How to convert a NumPy array to PIL image applying matplotlib colormap

Quite a busy one-liner, but here it is:

1. First ensure your NumPy array, myarray, is normalised with the max value at 1.0.
2. Apply the colormap directly to myarray.
3. Rescale to the 0-255 range.
4. Convert to integers, using np.uint8().
5. Use Image.fromarray().

And you're done:

from PIL import Image
from matplotlib import cm
im = Image.fromarray(np.uint8(cm.gist_earth(myarray)*255))

with plt.savefig():

with im.save():

• input = numpy_image
• np.unit8 -> converts to integers
• convert('RGB') -> converts to RGB

• Image.fromarray -> returns an image object

  from PIL import Image
  import numpy as np
  
  PIL_image = Image.fromarray(np.uint8(numpy_image)).convert('RGB')
  
  PIL_image = Image.fromarray(numpy_image.astype('uint8'), 'RGB')
  

The method described in the accepted answer didn't work for me even after applying changes mentioned in its comments. But the below simple code worked:

import matplotlib.pyplot as plt
plt.imsave(filename, np_array, cmap='Greys')

np_array could be either a 2D array with values from 0..1 floats o2 0..255 uint8, and in that case it needs cmap. For 3D arrays, cmap will be ignored.