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release_0.
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invokeai-b
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80c0e30099 | |||
ac440a1197 | |||
bb46c70ec5 |
6
.coveragerc
Normal file
@ -0,0 +1,6 @@
|
||||
[run]
|
||||
omit='.env/*'
|
||||
source='.'
|
||||
|
||||
[report]
|
||||
show_missing = true
|
32
.dev_scripts/diff_images.py
Normal file
@ -0,0 +1,32 @@
|
||||
import argparse
|
||||
|
||||
import numpy as np
|
||||
from PIL import Image
|
||||
|
||||
|
||||
def read_image_int16(image_path):
|
||||
image = Image.open(image_path)
|
||||
return np.array(image).astype(np.int16)
|
||||
|
||||
|
||||
def calc_images_mean_L1(image1_path, image2_path):
|
||||
image1 = read_image_int16(image1_path)
|
||||
image2 = read_image_int16(image2_path)
|
||||
assert image1.shape == image2.shape
|
||||
|
||||
mean_L1 = np.abs(image1 - image2).mean()
|
||||
return mean_L1
|
||||
|
||||
|
||||
def parse_args():
|
||||
parser = argparse.ArgumentParser()
|
||||
parser.add_argument('image1_path')
|
||||
parser.add_argument('image2_path')
|
||||
args = parser.parse_args()
|
||||
return args
|
||||
|
||||
|
||||
if __name__ == '__main__':
|
||||
args = parse_args()
|
||||
mean_L1 = calc_images_mean_L1(args.image1_path, args.image2_path)
|
||||
print(mean_L1)
|
After Width: | Height: | Size: 416 KiB |
1
.dev_scripts/sample_command.txt
Normal file
@ -0,0 +1 @@
|
||||
"a photograph of an astronaut riding a horse" -s50 -S42
|
19
.dev_scripts/test_regression_txt2img_dream_v1_4.sh
Normal file
@ -0,0 +1,19 @@
|
||||
# generate an image
|
||||
PROMPT_FILE=".dev_scripts/sample_command.txt"
|
||||
OUT_DIR="outputs/img-samples/test_regression_txt2img_v1_4"
|
||||
SAMPLES_DIR=${OUT_DIR}
|
||||
python scripts/dream.py \
|
||||
--from_file ${PROMPT_FILE} \
|
||||
--outdir ${OUT_DIR} \
|
||||
--sampler plms
|
||||
|
||||
# original output by CompVis/stable-diffusion
|
||||
IMAGE1=".dev_scripts/images/v1_4_astronaut_rides_horse_plms_step50_seed42.png"
|
||||
# new output
|
||||
IMAGE2=`ls -A ${SAMPLES_DIR}/*.png | sort | tail -n 1`
|
||||
|
||||
echo ""
|
||||
echo "comparing the following two images"
|
||||
echo "IMAGE1: ${IMAGE1}"
|
||||
echo "IMAGE2: ${IMAGE2}"
|
||||
python .dev_scripts/diff_images.py ${IMAGE1} ${IMAGE2}
|
23
.dev_scripts/test_regression_txt2img_v1_4.sh
Normal file
@ -0,0 +1,23 @@
|
||||
# generate an image
|
||||
PROMPT="a photograph of an astronaut riding a horse"
|
||||
OUT_DIR="outputs/txt2img-samples/test_regression_txt2img_v1_4"
|
||||
SAMPLES_DIR="outputs/txt2img-samples/test_regression_txt2img_v1_4/samples"
|
||||
python scripts/orig_scripts/txt2img.py \
|
||||
--prompt "${PROMPT}" \
|
||||
--outdir ${OUT_DIR} \
|
||||
--plms \
|
||||
--ddim_steps 50 \
|
||||
--n_samples 1 \
|
||||
--n_iter 1 \
|
||||
--seed 42
|
||||
|
||||
# original output by CompVis/stable-diffusion
|
||||
IMAGE1=".dev_scripts/images/v1_4_astronaut_rides_horse_plms_step50_seed42.png"
|
||||
# new output
|
||||
IMAGE2=`ls -A ${SAMPLES_DIR}/*.png | sort | tail -n 1`
|
||||
|
||||
echo ""
|
||||
echo "comparing the following two images"
|
||||
echo "IMAGE1: ${IMAGE1}"
|
||||
echo "IMAGE2: ${IMAGE2}"
|
||||
python .dev_scripts/diff_images.py ${IMAGE1} ${IMAGE2}
|
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
|
4
.gitattributes
vendored
Normal file
@ -0,0 +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.
|
||||
# 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>
|
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.
