DWSD: Dense Waste Segmentation Dataset

Waste disposal is a global challenge, especially in densely populated areas. Efficient waste segregation is critical for separating recyclable from non-recyclable materials. While developed countries have established and refined effective waste segmentation and recycling systems, our country still uses manual segregation to identify and process recyclable items. This study presents a dataset intended to improve automatic waste segmentation systems. The dataset consists of 784 images that have been manually annotated for waste classification. These images were primarily taken in and around Jadavpur University, including streets, parks, and lawns. Annotations were created with the Labelme program and are available in color annotation formats. The dataset includes 14 waste categories: plastic containers, plastic bottles, thermocol, metal bottles, plastic cardboard, glass, thermocol plates, plastic, paper, plastic cups, paper cups, aluminum foil, cloth, and nylon. The dataset includes a total of 2350 object segments.

垃圾处置是一项全球性挑战，在人口稠密区域尤为凸显。高效的垃圾分选是区分可回收与不可回收物料的关键环节。目前发达国家已建立并完善了成熟有效的垃圾分选与回收体系，而我国仍依靠人工分选来识别并处理可回收物。本研究构建了一款旨在优化自动垃圾分选系统的数据集。该数据集包含784张经人工标注的垃圾分类图像，主要拍摄于贾达夫普尔大学（Jadavpur University）校内及周边区域，涵盖街道、公园与草坪等场景。标注工作通过Labelme程序完成，采用彩色标注格式。该数据集共涵盖14类垃圾：塑料容器、塑料瓶、泡沫塑料（thermocol）、金属瓶、塑料纸板、玻璃、泡沫塑料餐盘、纯塑料、纸张、塑料杯、纸杯、铝箔、布料以及尼龙。数据集总计包含2350个目标分割区块。