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:
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
Release files for pystem 0.0.26
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| pystem-0.0.26.tar.gz | 35.5 kB | Details |
Release files / pystem-0.0.26.tar.gz
| Download URL | pystem-0.0.26.tar.gz |
|---|---|
| Size | 35.5 kB |
| Tags | Source |
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SHA-256 checksum How to use checksums |
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BLAKE2b-256 checksum How to use checksums |
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Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/3.3.0 pkginfo/1.5.0.1 requests/2.24.0 setuptools/49.2.0.post20200714 requests-toolbelt/0.9.1 tqdm/4.47.0 CPython/3.8.3
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