RGB to YUV and YUV to RGB conversion for Numpy

rgb2yuv_yuv2rgb.py

import numpy as np


#input is a RGB numpy array with shape (height,width,3), can be uint,int, float or double, values expected in the range 0..255
#output is a double YUV numpy array with shape (height,width,3), values in the range 0..255
def RGB2YUV( rgb ):
     
    m = np.array([[ 0.29900, -0.16874,  0.50000],
                 [0.58700, -0.33126, -0.41869],
                 [ 0.11400, 0.50000, -0.08131]])
     
    yuv = np.dot(rgb,m)
    yuv[:,:,1:]+=128.0
    return yuv

#input is an YUV numpy array with shape (height,width,3) can be uint,int, float or double,  values expected in the range 0..255
#output is a double RGB numpy array with shape (height,width,3), values in the range 0..255
def YUV2RGB( yuv ):
      
    m = np.array([[ 1.0, 1.0, 1.0],
                 [-0.000007154783816076815, -0.3441331386566162, 1.7720025777816772],
                 [ 1.4019975662231445, -0.7141380310058594 , 0.00001542569043522235] ])
    
    rgb = np.dot(yuv,m)
    rgb[:,:,0]-=179.45477266423404
    rgb[:,:,1]+=135.45870971679688
    rgb[:,:,2]-=226.8183044444304
    return rgb

Its public domain.

🥳

i get results for YUV2RGB out of 0,255

def YUV2RGB( yuv ):
      
    m = np.array([[ 1.0, 1.0, 1.0],
                 [-0.000007154783816076815, -0.3441331386566162, 1.7720025777816772],
                 [ 1.4019975662231445, -0.7141380310058594 , 0.00001542569043522235] ])
    
    rgb = np.dot(yuv,m)
    rgb[:,:,0]-=179.45477266423404
    rgb[:,:,1]+=135.45870971679688
    rgb[:,:,2]-=226.8183044444304
    rgb = rgb.clip(0,255)
    return rgb

This did not work for me, I had to make my own version: https://gist.github.com/awoimbee/83c0a409e8aeb1700d999505a5ee9bf7
I calculated the matrix's components from OpenCV's constants.

Wonderful! Please mark it as BT.601 colorspace.