Mirrored_Repos/InvokeAI
1
0
Fork 0
mirror of https://github.com/invoke-ai/InvokeAI synced 2024-08-30 20:32:17 +00:00
Code Issues Packages Projects Releases Wiki Activity

feat(nodes): tidy controlnet processor nodes & improve descriptions

Browse Source
This commit is contained in:
psychedelicious 2023-06-01 12:54:57 +10:00
parent c3935d3849
commit d6a959b000
1 changed files with 44 additions and 44 deletions
Show Stats Download Patch File Download Diff File Expand all files Collapse all files

88
invokeai/app/invocations/controlnet_image_processors.py
View File

@ -94,13 +94,13 @@ CONTROLNET_DEFAULT_MODELS = [
CONTROLNET_NAME_VALUES = Literal[tuple(CONTROLNET_DEFAULT_MODELS)]
class ControlField(BaseModel):
image: ImageField = Field(default=None, description="processed image")
control_model: Optional[str] = Field(default=None, description="control model used")
control_weight: Optional[float] = Field(default=1, description="weight given to controlnet")
image: ImageField = Field(default=None, description="The control image")
control_model: Optional[str] = Field(default=None, description="The ControlNet model to use")
control_weight: Optional[float] = Field(default=1, description="The weight given to the ControlNet")
begin_step_percent: float = Field(default=0, ge=0, le=1,
description="% of total steps at which controlnet is first applied")
description="When the ControlNet is first applied (% of total steps)")
end_step_percent: float = Field(default=1, ge=0, le=1,
description="% of total steps at which controlnet is last applied")
description="When the ControlNet is last applied (% of total steps)")
class Config:
schema_extra = {
@ -112,7 +112,7 @@ class ControlOutput(BaseInvocationOutput):
"""node output for ControlNet info"""
# fmt: off
type: Literal["control_output"] = "control_output"
control: ControlField = Field(default=None, description="The control info dict")
control: ControlField = Field(default=None, description="The output control image")
# fmt: on
@ -121,15 +121,15 @@ class ControlNetInvocation(BaseInvocation):
# fmt: off
type: Literal["controlnet"] = "controlnet"
# Inputs
image: ImageField = Field(default=None, description="image to process")
image: ImageField = Field(default=None, description="The control image")
control_model: CONTROLNET_NAME_VALUES = Field(default="lllyasviel/sd-controlnet-canny",
description="control model used")
control_weight: float = Field(default=1.0, ge=0, le=1, description="weight given to controlnet")
description="The ControlNet model to use")
control_weight: float = Field(default=1.0, ge=0, le=1, description="The weight given to the ControlNet")
# TODO: add support in backend core for begin_step_percent, end_step_percent, guess_mode
begin_step_percent: float = Field(default=0, ge=0, le=1,
description="% of total steps at which controlnet is first applied")
description="When the ControlNet is first applied (% of total steps)")
end_step_percent: float = Field(default=1, ge=0, le=1,
description="% of total steps at which controlnet is last applied")
description="When the ControlNet is last applied (% of total steps)")
# fmt: on
@ -152,7 +152,7 @@ class ImageProcessorInvocation(BaseInvocation, PILInvocationConfig):
# fmt: off
type: Literal["image_processor"] = "image_processor"
# Inputs
image: ImageField = Field(default=None, description="image to process")
image: ImageField = Field(default=None, description="The image to process")
# fmt: on
@ -204,8 +204,8 @@ class CannyImageProcessorInvocation(ImageProcessorInvocation, PILInvocationConfi
# fmt: off
type: Literal["canny_image_processor"] = "canny_image_processor"
# Input
low_threshold: float = Field(default=100, ge=0, description="low threshold of Canny pixel gradient")
high_threshold: float = Field(default=200, ge=0, description="high threshold of Canny pixel gradient")
low_threshold: int = Field(default=100, ge=0, le=255, description="The low threshold of the Canny pixel gradient (0-255)")
high_threshold: int = Field(default=200, ge=0, le=255, description="The high threshold of the Canny pixel gradient (0-255)")
# fmt: on
def run_processor(self, image):
