The Labeling Interface
An overview of the Labeling Interface for Roboflow's Annotation Tool, including shortcut keys.
On the right-hand side of the labeling interface, you will find the Toolbar. It contains the following options:
  • Drag/Select (represented by a hand icon) allows you to select, edit, and drag individual annotations.
    • Single-click an existing bounding box to select it. Once selected, you can change a bounding box's size with the circular white handles that appear on its corners and on each side. Or use the class editor to change the box's label.
    • Drag a box to move it.
    • Drag the background to pan.
    • Click the background to deselect all boxes.
    Drag Tool (D) selection
  • Bounding Box (represented by a rectangular box icon) allows you to draw new bounding-box annotations. In this mode, you will see crosshairs that will help you determine where to start drawing.
    • Click and drag across the image to create a new annotation, then use the Class Selector to choose its label.
Bounding Box Tool (B) selection
  • Polygon allows you to draw new polygonal annotations. In this mode, you will see crosshairs that will help you determine where to start drawing.
    • Click on the image around objects of interest to create an enclosed polygon annotation, then use the Class Selector to choose its label.
    Polygon Tool (P) selection
  • Smart Polygon allows you to draw new Smart Polygon annotations. In this mode, you will see a green dot when you are selecting a new area of interest (new label); a red dot when selecting areas to remove from the area of interest (parts of the object or image that you don't want to label/enclose with the polygon); and options to adjust the polygon by Convex Hull, Smooth, and Complex settings. Smart Polygon is particularly useful for (Instance and Semantic) Segmentation projects, however, you may see performance boosts in Object Detection models when labeling with Smart Polygons on Roboflow.
    Smart Polygon (S) Tool selection
  • Label Assist allows for the use of a Public Model (such as the COCO model) or one of your own dataset versions that was trained with Roboflow Train, for the automatic application of bounding box labels to images in your Annotation queue.
  • Mark Null (Null annotation) is to be used for the "labeling" of background, or null, images. This setting can also be used to clear all annotations from an image, or to mark the image as Unannotated.
Mark Null (N) Tool selection
  • While in Bounding Box (B), Polygon (P), or Smart Polygon (S) mode:
    • Undo reverts the previous action.
    • Redo reverses a previously undone action.
    • Repeat Previous reapplies label(s) on an image in the same location(s) as the last annotated image
When an image is selected, the Class Selector will appear. It contains the following options for choosing the label of a bounding box:
The Class Selector
  • Textfield to create a new class or filter existing classes.
  • Buttons to save or discard your changes.
  • Class List of the existing classes in the dataset (filtered by the text field and with the active option highlighted in purple) and, sometimes, a "Create class" option if the text you typed does not match an existing class.
At the bottom left of the screen, you will find the Zoom Tool. You can zoom in and out to fit more of the image on your screen at one time or to get a closer look for more detailed editing. There is also an option to "lock" the zoom to a specified percentage, or reset the zoom to fit the entirety of the image within the Annotation Tool's viewport.
Note that if you select the "Zoom Lock" option, all images will appear at this zoom-level. Deselect, or unlock, the lock to remove Zoom Lock.
Zoom Tool
On the left-hand sidebar you will find the following drawers:
  • Annotations (abbreviated Annots) show which classes are present and not present in an image and what color their boxes are.
    • Watch this spot for updates soon as we add filtering and fine-tuning features.
Annotations (Annots) Sidebar
  • Attributes contains information about your image including its dimensions, last-modified time, and whether it is in this dataset's training, validation, or test set.
Attributes Sidebar
  • Raw Data is mostly used for debugging and can be safely ignored by most users unless our support team requests that you access it. It contains Roboflow internal representation of the image.
Raw Data Sidebar
In the header you will find navigation to exit the labeling interface, move on to the next or previous image in the dataset, and perform the following actions:
  • View source image (represented by an eye with a slash through it) temporarily hides the bounding boxes to give you a closer look at the original image.
    • Options (represented by an ellipsis)
      • Use as Cover Photo marks the current image as the icon for the dataset on your homepage and uses it as the preview image for preprocessing and augmentation options.
      • Remove from Project removes the image from the project after confirmation.

