Nvidia is now using its AI model to generate photorealistic landscapes that closely match users’ rough sketches. The new image generator, Stable Diffusion, is trained on a 4,000 A100 Ezra-1 AI ultracluster.
The new AI painting model uses a tech called generative adversarial networks (GAN). Simply type in words and the system will modify the picture to fit those phrases.
What is GauGAN?
GauGAN is a generative adversarial network (GAN) that can create photorealistic images from simple sketches. It was developed by Nvidia, a company that specializes in deep learning technologies. It was named after post-Impressionist painter Paul Gauguin and consists of a generator and discriminator.
To train the model, the software was fed a huge dataset of 10 million high-quality landscape photos. It then learned how to mimic the textures and characteristics of these photographs, making it capable of generating convincing imitations of real landscapes.
Users can input a natural language description of a scene and then let the GauGAN AI craft a picture that matches the description. The model can also modify the image by adding or swapping words in the description, such as a “rocky beach” instead of “sunset.”
The system can also be used to generate a segmentation map — a rough outline that shows the location of objects in a scene. After generating the map, users can switch to a drawing mode and doodle any tweaks they want, using labels like “sky,” “tree,” and “river.” The tool’s smart paintbrush will then incorporate these doodles into the image.
Although GauGAN is a bit rough around the edges, it can still create some impressive results. During its testing period, it was able to generate realistic pictures of the sun setting over the ocean and snow falling in the mountains.
Its ability to create realistic images from sketches is a promising step in the direction of artificial intelligence as a design tool. This could help architects and urban planners better prototype designs. It would allow them to make changes to a synthetic scene quickly and easily.
This technology could also be useful for video game developers. Its ability to create realistic images from simple sketches can make it a valuable tool for creating high-quality virtual worlds and game environments.
Currently, the GauGAN image generation tool is only available on Nvidia’s Canvas app, but the software will eventually make its way onto the GPU maker’s website. Nvidia says it envisions the tool as a way to let everyone from architects and landscape designers to game developers craft virtual worlds that accurately reflect how they look in the real world.
Nvidia ai photo generator is a new AI tool from graphics processor maker Nvidia that allows anyone to create beautiful landscapes and other objects in just a few words. The tool uses generative adversarial networks (GANs) to generate AI art, and it’s a big leap forward from what GauGAN did in early 2019.
According to Nvidia, this new demo, called GauGAN2, was trained on ten million high-quality landscape images, using the company’s Selene supercomputer, which is one of the world’s top ten supercomputers. It also includes a discriminator that gives the generator network pixel-by-pixel feedback on how to improve the image it creates, so that it looks more realistic.
The demo is designed to be quick and easy to use – all you need to do is enter a few words that describe the scene you want to create, such as “snow-capped mountain range” or “desert hill.” You can then draw rough sketches, like “sky” or “rock,” to fine-tune your artwork before you send it off for AI processing.
Unlike other AI tools, GauGAN2 combines multiple modalities — text, semantic segmentation, drawing and style — into a single GAN framework that makes it easier to turn an artist’s vision into a high-quality AI-generated image. It’s a lot faster and easier to modify your creations than traditional techniques because it can automatically create a segmentation map, which is a detailed outline that depicts the position of individual items.
To create a photorealistic image, GauGAN2 uses a deep learning model. The system is able to generate a variety of different landscapes and other things by combining text, sketches and an AI-generated layout.
But it’s not quite as easy to use as Nvidia says in its video demonstration of the demo – the program takes a while to figure out how to use it and despite being fed 10 million landscape images, the demo sometimes produces strange, perhaps disturbing, images, such as what appears to be large pieces of foam insulation fighting for their life against a snowy backdrop. That could be due to a problem with the neural network that powers it, but it’s still a neat demonstration.
GauGAN 360 is a new experimental online art tool from Nvidia that turns rough sketches into synthetic 360deg HDR environments for use in 3D scenes. Like Nvidia’s original GauGAN painting app, the tool is based on artificial intelligence model that uses Generative Adversarial Networks to generate photorealistic images matching rough sketches painted by users.
It is a free, web-based app that allows users to paint a landscape and have GauGAN360 create a matching equirectangular image or cube map for use in 3D applications and videogames. It is a new, experimental feature of Nvidia’s GauGAN AI painting app and is designed to make the process of creating 360deg panoramas easier than ever before.
Nvidia has recently released a number of new programs for 3D content creation, such as NeuralVDB and Kaolin Wisp, that make it easier than ever to create high-quality 3D images. Moreover, the company’s new ai photo generator, GauGAN 360, is an example of how these tools can be used by anyone from a novice 3D artist to an experienced professional.
The GauGAN360 web interface is easy to navigate and has a few options for customization. For example, users can choose what brush color represents the ground elements of their landscape, and they can also select a texture to add to their image.
In addition to this, GauGAN360 allows for quick doodles to be transformed into synthetic 360deg panoramas that can be used in 3D software. The app works by analyzing the colors of your paint strokes and then generating a panorama that can be used in 3D software.
During its training period, the GauGAN360 AI model was fed 10 million high-quality landscape images that were then converted into a pixel format and trained to generate photos realistically. The result is a powerful tool that can generate 8K panoramas from even the most rough-looking doodles!
To use GauGAN360, you must agree to the terms of service. These terms give Nvidia (and the parties Nvidia works with) a worldwide license to host, store, reproduce, modify, communicate and publish your User Content in any manner it sees fit, including without limitation for neural network training, and they continue indefinitely after you stop using the GauGAN Research AI Playground. In addition, you agree that Nvidia and the parties it works with can use your feedback about the content you produce for general improvement purposes.
NVIDIA’s latest text-to-image generator is a fascinating and very powerful tool. It takes a simple phrase such as “sunset at a beach” and instantly transforms it into a photorealistic image. The system is based on generative adversarial networks, or GANs. The model was trained on 10 million nature photographs, so the end result is incredibly realistic.
The AI combines segmentation mapping and inpainting within a single GAN framework, making it a great way to turn text into photos. It also allows for multiple modalities — text, semantic segmentation, sketch and style — in one model.
A user may start by building a segmentation map, which is a high-level outline of where items in the scene should be placed. Then they can use their smart paintbrush to fine-tune the landscape with labeled sketches, naming them things such as sky, tree, rock, and river. Then, the smart paintbrush will merge those labels into a gorgeous piece of art.
It takes a bit of playing around with the demo before you can fully understand how it works, though. It’s easy to get the AI to generate a number of odd and sometimes disturbing images, such as what appears to be foam insulation wrangling in a lake and a Formula One race car chewing on a road.
Another interesting feature is the way that it separates high-level attributes, like a person’s identity, from low-level attributes, such as their hairstyle. This enables the AI to make small changes to each convolution layer without affecting other features.
As a result, a person’s hairstyle can be changed without their identity or other elements of the image being affected. This can be very helpful in situations where an image might otherwise appear artificial, such as in a faux celebrity face.
If you want to experiment with the GauGAN Text-to-Image Generator, head over to NVIDIA’s AI Demos. The site features a variety of unique and unusual NVIDIA Research demos that you can try for yourself.
The GauGAN Text-to-Image Generator is available on the site in both text and image formats. It also gives you an option to request alternatives, so that you can get an idea of what else the AI might be able to do for you.