Add 9 verified datacell UMI episodes (hot drinks, wash-up, vanity, desk tidy, phone stand)

.gitattributes

@@ -124,3 +124,57 @@ site/media/ego_starcap11_0622-1621_seg_07/left.mp4 filter=lfs diff=lfs merge=lfs
 site/media/ego_starcap11_0622-1621_seg_07/right.mp4 filter=lfs diff=lfs merge=lfs -text
 site/media/ego_starcap18_0710-2139_seg_03/left.mp4 filter=lfs diff=lfs merge=lfs -text
 site/media/ego_starcap18_0710-2139_seg_03/right.mp4 filter=lfs diff=lfs merge=lfs -text
+site/media/umi_desktidy_ep0/base0.mp4 filter=lfs diff=lfs merge=lfs -text
+site/media/umi_desktidy_ep0/base1.mp4 filter=lfs diff=lfs merge=lfs -text
+site/media/umi_desktidy_ep0/depthL.mp4 filter=lfs diff=lfs merge=lfs -text
+site/media/umi_desktidy_ep0/depthR.mp4 filter=lfs diff=lfs merge=lfs -text
+site/media/umi_desktidy_ep0/wristL.mp4 filter=lfs diff=lfs merge=lfs -text
+site/media/umi_desktidy_ep0/wristR.mp4 filter=lfs diff=lfs merge=lfs -text
+site/media/umi_desktidy_ep1/base0.mp4 filter=lfs diff=lfs merge=lfs -text
+site/media/umi_desktidy_ep1/base1.mp4 filter=lfs diff=lfs merge=lfs -text
+site/media/umi_desktidy_ep1/depthL.mp4 filter=lfs diff=lfs merge=lfs -text
+site/media/umi_desktidy_ep1/depthR.mp4 filter=lfs diff=lfs merge=lfs -text
+site/media/umi_desktidy_ep1/wristL.mp4 filter=lfs diff=lfs merge=lfs -text
+site/media/umi_desktidy_ep1/wristR.mp4 filter=lfs diff=lfs merge=lfs -text
+site/media/umi_hotdrinks_ep0/base0.mp4 filter=lfs diff=lfs merge=lfs -text
+site/media/umi_hotdrinks_ep0/base1.mp4 filter=lfs diff=lfs merge=lfs -text
+site/media/umi_hotdrinks_ep0/depthL.mp4 filter=lfs diff=lfs merge=lfs -text
+site/media/umi_hotdrinks_ep0/depthR.mp4 filter=lfs diff=lfs merge=lfs -text
+site/media/umi_hotdrinks_ep0/wristL.mp4 filter=lfs diff=lfs merge=lfs -text
+site/media/umi_hotdrinks_ep0/wristR.mp4 filter=lfs diff=lfs merge=lfs -text
+site/media/umi_hotdrinks_ep1/base0.mp4 filter=lfs diff=lfs merge=lfs -text
+site/media/umi_hotdrinks_ep1/base1.mp4 filter=lfs diff=lfs merge=lfs -text
+site/media/umi_hotdrinks_ep1/depthL.mp4 filter=lfs diff=lfs merge=lfs -text
+site/media/umi_hotdrinks_ep1/depthR.mp4 filter=lfs diff=lfs merge=lfs -text
+site/media/umi_hotdrinks_ep1/wristL.mp4 filter=lfs diff=lfs merge=lfs -text
+site/media/umi_hotdrinks_ep1/wristR.mp4 filter=lfs diff=lfs merge=lfs -text
+site/media/umi_phonestand_ep0/base0.mp4 filter=lfs diff=lfs merge=lfs -text
+site/media/umi_phonestand_ep0/base1.mp4 filter=lfs diff=lfs merge=lfs -text
+site/media/umi_phonestand_ep0/depthL.mp4 filter=lfs diff=lfs merge=lfs -text
+site/media/umi_phonestand_ep0/depthR.mp4 filter=lfs diff=lfs merge=lfs -text
+site/media/umi_phonestand_ep0/wristL.mp4 filter=lfs diff=lfs merge=lfs -text
+site/media/umi_phonestand_ep0/wristR.mp4 filter=lfs diff=lfs merge=lfs -text
+site/media/umi_vanity_ep0/base0.mp4 filter=lfs diff=lfs merge=lfs -text
+site/media/umi_vanity_ep0/base1.mp4 filter=lfs diff=lfs merge=lfs -text
+site/media/umi_vanity_ep0/depthL.mp4 filter=lfs diff=lfs merge=lfs -text
+site/media/umi_vanity_ep0/depthR.mp4 filter=lfs diff=lfs merge=lfs -text
+site/media/umi_vanity_ep0/wristL.mp4 filter=lfs diff=lfs merge=lfs -text
+site/media/umi_vanity_ep0/wristR.mp4 filter=lfs diff=lfs merge=lfs -text
+site/media/umi_vanity_ep1/base0.mp4 filter=lfs diff=lfs merge=lfs -text
+site/media/umi_vanity_ep1/base1.mp4 filter=lfs diff=lfs merge=lfs -text
+site/media/umi_vanity_ep1/depthL.mp4 filter=lfs diff=lfs merge=lfs -text
+site/media/umi_vanity_ep1/depthR.mp4 filter=lfs diff=lfs merge=lfs -text
+site/media/umi_vanity_ep1/wristL.mp4 filter=lfs diff=lfs merge=lfs -text
+site/media/umi_vanity_ep1/wristR.mp4 filter=lfs diff=lfs merge=lfs -text
+site/media/umi_washup_ep0/base0.mp4 filter=lfs diff=lfs merge=lfs -text
+site/media/umi_washup_ep0/base1.mp4 filter=lfs diff=lfs merge=lfs -text
+site/media/umi_washup_ep0/depthL.mp4 filter=lfs diff=lfs merge=lfs -text
+site/media/umi_washup_ep0/depthR.mp4 filter=lfs diff=lfs merge=lfs -text
+site/media/umi_washup_ep0/wristL.mp4 filter=lfs diff=lfs merge=lfs -text
+site/media/umi_washup_ep0/wristR.mp4 filter=lfs diff=lfs merge=lfs -text
+site/media/umi_washup_ep1/base0.mp4 filter=lfs diff=lfs merge=lfs -text
+site/media/umi_washup_ep1/base1.mp4 filter=lfs diff=lfs merge=lfs -text
+site/media/umi_washup_ep1/depthL.mp4 filter=lfs diff=lfs merge=lfs -text
+site/media/umi_washup_ep1/depthR.mp4 filter=lfs diff=lfs merge=lfs -text
+site/media/umi_washup_ep1/wristL.mp4 filter=lfs diff=lfs merge=lfs -text
+site/media/umi_washup_ep1/wristR.mp4 filter=lfs diff=lfs merge=lfs -text

build/build_assets.py

@@ -261,9 +261,9 @@ def imu_series(repo, seg, ft, f0, nframes, fps_src=60):
 
 def imu_block(imu):
     return [
-        {"group": "Head IMU · accel (m/s²)", "names": ["ax", "ay", "az"],
+        {"group": "Head IMU · accel (m/s²)", "names": ["ax", "ay", "az"],
          "values": [r3(imu["ax_ms2"], 2), r3(imu["ay_ms2"], 2), r3(imu["az_ms2"], 2)]},
-        {"group": "Head IMU · gyro (°/s)", "names": ["gx", "gy", "gz"],
+        {"group": "Head IMU · gyro (°/s)", "names": ["gx", "gy", "gz"],
          "values": [r3(imu["gx_dps"], 1), r3(imu["gy_dps"], 1), r3(imu["gz_dps"], 1)]},
     ]
 
@@ -325,9 +325,9 @@ def build_ego():
         ep = {
             "id": ep_id, "embodiment": "ego", "title": g, **ego_meta(L), "duration": EGO_DUR, "fps": 30,
             "source": {"repo": EGO_REPO, "path": seg, "t0": round(t0, 2)},
-            "specs": ["Head-mounted stereo", "1920×1200 @ 60 fps per eye", "IMU 600 Hz", "Faces blurred"],
-            "streams": [stream(ep_id, "left", "Head · stereo left", 960, 600),
-                        stream(ep_id, "right", "Head · stereo right", 960, 600)],
+            "specs": ["Head-mounted stereo", "1920×1200 @ 60 fps per eye", "IMU 600 Hz", "Faces blurred"],
+            "streams": [stream(ep_id, "left", "Head · stereo left", 960, 600),
+                        stream(ep_id, "right", "Head · stereo right", 960, 600)],
             "series": imu_block(imu),
         }
         write_episode(ep)
@@ -451,10 +451,10 @@ def build_hands():
             "source": {"repo": HANDS_REPO, "path": seg, "t0": round(t0, 2)},
             "specs": ["Head-mounted stereo", "21-joint MANO hands (2D + 3D)", "Per-frame, both hands", "IMU 600 Hz"],
             "tracking": {"any_hand": round(sum(1 for f in kp if f) / n, 3), "both_hands": round(sum(1 for f in kp if len(f) >= 2) / n, 3)},
-            "streams": [stream(ep_id, "left", "Head · stereo left + hand pose", 960, 600)],
+            "streams": [stream(ep_id, "left", "Head · stereo left + hand pose", 960, 600)],
             "hands": kp,
             "series": [
-                {"group": "Thumb–index aperture (cm)", "names": ["left hand", "right hand"],
+                {"group": "Thumb–index aperture (cm)", "names": ["left hand", "right hand"],
                  "values": [[None if v is None else round(v, 2) for v in aper[False]],
                             [None if v is None else round(v, 2) for v in aper[True]]]},
                 {"group": "Hands detected", "names": ["count"], "values": [[len(f) for f in kp]]},
@@ -498,75 +498,104 @@ UMI_SETS = [
     ("starpilot-ai/cell1_20260513_electronics-packing_esp-cable-2bb-jumpersmf-ff-dcy-dc_unpacking",
      "Electronics unpacking", "ESP32, USB cable, 2 breadboards, jumper wires, DC components", [0, 7]),
     ("starpilot-ai/cell1_20260518_electronics-packing_2esp-cable-bb-jumpersmm-2dcy_unpacking_unfolding",
-     "Electronics unpacking", "2× ESP32, USB cable, breadboard, jumper wires", [0]),
+     "Electronics unpacking", "2× ESP32, USB cable, breadboard, jumper wires", [0]),
 ]
 UMI_DUR = 30.0
-UMI_CAMS = [("observation.images.base_0_camera_rgb_image", "base0", "Scene camera 0", "rgb"),
+# Datacell episodes re-published by build/publish_datacells.py (one public repo per task cycle). Each one's task
+# label was checked by eye against its frames; keep `title` identical to that episode's task in the repo.
+# (repo, episode, id, title = verified sub-task, sector, setting, station = the cycle)
+DATACELL_UMI = [
+    ("starpilot-ai/YAMGripper_Cafe_HotDrinks", 0, "umi_hotdrinks_ep0", "Pour the drink into the cup",
+     "Food service", "Coffee & tea station", "Make & serve hot drinks"),
+    ("starpilot-ai/YAMGripper_Cafe_HotDrinks", 1, "umi_hotdrinks_ep1", "Add sugar and cream, stir",
+     "Food service", "Coffee & tea station", "Make & serve hot drinks"),
+    ("starpilot-ai/YAMGripper_Kitchen_WashUp", 0, "umi_washup_ep0", "Wash the pot and mugs",
+     "Kitchen", "Kitchen counter (sink-free)", "Wash up after cooking"),
+    ("starpilot-ai/YAMGripper_Kitchen_WashUp", 1, "umi_washup_ep1", "Wipe the counter and hang the towel",
+     "Kitchen", "Kitchen counter (sink-free)", "Wash up after cooking"),
+    ("starpilot-ai/YAMGripper_Bathroom_VanityRestock", 0, "umi_vanity_ep0", "Clear the used items",
+     "Hospitality", "Bathroom vanity", "Restock the vanity"),
+    ("starpilot-ai/YAMGripper_Bathroom_VanityRestock", 1, "umi_vanity_ep1", "Arrange the counter",
+     "Hospitality", "Bathroom vanity", "Restock the vanity"),
+    ("starpilot-ai/YAMGripper_Office_DeskTidy", 0, "umi_desktidy_ep0", "Sort the paper stacks",
+     "Office", "Office desk", "Tidy & rearrange the office desk"),
+    ("starpilot-ai/YAMGripper_Office_DeskTidy", 1, "umi_desktidy_ep1", "Pencils in the cup",
+     "Office", "Office desk", "Tidy & rearrange the office desk"),
+    ("starpilot-ai/YAMGripper_Office_PhoneStand", 0, "umi_phonestand_ep0", "Set up the phone",
+     "Office", "Office desk", "Set up the phone stand"),
+]
+DATACELL_DUR = 60.0   # the whole episode was label-checked, so a longer window stays on-task
+UMI_CAMS =[("observation.images.base_0_camera_rgb_image", "base0", "Scene camera 0", "rgb"),
             ("observation.images.base_1_camera_rgb_image", "base1", "Scene camera 1", "rgb"),
-            ("observation.images.left_wrist_0_camera_rgb_image", "wristL", "Left gripper · wrist RGB", "rgb"),
-            ("observation.images.right_wrist_0_camera_rgb_image", "wristR", "Right gripper · wrist RGB", "rgb"),
-            ("observation.images.left_wrist_0_camera_rgb_image_depth", "depthL", "Left gripper · wrist depth", "depth"),
-            ("observation.images.right_wrist_0_camera_rgb_image_depth", "depthR", "Right gripper · wrist depth", "depth")]
+            ("observation.images.left_wrist_0_camera_rgb_image", "wristL", "Left gripper · wrist RGB", "rgb"),
+            ("observation.images.right_wrist_0_camera_rgb_image", "wristR", "Right gripper · wrist RGB", "rgb"),
+            ("observation.images.left_wrist_0_camera_rgb_image_depth", "depthL", "Left gripper · wrist depth", "depth"),
+            ("observation.images.right_wrist_0_camera_rgb_image_depth", "depthR", "Right gripper · wrist depth", "depth")]
 
