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2 Commits

Author SHA1 Message Date
8c6a8d072d remove tab character 2023-12-15 09:35:06 -05:00
ec52f15f4b add frontend build steps to pypi workflow 2023-12-15 09:30:37 -05:00
1124 changed files with 28455 additions and 46782 deletions

8
.github/CODEOWNERS vendored
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@ -1,5 +1,5 @@
# continuous integration
/.github/workflows/ @lstein @blessedcoolant @hipsterusername @ebr
/.github/workflows/ @lstein @blessedcoolant @hipsterusername
# documentation
/docs/ @lstein @blessedcoolant @hipsterusername @Millu
@ -10,7 +10,7 @@
# installation and configuration
/pyproject.toml @lstein @blessedcoolant @hipsterusername
/docker/ @lstein @blessedcoolant @hipsterusername @ebr
/docker/ @lstein @blessedcoolant @hipsterusername
/scripts/ @ebr @lstein @hipsterusername
/installer/ @lstein @ebr @hipsterusername
/invokeai/assets @lstein @ebr @hipsterusername
@ -26,7 +26,9 @@
# front ends
/invokeai/frontend/CLI @lstein @hipsterusername
/invokeai/frontend/install @lstein @ebr @hipsterusername
/invokeai/frontend/install @lstein @ebr @hipsterusername
/invokeai/frontend/merge @lstein @blessedcoolant @hipsterusername
/invokeai/frontend/training @lstein @blessedcoolant @hipsterusername
/invokeai/frontend/web @psychedelicious @blessedcoolant @maryhipp @hipsterusername

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@ -40,14 +40,10 @@ jobs:
- name: Free up more disk space on the runner
# https://github.com/actions/runner-images/issues/2840#issuecomment-1284059930
run: |
echo "----- Free space before cleanup"
df -h
sudo rm -rf /usr/share/dotnet
sudo rm -rf "$AGENT_TOOLSDIRECTORY"
sudo swapoff /mnt/swapfile
sudo rm -rf /mnt/swapfile
echo "----- Free space after cleanup"
df -h
- name: Checkout
uses: actions/checkout@v3
@ -95,7 +91,6 @@ jobs:
# password: ${{ secrets.DOCKERHUB_TOKEN }}
- name: Build container
timeout-minutes: 40
id: docker_build
uses: docker/build-push-action@v4
with:

View File

@ -21,16 +21,16 @@ jobs:
if: github.event.pull_request.draft == false
runs-on: ubuntu-22.04
steps:
- name: Setup Node 18
- name: Setup Node 20
uses: actions/setup-node@v4
with:
node-version: '18'
node-version: '20'
- name: Checkout
uses: actions/checkout@v4
- name: Setup pnpm
uses: pnpm/action-setup@v2
with:
version: '8.12.1'
version: 8
- name: Install dependencies
run: 'pnpm install --prefer-frozen-lockfile'
- name: Typescript

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@ -1,15 +1,13 @@
name: PyPI Release
on:
push:
paths:
- 'invokeai/version/invokeai_version.py'
workflow_dispatch:
inputs:
publish_package:
description: 'Publish build on PyPi? [true/false]'
required: true
default: 'false'
jobs:
build-and-release:
release:
if: github.repository == 'invoke-ai/InvokeAI'
runs-on: ubuntu-22.04
env:
@ -17,39 +15,33 @@ jobs:
TWINE_PASSWORD: ${{ secrets.PYPI_API_TOKEN }}
TWINE_NON_INTERACTIVE: 1
steps:
- name: Checkout
- name: Checkout sources
uses: actions/checkout@v4
- name: Setup Node 18
- name: Setup Node 20
uses: actions/setup-node@v4
with:
node-version: '18'
node-version: '20'
- name: Setup pnpm
uses: pnpm/action-setup@v2
with:
version: '8.12.1'
version: 8
- name: Install frontend dependencies
run: pnpm install --prefer-frozen-lockfile
- name: Install pnpm dependencies
working-directory: invokeai/frontend/web
run: 'pnpm install --prefer-frozen-lockfile'
- name: Build frontend
run: pnpm run build
working-directory: invokeai/frontend/web
run: 'pnpm build'
- name: Install python dependencies
- name: Install python deps
run: pip install --upgrade build twine
- name: Build python package
- name: Build wheel package
run: python3 -m build
- name: Upload build as workflow artifact
uses: actions/upload-artifact@v4
with:
name: dist
path: dist
- name: Check distribution
run: twine check dist/*
@ -62,6 +54,6 @@ jobs:
EXISTS=scripts.pypi_helper.local_on_pypi(); \
print(f'PACKAGE_EXISTS={EXISTS}')" >> $GITHUB_ENV
- name: Publish build on PyPi
if: env.PACKAGE_EXISTS == 'False' && env.TWINE_PASSWORD != '' && github.event.inputs.publish_package == 'true'
- name: Upload package
if: env.PACKAGE_EXISTS == 'False' && env.TWINE_PASSWORD != ''
run: twine upload dist/*

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@ -1,10 +1,10 @@
<div align="center">
![project hero](https://github.com/invoke-ai/InvokeAI/assets/31807370/6e3728c7-e90e-4711-905c-3b55844ff5be)
![project hero](https://github.com/invoke-ai/InvokeAI/assets/31807370/1a917d94-e099-4fa1-a70f-7dd8d0691018)
# Invoke - Professional Creative AI Tools for Visual Media
## To learn more about Invoke, or implement our Business solutions, visit [invoke.com](https://www.invoke.com/about)
# Invoke AI - Generative AI for Professional Creatives
## Professional Creative Tools for Stable Diffusion, Custom-Trained Models, and more.
To learn more about Invoke AI, get started instantly, or implement our Business solutions, visit [invoke.ai](https://invoke.ai)
[![discord badge]][discord link]
@ -56,9 +56,7 @@ the foundation for multiple commercial products.
<div align="center">
![Highlighted Features - Canvas and Workflows](https://github.com/invoke-ai/InvokeAI/assets/31807370/708f7a82-084f-4860-bfbe-e2588c53548d)
![canvas preview](https://github.com/invoke-ai/InvokeAI/raw/main/docs/assets/canvas_preview.png)
</div>
@ -272,7 +270,7 @@ upgrade script.** See the next section for a Windows recipe.
3. Select option [1] to upgrade to the latest release.
4. Once the upgrade is finished you will be returned to the launcher
menu. Select option [6] "Re-run the configure script to fix a broken
menu. Select option [7] "Re-run the configure script to fix a broken
install or to complete a major upgrade".
This will run the configure script against the v2.3 directory and

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@ -2,17 +2,14 @@
## Any environment variables supported by InvokeAI can be specified here,
## in addition to the examples below.
# HOST_INVOKEAI_ROOT is the path on the docker host's filesystem where InvokeAI will store data.
# INVOKEAI_ROOT is the path to a path on the local filesystem where InvokeAI will store data.
# Outputs will also be stored here by default.
# If relative, it will be relative to the docker directory in which the docker-compose.yml file is located
#HOST_INVOKEAI_ROOT=../../invokeai-data
# INVOKEAI_ROOT is the path to the root of the InvokeAI repository within the container.
# INVOKEAI_ROOT=~/invokeai
# This **must** be an absolute path.
INVOKEAI_ROOT=
# Get this value from your HuggingFace account settings page.
# HUGGING_FACE_HUB_TOKEN=
## optional variables specific to the docker setup.
# GPU_DRIVER=nvidia #| rocm
# GPU_DRIVER=cuda # or rocm
# CONTAINER_UID=1000

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@ -59,16 +59,14 @@ RUN --mount=type=cache,target=/root/.cache/pip \
# #### Build the Web UI ------------------------------------
FROM node:20-slim AS web-builder
ENV PNPM_HOME="/pnpm"
ENV PATH="$PNPM_HOME:$PATH"
RUN corepack enable
FROM node:18 AS web-builder
WORKDIR /build
COPY invokeai/frontend/web/ ./
RUN --mount=type=cache,target=/pnpm/store \
pnpm install --frozen-lockfile
RUN npx vite build
RUN --mount=type=cache,target=/usr/lib/node_modules \
npm install --include dev
RUN --mount=type=cache,target=/usr/lib/node_modules \
yarn vite build
#### Runtime stage ---------------------------------------

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@ -1,14 +1,6 @@
# InvokeAI Containerized
All commands should be run within the `docker` directory: `cd docker`
## Quickstart :rocket:
On a known working Linux+Docker+CUDA (Nvidia) system, execute `./run.sh` in this directory. It will take a few minutes - depending on your internet speed - to install the core models. Once the application starts up, open `http://localhost:9090` in your browser to Invoke!
For more configuration options (using an AMD GPU, custom root directory location, etc): read on.
## Detailed setup
All commands are to be run from the `docker` directory: `cd docker`
#### Linux
@ -26,12 +18,12 @@ For more configuration options (using an AMD GPU, custom root directory location
This is done via Docker Desktop preferences
### Configure Invoke environment
## Quickstart
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`
1. `docker compose up`
The image will be built automatically if needed.
@ -45,21 +37,19 @@ The runtime directory (holding models and outputs) will be created in the locati
The Docker daemon on the system must be already set up to use the GPU. In case of Linux, this involves installing `nvidia-docker-runtime` and configuring the `nvidia` runtime as default. Steps will be different for AMD. Please see Docker documentation for the most up-to-date instructions for using your GPU with Docker.
To use an AMD GPU, set `GPU_DRIVER=rocm` in your `.env` file.
## Customize
Check the `.env.sample` file. It contains some environment variables for running in Docker. Copy it, name it `.env`, and fill it in with your own values. Next time you run `run.sh`, your custom values will be used.
Check the `.env.sample` file. It contains some environment variables for running in Docker. Copy it, name it `.env`, and fill it in with your own values. Next time you run `docker compose up`, your custom values will be used.
You can also set these values in `docker-compose.yml` directly, but `.env` will help avoid conflicts when code is updated.
Values are optional, but setting `INVOKEAI_ROOT` is highly recommended. The default is `~/invokeai`. Example:
Example (values are optional, but setting `INVOKEAI_ROOT` is highly recommended):
```bash
INVOKEAI_ROOT=/Volumes/WorkDrive/invokeai
HUGGINGFACE_TOKEN=the_actual_token
CONTAINER_UID=1000
GPU_DRIVER=nvidia
GPU_DRIVER=cuda
```
Any environment variables supported by InvokeAI can be set here - please see the [Configuration docs](https://invoke-ai.github.io/InvokeAI/features/CONFIGURATION/) for further detail.

11
docker/build.sh Executable file
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@ -0,0 +1,11 @@
#!/usr/bin/env bash
set -e
build_args=""
[[ -f ".env" ]] && build_args=$(awk '$1 ~ /\=[^$]/ {print "--build-arg " $0 " "}' .env)
echo "docker compose build args:"
echo $build_args
docker compose build $build_args

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@ -2,8 +2,23 @@
version: '3.8'
x-invokeai: &invokeai
services:
invokeai:
image: "local/invokeai:latest"
# edit below to run on a container runtime other than nvidia-container-runtime.
# not yet tested with rocm/AMD GPUs
# Comment out the "deploy" section to run on CPU only
deploy:
resources:
reservations:
devices:
- driver: nvidia
count: 1
capabilities: [gpu]
# For AMD support, comment out the deploy section above and uncomment the devices section below:
#devices:
# - /dev/kfd:/dev/kfd
# - /dev/dri:/dev/dri
build:
context: ..
dockerfile: docker/Dockerfile
@ -21,9 +36,7 @@ x-invokeai: &invokeai
ports:
- "${INVOKEAI_PORT:-9090}:9090"
volumes:
- type: bind
source: ${HOST_INVOKEAI_ROOT:-${INVOKEAI_ROOT:-~/invokeai}}
target: ${INVOKEAI_ROOT:-/invokeai}
- ${INVOKEAI_ROOT:-~/invokeai}:${INVOKEAI_ROOT:-/invokeai}
- ${HF_HOME:-~/.cache/huggingface}:${HF_HOME:-/invokeai/.cache/huggingface}
# - ${INVOKEAI_MODELS_DIR:-${INVOKEAI_ROOT:-/invokeai/models}}
# - ${INVOKEAI_MODELS_CONFIG_PATH:-${INVOKEAI_ROOT:-/invokeai/configs/models.yaml}}
@ -37,27 +50,3 @@ x-invokeai: &invokeai
# - |
# invokeai-model-install --yes --default-only --config_file ${INVOKEAI_ROOT}/config_custom.yaml
# invokeai-nodes-web --host 0.0.0.0
services:
invokeai-nvidia:
<<: *invokeai
deploy:
resources:
reservations:
devices:
- driver: nvidia
count: 1
capabilities: [gpu]
invokeai-cpu:
<<: *invokeai
profiles:
- cpu
invokeai-rocm:
<<: *invokeai
devices:
- /dev/kfd:/dev/kfd
- /dev/dri:/dev/dri
profiles:
- rocm

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@ -1,32 +1,11 @@
#!/usr/bin/env bash
set -e -o pipefail
set -e
run() {
local scriptdir=$(dirname "${BASH_SOURCE[0]}")
cd "$scriptdir" || exit 1
# This script is provided for backwards compatibility with the old docker setup.
# it doesn't do much aside from wrapping the usual docker compose CLI.
local build_args=""
local profile=""
SCRIPTDIR=$(dirname "${BASH_SOURCE[0]}")
cd "$SCRIPTDIR" || exit 1
touch .env
build_args=$(awk '$1 ~ /=[^$]/ && $0 !~ /^#/ {print "--build-arg " $0 " "}' .env) &&
profile="$(awk -F '=' '/GPU_DRIVER/ {print $2}' .env)"
[[ -z "$profile" ]] && profile="nvidia"
local service_name="invokeai-$profile"
if [[ ! -z "$build_args" ]]; then
printf "%s\n" "docker compose build args:"
printf "%s\n" "$build_args"
fi
docker compose build $build_args
unset build_args
printf "%s\n" "starting service $service_name"
docker compose --profile "$profile" up -d "$service_name"
docker compose logs -f
}
run
docker compose up -d
docker compose logs -f

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@ -1,277 +0,0 @@
# The InvokeAI Download Queue
The DownloadQueueService provides a multithreaded parallel download
queue for arbitrary URLs, with queue prioritization, event handling,
and restart capabilities.
## Simple Example
```
from invokeai.app.services.download import DownloadQueueService, TqdmProgress
download_queue = DownloadQueueService()
for url in ['https://github.com/invoke-ai/InvokeAI/blob/main/invokeai/assets/a-painting-of-a-fire.png?raw=true',
'https://github.com/invoke-ai/InvokeAI/blob/main/invokeai/assets/birdhouse.png?raw=true',
'https://github.com/invoke-ai/InvokeAI/blob/main/invokeai/assets/missing.png',
'https://civitai.com/api/download/models/152309?type=Model&format=SafeTensor',
]:
# urls start downloading as soon as download() is called
download_queue.download(source=url,
dest='/tmp/downloads',
on_progress=TqdmProgress().update
)
download_queue.join() # wait for all downloads to finish
for job in download_queue.list_jobs():
print(job.model_dump_json(exclude_none=True, indent=4),"\n")
```
Output:
```
{
"source": "https://github.com/invoke-ai/InvokeAI/blob/main/invokeai/assets/a-painting-of-a-fire.png?raw=true",
"dest": "/tmp/downloads",
"id": 0,
"priority": 10,
"status": "completed",
"download_path": "/tmp/downloads/a-painting-of-a-fire.png",
"job_started": "2023-12-04T05:34:41.742174",
"job_ended": "2023-12-04T05:34:42.592035",
"bytes": 666734,
"total_bytes": 666734
}
{
"source": "https://github.com/invoke-ai/InvokeAI/blob/main/invokeai/assets/birdhouse.png?raw=true",
"dest": "/tmp/downloads",
"id": 1,
"priority": 10,
"status": "completed",
"download_path": "/tmp/downloads/birdhouse.png",
"job_started": "2023-12-04T05:34:41.741975",
"job_ended": "2023-12-04T05:34:42.652841",
"bytes": 774949,
"total_bytes": 774949
}
{
"source": "https://github.com/invoke-ai/InvokeAI/blob/main/invokeai/assets/missing.png",
"dest": "/tmp/downloads",
"id": 2,
"priority": 10,
"status": "error",
"job_started": "2023-12-04T05:34:41.742079",
"job_ended": "2023-12-04T05:34:42.147625",
"bytes": 0,
"total_bytes": 0,
"error_type": "HTTPError(Not Found)",
"error": "Traceback (most recent call last):\n File \"/home/lstein/Projects/InvokeAI/invokeai/app/services/download/download_default.py\", line 182, in _download_next_item\n self._do_download(job)\n File \"/home/lstein/Projects/InvokeAI/invokeai/app/services/download/download_default.py\", line 206, in _do_download\n raise HTTPError(resp.reason)\nrequests.exceptions.HTTPError: Not Found\n"
}
{
"source": "https://civitai.com/api/download/models/152309?type=Model&format=SafeTensor",
"dest": "/tmp/downloads",
"id": 3,
"priority": 10,
"status": "completed",
"download_path": "/tmp/downloads/xl_more_art-full_v1.safetensors",
"job_started": "2023-12-04T05:34:42.147645",
"job_ended": "2023-12-04T05:34:43.735990",
"bytes": 719020768,
"total_bytes": 719020768
}
```
## The API
The default download queue is `DownloadQueueService`, an
implementation of ABC `DownloadQueueServiceBase`. It juggles multiple
background download requests and provides facilities for interrogating
and cancelling the requests. Access to a current or past download task
is mediated via `DownloadJob` objects which report the current status
of a job request
### The Queue Object
A default download queue is located in
`ApiDependencies.invoker.services.download_queue`. However, you can
create additional instances if you need to isolate your queue from the
main one.
```
queue = DownloadQueueService(event_bus=events)
```
`DownloadQueueService()` takes three optional arguments:
| **Argument** | **Type** | **Default** | **Description** |
|----------------|-----------------|---------------|-----------------|
| `max_parallel_dl` | int | 5 | Maximum number of simultaneous downloads allowed |
| `event_bus` | EventServiceBase | None | System-wide FastAPI event bus for reporting download events |
| `requests_session` | requests.sessions.Session | None | An alternative requests Session object to use for the download |
`max_parallel_dl` specifies how many download jobs are allowed to run
simultaneously. Each will run in a different thread of execution.
`event_bus` is an EventServiceBase, typically the one created at
InvokeAI startup. If present, download events are periodically emitted
on this bus to allow clients to follow download progress.
`requests_session` is a url library requests Session object. It is
used for testing.
### The Job object
The queue operates on a series of download job objects. These objects
specify the source and destination of the download, and keep track of
the progress of the download.
The only job type currently implemented is `DownloadJob`, a pydantic object with the
following fields:
| **Field** | **Type** | **Default** | **Description** |
|----------------|-----------------|---------------|-----------------|
| _Fields passed in at job creation time_ |
| `source` | AnyHttpUrl | | Where to download from |
| `dest` | Path | | Where to download to |
| `access_token` | str | | [optional] string containing authentication token for access |
| `on_start` | Callable | | [optional] callback when the download starts |
| `on_progress` | Callable | | [optional] callback called at intervals during download progress |
| `on_complete` | Callable | | [optional] callback called after successful download completion |
| `on_error` | Callable | | [optional] callback called after an error occurs |
| `id` | int | auto assigned | Job ID, an integer >= 0 |
| `priority` | int | 10 | Job priority. Lower priorities run before higher priorities |
| |
| _Fields updated over the course of the download task_
| `status` | DownloadJobStatus| | Status code |
| `download_path` | Path | | Path to the location of the downloaded file |
| `job_started` | float | | Timestamp for when the job started running |
| `job_ended` | float | | Timestamp for when the job completed or errored out |
| `job_sequence` | int | | A counter that is incremented each time a model is dequeued |
| `bytes` | int | 0 | Bytes downloaded so far |
| `total_bytes` | int | 0 | Total size of the file at the remote site |
| `error_type` | str | | String version of the exception that caused an error during download |
| `error` | str | | String version of the traceback associated with an error |
| `cancelled` | bool | False | Set to true if the job was cancelled by the caller|
When you create a job, you can assign it a `priority`. If multiple
jobs are queued, the job with the lowest priority runs first.
Every job has a `source` and a `dest`. `source` is a pydantic.networks AnyHttpUrl object.
The `dest` is a path on the local filesystem that specifies the
destination for the downloaded object. Its semantics are
described below.
When the job is submitted, it is assigned a numeric `id`. The id can
then be used to fetch the job object from the queue.
The `status` field is updated by the queue to indicate where the job
is in its lifecycle. Values are defined in the string enum
`DownloadJobStatus`, a symbol available from
`invokeai.app.services.download_manager`. Possible values are:
| **Value** | **String Value** | ** Description ** |
|--------------|---------------------|-------------------|
| `WAITING` | waiting | Job is on the queue but not yet running|
| `RUNNING` | running | The download is started |
| `COMPLETED` | completed | Job has finished its work without an error |
| `ERROR` | error | Job encountered an error and will not run again|
`job_started` and `job_ended` indicate when the job
was started (using a python timestamp) and when it completed.
In case of an error, the job's status will be set to `DownloadJobStatus.ERROR`, the text of the
Exception that caused the error will be placed in the `error_type`
field and the traceback that led to the error will be in `error`.
A cancelled job will have status `DownloadJobStatus.ERROR` and an
`error_type` field of "DownloadJobCancelledException". In addition,
the job's `cancelled` property will be set to True.
### Callbacks
Download jobs can be associated with a series of callbacks, each with
the signature `Callable[["DownloadJob"], None]`. The callbacks are assigned
using optional arguments `on_start`, `on_progress`, `on_complete` and
`on_error`. When the corresponding event occurs, the callback wil be
invoked and passed the job. The callback will be run in a `try:`
context in the same thread as the download job. Any exceptions that
occur during execution of the callback will be caught and converted
into a log error message, thereby allowing the download to continue.
#### `TqdmProgress`
The `invokeai.app.services.download.download_default` module defines a
class named `TqdmProgress` which can be used as an `on_progress`
handler to display a completion bar in the console. Use as follows:
```
from invokeai.app.services.download import TqdmProgress
download_queue.download(source='http://some.server.somewhere/some_file',
dest='/tmp/downloads',
on_progress=TqdmProgress().update
)
```
### Events
If the queue was initialized with the InvokeAI event bus (the case
when using `ApiDependencies.invoker.services.download_queue`), then
download events will also be issued on the bus. The events are:
* `download_started` -- This is issued when a job is taken off the
queue and a request is made to the remote server for the URL headers, but before any data
has been downloaded. The event payload will contain the keys `source`
and `download_path`. The latter contains the path that the URL will be
downloaded to.
* `download_progress -- This is issued periodically as the download
runs. The payload contains the keys `source`, `download_path`,
`current_bytes` and `total_bytes`. The latter two fields can be
used to display the percent complete.
* `download_complete` -- This is issued when the download completes
successfully. The payload contains the keys `source`, `download_path`
and `total_bytes`.
* `download_error` -- This is issued when the download stops because
of an error condition. The payload contains the fields `error_type`
and `error`. The former is the text representation of the exception,
and the latter is a traceback showing where the error occurred.
### Job control
To create a job call the queue's `download()` method. You can list all
jobs using `list_jobs()`, fetch a single job by its with
`id_to_job()`, cancel a running job with `cancel_job()`, cancel all
running jobs with `cancel_all_jobs()`, and wait for all jobs to finish
with `join()`.
#### job = queue.download(source, dest, priority, access_token)
Create a new download job and put it on the queue, returning the
DownloadJob object.
#### jobs = queue.list_jobs()
Return a list of all active and inactive `DownloadJob`s.
#### job = queue.id_to_job(id)
Return the job corresponding to given ID.
Return a list of all active and inactive `DownloadJob`s.
#### queue.prune_jobs()
Remove inactive (complete or errored) jobs from the listing returned
by `list_jobs()`.
#### queue.join()
Block until all pending jobs have run to completion or errored out.

View File

@ -46,18 +46,17 @@ We encourage you to ping @psychedelicious and @blessedcoolant on [Discord](http
```bash
node --version
```
2. Install [pnpm](https://pnpm.io/) and confirm it is installed by running this:
2. Install [yarn classic](https://classic.yarnpkg.com/lang/en/) and confirm it is installed by running this:
```bash
npm install --global pnpm
pnpm --version
npm install --global yarn
yarn --version
```
From `invokeai/frontend/web/` run `pnpm install` to get everything set up.
From `invokeai/frontend/web/` run `yarn install` to get everything set up.
Start everything in dev mode:
1. Ensure your virtual environment is running
2. Start the dev server: `pnpm dev`
2. Start the dev server: `yarn dev`
3. Start the InvokeAI Nodes backend: `python scripts/invokeai-web.py # run from the repo root`
4. Point your browser to the dev server address e.g. [http://localhost:5173/](http://localhost:5173/)
@ -73,4 +72,4 @@ For a number of technical and logistical reasons, we need to commit UI build art
If you submit a PR, there is a good chance we will ask you to include a separate commit with a build of the app.
To build for production, run `pnpm build`.
To build for production, run `yarn build`.

