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CNN Based model to classify Plant Leaf Diseases. Used Flask for the front-end and hosted on Heroku.

License: MIT License

JavaScript 0.20% Python 1.99% CSS 1.57% HTML 7.57% Jupyter Notebook 88.66% Procfile 0.01%

plant-leaf-disease-detection's Introduction

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;

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

plant-leaf-disease-detection's People

Contributors

ashishsalaskar1 avatar dependabot[bot] avatar imgbot[bot] avatar

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