 
 def build_umi():
-    for repo, title, kit, ep_list in UMI_SETS:
-        for e in ep_list:
-            info, row, data = lerobot_episode(repo, e)
-            ep_id = f"umi_{repo.split('_')[1]}_ep{e}"
-            n_all = len(data)
-            dur = min(UMI_DUR, n_all / 30 - 0.5)
-            f0 = max(0, int(n_all / 2 - dur * 15))
-            out = os.path.join(SITE, "media", ep_id)
-            streams = []
-            for key, short, label, kind in UMI_CAMS:
-                src, from_ts = lerobot_video(repo, row, key)
-                cut(src, os.path.join(out, short + ".mp4"), from_ts + f0 / 30, dur, 480)
-                streams.append(stream(ep_id, short, label, 480, 360, kind))
-            poster(os.path.join(out, "base0.mp4"), os.path.join(out, "poster.jpg"))
-            n = int(dur * 30)
-            d = data.iloc[f0:f0 + n]
-            S, A = stack(d, "observation.state"), stack(d, "action")
-            names = info["features"]["observation.state"]["names"]
-            ix = {nm: i for i, nm in enumerate(names)}
-            pk = "pose_abs" if "arm1_pose_abs_x" in ix else "pose"   # older cell1 exports have no *_abs
-            p1 = S[:, [ix[f"arm1_{pk}_{a}"] for a in "xyz"]]
-            p2 = S[:, [ix[f"arm2_{pk}_{a}"] for a in "xyz"]]
-            ep = {
-                "id": ep_id, "embodiment": "umi", "title": title, "sector": "Electronics assembly",
-                "setting": "Electronics kitting cell", "station": kit, "role": "Kitting operator",
-                "duration": round(n / 30, 2), "fps": 30,
-                "source": {"repo": repo, "episode": e, "frame0": f0},
-                "specs": ["2× parallel-jaw handheld gripper", "Wrist RGB + depth per gripper", "2 fixed scene cameras",
-                          "Gripper encoder + IMU", "6-DoF EE pose", "LeRobot v3.0"],
-                "streams": streams,
-                "series": [
-                    {"group": "Gripper width (cm) · action", "names": ["left", "right"],
-                     "values": [r3(A[:, 6] * 100, 2), r3(A[:, 13] * 100, 2)]},
-                    {"group": "Left EE position (m)", "names": ["x", "y", "z"], "values": [r3(p1[:, i]) for i in range(3)]},
-                    {"group": "Right EE position (m)", "names": ["x", "y", "z"], "values": [r3(p2[:, i]) for i in range(3)]},
-                    {"group": "Gripper IMU · gyro (rad/s)", "names": ["L gx", "L gy", "L gz"],
-                     "values": [r3(S[:, ix[f"arm1_imu_g{a}"]], 2) for a in "xyz"]},
-                ],
-                "traj3d": {"tracks": [{"name": "left gripper", "color": "#4aa3ff", "xyz": r3(p1)},
-                                      {"name": "right gripper", "color": "#ff5fa2", "xyz": r3(p2)}]},
-                "schema": {"state_dim": len(names), "action_dim": len(info["features"]["action"]["names"]),
-                           "action_names": info["features"]["action"]["names"]},
-            }
-            write_episode(ep)
-            add_index(ep)
-            print("  [umi]", ep_id)
+    jobs = [(repo, e, f"umi_{repo.split('_')[1]}_ep{e}", UMI_DUR,
+             {"title": title, "sector": "Electronics assembly", "setting": "Electronics kitting cell", "station": kit,
+              "role": "Kitting operator"})
+            for repo, title, kit, ep_list in UMI_SETS for e in ep_list]
+    jobs += [(repo, e, ep_id, DATACELL_DUR,
+              {"title": title, "sector": sector, "setting": setting, "station": station, "role": None})
+             for repo, e, ep_id, title, sector, setting, station in DATACELL_UMI]
+    for repo, e, ep_id, max_dur, meta in jobs:
+        info, row, data = lerobot_episode(repo, e)
+        n_all = len(data)
+        dur = min(max_dur, n_all / 30 - 0.5)
+        f0 = max(0, int(n_all / 2 - dur * 15))
+        out = os.path.join(SITE, "media", ep_id)
+        streams = []
+        for key, short, label, kind in UMI_CAMS:
+            src, from_ts = lerobot_video(repo, row, key)
+            cut(src, os.path.join(out, short + ".mp4"), from_ts + f0 / 30, dur, 480)
+            streams.append(stream(ep_id, short, label, 480, 360, kind))
+        poster(os.path.join(out, "base0.mp4"), os.path.join(out, "poster.jpg"))
+        n = int(dur * 30)
+        d = data.iloc[f0:f0 + n]
+        S, A = stack(d, "observation.state"), stack(d, "action")
+        names = info["features"]["observation.state"]["names"]
+        ix = {nm: i for i, nm in enumerate(names)}
+        pk = "pose_abs" if "arm1_pose_abs_x" in ix else "pose"   # older cell1 exports have no *_abs
+        p1 = S[:, [ix[f"arm1_{pk}_{a}"] for a in "xyz"]]
+        p2 = S[:, [ix[f"arm2_{pk}_{a}"] for a in "xyz"]]
+        n_scene = sum(k.startswith("observation.images.base_") for k in info["features"])
+        ep = {
+            "id": ep_id, "embodiment": "umi", **meta,
+            "duration": round(n / 30, 2), "fps": 30,
+            "source": {"repo": repo, "episode": e, "frame0": f0},
+            "specs": ["2× parallel-jaw handheld gripper", "Wrist RGB + depth per gripper", f"{n_scene} fixed scene cameras",
+                      "Gripper encoder + IMU", "6-DoF EE pose", "LeRobot v3.0"],
+            "streams": streams,
+            "series": [
+                {"group": "Gripper width (cm) · action", "names": ["left", "right"],
+                 "values": [r3(A[:, 6] * 100, 2), r3(A[:, 13] * 100, 2)]},
+                {"group": "Left EE position (m)", "names": ["x", "y", "z"], "values": [r3(p1[:, i]) for i in range(3)]},
+                {"group": "Right EE position (m)", "names": ["x", "y", "z"], "values": [r3(p2[:, i]) for i in range(3)]},
+                {"group": "Gripper IMU · gyro (rad/s)", "names": ["L gx", "L gy", "L gz"],
+                 "values": [r3(S[:, ix[f"arm1_imu_g{a}"]], 2) for a in "xyz"]},
+            ],
+            "traj3d": {"tracks": [{"name": "left gripper", "color": "#4aa3ff", "xyz": r3(p1)},
+                                  {"name": "right gripper", "color": "#ff5fa2", "xyz": r3(p2)}]},
+            "schema": {"state_dim": len(names), "action_dim": len(info["features"]["action"]["names"]),
+                       "action_names": info["features"]["action"]["names"]},
+        }
+        write_episode(ep)
+        add_index(ep)
+        print("  [umi]", ep_id)
 
 
 # ----------------------------------------------------------------------------------- mobile UMI (v2)
 MOBILE_SETS = [("starpilot-ai/mobile_umi_test_2", 0), ("starpilot-ai/mobile_umi_test_2", 1),
                ("starpilot-ai/mobile_umi_test", 0)]
-# The head stereo is mounted on its side: transpose=2 (90° CCW) turns it upright (checked against gravity
+# The head stereo is mounted on its side: transpose=2 (90° CCW) turns it upright (checked against gravity
 # from the head pose: world-up projects onto image +x). Wrist cameras are already upright.
-MOBILE_CAMS = [("observation.images.stereo_left", "stereoL", "Head · stereo left (175°)", "transpose=2"),
-               ("observation.images.stereo_right", "stereoR", "Head · stereo right (175°)", "transpose=2"),
-               ("observation.images.wrist_A", "wristA", "Gripper A (left) · wrist", None),
-               ("observation.images.wrist_B", "wristB", "Gripper B (right) · wrist", None)]
+MOBILE_CAMS = [("observation.images.stereo_left", "stereoL", "Head · stereo left (175°)", "transpose=2"),
+               ("observation.images.stereo_right", "stereoR", "Head · stereo right (175°)", "transpose=2"),
+               ("observation.images.wrist_A", "wristA", "Gripper A (left) · wrist", None),
+               ("observation.images.wrist_B", "wristB", "Gripper B (right) · wrist", None)]
 
 
 def build_mobile():
@@ -595,15 +624,15 @@ def build_mobile():
             "id": ep_id, "embodiment": "mobile_umi", "title": title, "sector": "Mobile manipulation",
             "setting": "Body-worn rig, untethered", "station": task, "role": None,
             "duration": round(n / 30, 2), "fps": 30, "source": {"repo": repo, "episode": e},
-            "specs": ["Head stereo 175° FOV + 2 wrist cameras", "Untethered: no external tracking",
+            "specs": ["Head stereo 175° FOV + 2 wrist cameras", "Untethered: no external tracking",
                       "Head pose from stereo VIO", "Gripper 6-DoF from ArUco cubes + IMU", "Jaw opening from finger markers",
                       "LeRobot v3.0"],
             "streams": streams,
             "series": [
-                {"group": "Gripper opening (0–1)", "names": ["A (left)", "B (right)"], "values": [r3(oa), r3(ob)]},
+                {"group": "Gripper opening (0–1)", "names": ["A (left)", "B (right)"], "values": [r3(oa), r3(ob)]},
                 {"group": "Gripper speed (m/s)", "names": ["A (left)", "B (right)"], "values": [r3(speed, 3), r3(speed_b, 3)]},
                 {"group": "Head position, world (m)", "names": ["x", "y", "z"], "values": [r3(head[:, i]) for i in range(3)]},
-                {"group": "Wrist IMU A · gyro (rad/s)", "names": ["gx", "gy", "gz"], "values": [r3(ia[:, 3 + i], 2) for i in range(3)]},
+                {"group": "Wrist IMU A · gyro (rad/s)", "names": ["gx", "gy", "gz"], "values": [r3(ia[:, 3 + i], 2) for i in range(3)]},
             ],
             "traj3d": {"tracks": [{"name": "head", "color": "#39d0c0", "xyz": r3(head[:, :3]), "quat": r3(head[:, 3:7], 4)},
                                   {"name": "gripper A", "color": "#4aa3ff", "xyz": r3(ga[:, :3])},

