def test_to_hue_vs_old():
img = _img()
hue_new = nphusl.to_hue(img)
for row in range(img.shape[0]):
for col in range(img.shape[1]):
husl_old = _ref_to_husl(img[row, col])
diff = 5.0 if husl_old[1] < 1 else 0.1
_diff(hue_new[row, col], husl_old[0], diff=diff)
def test_to_hue_vs_old():
img = _img()
rgb_arr = img * 255
hue_new = nphusl.to_hue(rgb_arr)
for row in range(rgb_arr.shape[0]):
for col in range(rgb_arr.shape[1]):
husl_old = husl.rgb_to_husl(*img[row, col])
diff = 5.0 if husl_old[1] < 1 else 0.0001
assert _diff(hue_new[row, col], husl_old[0], diff=diff)
def test_to_hue_gray():
img = _img()
img[..., 1] = img[..., 0]
img[..., 2] = img[..., 0]
rgb_arr = img[..., 0] * 255 # single channel
hue_new = nphusl.to_hue(rgb_arr)
for row in range(rgb_arr.shape[0]):
for col in range(rgb_arr.shape[1]):
hue_old = husl.rgb_to_husl(*img[row, col])
diff = 5.0 if hue_old[1] < 1 else 0.0001
assert _diff(hue_new[row, col], hue_old[0], diff=diff)
def test_to_hue_gray():
img = _img()
img = transform.ensure_rgb_float(img)
img[..., 1] = img[..., 0]
img[..., 2] = img[..., 0]
gray_arr = img[..., 0] # single channel
hue_new = nphusl.to_hue(gray_arr)
for row in range(gray_arr.shape[0]):
for col in range(gray_arr.shape[1]):
husl_old = husl.rgb_to_husl(*img[row, col])
assert husl_old[1] < 1 # low saturation
# inaccurate hue values at low saturation
_diff(hue_new[row, col], husl_old[0], diff=5)
def test_to_hue_3d():
img = _img() # 3D
as_husl = nphusl.rgb_to_husl(img / 255.0)
just_hue = nphusl.to_hue(img)
assert _diff(as_husl[..., 0], just_hue)
def test_to_hue():
img = _img()[0] # 2D
as_husl = nphusl.to_husl(img)
just_hue = nphusl.to_hue(img)
assert _diff(as_husl[..., 0], just_hue)
def test_to_hue_3d():
img = _img() # 3D
as_husl = _nphusl._rgb_to_husl(img / 255.0)
just_hue = nphusl.to_hue(img)
_diff(as_husl[..., 0], just_hue)
def test_to_hue_2d():
img = _img()[:, 14] # 2D RGB
as_husl = nphusl.to_husl(img)
just_hue = nphusl.to_hue(img)
_diff(as_husl[..., 0], just_hue)
