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Merge branch 'main' into enhance/invokeai-logs

Browse Source 
- resolve conflicts
- remove unused code identified by pyflakes
This commit is contained in:
Lincoln Stein 2023-04-28 10:09:46 -04:00
commit 6b79e2b407
427 changed files with 18057 additions and 2831 deletions
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14
.github/CODEOWNERS vendored
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@ -1,16 +1,16 @@
# continuous integration
/.github/workflows/ @mauwii @lstein @blessedcoolant
/.github/workflows/ @lstein @blessedcoolant
# documentation
/docs/ @lstein @mauwii @tildebyte @blessedcoolant
/mkdocs.yml @lstein @mauwii @blessedcoolant
/docs/ @lstein @tildebyte @blessedcoolant
/mkdocs.yml @lstein @blessedcoolant
# nodes
/invokeai/app/ @Kyle0654 @blessedcoolant
# installation and configuration
/pyproject.toml @mauwii @lstein @blessedcoolant
/docker/ @mauwii @lstein @blessedcoolant
/pyproject.toml @lstein @blessedcoolant
/docker/ @lstein @blessedcoolant
/scripts/ @ebr @lstein
/installer/ @lstein @ebr
/invokeai/assets @lstein @ebr
@ -22,11 +22,11 @@
/invokeai/backend @blessedcoolant @psychedelicious @lstein
# generation, model management, postprocessing
/invokeai/backend @keturn @damian0815 @lstein @blessedcoolant @jpphoto
/invokeai/backend @damian0815 @lstein @blessedcoolant @jpphoto @gregghelt2
# front ends
/invokeai/frontend/CLI @lstein
/invokeai/frontend/install @lstein @ebr @mauwii
/invokeai/frontend/install @lstein @ebr
/invokeai/frontend/merge @lstein @blessedcoolant @hipsterusername
/invokeai/frontend/training @lstein @blessedcoolant @hipsterusername
/invokeai/frontend/web @psychedelicious @blessedcoolant

2
.gitignore vendored
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@ -9,6 +9,8 @@ models/ldm/stable-diffusion-v1/model.ckpt
configs/models.user.yaml
config/models.user.yml
invokeai.init
.version
.last_model
# ignore the Anaconda/Miniconda installer used while building Docker image
anaconda.sh

9
README.md
View File

@ -33,6 +33,8 @@
</div>
_**Note: The UI is not fully functional on `main`. If you need a stable UI based on `main`, use the `pre-nodes` tag while we [migrate to a new backend](https://github.com/invoke-ai/InvokeAI/discussions/3246).**_
InvokeAI is a leading creative engine built to empower professionals and enthusiasts alike. Generate and create stunning visual media using the latest AI-driven technologies. InvokeAI offers an industry leading Web Interface, interactive Command Line Interface, and also serves as the foundation for multiple commercial products.
**Quick links**: [[How to Install](https://invoke-ai.github.io/InvokeAI/#installation)] [<a href="https://discord.gg/ZmtBAhwWhy">Discord Server</a>] [<a href="https://invoke-ai.github.io/InvokeAI/">Documentation and Tutorials</a>] [<a href="https://github.com/invoke-ai/InvokeAI/">Code and Downloads</a>] [<a href="https://github.com/invoke-ai/InvokeAI/issues">Bug Reports</a>] [<a href="https://github.com/invoke-ai/InvokeAI/discussions">Discussion, Ideas & Q&A</a>]
@ -84,7 +86,7 @@ installing lots of models.
6. Wait while the installer does its thing. After installing the software,
the installer will launch a script that lets you configure InvokeAI and
select a set of starting image generaiton models.
select a set of starting image generation models.
7. Find the folder that InvokeAI was installed into (it is not the
same as the unpacked zip file directory!) The default location of this
@ -148,6 +150,11 @@ not supported.
pip install InvokeAI --use-pep517 --extra-index-url https://download.pytorch.org/whl/rocm5.4.2
```
_For non-GPU systems:_
```terminal
pip install InvokeAI --use-pep517 --extra-index-url https://download.pytorch.org/whl/cpu
```
_For Macintoshes, either Intel or M1/M2:_
```sh

2
docs/features/NSFW.md
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@ -32,7 +32,7 @@ turned on and off on the command line using `--nsfw_checker` and
At installation time, InvokeAI will ask whether the checker should be
activated by default (neither argument given on the command line). The
response is stored in the InvokeAI initialization file (usually
`.invokeai` in your home directory). You can change the default at any
`invokeai.init` in your home directory). You can change the default at any
time by opening this file in a text editor and commenting or
uncommenting the line `--nsfw_checker`.

15
invokeai/app/api/dependencies.py
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@ -1,21 +1,22 @@
# Copyright (c) 2022 Kyle Schouviller (https://github.com/kyle0654)
import os
from argparse import Namespace
import invokeai.backend.util.logging as log
from ..services.default_graphs import create_system_graphs
from ..services.latent_storage import DiskLatentsStorage, ForwardCacheLatentsStorage
from ...backend import Globals
from ..services.model_manager_initializer import get_model_manager
from ..services.restoration_services import RestorationServices
from ..services.graph import GraphExecutionState
from ..services.graph import GraphExecutionState, LibraryGraph
from ..services.image_storage import DiskImageStorage
from ..services.invocation_queue import MemoryInvocationQueue
from ..services.invocation_services import InvocationServices
from ..services.invoker import Invoker
from ..services.processor import DefaultInvocationProcessor
from ..services.sqlite import SqliteItemStorage
from ..services.metadata import PngMetadataService
from .events import FastAPIEventService
@ -58,7 +59,9 @@ class ApiDependencies:
latents = ForwardCacheLatentsStorage(DiskLatentsStorage(f'{output_folder}/latents'))
images = DiskImageStorage(f'{output_folder}/images')
metadata = PngMetadataService()
images = DiskImageStorage(f'{output_folder}/images', metadata_service=metadata)
# TODO: build a file/path manager?
db_location = os.path.join(output_folder, "invokeai.db")
@ -68,7 +71,11 @@ class ApiDependencies:
events=events,
latents=latents,
images=images,
metadata=metadata,
queue=MemoryInvocationQueue(),
graph_library=SqliteItemStorage[LibraryGraph](
filename=db_location, table_name="graphs"
),
graph_execution_manager=SqliteItemStorage[GraphExecutionState](
filename=db_location, table_name="graph_executions"
),
@ -76,6 +83,8 @@ class ApiDependencies:
restoration=RestorationServices(config),
)
create_system_graphs(services.graph_library)
ApiDependencies.invoker = Invoker(services)
@staticmethod

2
invokeai/app/api/events.py
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@ -45,7 +45,7 @@ class FastAPIEventService(EventServiceBase):
)
except Empty:
await asyncio.sleep(0.001)
await asyncio.sleep(0.1)
pass
except asyncio.CancelledError as e:

30
invokeai/app/api/models/images.py
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@ -1,7 +1,19 @@
from typing import Optional
from pydantic import BaseModel, Field
from invokeai.app.models.image import ImageType
from invokeai.app.models.metadata import ImageMetadata
from invokeai.app.services.metadata import InvokeAIMetadata
class ImageResponseMetadata(BaseModel):
"""An image's metadata. Used only in HTTP responses."""
created: int = Field(description="The creation timestamp of the image")
width: int = Field(description="The width of the image in pixels")
height: int = Field(description="The height of the image in pixels")
invokeai: Optional[InvokeAIMetadata] = Field(
description="The image's InvokeAI-specific metadata"
)
class ImageResponse(BaseModel):
@ -11,4 +23,18 @@ class ImageResponse(BaseModel):
image_name: str = Field(description="The name of the image")
image_url: str = Field(description="The url of the image")
thumbnail_url: str = Field(description="The url of the image's thumbnail")
metadata: ImageMetadata = Field(description="The image's metadata")
metadata: ImageResponseMetadata = Field(description="The image's metadata")
class ProgressImage(BaseModel):
"""The progress image sent intermittently during processing"""
width: int = Field(description="The effective width of the image in pixels")
height: int = Field(description="The effective height of the image in pixels")
dataURL: str = Field(description="The image data as a b64 data URL")
class SavedImage(BaseModel):
image_name: str = Field(description="The name of the saved image")
thumbnail_name: str = Field(description="The name of the saved thumbnail")
created: int = Field(description="The created timestamp of the saved image")

130
invokeai/app/api/routers/images.py
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@ -1,13 +1,19 @@
# Copyright (c) 2022 Kyle Schouviller (https://github.com/kyle0654)
import io
from datetime import datetime, timezone
import json
import os
from typing import Any
import uuid
from fastapi import Path, Query, Request, UploadFile
from fastapi import Body, HTTPException, Path, Query, Request, UploadFile
from fastapi.responses import FileResponse, Response
from fastapi.routing import APIRouter
from PIL import Image
from invokeai.app.api.models.images import ImageResponse
from invokeai.app.api.models.images import (
ImageResponse,
ImageResponseMetadata,
)
from invokeai.app.services.item_storage import PaginatedResults
from ...services.image_storage import ImageType
@ -15,70 +21,128 @@ from ..dependencies import ApiDependencies
images_router = APIRouter(prefix="/v1/images", tags=["images"])
@images_router.get("/{image_type}/{image_name}", operation_id="get_image")
async def get_image(
image_type: ImageType = Path(description="The type of image to get"),
image_name: str = Path(description="The name of the image to get"),
):
"""Gets a result"""
# TODO: This is not really secure at all. At least make sure only output results are served
filename = ApiDependencies.invoker.services.images.get_path(image_type, image_name)
return FileResponse(filename)
) -> FileResponse:
"""Gets an image"""
@images_router.get("/{image_type}/thumbnails/{image_name}", operation_id="get_thumbnail")
path = ApiDependencies.invoker.services.images.get_path(
image_type=image_type, image_name=image_name
)
if ApiDependencies.invoker.services.images.validate_path(path):
return FileResponse(path)
else:
raise HTTPException(status_code=404)
@images_router.delete("/{image_type}/{image_name}", operation_id="delete_image")
async def delete_image(
image_type: ImageType = Path(description="The type of image to delete"),
image_name: str = Path(description="The name of the image to delete"),
) -> None:
"""Deletes an image and its thumbnail"""
ApiDependencies.invoker.services.images.delete(
image_type=image_type, image_name=image_name
)
@images_router.get(
"/{thumbnail_type}/thumbnails/{thumbnail_name}", operation_id="get_thumbnail"
)
async def get_thumbnail(
image_type: ImageType = Path(description="The type of image to get"),
image_name: str = Path(description="The name of the image to get"),
):
thumbnail_type: ImageType = Path(description="The type of thumbnail to get"),
thumbnail_name: str = Path(description="The name of the thumbnail to get"),
) -> FileResponse | Response:
"""Gets a thumbnail"""
# TODO: This is not really secure at all. At least make sure only output results are served
filename = ApiDependencies.invoker.services.images.get_path(image_type, 'thumbnails/' + image_name)
return FileResponse(filename)
path = ApiDependencies.invoker.services.images.get_path(
image_type=thumbnail_type, image_name=thumbnail_name, is_thumbnail=True
)
if ApiDependencies.invoker.services.images.validate_path(path):
return FileResponse(path)
else:
raise HTTPException(status_code=404)
@images_router.post(
"/uploads/",
operation_id="upload_image",
responses={
201: {"description": "The image was uploaded successfully"},
404: {"description": "Session not found"},
201: {
"description": "The image was uploaded successfully",
"model": ImageResponse,
},
415: {"description": "Image upload failed"},
},
status_code=201,
)
async def upload_image(file: UploadFile, request: Request):
async def upload_image(
file: UploadFile, request: Request, response: Response
) -> ImageResponse:
if not file.content_type.startswith("image"):
return Response(status_code=415)
raise HTTPException(status_code=415, detail="Not an image")
contents = await file.read()
try:
im = Image.open(contents)
img = Image.open(io.BytesIO(contents))
except:
# Error opening the image
return Response(status_code=415)
raise HTTPException(status_code=415, detail="Failed to read image")
filename = f"{uuid.uuid4()}_{str(int(datetime.now(timezone.utc).timestamp()))}.png"
ApiDependencies.invoker.services.images.save(ImageType.UPLOAD, filename, im)
return Response(
status_code=201,
headers={
"Location": request.url_for(
"get_image", image_type=ImageType.UPLOAD.value, image_name=filename
)
},
saved_image = ApiDependencies.invoker.services.images.save(
ImageType.UPLOAD, filename, img
)
invokeai_metadata = ApiDependencies.invoker.services.metadata.get_metadata(img)
image_url = ApiDependencies.invoker.services.images.get_uri(
ImageType.UPLOAD, saved_image.image_name
)
thumbnail_url = ApiDependencies.invoker.services.images.get_uri(
ImageType.UPLOAD, saved_image.image_name, True
)
res = ImageResponse(
image_type=ImageType.UPLOAD,
image_name=saved_image.image_name,
image_url=image_url,
thumbnail_url=thumbnail_url,
metadata=ImageResponseMetadata(
created=saved_image.created,
width=img.width,
height=img.height,
invokeai=invokeai_metadata,
),
)
response.status_code = 201
response.headers["Location"] = image_url
return res
@images_router.get(
"/",
operation_id="list_images",
responses={200: {"model": PaginatedResults[ImageResponse]}},
)
async def list_images(
image_type: ImageType = Query(default=ImageType.RESULT, description="The type of images to get"),
image_type: ImageType = Query(
default=ImageType.RESULT, description="The type of images to get"
),
page: int = Query(default=0, description="The page of images to get"),
per_page: int = Query(default=10, description="The number of images per page"),
) -> PaginatedResults[ImageResponse]:
"""Gets a list of images"""
result = ApiDependencies.invoker.services.images.list(
image_type, page, per_page
)
result = ApiDependencies.invoker.services.images.list(image_type, page, per_page)
return result

43
invokeai/app/api/routers/sessions.py
View File

@ -2,8 +2,7 @@
from typing import Annotated, List, Optional, Union
from fastapi import Body, Path, Query
from fastapi.responses import Response
from fastapi import Body, HTTPException, Path, Query, Response
from fastapi.routing import APIRouter
from pydantic.fields import Field
@ -76,7 +75,7 @@ async def get_session(
"""Gets a session"""
session = ApiDependencies.invoker.services.graph_execution_manager.get(session_id)
if session is None:
return Response(status_code=404)
raise HTTPException(status_code=404)
else:
return session
@ -99,7 +98,7 @@ async def add_node(
"""Adds a node to the graph"""
session = ApiDependencies.invoker.services.graph_execution_manager.get(session_id)
if session is None:
return Response(status_code=404)
raise HTTPException(status_code=404)
try:
session.add_node(node)
@ -108,9 +107,9 @@ async def add_node(
) # TODO: can this be done automatically, or add node through an API?
return session.id
except NodeAlreadyExecutedError:
return Response(status_code=400)
raise HTTPException(status_code=400)
except IndexError:
return Response(status_code=400)
raise HTTPException(status_code=400)
@session_router.put(
@ -132,7 +131,7 @@ async def update_node(
"""Updates a node in the graph and removes all linked edges"""
session = ApiDependencies.invoker.services.graph_execution_manager.get(session_id)
if session is None:
return Response(status_code=404)
raise HTTPException(status_code=404)
try:
session.update_node(node_path, node)
@ -141,9 +140,9 @@ async def update_node(
) # TODO: can this be done automatically, or add node through an API?
return session
except NodeAlreadyExecutedError:
return Response(status_code=400)
raise HTTPException(status_code=400)
except IndexError:
return Response(status_code=400)
raise HTTPException(status_code=400)
@session_router.delete(
@ -162,7 +161,7 @@ async def delete_node(
"""Deletes a node in the graph and removes all linked edges"""
session = ApiDependencies.invoker.services.graph_execution_manager.get(session_id)
if session is None:
return Response(status_code=404)
raise HTTPException(status_code=404)
try:
session.delete_node(node_path)
@ -171,9 +170,9 @@ async def delete_node(
) # TODO: can this be done automatically, or add node through an API?
return session
except NodeAlreadyExecutedError:
return Response(status_code=400)
raise HTTPException(status_code=400)
except IndexError:
return Response(status_code=400)
raise HTTPException(status_code=400)
@session_router.post(
@ -192,7 +191,7 @@ async def add_edge(
"""Adds an edge to the graph"""
session = ApiDependencies.invoker.services.graph_execution_manager.get(session_id)
if session is None:
return Response(status_code=404)
raise HTTPException(status_code=404)
try:
session.add_edge(edge)
@ -201,9 +200,9 @@ async def add_edge(
) # TODO: can this be done automatically, or add node through an API?
return session
except NodeAlreadyExecutedError:
return Response(status_code=400)
raise HTTPException(status_code=400)
except IndexError:
return Response(status_code=400)
raise HTTPException(status_code=400)
# TODO: the edge being in the path here is really ugly, find a better solution
@ -226,7 +225,7 @@ async def delete_edge(
"""Deletes an edge from the graph"""
session = ApiDependencies.invoker.services.graph_execution_manager.get(session_id)
if session is None:
return Response(status_code=404)
raise HTTPException(status_code=404)
try:
edge = Edge(
@ -239,9 +238,9 @@ async def delete_edge(
) # TODO: can this be done automatically, or add node through an API?
return session
except NodeAlreadyExecutedError:
return Response(status_code=400)
raise HTTPException(status_code=400)
except IndexError:
return Response(status_code=400)
raise HTTPException(status_code=400)
@session_router.put(
@ -259,14 +258,14 @@ async def invoke_session(
all: bool = Query(
default=False, description="Whether or not to invoke all remaining invocations"
),
) -> None:
) -> Response:
"""Invokes a session"""
session = ApiDependencies.invoker.services.graph_execution_manager.get(session_id)
if session is None:
return Response(status_code=404)
raise HTTPException(status_code=404)
if session.is_complete():
return Response(status_code=400)
raise HTTPException(status_code=400)
ApiDependencies.invoker.invoke(session, invoke_all=all)
return Response(status_code=202)
@ -281,7 +280,7 @@ async def invoke_session(
)
async def cancel_session_invoke(
session_id: str = Path(description="The id of the session to cancel"),
) -> None:
) -> Response:
"""Invokes a session"""
ApiDependencies.invoker.cancel(session_id)
return Response(status_code=202)

98
invokeai/app/cli/commands.py
View File

@ -2,17 +2,46 @@
from abc import ABC, abstractmethod
import argparse
from typing import Any, Callable, Iterable, Literal, get_args, get_origin, get_type_hints
from typing import Any, Callable, Iterable, Literal, Union, get_args, get_origin, get_type_hints
from pydantic import BaseModel, Field
import networkx as nx
import matplotlib.pyplot as plt
import invokeai.backend.util.logging as log
from ..models.image import ImageField
from ..services.graph import GraphExecutionState
from ..invocations.baseinvocation import BaseInvocation
from ..invocations.image import ImageField
from ..services.graph import GraphExecutionState, LibraryGraph, Edge
from ..services.invoker import Invoker
def add_field_argument(command_parser, name: str, field, default_override = None):
default = default_override if default_override is not None else field.default if field.default_factory is None else field.default_factory()
if get_origin(field.type_) == Literal:
allowed_values = get_args(field.type_)
allowed_types = set()
for val in allowed_values:
allowed_types.add(type(val))
allowed_types_list = list(allowed_types)
field_type = allowed_types_list[0] if len(allowed_types) == 1 else Union[allowed_types_list] # type: ignore
command_parser.add_argument(
f"--{name}",
dest=name,
type=field_type,
default=default,
choices=allowed_values,
help=field.field_info.description,
)
else:
command_parser.add_argument(
f"--{name}",
dest=name,
type=field.type_,
default=default,
help=field.field_info.description,
)
def add_parsers(
subparsers,
commands: list[type],
@ -37,30 +66,26 @@ def add_parsers(
if name in exclude_fields:
continue
if get_origin(field.type_) == Literal:
allowed_values = get_args(field.type_)
allowed_types = set()
for val in allowed_values:
allowed_types.add(type(val))
allowed_types_list = list(allowed_types)
field_type = allowed_types_list[0] if len(allowed_types) == 1 else Union[allowed_types_list] # type: ignore
add_field_argument(command_parser, name, field)
command_parser.add_argument(
f"--{name}",
dest=name,
type=field_type,
default=field.default if field.default_factory is None else field.default_factory(),
choices=allowed_values,
help=field.field_info.description,
)
else:
command_parser.add_argument(
f"--{name}",
dest=name,
type=field.type_,
default=field.default if field.default_factory is None else field.default_factory(),
help=field.field_info.description,
)
def add_graph_parsers(
subparsers,
graphs: list[LibraryGraph],
add_arguments: Callable[[argparse.ArgumentParser], None]|None = None
):
for graph in graphs:
command_parser = subparsers.add_parser(graph.name, help=graph.description)
if add_arguments is not None:
add_arguments(command_parser)
# Add arguments for inputs
for exposed_input in graph.exposed_inputs:
node = graph.graph.get_node(exposed_input.node_path)
field = node.__fields__[exposed_input.field]
default_override = getattr(node, exposed_input.field)
add_field_argument(command_parser, exposed_input.alias, field, default_override)
class CliContext:
@ -68,17 +93,38 @@ class CliContext:
session: GraphExecutionState
parser: argparse.ArgumentParser
defaults: dict[str, Any]
graph_nodes: dict[str, str]
nodes_added: list[str]
def __init__(self, invoker: Invoker, session: GraphExecutionState, parser: argparse.ArgumentParser):
self.invoker = invoker
self.session = session
self.parser = parser
self.defaults = dict()
self.graph_nodes = dict()
self.nodes_added = list()
def get_session(self):
self.session = self.invoker.services.graph_execution_manager.get(self.session.id)
return self.session
def reset(self):
self.session = self.invoker.create_execution_state()
self.graph_nodes = dict()
self.nodes_added = list()
# Leave defaults unchanged
def add_node(self, node: BaseInvocation):
self.get_session()
self.session.graph.add_node(node)
self.nodes_added.append(node.id)
self.invoker.services.graph_execution_manager.set(self.session)
def add_edge(self, edge: Edge):
self.get_session()
self.session.add_edge(edge)
self.invoker.services.graph_execution_manager.set(self.session)
class ExitCli(Exception):
"""Exception to exit the CLI"""

148
invokeai/app/cli_app.py
View File

@ -13,18 +13,21 @@ from typing import (
from pydantic import BaseModel
from pydantic.fields import Field
import invokeai.backend.util.logging as log
from invokeai.app.services.metadata import PngMetadataService
from .services.default_graphs import create_system_graphs
from .services.latent_storage import DiskLatentsStorage, ForwardCacheLatentsStorage
from ..backend import Args
from .cli.commands import BaseCommand, CliContext, ExitCli, add_parsers, get_graph_execution_history
from .cli.commands import BaseCommand, CliContext, ExitCli, add_graph_parsers, add_parsers
from .cli.completer import set_autocompleter
from .invocations import *
from .invocations.baseinvocation import BaseInvocation
from .services.events import EventServiceBase
from .services.model_manager_initializer import get_model_manager
from .services.restoration_services import RestorationServices
from .services.graph import Edge, EdgeConnection, GraphExecutionState, are_connection_types_compatible
from .services.graph import Edge, EdgeConnection, GraphExecutionState, GraphInvocation, LibraryGraph, are_connection_types_compatible
from .services.default_graphs import default_text_to_image_graph_id
from .services.image_storage import DiskImageStorage
from .services.invocation_queue import MemoryInvocationQueue
from .services.invocation_services import InvocationServices
@ -59,7 +62,7 @@ def add_invocation_args(command_parser):
)
def get_command_parser() -> argparse.ArgumentParser:
def get_command_parser(services: InvocationServices) -> argparse.ArgumentParser:
# Create invocation parser
parser = argparse.ArgumentParser()
@ -77,20 +80,72 @@ def get_command_parser() -> argparse.ArgumentParser:
commands = BaseCommand.get_all_subclasses()
add_parsers(subparsers, commands, exclude_fields=["type"])
# Create subparsers for exposed CLI graphs
# TODO: add a way to identify these graphs
text_to_image = services.graph_library.get(default_text_to_image_graph_id)
add_graph_parsers(subparsers, [text_to_image], add_arguments=add_invocation_args)
return parser
class NodeField():
alias: str
node_path: str
field: str
field_type: type
def __init__(self, alias: str, node_path: str, field: str, field_type: type):
self.alias = alias
self.node_path = node_path
self.field = field
self.field_type = field_type
def fields_from_type_hints(hints: dict[str, type], node_path: str) -> dict[str,NodeField]:
return {k:NodeField(alias=k, node_path=node_path, field=k, field_type=v) for k, v in hints.items()}
def get_node_input_field(graph: LibraryGraph, field_alias: str, node_id: str) -> NodeField:
"""Gets the node field for the specified field alias"""
exposed_input = next(e for e in graph.exposed_inputs if e.alias == field_alias)
node_type = type(graph.graph.get_node(exposed_input.node_path))
return NodeField(alias=exposed_input.alias, node_path=f'{node_id}.{exposed_input.node_path}', field=exposed_input.field, field_type=get_type_hints(node_type)[exposed_input.field])
def get_node_output_field(graph: LibraryGraph, field_alias: str, node_id: str) -> NodeField:
"""Gets the node field for the specified field alias"""
exposed_output = next(e for e in graph.exposed_outputs if e.alias == field_alias)
node_type = type(graph.graph.get_node(exposed_output.node_path))
node_output_type = node_type.get_output_type()
return NodeField(alias=exposed_output.alias, node_path=f'{node_id}.{exposed_output.node_path}', field=exposed_output.field, field_type=get_type_hints(node_output_type)[exposed_output.field])
def get_node_inputs(invocation: BaseInvocation, context: CliContext) -> dict[str, NodeField]:
"""Gets the inputs for the specified invocation from the context"""
node_type = type(invocation)
if node_type is not GraphInvocation:
return fields_from_type_hints(get_type_hints(node_type), invocation.id)
else:
graph: LibraryGraph = context.invoker.services.graph_library.get(context.graph_nodes[invocation.id])
return {e.alias: get_node_input_field(graph, e.alias, invocation.id) for e in graph.exposed_inputs}
def get_node_outputs(invocation: BaseInvocation, context: CliContext) -> dict[str, NodeField]:
"""Gets the outputs for the specified invocation from the context"""
node_type = type(invocation)
if node_type is not GraphInvocation:
return fields_from_type_hints(get_type_hints(node_type.get_output_type()), invocation.id)
else:
graph: LibraryGraph = context.invoker.services.graph_library.get(context.graph_nodes[invocation.id])
return {e.alias: get_node_output_field(graph, e.alias, invocation.id) for e in graph.exposed_outputs}
def generate_matching_edges(
a: BaseInvocation, b: BaseInvocation
a: BaseInvocation, b: BaseInvocation, context: CliContext
) -> list[Edge]:
"""Generates all possible edges between two invocations"""
atype = type(a)
btype = type(b)
aoutputtype = atype.get_output_type()
afields = get_type_hints(aoutputtype)
bfields = get_type_hints(btype)
afields = get_node_outputs(a, context)
bfields = get_node_inputs(b, context)
matching_fields = set(afields.keys()).intersection(bfields.keys())
@ -99,14 +154,14 @@ def generate_matching_edges(
matching_fields = matching_fields.difference(invalid_fields)
# Validate types
matching_fields = [f for f in matching_fields if are_connection_types_compatible(afields[f], bfields[f])]
matching_fields = [f for f in matching_fields if are_connection_types_compatible(afields[f].field_type, bfields[f].field_type)]
edges = [
Edge(
source=EdgeConnection(node_id=a.id, field=field),
destination=EdgeConnection(node_id=b.id, field=field)
source=EdgeConnection(node_id=afields[alias].node_path, field=afields[alias].field),
destination=EdgeConnection(node_id=bfields[alias].node_path, field=bfields[alias].field)
)
for field in matching_fields
for alias in matching_fields
]
return edges
@ -142,10 +197,12 @@ def invoke_cli():
# Currently nothing is done with the returned Completer
# object, but the object can be used to change autocompletion
# behavior on the fly, if desired.
completer = set_autocompleter(model_manager)
set_autocompleter(model_manager)
events = EventServiceBase()
metadata = PngMetadataService()
output_folder = os.path.abspath(
os.path.join(os.path.dirname(__file__), "../../../outputs")
)
@ -157,8 +214,12 @@ def invoke_cli():
model_manager=model_manager,
events=events,
latents = ForwardCacheLatentsStorage(DiskLatentsStorage(f'{output_folder}/latents')),
images=DiskImageStorage(f'{output_folder}/images'),
images=DiskImageStorage(f'{output_folder}/images', metadata_service=metadata),
metadata=metadata,
queue=MemoryInvocationQueue(),
graph_library=SqliteItemStorage[LibraryGraph](
filename=db_location, table_name="graphs"
),
graph_execution_manager=SqliteItemStorage[GraphExecutionState](
filename=db_location, table_name="graph_executions"
),
@ -166,9 +227,12 @@ def invoke_cli():
restoration=RestorationServices(config),
)
system_graphs = create_system_graphs(services.graph_library)
system_graph_names = set([g.name for g in system_graphs])
invoker = Invoker(services)
session: GraphExecutionState = invoker.create_execution_state()
parser = get_command_parser()
parser = get_command_parser(services)
re_negid = re.compile('^-[0-9]+$')
@ -186,11 +250,12 @@ def invoke_cli():
try:
# Refresh the state of the session
history = list(get_graph_execution_history(context.session))
#history = list(get_graph_execution_history(context.session))
history = list(reversed(context.nodes_added))
# Split the command for piping
cmds = cmd_input.split("|")
start_id = len(history)
start_id = len(context.nodes_added)
current_id = start_id
new_invocations = list()
for cmd in cmds:
@ -206,8 +271,24 @@ def invoke_cli():
args[field_name] = field_default
# Parse invocation
args["id"] = current_id
command = CliCommand(command=args)
command: CliCommand = None # type:ignore
system_graph: LibraryGraph|None = None
if args['type'] in system_graph_names:
system_graph = next(filter(lambda g: g.name == args['type'], system_graphs))
invocation = GraphInvocation(graph=system_graph.graph, id=str(current_id))
for exposed_input in system_graph.exposed_inputs:
if exposed_input.alias in args:
node = invocation.graph.get_node(exposed_input.node_path)
field = exposed_input.field
setattr(node, field, args[exposed_input.alias])
command = CliCommand(command = invocation)
context.graph_nodes[invocation.id] = system_graph.id
else:
args["id"] = current_id
command = CliCommand(command=args)
if command is None:
continue
# Run any CLI commands immediately
if isinstance(command.command, BaseCommand):
@ -218,6 +299,7 @@ def invoke_cli():
command.command.run(context)
continue
# TODO: handle linking with library graphs
# Pipe previous command output (if there was a previous command)
edges: list[Edge] = list()
if len(history) > 0 or current_id != start_id:
@ -230,7 +312,7 @@ def invoke_cli():
else context.session.graph.get_node(from_id)
)
matching_edges = generate_matching_edges(
from_node, command.command
from_node, command.command, context
)
edges.extend(matching_edges)
@ -243,7 +325,7 @@ def invoke_cli():
link_node = context.session.graph.get_node(node_id)
matching_edges = generate_matching_edges(
link_node, command.command
link_node, command.command, context
)
matching_destinations = [e.destination for e in matching_edges]
edges = [e for e in edges if e.destination not in matching_destinations]
@ -257,12 +339,14 @@ def invoke_cli():
if re_negid.match(node_id):
node_id = str(current_id + int(node_id))
# TODO: handle missing input/output
node_output = get_node_outputs(context.session.graph.get_node(node_id), context)[link[1]]
node_input = get_node_inputs(command.command, context)[link[2]]
edges.append(
Edge(
source=EdgeConnection(node_id=node_id, field=link[1]),
destination=EdgeConnection(
node_id=command.command.id, field=link[2]
)
source=EdgeConnection(node_id=node_output.node_path, field=node_output.field),
destination=EdgeConnection(node_id=node_input.node_path, field=node_input.field)
)
)
@ -271,10 +355,10 @@ def invoke_cli():
current_id = current_id + 1
# Add the node to the session
context.session.add_node(command.command)
context.add_node(command.command)
for edge in edges:
print(edge)
context.session.add_edge(edge)
context.add_edge(edge)
# Execute all remaining nodes
invoke_all(context)
@ -286,7 +370,7 @@ def invoke_cli():
except SessionError:
# Start a new session
log.warning("Session error: creating a new session")
context.session = context.invoker.create_execution_state()
context.reset()
except ExitCli:
break

