How To Use Stable Diffusion

Stable Diffusion has the most flexibility of any AI image generator. You can train your models on your own datasets to make it generate the images you want.

There are many ways to use Stable Diffusion. You can either download and run the software on your computer, create your own model with or LeapAI using nightcafe , or access the API through . The easiest option, and the one that I will show you here, is through DreamStudio ‘s official Stability AI web application. This is a simple way to play with Stable Diffusion. Let’s get started.

Sign up for Stable Diffusion

Stable Diffusion’s official web app is DreamStudio. Sign up for DreamStudio here:

1. Go to https://dreamstudio.ai/generate
2. Close pop-ups that tell you about new features and accept the terms of service, if asked.
3. Click Login at the top right and create a brand new account.

You will receive 25 credits upon registration. This is enough for you to generate 30 images using the default settings and try out seven different prompts. Additional credits are also very cheap: $10 will get you 1,000. If you run out of credits, you can always try running Stable Diffusion on your computer for free.

How to create an image using Stable Diffusion

Let’s begin by creating your first image. DreamStudio’s controls are located in the left-sidebar. There are a lot of options available than with DALL*E 2, but let’s keep it simple.

You can select a style image from the Style menu. There are a lot of options. The default, Enhance, produces realistic–but not photorealistic–images and is always a good option. You can also choose what you like: Anime or Photographic, Digital Art (but not photorealistic), Comic Book, Fantasy Art (but not photorealistic), Analog Film, Neon Punk (but not photorealistic), Isometric Low Poly, Line Art Craft Clay, Cinematic 3D Models, Pixel Art. Enjoy yourself.

The Prompt Box is the most important part. You can describe what you’d like Stable Diffusion create. You can always choose from a list of random suggestions to get some ideas, but you are free to enter anything you like. My favorite ones to try include:

• A painting in Vermeer’s style depicting a large, fluffy Irish wolfhound drinking beer in a pub.
• Impressionist painting of a Canadian riding a moose in a maple tree forest.
• Digital art in high definition of a cartoon purple calf.

Click Dream after you have entered your prompt.

The numbers on the button will tell you how many credits you will need to create the artwork using the settings that you have selected. The default value is 3.33.

After DreamStudio has finished its work, you will have four choices to choose from. You can then use the buttons on the right sidebar of your screen to either download the image (and optionally increase the resolution), reuse it in the prompt, create additional variations, edit the image, or make it the first image.

Stable Diffusion is a great way to refine your image.

While the style option gives you some control over images Stable Diffusion creates, the majority of power still lies in the prompts. DreamStudio gives you a few choices.

Focus on the prompt

The Prompt is the most important. You can make the most out of this box by describing the image in detail.

• The more specific your request, the better. If you want bananas, don’t say fruit–say bananas.
• Don’t complicate your instructions. The more specific you are, the more confusing things will be. The current generation of art creators may also struggle to understand quantities, colors, and sizes.
• Pay attention to the details. You may want to add descriptions for the medium, the lighting, the mood, the composition, the color, the subject and the environment.
• Try different things. Learning is best done by experimenting.Use negative promptsNegative prompt allows you to list what you don’t wish to be included in your image. This is not as powerful as I would like, but you can use it to skew the generated images.As an example, the image above uses “hills and grass, trees in fields, farms, etc.” as a negative prompt. Although some of these backgrounds are still present, they are less prominent across the four images when I use the prompt, “a portrait of purple cow, high-definition digital art.”Use an image to promptYou can upload an image in the Image field to be used as part of a prompt. This is a powerful tool that allows you to manipulate the composition, colors, and other aspects of the image. You can choose how much an uploaded image will influence the generated artwork. The default is 35 percent, but you can experiment with it.

In the above images, I used the prompt “a Zombie running through woods” with a picture of me running through woods. The image strength was set at 35% for the bottom options, and 70% for the top ones. You can see in both cases how the base image has an impact on the overall appearance.

