Skip to content

Trep48/Smart-Crop-Recommendation-System

Folders and files

NameName
Last commit message
Last commit date

Latest commit

 

History

1 Commit
 
 
 
 
 
 
 
 
 
 
 
 

Repository files navigation

# Smart Crop Recommendation System

The Smart Crop Recommendation System is designed to help farmers choose the best crop to grow based on various factors. This README provides detailed instructions on how to set up, run, and contribute to the project using terminal commands.

## Table of Contents

1. [Clone the Repository](#clone-the-repository)
2. [Create an Environment](#create-an-environment)
3. [Activate the Environment](#activate-the-environment)
4. [Install Dependencies](#install-dependencies)
5. [Generate Model](#generate-model)
6. [Run the Application](#run-the-application)
7. [License](#license)

## Clone the Repository

First, clone the repository to your local machine:

```sh
git clone https://github.com/Rvssm-Sandeep/Udyog-Saarathi-Application.git
cd Udyog-Saarathi-Application

Create an Environment

Create a project folder and a virtual environment within it:

mkdir myproject
cd myproject
py -3 -m venv .venv

Activate the Environment

Before you work on your project, activate the corresponding environment:

On Windows:

.venv\Scripts\activate

On macOS and Linux:

source .venv/bin/activate

Install Dependencies

Install the necessary dependencies:

pip install flask
pip install pandas
pip install scikit-learn

Generate Model

Run the Jupyter Notebook file to generate the .pkl file required for the model:

  1. Open Jupyter Notebook:
    jupyter notebook
  2. Run the cells in your .ipynb file to train the model and save it as a .pkl file.

Run the Application

Finally, run the application:

python app.py

Click on the development server link provided in the terminal to open the application in your browser.

That's it!

License

This project is licensed under the MIT License - see the LICENSE file for details.


This single README file includes all the necessary steps to clone the repository, create and activate a virtual environment, install dependencies, generate the model, and run the application. It ensures that anyone following the instructions will be able to set up and run your Smart Crop Recommendation System successfully.

About

No description, website, or topics provided.

Resources

Stars

Watchers

Forks

Releases

No releases published

Packages

No packages published