imshow doesn't need convert from BGR to RGB
Question:
As I’m lead to believe, OpenCV reads images in BGR colorspace ordering 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 ordering within the function automatically (from BGR to RGB) or the ordering has been BGR all along?
Answers:
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
If you do not need to use any other Image processing library (example Matplotlib’s imshow), there is no need to do color scale conversion. Below code is an example, where the color scale conversion is done but when the image is loaded, it is still loaded in BGR. This conversion is not needed as the image is displayed using cv2.imshow().
import cv2
# read the image #
image = cv2.imread('<<Image Path>>')
image_rgb = cv2.cvtColor(image,cv2.COLOR_BGR2RGB)
# write a function to draw circles on the image #
def draw_circle(event,x,y,flags,params):
if event == cv2.EVENT_RBUTTONDOWN:
cv2.circle(img=image_rgb,center=(x,y),radius=100,color=(0,0,255),thickness=10)
# Open CV callbacks #
cv2.namedWindow(winname='ImageWindow')
cv2.setMouseCallback('ImageWindow',draw_circle)
# display the image till the user hits the ESC key #
while True:
cv2.imshow('ImageWindow',image_rgb)
if cv2.waitKey(20) & 0xFF == 27:
break
cv2.destroyAllWindows()
Alternatively, you can use imutils.opencv2matplotlib() function, which does not need BGR to RGB conversion.
opencv_image_with_bgr_channels = cv2.imread('path/to/color_image.jpg')
matplotlib_compatible_image_with_rgb_channels = opencv_image_with_bgr_channels[:,:, ::-1]
This converts BGR to RGB Channels Image by reversing the channels.
for matplotlib we need to change BGR to RGB:
img = cv2.imread("image_name")
img = img[...,::-1]
plt.imshow(img)
As I’m lead to believe, OpenCV reads images in BGR colorspace ordering 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 ordering within the function automatically (from BGR to RGB) or the ordering 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
If you do not need to use any other Image processing library (example Matplotlib’s imshow), there is no need to do color scale conversion. Below code is an example, where the color scale conversion is done but when the image is loaded, it is still loaded in BGR. This conversion is not needed as the image is displayed using cv2.imshow().
import cv2
# read the image #
image = cv2.imread('<<Image Path>>')
image_rgb = cv2.cvtColor(image,cv2.COLOR_BGR2RGB)
# write a function to draw circles on the image #
def draw_circle(event,x,y,flags,params):
if event == cv2.EVENT_RBUTTONDOWN:
cv2.circle(img=image_rgb,center=(x,y),radius=100,color=(0,0,255),thickness=10)
# Open CV callbacks #
cv2.namedWindow(winname='ImageWindow')
cv2.setMouseCallback('ImageWindow',draw_circle)
# display the image till the user hits the ESC key #
while True:
cv2.imshow('ImageWindow',image_rgb)
if cv2.waitKey(20) & 0xFF == 27:
break
cv2.destroyAllWindows()
Alternatively, you can use imutils.opencv2matplotlib() function, which does not need BGR to RGB conversion.
opencv_image_with_bgr_channels = cv2.imread('path/to/color_image.jpg')
matplotlib_compatible_image_with_rgb_channels = opencv_image_with_bgr_channels[:,:, ::-1]
This converts BGR to RGB Channels Image by reversing the channels.
for matplotlib we need to change BGR to RGB:
img = cv2.imread("image_name")
img = img[...,::-1]
plt.imshow(img)