|
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: ${{ secrets.GITHUB_TOKEN }}
|
29
.github/workflows/lint-frontend.yml
vendored
Normal file
@ -0,0 +1,29 @@
|
||||
name: Lint frontend
|
||||
|
||||
on:
|
||||
pull_request:
|
||||
paths:
|
||||
- 'invokeai/frontend/**'
|
||||
push:
|
||||
paths:
|
||||
- 'invokeai/frontend/**'
|
||||
|
||||
defaults:
|
||||
run:
|
||||
working-directory: invokeai/frontend
|
||||
|
||||
jobs:
|
||||
lint-frontend:
|
||||
if: github.event.pull_request.draft == false
|
||||
runs-on: ubuntu-22.04
|
||||
steps:
|
||||
- name: Setup Node 18
|
||||
uses: actions/setup-node@v3
|
||||
with:
|
||||
node-version: '18'
|
||||
- uses: actions/checkout@v3
|
||||
- run: 'yarn install --frozen-lockfile'
|
||||
- run: 'yarn tsc'
|
||||
- run: 'yarn run madge'
|
||||
- run: 'yarn run lint --max-warnings=0'
|
||||
- run: 'yarn run prettier --check'
|
49
.github/workflows/mkdocs-material.yml
vendored
Normal file
@ -0,0 +1,49 @@
|
||||
name: mkdocs-material
|
||||
on:
|
||||
push:
|
||||
branches:
|
||||
- 'main'
|
||||
- 'development'
|
||||
|
||||
jobs:
|
||||
mkdocs-material:
|
||||
if: github.event.pull_request.draft == false
|
||||
runs-on: ubuntu-latest
|
||||
env:
|
||||
REPO_URL: '${{ 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/*
|
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: ${{ env.INVOKEAI_OUTDIR }}
|
237
.gitignore
vendored
Normal file
@ -0,0 +1,237 @@
|
||||
# ignore default image save location and model symbolic link
|
||||
.idea/
|
||||
embeddings/
|
||||
outputs/
|
||||
models/ldm/stable-diffusion-v1/model.ckpt
|
||||
**/restoration/codeformer/weights
|
||||
|
||||
# ignore user models config
|
||||
configs/models.user.yaml
|
||||
config/models.user.yml
|
||||
invokeai.init
|
||||
|
||||
# ignore the Anaconda/Miniconda installer used while building Docker image
|
||||
anaconda.sh
|
||||
|
||||
# ignore a directory which serves as a place for initial images
|
||||
inputs/
|
||||
|
||||
# Byte-compiled / optimized / DLL files
|
||||
__pycache__/
|
||||
*.py[cod]
