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-timeA “real-time” model can typically achieve 5-60 predictions per second. This translates to latency ranging up to 200 ms per prediction.
Supported Compute Chipsets
- Snapdragon® X Elite