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zhuxh-nvidia nv-shalinj commited on
Commit
f0a3e9a
·
1 Parent(s): f3c2ad6

Add Track 2 whole-body reconstruction dataset (#2)

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- Add Track 2 whole-body reconstruction dataset (0ea7577ec04d29b6bab0f9549d2c51a2bd3fd54d)
- Simplify Track 2 README (723ece5d24e8a679c9085b6c65f4b407bae416db)
- Align Track 2 README with Track 3 style (ffbb62aa4615aefe6623321404a6b11fbb21400b)


Co-authored-by: Shalin <nv-shalinj@users.noreply.huggingface.co>

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Files changed (50) hide show
  1. .gitattributes +29 -0
  2. track_2/.gitignore +4 -0
  3. track_2/README.md +84 -0
  4. track_2/data/chunk-000/episode_000000.parquet +3 -0
  5. track_2/data/chunk-000/episode_000001.parquet +3 -0
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  31. track_2/data/chunk-000/episode_000027.parquet +3 -0
  32. track_2/data/chunk-000/episode_000028.parquet +3 -0
  33. track_2/data/chunk-000/episode_000029.parquet +3 -0
  34. track_2/mesh/baseball_bat/baseball_bat.glb +3 -0
  35. track_2/mesh/big_black_box/big_black_box.glb +3 -0
  36. track_2/mesh/big_red_bowl/big_red_bowl.glb +3 -0
  37. track_2/mesh/black_platform/black_platform.glb +3 -0
  38. track_2/mesh/blue_easter_basket/blue_easter_basket.glb +3 -0
  39. track_2/mesh/blue_trash_can/blue_trash_can.glb +3 -0
  40. track_2/mesh/cane/cane.glb +3 -0
  41. track_2/mesh/contigo_coffee_mug/contigo_coffee_mug.glb +3 -0
  42. track_2/mesh/cyan_water_bottle/cyan_water_bottle.glb +3 -0
  43. track_2/mesh/iron/iron.glb +3 -0
  44. track_2/mesh/light_blue_book/light_blue_book.glb +3 -0
  45. track_2/mesh/monitor/monitor.glb +3 -0
  46. track_2/mesh/rice_cooker/rice_cooker.glb +3 -0
  47. track_2/mesh/rolling_luggage/rolling_luggage.glb +3 -0
  48. track_2/mesh/round_table/round_table.glb +3 -0
  49. track_2/mesh/skateboard/skateboard.glb +3 -0
  50. track_2/mesh/skinny_wood_chair/skinny_wood_chair.glb +3 -0
.gitattributes CHANGED
@@ -69,3 +69,32 @@ track_3/mesh/white_pot_lid/white_pot_lid.glb filter=lfs diff=lfs merge=lfs -text
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  track_3/mesh/wooden_piece_1/wooden_piece_1.glb filter=lfs diff=lfs merge=lfs -text
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  track_3/mesh/wooden_piece_2/wooden_piece_2.glb filter=lfs diff=lfs merge=lfs -text
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  track_3/mesh/wooden_spoon/wooden_spoon.glb filter=lfs diff=lfs merge=lfs -text
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  track_3/mesh/wooden_piece_1/wooden_piece_1.glb filter=lfs diff=lfs merge=lfs -text
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  track_3/mesh/wooden_piece_2/wooden_piece_2.glb filter=lfs diff=lfs merge=lfs -text
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  track_3/mesh/wooden_spoon/wooden_spoon.glb filter=lfs diff=lfs merge=lfs -text
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+ track_2/mesh/baseball_bat/baseball_bat.glb filter=lfs diff=lfs merge=lfs -text
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+ track_2/mesh/big_black_box/big_black_box.glb filter=lfs diff=lfs merge=lfs -text
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+ track_2/mesh/big_red_bowl/big_red_bowl.glb filter=lfs diff=lfs merge=lfs -text
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+ track_2/mesh/black_platform/black_platform.glb filter=lfs diff=lfs merge=lfs -text
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+ track_2/mesh/blue_easter_basket/blue_easter_basket.glb filter=lfs diff=lfs merge=lfs -text
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+ track_2/mesh/blue_trash_can/blue_trash_can.glb filter=lfs diff=lfs merge=lfs -text
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+ track_2/mesh/cane/cane.glb filter=lfs diff=lfs merge=lfs -text
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+ track_2/mesh/contigo_coffee_mug/contigo_coffee_mug.glb filter=lfs diff=lfs merge=lfs -text
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+ track_2/mesh/cyan_water_bottle/cyan_water_bottle.glb filter=lfs diff=lfs merge=lfs -text
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+ track_2/mesh/iron/iron.glb filter=lfs diff=lfs merge=lfs -text
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+ track_2/mesh/light_blue_book/light_blue_book.glb filter=lfs diff=lfs merge=lfs -text
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+ track_2/mesh/monitor/monitor.glb filter=lfs diff=lfs merge=lfs -text
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+ track_2/mesh/rice_cooker/rice_cooker.glb filter=lfs diff=lfs merge=lfs -text
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+ track_2/mesh/rolling_luggage/rolling_luggage.glb filter=lfs diff=lfs merge=lfs -text
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+ track_2/mesh/round_table/round_table.glb filter=lfs diff=lfs merge=lfs -text
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+ track_2/mesh/skateboard/skateboard.glb filter=lfs diff=lfs merge=lfs -text
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+ track_2/mesh/skinny_wood_chair/skinny_wood_chair.glb filter=lfs diff=lfs merge=lfs -text
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+ track_2/mesh/snack_box/snack_box.glb filter=lfs diff=lfs merge=lfs -text
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+ track_2/mesh/spray_bottle/spray_bottle.glb filter=lfs diff=lfs merge=lfs -text
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+ track_2/mesh/squeegee/squeegee.glb filter=lfs diff=lfs merge=lfs -text
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+ track_2/mesh/step_ladder/step_ladder.glb filter=lfs diff=lfs merge=lfs -text
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+ track_2/mesh/tall_bar_stool/tall_bar_stool.glb filter=lfs diff=lfs merge=lfs -text
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+ track_2/mesh/toy_stroller/toy_stroller.glb filter=lfs diff=lfs merge=lfs -text
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+ track_2/mesh/traffic_cone/traffic_cone.glb filter=lfs diff=lfs merge=lfs -text
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+ track_2/mesh/vacuum/vacuum.glb filter=lfs diff=lfs merge=lfs -text
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+ track_2/mesh/watering_can/watering_can.glb filter=lfs diff=lfs merge=lfs -text
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+ track_2/mesh/wet_floor_sign/wet_floor_sign.glb filter=lfs diff=lfs merge=lfs -text
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+ track_2/mesh/white_desk/white_desk.glb filter=lfs diff=lfs merge=lfs -text
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+ track_2/mesh/woven_basket/woven_basket.glb filter=lfs diff=lfs merge=lfs -text
track_2/.gitignore ADDED
@@ -0,0 +1,4 @@
 