Image settings for More Stable Diffusion

Stable Diffusion offers a few other settings that you can experiment with. They all have an impact on how many credits are required for each generation.

Start with two of the most basic:

• Aspect Ratio The default is 1:1, but you can also select 7:4, 3:1, 4:3, 4:3, 4:3, 5;4, 4:5, 2:3, 3:4, and 7:4 for a wider picture.
• Image count You can create anywhere between one to ten images per prompt.

You can choose four options under Advanced:

• Prompt Strength: Controls how heavily Stable Diffusion weighs your prompt while it is generating images. This is a number from 1 to 30 (the default seems to be 15). On the image above you can see that the prompt strength is set to 30 (bottom) and 1 (top).
• Steps of generation: Controls how many steps the model will take. In general, more is better. However, the benefits diminish over time.
• Seed : This controls the random base seed for the image. This is a random number between 1 to 4,294,967.295. You’ll get the same results every time you use the exact same seed and settings.
• Model You can select between three versions of Stable Diffusion – 2.1, SDXL preview, or 2.1-768.

These settings aren’t something you’ll need to use often, but they can be a good way to see what Stable Diffusion does when you give it an instruction.

Stable Diffusion: How to edit images

DreamStudio supports inpainting or outpainting. You can use an AI art creator to change details within an image, or to expand the image beyond its boundaries. To inpaint, or outpaint a picture:

1. Choose the Edit option in the top left corner of the sidebar.
2. Create a brand new image, or import an existing one.
3. Select an area that overlaps, type a prompt and click Dream. You will be given four options to expand your canvas.
4. Use the eraser to remove something from an image and then replace it with a prompt.

I find that DreamStudio ‘s inpainting/outpainting tools are less cohesive. They don’t seem to blend the new AI generations well. It’s a lot of fun to play with and shows how AI image creators could be used in the future.

Stable Diffusion: More than just a Diffusion System

DreamStudio may be the fastest and easiest way to start using Stable Diffusion but it is not the only option. If you enjoy it, then you might want to consider going deeper. You could train your own model, or install it on your computer so that you can create as many images you wish.

The AI image generators Dall*E 2, Middlejourney are also very good.

Benefits of Stable Diffusion in Image Editing

When it comes to editing images, stable diffusion offers several benefits:

1. This technique can provide better image quality and stability than traditional methods, such as deep-neural networks and Bayesian analysis.
2. It is a powerful tool that can enhance old photos or those with low resolution.
3. You can use it to enhance certain features of an image such as color, texture, and more.
4. This tool is versatile, as it can be used to create both static and animated images.
5. Manual editing can be time-consuming.

How Stable Diffusion Works for Image Processing

Stable diffusion analyzes and enhances images using deep neural networks. The network is composed of multiple layers that each handle a specific aspect of image processing such as noise reduction, filtering, color enhancement and so on.

During the training phase, the network receives thousands of images from different sources. The network generates images from these inputs, and compares them with the original images. The process is repeated repeatedly until the network reaches a stable state, meaning that the generated images closely resemble the input images.

After the network has been trained, images can be enhanced by putting them in the network and creating new images. The generated images are then compared with the originals and can be adjusted to achieve the desired results.

Check out this to see examples of diffusion stable in action.

Limitations of stable diffusion in image manipulation

Stable diffusion is a technique that has many advantages for image editing but also some limitations.

1. This can be a time-consuming and computationally intensive process, particularly when dealing with large videos or images.
2. The quality of results can vary depending on input data and network parameters.
3. This program is not suitable for some image editing tasks such as removing unwanted objects from a photo.
4. To work efficiently, it may be necessary to use specialized software and hardware tools. These can be costly.
5. This may not work for images with low contrast or noise.

Check out this article to learn more about AI generated images and what they are.

