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44 Commits

Author SHA1 Message Date
Lincoln Stein
b487fa4391 fix basicsr conflict on windows 2022-12-02 12:53:13 -05:00
Lincoln Stein
12b98ba4ec make invoke.sh executable 2022-12-02 12:53:13 -05:00
Lincoln Stein
fa25a64d37 remove references to binary installer from docs 2022-12-02 12:48:26 -05:00
Lincoln Stein
29540452f2 fix bad naming of invoke.sh.in 2022-12-02 11:25:37 -05:00
Lincoln Stein
c7960f930a fix regression in copy function 2022-12-02 10:53:42 -05:00
Lincoln Stein
c1c8b5026a apply current directory patch to binary installer .sh file 2022-12-02 10:53:42 -05:00
Lincoln Stein
5da42e0ad2 add back PYTORCH_ENABLE_MPS_FALLBACK 2022-12-02 10:53:42 -05:00
Lincoln Stein
34d6f35408 run .bat file in directory potentially containing spaces
- The previous fix for the "install in Windows system directory" error would fail
   if the path includes directories with spaces in them. This fixes that.

- In addition, addressing the same issue in source installer, although not
	yet reported in wild.
2022-12-02 10:53:42 -05:00
mauwii
401165ba35 correctly link current core team 2022-12-02 09:33:19 -05:00
mauwii
6d8057c84f fix POSTPROCESS ToC 2022-12-02 09:33:19 -05:00
mauwii
3f23dee6f4 add title 2022-12-02 09:33:19 -05:00
mauwii
8cdd961ad2 update IMG2IMG.md 2022-12-02 09:33:19 -05:00
mauwii
470b267939 update CONEPTS.md
- use table with correct syntax for screenshots
- switch Title and first Headline to look better in ToC
2022-12-02 09:33:19 -05:00
mauwii
bf399e303c add index.md to features
to prevent the menu being occupied from the expanded CLI ToC
Should maybe be fleshed out a bit
2022-12-02 09:33:19 -05:00
mauwii
b3d7ad7461 a lot of formatting updates to CLI.md 2022-12-02 09:33:19 -05:00
mauwii
cd66b2c76d fix links in older_docs_to_be_removed 2022-12-02 09:33:19 -05:00
psychedelicious
6b406e2b5e Adds tip for importing models on Windows 2022-12-02 09:25:36 -05:00
Lincoln Stein
6737cc1443 recompile for linux 2022-12-02 09:11:17 -05:00
Lincoln Stein
7fd0eeb9f9 update darwin requirements 2022-12-02 09:11:17 -05:00
Lincoln Stein
16e3b45fa2 update linux reuqirements file 2022-12-02 09:11:17 -05:00
Lincoln Stein
2f07ea03a9 binary installer fix
- bat file changes to directory it lives in rather than user's current directory
- restore incorrect requirements and compiled Darwin requirements file
2022-12-02 09:11:17 -05:00
Lincoln Stein
b563d75c58 restored mac requirements file 2022-12-02 09:11:17 -05:00
psychedelicious
a7b7b20d16 Updates docs release link to latest 2022-12-02 06:20:16 -05:00
Lincoln Stein
a47ef3ded9 change download links to release candidate 2022-12-01 23:24:23 -05:00
Lincoln Stein
7cb9b654f3 add compiled windows file 2022-12-01 23:07:48 -05:00
Lincoln Stein
8819e12a86 configure script changed from preload_models.py to configure_invokeai.py
This makes a cosmetic change. Instead of calling preload_models.py
(deprecated) it calls configure_invokeai.py. Currently the two do
the same thing.
2022-12-01 22:51:05 -05:00
Lincoln Stein
967eb60ea9 added the linux py3.10* file 2022-12-01 22:51:05 -05:00
psychedelicious
b1091ecda1 Fixes failed canvas generation when gallery is empty
There was some old logic from before Unified Canvas which aborted generation when there was no currentImage. 

If you have an image in the gallery, there is always a currentImage. But if gallery is empty, there is no currentImage. Generation would silently fail in this case.

We apparently never tested with an empty gallery and thus never ran into the issue. This removes this old and now-unused logic.
2022-12-01 22:29:56 -05:00
Lincoln Stein
2723dd9051 remove bad characters from end of user input
Some users were leaving whitespace at the end of their root
directories or ending them with a backslash. This caused the root
directory to become unusable. This removes whitespace and backslashes
from the end of the directory names.

Note that more needs to be done to cleanse the input, but for now
this will cover the cases we have seen so far in the wild.
2022-12-01 22:15:39 -05:00
Lincoln Stein
8f050d992e documentation fixes for release 2022-12-01 22:02:50 -05:00
Lincoln Stein
0346095876 fix incorrect syntax for .bat 2022-12-01 22:02:27 -05:00
Lincoln Stein
f9bbc55f74 Merge branch 'source-installer-improvements' into main 2022-12-01 23:18:54 +00:00
Lincoln Stein
878a3907e9 defer loading of Hugging Face concepts until needed
Some users have been complaining that the CLI "freezes" for a while
before the invoke> prompt appears. I believe this is due to internet
delay while the concepts library names are downloaded by the autocompleter.
I have changed logic so that the concepts are downloaded the first time
the user types a < and tabs.
2022-12-01 17:56:18 -05:00
Lincoln Stein
4cfb41d9ae configure_invokeai.py enhancement
- Adds a new option to download <a>ll the models, in addition
  to <r>ecommended and <c>ustomized.
2022-12-01 15:59:14 -05:00
Lincoln Stein
6ec64ecb3c fix commit conflict markers 2022-12-01 15:07:54 -05:00
Lincoln Stein
540315edaa rename to binary_installer in build docs 2022-12-01 14:58:07 -05:00
Lincoln Stein
cf10a1b736 Merge branch 'main' into source-installer-improvements 2022-12-01 19:45:47 +00:00
Lincoln Stein
9fb2a43780 rename "installer" to "binary_installer"
- Fix up internal names so scripts run properly
2022-12-01 19:40:47 +00:00
Lincoln Stein
1b743f7d9b source installer improvements and documentation
- Source installer provides more context for what it is doing, and
  sends user to help/troubleshooting pages when something goes wrong.

- install.sh and install.bat are renamed to install.sh.in and install.bat.in
  to discourage users from running them from within the

- Documentation updated
2022-12-01 19:40:13 +00:00
Damian Stewart
d7bf3f7d7b make .sh/.bat files inside installer/ non executable (#1664)
* make binary installer executables non-executable inside the repo

* update docs to match previous commit
2022-12-01 19:35:21 +01:00
Lincoln Stein
eba31e7caf Documentation updates for 2.2 release 2022-12-01 08:09:31 -05:00
Lincoln Stein
bde456f9fa fix startup messages and a startup crash
- make the warnings about patchmatch less redundant
- only warn about being unable to load concepts from Hugging Face
  library once
- do not crash when unable to load concepts from Hugging Face
  due to network connectivity issues
2022-12-01 07:42:31 -05:00
Lincoln Stein
9ee83380e6 fix missig history file in output director 2022-12-01 07:39:26 -05:00
Lincoln Stein
6982e6a469 rebuilt frontend 2022-11-30 19:20:57 -05:00
48 changed files with 1264 additions and 961 deletions

View File

@@ -6,23 +6,26 @@ IFS=$'\n\t'
echo "Be certain that you're in the 'installer' directory before continuing."
read -p "Press any key to continue, or CTRL-C to exit..."
VERSION='2.2.3'
# make the installer zip for linux and mac
rm -rf InvokeAI
mkdir -p InvokeAI
cp install.sh InvokeAI
cp install.sh.in InvokeAI/install.sh
chmod a+x InvokeAI/install.sh
cp readme.txt InvokeAI
zip -r InvokeAI-linux.zip InvokeAI
zip -r InvokeAI-mac.zip InvokeAI
zip -r InvokeAI-binary-$VERSION-linux.zip InvokeAI
zip -r InvokeAI-binary-$VERSION-mac.zip InvokeAI
# make the installer zip for windows
rm -rf InvokeAI
mkdir -p InvokeAI
cp install.bat InvokeAI
cp install.bat.in InvokeAI/install.bat
cp readme.txt InvokeAI
cp WinLongPathsEnabled.reg InvokeAI
zip -r InvokeAI-windows.zip InvokeAI
zip -r InvokeAI-binary-$VERSION-windows.zip InvokeAI
rm -rf InvokeAI

View File

@@ -10,6 +10,9 @@
@rem This enables a user to install this project without manually installing git or Python
@rem change to the script's directory
PUSHD "%~dp0"
set "no_cache_dir=--no-cache-dir"
if "%1" == "use-cache" (
set "no_cache_dir="
@@ -22,9 +25,7 @@ set INSTALL_ENV_DIR=%cd%\installer_files\env
@rem https://mamba.readthedocs.io/en/latest/installation.html
set MICROMAMBA_DOWNLOAD_URL=https://github.com/cmdr2/stable-diffusion-ui/releases/download/v1.1/micromamba.exe
set RELEASE_URL=https://github.com/invoke-ai/InvokeAI
#set RELEASE_SOURCEBALL=/archive/refs/heads/main.tar.gz
# RELEASE_SOURCEBALL=/archive/refs/heads/test-installer.tar.gz
RELEASE_SOURCEBALL=/archive/refs/heads/development.tar.gz
set RELEASE_SOURCEBALL=/archive/refs/heads/main.tar.gz
set PYTHON_BUILD_STANDALONE_URL=https://github.com/indygreg/python-build-standalone/releases/download
set PYTHON_BUILD_STANDALONE=20221002/cpython-3.10.7+20221002-x86_64-pc-windows-msvc-shared-install_only.tar.gz
@@ -127,7 +128,7 @@ if %errorlevel% neq 0 goto err_exit
echo ***** Updated pip and wheel *****
set err_msg=----- requirements file copy failed -----
copy installer\py3.10-windows-x86_64-cuda-reqs.txt requirements.txt
copy binary_installer\py3.10-windows-x86_64-cuda-reqs.txt requirements.txt
if %errorlevel% neq 0 goto err_exit
set err_msg=----- main pip install failed -----
@@ -140,11 +141,11 @@ set err_msg=----- InvokeAI setup failed -----
.venv\Scripts\python -m pip install %no_cache_dir% --no-warn-script-location -e .
if %errorlevel% neq 0 goto err_exit
copy installer\invoke.bat .\invoke.bat
copy binary_installer\invoke.bat.in .\invoke.bat
echo ***** Installed invoke launcher script ******
@rem more cleanup
rd /s /q installer installer_files
rd /s /q binary_installer installer_files
@rem preload the models
call .venv\Scripts\python scripts\configure_invokeai.py

View File

@@ -1,5 +1,9 @@
#!/usr/bin/env bash
# ensure we're in the correct folder in case user's CWD is somewhere else
scriptdir=$(dirname "$0")
cd "$scriptdir"
set -euo pipefail
IFS=$'\n\t'
@@ -22,6 +26,8 @@ function _err_exit {
# This enables a user to install this project without manually installing git or Python
echo -e "\n***** Installing InvokeAI into $(pwd)... *****\n"
export no_cache_dir="--no-cache-dir"
if [ $# -ge 1 ]; then
if [ "$1" = "use-cache" ]; then
@@ -29,10 +35,6 @@ if [ $# -ge 1 ]; then
fi
fi
echo "$no_cache_dir"
echo -e "\n***** Installing InvokeAI... *****\n"
OS_NAME=$(uname -s)
case "${OS_NAME}" in
@@ -80,19 +82,17 @@ if [ "$OS_NAME" == "darwin" ] && [ "$OS_ARCH" == "arm64" ]; then
fi
# config
echo "USING development BRANCH. REMEMBER TO CHANGE TO main BEFORE RELEASE"
INSTALL_ENV_DIR="$(pwd)/installer_files/env"
MICROMAMBA_DOWNLOAD_URL="https://micro.mamba.pm/api/micromamba/${MAMBA_OS_NAME}-${MAMBA_ARCH}/latest"
RELEASE_URL=https://github.com/invoke-ai/InvokeAI
# RELEASE_SOURCEBALL=/archive/refs/heads/main.tar.gz
# RELEASE_SOURCEBALL=/archive/refs/heads/test-installer.tar.gz
RELEASE_SOURCEBALL=/archive/refs/heads/development.tar.gz
RELEASE_SOURCEBALL=/archive/refs/heads/main.tar.gz
PYTHON_BUILD_STANDALONE_URL=https://github.com/indygreg/python-build-standalone/releases/download
if [ "$OS_NAME" == "darwin" ]; then
PYTHON_BUILD_STANDALONE=20221002/cpython-3.10.7+20221002-${PY_ARCH}-apple-darwin-install_only.tar.gz
elif [ "$OS_NAME" == "linux" ]; then
PYTHON_BUILD_STANDALONE=20221002/cpython-3.10.7+20221002-${PY_ARCH}-unknown-linux-gnu-install_only.tar.gz
fi
echo "INSTALLING $RELEASE_SOURCEBALL FROM $RELEASE_URL"
PACKAGES_TO_INSTALL=""
@@ -192,32 +192,33 @@ echo -e "We're running under"
_err_exit $? _err_msg
_err_msg="\n----- pip update failed -----\n"
.venv/bin/python3 -m pip install "$no_cache_dir" --no-warn-script-location --upgrade pip wheel
.venv/bin/python3 -m pip install $no_cache_dir --no-warn-script-location --upgrade pip
_err_exit $? _err_msg
echo -e "\n***** Updated pip and wheel *****\n"
echo -e "\n***** Updated pip *****\n"
_err_msg="\n----- requirements file copy failed -----\n"
cp installer/py3.10-${OS_NAME}-"${OS_ARCH}"-${CD}-reqs.txt requirements.txt
cp binary_installer/py3.10-${OS_NAME}-"${OS_ARCH}"-${CD}-reqs.txt requirements.txt
_err_exit $? _err_msg
_err_msg="\n----- main pip install failed -----\n"
.venv/bin/python3 -m pip install "$no_cache_dir" --no-warn-script-location -r requirements.txt
.venv/bin/python3 -m pip install $no_cache_dir --no-warn-script-location -r requirements.txt
_err_exit $? _err_msg
echo -e "\n***** Installed Python dependencies *****\n"
_err_msg="\n----- InvokeAI setup failed -----\n"
.venv/bin/python3 -m pip install "$no_cache_dir" --no-warn-script-location -e .
.venv/bin/python3 -m pip install $no_cache_dir --no-warn-script-location -e .
_err_exit $? _err_msg
echo -e "\n***** Installed InvokeAI *****\n"
cp installer/invoke.sh .
cp binary_installer/invoke.sh.in ./invoke.sh
chmod a+rx ./invoke.sh
echo -e "\n***** Installed invoke launcher script ******\n"
# more cleanup
rm -rf installer/ installer_files/
rm -rf binary_installer/ installer_files/
# preload the models
.venv/bin/python3 scripts/configure_invokeai.py
@@ -227,6 +228,8 @@ deactivate
echo -e "\n***** Finished downloading models *****\n"
echo "All done! Run the command './invoke.sh' to start InvokeAI."
echo "All done! Run the command"
echo " $scriptdir/invoke.sh"
echo "to start InvokeAI."
read -p "Press any key to exit..."
exit

