Using the labels layer#

In this document, you will learn about the napari Labels layer, including using the layer to display the results of image segmentation analyses, and how to manually segment images using the paintbrush and fill buckets. You will also understand how to add a labels image and edit it from the GUI and the console.

For more information about layers, refer to Layers at a glance.

When to use the labels layer#

The labels layer allows you to take an array of integers and display each integer as a different random color, with the background color 0 rendered as transparent.

The labels layer is especially useful for segmentation tasks where each pixel is assigned to a different class, as in semantic segmentation, or where pixels corresponding to different objects all get assigned the same label, as in instance segmentation.

GUI tools for the labels layer#

The GUI contains following tools in the layer controls panel for the labels layer:

  • Buttons

    • shuffle colors

    • label eraser

    • paintbrush

    • polygon tool

    • fill bucket

    • color picker

    • pan/zoom mode

  • Controls

    • label

    • opacity

    • brush size

    • blending

    • color mode

    • contour

    • n edit dim

    • contiguous

    • preserve labels

    • show selected

Buttons#

  • Shuffle colors

    The color that each integer gets assigned is random, aside from 0 which always gets assigned to be transparent. The colormap we use is designed such that nearby integers get assigned distinct colors. The exact colors that get assigned are determined by a random seed. Changing that seed will shuffle the colors assigned to each label. To change the seed, click on the shuffle colors button in the layer controls panel. This changes the color of existing labels. Shuffling colors can be useful as some colors may be hard to distinguish from the background or nearby objects.

  • Label eraser

    Use this tool to manually erase a label on the labels layer. Other layers will not be affected. The label eraser tool looks like this: image: eraser tool

  • Paintbrush

    One of the major use cases for the labels layer is to manually edit or create image segmentations. One of the tools that can be used for manual editing is the paintbrush, activated by clicking the paintbrush icon in the layer controls panel. Once the paintbrush is enabled, the pan and zoom functionality of the viewer canvas is disabled, and you can paint on the canvas. You can temporarily re-enable pan and zoom by pressing and holding the spacebar. This feature is useful if you want to move around the labels layer as you paint.

    Click the paintbrush icon and select a color from the label option by clicking on the + or - on the label bar in the layer controls panel. This will scroll through the available colors. Whatever color you pick will be the edge color of the label. Draw the edge of the label using the paintbrush. If you draw a continuous edge, you can fill it in using the paint bucket or fill bucket tool. It can be the same color as the edge or a different color.

    Adjust the size of your paintbrush using the brush size slider or using the default keybindings: [ and ]. The brush size can be as small as a single pixel for incredibly detailed painting.

    If you have a multidimensional labels layer then your paintbrush will edit data only in the visible slice by default. If you enable the n_dimensional property and paintbrush then your paintbrush will extend out into neighbouring slices according to its size.

    To quickly select the paintbrush, press the 2 key when the labels layer is selected.

  • Polygon

    Another tool that can be used to quickly add or edit image segmentations is the polygon tool. It combines functionality of the paintbrush and fill bucket tools by allowing for readily drawing enclosed instance segmentations. The polygon tool can be activated by clicking on the icon resembling a polygon in the layer control panel or by pressing 3. Once activated, the user actions are as follows:

    1. Left-click anywhere on the canvas to start drawing the polygon.

    2. Move the mouse to the location where you want the next vertex to be.

    3. Click again to set the vertex that is tracking the mouse cursor.

    4. After this step a polygon overlay will appear when moving the mouse. Repeat steps 2 and 3 until the shape to be segmented is enclosed by the polygon overlay.

    5. To undo the last added vertex, use a right-click.

    6. To cancel the drawing at any time without making a permanent change on the labels layer, press Esc. This will delete the polygon overlay.

    7. Press Enter to finish drawing at any time or double click within a radius of 20 screen pixels of the first vertex. This will add the polygon overlay to the labels layer.

