The following video goes through the basics of annotating images in the Label Editor.
Encord provides comprehensive support for image annotation. With the image editor, you can:
Before we get into the details of the label editor and making annotations, a quick note about scheduling annotation work. Annotation is done in the annotation phase of the task management system. In order to ensure annotation work is saved properly, it’s crucial that each labeling task is properly assigned to an annotator, annotators always access the task through the Queue tab in the Task Management System, and only the assigned annotator works on any given task at any given time.
Objects are annotated using bounding boxes, polygons, polylines, keypoints or primitives. Frames are annotated using classifications. Instantiating objects or classifications in the image editor generates a UUID that uniquely identifies that label in the frame.
Labels can be assigned with static classifications as defined in the specified Ontology. Static classifications define the global properties of an object (e.g., the butterfly is of type red admiral and is orange).
You can read more about automation for image annotation here.
Watch a tutorial for drawing a bounding box
Creating a bounding box requires an Ontology with a bounding box annotation type. Instantiate a new bounding box label by clicking on the specified class in the ‘Classes’ menu, or by using the specified hotkey (e.g., 1, 2, 3).
Bounding box labels can be assigned with static classifications should they be defined in your Ontology:
Watch a tutorial for drawing a rotatable bounding box
Traditional bounding boxes are great for annotating objects that appear in horizontal or vertical orientation, however, their accuracy may be limited when it comes to annotating objects at an angle. In such cases, use rotatable boxes to produce more accurate annotations.
Creating a rotatable bounding box requires an Ontology with a rotatable box annotation type.Instantiate a new rotatable box label by clicking on the specified class in the ‘Classes’ menu or using the specified hotkey. Resize rotatable boxes like normal bounding boxes, and then grab the rotation handle to adjust the position until you’re satisfied with the annotation’s accuracy, as below.
Rotatable boxes can be assigned static classifications should they be defined in your Ontology,
and you can export the labels as usual.
Watch a tutorial for working with polygons
Polygons are often necessary if you want to train your applications on the tightest object boundaries. Creating a polygon requires an Ontology with a polygon annotation type. Enable or disable free-hand drawing mode by pressing d on your keyboard. Polygon coarseness for polygons drawn free-hand is set in the ‘Settings’ drawer in the Drawing settings drop-down. Instantiate a new polygon label by clicking on the specified class in the ‘Classes’ menu or using the specified hotkey (e.g., 1, 2, 3).
A polygon can be closed by double-clicking anywhere on the canvas. Doing so will “snap” creating an edge between the last vertex to the first vertex drawn.
You can create a polygon using SAM 2, by placing vertices, or by using the polygon brush (F).
Polygon labels can be assigned static classifications should they be defined in your Ontology:
Watch a tutorial for drawing a polyline
Creating a polyline requires an Ontology with a polyline annotation type. Enable or disable free-hand drawing mode by pressing d on your keyboard. Polyline coarseness for polylines drawn free-hand is set in the ‘Settings’ drawer in the Drawing settings drop-down. Instantiate a new polyline label by clicking on the specified class in the ‘Classes’ menu or using the specified hotkey (e.g., 1, 2, 3).
When free-hand drawing is off, each mouse click places a point on the polyline. A polyline needs at least two points. Double-click anywhere on the canvas to finish, but note that the double-click doesn’t add a point or affect the shape. If only one point is placed, the polyline is canceled. Make sure to click at least twice before double-clicking to complete the shape.
Polyline labels can be assigned with static classifications should they be defined in your Ontology:
Watch a tutorial for drawing a keypoint
Creating a keypoint requires an Ontology with a keypoint annotation type. Instantiate a new keypoint label by clicking on the specified class in the ‘Classes’ menu or using the specified
hotkey (e.g., 1, 2, 3).
Keypoints labels can be assigned with static classifications should they be defined in your Ontology:
Creating a primitive requires an Ontology with a primitive annotation
type. Use primitives to templatize shapes (e.g., 3D cuboids, pose estimation skeletons) commonly
used by your annotation team.
Instantiate a new primitive label by clicking on the specified class in the ‘Classes’ menu or using the specified hotkey (e.g., 1, 2, 3).
Object primitives allow you to define properties of edges defined in your template as visible, occluded, or invisible. Toggle the edge property settings for a primitive by highlighting the primitive and clicking the Show controls button.
Primitive labels can be assigned with static classifications should they be defined in your Ontology:
Bitmasks allows you to create labels using a brush tool to select parts of an image. This can be useful when creating labels for vessel outlines, or labelling topologically separate regions belonging to the same frame classification.
When creating a bitmask, the process continues until you press the ENTER or ESC key. This allows you to easily create complex bitmask labels without interruption.
When you select your bitmask annotation type, the brush tool is selected by default. You can adjust the size of the Bitmask brush tool using the slider in the Bitmask popup, as seen in the screenshot above.
The brush tool can be selected by clicking the brush icon, or by pressing f on your keyboard while the popup is open.
When your label is ready, click Apply label, or press Enter.
Panoptic settings allow you to determine how different bitmasks interact with one another.
The Thresholding tool enables you to set a threshold that determines the parts of the image or frame that is labeled by the Bitmask. Consequently, only the parts of the image falling within th predefined range are labeled upon selection with the Thresholding tool, ensuring precise and targeted labeling.
When Thresholding is enabled, a mask covering the parts of the image that fall above the set threshold appears on the slice. This allows you to preview which parts of the image are labeled when a Bitmask label is applied. The mask color can be changed by clicking the circle icon.
The eyedropper tool enables you to pick a color or intensity value directly from the image.
Three different kinds of threshold can be selected using a dropdown:
When your label is ready, click Apply label, or press Enter.
The Eraser tool allows you to erase parts, or the entirety of your Bitmask selection if the Apply label button has not been clicked yet.
To select the threshold brush, click the eraser icon, or press h on your keyboard while the popup is open.
Combining bitmasks on an image or frame allows you to label objects that are split/separated in the image/video frame.
When creating a bitmask, the process continues until you press the ENTER or ESC key. This allows you to easily create complex bitmask labels without interruption.
To combine two or more bitmasks on an image / video frame:
Hold SHIFT.
Click the bitmasks you want to combine in the Label Editor workspace.
Right-click (on Mac press Cmd). A menu appears.
Select Combine bitmasks into. The bitmasks are now a single bitmask.
It is possible to prevent a Bitmask label from being overlapped by subsequent Bitmasks after the label is created. Use the toggle in the Labels section of the Label Editor to set the overlap behavior.
Choose between the following settings:
To update a bitmask label:
Bitmask labels can be moved to another location after being created.
Creating frame classification(s) requires an Ontology with a classification annotation type. Frame-level classifications consider the frame as a whole, not any given object’s localization. Instantiate a frame-level classification label by clicking on the specified class in the ‘Classes’ menu or using the specified hotkey (e.g., 1, 2, 3).
Encord currently supports radio, checklist, and free-form text input classification types. Edit existing classification labels by clicking on the + icon for the specified label.
Create both instance labels. In this example a chicken and its wing have been labeled using bounding boxes.
Click the Edit classifications button for the object with the Relation attribute. In the example this object is the wing, as seen below.
Encord’s Python SDK & APIs allow you to import model predictions programmatically. Importing model predictions helps to pre-annotate your data to save annotation costs.
See our documentation on automated labeling here.