|
||||
*$py.class
|
||||
|
||||
# C extensions
|
||||
*.so
|
||||
|
||||
# emacs autosave and recovery files
|
||||
*~
|
||||
.#*
|
||||
|
||||
# Distribution / packaging
|
||||
.Python
|
||||
build/
|
||||
develop-eggs/
|
||||
dist/
|
||||
downloads/
|
||||
eggs/
|
||||
.eggs/
|
||||
lib/
|
||||
lib64/
|
||||
parts/
|
||||
sdist/
|
||||
var/
|
||||
wheels/
|
||||
pip-wheel-metadata/
|
||||
share/python-wheels/
|
||||
*.egg-info/
|
||||
.installed.cfg
|
||||
*.egg
|
||||
MANIFEST
|
||||
|
||||
# PyInstaller
|
||||
# Usually these files are written by a python script from a template
|
||||
# before PyInstaller builds the exe, so as to inject date/other infos into it.
|
||||
*.manifest
|
||||
*.spec
|
||||
|
||||
# Installer logs
|
||||
pip-log.txt
|
||||
pip-delete-this-directory.txt
|
||||
|
||||
# Unit test / coverage reports
|
||||
htmlcov/
|
||||
.tox/
|
||||
.nox/
|
||||
.coverage
|
||||
.coverage.*
|
||||
.cache
|
||||
nosetests.xml
|
||||
coverage.xml
|
||||
cov.xml
|
||||
*.cover
|
||||
*.py,cover
|
||||
.hypothesis/
|
||||
.pytest_cache/
|
||||
cover/
|
||||
junit/
|
||||
|
||||
# Translations
|
||||
*.mo
|
||||
*.pot
|
||||
|
||||
# Django stuff:
|
||||
*.log
|
||||
local_settings.py
|
||||
db.sqlite3
|
||||
db.sqlite3-journal
|
||||
|
||||
# Flask stuff:
|
||||
instance/
|
||||
.webassets-cache
|
||||
|
||||
# Scrapy stuff:
|
||||
.scrapy
|
||||
|
||||
# Sphinx documentation
|
||||
docs/_build/
|
||||
|
||||
# PyBuilder
|
||||
.pybuilder/
|
||||
target/
|
||||
|
||||
# Jupyter Notebook
|
||||
.ipynb_checkpoints
|
||||
|
||||
# IPython
|
||||
profile_default/
|
||||
ipython_config.py
|
||||
|
||||
# pyenv
|
||||
# For a library or package, you might want to ignore these files since the code is
|
||||
# intended to run in multiple environments; otherwise, check them in:
|
||||
# .python-version
|
||||
.python-version
|
||||
|
||||
# pipenv
|
||||
# According to pypa/pipenv#598, it is recommended to include Pipfile.lock in version control.
|
||||
# However, in case of collaboration, if having platform-specific dependencies or dependencies
|
||||
# having no cross-platform support, pipenv may install dependencies that don't work, or not
|
||||
# install all needed dependencies.
|
||||
#Pipfile.lock
|
||||
|
||||
# poetry
|
||||
# Similar to Pipfile.lock, it is generally recommended to include poetry.lock in version control.
|
||||
# This is especially recommended for binary packages to ensure reproducibility, and is more
|
||||
# commonly ignored for libraries.
|
||||
# https://python-poetry.org/docs/basic-usage/#commit-your-poetrylock-file-to-version-control
|
||||
#poetry.lock
|
||||
|
||||
# pdm
|
||||
# Similar to Pipfile.lock, it is generally recommended to include pdm.lock in version control.
|
||||
#pdm.lock
|
||||
# pdm stores project-wide configurations in .pdm.toml, but it is recommended to not include it
|
||||
# in version control.
|
||||
# https://pdm.fming.dev/#use-with-ide
|
||||
.pdm.toml
|
||||
|
||||
# PEP 582; used by e.g. github.com/David-OConnor/pyflow
|
||||
__pypackages__/
|
||||
|
||||
# Celery stuff
|
||||
celerybeat-schedule
|
||||
celerybeat.pid
|
||||
|
||||
# SageMath parsed files
|
||||
*.sage.py
|
||||
|
||||
# Environments
|
||||
.env
|
||||
.venv
|
||||
env/
|
||||
venv/
|
||||
ENV/
|
||||
env.bak/
|
||||
venv.bak/
|
||||
|
||||
# Spyder project settings
|
||||
.spyderproject
|
||||
.spyproject
|
||||
|
||||
# Rope project settings
|
||||
.ropeproject
|
||||
|
||||
# mkdocs documentation
|
||||
/site
|
||||
|
||||
# mypy
|
||||
.mypy_cache/
|
||||
.dmypy.json
|
||||
dmypy.json
|
||||
|
||||
# Pyre type checker
|
||||
.pyre/
|
||||
|
||||
# pytype static type analyzer
|
||||
.pytype/
|
||||
|
||||
# Cython debug symbols
|
||||
cython_debug/
|
||||
|
||||
# PyCharm
|
||||
# JetBrains specific template is maintained in a separate JetBrains.gitignore that can
|
||||
# be found at https://github.com/github/gitignore/blob/main/Global/JetBrains.gitignore
|
||||
# and can be added to the global gitignore or merged into this file. For a more nuclear
|
||||
# option (not recommended) you can uncomment the following to ignore the entire idea folder.
|
||||
#.idea/
|
||||
|
||||
src
|
||||
**/__pycache__/
|
||||
outputs
|
||||
|
||||
# Logs and associated folders
|
||||
# created from generated embeddings.
|
||||
logs
|
||||
testtube
|
||||
checkpoints
|
||||
# If it's a Mac
|
||||
.DS_Store
|
||||
|
||||
# Let the frontend manage its own gitignore
|
||||
!invokeai/frontend/*
|
||||
|
||||
# Scratch folder
|
||||
.scratch/
|
||||
.vscode/
|
||||
gfpgan/
|
||||
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
|
0
.gitmodules
vendored
Normal file
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
|
19
.prettierrc.yaml
Normal file
@ -0,0 +1,19 @@
|
||||
embeddedLanguageFormatting: auto
|
||||
endOfLine: lf
|
||||
singleQuote: true
|
||||
semi: true
|
||||
trailingComma: es5
|
||||
useTabs: false
|
||||
overrides:
|
||||
- files: '*.md'
|
||||
options:
|
||||
proseWrap: always
|
||||
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.
|
17
LICENSE
@ -1,9 +1,16 @@
|
||||
All rights reserved by the authors.
|
||||
You must not distribute the weights provided to you directly or indirectly without explicit consent of the authors.
|
||||
You must not distribute harmful, offensive, dehumanizing content or otherwise harmful representations of people or their environments, cultures, religions, etc. produced with the model weights
|
||||
or other generated content described in the "Misuse and Malicious Use" section in the model card.
|
||||
The model weights are provided for research purposes only.
|
||||
MIT License
|
||||
|
||||
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
|
||||
in the Software without restriction, including without limitation the rights
|
||||
to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
|
||||
copies of the Software, and to permit persons to whom the Software is
|
||||
furnished to do so, subject to the following conditions:
|
||||
|
||||
The above copyright notice and this permission notice shall be included in all
|
||||
copies or substantial portions of the Software.
|
||||
|
||||
THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
|
||||
IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
|
||||
|
294
LICENSE-ModelWeights.txt
Normal file
@ -0,0 +1,294 @@
|
||||
Copyright (c) 2022 Robin Rombach and Patrick Esser and contributors
|
||||
|
||||
CreativeML Open RAIL-M
|
||||
dated August 22, 2022
|
||||
|
||||
Section I: PREAMBLE
|
||||
|
||||
Multimodal generative models are being widely adopted and used, and
|
||||
have the potential to transform the way artists, among other
|
||||
individuals, conceive and benefit from AI or ML technologies as a tool
|
||||
for content creation.
|
||||
|
||||
Notwithstanding the current and potential benefits that these
|
||||
artifacts can bring to society at large, there are also concerns about
|
||||
potential misuses of them, either due to their technical limitations
|
||||
or ethical considerations.
|
||||
|
||||
In short, this license strives for both the open and responsible
|
||||
downstream use of the accompanying model. When it comes to the open
|
||||
character, we took inspiration from open source permissive licenses
|
||||
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|
||||
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|
||||
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|
||||
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|
||||
Model may occur. At the same time, we strive to promote open and
|
||||
responsible research on generative models for art and content
|
||||
generation.