5
installer/invoke.sh → binary_installer/invoke.sh.in Executable file → Normal file
View File

@@ -4,6 +4,11 @@ set -eu
. .venv/bin/activate
# set required env var for torch on mac MPS
if [ "$(uname -s)" == "Darwin" ]; then
export PYTORCH_ENABLE_MPS_FALLBACK=1
fi
echo "Do you want to generate images using the"
echo "1. command-line"
echo "2. browser-based UI"

View File

@@ -4,7 +4,7 @@
#
# pip-compile --allow-unsafe --generate-hashes --output-file=installer/py3.10-darwin-x86_64-cpu-reqs.txt installer/requirements.in
#
--extra-index-url https://download.pytorch.org/whl/torch_stable.html
--extra-index-url https://download.pytorch.org/whl/cu116
--trusted-host https
absl-py==1.3.0 \
@@ -987,7 +987,6 @@ numpy==1.23.4 \
# pandas
# pyarrow
# pydeck
# pypatchmatch
# pytorch-lightning
# pywavelets
# qudida
@@ -1160,7 +1159,6 @@ pillow==9.3.0 \
# imageio
# k-diffusion
# matplotlib
# pypatchmatch
# realesrgan
# scikit-image
# streamlit
@@ -1296,9 +1294,6 @@ pyparsing==3.0.9 \
# via
# matplotlib
# packaging
pypatchmatch @ https://github.com/invoke-ai/PyPatchMatch/archive/129863937a8ab37f6bbcec327c994c0f932abdbc.zip \
--hash=sha256:4ad6ec95379e7d122d494ff76633cc7cf9b71330d5efda147fceba81e3dc6cd2
# via -r installer/requirements.in
pyreadline3==3.4.1 \
--hash=sha256:6f3d1f7b8a31ba32b73917cefc1f28cc660562f39aea8646d30bd6eff21f7bae \
--hash=sha256:b0efb6516fd4fb07b45949053826a62fa4cb353db5be2bbb4a7aa1fdd1e345fb
@@ -1831,27 +1826,27 @@ toolz==0.12.0 \
--hash=sha256:2059bd4148deb1884bb0eb770a3cde70e7f954cfbbdc2285f1f2de01fd21eb6f \
--hash=sha256:88c570861c440ee3f2f6037c4654613228ff40c93a6c25e0eba70d17282c6194
# via altair
torch==1.12.1 ; platform_system == "Darwin" \
--hash=sha256:03e31c37711db2cd201e02de5826de875529e45a55631d317aadce2f1ed45aa8 \
--hash=sha256:0b44601ec56f7dd44ad8afc00846051162ef9c26a8579dda0a02194327f2d55e \
--hash=sha256:42e115dab26f60c29e298559dbec88444175528b729ae994ec4c65d56fe267dd \
--hash=sha256:42f639501928caabb9d1d55ddd17f07cd694de146686c24489ab8c615c2871f2 \
--hash=sha256:4e1b9c14cf13fd2ab8d769529050629a0e68a6fc5cb8e84b4a3cc1dd8c4fe541 \
--hash=sha256:68104e4715a55c4bb29a85c6a8d57d820e0757da363be1ba680fa8cc5be17b52 \
--hash=sha256:69fe2cae7c39ccadd65a123793d30e0db881f1c1927945519c5c17323131437e \
--hash=sha256:6cf6f54b43c0c30335428195589bd00e764a6d27f3b9ba637aaa8c11aaf93073 \
--hash=sha256:743784ccea0dc8f2a3fe6a536bec8c4763bd82c1352f314937cb4008d4805de1 \
--hash=sha256:8a34a2fbbaa07c921e1b203f59d3d6e00ed379f2b384445773bd14e328a5b6c8 \
--hash=sha256:976c3f997cea38ee91a0dd3c3a42322785414748d1761ef926b789dfa97c6134 \
--hash=sha256:9b356aea223772cd754edb4d9ecf2a025909b8615a7668ac7d5130f86e7ec421 \
--hash=sha256:9c038662db894a23e49e385df13d47b2a777ffd56d9bcd5b832593fab0a7e286 \
--hash=sha256:a8320ba9ad87e80ca5a6a016e46ada4d1ba0c54626e135d99b2129a4541c509d \
--hash=sha256:b5dbcca369800ce99ba7ae6dee3466607a66958afca3b740690d88168752abcf \
--hash=sha256:bfec2843daa654f04fda23ba823af03e7b6f7650a873cdb726752d0e3718dada \
--hash=sha256:cd26d8c5640c3a28c526d41ccdca14cf1cbca0d0f2e14e8263a7ac17194ab1d2 \
--hash=sha256:e9c8f4a311ac29fc7e8e955cfb7733deb5dbe1bdaabf5d4af2765695824b7e0d \
--hash=sha256:f00c721f489089dc6364a01fd84906348fe02243d0af737f944fddb36003400d \
--hash=sha256:f3b52a634e62821e747e872084ab32fbcb01b7fa7dbb7471b6218279f02a178a
torch==1.12.0 ; platform_system == "Darwin" \
--hash=sha256:0399746f83b4541bcb5b219a18dbe8cade760aba1c660d2748a38c6dc338ebc7 \
--hash=sha256:0986685f2ec8b7c4d3593e8cfe96be85d462943f1a8f54112fc48d4d9fbbe903 \
--hash=sha256:13c7cca6b2ea3704d775444f02af53c5f072d145247e17b8cd7813ac57869f03 \
--hash=sha256:201abf43a99bb4980cc827dd4b38ac28f35e4dddac7832718be3d5479cafd2c1 \
--hash=sha256:2143d5fe192fd908b70b494349de5b1ac02854a8a902bd5f47d13d85b410e430 \
--hash=sha256:2568f011dddeb5990d8698cc375d237f14568ffa8489854e3b94113b4b6b7c8b \
--hash=sha256:3322d33a06e440d715bb214334bd41314c94632d9a2f07d22006bf21da3a2be4 \
--hash=sha256:349ea3ba0c0e789e0507876c023181f13b35307aebc2e771efd0e045b8e03e84 \
--hash=sha256:44a3804e9bb189574f5d02ccc2dc6e32e26a81b3e095463b7067b786048c6072 \
--hash=sha256:5ed69d5af232c5c3287d44cef998880dadcc9721cd020e9ae02f42e56b79c2e4 \
--hash=sha256:60d06ee2abfa85f10582d205404d52889d69bcbb71f7e211cfc37e3957ac19ca \
--hash=sha256:63341f96840a223f277e498d2737b39da30d9f57c7a1ef88857b920096317739 \
--hash=sha256:72207b8733523388c49d43ffcc4416d1d8cd64c40f7826332e714605ace9b1d2 \
--hash=sha256:7ddb167827170c4e3ff6a27157414a00b9fef93dea175da04caf92a0619b7aee \
--hash=sha256:844f1db41173b53fe40c44b3e04fcca23a6ce00ac328b7099f2800e611766845 \
--hash=sha256:a1325c9c28823af497cbf443369bddac9ac59f67f1e600f8ab9b754958e55b76 \
--hash=sha256:abbdc5483359b9495dc76e3bd7911ccd2ddc57706c117f8316832e31590af871 \
--hash=sha256:c0313438bc36448ffd209f5fb4e5f325b3af158cdf61c8829b8ddaf128c57816 \
--hash=sha256:e3e8348edca3e3cee5a67a2b452b85c57712efe1cc3ffdb87c128b3dde54534e \
--hash=sha256:fb47291596677570246d723ee6abbcbac07eeba89d8f83de31e3954f21f44879
# via
# -r installer/requirements.in
# accelerate
@@ -1882,26 +1877,26 @@ torchmetrics==0.10.2 \
--hash=sha256:43757d82266969906fc74b6e80766fcb2a0d52d6c3d09e3b7c98cf3b733fd20c \
--hash=sha256:daa29d96bff5cff04d80eec5b9f5076993d6ac9c2d2163e88b6b31f8d38f7c25
# via pytorch-lightning
torchvision==0.13.1 ; platform_system == "Darwin" \
--hash=sha256:0298bae3b09ac361866088434008d82b99d6458fe8888c8df90720ef4b347d44 \
--hash=sha256:08f592ea61836ebeceb5c97f4d7a813b9d7dc651bbf7ce4401563ccfae6a21fc \
--hash=sha256:099874088df104d54d8008f2a28539ca0117b512daed8bf3c2bbfa2b7ccb187a \
--hash=sha256:0e77706cc90462653620e336bb90daf03d7bf1b88c3a9a3037df8d111823a56e \
--hash=sha256:19286a733c69dcbd417b86793df807bd227db5786ed787c17297741a9b0d0fc7 \
--hash=sha256:3567fb3def829229ec217c1e38f08c5128ff7fb65854cac17ebac358ff7aa309 \
--hash=sha256:4d8bf321c4380854ef04613935fdd415dce29d1088a7ff99e06e113f0efe9203 \
--hash=sha256:5e631241bee3661de64f83616656224af2e3512eb2580da7c08e08b8c965a8ac \
--hash=sha256:7552e80fa222252b8b217a951c85e172a710ea4cad0ae0c06fbb67addece7871 \
--hash=sha256:7cb789ceefe6dcd0dc8eeda37bfc45efb7cf34770eac9533861d51ca508eb5b3 \
--hash=sha256:83e9e2457f23110fd53b0177e1bc621518d6ea2108f570e853b768ce36b7c679 \
--hash=sha256:87c137f343197769a51333076e66bfcd576301d2cd8614b06657187c71b06c4f \
--hash=sha256:899eec0b9f3b99b96d6f85b9aa58c002db41c672437677b553015b9135b3be7e \
--hash=sha256:8e4d02e4d8a203e0c09c10dfb478214c224d080d31efc0dbf36d9c4051f7f3c6 \
--hash=sha256:b167934a5943242da7b1e59318f911d2d253feeca0d13ad5d832b58eed943401 \
--hash=sha256:c5ed609c8bc88c575226400b2232e0309094477c82af38952e0373edef0003fd \
--hash=sha256:e9a563894f9fa40692e24d1aa58c3ef040450017cfed3598ff9637f404f3fe3b \
--hash=sha256:ef5fe3ec1848123cd0ec74c07658192b3147dcd38e507308c790d5943e87b88c \
--hash=sha256:f230a1a40ed70d51e463ce43df243ec520902f8725de2502e485efc5eea9d864
torchvision==0.13.0 ; platform_system == "Darwin" \
--hash=sha256:01e9e7b2e7724e66561e8d98f900985d80191e977c5c0b3f33ed31800ba0210c \
--hash=sha256:0e28740bd5695076f7c449af650fc474d6566722d446461c2ceebf9c9599b37f \
--hash=sha256:1b703701f0b99f307ad925b1abda2b3d5bdbf30643ff02102b6aeeb8840ae278 \
--hash=sha256:1e2049f1207631d42d743205f663f1d2235796565be3f18b0339d479626faf30 \
--hash=sha256:253eb0c67bf88cef4a79ec69058c3e94f9fde28b9e3699ad1afc0b3ed50f8075 \
--hash=sha256:42d95ab197d090efc5669fec02fbc603d05c859e50ca2c60180d1a113aa9b3e2 \
--hash=sha256:5c31e9b3004142dbfdf32adc4cf2d4fd709b820833e9786f839ae3a91ff65ef0 \
--hash=sha256:61d5093a50b7923a4e5bf9e0271001c29e01abec2348b7dd93370a0a9d15836c \
--hash=sha256:667cac55afb13cda7d362466e7eba3119e529b210e55507d231bead09aca5e1f \
--hash=sha256:6c4c35428c758adc485ff8f239b5ed68c1b6c26efa261a52e431cab0f7f22aec \
--hash=sha256:83a4d9d50787d1e886c94486b63b15978391f6cf1892fce6a93132c09b14e128 \
--hash=sha256:a20662c11dc14fd4eff102ceb946a7ee80b9f98303bb52435cc903f2c4c1fe10 \
--hash=sha256:acb72a40e5dc0cd454d28514dbdd589a5057afd9bb5c785b87a54718b999bfa1 \
--hash=sha256:ad458146aca15f652f9b0c227bebd5403602c7341f15f68f20ec119fa8e8f4a5 \
--hash=sha256:ada295dbfe55017b02acfab960a997387f5addbadd28ee5e575e24f692992ce4 \
--hash=sha256:b620a43df4131ad09f5761c415a016a9ea95aaf8ec8c91d030fb59bad591094a \
--hash=sha256:b7a2c9aebc7ef265777fe7e82577364288d98cf6b8cf0a63bb2621df78a7af1a \
--hash=sha256:c2278a189663087bb8e65915062aa7a25b8f8e5a3cfaa5879fe277e23e4bbf40 \
--hash=sha256:df16abf31e7a5fce8db1f781bf1e4f20c8bc730c7c3f657e946cc5820c04e465
# via
# -r installer/requirements.in
# basicsr

