In this post, I'm going to show you how you can generate images using the stable diffusion model on a Windows computer.

How to set up stable diffusion on Windows

This tutorial is based on the stable diffusion tutorial from keras.io. I started with that tutorial because it is relatively system agnostic, and because it uses optimizations that will help on my low powered Windows machine. We only need to make a few modifications to that tutorial to get everything to work on Windows.

Steps

1. Install python. First, check if python is installed using the following command:

python --version

If you already have python, then you can skip this step. Otherwise, type 'python' again to trigger the Windows Store installation process.

2. Install pip. You can install pip by downloading the installation script at https://bootstrap.pypa.io/get-pip.py. Run it using the following command.

python get-pip.py

3. Enable long file path support. This can be done in multiple ways. I think the easiest is to run PowerShell as administrator, then run the following command:

New-ItemProperty -Path "HKLM:\SYSTEM\CurrentControlSet\Control\FileSystem" `
-Name "LongPathsEnabled" -Value 1 -PropertyType DWORD -Force

4. Install dependencies. I had to manually install a few dependencies. Use the following command to install all needed dependencies.

pip install keras-cv tensorflow tensorflow_datasets matplotlib

5. Save the code to a file. Save the following code into a file called whatever you want. I called mine 'stable-diffusion.py'.

import time
import keras_cv
from tensorflow import keras
import matplotlib.pyplot as plt

model = keras_cv.models.StableDiffusion(img_width=512, img_height=512)

images = model.text_to_image("california impressionist landscape showing distant mountains", batch_size=1)

def plot_images(images):
    plt.figure(figsize=(20, 20))
    for i in range(len(images)):
        ax = plt.subplot(1, len(images), i + 1)
        plt.imshow(images[i])
        plt.axis("off")

plot_images(images)

plt.show()

6. Run the code.

python stable-diffusion.py

7. Enjoy. To change the prompt, simply alter the string that is fed into 'model.text_to_image' on line 8. Here are my first images created using this method and the given prompt.