mirror of
https://github.com/invoke-ai/InvokeAI.git
synced 2026-01-18 13:27:55 -05:00
Compare commits
1 Commits
| Author | SHA1 | Date | |
|---|---|---|---|
|
268db779b9 |
@@ -6,8 +6,6 @@ IFS=$'\n\t'
|
||||
echo "Be certain that you're in the 'installer' directory before continuing."
|
||||
read -p "Press any key to continue, or CTRL-C to exit..."
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||||
|
||||
VERSION='2.2.3'
|
||||
|
||||
# make the installer zip for linux and mac
|
||||
rm -rf InvokeAI
|
||||
mkdir -p InvokeAI
|
||||
@@ -15,8 +13,8 @@ cp install.sh.in InvokeAI/install.sh
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chmod a+x InvokeAI/install.sh
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cp readme.txt InvokeAI
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||||
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||||
zip -r InvokeAI-binary-$VERSION-linux.zip InvokeAI
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zip -r InvokeAI-binary-$VERSION-mac.zip InvokeAI
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zip -r InvokeAI-linux.zip InvokeAI
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zip -r InvokeAI-mac.zip InvokeAI
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|
||||
# make the installer zip for windows
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rm -rf InvokeAI
|
||||
@@ -25,7 +23,7 @@ cp install.bat.in InvokeAI/install.bat
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cp readme.txt InvokeAI
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cp WinLongPathsEnabled.reg InvokeAI
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||||
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zip -r InvokeAI-binary-$VERSION-windows.zip InvokeAI
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zip -r InvokeAI-windows.zip InvokeAI
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||||
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rm -rf InvokeAI
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||||
|
||||
|
||||
@@ -10,9 +10,6 @@
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@rem This enables a user to install this project without manually installing git or Python
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|
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@rem change to the script's directory
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PUSHD "%~dp0"
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||||
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||||
set "no_cache_dir=--no-cache-dir"
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if "%1" == "use-cache" (
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set "no_cache_dir="
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@@ -25,7 +22,9 @@ set INSTALL_ENV_DIR=%cd%\installer_files\env
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@rem https://mamba.readthedocs.io/en/latest/installation.html
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set MICROMAMBA_DOWNLOAD_URL=https://github.com/cmdr2/stable-diffusion-ui/releases/download/v1.1/micromamba.exe
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set RELEASE_URL=https://github.com/invoke-ai/InvokeAI
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set RELEASE_SOURCEBALL=/archive/refs/heads/main.tar.gz
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#set RELEASE_SOURCEBALL=/archive/refs/heads/main.tar.gz
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# RELEASE_SOURCEBALL=/archive/refs/heads/test-installer.tar.gz
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RELEASE_SOURCEBALL=/archive/refs/heads/development.tar.gz
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set PYTHON_BUILD_STANDALONE_URL=https://github.com/indygreg/python-build-standalone/releases/download
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set PYTHON_BUILD_STANDALONE=20221002/cpython-3.10.7+20221002-x86_64-pc-windows-msvc-shared-install_only.tar.gz
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@@ -214,7 +214,7 @@ _err_exit $? _err_msg
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echo -e "\n***** Installed InvokeAI *****\n"
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cp binary_installer/invoke.sh.in ./invoke.sh
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chmod a+rx ./invoke.sh
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chmod a+x ./invoke.sh
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echo -e "\n***** Installed invoke launcher script ******\n"
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|
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# more cleanup
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@@ -229,7 +229,7 @@ deactivate
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echo -e "\n***** Finished downloading models *****\n"
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|
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echo "All done! Run the command"
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echo " $scriptdir/invoke.sh"
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echo " \"$scriptdir/invoke.sh\""
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echo "to start InvokeAI."