    The polygon overlay will have the color of the label. The polygon overlay also has an opacity that can be adjusted the value of the opacity slider in the layer control panel. Furthermore, while the polygon overlay may be visible outside the canvas space during drawing, upon finishing drawing the polygon will be cut off so that the part outside the canvas space is removed. This ensures that the dimensions of the label image are not larger than the image for which you are segmenting of for which you are editing the segmentations.

    Note: if you use the polygon tool for adding or editing segmentations of 3D image data, you can only adjust labels in one plane, with the exception when viewing the image data as RGB. The polygon tool cannot be activated if the number of displayed dimensions is higher than two. If already active upon toggling the number of displayed dimensions, the polygon tool will be automatically deactivated.

  • Fill bucket

    Sometimes you might want to replace an entire label with a different label. This could be because you want to make two touching regions have the same label, or you want to replace only one label with a different one, or maybe you have painted around the edge of a region and you want to quickly fill in its inside. To do this you can select the fill bucket tool by clicking on its icon in the layer controls panel, and then click on a target region of interest in the layer. The fill bucket will fill using the currently selected label. If nothing is selected the entire layer will be filled with that label.

    By default, the fill bucket will change only contiguous or connected pixels of the same label as the pixel that is clicked on. If you want to change all the pixels of that label layer regardless of where they are in the slice, then you can set the contiguous property or checkbox to False. Then everything on that layer will be colored by the new label.

    If you have a multidimensional labels layer the fill bucket will edit data only in the visible slice by default. Enable the n_dimensional property and paintbrush so the fill bucket will extend out into neighbouring slices, either to all pixels with that label in the layer, or only connected pixels depending on if the contiguous property is disabled or not.

    To quickly select the fill bucket, press the 4 key when the labels layer is selected.

  • Color picker

    The color picker can be used to select another color at any time. Click the color picker tool then click on the existing color in the labels layer you would like to use. That color now appears on the label bar as the selected color. If the color does not exist in the label color pallette, it defaults to 0 and a checkerboard pattern appears in the thumbnail on the label bar to represent the transparent color.

    To quickly select the color picker, press the 5 key when the labels layer is selected.

    Note: The color of the label can be selected by clicking on the + or - symbols at either end of the bar or by clicking on the number in the center of the bar and typing in the number of the color to use. 255 colors are available.

Controls#

  • Label

    Use this control to choose a color for a label you are about to create or to change the color of an existing label.

  • Opacity

    Click and hold the oval on the opacity slider bar and adjust it to any value between 0.00 (clear) and 1.00 (completely opaque).

  • Brush size

    Adjust the size of the paintbrush using the brush size slider to any value from 1 to 40. 1 is as small as a single pixel.

  • Blending

    Select from translucent, translucent no depth, additive, minimum, or opaque from the dropdown. Refer to the Blending layers section of Layers at a glance for an explanation of each type of blending.

  • Color mode

    Select auto or direct from the dropdown. Auto is the default and allows color to be set via a hash function with a seed. Direct allows the color of each label to be set directly by a color dictionary, which can be accessed directly via the color property of the layer, layer.color.

  • Contour

    If this field has any value other than 0, only the contours of the labels will show. Change the value by clicking the - or + symbols on either end of the bar, or by clicking the number in the center of the bar and typing in the desired value.

  • n edit dim

    This is the number of dimensions across which labels will be edited.

  • Contiguous

    If this box is checked, the fill bucket changes only connected pixels of the same label.

  • Preserve labels

    If this box is checked, existing labels are preserved while painting. It defaults to false to allow painting on existing labels. When set to true, existing labels will be preserved during painting.

    You can toggle this mode using the default keybinding p. DOESN’T WORK

  • Show selected

    When this is checked, only the selected labels will be displayed. Selected labels are those labels that match the color in the label control. When it is not checked, all labels will be displayed.

