theia
:construction: This project is in beta!
Cut out houses from satellite imagery.
Table of Contents
Getting Started
These instructions will get you a copy of the project up and running on your local machine for development and testing purposes.
If you would just like to play around with the model without downloading anything to your machine, you can open this notebook in Google Colab (Note that a Google account is required to run the notebook): Open in Google Colab
Prerequisites
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/
To be able to view und run the example notebooks on your machine, jupyter is required. An installation guide can be found on their website: https://jupyter.org/install
Initial setup
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/aquila.git
git clone https://github.com/intelligenerator/aquila.git
cd aquila/
cd aquila/
git submodule init
git submodule init
git config submodule.recurse true
git config submodule.recurse true
git submodule update
git submodule update --init --recursive
Next, Download the xView2 dataset into the data/
folder.
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!
Running the notebook
To run the provided notebook on your machine, make sure you have jupyter installed.
First, create a jupyter kernel for your conda environment:
pip install --user ipykernel
python -m ipykernel install --user --name=torch
Then, open jupyter lab:
jupyter lab
Important: Make sure you use the kernel you created above. After opening the notebook, navigate to
Kernel
>Change Kernel...
in the UI and selecttorch
from the dropdown. See this blog post for more info: https://janakiev.com/blog/jupyter-virtual-envs/
Contributing
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.
Versioning
We use SemVer for versioning. For the versions available, see the tags on this repository.
Authors
The Intelligenerator Group - intelligenerator
See also the list of contributors who participated in this project.
License
This project is licensed under the MIT License - see the LICENSE.md file for details.
Acknowledgments
- U-Net: Convolutional Networks for Biomedical Image Segmentation - Initial research paper
- numpy gitignore - Gitignore inspiration
- github python gitignore template - The gitignore template
- python3 tutorial - Guide and explanations
- Contributor Covenant - Code of Conduct