DreamGenie

Overview

Dream Genie is an innovative application designed to enable users, especially older adults, to experience their dreams in a new light. It allows users to talk about a dream, then identifies key scenes and creates artistic representations of each scene.

Demo

Click the video to watch on youtube:

Here is an image example from a dream about dragons:

Features

• Voice/text input for dream scene generation.
• GPT-3 for splitting transcribed text into individual dream scenes.
• Image generation using Stable Diffusion.
• Flask-based web application for user interaction.
• MongoDB for data storage and feedback collection.

Getting Started

System Architecture and Deployment

Dream Genie is hosted on Microsoft Azure, leveraging Docker Compose for efficient server management. The deployment includes:

• Gunicorn Container: Handles application logic and incoming requests.
• Redis Container: Manages user session data.
• Nginx Container: Provides load balancing for high availability.

Additionally, the project employs localized servers with GPU support for computationally intensive tasks, such as running the Stable Diffusion and Whisper models.

Stable Diffusion and Whisper Services

• Stable Diffusion: This image generation model is used to create visual representations of dream scenes. It's hosted locally on our servers, accessed through Ngrok tunnels for security.
• Whisper: An open-source speech recognition model, Whisper is employed for transcribing user input and is similarly hosted on local servers.

For a detailed exploration of Dream Genie's architecture, deployment strategies, and technologies, please refer to our System Architecture Document (SAD).

Prerequisites

• Python 3.9+.
• Redis Server for caching and background tasks.

Installation

1. Clone the repository:

   git clone https://github.com/BDT2023/DreamGenie.git
   

2. Navigate to the project directory and install dependencies using the provided requirements.txt files.

Usage

Follow the instructions in the application for providing dream inputs and viewing generated scenes.

License

This project is licensed under MIT License - see the LICENSE.md file for details.

Acknowledgments

• Special thanks to all contributors and supporters of the Dream Genie project.
• Appreciation to the open-source community for various tools and libraries used in this project.

Contact

For any queries, please contact:

• Ben Eli @beneli1
• Daniel Bronfman @funkey7dan
• Tomer Pardilov @TomerPardi