OpenCV giving wrong color to colored images on loading

Question

I'm loading in a color image in Python OpenCV and plotting the same. However, the image I get has it's colors all mixed up.

Here is the code:

import cv2 import numpy as np from numpy import array, arange, uint8  from matplotlib import pyplot as plt   img = cv2.imread('lena_caption.png', cv2.IMREAD_COLOR) bw_img = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)  images = [] images.append(img) images.append(bw_img)  titles = ['Original Image','BW Image']  for i in xrange(len(images)):     plt.subplot(1,2,i+1),plt.imshow(images[i],'gray')     plt.title(titles[i])     plt.xticks([]),plt.yticks([])  plt.show() 

Here is the original image:

And here is the plotted image:

Answer 1

OpenCV uses BGR as its default colour order for images, matplotlib uses RGB. When you display an image loaded with OpenCv in matplotlib the channels will be back to front.

The easiest way of fixing this is to use OpenCV to explicitly convert it back to RGB, much like you do when creating the greyscale image.

RGB_img = cv2.cvtColor(img, cv2.COLOR_BGR2RGB) 

And then use that in your plot.

Answer 2

As an alternative to the previous answer, you can use (slightly faster)

img = cv2.imread('lena_caption.png')[...,::-1]

%timeit [cv2.cvtColor(cv2.imread(f), cv2.COLOR_BGR2RGB) for f in files]
231 ms ± 3.08 ms per loop (mean ± std. dev. of 7 runs, 1 loop each)

%timeit [cv2.imread(f)[...,::-1] for f in files]
220 ms ± 1.81 ms per loop (mean ± std. dev. of 7 runs, 1 loop each)