Look-up-table/Jupyter Notebook Segmentation Image import and visualization error

## Description
Unable to view and thus segment images in look-up-table demos in allen-classic segmentation via jupyter notebook. Follow error message is received when running the jupyter notebook:

After running the "Loading the data" commands (this happens with both 2D and 3D data sets, single channel images):
Failed to parse XML for the provided file. Error: not well-formed (invalid token): line 1, column 6
(1, 1, 20, 1024, 1024)

When I continue the pipeline, I get the following error in the "Preview of the image" commands:

`np.int` is a deprecated alias for the builtin `int`. To silence this warning, use `int` by itself. Doing this will not modify any behavior and is safe. When replacing `np.int`, you may wish to use e.g. `np.int64` or `np.int32` to specify the precision. If you wish to review your current use, check the release note link for additional information.
Deprecated in NumPy 1.20; for more details and guidance: https://numpy.org/devdocs/release/1.20.0-notes.html#deprecations
---------------------------------------------------------------------------
IndexError Traceback (most recent call last)
~\AppData\Local\Temp\ipykernel_31488\3651088532.py in
5 if N_CHANNELS==1:
6 ax.axis('off')
----> 7 ax.imshow(IMG[0,0,0,MID_SLICE,:,:], cmap=plt.cm.gray)
8 else:
9 for channel in range(N_CHANNELS):

IndexError: too many indices for array: array is 5-dimensional, but 6 were indexed

## Expected Behavior
Images should be able to be visualize then segmented (previously worked for me, roughly 1 year ago)

## Reproduction
1) Run jupyter notebook from anaconda (in aics-segmentation environment)
2) Pick any playground (dots for example)
3) run all steps until getting to "Loading the data"
4) Receive error

## Environment
Jupyter notebook via anaconda