Artificial Intelligence-based Fashion Attribute Recognition — The secret to revenue growth. | Labellerr — Labelling Made Easy | Blog
In the 21st century, fashion is not just limited to what people are wearing but highlights hidden cues about personality traits and other social elements about the person wearing a particular dress. The revenue of the fashion retail industry can be largely attributed to the precision in the sociological analysis done by the company of its prospective customers.
More than ever attention is required on the fashion analysis of what people choose to wear if a fashion retail enterprise is looking to offer a product range highly correlated with the customer’s needs and demands.
Artificial Intelligence and Fashion must go hand in hand
“Adoption of advanced analytics and artificial intelligence (AI) will be among the fashion industry’s most significant changes in the coming decade, and one of its biggest challenges”. Highlights a report by Boston Consulting Group.
The role of Artificial Intelligence in the fashion industry is not just a buzzword anymore for anybody associated with fashion retail. Computer vision AI-based solutions are assisting decision-makers in drawing parallels between sales and stock. The deep learning engines empowering the industry have come a long way in the application domain. And currently, a huge number of use-cases are revamped by the use of artificial intelligence.
Attribute Recognition
One such use case is the attribute recognition of the apparel donned by a person. Recognition of attributes of the clothing is a computer vision-enabled multi-class multi-label classification problem, with the primary aim to determine the elements of clothing and their attributes from a set of n attributes. The attributes when accounted for in aggregation define the visual appearance of the clothing item.
The Process
The photographs of celebrities and influencers, the driver of trends in the fashion segment, are parsed from the social media channels and fed to the deep learning computer vision-enabled object detection and classification model called the “attribute recognition model”. The model takes as input an image and detects the different kinds of clothing donned and classifies the clothing items based on their attributes.
Let’s take for example the image of a celeb wearing a T-shirt is fed to the attribute recognition model. The image is parsed by the model to detect the color (red, blue, green, etc.) of the T-shirt, print patterns (if any), type of neck (round, v-shaped, polo, etc.) including the detection of T-shirt on the high level.
Need of the hour
Attribute Recognition and analysis maps the company’s efforts in designing and implementing a new design of fashion apparel with the trend to follow along with the sociological and personal requirements of the customer at large. Thus securing a winning position on the podium in the ever-competitive fashion market as stated by the BCG report, “Data will become an even more important competitive advantage: the brands with the most usable data will win.”
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Visit our website at www.labellerr.com and mention your use case in brief and our customer engineer will contact you and help you prepare the plan and get you running on a trial with us to validate.
Originally published at https://blog.labellerr.com on March 17, 2021.
