如何将1d数组转换为3d数组（将灰度图像转换为rgb格式）？

Question

I have an image in the numpy array format, I wrote the code assuming rgb image as input but I have found that the input consists of black and white image.

for what should have been a RGB ie (256,256,3) dimension image, I got the input as Grayscale (256,256) array image and I want to convert it to (256,256,3)

This is what I have in numpy array:

[[0 0 0 ... 0 0 0]
 [0 0 0 ... 0 0 0]
 [0 0 0 ... 0 0 0]
 ...
 [0 0 0 ... 0 0 0]
 [0 0 0 ... 0 0 0]
 [0 0 0 ... 0 0 0]]
(256, 256)

This is what I want:(an array of same elements 3 times for every value in the array above)

[[[0. 0. 0.]
  [0. 0. 0.]
  [0. 0. 0.]
  ...
  [0. 0. 0.]
  [0. 0. 0.]
  [0. 0. 0.]]]

Is there any numpy function that does this? If not is there any way to do this in python array and convert it to numpy?

Answer 1

You can use numpy.dstack to stack the 2D arrays along the third axis:

import numpy as np

a = np.array([[1, 2], [3, 4]])
b = np.dstack([a, a, a])

results:

[[[1 1 1]
  [2 2 2]]
 [[3 3 3]
  [4 4 4]]]

or use opencv merge function to merge 3 color channels.

Answer 2

You can do it in two ways:

1. You can use opencv for this. To converts the image from Gray to RGB:

 import cv2 import numpy as np gray = np.random.rand(256, 256) gary2rgb = cv2.cvtColor(gray,cv2.COLOR_GRAY2RGB) 

2. Using only numpy, you can do it in the following way:

 import numpy as np def convert_gray2rgb(image): width, height = image.shape out = np.empty((width, height, 3), dtype=np.uint8) out[:, :, 0] = image out[:, :, 1] = image out[:, :, 2] = image return out gray = np.random.rand(256, 256) # gray scale image gray2rgb = convert_gray2rgb(gray)