Carlos Revilla@carlos_f_revilla366
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Acne-AI
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.
