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2548 Commits
2.0.0-rc8
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invokeai-b
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8e76bc2b5d | |||
93b1298d46 | |||
1af86618e3 | |||
b732bcad2f |
6
.coveragerc
Normal file
@ -0,0 +1,6 @@
|
||||
[run]
|
||||
omit='.env/*'
|
||||
source='.'
|
||||
|
||||
[report]
|
||||
show_missing = true
|
25
.dockerignore
Normal file
@ -0,0 +1,25 @@
|
||||
# use this file as a whitelist
|
||||
*
|
||||
!invokeai
|
||||
!ldm
|
||||
!pyproject.toml
|
||||
|
||||
# Guard against pulling in any models that might exist in the directory tree
|
||||
**/*.pt*
|
||||
**/*.ckpt
|
||||
|
||||
# ignore frontend but whitelist dist
|
||||
invokeai/frontend/
|
||||
!invokeai/frontend/dist/
|
||||
|
||||
# ignore invokeai/assets but whitelist invokeai/assets/web
|
||||
invokeai/assets/
|
||||
!invokeai/assets/web/
|
||||
|
||||
# Byte-compiled / optimized / DLL files
|
||||
**/__pycache__/
|
||||
**/*.py[cod]
|
||||
|
||||
# Distribution / packaging
|
||||
*.egg-info/
|
||||
*.egg
|
30
.editorconfig
Normal file
@ -0,0 +1,30 @@
|
||||
root = true
|
||||
|
||||
# All files
|
||||
[*]
|
||||
max_line_length = 80
|
||||
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
|
||||
max_line_length = 120
|
||||
|
||||
# css
|
||||
[*.css]
|
||||
indent_size = 4
|
||||
|
||||
# flake8
|
||||
[.flake8]
|
||||
indent_size = 4
|
||||
|
||||
# Markdown MkDocs
|
||||
[docs/**/*.md]
|
||||
max_line_length = 80
|
||||
indent_size = 4
|
||||
indent_style = unset
|
37
.flake8
Normal file
@ -0,0 +1,37 @@
|
||||
[flake8]
|
||||
max-line-length = 120
|
||||
extend-ignore =
|
||||
# See https://github.com/PyCQA/pycodestyle/issues/373
|
||||
E203,
|
||||
# use Bugbear's B950 instead
|
||||
E501,
|
||||
# from black repo https://github.com/psf/black/blob/main/.flake8
|
||||
E266, W503, B907
|
||||
extend-select =
|
||||
# Bugbear line length
|
||||
B950
|
||||
extend-exclude =
|
||||
scripts/orig_scripts/*
|
||||
ldm/models/*
|
||||
ldm/modules/*
|
||||
ldm/data/*
|
||||
ldm/generate.py
|
||||
ldm/util.py
|
||||
ldm/simplet2i.py
|
||||
per-file-ignores =
|
||||
# B950 line too long
|
||||
# W605 invalid escape sequence
|
||||
# F841 assigned to but never used
|
||||
# F401 imported but unused
|
||||
tests/test_prompt_parser.py: B950, W605, F401
|
||||
tests/test_textual_inversion.py: F841, B950
|
||||
# B023 Function definition does not bind loop variable
|
||||
scripts/legacy_api.py: F401, B950, B023, F841
|
||||
ldm/invoke/__init__.py: F401
|
||||
# B010 Do not call setattr with a constant attribute value
|
||||
ldm/invoke/server_legacy.py: B010
|
||||
# =====================
|
||||
# flake-quote settings:
|
||||
# =====================
|
||||
# Set this to match black style:
|
||||
inline-quotes = double
|
2
.gitattributes
vendored
@ -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
|
||||
|
61
.github/CODEOWNERS
vendored
Normal file
@ -0,0 +1,61 @@
|
||||
# continuous integration
|
||||
/.github/workflows/ @mauwii @lstein @blessedcoolant
|
||||
|
||||
# documentation
|
||||
/docs/ @lstein @mauwii @blessedcoolant
|
||||
mkdocs.yml @mauwii @lstein
|
||||
|
||||
# installation and configuration
|
||||
/pyproject.toml @mauwii @lstein @ebr
|
||||
/docker/ @mauwii
|
||||
/scripts/ @ebr @lstein @blessedcoolant
|
||||
/installer/ @ebr @lstein
|
||||
ldm/invoke/config @lstein @ebr
|
||||
invokeai/assets @lstein @blessedcoolant
|
||||
invokeai/configs @lstein @ebr @blessedcoolant
|
||||
/ldm/invoke/_version.py @lstein @blessedcoolant
|
||||
|
||||
# web ui
|
||||
/invokeai/frontend @blessedcoolant @psychedelicious
|
||||
/invokeai/backend @blessedcoolant @psychedelicious
|
||||
|
||||
# generation and model management
|
||||
/ldm/*.py @lstein @blessedcoolant
|
||||
/ldm/generate.py @lstein @keturn
|
||||
/ldm/invoke/args.py @lstein @blessedcoolant
|
||||
/ldm/invoke/ckpt* @lstein @blessedcoolant
|
||||
/ldm/invoke/ckpt_generator @lstein @blessedcoolant
|
||||
/ldm/invoke/CLI.py @lstein @blessedcoolant
|
||||
/ldm/invoke/config @lstein @ebr @mauwii @blessedcoolant
|
||||
/ldm/invoke/generator @keturn @damian0815
|
||||
/ldm/invoke/globals.py @lstein @blessedcoolant
|
||||
/ldm/invoke/merge_diffusers.py @lstein @blessedcoolant
|
||||
/ldm/invoke/model_manager.py @lstein @blessedcoolant
|
||||
/ldm/invoke/txt2mask.py @lstein @blessedcoolant
|
||||
/ldm/invoke/patchmatch.py @Kyle0654 @lstein
|
||||
/ldm/invoke/restoration @lstein @blessedcoolant
|
||||
|
||||
# attention, textual inversion, model configuration
|
||||
/ldm/models @damian0815 @keturn @blessedcoolant
|
||||
/ldm/modules/textual_inversion_manager.py @lstein @blessedcoolant
|
||||
/ldm/modules/attention.py @damian0815 @keturn
|
||||
/ldm/modules/diffusionmodules @damian0815 @keturn
|
||||
/ldm/modules/distributions @damian0815 @keturn
|
||||
/ldm/modules/ema.py @damian0815 @keturn
|
||||
/ldm/modules/embedding_manager.py @lstein
|
||||
/ldm/modules/encoders @damian0815 @keturn
|
||||
/ldm/modules/image_degradation @damian0815 @keturn
|
||||
/ldm/modules/losses @damian0815 @keturn
|
||||
/ldm/modules/x_transformer.py @damian0815 @keturn
|
||||
|
||||
# Nodes
|
||||
apps/ @Kyle0654 @jpphoto
|
||||
|
||||
# legacy REST API
|
||||
# these are dead code
|
||||
#/ldm/invoke/pngwriter.py @CapableWeb
|
||||
#/ldm/invoke/server_legacy.py @CapableWeb
|
||||
#/scripts/legacy_api.py @CapableWeb
|
||||
#/tests/legacy_tests.sh @CapableWeb
|
||||
|
||||
|
102
.github/ISSUE_TEMPLATE/BUG_REPORT.yml
vendored
Normal file
@ -0,0 +1,102 @@
|
||||
name: 🐞 Bug Report
|
||||
|
||||
description: File a bug report
|
||||
|
||||
title: '[bug]: '
|
||||
|
||||
labels: ['bug']
|
||||
|
||||
# assignees:
|
||||
# - moderator_bot
|
||||
# - lstein
|
||||
|
||||
body:
|
||||
- type: markdown
|
||||
attributes:
|
||||
value: |
|
||||
Thanks for taking the time to fill out this Bug Report!
|
||||
|
||||
- type: checkboxes
|
||||
attributes:
|
||||
label: Is there an existing issue for this?
|
||||
description: |
|
||||
Please use the [search function](https://github.com/invoke-ai/InvokeAI/issues?q=is%3Aissue+is%3Aopen+label%3Abug)
|
||||
irst to see if an issue already exists for the bug you encountered.
|
||||
options:
|
||||
- label: I have searched the existing issues
|
||||
required: true
|
||||
|
||||
- type: markdown
|
||||
attributes:
|
||||
value: __Describe your environment__
|
||||
|
||||
- type: dropdown
|
||||
id: os_dropdown
|
||||
attributes:
|
||||
label: OS
|
||||
description: Which operating System did you use when the bug occured
|
||||
multiple: false
|
||||
options:
|
||||
- 'Linux'
|
||||
- 'Windows'
|
||||
- 'macOS'
|
||||
validations:
|
||||
required: true
|
||||
|
||||
- type: dropdown
|
||||
id: gpu_dropdown
|
||||
attributes:
|
||||
label: GPU
|
||||
description: Which kind of Graphic-Adapter is your System using
|
||||
multiple: false
|
||||
options:
|
||||
- 'cuda'
|
||||
- 'amd'
|
||||
- 'mps'
|
||||
- 'cpu'
|
||||
validations:
|
||||
required: true
|
||||
|
||||
- type: input
|
||||
id: vram
|
||||
attributes:
|
||||
label: VRAM
|
||||
description: Size of the VRAM if known
|
||||
placeholder: 8GB
|
||||
validations:
|
||||
required: false
|
||||
|
||||
- type: textarea
|
||||
id: what-happened
|
||||
attributes:
|
||||
label: What happened?
|
||||
description: |
|
||||
Briefly describe what happened, what you expected to happen and how to reproduce this bug.
|
||||
placeholder: When using the webinterface and right-clicking on button X instead of the popup-menu there error Y appears
|
||||
validations:
|
||||
required: true
|
||||
|
||||
- type: textarea
|
||||
attributes:
|
||||
label: Screenshots
|
||||
description: If applicable, add screenshots to help explain your problem
|
||||
placeholder: this is what the result looked like <screenshot>
|
||||
validations:
|
||||
required: false
|
||||
|
||||
- type: textarea
|
||||
attributes:
|
||||
label: Additional context
|
||||
description: Add any other context about the problem here
|
||||
placeholder: Only happens when there is full moon and Friday the 13th on Christmas Eve 🎅🏻
|
||||
validations:
|
||||
required: false
|
||||
|
||||
- type: input
|
||||
id: contact
|
||||
attributes:
|
||||
label: Contact Details
|
||||
description: __OPTIONAL__ How can we get in touch with you if we need more info (besides this issue)?
|
||||
placeholder: ex. email@example.com, discordname, twitter, ...
|
||||
validations:
|
||||
required: false
|
56
.github/ISSUE_TEMPLATE/FEATURE_REQUEST.yml
vendored
Normal file
@ -0,0 +1,56 @@
|
||||
name: Feature Request
|
||||
description: Commit a idea or Request a new feature
|
||||
title: '[enhancement]: '
|
||||
labels: ['enhancement']
|
||||
# assignees:
|
||||
# - lstein
|
||||
# - tildebyte
|
||||
body:
|
||||
- type: markdown
|
||||
attributes:
|
||||
value: |
|
||||
Thanks for taking the time to fill out this Feature request!
|
||||
|
||||
- type: checkboxes
|
||||
attributes:
|
||||
label: Is there an existing issue for this?
|
||||
description: |
|
||||
Please make use of the [search function](https://github.com/invoke-ai/InvokeAI/labels/enhancement)
|
||||
to see if a simmilar issue already exists for the feature you want to request
|
||||
options:
|
||||
- label: I have searched the existing issues
|
||||
required: true
|
||||
|
||||
- type: input
|
||||
id: contact
|
||||
attributes:
|
||||
label: Contact Details
|
||||
description: __OPTIONAL__ How could we get in touch with you if we need more info (besides this issue)?
|
||||
placeholder: ex. email@example.com, discordname, twitter, ...
|
||||
validations:
|
||||
required: false
|
||||
|
||||
- type: textarea
|
||||
id: whatisexpected
|
||||
attributes:
|
||||
label: What should this feature add?
|
||||
description: Please try to explain the functionality this feature should add
|
||||
placeholder: |
|
||||
Instead of one huge textfield, it would be nice to have forms for bug-reports, feature-requests, ...
|
||||
Great benefits with automatic labeling, assigning and other functionalitys not available in that form
|
||||
via old-fashioned markdown-templates. I would also love to see the use of a moderator bot 🤖 like
|
||||
https://github.com/marketplace/actions/issue-moderator-with-commands to auto close old issues and other things
|
||||
validations:
|
||||
required: true
|
||||
|
||||
- type: textarea
|
||||
attributes:
|
||||
label: Alternatives
|
||||
description: Describe alternatives you've considered
|
||||
placeholder: A clear and concise description of any alternative solutions or features you've considered.
|
||||
|
||||
- type: textarea
|
||||
attributes:
|
||||
label: Aditional Content
|
||||
description: Add any other context or screenshots about the feature request here.
|
||||
placeholder: This is a Mockup of the design how I imagine it <screenshot>
|
36
.github/ISSUE_TEMPLATE/bug_report.md
vendored
@ -1,36 +0,0 @@
|
||||
---
|
||||
name: Bug report
|
||||
about: Create a report to help us improve
|
||||
title: ''
|
||||
labels: ''
|
||||
assignees: ''
|
||||
|
||||
---
|
||||
|
||||
**Describe your environment**
|
||||
- GPU: [cuda/amd/mps/cpu]
|
||||
- VRAM: [if known]
|
||||
- CPU arch: [x86/arm]
|
||||
- OS: [Linux/Windows/macOS]
|
||||
- Python: [Anaconda/miniconda/miniforge/pyenv/other (explain)]
|
||||
- Branch: [if `git status` says anything other than "On branch main" paste it here]
|
||||
- Commit: [run `git show` and paste the line that starts with "Merge" here]
|
||||
|
||||
**Describe the bug**
|
||||
A clear and concise description of what the bug is.
|
||||
|
||||
**To Reproduce**
|
||||
Steps to reproduce the behavior:
|
||||
1. Go to '...'
|
||||
2. Click on '....'
|
||||
3. Scroll down to '....'
|
||||
4. See error
|
||||
|
||||
**Expected behavior**
|
||||
A clear and concise description of what you expected to happen.
|
||||
|
||||
**Screenshots**
|
||||
If applicable, add screenshots to help explain your problem.
|
||||
|
||||
**Additional context**
|
||||
Add any other context about the problem here.
|
14
.github/ISSUE_TEMPLATE/config.yml
vendored
Normal file
@ -0,0 +1,14 @@
|
||||
blank_issues_enabled: false
|
||||
contact_links:
|
||||
- name: Project-Documentation
|
||||
url: https://invoke-ai.github.io/InvokeAI/
|
||||
about: Should be your first place to go when looking for manuals/FAQs regarding our InvokeAI Toolkit
|
||||
- name: Discord
|
||||
url: https://discord.gg/ZmtBAhwWhy
|
||||
about: Our Discord Community could maybe help you out via live-chat
|
||||
- name: GitHub Community Support
|
||||
url: https://github.com/orgs/community/discussions
|
||||
about: Please ask and answer questions regarding the GitHub Platform here.
