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metadata
title: PlateVision  YOLO-based License Plate Detection
emoji: 🚗
colorFrom: yellow
colorTo: blue
sdk: streamlit
sdk_version: 1.40.0
app_file: app.py
pinned: false
license: mit

A deep learning tool to classify tea leaves as healthy or unhealthy from images.

MIT License


Table of Contents


Demo

Demo Screenshot Main interface for uploading and classifying tea leaf images.

Demo Video Video walkthrough of the classification workflow.


Features

  • Classifies tea leaf images as healthy or unhealthy using deep learning.
  • Simple, interactive web-based UI for image upload and prediction.
  • Modular codebase for easy extension and retraining.
  • Fast inference for both single and batch image processing.

Installation / Setup

# Create a virtual environment
python -m venv .venv

# Activate it
# On Linux/Mac:
source .venv/bin/activate
# On Windows:
.venv\Scripts\activate

# Install dependencies
pip install -r requirements.txt

Usage

Run the application:

python app.py

This will launch the web interface in your browser.
Upload an image of a tea leaf to get a health classification.


Configuration / Options

  • UI and model configuration can be adjusted in the source files.
  • For advanced settings (e.g., model path, thresholds), edit the relevant Python files.

Contributing

Contributions are welcome!

  • Open issues for bugs or feature requests.
  • Submit pull requests for improvements.
  • Please follow standard Python code style and include tests where possible.

License

This project is licensed under the MIT License. See the LICENSE file for details.


Acknowledgements / Credits

  • Developed by Eslam Tarek.
  • Thanks to the open-source community for libraries and inspiration.