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feat: node editor

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squashed rebase on main after backendd refactor
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psychedelicious
2023-08-14 13:23:09 +10:00
parent d6c9bf5b38
commit f49fc7fb55
188 changed files with 8541 additions and 4660 deletions
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117
invokeai/app/invocations/param_easing.py
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@ -1,73 +1,63 @@
import io
from typing import Literal, Optional, Any
from typing import Literal, Optional
# from PIL.Image import Image
import PIL.Image
from matplotlib.ticker import MaxNLocator
from matplotlib.figure import Figure
from pydantic import BaseModel, Field
import numpy as np
import matplotlib.pyplot as plt
import numpy as np
import PIL.Image
from easing_functions import (
LinearInOut,
QuadEaseInOut,
QuadEaseIn,
QuadEaseOut,
CubicEaseInOut,
CubicEaseIn,
CubicEaseOut,
QuarticEaseInOut,
QuarticEaseIn,
QuarticEaseOut,
QuinticEaseInOut,
QuinticEaseIn,
QuinticEaseOut,
SineEaseInOut,
SineEaseIn,
SineEaseOut,
CircularEaseIn,
CircularEaseInOut,
CircularEaseOut,
ExponentialEaseInOut,
ExponentialEaseIn,
ExponentialEaseOut,
ElasticEaseIn,
ElasticEaseInOut,
ElasticEaseOut,
BackEaseIn,
BackEaseInOut,
BackEaseOut,
BounceEaseIn,
BounceEaseInOut,
BounceEaseOut,
CircularEaseIn,
CircularEaseInOut,
CircularEaseOut,
CubicEaseIn,
CubicEaseInOut,
CubicEaseOut,
ElasticEaseIn,
ElasticEaseInOut,
ElasticEaseOut,
ExponentialEaseIn,
ExponentialEaseInOut,
ExponentialEaseOut,
LinearInOut,
QuadEaseIn,
QuadEaseInOut,
QuadEaseOut,
QuarticEaseIn,
QuarticEaseInOut,
QuarticEaseOut,
QuinticEaseIn,
QuinticEaseInOut,
QuinticEaseOut,
SineEaseIn,
SineEaseInOut,
SineEaseOut,
)
from matplotlib.figure import Figure
from matplotlib.ticker import MaxNLocator
from pydantic import BaseModel, Field
from .baseinvocation import (
BaseInvocation,
BaseInvocationOutput,
InvocationContext,
InvocationConfig,
)
from ...backend.util.logging import InvokeAILogger
from .baseinvocation import BaseInvocation, InputField, InvocationContext, tags, title
from .collections import FloatCollectionOutput
@title("Float Range")
@tags("math", "range")
class FloatLinearRangeInvocation(BaseInvocation):
"""Creates a range"""
type: Literal["float_range"] = "float_range"
# Inputs
start: float = Field(default=5, description="The first value of the range")
stop: float = Field(default=10, description="The last value of the range")
steps: int = Field(default=30, description="number of values to interpolate over (including start and stop)")
class Config(InvocationConfig):
schema_extra = {
"ui": {"title": "Linear Range (Float)", "tags": ["math", "float", "linear", "range"]},
}
start: float = InputField(default=5, description="The first value of the range")
stop: float = InputField(default=10, description="The last value of the range")
steps: int = InputField(default=30, description="number of values to interpolate over (including start and stop)")
def invoke(self, context: InvocationContext) -> FloatCollectionOutput:
param_list = list(np.linspace(self.start, self.stop, self.steps))
@ -108,37 +98,32 @@ EASING_FUNCTIONS_MAP = {
"BounceInOut": BounceEaseInOut,
}
EASING_FUNCTION_KEYS: Any = Literal[tuple(list(EASING_FUNCTIONS_MAP.keys()))]
EASING_FUNCTION_KEYS = Literal[tuple(list(EASING_FUNCTIONS_MAP.keys()))]
# actually I think for now could just use CollectionOutput (which is list[Any]
@title("Step Param Easing")
@tags("step", "easing")
class StepParamEasingInvocation(BaseInvocation):
"""Experimental per-step parameter easing for denoising steps"""
type: Literal["step_param_easing"] = "step_param_easing"
# Inputs
# fmt: off
easing: EASING_FUNCTION_KEYS = Field(default="Linear", description="The easing function to use")
num_steps: int = Field(default=20, description="number of denoising steps")
start_value: float = Field(default=0.0, description="easing starting value")
end_value: float = Field(default=1.0, description="easing ending value")
start_step_percent: float = Field(default=0.0, description="fraction of steps at which to start easing")
end_step_percent: float = Field(default=1.0, description="fraction of steps after which to end easing")
easing: EASING_FUNCTION_KEYS = InputField(default="Linear", description="The easing function to use")
num_steps: int = InputField(default=20, description="number of denoising steps")
start_value: float = InputField(default=0.0, description="easing starting value")
end_value: float = InputField(default=1.0, description="easing ending value")
start_step_percent: float = InputField(default=0.0, description="fraction of steps at which to start easing")
end_step_percent: float = InputField(default=1.0, description="fraction of steps after which to end easing")
# if None, then start_value is used prior to easing start
pre_start_value: Optional[float] = Field(default=None, description="value before easing start")
pre_start_value: Optional[float] = InputField(default=None, description="value before easing start")
# if None, then end value is used prior to easing end
post_end_value: Optional[float] = Field(default=None, description="value after easing end")
mirror: bool = Field(default=False, description="include mirror of easing function")
post_end_value: Optional[float] = InputField(default=None, description="value after easing end")
mirror: bool = InputField(default=False, description="include mirror of easing function")
# FIXME: add alt_mirror option (alternative to default or mirror), or remove entirely
# alt_mirror: bool = Field(default=False, description="alternative mirroring by dual easing")
show_easing_plot: bool = Field(default=False, description="show easing plot")
# fmt: on
class Config(InvocationConfig):
schema_extra = {
"ui": {"title": "Param Easing By Step", "tags": ["param", "step", "easing"]},
}
# alt_mirror: bool = InputField(default=False, description="alternative mirroring by dual easing")
show_easing_plot: bool = InputField(default=False, description="show easing plot")
def invoke(self, context: InvocationContext) -> FloatCollectionOutput:
log_diagnostics = False