37 lines
1.1 KiB
Python
37 lines
1.1 KiB
Python
import os.path
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import uuid
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import torch
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import torchvision
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class SaveImagePath:
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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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"image_path":("IMAGE", {"forceInput": True}),
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}
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}
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RETURN_TYPES = ("STRING",)
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FUNCTION = "load"
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CATEGORY = "不忘科技-自定义节点🚩"
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def load(self, image_path:torch.Tensor):
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image_path = image_path.float()
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# 假设数据范围在 [0, 255]，进行归一化
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image_path = image_path / 255.0
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# 检查并调整形状（这里只是示例，具体调整需根据实际情况）
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if len(image_path.shape) == 3:
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image_path = image_path.unsqueeze(0) # 添加批次维度
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u = uuid.uuid4()
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p = os.path.join(os.path.dirname(os.path.abspath(__file__)), "output", "%s.jpg" % str(u))
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torchvision.utils.save_image(image_path, p)
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# u = uuid.uuid4()
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# p = os.path.join(os.path.dirname(os.path.abspath(__file__)),"output","%s.jpg" % str(u))
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# torchvision.utils.save_image(image_path, p)
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return (p,)
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