[python] 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 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

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

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()

The size of your image is not sufficient to see in a naked eye. So please try to use atleast 50x50

import cv2 as cv
import numpy as np

black_screen = np.zeros([50,50,3])

black_screen[:, :, 2] = np.ones([50,50])*64/255.0
cv.imshow("Simple_black", black_screen)
cv.waitKey(0)
cv.displayAllWindows()

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])