Update README.md

README.md

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----
-language:
-- en
-license: cc-by-nc-4.0
-size_categories:
-- 1K<n<10K
-task_categories:
-- video-classification
-- object-detection
-tags:
-- egocentric
-- dexterous-manipulation
-- hand-pose
-- robotics
-- embodied-ai
-- first-person
-- human-demonstration
-pretty_name: "OBayData Egocentric Dexterous Manipulation Demo"
-dataset_info:
-  config_name: default
-  splits:
-    - name: train
-      num_examples: 500
-    - name: test
-      num_examples: 100
----
-
-# OBayData Egocentric Dexterous Manipulation Demo
-
-## Dataset Description
-
-- **Homepage:** [obaydata.com](https://obaydata.com)
-- **Repository:** [obaydata/egocentric-data-collection](https://github.com/obaydata/egocentric-data-collection)
-- **Point of Contact:** contact@obaydata.com
-
-### Dataset Summary
-
-This is a **demo dataset** from [OBayData](https://obaydata.com), showcasing our egocentric dexterous manipulation data collection capabilities. It contains a curated subset of first-person human operation recordings captured with our multi-camera hardware setup across real-world scenarios.
-
-**This demo is intended for quality evaluation.** Full-scale data collection is available as a managed service — see [Production Data Service](#production-data-service) below.
-
-### Supported Tasks
-
-- **Action Recognition** — classify human manipulation actions from egocentric video
-- **Hand Pose Estimation** — predict 3D hand joint positions from first-person views
-- **Robot Learning from Human Demonstrations** — use as training signal for imitation learning and sim-to-real transfer
-- **Video Understanding** — temporal reasoning over long-horizon manipulation sequences
-- **Language-Grounded Manipulation** — map atomic language annotations to visual actions
-
-### Languages
-
-All annotations are in English.
-
-## Dataset Structure
-
-### Data Fields
-
-| Field | Type | Description |
-|---|---|---|
-| `video` | Video (MP4) | 1080p egocentric video from head-mounted camera |
-| `wrist_left` | Video (MP4) | 1080p video from left wrist camera |
-| `wrist_right` | Video (MP4) | 1080p video from right wrist camera |
-| `hand_pose` | JSON | Per-frame 3D hand joint positions (21 joints × 2 hands) |
-| `camera_extrinsics` | JSON | Per-frame camera pose (rotation + translation) |
-| `action_labels` | JSON | Temporal action segments with start/end timestamps and labels |
-| `language_annotations` | JSON | Atomic-level natural language descriptions of sub-actions |
-| `metadata` | JSON | Scenario type, session ID, operator ID, hardware config |
-
-### Data Splits
-
-| Split | Examples | Purpose |
-|---|---|---|
-| `train` | 500 | Model training and development |
-| `test` | 100 | Held-out evaluation |
-
-### Data Instances
-
-Each instance represents a single continuous manipulation session (typically 30 seconds to 5 minutes) with synchronized multi-view video and annotations.
-
-## Dataset Creation
-
-### Collection Process
-
-Data was collected using OBayData's standardized hardware rig:
-
-- **Head Camera** — head-mounted, capturing the egocentric viewpoint at 1080p / 30fps
-- **Dual Wrist Cameras** — left and right wrist-mounted cameras for close-up hand views
-- **Optional Tactile Gloves** — Manus METAGLOVES PRO for finger-level force and contact data (not included in this demo)
-- **Synchronization** — all streams are hardware-synchronized and temporally aligned
-
-Operators performed real manipulation tasks in authentic environments (not staged lab settings). Scenarios in this demo include kitchen tasks, object rearrangement, and tool use.
-
-### Annotation Pipeline
-
-1. **Camera Extrinsics** — estimated via structure-from-motion on the multi-view streams
-2. **Hand Pose Reconstruction** — 3D hand mesh fitting using multi-view optimization
-3. **Action Segmentation** — temporal boundaries annotated by trained human annotators
-4. **Language Annotations** — atomic-level descriptions written by annotators following a structured protocol (e.g., *"grasp the red mug handle with right hand"*, *"pour water into the bowl"*)
-
-All annotations undergo multi-stage quality review.
-
-### Source Data
-
-Recorded in real-world environments including residential kitchens, hotel rooms, and office spaces. No synthetic or simulated data.
-
-### Personal and Sensitive Information
-
-All operators provided informed consent. Faces are not visible in egocentric recordings. No personally identifiable information is included in the released annotations.