|
||||
|
||||
Even though downstream derivative versions of the model could be
|
||||
released under different licensing terms, the latter will always have
|
||||
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|
||||
in the original license (this license). We believe in the intersection
|
||||
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|
||||
to strike a balance between both in order to enable responsible
|
||||
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|
||||
|
||||
This License governs the use of the model (and its derivatives) and is
|
||||
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|
||||
|
||||
NOW THEREFORE, You and Licensor agree as follows:
|
||||
|
||||
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|
||||
|
||||
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|
||||
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|
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|
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|
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||||
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|
||||
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||||
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||||
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||||
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||||
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||||
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|
||||
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||||
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|
||||
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||||
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|
||||
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||||
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||||
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||||
|
||||
Section IV: OTHER PROVISIONS
|
||||
|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
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|
||||
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|
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|
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11. Accepting Warranty or Additional Liability. While redistributing
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12. If any provision of this License is held to be invalid, illegal or
|
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|
||||
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|
||||
|
||||
END OF TERMS AND CONDITIONS
|
||||
|
||||
|
||||
|
||||
|
||||
Attachment A
|
||||
|
||||
Use Restrictions
|
||||
|
||||
You agree not to use the Model or Derivatives of the Model:
|
||||
|
||||
- In any way that violates any applicable national, federal, state,
|
||||
local or international law or regulation;
|
||||
|
||||
- For the purpose of exploiting, harming or attempting to exploit or
|
||||
harm minors in any way;
|
||||
|
||||
- To generate or disseminate verifiably false information and/or
|
||||
content with the purpose of harming others;
|
||||
|
||||
- To generate or disseminate personal identifiable information that
|
||||
can be used to harm an individual;
|
||||
|
||||
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|
||||
|
||||
- For fully automated decision making that adversely impacts an
|
||||
individual’s legal rights or otherwise creates or modifies a
|
||||
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|
||||
|
||||
pp- For any use intended to or which has the effect of discriminating
|
||||
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|
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|
||||
characteristics;
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
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|
||||
- For any use intended to or which has the effect of discriminating
|
||||
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|
||||
characteristics or categories;
|
||||
|
||||
- To provide medical advice and medical results interpretation;
|
||||
|
||||
- To generate or disseminate information for the purpose to be used
|
||||
for administration of justice, law enforcement, immigration or
|
||||
asylum processes, such as predicting an individual will commit
|
||||
fraud/crime commitment (e.g. by text profiling, drawing causal
|
||||
relationships between assertions made in documents, indiscriminate
|
||||
and arbitrarily-targeted use).
|
544
README.md
@ -1,327 +1,287 @@
|
||||
# Stable Diffusion
|
||||
|
||||
This is a fork of CompVis/stable-diffusion, the wonderful open source
|
||||
text-to-image generator.
|
||||
|
||||
The original has been modified in several ways:
|
||||
|
||||
## Interactive command-line interface similar to the Discord bot
|
||||
|
||||
There is now a command-line script, located in scripts/dream.py, which
|
||||
provides an interactive interface to image generation similar to
|
||||
the "dream mothership" bot that Stable AI provided on its Discord
|
||||
server. The advantage of this is that the lengthy model
|
||||
initialization only happens once. After that image generation is
|
||||
fast.
|
||||
|
||||
The script uses the readline library to allow for in-line editing,
|
||||
command history (up and down arrows) and more.
|
||||
|
||||
Note that this has only been tested in the Linux environment!
|
||||
|
||||
~~~~
|
||||
(ldm) ~/stable-diffusion$ ./scripts/dream.py
|
||||
* Initializing, be patient...
|
||||
Loading model from models/ldm/text2img-large/model.ckpt
|
||||
LatentDiffusion: Running in eps-prediction mode
|
||||
DiffusionWrapper has 872.30 M params.
|
||||
making attention of type 'vanilla' with 512 in_channels
|
||||
Working with z of shape (1, 4, 32, 32) = 4096 dimensions.
|
||||
making attention of type 'vanilla' with 512 in_channels
|
||||
Loading Bert tokenizer from "models/bert"
|
||||
setting sampler to plms
|
||||
|
||||
* Initialization done! Awaiting your command...
|
||||
dream> ashley judd riding a camel -n2
|
||||
Outputs:
|
||||
outputs/txt2img-samples/00009.png: "ashley judd riding a camel" -n2 -S 416354203
|
||||
outputs/txt2img-samples/00010.png: "ashley judd riding a camel" -n2 -S 1362479620
|
||||
|
||||
dream> "your prompt here" -n6 -g
|
||||
outputs/txt2img-samples/00041.png: "your prompt here" -n6 -g -S 2685670268
|
||||
seeds for individual rows: [2685670268, 1216708065, 2335773498, 822223658, 714542046, 3395302430]
|
||||
~~~~
|
||||
|
||||
Command-line arguments passed to the script allow you to change
|
||||
various defaults, and select between the mature stable-diffusion
|
||||
weights (512x512) and the older (256x256) latent diffusion weights
|
||||
(laion400m). From the dream> prompt, the arguments are (mostly)
|
||||
identical to those used in the Discord bot, except you don't need to
|
||||
type "!dream". Pass "-h" (or "--help") to list the arguments.
|
||||
|
||||
This script also provides an img2img feature that lets you seed your
|
||||
creations with a drawing or photo.
|
||||
|
||||
For command-line help, type -h (or --help) at the dream> prompt.
|
||||
|
||||
## Simplified API for text to image generation
|
||||
|
||||
There is now a simplified API for text to image generation, which
|
||||
lets you create images from a prompt in just three lines of code:
|
||||
|
||||
~~~~
|
||||
from ldm.simplet2i import T2I
|
||||
model = T2I()
|
||||
outputs = model.text2image("a unicorn in manhattan")
|
||||
~~~~
|
||||
|
||||
Outputs is a list of lists in the format [[filename1,seed1],[filename2,seed2]...]
|
||||
Please see ldm/simplet2i.py for more information.
|
||||
|
||||
## Workaround for machines with limited internet connectivity
|
||||
|
||||
My development machine is a GPU node in a high-performance compute
|
||||
cluster which has no connection to the internet. During model
|
||||
initialization, stable-diffusion tries to download the Bert tokenizer
|
||||
and a file needed by the kornia library. This obviously didn't work
|
||||
for me.
