# bigmb/Unet-Segmentation-Pytorch-Nest-of-Unets

Implementation of different kinds of Unet Models for Image Segmentation - Unet , RCNN-Unet, Attention Unet, RCNN-Attention Unet, Nested Unet

Repository: https://github.com/bigmb/Unet-Segmentation-Pytorch-Nest-of-Unets
Canonical: https://ross.abutalabs.com/products/unet-segmentation-pytorch-nest-of-unets
Language: Python
License: MIT
License Family: permissive
Topics: unet, pytorch, imagesegmentation, segmentation, tensorvision, torchvision, torch, python3
Last push: 2022-11-28T17:44:40+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": 2668, "days_push": 1374, "days_rel": null, "gap_med": null, "n_releases_24m": 0}
- flags: no_releases
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 2249, forks 365 (observed 2026-08-28T04:06:30.319406+00:00)

## What it is
A PyTorch implementation of several U-Net variants for image segmentation, including UNet, R2U-Net, Attention U-Net, Attention R2U-Net, and Nested UNet (UNet++). It includes training scripts, Dice score evaluation, and layer visualization utilities.

## Use cases
- segment medical images with unet models in pytorch
- compare unet, attention unet, and nested unet architectures
- train a segmentation model on my own image dataset
- implement unet++ for image segmentation
- compute dice score for segmentation predictions

## When to choose
- you want ready-to-run PyTorch code for multiple U-Net variants in one place
- you are doing research or learning about segmentation architectures like Attention U-Net or UNet++
- you work on medical or biomedical image segmentation tasks

## When to avoid
- you need a production-grade, pip-installable segmentation library with an API
- you require models beyond the U-Net family or modern architectures like transformers
- you need actively maintained code with recent updates and community support

## Facets
- artifact type: library
- maturity: maintenance
- function: machine-learning, deep-learning, image-processing, computer-vision
- domain: deep-learning, computer-vision, image-processing, healthcare
- platform: python, cross-platform
- tags: unet, semantic-segmentation, pytorch, attention-unet, nested-unet, medical-imaging, research-code, gpu

## Member repositories
- bigmb/Unet-Segmentation-Pytorch-Nest-of-Unets (main) score 32

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:06:30.319406+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 2026-08-30T02:43:54.282625+00:00, confidence not recorded.
  - readme: https://github.com/bigmb/Unet-Segmentation-Pytorch-Nest-of-Unets (fetched 2026-08-28T04:06:30.319406+00:00, sha 44c685cd0917)
- Data as of 2026-08-30T08:39:29.467469+00:00.