performance evaluation of yolo models on different edge platforms

[Ritesh1]

How to do benchmarking of YOLO model on stm32 platforms.

Ritesh

[Julian E.]

Hello @Ritesh1 ,

You can benchmark YOLO models with the ST Edge AI Developer Cloud.

You first need to save your model as Keras, ONNX or TFLite (.h5, .hdf5, .keras, .onnx or tflite) and then follow this tutorial:

https://wiki.st.com/stm32mcu/wiki/AI:Getting_started_with_STM32Cube.AI_Developer_Cloud

I believe that you can find a .h5 for a yolo model in object detection in our ST Model Zoo: https://github.com/STMicroelectronics/stm32ai-modelzoo 

There, you can find it the pretrained_model folders, download it and use the ST Developer cloud to do the benchmarking.

Best Regards, 

Julian