pipe > detailer_pipe

Documentation

• Class name: ttN pipe2DETAILER
• Category: ttN/pipe
• Output node: False

The ttN pipe2DETAILER node is designed to enhance and detail a given pipeline with additional features and processing steps, incorporating bounding box detection, optional segmentation, and other detailing functionalities to refine the output.

Input types

Required

• pipe
  • Represents the pipeline to be enhanced and detailed, serving as the foundational structure for further processing.
  • Comfy dtype: PIPE_LINE
  • Python dtype: Dict[str, Any]
• bbox_detector
  • Specifies the bounding box detector to be used for identifying regions of interest within the pipeline's output.
  • Comfy dtype: BBOX_DETECTOR
  • Python dtype: Callable
• wildcard
  • A flexible input for additional specifications or configurations, allowing for custom adjustments to the detailing process.
  • Comfy dtype: STRING
  • Python dtype: str

Optional

• sam_model_opt
  • An optional model for semantic segmentation, providing additional detail through segmentation masks.
  • Comfy dtype: SAM_MODEL
  • Python dtype: Optional[Callable]
• segm_detector_opt
  • An optional segmentation detector to further refine the output with segmentation details.
  • Comfy dtype: SEGM_DETECTOR
  • Python dtype: Optional[Callable]
• detailer_hook
  • A hook for custom detailing functions, enabling further customization of the detailing process.
  • Comfy dtype: DETAILER_HOOK
  • Python dtype: Optional[Callable]

Output types

• detailer_pipe
  • Comfy dtype: DETAILER_PIPE
  • The enhanced and detailed version of the input pipeline, incorporating additional features and processing steps.
  • Python dtype: Tuple[Optional[Any], ...]
• pipe
  • Comfy dtype: PIPE_LINE
  • The original pipeline input, returned for reference or further processing.
  • Python dtype: Dict[str, Any]

Usage tips

• Infra type: CPU
• Common nodes: unknown

Source code

class ttN_pipe_2DETAILER:
    version = '1.2.0'
    @classmethod
    def INPUT_TYPES(s):
        return {"required": {"pipe": ("PIPE_LINE",),
                             "bbox_detector": ("BBOX_DETECTOR", ), 
                             "wildcard": ("STRING", {"multiline": True, "placeholder": "wildcard spec: if kept empty, this option will be ignored"}),
                            },
                "optional": {"sam_model_opt": ("SAM_MODEL", ), 
                             "segm_detector_opt": ("SEGM_DETECTOR",),
                             "detailer_hook": ("DETAILER_HOOK",),
                            },
                "hidden": {"ttNnodeVersion": ttN_pipe_2DETAILER.version},
                }

    RETURN_TYPES = ("DETAILER_PIPE", "PIPE_LINE" )
    RETURN_NAMES = ("detailer_pipe", "pipe")
    FUNCTION = "flush"

    CATEGORY = "ttN/pipe"

    def flush(self, pipe, bbox_detector, wildcard, sam_model_opt=None, segm_detector_opt=None, detailer_hook=None):
        detailer_pipe = (pipe.get('model'), pipe.get('clip'), pipe.get('vae'), pipe.get('positive'), pipe.get('negative'), wildcard,
                         bbox_detector, segm_detector_opt, sam_model_opt, detailer_hook, None, None, None, None)
        return (detailer_pipe, pipe, )