You can use the item() function:

import numpy as np

matrix = np.array([[[[7]]]])
print(matrix.item())

Output

7

See atleast_1d:

Convert inputs to arrays with at least one dimension.

>>> import numpy as np
>>> x = 42  # x is a scalar
>>> np.atleast_1d(x)
array([42])

>>> x_is_array = np.array(42)  # A zero dim array
>>> np.atleast_1d(x_is_array)
array([42])

>>> x_is_another_array = np.array([42])  # A 1d array
>>> np.atleast_1d(x_is_another_array)
array([42])

>>> np.atleast_1d(np.ones((3, 3)))  # Any other numpy array
array([[ 1.,  1.,  1.],
       [ 1.,  1.,  1.],
       [ 1.,  1.,  1.]])

For future reference:

As of numpy v1.16, asscalar is deprecated. Use np.ndarray.item instead. As the other answer said, generally it's nicer for functions to only return a single type, but there are notable APIs where this is not the case (like __getitem__ for numpy arrays and even lists!). So I would recommend

from typing import Union, Any

import numpy as np


def maybe_single_item(array: np.ndarray) -> Union[np.ndarray, Any]:
    try:
        return array.item()
    except TypeError:
        return array

(python 3.5+)