---
title: "YOLO26"
subtitle: "Real-time object detection"
category: "Vision AI"
model_type:
  - "Detection"
key_novelty: "Geti-built YOLOX-S with FP16 OpenVINO IR weights, packaged for direct inference through OpenVINO Model API."
license: apache-2.0
code: "https://github.com/open-mmlab/mmdetection/tree/main/configs/yolox"
tags:
  - robotics-ai-suite
  - vision-ai
  - "category:detection"
  - "chipset:ptl"
thumbnail: assets/thumbnail.png
---

YOLOX-S object detection model, a [Geti™](https://github.com/open-edge-platform/geti)
build of [YOLOX-S](https://github.com/open-mmlab/mmdetection/tree/main/configs/yolox)
converted to OpenVINO™ IR with FP16 weights. It maps an input image to bounding
boxes for detected objects. Model weights are hosted in the source repository
[OpenVINO/yolox_s-fp16-ov](https://huggingface.co/OpenVINO/yolox_s-fp16-ov).

# How to Use

1. Install required packages:

```sh
pip install openvino-model-api[huggingface]
```

2. Run model inference:

```python
import cv2
from model_api.models import Model
from model_api.visualizer import Visualizer

model = Model.from_pretrained("OpenVINO/yolox_s-fp16-ov")
image = cv2.imread("image.jpg")
result = model(image)
vis = Visualizer().render(image, result)
cv2.imwrite("output.jpg", vis)
```

# Legal information

The original model is distributed under the
[Apache-2.0](https://github.com/open-mmlab/mmdetection/blob/main/LICENSE) license.
More details can be found in the
[original model repository](https://github.com/open-mmlab/mmdetection/tree/main/configs/yolox).