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PROFARM

Machine Learning based Web Project to give Crop Predictions and Yield Predictions on basis of data supplied by user, and an API to get the results for usage in creation of more apps.

Created during Digital Village Hackathon hosted by Thapar Institute of Engg. Technology Patiala, in 2022.

API USAGE

FORMAT
http://profarm.ml/crop-api/<nitrogen>/<phosphorus>/<potassium>/<temperature>/<humidity>/<soilph>/<rainfall>/

RETURNS
Json Body with two fields 
1. crop_name (string)
2. accuracy (float)

Local Deployment on Windows

  1. Copy the dfhmain folder and requirements.txt file to a new folder.

  2. Create a Virtual Environment in the folder using -

pip install virtualenv

virtualenv dfhproject
  1. Enter the Venv
dfhproject\Scripts\activate
  1. Move to dfhmain and install required packages using -
cd dfhmain

pip install -r requirements.txt
  1. Perform migrations
python manage.py migrate
  1. Run the Project
python manage.py runserver

Access the project on https://127.0.0.1:8000

About

A 3-Step Web Application, which allows you to perform Crop Prediction and Yield Calculation based on input parameters using Machine Learning

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  • CSS 42.3%
  • Jupyter Notebook 35.8%
  • SCSS 9.1%
  • HTML 6.4%
  • Python 3.4%
  • JavaScript 3.0%