Damage Detection Dataset for Concrete Structures with Multi-Feature Backgrounds

The "Damage Detection Dataset for Concrete Structures with Multi-Feature Backgrounds" consists of 2,750 images of size 416x416, specifically curated to facilitate the detection of structural damage in various concrete surfaces. Each image captures real-world concrete structures with diverse backgrounds and environmental features, enhancing the dataset's utility for robust training and testing of damage detection models.

Additionally, the dataset includes corresponding XML annotation files for each image, providing precise bounding box coordinates and labels for different types of damage, such as cracks, spalling, and surface deterioration. This comprehensive dataset is ideal for researchers and engineers developing AI models for damage detection and localization in concrete structures under varied conditions.