Blood-Group-Prediction-from-Fingerprints-Using-CNN

ℹ️ Need Help or More Details?

If you have any questions, need project reports or PowerPoint presentations, or require the complete code and setup instructions, don't hesitate to contact me:

📧 Email: abhishekr2088@gmail.com 🔗 LinkedIn: Abhishek R

💻 System Architecture

The system architecture is designed to predict blood groups from fingerprint images using deep learning techniques. The architecture includes the following components:

➡️ Flow Chart

Here’s the general flow of the system:

Setup Instructions

Follow the steps below to set up the project environment:

🔧 Prerequisites

Before setting up the project, ensure that you have the following installed on your system:

Software Requirements:

• Python 3.x: Required for running the project and deep learning model.
• Anaconda: For managing environments and dependencies (can be installed via Anaconda website).
• Git: For cloning the repository (can be installed via Git website).
• Visual Studio Code or PyCharm: Recommended text editors/IDEs for code editing.

Setup Instructions

1. Clone the Repository

Clone the repository to your local machine:

git clone https://github.com/Karthikg1908/Blood-Group-Prediction-from-Fingerprints-Using-CNN.git
cd Blood-Group-Prediction-from-Fingerprints-Using-CNN

2. Create and Activate a Virtual Environment

It's recommended to use a virtual environment for managing dependencies

For Windows:

python -m venv venv
venv\Scripts\activate

For macOS/Linux:

python3 -m venv venv
source venv/bin/activate

3. Install Dependencies Using Conda

Install necessary dependencies using Conda:

conda install -c conda-forge keras
conda install -c anaconda scikit-learn
conda install -c conda-forge opencv
conda install -c anaconda scikit-image
conda install -c anaconda flask
conda install numpy
conda install pillow

4. Install Additional Dependencies Using pip

After installing the Conda dependencies, install the remaining packages with pip:

pip install tensorflow
pip install pandas
pip install werkzeug==2.3.7
pip install flask torch torchvision torchaudio pillow werkzeug flask-wtf wtforms

5. Run the Flask Application

Run the Flask application with the following command:

python app.py

6 Access the Web Application

Open a web browser and navigate to http://127.0.0.1:5000/ to use the fingerprint blood group prediction system.

🤝 Contributing

We welcome contributions to improve the project. If you'd like to contribute, please follow these steps:

1. Fork the repository.
2. Create a new branch for your changes.
3. Make the changes, and ensure to test them thoroughly.
4. Submit a pull request with a clear description of the changes.

For any issues or bugs, feel free to open an issue in the GitHub repository.

🚀 Future Improvements

• Improve model accuracy by experimenting with deeper architectures or other deep learning models (e.g., ResNet, Inception).
• Add support for real-time fingerprint scanning and blood group prediction.
• Extend the project to classify more characteristics from fingerprints, such as age or gender.

ℹ️ Need Help or More Details?

If you have any questions, need project reports or PowerPoint presentations, or require the complete code and setup instructions, don't hesitate to contact me:

📧 Email: abhishekr2088@gmail.com 🔗 LinkedIn: Abhishek R