Datasets:
File size: 3,320 Bytes
dd88850 | 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 | #!/usr/bin/env python3
from __future__ import annotations
import json
import os
from pathlib import Path
from typing import Any
def read_jsonl(path: str | Path) -> list[dict[str, Any]]:
with Path(path).open("r", encoding="utf-8") as f:
return [json.loads(line) for line in f if line.strip()]
def resolve_data_paths(row: dict[str, Any], data_root: str | Path | None = None) -> dict[str, Any]:
"""Return a copy of a row with image/mask-like paths resolved locally.
By default, `data_root` is read from FAME_DATA_ROOT. The episode loaders
pass the release root when `resolve_paths=True`, so bundled data paths work
without extra configuration.
"""
root_value = str(data_root or os.environ.get("FAME_DATA_ROOT", "")).strip()
if not root_value:
return dict(row)
root = Path(root_value)
out = dict(row)
for key in ["image", "mask"]:
value = out.get(key)
if isinstance(value, str) and value and not value.startswith("/") and "::" not in value:
out[key] = str(root / value)
return out
def load_episode(
release_root: str | Path,
task: str,
seed: int = 0,
k: int = 10,
resolve_paths: bool = False,
data_root: str | Path | None = None,
) -> tuple[list[dict[str, Any]], list[dict[str, Any]]]:
root = Path(release_root)
ep_dir = root / "FAME_benchmark" / "episodes" / f"k{k}_seed{seed}" / task
support = read_jsonl(ep_dir / "support.jsonl")
query = read_jsonl(ep_dir / "test.jsonl")
if resolve_paths:
local_root = Path(data_root) if data_root is not None else root
support = [resolve_data_paths(row, data_root=local_root) for row in support]
query = [resolve_data_paths(row, data_root=local_root) for row in query]
return support, query
def load_ood_episode(
release_root: str | Path,
pair_id: str,
setting: str = "k10_seed0",
resolve_paths: bool = False,
data_root: str | Path | None = None,
) -> tuple[list[dict[str, Any]], list[dict[str, Any]], dict[str, Any]]:
root = Path(release_root)
ep_dir = root / "FAME_benchmark" / "ood_episodes" / setting / pair_id
support = read_jsonl(ep_dir / "support.jsonl")
query = read_jsonl(ep_dir / "test.jsonl")
info = json.loads((ep_dir / "ood_pair_info.json").read_text(encoding="utf-8"))
if resolve_paths:
local_root = Path(data_root) if data_root is not None else root
support = [resolve_data_paths(row, data_root=local_root) for row in support]
query = [resolve_data_paths(row, data_root=local_root) for row in query]
return support, query, info
def list_tasks(release_root: str | Path) -> list[str]:
path = Path(release_root) / "FAME_benchmark" / "task_lists" / "FAME_benchmark_tasks.txt"
return [line.strip() for line in path.read_text(encoding="utf-8").splitlines() if line.strip()]
def list_ood_pairs(release_root: str | Path) -> list[str]:
path = Path(release_root) / "FAME_benchmark" / "task_lists" / "FAME_ood_pairs_all.txt"
if path.exists():
return [line.strip() for line in path.read_text(encoding="utf-8").splitlines() if line.strip()]
root = Path(release_root) / "FAME_benchmark" / "ood_episodes" / "k10_seed0"
return sorted(p.name for p in root.iterdir() if p.is_dir()) if root.exists() else []
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