mdzaheerjk/Discarded-Material-Identification-System
An end-to-end ML system to detect and classify waste in images/live video using a state-of-the-art object detection model for real-time accuracy. Built with modular design, automated pipelines, and CI/CD for cloud deployment.
This system helps organizations efficiently sort discarded materials by automatically identifying and classifying waste items from images or live video feeds. It takes visual input of waste as it appears on a conveyor belt or in a sorting facility and outputs real-time labels like 'cardboard,' 'plastic,' or 'metal,' enabling faster and more accurate segregation. Operations managers, recycling plant supervisors, or sustainability officers can use this to improve waste management processes.
Use this if you need to automate or significantly speed up the process of identifying different types of discarded materials in a waste stream using visual data.
Not ideal if your primary need is for chemical analysis or composition breakdown of materials, rather than visual classification of broad categories.
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MIT
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Last pushed
Jan 27, 2026
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