add support for libero2lerobot (#42)

* add libero2lerobot readme * use datatrove for libero2lerobot * update libero2lerobot readme * update README.md * Update libero2lerobot/README.md Co-authored-by: gemini-code-assist[bot] <176961590+gemini-code-assist[bot]@users.noreply.github.com> * Update libero2lerobot/README.md Co-authored-by: gemini-code-assist[bot] <176961590+gemini-code-assist[bot]@users.noreply.github.com> * fix * set upload_large_folder to false * use vectorized operations for faster transform --------- Co-authored-by: gemini-code-assist[bot] <176961590+gemini-code-assist[bot]@users.noreply.github.com>
2026-07-25 04:55:58 +00:00 · 2025-06-27 11:36:25 +08:00
parent e7ee6a0052
commit 4dc21b9b70
8 changed files with 932 additions and 1 deletions
@@ -0,0 +1,36 @@
+from pathlib import Path
+
+import numpy as np
+from h5py import File
+
+
+def load_local_episodes(input_h5: Path):
+    with File(input_h5, "r") as f:
+        for demo in f["data"].values():
+            demo_len = len(demo["obs/agentview_rgb"])
+            # (-1: open, 1: close) -> (0: close, 1: open)
+            action = np.array(demo["actions"])
+            action = np.concatenate(
+                [
+                    action[:, :6],
+                    (1 - np.clip(action[:, -1], 0, 1))[:, None],
+                ],
+                axis=1,
+            )
+            state = np.concatenate(
+                [
+                    np.array(demo["obs/ee_states"]),
+                    np.array(demo["obs/gripper_states"]),
+                ],
+                axis=1,
+            )
+            episode = {
+                "observation.images.image": np.array(demo["obs/agentview_rgb"]),
+                "observation.images.wrist_image": np.array(demo["obs/eye_in_hand_rgb"]),
+                "observation.state": np.array(state, dtype=np.float32),
+                "observation.states.ee_state": np.array(demo["obs/ee_states"], dtype=np.float32),
+                "observation.states.joint_state": np.array(demo["obs/joint_states"], dtype=np.float32),
+                "observation.states.gripper_state": np.array(demo["obs/gripper_states"], dtype=np.float32),
+                "action": np.array(action, dtype=np.float32),
+            }
+            yield [{**{k: v[i] for k, v in episode.items()}} for i in range(demo_len)]