facebookresearch / sam2Links
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.
☆18,185Updated last year
Alternatives and similar repositories for sam2
Users that are interested in sam2 are comparing it to the libraries listed below
Sorting:
- [ECCV 2024] Official implementation of the paper "Grounding DINO: Marrying DINO with Grounded Pre-Training for Open-Set Object Detection"☆9,493Updated last year
- PyTorch code and models for the DINOv2 self-supervised learning method.☆12,142Updated last week
- Grounded SAM: Marrying Grounding DINO with Segment Anything & Stable Diffusion & Recognize Anything - Automatically Detect , Segment and …☆17,281Updated last year
- Grounded SAM 2: Ground and Track Anything in Videos with Grounding DINO, Florence-2 and SAM 2☆3,147Updated last month
- The repository provides code for running inference with the SegmentAnything Model (SAM), links for downloading the trained model checkpoi…☆53,025Updated last year
- [CVPR 2024] Real-Time Open-Vocabulary Object Detection☆6,117Updated 10 months ago
- Fast Segment Anything☆8,215Updated last year
- CoTracker is a model for tracking any point (pixel) on a video.☆4,740Updated 11 months ago
- [NeurIPS 2023] Official implementation of the paper "Segment Everything Everywhere All at Once"☆4,761Updated last year
- An open source implementation of CLIP.☆13,178Updated last month
- Segment Anything in High Quality [NeurIPS 2023]☆4,149Updated 3 months ago
- [NeurIPS 2024] Depth Anything V2. A More Capable Foundation Model for Monocular Depth Estimation☆7,293Updated 11 months ago
- SAM with text prompt☆2,513Updated 4 months ago
- [CVPR 2024] Depth Anything: Unleashing the Power of Large-Scale Unlabeled Data. Foundation Model for Monocular Depth Estimation☆7,931Updated last year
- This is the official code for MobileSAM project that makes SAM lightweight for mobile applications and beyond!☆5,558Updated last week
- CLIP (Contrastive Language-Image Pretraining), Predict the most relevant text snippet given an image☆32,095Updated last year
- Efficient vision foundation models for high-resolution generation and perception.☆3,186Updated 3 months ago
- Official repository of "SAMURAI: Adapting Segment Anything Model for Zero-Shot Visual Tracking with Motion-Aware Memory"☆7,030Updated 9 months ago
- PyTorch code for BLIP: Bootstrapping Language-Image Pre-training for Unified Vision-Language Understanding and Generation☆5,626Updated last year
- Reference PyTorch implementation and models for DINOv3☆9,116Updated last month
- LAVIS - A One-stop Library for Language-Vision Intelligence☆11,087Updated last year
- Open-source and strong foundation image recognition models.☆3,536Updated 10 months ago
- Depth Pro: Sharp Monocular Metric Depth in Less Than a Second.☆5,135Updated 8 months ago
- Official codebase used to develop Vision Transformer, SigLIP, MLP-Mixer, LiT and more.☆3,297Updated 7 months ago
- [ECCV 2024] Official implementation of the paper "Semantic-SAM: Segment and Recognize Anything at Any Granularity"☆2,790Updated 5 months ago
- [NeurIPS'23 Oral] Visual Instruction Tuning (LLaVA) built towards GPT-4V level capabilities and beyond.☆24,220Updated last year
- Implementation of paper - YOLOv9: Learning What You Want to Learn Using Programmable Gradient Information☆9,458Updated last year
- Images to inference with no labeling (use foundation models to train supervised models).☆2,553Updated 7 months ago
- EfficientSAM: Leveraged Masked Image Pretraining for Efficient Segment Anything☆2,459Updated last year
- Inpaint anything using Segment Anything and inpainting models.☆7,557Updated last year