---
tags:
- ultralyticsplus
- ultralytics
- yolov8
- yolo
- vision
- object-detection
- pytorch
library_name: ultralytics
library_version: 8.0.4
inference: false

model-index:
- name: ultralyticsplus/yolov8s
  results:
  - task:
      type: object-detection

    metrics:
      - type: precision  # since mAP is not available on hf.co/metrics
        value: 0.449  # min: 0.0 - max: 1.0
        name: mAP
---

### Supported Labels

```
['Helmet', 'No Helmet']
```


### How to use

- Install [ultralyticsplus](https://github.com/fcakyon/ultralyticsplus):

```bash
pip install -U ultralyticsplus==0.0.14
```

- Load model and perform prediction:

```python
from ultralyticsplus import YOLO, render_result

# load model
model = YOLO('ultralyticsplus/yolov8s')

# set model parameters
model.overrides['conf'] = 0.25  # NMS confidence threshold
model.overrides['iou'] = 0.45  # NMS IoU threshold
model.overrides['agnostic_nms'] = False  # NMS class-agnostic
model.overrides['max_det'] = 1000  # maximum number of detections per image

# set image
image = 'https://github.com/ultralytics/yolov5/raw/master/data/images/zidane.jpg'

# perform inference
results = model.predict(image)

# observe results
print(results[0].boxes)
render = render_result(model=model, image=image, result=results[0])
render.show()
```