🖼️ Kerala Mural Restoration & Classification Web App
This project is a web-based application designed to assist in the restoration and classification of Kerala mural paintings using deep learning techniques. By leveraging the VGG-16 convolutional neural network, the application aims to identify and categorize degraded murals, facilitating preservation efforts for this traditional art form.
🔍 Features
Image Classification: Utilizes a pre-trained VGG-16 model to classify images of Kerala murals, distinguishing between various styles and degradation levels.
Restoration Assistance: Provides insights into the condition of murals, aiding in restoration planning.
User-Friendly Interface: Built with Flask, offering an intuitive platform for users to upload and analyze mural images.
🛠️ Technologies Used
Frontend: HTML, CSS, JavaScript
Backend: Python, Flask
Machine Learning: TensorFlow, Keras, VGG-16 model
📁 Project Structure
Muralwebsite/ ├── static/ ├── templates/ ├── main.py ├── server.py ├── requirements.txt ├── Procfile ├── runtime.txt └── transfer_learning_vgg16_mural_model.h5 static/: Contains static files like CSS and JavaScript.
templates/: Holds HTML templates for rendering pages.
main.py: Main application script.
server.py: Handles server configurations.
transfer_learning_vgg16_mural_model.h5: Pre-trained VGG-16 model for mural classification.
Screenshots
Working Video
Abitha Udayan - https://github.com/Abitha-01
Akhila Suresh - https://github.com/hardworker9005
Elizabath Gigi - https://github.com/Elizabathgi
Kshethra K S - https://github.com/kshethraks