mirror of
https://github.com/invoke-ai/InvokeAI
synced 2024-08-30 20:32:17 +00:00
Merge branch 'main' into feat/select-vram-in-config
This commit is contained in:
commit
0fd13d3604
@ -55,7 +55,7 @@ logger = InvokeAILogger.getLogger()
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class ApiDependencies:
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"""Contains and initializes all dependencies for the API"""
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invoker: Optional[Invoker] = None
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invoker: Invoker
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@staticmethod
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def initialize(config: InvokeAIAppConfig, event_handler_id: int, logger: Logger = logger):
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@ -68,8 +68,9 @@ class ApiDependencies:
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output_folder = config.output_path
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# TODO: build a file/path manager?
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db_location = config.db_path
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db_location.parent.mkdir(parents=True, exist_ok=True)
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db_path = config.db_path
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db_path.parent.mkdir(parents=True, exist_ok=True)
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db_location = str(db_path)
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graph_execution_manager = SqliteItemStorage[GraphExecutionState](
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filename=db_location, table_name="graph_executions"
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|
@ -3,6 +3,7 @@
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from typing import Literal, Optional
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import numpy
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import cv2
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from PIL import Image, ImageFilter, ImageOps, ImageChops
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from pydantic import Field
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from pathlib import Path
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@ -650,3 +651,143 @@ class ImageWatermarkInvocation(BaseInvocation, PILInvocationConfig):
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width=image_dto.width,
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height=image_dto.height,
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)
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class ImageHueAdjustmentInvocation(BaseInvocation):
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"""Adjusts the Hue of an image."""
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# fmt: off
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type: Literal["img_hue_adjust"] = "img_hue_adjust"
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# Inputs
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image: ImageField = Field(default=None, description="The image to adjust")
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hue: int = Field(default=0, description="The degrees by which to rotate the hue, 0-360")
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# fmt: on
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def invoke(self, context: InvocationContext) -> ImageOutput:
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pil_image = context.services.images.get_pil_image(self.image.image_name)
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# Convert image to HSV color space
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hsv_image = numpy.array(pil_image.convert("HSV"))
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# Convert hue from 0..360 to 0..256
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hue = int(256 * ((self.hue % 360) / 360))
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# Increment each hue and wrap around at 255
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hsv_image[:, :, 0] = (hsv_image[:, :, 0] + hue) % 256
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# Convert back to PIL format and to original color mode
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pil_image = Image.fromarray(hsv_image, mode="HSV").convert("RGBA")
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image_dto = context.services.images.create(
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image=pil_image,
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image_origin=ResourceOrigin.INTERNAL,
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image_category=ImageCategory.GENERAL,
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node_id=self.id,
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is_intermediate=self.is_intermediate,
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session_id=context.graph_execution_state_id,
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)
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return ImageOutput(
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image=ImageField(
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image_name=image_dto.image_name,
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),
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width=image_dto.width,
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height=image_dto.height,
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)
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class ImageLuminosityAdjustmentInvocation(BaseInvocation):
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"""Adjusts the Luminosity (Value) of an image."""
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# fmt: off
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type: Literal["img_luminosity_adjust"] = "img_luminosity_adjust"
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# Inputs
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image: ImageField = Field(default=None, description="The image to adjust")
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luminosity: float = Field(default=1.0, ge=0, le=1, description="The factor by which to adjust the luminosity (value)")
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# fmt: on
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def invoke(self, context: InvocationContext) -> ImageOutput:
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pil_image = context.services.images.get_pil_image(self.image.image_name)
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# Convert PIL image to OpenCV format (numpy array), note color channel
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# ordering is changed from RGB to BGR
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image = numpy.array(pil_image.convert("RGB"))[:, :, ::-1]
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# Convert image to HSV color space
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hsv_image = cv2.cvtColor(image, cv2.COLOR_BGR2HSV)
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# Adjust the luminosity (value)
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hsv_image[:, :, 2] = numpy.clip(hsv_image[:, :, 2] * self.luminosity, 0, 255)
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# Convert image back to BGR color space
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image = cv2.cvtColor(hsv_image, cv2.COLOR_HSV2BGR)
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# Convert back to PIL format and to original color mode
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pil_image = Image.fromarray(image[:, :, ::-1], "RGB").convert("RGBA")
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image_dto = context.services.images.create(
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image=pil_image,
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image_origin=ResourceOrigin.INTERNAL,
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image_category=ImageCategory.GENERAL,
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node_id=self.id,
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is_intermediate=self.is_intermediate,
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session_id=context.graph_execution_state_id,
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)
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return ImageOutput(
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image=ImageField(
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image_name=image_dto.image_name,
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),
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width=image_dto.width,
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height=image_dto.height,
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)
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class ImageSaturationAdjustmentInvocation(BaseInvocation):
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"""Adjusts the Saturation of an image."""
