Represent 3 values as 1 in numpy array

Question

I am attempting to convert a 3 channel numpy array to a single channel numpy array. I want to combine all 3 element values into 1 number using:

x << 16 + y << 8 + z

My code below does that but it seems to make alot of the numbers zero. Is that correct? Or am I doing something wrong? Should those last 2 numbers be zero or something else?

ar = np.array((
    ((255,255,255),),
    ((255,20,255),),
    ((0,255,255),),  # this becomes zero, is that correct? 
    ((22,10,12),),   # this becomes zero, is that correct? 
), dtype='uint8')
c1,c2,c3 = cv2.split(ar)
single = np.int32(c1) << 16 + np.int32(c2) << 8 + np.int32(c3)
print(single)
print(ar.shape)

[[1069547520]
[ 522240]
[ 0]
[ 0]]
(4, 1, 3)

John Zwinck · Accepted Answer · 2019-06-16 01:47:59Z

1

Add a column of zeros to make the array 4 bytes wide:

ar4 = np.insert(ar, 0, 0, 2)

Then simply view it as a big-endian array of 4-byte integers:

ar4.view('>u4')

This gives:

array([[[16777215]],
       [[16717055]],
       [[   65535]],
       [[ 1444364]]], dtype=uint32)

The only step here which really takes time is np.insert(), so if you are able to add that extra column while loading your data, the rest of the transformation is basically free (i.e. does not require copying data).

answered Jun 16, 2019 at 1:47

John Zwinck

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