Easy-to-use image segmentation library with awesome pre-trained model zoo, supporting wide-range of practical tasks in Semantic Segmentation, Interactive Segmentation, Panoptic Segmentation, Image Matting, 3D Segmentation, etc.
The repository provides code for running inference with the Meta Segment Anything Model 2 (SAM 2), links for downloading the trained model checkpoints, and example notebooks that show how to use the model.
Visual Geometry Grounded Transformer predicts camera parameters, depth maps, point maps, and point tracks from scene images, making it suitable for preliminary geometric estimation in 3D vision research and reconstruction workflows.