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Use Case

Virtual fashion designers

Generative AI models such as Language Models (LLMs), including OpenAI's GPT-3, and image generators can revolutionize the field of virtual fashion design. For example, designers can use LLMs to automatically generate creative ideas or descriptions for new clothing pieces. Additionally, they can use GPT-3 to generate fashion-oriented articles or blog posts to describe their designs.

On the other hand, image generators powered by Generative Adversarial Networks (GANs) can also be utilized to create visually appealing prototypes of new designs. A designer can input certain parameters like color, style, and fabric type, and the AI could generate an image of a potential design. This allows designers to experiment with different styles and shapes before deciding on a final design. Furthermore, AI-driven realistic digital avatars could be used in virtual reality fashion shows, transforming the way the industry operates.

How to build with Clevis

Text Input

Ask the user for their preferred color scheme for the design.

Prompt ChatGPT

Prompt ChatGPT to suggest a clothing item based on the color scheme provided by the user.

HTTP Request

Fetch fashion trend data from a fashion API.

Generate Image (DALL-E)

Generate a virtual clothing design using DALL-E based on the information collected so far.

Display Output

Display the generated virtual clothing design to the user.

The Virtual Fashion Designer is an example application that you can build using Clevis, a tool that enables rapid prototyping and deployment of AI applications. Using OpenAI technology, this app provides interactive design assistance to users.

In the first step, named Text Input, the app asks the user for their preferred color scheme. For instance, the user may input that they are fond of neutral tones or vibrant color palettes.

Subsequent to input collection, the app initiates a ChatGPT step. This involves employing ChatGPT, a conversational model by OpenAI, to suggest suitable clothing items grounded on the user-provided color scheme.

The next phase, Http Request, involves the app communicating with a fashion API. This helps it fetch contemporary fashion trends, which can subsequently influence the design process.

Upon gathering enough data, the app triggers the DALL·E step. This makes use of OpenAI's DALL-E, an AI model that produces unique images from textual descriptions, to design the virtual clothing item based on the collected data.

The final step, named Display Output, involves presenting the generated virtual fashion design to the user, ensuring a visual understanding of the design suggested by the AI.

Overall, the steps reveal how Clevis can help build AI applications within the fashion design arena.

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