Filter dataset
Use filters to narrow down, explore, and manage your dataset more effectively. Filters can be applied based on labels, tags, objects, issues, and more.
How this Helps
Filtering helps you instantly surface relevant slices of your dataset — whether you’re tracking mislabels, inspecting object classes, or exploring edge cases like blurry or low-light frames.
Visual Layer provides a flexible filtering system powered by logical structures. You’ll build filters in the Filter Menu, define them in the Query Modal, and review or edit them in the Query Panel.
Filter Menu
The Filter Menu is where you select filters to apply. It dynamically adapts to your dataset and the context of your view.
Available filter types include:
- Labels
- Object Labels
- User Tags
- Captions
- Duplicates
- Mislabels
- Outliers
- Quality Issues (e.g., Blurry, Bright, Dark)
- File Type
- Folder
The filters shown change depending on your current logic mode and view context.
Query Modal
Each filter opens a Query Modal, where you can configure:
- Condition: IS, IS NOT, CONTAINS, STARTS WITH, ENDS WITH and more
Conditions and input options vary by filter type.
Query Panel
The Query Panel shows all active filters, grouped by AND logic.
Filter Logic & Behavior
Filter Type | Supported Logic |
---|---|
Text Search | CONTAINS, DOES NOT CONTAIN |
Labels | IS, IS NOT, IS ONE OF |
Object Labels | IS, IS NOT, IS ONE OF |
User Tags | IS, IS NOT, IS ONE OF |
Captions | CONTAINS, DOES NOT CONTAIN |
Duplicates | IS |
Outliers | IS, IS NOT |
Mislabels | IS, IS NOT |
Quality Issues | IS, IS ONE OF |
File Type | IS |
Folder | IS, IS NOT, STARTS WITH, ENDS WITH |
Advanced Features
Cluster Navigation vs Filtering
Clusters are now fully decoupled from filters. You can enter a cluster to explore it without applying a filter based on that cluster.
Removing Filters
Users can delete any active filter, which will remove it from the query structure, allowing you to refine your dataset exploration further.