Curated Dataset and Inference Results for AI-Based Bridge Defect Detection Using Images and Videos

This repository contains curated dataset and inference results used in the study: "AI-powered bridge defect detection and condition assessment using drone-collected visual data." Contents:1. curated_dataset_images_annotations: Annotated images with YOLO-format labels for eight defect classes.2. curated_inference_results_images: Model predictions on test images.3. curated_dataset_bridge_videos: Raw bridge inspection videos. Defect classes:Crack, ACrack, Efflorescence, WConccor, Spalling, Wetspot, Rust, ExposedRebars. All annotations are manually created and used as ground truth for training and validation.Inference results are generated using a trained YOLO-based instance segmentation model. This dataset supports reproducibility and transparency of the proposed methodology.