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Publish validated items_handover_aug_r001: 5 trajectories

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  1. items_handover_aug_r001/README.md +7 -0
  2. items_handover_aug_r001/data/chunk-000/episode_000000.parquet +3 -0
  3. items_handover_aug_r001/data/chunk-000/episode_000001.parquet +3 -0
  4. items_handover_aug_r001/data/chunk-000/episode_000002.parquet +3 -0
  5. items_handover_aug_r001/data/chunk-000/episode_000003.parquet +3 -0
  6. items_handover_aug_r001/data/chunk-000/episode_000004.parquet +3 -0
  7. items_handover_aug_r001/meta/episodes.jsonl +5 -0
  8. items_handover_aug_r001/meta/episodes_stats.jsonl +0 -0
  9. items_handover_aug_r001/meta/info.json +385 -0
  10. items_handover_aug_r001/meta/stats.json +0 -0
  11. items_handover_aug_r001/meta/tasks.jsonl +1 -0
  12. items_handover_aug_r001/provenance/conversion_program.py +182 -0
  13. items_handover_aug_r001/provenance/conversion_receipt.json +312 -0
  14. items_handover_aug_r001/provenance/episodes.jsonl +5 -0
  15. items_handover_aug_r001/provenance/old_loader_CPU_receipt.json +156 -0
  16. items_handover_aug_r001/provenance/source_release/action_config.json +1466 -0
  17. items_handover_aug_r001/provenance/source_release/episodes.jsonl +5 -0
  18. items_handover_aug_r001/provenance/source_release/gym_config.json +1069 -0
  19. items_handover_aug_r001/provenance/source_release/production_metadata.json +299 -0
  20. items_handover_aug_r001/provenance/source_release/profile.json +216 -0
  21. items_handover_aug_r001/provenance/source_release/release_validation.json +63 -0
  22. items_handover_aug_r001/provenance/source_release/source_READY +1 -0
  23. items_handover_aug_r001/provenance/source_release/source_manifest.json +0 -0
  24. items_handover_aug_r001/provenance/source_release/source_receipt.json +36 -0
  25. items_handover_aug_r001/provenance/source_release/source_validation.json +222 -0
  26. items_handover_aug_r001/provenance/source_release_manifest.json +141 -0
  27. items_handover_aug_r001/provenance/source_validation.json +222 -0
  28. items_handover_aug_r001/release_manifest.json +60 -0
  29. items_handover_aug_r001/videos/chunk-000/observation.images.cam_high/episode_000000.mp4 +3 -0
  30. items_handover_aug_r001/videos/chunk-000/observation.images.cam_high/episode_000001.mp4 +3 -0
  31. items_handover_aug_r001/videos/chunk-000/observation.images.cam_high/episode_000002.mp4 +3 -0
  32. items_handover_aug_r001/videos/chunk-000/observation.images.cam_high/episode_000003.mp4 +3 -0
  33. items_handover_aug_r001/videos/chunk-000/observation.images.cam_high/episode_000004.mp4 +3 -0
  34. items_handover_aug_r001/videos/chunk-000/observation.images.cam_left_wrist/episode_000000.mp4 +3 -0
  35. items_handover_aug_r001/videos/chunk-000/observation.images.cam_left_wrist/episode_000001.mp4 +3 -0
  36. items_handover_aug_r001/videos/chunk-000/observation.images.cam_left_wrist/episode_000002.mp4 +3 -0
  37. items_handover_aug_r001/videos/chunk-000/observation.images.cam_left_wrist/episode_000003.mp4 +3 -0
  38. items_handover_aug_r001/videos/chunk-000/observation.images.cam_left_wrist/episode_000004.mp4 +3 -0
  39. items_handover_aug_r001/videos/chunk-000/observation.images.cam_right_wrist/episode_000000.mp4 +3 -0
  40. items_handover_aug_r001/videos/chunk-000/observation.images.cam_right_wrist/episode_000001.mp4 +3 -0
  41. items_handover_aug_r001/videos/chunk-000/observation.images.cam_right_wrist/episode_000002.mp4 +3 -0
  42. items_handover_aug_r001/videos/chunk-000/observation.images.cam_right_wrist/episode_000003.mp4 +3 -0
  43. items_handover_aug_r001/videos/chunk-000/observation.images.cam_right_wrist/episode_000004.mp4 +3 -0
items_handover_aug_r001/README.md ADDED
@@ -0,0 +1,7 @@
 
 
 
 
 
 
 
 
1
+ # items_handover_aug_r001
2
+
3
+ items_handover: 5 complete validated native trajectories, 2185 frames, 25 Hz, 14-dimensional CobotMagic states and actions, three 640×480 cameras.
