README.md

Agri-Cure: A Website for Crop Disease Detection and Management

Agri-Cure is a project that provides a website for farmers to help them find and manage crop diseases using machine learning models. It allows farmers to upload images of their crops and get instant diagnosis and recommendations for treatment.

Features

• Crop disease detection using deep learning models
• Crop disease management using best practices and guidelines
• Crop disease information and prevention tips
• User-friendly interface and easy navigation
• Compatible with web and mobile devices

Project Snapshots

How to use Agri-Cure?

To use Agri-Cure, you need to register an account on the website and log in. Then, you can access the following features:

• Upload: You can upload an image of your crop and select the crop type. The website will analyze the image and display the results, including the disease name, severity, and confidence score.
• Diagnosis: You can view the detailed diagnosis of your crop disease, including the symptoms, causes, and effects. You can also see the images of similar diseases for comparison.
• Treatment: You can view the recommended treatment for your crop disease, including the chemical and biological methods, dosage, frequency, and precautions. You can also see the alternative treatments and their pros and cons.
• Information: You can view the general information about crop diseases, such as their types, categories, distribution, and impact. You can also see the prevention tips and best practices for healthy crops.
• Feedback: You can provide feedback on the website's performance, accuracy, and usability. You can also report any errors or bugs you encounter.

Technologies used

Agri-Cure is built using the following technologies:

• Front-end: Vite-ReactJS App
• Back-end: NodeJS
• ML Model: TensorFlow, Keras, PyTorch

Installation

To install and run Agri-Cure on your local machine, you need to follow these steps:

1. Clone the git repository using the command git clone https://github.com/Denver04/Agri-Cure.git.
2. Install all the dependencies for python listed in requirements.txt file using pip install -r requirements.txt.
3. Navigate to the frontend directory using the command cd frontend.
4. Install the dependencies using the command npm install.
5. Start the vite react app using the command npm run dev.
6. Navigate to the backend directory using the command cd ../backend.
7. Install the dependencies using the command npm install.
8. Start the nodejs server using the command npm run dev.
9. Open your browser and go to the URL http://localhost:5173 to view the website.

Contributing

If you would like to contribute to Agri-Cure, please fork the repository and submit a pull request.

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