RiceRound
e614d4e974
Added environment-based configuration to streamline deployments Improved data validation logic for more robust CRUD operations Refined folder structure to optimize code organization
72 lines
2.1 KiB
Python
72 lines
2.1 KiB
Python
import torch
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from nodes import SaveImage
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import folder_paths
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class ExcuteCryptoNode:
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def __init__(self):
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pass
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@classmethod
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def INPUT_TYPES(s):
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return {
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"required": {
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"crypto_file_path": (
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"STRING",
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{"default": folder_paths.output_directory},
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)
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},
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"optional": {"input_anything": ("*",)},
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"hidden": {
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"unique_id": "UNIQUE_ID",
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"prompt": "PROMPT",
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"extra_pnginfo": "EXTRA_PNGINFO",
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},
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}
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RETURN_TYPES = ("IMAGE",)
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FUNCTION = "excute"
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CATEGORY = "__hidden__"
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def excute(self, **kwargs):
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batch_size = 1
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height = 1024
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width = 1024
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color = 16711680
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r = torch.full([batch_size, height, width, 1], (color >> 16 & 255) / 255)
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g = torch.full([batch_size, height, width, 1], (color >> 8 & 255) / 255)
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b = torch.full([batch_size, height, width, 1], (color & 255) / 255)
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return (torch.cat((r, g, b), dim=-1),)
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class CryptoCatImage(SaveImage):
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def __init__(self):
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super().__init__()
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@classmethod
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def INPUT_TYPES(s):
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return {
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"required": {
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"images": ("IMAGE", {"tooltip": "The images to save."}),
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"filename_prefix": (
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"STRING",
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{
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"default": "ComfyUI",
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"tooltip": "The prefix for the file to save. This may include formatting information such as %date:yyyy-MM-dd% or %Empty Latent Image.width% to include values from nodes.",
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},
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),
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},
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"hidden": {"prompt": "PROMPT", "extra_pnginfo": "EXTRA_PNGINFO"},
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}
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RETURN_TYPES = ()
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FUNCTION = "save_images"
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OUTPUT_NODE = True
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CATEGORY = "__hidden__"
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DESCRIPTION = "Saves the input images to your ComfyUI output directory."
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def save_images(
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self, images, filename_prefix="ComfyUI", prompt=None, extra_pnginfo=None
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):
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return super().save_images(images, filename_prefix, None, None)
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