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Datasets:
infosys
/
OpenHumnoidActuatedFaceData

Tasks:
Robotics
Reinforcement Learning
Modalities:
Image
Formats:
parquet
Size:
100K - 1M
Tags:
robotics
humanoid
reinforcement
learning
Libraries:
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License:
Dataset card Data Studio Files Community
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Convert dataset to Parquet

#1
by amirulofficialinfy - opened
base: refs/heads/main
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Files changed (47) hide show
  1. README.md +4 -135
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README.md CHANGED
@@ -40,10 +40,10 @@ dataset_info:
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  dtype: int32
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  splits:
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  - name: train
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- num_bytes: 153291676475
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  num_examples: 135236
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  download_size: 153306274200
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- dataset_size: 153291676475
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  - config_name: small
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  features:
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  - name: image
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  dtype: int32
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  splits:
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  - name: train
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- num_bytes: 22669945934
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  num_examples: 20000
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  download_size: 22672135072
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- dataset_size: 22669945934
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  configs:
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  - config_name: full
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  data_files:
@@ -98,135 +98,4 @@ configs:
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  - split: train
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  path: small/train-*
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  default: true
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- license: mit
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- task_categories:
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- - robotics
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- - reinforcement-learning
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- tags:
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- - robotics
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- - humanoid
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- - reinforcement
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- - learning
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- size_categories:
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- - 100K<n<1M
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  ---
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-
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- # 🤖 Open Humanoid Actuated Face Dataset
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-
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- <p align="center">
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- <img src="https://huggingface.co/datasets/iamirulofficial/Test2/resolve/main/imgesFace.png" alt="Sample Face Image" width="400"/>
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- </p>
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-
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- ## Dataset Summary
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- The **Open Humanoid Actuated Face Dataset** is designed for researchers working on
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- facial‑actuation control, robotics, reinforcement learning, and human–computer interaction.
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-
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- * **Origin** – collected during a reinforcement‑learning (RL) training loop whose objective was to reproduce human facial expressions.
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- * **Platform** – a modified **i2Head InMoov** humanoid head with a silicone skin.
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- * **Control** – **16 actuators** driving facial features and eyeballs.
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- * **Pairing** – each example contains the raw RGB image **and** the exact actuator angles that produced it.
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-
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- ---
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-
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- ## Dataset Structure
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-
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- | Field | Type | Description |
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- |-----------------|---------------|---------------------------------------------------------------|
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- | `image` | `Image` | RGB capture of the humanoid face (resolution **1280x720**). |
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- | `actuated_angle`| `struct` | 16 integer key - values (`"0"`, `"1"` .. so on) |
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-
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-
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- ### Actuator Index Reference
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-
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- | Idx | Actuator | Idx | Actuator |
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- |:---:|--------------------------------|:---:|-------------------------|
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- | 00  | Cheek – Left | 08  | Eyelid Upper – Right |
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- | 01  | Cheek – Right | 09  | Eyelid Lower – Right |
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- | 02  | Eyeball Sideways – Left | 10  | Forehead – Right |
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- | 03  | Eyeball Up/Down – Left | 11  | Forehead – Left |
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- | 04  | Eyelid Upper – Left | 12  | Upper Nose |
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- | 05  | Eyelid Lower – Left | 13  | Eyebrow – Right |
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- | 06  | Eyeball Up/Down – Right | 14  | Jaw |
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- | 07  | Eyeball Sideways – Right | 15  | Eyebrow – Left |
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-
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- ---
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-
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- ### Actuator Mapping Images
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-
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- | Full‑Face Map | Eye‑Only Map |
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- |:-------------:|:-----------:|
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- | <br><img src="https://huggingface.co/datasets/iamirulofficial/Test2/resolve/main/Screenshot%202025-05-02%20at%204.04.28%E2%80%AFPM.png" width="50%"/> | <br><img src="https://huggingface.co/datasets/iamirulofficial/Test2/resolve/main/Screenshot%202025-05-02%20at%204.03.56%E2%80%AFPM.png" width="50%"/> |
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-
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-
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- ---
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-
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- ## Dataset Statistics
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-
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- | Split | Samples | Size |
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- |-------|---------|------|
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- | **Train (full)** | **[135k]** | ≈ 153 GB |
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- | **Train (small)** | 20k | ≈ 22 GB |
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-
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-
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- ---
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-
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- ## Usage Example
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-
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- ```python
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- from datasets import load_dataset, Image
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-
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- # load the small subset
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- ds = load_dataset("infosys/OpenHumnoidActuatedFaceData", name="small", split="train")
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- ds = ds.cast_column("image", Image()) # decode image bytes ➜ PIL.Image
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-
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- img = ds[0]["image"]
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- angles = ds[0]["actuated_angle"] # {'0': 90, '1': 20, ...}
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- img.show()
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- print(angles)
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- ````
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-
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- > **Tip** 
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- > For the full corpus use `name="full"` (may require `streaming=True` once the dataset grows).
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-
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- ---
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-
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- ## Data Collection & RL Setup
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-
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- A detailed description of the RL pipeline, reward design, and actuator hardware will appear in our upcoming paper (in preparation, 2025). Briefly:
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-
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- 1. **Vision module** extracts target expression keypoints from live human video.
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- 2. **Policy network** predicts 16 actuator set‑points.
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- 3. **Real‑time reward** computes expression similarity + smoothness penalties.
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- 4. Images & angle vectors are logged every *N* steps, forming this dataset.
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-
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- ---
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-
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- ## License
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-
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- Released under the **MIT License** – free for commercial and non‑commercial use.
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-
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- ---
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-
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- ## Citation
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-
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- ```bibtex
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- @misc{amirul2025openhumanoidface,
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- title = {Open Humanoid Actuated Face Dataset},
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- author = {Amirul et al.},
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- year = {2025},
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- url = {https://huggingface.co/datasets/infosys/OpenHumnoidActuatedFaceData}
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- }
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- ```
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-
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- ---
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-
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- ## Contribution
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- 1. Amirul Islam (amirul.islam@infosys.com)
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- 2. Anant Pande (anant.pande@infosys.com)
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- 3. Allahbaksh Asadullah (allabaksh_asadullah@infosys.com) - Mentor
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-
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-
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- ## Acknowledgements
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-
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- Big thanks to the Infosys and Mohammed Rafee Tarafdar (CTO, Infosys) for providing us resources to work on this research project and thanks to all the community and everyone who helped us making this possible.
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-
 
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  dtype: int32
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  splits:
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  data_files:
 
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  - split: train
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  path: small/train-*
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  default: true
 
 
 
 
 
 
 
 
 
 
 
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  ---
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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