mirror of
https://github.com/invoke-ai/InvokeAI
synced 2024-08-30 20:32:17 +00:00
Merge branch 'main' into refactor/model-manager2/loader
This commit is contained in:
Lincoln Stein
GitHub
commit
411ec1ed64
@ -42,6 +42,7 @@ To use a community workflow, download the the `.json` node graph file and load i
|
||||
+ [Oobabooga](#oobabooga)
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||||
+ [Prompt Tools](#prompt-tools)
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||||
+ [Remote Image](#remote-image)
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||||
+ [BriaAI Background Remove](#briaai-remove-background)
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||||
+ [Remove Background](#remove-background)
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||||
+ [Retroize](#retroize)
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||||
+ [Size Stepper Nodes](#size-stepper-nodes)
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||||
@ -434,6 +435,17 @@ See full docs here: https://github.com/skunkworxdark/Prompt-tools-nodes/edit/mai
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||||
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||||
**Node Link:** https://github.com/fieldOfView/InvokeAI-remote_image
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||||
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||||
--------------------------------
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### BriaAI Remove Background
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**Description**: Implements one click background removal with BriaAI's new version 1.4 model which seems to be be producing better results than any other previous background removal tool.
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||||
**Node Link:** https://github.com/blessedcoolant/invoke_bria_rmbg
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||||
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||||
**View**
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<img src="https://raw.githubusercontent.com/blessedcoolant/invoke_bria_rmbg/main/assets/preview.jpg" />
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--------------------------------
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### Remove Background
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@ -14,11 +14,19 @@ function is_bin_in_path {
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}
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||||
function git_show {
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git show -s --format='%h %s' $1
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||||
git show -s --format=oneline --abbrev-commit "$1" | cat
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||||
}
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||||
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||||
if [[ -v "VIRTUAL_ENV" ]]; then
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||||
# we can't just call 'deactivate' because this function is not exported
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||||
# to the environment of this script from the bash process that runs the script
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||||
echo -e "${BRED}A virtual environment is activated. Please deactivate it before proceeding.${RESET}"
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exit -1
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fi
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||||
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||||
cd "$(dirname "$0")"
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echo
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||||
echo -e "${BYELLOW}This script must be run from the installer directory!${RESET}"
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echo "The current working directory is $(pwd)"
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||||
read -p "If that looks right, press any key to proceed, or CTRL-C to exit..."
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@ -32,13 +40,6 @@ if ! is_bin_in_path python && is_bin_in_path python3; then
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}
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||||
fi
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||||
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if [[ -v "VIRTUAL_ENV" ]]; then
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||||
# we can't just call 'deactivate' because this function is not exported
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||||
# to the environment of this script from the bash process that runs the script
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||||
echo -e "${BRED}A virtual environment is activated. Please deactivate it before proceeding.${RESET}"
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exit -1
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fi
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VERSION=$(
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cd ..
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python -c "from invokeai.version import __version__ as version; print(version)"
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@ -47,38 +48,9 @@ PATCH=""
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VERSION="v${VERSION}${PATCH}"
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echo -e "${BGREEN}HEAD${RESET}:"
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git_show
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git_show HEAD
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echo
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# ---------------------- FRONTEND ----------------------
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pushd ../invokeai/frontend/web >/dev/null
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echo
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echo "Installing frontend dependencies..."
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echo
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pnpm i --frozen-lockfile
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echo
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echo "Building frontend..."
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echo
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pnpm build
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popd
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# ---------------------- BACKEND ----------------------
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echo
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echo "Building wheel..."
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echo
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||||
# install the 'build' package in the user site packages, if needed
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# could be improved by using a temporary venv, but it's tiny and harmless
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if [[ $(python -c 'from importlib.util import find_spec; print(find_spec("build") is None)') == "True" ]]; then
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pip install --user build
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||||
fi
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||||
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||||
rm -rf ../build
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||||
python -m build --wheel --outdir dist/ ../.
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||||
# ----------------------
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echo
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@ -97,16 +69,13 @@ done
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mkdir InvokeAI-Installer/lib
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cp lib/*.py InvokeAI-Installer/lib
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# Move the wheel
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mv dist/*.whl InvokeAI-Installer/lib/
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# Install scripts
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# Mac/Linux
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cp install.sh.in InvokeAI-Installer/install.sh
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chmod a+x InvokeAI-Installer/install.sh
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# Windows
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perl -p -e "s/^set INVOKEAI_VERSION=.*/set INVOKEAI_VERSION=$VERSION/" install.bat.in >InvokeAI-Installer/install.bat
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cp install.bat.in InvokeAI-Installer/install.bat
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cp WinLongPathsEnabled.reg InvokeAI-Installer/
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# Zip everything up
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||||
@ -15,7 +15,6 @@ if "%1" == "use-cache" (
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@rem Config
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||||
@rem The version in the next line is replaced by an up to date release number
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||||
@rem when create_installer.sh is run. Change the release number there.
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set INVOKEAI_VERSION=latest
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set INSTRUCTIONS=https://invoke-ai.github.io/InvokeAI/installation/INSTALL_AUTOMATED/
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set TROUBLESHOOTING=https://invoke-ai.github.io/InvokeAI/installation/INSTALL_AUTOMATED/#troubleshooting
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set PYTHON_URL=https://www.python.org/downloads/windows/
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@ -11,7 +11,7 @@ import sys
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||||
import venv
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||||
from pathlib import Path
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||||
from tempfile import TemporaryDirectory
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||||
from typing import Union
|
||||
from typing import Optional, Tuple
|
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SUPPORTED_PYTHON = ">=3.10.0,<=3.11.100"
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INSTALLER_REQS = ["rich", "semver", "requests", "plumbum", "prompt-toolkit"]
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@ -21,40 +21,20 @@ OS = platform.uname().system
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ARCH = platform.uname().machine
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||||
VERSION = "latest"
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||||
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||||
### Feature flags
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||||
# Install the virtualenv into the runtime dir
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||||
FF_VENV_IN_RUNTIME = True
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||||
# Install the wheel packaged with the installer
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FF_USE_LOCAL_WHEEL = True
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||||
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class Installer:
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"""
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Deploys an InvokeAI installation into a given path
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||||
"""
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||||
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reqs: list[str] = INSTALLER_REQS
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||||
def __init__(self) -> None:
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||||
self.reqs = INSTALLER_REQS
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||||
self.preflight()
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||||
if os.getenv("VIRTUAL_ENV") is not None:
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||||
print("A virtual environment is already activated. Please 'deactivate' before installation.")
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||||
sys.exit(-1)
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||||
self.bootstrap()
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||||
|
||||
def preflight(self) -> None:
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||||
"""
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||||
Preflight checks
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||||
"""
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||||
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||||
# TODO
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||||
# verify python version
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||||
# on macOS verify XCode tools are present
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||||
# verify libmesa, libglx on linux
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||||
# check that the system arch is not i386 (?)
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||||
# check that the system has a GPU, and the type of GPU
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||||
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||||
pass
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||||
self.available_releases = get_github_releases()
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||||
|
||||
def mktemp_venv(self) -> TemporaryDirectory:
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||||
"""
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||||
@ -78,12 +58,9 @@ class Installer:
|
||||
|
||||
return venv_dir
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||||
|
||||
def bootstrap(self, verbose: bool = False) -> TemporaryDirectory:
|
||||
def bootstrap(self, verbose: bool = False) -> TemporaryDirectory | None:
|
||||
"""
|
||||
Bootstrap the installer venv with packages required at install time
|
||||
|
||||
:return: path to the virtual environment directory that was bootstrapped
|
||||
:rtype: TemporaryDirectory
|
||||
"""
|
||||
|
||||
print("Initializing the installer. This may take a minute - please wait...")
|
||||
@ -95,39 +72,27 @@ class Installer:
|
||||
cmd.extend(self.reqs)
|
||||
|
||||
try:
|
||||
res = subprocess.check_output(cmd).decode()
|
||||
# upgrade pip to the latest version to avoid a confusing message
|
||||
res = upgrade_pip(Path(venv_dir.name))
|
||||
if verbose:
|
||||
print(res)
|
||||
|
||||
# run the install prerequisites installation
|
||||
res = subprocess.check_output(cmd).decode()
|
||||
|
||||
if verbose:
|
||||
print(res)
|
||||
|
||||
return venv_dir
|
||||
except subprocess.CalledProcessError as e:
|
||||
print(e)
|
||||
|
||||
def app_venv(self, path: str = None):
|
||||
def app_venv(self, venv_parent) -> Path:
|
||||
"""
|
||||
Create a virtualenv for the InvokeAI installation
|
||||
"""
|
||||
|
||||
# explicit venv location
|
||||
# currently unused in normal operation
|
||||
# useful for testing or special cases
|
||||
if path is not None:
|
||||
venv_dir = Path(path)
|
||||
|
||||
# experimental / testing
|
||||
elif not FF_VENV_IN_RUNTIME:
|
||||
if OS == "Windows":
|
||||
venv_dir_parent = os.getenv("APPDATA", "~/AppData/Roaming")
|
||||
elif OS == "Darwin":
|
||||
# there is no environment variable on macOS to find this
|
||||
# TODO: confirm this is working as expected
|
||||
venv_dir_parent = "~/Library/Application Support"
|
||||
elif OS == "Linux":
|
||||
venv_dir_parent = os.getenv("XDG_DATA_DIR", "~/.local/share")
|
||||
venv_dir = Path(venv_dir_parent).expanduser().resolve() / f"InvokeAI/{VERSION}/venv"
|
||||
|
||||
# stable / current
|
||||
else:
|
||||
venv_dir = self.dest / ".venv"
|
||||
venv_dir = venv_parent / ".venv"
|
||||
|
||||
# Prefer to copy python executables
|
||||
# so that updates to system python don't break InvokeAI
|
||||
@ -141,7 +106,7 @@ class Installer:
|
||||
return venv_dir
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||||
|
||||
def install(
|
||||
self, root: str = "~/invokeai", version: str = "latest", yes_to_all=False, find_links: Path = None
|
||||
self, version=None, root: str = "~/invokeai", yes_to_all=False, find_links: Optional[Path] = None
|
||||
) -> None:
|
||||
"""
|
||||
Install the InvokeAI application into the given runtime path
|
||||
@ -158,15 +123,20 @@ class Installer:
|
||||
|
||||
import messages
|
||||
|
||||
messages.welcome()
|
||||
messages.welcome(self.available_releases)
|
||||
|
||||
default_path = os.environ.get("INVOKEAI_ROOT") or Path(root).expanduser().resolve()
|
||||
self.dest = default_path if yes_to_all else messages.dest_path(root)
|
||||
version = messages.choose_version(self.available_releases)
|
||||
|
||||
auto_dest = Path(os.environ.get("INVOKEAI_ROOT", root)).expanduser().resolve()
|
||||
destination = auto_dest if yes_to_all else messages.dest_path(root)
|
||||
if destination is None:
|
||||
print("Could not find or create the destination directory. Installation cancelled.")
|
||||
sys.exit(0)
|
||||
|
||||
# create the venv for the app
|
||||
self.venv = self.app_venv()
|
||||
self.venv = self.app_venv(venv_parent=destination)
|
||||
|
||||
self.instance = InvokeAiInstance(runtime=self.dest, venv=self.venv, version=version)
|
||||
self.instance = InvokeAiInstance(runtime=destination, venv=self.venv, version=version)
|
||||
|
||||
# install dependencies and the InvokeAI application
|
||||
(extra_index_url, optional_modules) = get_torch_source() if not yes_to_all else (None, None)
|
||||
@ -190,7 +160,7 @@ class InvokeAiInstance:
|
||||
A single runtime directory *may* be shared by multiple virtual environments, though this isn't currently tested or supported.
|
||||
"""
|
||||
|
||||
def __init__(self, runtime: Path, venv: Path, version: str) -> None:
|
||||
def __init__(self, runtime: Path, venv: Path, version: str = "stable") -> None:
|
||||
self.runtime = runtime
|
||||
self.venv = venv
|
||||
self.pip = get_pip_from_venv(venv)
|
||||
@ -199,6 +169,7 @@ class InvokeAiInstance:
|
||||
set_sys_path(venv)
|
||||
os.environ["INVOKEAI_ROOT"] = str(self.runtime.expanduser().resolve())
|
||||
os.environ["VIRTUAL_ENV"] = str(self.venv.expanduser().resolve())
|
||||
upgrade_pip(venv)
|
||||
|
||||
def get(self) -> tuple[Path, Path]:
|
||||
"""
|
||||
@ -212,54 +183,7 @@ class InvokeAiInstance:
|
||||
|
||||
def install(self, extra_index_url=None, optional_modules=None, find_links=None):
|
||||
"""
|
||||
Install this instance, including dependencies and the app itself
|
||||
|
||||
:param extra_index_url: the "--extra-index-url ..." line for pip to look in extra indexes.
|
||||
:type extra_index_url: str
|
||||
"""
|
||||
|
||||
import messages
|
||||
|
||||
# install torch first to ensure the correct version gets installed.
|
||||
# works with either source or wheel install with negligible impact on installation times.
|
||||
messages.simple_banner("Installing PyTorch :fire:")
|
||||
self.install_torch(extra_index_url, find_links)
|
||||
|
||||
messages.simple_banner("Installing the InvokeAI Application :art:")
|
||||
self.install_app(extra_index_url, optional_modules, find_links)
|
||||
|
||||
def install_torch(self, extra_index_url=None, find_links=None):
|
||||
"""
|
||||
Install PyTorch
|
||||
"""
|
||||
|
||||
from plumbum import FG, local
|
||||
|
||||
pip = local[self.pip]
|
||||
|
||||
(
|
||||
pip[
|
||||
"install",
|
||||
"--require-virtualenv",
|
||||
"numpy==1.26.3", # choose versions that won't be uninstalled during phase 2
|
||||
"urllib3~=1.26.0",
|
||||
"requests~=2.28.0",
|
||||
"torch==2.1.2",
|
||||
"torchmetrics==0.11.4",
|
||||
"torchvision==0.16.2",
|
||||
"--force-reinstall",
|
||||
"--find-links" if find_links is not None else None,
|
||||
find_links,
|
||||
"--extra-index-url" if extra_index_url is not None else None,
|
||||
extra_index_url,
|
||||
]
|
||||
& FG
|
||||
)
|
||||
|
||||
def install_app(self, extra_index_url=None, optional_modules=None, find_links=None):
|
||||
"""
|
||||
Install the application with pip.
|
||||
Supports installation from PyPi or from a local source directory.
|
||||
Install the package from PyPi.
|
||||
|
||||
:param extra_index_url: the "--extra-index-url ..." line for pip to look in extra indexes.
|
||||
:type extra_index_url: str
|
||||
@ -271,53 +195,52 @@ class InvokeAiInstance:
|
||||
:type find_links: Path
|
||||
"""
|
||||
|
||||
## this only applies to pypi installs; TODO actually use this
|
||||
if self.version == "pre":
|
||||
import messages
|
||||
|
||||
# not currently used, but may be useful for "install most recent version" option
|
||||
if self.version == "prerelease":
|
||||
version = None
|
||||
pre = "--pre"
|
||||
pre_flag = "--pre"
|
||||
elif self.version == "stable":
|
||||
version = None
|
||||
pre_flag = None
|
||||
else:
|
||||
version = self.version
|
||||
pre = None
|
||||
pre_flag = None
|
||||
|
||||
## TODO: only local wheel will be installed as of now; support for --version arg is TODO
|
||||
if FF_USE_LOCAL_WHEEL:
|
||||
# if no wheel, try to do a source install before giving up
|
||||
try:
|
||||
src = str(next(Path(__file__).parent.glob("InvokeAI-*.whl")))
|
||||
except StopIteration:
|
||||
try:
|
||||
src = Path(__file__).parents[1].expanduser().resolve()
|
||||
# if the above directory contains one of these files, we'll do a source install
|
||||
next(src.glob("pyproject.toml"))
|
||||
next(src.glob("invokeai"))
|
||||
except StopIteration:
|
||||
print("Unable to find a wheel or perform a source install. Giving up.")
|
||||
src = "invokeai"
|
||||
if optional_modules:
|
||||
src += optional_modules
|
||||
if version:
|
||||
src += f"=={version}"
|
||||
|
||||
elif version == "source":
|
||||
# this makes an assumption about the location of the installer package in the source tree
|
||||
src = Path(__file__).parents[1].expanduser().resolve()
|
||||
else:
|
||||
# will install from PyPi
|
||||
src = f"invokeai=={version}" if version is not None else "invokeai"
|
||||
messages.simple_banner("Installing the InvokeAI Application :art:")
|
||||
|
||||
from plumbum import FG, local
|
||||
from plumbum import FG, ProcessExecutionError, local # type: ignore
|
||||
|
||||
pip = local[self.pip]
|
||||
|
||||
(
|
||||
pip[
|
||||
pipeline = pip[
|
||||
"install",
|
||||
"--require-virtualenv",
|
||||
"--force-reinstall",
|
||||
"--use-pep517",
|
||||
str(src) + (optional_modules if optional_modules else ""),
|
||||
str(src),
|
||||
"--find-links" if find_links is not None else None,
|
||||
find_links,
|
||||
"--extra-index-url" if extra_index_url is not None else None,
|
||||
extra_index_url,
|
||||
pre,
|
||||
pre_flag,
|
||||
]
|
||||
& FG
|
||||
|
||||
try:
|
||||
_ = pipeline & FG
|
||||
except ProcessExecutionError as e:
|
||||
print(f"Error: {e}")
|
||||
print(
|
||||
"Could not install InvokeAI. Please try downloading the latest version of the installer and install again."
|
||||
)
|
||||
sys.exit(1)
|
||||
|
||||
def configure(self):
|
||||
"""
|
||||
@ -373,7 +296,6 @@ class InvokeAiInstance:
|
||||
|
||||
ext = "bat" if OS == "Windows" else "sh"
|
||||
|
||||
# scripts = ['invoke', 'update']
|
||||
scripts = ["invoke"]
|
||||
|
||||
for script in scripts:
|
||||
@ -408,6 +330,23 @@ def get_pip_from_venv(venv_path: Path) -> str:
|
||||
return str(venv_path.expanduser().resolve() / pip)
|
||||
|
||||
|
||||
def upgrade_pip(venv_path: Path) -> str | None:
|
||||
"""
|
||||
Upgrade the pip executable in the given virtual environment
|
||||
"""
|
||||
|
||||
python = "Scripts\\python.exe" if OS == "Windows" else "bin/python"
|
||||
python = str(venv_path.expanduser().resolve() / python)
|
||||
|
||||
try:
|
||||
result = subprocess.check_output([python, "-m", "pip", "install", "--upgrade", "pip"]).decode()
|
||||
except subprocess.CalledProcessError as e:
|
||||
print(e)
|
||||
result = None
|
||||
|
||||
return result
|
||||
|
||||
|
||||
def set_sys_path(venv_path: Path) -> None:
|
||||
"""
|
||||
Given a path to a virtual environment, set the sys.path, in a cross-platform fashion,
|
||||
@ -431,7 +370,43 @@ def set_sys_path(venv_path: Path) -> None:
|
||||
sys.path.append(str(Path(venv_path, lib, "site-packages").expanduser().resolve()))
|
||||
|
||||
|
||||
def get_torch_source() -> (Union[str, None], str):
|
||||
def get_github_releases() -> tuple[list, list] | None:
|
||||
"""
|
||||
Query Github for published (pre-)release versions.
