The BeachLitter dataset for image segmentation of beach litter

This dataset consists of 3500 images of beach litter and 3500 corresponding pixel-wise labelled images. Although performing such pixel-by-pixel semantic masking is expensive, it allows us to build machine-learning models that can perform more sophisticated automated visual processing. We believe this dataset may be of significance to the scientific communities concerned with marine pollution and computer vision, as this dataset can be used for benchmarking in the tasks involving the evaluation of marine pollution with various machine learning models. The beach litter images were obtained from coastal environment surveys conducted between 2011 and 2019 by the Yamagata Prefectural Government, Japan. These images were originally obtained owing to the reporting guidelines concerning regular coastal-environmental-cleanup and beach-litter-monitoring surveys. Based on these images, the Japan Agency for Marine-Earth Science and Technology created 3500 images comprising eight classes of semantic masks for beach litter detection本数据集包含3500张海滩垃圾图像，以及与之对应的3500张像素级标注（pixel-wise labelled）图像。尽管逐像素语义掩码（pixel-wise semantic masking）的标注成本高昂，但该数据集可支撑构建能够实现更复杂自动化视觉处理的机器学习模型。我们认为，本数据集对于海洋污染与计算机视觉领域的科研群体具有重要价值，其可用于各类基于机器学习模型评估海洋污染的任务的基准测试（benchmarking）。本数据集内的海滩垃圾图像采集自日本山形县厅（Yamagata Prefectural Government）于2011年至2019年间开展的沿海环境调查，这些图像最初是依据常规沿海环境清理与海滩垃圾监测调查的报告指南获取的。基于上述图像，日本海洋地球科学技术厅（Japan Agency for Marine-Earth Science and Technology）制作了3500张包含8类用于海滩垃圾检测的语义掩码的图像。

搜集汇总

背景与挑战

背景概述

该数据集是一个用于海滩垃圾图像分割的基准数据集，包含3500张海滩垃圾图像和对应的3500张像素级标注图像，涵盖八个语义类别。数据来源于2011年至2019年日本山形县的海岸环境调查，适用于海洋污染监测和计算机视觉研究，支持机器学习模型的开发和评估。数据集格式为JPG，聚焦于气候变化和环境领域，关键词包括海洋、海滩、垃圾、废物和航空图像。