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Author SHA1 Message Date
Millun Atluri
6539ef7c9f {release} v3.6.3 (#5696)
## What type of PR is this? (check all applicable)
Release Invoke 3.6.3


## Have you discussed this change with the InvokeAI team?
- [X] Yes
- [ ] No, because:

      
## Have you updated all relevant documentation?
- [X] Yes
- [ ] No


## Description
Invoke 3.6.3 Release



## QA Instructions, Screenshots, Recordings
Test the installer:
[InvokeAI-installer-v3.6.3.zip](https://github.com/invoke-ai/InvokeAI/files/14233359/InvokeAI-installer-v3.6.3.zip)

<!-- 
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software specifications as well as any other pertinent information. 
-->

## Merge Plan
Merge once approved
<!--
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- "This must be squash-merged when approved"
- "DO NOT MERGE - I will rebase and tidy commits before merging"
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## [optional] Are there any post deployment tasks we need to perform?
1. Release on PyPi & GitHub
2. Announce on Discord
2024-02-11 16:02:30 -05:00
Millun Atluri
14c9a1e4f3 Merge branch 'main' into release/3.6.3 2024-02-11 15:36:05 -05:00
Millun Atluri
64b0feca31 Update ruff 2024-02-11 15:24:28 -05:00
Millun Atluri
0be9a2d906 Update string formatting 2024-02-11 15:24:28 -05:00
Millun Atluri
d925f721b9 fix references to .env.sample (#5695)
## What type of PR is this? (check all applicable)

- [ ] Refactor
- [ ] Feature
- [ ] Bug Fix
- [ ] Optimization
- [x] Documentation Update
- [ ] Community Node Submission


## Have you discussed this change with the InvokeAI team?
- [ ] Yes
- [x] No, because: it is text only, simple, and (hopefully) self-evident

      
## Have you updated all relevant documentation?
- [x] Yes - as far as I can grep.
- [ ] No


## Description

`.env.sample` was misspelled as `env.sample` in a few places.

This changes documentation only. You may need to re-build/deploy docs,
I'm not sure.
2024-02-11 13:43:14 -05:00
Millun Atluri
4e5be1891a {release} v3.6.3 2024-02-11 10:34:47 -07:00
Adam Monsen
156d4ec3b2 fix references to .env.sample 2024-02-10 21:11:22 -08:00
psychedelicious
c45a43519a chore: bump deps
- ruff 0.1.11 -> 0.2.1
- update config format
2024-02-11 08:50:49 +11:00
psychedelicious
763816ca0c chore: bump deps
- pydantic 2.5.3 -> 2.6.1
- uvicorn 0.25.0 -> 0.27.1
2024-02-11 08:50:49 +11:00
B N
83a7c9059f translationBot(ui): update translation (German)
Currently translated at 78.1% (1107 of 1416 strings)

Co-authored-by: B N <berndnieschalk@gmail.com>
Translate-URL: https://hosted.weblate.org/projects/invokeai/web-ui/de/
Translation: InvokeAI/Web UI
2024-02-11 08:40:55 +11:00
psychedelicious
c5f069a255 feat(backend): remove dependency on basicsr
`basicsr` has a hard dependency on torchvision <= 0.16 and is unmaintained. Extract the code we need from it and remove the dep.

Closes #5108
2024-02-11 08:34:54 +11:00
Brandon
cd169ee082 fix(nodes): deep copy graph inputs (#5686)
## What type of PR is this? (check all applicable)

- [ ] Refactor
- [ ] Feature
- [x] Bug Fix
- [ ] Optimization
- [ ] Documentation Update
- [ ] Community Node Submission

## Description

The change to memory session storage brings a subtle behaviour change.

Previously, we serialized and deserialized everything (e.g. field state,
invocation outputs, etc) constantly. The meant we were effectively
working with deep-copied objects at all time. We could mutate objects
freely without worrying about other references to the object.

With memory storage, objects are now passed around by reference, and we
cannot handle them in the same way.

