ControlNet-v1-1-nightly VS ControlNet

1- https://github.com/lllyasviel/ControlNet-v1-1-nightly/issues/89

Install ControlNet and download the models you want to use (canny/depth/openpose should be enough for this): https://github.com/lllyasviel/ControlNet-v1-1-nightly

you can find the previous version on their git and if it's a previous version of v1.1 then you probably have to search for the right branch on the new git version and download that

Stable Diffusion: https://huggingface.co/runwayml/stable-diffusion-v1-5 with ControlNet extension: https://github.com/lllyasviel/ControlNet-v1-1-nightly running on Automatic1111 web UI: https://github.com/AUTOMATIC1111/stable-diffusion-webui

Sure thing, after testing midjourney a bit I found out that yhe quality of images produced is best but you have zero control on over what is produced. The big breakthrough here is ControlNet which is a Stable Diffusion extension that makes you control the initial noise based on image inputs (or at least this is what i understand) more on it here: https://github.com/lllyasviel/ControlNet-v1-1-nightly

https://github.com/lllyasviel/ControlNet-v1-1-nightly/issues/61 it seems get removed as duplicated.

It`s all possible. Have a look into Automatic1111`s Web UI, ControlNet, OpenPose and, if you don`t have a dedicated GPU with at least 8GB of VRAM, or at least 16GB of RAM to use the CPU, you can also use Stable Horde to use the webUI with a peer-to-peer connection, where you`ll only use a fraction of your resources, but you`ll be able to use local AI models with all the bells and whistles that you won`t get from "state-of-the-art" paid services.

Next up is ControlNet. Controlnet, as Illyasviel--creator of controlnet--describes it, "let's us control diffusion models!." ControlNet is a neural network structure to control diffusion models by adding extra connections. [8]. There is more to that than what I described, but the big take-away is that ControlNet takes a preprocessed image that you provide (or is generated) and uses that as a way of constraining the output the sampler's noise generates, allowing you to have a bit more control of the output. ControlNet is typically used for character or scene "artwork", which previously would have been a challenge with just prompting alone (at least with this current architecture).

For your first part of the comment, I can simply refer you to technologies like ControlNet, LoRA and prompt embedding: https://github.com/lllyasviel/ControlNet https://github.com/microsoft/LoRA

Here you can see what every controlnet preprocessor and model do, to give you an idea of ​​how to use

Ya, it takes awhile to really start getting comfortable with the wonkiness. If you are trying to do something specific, look for a LoRA, but in general I'd recommend you get controlnet so you can feed it a reference image. Another simple trick is to edit the image a bit in GIMP or a photo editor to get the color scheme you like and then feed it back to img2img at low denoising (0.1-0.2) to refine it. You can also add just garishly bad cartoon drawing or photoshop in assets and img2img will usually make something of them and blend them into your image, I find this easier than using img2img scribble.

If there are no errors, go to the "Extensions" tab, then "Install from URL". There, enter "https://github.com/lllyasviel/ControlNet" then click "Install".

This is a good place to start reading. Given the open-source nature of SD, there are setups of various difficulty available. A1111 is the "standard" people enjoy because it's easy to plug in new stuff (ControlNet, new models, etc.), but it's not inherently easy to set up and get going. There is an installer for it, but I haven't tried it.