View File

@ -1,10 +1,10 @@
document.addEventListener("DOMContentLoaded", function () {
var script = document.createElement("script");
script.src = "https://widget.kapa.ai/kapa-widget.bundle.js";
script.setAttribute("data-website-id", "b5973bb1-476b-451e-8cf4-98de86745a10");
script.setAttribute("data-project-name", "Invoke.AI");
script.setAttribute("data-project-color", "#11213C");
script.setAttribute("data-project-logo", "https://avatars.githubusercontent.com/u/113954515?s=280&v=4");
script.async = true;
document.head.appendChild(script);
});
document.addEventListener("DOMContentLoaded", function () {
var script = document.createElement("script");
script.src = "https://widget.kapa.ai/kapa-widget.bundle.js";
script.setAttribute("data-website-id", "b5973bb1-476b-451e-8cf4-98de86745a10");
script.setAttribute("data-project-name", "Invoke.AI");
script.setAttribute("data-project-color", "#11213C");
script.setAttribute("data-project-logo", "https://avatars.githubusercontent.com/u/113954515?s=280&v=4");
script.async = true;
document.head.appendChild(script);
});

View File

@ -13,7 +13,6 @@ If you'd prefer, you can also just download the whole node folder from the linke
To use a community workflow, download the the `.json` node graph file and load it into Invoke AI via the **Load Workflow** button in the Workflow Editor.
- Community Nodes
+ [Adapters-Linked](#adapters-linked-nodes)
+ [Average Images](#average-images)
+ [Clean Image Artifacts After Cut](#clean-image-artifacts-after-cut)
+ [Close Color Mask](#close-color-mask)
@ -33,11 +32,9 @@ To use a community workflow, download the the `.json` node graph file and load i
+ [Image Resize Plus](#image-resize-plus)
+ [Load Video Frame](#load-video-frame)
+ [Make 3D](#make-3d)
+ [Mask Operations](#mask-operations)
+ [Mask Operations](#mask-operations)
+ [Match Histogram](#match-histogram)
+ [Metadata-Linked](#metadata-linked-nodes)
+ [Negative Image](#negative-image)
+ [Nightmare Promptgen](#nightmare-promptgen)
+ [Negative Image](#negative-image)
+ [Oobabooga](#oobabooga)
+ [Prompt Tools](#prompt-tools)
+ [Remote Image](#remote-image)
@ -54,19 +51,6 @@ To use a community workflow, download the the `.json` node graph file and load i
- [Help](#help)
--------------------------------
### Adapters Linked Nodes
**Description:** A set of nodes for linked adapters (ControlNet, IP-Adaptor & T2I-Adapter). This allows multiple adapters to be chained together without using a `collect` node which means it can be used inside an `iterate` node without any collecting on every iteration issues.
- `ControlNet-Linked` - Collects ControlNet info to pass to other nodes.
- `IP-Adapter-Linked` - Collects IP-Adapter info to pass to other nodes.
- `T2I-Adapter-Linked` - Collects T2I-Adapter info to pass to other nodes.
Note: These are inherited from the core nodes so any update to the core nodes should be reflected in these.
**Node Link:** https://github.com/skunkworxdark/adapters-linked-nodes
--------------------------------
### Average Images
@ -323,20 +307,6 @@ See full docs here: https://github.com/skunkworxdark/Prompt-tools-nodes/edit/mai
<img src="https://github.com/skunkworxdark/match_histogram/assets/21961335/ed12f329-a0ef-444a-9bae-129ed60d6097" width="300" />
--------------------------------
### Metadata Linked Nodes
**Description:** A set of nodes for Metadata. Collect Metadata from within an `iterate` node & extract metadata from an image.
- `Metadata Item Linked` - Allows collecting of metadata while within an iterate node with no need for a collect node or conversion to metadata node.
- `Metadata From Image` - Provides Metadata from an image.
- `Metadata To String` - Extracts a String value of a label from metadata.
- `Metadata To Integer` - Extracts an Integer value of a label from metadata.
- `Metadata To Float` - Extracts a Float value of a label from metadata.
- `Metadata To Scheduler` - Extracts a Scheduler value of a label from metadata.
**Node Link:** https://github.com/skunkworxdark/metadata-linked-nodes
--------------------------------
### Negative Image
@ -347,13 +317,6 @@ Node Link: https://github.com/VeyDlin/negative-image-node
View:
</br><img src="https://raw.githubusercontent.com/VeyDlin/negative-image-node/master/.readme/node.png" width="500" />
--------------------------------
### Nightmare Promptgen
**Description:** Nightmare Prompt Generator - Uses a local text generation model to create unique imaginative (but usually nightmarish) prompts for InvokeAI. By default, it allows you to choose from some gpt-neo models I finetuned on over 2500 of my own InvokeAI prompts in Compel format, but you're able to add your own, as well. Offers support for replacing any troublesome words with a random choice from list you can also define.
**Node Link:** [https://github.com/gogurtenjoyer/nightmare-promptgen](https://github.com/gogurtenjoyer/nightmare-promptgen)
--------------------------------
### Oobabooga

File diff suppressed because it is too large Load Diff

File diff suppressed because it is too large Load Diff

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File diff suppressed because it is too large Load Diff

File diff suppressed because it is too large Load Diff

View File

@ -1,8 +1,8 @@
{
"name": "Text to Image - SD1.5",
"name": "Text to Image",
"author": "InvokeAI",
"description": "Sample text to image workflow for Stable Diffusion 1.5/2",
"version": "1.1.0",
"version": "1.0.1",
"contact": "invoke@invoke.ai",
"tags": "text2image, SD1.5, SD2, default",
"notes": "",
@ -18,19 +18,10 @@
{
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"fieldName": "prompt"
},
{
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{
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}
],
"meta": {
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"version": "2.0.0"
"version": "1.0.0"
},
"nodes": [
{
@ -39,56 +30,44 @@
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"label": "Negative Compel Prompt",
"isOpen": true,
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@ -97,60 +76,37 @@
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@ -158,40 +114,35 @@
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@ -200,24 +151,13 @@
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"type": "main_model_loader",
"label": "",
"isOpen": true,
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"base_model": "sd-1",
@ -229,40 +169,35 @@
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@ -271,56 +206,44 @@
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@ -329,36 +252,21 @@
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@ -366,20 +274,23 @@
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@ -388,224 +299,144 @@
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"height": 646,
"position": {
"x": 1400,
"y": 25
"x": 1476.5794704734735,
"y": 256.80174342731783
}
},
{
@ -614,185 +445,153 @@
"data": {
"id": "58c957f5-0d01-41fc-a803-b2bbf0413d4f",
"type": "l2i",
"label": "",
"isOpen": true,
"notes": "",
"isIntermediate": false,
"useCache": true,
"version": "1.2.0",
"nodePack": "invokeai",
"inputs": {
"metadata": {
"id": "ab375f12-0042-4410-9182-29e30db82c85",
"name": "metadata",
"type": "MetadataField",
"fieldKind": "input",
"label": "",
"type": {
"isCollection": false,
"isCollectionOrScalar": false,
"name": "MetadataField"
}
"label": ""
},
"latents": {
"id": "3a7e7efd-bff5-47d7-9d48-615127afee78",
"name": "latents",
"type": "LatentsField",
"fieldKind": "input",
"label": "",
"type": {
"isCollection": false,
"isCollectionOrScalar": false,
"name": "LatentsField"
}
"label": ""
},
"vae": {
"id": "a1f5f7a1-0795-4d58-b036-7820c0b0ef2b",
"name": "vae",
"type": "VaeField",
"fieldKind": "input",
"label": "",
"type": {
"isCollection": false,
"isCollectionOrScalar": false,
"name": "VaeField"
}
"label": ""
},
"tiled": {
"id": "da52059a-0cee-4668-942f-519aa794d739",
"name": "tiled",
"type": "boolean",
"fieldKind": "input",
"label": "",
"type": {
"isCollection": false,
"isCollectionOrScalar": false,
"name": "BooleanField"
},
"value": false
},
"fp32": {
"id": "c4841df3-b24e-4140-be3b-ccd454c2522c",
"name": "fp32",
"type": "boolean",
"fieldKind": "input",
"label": "",
"type": {
"isCollection": false,
"isCollectionOrScalar": false,
"name": "BooleanField"
},
"value": true
"value": false
}
},
"outputs": {
"image": {
"id": "72d667d0-cf85-459d-abf2-28bd8b823fe7",
"name": "image",
"fieldKind": "output",
"type": {
"isCollection": false,
"isCollectionOrScalar": false,
"name": "ImageField"
}
"type": "ImageField",
"fieldKind": "output"
},
"width": {
"id": "c8c907d8-1066-49d1-b9a6-83bdcd53addc",
"name": "width",
"fieldKind": "output",
"type": {
"isCollection": false,
"isCollectionOrScalar": false,
"name": "IntegerField"
}
"type": "integer",
"fieldKind": "output"
},
"height": {
"id": "230f359c-b4ea-436c-b372-332d7dcdca85",
"name": "height",
"fieldKind": "output",
"type": {
"isCollection": false,
"isCollectionOrScalar": false,
"name": "IntegerField"
}
"type": "integer",
"fieldKind": "output"
}
}
},
"label": "",
"isOpen": true,
"notes": "",
"embedWorkflow": false,
"isIntermediate": false,
"useCache": true,
"version": "1.0.0"
},
"width": 320,
"height": 266,
"height": 267,
"position": {
"x": 1800,
"y": 25
"x": 2037.9648469717395,
"y": 426.10844427600136
}
}
],
"edges": [
{
"id": "reactflow__edge-ea94bc37-d995-4a83-aa99-4af42479f2f2value-55705012-79b9-4aac-9f26-c0b10309785bseed",
"source": "ea94bc37-d995-4a83-aa99-4af42479f2f2",
"target": "55705012-79b9-4aac-9f26-c0b10309785b",
"type": "default",
"sourceHandle": "value",
"targetHandle": "seed"
"target": "55705012-79b9-4aac-9f26-c0b10309785b",
"targetHandle": "seed",
"id": "reactflow__edge-ea94bc37-d995-4a83-aa99-4af42479f2f2value-55705012-79b9-4aac-9f26-c0b10309785bseed",
"type": "default"
},
{
"id": "reactflow__edge-c8d55139-f380-4695-b7f2-8b3d1e1e3db8clip-7d8bf987-284f-413a-b2fd-d825445a5d6cclip",
"source": "c8d55139-f380-4695-b7f2-8b3d1e1e3db8",
"sourceHandle": "clip",
"target": "7d8bf987-284f-413a-b2fd-d825445a5d6c",
"type": "default",
"sourceHandle": "clip",
"targetHandle": "clip"
"targetHandle": "clip",
"id": "reactflow__edge-c8d55139-f380-4695-b7f2-8b3d1e1e3db8clip-7d8bf987-284f-413a-b2fd-d825445a5d6cclip",
"type": "default"
},
{
"id": "reactflow__edge-c8d55139-f380-4695-b7f2-8b3d1e1e3db8clip-93dc02a4-d05b-48ed-b99c-c9b616af3402clip",
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"type": "default",
"sourceHandle": "clip",
"targetHandle": "clip"
"targetHandle": "clip",
"id": "reactflow__edge-c8d55139-f380-4695-b7f2-8b3d1e1e3db8clip-93dc02a4-d05b-48ed-b99c-c9b616af3402clip",
"type": "default"
},
{
"id": "reactflow__edge-55705012-79b9-4aac-9f26-c0b10309785bnoise-eea2702a-19fb-45b5-9d75-56b4211ec03cnoise",
"source": "55705012-79b9-4aac-9f26-c0b10309785b",
"target": "eea2702a-19fb-45b5-9d75-56b4211ec03c",
"type": "default",
"sourceHandle": "noise",
"targetHandle": "noise"
"target": "eea2702a-19fb-45b5-9d75-56b4211ec03c",
"targetHandle": "noise",
"id": "reactflow__edge-55705012-79b9-4aac-9f26-c0b10309785bnoise-eea2702a-19fb-45b5-9d75-56b4211ec03cnoise",
"type": "default"
},
{
"id": "reactflow__edge-7d8bf987-284f-413a-b2fd-d825445a5d6cconditioning-eea2702a-19fb-45b5-9d75-56b4211ec03cpositive_conditioning",
"source": "7d8bf987-284f-413a-b2fd-d825445a5d6c",
"target": "eea2702a-19fb-45b5-9d75-56b4211ec03c",
"type": "default",
"sourceHandle": "conditioning",
"targetHandle": "positive_conditioning"
"target": "eea2702a-19fb-45b5-9d75-56b4211ec03c",
"targetHandle": "positive_conditioning",
"id": "reactflow__edge-7d8bf987-284f-413a-b2fd-d825445a5d6cconditioning-eea2702a-19fb-45b5-9d75-56b4211ec03cpositive_conditioning",
"type": "default"
},
{
"id": "reactflow__edge-93dc02a4-d05b-48ed-b99c-c9b616af3402conditioning-eea2702a-19fb-45b5-9d75-56b4211ec03cnegative_conditioning",
"source": "93dc02a4-d05b-48ed-b99c-c9b616af3402",
"target": "eea2702a-19fb-45b5-9d75-56b4211ec03c",
"type": "default",
"sourceHandle": "conditioning",
"targetHandle": "negative_conditioning"
},
{
"id": "reactflow__edge-c8d55139-f380-4695-b7f2-8b3d1e1e3db8unet-eea2702a-19fb-45b5-9d75-56b4211ec03cunet",
"source": "c8d55139-f380-4695-b7f2-8b3d1e1e3db8",
"target": "eea2702a-19fb-45b5-9d75-56b4211ec03c",
"type": "default",
"sourceHandle": "unet",
"targetHandle": "unet"
"targetHandle": "negative_conditioning",
"id": "reactflow__edge-93dc02a4-d05b-48ed-b99c-c9b616af3402conditioning-eea2702a-19fb-45b5-9d75-56b4211ec03cnegative_conditioning",
"type": "default"
},
{
"id": "reactflow__edge-eea2702a-19fb-45b5-9d75-56b4211ec03clatents-58c957f5-0d01-41fc-a803-b2bbf0413d4flatents",
"source": "eea2702a-19fb-45b5-9d75-56b4211ec03c",
"target": "58c957f5-0d01-41fc-a803-b2bbf0413d4f",
"type": "default",
"sourceHandle": "latents",
"targetHandle": "latents"
},
{
"id": "reactflow__edge-c8d55139-f380-4695-b7f2-8b3d1e1e3db8vae-58c957f5-0d01-41fc-a803-b2bbf0413d4fvae",
"source": "c8d55139-f380-4695-b7f2-8b3d1e1e3db8",
"sourceHandle": "unet",
"target": "eea2702a-19fb-45b5-9d75-56b4211ec03c",
"targetHandle": "unet",
"id": "reactflow__edge-c8d55139-f380-4695-b7f2-8b3d1e1e3db8unet-eea2702a-19fb-45b5-9d75-56b4211ec03cunet",
"type": "default"
},
{
"source": "eea2702a-19fb-45b5-9d75-56b4211ec03c",
"sourceHandle": "latents",
"target": "58c957f5-0d01-41fc-a803-b2bbf0413d4f",
"type": "default",
"targetHandle": "latents",
"id": "reactflow__edge-eea2702a-19fb-45b5-9d75-56b4211ec03clatents-58c957f5-0d01-41fc-a803-b2bbf0413d4flatents",
"type": "default"
},
{
"source": "c8d55139-f380-4695-b7f2-8b3d1e1e3db8",
"sourceHandle": "vae",
"targetHandle": "vae"
"target": "58c957f5-0d01-41fc-a803-b2bbf0413d4f",
"targetHandle": "vae",
"id": "reactflow__edge-c8d55139-f380-4695-b7f2-8b3d1e1e3db8vae-58c957f5-0d01-41fc-a803-b2bbf0413d4fvae",
"type": "default"
}
]
}
}

View File

@ -91,11 +91,9 @@ rm -rf InvokeAI-Installer
# copy content
mkdir InvokeAI-Installer
for f in templates *.txt *.reg; do
for f in templates lib *.txt *.reg; do
cp -r ${f} InvokeAI-Installer/
done
mkdir InvokeAI-Installer/lib
cp lib/*.py InvokeAI-Installer/lib
# Move the wheel
mv dist/*.whl InvokeAI-Installer/lib/
@ -113,6 +111,6 @@ cp WinLongPathsEnabled.reg InvokeAI-Installer/
zip -r InvokeAI-installer-$VERSION.zip InvokeAI-Installer
# clean up
rm -rf InvokeAI-Installer tmp dist ../invokeai/frontend/web/dist/
rm -rf InvokeAI-Installer tmp dist
exit 0

View File

@ -241,12 +241,12 @@ class InvokeAiInstance:
pip[
"install",
"--require-virtualenv",
"numpy==1.26.3", # choose versions that won't be uninstalled during phase 2
"numpy~=1.24.0", # choose versions that won't be uninstalled during phase 2
"urllib3~=1.26.0",
"requests~=2.28.0",
"torch==2.1.2",
"torch==2.1.1",
"torchmetrics==0.11.4",
"torchvision==0.16.2",
"torchvision>=0.16.1",
"--force-reinstall",
"--find-links" if find_links is not None else None,
find_links,

View File

@ -11,7 +11,6 @@ from ..services.board_images.board_images_default import BoardImagesService
from ..services.board_records.board_records_sqlite import SqliteBoardRecordStorage
from ..services.boards.boards_default import BoardService
from ..services.config import InvokeAIAppConfig
from ..services.download import DownloadQueueService
from ..services.image_files.image_files_disk import DiskImageFileStorage
from ..services.image_records.image_records_sqlite import SqliteImageRecordStorage
from ..services.images.images_default import ImageService
@ -30,7 +29,8 @@ from ..services.model_records import ModelRecordServiceSQL
from ..services.names.names_default import SimpleNameService
from ..services.session_processor.session_processor_default import DefaultSessionProcessor
from ..services.session_queue.session_queue_sqlite import SqliteSessionQueue
from ..services.shared.graph import GraphExecutionState
from ..services.shared.default_graphs import create_system_graphs
from ..services.shared.graph import GraphExecutionState, LibraryGraph
from ..services.urls.urls_default import LocalUrlService
from ..services.workflow_records.workflow_records_sqlite import SqliteWorkflowRecordsStorage
from .events import FastAPIEventService
@ -80,13 +80,13 @@ class ApiDependencies:
boards = BoardService()
events = FastAPIEventService(event_handler_id)
graph_execution_manager = SqliteItemStorage[GraphExecutionState](db=db, table_name="graph_executions")
graph_library = SqliteItemStorage[LibraryGraph](db=db, table_name="graphs")
image_records = SqliteImageRecordStorage(db=db)
images = ImageService()
invocation_cache = MemoryInvocationCache(max_cache_size=config.node_cache_size)
latents = ForwardCacheLatentsStorage(DiskLatentsStorage(f"{output_folder}/latents"))
model_manager = ModelManagerService(config, logger)
model_record_service = ModelRecordServiceSQL(db=db)
download_queue_service = DownloadQueueService(event_bus=events)
model_install_service = ModelInstallService(
app_config=config, record_store=model_record_service, event_bus=events
)
@ -107,6 +107,7 @@ class ApiDependencies:
configuration=configuration,
events=events,
graph_execution_manager=graph_execution_manager,
graph_library=graph_library,
image_files=image_files,
image_records=image_records,
images=images,
@ -115,7 +116,6 @@ class ApiDependencies:
logger=logger,
model_manager=model_manager,
model_records=model_record_service,
download_queue=download_queue_service,
model_install=model_install_service,
names=names,
performance_statistics=performance_statistics,
@ -127,6 +127,8 @@ class ApiDependencies:
workflow_records=workflow_records,
)
create_system_graphs(services.graph_library)
ApiDependencies.invoker = Invoker(services)
db.clean()

View File

@ -1,111 +0,0 @@
# Copyright (c) 2023 Lincoln D. Stein
"""FastAPI route for the download queue."""
from typing import List, Optional
from fastapi import Body, Path, Response
from fastapi.routing import APIRouter
from pydantic.networks import AnyHttpUrl
from starlette.exceptions import HTTPException
from invokeai.app.services.download import (
DownloadJob,
UnknownJobIDException,
)
from ..dependencies import ApiDependencies
download_queue_router = APIRouter(prefix="/v1/download_queue", tags=["download_queue"])
@download_queue_router.get(
"/",
operation_id="list_downloads",
)
async def list_downloads() -> List[DownloadJob]:
"""Get a list of active and inactive jobs."""
queue = ApiDependencies.invoker.services.download_queue
return queue.list_jobs()
@download_queue_router.patch(
"/",
operation_id="prune_downloads",
responses={
204: {"description": "All completed jobs have been pruned"},
400: {"description": "Bad request"},
},
)
async def prune_downloads():
"""Prune completed and errored jobs."""
queue = ApiDependencies.invoker.services.download_queue
queue.prune_jobs()
return Response(status_code=204)
@download_queue_router.post(
"/i/",
operation_id="download",
)
async def download(
source: AnyHttpUrl = Body(description="download source"),
dest: str = Body(description="download destination"),
priority: int = Body(default=10, description="queue priority"),
access_token: Optional[str] = Body(default=None, description="token for authorization to download"),
) -> DownloadJob:
"""Download the source URL to the file or directory indicted in dest."""
queue = ApiDependencies.invoker.services.download_queue
return queue.download(source, dest, priority, access_token)
@download_queue_router.get(
"/i/{id}",
operation_id="get_download_job",
responses={
200: {"description": "Success"},
404: {"description": "The requested download JobID could not be found"},
},
)
async def get_download_job(
id: int = Path(description="ID of the download job to fetch."),
) -> DownloadJob:
"""Get a download job using its ID."""
try:
job = ApiDependencies.invoker.services.download_queue.id_to_job(id)
return job
except UnknownJobIDException as e:
raise HTTPException(status_code=404, detail=str(e))
@download_queue_router.delete(
"/i/{id}",
operation_id="cancel_download_job",
responses={
204: {"description": "Job has been cancelled"},
404: {"description": "The requested download JobID could not be found"},
},
)
async def cancel_download_job(
id: int = Path(description="ID of the download job to cancel."),
):
"""Cancel a download job using its ID."""
try:
queue = ApiDependencies.invoker.services.download_queue
job = queue.id_to_job(id)
queue.cancel_job(job)
return Response(status_code=204)
except UnknownJobIDException as e:
raise HTTPException(status_code=404, detail=str(e))
@download_queue_router.delete(
"/i",
operation_id="cancel_all_download_jobs",
responses={
204: {"description": "Download jobs have been cancelled"},
},
)
async def cancel_all_download_jobs():
"""Cancel all download jobs."""
ApiDependencies.invoker.services.download_queue.cancel_all_jobs()
return Response(status_code=204)

View File

@ -26,7 +26,7 @@ from invokeai.backend.model_manager.config import (
from ..dependencies import ApiDependencies
model_records_router = APIRouter(prefix="/v1/model/record", tags=["model_manager_v2_unstable"])
model_records_router = APIRouter(prefix="/v1/model/record", tags=["model_manager_v2"])
class ModelsList(BaseModel):

View File

@ -23,11 +23,10 @@ class DynamicPromptsResponse(BaseModel):
)
async def parse_dynamicprompts(
prompt: str = Body(description="The prompt to parse with dynamicprompts"),
max_prompts: int = Body(ge=1, le=10000, default=1000, description="The max number of prompts to generate"),
max_prompts: int = Body(default=1000, description="The max number of prompts to generate"),
combinatorial: bool = Body(default=True, description="Whether to use the combinatorial generator"),
) -> DynamicPromptsResponse:
"""Creates a batch process"""
max_prompts = min(max_prompts, 10000)
generator: Union[RandomPromptGenerator, CombinatorialPromptGenerator]
try:
error: Optional[str] = None

View File

@ -45,7 +45,6 @@ if True: # hack to make flake8 happy with imports coming after setting up the c
app_info,
board_images,
boards,
download_queue,
images,
model_records,
models,
@ -117,7 +116,6 @@ app.include_router(sessions.session_router, prefix="/api")
app.include_router(utilities.utilities_router, prefix="/api")
app.include_router(models.models_router, prefix="/api")
app.include_router(model_records.model_records_router, prefix="/api")
app.include_router(download_queue.download_queue_router, prefix="/api")
app.include_router(images.images_router, prefix="/api")
app.include_router(boards.boards_router, prefix="/api")
app.include_router(board_images.board_images_router, prefix="/api")

View File

@ -1,3 +1,4 @@
import re
from dataclasses import dataclass
from typing import List, Optional, Union
@ -16,7 +17,6 @@ from invokeai.backend.stable_diffusion.diffusion.conditioning_data import (
from ...backend.model_management.lora import ModelPatcher
from ...backend.model_management.models import ModelNotFoundException, ModelType
from ...backend.util.devices import torch_dtype
from ..util.ti_utils import extract_ti_triggers_from_prompt
from .baseinvocation import (
BaseInvocation,
BaseInvocationOutput,
@ -87,7 +87,7 @@ class CompelInvocation(BaseInvocation):
# loras = [(context.services.model_manager.get_model(**lora.dict(exclude={"weight"})).context.model, lora.weight) for lora in self.clip.loras]
ti_list = []
for trigger in extract_ti_triggers_from_prompt(self.prompt):
for trigger in re.findall(r"<[a-zA-Z0-9., _-]+>", self.prompt):
name = trigger[1:-1]
try:
ti_list.append(
@ -210,7 +210,7 @@ class SDXLPromptInvocationBase:
# loras = [(context.services.model_manager.get_model(**lora.dict(exclude={"weight"})).context.model, lora.weight) for lora in self.clip.loras]
ti_list = []
for trigger in extract_ti_triggers_from_prompt(prompt):
for trigger in re.findall(r"<[a-zA-Z0-9., _-]+>", prompt):
name = trigger[1:-1]
try:
ti_list.append(

View File

@ -24,10 +24,9 @@ from controlnet_aux import (
)
from controlnet_aux.util import HWC3, ade_palette
from PIL import Image
from pydantic import BaseModel, ConfigDict, Field, field_validator, model_validator
from pydantic import BaseModel, ConfigDict, Field, field_validator
from invokeai.app.invocations.primitives import ImageField, ImageOutput
from invokeai.app.invocations.util import validate_begin_end_step, validate_weights
from invokeai.app.services.image_records.image_records_common import ImageCategory, ResourceOrigin
from invokeai.app.shared.fields import FieldDescriptions
@ -76,16 +75,17 @@ class ControlField(BaseModel):
resize_mode: CONTROLNET_RESIZE_VALUES = Field(default="just_resize", description="The resize mode to use")
@field_validator("control_weight")
@classmethod
def validate_control_weight(cls, v):
validate_weights(v)
"""Validate that all control weights in the valid range"""
if isinstance(v, list):
for i in v:
if i < -1 or i > 2:
raise ValueError("Control weights must be within -1 to 2 range")
else:
if v < -1 or v > 2:
raise ValueError("Control weights must be within -1 to 2 range")
return v
@model_validator(mode="after")
def validate_begin_end_step_percent(self):
validate_begin_end_step(self.begin_step_percent, self.end_step_percent)
return self
@invocation_output("control_output")
class ControlOutput(BaseInvocationOutput):
@ -95,17 +95,17 @@ class ControlOutput(BaseInvocationOutput):
control: ControlField = OutputField(description=FieldDescriptions.control)
@invocation("controlnet", title="ControlNet", tags=["controlnet"], category="controlnet", version="1.1.1")
@invocation("controlnet", title="ControlNet", tags=["controlnet"], category="controlnet", version="1.1.0")
class ControlNetInvocation(BaseInvocation):
"""Collects ControlNet info to pass to other nodes"""
image: ImageField = InputField(description="The control image")
control_model: ControlNetModelField = InputField(description=FieldDescriptions.controlnet_model, input=Input.Direct)
control_weight: Union[float, List[float]] = InputField(
default=1.0, ge=-1, le=2, description="The weight given to the ControlNet"
default=1.0, description="The weight given to the ControlNet"
)
begin_step_percent: float = InputField(
default=0, ge=0, le=1, description="When the ControlNet is first applied (% of total steps)"
default=0, ge=-1, le=2, description="When the ControlNet is first applied (% of total steps)"
)
end_step_percent: float = InputField(
default=1, ge=0, le=1, description="When the ControlNet is last applied (% of total steps)"
@ -113,17 +113,6 @@ class ControlNetInvocation(BaseInvocation):
control_mode: CONTROLNET_MODE_VALUES = InputField(default="balanced", description="The control mode used")
resize_mode: CONTROLNET_RESIZE_VALUES = InputField(default="just_resize", description="The resize mode used")
@field_validator("control_weight")
@classmethod
def validate_control_weight(cls, v):
validate_weights(v)
return v
@model_validator(mode="after")
def validate_begin_end_step_percent(self) -> "ControlNetInvocation":
validate_begin_end_step(self.begin_step_percent, self.end_step_percent)
return self
def invoke(self, context: InvocationContext) -> ControlOutput:
return ControlOutput(
control=ControlField(

View File

@ -2,7 +2,7 @@ import os
from builtins import float
from typing import List, Union
from pydantic import BaseModel, ConfigDict, Field, field_validator, model_validator
from pydantic import BaseModel, ConfigDict, Field
from invokeai.app.invocations.baseinvocation import (
BaseInvocation,
@ -15,7 +15,6 @@ from invokeai.app.invocations.baseinvocation import (
invocation_output,
)
from invokeai.app.invocations.primitives import ImageField
from invokeai.app.invocations.util import validate_begin_end_step, validate_weights
from invokeai.app.shared.fields import FieldDescriptions
from invokeai.backend.model_management.models.base import BaseModelType, ModelType
from invokeai.backend.model_management.models.ip_adapter import get_ip_adapter_image_encoder_model_id
@ -40,6 +39,7 @@ class IPAdapterField(BaseModel):
ip_adapter_model: IPAdapterModelField = Field(description="The IP-Adapter model to use.")
image_encoder_model: CLIPVisionModelField = Field(description="The name of the CLIP image encoder model.")
weight: Union[float, List[float]] = Field(default=1, description="The weight given to the ControlNet")
# weight: float = Field(default=1.0, ge=0, description="The weight of the IP-Adapter.")
begin_step_percent: float = Field(
default=0, ge=0, le=1, description="When the IP-Adapter is first applied (% of total steps)"
)
@ -47,17 +47,6 @@ class IPAdapterField(BaseModel):
default=1, ge=0, le=1, description="When the IP-Adapter is last applied (% of total steps)"
)
@field_validator("weight")
@classmethod
def validate_ip_adapter_weight(cls, v):
validate_weights(v)
return v
@model_validator(mode="after")
def validate_begin_end_step_percent(self):
validate_begin_end_step(self.begin_step_percent, self.end_step_percent)
return self
@invocation_output("ip_adapter_output")
class IPAdapterOutput(BaseInvocationOutput):
@ -65,7 +54,7 @@ class IPAdapterOutput(BaseInvocationOutput):
ip_adapter: IPAdapterField = OutputField(description=FieldDescriptions.ip_adapter, title="IP-Adapter")
@invocation("ip_adapter", title="IP-Adapter", tags=["ip_adapter", "control"], category="ip_adapter", version="1.1.1")
@invocation("ip_adapter", title="IP-Adapter", tags=["ip_adapter", "control"], category="ip_adapter", version="1.1.0")
class IPAdapterInvocation(BaseInvocation):
"""Collects IP-Adapter info to pass to other nodes."""
@ -75,27 +64,18 @@ class IPAdapterInvocation(BaseInvocation):
description="The IP-Adapter model.", title="IP-Adapter Model", input=Input.Direct, ui_order=-1
)
# weight: float = InputField(default=1.0, description="The weight of the IP-Adapter.", ui_type=UIType.Float)
weight: Union[float, List[float]] = InputField(
default=1, description="The weight given to the IP-Adapter", title="Weight"
default=1, ge=-1, description="The weight given to the IP-Adapter", title="Weight"
)
begin_step_percent: float = InputField(
default=0, ge=0, le=1, description="When the IP-Adapter is first applied (% of total steps)"
default=0, ge=-1, le=2, description="When the IP-Adapter is first applied (% of total steps)"
)
end_step_percent: float = InputField(
default=1, ge=0, le=1, description="When the IP-Adapter is last applied (% of total steps)"
)
@field_validator("weight")
@classmethod
def validate_ip_adapter_weight(cls, v):
validate_weights(v)
return v
@model_validator(mode="after")
def validate_begin_end_step_percent(self):
validate_begin_end_step(self.begin_step_percent, self.end_step_percent)
return self
def invoke(self, context: InvocationContext) -> IPAdapterOutput:
# Lookup the CLIP Vision encoder that is intended to be used with the IP-Adapter model.
ip_adapter_info = context.services.model_manager.model_info(

