Neural Networks
This section will describe how you can train, export, and integrate various AI models on our devices. We will show how to measure the performance of a model and possible ways to optimize the performance. Furthermore, we will talk about how to post-process outputs of models.Model Zoo
Visit our DepthAI Model Zoo to explore a range of pre-trained AI models, optimized for performance on DepthAI devices and suited for various applications.
Conversion
For adapting AI models from frameworks like PyTorch to Luxonis devices, check our Conversion page for easy-to-follow instructions.
Integrations
Explore our Integrations page for guidance on exporting Yolo models and using Roboflow models with our hardware.
Post-processing
Visit the Post-processing page for key steps to refine AI model outputs for use on Luxonis devices.
Performance Optimization
Enhance your AI models' performance on Luxonis devices with helpful tips from our Performance Optimization page.
Training
Learn about Luxonis's training and inference capabilities through our collection of Jupyter notebook tutorials.