View File

@@ -1,9 +1,10 @@
#
# This file is autogenerated by pip-compile with python 3.9
# To update, run:
# This file is autogenerated by pip-compile with Python 3.9
# by the following command:
#
# pip-compile --allow-unsafe --generate-hashes --output-file=installer/py3.10-linux-x86_64-cuda-reqs.txt installer/requirements.in
# pip-compile --allow-unsafe --generate-hashes --output-file=binary_installer/py3.10-linux-x86_64-cuda-reqs.txt binary_installer/requirements.in
#
--extra-index-url https://download.pytorch.org/whl/torch_stable.html
--extra-index-url https://download.pytorch.org/whl/cu116
--trusted-host https
@@ -17,7 +18,7 @@ accelerate==0.14.0 \
--hash=sha256:31c5bcc40564ef849b5bc1c4424a43ccaf9e26413b7df89c2e36bf81f070fd44 \
--hash=sha256:b15d562c0889d0cf441b01faa025dfc29b163d061b6cc7d489c2c83b0a55ffab
# via
# -r installer/requirements.in
# -r binary_installer/requirements.in
# k-diffusion
addict==2.4.0 \
--hash=sha256:249bb56bbfd3cdc2a004ea0ff4c2b6ddc84d53bc2194761636eb314d5cfa5dfc \
@@ -119,7 +120,7 @@ aiosignal==1.2.0 \
albumentations==1.3.0 \
--hash=sha256:294165d87d03bc8323e484927f0a5c1a3c64b0e7b9c32a979582a6c93c363bdf \
--hash=sha256:be1af36832c8893314f2a5550e8ac19801e04770734c1b70fa3c996b41f37bed
# via -r installer/requirements.in
# via -r binary_installer/requirements.in
altair==4.2.0 \
--hash=sha256:0c724848ae53410c13fa28be2b3b9a9dcb7b5caa1a70f7f217bd663bb419935a \
--hash=sha256:d87d9372e63b48cd96b2a6415f0cf9457f50162ab79dc7a31cd7e024dd840026
@@ -150,6 +151,10 @@ blinker==1.5 \
--hash=sha256:1eb563df6fdbc39eeddc177d953203f99f097e9bf0e2b8f9f3cf18b6ca425e36 \
--hash=sha256:923e5e2f69c155f2cc42dafbbd70e16e3fde24d2d4aa2ab72fbe386238892462
# via streamlit
boltons==21.0.0 \
--hash=sha256:65e70a79a731a7fe6e98592ecfb5ccf2115873d01dbc576079874629e5c90f13 \
--hash=sha256:b9bb7b58b2b420bbe11a6025fdef6d3e5edc9f76a42fb467afe7ca212ef9948b
# via torchsde
cachetools==5.2.0 \
--hash=sha256:6a94c6402995a99c3970cc7e4884bb60b4a8639938157eeed436098bf9831757 \
--hash=sha256:f9f17d2aec496a9aa6b76f53e3b614c965223c061982d434d160f930c698a9db
@@ -183,11 +188,11 @@ click==8.1.3 \
clip @ https://github.com/openai/CLIP/archive/d50d76daa670286dd6cacf3bcd80b5e4823fc8e1.zip \
--hash=sha256:b5842c25da441d6c581b53a5c60e0c2127ebafe0f746f8e15561a006c6c3be6a
# via
# -r installer/requirements.in
# -r binary_installer/requirements.in
# clipseg
clipseg @ https://github.com/invoke-ai/clipseg/archive/1f754751c85d7d4255fa681f4491ff5711c1c288.zip \
--hash=sha256:14f43ed42f90be3fe57f06de483cb8be0f67f87a6f62a011339d45a39f4b4189
# via -r installer/requirements.in
# via -r binary_installer/requirements.in
commonmark==0.9.1 \
--hash=sha256:452f9dc859be7f06631ddcb328b6919c67984aca654e5fefb3914d54691aed60 \
--hash=sha256:da2f38c92590f83de410ba1a3cbceafbc74fee9def35f9251ba9a971d6d66fd9
@@ -274,7 +279,7 @@ decorator==5.1.1 \
diffusers==0.7.2 \
--hash=sha256:4a5f8b3a5fbd936bba7d459611cb35ec62875030367be32b232f9e19543e25a9 \
--hash=sha256:fb814ffd150cc6f470380b8c6a521181a77beb2f44134d2aad2e4cd8aa2ced0e
# via -r installer/requirements.in
# via -r binary_installer/requirements.in
dnspython==2.2.1 \
--hash=sha256:0f7569a4a6ff151958b64304071d370daa3243d15941a7beedf0c9fe5105603e \
--hash=sha256:a851e51367fb93e9e1361732c1d60dab63eff98712e503ea7d92e6eccb109b4f
@@ -294,7 +299,7 @@ entrypoints==0.4 \
eventlet==0.33.1 \
--hash=sha256:a085922698e5029f820cf311a648ac324d73cec0e4792877609d978a4b5bbf31 \
--hash=sha256:afbe17f06a58491e9aebd7a4a03e70b0b63fd4cf76d8307bae07f280479b1515
# via -r installer/requirements.in
# via -r binary_installer/requirements.in
facexlib==0.2.5 \
--hash=sha256:31e20cc4ed5d63562d380e4564bae14ac0d5d1899a079bad87621e13564567e4 \
--hash=sha256:cc7ceb56c5424319c47223cf75eef6828c34c66082707c6eb35b95d39779f02d
@@ -320,15 +325,15 @@ flask==2.2.2 \
flask-cors==3.0.10 \
--hash=sha256:74efc975af1194fc7891ff5cd85b0f7478be4f7f59fe158102e91abb72bb4438 \
--hash=sha256:b60839393f3b84a0f3746f6cdca56c1ad7426aa738b70d6c61375857823181de
# via -r installer/requirements.in
# via -r binary_installer/requirements.in
flask-socketio==5.3.1 \
--hash=sha256:fd0ed0fc1341671d92d5f5b2f5503916deb7aa7e2940e6636cfa2c087c828bf9 \
--hash=sha256:ff0c721f20bff1e2cfba77948727a8db48f187e89a72fe50c34478ce6efb3353
# via -r installer/requirements.in
# via -r binary_installer/requirements.in
flaskwebgui==0.3.7 \
--hash=sha256:4a69955308eaa8bb256ba04a994dc8f58a48dcd6f9599694ab1bcd9f43d88a5d \
--hash=sha256:535974ce2672dcc74787c254de24cceed4101be75d96952dae82014dd57f061e
# via -r installer/requirements.in
# via -r binary_installer/requirements.in
fonttools==4.38.0 \
--hash=sha256:2bb244009f9bf3fa100fc3ead6aeb99febe5985fa20afbfbaa2f8946c2fbdaf1 \
--hash=sha256:820466f43c8be8c3009aef8b87e785014133508f0de64ec469e4efb643ae54fb
@@ -412,11 +417,11 @@ future==0.18.2 \
getpass-asterisk==1.0.1 \
--hash=sha256:20d45cafda0066d761961e0919728526baf7bb5151fbf48a7d5ea4034127d857 \
--hash=sha256:7cc357a924cf62fa4e15b73cb4e5e30685c9084e464ffdc3fd9000a2b54ea9e9
# via -r installer/requirements.in
gfpgan @ https://github.com/TencentARC/GFPGAN/archive/2eac2033893ca7f427f4035d80fe95b92649ac56.zip \
--hash=sha256:79e6d71c8f1df7c7ccb0ac6b9a2ccb615ad5cde818c8b6f285a8711c05aebf85
# via -r binary_installer/requirements.in
gfpgan @ https://github.com/invoke-ai/GFPGAN/archive/c796277a1cf77954e5fc0b288d7062d162894248.zip ; platform_system == "Linux" or platform_system == "Darwin" \
--hash=sha256:4155907b8b7db3686324554df7007eedd245cdf8656c21da9d9a3f44bef2fcaa
# via
# -r installer/requirements.in
# -r binary_installer/requirements.in
# realesrgan
gitdb==4.0.9 \
--hash=sha256:8033ad4e853066ba6ca92050b9df2f89301b8fc8bf7e9324d412a63f8bf1a8fd \
@@ -577,7 +582,7 @@ imageio-ffmpeg==0.4.7 \
--hash=sha256:7a08838f97f363e37ca41821b864fd3fdc99ab1fe2421040c78eb5f56a9e723e \
--hash=sha256:8e724d12dfe83e2a6eb39619e820243ca96c81c47c2648e66e05f7ee24e14312 \
--hash=sha256:fc60686ef03c2d0f842901b206223c30051a6a120384458761390104470846fd
# via -r installer/requirements.in
# via -r binary_installer/requirements.in
importlib-metadata==5.0.0 \
--hash=sha256:da31db32b304314d044d3c12c79bd59e307889b287ad12ff387b3500835fc2ab \
--hash=sha256:ddb0e35065e8938f867ed4928d0ae5bf2a53b7773871bfe6bcc7e4fcdc7dea43
@@ -610,9 +615,9 @@ jsonschema==4.17.0 \
# via
# altair
# jsonmerge
k-diffusion @ https://github.com/invoke-ai/k-diffusion/archive/7f16b2c33411f26b3eae78d10648d625cb0c1095.zip \
--hash=sha256:c3f2c84036aa98c3abf4552fafab04df5ca472aa639982795e05bb1db43ce5e4
# via -r installer/requirements.in
k-diffusion @ https://github.com/Birch-san/k-diffusion/archive/363386981fee88620709cf8f6f2eea167bd6cd74.zip \
--hash=sha256:8eac5cdc08736e6d61908a1b2948f2b2f62691b01dc1aab978bddb3451af0d66
# via -r binary_installer/requirements.in
kiwisolver==1.4.4 \
--hash=sha256:02f79693ec433cb4b5f51694e8477ae83b3205768a6fb48ffba60549080e295b \
--hash=sha256:03baab2d6b4a54ddbb43bba1a3a2d1627e82d205c5cf8f4c924dc49284b87166 \
@@ -1005,6 +1010,7 @@ numpy==1.23.4 \
# tifffile
# torch-fidelity
# torchmetrics
# torchsde
# torchvision
# transformers
oauthlib==3.2.2 \
@@ -1091,7 +1097,7 @@ pathtools==0.1.2 \
picklescan==0.0.5 \
--hash=sha256:368cf1b9a075bc1b6460ad82b694f260532b836c82f99d13846cd36e1bbe7f9a \
--hash=sha256:57153eca04d5df5009f2cdd595aef261b8a6f27e03046a1c84f672aa6869c592
# via -r installer/requirements.in
# via -r binary_installer/requirements.in
pillow==9.3.0 \
--hash=sha256:03150abd92771742d4a8cd6f2fa6246d847dcd2e332a18d0c15cc75bf6703040 \
--hash=sha256:073adb2ae23431d3b9bcbcff3fe698b62ed47211d0716b067385538a1b0f28b8 \
@@ -1300,11 +1306,11 @@ pyparsing==3.0.9 \
# packaging
pypatchmatch @ https://github.com/invoke-ai/PyPatchMatch/archive/129863937a8ab37f6bbcec327c994c0f932abdbc.zip \
--hash=sha256:4ad6ec95379e7d122d494ff76633cc7cf9b71330d5efda147fceba81e3dc6cd2
# via -r installer/requirements.in
# via -r binary_installer/requirements.in
pyreadline3==3.4.1 \
--hash=sha256:6f3d1f7b8a31ba32b73917cefc1f28cc660562f39aea8646d30bd6eff21f7bae \
--hash=sha256:b0efb6516fd4fb07b45949053826a62fa4cb353db5be2bbb4a7aa1fdd1e345fb
# via -r installer/requirements.in
# via -r binary_installer/requirements.in
pyrsistent==0.19.2 \
--hash=sha256:055ab45d5911d7cae397dc418808d8802fb95262751872c841c170b0dbf51eed \
--hash=sha256:111156137b2e71f3a9936baf27cb322e8024dac3dc54ec7fb9f0bcf3249e68bb \
@@ -1441,7 +1447,7 @@ qudida==0.0.4 \
realesrgan==0.3.0 \
--hash=sha256:0d36da96ab9f447071606e91f502ccdfb08f80cc82ee4f8caf720c7745ccec7e \
--hash=sha256:59336c16c30dd5130eff350dd27424acb9b7281d18a6810130e265606c9a6088
# via -r installer/requirements.in
# via -r binary_installer/requirements.in
regex==2022.10.31 \
--hash=sha256:052b670fafbe30966bbe5d025e90b2a491f85dfe5b2583a163b5e60a85a321ad \
--hash=sha256:0653d012b3bf45f194e5e6a41df9258811ac8fc395579fa82958a8b76286bea4 \
@@ -1656,6 +1662,7 @@ scipy==1.9.3 \
# scikit-learn
# torch-fidelity
# torchdiffeq
# torchsde
semver==2.13.0 \
--hash=sha256:ced8b23dceb22134307c1b8abfa523da14198793d9787ac838e70e29e77458d4 \
--hash=sha256:fa0fe2722ee1c3f57eac478820c3a5ae2f624af8264cbdf9000c980ff7f75e3f
@@ -1663,7 +1670,7 @@ semver==2.13.0 \
send2trash==1.8.0 \
--hash=sha256:d2c24762fd3759860a0aff155e45871447ea58d2be6bdd39b5c8f966a0c99c2d \
--hash=sha256:f20eaadfdb517eaca5ce077640cb261c7d2698385a6a0f072a4a5447fd49fa08
# via -r installer/requirements.in
# via -r binary_installer/requirements.in
sentry-sdk==1.10.1 \
--hash=sha256:06c0fa9ccfdc80d7e3b5d2021978d6eb9351fa49db9b5847cf4d1f2a473414ad \
--hash=sha256:105faf7bd7b7fa25653404619ee261527266b14103fe1389e0ce077bd23a9691
@@ -1754,11 +1761,11 @@ smmap==5.0.0 \
streamlit==1.14.0 \
--hash=sha256:62556d873567e1b3427bcd118a57ee6946619f363bd6bba38df2d1f8225ecba0 \
--hash=sha256:e078b8143d150ba721bdb9194218e311c5fe1d6d4156473a2dea6cc848a6c9fc
# via -r installer/requirements.in
# via -r binary_installer/requirements.in
taming-transformers-rom1504==0.0.6 \
--hash=sha256:051b5804c58caa247bcd51d17ddb525b4d5f892a29d42dc460f40e3e9e34e5d8 \
--hash=sha256:73fe5fc1108accee4236ee6976e0987ab236afad0af06cb9f037641a908d2c32
# via -r installer/requirements.in
# via -r binary_installer/requirements.in
tb-nightly==2.11.0a20221106 \
--hash=sha256:8940457ee42db92f01da8bcdbbea1a476735eda559dde5976f5728919960af4a
# via
@@ -1783,7 +1790,7 @@ tensorboard-plugin-wit==1.8.1 \
# tensorboard
test-tube==0.7.5 \
--hash=sha256:1379c33eb8cde3e9b36610f87da0f16c2e06496b1cfebac473df4e7be2faa124
# via -r installer/requirements.in
# via -r binary_installer/requirements.in
threadpoolctl==3.1.0 \
--hash=sha256:8b99adda265feb6773280df41eece7b2e6561b772d21ffd52e372f999024907b \
--hash=sha256:a335baacfaa4400ae1f0d8e3a58d6674d2f8828e3716bb2802c44955ad391380
@@ -1843,7 +1850,7 @@ torch==1.12.0+cu116 ; platform_system == "Linux" or platform_system == "Windows"
--hash=sha256:aa43d7b54b86f723f17c5c44df1078c59a6149fc4d42fbef08aafab9d61451c9 \
--hash=sha256:f772be831447dd01ebd26cbedf619e668d1b269d69bf6b4ff46b1378362bff26
# via
# -r installer/requirements.in
# -r binary_installer/requirements.in
# accelerate
# basicsr
# clean-fid
@@ -1859,11 +1866,12 @@ torch==1.12.0+cu116 ; platform_system == "Linux" or platform_system == "Windows"
# torch-fidelity
# torchdiffeq
# torchmetrics
# torchsde
# torchvision
torch-fidelity==0.3.0 \
--hash=sha256:3d3e33db98919759cc4f3f24cb27e1e74bdc7c905d90a780630e4e1c18492b66 \
--hash=sha256:d01284825595feb7dc3eae3dc9a0d8ced02be764813a3483f109bc142b52a1d3
# via -r installer/requirements.in
# via -r binary_installer/requirements.in
torchdiffeq==0.2.3 \
--hash=sha256:b5b01ec1294a2d8d5f77e567bf17c5de1237c0573cb94deefa88326f0e18c338 \
--hash=sha256:fe75f434b9090ac0c27702e02bed21472b0f87035be6581f51edc5d4013ea31a
@@ -1872,6 +1880,10 @@ torchmetrics==0.10.2 \
--hash=sha256:43757d82266969906fc74b6e80766fcb2a0d52d6c3d09e3b7c98cf3b733fd20c \
--hash=sha256:daa29d96bff5cff04d80eec5b9f5076993d6ac9c2d2163e88b6b31f8d38f7c25
# via pytorch-lightning
torchsde==0.2.5 \
--hash=sha256:222be9e15610d37a4b5a71cfa0c442178f9fd9ca02f6522a3e11c370b3d0906b \
--hash=sha256:4c34373a94a357bdf60bbfee00c850f3563d634491555820b900c9a4f7eff300
# via k-diffusion
torchvision==0.13.0+cu116 ; platform_system == "Linux" or platform_system == "Windows" \
--hash=sha256:1696feadf1921c8fa1549bad774221293298288ebedaa14e44bc3e57e964a369 \
--hash=sha256:572544b108eaf12638f3dca0f496a453c4b8d8256bcc8333d5355df641c0380c \
@@ -1882,7 +1894,7 @@ torchvision==0.13.0+cu116 ; platform_system == "Linux" or platform_system == "Wi
--hash=sha256:cb6bf0117b8f4b601baeae54e8a6bb5c4942b054835ba997f438ddcb7adcfb90 \
--hash=sha256:d1a3c124645e3460b3e50b54eb89a2575a5036bfa618f15dc4f5d635c716069d
# via
# -r installer/requirements.in
# -r binary_installer/requirements.in
# basicsr
# clean-fid
# clip
@@ -1921,10 +1933,13 @@ tqdm==4.64.1 \
# taming-transformers-rom1504
# torch-fidelity
# transformers
trampoline==0.1.2 \
--hash=sha256:36cc9a4ff9811843d177fc0e0740efbd7da39eadfe6e50c9e2937cbc06d899d9
# via torchsde
transformers==4.24.0 \
--hash=sha256:486f353a8e594002e48be0e2aba723d96eda839e63bfe274702a4b5eda85559b \
--hash=sha256:b7ab50039ef9bf817eff14ab974f306fd20a72350bdc9df3a858fd009419322e
# via -r installer/requirements.in
# via -r binary_installer/requirements.in
typing-extensions==4.4.0 \
--hash=sha256:1511434bb92bf8dd198c12b1cc812e800d4181cfcb867674e0f8279cc93087aa \
--hash=sha256:16fa4864408f655d35ec496218b85f79b3437c829e93320c7c9215ccfd92489e