4
+
5
+ This is a genuine LeRobot v2.1 derivative of sealed native v3.0 shard `items_handover_shard_000508`. State/action and every other Arrow column remain exact. Videos are losslessly remuxed at verified episode keyframes; every decoded RGB frame matches the source. Canonical episode, object and variant IDs and source hashes are in `provenance/episodes.jsonl`. This conversion creates zero new physical trajectories.
6
+
7
+ The v2.1 layout is intended for the pinned older π0.5 LeRobot loader. Training has not been run on this release. Geometry is still stored locally; its canonical IDs, exact SHA-256 and scale are recorded without claiming a Hugging Face object revision. Only train split is assigned; no independent evaluation split is claimed.
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+ version https://git-lfs.github.com/spec/v1
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+ oid sha256:76d4faead309285d1717ff17f440978f58843b5be5758a84cefa160c36e3679d
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+ size 203883
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+ size 210417
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+ size 217276
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items_handover_aug_r001/meta/episodes.jsonl ADDED
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+ {"episode_index": 0, "tasks": ["Pick up the pen, hand it over to the other arm and then place it in to the pen holder"], "length": 437}
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+ {"episode_index": 1, "tasks": ["Pick up the pen, hand it over to the other arm and then place it in to the pen holder"], "length": 437}
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+ {"episode_index": 2, "tasks": ["Pick up the pen, hand it over to the other arm and then place it in to the pen holder"], "length": 437}
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+ {"episode_index": 3, "tasks": ["Pick up the pen, hand it over to the other arm and then place it in to the pen holder"], "length": 437}
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+ {"episode_index": 4, "tasks": ["Pick up the pen, hand it over to the other arm and then place it in to the pen holder"], "length": 437}
items_handover_aug_r001/meta/episodes_stats.jsonl ADDED
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items_handover_aug_r001/meta/info.json ADDED
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+ {
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+ "codebase_version": "v2.1",
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+ "robot_type": "cobotmagic",
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+ "total_episodes": 5,
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+ "total_frames": 2185,
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+ "total_tasks": 1,
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+ "chunks_size": 1000,
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+ "fps": 25,
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+ "splits": {
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+ "train": "0:5"
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+ },
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+ "data_path": "data/chunk-{episode_chunk:03d}/episode_{episode_index:06d}.parquet",
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+ "video_path": "videos/chunk-{episode_chunk:03d}/{video_key}/episode_{episode_index:06d}.mp4",
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+ "features": {
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+ "observation.state": {
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+ "dtype": "float32",
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+ "shape": [
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+ 14
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+ ],
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+ "names": [
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+ "left_joint1",
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+ "left_joint2",
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+ "left_joint3",
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+ "left_joint4",
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+ "left_joint5",
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+ "left_joint6",
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+ "left_joint7",
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+ "right_joint1",
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+ "right_joint2",
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+ "right_joint3",
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+ "right_joint4",
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+ "right_joint5",
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+ "right_joint6",
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+ "right_joint7"
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+ ]
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+ "observation.qvel": {
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+ "dtype": "float32",
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+ "shape": [
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+ ],
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+ "names": [
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+ "left_joint1",
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+ "left_joint2",
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+ "left_joint3",
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+ "left_joint4",
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+ "left_joint5",
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+ "left_joint6",
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+ "left_joint7",
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+ "right_joint1",
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+ "right_joint2",
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+ "right_joint3",
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+ "right_joint4",
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+ "right_joint5",
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+ "right_joint6",
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+ "right_joint7"
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+ ]
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+ "dtype": "float32",
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+ "shape": [
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+ "names": [
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+ "left_joint1",
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+ "left_joint2",
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+ "left_joint3",
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+ "left_joint4",
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+ "left_joint5",
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+ "left_joint6",
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+ "left_joint7",
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+ "right_joint1",
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+ "right_joint2",
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+ "right_joint3",
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+ "right_joint4",
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+ "right_joint5",
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+ "right_joint6",
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+ "right_joint7"
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+ ]
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+ },
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+ "action": {
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+ "shape": [
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+ "names": [
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+ "left_joint1",