2
invokeai/app/invocations/baseinvocation.py
View File

@ -95,7 +95,7 @@ class UIConfig(TypedDict, total=False):
],
]
tags: List[str]
title: str
class CustomisedSchemaExtra(TypedDict):
ui: UIConfig

32
invokeai/app/invocations/collections.py
View File

@ -1,16 +1,17 @@
# Copyright (c) 2023 Kyle Schouviller (https://github.com/kyle0654)
from typing import Literal
from typing import Literal, Optional
import cv2 as cv
import numpy as np
import numpy.random
from PIL import Image, ImageOps
from pydantic import Field
from ..services.image_storage import ImageType
from .baseinvocation import BaseInvocation, InvocationContext, BaseInvocationOutput
from .image import ImageField, ImageOutput
from .baseinvocation import (
BaseInvocation,
InvocationConfig,
InvocationContext,
BaseInvocationOutput,
)
class IntCollectionOutput(BaseInvocationOutput):
@ -33,7 +34,9 @@ class RangeInvocation(BaseInvocation):
step: int = Field(default=1, description="The step of the range")
def invoke(self, context: InvocationContext) -> IntCollectionOutput:
return IntCollectionOutput(collection=list(range(self.start, self.stop, self.step)))
return IntCollectionOutput(
collection=list(range(self.start, self.stop, self.step))
)
class RandomRangeInvocation(BaseInvocation):
@ -43,8 +46,19 @@ class RandomRangeInvocation(BaseInvocation):
# Inputs
low: int = Field(default=0, description="The inclusive low value")
high: int = Field(default=np.iinfo(np.int32).max, description="The exclusive high value")
high: int = Field(
default=np.iinfo(np.int32).max, description="The exclusive high value"
)
size: int = Field(default=1, description="The number of values to generate")
seed: Optional[int] = Field(
ge=0,
le=np.iinfo(np.int32).max,
description="The seed for the RNG",
default_factory=lambda: numpy.random.randint(0, np.iinfo(np.int32).max),
)
def invoke(self, context: InvocationContext) -> IntCollectionOutput:
return IntCollectionOutput(collection=list(numpy.random.randint(self.low, self.high, size=self.size)))
rng = np.random.default_rng(self.seed)
return IntCollectionOutput(
collection=list(rng.integers(low=self.low, high=self.high, size=self.size))
)

15
invokeai/app/invocations/cv.py
View File

@ -9,7 +9,7 @@ from pydantic import BaseModel, Field
from invokeai.app.models.image import ImageField, ImageType
from .baseinvocation import BaseInvocation, InvocationContext, InvocationConfig
from .image import ImageOutput
from .image import ImageOutput, build_image_output
class CvInvocationConfig(BaseModel):
@ -56,7 +56,14 @@ class CvInpaintInvocation(BaseInvocation, CvInvocationConfig):
image_name = context.services.images.create_name(
context.graph_execution_state_id, self.id
)
context.services.images.save(image_type, image_name, image_inpainted)
return ImageOutput(
image=ImageField(image_type=image_type, image_name=image_name)
metadata = context.services.metadata.build_metadata(
session_id=context.graph_execution_state_id, node=self
)
context.services.images.save(image_type, image_name, image_inpainted, metadata)
return build_image_output(
image_type=image_type,
image_name=image_name,
image=image_inpainted,
)

176
invokeai/app/invocations/generate.py
View File

@ -9,13 +9,12 @@ from torch import Tensor
from pydantic import BaseModel, Field
from invokeai.app.models.image import ImageField, ImageType
from invokeai.app.invocations.util.get_model import choose_model
from invokeai.app.invocations.util.choose_model import choose_model
from .baseinvocation import BaseInvocation, InvocationContext, InvocationConfig
from .image import ImageOutput
from .image import ImageOutput, build_image_output
from ...backend.generator import Txt2Img, Img2Img, Inpaint, InvokeAIGenerator
from ...backend.stable_diffusion import PipelineIntermediateState
from ..models.exceptions import CanceledException
from ..util.step_callback import diffusers_step_callback_adapter
from ..util.step_callback import stable_diffusion_step_callback
SAMPLER_NAME_VALUES = Literal[tuple(InvokeAIGenerator.schedulers())]
@ -58,28 +57,31 @@ class TextToImageInvocation(BaseInvocation, SDImageInvocation):
# TODO: pass this an emitter method or something? or a session for dispatching?
def dispatch_progress(
self, context: InvocationContext, intermediate_state: PipelineIntermediateState
self,
context: InvocationContext,
source_node_id: str,
intermediate_state: PipelineIntermediateState,
) -> None:
if (context.services.queue.is_canceled(context.graph_execution_state_id)):
raise CanceledException
step = intermediate_state.step
if intermediate_state.predicted_original is not None:
# Some schedulers report not only the noisy latents at the current timestep,
# but also their estimate so far of what the de-noised latents will be.
sample = intermediate_state.predicted_original
else:
sample = intermediate_state.latents
diffusers_step_callback_adapter(sample, step, steps=self.steps, id=self.id, context=context)
stable_diffusion_step_callback(
context=context,
intermediate_state=intermediate_state,
node=self.dict(),
source_node_id=source_node_id,
)
def invoke(self, context: InvocationContext) -> ImageOutput:
# Handle invalid model parameter
model = choose_model(context.services.model_manager, self.model)
# Get the source node id (we are invoking the prepared node)
graph_execution_state = context.services.graph_execution_manager.get(
context.graph_execution_state_id
)
source_node_id = graph_execution_state.prepared_source_mapping[self.id]
outputs = Txt2Img(model).generate(
prompt=self.prompt,
step_callback=partial(self.dispatch_progress, context),
step_callback=partial(self.dispatch_progress, context, source_node_id),
**self.dict(
exclude={"prompt"}
), # Shorthand for passing all of the parameters above manually
@ -95,9 +97,18 @@ class TextToImageInvocation(BaseInvocation, SDImageInvocation):
image_name = context.services.images.create_name(
context.graph_execution_state_id, self.id
)
context.services.images.save(image_type, image_name, generate_output.image)
return ImageOutput(
image=ImageField(image_type=image_type, image_name=image_name)
metadata = context.services.metadata.build_metadata(
session_id=context.graph_execution_state_id, node=self
)
context.services.images.save(
image_type, image_name, generate_output.image, metadata
)
return build_image_output(
image_type=image_type,
image_name=image_name,
image=generate_output.image,
)
@ -117,20 +128,17 @@ class ImageToImageInvocation(TextToImageInvocation):
)
def dispatch_progress(
self, context: InvocationContext, intermediate_state: PipelineIntermediateState
) -> None:
if (context.services.queue.is_canceled(context.graph_execution_state_id)):
raise CanceledException
step = intermediate_state.step
if intermediate_state.predicted_original is not None:
# Some schedulers report not only the noisy latents at the current timestep,
# but also their estimate so far of what the de-noised latents will be.
sample = intermediate_state.predicted_original
else:
sample = intermediate_state.latents
diffusers_step_callback_adapter(sample, step, steps=self.steps, id=self.id, context=context)
self,
context: InvocationContext,
source_node_id: str,
intermediate_state: PipelineIntermediateState,
) -> None:
stable_diffusion_step_callback(
context=context,
intermediate_state=intermediate_state,
node=self.dict(),
source_node_id=source_node_id,
)
def invoke(self, context: InvocationContext) -> ImageOutput:
image = (
@ -145,15 +153,21 @@ class ImageToImageInvocation(TextToImageInvocation):
# Handle invalid model parameter
model = choose_model(context.services.model_manager, self.model)
# Get the source node id (we are invoking the prepared node)
graph_execution_state = context.services.graph_execution_manager.get(
context.graph_execution_state_id
)
source_node_id = graph_execution_state.prepared_source_mapping[self.id]
outputs = Img2Img(model).generate(
prompt=self.prompt,
init_image=image,
init_mask=mask,
step_callback=partial(self.dispatch_progress, context),
**self.dict(
exclude={"prompt", "image", "mask"}
), # Shorthand for passing all of the parameters above manually
)
prompt=self.prompt,
init_image=image,
init_mask=mask,
step_callback=partial(self.dispatch_progress, context, source_node_id),
**self.dict(
exclude={"prompt", "image", "mask"}
), # Shorthand for passing all of the parameters above manually
)
# Outputs is an infinite iterator that will return a new InvokeAIGeneratorOutput object
# each time it is called. We only need the first one.
@ -168,11 +182,19 @@ class ImageToImageInvocation(TextToImageInvocation):
image_name = context.services.images.create_name(
context.graph_execution_state_id, self.id
)
context.services.images.save(image_type, image_name, result_image)
return ImageOutput(
image=ImageField(image_type=image_type, image_name=image_name)
metadata = context.services.metadata.build_metadata(
session_id=context.graph_execution_state_id, node=self
)
context.services.images.save(image_type, image_name, result_image, metadata)
return build_image_output(
image_type=image_type,
image_name=image_name,
image=result_image,
)
class InpaintInvocation(ImageToImageInvocation):
"""Generates an image using inpaint."""
@ -188,20 +210,17 @@ class InpaintInvocation(ImageToImageInvocation):
)
def dispatch_progress(
self, context: InvocationContext, intermediate_state: PipelineIntermediateState
) -> None:
if (context.services.queue.is_canceled(context.graph_execution_state_id)):
raise CanceledException
step = intermediate_state.step
if intermediate_state.predicted_original is not None:
# Some schedulers report not only the noisy latents at the current timestep,
# but also their estimate so far of what the de-noised latents will be.
sample = intermediate_state.predicted_original
else:
sample = intermediate_state.latents
diffusers_step_callback_adapter(sample, step, steps=self.steps, id=self.id, context=context)
self,
context: InvocationContext,
source_node_id: str,
intermediate_state: PipelineIntermediateState,
) -> None:
stable_diffusion_step_callback(
context=context,
intermediate_state=intermediate_state,
node=self.dict(),
source_node_id=source_node_id,
)
def invoke(self, context: InvocationContext) -> ImageOutput:
image = (
@ -218,17 +237,23 @@ class InpaintInvocation(ImageToImageInvocation):
)
# Handle invalid model parameter
model = choose_model(context.services.model_manager, self.model)
model = choose_model(context.services.model_manager, self.model)
# Get the source node id (we are invoking the prepared node)
graph_execution_state = context.services.graph_execution_manager.get(
context.graph_execution_state_id
)
source_node_id = graph_execution_state.prepared_source_mapping[self.id]
outputs = Inpaint(model).generate(
prompt=self.prompt,
init_img=image,
init_mask=mask,
step_callback=partial(self.dispatch_progress, context),
**self.dict(
exclude={"prompt", "image", "mask"}
), # Shorthand for passing all of the parameters above manually
)
prompt=self.prompt,
init_img=image,
init_mask=mask,
step_callback=partial(self.dispatch_progress, context, source_node_id),
**self.dict(
exclude={"prompt", "image", "mask"}
), # Shorthand for passing all of the parameters above manually
)
# Outputs is an infinite iterator that will return a new InvokeAIGeneratorOutput object
# each time it is called. We only need the first one.
@ -243,7 +268,14 @@ class InpaintInvocation(ImageToImageInvocation):
image_name = context.services.images.create_name(
context.graph_execution_state_id, self.id
)
context.services.images.save(image_type, image_name, result_image)
return ImageOutput(
image=ImageField(image_type=image_type, image_name=image_name)
metadata = context.services.metadata.build_metadata(
session_id=context.graph_execution_state_id, node=self
)
context.services.images.save(image_type, image_name, result_image, metadata)
return build_image_output(
image_type=image_type,
image_name=image_name,
image=result_image,
)

175
invokeai/app/invocations/image.py
View File

@ -1,6 +1,5 @@
# Copyright (c) 2022 Kyle Schouviller (https://github.com/kyle0654)
from datetime import datetime, timezone
from typing import Literal, Optional
import numpy
@ -8,8 +7,12 @@ from PIL import Image, ImageFilter, ImageOps
from pydantic import BaseModel, Field
from ..models.image import ImageField, ImageType
from ..services.invocation_services import InvocationServices
from .baseinvocation import BaseInvocation, BaseInvocationOutput, InvocationContext, InvocationConfig
from .baseinvocation import (
BaseInvocation,
BaseInvocationOutput,
InvocationContext,
InvocationConfig,
)
class PILInvocationConfig(BaseModel):
@ -22,50 +25,73 @@ class PILInvocationConfig(BaseModel):
},
}
class ImageOutput(BaseInvocationOutput):
"""Base class for invocations that output an image"""
#fmt: off
# fmt: off
type: Literal["image"] = "image"
image: ImageField = Field(default=None, description="The output image")
#fmt: on
width: Optional[int] = Field(default=None, description="The width of the image in pixels")
height: Optional[int] = Field(default=None, description="The height of the image in pixels")
# fmt: on
class Config:
schema_extra = {
'required': [
'type',
'image',
]
"required": ["type", "image", "width", "height", "mode"]
}
def build_image_output(
image_type: ImageType, image_name: str, image: Image.Image
) -> ImageOutput:
"""Builds an ImageOutput and its ImageField"""
image_field = ImageField(
image_name=image_name,
image_type=image_type,
)
return ImageOutput(
image=image_field,
width=image.width,
height=image.height,
mode=image.mode,
)
class MaskOutput(BaseInvocationOutput):
"""Base class for invocations that output a mask"""
#fmt: off
# fmt: off
type: Literal["mask"] = "mask"
mask: ImageField = Field(default=None, description="The output mask")
#fmt: on
# fmt: on
class Config:
schema_extra = {
'required': [
'type',
'mask',
"required": [
"type",
"mask",
]
}
# TODO: this isn't really necessary anymore
class LoadImageInvocation(BaseInvocation):
"""Load an image from a filename and provide it as output."""
#fmt: off
"""Load an image and provide it as output."""
# fmt: off
type: Literal["load_image"] = "load_image"
# Inputs
image_type: ImageType = Field(description="The type of the image")
image_name: str = Field(description="The name of the image")
#fmt: on
# fmt: on
def invoke(self, context: InvocationContext) -> ImageOutput:
return ImageOutput(
image=ImageField(image_type=self.image_type, image_name=self.image_name)
image = context.services.images.get(self.image_type, self.image_name)
return build_image_output(
image_type=self.image_type,
image_name=self.image_name,
image=image,
)
@ -86,16 +112,17 @@ class ShowImageInvocation(BaseInvocation):
# TODO: how to handle failure?
return ImageOutput(
image=ImageField(
image_type=self.image.image_type, image_name=self.image.image_name
)
return build_image_output(
image_type=self.image.image_type,
image_name=self.image.image_name,
image=image,
)
class CropImageInvocation(BaseInvocation, PILInvocationConfig):
"""Crops an image to a specified box. The box can be outside of the image."""
#fmt: off
# fmt: off
type: Literal["crop"] = "crop"
# Inputs
@ -104,7 +131,7 @@ class CropImageInvocation(BaseInvocation, PILInvocationConfig):
y: int = Field(default=0, description="The top y coordinate of the crop rectangle")
width: int = Field(default=512, gt=0, description="The width of the crop rectangle")
height: int = Field(default=512, gt=0, description="The height of the crop rectangle")
#fmt: on
# fmt: on
def invoke(self, context: InvocationContext) -> ImageOutput:
image = context.services.images.get(
@ -120,15 +147,23 @@ class CropImageInvocation(BaseInvocation, PILInvocationConfig):
image_name = context.services.images.create_name(
context.graph_execution_state_id, self.id
)
context.services.images.save(image_type, image_name, image_crop)
return ImageOutput(
image=ImageField(image_type=image_type, image_name=image_name)
metadata = context.services.metadata.build_metadata(
session_id=context.graph_execution_state_id, node=self
)
context.services.images.save(image_type, image_name, image_crop, metadata)
return build_image_output(
image_type=image_type,
image_name=image_name,
image=image_crop,
)
class PasteImageInvocation(BaseInvocation, PILInvocationConfig):
"""Pastes an image into another image."""
#fmt: off
# fmt: off
type: Literal["paste"] = "paste"
# Inputs
@ -137,7 +172,7 @@ class PasteImageInvocation(BaseInvocation, PILInvocationConfig):
mask: Optional[ImageField] = Field(default=None, description="The mask to use when pasting")
x: int = Field(default=0, description="The left x coordinate at which to paste the image")
y: int = Field(default=0, description="The top y coordinate at which to paste the image")
#fmt: on
# fmt: on
def invoke(self, context: InvocationContext) -> ImageOutput:
base_image = context.services.images.get(
@ -170,21 +205,29 @@ class PasteImageInvocation(BaseInvocation, PILInvocationConfig):
image_name = context.services.images.create_name(
context.graph_execution_state_id, self.id
)
context.services.images.save(image_type, image_name, new_image)
return ImageOutput(
image=ImageField(image_type=image_type, image_name=image_name)
metadata = context.services.metadata.build_metadata(
session_id=context.graph_execution_state_id, node=self
)
context.services.images.save(image_type, image_name, new_image, metadata)
return build_image_output(
image_type=image_type,
image_name=image_name,
image=new_image,
)
class MaskFromAlphaInvocation(BaseInvocation, PILInvocationConfig):
"""Extracts the alpha channel of an image as a mask."""
#fmt: off
# fmt: off
type: Literal["tomask"] = "tomask"
# Inputs
image: ImageField = Field(default=None, description="The image to create the mask from")
invert: bool = Field(default=False, description="Whether or not to invert the mask")
#fmt: on
# fmt: on
def invoke(self, context: InvocationContext) -> MaskOutput:
image = context.services.images.get(
@ -199,22 +242,27 @@ class MaskFromAlphaInvocation(BaseInvocation, PILInvocationConfig):
image_name = context.services.images.create_name(
context.graph_execution_state_id, self.id
)
context.services.images.save(image_type, image_name, image_mask)
metadata = context.services.metadata.build_metadata(
session_id=context.graph_execution_state_id, node=self
)
context.services.images.save(image_type, image_name, image_mask, metadata)
return MaskOutput(mask=ImageField(image_type=image_type, image_name=image_name))
class BlurInvocation(BaseInvocation, PILInvocationConfig):
"""Blurs an image"""
#fmt: off
# fmt: off
type: Literal["blur"] = "blur"
# Inputs
image: ImageField = Field(default=None, description="The image to blur")
radius: float = Field(default=8.0, ge=0, description="The blur radius")
blur_type: Literal["gaussian", "box"] = Field(default="gaussian", description="The type of blur")
#fmt: on
# fmt: on
def invoke(self, context: InvocationContext) -> ImageOutput:
image = context.services.images.get(
self.image.image_type, self.image.image_name
@ -231,22 +279,28 @@ class BlurInvocation(BaseInvocation, PILInvocationConfig):
image_name = context.services.images.create_name(
context.graph_execution_state_id, self.id
)
context.services.images.save(image_type, image_name, blur_image)
return ImageOutput(
image=ImageField(image_type=image_type, image_name=image_name)
metadata = context.services.metadata.build_metadata(
session_id=context.graph_execution_state_id, node=self
)
context.services.images.save(image_type, image_name, blur_image, metadata)
return build_image_output(
image_type=image_type, image_name=image_name, image=blur_image
)
class LerpInvocation(BaseInvocation, PILInvocationConfig):
"""Linear interpolation of all pixels of an image"""
#fmt: off
# fmt: off
type: Literal["lerp"] = "lerp"
# Inputs
image: ImageField = Field(default=None, description="The image to lerp")
min: int = Field(default=0, ge=0, le=255, description="The minimum output value")
max: int = Field(default=255, ge=0, le=255, description="The maximum output value")
#fmt: on
# fmt: on
def invoke(self, context: InvocationContext) -> ImageOutput:
image = context.services.images.get(
@ -262,23 +316,29 @@ class LerpInvocation(BaseInvocation, PILInvocationConfig):
image_name = context.services.images.create_name(
context.graph_execution_state_id, self.id
)
context.services.images.save(image_type, image_name, lerp_image)
return ImageOutput(
image=ImageField(image_type=image_type, image_name=image_name)
metadata = context.services.metadata.build_metadata(
session_id=context.graph_execution_state_id, node=self
)
context.services.images.save(image_type, image_name, lerp_image, metadata)
return build_image_output(
image_type=image_type, image_name=image_name, image=lerp_image
)
class InverseLerpInvocation(BaseInvocation, PILInvocationConfig):
"""Inverse linear interpolation of all pixels of an image"""
#fmt: off
# fmt: off
type: Literal["ilerp"] = "ilerp"
# Inputs
image: ImageField = Field(default=None, description="The image to lerp")
min: int = Field(default=0, ge=0, le=255, description="The minimum input value")
max: int = Field(default=255, ge=0, le=255, description="The maximum input value")
#fmt: on
# fmt: on
def invoke(self, context: InvocationContext) -> ImageOutput:
image = context.services.images.get(
self.image.image_type, self.image.image_name
@ -298,7 +358,12 @@ class InverseLerpInvocation(BaseInvocation, PILInvocationConfig):
image_name = context.services.images.create_name(
context.graph_execution_state_id, self.id
)
context.services.images.save(image_type, image_name, ilerp_image)
return ImageOutput(
image=ImageField(image_type=image_type, image_name=image_name)
metadata = context.services.metadata.build_metadata(
session_id=context.graph_execution_state_id, node=self
)
context.services.images.save(image_type, image_name, ilerp_image, metadata)
return build_image_output(
image_type=image_type, image_name=image_name, image=ilerp_image
)

