License Plate Recognizer Streamlit

What is License Plate Recognizer Streamlit ?

License Plate Recognizer Streamlit is a Streamlit-based application designed for Automatic Number Plate Recognition (ANPR) or Automatic License Plate Recognition (ALPR). It leverages AI to accurately detect and recognize license plate numbers from images, making it a powerful tool for various applications such as traffic management, parking systems, and security surveillance.

Features

• Accurate License Plate Detection: The application uses advanced AI models to precisely identify and extract license plate numbers from images.
• Real-Time Processing: It supports real-time processing, enabling quick and efficient recognition of license plates.
• User-Friendly Interface: Built with Streamlit, the app offers an intuitive interface for uploading images and viewing results.
• Cross-Platform Compatibility: The application can be run on multiple operating systems, making it versatile for different environments.
• Support for Multiple Image Formats: It accepts various image formats, including JPG, PNG, and BMP.

How to use License Plate Recognizer Streamlit ?

1. Install Streamlit: Ensure you have Streamlit installed in your environment. You can install it using pip:

   pip install streamlit
   

2. Clone the Repository: Download or clone the License Plate Recognitizer Streamlit repository from GitHub.
3. Navigate to the Directory: Open your terminal or command prompt and navigate to the cloned repository directory.
4. Run the Application: Execute the Streamlit app with the following command:

   streamlit run app.py
   

5. Upload an Image: Once the app is running, upload an image containing a license plate.
6. View Results: The application will process the image and display the recognized license plate number.

Frequently Asked Questions

What image formats are supported?
The application supports JPG, PNG, and BMP formats.

Can I edit the recognized license plate number?
No, the application is designed for recognition only. Editing capabilities are not currently available.

How fast is the processing time?
Processing time depends on your system's hardware and the quality of the image. Typically, it takes a few seconds for recognition.