Standard DatasetsHuman Body High Precision 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 "Human Body High Precision Segmentation Dataset" is a comprehensive collection aimed at the apparel, e-commerce, and visual entertainment sectors, combining manually shot and internet-collected images with resolutions from 316 × 600 to 6601 × 9900. It focuses on high-precision segmentation of the human body, capturing intricate details of limbs, clothing, facial features, skin, and accessories.
Sample
Specification
Dataset ID
MD-Image-022
Dataset Name
Human Body High Precision Segmentation Dataset
Data Type
ImageVolume
About 424.8k
Data Collection
Shoot manually and collected from internet, image resolution ranges from 316*600 to 6601 x 9900
Annotation
Semantic Segmentation
Annotation Notes
High precision segmentation of human body, including limbs (left and right arms or upper and lower arms + left and right legs or legs), clothing (coats, jackets, dresses, dresses, dresses, skirts, coats, socks, trousers, ties), facial thinning (eyebrows, eyes, nose, mouth, beard), skin (skin color differentiates in some cases), caps, hair, accessories (Accessories, bags, belts, gloves, scarves), backgrounds, etc.)
Application Scenarios
Apparel;E-Commerce;Visual Entertainment
Data Collections
With around 424.8k images, this dataset offers detailed segmentation of various human body parts and apparel, including limbs, different types of clothing, facial features, and accessories like bags and belts. The high level of detail in the annotations, including distinctions in skin color and the inclusion of background elements, makes this dataset invaluable for applications requiring detailed human body analysis and virtual try-on systems, enhancing realism and user engagement in digital environments.
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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