This project demonstrates how to perform number plate detection and extraction using YOLOv5 for object detection, Tensorflow for Model Training and Pytesseract for optical character recognition.

The goal of this project is to develop a system that can detect and extract number plates from images. The system utilizes the YOLOv5 object detection algorithm to locate the number plates in an image. Once the number plates are detected, Pytesseract is used to extract the text from the number plates.

1. Clone the repository:

   git clone https://github.com/shaadclt/NumberPlate-Detection-Extraction.git

2. Install the required dependencies:

   pip install -r requirements.txt

3. Install Tesseract

You can either Install Tesseract via pre-built binary package or build it from source.. A C++ compiler with good C++17 support is required for building Tesseract from source.

1. Run the following command to perform number plate detection and extraction on images:

   python app.py

The results of the number plate detection and text extraction will be displayed.

Here are some examples of the output generated by the system:

Contributions are welcome! If you have any suggestions or improvements, please open an issue or submit a pull request.

This project is licensed under the MIT License.

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