Have you ever wondered how to create stunning images with just a few words? If so, you might want to check out Stable Diffusion, a powerful text-to-image diffusion model that can generate detailed images conditioned on text descriptions, outpainting, and image-to-image translations.
However, sometimes you might not be satisfied with the output that prevent you from getting the image you want. That’s where negative prompts come in handy. In this article, we will show you how to use negative prompts in Stable Diffusion, how they can improve your images, and what are the best negative prompts for different types of images.
What is Negative Prompt?
A negative prompt is a way to tell Stable Diffusion what you don’t want in your image. It helps you avoid unwanted elements, styles, or environments in your image creation. You can use negative prompts to fine-tune your image output, remove unwanted objects, and fix any errors.
How do you Enter Negative Prompts?
To use Stable Diffusion Negative Prompts List 2.1, you need to type them in the second text box before generating an image. The second text box is marked with a red circle in the picture below. The first text box is for the main prompt that describes what you want in your image.
The second text box is for the negative prompt that tells the AI what you don’t want in your image. After you enter both prompts, you can click on Generate image to start the image creation process. Negative prompts are a powerful way to customize your image output with Stable Diffusion Negative Prompts List 2.1.
Best Negative Prompts for Different Types of Images
Depending on what type of image you want to create, you might need different negative prompts to address different issues or challenges. For example, if you want to create a portrait of a person, you might need negative prompts to fix bad anatomy, extra limbs, cloned faces, blurry details, low contrast, over, etc.
For example, you can use negative prompts such as “bad anatomy, poor proportions, extra limbs, cloned faces, blurry details, low contrast, over/underexposed colors: -1.0” to avoid these issues. On the other hand, if you want to create a landscape of a place, you might need negative prompts to remove buildings, cars, people, animals, clouds, etc.
For example, you can use negative prompts such as “buildings, cars, people, animals, clouds: -1.0” to remove these elements. Similarly, if you want to create an animal of a species, you might need negative prompts to correct wrong colors, patterns, shapes, sizes, etc.
How to Experiment with Negative Prompts?
One of the best ways to use Stable Diffusion Negative Prompts List is to experiment with different negative prompts. By trying out different combinations and variations of negative prompts, you can discover new possibilities your images. Some of the features that you can use to experiment with negative prompts are:
Seeds: Seeds are random numbers that influence the output of the model. By changing the seed value, you can generate different outputs for the same prompt. You can use seeds to explore different outcomes and variations of your images with negative prompts.
Sampling methods: Sampling methods are algorithms that determine how the model samples from the probability distribution of the output. By changing the sampling method, you can control the randomness and diversity of the output. You can use sampling methods to balance between quality and diversity of your images with negative prompts.
CFG scale: CFG scale is a parameter that controls the strength of the text conditioning on the output. By changing the CFG scale value, you can control how much the output follows the text prompt. You can use CFG scale to modify how much your images match your text prompt with negative prompts.
Face restoration: Face restoration is a feature that enhances the quality and realism of faces in the output. By enabling or disabling face restoration, you can improve or degrade the faces in your output. You can use face restoration to optimize or experiment with faces in your images with negative prompts.
Model hash: Model hash is a parameter that specifies which version of Stable Diffusion model to use. By changing the model hash value, you can access different versions of Stable Diffusion model that have different capabilities and features. You can use model hash to switch between different models for your images with negative prompts.
How Negative Prompts Can Improve Your Images?
Stable Diffusion Negative Prompts List can improve your images by guiding the generation process and preventing undesired features from appearing in your output. Sometimes, Stable Diffusion might generate images that have some flaws or errors that ruin the quality or realism of your images.
For example, it might generate images that have bad anatomy, poor proportions, extra limbs, cloned faces, blurry details, low contrast, over/underexposed colors, etc. These issues can make your images look unnatural or unappealing. By using negative prompts, you can address these issues and improve your images significantly.
How to Avoid Overusing Negative Prompts?
While Stable Diffusion Negative Prompts List are very useful and powerful, they also have some potential drawbacks that you should be aware of. One of the main drawbacks of Stable Diffusion Negative Prompts List is that they can limit the creativity and diversity of the output.
For example, if you use negative prompts such as “no humans, no animals, no plants, no buildings, no cars, no clouds: -1.0”, you might end up with an empty or boring image that has nothing interesting or appealing in it. Another drawback of Stable Diffusion Negative Prompts List is that they can result in bland or unrealistic images.
If you use Stable Diffusion Negative Prompts List that are too vague or general, you might end up removing or reducing some features or elements that are essential or natural for the image type. For example, if you use negative prompts such as “no colors: -1.0”, you might end up with a grayscale image that lacks vibrancy and realism.
Tips and Tricks
- Use descriptive words or phrases that capture the essence of what you want to exclude from the output.
- Use synonyms or related words to cover more possibilities and variations.
- Use modifiers or qualifiers to narrow down or expand the scope of the negative prompt. General words such as “humans, beings, creatures, etc.”
- Use negations or opposites to reverse the meaning of the negative prompt.
You can also check out our blog, Stable Diffusion NSFW – Prompts Models in Google Colab for more tips and tutorials on Stable Diffusion NSFW Prompts Models in Google Colab. Stable Diffusion is a powerful tool that allows users to generate realistic images based on text prompts.
FAQs
Conclusion
Stable Diffusion Negative Prompts List are words that specify what to exclude from the output, such as “ugly, deformed, etc.” By using negative prompts, you can guide the generation process undesired features from appearing in your images. Stable Diffusion Negative Prompts List can help you improve the quality, and style of your images.
Best Stable Diffusion Negative Prompts List to Improve Images