How to visualize an image array with 2 color channels using openCV?-CodePudding

I have some image arrays with a shape of (128,256,2) which have two color channels. I am trying to open the image array using the openCV's imshow but I am continuously getting the following error: >

Invalid number of channels in input image:
>     'VScn::contains(scn)'
> where
>     'scn' is 2

I understand openCV can't open image array with two color space. Is there any way to open the image with the two color channels or to compute element-wise average and convert it an array with one color channel? Kindly help please!

> cv2.imshow("Window", img)

CodePudding user response：

Here is one way that demonstrates adding a black channel to two channels of an image in Python/OpenCV.

Input:

import cv2
import numpy as np

# read a 3 channel image
img = cv2.imread('lena.png')
h, w = img.shape[:2]

# separate channels
b,g,r = cv2.split(img)

# create black image the same size as image
black = np.zeros((h,w), dtype=np.uint8)

# replace the red channel with black
result = cv2.merge([b,g,black])

# save results
cv2.imwrite('lena_black.png', result)

# show results
cv2.imshow('result', result)
cv2.waitKey(0)

Result:

If you already have a 2 channel image, then simply create the black image and use np.dstack([2-channel-image, black]) to make a 3 channel image.

CodePudding user response：

OpenCV does not recognise images with only 2 channels, the solution is to add a black channel.

OpenCV images are represented as numpy arrays:

import cv2
img = cv2.imread(PATH_TO_IMG)

# This returns <class 'numpy.ndarray'>.
type(img)

Now we can use numpy functions to add the 3rd channel (black):

import cv2
import numpy as np

H, W, _ = img.shape
img = np.append(img, np.zeros((H, W, 1)), axis=-1)

cv2.imshow(window_name, img)
cv2.waitKey()

Credits to @fmw42.

Or, you could take the element-wise average across channels, and display it as a grayscale image:

import cv2
import numpy as np

img = np.average(img, axis=-1)

cv2.imshow(window_name, img)
cv2.waitKey()