137
invokeai/app/invocations/latent.py
View File

@ -1,12 +1,13 @@
# Copyright (c) 2023 Kyle Schouviller (https://github.com/kyle0654)
import random
from typing import Literal, Optional
from pydantic import BaseModel, Field
import torch
from invokeai.app.models.exceptions import CanceledException
from invokeai.app.invocations.util.get_model import choose_model
from invokeai.app.util.step_callback import diffusers_step_callback_adapter
from invokeai.app.invocations.util.choose_model import choose_model
from invokeai.app.util.step_callback import stable_diffusion_step_callback
from ...backend.model_management.model_manager import ModelManager
from ...backend.util.devices import choose_torch_device, torch_dtype
@ -18,7 +19,7 @@ from .baseinvocation import BaseInvocation, BaseInvocationOutput, InvocationCont
import numpy as np
from ..services.image_storage import ImageType
from .baseinvocation import BaseInvocation, InvocationContext
from .image import ImageField, ImageOutput
from .image import ImageField, ImageOutput, build_image_output
from ...backend.stable_diffusion import PipelineIntermediateState
from diffusers.schedulers import SchedulerMixin as Scheduler
import diffusers
@ -30,6 +31,8 @@ class LatentsField(BaseModel):
latents_name: Optional[str] = Field(default=None, description="The name of the latents")
class Config:
schema_extra = {"required": ["latents_name"]}
class LatentsOutput(BaseInvocationOutput):
"""Base class for invocations that output latents"""
@ -99,13 +102,17 @@ def get_noise(width:int, height:int, device:torch.device, seed:int = 0, latent_c
return x
def random_seed():
return random.randint(0, np.iinfo(np.uint32).max)
class NoiseInvocation(BaseInvocation):
"""Generates latent noise."""
type: Literal["noise"] = "noise"
# Inputs
seed: int = Field(default=0, ge=0, le=np.iinfo(np.uint32).max, description="The seed to use", )
seed: int = Field(ge=0, le=np.iinfo(np.uint32).max, description="The seed to use", default_factory=random_seed)
width: int = Field(default=512, multiple_of=64, gt=0, description="The width of the resulting noise", )
height: int = Field(default=512, multiple_of=64, gt=0, description="The height of the resulting noise", )
@ -139,11 +146,8 @@ class TextToLatentsInvocation(BaseInvocation):
# TODO: consider making prompt optional to enable providing prompt through a link
# fmt: off
prompt: Optional[str] = Field(description="The prompt to generate an image from")
seed: int = Field(default=-1,ge=-1, le=np.iinfo(np.uint32).max, description="The seed to use (-1 for a random seed)", )
noise: Optional[LatentsField] = Field(description="The noise to use")
steps: int = Field(default=10, gt=0, description="The number of steps to use to generate the image")
width: int = Field(default=512, multiple_of=64, gt=0, description="The width of the resulting image", )
height: int = Field(default=512, multiple_of=64, gt=0, description="The height of the resulting image", )
cfg_scale: float = Field(default=7.5, gt=0, description="The Classifier-Free Guidance, higher values may result in a result closer to the prompt", )
scheduler: SAMPLER_NAME_VALUES = Field(default="k_lms", description="The scheduler to use" )
seamless: bool = Field(default=False, description="Whether or not to generate an image that can tile without seams", )
@ -165,22 +169,15 @@ class TextToLatentsInvocation(BaseInvocation):
# TODO: pass this an emitter method or something? or a session for dispatching?
def dispatch_progress(
self, context: InvocationContext, intermediate_state: PipelineIntermediateState
) -> None:
if (context.services.queue.is_canceled(context.graph_execution_state_id)):
raise CanceledException
self, context: InvocationContext, source_node_id: str, intermediate_state: PipelineIntermediateState
) -> None:
stable_diffusion_step_callback(
context=context,
intermediate_state=intermediate_state,
node=self.dict(),
source_node_id=source_node_id,
)
step = intermediate_state.step
if intermediate_state.predicted_original is not None:
# Some schedulers report not only the noisy latents at the current timestep,
# but also their estimate so far of what the de-noised latents will be.
sample = intermediate_state.predicted_original
else:
sample = intermediate_state.latents
diffusers_step_callback_adapter(sample, step, steps=self.steps, id=self.id, context=context)
def get_model(self, model_manager: ModelManager) -> StableDiffusionGeneratorPipeline:
model_info = choose_model(model_manager, self.model)
model_name = model_info['model_name']
@ -190,7 +187,7 @@ class TextToLatentsInvocation(BaseInvocation):
model=model,
scheduler_name=self.scheduler
)
if isinstance(model, DiffusionPipeline):
for component in [model.unet, model.vae]:
configure_model_padding(component,
@ -226,8 +223,12 @@ class TextToLatentsInvocation(BaseInvocation):
def invoke(self, context: InvocationContext) -> LatentsOutput:
noise = context.services.latents.get(self.noise.latents_name)
# Get the source node id (we are invoking the prepared node)
graph_execution_state = context.services.graph_execution_manager.get(context.graph_execution_state_id)
source_node_id = graph_execution_state.prepared_source_mapping[self.id]
def step_callback(state: PipelineIntermediateState):
self.dispatch_progress(context, state)
self.dispatch_progress(context, source_node_id, state)
model = self.get_model(context.services.model_manager)
conditioning_data = self.get_conditioning_data(model)
@ -276,8 +277,12 @@ class LatentsToLatentsInvocation(TextToLatentsInvocation):
noise = context.services.latents.get(self.noise.latents_name)
latent = context.services.latents.get(self.latents.latents_name)
# Get the source node id (we are invoking the prepared node)
graph_execution_state = context.services.graph_execution_manager.get(context.graph_execution_state_id)
source_node_id = graph_execution_state.prepared_source_mapping[self.id]
def step_callback(state: PipelineIntermediateState):
self.dispatch_progress(context, state)
self.dispatch_progress(context, source_node_id, state)
model = self.get_model(context.services.model_manager)
conditioning_data = self.get_conditioning_data(model)
@ -287,7 +292,7 @@ class LatentsToLatentsInvocation(TextToLatentsInvocation):
initial_latents = latent if self.strength < 1.0 else torch.zeros_like(
latent, device=model.device, dtype=latent.dtype
)
timesteps, _ = model.get_img2img_timesteps(
self.steps,
self.strength,
@ -350,7 +355,79 @@ class LatentsToImageInvocation(BaseInvocation):
image_name = context.services.images.create_name(
context.graph_execution_state_id, self.id
)
context.services.images.save(image_type, image_name, image)
return ImageOutput(
image=ImageField(image_type=image_type, image_name=image_name)
metadata = context.services.metadata.build_metadata(
session_id=context.graph_execution_state_id, node=self
)
torch.cuda.empty_cache()
context.services.images.save(image_type, image_name, image, metadata)
return build_image_output(
image_type=image_type, image_name=image_name, image=image
)
LATENTS_INTERPOLATION_MODE = Literal[
"nearest", "linear", "bilinear", "bicubic", "trilinear", "area", "nearest-exact"
]
class ResizeLatentsInvocation(BaseInvocation):
"""Resizes latents to explicit width/height (in pixels). Provided dimensions are floor-divided by 8."""
type: Literal["lresize"] = "lresize"
# Inputs
latents: Optional[LatentsField] = Field(description="The latents to resize")
width: int = Field(ge=64, multiple_of=8, description="The width to resize to (px)")
height: int = Field(ge=64, multiple_of=8, description="The height to resize to (px)")
mode: Optional[LATENTS_INTERPOLATION_MODE] = Field(default="bilinear", description="The interpolation mode")
antialias: Optional[bool] = Field(default=False, description="Whether or not to antialias (applied in bilinear and bicubic modes only)")
def invoke(self, context: InvocationContext) -> LatentsOutput:
latents = context.services.latents.get(self.latents.latents_name)
resized_latents = torch.nn.functional.interpolate(
latents,
size=(self.height // 8, self.width // 8),
mode=self.mode,
antialias=self.antialias if self.mode in ["bilinear", "bicubic"] else False,
)
# https://discuss.huggingface.co/t/memory-usage-by-later-pipeline-stages/23699
torch.cuda.empty_cache()
name = f"{context.graph_execution_state_id}__{self.id}"
context.services.latents.set(name, resized_latents)
return LatentsOutput(latents=LatentsField(latents_name=name))
class ScaleLatentsInvocation(BaseInvocation):
"""Scales latents by a given factor."""
type: Literal["lscale"] = "lscale"
# Inputs
latents: Optional[LatentsField] = Field(description="The latents to scale")
scale_factor: float = Field(gt=0, description="The factor by which to scale the latents")
mode: Optional[LATENTS_INTERPOLATION_MODE] = Field(default="bilinear", description="The interpolation mode")
antialias: Optional[bool] = Field(default=False, description="Whether or not to antialias (applied in bilinear and bicubic modes only)")
def invoke(self, context: InvocationContext) -> LatentsOutput:
latents = context.services.latents.get(self.latents.latents_name)
# resizing
resized_latents = torch.nn.functional.interpolate(
latents,
scale_factor=self.scale_factor,
mode=self.mode,
antialias=self.antialias if self.mode in ["bilinear", "bicubic"] else False,
)
# https://discuss.huggingface.co/t/memory-usage-by-later-pipeline-stages/23699
torch.cuda.empty_cache()
name = f"{context.graph_execution_state_id}__{self.id}"
context.services.latents.set(name, resized_latents)
return LatentsOutput(latents=LatentsField(latents_name=name))

18
invokeai/app/invocations/params.py Normal file
View File

@ -0,0 +1,18 @@
# Copyright (c) 2023 Kyle Schouviller (https://github.com/kyle0654)
from typing import Literal
from pydantic import Field
from .baseinvocation import BaseInvocation, BaseInvocationOutput, InvocationContext
from .math import IntOutput
# Pass-through parameter nodes - used by subgraphs
class ParamIntInvocation(BaseInvocation):
"""An integer parameter"""
#fmt: off
type: Literal["param_int"] = "param_int"
a: int = Field(default=0, description="The integer value")
#fmt: on
def invoke(self, context: InvocationContext) -> IntOutput:
return IntOutput(a=self.a)

18
invokeai/app/invocations/reconstruct.py
View File

@ -1,12 +1,11 @@
from datetime import datetime, timezone
from typing import Literal, Union
from pydantic import Field
from invokeai.app.models.image import ImageField, ImageType
from ..services.invocation_services import InvocationServices
from .baseinvocation import BaseInvocation, InvocationContext, InvocationConfig
from .image import ImageOutput
from .image import ImageOutput, build_image_output
class RestoreFaceInvocation(BaseInvocation):
"""Restores faces in an image."""
@ -44,7 +43,14 @@ class RestoreFaceInvocation(BaseInvocation):
image_name = context.services.images.create_name(
context.graph_execution_state_id, self.id
)
context.services.images.save(image_type, image_name, results[0][0])
return ImageOutput(
image=ImageField(image_type=image_type, image_name=image_name)
metadata = context.services.metadata.build_metadata(
session_id=context.graph_execution_state_id, node=self
)
context.services.images.save(image_type, image_name, results[0][0], metadata)
return build_image_output(
image_type=image_type,
image_name=image_name,
image=results[0][0]
)

17
invokeai/app/invocations/upscale.py
View File

@ -1,14 +1,12 @@
# Copyright (c) 2022 Kyle Schouviller (https://github.com/kyle0654)
from datetime import datetime, timezone
from typing import Literal, Union
from pydantic import Field
from invokeai.app.models.image import ImageField, ImageType
from ..services.invocation_services import InvocationServices
from .baseinvocation import BaseInvocation, InvocationContext, InvocationConfig
from .image import ImageOutput
from .image import ImageOutput, build_image_output
class UpscaleInvocation(BaseInvocation):
@ -49,7 +47,14 @@ class UpscaleInvocation(BaseInvocation):
image_name = context.services.images.create_name(
context.graph_execution_state_id, self.id
)
context.services.images.save(image_type, image_name, results[0][0])
return ImageOutput(
image=ImageField(image_type=image_type, image_name=image_name)
metadata = context.services.metadata.build_metadata(
session_id=context.graph_execution_state_id, node=self
)
context.services.images.save(image_type, image_name, results[0][0], metadata)
return build_image_output(
image_type=image_type,
image_name=image_name,
image=results[0][0]
)

9
invokeai/app/invocations/util/get_model.py → invokeai/app/invocations/util/choose_model.py
View File

@ -1,12 +1,13 @@
import invokeai.backend.util.logging as log
from invokeai.app.invocations.baseinvocation import InvocationContext
from invokeai.backend.model_management.model_manager import ModelManager
def choose_model(model_manager: ModelManager, model_name: str):
"""Returns the default model if the `model_name` not a valid model, else returns the selected model."""
if model_manager.valid_model(model_name):
return model_manager.get_model(model_name)
model = model_manager.get_model(model_name)
else:
log.warning(f"'{model_name}' is not a valid model name. Using default model instead.")
return model_manager.get_model()
model = model_manager.get_model()
log.warning(f"{model_name}' is not a valid model name. Using default model \'{model['model_name']}\' instead.")
return model

15
invokeai/app/models/image.py
View File

@ -9,6 +9,14 @@ class ImageType(str, Enum):
UPLOAD = "uploads"
def is_image_type(obj):
try:
ImageType(obj)
except ValueError:
return False
return True
class ImageField(BaseModel):
"""An image field used for passing image objects between invocations"""
@ -18,9 +26,4 @@ class ImageField(BaseModel):
image_name: Optional[str] = Field(default=None, description="The name of the image")
class Config:
schema_extra = {
"required": [
"image_type",
"image_name",
]
}
schema_extra = {"required": ["image_type", "image_name"]}

11
invokeai/app/models/metadata.py
View File

@ -1,11 +0,0 @@
from typing import Optional
from pydantic import BaseModel, Field
class ImageMetadata(BaseModel):
"""An image's metadata"""
timestamp: float = Field(description="The creation timestamp of the image")
width: int = Field(description="The width of the image in pixels")
height: int = Field(description="The height of the image in pixels")
# TODO: figure out metadata
sd_metadata: Optional[dict] = Field(default={}, description="The image's SD-specific metadata")

56
invokeai/app/services/default_graphs.py Normal file
View File

@ -0,0 +1,56 @@
from ..invocations.latent import LatentsToImageInvocation, NoiseInvocation, TextToLatentsInvocation
from ..invocations.params import ParamIntInvocation
from .graph import Edge, EdgeConnection, ExposedNodeInput, ExposedNodeOutput, Graph, LibraryGraph
from .item_storage import ItemStorageABC
default_text_to_image_graph_id = '539b2af5-2b4d-4d8c-8071-e54a3255fc74'
def create_text_to_image() -> LibraryGraph:
return LibraryGraph(
id=default_text_to_image_graph_id,
name='t2i',
description='Converts text to an image',
graph=Graph(
nodes={
'width': ParamIntInvocation(id='width', a=512),
'height': ParamIntInvocation(id='height', a=512),
'3': NoiseInvocation(id='3'),
'4': TextToLatentsInvocation(id='4'),
'5': LatentsToImageInvocation(id='5')
},
edges=[
Edge(source=EdgeConnection(node_id='width', field='a'), destination=EdgeConnection(node_id='3', field='width')),
Edge(source=EdgeConnection(node_id='height', field='a'), destination=EdgeConnection(node_id='3', field='height')),
Edge(source=EdgeConnection(node_id='width', field='a'), destination=EdgeConnection(node_id='4', field='width')),
Edge(source=EdgeConnection(node_id='height', field='a'), destination=EdgeConnection(node_id='4', field='height')),
Edge(source=EdgeConnection(node_id='3', field='noise'), destination=EdgeConnection(node_id='4', field='noise')),
Edge(source=EdgeConnection(node_id='4', field='latents'), destination=EdgeConnection(node_id='5', field='latents')),
]
),
exposed_inputs=[
ExposedNodeInput(node_path='4', field='prompt', alias='prompt'),
ExposedNodeInput(node_path='width', field='a', alias='width'),
ExposedNodeInput(node_path='height', field='a', alias='height')
],
exposed_outputs=[
ExposedNodeOutput(node_path='5', field='image', alias='image')
])
def create_system_graphs(graph_library: ItemStorageABC[LibraryGraph]) -> list[LibraryGraph]:
"""Creates the default system graphs, or adds new versions if the old ones don't match"""
graphs: list[LibraryGraph] = list()
text_to_image = graph_library.get(default_text_to_image_graph_id)
# TODO: Check if the graph is the same as the default one, and if not, update it
#if text_to_image is None:
text_to_image = create_text_to_image()
graph_library.set(text_to_image)
graphs.append(text_to_image)
return graphs

45
invokeai/app/services/events.py
View File

@ -1,10 +1,9 @@
# Copyright (c) 2022 Kyle Schouviller (https://github.com/kyle0654)
from typing import Any, Dict, TypedDict
from typing import Any
from invokeai.app.api.models.images import ProgressImage
from invokeai.app.util.misc import get_timestamp
ProgressImage = TypedDict(
"ProgressImage", {"dataURL": str, "width": int, "height": int}
)
class EventServiceBase:
session_event: str = "session_event"
@ -14,7 +13,8 @@ class EventServiceBase:
def dispatch(self, event_name: str, payload: Any) -> None:
pass
def __emit_session_event(self, event_name: str, payload: Dict) -> None:
def __emit_session_event(self, event_name: str, payload: dict) -> None:
payload["timestamp"] = get_timestamp()
self.dispatch(
event_name=EventServiceBase.session_event,
payload=dict(event=event_name, data=payload),
@ -25,7 +25,8 @@ class EventServiceBase:
def emit_generator_progress(
self,
graph_execution_state_id: str,
invocation_id: str,
node: dict,
source_node_id: str,
progress_image: ProgressImage | None,
step: int,
total_steps: int,
@ -35,48 +36,60 @@ class EventServiceBase:
event_name="generator_progress",
payload=dict(
graph_execution_state_id=graph_execution_state_id,
invocation_id=invocation_id,
progress_image=progress_image,
node=node,
source_node_id=source_node_id,
progress_image=progress_image.dict() if progress_image is not None else None,
step=step,
total_steps=total_steps,
),
)
def emit_invocation_complete(
self, graph_execution_state_id: str, invocation_id: str, result: Dict
self,
graph_execution_state_id: str,
result: dict,
node: dict,
source_node_id: str,
) -> None:
"""Emitted when an invocation has completed"""
self.__emit_session_event(
event_name="invocation_complete",
payload=dict(
graph_execution_state_id=graph_execution_state_id,
invocation_id=invocation_id,
node=node,
source_node_id=source_node_id,
result=result,
),
)
def emit_invocation_error(
self, graph_execution_state_id: str, invocation_id: str, error: str
self,
graph_execution_state_id: str,
node: dict,
source_node_id: str,
error: str,
) -> None:
"""Emitted when an invocation has completed"""
self.__emit_session_event(
event_name="invocation_error",
payload=dict(
graph_execution_state_id=graph_execution_state_id,
invocation_id=invocation_id,
node=node,
source_node_id=source_node_id,
error=error,
),
)
def emit_invocation_started(
self, graph_execution_state_id: str, invocation_id: str
self, graph_execution_state_id: str, node: dict, source_node_id: str
) -> None:
"""Emitted when an invocation has started"""
self.__emit_session_event(
event_name="invocation_started",
payload=dict(
graph_execution_state_id=graph_execution_state_id,
invocation_id=invocation_id,
node=node,
source_node_id=source_node_id,
),
)
@ -84,5 +97,7 @@ class EventServiceBase:
"""Emitted when a session has completed all invocations"""
self.__emit_session_event(
event_name="graph_execution_state_complete",
payload=dict(graph_execution_state_id=graph_execution_state_id),
payload=dict(
graph_execution_state_id=graph_execution_state_id,
),
)

95
invokeai/app/services/graph.py
View File

@ -2,7 +2,6 @@
import copy
import itertools
import traceback
import uuid
from types import NoneType
from typing import (
@ -17,7 +16,7 @@ from typing import (
)
import networkx as nx
from pydantic import BaseModel, validator
from pydantic import BaseModel, root_validator, validator
from pydantic.fields import Field
from ..invocations import *
@ -26,7 +25,6 @@ from ..invocations.baseinvocation import (
BaseInvocationOutput,
InvocationContext,
)
from .invocation_services import InvocationServices
class EdgeConnection(BaseModel):
@ -215,7 +213,7 @@ InvocationOutputsUnion = Union[BaseInvocationOutput.get_all_subclasses_tuple()]
class Graph(BaseModel):
id: str = Field(description="The id of this graph", default_factory=uuid.uuid4)
id: str = Field(description="The id of this graph", default_factory=lambda: uuid.uuid4().__str__())
# TODO: use a list (and never use dict in a BaseModel) because pydantic/fastapi hates me
nodes: dict[str, Annotated[InvocationsUnion, Field(discriminator="type")]] = Field(
description="The nodes in this graph", default_factory=dict
@ -283,7 +281,8 @@ class Graph(BaseModel):
:raises InvalidEdgeError: the provided edge is invalid.
"""
if self._is_edge_valid(edge) and edge not in self.edges:
self._validate_edge(edge)
if edge not in self.edges:
self.edges.append(edge)
else:
raise InvalidEdgeError()
@ -354,7 +353,7 @@ class Graph(BaseModel):
return True
def _is_edge_valid(self, edge: Edge) -> bool:
def _validate_edge(self, edge: Edge):
"""Validates that a new edge doesn't create a cycle in the graph"""
# Validate that the nodes exist (edges may contain node paths, so we can't just check for nodes directly)
@ -362,54 +361,53 @@ class Graph(BaseModel):
from_node = self.get_node(edge.source.node_id)
to_node = self.get_node(edge.destination.node_id)
except NodeNotFoundError:
return False
raise InvalidEdgeError("One or both nodes don't exist")
# Validate that an edge to this node+field doesn't already exist
input_edges = self._get_input_edges(edge.destination.node_id, edge.destination.field)
if len(input_edges) > 0 and not isinstance(to_node, CollectInvocation):
return False
raise InvalidEdgeError(f'Edge to node {edge.destination.node_id} field {edge.destination.field} already exists')
# Validate that no cycles would be created
g = self.nx_graph_flat()
g.add_edge(edge.source.node_id, edge.destination.node_id)
if not nx.is_directed_acyclic_graph(g):
return False
raise InvalidEdgeError(f'Edge creates a cycle in the graph')
# Validate that the field types are compatible
if not are_connections_compatible(
from_node, edge.source.field, to_node, edge.destination.field
):
return False
raise InvalidEdgeError(f'Fields are incompatible')
# Validate if iterator output type matches iterator input type (if this edge results in both being set)
if isinstance(to_node, IterateInvocation) and edge.destination.field == "collection":
if not self._is_iterator_connection_valid(
edge.destination.node_id, new_input=edge.source
):
return False
raise InvalidEdgeError(f'Iterator input type does not match iterator output type')
# Validate if iterator input type matches output type (if this edge results in both being set)
if isinstance(from_node, IterateInvocation) and edge.source.field == "item":
if not self._is_iterator_connection_valid(
edge.source.node_id, new_output=edge.destination
):
return False
raise InvalidEdgeError(f'Iterator output type does not match iterator input type')
# Validate if collector input type matches output type (if this edge results in both being set)
if isinstance(to_node, CollectInvocation) and edge.destination.field == "item":
if not self._is_collector_connection_valid(
edge.destination.node_id, new_input=edge.source
):
return False
raise InvalidEdgeError(f'Collector output type does not match collector input type')
# Validate if collector output type matches input type (if this edge results in both being set)
if isinstance(from_node, CollectInvocation) and edge.source.field == "collection":
if not self._is_collector_connection_valid(
edge.source.node_id, new_output=edge.destination
):
return False
raise InvalidEdgeError(f'Collector input type does not match collector output type')
return True
def has_node(self, node_path: str) -> bool:
"""Determines whether or not a node exists in the graph."""
@ -733,7 +731,7 @@ class Graph(BaseModel):
for sgn in (
gn for gn in self.nodes.values() if isinstance(gn, GraphInvocation)
):
sgn.graph.nx_graph_flat(g, self._get_node_path(sgn.id, prefix))
g = sgn.graph.nx_graph_flat(g, self._get_node_path(sgn.id, prefix))
# TODO: figure out if iteration nodes need to be expanded
@ -750,9 +748,7 @@ class Graph(BaseModel):
class GraphExecutionState(BaseModel):
"""Tracks the state of a graph execution"""
id: str = Field(
description="The id of the execution state", default_factory=uuid.uuid4
)
id: str = Field(description="The id of the execution state", default_factory=lambda: uuid.uuid4().__str__())
# TODO: Store a reference to the graph instead of the actual graph?
graph: Graph = Field(description="The graph being executed")
@ -858,7 +854,8 @@ class GraphExecutionState(BaseModel):
def is_complete(self) -> bool:
"""Returns true if the graph is complete"""
return self.has_error() or all((k in self.executed for k in self.graph.nodes))
node_ids = set(self.graph.nx_graph_flat().nodes)
return self.has_error() or all((k in self.executed for k in node_ids))
def has_error(self) -> bool:
"""Returns true if the graph has any errors"""
@ -946,11 +943,11 @@ class GraphExecutionState(BaseModel):
def _iterator_graph(self) -> nx.DiGraph:
"""Gets a DiGraph with edges to collectors removed so an ancestor search produces all active iterators for any node"""
g = self.graph.nx_graph()
g = self.graph.nx_graph_flat()
collectors = (
n
for n in self.graph.nodes
if isinstance(self.graph.nodes[n], CollectInvocation)
if isinstance(self.graph.get_node(n), CollectInvocation)
)
for c in collectors:
g.remove_edges_from(list(g.in_edges(c)))
@ -962,7 +959,7 @@ class GraphExecutionState(BaseModel):
iterators = [
n
for n in nx.ancestors(g, node_id)
if isinstance(self.graph.nodes[n], IterateInvocation)
if isinstance(self.graph.get_node(n), IterateInvocation)
]
return iterators
@ -1098,7 +1095,9 @@ class GraphExecutionState(BaseModel):
# TODO: Add API for modifying underlying graph that checks if the change will be valid given the current execution state
def _is_edge_valid(self, edge: Edge) -> bool:
if not self._is_edge_valid(edge):
try:
self.graph._validate_edge(edge)
except InvalidEdgeError:
return False
# Invalid if destination has already been prepared or executed
@ -1144,4 +1143,52 @@ class GraphExecutionState(BaseModel):
self.graph.delete_edge(edge)
class ExposedNodeInput(BaseModel):
node_path: str = Field(description="The node path to the node with the input")
field: str = Field(description="The field name of the input")
alias: str = Field(description="The alias of the input")
class ExposedNodeOutput(BaseModel):
node_path: str = Field(description="The node path to the node with the output")
field: str = Field(description="The field name of the output")
alias: str = Field(description="The alias of the output")
class LibraryGraph(BaseModel):
id: str = Field(description="The unique identifier for this library graph", default_factory=uuid.uuid4)
graph: Graph = Field(description="The graph")
name: str = Field(description="The name of the graph")
description: str = Field(description="The description of the graph")
exposed_inputs: list[ExposedNodeInput] = Field(description="The inputs exposed by this graph", default_factory=list)
exposed_outputs: list[ExposedNodeOutput] = Field(description="The outputs exposed by this graph", default_factory=list)
@validator('exposed_inputs', 'exposed_outputs')
def validate_exposed_aliases(cls, v):
if len(v) != len(set(i.alias for i in v)):
raise ValueError("Duplicate exposed alias")
return v
@root_validator
def validate_exposed_nodes(cls, values):
graph = values['graph']
# Validate exposed inputs
for exposed_input in values['exposed_inputs']:
if not graph.has_node(exposed_input.node_path):
raise ValueError(f"Exposed input node {exposed_input.node_path} does not exist")
node = graph.get_node(exposed_input.node_path)
if get_input_field(node, exposed_input.field) is None:
raise ValueError(f"Exposed input field {exposed_input.field} does not exist on node {exposed_input.node_path}")
# Validate exposed outputs
for exposed_output in values['exposed_outputs']:
if not graph.has_node(exposed_output.node_path):
raise ValueError(f"Exposed output node {exposed_output.node_path} does not exist")
node = graph.get_node(exposed_output.node_path)
if get_output_field(node, exposed_output.field) is None:
raise ValueError(f"Exposed output field {exposed_output.field} does not exist on node {exposed_output.node_path}")
return values
GraphInvocation.update_forward_refs()

