Fashion Photo Annotation is one of the most important sectors that’s is disrupted by machine learning and computer vision today. With some of the world’s smartest startups and technology giants working on computer vision for fashion, it becomes crucial to have high quality annotated training data for creating strong machine learning models for the fashion retail industry. The use cases in fashion retail industry range from accurate cataloging of fashion products in e-commerce portals, adding fine level attributes to fashion products which cannot be easily done manually, thereby improving search and discovery and finally helping users to search using image, also known as Visual Search Infizoom had strong experience in helping AI startups with high quality training data for the fashion domain. Infizoom worked Huew (https://huew.co), a fashion discovery platform which connected fashion photos on social media platforms like Instagram with actual visually similar products from multiple e-commerce portals. Infizoom performed end to end tagging for object detection (detecting categories like dress, skirt, shirt, jeans etc) and annotating each apparel with fine level attributes like neck type, sleeve type, color, pattern etc. With Infizoom’s help, Huew developed one of the smartest fashion discovery platform.
Fashion photo annotation is a process that uses advanced machine learning technology to apply text labels which accurately describe the contents of photos in an image dataset. This technology is highly useful for both retail and branding applications as it helps automate the manual tagging process required to categorize product images in such a way that maximizes searchability and organization. The accuracy and consistency of fashion photo annotation enable companies to rapidly bring desired products to market, as well as ensure customers get precisely what they are looking for when shopping online or in-store.