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# fmt: off
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type: Literal["img_saturation_adjust"] = "img_saturation_adjust"
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# Inputs
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image: ImageField = Field(default=None, description="The image to adjust")
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saturation: float = Field(default=1.0, ge=0, le=1, description="The factor by which to adjust the saturation")
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# fmt: on
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def invoke(self, context: InvocationContext) -> ImageOutput:
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pil_image = context.services.images.get_pil_image(self.image.image_name)
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# Convert PIL image to OpenCV format (numpy array), note color channel
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# ordering is changed from RGB to BGR
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image = numpy.array(pil_image.convert("RGB"))[:, :, ::-1]
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# Convert image to HSV color space
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hsv_image = cv2.cvtColor(image, cv2.COLOR_BGR2HSV)
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# Adjust the saturation
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hsv_image[:, :, 1] = numpy.clip(hsv_image[:, :, 1] * self.saturation, 0, 255)
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# Convert image back to BGR color space
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image = cv2.cvtColor(hsv_image, cv2.COLOR_HSV2BGR)
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# Convert back to PIL format and to original color mode
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pil_image = Image.fromarray(image[:, :, ::-1], "RGB").convert("RGBA")
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image_dto = context.services.images.create(
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image=pil_image,
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image_origin=ResourceOrigin.INTERNAL,
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image_category=ImageCategory.GENERAL,
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node_id=self.id,
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is_intermediate=self.is_intermediate,
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session_id=context.graph_execution_state_id,
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)
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return ImageOutput(
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image=ImageField(
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image_name=image_dto.image_name,
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),
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width=image_dto.width,
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height=image_dto.height,
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)
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|
@ -3,9 +3,10 @@
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from __future__ import annotations
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from abc import ABC, abstractmethod
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from logging import Logger
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from pathlib import Path
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from pydantic import Field
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from typing import Optional, Union, Callable, List, Tuple, TYPE_CHECKING
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from typing import Literal, Optional, Union, Callable, List, Tuple, TYPE_CHECKING
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from types import ModuleType
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from invokeai.backend.model_management import (
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@ -193,7 +194,7 @@ class ModelManagerServiceBase(ABC):
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self,
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model_name: str,
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base_model: BaseModelType,
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model_type: Union[ModelType.Main, ModelType.Vae],
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model_type: Literal[ModelType.Main, ModelType.Vae],
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) -> AddModelResult:
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"""
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Convert a checkpoint file into a diffusers folder, deleting the cached
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@ -292,7 +293,7 @@ class ModelManagerService(ModelManagerServiceBase):
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def __init__(
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self,
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config: InvokeAIAppConfig,
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logger: ModuleType,
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logger: Logger,
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):
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"""
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Initialize with the path to the models.yaml config file.
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@ -396,7 +397,7 @@ class ModelManagerService(ModelManagerServiceBase):
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model_type,
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)
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def model_info(self, model_name: str, base_model: BaseModelType, model_type: ModelType) -> dict:
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def model_info(self, model_name: str, base_model: BaseModelType, model_type: ModelType) -> Union[dict, None]:
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"""
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Given a model name returns a dict-like (OmegaConf) object describing it.
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"""
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@ -416,7 +417,7 @@ class ModelManagerService(ModelManagerServiceBase):
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"""
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return self.mgr.list_models(base_model, model_type)
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def list_model(self, model_name: str, base_model: BaseModelType, model_type: ModelType) -> dict:
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def list_model(self, model_name: str, base_model: BaseModelType, model_type: ModelType) -> Union[dict, None]:
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"""
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Return information about the model using the same format as list_models()
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"""
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@ -429,7 +430,7 @@ class ModelManagerService(ModelManagerServiceBase):
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model_type: ModelType,
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model_attributes: dict,
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clobber: bool = False,
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) -> None:
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) -> AddModelResult:
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"""
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Update the named model with a dictionary of attributes. Will fail with an
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assertion error if the name already exists. Pass clobber=True to overwrite.
