README.md

Blood Group Detection from Fingerprint

This is a Streamlit application for detecting blood groups from fingerprint images using a pre-trained Keras (TensorFlow) model.

📌 Prerequisites

Make sure you have the following installed on Windows:

• Python 3.10 (Ensure it's added to PATH during installation)
• Git (for cloning the repository)
• pip (comes with Python)
• Docker (for containerization, optional)

🚀 Installation & Setup

Follow these steps to set up and run the project:

1️⃣ Clone the Repository

git clone https://github.com/yourusername/blood_group_detection_using_fingerprint_cnn.git
cd blood_group_detection_using_fingerprint_cnn

2️⃣ Create a Virtual Environment (Without Conda)

python -m venv venv --copies

3️⃣ Activate the Virtual Environment

venv\Scripts\activate

4️⃣ Install Required Dependencies

pip install -r requirements.txt

5️⃣ Run the Streamlit App

streamlit run app.py

🐳 Docker Setup (Optional)

If you want to containerize the application using Docker, follow these steps:

1️⃣ Build the Docker Image

docker build -t blood-group-app .

2️⃣ Run the Docker Container

docker run -p 8501:8501 blood-group-app

3️⃣ Access the Application

Open your browser and go to:

http://localhost:8501

📂 Project Structure

├── Model/
│   ├── keras_Model.h5   # Trained model file
│   ├── labels.txt       # Labels for classification
├── app.py               # Main Streamlit app
├── requirements.txt     # List of dependencies
├── Dockerfile           # Docker container setup
├── README.md            # Project documentation

🛠 Troubleshooting

• If streamlit is not recognized, make sure the virtual environment is activated.
• If TensorFlow is missing, try running:

  pip install tensorflow

• If you face Python version issues, ensure you’re using Python 3.10.
• If you encounter issues with Docker, try rebuilding the image:

  docker build --no-cache -t blood-group-app .

📜 License

This project is open-source. Feel free to modify and improve it! 🎉