convert a grayscale image to a 3-channel image
Question:
I want to convert a gray-scale image with shape (height,width)
to a 3 channels image with shape (height,width,nchannels)
. The work is done with a for-loop
, but there must be a neat way. Here is a piece code in program, can someone give a hint. please advice.
30 if img.shape == (height,width): # if img is grayscale, expand
31 print "convert 1-channel image to ", nchannels, " image."
32 new_img = np.zeros((height,width,nchannels))
33 for ch in range(nchannels):
34 for xx in range(height):
35 for yy in range(width):
36 new_img[xx,yy,ch] = img[xx,yy]
37 img = new_img
Answers:
You can use np.stack
to accomplish this much more concisely:
img = np.array([[1, 2], [3, 4]])
stacked_img = np.stack((img,)*3, axis=-1)
print(stacked_img)
# array([[[1, 1, 1],
# [2, 2, 2]],
# [[3, 3, 3],
# [4, 4, 4]]])
I want to convert a gray-scale image with shape (height,width)
to a 3 channels image with shape (height,width,nchannels)
. The work is done with a for-loop
, but there must be a neat way. Here is a piece code in program, can someone give a hint. please advice.
30 if img.shape == (height,width): # if img is grayscale, expand
31 print "convert 1-channel image to ", nchannels, " image."
32 new_img = np.zeros((height,width,nchannels))
33 for ch in range(nchannels):
34 for xx in range(height):
35 for yy in range(width):
36 new_img[xx,yy,ch] = img[xx,yy]
37 img = new_img
You can use np.stack
to accomplish this much more concisely:
img = np.array([[1, 2], [3, 4]])
stacked_img = np.stack((img,)*3, axis=-1)
print(stacked_img)
# array([[[1, 1, 1],
# [2, 2, 2]],
# [[3, 3, 3],
# [4, 4, 4]]])