Editing using the tools in the GUI#

Pan and zoom mode#

The default mode of the labels layer is to support panning and zooming. This mode is represented by the magnifying glass in the layer controls panel. While pan and zoom is selected, editing the layer is not possible. Once you click on one of the editing tools, pan and zoom is turned off. Return to pan and zoom mode by pressing the 6 key when the labels layer is selected.

Creating a new labels layer#

Create a brand-new empty labels layer by clicking the New labels layer button above the layer list. The shape of the new labels layer will match the size of any currently existing image layers, allowing you to paint on top of them.

Selecting a label#

A particular label can be chosen in one of three ways:

  • Using the label control inside the layer controls panel and typing in the numeric value of the desired label;

  • Using the + or - buttons to get to the desired label color or press the default keybinding m to set a new label; DOESN’T WORK

  • Selecting the color picker tool and then clicking on a pixel with the desired label color in the image.

When a label is chosen, the integer value associated with it appears inside the label control and the color of the label is shown in the thumbnail next to the control. If the 0 label is selected, then a checkerboard pattern is shown in the thumbnail to represent the transparent color.

You can quickly select the color picker by pressing the 5 key when the labels layer is selected.

While painting with a label, you can swap between the current (selected) label and the transparent background label (0) by pressing x.

You can set the selected label to a new label – one larger than the current largest label – by pressing m with either the paintbrush or fill bucket tools selected. This selection will guarantee that you are using a label that hasn’t been used before.

You can also increment or decrement the currently selected label by pressing the = or - keys, respectively.

Creating, deleting, merging, and splitting connected components#

Create and edit object segmentation maps using the color picker, paintbrush, and fill bucket tools. Below we show how to use these tools by performing common editing tasks on connected components (keep the contiguous box checked).

  • Creating or drawing a connected component

    • Press m to select a label color that has not been used.

    • Select the paintbrush tool and draw a closed contour around the object.

    • Select the fill bucket tool and click inside the contour to assign the label to all pixels of the object.

  • Deleting a connected component

    Select the background label with the color picker or press x, then use the fill bucket to set all pixels of the connected component to background.

  • Merging connected components

    • Select the label of one of the components with the color picker tool.

    • Select the fill bucket and fill the components to be merged.

  • Splitting a connected component

    Splitting a connected component will introduce an additional object.

    • Select the background label with the color picker or press x.

    • Use the paintbrush tool to draw a dividing line where you want to split the component.

    • Assign the new label to one of the parts with the fill bucket.

Undo/redo functionality#

When using the fill bucket or paintbrush it can be easy to make a mistake that you might want to undo or you might want to redo something that has just been undone. Use ctrl-z to redo and shift-ctrl-z to redo. There are plans to support this sort of functionality more generally, but for now these actions will undo the most recent painting or filling event, up to 100 events in the past.

Warning

If you have multidimensional data, adjusting the currently viewed slice will cause the undo history to be reset.

Controlling the labels layer from the console#

A simple example#

Create a new viewer and add a labels image in one go using the napari.view_labels() method. If you already have an existing viewer, you can add a Labels image to it using viewer.add_labels. The API for both methods is the same. In these examples we’ll mainly use add_labels to overlay a Labels layer onto on image.

In this example of instance segmentation, we will find and segment each of the coins in an image, assigning each one an integer label, and then overlay the results on the original image as follows:

import napari
from skimage import data
from skimage.filters import threshold_otsu
from skimage.segmentation import clear_border
from skimage.measure import label
from skimage.morphology import closing, square, remove_small_objects

coins = data.coins()[50:-50, 50:-50]
# apply threshold
thresh = threshold_otsu(coins)
bw = closing(coins > thresh, square(4))
# remove artifacts connected to image border
cleared = remove_small_objects(clear_border(bw), 20)
# label image regions
label_image = label(cleared)

# create the viewer and add the coins image
viewer = napari.view_image(coins, name='coins')
# add the labels
labels_layer = viewer.add_labels(label_image, name='segmentation')
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from napari.utils import nbscreenshot

nbscreenshot(viewer, alt_text="Segmentation of coins in an image, displayed using a labels layer")
Segmentation of coins in an image, displayed using a labels layer