161
invokeai/app/services/image_storage.py
View File

@ -1,24 +1,29 @@
# Copyright (c) 2022 Kyle Schouviller (https://github.com/kyle0654)
import datetime
import os
from glob import glob
from abc import ABC, abstractmethod
from enum import Enum
from pathlib import Path
from queue import Queue
from typing import Callable, Dict, List
from typing import Dict, List
from PIL.Image import Image
import PIL.Image as PILImage
from pydantic import BaseModel
from invokeai.app.api.models.images import ImageResponse
from invokeai.app.models.image import ImageField, ImageType
from invokeai.app.models.metadata import ImageMetadata
from send2trash import send2trash
from invokeai.app.api.models.images import (
ImageResponse,
ImageResponseMetadata,
SavedImage,
)
from invokeai.app.models.image import ImageType
from invokeai.app.services.metadata import (
InvokeAIMetadata,
MetadataServiceBase,
build_invokeai_metadata_pnginfo,
)
from invokeai.app.services.item_storage import PaginatedResults
from invokeai.app.util.save_thumbnail import save_thumbnail
from invokeai.backend.image_util import PngWriter
from invokeai.app.util.misc import get_timestamp
from invokeai.app.util.thumbnails import get_thumbnail_name, make_thumbnail
class ImageStorageBase(ABC):
@ -26,12 +31,14 @@ class ImageStorageBase(ABC):
@abstractmethod
def get(self, image_type: ImageType, image_name: str) -> Image:
"""Retrieves an image as PIL Image."""
pass
@abstractmethod
def list(
self, image_type: ImageType, page: int = 0, per_page: int = 10
) -> PaginatedResults[ImageResponse]:
"""Gets a paginated list of images."""
pass
# TODO: make this a bit more flexible for e.g. cloud storage
@ -39,35 +46,59 @@ class ImageStorageBase(ABC):
def get_path(
self, image_type: ImageType, image_name: str, is_thumbnail: bool = False
) -> str:
"""Gets the internal path to an image or its thumbnail."""
pass
# TODO: make this a bit more flexible for e.g. cloud storage
@abstractmethod
def get_uri(
self, image_type: ImageType, image_name: str, is_thumbnail: bool = False
) -> str:
"""Gets the external URI to an image or its thumbnail."""
pass
# TODO: make this a bit more flexible for e.g. cloud storage
@abstractmethod
def validate_path(self, path: str) -> bool:
"""Validates an image path."""
pass
@abstractmethod
def save(self, image_type: ImageType, image_name: str, image: Image) -> None:
def save(
self,
image_type: ImageType,
image_name: str,
image: Image,
metadata: InvokeAIMetadata | None = None,
) -> SavedImage:
"""Saves an image and a 256x256 WEBP thumbnail. Returns a tuple of the image name, thumbnail name, and created timestamp."""
pass
@abstractmethod
def delete(self, image_type: ImageType, image_name: str) -> None:
"""Deletes an image and its thumbnail (if one exists)."""
pass
def create_name(self, context_id: str, node_id: str) -> str:
return f"{context_id}_{node_id}_{str(int(datetime.datetime.now(datetime.timezone.utc).timestamp()))}.png"
"""Creates a unique contextual image filename."""
return f"{context_id}_{node_id}_{str(get_timestamp())}.png"
class DiskImageStorage(ImageStorageBase):
"""Stores images on disk"""
__output_folder: str
__pngWriter: PngWriter
__cache_ids: Queue # TODO: this is an incredibly naive cache
__cache: Dict[str, Image]
__max_cache_size: int
__metadata_service: MetadataServiceBase
def __init__(self, output_folder: str):
def __init__(self, output_folder: str, metadata_service: MetadataServiceBase):
self.__output_folder = output_folder
self.__pngWriter = PngWriter(output_folder)
self.__cache = dict()
self.__cache_ids = Queue()
self.__max_cache_size = 10 # TODO: get this from config
self.__metadata_service = metadata_service
Path(output_folder).mkdir(parents=True, exist_ok=True)
@ -100,18 +131,22 @@ class DiskImageStorage(ImageStorageBase):
for path in page_of_image_paths:
filename = os.path.basename(path)
img = PILImage.open(path)
invokeai_metadata = self.__metadata_service.get_metadata(img)
page_of_images.append(
ImageResponse(
image_type=image_type.value,
image_name=filename,
# TODO: DiskImageStorage should not be building URLs...?
image_url=f"api/v1/images/{image_type.value}/{filename}",
thumbnail_url=f"api/v1/images/{image_type.value}/thumbnails/{os.path.splitext(filename)[0]}.webp",
# TODO: Creation of this object should happen elsewhere, just making it fit here so it works
metadata=ImageMetadata(
timestamp=os.path.getctime(path),
image_url=self.get_uri(image_type, filename),
thumbnail_url=self.get_uri(image_type, filename, True),
# TODO: Creation of this object should happen elsewhere (?), just making it fit here so it works
metadata=ImageResponseMetadata(
created=int(os.path.getctime(path)),
width=img.width,
height=img.height,
invokeai=invokeai_metadata,
),
)
)
@ -142,43 +177,89 @@ class DiskImageStorage(ImageStorageBase):
def get_path(
self, image_type: ImageType, image_name: str, is_thumbnail: bool = False
) -> str:
# strip out any relative path shenanigans
basename = os.path.basename(image_name)
if is_thumbnail:
path = os.path.join(
self.__output_folder, image_type, "thumbnails", image_name
self.__output_folder, image_type, "thumbnails", basename
)
else:
path = os.path.join(self.__output_folder, image_type, image_name)
return path
path = os.path.join(self.__output_folder, image_type, basename)
def save(self, image_type: ImageType, image_name: str, image: Image) -> None:
image_subpath = os.path.join(image_type, image_name)
self.__pngWriter.save_image_and_prompt_to_png(
image, "", image_subpath, None
) # TODO: just pass full path to png writer
save_thumbnail(
image=image,
filename=image_name,
path=os.path.join(self.__output_folder, image_type, "thumbnails"),
)
abspath = os.path.abspath(path)
return abspath
def get_uri(
self, image_type: ImageType, image_name: str, is_thumbnail: bool = False
) -> str:
# strip out any relative path shenanigans
basename = os.path.basename(image_name)
if is_thumbnail:
thumbnail_basename = get_thumbnail_name(basename)
uri = f"api/v1/images/{image_type.value}/thumbnails/{thumbnail_basename}"
else:
uri = f"api/v1/images/{image_type.value}/{basename}"
return uri
def validate_path(self, path: str) -> bool:
try:
os.stat(path)
return True
except Exception:
return False
def save(
self,
image_type: ImageType,
image_name: str,
image: Image,
metadata: InvokeAIMetadata | None = None,
) -> SavedImage:
image_path = self.get_path(image_type, image_name)
# TODO: Reading the image and then saving it strips the metadata...
if metadata:
pnginfo = build_invokeai_metadata_pnginfo(metadata=metadata)
image.save(image_path, "PNG", pnginfo=pnginfo)
else:
image.save(image_path) # this saved image has an empty info
thumbnail_name = get_thumbnail_name(image_name)
thumbnail_path = self.get_path(image_type, thumbnail_name, is_thumbnail=True)
thumbnail_image = make_thumbnail(image)
thumbnail_image.save(thumbnail_path)
self.__set_cache(image_path, image)
self.__set_cache(thumbnail_path, thumbnail_image)
return SavedImage(
image_name=image_name,
thumbnail_name=thumbnail_name,
created=int(os.path.getctime(image_path)),
)
def delete(self, image_type: ImageType, image_name: str) -> None:
image_path = self.get_path(image_type, image_name)
thumbnail_path = self.get_path(image_type, image_name, True)
if os.path.exists(image_path):
os.remove(image_path)
basename = os.path.basename(image_name)
image_path = self.get_path(image_type, basename)
if os.path.exists(image_path):
send2trash(image_path)
if image_path in self.__cache:
del self.__cache[image_path]
if os.path.exists(thumbnail_path):
os.remove(thumbnail_path)
thumbnail_name = get_thumbnail_name(image_name)
thumbnail_path = self.get_path(image_type, thumbnail_name, True)
if os.path.exists(thumbnail_path):
send2trash(thumbnail_path)
if thumbnail_path in self.__cache:
del self.__cache[thumbnail_path]
def __get_cache(self, image_name: str) -> Image:
def __get_cache(self, image_name: str) -> Image | None:
return None if image_name not in self.__cache else self.__cache[image_name]
def __set_cache(self, image_name: str, image: Image):

29
invokeai/app/services/invocation_queue.py
View File

@ -1,30 +1,17 @@
# Copyright (c) 2022 Kyle Schouviller (https://github.com/kyle0654)
import time
from abc import ABC, abstractmethod
from queue import Queue
import time
from pydantic import BaseModel, Field
# TODO: make this serializable
class InvocationQueueItem:
# session_id: str
graph_execution_state_id: str
invocation_id: str
invoke_all: bool
timestamp: float
def __init__(
self,
# session_id: str,
graph_execution_state_id: str,
invocation_id: str,
invoke_all: bool = False,
):
# self.session_id = session_id
self.graph_execution_state_id = graph_execution_state_id
self.invocation_id = invocation_id
self.invoke_all = invoke_all
self.timestamp = time.time()
class InvocationQueueItem(BaseModel):
graph_execution_state_id: str = Field(description="The ID of the graph execution state")
invocation_id: str = Field(description="The ID of the node being invoked")
invoke_all: bool = Field(default=False)
timestamp: float = Field(default_factory=time.time)
class InvocationQueueABC(ABC):

7
invokeai/app/services/invocation_services.py
View File

@ -1,4 +1,5 @@
# Copyright (c) 2022 Kyle Schouviller (https://github.com/kyle0654)
from invokeai.app.services.metadata import MetadataServiceBase
from invokeai.backend import ModelManager
from .events import EventServiceBase
@ -14,11 +15,13 @@ class InvocationServices:
events: EventServiceBase
latents: LatentsStorageBase
images: ImageStorageBase
metadata: MetadataServiceBase
queue: InvocationQueueABC
model_manager: ModelManager
restoration: RestorationServices
# NOTE: we must forward-declare any types that include invocations, since invocations can use services
graph_library: ItemStorageABC["LibraryGraph"]
graph_execution_manager: ItemStorageABC["GraphExecutionState"]
processor: "InvocationProcessorABC"
@ -28,7 +31,9 @@ class InvocationServices:
events: EventServiceBase,
latents: LatentsStorageBase,
images: ImageStorageBase,
metadata: MetadataServiceBase,
queue: InvocationQueueABC,
graph_library: ItemStorageABC["LibraryGraph"],
graph_execution_manager: ItemStorageABC["GraphExecutionState"],
processor: "InvocationProcessorABC",
restoration: RestorationServices,
@ -37,7 +42,9 @@ class InvocationServices:
self.events = events
self.latents = latents
self.images = images
self.metadata = metadata
self.queue = queue
self.graph_library = graph_library
self.graph_execution_manager = graph_execution_manager
self.processor = processor
self.restoration = restoration

96
invokeai/app/services/metadata.py Normal file
View File

@ -0,0 +1,96 @@
import json
from abc import ABC, abstractmethod
from typing import Any, Dict, Optional, TypedDict
from PIL import Image, PngImagePlugin
from pydantic import BaseModel
from invokeai.app.models.image import ImageType, is_image_type
class MetadataImageField(TypedDict):
"""Pydantic-less ImageField, used for metadata parsing."""
image_type: ImageType
image_name: str
class MetadataLatentsField(TypedDict):
"""Pydantic-less LatentsField, used for metadata parsing."""
latents_name: str
# TODO: This is a placeholder for `InvocationsUnion` pending resolution of circular imports
NodeMetadata = Dict[
str, str | int | float | bool | MetadataImageField | MetadataLatentsField
]
class InvokeAIMetadata(TypedDict, total=False):
"""InvokeAI-specific metadata format."""
session_id: Optional[str]
node: Optional[NodeMetadata]
def build_invokeai_metadata_pnginfo(
metadata: InvokeAIMetadata | None,
) -> PngImagePlugin.PngInfo:
"""Builds a PngInfo object with key `"invokeai"` and value `metadata`"""
pnginfo = PngImagePlugin.PngInfo()
if metadata is not None:
pnginfo.add_text("invokeai", json.dumps(metadata))
return pnginfo
class MetadataServiceBase(ABC):
@abstractmethod
def get_metadata(self, image: Image.Image) -> InvokeAIMetadata | None:
"""Gets the InvokeAI metadata from a PIL Image, skipping invalid values"""
pass
@abstractmethod
def build_metadata(
self, session_id: str, node: BaseModel
) -> InvokeAIMetadata | None:
"""Builds an InvokeAIMetadata object"""
pass
class PngMetadataService(MetadataServiceBase):
"""Handles loading and building metadata for images."""
# TODO: Use `InvocationsUnion` to **validate** metadata as representing a fully-functioning node
def _load_metadata(self, image: Image.Image) -> dict | None:
"""Loads a specific info entry from a PIL Image."""
try:
info = image.info.get("invokeai")
if type(info) is not str:
return None
loaded_metadata = json.loads(info)
if type(loaded_metadata) is not dict:
return None
if len(loaded_metadata.items()) == 0:
return None
return loaded_metadata
except:
return None
def get_metadata(self, image: Image.Image) -> dict | None:
"""Retrieves an image's metadata as a dict"""
loaded_metadata = self._load_metadata(image)
return loaded_metadata
def build_metadata(self, session_id: str, node: BaseModel) -> InvokeAIMetadata:
metadata = InvokeAIMetadata(session_id=session_id, node=node.dict())
return metadata

12
invokeai/app/services/processor.py
View File

@ -43,10 +43,14 @@ class DefaultInvocationProcessor(InvocationProcessorABC):
queue_item.invocation_id
)
# get the source node id to provide to clients (the prepared node id is not as useful)
source_node_id = graph_execution_state.prepared_source_mapping[invocation.id]
# Send starting event
self.__invoker.services.events.emit_invocation_started(
graph_execution_state_id=graph_execution_state.id,
invocation_id=invocation.id,
node=invocation.dict(),
source_node_id=source_node_id
)
# Invoke
@ -75,7 +79,8 @@ class DefaultInvocationProcessor(InvocationProcessorABC):
# Send complete event
self.__invoker.services.events.emit_invocation_complete(
graph_execution_state_id=graph_execution_state.id,
invocation_id=invocation.id,
node=invocation.dict(),
source_node_id=source_node_id,
result=outputs.dict(),
)
@ -99,7 +104,8 @@ class DefaultInvocationProcessor(InvocationProcessorABC):
# Send error event
self.__invoker.services.events.emit_invocation_error(
graph_execution_state_id=graph_execution_state.id,
invocation_id=invocation.id,
node=invocation.dict(),
source_node_id=source_node_id,
error=error,
)

5
invokeai/app/util/misc.py Normal file
View File

@ -0,0 +1,5 @@
import datetime
def get_timestamp():
return int(datetime.datetime.now(datetime.timezone.utc).timestamp())

25
invokeai/app/util/save_thumbnail.py
View File

@ -1,25 +0,0 @@
import os
from PIL import Image
def save_thumbnail(
image: Image.Image,
filename: str,
path: str,
size: int = 256,
) -> str:
"""
Saves a thumbnail of an image, returning its path.
"""
base_filename = os.path.splitext(filename)[0]
thumbnail_path = os.path.join(path, base_filename + ".webp")
if os.path.exists(thumbnail_path):
return thumbnail_path
image_copy = image.copy()
image_copy.thumbnail(size=(size, size))
image_copy.save(thumbnail_path, "WEBP")
return thumbnail_path

62
invokeai/app/util/step_callback.py
View File

@ -1,16 +1,41 @@
import torch
from invokeai.app.api.models.images import ProgressImage
from invokeai.app.models.exceptions import CanceledException
from ..invocations.baseinvocation import InvocationContext
from ...backend.util.util import image_to_dataURL
from ...backend.generator.base import Generator
from ...backend.stable_diffusion import PipelineIntermediateState
def fast_latents_step_callback(
sample: torch.Tensor,
step: int,
steps: int,
id: str,
def stable_diffusion_step_callback(
context: InvocationContext,
intermediate_state: PipelineIntermediateState,
node: dict,
source_node_id: str,
):
if context.services.queue.is_canceled(context.graph_execution_state_id):
raise CanceledException
# Some schedulers report not only the noisy latents at the current timestep,
# but also their estimate so far of what the de-noised latents will be. Use
# that estimate if it is available.
if intermediate_state.predicted_original is not None:
sample = intermediate_state.predicted_original
else:
sample = intermediate_state.latents
# TODO: This does not seem to be needed any more?
# # txt2img provides a Tensor in the step_callback
# # img2img provides a PipelineIntermediateState
# if isinstance(sample, PipelineIntermediateState):
# # this was an img2img
# print('img2img')
# latents = sample.latents
# step = sample.step
# else:
# print('txt2img')
# latents = sample
# step = intermediate_state.step
# TODO: only output a preview image when requested
image = Generator.sample_to_lowres_estimated_image(sample)
@ -21,23 +46,10 @@ def fast_latents_step_callback(
dataURL = image_to_dataURL(image, image_format="JPEG")
context.services.events.emit_generator_progress(
context.graph_execution_state_id,
id,
{"width": width, "height": height, "dataURL": dataURL},
step,
steps,
graph_execution_state_id=context.graph_execution_state_id,
node=node,
source_node_id=source_node_id,
progress_image=ProgressImage(width=width, height=height, dataURL=dataURL),
step=intermediate_state.step,
total_steps=node["steps"],
)
def diffusers_step_callback_adapter(*cb_args, **kwargs):
"""
txt2img gives us a Tensor in the step_callbak, while img2img gives us a PipelineIntermediateState.
This adapter grabs the needed data and passes it along to the callback function.
"""
if isinstance(cb_args[0], PipelineIntermediateState):
progress_state: PipelineIntermediateState = cb_args[0]
return fast_latents_step_callback(
progress_state.latents, progress_state.step, **kwargs
)
else:
return fast_latents_step_callback(*cb_args, **kwargs)

15
invokeai/app/util/thumbnails.py Normal file
View File

@ -0,0 +1,15 @@
import os
from PIL import Image
def get_thumbnail_name(image_name: str) -> str:
"""Formats given an image name, returns the appropriate thumbnail image name"""
thumbnail_name = os.path.splitext(image_name)[0] + ".webp"
return thumbnail_name
def make_thumbnail(image: Image.Image, size: int = 256) -> Image.Image:
"""Makes a thumbnail from a PIL Image"""
thumbnail = image.copy()
thumbnail.thumbnail(size=(size, size))
return thumbnail

2
invokeai/backend/__init__.py
View File

@ -10,7 +10,7 @@ from .generator import (
Img2Img,
Inpaint
)
from .model_management import ModelManager
from .model_management import ModelManager, SDModelComponent
from .safety_checker import SafetyChecker
from .args import Args
from .globals import Globals

3
invokeai/backend/model_management/__init__.py
View File

@ -5,6 +5,7 @@ from .convert_ckpt_to_diffusers import (
convert_ckpt_to_diffusers,
load_pipeline_from_original_stable_diffusion_ckpt,
)
from .model_manager import ModelManager
from .model_manager import ModelManager,SDModelComponent

4
invokeai/backend/stable_diffusion/concepts_lib.py
View File

@ -58,7 +58,7 @@ class HuggingFaceConceptsLibrary(object):
self.concept_list.extend(list(local_concepts_to_add))
return self.concept_list
return self.concept_list
else:
elif Globals.internet_available is True:
try:
models = self.hf_api.list_models(
filter=ModelFilter(model_name="sd-concepts-library/")
@ -74,6 +74,8 @@ class HuggingFaceConceptsLibrary(object):
"You may load .bin and .pt file(s) manually using the --embedding_directory argument."
)
return self.concept_list
else:
return self.concept_list
def get_concept_model_path(self, concept_name: str) -> str:
"""

15
invokeai/backend/stable_diffusion/diffusers_pipeline.py
View File

@ -445,8 +445,15 @@ class StableDiffusionGeneratorPipeline(StableDiffusionPipeline):
@property
def _submodels(self) -> Sequence[torch.nn.Module]:
module_names, _, _ = self.extract_init_dict(dict(self.config))
values = [getattr(self, name) for name in module_names.keys()]
return [m for m in values if isinstance(m, torch.nn.Module)]
submodels = []
for name in module_names.keys():
if hasattr(self, name):
value = getattr(self, name)
else:
value = getattr(self.config, name)
if isinstance(value, torch.nn.Module):
submodels.append(value)
return submodels
def image_from_embeddings(
self,
@ -544,7 +551,7 @@ class StableDiffusionGeneratorPipeline(StableDiffusionPipeline):
yield PipelineIntermediateState(
run_id=run_id,
step=-1,
timestep=self.scheduler.num_train_timesteps,
timestep=self.scheduler.config.num_train_timesteps,
latents=latents,
)
@ -915,7 +922,7 @@ class StableDiffusionGeneratorPipeline(StableDiffusionPipeline):
@property
def channels(self) -> int:
"""Compatible with DiffusionWrapper"""
return self.unet.in_channels
return self.unet.config.in_channels
def decode_latents(self, latents):
# Explicit call to get the vae loaded, since `decode` isn't the forward method.

28
invokeai/backend/stable_diffusion/diffusion/cross_attention_control.py
View File

@ -10,8 +10,7 @@ import diffusers
import psutil
import torch
from compel.cross_attention_control import Arguments
from diffusers.models.cross_attention import AttnProcessor
from diffusers.models.unet_2d_condition import UNet2DConditionModel
from diffusers.models.attention_processor import AttentionProcessor
from torch import nn
import invokeai.backend.util.logging as log
@ -188,7 +187,7 @@ class Context:
class InvokeAICrossAttentionMixin:
"""
Enable InvokeAI-flavoured CrossAttention calculation, which does aggressive low-memory slicing and calls
Enable InvokeAI-flavoured Attention calculation, which does aggressive low-memory slicing and calls
through both to an attention_slice_wrangler and a slicing_strategy_getter for custom attention map wrangling
and dymamic slicing strategy selection.
"""
@ -209,7 +208,7 @@ class InvokeAICrossAttentionMixin:
Set custom attention calculator to be called when attention is calculated
:param wrangler: Callback, with args (module, suggested_attention_slice, dim, offset, slice_size),
which returns either the suggested_attention_slice or an adjusted equivalent.
`module` is the current CrossAttention module for which the callback is being invoked.
`module` is the current Attention module for which the callback is being invoked.
`suggested_attention_slice` is the default-calculated attention slice
`dim` is -1 if the attenion map has not been sliced, or 0 or 1 for dimension-0 or dimension-1 slicing.
If `dim` is >= 0, `offset` and `slice_size` specify the slice start and length.
@ -345,11 +344,11 @@ class InvokeAICrossAttentionMixin:
def restore_default_cross_attention(
model,
is_running_diffusers: bool,
restore_attention_processor: Optional[AttnProcessor] = None,
restore_attention_processor: Optional[AttentionProcessor] = None,
):
if is_running_diffusers:
unet = model
unet.set_attn_processor(restore_attention_processor or CrossAttnProcessor())
unet.set_attn_processor(restore_attention_processor or AttnProcessor())
else:
remove_attention_function(model)
@ -408,12 +407,9 @@ def override_cross_attention(model, context: Context, is_running_diffusers=False
def get_cross_attention_modules(
model, which: CrossAttentionType
) -> list[tuple[str, InvokeAICrossAttentionMixin]]:
from ldm.modules.attention import CrossAttention # avoid circular import
cross_attention_class: type = (
InvokeAIDiffusersCrossAttention
if isinstance(model, UNet2DConditionModel)
else CrossAttention
)
which_attn = "attn1" if which is CrossAttentionType.SELF else "attn2"
attention_module_tuples = [
@ -550,7 +546,7 @@ def get_mem_free_total(device):
class InvokeAIDiffusersCrossAttention(
diffusers.models.attention.CrossAttention, InvokeAICrossAttentionMixin
diffusers.models.attention.Attention, InvokeAICrossAttentionMixin
):
def __init__(self, **kwargs):
super().__init__(**kwargs)
@ -572,8 +568,8 @@ class InvokeAIDiffusersCrossAttention(
"""
# base implementation
class CrossAttnProcessor:
def __call__(self, attn: CrossAttention, hidden_states, encoder_hidden_states=None, attention_mask=None):
class AttnProcessor:
def __call__(self, attn: Attention, hidden_states, encoder_hidden_states=None, attention_mask=None):
batch_size, sequence_length, _ = hidden_states.shape
attention_mask = attn.prepare_attention_mask(attention_mask, sequence_length)
@ -601,9 +597,9 @@ class CrossAttnProcessor:
from dataclasses import dataclass, field
import torch
from diffusers.models.cross_attention import (
CrossAttention,
CrossAttnProcessor,
from diffusers.models.attention_processor import (
Attention,
AttnProcessor,
SlicedAttnProcessor,
)
@ -653,7 +649,7 @@ class SlicedSwapCrossAttnProcesser(SlicedAttnProcessor):
def __call__(
self,
attn: CrossAttention,
attn: Attention,
hidden_states,
encoder_hidden_states=None,
attention_mask=None,

6
invokeai/backend/stable_diffusion/diffusion/shared_invokeai_diffusion.py
View File

@ -5,7 +5,7 @@ from typing import Any, Callable, Dict, Optional, Union
import numpy as np
import torch
from diffusers.models.cross_attention import AttnProcessor
from diffusers.models.attention_processor import AttentionProcessor
from typing_extensions import TypeAlias
import invokeai.backend.util.logging as log
@ -102,7 +102,7 @@ class InvokeAIDiffuserComponent:
def override_cross_attention(
self, conditioning: ExtraConditioningInfo, step_count: int
) -> Dict[str, AttnProcessor]:
) -> Dict[str, AttentionProcessor]:
"""
setup cross attention .swap control. for diffusers this replaces the attention processor, so
the previous attention processor is returned so that the caller can restore it later.
@ -119,7 +119,7 @@ class InvokeAIDiffuserComponent:
)
def restore_default_cross_attention(
self, restore_attention_processor: Optional["AttnProcessor"] = None
self, restore_attention_processor: Optional["AttentionProcessor"] = None
):
self.conditioning = None
self.cross_attention_control_context = None

75
invokeai/frontend/install/invokeai_update.py
View File

@ -1,10 +1,9 @@
"""
'''
Minimalist updater script. Prompts user for the tag or branch to update to and runs
pip install <path_to_git_source>.
"""
'''
import os
import platform
import requests
from rich import box, print
from rich.console import Console, Group, group
@ -16,8 +15,10 @@ from rich.text import Text
from invokeai.version import __version__
INVOKE_AI_SRC = "https://github.com/invoke-ai/InvokeAI/archive"
INVOKE_AI_REL = "https://api.github.com/repos/invoke-ai/InvokeAI/releases"
INVOKE_AI_SRC="https://github.com/invoke-ai/InvokeAI/archive"
INVOKE_AI_TAG="https://github.com/invoke-ai/InvokeAI/archive/refs/tags"
INVOKE_AI_BRANCH="https://github.com/invoke-ai/InvokeAI/archive/refs/heads"
INVOKE_AI_REL="https://api.github.com/repos/invoke-ai/InvokeAI/releases"
OS = platform.uname().system
ARCH = platform.uname().machine
@ -28,22 +29,22 @@ if OS == "Windows":
else:
console = Console(style=Style(color="grey74", bgcolor="grey19"))
def get_versions() -> dict:
def get_versions()->dict:
return requests.get(url=INVOKE_AI_REL).json()
def welcome(versions: dict):
@group()
def text():
yield f"InvokeAI Version: [bold yellow]{__version__}"
yield ""
yield "This script will update InvokeAI to the latest release, or to a development version of your choice."
yield ""
yield "[bold yellow]Options:"
yield f"""[1] Update to the latest official release ([italic]{versions[0]['tag_name']}[/italic])
yield f'InvokeAI Version: [bold yellow]{__version__}'
yield ''
yield 'This script will update InvokeAI to the latest release, or to a development version of your choice.'
yield ''
yield '[bold yellow]Options:'
yield f'''[1] Update to the latest official release ([italic]{versions[0]['tag_name']}[/italic])
[2] Update to the bleeding-edge development version ([italic]main[/italic])
[3] Manually enter the tag or branch name you wish to update"""
[3] Manually enter the [bold]tag name[/bold] for the version you wish to update to
[4] Manually enter the [bold]branch name[/bold] for the version you wish to update to'''
console.rule()
print(
@ -59,33 +60,41 @@ def welcome(versions: dict):
)
console.line()
def main():
versions = get_versions()
welcome(versions)
tag = None
choice = Prompt.ask("Choice:", choices=["1", "2", "3"], default="1")
branch = None
release = None
choice = Prompt.ask('Choice:',choices=['1','2','3','4'],default='1')
if choice=='1':
release = versions[0]['tag_name']
elif choice=='2':
release = 'main'
elif choice=='3':
tag = Prompt.ask('Enter an InvokeAI tag name')
elif choice=='4':
branch = Prompt.ask('Enter an InvokeAI branch name')
if choice == "1":
tag = versions[0]["tag_name"]
elif choice == "2":
tag = "main"
elif choice == "3":
tag = Prompt.ask("Enter an InvokeAI tag or branch name")
print(f":crossed_fingers: Upgrading to [yellow]{tag}[/yellow]")
cmd = f"pip install {INVOKE_AI_SRC}/{tag}.zip --use-pep517"
print("")
print("")
if os.system(cmd) == 0:
print(f":heavy_check_mark: Upgrade successful")
print(f':crossed_fingers: Upgrading to [yellow]{tag if tag else release}[/yellow]')
if release:
cmd = f'pip install {INVOKE_AI_SRC}/{release}.zip --use-pep517 --upgrade'
elif tag:
cmd = f'pip install {INVOKE_AI_TAG}/{tag}.zip --use-pep517 --upgrade'
else:
print(f":exclamation: [bold red]Upgrade failed[/red bold]")
cmd = f'pip install {INVOKE_AI_BRANCH}/{branch}.zip --use-pep517 --upgrade'
print('')
print('')
if os.system(cmd)==0:
print(f':heavy_check_mark: Upgrade successful')
else:
print(f':exclamation: [bold red]Upgrade failed[/red bold]')
if __name__ == "__main__":
try:
main()
except KeyboardInterrupt:
pass

2
invokeai/frontend/web/.eslintignore
View File

@ -6,3 +6,5 @@ stats.html
index.html
.yarn/
*.scss
src/services/api/
src/services/fixtures/*

4
invokeai/frontend/web/.prettierignore
View File

@ -3,4 +3,8 @@ dist/
node_modules/
patches/
stats.html
index.html
.yarn/
*.scss
src/services/api/
src/services/fixtures/*