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+ "left_joint2",
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+ "left_joint3",
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+ "left_joint4",
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+ "left_joint5",
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+ "left_joint6",
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+ "left_joint7",
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+ "right_joint1",
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+ "right_joint2",
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+ "right_joint3",
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+ "right_joint4",
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+ "right_joint5",
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+ "right_joint6",
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+ "right_joint7"
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+ ]
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+ },
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+ "observation.images.cam_high": {
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+ "dtype": "video",
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+ "shape": [
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+ 480,
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+ 640,
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+ 3
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+ ],
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+ "names": [
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+ "channel"
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+ ],
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+ "info": {
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+ "video.width": 640,
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+ "video.codec": "av1",
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+ "video.pix_fmt": "yuv420p",
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+ "video.is_depth_map": false,
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+ "video.fps": 25,
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+ "video.channels": 3,
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+ "has_audio": false
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+ }
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+ },
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+ "observation.images.cam_right_wrist": {
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+ 480,
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+ "video.codec": "av1",
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+ "video.pix_fmt": "yuv420p",
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+ "video.is_depth_map": false,
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+ "video.fps": 25,
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+ "video.channels": 3,
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+ "has_audio": false
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+ }
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+ "shape": [
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+ 480,
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+ 640,
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+ 3
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+ ],
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+ "names": [
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+ "height",
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+ "width",
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+ "channel"
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+ ],
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+ "info": {
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+ "video.height": 480,
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+ "video.width": 640,
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+ "video.codec": "av1",
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+ "video.pix_fmt": "yuv420p",
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+ "video.is_depth_map": false,
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+ "video.fps": 25,
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+ "video.channels": 3,
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+ "has_audio": false
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+ "names": "distance"
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+ },
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+ "dtype": "int32",
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+ ],
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+ "names": "user_ids"
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+ "task2000_pen_left_grasp_contact.is_valid": {
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+ "dtype": "bool",
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+ "shape": [
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+ 64
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+ "names": "is_valid"
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+ },
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+ "shape": [
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+ "names": "impulse"
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+ "dtype": "float32",
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+ "shape": [
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+ "shape": [
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+ "names": "pen_pose"
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+ "shape": [
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+ ],
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+ "names": "holder_pose"
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+ ],
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items_handover_aug_r001/meta/stats.json ADDED
The diff for this file is too large to render. See raw diff
 
items_handover_aug_r001/meta/tasks.jsonl ADDED
@@ -0,0 +1 @@
 
 
1
+ {"task_index": 0, "task": "Pick up the pen, hand it over to the other arm and then place it in to the pen holder"}
items_handover_aug_r001/provenance/conversion_program.py ADDED
@@ -0,0 +1,182 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ """Export closed native v3 shards to independent, lossless v2.1 HF releases.
2
+
3
+ Only new staging outputs are written. Sealed source datasets, the production
4
+ ledger, assets and receipts remain untouched. Existing converter metadata/data
5
+ helpers are reused; video segments are remuxed at verified episode keyframes.
6
+ """
7
+
8
+ from __future__ import annotations
9
+
10
+ import hashlib
11
+ import importlib.util
12
+ import json
13
+ from pathlib import Path
14
+ import sqlite3
15
+ from fractions import Fraction
16
+ import shutil
17
+ import subprocess
18
+
19
+ import av
20
+ import numpy as np
21
+ import pyarrow.parquet as pq
22
+
23
+ ROOT = Path(__file__).resolve().parents[2]
24
+ CAMPAIGN = ROOT / "web/runs/data_generation/task2000_v1"
25
+ DEST = CAMPAIGN / "release_staging/hf_initial_task_release_v1/compatible_v21"
26
+ SHARDS = ((508, "items_handover_aug_r001"), (526, "item_assembly_aug_r001"))
27
+
28
+
29
+ def sha(path: Path) -> str:
30
+ h = hashlib.sha256()
31
+ with path.open("rb") as f:
32
+ for block in iter(lambda: f.read(1024 * 1024), b""):
33
+ h.update(block)
34
+ return h.hexdigest()
35
+
36
+
37
+ def write_json(path: Path, value: object) -> None:
38
+ path.parent.mkdir(parents=True, exist_ok=True)
39
+ path.write_text(json.dumps(value, indent=2, ensure_ascii=False, allow_nan=False) + "\n")
40
+
41
+
42
+ def hashes(root: Path) -> dict[str, str]:
43
+ return {str(p.relative_to(root)): sha(p) for p in sorted(root.rglob("*")) if p.is_file()}
44
+
45
+
46
+ def packet_split(src: Path, dst: Path, start: float, length: int, fps: int) -> dict:
47
+ """Copy compressed packets exactly; refuse a non-keyframe episode boundary."""
