Fingerprint-Based Blood Group Prediction

Introduction:

This repository contains the code for a simple web application that attempts to predict blood group based on fingerprint data. The project utilizes a pre-trained machine learning model (RandomForestClassifier) and a Flask web framework. This project is intended solely for educational purposes to illustrate the process of building a web application that interacts with a machine learning model.

Requirements:

• Python
• Flask
• Scikit-learn
• Pandas
• NumPy
• Pickle

Dataset:-

     https://www.kaggle.com/datasets/rajumavinmar/finger-print-based-blood-group-dataset/data

Features:

• Web-based interface for inputting fingerprint features.
• Pre-trained machine learning model for prediction.
• Display of predicted blood group (for demonstration purposes only).
• Error handling for invalid input.
• Model persistence using pickle for efficient loading.
• Feature scaling using StandardScaler to improve model performance.

Run the Flask app

     python app.py

Open your browser and visit http://127.0.0.1:5000/

Screenshot: