Automating the assessment of biofouling in images

Images and annotations used for training the computer vision models in the <i>Automating the assessment of biofouling in images using expert agreement as a gold standard</i> (2021) paper. Please cite this paper if you use this dataset. We include biofouling (SLoF), paint damage (Paint quality), and niche area annotations in the metadata. For biofouling, we use the Simplified Level of Fouling (SLoF) scale0: No fouling organisms, but biofilm or slime may be present.<br>1: Fouling organisms (e.g. barnacles, mussels, seaweed or tubeworms are visible but patchy (1-15% of surface covered).<br>2: A large number of fouling organisms are present (16-100% of surface covered).For paint quality, we use the following scale1: Paint not present or in poor condition (16-100% of surface scratched/corroded/fouled).<br>2: Paint visible and in fair condition or slightly obscured (1-15% of surface scratched/corroded/fouled)<br>3: Paint visible and in good condition.We are also releasing models trained on this dataset. Please see this github page for further information on using them.

本数据集包含用于训练《以专家共识为金标准的图像生物污损自动化评估》(Automating the assessment of biofouling in images using expert agreement as a gold standard，2021) 论文中计算机视觉模型的图像与标注。若使用本数据集，请引用该论文。
本数据集的元数据包含三类标注：生物污损（Simplified Level of Fouling，SLoF）、漆面损伤（Paint quality）以及生境区域（niche area）标注。
针对生物污损，我们采用生物污损简化等级（SLoF）量表进行分级：
0级：无污损生物附着，但可能存在生物膜或黏液；
1级：可见污损生物（如藤壶、贻贝、海藻或管蠕虫）但呈斑块状分布，覆盖表面1%~15%；
2级：存在大量污损生物，覆盖表面16%~100%。
针对漆面损伤，我们采用如下分级标准：
1级：漆面缺失或状态极差，表面16%~100%存在刮擦、腐蚀或污损；
2级：漆面可见且状态尚可，或仅轻微受损，表面1%~15%存在刮擦、腐蚀或污损；
3级：漆面可见且状态良好。
我们同时发布了基于本数据集训练得到的计算机视觉模型，相关使用细节请参阅该GitHub页面。