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.
Not supported
This model is currently not supported on any Automotive chipset.
To see performance metrics for this model on other chipsets, click the button below.
View for other chipsetsTechnical Details
Model checkpoint:DDRNet23s_imagenet.pth
Inference latency:RealTime
Input resolution:2048x1024
Number of output classes:19
Number of parameters:6.13M
Model size (float):21.7 MB
Model size (w8a8):6.11 MB
Applicable Scenarios
- Self-driving cars
License
Model:MIT
Tags
- real-time
Supported Automotive Devices
- SA7255P ADP
- SA8255P ADP
- SA8295P ADP
- SA8650P ADP
- SA8775P ADP
Supported Automotive Chipsets
- Qualcomm® SA7255P
- Qualcomm® SA8295P
- Qualcomm® SA8775P
Related Models
See all models
Looking for more? See models created by industry leaders.
Discover Model Makers