Interface Layout
When you open a dataset, the exploration interface loads with five main areas:| Area | Component | Description |
|---|---|---|
 | Navigation Tabs | Switch between Explore, Data, and Views |
 | Filter Panel | Apply and combine search criteria to narrow your dataset |
 | Action Bar | Access operations like export, share, and selected items management |
 | Details Sidebar | View metadata, insights, statistics, and access enrichment features |
 | Content Grid | Visual representation of your data in clusters, images, or objects |
Navigation Tabs
Three tabs organize your workflow when exploring datasets:| Tab | Purpose | Use Cases |
|---|---|---|
| Explore | Navigate your dataset using clusters, search, and filters | Browse patterns, find similar images, identify quality issues |
| Data | View all images in a flat grid without clustering | Review entire dataset linearly, perform bulk selections |
| Views | Access saved filter combinations and search queries | Quickly load previously defined queries, share analysis criteria with team |
Exploration Workflow
Effective dataset curation typically involves a multi-step process rather than a single query. These steps explain how to combine Visual Layer’s tools to move from broad discovery to a precise, curated selection.Find: Discover Relevant Content
Start by casting a wide net to locate potential candidates.
- Use Semantic Search for conceptual queries (e.g., “damaged packaging” or “outdoor crowd”).
- Use Cluster Navigation to browse high-level patterns without a specific query.
- Use Visual Search with an external image upload to find matches for a reference asset.
Narrow: Refine Your Results
Filter out irrelevant matches to focus on your specific criteria.
- Apply Visual Similarity on a specific search result. Crop a region (e.g., just the defect, not the background) to narrow the search visually.
- Add Metadata Filters (Folders, Labels, Dates) to restrict the search scope to relevant batches or sources.
Refine: Identify Distinctive Content
Ensure your selection represents the diversity of your data, not just the most common examples.
- Apply the Uniques Filter to hide repetitive content. Increasing the threshold surfaces only visually distinct items, covering edge cases and varied angles rather than just the average.
- Check Outliers to find rare examples or anomalies that might be missing from the main clusters.
Clean: Remove Redundancy and Issues
Polish the collection before finalizing.
- Review Duplicates to select single representative frames from burst sequences or near-identical backups.
- Filter Quality Issues (blur, dark, bright) to automatically exclude unusable or low-quality assets.
Organize: Save and Share
Preserve your work for the team.
- Save as View to capture the full combination of search queries, filters, and thresholds. Team members can access the dynamic collection without rebuilding the logic.
- Export the selection to JSON or CSV for downstream training or annotation workflows.