CropForesight (Frontend)

This Repository includes the frontend code of the CorpForesight webiste. The frontend of the project is written in HTML, CSS, Javascript, and ReactJS. Before moving ahead, a short intro about the project.

CropForesight🌾

CropForesight is a powerful crop recommendation website that helps farmers and agriculture enthusiasts make informed decisions about the best crop to cultivate on a given land. By utilizing machine learning algorithms and various environmental parameters such as nitrogen value of soil, phosphorus value, rainfall, pH, potassium, humidity, and temperature. CropForesight predicts the optimal crop choice, maximizing productivity and yield.

🌐 Live Demo

Table of Contents

• Features
• Technologies
• Usage
• Local Development
• Deployment
• Contributing
• License

Features

• Intelligent crop recommendation based on soil composition, rainfall, pH, potassium, humidity, and temperature.
• User-friendly interface to input land and environmental parameters.
• Efficient machine learning model leveraging Gaussian Naïve Bayes algorithm.
• Responsive frontend developed using ReactJS for seamless user experience.
• Scalable backend powered by FastAPI for quick data processing.

Technologies

HTML, CSS, Javascript, ReactJS

Usage

To experience the power of CropForesight, follow these simple steps:

✅ Visit the CropForesight website: https://abhijeet141.github.io/CropForesight-FrontEnd/.

✅ Enter the required details such as soil nitrogen value, phosphorus value, rainfall, pH, potassium, humidity, and temperature.

✅ Click on the "Recommend Crop" button to generate the optimal crop recommendation.

✅ Explore the recommended crop and gain insights into its suitability for your land.

Local Development

If you want to contribute to CropForesight or run it locally for development purposes, follow these steps:

1. Clone the frontend repository:

   git clone https://github.com/abhijeet141/CropForesight-FrontEnd.git

2. Change to the project directory:

   cd CropForesight-FrontEnd

3. Install the required dependencies:

   npm install

4. Run the frontend:

   npm start

5. Clone the backend repository:

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

6. Change to the CropForesight_BackEnd directory:

   cd CropForesight_BackEnd

7. Install the required dependencies:

   pip install -r requirements.txt

8. Run the backend:

```sh
 uvicorn main:app --reload

9. Open the website in your browser at http://localhost:3000 to access the local instance of CropForesight.

Deployment

✅ CropForesight's frontend is deployed and can be accessed online at https://crop-foresight-front-end.vercel.app/.

✅ Feel free to explore the website and witness the power of smart crop recommendation firsthand!

Contributing

We welcome contributions from anyone who is interested in improving this project. If you'd like to contribute, here are some ways you can get started:

• Submit a bug report if you find any issues with the application.
• Suggest new features or improvements.
• Submit a pull request to fix a bug or add a feature after an issue is assigned to you.

To submit a pull request, please follow these steps:

1. Fork the Project
2. Clone your forked repository

 git clone https://github.com/<your_github_username>/CropForesight-FrontEnd.git

3. Now go ahead and create a new branch and move to the branch

   git checkout -b fix-issue-<ISSUE-NUMBER>

4. After you have added your changes, follow the following command chain

   • Check the changed files

    git status -s

   • Add all the files to the staging area

     git add .

     or

     git add <file_name1> <file_name2>

   • Commit your changes

    git commit -m "<EXPLAIN-YOUR_CHANGES>"

5. Push your changes

   git push origin fix-issue-<ISSUE-NUMBER>

6. Open a Pull Request

Congratulations! 🎉 you've made your contribution.

GSSOC'23 Issue TimeLine

• Once an issue is assigned,the assignee is expected to submit a pr for review withing a week of the assignment.

• If the assignee fails to comply with the deadline, the issue will be assigned to the next person who had who had requested to be assigned.

GSSOC'23 Pointer System

Level 1 - Documentation/Minor bug fix

Points - 10

• Contributors can update existing documentation, write new documentation for features or code and improve the overall organisation and clarity of the projects documentation.

• Minor bug fixes refer to fixing small isolated issues in the codebase.

• Fixing issues such as typos, brokel links, or minor performance problems.

• Bug fixes are an important part of maintaining stability of and reliability of of an open-source project and every bug fix, no matter how small, contributes to the overall health of the project.

Level 2 - Enhancement of existing features

Points - 25

• Feature or enhancement contributions refer to adding new functionality to an open source project.

• Contributors can add new features, improve existing features, or add new functionality to existing features.

Level 3 - Refactoring/ Adding functionalities

Points - 45

• Core contributions, such as implementing major features or refactoring significant parts of the codebase. This needs a deep understanding of the codebase and its patterns.

Please follow the cotribution guide in all your interactions with the project. We will review your pull request and provide feedback. Once your changes are approved, we will merge them into the main branch.

License

This project is licensed under the MIT License.

Please feel free to modify the sections and add any additional information or badges relevant to your project. Let me know if you need further help.

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