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@ -478,7 +479,7 @@ class ModelManagerService(ModelManagerServiceBase):
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self,
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model_name: str,
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base_model: BaseModelType,
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model_type: Union[ModelType.Main, ModelType.Vae],
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model_type: Literal[ModelType.Main, ModelType.Vae],
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convert_dest_directory: Optional[Path] = Field(
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default=None, description="Optional directory location for merged model"
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),
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@ -573,9 +574,9 @@ class ModelManagerService(ModelManagerServiceBase):
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default=None, description="Base model shared by all models to be merged"
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),
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merged_model_name: str = Field(default=None, description="Name of destination model after merging"),
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alpha: Optional[float] = 0.5,
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alpha: float = 0.5,
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interp: Optional[MergeInterpolationMethod] = None,
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force: Optional[bool] = False,
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force: bool = False,
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merge_dest_directory: Optional[Path] = Field(
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default=None, description="Optional directory location for merged model"
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),
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@ -633,8 +634,8 @@ class ModelManagerService(ModelManagerServiceBase):
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model_name: str,
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base_model: BaseModelType,
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model_type: ModelType,
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new_name: str = None,
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new_base: BaseModelType = None,
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new_name: Optional[str] = None,
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new_base: Optional[BaseModelType] = None,
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):
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"""
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Rename the indicated model. Can provide a new name and/or a new base.
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|
@ -18,5 +18,5 @@ SEED_MAX = np.iinfo(np.uint32).max
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def get_random_seed():
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rng = np.random.default_rng(seed=0)
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rng = np.random.default_rng(seed=None)
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return int(rng.integers(0, SEED_MAX))
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|
@ -101,9 +101,9 @@ class ModelInstall(object):
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def __init__(
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self,
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config: InvokeAIAppConfig,
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prediction_type_helper: Callable[[Path], SchedulerPredictionType] = None,
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model_manager: ModelManager = None,
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access_token: str = None,
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prediction_type_helper: Optional[Callable[[Path], SchedulerPredictionType]] = None,
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model_manager: Optional[ModelManager] = None,
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access_token: Optional[str] = None,
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):
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self.config = config
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self.mgr = model_manager or ModelManager(config.model_conf_path)
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|
@ -234,7 +234,7 @@ import textwrap
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import yaml
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from dataclasses import dataclass
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from pathlib import Path
|
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from typing import Optional, List, Tuple, Union, Dict, Set, Callable, types
|
||||
from typing import Literal, Optional, List, Tuple, Union, Dict, Set, Callable, types
|
||||
from shutil import rmtree, move
|
||||
|
||||
import torch
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@ -518,7 +518,7 @@ class ModelManager(object):
|
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model_name: str,
|
||||
base_model: BaseModelType,
|
||||
model_type: ModelType,
|
||||
) -> dict:
|
||||
) -> Union[dict, None]:
|
||||
"""
|
||||
Given a model name returns the OmegaConf (dict-like) object describing it.
|
||||
"""
|
||||
@ -540,13 +540,15 @@ class ModelManager(object):
|
||||
model_name: str,
|
||||
base_model: BaseModelType,
|
||||
model_type: ModelType,
|
||||
) -> dict:
|
||||
) -> Union[dict, None]:
|
||||
"""
|
||||
Returns a dict describing one installed model, using
|
||||
the combined format of the list_models() method.
|
||||
"""
|
||||
models = self.list_models(base_model, model_type, model_name)
|
||||
return models[0] if models else None
|
||||
if len(models) > 1:
|
||||
return models[0]
|
||||
return None
|
||||
|
||||
def list_models(
|
||||
self,
|
||||
@ -560,7 +562,7 @@ class ModelManager(object):
|
||||
|
||||
model_keys = (
|
||||
[self.create_key(model_name, base_model, model_type)]
|
||||
if model_name
|
||||
if model_name and base_model and model_type
|
||||
else sorted(self.models, key=str.casefold)
|
||||
)
|
||||
models = []
|
||||
@ -596,7 +598,7 @@ class ModelManager(object):
|
||||
Print a table of models and their descriptions. This needs to be redone
|
||||
"""
|
||||
# TODO: redo
|
||||
for model_type, model_dict in self.list_models().items():
|
||||
for model_dict in self.list_models():
|
||||
for model_name, model_info in model_dict.items():
|
||||
line = f'{model_info["name"]:25s} {model_info["type"]:10s} {model_info["description"]}'
|
||||
print(line)
|
||||
@ -699,8 +701,8 @@ class ModelManager(object):
|
||||
model_name: str,
|
||||
base_model: BaseModelType,
|
||||
model_type: ModelType,
|
||||
new_name: str = None,
|
||||
new_base: BaseModelType = None,
|
||||
new_name: Optional[str] = None,
|
||||
new_base: Optional[BaseModelType] = None,
|
||||
):
|
||||
"""
|
||||
Rename or rebase a model.