|
||||
- name: GitHub Security Bug Bounty
|
||||
url: https://bounty.github.com/
|
||||
about: Please report security vulnerabilities of the GitHub Platform here.
|
20
.github/ISSUE_TEMPLATE/feature_request.md
vendored
@ -1,20 +0,0 @@
|
||||
---
|
||||
name: Feature request
|
||||
about: Suggest an idea for this project
|
||||
title: ''
|
||||
labels: ''
|
||||
assignees: ''
|
||||
|
||||
---
|
||||
|
||||
**Is your feature request related to a problem? Please describe.**
|
||||
A clear and concise description of what the problem is. Ex. I'm always frustrated when [...]
|
||||
|
||||
**Describe the solution you'd like**
|
||||
A clear and concise description of what you want to happen.
|
||||
|
||||
**Describe alternatives you've considered**
|
||||
A clear and concise description of any alternative solutions or features you've considered.
|
||||
|
||||
**Additional context**
|
||||
Add any other context or screenshots about the feature request here.
|
111
.github/workflows/build-container.yml
vendored
Normal file
@ -0,0 +1,111 @@
|
||||
name: build container image
|
||||
on:
|
||||
push:
|
||||
branches:
|
||||
- 'main'
|
||||
- 'update/ci/docker/*'
|
||||
- 'update/docker/*'
|
||||
paths:
|
||||
- 'pyproject.toml'
|
||||
- 'ldm/**'
|
||||
- 'invokeai/backend/**'
|
||||
- 'invokeai/configs/**'
|
||||
- 'invokeai/frontend/dist/**'
|
||||
- 'docker/Dockerfile'
|
||||
tags:
|
||||
- 'v*.*.*'
|
||||
workflow_dispatch:
|
||||
|
||||
|
||||
jobs:
|
||||
docker:
|
||||
if: github.event.pull_request.draft == false
|
||||
strategy:
|
||||
fail-fast: false
|
||||
matrix:
|
||||
flavor:
|
||||
- amd
|
||||
- cuda
|
||||
- cpu
|
||||
include:
|
||||
- flavor: amd
|
||||
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: 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 }}
|
||||
${{ vars.DOCKERHUB_REPOSITORY }}
|
||||
tags: |
|
||||
type=ref,event=branch
|
||||
type=ref,event=tag
|
||||
type=semver,pattern={{version}}
|
||||
type=semver,pattern={{major}}.{{minor}}
|
||||
type=semver,pattern={{major}}
|
||||
type=sha,enable=true,prefix=sha-,format=short
|
||||
flavor: |
|
||||
latest=${{ 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
|
||||
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 }}
|
||||
|
||||
- name: Build container
|
||||
id: docker_build
|
||||
uses: docker/build-push-action@v4
|
||||
with:
|
||||
context: .
|
||||
file: ${{ env.DOCKERFILE }}
|
||||
platforms: ${{ env.PLATFORMS }}
|
||||
push: ${{ github.ref == 'refs/heads/main' || github.ref == 'refs/tags/*' }}
|
||||
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: ${{ github.event.repository.description }}
|
34
.github/workflows/clean-caches.yml
vendored
Normal file
@ -0,0 +1,34 @@
|
||||
name: cleanup caches by a branch
|
||||
on:
|
||||
pull_request:
|
||||
types:
|
||||
- closed
|
||||
workflow_dispatch:
|
||||
|
||||
jobs:
|
||||
cleanup:
|
||||
runs-on: ubuntu-latest
|
||||
steps:
|
||||
- name: Check out code
|
||||
uses: actions/checkout@v3
|
||||
|
||||
- name: Cleanup
|
||||
run: |
|
||||
gh extension install actions/gh-actions-cache
|
||||
|
||||
REPO=${{ 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 }}
|
70
.github/workflows/create-caches.yml
vendored
@ -1,70 +0,0 @@
|
||||
name: Create Caches
|
||||
on:
|
||||
workflow_dispatch
|
||||
jobs:
|
||||
build:
|
||||
strategy:
|
||||
matrix:
|
||||
os: [ ubuntu-latest, macos-12 ]
|
||||
name: Create Caches on ${{ matrix.os }} conda
|
||||
runs-on: ${{ matrix.os }}
|
||||
steps:
|
||||
- name: Set platform variables
|
||||
id: vars
|
||||
run: |
|
||||
if [ "$RUNNER_OS" = "macOS" ]; then
|
||||
echo "::set-output name=ENV_FILE::environment-mac.yml"
|
||||
echo "::set-output name=PYTHON_BIN::/usr/local/miniconda/envs/ldm/bin/python"
|
||||
elif [ "$RUNNER_OS" = "Linux" ]; then
|
||||
echo "::set-output name=ENV_FILE::environment.yml"
|
||||
echo "::set-output name=PYTHON_BIN::/usr/share/miniconda/envs/ldm/bin/python"
|
||||
fi
|
||||
- name: Checkout sources
|
||||
uses: actions/checkout@v3
|
||||
- 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: |
|
||||
if [ ! -e models/ldm/stable-diffusion-v1 ]; then
|
||||
mkdir -p models/ldm/stable-diffusion-v1
|
||||
fi
|
||||
if [ ! -e models/ldm/stable-diffusion-v1/model.ckpt ]; then
|
||||
curl -o models/ldm/stable-diffusion-v1/model.ckpt ${{ secrets.SD_V1_4_URL }}
|
||||
fi
|
||||
- name: Use Cached Dependencies
|
||||
id: cache-conda-env-ldm
|
||||
uses: actions/cache@v3
|
||||
env:
|
||||
cache-name: cache-conda-env-ldm
|
||||
with:
|
||||
path: ~/.conda/envs/ldm
|
||||
key: ${{ env.cache-name }}
|
||||
restore-keys: |
|
||||
${{ env.cache-name }}-${{ runner.os }}-${{ hashFiles(steps.vars.outputs.ENV_FILE) }}
|
||||
- name: Install Dependencies
|
||||
if: ${{ steps.cache-conda-env-ldm.outputs.cache-hit != 'true' }}
|
||||
run: |
|
||||
conda env create -f ${{ steps.vars.outputs.ENV_FILE }}
|
||||
- name: Use Cached Huggingface and Torch models
|
||||
id: cache-huggingface-torch
|
||||
uses: actions/cache@v3
|
||||
env:
|
||||
cache-name: cache-huggingface-torch
|
||||
with:
|
||||
path: ~/.cache
|
||||
key: ${{ env.cache-name }}
|
||||
restore-keys: |
|
||||
${{ env.cache-name }}-${{ hashFiles('scripts/preload_models.py') }}
|
||||
- name: Download Huggingface and Torch models
|
||||
if: ${{ steps.cache-huggingface-torch.outputs.cache-hit != 'true' }}
|
||||
run: |
|
||||
${{ steps.vars.outputs.PYTHON_BIN }} scripts/preload_models.py
|
29
.github/workflows/lint-frontend.yml
vendored
Normal file
@ -0,0 +1,29 @@
|
||||
name: Lint frontend
|
||||
|
||||
on:
|
||||
pull_request:
|
||||
paths:
|
||||
- 'invokeai/frontend/**'
|
||||
push:
|
||||
paths:
|
||||
- 'invokeai/frontend/**'
|
||||
|
||||
defaults:
|
||||
run:
|
||||
working-directory: invokeai/frontend
|
||||
|
||||
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 tsc'
|
||||
- run: 'yarn run madge'
|
||||
- run: 'yarn run lint --max-warnings=0'
|
||||
- run: 'yarn run prettier --check'
|
28
.github/workflows/mkdocs-flow.yml
vendored
@ -1,28 +0,0 @@
|
||||
name: Deploy
|
||||
on:
|
||||
push:
|
||||
branches:
|
||||
- main
|
||||
pull_request:
|
||||
branches:
|
||||
- main
|
||||
jobs:
|
||||
build:
|
||||
name: Deploy docs to GitHub Pages
|
||||
runs-on: ubuntu-latest
|
||||
steps:
|
||||
- name: Checkout
|
||||
uses: actions/checkout@v3
|
||||
with:
|
||||
fetch-depth: 0
|
||||
- name: Build
|
||||
uses: Tiryoh/actions-mkdocs@v0
|
||||
with:
|
||||
mkdocs_version: 'latest' # option
|
||||
requirements: '/requirements-mkdocs.txt' # option
|
||||
configfile: '/mkdocs.yml' # option
|
||||
- name: Deploy
|
||||
uses: peaceiris/actions-gh-pages@v3
|
||||
with:
|
||||
github_token: ${{ secrets.GITHUB_TOKEN }}
|
||||
publish_dir: ./site
|
49
.github/workflows/mkdocs-material.yml
vendored
Normal file
@ -0,0 +1,49 @@
|
||||
name: mkdocs-material
|
||||
on:
|
||||
push:
|
||||
branches:
|
||||
- 'main'
|
||||
- 'development'
|
||||
|
||||
jobs:
|
||||
mkdocs-material:
|
||||
if: github.event.pull_request.draft == false
|
||||
runs-on: ubuntu-latest
|
||||
env:
|
||||
REPO_URL: '${{ 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
|
||||
with:
|
||||
fetch-depth: 0
|
||||
|
||||
- name: setup python
|
||||
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]"
|
||||
|
||||
- name: confirm buildability
|
||||
run: |
|
||||
python -m \
|
||||
mkdocs build \
|
||||
--clean \
|
||||
--verbose
|
||||
|
||||
- name: deploy to gh-pages
|
||||
if: ${{ github.ref == 'refs/heads/main' }}
|
||||
run: |
|
||||
python -m \
|
||||
mkdocs gh-deploy \
|
||||
--clean \
|
||||
--force
|
20
.github/workflows/pyflakes.yml
vendored
Normal file
@ -0,0 +1,20 @@
|
||||
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
|
41
.github/workflows/pypi-release.yml
vendored
Normal file
@ -0,0 +1,41 @@
|
||||
name: PyPI Release
|
||||
|
||||
on:
|
||||
push:
|
||||
paths:
|
||||
- 'ldm/invoke/_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/*
|
97
.github/workflows/test-invoke-conda.yml
vendored
@ -1,97 +0,0 @@
|
||||
name: Test Invoke with Conda
|
||||
on:
|
||||
push:
|
||||
branches:
|
||||
- 'main'
|
||||
- 'development'
|
||||
jobs:
|
||||
os_matrix:
|
||||
strategy:
|
||||
matrix:
|
||||
os: [ ubuntu-latest, macos-12 ]
|
||||
name: Test invoke.py on ${{ matrix.os }} with conda
|
||||
runs-on: ${{ matrix.os }}
|
||||
steps:
|
||||
- run: |
|
||||
echo The PR was merged
|
||||
- name: Set platform variables
|
||||
id: vars
|
||||
run: |
|
||||
# Note, can't "activate" via github action; specifying the env's python has the same effect
|
||||
if [ "$RUNNER_OS" = "macOS" ]; then
|
||||
echo "::set-output name=ENV_FILE::environment-mac.yml"
|
||||
echo "::set-output name=PYTHON_BIN::/usr/local/miniconda/envs/ldm/bin/python"
|
||||
elif [ "$RUNNER_OS" = "Linux" ]; then
|
||||
echo "::set-output name=ENV_FILE::environment.yml"
|
||||
echo "::set-output name=PYTHON_BIN::/usr/share/miniconda/envs/ldm/bin/python"
|
||||
fi
|
||||
- name: Checkout sources
|
||||
uses: actions/checkout@v3
|
||||
- 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: |
|
||||
if [ ! -e models/ldm/stable-diffusion-v1 ]; then
|
||||
mkdir -p models/ldm/stable-diffusion-v1
|
||||
fi
|
||||
if [ ! -e models/ldm/stable-diffusion-v1/model.ckpt ]; then
|
||||
curl -o models/ldm/stable-diffusion-v1/model.ckpt ${{ secrets.SD_V1_4_URL }}
|
||||
fi
|
||||
- name: Use Cached Dependencies
|
||||
id: cache-conda-env-ldm
|
||||
uses: actions/cache@v3
|
||||
env:
|
||||
cache-name: cache-conda-env-ldm
|
||||
with:
|
||||
path: ~/.conda/envs/ldm
|
||||
key: ${{ env.cache-name }}
|
||||
restore-keys: |
|
||||
${{ env.cache-name }}-${{ runner.os }}-${{ hashFiles(steps.vars.outputs.ENV_FILE) }}
|
||||
- name: Install Dependencies
|
||||
if: ${{ steps.cache-conda-env-ldm.outputs.cache-hit != 'true' }}
|
||||
run: |
|
||||
conda env create -f ${{ steps.vars.outputs.ENV_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: Download Huggingface and Torch models
|
||||
if: ${{ steps.cache-hugginface-torch.outputs.cache-hit != 'true' }}
|
||||
run: |
|
||||
${{ steps.vars.outputs.PYTHON_BIN }} scripts/preload_models.py
|
||||
# - name: Run tmate
|
||||
# uses: mxschmitt/action-tmate@v3
|
||||
# timeout-minutes: 30
|
||||
- name: Run the tests
|
||||
run: |
|
||||
# Note, can't "activate" via github action; specifying the env's python has the same effect
|
||||
if [ $(uname) = "Darwin" ]; then
|
||||
export PYTORCH_ENABLE_MPS_FALLBACK=1
|
||||
fi
|
||||
# Utterly hacky, but I don't know how else to do this
|
||||
if [[ ${{ github.ref }} == 'refs/heads/master' ]]; then
|
||||
time ${{ steps.vars.outputs.PYTHON_BIN }} scripts/invoke.py --from_file tests/preflight_prompts.txt
|
||||
elif [[ ${{ github.ref }} == 'refs/heads/development' ]]; then
|
||||
time ${{ steps.vars.outputs.PYTHON_BIN }} scripts/invoke.py --from_file tests/dev_prompts.txt
|
||||
fi
|
||||
mkdir -p outputs/img-samples
|
||||
- name: Archive results
|
||||
uses: actions/upload-artifact@v3
|
||||
with:
|
||||
name: results
|
||||
path: outputs/img-samples
|
67
.github/workflows/test-invoke-pip-skip.yml
vendored
Normal file
@ -0,0 +1,67 @@
|
||||
name: Test invoke.py pip
|
||||
on:
|
||||
pull_request:
|
||||
paths-ignore:
|
||||
- 'pyproject.toml'
|
||||
- 'ldm/**'
|
||||
- 'invokeai/backend/**'
|
||||
- 'invokeai/configs/**'
|
||||
- 'invokeai/frontend/dist/**'
|
||||
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"'
|
148
.github/workflows/test-invoke-pip.yml
vendored
Normal file
@ -0,0 +1,148 @@
|
||||
name: Test invoke.py pip
|
||||
on:
|
||||
push:
|
||||
branches:
|
||||
- 'main'
|
||||
paths:
|
||||
- 'pyproject.toml'
|
||||
- 'ldm/**'
|
||||
- 'invokeai/backend/**'
|
||||
- 'invokeai/configs/**'
|
||||
- 'invokeai/frontend/dist/**'
|
||||
pull_request:
|
||||
paths:
|
||||
- 'pyproject.toml'
|
||||
- 'ldm/**'
|
||||
- 'invokeai/backend/**'
|
||||
- 'invokeai/configs/**'
|
||||
- 'invokeai/frontend/dist/**'
|
||||
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
|
||||
if: ${{ github.ref == 'refs/heads/main' }}
|
||||
run: echo "TEST_PROMPTS=tests/preflight_prompts.txt" >> ${{ matrix.github-env }}
|
||||
|
||||
- name: set test prompt to Pull Request validation
|
||||
if: ${{ github.ref != 'refs/heads/main' }}
|
||||
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: set INVOKEAI_OUTDIR
|
||||
run: >
|
||||
python -c
|
||||
"import os;from ldm.invoke.globals import Globals;OUTDIR=os.path.join(Globals.root,str('outputs'));print(f'INVOKEAI_OUTDIR={OUTDIR}')"
|
||||
>> ${{ matrix.github-env }}
|
||||
|
||||
- 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
|
||||
run: >
|
||||
invokeai
|
||||
--no-patchmatch
|
||||
--no-nsfw_checker
|
||||
--from_file ${{ env.TEST_PROMPTS }}
|
||||
--outdir ${{ env.INVOKEAI_OUTDIR }}/${{ matrix.python-version }}/${{ matrix.pytorch }}
|
||||
|
||||
- name: Archive results
|
||||
id: archive-results
|
||||
uses: actions/upload-artifact@v3
|
||||
with:
