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Manual Installation Steps

If for some reason, you prefer not to use Plate Recognizer Installer, you can go through the steps below to manually install Stream with Docker.

danger

For the commands below, make sure to change XXXXX to the License Key and YYYYY to your Plate Recognizer Token. Get your token and license key.

List of Docker Images#

If you want to use a specific version of the software, set a tag. For example, platerecognizer/alpr:21-09-13. To see the whole list, select an image from Docker Hub and then click "Tags".

  • Intel x86 platerecognizer/alpr
  • Raspberry Pi platerecognizer/alpr-raspberry-pi
  • Nvidia Jetson (with GPU) platerecognizer/alpr-jetson
  • Intel x86 with Nvidia GPU platerecognizer/alpr-gpu
  • ZCU platerecognizer/alpr-zcu104

We have country specific images. To use those, add a tag to the image. For example, platerecognizer/alpr:thailand. Possible choices are

  • thailand, germany, korea, japan

Installation on an Intel CPU#

Abbreviated installation steps below. For a detailed, step-by-step guide, see the Install Docker and SDK on Windows and the associated FAQ for help.

  1. Sign up and log in.
  2. Subscribe to a SDK plan.
  3. Install Docker on your local machine. See requirements.
  4. Get our SDK image. In a terminal run docker pull platerecognizer/alpr
  5. Install and run the container:
docker run --rm -t -p 8080:8080 -v license:/license \  -e TOKEN=4805bee*********** -e LICENSE_KEY=AX******** \  platerecognizer/alpr
tip

If you use the engine for Thai vehicles, replace platerecognizer/alpr by platerecognizer/alpr:thailand.

Calling the API#

The container exposes a REST interface. To verify that the installation was successful, run those commands in a new terminal.

:: Get a picturecurl -o car.jpg https://app.platerecognizer.com/static/demo.jpg:: And read the license platecurl -F "[email protected]" http://localhost:8080/v1/plate-reader/

Installation on a Raspberry Pi (Armv7)#

Follow the steps 1) to 3) of the standard installation instructions.

  1. Get our SDK image. In a terminal run docker pull platerecognizer/alpr-raspberry-pi
  2. Run the container. Initialization can take up to 10-20 seconds. Use the command 5) but with image platerecognizer/alpr-raspberry-pi

Installation for Desktop GPU (Nvidia Only)#

If you have an Nvidia Jetson, follow these instructions. Make sure you have installed the right Nvidia drivers and have Nvidia-docker installed. Tested with drivers version 450. Follow the steps 1) to 3) of the standard installation instructions.

  1. Get our SDK image. In a terminal run docker pull platerecognizer/alpr-gpu

  2. Run the container.

    Option 1 (new version of nvidia-docker), notice the --gpus all:

docker run --gpus all --rm -t -p 8080:8080 -v license:/license -e TOKEN=YYYYY -e LICENSE_KEY=XXXXX platerecognizer/alpr-gpu
Option 2 (Deprecated nvidia-docker2 version): 
docker run --runtime nvidia --rm -t -p 8080:8080 -v license:/license -e TOKEN=YYYYY -e LICENSE_KEY=XXXXX platerecognizer/alpr-gpu

Installation for Nvidia Jetson#

Configure the Nvidia Jetson according to the official Jetson Nano Developer Kit Guide. Our image has been tested on Jetpack 4.6. For more Jetson information, check our FAQ.

Follow the steps 1) to 3) of the standard installation instructions.

  1. Get our SDK image. In a terminal run docker pull platerecognizer/alpr-jetson
  2. Run the container. The initial prediction can take up to 2-3 minutes. After the first prediction, inference speed is around 300ms.
docker run --runtime nvidia --rm -t -p 8080:8080 -v license:/license \  -e PROCESS_GPU_FRACTION=0.25 -e TOKEN=YYYYY -e LICENSE_KEY=XXXXX \  platerecognizer/alpr-jetson
tip
  • Having problems running the container? Check our Jetson FAQ.
  • Memory consumption may be high by default. You can control the amount of memory used with PROCESS_GPU_FRACTION.

Installation for Kubernetes#

Refer to the documentation with Helm charts here