-
-## Considerations for Using the Data
-
-### Intended Uses
-
-- Evaluating OBayData's data quality before commissioning large-scale collection
-- Research in egocentric vision, hand-object interaction, and robot learning
-- Benchmarking action recognition and hand pose estimation models
-- Prototyping language-grounded manipulation systems
-
-### Out-of-Scope Uses
-
-- This demo is **not** large enough for training production foundation models — contact us for scaled collection
-- Not suitable for surveillance or biometric applications
-- Not intended for commercial redistribution
-
-### Limitations
-
-- Demo contains a limited subset of scenarios (full service covers 1,000+ scenario types)
-- Tactile glove data is not included in this release
-- Annotation density may vary across sessions
-
-## Production Data Service
-
-This demo represents a small fraction of OBayData's collection capabilities.
-
-### Full Service Specifications
-
-| Capability | Details |
-|---|---|
-| **Monthly Capacity** | 100,000 hours/month |
-| **Availability** | Deliveries starting May 2026 |
-| **Scenario Coverage** | 1,000+ real-world scenarios (hospitality, manufacturing, retail, logistics, food service, etc.) |
-| **Pricing** | $5.50–$100/hour depending on volume, annotation complexity, and hardware config |
-| **Custom Scenarios** | Define your own tasks, environments, and skill requirements |
-| **Benchmark Alignment** | RoboTwin 2.0, PI Olympics, and custom benchmark protocols |
-
-### Contact Us
-
-- **Website:** [obaydata.com](https://obaydata.com)
-- **Email:** simon.su@obaydata.com
-- **Company:** New Oriental Bay Limited (香港新东湾有限公司)
-
-## Citation
-
-```bibtex
-@dataset{obaydata2026egocentric,
-  title={OBayData Egocentric Dexterous Manipulation Demo},
-  author={OBayData Team},
-  year={2026},
-  url={https://huggingface.co/datasets/obaydata/egocentric-dexterous-manipulation-demo},
-  publisher={Hugging Face}
-}
-```
-
-## License
-
-This demo dataset is released under [CC BY-NC 4.0](https://creativecommons.org/licenses/by-nc/4.0/). Commercial data collection available under custom licensing — contact us for details.
-
-
-### 1. First-Person & Third-Person Egocentric Video Data
-Camera: First-person monocular RGB + four-corner positioning cameras.
-Output: MP4/AVI, 720p/1080p/2K, 15/30fps. Production: 500H/week.
-- **Code:** swm6
-
-### 2. EgoCentric First-Person Binocular Data (Pico Camera)
-Camera: First-person binocular RGB (overlapping FOV, mimicking human eyes).
-Panoramic camera (FOV ~70×40°). Intrinsic offset <1%, distortion param diff <10⁻³.
-Output: MP4/AVI, 720p/1080p/2K, 15/30fps. Production: 500H/week. Price: ¥140/valid hour.
-- **Code:** dcty
-
-> Full copyright provided for all data.
+---
+language:
+- en
+license: cc-by-nc-4.0
+size_categories:
+- 1K<n<10K
+task_categories:
+- video-classification
+- object-detection
+tags:
+- egocentric
+- dexterous-manipulation
+- hand-pose
+- robotics
+- embodied-ai
+- first-person
+- human-demonstration
+pretty_name: "OBayData Egocentric Dexterous Manipulation Demo"
+dataset_info:
+  config_name: default
+  splits:
+    - name: train
+      num_examples: 500
+    - name: test
+      num_examples: 100
+---
+
+# OBayData Egocentric Dexterous Manipulation Demo
+
+## Dataset Description
+
+- **Homepage:** [obaydata.com](https://obaydata.com)
+- **Repository:** [obaydata/egocentric-data-collection](https://github.com/obaydata/egocentric-data-collection)
+- **Point of Contact:** contact@obaydata.com
+
+### Dataset Summary
+
+This is a **demo dataset** from [OBayData](https://obaydata.com), showcasing our egocentric dexterous manipulation data collection capabilities. It contains a curated subset of first-person human operation recordings captured with our multi-camera hardware setup across real-world scenarios.
+
+**This demo is intended for quality evaluation.** Full-scale data collection is available as a managed service — see [Production Data Service](#production-data-service) below.
+
+### Supported Tasks
+
+- **Action Recognition** — classify human manipulation actions from egocentric video
+- **Hand Pose Estimation** — predict 3D hand joint positions from first-person views
+- **Robot Learning from Human Demonstrations** — use as training signal for imitation learning and sim-to-real transfer
+- **Video Understanding** — temporal reasoning over long-horizon manipulation sequences
+- **Language-Grounded Manipulation** — map atomic language annotations to visual actions
+
+### Languages
+
+All annotations are in English.