|
||||
name: results
|
||||
path: ${{ env.INVOKEAI_OUTDIR }}
|
44
.gitignore
vendored
@ -1,7 +1,14 @@
|
||||
# ignore default image save location and model symbolic link
|
||||
.idea/
|
||||
embeddings/
|
||||
outputs/
|
||||
models/ldm/stable-diffusion-v1/model.ckpt
|
||||
ldm/dream/restoration/codeformer/weights
|
||||
**/restoration/codeformer/weights
|
||||
|
||||
# ignore user models config
|
||||
configs/models.user.yaml
|
||||
config/models.user.yml
|
||||
invokeai.init
|
||||
|
||||
# ignore the Anaconda/Miniconda installer used while building Docker image
|
||||
anaconda.sh
|
||||
@ -61,11 +68,13 @@ htmlcov/
|
||||
.cache
|
||||
nosetests.xml
|
||||
coverage.xml
|
||||
cov.xml
|
||||
*.cover
|
||||
*.py,cover
|
||||
.hypothesis/
|
||||
.pytest_cache/
|
||||
cover/
|
||||
junit/
|
||||
|
||||
# Translations
|
||||
*.mo
|
||||
@ -180,7 +189,7 @@ src
|
||||
**/__pycache__/
|
||||
outputs
|
||||
|
||||
# Logs and associated folders
|
||||
# Logs and associated folders
|
||||
# created from generated embeddings.
|
||||
logs
|
||||
testtube
|
||||
@ -189,13 +198,40 @@ checkpoints
|
||||
.DS_Store
|
||||
|
||||
# Let the frontend manage its own gitignore
|
||||
!frontend/*
|
||||
!invokeai/frontend/*
|
||||
|
||||
# Scratch folder
|
||||
.scratch/
|
||||
.vscode/
|
||||
gfpgan/
|
||||
models/ldm/stable-diffusion-v1/model.sha256
|
||||
models/ldm/stable-diffusion-v1/*.sha256
|
||||
|
||||
|
||||
# GFPGAN model files
|
||||
gfpgan/
|
||||
|
||||
# config file (will be created by installer)
|
||||
configs/models.yaml
|
||||
|
||||
# weights (will be created by installer)
|
||||
models/ldm/stable-diffusion-v1/*.ckpt
|
||||
models/clipseg
|
||||
models/gfpgan
|
||||
|
||||
# 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
|
||||
|
||||
# no longer stored in source directory
|
||||
models
|
||||
|
41
.pre-commit-config.yaml
Normal file
@ -0,0 +1,41 @@
|
||||
# See https://pre-commit.com for more information
|
||||
# See https://pre-commit.com/hooks.html for more hooks
|
||||
repos:
|
||||
- repo: https://github.com/psf/black
|
||||
rev: 23.1.0
|
||||
hooks:
|
||||
- id: black
|
||||
|
||||
- repo: https://github.com/pycqa/isort
|
||||
rev: 5.12.0
|
||||
hooks:
|
||||
- id: isort
|
||||
|
||||
- repo: https://github.com/PyCQA/flake8
|
||||
rev: 6.0.0
|
||||
hooks:
|
||||
- id: flake8
|
||||
additional_dependencies:
|
||||
- flake8-black
|
||||
- flake8-bugbear
|
||||
- flake8-comprehensions
|
||||
- flake8-simplify
|
||||
|
||||
- repo: https://github.com/pre-commit/mirrors-prettier
|
||||
rev: 'v3.0.0-alpha.4'
|
||||
hooks:
|
||||
- id: prettier
|
||||
|
||||
- repo: https://github.com/pre-commit/pre-commit-hooks
|
||||
rev: v4.4.0
|
||||
hooks:
|
||||
- id: check-added-large-files
|
||||
- id: check-executables-have-shebangs
|
||||
- id: check-shebang-scripts-are-executable
|
||||
- id: check-merge-conflict
|
||||
- id: check-symlinks
|
||||
- id: check-toml
|
||||
- id: end-of-file-fixer
|
||||
- id: no-commit-to-branch
|
||||
args: ['--branch', 'main']
|
||||
- id: trailing-whitespace
|
14
.prettierignore
Normal file
@ -0,0 +1,14 @@
|
||||
invokeai/frontend/.husky
|
||||
invokeai/frontend/patches
|
||||
|
||||
# Ignore artifacts:
|
||||
build
|
||||
coverage
|
||||
static
|
||||
invokeai/frontend/dist
|
||||
|
||||
# Ignore all HTML files:
|
||||
*.html
|
||||
|
||||
# Ignore deprecated docs
|
||||
docs/installation/deprecated_documentation
|
@ -1,9 +1,9 @@
|
||||
endOfLine: lf
|
||||
tabWidth: 2
|
||||
useTabs: false
|
||||
singleQuote: true
|
||||
quoteProps: as-needed
|
||||
embeddedLanguageFormatting: auto
|
||||
endOfLine: lf
|
||||
singleQuote: true
|
||||
semi: true
|
||||
trailingComma: es5
|
||||
useTabs: false
|
||||
overrides:
|
||||
- files: '*.md'
|
||||
options:
|
||||
@ -11,3 +11,9 @@ overrides:
|
||||
printWidth: 80
|
||||
parser: markdown
|
||||
cursorOffset: -1
|
||||
- files: docs/**/*.md
|
||||
options:
|
||||
tabWidth: 4
|
||||
- files: 'invokeai/frontend/public/locales/*.json'
|
||||
options:
|
||||
tabWidth: 4
|
||||
|
5
.pytest.ini
Normal file
@ -0,0 +1,5 @@
|
||||
[pytest]
|
||||
DJANGO_SETTINGS_MODULE = webtas.settings
|
||||
; python_files = tests.py test_*.py *_tests.py
|
||||
|
||||
addopts = --cov=. --cov-config=.coveragerc --cov-report xml:cov.xml
|
128
CODE_OF_CONDUCT.md
Normal file
@ -0,0 +1,128 @@
|
||||
# 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.
|
84
InvokeAI_Statement_of_Values.md
Normal file
@ -0,0 +1,84 @@
|
||||
<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
|
||||
artist’s 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.
|
13
LICENSE
@ -1,17 +1,6 @@
|
||||
MIT License
|
||||
|
||||
Copyright (c) 2022 Lincoln D. Stein (https://github.com/lstein)
|
||||
|
||||
This software is derived from a fork of the source code available from
|
||||
https://github.com/pesser/stable-diffusion and
|
||||
https://github.com/CompViz/stable-diffusion. They carry the following
|
||||
copyrights:
|
||||
|
||||
Copyright (c) 2022 Machine Vision and Learning Group, LMU Munich
|
||||
Copyright (c) 2022 Robin Rombach and Patrick Esser and contributors
|
||||
|
||||
Please see individual source code files for copyright and authorship
|
||||
attributions.
|
||||
Copyright (c) 2022 InvokeAI Team
|
||||
|
||||
Permission is hereby granted, free of charge, to any person obtaining a copy
|
||||
of this software and associated documentation files (the "Software"), to deal
|
||||
|
339
README.md
@ -1,30 +1,19 @@
|
||||
<div align="center">
|
||||
|
||||

|
||||
|
||||
# InvokeAI: A Stable Diffusion Toolkit
|
||||
|
||||
_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 aid diagnose issues faster._
|
||||
|
||||
_This repository was formally known as lstein/stable-diffusion_
|
||||
|
||||
# **Table of Contents**
|
||||
|
||||

|
||||
|
||||
[![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] [![CI checks on dev badge]][CI checks on dev link] [![latest commit to dev badge]][latest commit to dev link]
|
||||
[![CI checks on main badge]][CI checks on main link] [![latest commit to main badge]][latest commit to main link]
|
||||
|
||||
[![github open issues badge]][github open issues link] [![github open prs badge]][github open prs link]
|
||||
[![github open issues badge]][github open issues link] [![github open prs badge]][github open prs link] [![translation status badge]][translation status 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/workflows/test-invoke-conda.yml
|
||||
[CI checks on main link]:https://github.com/invoke-ai/InvokeAI/actions?query=branch%3Amain
|
||||
[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
|
||||
@ -35,166 +24,264 @@ _This repository was formally known as lstein/stable-diffusion_
|
||||
[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 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 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 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>
|
||||
|
||||
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, and runs on
|
||||
GPU cards with as little as 4 GB or RAM.
|
||||
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.
|
||||
|
||||
_Note: This fork is rapidly evolving. Please use the
|
||||
**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>]
|
||||
|
||||
_Note: InvokeAI 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 aid diagnose issues faster._
|
||||
requests. Be sure to use the provided templates. They will help us diagnose issues faster._
|
||||
|
||||
<div align="center">
|
||||
|
||||

|
||||
|
||||
</div>
|
||||
|
||||
## Table of Contents
|
||||
|
||||
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)
|
||||
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)
|
||||
|
||||
### Installation
|
||||
## Getting Started with InvokeAI
|
||||
|
||||
This fork is supported across multiple platforms. You can find individual installation instructions
|
||||
below.
|
||||
For full installation and upgrade instructions, please see:
|
||||
[InvokeAI Installation Overview](https://invoke-ai.github.io/InvokeAI/installation/)
|
||||
|
||||
- #### [Linux](docs/installation/INSTALL_LINUX.md)
|
||||
### Automatic Installer (suggested for 1st time users)
|
||||
|
||||
- #### [Windows](docs/installation/INSTALL_WINDOWS.md)
|
||||
1. Go to the bottom of the [Latest Release Page](https://github.com/invoke-ai/InvokeAI/releases/latest)
|
||||
|
||||
- #### [Macintosh](docs/installation/INSTALL_MAC.md)
|
||||
2. Download the .zip file for your OS (Windows/macOS/Linux).
|
||||
|
||||
### Hardware Requirements
|
||||
3. Unzip the file.
|
||||
|
||||
#### System
|
||||
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`.
|
||||
|
||||
You wil need one of the following:
|
||||
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 generaiton 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 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:
|
||||
|
||||
- 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)
|
||||
|
||||
#### Memory
|
||||
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
|
||||
|
||||
- At least 12 GB Main Memory RAM.
|
||||
|
||||
#### Disk
|
||||
### Disk
|
||||
|
||||
- At least 6 GB of free disk space for the machine learning model, Python, and all its dependencies.
|
||||
- At least 12 GB of free disk space for the machine learning model, Python, and all its dependencies.
|
||||
|
||||
#### Note
|
||||
## Features
|
||||
|
||||
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:
|
||||
Feature documentation can be reviewed by navigating to [the InvokeAI Documentation page](https://invoke-ai.github.io/InvokeAI/features/)
|
||||
|
||||
```bash
|
||||
(ldm) ~/stable-diffusion$ python scripts/invoke.py --precision=float32
|
||||
```
|
||||
### *Web Server & UI*
|
||||
|
||||
### Features
|
||||
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.
|
||||
|
||||
#### Major Features
|
||||
### *Unified Canvas*
|
||||
|
||||
- [Interactive Command Line Interface](docs/features/CLI.md)
|
||||
- [Image To Image](docs/features/IMG2IMG.md)
|
||||
- [Inpainting Support](docs/features/INPAINTING.md)
|
||||
- [Outpainting Support](docs/features/OUTPAINTING.md)
|
||||
- [Upscaling, face-restoration and outpainting](docs/features/POSTPROCESS.md)
|
||||
- [Seamless Tiling](docs/features/OTHER.md#seamless-tiling)
|
||||
- [Google Colab](docs/features/OTHER.md#google-colab)
|
||||
- [Web Server](docs/features/WEB.md)
|
||||
- [Reading Prompts From File](docs/features/PROMPTS.md#reading-prompts-from-a-file)
|
||||
- [Shortcut: Reusing Seeds](docs/features/OTHER.md#shortcuts-reusing-seeds)
|
||||
- [Prompt Blending](docs/features/PROMPTS.md#prompt-blending)
|
||||
- [Thresholding and Perlin Noise Initialization Options](/docs/features/OTHER.md#thresholding-and-perlin-noise-initialization-options)
|
||||
- [Negative/Unconditioned Prompts](docs/features/PROMPTS.md#negative-and-unconditioned-prompts)
|
||||
- [Variations](docs/features/VARIATIONS.md)
|
||||
- [Personalizing Text-to-Image Generation](docs/features/TEXTUAL_INVERSION.md)
|
||||
- [Simplified API for text to image generation](docs/features/OTHER.md#simplified-api)
|
||||
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.
|
||||
|
||||
#### Other Features
|
||||
### *Advanced Prompt Syntax*
|
||||
|
||||
- [Creating Transparent Regions for Inpainting](docs/features/INPAINTING.md#creating-transparent-regions-for-inpainting)
|
||||
- [Preload Models](docs/features/OTHER.md#preload-models)
|
||||
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.
|
||||
|
||||
### *Command Line Interface*
|
||||
|
||||
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...
|
||||
|
||||
### Latest Changes
|
||||
|
||||
- vNEXT (TODO 2022)
|
||||
For our latest changes, view our [Release
|
||||
Notes](https://github.com/invoke-ai/InvokeAI/releases) and the
|
||||
[CHANGELOG](docs/CHANGELOG.md).
