sd-webui-controlnet VS ComfyUI

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

The non standard licensing puts me off in contributing or using this. It is frustrating how the phrase opensource has been diluted in the AI/ML community. ComfyUI has a GPL license [1] while this project uses this [2]. I honestly don't know where I stand since this is a legal document using non-standard phrasing to describe how the rights around the source code.

This is a project that uses a custom license with less rights provided than the ComfyUI project it self-describes as improving. Am not sure the title is reflective of the project.

[1] - https://github.com/comfyanonymous/ComfyUI/blob/master/LICENS...

* LLaVA model: I'll add more documentation. You are right Llava could not generate images. For image generation I don't have immediate plans, but checkout these projects for local image generation.

- https://diffusionbee.com/

- https://github.com/comfyanonymous/ComfyUI

- https://github.com/AUTOMATIC1111/stable-diffusion-webui

Check out ComfyUI for a much more advanced and open source version of this.

https://github.com/comfyanonymous/ComfyUI

I use Stable Diffusion family models for innovative art products.

On a small scale, you have to professionalize ComfyUI’s development. My PR to make it installable and to make a plugin ecosystem that makes sense should not be sitting unmerged (https://github.com/comfyanonymous/ComfyUI/pull/298).

On a medium scale, CLIP is holding you back. I would eagerly buy a 48GB card to accommodate a batch size 1, gradient checkpointed LoRA-trainable model with T5 for conditioning. I want PixArt-a or DeepFloyd/IF with the SDXL dataset and training. I get I can achieve so much with SDXL on 24GB, including just barely a fine tuning, I understand the engineering decisions here, but it’s too weak on prompts.

On a large scale, I’m willing to spend a little money up front. In those conditions you can be far more innovative, you don’t have to make everything for $0. Shane Carruth didn’t make Primer for $0. I’m sure you’ve seen this movie, you get how astoundingly good it is. But he still spent something. He spent only slightly more than an RTX 6000 Ada.

Innovators have budgets. It’s still worth releasing the most powerful possible model for expensive hardware, this is why everyone is talking about Mixtral, but it’s especially true of visual art.

It's litegraph.js [1] and seems to be the only lib they include in /web [2] :

[1] https://github.com/jagenjo/litegraph.js

[2] https://github.com/comfyanonymous/ComfyUI/tree/master/web/li...

It's possibly you might get a later version of Comfy working, but I had no success with this method and the 1st Sept version of Comfy. The older versions are here under Assets... https://github.com/comfyanonymous/ComfyUI/releases

That said, please do learn coding and don't get discouraged when somebody says to learn PyTorch or recommends using a Jupiter notebook with no further information on how to translate the skill into images. I would highly recommend some short term goals. Get your feet wet by taking apart the UIs. The comfy API documentation is here and the A1111 API documentation is here. There is a difference in completeness, welcome to programming. Writing nodes or plugins is also a good way to jump into this world. Custom wildcard logic might be very attractive to you if you aren't the type that want to deal with a nested file structure to simulate logic.

For example ComfyUI can simply be downloaded and run using the portable version (https://github.com/comfyanonymous/ComfyUI/releases/download/latest/ComfyUI_windows_portable_nvidia_cu121_or_cpu.7z) if your not comfortable using GIT etc.

https://github.com/comfyanonymous/ComfyUI scroll down to "Install"