Classification
The Classification tab is where you define the object populations that your pipelines will detect and measure. Every detected object is assigned to one ore more classes class.
What is a Class?
Section titled “What is a Class?”A class represents a distinct object population in your experiment. Examples:
dapi@nucleus- nuclei stained with DAPIcy5@spot- extracellular vesicles in the Cy5 channelcy7@spot- vesicles in the Cy7 channelcoloc@cy5cy7- vesicles colocalising across both channels
Adding and Editing Classes
Section titled “Adding and Editing Classes”Click the + button to add a new class. Select an existing class and click the Edit button to open the Class Editor, which lets you set:
| Field | Description |
|---|---|
| Name | Class label, e.g. cy5@spot |
| Colour | Display colour used for detected objects in the viewer |
| Notes | Optional free-text description |
Auto-populate from Image Metadata
Section titled “Auto-populate from Image Metadata”Click the Auto button to have EVAnalyzer automatically create classes based on the channel information read from the current image. This creates one class per image channel as a starting point.
Object List
Section titled “Object List”Every image has an Object list panel - labeled “Objects”, with a live count (“N ROIs”) - that lists every object on the current image: both live-preview objects from a pipeline still being edited and objects you’ve added by hand (see Region Annotation).
Each row shows the object’s segmentation label, a chip counting how many other objects share that same label, and up to four stacked color swatches for its assigned classes (a single fallback swatch if it has none yet).
Click a row to select it - the object highlights on the image, and selecting an object directly on the image scrolls the list to match. Click the selected row again to deselect it.
Selected Object Detail
Section titled “Selected Object Detail”Selecting an object expands a detail panel showing:
- Its assigned classes, each with a small × button to remove that class from the object.
- Area, in both pixels² and the physical unit (nm²) derived from the image’s pixel calibration.
- Circularity.
- Per-channel intensity: sum (Σ) and average (μ), with each channel’s name and color shown where available.
Managing Objects
Section titled “Managing Objects”The panel’s footer toolbar, enabled once an object is selected:
- + Class - assigns the class currently selected above to the selected object.
- Delete (trash icon) - removes the object, after a confirmation dialog warning the action can’t be undone.
Hiding Unclassified Objects
Section titled “Hiding Unclassified Objects”The eye icon next to the class count, in this panel’s own header, toggles whether objects with no class assigned are shown in the Object list at all - hidden by default, so a large unfiltered detection result doesn’t drown out the objects you’ve actually classified.
How Classes Relate to Pipelines
Section titled “How Classes Relate to Pipelines”Classes defined here aren’t just labels - they’re what every object-processing pipeline step selects, filters, and reassigns by. See Object Classes for the full lifecycle, from a Threshold entry’s raw segmentation class through to a named class assigned by Classify Objects.