FastSD CPU ✨

FastSD CPU is a faster version of Stable Diffusion on CPU. Based on Latent Consistency Models. The application is available as :

Desktop GUI (Qt)
WebUI
CLI (CommandLine Interface)

Using OpenVINO, it took 10 seconds to create a single 512x512 image on a Core i7-12700.

Supported platforms

Windows
Linux
Raspberry PI 4
Mac (Need testers)

Features

Supports 256,512,768 image sizes
Supports Windows and Linux
Saves images and diffusion setting used to generate the image
Settings to control, steps, guidance, and seed
Added safety checker setting
Maximum inference steps increased to 25
Added OpenVINO support
Added web UI
Added CommandLine Interface(CLI)
Fixed OpenVINO image reproducibility issue
Fixed OpenVINO high RAM usage, thanks deinferno
Added multiple image generation support
Application settings

OpenVINO support

Thanks deinferno for the OpenVINO model contribution. We can get 2x speed improvement when using OpenVINO.

LCM Models

The following LCM models are supported:

LCM_Dreamshaper_v7 -https://huggingface.co/SimianLuo/LCM_Dreamshaper_v7 by Simian Luo
LCM_Dreamshaper_v7-openvino - https://huggingface.co/deinferno/LCM_Dreamshaper_v7-openvino by deinferno

FastSD CPU on Windows

❗You must have a working Python installation.(Recommended : Python 3.10 or 3.11 )

Clone/download this repo or download release.

Installation

Double click install.bat (It will take some time to install, depending on your internet speed.)

Run

You can run in desktop GUI mode or web UI mode.

Desktop GUI

To start desktop GUI, double click start.bat

Web UI

To start web UI, double click start-webui.bat

FastSD CPU on Linux

Ensure that you have Python 3.8 or higher version installed.

Clone/download this repo
In the terminal, enter into the fastsdcpu directory
Run the following command

chmod +x install.sh

./install.sh

To start Desktop GUI

./start.sh

To start Web UI

./start-webui.sh

Web UI screenshot

Google Colab

Due to the limitation of using CPU/OpenVINO inside collab, we are using GPU with collab.

CLI mode (Advanced users)

Open the terminal and enter it into the fastsdcpu folder. Activate the virtual environment using the command:

Windows users :

(Suppose FastSD CPU is available in the directory "d:\fastsdcpu") d:\fastsdcpu\env\Scripts\activate.bat

Linux users:

source env/bin/activate

Start CLI src/app.py -h

Raspberry PI 4 support

Thanks, WGNW_MGM, for Raspberry PI 4 testing.FastSD CPU worked without problems. System configuration - Raspberry Pi 4 with 4GB RAM and 8GB of SWAP memory.

License

The fastsdcpu project is available as open source under the terms of the MIT license

alienishi / fastsdcpu