188
invokeai/frontend/web/dist/assets/App-843b023b.js vendored
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188
invokeai/frontend/web/dist/assets/App-af7ef809.js vendored Normal file
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2
invokeai/frontend/web/dist/assets/ThemeLocaleProvider-680f01c6.js → invokeai/frontend/web/dist/assets/ThemeLocaleProvider-7791bd91.js vendored
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@ -1,4 +1,4 @@
import{j as y,cN as Ie,r as _,cO as bt,q as Lr,cP as o,cQ as b,cR as v,cS as S,cT as Vr,cU as ut,cV as vt,cM as ft,cW as mt,n as gt,cX as ht,E as pt}from"./index-f7f41e1f.js";import{d as yt,i as St,T as xt,j as $t,h as kt}from"./storeHooks-eaf47ae3.js";var Or=`
import{j as y,cO as Ie,r as _,cP as bt,q as Lr,cQ as o,cR as b,cS as v,cT as S,cU as Vr,cV as ut,cW as vt,cN as ft,cX as mt,n as gt,cY as ht,E as pt}from"./index-e53e8108.js";import{d as yt,i as St,T as xt,j as $t,h as kt}from"./storeHooks-5cde7d31.js";var Or=`
:root {
--chakra-vh: 100vh;
}

4
invokeai/frontend/web/dist/assets/index-f7f41e1f.js → invokeai/frontend/web/dist/assets/index-e53e8108.js vendored
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4
invokeai/frontend/web/dist/assets/storeHooks-eaf47ae3.js → invokeai/frontend/web/dist/assets/storeHooks-5cde7d31.js vendored
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2
invokeai/frontend/web/dist/index.html vendored
View File

@ -12,7 +12,7 @@
margin: 0;
}
</style>
<script type="module" crossorigin src="./assets/index-f7f41e1f.js"></script>
<script type="module" crossorigin src="./assets/index-e53e8108.js"></script>
<link rel="stylesheet" href="./assets/index-5483945c.css">
</head>

1
invokeai/frontend/web/dist/locales/ar.json vendored
View File

@ -8,7 +8,6 @@
"darkTheme": "داكن",
"lightTheme": "فاتح",
"greenTheme": "أخضر",
"text2img": "نص إلى صورة",
"img2img": "صورة إلى صورة",
"unifiedCanvas": "لوحة موحدة",
"nodes": "عقد",

1
invokeai/frontend/web/dist/locales/de.json vendored
View File

@ -7,7 +7,6 @@
"darkTheme": "Dunkel",
"lightTheme": "Hell",
"greenTheme": "Grün",
"text2img": "Text zu Bild",
"img2img": "Bild zu Bild",
"nodes": "Knoten",
"langGerman": "Deutsch",

4
invokeai/frontend/web/dist/locales/en.json vendored
View File

@ -505,7 +505,9 @@
"info": "Info",
"deleteImage": "Delete Image",
"initialImage": "Initial Image",
"showOptionsPanel": "Show Options Panel"
"showOptionsPanel": "Show Options Panel",
"hidePreview": "Hide Preview",
"showPreview": "Show Preview"
},
"settings": {
"models": "Models",

12
invokeai/frontend/web/dist/locales/es.json vendored
View File

@ -8,7 +8,6 @@
"darkTheme": "Oscuro",
"lightTheme": "Claro",
"greenTheme": "Verde",
"text2img": "Texto a Imagen",
"img2img": "Imagen a Imagen",
"unifiedCanvas": "Lienzo Unificado",
"nodes": "Nodos",
@ -70,7 +69,11 @@
"langHebrew": "Hebreo",
"pinOptionsPanel": "Pin del panel de opciones",
"loading": "Cargando",
"loadingInvokeAI": "Cargando invocar a la IA"
"loadingInvokeAI": "Cargando invocar a la IA",
"postprocessing": "Tratamiento posterior",
"txt2img": "De texto a imagen",
"accept": "Aceptar",
"cancel": "Cancelar"
},
"gallery": {
"generations": "Generaciones",
@ -404,7 +407,8 @@
"none": "ninguno",
"pickModelType": "Elige el tipo de modelo",
"v2_768": "v2 (768px)",
"addDifference": "Añadir una diferencia"
"addDifference": "Añadir una diferencia",
"scanForModels": "Buscar modelos"
},
"parameters": {
"images": "Imágenes",
@ -574,7 +578,7 @@
"autoSaveToGallery": "Guardar automáticamente en galería",
"saveBoxRegionOnly": "Guardar solo región dentro de la caja",
"limitStrokesToBox": "Limitar trazos a la caja",
"showCanvasDebugInfo": "Mostrar información de depuración de lienzo",
"showCanvasDebugInfo": "Mostrar la información adicional del lienzo",
"clearCanvasHistory": "Limpiar historial de lienzo",
"clearHistory": "Limpiar historial",
"clearCanvasHistoryMessage": "Limpiar el historial de lienzo también restablece completamente el lienzo unificado. Esto incluye todo el historial de deshacer/rehacer, las imágenes en el área de preparación y la capa base del lienzo.",

25
invokeai/frontend/web/dist/locales/fr.json vendored
View File

@ -8,7 +8,6 @@
"darkTheme": "Sombre",
"lightTheme": "Clair",
"greenTheme": "Vert",
"text2img": "Texte en image",
"img2img": "Image en image",
"unifiedCanvas": "Canvas unifié",
"nodes": "Nœuds",
@ -47,7 +46,19 @@
"statusLoadingModel": "Chargement du modèle",
"statusModelChanged": "Modèle changé",
"discordLabel": "Discord",
"githubLabel": "Github"
"githubLabel": "Github",
"accept": "Accepter",
"statusMergingModels": "Mélange des modèles",
"loadingInvokeAI": "Chargement de Invoke AI",
"cancel": "Annuler",
"langEnglish": "Anglais",
"statusConvertingModel": "Conversion du modèle",
"statusModelConverted": "Modèle converti",
"loading": "Chargement",
"pinOptionsPanel": "Épingler la page d'options",
"statusMergedModels": "Modèles mélangés",
"txt2img": "Texte vers image",
"postprocessing": "Post-Traitement"
},
"gallery": {
"generations": "Générations",
@ -518,5 +529,15 @@
"betaDarkenOutside": "Assombrir à l'extérieur",
"betaLimitToBox": "Limiter à la boîte",
"betaPreserveMasked": "Conserver masqué"
},
"accessibility": {
"uploadImage": "Charger une image",
"reset": "Réinitialiser",
"nextImage": "Image suivante",
"previousImage": "Image précédente",
"useThisParameter": "Utiliser ce paramètre",
"zoomIn": "Zoom avant",
"zoomOut": "Zoom arrière",
"showOptionsPanel": "Montrer la page d'options"
}
}

1
invokeai/frontend/web/dist/locales/he.json vendored
View File

@ -125,7 +125,6 @@
"langSimplifiedChinese": "סינית",
"langUkranian": "אוקראינית",
"langSpanish": "ספרדית",
"text2img": "טקסט לתמונה",
"img2img": "תמונה לתמונה",
"unifiedCanvas": "קנבס מאוחד",
"nodes": "צמתים",

14
invokeai/frontend/web/dist/locales/it.json vendored
View File

@ -8,7 +8,6 @@
"darkTheme": "Scuro",
"lightTheme": "Chiaro",
"greenTheme": "Verde",
"text2img": "Testo a Immagine",
"img2img": "Immagine a Immagine",
"unifiedCanvas": "Tela unificata",
"nodes": "Nodi",
@ -70,7 +69,11 @@
"loading": "Caricamento in corso",
"oceanTheme": "Oceano",
"langHebrew": "Ebraico",
"loadingInvokeAI": "Caricamento Invoke AI"
"loadingInvokeAI": "Caricamento Invoke AI",
"postprocessing": "Post Elaborazione",
"txt2img": "Testo a Immagine",
"accept": "Accetta",
"cancel": "Annulla"
},
"gallery": {
"generations": "Generazioni",
@ -404,7 +407,8 @@
"v2_768": "v2 (768px)",
"none": "niente",
"addDifference": "Aggiungi differenza",
"pickModelType": "Scegli il tipo di modello"
"pickModelType": "Scegli il tipo di modello",
"scanForModels": "Cerca modelli"
},
"parameters": {
"images": "Immagini",
@ -574,7 +578,7 @@
"autoSaveToGallery": "Salvataggio automatico nella Galleria",
"saveBoxRegionOnly": "Salva solo l'area di selezione",
"limitStrokesToBox": "Limita i tratti all'area di selezione",
"showCanvasDebugInfo": "Mostra informazioni di debug della Tela",
"showCanvasDebugInfo": "Mostra ulteriori informazioni sulla Tela",
"clearCanvasHistory": "Cancella cronologia Tela",
"clearHistory": "Cancella la cronologia",
"clearCanvasHistoryMessage": "La cancellazione della cronologia della tela lascia intatta la tela corrente, ma cancella in modo irreversibile la cronologia degli annullamenti e dei ripristini.",
@ -612,7 +616,7 @@
"copyMetadataJson": "Copia i metadati JSON",
"exitViewer": "Esci dal visualizzatore",
"zoomIn": "Zoom avanti",
"zoomOut": "Zoom Indietro",
"zoomOut": "Zoom indietro",
"rotateCounterClockwise": "Ruotare in senso antiorario",
"rotateClockwise": "Ruotare in senso orario",
"flipHorizontally": "Capovolgi orizzontalmente",

1
invokeai/frontend/web/dist/locales/ko.json vendored
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@ -11,7 +11,6 @@
"langArabic": "العربية",
"langEnglish": "English",
"langDutch": "Nederlands",
"text2img": "텍스트->이미지",
"unifiedCanvas": "통합 캔버스",
"langFrench": "Français",
"langGerman": "Deutsch",

1
invokeai/frontend/web/dist/locales/nl.json vendored
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@ -8,7 +8,6 @@
"darkTheme": "Donker",
"lightTheme": "Licht",
"greenTheme": "Groen",
"text2img": "Tekst naar afbeelding",
"img2img": "Afbeelding naar afbeelding",
"unifiedCanvas": "Centraal canvas",
"nodes": "Knooppunten",

1
invokeai/frontend/web/dist/locales/pl.json vendored
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@ -8,7 +8,6 @@
"darkTheme": "Ciemny",
"lightTheme": "Jasny",
"greenTheme": "Zielony",
"text2img": "Tekst na obraz",
"img2img": "Obraz na obraz",
"unifiedCanvas": "Tryb uniwersalny",
"nodes": "Węzły",

1
invokeai/frontend/web/dist/locales/pt.json vendored
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@ -20,7 +20,6 @@
"langSpanish": "Espanhol",
"langRussian": "Русский",
"langUkranian": "Украї́нська",
"text2img": "Texto para Imagem",
"img2img": "Imagem para Imagem",
"unifiedCanvas": "Tela Unificada",
"nodes": "Nós",

1
invokeai/frontend/web/dist/locales/pt_BR.json vendored
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@ -8,7 +8,6 @@
"darkTheme": "Noite",
"lightTheme": "Dia",
"greenTheme": "Verde",
"text2img": "Texto Para Imagem",
"img2img": "Imagem Para Imagem",
"unifiedCanvas": "Tela Unificada",
"nodes": "Nódulos",

1
invokeai/frontend/web/dist/locales/ru.json vendored
View File

@ -8,7 +8,6 @@
"darkTheme": "Темная",
"lightTheme": "Светлая",
"greenTheme": "Зеленая",
"text2img": "Изображение из текста (text2img)",
"img2img": "Изображение в изображение (img2img)",
"unifiedCanvas": "Универсальный холст",
"nodes": "Ноды",

1
invokeai/frontend/web/dist/locales/uk.json vendored
View File

@ -8,7 +8,6 @@
"darkTheme": "Темна",
"lightTheme": "Світла",
"greenTheme": "Зелена",
"text2img": "Зображення із тексту (text2img)",
"img2img": "Зображення із зображення (img2img)",
"unifiedCanvas": "Універсальне полотно",
"nodes": "Вузли",

1
invokeai/frontend/web/dist/locales/zh_CN.json vendored
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@ -8,7 +8,6 @@
"darkTheme": "暗色",
"lightTheme": "亮色",
"greenTheme": "绿色",
"text2img": "文字到图像",
"img2img": "图像到图像",
"unifiedCanvas": "统一画布",
"nodes": "节点",

1
invokeai/frontend/web/dist/locales/zh_Hant.json vendored
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@ -33,7 +33,6 @@
"langBrPortuguese": "巴西葡萄牙語",
"langRussian": "俄語",
"langSpanish": "西班牙語",
"text2img": "文字到圖像",
"unifiedCanvas": "統一畫布"
}
}

87
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@ -0,0 +1,87 @@
# Generated axios API client
- [Generated axios API client](#generated-axios-api-client)
- [Generation](#generation)
- [Generate the API client from the nodes web server](#generate-the-api-client-from-the-nodes-web-server)
- [Generate the API client from JSON](#generate-the-api-client-from-json)
- [Getting the JSON from the nodes web server](#getting-the-json-from-the-nodes-web-server)
- [Getting the JSON with a python script](#getting-the-json-with-a-python-script)
- [Generate the API client](#generate-the-api-client)
- [The generated client](#the-generated-client)
- [API client customisation](#api-client-customisation)
This API client is generated by an [openapi code generator](https://github.com/ferdikoomen/openapi-typescript-codegen).
All files in `invokeai/frontend/web/src/services/api/` are made by the generator.
## Generation
The axios client may be generated by from the OpenAPI schema from the nodes web server, or from JSON.
### Generate the API client from the nodes web server
We need to start the nodes web server, which serves the OpenAPI schema to the generator.
1. Start the nodes web server.
```bash
# from the repo root
python scripts/invoke-new.py --web
```
2. Generate the API client.
```bash
# from invokeai/frontend/web/
yarn api:web
```
### Generate the API client from JSON
The JSON can be acquired from the nodes web server, or with a python script.
#### Getting the JSON from the nodes web server
Start the nodes web server as described above, then download the file.
```bash
# from invokeai/frontend/web/
curl http://localhost:9090/openapi.json -o openapi.json
```
#### Getting the JSON with a python script
Run this python script from the repo root, so it can access the nodes server modules.
The script will output `openapi.json` in the repo root. Then we need to move it to `invokeai/frontend/web/`.
```bash
# from the repo root
python invokeai/app/util/generate_openapi_json.py
mv invokeai/app/util/openapi.json invokeai/frontend/web/services/fixtures/
```
#### Generate the API client
Now we can generate the API client from the JSON.
```bash
# from invokeai/frontend/web/
yarn api:file
```
## The generated client
The client will be written to `invokeai/frontend/web/services/api/`:
- `axios` client
- TS types
- An easily parseable schema, which we can use to generate UI
## API client customisation
The generator has a default `request.ts` file that implements a base `axios` client. The generated client uses this base client.
One shortcoming of this is base client is it does not provide response headers unless the response body is empty. To fix this, we provide our own lightly-patched `request.ts`.
To access the headers, call `getHeaders(response)` on any response from the generated api client. This function is exported from `invokeai/frontend/web/src/services/util/getHeaders.ts`.

21
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@ -0,0 +1,21 @@
# Events
Events via `socket.io`
## `actions.ts`
Redux actions for all socket events. Payloads all include a timestamp, and optionally some other data.
Any reducer (or middleware) can respond to the actions.
## `middleware.ts`
Redux middleware for events.
Handles dispatching the event actions. Only put logic here if it can't really go anywhere else.
For example, on connect we want to load images to the gallery if it's not populated. This requires dispatching a thunk, so we need to directly dispatch this in the middleware.
## `types.ts`
Hand-written types for the socket events. Cannot generate these from the server, but fortunately they are few and simple.

17
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@ -0,0 +1,17 @@
# Node Editor Design
WIP
nodes
everything in `src/features/nodes/`
have a look at `state.nodes.invocation`
- on socket connect, if no schema saved, fetch `localhost:9090/openapi.json`, save JSON to `state.nodes.schema`
- on fulfilled schema fetch, `parseSchema()` the schema. this outputs a `Record<string, Invocation>` which is saved to `state.nodes.invocations` - `Invocation` is like a template for the node
- when you add a node, the the `Invocation` template is passed to `InvocationComponent.tsx` to build the UI component for that node
- inputs/outputs have field types - and each field type gets an `FieldComponent` which includes a dispatcher to write state changes to redux `nodesSlice`
- `reactflow` sends changes to nodes/edges to redux
- to invoke, `buildNodesGraph()` state, then send this
- changed onClick Invoke button actions to build the schema, then when schema builds it dispatches the actual network request to create the session - see `session.ts`

29
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@ -0,0 +1,29 @@
# Package Scripts
WIP walkthrough of `package.json` scripts.
## `theme` & `theme:watch`
These run the Chakra CLI to generate types for the theme, or watch for code change and re-generate the types.
The CLI essentially monkeypatches Chakra's files in `node_modules`.
## `postinstall`
The `postinstall` script patches a few packages and runs the Chakra CLI to generate types for the theme.
### Patch `@chakra-ui/cli`
See: <https://github.com/chakra-ui/chakra-ui/issues/7394>
### Patch `redux-persist`
We want to persist the canvas state to `localStorage` but many canvas operations change data very quickly, so we need to debounce the writes to `localStorage`.
`redux-persist` is unfortunately unmaintained. The repo's current code is nonfunctional, but the last release's code depends on a package that was removed from `npm` for being malware, so we cannot just fork it.
So, we have to patch it directly. Perhaps a better way would be to write a debounced storage adapter, but I couldn't figure out how to do that.
### Patch `redux-deep-persist`
This package makes blacklisting and whitelisting persist configs very simple, but we have to patch it to match `redux-persist` for the types to work.

10
invokeai/frontend/web/README.md → invokeai/frontend/web/docs/README.md
View File

@ -1,10 +1,16 @@
# InvokeAI Web UI
- [InvokeAI Web UI](#invokeai-web-ui)
- [Stack](#stack)
- [Contributing](#contributing)
- [Dev Environment](#dev-environment)
- [Production builds](#production-builds)
The UI is a fairly straightforward Typescript React app. The only really fancy stuff is the Unified Canvas.
Code in `invokeai/frontend/web/` if you want to have a look.
## Details
## Stack
State management is Redux via [Redux Toolkit](https://github.com/reduxjs/redux-toolkit). Communication with server is a mix of HTTP and [socket.io](https://github.com/socketio/socket.io-client) (with a custom redux middleware to help).
@ -32,7 +38,7 @@ Start everything in dev mode:
1. Start the dev server: `yarn dev`
2. Start the InvokeAI UI per usual: `invokeai --web`
3. Point your browser to the dev server address e.g. `http://localhost:5173/`
3. Point your browser to the dev server address e.g. <http://localhost:5173/>
### Production builds

20
invokeai/frontend/web/index.d.ts vendored
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@ -1,6 +1,8 @@
import React, { PropsWithChildren } from 'react';
import { IAIPopoverProps } from '../web/src/common/components/IAIPopover';
import { IAIIconButtonProps } from '../web/src/common/components/IAIIconButton';
import { InvokeTabName } from 'features/ui/store/tabMap';
import { PartialAppConfig } from 'app/invokeai';
export {};
@ -64,9 +66,23 @@ declare module '@invoke-ai/invoke-ai-ui' {
declare class SettingsModal extends React.Component<SettingsModalProps> {
public constructor(props: SettingsModalProps);
}
declare class StatusIndicator extends React.Component<StatusIndicatorProps> {
public constructor(props: StatusIndicatorProps);
}
declare class ModelSelect extends React.Component<ModelSelectProps> {
public constructor(props: ModelSelectProps);
}
}
declare function Invoke(props: PropsWithChildren): JSX.Element;
interface InvokeProps extends PropsWithChildren {
apiUrl?: string;
token?: string;
config?: PartialAppConfig;
}
declare function Invoke(props: InvokeProps): JSX.Element;
export {
ThemeChanger,
@ -74,5 +90,7 @@ export {
IAIPopover,
IAIIconButton,
SettingsModal,
StatusIndicator,
ModelSelect,
};
export = Invoke;

19
invokeai/frontend/web/package.json
View File

@ -5,7 +5,11 @@
"scripts": {
"prepare": "cd ../../../ && husky install invokeai/frontend/web/.husky",
"dev": "concurrently \"vite dev\" \"yarn run theme:watch\"",
"dev:nodes": "concurrently \"vite dev --mode nodes\" \"yarn run theme:watch\"",
"dev:host": "concurrently \"vite dev --host\" \"yarn run theme:watch\"",
"build": "yarn run lint && vite build",
"api:web": "openapi -i http://localhost:9090/openapi.json -o src/services/api --client axios --useOptions --useUnionTypes --exportSchemas true --indent 2 --request src/services/fixtures/request.ts",
"api:file": "openapi -i src/services/fixtures/openapi.json -o src/services/api --client axios --useOptions --useUnionTypes --exportSchemas true --indent 2 --request src/services/fixtures/request.ts",
"preview": "vite preview",
"lint:madge": "madge --circular src/main.tsx",
"lint:eslint": "eslint --max-warnings=0 .",
@ -41,13 +45,16 @@
"@chakra-ui/react": "^2.5.1",
"@chakra-ui/styled-system": "^2.6.1",
"@chakra-ui/theme-tools": "^2.0.16",
"@dagrejs/graphlib": "^2.1.12",
"@emotion/react": "^11.10.6",
"@emotion/styled": "^11.10.6",
"@reduxjs/toolkit": "^1.9.2",
"@fontsource/inter": "^4.5.15",
"@reduxjs/toolkit": "^1.9.3",
"chakra-ui-contextmenu": "^1.0.5",
"dateformat": "^5.0.3",
"formik": "^2.2.9",
"framer-motion": "^9.0.4",
"fuse.js": "^6.6.2",
"i18next": "^22.4.10",
"i18next-browser-languagedetector": "^7.0.1",
"i18next-http-backend": "^2.1.1",
@ -67,15 +74,17 @@
"react-redux": "^8.0.5",
"react-transition-group": "^4.4.5",
"react-zoom-pan-pinch": "^2.6.1",
"reactflow": "^11.7.0",
"redux-deep-persist": "^1.0.7",
"redux-dynamic-middlewares": "^2.2.0",
"redux-persist": "^6.0.0",
"socket.io-client": "^4.6.0",
"use-image": "^1.1.0",
"uuid": "^9.0.0"
},
"devDependencies": {
"@fontsource/inter": "^4.5.15",
"@types/dateformat": "^5.0.0",
"@types/lodash": "^4.14.194",
"@types/react": "^18.0.28",
"@types/react-dom": "^18.0.11",
"@types/react-transition-group": "^4.4.5",
@ -83,6 +92,7 @@
"@typescript-eslint/eslint-plugin": "^5.52.0",
"@typescript-eslint/parser": "^5.52.0",
"@vitejs/plugin-react-swc": "^3.2.0",
"axios": "^1.3.4",
"babel-plugin-transform-imports": "^2.0.0",
"concurrently": "^7.6.0",
"eslint": "^8.34.0",
@ -90,13 +100,18 @@
"eslint-plugin-prettier": "^4.2.1",
"eslint-plugin-react": "^7.32.2",
"eslint-plugin-react-hooks": "^4.6.0",
"form-data": "^4.0.0",
"husky": "^8.0.3",
"lint-staged": "^13.1.2",
"madge": "^6.0.0",
"openapi-types": "^12.1.0",
"openapi-typescript-codegen": "^0.23.0",
"postinstall-postinstall": "^2.1.0",
"prettier": "^2.8.4",
"rollup-plugin-visualizer": "^5.9.0",
"terser": "^5.16.4",
"ts-toolbelt": "^9.6.0",
"typescript": "4.9.5",
"vite": "^4.1.2",
"vite-plugin-eslint": "^1.8.1",
"vite-tsconfig-paths": "^4.0.5",

59
invokeai/frontend/web/public/locales/de.json
View File

@ -18,7 +18,7 @@
"training": "Training",
"trainingDesc1": "Ein spezieller Arbeitsablauf zum Trainieren Ihrer eigenen Embeddings und Checkpoints mit Textual Inversion und Dreambooth über die Weboberfläche.",
"trainingDesc2": "InvokeAI unterstützt bereits das Training von benutzerdefinierten Embeddings mit Textual Inversion unter Verwendung des Hauptskripts.",
"upload": "Upload",
"upload": "Hochladen",
"close": "Schließen",
"load": "Laden",
"statusConnected": "Verbunden",
@ -41,12 +41,34 @@
"statusUpscaling": "Hochskalierung",
"statusUpscalingESRGAN": "Hochskalierung (ESRGAN)",
"statusLoadingModel": "Laden des Modells",
"statusModelChanged": "Modell Geändert"
"statusModelChanged": "Modell Geändert",
"cancel": "Abbruch",
"accept": "Annehmen",
"back": "Zurück",
"langEnglish": "Englisch",
"langDutch": "Niederländisch",
"langFrench": "Französisch",
"oceanTheme": "Ozean",
"langItalian": "Italienisch",
"langPortuguese": "Portogisisch",
"langRussian": "Russisch",
"langUkranian": "Ukrainisch",
"hotkeysLabel": "Tastenkombinationen",
"githubLabel": "Github",
"discordLabel": "Discord",
"txt2img": "Text zu Bild",
"postprocessing": "Nachbearbeitung",
"langPolish": "Polnisch",
"langJapanese": "Japanisch",
"langArabic": "Arabisch",
"langKorean": "Koreanisch",
"langHebrew": "Hebräisch",
"langSpanish": "Spanisch"
},
"gallery": {
"generations": "Erzeugungen",
"showGenerations": "Zeige Erzeugnisse",
"uploads": "Uploads",
"uploads": "Hochgelades",
"showUploads": "Zeige Uploads",
"galleryImageSize": "Bildgröße",
"galleryImageResetSize": "Größe zurücksetzen",
@ -312,7 +334,11 @@
"deleteModel": "Model löschen",
"deleteConfig": "Konfiguration löschen",
"deleteMsg1": "Möchten Sie diesen Model-Eintrag wirklich aus InvokeAI löschen?",
"deleteMsg2": "Dadurch wird die Modellprüfpunktdatei nicht von Ihrer Festplatte gelöscht. Sie können sie bei Bedarf erneut hinzufügen."
"deleteMsg2": "Dadurch wird die Modellprüfpunktdatei nicht von Ihrer Festplatte gelöscht. Sie können sie bei Bedarf erneut hinzufügen.",
"customConfig": "Benutzerdefinierte Konfiguration",
"invokeRoot": "InvokeAI Ordner",
"formMessageDiffusersVAELocationDesc": "Falls nicht angegeben, sucht InvokeAI nach der VAE-Datei innerhalb des oben angegebenen Modell Speicherortes.",
"checkpointModels": "Kontrollpunkte"
},
"parameters": {
"images": "Bilder",
@ -370,7 +396,10 @@
"useInitImg": "Ausgangsbild verwenden",
"deleteImage": "Bild löschen",
"initialImage": "Ursprüngliches Bild",
"showOptionsPanel": "Optionsleiste zeigen"
"showOptionsPanel": "Optionsleiste zeigen",
"cancel": {
"setType": "Abbruchart festlegen"
}
},
"settings": {
"displayInProgress": "Bilder in Bearbeitung anzeigen",
@ -489,5 +518,25 @@
"betaDarkenOutside": "Außen abdunkeln",
"betaLimitToBox": "Begrenzung auf das Feld",
"betaPreserveMasked": "Maskiertes bewahren"
},
"accessibility": {
"modelSelect": "Model Auswahl",
"uploadImage": "Bild hochladen",
"previousImage": "Voriges Bild",
"useThisParameter": "Benutze diesen Parameter",
"copyMetadataJson": "Kopiere metadata JSON",
"zoomIn": "Vergrößern",
"rotateClockwise": "Im Uhrzeigersinn drehen",
"flipHorizontally": "Horizontal drehen",
"flipVertically": "Vertikal drehen",
"modifyConfig": "Optionen einstellen",
"toggleAutoscroll": "Auroscroll ein/ausschalten",
"toggleLogViewer": "Log Betrachter ein/ausschalten",
"showGallery": "Zeige Galerie",
"showOptionsPanel": "Zeige Optionen",
"reset": "Zurücksetzen",
"nextImage": "Nächstes Bild",
"zoomOut": "Verkleinern",
"rotateCounterClockwise": "Gegen den Uhrzeigersinn verdrehen"
}
}

