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942788e 26dc037 942788e a4ea9dc 942788e 26dc037 942788e 26dc037 942788e | 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 | """Build GR00T dataset views (symlinked episodes + rewritten meta + stats) for the G1 tasks.
Usage: <groot python> prepare_groot_data.py <task> [<task> ...] (tasks: b6 basket a3 a7)
B6 always uses the fixed first 100 episodes (0-99) of b6-v5t7-ready-start-20261109.
"""
import hashlib
import json
import os
import subprocess
import sys
from pathlib import Path
H = Path(__file__).resolve().parent
G = H.parent
P = G.parent
OUT = G / "groot-data"
TASKS = {
"b6": (P / "b6-v5t7-ready-start-60ep-20261109/data/deliveries/g1/b6-v5t7-ready-start-20261109", 100),
"basket": (P / "basket-current-dynamics-100-v21-b0ff522/data", None), # HF basket-transfer-expert-v1 @current-dynamics-100-v21 b0ff522 (old ed77719 retired)
"trolley": (P / "trolley-push-expert-v1-20261110/data/trolley_push", 100), # HF trolley-push-expert-v1 @ef9024a: fixed first 100 of 103
"b7": (P / "b7-black-clothes-hamper-v1-1bb002a/data", 100), # HF b7-black-clothes-hamper-expert-v1 @1bb002a, first 100 of 107
"a6": (P / "a6-door-pull-v1-cf3ee9b/data/door_pull", None), # HF door-pull-expert-v1 @cf3ee9b (A6)
"c6t": (P / "c6-test8-06c231d/data", None), # c6 8-episode adaptation test only
"c6": (P / "c6-bathroom-door-fetch-v1-3afba69/data", None), # HF c6-bathroom-door-fetch-expert-v1 @3afba69 (C6)
"a3": (P / "a3-a7-20261109/a3-fridge-open-expert-v1/780fcf1e4bd7db947a8c2d8f7b92e61f24f71b45", None),
"a7": (P / "a3-a7-20261109/a7-cabinet-close-expert-v1/1935a98e8f55d4d1d2d1615ddb97c2679713595c", None),
"a18": (P / "a18-h2-dataset-audit-8e956a10/dataset", None),
"a17": (P / "a17-unscrew-bottle-v1-407e6e2/data", None), # HF a17-unscrew-bottle-expert-v1 @407e6e2
}
CONFIG = {"a18": "h2_body31_hand44_h16.py", "a17": "h2_body31_hand44_h16.py"}
H2_GROUPS = {"left_leg": (0, 6), "right_leg": (6, 12), "waist": (12, 15), "left_arm": (15, 22), "right_arm": (22, 29),
"head": (29, 31), "left_hand": (31, 53), "right_hand": (53, 75)}
def h2_modality(info):
f = info["features"]
names = f["observation.state"]["names"]
assert len(names) == 75 and names[:31] == f["action.body_target"]["names"] and names[31:] == f["action.hands"]["names"]
assert f["observation.projected_gravity"]["shape"] == [3]
state = {g: {"original_key": "observation.state", "start": a, "end": b} for g, (a, b) in H2_GROUPS.items()}
state["projected_gravity"] = {"original_key": "observation.projected_gravity", "start": 0, "end": 3}
return {"state": state,
"action": {"body_target": {"original_key": "action.body_target", "start": 0, "end": 31},
"left_hand_target": {"original_key": "action.hands", "start": 0, "end": 22},
"right_hand_target": {"original_key": "action.hands", "start": 22, "end": 44}},
"video": {"head": {"original_key": "observation.images.head"},
"chest": {"original_key": "observation.images.chest"}},
"annotation": {"human.task_description": {"original_key": "task_index"}}}
BODY = ["left_hip_pitch_joint", "left_hip_roll_joint", "left_hip_yaw_joint", "left_knee_joint", "left_ankle_pitch_joint",
"left_ankle_roll_joint", "right_hip_pitch_joint", "right_hip_roll_joint", "right_hip_yaw_joint",
"right_knee_joint", "right_ankle_pitch_joint", "right_ankle_roll_joint", "waist_yaw_joint", "waist_roll_joint",
"waist_pitch_joint", "left_shoulder_pitch_joint", "left_shoulder_roll_joint", "left_shoulder_yaw_joint",
"left_elbow_joint", "left_wrist_roll_joint", "left_wrist_pitch_joint", "left_wrist_yaw_joint",
"right_shoulder_pitch_joint", "right_shoulder_roll_joint", "right_shoulder_yaw_joint", "right_elbow_joint",
"right_wrist_roll_joint", "right_wrist_pitch_joint", "right_wrist_yaw_joint"]
GROUPS = {"left_leg": (0, 6), "right_leg": (6, 12), "waist": (12, 15), "left_arm": (15, 22), "right_arm": (22, 29)}
def jl(path):
return [json.loads(x) for x in Path(path).read_text().splitlines() if x.strip()]
def wl(path, rows):
Path(path).write_text("".join(json.dumps(r) + "\n" for r in rows))
def build(task):
src, limit = TASKS[task]
info = json.loads((src / "meta/info.json").read_text())
names = info["features"]["observation.state"]["names"]
if task in CONFIG:
idx = list(range(31))
else:
idx = [names.index(n) for n in BODY]
for g, (a, b) in GROUPS.items():
assert idx[a:b] == list(range(idx[a], idx[a] + (b - a))), (task, g, idx[a:b])
for key, dim in (("action.motion_token", 64), ("observation.inspire_left_hand_state", 6),
