Pneumonia Detection from Chest X-rays 🫁

This project uses a Convolutional Neural Network (CNN) to detect pneumonia from chest X-ray images. The model is trained on a labeled dataset and classifies images as either NORMAL or PNEUMONIA.

The main goals of this project are:

• Build and train a CNN using TensorFlow/Keras
• Evaluate predictions on test images
• Visualize model output using matplotlib
• Eventually implement Grad-CAM to understand which parts of the image the model focuses on

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🚧 Status: Work In Progress

This project is still in progress. Currently, the model can make predictions, but:

• Grad-CAM is not yet implemented
• Model performance may be affected by dataset imbalance
• Improvements and testing are ongoing

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✅ How to Run

1. Clone the repo and set up a Python virtual environment:

   python -m venv venv
   source venv/bin/activate  # or venv\Scripts\activate on Windows
   pip install -r requirements.txt
   

2. Download and extract the Chest X-Ray Pneumonia dataset into the data/ folder Text to display

3. Train the model

python main.py

4. Predict with test images

python evaluate.py