Video walkthrough of hotkeys
The following keyboard shortcuts are available to speed up your labeling flow. The meta key is usually the command key on macOS and the ctrl key on Linux and Windows.
If no annotation is selected, the following keyboard shortcuts apply:
  • meta - temporarily switches between the Drag/Select and Bounding Box (B) or Polygon (P) tools while held down. (For example, if you are in Bounding Box mode, hold down the meta key and click an existing bounding box to select it.)
  • b - Switches to the Bounding Box tool.
  • p - Switches to the Polygon tool.
  • d - Switches to the Drag/Select tool.
  • n - Switches to the Mark Null tool.
    • entering n while annotating an image that is already marked as Null will mark that image as Unannotated if it is currently in the Annotating queue.
  • s - switches to the Smart Polygon tool.
  • plus - Zooms In.
  • minus - Zooms Out.
  • zero - Returns to Default Zoom (fits image into the viewport).
  • one - Zooms to 100%.
  • escape (esc) - Exits the Labeling Tool.
  • left arrow - Navigates to the previous image.
  • right arrow - Navigates to the next image.
Once an annotation is selected and the Class Selector is visible, the shortcuts are as follows:
  • enter - Saves the Active Option (highlighted in purple) as the current class, or label, for the selected bounding box.
  • escape (esc) - Cancels and deselects the current box without changing its label (if the currently selected box was just drawn it will be deleted).
  • up arrow - Changes the Active Option (class/label) to the previous one.
  • down arrow - Changes the Active Option (class/label) to the next one.
  • backspace - Deletes the current bounding box if there is no text in the text field (this means you will usually have to push backspace twice to delete a box after selecting it; one time to delete the highlighted text and a second time to confirm deletion).

Roboflow Annotate now offers automated polygon labeling for all users. With as few as one click, you can apply a polygon annotation to objects in your datasets.
Labeling Images with the Roboflow Annotate Smart Polygon Tool
Polygon annotations are critical to prepare datasets for training instance segmentation or semantic segmentation models and can often improve model accuracy when used instead of bounding boxes for object detection models.
Polygons are more precise than bounding boxes but, without the proper tools, take more time to apply labels because adding a detailed bounding takes multiple interactions to label an object. For Roboflow users, that is no longer the case. Polygon labels are now as fast to apply to objects as bounding boxes in many instances.
To use the Smart Polygon feature, click Smart Polygon in the labeling toolbar (Shortcut Key: S).
Smart Polygon in the Annotation Toolbar
Then click the center of the object you want to label and Smart Polygon will apply an initial label to the object. This will use a machine learning model behind the scenes to suggest a shape for your object. The least amount of vertices required to accurately label your object is best.
Oftentimes the label will be predicted accurately with just a single click and you can move on to the next object by pressing enter, then selecting a class for your object.
Smart Polygons vs. Manual Polygon Annotation
Using the Smart Polygon options on the top-left of the annotation tool, you’re able to choose the number of vertices in your label by toggling between Convex Hull, Smooth, and Complex labels (and can also undo points you've placed if you make a mistake).
Smart Polygon Options (Convex Hull, Smooth, Complex labels)

Smart Polygon is helpful for labeling semantic segmentation data as well. Just be sure to properly order the objects' z-indexes so the masks are properly stacked according to how you would want to train your model. You can visualize the stacking by using the Layers tab in the sidebar. This will help you understand what your segmentation mask will look like once rasterized.
The Layers tab is available on all Roboflow project types. To edit a bounding box without changing the ordering of Layers, simply click on the Layer/annotation you'd like to edit in the Layers tab and then make your edits.

All users, including our free Public tier users, have access to Smart Polygon so login to give it a try and see how polygons might improve your model accuracy or speed up your labeling process.
If you're interested in building a project and in need of data, you can find instance segmentation and semantic segmentation datasets in Roboflow Universe to get your project started.
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Keyboard Shortcuts
Smart Polygons
Visualizing Segmentation Layers