|
||||
|
||||
- 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`.
|
||||
## Troubleshooting
|
||||
|
||||
- v1.14 (11 September 2022)
|
||||
|
||||
- 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)).
|
||||
- Inpainting support.
|
||||
- Improved web server GUI.
|
||||
- Lots of code and documentation cleanups.
|
||||
|
||||
- v1.13 (3 September 2022
|
||||
|
||||
- Support image variations (see [VARIATIONS](docs/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)
|
||||
- WebUI supports GFPGAN/ESRGAN facial reconstruction and upscaling
|
||||
[Kevin Gibbons](https://github.com/bakkot)
|
||||
- WebUI supports incremental display of in-progress images during generation
|
||||
[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))
|
||||
- Can specify --grid on invoke.py command line as the default.
|
||||
- Miscellaneous internal bug and stability fixes.
|
||||
- Works on M1 Apple hardware.
|
||||
- Multiple bug fixes.
|
||||
|
||||
For older changelogs, please visit the **[CHANGELOG](docs/features/CHANGELOG.md)**.
|
||||
|
||||
### Troubleshooting
|
||||
|
||||
Please check out our **[Q&A](docs/help/TROUBLESHOOT.md)** to get solutions for common installation
|
||||
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. 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).
|
||||
cleanup, testing, or code reviews, is very much encouraged to do so.
|
||||
|
||||
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.
|
||||
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
|
||||
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**.
|
||||
|
||||
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!
|
||||
|
||||
### Contributors
|
||||
|
||||
This fork is a combined effort of various people from across the world.
|
||||
[Check out the list of all these amazing people](docs/other/CONTRIBUTORS.md). We thank them for
|
||||
[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. Feel free to send me an
|
||||
email if you use and like the script.
|
||||
For support, please use this repository's GitHub Issues tracking service, or join the Discord.
|
||||
|
||||
Original portions of the software are Copyright (c) 2020
|
||||
[Lincoln D. Stein](https://github.com/lstein)
|
||||
Original portions of the software are Copyright (c) 2023 by respective contributors.
|
||||
|
||||
### Further Reading
|
||||
|
||||
Please see the original README for more information on this software and underlying algorithm,
|
||||
located in the file [README-CompViz.md](docs/other/README-CompViz.md).
|
||||
|
@ -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:
|
||||
|
||||

|
||||

|
||||
|
||||
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
|
||||
|
@ -1,61 +0,0 @@
|
||||
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 "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 "gfpgan_strength" in params and params["gfpgan_strength"]:
|
||||
switches.append(f'-G {params["gfpgan_strength"]}')
|
||||
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)
|
@ -1,821 +0,0 @@
|
||||
import mimetypes
|
||||
import transformers
|
||||
import json
|
||||
import os
|
||||
import traceback
|
||||
import eventlet
|
||||
import glob
|
||||
import shlex
|
||||
import math
|
||||
import shutil
|
||||
import sys
|
||||
|
||||
sys.path.append(".")
|
||||
|
||||
from argparse import ArgumentTypeError
|
||||
from modules.create_cmd_parser import create_cmd_parser
|
||||
|
||||
parser = create_cmd_parser()
|
||||
opt = parser.parse_args()
|
||||
|
||||
|
||||
from flask_socketio import SocketIO
|
||||
from flask import Flask, send_from_directory, url_for, jsonify
|
||||
from pathlib import Path
|
||||
from PIL import Image
|
||||
from pytorch_lightning import logging
|
||||
from threading import Event
|
||||
from uuid import uuid4
|
||||
from send2trash import send2trash
|
||||
|
||||
|
||||
from ldm.generate import Generate
|
||||
from ldm.invoke.restoration import Restoration
|
||||
from ldm.invoke.pngwriter import PngWriter, retrieve_metadata
|
||||
from ldm.invoke.args import APP_ID, APP_VERSION, calculate_init_img_hash
|
||||
from ldm.invoke.conditioning import split_weighted_subprompts
|
||||
|
||||
from modules.parameters import parameters_to_command
|
||||
|
||||
|
||||
"""
|
||||
USER CONFIG
|
||||
"""
|
||||
if opt.cors and "*" in opt.cors:
|
||||
raise ArgumentTypeError('"*" is not an allowed CORS origin')
|
||||
|
||||
|
||||
output_dir = "outputs/" # Base output directory for images
|
||||
host = opt.host # Web & socket.io host
|
||||
port = opt.port # Web & socket.io port
|
||||
verbose = opt.verbose # enables copious socket.io logging
|
||||
precision = opt.precision
|
||||
free_gpu_mem = opt.free_gpu_mem
|
||||
embedding_path = opt.embedding_path
|
||||
additional_allowed_origins = (
|
||||
opt.cors if opt.cors else []
|
||||
) # additional CORS allowed origins
|
||||
model = "stable-diffusion-1.4"
|
||||
|
||||
"""
|
||||
END USER CONFIG
|
||||
"""
|
||||
|
||||
|
||||
print("* Initializing, be patient...\n")
|
||||
|
||||
|
||||
"""
|
||||
SERVER SETUP
|
||||
"""
|
||||
|
||||
|
||||
# fix missing mimetypes on windows due to registry wonkiness
|
||||
mimetypes.add_type("application/javascript", ".js")
|
||||
mimetypes.add_type("text/css", ".css")
|
||||
|
||||
app = Flask(__name__, static_url_path="", static_folder="../frontend/dist/")
|
||||
|
||||
|
||||
app.config["OUTPUTS_FOLDER"] = "../outputs"
|
||||
|
||||
|
||||
@app.route("/outputs/<path:filename>")
|
||||
def outputs(filename):
|
||||
return send_from_directory(app.config["OUTPUTS_FOLDER"], filename)
|
||||
|
||||
|
||||
@app.route("/", defaults={"path": ""})
|
||||
def serve(path):
|
||||
return send_from_directory(app.static_folder, "index.html")
|
||||
|
||||
|
||||
logger = True if verbose else False
|
||||
engineio_logger = True if verbose else False
|
||||
|
||||
# default 1,000,000, needs to be higher for socketio to accept larger images
|
||||
max_http_buffer_size = 10000000
|
||||
|
||||
cors_allowed_origins = [f"http://{host}:{port}"] + additional_allowed_origins
|
||||
|
||||
socketio = SocketIO(
|
||||
app,
|
||||
logger=logger,
|
||||
engineio_logger=engineio_logger,
|
||||
max_http_buffer_size=max_http_buffer_size,
|
||||
cors_allowed_origins=cors_allowed_origins,
|
||||
ping_interval=(50, 50),
|
||||
ping_timeout=60,
|
||||
)
|
||||
|
||||
|
||||
"""
|
||||
END SERVER SETUP
|
||||
"""
|
||||
|
||||
|
||||
"""
|
||||
APP SETUP
|
||||
"""
|
||||
|
||||
|
||||
class CanceledException(Exception):
|
||||
pass
|
||||
|
||||
|
||||
try:
|
||||
gfpgan, codeformer, esrgan = None, None, None
|
||||
from ldm.invoke.restoration.base import Restoration
|
||||
|
||||
restoration = Restoration()
|
||||
gfpgan, codeformer = restoration.load_face_restore_models()
|
||||
esrgan = restoration.load_esrgan()
|
||||
|
||||
# coreformer.process(self, image, strength, device, seed=None, fidelity=0.75)
|
||||
|
||||
except (ModuleNotFoundError, ImportError):
|
||||
print(traceback.format_exc(), file=sys.stderr)
|
||||
print(">> You may need to install the ESRGAN and/or GFPGAN modules")
|
||||
|
||||
canceled = Event()
|
||||
|
||||
# reduce logging outputs to error
|
||||
transformers.logging.set_verbosity_error()
|
||||
logging.getLogger("pytorch_lightning").setLevel(logging.ERROR)
|
||||
|
||||
# Initialize and load model
|
||||
generate = Generate(
|
||||
model,
|
||||
precision=precision,
|
||||
embedding_path=embedding_path,
|
||||
)
|
||||
generate.free_gpu_mem = free_gpu_mem
|
||||
generate.load_model()
|
||||
|
||||
|
||||
# location for "finished" images
|
||||
result_path = os.path.join(output_dir, "img-samples/")
|
||||
|
||||
# temporary path for intermediates
|
||||
intermediate_path = os.path.join(result_path, "intermediates/")
|
||||
|
||||
# path for user-uploaded init images and masks
|
||||
init_image_path = os.path.join(result_path, "init-images/")
|
||||
mask_image_path = os.path.join(result_path, "mask-images/")
|
||||
|
||||
# txt log
|
||||
log_path = os.path.join(result_path, "invoke_log.txt")
|
||||
|
||||
# make all output paths
|
||||
[
|
||||
os.makedirs(path, exist_ok=True)
|
||||
for path in [result_path, intermediate_path, init_image_path, mask_image_path]
|
||||
]
|
||||
|
||||
|
||||
"""
|
||||
END APP SETUP
|
||||
"""
|
||||
|
||||
|
||||
"""
|
||||
SOCKET.IO LISTENERS
|
||||
"""
|
||||
|
||||
|
||||
@socketio.on("requestSystemConfig")
|
||||
def handle_request_capabilities():
|
||||
print(f">> System config requested")
|
||||
config = get_system_config()
|
||||
socketio.emit("systemConfig", config)
|
||||
|
||||
|
||||
@socketio.on("requestImages")
|
||||
def handle_request_images(page=1, offset=0, last_mtime=None):
|
||||
chunk_size = 50
|
||||
|
||||
if last_mtime:
|
||||
print(f">> Latest images requested")
|
||||
else:
|
||||
print(
|
||||
f">> Page {page} of images requested (page size {chunk_size} offset {offset})"
|
||||
)
|
||||
|
||||
paths = glob.glob(os.path.join(result_path, "*.png"))
|
||||
sorted_paths = sorted(paths, key=lambda x: os.path.getmtime(x), reverse=True)
|
||||
|
||||
if last_mtime:
|
||||
image_paths = filter(lambda x: os.path.getmtime(x) > last_mtime, sorted_paths)
|
||||
else:
|
||||
|
||||
image_paths = sorted_paths[
|
||||
slice(chunk_size * (page - 1) + offset, chunk_size * page + offset)
|
||||
]
|
||||
page = page + 1
|
||||
|
||||
image_array = []
|
||||
|
||||
for path in image_paths:
|
||||
metadata = retrieve_metadata(path)
|
||||
image_array.append(
|
||||
{
|
||||
"url": path,
|
||||
"mtime": os.path.getmtime(path),
|
||||
"metadata": metadata["sd-metadata"],
|
||||
}
|
||||
)
|
||||
|
||||
socketio.emit(
|
||||
"galleryImages",
|
||||
{
|
||||
"images": image_array,
|
||||
"nextPage": page,
|
||||
"offset": offset,
|
||||
"onlyNewImages": True if last_mtime else False,
|
||||
},
|
||||
)
|
||||
|
||||
|
||||
@socketio.on("generateImage")
|
||||
def handle_generate_image_event(
|
||||
generation_parameters, esrgan_parameters, gfpgan_parameters
|
||||
):
|
||||
print(
|
||||
f">> Image generation requested: {generation_parameters}\nESRGAN parameters: {esrgan_parameters}\nGFPGAN parameters: {gfpgan_parameters}"
|
||||
)
|
||||
generate_images(generation_parameters, esrgan_parameters, gfpgan_parameters)
|
||||
|
||||
|
||||
@socketio.on("runESRGAN")
|
||||
def handle_run_esrgan_event(original_image, esrgan_parameters):
|
||||
print(
|
||||
f'>> ESRGAN upscale requested for "{original_image["url"]}": {esrgan_parameters}'
|
||||
)
|
||||
progress = {
|
||||
"currentStep": 1,
|
||||
"totalSteps": 1,
|
||||
"currentIteration": 1,
|
||||
"totalIterations": 1,
|
||||
"currentStatus": "Preparing",
|
||||
"isProcessing": True,
|
||||
"currentStatusHasSteps": False,
|
||||
}
|
||||
|
||||
socketio.emit("progressUpdate", progress)
|
||||
eventlet.sleep(0)
|
||||
|
||||
image = Image.open(original_image["url"])
|
||||
|
||||
seed = (
|
||||
original_image["metadata"]["seed"]
|
||||
if "seed" in original_image["metadata"]
|
||||
else "unknown_seed"
|
||||
)
|
||||
|
||||
progress["currentStatus"] = "Upscaling"
|
||||
socketio.emit("progressUpdate", progress)
|
||||
eventlet.sleep(0)
|
||||
|
||||
image = esrgan.process(
|
||||
image=image,
|
||||
upsampler_scale=esrgan_parameters["upscale"][0],
|
||||
strength=esrgan_parameters["upscale"][1],
|
||||
seed=seed,
|
||||
)
|
||||
|
||||
progress["currentStatus"] = "Saving image"
|
||||
socketio.emit("progressUpdate", progress)
|
||||
eventlet.sleep(0)
|
||||
|
||||
esrgan_parameters["seed"] = seed
|
||||
metadata = parameters_to_post_processed_image_metadata(
|
||||
parameters=esrgan_parameters,
|
||||
original_image_path=original_image["url"],
|
||||
type="esrgan",
|
||||
)
|
||||
command = parameters_to_command(esrgan_parameters)
|
||||
|
||||
path = save_image(image, command, metadata, result_path, postprocessing="esrgan")
|
||||
|
||||
write_log_message(f'[Upscaled] "{original_image["url"]}" > "{path}": {command}')
|
||||
|
||||
progress["currentStatus"] = "Finished"
|
||||
progress["currentStep"] = 0
|
||||
progress["totalSteps"] = 0
|
||||
progress["currentIteration"] = 0
|
||||
progress["totalIterations"] = 0
|
||||
progress["isProcessing"] = False
|
||||
socketio.emit("progressUpdate", progress)
|
||||
eventlet.sleep(0)
|
||||
|
||||
socketio.emit(
|
||||
"esrganResult",
|
||||
{
|
||||
"url": os.path.relpath(path),
|
||||
"mtime": os.path.getmtime(path),
|
||||
"metadata": metadata,
|
||||
},
|
||||
)
|
||||
|
||||
|
||||
@socketio.on("runGFPGAN")
|
||||
def handle_run_gfpgan_event(original_image, gfpgan_parameters):
|
||||
print(
|
||||
f'>> GFPGAN face fix requested for "{original_image["url"]}": {gfpgan_parameters}'
|
||||
)
|
||||
progress = {
|
||||
"currentStep": 1,
|
||||
"totalSteps": 1,
|
||||
"currentIteration": 1,
|
||||
"totalIterations": 1,
|
||||
"currentStatus": "Preparing",
|
||||
"isProcessing": True,
|
||||
"currentStatusHasSteps": False,
|
||||
}
|
||||
|
||||
socketio.emit("progressUpdate", progress)
|
||||
eventlet.sleep(0)
|
||||
|
||||
image = Image.open(original_image["url"])
|
||||
|
||||
seed = (
|
||||
original_image["metadata"]["seed"]
|
||||
if "seed" in original_image["metadata"]
|
||||
else "unknown_seed"
|
||||
)
|
||||
|
||||
progress["currentStatus"] = "Fixing faces"
|
||||
socketio.emit("progressUpdate", progress)
|
||||
eventlet.sleep(0)
|
||||
|
||||
image = gfpgan.process(
|
||||
image=image, strength=gfpgan_parameters["gfpgan_strength"], seed=seed
|
||||
)
|
||||
|
||||
progress["currentStatus"] = "Saving image"
|
||||
socketio.emit("progressUpdate", progress)
|
||||
eventlet.sleep(0)
|
||||
|
||||
gfpgan_parameters["seed"] = seed
|
||||
metadata = parameters_to_post_processed_image_metadata(
|
||||
parameters=gfpgan_parameters,
|
||||
original_image_path=original_image["url"],
|
||||
type="gfpgan",
|
||||
)
|
||||
command = parameters_to_command(gfpgan_parameters)
|
||||
|
||||
path = save_image(image, command, metadata, result_path, postprocessing="gfpgan")
|
||||
|
||||
write_log_message(f'[Fixed faces] "{original_image["url"]}" > "{path}": {command}')
|
||||
|
||||
progress["currentStatus"] = "Finished"
|
||||
progress["currentStep"] = 0
|
||||
progress["totalSteps"] = 0
|
||||
progress["currentIteration"] = 0
|
||||
progress["totalIterations"] = 0
|
||||
progress["isProcessing"] = False
|
||||
socketio.emit("progressUpdate", progress)
|
||||
eventlet.sleep(0)
|
||||
|
||||
socketio.emit(
|
||||
"gfpganResult",
|
||||
{
|
||||
"url": os.path.relpath(path),
|
||||
"mtime": os.path.mtime(path),
|
||||
"metadata": metadata,
|
||||
},
|
||||
)
|
||||
|
||||
|
||||
@socketio.on("cancel")
|
||||
def handle_cancel():
|
||||
print(f">> Cancel processing requested")
|
||||
canceled.set()
|
||||
socketio.emit("processingCanceled")
