Search Results for "image convert"

Create textures, concept art, background assets, and more with a simple text prompt. Use the 'Seamless' option to create textures that tile perfectly with no visible seam. Texture entire scenes with 'Project Dream Texture' and depth to image. Re-style animations with the Cycles render pass. Run the models on your machine to iterate without slowdowns from a service. Create textures, concept art, and more with text prompts. Learn how to use the various configuration options to get exactly what you're looking for. Texture entire models and scenes with depth to image. Inpaint to fix up images and convert existing textures into seamless ones automatically. ...

Enlightened library to convert HTML and CSS to SVG. Satori supports the JSX syntax, which makes it very straightforward to use. Satori will render the element into a 600×400 SVG, and return the SVG string. Under the hood, it handles layout calculation, font, typography and more, to generate a SVG that matches the exact same HTML and CSS in a browser. Satori only accepts JSX elements that are pure and stateless. You can use a subset of HTML elements (see section below), or custom React...

A Python library for turning text quotes into graphical images. Generate an image using RGB background and foreground. The package comes with a built-in GenerateColors function that generates a fg and bg color with the correct amount of luminosity and returns them in tuples. Generate an image using a custom background image. The package comes with a builtin GenerateColors function that generates a fg and bg color with the correct amount of luminosity and returns them in tuples. We can...

point-e is the official repository for Point-E, a generative model developed by OpenAI that produces 3D point clouds from textual (or image) prompts. Its principal advantage is speed: it can generate 3D assets in just 1–2 minutes on a single GPU, which is significantly faster than many competing text-to-3D models. The model works via a two-stage diffusion approach: first, it uses a text → image diffusion network to produce a synthetic 2D view consistent with the prompt; then a second...

...This repository contains an op-for-op PyTorch reimplementation of DeepMind's BigGAN that was released with the paper Large Scale GAN Training for High Fidelity Natural Image Synthesis. This PyTorch implementation of BigGAN is provided with the pretrained 128x128, 256x256 and 512x512 models by DeepMind. We also provide the scripts used to download and convert these models from the TensorFlow Hub models. This reimplementation was done from the raw computation graph of the Tensorflow version and behave similarly to the TensorFlow version (variance of the output difference of the order of 1e-5). ...