48
+ dst.parent.mkdir(parents=True, exist_ok=True)
49
+ with av.open(str(src)) as reader:
50
+ stream = reader.streams.video[0]
51
+ base = stream.time_base
52
+ begin = Fraction(str(start)) / base
53
+ ticks = Fraction(1, fps) / base
54
+ if begin.denominator != 1 or ticks.denominator != 1:
55
+ raise ValueError("Episode boundary is not an integer source timestamp")
56
+ begin, ticks = int(begin), int(ticks)
57
+ end = begin + length * ticks
58
+ reader.seek(begin, stream=stream, backward=True, any_frame=False)
59
+ count = 0
60
+ for packet in reader.demux(stream):
61
+ if packet.pts is None or packet.pts < begin:
62
+ continue
63
+ if packet.pts >= end:
64
+ break
65
+ if packet.pts != begin + count * ticks or packet.dts != packet.pts:
66
+ raise ValueError("Packet timing is not an exact monotonic 25 Hz sequence")
67
+ if count == 0 and not packet.is_keyframe:
68
+ raise ValueError("Episode does not start with a codec keyframe")
69
+ count += 1
70
+ if count != length:
71
+ raise ValueError(f"Video packet count mismatch: {count} != {length}")
72
+ subprocess.run(["/home/graphvix/miniforge3/envs/robosyn/bin/ffmpeg", "-hide_banner", "-loglevel", "error", "-ss", f"{start:.6f}", "-i", str(src), "-t", f"{length / fps:.6f}", "-map", "0:v:0", "-c", "copy", "-avoid_negative_ts", "1", "-y", str(dst)], check=True, capture_output=True, timeout=300)
73
+ return {"packets": count, "first_packet_keyframe": True, "method": "lossless_ffmpeg_stream_copy"}
74
+
75
+
76
+ def decoded_hashes(path: Path, lengths: list[int], fps: int) -> list[str]:
77
+ """Fully decode each source/output frame and hash the exact RGB pixels."""
78
+ total = sum(lengths)
79
+ result, h, ep, in_ep, count = [], hashlib.sha256(), 0, 0, 0
80
+ with av.open(str(path)) as container:
81
+ stream = container.streams.video[0]
82
+ stream.codec_context.thread_count = 2
83
+ if stream.average_rate != Fraction(fps, 1):
84
+ raise ValueError("Unexpected video rate")
85
+ for frame in container.decode(stream):
86
+ if (frame.width, frame.height) != (640, 480):
87
+ raise ValueError("Unexpected camera resolution")
88
+ if frame.pts is None or abs(float(frame.pts * frame.time_base) - count / fps) > 1e-5:
89
+ raise ValueError("Decoded video has a dropped, shifted or duplicated timestamp")
90
+ if ep >= len(lengths):
91
+ raise ValueError("Extra decoded frames")
92
+ h.update(frame.to_ndarray(format="rgb24").tobytes())
93
+ in_ep += 1
94
+ count += 1
95
+ if in_ep == lengths[ep]:
96
+ result.append(h.hexdigest())
97
+ h, ep, in_ep = hashlib.sha256(), ep + 1, 0
98
+ if count != total or ep != len(lengths) or in_ep:
99
+ raise ValueError(f"Decoded video length mismatch: {count} != {total}")
100
+ return result
101
+
102
+
103
+ def main() -> None:
104
+ spec = importlib.util.spec_from_file_location("existing_v21_converter", ROOT / "scripts/convert_lerobot3.0_to_2.1.py")
105
+ conv = importlib.util.module_from_spec(spec)
106
+ spec.loader.exec_module(conv)
107
+ DEST.mkdir(parents=True, exist_ok=True)
108
+ db = sqlite3.connect(f"file:{CAMPAIGN / 'production.sqlite3'}?mode=ro", uri=True)
109
+ db.row_factory = sqlite3.Row
110
+ summary = []
111
+ for number, release in SHARDS:
112
+ shard = db.execute("SELECT id,task,state,qualified,profile FROM shards WHERE number=?", (number,)).fetchone()
113
+ assert shard["state"] == "complete" and shard["qualified"] == 5
114
+ rows = db.execute("SELECT id,payload FROM episodes WHERE shard=? ORDER BY native_episode", (shard["id"],)).fetchall()
115
