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VARS Annotation Setup

Configuration

Service Configuration

VARS requires a running backend microservice stack. The vars-quickstart-public project provides a Docker-based setup for all required services. Once the backend is running, do the following:

  1. Download VARS from GitHub
  2. If you're on macOS and get a message that VARS is damaged and can't be opened, that's Apple's Gatekeeper security. To bypass it:
    1. Open a terminal (Terminal.app is in /Applications/Utilities)
    2. cd to where VARS is installed, e.g. cd /Applications
    3. Run sudo xattr -d -r com.apple.quarantine "VARS Annotation.app"
    4. Relaunch VARS Annotation
  3. Point VARS at your configuration server (Raziel).

First, click on the settings button

VARS Annotation 1

Add your configuration server

Enter the URL to your Raziel configuration server along with your VARS username and password.

Configuration Dialog

Test your configuration

Click the Test button to verify the connection. If your dialog looks like the image below, click OK.

Configuration Dialog Success

Video Player Configuration

VARS communicates with external video players via UDP. Both VARS and the video player must be configured to use the same UDP port number.

VARS Port setting

Sharktopoda Port

Sharktopoda Port Setting

Under Sharktopoda > Preferences:

Sharktopoda 2 Network Preferences

Sharktopoda Annotation Settings

If you are working with localizations (bounding boxes drawn directly on video), check these settings in Sharktopoda:

Sharktopoda 2 Annotation Preferences

Machine Learning Configuration

ML Configuration

VARS can send the current video frame to a remote server where machine learning is applied to the image. To configure this, enter the URL of your ML endpoint in the settings dialog.

Machine Learning Endpoint

ML Usage

Click the ML button to send the current frame to the ML service. A window will appear showing proposed annotations. These annotations are not saved to the database until you explicitly accept them.

Machine Learning Button

The ML window displays the captured frame along with the proposed annotations:

Machine Learning Window

You can deselect any proposed annotation using the checkbox next to it, and edit the concept name using the combo box. When you're ready, use one of the three buttons at the bottom:

  1. Cancel — close without saving anything
  2. Save annotations — send the accepted annotations to the database
  3. Save annotations and image — save the annotations and create a framegrab from the ML window