https://github.com/arnab-0053/groot-web-app
Groot is a web application that can detect the plant disease just from its leaf.
https://github.com/arnab-0053/groot-web-app
artificial-intelligence flask keras machine-learning nextjs tailwindcss tensorflow webapp
Last synced: 2 months ago
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Groot is a web application that can detect the plant disease just from its leaf.
- Host: GitHub
- URL: https://github.com/arnab-0053/groot-web-app
- Owner: ArNAB-0053
- Created: 2024-03-10T12:52:42.000Z (over 2 years ago)
- Default Branch: main
- Last Pushed: 2024-07-26T05:57:06.000Z (almost 2 years ago)
- Last Synced: 2025-03-01T05:31:36.427Z (over 1 year ago)
- Topics: artificial-intelligence, flask, keras, machine-learning, nextjs, tailwindcss, tensorflow, webapp
- Language: Jupyter Notebook
- Homepage:
- Size: 164 MB
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
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Metadata Files:
- Readme: README.md
Awesome Lists containing this project
README
# Plant Disease Detection System - Groot 🌿
Welcome to the Groot. Groot is a plant leaf disease detection system based on deep learning. It has a training accuracy of 99% and a validation accuracy of 97%, using a model trained with TensorFlow and Keras. The trained model is integrated into a RESTful API with Flask. The system is then developed into a web application using Next.js and Tailwind CSS.
## Overview
This system consists of:
- **Model Training**: Utilizing TensorFlow and Keras, I trained a deep learning model with training accuracy of 99% and a validation accuracy of 97%.
- **API Integration**: Using Flask, I transformed the trained model into a RESTful API for seamless integration.
- **Web Application**: Built with Next.js and Tailwind CSS, the web app provides an intuitive interface for users to upload images and receive instant disease diagnosis.
## Key Features
- **Accurate Diagnosis**: It diagnoses variety of plant diseases with a high degree of accuracy.
- **Health Assessment**: It tells whether the plant is healthy or not.
- **Disease Identification**: Identifies specific diseases that are affecting the plant.
- **Detailed insights**: In case the plant is not healthy, it provides information on the symptoms and management recommendations.
## Demo
Check out the [demo video](https://drive.google.com/file/d/1ZRgELyHVwnB7xa-ZIZw3ZW9_dOqiUeP0/view?usp=sharing) to see the system in action!
## Getting Started
To get started with the Plant Disease Detection System, follow these steps:
1. Clone the repository.
2. Install the necessary dependencies.
3. Run the Flask server to start the API.
4. Launch the Next.js web app and upload images for diagnosis.
## Technologies Used
- TensorFlow
- Keras
- Flask
- Next.js
- Tailwind CSS