Clone the repository on your machine, then run the following command to install all dependencies:

pip install -r requirements.txt

Then login with your huggingface account with the command (required to download the weights):

huggingface-cli login

From that point, you can either run main.py and let it download the weights from huggingface automatically. Or if you prefer, you can download them manually with either of the following command:

# For Stable Diffusion 1.4
git clone https://huggingface.co/CompVis/stable-diffusion-v1-4
# For Stable Diffusion 1.5
git clone https://huggingface.co/runwayml/stable-diffusion-v1-5
# For Openjourney
git clone https://huggingface.co/prompthero/openjourney

It also required a slight amount of optimization by loading the model only once, since this is the most time-consuming task, and then use it as many times as desired.

This is also my first time writing a proper README, and while I can sense there are still improvements to be made, this is a nice practice of communication skills.

I believe there should be as little steps as possible required for a user to run a script, which is why I aimed for only huggingface-cli login to be required for setup, and python main.py to run it.

In terms of improvement, I could probably wrap the entire thing in a class so that another library could use it programatically without having to load the model if they don't. For instance, if this is used as a command for a discord bot, it is unnecessary to load the model if it turns out no users call the command while the bot is running.
I could perhaps have better results if I tweak the parameters a little more, 10 inference steps seems like a sweet spot, but 15 or 20 might yield better retults, the default however would often try too hard to give realistic results, while less than 10 steps barely change the input image.

I also came to the realisation that I was using the Strengh parameter wrong when using the model, since I thought it meant how much I'm trying to preserve the original image, rather than how much noise I add onto it. So changing it from 0.95 to 0.05 drastically reduced the issue of changing the original image too much.

I didn't like that using a local model required editing one line in the code so I added a model selection at the start, leaving the option to use Stable Diffusion 1.4 as well since 1.5 seems to take an insanely longer time to download for the first time due to the large checkpoints file.

I also changed the amount of steps back to default since changing the strench helped avoiding the AI straying too much. And choose to take slices of 32x32 from the r/Place canvas instead of 64x64 since it seems to have less messy results overall.
Following @mathieugalle's suggestion, I've also added Image.Resampling.NEAREST as an argument to Pillow's resize function.

If I'm going to update this further, I'll probably try to look into fine-tuning the model, in which case I'll probably release the fine-tuned model in the repository as well as removing the recursion.

In the future I might come back to try to ease using just about any model and adding OpenJourney V2 as a default.