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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.
Table of Contents
- Demo
- Features
- Installation / Setup
- Usage
- Configuration / Options
- Contributing
- License
- Acknowledgements / Credits
Demo
Main interface for uploading and classifying tea leaf images.
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.