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FromDetailerPipe

Documentation

  • Class name: FromDetailerPipe
  • Category: ImpactPack/Pipe
  • Output node: False

The FromDetailerPipe node is designed to extract and return various components from a given detailer pipe, including models, clips, VAEs, conditioning information, bounding box detectors, SAM models, segmentation detectors, and detailer hooks. This node facilitates the decomposition of a complex detailer pipe into its constituent elements for further processing or analysis.

Input types

Required

  • detailer_pipe
    • Represents the detailer pipe from which various components are extracted. It is crucial for the operation as it contains all the elements that need to be decomposed and returned individually.
    • Comfy dtype: DETAILER_PIPE
    • Python dtype: Tuple[torch.Tensor, ...]

Output types

  • model
    • Comfy dtype: MODEL
    • Returns the model component extracted from the detailer pipe, essential for further processing or analysis.
    • Python dtype: torch.Tensor
  • clip
    • Comfy dtype: CLIP
    • Returns the clip component extracted from the detailer pipe, essential for further processing or analysis.
    • Python dtype: torch.Tensor
  • vae
    • Comfy dtype: VAE
    • Returns the VAE component extracted from the detailer pipe, essential for further processing or analysis.
    • Python dtype: torch.Tensor
  • positive
    • Comfy dtype: CONDITIONING
    • Returns the positive conditioning information extracted from the detailer pipe, essential for further processing or analysis.
    • Python dtype: torch.Tensor
  • negative
    • Comfy dtype: CONDITIONING
    • Returns the negative conditioning information extracted from the detailer pipe, essential for further processing or analysis.
    • Python dtype: torch.Tensor
  • bbox_detector
    • Comfy dtype: BBOX_DETECTOR
    • Returns the bounding box detector component extracted from the detailer pipe, essential for further processing or analysis.
    • Python dtype: torch.Tensor
  • sam_model_opt
    • Comfy dtype: SAM_MODEL
    • Returns the SAM model component extracted from the detailer pipe, essential for further processing or analysis.
    • Python dtype: torch.Tensor
  • segm_detector_opt
    • Comfy dtype: SEGM_DETECTOR
    • Returns the segmentation detector component extracted from the detailer pipe, essential for further processing or analysis.
    • Python dtype: torch.Tensor
  • detailer_hook
    • Comfy dtype: DETAILER_HOOK
    • Returns the detailer hook component extracted from the detailer pipe, essential for further processing or analysis.
    • Python dtype: torch.Tensor

Usage tips

Source code

class FromDetailerPipe:
    @classmethod
    def INPUT_TYPES(s):
        return {"required": {"detailer_pipe": ("DETAILER_PIPE",), }, }

    RETURN_TYPES = ("MODEL", "CLIP", "VAE", "CONDITIONING", "CONDITIONING", "BBOX_DETECTOR", "SAM_MODEL", "SEGM_DETECTOR", "DETAILER_HOOK")
    RETURN_NAMES = ("model", "clip", "vae", "positive", "negative", "bbox_detector", "sam_model_opt", "segm_detector_opt", "detailer_hook")
    FUNCTION = "doit"

    CATEGORY = "ImpactPack/Pipe"

    def doit(self, detailer_pipe):
        model, clip, vae, positive, negative, wildcard, bbox_detector, segm_detector_opt, sam_model_opt, detailer_hook, _, _, _, _ = detailer_pipe
        return model, clip, vae, positive, negative, bbox_detector, sam_model_opt, segm_detector_opt, detailer_hook