The algorithm I'm using is:
def rgb2hsv(r, g, b):
r, g, b = r/255.0, g/255.0, b/255.0
mx = max(r, g, b)
mn = min(r, g, b)
df = mx-mn
if mx == mn:
h = 0
elif mx == r:
h = (60 * ((g-b)/df) + 360) % 360
elif mx == g:
h = (60 * ((b-r)/df) + 120) % 360
elif mx == b:
h = (60 * ((r-g)/df) + 240) % 360
if mx == 0:
s = 0
else:
s = df/mx
v = mx
return h, s, v
def my_bgr_to_hsv(bgr_image):
height, width, c = bgr_image.shape
hsv_image = np.zeros(shape = bgr_image.shape)
#The R,G,B values are divided by 255 to change the range from 0..255 to 0..1:
for h in range(height):
for w in range(width):
b,g,r = bgr_image[h,w]
hsv_image[h,w] = rgb2hsv(r,g,b)
return hsv_image
The problem that I'm getting is that when I want to display the image, I get only a black screen.
This is how I'm trying to display the image:
cv.imshow("hello", cv.cvtColor(np.uint8(hsv_image), cv.COLOR_HSV2BGR))
As you can see I convert it back to bgr in order to use cv.imshow, as it only uses bgr.
I don't think I understand enough of opencv or numpy to debug it.
Simply using imshow, shows the original picture in the wrong colors, which makes me think it can't be completely wrong.
