Running Stable Diffusion with Python

Stable Diffusion is a deep learning model that can generate pictures. In essence, it is a program in which you can provide input (such as a text prompt) and get back a tensor that represents an array of pixels, which, in turn, you can save as an image file. There’s no requirement that you must use a particular user interface. Before any user interface is available, you are supposed to run Stable Diffusion in code. In this tutorial, we will […]

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Further Stable Diffusion Pipeline with Diffusers

There are many ways you can access Stable Diffusion models and generate high-quality images. One popular method is using the Diffusers Python library. It provides a simple interface to Stable Diffusion, making it easy to leverage these powerful AI image generation models. The diffusers lowers the barrier to using cutting-edge generative AI, enabling rapid experimentation and development. This library is very powerful. Not only you can use it to generate pictures from text prompts, but also to leverage LoRA and […]

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Inpainting and Outpainting with Diffusers

Inpainting and outpainting are popular image editing techniques. You have seen how to perform inpainting and outpainting using the WebUI. You can do the same using code as well. In this post, you will see how you can use the diffusers library from Hugging Face to run Stable Diffusion pipeline to perform inpainting and outpainting. After finishing this tutorial, you will learn How to perform inpainting using the corresponding pipeline from diffusers How to understand a outpainting problem as a […]

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How to Use Stable Diffusion Effectively

From the prompt to the picture, Stable Diffusion is a pipeline with many components and parameters. All these components working together creates the output. If a component behave differently, the output will change. Therefore, a bad setting can easily ruin your picture. In this post, you will see: How the different components of the Stable Diffusion pipeline affects your output How to find the best configuration to help you generate a high quality picture Let’s get started. How to Use […]

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Using OpenPose with Stable Diffusion

We have just learned about ControlNet. Now, let’s explore the most effective way to control your character based on human pose. OpenPose is a great tool that can detect body keypoint locations in images and video. By integrating OpenPose with Stable Diffusion, we can guide the AI in generating images that match specific poses. In this post, you will learn about ControlNet’s OpenPose and how to use it to generate similar pose characters. Specifically, we will cover: What is Openpose, […]

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More Prompting Techniques for Stable Diffusion

The image diffusion model, in its simplest form, generates an image from the prompt. The prompt can be a text prompt or an image as long as a suitable encoder is available to convert it into a tensor that the model can use as a condition to guide the generation process. Text prompts are probably the easiest way to provide conditioning. It is easy to provide, but you may not find it easy enough to generate a picture that matches […]

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Using ControlNet with Stable Diffusion

ControlNet is a neural network that can improve image generation in Stable Diffusion by adding extra conditions. This allows users to have more control over the images generated. Instead of trying out different prompts, the ControlNet models enable users to generate consistent images with just one prompt. In this post, you will learn how to gain precise control over images generated by Stable Diffusion using ControlNet. Specifically, we will cover: What is ControlNet, and how it works How to use […]

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Inpainting and Outpainting with Stable Diffusion

Inpainting and outpainting have long been popular and well-studied image processing domains. Traditional approaches to these problems often relied on complex algorithms and deep learning techniques yet still gave inconsistent outputs. However, recent advancements in the form of Stable diffusion have reshaped these domains. Stable diffusion now offers enhanced efficacy in inpainting and outpainting while maintaining a remarkably lightweight nature. In this post, you will explore the concepts of inpainting and outpainting and see how you can do these with […]

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Using LoRA in Stable Diffusion

The deep learning model of Stable Diffusion is huge. The weight file is multiple GB large. Retraining the model means to update a lot of weights and that is a lot of work. Sometimes we must modify the Stable Diffusion model, for example, to define a new interpretation of prompts or make the model to generate a different style of painting by default. Indeed there are ways to make such an extension to existing model without modifying the existing model […]

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Generate Realistic Faces in Stable Diffusion

Stable Diffusion’s latest models are very good at generating hyper-realistic images, but they can struggle with accurately generating human faces. We can experiment with prompts, but to get seamless, photorealistic results for faces, we may need to try new methodologies and models.In this post, we will explore various techniques and models for generating highly realistic human faces with Stable Diffusion. Specifically, we will learn how to: Generate realistic images using WebUI and advanced settings. Use Stable Diffusion XL for photorealistic […]

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