File size: 6,394 Bytes
a15f109
 
c35da9d
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
2dd48e3
c35da9d
 
2dd48e3
c35da9d
a15f109
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
2dd48e3
a15f109
 
2dd48e3
a15f109
c35da9d
 
 
 
a15f109
 
 
 
 
2dd48e3
 
 
 
 
 
 
 
 
 
 
8f0c721
 
feadf4e
8f0c721
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
0657344
8f0c721
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
0657344
8f0c721
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
da8c0f0
8f0c721
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
feadf4e
8f0c721
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
206
207
208
209
210
211
212
213
214
215
216
217
218
219
220
221
222
223
224
225
226
227
228
229
230
231
232
233
---
dataset_info:
- config_name: full
  features:
  - name: image
    dtype: image
  - name: actuated_angle
    struct:
    - name: '0'
      dtype: int32
    - name: '1'
      dtype: int32
    - name: '2'
      dtype: int32
    - name: '3'
      dtype: int32
    - name: '4'
      dtype: int32
    - name: '5'
      dtype: int32
    - name: '6'
      dtype: int32
    - name: '7'
      dtype: int32
    - name: '8'
      dtype: int32
    - name: '9'
      dtype: int32
    - name: '10'
      dtype: int32
    - name: '11'
      dtype: int32
    - name: '12'
      dtype: int32
    - name: '13'
      dtype: int32
    - name: '14'
      dtype: int32
    - name: '15'
      dtype: int32
  splits:
  - name: train
    num_bytes: 153291676475
    num_examples: 135236
  download_size: 153306274200
  dataset_size: 153291676475
- config_name: small
  features:
  - name: image
    dtype: image
  - name: actuated_angle
    struct:
    - name: '0'
      dtype: int32
    - name: '1'
      dtype: int32
    - name: '2'
      dtype: int32
    - name: '3'
      dtype: int32
    - name: '4'
      dtype: int32
    - name: '5'
      dtype: int32
    - name: '6'
      dtype: int32
    - name: '7'
      dtype: int32
    - name: '8'
      dtype: int32
    - name: '9'
      dtype: int32
    - name: '10'
      dtype: int32
    - name: '11'
      dtype: int32
    - name: '12'
      dtype: int32
    - name: '13'
      dtype: int32
    - name: '14'
      dtype: int32
    - name: '15'
      dtype: int32
  splits:
  - name: train
    num_bytes: 22669945934
    num_examples: 20000
  download_size: 22672135072
  dataset_size: 22669945934
configs:
- config_name: full
  data_files:
  - split: train
    path: full/train-*
- config_name: small
  data_files:
  - split: train
    path: small/train-*
  default: true
license: mit
task_categories:
- robotics
- reinforcement-learning
tags:
- robotics
- humanoid
- reinforcement
- learning
size_categories:
- 100K<n<1M
---

# 🤖 Open Humanoid Actuated Face Dataset

<p align="center">
  <img src="https://huggingface.co/datasets/iamirulofficial/Test2/resolve/main/imgesFace.png" alt="Sample Face Image" width="400"/>
</p>

## Dataset Summary
The **Open Humanoid Actuated Face Dataset** is designed for researchers working on  
facial‑actuation control, robotics, reinforcement learning, and human–computer interaction.

* **Origin** – collected during a reinforcement‑learning (RL) training loop whose objective was to reproduce human facial expressions.
* **Platform** – a modified **i2Head InMoov** humanoid head with a silicone skin.
* **Control****16 actuators** driving facial features and eyeballs.
* **Pairing** – each example contains the raw RGB image **and** the exact actuator angles that produced it.

---

## Dataset Structure

| Field           | Type          | Description                                                   |
|-----------------|---------------|---------------------------------------------------------------|
| `image`         | `Image`       | RGB capture of the humanoid face (resolution **1280x720**). |
| `actuated_angle`| `struct`      | 16 integer key - values (`"0"``"1"` .. so on)  |


### Actuator Index Reference

| Idx | Actuator                       | Idx | Actuator                |
|:---:|--------------------------------|:---:|-------------------------|
| 00  | Cheek – Left                   | 08  | Eyelid Upper – Right    |
| 01  | Cheek – Right                  | 09  | Eyelid Lower – Right    |
| 02  | Eyeball Sideways – Left        | 10  | Forehead – Right        |
| 03  | Eyeball Up/Down – Left         | 11  | Forehead – Left         |
| 04  | Eyelid Upper – Left            | 12  | Upper Nose              |
| 05  | Eyelid Lower – Left            | 13  | Eyebrow – Right         |
| 06  | Eyeball Up/Down – Right        | 14  | Jaw                     |
| 07  | Eyeball Sideways – Right       | 15  | Eyebrow – Left          |

---

### Actuator Mapping Images

| Full‑Face Map | Eye‑Only Map |
|:-------------:|:-----------:|
| <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%"/> |


---

## Dataset Statistics

| Split | Samples | Size |
|-------|---------|------|
| **Train (full)**  | **[135k]** | ≈ 153 GB |
| **Train (small)** | 20k | ≈ 22 GB |


---

## Usage Example

```python
from datasets import load_dataset, Image

# load the small subset
ds = load_dataset("infosys/OpenHumnoidActuatedFaceData", name="small", split="train")
ds = ds.cast_column("image", Image())   # decode image bytes ➜ PIL.Image

img = ds[0]["image"]
angles = ds[0]["actuated_angle"]        # {'0': 90, '1': 20, ...}
img.show()
print(angles)
````

> **Tip** 
> For the full corpus use `name="full"` (may require `streaming=True` once the dataset grows).

---

## Data Collection & RL Setup

A detailed description of the RL pipeline, reward design, and actuator hardware will appear in our upcoming paper (in preparation, 2025). Briefly:

1. **Vision module** extracts target expression keypoints from live human video.
2. **Policy network** predicts 16 actuator set‑points.
3. **Real‑time reward** computes expression similarity + smoothness penalties.
4. Images & angle vectors are logged every *N* steps, forming this dataset.

---

## License

Released under the **MIT License** – free for commercial and non‑commercial use.

---

## Citation

```bibtex
@misc{amirul2025openhumanoidface,
  title   = {Open Humanoid Actuated Face Dataset},
  author  = {Amirul et al.},
  year    = {2025},
  url     = {https://huggingface.co/datasets/infosys/OpenHumnoidActuatedFaceData}
}
```

---

## Contribution
1. Amirul Islam (amirul.islam@infosys.com)
2. Anant Pande (anant.pande@infosys.com)
3. Allahbaksh Asadullah (allabaksh_asadullah@infosys.com) - Mentor


## Acknowledgements

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.