diffusion-models-class VS sd-webui-controlnet

When you use stable diffusion, you can adjust the classifier free guidance scale to control how much it follows the input prompt. From what I understand(check https://github.com/huggingface/diffusion-models-class/tree/main/unit3), what cfg does is that it generates an unconditional image and an image conditional on the text prompt, and then scale up the difference.

https://huggingface.co/learn/nlp-course/ https://huggingface.co/docs/transformers (go through the task guide) https://github.com/huggingface/diffusion-models-class http://d2l.ai/ https://www.youtube.com/watch?v=VMj-3S1tku0&list=PLAqhIrjkxbuWI23v9cThsA9GvCAUhRvKZ

I couldn't understand the original paper(havent done meth in a long time). This blog post and short course help me to understand.

The Diffusion Models Course is another good resource to learn more technical details.

Next, you need to become familiar with the diffusion model. I recommend this huggingface's course(https://github.com/huggingface/diffusion-models-class) because it is very high quality and you will learn while using diffusers. At first glance, it may not seem directly related to this game, but in my case, knowing what is happening in diffusers helped me in many ways: trial and error, inspiration for ideas, etc. I had no knowledge of pytorch (the deep learning library used for diffusers), so I also took this course (https://www.udacity.com/course/deep-learning-pytorch--ud188) which was in the prerequisites for that huggingface's course. It was also very good.

Hugging Face Dreambooth Hackaton details

Details: https://github.com/huggingface/diffusion-models-class/blob/main/hackathon/README.md

A crucial step for achieving stable diffusion controlnet settings is the installation of the controlnet extension in Google Colab. Whether on a Windows PC or Mac, installing controlnet is vital for stable diffusion of human pose details. Additionally, updating the controlnet extension is necessary to maintain stability and achieve the desired results in OpenPose model. To install the v1.1 controlnet extension, go to the “extensions” tab and install it from this URL: https://github.com/Mikubill/sd-webui-controlnet. If you already have v1 controlnets installed, delete the folder from stable-diffusion-webui/extensions/. Install the v1.

1.1.420 Image-wise ControlNet and StyleAlign

I opened a request thread on ControlNet GitHub you can give a support : https://github.com/Mikubill/sd-webui-controlnet/issues/2319

It has been possible for 7 months now

I sometimes use a very similar technique in Cinema4d (here is a link to a c4d file with preset materials referencing proper colors for Semantic Segmentation if any other c4d user wants to try it), but yours is a much more accessible solution as it's free and it's accessible online.

There are models available that give you more control - in some senses, at least.

For example, you can use Stable Diffusion with 'ControlNet' [1] where for example, you can input an 'openpose' to choose the pose of people in the scene.

There's also a 'Regional Prompter' [2] which lets you use different prompts for different areas of the image, giving you some control over the composition.

You can also use 'inpainting' to regenerate select parts of your image if, for example, you don't like the shape of the clouds.

Of course this stuff isn't perfect - for example, you'll get hands with the wrong number of fingers sometimes, no matter what you specify :)

[1] https://github.com/Mikubill/sd-webui-controlnet