fix basicsr conflict on windows

- 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.

binary_installer/create_installers.sh

@@ -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
 

binary_installer/install.bat.in

@@ -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

binary_installer/install.sh.in

@@ -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

binary_installer/invoke.sh.in

@@ -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"

binary_installer/py3.10-darwin-arm64-mps-reqs.txt

@@ -2,9 +2,10 @@
 # This file is autogenerated by pip-compile with python 3.10
 # To update, run:
 #
-#    pip-compile --allow-unsafe --generate-hashes --output-file=installer/py3.10-darwin-x86_64-cpu-reqs.txt installer/requirements.in
+#    pip-compile --allow-unsafe --generate-hashes --output-file=installer/py3.10-darwin-arm64-mps-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 \
@@ -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
@@ -608,8 +613,8 @@ 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 \
@@ -1003,6 +1008,7 @@ numpy==1.23.4 \
     #   tifffile
     #   torch-fidelity
     #   torchmetrics
+    #   torchsde
     #   torchvision
     #   transformers
 oauthlib==3.2.2 \
@@ -1654,6 +1660,7 @@ scipy==1.9.3 \
     #   scikit-learn
     #   torch-fidelity
     #   torchdiffeq
+    #   torchsde
 semver==2.13.0 \
     --hash=sha256:ced8b23dceb22134307c1b8abfa523da14198793d9787ac838e70e29e77458d4 \
     --hash=sha256:fa0fe2722ee1c3f57eac478820c3a5ae2f624af8264cbdf9000c980ff7f75e3f
@@ -1869,6 +1876,7 @@ torch==1.12.1 ; platform_system == "Darwin" \
     #   torch-fidelity
     #   torchdiffeq
     #   torchmetrics
+    #   torchsde
     #   torchvision
 torch-fidelity==0.3.0 \
     --hash=sha256:3d3e33db98919759cc4f3f24cb27e1e74bdc7c905d90a780630e4e1c18492b66 \
@@ -1882,6 +1890,10 @@ 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==0.13.1 ; platform_system == "Darwin" \
     --hash=sha256:0298bae3b09ac361866088434008d82b99d6458fe8888c8df90720ef4b347d44 \
     --hash=sha256:08f592ea61836ebeceb5c97f4d7a813b9d7dc651bbf7ce4401563ccfae6a21fc \
@@ -1942,6 +1954,9 @@ 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

binary_installer/py3.10-linux-x86_64-cuda-reqs.txt

@@ -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

binary_installer/py3.10-windows-x86_64-cuda-reqs.txt

@@ -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

binary_installer/requirements.in

@@ -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

docs/CHANGELOG.md

@@ -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>

docs/features/CLI.md

@@ -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!

docs/features/CONCEPTS.md

@@ -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
-"<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
-<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
 

docs/features/IMG2IMG.md

@@ -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`:

docs/features/OUTPAINTING.md

@@ -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.

docs/features/POSTPROCESS.md

@@ -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

docs/features/index.md

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

docs/index.md

@@ -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

docs/installation/BUILDING_BINARY_INSTALLERS.md

@@ -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.

docs/installation/INSTALLING_MODELS.md

@@ -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.                                                                                                                                                                                                                                                                                                                                                                                                                        |
 

docs/installation/INSTALL_INVOKE.md

@@ -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)

docs/installation/INSTALL_JUPYTER.md

@@ -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

docs/installation/INSTALL_MANUAL.md

@@ -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.

docs/installation/INSTALL_PATCHMATCH.md

@@ -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!
+
+
+
+

docs/installation/INSTALL_SOURCE.md

@@ -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
 

docs/installation/index.md

@@ -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

docs/installation/older_docs_to_be_removed/INSTALL_LINUX.md

@@ -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

docs/installation/older_docs_to_be_removed/INSTALL_MAC.md

@@ -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
 ```
 
 ---

docs/installation/older_docs_to_be_removed/INSTALL_WINDOWS.md

@@ -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

docs/other/CONTRIBUTORS.md

@@ -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**
 

frontend/dist/index.html

@@ -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>
 

frontend/src/app/socketio/emitters.ts

@@ -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);
 

frontend/src/common/util/parameterTranslation.ts

@@ -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;

ldm/invoke/concepts_lib.py

@@ -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
 

ldm/invoke/generator/inpaint.py

@@ -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')
 

ldm/invoke/readline.py

@@ -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)

ldm/modules/image_degradation/utils_image.py

@@ -193,7 +193,7 @@ def mkdir_and_rename(path):
     if os.path.exists(path):
         new_name = path + '_archived_' + get_timestamp()
         print('Path already exists. Rename it to [{:s}]'.format(new_name))
-        os.rename(path, new_name)
+        os.replace(path, new_name)
     os.makedirs(path)
 
 

notebooks/Stable_Diffusion_AI_Notebook.ipynb

@@ -74,8 +74,8 @@
         "#@title 3. Install dependencies\n",
         "import gc\n",
         "\n",
-        "!wget https://raw.githubusercontent.com/invoke-ai/InvokeAI/development/environments-and-requirements/requirements.txt\n",
-        "!wget https://raw.githubusercontent.com/invoke-ai/InvokeAI/development/environments-and-requirements/requirements-lin-win-colab-CUDA.txt\n",
+        "!wget https://raw.githubusercontent.com/invoke-ai/InvokeAI/development/environments-and-requirements/requirements-base.txt\n",
+        "!wget https://raw.githubusercontent.com/invoke-ai/InvokeAI/development/environments-and-requirements/requirements-win-colab-cuda.txt\n",
         "!pip install colab-xterm\n",
         "!pip install -r requirements-lin-win-colab-CUDA.txt\n",
         "!pip install clean-fid torchtext\n",
@@ -262,17 +262,17 @@
     },
     "gpuClass": "standard",
     "kernelspec": {
-      "display_name": "Python 3.10.4 64-bit",
+      "display_name": "Python 3.9.12 64-bit",
       "language": "python",
       "name": "python3"
     },
     "language_info": {
       "name": "python",
-      "version": "3.10.4"
+      "version": "3.9.12"
     },
     "vscode": {
       "interpreter": {
-        "hash": "3ad933181bd8a04b432d3370b9dc3b0662ad032c4dfaa4e4f1596c548f763858"
+        "hash": "4e870c5c5fe42db7e2c5647ae5af656ff3391bf8c2b729cbf7fa0e16ca8cb5af"
       }
     }
   },

scripts/configure_invokeai.py

@@ -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):

source_installer/create_installers.sh

@@ -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.."

source_installer/install.bat.in

@@ -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
+
 

source_installer/install.sh.in

@@ -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

source_installer/invoke.sh.in

@@ -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"