|
||||
|
||||
To work around this, I have modified ldm/modules/encoders/modules.py
|
||||
to look for locally cached Bert files rather than attempting to
|
||||
download them. For this to work, you must run
|
||||
"scripts/preload_models.py" once from an internet-connected machine
|
||||
prior to running the code on an isolated one. This assumes that both
|
||||
machines share a common network-mounted filesystem with a common
|
||||
.cache directory.
|
||||
|
||||
~~~~
|
||||
(ldm) ~/stable-diffusion$ python3 ./scripts/preload_models.py
|
||||
preloading bert tokenizer...
|
||||
Downloading: 100%|██████████████████████████████████| 28.0/28.0 [00:00<00:00, 49.3kB/s]
|
||||
Downloading: 100%|██████████████████████████████████| 226k/226k [00:00<00:00, 2.79MB/s]
|
||||
Downloading: 100%|██████████████████████████████████| 455k/455k [00:00<00:00, 4.36MB/s]
|
||||
Downloading: 100%|██████████████████████████████████| 570/570 [00:00<00:00, 477kB/s]
|
||||
...success
|
||||
preloading kornia requirements...
|
||||
Downloading: "https://github.com/DagnyT/hardnet/raw/master/pretrained/train_liberty_with_aug/checkpoint_liberty_with_aug.pth" to /u/lstein/.cache/torch/hub/checkpoints/checkpoint_liberty_with_aug.pth
|
||||
100%|███████████████████████████████████████████████| 5.10M/5.10M [00:00<00:00, 101MB/s]
|
||||
...success
|
||||
~~~~
|
||||
<div align="center">
|
||||
|
||||
If you don't need this change and want to download the files just in
|
||||
time, copy over the file ldm/modules/encoders/modules.py from the
|
||||
CompVis/stable-diffusion repository. Or you can run preload_models.py
|
||||
on the target machine.
|
||||

|
||||
|
||||
## Minor fixes
|
||||
# InvokeAI: A Stable Diffusion Toolkit
|
||||
|
||||
I added the requirement for torchmetrics to environment.yaml.
|
||||
|
||||
## Installation and support
|
||||
|
||||
Follow the directions from the original README, which starts below, to
|
||||
configure the environment and install requirements. 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.
|
||||
[![discord badge]][discord link]
|
||||
|
||||
*Author:* Lincoln D. Stein <lincoln.stein@gmail.com>
|
||||
|
||||
# Original README from CompViz/stable-diffusion
|
||||
*Stable Diffusion was made possible thanks to a collaboration with [Stability AI](https://stability.ai/) and [Runway](https://runwayml.com/) and builds upon our previous work:*
|
||||
|
||||
[**High-Resolution Image Synthesis with Latent Diffusion Models**](https://ommer-lab.com/research/latent-diffusion-models/)<br/>
|
||||
[Robin Rombach](https://github.com/rromb)\*,
|
||||
[Andreas Blattmann](https://github.com/ablattmann)\*,
|
||||
[Dominik Lorenz](https://github.com/qp-qp)\,
|
||||
[Patrick Esser](https://github.com/pesser),
|
||||
[Björn Ommer](https://hci.iwr.uni-heidelberg.de/Staff/bommer)<br/>
|
||||
|
||||
**CVPR '22 Oral**
|
||||
|
||||
which is available on [GitHub](https://github.com/CompVis/latent-diffusion). PDF at [arXiv](https://arxiv.org/abs/2112.10752). Please also visit our [Project page](https://ommer-lab.com/research/latent-diffusion-models/).
|
||||
|
||||

|
||||
[Stable Diffusion](#stable-diffusion-v1) is a latent text-to-image diffusion
|
||||
model.
|
||||
Thanks to a generous compute donation from [Stability AI](https://stability.ai/) and support from [LAION](https://laion.ai/), we were able to train a Latent Diffusion Model on 512x512 images from a subset of the [LAION-5B](https://laion.ai/blog/laion-5b/) database.
|
||||
Similar to Google's [Imagen](https://arxiv.org/abs/2205.11487),
|
||||
this model uses a frozen CLIP ViT-L/14 text encoder to condition the model on text prompts.
|
||||
With its 860M UNet and 123M text encoder, the model is relatively lightweight and runs on a GPU with at least 10GB VRAM.
|
||||
See [this section](#stable-diffusion-v1) below and the [model card](https://huggingface.co/CompVis/stable-diffusion).
|
||||
|
||||
|
||||
## Requirements
|
||||
A suitable [conda](https://conda.io/) environment named `ldm` can be created
|
||||
and activated with:
|
||||
|
||||
```
|
||||
conda env create -f environment.yaml
|
||||
conda activate ldm
|
||||
```
|
||||
|
||||
You can also update an existing [latent diffusion](https://github.com/CompVis/latent-diffusion) environment by running
|
||||
|
||||
```
|
||||
conda install pytorch torchvision -c pytorch
|
||||
pip install transformers==4.19.2
|
||||
pip install -e .
|
||||
```
|
||||
|
||||
|
||||
## Stable Diffusion v1
|
||||
|
||||
Stable Diffusion v1 refers to a specific configuration of the model
|
||||
architecture that uses a downsampling-factor 8 autoencoder with an 860M UNet
|
||||
and CLIP ViT-L/14 text encoder for the diffusion model. The model was pretrained on 256x256 images and
|
||||
then finetuned on 512x512 images.
|
||||
|
||||
*Note: Stable Diffusion v1 is a general text-to-image diffusion model and therefore mirrors biases and (mis-)conceptions that are present
|
||||
in its training data.
