ARTIFICIAL INTELLIEGENCE FASHION SYSTEM

Smart overview of the Invention

The system described utilizes an image-generative artificial intelligence (AI) engine to create realistic images of fashion items based on user inputs. It incorporates a memory component, an image-analysis engine, and an AI scoring network to generate, analyze, and score these images. The system is designed to allow users to customize fashion images by specifying attributes such as color, style, and material, and to visualize how these items might look on themselves or a model.

User Interaction

Users are provided with an interactive user interface to enter their desired fashion attributes. These can include various characteristics of clothing articles like color, style, occasion, and even specific details like collar and sleeve parts. The interface allows users to view and edit synthesized images, offering the option to hand-draw shapes or patterns on the clothing, enhancing customization.

Image Analysis and Scoring

Once an image is generated, an image-analysis engine creates an output dataset that includes information on color and shape distribution. The AI scoring network then evaluates this dataset to produce a first score. Additionally, a second score can be generated based on feedback from fashion designers, which aids in refining the AI's image generation capabilities by comparing and contrasting these scores.

Customization and Visualization

The system offers a smart UI that enables users to modify various clothing details through a smart input device. Users can upload inspirational images or drawings to guide the AI in generating specific clothing designs. Furthermore, users can visualize the AI-generated clothes on themselves or models by uploading photos, and even experiment with adding accessories like bags or earrings to the image.

Technical Implementation

The system is supported by at least one processor and a non-transitory computer-readable storage medium that stores instructions for executing its functions. The AI engine is continuously trained to improve its image generation by analyzing the interaction between AI-generated scores and designer feedback. This iterative process enhances the realism and customization of the fashion images produced.