|
||||
Return a tuple where the first element is a list of stable releases and the second element is a list of pre-releases.
|
||||
Return None if the query fails for any reason.
|
||||
"""
|
||||
|
||||
import requests
|
||||
|
||||
## get latest releases using github api
|
||||
url = "https://api.github.com/repos/invoke-ai/InvokeAI/releases"
|
||||
releases, pre_releases = [], []
|
||||
try:
|
||||
res = requests.get(url)
|
||||
res.raise_for_status()
|
||||
tag_info = res.json()
|
||||
for tag in tag_info:
|
||||
if not tag["prerelease"]:
|
||||
releases.append(tag["tag_name"].lstrip("v"))
|
||||
else:
|
||||
pre_releases.append(tag["tag_name"].lstrip("v"))
|
||||
except requests.HTTPError as e:
|
||||
print(f"Error: {e}")
|
||||
print("Could not fetch version information from GitHub. Please check your network connection and try again.")
|
||||
return
|
||||
except Exception as e:
|
||||
print(f"Error: {e}")
|
||||
print("An unexpected error occurred while trying to fetch version information from GitHub. Please try again.")
|
||||
return
|
||||
|
||||
releases.sort(reverse=True)
|
||||
pre_releases.sort(reverse=True)
|
||||
|
||||
return releases, pre_releases
|
||||
|
||||
|
||||
def get_torch_source() -> Tuple[str | None, str | None]:
|
||||
"""
|
||||
Determine the extra index URL for pip to use for torch installation.
|
||||
This depends on the OS and the graphics accelerator in use.
|
||||
@ -446,23 +421,24 @@ def get_torch_source() -> (Union[str, None], str):
|
||||
:rtype: list
|
||||
"""
|
||||
|
||||
from messages import graphical_accelerator
|
||||
from messages import select_gpu
|
||||
|
||||
# device can be one of: "cuda", "rocm", "cpu", "idk"
|
||||
device = graphical_accelerator()
|
||||
# device can be one of: "cuda", "rocm", "cpu", "cuda_and_dml, autodetect"
|
||||
device = select_gpu()
|
||||
|
||||
url = None
|
||||
optional_modules = "[onnx]"
|
||||
if OS == "Linux":
|
||||
if device == "rocm":
|
||||
if device.value == "rocm":
|
||||
url = "https://download.pytorch.org/whl/rocm5.6"
|
||||
elif device == "cpu":
|
||||
elif device.value == "cpu":
|
||||
url = "https://download.pytorch.org/whl/cpu"
|
||||
|
||||
if device == "cuda":
|
||||
elif OS == "Windows":
|
||||
if device.value == "cuda":
|
||||
url = "https://download.pytorch.org/whl/cu121"
|
||||
optional_modules = "[xformers,onnx-cuda]"
|
||||
if device == "cuda_and_dml":
|
||||
if device.value == "cuda_and_dml":
|
||||
url = "https://download.pytorch.org/whl/cu121"
|
||||
optional_modules = "[xformers,onnx-directml]"
|
||||
|
||||
|
||||
@ -5,10 +5,11 @@ Installer user interaction
|
||||
|
||||
import os
|
||||
import platform
|
||||
from enum import Enum
|
||||
from pathlib import Path
|
||||
|
||||
from prompt_toolkit import HTML, prompt
|
||||
from prompt_toolkit.completion import PathCompleter
|
||||
from prompt_toolkit.completion import FuzzyWordCompleter, PathCompleter
|
||||
from prompt_toolkit.validation import Validator
|
||||
from rich import box, print
|
||||
from rich.console import Console, Group, group
|
||||
@ -35,16 +36,26 @@ else:
|
||||
console = Console(style=Style(color="grey74", bgcolor="grey19"))
|
||||
|
||||
|
||||
def welcome():
|
||||
def welcome(available_releases: tuple | None = None) -> None:
|
||||
@group()
|
||||
def text():
|
||||
if (platform_specific := _platform_specific_help()) != "":
|
||||
if (platform_specific := _platform_specific_help()) is not None:
|
||||
yield platform_specific
|
||||
yield ""
|
||||
yield Text.from_markup(
|
||||
"Some of the installation steps take a long time to run. Please be patient. If the script appears to hang for more than 10 minutes, please interrupt with [i]Control-C[/] and retry.",
|
||||
justify="center",
|
||||
)
|
||||
if available_releases is not None:
|
||||
latest_stable = available_releases[0][0]
|
||||
last_pre = available_releases[1][0]
|
||||
yield ""
|
||||
yield Text.from_markup(
|
||||
f"[red3]🠶[/] Latest stable release (recommended): [b bright_white]{latest_stable}", justify="center"
|
||||
)
|
||||
yield Text.from_markup(
|
||||
f"[red3]🠶[/] Last published pre-release version: [b bright_white]{last_pre}", justify="center"
|
||||
)
|
||||
|
||||
console.rule()
|
||||
print(
|
||||
@ -61,19 +72,31 @@ def welcome():
|
||||
console.line()
|
||||
|
||||
|
||||
def confirm_install(dest: Path) -> bool:
|
||||
if dest.exists():
|
||||
print(f":exclamation: Directory {dest} already exists :exclamation:")
|
||||
dest_confirmed = Confirm.ask(
|
||||
":stop_sign: (re)install in this location?",
|
||||
default=False,
|
||||
def choose_version(available_releases: tuple | None = None) -> str:
|
||||
"""
|
||||
Prompt the user to choose an Invoke version to install
|
||||
"""
|
||||
|
||||
# short circuit if we couldn't get a version list
|
||||
# still try to install the latest stable version
|
||||
if available_releases is None:
|
||||
return "stable"
|
||||
|
||||
console.print(":grey_question: [orange3]Please choose an Invoke version to install.")
|
||||
|
||||
choices = available_releases[0] + available_releases[1]
|
||||
|
||||
response = prompt(
|
||||
message=f" <Enter> to install the recommended release ({choices[0]}). <Tab> or type to pick a version: ",
|
||||
complete_while_typing=True,
|
||||
completer=FuzzyWordCompleter(choices),
|
||||
)
|
||||
else:
|
||||
print(f"InvokeAI will be installed in {dest}")
|
||||
dest_confirmed = Confirm.ask("Use this location?", default=True)
|
||||
|
||||
console.print(f" Version {choices[0] if response == "" else response} will be installed.")
|
||||
|
||||
console.line()
|
||||
|
||||
return dest_confirmed
|
||||
return "stable" if response == "" else response
|
||||
|
||||
|
||||
def user_wants_auto_configuration() -> bool:
|
||||
@ -109,7 +132,23 @@ def user_wants_auto_configuration() -> bool:
|
||||
return choice.lower().startswith("a")
|
||||
|
||||
|
||||
def dest_path(dest=None) -> Path:
|
||||
def confirm_install(dest: Path) -> bool:
|
||||
if dest.exists():
|
||||
print(f":stop_sign: Directory {dest} already exists!")
|
||||
print(" Is this location correct?")
|
||||
default = False
|
||||
else:
|
||||
print(f":file_folder: InvokeAI will be installed in {dest}")
|
||||
default = True
|
||||
|
||||
dest_confirmed = Confirm.ask(" Please confirm:", default=default)
|
||||
|
||||
console.line()
|
||||
|
||||
return dest_confirmed
|
||||
|
||||
|
||||
def dest_path(dest=None) -> Path | None:
|
||||
"""
|
||||
Prompt the user for the destination path and create the path
|
||||
|
||||
@ -124,25 +163,21 @@ def dest_path(dest=None) -> Path:
|
||||
else:
|
||||
dest = Path.cwd().expanduser().resolve()
|
||||
prev_dest = init_path = dest
|
||||
|
||||
dest_confirmed = confirm_install(dest)
|
||||
dest_confirmed = False
|
||||
|
||||
while not dest_confirmed:
|
||||
# if the given destination already exists, the starting point for browsing is its parent directory.
|
||||
# the user may have made a typo, or otherwise wants to place the root dir next to an existing one.
|
||||
# if the destination dir does NOT exist, then the user must have changed their mind about the selection.
|
||||
# since we can't read their mind, start browsing at Path.cwd().
|
||||
browse_start = (prev_dest.parent if prev_dest.exists() else Path.cwd()).expanduser().resolve()
|
||||
browse_start = (dest or Path.cwd()).expanduser().resolve()
|
||||
|
||||
path_completer = PathCompleter(
|
||||
only_directories=True,
|
||||
expanduser=True,
|
||||
get_paths=lambda: [browse_start], # noqa: B023
|
||||
get_paths=lambda: [str(browse_start)], # noqa: B023
|
||||
# get_paths=lambda: [".."].extend(list(browse_start.iterdir()))
|
||||
)
|
||||
|
||||
console.line()
|
||||
console.print(f"[orange3]Please select the destination directory for the installation:[/] \\[{browse_start}]: ")
|
||||
|
||||
console.print(f":grey_question: [orange3]Please select the install destination:[/] \\[{browse_start}]: ")
|
||||
selected = prompt(
|
||||
">>> ",
|
||||
complete_in_thread=True,
|
||||
@ -155,6 +190,7 @@ def dest_path(dest=None) -> Path:
|
||||
)
|
||||
prev_dest = dest
|
||||
dest = Path(selected)
|
||||
|
||||
console.line()
|
||||
|
||||
dest_confirmed = confirm_install(dest.expanduser().resolve())
|
||||
@ -182,41 +218,45 @@ def dest_path(dest=None) -> Path:
|
||||
console.rule("Goodbye!")
|
||||
|
||||
|
||||
def graphical_accelerator():
|
||||
class GpuType(Enum):
|
||||
CUDA = "cuda"
|
||||
CUDA_AND_DML = "cuda_and_dml"
|
||||
ROCM = "rocm"
|
||||
CPU = "cpu"
|
||||
AUTODETECT = "autodetect"
|
||||
|
||||
|
||||
def select_gpu() -> GpuType:
|
||||
"""
|
||||
Prompt the user to select the graphical accelerator in their system
|
||||
This does not validate user's choices (yet), but only offers choices
|
||||
valid for the platform.
|
||||
CUDA is the fallback.
|
||||
We may be able to detect the GPU driver by shelling out to `modprobe` or `lspci`,
|
||||
but this is not yet supported or reliable. Also, some users may have exotic preferences.
|
||||
Prompt the user to select the GPU driver
|
||||
"""
|
||||
|
||||
if ARCH == "arm64" and OS != "Darwin":
|
||||
print(f"Only CPU acceleration is available on {ARCH} architecture. Proceeding with that.")
|
||||
return "cpu"
|
||||
return GpuType.CPU
|
||||
|
||||
nvidia = (
|
||||
"an [gold1 b]NVIDIA[/] GPU (using CUDA™)",
|
||||
"cuda",
|
||||
GpuType.CUDA,
|
||||
)
|
||||
nvidia_with_dml = (
|
||||
"an [gold1 b]NVIDIA[/] GPU (using CUDA™, and DirectML™ for ONNX) -- ALPHA",
|
||||
"cuda_and_dml",
|
||||
GpuType.CUDA_AND_DML,
|
||||
)
|
||||
amd = (
|
||||
"an [gold1 b]AMD[/] GPU (using ROCm™)",
|
||||
"rocm",
|
||||
GpuType.ROCM,
|
||||
)
|
||||
cpu = (
|
||||
"no compatible GPU, or specifically prefer to use the CPU",
|
||||
"cpu",
|
||||
"Do not install any GPU support, use CPU for generation (slow)",
|
||||
GpuType.CPU,
|
||||
)
|
||||
idk = (
|
||||
autodetect = (
|
||||
"I'm not sure what to choose",
|
||||
"idk",
|
||||
GpuType.AUTODETECT,
|
||||
)
|
||||
|
||||
options = []
|
||||
if OS == "Windows":
|
||||
options = [nvidia, nvidia_with_dml, cpu]
|
||||
if OS == "Linux":
|
||||
@ -230,7 +270,7 @@ def graphical_accelerator():
|
||||
return options[0][1]
|
||||
|
||||
# "I don't know" is always added the last option
|
||||
options.append(idk)
|
||||
options.append(autodetect) # type: ignore
|
||||
|
||||
options = {str(i): opt for i, opt in enumerate(options, 1)}
|
||||
|
||||
@ -265,9 +305,9 @@ def graphical_accelerator():
|
||||
),
|
||||
)
|
||||
|
||||
if options[choice][1] == "idk":
|
||||
if options[choice][1] is GpuType.AUTODETECT:
|
||||
console.print(
|
||||
"No problem. We will try to install a version that [i]should[/i] be compatible. :crossed_fingers:"
|
||||
"No problem. We will install CUDA support first :crossed_fingers: If Invoke does not detect a GPU, please re-run the installer and select one of the other GPU types."
|
||||
)
|
||||
|
||||
return options[choice][1]
|
||||
@ -291,7 +331,7 @@ def windows_long_paths_registry() -> None:
|
||||
"""
|
||||
|
||||
with open(str(Path(__file__).parent / "WinLongPathsEnabled.reg"), "r", encoding="utf-16le") as code:
|
||||
syntax = Syntax(code.read(), line_numbers=True)
|
||||
syntax = Syntax(code.read(), line_numbers=True, lexer="regedit")
|
||||
|
||||
console.print(
|
||||
Panel(
|
||||
@ -301,7 +341,7 @@ def windows_long_paths_registry() -> None:
|
||||
"We will now apply a registry fix to enable long paths on Windows. InvokeAI needs this to function correctly. We are asking your permission to modify the Windows Registry on your behalf.",
|
||||
"",
|
||||
"This is the change that will be applied:",
|
||||
syntax,
|
||||
str(syntax),
|
||||
]
|
||||
)
|
||||
),
|
||||
@ -340,7 +380,7 @@ def introduction() -> None:
|
||||
console.line(2)
|
||||
|
||||
|
||||
def _platform_specific_help() -> str:
|
||||
def _platform_specific_help() -> Text | None:
|
||||
if OS == "Darwin":
|
||||
text = Text.from_markup(
|
||||
"""[b wheat1]macOS Users![/]\n\nPlease be sure you have the [b wheat1]Xcode command-line tools[/] installed before continuing.\nIf not, cancel with [i]Control-C[/] and follow the Xcode install instructions at [deep_sky_blue1]https://www.freecodecamp.org/news/install-xcode-command-line-tools/[/]."""
|
||||
@ -354,5 +394,5 @@ def _platform_specific_help() -> str:
|
||||
[deep_sky_blue1]https://learn.microsoft.com/en-US/cpp/windows/latest-supported-vc-redist?view=msvc-170[/]"""
|
||||
)
|
||||
else:
|
||||
text = ""
|
||||
return
|
||||
return text
|
||||
|
||||
@ -15,7 +15,7 @@ echo 4. Download and install models
|
||||
echo 5. Change InvokeAI startup options
|
||||
echo 6. Re-run the configure script to fix a broken install or to complete a major upgrade
|
||||
echo 7. Open the developer console
|
||||
echo 8. Update InvokeAI
|
||||
echo 8. Update InvokeAI (DEPRECATED - please use the installer)
|
||||
echo 9. Run the InvokeAI image database maintenance script
|
||||
echo 10. Command-line help
|
||||
echo Q - Quit
|
||||
@ -52,7 +52,9 @@ IF /I "%choice%" == "1" (
|
||||
echo *** Type `exit` to quit this shell and deactivate the Python virtual environment ***
|
||||
call cmd /k
|
||||
) ELSE IF /I "%choice%" == "8" (
|
||||
echo Running invokeai-update...
|
||||
echo UPDATING FROM WITHIN THE APP IS BEING DEPRECATED.
|
||||
echo Please download the installer from https://github.com/invoke-ai/InvokeAI/releases/latest and run it to update your installation.
|
||||
timeout 4
|
||||
python -m invokeai.frontend.install.invokeai_update
|
||||
) ELSE IF /I "%choice%" == "9" (
|
||||
echo Running the db maintenance script...
|
||||
@ -77,4 +79,3 @@ pause
|
||||
|
||||
:ending
|
||||
exit /b
|
||||
|
||||
|
||||
@ -90,7 +90,9 @@ do_choice() {
|
||||
;;
|
||||
8)
|
||||
clear
|
||||
printf "Update InvokeAI\n"
|
||||
printf "UPDATING FROM WITHIN THE APP IS BEING DEPRECATED\n"
|
||||
printf "Please download the installer from https://github.com/invoke-ai/InvokeAI/releases/latest and run it to update your installation.\n"
|
||||
sleep 4
|
||||
python -m invokeai.frontend.install.invokeai_update
|
||||
;;
|
||||
9)
|
||||
@ -122,7 +124,7 @@ do_dialog() {
|
||||
5 "Change InvokeAI startup options"
|
||||
6 "Re-run the configure script to fix a broken install or to complete a major upgrade"
|
||||
7 "Open the developer console"
|
||||
8 "Update InvokeAI"
|
||||
8 "Update InvokeAI (DEPRECATED - please use the installer)"
|
||||
9 "Run the InvokeAI image database maintenance script"
|
||||
10 "Command-line help"
|
||||
)
|
||||
|
||||
@ -1,72 +0,0 @@
|
||||
@echo off
|
||||
setlocal EnableExtensions EnableDelayedExpansion
|
||||
|
||||
PUSHD "%~dp0"
|
||||
|
||||
set INVOKE_AI_VERSION=latest
|
||||
set arg=%1
|
||||
if "%arg%" neq "" (
|
||||
if "%arg:~0,2%" equ "/?" (
|
||||
echo Usage: update.bat ^<release name or branch^>
|
||||
echo Updates InvokeAI to use the indicated version of the code base.
|
||||
echo Find the version or branch for the release you want, and pass it as the argument.
|
||||
echo For example '.\update.bat v2.2.5' for release 2.2.5.
|
||||
echo '.\update.bat main' for the latest development version
|
||||
echo.
|
||||
echo If no argument provided then will install the most recent release, equivalent to
|
||||
echo '.\update.bat latest'
|
||||
exit /b
|
||||
) else (
|
||||
set INVOKE_AI_VERSION=%arg%
|
||||
)
|
||||
)
|
||||
|
||||
set INVOKE_AI_SRC="https://github.com/invoke-ai/InvokeAI/archive/!INVOKE_AI_VERSION!.zip"
|
||||
set INVOKE_AI_DEP=https://raw.githubusercontent.com/invoke-ai/InvokeAI/!INVOKE_AI_VERSION!/environments-and-requirements/requirements-base.txt
|
||||
set INVOKE_AI_MODELS=https://raw.githubusercontent.com/invoke-ai/InvokeAI/$INVOKE_AI_VERSION/configs/INITIAL_MODELS.yaml
|
||||
|
||||
call curl -I "%INVOKE_AI_DEP%" -fs >.tmp.out
|
||||
if %errorlevel% neq 0 (
|
||||
echo '!INVOKE_AI_VERSION!' is not a known branch name or tag. Please check the version and try again.
|
||||
echo "Press any key to continue"
|
||||
pause
|
||||
exit /b
|
||||
)
|
||||
del .tmp.out
|
||||
|
||||
echo This script will update InvokeAI and all its dependencies to !INVOKE_AI_SRC!.
|
||||
echo If you do not want to do this, press control-C now!
