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docs: user model, controlnet inpainting

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## Model
| Model | Target | mAP 50-95 |
| -------------------- | -------------- | --------- |
| face_yolov8n.pt | 2D / realistic | 0.366 |
| face_yolov8s.pt | 2D / realistic | 0.404 |
| mediapipe_face_full | realistic | - |
| mediapipe_face_short | realistic | - |
| Model | Target | mAP 50 | mAP 50-95 |
| -------------------- | ------------------- | ------ | --------- |
| face_yolov8n.pt | 2D / realistic face | 0.660 | 0.366 |
| face_yolov8s.pt | 2D / realistic face | 0.713 | 0.404 |
| mediapipe_face_full | realistic | - | - |
| mediapipe_face_short | realistic | - | - |
The yolo models can be found on huggingface [Bingsu/adetailer](https://huggingface.co/Bingsu/adetailer).
### Dataset
Datasets used for training the yolo models are:
Datasets used for training the yolo face detection models are:
- [roboflow AN](https://universe.roboflow.com/sed-b8vkf/an-lfg5i)
- [roboflow Anime Face CreateML](https://universe.roboflow.com/my-workspace-mph8o/anime-face-createml)
- [roboflow xml2txt](https://universe.roboflow.com/0oooooo0/xml2txt-njqx1)
- [wider face](http://shuoyang1213.me/WIDERFACE/index.html)
### User Model
Put your [ultralytics](https://github.com/ultralytics/ultralytics) model in `webui/models/adetailer`. The model name should end with `.pt` or `.pth`.
It must be a bbox detection model and use only label 0.
## ControlNet Inpainting
You can use the ControlNet inpaint extension if you have ControlNet installed and a ControlNet inpaint model.
On the ControlNet tab, select a ControlNet inpaint model and set the model weights.
## Example
![image](https://i.imgur.com/i74ukgi.png)