Standard Datasets

Clothing Segmentation Dataset

Advanced datasets and Generative AI are revolutionizing the fashion and e-commerce industries, providing customized experiences and immersive interactions for shoppers worldwide.Our datasets provide valuable insights into fashion trends, styles, and consumer preferences, enabling businesses to deliver personalized shopping experiences.

The "Clothing Segmentation Dataset" is designed to propel the capabilities of AI in the fashion industry by providing a comprehensive collection of images for semantic segmentation tasks. This dataset encompasses internet-collected images from various scenarios such as e-commerce platforms, fashion shows, social media, and offline user-generated content. It focuses on enabling precise segmentation of clothing items, including main human parts, clothing pieces, and accessories, to support the development of advanced AI models for automated image analysis and product categorization.

Sample

Specification

Dataset ID

MD-Fashion-3

Dataset Name

Clothing Segmentation Dataset

Data Type

Image

Volume

About 500k

Data Collection

Internet collected images covers typical scenarios such as e-commerce, fashion shows, social media and offline user-generated content, etc.

Annotation

Semantic Segmentation

Annotation Notes

Including the main human parts, clothing, accessories, etc.

Application Scenarios

Smart Retail;O2O;Sns;E-Commerce;Fashion & Apparel;Visual Entertainment

Data Collections

This dataset comprises approximately 500,000 images, offering an extensive collection for training AI models in the fashion sector. Each image is meticulously annotated to include the main human parts, various clothing items, and accessories, facilitating the development of models capable of performing detailed semantic segmentation. This rich dataset supports a range of applications across e-commerce, fashion and apparel, O2O platforms, smart retail, social networking services (SNS), and visual entertainment, providing a valuable tool for enhancing online shopping experiences and streamlining the retail process.

Quality Assurance

Relevant Open Datasets

To supplement our Face Parsing Dataset, users can explore these open datasets for additional resources:

Fashionpedia [Learn more]

This dataset includes 48,825 clothing images annotated with segmentation masks and fine-grained attributes, built upon an expertly crafted ontology that encompasses 27 main apparel categories and 19 apparel parts. It's designed to advance tasks combining both detection and attributes classification in the fashion domain.

DeepFashion2 [Learn more]

A comprehensive fashion dataset containing 491K images of 13 popular clothing categories from both commercial and consumer sources. Each item is meticulously labeled with attributes such as scale, occlusion, viewpoint, category, and style, making it a versatile benchmark for clothing image understanding.

DeepFashion [Learn more]

This dataset boasts around 800K diverse fashion images with rich annotations, including 46 categories, 1,000 descriptive attributes, bounding boxes, and landmark information. The variety ranges from well-posed product images to consumer photos, providing a broad spectrum for fashion image analysis.

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