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 Snapshot SDK with Docker.

Use the selector below to generate your Docker command based on country, architecture, and operating system. The parameters for the License Key and Token can be obtained here.

Docker Command Generator

Country:Select countryGlobalThailandGermanyKoreaJapanEgypt
Architecture:Intel x86 or amd64(x64)Intel x86 or amd64(x64) no-avxIntel x86 or amd64(x64) with Nvidia GPUARM based CPUs, Raspberry Pi or Apple M1Nvidia Jetson (with GPU) with Jetpack r32Nvidia Jetson with Jetpack r35ZCU
Host OS of the device:LinuxMacWindows

Restart policyNo (Docker Default)Unless StoppedAlwaysOn Failure

License key:

Token:

Run Command:

List of Docker Images

There are Docker images for various architectures and engine customizations for some countries.

Image structure: platerecognizer/<architecture>:<country>-<version>

• <architecture>
  • alpr for Intel x86 or amd64(x64)
  • alpr-gpu for x86 with Nvidia GPU
  • alpr-raspberry-pi for Raspberry Pi ARM based CPUS or Apple M1.
  • alpr-jetson for Nvidia Jetson (with GPU) with Jetpack r32.
  • alpr-jetson:r35 for Jetson with Jetpack r35.
  • alpr-zcu104 for ZCU.
• <country>:
  • leave blank for global engine
  • thailand
  • germany
  • korea
  • japan
  • egypt
• <version>: leave blank for latest.

To see the list of tags, select an image from Docker Hub and then click "Tags". Here are a couple of examples:

• Image for x86 with a specific version: platerecognizer/alpr:21-09-13
• Image for x86 customized for thailand: platerecognizer/alpr:thailand
• Image for Jetson: platerecognizer/alpr-jetson

Installation

Below, you can check the installation process in detail for various architectures.

info

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

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 --restart="unless-stopped" -t -p 8080:8080 -v license:/license \
  -e TOKEN=YYYYY -e LICENSE_KEY=XXXXX \
  platerecognizer/alpr

tip

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

Installation on a Raspberry Pi

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

4. Get our SDK image. In a terminal run docker pull platerecognizer/alpr-raspberry-pi
5. 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.

4. Get our SDK image. In a terminal run docker pull platerecognizer/alpr-gpu
5. Run the container.

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

docker run --gpus all --restart="unless-stopped" -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 --restart="unless-stopped" -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 currently supports Jetson 4.7.1 and 5.1.1 with revisions R32 and R35. For more Jetson information, check our FAQ.

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

4. Get our SDK image. In a terminal run docker pull platerecognizer/alpr-jetson
5. 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 --restart="unless-stopped" -t -p 8080:8080 \
  -v license:/license -e TOKEN=YYYYY -e LICENSE_KEY=XXXXX \
  platerecognizer/alpr-jetson

tip

• Having problems running the container? Check our Jetson FAQ.

info

Previously available PROCESS_GPU_FRACTION environment variable is no longer supported.

Installation for Kubernetes

Refer to the documentation with Helm charts here

Calling the API