|
||||
|
||||
|
||||
# TODO: I think this needs a safety mechanism.
|
||||
@socketio.on("deleteImage")
|
||||
def handle_delete_image(path, uuid):
|
||||
print(f'>> Delete requested "{path}"')
|
||||
send2trash(path)
|
||||
socketio.emit("imageDeleted", {"url": path, "uuid": uuid})
|
||||
|
||||
|
||||
# TODO: I think this needs a safety mechanism.
|
||||
@socketio.on("uploadInitialImage")
|
||||
def handle_upload_initial_image(bytes, name):
|
||||
print(f'>> Init image upload requested "{name}"')
|
||||
uuid = uuid4().hex
|
||||
split = os.path.splitext(name)
|
||||
name = f"{split[0]}.{uuid}{split[1]}"
|
||||
file_path = os.path.join(init_image_path, name)
|
||||
os.makedirs(os.path.dirname(file_path), exist_ok=True)
|
||||
newFile = open(file_path, "wb")
|
||||
newFile.write(bytes)
|
||||
socketio.emit("initialImageUploaded", {"url": file_path, "uuid": ""})
|
||||
|
||||
|
||||
# TODO: I think this needs a safety mechanism.
|
||||
@socketio.on("uploadMaskImage")
|
||||
def handle_upload_mask_image(bytes, name):
|
||||
print(f'>> Mask image upload requested "{name}"')
|
||||
uuid = uuid4().hex
|
||||
split = os.path.splitext(name)
|
||||
name = f"{split[0]}.{uuid}{split[1]}"
|
||||
file_path = os.path.join(mask_image_path, name)
|
||||
os.makedirs(os.path.dirname(file_path), exist_ok=True)
|
||||
newFile = open(file_path, "wb")
|
||||
newFile.write(bytes)
|
||||
socketio.emit("maskImageUploaded", {"url": file_path, "uuid": ""})
|
||||
|
||||
|
||||
"""
|
||||
END SOCKET.IO LISTENERS
|
||||
"""
|
||||
|
||||
|
||||
"""
|
||||
ADDITIONAL FUNCTIONS
|
||||
"""
|
||||
|
||||
|
||||
def get_system_config():
|
||||
return {
|
||||
"model": "stable diffusion",
|
||||
"model_id": model,
|
||||
"model_hash": generate.model_hash,
|
||||
"app_id": APP_ID,
|
||||
"app_version": APP_VERSION,
|
||||
}
|
||||
|
||||
|
||||
def parameters_to_post_processed_image_metadata(parameters, original_image_path, type):
|
||||
# top-level metadata minus `image` or `images`
|
||||
metadata = get_system_config()
|
||||
|
||||
orig_hash = calculate_init_img_hash(original_image_path)
|
||||
|
||||
image = {"orig_path": original_image_path, "orig_hash": orig_hash}
|
||||
|
||||
if type == "esrgan":
|
||||
image["type"] = "esrgan"
|
||||
image["scale"] = parameters["upscale"][0]
|
||||
image["strength"] = parameters["upscale"][1]
|
||||
elif type == "gfpgan":
|
||||
image["type"] = "gfpgan"
|
||||
image["strength"] = parameters["gfpgan_strength"]
|
||||
else:
|
||||
raise TypeError(f"Invalid type: {type}")
|
||||
|
||||
metadata["image"] = image
|
||||
return metadata
|
||||
|
||||
|
||||
def parameters_to_generated_image_metadata(parameters):
|
||||
# top-level metadata minus `image` or `images`
|
||||
|
||||
metadata = get_system_config()
|
||||
# remove any image keys not mentioned in RFC #266
|
||||
rfc266_img_fields = [
|
||||
"type",
|
||||
"postprocessing",
|
||||
"sampler",
|
||||
"prompt",
|
||||
"seed",
|
||||
"variations",
|
||||
"steps",
|
||||
"cfg_scale",
|
||||
"threshold",
|
||||
"perlin",
|
||||
"step_number",
|
||||
"width",
|
||||
"height",
|
||||
"extra",
|
||||
"seamless",
|
||||
]
|
||||
|
||||
rfc_dict = {}
|
||||
|
||||
for item in parameters.items():
|
||||
key, value = item
|
||||
if key in rfc266_img_fields:
|
||||
rfc_dict[key] = value
|
||||
|
||||
postprocessing = []
|
||||
|
||||
# 'postprocessing' is either null or an
|
||||
if "gfpgan_strength" in parameters:
|
||||
|
||||
postprocessing.append(
|
||||
{"type": "gfpgan", "strength": float(parameters["gfpgan_strength"])}
|
||||
)
|
||||
|
||||
if "upscale" in parameters:
|
||||
postprocessing.append(
|
||||
{
|
||||
"type": "esrgan",
|
||||
"scale": int(parameters["upscale"][0]),
|
||||
"strength": float(parameters["upscale"][1]),
|
||||
}
|
||||
)
|
||||
|
||||
rfc_dict["postprocessing"] = postprocessing if len(postprocessing) > 0 else None
|
||||
|
||||
# semantic drift
|
||||
rfc_dict["sampler"] = parameters["sampler_name"]
|
||||
|
||||
# display weighted subprompts (liable to change)
|
||||
subprompts = split_weighted_subprompts(parameters["prompt"])
|
||||
subprompts = [{"prompt": x[0], "weight": x[1]} for x in subprompts]
|
||||
rfc_dict["prompt"] = subprompts
|
||||
|
||||
# 'variations' should always exist and be an array, empty or consisting of {'seed': seed, 'weight': weight} pairs
|
||||
variations = []
|
||||
|
||||
if "with_variations" in parameters:
|
||||
variations = [
|
||||
{"seed": x[0], "weight": x[1]} for x in parameters["with_variations"]
|
||||
]
|
||||
|
||||
rfc_dict["variations"] = variations
|
||||
|
||||
if "init_img" in parameters:
|
||||
rfc_dict["type"] = "img2img"
|
||||
rfc_dict["strength"] = parameters["strength"]
|
||||
rfc_dict["fit"] = parameters["fit"] # TODO: Noncompliant
|
||||
rfc_dict["orig_hash"] = calculate_init_img_hash(parameters["init_img"])
|
||||
rfc_dict["init_image_path"] = parameters["init_img"] # TODO: Noncompliant
|
||||
rfc_dict["sampler"] = "ddim" # TODO: FIX ME WHEN IMG2IMG SUPPORTS ALL SAMPLERS
|
||||
if "init_mask" in parameters:
|
||||
rfc_dict["mask_hash"] = calculate_init_img_hash(
|
||||
parameters["init_mask"]
|
||||
) # TODO: Noncompliant
|
||||
rfc_dict["mask_image_path"] = parameters["init_mask"] # TODO: Noncompliant
|
||||
else:
|
||||
rfc_dict["type"] = "txt2img"
|
||||
|
||||
metadata["image"] = rfc_dict
|
||||
|
||||
return metadata
|
||||
|
||||
|
||||
def make_unique_init_image_filename(name):
|
||||
uuid = uuid4().hex
|
||||
split = os.path.splitext(name)
|
||||
name = f"{split[0]}.{uuid}{split[1]}"
|
||||
return name
|
||||
|
||||
|
||||
def write_log_message(message, log_path=log_path):
|
||||
"""Logs the filename and parameters used to generate or process that image to log file"""
|
||||
message = f"{message}\n"
|
||||
with open(log_path, "a", encoding="utf-8") as file:
|
||||
file.writelines(message)
|
||||
|
||||
|
||||
def save_image(
|
||||
image, command, metadata, output_dir, step_index=None, postprocessing=False
|
||||
):
|
||||
pngwriter = PngWriter(output_dir)
|
||||
prefix = pngwriter.unique_prefix()
|
||||
|
||||
seed = "unknown_seed"
|
||||
|
||||
if "image" in metadata:
|
||||
if "seed" in metadata["image"]:
|
||||
seed = metadata["image"]["seed"]
|
||||
|
||||
filename = f"{prefix}.{seed}"
|
||||
|
||||
if step_index:
|
||||
filename += f".{step_index}"
|
||||
if postprocessing:
|
||||
filename += f".postprocessed"
|
||||
|
||||
filename += ".png"
|
||||
|
||||
path = pngwriter.save_image_and_prompt_to_png(
|
||||
image=image, dream_prompt=command, metadata=metadata, name=filename
|
||||
)
|
||||
|
||||
return path
|
||||
|
||||
|
||||
def calculate_real_steps(steps, strength, has_init_image):
|
||||
return math.floor(strength * steps) if has_init_image else steps
|
||||
|
||||
|
||||
def generate_images(generation_parameters, esrgan_parameters, gfpgan_parameters):
|
||||
canceled.clear()
|
||||
|
||||
step_index = 1
|
||||
prior_variations = (
|
||||
generation_parameters["with_variations"]
|
||||
if "with_variations" in generation_parameters
|
||||
else []
|
||||
)
|
||||
"""
|
||||
If a result image is used as an init image, and then deleted, we will want to be
|
||||
able to use it as an init image in the future. Need to copy it.
|
||||
|
||||
If the init/mask image doesn't exist in the init_image_path/mask_image_path,
|
||||
make a unique filename for it and copy it there.
