Annotating

All annotation tabs work on the currently selected sample from the Dataset Explorer. The JSON field names below match the canonical OSL JSON Format page.

For samples with a UTC reference, localization events and dense captions use an absolute timestamp_utc as their stable time. The accompanying position_ms is projected onto the current shared media timeline for seeking and legacy compatibility. Adding, removing, filtering, or resynchronizing modalities can change that projected position without changing the annotation's UTC instant. See Synchronized Multi-Modality Playback.

Classification

Use CLS for clip-level labels.

1. Select a sample.
2. Open CLS.
3. Add or choose label heads and labels.
4. Select the label values for the current sample.

Effective manual changes are saved immediately into the sample's labels object. Single-label heads write {"label": "..."} and multi-label heads write {"labels": [...]}. Model predictions remain transient until accepted and rejected.

Localization

Use LOC for point events on the timeline.

1. Select a sample and open LOC.
2. Choose a label head and label.
3. Move the playhead to the event time.
4. Use the spotting controls to add the event.
5. Edit or delete rows in the event table when needed.

Events are stored in events[] with head, label, and position_ms. When the sample has an absolute origin, they also contain an authoritative timestamp_utc. The Time column displays YYYY-MM-DD HH:MM:SS.mmm UTC whenever that instant can be resolved, and otherwise displays relative MM:SS.mmm. Double-click a UTC Time cell to enter an ISO-compatible value, including Z or a timezone offset; the app normalizes it to UTC and updates position_ms for seeking. Inference displays transient confidence-bearing rows; confirming a row keeps the event and removes only the confidence marker.

Description

Use DESC for one or more ordered clip-level captions.

1. Select a sample and open DESC.
2. Select a caption from the list, or click Add Caption.
3. Edit its optional variant, language, and caption text.
4. Wait for autosave or save the project. Use Delete Caption to remove the selected row.

Each row is stored in captions[]. New rows start with lang set to en. Editing a row preserves its position and any optional fields not shown by the editor. This supports variant sets such as auto, clean, and refined.

Run Inference… discovers local or remote captioning models. A returned caption remains unchanged while the candidate is reviewed. Accepting appends it to the caption list; rejecting is non-mutating.

Dense Description

Use DENSE for timestamped text descriptions.

1. Select a sample and open DENSE.
2. Move the playhead to the desired timestamp.
3. Click Add New Description.
4. Enter text in the modal.
5. Edit time or text from the table when needed.

Dense descriptions are stored in dense_captions[] with position_ms, lang, and text, plus timestamp_utc when an absolute origin is available. The Time column follows the same UTC display and ISO-compatible editing rules as Localization, while row selection and media seeking continue to use the projected position_ms. Relative-only samples keep the existing relative-time editor.

Dense inference appends smart rows. Select a predicted row to confirm it as a manual description or reject it. Models may advertise time-range support.

Question/Answer

Use Q/A for grouped questions and one or more answers per question.

1. Select a sample and open Q/A.
2. Click Add to create a question group.
3. Choose a previous dataset question or enter custom question text.
4. Click Answer to add answer text.
5. Double-click or right-click a question or answer to edit or remove it.

Answers are stored as grouped answers[] entries with question and answers[]. The app does not write a top-level questions bank.

Select a question and use Run Inference… to run VQA. An unconfirmed answer carries confidence/model metadata; confirming it converts it to the normal answer string. See Local and Remote Inference.