Setting Up Private Filters (Repo or Reg)
Private Filters enable users to deploy and manage custom computer vision filters within their environments. These filters can be sourced from various Helm repositories or Docker registries.
Setting Up a Private Docker Registry
You may need to set up a private Docker registry to utilize private filters. You can achieve this using the FilterBox CLI or Kubernetes command-line tools (kubectl).
Using FilterBox for Docker Registry Setup
Step 1: Create a Kubernetes Secret for Docker Registry Credentials:
Use this command to initiate the setup.
You'll be prompted to enter your Docker Registry Server Configuration, including the server
URL, username
, password
, email
, and secret-name
.
Example Input:
This process creates a Kubernetes secret, plainsight-jfrog-test
, within the plainsight
namespace, enabling secure access to your private Docker registry.
Step 2: Create a values.yaml file to specify your filter configuration
Create a values.yaml
file specifying your filter configurations, including the video source (deviceSource
), Docker image (imageOverride
), and the newly created registry secret (imagePullSecrets
).
Example values.yaml:
Step 3: Deploy Your Private Filter
Use this command to deploy a Filter utilizing the configurations specified in the values.yaml
file:
-n plainsight
specifies the Kubernetes namespace where the filter should be deployed, which should match where the secret is stored.detect-cam1
is the name given to this particular deployment of the filter.plainsight-technologies/filter
is the Helm chart that defines how the filter application should be deployed.--version 0.18.0
specifies the version of the Helm chart to use.-f ./values.yaml
tells Helm to use the configurations provided in thevalues.yaml
file.
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