This is problematic for nodes that mutate their own inputs. There are
two ways this causes a problem:

- An output is used as input for multiple nodes. If the first node
mutates the output object while `invoke`ing, the next node will get the
mutated object.
- The invocation cache stores live python objects. When a node mutates
an output pulled from the cache, the next node that uses the cached
object will get the mutated object.

The solution is to deep-copy a node's inputs as they are set,
effectively reproducing the same behaviour as we had with the SQLite
session storage. Nodes can safely mutate their inputs and those changes
never leave the node's scope.

## Related Tickets & Documents

<!--
For pull requests that relate or close an issue, please include them
below. 

For example having the text: "closes #1234" would connect the current
pull
request to issue 1234.  And when we merge the pull request, Github will
automatically close the issue.
-->

- Closes  #5665

The root issue affects CLIP Skip because that node mutates its input
`ClipField`. Specifically, it increments `self.clip.skipped_layers` and
passes `self.clip` as its output. I don't know if there are any other
nodes that do this.

## QA Instructions, Screenshots, Recordings

Two issues to reproduce. 

First is the caching issue:


![image](https://github.com/invoke-ai/InvokeAI/assets/4822129/7a251e48-bc70-4b8e-8816-84aac41ce4d3)

Note the cache is enabled. Run this simple graph a couple times, and
check the outputs of the CLIP Skip node. You'll see the `skipped_layers`
value increasing each time.

Second is the nodes-sharing-inputs issue:


![image](https://github.com/invoke-ai/InvokeAI/assets/4822129/ecdaefab-2beb-4950-b4bf-2a5738ce6832)

Note the cache is _disabled_. Run the graph a couple times and check the
outputs of the two CLIP Skip nodes. You'll see that one has the expected
value for `skipped_layers` and the other has double that.

Now update to the PR and try again. You should see `skipped_layers` is
the right value in all cases.

<!-- 
Please provide steps on how to test changes, any hardware or 
software specifications as well as any other pertinent information. 
-->

## Merge Plan

This PR can be merged when approved. It needs a real review with
braintime.

<!--
A merge plan describes how this PR should be handled after it is
approved.

Example merge plans:
- "This PR can be merged when approved"
- "This must be squash-merged when approved"
- "DO NOT MERGE - I will rebase and tidy commits before merging"
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merged"

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the
database in any way.
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2024-02-09 13:24:10 -05:00
Brandon
66b106f107 Merge branch 'main' into fix/nodes/deep-copy-inputs 2024-02-09 11:49:16 -05:00
psychedelicious
b10d745dae fix(ui): when using control image dimensions, round to 8
The control image dimensions were set directly without rounding them to 8, causing an error during generation if they weren't a multiple of 8.
2024-02-09 08:44:11 -05:00
psychedelicious
d20f98fb4f fix(nodes): deep copy graph inputs
The change to memory session storage brings a subtle behaviour change.

Previously, we serialized and deserialized everything (e.g. field state, invocation outputs, etc) constantly. The meant we were effectively working with deep-copied objects at all time. We could mutate objects freely without worrying about other references to the object.

With memory storage, objects are now passed around by reference, and we cannot handle them in the same way.

This is problematic for nodes that mutate their own inputs. There are two ways this causes a problem:

- An output is used as input for multiple nodes. If the first node mutates the output object while `invoke`ing, the next node will get the mutated object.
- The invocation cache stores live python objects. When a node mutates an output pulled from the cache, the next node that uses the cached object will get the mutated object.

The solution is to deep-copy a node's inputs as they are set, effectively reproducing the same behaviour as we had with the SQLite session storage. Nodes can safely mutate their inputs and those changes never leave the node's scope.

