Skip to main content

A python module for segmentation of STEM images

Project description

Automatic segmentation of STEM images

Automatic segmentation of Scanning Transmission Electron Microscope (STEM) images with unsupervised machine learning

Learning more

If you want to learn more about this project, you may read our manuscript that is not yet completely finished, or our presentation for BiGmax workshop 2020.

Try it now: Binder

Getting Started

Prerequisites

python 3, numpy, scipy, scikit-learn, fftw3

Installing

via conda, the simplest way, highly recommended

conda install -c conda-forge pystem

via pip

1. First make sure that FFTW3 library is installed 
2. pip install pystem

via source code

1. First make sure that FFTW3 library is installed 
then type commands:
git clone https://github.com/NingWang1990/pySTEM.git
cd pySTEM
python setup.py build
python setup.py install --user

How to use

Examples can be found in the examples folder Give it a try right now by simply clicking the 'launch binder' button

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Files for pystem, version 0.0.25
Filename, size File type Python version Upload date Hashes
Filename, size pystem-0.0.25.tar.gz (35.2 kB) File type Source Python version None Upload date Hashes View

Supported by

AWS AWS Cloud computing Datadog Datadog Monitoring DigiCert DigiCert EV certificate Facebook / Instagram Facebook / Instagram PSF Sponsor Fastly Fastly CDN Google Google Object Storage and Download Analytics Pingdom Pingdom Monitoring Salesforce Salesforce PSF Sponsor Sentry Sentry Error logging StatusPage StatusPage Status page