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Updated: Aug 16, 2026
13:19
Deep Neural Networks for Image-Based Dietary Assessment
Published on: March 13, 2021
Image and attribute dataset for 16 464 post-consumer garments discarded or donated in Norway
Johan Berg Pettersen1, Solveig Aarak1, Edyy Vanessa Peña Benítez1
1Industrial Ecology Programme, Department of Energy and Process Engineering. Norwegian University of Science and Technology, Norway.
Data in Brief
|August 15, 2026
Summary
This study analyzed 16,464 post-consumer garments to create a database of clothing attributes and images. This data supports textile recovery, resale, and circular economy initiatives in sustainable fashion.
Area of Science:
- Sustainable Materials Science
- Circular Economy Studies
- Textile Recycling Research
Background:
- Growing emphasis on sustainable textile consumption and circular economy principles.
- European policy aims to boost textile resale and recovery, currently limited by low recycled fiber usage.
- Demand for comprehensive data on product composition and quality for post-consumer textiles.
Purpose of the Study:
- To create a detailed database of image and attribute data for post-consumer clothing.
- To provide data supporting estimations of fiber blends, recovery potential, and resale value.
- To inform circular economy innovations and sustainable textile policies.
Main Methods:
- Collection and sorting of 16,464 post-consumer garments (4,157 kg) from six Norwegian urban regions.
- Visual inspection of garments and care labels, alongside individual garment photography.
- Data compilation including product category, weight, wear level, brand, production details, and material composition.
Main Results:
- A comprehensive dataset of garment attributes and associated images was generated.
- Attributes cover product details, wear degree, brand, manufacturing, and specific components (buttons, zippers, etc.).
- Care label data provided insights into production year, country, and multi-layer fiber composition.
Conclusions:
- The generated database is a valuable resource for estimating textile recovery and resale potential.
- Data can inform strategies for sorting, product longevity, and the development of circular economy models for textiles.
- Findings support policymakers and extended producer responsibility (EPR) actors in advancing sustainable textile management.
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