Datasets:
Update README: 145 episodes, updated task distribution after deletions
Browse files
README.md
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@@ -29,12 +29,10 @@ RGB-D hand manipulation dataset captured with iPhone 13 TrueDepth sensor for hum
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| Metric | Value |
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|--------|-------|
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| Episodes |
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| Total Frames | ~
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| FPS | 30 |
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| Tasks | 12 manipulation tasks |
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| Total Duration | ~40 minutes |
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| Avg Episode Length | ~16.3 seconds |
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### Task Distribution
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| 7 | Get out of the room and close the door behind you. | 58–66 | 9 |
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| 8 | Put the sandals in the right place. | 67–76 | 10 |
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| 9 | Put the cleaning cloth in the laundry basket. | 77–86 | 10 |
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| 10 | Screw the cap back on the bottle. | 87–
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| 11 | Tuck the chairs into the table. |
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| 12 | Put the dishes in the sink. |
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---
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│
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├── data/
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│ ├── chunk-000/ # Parquet files (episodes 0-99)
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│
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│ │ └── ...
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│ └── chunk-001/ # Parquet files (episodes 100-146)
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│ ├── episode_000100.parquet
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│ └── ...
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│
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├── videos/
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│ ├── chunk-000/rgb/ # MP4 videos (episodes 0-99)
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│
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│ │ └── ...
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│ └── chunk-001/rgb/ # MP4 videos (episodes 100-146)
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│ ├── episode_000100.mp4
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│ └── ...
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│
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├── meta/
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│ ├── info.json # Dataset configuration (LeRobot format)
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│ ├── stats.json # Feature
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│ ├── events.json # Disturbance & recovery annotations
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│ └── annotations_motion_v1_frames.json
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│
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└── README.md
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```
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| Column | Type | Description |
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|--------|------|-------------|
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| `episode_index` | int64 | Episode number (0–
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| `frame_index` | int64 | Frame within episode |
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| `timestamp` | float64 | Time in seconds |
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| `language_instruction` | string | Task description |
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| `observation.camera_pose` | float[6] | Camera 6-DoF (x, y, z, roll, pitch, yaw) |
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| `observation.left_hand` | float[9] | Left hand keypoints
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| `observation.right_hand` | float[9] | Right hand keypoints
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| `action.camera_delta` | float[6] | Camera delta 6-DoF |
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| `action.left_hand_delta` | float[9] | Left hand delta keypoints |
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| `action.right_hand_delta` | float[9] | Right hand delta keypoints |
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| `rgb` | video | Synchronized RGB video frame |
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###
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**Coordinate System:**
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- Origin: Camera (iPhone TrueDepth)
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- X: Right (
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- Y: Down (positive)
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- Z: Forward (positive, into scene)
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---
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## Motion Semantics Annotations
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**File:** `meta/annotations_motion_v1_frames.json`
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Coarse temporal segmentation with motion intent, phase, and error labels.
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### Motion Types
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`grasp` | `pull` | `align` | `fold` | `smooth` | `insert` | `rotate` | `open` | `close` | `press` | `hold` | `release` | `place`
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---
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## Events Metadata
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**File:** `meta/events.json`
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Disturbances and recovery actions for select episodes.
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### Disturbance Types
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| Type | Description |
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|------|-------------|
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| `OCCLUSION` | Hand temporarily blocked from camera |
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| `TARGET_MOVED` | Object shifted unexpectedly |
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| `SLIP` | Object slipped during grasp |
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| `COLLISION` | Unintended contact |
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| `DEPTH_DROPOUT` | Depth sensor lost valid readings |
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### Recovery Actions
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| Action | Description |
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|--------|-------------|
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| `REGRASP` | Release and re-acquire object |
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| `REACH_ADJUST` | Modify approach trajectory |
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| `ABORT` | Stop current action |
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| `REPLAN` | Compute new action sequence |
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---
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episode = dataset[0]
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state = episode["observation.camera_pose"] # [6] camera 6-DoF
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rgb = episode["observation.images.rgb"] # Video frame
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task = episode["language_instruction"] # "Fold the t-shirt on the bed."
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```
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repo_type="dataset"
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df = pd.read_parquet(path)
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print(df["language_instruction"].iloc[0])
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print(f"Frames: {len(df)}")
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```
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---
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## Citation
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If you use this dataset in your research, please cite:
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```bibtex
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@dataset{dynamic_intelligence_2025,
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author = {Dynamic Intelligence},
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---
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## Hand Landmark Reference
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Each hand has tracked joints. The `observation.left_hand` and `observation.right_hand` contain 3D keypoints for key finger joints.
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---
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## Visualizer
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Explore the dataset interactively: [DI Hand Pose Sample Dataset Viewer](https://huggingface.co/spaces/DynamicIntelligence/dynamic_intelligence_sample_data)
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| Metric | Value |
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|--------|-------|
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| Episodes | 145 |
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| Total Frames | ~59,000 |
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| FPS | 30 |
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| Tasks | 12 manipulation tasks |
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### Task Distribution
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| 7 | Get out of the room and close the door behind you. | 58–66 | 9 |
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| 8 | Put the sandals in the right place. | 67–76 | 10 |
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| 9 | Put the cleaning cloth in the laundry basket. | 77–86 | 10 |
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| 10 | Screw the cap back on the bottle. | 87–95 | 9 |
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| 11 | Tuck the chairs into the table. | 96–126 | 31 |
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| 12 | Put the dishes in the sink. | 127–144 | 18 |
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---
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│
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├── data/
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│ ├── chunk-000/ # Parquet files (episodes 0-99)
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│ └── chunk-001/ # Parquet files (episodes 100-144)
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│
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├── videos/
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│ ├── chunk-000/rgb/ # MP4 videos (episodes 0-99)
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│ └── chunk-001/rgb/ # MP4 videos (episodes 100-144)
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│
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├── meta/
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│ ├── info.json # Dataset configuration (LeRobot format)
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│ ├── stats.json # Feature statistics
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│ ├── events.json # Disturbance & recovery annotations
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│ └── annotations_motion_v1_frames.json
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│
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└── README.md
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```
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| Column | Type | Description |
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|--------|------|-------------|
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| `episode_index` | int64 | Episode number (0–144) |
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| `frame_index` | int64 | Frame within episode |
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| `timestamp` | float64 | Time in seconds |
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| `language_instruction` | string | Task description |
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| `observation.camera_pose` | float[6] | Camera 6-DoF (x, y, z, roll, pitch, yaw) |
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| `observation.left_hand` | float[9] | Left hand keypoints |
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| `observation.right_hand` | float[9] | Right hand keypoints |
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| `action.camera_delta` | float[6] | Camera delta 6-DoF |
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| `action.left_hand_delta` | float[9] | Left hand delta keypoints |
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| `action.right_hand_delta` | float[9] | Right hand delta keypoints |
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### Coordinate System
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- Origin: Camera (iPhone TrueDepth)
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- X: Right, Y: Down, Z: Forward (into scene)
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---
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episode = dataset[0]
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state = episode["observation.camera_pose"] # [6] camera 6-DoF
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task = episode["language_instruction"] # "Fold the t-shirt on the bed."
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```
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repo_type="dataset"
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)
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df = pd.read_parquet(path)
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print(df["language_instruction"].iloc[0])
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```
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---
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## Citation
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```bibtex
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@dataset{dynamic_intelligence_2025,
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author = {Dynamic Intelligence},
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---
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## Visualizer
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Explore the dataset interactively: [DI Hand Pose Sample Dataset Viewer](https://huggingface.co/spaces/DynamicIntelligence/dynamic_intelligence_sample_data)
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