mirror of
https://github.com/comfyanonymous/ComfyUI.git
synced 2025-07-27 16:26:39 +00:00
Added some missing type defs, starting work on a revision (v3_01) to change formatting (need to change execution.py to recognize it as v3 as well)
This commit is contained in:
kosinkadink1@gmail.com
parent
2873aaf4db
commit
6854864db9
@ -115,6 +115,14 @@ class WidgetInputV3(InputV3, io_type=None):
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"widgetType": self.widgetType,
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})
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class OutputV3(IO_V3, io_type=None):
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def __init__(self, id: str, display_name: str=None, tooltip: str=None,
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is_output_list=False):
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self.id = id
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self.display_name = display_name
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self.tooltip = tooltip
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self.is_output_list = is_output_list
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def CustomType(io_type: IO | str) -> type[IO_V3]:
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name = f"{io_type}_IO_V3"
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return type(name, (IO_V3,), {}, io_type=io_type)
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@ -163,6 +171,9 @@ class BooleanInput(WidgetInputV3, io_type=IO.BOOLEAN):
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"label_off": self.label_off,
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})
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class BooleanOutput(OutputV3, io_type=IO.BOOLEAN):
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...
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class IntegerInput(WidgetInputV3, io_type=IO.INT):
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'''
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Integer input.
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@ -188,6 +199,9 @@ class IntegerInput(WidgetInputV3, io_type=IO.INT):
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"display": self.display_mode, # NOTE: in frontend, the parameter is called "display"
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})
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class IntegerOutput(OutputV3, io_type=IO.INT):
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...
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class FloatInput(WidgetInputV3, io_type=IO.FLOAT):
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'''
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Float input.
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@ -213,6 +227,9 @@ class FloatInput(WidgetInputV3, io_type=IO.FLOAT):
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"round": self.round,
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"display": self.display_mode, # NOTE: in frontend, the parameter is called "display"
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})
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class FloatOutput(OutputV3, io_type=IO.FLOAT):
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...
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class StringInput(WidgetInputV3, io_type=IO.STRING):
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'''
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@ -233,6 +250,9 @@ class StringInput(WidgetInputV3, io_type=IO.STRING):
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"placeholder": self.placeholder,
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})
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class StringOutput(OutputV3, io_type=IO.STRING):
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...
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class ComboInput(WidgetInputV3, io_type=IO.COMBO):
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'''Combo input (dropdown).'''
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Type = str
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@ -279,27 +299,193 @@ class MultiselectComboWidget(ComboInput, io_type=IO.COMBO):
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})
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class ImageInput(InputV3, io_type=IO.IMAGE):
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'''
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Image input.
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'''
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'''Image input.'''
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Type = torch.Tensor
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class ImageOutput(OutputV3, io_type=IO.IMAGE):
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'''Image output.'''
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Type = torch.Tensor
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def __init__(self, id: str, display_name: str=None, optional=False, tooltip: str=None):
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super().__init__(id, display_name, optional, tooltip)
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class MaskInput(InputV3, io_type=IO.MASK):
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'''
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Mask input.
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'''
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'''Mask input.'''
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Type = torch.Tensor
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class MaskOutput(OutputV3, io_type=IO.MASK):
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'''Mask output.'''
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Type = torch.Tensor
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def __init__(self, id: str, display_name: str=None, optional=False, tooltip: str=None):
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super().__init__(id, display_name, optional, tooltip)
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class LatentInput(InputV3, io_type=IO.LATENT):
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'''
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Latent input.
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'''
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def __init__(self, id: str, display_name: str=None, optional=False, tooltip: str=None):
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super().__init__(id, display_name, optional, tooltip)
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'''Latent input.'''
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# TODO: make Type a TypedDict
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...
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class LatentOutput(OutputV3, io_type=IO.LATENT):
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'''Latent output.'''
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# TODO: make Type a TypedDict
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...
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class ConditioningInput(InputV3, io_type=IO.CONDITIONING):
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'''Conditioning input.'''
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# TODO: make Type a TypedDict
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...
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class ConditioningOutput(OutputV3, io_type=IO.CONDITIONING):
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'''Conditioning output.'''
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# TODO: make Type a TypedDict
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...
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class SamplerInput(InputV3, io_type=IO.SAMPLER):
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'''Sampler input.'''
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...
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class SamplerOutput(OutputV3, io_type=IO.SAMPLER):
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'''Sampler output.'''
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...
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class SigmasInput(InputV3, io_type=IO.SIGMAS):
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'''Sigmas input.'''
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...
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class SigmasOutput(OutputV3, io_type=IO.SIGMAS):
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'''Sigmas output.'''
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...
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class GuiderInput(InputV3, io_type=IO.GUIDER):
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'''Guider input.'''
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...
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class GuiderOutput(OutputV3, io_type=IO.GUIDER):
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'''Guider output.'''
