Stufent
Student
AI Research Intern
Text to image generation
The project aims to create a web application that allows users to perform text-to-image conversions using the Stable Diffusion Model. Key Components: Frontend (React): The frontend of the application is developed using React, a popular JavaScript library for building user interfaces. It includes a form where users can enter the required parameters for text-to-image conversion, such as the prompt, number of images, negative prompt. Upon submission of the form, an API request is made to the backend to perform the conversion. Backend API (Django): The backend of the application is built using Django, a high-level Python web framework. It provides the necessary endpoints for text-to-image and image-to-image conversions. The API endpoints receive the parameters from the frontend, communicate with the Stable Diffusion Models API, and return the results back to the frontend. Stable Diffusion Models API: The application integrates with the Stable Diffusion Models API, which provides the text-to-image and image-to-image conversion functionalities. The API utilizes the Stable Diffusion pipeline and other related models to generate images based on the provided prompts and parameters. Communication (Axios): To facilitate communication between the frontend and backend, the application utilizes the Axios library. Axios is a popular JavaScript library for making HTTP requests, and it allows the frontend to send API requests to the backend endpoints and handle the responses.