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read -p "Press any key to exit..."
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exit
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|
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@@ -4,11 +4,6 @@ set -eu
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. .venv/bin/activate
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# set required env var for torch on mac MPS
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if [ "$(uname -s)" == "Darwin" ]; then
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export PYTORCH_ENABLE_MPS_FALLBACK=1
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fi
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|
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echo "Do you want to generate images using the"
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echo "1. command-line"
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echo "2. browser-based UI"
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File diff suppressed because it is too large
Load Diff
@@ -4,7 +4,7 @@
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#
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||||
# 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/cu116
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||||
--extra-index-url https://download.pytorch.org/whl/torch_stable.html
|
||||
--trusted-host https
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||||
|
||||
absl-py==1.3.0 \
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@@ -987,6 +987,7 @@ numpy==1.23.4 \
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# pandas
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# pyarrow
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# pydeck
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# pypatchmatch
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# pytorch-lightning
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# pywavelets
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# qudida
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@@ -1159,6 +1160,7 @@ pillow==9.3.0 \
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# imageio
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||||
# k-diffusion
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||||
# matplotlib
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||||
# pypatchmatch
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# realesrgan
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||||
# scikit-image
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||||
# streamlit
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||||
@@ -1294,6 +1296,9 @@ pyparsing==3.0.9 \
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||||
# via
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# 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
|
||||
@@ -1826,27 +1831,27 @@ toolz==0.12.0 \
|
||||
--hash=sha256:2059bd4148deb1884bb0eb770a3cde70e7f954cfbbdc2285f1f2de01fd21eb6f \
|
||||
--hash=sha256:88c570861c440ee3f2f6037c4654613228ff40c93a6c25e0eba70d17282c6194
|
||||
# via altair
|
||||
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
|
||||
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
|
||||
# via
|
||||
# -r installer/requirements.in
|
||||
# accelerate
|
||||
@@ -1877,26 +1882,26 @@ torchmetrics==0.10.2 \
|
||||
--hash=sha256:43757d82266969906fc74b6e80766fcb2a0d52d6c3d09e3b7c98cf3b733fd20c \
|
||||
--hash=sha256:daa29d96bff5cff04d80eec5b9f5076993d6ac9c2d2163e88b6b31f8d38f7c25
|
||||
# via pytorch-lightning
|
||||
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
|
||||
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
|
||||
# via
|
||||
# -r installer/requirements.in
|
||||
# basicsr
|
||||
|
||||
@@ -1,10 +1,9 @@
|
||||
#
|
||||
# This file is autogenerated by pip-compile with Python 3.9
|
||||
# by the following command:
|
||||
# This file is autogenerated by pip-compile with python 3.9
|
||||
# To update, run:
|
||||
#
|
||||
# pip-compile --allow-unsafe --generate-hashes --output-file=binary_installer/py3.10-linux-x86_64-cuda-reqs.txt binary_installer/requirements.in
|
||||
# pip-compile --allow-unsafe --generate-hashes --output-file=installer/py3.10-linux-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
|
||||
|
||||
@@ -18,7 +17,7 @@ accelerate==0.14.0 \
|
||||
--hash=sha256:31c5bcc40564ef849b5bc1c4424a43ccaf9e26413b7df89c2e36bf81f070fd44 \
|
||||
--hash=sha256:b15d562c0889d0cf441b01faa025dfc29b163d061b6cc7d489c2c83b0a55ffab
|
||||
# via
|
||||
# -r binary_installer/requirements.in
|
||||
# -r installer/requirements.in
|
||||
# k-diffusion
|
||||
addict==2.4.0 \
|
||||
--hash=sha256:249bb56bbfd3cdc2a004ea0ff4c2b6ddc84d53bc2194761636eb314d5cfa5dfc \
|
||||
@@ -120,7 +119,7 @@ aiosignal==1.2.0 \
|
||||
albumentations==1.3.0 \
|
||||
--hash=sha256:294165d87d03bc8323e484927f0a5c1a3c64b0e7b9c32a979582a6c93c363bdf \
|
||||
--hash=sha256:be1af36832c8893314f2a5550e8ac19801e04770734c1b70fa3c996b41f37bed
|
||||
# via -r binary_installer/requirements.in
|
||||
# via -r installer/requirements.in
|
||||
altair==4.2.0 \
|
||||
--hash=sha256:0c724848ae53410c13fa28be2b3b9a9dcb7b5caa1a70f7f217bd663bb419935a \
