Automatic License Plate Recognition (ALPR, ANPR) on Kubernetes

Get high-accuracy, developer-friendly automatic license plate recognition (ALPR) or automatic number plate recognition (ANPR) on Kubernetes!

Our machine-learning software:

• Works on dark, low-res, blurry images and tough angles, all vehicle types, etc. See our full ALPR results.
• Decodes license plate , vehicle type (e.g. SUV, van, pickup truck), vehicle make model (e.g. Honda Accord), color, and orientation. Ignores bumper stickers, car signs, etc.
• Is optimized for all 50 USA States, India, Brazil and 90+ countries worldwide.

Get license plate reader deployed on Kubernetes using Helm Charts in under 60 minutes:

• Access a simple REST API for easy integration in 8 programming languages.
• Returns results via JSON Response or Webhooks.
• Has fast inference speed up to 21 ms.
• Runs on-premise on Linux, Windows, Mac, Jetson , Kubernetes, Raspberry Pi, Zynq, 96Boards, LattePanda and more.

ALPR, ANPR software on Kubernetes is ideal for parking, toll, police surveillance, community security, and other use cases.

Our license plate recognition (LPR) software can also forward results to our full ALPR Dashboard and Parking Management software solution, ParkPow.

Sign up for a Free Trial now (no credit card required) or learn more at https://platerecognizer.com.

Installation

Instructions to install the Plate Recognizer SDK on your Kubernetes cluster.

1. Contact support to enable Kubernetes for your account.
2. Get helm from https://github.com/helm/helm/releases
3. Setup your Kubernetes cluster. For example, https://kubernetes.io/docs/tasks/tools/install-minikube/
   • If using Minikube, make sure to enable the following addons dashboard ingress helm-tiller
4. Clone this repository git clone https://github.com/parkpow/helm-charts.git and cd helm-charts
5. Install the chart helm install platerec-sdk platerec-helm/ --set TOKEN=<MY_TOKEN> --set LICENSE_KEY=<LICENSE_KEY>

Configuration

• To upgrade the chart, do helm upgrade platerec-sdk platerec-helm/ --set TOKEN=<MY_TOKEN> --set LICENSE_KEY=<LICENSE_KEY>
• To delete the deployment, do helm delete platerec-sdk
• To use the gpu version instead of the cpu version, do helm install platerec-sdk platerec-helm/ --set TOKEN=<MY_TOKEN> --set LICENSE_KEY=<LICENSE_KEY> --set image.repository=platerecognizer/alpr-gpu
• To deploy to a different namespace other than default, include --namespace <namespace-name> to the install/upgrade command as so helm install platerec-sdk platerec-helm/ --namespace <namespace-name> --set TOKEN=<MY_TOKEN> --set LICENSE_KEY=<LICENSE_KEY>

---

Configurations variables that can be changed (by adding them to the install command using --set parameter)

Parameter	Description	Default	Options
TOKEN	PlateRecognizer Token (required)	nil
LICENSE_KEY	PlateRecognizer SDK License (required)	nil
replicaCount	Number of Pods to run	1
image.repository	Plate Recognizer sdk	platerecognizer/alpr	[platerecognizer/alpr, platerecognizer/alpr-gpu]
image.pullPolicy	Image pull policy	Always	[Always, IfNotPresent]
image.pullSecrets	Specify docker-registry secret names as an array	[]	True
service.annotations	Service annotations	{}
service.type	Kubernetes Service type	ClusterIP	[LoadBalancer, ClusterIP]
service.port	Service HTTP port	8080
persistence.enabled	Enable persistence using PVC	False
persistence.existingClaim	Enable persistence using an existing PVC	nil
persistence.storageClass	PVC Storage Class	nil (uses alpha storage class annotation)
persistence.accessMode	PVC Access Mode	ReadWriteOnce	[ReadWriteMany, ReadWriteOnce ]
persistence.size	PVC Storage Request	10Gi

Minikube Notes

To access the instance when using a custom cluster in Minikube, run the following command:

• Simulate a load balancer minikube tunnel
• Then run the commands shown after the helm install command.
• You can also use this command to get the extenal_id kubectl get --namespace default svc -w platerec-sdk-test-platerec-helm
• Finally call the SDK endpoint with curl -F 'upload=@/path/to/car.jpg' http://<external_ip>:8080/alpr