29
invokeai/frontend/web/public/locales/en.json
View File

@ -8,7 +8,7 @@
"nextImage": "Next Image",
"useThisParameter": "Use this parameter",
"copyMetadataJson": "Copy metadata JSON",
"exitViewer": "ExitViewer",
"exitViewer": "Exit Viewer",
"zoomIn": "Zoom In",
"zoomOut": "Zoom Out",
"rotateCounterClockwise": "Rotate Counter-Clockwise",
@ -19,7 +19,8 @@
"toggleAutoscroll": "Toggle autoscroll",
"toggleLogViewer": "Toggle Log Viewer",
"showGallery": "Show Gallery",
"showOptionsPanel": "Show Options Panel"
"showOptionsPanel": "Show Options Panel",
"menu": "Menu"
},
"common": {
"hotkeysLabel": "Hotkeys",
@ -52,6 +53,7 @@
"txt2img": "Text To Image",
"img2img": "Image To Image",
"unifiedCanvas": "Unified Canvas",
"linear": "Linear",
"nodes": "Nodes",
"postprocessing": "Post Processing",
"nodesDesc": "A node based system for the generation of images is under development currently. Stay tuned for updates about this amazing feature.",
@ -61,7 +63,7 @@
"postProcessDesc3": "The Invoke AI Command Line Interface offers various other features including Embiggen.",
"training": "Training",
"trainingDesc1": "A dedicated workflow for training your own embeddings and checkpoints using Textual Inversion and Dreambooth from the web interface.",
"trainingDesc2": "InvokeAI already supports training custom embeddings using Textual Inversion using the main script.",
"trainingDesc2": "InvokeAI already supports training custom embeddourings using Textual Inversion using the main script.",
"upload": "Upload",
"close": "Close",
"cancel": "Cancel",
@ -95,7 +97,12 @@
"statusMergedModels": "Models Merged",
"pinOptionsPanel": "Pin Options Panel",
"loading": "Loading",
"loadingInvokeAI": "Loading Invoke AI"
"loadingInvokeAI": "Loading Invoke AI",
"random": "Random",
"generate": "Generate",
"openInNewTab": "Open in New Tab",
"dontAskMeAgain": "Don't ask me again",
"areYouSure": "Are you sure?"
},
"gallery": {
"generations": "Generations",
@ -111,7 +118,10 @@
"pinGallery": "Pin Gallery",
"allImagesLoaded": "All Images Loaded",
"loadMore": "Load More",
"noImagesInGallery": "No Images In Gallery"
"noImagesInGallery": "No Images In Gallery",
"deleteImage": "Delete Image",
"deleteImageBin": "Deleted images will be sent to your operating system's Bin.",
"deleteImagePermanent": "Deleted images cannot be restored."
},
"hotkeys": {
"keyboardShortcuts": "Keyboard Shortcuts",
@ -503,9 +513,10 @@
"useAll": "Use All",
"useInitImg": "Use Initial Image",
"info": "Info",
"deleteImage": "Delete Image",
"initialImage": "Initial Image",
"showOptionsPanel": "Show Options Panel"
"showOptionsPanel": "Show Options Panel",
"hidePreview": "Hide Preview",
"showPreview": "Show Preview"
},
"settings": {
"models": "Models",
@ -522,6 +533,10 @@
"resetComplete": "Web UI has been reset. Refresh the page to reload."
},
"toast": {
"serverError": "Server Error",
"disconnected": "Disconnected from Server",
"connected": "Connected to Server",
"canceled": "Processing Canceled",
"tempFoldersEmptied": "Temp Folder Emptied",
"uploadFailed": "Upload failed",
"uploadFailedMultipleImagesDesc": "Multiple images pasted, may only upload one image at a time",

16
invokeai/frontend/web/public/locales/es.json
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@ -73,7 +73,8 @@
"postprocessing": "Tratamiento posterior",
"txt2img": "De texto a imagen",
"accept": "Aceptar",
"cancel": "Cancelar"
"cancel": "Cancelar",
"linear": "Lineal"
},
"gallery": {
"generations": "Generaciones",
@ -483,7 +484,9 @@
"negativePrompts": "Preguntas negativas",
"imageToImage": "Imagen a imagen",
"denoisingStrength": "Intensidad de la eliminación del ruido",
"hiresStrength": "Alta resistencia"
"hiresStrength": "Alta resistencia",
"showPreview": "Mostrar la vista previa",
"hidePreview": "Ocultar la vista previa"
},
"settings": {
"models": "Modelos",
@ -529,7 +532,11 @@
"metadataLoadFailed": "Error al cargar metadatos",
"initialImageSet": "Imágen inicial establecida",
"initialImageNotSet": "Imagen inicial no establecida",
"initialImageNotSetDesc": "Error al establecer la imágen inicial"
"initialImageNotSetDesc": "Error al establecer la imágen inicial",
"serverError": "Error en el servidor",
"disconnected": "Desconectado del servidor",
"canceled": "Procesando la cancelación",
"connected": "Conectado al servidor"
},
"tooltip": {
"feature": {
@ -625,6 +632,7 @@
"toggleAutoscroll": "Activar el autodesplazamiento",
"toggleLogViewer": "Alternar el visor de registros",
"showGallery": "Mostrar galería",
"showOptionsPanel": "Mostrar el panel de opciones"
"showOptionsPanel": "Mostrar el panel de opciones",
"menu": "Menú"
}
}

122
invokeai/frontend/web/public/locales/fi.json Normal file
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@ -0,0 +1,122 @@
{
"accessibility": {
"reset": "Resetoi",
"useThisParameter": "Käytä tätä parametria",
"modelSelect": "Mallin Valinta",
"exitViewer": "Poistu katselimesta",
"uploadImage": "Lataa kuva",
"copyMetadataJson": "Kopioi metadata JSON:iin",
"invokeProgressBar": "Invoken edistymispalkki",
"nextImage": "Seuraava kuva",
"previousImage": "Edellinen kuva",
"zoomIn": "Lähennä",
"flipHorizontally": "Käännä vaakasuoraan",
"zoomOut": "Loitonna",
"rotateCounterClockwise": "Kierrä vastapäivään",
"rotateClockwise": "Kierrä myötäpäivään",
"flipVertically": "Käännä pystysuoraan",
"showGallery": "Näytä galleria",
"modifyConfig": "Muokkaa konfiguraatiota",
"toggleAutoscroll": "Kytke automaattinen vieritys",
"toggleLogViewer": "Kytke lokin katselutila",
"showOptionsPanel": "Näytä asetukset"
},
"common": {
"postProcessDesc2": "Erillinen käyttöliittymä tullaan julkaisemaan helpottaaksemme työnkulkua jälkikäsittelyssä.",
"training": "Kouluta",
"statusLoadingModel": "Ladataan mallia",
"statusModelChanged": "Malli vaihdettu",
"statusConvertingModel": "Muunnetaan mallia",
"statusModelConverted": "Malli muunnettu",
"langFrench": "Ranska",
"langItalian": "Italia",
"languagePickerLabel": "Kielen valinta",
"hotkeysLabel": "Pikanäppäimet",
"reportBugLabel": "Raportoi Bugista",
"langPolish": "Puola",
"themeLabel": "Teema",
"langDutch": "Hollanti",
"settingsLabel": "Asetukset",
"githubLabel": "Github",
"darkTheme": "Tumma",
"lightTheme": "Vaalea",
"greenTheme": "Vihreä",
"langGerman": "Saksa",
"langPortuguese": "Portugali",
"discordLabel": "Discord",
"langEnglish": "Englanti",
"oceanTheme": "Meren sininen",
"langRussian": "Venäjä",
"langUkranian": "Ukraina",
"langSpanish": "Espanja",
"upload": "Lataa",
"statusMergedModels": "Mallit yhdistelty",
"img2img": "Kuva kuvaksi",
"nodes": "Solmut",
"nodesDesc": "Solmupohjainen järjestelmä kuvien generoimiseen on parhaillaan kehitteillä. Pysy kuulolla päivityksistä tähän uskomattomaan ominaisuuteen liittyen.",
"postProcessDesc1": "Invoke AI tarjoaa monenlaisia jälkikäsittelyominaisuukisa. Kuvan laadun skaalaus sekä kasvojen korjaus ovat jo saatavilla WebUI:ssä. Voit ottaa ne käyttöön lisäasetusten valikosta teksti kuvaksi sekä kuva kuvaksi -välilehdiltä. Voit myös suoraan prosessoida kuvia käyttämällä kuvan toimintapainikkeita nykyisen kuvan yläpuolella tai tarkastelussa.",
"postprocessing": "Jälkikäsitellään",
"postProcessing": "Jälkikäsitellään",
"cancel": "Peruuta",
"close": "Sulje",
"accept": "Hyväksy",
"statusConnected": "Yhdistetty",
"statusError": "Virhe",
"statusProcessingComplete": "Prosessointi valmis",
"load": "Lataa",
"back": "Takaisin",
"statusGeneratingTextToImage": "Generoidaan tekstiä kuvaksi",
"trainingDesc2": "InvokeAI tukee jo mukautettujen upotusten kouluttamista tekstin inversiolla käyttäen pääskriptiä.",
"statusDisconnected": "Yhteys katkaistu",
"statusPreparing": "Valmistellaan",
"statusIterationComplete": "Iteraatio valmis",
"statusMergingModels": "Yhdistellään malleja",
"statusProcessingCanceled": "Valmistelu peruutettu",
"statusSavingImage": "Tallennetaan kuvaa",
"statusGeneratingImageToImage": "Generoidaan kuvaa kuvaksi",
"statusRestoringFacesGFPGAN": "Korjataan kasvoja (GFPGAN)",
"statusRestoringFacesCodeFormer": "Korjataan kasvoja (CodeFormer)",
"statusGeneratingInpainting": "Generoidaan sisällemaalausta",
"statusGeneratingOutpainting": "Generoidaan ulosmaalausta",
"statusRestoringFaces": "Korjataan kasvoja",
"pinOptionsPanel": "Kiinnitä asetukset -paneeli",
"loadingInvokeAI": "Ladataan Invoke AI:ta",
"loading": "Ladataan",
"statusGenerating": "Generoidaan",
"txt2img": "Teksti kuvaksi",
"trainingDesc1": "Erillinen työnkulku omien upotusten ja tarkastuspisteiden kouluttamiseksi käyttäen tekstin inversiota ja dreamboothia selaimen käyttöliittymässä.",
"postProcessDesc3": "Invoke AI:n komentorivi tarjoaa paljon muita ominaisuuksia, kuten esimerkiksi Embiggenin.",
"unifiedCanvas": "Yhdistetty kanvas",
"statusGenerationComplete": "Generointi valmis"
},
"gallery": {
"uploads": "Lataukset",
"showUploads": "Näytä lataukset",
"galleryImageResetSize": "Resetoi koko",
"maintainAspectRatio": "Säilytä kuvasuhde",
"galleryImageSize": "Kuvan koko",
"pinGallery": "Kiinnitä galleria",
"showGenerations": "Näytä generaatiot",
"singleColumnLayout": "Yhden sarakkeen asettelu",
"generations": "Generoinnit",
"gallerySettings": "Gallerian asetukset",
"autoSwitchNewImages": "Vaihda uusiin kuviin automaattisesti",
"allImagesLoaded": "Kaikki kuvat ladattu",
"noImagesInGallery": "Ei kuvia galleriassa",
"loadMore": "Lataa lisää"
},
"hotkeys": {
"keyboardShortcuts": "näppäimistön pikavalinnat",
"appHotkeys": "Sovelluksen pikanäppäimet",
"generalHotkeys": "Yleiset pikanäppäimet",
"galleryHotkeys": "Gallerian pikanäppäimet",
"unifiedCanvasHotkeys": "Yhdistetyn kanvaan pikanäppäimet",
"cancel": {
"desc": "Peruuta kuvan luominen",
"title": "Peruuta"
},
"invoke": {
"desc": "Luo kuva"
}
}
}

16
invokeai/frontend/web/public/locales/it.json
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@ -73,7 +73,8 @@
"postprocessing": "Post Elaborazione",
"txt2img": "Testo a Immagine",
"accept": "Accetta",
"cancel": "Annulla"
"cancel": "Annulla",
"linear": "Lineare"
},
"gallery": {
"generations": "Generazioni",
@ -483,7 +484,9 @@
},
"hSymmetryStep": "Passi Simmetria Orizzontale",
"vSymmetryStep": "Passi Simmetria Verticale",
"symmetry": "Simmetria"
"symmetry": "Simmetria",
"hidePreview": "Nascondi l'anteprima",
"showPreview": "Mostra l'anteprima"
},
"settings": {
"models": "Modelli",
@ -529,7 +532,11 @@
"metadataLoadFailed": "Impossibile caricare i metadati",
"initialImageSet": "Immagine iniziale impostata",
"initialImageNotSet": "Immagine iniziale non impostata",
"initialImageNotSetDesc": "Impossibile caricare l'immagine iniziale"
"initialImageNotSetDesc": "Impossibile caricare l'immagine iniziale",
"serverError": "Errore del Server",
"disconnected": "Disconnesso dal Server",
"connected": "Connesso al Server",
"canceled": "Elaborazione annullata"
},
"tooltip": {
"feature": {
@ -625,6 +632,7 @@
"showOptionsPanel": "Mostra il pannello opzioni",
"flipVertically": "Capovolgi verticalmente",
"toggleAutoscroll": "Attiva/disattiva lo scorrimento automatico",
"modifyConfig": "Modifica configurazione"
"modifyConfig": "Modifica configurazione",
"menu": "Menu"
}
}

73
invokeai/frontend/web/public/locales/ja.json
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@ -37,7 +37,43 @@
"statusUpscaling": "アップスケーリング",
"statusUpscalingESRGAN": "アップスケーリング (ESRGAN)",
"statusLoadingModel": "モデルを読み込む",
"statusModelChanged": "モデルを変更"
"statusModelChanged": "モデルを変更",
"cancel": "キャンセル",
"accept": "同意",
"langBrPortuguese": "Português do Brasil",
"langRussian": "Русский",
"langSimplifiedChinese": "简体中文",
"langUkranian": "Украї́нська",
"langSpanish": "Español",
"img2img": "img2img",
"unifiedCanvas": "Unified Canvas",
"statusMergingModels": "モデルのマージ",
"statusModelConverted": "変換済モデル",
"statusGeneratingInpainting": "Inpaintingを生成",
"statusIterationComplete": "Iteration Complete",
"statusGeneratingOutpainting": "Outpaintingを生成",
"loading": "ロード中",
"loadingInvokeAI": "Invoke AIをロード中",
"statusConvertingModel": "モデルの変換",
"statusMergedModels": "マージ済モデル",
"pinOptionsPanel": "オプションパネルを固定",
"githubLabel": "Github",
"hotkeysLabel": "ホットキー",
"langHebrew": "עברית",
"discordLabel": "Discord",
"langItalian": "Italiano",
"langEnglish": "English",
"oceanTheme": "オーシャン",
"langArabic": "アラビア語",
"langDutch": "Nederlands",
"langFrench": "Français",
"langGerman": "Deutsch",
"langPortuguese": "Português",
"nodes": "ノード",
"langKorean": "한국어",
"langPolish": "Polski",
"txt2img": "txt2img",
"postprocessing": "Post Processing"
},
"gallery": {
"uploads": "アップロード",
@ -46,11 +82,14 @@
"galleryImageResetSize": "サイズをリセット",
"gallerySettings": "ギャラリーの設定",
"maintainAspectRatio": "アスペクト比を維持",
"singleColumnLayout": "シングルカラムレイアウト",
"singleColumnLayout": "1カラムレイアウト",
"pinGallery": "ギャラリーにピン留め",
"allImagesLoaded": "すべての画像を読み込む",
"loadMore": "さらに読み込む",
"noImagesInGallery": "ギャラリーに画像がありません"
"noImagesInGallery": "ギャラリーに画像がありません",
"generations": "生成",
"showGenerations": "生成過程を見る",
"autoSwitchNewImages": "新しい画像に自動切替"
},
"hotkeys": {
"keyboardShortcuts": "キーボードショートカット",
@ -59,14 +98,16 @@
"galleryHotkeys": "ギャラリーのホットキー",
"unifiedCanvasHotkeys": "Unified Canvasのホットキー",
"invoke": {
"desc": "画像を生成"
"desc": "画像を生成",
"title": "Invoke"
},
"cancel": {
"title": "キャンセル",
"desc": "画像の生成をキャンセル"
},
"focusPrompt": {
"desc": "プロンプトテキストボックスにフォーカス"
"desc": "プロンプトテキストボックスにフォーカス",
"title": "プロジェクトにフォーカス"
},
"toggleOptions": {
"title": "オプションパネルのトグル",
@ -410,5 +451,27 @@
"accept": "同意",
"showHide": "表示/非表示",
"discardAll": "すべて破棄"
},
"accessibility": {
"modelSelect": "モデルを選択",
"invokeProgressBar": "進捗バー",
"reset": "リセット",
"uploadImage": "画像をアップロード",
"previousImage": "前の画像",
"nextImage": "次の画像",
"useThisParameter": "このパラメータを使用する",
"copyMetadataJson": "メタデータをコピー(JSON)",
"zoomIn": "ズームイン",
"exitViewer": "ExitViewer",
"zoomOut": "ズームアウト",
"rotateCounterClockwise": "反時計回りに回転",
"rotateClockwise": "時計回りに回転",
"flipHorizontally": "水平方向に反転",
"flipVertically": "垂直方向に反転",
"toggleAutoscroll": "自動スクロールの切替",
"modifyConfig": "Modify Config",
"toggleLogViewer": "Log Viewerの切替",
"showGallery": "ギャラリーを表示",
"showOptionsPanel": "オプションパネルを表示"
}
}

1
invokeai/frontend/web/public/locales/mn.json Normal file
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@ -0,0 +1 @@
{}

47
invokeai/frontend/web/public/locales/nl.json
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@ -62,7 +62,18 @@
"statusConvertingModel": "Omzetten van model",
"statusModelConverted": "Model omgezet",
"statusMergingModels": "Samenvoegen van modellen",
"statusMergedModels": "Modellen samengevoegd"
"statusMergedModels": "Modellen samengevoegd",
"cancel": "Annuleer",
"accept": "Akkoord",
"langPortuguese": "Português",
"pinOptionsPanel": "Zet deelscherm Opties vast",
"loading": "Bezig met laden",
"loadingInvokeAI": "Bezig met laden van Invoke AI",
"oceanTheme": "Oceaan",
"langHebrew": "עברית",
"langKorean": "한국어",
"txt2img": "Tekst naar afbeelding",
"postprocessing": "Nabewerking"
},
"gallery": {
"generations": "Gegenereerde afbeeldingen",
@ -301,7 +312,7 @@
"name": "Naam",
"nameValidationMsg": "Geef een naam voor je model",
"description": "Beschrijving",
"descriptionValidationMsg": "Voeg een beschrijving toe voor je model.",
"descriptionValidationMsg": "Voeg een beschrijving toe voor je model",
"config": "Configuratie",
"configValidationMsg": "Pad naar het configuratiebestand van je model.",
"modelLocation": "Locatie model",
@ -391,7 +402,13 @@
"modelMergeInterpAddDifferenceHelp": "In deze stand wordt model 3 eerst van model 2 afgehaald. Wat daar uitkomt wordt gemengd met model 1, gebruikmakend van de hierboven ingestelde alfawaarde.",
"inverseSigmoid": "Keer Sigmoid om",
"sigmoid": "Sigmoid",
"weightedSum": "Gewogen som"
"weightedSum": "Gewogen som",
"v2_base": "v2 (512px)",
"v2_768": "v2 (768px)",
"none": "geen",
"addDifference": "Voeg verschil toe",
"scanForModels": "Scan naar modellen",
"pickModelType": "Kies modelsoort"
},
"parameters": {
"images": "Afbeeldingen",
@ -561,7 +578,7 @@
"autoSaveToGallery": "Bewaar automatisch naar galerij",
"saveBoxRegionOnly": "Bewaar alleen tekengebied",
"limitStrokesToBox": "Beperk streken tot tekenvak",
"showCanvasDebugInfo": "Toon foutopsporingsgegevens canvas",
"showCanvasDebugInfo": "Toon aanvullende canvasgegevens",
"clearCanvasHistory": "Wis canvasgeschiedenis",
"clearHistory": "Wis geschiedenis",
"clearCanvasHistoryMessage": "Het wissen van de canvasgeschiedenis laat het huidige canvas ongemoeid, maar wist onherstelbaar de geschiedenis voor het ongedaan maken en herhalen.",
@ -587,5 +604,27 @@
"betaDarkenOutside": "Verduister buiten tekenvak",
"betaLimitToBox": "Beperk tot tekenvak",
"betaPreserveMasked": "Behoud masker"
},
"accessibility": {
"exitViewer": "Stop viewer",
"zoomIn": "Zoom in",
"rotateCounterClockwise": "Draai tegen de klok in",
"modelSelect": "Modelkeuze",
"invokeProgressBar": "Voortgangsbalk Invoke",
"reset": "Herstel",
"uploadImage": "Upload afbeelding",
"previousImage": "Vorige afbeelding",
"nextImage": "Volgende afbeelding",
"useThisParameter": "Gebruik deze parameter",
"copyMetadataJson": "Kopieer metagegevens-JSON",
"zoomOut": "Zoom uit",
"rotateClockwise": "Draai met de klok mee",
"flipHorizontally": "Spiegel horizontaal",
"flipVertically": "Spiegel verticaal",
"modifyConfig": "Wijzig configuratie",
"toggleAutoscroll": "Autom. scrollen aan/uit",
"toggleLogViewer": "Logboekviewer aan/uit",
"showGallery": "Toon galerij",
"showOptionsPanel": "Toon deelscherm Opties"
}
}

136
invokeai/frontend/web/public/locales/ru.json
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@ -9,7 +9,7 @@
"lightTheme": "Светлая",
"greenTheme": "Зеленая",
"img2img": "Изображение в изображение (img2img)",
"unifiedCanvas": "Универсальный холст",
"unifiedCanvas": "Единый холст",
"nodes": "Ноды",
"langRussian": "Русский",
"nodesDesc": "Cистема генерации изображений на основе нодов (узлов) уже разрабатывается. Следите за новостями об этой замечательной функции.",
@ -53,7 +53,28 @@
"loading": "Загрузка",
"loadingInvokeAI": "Загрузка Invoke AI",
"back": "Назад",
"statusConvertingModel": "Конвертация модели"
"statusConvertingModel": "Конвертация модели",
"cancel": "Отменить",
"accept": "Принять",
"oceanTheme": "Океан",
"langUkranian": "Украинский",
"langEnglish": "Английский",
"postprocessing": "Постобработка",
"langArabic": "Арабский",
"langSpanish": "Испанский",
"langSimplifiedChinese": "Китайский (упрощенный)",
"langDutch": "Нидерландский",
"langFrench": "Французский",
"langGerman": "Немецкий",
"langHebrew": "Иврит",
"langItalian": "Итальянский",
"langJapanese": "Японский",
"langKorean": "Корейский",
"langPolish": "Польский",
"langPortuguese": "Португальский",
"txt2img": "Текст в изображение (txt2img)",
"langBrPortuguese": "Португальский (Бразилия)",
"linear": "Линейная обработка"
},
"gallery": {
"generations": "Генерации",
@ -72,11 +93,11 @@
"noImagesInGallery": "Изображений нет"
},
"hotkeys": {
"keyboardShortcuts": "Клавиатурные сокращения",
"keyboardShortcuts": "Горячие клавиши",
"appHotkeys": "Горячие клавиши приложения",
"generalHotkeys": "Общие горячие клавиши",
"galleryHotkeys": "Горячие клавиши галереи",
"unifiedCanvasHotkeys": "Горячие клавиши универсального холста",
"unifiedCanvasHotkeys": "Горячие клавиши Единого холста",
"invoke": {
"title": "Invoke",
"desc": "Сгенерировать изображение"
@ -266,12 +287,12 @@
"desc": "Сбросить вид холста"
},
"previousStagingImage": {
"title": "Previous Staging Image",
"desc": "Предыдущее изображение"
"title": "Предыдущее изображение",
"desc": "Предыдущая область изображения"
},
"nextStagingImage": {
"title": "Next Staging Image",
"desc": "Следующее изображение"
"title": "Следующее изображение",
"desc": "Следующая область изображения"
},
"acceptStagingImage": {
"title": "Принять изображение",
@ -353,7 +374,42 @@
"modelConverted": "Модель преобразована",
"invokeRoot": "Каталог InvokeAI",
"modelsMerged": "Модели объединены",
"mergeModels": "Объединить модели"
"mergeModels": "Объединить модели",
"scanForModels": "Просканировать модели",
"sigmoid": "Сигмоид",
"formMessageDiffusersModelLocation": "Расположение Diffusers-модели",
"modelThree": "Модель 3",
"modelMergeHeaderHelp2": "Только Diffusers-модели доступны для объединения. Если вы хотите объединить checkpoint-модели, сначала преобразуйте их в Diffusers.",
"pickModelType": "Выбрать тип модели",
"formMessageDiffusersVAELocation": "Расположение VAE",
"v1": "v1",
"convertToDiffusersSaveLocation": "Путь сохранения",
"customSaveLocation": "Пользовательский путь сохранения",
"alpha": "Альфа",
"diffusersModels": "Diffusers",
"customConfig": "Пользовательский конфиг",
"pathToCustomConfig": "Путь к пользовательскому конфигу",
"inpainting": "v1 Inpainting",
"sameFolder": "В ту же папку",
"modelOne": "Модель 1",
"mergedModelCustomSaveLocation": "Пользовательский путь",
"none": "пусто",
"addDifference": "Добавить разницу",
"vaeRepoIDValidationMsg": "Онлайн репозиторий VAE",
"convertToDiffusersHelpText2": "Этот процесс заменит вашу запись в Model Manager на версию той же модели в Diffusers.",
"custom": "Пользовательский",
"modelTwo": "Модель 2",
"mergedModelSaveLocation": "Путь сохранения",
"merge": "Объединить",
"interpolationType": "Тип интерполяции",
"modelMergeInterpAddDifferenceHelp": "В этом режиме Модель 3 сначала вычитается из Модели 2. Результирующая версия смешивается с Моделью 1 с установленным выше коэффициентом Альфа.",
"modelMergeHeaderHelp1": "Вы можете объединить до трех разных моделей, чтобы создать смешанную, соответствующую вашим потребностям.",
"modelMergeAlphaHelp": "Альфа влияет на силу смешивания моделей. Более низкие значения альфа приводят к меньшему влиянию второй модели.",
"inverseSigmoid": "Обратный Сигмоид",
"weightedSum": "Взвешенная сумма",
"safetensorModels": "SafeTensors",
"v2_768": "v2 (768px)",
"v2_base": "v2 (512px)"
},
"parameters": {
"images": "Изображения",
@ -380,7 +436,7 @@
"scale": "Масштаб",
"otherOptions": "Другие параметры",
"seamlessTiling": "Бесшовный узор",
"hiresOptim": "Высокое разрешение",
"hiresOptim": "Оптимизация High Res",
"imageFit": "Уместить изображение",
"codeformerFidelity": "Точность",
"seamSize": "Размер шва",
@ -397,11 +453,11 @@
"infillScalingHeader": "Заполнение и масштабирование",
"img2imgStrength": "Сила обработки img2img",
"toggleLoopback": "Зациклить обработку",
"invoke": "Вызвать",
"invoke": "Invoke",
"promptPlaceholder": "Введите запрос здесь (на английском). [исключенные токены], (более значимые)++, (менее значимые)--, swap и blend тоже доступны (смотрите Github)",
"sendTo": "Отправить",
"sendToImg2Img": "Отправить в img2img",
"sendToUnifiedCanvas": "Отправить на холст",
"sendToUnifiedCanvas": "Отправить на Единый холст",
"copyImageToLink": "Скопировать ссылку",
"downloadImage": "Скачать",
"openInViewer": "Открыть в просмотрщике",
@ -413,7 +469,24 @@
"info": "Метаданные",
"deleteImage": "Удалить изображение",
"initialImage": "Исходное изображение",
"showOptionsPanel": "Показать панель настроек"
"showOptionsPanel": "Показать панель настроек",
"vSymmetryStep": "Шаг верт. симметрии",
"cancel": {
"immediate": "Отменить немедленно",
"schedule": "Отменить после текущей итерации",
"isScheduled": "Отмена",
"setType": "Установить тип отмены"
},
"general": "Основное",
"hiresStrength": "Сила High Res",
"symmetry": "Симметрия",
"hSymmetryStep": "Шаг гор. симметрии",
"hidePreview": "Скрыть предпросмотр",
"imageToImage": "Изображение в изображение",
"denoisingStrength": "Сила шумоподавления",
"copyImage": "Скопировать изображение",
"negativePrompts": "Исключающий запрос",
"showPreview": "Показать предпросмотр"
},
"settings": {
"models": "Модели",
@ -423,10 +496,11 @@
"displayHelpIcons": "Показывать значки подсказок",
"useCanvasBeta": "Показывать инструменты слева (Beta UI)",
"enableImageDebugging": "Включить отладку",
"resetWebUI": "Вернуть умолчания",
"resetWebUI": "Сброс настроек Web UI",
"resetWebUIDesc1": "Сброс настроек веб-интерфейса удаляет только локальный кэш браузера с вашими изображениями и настройками. Он не удаляет изображения с диска.",
"resetWebUIDesc2": "Если изображения не отображаются в галерее или не работает что-то еще, пожалуйста, попробуйте сбросить настройки, прежде чем сообщать о проблеме на GitHub.",
"resetComplete": "Интерфейс сброшен. Обновите эту страницу."
"resetComplete": "Интерфейс сброшен. Обновите эту страницу.",
"useSlidersForAll": "Использовать ползунки для всех параметров"
},
"toast": {
"tempFoldersEmptied": "Временная папка очищена",
@ -441,7 +515,7 @@
"imageSavedToGallery": "Изображение сохранено в галерею",
"canvasMerged": "Холст объединен",
"sentToImageToImage": "Отправить в img2img",
"sentToUnifiedCanvas": "Отправить на холст",
"sentToUnifiedCanvas": "Отправлено на Единый холст",
"parametersSet": "Параметры заданы",
"parametersNotSet": "Параметры не заданы",
"parametersNotSetDesc": "Не найдены метаданные изображения.",
@ -458,7 +532,11 @@
"metadataLoadFailed": "Не удалось загрузить метаданные",
"initialImageSet": "Исходное изображение задано",
"initialImageNotSet": "Исходное изображение не задано",
"initialImageNotSetDesc": "Не получилось загрузить исходное изображение"
"initialImageNotSetDesc": "Не получилось загрузить исходное изображение",
"serverError": "Ошибка сервера",
"disconnected": "Отключено от сервера",
"connected": "Подключено к серверу",
"canceled": "Обработка отменена"
},
"tooltip": {
"feature": {
@ -507,7 +585,7 @@
"autoSaveToGallery": "Автосохранение в галерее",
"saveBoxRegionOnly": "Сохранять только выделение",
"limitStrokesToBox": "Ограничить штрихи выделением",
"showCanvasDebugInfo": "Показать отладку холста",
"showCanvasDebugInfo": "Показать доп. информацию о холсте",
"clearCanvasHistory": "Очистить историю холста",
"clearHistory": "Очистить историю",
"clearCanvasHistoryMessage": "Очистка истории холста оставляет текущий холст нетронутым, но удаляет историю отмен и повторов.",
@ -535,6 +613,26 @@
"betaPreserveMasked": "Сохранять маскируемую область"
},
"accessibility": {
"modelSelect": "Выбор модели"
"modelSelect": "Выбор модели",
"uploadImage": "Загрузить изображение",
"nextImage": "Следующее изображение",
"previousImage": "Предыдущее изображение",
"zoomIn": "Приблизить",
"zoomOut": "Отдалить",
"rotateClockwise": "Повернуть по часовой стрелке",
"rotateCounterClockwise": "Повернуть против часовой стрелки",
"flipVertically": "Перевернуть вертикально",
"flipHorizontally": "Отразить горизонтально",
"toggleAutoscroll": "Включить автопрокрутку",
"toggleLogViewer": "Показать или скрыть просмотрщик логов",
"showOptionsPanel": "Показать опции",
"showGallery": "Показать галерею",
"invokeProgressBar": "Индикатор выполнения",
"reset": "Сброс",
"modifyConfig": "Изменить конфиг",
"useThisParameter": "Использовать этот параметр",
"copyMetadataJson": "Скопировать метаданные JSON",
"exitViewer": "Закрыть просмотрщик",
"menu": "Меню"
}
}

