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Pix2pix implementation in keras. The repository provides code to download the facades dataset, install requirements, and start training, and it references the original Image-to-Image Translation with Conditional Adversarial Networks paper.

Models & Machine Learning 0

MidJourney Styles and Keywords on GitHub is a reference repository containing styles and keywords for use with MidJourney AI, alongside pages showing resolution comparison, image weights, and additional related resources.

AI Image Generation 0
github.com

Upscaling refers to the ultimate-upscale-for-automatic1111 project, an upscaling extension for the AUTOMATIC1111 Stable Diffusion web UI. The public repository includes instructions, reference materials, example content, and API usage documentation for the tool, and contributions to the project are accepted from the public.

AI Image Generation 0

An archived, read-only GitHub repository holding an open solution to the Google AI Open Images Object Detection Track. It offers starter code, configs and notebooks, with RetinaNet training and references to the Neptune experiment platform; Neptune use is optional and the code can run as a plain Python script. The README notes the competition used Open Images Dataset V4.

AI Coding & Development 0
github.com

Hellwal is a color palette generator comparable to Pywal, written in C. Given a wallpaper image it generates color templates, which are saved to ~/.cache/hellwal/. Templates can reference colors 0 to 15 in hex, rgb or single rgb channel formats and support HSL and RGB operations. It is available via AUR, Homebrew and Nixpkgs, or can be built with make.

Linux & macOS Customization 0
github.com

torchvision is a package of popular datasets, model architectures and common image transformations for computer vision. The repository holds documentation, benchmarks, examples, packaging, references and tests alongside the torchvision code. Installation instructions point to official guidance for stable torch and torchvision versions; building from source is covered on the contributing page.

Models & Machine Learning 0