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...
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class NoiseInput(InputV3, io_type=IO.NOISE):
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'''Noise input.'''
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...
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class NoiseOutput(OutputV3, io_type=IO.NOISE):
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'''Noise output.'''
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...
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class ClipInput(InputV3, io_type=IO.CLIP):
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'''Clip input.'''
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...
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class ClipOutput(OutputV3, io_type=IO.CLIP):
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'''Clip output.'''
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...
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class ControlNetInput(InputV3, io_type=IO.CONTROL_NET):
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'''ControlNet input.'''
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...
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class ControlNetOutput(OutputV3, io_type=IO.CONTROL_NET):
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'''ControlNet output.'''
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...
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class VaeInput(InputV3, io_type=IO.VAE):
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'''Vae input.'''
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...
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class VaeOutput(OutputV3, io_type=IO.VAE):
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'''Vae output.'''
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...
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class ModelInput(InputV3, io_type=IO.MODEL):
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'''Model input.'''
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...
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class ModelOutput(OutputV3, io_type=IO.MODEL):
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'''Model output.'''
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...
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class ClipVisionInput(InputV3, io_type=IO.CLIP_VISION):
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'''ClipVision input.'''
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...
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class ClipVisionOutput(OutputV3, io_type=IO.CLIP_VISION):
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'''ClipVision output.'''
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...
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class ClipVisionOutputInput(InputV3, io_type=IO.CLIP_VISION_OUTPUT):
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'''CLipVisionOutput input.'''
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...
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class ClipVisionOutputOutput(OutputV3, io_type=IO.CLIP_VISION_OUTPUT):
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'''CLipVisionOutput output.'''
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...
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class StyleModelInput(InputV3, io_type=IO.STYLE_MODEL):
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'''StyleModel input.'''
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...
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class StyleModelOutput(OutputV3, io_type=IO.STYLE_MODEL):
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'''StyleModel output.'''
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...
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class GligenInput(InputV3, io_type=IO.GLIGEN):
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'''Gligen input.'''
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...
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class GligenOutput(OutputV3, io_type=IO.GLIGEN):
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'''Gligen output.'''
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...
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class UpscaleModelInput(InputV3, io_type=IO.UPSCALE_MODEL):
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'''UpscaleModel input.'''
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...
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class UpscaleModelOutput(OutputV3, io_type=IO.UPSCALE_MODEL):
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'''UpscaleModel output.'''
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...
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class AudioInput(InputV3, io_type=IO.AUDIO):
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'''Audio input.'''
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...
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class AudioOutput(OutputV3, io_type=IO.AUDIO):
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'''Audio output.'''
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...
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class PointInput(InputV3, io_type=IO.POINT):
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'''Point input.'''
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...
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class PointOutput(OutputV3, io_type=IO.POINT):
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'''Point output.'''
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...
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class FaceAnalysisInput(InputV3, io_type=IO.FACE_ANALYSIS):
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'''FaceAnalysis input.'''
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...
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class FaceAnalysisOutput(OutputV3, io_type=IO.FACE_ANALYSIS):
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'''FaceAnalysis output.'''
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...
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class BBOXInput(InputV3, io_type=IO.BBOX):
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'''Bbox input.'''
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...
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class BBOXOutput(OutputV3, io_type=IO.BBOX):
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'''Bbox output.'''
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...
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class SEGSInput(InputV3, io_type=IO.SEGS):
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'''SEGS input.'''
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...
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class SEGSOutput(OutputV3, io_type=IO.SEGS):
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'''SEGS output.'''
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...
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class VideoInput(InputV3, io_type=IO.VIDEO):
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'''Video input.'''
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...
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class VideoOutput(OutputV3, io_type=IO.VIDEO):
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'''Video output.'''
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...
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class MultitypedInput(InputV3, io_type="COMFY_MULTITYPED_V3"):
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'''
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@ -326,39 +512,6 @@ class MultitypedInput(InputV3, io_type="COMFY_MULTITYPED_V3"):
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return ",".join(x.io_type for x in self.io_types)
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class OutputV3:
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def __init__(self, id: str, display_name: str=None, tooltip: str=None,
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is_output_list=False):
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self.id = id
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self.display_name = display_name
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self.tooltip = tooltip
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self.is_output_list = is_output_list
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def __init_subclass__(cls, io_type, **kwargs):
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cls.io_type = io_type
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super().__init_subclass__(**kwargs)
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class IntegerOutput(OutputV3, io_type=IO.INT):
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pass
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class FloatOutput(OutputV3, io_type=IO.FLOAT):
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pass
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class StringOutput(OutputV3, io_type=IO.STRING):
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pass
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# def __init__(self, id: str, display_name: str=None, tooltip: str=None):
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# super().__init__(id, display_name, tooltip)
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class ImageOutput(OutputV3, io_type=IO.IMAGE):
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pass
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class MaskOutput(OutputV3, io_type=IO.MASK):
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pass
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class LatentOutput(OutputV3, io_type=IO.LATENT):
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pass
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class DynamicInput(InputV3, io_type=None):
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'''
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Abstract class for dynamic input registration.