254
invokeai/frontend/web/public/locales/sv.json Normal file
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@ -0,0 +1,254 @@
{
"accessibility": {
"copyMetadataJson": "Kopiera metadata JSON",
"zoomIn": "Zooma in",
"exitViewer": "Avslutningsvisare",
"modelSelect": "Välj modell",
"uploadImage": "Ladda upp bild",
"invokeProgressBar": "Invoke förloppsmätare",
"nextImage": "Nästa bild",
"toggleAutoscroll": "Växla automatisk rullning",
"flipHorizontally": "Vänd vågrätt",
"flipVertically": "Vänd lodrätt",
"zoomOut": "Zooma ut",
"toggleLogViewer": "Växla logvisare",
"reset": "Starta om",
"previousImage": "Föregående bild",
"useThisParameter": "Använd denna parametern",
"showGallery": "Visa galleri",
"rotateCounterClockwise": "Rotera moturs",
"rotateClockwise": "Rotera medurs",
"modifyConfig": "Ändra konfiguration",
"showOptionsPanel": "Visa inställningspanelen"
},
"common": {
"hotkeysLabel": "Snabbtangenter",
"reportBugLabel": "Rapportera bugg",
"githubLabel": "Github",
"discordLabel": "Discord",
"settingsLabel": "Inställningar",
"darkTheme": "Mörk",
"lightTheme": "Ljus",
"greenTheme": "Grön",
"oceanTheme": "Hav",
"langEnglish": "Engelska",
"langDutch": "Nederländska",
"langFrench": "Franska",
"langGerman": "Tyska",
"langItalian": "Italienska",
"langArabic": "العربية",
"langHebrew": "עברית",
"langPolish": "Polski",
"langPortuguese": "Português",
"langBrPortuguese": "Português do Brasil",
"langSimplifiedChinese": "简体中文",
"langJapanese": "日本語",
"langKorean": "한국어",
"langRussian": "Русский",
"unifiedCanvas": "Förenad kanvas",
"nodesDesc": "Ett nodbaserat system för bildgenerering är under utveckling. Håll utkik för uppdateringar om denna fantastiska funktion.",
"langUkranian": "Украї́нська",
"langSpanish": "Español",
"postProcessDesc2": "Ett dedikerat användargränssnitt kommer snart att släppas för att underlätta mer avancerade arbetsflöden av efterbehandling.",
"trainingDesc1": "Ett dedikerat arbetsflöde för träning av dina egna inbäddningar och kontrollpunkter genom Textual Inversion eller Dreambooth från webbgränssnittet.",
"trainingDesc2": "InvokeAI stöder redan träning av anpassade inbäddningar med hjälp av Textual Inversion genom huvudscriptet.",
"upload": "Ladda upp",
"close": "Stäng",
"cancel": "Avbryt",
"accept": "Acceptera",
"statusDisconnected": "Frånkopplad",
"statusGeneratingTextToImage": "Genererar text till bild",
"statusGeneratingImageToImage": "Genererar Bild till bild",
"statusGeneratingInpainting": "Genererar Måla i",
"statusGenerationComplete": "Generering klar",
"statusModelConverted": "Modell konverterad",
"statusMergingModels": "Sammanfogar modeller",
"pinOptionsPanel": "Nåla fast inställningspanelen",
"loading": "Laddar",
"loadingInvokeAI": "Laddar Invoke AI",
"statusRestoringFaces": "Återskapar ansikten",
"languagePickerLabel": "Språkväljare",
"themeLabel": "Tema",
"txt2img": "Text till bild",
"nodes": "Noder",
"img2img": "Bild till bild",
"postprocessing": "Efterbehandling",
"postProcessing": "Efterbehandling",
"load": "Ladda",
"training": "Träning",
"postProcessDesc1": "Invoke AI erbjuder ett brett utbud av efterbehandlingsfunktioner. Uppskalning och ansiktsåterställning finns redan tillgängligt i webbgränssnittet. Du kommer åt dem ifrån Avancerade inställningar-menyn under Bild till bild-fliken. Du kan också behandla bilder direkt genom att använda knappen bildåtgärder ovanför nuvarande bild eller i bildvisaren.",
"postProcessDesc3": "Invoke AI's kommandotolk erbjuder många olika funktioner, bland annat \"Förstora\".",
"statusGenerating": "Genererar",
"statusError": "Fel",
"back": "Bakåt",
"statusConnected": "Ansluten",
"statusPreparing": "Förbereder",
"statusProcessingCanceled": "Bearbetning avbruten",
"statusProcessingComplete": "Bearbetning färdig",
"statusGeneratingOutpainting": "Genererar Fyll ut",
"statusIterationComplete": "Itterering klar",
"statusSavingImage": "Sparar bild",
"statusRestoringFacesGFPGAN": "Återskapar ansikten (GFPGAN)",
"statusRestoringFacesCodeFormer": "Återskapar ansikten (CodeFormer)",
"statusUpscaling": "Skala upp",
"statusUpscalingESRGAN": "Uppskalning (ESRGAN)",
"statusModelChanged": "Modell ändrad",
"statusLoadingModel": "Laddar modell",
"statusConvertingModel": "Konverterar modell",
"statusMergedModels": "Modeller sammanfogade"
},
"gallery": {
"generations": "Generationer",
"showGenerations": "Visa generationer",
"uploads": "Uppladdningar",
"showUploads": "Visa uppladdningar",
"galleryImageSize": "Bildstorlek",
"allImagesLoaded": "Alla bilder laddade",
"loadMore": "Ladda mer",
"galleryImageResetSize": "Återställ storlek",
"gallerySettings": "Galleriinställningar",
"maintainAspectRatio": "Behåll bildförhållande",
"pinGallery": "Nåla fast galleri",
"noImagesInGallery": "Inga bilder i galleriet",
"autoSwitchNewImages": "Ändra automatiskt till nya bilder",
"singleColumnLayout": "Enkolumnslayout"
},
"hotkeys": {
"generalHotkeys": "Allmänna snabbtangenter",
"galleryHotkeys": "Gallerisnabbtangenter",
"unifiedCanvasHotkeys": "Snabbtangenter för sammanslagskanvas",
"invoke": {
"title": "Anropa",
"desc": "Genererar en bild"
},
"cancel": {
"title": "Avbryt",
"desc": "Avbryt bildgenerering"
},
"focusPrompt": {
"desc": "Fokusera området för promptinmatning",
"title": "Fokusprompt"
},
"pinOptions": {
"desc": "Nåla fast alternativpanelen",
"title": "Nåla fast alternativ"
},
"toggleOptions": {
"title": "Växla inställningar",
"desc": "Öppna och stäng alternativpanelen"
},
"toggleViewer": {
"title": "Växla visaren",
"desc": "Öppna och stäng bildvisaren"
},
"toggleGallery": {
"title": "Växla galleri",
"desc": "Öppna eller stäng galleribyrån"
},
"maximizeWorkSpace": {
"title": "Maximera arbetsyta",
"desc": "Stäng paneler och maximera arbetsyta"
},
"changeTabs": {
"title": "Växla flik",
"desc": "Byt till en annan arbetsyta"
},
"consoleToggle": {
"title": "Växla konsol",
"desc": "Öppna och stäng konsol"
},
"setSeed": {
"desc": "Använd seed för nuvarande bild",
"title": "välj seed"
},
"setParameters": {
"title": "Välj parametrar",
"desc": "Använd alla parametrar från nuvarande bild"
},
"setPrompt": {
"desc": "Använd prompt för nuvarande bild",
"title": "Välj prompt"
},
"restoreFaces": {
"title": "Återskapa ansikten",
"desc": "Återskapa nuvarande bild"
},
"upscale": {
"title": "Skala upp",
"desc": "Skala upp nuvarande bild"
},
"showInfo": {
"title": "Visa info",
"desc": "Visa metadata för nuvarande bild"
},
"sendToImageToImage": {
"title": "Skicka till Bild till bild",
"desc": "Skicka nuvarande bild till Bild till bild"
},
"deleteImage": {
"title": "Radera bild",
"desc": "Radera nuvarande bild"
},
"closePanels": {
"title": "Stäng paneler",
"desc": "Stäng öppna paneler"
},
"previousImage": {
"title": "Föregående bild",
"desc": "Visa föregående bild"
},
"nextImage": {
"title": "Nästa bild",
"desc": "Visa nästa bild"
},
"toggleGalleryPin": {
"title": "Växla gallerinål",
"desc": "Nålar fast eller nålar av galleriet i gränssnittet"
},
"increaseGalleryThumbSize": {
"title": "Förstora galleriets bildstorlek",
"desc": "Förstora miniatyrbildernas storlek"
},
"decreaseGalleryThumbSize": {
"title": "Minska gelleriets bildstorlek",
"desc": "Minska miniatyrbildernas storlek i galleriet"
},
"decreaseBrushSize": {
"desc": "Förminska storleken på kanvas- pensel eller suddgummi",
"title": "Minska penselstorlek"
},
"increaseBrushSize": {
"title": "Öka penselstorlek",
"desc": "Öka stoleken på kanvas- pensel eller suddgummi"
},
"increaseBrushOpacity": {
"title": "Öka penselns opacitet",
"desc": "Öka opaciteten för kanvaspensel"
},
"decreaseBrushOpacity": {
"desc": "Minska kanvaspenselns opacitet",
"title": "Minska penselns opacitet"
},
"moveTool": {
"title": "Flytta",
"desc": "Tillåt kanvasnavigation"
},
"fillBoundingBox": {
"title": "Fyll ram",
"desc": "Fyller ramen med pensels färg"
},
"keyboardShortcuts": "Snabbtangenter",
"appHotkeys": "Appsnabbtangenter",
"selectBrush": {
"desc": "Välj kanvaspensel",
"title": "Välj pensel"
},
"selectEraser": {
"desc": "Välj kanvassuddgummi",
"title": "Välj suddgummi"
},
"eraseBoundingBox": {
"title": "Ta bort ram"
}
}
}

64
invokeai/frontend/web/public/locales/tr.json Normal file
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@ -0,0 +1,64 @@
{
"accessibility": {
"invokeProgressBar": "Invoke ilerleme durumu",
"nextImage": "Sonraki Resim",
"useThisParameter": "Kullanıcı parametreleri",
"copyMetadataJson": "Metadata verilerini kopyala (JSON)",
"exitViewer": "Görüntüleme Modundan Çık",
"zoomIn": "Yakınlaştır",
"zoomOut": "Uzaklaştır",
"rotateCounterClockwise": "Döndür (Saat yönünün tersine)",
"rotateClockwise": "Döndür (Saat yönünde)",
"flipHorizontally": "Yatay Çevir",
"flipVertically": "Dikey Çevir",
"modifyConfig": "Ayarları Değiştir",
"toggleAutoscroll": "Otomatik kaydırmayı aç/kapat",
"toggleLogViewer": "Günlük Görüntüleyici Aç/Kapa",
"showOptionsPanel": "Ayarlar Panelini Göster",
"modelSelect": "Model Seçin",
"reset": "Sıfırla",
"uploadImage": "Resim Yükle",
"previousImage": "Önceki Resim",
"menu": "Menü",
"showGallery": "Galeriyi Göster"
},
"common": {
"hotkeysLabel": "Kısayol Tuşları",
"themeLabel": "Tema",
"languagePickerLabel": "Dil Seçimi",
"reportBugLabel": "Hata Bildir",
"githubLabel": "Github",
"discordLabel": "Discord",
"settingsLabel": "Ayarlar",
"darkTheme": "Karanlık Tema",
"lightTheme": "Aydınlık Tema",
"greenTheme": "Yeşil Tema",
"oceanTheme": "Okyanus Tema",
"langArabic": "Arapça",
"langEnglish": "İngilizce",
"langDutch": "Hollandaca",
"langFrench": "Fransızca",
"langGerman": "Almanca",
"langItalian": "İtalyanca",
"langJapanese": "Japonca",
"langPolish": "Lehçe",
"langPortuguese": "Portekizce",
"langBrPortuguese": "Portekizcr (Brezilya)",
"langRussian": "Rusça",
"langSimplifiedChinese": "Çince (Basit)",
"langUkranian": "Ukraynaca",
"langSpanish": "İspanyolca",
"txt2img": "Metinden Resime",
"img2img": "Resimden Metine",
"linear": "Çizgisel",
"nodes": "Düğümler",
"postprocessing": "İşlem Sonrası",
"postProcessing": "İşlem Sonrası",
"postProcessDesc2": "Daha gelişmiş özellikler için ve iş akışını kolaylaştırmak için özel bir kullanıcı arayüzü çok yakında yayınlanacaktır.",
"postProcessDesc3": "Invoke AI komut satırı arayüzü, bir çok yeni özellik sunmaktadır.",
"langKorean": "Korece",
"unifiedCanvas": "Akıllı Tuval",
"nodesDesc": "Görüntülerin oluşturulmasında hazırladığımız yeni bir sistem geliştirme aşamasındadır. Bu harika özellikler ve çok daha fazlası için bizi takip etmeye devam edin.",
"postProcessDesc1": "Invoke AI son kullanıcıya yönelik bir çok özellik sunar. Görüntü kalitesi yükseltme, yüz restorasyonu WebUI üzerinden kullanılabilir. Metinden resime ve resimden metne araçlarına gelişmiş seçenekler menüsünden ulaşabilirsiniz. İsterseniz mevcut görüntü ekranının üzerindeki veya görüntüleyicideki görüntüyü doğrudan düzenleyebilirsiniz."
}
}

173
invokeai/frontend/web/public/locales/uk.json
View File

@ -16,9 +16,9 @@
"postProcessing": "Постобробка",
"postProcessDesc1": "Invoke AI пропонує широкий спектр функцій постобробки. Збільшення зображення (upscale) та відновлення облич вже доступні в інтерфейсі. Отримайте доступ до них з меню 'Додаткові параметри' на вкладках 'Зображення із тексту' та 'Зображення із зображення'. Обробляйте зображення безпосередньо, використовуючи кнопки дій із зображеннями над поточним зображенням або в режимі перегляду.",
"postProcessDesc2": "Найближчим часом буде випущено спеціальний інтерфейс для більш сучасних процесів постобробки.",
"postProcessDesc3": "Інтерфейс командного рядка Invoke AI пропонує різні інші функції, включаючи збільшення Embiggen",
"postProcessDesc3": "Інтерфейс командного рядка Invoke AI пропонує різні інші функції, включаючи збільшення Embiggen.",
"training": "Навчання",
"trainingDesc1": "Спеціальний інтерфейс для навчання власних моделей з використанням Textual Inversion та Dreambooth",
"trainingDesc1": "Спеціальний інтерфейс для навчання власних моделей з використанням Textual Inversion та Dreambooth.",
"trainingDesc2": "InvokeAI вже підтримує навчання моделей за допомогою TI, через інтерфейс командного рядка.",
"upload": "Завантажити",
"close": "Закрити",
@ -43,7 +43,38 @@
"statusUpscaling": "Збільшення",
"statusUpscalingESRGAN": "Збільшення (ESRGAN)",
"statusLoadingModel": "Завантаження моделі",
"statusModelChanged": "Модель змінено"
"statusModelChanged": "Модель змінено",
"cancel": "Скасувати",
"accept": "Підтвердити",
"back": "Назад",
"postprocessing": "Постобробка",
"statusModelConverted": "Модель сконвертована",
"statusMergingModels": "Злиття моделей",
"loading": "Завантаження",
"loadingInvokeAI": "Завантаження Invoke AI",
"langHebrew": "Іврит",
"langKorean": "Корейська",
"langPortuguese": "Португальська",
"pinOptionsPanel": "Закріпити панель налаштувань",
"oceanTheme": "Океан",
"langArabic": "Арабська",
"langSimplifiedChinese": "Китайська (спрощена)",
"langSpanish": "Іспанська",
"langEnglish": "Англійська",
"langGerman": "Німецька",
"langItalian": "Італійська",
"langJapanese": "Японська",
"langPolish": "Польська",
"langBrPortuguese": "Португальська (Бразилія)",
"langRussian": "Російська",
"githubLabel": "Github",
"txt2img": "Текст в зображення (txt2img)",
"discordLabel": "Discord",
"langDutch": "Голландська",
"langFrench": "Французька",
"statusMergedModels": "Моделі об'єднані",
"statusConvertingModel": "Конвертація моделі",
"linear": "Лінійна обробка"
},
"gallery": {
"generations": "Генерації",
@ -284,15 +315,15 @@
"description": "Опис",
"descriptionValidationMsg": "Введіть опис моделі",
"config": "Файл конфігурації",
"configValidationMsg": "Шлях до файлу конфігурації",
"configValidationMsg": "Шлях до файлу конфігурації.",
"modelLocation": "Розташування моделі",
"modelLocationValidationMsg": "Шлях до файлу з моделлю",
"modelLocationValidationMsg": "Шлях до файлу з моделлю.",
"vaeLocation": "Розтышування VAE",
"vaeLocationValidationMsg": "Шлях до VAE",
"vaeLocationValidationMsg": "Шлях до VAE.",
"width": "Ширина",
"widthValidationMsg": "Початкова ширина зображень",
"widthValidationMsg": "Початкова ширина зображень.",
"height": "Висота",
"heightValidationMsg": "Початкова висота зображень",
"heightValidationMsg": "Початкова висота зображень.",
"addModel": "Додати модель",
"updateModel": "Оновити модель",
"availableModels": "Доступні моделі",
@ -319,7 +350,66 @@
"deleteModel": "Видалити модель",
"deleteConfig": "Видалити конфігурацію",
"deleteMsg1": "Ви точно хочете видалити модель із InvokeAI?",
"deleteMsg2": "Це не призведе до видалення файлу моделі з диску. Позніше ви можете додати його знову."
"deleteMsg2": "Це не призведе до видалення файлу моделі з диску. Позніше ви можете додати його знову.",
"allModels": "Усі моделі",
"diffusersModels": "Diffusers",
"scanForModels": "Сканувати моделі",
"convert": "Конвертувати",
"convertToDiffusers": "Конвертувати в Diffusers",
"formMessageDiffusersVAELocationDesc": "Якщо не надано, InvokeAI буде шукати файл VAE в розташуванні моделі, вказаній вище.",
"convertToDiffusersHelpText3": "Файл моделі на диску НЕ буде видалено або змінено. Ви можете знову додати його в Model Manager, якщо потрібно.",
"customConfig": "Користувальницький конфіг",
"invokeRoot": "Каталог InvokeAI",
"custom": "Користувальницький",
"modelTwo": "Модель 2",
"modelThree": "Модель 3",
"mergedModelName": "Назва об'єднаної моделі",
"alpha": "Альфа",
"interpolationType": "Тип інтерполяції",
"mergedModelSaveLocation": "Шлях збереження",
"mergedModelCustomSaveLocation": "Користувальницький шлях",
"invokeAIFolder": "Каталог InvokeAI",
"ignoreMismatch": "Ігнорувати невідповідності між вибраними моделями",
"modelMergeHeaderHelp2": "Тільки Diffusers-моделі доступні для об'єднання. Якщо ви хочете об'єднати checkpoint-моделі, спочатку перетворіть їх на Diffusers.",
"checkpointModels": "Checkpoints",
"repo_id": "ID репозиторію",
"v2_base": "v2 (512px)",
"repoIDValidationMsg": "Онлайн-репозиторій моделі",
"formMessageDiffusersModelLocationDesc": "Вкажіть хоча б одне.",
"formMessageDiffusersModelLocation": "Шлях до Diffusers-моделі",
"v2_768": "v2 (768px)",
"formMessageDiffusersVAELocation": "Шлях до VAE",
"convertToDiffusersHelpText5": "Переконайтеся, що у вас достатньо місця на диску. Моделі зазвичай займають від 4 до 7 Гб.",
"convertToDiffusersSaveLocation": "Шлях збереження",
"v1": "v1",
"convertToDiffusersHelpText6": "Ви хочете перетворити цю модель?",
"inpainting": "v1 Inpainting",
"modelConverted": "Модель перетворено",
"sameFolder": "У ту ж папку",
"statusConverting": "Перетворення",
"merge": "Об'єднати",
"mergeModels": "Об'єднати моделі",
"modelOne": "Модель 1",
"sigmoid": "Сігмоїд",
"weightedSum": "Зважена сума",
"none": "пусто",
"addDifference": "Додати різницю",
"pickModelType": "Вибрати тип моделі",
"convertToDiffusersHelpText4": "Це одноразова дія. Вона може зайняти від 30 до 60 секунд в залежності від характеристик вашого комп'ютера.",
"pathToCustomConfig": "Шлях до конфігу користувача",
"safetensorModels": "SafeTensors",
"addCheckpointModel": "Додати модель Checkpoint/Safetensor",
"addDiffuserModel": "Додати Diffusers",
"vaeRepoID": "ID репозиторію VAE",
"vaeRepoIDValidationMsg": "Онлайн-репозиторій VAE",
"modelMergeInterpAddDifferenceHelp": "У цьому режимі Модель 3 спочатку віднімається з Моделі 2. Результуюча версія змішується з Моделью 1 із встановленим вище коефіцієнтом Альфа.",
"customSaveLocation": "Користувальницький шлях збереження",
"modelMergeAlphaHelp": "Альфа впливає силу змішування моделей. Нижчі значення альфа призводять до меншого впливу другої моделі.",
"convertToDiffusersHelpText1": "Ця модель буде конвертована в формат 🧨 Diffusers.",
"convertToDiffusersHelpText2": "Цей процес замінить ваш запис в Model Manager на версію тієї ж моделі в Diffusers.",
"modelsMerged": "Моделі об'єднані",
"modelMergeHeaderHelp1": "Ви можете об'єднати до трьох різних моделей, щоб створити змішану, що відповідає вашим потребам.",
"inverseSigmoid": "Зворотній Сігмоїд"
},
"parameters": {
"images": "Зображення",
@ -346,7 +436,7 @@
"scale": "Масштаб",
"otherOptions": "інші параметри",
"seamlessTiling": "Безшовний узор",
"hiresOptim": "Висока роздільна здатність",
"hiresOptim": "Оптимізація High Res",
"imageFit": "Вмістити зображення",
"codeformerFidelity": "Точність",
"seamSize": "Размір шву",
@ -379,7 +469,24 @@
"info": "Метадані",
"deleteImage": "Видалити зображення",
"initialImage": "Початкове зображення",
"showOptionsPanel": "Показати панель налаштувань"
"showOptionsPanel": "Показати панель налаштувань",
"general": "Основне",
"cancel": {
"immediate": "Скасувати негайно",
"schedule": "Скасувати після поточної ітерації",
"isScheduled": "Відміна",
"setType": "Встановити тип скасування"
},
"vSymmetryStep": "Крок верт. симетрії",
"hiresStrength": "Сила High Res",
"hidePreview": "Сховати попередній перегляд",
"showPreview": "Показати попередній перегляд",
"imageToImage": "Зображення до зображення",
"denoisingStrength": "Сила шумоподавлення",
"copyImage": "Копіювати зображення",
"symmetry": "Симетрія",
"hSymmetryStep": "Крок гор. симетрії",
"negativePrompts": "Виключний запит"
},
"settings": {
"models": "Моделі",
@ -392,7 +499,8 @@
"resetWebUI": "Повернути початкові",
"resetWebUIDesc1": "Скидання настройок веб-інтерфейсу видаляє лише локальний кеш браузера з вашими зображеннями та налаштуваннями. Це не призводить до видалення зображень з диску.",
"resetWebUIDesc2": "Якщо зображення не відображаються в галереї або не працює ще щось, спробуйте скинути налаштування, перш ніж повідомляти про проблему на GitHub.",
"resetComplete": "Інтерфейс скинуто. Оновіть цю сторінку."
"resetComplete": "Інтерфейс скинуто. Оновіть цю сторінку.",
"useSlidersForAll": "Використовувати повзунки для всіх параметрів"
},
"toast": {
"tempFoldersEmptied": "Тимчасова папка очищена",
@ -410,21 +518,25 @@
"sentToUnifiedCanvas": "Надіслати на полотно",
"parametersSet": "Параметри задані",
"parametersNotSet": "Параметри не задані",
"parametersNotSetDesc": "Не знайдені метадані цього зображення",
"parametersNotSetDesc": "Не знайдені метадані цього зображення.",
"parametersFailed": "Проблема із завантаженням параметрів",
"parametersFailedDesc": "Неможливо завантажити початкове зображення",
"parametersFailedDesc": "Неможливо завантажити початкове зображення.",
"seedSet": "Сід заданий",
"seedNotSet": "Сід не заданий",
"seedNotSetDesc": "Не вдалося знайти сід для зображення",
"seedNotSetDesc": "Не вдалося знайти сід для зображення.",
"promptSet": "Запит заданий",
"promptNotSet": "Запит не заданий",
"promptNotSetDesc": "Не вдалося знайти запит для зображення",
"promptNotSetDesc": "Не вдалося знайти запит для зображення.",
"upscalingFailed": "Збільшення не вдалося",
"faceRestoreFailed": "Відновлення облич не вдалося",
"metadataLoadFailed": "Не вдалося завантажити метадані",
"initialImageSet": "Початкове зображення задане",
"initialImageNotSet": "Початкове зображення не задане",
"initialImageNotSetDesc": "Не вдалося завантажити початкове зображення"
"initialImageNotSetDesc": "Не вдалося завантажити початкове зображення",
"serverError": "Помилка сервера",
"disconnected": "Відключено від сервера",
"connected": "Підключено до сервера",
"canceled": "Обробку скасовано"
},
"tooltip": {
"feature": {
@ -473,10 +585,10 @@
"autoSaveToGallery": "Автозбереження до галереї",
"saveBoxRegionOnly": "Зберiгати тiльки видiлення",
"limitStrokesToBox": "Обмежити штрихи виділенням",
"showCanvasDebugInfo": "Показати налаштування полотна",
"showCanvasDebugInfo": "Показати дод. інформацію про полотно",
"clearCanvasHistory": "Очистити iсторiю полотна",
"clearHistory": "Очистити iсторiю",
"clearCanvasHistoryMessage": "Очищення історії полотна залишає поточне полотно незайманим, але видаляє історію скасування та повтору",
"clearCanvasHistoryMessage": "Очищення історії полотна залишає поточне полотно незайманим, але видаляє історію скасування та повтору.",
"clearCanvasHistoryConfirm": "Ви впевнені, що хочете очистити історію полотна?",
"emptyTempImageFolder": "Очистити тимчасову папку",
"emptyFolder": "Очистити папку",
@ -499,5 +611,28 @@
"betaDarkenOutside": "Затемнити зовні",
"betaLimitToBox": "Обмежити виділенням",
"betaPreserveMasked": "Зберiгати замасковану область"
},
"accessibility": {
"nextImage": "Наступне зображення",
"modelSelect": "Вибір моделі",
"invokeProgressBar": "Індикатор виконання",
"reset": "Скинути",
"uploadImage": "Завантажити зображення",
"useThisParameter": "Використовувати цей параметр",
"exitViewer": "Вийти з переглядача",
"zoomIn": "Збільшити",
"zoomOut": "Зменшити",
"rotateCounterClockwise": "Обертати проти годинникової стрілки",
"rotateClockwise": "Обертати за годинниковою стрілкою",
"toggleAutoscroll": "Увімкнути автопрокручування",
"toggleLogViewer": "Показати або приховати переглядач журналів",
"showGallery": "Показати галерею",
"previousImage": "Попереднє зображення",
"copyMetadataJson": "Скопіювати метадані JSON",
"flipVertically": "Перевернути по вертикалі",
"flipHorizontally": "Відобразити по горизонталі",
"showOptionsPanel": "Показати опції",
"modifyConfig": "Змінити конфігурацію",
"menu": "Меню"
}
}

