Replace numbers below threshold # in numpy array with zeroes

Question

So I have a very big Numpy array (2560x1920). Its actually from a grayscale picture where every pixel is given a number from 0-1 indicating its brightness.

I'm trying to replace all values below a threshold, say 0.5, with zeroes. This is probably a simple task but I'm a beginner with Numpy and I've searched around and still can't figure it out.

This is what I've attempted and I know its wrong...

for x in np.nditer(Image):
    if x < .5:
        x == 0

plt.imshow(Image, cmap=plt.cm.gray)
plt.show()

It just outputs the normal image without changing anything.

Also the array looks something like this (abbreviated obviously):

[[ 0.24565263  0.24565263  0.24902149 ...,  0.27528678  0.27265316
   0.27606536]
 [ 0.24565263  0.24565263  0.24902149 ...,  0.27870309  0.27606536
   0.27948296]
 [ 0.24228902  0.24228902  0.24565263 ...,  0.28212482  0.27948296
   0.282906  ]
 ..., 
 [ 0.29706944  0.29706944  0.29706944 ...,  0.17470162  0.17144636
   0.17144636]
 [ 0.29362457  0.29362457  0.29362457 ...,  0.17144636  0.16495056
   0.16170998]
 [ 0.2901852   0.2901852   0.2901852  ...,  0.16819602  0.16170998
   0.15847427]]

Answer 1

There is numpy's builtin indexing which can be used for replacing elements. This is can be done as:

Image[Image<0.5] = 0