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Add OKLab and Oklch image utilities and nodes, refactor color space nodes #8999

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e678764
Add OKLab and Oklch image utilities and nodes
JPPhoto Mar 27, 2026
33c7a87
refactor: unify oklab color conversions
JPPhoto Mar 27, 2026
e17dbe9
refactor: unify shared color conversions
JPPhoto Mar 28, 2026
783a06f
Merge remote-tracking branch 'origin/main' into oklab-oklch-support
JPPhoto Apr 4, 2026
0942e42
Merge branch 'invoke-ai:main' into oklab-oklch-support
JPPhoto Apr 5, 2026
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126 changes: 54 additions & 72 deletions invokeai/app/invocations/composition-nodes.py
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Original file line number Diff line number Diff line change
Expand Up @@ -14,22 +14,27 @@
from torchvision.transforms.functional import to_pil_image as pil_image_from_tensor

from invokeai.app.invocations.primitives import ImageOutput
from invokeai.backend.image_util.composition import (
CIELAB_TO_UPLAB_ICC_PATH,
MAX_FLOAT,
equivalent_achromatic_lightness,
gamut_clip_tensor,
from invokeai.backend.image_util.color_conversion import (
hsl_from_srgb,
linear_srgb_from_oklab,
linear_srgb_from_oklch,
linear_srgb_from_srgb,
okhsl_from_srgb,
okhsv_from_srgb,
oklab_from_linear_srgb,
remove_nans,
oklab_from_oklch,
oklch_from_oklab,
srgb_from_hsl,
srgb_from_linear_srgb,
srgb_from_okhsl,
srgb_from_okhsv,
)
from invokeai.backend.image_util.composition import (
CIELAB_TO_UPLAB_ICC_PATH,
MAX_FLOAT,
equivalent_achromatic_lightness,
gamut_clip_tensor,
remove_nans,
srgb_from_linear_srgb,
tensor_from_pil_image,
)
from invokeai.backend.stable_diffusion.diffusers_pipeline import image_resized_to_grid_as_tensor
Expand Down Expand Up @@ -136,20 +141,20 @@ def invoke(self, context: InvocationContext) -> ImageOutput:

if space == "hsv":
hsv_tensor = image_resized_to_grid_as_tensor(image_in.convert("HSV"), normalize=False, multiple_of=1)
hsv_tensor[0, :, :] = torch.remainder(torch.add(hsv_tensor[0, :, :], torch.div(self.degrees, 360.0)), 1.0)
hsv_tensor[0, :, :] = torch.remainder(torch.add(hsv_tensor[0, :, :] * 360.0, self.degrees), 360.0) / 360.0
image_out = pil_image_from_tensor(hsv_tensor, mode="HSV").convert("RGB")

elif space == "okhsl":
rgb_tensor = image_resized_to_grid_as_tensor(image_in.convert("RGB"), normalize=False, multiple_of=1)
hsl_tensor = okhsl_from_srgb(rgb_tensor, steps=(3 if self.ok_high_precision else 1))
hsl_tensor[0, :, :] = torch.remainder(torch.add(hsl_tensor[0, :, :], torch.div(self.degrees, 360.0)), 1.0)
hsl_tensor[0, :, :] = torch.remainder(torch.add(hsl_tensor[0, :, :], self.degrees), 360.0)
rgb_tensor = srgb_from_okhsl(hsl_tensor, alpha=0.0)
image_out = pil_image_from_tensor(rgb_tensor, mode="RGB")

elif space == "okhsv":
rgb_tensor = image_resized_to_grid_as_tensor(image_in.convert("RGB"), normalize=False, multiple_of=1)
hsv_tensor = okhsv_from_srgb(rgb_tensor, steps=(3 if self.ok_high_precision else 1))
hsv_tensor[0, :, :] = torch.remainder(torch.add(hsv_tensor[0, :, :], torch.div(self.degrees, 360.0)), 1.0)
hsv_tensor[0, :, :] = torch.remainder(torch.add(hsv_tensor[0, :, :], self.degrees), 360.0)
rgb_tensor = srgb_from_okhsv(hsv_tensor, alpha=0.0)
image_out = pil_image_from_tensor(rgb_tensor, mode="RGB")

Expand Down Expand Up @@ -197,24 +202,9 @@ def invoke(self, context: InvocationContext) -> ImageOutput:
rgb_tensor = image_resized_to_grid_as_tensor(image_in.convert("RGB"), normalize=False, multiple_of=1)

linear_srgb_tensor = linear_srgb_from_srgb(rgb_tensor)

lab_tensor = oklab_from_linear_srgb(linear_srgb_tensor)

# L*a*b* to L*C*h
c_tensor = torch.sqrt(torch.add(torch.pow(lab_tensor[1, :, :], 2.0), torch.pow(lab_tensor[2, :, :], 2.0)))
h_tensor = torch.atan2(lab_tensor[2, :, :], lab_tensor[1, :, :])