Closes  #5665
2024-02-09 21:17:32 +11:00
psychedelicious
c9c150f850 feat(ui): use cfgRescaleMultiplier on canvas graphs 2024-02-09 18:53:08 +11:00
skunkworxdark
a60e2b7c77 fix existing graphs with cfg_RescaleMultiplier not used 2024-02-09 18:53:08 +11:00
psychedelicious
da6e5b2ba1 fix(ui): fix lora count badge when none enabled 2024-02-08 19:22:28 -05:00
psychedelicious
c65d497cbc fix(ui): filter disabled LoRAs on sdxl 2024-02-08 19:22:28 -05:00
B N
a68d8fe203 translationBot(ui): update translation (German)
Currently translated at 74.4% (1054 of 1416 strings)

translationBot(ui): update translation (German)

Currently translated at 69.6% (986 of 1416 strings)

translationBot(ui): update translation (German)

Currently translated at 68.6% (972 of 1416 strings)

Co-authored-by: B N <berndnieschalk@gmail.com>
Translate-URL: https://hosted.weblate.org/projects/invokeai/web-ui/de/
Translation: InvokeAI/Web UI
2024-02-09 10:10:50 +11:00
Jennifer Player
5de2288cfa addressed feedback 2024-02-09 10:09:27 +11:00
Jennifer Player
2ce70b4457 added button on hover for exposing fields to linear workflow ui 2024-02-09 10:09:27 +11:00
Brandon Rising
6c5f743e2b Upgrade version of fastapi and socketio 2024-02-09 09:04:01 +11:00
Millun Atluri
bb242c4e1e Print correct version when a non-default version is selected for install (#5675)
…elected

## What type of PR is this? (check all applicable)

- [ ] Refactor
- [ ] Feature
- [x] Bug Fix
- [ ] Optimization
- [ ] Documentation Update
- [ ] Community Node Submission


## Have you discussed this change with the InvokeAI team?
- [x] Yes
- [ ] No, because:

      
## Have you updated all relevant documentation?
- [ ] Yes
- [ ] No


## Description

Small bugfix: the installer would always print the latest stable version
as the one to be installed, even if a different one was selected. The
selected version would still be installed correctly. This PR fixes the
message.

## QA Instructions, Screenshots, Recordings

Select a pre-release version on install and observe the correct version
being printed. Compare to current behaviour to ascertain the fix.

## Merge Plan

- "This PR can be merged when approved"

## Added/updated tests?

- [ ] Yes
- [x] No
2024-02-08 11:07:14 -05:00
Eugene Brodsky
c9e246ed1b fix(installer): print correct version when a non-default version is selected 2024-02-08 09:56:56 -05:00
B N
2175fe3823 translationBot(ui): update translation (German)
Currently translated at 66.2% (938 of 1416 strings)

Co-authored-by: B N <berndnieschalk@gmail.com>
Translate-URL: https://hosted.weblate.org/projects/invokeai/web-ui/de/
Translation: InvokeAI/Web UI
2024-02-08 07:57:55 +11:00
Eugene Brodsky
f64fc2c8b7 feat(installer): add a deprecation message to the in-launcher updater 2024-02-07 14:31:26 -05:00
Eugene Brodsky
3d1b5c57ea fix(installer): more reliably upgrade pip 2024-02-07 14:31:26 -05:00
Eugene Brodsky
31b9538976 feat(installer): improve directory selection experience 2024-02-07 14:31:26 -05:00
Eugene Brodsky
97c1545cca feat(installer): show latest versions in the welcome panel 2024-02-07 14:31:26 -05:00
Eugene Brodsky
6a8a3b50bc feat(installer): add an interactive version chooser 2024-02-07 14:31:26 -05:00
Eugene Brodsky
5a816818dc feat(installer): get list of (pre-)releases from github api 2024-02-07 14:31:26 -05:00
Eugene Brodsky
1cb866d1fc fix(installer): small formatting fix in welcome banner 2024-02-07 14:31:26 -05:00
Eugene Brodsky
29bcc4b595 fix(installer) slightly better typing for GPU selection 2024-02-07 14:31:26 -05:00
Eugene Brodsky
ca2bb6f0cc fix(installer): bubble up exceptions during install 2024-02-07 14:31:26 -05:00
Eugene Brodsky
1c8fc908b2 fix(installer): minor logic fixes 2024-02-07 14:31:26 -05:00
Eugene Brodsky
d397beaa47 fix(installer): upgrade the temporary pip before installation 2024-02-07 14:31:26 -05:00
Eugene Brodsky
60eea09629 feat(installer): *always* force-reinstall
This has repeatedly shown itself useful in fixing install issues,
especially regarding pytorch CPU/GPU version, so there is little
downside to making this the default.

