mirror of
https://github.com/invoke-ai/InvokeAI
synced 2024-08-30 20:32:17 +00:00
Merge branch 'main' into lstein/installer-for-new-model-layout
This commit is contained in:
Eugene Brodsky
GitHub
commit
7b97639961
@ -1,7 +1,7 @@
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# InvokeAI nodes for ControlNet image preprocessors
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# initial implementation by Gregg Helt, 2023
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# heavily leverages controlnet_aux package: https://github.com/patrickvonplaten/controlnet_aux
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from builtins import float
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from builtins import float, bool
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import numpy as np
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from typing import Literal, Optional, Union, List
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@ -94,6 +94,7 @@ CONTROLNET_DEFAULT_MODELS = [
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]
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CONTROLNET_NAME_VALUES = Literal[tuple(CONTROLNET_DEFAULT_MODELS)]
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CONTROLNET_MODE_VALUES = Literal[tuple(["balanced", "more_prompt", "more_control", "unbalanced"])]
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class ControlField(BaseModel):
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image: ImageField = Field(default=None, description="The control image")
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@ -104,6 +105,8 @@ class ControlField(BaseModel):
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description="When the ControlNet is first applied (% of total steps)")
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end_step_percent: float = Field(default=1, ge=0, le=1,
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description="When the ControlNet is last applied (% of total steps)")
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control_mode: CONTROLNET_MODE_VALUES = Field(default="balanced", description="The contorl mode to use")
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@validator("control_weight")
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def abs_le_one(cls, v):
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"""validate that all abs(values) are <=1"""
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@ -144,11 +147,11 @@ class ControlNetInvocation(BaseInvocation):
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control_model: CONTROLNET_NAME_VALUES = Field(default="lllyasviel/sd-controlnet-canny",
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description="control model used")
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control_weight: Union[float, List[float]] = Field(default=1.0, description="The weight given to the ControlNet")
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# TODO: add support in backend core for begin_step_percent, end_step_percent, guess_mode
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begin_step_percent: float = Field(default=0, ge=0, le=1,
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description="When the ControlNet is first applied (% of total steps)")
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end_step_percent: float = Field(default=1, ge=0, le=1,
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description="When the ControlNet is last applied (% of total steps)")
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control_mode: CONTROLNET_MODE_VALUES = Field(default="balanced", description="The control mode used")
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# fmt: on
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class Config(InvocationConfig):
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@ -166,7 +169,6 @@ class ControlNetInvocation(BaseInvocation):
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}
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def invoke(self, context: InvocationContext) -> ControlOutput:
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return ControlOutput(
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control=ControlField(
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image=self.image,
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@ -174,6 +176,7 @@ class ControlNetInvocation(BaseInvocation):
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control_weight=self.control_weight,
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begin_step_percent=self.begin_step_percent,
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end_step_percent=self.end_step_percent,
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control_mode=self.control_mode,
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),
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)
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@ -287,19 +287,14 @@ class TextToLatentsInvocation(BaseInvocation):
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control_height_resize = latents_shape[2] * 8
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control_width_resize = latents_shape[3] * 8
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if control_input is None:
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# print("control input is None")
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control_list = None
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elif isinstance(control_input, list) and len(control_input) == 0:
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# print("control input is empty list")
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control_list = None
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elif isinstance(control_input, ControlField):
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# print("control input is ControlField")
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control_list = [control_input]
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elif isinstance(control_input, list) and len(control_input) > 0 and isinstance(control_input[0], ControlField):
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# print("control input is list[ControlField]")
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control_list = control_input
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else:
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# print("input control is unrecognized:", type(self.control))
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control_list = None
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if (control_list is None):
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control_data = None
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@ -341,12 +336,15 @@ class TextToLatentsInvocation(BaseInvocation):
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# num_images_per_prompt=num_images_per_prompt,
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device=control_model.device,
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dtype=control_model.dtype,
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control_mode=control_info.control_mode,
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)
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control_item = ControlNetData(model=control_model,
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image_tensor=control_image,
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weight=control_info.control_weight,
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begin_step_percent=control_info.begin_step_percent,
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end_step_percent=control_info.end_step_percent)
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end_step_percent=control_info.end_step_percent,
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control_mode=control_info.control_mode,
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)
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control_data.append(control_item)
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# MultiControlNetModel has been refactored out, just need list[ControlNetData]
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return control_data
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@ -215,10 +215,12 @@ class GeneratorToCallbackinator(Generic[ParamType, ReturnType, CallbackType]):
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@dataclass
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class ControlNetData:
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model: ControlNetModel = Field(default=None)
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image_tensor: torch.Tensor= Field(default=None)
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weight: Union[float, List[float]]= Field(default=1.0)
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image_tensor: torch.Tensor = Field(default=None)
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weight: Union[float, List[float]] = Field(default=1.0)
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begin_step_percent: float = Field(default=0.0)
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end_step_percent: float = Field(default=1.0)
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control_mode: str = Field(default="balanced")
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@dataclass(frozen=True)
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class ConditioningData:
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@ -599,48 +601,68 @@ class StableDiffusionGeneratorPipeline(StableDiffusionPipeline):
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# TODO: should this scaling happen here or inside self._unet_forward?
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# i.e. before or after passing it to InvokeAIDiffuserComponent
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latent_model_input = self.scheduler.scale_model_input(latents, timestep)
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unet_latent_input = self.scheduler.scale_model_input(latents, timestep)
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# default is no controlnet, so set controlnet processing output to None
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down_block_res_samples, mid_block_res_sample = None, None
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if control_data is not None:
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# FIXME: make sure guidance_scale < 1.0 is handled correctly if doing per-step guidance setting
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# if conditioning_data.guidance_scale > 1.0:
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if conditioning_data.guidance_scale is not None:
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# expand the latents input to control model if doing classifier free guidance
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# (which I think for now is always true, there is conditional elsewhere that stops execution if
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# classifier_free_guidance is <= 1.0 ?)
