facebookresearch/EdgeTAM

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.

The repository provides code for running inference and finetuning with the Meta Segment Anything Model 3 (SAM 3), links for downloading the trained model checkpoints, and example notebooks that show how to use the model.

A distilled Segment Anything (SAM) model capable of running real-time with NVIDIA TensorRT

[SENSORS 2025] PicoSAM2 and PicoSAM3 are segmentation models running in-sensor on the Sony IMX500.

EfficientSAM: Leveraged Masked Image Pretraining for Efficient Segment Anything

D-FINE-seg Object Detection and Segmentation Framework (Train, Export, Inference)

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.

EfficientSAM3 compresses SAM3 into lightweight, edge-friendly models via progressive knowledge distillation for fast promptable concept segmentation and tracking.