DOI: 10.5281/zenodo.13788681
title: Clothing Dataset for Second-Hand Fashion

description: Second-Hand Fashion Dataset

Update Sep. 19th, 2024

- Some problematic and duplicate images have been removed from version 2.- All "gold dataset" data from `station1` and `station3` has been moved to a single `test100` folder.- JSON errors have been fixed - all JSON files should be parsed correctly now.

The new dataset has 31,638 items (+ about 100 items in `test100` folder) instead of the 31,997 items in version 2.

Overview

The dataset originates from projects focused on the sorting of used clothes within a sorting facility. The primary objective is to classify each garment into one of several categories to determine its ultimate destination: reuse, reuse outside Sweden (export), recycling, repair, remake, or thermal waste. 

The dataset has 31,638 clothing items, a massive update from the 3,000 items in version 1. The dataset collection started under the Vinnova funded project "AI for resource-efficient circular fashion" in Spring, 2022 and involves collaboration among three institutions: RISE Research Institutes of Sweden AB, Wargön Innovation AB, and Myrorna AB. The dataset has received further support through the EU project, CISUTAC (cisutac.eu).

Project page 

Webpage: second-hand-fashionThe webpage and dataset were uploaded and hosted by Farrukh Nauman, who no longer works at RISE as of August, 2025. The data will continue to be hosted here. 

Dataset Details

- The dataset contains 31,638 clothing items, each with a unique item ID in a datetime format. The items are divided into three stations: `station1`, `station2`, and `station3`. The `station1` and `station2` folders contain images and annotations from Wargön Innovation AB, while the `station3` folder contains data from Myrorna AB. Each clothing item has three images and a JSON file containing annotations. 

- Three images are provided for each clothing item:  1. Front view.  2. Back view.  3. Brand label close-up. About 4000-5000 brand images are missing because of privacy concerns: people's hands, faces, etc. Some clothing items did not have a brand label to begin with.

- Image resolutions are primarily in two sizes: `1280x720` and `1920x1080`. The background of the images is a table that used a measuring tape prior to January 2023, but later images have a square grid pattern with each square measuring `10x10` cm. 

- Each JSON file contains a list of annotations, some of which require nuanced interpretation (see `labels.py` for the options):    - `usage`: Arguably the most critical label, usage indicates the garment's intended pathway. Options include 'Reuse,' 'Repair,' 'Remake,' 'Recycle,' 'Export' (reuse outside Sweden), and 'Energy recovery' (thermal waste). About 99% of the garments fall into the 'Reuse,' 'Export,' or 'Recycle' categories.    - `trend`: This field refers to the general style of the garment, not a time-dependent trend as in some other datasets (e.g., Visuelle 2.0). It might be more accurately labeled as 'style.'    - `material`: Material annotations are mostly based on the readings from a Near Infrared (NIR) scanner and in some cases from the garment's brand label.    - Damage-related attributes include:        - `condition` (1-5 scale, 5 being the best)        - `pilling` (1-5 scale, 5 meaning no pilling)        - `stains`, `holes`, `smell` (each with options 'None,' 'Minor,' 'Major').                 Note: 'holes' and 'smell' were introduced after November 17th, 2022, and stains previously only had 'Yes'/'No' options. For `station1` and `station2`, we introduced additional damage location labels to assist in damage detection: 

            "damageimage": "back",
            "damageloc": "bottom left",
            "damage": "stain ",
            "damage2image": "front",
            "damage2loc": "None",
            "damage2": "",
            "damage3image": "back",
            "damage3loc": "bottom right",
            "damage3": "stain"

        Taken from `labels_2024_04_05_08_47_35.json` file. Additionally, we annotated a few hundred images with bounding box annotations that we aim to release at a later date.    - `comments`: The comments field is mostly empty, but sometimes contains important information about the garment, such as a detailed text description of the damage. 

- Whenever possible, ISO standards have been followed to define these attributes on a 1-5 scale (e.g., `pilling`).

- Gold dataset: 100 garments  were annotated multiple times by different annotators for **annotator agreement comparisons**. These 100 garments are placed inside a separate folder `test100`.

- The data has been annotated by a group of expert second-hand sorters at Wargön Innovation AB and Myrorna AB. 

- Some attributes, such as `price`, should be considered with caution. Many distinct pricing models exist in the second-hand industry:  - Price by weight  - Price by brand and demand (similar to first-hand fashion)  - Generic pricing at a fixed value (e.g., 1 Euro or 10 SEK)    Wargön Innovation AB does not set the prices in practice and their prices are suggestive only (`station1` and `station2`). Myrorna AB (`station3`), in contrast, does resale and sets the prices. 

Comments

- We received feedback on our version 1 that some images were too blurry or had poor lighting. The image quality has slightly improved, but largely remains similar to release 1. - Some users did not prefer a `tar.gz` format that we uploaded in version 1 of the dataset. We have now switched to `.zip` for convenience.- Extra care was taken not to leak personal information. This is why you will not see any entries for `annotator` attribute in the JSON files in station1/sep2023 since people used their real names. Since then, we used internally assigned IDs. - Many brand images contained people's hands, faces, or other personal information. We have removed about 4000-5000 brand images for privacy reasons. - Please inform us immediately if you find any personal information revelations in the dataset:    - Susanne Eriksson (Wargön Innovation AB): `susanne.eriksson@wargoninnovation.se`,      - Gabriella Engstrom (Wargön Innovation AB): `gabriella.engstrom@wargoninnovation.se`.

We went through 100k images four times to ensure no personal information is leaked, but we are human and can make mistakes.

Partners

The data collection for this dataset has been carried out in collaboration with the following partners:

1. RISE Research Institutes of Sweden AB: RISE is a leading research institute dedicated to advancing innovation and sustainability across various sectors, including fashion and textiles.

2. Wargön Innovation AB: Wargön Innovation is an expert in sustainable and circular fashion solutions, contributing valuable insights and expertise to the dataset creation.

3. Myrorna AB: Myrorna is Sweden's oldest chain of stores for collecting clothes and furnishings that can be reused. 

License

CC-BY 4.0. Please refer to the LICENSE file for more details. 

Acknowledgments

This dataset was made possible through the collaborative efforts of RISE Research Institutes of Sweden AB, Wargön Innovation AB, and Myrorna AB, with funding from Vinnova and support from the EU project CISUTAC. We extend our gratitude to all the expert second-hand sorters and annotators who contributed their expertise to this project.