|
||||
@ -753,7 +755,7 @@ class ModelManager(object):
|
||||
self,
|
||||
model_name: str,
|
||||
base_model: BaseModelType,
|
||||
model_type: Union[ModelType.Main, ModelType.Vae],
|
||||
model_type: Literal[ModelType.Main, ModelType.Vae],
|
||||
dest_directory: Optional[Path] = None,
|
||||
) -> AddModelResult:
|
||||
"""
|
||||
@ -767,6 +769,10 @@ class ModelManager(object):
|
||||
This will raise a ValueError unless the model is a checkpoint.
|
||||
"""
|
||||
info = self.model_info(model_name, base_model, model_type)
|
||||
|
||||
if info is None:
|
||||
raise FileNotFoundError(f"model not found: {model_name}")
|
||||
|
||||
if info["model_format"] != "checkpoint":
|
||||
raise ValueError(f"not a checkpoint format model: {model_name}")
|
||||
|
||||
@ -836,7 +842,7 @@ class ModelManager(object):
|
||||
|
||||
return search_folder, found_models
|
||||
|
||||
def commit(self, conf_file: Path = None) -> None:
|
||||
def commit(self, conf_file: Optional[Path] = None) -> None:
|
||||
"""
|
||||
Write current configuration out to the indicated file.
|
||||
"""
|
||||
@ -983,7 +989,7 @@ class ModelManager(object):
|
||||
# LS: hacky
|
||||
# Patch in the SD VAE from core so that it is available for use by the UI
|
||||
try:
|
||||
self.heuristic_import({self.resolve_model_path("core/convert/sd-vae-ft-mse")})
|
||||
self.heuristic_import({str(self.resolve_model_path("core/convert/sd-vae-ft-mse"))})
|
||||
except:
|
||||
pass
|
||||
|
||||
@ -1011,7 +1017,7 @@ class ModelManager(object):
|
||||
def heuristic_import(
|
||||
self,
|
||||
items_to_import: Set[str],
|
||||
prediction_type_helper: Callable[[Path], SchedulerPredictionType] = None,
|
||||
prediction_type_helper: Optional[Callable[[Path], SchedulerPredictionType]] = None,
|
||||
) -> Dict[str, AddModelResult]:
|
||||
"""Import a list of paths, repo_ids or URLs. Returns the set of
|
||||
successfully imported items.
