mirror of
https://github.com/invoke-ai/InvokeAI
synced 2024-08-30 20:32:17 +00:00
fix(nodes): fix constraints/validation for controlnet
- Fix `weight` and `begin_step_percent`, the constraints were mixed up - Add model validatort to ensure `begin_step_percent < end_step_percent` - Bump version
This commit is contained in:
psychedelicious
Kent Keirsey
parent
d256d93a2a
commit
2700d0e769
@ -24,9 +24,10 @@ from controlnet_aux import (
|
||||
)
|
||||
from controlnet_aux.util import HWC3, ade_palette
|
||||
from PIL import Image
|
||||
from pydantic import BaseModel, ConfigDict, Field, field_validator
|
||||
from pydantic import BaseModel, ConfigDict, Field, field_validator, model_validator
|
||||
|
||||
from invokeai.app.invocations.primitives import ImageField, ImageOutput
|
||||
from invokeai.app.invocations.util import validate_begin_end_step, validate_weights
|
||||
from invokeai.app.services.image_records.image_records_common import ImageCategory, ResourceOrigin
|
||||
from invokeai.app.shared.fields import FieldDescriptions
|
||||
|
||||
@ -75,17 +76,16 @@ class ControlField(BaseModel):
|
||||
resize_mode: CONTROLNET_RESIZE_VALUES = Field(default="just_resize", description="The resize mode to use")
|
||||
|
||||
@field_validator("control_weight")
|
||||
@classmethod
|
||||
def validate_control_weight(cls, v):
|
||||
"""Validate that all control weights in the valid range"""
|
||||
if isinstance(v, list):
|
||||
for i in v:
|
||||
if i < -1 or i > 2:
|
||||
raise ValueError("Control weights must be within -1 to 2 range")
|
||||
else:
|
||||
if v < -1 or v > 2:
|
||||
raise ValueError("Control weights must be within -1 to 2 range")
|
||||
validate_weights(v)
|
||||
return v
|
||||
|
||||
@model_validator(mode="after")
|
||||
def validate_begin_end_step_percent(self):
|
||||
validate_begin_end_step(self.begin_step_percent, self.end_step_percent)
|
||||
return self
|
||||
|
||||
|
||||
@invocation_output("control_output")
|
||||
class ControlOutput(BaseInvocationOutput):
|
||||
@ -95,17 +95,17 @@ class ControlOutput(BaseInvocationOutput):
|
||||
control: ControlField = OutputField(description=FieldDescriptions.control)
|
||||
|
||||
|
||||
@invocation("controlnet", title="ControlNet", tags=["controlnet"], category="controlnet", version="1.1.0")
|
||||
@invocation("controlnet", title="ControlNet", tags=["controlnet"], category="controlnet", version="1.1.1")
|
||||
class ControlNetInvocation(BaseInvocation):
|
||||
"""Collects ControlNet info to pass to other nodes"""
|
||||
|
||||
image: ImageField = InputField(description="The control image")
|
||||
control_model: ControlNetModelField = InputField(description=FieldDescriptions.controlnet_model, input=Input.Direct)
|
||||
control_weight: Union[float, List[float]] = InputField(
|
||||
default=1.0, description="The weight given to the ControlNet"
|
||||
default=1.0, ge=-1, le=2, description="The weight given to the ControlNet"
|
||||
)
|
||||
begin_step_percent: float = InputField(
|
||||
default=0, ge=-1, le=2, description="When the ControlNet is first applied (% of total steps)"
|
||||
default=0, ge=0, le=1, description="When the ControlNet is first applied (% of total steps)"
|
||||
)
|
||||
end_step_percent: float = InputField(
|
||||
default=1, ge=0, le=1, description="When the ControlNet is last applied (% of total steps)"
|
||||
@ -113,6 +113,17 @@ class ControlNetInvocation(BaseInvocation):
|
||||
control_mode: CONTROLNET_MODE_VALUES = InputField(default="balanced", description="The control mode used")
|
||||
resize_mode: CONTROLNET_RESIZE_VALUES = InputField(default="just_resize", description="The resize mode used")
|
||||
|
||||
@field_validator("control_weight")
|
||||
@classmethod
|
||||
def validate_control_weight(cls, v):
|
||||
validate_weights(v)
|
||||
return v
|
||||
|
||||
@model_validator(mode="after")
|
||||
def validate_begin_end_step_percent(self) -> "ControlNetInvocation":
|
||||
validate_begin_end_step(self.begin_step_percent, self.end_step_percent)
|
||||
return self
|
||||
|
||||
def invoke(self, context: InvocationContext) -> ControlOutput:
|
||||
return ControlOutput(
|
||||
control=ControlField(
|
||||
|
||||
@ -2,7 +2,7 @@ import os
|
||||
from builtins import float
|
||||
from typing import List, Union
|
||||
|
||||
from pydantic import BaseModel, ConfigDict, Field
|
||||
from pydantic import BaseModel, ConfigDict, Field, field_validator, model_validator
|
||||
|
||||
from invokeai.app.invocations.baseinvocation import (
|
||||
BaseInvocation,
|
||||
@ -15,6 +15,7 @@ from invokeai.app.invocations.baseinvocation import (
|
||||
invocation_output,
|
||||
)
|
||||
from invokeai.app.invocations.primitives import ImageField
|
||||
from invokeai.app.invocations.util import validate_begin_end_step, validate_weights
|
||||
from invokeai.app.shared.fields import FieldDescriptions
|
||||
from invokeai.backend.model_management.models.base import BaseModelType, ModelType
|
||||
from invokeai.backend.model_management.models.ip_adapter import get_ip_adapter_image_encoder_model_id
|
||||
@ -39,7 +40,6 @@ class IPAdapterField(BaseModel):
|
||||
ip_adapter_model: IPAdapterModelField = Field(description="The IP-Adapter model to use.")