Performance impact of this should be negligible. Packages will
be reinstalled from pip cache if possible, and downloaded only if
necessary. Impact may be felt on slower disks.
2024-02-07 14:31:26 -05:00
Eugene Brodsky
5b7b1122cb tidy(installer): clean up unused code 2024-02-07 14:31:26 -05:00
Eugene Brodsky
dfc8d1bb10 tidy(installer): remove unused argument / env var 2024-02-07 14:31:26 -05:00
Eugene Brodsky
f9fa62164e tidy(installer): remove .whl publishing and bundling - we now install from pypi 2024-02-07 14:31:26 -05:00
Eugene Brodsky
d47905d2fb chore(installer): reorder messages in util script
fail fast if there's a virtualenv activated
2024-02-07 14:31:26 -05:00
Eugene Brodsky
03b1cde97d tidy(installer): remove unused update scripts and references thereto 2024-02-07 14:31:26 -05:00
Eugene Brodsky
7162ff04df tidy(installer): do not preinstall torch separately 2024-02-07 14:31:26 -05:00
Eugene Brodsky
32b1e974ca feat(installer): install from PyPi instead of using prepackaged wheel 2024-02-07 14:31:26 -05:00
Eugene Brodsky
82c3c7fc38 tidy(installer): remove unused experimental venv location 2024-02-07 14:31:26 -05:00
Eugene Brodsky
3dcbb79ef7 chore(installer): typing pass 2024-02-07 14:31:26 -05:00
Millun Atluri
3b41104427 Minor dep updates for diffusers and numpy (#5673)
## What type of PR is this? (check all applicable)

- [ ] Refactor
- [ ] Feature
- [ ] Bug Fix
- [X] Optimization
- [ ] Documentation Update
- [ ] Community Node Submission


## Have you discussed this change with the InvokeAI team?
- [ ] Yes
- [X] No, because probably not needed

      
## Have you updated all relevant documentation?
- [ ] Yes
- [ ] No


## Description

These are another minor dep updates that I was able to test without any
regressions. This will ensure we are up-to-date again.
The fixes are very minor, probably not noticeable in InvokeAI (at least
for diffusers) but it's still good to have them.

This is also to make sure that the RC is releasing with the latest
packages to ensure extended testing.

Greetings

## Related Tickets & Documents

<!--
For pull requests that relate or close an issue, please include them
below. 

For example having the text: "closes #1234" would connect the current
pull
request to issue 1234.  And when we merge the pull request, Github will
automatically close the issue.
-->

- Related Issue #
- Closes #

## QA Instructions, Screenshots, Recordings

<!-- 
Please provide steps on how to test changes, any hardware or 
software specifications as well as any other pertinent information. 
-->

## Merge Plan

<!--
A merge plan describes how this PR should be handled after it is
approved.

Example merge plans:
- "This PR can be merged when approved"
- "This must be squash-merged when approved"
- "DO NOT MERGE - I will rebase and tidy commits before merging"
- "#dev-chat on discord needs to be advised of this change when it is
merged"

A merge plan is particularly important for large PRs or PRs that touch
the
database in any way.
-->

## Added/updated tests?

- [ ] Yes
- [ ] No : _please replace this line with details on why tests
      have not been included_

## [optional] Are there any post deployment tasks we need to perform?
2024-02-07 13:29:29 -05:00
Wubbbi
35bf7ee66d Minor dep updates 2024-02-07 17:58:28 +01:00
Millun Atluri
430e17a5d2 community node: BriaAI RMBG 1.4 (#5671)
## What type of PR is this? (check all applicable)

