95 lines
2.9 KiB
Markdown
95 lines
2.9 KiB
Markdown
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# Documentation
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- Class name: ImageListLoader
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- Category: List Stuff
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- Output node: False
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ImageListLoader节点旨在从指定源加载图像列表，便于在批处理或图像分析工作流程中处理和操作多个图像。
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# Input types
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## Required
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- folder_path
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- 指定要从中加载图像的目录路径。这个输入对于定位节点将处理的图像源至关重要。
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- Comfy dtype: STRING
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- Python dtype: str
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- file_filter
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- 定义用于过滤要加载的图像的文件模式，如'*.png'。这允许根据文件类型或命名约定选择性地加载图像。
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- Comfy dtype: STRING
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- Python dtype: str
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- sort_method
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- 确定加载图像的排序方法，可以是'numerical'（数字）或'alphabetical'（字母）。这会影响图像的处理顺序，对于需要特定顺序的工作流程至关重要。
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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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- Images
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- 将加载的图像作为列表输出，使它们可用于进一步处理或分析。这对于需要同时操作多个图像的工作流程至关重要。
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- Comfy dtype: IMAGE
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- Python dtype: List[torch.Tensor]
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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 ImageListLoader:
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def __init__(self) -> None:
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pass
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@classmethod
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def INPUT_TYPES(s) -> Dict[str, Dict[str, Any]]:
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return {
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"required": {
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"folder_path": ("STRING", {}),
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"file_filter": ("STRING", {"default": "*.png"}),
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"sort_method": (["numerical", "alphabetical"], {"default": "numerical"}),
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},
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}
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RELOAD_INST = True
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RETURN_TYPES = ("IMAGE",)
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RETURN_NAMES = ("Images",)
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INPUT_IS_LIST = False
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OUTPUT_IS_LIST = (True,)
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FUNCTION = "load_images"
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CATEGORY = "List Stuff"
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@staticmethod
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def numerical_sort(file_name: Path) -> int:
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subbed = re.sub("\D", "", str(file_name))
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if subbed == "":
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return 0
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return int(subbed)
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@staticmethod
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def alphabetical_sort(file_name: Path) -> str:
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return str(file_name)
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def load_images(
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self, folder_path: str, file_filter: str, sort_method: str
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) -> Tuple[List[Tensor]]:
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folder = Path(folder_path)
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if not folder.is_dir():
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raise Exception(f"Folder path {folder_path} does not exist.")
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sort_method_impl: Callable[[str], Union[SupportsDunderGT, SupportsDunderLT]]
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if sort_method == "numerical":
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sort_method_impl = self.numerical_sort
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elif sort_method == "alphabetical":
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sort_method_impl = self.alphabetical_sort
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else:
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raise ValueError(f"Unknown sort method {sort_method}")
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files = sorted(folder.glob(file_filter), key=sort_method_impl)
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images = [pil2tensor(Image.open(file)) for file in files]
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return (images,)
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```
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