A latent text-to-image diffusion model

The repository provides code for running inference with the SegmentAnything Model (SAM), links for downloading the trained model checkpoints, and example notebooks that show how to use the model.

Python programs, usually short, of considerable difficulty, to perfect particular skills.

Segment Anything in High Quality [NeurIPS 2023]

Optimized Stable Diffusion modified to run on lower GPU VRAM

Instant-ngp in pytorch+cuda trained with pytorch-lightning (high quality with high speed, with only few lines of legible code)

QuadTree Attention for Vision Transformers (ICLR2022)

Logo detection in images using SSD