Inspiration
We wanted to create an app that educates users about their skin, promoting informed decision-making and self-care.
What it does
ShineUp utilizes a Custom ML Model to analyze user-uploaded skin images. The app accurately classifies various skin conditions, including acne, milia, keratosis, rosacea, carcinoma, and eczema. Users receive quick, detailed assessments of their skin condition, encouraging prompt action and treatment.
How we built it
We used a skin disease dataset from Kaggle. We created a custom model on CreateML and trained and tested it with numerous iterations. We used OCR technology to extract text from the images of the products.
Challenges we ran into
It was very difficult to achieve the desired accuracy for our ML model and to find the correct dataset with good images of skin conditions.
Accomplishments that we're proud of
We're glad we figured out how to create a custom ML model on Xcode and finished in time. We're also glad we figured out the image-to-text conversion algorithm.
What we learned
We learned a lot about X-code, swift, and ML on this journey.
What's next for ShineUp
We plan to make a few UI changes, add more components and then eventually release the app onto the app store so that everyone can benefit from it!
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