Continued expansion is being made by Stable Diffusion, which is one of the most recent picture generators to be introduced. Because of its open-source nature, thousands of individuals are modifying it to produce solutions that we have never seen before. This adaptability is something that other generators, such as DALL-E 2 by OpenAI and Make-A-Scene by Meta, do not have because of access restrictions. code that is the source.
The generation model that was trained on the LAION-Aesthetics picture set went from being entirely unknown to becoming one of the most popular in a matter of weeks. Lexica is a Stable Diffusion image and quick search engine that is available to everyone. It was developed by Sharif Shameem, a developer, in response to the growing quantity of photographs that are being made on a daily basis, some of which are of significant quality.
As was indicated before, Stable Diffusion is capable of producing photorealistic images from text. Despite the fact that the software is able to answer to any question that is asked in English, the results will be more accurate if we utilize clear instructions in an organized fashion. To put it more precisely, one of the benefits of these models is the great level of control that users have over their experience.
The issue is that if we use random indications and leave out specifics about the style (for example, do we want a photorealistic image or an oil painting? ), the artistic level (do we favor Van Gogh or Leonardo da Vinci? ), and the lighting parameters (Unreal Engine or triadic scheme? ), the outcome might not be what we had anticipated. A resource that can “train” us in the use of this artificial intelligence is Lexica.
We are greeted by a pretty straightforward user experience when we enter lexica.art. According to the legend that is located beneath the name of the search engine, we will be searching through more than 5 million photos and indicators that are associated with stable diffusion. You have the option of scrolling down the grid and selecting any of the images that are already there before beginning the search. Because of this, you will be able to view the prompts that have been administered.
You will be able to locate the other compositions that were generated based on the initial indication if you click on the Copy URL button and then open the link that you choose to copy. This way, you will have an easier time finding ideas for your own creations and will also have a better notion of the directions that you will need to enter in order to make them come true or to make them as close as possible to what you envisage. If you want to filter down the results, you can also use the search box that is located on the homepage.
You have a number of options available to you in addition to the use of stable diffusion in the event that you wish to begin generating your own inventions. You are able to get started with DreamStudio, which is a front-end that is based on credits (you get 200 credits when you sign up for free) and is quite simple to use. You also have the option of merging the capabilities of this AI with graphics editing programs like as Photoshop and GIMP, among other tools. A number of people are already putting it into practice, and the outcomes are very remarkable.
Hello and welcome to this tutorial on stable diffusion! The new open-source Stable Diffusion AI model makes it possible for anyone to create images that have an amazing appearance, or what is commonly referred to as “art generated by artificial intelligence” (AI generated art).
Lexica is a new image search engine that was developed by Stable Diffusion. It allows you to search through millions of photos that were generated by Stable Diffusion. This tutorial will show you how to use Lexica. You might simply utilize it to look at pictures in order to get some ideas, or you could use its application programming interface (API) to include it into your next project. One of the most significant benefits of working with tools that are based on stable diffusion, such as Lexica, is that you do not have to generate the photos on your own; rather, you can simply use the ones that have already been indexed. Both time and computing power are saved as a result of this.
It was Sharif Shameem who came up with the idea for the website, and he has expressed the hope that it will “make stable diffusion prompting a bit less of a dark art and more of a science.”
www.lexica.art is the address of the website in question. It is really straightforward and easy to operate. By putting a query into the search bar, you will be able to search for available photographs. It is up to you to decide what the prompt will be; it might be a single word, a sentence, or even an entire paragraph.
As was indicated earlier, the website also allows you to produce photographs for your own use it. Simply click on the button that says “generate” after entering a prompt. Additionally, you have the ability to alter the characteristics of the model, such as the width, height, and seed. You also have the ability to include anything that you would like to be left out of your generation.
The Lexica team has also implemented a new application programming interface (API) capability that allows for programmatic access to the photos. To utilize the search API provided by Lexica, you must first generate a GET request and use the query parameter q as your search phrase. An example of this would be making a request to: in order to search for the phrase “apples”
You may even perform a search in reverse for images. You simply need to send Lexica the image you desire, and it will return the photographs that are most similar to it. When it comes to your next project or hackathon, this opens up a lot of options for you to exploit with stable diffusion. The URL of an image can be used as the query for a reverse image search, which is conducted as follows:
Visit our stable diffusion prompt guide on the instructional page, which is similar to this one, if you are interested in learning more about how to write good prompts. Our guide can be found here. Is it possible that you would like to develop a tool that is based on the concept of stable diffusion? Join our Stable Diffusion AI Hackathon if you are interested! I am grateful to you! You can find further tutorials and continue reading on our tutorial page if you found this tutorial to be enjoyable. -! Fabian Stehle, an intern in the field of data science at New Native
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