build/publish_datacells.py

@@ -0,0 +1,298 @@
+#!/usr/bin/env python3
+"""Publish hand-verified datacell (YAM gripper / UMI) episodes as small PUBLIC LeRobot v3 datasets.
+
+Source: the private nodogoro/datacells-data repo (HF token from the datacells dashboard /api/hf-token).
+Only episodes listed in PUBLIC_SETS are copied. Every one was reviewer-verified on the datacells /review page
+AND its task label was checked by eye against its frames (scene + both wrist cameras) on 2026-10-20 — the
+recorded sub-task is inferred from episode order and was wrong for some episodes, so never add an episode
+here without looking at it.
+
+What is deliberately NOT copied: __upload_info.md, custom_metadata.csv (operator names / ids), pose_status.csv.
+The README is generated here; nothing names operators or customers.
+
+    python build/publish_datacells.py            # stage into <cache>/public_datacells/<name>/
+    python build/publish_datacells.py --upload   # stage, then create + upload the public repos
+"""
+import argparse
+import json
+import os
+import re
+import subprocess
+import urllib.request
+
+import numpy as np
+import pandas as pd
+
+SRC_REPO = "nodogoro/datacells-data"
+DASH = "https://starpilot-datacells-eight.vercel.app"
+ORG = "starpilot-ai"
+
+ap = argparse.ArgumentParser()
+ap.add_argument("--cache", default="D:/sampler_cache")
+ap.add_argument("--upload", action="store_true")
+ap.add_argument("--force", action="store_true")
+args = ap.parse_args()
+SRC_CACHE = os.path.join(args.cache, "datacells")
+OUT_ROOT = os.path.join(args.cache, "public_datacells")
+
+# name -> (title, scene, [(source leaf, episode index, verified sub-task)])
+PUBLIC_SETS = {
+    "YAMGripper_Cafe_HotDrinks": ("Make & serve hot drinks", "Coffee & tea station", [
+        ("Cell-04/2026-07-19/make_serve_different_hot_drinks_c33_george_20260719-130047-223", 0,
+         "Pour the drink into the cup"),
+        ("Cell-04/2026-07-18/make_serve_different_hot_drinks_c33_aprem_20260718-135029-634", 1,
+         "Add sugar and cream, stir"),
+    ]),
+    "YAMGripper_Kitchen_WashUp": ("Wash up after cooking", "Kitchen counter (sink-free)", [
+        ("Cell-05/2026-07-19/wash_up_after_cooking_sink_free_c34_hesham_20260719-103836-028", 0,
+         "Wash the pot and mugs"),
+        ("Cell-05/2026-07-19/wash_up_after_cooking_sink_free_c34_hesham_20260719-101309-504", 2,
+         "Wipe the counter and hang the towel"),
+    ]),
+    "YAMGripper_Bathroom_VanityRestock": ("Restock the vanity", "Bathroom vanity", [
+        ("Cell-01/2026-07-18/restock_the_vanity_c36_george_20260718-130559-579", 0, "Clear the used items"),
+        ("Cell-01/2026-07-19/restock_the_vanity_c36_mohamed_salah_20260719-131028-421", 2, "Arrange the counter"),
+    ]),
+    "YAMGripper_Office_DeskTidy": ("Tidy & rearrange the office desk", "Office desk", [
+        ("Cell-03/2026-07-18/tidy_rearrange_the_office_desk_c37_abdelrhman_yasser_20260718-220158-811", 0,
+         "Sort the paper stacks"),
+        ("Cell-03/2026-07-18/tidy_rearrange_the_office_desk_c37_abdelrhman_yasser_20260718-213321-066", 1,
+         "Pencils in the cup"),
+    ]),
+    "YAMGripper_Office_PhoneStand": ("Set up the phone stand", "Office desk", [
+        ("Cell-02/2026-07-19/set_up_tear_down_the_phone_stand_desk_b_c38_abdo_20260719-205223-781", 0,
+         "Set up the phone"),
+    ]),
+}
+
+
+# ---------------------------------------------------------------------------------------- source access
+def hf_token():
+    req = urllib.request.Request(f"{DASH}/api/hf-token", data=b"{}", headers={
+        "X-Datacell-Password": os.environ.get("DATA_CELL_PASSWORD", "starchild"), "Content-Type": "application/json"})
+    return json.loads(urllib.request.urlopen(req, timeout=30).read())["token"]
+
+
+TOK = hf_token()
+
+
+def fetch(path):
+    """Download one file of the private source repo once into the cache; return the local path."""
+    local = os.path.join(SRC_CACHE, path)
+    if os.path.exists(local):
+        return local
+    os.makedirs(os.path.dirname(local), exist_ok=True)
+    req = urllib.request.Request(f"https://huggingface.co/datasets/{SRC_REPO}/resolve/main/{path}",
+                                 headers={"Authorization": f"Bearer {TOK}"})
+    with urllib.request.urlopen(req, timeout=600) as r, open(local + ".part", "wb") as f:
+        while chunk := r.read(1 << 20):
+            f.write(chunk)
+    os.replace(local + ".part", local)
+    return local
+
+
+def source_episode(leaf, e):
+    info = json.load(open(fetch(f"{leaf}/meta/info.json")))
+    eps = pd.read_parquet(fetch(f"{leaf}/meta/episodes/chunk-000/file-000.parquet"))
+    row = eps[eps.episode_index == e].iloc[0]
+    data = pd.read_parquet(fetch(f"{leaf}/data/chunk-{int(row['data/chunk_index']):03d}/"
+                                 f"file-{int(row['data/file_index']):03d}.parquet"))
+    data = data[data.episode_index == e].sort_values("frame_index").reset_index(drop=True)
+    return info, row, data
+
+
+def run(*cmd):
+    r = subprocess.run(cmd, capture_output=True, text=True)
+    if r.returncode:
+        raise RuntimeError(" ".join(cmd) + "\n" + r.stderr[-2000:])
+    return r.stdout
+
+
+def n_frames(mp4):
+    return int(run("ffprobe", "-v", "error", "-count_frames", "-select_streams", "v:0",
+                   "-show_entries", "stream=nb_read_frames", "-of", "csv=p=0", mp4).strip())
+
+
+# ----------------------------------------------------------------------------------------------- stats
+def dense(v):
+    """Parquet hands nested lists back as object arrays of arrays (image stats are 3x1x1); make them float."""
+    if isinstance(v, np.ndarray) and v.dtype == object:
+        return np.stack([dense(x) for x in v])
+    return np.asarray(v, dtype=float)
+
+
+def agg_stats(eps):
+    """Dataset stats.json from the per-episode stats/* columns, combined the way LeRobot aggregates them."""
+    out = {}
+    feats = sorted({c.split("/")[1] for c in eps.columns if c.startswith("stats/")})
+    for f in feats:
+        g = lambda s: [dense(v) for v in eps[f"stats/{f}/{s}"]]
+        cnt = np.array([float(np.asarray(c).ravel()[0]) for c in eps[f"stats/{f}/count"]])
+        w = cnt / cnt.sum()
+        mean = sum(wi * m for wi, m in zip(w, g("mean")))
+        var = sum(wi * (s ** 2 + (m - mean) ** 2) for wi, s, m in zip(w, g("std"), g("mean")))
+        st = {"min": np.min(g("min"), axis=0), "max": np.max(g("max"), axis=0), "mean": mean, "std": np.sqrt(var),
+              "count": np.array([cnt.sum()])}
+        for q in ["q01", "q10", "q50", "q90", "q99"]:
+            if f"stats/{f}/{q}" in eps.columns:
+                st[q] = sum(wi * v for wi, v in zip(w, g(q)))
+        out[f] = {k: (v.astype(int) if k == "count" else v).tolist() for k, v in st.items()}
+    return out
+
+
+# ----------------------------------------------------------------------------------------------- build
+def readme(name, title, scene, info, eps_meta, episodes):
+    hours = sum(int(r["length"]) for r in eps_meta) / info["fps"]
+    cams = [k.replace("observation.images.", "") for k, v in info["features"].items() if v["dtype"] == "video"]
+    lines = "\n".join(f"| {i} | {task} | {int(r['length']) / info['fps']:.1f} s |"
+                      for i, ((_, _, task), r) in enumerate(zip(episodes, eps_meta)))
+    return f"""---
+license: cc-by-4.0
+task_categories:
+- robotics
+tags:
+- LeRobot
+- umi
+- manipulation
+- bimanual
+configs:
+- config_name: default
+  data_files: data/*/*.parquet
+---
+
+# {title}
+
+Bimanual handheld-gripper (UMI-style) demonstrations recorded by Starpilot in a {scene.lower()} data cell.
+A human operator holds two instrumented parallel-jaw grippers; every episode is one sub-task of the
+"{title}" cycle.
+
+Each episode was checked by a reviewer and its task label confirmed against the video.
+
+| Episode | Task | Duration |
+|---|---|---|
+{lines}
+
+Total: {len(eps_meta)} episode(s), {hours:.0f} s at {info['fps']} fps.
+
+## Sensors
+
+- 2 handheld parallel-jaw grippers, each with a wrist RGB camera + an aligned depth stream, gripper encoder and IMU
+- {sum(c.startswith('base_') for c in cams)} fixed scene cameras
+- 6-DoF pose of each gripper (`arm*_pose_*` relative, `arm*_pose_abs_*` absolute), gripper opening and width
+
+Video streams: {", ".join(f"`{c}`" for c in cams)} (640x480, H.264).
+
+`observation.state` (46-dim) and `action` (14-dim: per gripper xyz + rotation vector + grip width) names are in
+`meta/info.json`.
+
+## Format
+
+[LeRobot](https://github.com/huggingface/lerobot) dataset, codebase v3.0 (`robot_type: starpilot_yam_gripper`).
+
+Explore clips from this and our other datasets at
+https://huggingface.co/spaces/starpilot-ai/starpilot-data-sample. More data: https://starpilot.ai
+"""
+
+
+def build(name, title, scene, episodes):
+    out = os.path.join(OUT_ROOT, name)
+    if os.path.exists(os.path.join(out, "meta", "info.json")) and not args.force:
+        print("[skip]", name)
+        return out
+    os.makedirs(os.path.join(out, "meta", "episodes", "chunk-000"), exist_ok=True)
+    os.makedirs(os.path.join(out, "data", "chunk-000"), exist_ok=True)
+    datas, eps_meta, info0 = [], [], None
+    tasks = list(dict.fromkeys(t for _, _, t in episodes))
+    g = 0
+    for i, (leaf, e, task) in enumerate(episodes):
+        info, row, data = source_episode(leaf, e)
+        if info0 is None:
+            info0 = info
+        assert info["features"] == info0["features"], f"{leaf}: schema differs within {name}"
+        n = len(data)
+        assert n == int(row["length"]), (leaf, e, n, row["length"])
+        d = data.copy()
+        d["episode_index"] = i
+        d["index"] = np.arange(g, g + n)
+        d["task_index"] = tasks.index(task)
+        datas.append(d)
+        m = row.to_dict()
+        m.update({"episode_index": i, "tasks": [task], "data/chunk_index": 0, "data/file_index": 0,
+                  "dataset_from_index": g, "dataset_to_index": g + n})
+        # one video file per episode per camera: frame-exact re-encode of exactly this episode's frames
+        for k, v in info["features"].items():
+            if v["dtype"] != "video":
+                continue
+            vk = f"videos/{k}"
+            src = fetch(f"{leaf}/{vk}/chunk-{int(row[vk + '/chunk_index']):03d}/file-{int(row[vk + '/file_index']):03d}.mp4")
+            dst = os.path.join(out, vk, "chunk-000", f"file-{i:03d}.mp4")
+            os.makedirs(os.path.dirname(dst), exist_ok=True)
+            crf = "12" if v["info"].get("video.is_depth_map") or k.endswith("_depth") else "18"
+            run("ffmpeg", "-hide_banner", "-loglevel", "error", "-y", "-ss", f"{float(row[vk + '/from_timestamp']):.6f}",
+                "-i", src, "-frames:v", str(n), "-an", "-c:v", "libx264", "-preset", "slow", "-crf", crf,
+                "-pix_fmt", "yuv420p", "-g", "30", "-movflags", "+faststart", dst + ".tmp.mp4")
+            os.replace(dst + ".tmp.mp4", dst)
+            got = n_frames(dst)
+            assert got == n, f"{dst}: {got} frames, expected {n}"
+            m.update({f"{vk}/chunk_index": 0, f"{vk}/file_index": i, f"{vk}/from_timestamp": 0.0,
+                      f"{vk}/to_timestamp": n / info["fps"]})
+        eps_meta.append(m)
+        g += n
+        print(f"  [{name}] ep{i} <- {leaf.split('/')[0]} #{e}  {n} frames  '{task}'")
+    pd.concat(datas, ignore_index=True).to_parquet(os.path.join(out, "data", "chunk-000", "file-000.parquet"), index=False)
+    em = pd.DataFrame(eps_meta)
+    em.to_parquet(os.path.join(out, "meta", "episodes", "chunk-000", "file-000.parquet"), index=False)
+    pd.DataFrame({"task_index": range(len(tasks))}, index=pd.Index(tasks, name="task")).to_parquet(
+        os.path.join(out, "meta", "tasks.parquet"))
+    info = dict(info0)
+    info.update({"total_episodes": len(episodes), "total_frames": g, "total_tasks": len(tasks),
+                 "splits": {"train": f"0:{len(episodes)}"}})
+    json.dump(info, open(os.path.join(out, "meta", "info.json"), "w"), indent=4)
+    json.dump(agg_stats(em), open(os.path.join(out, "meta", "stats.json"), "w"), indent=4)
+    open(os.path.join(out, "README.md"), "w", encoding="utf-8").write(readme(name, title, scene, info, eps_meta, episodes))
+    return out
+
+
+# ------------------------------------------------------------------------------------- publish guards
+# Text that must never appear in anything we publish: operator names (from the source leaf names) and
+# customer references.
+OPERATORS = {"george", "aprem", "hesham", "mohamed", "salah", "abdelrhman", "yasser", "abdo"}
+BANNED = re.compile(r"\bpi\b|\bpi[-_ ]|physical.?intelligence|" + "|".join(OPERATORS), re.I)
+
+
+def audit(out):
+    """Scan every text field we wrote (README, json, parquet strings/column names) for banned text."""
+    bad = []
+    for root, _, files in os.walk(out):
+        for f in files:
+            p = os.path.join(root, f)
+            if f.endswith((".md", ".json")):
+                txt = open(p, encoding="utf-8").read()
+            elif f.endswith(".parquet"):
+                df = pd.read_parquet(p)
+                txt = " ".join(map(str, df.columns)) + " " + " ".join(
+                    str(v) for c in df.columns if df[c].dtype == object for v in df[c].head(10000))
+                txt += " " + " ".join(map(str, df.index))
+            else:
+                continue
+            bad += [(p, m.group(0)) for m in BANNED.finditer(txt)]
+    return bad
+
+
+outs = {name: build(name, *spec) for name, spec in PUBLIC_SETS.items()}
+problems = [b for o in outs.values() for b in audit(o)]
+for p in problems:
+    print("BANNED TEXT:", p)
+if problems:
+    raise SystemExit("refusing to continue: banned text found")
+print("audit clean:", ", ".join(outs))
+
+if args.upload:
+    from huggingface_hub import HfApi
+    # huggingface_hub's default lookup misses this machine's token file, so read it explicitly
+    api = HfApi(token=os.environ.get("HF_TOKEN") or open(os.path.expanduser("~/.cache/huggingface/token")).read().strip())
+    for name, out in outs.items():
+        repo = f"{ORG}/{name}"
+        api.create_repo(repo, repo_type="dataset", private=False, exist_ok=True)
+        api.upload_folder(repo_id=repo, repo_type="dataset", folder_path=out, commit_message="Publish verified episodes")
+        print("[uploaded]", f"https://huggingface.co/datasets/{repo}")