 
 
 
 
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+ __pycache__/
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+ .mypy_cache/
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+ .ruff_cache/
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+ .DS_Store
track_2/README.md ADDED
@@ -0,0 +1,84 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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+ # Track 2
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+
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+ Human-object interaction sequences reconstructed with SOMA-X from four
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+ frame-synchronized RGB views. Every episode includes a full-body pose and one tracked
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+ object with a textured 3D mesh. Object poses are expressed as **`world_T_object` in the
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+ source OpenCV world frame**, so placing the mesh at a logged pose recovers its
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+ reconstructed location.
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+
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+ | | |
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+ |---|---|
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+ | Episodes | 30 |
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+ | Frames | 22,990 (440–1,003 per episode, mean 766) |
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+ | Rate | 30 fps nominal |
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+ | Tasks | 30 |
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+ | Cameras | 4 streams, 120 clips |
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+ | Objects | 29, each with a textured mesh |
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+
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+ ## Layout
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+
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+ ```
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+ track_2/
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+ ├── data/chunk-000/episode_0000NN.parquet human + object pose, one row per frame
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+ ├── videos/chunk-000/observation.images.<camera>/episode_0000NN.mp4
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+ ├── mesh/<object>/<object>.glb textured mesh
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+ └── meta/
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+ ├── info.json schema, counts, tasks, objects
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+ ├── episodes_metadata.jsonl episode → sequence, task, object, mesh
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+ ├── episodes.jsonl episode lengths and tasks
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+ ├── episodes_stats.jsonl per-episode feature statistics
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+ └── tasks.jsonl task descriptions
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+
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+ ```
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+
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+ ## Pose data
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+
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+ Each parquet has **13 columns**, one row per video frame:
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+
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+ ```
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+ observation.human.pose fixed_size_list<float32, 231>
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+ observation.human.translation fixed_size_list<float32, 3>
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+ observation.human.identity_coeffs fixed_size_list<float32, 45>
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+ observation.human.scale_params fixed_size_list<float32, 68>
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+ observation.human.bone_length_flexibles fixed_size_list<float32, 6>
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+ observation.object.pose fixed_size_list<float32, 7>
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+ observation.object.visible bool
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+ timestamp frame_index episode_index index task_index next.done
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+ ```
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+
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+ Each episode tracks exactly one object. Its name is stored in the parquet's schema
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+ metadata under `objects` and in `meta/episodes_metadata.jsonl` with the source sequence,
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+ task, and mesh path.
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+
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+ An object's name **is** its mesh folder: `white_desk` →
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+ `mesh/white_desk/white_desk.glb`.
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+
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+ ### Conventions
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+
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+ - **`observation.human.pose` contains 77 local rotation vectors in radians**, flattened
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+ in the joint order declared by `meta/info.json`.
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+ - Human translation is in metres. Identity, scale, and flexible-bone values are the
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+ corresponding SOMA-X body-model parameters.
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+ - **`observation.object.pose` is `[x, y, z, qw, qx, qy, qz]`** — translation in metres,
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+ **quaternion w-first**.
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+ - **Object poses are `world_T_object`** in the source OpenCV world frame. Each parquet
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+ declares this in schema metadata under `pose_convention`.
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+ - When `observation.object.visible` is false the object pose is all zeros — a zero
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+ quaternion, not a rotation. **Filter on visibility before using a pose.**
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+
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+ ## Cameras
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+
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+ | Stream | Resolution | Kind |
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+ |---|---|---|
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+ | `back_stereo_camera_left` | 1536×1152 | colour, static third-person |
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+ | `front_stereo_camera_left` | 1536×1152 | colour, static third-person |
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+ | `left_stereo_camera_left` | 1536×1152 | colour, static third-person |
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+ | `right_stereo_camera_left` | 1536×1152 | colour, static third-person |
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+
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+ Video is **frame-exact with the parquets** — row *i* corresponds to frame *i* in every
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+ clip, verified across all 120. Files are byte-identical copies of the
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+ source H.264 videos; no concatenation or re-encoding was performed.
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+
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+ The supplied export has **no camera intrinsics or extrinsics**, so meshes cannot be
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+ projected into the images from this dataset alone. The source calibration sequence
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+ identifier is preserved per episode, but it is not a calibration matrix.
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