Leaf Classification App

The image classification task is one of the most important applications of AI ,so build an app that can help farmers to detect Potato late blight disease, is an important aplication

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Inspiration

Potato late blight, caused by Phytophthora infestans, is a major disease worldwide that has a significant economic impact on potato crops, and remote sensing might help to detect the disease in early stages. This study aims to determine changes induced by potato late blight in two parameters of the red and red-edge spectral regions: the red-well point (RWP) and the red-edge point (REP) as a function of the number of days post-inoculation (DPI) at the leaf and canopy levelq

What it does

It's Artificial Intelligence App in the field of computer vision, specialized in image Classification task in order to help farmer to detect diseases in their potato crops

How we built it

Sample Steps

  1. Collect images and labell in three main classes. (Potato.Early_blight, Potato_Late_blight,. Potato_healthy)

  2. Train a Convolutional Neural Network to find a accurate model using the keras api

  3. Deploy the model in streamlit

Challenges we ran into

Deploy and register the model

What's next for Leaf Classification App

Deploy the sistem at scale to help farmers detect Potato Light in their Potato crops in Latin America using a cloud provider and a Machine Learning Operation System at scale

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