data} |
|
|
|
|
| def extract_obj_name_from_path(data): |
| for key in ("ref_obj_image_path", "ref_image_path"): |
| path = data.get(key) or "" |
| for marker in ("_##object##_", "_##human##_"): |
| if marker in path: |
| suffix = path.split(marker)[-1] |
| if suffix.endswith(".png"): |
| obj_raw = suffix[:-4].strip() |
| if obj_raw: |
| return obj_raw.replace("_", " ") |
| return None |
|
|
|
|
| def build_obj_dino_list(hoi_list, obj_dict, skip_missing_obj=False, fallback_obj_from_path=False): |
| out = [] |
| for data in hoi_list: |
| video_id = data["image_id"] |
| parts = video_id.split("=") |
| obj_id = parts[1] if len(parts) >= 2 else video_id |
| if obj_id in obj_dict: |
| obj_name = obj_dict[obj_id]["obj_en"] |
| else: |
| if fallback_obj_from_path: |
| obj_name = extract_obj_name_from_path(data) |
| if obj_name is None: |
| obj_name = CAPTION_OBJ_NAME_FALLBACK.get(video_id) |
| if obj_name is None: |
| if skip_missing_obj: |
| continue |
| raise KeyError( |
| f"obj_id '{obj_id}' not in obj table (video_id={video_id})" |
| ) |
| elif skip_missing_obj: |
| continue |
| else: |
| raise KeyError(f"obj_id '{obj_id}' not in obj table (video_id={video_id})") |
| out.append({ |
| "video_id": data["image_id"], |
| "mp4_img": data["ref_image_path"], |
| "obj_img": data["ref_obj_image_path"], |
| "obj_name": obj_name, |
| }) |
| return out |
|
|
|
|
| def build_tva_list(hoi_list): |
| return [ |
| {"video_id": item["image_id"], "prompt": item["caption"]} |
| for item in hoi_list |
| ] |
|
|
|
|
| def main(): |
| parser = argparse.ArgumentParser( |
| description="Generate OBJ-DINO and TVA manifests from an HOI eval JSON" |
| ) |
| parser.add_argument("--input", type=str, default=_DEFAULT_DATASET) |
| parser.add_argument("--obj_table", type=str, default=_DEFAULT_OBJ_TABLE) |
| parser.add_argument("--obj_dino_out", type=str, default=None) |
| parser.add_argument("--tva_out", type=str, default=None) |
| parser.add_argument("--skip_missing_obj", action="store_true") |
| parser.add_argument("--fallback_obj_from_path", action="store_true") |
| args = parser.parse_args() |
|
|
| if args.obj_dino_out is None: |
| args.obj_dino_out = osp.join( |
| _EVAL_ROOT, "benchmarks/manifests/obj_dino_crosstest.json" |
| ) |
| if args.tva_out is None: |
| args.tva_out = osp.join( |
| _EVAL_ROOT, "benchmarks/manifests/tva_crosstest.json" |
| ) |
|
|
| with open(args.input, "r", encoding="utf-8") as f: |
| hoi_list = json.load(f) |
| print(f"[prepare] loaded {len(hoi_list)} samples from {args.input}") |
|
|
| with open(args.obj_table, "r", encoding="utf-8") as f: |
| obj_dict = convert_obj_table(json.load(f)) |
| obj_dino_list = build_obj_dino_list( |
| hoi_list, |
| obj_dict, |
| skip_missing_obj=args.skip_missing_obj, |
| fallback_obj_from_path=args.fallback_obj_from_path, |
| ) |
| os.makedirs(osp.dirname(args.obj_dino_out), exist_ok=True) |
| with open(args.obj_dino_out, "w", encoding="utf-8") as f: |
| json.dump(obj_dino_list, f, ensure_ascii=False, indent=4) |
| print(f"[prepare] OBJ_DINO -> {args.obj_dino_out} ({len(obj_dino_list)} items)") |
|
|
| tva_list = build_tva_list(hoi_list) |
| os.makedirs(osp.dirname(args.tva_out), exist_ok=True) |
| with open(args.tva_out, "w", encoding="utf-8") as f: |
| json.dump(tva_list, f, ensure_ascii=False, indent=4) |
| print(f"[prepare] TVA -> {args.tva_out} ({len(tva_list)} items)") |
|
|
|
|
| if __name__ == "__main__": |
| main() |
|
|