View File

@ -220,7 +220,7 @@ def get_scheduler(
title="Denoise Latents",
tags=["latents", "denoise", "txt2img", "t2i", "t2l", "img2img", "i2i", "l2l"],
category="latents",
version="1.5.1",
version="1.5.0",
)
class DenoiseLatentsInvocation(BaseInvocation):
"""Denoises noisy latents to decodable images"""
@ -279,7 +279,7 @@ class DenoiseLatentsInvocation(BaseInvocation):
ui_order=7,
)
cfg_rescale_multiplier: float = InputField(
title="CFG Rescale Multiplier", default=0, ge=0, lt=1, description=FieldDescriptions.cfg_rescale_multiplier
default=0, ge=0, lt=1, description=FieldDescriptions.cfg_rescale_multiplier
)
latents: Optional[LatentsField] = InputField(
default=None,

View File

@ -1,6 +1,7 @@
# Copyright (c) 2023 Borisov Sergey (https://github.com/StAlKeR7779)
import inspect
import re
# from contextlib import ExitStack
from typing import List, Literal, Union
@ -20,7 +21,6 @@ from invokeai.backend import BaseModelType, ModelType, SubModelType
from ...backend.model_management import ONNXModelPatcher
from ...backend.stable_diffusion import PipelineIntermediateState
from ...backend.util import choose_torch_device
from ..util.ti_utils import extract_ti_triggers_from_prompt
from .baseinvocation import (
BaseInvocation,
BaseInvocationOutput,
@ -78,7 +78,7 @@ class ONNXPromptInvocation(BaseInvocation):
]
ti_list = []
for trigger in extract_ti_triggers_from_prompt(self.prompt):
for trigger in re.findall(r"<[a-zA-Z0-9., _-]+>", self.prompt):
name = trigger[1:-1]
try:
ti_list.append(

View File

@ -1,6 +1,6 @@
from typing import Union
from pydantic import BaseModel, ConfigDict, Field, field_validator, model_validator
from pydantic import BaseModel, ConfigDict, Field
from invokeai.app.invocations.baseinvocation import (
BaseInvocation,
@ -14,7 +14,6 @@ from invokeai.app.invocations.baseinvocation import (
)
from invokeai.app.invocations.controlnet_image_processors import CONTROLNET_RESIZE_VALUES
from invokeai.app.invocations.primitives import ImageField
from invokeai.app.invocations.util import validate_begin_end_step, validate_weights
from invokeai.app.shared.fields import FieldDescriptions
from invokeai.backend.model_management.models.base import BaseModelType
@ -38,17 +37,6 @@ class T2IAdapterField(BaseModel):
)
resize_mode: CONTROLNET_RESIZE_VALUES = Field(default="just_resize", description="The resize mode to use")
@field_validator("weight")
@classmethod
def validate_ip_adapter_weight(cls, v):
validate_weights(v)
return v
@model_validator(mode="after")
def validate_begin_end_step_percent(self):
validate_begin_end_step(self.begin_step_percent, self.end_step_percent)
return self
@invocation_output("t2i_adapter_output")
class T2IAdapterOutput(BaseInvocationOutput):
@ -56,7 +44,7 @@ class T2IAdapterOutput(BaseInvocationOutput):
@invocation(
"t2i_adapter", title="T2I-Adapter", tags=["t2i_adapter", "control"], category="t2i_adapter", version="1.0.1"
"t2i_adapter", title="T2I-Adapter", tags=["t2i_adapter", "control"], category="t2i_adapter", version="1.0.0"
)
class T2IAdapterInvocation(BaseInvocation):
"""Collects T2I-Adapter info to pass to other nodes."""
@ -73,7 +61,7 @@ class T2IAdapterInvocation(BaseInvocation):
default=1, ge=0, description="The weight given to the T2I-Adapter", title="Weight"
)
begin_step_percent: float = InputField(
default=0, ge=0, le=1, description="When the T2I-Adapter is first applied (% of total steps)"
default=0, ge=-1, le=2, description="When the T2I-Adapter is first applied (% of total steps)"
)
end_step_percent: float = InputField(
default=1, ge=0, le=1, description="When the T2I-Adapter is last applied (% of total steps)"
@ -83,17 +71,6 @@ class T2IAdapterInvocation(BaseInvocation):
description="The resize mode applied to the T2I-Adapter input image so that it matches the target output size.",
)
@field_validator("weight")
@classmethod
def validate_ip_adapter_weight(cls, v):
validate_weights(v)
return v
@model_validator(mode="after")
def validate_begin_end_step_percent(self):
validate_begin_end_step(self.begin_step_percent, self.end_step_percent)
return self
def invoke(self, context: InvocationContext) -> T2IAdapterOutput:
return T2IAdapterOutput(
t2i_adapter=T2IAdapterField(

View File

@ -77,7 +77,7 @@ class CalculateImageTilesInvocation(BaseInvocation):
title="Calculate Image Tiles Even Split",
tags=["tiles"],
category="tiles",
version="1.1.0",
version="1.0.0",
classification=Classification.Beta,
)
class CalculateImageTilesEvenSplitInvocation(BaseInvocation):
@ -97,11 +97,11 @@ class CalculateImageTilesEvenSplitInvocation(BaseInvocation):
ge=1,
description="Number of tiles to divide image into on the y axis",
)
overlap: int = InputField(
default=128,
overlap_fraction: float = InputField(
default=0.25,
ge=0,
multiple_of=8,
description="The overlap, in pixels, between adjacent tiles.",
lt=1,
description="Overlap between adjacent tiles as a fraction of the tile's dimensions (0-1)",
)
def invoke(self, context: InvocationContext) -> CalculateImageTilesOutput:
@ -110,7 +110,7 @@ class CalculateImageTilesEvenSplitInvocation(BaseInvocation):
image_width=self.image_width,
num_tiles_x=self.num_tiles_x,
num_tiles_y=self.num_tiles_y,
overlap=self.overlap,
overlap_fraction=self.overlap_fraction,
)
return CalculateImageTilesOutput(tiles=tiles)

View File

@ -1,14 +0,0 @@
from typing import Union
def validate_weights(weights: Union[float, list[float]]) -> None:
"""Validate that all control weights in the valid range"""
to_validate = weights if isinstance(weights, list) else [weights]
if any(i < -1 or i > 2 for i in to_validate):
raise ValueError("Control weights must be within -1 to 2 range")
def validate_begin_end_step(begin_step_percent: float, end_step_percent: float) -> None:
"""Validate that begin_step_percent is less than end_step_percent"""
if begin_step_percent >= end_step_percent:
raise ValueError("Begin step percent must be less than or equal to end step percent")

View File

@ -356,7 +356,7 @@ class InvokeAIAppConfig(InvokeAISettings):
else:
root = self.find_root().expanduser().absolute()
self.root = root # insulate ourselves from relative paths that may change
return root.resolve()
return root
@property
def root_dir(self) -> Path:

View File

@ -1,12 +0,0 @@
"""Init file for download queue."""
from .download_base import DownloadJob, DownloadJobStatus, DownloadQueueServiceBase, UnknownJobIDException
from .download_default import DownloadQueueService, TqdmProgress
__all__ = [
"DownloadJob",
"DownloadQueueServiceBase",
"DownloadQueueService",
"TqdmProgress",
"DownloadJobStatus",
"UnknownJobIDException",
]

View File

@ -1,217 +0,0 @@
# Copyright (c) 2023 Lincoln D. Stein and the InvokeAI Development Team
"""Model download service."""
from abc import ABC, abstractmethod
from enum import Enum
from functools import total_ordering
from pathlib import Path
from typing import Any, Callable, List, Optional
from pydantic import BaseModel, Field, PrivateAttr
from pydantic.networks import AnyHttpUrl
class DownloadJobStatus(str, Enum):
"""State of a download job."""
WAITING = "waiting" # not enqueued, will not run
RUNNING = "running" # actively downloading
COMPLETED = "completed" # finished running
CANCELLED = "cancelled" # user cancelled
ERROR = "error" # terminated with an error message
class DownloadJobCancelledException(Exception):
"""This exception is raised when a download job is cancelled."""
class UnknownJobIDException(Exception):
"""This exception is raised when an invalid job id is referened."""
class ServiceInactiveException(Exception):
"""This exception is raised when user attempts to initiate a download before the service is started."""
DownloadEventHandler = Callable[["DownloadJob"], None]
@total_ordering
class DownloadJob(BaseModel):
"""Class to monitor and control a model download request."""
# required variables to be passed in on creation
source: AnyHttpUrl = Field(description="Where to download from. Specific types specified in child classes.")
dest: Path = Field(description="Destination of downloaded model on local disk; a directory or file path")
access_token: Optional[str] = Field(default=None, description="authorization token for protected resources")
# automatically assigned on creation
id: int = Field(description="Numeric ID of this job", default=-1) # default id is a sentinel
priority: int = Field(default=10, description="Queue priority; lower values are higher priority")
# set internally during download process
status: DownloadJobStatus = Field(default=DownloadJobStatus.WAITING, description="Status of the download")
download_path: Optional[Path] = Field(default=None, description="Final location of downloaded file")
job_started: Optional[str] = Field(default=None, description="Timestamp for when the download job started")
job_ended: Optional[str] = Field(
default=None, description="Timestamp for when the download job ende1d (completed or errored)"
)
bytes: int = Field(default=0, description="Bytes downloaded so far")
total_bytes: int = Field(default=0, description="Total file size (bytes)")
# set when an error occurs
error_type: Optional[str] = Field(default=None, description="Name of exception that caused an error")
error: Optional[str] = Field(default=None, description="Traceback of the exception that caused an error")
# internal flag
_cancelled: bool = PrivateAttr(default=False)
# optional event handlers passed in on creation
_on_start: Optional[DownloadEventHandler] = PrivateAttr(default=None)
_on_progress: Optional[DownloadEventHandler] = PrivateAttr(default=None)
_on_complete: Optional[DownloadEventHandler] = PrivateAttr(default=None)
_on_cancelled: Optional[DownloadEventHandler] = PrivateAttr(default=None)
_on_error: Optional[DownloadEventHandler] = PrivateAttr(default=None)
def __le__(self, other: "DownloadJob") -> bool:
"""Return True if this job's priority is less than another's."""
return self.priority <= other.priority
def cancel(self) -> None:
"""Call to cancel the job."""
self._cancelled = True
# cancelled and the callbacks are private attributes in order to prevent
# them from being serialized and/or used in the Json Schema
@property
def cancelled(self) -> bool:
"""Call to cancel the job."""
return self._cancelled
@property
def on_start(self) -> Optional[DownloadEventHandler]:
"""Return the on_start event handler."""
return self._on_start
@property
def on_progress(self) -> Optional[DownloadEventHandler]:
"""Return the on_progress event handler."""
return self._on_progress
@property
def on_complete(self) -> Optional[DownloadEventHandler]:
"""Return the on_complete event handler."""
return self._on_complete
@property
def on_error(self) -> Optional[DownloadEventHandler]:
"""Return the on_error event handler."""
return self._on_error
@property
def on_cancelled(self) -> Optional[DownloadEventHandler]:
"""Return the on_cancelled event handler."""
return self._on_cancelled
def set_callbacks(
self,
on_start: Optional[DownloadEventHandler] = None,
on_progress: Optional[DownloadEventHandler] = None,
on_complete: Optional[DownloadEventHandler] = None,
on_cancelled: Optional[DownloadEventHandler] = None,
on_error: Optional[DownloadEventHandler] = None,
) -> None:
"""Set the callbacks for download events."""
self._on_start = on_start
self._on_progress = on_progress
self._on_complete = on_complete
self._on_error = on_error
self._on_cancelled = on_cancelled
class DownloadQueueServiceBase(ABC):
"""Multithreaded queue for downloading models via URL."""
@abstractmethod
def start(self, *args: Any, **kwargs: Any) -> None:
"""Start the download worker threads."""
@abstractmethod
def stop(self, *args: Any, **kwargs: Any) -> None:
"""Stop the download worker threads."""
@abstractmethod
def download(
self,
source: AnyHttpUrl,
dest: Path,
priority: int = 10,
access_token: Optional[str] = None,
on_start: Optional[DownloadEventHandler] = None,
on_progress: Optional[DownloadEventHandler] = None,
on_complete: Optional[DownloadEventHandler] = None,
on_cancelled: Optional[DownloadEventHandler] = None,
on_error: Optional[DownloadEventHandler] = None,
) -> DownloadJob:
"""
Create a download job.
:param source: Source of the download as a URL.
:param dest: Path to download to. See below.
:param on_start, on_progress, on_complete, on_error: Callbacks for the indicated
events.
:returns: A DownloadJob object for monitoring the state of the download.
The `dest` argument is a Path object. Its behavior is:
1. If the path exists and is a directory, then the URL contents will be downloaded
into that directory using the filename indicated in the response's `Content-Disposition` field.
If no content-disposition is present, then the last component of the URL will be used (similar to
wget's behavior).
2. If the path does not exist, then it is taken as the name of a new file to create with the downloaded
content.
3. If the path exists and is an existing file, then the downloader will try to resume the download from
the end of the existing file.
"""
pass
@abstractmethod
def list_jobs(self) -> List[DownloadJob]:
"""
List active download jobs.
:returns List[DownloadJob]: List of download jobs whose state is not "completed."
"""
pass
@abstractmethod
def id_to_job(self, id: int) -> DownloadJob:
"""
Return the DownloadJob corresponding to the integer ID.
:param id: ID of the DownloadJob.
Exceptions:
* UnknownJobIDException
"""
pass
@abstractmethod
def cancel_all_jobs(self):
"""Cancel all active and enquedjobs."""
pass
@abstractmethod
def prune_jobs(self):
"""Prune completed and errored queue items from the job list."""
pass
@abstractmethod
def cancel_job(self, job: DownloadJob):
"""Cancel the job, clearing partial downloads and putting it into ERROR state."""
pass
@abstractmethod
def join(self):
"""Wait until all jobs are off the queue."""
pass

View File

@ -1,418 +0,0 @@
# Copyright (c) 2023, Lincoln D. Stein
"""Implementation of multithreaded download queue for invokeai."""
import os
import re
import threading
import traceback
from logging import Logger
from pathlib import Path
from queue import Empty, PriorityQueue
from typing import Any, Dict, List, Optional, Set
import requests
from pydantic.networks import AnyHttpUrl
from requests import HTTPError
from tqdm import tqdm
from invokeai.app.services.events.events_base import EventServiceBase
from invokeai.app.util.misc import get_iso_timestamp
from invokeai.backend.util.logging import InvokeAILogger
from .download_base import (
DownloadEventHandler,
DownloadJob,
DownloadJobCancelledException,
DownloadJobStatus,
DownloadQueueServiceBase,
ServiceInactiveException,
UnknownJobIDException,
)
# Maximum number of bytes to download during each call to requests.iter_content()
DOWNLOAD_CHUNK_SIZE = 100000
class DownloadQueueService(DownloadQueueServiceBase):
"""Class for queued download of models."""
_jobs: Dict[int, DownloadJob]
_max_parallel_dl: int = 5
_worker_pool: Set[threading.Thread]
_queue: PriorityQueue[DownloadJob]
_stop_event: threading.Event
_lock: threading.Lock
_logger: Logger
_events: Optional[EventServiceBase] = None
_next_job_id: int = 0
_accept_download_requests: bool = False
_requests: requests.sessions.Session
def __init__(
self,
max_parallel_dl: int = 5,
event_bus: Optional[EventServiceBase] = None,
requests_session: Optional[requests.sessions.Session] = None,
):
"""
Initialize DownloadQueue.
:param max_parallel_dl: Number of simultaneous downloads allowed [5].
:param requests_session: Optional requests.sessions.Session object, for unit tests.
"""
self._jobs = {}
self._next_job_id = 0
self._queue = PriorityQueue()
self._stop_event = threading.Event()
self._worker_pool = set()
self._lock = threading.Lock()
self._logger = InvokeAILogger.get_logger("DownloadQueueService")
self._event_bus = event_bus
self._requests = requests_session or requests.Session()
self._accept_download_requests = False
self._max_parallel_dl = max_parallel_dl
def start(self, *args: Any, **kwargs: Any) -> None:
"""Start the download worker threads."""
with self._lock:
if self._worker_pool:
raise Exception("Attempt to start the download service twice")
self._stop_event.clear()
self._start_workers(self._max_parallel_dl)
self._accept_download_requests = True
def stop(self, *args: Any, **kwargs: Any) -> None:
"""Stop the download worker threads."""
with self._lock:
if not self._worker_pool:
raise Exception("Attempt to stop the download service before it was started")
self._accept_download_requests = False # reject attempts to add new jobs to queue
queued_jobs = [x for x in self.list_jobs() if x.status == DownloadJobStatus.WAITING]
active_jobs = [x for x in self.list_jobs() if x.status == DownloadJobStatus.RUNNING]
if queued_jobs:
self._logger.warning(f"Cancelling {len(queued_jobs)} queued downloads")
if active_jobs:
self._logger.info(f"Waiting for {len(active_jobs)} active download jobs to complete")
with self._queue.mutex:
self._queue.queue.clear()
self.join() # wait for all active jobs to finish
self._stop_event.set()
self._worker_pool.clear()
def download(
self,
source: AnyHttpUrl,
dest: Path,
priority: int = 10,
access_token: Optional[str] = None,
on_start: Optional[DownloadEventHandler] = None,
on_progress: Optional[DownloadEventHandler] = None,
on_complete: Optional[DownloadEventHandler] = None,
on_cancelled: Optional[DownloadEventHandler] = None,
on_error: Optional[DownloadEventHandler] = None,
) -> DownloadJob:
"""Create a download job and return its ID."""
if not self._accept_download_requests:
raise ServiceInactiveException(
"The download service is not currently accepting requests. Please call start() to initialize the service."
)
with self._lock:
id = self._next_job_id
self._next_job_id += 1
job = DownloadJob(
id=id,
source=source,
dest=dest,
priority=priority,
access_token=access_token,
)
job.set_callbacks(
on_start=on_start,
on_progress=on_progress,
on_complete=on_complete,
on_cancelled=on_cancelled,
on_error=on_error,
)
self._jobs[id] = job
self._queue.put(job)
return job
def join(self) -> None:
"""Wait for all jobs to complete."""
self._queue.join()
def list_jobs(self) -> List[DownloadJob]:
"""List all the jobs."""
return list(self._jobs.values())
def prune_jobs(self) -> None:
"""Prune completed and errored queue items from the job list."""
with self._lock:
to_delete = set()
for job_id, job in self._jobs.items():
if self._in_terminal_state(job):
to_delete.add(job_id)
for job_id in to_delete:
del self._jobs[job_id]
def id_to_job(self, id: int) -> DownloadJob:
"""Translate a job ID into a DownloadJob object."""
try:
return self._jobs[id]
except KeyError as excp:
raise UnknownJobIDException("Unrecognized job") from excp
def cancel_job(self, job: DownloadJob) -> None:
"""
Cancel the indicated job.
If it is running it will be stopped.
job.status will be set to DownloadJobStatus.CANCELLED
"""
with self._lock:
job.cancel()
def cancel_all_jobs(self, preserve_partial: bool = False) -> None:
"""Cancel all jobs (those not in enqueued, running or paused state)."""
for job in self._jobs.values():
if not self._in_terminal_state(job):
self.cancel_job(job)
def _in_terminal_state(self, job: DownloadJob) -> bool:
return job.status in [
DownloadJobStatus.COMPLETED,
DownloadJobStatus.CANCELLED,
DownloadJobStatus.ERROR,
]
def _start_workers(self, max_workers: int) -> None:
"""Start the requested number of worker threads."""
self._stop_event.clear()
for i in range(0, max_workers): # noqa B007
worker = threading.Thread(target=self._download_next_item, daemon=True)
self._logger.debug(f"Download queue worker thread {worker.name} starting.")
worker.start()
self._worker_pool.add(worker)
def _download_next_item(self) -> None:
"""Worker thread gets next job on priority queue."""
done = False
while not done:
if self._stop_event.is_set():
done = True
continue
try:
job = self._queue.get(timeout=1)
except Empty:
continue
try:
job.job_started = get_iso_timestamp()
self._do_download(job)
self._signal_job_complete(job)
except (OSError, HTTPError) as excp:
job.error_type = excp.__class__.__name__ + f"({str(excp)})"
job.error = traceback.format_exc()
self._signal_job_error(job)
except DownloadJobCancelledException:
self._signal_job_cancelled(job)
self._cleanup_cancelled_job(job)
finally:
job.job_ended = get_iso_timestamp()
self._queue.task_done()
self._logger.debug(f"Download queue worker thread {threading.current_thread().name} exiting.")
def _do_download(self, job: DownloadJob) -> None:
"""Do the actual download."""
url = job.source
header = {"Authorization": f"Bearer {job.access_token}"} if job.access_token else {}
open_mode = "wb"
# Make a streaming request. This will retrieve headers including
# content-length and content-disposition, but not fetch any content itself
resp = self._requests.get(str(url), headers=header, stream=True)
if not resp.ok:
raise HTTPError(resp.reason)
content_length = int(resp.headers.get("content-length", 0))
job.total_bytes = content_length
if job.dest.is_dir():
file_name = os.path.basename(str(url.path)) # default is to use the last bit of the URL
if match := re.search('filename="(.+)"', resp.headers.get("Content-Disposition", "")):
remote_name = match.group(1)
if self._validate_filename(job.dest.as_posix(), remote_name):
file_name = remote_name
job.download_path = job.dest / file_name
else:
job.dest.parent.mkdir(parents=True, exist_ok=True)
job.download_path = job.dest
assert job.download_path
# Don't clobber an existing file. See commit 82c2c85202f88c6d24ff84710f297cfc6ae174af
# for code that instead resumes an interrupted download.
if job.download_path.exists():
raise OSError(f"[Errno 17] File {job.download_path} exists")
# append ".downloading" to the path
in_progress_path = self._in_progress_path(job.download_path)
# signal caller that the download is starting. At this point, key fields such as
# download_path and total_bytes will be populated. We call it here because the might
# discover that the local file is already complete and generate a COMPLETED status.
self._signal_job_started(job)
# "range not satisfiable" - local file is at least as large as the remote file
if resp.status_code == 416 or (content_length > 0 and job.bytes >= content_length):
self._logger.warning(f"{job.download_path}: complete file found. Skipping.")
return
# "partial content" - local file is smaller than remote file
elif resp.status_code == 206 or job.bytes > 0:
self._logger.warning(f"{job.download_path}: partial file found. Resuming")
# some other error
elif resp.status_code != 200:
raise HTTPError(resp.reason)
self._logger.debug(f"{job.source}: Downloading {job.download_path}")
report_delta = job.total_bytes / 100 # report every 1% change
last_report_bytes = 0
# DOWNLOAD LOOP
with open(in_progress_path, open_mode) as file:
for data in resp.iter_content(chunk_size=DOWNLOAD_CHUNK_SIZE):
if job.cancelled:
raise DownloadJobCancelledException("Job was cancelled at caller's request")
job.bytes += file.write(data)
if (job.bytes - last_report_bytes >= report_delta) or (job.bytes >= job.total_bytes):
last_report_bytes = job.bytes
self._signal_job_progress(job)
# if we get here we are done and can rename the file to the original dest
in_progress_path.rename(job.download_path)
def _validate_filename(self, directory: str, filename: str) -> bool:
pc_name_max = os.pathconf(directory, "PC_NAME_MAX") if hasattr(os, "pathconf") else 260 # hardcoded for windows
pc_path_max = (
os.pathconf(directory, "PC_PATH_MAX") if hasattr(os, "pathconf") else 32767
) # hardcoded for windows with long names enabled
if "/" in filename:
return False
if filename.startswith(".."):
return False
if len(filename) > pc_name_max:
return False
if len(os.path.join(directory, filename)) > pc_path_max:
return False
return True
def _in_progress_path(self, path: Path) -> Path:
return path.with_name(path.name + ".downloading")
def _signal_job_started(self, job: DownloadJob) -> None:
job.status = DownloadJobStatus.RUNNING
if job.on_start:
try:
job.on_start(job)
except Exception as e:
self._logger.error(e)
if self._event_bus:
assert job.download_path
self._event_bus.emit_download_started(str(job.source), job.download_path.as_posix())
def _signal_job_progress(self, job: DownloadJob) -> None:
if job.on_progress:
try:
job.on_progress(job)
except Exception as e:
self._logger.error(e)
if self._event_bus:
assert job.download_path
self._event_bus.emit_download_progress(
str(job.source),
download_path=job.download_path.as_posix(),
current_bytes=job.bytes,
total_bytes=job.total_bytes,
)
def _signal_job_complete(self, job: DownloadJob) -> None:
job.status = DownloadJobStatus.COMPLETED
if job.on_complete:
try:
job.on_complete(job)
except Exception as e:
self._logger.error(e)
if self._event_bus:
assert job.download_path
self._event_bus.emit_download_complete(
str(job.source), download_path=job.download_path.as_posix(), total_bytes=job.total_bytes
)
def _signal_job_cancelled(self, job: DownloadJob) -> None:
job.status = DownloadJobStatus.CANCELLED
if job.on_cancelled:
try:
job.on_cancelled(job)
except Exception as e:
self._logger.error(e)
if self._event_bus:
self._event_bus.emit_download_cancelled(str(job.source))
def _signal_job_error(self, job: DownloadJob) -> None:
job.status = DownloadJobStatus.ERROR
if job.on_error:
try:
job.on_error(job)
except Exception as e:
self._logger.error(e)
if self._event_bus:
assert job.error_type
assert job.error
self._event_bus.emit_download_error(str(job.source), error_type=job.error_type, error=job.error)
def _cleanup_cancelled_job(self, job: DownloadJob) -> None:
self._logger.warning(f"Cleaning up leftover files from cancelled download job {job.download_path}")
try:
if job.download_path:
partial_file = self._in_progress_path(job.download_path)
partial_file.unlink()
except OSError as excp:
self._logger.warning(excp)
# Example on_progress event handler to display a TQDM status bar
# Activate with:
# download_service.download('http://foo.bar/baz', '/tmp', on_progress=TqdmProgress().job_update
class TqdmProgress(object):
"""TQDM-based progress bar object to use in on_progress handlers."""
_bars: Dict[int, tqdm] # the tqdm object
_last: Dict[int, int] # last bytes downloaded
def __init__(self) -> None: # noqa D107
self._bars = {}
self._last = {}
def update(self, job: DownloadJob) -> None: # noqa D102
job_id = job.id
# new job
if job_id not in self._bars:
assert job.download_path
dest = Path(job.download_path).name
self._bars[job_id] = tqdm(
desc=dest,
initial=0,
total=job.total_bytes,
unit="iB",
unit_scale=True,
)
self._last[job_id] = 0
self._bars[job_id].update(job.bytes - self._last[job_id])
self._last[job_id] = job.bytes

View File

@ -17,7 +17,6 @@ from invokeai.backend.model_management.models.base import BaseModelType, ModelTy
class EventServiceBase:
queue_event: str = "queue_event"
download_event: str = "download_event"
model_event: str = "model_event"
"""Basic event bus, to have an empty stand-in when not needed"""
@ -33,13 +32,6 @@ class EventServiceBase:
payload={"event": event_name, "data": payload},
)
def __emit_download_event(self, event_name: str, payload: dict) -> None:
payload["timestamp"] = get_timestamp()
self.dispatch(
event_name=EventServiceBase.download_event,
payload={"event": event_name, "data": payload},
)
def __emit_model_event(self, event_name: str, payload: dict) -> None:
payload["timestamp"] = get_timestamp()
self.dispatch(
@ -331,79 +323,6 @@ class EventServiceBase:
payload={"queue_id": queue_id},
)
def emit_download_started(self, source: str, download_path: str) -> None:
"""
Emit when a download job is started.
:param url: The downloaded url
"""
self.__emit_download_event(
event_name="download_started",
payload={"source": source, "download_path": download_path},
)
def emit_download_progress(self, source: str, download_path: str, current_bytes: int, total_bytes: int) -> None:
"""
Emit "download_progress" events at regular intervals during a download job.
:param source: The downloaded source
:param download_path: The local downloaded file
:param current_bytes: Number of bytes downloaded so far
:param total_bytes: The size of the file being downloaded (if known)
"""
self.__emit_download_event(
event_name="download_progress",
payload={
"source": source,
"download_path": download_path,
"current_bytes": current_bytes,
"total_bytes": total_bytes,
},
)
def emit_download_complete(self, source: str, download_path: str, total_bytes: int) -> None:
"""
Emit a "download_complete" event at the end of a successful download.
:param source: Source URL
:param download_path: Path to the locally downloaded file
:param total_bytes: The size of the downloaded file
"""
self.__emit_download_event(
event_name="download_complete",
payload={
"source": source,
"download_path": download_path,
"total_bytes": total_bytes,
},
)
def emit_download_cancelled(self, source: str) -> None:
"""Emit a "download_cancelled" event in the event that the download was cancelled by user."""
self.__emit_download_event(
event_name="download_cancelled",
payload={
"source": source,
},
)
def emit_download_error(self, source: str, error_type: str, error: str) -> None:
"""
Emit a "download_error" event when an download job encounters an exception.
:param source: Source URL
:param error_type: The name of the exception that raised the error
:param error: The traceback from this error
"""
self.__emit_download_event(
event_name="download_error",
payload={
"source": source,
"error_type": error_type,
"error": error,
},
)
def emit_model_install_started(self, source: str) -> None:
"""
Emitted when an install job is started.

