🩻 X-Ray Image Classification Web Application

This web application allows users to upload X-ray images and classify them into one of the following categories:

• COVID-19
• Pneumonia
• Tuberculosis
• Normal

🚀 Features

✅ User-friendly interface for uploading X-ray images
✅ Automated classification using a trained deep-learning model
✅ Quick and reliable results for medical screening

📦 Requirements

Ensure you have the following installed:

• Python 3.x
• Jupyter Notebook
• Flask
• TensorFlow
• Other dependencies (will be installed automatically upon running model.ipynb)

🔧 How to Use the Web Application

1️⃣ Download the Repository

Clone or download the repository to your local machine:

git clone <repository_link>
cd <repository_directory>

2️⃣ Train the Model

Run model.ipynb using Jupyter Notebook or any IDE of your choice to train the model. This will create an .h5 file (the trained model), which will be saved in your local Desktop directory.

Adjustable Training Parameters:

• SIZE: Number of training samples (default = 2000)
• batch_size: Number of images per batch (default = 8)
• epochs: Number of training iterations (default = 100)

For a quick test, use:

SIZE = 256
batch_size = 8
epochs = 10

Run the notebook:

jupyter notebook model.ipynb

3️⃣ Start the Web Application

After training is complete and the .h5 model file is saved on your Desktop, run:

python app.py

4️⃣ Access the Web App

Copy the local server address displayed in the terminal (e.g., http://127.0.0.1:5000/) and paste it into your browser. You can now upload X-ray images for classification.

📂 Folder Structure

├── app.py                  # Flask application  
├── model.ipynb             # Model training notebook  
├── static/                 # Static files (e.g., CSS, images)  
├── templates/              # HTML templates  
├── requirements.txt        # Dependencies  
└── README.md               # Project documentation  

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💡 Contributing

Feel free to contribute by submitting issues or pull requests! 😊