1
invokeai/frontend/web/public/locales/vi.json Normal file
View File

@ -0,0 +1 @@
{}

17
invokeai/frontend/web/public/locales/zh_CN.json
View File

@ -481,5 +481,22 @@
"betaDarkenOutside": "暗化外部区域",
"betaLimitToBox": "限制在框内",
"betaPreserveMasked": "保留遮罩层"
},
"accessibility": {
"modelSelect": "模型选择",
"invokeProgressBar": "Invoke 进度条",
"reset": "重置",
"nextImage": "下一张图片",
"useThisParameter": "使用此参数",
"uploadImage": "上传图片",
"previousImage": "上一张图片",
"copyMetadataJson": "复制JSON元数据",
"exitViewer": "退出视口（ExitViewer）",
"zoomIn": "放大",
"zoomOut": "缩小",
"rotateCounterClockwise": "逆时针旋转",
"rotateClockwise": "顺时针旋转",
"flipHorizontally": "水平翻转",
"flipVertically": "垂直翻转"
}
}

39
invokeai/frontend/web/src/Loading.tsx
View File

@ -1,39 +0,0 @@
import { Flex, Spinner, Text } from '@chakra-ui/react';
import { useTranslation } from 'react-i18next';
interface LoaderProps {
showText?: boolean;
text?: string;
}
// This component loads before the theme so we cannot use theme tokens here
const Loading = (props: LoaderProps) => {
const { t } = useTranslation();
const { showText = false, text = t('common.loadingInvokeAI') } = props;
return (
<Flex
width="100vw"
height="100vh"
alignItems="center"
justifyContent="center"
bg="#121212"
flexDirection="column"
rowGap={4}
>
<Spinner color="grey" w="5rem" h="5rem" />
{showText && (
<Text
color="grey"
fontWeight="semibold"
fontFamily="'Inter', sans-serif"
>
{text}
</Text>
)}
</Flex>
);
};
export default Loading;

81
invokeai/frontend/web/src/app/App.tsx
View File

@ -13,24 +13,53 @@ import { Box, Flex, Grid, Portal, useColorMode } from '@chakra-ui/react';
import { APP_HEIGHT, APP_WIDTH } from 'theme/util/constants';
import ImageGalleryPanel from 'features/gallery/components/ImageGalleryPanel';
import Lightbox from 'features/lightbox/components/Lightbox';
import { useAppSelector } from './storeHooks';
import { PropsWithChildren, useEffect } from 'react';
import { useAppDispatch, useAppSelector } from './storeHooks';
import { PropsWithChildren, useCallback, useEffect, useState } from 'react';
import { motion, AnimatePresence } from 'framer-motion';
import Loading from 'common/components/Loading/Loading';
import { useIsApplicationReady } from 'features/system/hooks/useIsApplicationReady';
import { PartialAppConfig } from './invokeai';
import { useGlobalHotkeys } from 'common/hooks/useGlobalHotkeys';
import { configChanged } from 'features/system/store/configSlice';
import { useFeatureStatus } from 'features/system/hooks/useFeatureStatus';
keepGUIAlive();
const App = (props: PropsWithChildren) => {
interface Props extends PropsWithChildren {
config?: PartialAppConfig;
}
const App = ({ config = {}, children }: Props) => {
useToastWatcher();
useGlobalHotkeys();
const currentTheme = useAppSelector((state) => state.ui.currentTheme);
const isLightboxEnabled = useFeatureStatus('lightbox').isFeatureEnabled;
const isApplicationReady = useIsApplicationReady();
const [loadingOverridden, setLoadingOverridden] = useState(false);
const { setColorMode } = useColorMode();
const dispatch = useAppDispatch();
useEffect(() => {
console.log('Received config: ', config);
dispatch(configChanged(config));
}, [dispatch, config]);
useEffect(() => {
setColorMode(['light'].includes(currentTheme) ? 'light' : 'dark');
}, [setColorMode, currentTheme]);
const handleOverrideClicked = useCallback(() => {
setLoadingOverridden(true);
}, []);
return (
<Grid w="100vw" h="100vh">
<Lightbox />
<Grid w="100vw" h="100vh" position="relative">
{isLightboxEnabled && <Lightbox />}
<ImageUploader>
<ProgressBar />
<Grid
@ -40,22 +69,54 @@ const App = (props: PropsWithChildren) => {
w={APP_WIDTH}
h={APP_HEIGHT}
>
{props.children || <SiteHeader />}
<Flex gap={4} w="full" h="full">
{children || <SiteHeader />}
<Flex
gap={4}
w={{ base: '100vw', xl: 'full' }}
h="full"
flexDir={{ base: 'column', xl: 'row' }}
>
<InvokeTabs />
<ImageGalleryPanel />
</Flex>
</Grid>
<Box>
<Console />
</Box>
</ImageUploader>
<AnimatePresence>
{!isApplicationReady && !loadingOverridden && (
<motion.div
key="loading"
initial={{ opacity: 1 }}
animate={{ opacity: 1 }}
exit={{ opacity: 0 }}
transition={{ duration: 0.3 }}
style={{ zIndex: 3 }}
>
<Box position="absolute" top={0} left={0} w="100vw" h="100vh">
<Loading />
</Box>
<Box
onClick={handleOverrideClicked}
position="absolute"
top={0}
right={0}
cursor="pointer"
w="2rem"
h="2rem"
/>
</motion.div>
)}
</AnimatePresence>
<Portal>
<FloatingParametersPanelButtons />
</Portal>
<Portal>
<FloatingGalleryButton />
</Portal>
<Portal>
<Console />
</Portal>
</Grid>
);
};

10
invokeai/frontend/web/src/app/constants.ts
View File

@ -31,13 +31,13 @@ export const DIFFUSERS_SAMPLERS: Array<string> = [
];
// Valid image widths
export const WIDTHS: Array<number> = Array.from(Array(65)).map(
(_x, i) => i * 64
export const WIDTHS: Array<number> = Array.from(Array(64)).map(
(_x, i) => (i + 1) * 64
);
// Valid image heights
export const HEIGHTS: Array<number> = Array.from(Array(65)).map(
(_x, i) => i * 64
export const HEIGHTS: Array<number> = Array.from(Array(64)).map(
(_x, i) => (i + 1) * 64
);
// Valid upscaling levels
@ -60,3 +60,5 @@ export const IN_PROGRESS_IMAGE_TYPES: Array<{
{ key: 'Fast', value: 'latents' },
{ key: 'Accurate', value: 'full-res' },
];
export const NODE_MIN_WIDTH = 250;

117
invokeai/frontend/web/src/app/invokeai.d.ts vendored
View File

@ -12,8 +12,12 @@
* 'gfpgan'.
*/
import { FacetoolType } from 'features/parameters/store/postprocessingSlice';
import { InvokeTabName } from 'features/ui/store/tabMap';
import { IRect } from 'konva/lib/types';
import { ImageMetadata, ImageType } from 'services/api';
import { AnyInvocation } from 'services/events/types';
import { O } from 'ts-toolbelt';
/**
* TODO:
@ -113,7 +117,7 @@ export declare type Metadata = SystemGenerationMetadata & {
};
// An Image has a UUID, url, modified timestamp, width, height and maybe metadata
export declare type Image = {
export declare type _Image = {
uuid: string;
url: string;
thumbnail: string;
@ -124,11 +128,23 @@ export declare type Image = {
category: GalleryCategory;
isBase64?: boolean;
dreamPrompt?: 'string';
name?: string;
};
/**
* ResultImage
*/
export declare type Image = {
name: string;
type: ImageType;
url: string;
thumbnail: string;
metadata: ImageMetadata;
};
// GalleryImages is an array of Image.
export declare type GalleryImages = {
images: Array<Image>;
images: Array<_Image>;
};
/**
@ -275,7 +291,7 @@ export declare type SystemStatusResponse = SystemStatus;
export declare type SystemConfigResponse = SystemConfig;
export declare type ImageResultResponse = Omit<Image, 'uuid'> & {
export declare type ImageResultResponse = Omit<_Image, 'uuid'> & {
boundingBox?: IRect;
generationMode: InvokeTabName;
};
@ -296,7 +312,7 @@ export declare type ErrorResponse = {
};
export declare type GalleryImagesResponse = {
images: Array<Omit<Image, 'uuid'>>;
images: Array<Omit<_Image, 'uuid'>>;
areMoreImagesAvailable: boolean;
category: GalleryCategory;
};
@ -320,3 +336,96 @@ export declare type UploadOutpaintingMergeImagePayload = {
dataURL: string;
name: string;
};
/**
* A disable-able application feature
*/
export declare type AppFeature =
| 'faceRestore'
| 'upscaling'
| 'lightbox'
| 'modelManager'
| 'githubLink'
| 'discordLink'
| 'bugLink'
| 'localization';
/**
* A disable-able Stable Diffusion feature
*/
export declare type StableDiffusionFeature =
| 'noiseConfig'
| 'variations'
| 'symmetry'
| 'tiling'
| 'hires';
/**
* Configuration options for the InvokeAI UI.
* Distinct from system settings which may be changed inside the app.
*/
export declare type AppConfig = {
/**
* Whether or not URLs should be transformed to use a different host
*/
shouldTransformUrls: boolean;
/**
* Whether or not we need to re-fetch images
*/
shouldFetchImages: boolean;
disabledTabs: InvokeTabName[];
disabledFeatures: AppFeature[];
canRestoreDeletedImagesFromBin: boolean;
sd: {
iterations: {
initial: number;
min: number;
sliderMax: number;
inputMax: number;
fineStep: number;
coarseStep: number;
};
width: {
initial: number;
min: number;
sliderMax: number;
inputMax: number;
fineStep: number;
coarseStep: number;
};
height: {
initial: number;
min: number;
sliderMax: number;
inputMax: number;
fineStep: number;
coarseStep: number;
};
steps: {
initial: number;
min: number;
sliderMax: number;
inputMax: number;
fineStep: number;
coarseStep: number;
};
guidance: {
initial: number;
min: number;
sliderMax: number;
inputMax: number;
fineStep: number;
coarseStep: number;
};
img2imgStrength: {
initial: number;
min: number;
sliderMax: number;
inputMax: number;
fineStep: number;
coarseStep: number;
};
};
};
export declare type PartialAppConfig = O.Partial<AppConfig, 'deep'>;

3
invokeai/frontend/web/src/app/selectors/readinessSelector.ts
View File

@ -20,6 +20,7 @@ export const readinessSelector = createSelector(
seedWeights,
initialImage,
seed,
isImageToImageEnabled,
} = generation;
const { isProcessing, isConnected } = system;
@ -33,7 +34,7 @@ export const readinessSelector = createSelector(
reasonsWhyNotReady.push('Missing prompt');
}
if (activeTabName === 'img2img' && !initialImage) {
if (isImageToImageEnabled && !initialImage) {
isReady = false;
reasonsWhyNotReady.push('No initial image selected');
}

10
invokeai/frontend/web/src/app/socketio/actions.ts
View File

@ -13,9 +13,13 @@ import { InvokeTabName } from 'features/ui/store/tabMap';
export const generateImage = createAction<InvokeTabName>(
'socketio/generateImage'
);
export const runESRGAN = createAction<InvokeAI.Image>('socketio/runESRGAN');
export const runFacetool = createAction<InvokeAI.Image>('socketio/runFacetool');
export const deleteImage = createAction<InvokeAI.Image>('socketio/deleteImage');
export const runESRGAN = createAction<InvokeAI._Image>('socketio/runESRGAN');
export const runFacetool = createAction<InvokeAI._Image>(
'socketio/runFacetool'
);
export const deleteImage = createAction<InvokeAI._Image>(
'socketio/deleteImage'
);
export const requestImages = createAction<GalleryCategory>(
'socketio/requestImages'
);

6
invokeai/frontend/web/src/app/socketio/emitters.ts
View File

@ -91,7 +91,7 @@ const makeSocketIOEmitters = (
})
);
},
emitRunESRGAN: (imageToProcess: InvokeAI.Image) => {
emitRunESRGAN: (imageToProcess: InvokeAI._Image) => {
dispatch(setIsProcessing(true));
const {
@ -119,7 +119,7 @@ const makeSocketIOEmitters = (
})
);
},
emitRunFacetool: (imageToProcess: InvokeAI.Image) => {
emitRunFacetool: (imageToProcess: InvokeAI._Image) => {
dispatch(setIsProcessing(true));
const {
@ -150,7 +150,7 @@ const makeSocketIOEmitters = (
})
);
},
emitDeleteImage: (imageToDelete: InvokeAI.Image) => {
emitDeleteImage: (imageToDelete: InvokeAI._Image) => {
const { url, uuid, category, thumbnail } = imageToDelete;
dispatch(removeImage(imageToDelete));
socketio.emit('deleteImage', url, thumbnail, uuid, category);

27
invokeai/frontend/web/src/app/socketio/listeners.ts
View File

@ -34,8 +34,9 @@ import type { RootState } from 'app/store';
import { addImageToStagingArea } from 'features/canvas/store/canvasSlice';
import {
clearInitialImage,
initialImageSelected,
setInfillMethod,
setInitialImage,
// setInitialImage,
setMaskPath,
} from 'features/parameters/store/generationSlice';
import { tabMap } from 'features/ui/store/tabMap';
@ -142,15 +143,17 @@ const makeSocketIOListeners = (
}
}
if (shouldLoopback) {
const activeTabName = tabMap[activeTab];
switch (activeTabName) {
case 'img2img': {
dispatch(setInitialImage(newImage));
break;
}
}
}
// TODO: fix
// if (shouldLoopback) {
// const activeTabName = tabMap[activeTab];
// switch (activeTabName) {
// case 'img2img': {
// dispatch(initialImageSelected(newImage.uuid));
// // dispatch(setInitialImage(newImage));
// break;
// }
// }
// }
dispatch(clearIntermediateImage());
@ -262,7 +265,7 @@ const makeSocketIOListeners = (
*/
// Generate a UUID for each image
const preparedImages = images.map((image): InvokeAI.Image => {
const preparedImages = images.map((image): InvokeAI._Image => {
return {
uuid: uuidv4(),
...image,
@ -334,7 +337,7 @@ const makeSocketIOListeners = (
if (
initialImage === url ||
(initialImage as InvokeAI.Image)?.url === url
(initialImage as InvokeAI._Image)?.url === url
) {
dispatch(clearInitialImage());
}

2
invokeai/frontend/web/src/app/socketio/middleware.ts
View File

@ -29,6 +29,8 @@ export const socketioMiddleware = () => {
path: `${window.location.pathname}socket.io`,
});
socketio.disconnect();
let areListenersSet = false;
const middleware: Middleware = (store) => (next) => (action) => {

104
invokeai/frontend/web/src/app/store.ts
View File

@ -2,18 +2,34 @@ import { combineReducers, configureStore } from '@reduxjs/toolkit';
import { persistReducer } from 'redux-persist';
import storage from 'redux-persist/lib/storage'; // defaults to localStorage for web
import dynamicMiddlewares from 'redux-dynamic-middlewares';
import { getPersistConfig } from 'redux-deep-persist';
import canvasReducer from 'features/canvas/store/canvasSlice';
import galleryReducer from 'features/gallery/store/gallerySlice';
import resultsReducer from 'features/gallery/store/resultsSlice';
import uploadsReducer from 'features/gallery/store/uploadsSlice';
import lightboxReducer from 'features/lightbox/store/lightboxSlice';
import generationReducer from 'features/parameters/store/generationSlice';
import postprocessingReducer from 'features/parameters/store/postprocessingSlice';
import systemReducer from 'features/system/store/systemSlice';
import configReducer from 'features/system/store/configSlice';
import uiReducer from 'features/ui/store/uiSlice';
import hotkeysReducer from 'features/ui/store/hotkeysSlice';
import modelsReducer from 'features/system/store/modelSlice';
import nodesReducer from 'features/nodes/store/nodesSlice';
import { socketioMiddleware } from './socketio/middleware';
import { socketMiddleware } from 'services/events/middleware';
import { canvasDenylist } from 'features/canvas/store/canvasPersistDenylist';
import { galleryDenylist } from 'features/gallery/store/galleryPersistDenylist';
import { generationDenylist } from 'features/parameters/store/generationPersistDenylist';
import { lightboxDenylist } from 'features/lightbox/store/lightboxPersistDenylist';
import { modelsDenylist } from 'features/system/store/modelsPersistDenylist';
import { nodesDenylist } from 'features/nodes/store/nodesPersistDenylist';
import { postprocessingDenylist } from 'features/parameters/store/postprocessingPersistDenylist';
import { systemDenylist } from 'features/system/store/systemPersistsDenylist';
import { uiDenylist } from 'features/ui/store/uiPersistDenylist';
/**
* redux-persist provides an easy and reliable way to persist state across reloads.
@ -24,54 +40,25 @@ import { socketioMiddleware } from './socketio/middleware';
* - Connection/processing status
* - Availability of external libraries like ESRGAN/GFPGAN
*
* These can be blacklisted in redux-persist.
* These can be denylisted in redux-persist.
*
* The necesssary nested persistors with blacklists are configured below.
* The necesssary nested persistors with denylists are configured below.
*/
const canvasBlacklist = [
'cursorPosition',
'isCanvasInitialized',
'doesCanvasNeedScaling',
].map((blacklistItem) => `canvas.${blacklistItem}`);
const systemBlacklist = [
'currentIteration',
'currentStatus',
'currentStep',
'isCancelable',
'isConnected',
'isESRGANAvailable',
'isGFPGANAvailable',
'isProcessing',
'socketId',
'totalIterations',
'totalSteps',
'openModel',
'cancelOptions.cancelAfter',
].map((blacklistItem) => `system.${blacklistItem}`);
const galleryBlacklist = [
'categories',
'currentCategory',
'currentImage',
'currentImageUuid',
'shouldAutoSwitchToNewImages',
'intermediateImage',
].map((blacklistItem) => `gallery.${blacklistItem}`);
const lightboxBlacklist = ['isLightboxOpen'].map(
(blacklistItem) => `lightbox.${blacklistItem}`
);
const rootReducer = combineReducers({
generation: generationReducer,
postprocessing: postprocessingReducer,
gallery: galleryReducer,
system: systemReducer,
canvas: canvasReducer,
ui: uiReducer,
gallery: galleryReducer,
generation: generationReducer,
lightbox: lightboxReducer,
models: modelsReducer,
nodes: nodesReducer,
postprocessing: postprocessingReducer,
results: resultsReducer,
system: systemReducer,
config: configReducer,
ui: uiReducer,
uploads: uploadsReducer,
hotkeys: hotkeysReducer,
});
const rootPersistConfig = getPersistConfig({
@ -79,24 +66,43 @@ const rootPersistConfig = getPersistConfig({
storage,
rootReducer,
blacklist: [
...canvasBlacklist,
...systemBlacklist,
...galleryBlacklist,
...lightboxBlacklist,
...canvasDenylist,
...galleryDenylist,
...generationDenylist,
...lightboxDenylist,
...modelsDenylist,
...nodesDenylist,
...postprocessingDenylist,
// ...resultsDenylist,
'results',
...systemDenylist,
...uiDenylist,
// ...uploadsDenylist,
'uploads',
'hotkeys',
'config',
],
debounce: 300,
});
const persistedReducer = persistReducer(rootPersistConfig, rootReducer);
// Continue with store setup
// TODO: rip the old middleware out when nodes is complete
export function buildMiddleware() {
if (import.meta.env.MODE === 'nodes' || import.meta.env.MODE === 'package') {
return socketMiddleware();
} else {
return socketioMiddleware();
}
}
export const store = configureStore({
reducer: persistedReducer,
middleware: (getDefaultMiddleware) =>
getDefaultMiddleware({
immutableCheck: false,
serializableCheck: false,
}).concat(socketioMiddleware()),
}).concat(dynamicMiddlewares),
devTools: {
// Uncommenting these very rapidly called actions makes the redux dev tools output much more readable
actionsDenylist: [

8
invokeai/frontend/web/src/app/storeUtils.ts Normal file
View File

@ -0,0 +1,8 @@
import { createAsyncThunk } from '@reduxjs/toolkit';
import { AppDispatch, RootState } from './store';
// https://redux-toolkit.js.org/usage/usage-with-typescript#defining-a-pre-typed-createasyncthunk
export const createAppAsyncThunk = createAsyncThunk.withTypes<{
state: RootState;
dispatch: AppDispatch;
}>();

86
invokeai/frontend/web/src/common/components/IAISlider.tsx
View File

@ -26,9 +26,18 @@ import {
import { clamp } from 'lodash';
import { useTranslation } from 'react-i18next';
import { FocusEvent, memo, useEffect, useMemo, useState } from 'react';
import {
FocusEvent,
memo,
MouseEvent,
useCallback,
useEffect,
useMemo,
useState,
} from 'react';
import { BiReset } from 'react-icons/bi';
import IAIIconButton, { IAIIconButtonProps } from './IAIIconButton';
import { roundDownToMultiple } from 'common/util/roundDownToMultiple';
export type IAIFullSliderProps = {
label: string;
@ -44,12 +53,10 @@ export type IAIFullSliderProps = {
inputReadOnly?: boolean;
withReset?: boolean;
handleReset?: () => void;
isResetDisabled?: boolean;
isSliderDisabled?: boolean;
isInputDisabled?: boolean;
tooltipSuffix?: string;
hideTooltip?: boolean;
isCompact?: boolean;
isDisabled?: boolean;
sliderFormControlProps?: FormControlProps;
sliderFormLabelProps?: FormLabelProps;
sliderMarkProps?: Omit<SliderMarkProps, 'value'>;
@ -80,10 +87,8 @@ const IAISlider = (props: IAIFullSliderProps) => {
withReset = false,
hideTooltip = false,
isCompact = false,
isDisabled = false,
handleReset,
isResetDisabled,
isSliderDisabled,
isInputDisabled,
sliderFormControlProps,
sliderFormLabelProps,
sliderMarkProps,
@ -112,31 +117,52 @@ const IAISlider = (props: IAIFullSliderProps) => {
[max, sliderNumberInputProps?.max]
);
const handleSliderChange = (v: number) => {
onChange(v);
};
const handleSliderChange = useCallback(
(v: number) => {
onChange(v);
},
[onChange]
);
const handleInputBlur = (e: FocusEvent<HTMLInputElement>) => {
if (e.target.value === '') e.target.value = String(min);
const clamped = clamp(
isInteger ? Math.floor(Number(e.target.value)) : Number(localInputValue),
min,
numberInputMax
);
onChange(clamped);
};
const handleInputBlur = useCallback(
(e: FocusEvent<HTMLInputElement>) => {
if (e.target.value === '') {
e.target.value = String(min);
}
const clamped = clamp(
isInteger
? Math.floor(Number(e.target.value))
: Number(localInputValue),
min,
numberInputMax
);
const quantized = roundDownToMultiple(clamped, step);
onChange(quantized);
setLocalInputValue(quantized);
},
[isInteger, localInputValue, min, numberInputMax, onChange, step]
);
const handleInputChange = (v: number | string) => {
const handleInputChange = useCallback((v: number | string) => {
setLocalInputValue(v);
};
}, []);
const handleResetDisable = () => {
if (!handleReset) return;
const handleResetDisable = useCallback(() => {
if (!handleReset) {
return;
}
handleReset();
};
}, [handleReset]);
const forceInputBlur = useCallback((e: MouseEvent) => {
if (e.target instanceof HTMLDivElement) {
e.target.focus();
}
}, []);
return (
<FormControl
onClick={forceInputBlur}
sx={
isCompact
? {
@ -149,6 +175,7 @@ const IAISlider = (props: IAIFullSliderProps) => {
}
: {}
}
isDisabled={isDisabled}
{...sliderFormControlProps}
>
<FormLabel {...sliderFormLabelProps} mb={-1}>
@ -166,15 +193,13 @@ const IAISlider = (props: IAIFullSliderProps) => {
onMouseEnter={() => setShowTooltip(true)}
onMouseLeave={() => setShowTooltip(false)}
focusThumbOnChange={false}
isDisabled={isSliderDisabled}
// width={width}
isDisabled={isDisabled}
{...rest}
>
{withSliderMarks && (
<>
<SliderMark
value={min}
// insetInlineStart={0}
sx={{
insetInlineStart: '0 !important',
insetInlineEnd: 'unset !important',
@ -185,7 +210,6 @@ const IAISlider = (props: IAIFullSliderProps) => {
</SliderMark>
<SliderMark
value={max}
// insetInlineEnd={0}
sx={{
insetInlineStart: 'unset !important',
insetInlineEnd: '0 !important',
@ -221,7 +245,7 @@ const IAISlider = (props: IAIFullSliderProps) => {
value={localInputValue}
onChange={handleInputChange}
onBlur={handleInputBlur}
isDisabled={isInputDisabled}
focusInputOnChange={false}
{...sliderNumberInputProps}
>
<NumberInputField
@ -244,10 +268,10 @@ const IAISlider = (props: IAIFullSliderProps) => {
<IAIIconButton
size="sm"
aria-label={t('accessibility.reset')}
tooltip="Reset"
tooltip={t('accessibility.reset')}
icon={<BiReset />}
isDisabled={isDisabled}
onClick={handleResetDisable}
isDisabled={isResetDisabled}
{...sliderIAIIconButtonProps}
/>
)}

3
invokeai/frontend/web/src/common/components/IAISwitch.tsx
View File

@ -34,10 +34,9 @@ const IAISwitch = (props: Props) => {
display="flex"
gap={4}
alignItems="center"
justifyContent="space-between"
{...formControlProps}
>
<FormLabel my={1} {...formLabelProps}>
<FormLabel my={1} flexGrow={1} {...formLabelProps}>
{label}
</FormLabel>
<Switch {...rest} />

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