I’ll begin by briefly saying thanks to all napari developers. The tool and its recent improvements (notably the visible-only layer loading) have made for some oohs and aahs at meetings in our department.
I have been working with a multiplex image dataset (single tissues labeled with up to 50 immunofluorescent stains, i.e. 50-channel images) where I have pre-processed an image pyramid for each channel into zarr format and visualize in napari 0.2.8 as follows:
# Convert pyramid to zarr cache = Cache(3e9) # Leverage three gigabytes of memory cache.register() viewer = napari.Viewer() # Using napari 0.2.8 base = imread('stain1.tiff') pyramid = list(pyramid_gaussian(base, downscale=2, max_layer=3, multichannel=False)) file_name = 'pyramid.zarr' zarr_root = zarr.open_group(file_name, mode='a') for i in range(0, len(pyramid)): shape = pyramid[i].shape z = zarr_root.create_dataset(str(i), shape=shape, chunks=(300,300), dtype='float') z[:] = pyramid[i] pyramid = [da.from_zarr(file_name + '/' + str(i)) for i in range(len(pyramid))] viewer.add_image(pyramid, blending='additive', visible=False, is_pyramid=True)
I notice some truncation of the image when viewing the top pyramid level, as illustrated in this video: https://www.loom.com/share/468528b725db4e138eab7c3bd05144bb
I tried re-processing each channel with varying chunk sizes, e.g. (300,300), (512,512), (1000,1000), but the problem persisted.
I then tried @sofroniewn’s pathology example by first pre-processing the image into zarr format (https://github.com/sofroniewn/image-demos/blob/master/helpers/make_2D_zarr_pathology.py) then visualizing in napari (https://github.com/sofroniewn/image-demos/blob/master/examples/pathology.py) and experienced similar behavior, as illustrated in this video: https://www.loom.com/share/9a8887c2180e4e8e810c8196ef76a0e4
Notably, the pathology demo throws the following error:
…while my own use case does not.
Any insight into why this might be would be most helpful.
Thanks and all the best,