Street Cleanliness and Recycling Bin Dataset

The Urban Street Cleanliness Dataset is a high-quality computer vision dataset designed for environmental monitoring, waste detection, and urban cleanliness assessment. It provides categorized street images to support AI-driven classification, segmentation, and object detection models.

Dataset Overview

• Dataset Focus: Environmental analysis, urban waste detection, and street cleanliness monitoring
• Image Categories:
  • Clean Streets: Streets free from litter or visible waste
  • Dirty Streets: Streets with scattered garbage or waste
  • Recycling Points (Ecopoints): Streets with visible recycling bins
• Use Cases: Ideal for AI-powered urban analysis, deep learning-based waste detection, smart city projects, and environmental monitoring
• Machine Learning Applications: Supports classification, segmentation, and object detection tasks
• High-Quality Annotations: Structured categorization for accurate model training in urban sustainability projects

Key Features

• Diverse Dataset: Includes images of various urban environments with different cleanliness conditions
• Multi-Class Categorization: Clearly labeled images for clean streets, dirty streets, and recycling bins
• AI & Deep Learning Ready: Optimized for classification, segmentation, and object detection models
• Supports Smart City Initiatives: Helps in developing automated waste detection and urban planning systems
• Environmental Impact Analysis: Valuable for research on urban waste management and sustainability
• Scalability: Can be expanded for real-time applications in smart city monitoring systems