("observation.inspire_right_hand_state", 6), ("observation.projected_gravity", 3),
("observation.images.ego_view", None), ("observation.images.chest", None)):
assert key in info["features"], (task, key)
if dim:
assert info["features"][key]["shape"] == [dim], (task, key)
episodes = jl(src / "meta/episodes.jsonl")
stats = jl(src / "meta/episodes_stats.jsonl")
n = len(episodes) if limit is None else limit
episodes, stats = episodes[:n], stats[:n]
assert [e["episode_index"] for e in episodes] == list(range(n)) == [s["episode_index"] for s in stats]
frames = sum(int(e["length"]) for e in episodes)
dst = OUT / task
if dst.exists():
raise SystemExit(f"{dst} exists")
(dst / "meta").mkdir(parents=True)
vkeys = [k for k, f in info["features"].items() if f.get("dtype") == "video"]
for e in episodes:
i = e["episode_index"]
chunk = i // int(info["chunks_size"])
rel = info["data_path"].format(episode_chunk=chunk, episode_index=i)
(dst / rel).parent.mkdir(parents=True, exist_ok=True)
os.symlink(src / rel, dst / rel)
for k in vkeys:
relv = info["video_path"].format(episode_chunk=chunk, video_key=k, episode_index=i)
(dst / relv).parent.mkdir(parents=True, exist_ok=True)
os.symlink(src / relv, dst / relv)
if task in CONFIG:
# stats.py computes stats for every low-dim feature in info.json and cannot handle e.g. observation.tactile
# [10,24,24]; keep only what the H2 modality uses (parquet columns stay untouched behind the symlinks).
keep = {"observation.state", "observation.projected_gravity", "action.body_target", "action.hands",
"observation.images.head", "observation.images.chest", "timestamp", "frame_index", "episode_index",
"index", "task_index"}
info["features"] = {k: v for k, v in info["features"].items() if k in keep}
vkeys = [k for k in vkeys if k in keep]
stats = [{**s, "stats": {k: v for k, v in s["stats"].items() if k in keep}} if "stats" in s else s
for s in stats]
info.update(total_episodes=n, total_frames=frames, total_videos=n * len(vkeys),
total_chunks=(n - 1) // int(info["chunks_size"]) + 1, splits={"train": f"0:{n}"})
(dst / "meta/info.json").write_text(json.dumps(info, indent=2))
wl(dst / "meta/episodes.jsonl", episodes)
wl(dst / "meta/episodes_stats.jsonl", stats)
(dst / "meta/tasks.jsonl").write_text((src / "meta/tasks.jsonl").read_text())
if task in CONFIG:
modality = h2_modality(info)
else:
state = {g: {"original_key": "observation.state", "start": idx[a], "end": idx[a] + (b - a)}
for g, (a, b) in GROUPS.items()}
state.update(left_hand={"original_key": "observation.inspire_left_hand_state", "start": 0, "end": 6},
right_hand={"original_key": "observation.inspire_right_hand_state", "start": 0, "end": 6},
projected_gravity={"original_key": "observation.projected_gravity", "start": 0, "end": 3})
modality = {"state": state,
"action": {"motion_token": {"original_key": "action.motion_token", "start": 0, "end": 64},
"left_hand_joints": {"original_key": "observation.inspire_left_hand_state", "start": 0, "end": 6},
"right_hand_joints": {"original_key": "observation.inspire_right_hand_state", "start": 0, "end": 6}},
"video": {"ego_view": {"original_key": "observation.images.ego_view"},
"chest": {"original_key": "observation.images.chest"}},
"annotation": {"human.task_description": {"original_key": "task_index"}}}
(dst / "meta/modality.json").write_text(json.dumps(modality, indent=2))
py = sys.executable
src_g = G / "HumanWAM/third_party/Isaac-GR00T"
env = dict(os.environ, PYTHONPATH=f"{src_g}:{H}")
done = None
for tag in ("NEW_EMBODIMENT", "new_embodiment"):
r = subprocess.run([py, str(src_g / "gr00t/data/stats.py"), "--dataset-path", str(dst), "--embodiment-tag", tag,
"--modality-config-path", str(H / CONFIG.get(task, "g1_feedback76_h16.py"))], env=env, cwd=src_g,
capture_output=True, text=True)
if r.returncode == 0:
done = tag
break
last = r.stdout[-1500:] + r.stderr[-1500:]
if done is None:
raise SystemExit(f"stats failed for {task}:\n{last}")
assert (dst / "meta/stats.json").is_file()
receipt = dict(task=task, source=str(src), episodes=n, frames=frames, video_keys=vkeys,
state_dim_raw=len(names), body_index=idx, stats_tag=done,
modality_sha256=hashlib.sha256((dst / "meta/modality.json").read_bytes()).hexdigest(),
stats_sha256=hashlib.sha256((dst / "meta/stats.json").read_bytes()).hexdigest())
(dst / "hb-dataset-receipt.json").write_text(json.dumps(receipt, indent=2) + "\n")
print("DATASET_OK", json.dumps(receipt)[:400], flush=True)
for t in sys.argv[1:]:
build(t)
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