|
||||
image_encoder_model: CLIPVisionModelField = Field(description="The name of the CLIP image encoder model.")
|
||||
weight: Union[float, List[float]] = Field(default=1, description="The weight given to the ControlNet")
|
||||
# weight: float = Field(default=1.0, ge=0, description="The weight of the IP-Adapter.")
|
||||
begin_step_percent: float = Field(
|
||||
default=0, ge=0, le=1, description="When the IP-Adapter is first applied (% of total steps)"
|
||||
)
|
||||
@ -47,6 +47,17 @@ class IPAdapterField(BaseModel):
|
||||
default=1, ge=0, le=1, description="When the IP-Adapter is last applied (% of total steps)"
|
||||
)
|
||||
|
||||
@field_validator("weight")
|
||||
@classmethod
|
||||
def validate_ip_adapter_weight(cls, v):
|
||||
validate_weights(v)
|
||||
return v
|
||||
|
||||
@model_validator(mode="after")
|
||||
def validate_begin_end_step_percent(self):
|
||||
validate_begin_end_step(self.begin_step_percent, self.end_step_percent)
|
||||
return self
|
||||
|
||||
|
||||
@invocation_output("ip_adapter_output")
|
||||
class IPAdapterOutput(BaseInvocationOutput):
|
||||
@ -54,7 +65,7 @@ class IPAdapterOutput(BaseInvocationOutput):
|
||||
ip_adapter: IPAdapterField = OutputField(description=FieldDescriptions.ip_adapter, title="IP-Adapter")
|
||||
|
||||
|
||||
@invocation("ip_adapter", title="IP-Adapter", tags=["ip_adapter", "control"], category="ip_adapter", version="1.1.0")
|
||||
@invocation("ip_adapter", title="IP-Adapter", tags=["ip_adapter", "control"], category="ip_adapter", version="1.1.1")
|
||||
class IPAdapterInvocation(BaseInvocation):
|
||||
"""Collects IP-Adapter info to pass to other nodes."""
|
||||
|
||||
@ -64,18 +75,27 @@ class IPAdapterInvocation(BaseInvocation):
|
||||
description="The IP-Adapter model.", title="IP-Adapter Model", input=Input.Direct, ui_order=-1
|
||||
)
|
||||
|
||||
# weight: float = InputField(default=1.0, description="The weight of the IP-Adapter.", ui_type=UIType.Float)
|
||||
weight: Union[float, List[float]] = InputField(
|
||||
default=1, ge=-1, description="The weight given to the IP-Adapter", title="Weight"
|
||||
default=1, description="The weight given to the IP-Adapter", title="Weight"
|
||||
)
|
||||
|
||||
begin_step_percent: float = InputField(
|
||||
default=0, ge=-1, le=2, description="When the IP-Adapter is first applied (% of total steps)"
|
||||
default=0, ge=0, le=1, description="When the IP-Adapter is first applied (% of total steps)"
|
||||
)
|
||||
end_step_percent: float = InputField(
|
||||
default=1, ge=0, le=1, description="When the IP-Adapter is last applied (% of total steps)"
|
||||
)
|
||||
|
||||
@field_validator("weight")
|
||||
@classmethod
|
||||
def validate_ip_adapter_weight(cls, v):
|
||||
validate_weights(v)
|
||||
return v
|
||||
|
||||
@model_validator(mode="after")
|
||||
def validate_begin_end_step_percent(self):
|
||||
validate_begin_end_step(self.begin_step_percent, self.end_step_percent)
|
||||
return self
|
||||
|
||||
def invoke(self, context: InvocationContext) -> IPAdapterOutput:
