How can I convert an RGB image into grayscale in Python

Question

I m trying to use matplotlib to read in an RGB image and convert it to grayscale   In matlab I use this   img   rgb2gray imread  image png       In the matplotlib tutorial they don t cover it  They just read in the image  import matplotlib image as mpimg img   mpimg imread  image png     and then they slice the array  but that s not the same thing as converting RGB to grayscale from what I understand   lum img   img     0    I find it hard to believe that numpy or matplotlib doesn t have a built-in function to convert from rgb to gray  Isn t this a common operation in image processing   I wrote a very simple function that works with the image imported using imread in 5 minutes  It s horribly inefficient  but that s why I was hoping for a professional implementation built-in    Sebastian has improved my function  but I m still hoping to find the built-in one   matlab s  NTSC PAL  implementation   import numpy as np  def rgb2gray rgb        r  g  b   rgb     0   rgb     1   rgb     2      gray   0 2989   r   0 5870   g   0 1140   b      return gray

User · Answer

The fastest and current way is to use Pillow  installed via pip install Pillow   The code is then   from PIL import Image img   Image open  input file jpg   convert  L   img save  output file jpg

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How about doing it with Pillow   from PIL import Image img   Image open  image png   convert  LA   img save  greyscale png       Using matplotlib and the formula  Y    0 2989 R   0 5870 G   0 1140 B    you could do   import numpy as np import matplotlib pyplot as plt import matplotlib image as mpimg  def rgb2gray rgb       return np dot rgb      3    0 2989  0 5870  0 1140    img   mpimg imread  image png        gray   rgb2gray img      plt imshow gray  cmap plt get cmap  gray    vmin 0  vmax 1  plt show

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I came to this question via Google  searching for a way to convert an already loaded image to grayscale   Here is a way to do it with SciPy   import scipy misc import scipy ndimage    Load an example image   Use scipy ndimage imread file name  mode  L   if you have your own img   scipy misc face      Convert the image R   img       0  G   img       1  B   img       2  img gray   R   299    1000   G   587    1000   B   114    1000    Show the image scipy misc imshow img gray

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If you re using NumPy SciPy already you may as well use   scipy ndimage imread file name  mode  L

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The tutorial is cheating because it is starting with a greyscale image encoded in RGB  so they are just slicing a single color channel and treating it as greyscale   The basic steps you need to do are to transform from the RGB colorspace to a colorspace that encodes with something approximating the luma chroma model  such as YUV YIQ or HSL HSV  then slice off the luma-like channel and use that as your greyscale image   matplotlib does not appear to provide a mechanism to convert to YUV YIQ  but it does let you convert to HSV   Try using matplotlib colors rgb to hsv img  then slicing the last value  V  from the array for your grayscale   It s not quite the same as a luma value  but it means you can do it all in matplotlib   Background    http   matplotlib sourceforge net api colors api html http   en wikipedia org wiki HSL and HSV   Alternatively  you could use PIL or the builtin colorsys rgb to yiq   to convert to a colorspace with a true luma value   You could also go all in and roll your own luma-only converter  though that s probably overkill

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Use img Convert    supports    L        RGB    and    CMYK     mode  import numpy as np from PIL import Image  img   Image open  IMG center 2018 02 03 00 34 32 784 jpg   img convert  L    print np array img    Output      135 123 134       30   3  14    137 130 137        9  20  13    170 177 183       14  10 250           112  99  91       90  88  80     95 103 111      102  85 103    112  96  86      182 148 114

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image myCamera getImage   crop xx xx xx xx  scale xx xx  greyscale     You can use greyscale   directly for the transformation

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You can also use scikit-image  which provides some functions to convert an image in ndarray  like rgb2gray   from skimage import color from skimage import io  img   color rgb2gray io imread  image png      Notes  The weights used in this conversion are calibrated for contemporary CRT phosphors   Y   0 2125 R   0 7154 G   0 0721 B  Alternatively  you can read image in grayscale by   from skimage import io img   io imread  image png   as gray True

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Three of the suggested methods were tested for speed with 1000 RGBA PNG images  224 x 256 pixels  running with Python 3 5 on Ubuntu 16 04 LTS  Xeon E5 2670 with SSD    Average run times  pil    1 037 seconds  scipy  1 040 seconds  sk     2 120 seconds  PIL and SciPy gave identical numpy arrays  ranging from 0 to 255   SkImage gives arrays from 0 to 1  In addition the colors are converted slightly different  see the example from the CUB-200 dataset   SkImage     PIL         SciPy       Original    Diff        Code   Performance run times   dict sk list    pil list    scipy list    for t in range 100       start time   time time       for i in range 1000           z   random choice filenames png          img   skimage color rgb2gray skimage io imread z       run times  sk   append time time   - start time   start time   time time   for i in range 1000       z   random choice filenames png      img   np array Image open z  convert  L    run times  pil   append time time   - start time   start time   time time   for i in range 1000       z   random choice filenames png      img   scipy ndimage imread z  mode  L   run times  scipy   append time time   - start time    for k  v in run times items        print    5     0 3f  seconds  format k  sum v    len v     Output z    Cardinal 0007 3025810472 jpg  img1   skimage color rgb2gray skimage io imread z     255 IPython display display PIL Image fromarray img1  convert  RGB    img2   np array Image open z  convert  L    IPython display display PIL Image fromarray img2   img3   scipy ndimage imread z  mode  L   IPython display display PIL Image fromarray img3    Comparison img diff   np ndarray shape img1 shape  dtype  float32   img diff fill 128  img diff     img1 - img3  img diff -  img diff min   img diff     255 img diff max    IPython display display PIL Image fromarray img diff  convert  RGB     Imports import skimage color import skimage io import random import time from PIL import Image import numpy as np import scipy ndimage import IPython display  Versions skimage version 0 13 0 scipy version 0 19 1 np version 1 13 1

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Using this formula   Y    0 299 R   0 587 G   0 114 B    We can do  import imageio import numpy as np import matplotlib pyplot as plt  pic   imageio imread   image    gray   lambda rgb   np dot rgb        3     0 299   0 587  0 114    gray   gray pic    plt imshow gray  cmap   plt get cmap name    gray      However  the GIMP converting color to grayscale image software has three algorithms to do the task

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you could do     import numpy as np import matplotlib pyplot as plt import matplotlib image as mpimg  def rgb to gray img           grayImage   np zeros img shape          R   np array img       0           G   np array img       1           B   np array img       2            R    R   299          G    G   587          B    B   114           Avg    R G B          grayImage   img          for i in range 3              grayImage     i    Avg          return grayImage         image   mpimg imread  your image png      grayImage   rgb to gray image    plt imshow grayImage  plt show

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You can always read the image file as grayscale right from the beginning using imread from OpenCV   img   cv2 imread  messi5 jpg   0    Furthermore  in case you want to read the image as RGB  do some processing and then convert to Gray Scale you could use cvtcolor from OpenCV   gray image   cv2 cvtColor image  cv2 COLOR BGR2GRAY

[python] How can I convert an RGB image into grayscale in Python?

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