/CropForesight_BackEnd

Primary LanguagePython

CropForesight BackEnd

The repository for the backend of the Crop Foresight project made using Pydantic and FastAPI.

By using various parameters like Nitrogen, Phosphorous, Potassium, rainfall, humidity, temperature and pH it predicts the most optimal crop for the land from among 22 crops ranging from rice or apples to cotton or lentils using a Gaussian Naive Bayes model


Table of Contents

  1. Technologies Used
  2. Running the Project Locally
  3. Contributing
  4. License
  5. Deployment

Technologies Used:

FastAPI scikit-learn Pandas NumPy

Runnning the Project Locally:

Clone the backend repository:

git clone https://github.com/abhijeet141/CropForesight_BackEnd.git

Change to the CropForesight_BackEnd directory:

cd CropForesight_BackEnd

Install the required dependencies:

pip install -r requirements.txt

Run the backend:

uvicorn main:app --reload
Open the website in your browser at http://localhost:3000.

Contributing

Refer to the contribution guidlines here

License

The entire project is licensed under the MIT License

Deployment

You can access the deployed frontend at:

https://crop-foresight-front-end.vercel.app/.