Metadata-Version: 2.5
Name: seetapsych-emo
Version: 0.0.3.post1
Summary: Facial affect/emotion recognition modules for SeetaPsych
Project-URL: Homepage, https://github.com/seetapsych/seetapsych-emo
Project-URL: Repository, https://github.com/seetapsych/seetapsych-emo
Project-URL: Issues, https://github.com/seetapsych/seetapsych-emo/issues
License: BSD 3-Clause License
        
        Copyright (c) 2026, Visual Information Processing and Learning (VIPL) group,
        Institute of Computing Technology, Chinese Academy of Sciences, Beijing, China;
        Southeast University, China;
        Beijing Seetatech Co., Ltd.
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License-File: LICENSE
Requires-Python: >=3.10
Requires-Dist: seetapsych-lib>=0.0.3
Provides-Extra: all
Requires-Dist: opencv-python>=4.13.0.90; extra == 'all'
Requires-Dist: safetensors>=0.7.0; extra == 'all'
Requires-Dist: timm>=1.0.27; extra == 'all'
Requires-Dist: torch>=2.9.1; extra == 'all'
Requires-Dist: torchvision>=0.24.1; extra == 'all'
Provides-Extra: dev
Requires-Dist: bandit>=1.7; extra == 'dev'
Requires-Dist: build>=1.4.4; extra == 'dev'
Requires-Dist: mypy>=1.11; extra == 'dev'
Requires-Dist: opencv-python>=4.13.0.90; extra == 'dev'
Requires-Dist: pytest>=8.0; extra == 'dev'
Requires-Dist: ruff>=0.6; extra == 'dev'
Requires-Dist: safetensors>=0.7.0; extra == 'dev'
Requires-Dist: timm>=1.0.27; extra == 'dev'
Requires-Dist: torch>=2.9.1; extra == 'dev'
Requires-Dist: torchvision>=0.24.1; extra == 'dev'
Requires-Dist: twine>=6.2.0; extra == 'dev'
Description-Content-Type: text/markdown

# SeetaPsych Emo

> Facial affect/emotion recognition modules for SeetaPsych

## Usage

This project is already included in the seetapsych-lib default configuration. Download and use it via `seetapsych-manager download`.

For usage, refer to [SeetaPsych](https://github.com/seetapsych/seetapsych-lib).

You can additionally add this algorithm module using the following methods.

### WebUI

Run `seetapsych-webui` with the `--dirs` argument to use it.

```
seetapsych-webui --files seetapsych_emo/modules/emonet.yml
```

### Programmatic Usage

Add the following code in your program to use this algorithm module.

```python
from seetapsych_lib.runtime.factory import Factory
from seetapsych_lib.runtime.pipeline import Pipeline

factory = Factory()
factory.load_file_modules("seetapsych_emo/modules/emonet.yml")

pipeline = Pipeline(factory, ...)

pipeline.add_attributes("face/expression", "face/action_units", "face/dimensional_affect")
```

### Module Catalog

| YAML Path | Packages |
|---|---|
| [emonet.yml](seetapsych_emo/modules/emonet.yml) | Emotions-SeetaEmoNet |

### SeetaEmoNet

Multi-task facial affect estimation: action units, categorical expressions, and continuous valence-arousal dimensions.

Module config: [emonet.yml](seetapsych_emo/modules/emonet.yml)

| Package Name | Provides Attributes | Requires Attributes |
|---|---|---|
| Emotions-SeetaEmoNet | face/action_units, face/expression, face/dimensional_affect | face/landmarks |

**Description**: Unified multi-task MAE-ViT model predicting 16 AUs, 7 expressions, and valence-arousal simultaneously from 5-point aligned face crops

**Parameters**: *(none)*

**Models**

| Name | Recommended |
|---|---|
| seeta-emo-ufanet-2604.safetensors | ✓ |

**Output Attributes**
- `face/action_units` — [spec](https://github.com/seetapsych/seetapsych-attributes#faceaction_units).
- `face/expression` — [spec](https://github.com/seetapsych/seetapsych-attributes#faceexpression).
- `face/dimensional_affect` — [spec](https://github.com/seetapsych/seetapsych-attributes#facedimensional_affect).

**Output details**:
- `face/expression`: 7 basic expression classes with confidence scores — neutral, anger, disgust, fear, happy, sad, surprise.
- `face/action_units`: 16 Facial Action Units with intensities — AU1, AU2, AU4, AU5, AU6, AU7, AU9, AU10, AU12, AU15, AU17, AU20, AU23, AU24, AU25, AU26.
- `face/dimensional_affect`: Continuous valence and arousal values in a dict `{valence: float, arousal: float}`.