|
||||
pause
|
||||
|
||||
call curl -L "%INVOKE_AI_DEP%" > environments-and-requirements/requirements-base.txt
|
||||
call curl -L "%INVOKE_AI_MODELS%" > configs/INITIAL_MODELS.yaml
|
||||
|
||||
|
||||
call .venv\Scripts\activate.bat
|
||||
call .venv\Scripts\python -mpip install -r requirements.txt
|
||||
if %errorlevel% neq 0 (
|
||||
echo Installation of requirements failed. See https://invoke-ai.github.io/InvokeAI/installation/INSTALL_AUTOMATED/#troubleshooting for suggestions.
|
||||
pause
|
||||
exit /b
|
||||
)
|
||||
|
||||
call .venv\Scripts\python -mpip install !INVOKE_AI_SRC!
|
||||
if %errorlevel% neq 0 (
|
||||
echo Installation of InvokeAI failed. See https://invoke-ai.github.io/InvokeAI/installation/INSTALL_AUTOMATED/#troubleshooting for suggestions.
|
||||
pause
|
||||
exit /b
|
||||
)
|
||||
|
||||
@rem call .venv\Scripts\invokeai-configure --root=.
|
||||
|
||||
@rem if %errorlevel% neq 0 (
|
||||
@rem echo Configuration InvokeAI failed. See https://invoke-ai.github.io/InvokeAI/installation/INSTALL_AUTOMATED/#troubleshooting for suggestions.
|
||||
@rem pause
|
||||
@rem exit /b
|
||||
@rem )
|
||||
|
||||
echo InvokeAI has been updated to '%INVOKE_AI_VERSION%'
|
||||
|
||||
echo "Press any key to continue"
|
||||
pause
|
||||
endlocal
|
||||
@ -1,58 +0,0 @@
|
||||
#!/usr/bin/env bash
|
||||
|
||||
set -eu
|
||||
|
||||
if [ $# -ge 1 ] && [ "${1:0:2}" == "-h" ]; then
|
||||
echo "Usage: update.sh <release>"
|
||||
echo "Updates InvokeAI to use the indicated version of the code base."
|
||||
echo "Find the version or branch for the release you want, and pass it as the argument."
|
||||
echo "For example: update.sh v2.2.5 for release 2.2.5."
|
||||
echo " update.sh main for the current development version."
|
||||
echo ""
|
||||
echo "If no argument provided then will install the version tagged with 'latest', equivalent to"
|
||||
echo "update.sh latest"
|
||||
exit -1
|
||||
fi
|
||||
|
||||
INVOKE_AI_VERSION=${1:-latest}
|
||||
|
||||
INVOKE_AI_SRC="https://github.com/invoke-ai/InvokeAI/archive/$INVOKE_AI_VERSION.zip"
|
||||
INVOKE_AI_DEP=https://raw.githubusercontent.com/invoke-ai/InvokeAI/$INVOKE_AI_VERSION/environments-and-requirements/requirements-base.txt
|
||||
INVOKE_AI_MODELS=https://raw.githubusercontent.com/invoke-ai/InvokeAI/$INVOKE_AI_VERSION/configs/INITIAL_MODELS.yaml
|
||||
|
||||
# ensure we're in the correct folder in case user's CWD is somewhere else
|
||||
scriptdir=$(dirname "$0")
|
||||
cd "$scriptdir"
|
||||
|
||||
function _err_exit {
|
||||
if test "$1" -ne 0
|
||||
then
|
||||
echo "Something went wrong while installing InvokeAI and/or its requirements."
|
||||
echo "Update cannot continue. Please report this error to https://github.com/invoke-ai/InvokeAI/issues"
|
||||
echo -e "Error code $1; Error caught was '$2'"
|
||||
read -p "Press any key to exit..."
|
||||
exit
|
||||
fi
|
||||
}
|
||||
|
||||
if ! curl -I "$INVOKE_AI_DEP" -fs >/dev/null; then
|
||||
echo \'$INVOKE_AI_VERSION\' is not a known branch name or tag. Please check the version and try again.
|
||||
exit
|
||||
fi
|
||||
|
||||
echo This script will update InvokeAI and all its dependencies to version \'$INVOKE_AI_VERSION\'.
|
||||
echo If you do not want to do this, press control-C now!
|
||||
read -p "Press any key to continue, or CTRL-C to exit..."
|
||||
|
||||
curl -L "$INVOKE_AI_DEP" > environments-and-requirements/requirements-base.txt
|
||||
curl -L "$INVOKE_AI_MODELS" > configs/INITIAL_MODELS.yaml
|
||||
|
||||
. .venv/bin/activate
|
||||
|
||||
./.venv/bin/python -mpip install -r requirements.txt
|
||||
_err_exit $? "The pip program failed to install InvokeAI's requirements."
|
||||
|
||||
./.venv/bin/python -mpip install $INVOKE_AI_SRC
|
||||
_err_exit $? "The pip program failed to install InvokeAI."
|
||||
|
||||
echo InvokeAI updated to \'$INVOKE_AI_VERSION\'
|
||||
@ -14,7 +14,7 @@ class SocketIO:
|
||||
|
||||
def __init__(self, app: FastAPI):
|
||||
self.__sio = AsyncServer(async_mode="asgi", cors_allowed_origins="*")
|
||||
self.__app = ASGIApp(socketio_server=self.__sio, socketio_path="socket.io")
|
||||
self.__app = ASGIApp(socketio_server=self.__sio, socketio_path="/ws/socket.io")
|
||||
app.mount("/ws", self.__app)
|
||||
|
||||
self.__sio.on("subscribe_queue", handler=self._handle_sub_queue)
|
||||
|
||||
@ -5,12 +5,12 @@ from typing import Literal
|
||||
import cv2
|
||||
import numpy as np
|
||||
import torch
|
||||
from basicsr.archs.rrdbnet_arch import RRDBNet
|
||||
from PIL import Image
|
||||
from pydantic import ConfigDict
|
||||
|
||||
from invokeai.app.invocations.primitives import ImageField, ImageOutput
|
||||
from invokeai.app.services.image_records.image_records_common import ImageCategory, ResourceOrigin
|
||||
from invokeai.backend.image_util.basicsr.rrdbnet_arch import RRDBNet
|
||||
from invokeai.backend.image_util.realesrgan.realesrgan import RealESRGAN
|
||||
from invokeai.backend.util.devices import choose_torch_device
|
||||
|
||||
|
||||
@ -54,6 +54,17 @@ class DefaultInvocationProcessor(InvocationProcessorABC):
|
||||
else None
|
||||
)
|
||||
|
||||
def stats_cleanup(graph_execution_state_id: str) -> None:
|
||||
if profiler:
|
||||
profile_path = profiler.stop()
|
||||
stats_path = profile_path.with_suffix(".json")
|
||||
self.__invoker.services.performance_statistics.dump_stats(
|
||||
graph_execution_state_id=graph_execution_state_id, output_path=stats_path
|
||||
)
|
||||
with suppress(GESStatsNotFoundError):
|
||||
self.__invoker.services.performance_statistics.log_stats(graph_execution_state_id)
|
||||
self.__invoker.services.performance_statistics.reset_stats(graph_execution_state_id)
|
||||
|
||||
while not stop_event.is_set():
|
||||
try:
|
||||
queue_item = self.__invoker.services.queue.get()
|
||||
@ -156,8 +167,7 @@ class DefaultInvocationProcessor(InvocationProcessorABC):
|
||||
pass
|
||||
|
||||
except CanceledException:
|
||||
with suppress(GESStatsNotFoundError):
|
||||
self.__invoker.services.performance_statistics.reset_stats(graph_execution_state.id)
|
||||
stats_cleanup(graph_execution_state.id)
|
||||
pass
|
||||
|
||||
except Exception as e:
|
||||
@ -182,8 +192,6 @@ class DefaultInvocationProcessor(InvocationProcessorABC):
|
||||
error_type=e.__class__.__name__,
|
||||
error=error,
|
||||
)
|
||||
with suppress(GESStatsNotFoundError):
|
||||
self.__invoker.services.performance_statistics.reset_stats(graph_execution_state.id)
|
||||
pass
|
||||
|
||||
# Check queue to see if this is canceled, and skip if so
|
||||
@ -215,21 +223,13 @@ class DefaultInvocationProcessor(InvocationProcessorABC):
|
||||
error=traceback.format_exc(),
|
||||
)
|
||||
elif is_complete:
|
||||
with suppress(GESStatsNotFoundError):
|
||||
self.__invoker.services.performance_statistics.log_stats(graph_execution_state.id)
|
||||
self.__invoker.services.events.emit_graph_execution_complete(
|
||||
queue_batch_id=queue_item.session_queue_batch_id,
|
||||
queue_item_id=queue_item.session_queue_item_id,
|
||||
queue_id=queue_item.session_queue_id,
|
||||
graph_execution_state_id=graph_execution_state.id,
|
||||
)
|
||||
if profiler:
|
||||
profile_path = profiler.stop()
|
||||
stats_path = profile_path.with_suffix(".json")
|
||||
self.__invoker.services.performance_statistics.dump_stats(
|
||||
graph_execution_state_id=graph_execution_state.id, output_path=stats_path
|
||||
)
|
||||
self.__invoker.services.performance_statistics.reset_stats(graph_execution_state.id)
|
||||
stats_cleanup(graph_execution_state.id)
|
||||
|
||||
except KeyboardInterrupt:
|
||||
pass # Log something? KeyboardInterrupt is probably not going to be seen by the processor
|
||||
|
||||
@ -113,9 +113,9 @@ class InvocationStatsService(InvocationStatsServiceBase):
|
||||
del self._stats[graph_execution_state_id]
|
||||
del self._cache_stats[graph_execution_state_id]
|
||||
except KeyError as e:
|
||||
msg = f"Attempted to clear statistics for unknown graph {graph_execution_state_id}: {e}."
|
||||
logger.error(msg)
|
||||
raise GESStatsNotFoundError(msg) from e
|
||||
raise GESStatsNotFoundError(
|
||||
f"Attempted to clear statistics for unknown graph {graph_execution_state_id}: {e}."
|
||||
) from e
|
||||
|
||||
def get_stats(self, graph_execution_state_id: str) -> InvocationStatsSummary:
|
||||
graph_stats_summary = self._get_graph_summary(graph_execution_state_id)
|
||||
@ -143,9 +143,9 @@ class InvocationStatsService(InvocationStatsServiceBase):
|
||||
try:
|
||||
cache_stats = self._cache_stats[graph_execution_state_id]
|
||||
except KeyError as e:
|
||||
msg = f"Attempted to get model cache statistics for unknown graph {graph_execution_state_id}: {e}."
|
||||
logger.error(msg)
|
||||
raise GESStatsNotFoundError(msg) from e
|
||||
raise GESStatsNotFoundError(
|
||||
f"Attempted to get model cache statistics for unknown graph {graph_execution_state_id}: {e}."
|
||||
) from e
|
||||
|
||||
return ModelCacheStatsSummary(
|
||||
cache_hits=cache_stats.hits,
|
||||
@ -161,9 +161,9 @@ class InvocationStatsService(InvocationStatsServiceBase):
|
||||
try:
|
||||
graph_stats = self._stats[graph_execution_state_id]
|
||||
except KeyError as e:
|
||||
msg = f"Attempted to get graph statistics for unknown graph {graph_execution_state_id}: {e}."
|
||||
logger.error(msg)
|
||||
raise GESStatsNotFoundError(msg) from e
|
||||
raise GESStatsNotFoundError(
|
||||
f"Attempted to get graph statistics for unknown graph {graph_execution_state_id}: {e}."
|
||||
) from e
|
||||
|
||||
return graph_stats.get_graph_stats_summary(graph_execution_state_id)
|
||||
|
||||
@ -171,8 +171,8 @@ class InvocationStatsService(InvocationStatsServiceBase):
|
||||
try:
|
||||
graph_stats = self._stats[graph_execution_state_id]
|
||||
except KeyError as e:
|
||||
msg = f"Attempted to get node statistics for unknown graph {graph_execution_state_id}: {e}."
|
||||
logger.error(msg)
|
||||
raise GESStatsNotFoundError(msg) from e
|
||||
raise GESStatsNotFoundError(
|
||||
f"Attempted to get node statistics for unknown graph {graph_execution_state_id}: {e}."
|
||||
) from e
|
||||
|
||||
return graph_stats.get_node_stats_summaries()
|
||||
|
||||
@ -2,7 +2,7 @@
|
||||
|
||||
import copy
|
||||
import itertools
|
||||
from typing import Annotated, Any, Optional, Union, get_args, get_origin, get_type_hints
|
||||
from typing import Annotated, Any, Optional, TypeVar, Union, get_args, get_origin, get_type_hints
|
||||
|
||||
import networkx as nx
|
||||
from pydantic import BaseModel, ConfigDict, field_validator, model_validator
|
||||
@ -141,6 +141,16 @@ def are_connections_compatible(
|
||||
return are_connection_types_compatible(from_node_field, to_node_field)
|
||||
|
||||
|
||||
T = TypeVar("T")
|
||||
|
||||
|
||||
def copydeep(obj: T) -> T:
|
||||
"""Deep-copies an object. If it is a pydantic model, use the model's copy method."""
|
||||
if isinstance(obj, BaseModel):
|
||||
return obj.model_copy(deep=True)
|
||||
return copy.deepcopy(obj)
|
||||
|
||||
|
||||
class NodeAlreadyInGraphError(ValueError):
|
||||
pass
|
||||
|
||||
@ -1118,17 +1128,22 @@ class GraphExecutionState(BaseModel):
|
||||
|
||||
def _prepare_inputs(self, node: BaseInvocation):
|
||||
input_edges = [e for e in self.execution_graph.edges if e.destination.node_id == node.id]
|
||||
# Inputs must be deep-copied, else if a node mutates the object, other nodes that get the same input
|
||||
# will see the mutation.
|
||||
if isinstance(node, CollectInvocation):
|
||||
output_collection = [
|
||||
getattr(self.results[edge.source.node_id], edge.source.field)
|
||||
copydeep(getattr(self.results[edge.source.node_id], edge.source.field))
|
||||
for edge in input_edges
|
||||
if edge.destination.field == "item"
|
||||
]
|
||||
node.collection = output_collection
|
||||
else:
|
||||
for edge in input_edges:
|
||||
output_value = getattr(self.results[edge.source.node_id], edge.source.field)
|
||||
setattr(node, edge.destination.field, output_value)
|
||||
setattr(
|
||||
node,
|
||||
edge.destination.field,
|
||||
copydeep(getattr(self.results[edge.source.node_id], edge.source.field)),
|
||||
)
|
||||
|
||||
# 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:
|
||||
|
||||
201
invokeai/backend/image_util/basicsr/LICENSE
Normal file
201
invokeai/backend/image_util/basicsr/LICENSE
Normal file
@ -0,0 +1,201 @@
|
||||
Apache License
|
||||
Version 2.0, January 2004
|
||||
http://www.apache.org/licenses/
|
||||
|
||||
TERMS AND CONDITIONS FOR USE, REPRODUCTION, AND DISTRIBUTION
|
||||
|
||||
1. Definitions.
|
||||
|
||||
"License" shall mean the terms and conditions for use, reproduction,
|
||||
and distribution as defined by Sections 1 through 9 of this document.
|
||||
|
||||
"Licensor" shall mean the copyright owner or entity authorized by
|
||||
the copyright owner that is granting the License.
|
||||
|
||||
"Legal Entity" shall mean the union of the acting entity and all
|
||||
other entities that control, are controlled by, or are under common
|
||||
control with that entity. For the purposes of this definition,
|
||||
"control" means (i) the power, direct or indirect, to cause the
|
||||
direction or management of such entity, whether by contract or
|
||||
otherwise, or (ii) ownership of fifty percent (50%) or more of the
|
||||
outstanding shares, or (iii) beneficial ownership of such entity.
|
||||
|
||||
"You" (or "Your") shall mean an individual or Legal Entity
|
||||
exercising permissions granted by this License.
|
||||
|
||||
"Source" form shall mean the preferred form for making modifications,
|
||||
including but not limited to software source code, documentation
|
||||
source, and configuration files.
|
||||
|
||||
"Object" form shall mean any form resulting from mechanical
|
||||
transformation or translation of a Source form, including but
|
||||
not limited to compiled object code, generated documentation,
|
||||
and conversions to other media types.
|
||||
|
||||
"Work" shall mean the work of authorship, whether in Source or
|
||||
Object form, made available under the License, as indicated by a
|
||||
copyright notice that is included in or attached to the work
|
||||
(an example is provided in the Appendix below).
|
||||
|
||||
"Derivative Works" shall mean any work, whether in Source or Object
|
||||
form, that is based on (or derived from) the Work and for which the
|
||||
editorial revisions, annotations, elaborations, or other modifications
|
||||
represent, as a whole, an original work of authorship. For the purposes
|
||||
of this License, Derivative Works shall not include works that remain
|
||||
separable from, or merely link (or bind by name) to the interfaces of,
|
||||
the Work and Derivative Works thereof.
|
||||
|
||||
"Contribution" shall mean any work of authorship, including
|
||||
the original version of the Work and any modifications or additions
|
||||
to that Work or Derivative Works thereof, that is intentionally
|
||||
submitted to Licensor for inclusion in the Work by the copyright owner
|
||||
or by an individual or Legal Entity authorized to submit on behalf of
|
||||
the copyright owner. For the purposes of this definition, "submitted"
|
||||
means any form of electronic, verbal, or written communication sent
|
||||
to the Licensor or its representatives, including but not limited to
|
||||
communication on electronic mailing lists, source code control systems,
|
||||
and issue tracking systems that are managed by, or on behalf of, the
|
||||
Licensor for the purpose of discussing and improving the Work, but
|
||||
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|
||||
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|
||||
|
||||
"Contributor" shall mean Licensor and any individual or Legal Entity
|
||||
on behalf of whom a Contribution has been received by Licensor and
|
||||
subsequently incorporated within the Work.
|
||||
|
||||
2. Grant of Copyright License. Subject to the terms and conditions of
|
||||
this License, each Contributor hereby grants to You a perpetual,
|
||||
worldwide, non-exclusive, no-charge, royalty-free, irrevocable
|
||||
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|
||||
publicly display, publicly perform, sublicense, and distribute the
|
||||
Work and such Derivative Works in Source or Object form.
|
||||
|
||||
3. Grant of Patent License. Subject to the terms and conditions of
|
||||
this License, each Contributor hereby grants to You a perpetual,
|
||||
worldwide, non-exclusive, no-charge, royalty-free, irrevocable
|
||||
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|
||||
use, offer to sell, sell, import, and otherwise transfer the Work,
|
||||
where such license applies only to those patent claims licensable
|
||||
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|
||||
Contribution(s) alone or by combination of their Contribution(s)
|
||||
with the Work to which such Contribution(s) was submitted. If You
|
||||
institute patent litigation against any entity (including a
|
||||
cross-claim or counterclaim in a lawsuit) alleging that the Work
|
||||
or a Contribution incorporated within the Work constitutes direct
|
||||
or contributory patent infringement, then any patent licenses
|
||||
granted to You under this License for that Work shall terminate
|
||||
as of the date such litigation is filed.
