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Optimize Hue & Saturation node #2774

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merged 2 commits into from
Apr 9, 2024
Merged

Optimize Hue & Saturation node #2774

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c888b4a
Optimize Hue & Saturation node
RunDevelopment Apr 9, 2024
a59dae5
# type: ignore
RunDevelopment Apr 9, 2024
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42 changes: 28 additions & 14 deletions backend/src/packages/chaiNNer_standard/image_adjustment/adjustments/hue_and_saturation.py
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Original file line number Diff line number Diff line change
Expand Up @@ -12,8 +12,12 @@

def with_lightness(img: np.ndarray, lightness: float) -> np.ndarray:
if lightness > 0:
return img + (1 - img) * lightness
assert lightness <= 1
res = img * (1 - lightness)
res += lightness
return res
elif lightness < 0:
assert lightness >= -1
return img * (1 + lightness)
else:
return img
Expand Down Expand Up @@ -63,7 +67,9 @@ def with_lightness(img: np.ndarray, lightness: float) -> np.ndarray:
gradient=["#000000", "#ffffff"],
),
],
outputs=[ImageOutput(image_type="Input0")],
outputs=[
ImageOutput(image_type="Input0", assume_normalized=True),
],
)
def hue_and_saturation_node(
img: np.ndarray,
Expand All @@ -88,24 +94,32 @@ def hue_and_saturation_node(
alpha = None
if c > 3:
alpha = img[:, :, 3]
img = img[:, :, :3]

h, l, s = cv2.split(cv2.cvtColor(img[:, :, :3], cv2.COLOR_BGR2HLS))
if hue != 0 or saturation != 0:
# Convert to HLS color space
h, l, s = cv2.split(cv2.cvtColor(img, cv2.COLOR_BGR2HLS))

# Adjust hue
if hue != 0:
h += hue # type: ignore
h[h >= 360] -= 360 # Wrap positive overflow
h[h < 0] += 360 # Wrap negative overflow
# Adjust hue
if hue != 0:
h += hue # type: ignore
h[h >= 360] -= 360 # Wrap positive overflow
h[h < 0] += 360 # Wrap negative overflow

# Adjust saturation
if saturation != 0:
saturation = 1 + saturation
s = np.clip(s * saturation, 0, 1) # type: ignore
# Adjust saturation
if saturation != 0:
factor = 1 + saturation
s *= factor # type: ignore
if factor > 1:
s = np.clip(s, 0, 1, out=s)

img = cv2.cvtColor(cv2.merge([h, l, s]), cv2.COLOR_HLS2BGR)
# we assume that this returns normalized values in Change Color Model,
# so it should be fine here as well
img = cv2.cvtColor(cv2.merge([h, l, s]), cv2.COLOR_HLS2BGR)

# Adjust lightness
img = with_lightness(img, lightness)
if lightness != 0:
img = with_lightness(img, lightness)

# Re-add alpha, if it exists
if alpha is not None:
Expand Down
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