|
||||
# Lookup the CLIP Vision encoder that is intended to be used with the IP-Adapter model.
|
||||
ip_adapter_info = context.services.model_manager.model_info(
|
||||
|
||||
@ -1,6 +1,6 @@
|
||||
from typing import Union
|
||||
|
||||
from pydantic import BaseModel, ConfigDict, Field
|
||||
from pydantic import BaseModel, ConfigDict, Field, field_validator, model_validator
|
||||
|
||||
from invokeai.app.invocations.baseinvocation import (
|
||||
BaseInvocation,
|
||||
@ -14,6 +14,7 @@ from invokeai.app.invocations.baseinvocation import (
|
||||
)
|
||||
from invokeai.app.invocations.controlnet_image_processors import CONTROLNET_RESIZE_VALUES
|
||||
from invokeai.app.invocations.primitives import ImageField
|
||||
from invokeai.app.invocations.util import validate_begin_end_step, validate_weights
|
||||
from invokeai.app.shared.fields import FieldDescriptions
|
||||
from invokeai.backend.model_management.models.base import BaseModelType
|
||||
|
||||
@ -37,6 +38,17 @@ class T2IAdapterField(BaseModel):
|
||||
)
|
||||
resize_mode: CONTROLNET_RESIZE_VALUES = Field(default="just_resize", description="The resize mode to use")
|
||||
|
||||
@field_validator("weight")
|
||||
@classmethod
|
||||
def validate_ip_adapter_weight(cls, v):
|
||||
validate_weights(v)
|
||||
return v
|
||||
|
||||
@model_validator(mode="after")
|
||||
def validate_begin_end_step_percent(self):
|
||||
validate_begin_end_step(self.begin_step_percent, self.end_step_percent)
|
||||
return self
|
||||
|
||||
|
||||
@invocation_output("t2i_adapter_output")
|
||||
class T2IAdapterOutput(BaseInvocationOutput):
|
||||
@ -44,7 +56,7 @@ class T2IAdapterOutput(BaseInvocationOutput):
|
||||
|
||||
|
||||
@invocation(
|
||||
"t2i_adapter", title="T2I-Adapter", tags=["t2i_adapter", "control"], category="t2i_adapter", version="1.0.0"
|
||||
"t2i_adapter", title="T2I-Adapter", tags=["t2i_adapter", "control"], category="t2i_adapter", version="1.0.1"
|
||||
)
|
||||
class T2IAdapterInvocation(BaseInvocation):
|
||||
"""Collects T2I-Adapter info to pass to other nodes."""
|
||||
@ -61,7 +73,7 @@ class T2IAdapterInvocation(BaseInvocation):
|
||||
default=1, ge=0, description="The weight given to the T2I-Adapter", title="Weight"
|
||||
)
|
||||
begin_step_percent: float = InputField(
|
||||
default=0, ge=-1, le=2, description="When the T2I-Adapter is first applied (% of total steps)"
|
||||
default=0, ge=0, le=1, description="When the T2I-Adapter is first applied (% of total steps)"
|
||||
)
|
||||
end_step_percent: float = InputField(
|
||||
default=1, ge=0, le=1, description="When the T2I-Adapter is last applied (% of total steps)"
|
||||
@ -71,6 +83,17 @@ class T2IAdapterInvocation(BaseInvocation):
|
||||
description="The resize mode applied to the T2I-Adapter input image so that it matches the target output size.",
|
||||
)
|
||||
|
||||
@field_validator("weight")
|
||||
@classmethod
|
||||
def validate_ip_adapter_weight(cls, v):
|
||||
validate_weights(v)
|
||||
return v
|
||||
|
||||
@model_validator(mode="after")
|
||||
def validate_begin_end_step_percent(self):
|
||||
validate_begin_end_step(self.begin_step_percent, self.end_step_percent)
|
||||
return self
|
||||
|
||||
def invoke(self, context: InvocationContext) -> T2IAdapterOutput:
|
||||
return T2IAdapterOutput(
|
||||
t2i_adapter=T2IAdapterField(
|
||||
|
||||
14
invokeai/app/invocations/util.py
Normal file
14
invokeai/app/invocations/util.py
Normal file
@ -0,0 +1,14 @@
|
||||
from typing import Union
|
||||
|
||||
|
||||
def validate_weights(weights: Union[float, list[float]]) -> None:
|
||||
"""Validate that all control weights in the valid range"""
|
||||
to_validate = weights if isinstance(weights, list) else [weights]
|
||||
if any(i < -1 or i > 2 for i in to_validate):
|
||||
raise ValueError("Control weights must be within -1 to 2 range")
|
||||
|
||||
|
||||
def validate_begin_end_step(begin_step_percent: float, end_step_percent: float) -> None:
|
||||
"""Validate that begin_step_percent is less than end_step_percent"""
|
||||
if begin_step_percent >= end_step_percent:
|
||||
raise ValueError("Begin step percent must be less than or equal to end step percent")
|
||||
Loading…
Reference in New Issue
Block a user