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latent_control_input = torch.cat([latent_model_input] * 2)
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else:
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latent_control_input = latent_model_input
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# control_data should be type List[ControlNetData]
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# this loop covers both ControlNet (one ControlNetData in list)
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# and MultiControlNet (multiple ControlNetData in list)
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for i, control_datum in enumerate(control_data):
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# print("controlnet", i, "==>", type(control_datum))
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control_mode = control_datum.control_mode
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# soft_injection and cfg_injection are the two ControlNet control_mode booleans
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# that are combined at higher level to make control_mode enum
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# soft_injection determines whether to do per-layer re-weighting adjustment (if True)
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# or default weighting (if False)
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soft_injection = (control_mode == "more_prompt" or control_mode == "more_control")
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# cfg_injection = determines whether to apply ControlNet to only the conditional (if True)
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# or the default both conditional and unconditional (if False)
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cfg_injection = (control_mode == "more_control" or control_mode == "unbalanced")
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first_control_step = math.floor(control_datum.begin_step_percent * total_step_count)
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last_control_step = math.ceil(control_datum.end_step_percent * total_step_count)
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# only apply controlnet if current step is within the controlnet's begin/end step range
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if step_index >= first_control_step and step_index <= last_control_step:
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# print("running controlnet", i, "for step", step_index)
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if cfg_injection:
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control_latent_input = unet_latent_input
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else:
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# expand the latents input to control model if doing classifier free guidance
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# (which I think for now is always true, there is conditional elsewhere that stops execution if
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# classifier_free_guidance is <= 1.0 ?)
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control_latent_input = torch.cat([unet_latent_input] * 2)
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if cfg_injection: # only applying ControlNet to conditional instead of in unconditioned
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encoder_hidden_states = torch.cat([conditioning_data.unconditioned_embeddings])
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else:
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encoder_hidden_states = torch.cat([conditioning_data.unconditioned_embeddings,
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conditioning_data.text_embeddings])
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if isinstance(control_datum.weight, list):
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# if controlnet has multiple weights, use the weight for the current step
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controlnet_weight = control_datum.weight[step_index]
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else:
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# if controlnet has a single weight, use it for all steps
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controlnet_weight = control_datum.weight
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# controlnet(s) inference
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down_samples, mid_sample = control_datum.model(
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sample=latent_control_input,
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sample=control_latent_input,
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timestep=timestep,
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encoder_hidden_states=torch.cat([conditioning_data.unconditioned_embeddings,
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conditioning_data.text_embeddings]),
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encoder_hidden_states=encoder_hidden_states,
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controlnet_cond=control_datum.image_tensor,
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conditioning_scale=controlnet_weight,
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# cross_attention_kwargs,
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guess_mode=False,
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conditioning_scale=controlnet_weight, # controlnet specific, NOT the guidance scale
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guess_mode=soft_injection, # this is still called guess_mode in diffusers ControlNetModel
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return_dict=False,
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)
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if cfg_injection:
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# Inferred ControlNet only for the conditional batch.
