how to convert an RGB image to numpy array

Question

I have an RGB image  I want to convert it to numpy array  I did the following  im   cv LoadImage  abc tiff   a   numpy asarray im    It creates an array with no shape  I assume it is a iplimage object

User · Answer

Late answer  but I ve come to prefer the imageio module to the other alternatives  import imageio im   imageio imread  abc tiff     Similar to cv2 imread    it produces a numpy array by default  but in RGB form

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You need to use cv LoadImageM instead of cv LoadImage   In  1   import cv In  2   import numpy as np In  3   x   cv LoadImageM  im tif   In  4   im   np asarray x  In  5   im shape Out 5    487  650  3

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load the image by using following syntax -  from keras preprocessing import image  X test image load img  four png  target size  28 28  color mode  grayscale     loading image and then convert it into grayscale and with it s target size  X test image img to array X test    convert image into array

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When using the answer from David Poole I get a SystemError with gray scale PNGs and maybe other files  My solution is   import numpy as np from PIL import Image  img   Image open  filename   try      data   np asarray  img  dtype  uint8    except SystemError      data   np asarray  img getdata    dtype  uint8      Actually img getdata   would work for all files  but it s slower  so I use it only when the other method fails

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You can also use matplotlib for this   from matplotlib image import imread  img   imread  abc tiff   print type img     output   lt class  numpy ndarray  gt

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You can use newer OpenCV python interface  if I m not mistaken it is available since OpenCV 2 2   It natively uses numpy arrays   import cv2 im   cv2 imread  abc tiff  mode  RGB   print type im    result    lt type  numpy ndarray  gt

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I also adopted imageio  but I found the following machinery useful for pre- and post-processing   import imageio import numpy as np  def imload  a    k       i   imageio imread  a    k      i   i transpose  1  0  2      x and y are mixed up for some reason        i   np flip i  1     make coordinate system right-handed           return i 255   def imsave i  url   a    k         Original order of arguments was counterintuitive  It should       read verbally  Save the image to the URL      not  Save to the       URL the image        i   np flip i  1      i   i transpose  1  0  2       i    255      i   i round       i   np maximum i  0      i   np minimum i  255       i   np asarray i  dtype np uint8       imageio imwrite url  i   a    k    The rationale is that I am using numpy for image processing  not just image displaying  For this purpose  uint8s are awkward  so I convert to floating point values ranging from 0 to 1   When saving images  I noticed I had to cut the out-of-range values myself  or else I ended up with a really gray output   The gray output was the result of imageio compressing the full range  which was outside of  0  256   to values that were inside the range    There were a couple other oddities  too  which I mentioned in the comments

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OpenCV image format supports the numpy array interface  A helper function can be made to support either grayscale or color images  This means the BGR -  RGB conversion can be conveniently done with a numpy slice  not a full copy of image data   Note  this is a stride trick  so modifying the output array will also change the OpenCV image data  If you want a copy  use  copy   method on the array   import numpy as np  def img as array im          OpenCV s native format to a numpy array view        w  h  n   im width  im height  im channels     modes    1   L   3   RGB   4   RGBA       if n not in modes          raise Exception  unsupported number of channels   0   format n       out   np asarray im      if n    1          out   out         -1     BGR - gt  RGB conversion     return out

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You can get numpy array of rgb image easily by using numpy and Image from PIL  import numpy as np from PIL import Image import matplotlib pyplot as plt  im   Image open   image name     These two lines im arr   np array im   are all you need plt imshow im arr   Just to verify that image array has been constructed properly

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PIL  Python Imaging Library  and Numpy work well together   I use the following functions   from PIL import Image import numpy as np  def load image  infilename         img   Image open  infilename       img load       data   np asarray  img  dtype  int32        return data  def save image  npdata  outfilename         img   Image fromarray  np asarray  np clip npdata 0 255   dtype  uint8     L        img save  outfilename     The  Image fromarray  is a little ugly because I clip incoming data to  0 255   convert to bytes  then create a grayscale image  I mostly work in gray   An RGB image would be something like    outimg   Image fromarray  ycc uint8   RGB     outimg save   ycc tif

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As of today  your best bet is to use   img   cv2 imread image path      reads an image in the BGR format img   cv2 cvtColor img  cv2 COLOR BGR2RGB      BGR - gt  RGB   You ll see img will be a numpy array of type    lt class  numpy ndarray  gt

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Using Keras  from keras preprocessing import image    img   image load img  path to image   target size  300  300   x   image img to array img  x   np expand dims x  axis 0  images   np vstack  x

[python] how to convert an RGB image to numpy array?

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