+ episodes = [json.loads(r["payload"]) for r in rows]
116
+ source = Path(episodes[0]["dataset"])
117
+ result = Path(episodes[0]["shard"])
118
+ source_hashes = hashes(source)
119
+ validation = json.loads((result / "validation.json").read_text())
120
+ assert len(episodes) == validation["accepted_episodes"] == 5 and validation["status"] == "passed"
121
+ assert all(x["quality"]["passed"] and all(x["quality"]["checks"].values()) for x in validation["episode_checks"])
122
+ target = DEST / release
123
+ if target.exists():
124
+ raise FileExistsError(f"Refuse to overwrite prepared release: {target}")
125
+ target.mkdir()
126
+ records = conv.load_episode_records(source)
127
+ info = conv.load_info(source)
128
+ assert info["codebase_version"] == "v3.0" and info["fps"] == 25
129
+ assert len(records) == 5 and [int(x["episode_index"]) for x in records] == list(range(5))
130
+ cameras = sorted(k for k, v in info["features"].items() if v["dtype"] == "video")
131
+ assert cameras == ["observation.images.cam_high", "observation.images.cam_left_wrist", "observation.images.cam_right_wrist"]
132
+ chunks = int(info["chunks_size"])
133
+ conv.convert_info(source, target, records, cameras)
134
+ conv.copy_global_stats(source, target)
135
+ conv.convert_tasks(source, target)
136
+ conv.convert_data(source, target, records, chunks)
137
+ conv.convert_episodes_metadata(target, records)
138
+ lengths = [int(r["length"]) for r in records]
139
+ videos = []
140
+ for camera in cameras:
141
+ source_video = source / info["video_path"].format(video_key=camera, chunk_index=0, file_index=0)
142
+ expected = decoded_hashes(source_video, lengths, 25)
143
+ for record, expected_rgb in zip(records, expected):
144
+ ep = int(record["episode_index"])
145
+ destination = target / conv.LEGACY_VIDEO_PATH_TEMPLATE.format(episode_chunk=ep // chunks, episode_index=ep, video_key=camera)
146
+ proof = packet_split(source_video, destination, float(record[f"videos/{camera}/from_timestamp"]), int(record["length"]), 25)
147
+ actual_rgb = decoded_hashes(destination, [int(record["length"])], 25)[0]
148
+ assert expected_rgb == actual_rgb
149
+ videos.append({"episode_index": ep, "camera": camera, "frames": int(record["length"]), "fps": 25, "width": 640, "height": 480, "source_rgb_sha256": expected_rgb, "converted_rgb_sha256": actual_rgb, **proof})
150
+ arrays = []
151
+ source_table = pq.read_table(source / info["data_path"].format(chunk_index=0, file_index=0))
152
+ for record in records:
153
+ ep = int(record["episode_index"])
154
+ original = source_table.slice(int(record["dataset_from_index"]), int(record["length"])).replace_schema_metadata(None)
155
+ transformed = pq.read_table(target / conv.LEGACY_DATA_PATH_TEMPLATE.format(episode_chunk=ep // chunks, episode_index=ep))
156
+ assert original.equals(transformed)
157
+ for key in ("observation.state", "action"):
158
+ arr = np.stack(transformed[key].to_pylist())
159
+ assert arr.shape == (int(record["length"]), 14) and np.isfinite(arr).all()
160
+ assert np.allclose(np.asarray(transformed["timestamp"].to_pylist()), np.arange(int(record["length"]))/25, atol=1e-5, rtol=0)
161
+ arrays.append({"episode_index": ep, "all_arrow_columns_values_exact": True, "finite_14d_state_action": True, "timestamps_25hz": True, "frames": int(record["length"])})
162
+ assert hashes(source) == source_hashes
163
+ provenance = target / "provenance"
164
+ provenance.mkdir()
165
+ source_release = DEST.parent / release
166
+ if source_release.is_dir():
167