View File

@@ -4,6 +4,7 @@
#
# pip-compile --allow-unsafe --generate-hashes --output-file=installer/py3.10-windows-x86_64-cuda-reqs.txt installer/requirements.in
#
--extra-index-url https://download.pytorch.org/whl/torch_stable.html
--extra-index-url https://download.pytorch.org/whl/cu116
--trusted-host https
@@ -150,6 +151,10 @@ blinker==1.5 \
--hash=sha256:1eb563df6fdbc39eeddc177d953203f99f097e9bf0e2b8f9f3cf18b6ca425e36 \
--hash=sha256:923e5e2f69c155f2cc42dafbbd70e16e3fde24d2d4aa2ab72fbe386238892462
# via streamlit
boltons==21.0.0 \
--hash=sha256:65e70a79a731a7fe6e98592ecfb5ccf2115873d01dbc576079874629e5c90f13 \
--hash=sha256:b9bb7b58b2b420bbe11a6025fdef6d3e5edc9f76a42fb467afe7ca212ef9948b
# via torchsde
cachetools==5.2.0 \
--hash=sha256:6a94c6402995a99c3970cc7e4884bb60b4a8639938157eeed436098bf9831757 \
--hash=sha256:f9f17d2aec496a9aa6b76f53e3b614c965223c061982d434d160f930c698a9db
@@ -614,8 +619,8 @@ jsonschema==4.17.0 \
# via
# altair
# jsonmerge
k-diffusion @ https://github.com/invoke-ai/k-diffusion/archive/7f16b2c33411f26b3eae78d10648d625cb0c1095.zip \
--hash=sha256:c3f2c84036aa98c3abf4552fafab04df5ca472aa639982795e05bb1db43ce5e4
k-diffusion @ https://github.com/Birch-san/k-diffusion/archive/363386981fee88620709cf8f6f2eea167bd6cd74.zip \
--hash=sha256:8eac5cdc08736e6d61908a1b2948f2b2f62691b01dc1aab978bddb3451af0d66
# via -r installer/requirements.in
kiwisolver==1.4.4 \
--hash=sha256:02f79693ec433cb4b5f51694e8477ae83b3205768a6fb48ffba60549080e295b \
@@ -1009,6 +1014,7 @@ numpy==1.23.4 \
# tifffile
# torch-fidelity
# torchmetrics
# torchsde
# torchvision
# transformers
oauthlib==3.2.2 \
@@ -1660,6 +1666,7 @@ scipy==1.9.3 \
# scikit-learn
# torch-fidelity
# torchdiffeq
# torchsde
semver==2.13.0 \
--hash=sha256:ced8b23dceb22134307c1b8abfa523da14198793d9787ac838e70e29e77458d4 \
--hash=sha256:fa0fe2722ee1c3f57eac478820c3a5ae2f624af8264cbdf9000c980ff7f75e3f
@@ -1863,6 +1870,7 @@ torch==1.12.0+cu116 ; platform_system == "Linux" or platform_system == "Windows"
# torch-fidelity
# torchdiffeq
# torchmetrics
# torchsde
# torchvision
torch-fidelity==0.3.0 \
--hash=sha256:3d3e33db98919759cc4f3f24cb27e1e74bdc7c905d90a780630e4e1c18492b66 \
@@ -1876,6 +1884,10 @@ torchmetrics==0.10.2 \
--hash=sha256:43757d82266969906fc74b6e80766fcb2a0d52d6c3d09e3b7c98cf3b733fd20c \
--hash=sha256:daa29d96bff5cff04d80eec5b9f5076993d6ac9c2d2163e88b6b31f8d38f7c25
# via pytorch-lightning
torchsde==0.2.5 \
--hash=sha256:222be9e15610d37a4b5a71cfa0c442178f9fd9ca02f6522a3e11c370b3d0906b \
--hash=sha256:4c34373a94a357bdf60bbfee00c850f3563d634491555820b900c9a4f7eff300
# via k-diffusion
torchvision==0.13.0+cu116 ; platform_system == "Linux" or platform_system == "Windows" \
--hash=sha256:1696feadf1921c8fa1549bad774221293298288ebedaa14e44bc3e57e964a369 \
--hash=sha256:572544b108eaf12638f3dca0f496a453c4b8d8256bcc8333d5355df641c0380c \
@@ -1925,6 +1937,9 @@ tqdm==4.64.1 \
# taming-transformers-rom1504
# torch-fidelity
# transformers
trampoline==0.1.2 \
--hash=sha256:36cc9a4ff9811843d177fc0e0740efbd7da39eadfe6e50c9e2937cbc06d899d9
# via torchsde
transformers==4.24.0 \
--hash=sha256:486f353a8e594002e48be0e2aba723d96eda839e63bfe274702a4b5eda85559b \
--hash=sha256:b7ab50039ef9bf817eff14ab974f306fd20a72350bdc9df3a858fd009419322e

View File

@@ -1,5 +1,6 @@
--prefer-binary
--extra-index-url https://download.pytorch.org/whl/torch_stable.html
--extra-index-url https://download.pytorch.org/whl/cu116
--trusted-host https://download.pytorch.org
accelerate~=0.14
albumentations
@@ -25,6 +26,7 @@ transformers
picklescan
https://github.com/openai/CLIP/archive/d50d76daa670286dd6cacf3bcd80b5e4823fc8e1.zip
https://github.com/invoke-ai/clipseg/archive/1f754751c85d7d4255fa681f4491ff5711c1c288.zip
https://github.com/TencentARC/GFPGAN/archive/2eac2033893ca7f427f4035d80fe95b92649ac56.zip
https://github.com/invoke-ai/k-diffusion/archive/7f16b2c33411f26b3eae78d10648d625cb0c1095.zip
https://github.com/invoke-ai/GFPGAN/archive/3f5d2397361199bc4a91c08bb7d80f04d7805615.zip ; platform_system=='Windows'
https://github.com/invoke-ai/GFPGAN/archive/c796277a1cf77954e5fc0b288d7062d162894248.zip ; platform_system=='Linux' or platform_system=='Darwin'
https://github.com/Birch-san/k-diffusion/archive/363386981fee88620709cf8f6f2eea167bd6cd74.zip
https://github.com/invoke-ai/PyPatchMatch/archive/129863937a8ab37f6bbcec327c994c0f932abdbc.zip

View File

@@ -171,12 +171,12 @@ title: Changelog
- Integrate sd-v1-5 model into test matrix (easily expandable), remove
unecesarry caches by @mauwii in
https://github.com/invoke-ai/InvokeAI/pull/1293
- add --no-interactive to preload_models step by @mauwii in
- add --no-interactive to configure_invokeai step by @mauwii in
https://github.com/invoke-ai/InvokeAI/pull/1302
- 1-click installer and updater. Uses micromamba to install git and conda into a
contained environment (if necessary) before running the normal installation
script by @cmdr2 in https://github.com/invoke-ai/InvokeAI/pull/1253
- preload_models.py script downloads the weight files by @lstein in
- configure_invokeai.py script downloads the weight files by @lstein in
https://github.com/invoke-ai/InvokeAI/pull/1290
## v2.0.1 <small>(13 October 2022)</small>

