how to save an array as a grayscale image with matplotlib/numpy?
Question:
I am trying to save a numpy array of dimensions 128×128 pixels into a grayscale image.
I simply thought that the pyplot.imsave function would do the job but it’s not, it somehow converts my array into an RGB image.
I tried to force the colormap to Gray during conversion but eventhough the saved image appears in grayscale, it still has a 128x128x4 dimension.
Here is a code sample I wrote to show the behaviour :
import numpy as np
import matplotlib.pyplot as plt
import matplotlib.image as mplimg
from matplotlib import cm
x_tot = 10e-3
nx = 128
x = np.arange(-x_tot/2, x_tot/2, x_tot/nx)
[X, Y] = np.meshgrid(x,x)
R = np.sqrt(X**2 + Y**2)
diam = 5e-3
I = np.exp(-2*(2*R/diam)**4)
plt.figure()
plt.imshow(I, extent = [-x_tot/2, x_tot/2, -x_tot/2, x_tot/2])
print I.shape
plt.imsave('image.png', I)
I2 = plt.imread('image.png')
print I2.shape
mplimg.imsave('image2.png',np.uint8(I), cmap = cm.gray)
testImg = plt.imread('image2.png')
print testImg.shape
In both cases the results of the “print” function are (128,128,4).
Can anyone explain why the imsave function is creating those dimensions eventhough my input array is of a luminance type?
And of course, does anyone have a solution to save the array into a standard grayscale format?
Thanks!
Answers:
With PIL it should work like this
from PIL import Image
I8 = (((I - I.min()) / (I.max() - I.min())) * 255.9).astype(np.uint8)
img = Image.fromarray(I8)
img.save("file.png")
I didn’t want to use PIL in my code and as noted in the question I ran into the same problem with pyplot, where even in grayscale, the file is saved in MxNx3 matrix.
Since the actual image on disk wasn’t important to me, I ended up writing the matrix as is and reading it back “as-is” using numpy’s save and load methods:
np.save("filename", image_matrix)
And:
np.load("filename.npy")
There is also a possibility to use scikit-image, then there is no need to convert numpy array into a PIL object.
from skimage import io
io.imsave('output.tiff', I.astype(np.uint16))
There is also an alternative of using imageio. It provides an easy and convenient API and it is bundled with Anaconda. It can save grayscale images as a single color channel file.
Quoting the documentation
>>> import imageio
>>> im = imageio.imread('imageio:astronaut.png')
>>> im.shape # im is a numpy array
(512, 512, 3)
>>> imageio.imwrite('astronaut-gray.jpg', im[:, :, 0])
I am trying to save a numpy array of dimensions 128×128 pixels into a grayscale image.
I simply thought that the pyplot.imsave function would do the job but it’s not, it somehow converts my array into an RGB image.
I tried to force the colormap to Gray during conversion but eventhough the saved image appears in grayscale, it still has a 128x128x4 dimension.
Here is a code sample I wrote to show the behaviour :
import numpy as np
import matplotlib.pyplot as plt
import matplotlib.image as mplimg
from matplotlib import cm
x_tot = 10e-3
nx = 128
x = np.arange(-x_tot/2, x_tot/2, x_tot/nx)
[X, Y] = np.meshgrid(x,x)
R = np.sqrt(X**2 + Y**2)
diam = 5e-3
I = np.exp(-2*(2*R/diam)**4)
plt.figure()
plt.imshow(I, extent = [-x_tot/2, x_tot/2, -x_tot/2, x_tot/2])
print I.shape
plt.imsave('image.png', I)
I2 = plt.imread('image.png')
print I2.shape
mplimg.imsave('image2.png',np.uint8(I), cmap = cm.gray)
testImg = plt.imread('image2.png')
print testImg.shape
In both cases the results of the “print” function are (128,128,4).
Can anyone explain why the imsave function is creating those dimensions eventhough my input array is of a luminance type?
And of course, does anyone have a solution to save the array into a standard grayscale format?
Thanks!
With PIL it should work like this
from PIL import Image
I8 = (((I - I.min()) / (I.max() - I.min())) * 255.9).astype(np.uint8)
img = Image.fromarray(I8)
img.save("file.png")
I didn’t want to use PIL in my code and as noted in the question I ran into the same problem with pyplot, where even in grayscale, the file is saved in MxNx3 matrix.
Since the actual image on disk wasn’t important to me, I ended up writing the matrix as is and reading it back “as-is” using numpy’s save and load methods:
np.save("filename", image_matrix)
And:
np.load("filename.npy")
There is also a possibility to use scikit-image, then there is no need to convert numpy array into a PIL object.
from skimage import io
io.imsave('output.tiff', I.astype(np.uint16))
There is also an alternative of using imageio. It provides an easy and convenient API and it is bundled with Anaconda. It can save grayscale images as a single color channel file.
Quoting the documentation
>>> import imageio
>>> im = imageio.imread('imageio:astronaut.png')
>>> im.shape # im is a numpy array
(512, 512, 3)
>>> imageio.imwrite('astronaut-gray.jpg', im[:, :, 0])