2 projects for "python code generator page" with 2 filters applied:

  • Simple, Secure Domain Registration Icon
    Simple, Secure Domain Registration

    Get your domain at wholesale price. Cloudflare offers simple, secure registration with no markups, plus free DNS, CDN, and SSL integration.

    Register or renew your domain and pay only what we pay. No markups, hidden fees, or surprise add-ons. Choose from over 400 TLDs (.com, .ai, .dev). Every domain is integrated with Cloudflare's industry-leading DNS, CDN, and free SSL to make your site faster and more secure. Simple, secure, at-cost domain registration.
    Sign up for free
  • Gen AI apps are built with MongoDB Atlas Icon
    Gen AI apps are built with MongoDB Atlas

    Build gen AI apps with an all-in-one modern database: MongoDB Atlas

    MongoDB Atlas provides built-in vector search and a flexible document model so developers can build, scale, and run gen AI apps without stitching together multiple databases. From LLM integration to semantic search, Atlas simplifies your AI architecture—and it’s free to get started.
    Start Free
  • 1
    InfoGAN

    InfoGAN

    Code for reproducing key results in the paper

    ... the generator to structure its latent space in a way where certain latent variables control meaningful, distinct factors (e.g. rotation, width, stroke thickness) in the output images. The repository includes code for experiments (e.g. on MNIST), launcher scripts, and some tests. It depends on a development version of TensorFlow (the code expects features not in older stable releases), and also uses other libraries like prettytensor and progressbar.
    Downloads: 0 This Week
    Last Update:
    See Project
  • 2
    SG2Im

    SG2Im

    Code for "Image Generation from Scene Graphs", Johnson et al, CVPR 201

    .... This separation lets the model reason about geometry and composition before committing to texture and color, improving spatial fidelity. The repository includes training code, datasets, and evaluation scripts so researchers can reproduce baselines and extend components such as the graph encoder or image generator. In practice, sg2im demonstrates how structured semantics can guide generative models to produce controllable, compositional imagery.
    Downloads: 0 This Week
    Last Update:
    See Project
  • Previous
  • You're on page 1
  • Next