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# To apply the output of ControlNet to both the unconditional and conditional batches,
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# add 0 to the unconditional batch to keep it unchanged.
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down_samples = [torch.cat([torch.zeros_like(d), d]) for d in down_samples]
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mid_sample = torch.cat([torch.zeros_like(mid_sample), mid_sample])
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if down_block_res_samples is None and mid_block_res_sample is None:
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down_block_res_samples, mid_block_res_sample = down_samples, mid_sample
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else:
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@ -653,11 +675,11 @@ class StableDiffusionGeneratorPipeline(StableDiffusionPipeline):
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# predict the noise residual
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noise_pred = self.invokeai_diffuser.do_diffusion_step(
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latent_model_input,
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t,
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conditioning_data.unconditioned_embeddings,
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conditioning_data.text_embeddings,
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conditioning_data.guidance_scale,
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x=unet_latent_input,
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sigma=t,
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unconditioning=conditioning_data.unconditioned_embeddings,
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conditioning=conditioning_data.text_embeddings,
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unconditional_guidance_scale=conditioning_data.guidance_scale,
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step_index=step_index,
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total_step_count=total_step_count,
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down_block_additional_residuals=down_block_res_samples, # from controlnet(s)
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@ -962,6 +984,7 @@ class StableDiffusionGeneratorPipeline(StableDiffusionPipeline):
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device="cuda",
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dtype=torch.float16,
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do_classifier_free_guidance=True,
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control_mode="balanced"
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):
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if not isinstance(image, torch.Tensor):
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@ -992,6 +1015,7 @@ class StableDiffusionGeneratorPipeline(StableDiffusionPipeline):
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repeat_by = num_images_per_prompt
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image = image.repeat_interleave(repeat_by, dim=0)
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image = image.to(device=device, dtype=dtype)
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if do_classifier_free_guidance:
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cfg_injection = (control_mode == "more_control" or control_mode == "unbalanced")
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if do_classifier_free_guidance and not cfg_injection:
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image = torch.cat([image] * 2)
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return image
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@ -23,7 +23,7 @@
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"dev": "concurrently \"vite dev\" \"yarn run theme:watch\"",
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"dev:host": "concurrently \"vite dev --host\" \"yarn run theme:watch\"",
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"build": "yarn run lint && vite build",
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"typegen": "npx openapi-typescript http://localhost:9090/openapi.json --output src/services/schema.d.ts -t",
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"typegen": "npx openapi-typescript http://localhost:9090/openapi.json --output src/services/api/schema.d.ts -t",
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"preview": "vite preview",
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"lint:madge": "madge --circular src/main.tsx",
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"lint:eslint": "eslint --max-warnings=0 .",
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@ -55,34 +55,35 @@
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"dependencies": {
|
||||
"@chakra-ui/anatomy": "^2.1.1",
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||||
"@chakra-ui/icons": "^2.0.19",
|
||||
"@chakra-ui/react": "^2.6.0",
|
||||
"@chakra-ui/styled-system": "^2.9.0",
|
||||
"@chakra-ui/theme-tools": "^2.0.16",
|
||||
"@dagrejs/graphlib": "^2.1.12",
|
||||
"@chakra-ui/react": "^2.7.1",
|
||||
"@chakra-ui/styled-system": "^2.9.1",
|
||||
"@chakra-ui/theme-tools": "^2.0.18",
|
||||
"@dagrejs/graphlib": "^2.1.13",
|
||||
"@dnd-kit/core": "^6.0.8",
|
||||
"@dnd-kit/modifiers": "^6.0.1",
|
||||
"@emotion/react": "^11.11.1",
|
||||
"@emotion/styled": "^11.10.6",
|
||||
"@floating-ui/react-dom": "^2.0.0",
|
||||
"@fontsource/inter": "^4.5.15",
|
||||
"@mantine/core": "^6.0.13",
|
||||
"@mantine/hooks": "^6.0.13",
|
||||
"@emotion/styled": "^11.11.0",
|
||||
"@floating-ui/react-dom": "^2.0.1",
|
||||
"@fontsource-variable/inter": "^5.0.3",
|
||||
"@fontsource/inter": "^5.0.3",
|
||||
"@mantine/core": "^6.0.14",
|
||||
"@mantine/hooks": "^6.0.14",
|
||||
"@reduxjs/toolkit": "^1.9.5",
|
||||
"@roarr/browser-log-writer": "^1.1.5",
|
||||
"chakra-ui-contextmenu": "^1.0.5",
|
||||
"dateformat": "^5.0.3",
|