- [x] Community Node Submission


## Description

- Adds BriaAI's new 1.4 model for background removal. Far superior
results from what I've tested compared to any other BG removal so far:
https://github.com/blessedcoolant/invoke_bria_rmbg
2024-02-07 11:06:31 -05:00
blessedcoolant
400d66fa5d community node: BriaAI RMBG 1.4 2024-02-07 19:55:04 +05:30
Mary Hipp Rogers
800c481515 add actions for workflow library (#5669)
Co-authored-by: Mary Hipp <maryhipp@Marys-MacBook-Air.local>
2024-02-07 14:14:54 +00:00
psychedelicious
79ae9c4e64 feat(nodes): move profiler/stats cleanup logic to function
Harder to miss something going forward.
2024-02-07 11:26:15 +11:00
psychedelicious
0dc6cb0535 feat(nodes): do not log stats errors
The stats service was logging error messages when attempting to retrieve stats for a graph that it wasn't tracking. This was rather noisy.

Instead of logging these errors within the service, we now will just raise the error and let the consumer of the service decide whether or not to log. Our usage of the service at this time is to suppress errors - we don't want to log anything to the console.

Note: With the improvements in the previous two commits, we shouldn't get these errors moving forward, but I still think this change is correct.
2024-02-07 11:26:15 +11:00
psychedelicious
810fc19e43 feat(nodes): log stats for canceled graphs
When an invocation is canceled, we consider the graph canceled. Log its graph's stats before resetting its graph's stats. No reason to not log these stats.

We also should stop the profiler at this point, because this graph is finished. If we don't stop it manually, it will stop itself and write the profile to disk when it is next started, but the resultant profile will include more than just its target graph.

Now we get both stats and profiles for canceled graphs.
2024-02-07 11:26:15 +11:00
psychedelicious
e0e106367d fix(nodes): do not clear invocation stats on invoke error
When an invocation errored, we clear the stats for the whole graph. Later on, we check the graph for errors and see the failed invocation, and we consider the graph failed. We then attempts to log the stats for the failed graph.

Except now the failed graph has no stats, and the stats raises an error.

The user sees, in the terminal:
- An invocation error
- A stats error (scary!)
- No stats for the failed graph (uninformative!)

What the user should see:
- An invocation error
- Graph stats

The fix is simple - don't reset the graph stats when an invocation has an error.
2024-02-07 11:26:15 +11:00
48 changed files with 1281 additions and 644 deletions

View File

@@ -28,7 +28,7 @@ This is done via Docker Desktop preferences
### Configure Invoke environment
1. Make a copy of `env.sample` and name it `.env` (`cp env.sample .env` (Mac/Linux) or `copy example.env .env` (Windows)). Make changes as necessary. Set `INVOKEAI_ROOT` to an absolute path to:
1. Make a copy of `.env.sample` and name it `.env` (`cp .env.sample .env` (Mac/Linux) or `copy example.env .env` (Windows)). Make changes as necessary. Set `INVOKEAI_ROOT` to an absolute path to:
a. the desired location of the InvokeAI runtime directory, or
b. an existing, v3.0.0 compatible runtime directory.
1. Execute `run.sh`

View File

@@ -69,7 +69,7 @@ a token and copy it, since you will need in for the next step.
### Setup
Set up your environmnent variables. In the `docker` directory, make a copy of `env.sample` and name it `.env`. Make changes as necessary.
Set up your environmnent variables. In the `docker` directory, make a copy of `.env.sample` and name it `.env`. Make changes as necessary.
Any environment variables supported by InvokeAI can be set here - please see the [CONFIGURATION](../features/CONFIGURATION.md) for further detail.

