Iris

Detecting Eye-Diseases using ML

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Inspiration

People who have diabetes may develop diabetic retinopathy (DR) which can impair everyday living quality and victims' chances of survival by causing vision loss and blindness. The current inadequate management of ocular diseases is made worse by the inconsistency between clinicians, which is essential for a prompt and accurate diagnosis

What it does

The first signs of fatigue or disease were shown by our eyes. Thus came the design of A.Iris- a web app to accurately detect eye diseases and provide results quickly. A.Iris solves the problem of detecting eye diseases by using advanced machine learning models and a user-friendly interface.

How we built it

Python libraries:

  • pillow
  • tensorflow
  • keras
  • numpy
  • pandas
  • sklearn and more

User interface: Streamlit

API: Openstreetmap

Dataset: Kaggle (ocular-disease-recognition-odir5k)

Challenges we ran into

  • Integrating Models with our Frontend
  • Finding data and Training our Models
  • Using Streamlit
  • Finding ApI's

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