||||
"downshift": "^7.6.0",
|
||||
"formik": "^2.2.9",
|
||||
"framer-motion": "^10.12.4",
|
||||
"formik": "^2.4.2",
|
||||
"framer-motion": "^10.12.17",
|
||||
"fuse.js": "^6.6.2",
|
||||
"i18next": "^22.4.15",
|
||||
"i18next-browser-languagedetector": "^7.0.1",
|
||||
"i18next-http-backend": "^2.2.0",
|
||||
"konva": "^9.0.1",
|
||||
"i18next": "^23.2.3",
|
||||
"i18next-browser-languagedetector": "^7.0.2",
|
||||
"i18next-http-backend": "^2.2.1",
|
||||
"konva": "^9.2.0",
|
||||
"lodash-es": "^4.17.21",
|
||||
"nanostores": "^0.9.2",
|
||||
"openapi-fetch": "^0.4.0",
|
||||
"overlayscrollbars": "^2.1.1",
|
||||
"overlayscrollbars": "^2.2.0",
|
||||
"overlayscrollbars-react": "^0.5.0",
|
||||
"patch-package": "^7.0.0",
|
||||
"query-string": "^8.1.0",
|
||||
@ -92,21 +93,21 @@
|
||||
"react-dom": "^18.2.0",
|
||||
"react-dropzone": "^14.2.3",
|
||||
"react-hotkeys-hook": "4.4.0",
|
||||
"react-i18next": "^12.2.2",
|
||||
"react-icons": "^4.9.0",
|
||||
"react-konva": "^18.2.7",
|
||||
"react-redux": "^8.0.5",
|
||||
"react-resizable-panels": "^0.0.42",
|
||||
"react-i18next": "^13.0.1",
|
||||
"react-icons": "^4.10.1",
|
||||
"react-konva": "^18.2.10",
|
||||
"react-redux": "^8.1.1",
|
||||
"react-resizable-panels": "^0.0.52",
|
||||
"react-use": "^17.4.0",
|
||||
"react-virtuoso": "^4.3.5",
|
||||
"react-zoom-pan-pinch": "^3.0.7",
|
||||
"reactflow": "^11.7.0",
|
||||
"react-virtuoso": "^4.3.11",
|
||||
"react-zoom-pan-pinch": "^3.0.8",
|
||||
"reactflow": "^11.7.4",
|
||||
"redux-dynamic-middlewares": "^2.2.0",
|
||||
"redux-remember": "^3.3.1",
|
||||
"roarr": "^7.15.0",
|
||||
"serialize-error": "^11.0.0",
|
||||
"socket.io-client": "^4.6.0",
|
||||
"use-image": "^1.1.0",
|
||||
"socket.io-client": "^4.7.0",
|
||||
"use-image": "^1.1.1",
|
||||
"uuid": "^9.0.0",
|
||||
"zod": "^3.21.4"
|
||||
},
|
||||
@ -117,22 +118,22 @@
|
||||
"ts-toolbelt": "^9.6.0"
|
||||
},
|
||||
"devDependencies": {
|
||||
"@chakra-ui/cli": "^2.4.0",
|
||||
"@chakra-ui/cli": "^2.4.1",
|
||||
"@types/dateformat": "^5.0.0",
|
||||
"@types/lodash-es": "^4.14.194",
|
||||
"@types/node": "^18.16.2",
|
||||
"@types/react": "^18.2.0",
|
||||
"@types/react-dom": "^18.2.1",
|
||||
"@types/node": "^20.3.1",
|
||||
"@types/react": "^18.2.14",
|
||||
"@types/react-dom": "^18.2.6",
|
||||
"@types/react-redux": "^7.1.25",
|
||||
"@types/react-transition-group": "^4.4.5",
|
||||
"@types/uuid": "^9.0.0",
|
||||
"@typescript-eslint/eslint-plugin": "^5.59.1",
|
||||
"@typescript-eslint/parser": "^5.59.1",
|
||||
"@vitejs/plugin-react-swc": "^3.3.0",
|
||||
"@types/react-transition-group": "^4.4.6",
|
||||
"@types/uuid": "^9.0.2",
|
||||
"@typescript-eslint/eslint-plugin": "^5.60.0",
|
||||
"@typescript-eslint/parser": "^5.60.0",
|
||||
"@vitejs/plugin-react-swc": "^3.3.2",
|
||||
"axios": "^1.4.0",
|
||||
"babel-plugin-transform-imports": "^2.0.0",
|
||||
"concurrently": "^8.0.1",
|
||||
"eslint": "^8.39.0",
|
||||
"concurrently": "^8.2.0",
|
||||
"eslint": "^8.43.0",
|
||||
"eslint-config-prettier": "^8.8.0",
|
||||
"eslint-plugin-prettier": "^4.2.1",
|
||||
"eslint-plugin-react": "^7.32.2",
|
||||
@ -140,16 +141,16 @@
|
||||
"form-data": "^4.0.0",
|
||||
"husky": "^8.0.3",
|
||||
"lint-staged": "^13.2.2",
|
||||
"madge": "^6.0.0",
|
||||
"openapi-types": "^12.1.0",
|
||||
"madge": "^6.1.0",
|
||||
"openapi-types": "^12.1.3",
|
||||
"openapi-typescript": "^6.2.8",
|
||||
"openapi-typescript-codegen": "^0.24.0",
|
||||
"postinstall-postinstall": "^2.1.0",
|
||||
"prettier": "^2.8.8",
|
||||
"rollup-plugin-visualizer": "^5.9.0",
|
||||
"terser": "^5.17.1",
|
||||
"rollup-plugin-visualizer": "^5.9.2",
|
||||
"terser": "^5.18.1",
|
||||
"ts-toolbelt": "^9.6.0",
|
||||
"vite": "^4.3.3",
|
||||
"vite": "^4.3.9",
|
||||
"vite-plugin-css-injected-by-js": "^3.1.1",
|
||||
"vite-plugin-dts": "^2.3.0",
|
||||
"vite-plugin-eslint": "^1.8.1",
|
||||
|
||||
@ -1,14 +0,0 @@
|
||||
diff --git a/node_modules/@chakra-ui/cli/dist/scripts/read-theme-file.worker.js b/node_modules/@chakra-ui/cli/dist/scripts/read-theme-file.worker.js
|
||||
index 937cf0d..7dcc0c0 100644
|
||||
--- a/node_modules/@chakra-ui/cli/dist/scripts/read-theme-file.worker.js
|
||||
+++ b/node_modules/@chakra-ui/cli/dist/scripts/read-theme-file.worker.js
|
||||
@@ -50,7 +50,8 @@ async function readTheme(themeFilePath) {
|
||||
project: tsConfig.configFileAbsolutePath,
|
||||
compilerOptions: {
|
||||
module: "CommonJS",
|
||||
- esModuleInterop: true
|
||||
+ esModuleInterop: true,
|
||||
+ jsx: 'react'
|
||||
},
|
||||
transpileOnly: true,
|
||||
swc: true
|
||||
@ -524,7 +524,8 @@
|
||||
"initialImage": "Initial Image",
|
||||
"showOptionsPanel": "Show Options Panel",
|
||||
"hidePreview": "Hide Preview",
|
||||
"showPreview": "Show Preview"
|
||||
"showPreview": "Show Preview",
|
||||
"controlNetControlMode": "Control Mode"
|
||||
},
|
||||
"settings": {
|
||||
"models": "Models",
|
||||
|
||||
@ -14,7 +14,7 @@ import { invokeAIThemeColors } from 'theme/colors/invokeAI';
|
||||
import { lightThemeColors } from 'theme/colors/lightTheme';
|
||||
import { oceanBlueColors } from 'theme/colors/oceanBlue';
|
||||
|
||||
import '@fontsource/inter/variable.css';
|
||||
import '@fontsource-variable/inter';
|
||||
import { MantineProvider } from '@mantine/core';
|
||||
import { mantineTheme } from 'mantine-theme/theme';
|
||||
import 'overlayscrollbars/overlayscrollbars.css';
|
||||
|
||||
@ -1,26 +1,27 @@
|
||||
import { Box, ChakraProps, Flex } from '@chakra-ui/react';
|
||||
import { useAppDispatch } from 'app/store/storeHooks';
|
||||
import { memo, useCallback } from 'react';
|
||||
import { FaCopy, FaTrash } from 'react-icons/fa';
|
||||
import {
|
||||
ControlNetConfig,
|
||||
controlNetAdded,
|
||||
controlNetRemoved,
|
||||
controlNetToggled,
|
||||
} from '../store/controlNetSlice';
|
||||
import { useAppDispatch } from 'app/store/storeHooks';
|
||||
import ParamControlNetModel from './parameters/ParamControlNetModel';
|
||||
import ParamControlNetWeight from './parameters/ParamControlNetWeight';
|
||||
import { Flex, Box, ChakraProps } from '@chakra-ui/react';
