Reputation: 11751
I'm new to numpy and trying to understand the following example from here. I'm having trouble understanding the output of
>>> palette[image]
When the indexed array a is multidimensional, a single array of indices refers to the first dimension of a. The following example shows this behavior by converting an image of labels into a color image using a palette.
>>> palette = array( [ [0,0,0], # black
... [255,0,0], # red
... [0,255,0], # green
... [0,0,255], # blue
... [255,255,255] ] ) # white
>>> image = array( [ [ 0, 1, 2, 0 ], # each value corresponds to a color in the palette
... [ 0, 3, 4, 0 ] ] )
>>> palette[image] # the (2,4,3) color image
array([[[ 0, 0, 0],
[255, 0, 0],
[ 0, 255, 0],
[ 0, 0, 0]],
[[ 0, 0, 0],
[ 0, 0, 255],
[255, 255, 255],
[ 0, 0, 0]]])
Upvotes: 1
Views: 231
Reputation: 86306
You are creating a 3D array, where first 2D array (withing 3D array) is given by extracting rows from palette
as given by indices of image[0]
and the second array is given by extracting rows from palette
as given by indices of image[1]
.
>>> palette = array( [ [0,0,0], # black
... [255,0,0], # red
... [0,255,0], # green
... [0,0,255], # blue
... [255,255,255] ] ) # white
>>> image = array( [ [ 0, 1, 2, 0 ], # each value corresponds to a color in the palette
... [ 0, 3, 4, 0 ] ] )
>>> palette[image] # the (2,4,3) color image
array([[[ 0, 0, 0], # row at index 0 of palete
[255, 0, 0], # index 1
[ 0, 255, 0], # index 2
[ 0, 0, 0]], # index 0
[[ 0, 0, 0], # index 0
[ 0, 0, 255], # index 3
[255, 255, 255], # index 4
[ 0, 0, 0]]]) # index 0
Upvotes: 2
Reputation: 8617
This might help you understand:
array([[[ 0, 0, 0], # palette[0]
[255, 0, 0], # palette[1]
[ 0, 255, 0], # palette[2]
[ 0, 0, 0]], # palette[0]
[[ 0, 0, 0], # palette[0]
[ 0, 0, 255], # palette[3]
[255, 255, 255], # palette[4]
[ 0, 0, 0]]]) # palette[0]
Upvotes: 0