|
||||
|
||||
4. Redistribution. You may reproduce and distribute copies of the
|
||||
Work or Derivative Works thereof in any medium, with or without
|
||||
modifications, and in Source or Object form, provided that You
|
||||
meet the following conditions:
|
||||
|
||||
(a) You must give any other recipients of the Work or
|
||||
Derivative Works a copy of this License; and
|
||||
|
||||
(b) You must cause any modified files to carry prominent notices
|
||||
stating that You changed the files; and
|
||||
|
||||
(c) You must retain, in the Source form of any Derivative Works
|
||||
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|
||||
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|
||||
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|
||||
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|
||||
|
||||
(d) If the Work includes a "NOTICE" text file as part of its
|
||||
distribution, then any Derivative Works that You distribute must
|
||||
include a readable copy of the attribution notices contained
|
||||
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|
||||
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|
||||
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|
||||
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|
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
|
||||
You may add Your own copyright statement to Your modifications and
|
||||
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|
||||
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|
||||
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|
||||
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|
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|
||||
|
||||
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|
||||
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|
||||
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|
||||
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|
||||
Notwithstanding the above, nothing herein shall supersede or modify
|
||||
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|
||||
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||||
|
||||
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|
||||
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|
||||
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||||
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|
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|
||||
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||||
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|
||||
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|
||||
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|
||||
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|
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|
||||
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|
||||
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||||
on Your own behalf and on Your sole responsibility, not on behalf
|
||||
of any other Contributor, and only if You agree to indemnify,
|
||||
defend, and hold each Contributor harmless for any liability
|
||||
incurred by, or claims asserted against, such Contributor by reason
|
||||
of your accepting any such warranty or additional liability.
|
||||
|
||||
END OF TERMS AND CONDITIONS
|
||||
|
||||
APPENDIX: How to apply the Apache License to your work.
|
||||
|
||||
To apply the Apache License to your work, attach the following
|
||||
boilerplate notice, with the fields enclosed by brackets "[]"
|
||||
replaced with your own identifying information. (Don't include
|
||||
the brackets!) The text should be enclosed in the appropriate
|
||||
comment syntax for the file format. We also recommend that a
|
||||
file or class name and description of purpose be included on the
|
||||
same "printed page" as the copyright notice for easier
|
||||
identification within third-party archives.
|
||||
|
||||
Copyright 2018-2022 BasicSR Authors
|
||||
|
||||
Licensed under the Apache License, Version 2.0 (the "License");
|
||||
you may not use this file except in compliance with the License.
|
||||
You may obtain a copy of the License at
|
||||
|
||||
http://www.apache.org/licenses/LICENSE-2.0
|
||||
|
||||
Unless required by applicable law or agreed to in writing, software
|
||||
distributed under the License is distributed on an "AS IS" BASIS,
|
||||
WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
|
||||
See the License for the specific language governing permissions and
|
||||
limitations under the License.
|
||||
18
invokeai/backend/image_util/basicsr/__init__.py
Normal file
18
invokeai/backend/image_util/basicsr/__init__.py
Normal file
@ -0,0 +1,18 @@
|
||||
"""
|
||||
Adapted from https://github.com/XPixelGroup/BasicSR
|
||||
License: Apache-2.0
|
||||
|
||||
As of Feb 2024, `basicsr` appears to be unmaintained. It imports a function from `torchvision` that is removed in
|
||||
`torchvision` 0.17. Here is the deprecation warning:
|
||||
|
||||
UserWarning: The torchvision.transforms.functional_tensor module is deprecated in 0.15 and will be **removed in
|
||||
0.17**. Please don't rely on it. You probably just need to use APIs in torchvision.transforms.functional or in
|
||||
torchvision.transforms.v2.functional.
|
||||
|
||||
As a result, a dependency on `basicsr` means we cannot keep our `torchvision` dependency up to date.
|
||||
|
||||
Because we only rely on a single class `RRDBNet` from `basicsr`, we've copied the relevant code here and removed the
|
||||
dependency on `basicsr`.
|
||||
|
||||
The code is almost unchanged, only a few type annotations have been added. The license is also copied.
|
||||
"""
|
||||
75
invokeai/backend/image_util/basicsr/arch_util.py
Normal file
75
invokeai/backend/image_util/basicsr/arch_util.py
Normal file
@ -0,0 +1,75 @@
|
||||
from typing import Type
|
||||
|
||||
import torch
|
||||
from torch import nn as nn
|
||||
from torch.nn import init as init
|
||||
from torch.nn.modules.batchnorm import _BatchNorm
|
||||
|
||||
|
||||
@torch.no_grad()
|
||||
def default_init_weights(
|
||||
module_list: list[nn.Module] | nn.Module, scale: float = 1, bias_fill: float = 0, **kwargs
|
||||
) -> None:
|
||||
"""Initialize network weights.
|
||||
|
||||
Args:
|
||||
module_list (list[nn.Module] | nn.Module): Modules to be initialized.
|
||||
scale (float): Scale initialized weights, especially for residual
|
||||
blocks. Default: 1.
|
||||
bias_fill (float): The value to fill bias. Default: 0
|
||||
kwargs (dict): Other arguments for initialization function.
|
||||
"""
|
||||
if not isinstance(module_list, list):
|
||||
module_list = [module_list]
|
||||
for module in module_list:
|
||||
for m in module.modules():
|
||||
if isinstance(m, nn.Conv2d):
|
||||
init.kaiming_normal_(m.weight, **kwargs)
|
||||
m.weight.data *= scale
|
||||
if m.bias is not None:
|
||||
m.bias.data.fill_(bias_fill)
|
||||
elif isinstance(m, nn.Linear):
|
||||
init.kaiming_normal_(m.weight, **kwargs)
|
||||
m.weight.data *= scale
|
||||
if m.bias is not None:
|
||||
m.bias.data.fill_(bias_fill)
|
||||
elif isinstance(m, _BatchNorm):
|
||||
init.constant_(m.weight, 1)
|
||||
if m.bias is not None:
|
||||
m.bias.data.fill_(bias_fill)
|
||||
|
||||
|
||||
def make_layer(basic_block: Type[nn.Module], num_basic_block: int, **kwarg) -> nn.Sequential:
|
||||
"""Make layers by stacking the same blocks.
|
||||
|
||||
Args:
|
||||
basic_block (Type[nn.Module]): nn.Module class for basic block.
|
||||
num_basic_block (int): number of blocks.
|
||||
|
||||
Returns:
|
||||
nn.Sequential: Stacked blocks in nn.Sequential.
|
||||
"""
|
||||
layers = []
|
||||
for _ in range(num_basic_block):
|
||||
layers.append(basic_block(**kwarg))
|
||||
return nn.Sequential(*layers)
|
||||
|
||||
|
||||
# TODO: may write a cpp file
|
||||
def pixel_unshuffle(x: torch.Tensor, scale: int) -> torch.Tensor:
|
||||
"""Pixel unshuffle.
|
||||
|
||||
Args:
|
||||
x (Tensor): Input feature with shape (b, c, hh, hw).
|
||||
scale (int): Downsample ratio.
|
||||
|
||||
Returns:
|
||||
Tensor: the pixel unshuffled feature.
|
||||
"""
|
||||
b, c, hh, hw = x.size()
|
||||
out_channel = c * (scale**2)
|
||||
assert hh % scale == 0 and hw % scale == 0
|
||||
h = hh // scale
|
||||
w = hw // scale
|
||||
x_view = x.view(b, c, h, scale, w, scale)
|
||||
return x_view.permute(0, 1, 3, 5, 2, 4).reshape(b, out_channel, h, w)
|
||||
125
invokeai/backend/image_util/basicsr/rrdbnet_arch.py
Normal file
125
invokeai/backend/image_util/basicsr/rrdbnet_arch.py
Normal file
@ -0,0 +1,125 @@
|
||||
import torch
|
||||
from torch import nn as nn
|
||||
from torch.nn import functional as F
|
||||
|
||||
from .arch_util import default_init_weights, make_layer, pixel_unshuffle
|
||||
|
||||
|
||||
class ResidualDenseBlock(nn.Module):
|
||||
"""Residual Dense Block.
|
||||
|
||||
Used in RRDB block in ESRGAN.
|
||||
|
||||
Args:
|
||||
num_feat (int): Channel number of intermediate features.
|
||||
num_grow_ch (int): Channels for each growth.
|
||||
"""
|
||||
|
||||
def __init__(self, num_feat: int = 64, num_grow_ch: int = 32) -> None:
|
||||
super(ResidualDenseBlock, self).__init__()
|
||||
self.conv1 = nn.Conv2d(num_feat, num_grow_ch, 3, 1, 1)
|
||||
self.conv2 = nn.Conv2d(num_feat + num_grow_ch, num_grow_ch, 3, 1, 1)
|
||||
self.conv3 = nn.Conv2d(num_feat + 2 * num_grow_ch, num_grow_ch, 3, 1, 1)
|
||||
self.conv4 = nn.Conv2d(num_feat + 3 * num_grow_ch, num_grow_ch, 3, 1, 1)
|
||||
self.conv5 = nn.Conv2d(num_feat + 4 * num_grow_ch, num_feat, 3, 1, 1)
|
||||
|
||||
self.lrelu = nn.LeakyReLU(negative_slope=0.2, inplace=True)
|
||||
|
||||
# initialization
|
||||
default_init_weights([self.conv1, self.conv2, self.conv3, self.conv4, self.conv5], 0.1)
|
||||
|
||||
def forward(self, x: torch.Tensor) -> torch.Tensor:
|
||||
x1 = self.lrelu(self.conv1(x))
|
||||
x2 = self.lrelu(self.conv2(torch.cat((x, x1), 1)))
|
||||
x3 = self.lrelu(self.conv3(torch.cat((x, x1, x2), 1)))
|
||||
x4 = self.lrelu(self.conv4(torch.cat((x, x1, x2, x3), 1)))
|
||||
x5 = self.conv5(torch.cat((x, x1, x2, x3, x4), 1))
|
||||
# Empirically, we use 0.2 to scale the residual for better performance
|
||||
return x5 * 0.2 + x
|
||||
|
||||
|
||||
class RRDB(nn.Module):
|
||||
"""Residual in Residual Dense Block.
|
||||
|
||||
Used in RRDB-Net in ESRGAN.
|
||||
|
||||
Args:
|
||||
num_feat (int): Channel number of intermediate features.
|
||||
num_grow_ch (int): Channels for each growth.
|
||||
"""
|
||||
|
||||
def __init__(self, num_feat: int, num_grow_ch: int = 32) -> None:
|
||||
super(RRDB, self).__init__()
|
||||
self.rdb1 = ResidualDenseBlock(num_feat, num_grow_ch)
|
||||
self.rdb2 = ResidualDenseBlock(num_feat, num_grow_ch)
|
||||
self.rdb3 = ResidualDenseBlock(num_feat, num_grow_ch)
|
||||
|
||||
def forward(self, x: torch.Tensor) -> torch.Tensor:
|
||||
out = self.rdb1(x)
|
||||
out = self.rdb2(out)
|
||||
out = self.rdb3(out)
|
||||
# Empirically, we use 0.2 to scale the residual for better performance
|
||||
return out * 0.2 + x
|
||||
|
||||
|
||||
class RRDBNet(nn.Module):
|
||||
"""Networks consisting of Residual in Residual Dense Block, which is used
|
||||
in ESRGAN.
|
||||
|
||||
ESRGAN: Enhanced Super-Resolution Generative Adversarial Networks.
|
||||
|
||||
We extend ESRGAN for scale x2 and scale x1.
|
||||
Note: This is one option for scale 1, scale 2 in RRDBNet.
|
||||
We first employ the pixel-unshuffle (an inverse operation of pixelshuffle to reduce the spatial size
|
||||
and enlarge the channel size before feeding inputs into the main ESRGAN architecture.
|
||||
|
||||
Args:
|
||||
num_in_ch (int): Channel number of inputs.
|
||||
num_out_ch (int): Channel number of outputs.
|
||||
num_feat (int): Channel number of intermediate features.
|
||||
Default: 64
|
||||
num_block (int): Block number in the trunk network. Defaults: 23
|
||||
num_grow_ch (int): Channels for each growth. Default: 32.
|
||||
"""
|
||||
|
||||
def __init__(
|
||||
self,
|
||||
num_in_ch: int,
|
||||
num_out_ch: int,
|
||||
scale: int = 4,
|
||||
num_feat: int = 64,
|
||||
num_block: int = 23,
|
||||
num_grow_ch: int = 32,
|
||||
) -> None:
|
||||
super(RRDBNet, self).__init__()
|
||||
self.scale = scale
|
||||
if scale == 2:
|
||||
num_in_ch = num_in_ch * 4
|
||||
elif scale == 1:
|
||||
num_in_ch = num_in_ch * 16
|
||||
self.conv_first = nn.Conv2d(num_in_ch, num_feat, 3, 1, 1)
|
||||
self.body = make_layer(RRDB, num_block, num_feat=num_feat, num_grow_ch=num_grow_ch)
|
||||
self.conv_body = nn.Conv2d(num_feat, num_feat, 3, 1, 1)
|
||||
# upsample
|
||||
self.conv_up1 = nn.Conv2d(num_feat, num_feat, 3, 1, 1)
|
||||
self.conv_up2 = nn.Conv2d(num_feat, num_feat, 3, 1, 1)
|
||||
self.conv_hr = nn.Conv2d(num_feat, num_feat, 3, 1, 1)
|
||||
self.conv_last = nn.Conv2d(num_feat, num_out_ch, 3, 1, 1)
|
||||
|
||||
self.lrelu = nn.LeakyReLU(negative_slope=0.2, inplace=True)
|
||||
|
||||
def forward(self, x: torch.Tensor) -> torch.Tensor:
|
||||
if self.scale == 2:
|
||||
feat = pixel_unshuffle(x, scale=2)
|
||||
elif self.scale == 1:
|
||||
feat = pixel_unshuffle(x, scale=4)
|
||||
else:
|
||||
feat = x
|
||||
feat = self.conv_first(feat)
|
||||
body_feat = self.conv_body(self.body(feat))
|
||||
feat = feat + body_feat
|
||||
# upsample
|
||||
feat = self.lrelu(self.conv_up1(F.interpolate(feat, scale_factor=2, mode="nearest")))
|
||||
feat = self.lrelu(self.conv_up2(F.interpolate(feat, scale_factor=2, mode="nearest")))
|
||||
out = self.conv_last(self.lrelu(self.conv_hr(feat)))
|
||||
return out
|
||||
@ -7,10 +7,10 @@ import cv2
|
||||
import numpy as np
|
||||
import numpy.typing as npt
|
||||
import torch
|
||||
from basicsr.archs.rrdbnet_arch import RRDBNet
|
||||
from cv2.typing import MatLike
|
||||
from tqdm import tqdm
|
||||
|
||||
from invokeai.backend.image_util.basicsr.rrdbnet_arch import RRDBNet
|
||||
from invokeai.backend.util.devices import choose_torch_device
|
||||
|
||||
"""
|
||||
|
||||
@ -56,7 +56,7 @@
|
||||
"nodeEditor": "Knoten Editor",
|
||||
"statusMergingModels": "Modelle zusammenführen",
|
||||
"ipAdapter": "IP Adapter",
|
||||
"controlAdapter": "Control Adapter",
|
||||
"controlAdapter": "Control-Adapter",
|
||||
"auto": "Automatisch",
|
||||
"controlNet": "ControlNet",
|
||||
"imageFailedToLoad": "Kann Bild nicht laden",
|
||||
@ -75,12 +75,12 @@
|
||||
"linear": "Linear",
|
||||
"imagePrompt": "Bild Prompt",
|
||||
"checkpoint": "Checkpoint",
|
||||
"inpaint": "inpaint",
|
||||
"inpaint": "Inpaint",
|
||||
"simple": "Einfach",
|
||||
"template": "Vorlage",
|
||||
"outputs": "Ausgabe",
|
||||
"data": "Daten",
|
||||
"safetensors": "Safetensors",
|
||||
"safetensors": "Safe-Tensors",
|
||||
"outpaint": "Ausmalen",
|
||||
"details": "Details",
|
||||
"format": "Format",
|
||||
@ -115,7 +115,8 @@
|
||||
"orderBy": "Ordnen nach",
|
||||
"saveAs": "Speicher als",
|
||||
"updated": "Aktualisiert",
|
||||
"copy": "Kopieren"
|
||||
"copy": "Kopieren",
|
||||
"aboutHeading": "Nutzen Sie Ihre kreative Energie"
|
||||
},
|
||||
"gallery": {
|
||||
"generations": "Erzeugungen",
|
||||
@ -146,26 +147,30 @@
|
||||
"deleteImagePermanent": "Gelöschte Bilder können nicht wiederhergestellt werden.",
|
||||
"autoAssignBoardOnClick": "Board per Klick automatisch zuweisen",
|
||||
"noImageSelected": "Kein Bild ausgewählt",
|
||||
"problemDeletingImagesDesc": "Eins oder mehr Bilder könnten nicht gelöscht werden",
|
||||
"problemDeletingImagesDesc": "Ein oder mehrere Bilder konnten nicht gelöscht werden",
|
||||
"starImage": "Bild markieren",
|
||||
"assets": "Ressourcen",
|
||||
"unstarImage": "Markierung Entfernen",
|
||||
"image": "Bild",
|
||||
"deleteSelection": "Lösche markierte"
|
||||
"deleteSelection": "Lösche markierte",
|
||||
"dropToUpload": "$t(gallery.drop) zum hochladen",
|
||||
"dropOrUpload": "$t(gallery.drop) oder hochladen",
|
||||
"drop": "Ablegen",
|
||||
"problemDeletingImages": "Problem beim Löschen der Bilder"
|
||||
},
|
||||
"hotkeys": {
|
||||
"keyboardShortcuts": "Tastenkürzel",
|
||||
"appHotkeys": "App-Tastenkombinationen",
|
||||
"generalHotkeys": "Allgemeine Tastenkürzel",
|
||||
"galleryHotkeys": "Galerie Tastenkürzel",
|
||||
"unifiedCanvasHotkeys": "Unified Canvas Tastenkürzel",
|
||||
"generalHotkeys": "Allgemein",
|
||||
"galleryHotkeys": "Galerie",
|
||||
"unifiedCanvasHotkeys": "Leinwand",
|
||||
"invoke": {
|
||||
"desc": "Ein Bild erzeugen",
|
||||
"title": "Invoke"
|
||||
},
|
||||
"cancel": {
|
||||
"title": "Abbrechen",
|
||||
"desc": "Bilderzeugung abbrechen"
|
||||
"desc": "Aktuelle Bilderzeugung abbrechen"
|
||||
},
|
||||
"focusPrompt": {
|
||||
"title": "Fokussiere Prompt",
|
||||
@ -351,42 +356,55 @@
|
||||
"title": "Staging-Bild akzeptieren",
|
||||
"desc": "Akzeptieren Sie das aktuelle Bild des Staging-Bereichs"
|
||||
},
|
||||
"nodesHotkeys": "Knoten Tastenkürzel",
|
||||
"nodesHotkeys": "Knoten",
|
||||
"addNodes": {
|
||||
"title": "Knotenpunkt hinzufügen",
|
||||
"desc": "Öffnet das Menü zum Hinzufügen von Knoten"
|
||||
},
|
||||
"cancelAndClear": {
|
||||
"title": "Abbruch und leeren"
|
||||
"title": "Abbruch und leeren",
|
||||
"desc": "Aktuelle Berechnung abbrechen und alle wartenden löschen"
|
||||
},
|
||||
"noHotkeysFound": "Kein Hotkey gefunden",
|
||||
"searchHotkeys": "Hotkeys durchsuchen",
|
||||
"clearSearch": "Suche leeren"
|
||||
"clearSearch": "Suche leeren",
|
||||
"resetOptionsAndGallery": {
|
||||
"desc": "Optionen und Galerie-Panels zurücksetzen",
|
||||
"title": "Optionen und Galerie zurücksetzen"
|
||||
},
|
||||
"remixImage": {
|
||||
"desc": "Alle Parameter außer Seed vom aktuellen Bild verwenden",
|
||||
"title": "Remix des Bilds erstellen"
|
||||
},
|
||||
"toggleOptionsAndGallery": {
|
||||
"title": "Optionen und Galerie umschalten",
|
||||
"desc": "Optionen und Galerie-Panels öffnen und schließen"
|
||||
}
|
||||
},
|
||||
"modelManager": {
|
||||
"modelAdded": "Model hinzugefügt",
|
||||
"modelUpdated": "Model aktualisiert",
|
||||
"modelEntryDeleted": "Modelleintrag gelöscht",
|
||||
"cannotUseSpaces": "Leerzeichen können nicht verwendet werden",
|
||||
"addNew": "Neue hinzufügen",
|
||||
"addNewModel": "Neues Model hinzufügen",
|
||||
"addNew": "Neu hinzufügen",
|
||||
"addNewModel": "Neues Modell hinzufügen",
|
||||
"addManually": "Manuell hinzufügen",
|
||||
"nameValidationMsg": "Geben Sie einen Namen für Ihr Model ein",
|
||||
"description": "Beschreibung",
|
||||
"descriptionValidationMsg": "Fügen Sie eine Beschreibung für Ihr Model hinzu",
|
||||
"config": "Konfiguration",
|
||||
"configValidationMsg": "Pfad zur Konfigurationsdatei Ihres Models.",
|
||||
"configValidationMsg": "Pfad zur Konfigurationsdatei Ihres Modells.",
|
||||
"modelLocation": "Ort des Models",
|
||||
"modelLocationValidationMsg": "Pfad zum Speicherort Ihres Models",
|
||||
"vaeLocation": "VAE Ort",
|
||||
"vaeLocationValidationMsg": "Pfad zum Speicherort Ihres VAE.",
|
||||
"width": "Breite",
|
||||
"widthValidationMsg": "Standardbreite Ihres Models.",
|
||||
"widthValidationMsg": "Standardbreite Ihres Modells.",
|
||||
"height": "Höhe",
|
||||
"heightValidationMsg": "Standardbhöhe Ihres Models.",
|
||||
"addModel": "Model hinzufügen",
|
||||
"addModel": "Modell hinzufügen",
|
||||
"updateModel": "Model aktualisieren",
|
||||
"availableModels": "Verfügbare Models",
|
||||
"availableModels": "Verfügbare Modelle",
|
||||
"search": "Suche",
|
||||
"load": "Laden",
|
||||
"active": "Aktiv",
|
||||
@ -483,7 +501,7 @@
|
||||
"quickAdd": "Schnell hinzufügen",
|
||||
"simpleModelDesc": "Geben Sie einen Pfad zu einem lokalen Diffusers-Modell, einem lokalen Checkpoint-/Safetensors-Modell, einer HuggingFace-Repo-ID oder einer Checkpoint-/Diffusers-Modell-URL an.",
|
||||
"modelDeleted": "Modell gelöscht",
|
||||
"inpainting": "v1 Inpainting",
|
||||
"inpainting": "V1-Inpainting",
|
||||
"modelUpdateFailed": "Modellaktualisierung fehlgeschlagen",
|
||||
"useCustomConfig": "Benutzerdefinierte Konfiguration verwenden",
|
||||
"settings": "Einstellungen",
|
||||
@ -500,12 +518,14 @@
|
||||
"interpolationType": "Interpolationstyp",
|
||||
"oliveModels": "Olives",
|
||||
"variant": "Variante",
|
||||
"loraModels": "LoRAs",
|
||||
"loraModels": "\"LoRAs\"",
|
||||
"modelDeleteFailed": "Modell konnte nicht gelöscht werden",
|
||||
"mergedModelName": "Zusammengeführter Modellname",
|
||||
"checkpointOrSafetensors": "$t(common.checkpoint) / $t(common.safetensors)",
|
||||
"formMessageDiffusersModelLocation": "Diffusers Modell Speicherort",
|
||||
"noModelSelected": "Kein Modell ausgewählt"
|
||||
"noModelSelected": "Kein Modell ausgewählt",
|
||||
"conversionNotSupported": "Umwandlung nicht unterstützt",
|
||||
"configFile": "Konfigurationsdatei"
|
||||
},
|
||||
"parameters": {
|
||||
"images": "Bilder",
|
||||
@ -583,7 +603,8 @@
|
||||
"resetWebUIDesc2": "Wenn die Bilder nicht in der Galerie angezeigt werden oder etwas anderes nicht funktioniert, versuchen Sie bitte, die Einstellungen zurückzusetzen, bevor Sie einen Fehler auf GitHub melden.",
|
||||
"resetComplete": "Die Web-Oberfläche wurde zurückgesetzt.",
|
||||
"models": "Modelle",
|
||||
"useSlidersForAll": "Schieberegler für alle Optionen verwenden"
|
||||
"useSlidersForAll": "Schieberegler für alle Optionen verwenden",
|
||||
"showAdvancedOptions": "Erweiterte Optionen anzeigen"
|
||||
},
|
||||
"toast": {
|
||||
"tempFoldersEmptied": "Temp-Ordner geleert",
|
||||
@ -626,7 +647,7 @@
|
||||
"upscale": "Verwenden Sie ESRGAN, um das Bild unmittelbar nach der Erzeugung zu vergrößern.",
|
||||
"faceCorrection": "Gesichtskorrektur mit GFPGAN oder Codeformer: Der Algorithmus erkennt Gesichter im Bild und korrigiert alle Fehler. Ein hoher Wert verändert das Bild stärker, was zu attraktiveren Gesichtern führt. Codeformer mit einer höheren Genauigkeit bewahrt das Originalbild auf Kosten einer stärkeren Gesichtskorrektur.",
|
||||
"imageToImage": "Bild zu Bild lädt ein beliebiges Bild als Ausgangsbild, aus dem dann zusammen mit dem Prompt ein neues Bild erzeugt wird. Je höher der Wert ist, desto stärker wird das Ergebnisbild verändert. Werte von 0,0 bis 1,0 sind möglich, der empfohlene Bereich ist .25-.75",
|
||||
"boundingBox": "Der Begrenzungsrahmen ist derselbe wie die Einstellungen für Breite und Höhe bei Text zu Bild oder Bild zu Bild. Es wird nur der Bereich innerhalb des Rahmens verarbeitet.",
|
||||
"boundingBox": "Der Begrenzungsrahmen ist derselbe wie die Einstellungen für Breite und Höhe bei Text-zu-Bild oder Bild-zu-Bild. Es wird nur der Bereich innerhalb des Rahmens verarbeitet.",
|
||||
"seamCorrection": "Steuert die Behandlung von sichtbaren Übergängen, die zwischen den erzeugten Bildern auf der Leinwand auftreten.",
|
||||
"infillAndScaling": "Verwalten Sie Infill-Methoden (für maskierte oder gelöschte Bereiche der Leinwand) und Skalierung (nützlich für kleine Begrenzungsrahmengrößen)."
|
||||
}
|
||||
@ -656,7 +677,7 @@
|
||||
"redo": "Wiederherstellen",
|
||||
"clearCanvas": "Leinwand löschen",
|
||||
"canvasSettings": "Leinwand-Einstellungen",
|
||||
"showIntermediates": "Zwischenprodukte anzeigen",
|
||||
"showIntermediates": "Zwischenbilder anzeigen",
|
||||
"showGrid": "Gitternetz anzeigen",
|
||||
"snapToGrid": "Am Gitternetz einrasten",
|
||||
"darkenOutsideSelection": "Außerhalb der Auswahl verdunkeln",
|
||||
@ -694,7 +715,7 @@
|
||||
"showResultsOff": "Zeige Ergebnisse (Aus)"
|
||||
},
|
||||
"accessibility": {
|
||||
"modelSelect": "Model Auswahl",
|
||||
"modelSelect": "Modell-Auswahl",
|
||||
"uploadImage": "Bild hochladen",
|
||||
"previousImage": "Voriges Bild",
|
||||
"useThisParameter": "Benutze diesen Parameter",
|
||||
@ -706,11 +727,11 @@
|
||||
"modifyConfig": "Optionen einstellen",
|
||||
"toggleAutoscroll": "Auroscroll ein/ausschalten",
|
||||
"toggleLogViewer": "Log Betrachter ein/ausschalten",
|
||||
"showOptionsPanel": "Zeige Optionen",
|
||||
"showOptionsPanel": "Seitenpanel anzeigen",
|
||||
"reset": "Zurücksetzten",
|
||||
"nextImage": "Nächstes Bild",
|
||||
"zoomOut": "Verkleinern",
|
||||
"rotateCounterClockwise": "Gegen den Uhrzeigersinn verdrehen",
|
||||
"rotateCounterClockwise": "Gegen den Uhrzeigersinn drehen",
|
||||
"showGalleryPanel": "Galeriefenster anzeigen",
|
||||
"exitViewer": "Betrachten beenden",
|
||||
"menu": "Menü",
|
||||
@ -732,7 +753,7 @@
|
||||
"selectBoard": "Ordner aussuchen",
|
||||
"cancel": "Abbrechen",
|
||||
"addBoard": "Ordner hinzufügen",
|
||||
"uncategorized": "Nicht kategorisiert",
|
||||
"uncategorized": "Ohne Kategorie",
|
||||
"downloadBoard": "Ordner runterladen",
|
||||
"changeBoard": "Ordner wechseln",
|
||||
"loading": "Laden...",
|
||||
@ -742,15 +763,15 @@
|
||||
"deleteBoard": "Löschen Ordner",
|
||||
"deleteBoardAndImages": "Löschen Ordner und Bilder",
|
||||
"deletedBoardsCannotbeRestored": "Gelöschte Ordner könnte nicht wiederhergestellt werden",
|
||||
"movingImagesToBoard_one": "Verschiebe {{count}} Bild zu Ordner",
|
||||
"movingImagesToBoard_other": "Verschiebe {{count}} Bilder in Ordner"
|
||||
"movingImagesToBoard_one": "Verschiebe {{count}} Bild zu Ordner:",
|
||||
"movingImagesToBoard_other": "Verschiebe {{count}} Bilder in Ordner:"
|
||||
},
|
||||
"controlnet": {
|
||||
"showAdvanced": "Zeige Erweitert",
|
||||
"contentShuffleDescription": "Mischt den Inhalt von einem Bild",
|
||||
"addT2IAdapter": "$t(common.t2iAdapter) hinzufügen",
|
||||
"importImageFromCanvas": "Importieren Bild von Zeichenfläche",
|
||||
"lineartDescription": "Konvertiere Bild zu Lineart",
|
||||
"importImageFromCanvas": "Bild von Zeichenfläche importieren",
|
||||
"lineartDescription": "Konvertiere Bild in Strichzeichnung",
|
||||
"importMaskFromCanvas": "Importiere Maske von Zeichenfläche",
|
||||
"hed": "HED",
|
||||
"hideAdvanced": "Verstecke Erweitert",
|
||||
@ -764,7 +785,7 @@
|
||||
"depthMidasDescription": "Tiefenmap erstellen mit Midas",
|
||||
"controlnet": "$t(controlnet.controlAdapter_one) #{{number}} ($t(common.controlNet))",
|
||||
"t2iEnabledControlNetDisabled": "$t(common.t2iAdapter) ist aktiv, $t(common.controlNet) ist deaktiviert",
|
||||
"weight": "Breite",
|
||||
"weight": "Einfluss",
|
||||
"selectModel": "Wähle ein Modell",
|
||||
"depthMidas": "Tiefe (Midas)",
|
||||
"w": "W",
|
||||
@ -786,17 +807,17 @@
|
||||
"toggleControlNet": "Schalten ControlNet um",
|
||||
"delete": "Löschen",
|
||||
"controlAdapter_one": "Control Adapter",
|
||||
"controlAdapter_other": "Control Adapters",
|
||||
"colorMapTileSize": "Tile Größe",
|
||||
"controlAdapter_other": "Control Adapter",
|
||||
"colorMapTileSize": "Kachelgröße",
|
||||
"depthZoeDescription": "Tiefenmap erstellen mit Zoe",
|
||||
"setControlImageDimensions": "Setze Control Bild Auflösung auf Breite/Höhe",
|
||||
"setControlImageDimensions": "Setze Control-Bild Auflösung auf Breite/Höhe",
|
||||
"handAndFace": "Hand und Gesicht",
|
||||
"enableIPAdapter": "Aktiviere IP Adapter",
|
||||
"resize": "Größe ändern",
|
||||
"resetControlImage": "Zurücksetzen vom Referenz Bild",
|
||||
"balanced": "Ausgewogen",
|
||||
"prompt": "Prompt",
|
||||
"resizeMode": "Größenänderungsmodus",
|
||||
"resizeMode": "Größe",
|
||||
"processor": "Prozessor",
|
||||
"saveControlImage": "Speichere Referenz Bild",
|
||||
"safe": "Speichern",
|
||||
@ -807,33 +828,33 @@
|
||||
"mlsdDescription": "Minimalistischer Liniensegmentdetektor",
|
||||
"openPoseDescription": "Schätzung der menschlichen Pose mit Openpose",
|
||||
"control": "Kontrolle",
|
||||
"coarse": "Coarse",
|
||||
"coarse": "Grob",
|
||||
"crop": "Zuschneiden",
|
||||
"pidiDescription": "PIDI-Bildverarbeitung",
|
||||
"mediapipeFace": "Mediapipe Gesichter",
|
||||
"mlsd": "M-LSD",
|
||||
"controlMode": "Steuermodus",
|
||||
"cannyDescription": "Canny Ecken Erkennung",
|
||||
"lineart": "Lineart",
|
||||
"cannyDescription": "Canny Umrisserkennung",
|
||||
"lineart": "Linienzeichnung",
|
||||
"lineartAnimeDescription": "Lineart-Verarbeitung im Anime-Stil",
|
||||
"minConfidence": "Minimales Vertrauen",
|
||||
"megaControl": "Mega-Kontrolle",
|
||||
"autoConfigure": "Prozessor automatisch konfigurieren",
|
||||
"normalBaeDescription": "Normale BAE-Verarbeitung",
|
||||
"noneDescription": "Es wurde keine Verarbeitung angewendet",
|
||||
"openPose": "Openpose",
|
||||
"lineartAnime": "Lineart Anime",
|
||||
"openPose": "Openpose / \"Pose nutzen\"",
|
||||
"lineartAnime": "Lineart Anime / \"Strichzeichnung Anime\"",
|
||||
"mediapipeFaceDescription": "Gesichtserkennung mit Mediapipe",
|
||||
"canny": "Canny",
|
||||
"canny": "\"Canny\"",
|
||||
"hedDescription": "Ganzheitlich verschachtelte Kantenerkennung",
|
||||
"scribble": "Scribble",
|
||||
"maxFaces": "Maximal Anzahl Gesichter",
|
||||
"maxFaces": "Maximale Anzahl Gesichter",
|
||||
"resizeSimple": "Größe ändern (einfach)",
|
||||
"large": "Groß",
|
||||
"modelSize": "Modell Größe",
|
||||
"small": "Klein",
|
||||
"base": "Basis",
|
||||
"depthAnything": "Depth Anything",
|
||||
"depthAnything": "Depth Anything / \"Tiefe irgendwas\"",
|
||||
"depthAnythingDescription": "Erstellung einer Tiefenkarte mit der Depth Anything-Technik"
|
||||
},
|
||||
"queue": {
|
||||
@ -876,7 +897,7 @@
|
||||
"enqueueing": "Stapel in der Warteschlange",
|
||||
"queueMaxExceeded": "Maximum von {{max_queue_size}} Elementen erreicht, würde {{skip}} Elemente überspringen",
|
||||
"cancelBatchFailed": "Problem beim Abbruch vom Stapel",
|
||||
"clearQueueAlertDialog2": "bist du sicher die Warteschlange zu leeren?",
|
||||
"clearQueueAlertDialog2": "Warteschlange wirklich leeren?",
|
||||
"pruneSucceeded": "{{item_count}} abgeschlossene Elemente aus der Warteschlange entfernt",
|
||||
"pauseSucceeded": "Prozessor angehalten",
|
||||
"cancelFailed": "Problem beim Stornieren des Auftrags",
|
||||
@ -890,78 +911,175 @@
|
||||
"resumeSucceeded": "Prozessor wieder aufgenommen",
|
||||
"resumeTooltip": "Prozessor wieder aufnehmen",
|
||||
"time": "Zeit",
|
||||
"batchQueuedDesc_one": "{{count}} Eintrage ans {{direction}} der Wartschlange hinzugefügt",
|
||||
"batchQueuedDesc_other": "{{count}} Einträge ans {{direction}} der Wartschlange hinzugefügt"
|
||||
"batchQueuedDesc_one": "{{count}} Eintrag ans {{direction}} der Wartschlange hinzugefügt",
|
||||
"batchQueuedDesc_other": "{{count}} Einträge ans {{direction}} der Wartschlange hinzugefügt",
|
||||
"openQueue": "Warteschlange öffnen",
|
||||
"batchFailedToQueue": "Fehler beim Einreihen in die Stapelverarbeitung",
|
||||
"batchFieldValues": "Stapelverarbeitungswerte",
|
||||
"batchQueued": "Stapelverarbeitung eingereiht",
|
||||
"graphQueued": "Graph eingereiht",
|
||||
"graphFailedToQueue": "Fehler beim Einreihen des Graphen"
|
||||
},
|
||||
"metadata": {
|
||||
"negativePrompt": "Negativ Beschreibung",
|
||||
"metadata": "Meta-Data",
|
||||
"strength": "Bild zu Bild stärke",
|
||||
"metadata": "Meta-Daten",
|
||||
"strength": "Bild zu Bild Stärke",
|
||||
"imageDetails": "Bild Details",
|
||||
"model": "Modell",
|
||||
"noImageDetails": "Keine Bild Details gefunden",
|
||||
"cfgScale": "CFG-Skala",
|
||||
"fit": "Bild zu Bild passen",
|
||||
"fit": "Bild zu Bild anpassen",
|
||||
"height": "Höhe",
|
||||
"noMetaData": "Keine Meta-Data gefunden",
|
||||
"noMetaData": "Keine Meta-Daten gefunden",
|
||||
"width": "Breite",
|
||||
"createdBy": "Erstellt von",
|
||||
"steps": "Schritte",
|
||||
"seamless": "Nahtlos",
|
||||
"positivePrompt": "Positiver Prompt",
|
||||
"generationMode": "Generierungsmodus",
|
||||
"Threshold": "Noise Schwelle",
|
||||
"seed": "Samen",
|
||||
"perlin": "Perlin Noise",
|
||||
"Threshold": "Rauschen-Schwelle",
|
||||
"seed": "Seed",
|
||||
"perlin": "Perlin-Rauschen",
|
||||
"hiresFix": "Optimierung für hohe Auflösungen",
|
||||
"initImage": "Erstes Bild",
|
||||
"variations": "Samengewichtspaare",
|
||||
"variations": "Seed-Gewichtungs-Paare",
|
||||
"vae": "VAE",
|
||||
"workflow": "Arbeitsablauf",
|
||||
"scheduler": "Scheduler",
|
||||
"scheduler": "Planer",
|
||||
"noRecallParameters": "Es wurden keine Parameter zum Abrufen gefunden",
|
||||
"recallParameters": "Recall Parameters"
|
||||
"recallParameters": "Parameter wiederherstellen"
|
||||
},
|
||||
"popovers": {
|
||||
"noiseUseCPU": {
|
||||
"heading": "Nutze Prozessor rauschen"
|
||||
"heading": "Nutze Prozessor rauschen",
|
||||
"paragraphs": [
|
||||
"Entscheidet, ob auf der CPU oder GPU Rauschen erzeugt wird.",
|
||||
"Mit aktiviertem CPU-Rauschen wird ein bestimmter Seedwert das gleiche Bild auf jeder Maschine erzeugen.",
|
||||
"CPU-Rauschen einzuschalten beeinflusst nicht die Systemleistung."
