HSLA to HSV Converter
Converting a color from HSLA (Hue, Saturation, Lightness, Alpha) to HSV (Hue, Saturation, Value) involves transforming the color values from one color space to another. The conversion can be useful in graphic design and image processing applications.
To convert HSLA to HSV, you can follow these steps:
Convert the HSLA values to their corresponding RGB values. There are different formulas to do this, but one common approach is to use the following formulas:
C = (1 - abs(2L - 1)) * S
X = C * (1 - abs((H / 60) mod 2 - 1))
m = L - C / 2
(R,G,B) =
(C,X,0) if 0 <= H < 60
(X,C,0) if 60 <= H < 120
(0,C,X) if 120 <= H < 180
(0,X,C) if 180 <= H < 240
(X,0,C) if 240 <= H < 300
(C,0,X) if 300 <= H < 360
(R,G,B) = (0,0,0) if S = 0
where H, S, and L are the hue, saturation, and lightness values of the HSLA color, respectively.
Normalize the RGB values to the range 0-1 by dividing each value by 255.
Find the minimum and maximum values among the normalized RGB values.
Calculate the value (V) of the HSV color as the maximum value among the RGB values.
Calculate the saturation (S) of the HSV color as:
S = 0 if V = 0
S = (V - min(R, G, B)) / V otherwise
Calculate the hue (H) of the HSV color as:
scss
H = 0 if V = min(R, G, B)
H = 60 * (G - B) / (V - min(R, G, B)) + 0 if V = R
H = 60 * (B - R) / (V - min(R, G, B)) + 120 if V = G
H = 60 * (R - G) / (V - min(R, G, B)) + 240 if V = B
H = 60 * (B - R) / (V - min(R, G, B)) + 360 if V = min(R, G, B)
Normalize the hue value to the range 0-360.
Normalize the alpha value to the range 0-1.
Here is an example Python function that implements this algorithm:
python
def hsla_to_hsva(hsla):
h, s, l, a = hsla
r, g, b = colorsys.hls_to_rgb(h / 360, l, s)
r, g, b = r * 255, g * 255, b * 255
v = max(r, g, b)
if v == 0:
s = 0
else:
s = (v - min(r, g, b)) / v
if s == 0:
h = 0
else:
if v == r:
h = 60 * (g - b) / (v - min(r, g, b))
elif v == g:
h = 60 * (b - r) / (v - min(r, g
To convert HSLA to HSV, you can follow these steps:
Convert the HSLA values to their corresponding RGB values. There are different formulas to do this, but one common approach is to use the following formulas:
C = (1 - abs(2L - 1)) * S
X = C * (1 - abs((H / 60) mod 2 - 1))
m = L - C / 2
(R,G,B) =
(C,X,0) if 0 <= H < 60
(X,C,0) if 60 <= H < 120
(0,C,X) if 120 <= H < 180
(0,X,C) if 180 <= H < 240
(X,0,C) if 240 <= H < 300
(C,0,X) if 300 <= H < 360
(R,G,B) = (0,0,0) if S = 0
where H, S, and L are the hue, saturation, and lightness values of the HSLA color, respectively.
Normalize the RGB values to the range 0-1 by dividing each value by 255.
Find the minimum and maximum values among the normalized RGB values.
Calculate the value (V) of the HSV color as the maximum value among the RGB values.
Calculate the saturation (S) of the HSV color as:
S = 0 if V = 0
S = (V - min(R, G, B)) / V otherwise
Calculate the hue (H) of the HSV color as:
scss
H = 0 if V = min(R, G, B)
H = 60 * (G - B) / (V - min(R, G, B)) + 0 if V = R
H = 60 * (B - R) / (V - min(R, G, B)) + 120 if V = G
H = 60 * (R - G) / (V - min(R, G, B)) + 240 if V = B
H = 60 * (B - R) / (V - min(R, G, B)) + 360 if V = min(R, G, B)
Normalize the hue value to the range 0-360.
Normalize the alpha value to the range 0-1.
Here is an example Python function that implements this algorithm:
python
def hsla_to_hsva(hsla):
h, s, l, a = hsla
r, g, b = colorsys.hls_to_rgb(h / 360, l, s)
r, g, b = r * 255, g * 255, b * 255
v = max(r, g, b)
if v == 0:
s = 0
else:
s = (v - min(r, g, b)) / v
if s == 0:
h = 0
else:
if v == r:
h = 60 * (g - b) / (v - min(r, g, b))
elif v == g:
h = 60 * (b - r) / (v - min(r, g