Optimized solutions for mobile device deployment
The following optimization measures can be taken for mobile device performance limitations:
- Lightweight model selection:Preferred smaller scale model versions like SpatialLM1.1-Qwen-0.5B
- Cloud Collaboration Program:Consider point cloud preprocessing done on the device side and the inference process on the cloud side
- Data simplification:Reducing the density of the input point cloud to find a balance between accuracy and performance
- Hardware acceleration:Take advantage of AI acceleration on mobile GPUs or optimize models with tools like TensorRT
For scenarios with high real-time requirements, the model can be generated by pre-scanning the environment and only locally updated at runtime.
This answer comes from the articleSpatialLM: Sweep the room, AI automatically draws 3D models for youThe
May not be reproduced without permission:AI productivity tools " How to overcome performance bottlenecks in deploying SpatialLM on mobile devices?
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