site/app.js

@@ -1,562 +1,567 @@
-// Starpilot Sampler: landing page + LeRobot-style episode explorer. No build step; three.js only for the 3D panel.
-
-const EMB = {
-  ego: {
-    name: "Ego", long: "Egocentric video", color: "var(--ego)", hex: "#2dd4bf",
-    blurb: "A head-mounted stereo camera worn through a full shift of real work.",
-    bullets: ["Stereo 1920×1200 @ 60 fps", "Head IMU @ 600 Hz", "Industrial sector, setting & task labels", "Faces blurred"],
-  },
-  hands: {
-    name: "Ego + hands", long: "Ego with 3D hand pose", color: "var(--hands)", hex: "#a78bfa",
-    blurb: "The same ego video with per-frame 21-joint MANO hand pose for both hands.",
-    bullets: ["2D + 3D keypoints, both hands", "MANO pose & shape parameters", "Grasp aperture derivable per frame", "Stereo + IMU, as ego"],
-  },
-  umi: {
-    name: "UMI", long: "Handheld parallel-jaw grippers", color: "var(--umi)", hex: "#4aa3ff",
-    blurb: "Bimanual handheld grippers with the same jaw geometry as the target robot, in an instrumented cell.",
-    bullets: ["Wrist RGB + depth on each gripper", "2 fixed scene cameras", "6-DoF EE pose + jaw width", "Gripper encoder + IMU"],
-  },
-  mobile_umi: {
-    name: "Mobile UMI", long: "Multi-embodiment grippers and mobile-UMI", color: "var(--mobile_umi)", hex: "#f5a524",
-    blurb: "Body-worn and fully untethered. On-board stereo SLAM localises the head and both grippers anywhere.",
-    bullets: ["Head stereo 175° + 2 wrist cams", "No mocap or base stations", "Head + gripper 6-DoF, world frame", "Dense SLAM map per take"],
-  },
-};
-const EMB_ORDER = ["ego", "hands", "umi", "mobile_umi"];
-// Episode shown on each embodiment card (and first in the hero mosaic); otherwise the first in the list.
-const FEATURED = { ego: "ego_starcap28_0714-0024_seg_00" };
-// Technical spec per embodiment. Sources: dataset cards + meta/info.json on HF, the recorder's frames.csv/imu.csv
-// format, Starpilot_gripper_recorder README (UMI sensors), mobile_umi_test_2 README (mobile UMI timing/frames).
-const SPECS = {
-  ego: [
-    ["Camera", "Head-mounted stereo pair"],
-    ["Video", "1920×1200 per eye · 60 fps"],
-    ["Timing", "Per-frame exposure start/end timestamps on the camera clock"],
-    ["IMU", "6-axis (accel m/s², gyro °/s) · 600 Hz · ~10 samples per frame, on the same clock as the exposures"],
-    ["Labels", "Industry → setting → station taxonomy, job role, difficulty, quality score"],
-    ["Privacy", "Faces blurred per frame"],
-    ["Files", "left.mp4 · right.mp4 · frames.csv · imu.csv · labels.json, in 5–10 min segments"],
-  ],
-  hands: [
-    ["Base", "Ego stereo video + 600 Hz IMU, as Ego"],
-    ["Hand model", "MANO, 21 joints, both hands, left/right labelled"],
-    ["Per frame", "2D keypoints (px) · 3D joints (m, hand frame) · global orientation · 45-D articulation · 10-D shape β · camera translation · bbox"],
-    ["Rate", "Every video frame (60 fps)"],
-    ["Derived", "Grasp aperture (thumb–index distance, cm), hand presence"],
-    ["Coverage", "Clips shown here: ≥90% of frames tracked"],
-    ["Files", "hands.jsonl next to the ego files"],
-  ],
-  umi: [
-    ["Grippers", "2 handheld parallel-jaw grippers, 0–82 mm stroke"],
-    ["Wrist camera", "Intel RealSense D405 per gripper · RGB + depth 640×480 · 30 fps · depth 50–550 mm"],
-    ["Scene cameras", "2 fixed RGB · 640×480 · 30 fps"],
-    ["EE pose", "HTC Vive tracker (Lighthouse) · 6-DoF per gripper · episode-relative SE(3)"],
-    ["Gripper", "Jaw encoder ~100 Hz · jaw width (m)"],
-    ["IMU", "6-axis per gripper · ~100 Hz"],
-    ["Action", "14-D: per arm, EE delta translation + rotation vector in the previous EE frame + absolute jaw width"],
-    ["Format", "LeRobot v3.0 · 30 fps · 32-D state"],
-  ],
-  mobile_umi: [
-    ["Head camera", "Stereo 175° FOV · 2 × 1920×1200 · 60 fps · 60.2 mm baseline · KB4 fisheye calibration"],
-    ["Wrist cameras", "1 per gripper · 1920×1200 · 60 fps · 6-axis IMU"],
-    ["Timing", "Per-frame exposure timestamps · cross-camera alignment p50 1.4 ms, p95 3.2 ms"],
-    ["Head pose", "Stereo visual odometry · gravity-aligned world frame (m)"],
-    ["Gripper pose", "6-DoF from stereo-triangulated ArUco cubes, gaps bridged by wrist IMU, gyro-fused orientation"],
-    ["Jaw opening", "Finger-marker tracking in the wrist camera, 0–1"],
-    ["Map", "Dense coloured point cloud from stereo depth, ICP-refined"],
-    ["Format", "LeRobot v3.0 · 30 fps · 23-D state"],
-  ],
-};
-// Source datasets for the Download section (sizes from the HF API, 2026-10-09).
-const DATASETS = [
-  { emb: "ego", repo: "starpilot-ai/ego_sample_v0.1.3", size: "1.8 TB", what: "876 ego segments: stereo video, IMU, labels", tip: "Large: the command fetches one segment per recording; drop --include for everything" },
-  { emb: "hands", repo: "starpilot-ai/handTrackingSample", size: "157 GB", what: "120 ego segments with per-frame MANO hand pose", tip: "Large: the command fetches one segment per recording; drop --include for everything" },
-  { emb: "umi", repo: "starpilot-ai/cell1_20260512_electronics-packing_esp-cable-2servoblue-bb-jumpersff-mm-prototypeboar", size: "1.1 GB", what: "Electronics kitting · 5 episodes · LeRobot v3", lerobot: true },
-  { emb: "umi", repo: "starpilot-ai/cell1_20260513_electronics-packing_esp-cable-2bb-jumpersmf-ff-dcy-dc_unpacking", size: "0.97 GB", what: "Electronics unpacking · 8 episodes · LeRobot v3", lerobot: true },
-  { emb: "umi", repo: "starpilot-ai/cell1_20260518_electronics-packing_2esp-cable-bb-jumpersmm-2dcy_unpacking_unfolding", size: "84 MB", what: "Electronics unpacking · 1 episode · LeRobot v3", lerobot: true },
-  { emb: "mobile_umi", repo: "starpilot-ai/mobile_umi_test_2", size: "63 MB", what: "Pouring + folding · 2 episodes · LeRobot v3", lerobot: true },
-  { emb: "mobile_umi", repo: "starpilot-ai/mobile_umi_test", size: "73 MB", what: "Bench task · 1 episode · LeRobot v3", lerobot: true },
-];
-const dlCmd = (repo, include) => `hf download ${repo} --repo-type dataset${include ? ` --include "${include}"` : ""} --local-dir ${repo.split("/")[1]}`;
-function copyBox(text) {
-  const btn = h("button", { class: "copy", onclick: async () => {
-    try { await navigator.clipboard.writeText(text); btn.textContent = "Copied"; } catch { btn.textContent = "Select + copy"; }
-    setTimeout(() => (btn.textContent = "Copy"), 1500);
-  } }, "Copy");
-  return h("div", { class: "cmd" }, h("code", {}, text), btn);
-}
-
-const HAND_CHAINS = [[0, 1, 2, 3, 4], [0, 5, 6, 7, 8], [0, 9, 10, 11, 12], [0, 13, 14, 15, 16], [0, 17, 18, 19, 20], [5, 9, 13, 17]];
-const XYZ = ["#ff6b6b", "#51cf66", "#4dabf7"];
-
-const $ = (s, el = document) => el.querySelector(s);
-const h = (tag, attrs = {}, ...kids) => {
-  const el = document.createElement(tag);
-  for (const [k, v] of Object.entries(attrs)) {
-    if (k === "style" && typeof v === "object") for (const [sk, sv] of Object.entries(v)) sk.startsWith("--") ? el.style.setProperty(sk, sv) : (el.style[sk] = sv);
-    else if (k.startsWith("on")) el.addEventListener(k.slice(2), v);
-    else if (v !== null && v !== undefined && v !== false) el.setAttribute(k, v === true ? "" : v);
-  }
-  for (const kid of kids.flat()) if (kid !== null && kid !== undefined) el.append(kid.nodeType ? kid : document.createTextNode(kid));
-  return el;
-};
-const fmtT = (t) => `${Math.floor(t / 60)}:${(t % 60).toFixed(2).padStart(5, "0")}`;
-
-let INDEX = null;
-const epCache = new Map();
-const getEp = (id) => {
-  if (!epCache.has(id)) epCache.set(id, fetch(`data/episodes/${id}.json`).then((r) => r.json()));
-  return epCache.get(id);
-};
-
-// ------------------------------------------------------------------------------------------ router
-let cleanup = [];
-function route() {
-  cleanup.forEach((f) => f());
-  cleanup = [];
-  const raw = location.hash.slice(1) || "/";
-  const [pathQ, anchor] = raw.split("#");
-  const [path, qs] = pathQ.split("?");
-  const q = new URLSearchParams(qs || "");
-  if (path.startsWith("/explore")) renderExplore(q);
-  else renderLanding(anchor);
-}
-window.addEventListener("hashchange", route);
-
-// --------------------------------------------------------------------------------------- hand overlay
-function drawHands(canvas, frame) {
-  const dpr = window.devicePixelRatio || 1;
-  const W = canvas.clientWidth, H = canvas.clientHeight;
-  if (canvas.width !== Math.round(W * dpr) || canvas.height !== Math.round(H * dpr)) {
-    canvas.width = Math.round(W * dpr); canvas.height = Math.round(H * dpr);
-  }
-  const ctx = canvas.getContext("2d");
-  ctx.setTransform(dpr, 0, 0, dpr, 0, 0);
-  ctx.clearRect(0, 0, W, H);
-  if (!frame) return;
-  const lw = Math.max(1.5, W / 420);
-  for (const hand of frame) {
-    const k = hand.k, col = hand.r ? "#ff5fa2" : "#4aa3ff";
-    const P = (i) => [k[2 * i] * W, k[2 * i + 1] * H];
-    ctx.strokeStyle = col; ctx.lineWidth = lw; ctx.lineJoin = ctx.lineCap = "round";
-    ctx.shadowColor = "rgba(0,0,0,.6)"; ctx.shadowBlur = 3;
-    for (const ch of HAND_CHAINS) {
-      ctx.beginPath();
-      ch.forEach((j, n) => { const [x, y] = P(j); n ? ctx.lineTo(x, y) : ctx.moveTo(x, y); });
-      ctx.stroke();
-    }
-    ctx.shadowBlur = 0;
-    for (let j = 0; j < 21; j++) {
-      const [x, y] = P(j);
-      ctx.beginPath(); ctx.arc(x, y, j % 4 === 0 && j ? lw * 1.6 : lw * 1.1, 0, 7);
-      ctx.fillStyle = j % 4 === 0 && j ? "#fff" : col; ctx.fill();
-    }
-  }
-}
-
-// ---------------------------------------------------------------------------------------- landing
-function renderLanding(anchor) {
-  const app = $("#app");
-  app.replaceChildren($("#tpl-landing").content.cloneNode(true));
-  const eps = INDEX.episodes, st = INDEX.stats;
-  const byEmb = Object.fromEntries(EMB_ORDER.map((e) => [e, eps.filter((x) => x.embodiment === e)
-    .sort((a, b) => (b.id === FEATURED[e]) - (a.id === FEATURED[e]) || ((b.tracking?.any_hand || 0) + (b.tracking?.both_hands || 0)) - ((a.tracking?.any_hand || 0) + (a.tracking?.both_hands || 0)))]));
-
-  // hero mosaic: interleave embodiments
-  const mosaic = $("#mosaic");
-  const picks = [];
-  for (let i = 0; picks.length < 12 && i < 20; i++)
-    for (const e of ["ego", "umi", "hands", "mobile_umi"]) if (byEmb[e][i] && picks.length < 12) picks.push(byEmb[e][i]);
-  for (const ep of picks) mosaic.append(h("video", { src: ep.preview, muted: true, autoplay: true, loop: true, playsinline: true, preload: "auto" }));
-  mosaic.querySelectorAll("video").forEach((v) => { v.muted = true; v.play().catch(() => {}); });
-
-  // stats
-  const settings = new Set(eps.map((e) => e.setting));
-  const statRows = [
-    [`${st.ego_hours} h`, "ego video in the public sample"],
-    [st.ego_environments, "distinct environments"],
-    [st.ego_cameras, "capture rigs in the field"],
-    [settings.size, "industrial settings shown here"],
-    [4, "embodiments, one schema"],
-    [eps.length, "episodes to explore"],
-  ];
-  $("#stats").append(...statRows.map(([v, k]) => h("div", { class: "stat" }, h("div", { class: "v" }, String(v)), h("div", { class: "k" }, k))));
-
-  // embodiment cards
-  const grid = $("#emb-grid");
-  EMB_ORDER.forEach((e, i) => {
-    const m = EMB[e], first = byEmb[e][0];
-    const vid = first ? h("video", { src: first.preview, muted: true, autoplay: true, loop: true, playsinline: true }) : h("div");
-    const canvas = h("canvas");
-    const card = h("a", { class: "emb-card", href: `#/explore?emb=${e}`, style: { "--c": m.color } },
-      h("div", { class: "media" }, vid, canvas, h("span", { class: "num" }, `0${i + 1} · ${byEmb[e].length} episodes`)),
-      h("div", { class: "body" },
-        h("h3", {}, m.long),
-        h("p", {}, m.blurb),
-        h("ul", {}, ...m.bullets.map((b) => h("li", {}, b))),
-        h("span", { class: "go" }, `Explore ${m.name} →`)));
-    grid.append(card);
-    if (vid.tagName === "VIDEO") { vid.muted = true; vid.play().catch(() => {}); }
-    if (e === "hands" && first) {
-      getEp(first.id).then((ep) => {
-        let raf;
-        const loop = () => { drawHands(canvas, ep.hands[Math.min(ep.hands.length - 1, Math.floor(vid.currentTime * ep.fps))]); raf = requestAnimationFrame(loop); };
-        loop();
-        cleanup.push(() => cancelAnimationFrame(raf));
-      });
-    }
-  });
-
-  // full-corpus numbers for the contact block (filled from data/corpus.json; hidden if absent)
-  fetch("data/corpus.json").then((r) => (r.ok ? r.json() : null)).then((c) => {
-    if (c?.stats?.length) $("#big-stats").append(...c.stats.map(([v, k]) => h("div", {}, h("div", { class: "v" }, v), h("div", { class: "k" }, k))));
-  }).catch(() => {});
-
-  // download cards
-  $("#dl-grid").append(...DATASETS.map((d) => h("div", { class: "dl", style: { "--c": EMB[d.emb].color } },
-    h("div", { class: "dl-top" },
-      h("span", { class: "badge emb", style: { "--c": EMB[d.emb].color } }, EMB[d.emb].name),
-      h("span", { class: "dl-size" }, d.size)),
-    h("a", { class: "dl-name", href: `https://huggingface.co/datasets/${d.repo}`, target: "_blank", rel: "noopener" }, d.repo.replace("starpilot-ai/", "")),
-    h("div", { class: "dl-what" }, d.what),
-    copyBox(d.lerobot ? dlCmd(d.repo) : dlCmd(d.repo, "*/seg_00/*")),
-    d.tip && h("div", { class: "dl-tip" }, d.tip),
-    h("a", { class: "btn ghost sm", href: `https://huggingface.co/datasets/${d.repo}/tree/main`, target: "_blank", rel: "noopener" }, "⬇ Browse & download files"))));
-
-  // sensor spec sheets
-  $("#spec-grid").append(...EMB_ORDER.map((e) => h("div", { class: "spec", style: { "--c": EMB[e].color } },
-    h("div", { class: "spec-head" }, h("span", { class: "dot" }), EMB[e].long),
-    h("dl", {}, ...SPECS[e].flatMap(([k, v]) => [h("dt", {}, k), h("dd", {}, v)])))));
-
-  // sector chips
-  const bySetting = new Map();
-  for (const e of eps) {
-    if (!bySetting.has(e.setting)) bySetting.set(e.setting, new Set());
-    bySetting.get(e.setting).add(e.embodiment);
-  }
-  const counts = eps.reduce((m, e) => m.set(e.setting, (m.get(e.setting) || 0) + 1), new Map());
-  $("#sectors").append(...[...bySetting.entries()].sort((a, b) => counts.get(b[0]) - counts.get(a[0])).map(([s, embs]) =>
-    h("a", { class: "chip", href: `#/explore?q=${encodeURIComponent(s)}` },
-      h("span", { class: "sw" }, ...EMB_ORDER.filter((e) => embs.has(e)).map((e) => h("i", { style: { background: EMB[e].color } }))),
-      s, h("span", { class: "n" }, String(counts.get(s))))));
-
-  const repos = [...new Set(eps.map((e) => e.source?.repo).filter(Boolean))];
-  $("#foot-sources").append("Sources: ", ...repos.flatMap((r, i) => [i ? " · " : "", h("a", { href: `https://huggingface.co/datasets/${r}`, target: "_blank", rel: "noopener" }, r.replace("starpilot-ai/", ""))]));
-
-  if (anchor) requestAnimationFrame(() => document.getElementById(anchor)?.scrollIntoView());
-  else window.scrollTo(0, 0);
-  cleanup.push(() => app.querySelectorAll("video").forEach((v) => { v.pause(); v.removeAttribute("src"); v.load(); }));
-}
-
-// ---------------------------------------------------------------------------------------- explorer
-function renderExplore(q) {
-  const app = $("#app");
-  let shell = $(".explore", app);
-  if (!shell) {
-    app.replaceChildren($("#tpl-explore").content.cloneNode(true));
-    shell = $(".explore", app);
-  }
-  window.scrollTo(0, 0);
-  const emb = q.get("emb") || "all";
-  const text = (q.get("q") || "").toLowerCase();
-  const sel = q.get("ep");
-
-  const tabs = $("#emb-tabs");
-  tabs.replaceChildren(...["all", ...EMB_ORDER].map((e) =>
-    h("button", { class: "tab" + (e === emb ? " on" : ""), onclick: () => nav({ emb: e, q: $("#search").value }) },
-      e === "all" ? "All" : [h("i", { style: { background: EMB[e].color } }), EMB[e].name])));
-  const search = $("#search");
-  if (document.activeElement !== search) search.value = q.get("q") || "";
-  search.oninput = () => { clearTimeout(search._t); search._t = setTimeout(() => nav({ emb, q: search.value }, true), 200); };
-
-  const list = INDEX.episodes.filter((e) => (emb === "all" || e.embodiment === emb) &&