View File

@@ -130,20 +130,34 @@ file should contain the startup options as you would type them on the
command line (`--steps=10 --grid`), one argument per line, or a
mixture of both using any of the accepted command switch formats:
!!! example ""
!!! example "my unmodified initialization file"
```bash
--web
--steps=28
--grid
-f 0.6 -C 11.0 -A k_euler_a
```bash title="~/.invokeai" linenums="1"
# InvokeAI initialization file
# This is the InvokeAI initialization file, which contains command-line default values.
# Feel free to edit. If anything goes wrong, you can re-initialize this file by deleting
# or renaming it and then running configure_invokeai.py again.
# The --root option below points to the folder in which InvokeAI stores its models, configs and outputs.
--root="/Users/mauwii/invokeai"
# the --outdir option controls the default location of image files.
--outdir="/Users/mauwii/invokeai/outputs"
# You may place other frequently-used startup commands here, one or more per line.
# Examples:
# --web --host=0.0.0.0
# --steps=20
# -Ak_euler_a -C10.0
```
Note that the initialization file only accepts the command line arguments.
There are additional arguments that you can provide on the `invoke>` command
line (such as `-n` or `--iterations`) that cannot be entered into this file.
Also be alert for empty blank lines at the end of the file, which will cause
an arguments error at startup time.
!!! note
The initialization file only accepts the command line arguments.
There are additional arguments that you can provide on the `invoke>` command
line (such as `-n` or `--iterations`) that cannot be entered into this file.
Also be alert for empty blank lines at the end of the file, which will cause
an arguments error at startup time.
## List of prompt arguments
@@ -195,15 +209,17 @@ Here are the invoke> command that apply to txt2img:
| `--with_variations <pattern>` | | `None` | Combine two or more variations. See [Variations](./VARIATIONS.md) for now to use this. |
| `--save_intermediates <n>` | | `None` | Save the image from every nth step into an "intermediates" folder inside the output directory |
Note that the width and height of the image must be multiples of 64. You can
provide different values, but they will be rounded down to the nearest multiple
of 64.
!!! note
### This is an example of img2img:
the width and height of the image must be multiples of 64. You can
provide different values, but they will be rounded down to the nearest multiple
of 64.
```
invoke> waterfall and rainbow -I./vacation-photo.png -W640 -H480 --fit
```
!!! example "This is a example of img2img"
```bash
invoke> waterfall and rainbow -I./vacation-photo.png -W640 -H480 --fit
```
This will modify the indicated vacation photograph by making it more like the
prompt. Results will vary greatly depending on what is in the image. We also ask
@@ -253,7 +269,7 @@ description of the part of the image to replace. For example, if you have an
image of a breakfast plate with a bagel, toast and scrambled eggs, you can
selectively mask the bagel and replace it with a piece of cake this way:
```
```bash
invoke> a piece of cake -I /path/to/breakfast.png -tm bagel
```
@@ -265,7 +281,7 @@ are getting too much or too little masking you can adjust the threshold down (to
get more mask), or up (to get less). In this example, by passing `-tm` a higher
value, we are insisting on a more stringent classification.
```
```bash
invoke> a piece of cake -I /path/to/breakfast.png -tm bagel 0.6
```
@@ -275,16 +291,16 @@ You can load and use hundreds of community-contributed Textual
Inversion models just by typing the appropriate trigger phrase. Please
see [Concepts Library](CONCEPTS.md) for more details.
# Other Commands
## Other Commands
The CLI offers a number of commands that begin with "!".
## Postprocessing images
### Postprocessing images
To postprocess a file using face restoration or upscaling, use the `!fix`
command.
### `!fix`
#### `!fix`
This command runs a post-processor on a previously-generated image. It takes a
PNG filename or path and applies your choice of the `-U`, `-G`, or `--embiggen`
@@ -311,19 +327,19 @@ Some examples:
[1] outputs/img-samples/000017.4829112.gfpgan-00.png: !fix "outputs/img-samples/0000045.4829112.png" -s 50 -S -W 512 -H 512 -C 7.5 -A k_lms -G 0.8
```
### !mask
#### `!mask`
This command takes an image, a text prompt, and uses the `clipseg` algorithm to
automatically generate a mask of the area that matches the text prompt. It is
useful for debugging the text masking process prior to inpainting with the
`--text_mask` argument. See [INPAINTING.md] for details.
## Model selection and importation
### Model selection and importation
The CLI allows you to add new models on the fly, as well as to switch among them
rapidly without leaving the script.
### !models
#### `!models`
This prints out a list of the models defined in `config/models.yaml'. The active
model is bold-faced
@@ -336,7 +352,7 @@ laion400m not loaded <no description>
waifu-diffusion not loaded Waifu Diffusion v1.3
</pre>
### !switch <model>
#### `!switch <model>`
This quickly switches from one model to another without leaving the CLI script.
`invoke.py` uses a memory caching system; once a model has been loaded,
@@ -361,7 +377,7 @@ invoke> !switch waifu-diffusion
| Making attention of type 'vanilla' with 512 in_channels
| Using faster float16 precision
>> Model loaded in 18.24s
>> Max VRAM used to load the model: 2.17G
>> Max VRAM used to load the model: 2.17G
>> Current VRAM usage:2.17G
>> Setting Sampler to k_lms
@@ -381,7 +397,7 @@ laion400m not loaded <no description>
waifu-diffusion cached Waifu Diffusion v1.3
</pre>
### !import_model <path/to/model/weights>
#### `!import_model <path/to/model/weights>`
This command imports a new model weights file into InvokeAI, makes it available
for image generation within the script, and writes out the configuration for the
@@ -428,10 +444,10 @@ OK to import [n]? <b>y</b>
| Working with z of shape (1, 4, 32, 32) = 4096 dimensions.
| Making attention of type 'vanilla' with 512 in_channels
| Using faster float16 precision
invoke>
invoke>
</pre>
###!edit_model <name_of_model>
#### `!edit_model <name_of_model>`
The `!edit_model` command can be used to modify a model that is already defined
in `config/models.yaml`. Call it with the short name of the model you wish to
@@ -468,12 +484,12 @@ text... Outputs: [2] outputs/img-samples/000018.2273800735.embiggen-00.png: !fix
"outputs/img-samples/000017.243781548.gfpgan-00.png" -s 50 -S 2273800735 -W 512
-H 512 -C 7.5 -A k_lms --embiggen 3.0 0.75 0.25 ```
## History processing
### History processing
The CLI provides a series of convenient commands for reviewing previous actions,
retrieving them, modifying them, and re-running them.
### !history
#### `!history`
The invoke script keeps track of all the commands you issue during a session,
allowing you to re-run them. On Mac and Linux systems, it also writes the
@@ -485,20 +501,22 @@ during the session (Windows), or the most recent 1000 commands (Mac|Linux). You
can then repeat a command by using the command `!NNN`, where "NNN" is the
history line number. For example:
```bash
invoke> !history
...
[14] happy woman sitting under tree wearing broad hat and flowing garment
[15] beautiful woman sitting under tree wearing broad hat and flowing garment
[18] beautiful woman sitting under tree wearing broad hat and flowing garment -v0.2 -n6
[20] watercolor of beautiful woman sitting under tree wearing broad hat and flowing garment -v0.2 -n6 -S2878767194
[21] surrealist painting of beautiful woman sitting under tree wearing broad hat and flowing garment -v0.2 -n6 -S2878767194
...
invoke> !20
invoke> watercolor of beautiful woman sitting under tree wearing broad hat and flowing garment -v0.2 -n6 -S2878767194
```
!!! example ""
### !fetch
```bash
invoke> !history
...
[14] happy woman sitting under tree wearing broad hat and flowing garment
[15] beautiful woman sitting under tree wearing broad hat and flowing garment
[18] beautiful woman sitting under tree wearing broad hat and flowing garment -v0.2 -n6
[20] watercolor of beautiful woman sitting under tree wearing broad hat and flowing garment -v0.2 -n6 -S2878767194
[21] surrealist painting of beautiful woman sitting under tree wearing broad hat and flowing garment -v0.2 -n6 -S2878767194
...
invoke> !20
invoke> watercolor of beautiful woman sitting under tree wearing broad hat and flowing garment -v0.2 -n6 -S2878767194
```
####`!fetch`
This command retrieves the generation parameters from a previously generated
image and either loads them into the command line (Linux|Mac), or prints them
@@ -508,33 +526,36 @@ a folder with image png files, and wildcard \*.png to retrieve the dream command
used to generate the images, and save them to a file commands.txt for further
processing.
This example loads the generation command for a single png file:
!!! example "load the generation command for a single png file"
```bash
invoke> !fetch 0000015.8929913.png
# the script returns the next line, ready for editing and running:
invoke> a fantastic alien landscape -W 576 -H 512 -s 60 -A plms -C 7.5
```
```bash
invoke> !fetch 0000015.8929913.png
# the script returns the next line, ready for editing and running:
invoke> a fantastic alien landscape -W 576 -H 512 -s 60 -A plms -C 7.5
```
This one fetches the generation commands from a batch of files and stores them
into `selected.txt`:
!!! example "fetch the generation commands from a batch of files and store them into `selected.txt`"
```bash
invoke> !fetch outputs\selected-imgs\*.png selected.txt
```
```bash
invoke> !fetch outputs\selected-imgs\*.png selected.txt
```
### !replay
#### `!replay`
This command replays a text file generated by !fetch or created manually
```
invoke> !replay outputs\selected-imgs\selected.txt
```
!!! example
Note that these commands may behave unexpectedly if given a PNG file that was
not generated by InvokeAI.
```bash
invoke> !replay outputs\selected-imgs\selected.txt
```
### !search <search string>
!!! note
These commands may behave unexpectedly if given a PNG file that was
not generated by InvokeAI.
#### `!search <search string>`
This is similar to !history but it only returns lines that contain
`search string`. For example:
@@ -544,7 +565,7 @@ invoke> !search surreal
[21] surrealist painting of beautiful woman sitting under tree wearing broad hat and flowing garment -v0.2 -n6 -S2878767194
```
### `!clear`
#### `!clear`
This clears the search history from memory and disk. Be advised that this
operation is irreversible and does not issue any warnings!

View File

@@ -1,130 +1,110 @@
---
title: The Hugging Face Concepts Library and Importing Textual Inversion files
title: Concepts Library
---
# :material-file-document: Concepts Library
# :material-library-shelves: The Hugging Face Concepts Library and Importing Textual Inversion files
## Using Textual Inversion Files
Textual inversion (TI) files are small models that customize the output of
Stable Diffusion image generation. They can augment SD with
specialized subjects and artistic styles. They are also known as
"embeds" in the machine learning world.
Stable Diffusion image generation. They can augment SD with specialized subjects
and artistic styles. They are also known as "embeds" in the machine learning
world.
Each TI file introduces one or more vocabulary terms to the SD
model. These are known in InvokeAI as "triggers." Triggers are often,
but not always, denoted using angle brackets as in
"&lt;trigger-phrase&gt;". The two most common type of TI files that you'll
encounter are `.pt` and `.bin` files, which are produced by different
TI training packages. InvokeAI supports both formats, but its [built-in
TI training system](TEXTUAL_INVERSION.md) produces `.pt`.
Each TI file introduces one or more vocabulary terms to the SD model. These are
known in InvokeAI as "triggers." Triggers are often, but not always, denoted
using angle brackets as in "&lt;trigger-phrase&gt;". The two most common type of
TI files that you'll encounter are `.pt` and `.bin` files, which are produced by
different TI training packages. InvokeAI supports both formats, but its
[built-in TI training system](TEXTUAL_INVERSION.md) produces `.pt`.
The [Hugging Face company](https://huggingface.co/sd-concepts-library)
has amassed a large ligrary of &gt;800 community-contributed TI files
covering a broad range of subjects and styles. InvokeAI has built-in
support for this library which downloads and merges TI files
automatically upon request. You can also install your own or others'
TI files by placing them in a designated directory.
The [Hugging Face company](https://huggingface.co/sd-concepts-library) has
amassed a large ligrary of &gt;800 community-contributed TI files covering a
broad range of subjects and styles. InvokeAI has built-in support for this
library which downloads and merges TI files automatically upon request. You can
also install your own or others' TI files by placing them in a designated
directory.
### An Example
Here are a few examples to illustrate how it works. All these images
were generated using the command-line client and the Stable Diffusion
1.5 model:
Here are a few examples to illustrate how it works. All these images were
generated using the command-line client and the Stable Diffusion 1.5 model:
Japanese gardener
<br>
<img src="../assets/concepts/image1.png">
Japanese gardener &lt;ghibli-face&gt;
<br>
<img src="../assets/concepts/image2.png">
Japanese gardener &lt;hoi4-leaders&gt;
<br>
<img src="../assets/concepts/image3.png">
Japanese gardener &lt;cartoona-animals&gt;
<br>
<img src="../assets/concepts/image4.png">
| Japanese gardener | Japanese gardener &lt;ghibli-face&gt; | Japanese gardener &lt;hoi4-leaders&gt; | Japanese gardener &lt;cartoona-animals&gt; |
| :--------------------------------: | :-----------------------------------: | :------------------------------------: | :----------------------------------------: |
| ![](../assets/concepts/image1.png) | ![](../assets/concepts/image2.png) | ![](../assets/concepts/image3.png) | ![](../assets/concepts/image4.png) |
You can also combine styles and concepts:
A portrait of &lt;alf&gt; in &lt;cartoona-animal&gt; style
<br>
<img src="../assets/concepts/image5.png">
<figure markdown>
![](../assets/concepts/image5.png)
<figcaption>A portrait of &lt;alf&gt; in &lt;cartoona-animal&gt; style</figcaption>
</figure>
## Using a Hugging Face Concept
Hugging Face TI concepts are downloaded and installed automatically as
you require them. This requires your machine to be connected to the
Internet. To find out what each concept is for, you can browse the
[Hugging Face concepts
library](https://huggingface.co/sd-concepts-library) and look at
examples of what each concept produces.
Hugging Face TI concepts are downloaded and installed automatically as you
require them. This requires your machine to be connected to the Internet. To
find out what each concept is for, you can browse the
[Hugging Face concepts library](https://huggingface.co/sd-concepts-library) and
look at examples of what each concept produces.
When you have an idea of a concept you wish to try, go to the
command-line client (CLI) and type a "&lt;" character and the beginning
of the Hugging Face concept name you wish to load. Press the Tab key,
and the CLI will show you all matching concepts. You can also type "&lt;"
and Tab to get a listing of all ~800 concepts, but be prepared to
scroll up to see them all! If there is more than one match you can
continue to type and Tab until the concept is completed.
When you have an idea of a concept you wish to try, go to the command-line
client (CLI) and type a "&lt;" character and the beginning of the Hugging Face
concept name you wish to load. Press the Tab key, and the CLI will show you all
matching concepts. You can also type "&lt;" and Tab to get a listing of all ~800
concepts, but be prepared to scroll up to see them all! If there is more than
one match you can continue to type and Tab until the concept is completed.
For example if you type "&lt;x" and Tab, you'll be prompted with the completions:
For example if you type "&lt;x" and Tab, you'll be prompted with the
completions:
```
<xatu2> <xatu> <xbh> <xi> <xidiversity> <xioboma> <xuna> <xyz>
<xatu2> <xatu> <xbh> <xi> <xidiversity> <xioboma> <xuna> <xyz>
```
Now type "id" and press Tab. It will be autocompleted to
"&lt;xidiversity&gt;" because this is a unique match.
Now type "id" and press Tab. It will be autocompleted to "&lt;xidiversity&gt;"
because this is a unique match.
Finish your prompt and generate as usual. You may include multiple
concept terms in the prompt.
Finish your prompt and generate as usual. You may include multiple concept terms
in the prompt.
If you have never used this concept before, you will see a message
that the TI model is being downloaded and installed. After this, the
concept will be saved locally (in the `models/sd-concepts-library`
directory) for future use.
If you have never used this concept before, you will see a message that the TI
model is being downloaded and installed. After this, the concept will be saved
locally (in the `models/sd-concepts-library` directory) for future use.
Several steps happen during downloading and
installation, including a scan of the file for malicious code. Should
any errors occur, you will be warned and the concept will fail to
load. Generation will then continue treating the trigger term as a
normal string of characters (e.g. as literal "&lt;ghibli-face&gt;").
Several steps happen during downloading and installation, including a scan of
the file for malicious code. Should any errors occur, you will be warned and the
concept will fail to load. Generation will then continue treating the trigger
term as a normal string of characters (e.g. as literal "&lt;ghibli-face&gt;").
Currently auto-installation of concepts is a feature only available on
the command-line client. Support for the WebUI is a work in progress.
Currently auto-installation of concepts is a feature only available on the
command-line client. Support for the WebUI is a work in progress.
## Installing your Own TI Files
You may install any number of `.pt` and `.bin` files simply by copying
them into the `embeddings` directory of the InvokeAI runtime directory
(usually `invokeai` in your home directory). You may create
subdirectories in order to organize the files in any way you wish. Be
careful not to overwrite one file with another. For example, TI files
generated by the Hugging Face toolkit share the named
`learned_embedding.bin`. You can use subdirectories to keep them
distinct.
You may install any number of `.pt` and `.bin` files simply by copying them into
the `embeddings` directory of the InvokeAI runtime directory (usually `invokeai`
in your home directory). You may create subdirectories in order to organize the
files in any way you wish. Be careful not to overwrite one file with another.
For example, TI files generated by the Hugging Face toolkit share the named
`learned_embedding.bin`. You can use subdirectories to keep them distinct.
At startup time, InvokeAI will scan the `embeddings` directory and
load any TI files it finds there. At startup you will see a message
similar to this one:
At startup time, InvokeAI will scan the `embeddings` directory and load any TI
files it finds there. At startup you will see a message similar to this one:
```
```bash
>> Current embedding manager terms: *, <HOI4-Leader>, <princess-knight>
```
Note the "*" trigger term. This is a placeholder term that many early
TI tutorials taught people to use rather than a more descriptive
term. Unfortunately, if you have multiple TI files that all use this
term, only the first one loaded will be triggered by use of the term.
Note the `*` trigger term. This is a placeholder term that many early TI
tutorials taught people to use rather than a more descriptive term.
Unfortunately, if you have multiple TI files that all use this term, only the
first one loaded will be triggered by use of the term.
To avoid this problem, you can use the `merge_embeddings.py` script to
merge two or more TI files together. If it encounters a collision of
terms, the script will prompt you to select new terms that do not
collide. See [Textual Inversion](TEXTUAL_INVERSION.md) for details.
To avoid this problem, you can use the `merge_embeddings.py` script to merge two
or more TI files together. If it encounters a collision of terms, the script
will prompt you to select new terms that do not collide. See
[Textual Inversion](TEXTUAL_INVERSION.md) for details.
## Further Reading

