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.