Cropify is a web application built with React that aims to assist farmers in optimizing their crop yield and diagnosing plant diseases. By leveraging machine learning models such as Convolutional Neural Networks (CNN), Naive Bayes, Light Gradient Boosting Machine (Light GBM), and Decision Trees, Cropify offers predictive insights to farmers based on input data, including images of plant leaves.
Cropify offers the following key features:
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Yield Prediction: Predicts the potential yield for various crops based on factors such as soil quality, weather conditions, and historical data.
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Disease Detection: Utilizes image recognition techniques powered by CNN to identify diseases affecting plant leaves accurately. Farmers can upload images of plant leaves, and Cropify will diagnose the disease and recommend appropriate treatments.
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Crop Recommendation: Recommends the best crop to cultivate on the farmer's land based on soil type, climate, and other environmental factors. This recommendation is generated using machine learning algorithms such as Naive Bayes and Decision Trees.
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Fertilizer Recommendation: Suggests the most suitable fertilizer for a particular crop and soil type, enhancing crop productivity and minimizing resource wastage.
To run Cropify locally, follow these steps:
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Clone this repository to your local machine.
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Navigate to the project directory.
cd Cropify
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Install dependencies using npm or yarn.
npm install
yarn install
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Start the development server.
npm start
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Open your web browser and navigate to http://localhost:3000 to access Cropify.
Cropify is built using the following technologies:
- React: Frontend JavaScript library for building user interfaces.
- TensorFlow.js: JavaScript library for training and deploying machine learning models in the browser.
- Node.js: JavaScript runtime environment for executing server-side code.
- Express: Web application framework for Node.js used for building the backend API.
- CNN, Naive Bayes, Light GBM, Decision Trees: Machine learning models used for yield prediction, disease detection, crop recommendation, and fertilizer recommendation.
We welcome contributions from the community to enhance Cropify further. If you'd like to contribute, please follow these guidelines:
- Fork the repository on GitHub.
- Create a new branch for your feature or bug fix.
- Make your changes and commit them with descriptive messages.
- Push your changes to your fork.
- Submit a pull request to the main repository's develop branch.
This project is licensed under the MIT License.
We would like to thank the following individuals and organizations for their contributions to Cropify: