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.

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.

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	Emotions-SeetaEmoNet

SeetaEmoNet

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

Module config: 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.
face/expression — spec.
face/dimensional_affect — spec.

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}.

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Source Distribution

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Provenance

The following attestation bundles were made for seetapsych_emo-0.0.3.post1.tar.gz:

Publisher: publish.yml on seetapsych/seetapsych-emo

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- Statement type: https://in-toto.io/Statement/v1
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- Sigstore integration time: Sep 3, 2026
Source repository:
- Permalink: seetapsych/seetapsych-emo@6fdb1b6bbe7999209e8702e19815b859a7cc3033
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