LeafCare Image Analysis

LeafCare Image Analysis is a Streamlit-based application wrapped in a Docker container designed to classify plant diseases from images. This application uses a pre-trained Convolutional Neural Network (CNN) to predict the type of disease affecting a plant based on its leaf image.

Features

• Image Upload: Users can upload images of plant leaves to diagnose potential diseases.
• Disease Prediction: Utilizes a trained CNN model to classify diseases from images.
• Interactive UI: Built with Streamlit, offering an intuitive user interface for easy interaction.

Interactive Web App

For an interactive experience, you can visit and use the web application hosted on Hugging Face Spaces at LeafCare on Hugging Face Spaces.

Getting Started

These instructions will get you a copy of the project up and running on your local machine for development and testing purposes.

Prerequisites

You need to have Docker installed on your machine to run the application in a container.

• Install Docker

Installation

Clone the repository to your local machine:

git clone https://https://github.com/Shubham235Chandra/LeafCare-Image-Analysis.git
cd into-the-project-directory

Build the Docker image:

docker build -t leafcare-image-analysis .

Run the Docker container:

docker run -p 8501:8501 leafcare-image-analysis

Accessing the Application

Once the container is running, you can access the application by navigating to http://localhost:8501 in your web browser.

Built With

• Python - The programming language used.
• TensorFlow - The machine learning framework used.
• Streamlit - The web framework used.
• Docker - Containerization platform.

Contributing

Please read CONTRIBUTING.md for details on our code of conduct, and the process for submitting pull requests to us.

Versioning

We use SemVer for versioning. For the versions available, see the tags on this repository.

Authors

• Your Name - Initial work - YourGitHub

See also the list of contributors who participated in this project.

License

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

Credits

• Shubham Chandra - Project Lead and Developer

Dataset

This project uses the PlantVillage Dataset hosted on Kaggle, which contains images of plant leaves categorized by disease types.