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DWSD: Dense Waste Segmentation Dataset

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submitted on 2025-05-01, 09:01 and posted on 2025-05-01, 09:10 authored by Asfak Ali, Suvojit Acharjee, MD Manarul Sk, Salman Alharthi, Sheli Sinha Chaudhuri, Adnan AkhunzadaAdnan Akhunzada

Waste disposal is a global challenge, especially in densely populated areas. Efficient waste segregation is critical for separating recyclable from non-recyclable materials. While developed countries have established and refined effective waste segmentation and recycling systems, our country still uses manual segregation to identify and process recyclable items. This study presents a dataset intended to improve automatic waste segmentation systems. The dataset consists of 784 images that have been manually annotated for waste classification. These images were primarily taken in and around Jadavpur University, including streets, parks, and lawns. Annotations were created with the Labelme program and are available in color annotation formats. The dataset includes 14 waste categories: plastic containers, plastic bottles, thermocol, metal bottles, plastic cardboard, glass, thermocol plates, plastic, paper, plastic cups, paper cups, aluminum foil, cloth, and nylon. The dataset includes a total of 2350 object segments.

Other Information:

Published in: Mendely Data
License: http://creativecommons.org/licenses/by/4.0/
See dataset on publisher's website: https://data.mendeley.com/datasets/gr99ny6b8p/1


History

Language

  • English

Publisher

Elsevier

Publication Year

  • 2024

License statement

This Item is licensed under the Creative Commons Attribution 4.0 International License.

Institution affiliated with

  • University of Doha for Science and Technology
  • College of Computing and Information Technology - UDST

Related Publications

Ali, A., Acharjee, S., Sk., Md. M., Alharthi, S. Z., Chaudhuri, S. S., & Akhunzada, A. (2025). DWSD: Dense waste segmentation dataset. Data in Brief, 59, 111340. https://doi.org/10.1016/j.dib.2025.111340