View File

@ -11,7 +11,6 @@ if TYPE_CHECKING:
from .board_records.board_records_base import BoardRecordStorageBase
from .boards.boards_base import BoardServiceABC
from .config import InvokeAIAppConfig
from .download import DownloadQueueServiceBase
from .events.events_base import EventServiceBase
from .image_files.image_files_base import ImageFileStorageBase
from .image_records.image_records_base import ImageRecordStorageBase
@ -28,7 +27,7 @@ if TYPE_CHECKING:
from .names.names_base import NameServiceBase
from .session_processor.session_processor_base import SessionProcessorBase
from .session_queue.session_queue_base import SessionQueueBase
from .shared.graph import GraphExecutionState
from .shared.graph import GraphExecutionState, LibraryGraph
from .urls.urls_base import UrlServiceBase
from .workflow_records.workflow_records_base import WorkflowRecordsStorageBase
@ -44,6 +43,7 @@ class InvocationServices:
configuration: "InvokeAIAppConfig"
events: "EventServiceBase"
graph_execution_manager: "ItemStorageABC[GraphExecutionState]"
graph_library: "ItemStorageABC[LibraryGraph]"
images: "ImageServiceABC"
image_records: "ImageRecordStorageBase"
image_files: "ImageFileStorageBase"
@ -51,7 +51,6 @@ class InvocationServices:
logger: "Logger"
model_manager: "ModelManagerServiceBase"
model_records: "ModelRecordServiceBase"
download_queue: "DownloadQueueServiceBase"
model_install: "ModelInstallServiceBase"
processor: "InvocationProcessorABC"
performance_statistics: "InvocationStatsServiceBase"
@ -72,6 +71,7 @@ class InvocationServices:
configuration: "InvokeAIAppConfig",
events: "EventServiceBase",
graph_execution_manager: "ItemStorageABC[GraphExecutionState]",
graph_library: "ItemStorageABC[LibraryGraph]",
images: "ImageServiceABC",
image_files: "ImageFileStorageBase",
image_records: "ImageRecordStorageBase",
@ -79,7 +79,6 @@ class InvocationServices:
logger: "Logger",
model_manager: "ModelManagerServiceBase",
model_records: "ModelRecordServiceBase",
download_queue: "DownloadQueueServiceBase",
model_install: "ModelInstallServiceBase",
processor: "InvocationProcessorABC",
performance_statistics: "InvocationStatsServiceBase",
@ -98,6 +97,7 @@ class InvocationServices:
self.configuration = configuration
self.events = events
self.graph_execution_manager = graph_execution_manager
self.graph_library = graph_library
self.images = images
self.image_files = image_files
self.image_records = image_records
@ -105,7 +105,6 @@ class InvocationServices:
self.logger = logger
self.model_manager = model_manager
self.model_records = model_records
self.download_queue = download_queue
self.model_install = model_install
self.processor = processor
self.performance_statistics = performance_statistics

View File

@ -11,6 +11,7 @@ from typing_extensions import Annotated
from invokeai.app.services.config import InvokeAIAppConfig
from invokeai.app.services.events import EventServiceBase
from invokeai.app.services.invoker import Invoker
from invokeai.app.services.model_records import ModelRecordServiceBase
from invokeai.backend.model_manager import AnyModelConfig
@ -156,12 +157,12 @@ class ModelInstallServiceBase(ABC):
:param event_bus: InvokeAI event bus for reporting events to.
"""
@abstractmethod
def start(self, *args: Any, **kwarg: Any) -> None:
"""Start the installer service."""
def start(self, invoker: Invoker) -> None:
"""Call at InvokeAI startup time."""
self.sync_to_config()
@abstractmethod
def stop(self, *args: Any, **kwarg: Any) -> None:
def stop(self) -> None:
"""Stop the model install service. After this the objection can be safely deleted."""
@property

View File

@ -71,6 +71,7 @@ class ModelInstallService(ModelInstallServiceBase):
self._install_queue = Queue()
self._cached_model_paths = set()
self._models_installed = set()
self._start_installer_thread()
@property
def app_config(self) -> InvokeAIAppConfig: # noqa D102
@ -84,13 +85,8 @@ class ModelInstallService(ModelInstallServiceBase):
def event_bus(self) -> Optional[EventServiceBase]: # noqa D102
return self._event_bus
def start(self, *args: Any, **kwarg: Any) -> None:
"""Start the installer thread."""
self._start_installer_thread()
self.sync_to_config()
def stop(self, *args: Any, **kwarg: Any) -> None:
"""Stop the installer thread; after this the object can be deleted and garbage collected."""
def stop(self, *args, **kwargs) -> None:
"""Stop the install thread; after this the object can be deleted and garbage collected."""
self._install_queue.put(STOP_JOB)
def _start_installer_thread(self) -> None:

View File

@ -5,7 +5,6 @@ from invokeai.app.services.image_files.image_files_base import ImageFileStorageB
from invokeai.app.services.shared.sqlite.sqlite_database import SqliteDatabase
from invokeai.app.services.shared.sqlite_migrator.migrations.migration_1 import build_migration_1
from invokeai.app.services.shared.sqlite_migrator.migrations.migration_2 import build_migration_2
from invokeai.app.services.shared.sqlite_migrator.migrations.migration_3 import build_migration_3
from invokeai.app.services.shared.sqlite_migrator.sqlite_migrator_impl import SqliteMigrator
@ -28,7 +27,6 @@ def init_db(config: InvokeAIAppConfig, logger: Logger, image_files: ImageFileSto
migrator = SqliteMigrator(db=db)
migrator.register_migration(build_migration_1())
migrator.register_migration(build_migration_2(image_files=image_files, logger=logger))
migrator.register_migration(build_migration_3())
migrator.run_migrations()
return db

View File

@ -11,8 +11,6 @@ from invokeai.app.services.workflow_records.workflow_records_common import (
UnsafeWorkflowWithVersionValidator,
)
from .util.migrate_yaml_config_1 import MigrateModelYamlToDb1
class Migration2Callback:
def __init__(self, image_files: ImageFileStorageBase, logger: Logger):
@ -26,7 +24,6 @@ class Migration2Callback:
self._add_workflow_library(cursor)
self._drop_model_manager_metadata(cursor)
self._recreate_model_config(cursor)
self._migrate_model_config_records(cursor)
self._migrate_embedded_workflows(cursor)
def _add_images_has_workflow(self, cursor: sqlite3.Cursor) -> None:
@ -134,11 +131,6 @@ class Migration2Callback:
"""
)
def _migrate_model_config_records(self, cursor: sqlite3.Cursor) -> None:
"""After updating the model config table, we repopulate it."""
model_record_migrator = MigrateModelYamlToDb1(cursor)
model_record_migrator.migrate()
def _migrate_embedded_workflows(self, cursor: sqlite3.Cursor) -> None:
"""
In the v3.5.0 release, InvokeAI changed how it handles embedded workflows. The `images` table in
@ -167,9 +159,6 @@ class Migration2Callback:
except ImageFileNotFoundException:
self._logger.warning(f"Image {image_name} not found, skipping")
continue
except Exception as e:
self._logger.warning(f"Error while checking image {image_name}, skipping: {e}")
continue
if "invokeai_workflow" in pil_image.info:
try:
UnsafeWorkflowWithVersionValidator.validate_json(pil_image.info.get("invokeai_workflow", ""))

View File

@ -1,75 +0,0 @@
import sqlite3
from invokeai.app.services.shared.sqlite_migrator.sqlite_migrator_common import Migration
from .util.migrate_yaml_config_1 import MigrateModelYamlToDb1
class Migration3Callback:
def __init__(self) -> None:
pass
def __call__(self, cursor: sqlite3.Cursor) -> None:
self._drop_model_manager_metadata(cursor)
self._recreate_model_config(cursor)
self._migrate_model_config_records(cursor)
def _drop_model_manager_metadata(self, cursor: sqlite3.Cursor) -> None:
"""Drops the `model_manager_metadata` table."""
cursor.execute("DROP TABLE IF EXISTS model_manager_metadata;")
def _recreate_model_config(self, cursor: sqlite3.Cursor) -> None:
"""
Drops the `model_config` table, recreating it.
In 3.4.0, this table used explicit columns but was changed to use json_extract 3.5.0.
Because this table is not used in production, we are able to simply drop it and recreate it.
"""
cursor.execute("DROP TABLE IF EXISTS model_config;")
cursor.execute(
"""--sql
CREATE TABLE IF NOT EXISTS model_config (
id TEXT NOT NULL PRIMARY KEY,
-- The next 3 fields are enums in python, unrestricted string here
base TEXT GENERATED ALWAYS as (json_extract(config, '$.base')) VIRTUAL NOT NULL,
type TEXT GENERATED ALWAYS as (json_extract(config, '$.type')) VIRTUAL NOT NULL,
name TEXT GENERATED ALWAYS as (json_extract(config, '$.name')) VIRTUAL NOT NULL,
path TEXT GENERATED ALWAYS as (json_extract(config, '$.path')) VIRTUAL NOT NULL,
format TEXT GENERATED ALWAYS as (json_extract(config, '$.format')) VIRTUAL NOT NULL,
original_hash TEXT, -- could be null
-- Serialized JSON representation of the whole config object,
-- which will contain additional fields from subclasses
config TEXT NOT NULL,
created_at DATETIME NOT NULL DEFAULT(STRFTIME('%Y-%m-%d %H:%M:%f', 'NOW')),
-- Updated via trigger
updated_at DATETIME NOT NULL DEFAULT(STRFTIME('%Y-%m-%d %H:%M:%f', 'NOW')),
-- unique constraint on combo of name, base and type
UNIQUE(name, base, type)
);
"""
)
def _migrate_model_config_records(self, cursor: sqlite3.Cursor) -> None:
"""After updating the model config table, we repopulate it."""
model_record_migrator = MigrateModelYamlToDb1(cursor)
model_record_migrator.migrate()
def build_migration_3() -> Migration:
"""
Build the migration from database version 2 to 3.
This migration does the following:
- Drops the `model_config` table, recreating it
- Migrates data from `models.yaml` into the `model_config` table
"""
migration_3 = Migration(
from_version=2,
to_version=3,
callback=Migration3Callback(),
)
return migration_3

View File

@ -1,975 +0,0 @@
{
"name": "Prompt from File",
"author": "InvokeAI",
"description": "Sample workflow using Prompt from File node",
"version": "0.1.0",
"contact": "invoke@invoke.ai",
"tags": "text2image, prompt from file, default",
"notes": "",
"exposedFields": [
{
"nodeId": "d6353b7f-b447-4e17-8f2e-80a88c91d426",
"fieldName": "model"
},
{
"nodeId": "1b7e0df8-8589-4915-a4ea-c0088f15d642",
"fieldName": "file_path"
}
],
"meta": {
"category": "default",
"version": "2.0.0"
},
"id": "d1609af5-eb0a-4f73-b573-c9af96a8d6bf",
"nodes": [
{
"id": "c2eaf1ba-5708-4679-9e15-945b8b432692",
"type": "invocation",
"data": {
"id": "c2eaf1ba-5708-4679-9e15-945b8b432692",
"type": "compel",
"label": "",
"isOpen": false,
"notes": "",
"isIntermediate": true,
"useCache": true,
"version": "1.0.0",
"nodePack": "invokeai",
"inputs": {
"prompt": {
"id": "dcdf3f6d-9b96-4bcd-9b8d-f992fefe4f62",
"name": "prompt",
"fieldKind": "input",
"label": "",
"type": {
"isCollection": false,
"isCollectionOrScalar": false,
"name": "StringField"
},
"value": ""
},
"clip": {
"id": "3f1981c9-d8a9-42eb-a739-4f120eb80745",
"name": "clip",
"fieldKind": "input",
"label": "",
"type": {
"isCollection": false,
"isCollectionOrScalar": false,
"name": "ClipField"
}
}
},
"outputs": {
"conditioning": {
"id": "46205e6c-c5e2-44cb-9c82-1cd20b95674a",
"name": "conditioning",
"fieldKind": "output",
"type": {
"isCollection": false,
"isCollectionOrScalar": false,
"name": "ConditioningField"
}
}
}
},
"width": 320,
"height": 32,
"position": {
"x": 925,
"y": -200
}
},
{
"id": "1b7e0df8-8589-4915-a4ea-c0088f15d642",
"type": "invocation",
"data": {
"id": "1b7e0df8-8589-4915-a4ea-c0088f15d642",
"type": "prompt_from_file",
"label": "Prompts from File",
"isOpen": true,
"notes": "",
"isIntermediate": true,
"useCache": true,
"version": "1.0.1",
"nodePack": "invokeai",
"inputs": {
"file_path": {
"id": "37e37684-4f30-4ec8-beae-b333e550f904",
"name": "file_path",
"fieldKind": "input",
"label": "Prompts File Path",
"type": {
"isCollection": false,
"isCollectionOrScalar": false,
"name": "StringField"
},
"value": ""
},
"pre_prompt": {
"id": "7de02feb-819a-4992-bad3-72a30920ddea",
"name": "pre_prompt",
"fieldKind": "input",
"label": "",
"type": {
"isCollection": false,
"isCollectionOrScalar": false,
"name": "StringField"
},
"value": ""
},
"post_prompt": {
"id": "95f191d8-a282-428e-bd65-de8cb9b7513a",
"name": "post_prompt",
"fieldKind": "input",
"label": "",
"type": {
"isCollection": false,
"isCollectionOrScalar": false,
"name": "StringField"
},
"value": ""
},
"start_line": {
"id": "efee9a48-05ab-4829-8429-becfa64a0782",
"name": "start_line",
"fieldKind": "input",
"label": "",
"type": {
"isCollection": false,
"isCollectionOrScalar": false,
"name": "IntegerField"
},
"value": 1
},
"max_prompts": {
"id": "abebb428-3d3d-49fd-a482-4e96a16fff08",
"name": "max_prompts",
"fieldKind": "input",
"label": "",
"type": {
"isCollection": false,
"isCollectionOrScalar": false,
"name": "IntegerField"
},
"value": 1
}
},
"outputs": {
"collection": {
"id": "77d5d7f1-9877-4ab1-9a8c-33e9ffa9abf3",
"name": "collection",
"fieldKind": "output",
"type": {
"isCollection": true,
"isCollectionOrScalar": false,
"name": "StringField"
}
}
}
},
"width": 320,
"height": 580,
"position": {
"x": 475,
"y": -400
}
},
{
"id": "1b89067c-3f6b-42c8-991f-e3055789b251",
"type": "invocation",
"data": {
"id": "1b89067c-3f6b-42c8-991f-e3055789b251",
"type": "iterate",
"label": "",
"isOpen": false,
"notes": "",
"isIntermediate": true,
"useCache": true,
"version": "1.1.0",
"inputs": {
"collection": {
"id": "4c564bf8-5ed6-441e-ad2c-dda265d5785f",
"name": "collection",
"fieldKind": "input",
"label": "",
"type": {
"isCollection": true,
"isCollectionOrScalar": false,
"name": "CollectionField"
}
}
},
"outputs": {
"item": {
"id": "36340f9a-e7a5-4afa-b4b5-313f4e292380",
"name": "item",
"fieldKind": "output",
"type": {
"isCollection": false,
"isCollectionOrScalar": false,
"name": "CollectionItemField"
}
},
"index": {
"id": "1beca95a-2159-460f-97ff-c8bab7d89336",
"name": "index",
"fieldKind": "output",
"type": {
"isCollection": false,
"isCollectionOrScalar": false,
"name": "IntegerField"
}
},
"total": {
"id": "ead597b8-108e-4eda-88a8-5c29fa2f8df9",
"name": "total",
"fieldKind": "output",
"type": {
"isCollection": false,
"isCollectionOrScalar": false,
"name": "IntegerField"
}
}
}
},
"width": 320,
"height": 32,
"position": {
"x": 925,
"y": -400
}
},
{
"id": "d6353b7f-b447-4e17-8f2e-80a88c91d426",
"type": "invocation",
"data": {
"id": "d6353b7f-b447-4e17-8f2e-80a88c91d426",
"type": "main_model_loader",
"label": "",
"isOpen": true,
"notes": "",
"isIntermediate": true,
"useCache": true,
"version": "1.0.0",
"nodePack": "invokeai",
"inputs": {
"model": {
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},
{
"id": "reactflow__edge-ea18915f-2c5b-4569-b725-8e9e9122e8d3noise-ad487d0c-dcbb-49c5-bb8e-b28d4cbc5a63noise",
"source": "ea18915f-2c5b-4569-b725-8e9e9122e8d3",
"target": "ad487d0c-dcbb-49c5-bb8e-b28d4cbc5a63",
"type": "default",
"sourceHandle": "noise",
"targetHandle": "noise"
},
{
"id": "reactflow__edge-6fd74a17-6065-47a5-b48b-f4e2b8fa7953value-ea18915f-2c5b-4569-b725-8e9e9122e8d3seed",
"source": "6fd74a17-6065-47a5-b48b-f4e2b8fa7953",
"target": "ea18915f-2c5b-4569-b725-8e9e9122e8d3",
"type": "default",
"sourceHandle": "value",
"targetHandle": "seed"
},
{
"id": "reactflow__edge-ad487d0c-dcbb-49c5-bb8e-b28d4cbc5a63latents-a9683c0a-6b1f-4a5e-8187-c57e764b3400latents",
"source": "ad487d0c-dcbb-49c5-bb8e-b28d4cbc5a63",
"target": "a9683c0a-6b1f-4a5e-8187-c57e764b3400",
"type": "default",
"sourceHandle": "latents",
"targetHandle": "latents"
},
{
"id": "reactflow__edge-24e9d7ed-4836-4ec4-8f9e-e747721f9818vae-a9683c0a-6b1f-4a5e-8187-c57e764b3400vae",
"source": "24e9d7ed-4836-4ec4-8f9e-e747721f9818",
"target": "a9683c0a-6b1f-4a5e-8187-c57e764b3400",
"type": "default",
"sourceHandle": "vae",
"targetHandle": "vae"
},
{
"id": "reactflow__edge-c41e705b-f2e3-4d1a-83c4-e34bb9344966clip-85b77bb2-c67a-416a-b3e8-291abe746c44clip",
"source": "c41e705b-f2e3-4d1a-83c4-e34bb9344966",
"target": "85b77bb2-c67a-416a-b3e8-291abe746c44",
"type": "default",
"sourceHandle": "clip",
"targetHandle": "clip"
}
]
}

View File

@ -1,8 +0,0 @@
import re
def extract_ti_triggers_from_prompt(prompt: str) -> list[str]:
ti_triggers = []
for trigger in re.findall(r"<[a-zA-Z0-9., _-]+>", prompt):
ti_triggers.append(trigger)
return ti_triggers

View File

@ -28,7 +28,7 @@ def check_invokeai_root(config: InvokeAIAppConfig):
print("== STARTUP ABORTED ==")
print("** One or more necessary files is missing from your InvokeAI root directory **")
print("** Please rerun the configuration script to fix this problem. **")
print("** From the launcher, selection option [6]. **")
print("** From the launcher, selection option [7]. **")
print(
'** From the command line, activate the virtual environment and run "invokeai-configure --yes --skip-sd-weights" **'
)

View File

@ -1,31 +0,0 @@
# Copyright (c) 2024 Lincoln Stein and the InvokeAI Development Team
"""
This module exports the function has_baked_in_sdxl_vae().
It returns True if an SDXL checkpoint model has the original SDXL 1.0 VAE,
which doesn't work properly in fp16 mode.
"""
import hashlib
from pathlib import Path
from safetensors.torch import load_file
SDXL_1_0_VAE_HASH = "bc40b16c3a0fa4625abdfc01c04ffc21bf3cefa6af6c7768ec61eb1f1ac0da51"
def has_baked_in_sdxl_vae(checkpoint_path: Path) -> bool:
"""Return true if the checkpoint contains a custom (non SDXL-1.0) VAE."""
hash = _vae_hash(checkpoint_path)
return hash != SDXL_1_0_VAE_HASH
def _vae_hash(checkpoint_path: Path) -> str:
checkpoint = load_file(checkpoint_path, device="cpu")
vae_keys = [x for x in checkpoint.keys() if x.startswith("first_stage_model.")]
hash = hashlib.new("sha256")
for key in vae_keys:
value = checkpoint[key]
hash.update(bytes(key, "UTF-8"))
hash.update(bytes(str(value), "UTF-8"))
return hash.hexdigest()

View File

@ -13,7 +13,6 @@ from safetensors.torch import load_file
from transformers import CLIPTextModel, CLIPTokenizer
from invokeai.app.shared.models import FreeUConfig
from invokeai.backend.model_management.model_load_optimizations import skip_torch_weight_init
from .models.lora import LoRAModel
@ -212,17 +211,11 @@ class ModelPatcher:
for i in range(ti_embedding.shape[0]):
new_tokens_added += ti_tokenizer.add_tokens(_get_trigger(ti_name, i))
# Modify text_encoder.
# resize_token_embeddings(...) constructs a new torch.nn.Embedding internally. Initializing the weights of
# this embedding is slow and unnecessary, so we wrap this step in skip_torch_weight_init() to save some
# time.
with skip_torch_weight_init():
text_encoder.resize_token_embeddings(init_tokens_count + new_tokens_added, pad_to_multiple_of)
# modify text_encoder
text_encoder.resize_token_embeddings(init_tokens_count + new_tokens_added, pad_to_multiple_of)
model_embeddings = text_encoder.get_input_embeddings()
for ti_name, ti in ti_list:
ti_embedding = _get_ti_embedding(text_encoder.get_input_embeddings(), ti)
for ti_name, _ in ti_list:
ti_tokens = []
for i in range(ti_embedding.shape[0]):
embedding = ti_embedding[i]

View File

@ -370,8 +370,6 @@ class LoRACheckpointProbe(CheckpointProbeBase):
return BaseModelType.StableDiffusion1
elif token_vector_length == 1024:
return BaseModelType.StableDiffusion2
elif token_vector_length == 1280:
return BaseModelType.StableDiffusionXL # recognizes format at https://civitai.com/models/224641
elif token_vector_length == 2048:
return BaseModelType.StableDiffusionXL
else:
@ -391,7 +389,7 @@ class TextualInversionCheckpointProbe(CheckpointProbeBase):
elif "clip_g" in checkpoint:
token_dim = checkpoint["clip_g"].shape[-1]
else:
token_dim = list(checkpoint.values())[0].shape[-1]
token_dim = list(checkpoint.values())[0].shape[0]
if token_dim == 768:
return BaseModelType.StableDiffusion1
elif token_dim == 1024:

View File

@ -1,16 +1,11 @@
import json
import os
from enum import Enum
from pathlib import Path
from typing import Literal, Optional
from omegaconf import OmegaConf
from pydantic import Field
from invokeai.app.services.config import InvokeAIAppConfig
from invokeai.backend.model_management.detect_baked_in_vae import has_baked_in_sdxl_vae
from invokeai.backend.util.logging import InvokeAILogger
from .base import (
BaseModelType,
DiffusersModel,
@ -121,28 +116,14 @@ class StableDiffusionXLModel(DiffusersModel):
# The convert script adapted from the diffusers package uses
# strings for the base model type. To avoid making too many
# source code changes, we simply translate here
if Path(output_path).exists():
return output_path
if isinstance(config, cls.CheckpointConfig):
from invokeai.backend.model_management.models.stable_diffusion import _convert_ckpt_and_cache
# Hack in VAE-fp16 fix - If model sdxl-vae-fp16-fix is installed,
# then we bake it into the converted model unless there is already
# a nonstandard VAE installed.
kwargs = {}
app_config = InvokeAIAppConfig.get_config()
vae_path = app_config.models_path / "sdxl/vae/sdxl-vae-fp16-fix"
if vae_path.exists() and not has_baked_in_sdxl_vae(Path(model_path)):
InvokeAILogger.get_logger().warning("No baked-in VAE detected. Inserting sdxl-vae-fp16-fix.")
kwargs["vae_path"] = vae_path
return _convert_ckpt_and_cache(
version=base_model,
model_config=config,
output_path=output_path,
use_safetensors=False, # corrupts sdxl models for some reason
**kwargs,
)
else:
return model_path

View File

@ -9,7 +9,7 @@ def lora_token_vector_length(checkpoint: dict) -> int:
:param checkpoint: The checkpoint
"""
def _get_shape_1(key: str, tensor, checkpoint) -> int:
def _get_shape_1(key, tensor, checkpoint):
lora_token_vector_length = None
if "." not in key:
@ -57,10 +57,6 @@ def lora_token_vector_length(checkpoint: dict) -> int:
for key, tensor in checkpoint.items():
if key.startswith("lora_unet_") and ("_attn2_to_k." in key or "_attn2_to_v." in key):
lora_token_vector_length = _get_shape_1(key, tensor, checkpoint)
elif key.startswith("lora_unet_") and (
"time_emb_proj.lora_down" in key
): # recognizes format at https://civitai.com/models/224641
lora_token_vector_length = _get_shape_1(key, tensor, checkpoint)
elif key.startswith("lora_te") and "_self_attn_" in key:
tmp_length = _get_shape_1(key, tensor, checkpoint)
if key.startswith("lora_te_"):

