CheXNet Replica

This project implements a replica of the CheXNet model, a convolutional neural network trained for detecting various lung conditions from X-ray images, following the implementation presented here.

Project Description

The train.py script contains the implementation of the CheXNet model and its training. The model is trained using X-ray image data and corresponding labels for 14 classes of lung conditions.

Project Structure

• train.py: Main script that includes the model definition, training functions, and evaluation.
• split/: Directory containing the split of data into training, validation, and test sets.
• models/: Directory where trained models are saved.

Usage Instructions

1. Download the ChestX-ray14 database in the data_chexnet/ folder.
2. Unpack files in separate directories (e.g. images_01.tar.gz into images_001)
3. Ensure you have Python and the required libraries installed.
4. Run the train.py script to train and evaluate the CheXNet model.
5. Trained models will be saved in the models/ directory and training logs in the logs/ directory.

Dependencies

The project requires the following dependencies:

• Python 3.x
• PyTorch
• scikit-learn
• torchvision
• PIL (Pillow)
• numpy
• tensorboard