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2bb048a 43b1cdb 2bb048a | 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 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191 192 193 194 195 196 197 198 199 200 201 202 203 204 205 206 207 208 209 210 211 212 213 214 215 216 217 218 219 220 221 222 223 224 225 226 227 228 229 230 231 232 233 234 235 236 237 238 239 240 241 242 243 244 245 246 247 248 249 250 251 252 253 254 255 256 257 258 259 260 261 262 263 264 265 266 | #!/usr/bin/env python3
from __future__ import annotations
import json
from pathlib import Path
from typing import Any, Callable
KNOWN_DATASET_NAMES = (
"ARX-data",
"dex_fold_v2_mix",
"droid_lerobot",
"libero",
"libero_zty50",
"VLABench_5",
)
KNOWN_VIDEO_SUFFIXES = {".mp4", ".avi", ".mov", ".mkv", ".webm"}
PORTABLE_IMAGE_ROOT = Path("_extracted_frames")
LEGACY_PORTABLE_IMAGE_ROOTS = (
Path("extracted_frames"),
Path("progress_data") / "VLAC_preprocessed_data" / "data",
)
GENERATED_MARKER_FILENAME = "_GENERATED"
PUBLIC_BENCHMARK_JSON_NAME = "video_progress_benchmark_file.json"
PUBLIC_RELEASE_ROOT_PLACEHOLDER = "__VLAC2_RELEASE_ROOT__"
PUBLIC_FRAMES_ROOT_PLACEHOLDER = "__VLAC2_FRAMES_ROOT__"
PUBLIC_BENCHMARK_DIRNAME = "benchmark_splits"
FULL_RELEASE_BENCHMARK_DIRNAME = "benchmark_style_all"
LEGACY_BENCHMARK_DIRNAME = "benchmark_json"
def portable_image_roots() -> tuple[Path, ...]:
roots = [PORTABLE_IMAGE_ROOT, *LEGACY_PORTABLE_IMAGE_ROOTS]
deduped: list[Path] = []
seen: set[tuple[str, ...]] = set()
for root in roots:
key = root.parts
if key in seen:
continue
seen.add(key)
deduped.append(root)
return tuple(deduped)
def load_json(path: Path) -> Any:
return json.loads(path.read_text(encoding="utf-8"))
def dump_json(path: Path, payload: Any) -> None:
path.parent.mkdir(parents=True, exist_ok=True)
path.write_text(json.dumps(payload, ensure_ascii=False, indent=2) + "\n", encoding="utf-8")
def ensure_generated_marker(output_root: Path) -> Path:
output_root.mkdir(parents=True, exist_ok=True)
marker_path = output_root / GENERATED_MARKER_FILENAME
marker_path.write_text(
"This directory is generated by the VLAC2 public frame-extraction workflow.\n",
encoding="utf-8",
)
return marker_path
def ensure_release_tree(release_root: Path) -> dict[str, Path]:
release_root = release_root.resolve()
paths = {
"release_root": release_root,
"raw_root": release_root / "data",
"benchmark_root": release_root / PUBLIC_BENCHMARK_DIRNAME,
"portable_image_root": release_root / PORTABLE_IMAGE_ROOT,
"scripts_root": release_root / "scripts",
}
for key in ("release_root", "raw_root", "benchmark_root", "scripts_root"):
paths[key].mkdir(parents=True, exist_ok=True)
return paths
def _normalized_parts(raw_path: str | Path) -> list[str]:
raw = str(raw_path or "").strip().replace("\\", "/")
if not raw:
raise ValueError("empty path")
return [part for part in Path(raw).parts if part not in ("", ".", "/")]
def dataset_relative_path(raw_path: str | Path) -> Path:
parts = _normalized_parts(raw_path)
for idx, part in enumerate(parts):
if part in KNOWN_DATASET_NAMES:
return Path(*parts[idx:])
for portable_root in portable_image_roots():
marker_parts = list(portable_root.parts)
marker_len = len(marker_parts)
for idx in range(max(0, len(parts) - marker_len + 1)):
if parts[idx : idx + marker_len] == marker_parts:
tail = parts[idx + marker_len :]
if not tail:
break
for tail_idx, part in enumerate(tail):
if part in KNOWN_DATASET_NAMES:
return Path(*tail[tail_idx:])
return Path(*tail)
return Path(*parts)
def normalize_main_path(raw_main_path: str | Path) -> Path:
rel = dataset_relative_path(raw_main_path)
if rel.suffix.lower() in KNOWN_VIDEO_SUFFIXES:
return rel.with_suffix("")
return rel
def main_path_from_frame_path(raw_frame_path: str | Path) -> Path:
rel = dataset_relative_path(raw_frame_path)
if rel.suffix:
return rel.parent
return rel
def portable_frame_path_from_any(raw_frame_path: str | Path) -> Path:
return PORTABLE_IMAGE_ROOT / dataset_relative_path(raw_frame_path)
def placeholder_frame_path_from_any(raw_frame_path: str | Path) -> str:
return f"{PUBLIC_FRAMES_ROOT_PLACEHOLDER}/{dataset_relative_path(raw_frame_path).as_posix()}"
