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Add custom nodes, Civitai loras (LFS), and vast.ai setup script
Includes 30 custom nodes committed directly, 7 Civitai-exclusive
loras stored via Git LFS, and a setup script that installs all
dependencies and downloads HuggingFace-hosted models on vast.ai.

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
2026-02-09 00:56:42 +00:00

129 lines
4.1 KiB
Python

import sys
from . import hooks
from . import defs
class SEGSOrderedFilterDetailerHookProvider:
@classmethod
def INPUT_TYPES(s):
return {"required": {
"target": (["area(=w*h)", "width", "height", "x1", "y1", "x2", "y2"],),
"order": ("BOOLEAN", {"default": True, "label_on": "descending", "label_off": "ascending"}),
"take_start": ("INT", {"default": 0, "min": 0, "max": sys.maxsize, "step": 1}),
"take_count": ("INT", {"default": 1, "min": 0, "max": sys.maxsize, "step": 1}),
},
}
RETURN_TYPES = ("DETAILER_HOOK", )
FUNCTION = "doit"
CATEGORY = "ImpactPack/Util"
def doit(self, target, order, take_start, take_count):
hook = hooks.SEGSOrderedFilterDetailerHook(target, order, take_start, take_count)
return (hook, )
class SEGSRangeFilterDetailerHookProvider:
@classmethod
def INPUT_TYPES(s):
return {"required": {
"target": (["area(=w*h)", "width", "height", "x1", "y1", "x2", "y2", "length_percent"],),
"mode": ("BOOLEAN", {"default": True, "label_on": "inside", "label_off": "outside"}),
"min_value": ("INT", {"default": 0, "min": 0, "max": sys.maxsize, "step": 1}),
"max_value": ("INT", {"default": 67108864, "min": 0, "max": sys.maxsize, "step": 1}),
},
}
RETURN_TYPES = ("DETAILER_HOOK", )
FUNCTION = "doit"
CATEGORY = "ImpactPack/Util"
def doit(self, target, mode, min_value, max_value):
hook = hooks.SEGSRangeFilterDetailerHook(target, mode, min_value, max_value)
return (hook, )
class SEGSLabelFilterDetailerHookProvider:
@classmethod
def INPUT_TYPES(s):
return {"required": {
"segs": ("SEGS", ),
"preset": (['all'] + defs.detection_labels,),
"labels": ("STRING", {"multiline": True, "placeholder": "List the types of segments to be allowed, separated by commas"}),
},
}
RETURN_TYPES = ("DETAILER_HOOK", )
FUNCTION = "doit"
CATEGORY = "ImpactPack/Util"
def doit(self, preset, labels):
hook = hooks.SEGSLabelFilterDetailerHook(labels)
return (hook, )
class PreviewDetailerHookProvider:
@classmethod
def INPUT_TYPES(s):
return {
"required": {"quality": ("INT", {"default": 95, "min": 20, "max": 100})},
"hidden": {"unique_id": "UNIQUE_ID"},
}
RETURN_TYPES = ("DETAILER_HOOK", "UPSCALER_HOOK")
FUNCTION = "doit"
CATEGORY = "ImpactPack/Util"
NOT_IDEMPOTENT = True
def doit(self, quality, unique_id):
hook = hooks.PreviewDetailerHook(unique_id, quality)
return hook, hook
class LamaRemoverDetailerHookProvider:
@classmethod
def INPUT_TYPES(s):
return {
"required": {
"mask_threshold":("INT", {"default": 250, "min": 0, "max": 255, "step": 1, "display": "slider"}),
"gaussblur_radius": ("INT", {"default": 8, "min": 0, "max": 20, "step": 1, "display": "slider"}),
"skip_sampling": ("BOOLEAN", {"default": True}),
}
}
RETURN_TYPES = ("DETAILER_HOOK", )
FUNCTION = "doit"
CATEGORY = "ImpactPack/Util"
def doit(self, mask_threshold, gaussblur_radius, skip_sampling):
hook = hooks.LamaRemoverDetailerHook(mask_threshold, gaussblur_radius, skip_sampling)
return (hook, )
class BlackPatchRetryHookProvider:
@classmethod
def INPUT_TYPES(s):
return {
"required": {
"mean_thresh": ("INT", {"default": 10, "min": 0, "max": 255}),
"var_thresh": ("INT", {"default": 5, "min": 0, "max": 255})
},
}
RETURN_TYPES = ("DETAILER_HOOK", )
FUNCTION = "doit"
CATEGORY = "ImpactPack/Util"
NOT_IDEMPOTENT = True
def doit(self, mean_thresh, var_thresh):
hook = hooks.BlackPatchRetryHook(mean_thresh, var_thresh)
return hook,