#super resolution

Utilizing state-of-the-art models, this project converts text into detailed images and integrates smoothly with platforms like Hugging Face and Colab. It enhances image creation with super-resolution, fine-tuning, and auto-selection via CLIP, and supports video generation, offering a robust toolkit for various creative needs.

This project provides an efficient solution for real-time super resolution of low-resolution videos utilizing the SR-GAN inspired architecture and pixel shuffle technique. Capable of processing videos up to 720p at 30fps on MPS devices, it offers a pretrained model for image inference and detailed instructions for custom training with editable CLI configurations. The repository welcomes contributions for model enhancement and feature expansion, facilitating advancements in video quality through established machine learning methodologies.