View File

@@ -42,6 +42,7 @@ To use a community workflow, download the the `.json` node graph file and load i
+ [Oobabooga](#oobabooga)
+ [Prompt Tools](#prompt-tools)
+ [Remote Image](#remote-image)
+ [BriaAI Background Remove](#briaai-remove-background)
+ [Remove Background](#remove-background)
+ [Retroize](#retroize)
+ [Size Stepper Nodes](#size-stepper-nodes)
@@ -434,6 +435,17 @@ See full docs here: https://github.com/skunkworxdark/Prompt-tools-nodes/edit/mai
**Node Link:** https://github.com/fieldOfView/InvokeAI-remote_image
--------------------------------
### BriaAI Remove Background
**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.
**Node Link:** https://github.com/blessedcoolant/invoke_bria_rmbg
**View**
<img src="https://raw.githubusercontent.com/blessedcoolant/invoke_bria_rmbg/main/assets/preview.jpg" />
--------------------------------
### Remove Background

View File

@@ -14,11 +14,19 @@ function is_bin_in_path {
}
function git_show {
git show -s --format='%h %s' $1
git show -s --format=oneline --abbrev-commit "$1" | cat
}
if [[ -v "VIRTUAL_ENV" ]]; then
# we can't just call 'deactivate' because this function is not exported
# to the environment of this script from the bash process that runs the script
echo -e "${BRED}A virtual environment is activated. Please deactivate it before proceeding.${RESET}"
exit -1
fi
cd "$(dirname "$0")"
echo
echo -e "${BYELLOW}This script must be run from the installer directory!${RESET}"
echo "The current working directory is $(pwd)"
read -p "If that looks right, press any key to proceed, or CTRL-C to exit..."
@@ -32,13 +40,6 @@ if ! is_bin_in_path python && is_bin_in_path python3; then
}
fi
if [[ -v "VIRTUAL_ENV" ]]; then
# we can't just call 'deactivate' because this function is not exported
# to the environment of this script from the bash process that runs the script
echo -e "${BRED}A virtual environment is activated. Please deactivate it before proceeding.${RESET}"
exit -1
fi
VERSION=$(
cd ..
python -c "from invokeai.version import __version__ as version; print(version)"
@@ -47,38 +48,9 @@ PATCH=""
VERSION="v${VERSION}${PATCH}"
echo -e "${BGREEN}HEAD${RESET}:"
git_show
git_show HEAD
echo
# ---------------------- FRONTEND ----------------------
pushd ../invokeai/frontend/web >/dev/null
echo
echo "Installing frontend dependencies..."
echo
pnpm i --frozen-lockfile
echo
echo "Building frontend..."
echo
pnpm build
popd
# ---------------------- BACKEND ----------------------
echo
echo "Building wheel..."
echo
# install the 'build' package in the user site packages, if needed
# could be improved by using a temporary venv, but it's tiny and harmless
if [[ $(python -c 'from importlib.util import find_spec; print(find_spec("build") is None)') == "True" ]]; then
pip install --user build
fi
rm -rf ../build
python -m build --wheel --outdir dist/ ../.
# ----------------------
echo
@@ -97,16 +69,13 @@ done
mkdir InvokeAI-Installer/lib
cp lib/*.py InvokeAI-Installer/lib
# Move the wheel
mv dist/*.whl InvokeAI-Installer/lib/
# Install scripts
# Mac/Linux
cp install.sh.in InvokeAI-Installer/install.sh
chmod a+x InvokeAI-Installer/install.sh
# Windows
perl -p -e "s/^set INVOKEAI_VERSION=.*/set INVOKEAI_VERSION=$VERSION/" install.bat.in >InvokeAI-Installer/install.bat
cp install.bat.in InvokeAI-Installer/install.bat
cp WinLongPathsEnabled.reg InvokeAI-Installer/
# Zip everything up

View File

@@ -15,7 +15,6 @@ if "%1" == "use-cache" (
@rem Config
@rem The version in the next line is replaced by an up to date release number
@rem when create_installer.sh is run. Change the release number there.
set INVOKEAI_VERSION=latest
set INSTRUCTIONS=https://invoke-ai.github.io/InvokeAI/installation/INSTALL_AUTOMATED/
set TROUBLESHOOTING=https://invoke-ai.github.io/InvokeAI/installation/INSTALL_AUTOMATED/#troubleshooting
set PYTHON_URL=https://www.python.org/downloads/windows/

