Qualcomm® AI HubAI Hub

SINet

Lightweight portrait segmentation for background removal.

SINet is a machine learning model that is designed to segment people from close‑up portrait images in real time.

Model RepositoryHugging FaceResearch Paper

Technical Details

Model checkpoint:SINet.pth
Input resolution:224x224
Number of parameters:91.9K
Model size:430 KB
Number of output classes:2 (foreground / background)

Applicable Scenarios

  • Background replacement
  • Face removal

Licenses

Source Model:OTHER
Deployable Model:AI Model Hub License

Supported Automotive Devices

  • SA7255P ADP
  • SA8255 (Proxy)
  • SA8295P ADP
  • SA8650 (Proxy)
  • SA8775P ADP

Supported Automotive Chipsets

  • Qualcomm® SA7255P
  • Qualcomm® SA8255P (Proxy)
  • Qualcomm® SA8295P
  • Qualcomm® SA8650P (Proxy)
  • Qualcomm® SA8775P

Related Models

See all models
View details for the FCN-ResNet50 model.

FCN-ResNet50

Fully-convolutional network model for image segmentation.

View details for the Unet-Segmentation model.

Unet-Segmentation

Real-time segmentation optimized for mobile and edge.

View details for the MediaPipe-Selfie-Segmentation model.

MediaPipe-Selfie-Segmentation

Segments the person from background in a selfie image and realtime background segmentation in video conferencing.

Looking for more? See models created by industry leaders.

Discover Model Makers