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Plant disease detection using Machine Learning. This is an open source project that is a continuation from @imskr open source work https://github.com/imskr/Plant_Disease_Detection

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Plant Disease Detector 2.0


Models are trained on the preprocessed dataset which can be downloaded here.

Local Set-Up

Local:

  • It is recommended to set up the project inside a virtual environment to keep the dependencies separated.
  • Activate your virtual environment.
  • Install dependencies by running pip install -r requirements.txt.
  • Start up the server by running python app/server.py serve.
  • Visit http://localhost:8080/ to explore and test.

Docker:

Make Sure the Docker is installed in your local Machine. Click Here to know that how to install Docker.

  • Mac:

    $ git clone 
    $ cd Plant_Disease_Detection
    $ docker build -t fastai-v3 .
    $ docker run --rm -it -p 8080:8080 fastai-v3

    Go to http://localhost:8080/ to test your app.

  • Windows:

    $ git clone 
    $ cd Plant_Disease_Detection
    $ docker build -t fastai-v3 .
    $ docker run --rm -it -p 8080:8080 fastai-v3

    Go to http://localhost:8080/ to test your app.

    Note: Windows 10 Pro required.

  • Linux:

    $ git clone 
    $ cd Plant_Disease_Detection
    $ docker build -t fastai-v3 .
    $ docker run --rm -it -p 8080:8080 fastai-v3
    

    Note: If this doesn't work use --no-cache flag in the build command.

    Go to http://localhost:8080/ to test your app.

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Plant disease detection using Machine Learning. This is an open source project that is a continuation from @imskr open source work https://github.com/imskr/Plant_Disease_Detection

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