Creating a single number from a numpy array - Python
Welcome to Data Science! You're question needs a little more detail... there are many many ways to make an array into a single number. You should say a little more about what you mean by meaningful.

Here are a few examples, using your example array, which may seem outrageously simple, but do indeed form the basis to many of the techniques used in modern research:

In [1]: import numpy as np

In [2]: x = np.array([[129, 155, 191], [123, 150, 185], [120, 149, 183]], dtype=np.float32)

In [3]: x
Out[3]: 
array([[129., 155., 191.],
       [123., 150., 185.],
       [120., 149., 183.]], dtype=float32)


Now here are a few (randomly selected) ways to create a single number from your array:

In [4]: np.mean(x)    # the mean / average
Out[4]: 153.88889

In [5]: np.sum(x)    # the sum
Out[5]: 1385.0

In [6]: np.std(x)    # the standard deviation
Out[6]: 25.722641

In [7]: np.linalg.norm(x)    # the Frobius norm - a distance measure
Out[7]: 468.07156

In [8]: np.max(x)
Out[8]: 191.0


These might seem stupidly simple, but if we were to treat your array as a single block from a larger image-array, then these might represent pooling-layers that are used to down-sample arrays as they are passed through a neural network. Just have a look at the available pooling layers within the Keras library.

Which method you might want to use will heavily depend on your use case, your dataset and your model.