Pneumonia Detection using Convolutional Neural Network

Project Description :

This project uses Convolutional Neural Networks (CNN) to detect Pneumonia from chest X-ray images. The dataset is sourced from the Kaggle dataset "Chest X-Ray Images (Pneumonia)" by Paul Mooney.

Dataset :

The dataset consists of X-ray images categorized into two classes:

• Normal
• Pneumonia

You can download the dataset from Kaggle

Usage :

<> Create a virtual environment and activate it.

python3 -m venv venv
source venv/bin/activate

<>Install the required packages.

pip install -r requirements.txt

<> Download the dataset and place it in the data/ directory and run the ipy notebook file.

Model Architecture :

The CNN model architecture consists of several convolutional layers, each followed by max-pooling layers, and finally dense layers for classification.

Summary of the model :

• Conv2D layers with ReLU activation
• MaxPooling2D layers
• Flatten layer
• Dense layers with ReLU activation
• Output Dense layer with sigmoid activation for binary classification

Results :

• Training accuracy : 98.16%
• Validation accuracy : 100%

Sample Inputs :

Sample Outputs :