CRACK500 with noisy annotation masks

This is the repository to host the dataset to train noisy labelled crack segmentation algorithm proposed by Zhang, et al. (upcoming) in the article "SelectSeg: Uncertainty-based selective training and prediction for accurate crack segmentation under limited data and noisy annotations". In the zip folder, you can find "train_crop_mask_(10,20,50,100)pct", corresponding to the case where 10%, 20%, 50%, and 100% masks have been replaced by their noisy version. For other files, including training images, and validation/test dataset, we refer the interested readers to https://github.com/fyangneil/pavement-crack-detection for the original development.