OpenCV giving wrong color to colored images on loading
PythonImageOpencvColorsRgbPython Problem Overview
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:
Python Solutions
Solution 1 - Python
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.
Solution 2 - Python
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)
Solution 3 - Python
Simple one-line solution
np.flip(img, axis=-1)
This can convert both ways. From RGB to BGR, and from BGR to RGB.
Solution 4 - Python
If you try to read an image using OpenCV, it will use BGR as the default. So you have to use a different approach to read an Image. I have made the required changes to your code to get the desired output has been given below.
import cv2
import numpy as np
from numpy import array, arange, uint8
from matplotlib import pyplot as plt
img = cv2.cvtColor(cv2.imread('lena_caption.png'), cv2.COLOR_BGR2RGB)
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()
Output:
Solution 5 - Python
You may also want to try cv2.IMREAD_UNCHANGED(). See more here to see how it differs from IMREAD_COLOR:
https://www.geeksforgeeks.org/python-opencv-cv2-imread-method/
Solution 6 - Python
after reading the image, reverting the order of bgr matrix to rgb by reading the matrix from right to left:
x = cv2.imread('./image.jpg')
x=x[:,:,::-1]
plt.imshow(x)