|
||||
Details on the training procedure and data, as well as the intended use of the model can be found in the corresponding [model card](https://huggingface.co/CompVis/stable-diffusion).
|
||||
Research into the safe deployment of general text-to-image models is an ongoing effort. To prevent misuse and harm, we currently provide access to the checkpoints only for [academic research purposes upon request](https://stability.ai/academia-access-form).
|
||||
**This is an experiment in safe and community-driven publication of a capable and general text-to-image model. We are working on a public release with a more permissive license that also incorporates ethical considerations.***
|
||||
|
||||
[Request access to Stable Diffusion v1 checkpoints for academic research](https://stability.ai/academia-access-form)
|
||||
|
||||
### Weights
|
||||
|
||||
We currently provide three checkpoints, `sd-v1-1.ckpt`, `sd-v1-2.ckpt` and `sd-v1-3.ckpt`,
|
||||
which were trained as follows,
|
||||
|
||||
- `sd-v1-1.ckpt`: 237k steps at resolution `256x256` on [laion2B-en](https://huggingface.co/datasets/laion/laion2B-en).
|
||||
194k steps at resolution `512x512` on [laion-high-resolution](https://huggingface.co/datasets/laion/laion-high-resolution) (170M examples from LAION-5B with resolution `>= 1024x1024`).
|
||||
- `sd-v1-2.ckpt`: Resumed from `sd-v1-1.ckpt`.
|
||||
515k steps at resolution `512x512` on "laion-improved-aesthetics" (a subset of laion2B-en,
|
||||
filtered to images with an original size `>= 512x512`, estimated aesthetics score `> 5.0`, and an estimated watermark probability `< 0.5`. The watermark estimate is from the LAION-5B metadata, the aesthetics score is estimated using an [improved aesthetics estimator](https://github.com/christophschuhmann/improved-aesthetic-predictor)).
|
||||
- `sd-v1-3.ckpt`: Resumed from `sd-v1-2.ckpt`. 195k steps at resolution `512x512` on "laion-improved-aesthetics" and 10\% dropping of the text-conditioning to improve [classifier-free guidance sampling](https://arxiv.org/abs/2207.12598).
|
||||
|
||||
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:
|
||||

|
||||
|
||||
|
||||
|
||||
### Text-to-Image with Stable Diffusion
|
||||

|
||||

|
||||
[![latest release badge]][latest release link] [![github stars badge]][github stars link] [![github forks badge]][github forks link]
|
||||
|
||||
Stable Diffusion is a latent diffusion model conditioned on the (non-pooled) text embeddings of a CLIP ViT-L/14 text encoder.
|
||||
[![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] [![translation status badge]][translation status link]
|
||||
|
||||
#### Sampling Script
|
||||
[CI checks on main badge]: https://flat.badgen.net/github/checks/invoke-ai/InvokeAI/main?label=CI%20status%20on%20main&cache=900&icon=github
|
||||
[CI checks on main link]:https://github.com/invoke-ai/InvokeAI/actions?query=branch%3Amain
|
||||
[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
|
||||
[github forks link]: https://useful-forks.github.io/?repo=invoke-ai%2FInvokeAI
|
||||
[github open issues badge]: https://flat.badgen.net/github/open-issues/invoke-ai/InvokeAI?icon=github
|
||||
[github open issues link]: https://github.com/invoke-ai/InvokeAI/issues?q=is%3Aissue+is%3Aopen
|
||||
[github open prs badge]: https://flat.badgen.net/github/open-prs/invoke-ai/InvokeAI?icon=github
|
||||
[github open prs link]: https://github.com/invoke-ai/InvokeAI/pulls?q=is%3Apr+is%3Aopen
|
||||
[github stars badge]: https://flat.badgen.net/github/stars/invoke-ai/InvokeAI?icon=github
|
||||
[github stars link]: https://github.com/invoke-ai/InvokeAI/stargazers
|
||||
[latest commit to main badge]: https://flat.badgen.net/github/last-commit/invoke-ai/InvokeAI/main?icon=github&color=yellow&label=last%20dev%20commit&cache=900
|
||||
[latest commit to main link]: https://github.com/invoke-ai/InvokeAI/commits/main
|
||||
[latest 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/
|
||||
|
||||
After [obtaining the weights](#weights), link them
|
||||
```
|
||||
mkdir -p models/ldm/stable-diffusion-v1/
|
||||
ln -s <path/to/model.ckpt> models/ldm/stable-diffusion-v1/model.ckpt
|
||||
```
|
||||
and sample with
|
||||
```
|
||||
python scripts/txt2img.py --prompt "a photograph of an astronaut riding a horse" --plms
|
||||
```
|
||||
</div>
|
||||
|
||||
By default, this uses a guidance scale of `--scale 7.5`, [Katherine Crowson's implementation](https://github.com/CompVis/latent-diffusion/pull/51) of the [PLMS](https://arxiv.org/abs/2202.09778) sampler,
|
||||
and renders images of size 512x512 (which it was trained on) in 50 steps. All supported arguments are listed below (type `python scripts/txt2img.py --help`).
|
||||
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.
