47 lines
1.3 KiB
Python
47 lines
1.3 KiB
Python
from .imagefunc import *
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NODE_NAME = 'AddGrain'
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class AddGrain:
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def __init__(self):
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pass
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@classmethod
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def INPUT_TYPES(self):
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return {
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"required": {
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"image": ("IMAGE", ), #
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"grain_power": ("FLOAT", {"default": 0.5, "min": 0, "max": 1, "step": 0.01}),
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"grain_scale": ("FLOAT", {"default": 1, "min": 0.1, "max": 10, "step": 0.1}),
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"grain_sat": ("FLOAT", {"default": 1, "min": 0, "max": 1, "step": 0.01}),
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},
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"optional": {
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}
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}
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RETURN_TYPES = ("IMAGE",)
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RETURN_NAMES = ("image",)
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FUNCTION = 'add_grain'
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CATEGORY = '😺dzNodes/LayerFilter'
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def add_grain(self, image, grain_power, grain_scale, grain_sat):
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ret_images = []
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for i in image:
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_canvas = tensor2pil(torch.unsqueeze(i, 0)).convert('RGB')
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_canvas = image_add_grain(_canvas, grain_scale, grain_power, grain_sat, toe=0, seed=int(time.time()))
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ret_images.append(pil2tensor(_canvas))
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log(f"{NODE_NAME} Processed {len(ret_images)} image(s).", message_type='finish')
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return (torch.cat(ret_images, dim=0),)
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NODE_CLASS_MAPPINGS = {
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"LayerFilter: AddGrain": AddGrain
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}
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NODE_DISPLAY_NAME_MAPPINGS = {
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"LayerFilter: AddGrain": "LayerFilter: Add Grain"
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} |