NeuroInfuse

Seamlessly integrates objects into background images while preserving their template!

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Inspiration

Non-creative individuals often struggle to visualize how different elements can come together cohesively. This limits their ability to explore design or architectural ideas. NeuroInfuse was created to solve this problem by leveraging AI to seamlessly integrate objects into background images while preserving their structure, making creative design accessible to everyone.

What it does

NeuroInfuse is an AI-powered tool that seamlessly integrates objects into background images while maintaining their original structure. It functions like an automated version of Photoshop, using a Stable Diffusion model to blend elements naturally and realistically. Users can input objects and backgrounds, and the system generates a cohesive composition.

How we built it

NeuroInfuse was built using a combination of modern technologies:

  • Frontend: Developed with React and TypeScript for a responsive and intuitive user interface.
  • Backend: Powered by FastAPI to handle communication between the frontend and the AI model.
  • AI Model: Utilized PyTorch and Stable Diffusion for image generation and integration.
  • Integration: The system was designed to ensure smooth interaction between the frontend, backend, and AI components.

Challenges we ran into

  • Model Optimization: Ensuring the Stable Diffusion model could process images quickly and efficiently was a significant challenge. We managed to optimize the model, however, to process the images from 10 minutes to only 30 seconds.
  • Preserving Object Structure: Maintaining the integrity of objects while blending them into backgrounds required fine-tuning the AI model.
  • User Experience: Balancing the complexity of AI processing with a simple and intuitive interface was a key hurdle.
  • Scalability: Handling large image files and ensuring the system could scale for multiple users required careful planning.

Accomplishments that we're proud of

  • Successfully integrating Stable Diffusion into a user-friendly web application.
  • Creating a tool that democratizes design by making it accessible to non-creative individuals.
  • Building a seamless pipeline between the frontend, backend, and AI model.
  • Delivering a functional and visually impressive product within a limited timeframe.

What we learned

  • How to optimize AI models for real-time performance.
  • The importance of iterative development and user feedback in refining the product.
  • Improved collaboration and communication skills while working as a team.
  • Gained deeper insights into full-stack development, particularly with React, TypeScript, and FastAPI.

What's next for NeuroInfuse

  • Advanced Customization: Allow users to adjust parameters like lighting, shadows, and perspective for more control over the final output.
  • Multi-Object Integration: Enable the seamless blending of multiple objects into a single background.
  • Production: Deploy the whole application and the model on AWS.

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