A great way to extend the utility of SkinSense is to support users directly at the point of purchase. Even with a precise skin diagnosis, many users find it challenging to navigate the complex chemical names on product labels while standing in a store. For instance, a user who knows they have "Dry Skin" might still struggle to identify specific drying alcohols or harsh sulfates hidden in a long ingredient list. Adding a "Real-Time Checker" would help translate our AI’s diagnosis into confident, safe purchasing decisions in the physical world.
Proposed Solution
I suggest implementing an AI Ingredient Scanner that uses OCR to act as a personal shopping assistant. By utilizing the FastAPI service to handle image-to-text extraction from product photos, we can cross-reference those ingredients against the user’s analyzed skin profile stored in Spring Boot. The React frontend could then display a "Compatibility Score" and highlight any "Red Flag" ingredients using a clean, bento-style UI. This would turn SkinSense into an end-to-end skincare companion, and since I have experience building layout-aware OCR systems, I’d love to help implement this module!
A great way to extend the utility of SkinSense is to support users directly at the point of purchase. Even with a precise skin diagnosis, many users find it challenging to navigate the complex chemical names on product labels while standing in a store. For instance, a user who knows they have "Dry Skin" might still struggle to identify specific drying alcohols or harsh sulfates hidden in a long ingredient list. Adding a "Real-Time Checker" would help translate our AI’s diagnosis into confident, safe purchasing decisions in the physical world.
Proposed Solution
I suggest implementing an AI Ingredient Scanner that uses OCR to act as a personal shopping assistant. By utilizing the FastAPI service to handle image-to-text extraction from product photos, we can cross-reference those ingredients against the user’s analyzed skin profile stored in Spring Boot. The React frontend could then display a "Compatibility Score" and highlight any "Red Flag" ingredients using a clean, bento-style UI. This would turn SkinSense into an end-to-end skincare companion, and since I have experience building layout-aware OCR systems, I’d love to help implement this module!