shiv2398/Detection-of-Alzheimer-Disease-

Alzheimer Detection using Deep Learning 🧠💻

Table of Contents

1. Introduction
2. Train the Model
   • Command
   • Arguments
   • Data Paths
   • Validation
   • Imbalanced Data
   • Example
3. Test the Model
   • Command
   • Arguments
   • Example
4. Model Testing
   • Command
   • Arguments
   • Example

Introduction

This project focuses on Alzheimer detection using deep learning techniques. The provided CLI (Command-Line Interface) allows you to train, test, and perform model testing with ease.

Train the Model

Command

python main.py train --train_data_path <train_data_path> --Epochs <num_epochs> --model <model_name> --test_data_path <test_data_path> [--val_exp] [--val_data_path <val_data_path>] [--biased]

Arguments

• --train_data_path: Path to the training data.
• --Epochs: Number of training epochs.
• --model: Specify the model architecture.
• --test_data_path: Path to the test data.

Data Paths

• Ensure that the provided data paths exist.

Validation

• Use --val_exp to indicate the use of explicit validation data.
• If --val_exp is provided, include --val_data_path with the validation data path.

Imbalanced Data

• Include --biased if the data is imbalanced.

Example

python main.py train --train_data_path data/train_data --Epochs 50 --model CNN_model --test_data_path data/test_data --val_exp --val_data_path data/val_data --biased

Test the Model

Command

python main.py test --model <model_name> --test_data_path <test_data_path> --model_path <model_path>

Arguments

• --model: Specify the model architecture.
• --test_data_path: Path to the test data.
• --model_path: Path to the saved model.

Example

python main.py test --model CNN_model --test_data_path data/test_data --model_path saved_models/CNN_model_epoch_50.h5

Model Testing

Command

python main.py model_testing --model <model_name> --test_data_path <test_data_path> --model_path <model_path>

Arguments

• --model: Specify the model architecture.
• --test_data_path: Path to the test data.
• --model_path: Path to the saved model.

Example

python main.py model_testing --model CNN_model --test_data_path data/test_data --model_path saved_models/CNN_model_epoch_50.h5