问题
I'm using OpenCV with Python. My code is:
img_hsv = cv2.cvtColor(image,cv.CV_BGR2HSV)
img_lab = cv2.cvtColor(image,cv.CV_BGR2Lab)
When I access to a pixel value I'm getting 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 not correct because when I translate the values of OpenCV like you said to HSV I get random colors.
For example. Original image detection with the values of img_hsv:
If I get those values and I reverse the order, I am getting the 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 of the img_hsv, if I invert the order I am getting the RGB Value... What is OpenCV doing in img_hsv = cv2.cvtColor(image,cv.CV_BGR2HSV) then? I think OpenCV returns BGR values...
回答1:
OpenCV brings the output of all the color spaces in the range (0, 255) Note: This is Mat type dependent, 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 Lab color space :
L(Lab original) = L(OpenCV) * 100/255.0
a(Lab original) = a(OpenCV) - 128
b(Lab original) = b(OpenCV) - 128
Reference
Adding a check, 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
来源：https://stackoverflow.com/questions/43307959/how-to-get-hsv-and-lab-color-space