LoadImage Fails to Load Certain JPEGs

Describe the bug LoadImage fails to correctly load certain JPEGs. The produced array contains streaked information. Test image included:

.

To Reproduce

im=LoadImage(image_only=True)("bad_image.jpg")
plt.imshow(im[0],cmap="gray")

This produces

Expected behavior Image should look like the attached image but comes out corrupted when viewed with matplotlib, using plt.imread does work.

Environment (please complete the following information):

• Ubuntu
• Python version 3.7
• MONAI version 62903b6924e572edfb0d44ce333dd0251e659bfe
• CUDA/cuDNN version 11, 7.5
• GPU Titan Xp

[ericspod]

From looking at the ITK code further I think keep_axis should always be False. It would only be True if data was being read in Fortran-ordering as opposed to C-ordering, simply reversing the shape will just cause the memory view to be interpreted in a transposed order. In GetArrayViewFromImage if keep_axis is True the ordering of the shape is reversed but the returned Numpy array still interprets the underlying memory segment in C-ordering, this is why we get the transposed image as I showed.

I think the keep_axis parameter is not explained correctly since it should only be True if memview is a view into Fortran-ordered segments, the documentation does not state this. Further if this is the case it would be better to leave the shape reversed (ie. in HW(D)C ordering) and set the order argument for numpy.array to F to use Fortran-ordering internally.

[thewtex]

The axes referenced in the keep_axes argument to itk.array_view_from_image are referencing the order of indexing of the spatial dimensions. We will add a new kwarg to itk.array_view_from_image to specify whether the channels should be contiguous or interleaved. Until that is released, we can use #1147