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import cv2

import torch

import numpy as np

class CV2Tonemap:

def __init__(self):

pass

@classmethod

def INPUT_TYPES(s):

return {

"required": {

"image": ("IMAGE",),

"gamma": ("FLOAT", {"default": 1.0, "min": 0.00, "max": 8.0, "step": 0.01}),

"mult": ("FLOAT", {"default": 1.0, "min": 0.00, "max": 8.0, "step": 0.01}),

}

}

RETURN_TYPES = ("IMAGE",)

FUNCTION = "apply_tonemap"

CATEGORY = "ColorMod/tonemap"

TITLE = "Tonemap (simple)"

tonemap_op = getattr(cv2, "createTonemap", None)

def tonemap(self, raw, mult, **kwargs):

img = self.tonemap_op(**kwargs).process(raw)

return np.clip(img * mult, 0.0, 1.0)

def apply_tonemap(self, image, **kwargs):

out = []

for raw in image:

raw = raw.cpu().numpy()[:, :, ::-1]

img = self.tonemap(raw, **kwargs)

out.append(

torch.from_numpy(img[:, :, ::-1].copy())

)

out = torch.stack(out, dim=0)

return (out,)

class CV2TonemapDrago(CV2Tonemap):

def __init__(self):

super().__init__()

@classmethod

def INPUT_TYPES(s):

return {

"required": {

"image": ("IMAGE",),

"gamma": ("FLOAT", {"default": 1.0, "min": 0.0, "max": 8.0, "step": 0.01}),

"saturation": ("FLOAT", {"default": 1.0, "min": 0.0, "max": 8.0, "step": 0.01}),

"bias": ("FLOAT", {"default": 1.0, "min": 0.0, "max": 1.0, "step": 0.01}),

"mult": ("FLOAT", {"default": 1.0, "min": 0.0, "max": 8.0, "step": 0.01}),

}

}

TITLE = "Tonemap (Drago)"

tonemap_op = getattr(cv2, "createTonemapDrago", None)

class CV2TonemapDurand(CV2Tonemap):

def __init__(self):

super().__init__()

@classmethod

def INPUT_TYPES(s):

return {

"required": {

"image": ("IMAGE",),

"gamma": ("FLOAT", {"default": 1.0, "min": 0.0, "max": 8.0, "step": 0.01}),

"contrast": ("FLOAT", {"default": 1.0, "min": 0.0, "max": 8.0, "step": 0.01}),

"saturation": ("FLOAT", {"default": 1.0, "min": 0.0, "max": 8.0, "step": 0.01}),

"sigma_space": ("FLOAT", {"default": 1.0, "min": 0.0, "max": 8.0, "step": 0.01}),

"sigma_color": ("FLOAT", {"default": 1.0, "min": 0.0, "max": 8.0, "step": 0.01}),

"mult": ("FLOAT", {"default": 1.0, "min": 0.0, "max": 8.0, "step": 0.01}),

}

}

TITLE = "Tonemap (Durand)"

tonemap_op = getattr(cv2, "createTonemapDurand", None)

class CV2TonemapMantiuk(CV2Tonemap):

def __init__(self):

super().__init__()

@classmethod

def INPUT_TYPES(s):

return {

"required": {

"image": ("IMAGE",),

"gamma": ("FLOAT", {"default": 1.0, "min": 0.0, "max": 8.0, "step": 0.01}),

"scale": ("FLOAT", {"default": 1.0, "min": 0.0, "max": 8.0, "step": 0.01}),

"saturation": ("FLOAT", {"default": 1.0, "min": 0.0, "max": 8.0, "step": 0.01}),

"mult": ("FLOAT", {"default": 1.0, "min": 0.0, "max": 8.0, "step": 0.01}),

}

}

TITLE = "Tonemap (Mantiuk)"

tonemap_op = getattr(cv2, "createTonemapMantiuk", None)

class CV2TonemapReinhard(CV2Tonemap):

def __init__(self):

super().__init__()

@classmethod

def INPUT_TYPES(s):

return {

"required": {

"image": ("IMAGE",),

"gamma": ("FLOAT", {"default": 1.0, "min": 0.0, "max": 8.0, "step": 0.01}),

"intensity": ("FLOAT", {"default": 0.0, "min":-8.0, "max": 8.0, "step": 0.01}),

"light_adapt": ("FLOAT", {"default": 1.0, "min": 0.0, "max": 1.6, "step": 0.01}),

"color_adapt": ("FLOAT", {"default": 1.0, "min": 0.0, "max": 1.6, "step": 0.01}),

"mult": ("FLOAT", {"default": 1.0, "min": 0.0, "max": 8.0, "step": 0.01}),

}

}

TITLE = "Tonemap (Reinhard)"

tonemap_op = getattr(cv2, "createTonemapReinhard", None)

NODE_CLASS_MAPPINGS = {

"CV2Tonemap": CV2Tonemap,

"CV2TonemapDrago": CV2TonemapDrago,

"CV2TonemapDurand": CV2TonemapDurand,

"CV2TonemapMantiuk": CV2TonemapMantiuk,

"CV2TonemapReinhard": CV2TonemapReinhard,

}

# not all cv2 versions support all tonemap nodes (e.g Durand require nonfree)

for name in list(NODE_CLASS_MAPPINGS.keys()):

if NODE_CLASS_MAPPINGS[name].tonemap_op is None:

print(f"ColorMod: Ignoring node '{name}' due to cv2 edition/version")

del NODE_CLASS_MAPPINGS[name]