# bubbliiiing/unet-pytorch

这是一个unet-pytorch的源码，可以训练自己的模型

Repository: https://github.com/bubbliiiing/unet-pytorch
Canonical: https://ross.abutalabs.com/products/unet-pytorch
Language: Python
License: MIT
License Family: permissive
Last push: 2024-05-17T16:05:11+00:00

## Health v2 (maintenance only)
Score: 23/100 (v2, computed 2026-09-03T02:20:16.233290+00:00)
- activity 0, release rhythm 8, longevity 100
- inputs: {"age_days": 2001, "days_push": 838, "days_rel": null, "gap_med": null, "n_releases_24m": 0}
- flags: none
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 1725, forks 285 (observed 2026-08-28T04:05:28.080718+00:00)

## What it is
A PyTorch implementation of the U-Net semantic segmentation model with training, prediction, and mIoU evaluation scripts. It supports multiple backbones (VGG, ResNet50) and lets users train custom models on their own VOC-format or medical imaging datasets.

## Use cases
- train a custom image segmentation model on my own dataset
- segment medical images with unet
- run semantic segmentation inference with pretrained weights
- evaluate segmentation models with miou
- learn how unet works in pytorch
- fine-tune unet with vgg or resnet backbone

## When to choose
- you need a well-commented, educational U-Net implementation in PyTorch
- you want to train segmentation on VOC-format or medical datasets
- you need pretrained weights and simple train/predict scripts

## When to avoid
- you need state-of-the-art segmentation accuracy on complex datasets like VOC
- you want a production-ready segmentation service rather than training scripts
- you need models other than U-Net or non-PyTorch frameworks

## Facets
- artifact type: library
- maturity: maintenance
- function: machine-learning, deep-learning, image-processing, computer-vision
- domain: deep-learning, computer-vision, image-processing, machine-learning
- platform: python
- tags: unet, semantic-segmentation, pytorch, image-segmentation, model-training, pretrained-weights

## Member repositories
- bubbliiiing/unet-pytorch (main) score 23

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:05:28.080718+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 2026-08-30T03:32:35.050050+00:00, confidence not recorded.
  - readme: https://github.com/bubbliiiing/unet-pytorch (fetched 2026-08-28T04:05:28.080718+00:00, sha 176bffa29597)
- Data as of 2026-08-30T08:39:29.467469+00:00.