How to export and optimize YOLO-NAS object detection model for real-time with ONNX and TensorRT
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In this video 📝 we are going to cover how to export and optimize YOLO-NAS models to ONNX and TensorRT for real-time performance. We will cover the whole pipeline step by step so you can follow along. The speedups we can get from optimizing our models are crazy without really loosing accuracy. It's a ton of information to ingest, but very important in the world of deep learning and computer vision. This is how good real-world applications and projects are made.
Code: https://github.com/niconielsen32/YOLO...
YOLO-NAS GitHub: https://github.com/Deci-AI/super-grad...
Supergradient documentation: https://docs.deci.ai/super-gradients/...
Deci's models: https://deci.ai/foundation-models/
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Timestamps:
0:00 Intro
0:44 YOLO-NAS Documentation
3:59 Install Cuda & TensortRT
4:55 Optimize to ONNX
11:36 Results ONNX
14:33 Convert to TensorRT
21:45 TensorRT Results
22:51 Outro
tags:
#YOLO-NAS #ONNX #TensorRT #supergradients
