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you can find "train_crop_mask_(10,20,50,100)pct", corresponding to the case where 10%, 20%, 50%, and 100% masks have been replaced by their noisy version.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.

本仓库旨在托管用于训练噪声标签裂纹分割算法的数据集，该算法由张等人在即将发表的论文《SelectSeg：在数据有限和噪声标注条件下，基于不确定性的选择性训练与预测以实现精确裂纹分割》中提出。在压缩包中，您可以找到“train_crop_mask_(10,20,50,100)pct”，其中对应于10%、20%、50%和100%的掩码已被其噪声版本所替换。至于其他文件，包括训练图像以及验证/测试数据集，我们建议感兴趣的读者参考https://github.com/fyangneil/pavement-crack-detection以获取原始开发信息。