---
title: "YOLOx ONNX models use in Frigate"
url: https://michalasobczak.pl/posts/yolox-onnx-models-use-in-frigate.html
author: "Michał Sobczak"
description: "YOLOX is an anchor-free version of YOLO, with a simpler design but better performance! It aims to bridge the gap between research and industrial communities. For more details, please refer to our report on Arxiv. https://yolox.readthedocs.io/en/latest/demo/onnx_readme.html https://github.com/Megvii-BaseDetection/YOLOX/tree/main/demo/ONNXRuntime To configure this in Frigate:"
published: 2025-09-04T05:59:53.000Z
updated: 2025-09-04T06:50:59.000Z
language: en
categories: ["AI/ML"]
tags: ["Frigate", "ML", "ONNX", "YOLOx"]
license: CC BY-NC-ND 4.0 (https://creativecommons.org/licenses/by-nc-nd/4.0/)
---
# YOLOx ONNX models use in Frigate

> YOLOX is an anchor-free version of YOLO, with a simpler design but better performance! It aims to bridge the gap between research and industrial communities. For more details, please refer to our [report on Arxiv](https://arxiv.org/abs/2107.08430).

[https://yolox.readthedocs.io/en/latest/demo/onnx\_readme.html](https://yolox.readthedocs.io/en/latest/demo/onnx_readme.html)

[https://github.com/Megvii-BaseDetection/YOLOX/tree/main/demo/ONNXRuntime](https://github.com/Megvii-BaseDetection/YOLOX/tree/main/demo/ONNXRuntime)

To configure this in Frigate:

```yaml
detectors:
  onnx:
    type: onnx
model:
  model_type: yolox
  width: 640
  height: 640
  input_tensor: nchw
  input_dtype: float_denorm
  path: /config/yolox_m.onnx
  labelmap_path: /labelmap/coco-80.txt
```