LEAP 2024 Hackathon 

Registration opens

Opening remarks by NewNative, discussing Lablab's mission and vision

NewNative - Brief Introduction to the Hackathon, Challenge, lablab.ai platform, and Discord server.

NewNative. Participants are encouraged to begin working on their projects.

Official Hackathon Kick-off - NewNative

It is a perfect time to connect with potential team members and energize with coffee.

1st Matchmaking Coffee session begins

Emmanuel Iriarte - Building your AI application in rapid prototyping

Workshop

2nd Matchmaking Coffee session begin

Participants resume working on their projects.

Harry Berg

How to launch your career in Ai & Data at supersonic speed.


How to Architect and deliver production-grade, high-speed computation and artificial intelligence software for real-time analytics

Workshop - Anton Alexander

Hacking Commences.

AI personalization in social media and marketing

Ash Barbour 

Workshop -  Jens Ingelsted - How to Pitch 

Hacking Commences

Lossless Data Compression based on new math theory & algorithm

Workshop - Claus Rosenberg Gotthard 

How AI is changing the way we build and operate software


Pawel Czech

End of submissions. Judging commences, and finalists are selected.

End of Closing Ceremony

Winner announcements at the main stage

Providing effective AI solutions for acne 

HeartToHeart

Dhruv Batra

Carlos F Revilla

Kunsh

Sooren Ghodsi

Our project is a revolutionary web-based application designed to transform the approach to acne treatment and skincare. At its core, the application leverages a sophisticated machine learning model, the DinoV2, to accurately analyze user-uploaded images of acne. This model classifies acne into specific types such as comedonica, conglobata, and papulopustulosa.

Once the acne type is identified, our system integrates with OpenAI's powerful GPT-3.5-turbo model to generate personalized and comprehensive skincare advice, treatment options, and educational content tailored to the identified acne type. This integration ensures that each user receives information that is not only accurate but also relevant and practical for their specific condition.

The application's backend, built with Flask, handles image processing, machine learning computations, and API interactions seamlessly, providing a smooth and responsive user experience. The frontend, designed with user accessibility in mind, makes it easy for users to upload images and view their results.

Our aim is to empower individuals with actionable insights about their skin health, making professional-grade skincare advice accessible from the comfort of their homes. This project represents a meaningful contribution to personal health and well-being with machine learning that we hope will inspire and shape future technologies.

A cutting-edge, user-friendly web application utilizing DinoV2 self-supervised vision transformer and generative AI to analyze and provide customized skincare recommendations based on individual acne types.


"HeartToHeart team on LEAP 2024 Hackathon Hackathon"

Team Idea

Submission