The purpose of this project is to quantify the amount of plastic generated through grocery store sales. The project aims to develop a model capable of accurately classifying the amount of plastic in grocery store products using deep learning techniques.
The primary objective of this project is to develop a model capable of accurately classifying the labeled product images according to the amount of plastic in them. The team will develop a set of 6,000 product images that will be classified into four categories: no-plastic, some-plastic, heavy-plastic, and no-image (not a product). In addition, they will collect 350,000 unlabeled images of products in-situ and aim to classify them according to the amount of plastic present.
Dhruv Kamalesh Kumar - kamaleshkumar.d@northeastern.edu
Yalala Mohit - mohit.y@northeastern.edu
Github Code - https://github.com/DB-25/plastic_usage_classification (Private)
PPT - https://docs.google.com/presentation/d/1LfYQy4zYn1mx-We8hg889fRaw2H4y0gcDv_2w9NCdpI/edit?usp=sharing
Video Presentation - https://drive.google.com/file/d/1cBOUYYvzQw0MOCYVA9kZck_UHCKLcygV/view?usp=sharing