|
||||
--hash=sha256:d87d9372e63b48cd96b2a6415f0cf9457f50162ab79dc7a31cd7e024dd840026
|
||||
@@ -151,10 +150,6 @@ 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
|
||||
@@ -188,11 +183,11 @@ click==8.1.3 \
|
||||
clip @ https://github.com/openai/CLIP/archive/d50d76daa670286dd6cacf3bcd80b5e4823fc8e1.zip \
|
||||
--hash=sha256:b5842c25da441d6c581b53a5c60e0c2127ebafe0f746f8e15561a006c6c3be6a
|
||||
# via
|
||||
# -r binary_installer/requirements.in
|
||||
# -r installer/requirements.in
|
||||
# clipseg
|
||||
clipseg @ https://github.com/invoke-ai/clipseg/archive/1f754751c85d7d4255fa681f4491ff5711c1c288.zip \
|
||||
--hash=sha256:14f43ed42f90be3fe57f06de483cb8be0f67f87a6f62a011339d45a39f4b4189
|
||||
# via -r binary_installer/requirements.in
|
||||
# via -r installer/requirements.in
|
||||
commonmark==0.9.1 \
|
||||
--hash=sha256:452f9dc859be7f06631ddcb328b6919c67984aca654e5fefb3914d54691aed60 \
|
||||
--hash=sha256:da2f38c92590f83de410ba1a3cbceafbc74fee9def35f9251ba9a971d6d66fd9
|
||||
@@ -279,7 +274,7 @@ decorator==5.1.1 \
|
||||
diffusers==0.7.2 \
|
||||
--hash=sha256:4a5f8b3a5fbd936bba7d459611cb35ec62875030367be32b232f9e19543e25a9 \
|
||||
--hash=sha256:fb814ffd150cc6f470380b8c6a521181a77beb2f44134d2aad2e4cd8aa2ced0e
|
||||
# via -r binary_installer/requirements.in
|
||||
# via -r installer/requirements.in
|
||||
dnspython==2.2.1 \
|
||||
--hash=sha256:0f7569a4a6ff151958b64304071d370daa3243d15941a7beedf0c9fe5105603e \
|
||||
--hash=sha256:a851e51367fb93e9e1361732c1d60dab63eff98712e503ea7d92e6eccb109b4f
|
||||
@@ -299,7 +294,7 @@ entrypoints==0.4 \
|
||||
eventlet==0.33.1 \
|
||||
--hash=sha256:a085922698e5029f820cf311a648ac324d73cec0e4792877609d978a4b5bbf31 \
|
||||
--hash=sha256:afbe17f06a58491e9aebd7a4a03e70b0b63fd4cf76d8307bae07f280479b1515
|
||||
# via -r binary_installer/requirements.in
|
||||
# via -r installer/requirements.in
|
||||
facexlib==0.2.5 \
|
||||
--hash=sha256:31e20cc4ed5d63562d380e4564bae14ac0d5d1899a079bad87621e13564567e4 \
|
||||
--hash=sha256:cc7ceb56c5424319c47223cf75eef6828c34c66082707c6eb35b95d39779f02d
|
||||
@@ -325,15 +320,15 @@ flask==2.2.2 \
|
||||
flask-cors==3.0.10 \
|
||||
--hash=sha256:74efc975af1194fc7891ff5cd85b0f7478be4f7f59fe158102e91abb72bb4438 \
|
||||
--hash=sha256:b60839393f3b84a0f3746f6cdca56c1ad7426aa738b70d6c61375857823181de
|
||||
# via -r binary_installer/requirements.in
|
||||
# via -r installer/requirements.in
|
||||
flask-socketio==5.3.1 \
|
||||
--hash=sha256:fd0ed0fc1341671d92d5f5b2f5503916deb7aa7e2940e6636cfa2c087c828bf9 \
|
||||
--hash=sha256:ff0c721f20bff1e2cfba77948727a8db48f187e89a72fe50c34478ce6efb3353
|
||||
# via -r binary_installer/requirements.in
|
||||
# via -r installer/requirements.in
|
||||
flaskwebgui==0.3.7 \
|
||||
--hash=sha256:4a69955308eaa8bb256ba04a994dc8f58a48dcd6f9599694ab1bcd9f43d88a5d \
|
||||
--hash=sha256:535974ce2672dcc74787c254de24cceed4101be75d96952dae82014dd57f061e
|
||||
# via -r binary_installer/requirements.in
|
||||
# via -r installer/requirements.in
|
||||
fonttools==4.38.0 \
|
||||
--hash=sha256:2bb244009f9bf3fa100fc3ead6aeb99febe5985fa20afbfbaa2f8946c2fbdaf1 \
|
||||
--hash=sha256:820466f43c8be8c3009aef8b87e785014133508f0de64ec469e4efb643ae54fb
|
||||
@@ -417,11 +412,11 @@ future==0.18.2 \
|
||||
getpass-asterisk==1.0.1 \
|
||||
--hash=sha256:20d45cafda0066d761961e0919728526baf7bb5151fbf48a7d5ea4034127d857 \
|
||||
--hash=sha256:7cc357a924cf62fa4e15b73cb4e5e30685c9084e464ffdc3fd9000a2b54ea9e9
|
||||
# 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
|
||||
gfpgan @ https://github.com/TencentARC/GFPGAN/archive/2eac2033893ca7f427f4035d80fe95b92649ac56.zip \
|
||||
--hash=sha256:79e6d71c8f1df7c7ccb0ac6b9a2ccb615ad5cde818c8b6f285a8711c05aebf85
|
||||
# via
|
||||
# -r binary_installer/requirements.in
|
||||
# -r installer/requirements.in
|
||||
# realesrgan
|
||||
gitdb==4.0.9 \
|
||||
--hash=sha256:8033ad4e853066ba6ca92050b9df2f89301b8fc8bf7e9324d412a63f8bf1a8fd \
|
||||
@@ -582,7 +577,7 @@ imageio-ffmpeg==0.4.7 \
|
||||
--hash=sha256:7a08838f97f363e37ca41821b864fd3fdc99ab1fe2421040c78eb5f56a9e723e \
|
||||
--hash=sha256:8e724d12dfe83e2a6eb39619e820243ca96c81c47c2648e66e05f7ee24e14312 \
|
||||
--hash=sha256:fc60686ef03c2d0f842901b206223c30051a6a120384458761390104470846fd
|
||||
# via -r binary_installer/requirements.in
|
||||
# via -r installer/requirements.in
|
||||
importlib-metadata==5.0.0 \
|
||||
--hash=sha256:da31db32b304314d044d3c12c79bd59e307889b287ad12ff387b3500835fc2ab \
|
||||
--hash=sha256:ddb0e35065e8938f867ed4928d0ae5bf2a53b7773871bfe6bcc7e4fcdc7dea43
|
||||
@@ -615,9 +610,9 @@ jsonschema==4.17.0 \
|
||||
# via
|
||||
# altair
|
||||
# jsonmerge
|
||||
k-diffusion @ https://github.com/Birch-san/k-diffusion/archive/363386981fee88620709cf8f6f2eea167bd6cd74.zip \
|
||||
--hash=sha256:8eac5cdc08736e6d61908a1b2948f2b2f62691b01dc1aab978bddb3451af0d66
|
||||
# via -r binary_installer/requirements.in
|
||||
k-diffusion @ https://github.com/invoke-ai/k-diffusion/archive/7f16b2c33411f26b3eae78d10648d625cb0c1095.zip \
|
||||
--hash=sha256:c3f2c84036aa98c3abf4552fafab04df5ca472aa639982795e05bb1db43ce5e4
|
||||
# via -r installer/requirements.in
|
||||
kiwisolver==1.4.4 \
|
||||
--hash=sha256:02f79693ec433cb4b5f51694e8477ae83b3205768a6fb48ffba60549080e295b \
|
||||
--hash=sha256:03baab2d6b4a54ddbb43bba1a3a2d1627e82d205c5cf8f4c924dc49284b87166 \
|
||||
@@ -1010,7 +1005,6 @@ numpy==1.23.4 \
|
||||
# tifffile
|
||||
# torch-fidelity
|
||||
# torchmetrics
|
||||
# torchsde
|
||||
# torchvision
|
||||
# transformers
|
||||
oauthlib==3.2.2 \
|
||||
@@ -1097,7 +1091,7 @@ pathtools==0.1.2 \
|
||||
picklescan==0.0.5 \
|
||||
--hash=sha256:368cf1b9a075bc1b6460ad82b694f260532b836c82f99d13846cd36e1bbe7f9a \
|
||||
--hash=sha256:57153eca04d5df5009f2cdd595aef261b8a6f27e03046a1c84f672aa6869c592
|
||||
# via -r binary_installer/requirements.in
|
||||
# via -r installer/requirements.in
|
||||
pillow==9.3.0 \
|
||||
--hash=sha256:03150abd92771742d4a8cd6f2fa6246d847dcd2e332a18d0c15cc75bf6703040 \
|
||||
--hash=sha256:073adb2ae23431d3b9bcbcff3fe698b62ed47211d0716b067385538a1b0f28b8 \
|
||||
@@ -1306,11 +1300,11 @@ pyparsing==3.0.9 \
|
||||
# packaging
|
||||
pypatchmatch @ https://github.com/invoke-ai/PyPatchMatch/archive/129863937a8ab37f6bbcec327c994c0f932abdbc.zip \
|
||||
--hash=sha256:4ad6ec95379e7d122d494ff76633cc7cf9b71330d5efda147fceba81e3dc6cd2
|
||||
# via -r binary_installer/requirements.in
|
||||
# via -r installer/requirements.in
|
||||
pyreadline3==3.4.1 \
|
||||
--hash=sha256:6f3d1f7b8a31ba32b73917cefc1f28cc660562f39aea8646d30bd6eff21f7bae \
|
||||
--hash=sha256:b0efb6516fd4fb07b45949053826a62fa4cb353db5be2bbb4a7aa1fdd1e345fb
|
||||
# via -r binary_installer/requirements.in
|
||||
# via -r installer/requirements.in
|
||||
pyrsistent==0.19.2 \
|
||||
--hash=sha256:055ab45d5911d7cae397dc418808d8802fb95262751872c841c170b0dbf51eed \
|
||||
--hash=sha256:111156137b2e71f3a9936baf27cb322e8024dac3dc54ec7fb9f0bcf3249e68bb \
|
||||
@@ -1447,7 +1441,7 @@ qudida==0.0.4 \
|
||||
realesrgan==0.3.0 \
|
||||
--hash=sha256:0d36da96ab9f447071606e91f502ccdfb08f80cc82ee4f8caf720c7745ccec7e \
|
||||
--hash=sha256:59336c16c30dd5130eff350dd27424acb9b7281d18a6810130e265606c9a6088
|
||||
# via -r binary_installer/requirements.in
|
||||
# via -r installer/requirements.in
|
||||
regex==2022.10.31 \
|
||||
--hash=sha256:052b670fafbe30966bbe5d025e90b2a491f85dfe5b2583a163b5e60a85a321ad \
|
||||
--hash=sha256:0653d012b3bf45f194e5e6a41df9258811ac8fc395579fa82958a8b76286bea4 \
|
||||
@@ -1662,7 +1656,6 @@ scipy==1.9.3 \
|
||||
# scikit-learn
|
||||
# torch-fidelity
|
||||
# torchdiffeq
|
||||
# torchsde
|
||||
semver==2.13.0 \
|
||||
--hash=sha256:ced8b23dceb22134307c1b8abfa523da14198793d9787ac838e70e29e77458d4 \
|
||||
--hash=sha256:fa0fe2722ee1c3f57eac478820c3a5ae2f624af8264cbdf9000c980ff7f75e3f
|
||||
@@ -1670,7 +1663,7 @@ semver==2.13.0 \
|
||||
send2trash==1.8.0 \
|
||||
--hash=sha256:d2c24762fd3759860a0aff155e45871447ea58d2be6bdd39b5c8f966a0c99c2d \
|
||||
--hash=sha256:f20eaadfdb517eaca5ce077640cb261c7d2698385a6a0f072a4a5447fd49fa08
|
||||
# via -r binary_installer/requirements.in
|
||||
# via -r installer/requirements.in
|
||||
sentry-sdk==1.10.1 \
|
||||
--hash=sha256:06c0fa9ccfdc80d7e3b5d2021978d6eb9351fa49db9b5847cf4d1f2a473414ad \
|
||||
--hash=sha256:105faf7bd7b7fa25653404619ee261527266b14103fe1389e0ce077bd23a9691
|
||||
@@ -1761,11 +1754,11 @@ smmap==5.0.0 \
|
||||
streamlit==1.14.0 \
|
||||
--hash=sha256:62556d873567e1b3427bcd118a57ee6946619f363bd6bba38df2d1f8225ecba0 \
|
||||
--hash=sha256:e078b8143d150ba721bdb9194218e311c5fe1d6d4156473a2dea6cc848a6c9fc
|
||||
# via -r binary_installer/requirements.in
|
||||
# via -r installer/requirements.in
|
||||
taming-transformers-rom1504==0.0.6 \
|
||||
--hash=sha256:051b5804c58caa247bcd51d17ddb525b4d5f892a29d42dc460f40e3e9e34e5d8 \
|
||||
--hash=sha256:73fe5fc1108accee4236ee6976e0987ab236afad0af06cb9f037641a908d2c32
|
||||
# via -r binary_installer/requirements.in
|
||||
# via -r installer/requirements.in
|
||||
tb-nightly==2.11.0a20221106 \
|
||||
--hash=sha256:8940457ee42db92f01da8bcdbbea1a476735eda559dde5976f5728919960af4a
|
||||
# via
|
||||
@@ -1790,7 +1783,7 @@ tensorboard-plugin-wit==1.8.1 \
|
||||
# tensorboard
|
||||
test-tube==0.7.5 \
|
||||
--hash=sha256:1379c33eb8cde3e9b36610f87da0f16c2e06496b1cfebac473df4e7be2faa124
|
||||
# via -r binary_installer/requirements.in
|
||||
# via -r installer/requirements.in
|
||||
threadpoolctl==3.1.0 \
|
||||
--hash=sha256:8b99adda265feb6773280df41eece7b2e6561b772d21ffd52e372f999024907b \
|
||||
--hash=sha256:a335baacfaa4400ae1f0d8e3a58d6674d2f8828e3716bb2802c44955ad391380
|
||||
@@ -1850,7 +1843,7 @@ torch==1.12.0+cu116 ; platform_system == "Linux" or platform_system == "Windows"
|
||||
--hash=sha256:aa43d7b54b86f723f17c5c44df1078c59a6149fc4d42fbef08aafab9d61451c9 \
|
||||
--hash=sha256:f772be831447dd01ebd26cbedf619e668d1b269d69bf6b4ff46b1378362bff26
|
||||
# via
|
||||
# -r binary_installer/requirements.in
|
||||
# -r installer/requirements.in
|
||||
# accelerate
|
||||
# basicsr
|
||||
# clean-fid
|
||||
@@ -1866,12 +1859,11 @@ 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 binary_installer/requirements.in
|
||||
# via -r installer/requirements.in
|
||||
torchdiffeq==0.2.3 \
|
||||
--hash=sha256:b5b01ec1294a2d8d5f77e567bf17c5de1237c0573cb94deefa88326f0e18c338 \
|
||||
--hash=sha256:fe75f434b9090ac0c27702e02bed21472b0f87035be6581f51edc5d4013ea31a
|
||||
@@ -1880,10 +1872,6 @@ 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 \
|
||||
