luca-medeiros/lang-segment-anything

Health v2 · maintenance only

Adoption not part of the score

2598 stars · 300 forks observed · 2026-08-28

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

A Python library combining Meta's Segment Anything Model 2 with GroundingDINO to generate segmentation masks for objects in images specified via free-form text prompts. It supports zero-shot text-to-bbox detection, batch inference, and deployment as an API endpoint.

Use cases

• segment specific objects in an image using a text prompt
• zero-shot object detection with bounding boxes from text descriptions
• generate masks for objects like 'wheel' or 'person' in photos
• batch image segmentation with custom text prompts
• deploy a text-prompted segmentation model as an API endpoint
• annotate images for computer vision datasets

When to choose

• you need to segment objects by name without training a custom model
• you want zero-shot detection and segmentation in one pipeline
• you need batch inference or a ready-made serving endpoint
• you want a simple Python API on top of SAM 2 and GroundingDINO

When to avoid

• you need real-time segmentation on CPU-constrained hardware
• you require fine-grained class labels beyond text-prompt grounding
• you cannot download large model checkpoints or lack a GPU
• you need a lightweight pure-detection model without masks

Facets

library · maturity active

computer-vision image-processing machine-learning deep-learning computer-vision image-processing artificial-intelligence machine-learning python cross-platform segment-anything grounding-dino zero-shot-detection instance-segmentation text-prompt sam2 object-detection gradio docker gpu

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