# ShawnBIT/UNet-family

Paper and implementation of UNet-related model.

Repository: https://github.com/ShawnBIT/UNet-family
Canonical: https://ross.abutalabs.com/products/unet-family
Language: Python
License Family: other
Topics: segmentation, unet, pytorch
Last push: 2020-05-21T15:16:05+00:00

## Health v2 (maintenance only)
Score: 32/100 (v2, computed 2026-09-02T17:46:02.011165+00:00)
- activity 0, release rhythm 35, longevity 100
- inputs: {"age_days": 2812, "days_push": 2295, "days_rel": null, "gap_med": null, "n_releases_24m": 0}
- flags: no_releases, no_license
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 2592, forks 499 (observed 2026-08-28T04:07:02.984156+00:00)

## What it is
A curated collection of UNet-family semantic segmentation models with PyTorch implementations and links to original papers and third-party code. It focuses on medical image segmentation architectures like UNet, V-Net, 3D U-Net, and UNet++.

## Use cases
- segment medical images with unet
- implement unet++ in pytorch
- compare unet variants for semantic segmentation
- find papers and code for medical image segmentation models
- train a 3d unet on volumetric data
- get a starting point for biomedical image segmentation

## When to choose
- you need reference PyTorch implementations of UNet and its variants
- you want a survey of UNet-family papers with linked code
- you are doing medical or biomedical image segmentation research

## When to avoid
- you need a production-ready, maintained segmentation framework
- you require a licensed library for commercial use (no license is provided)
- you need segmentation architectures beyond the UNet family

## Facets
- artifact type: library
- maturity: maintenance
- function: machine-learning, deep-learning, image-processing, computer-vision
- domain: deep-learning, computer-vision, healthcare, image-processing
- platform: python
- tags: unet, semantic-segmentation, medical-imaging, pytorch, model-zoo, paper-collection

## Member repositories
- ShawnBIT/UNet-family (main) score 32

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:07:02.984156+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 2026-08-30T02:22:17.350472+00:00, confidence not recorded.
  - readme: https://github.com/ShawnBIT/UNet-family (fetched 2026-08-28T04:07:02.984156+00:00, sha 0951900ac347)
- Data as of 2026-08-30T08:39:29.467469+00:00.