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custom_nodes
f2dbf59
from .imagefunc import *
NODE_NAME = 'ChannelShake'
class ChannelShake:
def __init__(self):
pass
@classmethod
def INPUT_TYPES(self):
channel_mode = ['RGB', 'RBG', 'BGR', 'BRG', 'GBR', 'GRB']
return {
"required": {
"image": ("IMAGE", ), #
"distance": ("INT", {"default": 20, "min": 1, "max": 999, "step": 1}), # 距离
"angle": ("FLOAT", {"default": 40, "min": -360, "max": 360, "step": 0.1}), # 角度
"mode": (channel_mode,), # 模式
},
"optional": {
}
}
RETURN_TYPES = ("IMAGE",)
RETURN_NAMES = ("image",)
FUNCTION = 'channel_shake'
CATEGORY = '😺dzNodes/LayerFilter'
def channel_shake(self, image, distance, angle, mode, ):
ret_images = []
for i in image:
i = torch.unsqueeze(i, 0)
_canvas = tensor2pil(i).convert('RGB')
R, G, B = _canvas.split()
x = int(math.cos(angle) * distance)
y = int(math.sin(angle) * distance)
if mode.startswith('R'):
R = shift_image(R.convert('RGB'), -x, -y).convert('L')
if mode.startswith('G'):
G = shift_image(G.convert('RGB'), -x, -y).convert('L')
if mode.startswith('B'):
B = shift_image(B.convert('RGB'), -x, -y).convert('L')
if mode.endswith('R'):
R = shift_image(R.convert('RGB'), x, y).convert('L')
if mode.endswith('G'):
G = shift_image(G.convert('RGB'), x, y).convert('L')
if mode.endswith('B'):
B = shift_image(B.convert('RGB'), x, y).convert('L')
ret_image = Image.merge('RGB', [R, G, B])
ret_images.append(pil2tensor(ret_image))
log(f"{NODE_NAME} Processed {len(ret_images)} image(s).", message_type='finish')
return (torch.cat(ret_images, dim=0),)
NODE_CLASS_MAPPINGS = {
"LayerFilter: ChannelShake": ChannelShake
}
NODE_DISPLAY_NAME_MAPPINGS = {
"LayerFilter: ChannelShake": "LayerFilter: ChannelShake"
}