View File

@ -1,12 +1,8 @@
# Copyright (c) 2023 Lincoln D. Stein
"""Migrate from the InvokeAI v2 models.yaml format to the v3 sqlite format."""
import json
import sqlite3
from hashlib import sha1
from logging import Logger
from pathlib import Path
from typing import Optional
from omegaconf import DictConfig, OmegaConf
from pydantic import TypeAdapter
@ -14,12 +10,13 @@ from pydantic import TypeAdapter
from invokeai.app.services.config import InvokeAIAppConfig
from invokeai.app.services.model_records import (
DuplicateModelException,
ModelRecordServiceSQL,
UnknownModelException,
)
from invokeai.app.services.shared.sqlite.sqlite_database import SqliteDatabase
from invokeai.backend.model_manager.config import (
AnyModelConfig,
BaseModelType,
ModelConfigFactory,
ModelType,
)
from invokeai.backend.model_manager.hash import FastModelHash
@ -28,9 +25,9 @@ from invokeai.backend.util.logging import InvokeAILogger
ModelsValidator = TypeAdapter(AnyModelConfig)
class MigrateModelYamlToDb1:
class MigrateModelYamlToDb:
"""
Migrate the InvokeAI models.yaml format (VERSION 3.0.0) to SQL3 database format (VERSION 3.5.0).
Migrate the InvokeAI models.yaml format (VERSION 3.0.0) to SQL3 database format (VERSION 3.2.0)
The class has one externally useful method, migrate(), which scans the
currently models.yaml file and imports all its entries into invokeai.db.
@ -44,13 +41,17 @@ class MigrateModelYamlToDb1:
config: InvokeAIAppConfig
logger: Logger
cursor: sqlite3.Cursor
def __init__(self, cursor: sqlite3.Cursor = None) -> None:
def __init__(self) -> None:
self.config = InvokeAIAppConfig.get_config()
self.config.parse_args()
self.logger = InvokeAILogger.get_logger()
self.cursor = cursor
def get_db(self) -> ModelRecordServiceSQL:
"""Fetch the sqlite3 database for this installation."""
db_path = None if self.config.use_memory_db else self.config.db_path
db = SqliteDatabase(db_path=db_path, logger=self.logger, verbose=self.config.log_sql)
return ModelRecordServiceSQL(db)
def get_yaml(self) -> DictConfig:
"""Fetch the models.yaml DictConfig for this installation."""
@ -61,10 +62,8 @@ class MigrateModelYamlToDb1:
def migrate(self) -> None:
"""Do the migration from models.yaml to invokeai.db."""
try:
yaml = self.get_yaml()
except OSError:
return
db = self.get_db()
yaml = self.get_yaml()
for model_key, stanza in yaml.items():
if model_key == "__metadata__":
@ -87,62 +86,22 @@ class MigrateModelYamlToDb1:
new_config: AnyModelConfig = ModelsValidator.validate_python(stanza) # type: ignore # see https://github.com/pydantic/pydantic/discussions/7094
try:
if original_record := self._search_by_path(stanza.path):
key = original_record.key
if original_record := db.search_by_path(stanza.path):
key = original_record[0].key
self.logger.info(f"Updating model {model_name} with information from models.yaml using key {key}")
self._update_model(key, new_config)
db.update_model(key, new_config)
else:
self.logger.info(f"Adding model {model_name} with key {model_key}")
self._add_model(new_key, new_config)
db.add_model(new_key, new_config)
except DuplicateModelException:
self.logger.warning(f"Model {model_name} is already in the database")
except UnknownModelException:
self.logger.warning(f"Model at {stanza.path} could not be found in database")
def _search_by_path(self, path: Path) -> Optional[AnyModelConfig]:
self.cursor.execute(
"""--sql
SELECT config FROM model_config
WHERE path=?;
""",
(str(path),),
)
results = [ModelConfigFactory.make_config(json.loads(x[0])) for x in self.cursor.fetchall()]
return results[0] if results else None
def _update_model(self, key: str, config: AnyModelConfig) -> None:
record = ModelConfigFactory.make_config(config, key=key) # ensure it is a valid config obect
json_serialized = record.model_dump_json() # and turn it into a json string.
self.cursor.execute(
"""--sql
UPDATE model_config
SET
config=?
WHERE id=?;
""",
(json_serialized, key),
)
if self.cursor.rowcount == 0:
raise UnknownModelException("model not found")
def main():
MigrateModelYamlToDb().migrate()
def _add_model(self, key: str, config: AnyModelConfig) -> None:
record = ModelConfigFactory.make_config(config, key=key) # ensure it is a valid config obect.
json_serialized = record.model_dump_json() # and turn it into a json string.
try:
self.cursor.execute(
"""--sql
INSERT INTO model_config (
id,
original_hash,
config
)
VALUES (?,?,?);
""",
(
key,
record.original_hash,
json_serialized,
),
)
except sqlite3.IntegrityError as exc:
raise DuplicateModelException(f"{record.name}: model is already in database") from exc
if __name__ == "__main__":
main()

View File

@ -400,8 +400,6 @@ class LoRACheckpointProbe(CheckpointProbeBase):
return BaseModelType.StableDiffusion1
elif token_vector_length == 1024:
return BaseModelType.StableDiffusion2
elif token_vector_length == 1280:
return BaseModelType.StableDiffusionXL # recognizes format at https://civitai.com/models/224641
elif token_vector_length == 2048:
return BaseModelType.StableDiffusionXL
else:

View File

@ -276,11 +276,7 @@ class StableDiffusionGeneratorPipeline(StableDiffusionPipeline):
self.disable_attention_slicing()
return
elif config.attention_type == "torch-sdp":
if hasattr(torch.nn.functional, "scaled_dot_product_attention"):
# diffusers enables sdp automatically
return
else:
raise Exception("torch-sdp attention slicing not available")
raise Exception("torch-sdp attention slicing not yet implemented")
# the remainder if this code is called when attention_type=='auto'
if self.unet.device.type == "cuda":
@ -288,7 +284,7 @@ class StableDiffusionGeneratorPipeline(StableDiffusionPipeline):
self.enable_xformers_memory_efficient_attention()
return
elif hasattr(torch.nn.functional, "scaled_dot_product_attention"):
# diffusers enables sdp automatically
# diffusers enable sdp automatically
return
if self.unet.device.type == "cpu" or self.unet.device.type == "mps":

View File

@ -102,7 +102,7 @@ def calc_tiles_with_overlap(
def calc_tiles_even_split(
image_height: int, image_width: int, num_tiles_x: int, num_tiles_y: int, overlap: int = 0
image_height: int, image_width: int, num_tiles_x: int, num_tiles_y: int, overlap_fraction: float = 0
) -> list[Tile]:
"""Calculate the tile coordinates for a given image shape with the number of tiles requested.
@ -111,35 +111,31 @@ def calc_tiles_even_split(
image_width (int): The image width in px.
num_x_tiles (int): The number of tile to split the image into on the X-axis.
num_y_tiles (int): The number of tile to split the image into on the Y-axis.
overlap (int, optional): The overlap between adjacent tiles in pixels. Defaults to 0.
overlap_fraction (float, optional): The target overlap as fraction of the tiles size. Defaults to 0.
Returns:
list[Tile]: A list of tiles that cover the image shape. Ordered from left-to-right, top-to-bottom.
"""
# Ensure the image is divisible by LATENT_SCALE_FACTOR
# Ensure tile size is divisible by 8
if image_width % LATENT_SCALE_FACTOR != 0 or image_height % LATENT_SCALE_FACTOR != 0:
raise ValueError(f"image size (({image_width}, {image_height})) must be divisible by {LATENT_SCALE_FACTOR}")
# Calculate the tile size based on the number of tiles and overlap, and ensure it's divisible by 8 (rounding down)
if num_tiles_x > 1:
# ensure the overlap is not more than the maximum overlap if we only have 1 tile then we dont care about overlap
assert overlap <= image_width - (LATENT_SCALE_FACTOR * (num_tiles_x - 1))
tile_size_x = LATENT_SCALE_FACTOR * math.floor(
((image_width + overlap * (num_tiles_x - 1)) // num_tiles_x) / LATENT_SCALE_FACTOR
)
assert overlap < tile_size_x
else:
tile_size_x = image_width
# Calculate the overlap size based on the percentage and adjust it to be divisible by 8 (rounding up)
overlap_x = LATENT_SCALE_FACTOR * math.ceil(
int((image_width / num_tiles_x) * overlap_fraction) / LATENT_SCALE_FACTOR
)
overlap_y = LATENT_SCALE_FACTOR * math.ceil(
int((image_height / num_tiles_y) * overlap_fraction) / LATENT_SCALE_FACTOR
)
if num_tiles_y > 1:
# ensure the overlap is not more than the maximum overlap if we only have 1 tile then we dont care about overlap
assert overlap <= image_height - (LATENT_SCALE_FACTOR * (num_tiles_y - 1))
tile_size_y = LATENT_SCALE_FACTOR * math.floor(
((image_height + overlap * (num_tiles_y - 1)) // num_tiles_y) / LATENT_SCALE_FACTOR
)
assert overlap < tile_size_y
else:
tile_size_y = image_height
# Calculate the tile size based on the number of tiles and overlap, and ensure it's divisible by 8 (rounding down)
tile_size_x = LATENT_SCALE_FACTOR * math.floor(
((image_width + overlap_x * (num_tiles_x - 1)) // num_tiles_x) / LATENT_SCALE_FACTOR
)
tile_size_y = LATENT_SCALE_FACTOR * math.floor(
((image_height + overlap_y * (num_tiles_y - 1)) // num_tiles_y) / LATENT_SCALE_FACTOR
)
# tiles[y * num_tiles_x + x] is the tile for the y'th row, x'th column.
tiles: list[Tile] = []
@ -147,7 +143,7 @@ def calc_tiles_even_split(
# Calculate tile coordinates. (Ignore overlap values for now.)
for tile_idx_y in range(num_tiles_y):
# Calculate the top and bottom of the row
top = tile_idx_y * (tile_size_y - overlap)
top = tile_idx_y * (tile_size_y - overlap_y)
bottom = min(top + tile_size_y, image_height)
# For the last row adjust bottom to be the height of the image
if tile_idx_y == num_tiles_y - 1:
@ -155,7 +151,7 @@ def calc_tiles_even_split(
for tile_idx_x in range(num_tiles_x):
# Calculate the left & right coordinate of each tile
left = tile_idx_x * (tile_size_x - overlap)
left = tile_idx_x * (tile_size_x - overlap_x)
right = min(left + tile_size_x, image_width)
# For the last tile in the row adjust right to be the width of the image
if tile_idx_x == num_tiles_x - 1:

View File

@ -1,9 +1,11 @@
from __future__ import annotations
import platform
from contextlib import nullcontext
from typing import Union
import torch
from packaging import version
from torch import autocast
from invokeai.app.services.config import InvokeAIAppConfig
@ -35,7 +37,7 @@ def choose_precision(device: torch.device) -> str:
device_name = torch.cuda.get_device_name(device)
if not ("GeForce GTX 1660" in device_name or "GeForce GTX 1650" in device_name):
return "float16"
elif device.type == "mps":
elif device.type == "mps" and version.parse(platform.mac_ver()[0]) < version.parse("14.0.0"):
return "float16"
return "float32"
@ -44,7 +46,7 @@ def torch_dtype(device: torch.device) -> torch.dtype:
if config.full_precision:
return torch.float32
if choose_precision(device) == "float16":
return torch.bfloat16 if device.type == "cuda" else torch.float16
return torch.float16
else:
return torch.float32

View File

@ -4,7 +4,6 @@ pip install <path_to_git_source>.
"""
import os
import platform
from distutils.version import LooseVersion
import pkg_resources
import psutil
@ -32,6 +31,10 @@ else:
console = Console(style=Style(color="grey74", bgcolor="grey19"))
def get_versions() -> dict:
return requests.get(url=INVOKE_AI_REL).json()
def invokeai_is_running() -> bool:
for p in psutil.process_iter():
try:
@ -47,20 +50,6 @@ def invokeai_is_running() -> bool:
return False
def get_pypi_versions():
url = "https://pypi.org/pypi/invokeai/json"
try:
data = requests.get(url).json()
except Exception:
raise Exception("Unable to fetch version information from PyPi")
versions = list(data["releases"].keys())
versions.sort(key=LooseVersion, reverse=True)
latest_version = [v for v in versions if "rc" not in v][0]
latest_release_candidate = [v for v in versions if "rc" in v][0]
return latest_version, latest_release_candidate, versions
def welcome(latest_release: str, latest_prerelease: str):
@group()
def text():
@ -68,10 +57,14 @@ def welcome(latest_release: str, latest_prerelease: str):
yield ""
yield "This script will update InvokeAI to the latest release, or to the development version of your choice."
yield ""
yield "When updating to an arbitrary tag or branch, be aware that the front end may be mismatched to the backend,"
yield "making the web frontend unusable. Please downgrade to the latest release if this happens."
yield ""
yield "[bold yellow]Options:"
yield f"""[1] Update to the latest [bold]official release[/bold] ([italic]{latest_release}[/italic])
[2] Update to the latest [bold]pre-release[/bold] (may be buggy, database backups are recommended before installation; caveat emptor!) ([italic]{latest_prerelease}[/italic])
[3] Manually enter the [bold]version[/bold] you wish to update to"""
[2] Update to the latest [bold]pre-release[/bold] (may be buggy; caveat emptor!) ([italic]{latest_prerelease}[/italic])
[3] Manually enter the [bold]tag name[/bold] for the version you wish to update to
[4] Manually enter the [bold]branch name[/bold] for the version you wish to update to"""
console.rule()
print(
@ -99,35 +92,44 @@ def get_extras():
def main():
versions = get_versions()
released_versions = [x for x in versions if not (x["draft"] or x["prerelease"])]
prerelease_versions = [x for x in versions if not x["draft"] and x["prerelease"]]
latest_release = released_versions[0]["tag_name"] if len(released_versions) else None
latest_prerelease = prerelease_versions[0]["tag_name"] if len(prerelease_versions) else None
if invokeai_is_running():
print(":exclamation: [bold red]Please terminate all running instances of InvokeAI before updating.[/red bold]")
input("Press any key to continue...")
return
latest_release, latest_prerelease, versions = get_pypi_versions()
welcome(latest_release, latest_prerelease)
release = latest_release
choice = Prompt.ask("Choice:", choices=["1", "2", "3"], default="1")
tag = None
branch = None
release = None
choice = Prompt.ask("Choice:", choices=["1", "2", "3", "4"], default="1")
if choice == "1":
release = latest_release
elif choice == "2":
release = latest_prerelease
elif choice == "3":
while True:
release = Prompt.ask("Enter an InvokeAI version")
release.strip()
if release in versions:
break
print(f":exclamation: [bold red]'{release}' is not a recognized InvokeAI release.[/red bold]")
while not tag:
tag = Prompt.ask("Enter an InvokeAI tag name")
elif choice == "4":
while not branch:
branch = Prompt.ask("Enter an InvokeAI branch name")
extras = get_extras()
print(f":crossed_fingers: Upgrading to [yellow]{release}[/yellow]")
cmd = f'pip install "invokeai{extras}=={release}" --use-pep517 --upgrade'
print(f":crossed_fingers: Upgrading to [yellow]{tag or release or branch}[/yellow]")
if release:
cmd = f'pip install "invokeai{extras} @ {INVOKE_AI_SRC}/{release}.zip" --use-pep517 --upgrade'
elif tag:
cmd = f'pip install "invokeai{extras} @ {INVOKE_AI_TAG}/{tag}.zip" --use-pep517 --upgrade'
else:
cmd = f'pip install "invokeai{extras} @ {INVOKE_AI_BRANCH}/{branch}.zip" --use-pep517 --upgrade'
print("")
print("")
if os.system(cmd) == 0:

View File

@ -7,4 +7,4 @@ stats.html
index.html
.yarn/
*.scss
src/services/api/schema.ts
src/services/api/schema.d.ts

View File

@ -28,16 +28,12 @@ module.exports = {
'i18next',
'path',
'unused-imports',
'simple-import-sort',
'eslint-plugin-import',
// These rules are too strict for normal usage, but are useful for optimizing rerenders
// '@arthurgeron/react-usememo',
],
root: true,
rules: {
'path/no-relative-imports': ['error', { maxDepth: 0 }],
curly: 'error',
'i18next/no-literal-string': 'warn',
'i18next/no-literal-string': 2,
'react/jsx-no-bind': ['error', { allowBind: true }],
'react/jsx-curly-brace-presence': [
'error',
@ -47,7 +43,6 @@ module.exports = {
'no-var': 'error',
'brace-style': 'error',
'prefer-template': 'error',
'import/no-duplicates': 'error',
radix: 'error',
'space-before-blocks': 'error',
'import/prefer-default-export': 'off',
@ -62,18 +57,6 @@ module.exports = {
argsIgnorePattern: '^_',
},
],
// These rules are too strict for normal usage, but are useful for optimizing rerenders
// '@arthurgeron/react-usememo/require-usememo': [
// 'warn',
// {
// strict: false,
// checkHookReturnObject: false,
// fix: { addImports: true },
// checkHookCalls: false,
// },
// ],
// '@arthurgeron/react-usememo/require-memo': 'warn',
'@typescript-eslint/ban-ts-comment': 'warn',
'@typescript-eslint/no-explicit-any': 'warn',
'@typescript-eslint/no-empty-interface': [
@ -82,26 +65,7 @@ module.exports = {
allowSingleExtends: true,
},
],
'@typescript-eslint/consistent-type-imports': [
'error',
{
prefer: 'type-imports',
fixStyle: 'separate-type-imports',
disallowTypeAnnotations: true,
},
],
'@typescript-eslint/no-import-type-side-effects': 'error',
'simple-import-sort/imports': 'error',
'simple-import-sort/exports': 'error',
},
overrides: [
{
files: ['*.stories.tsx'],
rules: {
'i18next/no-literal-string': 'off',
},
},
],
settings: {
react: {
version: 'detect',

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@ -8,7 +8,6 @@ pnpm-debug.log*
lerna-debug.log*
node_modules
.pnpm-store
# We want to distribute the repo
dist
dist/**

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@ -9,8 +9,7 @@ index.html
.yarn/
.yalc/
*.scss
src/services/api/schema.ts
src/services/api/schema.d.ts
static/
src/theme/css/overlayscrollbars.css
src/theme_/css/overlayscrollbars.css
pnpm-lock.yaml

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@ -1,25 +0,0 @@
import { PropsWithChildren, memo, useEffect } from 'react';
import { modelChanged } from '../src/features/parameters/store/generationSlice';
import { useAppDispatch } from '../src/app/store/storeHooks';
import { useGlobalModifiersInit } from '../src/common/hooks/useGlobalModifiers';
/**
* Initializes some state for storybook. Must be in a different component
* so that it is run inside the redux context.
*/
export const ReduxInit = memo((props: PropsWithChildren) => {
const dispatch = useAppDispatch();
useGlobalModifiersInit();
useEffect(() => {
dispatch(
modelChanged({
model_name: 'test_model',
base_model: 'sd-1',
model_type: 'main',
})
);
}, []);
return props.children;
});
ReduxInit.displayName = 'ReduxInit';

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@ -6,7 +6,6 @@ const config: StorybookConfig = {
'@storybook/addon-links',
'@storybook/addon-essentials',
'@storybook/addon-interactions',
'@storybook/addon-storysource',
],
framework: {
name: '@storybook/react-vite',

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@ -1,17 +1,16 @@
import { Preview } from '@storybook/react';
import { themes } from '@storybook/theming';
import i18n from 'i18next';
import React from 'react';
import { initReactI18next } from 'react-i18next';
import { Provider } from 'react-redux';
import GlobalHotkeys from '../src/app/components/GlobalHotkeys';
import ThemeLocaleProvider from '../src/app/components/ThemeLocaleProvider';
import { $baseUrl } from '../src/app/store/nanostores/baseUrl';
import { createStore } from '../src/app/store/store';
import { Container } from '@chakra-ui/react';
// TODO: Disabled for IDE performance issues with our translation JSON
// eslint-disable-next-line @typescript-eslint/ban-ts-comment
// @ts-ignore
import translationEN from '../public/locales/en.json';
import { ReduxInit } from './ReduxInit';
i18n.use(initReactI18next).init({
lng: 'en',
@ -26,21 +25,17 @@ i18n.use(initReactI18next).init({
});
const store = createStore(undefined, false);
$baseUrl.set('http://localhost:9090');
const preview: Preview = {
decorators: [
(Story) => {
return (
<Provider store={store}>
<ThemeLocaleProvider>
<ReduxInit>
<Story />
</ReduxInit>
</ThemeLocaleProvider>
</Provider>
);
},
(Story) => (
<Provider store={store}>
<ThemeLocaleProvider>
<GlobalHotkeys />
<Story />
</ThemeLocaleProvider>
</Provider>
),
],
parameters: {
docs: {

View File

@ -1,15 +0,0 @@
{
"entry": ["src/main.tsx"],
"extensions": [".ts", ".tsx"],
"ignorePatterns": [
"**/node_modules/**",
"dist/**",
"public/**",
"**/*.stories.tsx",
"config/**"
],
"ignoreUnresolved": [],
"ignoreUnimported": ["src/i18.d.ts", "vite.config.ts", "src/vite-env.d.ts"],
"respectGitignore": true,
"ignoreUnused": []
}

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@ -1,6 +1,6 @@
import react from '@vitejs/plugin-react-swc';
import { visualizer } from 'rollup-plugin-visualizer';
import type { PluginOption, UserConfig } from 'vite';
import { PluginOption, UserConfig } from 'vite';
import eslint from 'vite-plugin-eslint';
import tsconfigPaths from 'vite-tsconfig-paths';

View File

@ -1,6 +1,5 @@
import type { UserConfig } from 'vite';
import { commonPlugins } from './common.mjs';
import { UserConfig } from 'vite';
import { commonPlugins } from './common';
export const appConfig: UserConfig = {
base: './',

View File

@ -1,9 +1,8 @@
import path from 'path';
import type { UserConfig } from 'vite';
import cssInjectedByJsPlugin from 'vite-plugin-css-injected-by-js';
import { UserConfig } from 'vite';
import dts from 'vite-plugin-dts';
import { commonPlugins } from './common.mjs';
import cssInjectedByJsPlugin from 'vite-plugin-css-injected-by-js';
import { commonPlugins } from './common';
export const packageConfig: UserConfig = {
base: './',

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@ -1,4 +0,0 @@
<svg width="32" height="32" viewBox="0 0 32 32" fill="none" xmlns="http://www.w3.org/2000/svg">
<rect width="32" height="32" rx="6" fill="#E6FD13"/>
<path d="M19.2378 10.9H25V7H7V10.9H12.7622L19.2378 21.1H25V25H7V21.1H12.7622" stroke="#181818" stroke-width="1.5"/>
</svg>

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@ -1,3 +0,0 @@
<svg width="44" height="44" viewBox="0 0 44 44" fill="none" xmlns="http://www.w3.org/2000/svg">
<path d="M29.1951 10.6667H42V2H2V10.6667H14.8049L29.1951 33.3333H42V42H2V33.3333H14.8049" stroke="#E6FD13" stroke-width="2.8"/>
</svg>

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@ -1,27 +1,24 @@
<!DOCTYPE html>
<html lang="en">
<head>
<meta charset="UTF-8" />
<meta name="viewport" content="width=device-width, initial-scale=1.0" />
<meta http-equiv="Cache-Control" content="no-cache, no-store, must-revalidate">
<meta http-equiv="Pragma" content="no-cache">
<meta http-equiv="Expires" content="0">
<title>InvokeAI - A Stable Diffusion Toolkit</title>
<link rel="shortcut icon" type="icon" href="favicon.ico" />
<style>
html,
body {
padding: 0;
margin: 0;
}
</style>
</head>
<head>
<meta charset="UTF-8" />
<meta name="viewport" content="width=device-width, initial-scale=1.0" />
<meta http-equiv="Cache-Control" content="no-cache, no-store, must-revalidate">
<meta http-equiv="Pragma" content="no-cache">
<meta http-equiv="Expires" content="0">
<title>InvokeAI - A Stable Diffusion Toolkit</title>
<link rel="mask-icon" type="icon" href="favicon-outline.svg" color="#E6FD13" sizes="any" />
<link rel="icon" type="icon" href="favicon-key.svg" />
<style>
html,
body {
padding: 0;
margin: 0;
}
</style>
</head>
<body dir="ltr">
<div id="root"></div>
<script type="module" src="/src/main.tsx"></script>
</body>
</html>
<body dir="ltr">
<div id="root"></div>
<script type="module" src="/src/main.tsx"></script>
</body>
</html>

View File

@ -31,17 +31,13 @@
"lint": "concurrently -g -n eslint,prettier,tsc,madge -c cyan,green,magenta,yellow \"pnpm run lint:eslint\" \"pnpm run lint:prettier\" \"pnpm run lint:tsc\" \"pnpm run lint:madge\"",
"fix": "eslint --fix . && prettier --log-level warn --write .",
"preinstall": "npx only-allow pnpm",
"postinstall": "pnpm run theme",
"postinstall": "patch-package && pnpm run theme",
"theme": "chakra-cli tokens src/theme/theme.ts",
"theme:watch": "chakra-cli tokens src/theme/theme.ts --watch",
"storybook": "storybook dev -p 6006",
"build-storybook": "storybook build",
"unimported": "npx unimported"
"build-storybook": "storybook build"
},
"madge": {
"excludeRegExp": [
"^index.ts$"
],
"detectiveOptions": {
"ts": {
"skipTypeImports": true
@ -57,57 +53,56 @@
"@chakra-ui/layout": "^2.3.1",
"@chakra-ui/portal": "^2.1.0",
"@chakra-ui/react": "^2.8.2",
"@chakra-ui/react-use-size": "^2.1.0",
"@chakra-ui/styled-system": "^2.9.2",
"@chakra-ui/theme-tools": "^2.1.2",
"@dagrejs/graphlib": "^2.1.13",
"@dnd-kit/core": "^6.1.0",
"@dnd-kit/utilities": "^3.2.2",
"@emotion/react": "^11.11.3",
"@emotion/react": "^11.11.1",
"@emotion/styled": "^11.11.0",
"@fontsource-variable/inter": "^5.0.16",
"@mantine/form": "6.0.21",
"@mantine/core": "^6.0.19",
"@mantine/form": "^6.0.19",
"@mantine/hooks": "^6.0.19",
"@nanostores/react": "^0.7.1",
"@reduxjs/toolkit": "2.0.1",
"@reduxjs/toolkit": "^2.0.1",
"@roarr/browser-log-writer": "^1.3.0",
"chakra-react-select": "^4.7.6",
"@storybook/manager-api": "^7.6.4",
"@storybook/theming": "^7.6.4",
"compare-versions": "^6.1.0",
"dateformat": "^5.0.3",
"framer-motion": "^10.17.9",
"i18next": "^23.7.16",
"framer-motion": "^10.16.15",
"i18next": "^23.7.8",
"i18next-http-backend": "^2.4.2",
"idb-keyval": "^6.2.1",
"jsondiffpatch": "^0.6.0",
"konva": "^9.3.0",
"konva": "^9.2.3",
"lodash-es": "^4.17.21",
"nanostores": "^0.9.5",
"new-github-issue-url": "^1.0.0",
"overlayscrollbars": "^2.4.6",
"overlayscrollbars": "^2.4.5",
"overlayscrollbars-react": "^0.5.3",
"patch-package": "^8.0.0",
"query-string": "^8.1.0",
"react": "^18.2.0",
"react-colorful": "^5.6.1",
"react-dom": "^18.2.0",
"react-dropzone": "^14.2.3",
"react-error-boundary": "^4.0.12",
"react-hook-form": "^7.49.2",
"react-hotkeys-hook": "4.4.3",
"react-i18next": "^14.0.0",
"react-error-boundary": "^4.0.11",
"react-hotkeys-hook": "4.4.1",
"react-i18next": "^13.5.0",
"react-icons": "^4.12.0",
"react-konva": "^18.2.10",
"react-redux": "9.0.4",
"react-resizable-panels": "^1.0.7",
"react-select": "5.8.0",
"react-textarea-autosize": "^8.5.3",
"react-redux": "^9.0.2",
"react-resizable-panels": "^0.0.55",
"react-use": "^17.4.2",
"react-virtuoso": "^4.6.2",
"reactflow": "^11.10.1",
"redux-dynamic-middlewares": "^2.2.0",
"redux-remember": "^5.1.0",
"redux-remember": "^5.0.0",
"roarr": "^7.21.0",
"serialize-error": "^11.0.3",
"socket.io-client": "^4.7.3",
"type-fest": "^4.9.0",
"socket.io-client": "^4.7.2",
"type-fest": "^4.8.3",
"use-debounce": "^10.0.0",
"use-image": "^1.1.1",
"uuid": "^9.0.1",
@ -122,56 +117,44 @@
"ts-toolbelt": "^9.6.0"
},
"devDependencies": {
"@arthurgeron/eslint-plugin-react-usememo": "^2.2.3",
"@chakra-ui/cli": "^2.4.1",
"@storybook/addon-docs": "^7.6.7",
"@storybook/addon-essentials": "^7.6.7",
"@storybook/addon-interactions": "^7.6.7",
"@storybook/addon-links": "^7.6.7",
"@storybook/addon-storysource": "^7.6.7",
"@storybook/blocks": "^7.6.7",
"@storybook/manager-api": "^7.6.7",
"@storybook/react": "^7.6.7",
"@storybook/react-vite": "^7.6.7",
"@storybook/test": "^7.6.7",
"@storybook/theming": "^7.6.7",
"@storybook/addon-essentials": "^7.6.4",
"@storybook/addon-interactions": "^7.6.4",
"@storybook/addon-links": "^7.6.4",
"@storybook/blocks": "^7.6.4",
"@storybook/react": "^7.6.4",
"@storybook/react-vite": "^7.6.4",
"@storybook/test": "^7.6.4",
"@types/dateformat": "^5.0.2",
"@types/lodash-es": "^4.17.12",
"@types/node": "^20.10.7",
"@types/react": "^18.2.47",
"@types/react-dom": "^18.2.18",
"@types/node": "^20.9.0",
"@types/react": "^18.2.37",
"@types/react-dom": "^18.2.17",
"@types/uuid": "^9.0.7",
"@typescript-eslint/eslint-plugin": "^6.18.0",
"@typescript-eslint/parser": "^6.18.0",
"@typescript-eslint/eslint-plugin": "^6.13.2",
"@typescript-eslint/parser": "^6.13.2",
"@vitejs/plugin-react-swc": "^3.5.0",
"concurrently": "^8.2.2",
"eslint": "^8.56.0",
"eslint": "^8.55.0",
"eslint-config-prettier": "^9.1.0",
"eslint-plugin-i18next": "^6.0.3",
"eslint-plugin-import": "^2.29.1",
"eslint-plugin-path": "^1.2.3",
"eslint-plugin-path": "^1.2.2",
"eslint-plugin-react": "^7.33.2",
"eslint-plugin-react-hooks": "^4.6.0",
"eslint-plugin-simple-import-sort": "^10.0.0",
"eslint-plugin-storybook": "^0.6.15",
"eslint-plugin-unused-imports": "^3.0.0",
"madge": "^6.1.0",
"openapi-types": "^12.1.3",
"openapi-typescript": "^6.7.3",
"prettier": "^3.1.1",
"rollup-plugin-visualizer": "^5.12.0",
"storybook": "^7.6.7",
"openapi-typescript": "^6.7.2",
"prettier": "^3.1.0",
"rollup-plugin-visualizer": "^5.10.0",
"storybook": "^7.6.4",
"ts-toolbelt": "^9.6.0",
"typescript": "^5.3.3",
"vite": "^5.0.11",
"vite-plugin-css-injected-by-js": "^3.3.1",
"vite-plugin-dts": "^3.7.0",
"vite": "^4.5.1",
"vite-plugin-css-injected-by-js": "^3.3.0",
"vite-plugin-dts": "^3.6.4",
"vite-plugin-eslint": "^1.8.1",
"vite-tsconfig-paths": "^4.2.3"
},
"pnpm": {
"patchedDependencies": {
"reselect@5.0.1": "patches/reselect@5.0.1.patch"
}
"vite-tsconfig-paths": "^4.2.2"
}
}

