https://github.com/imperialcollegelondon/ipwgan
Science Score: 26.0%
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Low similarity (5.4%) to scientific vocabulary
Repository
Basic Info
- Host: GitHub
- Owner: ImperialCollegeLondon
- Language: Python
- Default Branch: main
- Size: 170 KB
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- Stars: 7
- Watchers: 2
- Forks: 1
- Open Issues: 0
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Metadata Files
README.md
IPWGAN
Here is a Code of IPWGAN- Improved Pymarid Wasserstein Generative Adversarial Network
IPWGAN, Improved Pyramid Wasserstein Generative Adversarial Network, use to generate complex porous media.
Features
- Feature 1: add pyramid structure generator to capture multiscale characterization
- Feature 2: add Feature Statistics Mixing Regularization to control the process of training
- Feature 3: add -LP to control training process.
Usage
Create dataset: python createtrainingimagess.py --image D:\fw3L.tif --name fw3r --target_dir I:\wet255128
Training: python mainWGANFPN.py --dataset 3D --dataroot SAV --imageSize 128 --batchSize 8 --ngf 64 --ndf 16 --nz 512 --niter 1600 --lr 0.00005 --ngpu 1 –cuda
Generation: python generatorWFPNM.py --imageSize 128 --ngf 64 --ndf 16 --nz 512 --netG SAVInetGepochtrain500ppp.pth --experiment nb --imsize 8 –cuda
Paper
Cite as: Linqi Zhu, Branko Bijeljic, Martin Julian Blunt. Generation of Heterogeneous Pore-Space Images Using Improved Pyramid Wasserstein Generative Adversarial Networks. ESS Open Archive . December 03, 2023. DOI: 10.22541/essoar.170158343.30188169/v1
Owner
- Name: Imperial College London
- Login: ImperialCollegeLondon
- Kind: organization
- Email: icgithub-support@imperial.ac.uk
- Location: Imperial College London
- Repositories: 311
- Profile: https://github.com/ImperialCollegeLondon
Imperial College main code repository
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