LayerMask: CreateGradientMask¶
Documentation¶
- Class name:
LayerMask: CreateGradientMask - Category:
😺dzNodes/LayerMask - Output node:
False
This node is designed to create gradient masks with customizable dimensions, gradient direction, scale, offset, and opacity. It allows for the creation of nuanced layer masks that can be applied to images for various effects, such as fading or blending.
Input types¶
Required¶
width- Specifies the width of the gradient mask to be created. It determines the horizontal dimension of the resulting mask.
- Comfy dtype:
INT - Python dtype:
int
height- Specifies the height of the gradient mask to be created. It determines the vertical dimension of the resulting mask.
- Comfy dtype:
INT - Python dtype:
int
gradient_side- Determines the side from which the gradient starts. This affects the direction of the gradient applied to the mask.
- Comfy dtype:
COMBO[STRING] - Python dtype:
str
gradient_scale- Controls the scale of the gradient effect within the mask, affecting how gradual or steep the gradient appears.
- Comfy dtype:
INT - Python dtype:
int
gradient_offset- Adjusts the starting point of the gradient within the mask, allowing for shifted gradient effects.
- Comfy dtype:
INT - Python dtype:
int
opacity- Sets the opacity level of the gradient mask, enabling transparency effects.
- Comfy dtype:
INT - Python dtype:
int
Optional¶
size_as- Optionally specifies another object's size to match for the gradient mask, providing flexibility in mask dimensions.
- Comfy dtype:
* - Python dtype:
object
Output types¶
mask- Comfy dtype:
MASK - The resulting gradient mask, ready for application to images or layers for various visual effects.
- Python dtype:
object
- Comfy dtype:
Usage tips¶
- Infra type:
CPU - Common nodes: unknown
Source code¶
class CreateGradientMask:
def __init__(self):
pass
@classmethod
def INPUT_TYPES(self):
side = ['bottom', 'top', 'left', 'right', 'center']
return {
"required": {
"width": ("INT", {"default": 512, "min": 4, "max": 99999, "step": 1}),
"height": ("INT", {"default": 512, "min": 4, "max": 99999, "step": 1}),
"gradient_side": (side,),
"gradient_scale": ("INT", {"default": 100, "min": 1, "max": 9999, "step": 1}),
"gradient_offset": ("INT", {"default": 0, "min": -9999, "max": 9999, "step": 1}),
"opacity": ("INT", {"default": 100, "min": 0, "max": 100, "step": 1}),
},
"optional": {
"size_as": (any, {}),
}
}
RETURN_TYPES = ("MASK",)
RETURN_NAMES = ("mask",)
FUNCTION = 'create_gradient_mask'
CATEGORY = '😺dzNodes/LayerMask'
def create_gradient_mask(self, width, height, gradient_side, gradient_scale, gradient_offset, opacity, size_as=None):
if size_as is not None:
if size_as.shape[0] > 0:
_asimage = tensor2pil(size_as[0])
else:
_asimage = tensor2pil(size_as)
width, height = _asimage.size
_black = Image.new('L', size=(width, height), color='black')
_white = Image.new('L', size=(width, height), color='white')
_canvas = copy.deepcopy(_black)
debug_image1 = copy.deepcopy(_black).convert('RGB')
debug_image2 = copy.deepcopy(_black).convert('RGB')
start_color = '#FFFFFF'
end_color = '#000000'
if gradient_side == 'bottom':
_gradient = create_gradient(start_color, end_color, width, height, direction='bottom')
if gradient_scale != 100:
_gradient = _gradient.resize((width, int(height * gradient_scale / 100)))
_canvas.paste(_gradient.convert('L'), box=(0, gradient_offset))
if gradient_offset > height:
_canvas = _white
elif gradient_offset > 0:
_canvas.paste(_white, box=(0, gradient_offset - height))
elif gradient_side == 'top':
_gradient = create_gradient(start_color, end_color, width, height, direction='top')
if gradient_scale != 100:
_gradient = _gradient.resize((width, int(height * gradient_scale / 100)))
_canvas.paste(_gradient.convert('L'), box=(0, height - int(height * gradient_scale / 100) + gradient_offset))
if gradient_offset < -height:
_canvas = _white
elif gradient_offset < 0:
_canvas.paste(_white, box=(0, height + gradient_offset))
elif gradient_side == 'left':
_gradient = create_gradient(start_color, end_color, width, height, direction='left')
if gradient_scale != 100:
_gradient = _gradient.resize((int(width * gradient_scale / 100), height))
_canvas.paste(_gradient.convert('L'), box=(width - int(width * gradient_scale / 100) + gradient_offset, 0))
if gradient_offset < -width:
_canvas = _white
elif gradient_offset < 0:
_canvas.paste(_white, box=(width + gradient_offset, 0))
elif gradient_side == 'right':
_gradient = create_gradient(start_color, end_color, width, height, direction='right')
if gradient_scale != 100:
_gradient = _gradient.resize((int(width * gradient_scale / 100), height))
_canvas.paste(_gradient.convert('L'), box=(gradient_offset, 0))
if gradient_offset > width:
_canvas = _white
elif gradient_offset > 0:
_canvas.paste(_white, box=(gradient_offset - width, 0))
else:
_gradient = create_box_gradient(start_color_inhex='#000000', end_color_inhex='#FFFFFF',
width=width, height=height, scale=int(gradient_scale))
_gradient = _gradient.convert('L')
debug_image1 = _gradient
_blur_mask = Image.new('L', size=(width*2, height*2), color='black')
_blur_mask.paste(_gradient, box=(int(width/2), int(height/2)))
_blur_mask = gaussian_blur(_blur_mask, int((width + height) * gradient_scale / 100 / 16))
_gamma_mask = gamma_trans(_blur_mask, 0.15)
(crop_x, crop_y, crop_width, crop_height) = mask_area(_gamma_mask)
crop_box = (crop_x, crop_y, crop_x + crop_width, crop_y + crop_height)
_blur_mask = _blur_mask.crop(crop_box)
_blur_mask = _blur_mask.resize((width, height), Image.BILINEAR)
if gradient_offset != 0:
resize_width = int(width - gradient_offset)
resize_height = int(height - gradient_offset)
if resize_width < 1:
resize_width = 1
if resize_height < 1:
resize_height = 1
_blur_mask = _blur_mask.resize((resize_width, resize_height), Image.BILINEAR)
paste_box = (int((width - resize_width) / 2), int((height - resize_height) / 2))
else:
paste_box = (0,0)
_canvas.paste(_blur_mask, box=paste_box)
# opacity
if opacity < 100:
_canvas = chop_image(_black, _canvas, 'normal', opacity)
log(f"{NODE_NAME} Processed.", message_type='finish')
return (image2mask(_canvas),)