ImageEffectsAdjustment¶
Documentation¶
- Class name:
ImageEffectsAdjustment - Category:
image/effects - Output node:
False
This node applies a series of image adjustments including brightness, contrast, saturation, hue, gamma, and sharpness, along with RGB color scaling, to a batch of images. It allows for fine-tuning of visual aspects of images to achieve desired effects or corrections.
Input types¶
Required¶
images- The batch of images to be adjusted. Each adjustment is applied to all images in the batch, allowing for consistent image processing across multiple inputs.
- Comfy dtype:
IMAGE - Python dtype:
torch.Tensor
brightness- Adjusts the brightness level of the images. A value greater than 1.0 increases brightness, while a value less than 1.0 decreases it.
- Comfy dtype:
FLOAT - Python dtype:
float
contrast- Modifies the contrast of the images. Values greater than 1.0 enhance contrast, whereas values less than 1.0 reduce it.
- Comfy dtype:
FLOAT - Python dtype:
float
saturation- Alters the saturation level of the images, enhancing or diminishing the intensity of colors.
- Comfy dtype:
FLOAT - Python dtype:
float
hue- Changes the hue of the images, allowing for shifts in color spectrum.
- Comfy dtype:
FLOAT - Python dtype:
float
gamma- Applies gamma correction to the images, adjusting the luminance.
- Comfy dtype:
FLOAT - Python dtype:
float
sharpness- Adjusts the sharpness of the images, making them appear clearer or softer.
- Comfy dtype:
FLOAT - Python dtype:
float
red- Scales the red channel of the images, affecting the intensity of red hues.
- Comfy dtype:
FLOAT - Python dtype:
float
green- Scales the green channel of the images, affecting the intensity of green hues.
- Comfy dtype:
FLOAT - Python dtype:
float
blue- Scales the blue channel of the images, affecting the intensity of blue hues.
- Comfy dtype:
FLOAT - Python dtype:
float
Output types¶
image- Comfy dtype:
IMAGE - The batch of images after applying the specified adjustments, potentially including changes in brightness, contrast, saturation, hue, gamma, sharpness, and RGB color scaling.
- Python dtype:
torch.Tensor
- Comfy dtype:
Usage tips¶
- Infra type:
GPU - Common nodes: unknown
Source code¶
class ImageEffectsAdjustment:
def __init__(self):
pass
@classmethod
def INPUT_TYPES(cls):
return {
"required": {
"images": ("IMAGE",),
"brightness": ("FLOAT", {
"default": 1.0,
"step": 0.01
}),
"contrast": ("FLOAT", {
"default": 1.0,
"step": 0.01
}),
"saturation": ("FLOAT", {
"default": 1.0,
"step": 0.01
}),
"hue": ("FLOAT", {
"default": 0.5,
"max": 1.0,
"step": 0.01
}),
"gamma": ("FLOAT", {
"default": 1.0,
"step": 0.01
}),
"sharpness": ("FLOAT", {
"default": 1.0,
"step": 0.01
}),
"red": ("FLOAT", {
"default": 1.0,
"step": 0.01
}),
"green": ("FLOAT", {
"default": 1.0,
"step": 0.01
}),
"blue": ("FLOAT", {
"default": 1.0,
"step": 0.01
}),
},
}
RETURN_TYPES = ("IMAGE",)
FUNCTION = "node"
CATEGORY = "image/effects"
def node(self, images, brightness, contrast, saturation, hue, gamma, sharpness, red, green, blue):
# noinspection PyUnboundLocalVariable
def apply(img):
rgba = False
if len(img[0, 0, :]) == 4:
a = img[:, :, 3].unsqueeze(2)
img = img[:, :, 0:3]
rgba = True
img = img.permute(2, 0, 1)
if brightness != 1.0:
img = F.adjust_brightness(img, brightness)
if contrast != 1.0:
img = F.adjust_contrast(img, contrast)
if saturation != 1.0:
img = F.adjust_saturation(img, saturation)
if hue != 0.5:
img = F.adjust_hue(img, hue - 0.5)
if gamma != 1.0:
img = F.adjust_gamma(img, gamma)
if sharpness != 1.0:
img = F.adjust_sharpness(img, sharpness)
img = img.permute(1, 2, 0)
r, g, b = torch.chunk(img, 3, dim=2)
r = torch.clamp(r * red, 0, 1)
g = torch.clamp(g * green, 0, 1)
b = torch.clamp(b * blue, 0, 1)
if rgba:
return torch.cat([r, g, b, a], dim=2)
else:
return torch.cat([r, g, b], dim=2)
return (torch.stack([
apply(images[i]) for i in range(len(images))
]),)