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Add remaining seven DexJoCo tasks with all native camera views

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  1. README.md +31 -13
  2. bimanual_assembly_delta_n100/episodes.json +0 -0
  3. bimanual_assembly_delta_n100/images.json +0 -0
  4. bimanual_assembly_delta_n100/ph_finetune/normalization.npz +3 -0
  5. bimanual_assembly_delta_n100/ph_finetune/train.npz +3 -0
  6. bimanual_assembly_delta_n100/ph_pretrain/normalization.npz +3 -0
  7. bimanual_assembly_delta_n100/ph_pretrain/train.npz +3 -0
  8. bimanual_assembly_delta_n100/videos.zip +3 -0
  9. bimanual_hanoi_delta_n100/episodes.json +0 -0
  10. bimanual_hanoi_delta_n100/images.json +0 -0
  11. bimanual_hanoi_delta_n100/ph_finetune/normalization.npz +3 -0
  12. bimanual_hanoi_delta_n100/ph_finetune/train.npz +3 -0
  13. bimanual_hanoi_delta_n100/ph_pretrain/normalization.npz +3 -0
  14. bimanual_hanoi_delta_n100/ph_pretrain/train.npz +3 -0
  15. bimanual_hanoi_delta_n100/videos.zip +3 -0
  16. bimanual_microwave_cook_delta_n100/episodes.json +0 -0
  17. bimanual_microwave_cook_delta_n100/images.json +0 -0
  18. bimanual_microwave_cook_delta_n100/ph_finetune/normalization.npz +3 -0
  19. bimanual_microwave_cook_delta_n100/ph_finetune/train.npz +3 -0
  20. bimanual_microwave_cook_delta_n100/ph_pretrain/normalization.npz +3 -0
  21. bimanual_microwave_cook_delta_n100/ph_pretrain/train.npz +3 -0
  22. bimanual_microwave_cook_delta_n100/videos.zip +3 -0
  23. bimanual_photograph_delta_n100/episodes.json +0 -0
  24. bimanual_photograph_delta_n100/images.json +0 -0
  25. bimanual_photograph_delta_n100/ph_finetune/normalization.npz +3 -0
  26. bimanual_photograph_delta_n100/ph_finetune/train.npz +3 -0
  27. bimanual_photograph_delta_n100/ph_pretrain/normalization.npz +3 -0
  28. bimanual_photograph_delta_n100/ph_pretrain/train.npz +3 -0
  29. bimanual_photograph_delta_n100/videos.zip +3 -0
  30. bimanual_unlock_ipad_delta_n100/episodes.json +0 -0
  31. bimanual_unlock_ipad_delta_n100/images.json +0 -0
  32. bimanual_unlock_ipad_delta_n100/ph_finetune/normalization.npz +3 -0
  33. bimanual_unlock_ipad_delta_n100/ph_finetune/train.npz +3 -0
  34. bimanual_unlock_ipad_delta_n100/ph_pretrain/normalization.npz +3 -0
  35. bimanual_unlock_ipad_delta_n100/ph_pretrain/train.npz +3 -0
  36. bimanual_unlock_ipad_delta_n100/videos.zip +3 -0
  37. fold_glasses_delta_n100/episodes.json +0 -0
  38. fold_glasses_delta_n100/images.json +0 -0
  39. fold_glasses_delta_n100/ph_finetune/normalization.npz +3 -0
  40. fold_glasses_delta_n100/ph_finetune/train.npz +3 -0
  41. fold_glasses_delta_n100/ph_pretrain/normalization.npz +3 -0
  42. fold_glasses_delta_n100/ph_pretrain/train.npz +3 -0
  43. fold_glasses_delta_n100/videos.zip +3 -0
  44. manifest.json +303 -0
  45. water_plant_delta_n100/episodes.json +0 -0
  46. water_plant_delta_n100/images.json +0 -0
  47. water_plant_delta_n100/ph_finetune/normalization.npz +3 -0
  48. water_plant_delta_n100/ph_finetune/train.npz +3 -0
  49. water_plant_delta_n100/ph_pretrain/normalization.npz +3 -0
  50. water_plant_delta_n100/ph_pretrain/train.npz +3 -0
README.md CHANGED
@@ -10,16 +10,25 @@ tags:
10
 
11
  Processed image-and-state demonstrations. Action layout: world position delta (3),
12
  world relative SO(3) rotation vector (3), absolute Allegro joint targets (16).
 