+ shutil.copytree(source_release / "provenance", provenance / "source_release")
168
+ shutil.copy2(source_release / "release_manifest.json", provenance / "source_release_manifest.json")
169
+ (provenance / "episodes.jsonl").write_text("".join(json.dumps(e, ensure_ascii=False, allow_nan=False) + "\n" for e in episodes))
170
+ write_json(provenance / "source_validation.json", validation)
171
+ output_hashes = hashes(target)
172
+ receipt = {"status": "passed", "release_id": release, "task": shard["task"], "source_shard_id": shard["id"], "source_profile_id": shard["profile"], "source_dataset": str(source), "output_dataset": str(target), "source_format": "v3.0", "output_format": "v2.1", "episodes": 5, "frames": sum(lengths), "fps": 25, "independent_physical_episode_count_added": 0, "source_dataset_unchanged": True, "source_file_sha256": source_hashes, "converted_file_sha256": output_hashes, "data_checks": arrays, "video_checks": videos, "canonical_episode_ids": [e["id"] for e in episodes], "existing_converter_sha256": sha(ROOT / "scripts/convert_lerobot3.0_to_2.1.py"), "conversion_script_sha256": sha(Path(__file__)), "training_executed": False, "objects_repo_id": None, "hf_revision": None}
173
+ write_json(provenance / "conversion_receipt.json", receipt)
174
+ (target / "README.md").write_text(f"# {release}\n\n{shard['task']}: 5 complete validated native trajectories, {sum(lengths)} frames, 25 Hz, 14-dimensional CobotMagic states and actions, three 640×480 cameras.\n\nThis is a genuine LeRobot v2.1 derivative of sealed native v3.0 shard `{shard['id']}`. State/action and every other Arrow column remain exact. Videos are losslessly remuxed at verified episode keyframes; every decoded RGB frame matches the source. Canonical episode, object and variant IDs and source hashes are in `provenance/episodes.jsonl`. This conversion creates zero new physical trajectories.\n\nThe v2.1 layout is intended for the pinned older π0.5 LeRobot loader. Training has not been run on this release. Geometry is still stored locally; its canonical IDs, exact SHA-256 and scale are recorded without claiming a Hugging Face object revision. Only train split is assigned; no independent evaluation split is claimed.\n")
175
+ write_json(target / "release_manifest.json", {"schema_version": "task2000.hf_derived_release.v1", "release_id": release, "task": shard["task"], "episodes": 5, "source_dataset_codebase_version": "v3.0", "dataset_codebase_version": "v2.1", "conversion_receipt": "provenance/conversion_receipt.json", "files": hashes(target), "hf_revision": None, "training_executed": False})
176
+ summary.append({"release": release, "dataset": str(target), "episodes": 5, "frames": sum(lengths), "receipt_sha256": sha(provenance / "conversion_receipt.json")})
177
+ print(json.dumps(summary[-1]), flush=True)
178
+ write_json(DEST / "conversion_summary.json", {"status": "passed", "releases": summary, "episodes": 10, "new_independent_trajectories": 0})
179
+
180
+
181
+ if __name__ == "__main__":
182
+ main()
items_handover_aug_r001/provenance/conversion_receipt.json ADDED
@@ -0,0 +1,312 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "status": "passed",
3
+ "release_id": "items_handover_aug_r001",
4
+ "task": "items_handover",
5
+ "source_shard_id": "items_handover_shard_000508",
6
+ "source_profile_id": "items_handover_profile_e7037c1630f84491",
7
+ "source_dataset": "/home/graphvix/projects/RoboSynChallenge/web/runs/data_generation/task2000_v1/shards/items_handover_shard_000508/result/dataset/cobotmagic_Sim_items_handover_000",
