70 lines
2.3 KiB
Python
70 lines
2.3 KiB
Python
# SPDX-License-Identifier: Apache-2.0
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# Copyright 2025-2026 Raykosan (RaykoStudio)
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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import torch
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from comfy.model_patcher import ModelPatcher
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class RS_SaturationSwitch:
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@classmethod
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def INPUT_TYPES(cls):
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return {
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"required": {
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"image": ("IMAGE",),
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"intensity": ("FLOAT", {
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"default": 1.0,
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"min": 0.0,
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"max": 3.0,
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"step": 0.05,
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"display_name": "Intensity",
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"description": "0.0=Grayscale, 1.0=Original, 1.5=Subtle Boost"
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}),
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},
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}
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RETURN_TYPES = ("IMAGE",)
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FUNCTION = "apply_saturation"
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CATEGORY = "🦊 RaykoStudio"
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DESCRIPTION = "Artifact-free saturation control with proper tensor handling"
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def apply_saturation(self, image, intensity):
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if intensity == 1.0:
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return (image,)
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img = image.clone().float()
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r, g, b = img[..., 0], img[..., 1], img[..., 2]
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l = 0.299 * r + 0.587 * g + 0.114 * b
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l = l.unsqueeze(-1)
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if intensity < 1.0:
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result = l + intensity * (img - l)
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else:
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boost = 1.0 + (intensity - 1.0) * 0.7
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delta = img - l
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result = l + boost * delta
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result = torch.where(
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(result < 0) | (result > 1),
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l + 0.9 * delta,
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result
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)
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if result.dim() == 3:
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result = result.unsqueeze(0)
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return (result.clamp(0, 1).to(image.dtype),)
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NODE_CLASS_MAPPINGS = {"RS_Saturation": RS_SaturationSwitch}
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NODE_DISPLAY_NAME_MAPPINGS = {"RS_Saturation": "🦊 RS Saturation"} |