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Switching to ControlField for output from controlnet nodes.

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user1
2023-05-04 14:21:11 -07:00
committed by Kent Keirsey
parent 78cd106c23
commit 5e4c0217c7
3 changed files with 75 additions and 22 deletions
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29
invokeai/app/invocations/latent.py
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@ -1,10 +1,10 @@
# Copyright (c) 2023 Kyle Schouviller (https://github.com/kyle0654)
import random
from typing import Literal, Optional, Union
import einops
from pydantic import BaseModel, Field, validator
import torch
from typing import Literal, Optional, Union, List
from diffusers.pipelines.stable_diffusion.pipeline_stable_diffusion_controlnet import MultiControlNetModel
@ -13,6 +13,7 @@ from invokeai.app.models.image import ImageCategory
from invokeai.app.util.misc import SEED_MAX, get_random_seed
from invokeai.app.util.step_callback import stable_diffusion_step_callback
from .controlnet_image_processors import ControlField
from ...backend.model_management.model_manager import ModelManager
from ...backend.util.devices import choose_torch_device, torch_dtype
@ -174,8 +175,7 @@ class TextToLatentsInvocation(BaseInvocation):
# seamless: bool = Field(default=False, description="Whether or not to generate an image that can tile without seams", )
# seamless_axes: str = Field(default="", description="The axes to tile the image on, 'x' and/or 'y'")
progress_images: bool = Field(default=False, description="Whether or not to produce progress images during generation", )
control_model: Optional[str] = Field(default=None, description="The control model to use")
control_image: Optional[ImageField] = Field(default=None, description="The processed control image")
control: Optional[ControlField] = Field(default=None, description="The control to use")
# fmt: on
# Schema customisation
@ -257,21 +257,32 @@ class TextToLatentsInvocation(BaseInvocation):
model = self.get_model(context.services.model_manager)
conditioning_data = self.get_conditioning_data(context, model)
# loading controlnet model
if (self.control_model is None or self.control_model==''):
control_model = None
print("type of control input: ", type(self.control))
if (self.control is None):
control_model_name = None
control_image_field = None
control_weight = None
else:
control_model_name = self.control.control_model
control_image_field = self.control.image
control_weight = self.control.control_weight
# # loading controlnet model
# if (self.control_model is None or self.control_model==''):
# control_model = None
# else:
# FIXME: change this to dropdown menu?
# FIXME: generalize so don't have to hardcode torch_dtype and device
control_model = ControlNetModel.from_pretrained(self.control_model,
control_model = ControlNetModel.from_pretrained(control_model_name,
torch_dtype=torch.float16).to("cuda")
model.control_model = control_model
# loading controlnet image (currently requires pre-processed image)
control_image = (
None if self.control_image is None
None if control_image_field is None
else context.services.images.get(
self.control_image.image_type, self.control_image.image_name
control_image_field.image_type, control_image_field.image_name
)
)