segment-anything-model
Foundation model for image segmentation with zero-shot transfer. Use when you need to segment any object in images using points, boxes, or masks as prompts, or automatically generate all object masks in an image.
npx skills add Orchestra-Research/AI-Research-SKILLs --skill segment-anything --agent claude-code
Same command for any agent — swap --agent for codex, cursor, copilot.
Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.
# Segment Anything Model (SAM) Comprehensive guide to using Meta AI's Segment Anything Model for zero-shot image segmentation. ## When to use SAM **Use SAM when:** - Need to segment any object in images without task-specific training - Building interactive annotation tools with point/box prompts - Generating training data for other vision models - Need zero-shot transfer to new image domains - Building object detection/segmentation pipelines - Processing medical, satellite, or domain-specific images **Key features:** - **Zero-shot segmentation**: Works on any image domain without fine-tuning - **Flexible prompts**: Points, bounding boxes, or previous masks - **Automatic segmentation**: Generate all object masks automatically - **High quality**: Trained on 1.1 billion masks from 11 million images - **Multiple model sizes**: ViT-B (fastest), ViT-L, ViT-H (most accurate) - **ONNX export**: Deploy in browsers and edge devices **Use alternatives instead:** - **YOLO/Detectron2**: For real-time object detection with classes - **Mask2Former**: For semantic/panoptic segmentation with categories - **GroundingDINO + SAM**: For text-prompted segmentation - **SAM 2**: For video segmentation tas
- When to use SAM
- Quick start
- Installation
- Download checkpoints
- Basic usage with SamPredictor
- HuggingFace Transformers
- Core concepts
- Model architecture
- Model variants
- Prompt types
- Interactive segmentation
- Point prompts
- Box prompts
- Combined prompts
From GitHub pip install git+https://github.com/facebookresearch/segment-anything.git Optional dependencies pip install opencv-python pycocotools matplotlib Or use HuggingFace transformers pip install transformers ViT-H (largest, most accurate) - 2.4GB wget https://dl.fbaipublicfiles.com/segment_anything/sam_vit_h_4b8939.pth ViT-L (medium) - 1.2GB wget https://dl.fbaipublicfiles.com/segment_anything/sam_vit_l_0b3195.pth
What does the segment-anything-model skill do?
Foundation model for image segmentation with zero-shot transfer. Use when you need to segment any object in images using points, boxes, or masks as prompts, or automatically generate all object masks in an image.
How do I install it?
Run `npx skills add Orchestra-Research/AI-Research-SKILLs --skill segment-anything --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.
Where does this skill come from?
From Orchestra-Research/AI-Research-SKILLs, a repository with 11,391 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.
Is a popular skill a good skill?
Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.