# Rotate h
rot_rads = (self.degrees / 180.0) * PI

h_rot = torch.add(h_tensor, rot_rads)
h_rot = torch.remainder(torch.add(h_rot, 2 * PI), 2 * PI)

# L*C*h to L*a*b*
lab_tensor[1, :, :] = torch.mul(c_tensor, torch.cos(h_rot))
lab_tensor[2, :, :] = torch.mul(c_tensor, torch.sin(h_rot))

linear_srgb_tensor = linear_srgb_from_oklab(lab_tensor)
oklch_tensor = oklch_from_oklab(oklab_from_linear_srgb(linear_srgb_tensor))
oklch_tensor[2, :, :] = torch.remainder(torch.add(oklch_tensor[2, :, :], self.degrees), 360.0)
linear_srgb_tensor = linear_srgb_from_oklch(oklch_tensor)

rgb_tensor = srgb_from_linear_srgb(
linear_srgb_tensor, alpha=self.ok_adaptive_gamut, steps=(3 if self.ok_high_precision else 1)
Expand Down Expand Up @@ -602,14 +592,14 @@ def prepare_tensors_from_images(
image_hsv_upper, image_hsv_lower = image_upper.convert("HSV"), image_lower.convert("HSV")
upper_hsv_tensor = torch.stack(
[
tensor_from_pil_image(image_hsv_upper.getchannel("H"), normalize=False)[0, :, :],
tensor_from_pil_image(image_hsv_upper.getchannel("H"), normalize=False)[0, :, :] * 360.0,
tensor_from_pil_image(image_hsv_upper.getchannel("S"), normalize=False)[0, :, :],
tensor_from_pil_image(image_hsv_upper.getchannel("V"), normalize=False)[0, :, :],
]
)
lower_hsv_tensor = torch.stack(
[
tensor_from_pil_image(image_hsv_lower.getchannel("H"), normalize=False)[0, :, :],
tensor_from_pil_image(image_hsv_lower.getchannel("H"), normalize=False)[0, :, :] * 360.0,
tensor_from_pil_image(image_hsv_lower.getchannel("S"), normalize=False)[0, :, :],
tensor_from_pil_image(image_hsv_lower.getchannel("V"), normalize=False)[0, :, :],
]
Expand Down Expand Up @@ -655,29 +645,8 @@ def prepare_tensors_from_images(
if "oklch" in required:
upper_oklab_tensor = oklab_from_linear_srgb(upper_rgb_l_tensor)
lower_oklab_tensor = oklab_from_linear_srgb(lower_rgb_l_tensor)

upper_oklch_tensor = torch.stack(
[
upper_oklab_tensor[0, :, :],
torch.sqrt(
torch.add(
torch.pow(upper_oklab_tensor[1, :, :], 2.0), torch.pow(upper_oklab_tensor[2, :, :], 2.0)
)
),
torch.atan2(upper_oklab_tensor[2, :, :], upper_oklab_tensor[1, :, :]),
]
)
lower_oklch_tensor = torch.stack(
[
lower_oklab_tensor[0, :, :],
torch.sqrt(
torch.add(
torch.pow(lower_oklab_tensor[1, :, :], 2.0), torch.pow(lower_oklab_tensor[2, :, :], 2.0)
)
),
torch.atan2(lower_oklab_tensor[2, :, :], lower_oklab_tensor[1, :, :]),
]
)
upper_oklch_tensor = oklch_from_oklab(upper_oklab_tensor)
lower_oklch_tensor = oklch_from_oklab(lower_oklab_tensor)

