Filtering, sorting, and searching data in Encord Active is crucial for various reasons. It enables insights and actionable results on the following key aspects and more:

• Identification of patterns, trends, or anomalies within a subset of the data.

• Recognition of duplicates, outliers, and inconsistencies.

• Removal of irrelevant, noisy, and erroneous data.

• Understanding a model’s behaviour and potential skewness when facing different subsets of the data.

• After filtering, sorting, and searching your data, use Collections with Annotate Projects to streamline your annotation process.

Encord Active provides the following methods:

• Filter: Refine your searches using quality metrics, Collections, data types, annotation types, annotation classes, and by annotator from Annotate. This includes filtering by nested attributes within annotation classes.

• Sort: Sort your data/labels/predictions, in ascending or descending order, using quality metrics.

• Natural language and image search: Enter descriptive queries in everyday language or use images to make it easier to find relevant images without the need for specific keywords or complex search parameters.

• Embedding plot: A two-dimensional visualization technique used by Encord to represent high-dimensional data in a more interpretable form. Use the plot to select points within a specific rectangular area, thereby focusing on a particular subset of data points for in-depth analysis.

​

Filters

In the Active Explorer for a Project you can refine searches by data quality metrics, label quality metrics, Collections, data types, annotation types, annotation classes, and by annotator from Annotate.

Collections: Collections are a new way to save interesting groups of data units and labels, to support and guide your downstream workflow.

Custom Metadata: Custom metadata added to Annotate Projects. When an Annotate Project imports to Active, if that Annotate Project has custom metadata, the custom metadata is available to filter your data in Active.

Custom embeddings: Data, labels, and Predictions can be filtered by custom embeddings.

Annotation invalid: Data, labels, and Predictions can be filtered by: Well-formed Annotation and Invalid Annotation

Annotation Type:: Data, labels, and Predictions can be filtered by: classification, bounding box, rotatable bounding box, point, polyline, polygon, skeleton, and bitmask.

Annotator:: Data, labels, and Predictions can be filtered by the person who annotated the images/videos.

Class: Data, labels, and Predictions can be filtered by annotation class.

Data title: Data, labels, and Predictions can be filtered by the name of the data unit.

Data Types: Data, labels, and Predictions can be filtered by: images, image sequences, image groups, DICOM series, audio files, and videos.

Dataset: Datasets included in an Annotate Project.

Manual Annotation: Data, labels, and Predictions can be filtered by: Manual Annotation and Automated Annotation.

Prediction IOU: Data, labels, and Predictions can be filtered by Prediction IOU.

Priorities: Data, labels, and Predictions can be filtered by the priority specified in Annotate.

Workflow stage: Data, labels, and Predictions can filter by non-Consensus stages (data, labels, and annotators) and Consensus stages (data only).

To filter data, labels, or predictions:

1. Log in to the Encord platform. The landing page for the Encord platform appears.

2. Click Active in the main menu. The landing page for Active appears.

3. Click the Project. The landing page for the Project appears with the Explorer tab selected.

4. Select Data, Labels, or Predictions.

5. Click Filters. The Filters tab appears.

6. Click Add Filter. A menu appears.

7. Add and configure the filters you need. Images/video filter in the Explorer workspace.

​

Filter Nested Attributes

Active supports filtering on the top level Classes and nested attributes on both Objects and Classifications. Supports up to seven levels of depth.

To filter nested attributes:

1. Log in to the Encord platform. The landing page for the Encord platform appears.

2. Click Active in the main menu. The landing page for Active appears.

3. Click the Project. The landing page for the Project appears with the Explorer tab selected.

4. Select Data, Labels, or Predictions.

5. Click Filters. The Filters tab appears.

6. Click Add Filter. A menu appears.

7. Select Class.

   

8. Select the class and the nested attribute for the class.

​

Preset Filters

Preset filters provide a way to save your filtering criteria for use and reuse on other Projects. Preset filters are made up of global and local filter criteria.

Global filter criteria are filters, and their settings, that can apply to any Project. For example, Data Quality Metrics like Area, Blue Value, and Sharpness or Label Quality Metrics like Annotation Quality, Confidence, or Label Duplicates.

Local filter criteria are filters that can only be applied to a specific Project. For example, the following filters and their settings are likely only applicable to a specific Project: Class, Dataset, or Collection.

​

Create a Preset Filter

Create Presets (Preset Filters and their settings) from the Filter tab in your Projects.

​

Use a Preset Filter in a Project

Once you have created one or more Preset Filters, you can apply them to any of your Projects from the Filter tab.

​

Sorting

Sort your data, in ascending or descending order, using data quality metrics. Sort your labels or predictions, in ascending or descending order, using label quality metrics.

To sort data, labels, or predictions:

1. Log in to the Encord platform. The landing page for the Encord platform appears.

2. Click Active in the main menu. The landing page for Active appears.

3. Click the Project. The landing page for the Project appears with the Explorer tab selected.

4. Select Data, Labels, or Predictions.

5. Select the metric to sort the data.

6. Specify ascending or descending order.