bing-su / asdff Goto Github PK

I've noticed that there numpy used in places. Could we have a torch check to see if device is cuda, and to use torch instead of numpy when a gpu is available? This will greatly speed things up instead of using the cpu in these instances.

PyTorch supports both CPU and GPU acceleration, so an if statement probably wouldn't even be necessary.

After testing, the adetailer plug-in can make sdxl perform well on webui, but I want to use it in a script. Can this pipe support sdxl?Much appreciated.

I wanted implement the controller of Detection and Mask Preprocessing using slider bar as above.
howerever, I couldn't find any arguments/parmetres related with Detection & Mask Preprocessing.

anyone knows how to set up those parametres?

So the face oddly gets darker when using the pipeline and I don't notice hands getting fixed like in a11. How do I adjust it so the face isn't so dark.any way to focus on what we are selecting? Like face only, hands only, etc. Are there any models to change how the eyes are generated? Thanks!

Upgraded to Diffusers 0.23.1 and I get the following error. Not really sure what changed, maybe you have some insight? Much appreciated.

Traceback (most recent call last):
  File "D:\diffusion-ai\main2.py", line 8, in <module>
    from generation import shibiko_init, shibiko_create
  File "D:\diffusion-ai\generation.py", line 10, in <module>
    from asdff import AdPipeline
  File "D:\diffusion-ai\.venv\lib\site-packages\asdff\__init__.py", line 2, in <
module>
    from .sd import AdCnPipeline, AdPipeline
  File "D:\diffusion-ai\.venv\lib\site-packages\asdff\sd.py", line 18, in <modul
e>
    class AdPipeline(AdPipelineBase, StableDiffusionPipeline):
TypeError: metaclass conflict: the metaclass of a derived class must be a (non-s
trict) subclass of the metaclasses of all its bases

How to use asdff aka ADetailer with StableDiffusionXLPipeline?

How to use the AdCnPipeline with inpainting?

I initialized the call as

pipe = AdCnPipeline.from_pretrained("stablediffusionapi/counterfeit-v30", torch_dtype=torch.float16, controlnet=controlnet)

but now how to activate inpainting?

In the UI, I was able to load my checkpoints and use it as main prompt. It works wonders.

Additionally, how do I design it so that it is similar to the A1111 workflow:

1. I generate an image with StableDiffusionPipeline
2. Send the image to adetailer with prompt that uses textual inversion token
3. It outputs a refined image