Showing 2 open source projects for "artificial images"

View related business solutions
  • Red Hat Enterprise Linux on Microsoft Azure Icon
    Red Hat Enterprise Linux on Microsoft Azure

    Deploy Red Hat Enterprise Linux on Microsoft Azure for a secure, reliable, and scalable cloud environment, fully integrated with Microsoft services.

    Red Hat Enterprise Linux (RHEL) on Microsoft Azure provides a secure, reliable, and flexible foundation for your cloud infrastructure. Red Hat Enterprise Linux on Microsoft Azure is ideal for enterprises seeking to enhance their cloud environment with seamless integration, consistent performance, and comprehensive support.
  • Passwordless authentication enables a secure and frictionless experience for your users | Auth0 Icon
    Over two-thirds of people reuse passwords across sites, resulting in an increasingly insecure e-commerce ecosystem. Learn how passwordless can not only mitigate these issues but make the authentication experience delightful. Implement Auth0 in any application in just five minutes
  • 1
    Dream Textures

    Dream Textures

    Stable Diffusion built-in to Blender

    ... 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. Outpaint to increase the size of an image by extending it in any direction. Perform style transfer and create novel animations with Stable Diffusion as a post processing step. Dream Textures has been tested with CUDA and Apple Silicon GPUs. Over 4GB of VRAM is recommended.
    Downloads: 23 This Week
    Last Update:
    See Project
  • 2
    DALL-E 2 - Pytorch

    DALL-E 2 - Pytorch

    Implementation of DALL-E 2, OpenAI's updated text-to-image synthesis

    ... as the denoising network) To train DALLE-2 is a 3 step process, with the training of CLIP being the most important. To train CLIP, you can either use x-clip package, or join the LAION discord, where a lot of replication efforts are already underway. Then, you will need to train the decoder, which learns to generate images based on the image embedding coming from the trained CLIP.
    Downloads: 1 This Week
    Last Update:
    See Project
  • Previous
  • You're on page 1
  • Next