version: '1.0'
module:
  uid: 46b16f61-3170-419c-906b-e27def024b5a
  name: SeetaDenseLandmarks
  version: '1.0'
  description: 'Predict 280-point dense facial landmarks from face bounding box or sparse facial landmarks with optional second-pass refinement.'
  keywords:
    - Face
    - Landmarks
  requirements:
    - seetapsych-face-ex
    - numpy>=2.2.6
    - onnx>=1.20.1
    - onnxruntime>=1.24; sys_platform == 'darwin' and python_version > '3.10'
    - onnxruntime<1.24; sys_platform == 'darwin' and python_version <= '3.10'
    - onnxruntime-gpu>=1.24; sys_platform != 'darwin' and python_version > '3.10'
    - onnxruntime-gpu<1.24; sys_platform != 'darwin' and python_version <= '3.10'
    - opencv-python>=4.11.0.86
    - scikit-image>=0.25.2
packages:
  - uid: 35bb9050-6ccb-4c8e-a882-224873322ee7
    name: DenseLandmarks[280]-Seeta
    description: 280-point dense facial landmark predictor supporting bbox→initial→refine two-pass or sparse-landmark input paths
    version: '1.0'
    usage_models: []
    inputs: []
    provides:
      - face/dense_landmarks
    requires:
      - face/detection
    entry:
      method: seetapsych_face_ex.dense_landmarks.package.load
    parameters:
      - name: refine
        type: boolean
        value: true
        text: Enable Refinement Pass
        description: Enable second-pass landmark refinement via 5-point similarity alignment. Disable for higher throughput with minor accuracy trade-off.
    models:
      - uid: 180e2494-911a-4ee6-9fa3-1abc7be600f2
        name: seeta-face-ex-dense-landmarks-280.onnx
        version: '1.0'
        recommended: true
        download:
          index: seeta-face-ex-dense-landmarks-280.onnx
          sha256: 5178b427b8aa560d7e134d701781a291768d17423d4b5b37d6b1e453ab6ac1fd
          url: https://www.modelscope.cn/models/seetapsych/seetapsych-models/resolve/master/seetapsych/face-ex/seeta-face-ex-dense-landmarks-280.onnx