Accurate, fast and easy to use API for license plate recognition. Trained on data from over 100 countries and regions around the world. The core of our license plate detection system is based on state of the art deep neural networks architectures.

Integrate with our ALPR API in a few lines of code. Get an easy to use JSON response with the number plate value of vehicles and the bounding boxes.

• Reading License Plates from Images
  • Lookups For a Specific Region
  • Process Multiple Files (Batch Mode)
  • Running the ALPR Locally (SDK)
• Automatic Image Transfer
• Code Samples
• Number Plate Recognition on a Video

Get your API key from Plate Recognizer. Replace MY_API_KEY with your API key and run the following command:

pip install requests
python plate_recognition.py --api-key MY_API_KEY /path/to/vehicle.jpg

The result includes the bounding boxes (rectangle around object) and the plate value for each plate. The JSON output can easily be consumed by your application.

[
  {
    "version": 1,
    "results": [
      {
        "box": {
          "xmin": 85,
          "ymin": 85,
          "ymax": 211,
          "xmax": 331
        },
        "plate": "ABC123",
        "score": 0.904,
        "dscore": 0.92
      }
    ],
    "filename": "car.jpg"
  }
]

You can match the license plate patterns of a specific region.

python plate_recognition.py --api-key MY_API_KEY --regions fr --regions it /path/to/car.jpg

You can also run the license plate reader on many files at once. To run the script on all the images of a directory, use:

python plate_recognition.py --api-key MY_API_KEY /path/to/car1.jpg /path/to/car2.jpg /path/to/trucks*.jpg

To use a locally hosted sdk, pass the url to the docker container as follows:

python plate_recognition.py --sdk-url http://localhost:8080 /path/to/vehicle.jpg

Monitor a folder and automatically process images (Cloud or SDK) as they are added. It can also forward the results to our parking management service Parkpow.

To get started: python transfer.py --help

See sample projects to use the API in C++, C# or Java. View how to integrate with other languages in our documentation.

To do ANPR on videos, you will also need to install OpenCV. Here are the installation instructions. Those 2 python packages are also needed:

pip install requests
pip install pillow

The script alpr_video.py lets you perform license plate recognition on a video file. It looks at each frame of the video and reads license plates. If you are only interested in one part of the video, you may use the --start and --end arguments. Additionally, you can use the --skip argument to read 1 in every N frames. It will speed up the analysis of large videos. Here's an example:

python alpr_video.py --api MY_API_KEY --start 900 --end 2000 --skip 3 /path/to/cars.mp4

OpenCV is also capable of reading live video streams. See this page for an example.

Have questions? Let us know how we can help.

Provided by Plate Recognizer, a subsidiary of ParkPow.