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@ -566,7 +719,7 @@ def prepare_class_clone(c: ComfyNodeV3 | type[ComfyNodeV3]) -> type[ComfyNodeV3]
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type_clone: type[ComfyNodeV3] = type(f"CLEAN_{c_type.__name__}", c_type.__bases__, {})
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# TODO: what parameters should be carried over?
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type_clone.SCHEMA = c_type.SCHEMA
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# TODO: add anything we would want to expose inside node's EXECUTE function
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# TODO: add anything we would want to expose inside node's execute function
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return type_clone
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@ -698,7 +851,7 @@ class ComfyNodeV3(ABC):
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cls.GET_SCHEMA()
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return cls._OUTPUT_TOOLTIPS
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FUNCTION = "EXECUTE"
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FUNCTION = "execute"
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@classmethod
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def INPUT_TYPES(cls) -> dict[str, dict]:
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@ -763,7 +916,7 @@ class ComfyNodeV3(ABC):
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# create separate lists from output fields
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output = []
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output_is_list = []
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output_name = []
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output_name = []
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output_tooltips = []
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if schema.outputs:
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for o in schema.outputs:
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1122
comfy_api/v3_01/io.py
Normal file
1122
comfy_api/v3_01/io.py
Normal file
File diff suppressed because it is too large
Load Diff
74
comfy_extras/nodes_v3_01_test.py
Normal file
74
comfy_extras/nodes_v3_01_test.py
Normal file
@ -0,0 +1,74 @@
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import torch
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from comfy_api.v3_01 import io
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import logging
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class XYZ:
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Type = tuple[int,str]
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class Input(io.InputV3, io_type="XYZ"):
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...
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class Output(io.OutputV3, io_type="XYZ"):
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...
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class V3TestNode(io.ComfyNodeV3):
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def __init__(self):
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self.hahajkunless = ";)"
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@classmethod
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def DEFINE_SCHEMA(cls):
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return io.SchemaV3(
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node_id="V3_01_TestNode1",
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display_name="V3_01 Test Node",
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description="This is a funky V3_01 node test.",
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category="v3 nodes",
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inputs=[
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io.Image.Input("image", display_name="new_image"),
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XYZ.Input("xyz", optional=True),
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#CustomInput("xyz", "XYZ", optional=True),
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io.Mask.Input("mask", optional=True),
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io.Integer.Input("some_int", display_name="new_name", min=0, max=127, default=42,
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tooltip="My tooltip 😎", display_mode=io.NumberDisplay.slider),
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io.ComboInput("combo", options=["a", "b", "c"], tooltip="This is a combo input"),
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# ComboInput("combo", image_upload=True, image_folder=FolderType.output,
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# remote=RemoteOptions(
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# route="/internal/files/output",
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# refresh_button=True,
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# ),
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# tooltip="This is a combo input"),
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# IntegerInput("some_int", display_name="new_name", min=0, tooltip="My tooltip 😎", display=NumberDisplay.slider, ),
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# ComboDynamicInput("mask", behavior=InputBehavior.optional),
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# IntegerInput("some_int", display_name="new_name", min=0, tooltip="My tooltip 😎", display=NumberDisplay.slider,
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# dependent_inputs=[ComboDynamicInput("mask", behavior=InputBehavior.optional)],
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# dependent_values=[lambda my_value: IO.STRING if my_value < 5 else IO.NUMBER],
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# ),
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# ["option1", "option2". "option3"]
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# ComboDynamicInput["sdfgjhl", [ComboDynamicOptions("option1", [IntegerInput("some_int", display_name="new_name", min=0, tooltip="My tooltip 😎", display=NumberDisplay.slider, ImageInput(), MaskInput(), String()]),
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# CombyDynamicOptons("option2", [])
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# ]]
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],
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outputs=[
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io.Integer.Output("int_output"),
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io.Image.Output("img_output", display_name="img🖼️", tooltip="This is an image"),
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],
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hidden=[
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],
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is_output_node=True,
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)
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@classmethod
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def execute(cls, image: io.Image.Type, some_int: int, combo: io.ComboInput.Type, xyz: XYZ.Type=None, mask: io.Mask.Type=None):
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some_int
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if hasattr(cls, "hahajkunless"):
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raise Exception("The 'cls' variable leaked instance state between runs!")
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if hasattr(cls, "doohickey"):
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raise Exception("The 'cls' variable leaked state on class properties between runs!")
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cls.doohickey = "LOLJK"
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return io.NodeOutput(some_int, image)
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NODES_LIST: list[io.ComfyNodeV3] = [
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V3TestNode,
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]
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