|
||||
import { FaCopy, FaTrash } from 'react-icons/fa';
|
||||
|
||||
import ParamControlNetBeginEnd from './parameters/ParamControlNetBeginEnd';
|
||||
import ControlNetImagePreview from './ControlNetImagePreview';
|
||||
import IAIIconButton from 'common/components/IAIIconButton';
|
||||
import { v4 as uuidv4 } from 'uuid';
|
||||
import { useToggle } from 'react-use';
|
||||
import ParamControlNetProcessorSelect from './parameters/ParamControlNetProcessorSelect';
|
||||
import ControlNetProcessorComponent from './ControlNetProcessorComponent';
|
||||
import IAISwitch from 'common/components/IAISwitch';
|
||||
import { ChevronUpIcon } from '@chakra-ui/icons';
|
||||
import IAIIconButton from 'common/components/IAIIconButton';
|
||||
import IAISwitch from 'common/components/IAISwitch';
|
||||
import { useToggle } from 'react-use';
|
||||
import { v4 as uuidv4 } from 'uuid';
|
||||
import ControlNetImagePreview from './ControlNetImagePreview';
|
||||
import ControlNetProcessorComponent from './ControlNetProcessorComponent';
|
||||
import ParamControlNetShouldAutoConfig from './ParamControlNetShouldAutoConfig';
|
||||
import ParamControlNetBeginEnd from './parameters/ParamControlNetBeginEnd';
|
||||
import ParamControlNetControlMode from './parameters/ParamControlNetControlMode';
|
||||
import ParamControlNetProcessorSelect from './parameters/ParamControlNetProcessorSelect';
|
||||
|
||||
const expandedControlImageSx: ChakraProps['sx'] = { maxH: 96 };
|
||||
|
||||
@ -36,6 +37,7 @@ const ControlNet = (props: ControlNetProps) => {
|
||||
weight,
|
||||
beginStepPct,
|
||||
endStepPct,
|
||||
controlMode,
|
||||
controlImage,
|
||||
processedControlImage,
|
||||
processorNode,
|
||||
@ -137,48 +139,51 @@ const ControlNet = (props: ControlNetProps) => {
|
||||
</Flex>
|
||||
{isEnabled && (
|
||||
<>
|
||||
<Flex sx={{ gap: 4, w: 'full' }}>
|
||||
<Flex
|
||||
sx={{
|
||||
flexDir: 'column',
|
||||
gap: 2,
|
||||
w: 'full',
|
||||
h: isExpanded ? 28 : 24,
|
||||
paddingInlineStart: 1,
|
||||
paddingInlineEnd: isExpanded ? 1 : 0,
|
||||
pb: 2,
|
||||
justifyContent: 'space-between',
|
||||
}}
|
||||
>
|
||||
<ParamControlNetWeight
|
||||
controlNetId={controlNetId}
|
||||
weight={weight}
|
||||
mini={!isExpanded}
|
||||
/>
|
||||
<ParamControlNetBeginEnd
|
||||
controlNetId={controlNetId}
|
||||
beginStepPct={beginStepPct}
|
||||
endStepPct={endStepPct}
|
||||
mini={!isExpanded}
|
||||
/>
|
||||
</Flex>
|
||||
{!isExpanded && (
|
||||
<Flex sx={{ w: 'full', flexDirection: 'column' }}>
|
||||
<Flex sx={{ gap: 4, w: 'full' }}>
|
||||
<Flex
|
||||
sx={{
|
||||
alignItems: 'center',
|
||||
justifyContent: 'center',
|
||||
h: 24,
|
||||
w: 24,
|
||||
aspectRatio: '1/1',
|
||||
flexDir: 'column',
|
||||
gap: 3,
|
||||
w: 'full',
|
||||
paddingInlineStart: 1,
|
||||
paddingInlineEnd: isExpanded ? 1 : 0,
|
||||
pb: 2,
|
||||
justifyContent: 'space-between',
|
||||
}}
|
||||
>
|
||||
<ControlNetImagePreview
|
||||
controlNet={props.controlNet}
|
||||
height={24}
|
||||
<ParamControlNetWeight
|
||||
controlNetId={controlNetId}
|
||||
weight={weight}
|
||||
mini={!isExpanded}
|
||||
/>
|
||||
<ParamControlNetBeginEnd
|
||||
controlNetId={controlNetId}
|
||||
beginStepPct={beginStepPct}
|
||||
endStepPct={endStepPct}
|
||||
mini={!isExpanded}
|
||||
/>
|
||||
</Flex>
|
||||
)}
|
||||
{!isExpanded && (
|
||||
<Flex
|
||||
sx={{
|
||||
alignItems: 'center',
|
||||
justifyContent: 'center',
|
||||
h: 24,
|
||||
w: 24,
|
||||
aspectRatio: '1/1',
|
||||
}}
|
||||
>
|
||||
<ControlNetImagePreview controlNet={props.controlNet} />
|
||||
</Flex>
|
||||
)}
|
||||
</Flex>
|
||||
<ParamControlNetControlMode
|
||||
controlNetId={controlNetId}
|
||||
controlMode={controlMode}
|
||||
/>
|
||||
</Flex>
|
||||
|
||||
{isExpanded && (
|
||||
<>
|
||||
<Box mt={2}>
|
||||
|
||||
@ -0,0 +1,45 @@
|
||||
import { useAppDispatch } from 'app/store/storeHooks';
|
||||
import IAIMantineSelect from 'common/components/IAIMantineSelect';
|
||||
import {
|
||||
ControlModes,
|
||||
controlNetControlModeChanged,
|
||||
} from 'features/controlNet/store/controlNetSlice';
|
||||
import { useCallback } from 'react';
|
||||
import { useTranslation } from 'react-i18next';
|
||||
|
||||
type ParamControlNetControlModeProps = {
|
||||
controlNetId: string;
|
||||
controlMode: string;
|
||||
};
|
||||
|
||||
const CONTROL_MODE_DATA = [
|
||||
{ label: 'Balanced', value: 'balanced' },
|
||||
{ label: 'Prompt', value: 'more_prompt' },
|
||||
{ label: 'Control', value: 'more_control' },
|
||||
{ label: 'Mega Control', value: 'unbalanced' },
|
||||
];
|
||||
|
||||
export default function ParamControlNetControlMode(
|
||||
props: ParamControlNetControlModeProps
|
||||
) {
|
||||
const { controlNetId, controlMode = false } = props;
|
||||
const dispatch = useAppDispatch();
|
||||
|
||||
const { t } = useTranslation();
|
||||
|
||||
const handleControlModeChange = useCallback(
|
||||
(controlMode: ControlModes) => {
|
||||
dispatch(controlNetControlModeChanged({ controlNetId, controlMode }));
|
||||
},
|
||||
[controlNetId, dispatch]
|
||||
);
|
||||
|
||||
return (
|
||||
<IAIMantineSelect
|
||||
label={t('parameters.controlNetControlMode')}
|
||||
data={CONTROL_MODE_DATA}
|
||||
value={String(controlMode)}
|
||||
onChange={handleControlModeChange}
|
||||
/>
|
||||
);
|
||||
}
|
||||
@ -1,6 +1,5 @@
|
||||
import {
|
||||
ControlNetProcessorType,
|
||||
RequiredCannyImageProcessorInvocation,
|
||||
RequiredControlNetProcessorNode,
|
||||
} from './types';
|
||||
|
||||
@ -23,7 +22,7 @@ type ControlNetProcessorsDict = Record<
|
||||
*
|
||||
* TODO: Generate from the OpenAPI schema
|
||||
*/
|
||||
export const CONTROLNET_PROCESSORS = {
|
||||
export const CONTROLNET_PROCESSORS: ControlNetProcessorsDict = {
|
||||
none: {
|
||||
type: 'none',
|
||||
label: 'none',
|
||||
@ -174,6 +173,8 @@ export const CONTROLNET_PROCESSORS = {
|
||||
},
|
||||
};
|
||||
|
||||
type ControlNetModelsDict = Record<string, ControlNetModel>;
|
||||
|
||||
type ControlNetModel = {
|
||||
type: string;
|
||||
label: string;
|
||||
