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Smart Agri App

This repository contains a Flask server and web application designed for agriculture-related functionalities, such as image-based predictions, leveraging Python, ESP32 hardware, and HTML for UI.

Features

• Image Classification: Uses ResNet for analyzing agricultural images.
• Web Interface: Flask serves as the backend for routing, with templates and static files for the frontend.
• Hardware Integration: Code for ESP32 setup included, enabling remote hardware interaction.

Installation

1. Clone the repo: git clone https://github.com/R3tr0gh057/Agri-project
2. Install dependencies: pip install -r requirements.txt
3. Run the server: python server.py

Usage

• Access the web interface at localhost:80 after starting the server.
• Image predictions are sent in base64 format.
• You can test the prediction algorithm by running python image.py

Directory Structure

• /static: Contains CSS and JavaScript files.
• /templates: HTML templates for the web interface.
• /hardware: ESP32 hardware configuration.

Endpoints

• /predict: accepts POST requests, returns the prediction class of the plant.

License

This project is licensed under the MIT License.

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