8
+ "output_dataset": "/home/graphvix/projects/RoboSynChallenge/web/runs/data_generation/task2000_v1/release_staging/hf_initial_task_release_v1/compatible_v21/items_handover_aug_r001",
9
+ "source_format": "v3.0",
10
+ "output_format": "v2.1",
11
+ "episodes": 5,
12
+ "frames": 2185,
13
+ "fps": 25,
14
+ "independent_physical_episode_count_added": 0,
15
+ "source_dataset_unchanged": true,
16
+ "source_file_sha256": {
17
+ "data/chunk-000/file-000.parquet": "131eb7f2bd992eee981a42397a89e53ee1c0376d2805edf02677b14122ddb3d0",
18
+ "meta/episodes/chunk-000/file-000.parquet": "badbac7eedf43bdeb59ecc68a8e148830b4800261d1cabe449283c253d42f7aa",
19
+ "meta/info.json": "a26e76b825beeb29efd5e79ecd50c73fd3a8918dce8ff733ce5f4198e8ba784d",
20
+ "meta/stats.json": "f8082d92256ac7d9c4426210ace5d7fbe9112cd80ab11ec43d368719d8775229",
21
+ "meta/tasks.parquet": "79cffa5fd4ea0cc5b2ba603f643c642809a202683ad062c69b7358465db3966f",
22
+ "videos/observation.images.cam_high/chunk-000/file-000.mp4": "5ab8a42cc7bf3d3469b17cd87e5d8e7a95baeb33b14fe42284369b4569cddbcf",
23
+ "videos/observation.images.cam_left_wrist/chunk-000/file-000.mp4": "0391f42b67606f2a05682fb115bb42ab2e929e1d61ae004948f4eb756e262d59",
24
+ "videos/observation.images.cam_right_wrist/chunk-000/file-000.mp4": "4092aa214fdaf2306240630a94210c1832baa7295f767e6c41f28ecc4b9d5f12"
25
+ },
26
+ "converted_file_sha256": {
27
+ "data/chunk-000/episode_000000.parquet": "76d4faead309285d1717ff17f440978f58843b5be5758a84cefa160c36e3679d",
28
+ "data/chunk-000/episode_000001.parquet": "5af8c331a7450d5a5beab0643f0a5192c27cd6b854a3f108de83d9ddcf33fef6",
29
+ "data/chunk-000/episode_000002.parquet": "d945eb88a9018152be0ba23c2481bd38b4335214e5416c3a37b3ca504c377ce8",
30
+ "data/chunk-000/episode_000003.parquet": "6c45dcc3f587eeb5cb9200f56542ff97dec4022e212f44f2f619c2cbb79bf493",
31
+ "data/chunk-000/episode_000004.parquet": "833ba8e696e4aeb50b6f849ad4020c310276ce92e3c9cabf8f3d07c4903e6674",
32
+ "meta/episodes.jsonl": "64ce7c7092bda5ac1bca6f27ba10e968378d8f6bbf54ebda652c7b442b0b69a9",
33
+ "meta/episodes_stats.jsonl": "e81edb4c259f48fa0b09e479a5f5c3cc88f2110f1db87e209394f6883dcbaa63",
34
+ "meta/info.json": "95fdee07042bafc81d526d4cdbaaeb2b230830f50a31c5deddec858357fceb2c",
35
+ "meta/stats.json": "f8082d92256ac7d9c4426210ace5d7fbe9112cd80ab11ec43d368719d8775229",
36
+ "meta/tasks.jsonl": "1a97d4240c5c68634ab1554a777e3e0f2d5ed1da21a309aa93f679a2d44ca135",
37
+ "provenance/episodes.jsonl": "02bf107813c12dcd3f1ac2918c5bbcc6ea0413d0bdafbb002572693046654bda",
38
+ "provenance/source_release/action_config.json": "3e032a04c6f64641d5a4585c01ffccb17d54ffbfb3c7a97392618dce68dd66a9",
39
+ "provenance/source_release/episodes.jsonl": "f6514d9b45a442cadb045103600571bdc3fe95e66d86a05bfa894ee24f998a81",
40
+ "provenance/source_release/gym_config.json": "0d41c985fae147c7a5557544805bbaeac715fa0d21f682ecea270ccb01d03d54",
41
+ "provenance/source_release/production_metadata.json": "e57d05f93a3f14ecf8e4845fcfe64bdeec4723ea9049dcecc3826b4ce443e237",
42
+ "provenance/source_release/profile.json": "75e31f13a1ac60b1581f81ff902e61aa52d3757fbb811d2763b6cf32e9feb4f9",
43
+ "provenance/source_release/release_validation.json": "c94db8c669ec02548e96f6107da53ca323f77eb3268f57c80507dc532e4a45ac",
44
+ "provenance/source_release/source_READY": "cf7e18c4666ad030a537b10f18535a128660f2e8be6c254fad019a75eebc4e52",
45
+ "provenance/source_release/source_manifest.json": "11e1e126bff3a6b1cb1118c1c991ef0c58e7a17dab2572e9a32770e10a73edc8",
46
