2-1 Let’s prepare the environment to use Stable Diffusion(Stable Diffusion Practical Guide Table of Contents)

List

Chapter 1 Let's learn about image generation AI

• 1-1 Let's create images with AI
• 1-2 The birth and evolution of image generation AI
• 1-3 Let's think about the 'definition of AI' at the present time
• 1-4 Let's learn about artificial neural networks
• 1-5 Let's learn about the principle of image generation by the diffusion model

Chapter 2 Let's start building the environment

• 2-1 Let's prepare the environment to use Stable Diffusion
• 2-2 Let's build the environment using Google Colab
• 2-3 Let's build the Stability Matrix in the local environment
• 2-4 Let's create images with simple words
• 2-5 Download the model
• 2-6 Download the VAE

Chapter 3 Let's create images with prompts

• 3-1 Create images as you think using prompts
• 3-2 Build negative prompts
• 3-3 Let's create images 'as you think'
• 3-4 Let's increase the resolution of the image
• 3-5 Let's adjust various parameters
• 3-6 Let's test various prompts

Chapter 4 Let's create images using images

• 4-1 You can do it with img2img Let's figure out what's there
• 4-2 Let's create an image using Sketch
• 4-3 Let's edit an image using Inpaint
• 4-4 Apply Inpaint to modify an image
• 4-5 Extend an image using Outpainting
• 4-6 Increase the resolution of an image using img2img
• 4-7 Let's upscale with the extension function

Chapter 5 Let's use ControlNet

• 5-1 Let's learn about ControlNet
• 5-2 Download and prepare ControlNet
• 5-3 Create an image using ControlNet
• 5-4 Understand the role of the preprocessor

Chapter 6 Let's create and use LoRA

• 6-1 Let's learn what we can do with additional learning
• 6-2 Let's create an image using LoRA
• 6-3 Create your own dedicated painting style LoRA
• 6-4 Let's create various types of LoRA
• 6-5 Let's evaluate the learning content

Chapter 7 Let's use the image generation AI more

Let's now prepare an environment to use Stable Diffusion. In order to use the application comfortably, you need to configure an environment that is most suitable for your PC environment and the device you want to use.

>>>Let's try creating images using AI

As explained in Chapter 1, Stable Diffusion requires advanced computational power to generate images. Currently, this role is taken care of by CPUs and GPUs, which are computationally intensive. In particular, GPUs, which are capable of advanced computation, are often used for AI learning and inference.

In order to use the existing generative AI models, you generally need to prepare an advanced computational processing unit. As you know, you will have to spend a lot of money to purchase a PC equipped with a GPU that can run generative AI smoothly. However, it is not necessarily the case that only those with high-performance PCs can use Stable Diffusion.

This is because of the technology called cloud computing. Using this technology, you can use external computational devices and memory devices connected to the Internet as if they were your own PC. You don’t need to make much of the initial investment that was originally required, and the cost is only a few tens of thousands of won per month.

Not only those who already have an environment to operate AI, but also those who want to try it out or use it on devices other than PCs can all use cloud services. In this article, we will explain the introduction and support of an image generation environment using a cloud computing service called Google Colaboratory (hereinafter referred to as Colab).

Up to the last part of this article, we have organized the content so that you do not have to worry about 'cost' and 'mathematical and programming knowledge', which are also barriers to entry for generative AI. I hope that after reading the article to the end, you will understand image generation AI more deeply.

>>> Find the usage environment that best suits you

So, let's find the environment that best suits your needs and situation so that you can start setting up your environment right away from the next chapter.

Stable Diffusion Minimum Requirements

Minimum Specs (Low-End)

OS: Windows 10, Linux, macOS

GPU: 4GB VRAM (GTX 1650, RTX 2060)

RAM: 8GB

Storage: 10GB free space

CPU: Intel i5-6th Gen or AMD equivalent

Note: 4GB VRAM is very slow and may not run on some models.

Recommended Specs (Optimal)

OS: Windows 10/11, Linux (Ubuntu 20.04+)

GPU: 8GB VRAM (RTX 3060, RTX 3070, RX 6800)

RAM: 16GB

Storage: 20GB free space

CPU: Intel i7-10th Gen or AMD Ryzen 7

RTX 3060 (12GB) or higher is ideal for smooth performance.

High-End Specs (Fast Performance)

GPU: RTX 3090, RTX 4090, A100 (24GB+ VRAM)

RAM: 32GB+

CPU: Intel i9 or AMD Ryzen 9

SSD: NVMe SSD (faster loading)

Required for large models and high-res images.