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@ -83,6 +83,10 @@
"title": "خيارات التثبيت",
"desc": "ثبت لوحة الخيارات"
},
"toggleViewer": {
"title": "تبديل العارض",
"desc": "فتح وإغلاق مشاهد الصور"
},
"toggleGallery": {
"title": "تبديل المعرض",
"desc": "فتح وإغلاق درابزين المعرض"
@ -143,6 +147,10 @@
"title": "الصورة التالية",
"desc": "عرض الصورة التالية في الصالة"
},
"toggleGalleryPin": {
"title": "تبديل تثبيت الصالة",
"desc": "يثبت ويفتح تثبيت الصالة على الواجهة الرسومية"
},
"increaseGalleryThumbSize": {
"title": "زيادة حجم صورة الصالة",
"desc": "يزيد حجم الصور المصغرة في الصالة"

View File

@ -168,6 +168,10 @@
"title": "Optionen anheften",
"desc": "Anheften des Optionsfeldes"
},
"toggleViewer": {
"title": "Bildbetrachter umschalten",
"desc": "Bildbetrachter öffnen und schließen"
},
"toggleGallery": {
"title": "Galerie umschalten",
"desc": "Öffnen und Schließen des Galerie-Schubfachs"
@ -228,6 +232,10 @@
"title": "Nächstes Bild",
"desc": "Nächstes Bild in Galerie anzeigen"
},
"toggleGalleryPin": {
"title": "Galerie anheften umschalten",
"desc": "Heftet die Galerie an die Benutzeroberfläche bzw. löst die sie"
},
"increaseGalleryThumbSize": {
"title": "Größe der Galeriebilder erhöhen",
"desc": "Vergrößert die Galerie-Miniaturansichten"
@ -752,6 +760,7 @@
"w": "W",
"addControlNet": "$t(common.controlNet) hinzufügen",
"none": "Kein",
"incompatibleBaseModel": "Inkompatibles Basismodell:",
"enableControlnet": "Aktiviere ControlNet",
"detectResolution": "Auflösung erkennen",
"controlNetT2IMutexDesc": "$t(common.controlNet) und $t(common.t2iAdapter) zur gleichen Zeit wird nicht unterstützt.",

View File

@ -50,33 +50,9 @@
"uncategorized": "Uncategorized",
"downloadBoard": "Download Board"
},
"accordions": {
"generation": {
"title": "Generation",
"modelTab": "Model",
"conceptsTab": "Concepts"
},
"image": {
"title": "Image"
},
"advanced": {
"title": "Advanced"
},
"control": {
"title": "Control",
"controlAdaptersTab": "Control Adapters",
"ipTab": "Image Prompts"
},
"compositing": {
"title": "Compositing",
"coherenceTab": "Coherence Pass",
"infillTab": "Infill"
}
},
"common": {
"accept": "Accept",
"advanced": "Advanced",
"advancedOptions": "Advanced Options",
"ai": "ai",
"areYouSure": "Are you sure?",
"auto": "Auto",
@ -86,7 +62,6 @@
"copyError": "$t(gallery.copy) Error",
"close": "Close",
"on": "On",
"or": "or",
"checkpoint": "Checkpoint",
"communityLabel": "Community",
"controlNet": "ControlNet",
@ -104,7 +79,6 @@
"file": "File",
"folder": "Folder",
"format": "format",
"free": "Free",
"generate": "Generate",
"githubLabel": "Github",
"hotkeysLabel": "Hotkeys",
@ -157,7 +131,6 @@
"save": "Save",
"saveAs": "Save As",
"settingsLabel": "Settings",
"preferencesLabel": "Preferences",
"simple": "Simple",
"somethingWentWrong": "Something went wrong",
"statusConnected": "Connected",
@ -248,6 +221,7 @@
"colorMapTileSize": "Tile Size",
"importImageFromCanvas": "Import Image From Canvas",
"importMaskFromCanvas": "Import Mask From Canvas",
"incompatibleBaseModel": "Incompatible base model:",
"lineart": "Lineart",
"lineartAnime": "Lineart Anime",
"lineartAnimeDescription": "Anime-style lineart processing",
@ -272,7 +246,6 @@
"prompt": "Prompt",
"resetControlImage": "Reset Control Image",
"resize": "Resize",
"resizeSimple": "Resize (Simple)",
"resizeMode": "Resize Mode",
"safe": "Safe",
"saveControlImage": "Save Control Image",
@ -311,7 +284,7 @@
"queue": "Queue",
"queueFront": "Add to Front of Queue",
"queueBack": "Add to Queue",
"queueCountPrediction": "{{promptsCount}} prompts × {{iterations}} iterations -> {{count}} generations",
"queueCountPrediction": "Add {{predicted}} to Queue",
"queueMaxExceeded": "Max of {{max_queue_size}} exceeded, would skip {{skip}}",
"queuedCount": "{{pending}} Pending",
"queueTotal": "{{total}} Total",
@ -367,8 +340,7 @@
"back": "back",
"batchFailedToQueue": "Failed to Queue Batch",
"graphQueued": "Graph queued",
"graphFailedToQueue": "Failed to queue graph",
"openQueue": "Open Queue"
"graphFailedToQueue": "Failed to queue graph"
},
"invocationCache": {
"invocationCache": "Invocation Cache",
@ -428,9 +400,6 @@
"problemDeletingImagesDesc": "One or more images could not be deleted"
},
"hotkeys": {
"searchHotkeys": "Search Hotkeys",
"clearSearch": "Clear Search",
"noHotkeysFound": "No Hotkeys Found",
"acceptStagingImage": {
"desc": "Accept Current Staging Area Image",
"title": "Accept Staging Image"
@ -439,15 +408,11 @@
"desc": "Opens the add node menu",
"title": "Add Nodes"
},
"appHotkeys": "App",
"appHotkeys": "App Hotkeys",
"cancel": {
"desc": "Cancel current queue item",
"desc": "Cancel image generation",
"title": "Cancel"
},
"cancelAndClear": {
"desc": "Cancel current queue item and clear all pending items",
"title": "Cancel and Clear"
},
"changeTabs": {
"desc": "Switch to another workspace",
"title": "Change Tabs"
@ -504,8 +469,8 @@
"desc": "Focus the prompt input area",
"title": "Focus Prompt"
},
"galleryHotkeys": "Gallery",
"generalHotkeys": "General",
"galleryHotkeys": "Gallery Hotkeys",
"generalHotkeys": "General Hotkeys",
"hideMask": {
"desc": "Hide and unhide mask",
"title": "Hide Mask"
@ -526,7 +491,7 @@
"desc": "Generate an image",
"title": "Invoke"
},
"keyboardShortcuts": "Hotkeys",
"keyboardShortcuts": "Keyboard Shortcuts",
"maximizeWorkSpace": {
"desc": "Close panels and maximize work area",
"title": "Maximize Workspace"
@ -547,7 +512,7 @@
"desc": "Next Staging Area Image",
"title": "Next Staging Image"
},
"nodesHotkeys": "Nodes",
"nodesHotkeys": "Nodes Hotkeys",
"pinOptions": {
"desc": "Pin the options panel",
"title": "Pin Options"
@ -616,31 +581,31 @@
"desc": "Open and close the gallery drawer",
"title": "Toggle Gallery"
},
"toggleOptions": {
"desc": "Open and close the options panel",
"title": "Toggle Options"
},
"toggleOptionsAndGallery": {
"desc": "Open and close the options and gallery panels",
"title": "Toggle Options and Gallery"
},
"resetOptionsAndGallery": {
"desc": "Resets the options and gallery panels",
"title": "Reset Options and Gallery"
"toggleGalleryPin": {
"desc": "Pins and unpins the gallery to the UI",
"title": "Toggle Gallery Pin"
},
"toggleLayer": {
"desc": "Toggles mask/base layer selection",
"title": "Toggle Layer"
},
"toggleOptions": {
"desc": "Open and close the options panel",
"title": "Toggle Options"
},
"toggleSnap": {
"desc": "Toggles Snap to Grid",
"title": "Toggle Snap"
},
"toggleViewer": {
"desc": "Open and close Image Viewer",
"title": "Toggle Viewer"
},
"undoStroke": {
"desc": "Undo a brush stroke",
"title": "Undo Stroke"
},
"unifiedCanvasHotkeys": "Unified Canvas",
"unifiedCanvasHotkeys": "Unified Canvas Hotkeys",
"upscale": {
"desc": "Upscale the current image",
"title": "Upscale"
@ -823,23 +788,17 @@
},
"models": {
"addLora": "Add LoRA",
"allLoRAsAdded": "All LoRAs added",
"loraAlreadyAdded": "LoRA already added",
"esrganModel": "ESRGAN Model",
"loading": "loading",
"incompatibleBaseModel": "Incompatible base model",
"noMainModelSelected": "No main model selected",
"noLoRAsAvailable": "No LoRAs available",
"noLoRAsLoaded": "No LoRAs Loaded",
"noMatchingLoRAs": "No matching LoRAs",
"noMatchingModels": "No matching Models",
"noModelsAvailable": "No models available",
"lora": "LoRA",
"selectLoRA": "Select a LoRA",
"selectModel": "Select a Model",
"noLoRAsInstalled": "No LoRAs installed",
"noRefinerModelsInstalled": "No SDXL Refiner models installed",
"defaultVAE": "Default VAE"
"noRefinerModelsInstalled": "No SDXL Refiner models installed"
},
"nodes": {
"addNode": "Add Node",
@ -1078,14 +1037,8 @@
"prototypeDesc": "This invocation is a prototype. It may have breaking changes during app updates and may be removed at any time."
},
"parameters": {
"aspect": "Aspect",
"aspectRatio": "Aspect Ratio",
"aspectRatioFree": "Free",
"lockAspectRatio": "Lock Aspect Ratio",
"swapDimensions": "Swap Dimensions",
"setToOptimalSize": "Optimize size for model",
"setToOptimalSizeTooSmall": "$t(parameters.setToOptimalSize) (may be too small)",
"setToOptimalSizeTooLarge": "$t(parameters.setToOptimalSize) (may be too large)",
"boundingBoxHeader": "Bounding Box",
"boundingBoxHeight": "Bounding Box Height",
"boundingBoxWidth": "Bounding Box Width",
@ -1124,7 +1077,6 @@
"imageFit": "Fit Initial Image To Output Size",
"images": "Images",
"imageToImage": "Image to Image",
"imageSize": "Image Size",
"img2imgStrength": "Image To Image Strength",
"infillMethod": "Infill Method",
"infillScalingHeader": "Infill and Scaling",
@ -1139,7 +1091,7 @@
"noControlImageForControlAdapter": "Control Adapter #{{number}} has no control image",
"noInitialImageSelected": "No initial image selected",
"noModelForControlAdapter": "Control Adapter #{{number}} has no model selected.",
"incompatibleBaseModelForControlAdapter": "Control Adapter #{{number}} model is incompatible with main model.",
"incompatibleBaseModelForControlAdapter": "Control Adapter #{{number}} model is invalid with main model.",
"noModelSelected": "No model selected",
"noPrompts": "No prompts generated",
"noNodesInGraph": "No nodes in graph",
@ -1175,8 +1127,8 @@
"seamCorrectionHeader": "Seam Correction",
"seamHighThreshold": "High",
"seamlessTiling": "Seamless Tiling",
"seamlessXAxis": "Seamless Tiling X Axis",
"seamlessYAxis": "Seamless Tiling Y Axis",
"seamlessXAxis": "X Axis",
"seamlessYAxis": "Y Axis",
"seamlessX": "Seamless X",
"seamlessY": "Seamless Y",
"seamlessX&Y": "Seamless X & Y",
@ -1219,7 +1171,6 @@
},
"dynamicPrompts": {
"combinatorial": "Combinatorial Generation",
"showDynamicPrompts": "Show Dynamic Prompts",
"dynamicPrompts": "Dynamic Prompts",
"enableDynamicPrompts": "Enable Dynamic Prompts",
"maxPrompts": "Max Prompts",
@ -1232,13 +1183,11 @@
"perIterationDesc": "Use a different seed for each iteration",
"perPromptLabel": "Seed per Image",
"perPromptDesc": "Use a different seed for each image"
},
"loading": "Generating Dynamic Prompts..."
}
},
"sdxl": {
"cfgScale": "CFG Scale",
"concatPromptStyle": "Linking Prompt & Style",
"freePromptStyle": "Manual Style Prompting",
"concatPromptStyle": "Concatenate Prompt & Style",
"denoisingStrength": "Denoising Strength",
"loading": "Loading...",
"negAestheticScore": "Negative Aesthetic Score",

View File

@ -127,6 +127,10 @@
"title": "Fijar opciones",
"desc": "Fijar el panel de opciones"
},
"toggleViewer": {
"title": "Alternar visor",
"desc": "Mostar y ocultar el visor de imágenes"
},
"toggleGallery": {
"title": "Alternar galería",
"desc": "Mostar y ocultar la galería de imágenes"
@ -187,6 +191,10 @@
"title": "Imagen siguiente",
"desc": "Muetra la imagen siguiente en la galería"
},
"toggleGalleryPin": {
"title": "Alternar fijado de galería",
"desc": "Fijar o desfijar la galería en la interfaz"
},
"increaseGalleryThumbSize": {
"title": "Aumentar imagen en galería",
"desc": "Aumenta el tamaño de las miniaturas de la galería"
@ -719,6 +727,9 @@
"showMinimapnodes": "Mostrar el minimapa",
"reloadNodeTemplates": "Recargar las plantillas de nodos",
"loadWorkflow": "Cargar el flujo de trabajo",
"resetWorkflow": "Reiniciar e flujo de trabajo",
"resetWorkflowDesc": "¿Está seguro de que deseas restablecer este flujo de trabajo?",
"resetWorkflowDesc2": "Al reiniciar el flujo de trabajo se borrarán todos los nodos, aristas y detalles del flujo de trabajo.",
"downloadWorkflow": "Descargar el flujo de trabajo en un archivo JSON"
}
}

View File

@ -96,6 +96,10 @@
"title": "Epinglage des options",
"desc": "Epingler le panneau d'options"
},
"toggleViewer": {
"title": "Affichage de la visionneuse",
"desc": "Afficher et masquer la visionneuse d'image"
},
"toggleGallery": {
"title": "Affichage de la galerie",
"desc": "Afficher et masquer la galerie"
@ -156,6 +160,10 @@
"title": "Image suivante",
"desc": "Afficher l'image suivante dans la galerie"
},
"toggleGalleryPin": {
"title": "Activer/désactiver l'épinglage de la galerie",
"desc": "Épingle ou dépingle la galerie à l'interface"
},
"increaseGalleryThumbSize": {
"title": "Augmenter la taille des miniatures de la galerie",
"desc": "Augmente la taille des miniatures de la galerie"

View File

@ -192,6 +192,10 @@
"title": "הצמד הגדרות",
"desc": "הצמד את פאנל ההגדרות"
},
"toggleViewer": {
"title": "הצג את חלון ההצגה",
"desc": "פתח וסגור את מציג התמונות"
},
"changeTabs": {
"title": "החלף לשוניות",
"desc": "החלף לאיזור עבודה אחר"
@ -232,6 +236,10 @@
"title": "תמונה קודמת",
"desc": "הצג את התמונה הקודמת בגלריה"
},
"toggleGalleryPin": {
"title": "הצג את מצמיד הגלריה",
"desc": "הצמדה וביטול הצמדה של הגלריה לממשק המשתמש"
},
"decreaseGalleryThumbSize": {
"title": "הקטנת גודל תמונת גלריה",
"desc": "מקטין את גודל התמונות הממוזערות של הגלריה"

View File

@ -113,10 +113,7 @@
"orderBy": "Ordinato per",
"nextPage": "Pagina successiva",
"saveAs": "Salva come",
"unsaved": "Non salvato",
"direction": "Direzione",
"advancedOptions": "Opzioni avanzate",
"free": "Libero"
"unsaved": "Non salvato"
},
"gallery": {
"generations": "Generazioni",
@ -134,7 +131,7 @@
"noImagesInGallery": "Nessuna immagine da visualizzare",
"deleteImage": "Elimina l'immagine",
"deleteImagePermanent": "Le immagini eliminate non possono essere ripristinate.",
"deleteImageBin": "Le immagini eliminate verranno spostate nel cestino del tuo sistema operativo.",
"deleteImageBin": "Le immagini eliminate verranno spostate nel Cestino del tuo sistema operativo.",
"assets": "Risorse",
"autoAssignBoardOnClick": "Assegna automaticamente la bacheca al clic",
"featuresWillReset": "Se elimini questa immagine, quelle funzionalità verranno immediatamente ripristinate.",
@ -159,18 +156,18 @@
"problemDeletingImages": "Problema durante l'eliminazione delle immagini"
},
"hotkeys": {
"keyboardShortcuts": "Tasti di scelta rapida",
"appHotkeys": "Applicazione",
"generalHotkeys": "Generale",
"galleryHotkeys": "Galleria",
"unifiedCanvasHotkeys": "Tela Unificata",
"keyboardShortcuts": "Tasti rapidi",
"appHotkeys": "Tasti di scelta rapida dell'applicazione",
"generalHotkeys": "Tasti di scelta rapida generali",
"galleryHotkeys": "Tasti di scelta rapida della galleria",
"unifiedCanvasHotkeys": "Tasti di scelta rapida Tela Unificata",
"invoke": {
"title": "Invoke",
"desc": "Genera un'immagine"
},
"cancel": {
"title": "Annulla",
"desc": "Annulla l'elemento della coda corrente"
"desc": "Annulla la generazione dell'immagine"
},
"focusPrompt": {
"title": "Metti a fuoco il Prompt",
@ -184,8 +181,12 @@
"title": "Appunta le opzioni",
"desc": "Blocca il pannello delle opzioni"
},
"toggleViewer": {
"title": "Attiva/disattiva visualizzatore",
"desc": "Apre e chiude il visualizzatore immagini"
},
"toggleGallery": {
"title": "Attiva/disattiva galleria",
"title": "Attiva/disattiva Galleria",
"desc": "Apre e chiude il pannello della galleria"
},
"maximizeWorkSpace": {
@ -244,6 +245,10 @@
"title": "Immagine successiva",
"desc": "Visualizza l'immagine successiva nella galleria"
},
"toggleGalleryPin": {
"title": "Attiva/disattiva il blocco della galleria",
"desc": "Blocca/sblocca la galleria dall'interfaccia utente"
},
"increaseGalleryThumbSize": {
"title": "Aumenta dimensione immagini nella galleria",
"desc": "Aumenta la dimensione delle miniature della galleria"
@ -356,26 +361,11 @@
"title": "Accetta l'immagine della sessione",
"desc": "Accetta l'immagine dell'area della sessione corrente"
},
"nodesHotkeys": "Nodi",
"nodesHotkeys": "Tasti di scelta rapida dei Nodi",
"addNodes": {
"title": "Aggiungi Nodi",
"desc": "Apre il menu Aggiungi Nodi"
},
"cancelAndClear": {
"desc": "Annulla l'elemento della coda corrente e cancella tutti gli elementi in sospeso",
"title": "Annulla e cancella"
},
"resetOptionsAndGallery": {
"title": "Ripristina Opzioni e Galleria",
"desc": "Reimposta le opzioni e i pannelli della galleria"
},
"searchHotkeys": "Cerca tasti di scelta rapida",
"noHotkeysFound": "Nessun tasto di scelta rapida trovato",
"toggleOptionsAndGallery": {
"desc": "Apre e chiude le opzioni e i pannelli della galleria",
"title": "Attiva/disattiva le Opzioni e la Galleria"
},
"clearSearch": "Cancella ricerca"
}
},
"modelManager": {
"modelManager": "Gestione Modelli",
@ -590,8 +580,8 @@
"hidePreview": "Nascondi l'anteprima",
"showPreview": "Mostra l'anteprima",
"noiseSettings": "Rumore",
"seamlessXAxis": "Piastrella senza cucitura Asse X",
"seamlessYAxis": "Piastrella senza cucitura Asse Y",
"seamlessXAxis": "Asse X",
"seamlessYAxis": "Asse Y",
"scheduler": "Campionatore",
"boundingBoxWidth": "Larghezza riquadro di delimitazione",
"boundingBoxHeight": "Altezza riquadro di delimitazione",
@ -651,14 +641,7 @@
"unmasked": "No maschera",
"cfgRescaleMultiplier": "Moltiplicatore riscala CFG",
"cfgRescale": "Riscala CFG",
"useSize": "Usa Dimensioni",
"setToOptimalSize": "Ottimizza le dimensioni per il modello",
"setToOptimalSizeTooSmall": "$t(parameters.setToOptimalSize) (potrebbe essere troppo piccolo)",
"imageSize": "Dimensione dell'immagine",
"lockAspectRatio": "Blocca proporzioni",
"swapDimensions": "Scambia dimensioni",
"aspect": "Aspetto",
"setToOptimalSizeTooLarge": "$t(parameters.setToOptimalSize) (potrebbe essere troppo grande)"
"useSize": "Usa Dimensioni"
},
"settings": {
"models": "Modelli",
@ -915,8 +898,11 @@
"zoomInNodes": "Ingrandire",
"fitViewportNodes": "Adatta vista",
"showGraphNodes": "Mostra sovrapposizione grafico",
"resetWorkflowDesc2": "Il ripristino dell'editor del flusso di lavoro cancellerà tutti i nodi, le connessioni e i dettagli del flusso di lavoro. I flussi di lavoro salvati non saranno interessati.",
"reloadNodeTemplates": "Ricarica i modelli di nodo",
"loadWorkflow": "Importa flusso di lavoro JSON",
"resetWorkflow": "Reimposta l'editor del flusso di lavoro",
"resetWorkflowDesc": "Sei sicuro di voler reimpostare l'editor del flusso di lavoro?",
"downloadWorkflow": "Esporta flusso di lavoro JSON",
"scheduler": "Campionatore",
"addNode": "Aggiungi nodo",
@ -1126,11 +1112,7 @@
"deletedInvalidEdge": "Eliminata connessione non valida {{source}} -> {{target}}",
"unknownInput": "Input sconosciuto: {{name}}",
"prototypeDesc": "Questa invocazione è un prototipo. Potrebbe subire modifiche sostanziali durante gli aggiornamenti dell'app e potrebbe essere rimossa in qualsiasi momento.",
"betaDesc": "Questa invocazione è in versione beta. Fino a quando non sarà stabile, potrebbe subire modifiche importanti durante gli aggiornamenti dell'app. Abbiamo intenzione di supportare questa invocazione a lungo termine.",
"newWorkflow": "Nuovo flusso di lavoro",
"newWorkflowDesc": "Creare un nuovo flusso di lavoro?",
"newWorkflowDesc2": "Il flusso di lavoro attuale presenta modifiche non salvate.",
"unsupportedAnyOfLength": "unione di troppi elementi ({{count}})"
"betaDesc": "Questa invocazione è in versione beta. Fino a quando non sarà stabile, potrebbe subire modifiche importanti durante gli aggiornamenti dell'app. Abbiamo intenzione di supportare questa invocazione a lungo termine."
},
"boards": {
"autoAddBoard": "Aggiungi automaticamente bacheca",
@ -1194,6 +1176,7 @@
"w": "W",
"processor": "Processore",
"none": "Nessuno",
"incompatibleBaseModel": "Modello base incompatibile:",
"pidiDescription": "Elaborazione immagini PIDI",
"fill": "Riempie",
"colorMapDescription": "Genera una mappa dei colori dall'immagine",
@ -1229,13 +1212,12 @@
"minConfidence": "Confidenza minima",
"scribble": "Scribble",
"amult": "Angolo di illuminazione",
"coarse": "Approssimativo",
"resizeSimple": "Ridimensiona (semplice)"
"coarse": "Approssimativo"
},
"queue": {
"queueFront": "Aggiungi all'inizio della coda",
"queueBack": "Aggiungi alla coda",
"queueCountPrediction": "{{promptsCount}} prompt × {{iterations}} iterazioni -> {{count}} generazioni",
"queueCountPrediction": "Aggiungi {{predicted}} alla coda",
"queue": "Coda",
"status": "Stato",
"pruneSucceeded": "Rimossi {{item_count}} elementi completati dalla coda",
@ -1293,8 +1275,7 @@
"graphFailedToQueue": "Impossibile mettere in coda il grafico",
"queueMaxExceeded": "È stato superato il limite massimo di {{max_queue_size}} e {{skip}} elementi verrebbero saltati",
"batchFieldValues": "Valori Campi Lotto",
"time": "Tempo",
"openQueue": "Apri coda"
"time": "Tempo"
},
"embedding": {
"noMatchingEmbedding": "Nessun Incorporamento corrispondente",
@ -1314,12 +1295,7 @@
"noLoRAsInstalled": "Nessun LoRA installato",
"esrganModel": "Modello ESRGAN",
"addLora": "Aggiungi LoRA",
"noLoRAsLoaded": "Nessun LoRA caricato",
"noMainModelSelected": "Nessun modello principale selezionato",
"allLoRAsAdded": "Tutti i LoRA aggiunti",
"defaultVAE": "VAE predefinito",
"incompatibleBaseModel": "Modello base incompatibile",
"loraAlreadyAdded": "LoRA già aggiunto"
"noLoRAsLoaded": "Nessuna LoRA caricata"
},
"invocationCache": {
"disable": "Disabilita",
@ -1353,9 +1329,7 @@
"promptsWithCount_many": "{{count}} Prompt",
"promptsWithCount_other": "{{count}} Prompt",
"dynamicPrompts": "Prompt dinamici",
"promptsPreview": "Anteprima dei prompt",
"showDynamicPrompts": "Mostra prompt dinamici",
"loading": "Generazione prompt dinamici..."
"promptsPreview": "Anteprima dei prompt"
},
"popovers": {
"paramScheduler": {
@ -1581,7 +1555,7 @@
"scheduler": "Campionatore",
"noModelsAvailable": "Nessun modello disponibile",
"denoisingStrength": "Forza di riduzione del rumore",
"concatPromptStyle": "Collega Prompt & Stile",
"concatPromptStyle": "Concatena Prompt & Stile",
"loading": "Caricamento...",
"steps": "Passi",
"refinerStart": "Inizio Affinamento",
@ -1592,8 +1566,7 @@
"useRefiner": "Utilizza l'affinatore",
"refinermodel": "Modello Affinatore",
"posAestheticScore": "Punteggio estetico positivo",
"posStylePrompt": "Prompt Stile positivo",
"freePromptStyle": "Prompt di stile manuale"
"posStylePrompt": "Prompt Stile positivo"
},
"metadata": {
"initImage": "Immagine iniziale",
@ -1646,6 +1619,7 @@
"saveWorkflow": "Salva flusso di lavoro",
"openWorkflow": "Apri flusso di lavoro",
"clearWorkflowSearchFilter": "Cancella il filtro di ricerca del flusso di lavoro",
"workflowEditorReset": "Reimpostazione dell'editor del flusso di lavoro",
"workflowLibrary": "Libreria",
"noRecentWorkflows": "Nessun flusso di lavoro recente",
"workflowSaved": "Flusso di lavoro salvato",
@ -1659,35 +1633,9 @@
"deleteWorkflow": "Elimina flusso di lavoro",
"workflows": "Flussi di lavoro",
"noDescription": "Nessuna descrizione",
"userWorkflows": "I miei flussi di lavoro",
"newWorkflowCreated": "Nuovo flusso di lavoro creato",
"downloadWorkflow": "Salva su file",
"uploadWorkflow": "Carica da file"
"userWorkflows": "I miei flussi di lavoro"
},
"app": {
"storeNotInitialized": "Il negozio non è inizializzato"
},
"accordions": {
"compositing": {
"infillTab": "Riempimento",
"coherenceTab": "Passaggio di coerenza",
"title": "Composizione"
},
"control": {
"controlAdaptersTab": "Adattatori di Controllo",
"ipTab": "Prompt immagine",
"title": "Controllo"
},
"generation": {
"title": "Generazione",
"conceptsTab": "Concetti",
"modelTab": "Modello"
},
"advanced": {
"title": "Avanzate"
},
"image": {
"title": "Immagine"
}
}
}

