How to convert a python numpy array to an RGB image with Opencv 2.4?

I have searched for similar questions, but haven't found anything helpful as most solutions use older versions of OpenCV.

I have a 3D numpy array, and I would like to display and/or save it as a BGR image using OpenCV (cv2).

As a short example, suppose I had:

import numpy, cv2
b = numpy.zeros([5,5,3])

b[:,:,0] = numpy.ones([5,5])*64
b[:,:,1] = numpy.ones([5,5])*128
b[:,:,2] = numpy.ones([5,5])*192

What I would like to do is save and display b as a color image similar to:

cv2.imwrite('color_img.jpg', b)
cv2.imshow('Color image', b)
cv2.waitKey(0)
cv2.destroyAllWindows()

This doesn't work, presumably because the data type of b isn't correct, but after substantial searching, I can't figure out how to change it to the correct one. If you can offer any pointers, it would be greatly appreciated!

You don't need to convert NumPy array to Mat because OpenCV cv2 module can accept NumPyarray. The only thing you need to care for is that {0,1} is mapped to {0,255} and any value bigger than 1 in NumPy array is equal to 255. So you should divide by 255 in your code, as shown below.

img = numpy.zeros([5,5,3])

img[:,:,0] = numpy.ones([5,5])*64/255.0
img[:,:,1] = numpy.ones([5,5])*128/255.0
img[:,:,2] = numpy.ones([5,5])*192/255.0

cv2.imwrite('color_img.jpg', img)
cv2.imshow("image", img)
cv2.waitKey()

You are looking for scipy.misc.toimage:

import scipy.misc
rgb = scipy.misc.toimage(np_array)

It seems to be also in scipy 1.0, but has a deprecation warning. Instead, you can use pillow and PIL.Image.fromarray

The images c, d, e , and f in the following show colorspace conversion they also happen to be numpy arrays <type 'numpy.ndarray'>:

import numpy, cv2
def show_pic(p):
        ''' use esc to see the results'''
        print(type(p))
        cv2.imshow('Color image', p)
        while True:
            k = cv2.waitKey(0) & 0xFF
            if k == 27: break 
        return
        cv2.destroyAllWindows()

b = numpy.zeros([200,200,3])

b[:,:,0] = numpy.ones([200,200])*255
b[:,:,1] = numpy.ones([200,200])*255
b[:,:,2] = numpy.ones([200,200])*0
cv2.imwrite('color_img.jpg', b)


c = cv2.imread('color_img.jpg', 1)
c = cv2.cvtColor(c, cv2.COLOR_BGR2RGB)

d = cv2.imread('color_img.jpg', 1)
d = cv2.cvtColor(c, cv2.COLOR_RGB2BGR)

e = cv2.imread('color_img.jpg', -1)
e = cv2.cvtColor(c, cv2.COLOR_BGR2RGB)

f = cv2.imread('color_img.jpg', -1)
f = cv2.cvtColor(c, cv2.COLOR_RGB2BGR)


pictures = [d, c, f, e]

for p in pictures:
        show_pic(p)
# show the matrix
print(c)
print(c.shape)

See here for more info: http://docs.opencv.org/modules/imgproc/doc/miscellaneous_transformations.html#cvtcolor

OR you could:

img = numpy.zeros([200,200,3])

img[:,:,0] = numpy.ones([200,200])*255
img[:,:,1] = numpy.ones([200,200])*255
img[:,:,2] = numpy.ones([200,200])*0

r,g,b = cv2.split(img)
img_bgr = cv2.merge([b,g,r])

If anyone else simply wants to display a black image as a background, here e.g. for 500x500 px:

import cv2
import numpy as np

black_screen  = np.zeros([500,500,3])
cv2.imshow("Simple_black", black_screen)
cv2.waitKey(0)

This is due to the fact that cv2 uses the type "uint8" from numpy. Therefore, you should define the type when creating the array.

Something like the following:

import numpy
import cv2

b = numpy.zeros([5,5,3], dtype=numpy.uint8)
b[:,:,0] = numpy.ones([5,5])*64
b[:,:,1] = numpy.ones([5,5])*128
b[:,:,2] = numpy.ones([5,5])*192