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sam2-segmentation

Segment objects in video frames using click points and Segment Anything 2 models.

3.0k|463|Updated Mar 5, 2019
Search Tags:#computer vision#segmentation#image analysis#annotation#masking#sam2
One-click install
npx skills add https://github.com/SharpAI/DeepCamera --skill sam2-segmentation
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: sam2-segmentation
Source: https://github.com/SharpAI/DeepCamera/tree/main/skills/analysis/sam2-segmentation
Command: npx skills add https://github.com/SharpAI/DeepCamera --skill sam2-segmentation

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires segment-anything-2, torch, torchvision, numpy, opencv-python-headless, Pillow, and includes scripts (resource) and references (resource) components.

What problem does it solve?

This Skill allows users to interactively segment objects within video frames by simply clicking on them, simplifying complex annotation and analysis tasks.

Core Features & Use Cases

  • Click-to-segment: Generate precise masks for any object by clicking on it.
  • Video Propagation: Track segmented objects across multiple frames.
  • Annotation Export: Export masks in COCO format for dataset creation.
  • Background Removal: Isolate objects from their backgrounds.
  • Use Case: Quickly create masks for specific individuals or objects in surveillance footage for tracking or analysis.

Quick Start

Use the sam2-segmentation skill to segment the object at coordinates x=450, y=320 in the current frame.

Frequently Asked Questions about sam2-segmentation

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I perform interactive image segmentation using click points?▼

Video propagation tracking across multiple frames is supported by Segment Anything 2. This Skill extends object masking from a single click point to track segmented objects throughout subsequent video frames automatically.

Can I export segmentation masks in COCO format for dataset annotation?▼

Segmentation masks can be exported in COCO format for dataset annotation. This Skill generates precise object masks from click points and structures the output for immediate use in dataset creation and annotation tasks.

What dependencies do I need to run Segment Anything 2 for object masking?▼

To run Segment Anything 2 for object masking, you need PyTorch, OpenCV, and the segment-anything-2 library. Additional dependencies include torchvision, numpy, and Pillow for model inference and image processing.

How do I remove backgrounds from video frames using PyTorch and OpenCV?▼

Background removal from video frames using PyTorch and OpenCV is achieved by isolating segmented objects. This Skill leverages Segment Anything 2 to generate precise masks, allowing you to separate targeted objects from their backgrounds.

Are there limitations when using segment-anything-2 for surveillance footage analysis?▼

Surveillance footage analysis with segment-anything-2 requires clear click points for initial object masking. While video propagation tracks objects across frames, performance depends on PyTorch model inference capabilities and visual clarity within the footage.

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