onnx to hef model

user413 · January 22, 2026, 9:48am

want to deploy a custom yolov8 model to hailo. I have trained a model using ultrlytics and after that I converted this model to onnx format. After that to convert my model to hef format I followed the steps.
first I made parsing using:
hailomz parse yolov8n --ckpt /home/usr/hailo-models/hailo-n178.onnx --hw-arch hailo8 --start-node-names 'images' --end-node-names
how can i decide which are the --end-node-names, and how the nms configuration follow that --end-node-names

Michael · January 22, 2026, 9:53am

Hi,

We recently updated our retraining guide.

github.com/hailo-ai/hailo-apps

doc/developer_guide/retraining_example.md

main

# YOLOv8 Retraining Example

This guide demonstrates how to retrain a YOLOv8 model for barcode detection using the Kaggle barcode-detector dataset. After training, we'll convert the model to HEF format and deploy it on the Raspberry Pi 5 AI Kit (or any x86 platform with a Hailo accelerator).

#### Required compute resources:
- **Training phase**: Any cloud service with GPU resources (including Python notebook-based services like Google Colab)
- **Hailo compilation phase**: Conversion to HEF format is compute-intensive but manageable on standard PCs (e.g., overnight task)

For complete reference implementations, see the Jupyter notebooks (please note some of the stages, including installations, might take time): 
- [`retraining.ipynb`](retraining.ipynb)
- [`compilation.ipynb`](compilation.ipynb)

## Training Setup

### Set up environment

First, create a Python virtual environment:

```bash
python -m venv env

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Thanks,