-    (!text || [e.title, e.sector, e.setting, e.id].join(" ").toLowerCase().includes(text)));
-  const L = $("#ep-list");
-  L.replaceChildren();
-  for (const e of EMB_ORDER) {
-    const items = list.filter((x) => x.embodiment === e);
-    if (!items.length) continue;
-    L.append(h("div", { class: "ep-group" }, `${EMB[e].long} · ${items.length}`));
-    for (const it of items)
-      L.append(h("a", { class: "ep-item" + (it.id === (sel || list[0]?.id) ? " on" : ""), href: link({ emb, q: q.get("q"), ep: it.id }), style: { "--c": EMB[e].color } },
-        h("img", { src: it.poster, loading: "lazy", alt: "" }),
-        h("div", {}, h("div", { class: "t" }, it.title), h("div", { class: "s" }, `${it.sector} · ${it.duration}s · ${it.n_streams} cam`))));
-  }
-  const cur = list.find((e) => e.id === sel) || list[0];
-  const viewer = $("#viewer");
-  if (!cur) { viewer.replaceChildren(h("div", { class: "empty" }, "No episodes match.")); return; }
-  $(".ep-item.on", L)?.scrollIntoView({ block: "nearest" });
-  renderEpisode(viewer, cur.id);
-}
-const link = (o) => "#/explore?" + new URLSearchParams(Object.entries(o).filter(([, v]) => v && v !== "all")).toString();
-function nav(o, replace) {
-  const u = link(o);
-  if (replace) history.replaceState(null, "", u), route(); else location.hash = u.slice(1);
-}
-
-async function renderEpisode(viewer, id) {
-  viewer.replaceChildren(h("div", { class: "empty" }, "Loading…"));
-  const ep = await getEp(id);
-  const m = EMB[ep.embodiment];
-  const src = ep.source || {};
-  const srcHref = `https://huggingface.co/datasets/${src.repo}` + (src.path ? `/tree/main/${src.path}` : "");
-  const srcTxt = src.path ? `${src.path} @ ${src.t0}s` : `episode ${src.episode}` + (src.frame0 ? ` @ frame ${src.frame0}` : "");
-
-  const portrait = ep.streams.some((s) => s.h > s.w);
-  const cams = h("div", { class: `cams n${Math.min(ep.streams.length, 3)}` + (portrait ? " portrait" : "") });
-  const videos = [], overlays = [];
-  for (const s of ep.streams) {
-    const v = h("video", { src: s.src, muted: true, playsinline: true, preload: "auto" });
-    v.muted = true;
-    const box = h("div", { class: "cam", style: { aspectRatio: `${s.w}/${s.h}` } }, v, h("span", { class: "lbl" }, s.label));
-    if (ep.hands && s.key === "left") { const c = h("canvas"); box.append(c); overlays.push(c); }
-    videos.push(v); cams.append(box);
-  }
-
-  const playBtn = h("button", {}, "❚❚ Pause");
-  const scrub = h("input", { type: "range", min: 0, max: ep.duration, step: 1 / ep.fps, value: 0 });
-  const timeEl = h("span", { class: "time" });
-  const speeds = [0.5, 1, 2].map((r) => h("button", { class: r === 1 ? "on" : "", onclick: (ev) => {
-    videos.forEach((v) => (v.playbackRate = r));
-    speeds.forEach((b) => b.classList.toggle("on", b === ev.currentTarget));
-  } }, `${r}×`));
-  const controls = h("div", { class: "controls" }, playBtn, scrub, ...speeds, timeEl);
-
-  // download menu: the clips shown here + the full-resolution source on Hugging Face
-  const dlFiles = [...ep.streams.map((s) => [`${s.label} · clip (mp4)`, s.src, `${ep.id}_${s.key}.mp4`]),
-    ["Signals + metadata (json)", `data/episodes/${ep.id}.json`, `${ep.id}.json`]];
-  const srcCmd = src.path ? dlCmd(src.repo, `${src.path}/*`) : dlCmd(src.repo);
-  const dlPanel = h("div", { class: "dl-pop", hidden: true },
-    h("div", { class: "dl-pop-h" }, "This clip"),
-    ...dlFiles.map(([label, href, name]) => h("a", { href, download: name }, "⬇ ", label)),
-    h("div", { class: "dl-pop-h" }, src.path ? "Full-resolution source segment" : `Full source dataset (episode ${src.episode})`),
-    copyBox(srcCmd),
-    h("a", { href: srcHref, target: "_blank", rel: "noopener" }, "Open on Hugging Face ↗"));
-  const dlBtn = h("button", { class: "dl-btn", onclick: (e) => { e.stopPropagation(); dlPanel.hidden = !dlPanel.hidden; } }, "⬇ Download");
-  const dlWrap = h("div", { class: "dl-wrap" }, dlBtn, dlPanel);
-  const closeDl = (e) => { if (!dlWrap.contains(e.target)) dlPanel.hidden = true; };
-  document.addEventListener("click", closeDl);
-  cleanup.push(() => document.removeEventListener("click", closeDl));
-
-  const panels = h("div", { class: "panels" });
-  const charts = (ep.series || []).map((g) => new Chart(g, ep, (t) => seek(t)));
-  let three = null;
-  if (ep.traj3d) {
-    const div = h("div", { class: "three" });
-    panels.append(h("div", { class: "panel p3d" },
-      h("h4", {}, "3D trajectories", h("span", { class: "legend" }, ...ep.traj3d.tracks.map((t) => h("span", {}, h("i", { style: { background: t.color } }), t.name)))),
-      div, h("div", { class: "hint" }, "Drag to orbit · scroll to zoom · faint line = full episode, bright = last 2 s")));
-    three = await makeThree(div, ep);
-  }
-  charts.forEach((c) => panels.append(c.el));
-
-  viewer.replaceChildren(
-    h("div", { class: "v-head", style: { "--c": m.color } },
-      h("div", {},
-        h("h2", {}, ep.title),
-        h("div", { class: "badges" },
-          h("span", { class: "badge emb", style: { "--c": m.color } }, m.long),
-          ep.sector && h("span", { class: "badge" }, ep.sector),
-          ep.station && h("span", { class: "badge" }, ep.station),
-          ep.role && h("span", { class: "badge" }, ep.role),
-          ep.difficulty && h("span", { class: "badge" }, `difficulty: ${ep.difficulty}`))),
-      h("div", { class: "v-right" }, dlWrap,
-        h("div", { class: "v-src" }, "source ", h("a", { href: srcHref, target: "_blank", rel: "noopener" }, src.repo), h("br"), srcTxt))),
-    h("div", { class: "specs", style: { "--c": m.color } }, ...(ep.specs || []).map((s) => h("span", {}, s))),
-    cams, controls, panels);
-
-  // ---- sync engine: video 0 is the clock; the others are nudged when they drift
-  const master = videos[0];
-  let raf, dragging = false;
-  const seek = (t) => { videos.forEach((v) => (v.currentTime = t)); };
-  const play = () => { videos.forEach((v) => v.play().catch(() => {})); playBtn.textContent = "❚❚ Pause"; };
-  const pause = () => { videos.forEach((v) => v.pause()); playBtn.textContent = "▶ Play"; };
-  playBtn.onclick = () => (master.paused ? play() : pause());
-  scrub.oninput = () => { dragging = true; seek(+scrub.value); };
-  scrub.onchange = () => { dragging = false; };
-  master.addEventListener("ended", () => { seek(0); play(); });
-  const tick = () => {
-    const t = master.currentTime || 0;
-    if (!master.paused) for (const v of videos.slice(1)) if (Math.abs(v.currentTime - t) > 0.1 && v.readyState >= 2) v.currentTime = t;
-    if (!dragging) scrub.value = t;
-    const fi = Math.min(Math.floor(t * ep.fps), Math.round(ep.duration * ep.fps) - 1);
-    timeEl.textContent = `${fmtT(t)} · frame ${fi}`;
-    overlays.forEach((c) => drawHands(c, ep.hands[fi]));
-    charts.forEach((c) => c.draw(t));
-    three?.update(fi);
-    raf = requestAnimationFrame(tick);
-  };
-  tick();
-  play();
-  const onKey = (e) => {
-    if (e.target.tagName === "INPUT") return;
-    if (e.code === "Space") { e.preventDefault(); master.paused ? play() : pause(); }
-    if (e.code === "ArrowRight") seek(Math.min(ep.duration, master.currentTime + (e.shiftKey ? 1 / ep.fps : 1)));
-    if (e.code === "ArrowLeft") seek(Math.max(0, master.currentTime - (e.shiftKey ? 1 / ep.fps : 1)));
-  };
-  window.addEventListener("keydown", onKey);
-  cleanup.push(() => {
-    cancelAnimationFrame(raf); window.removeEventListener("keydown", onKey); three?.dispose();
-    videos.forEach((v) => { v.pause(); v.removeAttribute("src"); v.load(); });
-  });
-}
-
-// ----------------------------------------------------------------------------------------- charts
-class Chart {
-  constructor(g, ep, onSeek) {
-    this.g = g; this.ep = ep;
-    this.colors = g.names.map((n, i) => {
-      const s = n.toLowerCase();
-      if (/^(left|a\b|a \(|l )/.test(s) || s.startsWith("left")) return "#4aa3ff";
-      if (/^(right|b\b|b \(|r )/.test(s) || s.startsWith("right")) return "#ff5fa2";
-      if (g.names.length === 3) return XYZ[i];
-      return ["#f5a524", "#2dd4bf", "#a78bfa"][i % 3];
-    });
-    this.canvas = h("canvas", { class: "chart" });
-    this.val = g.names.map(() => h("b"));
-    this.el = h("div", { class: "panel" },
-      h("h4", {}, g.group, h("span", { class: "legend" }, ...g.names.map((n, i) => h("span", {}, h("i", { style: { background: this.colors[i] } }), `${n} `, this.val[i])))),
-      this.canvas);
-    let down = false;
-    const at = (e) => { const r = this.canvas.getBoundingClientRect(); onSeek(Math.max(0, Math.min(1, (e.clientX - r.left - 34) / (r.width - 40))) * ep.duration); };
-    this.canvas.addEventListener("pointerdown", (e) => { down = true; at(e); });
-    window.addEventListener("pointerup", () => (down = false));
-    this.canvas.addEventListener("pointermove", (e) => down && at(e));
-    let lo = Infinity, hi = -Infinity;
-    for (const s of g.values) for (const v of s) if (v !== null && Number.isFinite(v)) { lo = Math.min(lo, v); hi = Math.max(hi, v); }
-    if (!Number.isFinite(lo)) { lo = 0; hi = 1; }
-    if (hi - lo < 1e-6) { hi += 0.5; lo -= 0.5; }
-    const pad = (hi - lo) * 0.08;
-    this.lo = lo - pad; this.hi = hi + pad;
-  }
-  layout() {
-    const dpr = window.devicePixelRatio || 1, W = this.canvas.clientWidth, H = this.canvas.clientHeight;
-    if (this.W === W && this.H === H) return;
-    this.W = W; this.H = H;
-    this.canvas.width = Math.round(W * dpr); this.canvas.height = Math.round(H * dpr);
-    const off = (this.bg = document.createElement("canvas"));
-    off.width = this.canvas.width; off.height = this.canvas.height;
-    const c = off.getContext("2d");
-    c.setTransform(dpr, 0, 0, dpr, 0, 0);
-    const X0 = 34, X1 = W - 6, Y0 = 6, Y1 = H - 16;
-    Object.assign(this, { X0, X1, Y0, Y1 });
-    const y = (v) => Y1 - ((v - this.lo) / (this.hi - this.lo)) * (Y1 - Y0);
-    c.font = "10px JetBrains Mono, monospace"; c.fillStyle = "#6b7385"; c.strokeStyle = "#252b38"; c.lineWidth = 1;
-    for (let k = 0; k <= 3; k++) {
-      const v = this.lo + ((this.hi - this.lo) * k) / 3, yy = y(v);
-      c.beginPath(); c.moveTo(X0, yy); c.lineTo(X1, yy); c.stroke();
-      c.fillText(Math.abs(v) >= 100 ? v.toFixed(0) : v.toFixed(Math.abs(v) >= 10 ? 1 : 2), 0, yy + 3);
-    }
-    for (let s = 0; s <= this.ep.duration; s += this.ep.duration > 20 ? 5 : 2) c.fillText(`${s}s`, X0 + (s / this.ep.duration) * (X1 - X0) - 6, H - 3);
-    this.g.values.forEach((s, i) => {
-      c.strokeStyle = this.colors[i]; c.lineWidth = 1.4; c.beginPath();
-      let pen = false;
-      s.forEach((v, k) => {
-        if (v === null || !Number.isFinite(v)) { pen = false; return; }
-        const xx = X0 + (k / (s.length - 1)) * (X1 - X0);
-        pen ? c.lineTo(xx, y(v)) : c.moveTo(xx, y(v));
-        pen = true;
-      });
-      c.stroke();
-    });
-    this.y = y;
-  }
-  draw(t) {
-    this.layout();
-    const c = this.canvas.getContext("2d"), dpr = window.devicePixelRatio || 1;
-    c.setTransform(1, 0, 0, 1, 0, 0);
-    c.clearRect(0, 0, this.canvas.width, this.canvas.height);
-    c.drawImage(this.bg, 0, 0);
-    c.setTransform(dpr, 0, 0, dpr, 0, 0);
-    const x = this.X0 + (t / this.ep.duration) * (this.X1 - this.X0);
-    c.strokeStyle = "rgba(255,255,255,.75)"; c.lineWidth = 1;
-    c.beginPath(); c.moveTo(x, this.Y0); c.lineTo(x, this.Y1); c.stroke();
-    this.g.values.forEach((s, i) => {
-      const k = Math.min(s.length - 1, Math.round((t / this.ep.duration) * (s.length - 1)));
-      const v = s[k];
-      this.val[i].textContent = v === null || v === undefined ? "–" : (+v).toFixed(Math.abs(v) >= 100 ? 0 : 2);
-      if (v === null || !Number.isFinite(v)) return;
-      c.fillStyle = this.colors[i]; c.beginPath(); c.arc(x, this.y(v), 3, 0, 7); c.fill();
-    });
-  }
-}
-
-// --------------------------------------------------------------------------------------------- 3D
-async function makeThree(div, ep) {
-  const THREE = await import("three");
-  const { OrbitControls } = await import("three/addons/controls/OrbitControls.js");
-  const W = div.clientWidth || 400, H = div.clientHeight || 300;
-  const renderer = new THREE.WebGLRenderer({ antialias: true });
-  renderer.setPixelRatio(window.devicePixelRatio || 1);
-  renderer.setSize(W, H);
-  renderer.setClearColor(0x07090c);
-  div.append(renderer.domElement);
-  const scene = new THREE.Scene();
-  const cam = new THREE.PerspectiveCamera(45, W / H, 0.01, 100);
-  cam.up.set(0, 0, 1);
-
-  const all = ep.traj3d.tracks.flatMap((t) => t.xyz);
-  const c = [0, 1, 2].map((i) => all.reduce((s, p) => s + p[i], 0) / all.length);
-  const ext = Math.max(...[0, 1, 2].map((i) => Math.max(...all.map((p) => p[i])) - Math.min(...all.map((p) => p[i]))), 0.2);
-  const center = new THREE.Vector3(...c);
-
-  const grid = new THREE.GridHelper(ext * 3, 12, 0x2a3140, 0x1a1f29);
-  grid.rotation.x = Math.PI / 2;
-  grid.position.set(c[0], c[1], Math.min(...all.map((p) => p[2])) - 0.02);
-  scene.add(grid);
-  const axes = new THREE.AxesHelper(ext * 0.25);
-  axes.position.copy(grid.position);
-  scene.add(axes);
-
-  const tracks = ep.traj3d.tracks.map((t) => {
-    const col = new THREE.Color(t.color);
-    const pts = t.xyz.map((p) => new THREE.Vector3(...p));
-    const full = new THREE.Line(new THREE.BufferGeometry().setFromPoints(pts), new THREE.LineBasicMaterial({ color: col, transparent: true, opacity: 0.22 }));
-    const trailGeo = new THREE.BufferGeometry().setFromPoints(pts);
-    const trail = new THREE.Line(trailGeo, new THREE.LineBasicMaterial({ color: col }));
-    const dot = new THREE.Mesh(new THREE.SphereGeometry(ext * 0.022, 16, 12), new THREE.MeshBasicMaterial({ color: col }));
-    scene.add(full, trail, dot);
-    let frust = null;
-    if (t.quat) {
-      // camera frustum for the head (camera looks along +z, image y down)
-      const s = ext * 0.08, g = new THREE.BufferGeometry();
-      const P = [[0, 0, 0], [-s, -s * 0.6, s * 1.4], [s, -s * 0.6, s * 1.4], [s, s * 0.6, s * 1.4], [-s, s * 0.6, s * 1.4]];
-      const idx = [0, 1, 0, 2, 0, 3, 0, 4, 1, 2, 2, 3, 3, 4, 4, 1];
-      g.setAttribute("position", new THREE.Float32BufferAttribute(idx.flatMap((i) => P[i]), 3));
-      frust = new THREE.LineSegments(g, new THREE.LineBasicMaterial({ color: 0xffffff }));
-      scene.add(frust);
-    }
-    return { t, trail, trailGeo, dot, frust };
-  });
-
-  cam.position.copy(center).add(new THREE.Vector3(ext * 0.75, -ext * 0.95, ext * 0.7));
-  const controls = new OrbitControls(cam, renderer.domElement);
-  controls.target.copy(center);
-  controls.enableDamping = true;
-  controls.update();
-
-  const ro = new ResizeObserver(() => {
-    const w = div.clientWidth, hh = div.clientHeight;
-    if (!w) return;
-    renderer.setSize(w, hh); cam.aspect = w / hh; cam.updateProjectionMatrix();
-  });
-  ro.observe(div);
-  const q = new THREE.Quaternion();
-  return {
-    update(fi) {
-      for (const { t, trail, trailGeo, dot, frust } of tracks) {
-        const k = Math.max(0, Math.min(t.xyz.length - 1, fi));
-        dot.position.set(...t.xyz[k]);
-        const a = Math.max(0, k - ep.fps * 2);
-        trailGeo.setDrawRange(a, k - a + 1);
-        if (frust) { frust.position.set(...t.xyz[k]); q.set(...t.quat[k]); frust.quaternion.copy(q); }
-      }
-      controls.update();
-      renderer.render(scene, cam);
-    },
-    dispose() { ro.disconnect(); controls.dispose(); renderer.dispose(); },
-  };
-}
-
-// ------------------------------------------------------------------------------------------- boot
-fetch("data/index.json").then((r) => r.json()).then((j) => { INDEX = j; route(); });
+// Starpilot Sampler: landing page + LeRobot-style episode explorer. No build step; three.js only for the 3D panel.
+
+const EMB = {
+  ego: {
+    name: "Ego", long: "Egocentric video", color: "var(--ego)", hex: "#2dd4bf",
+    blurb: "A head-mounted stereo camera worn through a full shift of real work.",
+    bullets: ["Stereo 1920×1200 @ 60 fps", "Head IMU @ 600 Hz", "Industrial sector, setting & task labels", "Faces blurred"],