+ "provenance/source_release/source_receipt.json": "1e225104cd372a0eb5be5f718a721a64565691612085ca2e6ee6e25b9f7221ec",
47
+ "provenance/source_release/source_validation.json": "0079a239e1604845e02f81173d2012af322c0f918b75fa57a4697159e6abd4da",
48
+ "provenance/source_release_manifest.json": "f96b8de5a7a9eff3fc9829d50cb96f29e744a5f1697cb5477e3022bdf931186d",
49
+ "provenance/source_validation.json": "0079a239e1604845e02f81173d2012af322c0f918b75fa57a4697159e6abd4da",
50
+ "videos/chunk-000/observation.images.cam_high/episode_000000.mp4": "e788760ee03a0039cc685cea59dd5424c14c811ee5ea80bf318e5e896e07be6e",
51
+ "videos/chunk-000/observation.images.cam_high/episode_000001.mp4": "ebc22f28cdc9b78fef7eccad5fa96f4099e809cd9d1d24708e8110df1dcaabc6",
52
+ "videos/chunk-000/observation.images.cam_high/episode_000002.mp4": "2c3ee720a16d0448e9dcfc6c98c666ec533a841a586b38446fcff62eda5cb749",
53
+ "videos/chunk-000/observation.images.cam_high/episode_000003.mp4": "27b3053a9fd2efa076df57cce0e9088e1de8a350978532ab8b0f104a3a3dd7a3",
54
+ "videos/chunk-000/observation.images.cam_high/episode_000004.mp4": "5b436644675ee4d7f538e0dd52362d2228eadfc3d9b4b849cba14aa64bcca0b2",
55
+ "videos/chunk-000/observation.images.cam_left_wrist/episode_000000.mp4": "8641e2f017fbfe179ed27d59bff8b60a67bbf9a3f4359e726efa12ecd6136b02",
56
+ "videos/chunk-000/observation.images.cam_left_wrist/episode_000001.mp4": "ae5424dde3f477713e23104bca785c1c37f8d1ffcae7a945f02bc338e7a8a78a",
57
+ "videos/chunk-000/observation.images.cam_left_wrist/episode_000002.mp4": "c222ab490bb4b3117450396ead1eec49c4f51bcb7e9485b30e75a604ebc45e49",
58
+ "videos/chunk-000/observation.images.cam_left_wrist/episode_000003.mp4": "4c4ea9cbebc6a06124db30d920877b3b0abeacc771b6a43a457bf38c3ad9ca66",
59
+ "videos/chunk-000/observation.images.cam_left_wrist/episode_000004.mp4": "23ffa9b113ff17dfae86c4945796ea92bf8d5e166ef15257ed822a38d0d7768d",
60
+ "videos/chunk-000/observation.images.cam_right_wrist/episode_000000.mp4": "f56fca83c53a6a684999053a203e5e2688ffb42c6065bd33ec2a45cec34d9aba",
61
+ "videos/chunk-000/observation.images.cam_right_wrist/episode_000001.mp4": "91c3469745d1f14fe74bf8a3de685873529e7f95c4487b343095ab6b5cd38335",
62
+ "videos/chunk-000/observation.images.cam_right_wrist/episode_000002.mp4": "55d736880956052a19c83622cf6aee0cd246e8e106ce49ae00d723c7213dddf4",
63
+ "videos/chunk-000/observation.images.cam_right_wrist/episode_000003.mp4": "34a6cd0295d49527f927f81d16e06b1a5f70f7cb162332f711c34497957f80ff",
64
+ "videos/chunk-000/observation.images.cam_right_wrist/episode_000004.mp4": "f7f1dd4777ec8fe24ae2aeb39a69d64b697a62700ac8a5118b19709eae55e2ee"
65
+ },
66
+ "data_checks": [
67
+ {
68
+ "episode_index": 0,
69
+ "all_arrow_columns_values_exact": true,
70
+ "finite_14d_state_action": true,
71
+ "timestamps_25hz": true,
72
+ "frames": 437
73
+ },
74
+ {
75
+ "episode_index": 1,
76
+ "all_arrow_columns_values_exact": true,
77
+ "finite_14d_state_action": true,
78
+ "timestamps_25hz": true,
79
+ "frames": 437
80
+ },
81
+ {
82
+ "episode_index": 2,
83
+ "all_arrow_columns_values_exact": true,
84
+ "finite_14d_state_action": true,
85
+ "timestamps_25hz": true,
86
+ "frames": 437
87
+ },
88
+ {
89
+ "episode_index": 3,
90
+ "all_arrow_columns_values_exact": true,
91
+ "finite_14d_state_action": true,
92
+ "timestamps_25hz": true,
93
+ "frames": 437
94
+ },
95
+ {
96
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items_handover_aug_r001/provenance/source_release/episodes.jsonl ADDED
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