I have a bunch of images (of cats) and want to plot one of them. The values image are in the format UInt8 and contain 3 bands. When I try to plot using plots I get the following error, ERROR: StackOverflowError.
Using Plots
# Get data
train_data_x = fid["train_set_x"] |> HDF5.read
#Out >
3×64×64×209 Array{UInt8, 4}:
[:, :, 1, 1] =
0x11 0x16 0x19 0x19 0x1b … 0x01 0x01 0x01 0x01
0x1f 0x21 0x23 0x23 0x24 0x1c 0x1c 0x1a 0x16
0x38 0x3b 0x3e 0x3e 0x40 0x3a 0x39 0x38 0x33
...
# Reshape to be in the format, no_of_images x length x width x channels
train_data_rsp = reshape(train_data_x, (209,64,64,3))
# Get first image
first_img = train_data_rsp[1, :, :, :]
plot(first_img)
Out >
ERROR: StackOverflowError:
# I also tried plotting one band and I get a line plot
plot(train_data_rsp[1,:,:,1])
#Out >

Any ideas whats incorrect with my code?
First, I'd be careful about how you're reshapeing; I think this will merely rearrange the pixels in your images instead of swapping the dimensions, which it seems like you want to do. You may want train_data_rsp = permutedims(train_data_x, (4, 2, 3, 1)) which will actually swap the dimensions around and give you a 209×64×64×3 array with the semantics of which pixels belong to which images preserved.
Then, Julia's Images package has a colorview function that lets you combine the separate R,G,B channels into a single image. You'll first need to convert your array element type into N0f8 (a single-byte format where 0 corresponds to 0 and 255 to 1) so that Images can work with it. It would look something like this:
julia> arr_rgb = N0f8.(first_img // 255) # rescale UInt8 in range [0,255] to Rational with denominator 255 in range [0,1]
64×64×3 Array{N0f8,3} with eltype N0f8:
[...]
julia> img = colorview(RGB, map(i->selectdim(arr_rgb, 3, i), 1:3)...)
64×64 mappedarray(RGB{N0f8}, ImageCore.extractchannels, view(::Array{N0f8,3}, :, :, 1), view(::Array{N0f8,3}, :, :, 2), view(::Array{N0f8,3}, :, :, 3)) with eltype RGB{N0f8}:
[...]
Then you should be able to plot this image.
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