def absolute_frame_path_from_any(raw_frame_path: str | Path, frames_root: Path) -> Path:
raw = str(raw_frame_path or "").strip()
if not raw:
raise ValueError("empty frame path")
path = Path(raw)
if path.is_absolute():
return path
parts = _normalized_parts(raw)
if parts and parts[0] in (PUBLIC_FRAMES_ROOT_PLACEHOLDER, PUBLIC_RELEASE_ROOT_PLACEHOLDER):
parts = parts[1:]
for portable_root in portable_image_roots():
marker_parts = list(portable_root.parts)
if parts[: len(marker_parts)] == marker_parts:
return frames_root.resolve() / Path(*parts[len(marker_parts) :])
if parts and parts[0] in KNOWN_DATASET_NAMES:
return frames_root.resolve() / Path(*parts)
return frames_root.resolve() / Path(*parts)
def rewrite_benchmark_image_paths(
rows: list[dict[str, Any]],
path_rewriter: Callable[[str], str],
) -> list[dict[str, Any]]:
rewritten_rows: list[dict[str, Any]] = []
for row in rows:
rewritten = dict(row)
frame_index = dict(row.get("frame_index") or {})
if frame_index:
rewritten_frame_index: dict[str, dict[str, str]] = {}
for frame_idx, images in frame_index.items():
image_map = dict(images or {})
rewritten_frame_index[str(frame_idx)] = {
str(view): path_rewriter(str(image_path))
for view, image_path in image_map.items()
if str(image_path or "").strip()
}
rewritten["frame_index"] = rewritten_frame_index
reference_context = row.get("reference_context")
if isinstance(reference_context, dict):
rewritten_ref = dict(reference_context)
anchors = list(reference_context.get("reference_anchors") or [])
rewritten_anchors: list[dict[str, Any]] = []
for anchor in anchors:
rewritten_anchor = dict(anchor)
images = dict(anchor.get("images") or {})
if images:
rewritten_anchor["images"] = {
str(view): path_rewriter(str(image_path))
for view, image_path in images.items()
if str(image_path or "").strip()
}
rewritten_anchors.append(rewritten_anchor)
rewritten_ref["reference_anchors"] = rewritten_anchors
rewritten["reference_context"] = rewritten_ref
videos = row.get("videos")
if isinstance(videos, list):
rewritten_videos: list[Any] = []
for item in videos:
if isinstance(item, list):
rewritten_videos.append(
[path_rewriter(str(path)) for path in item if str(path or "").strip()]
)
elif isinstance(item, str) and item.strip():
rewritten_videos.append(path_rewriter(item))
rewritten["videos"] = rewritten_videos
images = row.get("images")
if isinstance(images, list):
rewritten["images"] = [
path_rewriter(str(path))
for path in images
if str(path or "").strip()
]
rewritten_rows.append(rewritten)
return rewritten_rows
def infer_main_path_from_row(row: dict[str, Any]) -> Path | None:
for meta_key in ("metadata", "_meta", "meta"):
meta = row.get(meta_key)
if isinstance(meta, dict):
raw_main_path = str(meta.get("main_path") or "").strip()
if raw_main_path:
return normalize_main_path(raw_main_path)
frame_index = row.get("frame_index")
if isinstance(frame_index, dict):
for images in frame_index.values():
if not isinstance(images, dict):
continue
for image_path in images.values():
if str(image_path or "").strip():
return main_path_from_frame_path(str(image_path))
videos = row.get("videos")
if isinstance(videos, list) and videos:
first = videos[0]
if isinstance(first, list) and first:
return main_path_from_frame_path(str(first[0]))
if isinstance(first, str) and first.strip():
return main_path_from_frame_path(first)
return None
def discover_benchmark_jsons(benchmark_root: Path) -> list[Path]:
benchmark_root = benchmark_root.resolve()
candidates: list[Path] = []
seen: set[Path] = set()
for path in sorted(benchmark_root.glob(f"**/{PUBLIC_BENCHMARK_JSON_NAME}")):
resolved = path.resolve()
if resolved in seen:
continue
seen.add(resolved)
candidates.append(resolved)
return candidates
def resolve_benchmark_root(release_root: Path) -> Path:
release_root = release_root.resolve()
preferred = release_root / PUBLIC_BENCHMARK_DIRNAME
full_release = release_root / FULL_RELEASE_BENCHMARK_DIRNAME
legacy = release_root / LEGACY_BENCHMARK_DIRNAME
if preferred.exists():
return preferred
if full_release.exists():
return full_release
if legacy.exists():
return legacy
return preferred
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