|
||||
"""
|
||||
if "init_img" in generation_parameters:
|
||||
filename = os.path.basename(generation_parameters["init_img"])
|
||||
if not os.path.exists(os.path.join(init_image_path, filename)):
|
||||
unique_filename = make_unique_init_image_filename(filename)
|
||||
new_path = os.path.join(init_image_path, unique_filename)
|
||||
shutil.copy(generation_parameters["init_img"], new_path)
|
||||
generation_parameters["init_img"] = new_path
|
||||
if "init_mask" in generation_parameters:
|
||||
filename = os.path.basename(generation_parameters["init_mask"])
|
||||
if not os.path.exists(os.path.join(mask_image_path, filename)):
|
||||
unique_filename = make_unique_init_image_filename(filename)
|
||||
new_path = os.path.join(init_image_path, unique_filename)
|
||||
shutil.copy(generation_parameters["init_img"], new_path)
|
||||
generation_parameters["init_mask"] = new_path
|
||||
|
||||
totalSteps = calculate_real_steps(
|
||||
steps=generation_parameters["steps"],
|
||||
strength=generation_parameters["strength"]
|
||||
if "strength" in generation_parameters
|
||||
else None,
|
||||
has_init_image="init_img" in generation_parameters,
|
||||
)
|
||||
|
||||
progress = {
|
||||
"currentStep": 1,
|
||||
"totalSteps": totalSteps,
|
||||
"currentIteration": 1,
|
||||
"totalIterations": generation_parameters["iterations"],
|
||||
"currentStatus": "Preparing",
|
||||
"isProcessing": True,
|
||||
"currentStatusHasSteps": False,
|
||||
}
|
||||
|
||||
socketio.emit("progressUpdate", progress)
|
||||
eventlet.sleep(0)
|
||||
|
||||
def image_progress(sample, step):
|
||||
if canceled.is_set():
|
||||
raise CanceledException
|
||||
|
||||
nonlocal step_index
|
||||
nonlocal generation_parameters
|
||||
nonlocal progress
|
||||
|
||||
progress["currentStep"] = step + 1
|
||||
progress["currentStatus"] = "Generating"
|
||||
progress["currentStatusHasSteps"] = True
|
||||
|
||||
if (
|
||||
generation_parameters["progress_images"]
|
||||
and step % 5 == 0
|
||||
and step < generation_parameters["steps"] - 1
|
||||
):
|
||||
image = generate.sample_to_image(sample)
|
||||
|
||||
metadata = parameters_to_generated_image_metadata(generation_parameters)
|
||||
command = parameters_to_command(generation_parameters)
|
||||
path = save_image(image, command, metadata, intermediate_path, step_index=step_index, postprocessing=False)
|
||||
|
||||
step_index += 1
|
||||
socketio.emit(
|
||||
"intermediateResult",
|
||||
{
|
||||
"url": os.path.relpath(path),
|
||||
"mtime": os.path.getmtime(path),
|
||||
"metadata": metadata,
|
||||
},
|
||||
)
|
||||
socketio.emit("progressUpdate", progress)
|
||||
eventlet.sleep(0)
|
||||
|
||||
def image_done(image, seed, first_seed):
|
||||
nonlocal generation_parameters
|
||||
nonlocal esrgan_parameters
|
||||
nonlocal gfpgan_parameters
|
||||
nonlocal progress
|
||||
|
||||
step_index = 1
|
||||
nonlocal prior_variations
|
||||
|
||||
progress["currentStatus"] = "Generation complete"
|
||||
socketio.emit("progressUpdate", progress)
|
||||
eventlet.sleep(0)
|
||||
|
||||
all_parameters = generation_parameters
|
||||
postprocessing = False
|
||||
|
||||
if (
|
||||
"variation_amount" in all_parameters
|
||||
and all_parameters["variation_amount"] > 0
|
||||
):
|
||||
first_seed = first_seed or seed
|
||||
this_variation = [[seed, all_parameters["variation_amount"]]]
|
||||
all_parameters["with_variations"] = prior_variations + this_variation
|
||||
all_parameters["seed"] = first_seed
|
||||
elif ("with_variations" in all_parameters):
|
||||
all_parameters["seed"] = first_seed
|
||||
else:
|
||||
all_parameters["seed"] = seed
|
||||
|
||||
if esrgan_parameters:
|
||||
progress["currentStatus"] = "Upscaling"
|
||||
progress["currentStatusHasSteps"] = False
|
||||
socketio.emit("progressUpdate", progress)
|
||||
eventlet.sleep(0)
|
||||
|
||||
image = esrgan.process(
|
||||
image=image,
|
||||
upsampler_scale=esrgan_parameters["level"],
|
||||
strength=esrgan_parameters["strength"],
|
||||
seed=seed,
|
||||
)
|
||||
|
||||
postprocessing = True
|
||||
all_parameters["upscale"] = [
|
||||
esrgan_parameters["level"],
|
||||
esrgan_parameters["strength"],
|
||||
]
|
||||
|
||||
if gfpgan_parameters:
|
||||
progress["currentStatus"] = "Fixing faces"
|
||||
progress["currentStatusHasSteps"] = False
|
||||
socketio.emit("progressUpdate", progress)
|
||||
eventlet.sleep(0)
|
||||
|
||||
image = gfpgan.process(
|
||||
image=image, strength=gfpgan_parameters["strength"], seed=seed
|
||||
)
|
||||
postprocessing = True
|
||||
all_parameters["gfpgan_strength"] = gfpgan_parameters["strength"]
|
||||
|
||||
progress["currentStatus"] = "Saving image"
|
||||
socketio.emit("progressUpdate", progress)
|
||||
eventlet.sleep(0)
|
||||
|
||||
metadata = parameters_to_generated_image_metadata(all_parameters)
|
||||
command = parameters_to_command(all_parameters)
|
||||
|
||||
path = save_image(
|
||||
image, command, metadata, result_path, postprocessing=postprocessing
|
||||
)
|
||||
|
||||
print(f'>> Image generated: "{path}"')
|
||||
write_log_message(f'[Generated] "{path}": {command}')
|
||||
|
||||
if progress["totalIterations"] > progress["currentIteration"]:
|
||||
progress["currentStep"] = 1
|
||||
progress["currentIteration"] += 1
|
||||
progress["currentStatus"] = "Iteration finished"
|
||||
progress["currentStatusHasSteps"] = False
|
||||
else:
|
||||
progress["currentStep"] = 0
|
||||
progress["totalSteps"] = 0
|
||||
progress["currentIteration"] = 0
|
||||
progress["totalIterations"] = 0
|
||||
progress["currentStatus"] = "Finished"
|
||||
progress["isProcessing"] = False
|
||||
|
||||
socketio.emit("progressUpdate", progress)
|
||||
eventlet.sleep(0)
|
||||
|
||||
socketio.emit(
|
||||
"generationResult",
|
||||
{
|
||||
"url": os.path.relpath(path),
|
||||
"mtime": os.path.getmtime(path),
|
||||
"metadata": metadata,
|
||||
},
|
||||
)
|
||||
eventlet.sleep(0)
|
||||
|
||||
try:
|
||||
generate.prompt2image(
|
||||
**generation_parameters,
|
||||
step_callback=image_progress,
|
||||
image_callback=image_done,
|
||||
)
|
||||
|
||||
except KeyboardInterrupt:
|
||||
raise
|
||||
except CanceledException:
|
||||
pass
|
||||
except Exception as e:
|
||||
socketio.emit("error", {"message": (str(e))})
|
||||
print("\n")
|
||||
traceback.print_exc()
|
||||
print("\n")
|
||||
|
||||
|
||||
"""
|
||||
END ADDITIONAL FUNCTIONS
|
||||
"""
|
||||
|
||||
|
||||
if __name__ == "__main__":
|
||||
print(f">> Starting server at http://{host}:{port}")
|
||||
socketio.run(app, host=host, port=port)
|
@ -1,54 +0,0 @@
|
||||
model:
|
||||
base_learning_rate: 4.5e-6
|
||||
target: ldm.models.autoencoder.AutoencoderKL
|
||||
params:
|
||||
monitor: "val/rec_loss"
|
||||
embed_dim: 16
|
||||
lossconfig:
|
||||
target: ldm.modules.losses.LPIPSWithDiscriminator
|
||||
params:
|
||||
disc_start: 50001
|
||||
kl_weight: 0.000001
|
||||
disc_weight: 0.5
|
||||
|
||||
ddconfig:
|
||||
double_z: True
|
||||
z_channels: 16
|
||||
resolution: 256
|
||||
in_channels: 3
|
||||
out_ch: 3
|
||||
ch: 128
|
||||
ch_mult: [ 1,1,2,2,4] # num_down = len(ch_mult)-1
|
||||
num_res_blocks: 2
|
||||
attn_resolutions: [16]
|
||||
dropout: 0.0
|
||||
|
||||
|
||||
data:
|
||||
target: main.DataModuleFromConfig
|
||||
params:
|
||||
batch_size: 12
|
||||
wrap: True
|
||||
train:
|
||||
target: ldm.data.imagenet.ImageNetSRTrain
|
||||
params:
|
||||
size: 256
|
||||
degradation: pil_nearest
|
||||
validation:
|
||||
target: ldm.data.imagenet.ImageNetSRValidation
|
||||
params:
|
||||
size: 256
|
||||
degradation: pil_nearest
|
||||
|
||||
lightning:
|
||||
callbacks:
|
||||
image_logger:
|
||||
target: main.ImageLogger
|
||||
params:
|
||||
batch_frequency: 1000
|
||||
max_images: 8
|
||||
increase_log_steps: True
|
||||
|
||||
trainer:
|
||||
benchmark: True
|
||||
accumulate_grad_batches: 2
|
@ -1,53 +0,0 @@
|
||||
model:
|
||||
base_learning_rate: 4.5e-6
|
||||
target: ldm.models.autoencoder.AutoencoderKL
|
||||
params:
|
||||
monitor: "val/rec_loss"
|
||||
embed_dim: 4
|
||||
lossconfig:
|
||||
target: ldm.modules.losses.LPIPSWithDiscriminator
|
||||
params:
|
||||
disc_start: 50001
|
||||
kl_weight: 0.000001
|
||||
disc_weight: 0.5
|
||||
|
||||
ddconfig:
|
||||
double_z: True
|
||||
z_channels: 4
|
||||
resolution: 256
|
||||
in_channels: 3
|
||||
out_ch: 3
|
||||
ch: 128
|
||||
ch_mult: [ 1,2,4,4 ] # num_down = len(ch_mult)-1
|
||||
num_res_blocks: 2
|
||||
attn_resolutions: [ ]
|
||||
dropout: 0.0
|
||||
|
||||
data:
|
||||
target: main.DataModuleFromConfig
|
||||
params:
|
||||
batch_size: 12
|
||||
wrap: True
|
||||
train:
|
||||
target: ldm.data.imagenet.ImageNetSRTrain
|
||||
params:
|
||||
size: 256
|
||||
degradation: pil_nearest
|
||||
validation:
|
||||
target: ldm.data.imagenet.ImageNetSRValidation
|
||||
params:
|
||||
size: 256
|
||||
degradation: pil_nearest
|
||||
|
||||
lightning:
|
||||
callbacks:
|
||||
image_logger:
|
||||
target: main.ImageLogger
|
||||
params:
|
||||
batch_frequency: 1000
|
||||
max_images: 8
|
||||
increase_log_steps: True
|
||||
|
||||
trainer:
|
||||
benchmark: True
|
||||
accumulate_grad_batches: 2
|
@ -1,54 +0,0 @@
|
||||
model:
|
||||
base_learning_rate: 4.5e-6
|
||||
target: ldm.models.autoencoder.AutoencoderKL
|
||||
params:
|
||||
monitor: "val/rec_loss"
|
||||
embed_dim: 3
|
||||
lossconfig:
|
||||
target: ldm.modules.losses.LPIPSWithDiscriminator
|
||||
params:
|
||||
disc_start: 50001
|
||||
kl_weight: 0.000001
|
||||
disc_weight: 0.5
|
||||
|
||||
ddconfig:
|
||||
double_z: True
|
||||
z_channels: 3
|
||||
resolution: 256
|
||||
in_channels: 3
|
||||
out_ch: 3
|
||||
ch: 128
|
||||
ch_mult: [ 1,2,4 ] # num_down = len(ch_mult)-1
|
||||
num_res_blocks: 2
|
||||
attn_resolutions: [ ]
|
||||
dropout: 0.0
|
||||
|
||||
|
||||
data:
|
||||
target: main.DataModuleFromConfig
|
||||
params:
|
||||
batch_size: 12
|
||||
wrap: True
|
||||
train:
|
||||
target: ldm.data.imagenet.ImageNetSRTrain
|
||||
params:
|
||||
size: 256
|
||||
degradation: pil_nearest
|
||||
validation:
|
||||
target: ldm.data.imagenet.ImageNetSRValidation
|
||||
params:
|
||||
size: 256
|
||||
degradation: pil_nearest
|
||||
|
||||
lightning:
|
||||
callbacks:
|
||||
image_logger:
|
||||
target: main.ImageLogger
|
||||
params:
|
||||
batch_frequency: 1000
|
||||
max_images: 8
|
||||
increase_log_steps: True
|
||||
|
||||
trainer:
|
||||
benchmark: True
|
||||
accumulate_grad_batches: 2
|
@ -1,53 +0,0 @@
|
||||
model:
|
||||
base_learning_rate: 4.5e-6
|
||||
target: ldm.models.autoencoder.AutoencoderKL
|
||||
params:
|
||||
monitor: "val/rec_loss"
|
||||
embed_dim: 64
|
||||
lossconfig:
|
||||
target: ldm.modules.losses.LPIPSWithDiscriminator
|
||||
params:
|
||||
disc_start: 50001
|
||||
kl_weight: 0.000001
|
||||
disc_weight: 0.5
|
||||
|
||||
ddconfig:
|
||||
double_z: True
|
||||
z_channels: 64
|
||||
resolution: 256
|
||||
in_channels: 3
|
||||
out_ch: 3
|
||||
ch: 128
|
||||
ch_mult: [ 1,1,2,2,4,4] # num_down = len(ch_mult)-1
|
||||
num_res_blocks: 2
|
||||
attn_resolutions: [16,8]
|
||||
dropout: 0.0
|
||||
|
||||
data:
|
||||
target: main.DataModuleFromConfig
|
||||
params:
|
||||
batch_size: 12
|
||||
wrap: True
|
||||
train:
|
||||
target: ldm.data.imagenet.ImageNetSRTrain
|
||||
params:
|
||||
size: 256
|
||||
degradation: pil_nearest
|
||||
validation:
|
||||
target: ldm.data.imagenet.ImageNetSRValidation
|
||||
params:
|
||||
size: 256
|
||||
degradation: pil_nearest
|
||||
|
||||
lightning:
|
||||
callbacks:
|
||||
image_logger:
|
||||
target: main.ImageLogger
|
||||
params:
|
||||
batch_frequency: 1000
|
||||
max_images: 8
|
||||
increase_log_steps: True
|
||||
|
||||
trainer:
|
||||
benchmark: True
|
||||
accumulate_grad_batches: 2
|
@ -1,86 +0,0 @@
|
||||
model:
|
||||
base_learning_rate: 2.0e-06
|
||||
target: ldm.models.diffusion.ddpm.LatentDiffusion
|
||||
params:
|
||||
linear_start: 0.0015
|
||||
linear_end: 0.0195
|
||||
num_timesteps_cond: 1
|
||||
log_every_t: 200
|
||||
timesteps: 1000
|
||||
first_stage_key: image
|
||||
image_size: 64
|
||||
channels: 3
|
||||
monitor: val/loss_simple_ema
|
||||
|
||||
unet_config:
|
||||
target: ldm.modules.diffusionmodules.openaimodel.UNetModel
|
||||
params:
|
||||
image_size: 64
|
||||
in_channels: 3
|
||||
out_channels: 3
|
||||
model_channels: 224
|
||||
attention_resolutions:
|
||||
# note: this isn\t actually the resolution but
|
||||
# the downsampling factor, i.e. this corresnponds to
|
||||
# attention on spatial resolution 8,16,32, as the
|
||||
# spatial reolution of the latents is 64 for f4
|
||||
- 8
|
||||
- 4
|
||||
- 2
|
||||
num_res_blocks: 2
|
||||
channel_mult:
|
||||
- 1
|
||||
- 2
|
||||
- 3
|
||||
- 4
|
||||
num_head_channels: 32