Arguments of view_labels and add_labels#

view_labels() and add_labels() accept the same layer-creation parameters.

help(napari.view_labels)
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Help on function view_labels in module napari.view_layers:

view_labels(data, *, affine=None, blending='translucent', cache=True, colormap=None, depiction='volume', experimental_clipping_planes=None, features=None, metadata=None, multiscale=None, name=None, opacity=0.7, plane=None, projection_mode='none', properties=None, rendering='iso_categorical', rotate=None, scale=None, shear=None, translate=None, visible=True, title='napari', ndisplay=2, order=(), axis_labels=(), show=True, camera: napari.components.camera.Camera = None, cursor: napari.components.cursor.Cursor = None, dims: napari.components.dims.Dims = None, grid: napari.components.grid.GridCanvas = None, layers: napari.components.layerlist.LayerList = None, help: str = '', status: Union[str, dict] = 'Ready', tooltip: napari.components.tooltip.Tooltip = None, theme: str = None, mouse_over_canvas: bool = False) -> napari.viewer.Viewer
    Create a viewer and add a labels layer.
    
    Parameters
    ----------
    data : array or list of array
        Labels data as an array or multiscale. Must be integer type or bools.
        Please note multiscale rendering is only supported in 2D. In 3D, only
        the lowest resolution scale is displayed.
    affine : n-D array or napari.utils.transforms.Affine
        (N+1, N+1) affine transformation matrix in homogeneous coordinates.
        The first (N, N) entries correspond to a linear transform and
        the final column is a length N translation vector and a 1 or a napari
        `Affine` transform object. Applied as an extra transform on top of the
        provided scale, rotate, and shear values.
    blending : str
        One of a list of preset blending modes that determines how RGB and
        alpha values of the layer visual get mixed. Allowed values are
        {'opaque', 'translucent', and 'additive'}.
    cache : bool
        Whether slices of out-of-core datasets should be cached upon retrieval.
        Currently, this only applies to dask arrays.
    colormap : CyclicLabelColormap or DirectLabelColormap or None
        Colormap to use for the labels. If None, a random colormap will be
        used.
    depiction : str
        3D Depiction mode. Must be one of {'volume', 'plane'}.
        The default value is 'volume'.
    experimental_clipping_planes : list of dicts, list of ClippingPlane, or ClippingPlaneList
        Each dict defines a clipping plane in 3D in data coordinates.
        Valid dictionary keys are {'position', 'normal', and 'enabled'}.
        Values on the negative side of the normal are discarded if the plane is enabled.
    features : dict[str, array-like] or DataFrame
        Features table where each row corresponds to a label and each column
        is a feature. The first row corresponds to the background label.
    metadata : dict
        Layer metadata.
    multiscale : bool
        Whether the data is a multiscale image or not. Multiscale data is
        represented by a list of array like image data. If not specified by
        the user and if the data is a list of arrays that decrease in shape
        then it will be taken to be multiscale. The first image in the list
        should be the largest. Please note multiscale rendering is only
        supported in 2D. In 3D, only the lowest resolution scale is
        displayed.
    name : str
        Name of the layer.
    opacity : float
        Opacity of the layer visual, between 0.0 and 1.0.
    plane : dict or SlicingPlane
        Properties defining plane rendering in 3D. Properties are defined in
        data coordinates. Valid dictionary keys are
        {'position', 'normal', 'thickness', and 'enabled'}.
    projection_mode : str
        How data outside the viewed dimensions but inside the thick Dims slice will
        be projected onto the viewed dimensions
    properties : dict {str: array (N,)} or DataFrame
        Properties for each label. Each property should be an array of length
        N, where N is the number of labels, and the first property corresponds
        to background.
    rendering : str
        3D Rendering mode used by vispy. Must be one {'translucent', 'iso_categorical'}.
        'translucent' renders without lighting. 'iso_categorical' uses isosurface
        rendering to calculate lighting effects on labeled surfaces.
        The default value is 'iso_categorical'.
    rotate : float, 3-tuple of float, or n-D array.
        If a float convert into a 2D rotation matrix using that value as an
        angle. If 3-tuple convert into a 3D rotation matrix, using a yaw,
        pitch, roll convention. Otherwise assume an nD rotation. Angles are
        assumed to be in degrees. They can be converted from radians with
        np.degrees if needed.
    scale : tuple of float
        Scale factors for the layer.
    shear : 1-D array or n-D array
        Either a vector of upper triangular values, or an nD shear matrix with
        ones along the main diagonal.
    translate : tuple of float
        Translation values for the layer.
    visible : bool
        Whether the layer visual is currently being displayed.
        title : string, optional
        The title of the viewer window. By default 'napari'.
    ndisplay : {2, 3}, optional
        Number of displayed dimensions. By default 2.
    order : tuple of int, optional
        Order in which dimensions are displayed where the last two or last
        three dimensions correspond to row x column or plane x row x column if
        ndisplay is 2 or 3. By default None
    axis_labels : list of str, optional
        Dimension names. By default they are labeled with sequential numbers
    show : bool, optional
        Whether to show the viewer after instantiation. By default True.
    