|
||||
]
|
||||
},
|
||||
"paramModel": {
|
||||
"heading": "Modell"
|
||||
"heading": "Modell",
|
||||
"paragraphs": [
|
||||
"Modell für die Entrauschungsschritte.",
|
||||
"Verschiedene Modelle werden in der Regel so trainiert, dass sie sich auf die Erzeugung bestimmter Ästhetik und/oder Inhalte spezialisiert."
|
||||
]
|
||||
},
|
||||
"paramIterations": {
|
||||
"heading": "Iterationen"
|
||||
"heading": "Iterationen",
|
||||
"paragraphs": [
|
||||
"Die Anzahl der Bilder, die erzeugt werden sollen.",
|
||||
"Wenn \"Dynamische Prompts\" aktiviert ist, wird jeder einzelne Prompt so oft generiert."
|
||||
]
|
||||
},
|
||||
"paramCFGScale": {
|
||||
"heading": "CFG-Skala"
|
||||
"heading": "CFG-Skala",
|
||||
"paragraphs": [
|
||||
"Bestimmt, wie viel Ihr Prompt den Erzeugungsprozess beeinflusst."
|
||||
]
|
||||
},
|
||||
"paramSteps": {
|
||||
"heading": "Schritte"
|
||||
"heading": "Schritte",
|
||||
"paragraphs": [
|
||||
"Anzahl der Schritte, die bei jeder Generierung durchgeführt werden.",
|
||||
"Höhere Schrittzahlen werden in der Regel bessere Bilder ergeben, aber mehr Zeit benötigen."
|
||||
]
|
||||
},
|
||||
"lora": {
|
||||
"heading": "LoRA Gewichte"
|
||||
"heading": "LoRA Gewichte",
|
||||
"paragraphs": [
|
||||
"Höhere LoRA-Wichtungen führen zu größeren Auswirkungen auf das endgültige Bild."
|
||||
]
|
||||
},
|
||||
"infillMethod": {
|
||||
"heading": "Füllmethode"
|
||||
"heading": "Füllmethode",
|
||||
"paragraphs": [
|
||||
"Infill-Methode für den ausgewählten Bereich."
|
||||
]
|
||||
},
|
||||
"paramVAE": {
|
||||
"heading": "VAE"
|
||||
"heading": "VAE",
|
||||
"paragraphs": [
|
||||
"Verwendetes Modell, um den KI-Ausgang in das endgültige Bild zu übersetzen."
|
||||
]
|
||||
},
|
||||
"paramRatio": {
|
||||
"heading": "Seitenverhältnis",
|
||||
"paragraphs": [
|
||||
"Das Seitenverhältnis des erzeugten Bildes.",
|
||||
"Für SD1.5-Modelle wird eine Bildgröße von 512x512 Pixel empfohlen, für SDXL-Modelle sind es 1024x1024 Pixel."
|
||||
]
|
||||
},
|
||||
"paramDenoisingStrength": {
|
||||
"paragraphs": [
|
||||
"Wie viel Rauschen dem Eingabebild hinzugefügt wird.",
|
||||
"0 wird zu einem identischen Bild führen, während 1 zu einem völlig neuen Bild führt."
|
||||
],
|
||||
"heading": "Stärke der Entrauschung"
|
||||
},
|
||||
"paramVAEPrecision": {
|
||||
"heading": "VAE-Präzision",
|
||||
"paragraphs": [
|
||||
"Die bei der VAE-Kodierung und Dekodierung verwendete Präzision. FP16/Halbpräzision ist effizienter, aber auf Kosten kleiner Bildvariationen."
|
||||
]
|
||||
},
|
||||
"paramCFGRescaleMultiplier": {
|
||||
"heading": "CFG Rescale Multiplikator",
|
||||
"paragraphs": [
|
||||
"Rescale-Multiplikator für die CFG-Lenkung, der für Modelle verwendet wird, die mit dem zero-terminal SNR (ztsnr) trainiert wurden. Empfohlener Wert: 0,7."
|
||||
]
|
||||
},
|
||||
"scaleBeforeProcessing": {
|
||||
"paragraphs": [
|
||||
"Skaliert den ausgewählten Bereich auf die Größe, die für das Modell am besten geeignet ist."
|
||||
],
|
||||
"heading": "Skalieren vor der Verarbeitung"
|
||||
},
|
||||
"paramSeed": {
|
||||
"paragraphs": [
|
||||
"Kontrolliert das für die Erzeugung verwendete Startrauschen.",
|
||||
"Deaktivieren Sie “Random Seed”, um identische Ergebnisse mit den gleichen Generierungseinstellungen zu erzeugen."
|
||||
],
|
||||
"heading": "Seed"
|
||||
},
|
||||
"dynamicPromptsMaxPrompts": {
|
||||
"paragraphs": [
|
||||
"Beschränkt die Anzahl der Prompts, die von \"Dynamic Prompts\" generiert werden können."
|
||||
],
|
||||
"heading": "Maximale Prompts"
|
||||
},
|
||||
"dynamicPromptsSeedBehaviour": {
|
||||
"paragraphs": [
|
||||
"Bestimmt, wie der Seed-Wert beim Erzeugen von Prompts verwendet wird.",
|
||||
"Verwenden Sie dies, um schnelle Variationen eines einzigen Seeds zu erkunden.",
|
||||
"Wenn Sie z. B. 5 Prompts haben, wird jedes Bild den selben Seed-Wert verwenden.",
|
||||
"\"Per Bild\" wird einen einzigartigen Seed-Wert für jedes Bild verwenden. Dies bietet mehr Variationen."
|
||||
],
|
||||
"heading": "Seed-Verhalten"
|
||||
}
|
||||
},
|
||||
"ui": {
|
||||
"lockRatio": "Verhältnis sperren",
|
||||
"hideProgressImages": "Verstecke Prozess Bild",
|
||||
"showProgressImages": "Zeige Prozess Bild"
|
||||
"showProgressImages": "Zeige Prozess Bild",
|
||||
"swapSizes": "Tausche Größen"
|
||||
},
|
||||
"invocationCache": {
|
||||
"disable": "Deaktivieren",
|
||||
"misses": "Cache Nötig",
|
||||
"misses": "Cache nicht genutzt",
|
||||
"hits": "Cache Treffer",
|
||||
"enable": "Aktivieren",
|
||||
"clear": "Leeren",
|
||||
"maxCacheSize": "Maximale Cache Größe",
|
||||
"cacheSize": "Cache Größe",
|
||||
"useCache": "Benutze Cache"
|
||||
"useCache": "Benutze Cache",
|
||||
"enableFailed": "Problem beim Aktivieren des Zwischenspeichers",
|
||||
"disableFailed": "Problem bei Deaktivierung des Cache",
|
||||
"enableSucceeded": "Zwischenspeicher aktiviert",
|
||||
"disableSucceeded": "Invocation-Cache deaktiviert",
|
||||
"clearSucceeded": "Zwischenspeicher gelöscht",
|
||||
"invocationCache": "Zwischenspeicher",
|
||||
"clearFailed": "Problem beim Löschen des Zwischenspeichers"
|
||||
},
|
||||
"embedding": {
|
||||
"noMatchingEmbedding": "Keine passenden Embeddings",
|
||||
@ -1000,10 +1118,151 @@
|
||||
"colorCodeEdges": "Farbkodierte Kanten",
|
||||
"addNodeToolTip": "Knoten hinzufügen (Umschalt+A, Leertaste)",
|
||||
"boardField": "Ordner",
|
||||
"boardFieldDescription": "Ein Galerie Ordner"
|
||||
"boardFieldDescription": "Ein Galerie Ordner",
|
||||
"collectionFieldType": "{{name}} Sammlung",
|
||||
"controlCollectionDescription": "Kontrollinformationen zwischen Knotenpunkten weitergegeben.",
|
||||
"connectionWouldCreateCycle": "Verbindung würde einen Kreislauf/cycle schaffen",
|
||||
"ipAdapterDescription": "Ein Adapter für die Bildabfrage (IP-Adapter) / Bildprompt-Adapter.",
|
||||
"controlField": "Kontrolle",
|
||||
"inputFields": "Eingabefelder",
|
||||
"imageField": "Bild",
|
||||
"inputMayOnlyHaveOneConnection": "Eingang darf nur eine Verbindung haben",
|
||||
"integerCollectionDescription": "Eine Sammlung ganzer Zahlen.",
|
||||
"integerDescription": "\"Integer\" sind ganze Zahlen ohne Dezimalpunkt.",
|
||||
"conditioningPolymorphic": "Konditionierung polymorphisch",
|
||||
"conditioningPolymorphicDescription": "Die Konditionierung kann zwischen den Knoten weitergegeben werden.",
|
||||
"invalidOutputSchema": "Ungültiges Ausgabeschema",
|
||||
"ipAdapterModel": "IP-Adapter Modell",
|
||||
"conditioningFieldDescription": "Die Konditionierung kann zwischen den Knotenpunkten weitergegeben werden.",
|
||||
"ipAdapterCollectionDescription": "Eine Sammlung von IP-Adaptern.",
|
||||
"collectionDescription": "Zu erledigen",
|
||||
"imageFieldDescription": "Bilder können zwischen Knoten weitergegeben werden.",
|
||||
"imagePolymorphic": "Bild Polymorphie",
|
||||
"imagePolymorphicDescription": "Eine Bildersammlung.",
|
||||
"inputField": "Eingabefeld",
|
||||
"hideLegendNodes": "Feldtyp-Legende ausblenden",
|
||||
"collectionItemDescription": "Zu erledigen",
|
||||
"inputNode": "Eingangsknoten",
|
||||
"integer": "Ganze Zahl",
|
||||
"integerCollection": "Ganzzahlige Sammlung",
|
||||
"addLinearView": "Zur linearen Ansicht hinzufügen",
|
||||
"currentImageDescription": "Zeigt das aktuelle Bild im Node-Editor an",
|
||||
"ipAdapter": "IP-Adapter",
|
||||
"hideMinimapnodes": "Miniatur-Kartenansicht ausblenden",
|
||||
"imageCollection": "Bildersammlung",
|
||||
"imageCollectionDescription": "Eine Sammlung von Bildern.",
|
||||
"denoiseMaskField": "Entrauschen-Maske",
|
||||
"ipAdapterCollection": "IP-Adapter Sammlung",
|
||||
"newWorkflowDesc2": "Ihr aktueller Arbeitsablauf hat ungespeicherte Änderungen.",
|
||||
"problemSettingTitle": "Problem beim Einstellen des Titels",
|
||||
"noConnectionData": "Keine Verbindungsdaten",
|
||||
"outputField": "Ausgabefeld",
|
||||
"outputFieldInInput": "Ausgabefeld im Eingang",
|
||||
"problemReadingWorkflow": "Problem beim Lesen des Arbeitsablaufs vom Bild",
|
||||
"reloadNodeTemplates": "Knoten-Vorlagen neu laden",
|
||||
"newWorkflow": "Neuer Arbeitsablauf",
|
||||
"newWorkflowDesc": "Einen neuen Arbeitsablauf erstellen?",
|
||||
"noFieldsLinearview": "Keine Felder zur linearen Ansicht hinzugefügt",
|
||||
"clearWorkflow": "Arbeitsablauf löschen",
|
||||
"clearWorkflowDesc": "Diesen Arbeitsablauf löschen und neu starten?",
|
||||
"noConnectionInProgress": "Es besteht keine Verbindung",
|
||||
"notes": "Anmerkungen",
|
||||
"nodeVersion": "Knoten Version",
|
||||
"noOutputSchemaName": "Kein Name des Ausgabeschemas im ref-Objekt gefunden",
|
||||
"node": "Knoten",
|
||||
"nodeSearch": "Knoten suchen",
|
||||
"removeLinearView": "Entfernen aus Linear View",
|
||||
"nodeOutputs": "Knoten-Ausgänge",
|
||||
"nodeTemplate": "Knoten-Vorlage",
|
||||
"nodeType": "Knotentyp",
|
||||
"noFieldType": "Kein Feldtyp",
|
||||
"oNNXModelField": "ONNX-Modell",
|
||||
"noMatchingNodes": "Keine passenden Knoten",
|
||||
"noNodeSelected": "Kein Knoten gewählt",
|
||||
"noImageFoundState": "Kein Anfangsbild im Status gefunden",
|
||||
"nodeOpacity": "Knoten-Deckkraft",
|
||||
"noOutputRecorded": "Keine Ausgänge aufgezeichnet",
|
||||
"outputSchemaNotFound": "Ausgabeschema nicht gefunden",
|
||||
"oNNXModelFieldDescription": "ONNX-Modellfeld.",
|
||||
"outputNode": "Ausgabeknoten",
|
||||
"pickOne": "Eins auswählen",
|
||||
"problemReadingMetadata": "Problem beim Lesen von Metadaten aus dem Bild",
|
||||
"notesDescription": "Anmerkungen zum Arbeitsablauf hinzufügen",
|
||||
"outputFields": "Ausgabefelder",
|
||||
"sDXLRefinerModelField": "Refiner-Modell",
|
||||
"sDXLMainModelFieldDescription": "SDXL Modellfeld.",
|
||||
"clearWorkflowDesc2": "Ihr aktueller Arbeitsablauf hat ungespeicherte Änderungen.",
|
||||
"skipped": "Übersprungen",
|
||||
"schedulerDescription": "Zu erledigen",
|
||||
"scheduler": "Planer",
|
||||
"showGraphNodes": "Graph Overlay anzeigen",
|
||||
"showMinimapnodes": "MiniMap anzeigen",
|
||||
"sDXLMainModelField": "SDXL Modell",
|
||||
"skippedReservedInput": "Reserviertes Eingabefeld übersprungen",
|
||||
"sDXLRefinerModelFieldDescription": "Zu erledigen",
|
||||
"showLegendNodes": "Feldtyp-Legende anzeigen",
|
||||
"skippedReservedOutput": "Reserviertes Ausgangsfeld übersprungen",
|
||||
"skippingInputNoTemplate": "Überspringe Eingabefeld ohne Vorlage",
|
||||
"executionStateCompleted": "Erledigt",
|
||||
"denoiseMaskFieldDescription": "Denoise Maske kann zwischen Knoten weitergegeben werden",
|
||||
"downloadWorkflow": "Workflow JSON herunterladen",
|
||||
"executionStateInProgress": "In Bearbeitung",
|
||||
"snapToGridHelp": "Knoten am Gitternetz einrasten bei Bewegung",
|
||||
"controlCollection": "Control-Sammlung",
|
||||
"controlFieldDescription": "Control-Informationen zwischen Knotenpunkten weitergegeben.",
|
||||
"latentsField": "Latents",
|
||||
"mainModelFieldDescription": "Zu erledigen",
|
||||
"missingTemplate": "Ungültiger Knoten: Knoten {{node}} vom Typ {{type}} fehlt Vorlage (nicht installiert?)",
|
||||
"skippingUnknownInputType": "Überspringe unbekannten Eingabe-Feldtyp",
|
||||
"stringCollectionDescription": "Eine Sammlung von Zeichenfolgen.",
|
||||
"string": "Zeichenfolge",
|
||||
"stringCollection": "Sammlung von Zeichenfolgen",
|
||||
"stringDescription": "Zeichenfolgen (Strings) sind Text.",
|
||||
"fieldTypesMustMatch": "Feldtypen müssen übereinstimmen",
|
||||
"fitViewportNodes": "An Ansichtsgröße anpassen",
|
||||
"missingCanvaInitMaskImages": "Fehlende Startbilder und Masken auf der Arbeitsfläche",
|
||||
"missingCanvaInitImage": "Fehlendes Startbild auf der Arbeitsfläche",
|
||||
"ipAdapterModelDescription": "IP-Adapter-Modellfeld",
|
||||
"latentsPolymorphicDescription": "Zwischen Nodes können Latents weitergegeben werden.",
|
||||
"loadingNodes": "Lade Nodes...",
|
||||
"latentsCollectionDescription": "Zwischen Knoten können Latents weitergegeben werden.",
|
||||
"mismatchedVersion": "Ungültiger Knoten: Knoten {{node}} vom Typ {{type}} hat keine passende Version (Update versuchen?)",
|
||||
"colorCollectionDescription": "Zu erledigen",
|
||||
"ipAdapterPolymorphicDescription": "Eine Sammlung von IP-Adaptern.",
|
||||
"fullyContainNodesHelp": "Nodes müssen vollständig innerhalb der Auswahlbox sein, um ausgewählt werden zu können",
|
||||
"latentsFieldDescription": "Zwischen Nodes können Latents weitergegeben werden.",
|
||||
"noWorkflow": "Kein Workflow",
|
||||
"hideGraphNodes": "Graph Overlay verbergen",
|
||||
"sourceNode": "Quellknoten",
|
||||
"executionStateError": "Fehler",
|
||||
"latentsCollection": "Latents Sammlung",
|
||||
"maybeIncompatible": "Möglicherweise inkompatibel mit installierten",
|
||||
"nodePack": "Knoten-Pack",
|
||||
"skippingUnknownOutputType": "Überspringe unbekannten Ausgabe-Feldtyp",
|
||||
"loadWorkflow": "Lade Workflow",
|
||||
"snapToGrid": "Am Gitternetz einrasten",
|
||||
"skippingReservedFieldType": "Überspringe reservierten Feldtyp",
|
||||
"loRAModelField": "LoRA",
|
||||
"loRAModelFieldDescription": "Zu erledigen",
|
||||
"mainModelField": "Modell",
|
||||
"doesNotExist": "existiert nicht",
|
||||
"vaeField": "VAE",
|
||||
"unknownOutput": "Unbekannte Ausgabe: {{name}}",
|
||||
"updateNode": "Knoten updaten",
|
||||
"edge": "Rand / Kante",
|
||||
"sourceNodeDoesNotExist": "Ungültiger Rand: Quell- / Ausgabe-Knoten {{node}} existiert nicht",
|
||||
"updateAllNodes": "Update Knoten",
|
||||
"allNodesUpdated": "Alle Knoten aktualisiert",
|
||||
"unknownTemplate": "Unbekannte Vorlage",
|
||||
"floatDescription": "Floats sind Zahlen mit einem Dezimalpunkt.",
|
||||
"updateApp": "Update App",
|
||||
"vaeFieldDescription": "VAE Submodell.",
|
||||
"unknownInput": "Unbekannte Eingabe: {{name}}",
|
||||
"unknownNodeType": "Unbekannter Knotentyp",
|
||||
"float": "Kommazahlen"
|
||||
},
|
||||
"hrf": {
|
||||
"enableHrf": "Aktivieren Sie die Korrektur für hohe Auflösungen",
|
||||
"enableHrf": "Korrektur für hohe Auflösungen",
|
||||
"upscaleMethod": "Vergrößerungsmethoden",
|
||||
"enableHrfTooltip": "Generieren Sie mit einer niedrigeren Anfangsauflösung, skalieren Sie auf die Basisauflösung hoch und führen Sie dann Image-to-Image aus.",
|
||||
"metadata": {
|
||||
@ -1026,7 +1285,14 @@
|
||||
"noLoRAsInstalled": "Keine LoRAs installiert",
|
||||
"selectLoRA": "Wählen ein LoRA aus",
|
||||
"esrganModel": "ESRGAN Modell",
|
||||
"addLora": "LoRA hinzufügen"
|
||||
"addLora": "LoRA hinzufügen",