+
+## Dataset Structure
+
+### Data Fields
+
+| Field | Type | Description |
+|---|---|---|
+| `video` | Video (MP4) | 1080p egocentric video from head-mounted camera |
+| `wrist_left` | Video (MP4) | 1080p video from left wrist camera |
+| `wrist_right` | Video (MP4) | 1080p video from right wrist camera |
+| `hand_pose` | JSON | Per-frame 3D hand joint positions (21 joints × 2 hands) |
+| `camera_extrinsics` | JSON | Per-frame camera pose (rotation + translation) |
+| `action_labels` | JSON | Temporal action segments with start/end timestamps and labels |
+| `language_annotations` | JSON | Atomic-level natural language descriptions of sub-actions |
+| `metadata` | JSON | Scenario type, session ID, operator ID, hardware config |
+
+### Data Splits
+
+| Split | Examples | Purpose |
+|---|---|---|
+| `train` | 500 | Model training and development |
+| `test` | 100 | Held-out evaluation |
+
+### Data Instances
+
+Each instance represents a single continuous manipulation session (typically 30 seconds to 5 minutes) with synchronized multi-view video and annotations.
+
+## Dataset Creation
+
+### Collection Process
+
+Data was collected using OBayData's standardized hardware rig:
+
+- **Head Camera** — head-mounted, capturing the egocentric viewpoint at 1080p / 30fps
+- **Dual Wrist Cameras** — left and right wrist-mounted cameras for close-up hand views
+- **Optional Tactile Gloves** — Manus METAGLOVES PRO for finger-level force and contact data (not included in this demo)
+- **Synchronization** — all streams are hardware-synchronized and temporally aligned
+
+Operators performed real manipulation tasks in authentic environments (not staged lab settings). Scenarios in this demo include kitchen tasks, object rearrangement, and tool use.
+
+### Annotation Pipeline
+
+1. **Camera Extrinsics** — estimated via structure-from-motion on the multi-view streams
+2. **Hand Pose Reconstruction** — 3D hand mesh fitting using multi-view optimization
+3. **Action Segmentation** — temporal boundaries annotated by trained human annotators
+4. **Language Annotations** — atomic-level descriptions written by annotators following a structured protocol (e.g., *"grasp the red mug handle with right hand"*, *"pour water into the bowl"*)
+
+All annotations undergo multi-stage quality review.
+
+### Source Data
+
+Recorded in real-world environments including residential kitchens, hotel rooms, and office spaces. No synthetic or simulated data.
+
+### Personal and Sensitive Information
+
+All operators provided informed consent. Faces are not visible in egocentric recordings. No personally identifiable information is included in the released annotations.
+
+## Considerations for Using the Data
+
+### Intended Uses
+
+- Evaluating OBayData's data quality before commissioning large-scale collection
+- Research in egocentric vision, hand-object interaction, and robot learning
+- Benchmarking action recognition and hand pose estimation models
+- Prototyping language-grounded manipulation systems
+
+### Out-of-Scope Uses
+
+- This demo is **not** large enough for training production foundation models — contact us for scaled collection
+- Not suitable for surveillance or biometric applications
+- Not intended for commercial redistribution
+
+### Limitations
+
+- Demo contains a limited subset of scenarios (full service covers 1,000+ scenario types)
+- Tactile glove data is not included in this release
+- Annotation density may vary across sessions
+
+## Production Data Service
+
+This demo represents a small fraction of OBayData's collection capabilities.
+
+### Full Service Specifications
+
+| Capability | Details |
+|---|---|
+| **Monthly Capacity** | 100,000 hours/month |
+| **Availability** | Deliveries starting May 2026 |
+| **Scenario Coverage** | 1,000+ real-world scenarios (hospitality, manufacturing, retail, logistics, food service, etc.) |
+| **Pricing** | $5.50–$100/hour depending on volume, annotation complexity, and hardware config |
+| **Custom Scenarios** | Define your own tasks, environments, and skill requirements |
+| **Benchmark Alignment** | RoboTwin 2.0, PI Olympics, and custom benchmark protocols |
+
+### Contact Us
+
+- **Website:** [obaydata.com](https://obaydata.com)
+- **Email:** simon.su@obaydata.com
+- **Company:** New Oriental Bay Limited (香港新东湾有限公司)
+
+## Citation
+
+```bibtex
+@dataset{obaydata2026egocentric,
+  title={OBayData Egocentric Dexterous Manipulation Demo},
+  author={OBayData Team},
+  year={2026},
+  url={https://huggingface.co/datasets/obaydata/egocentric-dexterous-manipulation-demo},
+  publisher={Hugging Face}
+}
+```
+
+## License
+
+This demo dataset is released under [CC BY-NC 4.0](https://creativecommons.org/licenses/by-nc/4.0/). Commercial data collection available under custom licensing — contact us for details.
+
+