|
||||
|
@ -33,7 +33,7 @@ class ModelMerger(object):
|
||||
self,
|
||||
model_paths: List[Path],
|
||||
alpha: float = 0.5,
|
||||
interp: MergeInterpolationMethod = None,
|
||||
interp: Optional[MergeInterpolationMethod] = None,
|
||||
force: bool = False,
|
||||
**kwargs,
|
||||
) -> DiffusionPipeline:
|
||||
@ -73,7 +73,7 @@ class ModelMerger(object):
|
||||
base_model: Union[BaseModelType, str],
|
||||
merged_model_name: str,
|
||||
alpha: float = 0.5,
|
||||
interp: MergeInterpolationMethod = None,
|
||||
interp: Optional[MergeInterpolationMethod] = None,
|
||||
force: bool = False,
|
||||
merge_dest_directory: Optional[Path] = None,
|
||||
**kwargs,
|
||||
@ -122,7 +122,7 @@ class ModelMerger(object):
|
||||
dump_path.mkdir(parents=True, exist_ok=True)
|
||||
dump_path = dump_path / merged_model_name
|
||||
|
||||
merged_pipe.save_pretrained(dump_path, safe_serialization=1)
|
||||
merged_pipe.save_pretrained(dump_path, safe_serialization=True)
|
||||
attributes = dict(
|
||||
path=str(dump_path),
|
||||
description=f"Merge of models {', '.join(model_names)}",
|
||||
|
@ -1,6 +1,8 @@
|
||||
from __future__ import annotations
|
||||
|
||||
from contextlib import nullcontext
|
||||
from packaging import version
|
||||
import platform
|
||||
|
||||
import torch
|
||||
from torch import autocast
|
||||
@ -30,7 +32,7 @@ def choose_precision(device: torch.device) -> str:
|
||||
device_name = torch.cuda.get_device_name(device)
|
||||
if not ("GeForce GTX 1660" in device_name or "GeForce GTX 1650" in device_name):
|
||||
return "float16"
|
||||
elif device.type == "mps":
|
||||
elif device.type == "mps" and version.parse(platform.mac_ver()[0]) < version.parse("14.0.0"):
|
||||
return "float16"
|
||||
return "float32"
|
||||
|
||||
|
169
invokeai/frontend/web/dist/assets/App-3594329a.js
vendored
Normal file
169
invokeai/frontend/web/dist/assets/App-3594329a.js
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vendored
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@ -1,4 +1,4 @@
|
||||
import{A as m,f$ as Je,z as y,a4 as Ka,g0 as Xa,af as va,aj as d,g1 as b,g2 as t,g3 as Ya,g4 as h,g5 as ua,g6 as Ja,g7 as Qa,aI as Za,g8 as et,ad as rt,g9 as at}from"./index-18f2f740.js";import{s as fa,n as o,t as tt,o as ha,p as ot,q as ma,v as ga,w as ya,x as it,y as Sa,z as pa,A as xr,B as nt,D as lt,E as st,F as xa,G as $a,H as ka,J as dt,K as _a,L as ct,M as bt,N as vt,O as ut,Q as wa,R as ft,S as ht,T as mt,U as gt,V as yt,W as St,e as pt,X as xt}from"./MantineProvider-b20a2267.js";var za=String.raw,Ca=za`
|
||||
import{B as m,g7 as Je,A as y,a5 as Ka,g8 as Xa,af as va,aj as d,g9 as b,ga as t,gb as Ya,gc as h,gd as ua,ge as Ja,gf as Qa,aL as Za,gg as et,ad as rt,gh as at}from"./index-de589048.js";import{s as fa,n as o,t as tt,o as ha,p as ot,q as ma,v as ga,w as ya,x as it,y as Sa,z as pa,A as xr,B as nt,D as lt,E as st,F as xa,G as $a,H as ka,J as dt,K as _a,L as ct,M as bt,N as vt,O as ut,Q as wa,R as ft,S as ht,T as mt,U as gt,V as yt,W as St,e as pt,X as xt}from"./menu-11348abc.js";var za=String.raw,Ca=za`
|
||||
:root,
|
||||
:host {
|
||||
--chakra-vh: 100vh;
|
125
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1
invokeai/frontend/web/dist/assets/menu-11348abc.js
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2
invokeai/frontend/web/dist/index.html
vendored
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vendored
@ -12,7 +12,7 @@
|
||||
margin: 0;
|
||||
}
|
||||
</style>
|
||||
<script type="module" crossorigin src="./assets/index-18f2f740.js"></script>
|
||||
<script type="module" crossorigin src="./assets/index-de589048.js"></script>
|
||||
</head>
|
||||
|
||||
<body dir="ltr">
|
||||
|
3
invokeai/frontend/web/dist/locales/en.json
vendored
3
invokeai/frontend/web/dist/locales/en.json
vendored
@ -124,7 +124,8 @@
|
||||
"deleteImageBin": "Deleted images will be sent to your operating system's Bin.",
|
||||
"deleteImagePermanent": "Deleted images cannot be restored.",
|
||||
"images": "Images",
|
||||
"assets": "Assets"
|
||||
"assets": "Assets",
|
||||
"autoAssignBoardOnClick": "Auto-Assign Board on Click"
|
||||
},
|
||||
"hotkeys": {
|
||||
"keyboardShortcuts": "Keyboard Shortcuts",
|
||||
|
@ -1 +1 @@
|
||||
__version__ = "3.0.1post3"
|
||||
__version__ = "3.0.2a1"
|
||||
|
Loading…
Reference in New Issue
Block a user