|
||||
|
||||
```commandline
|
||||
usage: txt2img.py [-h] [--prompt [PROMPT]] [--outdir [OUTDIR]] [--skip_grid] [--skip_save] [--ddim_steps DDIM_STEPS] [--plms] [--laion400m] [--fixed_code] [--ddim_eta DDIM_ETA] [--n_iter N_ITER] [--H H] [--W W] [--C C] [--f F] [--n_samples N_SAMPLES] [--n_rows N_ROWS]
|
||||
[--scale SCALE] [--from-file FROM_FILE] [--config CONFIG] [--ckpt CKPT] [--seed SEED] [--precision {full,autocast}]
|
||||
**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>]
|
||||
|
||||
optional arguments:
|
||||
-h, --help show this help message and exit
|
||||
--prompt [PROMPT] the prompt to render
|
||||
--outdir [OUTDIR] dir to write results to
|
||||
--skip_grid do not save a grid, only individual samples. Helpful when evaluating lots of samples
|
||||
--skip_save do not save individual samples. For speed measurements.
|
||||
--ddim_steps DDIM_STEPS
|
||||
number of ddim sampling steps
|
||||
--plms use plms sampling
|
||||
--laion400m uses the LAION400M model
|
||||
--fixed_code if enabled, uses the same starting code across samples
|
||||
--ddim_eta DDIM_ETA ddim eta (eta=0.0 corresponds to deterministic sampling
|
||||
--n_iter N_ITER sample this often
|
||||
--H H image height, in pixel space
|
||||
--W W image width, in pixel space
|
||||
--C C latent channels
|
||||
--f F downsampling factor
|
||||
--n_samples N_SAMPLES
|
||||
how many samples to produce for each given prompt. A.k.a. batch size
|
||||
--n_rows N_ROWS rows in the grid (default: n_samples)
|
||||
--scale SCALE unconditional guidance scale: eps = eps(x, empty) + scale * (eps(x, cond) - eps(x, empty))
|
||||
--from-file FROM_FILE
|
||||
if specified, load prompts from this file
|
||||
--config CONFIG path to config which constructs model
|
||||
--ckpt CKPT path to checkpoint of model
|
||||
--seed SEED the seed (for reproducible sampling)
|
||||
--precision {full,autocast}
|
||||
evaluate at this precision
|
||||
_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 us diagnose issues faster._
|
||||
|
||||
```
|
||||
Note: The inference config for all v1 versions is designed to be used with EMA-only checkpoints.
|
||||
For this reason `use_ema=False` is set in the configuration, otherwise the code will try to switch from
|
||||
non-EMA to EMA weights. If you want to examine the effect of EMA vs no EMA, we provide "full" checkpoints
|
||||
which contain both types of weights. For these, `use_ema=False` will load and use the non-EMA weights.
|
||||
<div align="center">
|
||||
|
||||

|
||||
|
||||
#### Diffusers Integration
|
||||
</div>
|
||||
|
||||
Another way to download and sample Stable Diffusion is by using the [diffusers library](https://github.com/huggingface/diffusers/tree/main#new--stable-diffusion-is-now-fully-compatible-with-diffusers)
|
||||
```py
|
||||
# make sure you're logged in with `huggingface-cli login`
|
||||
from torch import autocast
|
||||
from diffusers import StableDiffusionPipeline, LMSDiscreteScheduler
|
||||
## Table of Contents
|
||||
|
||||
pipe = StableDiffusionPipeline.from_pretrained(
|
||||
"CompVis/stable-diffusion-v1-3-diffusers",
|
||||
use_auth_token=True
|
||||
)
|
||||
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)
|
||||
|
||||
prompt = "a photo of an astronaut riding a horse on mars"
|
||||
with autocast("cuda"):
|
||||
image = pipe(prompt)["sample"][0]
|
||||
## Getting Started with InvokeAI
|
||||
|
||||
image.save("astronaut_rides_horse.png")
|
||||
```
|
||||
For full installation and upgrade instructions, please see:
|
||||
[InvokeAI Installation Overview](https://invoke-ai.github.io/InvokeAI/installation/)
|
||||
|
||||
### Automatic Installer (suggested for 1st time users)
|
||||
|
||||
1. Go to the bottom of the [Latest Release Page](https://github.com/invoke-ai/InvokeAI/releases/latest)
|
||||
|
||||
### Image Modification with Stable Diffusion
|
||||
2. Download the .zip file for your OS (Windows/macOS/Linux).
|
||||
|
||||
By using a diffusion-denoising mechanism as first proposed by [SDEdit](https://arxiv.org/abs/2108.01073), the model can be used for different
|
||||
tasks such as text-guided image-to-image translation and upscaling. Similar to the txt2img sampling script,
|
||||
we provide a script to perform image modification with Stable Diffusion.
|
||||
3. Unzip the file.
|
||||
|
||||
The following describes an example where a rough sketch made in [Pinta](https://www.pinta-project.com/) is converted into a detailed artwork.
|
||||
```
|
||||
python scripts/img2img.py --prompt "A fantasy landscape, trending on artstation" --init-img <path-to-img.jpg> --strength 0.8
|
||||
```
|
||||
Here, strength is a value between 0.0 and 1.0, that controls the amount of noise that is added to the input image.
|
||||
Values that approach 1.0 allow for lots of variations but will also produce images that are not semantically consistent with the input. See the following example.
|
||||
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`.
|
||||
|
||||
**Input**
|
||||
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.
|
||||
|
||||
**Outputs**
|
||||
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`
|
||||
|
||||
This procedure can, for example, also be used to upscale samples from the base model.
|
||||
|
||||
|
||||
## Comments
|
||||
|
||||
- Our codebase for the diffusion models builds heavily on [OpenAI's ADM codebase](https://github.com/openai/guided-diffusion)
|
||||
and [https://github.com/lucidrains/denoising-diffusion-pytorch](https://github.com/lucidrains/denoising-diffusion-pytorch).
|
||||
Thanks for open-sourcing!
|
||||
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.
