The algorithm, in the experimental study phase, allows to identify the clothing items present in the image and to divide the element into sections.
It also allows you to classify and assign attributes. The main application areas are listed below:
- Visual recommendation systems: the system recognizes, through the presence of one or more rooms, the garment(s) worn by the customer. Starting from this information and possibly from the historical data associated with the user profile, it proposes a personalized list of products that could be of interest to you. The history of user-product interactions is completed with the visual characteristics extracted from the images of the products by means of machine learning models to generate the final recommendations. The customer views this personalized list and can provide feedback on each specific recommended product. The personalized list will contain products of the customer's liking and present in physical or digital stores.
- Generative models for the automatic and personalized creation of new garments: the system recognizes, through the presence of one or more rooms, the garment(s) worn by the customer. Starting from this information and possibly from the historical data associated with the user profile, it proposes new images, created ad hoc, which reflect the visual aspects that the model has learned. The customer views the images created.
- Augmented reality: the customer can select an item of clothing and / or accessory of his interest from a totem and perform a ""virtual test"" in real time. The segmentation mechanisms of the body (or part of it) will be used to which the images of the garment / accessory will be superimposed.
- Private companies for the improvement of the customer's customer experience