View File

@@ -12,21 +12,19 @@ stable diffusion to build the prompt on top of the image you provide, preserving
the original's basic shape and layout. To use it, provide the `--init_img`
option as shown here:
```commandline
tree on a hill with a river, nature photograph, national geographic -I./test-pictures/tree-and-river-sketch.png -f 0.85
```
!!! example ""
This will take the original image shown here:
```commandline
tree on a hill with a river, nature photograph, national geographic -I./test-pictures/tree-and-river-sketch.png -f 0.85
```
<figure markdown>
![original-image](https://user-images.githubusercontent.com/50542132/193946000-c42a96d8-5a74-4f8a-b4c3-5213e6cadcce.png){ width=320 }
</figure>
<figure markdown>
and generate a new image based on it as shown here:
| original image | generated image |
| :------------: | :-------------: |
| ![original-image](https://user-images.githubusercontent.com/50542132/193946000-c42a96d8-5a74-4f8a-b4c3-5213e6cadcce.png){ width=320 } | ![generated-image](https://user-images.githubusercontent.com/111189/194135515-53d4c060-e994-4016-8121-7c685e281ac9.png){ width=320 } |
<figure markdown>
![generated-image](https://user-images.githubusercontent.com/111189/194135515-53d4c060-e994-4016-8121-7c685e281ac9.png){ width=320 }
</figure>
</figure>
The `--init_img` (`-I`) option gives the path to the seed picture. `--strength`
(`-f`) controls how much the original will be modified, ranging from `0.0` (keep
@@ -88,13 +86,15 @@ from a prompt. If the step count is 10, then the "latent space" (Stable
Diffusion's internal representation of the image) for the prompt "fire" with
seed `1592514025` develops something like this:
```bash
invoke> "fire" -s10 -W384 -H384 -S1592514025
```
!!! example ""
<figure markdown>
![latent steps](../assets/img2img/000019.steps.png)
</figure>
```bash
invoke> "fire" -s10 -W384 -H384 -S1592514025
```
<figure markdown>
![latent steps](../assets/img2img/000019.steps.png){ width=720 }
</figure>
Put simply: starting from a frame of fuzz/static, SD finds details in each frame
that it thinks look like "fire" and brings them a little bit more into focus,
@@ -109,25 +109,23 @@ into the sequence at the appropriate point, with just the right amount of noise.
### A concrete example
I want SD to draw a fire based on this hand-drawn image:
!!! example "I want SD to draw a fire based on this hand-drawn image"
<figure markdown>
![drawing of a fireplace](../assets/img2img/fire-drawing.png)
</figure>
![drawing of a fireplace](../assets/img2img/fire-drawing.png){ align=left }
Let's only do 10 steps, to make it easier to see what's happening. If strength
is `0.7`, this is what the internal steps the algorithm has to take will look
like:
Let's only do 10 steps, to make it easier to see what's happening. If strength
is `0.7`, this is what the internal steps the algorithm has to take will look
like:
<figure markdown>
![gravity32](../assets/img2img/000032.steps.gravity.png)
</figure>
<figure markdown>
![gravity32](../assets/img2img/000032.steps.gravity.png)
</figure>
With strength `0.4`, the steps look more like this:
With strength `0.4`, the steps look more like this:
<figure markdown>
![gravity30](../assets/img2img/000030.steps.gravity.png)
</figure>
<figure markdown>
![gravity30](../assets/img2img/000030.steps.gravity.png)
</figure>
Notice how much more fuzzy the starting image is for strength `0.7` compared to
`0.4`, and notice also how much longer the sequence is with `0.7`:

View File

@@ -120,7 +120,7 @@ A number of caveats:
(`--iterations`) argument.
3. Your results will be _much_ better if you use the `inpaint-1.5` model
released by runwayML and installed by default by `scripts/preload_models.py`.
released by runwayML and installed by default by `scripts/configure_invokeai.py`.
This model was trained specifically to harmoniously fill in image gaps. The
standard model will work as well, but you may notice color discontinuities at
the border.

View File

@@ -28,21 +28,17 @@ should "just work" without further intervention. Simply pass the `--upscale`
the popup in the Web GUI.
**GFPGAN** requires a series of downloadable model files to work. These are
loaded when you run `scripts/preload_models.py`. If GFPAN is failing with an
loaded when you run `scripts/configure_invokeai.py`. If GFPAN is failing with an
error, please run the following from the InvokeAI directory:
```bash
python scripts/preload_models.py
python scripts/configure_invokeai.py
```
If you do not run this script in advance, the GFPGAN module will attempt to
download the models files the first time you try to perform facial
reconstruction.
## Usage
You will now have access to two new prompt arguments.
### Upscaling
`-U : <upscaling_factor> <upscaling_strength>`
@@ -110,7 +106,7 @@ This repo also allows you to perform face restoration using
[CodeFormer](https://github.com/sczhou/CodeFormer).
In order to setup CodeFormer to work, you need to download the models like with
GFPGAN. You can do this either by running `preload_models.py` or by manually
GFPGAN. You can do this either by running `configure_invokeai.py` or by manually
downloading the
[model file](https://github.com/sczhou/CodeFormer/releases/download/v0.1.0/codeformer.pth)
and saving it to `ldm/invoke/restoration/codeformer/weights` folder.
@@ -119,7 +115,7 @@ You can use `-ft` prompt argument to swap between CodeFormer and the default
GFPGAN. The above mentioned `-G` prompt argument will allow you to control the
strength of the restoration effect.
### Usage
### CodeFormer Usage
The following command will perform face restoration with CodeFormer instead of
the default gfpgan.
@@ -160,7 +156,7 @@ A new file named `000044.2945021133.fixed.png` will be created in the output
directory. Note that the `!fix` command does not replace the original file,
unlike the behavior at generate time.
### Disabling
## How to disable
If, for some reason, you do not wish to load the GFPGAN and/or ESRGAN libraries,
you can disable them on the invoke.py command line with the `--no_restore` and

5
docs/features/index.md Normal file
View File

@@ -0,0 +1,5 @@
---
title: Overview
---
Here you can find the documentation for different features.

View File

@@ -86,6 +86,10 @@ AMD card (using the ROCm driver). For full installation and upgrade
instructions, please see:
[InvokeAI Installation Overview](https://invoke-ai.github.io/InvokeAI/installation/)
Linux users who wish to make use of the PyPatchMatch inpainting
functions will need to perform a bit of extra work to enable this
module. Instructions can be found at [Installing PyPatchMatch](installation/INSTALL_PATCHMATCH.md).
## :fontawesome-solid-computer: Hardware Requirements
### :octicons-cpu-24: System
@@ -123,7 +127,8 @@ You wil need one of the following:
- [The InvokeAI Web Interface](features/WEB.md)
- [WebGUI hotkey reference guide](features/WEBUIHOTKEYS.md)
<!-- this link does not exist - [WebGUI Unified Canvas for Img2Img, inpainting and outpainting](features/UNIFIED_CANVAS.md) -->
- [WebGUI Unified Canvas for Img2Img, inpainting and outpainting](features/UNIFIED_CANVAS.md)
<!-- seperator -->
- [The Command Line Interace](features/CLI.md)
- [Image2Image](features/IMG2IMG.md)
- [Inpainting](features/INPAINTING.md)
@@ -136,6 +141,7 @@ You wil need one of the following:
- [Prompt Engineering](features/PROMPTS.md)
<!-- seperator -->
- Miscellaneous
- [NSFW Checker](features/NSFW.md)
- [Embiggen upscaling](features/EMBIGGEN.md)
- [Other](features/OTHER.md)
@@ -160,7 +166,7 @@ You wil need one of the following:
- You can now load
[multiple models and switch among them quickly](https://docs.google.com/presentation/d/1WywGA1rny7bpFh7CLSdTr4nNpVKdlUeT0Bj0jCsILyU/edit?usp=sharing)
without leaving the CLI.
- The installation process (via `scripts/preload_models.py`) now lets you select
- The installation process (via `scripts/configure_invokeai.py`) now lets you select
among several popular
[Stable Diffusion models](https://invoke-ai.github.io/InvokeAI/installation/INSTALLING_MODELS/)
and downloads and installs them on your behalf. Among other models, this

View File

@@ -0,0 +1,89 @@
---
title: build binary installers
---
# :simple-buildkite: How to build "binary" installers (InvokeAI-mac/windows/linux_on_*.zip)
## 1. Ensure `installers/requirements.in` is correct
and up to date on the branch to be installed.
## <a name="step-2"></a> 2. Run `pip-compile` on each platform.
On each target platform, in the branch that is to be installed, and
inside the InvokeAI git root folder, run the following commands:
```commandline
conda activate invokeai # or however you activate python
pip install pip-tools
pip-compile --allow-unsafe --generate-hashes --output-file=binary_installer/<reqsfile>.txt binary_installer/requirements.in
```
where `<reqsfile>.txt` is whichever of
```commandline
py3.10-darwin-arm64-mps-reqs.txt
py3.10-darwin-x86_64-reqs.txt
py3.10-linux-x86_64-cuda-reqs.txt
py3.10-windows-x86_64-cuda-reqs.txt
```
matches the current OS and architecture.
> There is no way to cross-compile these. They must be done on a system matching the target OS and arch.
## <a name="step-3"></a> 3. Set github repository and branch
Once all reqs files have been collected and committed **to the branch
to be installed**, edit `binary_installer/install.sh.in` and `binary_installer/install.bat.in` so that `RELEASE_URL`
and `RELEASE_SOURCEBALL` point to the github repo and branch that is
to be installed.
For example, to install `main` branch of `InvokeAI`, they should be
set as follows:
`install.sh.in`:
```commandline
RELEASE_URL=https://github.com/invoke-ai/InvokeAI
RELEASE_SOURCEBALL=/archive/refs/heads/main.tar.gz
```
`install.bat.in`:
```commandline
set RELEASE_URL=https://github.com/invoke-ai/InvokeAI
set RELEASE_SOURCEBALL=/archive/refs/heads/main.tar.gz
```
Or, to install `damians-cool-feature` branch of `damian0815`, set them
as follows:
`install.sh.in`:
```commandline
RELEASE_URL=https://github.com/damian0815/InvokeAI
RELEASE_SOURCEBALL=/archive/refs/heads/damians-cool-feature.tar.gz
```
`install.bat.in`:
```commandline
set RELEASE_URL=https://github.com/damian0815/InvokeAI
set RELEASE_SOURCEBALL=/archive/refs/heads/damians-cool-feature.tar.gz
```
The branch and repo specified here **must** contain the correct reqs
files. The installer zip files **do not** contain requirements files,
they are pulled from the specified branch during the installation
process.
## 4. Create zip files.
cd into the `installers/` folder and run
`./create_installers.sh`. This will create
`InvokeAI-mac_on_<branch>.zip`,
`InvokeAI-windows_on_<branch>.zip` and
`InvokeAI-linux_on_<branch>.zip`. These files can be distributed to end users.
These zips will continue to function as installers for all future
pushes to those branches, as long as necessary changes to
`requirements.in` are propagated in a timely manner to the
`py3.10-*-reqs.txt` files using pip-compile as outlined in [step
2](#step-2).
To actually install, users should unzip the appropriate zip file into an empty
folder and run `install.sh` on macOS/Linux or `install.bat` on
Windows.

View File

@@ -56,7 +56,7 @@ unofficial Stable Diffusion models and where they can be obtained.
There are three ways to install weights files:
1. During InvokeAI installation, the `preload_models.py` script can download
1. During InvokeAI installation, the `configure_invokeai.py` script can download
them for you.
2. You can use the command-line interface (CLI) to import, configure and modify
@@ -65,13 +65,13 @@ There are three ways to install weights files:
3. You can download the files manually and add the appropriate entries to
`models.yaml`.
### Installation via `preload_models.py`
### Installation via `configure_invokeai.py`
This is the most automatic way. Run `scripts/preload_models.py` from the
This is the most automatic way. Run `scripts/configure_invokeai.py` from the
console. It will ask you to select which models to download and lead you through
the steps of setting up a Hugging Face account if you haven't done so already.
To start, run `python scripts/preload_models.py` from within the InvokeAI:
To start, run `python scripts/configure_invokeai.py` from within the InvokeAI:
directory
!!! example ""
@@ -162,6 +162,12 @@ the command-line client's `!import_model` command.
Type a bit of the path name and hit ++tab++ in order to get a choice of
possible completions.
!!! tip "on Windows, you can drag model files onto the command-line"
Once you have typed in `!import_model `, you can drag the model `.ckpt` file
onto the command-line to insert the model path. This way, you don't need to
type it or copy/paste.
4. Follow the wizard's instructions to complete installation as shown in the
example here:
@@ -238,7 +244,7 @@ arabian-nights-1.0:
| arabian-nights-1.0 | This is the name of the model that you will refer to from within the CLI and the WebGUI when you need to load and use the model. |
| description | Any description that you want to add to the model to remind you what it is. |
| weights | Relative path to the .ckpt weights file for this model. |
| config | This is the confusingly-named configuration file for the model itself. Use `./configs/stable-diffusion/v1-inference.yaml` unless the model happens to need a custom configuration, in which case the place you downloaded it from will tell you what to use instead. For example, the runwayML custom inpainting model requires the file `configs/stable-diffusion/v1-inpainting-inference.yaml`. This is already inclued in the InvokeAI distribution and is configured automatically for you by the `preload_models.py` script. |
| config | This is the confusingly-named configuration file for the model itself. Use `./configs/stable-diffusion/v1-inference.yaml` unless the model happens to need a custom configuration, in which case the place you downloaded it from will tell you what to use instead. For example, the runwayML custom inpainting model requires the file `configs/stable-diffusion/v1-inpainting-inference.yaml`. This is already inclued in the InvokeAI distribution and is configured automatically for you by the `configure_invokeai.py` script. |
| vae | If you want to add a VAE file to the model, then enter its path here. |
| width, height | This is the width and height of the images used to train the model. Currently they are always 512 and 512. |

View File

@@ -1,8 +1,8 @@
---
title: InvokeAI Installer
title: InvokeAI Binary Installer
---
The InvokeAI installer is a shell script that will install InvokeAI onto a stock
The InvokeAI binary installer is a shell script that will install InvokeAI onto a stock
computer running recent versions of Linux, MacOSX or Windows. It will leave you
with a version that runs a stable version of InvokeAI. When a new version of
InvokeAI is released, you will download and reinstall the new version.
@@ -36,7 +36,7 @@ recommended model weights files.
1. Download the
[latest release](https://github.com/invoke-ai/InvokeAI/releases/latest) of
InvokeAI's installer for your platform
InvokeAI's installer for your platform. Look for a file named `InvokeAI-binary-<your platform>.zip`
2. Place the downloaded package someplace where you have plenty of HDD space,
and have full permissions (i.e. `~/` on Lin/Mac; your home folder on Windows)

View File

@@ -2,7 +2,7 @@
title: Running InvokeAI on Google Colab using a Jupyter Notebook
---
# THIS NEEDS TO BE FLESHED OUT
# THIS DOCUMENTATION IS UNFINISHED - VOLUNTEERS GRATEFULLY ACCEPTED
## Introduction
@@ -22,6 +22,4 @@ start running the cells one-by-one.
### Updating the stable version
### Updating to the development version
## Troubleshooting

View File

@@ -155,10 +155,10 @@ command-line completion.
process for this is described in [here](INSTALLING_MODELS.md).
```bash
python scripts/preload_models.py
python scripts/configure_invokeai.py
```
The script `preload_models.py` will interactively guide you through the
The script `configure_invokeai.py` will interactively guide you through the
process of downloading and installing the weights files needed for InvokeAI.
Note that the main Stable Diffusion weights file is protected by a license
agreement that you have to agree to. The script will list the steps you need
@@ -220,7 +220,7 @@ greatest version, launch the Anaconda window, enter `InvokeAI` and type:
```bash
git pull
conda env update
python scripts/preload_models.py --no-interactive #optional
python scripts/configure_invokeai.py --no-interactive #optional
```
This will bring your local copy into sync with the remote one. The last step may
@@ -359,7 +359,7 @@ brew install llvm
If brew config has Clang installed, update to the latest llvm and try creating the environment again.
#### `preload_models.py` or `invoke.py` crashes at an early stage
#### `configure_invokeai.py` or `invoke.py` crashes at an early stage
This is usually due to an incomplete or corrupted Conda install. Make sure you
have linked to the correct environment file and run `conda update` again.

