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diffusion_reconstruction_results

Results of "Conditional diffusion-based microstructure reconstruction"

https://github.com/choropent/diffusion_reconstruction_results

Science Score: 67.0%

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Repository

Results of "Conditional diffusion-based microstructure reconstruction"

Basic Info
  • Host: GitHub
  • Owner: choROPeNt
  • License: mit
  • Language: Python
  • Default Branch: main
  • Size: 1.47 MB
Statistics
  • Stars: 4
  • Watchers: 1
  • Forks: 0
  • Open Issues: 0
  • Releases: 0
Created over 3 years ago · Last pushed almost 3 years ago
Metadata Files
Readme License Citation

README.md

arXiv DOI:10.1016/j.mtcomm.2023.105608

Results of "Conditional diffusion-based microstructure reconstruction"

This repository contains all samples generated in the paper "Conditional diffusion-based microstructure reconstruction". For training and sampling of the conditional diffusion models the implementation of OpenAI improved-difusion and "Improved Denoising Diffusion Probabilistic Models" was used, respectively.

The following READDME.md contains the instructions to vizualize the generated samples. The samples are stored as *.npz containing 64 samples the size 256x256x3 [h,w,c] for each class and correspdoning model introduced in "Conditional diffusion-based microstructure reconstruction".

Prerequisites

  • Python3

Requirements

  • numpy >= 1.22.3
  • pillow >= 9.1.0
  • matplotlib >= 3.5.2

to install all necessary packages and their dependencies please run python -m pip install -r requirements.txt sometimes you may run python3 -m pip install -r requirements.txt

Usage

Just to vizualize the sampled microstructures you can set only the --file=<path-to-file> argument: python vizualize_samples.py --file=<path-to-file> This is the expected outpt as a matplotlib figure:

If you want to save the samples in ´*.tif´ imagefile format you have to specify the output directory with the argument --dir=<path-to-save-images>:

python vizualize_samples.py --file=<path-to-file> --dir=<path-to-save-images>

examples

The following table shows selected images from the coresponding sample files and class, respectively.

| class | sample file | example image | |----------|:-------------:|------:| | martensite | samples_martensite_64x256x256x3.npz | | | biological | samples_biological_64x256x256x3.npz | | | FVC60 | samples_FVC60_64x256x256x3.npz | |

Owner

  • Name: Christian Düreth
  • Login: choROPeNt
  • Kind: user
  • Location: Dresden
  • Company: TU Dresden

research associate | composite | mechanical enginnering | machine learrning | computer vision

Citation (CITATION.cff) 

# This CITATION.cff file was generated with cffinit.
# Visit https://bit.ly/cffinit to generate yours today!

cff-version: 1.2.0
title: >-
  Results of "Conditional diffusion-based microstructure
  reconstruction"
message: >-
  If you use this dataset, please cite it using the metadata
  from this file.
type: dataset
authors:
  - given-names: Christian
    family-names: Düreth
    email: christain.duereth@tu-dresden.de
    orcid: 'https://orcid.org/0000-0002-6817-1020'
    affiliation: >-
      TU Dresden - Institute of Lightweight Engineering and
      Polymer Technology
  - given-names: Paul
    family-names: Seibert
    email: paul.seibert@tu-dresden.de
    affiliation: TU Dresden - Institute of Solid Mechanics
    orcid: 'https://orcid.org/0000-0002-8774-8462'
  - given-names: Dennis
    family-names: Rücker
    email: dennis.ruecker@mailbox.tu-dresden.de
    affiliation: TU Dresden - Institute of Solid Mechanics
  - given-names: Stephanie
    family-names: Handford
    email: stephanie.handford@mailbox.tu-dresden.de
    affiliation: University of Mississippi
  - given-names: Markus
    family-names: Kästner
    email: markus.kaestner@tu-dresden.de
    affiliation: TU Dresden - Institute of Solid Mechanics
    orcid: 'https://orcid.org/0000-0003-3358-1545'
  - given-names: Maik
    family-names: Gude
    orcid: 'https://orcid.org/0000-0003-1370-064X'
    email: maik.gude@tu-dresden.de
    affiliation: >-
      TU Dresden - Institute of Lightweight Engineering and
      Polymer Technology
identifiers:
  - type: doi
    value: 10.48550/arXiv.2211.13497
    description: >-
      Conditional diffusion-based microstructure
      reconstruction
repository-code: >-
  https://github.com/choROPeNt/diffusion_reconstruction_results
license: MIT

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Dependencies

requirements.txt pypi
  • matplotlib >=3.5.2git
  • numpy >=1.22.3
  • pillow >=9.1.0