+  },
+  hands: {
+    name: "Ego + hands", long: "Ego with 3D hand pose", color: "var(--hands)", hex: "#a78bfa",
+    blurb: "The same ego video with per-frame 21-joint MANO hand pose for both hands.",
+    bullets: ["2D + 3D keypoints, both hands", "MANO pose & shape parameters", "Grasp aperture derivable per frame", "Stereo + IMU, as ego"],
+  },
+  umi: {
+    name: "UMI", long: "Handheld parallel-jaw grippers", color: "var(--umi)", hex: "#4aa3ff",
+    blurb: "Bimanual handheld grippers with the same jaw geometry as the target robot, in an instrumented cell.",
+    bullets: ["Wrist RGB + depth on each gripper", "2–4 fixed scene cameras", "6-DoF EE pose + jaw width", "Gripper encoder + IMU"],
+  },
+  mobile_umi: {
+    name: "Mobile UMI", long: "Multi-embodiment grippers and mobile-UMI", color: "var(--mobile_umi)", hex: "#f5a524",
+    blurb: "Body-worn and fully untethered. On-board stereo SLAM localises the head and both grippers anywhere.",
+    bullets: ["Head stereo 175° + 2 wrist cams", "No mocap or base stations", "Head + gripper 6-DoF, world frame", "Dense SLAM map per take"],
+  },
+};
+const EMB_ORDER = ["ego", "hands", "umi", "mobile_umi"];
+// Episode shown on each embodiment card (and first in the hero mosaic); otherwise the first in the list.
+const FEATURED = { ego: "ego_starcap28_0714-0024_seg_00" };
+// Technical spec per embodiment. Sources: dataset cards + meta/info.json on HF, the recorder's frames.csv/imu.csv
+// format, Starpilot_gripper_recorder README (UMI sensors), mobile_umi_test_2 README (mobile UMI timing/frames).
+const SPECS = {
+  ego: [
+    ["Camera", "Head-mounted stereo pair"],
+    ["Video", "1920×1200 per eye · 60 fps"],
+    ["Timing", "Per-frame exposure start/end timestamps on the camera clock"],
+    ["IMU", "6-axis (accel m/s², gyro °/s) · 600 Hz · ~10 samples per frame, on the same clock as the exposures"],
+    ["Labels", "Industry → setting → station taxonomy, job role, difficulty, quality score"],
+    ["Privacy", "Faces blurred per frame"],
+    ["Files", "left.mp4 · right.mp4 · frames.csv · imu.csv · labels.json, in 5–10 min segments"],
+  ],
+  hands: [
+    ["Base", "Ego stereo video + 600 Hz IMU, as Ego"],
+    ["Hand model", "MANO, 21 joints, both hands, left/right labelled"],
+    ["Per frame", "2D keypoints (px) · 3D joints (m, hand frame) · global orientation · 45-D articulation · 10-D shape β · camera translation · bbox"],
+    ["Rate", "Every video frame (60 fps)"],
+    ["Derived", "Grasp aperture (thumb–index distance, cm), hand presence"],
+    ["Coverage", "Clips shown here: ≥90% of frames tracked"],
+    ["Files", "hands.jsonl next to the ego files"],
+  ],
+  umi: [
+    ["Grippers", "2 handheld parallel-jaw grippers, 0–82 mm stroke"],
+    ["Wrist camera", "Intel RealSense D405 per gripper · RGB + depth 640×480 · 30 fps · depth 50–550 mm"],
+    ["Scene cameras", "2–4 fixed RGB · 640×480 �� 30 fps"],
+    ["EE pose", "HTC Vive tracker (Lighthouse) · 6-DoF per gripper · episode-relative SE(3)"],
+    ["Gripper", "Jaw encoder ~100 Hz · jaw width (m)"],
+    ["IMU", "6-axis per gripper · ~100 Hz"],
+    ["Action", "14-D: per arm, EE delta translation + rotation vector in the previous EE frame + absolute jaw width"],
+    ["Format", "LeRobot v3.0 · 30 fps · 32-D or 46-D state (46-D adds absolute EE pose)"],
+  ],
+  mobile_umi: [
+    ["Head camera", "Stereo 175° FOV · 2 × 1920×1200 · 60 fps · 60.2 mm baseline · KB4 fisheye calibration"],
+    ["Wrist cameras", "1 per gripper · 1920×1200 · 60 fps · 6-axis IMU"],
+    ["Timing", "Per-frame exposure timestamps · cross-camera alignment p50 1.4 ms, p95 3.2 ms"],
+    ["Head pose", "Stereo visual odometry · gravity-aligned world frame (m)"],
+    ["Gripper pose", "6-DoF from stereo-triangulated ArUco cubes, gaps bridged by wrist IMU, gyro-fused orientation"],
+    ["Jaw opening", "Finger-marker tracking in the wrist camera, 0–1"],
+    ["Map", "Dense coloured point cloud from stereo depth, ICP-refined"],
+    ["Format", "LeRobot v3.0 · 30 fps · 23-D state"],
+  ],
+};
+// Source datasets for the Download section (sizes from the HF API, 2026-10-09).
+const DATASETS = [
+  { emb: "ego", repo: "starpilot-ai/ego_sample_v0.1.3", size: "1.8 TB", what: "876 ego segments: stereo video, IMU, labels", tip: "Large: the command fetches one segment per recording; drop --include for everything" },
+  { emb: "hands", repo: "starpilot-ai/handTrackingSample", size: "157 GB", what: "120 ego segments with per-frame MANO hand pose", tip: "Large: the command fetches one segment per recording; drop --include for everything" },
+  { emb: "umi", repo: "starpilot-ai/cell1_20260512_electronics-packing_esp-cable-2servoblue-bb-jumpersff-mm-prototypeboar", size: "1.1 GB", what: "Electronics kitting · 5 episodes · LeRobot v3", lerobot: true },
+  { emb: "umi", repo: "starpilot-ai/cell1_20260513_electronics-packing_esp-cable-2bb-jumpersmf-ff-dcy-dc_unpacking", size: "0.97 GB", what: "Electronics unpacking · 8 episodes · LeRobot v3", lerobot: true },
+  { emb: "umi", repo: "starpilot-ai/cell1_20260518_electronics-packing_2esp-cable-bb-jumpersmm-2dcy_unpacking_unfolding", size: "84 MB", what: "Electronics unpacking · 1 episode · LeRobot v3", lerobot: true },
+  { emb: "umi", repo: "starpilot-ai/YAMGripper_Cafe_HotDrinks", size: "243 MB", what: "Make & serve hot drinks · 2 episodes · LeRobot v3", lerobot: true },
+  { emb: "umi", repo: "starpilot-ai/YAMGripper_Kitchen_WashUp", size: "388 MB", what: "Wash up after cooking · 2 episodes · LeRobot v3", lerobot: true },
+  { emb: "umi", repo: "starpilot-ai/YAMGripper_Bathroom_VanityRestock", size: "374 MB", what: "Restock the vanity · 2 episodes · LeRobot v3", lerobot: true },
+  { emb: "umi", repo: "starpilot-ai/YAMGripper_Office_DeskTidy", size: "266 MB", what: "Tidy the office desk · 2 episodes · LeRobot v3", lerobot: true },
+  { emb: "umi", repo: "starpilot-ai/YAMGripper_Office_PhoneStand", size: "209 MB", what: "Set up the phone stand · 1 episode · LeRobot v3", lerobot: true },
+  { emb: "mobile_umi", repo: "starpilot-ai/mobile_umi_test_2", size: "63 MB", what: "Pouring + folding · 2 episodes · LeRobot v3", lerobot: true },
+  { emb: "mobile_umi", repo: "starpilot-ai/mobile_umi_test", size: "73 MB", what: "Bench task · 1 episode · LeRobot v3", lerobot: true },
+];
+const dlCmd = (repo, include) => `hf download ${repo} --repo-type dataset${include ? ` --include "${include}"` : ""} --local-dir ${repo.split("/")[1]}`;
+function copyBox(text) {
+  const btn = h("button", { class: "copy", onclick: async () => {
+    try { await navigator.clipboard.writeText(text); btn.textContent = "Copied"; } catch { btn.textContent = "Select + copy"; }
+    setTimeout(() => (btn.textContent = "Copy"), 1500);
+  } }, "Copy");
+  return h("div", { class: "cmd" }, h("code", {}, text), btn);
+}
+
+const HAND_CHAINS = [[0, 1, 2, 3, 4], [0, 5, 6, 7, 8], [0, 9, 10, 11, 12], [0, 13, 14, 15, 16], [0, 17, 18, 19, 20], [5, 9, 13, 17]];
+const XYZ = ["#ff6b6b", "#51cf66", "#4dabf7"];
+
+const $ = (s, el = document) => el.querySelector(s);
+const h = (tag, attrs = {}, ...kids) => {
+  const el = document.createElement(tag);
+  for (const [k, v] of Object.entries(attrs)) {
+    if (k === "style" && typeof v === "object") for (const [sk, sv] of Object.entries(v)) sk.startsWith("--") ? el.style.setProperty(sk, sv) : (el.style[sk] = sv);
+    else if (k.startsWith("on")) el.addEventListener(k.slice(2), v);
+    else if (v !== null && v !== undefined && v !== false) el.setAttribute(k, v === true ? "" : v);
+  }
+  for (const kid of kids.flat()) if (kid !== null && kid !== undefined) el.append(kid.nodeType ? kid : document.createTextNode(kid));
+  return el;
+};
+const fmtT = (t) => `${Math.floor(t / 60)}:${(t % 60).toFixed(2).padStart(5, "0")}`;
+
+let INDEX = null;
+const epCache = new Map();
+const getEp = (id) => {
+  if (!epCache.has(id)) epCache.set(id, fetch(`data/episodes/${id}.json`).then((r) => r.json()));
+  return epCache.get(id);
+};
+
+// ------------------------------------------------------------------------------------------ router
+let cleanup = [];
+function route() {
+  cleanup.forEach((f) => f());
+  cleanup = [];
+  const raw = location.hash.slice(1) || "/";
+  const [pathQ, anchor] = raw.split("#");
+  const [path, qs] = pathQ.split("?");
+  const q = new URLSearchParams(qs || "");
+  if (path.startsWith("/explore")) renderExplore(q);
+  else renderLanding(anchor);
+}
+window.addEventListener("hashchange", route);
+
+// --------------------------------------------------------------------------------------- hand overlay
+function drawHands(canvas, frame) {
+  const dpr = window.devicePixelRatio || 1;
+  const W = canvas.clientWidth, H = canvas.clientHeight;
+  if (canvas.width !== Math.round(W * dpr) || canvas.height !== Math.round(H * dpr)) {
+    canvas.width = Math.round(W * dpr); canvas.height = Math.round(H * dpr);
+  }
+  const ctx = canvas.getContext("2d");
+  ctx.setTransform(dpr, 0, 0, dpr, 0, 0);
+  ctx.clearRect(0, 0, W, H);
+  if (!frame) return;
+  const lw = Math.max(1.5, W / 420);
+  for (const hand of frame) {
+    const k = hand.k, col = hand.r ? "#ff5fa2" : "#4aa3ff";
+    const P = (i) => [k[2 * i] * W, k[2 * i + 1] * H];
+    ctx.strokeStyle = col; ctx.lineWidth = lw; ctx.lineJoin = ctx.lineCap = "round";
+    ctx.shadowColor = "rgba(0,0,0,.6)"; ctx.shadowBlur = 3;
+    for (const ch of HAND_CHAINS) {
+      ctx.beginPath();
+      ch.forEach((j, n) => { const [x, y] = P(j); n ? ctx.lineTo(x, y) : ctx.moveTo(x, y); });
+      ctx.stroke();
+    }
+    ctx.shadowBlur = 0;
+    for (let j = 0; j < 21; j++) {
+      const [x, y] = P(j);
+      ctx.beginPath(); ctx.arc(x, y, j % 4 === 0 && j ? lw * 1.6 : lw * 1.1, 0, 7);
+      ctx.fillStyle = j % 4 === 0 && j ? "#fff" : col; ctx.fill();
+    }
+  }
+}
+
+// ---------------------------------------------------------------------------------------- landing
+function renderLanding(anchor) {
+  const app = $("#app");
+  app.replaceChildren($("#tpl-landing").content.cloneNode(true));
+  const eps = INDEX.episodes, st = INDEX.stats;
+  const byEmb = Object.fromEntries(EMB_ORDER.map((e) => [e, eps.filter((x) => x.embodiment === e)
+    .sort((a, b) => (b.id === FEATURED[e]) - (a.id === FEATURED[e]) || ((b.tracking?.any_hand || 0) + (b.tracking?.both_hands || 0)) - ((a.tracking?.any_hand || 0) + (a.tracking?.both_hands || 0)))]));
+
+  // hero mosaic: interleave embodiments
+  const mosaic = $("#mosaic");
+  const picks = [];
+  for (let i = 0; picks.length < 12 && i < 20; i++)
+    for (const e of ["ego", "umi", "hands", "mobile_umi"]) if (byEmb[e][i] && picks.length < 12) picks.push(byEmb[e][i]);
+  for (const ep of picks) mosaic.append(h("video", { src: ep.preview, muted: true, autoplay: true, loop: true, playsinline: true, preload: "auto" }));
+  mosaic.querySelectorAll("video").forEach((v) => { v.muted = true; v.play().catch(() => {}); });
+
+  // stats
+  const settings = new Set(eps.map((e) => e.setting));
+  const statRows = [
+    [`${st.ego_hours} h`, "ego video in the public sample"],
+    [st.ego_environments, "distinct environments"],
+    [st.ego_cameras, "capture rigs in the field"],
+    [settings.size, "industrial settings shown here"],
+    [4, "embodiments, one schema"],
+    [eps.length, "episodes to explore"],
+  ];
+  $("#stats").append(...statRows.map(([v, k]) => h("div", { class: "stat" }, h("div", { class: "v" }, String(v)), h("div", { class: "k" }, k))));
+
+  // embodiment cards
+  const grid = $("#emb-grid");
+  EMB_ORDER.forEach((e, i) => {
+    const m = EMB[e], first = byEmb[e][0];
+    const vid = first ? h("video", { src: first.preview, muted: true, autoplay: true, loop: true, playsinline: true }) : h("div");
+    const canvas = h("canvas");
+    const card = h("a", { class: "emb-card", href: `#/explore?emb=${e}`, style: { "--c": m.color } },
+      h("div", { class: "media" }, vid, canvas, h("span", { class: "num" }, `0${i + 1} · ${byEmb[e].length} episodes`)),
+      h("div", { class: "body" },
+        h("h3", {}, m.long),
+        h("p", {}, m.blurb),
+        h("ul", {}, ...m.bullets.map((b) => h("li", {}, b))),
+        h("span", { class: "go" }, `Explore ${m.name} →`)));
+    grid.append(card);
+    if (vid.tagName === "VIDEO") { vid.muted = true; vid.play().catch(() => {}); }
+    if (e === "hands" && first) {
+      getEp(first.id).then((ep) => {
+        let raf;
+        const loop = () => { drawHands(canvas, ep.hands[Math.min(ep.hands.length - 1, Math.floor(vid.currentTime * ep.fps))]); raf = requestAnimationFrame(loop); };
+        loop();
+        cleanup.push(() => cancelAnimationFrame(raf));
+      });
+    }
+  });
+
+  // full-corpus numbers for the contact block (filled from data/corpus.json; hidden if absent)
+  fetch("data/corpus.json").then((r) => (r.ok ? r.json() : null)).then((c) => {
+    if (c?.stats?.length) $("#big-stats").append(...c.stats.map(([v, k]) => h("div", {}, h("div", { class: "v" }, v), h("div", { class: "k" }, k))));
+  }).catch(() => {});
+
+  // download cards
+  $("#dl-grid").append(...DATASETS.map((d) => h("div", { class: "dl", style: { "--c": EMB[d.emb].color } },
+    h("div", { class: "dl-top" },
+      h("span", { class: "badge emb", style: { "--c": EMB[d.emb].color } }, EMB[d.emb].name),
+      h("span", { class: "dl-size" }, d.size)),
+    h("a", { class: "dl-name", href: `https://huggingface.co/datasets/${d.repo}`, target: "_blank", rel: "noopener" }, d.repo.replace("starpilot-ai/", "")),
+    h("div", { class: "dl-what" }, d.what),
+    copyBox(d.lerobot ? dlCmd(d.repo) : dlCmd(d.repo, "*/seg_00/*")),
+    d.tip && h("div", { class: "dl-tip" }, d.tip),
+    h("a", { class: "btn ghost sm", href: `https://huggingface.co/datasets/${d.repo}/tree/main`, target: "_blank", rel: "noopener" }, "⬇ Browse & download files"))));
+
+  // sensor spec sheets
+  $("#spec-grid").append(...EMB_ORDER.map((e) => h("div", { class: "spec", style: { "--c": EMB[e].color } },
+    h("div", { class: "spec-head" }, h("span", { class: "dot" }), EMB[e].long),
+    h("dl", {}, ...SPECS[e].flatMap(([k, v]) => [h("dt", {}, k), h("dd", {}, v)])))));
+
+  // sector chips
+  const bySetting = new Map();
+  for (const e of eps) {
+    if (!bySetting.has(e.setting)) bySetting.set(e.setting, new Set());
+    bySetting.get(e.setting).add(e.embodiment);
+  }
+  const counts = eps.reduce((m, e) => m.set(e.setting, (m.get(e.setting) || 0) + 1), new Map());
+  $("#sectors").append(...[...bySetting.entries()].sort((a, b) => counts.get(b[0]) - counts.get(a[0])).map(([s, embs]) =>
+    h("a", { class: "chip", href: `#/explore?q=${encodeURIComponent(s)}` },
+      h("span", { class: "sw" }, ...EMB_ORDER.filter((e) => embs.has(e)).map((e) => h("i", { style: { background: EMB[e].color } }))),
+      s, h("span", { class: "n" }, String(counts.get(s))))));
+
+  const repos = [...new Set(eps.map((e) => e.source?.repo).filter(Boolean))];
+  $("#foot-sources").append("Sources: ", ...repos.flatMap((r, i) => [i ? " · " : "", h("a", { href: `https://huggingface.co/datasets/${r}`, target: "_blank", rel: "noopener" }, r.replace("starpilot-ai/", ""))]));
+
+  if (anchor) requestAnimationFrame(() => document.getElementById(anchor)?.scrollIntoView());
+  else window.scrollTo(0, 0);
+  cleanup.push(() => app.querySelectorAll("video").forEach((v) => { v.pause(); v.removeAttribute("src"); v.load(); }));
+}
+
+// ---------------------------------------------------------------------------------------- explorer
+function renderExplore(q) {
+  const app = $("#app");
+  let shell = $(".explore", app);
+  if (!shell) {
+    app.replaceChildren($("#tpl-explore").content.cloneNode(true));
+    shell = $(".explore", app);
+  }
+  window.scrollTo(0, 0);
+  const emb = q.get("emb") || "all";
+  const text = (q.get("q") || "").toLowerCase();
+  const sel = q.get("ep");
+
+  const tabs = $("#emb-tabs");
+  tabs.replaceChildren(...["all", ...EMB_ORDER].map((e) =>
+    h("button", { class: "tab" + (e === emb ? " on" : ""), onclick: () => nav({ emb: e, q: $("#search").value }) },