View File

@@ -0,0 +1,86 @@
---
title: Installing PyPatchMatch
---
# :octicons-paintbrush-16: Installing PyPatchMatch
pypatchmatch is a Python module for inpainting images. It is not
needed to run InvokeAI, but it greatly improves the quality of
inpainting and outpainting and is recommended.
Unfortunately, it is a C++ optimized module and installation
can be somewhat challenging. This guide leads you through the steps.
## Windows
You're in luck! On Windows platforms PyPatchMatch will install
automatically on Windows systems with no extra intervention.
## Macintosh
PyPatchMatch is not currently supported, but the team is working on
it.
## Linux
Prior to installing PyPatchMatch, you need to take the following
steps:
1. Install the `build-essential` tools:
```
sudo apt update
sudo apt install build-essential
```
2. Install `opencv`:
```
sudo apt install python3-opencv libopencv-dev
```
3. Fix the naming of the `opencv` package configuration file:
```
cd /usr/lib/x86_64-linux-gnu/pkgconfig/
ln -sf opencv4.pc opencv.pc
4. Activate the environment you use for invokeai, either with
`conda` or with a virtual environment.
5. Do a "develop" install of pypatchmatch:
```
pip install -e git+https://github.com/invoke-ai/PyPatchMatch@0.1.3#egg=pypatchmatch
```
6. Confirm that pypatchmatch is installed.
At the command-line prompt enter `python`, and
then at the `>>>` line type `from patchmatch import patch_match`:
It should look like the follwing:
```
Python 3.9.5 (default, Nov 23 2021, 15:27:38)
[GCC 9.3.0] on linux
Type "help", "copyright", "credits" or "license" for more information.
>>> from patchmatch import patch_match
Compiling and loading c extensions from "/home/lstein/Projects/InvokeAI/.invokeai-env/src/pypatchmatch/patchmatch".
rm -rf build/obj libpatchmatch.so
mkdir: created directory 'build/obj'
mkdir: created directory 'build/obj/csrc/'
[dep] csrc/masked_image.cpp ...
[dep] csrc/nnf.cpp ...
[dep] csrc/inpaint.cpp ...
[dep] csrc/pyinterface.cpp ...
[CC] csrc/pyinterface.cpp ...
[CC] csrc/inpaint.cpp ...
[CC] csrc/nnf.cpp ...
[CC] csrc/masked_image.cpp ...
[link] libpatchmatch.so ...
```
If you see no errors, then you're ready to go!

View File

@@ -27,7 +27,7 @@ Though there are multiple steps, there really is only one click involved to kick
off the process.
1. The source installer is distributed in ZIP files. Go to the
[latest release](https://github.com/invoke-ai/InvokeAI/releases/latest), and
[latest release](https://github.com/invoke-ai/InvokeAI/releases/tag/2.2.0-rc4), and
look for a series of files named:
- invokeAI-src-installer-mac.zip
@@ -55,7 +55,7 @@ off the process.
named `install.bat` on Windows systems and `install.sh` on Linux and
Macintosh systems.
4. Alternatively, form the command line, run the shell script or .bat file:
4. Alternatively, from the command line, run the shell script or .bat file:
```cmd
C:\Documents\Linco> cd invokeAI
@@ -66,8 +66,17 @@ off the process.
requirements including Conda, Git and Python, then download the current
InvokeAI code and install it along with its dependencies.
Be aware that some of the library download and install steps take a long time.
In particular, the `pytorch` package is quite large and often appears to get
"stuck" at 99.9%. Similarly, the `pip installing requirements` step may
appear to hang. Have patience and the installation step will eventually
resume. However, there are occasions when the library install does
legitimately get stuck. If you have been waiting for more than ten minutes
and nothing is happening, you can interrupt the script with ^C. You may restart
it and it will pick up where it left off.
6. After installation completes, the installer will launch a script called
`preload_models.py`, which will guide you through the first-time process of
`configure_invokeai.py`, which will guide you through the first-time process of
selecting one or more Stable Diffusion model weights files, downloading and
configuring them.
@@ -110,6 +119,71 @@ python scripts/invoke.py --web --max_load_models=3 \
These options are described in detail in the
[Command-Line Interface](../features/CLI.md) documentation.
## Troubleshooting
_Package dependency conflicts_ If you have previously installed
InvokeAI or another Stable Diffusion package, the installer may
occasionally pick up outdated libraries and either the installer or
`invoke` will fail with complaints out library conflicts. There are
two steps you can take to clear this problem. Both of these are done
from within the "developer's console", which you can get to by
launching `invoke.sh` (or `invoke.bat`) and selecting launch option
#3:
1. Remove the previous `invokeai` environment completely. From within
the developer's console, give the command `conda env remove -n
invokeai`. This will delete previous files installed by `invoke`.
Then exit from the developer's console and launch the script
`update.sh` (or `update.bat`). This will download the most recent
InvokeAI (including bug fixes) and reinstall the environment.
You should then be able to run `invoke.sh`/`invoke.bat`.
2. If this doesn't work, you can try cleaning your system's conda
cache. This is slightly more extreme, but won't interfere with
any other python-based programs installed on your computer.
From the developer's console, run the command `conda clean -a`
and answer "yes" to all prompts.
After this is done, run `update.sh` and try again as before.
_"Corrupted configuration file."__ Everything seems to install ok, but
`invoke` complains of a corrupted configuration file and goes calls
`configure_invokeai.py` to fix, but this doesn't fix the problem.
This issue is often caused by a misconfigured configuration directive
in the `.invokeai` initialization file that contains startup settings.
This can be corrected by fixing the offending line.
First find `.invokeai`. It is a small text file located in your home
directory, `~/.invokeai` on Mac and Linux systems, and `C:\Users\*your
name*\.invokeai` on Windows systems. Open it with a text editor
(e.g. Notepad on Windows, TextEdit on Macs, or `nano` on Linux)
and look for the lines starting with `--root` and `--outdir`.
An example is here:
```cmd
--root="/home/lstein/invokeai"
--outdir="/home/lstein/invokeai/outputs"
```
There should not be whitespace before or after the directory paths,
and the paths should not end with slashes:
```cmd
--root="/home/lstein/invokeai " # wrong! no whitespace here
--root="/home\lstein\invokeai\" # wrong! shouldn't end in a slash
```
Fix the problem with your text editor and save as a **plain text**
file. This should clear the issue.
_If none of these maneuvers fixes the problem_ then please report the
problem to the [InvokeAI
Issues](https://github.com/invoke-ai/InvokeAI/issues) section, or
visit our [Discord Server](https://discord.gg/ZmtBAhwWhy) for interactive assistance.
## Updating to newer versions
This section describes how to update InvokeAI to new versions of the software.
@@ -119,31 +193,15 @@ This section describes how to update InvokeAI to new versions of the software.
This distribution is changing rapidly, and we add new features on a daily basis.
To update to the latest released version (recommended), run the `update.sh`
(Linux/Mac) or `update.bat` (Windows) scripts. This will fetch the latest
release and re-run the `preload_models` script to download any updated models
release and re-run the `configure_invokeai` script to download any updated models
files that may be needed. You can also use this to add additional models that
you did not select at installation time.
### Updating to the development version
There may be times that there is a feature in the `development` branch of
InvokeAI that you'd like to take advantage of. Or perhaps there is a branch that
corrects an annoying bug. To do this, you will use the developer's console.
From within the invokeAI directory, run the command `invoke.sh` (Linux/Mac) or
`invoke.bat` (Windows) and selection option (3) to open the developers console.
Then run the following command to get the `development branch`:
```bash
git checkout development
git pull
conda env update
```
You can now close the developer console and run `invoke` as before. If you get
complaints about missing models, then you may need to do the additional step of
running `preload_models.py`. This happens relatively infrequently. To do this,
running `configure_invokeai.py`. This happens relatively infrequently. To do this,
simply open up the developer's console again and type
`python scripts/preload_models.py`.
`python scripts/configure_invokeai.py`.
## Troubleshooting

View File

@@ -5,37 +5,26 @@ title: Overview
We offer several ways to install InvokeAI, each one suited to your
experience and preferences.
1. [InvokeAI installer](INSTALL_INVOKE.md)
1. [InvokeAI source code installer](INSTALL_SOURCE.md)
This is a installer script that installs InvokeAI and all the
third party libraries it depends on. When a new version of
InvokeAI is released, you will download and reinstall the new
version.
This is a script that will install Python, the Anaconda ("conda")
package manager, all of InvokeAI's its essential third party
libraries and InvokeAI itself. It includes access to a "developer
console" which will help us debug problems with you and give you
to access experimental features.
This installer is designed for people who want the system to "just
work", don't have an interest in tinkering with it, and do not
care about upgrading to unreleased experimental features.
When a new InvokeAI feature is available, even between releases,
you will be able to upgrade and try it out by running an `update`
script. This method is recommended for individuals who wish to
stay on the cutting edge of InvokeAI development and are not
afraid of occasional breakage.
**Important Caveats**
- This script does not support AMD GPUs. For Linux AMD support,
please use the manual or source code installer methods.
- This script has difficulty on some Macintosh machines
that have previously been used for Python development due to
conflicting development tools versions. Mac developers may wish
to try the source code installer or one of the manual methods instead.
- This script is a bit cranky and occasionally hangs or times out,
forcing you to cancel and restart the script (it will pick up where
it left off).
2. [Source code installer](INSTALL_SOURCE.md)
This is a script that will install InvokeAI and all its essential
third party libraries. In contrast to the previous installer, it
includes access to a "developer console" which will allow you to
access experimental features on the development branch.
This method is recommended for individuals who are wish to stay
on the cutting edge of InvokeAI development and are not afraid
of occasional breakage.
3. [Manual Installation](INSTALL_MANUAL.md)
2. [Manual Installation](INSTALL_MANUAL.md)
In this method you will manually run the commands needed to install
InvokeAI and its dependencies. We offer two recipes: one suited to
@@ -47,14 +36,14 @@ experience and preferences.
the cutting edge of future InvokeAI development and is willing to put
up with occasional glitches and breakage.
4. [Docker Installation](INSTALL_DOCKER.md)
3. [Docker Installation](INSTALL_DOCKER.md)
We also offer a method for creating Docker containers containing
InvokeAI and its dependencies. This method is recommended for
individuals with experience with Docker containers and understand
the pluses and minuses of a container-based install.
5. [Jupyter Notebooks Installation](INSTALL_JUPYTER.md)
4. [Jupyter Notebooks Installation](INSTALL_JUPYTER.md)
This method is suitable for running InvokeAI on a Google Colab
account. It is recommended for individuals who have previously

View File

@@ -69,7 +69,7 @@ title: Manual Installation, Linux
machine-learning models:
```bash
(invokeai) ~/InvokeAI$ python3 scripts/preload_models.py
(invokeai) ~/InvokeAI$ python3 scripts/configure_invokeai.py
```
!!! note
@@ -79,7 +79,7 @@ title: Manual Installation, Linux
and obtaining an access token for downloading. It will then download and
install the weights files for you.
Please look [here](INSTALLING_MODELS.md) for a manual process for doing
Please look [here](../INSTALL_MANUAL.md) for a manual process for doing
the same thing.
7. Start generating images!
@@ -112,7 +112,7 @@ title: Manual Installation, Linux
To use an alternative model you may invoke the `!switch` command in
the CLI, or pass `--model <model_name>` during `invoke.py` launch for
either the CLI or the Web UI. See [Command Line
Client](../features/CLI.md#model-selection-and-importation). The
Client](../../features/CLI.md#model-selection-and-importation). The
model names are defined in `configs/models.yaml`.
8. Subsequently, to relaunch the script, be sure to run "conda activate

View File

@@ -111,7 +111,7 @@ will do our best to help.
!!! todo "Download the model weight files"
The `preload_models.py` script downloads and installs the model weight
The `configure_invokeai.py` script downloads and installs the model weight
files for you. It will lead you through the process of getting a Hugging Face
account, accepting the Stable Diffusion model weight license agreement, and
creating a download token:
@@ -119,7 +119,7 @@ will do our best to help.
```bash
# This will take some time, depending on the speed of your internet connection
# and will consume about 10GB of space
python scripts/preload_models.py
python scripts/configure_invokeai.py
```
!!! todo "Run InvokeAI!"
@@ -150,7 +150,7 @@ will do our best to help.
To use an alternative model you may invoke the `!switch` command in
the CLI, or pass `--model <model_name>` during `invoke.py` launch for
either the CLI or the Web UI. See [Command Line
Client](../features/CLI.md#model-selection-and-importation). The
Client](../../features/CLI.md#model-selection-and-importation). The
model names are defined in `configs/models.yaml`.
---
@@ -220,8 +220,8 @@ There are several causes of these errors:
with "(invokeai)" then you activated it. If it begins with "(base)" or
something else you haven't.
2. You might've run `./scripts/preload_models.py` or `./scripts/invoke.py`
instead of `python ./scripts/preload_models.py` or
2. You might've run `./scripts/configure_invokeai.py` or `./scripts/invoke.py`
instead of `python ./scripts/configure_invokeai.py` or
`python ./scripts/invoke.py`. The cause of this error is long so it's below.
<!-- I could not find out where the error is, otherwise would have marked it as a footnote -->
@@ -359,7 +359,7 @@ python ./scripts/txt2img.py \
### OSError: Can't load tokenizer for 'openai/clip-vit-large-patch14'
```bash
python scripts/preload_models.py
python scripts/configure_invokeai.py
```
---

View File

@@ -65,7 +65,7 @@ Note that you will need NVIDIA drivers, Python 3.10, and Git installed beforehan
7. Load the big stable diffusion weights files and a couple of smaller machine-learning models:
```bash
python scripts/preload_models.py
python scripts/configure_invokeai.py
```
!!! note
@@ -75,7 +75,7 @@ Note that you will need NVIDIA drivers, Python 3.10, and Git installed beforehan
obtaining an access token for downloading. It will then download and install the
weights files for you.
Please look [here](INSTALLING_MODELS.md) for a manual process for doing the
Please look [here](../INSTALL_MANUAL.md) for a manual process for doing the
same thing.
8. Start generating images!
@@ -108,7 +108,7 @@ Note that you will need NVIDIA drivers, Python 3.10, and Git installed beforehan
To use an alternative model you may invoke the `!switch` command in
the CLI, or pass `--model <model_name>` during `invoke.py` launch for
either the CLI or the Web UI. See [Command Line
Client](../features/CLI.md#model-selection-and-importation). The
Client](../../features/CLI.md#model-selection-and-importation). The
model names are defined in `configs/models.yaml`.
9. Subsequently, to relaunch the script, first activate the Anaconda

