SpectralWaste Dataset: Multimodal Data for Waste Sorting Automation

This dataset contains multimodal images captured in a real waste processing facility specialized in plastics, cartons, and cans. The data was collected with a true-to-life prototype of the conveyor belt installed on the waste separation line, closely mimicking the actual installation. The setup has two synchronized cameras: a line-scan RGB camera (Teledyne DALSA Linea) and line-scan hyperspectral sensor (Specim FX17) that captures 224 contiguous spectral bands in a range from 900 to 1700 nm. The images are annotated for semantic segmentation with categories based on the requirements of the facility. Each one represents elements that commonly cause operational problems in recycling lines and impact the efficiency of the sorting process. Among these problems, machinery jams pose significant issues because they can cause complete stoppages in the process until the obstructing object is removed. The categories include: film and basket, large objects that can clog the conveyor belts as they are not easily breakable; video tape and filament, representing long objects prone to entangling with mechanical parts and requiring manual intervention; trash bag, which encompasses closed bags containing waste that need to be mechanically opened for further processing; and cardboard, paper objects whose recovery adds value by sending them to another recycling process. Our project page can be found at https://sites.google.com/unizar.es/spectralwaste.本数据集包含采集自一家专注于塑料、纸箱与金属罐的真实废弃物处理工厂的多模态图像（multimodal images）。数据采集依托安装于废弃物分选线上的高保真传送带原型装置，该装置严格复刻了实际生产线的布局。采集系统搭载两台同步相机：一台线扫描RGB相机（Teledyne DALSA Linea），以及一台可捕获900至1700 nm波段内224个连续光谱波段的线扫描高光谱传感器（Specim FX17）。 本数据集的图像均基于该工厂的实际需求进行语义分割（semantic segmentation）标注，标注类别对应回收生产线中常见的影响分选效率的各类运行故障源。其中，机械卡滞问题尤为突出，一旦发生将导致整条生产线完全停机，直至阻塞物被清除。本次标注的类别包括：薄膜与筐体——不易破碎、易堵塞传送带的大型杂物；胶带与细丝——易缠绕机械部件、需人工干预处理的长条形杂物；垃圾袋——内含废弃物的密闭袋体，需通过机械拆解后开展后续处理；以及纸板——可通过回收再利用实现价值增值的纸质杂物。 本项目的公开页面可通过以下链接访问：https://sites.google.com/unizar.es/spectralwaste。