View File

@@ -11,7 +11,7 @@ import sys
import venv
from pathlib import Path
from tempfile import TemporaryDirectory
from typing import Union
from typing import Optional, Tuple
SUPPORTED_PYTHON = ">=3.10.0,<=3.11.100"
INSTALLER_REQS = ["rich", "semver", "requests", "plumbum", "prompt-toolkit"]
@@ -21,40 +21,20 @@ OS = platform.uname().system
ARCH = platform.uname().machine
VERSION = "latest"
### Feature flags
# Install the virtualenv into the runtime dir
FF_VENV_IN_RUNTIME = True
# Install the wheel packaged with the installer
FF_USE_LOCAL_WHEEL = True
class Installer:
"""
Deploys an InvokeAI installation into a given path
"""
reqs: list[str] = INSTALLER_REQS
def __init__(self) -> None:
self.reqs = INSTALLER_REQS
self.preflight()
if os.getenv("VIRTUAL_ENV") is not None:
print("A virtual environment is already activated. Please 'deactivate' before installation.")
sys.exit(-1)
self.bootstrap()
def preflight(self) -> None:
"""
Preflight checks
"""
# TODO
# verify python version
# on macOS verify XCode tools are present
# verify libmesa, libglx on linux
# check that the system arch is not i386 (?)
# check that the system has a GPU, and the type of GPU
pass
self.available_releases = get_github_releases()
def mktemp_venv(self) -> TemporaryDirectory:
"""
@@ -78,12 +58,9 @@ class Installer:
return venv_dir
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
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[
"install",
"--require-virtualenv",
"--use-pep517",
str(src) + (optional_modules if optional_modules else ""),
"--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,
]
& FG
)
pipeline = pip[
"install",
"--require-virtualenv",
"--force-reinstall",
"--use-pep517",
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_flag,
]
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.
@@ -446,25 +421,26 @@ 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":
url = "https://download.pytorch.org/whl/cu121"
optional_modules = "[xformers,onnx-cuda]"
if device == "cuda_and_dml":
url = "https://download.pytorch.org/whl/cu121"
optional_modules = "[xformers,onnx-directml]"
elif OS == "Windows":
if device.value == "cuda":
url = "https://download.pytorch.org/whl/cu121"
optional_modules = "[xformers,onnx-cuda]"
if device.value == "cuda_and_dml":
url = "https://download.pytorch.org/whl/cu121"
optional_modules = "[xformers,onnx-directml]"
# in all other cases, Torch wheels should be coming from PyPi as of Torch 1.13

View File

@@ -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 +72,30 @@ 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,
)
else:
print(f"InvokeAI will be installed in {dest}")
dest_confirmed = Confirm.ask("Use this location?", default=True)
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),
)
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 +131,23 @@ 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 +162,21 @@ 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 +189,7 @@ def dest_path(dest=None) -> Path:
)
prev_dest = dest
dest = Path(selected)
console.line()
dest_confirmed = confirm_install(dest.expanduser().resolve())
@@ -182,41 +217,45 @@ 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 +269,7 @@ 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 +304,9 @@ 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 +330,7 @@ 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 +340,7 @@ 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 +379,7 @@ 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 +393,5 @@ 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

View File

@@ -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
@@ -52,8 +52,10 @@ 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...
python -m invokeai.frontend.install.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...
python .venv\Scripts\invokeai-db-maintenance.exe
@@ -77,4 +79,3 @@ pause
:ending
exit /b

View File

@@ -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"
)

View File

@@ -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

View File

@@ -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\'

View File

@@ -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)

View File

@@ -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

View File

@@ -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)
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,
)
stats_cleanup(graph_execution_state.id)
except KeyboardInterrupt:
pass # Log something? KeyboardInterrupt is probably not going to be seen by the processor

View File

@@ -106,9 +106,9 @@ 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)
@@ -136,9 +136,9 @@ 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,
@@ -154,9 +154,9 @@ 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)
@@ -164,8 +164,8 @@ 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()

View File

@@ -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:

View File

@@ -0,0 +1,201 @@
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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
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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
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Unless required by applicable law or agreed to in writing, software
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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.

