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wiste

https://github.com/dongh-1106/wiste

Science Score: 44.0%

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    Low similarity (6.2%) to scientific vocabulary
Last synced: 10 months ago · JSON representation ·

Repository

Basic Info
  • Host: GitHub
  • Owner: dongh-1106
  • License: apache-2.0
  • Language: Python
  • Default Branch: main
  • Size: 8.48 MB
Statistics
  • Stars: 3
  • Watchers: 1
  • Forks: 1
  • Open Issues: 0
  • Releases: 0
Created about 3 years ago · Last pushed over 2 years ago
Metadata Files
Readme License Citation

README.md

WISTE

This is the code for paper "Water Index Swin Transformer Ensemble (WISTE) for Water Body Extraction from Multispectral Remote Sensing Image"

This code is based on Swin Transformer.

Installation

Please refer to MMSegmentation for installation and dataset preparation.

Inference

```

single-gpu testing

python tools/test.py --eval mIoU

multi-gpu testing

tools/disttest.sh <CONFIGFILE> --eval mIoU

multi-gpu, multi-scale testing

tools/disttest.sh <CONFIGFILE> --aug-test --eval mIoU ```

Pretrained model

Pretrained model can be download here: pretrained model

WISTE model

WISTE model can be download by BaiduNetdisk.,extraction code is [covf]

Training

To train with pre-trained models, run: ```

single-gpu training

python tools/train.py --options model.pretrained= [model.backbone.use_checkpoint=True] [other optional arguments]

multi-gpu training

tools/disttrain.sh <CONFIGFILE> --options model.pretrained= [model.backbone.use_checkpoint=True] [other optional arguments] ```

PME

To use PME module, please run: python ./pme.py

Owner

  • Login: dongh-1106
  • Kind: user

Citation (CITATION.cff) 

cff-version: 1.2.0
message: "If you use this software, please cite it as below."
authors:
  - name: "MMSegmentation Contributors"
title: "OpenMMLab Semantic Segmentation Toolbox and Benchmark"
date-released: 2020-07-10
url: "https://github.com/open-mmlab/mmsegmentation"
license: Apache-2.0

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Dependencies

requirements/docs.txt pypi
  • docutils ==0.16.0
  • myst-parser *
  • sphinx ==4.0.2
  • sphinx_copybutton *
  • sphinx_markdown_tables *
requirements/mminstall.txt pypi
  • mmcls >=0.20.1
  • mmcv-full >=1.4.4,<=1.6.0
requirements/optional.txt pypi
  • cityscapesscripts *
requirements/readthedocs.txt pypi
  • mmcv *
  • prettytable *
  • torch *
  • torchvision *
requirements/runtime.txt pypi
  • matplotlib *
  • mmcls >=0.20.1
  • numpy *
  • packaging *
  • prettytable *
requirements/tests.txt pypi
  • codecov * test
  • flake8 * test
  • interrogate * test
  • pytest * test
  • xdoctest >=0.10.0 test
  • yapf * test
requirements.txt pypi
setup.py pypi