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U2Net-Segmentation

Salient object segmentation for high‑quality foreground extraction.

U2‑Net is a machine learning model for salient object detection and foreground extraction. It uses a two‑level nested U‑structure (RSU blocks) to capture both local and global context at multiple scales, producing high‑quality binary foreground masks. The model is trained on the DUTS dataset and is well‑suited for background removal, portrait segmentation, and object extraction on mobile and edge devices.

Not supported

This model is currently not supported on any Automotive chipset.

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Technical Details

Input resolution:320x320
Model checkpoint:u2net.pth
Number of output classes:1 (salient foreground mask)
Number of parameters:44.0M

Applicable Scenarios

  • Background Removal
  • Portrait Segmentation
  • E-Commerce Product Imaging

License

Tags

  • real-time

Supported Automotive Devices

  • SA7255P ADP
  • SA8255P ADP
  • SA8295P ADP
  • SA8650P ADP
  • SA8775P ADP

Supported Automotive Chipsets

  • Qualcomm® SA7255P
  • Qualcomm® SA8255P
  • Qualcomm® SA8295P
  • Qualcomm® SA8650P
  • Qualcomm® SA8775P

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