How to convert numpy matrix to cv2 image [python]

Question

I have a numpy 2d matrix which represents a colored image. This matrix has some negative and floating point numbers but of course I can display the image using imshow(my_matrix).

my_matrix_screenshot

I need to perform histogram equalization to this colored image so I found a code here in stackoverflow using cv2 (OpenCV Python equalizeHist colored image) but the problem is I am unable to convert the 2d matrix to cv matrix which takes three channels for RGB.

I was searching again but all I found is to convert regular 3d numpy matrix to cv2 matrix so how can numpy 2d matrix be converted to cv2 matrix which has 3 channels?

Solution

because the numpy.ndarray is the base of cv2, so you just write the code as usual,like

img_np = np.ones([100,100])
img_cv = cv2.resize(img_np,(200,200))

you can try

Comments

[user2266175]

Thank you! but I get totally distracted image or you can say different image when I used the code above!

[Prasad]

Hope you have not used np.random.rand line while running. You have to replace that line with your already existing 90x100 numpy array. I generated a random array just for the code completion sake.

[user2266175]

of course not. I just plugged my matrix over there ;) but I got the weird result. I don't know if it is possible to send you the original image and the resulted image. here is what I am doing: a = new_img_tmp a = np.expand_dims(a, axis = 2) a = np.concatenate((a, a, a), axis = 2) print(a.shape) # (90, 100, 3) plt.imshow(a) plt.show()

[Rafael_Espericueta]

This answer seems to be answering an entirely different question. The question didn't ask about resizing an array.