Metadata-Version: 2.1
Name: alzheimer_classification
Version: 0.1.0
Summary: Detecting the stage of Alzheimer's based on MRI images.
Author: s24575
Author-email: sawickigrzegorz66@gmail.com
Requires-Python: >=3.11.6,<4.0.0
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.12
Requires-Dist: matplotlib (>=3.9.0,<4.0.0)
Requires-Dist: numpy (<2.0.0)
Requires-Dist: pre-commit (>=3.7.1,<4.0.0)
Requires-Dist: pytorch-lightning (>=2.3.1,<3.0.0)
Requires-Dist: tensorboard (>=2.17.0,<3.0.0)
Requires-Dist: torch (>=2.3.1,<3.0.0)
Requires-Dist: torchvision (>=0.18.1,<0.19.0)
Description-Content-Type: text/markdown

# Stage of Alzheimer's classification.

The purpose of this project is to detect the stage of Alzheimer's based on MRI images.

### Dataset

The models are designed to be trained on [Alzheimer's Dataset ( 4 class of Images)](https://www.kaggle.com/datasets/tourist55/alzheimers-dataset-4-class-of-images) from Kaggle.

### Requirements
* Python 3.11+
* Poetry

### Training a Model

To train a model, run:

    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.

### Predicting with a Model

To predict using a trained model, run:

    python predict.py -m vgg16 -f model_filename -i path_to_image
        -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.