Compare Stable Diffusion to Other Image Editing Methods

Image editing techniques include: Stable diffusion, and many others. Other techniques include:

• Manual editing: This is the process of manually adjusting color, brightness, contrast and other parameters with image editing software.
• Traditional approaches include deep neural networks (DNN), Bayesian image analyses, and other statistical methods.
• Other AI-powered tools: These include other generative models such as GANs or StyleGANs as well as other AI-powered editing software such as Adobe Sensei.

The best technique will depend on your specific needs.

You can also read our useful Tips

1. Keep your original image in case you need to go back.
2. Try experimenting with different parameters in order to get the desired result.
3. Stable Diffusion can cause image detail to be lost if used too much.
4. For best results, use a high resolution image.
5. For best results, consider using other editing techniques along with stable diffusion.

Related Questions

What is stable diffusion?

Stable diffusion, an AI-powered technique for image editing that uses deep neural network to produce high-quality pictures. It creates images by training models with input images.

How does stable diffusion affect image quality?

Stable diffusion improves image quality through the generation of high-quality images using low-quality sources, as well as by enhancing certain features such colors, textures and more. The quality of the result can vary depending on input data and network parameters.

What are the benefits of using stable diffusion in image editing?

Stable diffusion improves the quality and stability of images. It can also be used to enhance certain features within an image. It can be computationally intense, have varying quality, not work for all images or tasks, and require special hardware and software. The best image editing technique depends on the individual’s needs. Stable diffusion is a powerful tool that can enhance images. However, it must be used with caution and combined with other techniques to achieve the best results.

What are the similarities and differences between DALL-E (Dall-E) and Midjourney (Midjourney)?

DALL-E’s and Midjourney’s approaches to image generation and manipulation are similar. Both use artificial intelligence to allow users to create images and modify them according to their preference. There may be some differences between their features and functionality.

Midjourney can be used in specific industries or applications.

Midjourney is applicable to a wide range of industries and applications. Image manipulation can be used in graphic design and advertising. It is a powerful tool for professionals in a variety of fields, allowing them to customize and manipulate images with ease.

You can use DALL E images for free.

The creators and owners of DALL-E set the terms and conditions for the availability and use of their images. Refer to the guidelines and conditions provided by DALL-E’s creators to better understand their permissions and limitations.

What is MidJourney AI?

MidJourney, a machine-learning-based artificial intelligence (AI) system, is a good example. It uses advanced algorithms and neural network to develop its image-manipulation capabilities. MidJourney is trained on massive amounts of data to learn how to generate and understand images that are aligned with human creativity.

Future of Stable Diffusion

What is the next step? Stable AI released the Stable Diffusion Version 2, which has many improvements and new features over the original V1 release. StableDiffusion2 introduces a major change in the text encoder. OpenAI’s CLIP was used in version 1. This CLIP was trained on datasets that were not available to the public. Stable Diffusion 2 replaces OpenCLIP with LAION‘s OpenCLIP with backing from Stability AI. This improvement leads to an obvious improvement in the images produced. Text-to-image model in this update is able to generate images of default resolutions 512×512 pixels or 768×768 pixel. We can expect to see more technical improvements and new features as AI researchers and companies continue research and development.

DALL-E, Midjourney and Stable Diffusion – Which is better?

The best model to use depends on your specific needs and preferences. Each model has its own strengths and characteristics which make it suitable for a variety of use cases.

DALL-E is a powerful tool that can transform textual descriptions into stunning visuals. It is able to produce images that are more complex and imaginative than what we see in real life.

Midjourney, on the other hand offers an interactive interface which allows users to change various attributes of generated images in real time. The level of customization allows users to experiment with their ideas and make adjustments in real time to achieve the desired results.

Stable Diffusion is a new approach that focuses on the generation of diverse, high-quality images using diffusion. It may not have the same level interactivity of Midjourney’s or DALL-E’s textual prompt capabilities but it still produces high-quality images. It allows different levels of intervention in the creation process.

The “better model” depends on the needs of your business. When choosing the best model for your needs, consider factors like the level of creativity you want, the interactivity, the image quality and the resources available.

Also Read: How To Train Stable Diffusion