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
Technologies Used:
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: