Compare commits

..

30 Commits

Author SHA1 Message Date
a338616ced final documentation fixes prior to release 2022-11-03 00:00:09 -04:00
65a99c47d3 add missing documentation image 2022-11-02 23:41:50 -04:00
e4bb49b4f0 update outpaint documentation 2022-11-02 23:41:16 -04:00
2ad489a1ef dream->invoke in inpainting docs 2022-11-02 23:18:30 -04:00
ecb904f8b7 update environment-mac.yml 2022-11-02 23:12:48 -04:00
61ead2c92d replace old fashined markdown templates with forms
this will help the readability of issues a lot 🤓
2022-11-02 22:26:01 -04:00
c5a8c499ab Raise exception instead of undefined internal state
Hi, please consider raising a proper exception here instead of an undefined internal state. This happens for example if the filepath to the model.ckpt is invalid on first load.
2022-11-02 22:26:00 -04:00
bd6278c361 Fixes indentation causing rendering issue with github.io page 2022-11-02 22:25:13 -04:00
e24d4dc15b Fix discord link
The discord badge has the correct link but the quick links did not
2022-11-02 22:25:12 -04:00
3d4c70604d update requirements to address #1149 2022-11-02 22:25:12 -04:00
d73aea43b7 update precision info 2022-11-02 22:17:50 -04:00
358f0af79a fix prompt in README.md 2022-11-02 22:17:50 -04:00
0650735f74 (re-) fix a lot in mkdocs 2022-11-02 22:17:50 -04:00
e469bbb89e fix links to point to invoke-ai.github.io 2022-11-02 22:17:14 -04:00
a46633a355 adding license using GitHub template
Did not attempt to add additional copyright information.
2022-11-02 22:17:14 -04:00
7275006c37 remove license files temporarily 2022-11-02 22:17:14 -04:00
e438d46314 remove additional copyrights from license file
Trying to get GitHub to recognize our MIT license. Perhaps the additional copyrights are confusing it.
2022-11-02 22:17:14 -04:00
bf8d6d8908 Second try at getting GitHub to register license 2022-11-02 22:17:13 -04:00
b9e1aeb2dd Fix broken links to CLI.md
* Looks like there was a bad paste
2022-11-02 22:16:28 -04:00
fd81a69b4d add current branch to push trigger 2022-11-02 22:16:13 -04:00
5a15ad3148 switch to default channel in environment-mac.yml 2022-11-02 22:15:45 -04:00
22a37ef714 use very short validation for Pull Requests 2022-11-02 22:12:15 -04:00
59c8024f0c remove pr trigger 2022-11-02 22:10:31 -04:00
22b3a59f16 squash merge update-gh-actions into fix-gh-actions
* fix mkdocs deployment

* update path to python bin

* add trigger for current branch

* change path to python_bin for mac as well

* try to use setup-python@v4 instead of setting env

* remove setup conda action

* try to use $CONDA

* remove overseen action

* change branch from master to main

* sort out if then else for faster syntax

* remove more if functions

* add updates to create-caches as well

* eliminate the rest of if functions

* try to unpin pytorch and torchvision

* restore pinned versions

* try switching from set-output to use env

* update test-invoke-conda as well

* fix env var creation

* quote variable

* add second equal to compare

* try another way to use outputs

* fix outputs

* pip install for mac before creating conda env

* fix output variable

* fix python bin path

* remove pip install for before creating conda env

* unpin streamlit version in conda mac env

* try to make git-workflows better readable

* remove 4gotten trigger

* Update-gh-actions (#6)

* fix mkdocs deployment

* update path to python bin

* add trigger for current branch

* change path to python_bin for mac as well

* try to use setup-python@v4 instead of setting env

* remove setup conda action

* try to use $CONDA

* remove overseen action

* change branch from master to main

* sort out if then else for faster syntax

* remove more if functions

* add updates to create-caches as well

* eliminate the rest of if functions

* try to unpin pytorch and torchvision

* restore pinned versions

* try switching from set-output to use env

* update test-invoke-conda as well

* fix env var creation

* quote variable

* add second equal to compare

* try another way to use outputs

* fix outputs

* pip install for mac before creating conda env

* fix output variable

* fix python bin path

* remove pip install for before creating conda env

* unpin streamlit version in conda mac env

* try to make git-workflows better readable

* use macos-latest

* try to update conda before creating mac env

* better conda update trial

* re-pin streamlit version

* re-added trigger to run workflow in current branch

* try to find out if conda mac env could be updated

* install cmake, protobuf and rust b4 conda

* add yes to conda update

* lets try anaconda3-2022.05

* try environment.yml for mac as well

* reenable conda mac env, add pip install
also fix gitignore by changing from dream to invoke

* remove
- unecesary virtualenv creation
- conda update

change != macos back to == linux

* remove cmake from brew install since pre-installed

* disable opencv-python pip requirement

* fixed commands to find latest package versions

* update requirements for mac env

* back to the roots - only install conda env
depending on runner_os with or without extra env variables

* check out macOS in azure-pipelines
since becoming kind of tired of the GitHub Runner which is broken as ...

* let's try to setup python and update conda env

* initialize conda before using it

* add trigger in azure-pipelines.yml

* And another go for update first ....

* update azure-pipelines.yml
- add caching
- add checkpoint download
- add paths to trigger
and more

* unquote checkpoint-url

* fix chekpoint-url variable

* mkdir before downloading model

* set pr trigger to main, rename anaconda cache

* unique cacheHitVariables

* try to use macos-latest instead of macos-12

* update test-invoke-conda.yml:
- remove unecesarry echo step
- use s-weigand/setup-conda@v1
- remove conda update from install deps step since updated with action

* update test-invoke-conda.yml:
- rename conda env cache from ldm to invokeai
- reorder steps:
  1. checkout sources
  2. setup python
  3. setup conda
  4. keep order after set platform variables

* change macos back to 12 since also fails with 11

* update condition in run the tests
make difference between main or not main

* fix path to cache invokeai conda env

* fix invokeai conda env cache path

* update mkdocs-flow.yml

* change conda-channel priority

* update create-caches

* update conda env also when cache was used

* os dependend conda env cache path

* use existing CONDA env pointing to conda root

* create CONDA_ROOT output from $CONDA

* use output variable to define test prompts

* use setup-python v4, get rid of PYTHON_BIN env

* add runner.os to result artifacts name

* update test-invoke-conda.yml:
- reuse macos-latest
- disable setup python 3.9
- setup conda with default python version
- create or update conda environment depending on cache success
- remove name parameter from conda update since name is set in env yml

* improve mkdocs-flow.yml

* disable cache-hugginface-torch
since preload_models.py downloads to more than one location

* update mkdocs-flow.yml with new name

* rename mkdocs action to mkdocs-material

* try to ignore error when creating conda env
maybe it would still be usable, lets see ;P

* remove bloat

* update environment-mac.yml
to match dependencies of invoke-ai/InvokeAI's main branch

* disable conda update, tweak prompt condition

* try to set some env vars for macOS to fix conda

* stop ignoring error, use env instead of outputs

* tweak `[[` connditions

* update python and pip dependencie
makes a difference of 1 sec per itteration compared to 3.9!!!
also I see no reason why using a old pip version would be beneficial

* remove unecesarry env for macOS
everything was pre-tested on my MacBook Air 2020 with M1

* update conda env in setup step

* activate conda env after installation

* update test-invoke-conda.yml
- set conda env dependent on matrix.os
- set CONDA_ENV_NAME to prevent breaking action when renaming conda env
- fix conda env activation

* fix activate conda env

* set bash -l as default shell

* use action to activate conda env

* add conda env file to env activation

* try to replace s-weigeand with conda-incubator

* remove azure-pipelines.yml
funniest part is that the macos runner is the same as the one on github!

* include environment-file in matrix
- also disable auto-activate-base and auto-update-conda
- include macos-latest and macos-12 for debugging purpose
- set miniforge-version in matrix

* fix miniforge-variant, set fail-fast to false

* add step to setup miniconda
- make default shell a matrix variable
- remove bloat

* use a mac env yml without pinned versions

* unpin nomkl, pytorch and torchvision
also removed opencv-pyhton

* cache conda pkgs dir instead of conda env

* use python 3.10, exclude macos-12 from cache

* fix expression

* prepare for PR

* fix doubled id

* reuse pinned versions in mac conda env
- updated python pip version
- unpined pytorch and torchvision
- removed opencv-python
- updated versions to most recent (tested locally)

* fix classical copy/paste error

* remove unused env from shell-block comment

* fix hashFiles function to determine restore-keys

* reenable caching `~.cache`, update create-caches

* unpin all versions in mac conda env file
this was the only way I got it working in the action, also works locally
tested on MacBook Air 2020 M1
remove environment-mac-unpinned.yml

* prepare merge by removing this branch from trigger

* include pull_request trigger for main and dev

* remove pull_request trigger
2022-11-02 22:10:31 -04:00
48e21486cb remove pr trigger 2022-11-02 22:07:42 -04:00
a6fa882b7c squash merge update-gh-actions into fix-gh-actions
* fix mkdocs deployment

* update path to python bin

* add trigger for current branch

* change path to python_bin for mac as well

* try to use setup-python@v4 instead of setting env

* remove setup conda action

* try to use $CONDA

* remove overseen action

* change branch from master to main

* sort out if then else for faster syntax

* remove more if functions

* add updates to create-caches as well

* eliminate the rest of if functions

* try to unpin pytorch and torchvision

* restore pinned versions

* try switching from set-output to use env

* update test-invoke-conda as well

* fix env var creation

* quote variable

* add second equal to compare

* try another way to use outputs

* fix outputs

* pip install for mac before creating conda env

* fix output variable

* fix python bin path

* remove pip install for before creating conda env

* unpin streamlit version in conda mac env

* try to make git-workflows better readable

* remove 4gotten trigger

* Update-gh-actions (#6)

* fix mkdocs deployment

* update path to python bin

* add trigger for current branch

* change path to python_bin for mac as well

* try to use setup-python@v4 instead of setting env

* remove setup conda action

* try to use $CONDA

* remove overseen action

* change branch from master to main

* sort out if then else for faster syntax

* remove more if functions

* add updates to create-caches as well

* eliminate the rest of if functions

* try to unpin pytorch and torchvision

* restore pinned versions

* try switching from set-output to use env

* update test-invoke-conda as well

* fix env var creation

* quote variable

* add second equal to compare

* try another way to use outputs

* fix outputs

* pip install for mac before creating conda env

* fix output variable

* fix python bin path

* remove pip install for before creating conda env

* unpin streamlit version in conda mac env

* try to make git-workflows better readable

* use macos-latest

* try to update conda before creating mac env

* better conda update trial

* re-pin streamlit version

* re-added trigger to run workflow in current branch

* try to find out if conda mac env could be updated

* install cmake, protobuf and rust b4 conda

* add yes to conda update

* lets try anaconda3-2022.05

* try environment.yml for mac as well

* reenable conda mac env, add pip install
also fix gitignore by changing from dream to invoke

* remove
- unecesary virtualenv creation
- conda update

change != macos back to == linux

* remove cmake from brew install since pre-installed

* disable opencv-python pip requirement

* fixed commands to find latest package versions

* update requirements for mac env

* back to the roots - only install conda env
depending on runner_os with or without extra env variables

* check out macOS in azure-pipelines
since becoming kind of tired of the GitHub Runner which is broken as ...

* let's try to setup python and update conda env

* initialize conda before using it

* add trigger in azure-pipelines.yml

* And another go for update first ....

* update azure-pipelines.yml
- add caching
- add checkpoint download
- add paths to trigger
and more

* unquote checkpoint-url

* fix chekpoint-url variable

* mkdir before downloading model

* set pr trigger to main, rename anaconda cache

* unique cacheHitVariables

* try to use macos-latest instead of macos-12

* update test-invoke-conda.yml:
- remove unecesarry echo step
- use s-weigand/setup-conda@v1
- remove conda update from install deps step since updated with action

* update test-invoke-conda.yml:
- rename conda env cache from ldm to invokeai
- reorder steps:
  1. checkout sources
  2. setup python
  3. setup conda
  4. keep order after set platform variables

* change macos back to 12 since also fails with 11

* update condition in run the tests
make difference between main or not main

* fix path to cache invokeai conda env

* fix invokeai conda env cache path

* update mkdocs-flow.yml

* change conda-channel priority

* update create-caches

* update conda env also when cache was used

* os dependend conda env cache path

* use existing CONDA env pointing to conda root

* create CONDA_ROOT output from $CONDA

* use output variable to define test prompts

* use setup-python v4, get rid of PYTHON_BIN env

* add runner.os to result artifacts name

* update test-invoke-conda.yml:
- reuse macos-latest
- disable setup python 3.9
- setup conda with default python version
- create or update conda environment depending on cache success
- remove name parameter from conda update since name is set in env yml

* improve mkdocs-flow.yml

* disable cache-hugginface-torch
since preload_models.py downloads to more than one location

* update mkdocs-flow.yml with new name

* rename mkdocs action to mkdocs-material

* try to ignore error when creating conda env
maybe it would still be usable, lets see ;P

* remove bloat

* update environment-mac.yml
to match dependencies of invoke-ai/InvokeAI's main branch

* disable conda update, tweak prompt condition

* try to set some env vars for macOS to fix conda

* stop ignoring error, use env instead of outputs

* tweak `[[` connditions

* update python and pip dependencie
makes a difference of 1 sec per itteration compared to 3.9!!!
also I see no reason why using a old pip version would be beneficial

* remove unecesarry env for macOS
everything was pre-tested on my MacBook Air 2020 with M1

* update conda env in setup step

* activate conda env after installation

* update test-invoke-conda.yml
- set conda env dependent on matrix.os
- set CONDA_ENV_NAME to prevent breaking action when renaming conda env
- fix conda env activation

* fix activate conda env

* set bash -l as default shell

* use action to activate conda env

* add conda env file to env activation

* try to replace s-weigeand with conda-incubator

* remove azure-pipelines.yml
funniest part is that the macos runner is the same as the one on github!

* include environment-file in matrix
- also disable auto-activate-base and auto-update-conda
- include macos-latest and macos-12 for debugging purpose
- set miniforge-version in matrix

* fix miniforge-variant, set fail-fast to false

* add step to setup miniconda
- make default shell a matrix variable
- remove bloat

* use a mac env yml without pinned versions

* unpin nomkl, pytorch and torchvision
also removed opencv-pyhton

* cache conda pkgs dir instead of conda env

* use python 3.10, exclude macos-12 from cache

* fix expression

* prepare for PR

* fix doubled id

* reuse pinned versions in mac conda env
- updated python pip version
- unpined pytorch and torchvision
- removed opencv-python
- updated versions to most recent (tested locally)

* fix classical copy/paste error

* remove unused env from shell-block comment

* fix hashFiles function to determine restore-keys

* reenable caching `~.cache`, update create-caches

* unpin all versions in mac conda env file
this was the only way I got it working in the action, also works locally
tested on MacBook Air 2020 M1
remove environment-mac-unpinned.yml

* prepare merge by removing this branch from trigger

* include pull_request trigger for main and dev

* remove pull_request trigger
2022-11-02 22:07:42 -04:00
aa12adccf3 restore inline images
<div> around the inline images works great in gh-pages, but breaks plain old markdown in GitHub code display. This removes the <div>s, causing slight degradation in quality of gh-page appearance.
2022-11-02 22:02:17 -04:00
282a2f642b restore inline images
<div> seems to be messing with the ability of the plain-old markdown processor to display inline images. Slightly degrades appearance of gh-pages.
2022-11-02 22:02:16 -04:00
d211c34f7b Update 'ldm' env to 'invokeai' in troubleshooting steps 2022-11-02 22:01:48 -04:00
e995e97690 Update generate.py
Fixed spelling mistake (open source king)
2022-11-02 22:01:17 -04:00
1524 changed files with 66307 additions and 320005 deletions

View File

@ -1,25 +1,3 @@
# use this file as a whitelist
*
!invokeai
!ldm
!pyproject.toml
# ignore frontend/web but whitelist dist
invokeai/frontend/web/
!invokeai/frontend/web/dist/
# ignore invokeai/assets but whitelist invokeai/assets/web
invokeai/assets/
!invokeai/assets/web/
# Guard against pulling in any models that might exist in the directory tree
**/*.pt*
**/*.ckpt
# Byte-compiled / optimized / DLL files
**/__pycache__/
**/*.py[cod]
# Distribution / packaging
**/*.egg-info/
**/*.egg
!environment*.yml
!docker-build

View File

@ -1,12 +0,0 @@
# All files
[*]
charset = utf-8
end_of_line = lf
indent_size = 2
indent_style = space
insert_final_newline = true
trim_trailing_whitespace = true
# Python
[*.py]
indent_size = 4

View File

@ -1 +0,0 @@
b3dccfaeb636599c02effc377cdd8a87d658256c

2
.gitattributes vendored
View File

@ -1,4 +1,4 @@
# Auto normalizes line endings on commit so devs don't need to change local settings.
# Only affects text files and ignores other file types.
# Only affects text files and ignores other file types.
# For more info see: https://www.aleksandrhovhannisyan.com/blog/crlf-vs-lf-normalizing-line-endings-in-git/
* text=auto

38
.github/CODEOWNERS vendored
View File

@ -1,34 +1,4 @@
# continuous integration
/.github/workflows/ @lstein @blessedcoolant
# documentation
/docs/ @lstein @blessedcoolant @hipsterusername
/mkdocs.yml @lstein @blessedcoolant
# nodes
/invokeai/app/ @Kyle0654 @blessedcoolant
# installation and configuration
/pyproject.toml @lstein @blessedcoolant
/docker/ @lstein @blessedcoolant
/scripts/ @ebr @lstein
/installer/ @lstein @ebr
/invokeai/assets @lstein @ebr
/invokeai/configs @lstein
/invokeai/version @lstein @blessedcoolant
# web ui
/invokeai/frontend @blessedcoolant @psychedelicious @lstein @maryhipp
/invokeai/backend @blessedcoolant @psychedelicious @lstein @maryhipp
# generation, model management, postprocessing
/invokeai/backend @damian0815 @lstein @blessedcoolant @jpphoto @gregghelt2 @StAlKeR7779
# front ends
/invokeai/frontend/CLI @lstein
/invokeai/frontend/install @lstein @ebr
/invokeai/frontend/merge @lstein @blessedcoolant
/invokeai/frontend/training @lstein @blessedcoolant
/invokeai/frontend/web @psychedelicious @blessedcoolant @maryhipp
ldm/invoke/pngwriter.py @CapableWeb
ldm/invoke/server_legacy.py @CapableWeb
scripts/legacy_api.py @CapableWeb
tests/legacy_tests.sh @CapableWeb

View File

@ -65,16 +65,6 @@ body:
placeholder: 8GB
validations:
required: false
- type: input
id: version-number
attributes:
label: What version did you experience this issue on?
description: |
Please share the version of Invoke AI that you experienced the issue on. If this is not the latest version, please update first to confirm the issue still exists. If you are testing main, please include the commit hash instead.
placeholder: X.X.X
validations:
required: true
- type: textarea
id: what-happened

19
.github/stale.yaml vendored
View File

@ -1,19 +0,0 @@
# Number of days of inactivity before an issue becomes stale
daysUntilStale: 28
# Number of days of inactivity before a stale issue is closed
daysUntilClose: 14
# Issues with these labels will never be considered stale
exemptLabels:
- pinned
- security
# Label to use when marking an issue as stale
staleLabel: stale
# Comment to post when marking an issue as stale. Set to `false` to disable
markComment: >
This issue has been automatically marked as stale because it has not had
recent activity. It will be closed if no further activity occurs. Please
update the ticket if this is still a problem on the latest release.
# Comment to post when closing a stale issue. Set to `false` to disable
closeComment: >
Due to inactivity, this issue has been automatically closed. If this is
still a problem on the latest release, please recreate the issue.

View File

@ -1,114 +1,42 @@
# Building the Image without pushing to confirm it is still buildable
# confirum functionality would unfortunately need way more resources
name: build container image
on:
push:
branches:
- 'main'
- 'update/ci/docker/*'
- 'update/docker/*'
- 'dev/ci/docker/*'
- 'dev/docker/*'
paths:
- 'pyproject.toml'
- '.dockerignore'
- 'invokeai/**'
- 'docker/Dockerfile'
tags:
- 'v*.*.*'
workflow_dispatch:
permissions:
contents: write
packages: write
- 'development'
pull_request:
branches:
- 'main'
- 'development'
jobs:
docker:
if: github.event.pull_request.draft == false
strategy:
fail-fast: false
matrix:
flavor:
- rocm
- cuda
- cpu
include:
- flavor: rocm
pip-extra-index-url: 'https://download.pytorch.org/whl/rocm5.2'
- flavor: cuda
pip-extra-index-url: ''
- flavor: cpu
pip-extra-index-url: 'https://download.pytorch.org/whl/cpu'
runs-on: ubuntu-latest
name: ${{ matrix.flavor }}
env:
PLATFORMS: 'linux/amd64,linux/arm64'
DOCKERFILE: 'docker/Dockerfile'
steps:
- name: prepare docker-tag
env:
repository: ${{ github.repository }}
run: echo "dockertag=${repository,,}" >> $GITHUB_ENV
- name: Checkout
uses: actions/checkout@v3
- name: Docker meta
id: meta
uses: docker/metadata-action@v4
with:
github-token: ${{ secrets.GITHUB_TOKEN }}
images: |
ghcr.io/${{ github.repository }}
${{ vars.DOCKERHUB_REPOSITORY }}
tags: |
type=ref,event=branch
type=ref,event=tag
type=pep440,pattern={{version}}
type=pep440,pattern={{major}}.{{minor}}
type=pep440,pattern={{major}}
type=sha,enable=true,prefix=sha-,format=short
flavor: |
latest=${{ matrix.flavor == 'cuda' && github.ref == 'refs/heads/main' }}
suffix=-${{ matrix.flavor }},onlatest=false
- name: Set up QEMU
uses: docker/setup-qemu-action@v2
- name: Set up Docker Buildx
uses: docker/setup-buildx-action@v2
- name: Cache Docker layers
uses: actions/cache@v2
with:
platforms: ${{ env.PLATFORMS }}
- name: Login to GitHub Container Registry
if: github.event_name != 'pull_request'
uses: docker/login-action@v2
with:
registry: ghcr.io
username: ${{ github.repository_owner }}
password: ${{ secrets.GITHUB_TOKEN }}
- name: Login to Docker Hub
if: github.event_name != 'pull_request' && vars.DOCKERHUB_REPOSITORY != ''
uses: docker/login-action@v2
with:
username: ${{ secrets.DOCKERHUB_USERNAME }}
password: ${{ secrets.DOCKERHUB_TOKEN }}
path: /tmp/.buildx-cache
key: buildx-${{ hashFiles('docker-build/Dockerfile') }}
- name: Build container
id: docker_build
uses: docker/build-push-action@v4
uses: docker/build-push-action@v3
with:
context: .
file: ${{ env.DOCKERFILE }}
platforms: ${{ env.PLATFORMS }}
push: ${{ github.ref == 'refs/heads/main' || github.ref_type == 'tag' }}
tags: ${{ steps.meta.outputs.tags }}
labels: ${{ steps.meta.outputs.labels }}
build-args: PIP_EXTRA_INDEX_URL=${{ matrix.pip-extra-index-url }}
cache-from: |
type=gha,scope=${{ github.ref_name }}-${{ matrix.flavor }}
type=gha,scope=main-${{ matrix.flavor }}
cache-to: type=gha,mode=max,scope=${{ github.ref_name }}-${{ matrix.flavor }}
- name: Docker Hub Description
if: github.ref == 'refs/heads/main' || github.ref == 'refs/tags/*' && vars.DOCKERHUB_REPOSITORY != ''
uses: peter-evans/dockerhub-description@v3
with:
username: ${{ secrets.DOCKERHUB_USERNAME }}
password: ${{ secrets.DOCKERHUB_TOKEN }}
repository: ${{ vars.DOCKERHUB_REPOSITORY }}
short-description: ${{ github.event.repository.description }}
file: docker-build/Dockerfile
platforms: linux/amd64
push: false
tags: ${{ env.dockertag }}:latest
cache-from: type=local,src=/tmp/.buildx-cache
cache-to: type=local,dest=/tmp/.buildx-cache

View File

@ -1,34 +0,0 @@
name: cleanup caches by a branch
on:
pull_request:
types:
- closed
workflow_dispatch:
jobs:
cleanup:
runs-on: ubuntu-latest
steps:
- name: Check out code
uses: actions/checkout@v3
- name: Cleanup
run: |
gh extension install actions/gh-actions-cache
REPO=${{ github.repository }}
BRANCH=${{ github.ref }}
echo "Fetching list of cache key"
cacheKeysForPR=$(gh actions-cache list -R $REPO -B $BRANCH | cut -f 1 )
## Setting this to not fail the workflow while deleting cache keys.
set +e
echo "Deleting caches..."
for cacheKey in $cacheKeysForPR
do
gh actions-cache delete $cacheKey -R $REPO -B $BRANCH --confirm
done
echo "Done"
env:
GH_TOKEN: ${{ secrets.GITHUB_TOKEN }}

View File

@ -1,27 +0,0 @@
name: Close inactive issues
on:
schedule:
- cron: "00 6 * * *"
env:
DAYS_BEFORE_ISSUE_STALE: 14
DAYS_BEFORE_ISSUE_CLOSE: 28
jobs:
close-issues:
runs-on: ubuntu-latest
permissions:
issues: write
pull-requests: write
steps:
- uses: actions/stale@v5
with:
days-before-issue-stale: ${{ env.DAYS_BEFORE_ISSUE_STALE }}
days-before-issue-close: ${{ env.DAYS_BEFORE_ISSUE_CLOSE }}
stale-issue-label: "Inactive Issue"
stale-issue-message: "There has been no activity in this issue for ${{ env.DAYS_BEFORE_ISSUE_STALE }} days. If this issue is still being experienced, please reply with an updated confirmation that the issue is still being experienced with the latest release."
close-issue-message: "Due to inactivity, this issue was automatically closed. If you are still experiencing the issue, please recreate the issue."
days-before-pr-stale: -1
days-before-pr-close: -1
repo-token: ${{ secrets.GITHUB_TOKEN }}
operations-per-run: 500

80
.github/workflows/create-caches.yml vendored Normal file
View File

@ -0,0 +1,80 @@
name: Create Caches
on: workflow_dispatch
jobs:
os_matrix:
strategy:
matrix:
os: [ubuntu-latest, macos-latest]
include:
- os: ubuntu-latest
environment-file: environment.yml
default-shell: bash -l {0}
- os: macos-latest
environment-file: environment-mac.yml
default-shell: bash -l {0}
name: Test invoke.py on ${{ matrix.os }} with conda
runs-on: ${{ matrix.os }}
defaults:
run:
shell: ${{ matrix.default-shell }}
steps:
- name: Checkout sources
uses: actions/checkout@v3
- name: setup miniconda
uses: conda-incubator/setup-miniconda@v2
with:
auto-activate-base: false
auto-update-conda: false
miniconda-version: latest
- name: set environment
run: |
[[ "$GITHUB_REF" == 'refs/heads/main' ]] \
&& echo "TEST_PROMPTS=tests/preflight_prompts.txt" >> $GITHUB_ENV \
|| echo "TEST_PROMPTS=tests/dev_prompts.txt" >> $GITHUB_ENV
echo "CONDA_ROOT=$CONDA" >> $GITHUB_ENV
echo "CONDA_ENV_NAME=invokeai" >> $GITHUB_ENV
- name: Use Cached Stable Diffusion v1.4 Model
id: cache-sd-v1-4
uses: actions/cache@v3
env:
cache-name: cache-sd-v1-4
with:
path: models/ldm/stable-diffusion-v1/model.ckpt
key: ${{ env.cache-name }}
restore-keys: ${{ env.cache-name }}
- name: Download Stable Diffusion v1.4 Model
if: ${{ steps.cache-sd-v1-4.outputs.cache-hit != 'true' }}
run: |
[[ -d models/ldm/stable-diffusion-v1 ]] \
|| mkdir -p models/ldm/stable-diffusion-v1
[[ -r models/ldm/stable-diffusion-v1/model.ckpt ]] \
|| curl \
-H "Authorization: Bearer ${{ secrets.HUGGINGFACE_TOKEN }}" \
-o models/ldm/stable-diffusion-v1/model.ckpt \
-L https://huggingface.co/CompVis/stable-diffusion-v-1-4-original/resolve/main/sd-v1-4.ckpt
- name: Activate Conda Env
uses: conda-incubator/setup-miniconda@v2
with:
activate-environment: ${{ env.CONDA_ENV_NAME }}
environment-file: ${{ matrix.environment-file }}
- name: Use Cached Huggingface and Torch models
id: cache-hugginface-torch
uses: actions/cache@v3
env:
cache-name: cache-hugginface-torch
with:
path: ~/.cache
key: ${{ env.cache-name }}
restore-keys: |
${{ env.cache-name }}-${{ hashFiles('scripts/preload_models.py') }}
- name: run preload_models.py
run: python scripts/preload_models.py

View File

@ -1,37 +0,0 @@
name: Lint frontend
on:
pull_request:
paths:
- 'invokeai/frontend/web/**'
types:
- 'ready_for_review'
- 'opened'
- 'synchronize'
push:
branches:
- 'main'
paths:
- 'invokeai/frontend/web/**'
merge_group:
workflow_dispatch:
defaults:
run:
working-directory: invokeai/frontend/web
jobs:
lint-frontend:
if: github.event.pull_request.draft == false
runs-on: ubuntu-22.04
steps:
- name: Setup Node 18
uses: actions/setup-node@v3
with:
node-version: '18'
- uses: actions/checkout@v3
- run: 'yarn install --frozen-lockfile'
- run: 'yarn run lint:tsc'
- run: 'yarn run lint:madge'
- run: 'yarn run lint:eslint'
- run: 'yarn run lint:prettier'

View File

@ -2,19 +2,12 @@ name: mkdocs-material
on:
push:
branches:
- 'refs/heads/v2.3'
permissions:
contents: write
- 'main'
- 'development'
jobs:
mkdocs-material:
if: github.event.pull_request.draft == false
runs-on: ubuntu-latest
env:
REPO_URL: '${{ github.server_url }}/${{ github.repository }}'
REPO_NAME: '${{ github.repository }}'
SITE_URL: 'https://${{ github.repository_owner }}.github.io/InvokeAI'
steps:
- name: checkout sources
uses: actions/checkout@v3
@ -25,15 +18,11 @@ jobs:
uses: actions/setup-python@v4
with:
python-version: '3.10'
cache: pip
cache-dependency-path: pyproject.toml
- name: install requirements
env:
PIP_USE_PEP517: 1
run: |
python -m \
pip install ".[docs]"
pip install -r requirements-mkdocs.txt
- name: confirm buildability
run: |
@ -43,7 +32,7 @@ jobs:
--verbose
- name: deploy to gh-pages
if: ${{ github.ref == 'refs/heads/v2.3' }}
if: ${{ github.ref == 'refs/heads/main' }}
run: |
python -m \
mkdocs gh-deploy \

View File

@ -1,20 +0,0 @@
on:
pull_request:
push:
branches:
- main
- development
- 'release-candidate-*'
jobs:
pyflakes:
name: runner / pyflakes
if: github.event.pull_request.draft == false
runs-on: ubuntu-latest
steps:
- uses: actions/checkout@v2
- name: pyflakes
uses: reviewdog/action-pyflakes@v1
with:
github_token: ${{ secrets.GITHUB_TOKEN }}
reporter: github-pr-review

View File

@ -1,41 +0,0 @@
name: PyPI Release
on:
push:
paths:
- 'invokeai/version/invokeai_version.py'
workflow_dispatch:
jobs:
release:
if: github.repository == 'invoke-ai/InvokeAI'
runs-on: ubuntu-22.04
env:
TWINE_USERNAME: __token__
TWINE_PASSWORD: ${{ secrets.PYPI_API_TOKEN }}
TWINE_NON_INTERACTIVE: 1
steps:
- name: checkout sources
uses: actions/checkout@v3
- name: install deps
run: pip install --upgrade build twine
- name: build package
run: python3 -m build
- name: check distribution
run: twine check dist/*
- name: check PyPI versions
if: github.ref == 'refs/heads/main' || github.ref == 'refs/heads/v2.3'
run: |
pip install --upgrade requests
python -c "\
import scripts.pypi_helper; \
EXISTS=scripts.pypi_helper.local_on_pypi(); \
print(f'PACKAGE_EXISTS={EXISTS}')" >> $GITHUB_ENV
- name: upload package
if: env.PACKAGE_EXISTS == 'False' && env.TWINE_PASSWORD != ''
run: twine upload dist/*

113
.github/workflows/test-invoke-conda.yml vendored Normal file
View File

@ -0,0 +1,113 @@
name: Test invoke.py
on:
push:
branches:
- 'main'
- 'development'
- 'fix-gh-actions-fork'
pull_request:
branches:
- 'main'
- 'development'
jobs:
matrix:
strategy:
fail-fast: false
matrix:
stable-diffusion-model:
# - 'https://huggingface.co/CompVis/stable-diffusion-v-1-4-original/resolve/main/sd-v1-4.ckpt'
- 'https://huggingface.co/runwayml/stable-diffusion-v1-5/resolve/main/v1-5-pruned-emaonly.ckpt'
os:
- ubuntu-latest
- macOS-12
include:
- os: ubuntu-latest
environment-file: environment.yml
default-shell: bash -l {0}
- os: macOS-12
environment-file: environment-mac.yml
default-shell: bash -l {0}
# - stable-diffusion-model: https://huggingface.co/CompVis/stable-diffusion-v-1-4-original/resolve/main/sd-v1-4.ckpt
# stable-diffusion-model-dl-path: models/ldm/stable-diffusion-v1/sd-v1-4.ckpt
# stable-diffusion-model-switch: stable-diffusion-1.4
- stable-diffusion-model: https://huggingface.co/runwayml/stable-diffusion-v1-5/resolve/main/v1-5-pruned-emaonly.ckpt
stable-diffusion-model-dl-path: models/ldm/stable-diffusion-v1/v1-5-pruned-emaonly.ckpt
stable-diffusion-model-switch: stable-diffusion-1.5
name: ${{ matrix.os }} with ${{ matrix.stable-diffusion-model-switch }}
runs-on: ${{ matrix.os }}
env:
CONDA_ENV_NAME: invokeai
defaults:
run:
shell: ${{ matrix.default-shell }}
steps:
- name: Checkout sources
id: checkout-sources
uses: actions/checkout@v3
- name: create models.yaml from example
run: cp configs/models.yaml.example configs/models.yaml
- name: Use cached conda packages
id: use-cached-conda-packages
uses: actions/cache@v3
with:
path: ~/conda_pkgs_dir
key: conda-pkgs-${{ runner.os }}-${{ runner.arch }}-${{ hashFiles(matrix.environment-file) }}
- name: Activate Conda Env
id: activate-conda-env
uses: conda-incubator/setup-miniconda@v2
with:
activate-environment: ${{ env.CONDA_ENV_NAME }}
environment-file: ${{ matrix.environment-file }}
miniconda-version: latest
- name: set test prompt to main branch validation
if: ${{ github.ref == 'refs/heads/main' }}
run: echo "TEST_PROMPTS=tests/preflight_prompts.txt" >> $GITHUB_ENV
- name: set test prompt to development branch validation
if: ${{ github.ref == 'refs/heads/development' }}
run: echo "TEST_PROMPTS=tests/dev_prompts.txt" >> $GITHUB_ENV
- name: set test prompt to Pull Request validation
if: ${{ github.ref != 'refs/heads/main' && github.ref != 'refs/heads/development' }}
run: echo "TEST_PROMPTS=tests/validate_pr_prompt.txt" >> $GITHUB_ENV
- name: Download ${{ matrix.stable-diffusion-model-switch }}
id: download-stable-diffusion-model
run: |
[[ -d models/ldm/stable-diffusion-v1 ]] \
|| mkdir -p models/ldm/stable-diffusion-v1
curl \
-H "Authorization: Bearer ${{ secrets.HUGGINGFACE_TOKEN }}" \
-o ${{ matrix.stable-diffusion-model-dl-path }} \
-L ${{ matrix.stable-diffusion-model }}
- name: run preload_models.py
id: run-preload-models
run: |
python scripts/preload_models.py \
--no-interactive
- name: Run the tests
id: run-tests
run: |
time python scripts/invoke.py \
--model ${{ matrix.stable-diffusion-model-switch }} \
--from_file ${{ env.TEST_PROMPTS }}
- name: export conda env
id: export-conda-env
run: |
mkdir -p outputs/img-samples
conda env export --name ${{ env.CONDA_ENV_NAME }} > outputs/img-samples/environment-${{ runner.os }}-${{ runner.arch }}.yml
- name: Archive results
id: archive-results
uses: actions/upload-artifact@v3
with:
name: results_${{ matrix.os }}_${{ matrix.stable-diffusion-model-switch }}
path: outputs/img-samples

View File

@ -1,66 +0,0 @@
name: Test invoke.py pip
on:
pull_request:
paths:
- '**'
- '!pyproject.toml'
- '!invokeai/**'
- 'invokeai/frontend/web/**'
merge_group:
workflow_dispatch:
concurrency:
group: ${{ github.workflow }}-${{ github.head_ref || github.run_id }}
cancel-in-progress: true
jobs:
matrix:
if: github.event.pull_request.draft == false
strategy:
matrix:
python-version:
# - '3.9'
- '3.10'
pytorch:
# - linux-cuda-11_6
- linux-cuda-11_7
- linux-rocm-5_2
- linux-cpu
- macos-default
- windows-cpu
# - windows-cuda-11_6
# - windows-cuda-11_7
include:
# - pytorch: linux-cuda-11_6
# os: ubuntu-22.04
# extra-index-url: 'https://download.pytorch.org/whl/cu116'
# github-env: $GITHUB_ENV
- pytorch: linux-cuda-11_7
os: ubuntu-22.04
github-env: $GITHUB_ENV
- pytorch: linux-rocm-5_2
os: ubuntu-22.04
extra-index-url: 'https://download.pytorch.org/whl/rocm5.2'
github-env: $GITHUB_ENV
- pytorch: linux-cpu
os: ubuntu-22.04
extra-index-url: 'https://download.pytorch.org/whl/cpu'
github-env: $GITHUB_ENV
- pytorch: macos-default
os: macOS-12
github-env: $GITHUB_ENV
- pytorch: windows-cpu
os: windows-2022
github-env: $env:GITHUB_ENV
# - pytorch: windows-cuda-11_6
# os: windows-2022
# extra-index-url: 'https://download.pytorch.org/whl/cu116'
# github-env: $env:GITHUB_ENV
# - pytorch: windows-cuda-11_7
# os: windows-2022
# extra-index-url: 'https://download.pytorch.org/whl/cu117'
# github-env: $env:GITHUB_ENV
name: ${{ matrix.pytorch }} on ${{ matrix.python-version }}
runs-on: ${{ matrix.os }}
steps:
- run: 'echo "No build required"'

View File

@ -1,139 +0,0 @@
name: Test invoke.py pip
on:
push:
branches:
- 'main'
paths:
- 'pyproject.toml'
- 'invokeai/**'
- '!invokeai/frontend/web/**'
pull_request:
paths:
- 'pyproject.toml'
- 'invokeai/**'
- '!invokeai/frontend/web/**'
types:
- 'ready_for_review'
- 'opened'
- 'synchronize'
merge_group:
workflow_dispatch:
concurrency:
group: ${{ github.workflow }}-${{ github.head_ref || github.run_id }}
cancel-in-progress: true
jobs:
matrix:
if: github.event.pull_request.draft == false
strategy:
matrix:
python-version:
# - '3.9'
- '3.10'
pytorch:
# - linux-cuda-11_6
- linux-cuda-11_7
- linux-rocm-5_2
- linux-cpu
- macos-default
- windows-cpu
# - windows-cuda-11_6
# - windows-cuda-11_7
include:
# - pytorch: linux-cuda-11_6
# os: ubuntu-22.04
# extra-index-url: 'https://download.pytorch.org/whl/cu116'
# github-env: $GITHUB_ENV
- pytorch: linux-cuda-11_7
os: ubuntu-22.04
github-env: $GITHUB_ENV
- pytorch: linux-rocm-5_2
os: ubuntu-22.04
extra-index-url: 'https://download.pytorch.org/whl/rocm5.2'
github-env: $GITHUB_ENV
- pytorch: linux-cpu
os: ubuntu-22.04
extra-index-url: 'https://download.pytorch.org/whl/cpu'
github-env: $GITHUB_ENV
- pytorch: macos-default
os: macOS-12
github-env: $GITHUB_ENV
- pytorch: windows-cpu
os: windows-2022
github-env: $env:GITHUB_ENV
# - pytorch: windows-cuda-11_6
# os: windows-2022
# extra-index-url: 'https://download.pytorch.org/whl/cu116'
# github-env: $env:GITHUB_ENV
# - pytorch: windows-cuda-11_7
# os: windows-2022
# extra-index-url: 'https://download.pytorch.org/whl/cu117'
# github-env: $env:GITHUB_ENV
name: ${{ matrix.pytorch }} on ${{ matrix.python-version }}
runs-on: ${{ matrix.os }}
env:
PIP_USE_PEP517: '1'
steps:
- name: Checkout sources
id: checkout-sources
uses: actions/checkout@v3
- name: set test prompt to main branch validation
run: echo "TEST_PROMPTS=tests/validate_pr_prompt.txt" >> ${{ matrix.github-env }}
- name: setup python
uses: actions/setup-python@v4
with:
python-version: ${{ matrix.python-version }}
cache: pip
cache-dependency-path: pyproject.toml
- name: install invokeai
env:
PIP_EXTRA_INDEX_URL: ${{ matrix.extra-index-url }}
run: >
pip3 install
--editable=".[test]"
- name: run pytest
id: run-pytest
run: pytest
- name: run invokeai-configure
id: run-preload-models
env:
HUGGING_FACE_HUB_TOKEN: ${{ secrets.HUGGINGFACE_TOKEN }}
run: >
invokeai-configure
--yes
--default_only
--full-precision
# can't use fp16 weights without a GPU
- name: run invokeai
id: run-invokeai
env:
# Set offline mode to make sure configure preloaded successfully.
HF_HUB_OFFLINE: 1
HF_DATASETS_OFFLINE: 1
TRANSFORMERS_OFFLINE: 1
INVOKEAI_OUTDIR: ${{ github.workspace }}/results
run: >
invokeai
--no-patchmatch
--no-nsfw_checker
--precision=float32
--always_use_cpu
--use_memory_db
--outdir ${{ env.INVOKEAI_OUTDIR }}/${{ matrix.python-version }}/${{ matrix.pytorch }}
--from_file ${{ env.TEST_PROMPTS }}
- name: Archive results
id: archive-results
env:
INVOKEAI_OUTDIR: ${{ github.workspace }}/results
uses: actions/upload-artifact@v3
with:
name: results
path: ${{ env.INVOKEAI_OUTDIR }}

33
.gitignore vendored
View File

@ -1,16 +1,10 @@
# ignore default image save location and model symbolic link
.idea/
embeddings/
outputs/
models/ldm/stable-diffusion-v1/model.ckpt
**/restoration/codeformer/weights
ldm/invoke/restoration/codeformer/weights
# ignore user models config
configs/models.user.yaml
config/models.user.yml
invokeai.init
.version
.last_model
# ignore the Anaconda/Miniconda installer used while building Docker image
anaconda.sh
@ -65,20 +59,16 @@ pip-delete-this-directory.txt
htmlcov/
.tox/
.nox/
.coveragerc
.coverage
.coverage.*
.cache
nosetests.xml
coverage.xml
cov.xml
*.cover
*.py,cover
.hypothesis/
.pytest_cache/
.pytest.ini
cover/
junit/
# Translations
*.mo
@ -201,10 +191,8 @@ checkpoints
# If it's a Mac
.DS_Store
invokeai/frontend/web/dist/*
# Let the frontend manage its own gitignore
!invokeai/frontend/web/*
!frontend/*
# Scratch folder
.scratch/
@ -212,24 +200,11 @@ invokeai/frontend/web/dist/*
gfpgan/
models/ldm/stable-diffusion-v1/*.sha256
# GFPGAN model files
gfpgan/
# config file (will be created by installer)
configs/models.yaml
# ignore initfile
.invokeai
# ignore environment.yml and requirements.txt
# these are links to the real files in environments-and-requirements
environment.yml
requirements.txt
# source installer files
installer/*zip
installer/install.bat
installer/install.sh
installer/update.bat
installer/update.sh
# weights (will be created by installer)
models/ldm/stable-diffusion-v1/*.ckpt

View File

@ -1,128 +0,0 @@
# Contributor Covenant Code of Conduct
## Our Pledge
We as members, contributors, and leaders pledge to make participation in our
community a harassment-free experience for everyone, regardless of age, body
size, visible or invisible disability, ethnicity, sex characteristics, gender
identity and expression, level of experience, education, socio-economic status,
nationality, personal appearance, race, religion, or sexual identity
and orientation.
We pledge to act and interact in ways that contribute to an open, welcoming,
diverse, inclusive, and healthy community.
## Our Standards
Examples of behavior that contributes to a positive environment for our
community include:
* Demonstrating empathy and kindness toward other people
* Being respectful of differing opinions, viewpoints, and experiences
* Giving and gracefully accepting constructive feedback
* Accepting responsibility and apologizing to those affected by our mistakes,
and learning from the experience
* Focusing on what is best not just for us as individuals, but for the
overall community
Examples of unacceptable behavior include:
* The use of sexualized language or imagery, and sexual attention or
advances of any kind
* Trolling, insulting or derogatory comments, and personal or political attacks
* Public or private harassment
* Publishing others' private information, such as a physical or email
address, without their explicit permission
* Other conduct which could reasonably be considered inappropriate in a
professional setting
## Enforcement Responsibilities
Community leaders are responsible for clarifying and enforcing our standards of
acceptable behavior and will take appropriate and fair corrective action in
response to any behavior that they deem inappropriate, threatening, offensive,
or harmful.
Community leaders have the right and responsibility to remove, edit, or reject
comments, commits, code, wiki edits, issues, and other contributions that are
not aligned to this Code of Conduct, and will communicate reasons for moderation
decisions when appropriate.
## Scope
This Code of Conduct applies within all community spaces, and also applies when
an individual is officially representing the community in public spaces.
Examples of representing our community include using an official e-mail address,
posting via an official social media account, or acting as an appointed
representative at an online or offline event.
## Enforcement
Instances of abusive, harassing, or otherwise unacceptable behavior
may be reported to the community leaders responsible for enforcement
at https://github.com/invoke-ai/InvokeAI/issues. All complaints will
be reviewed and investigated promptly and fairly.
All community leaders are obligated to respect the privacy and security of the
reporter of any incident.
## Enforcement Guidelines
Community leaders will follow these Community Impact Guidelines in determining
the consequences for any action they deem in violation of this Code of Conduct:
### 1. Correction
**Community Impact**: Use of inappropriate language or other behavior deemed
unprofessional or unwelcome in the community.
**Consequence**: A private, written warning from community leaders, providing
clarity around the nature of the violation and an explanation of why the
behavior was inappropriate. A public apology may be requested.
### 2. Warning
**Community Impact**: A violation through a single incident or series
of actions.
**Consequence**: A warning with consequences for continued behavior. No
interaction with the people involved, including unsolicited interaction with
those enforcing the Code of Conduct, for a specified period of time. This
includes avoiding interactions in community spaces as well as external channels
like social media. Violating these terms may lead to a temporary or
permanent ban.
### 3. Temporary Ban
**Community Impact**: A serious violation of community standards, including
sustained inappropriate behavior.
**Consequence**: A temporary ban from any sort of interaction or public
communication with the community for a specified period of time. No public or
private interaction with the people involved, including unsolicited interaction
with those enforcing the Code of Conduct, is allowed during this period.
Violating these terms may lead to a permanent ban.
### 4. Permanent Ban
**Community Impact**: Demonstrating a pattern of violation of community
standards, including sustained inappropriate behavior, harassment of an
individual, or aggression toward or disparagement of classes of individuals.
**Consequence**: A permanent ban from any sort of public interaction within
the community.
## Attribution
This Code of Conduct is adapted from the [Contributor Covenant][homepage],
version 2.0, available at
https://www.contributor-covenant.org/version/2/0/code_of_conduct.html.
Community Impact Guidelines were inspired by [Mozilla's code of conduct
enforcement ladder](https://github.com/mozilla/diversity).
[homepage]: https://www.contributor-covenant.org
For answers to common questions about this code of conduct, see the FAQ at
https://www.contributor-covenant.org/faq. Translations are available at
https://www.contributor-covenant.org/translations.

View File

@ -1,84 +0,0 @@
<img src="docs/assets/invoke_ai_banner.png" align="center">
Invoke-AI is a community of software developers, researchers, and user
interface experts who have come together on a voluntary basis to build
software tools which support cutting edge AI text-to-image
applications. This community is open to anyone who wishes to
contribute to the effort and has the skill and time to do so.
# Our Values
The InvokeAI team is a diverse community which includes individuals
from various parts of the world and many walks of life. Despite our
differences, we share a number of core values which we ask prospective
contributors to understand and respect. We believe:
1. That Open Source Software is a positive force in the world. We
create software that can be used, reused, and redistributed, without
restrictions, under a straightforward Open Source license (MIT). We
believe that Open Source benefits society as a whole by increasing the
availability of high quality software to all.
2. That those who create software should receive proper attribution
for their creative work. While we support the exchange and reuse of
Open Source Software, we feel strongly that the original authors of a
piece of code should receive credit for their contribution, and we
endeavor to do so whenever possible.
3. That there is moral ambiguity surrounding AI-assisted art. We are
aware of the moral and ethical issues surrounding the release of the
Stable Diffusion model and similar products. We are aware that, due to
the composition of their training sets, current AI-generated image
models are biased against certain ethnic groups, cultural concepts of
beauty, ethnic stereotypes, and gender roles.
1. We recognize the potential for harm to these groups that these biases
represent and trust that future AI models will take steps towards
reducing or eliminating the biases noted above, respect and give due
credit to the artists whose work is sourced, and call on developers
and users to favor these models over the older ones as they become
available.
4. We are deeply committed to ensuring that this technology benefits
everyone, including artists. We see AI art not as a replacement for
the artist, but rather as a tool to empower them. With that
in mind, we are constantly debating how to build systems that put
artists needs first: tools which can be readily integrated into an
artists existing workflows and practices, enhancing their work and
helping them to push it further. Every decision we take as a team,
which includes several artists, aims to build towards that goal.
5. That artificial intelligence can be a force for good in the world,
but must be used responsibly. Artificial intelligence technologies
have the potential to improve society, in everything from cancer care,
to customer service, to creative writing.
1. While we do not believe that software should arbitrarily limit what
users can do with it, we recognize that when used irresponsibly, AI
has the potential to do much harm. Our Discord server is actively
moderated in order to minimize the potential of harm from
user-contributed images. In addition, we ask users of our software to
refrain from using it in any way that would cause mental, emotional or
physical harm to individuals and vulnerable populations including (but
not limited to) women; minors; ethnic minorities; religious groups;
members of LGBTQIA communities; and people with disabilities or
impairments.
2. Note that some of the image generation AI models which the Invoke-AI
toolkit supports carry licensing agreements which impose restrictions
on how the model is used. We ask that our users read and agree to
these terms if they wish to make use of these models. These agreements
are distinct from the MIT license which applies to the InvokeAI
software and source code.
6. That mutual respect is key to a healthy software development
community. Members of the InvokeAI community are expected to treat
each other with respect, beneficence, and empathy. Each of us has a
different background and a unique set of skills. We strive to help
each other grow and gain new skills, and we apportion expectations in
a way that balances the members' time, skillset, and interest
area. Disputes are resolved by open and honest communication.
## Signature
This document has been collectively crafted and approved by the current InvokeAI team members, as of 28 Nov 2022: **lstein** (Lincoln Stein), **blessedcoolant**, **hipsterusername** (Kent Keirsey), **Kyle0654** (Kyle Schouviller), **damian0815**, **mauwii** (Matthias Wild), **Netsvetaev** (Artur Netsvetaev), **psychedelicious**, **tildebyte**, **keturn**, and **ebr** (Eugene Brodsky). Although individuals within the group may hold differing views on particular details and/or their implications, we are all in agreement about its fundamental statements, as well as their significance and importance to this project moving forward.

364
README.md
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@ -1,19 +1,23 @@
<div align="center">
![project logo](https://github.com/invoke-ai/InvokeAI/raw/main/docs/assets/invoke_ai_banner.png)
# InvokeAI: A Stable Diffusion Toolkit
_Formerly known as lstein/stable-diffusion_
![project logo](docs/assets/logo.png)
[![discord badge]][discord link]
[![latest release badge]][latest release link] [![github stars badge]][github stars link] [![github forks badge]][github forks link]
[![CI checks on main badge]][CI checks on main link] [![latest commit to main badge]][latest commit to main link]
[![CI checks on main badge]][CI checks on main link] [![CI checks on dev badge]][CI checks on dev link] [![latest commit to dev badge]][latest commit to dev link]
[![github open issues badge]][github open issues link] [![github open prs badge]][github open prs link] [![translation status badge]][translation status link]
[![github open issues badge]][github open issues link] [![github open prs badge]][github open prs link]
[CI checks on dev badge]: https://flat.badgen.net/github/checks/invoke-ai/InvokeAI/development?label=CI%20status%20on%20dev&cache=900&icon=github
[CI checks on dev link]: https://github.com/invoke-ai/InvokeAI/actions?query=branch%3Adevelopment
[CI checks on main badge]: https://flat.badgen.net/github/checks/invoke-ai/InvokeAI/main?label=CI%20status%20on%20main&cache=900&icon=github
[CI checks on main link]:https://github.com/invoke-ai/InvokeAI/actions?query=branch%3Amain
[CI checks on main link]: https://github.com/invoke-ai/InvokeAI/actions/workflows/test-invoke-conda.yml
[discord badge]: https://flat.badgen.net/discord/members/ZmtBAhwWhy?icon=discord
[discord link]: https://discord.gg/ZmtBAhwWhy
[github forks badge]: https://flat.badgen.net/github/forks/invoke-ai/InvokeAI?icon=github
@ -24,276 +28,174 @@
[github open prs link]: https://github.com/invoke-ai/InvokeAI/pulls?q=is%3Apr+is%3Aopen
[github stars badge]: https://flat.badgen.net/github/stars/invoke-ai/InvokeAI?icon=github
[github stars link]: https://github.com/invoke-ai/InvokeAI/stargazers
[latest commit to main badge]: https://flat.badgen.net/github/last-commit/invoke-ai/InvokeAI/main?icon=github&color=yellow&label=last%20dev%20commit&cache=900
[latest commit to main link]: https://github.com/invoke-ai/InvokeAI/commits/main
[latest commit to dev badge]: https://flat.badgen.net/github/last-commit/invoke-ai/InvokeAI/development?icon=github&color=yellow&label=last%20dev%20commit&cache=900
[latest commit to dev link]: https://github.com/invoke-ai/InvokeAI/commits/development
[latest release badge]: https://flat.badgen.net/github/release/invoke-ai/InvokeAI/development?icon=github
[latest release link]: https://github.com/invoke-ai/InvokeAI/releases
[translation status badge]: https://hosted.weblate.org/widgets/invokeai/-/svg-badge.svg
[translation status link]: https://hosted.weblate.org/engage/invokeai/
</div>
_**Note: The UI is not fully functional on `main`. If you need a stable UI based on `main`, use the `pre-nodes` tag while we [migrate to a new backend](https://github.com/invoke-ai/InvokeAI/discussions/3246).**_
This is a fork of
[CompVis/stable-diffusion](https://github.com/CompVis/stable-diffusion),
the open source text-to-image generator. It provides a streamlined
process with various new features and options to aid the image
generation process. It runs on Windows, Mac and Linux machines, with
GPU cards with as little as 4 GB of RAM. It provides both a polished
Web interface (see below), and an easy-to-use command-line interface.
InvokeAI is a leading creative engine built to empower professionals and enthusiasts alike. Generate and create stunning visual media using the latest AI-driven technologies. InvokeAI offers an industry leading Web Interface, interactive Command Line Interface, and also serves as the foundation for multiple commercial products.
**Quick links**: [<a href="https://discord.gg/ZmtBAhwWhy">Discord Server</a>] [<a href="https://invoke-ai.github.io/InvokeAI/">Documentation and Tutorials</a>] [<a href="https://github.com/invoke-ai/InvokeAI/">Code and Downloads</a>] [<a href="https://github.com/invoke-ai/InvokeAI/issues">Bug Reports</a>] [<a href="https://github.com/invoke-ai/InvokeAI/discussions">Discussion, Ideas & Q&A</a>]
**Quick links**: [[How to Install](https://invoke-ai.github.io/InvokeAI/#installation)] [<a href="https://discord.gg/ZmtBAhwWhy">Discord Server</a>] [<a href="https://invoke-ai.github.io/InvokeAI/">Documentation and Tutorials</a>] [<a href="https://github.com/invoke-ai/InvokeAI/">Code and Downloads</a>] [<a href="https://github.com/invoke-ai/InvokeAI/issues">Bug Reports</a>] [<a href="https://github.com/invoke-ai/InvokeAI/discussions">Discussion, Ideas & Q&A</a>]
<div align="center"><img src="docs/assets/invoke-web-server-1.png" width=640></div>
_Note: InvokeAI is rapidly evolving. Please use the
_Note: This fork is rapidly evolving. Please use the
[Issues](https://github.com/invoke-ai/InvokeAI/issues) tab to report bugs and make feature
requests. Be sure to use the provided templates. They will help us diagnose issues faster._
## FOR DEVELOPERS - MIGRATING TO THE 3.0.0 MODELS FORMAT
The models directory and models.yaml have changed. To migrate to the
new layout, please follow this recipe:
1. Run `python scripts/migrate_models_to_3.0.py <path_to_root_directory>
2. This will create a new models directory named `models-3.0` and a
new config directory named `models.yaml-3.0`, both in the current
working directory. If you prefer to name them something else, pass
the `--dest-directory` and/or `--dest-yaml` arguments.
3. Check that the new models directory and yaml file look ok.
4. Replace the existing directory and file, keeping backup copies just in
case.
<div align="center">
![canvas preview](https://github.com/invoke-ai/InvokeAI/raw/main/docs/assets/canvas_preview.png)
</div>
requests. Be sure to use the provided templates. They will help aid diagnose issues faster._
## Table of Contents
1. [Quick Start](#getting-started-with-invokeai)
2. [Installation](#detailed-installation-instructions)
3. [Hardware Requirements](#hardware-requirements)
4. [Features](#features)
5. [Latest Changes](#latest-changes)
6. [Troubleshooting](#troubleshooting)
7. [Contributing](#contributing)
8. [Contributors](#contributors)
9. [Support](#support)
10. [Further Reading](#further-reading)
1. [Installation](#installation)
2. [Hardware Requirements](#hardware-requirements)
3. [Features](#features)
4. [Latest Changes](#latest-changes)
5. [Troubleshooting](#troubleshooting)
6. [Contributing](#contributing)
7. [Contributors](#contributors)
8. [Support](#support)
9. [Further Reading](#further-reading)
## Getting Started with InvokeAI
### Installation
For full installation and upgrade instructions, please see:
[InvokeAI Installation Overview](https://invoke-ai.github.io/InvokeAI/installation/)
This fork is supported across multiple platforms. You can find individual installation instructions
below.
### Automatic Installer (suggested for 1st time users)
- #### [Linux](https://invoke-ai.github.io/InvokeAI/installation/INSTALL_LINUX/)
1. Go to the bottom of the [Latest Release Page](https://github.com/invoke-ai/InvokeAI/releases/latest)
- #### [Windows](https://invoke-ai.github.io/InvokeAI/installation/INSTALL_WINDOWS/)
2. Download the .zip file for your OS (Windows/macOS/Linux).
- #### [Macintosh](https://invoke-ai.github.io/InvokeAI/installation/INSTALL_MAC/)
3. Unzip the file.
### Hardware Requirements
4. If you are on Windows, double-click on the `install.bat` script. On
macOS, open a Terminal window, drag the file `install.sh` from Finder
into the Terminal, and press return. On Linux, run `install.sh`.
#### System
5. You'll be asked to confirm the location of the folder in which
to install InvokeAI and its image generation model files. Pick a
location with at least 15 GB of free memory. More if you plan on
installing lots of models.
6. Wait while the installer does its thing. After installing the software,
the installer will launch a script that lets you configure InvokeAI and
select a set of starting image generation models.
7. Find the folder that InvokeAI was installed into (it is not the
same as the unpacked zip file directory!) The default location of this
folder (if you didn't change it in step 5) is `~/invokeai` on
Linux/Mac systems, and `C:\Users\YourName\invokeai` on Windows. This directory will contain launcher scripts named `invoke.sh` and `invoke.bat`.
8. On Windows systems, double-click on the `invoke.bat` file. On
macOS, open a Terminal window, drag `invoke.sh` from the folder into
the Terminal, and press return. On Linux, run `invoke.sh`
9. Press 2 to open the "browser-based UI", press enter/return, wait a
minute or two for Stable Diffusion to start up, then open your browser
and go to http://localhost:9090.
10. Type `banana sushi` in the box on the top left and click `Invoke`
### Command-Line Installation (for users familiar with Terminals)
You must have Python 3.9 or 3.10 installed on your machine. Earlier or later versions are
not supported.
1. Open a command-line window on your machine. The PowerShell is recommended for Windows.
2. Create a directory to install InvokeAI into. You'll need at least 15 GB of free space:
```terminal
mkdir invokeai
````
3. Create a virtual environment named `.venv` inside this directory and activate it:
```terminal
cd invokeai
python -m venv .venv --prompt InvokeAI
```
4. Activate the virtual environment (do it every time you run InvokeAI)
_For Linux/Mac users:_
```sh
source .venv/bin/activate
```
_For Windows users:_
```ps
.venv\Scripts\activate
```
5. Install the InvokeAI module and its dependencies. Choose the command suited for your platform & GPU.
_For Windows/Linux with an NVIDIA GPU:_
```terminal
pip install "InvokeAI[xformers]" --use-pep517 --extra-index-url https://download.pytorch.org/whl/cu117
```
_For Linux with an AMD GPU:_
```sh
pip install InvokeAI --use-pep517 --extra-index-url https://download.pytorch.org/whl/rocm5.4.2
```
_For non-GPU systems:_
```terminal
pip install InvokeAI --use-pep517 --extra-index-url https://download.pytorch.org/whl/cpu
```
_For Macintoshes, either Intel or M1/M2:_
```sh
pip install InvokeAI --use-pep517
```
6. Configure InvokeAI and install a starting set of image generation models (you only need to do this once):
```terminal
invokeai-configure
```
7. Launch the web server (do it every time you run InvokeAI):
```terminal
invokeai --web
```
8. Point your browser to http://localhost:9090 to bring up the web interface.
9. Type `banana sushi` in the box on the top left and click `Invoke`.
Be sure to activate the virtual environment each time before re-launching InvokeAI,
using `source .venv/bin/activate` or `.venv\Scripts\activate`.
### Detailed Installation Instructions
This fork is supported across Linux, Windows and Macintosh. Linux
users can use either an Nvidia-based card (with CUDA support) or an
AMD card (using the ROCm driver). For full installation and upgrade
instructions, please see:
[InvokeAI Installation Overview](https://invoke-ai.github.io/InvokeAI/installation/INSTALL_SOURCE/)
## Hardware Requirements
InvokeAI is supported across Linux, Windows and macOS. Linux
users can use either an Nvidia-based card (with CUDA support) or an
AMD card (using the ROCm driver).
### System
You will need one of the following:
You wil need one of the following:
- An NVIDIA-based graphics card with 4 GB or more VRAM memory.
- An Apple computer with an M1 chip.
- An AMD-based graphics card with 4GB or more VRAM memory. (Linux only)
We do not recommend the GTX 1650 or 1660 series video cards. They are
unable to run in half-precision mode and do not have sufficient VRAM
to render 512x512 images.
### Memory
#### Memory
- At least 12 GB Main Memory RAM.
### Disk
#### Disk
- At least 12 GB of free disk space for the machine learning model, Python, and all its dependencies.
## Features
**Note**
Feature documentation can be reviewed by navigating to [the InvokeAI Documentation page](https://invoke-ai.github.io/InvokeAI/features/)
If you have a Nvidia 10xx series card (e.g. the 1080ti), please
run the dream script in full-precision mode as shown below.
### *Web Server & UI*
Similarly, specify full-precision mode on Apple M1 hardware.
InvokeAI offers a locally hosted Web Server & React Frontend, with an industry leading user experience. The Web-based UI allows for simple and intuitive workflows, and is responsive for use on mobile devices and tablets accessing the web server.
Precision is auto configured based on the device. If however you encounter
errors like 'expected type Float but found Half' or 'not implemented for Half'
you can try starting `invoke.py` with the `--precision=float32` flag:
### *Unified Canvas*
```bash
(invokeai) ~/InvokeAI$ python scripts/invoke.py --precision=float32
```
The Unified Canvas is a fully integrated canvas implementation with support for all core generation capabilities, in/outpainting, brush tools, and more. This creative tool unlocks the capability for artists to create with AI as a creative collaborator, and can be used to augment AI-generated imagery, sketches, photography, renders, and more.
### Features
### *Advanced Prompt Syntax*
#### Major Features
InvokeAI's advanced prompt syntax allows for token weighting, cross-attention control, and prompt blending, allowing for fine-tuned tweaking of your invocations and exploration of the latent space.
- [Web Server](https://invoke-ai.github.io/InvokeAI/features/WEB/)
- [Interactive Command Line Interface](https://invoke-ai.github.io/InvokeAI/features/CLI/)
- [Image To Image](https://invoke-ai.github.io/InvokeAI/features/IMG2IMG/)
- [Inpainting Support](https://invoke-ai.github.io/InvokeAI/features/INPAINTING/)
- [Outpainting Support](https://invoke-ai.github.io/InvokeAI/features/OUTPAINTING/)
- [Upscaling, face-restoration and outpainting](https://invoke-ai.github.io/InvokeAI/features/POSTPROCESS/)
- [Reading Prompts From File](https://invoke-ai.github.io/InvokeAI/features/PROMPTS/#reading-prompts-from-a-file)
- [Prompt Blending](https://invoke-ai.github.io/InvokeAI/features/PROMPTS/#prompt-blending)
- [Thresholding and Perlin Noise Initialization Options](https://invoke-ai.github.io/InvokeAI/features/OTHER/#thresholding-and-perlin-noise-initialization-options)
- [Negative/Unconditioned Prompts](https://invoke-ai.github.io/InvokeAI/features/PROMPTS/#negative-and-unconditioned-prompts)
- [Variations](https://invoke-ai.github.io/InvokeAI/features/VARIATIONS/)
- [Personalizing Text-to-Image Generation](https://invoke-ai.github.io/InvokeAI/features/TEXTUAL_INVERSION/)
- [Simplified API for text to image generation](https://invoke-ai.github.io/InvokeAI/features/OTHER/#simplified-api)
### *Command Line Interface*
#### Other Features
For users utilizing a terminal-based environment, or who want to take advantage of CLI features, InvokeAI offers an extensive and actively supported command-line interface that provides the full suite of generation functionality available in the tool.
### Other features
- *Support for both ckpt and diffusers models*
- *SD 2.0, 2.1 support*
- *Noise Control & Tresholding*
- *Popular Sampler Support*
- *Upscaling & Face Restoration Tools*
- *Embedding Manager & Support*
- *Model Manager & Support*
### Coming Soon
- *Node-Based Architecture & UI*
- And more...
- [Google Colab](https://invoke-ai.github.io/InvokeAI/features/OTHER/#google-colab)
- [Seamless Tiling](https://invoke-ai.github.io/InvokeAI/features/OTHER/#seamless-tiling)
- [Shortcut: Reusing Seeds](https://invoke-ai.github.io/InvokeAI/features/OTHER/#shortcuts-reusing-seeds)
- [Preload Models](https://invoke-ai.github.io/InvokeAI/features/OTHER/#preload-models)
### Latest Changes
For our latest changes, view our [Release
Notes](https://github.com/invoke-ai/InvokeAI/releases) and the
[CHANGELOG](docs/CHANGELOG.md).
### v2.1.0 major changes <small>(2 November 2022)</small>
## Troubleshooting
- [Inpainting](https://invoke-ai.github.io/InvokeAI/features/INPAINTING/) support in the WebGUI
- Greatly improved navigation and user experience in the [WebGUI](https://invoke-ai.github.io/InvokeAI/features/WEB/)
- The prompt syntax has been enhanced with [prompt weighting, cross-attention and prompt merging](https://invoke-ai.github.io/InvokeAI/features/PROMPTS/).
- You can now load [multiple models and switch among them quickly](https://docs.google.com/presentation/d/1WywGA1rny7bpFh7CLSdTr4nNpVKdlUeT0Bj0jCsILyU/edit?usp=sharing) without leaving the CLI.
- The installation process (via `scripts/preload_models.py`) now lets you select among several popular [Stable Diffusion models](https://invoke-ai.github.io/InvokeAI/installation/INSTALLING_MODELS/) and downloads and installs them on your behalf. Among other models, this script will install the current Stable Diffusion 1.5 model as well as a StabilityAI variable autoencoder (VAE) which improves face generation.
- Tired of struggling with photoeditors to get the masked region of for inpainting just right? Let the AI make the mask for you using [text masking](https://docs.google.com/presentation/d/1pWoY510hCVjz0M6X9CBbTznZgW2W5BYNKrmZm7B45q8/edit#slide=id.p). This feature allows you to specify the part of the image to paint over using just English-language phrases.
- Tired of seeing the head of your subjects cropped off? Uncrop them in the CLI with the [outcrop feature](https://invoke-ai.github.io/InvokeAI/features/OUTPAINTING/#outcrop).
- Tired of seeing your subject's bodies duplicated or mangled when generating larger-dimension images? Check out the `--hires` option in the CLI, or select the corresponding toggle in the WebGUI.
- We now support textual inversion and fine-tune .bin styles and subjects from the Hugging Face archive of [SD Concepts](https://huggingface.co/sd-concepts-library). Load the .bin file using the `--embedding_path` option. (The next version will support merging and loading of multiple simultaneous models).
<a href="https://invoke-ai.github.io/InvokeAI/CHANGELOG/>Complete Changelog</a>
- v2.0.1 (13 October 2022)
- fix noisy images at high step count when using k* samplers
- dream.py script now calls invoke.py module directly rather than
via a new python process (which could break the environment)
- v2.0.0 (9 October 2022)
- `dream.py` script renamed `invoke.py`. A `dream.py` script wrapper remains
for backward compatibility.
- Completely new WebGUI - launch with `python3 scripts/invoke.py --web`
- Support for <a href="https://invoke-ai.github.io/InvokeAI/features/INPAINTING/">inpainting</a> and <a href="https://invoke-ai.github.io/InvokeAI/features/OUTPAINTING/">outpainting</a>
- img2img runs on all k* samplers
- Support for <a href="https://invoke-ai.github.io/InvokeAI/features/PROMPTS/#negative-and-unconditioned-prompts">negative prompts</a>
- Support for CodeFormer face reconstruction
- Support for Textual Inversion on Macintoshes
- Support in both WebGUI and CLI for <a href="https://invoke-ai.github.io/InvokeAI/features/POSTPROCESS/">post-processing of previously-generated images</a>
using facial reconstruction, ESRGAN upscaling, outcropping (similar to DALL-E infinite canvas),
and "embiggen" upscaling. See the `!fix` command.
- New `--hires` option on `invoke>` line allows <a href="https://invoke-ai.github.io/InvokeAI/features/CLI/#txt2img">larger images to be created without duplicating elements</a>, at the cost of some performance.
- New `--perlin` and `--threshold` options allow you to add and control variation
during image generation (see <a href="https://github.com/invoke-ai/InvokeAI/blob/main/docs/features/OTHER.md#thresholding-and-perlin-noise-initialization-options">Thresholding and Perlin Noise Initialization</a>
- Extensive metadata now written into PNG files, allowing reliable regeneration of images
and tweaking of previous settings.
- Command-line completion in `invoke.py` now works on Windows, Linux and Mac platforms.
- Improved <a href="https://invoke-ai.github.io/InvokeAI/features/CLI/">command-line completion behavior</a>.
New commands added:
- List command-line history with `!history`
- Search command-line history with `!search`
- Clear history with `!clear`
- Deprecated `--full_precision` / `-F`. Simply omit it and `invoke.py` will auto
configure. To switch away from auto use the new flag like `--precision=float32`.
For older changelogs, please visit the **[CHANGELOG](https://invoke-ai.github.io/InvokeAI/CHANGELOG#v114-11-september-2022)**.
### Troubleshooting
Please check out our **[Q&A](https://invoke-ai.github.io/InvokeAI/help/TROUBLESHOOT/#faq)** to get solutions for common installation
problems and other issues.
## Contributing
# Contributing
Anyone who wishes to contribute to this project, whether documentation, features, bug fixes, code
cleanup, testing, or code reviews, is very much encouraged to do so.
To join, just raise your hand on the InvokeAI Discord server (#dev-chat) or the GitHub discussion board.
If you'd like to help with translation, please see our [translation guide](docs/other/TRANSLATION.md).
If you are unfamiliar with how
cleanup, testing, or code reviews, is very much encouraged to do so. If you are unfamiliar with how
to contribute to GitHub projects, here is a
[Getting Started Guide](https://opensource.com/article/19/7/create-pull-request-github). A full set of contribution guidelines, along with templates, are in progress. You can **make your pull request against the "main" branch**.
[Getting Started Guide](https://opensource.com/article/19/7/create-pull-request-github).
We hope you enjoy using our software as much as we enjoy creating it,
and we hope that some of those of you who are reading this will elect
to become part of our community.
Welcome to InvokeAI!
A full set of contribution guidelines, along with templates, are in progress, but for now the most
important thing is to **make your pull request against the "development" branch**, and not against
"main". This will help keep public breakage to a minimum and will allow you to propose more radical
changes.
### Contributors
@ -301,11 +203,15 @@ This fork is a combined effort of various people from across the world.
[Check out the list of all these amazing people](https://invoke-ai.github.io/InvokeAI/other/CONTRIBUTORS/). We thank them for
their time, hard work and effort.
Thanks to [Weblate](https://weblate.org/) for generously providing translation services to this project.
### Support
For support, please use this repository's GitHub Issues tracking service, or join the Discord.
For support, please use this repository's GitHub Issues tracking service. Feel free to send me an
email if you use and like the script.
Original portions of the software are Copyright (c) 2023 by respective contributors.
Original portions of the software are Copyright (c) 2020
[Lincoln D. Stein](https://github.com/lstein)
### Further Reading
Please see the original README for more information on this software and underlying algorithm,
located in the file [README-CompViz.md](https://invoke-ai.github.io/InvokeAI/other/README-CompViz/).

View File

@ -21,7 +21,7 @@ This model card focuses on the model associated with the Stable Diffusion model,
# Uses
## Direct Use
## Direct Use
The model is intended for research purposes only. Possible research areas and
tasks include
@ -68,11 +68,11 @@ Using the model to generate content that is cruel to individuals is a misuse of
considerations.
### Bias
While the capabilities of image generation models are impressive, they can also reinforce or exacerbate social biases.
Stable Diffusion v1 was trained on subsets of [LAION-2B(en)](https://laion.ai/blog/laion-5b/),
which consists of images that are primarily limited to English descriptions.
Texts and images from communities and cultures that use other languages are likely to be insufficiently accounted for.
This affects the overall output of the model, as white and western cultures are often set as the default. Further, the
While the capabilities of image generation models are impressive, they can also reinforce or exacerbate social biases.
Stable Diffusion v1 was trained on subsets of [LAION-2B(en)](https://laion.ai/blog/laion-5b/),
which consists of images that are primarily limited to English descriptions.
Texts and images from communities and cultures that use other languages are likely to be insufficiently accounted for.
This affects the overall output of the model, as white and western cultures are often set as the default. Further, the
ability of the model to generate content with non-English prompts is significantly worse than with English-language prompts.
@ -84,7 +84,7 @@ The model developers used the following dataset for training the model:
- LAION-2B (en) and subsets thereof (see next section)
**Training Procedure**
Stable Diffusion v1 is a latent diffusion model which combines an autoencoder with a diffusion model that is trained in the latent space of the autoencoder. During training,
Stable Diffusion v1 is a latent diffusion model which combines an autoencoder with a diffusion model that is trained in the latent space of the autoencoder. During training,
- Images are encoded through an encoder, which turns images into latent representations. The autoencoder uses a relative downsampling factor of 8 and maps images of shape H x W x 3 to latents of shape H/f x W/f x 4
- Text prompts are encoded through a ViT-L/14 text-encoder.
@ -108,12 +108,12 @@ filtered to images with an original size `>= 512x512`, estimated aesthetics scor
- **Batch:** 32 x 8 x 2 x 4 = 2048
- **Learning rate:** warmup to 0.0001 for 10,000 steps and then kept constant
## Evaluation Results
## Evaluation Results
Evaluations with different classifier-free guidance scales (1.5, 2.0, 3.0, 4.0,
5.0, 6.0, 7.0, 8.0) and 50 PLMS sampling
steps show the relative improvements of the checkpoints:
![pareto](assets/v1-variants-scores.jpg)
![pareto](assets/v1-variants-scores.jpg)
Evaluated using 50 PLMS steps and 10000 random prompts from the COCO2017 validation set, evaluated at 512x512 resolution. Not optimized for FID scores.
## Environmental Impact

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@ -0,0 +1,55 @@
import argparse
import os
from ldm.invoke.args import PRECISION_CHOICES
def create_cmd_parser():
parser = argparse.ArgumentParser(description="InvokeAI web UI")
parser.add_argument(
"--host",
type=str,
help="The host to serve on",
default="localhost",
)
parser.add_argument("--port", type=int, help="The port to serve on", default=9090)
parser.add_argument(
"--cors",
nargs="*",
type=str,
help="Additional allowed origins, comma-separated",
)
parser.add_argument(
"--embedding_path",
type=str,
help="Path to a pre-trained embedding manager checkpoint - can only be set on command line",
)
# TODO: Can't get flask to serve images from any dir (saving to the dir does work when specified)
# parser.add_argument(
# "--output_dir",
# default="outputs/",
# type=str,
# help="Directory for output images",
# )
parser.add_argument(
"-v",
"--verbose",
action="store_true",
help="Enables verbose logging",
)
parser.add_argument(
"--precision",
dest="precision",
type=str,
choices=PRECISION_CHOICES,
metavar="PRECISION",
help=f'Set model precision. Defaults to auto selected based on device. Options: {", ".join(PRECISION_CHOICES)}',
default="auto",
)
parser.add_argument(
'--free_gpu_mem',
dest='free_gpu_mem',
action='store_true',
help='Force free gpu memory before final decoding',
)
return parser

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@ -0,0 +1,69 @@
from backend.modules.parse_seed_weights import parse_seed_weights
import argparse
SAMPLER_CHOICES = [
"ddim",
"k_dpm_2_a",
"k_dpm_2",
"k_euler_a",
"k_euler",
"k_heun",
"k_lms",
"plms",
]
def parameters_to_command(params):
"""
Converts dict of parameters into a `invoke.py` REPL command.
"""
switches = list()
if "prompt" in params:
switches.append(f'"{params["prompt"]}"')
if "steps" in params:
switches.append(f'-s {params["steps"]}')
if "seed" in params:
switches.append(f'-S {params["seed"]}')
if "width" in params:
switches.append(f'-W {params["width"]}')
if "height" in params:
switches.append(f'-H {params["height"]}')
if "cfg_scale" in params:
switches.append(f'-C {params["cfg_scale"]}')
if "sampler_name" in params:
switches.append(f'-A {params["sampler_name"]}')
if "seamless" in params and params["seamless"] == True:
switches.append(f"--seamless")
if "hires_fix" in params and params["hires_fix"] == True:
switches.append(f"--hires")
if "init_img" in params and len(params["init_img"]) > 0:
switches.append(f'-I {params["init_img"]}')
if "init_mask" in params and len(params["init_mask"]) > 0:
switches.append(f'-M {params["init_mask"]}')
if "init_color" in params and len(params["init_color"]) > 0:
switches.append(f'--init_color {params["init_color"]}')
if "strength" in params and "init_img" in params:
switches.append(f'-f {params["strength"]}')
if "fit" in params and params["fit"] == True:
switches.append(f"--fit")
if "facetool" in params:
switches.append(f'-ft {params["facetool"]}')
if "facetool_strength" in params and params["facetool_strength"]:
switches.append(f'-G {params["facetool_strength"]}')
elif "gfpgan_strength" in params and params["gfpgan_strength"]:
switches.append(f'-G {params["gfpgan_strength"]}')
if "codeformer_fidelity" in params:
switches.append(f'-cf {params["codeformer_fidelity"]}')
if "upscale" in params and params["upscale"]:
switches.append(f'-U {params["upscale"][0]} {params["upscale"][1]}')
if "variation_amount" in params and params["variation_amount"] > 0:
switches.append(f'-v {params["variation_amount"]}')
if "with_variations" in params:
seed_weight_pairs = ",".join(
f"{seed}:{weight}" for seed, weight in params["with_variations"]
)
switches.append(f"-V {seed_weight_pairs}")
return " ".join(switches)

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@ -0,0 +1,27 @@
# This file describes the alternative machine learning models
# available to InvokeAI script.
#
# To add a new model, follow the examples below. Each
# model requires a model config file, a weights file,
# and the width and height of the images it
# was trained on.
stable-diffusion-1.5:
description: The newest Stable Diffusion version 1.5 weight file (4.27 GB)
weights: ./models/ldm/stable-diffusion-v1/v1-5-pruned-emaonly.ckpt
config: ./configs/stable-diffusion/v1-inference.yaml
width: 512
height: 512
vae: ./models/ldm/stable-diffusion-v1/vae-ft-mse-840000-ema-pruned.ckpt
default: true
stable-diffusion-1.4:
description: Stable Diffusion inference model version 1.4
config: configs/stable-diffusion/v1-inference.yaml
weights: models/ldm/stable-diffusion-v1/sd-v1-4.ckpt
vae: models/ldm/stable-diffusion-v1/vae-ft-mse-840000-ema-pruned.ckpt
width: 512
height: 512
inpainting-1.5:
weights: models/ldm/stable-diffusion-v1/sd-v1-5-inpainting.ckpt
config: configs/stable-diffusion/v1-inpainting-inference.yaml
vae: models/ldm/stable-diffusion-v1/vae-ft-mse-840000-ema-pruned.ckpt
description: RunwayML SD 1.5 model optimized for inpainting

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@ -0,0 +1,110 @@
model:
base_learning_rate: 5.0e-03
target: ldm.models.diffusion.ddpm.LatentDiffusion
params:
linear_start: 0.00085
linear_end: 0.0120
num_timesteps_cond: 1
log_every_t: 200
timesteps: 1000
first_stage_key: image
cond_stage_key: caption
image_size: 64
channels: 4
cond_stage_trainable: true # Note: different from the one we trained before
conditioning_key: crossattn
monitor: val/loss_simple_ema
scale_factor: 0.18215
use_ema: False
embedding_reg_weight: 0.0
personalization_config:
target: ldm.modules.embedding_manager.EmbeddingManager
params:
placeholder_strings: ["*"]
initializer_words: ["sculpture"]
per_image_tokens: false
num_vectors_per_token: 1
progressive_words: False
unet_config:
target: ldm.modules.diffusionmodules.openaimodel.UNetModel
params:
image_size: 32 # unused
in_channels: 4
out_channels: 4
model_channels: 320
attention_resolutions: [ 4, 2, 1 ]
num_res_blocks: 2
channel_mult: [ 1, 2, 4, 4 ]
num_heads: 8
use_spatial_transformer: True
transformer_depth: 1
context_dim: 768
use_checkpoint: True
legacy: False
first_stage_config:
target: ldm.models.autoencoder.AutoencoderKL
params:
embed_dim: 4
monitor: val/rec_loss
ddconfig:
double_z: true
z_channels: 4
resolution: 256
in_channels: 3
out_ch: 3
ch: 128
ch_mult:
- 1
- 2
- 4
- 4
num_res_blocks: 2
attn_resolutions: []
dropout: 0.0
lossconfig:
target: torch.nn.Identity
cond_stage_config:
target: ldm.modules.encoders.modules.FrozenCLIPEmbedder
data:
target: main.DataModuleFromConfig
params:
batch_size: 1
num_workers: 2
wrap: false
train:
target: ldm.data.personalized.PersonalizedBase
params:
size: 512
set: train
per_image_tokens: false
repeats: 100
validation:
target: ldm.data.personalized.PersonalizedBase
params:
size: 512
set: val
per_image_tokens: false
repeats: 10
lightning:
modelcheckpoint:
params:
every_n_train_steps: 500
callbacks:
image_logger:
target: main.ImageLogger
params:
batch_frequency: 500
max_images: 8
increase_log_steps: False
trainer:
benchmark: True
max_steps: 4000000
# max_steps: 4000

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@ -0,0 +1,103 @@
model:
base_learning_rate: 5.0e-03
target: ldm.models.diffusion.ddpm.LatentDiffusion
params:
linear_start: 0.00085
linear_end: 0.0120
num_timesteps_cond: 1
log_every_t: 200
timesteps: 1000
first_stage_key: image
cond_stage_key: caption
image_size: 64
channels: 4
cond_stage_trainable: true # Note: different from the one we trained before
conditioning_key: crossattn
monitor: val/loss_simple_ema
scale_factor: 0.18215
use_ema: False
embedding_reg_weight: 0.0
personalization_config:
target: ldm.modules.embedding_manager.EmbeddingManager
params:
placeholder_strings: ["*"]
initializer_words: ["painting"]
per_image_tokens: false
num_vectors_per_token: 1
unet_config:
target: ldm.modules.diffusionmodules.openaimodel.UNetModel
params:
image_size: 32 # unused
in_channels: 4
out_channels: 4
model_channels: 320
attention_resolutions: [ 4, 2, 1 ]
num_res_blocks: 2
channel_mult: [ 1, 2, 4, 4 ]
num_heads: 8
use_spatial_transformer: True
transformer_depth: 1
context_dim: 768
use_checkpoint: True
legacy: False
first_stage_config:
target: ldm.models.autoencoder.AutoencoderKL
params:
embed_dim: 4
monitor: val/rec_loss
ddconfig:
double_z: true
z_channels: 4
resolution: 256
in_channels: 3
out_ch: 3
ch: 128
ch_mult:
- 1
- 2
- 4
- 4
num_res_blocks: 2
attn_resolutions: []
dropout: 0.0
lossconfig:
target: torch.nn.Identity
cond_stage_config:
target: ldm.modules.encoders.modules.FrozenCLIPEmbedder
data:
target: main.DataModuleFromConfig
params:
batch_size: 2
num_workers: 16
wrap: false
train:
target: ldm.data.personalized_style.PersonalizedBase
params:
size: 512
set: train
per_image_tokens: false
repeats: 100
validation:
target: ldm.data.personalized_style.PersonalizedBase
params:
size: 512
set: val
per_image_tokens: false
repeats: 10
lightning:
callbacks:
image_logger:
target: main.ImageLogger
params:
batch_frequency: 500
max_images: 8
increase_log_steps: False
trainer:
benchmark: True

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@ -0,0 +1,79 @@
model:
base_learning_rate: 1.0e-04
target: ldm.models.diffusion.ddpm.LatentDiffusion
params:
linear_start: 0.00085
linear_end: 0.0120
num_timesteps_cond: 1
log_every_t: 200
timesteps: 1000
first_stage_key: "jpg"
cond_stage_key: "txt"
image_size: 64
channels: 4
cond_stage_trainable: false # Note: different from the one we trained before
conditioning_key: crossattn
monitor: val/loss_simple_ema
scale_factor: 0.18215
use_ema: False
scheduler_config: # 10000 warmup steps
target: ldm.lr_scheduler.LambdaLinearScheduler
params:
warm_up_steps: [ 10000 ]
cycle_lengths: [ 10000000000000 ] # incredibly large number to prevent corner cases
f_start: [ 1.e-6 ]
f_max: [ 1. ]
f_min: [ 1. ]
personalization_config:
target: ldm.modules.embedding_manager.EmbeddingManager
params:
placeholder_strings: ["*"]
initializer_words: ['face', 'man', 'photo', 'africanmale']
per_image_tokens: false
num_vectors_per_token: 1
progressive_words: False
unet_config:
target: ldm.modules.diffusionmodules.openaimodel.UNetModel
params:
image_size: 32 # unused
in_channels: 4
out_channels: 4
model_channels: 320
attention_resolutions: [ 4, 2, 1 ]
num_res_blocks: 2
channel_mult: [ 1, 2, 4, 4 ]
num_heads: 8
use_spatial_transformer: True
transformer_depth: 1
context_dim: 768
use_checkpoint: True
legacy: False
first_stage_config:
target: ldm.models.autoencoder.AutoencoderKL
params:
embed_dim: 4
monitor: val/rec_loss
ddconfig:
double_z: true
z_channels: 4
resolution: 256
in_channels: 3
out_ch: 3
ch: 128
ch_mult:
- 1
- 2
- 4
- 4
num_res_blocks: 2
attn_resolutions: []
dropout: 0.0
lossconfig:
target: torch.nn.Identity
cond_stage_config:
target: ldm.modules.encoders.modules.WeightedFrozenCLIPEmbedder

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@ -0,0 +1,79 @@
model:
base_learning_rate: 7.5e-05
target: ldm.models.diffusion.ddpm.LatentInpaintDiffusion
params:
linear_start: 0.00085
linear_end: 0.0120
num_timesteps_cond: 1
log_every_t: 200
timesteps: 1000
first_stage_key: "jpg"
cond_stage_key: "txt"
image_size: 64
channels: 4
cond_stage_trainable: false # Note: different from the one we trained before
conditioning_key: hybrid # important
monitor: val/loss_simple_ema
scale_factor: 0.18215
finetune_keys: null
scheduler_config: # 10000 warmup steps
target: ldm.lr_scheduler.LambdaLinearScheduler
params:
warm_up_steps: [ 2500 ] # NOTE for resuming. use 10000 if starting from scratch
cycle_lengths: [ 10000000000000 ] # incredibly large number to prevent corner cases
f_start: [ 1.e-6 ]
f_max: [ 1. ]
f_min: [ 1. ]
personalization_config:
target: ldm.modules.embedding_manager.EmbeddingManager
params:
placeholder_strings: ["*"]
initializer_words: ['face', 'man', 'photo', 'africanmale']
per_image_tokens: false
num_vectors_per_token: 1
progressive_words: False
unet_config:
target: ldm.modules.diffusionmodules.openaimodel.UNetModel
params:
image_size: 32 # unused
in_channels: 9 # 4 data + 4 downscaled image + 1 mask
out_channels: 4
model_channels: 320
attention_resolutions: [ 4, 2, 1 ]
num_res_blocks: 2
channel_mult: [ 1, 2, 4, 4 ]
num_heads: 8
use_spatial_transformer: True
transformer_depth: 1
context_dim: 768
use_checkpoint: True
legacy: False
first_stage_config:
target: ldm.models.autoencoder.AutoencoderKL
params:
embed_dim: 4
monitor: val/rec_loss
ddconfig:
double_z: true
z_channels: 4
resolution: 256
in_channels: 3
out_ch: 3
ch: 128
ch_mult:
- 1
- 2
- 4
- 4
num_res_blocks: 2
attn_resolutions: []
dropout: 0.0
lossconfig:
target: torch.nn.Identity
cond_stage_config:
target: ldm.modules.encoders.modules.WeightedFrozenCLIPEmbedder

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@ -0,0 +1,110 @@
model:
base_learning_rate: 5.0e-03
target: ldm.models.diffusion.ddpm.LatentDiffusion
params:
linear_start: 0.00085
linear_end: 0.0120
num_timesteps_cond: 1
log_every_t: 200
timesteps: 1000
first_stage_key: image
cond_stage_key: caption
image_size: 64
channels: 4
cond_stage_trainable: true # Note: different from the one we trained before
conditioning_key: crossattn
monitor: val/loss_simple_ema
scale_factor: 0.18215
use_ema: False
embedding_reg_weight: 0.0
personalization_config:
target: ldm.modules.embedding_manager.EmbeddingManager
params:
placeholder_strings: ["*"]
initializer_words: ['face', 'man', 'photo', 'africanmale']
per_image_tokens: false
num_vectors_per_token: 6
progressive_words: False
unet_config:
target: ldm.modules.diffusionmodules.openaimodel.UNetModel
params:
image_size: 32 # unused
in_channels: 4
out_channels: 4
model_channels: 320
attention_resolutions: [ 4, 2, 1 ]
num_res_blocks: 2
channel_mult: [ 1, 2, 4, 4 ]
num_heads: 8
use_spatial_transformer: True
transformer_depth: 1
context_dim: 768
use_checkpoint: True
legacy: False
first_stage_config:
target: ldm.models.autoencoder.AutoencoderKL
params:
embed_dim: 4
monitor: val/rec_loss
ddconfig:
double_z: true
z_channels: 4
resolution: 256
in_channels: 3
out_ch: 3
ch: 128
ch_mult:
- 1
- 2
- 4
- 4
num_res_blocks: 2
attn_resolutions: []
dropout: 0.0
lossconfig:
target: torch.nn.Identity
cond_stage_config:
target: ldm.modules.encoders.modules.FrozenCLIPEmbedder
data:
target: main.DataModuleFromConfig
params:
batch_size: 1
num_workers: 2
wrap: false
train:
target: ldm.data.personalized.PersonalizedBase
params:
size: 512
set: train
per_image_tokens: false
repeats: 100
validation:
target: ldm.data.personalized.PersonalizedBase
params:
size: 512
set: val
per_image_tokens: false
repeats: 10
lightning:
modelcheckpoint:
params:
every_n_train_steps: 500
callbacks:
image_logger:
target: main.ImageLogger
params:
batch_frequency: 500
max_images: 5
increase_log_steps: False
trainer:
benchmark: False
max_steps: 6200
# max_steps: 4000

4
coverage/.gitignore vendored
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@ -1,4 +0,0 @@
# Ignore everything in this directory
*
# Except this file
!.gitignore

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docker-build/Dockerfile Normal file
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FROM ubuntu AS get_miniconda
SHELL ["/bin/bash", "-c"]
# install wget
RUN apt-get update \
&& apt-get install -y \
wget \
&& apt-get clean \
&& rm -rf /var/lib/apt/lists/*
# download and install miniconda
ARG conda_version=py39_4.12.0-Linux-x86_64
ARG conda_prefix=/opt/conda
RUN wget --progress=dot:giga -O /miniconda.sh \
https://repo.anaconda.com/miniconda/Miniconda3-${conda_version}.sh \
&& bash /miniconda.sh -b -p ${conda_prefix} \
&& rm -f /miniconda.sh
FROM ubuntu AS invokeai
# use bash
SHELL [ "/bin/bash", "-c" ]
# clean bashrc
RUN echo "" > ~/.bashrc
# Install necesarry packages
RUN apt-get update \
&& apt-get install -y \
--no-install-recommends \
gcc \
git \
libgl1-mesa-glx \
libglib2.0-0 \
pip \
python3 \
python3-dev \
&& apt-get clean \
&& rm -rf /var/lib/apt/lists/*
# clone repository and create symlinks
ARG invokeai_git=https://github.com/invoke-ai/InvokeAI.git
ARG project_name=invokeai
RUN git clone ${invokeai_git} /${project_name} \
&& mkdir /${project_name}/models/ldm/stable-diffusion-v1 \
&& ln -s /data/models/sd-v1-4.ckpt /${project_name}/models/ldm/stable-diffusion-v1/model.ckpt \
&& ln -s /data/outputs/ /${project_name}/outputs
# set workdir
WORKDIR /${project_name}
# install conda env and preload models
ARG conda_prefix=/opt/conda
ARG conda_env_file=environment.yml
COPY --from=get_miniconda ${conda_prefix} ${conda_prefix}
RUN source ${conda_prefix}/etc/profile.d/conda.sh \
&& conda init bash \
&& source ~/.bashrc \
&& conda env create \
--name ${project_name} \
--file ${conda_env_file} \
&& rm -Rf ~/.cache \
&& conda clean -afy \
&& echo "conda activate ${project_name}" >> ~/.bashrc \
&& ln -s /data/models/GFPGANv1.4.pth ./src/gfpgan/experiments/pretrained_models/GFPGANv1.4.pth \
&& conda activate ${project_name} \
&& python scripts/preload_models.py
# Copy entrypoint and set env
ENV CONDA_PREFIX=${conda_prefix}
ENV PROJECT_NAME=${project_name}
COPY docker-build/entrypoint.sh /
ENTRYPOINT [ "/entrypoint.sh" ]

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#!/usr/bin/env bash
set -e
# IMPORTANT: You need to have a token on huggingface.co to be able to download the checkpoint!!!
# configure values by using env when executing build.sh
# f.e. env ARCH=aarch64 GITHUB_INVOKE_AI=https://github.com/yourname/yourfork.git ./build.sh
source ./docker-build/env.sh || echo "please run from repository root" || exit 1
invokeai_conda_version=${INVOKEAI_CONDA_VERSION:-py39_4.12.0-${platform/\//-}}
invokeai_conda_prefix=${INVOKEAI_CONDA_PREFIX:-\/opt\/conda}
invokeai_conda_env_file=${INVOKEAI_CONDA_ENV_FILE:-environment.yml}
invokeai_git=${INVOKEAI_GIT:-https://github.com/invoke-ai/InvokeAI.git}
huggingface_token=${HUGGINGFACE_TOKEN?}
# print the settings
echo "You are using these values:"
echo -e "project_name:\t\t ${project_name}"
echo -e "volumename:\t\t ${volumename}"
echo -e "arch:\t\t\t ${arch}"
echo -e "platform:\t\t ${platform}"
echo -e "invokeai_conda_version:\t ${invokeai_conda_version}"
echo -e "invokeai_conda_prefix:\t ${invokeai_conda_prefix}"
echo -e "invokeai_conda_env_file: ${invokeai_conda_env_file}"
echo -e "invokeai_git:\t\t ${invokeai_git}"
echo -e "invokeai_tag:\t\t ${invokeai_tag}\n"
_runAlpine() {
docker run \
--rm \
--interactive \
--tty \
--mount source="$volumename",target=/data \
--workdir /data \
alpine "$@"
}
_copyCheckpoints() {
echo "creating subfolders for models and outputs"
_runAlpine mkdir models
_runAlpine mkdir outputs
echo -n "downloading sd-v1-4.ckpt"
_runAlpine wget --header="Authorization: Bearer ${huggingface_token}" -O models/sd-v1-4.ckpt https://huggingface.co/CompVis/stable-diffusion-v-1-4-original/resolve/main/sd-v1-4.ckpt
echo "done"
echo "downloading GFPGANv1.4.pth"
_runAlpine wget -O models/GFPGANv1.4.pth https://github.com/TencentARC/GFPGAN/releases/download/v1.3.0/GFPGANv1.4.pth
}
_checkVolumeContent() {
_runAlpine ls -lhA /data/models
}
_getModelMd5s() {
_runAlpine \
alpine sh -c "md5sum /data/models/*"
}
if [[ -n "$(docker volume ls -f name="${volumename}" -q)" ]]; then
echo "Volume already exists"
if [[ -z "$(_checkVolumeContent)" ]]; then
echo "looks empty, copying checkpoint"
_copyCheckpoints
fi
echo "Models in ${volumename}:"
_checkVolumeContent
else
echo -n "createing docker volume "
docker volume create "${volumename}"
_copyCheckpoints
fi
# Build Container
docker build \
--platform="${platform}" \
--tag "${invokeai_tag}" \
--build-arg project_name="${project_name}" \
--build-arg conda_version="${invokeai_conda_version}" \
--build-arg conda_prefix="${invokeai_conda_prefix}" \
--build-arg conda_env_file="${invokeai_conda_env_file}" \
--build-arg invokeai_git="${invokeai_git}" \
--file ./docker-build/Dockerfile \
.

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#!/bin/bash
set -e
source "${CONDA_PREFIX}/etc/profile.d/conda.sh"
conda activate "${PROJECT_NAME}"
python scripts/invoke.py \
${@:---web --host=0.0.0.0}

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#!/usr/bin/env bash
project_name=${PROJECT_NAME:-invokeai}
volumename=${VOLUMENAME:-${project_name}_data}
arch=${ARCH:-x86_64}
platform=${PLATFORM:-Linux/${arch}}
invokeai_tag=${INVOKEAI_TAG:-${project_name}-${arch}}
export project_name
export volumename
export arch
export platform
export invokeai_tag

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#!/usr/bin/env bash
set -e
source ./docker-build/env.sh || echo "please run from repository root" || exit 1
docker run \
--interactive \
--tty \
--rm \
--platform "$platform" \
--name "$project_name" \
--hostname "$project_name" \
--mount source="$volumename",target=/data \
--publish 9090:9090 \
"$invokeai_tag" ${1:+$@}

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# syntax=docker/dockerfile:1
ARG PYTHON_VERSION=3.9
##################
## base image ##
##################
FROM --platform=${TARGETPLATFORM} python:${PYTHON_VERSION}-slim AS python-base
LABEL org.opencontainers.image.authors="mauwii@outlook.de"
# Prepare apt for buildkit cache
RUN rm -f /etc/apt/apt.conf.d/docker-clean \
&& echo 'Binary::apt::APT::Keep-Downloaded-Packages "true";' >/etc/apt/apt.conf.d/keep-cache
# Install dependencies
RUN \
--mount=type=cache,target=/var/cache/apt,sharing=locked \
--mount=type=cache,target=/var/lib/apt,sharing=locked \
apt-get update \
&& apt-get install -y \
--no-install-recommends \
libgl1-mesa-glx=20.3.* \
libglib2.0-0=2.66.* \
libopencv-dev=4.5.*
# Set working directory and env
ARG APPDIR=/usr/src
ARG APPNAME=InvokeAI
WORKDIR ${APPDIR}
ENV PATH ${APPDIR}/${APPNAME}/bin:$PATH
# Keeps Python from generating .pyc files in the container
ENV PYTHONDONTWRITEBYTECODE 1
# Turns off buffering for easier container logging
ENV PYTHONUNBUFFERED 1
# Don't fall back to legacy build system
ENV PIP_USE_PEP517=1
#######################
## build pyproject ##
#######################
FROM python-base AS pyproject-builder
# Install build dependencies
RUN \
--mount=type=cache,target=/var/cache/apt,sharing=locked \
--mount=type=cache,target=/var/lib/apt,sharing=locked \
apt-get update \
&& apt-get install -y \
--no-install-recommends \
build-essential=12.9 \
gcc=4:10.2.* \
python3-dev=3.9.*
# Prepare pip for buildkit cache
ARG PIP_CACHE_DIR=/var/cache/buildkit/pip
ENV PIP_CACHE_DIR ${PIP_CACHE_DIR}
RUN mkdir -p ${PIP_CACHE_DIR}
# Create virtual environment
RUN --mount=type=cache,target=${PIP_CACHE_DIR} \
python3 -m venv "${APPNAME}" \
--upgrade-deps
# Install requirements
COPY --link pyproject.toml .
COPY --link invokeai/version/invokeai_version.py invokeai/version/__init__.py invokeai/version/
ARG PIP_EXTRA_INDEX_URL
ENV PIP_EXTRA_INDEX_URL ${PIP_EXTRA_INDEX_URL}
RUN --mount=type=cache,target=${PIP_CACHE_DIR} \
"${APPNAME}"/bin/pip install .
# Install pyproject.toml
COPY --link . .
RUN --mount=type=cache,target=${PIP_CACHE_DIR} \
"${APPNAME}/bin/pip" install .
# Build patchmatch
RUN python3 -c "from patchmatch import patch_match"
#####################
## runtime image ##
#####################
FROM python-base AS runtime
# Create a new user
ARG UNAME=appuser
RUN useradd \
--no-log-init \
-m \
-U \
"${UNAME}"
# Create volume directory
ARG VOLUME_DIR=/data
RUN mkdir -p "${VOLUME_DIR}" \
&& chown -hR "${UNAME}:${UNAME}" "${VOLUME_DIR}"
# Setup runtime environment
USER ${UNAME}:${UNAME}
COPY --chown=${UNAME}:${UNAME} --from=pyproject-builder ${APPDIR}/${APPNAME} ${APPNAME}
ENV INVOKEAI_ROOT ${VOLUME_DIR}
ENV TRANSFORMERS_CACHE ${VOLUME_DIR}/.cache
ENV INVOKE_MODEL_RECONFIGURE "--yes --default_only"
EXPOSE 9090
ENTRYPOINT [ "invokeai" ]
CMD [ "--web", "--host", "0.0.0.0", "--port", "9090" ]
VOLUME [ "${VOLUME_DIR}" ]

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#!/usr/bin/env bash
set -e
# If you want to build a specific flavor, set the CONTAINER_FLAVOR environment variable
# e.g. CONTAINER_FLAVOR=cpu ./build.sh
# Possible Values are:
# - cpu
# - cuda
# - rocm
# Don't forget to also set it when executing run.sh
# if it is not set, the script will try to detect the flavor by itself.
#
# Doc can be found here:
# https://invoke-ai.github.io/InvokeAI/installation/040_INSTALL_DOCKER/
SCRIPTDIR=$(dirname "${BASH_SOURCE[0]}")
cd "$SCRIPTDIR" || exit 1
source ./env.sh
DOCKERFILE=${INVOKE_DOCKERFILE:-./Dockerfile}
# print the settings
echo -e "You are using these values:\n"
echo -e "Dockerfile:\t\t${DOCKERFILE}"
echo -e "index-url:\t\t${PIP_EXTRA_INDEX_URL:-none}"
echo -e "Volumename:\t\t${VOLUMENAME}"
echo -e "Platform:\t\t${PLATFORM}"
echo -e "Container Registry:\t${CONTAINER_REGISTRY}"
echo -e "Container Repository:\t${CONTAINER_REPOSITORY}"
echo -e "Container Tag:\t\t${CONTAINER_TAG}"
echo -e "Container Flavor:\t${CONTAINER_FLAVOR}"
echo -e "Container Image:\t${CONTAINER_IMAGE}\n"
# Create docker volume
if [[ -n "$(docker volume ls -f name="${VOLUMENAME}" -q)" ]]; then
echo -e "Volume already exists\n"
else
echo -n "creating docker volume "
docker volume create "${VOLUMENAME}"
fi
# Build Container
docker build \
--platform="${PLATFORM:-linux/amd64}" \
--tag="${CONTAINER_IMAGE:-invokeai}" \
${CONTAINER_FLAVOR:+--build-arg="CONTAINER_FLAVOR=${CONTAINER_FLAVOR}"} \
${PIP_EXTRA_INDEX_URL:+--build-arg="PIP_EXTRA_INDEX_URL=${PIP_EXTRA_INDEX_URL}"} \
${PIP_PACKAGE:+--build-arg="PIP_PACKAGE=${PIP_PACKAGE}"} \
--file="${DOCKERFILE}" \
..

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#!/usr/bin/env bash
# This file is used to set environment variables for the build.sh and run.sh scripts.
# Try to detect the container flavor if no PIP_EXTRA_INDEX_URL got specified
if [[ -z "$PIP_EXTRA_INDEX_URL" ]]; then
# Activate virtual environment if not already activated and exists
if [[ -z $VIRTUAL_ENV ]]; then
[[ -e "$(dirname "${BASH_SOURCE[0]}")/../.venv/bin/activate" ]] \
&& source "$(dirname "${BASH_SOURCE[0]}")/../.venv/bin/activate" \
&& echo "Activated virtual environment: $VIRTUAL_ENV"
fi
# Decide which container flavor to build if not specified
if [[ -z "$CONTAINER_FLAVOR" ]] && python -c "import torch" &>/dev/null; then
# Check for CUDA and ROCm
CUDA_AVAILABLE=$(python -c "import torch;print(torch.cuda.is_available())")
ROCM_AVAILABLE=$(python -c "import torch;print(torch.version.hip is not None)")
if [[ "${CUDA_AVAILABLE}" == "True" ]]; then
CONTAINER_FLAVOR="cuda"
elif [[ "${ROCM_AVAILABLE}" == "True" ]]; then
CONTAINER_FLAVOR="rocm"
else
CONTAINER_FLAVOR="cpu"
fi
fi
# Set PIP_EXTRA_INDEX_URL based on container flavor
if [[ "$CONTAINER_FLAVOR" == "rocm" ]]; then
PIP_EXTRA_INDEX_URL="https://download.pytorch.org/whl/rocm"
elif [[ "$CONTAINER_FLAVOR" == "cpu" ]]; then
PIP_EXTRA_INDEX_URL="https://download.pytorch.org/whl/cpu"
# elif [[ -z "$CONTAINER_FLAVOR" || "$CONTAINER_FLAVOR" == "cuda" ]]; then
# PIP_PACKAGE=${PIP_PACKAGE-".[xformers]"}
fi
fi
# Variables shared by build.sh and run.sh
REPOSITORY_NAME="${REPOSITORY_NAME-$(basename "$(git rev-parse --show-toplevel)")}"
REPOSITORY_NAME="${REPOSITORY_NAME,,}"
VOLUMENAME="${VOLUMENAME-"${REPOSITORY_NAME}_data"}"
ARCH="${ARCH-$(uname -m)}"
PLATFORM="${PLATFORM-linux/${ARCH}}"
INVOKEAI_BRANCH="${INVOKEAI_BRANCH-$(git branch --show)}"
CONTAINER_REGISTRY="${CONTAINER_REGISTRY-"ghcr.io"}"
CONTAINER_REPOSITORY="${CONTAINER_REPOSITORY-"$(whoami)/${REPOSITORY_NAME}"}"
CONTAINER_FLAVOR="${CONTAINER_FLAVOR-cuda}"
CONTAINER_TAG="${CONTAINER_TAG-"${INVOKEAI_BRANCH##*/}-${CONTAINER_FLAVOR}"}"
CONTAINER_IMAGE="${CONTAINER_REGISTRY}/${CONTAINER_REPOSITORY}:${CONTAINER_TAG}"
CONTAINER_IMAGE="${CONTAINER_IMAGE,,}"
# enable docker buildkit
export DOCKER_BUILDKIT=1

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#!/usr/bin/env bash
set -e
# How to use: https://invoke-ai.github.io/InvokeAI/installation/040_INSTALL_DOCKER/
SCRIPTDIR=$(dirname "${BASH_SOURCE[0]}")
cd "$SCRIPTDIR" || exit 1
source ./env.sh
# Create outputs directory if it does not exist
[[ -d ./outputs ]] || mkdir ./outputs
echo -e "You are using these values:\n"
echo -e "Volumename:\t${VOLUMENAME}"
echo -e "Invokeai_tag:\t${CONTAINER_IMAGE}"
echo -e "local Models:\t${MODELSPATH:-unset}\n"
docker run \
--interactive \
--tty \
--rm \
--platform="${PLATFORM}" \
--name="${REPOSITORY_NAME}" \
--hostname="${REPOSITORY_NAME}" \
--mount type=volume,volume-driver=local,source="${VOLUMENAME}",target=/data \
--mount type=bind,source="$(pwd)"/outputs/,target=/data/outputs/ \
${MODELSPATH:+--mount="type=bind,source=${MODELSPATH},target=/data/models"} \
${HUGGING_FACE_HUB_TOKEN:+--env="HUGGING_FACE_HUB_TOKEN=${HUGGING_FACE_HUB_TOKEN}"} \
--publish=9090:9090 \
--cap-add=sys_nice \
${GPU_FLAGS:+--gpus="${GPU_FLAGS}"} \
"${CONTAINER_IMAGE}" ${@:+$@}
echo -e "\nCleaning trash folder ..."
for f in outputs/.Trash*; do
if [ -e "$f" ]; then
rm -Rf "$f"
break
fi
done

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@ -4,425 +4,133 @@ title: Changelog
# :octicons-log-16: **Changelog**
## v2.3.0 <small>(15 January 2023)</small>
## v2.1.0 (2 November 2022)
- update mac instructions to use invokeai for env name by @willwillems in https://github.com/invoke-ai/InvokeAI/pull/1030
- Update .gitignore by @blessedcoolant in https://github.com/invoke-ai/InvokeAI/pull/1040
- reintroduce fix for m1 from https://github.com/invoke-ai/InvokeAI/pull/579 missing after merge by @skurovec in https://github.com/invoke-ai/InvokeAI/pull/1056
- Update Stable_Diffusion_AI_Notebook.ipynb (Take 2) by @ChloeL19 in https://github.com/invoke-ai/InvokeAI/pull/1060
- Print out the device type which is used by @manzke in https://github.com/invoke-ai/InvokeAI/pull/1073
- Hires Addition by @hipsterusername in https://github.com/invoke-ai/InvokeAI/pull/1063
- fix for "1 leaked semaphore objects to clean up at shutdown" on M1 by @skurovec in https://github.com/invoke-ai/InvokeAI/pull/1081
- Forward dream.py to invoke.py using the same interpreter, add deprecation warning by @db3000 in https://github.com/invoke-ai/InvokeAI/pull/1077
- fix noisy images at high step counts by @lstein in https://github.com/invoke-ai/InvokeAI/pull/1086
- Generalize facetool strength argument by @db3000 in https://github.com/invoke-ai/InvokeAI/pull/1078
- Enable fast switching among models at the invoke> command line by @lstein in https://github.com/invoke-ai/InvokeAI/pull/1066
- Fix Typo, committed changing ldm environment to invokeai by @jdries3 in https://github.com/invoke-ai/InvokeAI/pull/1095
- Update generate.py by @unreleased in https://github.com/invoke-ai/InvokeAI/pull/1109
- Update 'ldm' env to 'invokeai' in troubleshooting steps by @19wolf in https://github.com/invoke-ai/InvokeAI/pull/1125
- Fixed documentation typos and resolved merge conflicts by @rupeshs in https://github.com/invoke-ai/InvokeAI/pull/1123
- Fix broken doc links, fix malaprop in the project subtitle by @majick in https://github.com/invoke-ai/InvokeAI/pull/1131
- Only output facetool parameters if enhancing faces by @db3000 in https://github.com/invoke-ai/InvokeAI/pull/1119
- Update gitignore to ignore codeformer weights at new location by @spezialspezial in https://github.com/invoke-ai/InvokeAI/pull/1136
- fix links to point to invoke-ai.github.io #1117 by @mauwii in https://github.com/invoke-ai/InvokeAI/pull/1143
- Rework-mkdocs by @mauwii in https://github.com/invoke-ai/InvokeAI/pull/1144
- add option to CLI and pngwriter that allows user to set PNG compression level by @lstein in https://github.com/invoke-ai/InvokeAI/pull/1127
- Fix img2img DDIM index out of bound by @wfng92 in https://github.com/invoke-ai/InvokeAI/pull/1137
- Fix gh actions by @mauwii in https://github.com/invoke-ai/InvokeAI/pull/1128
- update mac instructions to use invokeai for env name by @willwillems in https://github.com/invoke-ai/InvokeAI/pull/1030
- Update .gitignore by @blessedcoolant in https://github.com/invoke-ai/InvokeAI/pull/1040
- reintroduce fix for m1 from https://github.com/invoke-ai/InvokeAI/pull/579 missing after merge by @skurovec in https://github.com/invoke-ai/InvokeAI/pull/1056
- Update Stable_Diffusion_AI_Notebook.ipynb (Take 2) by @ChloeL19 in https://github.com/invoke-ai/InvokeAI/pull/1060
- Print out the device type which is used by @manzke in https://github.com/invoke-ai/InvokeAI/pull/1073
- Hires Addition by @hipsterusername in https://github.com/invoke-ai/InvokeAI/pull/1063
- fix for "1 leaked semaphore objects to clean up at shutdown" on M1 by @skurovec in https://github.com/invoke-ai/InvokeAI/pull/1081
- Forward dream.py to invoke.py using the same interpreter, add deprecation warning by @db3000 in https://github.com/invoke-ai/InvokeAI/pull/1077
- fix noisy images at high step counts by @lstein in https://github.com/invoke-ai/InvokeAI/pull/1086
- Generalize facetool strength argument by @db3000 in https://github.com/invoke-ai/InvokeAI/pull/1078
- Enable fast switching among models at the invoke> command line by @lstein in https://github.com/invoke-ai/InvokeAI/pull/1066
- Fix Typo, committed changing ldm environment to invokeai by @jdries3 in https://github.com/invoke-ai/InvokeAI/pull/1095
- Fixed documentation typos and resolved merge conflicts by @rupeshs in https://github.com/invoke-ai/InvokeAI/pull/1123
- Only output facetool parameters if enhancing faces by @db3000 in https://github.com/invoke-ai/InvokeAI/pull/1119
- add option to CLI and pngwriter that allows user to set PNG compression level by @lstein in https://github.com/invoke-ai/InvokeAI/pull/1127
- Fix img2img DDIM index out of bound by @wfng92 in https://github.com/invoke-ai/InvokeAI/pull/1137
- Add text prompt to inpaint mask support by @lstein in https://github.com/invoke-ai/InvokeAI/pull/1133
- Respect http[s] protocol when making socket.io middleware by @damian0815 in https://github.com/invoke-ai/InvokeAI/pull/976
- WebUI: Adds Codeformer support by @psychedelicious in https://github.com/invoke-ai/InvokeAI/pull/1151
- Skips normalizing prompts for web UI metadata by @psychedelicious in https://github.com/invoke-ai/InvokeAI/pull/1165
- Add Asymmetric Tiling by @carson-katri in https://github.com/invoke-ai/InvokeAI/pull/1132
- Web UI: Increases max CFG Scale to 200 by @psychedelicious in https://github.com/invoke-ai/InvokeAI/pull/1172
- Corrects color channels in face restoration; Fixes #1167 by @psychedelicious in https://github.com/invoke-ai/InvokeAI/pull/1175
- Flips channels using array slicing instead of using OpenCV by @psychedelicious in https://github.com/invoke-ai/InvokeAI/pull/1178
- Fix typo in docs: s/Formally/Formerly by @noodlebox in https://github.com/invoke-ai/InvokeAI/pull/1176
- fix clipseg loading problems by @lstein in https://github.com/invoke-ai/InvokeAI/pull/1177
- Correct color channels in upscale using array slicing by @wfng92 in https://github.com/invoke-ai/InvokeAI/pull/1181
- Web UI: Filters existing images when adding new images; Fixes #1085 by @psychedelicious in https://github.com/invoke-ai/InvokeAI/pull/1171
- fix a number of bugs in textual inversion by @lstein in https://github.com/invoke-ai/InvokeAI/pull/1190
- Improve !fetch, add !replay command by @ArDiouscuros in https://github.com/invoke-ai/InvokeAI/pull/882
- Fix generation of image with s>1000 by @holstvoogd in https://github.com/invoke-ai/InvokeAI/pull/951
- Web UI: Gallery improvements by @psychedelicious in https://github.com/invoke-ai/InvokeAI/pull/1198
- Update CLI.md by @krummrey in https://github.com/invoke-ai/InvokeAI/pull/1211
- outcropping improvements by @lstein in https://github.com/invoke-ai/InvokeAI/pull/1207
- add support for loading VAE autoencoders by @lstein in https://github.com/invoke-ai/InvokeAI/pull/1216
- remove duplicate fix_func for MPS by @wfng92 in https://github.com/invoke-ai/InvokeAI/pull/1210
- Metadata storage and retrieval fixes by @lstein in https://github.com/invoke-ai/InvokeAI/pull/1204
- nix: add shell.nix file by @Cloudef in https://github.com/invoke-ai/InvokeAI/pull/1170
- Web UI: Changes vite dist asset paths to relative by @psychedelicious in https://github.com/invoke-ai/InvokeAI/pull/1185
- Web UI: Removes isDisabled from PromptInput by @psychedelicious in https://github.com/invoke-ai/InvokeAI/pull/1187
- Allow user to generate images with initial noise as on M1 / mps system by @ArDiouscuros in https://github.com/invoke-ai/InvokeAI/pull/981
- feat: adding filename format template by @plucked in https://github.com/invoke-ai/InvokeAI/pull/968
- Web UI: Fixes broken bundle by @psychedelicious in https://github.com/invoke-ai/InvokeAI/pull/1242
- Support runwayML custom inpainting model by @lstein in https://github.com/invoke-ai/InvokeAI/pull/1243
- Update IMG2IMG.md by @talitore in https://github.com/invoke-ai/InvokeAI/pull/1262
- New dockerfile - including a build- and a run- script as well as a GH-Action by @mauwii in https://github.com/invoke-ai/InvokeAI/pull/1233
- cut over from karras to model noise schedule for higher steps by @lstein in https://github.com/invoke-ai/InvokeAI/pull/1222
- Prompt tweaks by @lstein in https://github.com/invoke-ai/InvokeAI/pull/1268
- Outpainting implementation by @Kyle0654 in https://github.com/invoke-ai/InvokeAI/pull/1251
- fixing aspect ratio on hires by @tjennings in https://github.com/invoke-ai/InvokeAI/pull/1249
- Fix-build-container-action by @mauwii in https://github.com/invoke-ai/InvokeAI/pull/1274
- handle all unicode characters by @damian0815 in https://github.com/invoke-ai/InvokeAI/pull/1276
- adds models.user.yml to .gitignore by @JakeHL in https://github.com/invoke-ai/InvokeAI/pull/1281
- remove debug branch, set fail-fast to false by @mauwii in https://github.com/invoke-ai/InvokeAI/pull/1284
- Protect-secrets-on-pr by @mauwii in https://github.com/invoke-ai/InvokeAI/pull/1285
- Web UI: Adds initial inpainting implementation by @psychedelicious in https://github.com/invoke-ai/InvokeAI/pull/1225
- fix environment-mac.yml - tested on x64 and arm64 by @mauwii in https://github.com/invoke-ai/InvokeAI/pull/1289
- Use proper authentication to download model by @mauwii in https://github.com/invoke-ai/InvokeAI/pull/1287
- Prevent indexing error for mode RGB by @spezialspezial in https://github.com/invoke-ai/InvokeAI/pull/1294
- Integrate sd-v1-5 model into test matrix (easily expandable), remove unecesarry caches by @mauwii in https://github.com/invoke-ai/InvokeAI/pull/1293
- add --no-interactive to preload_models step by @mauwii in https://github.com/invoke-ai/InvokeAI/pull/1302
- 1-click installer and updater. Uses micromamba to install git and conda into a contained environment (if necessary) before running the normal installation script by @cmdr2 in https://github.com/invoke-ai/InvokeAI/pull/1253
- preload_models.py script downloads the weight files by @lstein in https://github.com/invoke-ai/InvokeAI/pull/1290
**Transition to diffusers
## v2.0.1 (13 October 2022)
Version 2.3 provides support for both the traditional `.ckpt` weight
checkpoint files as well as the HuggingFace `diffusers` format. This
introduces several changes you should know about.
1. The models.yaml format has been updated. There are now two
different type of configuration stanza. The traditional ckpt
one will look like this, with a `format` of `ckpt` and a
`weights` field that points to the absolute or ROOTDIR-relative
location of the ckpt file.
```
inpainting-1.5:
description: RunwayML SD 1.5 model optimized for inpainting (4.27 GB)
repo_id: runwayml/stable-diffusion-inpainting
format: ckpt
width: 512
height: 512
weights: models/ldm/stable-diffusion-v1/sd-v1-5-inpainting.ckpt
config: configs/stable-diffusion/v1-inpainting-inference.yaml
vae: models/ldm/stable-diffusion-v1/vae-ft-mse-840000-ema-pruned.ckpt
```
A configuration stanza for a diffusers model hosted at HuggingFace will look like this,
with a `format` of `diffusers` and a `repo_id` that points to the
repository ID of the model on HuggingFace:
```
stable-diffusion-2.1:
description: Stable Diffusion version 2.1 diffusers model (5.21 GB)
repo_id: stabilityai/stable-diffusion-2-1
format: diffusers
```
A configuration stanza for a diffuers model stored locally should
look like this, with a `format` of `diffusers`, but a `path` field
that points at the directory that contains `model_index.json`:
```
waifu-diffusion:
description: Latest waifu diffusion 1.4
format: diffusers
path: models/diffusers/hakurei-haifu-diffusion-1.4
```
2. In order of precedence, InvokeAI will now use HF_HOME, then
XDG_CACHE_HOME, then finally default to `ROOTDIR/models` to
store HuggingFace diffusers models.
Consequently, the format of the models directory has changed to
mimic the HuggingFace cache directory. When HF_HOME and XDG_HOME
are not set, diffusers models are now automatically downloaded
and retrieved from the directory `ROOTDIR/models/diffusers`,
while other models are stored in the directory
`ROOTDIR/models/hub`. This organization is the same as that used
by HuggingFace for its cache management.
This allows you to share diffusers and ckpt model files easily with
other machine learning applications that use the HuggingFace
libraries. To do this, set the environment variable HF_HOME
before starting up InvokeAI to tell it what directory to
cache models in. To tell InvokeAI to use the standard HuggingFace
cache directory, you would set HF_HOME like this (Linux/Mac):
`export HF_HOME=~/.cache/huggingface`
Both HuggingFace and InvokeAI will fall back to the XDG_CACHE_HOME
environment variable if HF_HOME is not set; this path
takes precedence over `ROOTDIR/models` to allow for the same sharing
with other machine learning applications that use HuggingFace
libraries.
3. If you upgrade to InvokeAI 2.3.* from an earlier version, there
will be a one-time migration from the old models directory format
to the new one. You will see a message about this the first time
you start `invoke.py`.
4. Both the front end back ends of the model manager have been
rewritten to accommodate diffusers. You can import models using
their local file path, using their URLs, or their HuggingFace
repo_ids. On the command line, all these syntaxes work:
```
!import_model stabilityai/stable-diffusion-2-1-base
!import_model /opt/sd-models/sd-1.4.ckpt
!import_model https://huggingface.co/Fictiverse/Stable_Diffusion_PaperCut_Model/blob/main/PaperCut_v1.ckpt
```
**KNOWN BUGS (15 January 2023)
1. On CUDA systems, the 768 pixel stable-diffusion-2.0 and
stable-diffusion-2.1 models can only be run as `diffusers` models
when the `xformer` library is installed and configured. Without
`xformers`, InvokeAI returns black images.
2. Inpainting and outpainting have regressed in quality.
Both these issues are being actively worked on.
## v2.2.4 <small>(11 December 2022)</small>
**the `invokeai` directory**
Previously there were two directories to worry about, the directory that
contained the InvokeAI source code and the launcher scripts, and the `invokeai`
directory that contained the models files, embeddings, configuration and
outputs. With the 2.2.4 release, this dual system is done away with, and
everything, including the `invoke.bat` and `invoke.sh` launcher scripts, now
live in a directory named `invokeai`. By default this directory is located in
your home directory (e.g. `\Users\yourname` on Windows), but you can select
where it goes at install time.
After installation, you can delete the install directory (the one that the zip
file creates when it unpacks). Do **not** delete or move the `invokeai`
directory!
**Initialization file `invokeai/invokeai.init`**
You can place frequently-used startup options in this file, such as the default
number of steps or your preferred sampler. To keep everything in one place, this
file has now been moved into the `invokeai` directory and is named
`invokeai.init`.
**To update from Version 2.2.3**
The easiest route is to download and unpack one of the 2.2.4 installer files.
When it asks you for the location of the `invokeai` runtime directory, respond
with the path to the directory that contains your 2.2.3 `invokeai`. That is, if
`invokeai` lives at `C:\Users\fred\invokeai`, then answer with `C:\Users\fred`
and answer "Y" when asked if you want to reuse the directory.
The `update.sh` (`update.bat`) script that came with the 2.2.3 source installer
does not know about the new directory layout and won't be fully functional.
**To update to 2.2.5 (and beyond) there's now an update path**
As they become available, you can update to more recent versions of InvokeAI
using an `update.sh` (`update.bat`) script located in the `invokeai` directory.
Running it without any arguments will install the most recent version of
InvokeAI. Alternatively, you can get set releases by running the `update.sh`
script with an argument in the command shell. This syntax accepts the path to
the desired release's zip file, which you can find by clicking on the green
"Code" button on this repository's home page.
**Other 2.2.4 Improvements**
- Fix InvokeAI GUI initialization by @addianto in #1687
- fix link in documentation by @lstein in #1728
- Fix broken link by @ShawnZhong in #1736
- Remove reference to binary installer by @lstein in #1731
- documentation fixes for 2.2.3 by @lstein in #1740
- Modify installer links to point closer to the source installer by @ebr in
#1745
- add documentation warning about 1650/60 cards by @lstein in #1753
- Fix Linux source URL in installation docs by @andybearman in #1756
- Make install instructions discoverable in readme by @damian0815 in #1752
- typo fix by @ofirkris in #1755
- Non-interactive model download (support HUGGINGFACE_TOKEN) by @ebr in #1578
- fix(srcinstall): shell installer - cp scripts instead of linking by @tildebyte
in #1765
- stability and usage improvements to binary & source installers by @lstein in
#1760
- fix off-by-one bug in cross-attention-control by @damian0815 in #1774
- Eventually update APP_VERSION to 2.2.3 by @spezialspezial in #1768
- invoke script cds to its location before running by @lstein in #1805
- Make PaperCut and VoxelArt models load again by @lstein in #1730
- Fix --embedding_directory / --embedding_path not working by @blessedcoolant in
#1817
- Clean up readme by @hipsterusername in #1820
- Optimized Docker build with support for external working directory by @ebr in
#1544
- disable pushing the cloud container by @mauwii in #1831
- Fix docker push github action and expand with additional metadata by @ebr in
#1837
- Fix Broken Link To Notebook by @VedantMadane in #1821
- Account for flat models by @spezialspezial in #1766
- Update invoke.bat.in isolate environment variables by @lynnewu in #1833
- Arch Linux Specific PatchMatch Instructions & fixing conda install on linux by
@SammCheese in #1848
- Make force free GPU memory work in img2img by @addianto in #1844
- New installer by @lstein
## v2.2.3 <small>(2 December 2022)</small>
!!! Note
This point release removes references to the binary installer from the
installation guide. The binary installer is not stable at the current
time. First time users are encouraged to use the "source" installer as
described in [Installing InvokeAI with the Source Installer](installation/deprecated_documentation/INSTALL_SOURCE.md)
With InvokeAI 2.2, this project now provides enthusiasts and professionals a
robust workflow solution for creating AI-generated and human facilitated
compositions. Additional enhancements have been made as well, improving safety,
ease of use, and installation.
Optimized for efficiency, InvokeAI needs only ~3.5GB of VRAM to generate a
512x768 image (and less for smaller images), and is compatible with
Windows/Linux/Mac (M1 & M2).
You can see the [release video](https://youtu.be/hIYBfDtKaus) here, which
introduces the main WebUI enhancement for version 2.2 -
[The Unified Canvas](features/UNIFIED_CANVAS.md). This new workflow is the
biggest enhancement added to the WebUI to date, and unlocks a stunning amount of
potential for users to create and iterate on their creations. The following
sections describe what's new for InvokeAI.
## v2.2.2 <small>(30 November 2022)</small>
!!! note
The binary installer is not ready for prime time. First time users are recommended to install via the "source" installer accessible through the links at the bottom of this page.****
With InvokeAI 2.2, this project now provides enthusiasts and professionals a
robust workflow solution for creating AI-generated and human facilitated
compositions. Additional enhancements have been made as well, improving safety,
ease of use, and installation.
Optimized for efficiency, InvokeAI needs only ~3.5GB of VRAM to generate a
512x768 image (and less for smaller images), and is compatible with
Windows/Linux/Mac (M1 & M2).
You can see the [release video](https://youtu.be/hIYBfDtKaus) here, which
introduces the main WebUI enhancement for version 2.2 -
[The Unified Canvas](https://invoke-ai.github.io/InvokeAI/features/UNIFIED_CANVAS/).
This new workflow is the biggest enhancement added to the WebUI to date, and
unlocks a stunning amount of potential for users to create and iterate on their
creations. The following sections describe what's new for InvokeAI.
## v2.2.0 <small>(2 December 2022)</small>
With InvokeAI 2.2, this project now provides enthusiasts and professionals a
robust workflow solution for creating AI-generated and human facilitated
compositions. Additional enhancements have been made as well, improving safety,
ease of use, and installation.
Optimized for efficiency, InvokeAI needs only ~3.5GB of VRAM to generate a
512x768 image (and less for smaller images), and is compatible with
Windows/Linux/Mac (M1 & M2).
You can see the [release video](https://youtu.be/hIYBfDtKaus) here, which
introduces the main WebUI enhancement for version 2.2 -
[The Unified Canvas](features/UNIFIED_CANVAS.md). This new workflow is the
biggest enhancement added to the WebUI to date, and unlocks a stunning amount of
potential for users to create and iterate on their creations. The following
sections describe what's new for InvokeAI.
## v2.1.3 <small>(13 November 2022)</small>
- A choice of installer scripts that automate installation and configuration.
See
[Installation](installation/index.md).
- A streamlined manual installation process that works for both Conda and
PIP-only installs. See
[Manual Installation](installation/020_INSTALL_MANUAL.md).
- The ability to save frequently-used startup options (model to load, steps,
sampler, etc) in a `.invokeai` file. See
[Client](features/CLI.md)
- Support for AMD GPU cards (non-CUDA) on Linux machines.
- Multiple bugs and edge cases squashed.
## v2.1.0 <small>(2 November 2022)</small>
- update mac instructions to use invokeai for env name by @willwillems in #1030
- Update .gitignore by @blessedcoolant in #1040
- reintroduce fix for m1 from #579 missing after merge by @skurovec in #1056
- Update Stable_Diffusion_AI_Notebook.ipynb (Take 2) by @ChloeL19 in #1060
- Print out the device type which is used by @manzke in #1073
- Hires Addition by @hipsterusername in #1063
- fix for "1 leaked semaphore objects to clean up at shutdown" on M1 by
@skurovec in #1081
- Forward dream.py to invoke.py using the same interpreter, add deprecation
warning by @db3000 in #1077
- fix noisy images at high step counts by @lstein in #1086
- Generalize facetool strength argument by @db3000 in #1078
- Enable fast switching among models at the invoke> command line by @lstein in
#1066
- Fix Typo, committed changing ldm environment to invokeai by @jdries3 in #1095
- Update generate.py by @unreleased in #1109
- Update 'ldm' env to 'invokeai' in troubleshooting steps by @19wolf in #1125
- Fixed documentation typos and resolved merge conflicts by @rupeshs in #1123
- Fix broken doc links, fix malaprop in the project subtitle by @majick in #1131
- Only output facetool parameters if enhancing faces by @db3000 in #1119
- Update gitignore to ignore codeformer weights at new location by
@spezialspezial in #1136
- fix links to point to invoke-ai.github.io #1117 by @mauwii in #1143
- Rework-mkdocs by @mauwii in #1144
- add option to CLI and pngwriter that allows user to set PNG compression level
by @lstein in #1127
- Fix img2img DDIM index out of bound by @wfng92 in #1137
- Fix gh actions by @mauwii in #1128
- update mac instructions to use invokeai for env name by @willwillems in #1030
- Update .gitignore by @blessedcoolant in #1040
- reintroduce fix for m1 from #579 missing after merge by @skurovec in #1056
- Update Stable_Diffusion_AI_Notebook.ipynb (Take 2) by @ChloeL19 in #1060
- Print out the device type which is used by @manzke in #1073
- Hires Addition by @hipsterusername in #1063
- fix for "1 leaked semaphore objects to clean up at shutdown" on M1 by
@skurovec in #1081
- Forward dream.py to invoke.py using the same interpreter, add deprecation
warning by @db3000 in #1077
- fix noisy images at high step counts by @lstein in #1086
- Generalize facetool strength argument by @db3000 in #1078
- Enable fast switching among models at the invoke> command line by @lstein in
#1066
- Fix Typo, committed changing ldm environment to invokeai by @jdries3 in #1095
- Fixed documentation typos and resolved merge conflicts by @rupeshs in #1123
- Only output facetool parameters if enhancing faces by @db3000 in #1119
- add option to CLI and pngwriter that allows user to set PNG compression level
by @lstein in #1127
- Fix img2img DDIM index out of bound by @wfng92 in #1137
- Add text prompt to inpaint mask support by @lstein in #1133
- Respect http[s] protocol when making socket.io middleware by @damian0815 in
#976
- WebUI: Adds Codeformer support by @psychedelicious in #1151
- Skips normalizing prompts for web UI metadata by @psychedelicious in #1165
- Add Asymmetric Tiling by @carson-katri in #1132
- Web UI: Increases max CFG Scale to 200 by @psychedelicious in #1172
- Corrects color channels in face restoration; Fixes #1167 by @psychedelicious
in #1175
- Flips channels using array slicing instead of using OpenCV by @psychedelicious
in #1178
- Fix typo in docs: s/Formally/Formerly by @noodlebox in #1176
- fix clipseg loading problems by @lstein in #1177
- Correct color channels in upscale using array slicing by @wfng92 in #1181
- Web UI: Filters existing images when adding new images; Fixes #1085 by
@psychedelicious in #1171
- fix a number of bugs in textual inversion by @lstein in #1190
- Improve !fetch, add !replay command by @ArDiouscuros in #882
- Fix generation of image with s>1000 by @holstvoogd in #951
- Web UI: Gallery improvements by @psychedelicious in #1198
- Update CLI.md by @krummrey in #1211
- outcropping improvements by @lstein in #1207
- add support for loading VAE autoencoders by @lstein in #1216
- remove duplicate fix_func for MPS by @wfng92 in #1210
- Metadata storage and retrieval fixes by @lstein in #1204
- nix: add shell.nix file by @Cloudef in #1170
- Web UI: Changes vite dist asset paths to relative by @psychedelicious in #1185
- Web UI: Removes isDisabled from PromptInput by @psychedelicious in #1187
- Allow user to generate images with initial noise as on M1 / mps system by
@ArDiouscuros in #981
- feat: adding filename format template by @plucked in #968
- Web UI: Fixes broken bundle by @psychedelicious in #1242
- Support runwayML custom inpainting model by @lstein in #1243
- Update IMG2IMG.md by @talitore in #1262
- New dockerfile - including a build- and a run- script as well as a GH-Action
by @mauwii in #1233
- cut over from karras to model noise schedule for higher steps by @lstein in
#1222
- Prompt tweaks by @lstein in #1268
- Outpainting implementation by @Kyle0654 in #1251
- fixing aspect ratio on hires by @tjennings in #1249
- Fix-build-container-action by @mauwii in #1274
- handle all unicode characters by @damian0815 in #1276
- adds models.user.yml to .gitignore by @JakeHL in #1281
- remove debug branch, set fail-fast to false by @mauwii in #1284
- Protect-secrets-on-pr by @mauwii in #1285
- Web UI: Adds initial inpainting implementation by @psychedelicious in #1225
- fix environment-mac.yml - tested on x64 and arm64 by @mauwii in #1289
- Use proper authentication to download model by @mauwii in #1287
- Prevent indexing error for mode RGB by @spezialspezial in #1294
- Integrate sd-v1-5 model into test matrix (easily expandable), remove
unecesarry caches by @mauwii in #1293
- add --no-interactive to configure_invokeai step by @mauwii in #1302
- 1-click installer and updater. Uses micromamba to install git and conda into a
contained environment (if necessary) before running the normal installation
script by @cmdr2 in #1253
- configure_invokeai.py script downloads the weight files by @lstein in #1290
## v2.0.1 <small>(13 October 2022)</small>
- fix noisy images at high step count when using k\* samplers
- dream.py script now calls invoke.py module directly rather than via a new
python process (which could break the environment)
- fix noisy images at high step count when using k* samplers
- dream.py script now calls invoke.py module directly rather than
via a new python process (which could break the environment)
## v2.0.0 <small>(9 October 2022)</small>
- `dream.py` script renamed `invoke.py`. A `dream.py` script wrapper remains for
backward compatibility.
- `dream.py` script renamed `invoke.py`. A `dream.py` script wrapper remains
for backward compatibility.
- Completely new WebGUI - launch with `python3 scripts/invoke.py --web`
- Support for [inpainting](features/INPAINTING.md) and
[outpainting](features/OUTPAINTING.md)
- img2img runs on all k\* samplers
- Support for
[negative prompts](features/PROMPTS.md#negative-and-unconditioned-prompts)
- Support for [inpainting](features/INPAINTING.md) and [outpainting](features/OUTPAINTING.md)
- img2img runs on all k* samplers
- Support for [negative prompts](features/PROMPTS.md#negative-and-unconditioned-prompts)
- Support for CodeFormer face reconstruction
- Support for Textual Inversion on Macintoshes
- Support in both WebGUI and CLI for
[post-processing of previously-generated images](features/POSTPROCESS.md)
using facial reconstruction, ESRGAN upscaling, outcropping (similar to DALL-E
infinite canvas), and "embiggen" upscaling. See the `!fix` command.
- New `--hires` option on `invoke>` line allows
[larger images to be created without duplicating elements](features/CLI.md#this-is-an-example-of-txt2img),
at the cost of some performance.
- New `--perlin` and `--threshold` options allow you to add and control
variation during image generation (see
[Thresholding and Perlin Noise Initialization](features/OTHER.md#thresholding-and-perlin-noise-initialization-options))
- Extensive metadata now written into PNG files, allowing reliable regeneration
of images and tweaking of previous settings.
- Command-line completion in `invoke.py` now works on Windows, Linux and Mac
platforms.
- Improved [command-line completion behavior](features/CLI.md) New commands
added:
- Support in both WebGUI and CLI for [post-processing of previously-generated images](features/POSTPROCESS.md)
using facial reconstruction, ESRGAN upscaling, outcropping (similar to DALL-E infinite canvas),
and "embiggen" upscaling. See the `!fix` command.
- New `--hires` option on `invoke>` line allows [larger images to be created without duplicating elements](features/CLI.md#this-is-an-example-of-txt2img), at the cost of some performance.
- New `--perlin` and `--threshold` options allow you to add and control variation
during image generation (see [Thresholding and Perlin Noise Initialization](features/OTHER.md#thresholding-and-perlin-noise-initialization-options))
- Extensive metadata now written into PNG files, allowing reliable regeneration of images
and tweaking of previous settings.
- Command-line completion in `invoke.py` now works on Windows, Linux and Mac platforms.
- Improved [command-line completion behavior](features/CLI.md)
New commands added:
- List command-line history with `!history`
- Search command-line history with `!search`
- Clear history with `!clear`
- Deprecated `--full_precision` / `-F`. Simply omit it and `invoke.py` will auto
configure. To switch away from auto use the new flag like
`--precision=float32`.
configure. To switch away from auto use the new flag like `--precision=float32`.
## v1.14 <small>(11 September 2022)</small>
- Memory optimizations for small-RAM cards. 512x512 now possible on 4 GB GPUs.
- Full support for Apple hardware with M1 or M2 chips.
- Add "seamless mode" for circular tiling of image. Generates beautiful effects.
([prixt](https://github.com/prixt)).
([prixt](https://github.com/prixt)).
- Inpainting support.
- Improved web server GUI.
- Lots of code and documentation cleanups.
@ -430,17 +138,16 @@ sections describe what's new for InvokeAI.
## v1.13 <small>(3 September 2022)</small>
- Support image variations (see [VARIATIONS](features/VARIATIONS.md)
([Kevin Gibbons](https://github.com/bakkot) and many contributors and
reviewers)
- Supports a Google Colab notebook for a standalone server running on Google
hardware [Arturo Mendivil](https://github.com/artmen1516)
([Kevin Gibbons](https://github.com/bakkot) and many contributors and reviewers)
- Supports a Google Colab notebook for a standalone server running on Google hardware
[Arturo Mendivil](https://github.com/artmen1516)
- WebUI supports GFPGAN/ESRGAN facial reconstruction and upscaling
[Kevin Gibbons](https://github.com/bakkot)
[Kevin Gibbons](https://github.com/bakkot)
- WebUI supports incremental display of in-progress images during generation
[Kevin Gibbons](https://github.com/bakkot)
[Kevin Gibbons](https://github.com/bakkot)
- A new configuration file scheme that allows new models (including upcoming
stable-diffusion-v1.5) to be added without altering the code.
([David Wager](https://github.com/maddavid12))
stable-diffusion-v1.5) to be added without altering the code.
([David Wager](https://github.com/maddavid12))
- Can specify --grid on invoke.py command line as the default.
- Miscellaneous internal bug and stability fixes.
- Works on M1 Apple hardware.
@ -452,59 +159,49 @@ sections describe what's new for InvokeAI.
- Improved file handling, including ability to read prompts from standard input.
(kudos to [Yunsaki](https://github.com/yunsaki)
- The web server is now integrated with the invoke.py script. Invoke by adding
--web to the invoke.py command arguments.
- The web server is now integrated with the invoke.py script. Invoke by adding --web to
the invoke.py command arguments.
- Face restoration and upscaling via GFPGAN and Real-ESGAN are now automatically
enabled if the GFPGAN directory is located as a sibling to Stable Diffusion.
VRAM requirements are modestly reduced. Thanks to both
[Blessedcoolant](https://github.com/blessedcoolant) and
VRAM requirements are modestly reduced. Thanks to both [Blessedcoolant](https://github.com/blessedcoolant) and
[Oceanswave](https://github.com/oceanswave) for their work on this.
- You can now swap samplers on the invoke> command line.
[Blessedcoolant](https://github.com/blessedcoolant)
- You can now swap samplers on the invoke> command line. [Blessedcoolant](https://github.com/blessedcoolant)
---
## v1.11 <small>(26 August 2022)</small>
- NEW FEATURE: Support upscaling and face enhancement using the GFPGAN module.
(kudos to [Oceanswave](https://github.com/Oceanswave)
- You now can specify a seed of -1 to use the previous image's seed, -2 to use
the seed for the image generated before that, etc. Seed memory only extends
back to the previous command, but will work on all images generated with the
-n# switch.
- NEW FEATURE: Support upscaling and face enhancement using the GFPGAN module. (kudos to [Oceanswave](https://github.com/Oceanswave)
- You now can specify a seed of -1 to use the previous image's seed, -2 to use the seed for the image generated before that, etc.
Seed memory only extends back to the previous command, but will work on all images generated with the -n# switch.
- Variant generation support temporarily disabled pending more general solution.
- Created a feature branch named **yunsaki-morphing-invoke** which adds
experimental support for iteratively modifying the prompt and its parameters.
Please
see[Pull Request #86](https://github.com/lstein/stable-diffusion/pull/86) for
a synopsis of how this works. Note that when this feature is eventually added
to the main branch, it will may be modified significantly.
- Created a feature branch named **yunsaki-morphing-invoke** which adds experimental support for
iteratively modifying the prompt and its parameters. Please see[Pull Request #86](https://github.com/lstein/stable-diffusion/pull/86)
for a synopsis of how this works. Note that when this feature is eventually added to the main branch, it will may be modified
significantly.
---
## v1.10 <small>(25 August 2022)</small>
- A barebones but fully functional interactive web server for online generation
of txt2img and img2img.
- A barebones but fully functional interactive web server for online generation of txt2img and img2img.
---
## v1.09 <small>(24 August 2022)</small>
- A new -v option allows you to generate multiple variants of an initial image
in img2img mode. (kudos to [Oceanswave](https://github.com/Oceanswave).
[ See this discussion in the PR for examples and details on use](https://github.com/lstein/stable-diffusion/pull/71#issuecomment-1226700810))
- Added ability to personalize text to image generation (kudos to
[Oceanswave](https://github.com/Oceanswave) and
[nicolai256](https://github.com/nicolai256))
in img2img mode. (kudos to [Oceanswave](https://github.com/Oceanswave). [
See this discussion in the PR for examples and details on use](https://github.com/lstein/stable-diffusion/pull/71#issuecomment-1226700810))
- Added ability to personalize text to image generation (kudos to [Oceanswave](https://github.com/Oceanswave) and [nicolai256](https://github.com/nicolai256))
- Enabled all of the samplers from k_diffusion
---
## v1.08 <small>(24 August 2022)</small>
- Escape single quotes on the invoke> command before trying to parse. This
avoids parse errors.
- Escape single quotes on the invoke> command before trying to parse. This avoids
parse errors.
- Removed instruction to get Python3.8 as first step in Windows install.
Anaconda3 does it for you.
- Added bounds checks for numeric arguments that could cause crashes.
@ -514,36 +211,34 @@ sections describe what's new for InvokeAI.
## v1.07 <small>(23 August 2022)</small>
- Image filenames will now never fill gaps in the sequence, but will be assigned
the next higher name in the chosen directory. This ensures that the alphabetic
and chronological sort orders are the same.
- Image filenames will now never fill gaps in the sequence, but will be assigned the
next higher name in the chosen directory. This ensures that the alphabetic and chronological
sort orders are the same.
---
## v1.06 <small>(23 August 2022)</small>
- Added weighted prompt support contributed by
[xraxra](https://github.com/xraxra)
- Example of using weighted prompts to tweak a demonic figure contributed by
[bmaltais](https://github.com/bmaltais)
- Added weighted prompt support contributed by [xraxra](https://github.com/xraxra)
- Example of using weighted prompts to tweak a demonic figure contributed by [bmaltais](https://github.com/bmaltais)
---
## v1.05 <small>(22 August 2022 - after the drop)</small>
- Filenames now use the following formats: 000010.95183149.png -- Two files
produced by the same command (e.g. -n2), 000010.26742632.png -- distinguished
by a different seed.
- Filenames now use the following formats:
000010.95183149.png -- Two files produced by the same command (e.g. -n2),
000010.26742632.png -- distinguished by a different seed.
000011.455191342.01.png -- Two files produced by the same command using
000011.455191342.02.png -- a batch size>1 (e.g. -b2). They have the same seed.
000011.4160627868.grid#1-4.png -- a grid of four images (-g); the whole grid
can be regenerated with the indicated key
000011.4160627868.grid#1-4.png -- a grid of four images (-g); the whole grid can
be regenerated with the indicated key
- It should no longer be possible for one image to overwrite another
- You can use the "cd" and "pwd" commands at the invoke> prompt to set and
retrieve the path of the output directory.
- You can use the "cd" and "pwd" commands at the invoke> prompt to set and retrieve
the path of the output directory.
---
@ -557,28 +252,26 @@ sections describe what's new for InvokeAI.
## v1.03 <small>(22 August 2022)</small>
- The original txt2img and img2img scripts from the CompViz repository have been
moved into a subfolder named "orig_scripts", to reduce confusion.
- The original txt2img and img2img scripts from the CompViz repository have been moved into
a subfolder named "orig_scripts", to reduce confusion.
---
## v1.02 <small>(21 August 2022)</small>
- A copy of the prompt and all of its switches and options is now stored in the
corresponding image in a tEXt metadata field named "Dream". You can read the
prompt using scripts/images2prompt.py, or an image editor that allows you to
explore the full metadata. **Please run "conda env update" to load the k_lms
dependencies!!**
- A copy of the prompt and all of its switches and options is now stored in the corresponding
image in a tEXt metadata field named "Dream". You can read the prompt using scripts/images2prompt.py,
or an image editor that allows you to explore the full metadata.
**Please run "conda env update" to load the k_lms dependencies!!**
---
## v1.01 <small>(21 August 2022)</small>
- added k_lms sampling. **Please run "conda env update" to load the k_lms
dependencies!!**
- use half precision arithmetic by default, resulting in faster execution and
lower memory requirements Pass argument --full_precision to invoke.py to get
slower but more accurate image generation
- added k_lms sampling.
**Please run "conda env update" to load the k_lms dependencies!!**
- use half precision arithmetic by default, resulting in faster execution and lower memory requirements
Pass argument --full_precision to invoke.py to get slower but more accurate image generation
---

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