 
13
  Deltas use the measured observation at the same timestep. Both states and actions
14
  are min-max normalized; BC and RL share the same normalization statistics.
15
  Observation version: `initial_object_pose_v1`.
16
 
17
- | Task | Episodes | Transitions |
18
- | --- | ---: | ---: |
19
- | pinch_tongs | 100 | 40469 |
20
- | pick_bucket | 100 | 43581 |
21
- | hammer_nail | 100 | 21563 |
22
- | click_mouse | 100 | 32702 |
 
 
 
 
 
 
 
23
 
24
  Each task contains `ph_pretrain/train.npz`, `ph_finetune/train.npz`, their
25
  `normalization.npz` files, and `episodes.json`. The manifest records SHA-256 hashes.
@@ -27,9 +36,10 @@ RL rewards and terminals are 1 only at each retained demonstration's final frame
27
  These are synthetic end-of-demo success labels, not replay-verified success times
28
  for the original recordings. No model checkpoints are included.
29
 
30
- ## RGB images (all four cameras)
31
 
32
- Every selected episode includes `front`, `wrist`, `ego_left`, and `ego_right`.
 
33
  The original MP4 files are preserved byte for byte, including their resolution.
34
  `images.json` maps each processed timestep to its exact source video frame;
35
  the same initial-prefix cut is used for states, delta actions, and images.
@@ -40,15 +50,17 @@ script automatically extracts and verifies them, preserving the original bytes.
40
  Use `agent.dataset.dexjoco_image.DexJoCoImageDataset` (BC) or
41
  `DexJoCoImageQLearningDataset` (offline RL) from the accompanying checkout.
42
  The loader returns RGB uint8 `(B, history, 3 * cameras, height, width)` in
43
- `conditions["rgb"]` and normalized robot proprioception (first 23 state columns)
 
44
  in `conditions["state"]`. Task/object privileged state is excluded by default.
45
  Frames are decoded on demand, with bounded caches and exact PTS-based seeking.
46
- Choose cameras and image size at training time; defaults are `front,wrist` and
47
- 224 x 224. The loader reads the published videos directly; no source-dataset
 
48
  download or offline image conversion is required.
49
 
50
  Choose the number of published episodes used for training with
51
- `max_n_episodes`; all four camera views remain available.
52
 
53
 
54
  ## Array format
@@ -58,7 +70,7 @@ Load NPZ files with `numpy.load(path, allow_pickle=False)`.
58
  | Key | Shape | Meaning |
59
  | --- | --- | --- |
60
  | `states` | `(T, obs_dim)` | Normalized observations, float32 |
61
- | `actions` | `(T, 22)` | Normalized pose deltas and absolute hand targets, float32 |
62
  | `traj_lengths` | `(N,)` | Episode lengths, int64; sum equals T |
63
  | `rewards`, `terminals` | `(T,)` | Finetuning split only, float32 |
64
 
@@ -70,6 +82,12 @@ Unnormalize actions before decoding them with the latest measured robot pose:
70
  `R_target = Exp(delta_rotvec) @ R_observed`. Hand targets stay absolute.
71
  The state and raw target quaternions use wxyz ordering.
72
 
 
 
 
 
 
 
73
  For `initial_object_pose_v1`, object pose features describe the initial object
74
  poses, matching the original recordings. They do not track moving objects.
75
 
 
10
 
11
  Processed image-and-state demonstrations. Action layout: world position delta (3),
12
  world relative SO(3) rotation vector (3), absolute Allegro joint targets (16).
13
+ This is 22 values for single-arm tasks; bimanual tasks concatenate right then
14
+ left arm blocks for 44 values, preserving each recorded hand's joint ordering.
15
  Deltas use the measured observation at the same timestep. Both states and actions
16
  are min-max normalized; BC and RL share the same normalization statistics.
17
  Observation version: `initial_object_pose_v1`.
18
 