|
||||
first_stage_config:
|
||||
target: ldm.models.autoencoder.VQModelInterface
|
||||
params:
|
||||
embed_dim: 3
|
||||
n_embed: 8192
|
||||
ckpt_path: models/first_stage_models/vq-f4/model.ckpt
|
||||
ddconfig:
|
||||
double_z: false
|
||||
z_channels: 3
|
||||
resolution: 256
|
||||
in_channels: 3
|
||||
out_ch: 3
|
||||
ch: 128
|
||||
ch_mult:
|
||||
- 1
|
||||
- 2
|
||||
- 4
|
||||
num_res_blocks: 2
|
||||
attn_resolutions: []
|
||||
dropout: 0.0
|
||||
lossconfig:
|
||||
target: torch.nn.Identity
|
||||
cond_stage_config: __is_unconditional__
|
||||
data:
|
||||
target: main.DataModuleFromConfig
|
||||
params:
|
||||
batch_size: 48
|
||||
num_workers: 5
|
||||
wrap: false
|
||||
train:
|
||||
target: taming.data.faceshq.CelebAHQTrain
|
||||
params:
|
||||
size: 256
|
||||
validation:
|
||||
target: taming.data.faceshq.CelebAHQValidation
|
||||
params:
|
||||
size: 256
|
||||
|
||||
|
||||
lightning:
|
||||
callbacks:
|
||||
image_logger:
|
||||
target: main.ImageLogger
|
||||
params:
|
||||
batch_frequency: 5000
|
||||
max_images: 8
|
||||
increase_log_steps: False
|
||||
|
||||
trainer:
|
||||
benchmark: True
|
@ -1,98 +0,0 @@
|
||||
model:
|
||||
base_learning_rate: 1.0e-06
|
||||
target: ldm.models.diffusion.ddpm.LatentDiffusion
|
||||
params:
|
||||
linear_start: 0.0015
|
||||
linear_end: 0.0195
|
||||
num_timesteps_cond: 1
|
||||
log_every_t: 200
|
||||
timesteps: 1000
|
||||
first_stage_key: image
|
||||
cond_stage_key: class_label
|
||||
image_size: 32
|
||||
channels: 4
|
||||
cond_stage_trainable: true
|
||||
conditioning_key: crossattn
|
||||
monitor: val/loss_simple_ema
|
||||
unet_config:
|
||||
target: ldm.modules.diffusionmodules.openaimodel.UNetModel
|
||||
params:
|
||||
image_size: 32
|
||||
in_channels: 4
|
||||
out_channels: 4
|
||||
model_channels: 256
|
||||
attention_resolutions:
|
||||
#note: this isn\t actually the resolution but
|
||||
# the downsampling factor, i.e. this corresnponds to
|
||||
# attention on spatial resolution 8,16,32, as the
|
||||
# spatial reolution of the latents is 32 for f8
|
||||
- 4
|
||||
- 2
|
||||
- 1
|
||||
num_res_blocks: 2
|
||||
channel_mult:
|
||||
- 1
|
||||
- 2
|
||||
- 4
|
||||
num_head_channels: 32
|
||||
use_spatial_transformer: true
|
||||
transformer_depth: 1
|
||||
context_dim: 512
|
||||
first_stage_config:
|
||||
target: ldm.models.autoencoder.VQModelInterface
|
||||
params:
|
||||
embed_dim: 4
|
||||
n_embed: 16384
|
||||
ckpt_path: configs/first_stage_models/vq-f8/model.yaml
|
||||
ddconfig:
|
||||
double_z: false
|
||||
z_channels: 4
|
||||
resolution: 256
|
||||
in_channels: 3
|
||||
out_ch: 3
|
||||
ch: 128
|
||||
ch_mult:
|
||||
- 1
|
||||
- 2
|
||||
- 2
|
||||
- 4
|
||||
num_res_blocks: 2
|
||||
attn_resolutions:
|
||||
- 32
|
||||
dropout: 0.0
|
||||
lossconfig:
|
||||
target: torch.nn.Identity
|
||||
cond_stage_config:
|
||||
target: ldm.modules.encoders.modules.ClassEmbedder
|
||||
params:
|
||||
embed_dim: 512
|
||||
key: class_label
|
||||
data:
|
||||
target: main.DataModuleFromConfig
|
||||
params:
|
||||
batch_size: 64
|
||||
num_workers: 12
|
||||
wrap: false
|
||||
train:
|
||||
target: ldm.data.imagenet.ImageNetTrain
|
||||
params:
|
||||
config:
|
||||
size: 256
|
||||
validation:
|
||||
target: ldm.data.imagenet.ImageNetValidation
|
||||
params:
|
||||
config:
|
||||
size: 256
|
||||
|
||||
|
||||
lightning:
|
||||
callbacks:
|
||||
image_logger:
|
||||
target: main.ImageLogger
|
||||
params:
|
||||
batch_frequency: 5000
|
||||
max_images: 8
|
||||
increase_log_steps: False
|
||||
|
||||
trainer:
|
||||
benchmark: True
|
@ -1,68 +0,0 @@
|
||||
model:
|
||||
base_learning_rate: 0.0001
|
||||
target: ldm.models.diffusion.ddpm.LatentDiffusion
|
||||
params:
|
||||
linear_start: 0.0015
|
||||
linear_end: 0.0195
|
||||
num_timesteps_cond: 1
|
||||
log_every_t: 200
|
||||
timesteps: 1000
|
||||
first_stage_key: image
|
||||
cond_stage_key: class_label
|
||||
image_size: 64
|
||||
channels: 3
|
||||
cond_stage_trainable: true
|
||||
conditioning_key: crossattn
|
||||
monitor: val/loss
|
||||
use_ema: False
|
||||
|
||||
unet_config:
|
||||
target: ldm.modules.diffusionmodules.openaimodel.UNetModel
|
||||
params:
|
||||
image_size: 64
|
||||
in_channels: 3
|
||||
out_channels: 3
|
||||
model_channels: 192
|
||||
attention_resolutions:
|
||||
- 8
|
||||
- 4
|
||||
- 2
|
||||
num_res_blocks: 2
|
||||
channel_mult:
|
||||
- 1
|
||||
- 2
|
||||
- 3
|
||||
- 5
|
||||
num_heads: 1
|
||||
use_spatial_transformer: true
|
||||
transformer_depth: 1
|
||||
context_dim: 512
|
||||
|
||||
first_stage_config:
|
||||
target: ldm.models.autoencoder.VQModelInterface
|
||||
params:
|
||||
embed_dim: 3
|
||||
n_embed: 8192
|
||||
ddconfig:
|
||||
double_z: false
|
||||
z_channels: 3
|
||||
resolution: 256
|
||||
in_channels: 3
|
||||
out_ch: 3
|
||||
ch: 128
|
||||
ch_mult:
|
||||
- 1
|
||||
- 2
|
||||
- 4
|
||||
num_res_blocks: 2
|
||||
attn_resolutions: []
|
||||
dropout: 0.0
|
||||
lossconfig:
|
||||
target: torch.nn.Identity
|
||||
|
||||
cond_stage_config:
|
||||
target: ldm.modules.encoders.modules.ClassEmbedder
|
||||
params:
|
||||
n_classes: 1001
|
||||
embed_dim: 512
|
||||
key: class_label
|
@ -1,85 +0,0 @@
|
||||
model:
|
||||
base_learning_rate: 2.0e-06
|
||||
target: ldm.models.diffusion.ddpm.LatentDiffusion
|
||||
params:
|
||||
linear_start: 0.0015
|
||||
linear_end: 0.0195
|
||||
num_timesteps_cond: 1
|
||||
log_every_t: 200
|
||||
timesteps: 1000
|
||||
first_stage_key: image
|
||||
image_size: 64
|
||||
channels: 3
|
||||
monitor: val/loss_simple_ema
|
||||
unet_config:
|
||||
target: ldm.modules.diffusionmodules.openaimodel.UNetModel
|
||||
params:
|
||||
image_size: 64
|
||||
in_channels: 3
|
||||
out_channels: 3
|
||||
model_channels: 224
|
||||
attention_resolutions:
|
||||
# note: this isn\t actually the resolution but
|
||||
# the downsampling factor, i.e. this corresnponds to
|
||||
# attention on spatial resolution 8,16,32, as the
|
||||
# spatial reolution of the latents is 64 for f4
|
||||
- 8
|
||||
- 4
|
||||
- 2
|
||||
num_res_blocks: 2
|
||||
channel_mult:
|
||||
- 1
|
||||
- 2
|
||||
- 3
|
||||
- 4
|
||||
num_head_channels: 32
|
||||
first_stage_config:
|
||||
target: ldm.models.autoencoder.VQModelInterface
|
||||
params:
|
||||
embed_dim: 3
|
||||
n_embed: 8192
|
||||
ckpt_path: configs/first_stage_models/vq-f4/model.yaml
|
||||
ddconfig:
|
||||
double_z: false
|
||||
z_channels: 3
|
||||
resolution: 256
|
||||
in_channels: 3
|
||||
out_ch: 3
|
||||
ch: 128
|
||||
ch_mult:
|
||||
- 1
|
||||
- 2
|
||||
- 4
|
||||
num_res_blocks: 2
|
||||
attn_resolutions: []
|
||||
dropout: 0.0
|
||||
lossconfig:
|
||||
target: torch.nn.Identity
|
||||
cond_stage_config: __is_unconditional__
|
||||
data:
|
||||
target: main.DataModuleFromConfig
|
||||
params:
|
||||
batch_size: 42
|
||||
num_workers: 5
|
||||
wrap: false
|
||||
train:
|
||||
target: taming.data.faceshq.FFHQTrain
|
||||
params:
|
||||
size: 256
|
||||
validation:
|
||||
target: taming.data.faceshq.FFHQValidation
|
||||
params:
|
||||
size: 256
|
||||
|
||||
|
||||
lightning:
|
||||
callbacks:
|
||||
image_logger:
|
||||
target: main.ImageLogger
|
||||
params:
|
||||
batch_frequency: 5000
|
||||
max_images: 8
|
||||
increase_log_steps: False
|
||||
|
||||
trainer:
|
||||
benchmark: True
|
@ -1,85 +0,0 @@
|
||||
model:
|
||||
base_learning_rate: 2.0e-06
|
||||
target: ldm.models.diffusion.ddpm.LatentDiffusion
|
||||
params:
|
||||
linear_start: 0.0015
|
||||
linear_end: 0.0195
|
||||
num_timesteps_cond: 1
|
||||
log_every_t: 200
|
||||
timesteps: 1000
|
||||
first_stage_key: image
|
||||
image_size: 64
|
||||
channels: 3
|
||||
monitor: val/loss_simple_ema
|
||||
unet_config:
|
||||
target: ldm.modules.diffusionmodules.openaimodel.UNetModel
|
||||
params:
|
||||
image_size: 64
|
||||
in_channels: 3
|
||||
out_channels: 3
|
||||
model_channels: 224
|
||||
attention_resolutions:
|
||||
# note: this isn\t actually the resolution but
|
||||
# the downsampling factor, i.e. this corresnponds to
|
||||
# attention on spatial resolution 8,16,32, as the
|
||||
# spatial reolution of the latents is 64 for f4
|
||||
- 8
|
||||
- 4
|
||||
- 2
|
||||
num_res_blocks: 2
|
||||
channel_mult:
|
||||
- 1
|
||||
- 2
|
||||
- 3
|
||||
- 4
|
||||
num_head_channels: 32
|
||||
first_stage_config:
|
||||
target: ldm.models.autoencoder.VQModelInterface
|
||||
params:
|
||||
ckpt_path: configs/first_stage_models/vq-f4/model.yaml
|
||||
embed_dim: 3
|
||||
n_embed: 8192
|
||||
ddconfig:
|
||||
double_z: false
|
||||
z_channels: 3
|
||||
resolution: 256
|
||||
in_channels: 3
|
||||
out_ch: 3
|
||||
ch: 128
|
||||
ch_mult:
|
||||
- 1
|
||||
- 2
|
||||
- 4
|
||||
num_res_blocks: 2
|
||||
attn_resolutions: []
|
||||
dropout: 0.0
|
||||
lossconfig:
|
||||
target: torch.nn.Identity
|
||||
cond_stage_config: __is_unconditional__
|
||||
data:
|
||||
target: main.DataModuleFromConfig
|
||||
params:
|
||||
batch_size: 48
|
||||
num_workers: 5
|
||||
wrap: false
|
||||
train:
|
||||
target: ldm.data.lsun.LSUNBedroomsTrain
|
||||
params:
|
||||
size: 256
|
||||
validation:
|
||||
target: ldm.data.lsun.LSUNBedroomsValidation
|
||||
params:
|
||||
size: 256
|
||||
|
||||
|
||||
lightning:
|
||||
callbacks:
|
||||
image_logger:
|
||||
target: main.ImageLogger
|
||||
params:
|
||||
batch_frequency: 5000
|
||||
max_images: 8
|
||||
increase_log_steps: False
|
||||
|
||||
trainer:
|
||||
benchmark: True
|
@ -1,91 +0,0 @@
|
||||
model:
|
||||
base_learning_rate: 5.0e-5 # set to target_lr by starting main.py with '--scale_lr False'
|
||||
target: ldm.models.diffusion.ddpm.LatentDiffusion
|
||||
params:
|
||||
linear_start: 0.0015
|
||||
linear_end: 0.0155
|
||||
num_timesteps_cond: 1
|
||||
log_every_t: 200
|
||||
timesteps: 1000
|
||||
loss_type: l1
|
||||
first_stage_key: "image"
|
||||
cond_stage_key: "image"
|
||||
image_size: 32
|
||||
channels: 4
|
||||
cond_stage_trainable: False
|
||||
concat_mode: False
|
||||
scale_by_std: True
|
||||
monitor: 'val/loss_simple_ema'
|
||||
|
||||
scheduler_config: # 10000 warmup steps
|
||||
target: ldm.lr_scheduler.LambdaLinearScheduler
|
||||
params:
|
||||
warm_up_steps: [10000]
|
||||
cycle_lengths: [10000000000000]
|
||||
f_start: [1.e-6]
|
||||
f_max: [1.]
|
||||
f_min: [ 1.]
|
||||
|
||||
unet_config:
|
||||
target: ldm.modules.diffusionmodules.openaimodel.UNetModel
|
||||
params:
|
||||
image_size: 32
|
||||
in_channels: 4
|
||||
out_channels: 4
|
||||
model_channels: 192
|
||||
attention_resolutions: [ 1, 2, 4, 8 ] # 32, 16, 8, 4
|
||||
num_res_blocks: 2
|
||||
channel_mult: [ 1,2,2,4,4 ] # 32, 16, 8, 4, 2
|
||||
num_heads: 8
|
||||
use_scale_shift_norm: True
|
||||
resblock_updown: True
|
||||
|
||||
first_stage_config:
|
||||
target: ldm.models.autoencoder.AutoencoderKL
|
||||
params:
|
||||
embed_dim: 4
|
||||
monitor: "val/rec_loss"
|
||||
ckpt_path: "models/first_stage_models/kl-f8/model.ckpt"
|
||||
ddconfig:
|
||||
double_z: True
|
||||
z_channels: 4
|
||||
resolution: 256
|
||||
in_channels: 3
|
||||
out_ch: 3
|
||||
ch: 128
|
||||
ch_mult: [ 1,2,4,4 ] # num_down = len(ch_mult)-1
|
||||
num_res_blocks: 2
|
||||
attn_resolutions: [ ]
|
||||
dropout: 0.0
|
||||
lossconfig:
|
||||
target: torch.nn.Identity
|
||||
|
||||
cond_stage_config: "__is_unconditional__"
|
||||
|
||||
data:
|
||||
target: main.DataModuleFromConfig
|
||||
params:
|
||||
batch_size: 96
|
||||
num_workers: 5
|
||||
wrap: False
|
||||
train:
|
||||
target: ldm.data.lsun.LSUNChurchesTrain
|
||||
params:
|
||||
size: 256
|
||||
validation:
|
||||
target: ldm.data.lsun.LSUNChurchesValidation
|
||||
params:
|
||||
size: 256
|
||||
|
||||
lightning:
|
||||
callbacks:
|
||||
image_logger:
|
||||
target: main.ImageLogger
|
||||
params:
|
||||
batch_frequency: 5000
|
||||
max_images: 8
|
||||
increase_log_steps: False
|
||||
|
||||
|
||||
trainer:
|
||||
benchmark: True
|
@ -1,71 +0,0 @@
|
||||
model:
|
||||
base_learning_rate: 5.0e-05
|
||||
target: ldm.models.diffusion.ddpm.LatentDiffusion
|
||||
params:
|
||||
linear_start: 0.00085
|
||||
linear_end: 0.012
|
||||
num_timesteps_cond: 1
|
||||
log_every_t: 200
|
||||
timesteps: 1000
|
||||
first_stage_key: image
|
||||
cond_stage_key: caption
|
||||
image_size: 32
|
||||
channels: 4
|
||||
cond_stage_trainable: true
|
||||
conditioning_key: crossattn
|
||||
monitor: val/loss_simple_ema
|
||||
scale_factor: 0.18215
|
||||
use_ema: False
|
||||
|
||||
unet_config:
|
||||
target: ldm.modules.diffusionmodules.openaimodel.UNetModel
|
||||
params:
|
||||
image_size: 32
|
||||
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: 1280
|
||||
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.BERTEmbedder
|
||||
params:
