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plant-disease-detection's Introduction

Plant-disease-detection

๐Ÿ“„ Abstract

This data contains images of diseased plant leaves acquired from a specific village in India. We will make use of Deep Learning to detect the type of disease a particular leaf or plant has acquired.

๐ŸŽฏ Objective

We will be deploying the model on an app so that the user can make use of the camera on their cell phone's to capture the image of the plant leaf which in turn will be processed on our trained model to detect the type of disease in that particular plant's leaves.

๐Ÿ“ Major Checkpoints and Pipelines

  • โ›ณ Data Science
    • Data cleaning and pipelining
    • Building a model
    • Training the model
    • Testing the model
    • Improvising the model
    • Saving the model in a pickle file extension
  • โ›ณ Creation of API
    • Importing the Pickle file
    • Testing the API
  • โ›ณ App Development
    • Front End
      • Home page
      • Input integration
    • Back End
      • Integrating the API with the app
      • Integrating a camera in the app
      • Calling of responses for the input.

๐Ÿ“š Tech stack

  • Python
  • GIT
  • Github
  • JAVA
  • XML
  • Android Studio

plant-disease-detection's People

Contributors

shruti8301 avatar nishil07 avatar eshikashah avatar

Watchers

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plant-disease-detection's Issues

Building the Model

  • Choosing the Algorithm
  • Setting the hyper parameters
  • Training the Model
  • Testing the Model
  • Enhancing the model

Creating Data Loaders

  • Importing the dataset
  • Splitting it into test-loaders and train-loaders
  • Handing it over for model making

Understanding the Problem Statement

  • Reading the problem statement.
  • Reading and understanding the dataset
  • Making the ReadME
  • Making the Technology stack
  • Marking the goals to be achieved
  • Analyzing the procedure to be followed
  • Jotting down the expected results.

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