@ -219,11 +219,11 @@ class HedImageprocessorInvocation(ImageProcessorInvocation, PILInvocationConfig)
# fmt: off
type: Literal["hed_image_processor"] = "hed_image_processor"
# Inputs
detect_resolution: int = Field(default=512, ge=0, description="pixel resolution for edge detection")
image_resolution: int = Field(default=512, ge=0, description="pixel resolution for output image")
detect_resolution: int = Field(default=512, ge=0, description="The pixel resolution for edge detection")
image_resolution: int = Field(default=512, ge=0, description="The pixel resolution for the output image")
# safe not supported in controlnet_aux v0.0.3
# safe: bool = Field(default=False, description="whether to use safe mode")
scribble: bool = Field(default=False, description="whether to use scribble mode")
scribble: bool = Field(default=False, description="Whether to use scribble mode")
# fmt: on
def run_processor(self, image):
@ -243,9 +243,9 @@ class LineartImageProcessorInvocation(ImageProcessorInvocation, PILInvocationCon
# fmt: off
type: Literal["lineart_image_processor"] = "lineart_image_processor"
# Inputs
detect_resolution: int = Field(default=512, ge=0, description="pixel resolution for edge detection")
image_resolution: int = Field(default=512, ge=0, description="pixel resolution for output image")
coarse: bool = Field(default=False, description="whether to use coarse mode")
detect_resolution: int = Field(default=512, ge=0, description="The pixel resolution for edge detection")
image_resolution: int = Field(default=512, ge=0, description="The pixel resolution for the output image")
coarse: bool = Field(default=False, description="Whether to use coarse mode")
# fmt: on
def run_processor(self, image):
@ -262,8 +262,8 @@ class LineartAnimeImageProcessorInvocation(ImageProcessorInvocation, PILInvocati
# fmt: off
type: Literal["lineart_anime_image_processor"] = "lineart_anime_image_processor"
# Inputs
detect_resolution: int = Field(default=512, ge=0, description="pixel resolution for edge detection")
image_resolution: int = Field(default=512, ge=0, description="pixel resolution for output image")
detect_resolution: int = Field(default=512, ge=0, description="The pixel resolution for edge detection")
image_resolution: int = Field(default=512, ge=0, description="The pixel resolution for the output image")
# fmt: on
def run_processor(self, image):
@ -280,9 +280,9 @@ class OpenposeImageProcessorInvocation(ImageProcessorInvocation, PILInvocationCo
# fmt: off
type: Literal["openpose_image_processor"] = "openpose_image_processor"
# Inputs
hand_and_face: bool = Field(default=False, description="whether to use hands and face mode")
detect_resolution: int = Field(default=512, ge=0, description="pixel resolution for edge detection")
image_resolution: int = Field(default=512, ge=0, description="pixel resolution for output image")
hand_and_face: bool = Field(default=False, description="Whether to use hands and face mode")
detect_resolution: int = Field(default=512, ge=0, description="The pixel resolution for edge detection")
image_resolution: int = Field(default=512, ge=0, description="The pixel resolution for the output image")
# fmt: on
def run_processor(self, image):
@ -300,8 +300,8 @@ class MidasDepthImageProcessorInvocation(ImageProcessorInvocation, PILInvocation
# fmt: off
type: Literal["midas_depth_image_processor"] = "midas_depth_image_processor"
# Inputs
a_mult: float = Field(default=2.0, ge=0, description="Midas parameter a = amult * PI")
bg_th: float = Field(default=0.1, ge=0, description="Midas parameter bg_th")
a_mult: float = Field(default=2.0, ge=0, description="Midas parameter `a_mult` (a = a_mult * PI)")
bg_th: float = Field(default=0.1, ge=0, description="Midas parameter `bg_th`")
# depth_and_normal not supported in controlnet_aux v0.0.3
# depth_and_normal: bool = Field(default=False, description="whether to use depth and normal mode")
# fmt: on
@ -322,8 +322,8 @@ class NormalbaeImageProcessorInvocation(ImageProcessorInvocation, PILInvocationC
# fmt: off
type: Literal["normalbae_image_processor"] = "normalbae_image_processor"
