mirror of
https://github.com/Bing-su/adetailer.git
synced 2026-01-26 19:29:54 +00:00
103 lines
6.0 KiB
Markdown
103 lines
6.0 KiB
Markdown
# !After Detailer
|
||
|
||
!After Detailer is a extension for stable diffusion webui, similar to Detection Detailer, except it uses ultralytics instead of the mmdet.
|
||
|
||
## Install
|
||
|
||
(from Mikubill/sd-webui-controlnet)
|
||
|
||
1. Open "Extensions" tab.
|
||
2. Open "Install from URL" tab in the tab.
|
||
3. Enter `https://github.com/Bing-su/adetailer.git` to "URL for extension's git repository".
|
||
4. Press "Install" button.
|
||
5. Wait 5 seconds, and you will see the message "Installed into stable-diffusion-webui\extensions\adetailer. Use Installed tab to restart".
|
||
6. Go to "Installed" tab, click "Check for updates", and then click "Apply and restart UI". (The next time you can also use this method to update extensions.)
|
||
7. Completely restart A1111 webui including your terminal. (If you do not know what is a "terminal", you can reboot your computer: turn your computer off and turn it on again.)
|
||
|
||
You can now install it directly from the Extensions tab.
|
||
|
||
|
||
|
||
You **DON'T** need to download any model from huggingface.
|
||
|
||
## Options
|
||
|
||
| Model, Prompts | | |
|
||
| --------------------------------- | ------------------------------------- | ------------------------------------------------- |
|
||
| ADetailer model | Determine what to detect. | `None` = disable |
|
||
| ADetailer prompt, negative prompt | Prompts and negative prompts to apply | If left blank, it will use the same as the input. |
|
||
|
||
| Detection | | |
|
||
| ------------------------------------ | -------------------------------------------------------------------------------------------- | --- |
|
||
| Detection model confidence threshold | Only objects with a detection model confidence above this threshold are used for inpainting. | |
|
||
| Mask min/max ratio | Only use masks whose area is between those ratios for the area of the entire image. | |
|
||
|
||
If you want to exclude objects in the background, try setting the min ratio to around `0.01`.
|
||
|
||
| Mask Preprocessing | | |
|
||
| ------------------------------- | ----------------------------------------------------------------------------------------------------------------------------------- | --------------------------------------------------------------------------------------- |
|
||
| Mask x, y offset | Moves the mask horizontally and vertically by | |
|
||
| Mask erosion (-) / dilation (+) | Enlarge or reduce the detected mask. | [opencv example](https://docs.opencv.org/4.7.0/db/df6/tutorial_erosion_dilatation.html) |
|
||
| Mask merge mode | `None`: Inpaint each mask<br/>`Merge`: Merge all masks and inpaint<br/>`Merge and Invert`: Merge all masks and Invert, then inpaint | |
|
||
|
||
#### Inpainting
|
||
|
||
|
||
|
||
Each option corresponds to a corresponding option on the inpaint tab.
|
||
|
||
## 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.
|
||
|
||
## Model
|
||
|
||
| 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 face | - | - |
|
||
| mediapipe_face_short | realistic face | - | - |
|
||
| hand_yolov8n.pt | 2D / realistic hand | 0.767 | 0.505 |
|
||
| person_yolov8n-seg.pt | 2D / realistic person | 0.782 (bbox)<br/>0.761 (mask) | 0.555 (bbox)<br/>0.460 (mask) |
|
||
| person_yolov8s-seg.pt | 2D / realistic person | 0.824 (bbox)<br/>0.809 (mask) | 0.605 (bbox)<br/>0.508 (mask) |
|
||
|
||
The yolo models can be found on huggingface [Bingsu/adetailer](https://huggingface.co/Bingsu/adetailer).
|
||
|
||
### 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 or segment model and use all label.
|
||
|
||
### Dataset
|
||
|
||
Datasets used for training the yolo models are:
|
||
|
||
#### 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)
|
||
|
||
#### Person
|
||
|
||
- [coco2017](https://cocodataset.org/#home) (only person)
|
||
- [AniSeg](https://github.com/jerryli27/AniSeg)
|
||
- [skytnt/anime-segmentation](https://huggingface.co/datasets/skytnt/anime-segmentation)
|
||
|
||
## Example
|
||
|
||
|
||
|
||
|
||
[](https://ko-fi.com/F1F1L7V2N)
|