@@ -1894,7 +1882,7 @@ torchvision==0.13.0+cu116 ; platform_system == "Linux" or platform_system == "Wi
|
||||
--hash=sha256:cb6bf0117b8f4b601baeae54e8a6bb5c4942b054835ba997f438ddcb7adcfb90 \
|
||||
--hash=sha256:d1a3c124645e3460b3e50b54eb89a2575a5036bfa618f15dc4f5d635c716069d
|
||||
# via
|
||||
# -r binary_installer/requirements.in
|
||||
# -r installer/requirements.in
|
||||
# basicsr
|
||||
# clean-fid
|
||||
# clip
|
||||
@@ -1933,13 +1921,10 @@ 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 binary_installer/requirements.in
|
||||
# via -r installer/requirements.in
|
||||
typing-extensions==4.4.0 \
|
||||
--hash=sha256:1511434bb92bf8dd198c12b1cc812e800d4181cfcb867674e0f8279cc93087aa \
|
||||
--hash=sha256:16fa4864408f655d35ec496218b85f79b3437c829e93320c7c9215ccfd92489e
|
||||
|
||||
@@ -4,7 +4,6 @@
|
||||
#
|
||||
# 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
|
||||
|
||||
@@ -151,10 +150,6 @@ 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
|
||||
@@ -619,8 +614,8 @@ jsonschema==4.17.0 \
|
||||
# via
|
||||
# altair
|
||||
# jsonmerge
|
||||
k-diffusion @ https://github.com/Birch-san/k-diffusion/archive/363386981fee88620709cf8f6f2eea167bd6cd74.zip \
|
||||
--hash=sha256:8eac5cdc08736e6d61908a1b2948f2b2f62691b01dc1aab978bddb3451af0d66
|
||||
k-diffusion @ https://github.com/invoke-ai/k-diffusion/archive/7f16b2c33411f26b3eae78d10648d625cb0c1095.zip \
|
||||
--hash=sha256:c3f2c84036aa98c3abf4552fafab04df5ca472aa639982795e05bb1db43ce5e4
|
||||
# via -r installer/requirements.in
|
||||
kiwisolver==1.4.4 \
|
||||
--hash=sha256:02f79693ec433cb4b5f51694e8477ae83b3205768a6fb48ffba60549080e295b \
|
||||
@@ -1014,7 +1009,6 @@ numpy==1.23.4 \
|
||||
# tifffile
|
||||
# torch-fidelity
|
||||
# torchmetrics
|
||||
# torchsde
|
||||
# torchvision
|
||||
# transformers
|
||||
oauthlib==3.2.2 \
|
||||
@@ -1666,7 +1660,6 @@ scipy==1.9.3 \
|
||||
# scikit-learn
|
||||
# torch-fidelity
|
||||
# torchdiffeq
|
||||
# torchsde
|
||||
semver==2.13.0 \
|
||||
--hash=sha256:ced8b23dceb22134307c1b8abfa523da14198793d9787ac838e70e29e77458d4 \
|
||||
--hash=sha256:fa0fe2722ee1c3f57eac478820c3a5ae2f624af8264cbdf9000c980ff7f75e3f
|
||||
@@ -1870,7 +1863,6 @@ 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 \
|
||||
@@ -1884,10 +1876,6 @@ 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 \
|
||||
@@ -1937,9 +1925,6 @@ 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
|
||||
|
||||
@@ -1,6 +1,5 @@
|
||||
--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
|
||||
@@ -26,7 +25,6 @@ transformers
|
||||
picklescan
|
||||
https://github.com/openai/CLIP/archive/d50d76daa670286dd6cacf3bcd80b5e4823fc8e1.zip
|
||||
https://github.com/invoke-ai/clipseg/archive/1f754751c85d7d4255fa681f4491ff5711c1c288.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/TencentARC/GFPGAN/archive/2eac2033893ca7f427f4035d80fe95b92649ac56.zip
|
||||
https://github.com/invoke-ai/k-diffusion/archive/7f16b2c33411f26b3eae78d10648d625cb0c1095.zip
|
||||
https://github.com/invoke-ai/PyPatchMatch/archive/129863937a8ab37f6bbcec327c994c0f932abdbc.zip
|
||||
|
||||
@@ -130,34 +130,20 @@ 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 "my unmodified initialization file"
|
||||
!!! example ""
|
||||
|
||||
```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
|
||||
```bash
|
||||
--web
|
||||
--steps=28
|
||||
--grid
|
||||
-f 0.6 -C 11.0 -A k_euler_a
|
||||
```
|
||||
|
||||
!!! 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.
|
||||
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.
|
||||
|
||||
## List of prompt arguments
|
||||
|
||||
@@ -209,17 +195,15 @@ 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
|
||||
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.
|
||||
|
||||
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.
|
||||
### This is an example of img2img:
|
||||
|
||||
!!! example "This is a example of img2img"
|
||||
|
||||
```bash
|
||||
invoke> waterfall and rainbow -I./vacation-photo.png -W640 -H480 --fit
|
||||
```
|
||||
```
|
||||
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
|
||||
@@ -269,7 +253,7 @@ 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
|
||||
```
|
||||
|
||||
@@ -281,7 +265,7 @@ 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
|
||||
```
|
||||
|
||||
@@ -291,16 +275,16 @@ 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`
|
||||
@@ -327,19 +311,19 @@ 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
|
||||
@@ -352,7 +336,7 @@ 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,
|
||||
@@ -377,7 +361,7 @@ 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
|
||||
|
||||
@@ -397,7 +381,7 @@ 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
|
||||
@@ -444,10 +428,10 @@ 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
|
||||
@@ -484,12 +468,12 @@ 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
|
||||
@@ -501,22 +485,20 @@ 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:
|
||||
|
||||
!!! 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
|
||||
```
|
||||
|
||||
```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`
|
||||
### !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
|
||||
@@ -526,36 +508,33 @@ 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.