@ -181,7 +182,7 @@ type ControlNetModel = {
|
||||
defaultProcessor?: ControlNetProcessorType;
|
||||
};
|
||||
|
||||
export const CONTROLNET_MODELS = {
|
||||
export const CONTROLNET_MODELS: ControlNetModelsDict = {
|
||||
'lllyasviel/control_v11p_sd15_canny': {
|
||||
type: 'lllyasviel/control_v11p_sd15_canny',
|
||||
label: 'Canny',
|
||||
@ -190,6 +191,7 @@ export const CONTROLNET_MODELS = {
|
||||
'lllyasviel/control_v11p_sd15_inpaint': {
|
||||
type: 'lllyasviel/control_v11p_sd15_inpaint',
|
||||
label: 'Inpaint',
|
||||
defaultProcessor: 'none',
|
||||
},
|
||||
'lllyasviel/control_v11p_sd15_mlsd': {
|
||||
type: 'lllyasviel/control_v11p_sd15_mlsd',
|
||||
@ -209,6 +211,7 @@ export const CONTROLNET_MODELS = {
|
||||
'lllyasviel/control_v11p_sd15_seg': {
|
||||
type: 'lllyasviel/control_v11p_sd15_seg',
|
||||
label: 'Segmentation',
|
||||
defaultProcessor: 'none',
|
||||
},
|
||||
'lllyasviel/control_v11p_sd15_lineart': {
|
||||
type: 'lllyasviel/control_v11p_sd15_lineart',
|
||||
@ -223,6 +226,7 @@ export const CONTROLNET_MODELS = {
|
||||
'lllyasviel/control_v11p_sd15_scribble': {
|
||||
type: 'lllyasviel/control_v11p_sd15_scribble',
|
||||
label: 'Scribble',
|
||||
defaultProcessor: 'none',
|
||||
},
|
||||
'lllyasviel/control_v11p_sd15_softedge': {
|
||||
type: 'lllyasviel/control_v11p_sd15_softedge',
|
||||
@ -242,10 +246,12 @@ export const CONTROLNET_MODELS = {
|
||||
'lllyasviel/control_v11f1e_sd15_tile': {
|
||||
type: 'lllyasviel/control_v11f1e_sd15_tile',
|
||||
label: 'Tile (experimental)',
|
||||
defaultProcessor: 'none',
|
||||
},
|
||||
'lllyasviel/control_v11e_sd15_ip2p': {
|
||||
type: 'lllyasviel/control_v11e_sd15_ip2p',
|
||||
label: 'Pix2Pix (experimental)',
|
||||
defaultProcessor: 'none',
|
||||
},
|
||||
'CrucibleAI/ControlNetMediaPipeFace': {
|
||||
type: 'CrucibleAI/ControlNetMediaPipeFace',
|
||||
|
||||
@ -18,12 +18,19 @@ import { forEach } from 'lodash-es';
|
||||
import { isAnySessionRejected } from 'services/api/thunks/session';
|
||||
import { appSocketInvocationError } from 'services/events/actions';
|
||||
|
||||
export type ControlModes =
|
||||
| 'balanced'
|
||||
| 'more_prompt'
|
||||
| 'more_control'
|
||||
| 'unbalanced';
|
||||
|
||||
export const initialControlNet: Omit<ControlNetConfig, 'controlNetId'> = {
|
||||
isEnabled: true,
|
||||
model: CONTROLNET_MODELS['lllyasviel/control_v11p_sd15_canny'].type,
|
||||
weight: 1,
|
||||
beginStepPct: 0,
|
||||
endStepPct: 1,
|
||||
controlMode: 'balanced',
|
||||
controlImage: null,
|
||||
processedControlImage: null,
|
||||
processorType: 'canny_image_processor',
|
||||
@ -39,6 +46,7 @@ export type ControlNetConfig = {
|
||||
weight: number;
|
||||
beginStepPct: number;
|
||||
endStepPct: number;
|
||||
controlMode: ControlModes;
|
||||
controlImage: string | null;
|
||||
processedControlImage: string | null;
|
||||
processorType: ControlNetProcessorType;
|
||||
@ -181,6 +189,13 @@ export const controlNetSlice = createSlice({
|
||||
const { controlNetId, endStepPct } = action.payload;
|
||||
state.controlNets[controlNetId].endStepPct = endStepPct;
|
||||
},
|
||||
controlNetControlModeChanged: (
|
||||
state,
|
||||
action: PayloadAction<{ controlNetId: string; controlMode: ControlModes }>
|
||||
) => {
|
||||
const { controlNetId, controlMode } = action.payload;
|
||||
state.controlNets[controlNetId].controlMode = controlMode;
|
||||
},
|
||||
controlNetProcessorParamsChanged: (
|
||||
state,
|
||||
action: PayloadAction<{
|
||||
@ -307,6 +322,7 @@ export const {
|
||||
controlNetWeightChanged,
|
||||
controlNetBeginStepPctChanged,
|
||||
controlNetEndStepPctChanged,
|
||||
controlNetControlModeChanged,
|
||||
controlNetProcessorParamsChanged,
|
||||
controlNetProcessorTypeChanged,
|
||||
controlNetReset,
|
||||
|
||||
@ -44,6 +44,7 @@ export const addControlNetToLinearGraph = (
|
||||
processedControlImage,
|
||||
beginStepPct,
|
||||
endStepPct,
|
||||
controlMode,
|
||||
model,
|
||||
processorType,
|
||||
weight,
|
||||
@ -59,6 +60,7 @@ export const addControlNetToLinearGraph = (
|
||||
type: 'controlnet',
|
||||
begin_step_percent: beginStepPct,
|
||||
end_step_percent: endStepPct,
|
||||
control_mode: controlMode,
|
||||
control_model: model as ControlNetInvocation['control_model'],
|
||||
control_weight: weight,
|
||||
};
|
||||
|
||||
@ -17,7 +17,6 @@ import { setActiveTab, togglePanels } from 'features/ui/store/uiSlice';
|
||||
import { memo, MouseEvent, ReactNode, useCallback, useMemo } from 'react';
|
||||
import { useHotkeys } from 'react-hotkeys-hook';
|
||||
import { MdDeviceHub, MdGridOn } from 'react-icons/md';
|
||||
import { GoTextSize } from 'react-icons/go';
|
||||
import {
|
||||
activeTabIndexSelector,
|
||||
activeTabNameSelector,
|
||||
@ -33,7 +32,7 @@ import ImageGalleryContent from 'features/gallery/components/ImageGalleryContent
|
||||
import TextToImageTab from './tabs/TextToImage/TextToImageTab';
|
||||
import UnifiedCanvasTab from './tabs/UnifiedCanvas/UnifiedCanvasTab';
|
||||
import NodesTab from './tabs/Nodes/NodesTab';
|
||||
import { FaImage } from 'react-icons/fa';
|
||||
import { FaFont, FaImage } from 'react-icons/fa';
|
||||
import ResizeHandle from './tabs/ResizeHandle';
|
||||
import ImageTab from './tabs/ImageToImage/ImageToImageTab';
|
||||
import AuxiliaryProgressIndicator from 'app/components/AuxiliaryProgressIndicator';
|
||||
@ -47,7 +46,7 @@ export interface InvokeTabInfo {
|
||||
const tabs: InvokeTabInfo[] = [
|
||||
{
|
||||
id: 'txt2img',
|
||||
icon: <Icon as={GoTextSize} sx={{ boxSize: 6, pointerEvents: 'none' }} />,
|
||||
icon: <Icon as={FaFont} sx={{ boxSize: 6, pointerEvents: 'none' }} />,
|
||||
content: <TextToImageTab />,
|
||||
},
|
||||
{
|
||||
|
||||
@ -0,0 +1,36 @@
|
||||
/* istanbul ignore file */
|
||||
/* tslint:disable */
|
||||
/* eslint-disable */
|
||||
|
||||
import type { ImageField } from './ImageField';
|
||||
|
||||
/**
|
||||
* Applies HED edge detection to image
|
||||
*/
|
||||
export type HedImageProcessorInvocation = {
|
||||
/**
|
||||
* The id of this node. Must be unique among all nodes.
