---
license: agpl-3.0
library_name: ultralytics
datasets:
- wider_face
---

# YOLOv8 for Face Detection

## Datasets

### Face

- [Anime Face CreateML](https://universe.roboflow.com/my-workspace-mph8o/anime-face-createml)
- [xml2txt](https://universe.roboflow.com/0oooooo0/xml2txt-njqx1)
- [AN](https://universe.roboflow.com/sed-b8vkf/an-lfg5i)
- [wider face](http://shuoyang1213.me/WIDERFACE/index.html)

### Hand

- [AnHDet](https://universe.roboflow.com/1-yshhi/anhdet)
- [hand-detection-fuao9](https://universe.roboflow.com/catwithawand/hand-detection-fuao9)

## Info

| Model              | Target              | mAP 50 | mAP 50-95 |
| ------------------ | ------------------- | ------ | --------- |
| face_yolov8n.pt    | 2D / realistic face | 0.660  | 0.366     |
| face_yolov8n_v2.pt | 2D / realistic face | 0.669  | 0.372     |
| face_yolov8s.pt    | 2D / realistic face | 0.713  | 0.404     |
| face_yolov8m.pt    | 2D / realistic face | 0.737  | 0.424     |
| hand_yolov8n.pt    | 2D / realistic hand | 0.767  | 0.505     |

## Usage

```python
from huggingface_hub import hf_hub_download
from ultralytics import YOLO

path = hf_hub_download("Bingsu/adetailer", "face_yolov8n.pt")
model = YOLO(path)
```

```python
import cv2
from PIL import Image

img = "https://farm5.staticflickr.com/4139/4887614566_6b57ec4422_z.jpg"
output = model(img)
pred = output[0].plot()
pred = cv2.cvtColor(pred, cv2.COLOR_BGR2RGB)
pred = Image.fromarray(pred)
pred
```

![image](https://i.imgur.com/9ny1wmD.png)