Urban Civic Issues Image Dataset: Potholes and Garbage (QR4Change)

This dataset has been developed to support research in computer vision for urban infrastructure monitoring and waste management, as part of the project QR4Change: A Smart QR-Based Civic Grievance Reporting System. The project aims to provide a technology-driven platform where citizens can conveniently report civic issues through QR codes, while automated image analysis assists municipal authorities in prioritizing and addressing complaints. The images were collected from diverse sources, including open-source repositories, government portals, and on-field surveys in Pune (covering regions such as Kondhwa, Bibewadi, Swargate, and Market Yard). The dataset is organized into two major categories: Pothole Dataset: A total of 2,966 images, consisting of 1,004 pothole images and 1,962 plain road (non-pothole) images. Garbage Dataset: A total of 1,971 images, consisting of 712 garbage dump images and 1,259 non-garbage images. This dataset not only underpins the QR4Change project but is also intended to serve the wider research community in developing and evaluating machine learning models for tasks such as image classification, object detection, and smart city civic issue analysis.本数据集为支撑城市基础设施监测与废弃物管理领域的计算机视觉研究而构建，隶属于项目QR4Change：基于智能二维码的市民诉求上报系统（QR4Change: A Smart QR-Based Civic Grievance Reporting System）。该项目旨在打造技术驱动的平台，使市民可通过二维码便捷上报城市公共事务诉求，同时借助自动化图像分析功能，协助市政部门优先处理并解决各类投诉。 图像采集自多种渠道，包括开源仓库、政府门户网站，以及在浦那（涵盖孔德瓦、比贝瓦迪、斯瓦加特和市场园区等区域）开展的实地调研。 本数据集分为两大核心类别： 路面坑洼数据集（Pothole Dataset）：共计2966张图像，包含1004张路面坑洼图像与1962张平整路面（非坑洼）图像。 垃圾数据集（Garbage Dataset）：共计1971张图像，包含712张垃圾堆放图像与1259张非垃圾场景图像。 本数据集不仅为QR4Change项目提供核心支撑，同时也可为更广泛的研究群体提供服务，用于开发与评估面向图像分类、目标检测以及智慧城市公共事务分析等任务的机器学习模型。