Edit DetailerPipe (SDXL)¶
Documentation¶
- Class name:
EditDetailerPipeSDXL
- Category:
ImpactPack/Pipe
- Output node:
False
The EditDetailerPipeSDXL node is designed to enhance and refine the details of inputs through a sophisticated editing pipeline. It allows for the integration of various models and techniques, including LoRA and Wildcards, to achieve more precise and impactful modifications.
Input types¶
Required¶
detailer_pipe
- Represents the initial detailer pipeline to be enhanced or modified. It serves as the foundation for further refinements.
- Comfy dtype:
DETAILER_PIPE
- Python dtype:
tuple
wildcard
- Allows for dynamic text input that can be used to modify or influence the detailer pipeline in a flexible manner.
- Comfy dtype:
STRING
- Python dtype:
str
Select to add LoRA
- Provides a selection mechanism for integrating LoRA (Low-Rank Adaptation) techniques into the text, enhancing its detail and specificity.
- Comfy dtype:
COMBO[STRING]
- Python dtype:
List[str]
Select to add Wildcard
- Enables the selection of predefined Wildcards to be added to the text, offering additional customization and detail enhancement.
- Comfy dtype:
COMBO[STRING]
- Python dtype:
List[str]
Optional¶
model
- Specifies the model to be used in the detailer pipeline, contributing to the enhancement process.
- Comfy dtype:
MODEL
- Python dtype:
MODEL
clip
- Defines the CLIP model to be integrated into the pipeline for improved content understanding and manipulation.
- Comfy dtype:
CLIP
- Python dtype:
CLIP
vae
- Specifies the VAE model to be used for generating or modifying content within the pipeline.
- Comfy dtype:
VAE
- Python dtype:
VAE
positive
- Defines positive conditioning to guide the generation or modification process towards desired attributes.
- Comfy dtype:
CONDITIONING
- Python dtype:
CONDITIONING
negative
- Specifies negative conditioning to steer the generation or modification process away from undesired attributes.
- Comfy dtype:
CONDITIONING
- Python dtype:
CONDITIONING
refiner_model
- Specifies an additional model for refining the details further in the pipeline.
- Comfy dtype:
MODEL
- Python dtype:
MODEL
refiner_clip
- Defines an additional CLIP model for enhanced content understanding and manipulation in the refinement process.
- Comfy dtype:
CLIP
- Python dtype:
CLIP
refiner_positive
- Defines additional positive conditioning for the refinement process, enhancing desired attributes.
- Comfy dtype:
CONDITIONING
- Python dtype:
CONDITIONING
refiner_negative
- Specifies additional negative conditioning for the refinement process, avoiding undesired attributes.
- Comfy dtype:
CONDITIONING
- Python dtype:
CONDITIONING
bbox_detector
- Specifies a bounding box detector to be used for object detection and localization within the pipeline.
- Comfy dtype:
BBOX_DETECTOR
- Python dtype:
BBOX_DETECTOR
sam_model
- Specifies a SAM model to be integrated for semantic adjustment or manipulation within the pipeline.
- Comfy dtype:
SAM_MODEL
- Python dtype:
SAM_MODEL
segm_detector
- Defines a segmentation detector to be used for segmenting different parts or objects within the content.
- Comfy dtype:
SEGM_DETECTOR
- Python dtype:
SEGM_DETECTOR
detailer_hook
- Provides a hook for custom detailer functions or modifications to be applied within the pipeline.
- Comfy dtype:
DETAILER_HOOK
- Python dtype:
DETAILER_HOOK
Output types¶
detailer_pipe
- Comfy dtype:
DETAILER_PIPE
- Outputs the enhanced detailer pipeline, incorporating all specified models, techniques, and modifications.
- Python dtype:
tuple
- Comfy dtype:
Usage tips¶
- Infra type:
CPU
- Common nodes: unknown
Source code¶
class EditDetailerPipeSDXL(EditDetailerPipe):
@classmethod
def INPUT_TYPES(s):
return {
"required": {
"detailer_pipe": ("DETAILER_PIPE",),
"wildcard": ("STRING", {"multiline": True, "dynamicPrompts": False}),
"Select to add LoRA": (["Select the LoRA to add to the text"] + folder_paths.get_filename_list("loras"),),
"Select to add Wildcard": (["Select the Wildcard to add to the text"],),
},
"optional": {
"model": ("MODEL",),
"clip": ("CLIP",),
"vae": ("VAE",),
"positive": ("CONDITIONING",),
"negative": ("CONDITIONING",),
"refiner_model": ("MODEL",),
"refiner_clip": ("CLIP",),
"refiner_positive": ("CONDITIONING",),
"refiner_negative": ("CONDITIONING",),
"bbox_detector": ("BBOX_DETECTOR",),
"sam_model": ("SAM_MODEL",),
"segm_detector": ("SEGM_DETECTOR",),
"detailer_hook": ("DETAILER_HOOK",),
},
}