README.md

Maltese Christian Statue (MCS) Classification Dataset

Introduction

The Maltese Christian Statue (MCS) Classifier project explores the question: Can Artificial Intelligence (AI) be utilised to recognise and differentiate between Maltese Christian statues in images? Built from the curated MCS Image Classification Dataset, which represents 17 distinct categories of Maltese Christian statues, this project aims to assist those unfamiliar with the culture or religion by offering an accessible window into Malta's rich religious heritage.

Image classification is a fundamental task in computer vision, involving the process of categorising images into predefined classes or categories. It leverages machine learning algorithms to analyse the visual content of images and assign them to appropriate labels based on their features and characteristics. In the context of the MCS Classifier project, image classification techniques are employed to automatically identify and categorise Maltese Christian statues depicted in images.

This initiative aims to safeguard and promote Maltese religious culture, especially during the solemn period of Lent. It serves as a bridge, introducing tourists to the intricacies of Maltese religious iconography, fostering understanding and appreciation.

Employing advanced image classification techniques, this project integrates artificial intelligence into the context of Maltese Christianity, a domain where such technology has been traditionally less explored. It is essential to underscore that the project is not intended to mock or disrespect religious beliefs. On the contrary, it adopts a respectful and reverent approach, aiming to enrich understanding and foster deeper engagement with Malta's religious heritage.

Ultimately, the project aspires to contribute positively to the perpetuation and enrichment of Maltese religious heritage, potentially inspiring greater belief and dedication to its cause.

MCS Dataset

The MCS Dataset features 17 categories of Christian statues found in Malta, specifically in the parish church of Ħaż-Żebbuġ dedicated to St Philip of Agira, and some photos from other parishes. Please note that the images retrieved for the creation of this dataset were extracted from public domain sources and are not intended for commercial use.

The categories in the MCS Dataset are:

1. Christmas Cribs
2. Jesus has Risen
3. Jesus praying in Gethsemane
4. Our Lady of Grace
5. Saint Joseph
6. Saint Philip of Agira
7. Simon of Cyrene
8. The Betrayal of Judas
9. The Cross
10. The Crucifixion
11. The Ecce Homo
12. The Flogged
13. The Lady of Sorrows
14. The Last Supper
15. The Monument
16. The Redeemer
17. The Veronica

Sample images from the MCS Dataset are displayed below:

MCS Dataset Distribution

The MCS Dataset consists of 5,000 images distributed across the 17 classes. Illustrated below is the distribution of the dataset across the classes. Additionally it is also important to note that the dataset is split into 80% training and 20% testing sets. Furthermore, Data Augmentation techniques were also used to increase the size of the dataset.

MCS Classifier Model Predictions

Illustrated below are predictions made by the MCS Classifier Model on unseen images from the test dataset. The model demonstrates its ability to classify Maltese Christian statues accurately.

Installation

To get started, clone the repository and navigate to it:

git clone https://github.com/mbar0075/Maltese-Christian-Statue-Classifier.git
cd Maltese-Christian-Statue-Classifier