41 lines
1.2 KiB
Python
41 lines
1.2 KiB
Python
from PIL import Image
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import numpy as np
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import torch
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import folder_paths
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import os
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class AutioPath:
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def __init__(self):
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self.input_autio_dir = os.path.join(folder_paths.get_input_directory(), 'autio')
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if not os.path.exists(self.input_autio_dir):
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os .makedirs(self.input_autio_dir)
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@classmethod
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def INPUT_TYPES(cls):
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input_autio_dir = os.path.join(folder_paths.get_input_directory(), 'autio')
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if not os.path.exists(input_autio_dir):
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os .makedirs(input_autio_dir)
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autiofiles = [f for f in os.listdir(input_autio_dir) if os.path.isfile(os.path.join(input_autio_dir, f))]
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return {
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"required": {
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"autio": (sorted(autiofiles), ),
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}
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}
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RETURN_TYPES = ("STRING",)
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RETURN_NAMES = ("音频地址",)
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FUNCTION = "get_autio_path"
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CATEGORY = "lam"
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def get_autio_path(self,autio):
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autio_path = folder_paths.get_annotated_filepath(autio,self.input_autio_dir)
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return (autio_path, )
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NODE_CLASS_MAPPINGS = {
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"AutioPath": AutioPath
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}
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# A dictionary that contains the friendly/humanly readable titles for the nodes
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NODE_DISPLAY_NAME_MAPPINGS = {
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"AutioPath": "获取音频地址"
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}
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