Freeform Text

Select frame sequences with the video scrubber and write freeform text annotations to train a VLM on temporal reasoning tasks.

Before You Start

Freeform text annotations for videos let you describe what happens across a sequence of frames. You use the timeline scrubber to select a frame range, then write text in any format (JSON, plain text, or custom schemas) that describes the action, event, or scene within that range. This guide walks through creating video freeform text annotations in Datature Vi.


Open the annotator

Go to your dataset, then click the Annotate tab. Click any video thumbnail in the bottom strip to load it into the Video Annotator.

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Open the Annotator tab

Open the Annotator tab

Go to the Dataset Overview page and click the Annotator tab to open the labeling interface.

You should see
Dataset Overview showing video and annotation count

Your annotations are ready when you see annotation count matching the video count in the Dataset Overview.


The timeline scrubber

The timeline scrubber is the core tool for video annotation. It displays the video's frames as a horizontal timeline below the video player.

Frame selection: Drag the start and end handles on the timeline to define a frame sequence. The selected range highlights in color, and the video player shows the current frame within that range.

Playback controls: Use the play/pause button to preview the selected sequence. The frame counter shows your position (e.g., "13 / 49") and the timestamp shows the current time within the video.

Multiple sequences: Each annotation occupies a distinct segment on the timeline, shown as colored blocks. You can create multiple non-overlapping sequences per video, each with its own freeform text annotation.

Navigation: Click anywhere on the timeline to jump to that frame. Use the previous/next frame buttons to step through frames one at a time.


Keyboard shortcuts

Keyboard shortcuts

Key
Action

Annotation guidelines

These guidelines produce annotations that train well for temporal reasoning tasks.

JSON example for action recognition:

{
  "caption": "A Segway bumps over a series of small speed bumps, the rider maintaining balance with slight adjustments.",
  "action": "using segway",
  "physics_rules_followed": [
    "The Segway wheels rotate.",
    "The rider and Segway move forward.",
    "The rider's shadow length changes as the sun's angle changes."
  ],
  "physics_rules_unfollowed": [],
  "physics_rules_cannot_be_determined": [],
  "human_violated_rules": [
    "The Segway should experience a change in speed when going over speed bumps"
  ]
}

Plain text example:

  Caption: A Segway bumps over a series of small speed bumps
  Action: Using segway
  Physics followed: Wheels rotate, forward movement, shadow changes with sun angle
  Physics violated: None
  Human violated: No speed change over speed bumps

Edit or delete annotations

To edit an annotation: Click the corresponding segment on the timeline to select it, then modify the text in the Freeform panel. Changes save automatically.

To adjust frame boundaries: Click a segment on the timeline, then drag the start or end handle to resize it.

To delete an annotation: Click the segment on the timeline, then clear the text in the Freeform panel or use the delete option.

Deletions Cannot Be Undone

Deleted annotations and frame sequences cannot be recovered. Export your dataset regularly as a backup.


Chain-of-thought reasoning


Next steps


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