nodes/chflame163-ComfyUI_LayerStyle
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Update drop shadow node to make background image optional and output transparent image

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This commit is contained in:
Alexis Rolland
2024-11-21 20:48:26 +08:00
parent 692c26dbee
commit 1ad5192341
1 changed files with 16 additions and 8 deletions
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py/drop_shadow_v2.py
+16 -8
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@@ -1,3 +1,4 @@
from PIL import Image
from .imagefunc import *
NODE_NAME = 'DropShadowV2'
@@ -12,7 +13,6 @@ class DropShadowV2:
return {
"required": {
"background_image": ("IMAGE", ), #
"layer_image": ("IMAGE",), #
"invert_mask": ("BOOLEAN", {"default": True}), # 反转mask
"blend_mode": (chop_mode_v2,), # 混合模式
@@ -24,6 +24,7 @@ class DropShadowV2:
"shadow_color": ("STRING", {"default": "#000000"}), # 背景颜色
},
"optional": {
"background_image": ("IMAGE", ), #
"layer_mask": ("MASK",), #
}
}
@@ -33,11 +34,18 @@ class DropShadowV2:
FUNCTION = 'drop_shadow_v2'
CATEGORY = '😺dzNodes/LayerStyle'
def drop_shadow_v2(self, background_image, layer_image,
invert_mask, blend_mode, opacity, distance_x, distance_y,
grow, blur, shadow_color,
layer_mask=None
):
def drop_shadow_v2(self, layer_image, invert_mask, blend_mode, opacity,
distance_x, distance_y, grow, blur, shadow_color,
background_image=None, layer_mask=None
):
# If background image is empty, create transparent background
# image for each layer image
if background_image == None:
background_image = []
for l in layer_image:
m = tensor2pil(l)
background_image.append(pil2tensor(Image.new('RGBA', (m.width, m.height), (0, 0, 0, 0))))
b_images = []
l_images = []
@@ -65,7 +73,7 @@ class DropShadowV2:
max_batch = max(len(b_images), len(l_images), len(l_masks))
distance_x = -distance_x
distance_y = -distance_y
shadow_color = Image.new("RGB", tensor2pil(l_images[0]).size, color=shadow_color)
shadow_color = Image.new("RGBA", tensor2pil(l_images[0]).size, color=shadow_color)
for i in range(max_batch):
background_image = b_images[i] if i < len(b_images) else b_images[-1]
@@ -73,7 +81,7 @@ class DropShadowV2:
_mask = l_masks[i] if i < len(l_masks) else l_masks[-1]
# preprocess
_canvas = tensor2pil(background_image).convert('RGB')
_canvas = tensor2pil(background_image).convert('RGBA')
_layer = tensor2pil(layer_image)
if _mask.size != _layer.size: