How to use the napari.view_image function in napari

visible = False
                    else:
                        visible = True
                else:
                    visible = True

                # Drop channel from dims string
                dims = (
                    dims.replace(Dimensions.Channel, "")
                    if Dimensions.Channel in dims
                    else dims
                )

                # Run napari
                with napari.gui_qt():
                    napari.view_image(
                        data,
                        is_pyramid=False,
                        ndisplay=3 if Dimensions.SpatialZ in dims else 2,
                        channel_axis=c_axis,
                        axis_labels=dims,
                        title=title,
                        visible=visible,
                        **kwargs,
                    )

        except ModuleNotFoundError:
            raise ModuleNotFoundError(
                f"'napari' has not been installed. To use this function install napari "
                f"with either: pip install napari' or "

"""
Display one image using the add_image API.
"""

from skimage import data
import napari


with napari.gui_qt():
    # create the viewer with an image
    viewer = napari.view_image(data.astronaut(), rgb=True)

if isinstance(self.reader, ArrayLikeReader):
                title = f"napari: {self.dask_data.shape}"
            else:
                title = f"napari: {self.reader._file.name}"

            # Handle RGB entirely differently
            if rgb:
                # Swap channel to last dimension
                new_dims = f"{dims.replace(Dimensions.Channel, '')}{Dimensions.Channel}"
                data = transforms.transpose_to_dims(
                    data=data, given_dims=dims, return_dims=new_dims
                )

                # Run napari
                with napari.gui_qt():
                    napari.view_image(
                        data,
                        is_pyramid=False,
                        ndisplay=3 if Dimensions.SpatialZ in dims else 2,
                        title=title,
                        axis_labels=dims.replace(Dimensions.Channel, ""),
                        rgb=rgb,
                        **kwargs,
                    )

            # Handle all other images besides RGB not requested
            else:
                # Channel axis
                c_axis = (
                    dims.index(Dimensions.Channel)
                    if Dimensions.Channel in dims
                    else None

"""
Display one points layer ontop of one image layer using the add_points and
add_image APIs
"""

import numpy as np
from skimage import data
import napari


print("click to add points; close the window when finished.")

with napari.gui_qt():
    viewer = napari.view_image(data.astronaut(), rgb=True)
    points = viewer.add_points(np.zeros((0, 2)))
    points.mode = 'add'

print("you clicked on:")
print(points.data)

"""
Display a labels layer above of an image layer using the add_labels and
add_image APIs
"""

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


with napari.gui_qt():
    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]
    viewer.add_labels(labeled, name='blob ID')

"""
Display a labels layer above of an image layer using the add_labels and
add_image APIs
"""

from skimage import data
from skimage.color import rgb2gray
from skimage.segmentation import slic
import napari


with napari.gui_qt():
    astro = data.astronaut()

    # initialise viewer with astro image
    viewer = napari.view_image(rgb2gray(astro), name='astronaut', rgb=False)

    # add the labels
    # we add 1 because SLIC returns labels from 0, which we consider background
    labels = slic(astro, multichannel=True, compactness=20) + 1
    label_layer = viewer.add_labels(labels, name='segmentation')

    # Set the labels layer mode to picker with a string
    label_layer.mode = 'picker'
    print(f'The color of label 5 is {label_layer.get_color(5)}')

from skimage.color import rgb2gray
from skimage.transform import pyramid_gaussian
import napari
import numpy as np


# create pyramid from astronaut image
base = np.tile(data.astronaut(), (8, 8, 1))
pyramid = list(
    pyramid_gaussian(base, downscale=2, max_layer=4, multichannel=True)
)
print('pyramid level shapes: ', [p.shape[:2] for p in pyramid])

with napari.gui_qt():
    # add image pyramid
    napari.view_image(pyramid, is_pyramid=True)

"""
Display multiple image layers using the add_image API and then reorder them
using the layers swap method and remove one
"""

from skimage import data
from skimage.color import rgb2gray
import numpy as np
import napari


with napari.gui_qt():
    # create the viewer with several image layers
    viewer = napari.view_image(rgb2gray(data.astronaut()), name='astronaut')
    viewer.add_image(data.camera(), name='photographer')
    viewer.add_image(data.coins(), name='coins')
    viewer.add_image(data.moon(), name='moon')
    viewer.add_image(np.random.random((512, 512)), name='random')
    viewer.add_image(data.binary_blobs(length=512, volume_fraction=0.2, n_dim=2), name='blobs')
    viewer.grid_view()

# create pyramid from astronaut image
astronaut = data.astronaut()
base = np.tile(astronaut, (3, 3, 1))
pyramid = list(
    pyramid_gaussian(base, downscale=2, max_layer=3, multichannel=True)
)
pyramid = [
    np.array([p * (abs(3 - i) + 1) / 4 for i in range(6)]) for p in pyramid
]
print('pyramid level shapes: ', [p.shape for p in pyramid])

with napari.gui_qt():
    # add image pyramid
    napari.view_image(pyramid, is_pyramid=True)

import numpy as np
from skimage import data
import napari


with napari.gui_qt():
    blobs = np.stack(
        [
            data.binary_blobs(
                length=128, blob_size_fraction=0.05, n_dim=3, volume_fraction=f
            )
            for f in np.linspace(0.05, 0.5, 10)
        ],
        axis=0,
    )
    viewer = napari.view_image(blobs.astype(float))

    # add the points
    points = np.array(
        [
            [0, 0, 100, 100],
            [0, 0, 50, 120],
            [1, 0, 100, 40],
            [2, 10, 110, 100],
            [9, 8, 80, 100],
        ]
    )
    viewer.add_points(
        points, size=[0, 6, 10, 10], face_color='blue', n_dimensional=True
    )