View 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.
"""

View 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)

View 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

View File

@@ -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
"""

View File

@@ -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"
}
}

View File

@@ -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 };

View File

@@ -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]);

View File

@@ -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');

View File

@@ -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);

View File

@@ -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);

View File

@@ -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) => (
<EditableFieldTitle
ref={ref}
nodeId={nodeId}
fieldName={fieldName}
kind="input"
isMissingInput={isMissingInput}
withTooltip
/>
)}
</FieldContextMenu>
<Flex flexDir="column" w="full" gap={1} onMouseEnter={onMouseEnter} onMouseLeave={onMouseLeave}>
<Flex>
<EditableFieldTitle
nodeId={nodeId}
fieldName={fieldName}
kind="input"
isMissingInput={isMissingInput}
withTooltip
/>
{isHovered && <FieldLinearViewToggle nodeId={nodeId} fieldName={fieldName} />}
</Flex>
<InputFieldRenderer nodeId={nodeId} fieldName={fieldName} />
</Flex>
</FormControl>

View File

@@ -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('.', '_')}`;

View File

@@ -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,

View File

@@ -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,

View File

@@ -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,

View File

@@ -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,

View File

@@ -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,

View File

@@ -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,

View File

@@ -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,

View File

@@ -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,

View File

@@ -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,

View File

@@ -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,

View File

@@ -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,

View File

@@ -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);

View File

@@ -1,19 +1,25 @@
import { useAppDispatch } from 'app/store/storeHooks';
import { $builtWorkflow } from 'features/nodes/hooks/useWorkflowWatcher';
const downloadWorkflow = () => {
const workflow = $builtWorkflow.get();
if (!workflow) {
return;
}
const blob = new Blob([JSON.stringify(workflow, null, 2)]);
const a = document.createElement('a');
a.href = URL.createObjectURL(blob);
a.download = `${workflow.name || 'My Workflow'}.json`;
document.body.appendChild(a);
a.click();
a.remove();
};
import { workflowDownloaded } from 'features/workflowLibrary/store/actions';
import { useCallback } from 'react';
export const useDownloadWorkflow = () => {
const dispatch = useAppDispatch();
const downloadWorkflow = useCallback(() => {
const workflow = $builtWorkflow.get();
if (!workflow) {
return;
}
const blob = new Blob([JSON.stringify(workflow, null, 2)]);
const a = document.createElement('a');
a.href = URL.createObjectURL(blob);
a.download = `${workflow.name || 'My Workflow'}.json`;
document.body.appendChild(a);
a.click();
a.remove();
dispatch(workflowDownloaded());
}, [dispatch]);
return downloadWorkflow;
};

View File

@@ -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'));

View File

@@ -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));

View File

@@ -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, {

View File

@@ -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');

View File

@@ -1 +1 @@
__version__ = "3.6.2"
__version__ = "3.6.3"

View File

@@ -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",
@@ -140,7 +139,7 @@ dependencies = [
"invokeai-merge2" = "invokeai.frontend.merge.merge_diffusers2:main"
"invokeai-ti" = "invokeai.frontend.training:invokeai_textual_inversion"
"invokeai-model-install" = "invokeai.frontend.install.model_install:main"
"invokeai-model-install2" = "invokeai.frontend.install.model_install2:main" # will eventually be renamed to invokeai-model-install
"invokeai-model-install2" = "invokeai.frontend.install.model_install2:main" # will eventually be renamed to invokeai-model-install
"invokeai-migrate3" = "invokeai.backend.install.migrate_to_3:main"
"invokeai-update" = "invokeai.frontend.install.invokeai_update:main"
"invokeai-metadata" = "invokeai.backend.image_util.invoke_metadata:main"
@@ -207,13 +206,6 @@ 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__",
@@ -222,6 +214,15 @@ 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