i want to make a video stream program over udp, with opencv, i want to make a compression by converting the 255 color values into 16 color values, because it will save trafic by half and the quality isnt that bad. i know how to convert 255 values to 16 values:
opencvimg = numpy.multiply(opencvimg//16,16)
but i dont know a efficient way to get two values into 1 byte to save traffic. it has to be efficient cause i want it to run on a rpi (full code on github.com/Open-ATS-Github).
CodePudding user response:
There is a solution that involves no explicit arithmetic: you can build a full lookup-table of 256 x 256 entries, giving the packed result for a pair of input bytes.
If such a table seems unreasonably large, think that you are working with images, which are even larger.
Whether it is better to work with a flat vector or with a matrix and if cache effects will not ruin the effort is a matter of experimentation.
CodePudding user response:
I think you mean this:
import numpy as np
# Make synthetic data
x = np.arange(256, dtype=np.uint8)
# Take pairs of elements shifted by 4 bits and OR together
d2by4 = (x[::2] & 0xf0) | (x[1::2] >> 4)
In [16]: d2by4.dtype
Out[16]: dtype('uint8')
In [21]: d2by4
Out[21]:
array([ 0, 0, 0, 0, 0, 0, 0, 0, 17, 17, 17, 17, 17,
17, 17, 17, 34, 34, 34, 34, 34, 34, 34, 34, 51, 51,
51, 51, 51, 51, 51, 51, 68, 68, 68, 68, 68, 68, 68,
68, 85, 85, 85, 85, 85, 85, 85, 85, 102, 102, 102, 102,
102, 102, 102, 102, 119, 119, 119, 119, 119, 119, 119, 119, 136,
136, 136, 136, 136, 136, 136, 136, 153, 153, 153, 153, 153, 153,
153, 153, 170, 170, 170, 170, 170, 170, 170, 170, 187, 187, 187,
187, 187, 187, 187, 187, 204, 204, 204, 204, 204, 204, 204, 204,
221, 221, 221, 221, 221, 221, 221, 221, 238, 238, 238, 238, 238,
238, 238, 238, 255, 255, 255, 255, 255, 255, 255, 255], dtype=uint8)
That says... "take the high nibble of every second element of x
starting with the first and OR it together with the upper nibble shifted right by 4 bits of every second element of x
starting with the second."