Dataset
The purpose of the datasets is to boost the development of AI-tools for automatic sorting and valuing of garments related to condition. Condition is seen as the most crucial property for the sorting step and development of an efficient sorting process.
These datasets provide images and information about two of the most common defect-types, holes and spots. Focus for the datasets has been on the garment types T-shirts, trousers and jackets.
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Garment Conditions - Holes
The dataset focuses on detection of holes in post-consumer garments, with a specific focus on the garment-types jackets, trousers and T-shirts. The purpose of the dataset is to support the development, testing, and evaluation of automated methods (e.g. computer vision and AI) for quickly and accurately determining the condition of a garment.
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Garment Conditions - Spots
The dataset focuses on detection of spots/discoloration in post-consumer garments, with a specific focus on the garment-types jackets, trousers and T-shirts. The purpose of the dataset is to support the development, testing, and evaluation of automated methods (e.g. computer vision and AI) for quickly and accurately determining the condition of a garment.