Hi everyone,
I realize this might be a bit of a basic question, and I’m sorry in advance if it comes off as annoying or if it’s already been answered somewhere.
I’m completely new to AI accelerators and the whole topic of running neural networks. I recently started working with the Hailo platform but I’m a bit stuck on how to actually run one of the models from the Hailo model zoo using Python.
I was able to run the tests from the hailo-rpi5-examples but I want to use the damoyolo and the mspn_regnetx_800mf models. I found the precompiled .hef files but I found nothing about actually running the model and post processing the results.
tl;dr:
My Questions:
How do I load and run a precompiled .hef model (for example damoyolo or mspn_regnetx_800mf) from the model zoo in a Python script?
What’s the typical workflow to feed data into the model and get results back?
And most importantly: how do I interpret the model outputs (e.g., do post-processing for object detection or classification)?
I’ve been digging through the docs and examples, but as a beginner it’s still a bit overwhelming. If someone could point me to a simple example or explain the rough steps, that would help me out a lot.
Thanks in advance,
BatiFPV