|
||||
*/
|
||||
id: string;
|
||||
/**
|
||||
* Whether or not this node is an intermediate node.
|
||||
*/
|
||||
is_intermediate?: boolean;
|
||||
type?: 'hed_image_processor';
|
||||
/**
|
||||
* The image to process
|
||||
*/
|
||||
image?: ImageField;
|
||||
/**
|
||||
* The pixel resolution for detection
|
||||
*/
|
||||
detect_resolution?: number;
|
||||
/**
|
||||
* The pixel resolution for the output image
|
||||
*/
|
||||
image_resolution?: number;
|
||||
/**
|
||||
* Whether to use scribble mode
|
||||
*/
|
||||
scribble?: boolean;
|
||||
};
|
||||
@ -648,6 +648,13 @@ export type components = {
|
||||
* @default 1
|
||||
*/
|
||||
end_step_percent: number;
|
||||
/**
|
||||
* Control Mode
|
||||
* @description The contorl mode to use
|
||||
* @default balanced
|
||||
* @enum {string}
|
||||
*/
|
||||
control_mode?: "balanced" | "more_prompt" | "more_control" | "unbalanced";
|
||||
};
|
||||
/**
|
||||
* ControlNetInvocation
|
||||
@ -701,6 +708,13 @@ export type components = {
|
||||
* @default 1
|
||||
*/
|
||||
end_step_percent?: number;
|
||||
/**
|
||||
* Control Mode
|
||||
* @description The control mode used
|
||||
* @default balanced
|
||||
* @enum {string}
|
||||
*/
|
||||
control_mode?: "balanced" | "more_prompt" | "more_control" | "unbalanced";
|
||||
};
|
||||
/** ControlNetModelConfig */
|
||||
ControlNetModelConfig: {
|
||||
@ -2903,7 +2917,7 @@ export type components = {
|
||||
/** ModelsList */
|
||||
ModelsList: {
|
||||
/** Models */
|
||||
models: (components["schemas"]["StableDiffusion1ModelCheckpointConfig"] | components["schemas"]["StableDiffusion1ModelDiffusersConfig"] | components["schemas"]["VaeModelConfig"] | components["schemas"]["LoRAModelConfig"] | components["schemas"]["ControlNetModelConfig"] | components["schemas"]["TextualInversionModelConfig"] | components["schemas"]["StableDiffusion2ModelDiffusersConfig"] | components["schemas"]["StableDiffusion2ModelCheckpointConfig"])[];
|
||||
models: (components["schemas"]["StableDiffusion1ModelDiffusersConfig"] | components["schemas"]["StableDiffusion1ModelCheckpointConfig"] | components["schemas"]["VaeModelConfig"] | components["schemas"]["LoRAModelConfig"] | components["schemas"]["ControlNetModelConfig"] | components["schemas"]["TextualInversionModelConfig"] | components["schemas"]["StableDiffusion2ModelCheckpointConfig"] | components["schemas"]["StableDiffusion2ModelDiffusersConfig"])[];
|
||||
};
|
||||
/**
|
||||
* MultiplyInvocation
|
||||
@ -4163,18 +4177,18 @@ export type components = {
|
||||
*/
|
||||
image?: components["schemas"]["ImageField"];
|
||||
};
|
||||
/**
|
||||
* StableDiffusion1ModelFormat
|
||||
* @description An enumeration.
|
||||
* @enum {string}
|
||||
*/
|
||||
StableDiffusion1ModelFormat: "checkpoint" | "diffusers";
|
||||
/**
|
||||
* StableDiffusion2ModelFormat
|
||||
* @description An enumeration.
|
||||
* @enum {string}
|
||||
*/
|
||||
StableDiffusion2ModelFormat: "checkpoint" | "diffusers";
|
||||
/**
|
||||
* StableDiffusion1ModelFormat
|
||||
* @description An enumeration.
|
||||
* @enum {string}
|
||||
*/
|
||||
StableDiffusion1ModelFormat: "checkpoint" | "diffusers";
|
||||
};
|
||||
responses: never;
|
||||
parameters: never;
|
||||
|
||||
@ -1,81 +1,78 @@
|
||||
import { components } from './schema';
|
||||
|
||||
type schemas = components['schemas'];
|
||||
|
||||
/**
|
||||
* Types from the API, re-exported from the types generated by `openapi-typescript`.