|
||||
|
||||
!!! example "load the generation command for a single png file"
|
||||
This example loads 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
|
||||
```
|
||||
|
||||
!!! example "fetch the generation commands from a batch of files and store them into `selected.txt`"
|
||||
This one fetches the generation commands from a batch of files and stores 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
|
||||
|
||||
!!! example
|
||||
```
|
||||
invoke> !replay outputs\selected-imgs\selected.txt
|
||||
```
|
||||
|
||||
```bash
|
||||
invoke> !replay outputs\selected-imgs\selected.txt
|
||||
```
|
||||
Note that these commands may behave unexpectedly if given a PNG file that was
|
||||
not generated by InvokeAI.
|
||||
|
||||
!!! note
|
||||
|
||||
These commands may behave unexpectedly if given a PNG file that was
|
||||
not generated by InvokeAI.
|
||||
|
||||
#### `!search <search string>`
|
||||
### !search <search string>
|
||||
|
||||
This is similar to !history but it only returns lines that contain
|
||||
`search string`. For example:
|
||||
@@ -565,7 +544,7 @@ 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!
|
||||
|
||||
@@ -1,110 +1,130 @@
|
||||
---
|
||||
title: Concepts Library
|
||||
title: The Hugging Face Concepts Library and Importing Textual Inversion files
|
||||
---
|
||||
|
||||
# :material-library-shelves: The Hugging Face Concepts Library and Importing Textual Inversion files
|
||||
# :material-file-document: Concepts Library
|
||||
|
||||
## 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 "<trigger-phrase>". 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
|
||||
"<trigger-phrase>". 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 >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 >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 | Japanese gardener <ghibli-face> | Japanese gardener <hoi4-leaders> | Japanese gardener <cartoona-animals> |
|
||||
| :--------------------------------: | :-----------------------------------: | :------------------------------------: | :----------------------------------------: |
|
||||
|  |  |  |  |
|
||||
Japanese gardener
|
||||
<br>
|
||||
<img src="../assets/concepts/image1.png">
|
||||
|
||||
Japanese gardener <ghibli-face>
|
||||
<br>
|
||||
<img src="../assets/concepts/image2.png">
|
||||
|
||||
Japanese gardener <hoi4-leaders>
|
||||
<br>
|
||||
<img src="../assets/concepts/image3.png">
|
||||
|
||||
Japanese gardener <cartoona-animals>
|
||||
<br>
|
||||
<img src="../assets/concepts/image4.png">
|
||||
|
||||
You can also combine styles and concepts:
|
||||
|
||||
<figure markdown>
|
||||
|
||||
<figcaption>A portrait of <alf> in <cartoona-animal> style</figcaption>
|
||||
</figure>
|
||||
A portrait of <alf> in <cartoona-animal> style
|
||||
<br>
|
||||
<img src="../assets/concepts/image5.png">
|
||||
|
||||
## 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 "<" 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 "<" 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 "<" 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 "<"
|
||||
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 "<x" and Tab, you'll be prompted with the
|
||||
completions:
|
||||
For example if you type "<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 "<xidiversity>"
|
||||
because this is a unique match.
|
||||
Now type "id" and press Tab. It will be autocompleted to
|
||||
"<xidiversity>" 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 "<ghibli-face>").
|
||||
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 "<ghibli-face>").
|
||||
|
||||
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
|
||||
|
||||
|
||||
@@ -12,19 +12,21 @@ 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:
|
||||
|
||||
!!! example ""
|
||||
```commandline
|
||||
tree on a hill with a river, nature photograph, national geographic -I./test-pictures/tree-and-river-sketch.png -f 0.85
|
||||
```
|
||||
|
||||
```commandline
|
||||
tree on a hill with a river, nature photograph, national geographic -I./test-pictures/tree-and-river-sketch.png -f 0.85
|
||||
```
|
||||
This will take the original image shown here:
|
||||
|
||||
<figure markdown>
|
||||
<figure markdown>
|
||||
{ width=320 }
|
||||
</figure>
|
||||
|
||||
| original image | generated image |
|
||||
| :------------: | :-------------: |
|
||||
| { width=320 } | { width=320 } |
|
||||
and generate a new image based on it as shown here:
|
||||
|
||||
</figure>
|
||||
<figure markdown>
|
||||
{ width=320 }
|
||||
</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
|
||||
@@ -86,15 +88,13 @@ 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:
|
||||
|
||||
!!! example ""
|
||||
```bash
|
||||
invoke> "fire" -s10 -W384 -H384 -S1592514025
|
||||
```
|
||||
|
||||
```bash
|
||||
invoke> "fire" -s10 -W384 -H384 -S1592514025
|
||||
```
|
||||
|
||||
<figure markdown>
|
||||
{ width=720 }
|
||||
</figure>
|
||||
<figure markdown>
|
||||
|
||||
</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,
|
||||
@@ -109,23 +109,25 @@ into the sequence at the appropriate point, with just the right amount of noise.
|
||||
|
||||
### A concrete example
|
||||
|
||||
!!! example "I want SD to draw a fire based on this hand-drawn image"
|
||||
I want SD to draw a fire based on this hand-drawn image:
|
||||
|
||||
{ align=left }
|
||||
<figure markdown>
|
||||
|
||||
</figure>
|
||||
|
||||
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>
|
||||
|
||||
</figure>
|
||||
<figure markdown>
|
||||
|
||||
</figure>
|
||||
|
||||
With strength `0.4`, the steps look more like this:
|
||||
With strength `0.4`, the steps look more like this:
|
||||
|
||||
<figure markdown>
|
||||
|
||||
</figure>
|
||||
<figure markdown>
|
||||
|
||||
</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`:
|
||||
|
||||
@@ -39,6 +39,10 @@ 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>`
|
||||
@@ -115,7 +119,7 @@ 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.
