dream-conveyor

This is a framework on top of a framework to fascilitate (and automate) generation of large quantities of ungodly visual horrors and occasionall AI art. Sometimes the latter look more like the former, never vice versa. Use at your own risk.

Rationale

When initially generating AI art using my CPU (I'm cheap), waiting for individual results is time-consuming. A background script based on the diffusers library by Hugging Face would simplify the process. Initially, I wrote custom code for various tasks, but it lacked scalability and reusability. Over time, I identified recurring usage patterns and developed a framework to generate images efficiently in the background. Especially when parameters are changed slightly with each iteration (see Gradients).

DISCLAIMER: This piece of software is a result of me implementing my personal take on Stable Diffusion image generation workflow. If you find it useful — great, otherwise you should probably look elsewhere.

Quickstart

Start by installing poetry globally, it will help you manage the rest of the requirements and create a virtual environment for you.

pip install poetry

Now install the dependencies by running the following in the project folder.

poetry install

After poetry install you will probably be switched to a virtual environment (i.e poetry shell) automatically. If not, run poetry shell.

The next step would be to configure accelerate.

accelerate config

In some more complicated cases that might not be enough, refer to accelerate documentation if it's giving you issues.

Most of this can be run w/o accelerate but it does accelerate things immensely.

Now you're ready to start generating images. Run this command to start:

accelerate launch run.py ./example/

./example/ can be replaced with any folder on your machine. I have several folders on mine that I use for different projects.

When the script is run it will create the folder (if it doesn't exist) and add a configuration file in that folder that will probably look like this:

base_img: null
cfg: 9
mask_img: null
negative: ''
prompt: ''
seed: null
steps: 24
strength: 0.5

You can update this configuration even while the script is running, that's the whole point. If you change any of the parameters, they will take effect for the next image that will start generation.

I will cover all the implications and various scenarios in series of more in-depth tutorials.

Gradients

TBD

Supported Models

Tested with the following models:

• dreamlike-art/dreamlike-photoreal-2.0
• wavymulder/Analog-Diffusion
• runwayml/stable-diffusion-v1-5
• runwayml/stable-diffusion-inpainting
• stabilityai/stable-diffusion-2
• stabilityai/stable-diffusion-2-inpainting
• darkstorm2150/Protogen_x3.4_Official_Release