View File

@@ -15,16 +15,16 @@ We thank them for all of their time and hard work.
## **Current core team**
* lstein (Lincoln Stein) - Co-maintainer
* blessedcoolant - Co-maintainer
* hipsterusername (Kent Keirsey) - Product Manager
* psychedelicious - Web Team Leader
* Kyle0654 (Kyle Schouviller) - Node Architect and General Backend Wizard
* damian0815 - Attention Systems and Gameplay Engineer
* mauwii (Matthias Wild) - Continuous integration and product maintenance engineer
* Netsvetaev (Artur Netsvetaev) - UI/UX Developer
* tildebyte - general gadfly and resident (self-appointed) know-it-all
* keturn - Lead for Diffusers port
* @lstein (Lincoln Stein) - Co-maintainer
* @blessedcoolant - Co-maintainer
* @hipsterusername (Kent Keirsey) - Product Manager
* @psychedelicious - Web Team Leader
* @Kyle0654 (Kyle Schouviller) - Node Architect and General Backend Wizard
* @damian0815 - Attention Systems and Gameplay Engineer
* @mauwii (Matthias Wild) - Continuous integration and product maintenance engineer
* @Netsvetaev (Artur Netsvetaev) - UI/UX Developer
* @tildebyte - general gadfly and resident (self-appointed) know-it-all
* @keturn - Lead for Diffusers port
## **Contributions by**

File diff suppressed because one or more lines are too long

View File

@@ -6,7 +6,7 @@
<meta name="viewport" content="width=device-width, initial-scale=1.0" />
<title>InvokeAI - A Stable Diffusion Toolkit</title>
<link rel="shortcut icon" type="icon" href="./assets/favicon.0d253ced.ico" />
<script type="module" crossorigin src="./assets/index.faf4c870.js"></script>
<script type="module" crossorigin src="./assets/index.637f12bd.js"></script>
<link rel="stylesheet" href="./assets/index.c609c0c8.css">
</head>

View File

@@ -42,7 +42,6 @@ const makeSocketIOEmitters = (
options: optionsState,
system: systemState,
canvas: canvasState,
gallery: galleryState,
} = state;
const frontendToBackendParametersConfig: FrontendToBackendParametersConfig =
@@ -55,13 +54,6 @@ const makeSocketIOEmitters = (
dispatch(generationRequested());
if (!['txt2img', 'img2img'].includes(generationMode)) {
if (!galleryState.currentImage?.url) return;
frontendToBackendParametersConfig.imageToProcessUrl =
galleryState.currentImage.url;
}
const { generationParameters, esrganParameters, facetoolParameters } =
frontendToBackendParameters(frontendToBackendParametersConfig);

View File

@@ -30,13 +30,7 @@ export const frontendToBackendParameters = (
): { [key: string]: any } => {
const canvasBaseLayer = getCanvasBaseLayer();
const {
generationMode,
optionsState,
canvasState,
systemState,
imageToProcessUrl,
} = config;
const { generationMode, optionsState, canvasState, systemState } = config;
const {
cfgScale,
@@ -164,7 +158,6 @@ export const frontendToBackendParameters = (
generationParameters.fit = false;
generationParameters.init_img = imageToProcessUrl;
generationParameters.strength = img2imgStrength;
generationParameters.invert_mask = shouldPreserveMaskedArea;

View File

@@ -36,7 +36,7 @@ class Concepts(object):
models = self.hf_api.list_models(filter=ModelFilter(model_name='sd-concepts-library/'))
self.concept_list = [a.id.split('/')[1] for a in models]
except Exception as e:
print(' ** WARNING: Hugging Face textual inversion concepts libraries could not be loaded. The error was {str(e)}.')
print(f' ** WARNING: Hugging Face textual inversion concepts libraries could not be loaded. The error was {str(e)}.')
print(' ** You may load .bin and .pt file(s) manually using the --embedding_directory argument.')
return self.concept_list

View File

@@ -27,7 +27,7 @@ if Globals.try_patchmatch:
print('>> Patchmatch initialized')
infill_methods.append('patchmatch')
else:
print('>> Patchmatch not loaded, please see https://github.com/invoke-ai/InvokeAI/blob/patchmatch-install-docs/docs/installation/INSTALL_PATCHMATCH.md')
print('>> Patchmatch not loaded (nonfatal)')
else:
print('>> Patchmatch loading disabled')

View File

@@ -101,7 +101,8 @@ class Completer(object):
self.linebuffer = None
self.auto_history_active = True
self.extensions = None
self.concepts = Concepts().list_concepts()
self.concepts = None
self.embedding_terms = set()
return
def complete(self, text, state):
@@ -270,16 +271,21 @@ class Completer(object):
return matches
def add_embedding_terms(self, terms:list[str]):
self.concepts = Concepts().list_concepts()
self.concepts.extend(terms)
self.embedding_terms = set(terms)
if self.concepts:
self.embedding_terms.update(self.concepts)
def _concept_completions(self, text, state):
if self.concepts is None:
self.concepts = set(Concepts().list_concepts())
self.embedding_terms.update(self.concepts)
partial = text[1:] # this removes the leading '<'
if len(partial) == 0:
return self.concepts # whole dump - think if user wants this!
return list(self.embedding_terms) # whole dump - think if user wants this!
matches = list()
for concept in self.concepts:
for concept in self.embedding_terms:
if concept.startswith(partial):
matches.append(f'<{concept}>')
matches.sort()
@@ -416,7 +422,11 @@ def get_completer(opt:Args, models=[])->Completer:
readline.parse_and_bind('set skip-completed-text on')
readline.parse_and_bind('set show-all-if-ambiguous on')
histfile = os.path.join(os.path.expanduser(opt.outdir), '.invoke_history')
outdir = os.path.expanduser(opt.outdir)
if os.path.isabs(outdir):
histfile = os.path.join(outdir,'.invoke_history')
else:
histfile = os.path.join(Globals.root, outdir, '.invoke_history')
try:
readline.read_history_file(histfile)
readline.set_history_length(1000)

25
scripts/configure_invokeai.py Normal file → Executable file
View File

@@ -108,11 +108,13 @@ completely skip this step.
completer.complete_extensions(None) # turn off path-completion mode
selection = None
while selection is None:
choice = input('Download <r>ecommended models, <c>ustomize the list, or <s>kip this step? [r]: ')
choice = input('Download <r>ecommended models, <a>ll models, <c>ustomized list, or <s>kip this step? [r]: ')
if choice.startswith(('r','R')) or len(choice)==0:
selection = 'recommended'
elif choice.startswith(('c','C')):
selection = 'customized'
elif choice.startswith(('a','A')):
selection = 'all'
elif choice.startswith(('s','S')):
selection = 'skip'
return selection
@@ -166,7 +168,14 @@ def recommended_datasets()->dict:
if Datasets[ds]['recommended']:
datasets[ds]=True
return datasets
#---------------------------------------------
def all_datasets()->dict:
datasets = dict()
for ds in Datasets.keys():
datasets[ds]=True
return datasets
#-------------------------------Authenticate against Hugging Face
def authenticate():
print('''
@@ -217,7 +226,9 @@ This involves a few easy steps.
(You can enter anything you like in the token creation field marked "Name".
"Role" should be "read").
Now copy the token to your clipboard and paste it here: '''
Now copy the token to your clipboard and paste it at the prompt. Windows
users can paste with right-click.
Token: '''
)
access_token = getpass_asterisk.getpass_asterisk()
return access_token
@@ -526,6 +537,8 @@ def download_weights(opt:dict):
if choice == 'recommended':
models = recommended_datasets()
elif choice == 'all':
models = all_datasets()
elif choice == 'customized':
models = select_datasets(choice)
if models is None and yes_or_no('Quit?',default_yes=False):
@@ -571,7 +584,8 @@ def select_root(root:str, yes_to_all:bool=False):
completer.set_default_dir(default)
completer.complete_extensions(())
completer.set_line(default)
return input(f"Select a directory in which to install InvokeAI's models and configuration files [{default}]: ") or default
directory = input(f"Select a directory in which to install InvokeAI's models and configuration files [{default}]: ").strip(' \\')
return directory or default
#-------------------------------------
def select_outputs(root:str,yes_to_all:bool=False):
@@ -581,7 +595,8 @@ def select_outputs(root:str,yes_to_all:bool=False):
completer.set_default_dir(os.path.expanduser('~'))
completer.complete_extensions(())
completer.set_line(default)
return input(f'Select the default directory for image outputs [{default}]: ') or default
directory = input(f'Select the default directory for image outputs [{default}]: ').strip(' \\')
return directory or default
#-------------------------------------
def initialize_rootdir(root:str,yes_to_all:bool=False):

Binary file not shown.

View File

@@ -2,22 +2,26 @@
cd "$(dirname "${BASH_SOURCE[0]}")"
VERSION='2.2.3'
# make the installer zip for linux and mac
rm -rf invokeAI
mkdir -p invokeAI
cp install.sh invokeAI
cp install.sh.in invokeAI/install.sh
chmod a+x invokeAI/install.sh
cp readme.txt invokeAI
zip -r invokeAI-src-installer-linux.zip invokeAI
zip -r invokeAI-src-installer-mac.zip invokeAI
zip -r invokeAI-src-installer-$VERSION-linux.zip invokeAI
zip -r invokeAI-src-installer-$VERSION-mac.zip invokeAI
# make the installer zip for windows
rm -rf invokeAI
mkdir -p invokeAI
cp install.bat invokeAI
cp install.bat.in invokeAI/install.bat
cp readme.txt invokeAI
cp WinLongPathsEnabled.reg invokeAI
zip -r invokeAI-src-installer-windows.zip invokeAI
zip -r invokeAI-src-installer-$VERSION-windows.zip invokeAI
rm -rf invokeAI
echo "The installer zips are ready to be distributed.."

View File

@@ -5,12 +5,20 @@
@rem For users who already have git and conda, this step will be skipped.
@rem Next, it'll checkout the project's git repo, if necessary.
@rem Finally, it'll create the conda environment and preload the models.
@rem Finally, it'll create the conda environment and configure InvokeAI.
@rem This enables a user to install this project without manually installing conda and git.
echo "Installing InvokeAI.."
echo.
@rem change to the script's directory
PUSHD "%~dp0"
echo "InvokeAI source installer..."
echo ""
echo "Some of the installation steps take a long time to run. Please be patient."
echo "If the script appears to hang for more than 10 minutes, please interrupt with control-C and retry."
echo "<Press any key to start the install process>"
pause
echo ""
@rem config
set MAMBA_ROOT_PREFIX=%cd%\installer_files\mamba
@@ -84,23 +92,23 @@ copy environments-and-requirements\environment-win-cuda.yml environment.yml
call conda env create
if "%ERRORLEVEL%" NEQ "0" (
echo ""
echo "Something went wrong while installing Python libraries and cannot continue.
echo "Please visit https://invoke-ai.github.io/InvokeAI/#installation for alternative"
echo "installation methods."
echo "Press any key to continue"
echo "Something went wrong while installing Python libraries and cannot continue."
echo "See https://invoke-ai.github.io/InvokeAI/INSTALL_SOURCE#troubleshooting for troubleshooting"
echo "tips, or visit https://invoke-ai.github.io/InvokeAI/#installation for alternative"
echo "installation methods"
pause
exit /b
)
copy source_installer\invoke.bat invoke.bat
copy source_installer\update.bat update.bat
copy source_installer\invoke.bat.in .\invoke.bat
copy source_installer\update.bat.in .\update.bat
call conda activate invokeai
@rem preload the models
call python scripts\preload_models.py
@rem call configure script
call python scripts\configure_invokeai.py
if "%ERRORLEVEL%" NEQ "0" (
echo ""
echo "The preload_models.py script crashed or was cancelled."
echo "The configure script crashed or was cancelled."
echo "InvokeAI is not ready to run. To run preload_models.py again,"
echo "run the command 'update.bat' in this directory."
echo "Press any key to continue"
@@ -114,5 +122,6 @@ echo "* InvokeAI installed successfully *"
echo "You can now start generating images by double-clicking the 'invoke.bat' file (inside this folder)
echo "Press any key to continue"
pause
exit 0
exit /b

View File

@@ -1,17 +1,21 @@
#!/bin/bash
#!/usr/bin/env bash
# This script will install git and conda (if not found on the PATH variable)
# using micromamba (an 8mb static-linked single-file binary, conda replacement).
# For users who already have git and conda, this step will be skipped.
# Next, it'll checkout the project's git repo, if necessary.
# Finally, it'll create the conda environment and preload the models.
# Finally, it'll create the conda environment and configure InvokeAI.
# This enables a user to install this project without manually installing conda and git.
cd "$(dirname "${BASH_SOURCE[0]}")"
echo "Installing InvokeAI.."
echo "InvokeAI source installer..."
echo ""
echo "Some of the installation steps take a long time to run. Please be patient."
echo "If the script appears to hang for more than 10 minutes, please interrupt with control-C and retry."
read -n 1 -s -r -p "<Press any key to start the install>"
echo ""
OS_NAME=$(uname -s)
@@ -112,21 +116,24 @@ status=$?
if test $status -ne 0
then
echo "Something went wrong while installing Python libraries and cannot continue."
echo "Please visit https://invoke-ai.github.io/InvokeAI/#installation for alternative"
echo "installation methods"
echo "Something went wrong while installing Python libraries and cannot continue."
echo "See https://invoke-ai.github.io/InvokeAI/INSTALL_SOURCE#troubleshooting for troubleshooting"
echo "tips, or visit https://invoke-ai.github.io/InvokeAI/#installation for alternative"
echo "installation methods"
else
ln -sf ./source_installer/invoke.sh .
ln -sf ./source_installer/update.sh .
ln -sf ./source_installer/invoke.sh.in ./invoke.sh
ln -sf ./source_installer/update.sh.in ./update.sh
chmod a+rx ./source_installer/invoke.sh.in
chmod a+rx ./source_installer/update.sh.in
conda activate invokeai
# preload the models
echo "Calling the preload_models.py script"
python scripts/preload_models.py
# configure
echo "Calling the configure_invokeai script"
python scripts/configure_invokeai.py
status=$?
if test $status -ne 0
then
echo "The preload_models.py script crashed or was cancelled."
echo "The configure_invoke.py script crashed or was cancelled."
echo "InvokeAI is not ready to run. Try again by running"
echo "update.sh in this directory."
else

View File

@@ -10,6 +10,11 @@ source "$CONDA_BASEPATH/etc/profile.d/conda.sh" # otherwise conda complains abou
conda activate invokeai
# set required env var for torch on mac MPS
if [ "$(uname -s)" == "Darwin" ]; then
export PYTORCH_ENABLE_MPS_FALLBACK=1
fi
if [ "$0" != "bash" ]; then
echo "Do you want to generate images using the"
echo "1. command-line"