|
||||
|
||||
### CodeFormer Usage
|
||||
### Usage
|
||||
|
||||
The following command will perform face restoration with CodeFormer instead of
|
||||
the default gfpgan.
|
||||
@@ -156,7 +160,7 @@ 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.
|
||||
|
||||
## How to disable
|
||||
### Disabling
|
||||
|
||||
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
|
||||
|
||||
@@ -1,5 +0,0 @@
|
||||
---
|
||||
title: Overview
|
||||
---
|
||||
|
||||
Here you can find the documentation for different features.
|
||||
@@ -86,10 +86,6 @@ 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
|
||||
|
||||
@@ -1,8 +1,4 @@
|
||||
---
|
||||
title: build binary installers
|
||||
---
|
||||
|
||||
# :simple-buildkite: How to build "binary" installers (InvokeAI-mac/windows/linux_on_*.zip)
|
||||
# How to build "binary" installers (InvokeAI-mac/windows/linux_on_*.zip)
|
||||
|
||||
## 1. Ensure `installers/requirements.in` is correct
|
||||
|
||||
|
||||
@@ -162,12 +162,6 @@ 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:
|
||||
|
||||
|
||||
@@ -1,8 +1,8 @@
|
||||
---
|
||||
title: InvokeAI Binary Installer
|
||||
title: InvokeAI Installer
|
||||
---
|
||||
|
||||
The InvokeAI binary installer is a shell script that will install InvokeAI onto a stock
|
||||
The InvokeAI 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. Look for a file named `InvokeAI-binary-<your platform>.zip`
|
||||
InvokeAI's installer for your platform
|
||||
|
||||
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)
|
||||
|
||||
@@ -1,86 +0,0 @@
|
||||
---
|
||||
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!
|
||||
|
||||
|
||||
|
||||
|
||||
@@ -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/tag/2.2.0-rc4), and
|
||||
[latest release](https://github.com/invoke-ai/InvokeAI/releases/latest), and
|
||||
look for a series of files named:
|
||||
|
||||
- invokeAI-src-installer-mac.zip
|
||||
|
||||
@@ -5,7 +5,31 @@ title: Overview
|
||||
We offer several ways to install InvokeAI, each one suited to your
|
||||
experience and preferences.
|
||||
|
||||
1. [InvokeAI source code installer](INSTALL_SOURCE.md)
|
||||
1. [InvokeAI binary installer](INSTALL_INVOKE.md)
|
||||
|
||||
This is a installer script that installs InvokeAI and all the
|
||||
third party libraries it depends on. It includes access to a
|
||||
"developer console" which will help us debug problems with you and
|
||||
give you to access experimental features.
|
||||
|
||||
When a new InvokeAI release is available, you will run an `update`
|
||||
script to download and install the new version. Intermediate versions
|
||||
that contain experimental and possibly unstable features will not be
|
||||
available.
|
||||
|
||||
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.
|
||||
|
||||
**Important Caveats**
|
||||
- This script does not support AMD GPUs. For Linux AMD support,
|
||||
please use the manual or source code installer methods.
|
||||
- The tab autocomplete feature of the command-line client,
|
||||
which completes commonly used filenames and commands, will
|
||||
not work in this version. All Web UI functions are fully
|
||||
operational, however.
|
||||
|
||||
2. [InvokeAI source code installer](INSTALL_SOURCE.md)
|
||||
|
||||
This is a script that will install Python, the Anaconda ("conda")
|
||||
package manager, all of InvokeAI's its essential third party
|
||||
@@ -22,7 +46,8 @@ experience and preferences.
|
||||
**Important Caveats**
|
||||
- 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).
|
||||
it left off). It also takes noticeably longer to run than the
|
||||
binary installer.
|
||||
|
||||
2. [Manual Installation](INSTALL_MANUAL.md)
|
||||
|
||||
|
||||
@@ -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](../INSTALL_MANUAL.md) for a manual process for doing
|
||||
Please look [here](INSTALLING_MODELS.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
|
||||
|
||||
@@ -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`.
|
||||
|
||||
---
|
||||
|
||||
@@ -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](../INSTALL_MANUAL.md) for a manual process for doing the
|
||||
Please look [here](INSTALLING_MODELS.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
|
||||
|
||||
@@ -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
2
frontend/dist/index.html
vendored
2
frontend/dist/index.html
vendored
@@ -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.637f12bd.js"></script>
|
||||
<script type="module" crossorigin src="./assets/index.bd109a2c.js"></script>
|
||||
<link rel="stylesheet" href="./assets/index.c609c0c8.css">
|
||||
</head>
|
||||
|
||||
|
||||
@@ -42,6 +42,7 @@ const makeSocketIOEmitters = (
|
||||
options: optionsState,
|
||||
system: systemState,
|
||||
canvas: canvasState,
|
||||
gallery: galleryState,
|
||||
} = state;
|
||||
|
||||
const frontendToBackendParametersConfig: FrontendToBackendParametersConfig =
|
||||
@@ -54,6 +55,13 @@ 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);
|
||||
|
||||
|
||||
@@ -30,7 +30,13 @@ export const frontendToBackendParameters = (
|
||||
): { [key: string]: any } => {
|
||||
const canvasBaseLayer = getCanvasBaseLayer();
|
||||
|
||||
const { generationMode, optionsState, canvasState, systemState } = config;
|
||||
const {
|
||||
generationMode,
|
||||
optionsState,
|
||||
canvasState,
|
||||
systemState,
|
||||
imageToProcessUrl,
|
||||
} = config;
|
||||
|
||||
const {
|
||||
cfgScale,
|
||||
@@ -158,6 +164,7 @@ export const frontendToBackendParameters = (
|
||||
|
||||
generationParameters.fit = false;
|
||||
|
||||
generationParameters.init_img = imageToProcessUrl;
|
||||
generationParameters.strength = img2imgStrength;
|
||||
|
||||
generationParameters.invert_mask = shouldPreserveMaskedArea;
|
||||
|
||||
@@ -102,7 +102,6 @@ class Completer(object):
|
||||
self.auto_history_active = True
|
||||
self.extensions = None
|
||||
self.concepts = None
|
||||
self.embedding_terms = set()
|
||||
return
|
||||
|
||||
def complete(self, text, state):
|
||||
@@ -271,21 +270,17 @@ class Completer(object):
|
||||
return matches
|
||||
|
||||
def add_embedding_terms(self, terms:list[str]):
|
||||
self.embedding_terms = set(terms)
|
||||
self.concepts = Concepts().list_concepts()
|
||||
if self.concepts:
|
||||
self.embedding_terms.update(self.concepts)
|
||||
self.concepts.extend(terms)
|
||||
|
||||
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 list(self.embedding_terms) # whole dump - think if user wants this!
