50 lines
2.1 KiB
Markdown
50 lines
2.1 KiB
Markdown
# Documentation
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- Class name: LoadInpaintModel
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- Category: inpaint
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- Output node: False
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- Repo Ref: https://github.com/Acly/comfyui-inpaint-nodes
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LoadInpaintModel 类旨在方便加载修复模型，这些是专门用于填充图像中缺失或损坏部分的神经网络架构。它抽象了模型加载的复杂性，确保加载过程是流畅和可靠的。该节点的功能对于初始化修复过程至关重要，为进一步的图像操作提供了基础。
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# Input types
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## Required
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- model_name
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- 参数 'model_name' 非常重要，因为它标识了要加载的特定修复模型。它通过确定将用于修复任务的神经网络架构，影响节点的执行。正确的模型名称对于实现所需的图像恢复结果至关重要。
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- Comfy dtype: str
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- Python dtype: str
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# Output types
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- INPAINT_MODEL
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- 输出 'INPAINT_MODEL' 代表已加载的修复模型，可供后续图像处理任务使用。它封装了模型的已训练权重和架构，标志着加载过程的完成，并使模型能够执行其指定功能。
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- Comfy dtype: torch.nn.Module
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- Python dtype: torch.nn.Module
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# Usage tips
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- Infra type: CPU
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# Source code
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```
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class LoadInpaintModel:
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@classmethod
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def INPUT_TYPES(s):
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return {'required': {'model_name': (folder_paths.get_filename_list('inpaint'),)}}
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RETURN_TYPES = ('INPAINT_MODEL',)
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CATEGORY = 'inpaint'
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FUNCTION = 'load'
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def load(self, model_name: str):
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model_file = folder_paths.get_full_path('inpaint', model_name)
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if model_file is None:
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raise RuntimeError(f'Model file not found: {model_name}')
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if model_file.endswith('.pt'):
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sd = torch.jit.load(model_file, map_location='cpu').state_dict()
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else:
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sd = comfy.utils.load_torch_file(model_file, safe_load=True)
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if 'synthesis.first_stage.conv_first.conv.resample_filter' in sd:
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model = mat.load(sd)
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else:
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model = comfy_extras.chainner_models.model_loading.load_state_dict(sd)
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model = model.eval()
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return (model,)
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``` |