> ## Documentation Index
> Fetch the complete documentation index at: https://avala.ai/docs/llms.txt
> Use this file to discover all available pages before exploring further.

# Classification Tool

> Apply image-level or frame-level labels without drawing any geometry

The Classification tool applies labels at the image level or frame level, without drawing any geometry. Use it for scene-level metadata like weather, lighting, or scene type.

## When to Use

Use classification when:

* You need to label the entire image or frame, not specific objects
* The task involves scene classification (weather, time of day, scene type)
* You need metadata tags for filtering or stratifying datasets
* You want to combine scene-level context with object-level annotations from other tools

Consider a different tool when:

* You need to localize specific objects -- use [Bounding Box](/docs/annotation/guides/tools/bounding-box), [Polygon](/docs/annotation/guides/tools/polygon), or [Segmentation](/docs/annotation/guides/tools/segmentation)
* You need pose estimation -- use the [Keypoint](/docs/annotation/guides/tools/keypoint) tool

## Usage

1. Press `K` or select the **Classification tool** from the toolbar
2. The classification panel appears (or the label panel switches to classification mode)
3. Select one or more labels that describe the image/frame:
   * Weather: sunny, rainy, foggy
   * Scene: highway, urban, parking lot
   * Time of day: daytime, nighttime
4. Classifications are saved automatically when you navigate to the next item

## Multi-Label vs. Single-Label

* **Single-label**: Only one classification can be selected (radio buttons)
* **Multi-label**: Multiple classifications can be selected (checkboxes)

This is configured at the project level when defining the label taxonomy. Check your project setup to understand which mode applies.

## Shortcuts

| Shortcut               | Action                           |
| ---------------------- | -------------------------------- |
| `K`                    | Activate the Classification tool |
| `Ctrl+Z` / `⌘Z`        | Undo                             |
| `Ctrl+Shift+Z` / `⌘⇧Z` | Redo                             |

## Common Mistakes

* **Applying object-level labels at the scene level**: Classification is for the entire image, not for individual objects -- use bounding boxes or polygons for object-level labeling
* **Inconsistent labeling criteria**: Define clear rules for ambiguous cases (e.g., is a cloudy sky with patches of blue "sunny" or "cloudy"?)
* **Forgetting to classify**: Unlike drawing annotations, classification has no visible geometry to remind you -- make sure every image has its classification labels set

## Advanced Tips

* Use classification for metadata that applies to the entire image, not to specific objects
* Combine with object-level annotations: classification for scene context, boxes/polygons for objects
* In video sequences, classification can vary per frame (e.g., lighting changes during a clip)
* Classification labels are useful for building dataset subsets -- filter by scene type to create focused training splits

## Related Tools

* [Bounding Box](/docs/annotation/guides/tools/bounding-box) -- For localizing specific objects
* [Polygon](/docs/annotation/guides/tools/polygon) -- For precise object outlines
* [Segmentation](/docs/annotation/guides/tools/segmentation) -- For pixel-level masks
* [Keypoint](/docs/annotation/guides/tools/keypoint) -- For pose estimation