Extracting a region from an image using slicing in Python, OpenCV

Question

I have an image and I want to extract a region from it. I have coordinates of left upper corner and right lower corner of this region. In gray scale I do it like this:

I = cv2.imread("lena.png") I = cv2.cvtColor(I, cv2.COLOR_RGB2GRAY) region = I[248:280,245:288] tools.show_1_image_pylab(region) 

I can't figure it out how to do it in color. I thought of extracting each channel R, G, B; slicing this region from each of the channels and to merge them back together but there is gotta be a shorter way.

Answer 1

There is a slight difference in pixel ordering in OpenCV and Matplotlib.

OpenCV follows BGR order, while matplotlib likely follows RGB order.

So when you display an image loaded in OpenCV using pylab functions, you may need to convert it into RGB mode. ( I am not sure if any easy method is there). Below method demonstrate it:

import cv2 import numpy as np import matplotlib.pyplot as plt  img = cv2.imread('messi4.jpg') b,g,r = cv2.split(img) img2 = cv2.merge([r,g,b]) plt.subplot(121);plt.imshow(img) # expects distorted color plt.subplot(122);plt.imshow(img2) # expect true color plt.show()  cv2.imshow('bgr image',img) # expects true color cv2.imshow('rgb image',img2) # expects distorted color cv2.waitKey(0) cv2.destroyAllWindows() 

NB : Please check @Amro 's comment below for better method of conversion between BGR and RGB. img2 = img[:,:,::-1] . Very simple.

Run this code and see the difference in result yourself. Below is what I got :

Using Matplotlib :

Using OpenCV :

Answer 2

2 more options not mentioned yet:

img[..., ::-1] # same as the mentioned img[:, :, ::-1] but slightly shorter 

and the versatile

cv2.cvtColor(img, cv2.COLOR_BGR2RGB)