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Atomvision is a deep learning framework for atomistic image data.



First create a conda environment: Install miniconda environment from Based on your system requirements, you'll get a file something like 'Miniconda3-latest-XYZ'.


bash (for linux)
bash (for Mac)

Download 32/64 bit python 3.6 miniconda exe and install (for windows) Now, let's make a conda environment, say "version", choose other name as you like::

conda create --name vision python=3.8
source activate vision

Now, let's install the package:

Method 1 (using

git clone
cd atomvision
python develop

Method 2 (using pypi):

As an alternate method, AtomVision can also be installed using pip command as follows:

pip install atomvision


Generating STEM image with convolution approximation: graphene example --file_path atomvision/tests/POSCAR --output_path STEM.png

2D-Bravais lattice classification example

This example shows how to classify 2D-lattice (5 Bravais classes) for 2D-materials STM/STEM images.

We will use imagessample_data folder. It was generated with script. There are two folders train_folder, test_folder with sub-folders 0,1,2,3,4,... for individual classes and they contain images for these classes. --model densenet --train_folder atomvision/sample_data/test_folder --test_folder atomvision/sample_data/test_folder --epochs 5 --batch_size 16

Generating a t-SNE plot --data_dir atomvision/sample_data/test_folder

Generative Adversarial Network --dataset_path atomvision/sample_data/test_folder/0 --epochs 2

Autoencoder --train_folder atomvision/sample_data/test_folder --test_folder atomvision/sample_data/test_folder --epochs 10


  1. AtomVision: A machine vision library for atomistic images

  2. The joint automated repository for various integrated simulations (JARVIS) for data-driven materials design

  3. Computational scanning tunneling microscope image database

Please see detailed publications list here.

How to contribute

For detailed instructions, please see Contribution instructions


Please report bugs as Github issues ( or email to

Funding support


Code of conduct

Please see Code of conduct

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