|
||||
|
||||
- The implementation of the transformer encoder is from [x-transformers](https://github.com/lucidrains/x-transformers) by [lucidrains](https://github.com/lucidrains?tab=repositories).
|
||||
10. Type `banana sushi` in the box on the top left and click `Invoke`
|
||||
|
||||
### Command-Line Installation (for users familiar with Terminals)
|
||||
|
||||
## BibTeX
|
||||
You must have Python 3.9 or 3.10 installed on your machine. Earlier or later versions are
|
||||
not supported.
|
||||
|
||||
```
|
||||
@misc{rombach2021highresolution,
|
||||
title={High-Resolution Image Synthesis with Latent Diffusion Models},
|
||||
author={Robin Rombach and Andreas Blattmann and Dominik Lorenz and Patrick Esser and Björn Ommer},
|
||||
year={2021},
|
||||
eprint={2112.10752},
|
||||
archivePrefix={arXiv},
|
||||
primaryClass={cs.CV}
|
||||
}
|
||||
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)
|
||||
|
||||
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
|
||||
|
||||
- At least 12 GB of free disk space for the machine learning model, Python, and all its dependencies.
|
||||
|
||||
## Features
|
||||
|
||||
Feature documentation can be reviewed by navigating to [the InvokeAI Documentation page](https://invoke-ai.github.io/InvokeAI/features/)
|
||||
|
||||
### *Web Server & UI*
|
||||
|
||||
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.
|
||||
|
||||
### *Unified Canvas*
|
||||
|
||||
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.
|
||||
|
||||
### *Advanced Prompt Syntax*
|
||||
|
||||
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
|
||||
|
||||
For our latest changes, view our [Release
|
||||
Notes](https://github.com/invoke-ai/InvokeAI/releases) and the
|
||||
[CHANGELOG](docs/CHANGELOG.md).
|
||||
|
||||
## Troubleshooting
|
||||
|
||||
Please check out our **[Q&A](https://invoke-ai.github.io/InvokeAI/help/TROUBLESHOOT/#faq)** to get solutions for common installation
|
||||
problems and other issues.
|
||||
|
||||
## Contributing
|
||||
|
||||
Anyone who wishes to contribute to this project, whether documentation, features, bug fixes, code
|
||||
cleanup, testing, or code reviews, is very much encouraged to do so.
|
||||
|
||||
To join, just raise your hand on the InvokeAI Discord server (#dev-chat) or the GitHub discussion board.
|
||||
|
||||
If you'd like to help with translation, please see our [translation guide](docs/other/TRANSLATION.md).
|
||||
|
||||
If you are unfamiliar with how
|
||||
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](https://invoke-ai.github.io/InvokeAI/other/CONTRIBUTORS/). We thank them for
|
||||
their time, hard work and effort.
|
||||
|
||||
Thanks to [Weblate](https://weblate.org/) for generously providing translation services to this project.
|
||||
|
||||
### Support
|
||||
|
||||
For support, please use this repository's GitHub Issues tracking service, or join the Discord.
|
||||
|
||||
Original portions of the software are Copyright (c) 2023 by respective contributors.
|
||||
|
||||
|
@ -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
|
@ -1,68 +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
|
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
|
||||
}
|
587
docs/CHANGELOG.md
Normal file
@ -0,0 +1,587 @@
|
||||
---
|
||||
title: Changelog
|
||||
---
|
||||
|
||||
# :octicons-log-16: **Changelog**
|
||||
|
||||
## 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 <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.
|
||||
- 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
|
||||
[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)
|
||||
|
||||
---
|
||||
|
||||
## 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.
|
||||
- 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.
|
||||
|
||||
---
|
||||
|
||||
## v1.10 <small>(25 August 2022)</small>
|
||||
|
||||
- A barebones but fully functional interactive web server for online generation
|
||||
of txt2img and img2img.
|
||||
|
||||
---
|
||||
|
||||
## v1.09 <small>(24 August 2022)</small>
|
||||
|
||||
- A new -v option allows you to generate multiple variants of an initial image
|
||||
in img2img mode. (kudos to [Oceanswave](https://github.com/Oceanswave).
|
||||
[ See this discussion in the PR for examples and details on use](https://github.com/lstein/stable-diffusion/pull/71#issuecomment-1226700810))
|
||||
- Added ability to personalize text to image generation (kudos to
|
||||
[Oceanswave](https://github.com/Oceanswave) and
|
||||
[nicolai256](https://github.com/nicolai256))
|
||||
- Enabled all of the samplers from k_diffusion
|
||||
|
||||
---
|
||||
|
||||
## v1.08 <small>(24 August 2022)</small>
|
||||
|
||||
- Escape single quotes on the invoke> command before trying to parse. This
|
||||
avoids parse errors.
|
||||
- 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.
|
||||
- Cleaned up the copyright and license agreement files.
|
||||
|
||||
---
|
||||
|
||||
## 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.
|
||||
|
||||
---
|
||||
|
||||
## 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)
|
||||
|
||||
---
|
||||
|
||||
## 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.
|
||||
|
||||
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
|
||||
|
||||
- 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.
|
||||
|
||||
---
|
||||
|
||||
## 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
|
||||
tokenizer.
|
||||
|
||||
---
|
||||
|
||||
## 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.
|
||||
|
||||
---
|
||||
|
||||
## 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!!**
|
||||
|
||||
---
|
||||
|
||||
## 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
|
||||
|
||||
---
|
||||
|
||||
## Links
|
||||
|
||||
- **[Read Me](index.md)**
|
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