return (
upper_rgb_l_tensor,
Expand Down Expand Up @@ -736,7 +705,17 @@ def adaptive_clipped(rgb_tensor: torch.Tensor, clamp: bool = True, replace_with:
"HSL": lambda t: linear_srgb_from_srgb(srgb_from_hsl(t)),
"HSV": lambda t: linear_srgb_from_srgb(
tensor_from_pil_image(
pil_image_from_tensor(t.clamp(0.0, 1.0), mode="HSV").convert("RGB"), normalize=False
pil_image_from_tensor(
torch.stack(
[
torch.remainder(t[0, :, :], 360.0) / 360.0,
t[1, :, :].clamp(0.0, 1.0),
t[2, :, :].clamp(0.0, 1.0),
]
),
mode="HSV",
).convert("RGB"),
normalize=False,
)
),
"Okhsl": lambda t: linear_srgb_from_srgb(
Expand All @@ -745,15 +724,7 @@ def adaptive_clipped(rgb_tensor: torch.Tensor, clamp: bool = True, replace_with:
"Okhsv": lambda t: linear_srgb_from_srgb(
srgb_from_okhsv(t, alpha=self.adaptive_gamut, steps=(3 if self.high_precision else 1))
),
"Oklch": lambda t: linear_srgb_from_oklab(
torch.stack(
[
t[0, :, :],
torch.mul(t[1, :, :], torch.cos(t[2, :, :])),
torch.mul(t[1, :, :], torch.sin(t[2, :, :])),
]
)
),
"Oklch": lambda t: linear_srgb_from_oklab(oklab_from_oklch(t)),
"LCh": lambda t: linear_srgb_from_srgb(
tensor_from_pil_image(
self.image_convert_with_xform(
Expand Down Expand Up @@ -784,9 +755,9 @@ def adaptive_clipped(rgb_tensor: torch.Tensor, clamp: bool = True, replace_with:
alpha_upper_tensor,
alpha_lower_tensor,
mask_tensor,
upper_hsv_tensor, # h_rgb, s_hsv, v_hsv
upper_hsv_tensor, # h_hsv_degrees, s_hsv, v_hsv
lower_hsv_tensor,
upper_hsl_tensor, # , s_hsl, l_hsl
upper_hsl_tensor, # h_hsl_degrees, s_hsl, l_hsl
lower_hsl_tensor,
upper_lab_tensor, # l_lab, a_lab, b_lab
lower_lab_tensor,
Expand All @@ -796,11 +767,11 @@ def adaptive_clipped(rgb_tensor: torch.Tensor, clamp: bool = True, replace_with:
lower_l_eal_tensor,
upper_oklab_tensor, # l_oklab, a_oklab, b_oklab
lower_oklab_tensor,
upper_oklch_tensor, # , c_oklab, h_oklab
upper_oklch_tensor, # l_oklab, c_oklab, h_oklab_degrees
lower_oklch_tensor,
upper_okhsv_tensor, # h_okhsv, s_okhsv, v_okhsv
upper_okhsv_tensor, # h_okhsv_degrees, s_okhsv, v_okhsv
lower_okhsv_tensor,
upper_okhsl_tensor, # h_okhsl, s_okhsl, l_r_oklab
upper_okhsl_tensor, # h_okhsl_degrees, s_okhsl, l_r_oklab
lower_okhsl_tensor,
) = image_tensors

Expand Down Expand Up @@ -850,6 +821,17 @@ def adaptive_clipped(rgb_tensor: torch.Tensor, clamp: bool = True, replace_with:
"LCh": 2,
}[color_space]

hue_period = {
"RGB": None,
"Linear": None,
"HSL": 360.0,
"HSV": 360.0,
"Okhsl": 360.0,
"Okhsv": 360.0,
"Oklch": 360.0,
"LCh": 2.0 * PI,
}[color_space]

if blend_mode == "Normal":
upper_rgb_l_tensor = reassembly_function(upper_space_tensor)

Expand Down Expand Up @@ -982,19 +964,19 @@ def adaptive_clipped(rgb_tensor: torch.Tensor, clamp: bool = True, replace_with:
elif blend_mode == "Linear Dodge (Add)":
lower_space_tensor = torch.add(lower_space_tensor, upper_space_tensor)
if hue_index is not None:
lower_space_tensor[hue_index, :, :] = torch.remainder(lower_space_tensor[hue_index, :, :], 1.0)
lower_space_tensor[hue_index, :, :] = torch.remainder(lower_space_tensor[hue_index, :, :], hue_period)
upper_rgb_l_tensor = adaptive_clipped(reassembly_function(lower_space_tensor))

elif blend_mode == "Color Dodge":
lower_space_tensor = torch.div(lower_space_tensor, torch.add(torch.mul(upper_space_tensor, -1.0), 1.0))
if hue_index is not None:
lower_space_tensor[hue_index, :, :] = torch.remainder(lower_space_tensor[hue_index, :, :], 1.0)
lower_space_tensor[hue_index, :, :] = torch.remainder(lower_space_tensor[hue_index, :, :], hue_period)
upper_rgb_l_tensor = adaptive_clipped(reassembly_function(lower_space_tensor))

elif blend_mode == "Divide":
lower_space_tensor = torch.div(lower_space_tensor, upper_space_tensor)
if hue_index is not None:
lower_space_tensor[hue_index, :, :] = torch.remainder(lower_space_tensor[hue_index, :, :], 1.0)
lower_space_tensor[hue_index, :, :] = torch.remainder(lower_space_tensor[hue_index, :, :], hue_period)
upper_rgb_l_tensor = adaptive_clipped(reassembly_function(lower_space_tensor))

elif blend_mode == "Linear Burn":
Expand Down Expand Up @@ -1088,7 +1070,7 @@ def adaptive_clipped(rgb_tensor: torch.Tensor, clamp: bool = True, replace_with:
elif blend_mode == "Subtract":
lower_space_tensor = torch.sub(lower_space_tensor, upper_space_tensor)
if hue_index is not None:
lower_space_tensor[hue_index, :, :] = torch.remainder(lower_space_tensor[hue_index, :, :], 1.0)
lower_space_tensor[hue_index, :, :] = torch.remainder(lower_space_tensor[hue_index, :, :], hue_period)
upper_rgb_l_tensor = adaptive_clipped(reassembly_function(lower_space_tensor))

elif blend_mode == "Difference":
Expand Down
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