I have a four-dimensional data in array trainAll of shape N × H × W × 3. I need to separate it so I did
X_train = trainAll[:,:,:,1]
Y_train = trainAll[:,:,:,1:3]
As expected, Y_train.shape was N × H × W × 2.
But X_train.shape is N × H × W because the last dimension has just size 1.
But neural network need four dimensional array, so it should look like
N × H × W × 1
The amazing thing is, if I do trainAll[:,:,:,2:3] then I get N*H*W*1 but I want the first dimension separated, not the last.
Honestly, I was unable to google because I did not know what to ask. So can any one help me out, so that I can not only separate first dimension but also shape is N × H × W × 1 instead of N × H × W ?
Just try to add a new axis as the desired dimension. (Here, as the fourth dimension).
X_train = trainAll[:, :, :, 0]
X_train = X_train[:, :, :, np.newaxis]
# now, X_train.shape will be N * H * W * 1
The reason why you don't get them at the first place when you slice them is because slice hands the result as (n,) when using a single index and you make it (n, 1) by adding a new axis.