19
+ | Task | Episodes | Transitions | State dimension | Action dimension |
20
+ | --- | ---: | ---: | ---: | ---: |
21
+ | pinch_tongs | 100 | 40469 | 31 | 22 |
22
+ | pick_bucket | 100 | 43581 | 38 | 22 |
23
+ | hammer_nail | 100 | 21563 | 38 | 22 |
24
+ | click_mouse | 100 | 32702 | 31 | 22 |
25
+ | fold_glasses | 100 | 53878 | 38 | 22 |
26
+ | water_plant | 100 | 27745 | 38 | 22 |
27
+ | bimanual_assembly | 100 | 54630 | 61 | 44 |
28
+ | bimanual_hanoi | 100 | 107764 | 50 | 44 |
29
+ | bimanual_microwave_cook | 100 | 68503 | 61 | 44 |
30
+ | bimanual_photograph | 100 | 34377 | 61 | 44 |
31
+ | bimanual_unlock_ipad | 100 | 41042 | 61 | 44 |
32
 
33
  Each task contains `ph_pretrain/train.npz`, `ph_finetune/train.npz`, their
34
  `normalization.npz` files, and `episodes.json`. The manifest records SHA-256 hashes.
 
36
  These are synthetic end-of-demo success labels, not replay-verified success times
37
  for the original recordings. No model checkpoints are included.
38
 
39
+ ## RGB images (all native cameras)
40
 
41
+ Single-arm episodes include `front`, `wrist`, `ego_left`, and `ego_right`.
42
+ Bimanual episodes include `ego`, `wrist_left`, and `wrist_right`.
43
  The original MP4 files are preserved byte for byte, including their resolution.
44
  `images.json` maps each processed timestep to its exact source video frame;
45
  the same initial-prefix cut is used for states, delta actions, and images.
 
50
  Use `agent.dataset.dexjoco_image.DexJoCoImageDataset` (BC) or
51
  `DexJoCoImageQLearningDataset` (offline RL) from the accompanying checkout.
52
  The loader returns RGB uint8 `(B, history, 3 * cameras, height, width)` in
53
+ `conditions["rgb"]` and normalized robot proprioception (first 23 state columns
54
+ for single-arm tasks, first 46 for bimanual tasks)
55
  in `conditions["state"]`. Task/object privileged state is excluded by default.
56
  Frames are decoded on demand, with bounded caches and exact PTS-based seeking.
57
+ Choose cameras and image size at training time; defaults are `front,wrist` for
58
+ single-arm tasks, all three cameras for bimanual tasks, and 224 x 224 pixels.
59
+ The loader reads the published videos directly; no source-dataset
60
  download or offline image conversion is required.
61
 
62
  Choose the number of published episodes used for training with
63
+ `max_n_episodes`; all native camera views remain available.
64
 
65
 
66
  ## Array format
 
70
  | Key | Shape | Meaning |
71
  | --- | --- | --- |
72
  | `states` | `(T, obs_dim)` | Normalized observations, float32 |
73
+ | `actions` | `(T, action_dim)` | Normalized pose deltas and absolute hand targets, float32 |
74
  | `traj_lengths` | `(N,)` | Episode lengths, int64; sum equals T |
75
  | `rewards`, `terminals` | `(T,)` | Finetuning split only, float32 |
76
 
 
82
  `R_target = Exp(delta_rotvec) @ R_observed`. Hand targets stay absolute.
83
  The state and raw target quaternions use wxyz ordering.
84
 
85
+ Bimanual state begins `[right_pose7, left_pose7, right_hand16, left_hand16]`.
86
+ Bimanual raw targets and `decode_actions` output instead use
87
+ `[right_pose7, right_hand16, left_pose7, left_hand16]`.
88
+ Before sending decoded targets to the simulator's policy-mode API, reorder
89
+ them to `[right_pose7, left_pose7, right_hand16, left_hand16]`.
90
+
91
  For `initial_object_pose_v1`, object pose features describe the initial object
92
  poses, matching the original recordings. They do not track moving objects.
93
 
bimanual_assembly_delta_n100/episodes.json ADDED
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manifest.json CHANGED
@@ -181,6 +181,309 @@
181
  "ego_right"
182
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