docs: update readme

This commit is contained in:
Bingsu
2023-07-27 17:08:36 +09:00
parent 20c263c4f8
commit 02719eec36

View File

@@ -44,15 +44,26 @@ Applied in this order: x, y offset → erosion/dilation → merge/invert.
#### Inpainting
![image](https://i.imgur.com/wyWlT1n.png)
Each option corresponds to a corresponding option on the inpaint tab.
Each option corresponds to a corresponding option on the inpaint tab. Therefore, please refer to the inpaint tab for usage details on how to use each option.
## ControlNet Inpainting
You can use the ControlNet extension if you have ControlNet installed and ControlNet models.
Support `inpaint, scribble, lineart, openpose, tile` controlnet models. Once you choose a model, the preprocessor is set automatically.
Support `inpaint, scribble, lineart, openpose, tile` controlnet models. Once you choose a model, the preprocessor is set automatically. It works separately from the model set by the Controlnet extension.
## Advanced Options
API request example: [wiki/API](https://github.com/Bing-su/adetailer/wiki/API)
`ui-config.json` entries: [wiki/ui-config.json](https://github.com/Bing-su/adetailer/wiki/ui-config.json)
`[SEP], [SKIP]` tokens: [wiki/Advanced](https://github.com/Bing-su/adetailer/wiki/Advanced)
## Media
- 🎥 [どこよりも詳しいAfter Detailer (adetailer)の使い方① 【Stable Diffusion】](https://youtu.be/sF3POwPUWCE)
- 🎥 [どこよりも詳しいAfter Detailer (adetailer)の使い方② 【Stable Diffusion】](https://youtu.be/urNISRdbIEg)
## Model
@@ -69,34 +80,12 @@ Support `inpaint, scribble, lineart, openpose, tile` controlnet models. Once you
The yolo models can be found on huggingface [Bingsu/adetailer](https://huggingface.co/Bingsu/adetailer).
### User Model
### Additional Model
Put your [ultralytics](https://github.com/ultralytics/ultralytics) model in `webui/models/adetailer`. The model name should end with `.pt` or `.pth`.
Put your [ultralytics](https://github.com/ultralytics/ultralytics) yolo 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
![image](https://i.imgur.com/38RSxSO.png)