59 lines
1.9 KiB
Markdown
59 lines
1.9 KiB
Markdown
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# Documentation
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- Class name: AV_IPAdapterPipeline
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- Category: Art Venture/IP Adapter
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- Output node: False
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AV_IPAdapterPipeline节点旨在加载和配置IP适配器和剪辑视觉模型，以便在艺术生成管道中使用。它促进了这些模型在统一管道中的集成，从而实现增强的图像处理和操作能力。
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# Input types
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## Required
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- ip_adapter_name
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- 指定要加载的IP适配器模型的名称。这对于识别和加载正确的IP适配器模型至关重要。
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- Comfy dtype: COMBO[STRING]
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- Python dtype: str
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- clip_name
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- 确定要加载的剪辑视觉模型的名称。这对于获取和整合适当的剪辑视觉模型到管道中至关重要。
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- Comfy dtype: COMBO[STRING]
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- Python dtype: str
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# Output types
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- p
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- 输出的p参数代表经过配置的IP适配器和剪辑视觉模型的集成管道。它封装了可用于后续艺术生成任务的处理能力。
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- Comfy dtype: IPADAPTER
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- Python dtype: unknown
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## Usage tips
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- Infra type: `CPU`
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- Common nodes: unknown
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## Source code
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```python
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class AV_IPAdapterPipeline:
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@classmethod
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def INPUT_TYPES(cls):
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return {
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"required": {
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"ip_adapter_name": (folder_paths.get_filename_list("ipadapter"),),
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"clip_name": (folder_paths.get_filename_list("clip_vision"),),
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}
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}
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RETURN_TYPES = ("IPADAPTER",)
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RETURN_NAMES = "pipeline"
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CATEGORY = "Art Venture/IP Adapter"
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FUNCTION = "load_ip_adapter"
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def load_ip_adapter(ip_adapter_name, clip_name):
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ip_adapter = loader.load_ipadapter_model(ip_adapter_name)[0]
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clip_path = folder_paths.get_full_path("clip_vision", clip_name)
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clip_vision = comfy.clip_vision.load(clip_path)
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pipeline = {"ipadapter": {"model": ip_adapter}, "clipvision": {"model": clip_vision}}
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return pipeline
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```
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