Plant Leaf Disease Detection using Machine Learning

A system which allows the user to upload image of a plant leaf and predict if it is disease affected;

• Demo Video - Web Application: https://drive.google.com/file/d/1X38fXQnTdRsdOka1jJW9CoURDNNgc_V5/view?usp=sharing
• Demo Video - Android Application: https://drive.google.com/file/d/1B_JmcuyiOlUoGolBFFUnIN9XWqElXcH7/view?usp=sharing
• Project Report: https://drive.google.com/file/d/134S-2Es4jajlHdyalZgmlbw77HOLt8VC/view?usp=sharing
• Project Paper: https://drive.google.com/file/d/1P3HJ5hr53-1KexXE0dG7CdUjzEPb7z5g/view?usp=sharing

Plants currently identified:

• Maize
• Corn

Machine Learning Model

• Used Convolution Neural Networks
• Used Tensorflow for builiding the CNN

Rest API's Created

Used pickle to save the ML model and Flask to provide the Frontend as well the API's.

API Route : https://plantdiseaseash.herokuapp.com/train or https://plantdiseaseash.herokuapp.com/test Method: GET Action: Trains the ML model and return the training metrics which can be further used for visualisation.

Method	API ROUTE	Actions
GET	https://plantdiseaseash.herokuapp.com/test or https://plantdiseaseash.herokuapp.com/test	Trains the ML model and return the training metrics which can be further used for visualisation
POST	https://plantdiseaseash.herokuapp.com/predict	Image to be tested is uploaded via a POST request and the predictions are returned.
GET	https://plantdiseaseash.herokuapp.com/getAllDiseases	Returns a JSON object containing list of disease classes.

Hosted on Heroku.com

• Main Prediction Page: https://plantdiseaseash.herokuapp.com/home
• Model Training Visualization : https://plantdiseasetrain.herokuapp.com/