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.
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
- 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
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