2D numpy array showing as 1D

This is because the arrays are constructed to be arrays of objects. Basically each element in the array is pointing to another array of size (1, ) which points to another array of size (10304, ). This is not equivalent to a normal ndarray in numpy so the shape is not recognized correctly. You can check this by looking at the dtypes.

To replicate what you see:

import numpy as np

arr = np.empty(200, dtype='object')
for i in range(200):
    temp_arr = np.empty(1, dtype='object')
    temp_arr[0] = np.zeros(10304)
    arr[i] = temp_arr
print(arr.shape)
print(arr[0].shape)
print(arr[0][0].shape)

(200,)
(1,)
(10304,)

To get the (200, 10304) array back you need to "unpack" them:

new_arr = np.array([x[0] for x in arr])

#(200, 10304)