|
||||
"defaultVAE": "Standard VAE",
|
||||
"noLoRAsLoaded": "Keine LoRAs geladen",
|
||||
"lora": "LoRA",
|
||||
"allLoRAsAdded": "Alle LoRAs hinzugefügt",
|
||||
"incompatibleBaseModel": "Inkompatibles Basismodell",
|
||||
"noMainModelSelected": "Kein Hauptmodell ausgewählt",
|
||||
"loraAlreadyAdded": "LoRA bereits hinzugefügt"
|
||||
},
|
||||
"accordions": {
|
||||
"generation": {
|
||||
@ -1050,5 +1316,40 @@
|
||||
"infillTab": "Füllung",
|
||||
"title": "Compositing"
|
||||
}
|
||||
},
|
||||
"workflows": {
|
||||
"workflows": "Arbeitsabläufe",
|
||||
"noSystemWorkflows": "Keine System-Arbeitsabläufe",
|
||||
"workflowName": "Arbeitsablauf-Name",
|
||||
"workflowIsOpen": "Arbeitsablauf ist offen",
|
||||
"saveWorkflowAs": "Arbeitsablauf speichern als",
|
||||
"searchWorkflows": "Suche Arbeitsabläufe",
|
||||
"newWorkflowCreated": "Neuer Arbeitsablauf erstellt",
|
||||
"problemSavingWorkflow": "Problem beim Speichern des Arbeitsablaufs",
|
||||
"noRecentWorkflows": "Keine kürzlichen Arbeitsabläufe",
|
||||
"problemLoading": "Problem beim Laden von Arbeitsabläufen",
|
||||
"downloadWorkflow": "Speichern als",
|
||||
"savingWorkflow": "Speichere Arbeitsablauf...",
|
||||
"saveWorkflow": "Arbeitsablauf speichern",
|
||||
"noWorkflows": "Keine Arbeitsabläufe",
|
||||
"workflowLibrary": "Bibliothek",
|
||||
"defaultWorkflows": "Standard-Arbeitsabläufe",
|
||||
"unnamedWorkflow": "Unbenannter Arbeitsablauf",
|
||||
"noDescription": "Keine Beschreibung",
|
||||
"clearWorkflowSearchFilter": "Suchfilter zurücksetzen",
|
||||
"workflowEditorMenu": "Arbeitsablauf-Editor Menü",
|
||||
"deleteWorkflow": "Arbeitsablauf löschen",
|
||||
"userWorkflows": "Meine Arbeitsabläufe",
|
||||
"workflowSaved": "Arbeitsablauf gespeichert",
|
||||
"uploadWorkflow": "Aus Datei laden",
|
||||
"projectWorkflows": "Projekt-Arbeitsabläufe",
|
||||
"openWorkflow": "Arbeitsablauf öffnen",
|
||||
"noUserWorkflows": "Keine Benutzer-Arbeitsabläufe",
|
||||
"saveWorkflowToProject": "Arbeitsablauf in Projekt speichern",
|
||||
"workflowCleared": "Arbeitsablauf gelöscht",
|
||||
"loading": "Lade Arbeitsabläufe"
|
||||
},
|
||||
"app": {
|
||||
"storeNotInitialized": "App-Store ist nicht initialisiert"
|
||||
}
|
||||
}
|
||||
|
||||
@ -1,4 +1,6 @@
|
||||
import { useAppToaster } from 'app/components/Toaster';
|
||||
import { useAppDispatch } from 'app/store/storeHooks';
|
||||
import { imageDownloaded } from 'features/gallery/store/actions';
|
||||
import { useCallback } from 'react';
|
||||
import { useTranslation } from 'react-i18next';
|
||||
|
||||
@ -8,6 +10,7 @@ export const useDownloadImage = () => {
|
||||
const toaster = useAppToaster();
|
||||
const { t } = useTranslation();
|
||||
const imageUrlToBlob = useImageUrlToBlob();
|
||||
const dispatch = useAppDispatch();
|
||||
|
||||
const downloadImage = useCallback(
|
||||
async (image_url: string, image_name: string) => {
|
||||
@ -26,6 +29,7 @@ export const useDownloadImage = () => {
|
||||
document.body.appendChild(a);
|
||||
a.click();
|
||||
window.URL.revokeObjectURL(url);
|
||||
dispatch(imageDownloaded());
|
||||
} catch (err) {
|
||||
toaster({
|
||||
title: t('toast.problemDownloadingImage'),
|
||||
@ -36,7 +40,7 @@ export const useDownloadImage = () => {
|
||||
});
|
||||
}
|
||||
},
|
||||
[t, toaster, imageUrlToBlob]
|
||||
[t, toaster, imageUrlToBlob, dispatch]
|
||||
);
|
||||
|
||||
return { downloadImage };
|
||||
|
||||
@ -5,6 +5,7 @@ import { createMemoizedSelector } from 'app/store/createMemoizedSelector';
|
||||
import { useAppDispatch, useAppSelector } from 'app/store/storeHooks';
|
||||
import IAIDndImage from 'common/components/IAIDndImage';
|
||||
import IAIDndImageIcon from 'common/components/IAIDndImageIcon';
|
||||
import { roundToMultiple } from 'common/util/roundDownToMultiple';
|
||||
import { setBoundingBoxDimensions } from 'features/canvas/store/canvasSlice';
|
||||
import { useControlAdapterControlImage } from 'features/controlAdapters/hooks/useControlAdapterControlImage';
|
||||
import { useControlAdapterProcessedControlImage } from 'features/controlAdapters/hooks/useControlAdapterProcessedControlImage';
|
||||
@ -91,19 +92,14 @@ const ControlAdapterImagePreview = ({ isSmall, id }: Props) => {
|
||||
return;
|
||||
}
|
||||
|
||||
const width = roundToMultiple(controlImage.width, 8);
|
||||
const height = roundToMultiple(controlImage.height, 8);
|
||||
|
||||
if (activeTabName === 'unifiedCanvas') {
|
||||
dispatch(
|
||||
setBoundingBoxDimensions(
|
||||
{
|
||||
width: controlImage.width,
|
||||
height: controlImage.height,
|
||||
},
|
||||
optimalDimension
|
||||
)
|
||||
);
|
||||
dispatch(setBoundingBoxDimensions({ width, height }, optimalDimension));
|
||||
} else {
|
||||
dispatch(widthChanged(controlImage.width));
|
||||
dispatch(heightChanged(controlImage.height));
|
||||
dispatch(widthChanged(width));
|
||||
dispatch(heightChanged(height));
|
||||
}
|
||||
}, [controlImage, activeTabName, dispatch, optimalDimension]);
|
||||
|
||||
|
||||
@ -14,3 +14,5 @@ export const requestedBoardImagesDeletion = createAction<RequestedBoardImagesDel
|
||||
export const sentImageToCanvas = createAction('gallery/sentImageToCanvas');
|
||||
|
||||
export const sentImageToImg2Img = createAction('gallery/sentImageToImg2Img');
|
||||
|
||||
export const imageDownloaded = createAction('gallery/imageDownloaded');
|
||||
|
||||
@ -1,84 +0,0 @@
|
||||
import type { ContextMenuProps } from '@invoke-ai/ui-library';
|
||||
import { ContextMenu, MenuGroup, MenuItem, MenuList } from '@invoke-ai/ui-library';
|
||||
import { createSelector } from '@reduxjs/toolkit';
|
||||
import { useAppDispatch, useAppSelector } from 'app/store/storeHooks';
|
||||
import { useFieldInputKind } from 'features/nodes/hooks/useFieldInputKind';
|
||||
import { useFieldLabel } from 'features/nodes/hooks/useFieldLabel';
|
||||
import { useFieldTemplateTitle } from 'features/nodes/hooks/useFieldTemplateTitle';
|
||||
import {
|
||||
selectWorkflowSlice,
|
||||
workflowExposedFieldAdded,
|
||||
workflowExposedFieldRemoved,
|
||||
} from 'features/nodes/store/workflowSlice';
|
||||
import type { ReactNode } from 'react';
|
||||
import { memo, useCallback, useMemo } from 'react';
|
||||
import { useTranslation } from 'react-i18next';
|
||||
import { PiMinusBold, PiPlusBold } from 'react-icons/pi';
|
||||
|
||||
type Props = {
|
||||
nodeId: string;
|
||||
fieldName: string;
|
||||
kind: 'input' | 'output';
|
||||
children: ContextMenuProps<HTMLDivElement>['children'];
|
||||
};
|
||||
|
||||
const FieldContextMenu = ({ nodeId, fieldName, kind, children }: Props) => {
|
||||
const dispatch = useAppDispatch();
|
||||
const label = useFieldLabel(nodeId, fieldName);
|
||||
const fieldTemplateTitle = useFieldTemplateTitle(nodeId, fieldName, kind);
|
||||
const input = useFieldInputKind(nodeId, fieldName);
|
||||
const { t } = useTranslation();
|
||||
|
||||
const selectIsExposed = useMemo(
|
||||
() =>
|
||||
createSelector(selectWorkflowSlice, (workflow) => {
|
||||
return Boolean(workflow.exposedFields.find((f) => f.nodeId === nodeId && f.fieldName === fieldName));
|
||||
}),
|
||||
[fieldName, nodeId]
|
||||
);
|
||||
|
||||
const mayExpose = useMemo(() => input && ['any', 'direct'].includes(input), [input]);
|
||||
|
||||
const isExposed = useAppSelector(selectIsExposed);
|
||||
|
||||
const handleExposeField = useCallback(() => {
|
||||
dispatch(workflowExposedFieldAdded({ nodeId, fieldName }));
|
||||
}, [dispatch, fieldName, nodeId]);
|
||||
|
||||
const handleUnexposeField = useCallback(() => {
|
||||
dispatch(workflowExposedFieldRemoved({ nodeId, fieldName }));
|
||||
}, [dispatch, fieldName, nodeId]);
|
||||
|
||||
const menuItems = useMemo(() => {
|
||||
const menuItems: ReactNode[] = [];
|
||||
if (mayExpose && !isExposed) {
|
||||
menuItems.push(
|
||||
<MenuItem key={`${nodeId}.${fieldName}.expose-field`} icon={<PiPlusBold />} onClick={handleExposeField}>
|
||||
{t('nodes.addLinearView')}
|
||||
</MenuItem>
|
||||
);
|
||||
}
|
||||
if (mayExpose && isExposed) {
|
||||
menuItems.push(
|
||||
<MenuItem key={`${nodeId}.${fieldName}.unexpose-field`} icon={<PiMinusBold />} onClick={handleUnexposeField}>
|
||||
{t('nodes.removeLinearView')}
|
||||
</MenuItem>
|
||||
);
|
||||
}
|
||||
return menuItems;
|
||||
}, [fieldName, handleExposeField, handleUnexposeField, isExposed, mayExpose, nodeId, t]);
|
||||
|
||||
const renderMenuFunc = useCallback(
|
||||
() =>
|
||||
!menuItems.length ? null : (
|
||||
<MenuList visibility="visible">
|
||||
<MenuGroup title={label || fieldTemplateTitle || t('nodes.unknownField')}>{menuItems}</MenuGroup>
|
||||
</MenuList>
|
||||
),
|
||||
[fieldTemplateTitle, label, menuItems, t]
|
||||
);
|
||||
|
||||
return <ContextMenu renderMenu={renderMenuFunc}>{children}</ContextMenu>;
|
||||
};
|
||||
|
||||
export default memo(FieldContextMenu);
|
||||
@ -0,0 +1,67 @@
|
||||
import { IconButton } from '@invoke-ai/ui-library';
|
||||
import { createSelector } from '@reduxjs/toolkit';
|
||||
import { useAppDispatch, useAppSelector } from 'app/store/storeHooks';
|
||||
import {
|
||||
selectWorkflowSlice,
|
||||
workflowExposedFieldAdded,
|
||||
workflowExposedFieldRemoved,
|
||||
} from 'features/nodes/store/workflowSlice';
|
||||
import { memo, useCallback, useMemo } from 'react';
|
||||
import { useTranslation } from 'react-i18next';
|
||||
import { PiMinusBold, PiPlusBold } from 'react-icons/pi';
|
||||
|
||||
type Props = {
|
||||
nodeId: string;
|
||||
fieldName: string;
|
||||
};
|
||||
|
||||
const FieldLinearViewToggle = ({ nodeId, fieldName }: Props) => {
|
||||
const dispatch = useAppDispatch();
|
||||
const { t } = useTranslation();
|
||||
|
||||
const selectIsExposed = useMemo(
|
||||
() =>
|
||||
createSelector(selectWorkflowSlice, (workflow) => {
|
||||
return Boolean(workflow.exposedFields.find((f) => f.nodeId === nodeId && f.fieldName === fieldName));
|
||||
}),
|
||||
[fieldName, nodeId]
|
||||
);
|
||||
|
||||
const isExposed = useAppSelector(selectIsExposed);
|
||||
|
||||
const handleExposeField = useCallback(() => {
|
||||
dispatch(workflowExposedFieldAdded({ nodeId, fieldName }));
|
||||
}, [dispatch, fieldName, nodeId]);
|
||||
|
||||
const handleUnexposeField = useCallback(() => {
|
||||
dispatch(workflowExposedFieldRemoved({ nodeId, fieldName }));
|
||||
}, [dispatch, fieldName, nodeId]);
|
||||
|
||||
if (!isExposed) {
|
||||
return (
|
||||
<IconButton
|
||||
variant="ghost"
|
||||
tooltip={t('nodes.addLinearView')}
|
||||
aria-label={t('nodes.addLinearView')}
|
||||
icon={<PiPlusBold />}
|
||||
onClick={handleExposeField}
|
||||
pointerEvents="auto"
|
||||
size="xs"
|
||||
/>
|
||||
);
|
||||
} else {
|
||||
return (
|
||||
<IconButton
|
||||
variant="ghost"
|
||||
tooltip={t('nodes.removeLinearView')}
|
||||
aria-label={t('nodes.removeLinearView')}
|
||||
icon={<PiMinusBold />}
|
||||
onClick={handleUnexposeField}
|
||||
pointerEvents="auto"
|
||||
size="xs"
|
||||
/>
|
||||
);
|
||||
}
|
||||
};
|
||||
|
||||
export default memo(FieldLinearViewToggle);
|
||||
@ -4,12 +4,12 @@ import { useDoesInputHaveValue } from 'features/nodes/hooks/useDoesInputHaveValu
|
||||
import { useFieldInputInstance } from 'features/nodes/hooks/useFieldInputInstance';
|
||||
import { useFieldInputTemplate } from 'features/nodes/hooks/useFieldInputTemplate';
|
||||
import type { PropsWithChildren } from 'react';
|
||||
import { memo, useMemo } from 'react';
|
||||
import { memo, useCallback, useMemo, useState } from 'react';
|
||||
import { useTranslation } from 'react-i18next';
|
||||
|
||||
import EditableFieldTitle from './EditableFieldTitle';
|
||||
import FieldContextMenu from './FieldContextMenu';
|
||||
import FieldHandle from './FieldHandle';
|
||||
import FieldLinearViewToggle from './FieldLinearViewToggle';
|
||||
import InputFieldRenderer from './InputFieldRenderer';
|
||||
|
||||
interface Props {
|
||||
@ -22,6 +22,7 @@ const InputField = ({ nodeId, fieldName }: Props) => {
|
||||
const fieldTemplate = useFieldInputTemplate(nodeId, fieldName);
|
||||
const fieldInstance = useFieldInputInstance(nodeId, fieldName);
|
||||
const doesFieldHaveValue = useDoesInputHaveValue(nodeId, fieldName);
|
||||
const [isHovered, setIsHovered] = useState(false);
|
||||
|
||||
const { isConnected, isConnectionInProgress, isConnectionStartField, connectionError, shouldDim } =
|
||||
useConnectionState({ nodeId, fieldName, kind: 'input' });
|
||||
@ -46,6 +47,14 @@ const InputField = ({ nodeId, fieldName }: Props) => {
|
||||
return false;
|
||||
}, [fieldTemplate, isConnected, doesFieldHaveValue]);
|
||||
|
||||
const onMouseEnter = useCallback(() => {
|
||||
setIsHovered(true);
|
||||
}, []);
|
||||
|
||||
const onMouseLeave = useCallback(() => {
|
||||
setIsHovered(false);
|
||||
}, []);
|
||||
|
||||
if (!fieldTemplate || !fieldInstance) {
|
||||
return (
|
||||
<InputFieldWrapper shouldDim={shouldDim}>
|
||||
@ -87,19 +96,17 @@ const InputField = ({ nodeId, fieldName }: Props) => {
|
||||
return (
|
||||
<InputFieldWrapper shouldDim={shouldDim}>
|
||||
<FormControl isInvalid={isMissingInput} isDisabled={isConnected} orientation="vertical" px={2}>
|
||||
<Flex flexDir="column" w="full" gap={1}>
|
||||
<FieldContextMenu nodeId={nodeId} fieldName={fieldName} kind="input">
|
||||
{(ref) => (
|
||||
<Flex flexDir="column" w="full" gap={1} onMouseEnter={onMouseEnter} onMouseLeave={onMouseLeave}>
|
||||
<Flex>
|
||||
<EditableFieldTitle
|
||||
ref={ref}
|
||||
nodeId={nodeId}
|
||||
fieldName={fieldName}
|
||||
kind="input"
|
||||
isMissingInput={isMissingInput}
|
||||
withTooltip
|
||||
/>
|
||||
)}
|
||||
</FieldContextMenu>
|
||||
{isHovered && <FieldLinearViewToggle nodeId={nodeId} fieldName={fieldName} />}
|
||||
</Flex>
|
||||
<InputFieldRenderer nodeId={nodeId} fieldName={fieldName} />
|
||||
</Flex>
|
||||
</FormControl>
|
||||
|
||||
@ -1,7 +1,7 @@
|
||||
import type { RootState } from 'app/store/store';
|
||||
import type { LoRAMetadataItem } from 'features/nodes/types/metadata';
|
||||
import { zLoRAMetadataItem } from 'features/nodes/types/metadata';
|
||||
import { forEach, size } from 'lodash-es';
|
||||
import { filter, size } from 'lodash-es';
|
||||
import type { NonNullableGraph, SDXLLoraLoaderInvocation } from 'services/api/types';
|
||||
|
||||
import {
|
||||
@ -31,8 +31,8 @@ export const addSDXLLoRAsToGraph = (
|
||||
* So we need to inject a LoRA chain into the graph.
