Pneumonia Detection Using AI 🧠🫁

This project uses deep learning to detect pneumonia from chest X-ray images. It includes a trained CNN model and a user-friendly web interface built with Streamlit.

🔍 Features

• Upload a chest X-ray to detect pneumonia

• Deep learning model (CNN) with high accuracy

• Simple web interface using Streamlit

• Login and registration system

• Custom-styled UI

📁 Project Structure

Pneumonia_Detection_UsIng_AI/ ├── dataset/ # Dataset files

├── model/ # Saved CNN model

├── pneumonia_cnn_model.ipynb # Model training notebook

├── app.py # Streamlit web app

├── requirements.txt # Dependencies

└── README.md # Project documentation

💻 How to Run

1. Clone this repository:

git clone https://github.com/rishika712/Pneumonia_Detection_UsIng_AI.git

cd Pneumonia_Detection_UsIng_AI

2. Install required libraries:

pip install -r requirements.txt

3. Run the app:

streamlit run app.py

Make sure the trained model file (pneumonia_model.h5) is in the right folder.

📊 Dataset

• Source: Kaggle - Chest X-Ray Images (Pneumonia)

• Two classes: NORMAL and PNEUMONIA

🧠 Model Details

• Convolutional Neural Network (CNN)

• Built with TensorFlow and Keras

• Trained, validated, and tested on chest X-ray images

🌐 Deployment

• Built using Streamlit

• Can be deployed on Streamlit Cloud, Render, or Heroku

🔐 Authentication

• Basic login/signup system using a text file

• Styled buttons and background for better user experience

🛠️ Technologies Used

• Python

• TensorFlow / Keras

• OpenCV

• Streamlit

• NumPy / Pandas

🚀 Future Enhancements

• Improve UI/UX

• Add admin dashboard

• Support detection of other diseases

🤝 Contributing

Contributions are welcome! Feel free to open issues or pull requests.

📄 License

This project is licensed under the MIT License.

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Made by Rishika