+      e === "all" ? "All" : [h("i", { style: { background: EMB[e].color } }), EMB[e].name])));
+  const search = $("#search");
+  if (document.activeElement !== search) search.value = q.get("q") || "";
+  search.oninput = () => { clearTimeout(search._t); search._t = setTimeout(() => nav({ emb, q: search.value }, true), 200); };
+
+  const list = INDEX.episodes.filter((e) => (emb === "all" || e.embodiment === emb) &&
+    (!text || [e.title, e.sector, e.setting, e.id].join(" ").toLowerCase().includes(text)));
+  const L = $("#ep-list");
+  L.replaceChildren();
+  for (const e of EMB_ORDER) {
+    const items = list.filter((x) => x.embodiment === e);
+    if (!items.length) continue;
+    L.append(h("div", { class: "ep-group" }, `${EMB[e].long} · ${items.length}`));
+    for (const it of items)
+      L.append(h("a", { class: "ep-item" + (it.id === (sel || list[0]?.id) ? " on" : ""), href: link({ emb, q: q.get("q"), ep: it.id }), style: { "--c": EMB[e].color } },
+        h("img", { src: it.poster, loading: "lazy", alt: "" }),
+        h("div", {}, h("div", { class: "t" }, it.title), h("div", { class: "s" }, `${it.sector} · ${it.duration}s · ${it.n_streams} cam`))));
+  }
+  const cur = list.find((e) => e.id === sel) || list[0];
+  const viewer = $("#viewer");
+  if (!cur) { viewer.replaceChildren(h("div", { class: "empty" }, "No episodes match.")); return; }
+  $(".ep-item.on", L)?.scrollIntoView({ block: "nearest" });
+  renderEpisode(viewer, cur.id);
+}
+const link = (o) => "#/explore?" + new URLSearchParams(Object.entries(o).filter(([, v]) => v && v !== "all")).toString();
+function nav(o, replace) {
+  const u = link(o);
+  if (replace) history.replaceState(null, "", u), route(); else location.hash = u.slice(1);
+}
+
+async function renderEpisode(viewer, id) {
+  viewer.replaceChildren(h("div", { class: "empty" }, "Loading…"));
+  const ep = await getEp(id);
+  const m = EMB[ep.embodiment];
+  const src = ep.source || {};
+  const srcHref = `https://huggingface.co/datasets/${src.repo}` + (src.path ? `/tree/main/${src.path}` : "");
+  const srcTxt = src.path ? `${src.path} @ ${src.t0}s` : `episode ${src.episode}` + (src.frame0 ? ` @ frame ${src.frame0}` : "");
+
+  const portrait = ep.streams.some((s) => s.h > s.w);
+  const cams = h("div", { class: `cams n${Math.min(ep.streams.length, 3)}` + (portrait ? " portrait" : "") });
+  const videos = [], overlays = [];
+  for (const s of ep.streams) {
+    const v = h("video", { src: s.src, muted: true, playsinline: true, preload: "auto" });
+    v.muted = true;
+    const box = h("div", { class: "cam", style: { aspectRatio: `${s.w}/${s.h}` } }, v, h("span", { class: "lbl" }, s.label));
+    if (ep.hands && s.key === "left") { const c = h("canvas"); box.append(c); overlays.push(c); }
+    videos.push(v); cams.append(box);
+  }
+
+  const playBtn = h("button", {}, "❚❚ Pause");
+  const scrub = h("input", { type: "range", min: 0, max: ep.duration, step: 1 / ep.fps, value: 0 });
+  const timeEl = h("span", { class: "time" });
+  const speeds = [0.5, 1, 2].map((r) => h("button", { class: r === 1 ? "on" : "", onclick: (ev) => {
+    videos.forEach((v) => (v.playbackRate = r));
+    speeds.forEach((b) => b.classList.toggle("on", b === ev.currentTarget));
+  } }, `${r}×`));
+  const controls = h("div", { class: "controls" }, playBtn, scrub, ...speeds, timeEl);
+
+  // download menu: the clips shown here + the full-resolution source on Hugging Face
+  const dlFiles = [...ep.streams.map((s) => [`${s.label} · clip (mp4)`, s.src, `${ep.id}_${s.key}.mp4`]),
+    ["Signals + metadata (json)", `data/episodes/${ep.id}.json`, `${ep.id}.json`]];
+  const srcCmd = src.path ? dlCmd(src.repo, `${src.path}/*`) : dlCmd(src.repo);
+  const dlPanel = h("div", { class: "dl-pop", hidden: true },
+    h("div", { class: "dl-pop-h" }, "This clip"),
+    ...dlFiles.map(([label, href, name]) => h("a", { href, download: name }, "⬇ ", label)),
+    h("div", { class: "dl-pop-h" }, src.path ? "Full-resolution source segment" : `Full source dataset (episode ${src.episode})`),
+    copyBox(srcCmd),
+    h("a", { href: srcHref, target: "_blank", rel: "noopener" }, "Open on Hugging Face ↗"));
+  const dlBtn = h("button", { class: "dl-btn", onclick: (e) => { e.stopPropagation(); dlPanel.hidden = !dlPanel.hidden; } }, "⬇ Download");
+  const dlWrap = h("div", { class: "dl-wrap" }, dlBtn, dlPanel);
+  const closeDl = (e) => { if (!dlWrap.contains(e.target)) dlPanel.hidden = true; };
+  document.addEventListener("click", closeDl);
+  cleanup.push(() => document.removeEventListener("click", closeDl));
+
+  const panels = h("div", { class: "panels" });
+  const charts = (ep.series || []).map((g) => new Chart(g, ep, (t) => seek(t)));
+  let three = null;
+  if (ep.traj3d) {
+    const div = h("div", { class: "three" });
+    panels.append(h("div", { class: "panel p3d" },
+      h("h4", {}, "3D trajectories", h("span", { class: "legend" }, ...ep.traj3d.tracks.map((t) => h("span", {}, h("i", { style: { background: t.color } }), t.name)))),
+      div, h("div", { class: "hint" }, "Drag to orbit · scroll to zoom · faint line = full episode, bright = last 2 s")));
+    three = await makeThree(div, ep);
+  }
+  charts.forEach((c) => panels.append(c.el));
+
+  viewer.replaceChildren(
+    h("div", { class: "v-head", style: { "--c": m.color } },
+      h("div", {},
+        h("h2", {}, ep.title),
+        h("div", { class: "badges" },
+          h("span", { class: "badge emb", style: { "--c": m.color } }, m.long),
+          ep.sector && h("span", { class: "badge" }, ep.sector),
+          ep.station && h("span", { class: "badge" }, ep.station),
+          ep.role && h("span", { class: "badge" }, ep.role),
+          ep.difficulty && h("span", { class: "badge" }, `difficulty: ${ep.difficulty}`))),
+      h("div", { class: "v-right" }, dlWrap,
+        h("div", { class: "v-src" }, "source ", h("a", { href: srcHref, target: "_blank", rel: "noopener" }, src.repo), h("br"), srcTxt))),
+    h("div", { class: "specs", style: { "--c": m.color } }, ...(ep.specs || []).map((s) => h("span", {}, s))),
+    cams, controls, panels);
+
+  // ---- sync engine: video 0 is the clock; the others are nudged when they drift
+  const master = videos[0];
+  let raf, dragging = false;
+  const seek = (t) => { videos.forEach((v) => (v.currentTime = t)); };
+  const play = () => { videos.forEach((v) => v.play().catch(() => {})); playBtn.textContent = "❚❚ Pause"; };
+  const pause = () => { videos.forEach((v) => v.pause()); playBtn.textContent = "▶ Play"; };
+  playBtn.onclick = () => (master.paused ? play() : pause());
+  scrub.oninput = () => { dragging = true; seek(+scrub.value); };
+  scrub.onchange = () => { dragging = false; };
+  master.addEventListener("ended", () => { seek(0); play(); });
+  const tick = () => {
+    const t = master.currentTime || 0;
+    if (!master.paused) for (const v of videos.slice(1)) if (Math.abs(v.currentTime - t) > 0.1 && v.readyState >= 2) v.currentTime = t;
+    if (!dragging) scrub.value = t;
+    const fi = Math.min(Math.floor(t * ep.fps), Math.round(ep.duration * ep.fps) - 1);
+    timeEl.textContent = `${fmtT(t)} · frame ${fi}`;
+    overlays.forEach((c) => drawHands(c, ep.hands[fi]));
+    charts.forEach((c) => c.draw(t));
+    three?.update(fi);
+    raf = requestAnimationFrame(tick);
+  };
+  tick();
+  play();
+  const onKey = (e) => {
+    if (e.target.tagName === "INPUT") return;
+    if (e.code === "Space") { e.preventDefault(); master.paused ? play() : pause(); }
+    if (e.code === "ArrowRight") seek(Math.min(ep.duration, master.currentTime + (e.shiftKey ? 1 / ep.fps : 1)));
+    if (e.code === "ArrowLeft") seek(Math.max(0, master.currentTime - (e.shiftKey ? 1 / ep.fps : 1)));
+  };
+  window.addEventListener("keydown", onKey);
+  cleanup.push(() => {
+    cancelAnimationFrame(raf); window.removeEventListener("keydown", onKey); three?.dispose();
+    videos.forEach((v) => { v.pause(); v.removeAttribute("src"); v.load(); });
+  });
+}
+
+// ----------------------------------------------------------------------------------------- charts
+class Chart {
+  constructor(g, ep, onSeek) {
+    this.g = g; this.ep = ep;
+    this.colors = g.names.map((n, i) => {
+      const s = n.toLowerCase();
+      if (/^(left|a\b|a \(|l )/.test(s) || s.startsWith("left")) return "#4aa3ff";
+      if (/^(right|b\b|b \(|r )/.test(s) || s.startsWith("right")) return "#ff5fa2";
+      if (g.names.length === 3) return XYZ[i];
+      return ["#f5a524", "#2dd4bf", "#a78bfa"][i % 3];
+    });
+    this.canvas = h("canvas", { class: "chart" });
+    this.val = g.names.map(() => h("b"));
+    this.el = h("div", { class: "panel" },
+      h("h4", {}, g.group, h("span", { class: "legend" }, ...g.names.map((n, i) => h("span", {}, h("i", { style: { background: this.colors[i] } }), `${n} `, this.val[i])))),
+      this.canvas);
+    let down = false;
+    const at = (e) => { const r = this.canvas.getBoundingClientRect(); onSeek(Math.max(0, Math.min(1, (e.clientX - r.left - 34) / (r.width - 40))) * ep.duration); };
+    this.canvas.addEventListener("pointerdown", (e) => { down = true; at(e); });
+    window.addEventListener("pointerup", () => (down = false));
+    this.canvas.addEventListener("pointermove", (e) => down && at(e));
+    let lo = Infinity, hi = -Infinity;
+    for (const s of g.values) for (const v of s) if (v !== null && Number.isFinite(v)) { lo = Math.min(lo, v); hi = Math.max(hi, v); }
+    if (!Number.isFinite(lo)) { lo = 0; hi = 1; }
+    if (hi - lo < 1e-6) { hi += 0.5; lo -= 0.5; }
+    const pad = (hi - lo) * 0.08;
+    this.lo = lo - pad; this.hi = hi + pad;
+  }
+  layout() {
+    const dpr = window.devicePixelRatio || 1, W = this.canvas.clientWidth, H = this.canvas.clientHeight;
+    if (this.W === W && this.H === H) return;
+    this.W = W; this.H = H;
+    this.canvas.width = Math.round(W * dpr); this.canvas.height = Math.round(H * dpr);
+    const off = (this.bg = document.createElement("canvas"));
+    off.width = this.canvas.width; off.height = this.canvas.height;
+    const c = off.getContext("2d");
+    c.setTransform(dpr, 0, 0, dpr, 0, 0);
+    const X0 = 34, X1 = W - 6, Y0 = 6, Y1 = H - 16;
+    Object.assign(this, { X0, X1, Y0, Y1 });
+    const y = (v) => Y1 - ((v - this.lo) / (this.hi - this.lo)) * (Y1 - Y0);
+    c.font = "10px JetBrains Mono, monospace"; c.fillStyle = "#6b7385"; c.strokeStyle = "#252b38"; c.lineWidth = 1;
+    for (let k = 0; k <= 3; k++) {
+      const v = this.lo + ((this.hi - this.lo) * k) / 3, yy = y(v);
+      c.beginPath(); c.moveTo(X0, yy); c.lineTo(X1, yy); c.stroke();
+      c.fillText(Math.abs(v) >= 100 ? v.toFixed(0) : v.toFixed(Math.abs(v) >= 10 ? 1 : 2), 0, yy + 3);
+    }
+    for (let s = 0; s <= this.ep.duration; s += this.ep.duration > 20 ? 5 : 2) c.fillText(`${s}s`, X0 + (s / this.ep.duration) * (X1 - X0) - 6, H - 3);
+    this.g.values.forEach((s, i) => {
+      c.strokeStyle = this.colors[i]; c.lineWidth = 1.4; c.beginPath();
+      let pen = false;
+      s.forEach((v, k) => {
+        if (v === null || !Number.isFinite(v)) { pen = false; return; }
+        const xx = X0 + (k / (s.length - 1)) * (X1 - X0);
+        pen ? c.lineTo(xx, y(v)) : c.moveTo(xx, y(v));
+        pen = true;
+      });
+      c.stroke();
+    });
+    this.y = y;
+  }
+  draw(t) {
+    this.layout();
+    const c = this.canvas.getContext("2d"), dpr = window.devicePixelRatio || 1;
+    c.setTransform(1, 0, 0, 1, 0, 0);
+    c.clearRect(0, 0, this.canvas.width, this.canvas.height);
+    c.drawImage(this.bg, 0, 0);
+    c.setTransform(dpr, 0, 0, dpr, 0, 0);
+    const x = this.X0 + (t / this.ep.duration) * (this.X1 - this.X0);
+    c.strokeStyle = "rgba(255,255,255,.75)"; c.lineWidth = 1;
+    c.beginPath(); c.moveTo(x, this.Y0); c.lineTo(x, this.Y1); c.stroke();
+    this.g.values.forEach((s, i) => {
+      const k = Math.min(s.length - 1, Math.round((t / this.ep.duration) * (s.length - 1)));
+      const v = s[k];
+      this.val[i].textContent = v === null || v === undefined ? "–" : (+v).toFixed(Math.abs(v) >= 100 ? 0 : 2);
+      if (v === null || !Number.isFinite(v)) return;
+      c.fillStyle = this.colors[i]; c.beginPath(); c.arc(x, this.y(v), 3, 0, 7); c.fill();
+    });
+  }
+}
+
+// --------------------------------------------------------------------------------------------- 3D
+async function makeThree(div, ep) {
+  const THREE = await import("three");
+  const { OrbitControls } = await import("three/addons/controls/OrbitControls.js");
+  const W = div.clientWidth || 400, H = div.clientHeight || 300;
+  const renderer = new THREE.WebGLRenderer({ antialias: true });
+  renderer.setPixelRatio(window.devicePixelRatio || 1);
+  renderer.setSize(W, H);
+  renderer.setClearColor(0x07090c);
+  div.append(renderer.domElement);
+  const scene = new THREE.Scene();
+  const cam = new THREE.PerspectiveCamera(45, W / H, 0.01, 100);
+  cam.up.set(0, 0, 1);
+
+  const all = ep.traj3d.tracks.flatMap((t) => t.xyz);
+  const c = [0, 1, 2].map((i) => all.reduce((s, p) => s + p[i], 0) / all.length);
+  const ext = Math.max(...[0, 1, 2].map((i) => Math.max(...all.map((p) => p[i])) - Math.min(...all.map((p) => p[i]))), 0.2);
+  const center = new THREE.Vector3(...c);
+
+  const grid = new THREE.GridHelper(ext * 3, 12, 0x2a3140, 0x1a1f29);
+  grid.rotation.x = Math.PI / 2;
+  grid.position.set(c[0], c[1], Math.min(...all.map((p) => p[2])) - 0.02);
+  scene.add(grid);
+  const axes = new THREE.AxesHelper(ext * 0.25);
+  axes.position.copy(grid.position);
+  scene.add(axes);
+
+  const tracks = ep.traj3d.tracks.map((t) => {
+    const col = new THREE.Color(t.color);
+    const pts = t.xyz.map((p) => new THREE.Vector3(...p));
+    const full = new THREE.Line(new THREE.BufferGeometry().setFromPoints(pts), new THREE.LineBasicMaterial({ color: col, transparent: true, opacity: 0.22 }));
+    const trailGeo = new THREE.BufferGeometry().setFromPoints(pts);
+    const trail = new THREE.Line(trailGeo, new THREE.LineBasicMaterial({ color: col }));
+    const dot = new THREE.Mesh(new THREE.SphereGeometry(ext * 0.022, 16, 12), new THREE.MeshBasicMaterial({ color: col }));
+    scene.add(full, trail, dot);
+    let frust = null;
+    if (t.quat) {
+      // camera frustum for the head (camera looks along +z, image y down)
+      const s = ext * 0.08, g = new THREE.BufferGeometry();
+      const P = [[0, 0, 0], [-s, -s * 0.6, s * 1.4], [s, -s * 0.6, s * 1.4], [s, s * 0.6, s * 1.4], [-s, s * 0.6, s * 1.4]];
+      const idx = [0, 1, 0, 2, 0, 3, 0, 4, 1, 2, 2, 3, 3, 4, 4, 1];
+      g.setAttribute("position", new THREE.Float32BufferAttribute(idx.flatMap((i) => P[i]), 3));
+      frust = new THREE.LineSegments(g, new THREE.LineBasicMaterial({ color: 0xffffff }));
+      scene.add(frust);
+    }
+    return { t, trail, trailGeo, dot, frust };
+  });
+
+  cam.position.copy(center).add(new THREE.Vector3(ext * 0.75, -ext * 0.95, ext * 0.7));
+  const controls = new OrbitControls(cam, renderer.domElement);
+  controls.target.copy(center);
+  controls.enableDamping = true;
+  controls.update();
+
+  const ro = new ResizeObserver(() => {
+    const w = div.clientWidth, hh = div.clientHeight;
+    if (!w) return;
+    renderer.setSize(w, hh); cam.aspect = w / hh; cam.updateProjectionMatrix();
+  });
+  ro.observe(div);
+  const q = new THREE.Quaternion();
+  return {
+    update(fi) {
+      for (const { t, trail, trailGeo, dot, frust } of tracks) {
+        const k = Math.max(0, Math.min(t.xyz.length - 1, fi));
+        dot.position.set(...t.xyz[k]);
+        const a = Math.max(0, k - ep.fps * 2);
+        trailGeo.setDrawRange(a, k - a + 1);
+        if (frust) { frust.position.set(...t.xyz[k]); q.set(...t.quat[k]); frust.quaternion.copy(q); }
+      }
+      controls.update();
+      renderer.render(scene, cam);
+    },
+    dispose() { ro.disconnect(); controls.dispose(); renderer.dispose(); },
+  };
+}
+
+// ------------------------------------------------------------------------------------------- boot
+fetch("data/index.json").then((r) => r.json()).then((j) => { INDEX = j; route(); });

