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DDRNet23-Slim

Segment images or video by class in real‑time on device.

DDRNet23Slim is a machine learning model that segments an image into semantic classes, specifically designed for road‑based scenes. It is designed for the application of self‑driving cars.

Model RepositoryHugging FaceResearch Paper

Technical Details

Model checkpoint:DDRNet23s_imagenet.pth
Inference latency:RealTime
Input resolution:2048x1024
Number of parameters:5.69M
Model size:21.7 MB
Number of output classes:19

Applicable Scenarios

  • Self-driving cars

Licenses

Source Model:MIT
Deployable Model:AI Model Hub License

Tags

  • real-time

Supported Automotive Devices

  • SA8255 (Proxy)
  • SA8295P ADP
  • SA8650 (Proxy)
  • SA8775 (Proxy)

Supported Automotive Chipsets

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

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