The repository contains the code for the article "Towards Totally Defined Nanocatalysis: Deep Learning Reveals the Extraordinary Activity of Single Pd/C Particles" by Dmitry B. Eremin, Alexey S. Galushko, Daniil A. Boiko, Evgeniy O. Pentsak, Igor V. Chistyakov, and Valentine P. Ananikov
- tdnc/ — a Python module, which contains useful functions and classes for training segmentation models for SEM image analysis
- configs/ — task-specific configuration files, allowing to reproduce the models
- train.py — the segmentation model training script
- inference.py – the code to perform inference of the models
- configs/augmentations/ – augmentations, specific for each material
All models can be retrained with the following command
for f in configs/*.yaml; do python train.py --config $f; doneThe training was performed on a single NVIDIA 1080 TI.