site/data/episodes/ego_20260629-225207_seg_00.json

@@ -1 +1 @@
-{"id":"ego_20260629-225207_seg_00","embodiment":"ego","title":"Fabrication shop","sector":"Fabrication","setting":"Fabrication shop","station":"Packaging Area","role":"Packaging technician","difficulty":"medium","quality":0.936,"camera":"orangepi5-71715111","duration":20.0,"fps":30,"source":{"repo":"starpilot-ai/ego_sample_v0.1.3","path":"20260629-225207/seg_00","t0":380.0},"specs":["Head-mounted stereo","1920\u00d71200 @ 60 fps per eye","IMU 600 Hz","Faces blurred"],"streams":[{"key":"left","label":"Head \u00b7 stereo left","src":"media/ego_20260629-225207_seg_00/left.mp4","w":960,"h":600,"kind":"rgb"},{"key":"right","label":"Head \u00b7 stereo right","src":"media/ego_20260629-225207_seg_00/right.mp4","w":960,"h":600,"kind":"rgb"}],"series":[{"group":"Head IMU \u00b7 accel 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site/data/episodes/ego_starcap10_0713-2154_seg_00.json

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site/data/episodes/ego_starcap12_0709-062242_seg_00.json

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site/data/episodes/ego_starcap19_0715-075327_seg_01.json

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site/data/episodes/ego_starcap21_0710-2044_seg_02.json

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site/data/episodes/ego_starcap22_0623-0036_seg_01.json

@@ -1 +1 @@
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site/data/episodes/ego_starcap24_0630-0036_seg_01.json

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site/data/episodes/ego_starcap2_0629-2217_seg_00.json

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site/data/episodes/ego_starcap32_0716-1009_seg_00.json

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site/data/episodes/ego_starcap34_0712-0641_seg_01.json

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site/data/episodes/ego_starcap6_0707-1655_seg_00.json

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site/data/episodes/ego_starcap9_0622-0917_seg_00.json

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site/data/index.json

@@ -500,6 +500,150 @@
    "preview": "media/umi_20260518_ep0/base0.mp4",
    "n_streams": 6
   },
+  {
+   "id": "umi_hotdrinks_ep0",
+   "embodiment": "umi",
+   "title": "Pour the drink into the cup",
+   "sector": "Food service",
+   "setting": "Coffee & tea station",
+   "duration": 41.3,
+   "source": {
+    "repo": "starpilot-ai/YAMGripper_Cafe_HotDrinks",
+    "episode": 0,
+    "frame0": 7
+   },
+   "poster": "media/umi_hotdrinks_ep0/poster.jpg",
+   "preview": "media/umi_hotdrinks_ep0/base0.mp4",
+   "n_streams": 6
+  },
+  {
+   "id": "umi_hotdrinks_ep1",
+   "embodiment": "umi",
+   "title": "Add sugar and cream, stir",
+   "sector": "Food service",
+   "setting": "Coffee & tea station",
+   "duration": 44.93,
+   "source": {
+    "repo": "starpilot-ai/YAMGripper_Cafe_HotDrinks",
+    "episode": 1,
+    "frame0": 7
+   },
+   "poster": "media/umi_hotdrinks_ep1/poster.jpg",
+   "preview": "media/umi_hotdrinks_ep1/base0.mp4",
+   "n_streams": 6
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