Plant Disease Detection and Diagnosis using Deep Learning

It's a B.Tech Final Year - 2019 Project

Installation

1. Install postgres and complete it's configuration

2. Use the package manager pip for installation and python3.6 or above

3. Create a virtual environment (using virtualenv etc.)

    pip install virtualenv

# We use virtualenvwrapper for easy management of envs
    pip install virtualenvwrapper # for linux
    pip install virtualenvwrapper-win # for windows

# Create virtual environment
    mkvirtualenv env_name
    setprojectdir .     # assuming you are in git-directory

4. Install the requirements

    pip install -r requirements.txt

5. To deactivate the env simply quit the terminal or enter

    deactivate

Usage

1. Copy "trained_models" folders to the path "/app/tf_disease_classifier/trained_models"
2. Set app settings and environment variables
   • rename .env.example to .env and set the values as directed in the file
3. Run the following commands to set migrations:

    python manage.py db init
    python manage.py db migrate -m "Inital commit"
    python manage.py db upgrade

4. Finally run the flask app

    python run.py

Postman environment setup

1. Load 'btp-2019.postman_collection.json' into Postman
2. Create an enviroment and set {key:value} as:
   • key = url
   • value = http://localhost:5000
3. Now test the different apis:
   • first register admin and user
   • use admin to register plants and diseases