|
||||
*/
|
||||
|
||||
// Images
|
||||
export type ImageDTO = components['schemas']['ImageDTO'];
|
||||
export type BoardDTO = components['schemas']['BoardDTO'];
|
||||
export type BoardChanges = components['schemas']['BoardChanges'];
|
||||
export type ImageChanges = components['schemas']['ImageRecordChanges'];
|
||||
export type ImageCategory = components['schemas']['ImageCategory'];
|
||||
export type ResourceOrigin = components['schemas']['ResourceOrigin'];
|
||||
export type ImageField = components['schemas']['ImageField'];
|
||||
export type ImageDTO = schemas['ImageDTO'];
|
||||
export type BoardDTO = schemas['BoardDTO'];
|
||||
export type BoardChanges = schemas['BoardChanges'];
|
||||
export type ImageChanges = schemas['ImageRecordChanges'];
|
||||
export type ImageCategory = schemas['ImageCategory'];
|
||||
export type ResourceOrigin = schemas['ResourceOrigin'];
|
||||
export type ImageField = schemas['ImageField'];
|
||||
export type OffsetPaginatedResults_BoardDTO_ =
|
||||
components['schemas']['OffsetPaginatedResults_BoardDTO_'];
|
||||
schemas['OffsetPaginatedResults_BoardDTO_'];
|
||||
export type OffsetPaginatedResults_ImageDTO_ =
|
||||
components['schemas']['OffsetPaginatedResults_ImageDTO_'];
|
||||
schemas['OffsetPaginatedResults_ImageDTO_'];
|
||||
|
||||
// Models
|
||||
export type ModelType = components['schemas']['ModelType'];
|
||||
export type BaseModelType = components['schemas']['BaseModelType'];
|
||||
export type PipelineModelField = components['schemas']['PipelineModelField'];
|
||||
export type ModelsList = components['schemas']['ModelsList'];
|
||||
export type ModelType = schemas['ModelType'];
|
||||
export type BaseModelType = schemas['BaseModelType'];
|
||||
export type PipelineModelField = schemas['PipelineModelField'];
|
||||
export type ModelsList = schemas['ModelsList'];
|
||||
|
||||
// Graphs
|
||||
export type Graph = components['schemas']['Graph'];
|
||||
export type Edge = components['schemas']['Edge'];
|
||||
export type GraphExecutionState = components['schemas']['GraphExecutionState'];
|
||||
export type Graph = schemas['Graph'];
|
||||
export type Edge = schemas['Edge'];
|
||||
export type GraphExecutionState = schemas['GraphExecutionState'];
|
||||
|
||||
// General nodes
|
||||
export type CollectInvocation = components['schemas']['CollectInvocation'];
|
||||
export type IterateInvocation = components['schemas']['IterateInvocation'];
|
||||
export type RangeInvocation = components['schemas']['RangeInvocation'];
|
||||
export type RandomRangeInvocation =
|
||||
components['schemas']['RandomRangeInvocation'];
|
||||
export type RangeOfSizeInvocation =
|
||||
components['schemas']['RangeOfSizeInvocation'];
|
||||
export type InpaintInvocation = components['schemas']['InpaintInvocation'];
|
||||
export type ImageResizeInvocation =
|
||||
components['schemas']['ImageResizeInvocation'];
|
||||
export type RandomIntInvocation = components['schemas']['RandomIntInvocation'];
|
||||
export type CompelInvocation = components['schemas']['CompelInvocation'];
|
||||
export type CollectInvocation = schemas['CollectInvocation'];
|
||||
export type IterateInvocation = schemas['IterateInvocation'];
|
||||
export type RangeInvocation = schemas['RangeInvocation'];
|
||||
export type RandomRangeInvocation = schemas['RandomRangeInvocation'];
|
||||
export type RangeOfSizeInvocation = schemas['RangeOfSizeInvocation'];
|
||||
export type InpaintInvocation = schemas['InpaintInvocation'];
|
||||
export type ImageResizeInvocation = schemas['ImageResizeInvocation'];
|
||||
export type RandomIntInvocation = schemas['RandomIntInvocation'];
|
||||
export type CompelInvocation = schemas['CompelInvocation'];
|
||||
|
||||
// ControlNet Nodes
|
||||
export type ControlNetInvocation = schemas['ControlNetInvocation'];
|
||||
export type CannyImageProcessorInvocation =
|
||||
components['schemas']['CannyImageProcessorInvocation'];
|
||||
schemas['CannyImageProcessorInvocation'];
|
||||
export type ContentShuffleImageProcessorInvocation =
|
||||
components['schemas']['ContentShuffleImageProcessorInvocation'];
|
||||
schemas['ContentShuffleImageProcessorInvocation'];
|
||||
export type HedImageProcessorInvocation =
|
||||
components['schemas']['HedImageProcessorInvocation'];
|
||||
schemas['HedImageProcessorInvocation'];
|
||||
export type LineartAnimeImageProcessorInvocation =
|
||||
components['schemas']['LineartAnimeImageProcessorInvocation'];
|
||||
schemas['LineartAnimeImageProcessorInvocation'];
|
||||
export type LineartImageProcessorInvocation =
|
||||
components['schemas']['LineartImageProcessorInvocation'];
|
||||
schemas['LineartImageProcessorInvocation'];
|
||||
export type MediapipeFaceProcessorInvocation =
|
||||
components['schemas']['MediapipeFaceProcessorInvocation'];
|
||||
schemas['MediapipeFaceProcessorInvocation'];
|
||||
export type MidasDepthImageProcessorInvocation =
|
||||
components['schemas']['MidasDepthImageProcessorInvocation'];
|
||||
schemas['MidasDepthImageProcessorInvocation'];
|
||||
export type MlsdImageProcessorInvocation =
|
||||
components['schemas']['MlsdImageProcessorInvocation'];
|
||||
schemas['MlsdImageProcessorInvocation'];
|
||||
export type NormalbaeImageProcessorInvocation =
|
||||
components['schemas']['NormalbaeImageProcessorInvocation'];
|
||||
schemas['NormalbaeImageProcessorInvocation'];
|
||||
export type OpenposeImageProcessorInvocation =
|
||||
components['schemas']['OpenposeImageProcessorInvocation'];
|
||||
schemas['OpenposeImageProcessorInvocation'];
|
||||
export type PidiImageProcessorInvocation =
|
||||
components['schemas']['PidiImageProcessorInvocation'];
|
||||
schemas['PidiImageProcessorInvocation'];
|
||||
export type ZoeDepthImageProcessorInvocation =
|
||||
components['schemas']['ZoeDepthImageProcessorInvocation'];
|
||||
schemas['ZoeDepthImageProcessorInvocation'];
|
||||
|
||||
// Node Outputs
|
||||
export type ImageOutput = components['schemas']['ImageOutput'];
|
||||
export type MaskOutput = components['schemas']['MaskOutput'];
|
||||
export type PromptOutput = components['schemas']['PromptOutput'];
|
||||
export type IterateInvocationOutput =
|
||||
components['schemas']['IterateInvocationOutput'];
|
||||
export type CollectInvocationOutput =
|
||||
components['schemas']['CollectInvocationOutput'];
|
||||
export type LatentsOutput = components['schemas']['LatentsOutput'];
|
||||
export type GraphInvocationOutput =
|
||||
components['schemas']['GraphInvocationOutput'];
|
||||
export type ImageOutput = schemas['ImageOutput'];
|
||||
export type MaskOutput = schemas['MaskOutput'];
|
||||
export type PromptOutput = schemas['PromptOutput'];
|
||||
export type IterateInvocationOutput = schemas['IterateInvocationOutput'];
|
||||
export type CollectInvocationOutput = schemas['CollectInvocationOutput'];
|
||||
export type LatentsOutput = schemas['LatentsOutput'];
|
||||
export type GraphInvocationOutput = schemas['GraphInvocationOutput'];
|
||||
|
||||
File diff suppressed because it is too large
Load Diff
Loading…
Reference in New Issue
Block a user