How to get the HSV and LAB color space?
I am using OpenCV with Python. My code:
img_hsv = cv2.cvtColor(image,cv.CV_BGR2HSV)
img_lab = cv2.cvtColor(image,cv.CV_BGR2Lab)
When I access a pixel value, I get the values in RGB space, for example:
img_hsv[x][y] = [255,255,255]
How can I normalize HSV and LAB color space? HSV = 360º 100% 100% and LAB = 128 100 100
Edit1. Answering to Rick M: Your solution is wrong because when I translate the OpenCV values as you said to HSV I get random colors.
For example. Initial image detection with values img_hsv
:
If I get these values and I reverse the order, I get RGB values:
HSV Value = 16, 25, 230 -> Invert -> 230, 25, 16 = RGB Value
HSV Value = 97, 237, 199 -> Invert -> 199, 237, 97 = RGB Value
So when I get the values img_hsv
, if I invert the order, I get the RGB value ... What is OpenCV in img_hsv = cv2.cvtColor(image,cv.CV_BGR2HSV)
then? I think OpenCV is returning BGR values ...
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OpenCV displays all the color space in the range (0, 255) Note. It depends on the Mata type assuming 8UC3
here .
So, to bring HSV to its range:
H(HSV original) = H(OpenCV) * 2.0 S(HSV original) = S(OpenCV) * 100/255.0 V(HSV original) = V(OpenCV) * 100/255.0
similarly for the Lab color space:
L(Lab original) = L(OpenCV) * 100/255.0 a(Lab original) = a(OpenCV) - 128 b(Lab original) = b(OpenCV) - 128
Adding validation, real color conversion , python code:
image_rgb = np.zeros((300, 300, 3), np.uint8)
image[:] = (255, 255, 255)
img_hsv = cv2.cvtColor(image_rgb, cv2.COLOR_RGB2HSV)
h = img_hsv[100, 100, 0]
s = img_hsv[100, 100, 1]
v = img_hsv[100, 100, 2]
print h , s , v
>>> 0 0 255
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