A convolutional neural network designed to detect lung lesions in chest radiographs. Read the writeup for a more in-depth explanation!
Warning: this project relies on being on an Intel system with GPUs that have CUDA support!
You will need to install Poetry if you do not already have it. Follow the instructions here to get it.
From there, you can run poetry install to install the needed dependencies. Then, run poetry shell to enter a virtual environment.
You'll need a copy of the CheXpert dataset, which can be obtained here.
After that, you can run preprocess.py like so:
python preprocess.py <path-to-train-csv>
This will generate a file called all.csv within the current directory. To begin training the model you can now run the following command:
python main.py ./all.csv <path-to-data-folder>
For an example: I installed CheXpert to ~/aux, so that's what I would put as my data folder.
You can run tests for nescient by running tox -e ALL. This will run pytest to run tests, interrogate to checks the documentation coverage, and mypy to do type checking.
If you're in the mood for some experimentation, nescient also installs py-spy as a dev dependency for profiling information.
You can generate documentation for nescient by running pdoc nescient.