Assess damage of buildings.
These instructions will get you a copy of the project up and running on your local machine for development and testing purposes.
You will need python3 and pip3 installed on your machine. You can install it from the official website https://www.python.org/.
To install pytorch with CUDA support, conda is recommended. An installation guide is available in the conda docs: https://docs.conda.io/projects/conda/en/latest/user-guide/install/
A step by step series of examples that tell you how to get the project up and running.
Clone the git repository
git clone https://github.com/intelligenerator/perses.git
cd perses
git submodule init
git config submodule.recurse true
git submodule update --init --recursive
Then create your conda virtual environment
conda create --name torch
conda activate torch
Next, installed the required packages. This may vary based on your system hardware and requirements. Read more about pytorch installation: https://pytorch.org/get-started/locally/
conda install pytorch torchvision cudatoolkit=10.2 -c pytorch
To exit the virtual environment run
conda deactivate
Happy coding!
Open the dnet.ipynb notebook in jupyter lab to start experimenting or to train your own model.
Perses comes with an explainable AI notebook. This notebook uses Captum to interpret the perses model.
To run the notebook and inspect the model behind perses, you must first install captum in your conda environment. See the captum docs for more information.
conda activate torch
conda install captum -c pytorch
You can now open the notebook in jupyter lab to interpret perses!
Please read CONTRIBUTING.md and CODE_OF_CONDUCT.md for details on our code of conduct, and the process for submitting pull requests to us.
We use SemVer for versioning. For the versions available, see the tags on this repository.
Boldizsar Zopcsak - BoldizsarZopcsak
See also the list of contributors who participated in this project.
This project is licensed under the MIT License - see the LICENSE.md file for details.
- DEVELOPING CUSTOM PYTORCH DATALOADERS
- Contributor Covenant - Code of Conduct
- Captum - Model Interpretability for PyTorch