# Inputs
detect_resolution: int = Field(default=512, ge=0, description="pixel resolution for edge detection")
image_resolution: int = Field(default=512, ge=0, description="pixel resolution for output image")
detect_resolution: int = Field(default=512, ge=0, description="The pixel resolution for edge detection")
image_resolution: int = Field(default=512, ge=0, description="The pixel resolution for the output image")
# fmt: on
def run_processor(self, image):
@ -339,10 +339,10 @@ class MlsdImageProcessorInvocation(ImageProcessorInvocation, PILInvocationConfig
# fmt: off
type: Literal["mlsd_image_processor"] = "mlsd_image_processor"
# Inputs
detect_resolution: int = Field(default=512, ge=0, description="pixel resolution for edge detection")
image_resolution: int = Field(default=512, ge=0, description="pixel resolution for output image")
thr_v: float = Field(default=0.1, ge=0, description="MLSD parameter thr_v")
thr_d: float = Field(default=0.1, ge=0, description="MLSD parameter thr_d")
detect_resolution: int = Field(default=512, ge=0, description="The pixel resolution for edge detection")
image_resolution: int = Field(default=512, ge=0, description="The pixel resolution for the output image")
thr_v: float = Field(default=0.1, ge=0, description="MLSD parameter `thr_v`")
thr_d: float = Field(default=0.1, ge=0, description="MLSD parameter `thr_d`")
# fmt: on
def run_processor(self, image):
@ -360,10 +360,10 @@ class PidiImageProcessorInvocation(ImageProcessorInvocation, PILInvocationConfig
# fmt: off
type: Literal["pidi_image_processor"] = "pidi_image_processor"
# Inputs
detect_resolution: int = Field(default=512, ge=0, description="pixel resolution for edge detection")
image_resolution: int = Field(default=512, ge=0, description="pixel resolution for output image")
safe: bool = Field(default=False, description="whether to use safe mode")
scribble: bool = Field(default=False, description="whether to use scribble mode")
detect_resolution: int = Field(default=512, ge=0, description="The pixel resolution for edge detection")
image_resolution: int = Field(default=512, ge=0, description="The pixel resolution for the output image")
safe: bool = Field(default=False, description="Whether to use safe mode")
scribble: bool = Field(default=False, description="Whether to use scribble mode")
# fmt: on
def run_processor(self, image):
@ -381,11 +381,11 @@ class ContentShuffleImageProcessorInvocation(ImageProcessorInvocation, PILInvoca
# fmt: off
type: Literal["content_shuffle_image_processor"] = "content_shuffle_image_processor"
# Inputs
detect_resolution: int = Field(default=512, ge=0, description="pixel resolution for edge detection")
image_resolution: int = Field(default=512, ge=0, description="pixel resolution for output image")
h: Union[int | None] = Field(default=512, ge=0, description="content shuffle h parameter")
w: Union[int | None] = Field(default=512, ge=0, description="content shuffle w parameter")
f: Union[int | None] = Field(default=256, ge=0, description="cont")
detect_resolution: int = Field(default=512, ge=0, description="The pixel resolution for edge detection")
image_resolution: int = Field(default=512, ge=0, description="The pixel resolution for the output image")
h: Union[int, None] = Field(default=512, ge=0, description="Content shuffle `h` parameter")
w: Union[int, None] = Field(default=512, ge=0, description="Content shuffle `w` parameter")
f: Union[int, None] = Field(default=256, ge=0, description="Content shuffle `f` parameter")
# fmt: on
def run_processor(self, image):
@ -418,8 +418,8 @@ class MediapipeFaceProcessorInvocation(ImageProcessorInvocation, PILInvocationCo
# fmt: off
type: Literal["mediapipe_face_processor"] = "mediapipe_face_processor"
# Inputs
max_faces: int = Field(default=1, ge=1, description="maximum number of faces to detect")
min_confidence: float = Field(default=0.5, ge=0, le=1, description="minimum confidence for face detection")
max_faces: int = Field(default=1, ge=1, description="Maximum number of faces to detect")
min_confidence: float = Field(default=0.5, ge=0, le=1, description="Minimum confidence for face detection")
# fmt: on
def run_processor(self, image):