# yatengLG/ISAT_with_segment_anything

Labeling tool with SAM(segment anything model),supports SAM, SAM2, SAM3, sam-hq, MobileSAM EdgeSAM etc.交互式半自动图像标注工具

Repository: https://github.com/yatengLG/ISAT_with_segment_anything
Canonical: https://ross.abutalabs.com/products/isat_with_segment_anything
Language: Python
License: NOASSERTION
License Family: other
Topics: annotation-tool, computer-vision, labeling-tool, segment-anything, labeling, segment-anything-2, sam, sam2, video-segmentation, sam3, text-prompt
Last push: 2026-08-18T00:43:07+00:00

## Health v2 (maintenance only)
Score: 84/100 (v2, computed 2026-09-03T02:20:16.233290+00:00)
- activity 98, release rhythm 63, longevity 88
- inputs: {"age_days": 1233, "days_push": 16, "days_rel": 245, "gap_med": 13, "n_releases_24m": 30}
- flags: no_license
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 2166, forks 212 (observed 2026-08-28T04:06:21.368849+00:00)

## What it is
ISAT_with_segment_anything is an interactive semi-automatic image annotation tool built on the Segment Anything Model family (SAM, SAM2, SAM3, sam-hq, MobileSAM, EdgeSAM). It supports point, box, text, and visual prompts for fast segmentation labeling, plus a plugin system for extending functionality.

## Use cases
- annotate images for semantic segmentation datasets
- create segmentation masks with SAM click prompts
- label objects in images using text prompts
- annotate video frames for segmentation
- export masks for training computer vision models
- auto-annotate images with YOLO models

## When to choose
- you need fast semi-automatic segmentation labels for training data
- you want a GUI annotation tool leveraging SAM-family models
- you need text or visual prompt based labeling with SAM3
- you want an extensible annotation tool with plugins

## When to avoid
- you only need bounding-box annotation for detection tasks
- you need a web-based collaborative annotation platform for teams
- you lack a GPU or the resources to run SAM models locally

## Facets
- artifact type: application
- maturity: active
- function: image-processing, computer-vision, machine-learning, gui, plugin-system
- domain: computer-vision, image-processing, machine-learning, artificial-intelligence, developer-tools
- platform: python, cross-platform
- tags: segment-anything, image-annotation, labeling-tool, sam, sam2, sam3, semantic-segmentation, video-segmentation, semi-automatic-annotation, desktop

## Member repositories
- yatengLG/ISAT_with_segment_anything (main) score 84

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:06:21.368849+00:00.
- Health v2: computed from the inputs above; adoption is never an input.
- Inferred fields (summary, facets, guidance): AI-extracted, prompt v1, taxonomy v1, on 2026-08-30T02:49:57.937727+00:00, confidence not recorded.
  - readme: https://github.com/yatengLG/ISAT_with_segment_anything (fetched 2026-08-28T04:06:21.368849+00:00, sha df966c0aa75c)
- Data as of 2026-08-30T08:39:29.467469+00:00.