View File

@ -133,6 +133,10 @@
"title": "ピン",
"desc": "オプションパネルを固定"
},
"toggleViewer": {
"title": "ビュワーのトグル",
"desc": "ビュワーを開閉"
},
"toggleGallery": {
"title": "ギャラリーのトグル",
"desc": "ギャラリードロワーの開閉"
@ -193,6 +197,10 @@
"title": "次の画像",
"desc": "ギャラリー内の1つ後の画像を表示"
},
"toggleGalleryPin": {
"title": "ギャラリードロワーの固定",
"desc": "ギャラリーをUIにピン留め/解除"
},
"increaseGalleryThumbSize": {
"title": "ギャラリーの画像を拡大",
"desc": "ギャラリーのサムネイル画像を拡大"
@ -582,6 +590,7 @@
"processor": "プロセッサー",
"addControlNet": "$t(common.controlNet)を追加",
"none": "なし",
"incompatibleBaseModel": "互換性のないベースモデル:",
"enableControlnet": "コントロールネットを有効化",
"detectResolution": "検出解像度",
"controlNetT2IMutexDesc": "$t(common.controlNet)と$t(common.t2iAdapter)の同時使用は現在サポートされていません。",

View File

@ -15,7 +15,7 @@
"langBrPortuguese": "Português do Brasil",
"langRussian": "Русский",
"langSpanish": "Español",
"nodes": "Workflow Editor",
"nodes": "노드",
"nodesDesc": "이미지 생성을 위한 노드 기반 시스템은 현재 개발 중입니다. 이 놀라운 기능에 대한 업데이트를 계속 지켜봐 주세요.",
"postProcessing": "후처리",
"postProcessDesc2": "보다 진보된 후처리 작업을 위한 전용 UI가 곧 출시될 예정입니다.",
@ -25,7 +25,7 @@
"trainingDesc2": "InvokeAI는 이미 메인 스크립트를 사용한 Textual Inversion를 이용한 Custom embedding 학습을 지원하고 있습니다.",
"upload": "업로드",
"close": "닫기",
"load": "불러오기",
"load": "로드",
"back": "뒤로 가기",
"statusConnected": "연결됨",
"statusDisconnected": "연결 끊김",
@ -58,69 +58,7 @@
"statusGeneratingImageToImage": "이미지->이미지 생성",
"statusProcessingComplete": "처리 완료",
"statusIterationComplete": "반복(Iteration) 완료",
"statusSavingImage": "이미지 저장",
"t2iAdapter": "T2I 어댑터",
"communityLabel": "커뮤니티",
"txt2img": "텍스트->이미지",
"dontAskMeAgain": "다시 묻지 마세요",
"loadingInvokeAI": "Invoke AI 불러오는 중",
"checkpoint": "체크포인트",
"format": "형식",
"unknown": "알려지지 않음",
"areYouSure": "확실하나요?",
"folder": "폴더",
"inpaint": "inpaint",
"updated": "업데이트 됨",
"on": "켜기",
"save": "저장",
"langPortuguese": "Português",
"created": "생성됨",
"nodeEditor": "Node Editor",
"error": "에러",
"prevPage": "이전 페이지",
"ipAdapter": "IP 어댑터",
"controlAdapter": "제어 어댑터",
"installed": "설치됨",
"accept": "수락",
"ai": "인공지능",
"auto": "자동",
"file": "파일",
"openInNewTab": "새 탭에서 열기",
"delete": "삭제",
"template": "템플릿",
"cancel": "취소",
"controlNet": "컨트롤넷",
"outputs": "결과물",
"unknownError": "알려지지 않은 에러",
"statusProcessing": "처리 중",
"linear": "선형",
"imageFailedToLoad": "이미지를 로드할 수 없음",
"direction": "방향",
"data": "데이터",
"somethingWentWrong": "뭔가 잘못됐어요",
"imagePrompt": "이미지 프롬프트",
"modelManager": "Model Manager",
"lightMode": "라이트 모드",
"safetensors": "Safetensors",
"outpaint": "outpaint",
"langKorean": "한국어",
"orderBy": "정렬 기준",
"generate": "생성",
"copyError": "$t(gallery.copy) 에러",
"learnMore": "더 알아보기",
"nextPage": "다음 페이지",
"saveAs": "다른 이름으로 저장",
"darkMode": "다크 모드",
"loading": "불러오는 중",
"random": "랜덤",
"langHebrew": "Hebrew",
"batch": "Batch 매니저",
"postprocessing": "후처리",
"advanced": "고급",
"unsaved": "저장되지 않음",
"input": "입력",
"details": "세부사항",
"notInstalled": "설치되지 않음"
"statusSavingImage": "이미지 저장"
},
"gallery": {
"showGenerations": "생성된 이미지 보기",
@ -130,35 +68,7 @@
"galleryImageSize": "이미지 크기",
"galleryImageResetSize": "사이즈 리셋",
"gallerySettings": "갤러리 설정",
"maintainAspectRatio": "종횡비 유지",
"deleteSelection": "선택 항목 삭제",
"featuresWillReset": "이 이미지를 삭제하면 해당 기능이 즉시 재설정됩니다.",
"deleteImageBin": "삭제된 이미지는 운영 체제의 Bin으로 전송됩니다.",
"assets": "자산",
"problemDeletingImagesDesc": "하나 이상의 이미지를 삭제할 수 없습니다",
"noImagesInGallery": "보여줄 이미지가 없음",
"autoSwitchNewImages": "새로운 이미지로 자동 전환",
"loading": "불러오는 중",
"unableToLoad": "갤러리를 로드할 수 없음",
"preparingDownload": "다운로드 준비",
"preparingDownloadFailed": "다운로드 준비 중 발생한 문제",
"singleColumnLayout": "단일 열 레이아웃",
"image": "이미지",
"loadMore": "더 불러오기",
"drop": "드랍",
"problemDeletingImages": "이미지 삭제 중 발생한 문제",
"downloadSelection": "선택 항목 다운로드",
"deleteImage": "이미지 삭제",
"currentlyInUse": "이 이미지는 현재 다음 기능에서 사용되고 있습니다:",
"allImagesLoaded": "불러온 모든 이미지",
"dropOrUpload": "$t(gallery.drop) 또는 업로드",
"copy": "복사",
"download": "다운로드",
"deleteImagePermanent": "삭제된 이미지는 복원할 수 없습니다.",
"noImageSelected": "선택된 이미지 없음",
"autoAssignBoardOnClick": "클릭 시 Board로 자동 할당",
"setCurrentImage": "현재 이미지로 설정",
"dropToUpload": "업로드를 위해 $t(gallery.drop)"
"maintainAspectRatio": "종횡비 유지"
},
"unifiedCanvas": {
"betaPreserveMasked": "마스크 레이어 유지"
@ -169,743 +79,6 @@
"nextImage": "다음 이미지",
"mode": "모드",
"menu": "메뉴",
"modelSelect": "모델 선택",
"zoomIn": "확대하기",
"rotateClockwise": "시계방향으로 회전",
"uploadImage": "이미지 업로드",
"showGalleryPanel": "갤러리 패널 표시",
"useThisParameter": "해당 변수 사용",
"reset": "리셋",
"loadMore": "더 불러오기",
"zoomOut": "축소하기",
"rotateCounterClockwise": "반시계방향으로 회전",
"showOptionsPanel": "사이드 패널 표시",
"toggleAutoscroll": "자동 스크롤 전환",
"toggleLogViewer": "Log Viewer 전환"
},
"modelManager": {
"pathToCustomConfig": "사용자 지정 구성 경로",
"importModels": "모델 가져오기",
"availableModels": "사용 가능한 모델",
"conversionNotSupported": "변환이 지원되지 않음",
"noCustomLocationProvided": "사용자 지정 위치가 제공되지 않음",
"onnxModels": "Onnx",
"vaeRepoID": "VAE Repo ID",
"modelExists": "모델 존재",
"custom": "사용자 지정",
"addModel": "모델 추가",
"none": "없음",
"modelConverted": "변환된 모델",
"width": "너비",
"weightedSum": "가중합",
"inverseSigmoid": "Inverse Sigmoid",
"invokeAIFolder": "Invoke AI 폴더",
"syncModelsDesc": "모델이 백엔드와 동기화되지 않은 경우 이 옵션을 사용하여 새로 고침할 수 있습니다. 이는 일반적으로 응용 프로그램이 부팅된 후 수동으로 모델.yaml 파일을 업데이트하거나 InvokeAI root 폴더에 모델을 추가하는 경우에 유용합니다.",
"convert": "변환",
"vae": "VAE",
"noModels": "모델을 찾을 수 없음",
"statusConverting": "변환중",
"sigmoid": "Sigmoid",
"deleteModel": "모델 삭제",
"modelLocation": "모델 위치",
"merge": "병합",
"v1": "v1",
"description": "Description",
"modelMergeInterpAddDifferenceHelp": "이 모드에서 모델 3은 먼저 모델 2에서 차감됩니다. 결과 버전은 위에 설정된 Alpha 비율로 모델 1과 혼합됩니다.",
"customConfig": "사용자 지정 구성",
"cannotUseSpaces": "공백을 사용할 수 없음",
"formMessageDiffusersModelLocationDesc": "적어도 하나 이상 입력해 주세요.",
"addDiffuserModel": "Diffusers 추가",
"search": "검색",
"predictionType": "예측 유형(안정 확산 2.x 모델 및 간혹 안정 확산 1.x 모델의 경우)",
"widthValidationMsg": "모형의 기본 너비.",
"selectAll": "모두 선택",
"vaeLocation": "VAE 위치",
"selectModel": "모델 선택",
"modelAdded": "추가된 모델",
"repo_id": "Repo ID",
"modelSyncFailed": "모델 동기화 실패",
"convertToDiffusersHelpText6": "이 모델을 변환하시겠습니까?",
"config": "구성",
"quickAdd": "빠른 추가",
"selected": "선택된",
"modelTwo": "모델 2",
"simpleModelDesc": "로컬 Difffusers 모델, 로컬 체크포인트/안전 센서 모델 HuggingFace Repo ID 또는 체크포인트/Diffusers 모델 URL의 경로를 제공합니다.",
"customSaveLocation": "사용자 정의 저장 위치",
"advanced": "고급",
"modelsFound": "발견된 모델",
"load": "불러오기",
"height": "높이",
"modelDeleted": "삭제된 모델",
"inpainting": "v1 Inpainting",
"vaeLocationValidationMsg": "VAE가 있는 경로.",
"convertToDiffusersHelpText2": "이 프로세스는 모델 관리자 항목을 동일한 모델의 Diffusers 버전으로 대체합니다.",
"modelUpdateFailed": "모델 업데이트 실패",
"modelUpdated": "업데이트된 모델",
"noModelsFound": "모델을 찾을 수 없음",
"useCustomConfig": "사용자 지정 구성 사용",
"formMessageDiffusersVAELocationDesc": "제공되지 않은 경우 호출AIA 파일을 위의 모델 위치 내에서 VAE 파일을 찾습니다.",
"formMessageDiffusersVAELocation": "VAE 위치",
"checkpointModels": "Checkpoints",
"modelOne": "모델 1",
"settings": "설정",
"heightValidationMsg": "모델의 기본 높이입니다.",
"selectAndAdd": "아래 나열된 모델 선택 및 추가",
"convertToDiffusersHelpText5": "디스크 공간이 충분한지 확인해 주세요. 모델은 일반적으로 2GB에서 7GB 사이로 다양합니다.",
"deleteConfig": "구성 삭제",
"deselectAll": "모두 선택 취소",
"modelConversionFailed": "모델 변환 실패",
"clearCheckpointFolder": "Checkpoint Folder 지우기",
"modelEntryDeleted": "모델 항목 삭제",
"deleteMsg1": "InvokeAI에서 이 모델을 삭제하시겠습니까?",
"syncModels": "동기화 모델",
"mergedModelSaveLocation": "위치 저장",
"checkpointOrSafetensors": "$t(common.checkpoint) / $t(common.safetensors)",
"modelType": "모델 유형",
"nameValidationMsg": "모델 이름 입력",
"cached": "cached",
"modelsMerged": "병합된 모델",
"formMessageDiffusersModelLocation": "Diffusers 모델 위치",
"modelsMergeFailed": "모델 병합 실패",
"convertingModelBegin": "모델 변환 중입니다. 잠시만 기다려 주십시오.",
"v2_base": "v2 (512px)",
"scanForModels": "모델 검색",
"modelLocationValidationMsg": "Diffusers 모델이 저장된 로컬 폴더의 경로 제공",
"name": "이름",
"selectFolder": "폴더 선택",
"updateModel": "모델 업데이트",
"addNewModel": "새로운 모델 추가",
"customConfigFileLocation": "사용자 지정 구성 파일 위치",
"descriptionValidationMsg": "모델에 대한 description 추가",
"safetensorModels": "SafeTensors",
"convertToDiffusersHelpText1": "이 모델은 🧨 Diffusers 형식으로 변환됩니다.",
"modelsSynced": "동기화된 모델",
"vaePrecision": "VAE 정밀도",
"invokeRoot": "InvokeAI 폴더",
"checkpointFolder": "Checkpoint Folder",
"mergedModelCustomSaveLocation": "사용자 지정 경로",
"mergeModels": "모델 병합",
"interpolationType": "Interpolation 타입",
"modelMergeHeaderHelp2": "Diffusers만 병합이 가능합니다. 체크포인트 모델 병합을 원하신다면 먼저 Diffusers로 변환해주세요.",
"convertToDiffusersSaveLocation": "위치 저장",
"deleteMsg2": "모델이 InvokeAI root 폴더에 있으면 디스크에서 모델이 삭제됩니다. 사용자 지정 위치를 사용하는 경우 모델이 디스크에서 삭제되지 않습니다.",
"oliveModels": "Olives",
"repoIDValidationMsg": "모델의 온라인 저장소",
"baseModel": "기본 모델",
"scanAgain": "다시 검색",
"pickModelType": "모델 유형 선택",
"sameFolder": "같은 폴더",
"addNew": "New 추가",
"manual": "매뉴얼",
"convertToDiffusersHelpText3": "디스크의 체크포인트 파일이 InvokeAI root 폴더에 있으면 삭제됩니다. 사용자 지정 위치에 있으면 삭제되지 않습니다.",
"addCheckpointModel": "체크포인트 / 안전 센서 모델 추가",
"configValidationMsg": "모델의 구성 파일에 대한 경로.",
"modelManager": "모델 매니저",
"variant": "Variant",
"vaeRepoIDValidationMsg": "VAE의 온라인 저장소",
"loraModels": "LoRAs",
"modelDeleteFailed": "모델을 삭제하지 못했습니다",
"convertToDiffusers": "Diffusers로 변환",
"allModels": "모든 모델",
"modelThree": "모델 3",
"findModels": "모델 찾기",
"notLoaded": "로드되지 않음",
"alpha": "Alpha",
"diffusersModels": "Diffusers",
"modelMergeAlphaHelp": "Alpha는 모델의 혼합 강도를 제어합니다. Alpha 값이 낮을수록 두 번째 모델의 영향력이 줄어듭니다.",
"addDifference": "Difference 추가",
"noModelSelected": "선택한 모델 없음",
"modelMergeHeaderHelp1": "최대 3개의 다른 모델을 병합하여 필요에 맞는 혼합물을 만들 수 있습니다.",
"ignoreMismatch": "선택한 모델 간의 불일치 무시",
"v2_768": "v2 (768px)",
"convertToDiffusersHelpText4": "이것은 한 번의 과정일 뿐입니다. 컴퓨터 사양에 따라 30-60초 정도 소요될 수 있습니다.",
"model": "모델",
"addManually": "Manually 추가",
"addSelected": "Selected 추가",
"mergedModelName": "병합된 모델 이름",
"delete": "삭제"
},
"controlnet": {
"amult": "a_mult",
"resize": "크기 조정",
"showAdvanced": "고급 표시",
"contentShuffleDescription": "이미지에서 content 섞기",
"bgth": "bg_th",
"addT2IAdapter": "$t(common.t2iAdapter) 추가",
"pidi": "PIDI",
"importImageFromCanvas": "캔버스에서 이미지 가져오기",
"lineartDescription": "이미지->lineart 변환",
"normalBae": "Normal BAE",
"importMaskFromCanvas": "캔버스에서 Mask 가져오기",
"hed": "HED",
"contentShuffle": "Content Shuffle",
"controlNetEnabledT2IDisabled": "$t(common.controlNet) 사용 가능, $t(common.t2iAdapter) 사용 불가능",
"ipAdapterModel": "Adapter 모델",
"resetControlImage": "Control Image 재설정",
"beginEndStepPercent": "Begin / End Step Percentage",
"mlsdDescription": "Minimalist Line Segment Detector",
"duplicate": "복제",
"balanced": "Balanced",
"f": "F",
"h": "H",
"prompt": "프롬프트",
"depthMidasDescription": "Midas를 사용하여 Depth map 생성하기",
"openPoseDescription": "Openpose를 이용한 사람 포즈 추정",
"control": "Control",
"resizeMode": "크기 조정 모드",
"t2iEnabledControlNetDisabled": "$t(common.t2iAdapter) 사용 가능,$t(common.controlNet) 사용 불가능",
"coarse": "Coarse",
"weight": "Weight",
"selectModel": "모델 선택",
"crop": "Crop",
"depthMidas": "Depth (Midas)",
"w": "W",
"processor": "프로세서",
"addControlNet": "$t(common.controlNet) 추가",
"none": "해당없음",
"enableControlnet": "사용 가능한 ControlNet",
"detectResolution": "해상도 탐지",
"controlNetT2IMutexDesc": "$t(common.controlNet)와 $t(common.t2iAdapter)는 현재 동시에 지원되지 않습니다.",
"pidiDescription": "PIDI image 처리",
"mediapipeFace": "Mediapipe Face",
"mlsd": "M-LSD",
"controlMode": "Control Mode",
"fill": "채우기",
"cannyDescription": "Canny 모서리 삭제",
"addIPAdapter": "$t(common.ipAdapter) 추가",
"lineart": "Lineart",
"colorMapDescription": "이미지에서 color map을 생성합니다",
"lineartAnimeDescription": "Anime-style lineart 처리",
"minConfidence": "Min Confidence",
"imageResolution": "이미지 해상도",
"megaControl": "Mega Control",
"depthZoe": "Depth (Zoe)",
"colorMap": "색",
"lowThreshold": "Low Threshold",
"autoConfigure": "프로세서 자동 구성",
"highThreshold": "High Threshold",
"normalBaeDescription": "Normal BAE 처리",
"noneDescription": "처리되지 않음",
"saveControlImage": "Control Image 저장",
"openPose": "Openpose",
"toggleControlNet": "해당 ControlNet으로 전환",
"delete": "삭제",
"controlAdapter_other": "Control Adapter(s)",
"safe": "Safe",
"colorMapTileSize": "타일 크기",
"lineartAnime": "Lineart Anime",
"ipAdapterImageFallback": "IP Adapter Image가 선택되지 않음",
"mediapipeFaceDescription": "Mediapipe를 사용하여 Face 탐지",
"canny": "Canny",
"depthZoeDescription": "Zoe를 사용하여 Depth map 생성하기",
"hedDescription": "Holistically-Nested 모서리 탐지",
"setControlImageDimensions": "Control Image Dimensions를 W/H로 설정",
"scribble": "scribble",
"resetIPAdapterImage": "IP Adapter Image 재설정",
"handAndFace": "Hand and Face",
"enableIPAdapter": "사용 가능한 IP Adapter",
"maxFaces": "Max Faces"
},
"hotkeys": {
"toggleSnap": {
"desc": "Snap을 Grid로 전환",
"title": "Snap 전환"
},
"setSeed": {
"title": "시드 설정",
"desc": "현재 이미지의 시드 사용"
},
"keyboardShortcuts": "키보드 바로 가기",
"decreaseGalleryThumbSize": {
"desc": "갤러리 미리 보기 크기 축소",
"title": "갤러리 이미지 크기 축소"
},
"previousStagingImage": {
"title": "이전 스테이징 이미지",
"desc": "이전 스테이징 영역 이미지"
},
"decreaseBrushSize": {
"title": "브러시 크기 줄이기",
"desc": "캔버스 브러시/지우개 크기 감소"
},
"consoleToggle": {
"desc": "콘솔 열고 닫기",
"title": "콘솔 전환"
},
"selectBrush": {
"desc": "캔버스 브러시를 선택",
"title": "브러시 선택"
},
"upscale": {
"desc": "현재 이미지를 업스케일",
"title": "업스케일"
},
"previousImage": {
"title": "이전 이미지",
"desc": "갤러리에 이전 이미지 표시"
},
"unifiedCanvasHotkeys": "Unified Canvas Hotkeys",
"toggleOptions": {
"desc": "옵션 패널을 열고 닫기",
"title": "옵션 전환"
},
"selectEraser": {
"title": "지우개 선택",
"desc": "캔버스 지우개를 선택"
},
"setPrompt": {
"title": "프롬프트 설정",
"desc": "현재 이미지의 프롬프트 사용"
},
"acceptStagingImage": {
"desc": "현재 준비 영역 이미지 허용",
"title": "준비 이미지 허용"
},
"resetView": {
"desc": "Canvas View 초기화",
"title": "View 초기화"
},
"hideMask": {
"title": "Mask 숨김",
"desc": "mask 숨김/숨김 해제"
},
"pinOptions": {
"title": "옵션 고정",
"desc": "옵션 패널을 고정"
},
"toggleGallery": {
"desc": "gallery drawer 열기 및 닫기",
"title": "Gallery 전환"
},
"quickToggleMove": {
"title": "빠른 토글 이동",
"desc": "일시적으로 이동 모드 전환"
},
"generalHotkeys": "General Hotkeys",
"showHideBoundingBox": {
"desc": "bounding box 표시 전환",
"title": "Bounding box 표시/숨김"
},
"showInfo": {
"desc": "현재 이미지의 metadata 정보 표시",
"title": "정보 표시"
},
"copyToClipboard": {
"title": "클립보드로 복사",
"desc": "현재 캔버스를 클립보드로 복사"
},
"restoreFaces": {
"title": "Faces 복원",
"desc": "현재 이미지 복원"
},
"fillBoundingBox": {
"title": "Bounding Box 채우기",
"desc": "bounding box를 브러시 색으로 채웁니다"
},
"closePanels": {
"desc": "열린 panels 닫기",
"title": "panels 닫기"
},
"downloadImage": {
"desc": "현재 캔버스 다운로드",
"title": "이미지 다운로드"
},
"setParameters": {
"title": "매개 변수 설정",
"desc": "현재 이미지의 모든 매개 변수 사용"
},
"maximizeWorkSpace": {
"desc": "패널을 닫고 작업 면적을 극대화",
"title": "작업 공간 극대화"
},
"galleryHotkeys": "Gallery Hotkeys",
"cancel": {
"desc": "이미지 생성 취소",
"title": "취소"
},
"saveToGallery": {
"title": "갤러리에 저장",
"desc": "현재 캔버스를 갤러리에 저장"
},
"eraseBoundingBox": {
"desc": "bounding box 영역을 지웁니다",
"title": "Bounding Box 지우기"
},
"nextImage": {
"title": "다음 이미지",
"desc": "갤러리에 다음 이미지 표시"
},
"colorPicker": {
"desc": "canvas color picker 선택",
"title": "Color Picker 선택"
},
"invoke": {
"desc": "이미지 생성",
"title": "불러오기"
},
"sendToImageToImage": {
"desc": "현재 이미지를 이미지로 보내기"
},
"toggleLayer": {
"desc": "mask/base layer 선택 전환",
"title": "Layer 전환"
},
"increaseBrushSize": {
"title": "브러시 크기 증가",
"desc": "캔버스 브러시/지우개 크기 증가"
},
"appHotkeys": "App Hotkeys",
"deleteImage": {
"title": "이미지 삭제",
"desc": "현재 이미지 삭제"
},
"moveTool": {
"desc": "캔버스 탐색 허용",
"title": "툴 옮기기"
},
"clearMask": {
"desc": "전체 mask 제거",
"title": "Mask 제거"
},
"increaseGalleryThumbSize": {
"title": "갤러리 이미지 크기 증가",
"desc": "갤러리 미리 보기 크기를 늘립니다"
},
"increaseBrushOpacity": {
"desc": "캔버스 브러시의 불투명도를 높입니다",
"title": "브러시 불투명도 증가"
},
"focusPrompt": {
"desc": "프롬프트 입력 영역에 초점을 맞춥니다",
"title": "프롬프트에 초점 맞추기"
},
"decreaseBrushOpacity": {
"desc": "캔버스 브러시의 불투명도를 줄입니다",
"title": "브러시 불투명도 감소"
},
"nextStagingImage": {
"desc": "다음 스테이징 영역 이미지",
"title": "다음 스테이징 이미지"
},
"redoStroke": {
"title": "Stroke 다시 실행",
"desc": "brush stroke 다시 실행"
},
"nodesHotkeys": "Nodes Hotkeys",
"addNodes": {
"desc": "노드 추가 메뉴 열기",
"title": "노드 추가"
},
"undoStroke": {
"title": "Stroke 실행 취소",
"desc": "brush stroke 실행 취소"
},
"changeTabs": {
"desc": "다른 workspace으로 전환",
"title": "탭 바꾸기"
},
"mergeVisible": {
"desc": "캔버스의 보이는 모든 레이어 병합"
}
},
"nodes": {
"inputField": "입력 필드",
"controlFieldDescription": "노드 간에 전달된 Control 정보입니다.",
"latentsFieldDescription": "노드 사이에 Latents를 전달할 수 있습니다.",
"denoiseMaskFieldDescription": "노드 간에 Denoise Mask가 전달될 수 있음",
"floatCollectionDescription": "실수 컬렉션.",
"missingTemplate": "잘못된 노드: {{type}} 유형의 {{node}} 템플릿 누락(설치되지 않으셨나요?)",
"outputSchemaNotFound": "Output schema가 발견되지 않음",
"ipAdapterPolymorphicDescription": "IP-Adapters 컬렉션.",
"latentsPolymorphicDescription": "노드 사이에 Latents를 전달할 수 있습니다.",
"colorFieldDescription": "RGBA 색.",
"mainModelField": "모델",
"ipAdapterCollection": "IP-Adapters 컬렉션",
"conditioningCollection": "Conditioning 컬렉션",
"maybeIncompatible": "설치된 것과 호환되지 않을 수 있음",
"ipAdapterPolymorphic": "IP-Adapter 다형성",
"noNodeSelected": "선택한 노드 없음",
"addNode": "노드 추가",
"hideGraphNodes": "그래프 오버레이 숨기기",
"enum": "Enum",
"loadWorkflow": "Workflow 불러오기",
"integerPolymorphicDescription": "정수 컬렉션.",
"noOutputRecorded": "기록된 출력 없음",
"conditioningCollectionDescription": "노드 간에 Conditioning을 전달할 수 있습니다.",
"colorPolymorphic": "색상 다형성",
"colorCodeEdgesHelp": "연결된 필드에 따른 색상 코드 선",
"collectionDescription": "해야 할 일",
"hideLegendNodes": "필드 유형 범례 숨기기",
"addLinearView": "Linear View에 추가",
"float": "실수",
"targetNodeFieldDoesNotExist": "잘못된 모서리: 대상/입력 필드 {{node}}. {{field}}이(가) 없습니다",
"animatedEdges": "애니메이션 모서리",
"conditioningPolymorphic": "Conditioning 다형성",
"integer": "정수",
"colorField": "색",
"boardField": "Board",
"nodeTemplate": "노드 템플릿",
"latentsCollection": "Latents 컬렉션",
"nodeOpacity": "노드 불투명도",
"sourceNodeDoesNotExist": "잘못된 모서리: 소스/출력 노드 {{node}}이(가) 없습니다",
"pickOne": "하나 고르기",
"collectionItemDescription": "해야 할 일",
"integerDescription": "정수는 소수점이 없는 숫자입니다.",
"outputField": "출력 필드",
"conditioningPolymorphicDescription": "노드 간에 Conditioning을 전달할 수 있습니다.",
"noFieldsLinearview": "Linear View에 추가된 필드 없음",
"imagePolymorphic": "이미지 다형성",
"nodeSearch": "노드 검색",
"imagePolymorphicDescription": "이미지 컬렉션.",
"floatPolymorphic": "실수 다형성",
"outputFieldInInput": "입력 중 출력필드",
"doesNotExist": "존재하지 않음",
"ipAdapterCollectionDescription": "IP-Adapters 컬렉션.",
"controlCollection": "Control 컬렉션",
"inputMayOnlyHaveOneConnection": "입력에 하나의 연결만 있을 수 있습니다",
"notes": "메모",
"nodeOutputs": "노드 결과물",
"currentImageDescription": "Node Editor에 현재 이미지를 표시합니다",
"downloadWorkflow": "Workflow JSON 다운로드",
"ipAdapter": "IP-Adapter",
"integerCollection": "정수 컬렉션",
"collectionItem": "컬렉션 아이템",
"noConnectionInProgress": "진행중인 연결이 없습니다",
"controlCollectionDescription": "노드 간에 전달된 Control 정보입니다.",
"noConnectionData": "연결 데이터 없음",
"outputFields": "출력 필드",
"fieldTypesMustMatch": "필드 유형은 일치해야 합니다",
"edge": "Edge",
"inputNode": "입력 노드",
"enumDescription": "Enums은 여러 옵션 중 하나일 수 있는 값입니다.",
"sourceNodeFieldDoesNotExist": "잘못된 모서리: 소스/출력 필드 {{node}}. {{field}}이(가) 없습니다",
"loRAModelFieldDescription": "해야 할 일",
"imageField": "이미지",
"animatedEdgesHelp": "선택한 노드에 연결된 선택한 가장자리 및 가장자리를 애니메이션화합니다",
"cannotDuplicateConnection": "중복 연결을 만들 수 없습니다",
"booleanPolymorphic": "Boolean 다형성",
"noWorkflow": "Workflow 없음",
"colorCollectionDescription": "해야 할 일",
"integerCollectionDescription": "정수 컬렉션.",
"colorPolymorphicDescription": "색의 컬렉션.",
"denoiseMaskField": "Denoise Mask",
"missingCanvaInitImage": "캔버스 init 이미지 누락",
"conditioningFieldDescription": "노드 간에 Conditioning을 전달할 수 있습니다.",
"clipFieldDescription": "Tokenizer 및 text_encoder 서브모델.",
"fullyContainNodesHelp": "선택하려면 노드가 선택 상자 안에 완전히 있어야 합니다",
"noImageFoundState": "상태에서 초기 이미지를 찾을 수 없습니다",
"clipField": "Clip",
"nodePack": "Node pack",
"nodeType": "노드 유형",
"noMatchingNodes": "일치하는 노드 없음",
"fullyContainNodes": "선택할 노드 전체 포함",
"integerPolymorphic": "정수 다형성",
"executionStateInProgress": "진행중",
"noFieldType": "필드 유형 없음",
"colorCollection": "색의 컬렉션.",
"executionStateError": "에러",
"noOutputSchemaName": "ref 개체에 output schema 이름이 없습니다",
"ipAdapterModel": "IP-Adapter 모델",
"latentsPolymorphic": "Latents 다형성",
"ipAdapterDescription": "이미지 프롬프트 어댑터(IP-Adapter).",
"boolean": "Booleans",
"missingCanvaInitMaskImages": "캔버스 init 및 mask 이미지 누락",
"problemReadingMetadata": "이미지에서 metadata를 읽는 중 문제가 발생했습니다",
"hideMinimapnodes": "미니맵 숨기기",
"oNNXModelField": "ONNX 모델",
"executionStateCompleted": "완료된",
"node": "노드",
"currentImage": "현재 이미지",
"controlField": "Control",
"booleanDescription": "Booleans은 참 또는 거짓입니다.",
"collection": "컬렉션",
"ipAdapterModelDescription": "IP-Adapter 모델 필드",
"cannotConnectInputToInput": "입력을 입력에 연결할 수 없습니다",
"invalidOutputSchema": "잘못된 output schema",
"boardFieldDescription": "A gallery board",
"floatDescription": "실수는 소수점이 있는 숫자입니다.",
"floatPolymorphicDescription": "실수 컬렉션.",
"conditioningField": "Conditioning",
"collectionFieldType": "{{name}} 컬렉션",
"floatCollection": "실수 컬렉션",
"latentsField": "Latents",
"cannotConnectOutputToOutput": "출력을 출력에 연결할 수 없습니다",
"booleanCollection": "Boolean 컬렉션",
"connectionWouldCreateCycle": "연결하면 주기가 생성됩니다",
"cannotConnectToSelf": "자체에 연결할 수 없습니다",
"notesDescription": "Workflow에 대한 메모 추가",
"inputFields": "입력 필드",
"colorCodeEdges": "색상-코드 선",
"targetNodeDoesNotExist": "잘못된 모서리: 대상/입력 노드 {{node}}이(가) 없습니다",
"imageCollectionDescription": "이미지 컬렉션.",
"mismatchedVersion": "잘못된 노드: {{type}} 유형의 {{node}} 노드에 일치하지 않는 버전이 있습니다(업데이트 해보시겠습니까?)",
"imageFieldDescription": "노드 간에 이미지를 전달할 수 있습니다.",
"outputNode": "출력노드",
"addNodeToolTip": "노드 추가(Shift+A, Space)",
"collectionOrScalarFieldType": "{{name}} 컬렉션|Scalar",
"nodeVersion": "노드 버전",
"loadingNodes": "노드 로딩중...",
"mainModelFieldDescription": "해야 할 일",
"loRAModelField": "LoRA",
"deletedInvalidEdge": "잘못된 모서리 {{source}} -> {{target}} 삭제",
"latentsCollectionDescription": "노드 사이에 Latents를 전달할 수 있습니다.",
"oNNXModelFieldDescription": "ONNX 모델 필드.",
"imageCollection": "이미지 컬렉션"
},
"queue": {
"status": "상태",
"pruneSucceeded": "Queue로부터 {{item_count}} 완성된 항목 잘라내기",
"cancelTooltip": "현재 항목 취소",
"queueEmpty": "비어있는 Queue",
"pauseSucceeded": "중지된 프로세서",
"in_progress": "진행 중",
"queueFront": "Front of Queue에 추가",
"notReady": "Queue를 생성할 수 없음",
"batchFailedToQueue": "Queue Batch에 실패",
"completed": "완성된",
"queueBack": "Queue에 추가",
"batchValues": "Batch 값들",
"cancelFailed": "항목 취소 중 발생한 문제",
"queueCountPrediction": "Queue에 {{predicted}} 추가",
"batchQueued": "Batch Queued",
"pauseFailed": "프로세서 중지 중 발생한 문제",
"clearFailed": "Queue 제거 중 발생한 문제",
"queuedCount": "{{pending}} Pending",
"front": "front",
"clearSucceeded": "제거된 Queue",
"pause": "중지",
"pruneTooltip": "{{item_count}} 완성된 항목 잘라내기",
"cancelSucceeded": "취소된 항목",
"batchQueuedDesc_other": "queue의 {{direction}}에 추가된 {{count}}세션",
"queue": "Queue",
"batch": "Batch",
"clearQueueAlertDialog": "Queue를 지우면 처리 항목이 즉시 취소되고 Queue가 완전히 지워집니다.",
"resumeFailed": "프로세서 재개 중 발생한 문제",
"clear": "제거하다",
"prune": "잘라내다",
"total": "총 개수",
"canceled": "취소된",
"pruneFailed": "Queue 잘라내는 중 발생한 문제",
"cancelBatchSucceeded": "취소된 Batch",
"clearTooltip": "모든 항목을 취소하고 제거",
"current": "최근",
"pauseTooltip": "프로세서 중지",
"failed": "실패한",
"cancelItem": "항목 취소",
"next": "다음",
"cancelBatch": "Batch 취소",
"back": "back",
"batchFieldValues": "Batch 필드 값들",
"cancel": "취소",
"session": "세션",
"time": "시간",
"queueTotal": "{{total}} Total",
"resumeSucceeded": "재개된 프로세서",
"enqueueing": "Queueing Batch",
"resumeTooltip": "프로세서 재개",
"resume": "재개",
"cancelBatchFailed": "Batch 취소 중 발생한 문제",
"clearQueueAlertDialog2": "Queue를 지우시겠습니까?",
"item": "항목",
"graphFailedToQueue": "queue graph에 실패"
},
"metadata": {
"positivePrompt": "긍정적 프롬프트",
"negativePrompt": "부정적인 프롬프트",
"generationMode": "Generation Mode",
"Threshold": "Noise Threshold",
"metadata": "Metadata",
"seed": "시드",
"imageDetails": "이미지 세부 정보",
"perlin": "Perlin Noise",
"model": "모델",
"noImageDetails": "이미지 세부 정보를 찾을 수 없습니다",
"hiresFix": "고해상도 최적화",
"cfgScale": "CFG scale",
"initImage": "초기이미지",
"recallParameters": "매개변수 호출",
"height": "Height",
"variations": "Seed-weight 쌍",
"noMetaData": "metadata를 찾을 수 없습니다",
"cfgRescaleMultiplier": "$t(parameters.cfgRescaleMultiplier)",
"width": "너비",
"vae": "VAE",
"createdBy": "~에 의해 생성된",
"workflow": "작업의 흐름",
"steps": "단계",
"scheduler": "스케줄러",
"noRecallParameters": "호출할 매개 변수가 없습니다"
},
"invocationCache": {
"useCache": "캐시 사용",
"disable": "이용 불가능한",
"misses": "캐시 미스",
"enableFailed": "Invocation 캐시를 사용하도록 설정하는 중 발생한 문제",
"invocationCache": "Invocation 캐시",
"clearSucceeded": "제거된 Invocation 캐시",
"enableSucceeded": "이용 가능한 Invocation 캐시",
"clearFailed": "Invocation 캐시 제거 중 발생한 문제",
"hits": "캐시 적중",
"disableSucceeded": "이용 불가능한 Invocation 캐시",
"disableFailed": "Invocation 캐시를 이용하지 못하게 설정 중 발생한 문제",
"enable": "이용 가능한",
"clear": "제거",
"maxCacheSize": "최대 캐시 크기",
"cacheSize": "캐시 크기"
},
"embedding": {
"noEmbeddingsLoaded": "불러온 Embeddings이 없음",
"noMatchingEmbedding": "일치하는 Embeddings이 없음",
"addEmbedding": "Embedding 추가",
"incompatibleModel": "호환되지 않는 기본 모델:"
},
"hrf": {
"enableHrf": "이용 가능한 고해상도 고정",
"upscaleMethod": "업스케일 방법",
"enableHrfTooltip": "낮은 초기 해상도로 생성하고 기본 해상도로 업스케일한 다음 Image-to-Image를 실행합니다.",
"metadata": {
"strength": "고해상도 고정 강도",
"enabled": "고해상도 고정 사용",
"method": "고해상도 고정 방법"
},
"hrf": "고해상도 고정",
"hrfStrength": "고해상도 고정 강도"
},
"models": {
"noLoRAsLoaded": "로드된 LoRA 없음",
"noMatchingModels": "일치하는 모델 없음",
"esrganModel": "ESRGAN 모델",
"loading": "로딩중",
"noMatchingLoRAs": "일치하는 LoRA 없음",
"noLoRAsAvailable": "사용 가능한 LoRA 없음",
"noModelsAvailable": "사용 가능한 모델이 없음",
"addLora": "LoRA 추가",
"selectModel": "모델 선택",
"noRefinerModelsInstalled": "SDXL Refiner 모델이 설치되지 않음",
"noLoRAsInstalled": "설치된 LoRA 없음",
"selectLoRA": "LoRA 선택"
},
"boards": {
"autoAddBoard": "자동 추가 Board",
"topMessage": "이 보드에는 다음 기능에 사용되는 이미지가 포함되어 있습니다:",
"move": "이동",
"menuItemAutoAdd": "해당 Board에 자동 추가",
"myBoard": "나의 Board",
"searchBoard": "Board 찾는 중...",
"deleteBoardOnly": "Board만 삭제",
"noMatching": "일치하는 Board들이 없음",
"movingImagesToBoard_other": "{{count}}이미지를 Board로 이동시키기",
"selectBoard": "Board 선택",
"cancel": "취소",
"addBoard": "Board 추가",
"bottomMessage": "이 보드와 이미지를 삭제하면 현재 사용 중인 모든 기능이 재설정됩니다.",
"uncategorized": "미분류",
"downloadBoard": "Board 다운로드",
"changeBoard": "Board 바꾸기",
"loading": "불러오는 중...",
"clearSearch": "검색 지우기",
"deleteBoard": "Board 삭제",
"deleteBoardAndImages": "Board와 이미지 삭제",
"deletedBoardsCannotbeRestored": "삭제된 Board는 복원할 수 없습니다"
"modelSelect": "모델 선택"
}
}

