Heritage_cracks

Published: 23 June 2026| Version 3 | DOI: 10.17632/b32hyvv2nn.3
Contributors:
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Description

The HeritageCracks dataset is a comprehensive collection of images designed to characterize superficial damage in historical monuments within the city of Morelia, primarily focusing on temples. This dataset enables the automated detection and classification of structural deterioration using computer vision and deep learning techniques, contributing to the preservation and structural health monitoring of cultural heritage. This dataset is structured to facilitate the training and evaluation of machine learning models. The data distribution has been carefully divided to ensure optimal model performance: 75% for Training 15% for Validation 10% for Testing Note: The total dataset size after augmentation is 1,716 images.

Files

Steps to reproduce

We welcome contributions to improve the HeritageCracks dataset! If you'd like to contribute: Fork the repository. Create a new branch (git checkout -b feature/NewData). Commit your changes (git commit -m 'Add new images of temple X'). Push to the branch (git push origin feature/NewData). Open a Pull Request. For major changes or additions to the dataset, please open an issue first to discuss what you would like to change.

Categories

Architecture, Civil Engineering, Objective

Licence