DeepFloyd

Welcome to DeepFloyd IF, the revolutionary modular neural network that brings your images to life in stunning high-resolution detail. Our unique cascaded approach, powered by multiple neural modules, produces a synergistic effect that will leave you amazed.

Using our base model, we start by generating low-resolution samples. But don't be fooled by their initial quality, because we then boost these samples with a series of upscale models to create breathtaking high-resolution images.

What sets DeepFloyd IF apart is our use of diffusion models in both the base and super-resolution models. By introducing random noise through Markov chain steps, we not only add a touch of unpredictability to the process but also generate completely new data samples from the noise. The result is an outstanding zero-shot FID score and deep text understanding.

Operating within the pixel space, rather than latent diffusion, DeepFloyd IF allows for the fusion of different texts, styles, textures, and spatial relations. We achieve image-to-image translation by resizing the original image to 64 pixels, applying forward diffusion to introduce noise, and then denoising the image with a new prompt during the backward diffusion process.

This approach opens up endless possibilities for customization. You can tweak the style, patterns, and details in the output while still preserving the essence of the source image. Whether you want to embroider it on fabric, insert it into a stained-glass window, include it in a collage, or light it up on a neon sign, DeepFloyd IF is the perfect tool for adding uniqueness and creativity to your projects.