Skip to content

AI Image Tagging

Image Tagging describes what is in your video frames using AI, adding the results as searchable keywords. It is the broadest of the three AI options: where scene classification picks one setting and object detection finds a fixed set of 80 object types, image tagging recognises a broad, open vocabulary of scenes, objects, settings and activities — for example beach, kitchen, crowd, airplane, sunset, construction site.

It runs from the AI Scenes batch tool, alongside scene classification and object detection. Detected tags become orange keywords on the thumbnail and video.

Download the model (first use)

Image tagging uses a model that is downloaded on demand, so it is not part of the installer. The first time you want to use it:

  1. Open AI models (from the start page, or Manage AI models... in Preferences).
  2. Under Image tagging, click Download.

The model is stored per user and works without admin rights. Once downloaded, the Image Tagging option becomes available in the AI Scenes tool.

Tag your videos

  1. Right-click a video (or use the start page) and choose Classify Scenes... to open the AI Scenes tool.
  2. Tick Image Tagging. You can combine it with scene classification and object detection, or use it on its own.
  3. Set the Tag sensitivity. Higher values give fewer, more confident tags; lower values tag more freely. The default (3.0) is a good starting point — raise it if you see tags that don't belong, lower it if frames you expect to be tagged come back empty.
  4. Choose which videos to process and the frame skip, then click Start.

Tags appear as orange keywords. Search for them like any other keyword, and manage them in the Keyword Manager (they show up with the type Tag).

While processing, each tag is listed with a z-score — how far above the sensitivity threshold it scored — so a higher number means a stronger, more confident match (a clear subject might score around 5, while a borderline one sits just above your sensitivity value).

Tips

  • Tagging looks at the whole frame, so it captures scenes and settings, not just distinct objects — a good complement to object detection.
  • If a catalog tags too much or too little overall, adjust the Tag sensitivity and re-run; there is no need to re-download anything.
  • Tagging is heavier per frame than object detection. Use the frame-skip setting to keep large catalogs fast — you rarely need every thumbnail tagged.

Troubleshooting

The Image Tagging checkbox is greyed out -- the model isn't downloaded yet. Get it from the AI models dialog (see above).

Too many or too few tags -- adjust the Tag sensitivity slider and re-run. Higher = fewer, stronger tags.

Common subjects like people or faces aren't tagged -- because they appear in so many frames, the AI needs a stronger-than-usual signal to tag them, so they can come back empty at the default sensitivity. Lower the Tag sensitivity if you want these tagged.