Export Figure

Display a variety of layer types in the napari viewer and export the figure with viewer.export_figure(). The exported figure is then added back as an image layer.

Exported figures include the extent of all data in 2D view, and does not presently work for 3D views. To capture the extent of the canvas, instead of the layers, see viewer.screenshot(): To screenshot and Comparison of Screenshot and Figure Export.

Tags: visualization-advanced

import numpy as np
from skimage import data

import napari

# create the viewer and window
viewer = napari.Viewer()

# add the image
img_layer = viewer.add_image(data.camera(), name='photographer')
img_layer.colormap = 'gray'

# create a list of polygons
polygons = [
    np.array([[11, 13], [111, 113], [22, 246]]),
    np.array(
        [
            [505, 60],
            [402, 71],
            [383, 42],
            [251, 95],
            [212, 59],
            [131, 137],
            [126, 187],
            [191, 204],
            [171, 248],
            [211, 260],
            [273, 243],
            [264, 225],
            [430, 173],
            [512, 160],
        ]
    ),
    np.array(
        [
            [310, 382],
            [229, 381],
            [209, 401],
            [221, 411],
            [258, 411],
            [300, 412],
            [306, 435],
            [268, 434],
            [265, 454],
            [298, 461],
            [307, 461],
            [307, 507],
            [349, 510],
            [352, 369],
            [330, 366],
            [330, 366],
        ]
    ),
]

# add polygons
layer = viewer.add_shapes(
    polygons,
    shape_type='polygon',
    edge_width=1,
    edge_color='coral',
    face_color='royalblue',
    name='shapes',
)

# add an ellipse to the layer
ellipse = np.array([[59, 222], [110, 289], [170, 243], [119, 176]])
layer.add(
    ellipse,
    shape_type='ellipse',
    edge_width=5,
    edge_color='coral',
    face_color='purple',
)

labels = layer.to_labels([512, 512])
labels_layer = viewer.add_labels(labels, name='labels')

points = np.array([[100, 100], [200, 200], [333, 111]])
size = np.array([10, 20, 20])
viewer.add_points(points, size=size)

# Add scale bar of a defined length to the exported figure
viewer.scale_bar.visible = True
viewer.scale_bar.length = 250

# Export figure and change theme before and after exporting to show that the background canvas margins
# are not in the exported figure.
viewer.theme = "light"
# Optionally for saving the exported figure: viewer.export_figure(path="export_figure.png")
export_figure = viewer.export_figure(flash=False) # bug: default flash=True causes the canvas to be grayscale in docs
scaled_export_figure = viewer.export_figure(scale_factor=5, flash=False)
viewer.theme = "dark"

viewer.add_image(export_figure, rgb=True, name='exported_figure')
viewer.add_image(scaled_export_figure, rgb=True, name='scaled_exported_figure')
viewer.reset_view()

# from skimage.io import imsave
# imsave('screenshot.png', screenshot)

if __name__ == '__main__':
    napari.run()