|
||||
*/
|
||||
|
||||
const { loras } = state.lora;
|
||||
const loraCount = size(loras);
|
||||
const enabledLoRAs = filter(state.lora.loras, (l) => l.isEnabled ?? false);
|
||||
const loraCount = size(enabledLoRAs);
|
||||
|
||||
if (loraCount === 0) {
|
||||
return;
|
||||
@ -59,7 +59,7 @@ export const addSDXLLoRAsToGraph = (
|
||||
let lastLoraNodeId = '';
|
||||
let currentLoraIndex = 0;
|
||||
|
||||
forEach(loras, (lora) => {
|
||||
enabledLoRAs.forEach((lora) => {
|
||||
const { model_name, base_model, weight } = lora;
|
||||
const currentLoraNodeId = `${LORA_LOADER}_${model_name.replace('.', '_')}`;
|
||||
|
||||
|
||||
@ -123,6 +123,7 @@ export const buildCanvasImageToImageGraph = (state: RootState, initialImage: Ima
|
||||
id: DENOISE_LATENTS,
|
||||
is_intermediate,
|
||||
cfg_scale,
|
||||
cfg_rescale_multiplier,
|
||||
scheduler,
|
||||
steps,
|
||||
denoising_start: 1 - strength,
|
||||
|
||||
@ -58,6 +58,7 @@ export const buildCanvasInpaintGraph = (
|
||||
negativePrompt,
|
||||
model,
|
||||
cfgScale: cfg_scale,
|
||||
cfgRescaleMultiplier: cfg_rescale_multiplier,
|
||||
scheduler,
|
||||
steps,
|
||||
img2imgStrength: strength,
|
||||
@ -152,6 +153,7 @@ export const buildCanvasInpaintGraph = (
|
||||
is_intermediate,
|
||||
steps: steps,
|
||||
cfg_scale: cfg_scale,
|
||||
cfg_rescale_multiplier,
|
||||
scheduler: scheduler,
|
||||
denoising_start: 1 - strength,
|
||||
denoising_end: 1,
|
||||
@ -175,6 +177,7 @@ export const buildCanvasInpaintGraph = (
|
||||
is_intermediate,
|
||||
steps: canvasCoherenceSteps,
|
||||
cfg_scale: cfg_scale,
|
||||
cfg_rescale_multiplier,
|
||||
scheduler: scheduler,
|
||||
denoising_start: 1 - canvasCoherenceStrength,
|
||||
denoising_end: 1,
|
||||
|
||||
@ -60,6 +60,7 @@ export const buildCanvasOutpaintGraph = (
|
||||
negativePrompt,
|
||||
model,
|
||||
cfgScale: cfg_scale,
|
||||
cfgRescaleMultiplier: cfg_rescale_multiplier,
|
||||
scheduler,
|
||||
steps,
|
||||
img2imgStrength: strength,
|
||||
@ -161,6 +162,7 @@ export const buildCanvasOutpaintGraph = (
|
||||
is_intermediate,
|
||||
steps: steps,
|
||||
cfg_scale: cfg_scale,
|
||||
cfg_rescale_multiplier,
|
||||
scheduler: scheduler,
|
||||
denoising_start: 1 - strength,
|
||||
denoising_end: 1,
|
||||
@ -184,6 +186,7 @@ export const buildCanvasOutpaintGraph = (
|
||||
is_intermediate,
|
||||
steps: canvasCoherenceSteps,
|
||||
cfg_scale: cfg_scale,
|
||||
cfg_rescale_multiplier,
|
||||
scheduler: scheduler,
|
||||
denoising_start: 1 - canvasCoherenceStrength,
|
||||
denoising_end: 1,
|
||||
|
||||
@ -124,6 +124,7 @@ export const buildCanvasSDXLImageToImageGraph = (state: RootState, initialImage:
|
||||
id: SDXL_DENOISE_LATENTS,
|
||||
is_intermediate,
|
||||
cfg_scale,
|
||||
cfg_rescale_multiplier,
|
||||
scheduler,
|
||||
steps,
|
||||
denoising_start: refinerModel ? Math.min(refinerStart, 1 - strength) : 1 - strength,
|
||||
|
||||
@ -60,6 +60,7 @@ export const buildCanvasSDXLInpaintGraph = (
|
||||
negativePrompt,
|
||||
model,
|
||||
cfgScale: cfg_scale,
|
||||
cfgRescaleMultiplier: cfg_rescale_multiplier,
|
||||
scheduler,
|
||||
steps,
|
||||
seed,
|
||||
@ -151,6 +152,7 @@ export const buildCanvasSDXLInpaintGraph = (
|
||||
is_intermediate,
|
||||
steps: steps,
|
||||
cfg_scale: cfg_scale,
|
||||
cfg_rescale_multiplier,
|
||||
scheduler: scheduler,
|
||||
denoising_start: refinerModel ? Math.min(refinerStart, 1 - strength) : 1 - strength,
|
||||
denoising_end: refinerModel ? refinerStart : 1,
|
||||
@ -174,6 +176,7 @@ export const buildCanvasSDXLInpaintGraph = (
|
||||
is_intermediate,
|
||||
steps: canvasCoherenceSteps,
|
||||
cfg_scale: cfg_scale,
|
||||
cfg_rescale_multiplier,
|
||||
scheduler: scheduler,
|
||||
denoising_start: 1 - canvasCoherenceStrength,
|
||||
denoising_end: 1,
|
||||
|
||||
@ -62,6 +62,7 @@ export const buildCanvasSDXLOutpaintGraph = (
|
||||
negativePrompt,
|
||||
model,
|
||||
cfgScale: cfg_scale,
|
||||
cfgRescaleMultiplier: cfg_rescale_multiplier,
|
||||
scheduler,
|
||||
steps,
|
||||
seed,
|
||||
@ -160,6 +161,7 @@ export const buildCanvasSDXLOutpaintGraph = (
|
||||
is_intermediate,
|
||||
steps: steps,
|
||||
cfg_scale: cfg_scale,
|
||||
cfg_rescale_multiplier,
|
||||
scheduler: scheduler,
|
||||
denoising_start: refinerModel ? Math.min(refinerStart, 1 - strength) : 1 - strength,
|
||||
denoising_end: refinerModel ? refinerStart : 1,
|
||||
@ -183,6 +185,7 @@ export const buildCanvasSDXLOutpaintGraph = (
|
||||
is_intermediate,
|
||||
steps: canvasCoherenceSteps,
|
||||
cfg_scale: cfg_scale,
|
||||
cfg_rescale_multiplier,
|
||||
scheduler: scheduler,
|
||||
denoising_start: 1 - canvasCoherenceStrength,
|
||||
denoising_end: 1,
|
||||
|
||||
@ -117,6 +117,7 @@ export const buildCanvasSDXLTextToImageGraph = (state: RootState): NonNullableGr
|
||||
id: SDXL_DENOISE_LATENTS,
|
||||
is_intermediate,
|
||||
cfg_scale,
|
||||
cfg_rescale_multiplier,
|
||||
scheduler,
|
||||
steps,
|
||||
denoising_start: 0,
|
||||
|
||||
@ -115,6 +115,7 @@ export const buildCanvasTextToImageGraph = (state: RootState): NonNullableGraph
|
||||
id: DENOISE_LATENTS,
|
||||
is_intermediate,
|
||||
cfg_scale,
|
||||
cfg_rescale_multiplier,
|
||||
scheduler,
|
||||
steps,
|
||||
denoising_start: 0,
|
||||
|
||||
@ -123,6 +123,7 @@ export const buildLinearImageToImageGraph = (state: RootState): NonNullableGraph
|
||||
type: 'denoise_latents',
|
||||
id: DENOISE_LATENTS,
|
||||
cfg_scale,
|
||||
cfg_rescale_multiplier,
|
||||
scheduler,
|
||||
steps,
|
||||
denoising_start: 1 - strength,
|
||||
|
||||
@ -126,6 +126,7 @@ export const buildLinearSDXLImageToImageGraph = (state: RootState): NonNullableG
|
||||
type: 'denoise_latents',
|
||||
id: SDXL_DENOISE_LATENTS,
|
||||
cfg_scale,
|
||||
cfg_rescale_multiplier,
|
||||
scheduler,
|
||||
steps,
|
||||
denoising_start: refinerModel ? Math.min(refinerStart, 1 - strength) : 1 - strength,
|
||||
|
||||
@ -109,6 +109,7 @@ export const buildLinearSDXLTextToImageGraph = (state: RootState): NonNullableGr
|
||||
type: 'denoise_latents',
|
||||
id: SDXL_DENOISE_LATENTS,
|
||||
cfg_scale,
|
||||
cfg_rescale_multiplier,
|
||||
scheduler,
|
||||
steps,
|
||||
denoising_start: 0,
|
||||
|
||||
@ -23,7 +23,7 @@ import ParamMainModelSelect from 'features/parameters/components/MainModel/Param
|
||||
import { selectGenerationSlice } from 'features/parameters/store/generationSlice';
|
||||
import { useExpanderToggle } from 'features/settingsAccordions/hooks/useExpanderToggle';
|
||||
import { useStandaloneAccordionToggle } from 'features/settingsAccordions/hooks/useStandaloneAccordionToggle';
|
||||
import { filter, size } from 'lodash-es';
|
||||
import { filter } from 'lodash-es';
|
||||
import { memo } from 'react';
|
||||
import { useTranslation } from 'react-i18next';
|
||||
|
||||
@ -33,7 +33,7 @@ const formLabelProps: FormLabelProps = {
|
||||
|
||||
const badgesSelector = createMemoizedSelector(selectLoraSlice, selectGenerationSlice, (lora, generation) => {
|
||||
const enabledLoRAsCount = filter(lora.loras, (l) => !!l.isEnabled).length;
|
||||
const loraTabBadges = size(lora.loras) ? [enabledLoRAsCount] : [];
|
||||
const loraTabBadges = enabledLoRAsCount ? [enabledLoRAsCount] : [];
|
||||
const accordionBadges: (string | number)[] = [];
|
||||
if (generation.model) {
|
||||
accordionBadges.push(generation.model.model_name);
|
||||
|
||||
@ -1,6 +1,12 @@
|
||||
import { useAppDispatch } from 'app/store/storeHooks';
|
||||
import { $builtWorkflow } from 'features/nodes/hooks/useWorkflowWatcher';
|
||||
import { workflowDownloaded } from 'features/workflowLibrary/store/actions';
|
||||
import { useCallback } from 'react';
|
||||
|
||||
const downloadWorkflow = () => {
|
||||
export const useDownloadWorkflow = () => {
|
||||
const dispatch = useAppDispatch();
|
||||
|
||||
const downloadWorkflow = useCallback(() => {
|
||||
const workflow = $builtWorkflow.get();
|
||||
if (!workflow) {
|
||||
return;
|
||||
@ -12,8 +18,8 @@ const downloadWorkflow = () => {
|
||||
document.body.appendChild(a);
|
||||
a.click();
|
||||
a.remove();
|
||||
};
|
||||
dispatch(workflowDownloaded());
|
||||
}, [dispatch]);
|
||||
|
||||
export const useDownloadWorkflow = () => {
|
||||
return downloadWorkflow;
|
||||
};
|
||||
|
||||
@ -3,6 +3,7 @@ import { useAppDispatch } from 'app/store/storeHooks';
|
||||
import { workflowLoadRequested } from 'features/nodes/store/actions';
|
||||
import { addToast } from 'features/system/store/systemSlice';
|
||||
import { makeToast } from 'features/system/util/makeToast';
|
||||
import { workflowLoadedFromFile } from 'features/workflowLibrary/store/actions';
|
||||
import type { RefObject } from 'react';
|
||||
import { useCallback } from 'react';
|
||||
import { useTranslation } from 'react-i18next';
|
||||
@ -29,6 +30,7 @@ export const useLoadWorkflowFromFile: UseLoadWorkflowFromFile = ({ resetRef }) =
|
||||
try {
|
||||
const parsedJSON = JSON.parse(String(rawJSON));
|
||||
dispatch(workflowLoadRequested({ workflow: parsedJSON, asCopy: true }));
|
||||
dispatch(workflowLoadedFromFile());
|
||||
} catch (e) {
|
||||
// There was a problem reading the file
|
||||
logger.error(t('nodes.unableToLoadWorkflow'));
|
||||
|
||||
@ -4,6 +4,7 @@ import { useAppDispatch } from 'app/store/storeHooks';
|
||||
import { $builtWorkflow } from 'features/nodes/hooks/useWorkflowWatcher';
|
||||
import { workflowIDChanged, workflowSaved } from 'features/nodes/store/workflowSlice';
|
||||
import type { WorkflowV2 } from 'features/nodes/types/workflow';
|
||||
import { workflowUpdated } from 'features/workflowLibrary/store/actions';
|
||||
import { useCallback, useRef } from 'react';
|
||||
import { useTranslation } from 'react-i18next';
|
||||
import { useCreateWorkflowMutation, useUpdateWorkflowMutation, workflowsApi } from 'services/api/endpoints/workflows';
|
||||
@ -41,6 +42,7 @@ export const useSaveLibraryWorkflow: UseSaveLibraryWorkflow = () => {
|
||||
try {
|
||||
if (isWorkflowWithID(workflow)) {
|
||||
await updateWorkflow(workflow).unwrap();
|
||||
dispatch(workflowUpdated());
|
||||
} else {
|
||||
const data = await createWorkflow(workflow).unwrap();
|
||||
dispatch(workflowIDChanged(data.workflow.id));
|
||||
|
||||
@ -9,6 +9,7 @@ import {
|
||||
workflowSaved,
|
||||
} from 'features/nodes/store/workflowSlice';
|
||||
import type { WorkflowCategory } from 'features/nodes/types/workflow';
|
||||
import { newWorkflowSaved } from 'features/workflowLibrary/store/actions';
|
||||
import { useCallback, useRef } from 'react';
|
||||
import { useTranslation } from 'react-i18next';
|
||||
import { useCreateWorkflowMutation, workflowsApi } from 'services/api/endpoints/workflows';
|
||||
@ -56,6 +57,7 @@ export const useSaveWorkflowAs: UseSaveWorkflowAs = () => {
|
||||
dispatch(workflowNameChanged(data.workflow.name));
|
||||
dispatch(workflowCategoryChanged(data.workflow.meta.category));
|
||||
dispatch(workflowSaved());
|
||||
dispatch(newWorkflowSaved({ category }));
|
||||
|
||||
onSuccess && onSuccess();
|
||||
toast.update(toastRef.current, {
|
||||
|
||||
@ -0,0 +1,10 @@
|
||||
import { createAction } from '@reduxjs/toolkit';
|
||||
import type { WorkflowCategory } from 'features/nodes/types/workflow';
|
||||
|
||||
export const workflowDownloaded = createAction('workflowLibrary/workflowDownloaded');
|
||||
|
||||
export const workflowLoadedFromFile = createAction('workflowLibrary/workflowLoadedFromFile');
|
||||
|
||||
export const newWorkflowSaved = createAction<{ category: WorkflowCategory }>('workflowLibrary/newWorkflowSaved');
|
||||
|
||||
export const workflowUpdated = createAction('workflowLibrary/workflowUpdated');
|
||||
@ -34,14 +34,13 @@ classifiers = [
|
||||
dependencies = [
|
||||
# Core generation dependencies, pinned for reproducible builds.
|
||||
"accelerate==0.26.1",
|
||||
"basicsr==1.4.2",
|
||||
"clip_anytorch==2.5.2", # replacing "clip @ https://github.com/openai/CLIP/archive/eaa22acb90a5876642d0507623e859909230a52d.zip",
|
||||
"compel==2.0.2",
|
||||
"controlnet-aux==0.0.7",
|
||||
"diffusers[torch]==0.26.1",
|
||||
"diffusers[torch]==0.26.2",
|
||||
"invisible-watermark==0.2.0", # needed to install SDXL base and refiner using their repo_ids
|
||||
"mediapipe==0.10.7", # needed for "mediapipeface" controlnet model
|
||||
"numpy==1.26.3", # >1.24.0 is needed to use the 'strict' argument to np.testing.assert_array_equal()
|
||||
"numpy==1.26.4", # >1.24.0 is needed to use the 'strict' argument to np.testing.assert_array_equal()
|
||||
"onnx==1.15.0",
|
||||
"onnxruntime==1.16.3",
|
||||
"opencv-python==4.9.0.80",
|
||||
@ -55,13 +54,13 @@ dependencies = [
|
||||
"transformers==4.37.2",
|
||||
|
||||
# Core application dependencies, pinned for reproducible builds.
|
||||
"fastapi-events==0.10.0",
|
||||
"fastapi==0.108.0",
|
||||
"fastapi-events==0.10.1",
|
||||
"fastapi==0.109.2",
|
||||
"huggingface-hub==0.20.3",
|
||||
"pydantic-settings==2.1.0",
|
||||
"pydantic==2.5.3",
|
||||
"python-socketio==5.11.0",
|
||||
"uvicorn[standard]==0.25.0",
|
||||
"pydantic==2.6.1",
|
||||
"python-socketio==5.11.1",
|
||||
"uvicorn[standard]==0.27.1",
|
||||
|
||||
# Auxiliary dependencies, pinned only if necessary.
|
||||
"albumentations",
|
||||
@ -111,7 +110,7 @@ dependencies = [
|
||||
]
|
||||
"dev" = ["jurigged", "pudb", "snakeviz", "gprof2dot"]
|
||||
"test" = [
|
||||
"ruff==0.1.11",
|
||||
"ruff==0.2.1",
|
||||
"ruff-lsp",
|
||||
"mypy",
|
||||
"pre-commit",
|
||||
@ -205,13 +204,6 @@ output = "coverage/index.xml"
|
||||
#=== Begin: Ruff
|
||||
[tool.ruff]
|
||||
line-length = 120
|
||||
ignore = [
|
||||
"E501", # https://docs.astral.sh/ruff/rules/line-too-long/
|
||||
"C901", # https://docs.astral.sh/ruff/rules/complex-structure/
|
||||
"B008", # https://docs.astral.sh/ruff/rules/function-call-in-default-argument/
|
||||
"B904", # https://docs.astral.sh/ruff/rules/raise-without-from-inside-except/
|
||||
]
|
||||
select = ["B", "C", "E", "F", "W", "I"]
|
||||
exclude = [
|
||||
".git",
|
||||
"__pycache__",
|
||||
@ -220,6 +212,15 @@ exclude = [
|
||||
"invokeai/frontend/web/node_modules/",
|
||||
".venv*",
|
||||
]
|
||||
|
||||
[tool.ruff.lint]
|
||||
ignore = [
|
||||
"E501", # https://docs.astral.sh/ruff/rules/line-too-long/
|
||||
"C901", # https://docs.astral.sh/ruff/rules/complex-structure/
|
||||
"B008", # https://docs.astral.sh/ruff/rules/function-call-in-default-argument/
|
||||
"B904", # https://docs.astral.sh/ruff/rules/raise-without-from-inside-except/
|
||||
]
|
||||
select = ["B", "C", "E", "F", "W", "I"]
|
||||
#=== End: Ruff
|
||||
|
||||
#=== Begin: MyPy
|
||||
|
||||
Loading…
Reference in New Issue
Block a user