As I'm lead to believe, OpenCV reads images in the BGR colorspace and we usually have to convert it back to RGB like this:
img = cv2.cvtColor(img, cv2.COLOR_BGR2RGB)
But when I try to simply read an image and show it, the coloring seems fine (without the need to convert BGR to RGB):
img_bgr = cv2.imread(image_path)
cv2.imshow('BGR Image',img_bgr)
img_rgb = cv2.cvtColor(img_bgr, cv2.COLOR_BGR2RGB)
cv2.imshow('RGB Image',img_rgb )
cv2.waitkey(0)
So is imshow() changing the colorspace within the function automatically (from BGR to RGB) or the colorspace has been BGR all along?
BGR and RGB are not color spaces, they are just conventions for the order of the different color channels. cv2.cvtColor(img, cv2.COLOR_BGR2RGB) doesn't do any computations (like a conversion to say HSV would), it just switches around the order. Any ordering would be valid - in reality, the three values (red, green and blue) are stacked to form one pixel. You can arrange them any way you like, as long as you tell the display what order you gave it.
OpenCV imread, imwrite and imshow indeed all work with the BGR order, so there is no need to change the order when you read an image with cv2.imread and then want to show it with cv2.imshow.
While BGR is used consistently throughout OpenCV, most other image processing libraries use the RGB ordering. If you want to use matplotlib's imshow but read the image with OpenCV, you would need to convert from BGR to RGB.
screen = cv2.cvtColor(screen, cv2.COLOR_RGB2BGR)
this one line code changes rgb to bgr