View File

@ -148,6 +148,10 @@
"title": "Zet Opties vast",
"desc": "Zet het deelscherm Opties vast"
},
"toggleViewer": {
"title": "Zet Viewer vast",
"desc": "Opent of sluit Afbeeldingsviewer"
},
"toggleGallery": {
"title": "Zet Galerij vast",
"desc": "Opent of sluit het deelscherm Galerij"
@ -208,6 +212,10 @@
"title": "Volgende afbeelding",
"desc": "Toont de volgende afbeelding in de galerij"
},
"toggleGalleryPin": {
"title": "Zet galerij vast/los",
"desc": "Zet de galerij vast of los aan de gebruikersinterface"
},
"increaseGalleryThumbSize": {
"title": "Vergroot afbeeldingsgrootte galerij",
"desc": "Vergroot de grootte van de galerijminiaturen"
@ -836,6 +844,9 @@
"hideLegendNodes": "Typelegende veld verbergen",
"reloadNodeTemplates": "Herlaad knooppuntsjablonen",
"loadWorkflow": "Laad werkstroom",
"resetWorkflow": "Herstel werkstroom",
"resetWorkflowDesc": "Weet je zeker dat je deze werkstroom wilt herstellen?",
"resetWorkflowDesc2": "Herstel van een werkstroom haalt alle knooppunten, randen en werkstroomdetails weg.",
"downloadWorkflow": "Download JSON van werkstroom",
"booleanPolymorphicDescription": "Een verzameling Booleanse waarden.",
"scheduler": "Planner",
@ -1063,6 +1074,7 @@
"processor": "Verwerker",
"addControlNet": "Voeg $t(common.controlNet) toe",
"none": "Geen",
"incompatibleBaseModel": "Niet-compatibel basismodel:",
"enableControlnet": "Schakel ControlNet in",
"detectResolution": "Herken resolutie",
"controlNetT2IMutexDesc": "Gelijktijdig gebruik van $t(common.controlNet) en $t(common.t2iAdapter) wordt op dit moment niet ondersteund.",

View File

@ -86,6 +86,10 @@
"title": "Przypnij opcje",
"desc": "Przypina panel opcji"
},
"toggleViewer": {
"title": "Przełącz podgląd",
"desc": "Otwiera lub zamyka widok podglądu"
},
"toggleGallery": {
"title": "Przełącz galerię",
"desc": "Wysuwa lub chowa galerię"
@ -146,6 +150,10 @@
"title": "Następny obraz",
"desc": "Aktywuje następny obraz z galerii"
},
"toggleGalleryPin": {
"title": "Przypnij galerię",
"desc": "Przypina lub odpina widok galerii"
},
"increaseGalleryThumbSize": {
"title": "Powiększ obrazy",
"desc": "Powiększa rozmiar obrazów w galerii"

View File

@ -81,6 +81,10 @@
"hotkeys": {
"generalHotkeys": "Atalhos Gerais",
"galleryHotkeys": "Atalhos da Galeria",
"toggleViewer": {
"title": "Ativar Visualizador",
"desc": "Abrir e fechar o Visualizador de Imagens"
},
"maximizeWorkSpace": {
"desc": "Fechar painéis e maximixar área de trabalho",
"title": "Maximizar a Área de Trabalho"
@ -228,6 +232,10 @@
"title": "Apagar Imagem",
"desc": "Apaga a imagem atual"
},
"toggleGalleryPin": {
"title": "Ativar Fixar Galeria",
"desc": "Fixa e desafixa a galeria na interface"
},
"increaseGalleryThumbSize": {
"title": "Aumentar Tamanho da Galeria de Imagem",
"desc": "Aumenta o tamanho das thumbs na galeria"

View File

@ -103,6 +103,10 @@
"title": "Fixar Opções",
"desc": "Fixar o painel de opções"
},
"toggleViewer": {
"title": "Ativar Visualizador",
"desc": "Abrir e fechar o Visualizador de Imagens"
},
"toggleGallery": {
"title": "Ativar Galeria",
"desc": "Abrir e fechar a gaveta da galeria"
@ -163,6 +167,10 @@
"title": "Próxima Imagem",
"desc": "Mostra a próxima imagem na galeria"
},
"toggleGalleryPin": {
"title": "Ativar Fixar Galeria",
"desc": "Fixa e desafixa a galeria na interface"
},
"increaseGalleryThumbSize": {
"title": "Aumentar Tamanho da Galeria de Imagem",
"desc": "Aumenta o tamanho das thumbs na galeria"

View File

@ -121,11 +121,7 @@
"unsaved": "несохраненный",
"input": "Вход",
"details": "Детали",
"notInstalled": "Нет $t(common.installed)",
"preferencesLabel": "Предпочтения",
"or": "или",
"advancedOptions": "Расширенные настройки",
"free": "Свободно"
"notInstalled": "Нет $t(common.installed)"
},
"gallery": {
"generations": "Генерации",
@ -193,6 +189,10 @@
"title": "Закрепить параметры",
"desc": "Закрепить панель параметров"
},
"toggleViewer": {
"title": "Показать просмотр",
"desc": "Открывать и закрывать просмотрщик изображений"
},
"toggleGallery": {
"title": "Показать галерею",
"desc": "Открывать и закрывать ящик галереи"
@ -253,6 +253,10 @@
"title": "Следующее изображение",
"desc": "Отображение следующего изображения в галерее"
},
"toggleGalleryPin": {
"title": "Закрепить галерею",
"desc": "Закрепляет и открепляет галерею"
},
"increaseGalleryThumbSize": {
"title": "Увеличить размер миниатюр галереи",
"desc": "Увеличивает размер миниатюр галереи"
@ -369,22 +373,7 @@
"desc": "Открывает меню добавления узла",
"title": "Добавление узлов"
},
"nodesHotkeys": "Горячие клавиши узлов",
"cancelAndClear": {
"desc": "Отмена текущего элемента очереди и очистка всех ожидающих элементов",
"title": "Отменить и очистить"
},
"resetOptionsAndGallery": {
"title": "Сброс настроек и галереи",
"desc": "Сброс панелей галереи и настроек"
},
"searchHotkeys": "Поиск горячих клавиш",
"noHotkeysFound": "Горячие клавиши не найдены",
"toggleOptionsAndGallery": {
"desc": "Открытие и закрытие панели опций и галереи",
"title": "Переключить опции и галерею"
},
"clearSearch": "Очистить поиск"
"nodesHotkeys": "Горячие клавиши узлов"
},
"modelManager": {
"modelManager": "Менеджер моделей",
@ -534,7 +523,7 @@
"parameters": {
"images": "Изображения",
"steps": "Шаги",
"cfgScale": "Шкала точности (CFG)",
"cfgScale": "Точность следования запросу (CFG)",
"width": "Ширина",
"height": "Высота",
"seed": "Сид",
@ -920,6 +909,9 @@
"hideLegendNodes": "Скрыть тип поля",
"showMinimapnodes": "Показать миникарту",
"loadWorkflow": "Загрузить рабочий процесс",
"resetWorkflowDesc2": "Сброс рабочего процесса очистит все узлы, ребра и детали рабочего процесса.",
"resetWorkflow": "Сбросить рабочий процесс",
"resetWorkflowDesc": "Вы уверены, что хотите сбросить этот рабочий процесс?",
"reloadNodeTemplates": "Перезагрузить шаблоны узлов",
"downloadWorkflow": "Скачать JSON рабочего процесса",
"booleanPolymorphicDescription": "Коллекция логических значений.",
@ -1173,6 +1165,7 @@
"processor": "Процессор",
"addControlNet": "Добавить $t(common.controlNet)",
"none": "ничего",
"incompatibleBaseModel": "Несовместимая базовая модель:",
"controlNetT2IMutexDesc": "$t(common.controlNet) и $t(common.t2iAdapter) одновременно в настоящее время не поддерживаются.",
"ip_adapter": "$t(controlnet.controlAdapter_one) №{{number}} $t(common.ipAdapter)",
"pidiDescription": "PIDI-обработка изображений",
@ -1207,8 +1200,7 @@
"handAndFace": "Руки и Лицо",
"enableIPAdapter": "Включить IP Adapter",
"maxFaces": "Макс Лица",
"mlsdDescription": "Минималистичный детектор отрезков линии",
"resizeSimple": "Изменить размер (простой)"
"mlsdDescription": "Минималистичный детектор отрезков линии"
},
"boards": {
"autoAddBoard": "Авто добавление Доски",
@ -1560,8 +1552,7 @@
"cancelBatchFailed": "Проблема с отменой пакета",
"clearQueueAlertDialog2": "Вы уверены, что хотите очистить очередь?",
"item": "Элемент",
"graphFailedToQueue": "Не удалось поставить график в очередь",
"openQueue": "Открыть очередь"
"graphFailedToQueue": "Не удалось поставить график в очередь"
},
"sdxl": {
"refinerStart": "Запуск перерисовщика",
@ -1608,6 +1599,7 @@
"saveWorkflow": "Сохранить рабочий процесс",
"openWorkflow": "Открытый рабочий процесс",
"clearWorkflowSearchFilter": "Очистить фильтр поиска рабочих процессов",
"workflowEditorReset": "Сброс редактора рабочих процессов",
"workflowLibrary": "Библиотека",
"downloadWorkflow": "Скачать рабочий процесс",
"noRecentWorkflows": "Нет недавних рабочих процессов",
@ -1656,38 +1648,9 @@
"selectModel": "Выберите модель",
"noRefinerModelsInstalled": "Модели SDXL Refiner не установлены",
"noLoRAsInstalled": "Нет установленных LoRA",
"selectLoRA": "Выберите LoRA",
"noMainModelSelected": "Базовая модель не выбрана",
"lora": "LoRA",
"allLoRAsAdded": "Все LoRA добавлены",
"defaultVAE": "Стандартное VAE",
"incompatibleBaseModel": "Несовместимая базовая модель",
"loraAlreadyAdded": "LoRA уже добавлена"
"selectLoRA": "Выберите LoRA"
},
"app": {
"storeNotInitialized": "Магазин не инициализирован"
},
"accordions": {
"compositing": {
"infillTab": "Заполнение",
"coherenceTab": "Согласованность",
"title": "Композиция"
},
"control": {
"controlAdaptersTab": "Адаптеры контроля",
"ipTab": "Запросы изображений",
"title": "Контроль"
},
"generation": {
"title": "Генерация",
"conceptsTab": "Концепты",
"modelTab": "Модель"
},
"advanced": {
"title": "Расширенные"
},
"image": {
"title": "Изображение"
}
}
}

View File

@ -129,6 +129,10 @@
"title": "Växla inställningar",
"desc": "Öppna och stäng alternativpanelen"
},
"toggleViewer": {
"title": "Växla visaren",
"desc": "Öppna och stäng bildvisaren"
},
"toggleGallery": {
"title": "Växla galleri",
"desc": "Öppna eller stäng galleribyrån"
@ -189,6 +193,10 @@
"title": "Nästa bild",
"desc": "Visa nästa bild"
},
"toggleGalleryPin": {
"title": "Växla gallerinål",
"desc": "Nålar fast eller nålar av galleriet i gränssnittet"
},
"increaseGalleryThumbSize": {
"title": "Förstora galleriets bildstorlek",
"desc": "Förstora miniatyrbildernas storlek"

View File

@ -111,6 +111,10 @@
"title": "Закріпити параметри",
"desc": "Закріпити панель параметрів"
},
"toggleViewer": {
"title": "Показати перегляд",
"desc": "Відкривати і закривати переглядач зображень"
},
"toggleGallery": {
"title": "Показати галерею",
"desc": "Відкривати і закривати скриньку галереї"
@ -171,6 +175,10 @@
"title": "Наступне зображення",
"desc": "Відображення наступного зображення в галереї"
},
"toggleGalleryPin": {
"title": "Закріпити галерею",
"desc": "Закріплює і відкріплює галерею"
},
"increaseGalleryThumbSize": {
"title": "Збільшити розмір мініатюр галереї",
"desc": "Збільшує розмір мініатюр галереї"

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