Working with CSV of MNIST sign language in Julia deep learning

Hello,
I am trying to make a convolusional neural network on MNISt sign language dataset. It si provided in a CSV format where each row is one picture and there are 784 columns refering to a single pixel (the pictures have a size 28x28).
My problem is that in order to perform the algorithm I need to transpose my data to a different format, the same as is the format of a built-in ML dataset fashion MNIST, which is:

Array{Array{ColorTypes.Gray{FixedPointNumbers.Normed{UInt8,8}},2},1}.

I would like to end up with the following format, where my data is joined with the encoded labels:

Array{Tuple{Array{Float32,4},Flux.OneHotMatrix{Array{Flux.OneHotVector,1}}},1}:

I was trying to use reshape function to convert it to a 4-domensional array, but all I get is:
7172×28×28×1 Array{Float64,4}.

My labels are in the following (correct) format:
25×7172 Flux.OneHotMatrix{Array{Flux.OneHotVector,1}}:

I am new to Julia and some of the code I am using has been written by someone else.
I would appreciate your explanation of the format and please feel free to tell me if I haven’t put all the necessary information.