Trash screen blockage detection using cameras and deep learning: code and dataset

This dataset provides access to the images and network weights produced during our research on trash screen detection, along with minimum working examples allowing to use the network weights on new trash screen camera images. The images come from 54 different cameras with open access feeds provided by the Environment Agency (http://eadevonwebcams.org.uk/), and were collected from January 2022 to January 2023. The images were manually annotated with a "clear" (if the trash screen looks clear), "blocked" (if the trash screen looks blocked) or "other" (if unsure) label. The network weights and minimum working examples allow to estimate labels of new trash screen images using three different methods: a classifier, a siamese network and an anomaly detection method.

本数据集提供了我们在垃圾滤网检测研究过程中生成的图像与网络权重文件，同时附带可将该网络权重应用于全新垃圾滤网相机图像的最小工作示例。本次使用的图像源自英国环境署（Environment Agency，http://eadevonwebcams.org.uk/）提供的54路公开可访问摄像头流，采集时段为2022年1月至2023年1月。所有图像均经人工标注，标签分为"清晰"（垃圾滤网外观无遮挡）、"堵塞"（垃圾滤网外观被遮挡）与"其他"（无法确定遮挡情况）三类。本数据集附带的网络权重与最小工作示例，支持通过三种不同方法对全新垃圾滤网图像进行标签预估：分类器、孪生网络（Siamese Network）与异常检测方法。