def test_rgb_to_husl():
rgb_arr = _img()
husl_new = nphusl.rgb_to_husl(rgb_arr)
for i in range(rgb_arr.shape[0]):
for j in range(rgb_arr.shape[1]):
assert _diff_hue(husl_new[i, j],
husl.rgb_to_husl(*rgb_arr[i, j]))
def test_to_husl_2d():
img = _img()[0]
rgb_arr = img * 255
husl_new = nphusl.to_husl(rgb_arr)
for row in range(rgb_arr.shape[0]):
husl_old = husl.rgb_to_husl(*img[row])
assert _diff(husl_new[row], husl_old)
def test_rgb_to_husl_3d():
rgb_arr = np.ascontiguousarray(_img()[:5, :5])
husl_new = nphusl.rgb_to_husl(rgb_arr)
for row in range(husl_new.shape[0]):
for col in range(husl_new.shape[1]):
husl_old = husl.rgb_to_husl(*rgb_arr[row][col])
assert _diff_hue(husl_new[row, col], husl_old)
def test_to_husl_2d():
img = np.ascontiguousarray(_img()[:, 4])
float_img = transform.ensure_rgb_float(img)
husl_new = nphusl.to_husl(img)
for row in range(img.shape[0]):
husl_old = husl.rgb_to_husl(*float_img[row])
_diff_husl(husl_new[row], husl_old)
def test_cython_rgb_to_husl():
from nphusl import _nphusl_cython as cy
rgb = np.ndarray(dtype=float, shape=(2, 2, 3))
rgb[:] = 200.0, 90.2, 240.4
rgb[:] /= 255.0
hsl = cy.rgb_to_husl(rgb)
hsl_std = husl.rgb_to_husl(*(200.0/255, 90.2/255, 240.4/255))
assert _diff(hsl, hsl_std, 0.1)
def test_to_husl_3d():
img = _img()
rgb_arr = img * 255
husl_new = nphusl.to_husl(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])
assert _diff_hue(husl_new[row, col], husl_old)
def test_to_husl_3d():
img = _img()
float_img = transform.ensure_rgb_float(img)
husl_new = nphusl.to_husl(img)
for row in range(img.shape[0]):
for col in range(img.shape[1]):
husl_old = husl.rgb_to_husl(*float_img[row, col])
_diff_husl(husl_new[row, col], husl_old)
def husl(self):
HUSL_Value = self.HUSL_Value
_vmap = self._vmap
result = _vmap.get("husl")
if result is None:
h, s, l = husl.rgb_to_husl(*self.rgb)
result = _vmap["husl"] = HUSL_Value(h, s / 100., l / 100.)
return result
def test_rgb_to_husl_3d():
rgb_arr = np.ascontiguousarray(_img()[:5, :5])
float_arr = transform.ensure_rgb_float(rgb_arr)
husl_new = _nphusl._rgb_to_husl(rgb_arr)
for row in range(husl_new.shape[0]):
for col in range(husl_new.shape[1]):
husl_old = husl.rgb_to_husl(*float_arr[row, col])
_diff_husl(husl_new[row, col], husl_old)
def husl (self) :
HUSL_Value = self.HUSL_Value
_vmap = self._vmap
result = _vmap.get ("husl")
if result is None :
h, s, l = husl.rgb_to_husl (* self.rgb)
result = _vmap ["husl"] = HUSL_Value (h, s / 100., l / 100.)
return result
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_husl_gray():
img = _img()
img[..., 1] = img[..., 0]
img[..., 2] = img[..., 0]
rgb_arr = img[..., 0] * 255 # single channel
husl_new = nphusl.to_husl(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])
assert _diff_hue(husl_new[row, col], husl_old)
def test_to_husl_gray():
img = transform.ensure_rgb_float(_img())
img[..., 1] = img[..., 0]
img[..., 2] = img[..., 0]
gray_arr = img[..., 0] # single channel
husl_new = nphusl.to_husl(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])
_diff_husl(husl_new[row, col], husl_old)
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_lch_to_husl():
rgb_arr = _img()
lch_arr = nphusl.rgb_to_lch(rgb_arr)
hsl_from_lch_arr = nphusl.lch_to_husl(lch_arr)
hsl_from_rgb_arr = nphusl.rgb_to_husl(rgb_arr)
print(rgb_arr[30:34, 0])
print(hsl_from_lch_arr[30:34, 0])
print(hsl_from_rgb_arr[30:34, 0])
for i in range(rgb_arr.shape[0]):
old_lch = husl.rgb_to_lch(*rgb_arr[i, 0])
hsl_old = husl.lch_to_husl(old_lch)
hsl_old = husl.rgb_to_husl(*rgb_arr[i, 0])
assert _diff(lch_arr[i, 0], old_lch)
assert _diff_hue(hsl_from_lch_arr[i, 0], hsl_from_rgb_arr[i, 0])
assert _diff_hue(hsl_from_lch_arr[i, 0], hsl_from_rgb_arr[i, 0])
def test_to_husl_gray_3d():
img = _img()
img[..., 1] = img[..., 0] # makes things gray
img[..., 2] = img[..., 0] # makes things gray
img_float = transform.ensure_rgb_float(img)
husl_new = nphusl.to_husl(img)
was_wrong = False
for row in range(img.shape[0]):
for col in range(img.shape[1]):
husl_old = husl.rgb_to_husl(*img_float[row, col])
a = husl.husl_to_rgb(*husl_old)
b = husl.husl_to_rgb(*husl_new[row, col])
a = np.asarray(a)
b = np.asarray(b)
i = row * img.shape[1] * 3 + col * 3
_diff_husl(husl_new[row, col], husl_old)
def _ref_to_husl(rgb):
asfloat = (c / 255.0 for c in rgb)
return husl.rgb_to_husl(*asfloat)