|
||||
return self.concepts # whole dump - think if user wants this!
|
||||
|
||||
matches = list()
|
||||
for concept in self.embedding_terms:
|
||||
for concept in self.concepts:
|
||||
if concept.startswith(partial):
|
||||
matches.append(f'<{concept}>')
|
||||
matches.sort()
|
||||
|
||||
@@ -226,9 +226,7 @@ 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 at the prompt. Windows
|
||||
users can paste with right-click.
|
||||
Token: '''
|
||||
Now copy the token to your clipboard and paste it here: '''
|
||||
)
|
||||
access_token = getpass_asterisk.getpass_asterisk()
|
||||
return access_token
|
||||
@@ -584,8 +582,7 @@ def select_root(root:str, yes_to_all:bool=False):
|
||||
completer.set_default_dir(default)
|
||||
completer.complete_extensions(())
|
||||
completer.set_line(default)
|
||||
directory = input(f"Select a directory in which to install InvokeAI's models and configuration files [{default}]: ").strip(' \\')
|
||||
return directory or default
|
||||
return input(f"Select a directory in which to install InvokeAI's models and configuration files [{default}]: ") or default
|
||||
|
||||
#-------------------------------------
|
||||
def select_outputs(root:str,yes_to_all:bool=False):
|
||||
@@ -595,8 +592,7 @@ def select_outputs(root:str,yes_to_all:bool=False):
|
||||
completer.set_default_dir(os.path.expanduser('~'))
|
||||
completer.complete_extensions(())
|
||||
completer.set_line(default)
|
||||
directory = input(f'Select the default directory for image outputs [{default}]: ').strip(' \\')
|
||||
return directory or default
|
||||
return input(f'Select the default directory for image outputs [{default}]: ') or default
|
||||
|
||||
#-------------------------------------
|
||||
def initialize_rootdir(root:str,yes_to_all:bool=False):
|
||||
|
||||
@@ -2,8 +2,6 @@
|
||||
|
||||
cd "$(dirname "${BASH_SOURCE[0]}")"
|
||||
|
||||
VERSION='2.2.3'
|
||||
|
||||
# make the installer zip for linux and mac
|
||||
rm -rf invokeAI
|
||||
mkdir -p invokeAI
|
||||
@@ -11,8 +9,8 @@ cp install.sh.in invokeAI/install.sh
|
||||
chmod a+x invokeAI/install.sh
|
||||
cp readme.txt invokeAI
|
||||
|
||||
zip -r invokeAI-src-installer-$VERSION-linux.zip invokeAI
|
||||
zip -r invokeAI-src-installer-$VERSION-mac.zip invokeAI
|
||||
zip -r invokeAI-src-installer-linux.zip invokeAI
|
||||
zip -r invokeAI-src-installer-mac.zip invokeAI
|
||||
|
||||
# make the installer zip for windows
|
||||
rm -rf invokeAI
|
||||
@@ -21,7 +19,7 @@ cp install.bat.in invokeAI/install.bat
|
||||
cp readme.txt invokeAI
|
||||
cp WinLongPathsEnabled.reg invokeAI
|
||||
|
||||
zip -r invokeAI-src-installer-$VERSION-windows.zip invokeAI
|
||||
zip -r invokeAI-src-installer-windows.zip invokeAI
|
||||
|
||||
rm -rf invokeAI
|
||||
echo "The installer zips are ready to be distributed.."
|
||||
|
||||
@@ -5,13 +5,10 @@
|
||||
@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 configure InvokeAI.
|
||||
@rem Finally, it'll create the conda environment and preload the models.
|
||||
|
||||
@rem This enables a user to install this project without manually installing conda and git.
|
||||
|
||||
@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."
|
||||
@@ -104,11 +101,11 @@ copy source_installer\invoke.bat.in .\invoke.bat
|
||||
copy source_installer\update.bat.in .\update.bat
|
||||
|
||||
call conda activate invokeai
|
||||
@rem call configure script
|
||||
call python scripts\configure_invokeai.py
|
||||
@rem preload the models
|
||||
call python scripts\preload_models.py
|
||||
if "%ERRORLEVEL%" NEQ "0" (
|
||||
echo ""
|
||||
echo "The configure script crashed or was cancelled."
|
||||
echo "The preload_models.py 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"
|
||||
|
||||
@@ -5,7 +5,7 @@
|
||||
# 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 configure InvokeAI.
|
||||
# Finally, it'll create the conda environment and preload the models.
|
||||
|
||||
# This enables a user to install this project without manually installing conda and git.
|
||||
|
||||
@@ -123,12 +123,10 @@ then
|
||||
else
|
||||
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
|
||||
# configure
|
||||
echo "Calling the configure_invokeai script"
|
||||
# preload the models
|
||||
echo "Calling the preload_models.py script"
|
||||
python scripts/configure_invokeai.py
|
||||
status=$?
|
||||
if test $status -ne 0
|
||||
|
||||
@@ -10,11 +10,6 @@ source "$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"
|
||||
|
||||
Reference in New Issue
Block a user