HarborYuan/ovsam

Health v2 · maintenance only

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Adoption not part of the score

1033 stars · 36 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-30, confidence not recorded

Official PyTorch implementation of Open-Vocabulary SAM (ECCV 2024), a model that unifies SAM's interactive segmentation with CLIP's open-vocabulary recognition via SAM2CLIP and CLIP2SAM knowledge transfer modules. It also includes RWKV-SAM, an efficient SAM variant, and offers a Hugging Face demo plus local Gradio demo.

Use cases

• segment and recognize objects from 22,000 classes interactively
• run open-vocabulary segmentation on custom images
• distill SAM knowledge into CLIP for unified segmentation and recognition
• benchmark open-vocabulary detection on COCO
• try efficient RWKV-based SAM segmentation
• run a local gradio demo of interactive segmentation with recognition

When to choose

• you need interactive segmentation with open-vocabulary recognition in one model
• you want to reproduce ECCV 2024 Open-Vocabulary SAM or RWKV-SAM research results
• you need lower computational cost than naively combining SAM and CLIP
• you want a pretrained model covering ~22k classes

When to avoid

• you only need plain SAM segmentation without recognition
• you need a production-ready supported product rather than research code
• you cannot run GPU inference
• you need a non-PyTorch framework

Facets

library · maturity active

machine-learning computer-vision image-processing computer-vision image-processing artificial-intelligence deep-learning python segment-anything clip open-vocabulary image-segmentation zero-shot-recognition eccv-2024 knowledge-distillation rwkv research-code linux gpu

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