The purpose of this project is to detect the stage of Alzheimer's based on MRI images.
The models are designed to be trained on Alzheimer's Dataset ( 4 class of Images) from Kaggle. It has already been downloaded and is available in the dataset/ directory.
- Python 3.9+
- Poetry
poetry install
python train.py -m vgg16 -f model_filename
-m/--model_name: Name of the model to train (vgg16 or cnn).
-f/--filename: Filename to save the trained model.
python predict.py -m vgg16 -f model_filename -i ../dataset/test/ModerateDemented/27.jpg
-m/--model_name: Name of the model to use for prediction (vgg16 or cnn).
-f/--filename: Filename of the trained model.
-i/--image_path: Path to the image file to predict.
To view all metrics collected during model training, run:
tensorboard --logdir ../lightning_logs
Install pre-commits https://pre-commit.com/#installation
If you are using VS-code install the extension https://marketplace.visualstudio.com/items?itemName=MarkLarah.pre-commit-vscode
To make a dry-run of the pre-commits, to see if your code passes, run:
pre-commit run --all-files
Dependencies are handled by poetry
framework, to add new a new dependency, run:
poetry add <package_name>