2 docs tagged with "Ultralytics"

This tutorial will guide you to benchmark pre-trained YOLO models on Synaptics Astra™ Machina™ boards to evaluate their performance in terms of inference speed. Our SyNAP toolkit supports up to the latest YOLOv11 version, allowing you to easily benchmark and deploy models with minimal effort. You can run pre-trained models from Ultralytics or even your own fine-tuned models. Since Ultralytics has been at the forefront of creating state-of-the-art YOLO models, let’s use their YOLOv8 Nano as an example to showcase how you can benchmark its performance on SL1680's NPU.

In this example, you can dive deep on how model conversion and optimization works using SyNAP Toolkit on a Synaptics Astra™ Machina™ board. You can export the YOLOv8 body pose model from Ultralytics, use SyNAP to perform an optimized model compilation targeting the NPU in Synaptics Astra SL1680, run inference on the board, and display the results.