    
    Returns
    -------
    viewer : :class:`napari.Viewer`
        The newly-created viewer.

Labels data#

The labels layer is a subclass of the image layer and as such can support the same NumPy-like arrays, including dask arrays, xarrays, and zarr arrays. A Labels layer must be integer valued, and the background label must be 0.

Because the labels layer subclasses the image layer, it inherits the great properties of the image layer, like supporting lazy loading and multiscale images for big data layers. For more information about both these concepts see the details in the image layer guide.

Creating a new labels layer#

As you can edit a Labels layer using the paintbrush and fill bucket, it is possible to create a brand-new empty labels layers by clicking the new labels layer button above the layers list. The shape of the new labels layer will match the size of any currently existing image layers, allowing you to paint on top of them.

Want to save without compression?

When saving a labels layer, lossless zlib compression is applied by default. To save with a different level of compression, consider using imageio.imwrite.

Adjusting compression can be accomplished by including the appropriate keyword arguments as outlined in the following locations for tif or png files.

Non-editable mode#

If you want to disable editing of the labels layer you can set the editable property of the layer to False.

As noted in the section on 3D rendering, when using 3D rendering the labels layer is not editable. Similarly, for now, a labels layer where the data is represented as a multiscale image is not editable.

3D rendering#

All layers can be rendered in both 2D and 3D. One of the viewer buttons at the bottom of the left panel can toggle between these 2 modes. When in 2D, the button looks like this: image: 2D/3D button, ready to switch to 3D mode. When in 3D, the button looks like this: image: 2D/3D button, ready to switch to 2D mode.

The number of dimensions sliders will be 2 or 3 less than the total number of dimensions of the layer, allowing you to browse volumetric timeseries data and other high dimensional data.

import napari
from skimage import data
from scipy import ndimage as ndi

blobs = data.binary_blobs(length=128, volume_fraction=0.1, n_dim=3)
viewer = napari.view_image(blobs.astype(float), name='blobs')
labeled = ndi.label(blobs)[0]
labels_layer = viewer.add_labels(labeled, name='blob ID')
viewer.dims.ndisplay = 3
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# programmatically adjust the camera angle
viewer.camera.zoom = 2
viewer.camera.angles = (3, 38, 53)
nbscreenshot(viewer, alt_text="A 3D view of a labels layer on top of 3D blobs")
A 3D view of a labels layer on top of 3D blobs

Note that in 3D rendering mode the colorpicker, paintbrush, and fill bucket options are all disabled. Those options allow for layer editing and are only supported when viewing a layer rendered in 2D.