version: '1.0'
module:
  uid: c19c71aa-7558-4f73-abf7-b5d929bc0dfa
  name: SeetaEmoNet
  version: '1.0'
  description: 'Multi-task facial affect estimation: action units, categorical expressions, and continuous valence-arousal dimensions.'
  keywords:
    - Emotion
    - Expression
    - Action Units
    - Affect
  requirements:
    - seetapsych-emo>=0.0.3
    - timm>=1.0.27
    - torch>=2.5.1
    - torchvision>=0.20.1
    - safetensors>=0.7.0
    - opencv-python>=4.13.0.90
packages:
  - uid: 2951cff6-46c0-4506-8f6b-ba016a00a35b
    name: Emotions-SeetaEmoNet
    description: Unified multi-task MAE-ViT model predicting 16 AUs, 7 expressions, and valence-arousal simultaneously from 5-point aligned face crops
    version: '1.0'
    usage_models: []
    inputs: []
    provides:
      - face/action_units
      - face/expression
      - face/dimensional_affect
    requires:
      - face/landmarks
    entry:
      method: seetapsych_emo.emonet.package.load
    models:
      - uid: 80b96924-b762-4fb7-ad60-813a91c6b7d0
        name: seeta-emo-ufanet-2604.safetensors
        version: '1.0'
        recommended: true
        metadata:
          model_name: mae_vit_base_patch16
        download:
          index: seeta-emo-ufanet-2604.safetensors
          sha256: 15968f366390a3c8ac1d1ad8a07214bf3817039cfdff990a06081174e2912cc9
          url: https://www.modelscope.cn/models/seetapsych/seetapsych-models/resolve/master/seetapsych/emo/seeta-emo-ufanet-2604.safetensors