|
||||
n_embed: 1280
|
||||
n_layer: 32
|
@ -1,18 +0,0 @@
|
||||
# This file describes the alternative machine learning models
|
||||
# available to the dream 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.
|
||||
|
||||
laion400m:
|
||||
config: configs/latent-diffusion/txt2img-1p4B-eval.yaml
|
||||
weights: models/ldm/text2img-large/model.ckpt
|
||||
width: 256
|
||||
height: 256
|
||||
stable-diffusion-1.4:
|
||||
config: configs/stable-diffusion/v1-inference.yaml
|
||||
weights: models/ldm/stable-diffusion-v1/model.ckpt
|
||||
width: 512
|
||||
height: 512
|
@ -1,68 +0,0 @@
|
||||
model:
|
||||
base_learning_rate: 0.0001
|
||||
target: ldm.models.diffusion.ddpm.LatentDiffusion
|
||||
params:
|
||||
linear_start: 0.0015
|
||||
linear_end: 0.015
|
||||
num_timesteps_cond: 1
|
||||
log_every_t: 200
|
||||
timesteps: 1000
|
||||
first_stage_key: jpg
|
||||
cond_stage_key: nix
|
||||
image_size: 48
|
||||
channels: 16
|
||||
cond_stage_trainable: false
|
||||
conditioning_key: crossattn
|
||||
monitor: val/loss_simple_ema
|
||||
scale_by_std: false
|
||||
scale_factor: 0.22765929
|
||||
unet_config:
|
||||
target: ldm.modules.diffusionmodules.openaimodel.UNetModel
|
||||
params:
|
||||
image_size: 48
|
||||
in_channels: 16
|
||||
out_channels: 16
|
||||
model_channels: 448
|
||||
attention_resolutions:
|
||||
- 4
|
||||
- 2
|
||||
- 1
|
||||
num_res_blocks: 2
|
||||
channel_mult:
|
||||
- 1
|
||||
- 2
|
||||
- 3
|
||||
- 4
|
||||
use_scale_shift_norm: false
|
||||
resblock_updown: false
|
||||
num_head_channels: 32
|
||||
use_spatial_transformer: true
|
||||
transformer_depth: 1
|
||||
context_dim: 768
|
||||
use_checkpoint: true
|
||||
first_stage_config:
|
||||
target: ldm.models.autoencoder.AutoencoderKL
|
||||
params:
|
||||
monitor: val/rec_loss
|
||||
embed_dim: 16
|
||||
ddconfig:
|
||||
double_z: true
|
||||
z_channels: 16
|
||||
resolution: 256
|
||||
in_channels: 3
|
||||
out_ch: 3
|
||||
ch: 128
|
||||
ch_mult:
|
||||
- 1
|
||||
- 1
|
||||
- 2
|
||||
- 2
|
||||
- 4
|
||||
num_res_blocks: 2
|
||||
attn_resolutions:
|
||||
- 16
|
||||
dropout: 0.0
|
||||
lossconfig:
|
||||
target: torch.nn.Identity
|
||||
cond_stage_config:
|
||||
target: torch.nn.Identity
|
@ -1,110 +0,0 @@
|
||||
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
|
||||
|
@ -1,79 +0,0 @@
|
||||
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: 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
|
@ -1,110 +0,0 @@
|
||||
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
|
||||
|
@ -1,57 +0,0 @@
|
||||
FROM debian
|
||||
|
||||
ARG gsd
|
||||
ENV GITHUB_STABLE_DIFFUSION $gsd
|
||||
|
||||
ARG rsd
|
||||
ENV REQS $rsd
|
||||
|
||||
ARG cs
|
||||
ENV CONDA_SUBDIR $cs
|
||||
|
||||
ENV PIP_EXISTS_ACTION="w"
|
||||
|
||||
# TODO: Optimize image size
|
||||
|
||||
SHELL ["/bin/bash", "-c"]
|
||||
|
||||
WORKDIR /
|
||||
RUN apt update && apt upgrade -y \
|
||||
&& apt install -y \
|
||||
git \
|
||||
libgl1-mesa-glx \
|
||||
libglib2.0-0 \
|
||||
pip \
|
||||
python3 \
|
||||
&& git clone $GITHUB_STABLE_DIFFUSION
|
||||
|
||||
# Install Anaconda or Miniconda
|
||||
COPY anaconda.sh .
|
||||
RUN bash anaconda.sh -b -u -p /anaconda && /anaconda/bin/conda init bash
|
||||
|
||||
# SD
|
||||
WORKDIR /stable-diffusion
|
||||
RUN source ~/.bashrc \
|
||||
&& conda create -y --name ldm && conda activate ldm \
|
||||
&& conda config --env --set subdir $CONDA_SUBDIR \
|
||||
&& pip3 install -r $REQS \
|
||||
&& pip3 install basicsr facexlib realesrgan \
|
||||
&& mkdir models/ldm/stable-diffusion-v1 \
|
||||
&& ln -s "/data/sd-v1-4.ckpt" models/ldm/stable-diffusion-v1/model.ckpt
|
||||
|
||||
# Face restoreation
|
||||
# by default expected in a sibling directory to stable-diffusion
|
||||
WORKDIR /
|
||||
RUN git clone https://github.com/TencentARC/GFPGAN.git
|
||||
|
||||
WORKDIR /GFPGAN
|
||||
RUN pip3 install -r requirements.txt \
|
||||
&& python3 setup.py develop \
|
||||
&& ln -s "/data/GFPGANv1.4.pth" experiments/pretrained_models/GFPGANv1.4.pth
|
||||
|
||||
WORKDIR /stable-diffusion
|
||||
RUN python3 scripts/preload_models.py
|
||||
|
||||
WORKDIR /
|
||||
COPY entrypoint.sh .
|
||||
ENTRYPOINT ["/entrypoint.sh"]
|
@ -1,10 +0,0 @@
|
||||
#!/bin/bash
|
||||
|
||||
cd /stable-diffusion
|
||||
|
||||
if [ $# -eq 0 ]; then
|
||||
python3 scripts/dream.py --full_precision -o /data
|
||||
# bash
|
||||
else
|
||||
python3 scripts/dream.py --full_precision -o /data "$@"
|
||||
fi
|
103
docker/Dockerfile
Normal file
@ -0,0 +1,103 @@
|
||||
# syntax=docker/dockerfile:1
|
||||
|
||||
ARG PYTHON_VERSION=3.9
|
||||
##################
|
||||
## base image ##
|
||||
##################
|
||||
FROM python:${PYTHON_VERSION}-slim AS python-base
|
||||
|
||||
LABEL org.opencontainers.image.authors="mauwii@outlook.de"
|
||||
|
||||
# prepare 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 necessary packages
|
||||
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 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},sharing=locked \
|
||||
python3 -m venv "${APPNAME}" \
|
||||
--upgrade-deps
|
||||
|
||||
# copy sources
|
||||
COPY --link . .
|
||||
|
||||
# install pyproject.toml
|
||||
ARG PIP_EXTRA_INDEX_URL
|
||||
ENV PIP_EXTRA_INDEX_URL ${PIP_EXTRA_INDEX_URL}
|
||||
RUN --mount=type=cache,target=${PIP_CACHE_DIR},sharing=locked \
|
||||
"${APPNAME}/bin/pip" install .
|
||||
|
||||
# build patchmatch
|
||||
RUN python3 -c "from patchmatch import patch_match"
|
||||
|
||||
#####################
|
||||
## runtime image ##
|
||||
#####################
|
||||
FROM python-base AS runtime
|
||||
|
||||
# Create a new user
|
||||
ARG UNAME=appuser
|
||||
RUN useradd \
|
||||
--no-log-init \
|
||||
-m \
|
||||
-U \
|
||||
"${UNAME}"
|
||||
|
||||
# create volume directory
|
||||
ARG VOLUME_DIR=/data
|
||||
RUN mkdir -p "${VOLUME_DIR}" \
|
||||
&& chown -R "${UNAME}" "${VOLUME_DIR}"
|
||||
|
||||
# setup runtime environment
|
||||
USER ${UNAME}
|
||||
COPY --chown=${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}" ]
|
51
docker/build.sh
Executable file
@ -0,0 +1,51 @@
|
||||
#!/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_BUILDKIT=1 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="${DOCKERFILE}" \
|
||||
..
|
51
docker/env.sh
Normal file
@ -0,0 +1,51 @@
|
||||
#!/usr/bin/env bash
|
||||
|
||||
# This file is used to set environment variables for the build.sh and run.sh scripts.
|
||||
|
||||
# Try to detect the container flavor if no PIP_EXTRA_INDEX_URL got specified
|
||||
if [[ -z "$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="${CONTAINER_IMAGE,,}"
|
41
docker/run.sh
Executable file
@ -0,0 +1,41 @@
|
||||
#!/usr/bin/env bash
|
||||
set -e
|
||||
|
||||
# How to use: https://invoke-ai.github.io/InvokeAI/installation/040_INSTALL_DOCKER/
|
||||
|
||||
SCRIPTDIR=$(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=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}" ${@:+$@}
|
||||
|
||||
# Remove Trash folder
|
||||
for f in outputs/.Trash*; do
|
||||
if [ -e "$f" ]; then
|
||||
rm -Rf "$f"
|
||||
break
|
||||
fi
|
||||
done
|
5
docs/.markdownlint.jsonc
Normal file
@ -0,0 +1,5 @@
|
||||
{
|
||||
"MD046": false,
|
||||
"MD007": false,
|
||||
"MD030": false
|
||||
}
|
@ -1,64 +1,510 @@
|
||||
# **Changelog**
|
||||
---
|
||||
title: Changelog
|
||||
---
|
||||
|
||||
## v1.13 (in process)
|
||||
# :octicons-log-16: **Changelog**
|
||||
|
||||
- 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)
|
||||
- WebUI supports incremental display of in-progress images during generation [Kevin Gibbons](https://github.com/bakkot)
|
||||
- Output directory can be specified on the invoke> command line.
|
||||
- The grid was displaying duplicated images when not enough images to fill the final row [Muhammad Usama](https://github.com/SMUsamaShah)
|
||||
## v2.3.0 <small>(15 January 2023)</small>
|
||||
|
||||
**Transition to diffusers
|
||||
|
||||
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)
|
||||
|
||||
## v2.0.0 <small>(9 October 2022)</small>
|
||||
|
||||
- `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 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:
|
||||
- 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`.
|
||||
|
||||
## 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)).
|
||||
- Inpainting support.
|
||||
- Improved web server GUI.
|
||||
- Lots of code and documentation cleanups.
|
||||
|
||||
## 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)
|
||||
- WebUI supports GFPGAN/ESRGAN facial reconstruction and upscaling
|
||||
[Kevin Gibbons](https://github.com/bakkot)
|
||||
- WebUI supports incremental display of in-progress images during generation
|
||||
[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))
|
||||
- Can specify --grid on invoke.py command line as the default.
|
||||
- Miscellaneous internal bug and stability fixes.
|
||||
- Works on M1 Apple hardware.
|
||||
- Multiple bug fixes.
|
||||
|
||||
---
|
||||
|
||||
## v1.12 (28 August 2022)
|
||||
## v1.12 <small>(28 August 2022)</small>
|
||||
|
||||
- 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 (26 August 2022)
|
||||
## 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 (25 August 2022)
|
||||
## 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 (24 August 2022)
|
||||
## 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 (24 August 2022)
|
||||
## 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.
|
||||
@ -66,40 +512,42 @@
|
||||
|
||||
---
|
||||
|
||||
## v1.07 (23 August 2022)
|
||||
## 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 (23 August 2022)
|
||||
## 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 (22 August 2022 - after the drop)
|
||||
## 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.
|
||||
|
||||
---
|
||||
|
||||
## v1.04 (22 August 2022 - after the drop)
|
||||
## v1.04 <small>(22 August 2022 - after the drop)</small>
|
||||
|
||||
- Updated README to reflect installation of the released weights.
|
||||
- Suppressed very noisy and inconsequential warning when loading the frozen CLIP
|
||||
@ -107,31 +555,33 @@
|
||||
|
||||
---
|
||||
|
||||
## v1.03 (22 August 2022)
|
||||
## 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 (21 August 2022)
|
||||
## 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 (21 August 2022)
|
||||
## 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
|
||||
|
||||
---
|
||||
|
||||
## Links
|
||||
|
||||
- **[Read Me](../readme.md)**
|
||||
- **[Read Me](index.md)**
|
||||
|
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docs/assets/Lincoln-and-Parrot-512-transparent.png
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docs/assets/Lincoln-and-Parrot-512.png
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docs/assets/canvas/biker_granny.png
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docs/assets/concepts/image1.png
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docs/assets/concepts/image3.png
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docs/assets/concepts/image5.png
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docs/assets/inpainting/000019.curly.hair.deselected.png
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docs/assets/inpainting/000019.curly.hair.masked.png
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docs/assets/inpainting/000019.curly.hair.selected.png
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docs/assets/inpainting/000024.801380492.png
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docs/assets/installer-walkthrough/choose-gpu.png
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docs/assets/installer-walkthrough/confirm-directory.png
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docs/assets/installer-walkthrough/downloading-models.png
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docs/assets/installer-walkthrough/installing-models.png
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docs/assets/installer-walkthrough/settings-form.png
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docs/assets/installer-walkthrough/unpacked-zipfile.png
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docs/assets/installing-models/webui-models-1.png
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docs/assets/installing-models/webui-models-2.png
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docs/assets/installing-models/webui-models-3.png
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docs/assets/installing-models/webui-models-4.png
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docs/assets/invoke-web-server-1.png
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docs/assets/invoke-web-server-2.png
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docs/assets/invoke-web-server-3.png
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docs/assets/invoke-web-server-4.png
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docs/assets/invoke-web-server-5.png
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docs/assets/invoke-web-server-7.png
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docs/assets/invoke-web-server-8.png
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docs/assets/invoke-web-server-9.png
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docs/assets/invoke_ai_banner.png
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docs/assets/invoke_web_dark.png
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docs/assets/invoke_web_light.png
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After Width: | Height: | Size: 838 KiB |
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docs/assets/invoke_web_server.png
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docs/assets/outpainting/curly-outcrop-2.png
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After Width: | Height: | Size: 635 KiB |
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docs/assets/prompt_syntax/apricots--1.png
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