License Plate Recognition is a computer vision project that utilizes OpenCV to detect and extract license plate regions from a live video feed or recorded video. It applies a Haar cascade classifier trained on license plate images to identify and draw bounding boxes around license plates in real-time.
To run the License Plate Recognition project, you need the following dependencies:
- Python 3.x
- OpenCV (cv2 module)
- NumPy
You can install the required dependencies using pip:
pip install opencv-python numpy
- Clone the repository:
git clone https://github.com/your-username/license-plate-recognition.git
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Navigate to the project directory:
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Download the SAmple video in link:"https://drive.google.com/file/d/12sBfgLICdQEnDSOkVFZiJuUE6d3BeanT/view"
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Run the
main.pyscript: -
The program will start capturing video from the default camera. It will detect license plates in the video feed and draw bounding boxes around them. If a license plate is detected, you can press the 'a' key to save the corresponding region of interest (ROI) as an image.
Contributions to the License Plate Recognition project are welcome! If you find any issues or have suggestions for improvements, feel free to open an issue or submit a pull request.
This project is licensed under the MIT License.