I have a numpy array with shape (3, 256, 256) which is a 3 channel (RGB) image of resoulution 256x256. I am trying to save this to disk with Image from PIL by doing the following:
from PIL import Image
import numpy as np
#... get array s.t. arr.shape = (3,256, 256)
img = Image.fromarray(arr, 'RGB')
img.save('out.png')
However this is saving an image of dimensions 256x3 to disk
The @Dietrich answer is valid, however in some cases it will flip the image. Since the transpose operator reverses the index, if the image is stored in RGB x rows x cols the transpose operator will yield cols x rows x RGB (which is the rotated image and not the desired result).
>>> arr = np.random.uniform(size=(3,256,257))*255
Note the 257 for visualization purposes.
>>> arr.T.shape
(257, 256, 3)
>>> arr.transpose(1, 2, 0).shape
(256, 257, 3)
The last one is what you might want in some cases, since it reorders the image (rows x cols x RGB in the example) instead of fully transpose it.
>>> arr = np.random.uniform(size=(3,256,256))*255
>>> arr = np.ascontiguousarray(arr.transpose(1,2,0))
>>> img = Image.fromarray(arr, 'RGB')
>>> img.save('out.png')
Probably the cast to contiguous array is not even needed, but is better to be sure that the image is contiguous before saving it.
Try transposing arr which gives you an (256, 256, 3) array:
arr = np.random.uniform(size=(3,256,256))*255
img = Image.fromarray(arr.T, 'RGB')
img.save('out.png')
You can use opencv to do merge three channel and save as img.
import cv2
import numpy as np
arr = np.random.uniform(size=(3,256,256))*255 # It's a r,g,b array
img = cv2.merge((arr[2], arr[1], arr[0])) # Use opencv to merge as b,g,r
cv2.imwrite('out.png', img)
np.swapaxesto reshape to a(256,256,3)array?Image.fromarray(np.uint8(arr), 'RGB')