remove deprecated binary installer

This should prevent the errors that users are seeing with spaces in the
file paths

.github/workflows/pypi-release.yml

@@ -28,7 +28,7 @@ jobs:
         run: twine check dist/*
 
       - name: check PyPI versions
-        if: github.ref == 'refs/heads/main'
+        if: github.ref == 'refs/heads/main' || github.ref == 'refs/heads/v2.3'
         run: |
           pip install --upgrade requests
           python -c "\

binary_installer/install.bat.in

@@ -1,164 +0,0 @@
-@echo off
-
-@rem This script will install git (if not found on the PATH variable)
-@rem  using micromamba (an 8mb static-linked single-file binary, conda replacement).
-@rem For users who already have git, this step will be skipped.
-
-@rem Next, it'll download the project's source code.
-@rem Then it will download a self-contained, standalone Python and unpack it.
-@rem Finally, it'll create the Python virtual environment and preload the models.
-
-@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="
-)
-
-echo ***** Installing InvokeAI.. *****
-@rem Config
-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
-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
-
-set PACKAGES_TO_INSTALL=
-
-call git --version >.tmp1 2>.tmp2
-if "%ERRORLEVEL%" NEQ "0" set PACKAGES_TO_INSTALL=%PACKAGES_TO_INSTALL% git
-
-@rem Cleanup
-del /q .tmp1 .tmp2
-
-@rem (if necessary) install git into a contained environment
-if "%PACKAGES_TO_INSTALL%" NEQ "" (
-    @rem download micromamba
-    echo ***** Downloading micromamba from %MICROMAMBA_DOWNLOAD_URL% to micromamba.exe *****
-
-    call curl -L "%MICROMAMBA_DOWNLOAD_URL%" > micromamba.exe
-
-    @rem test the mamba binary
-    echo ***** Micromamba version:  *****
-    call micromamba.exe --version
-
-    @rem create the installer env
-    if not exist "%INSTALL_ENV_DIR%" (
-        call micromamba.exe create -y --prefix "%INSTALL_ENV_DIR%"
-    )
-
-    echo ***** Packages to install:%PACKAGES_TO_INSTALL% *****
-
-    call micromamba.exe install -y --prefix "%INSTALL_ENV_DIR%" -c conda-forge %PACKAGES_TO_INSTALL%
-
-    if not exist "%INSTALL_ENV_DIR%" (
-        echo ----- There was a problem while installing "%PACKAGES_TO_INSTALL%" using micromamba. Cannot continue. -----
-        pause
-        exit /b
-    )
-)
-
-del /q micromamba.exe
-
-@rem For 'git' only
-set PATH=%INSTALL_ENV_DIR%\Library\bin;%PATH%
-
-@rem Download/unpack/clean up InvokeAI release sourceball
-set err_msg=----- InvokeAI source download failed -----
-echo Trying to download "%RELEASE_URL%%RELEASE_SOURCEBALL%"
-curl -L %RELEASE_URL%%RELEASE_SOURCEBALL% --output InvokeAI.tgz
-if %errorlevel% neq 0 goto err_exit
-
-set err_msg=----- InvokeAI source unpack failed -----
-tar -zxf InvokeAI.tgz
-if %errorlevel% neq 0 goto err_exit
-
-del /q InvokeAI.tgz
-
-set err_msg=----- InvokeAI source copy failed -----
-cd InvokeAI-*
-xcopy . .. /e /h
-if %errorlevel% neq 0 goto err_exit
-cd ..
-
-@rem cleanup
-for /f %%i in ('dir /b InvokeAI-*') do rd /s /q %%i
-rd /s /q .dev_scripts .github docker-build tests
-del /q requirements.in requirements-mkdocs.txt shell.nix
-
-echo ***** Unpacked InvokeAI source *****
-
-@rem Download/unpack/clean up python-build-standalone
-set err_msg=----- Python download failed -----
-curl -L %PYTHON_BUILD_STANDALONE_URL%/%PYTHON_BUILD_STANDALONE% --output python.tgz
-if %errorlevel% neq 0 goto err_exit
-
-set err_msg=----- Python unpack failed -----
-tar -zxf python.tgz
-if %errorlevel% neq 0 goto err_exit
-
-del /q python.tgz
-
-echo ***** Unpacked python-build-standalone *****
-
-@rem create venv
-set err_msg=----- problem creating venv -----
-.\python\python -E -s -m venv .venv
-if %errorlevel% neq 0 goto err_exit
-call .venv\Scripts\activate.bat
-
-echo ***** Created Python virtual environment *****
-
-@rem Print venv's Python version
-set err_msg=----- problem calling venv's python -----
-echo We're running under
-.venv\Scripts\python --version
-if %errorlevel% neq 0 goto err_exit
-
-set err_msg=----- pip update failed -----
-.venv\Scripts\python -m pip install %no_cache_dir% --no-warn-script-location --upgrade pip wheel
-if %errorlevel% neq 0 goto err_exit
-
-echo ***** Updated pip and wheel *****
-
-set err_msg=----- requirements file copy failed -----
-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 -----
-.venv\Scripts\python -m pip install %no_cache_dir% --no-warn-script-location -r requirements.txt
-if %errorlevel% neq 0 goto err_exit
-
-echo ***** Installed Python dependencies *****
-
-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 binary_installer\invoke.bat.in .\invoke.bat
-echo ***** Installed invoke launcher script ******
-
-@rem more cleanup
-rd /s /q binary_installer installer_files
-
-@rem preload the models
-call .venv\Scripts\python ldm\invoke\config\invokeai_configure.py
-set err_msg=----- model download clone failed -----
-if %errorlevel% neq 0 goto err_exit
-deactivate
-
-echo ***** Finished downloading models *****
-
-echo All done! Execute the file invoke.bat in this directory to start InvokeAI
-pause
-exit
-
-:err_exit
-    echo %err_msg%
-    pause
-    exit

binary_installer/install.sh.in

@@ -1,235 +0,0 @@
-#!/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'
-
-function _err_exit {
-    if test "$1" -ne 0
-    then
-        echo -e "Error code $1; Error caught was '$2'"
-        read -p "Press any key to exit..."
-        exit
-    fi
-}
-
-# This script will install git (if not found on the PATH variable)
-#  using micromamba (an 8mb static-linked single-file binary, conda replacement).
-# For users who already have git, this step will be skipped.
-
-# Next, it'll download the project's source code.
-# Then it will download a self-contained, standalone Python and unpack it.
-# Finally, it'll create the Python virtual environment and preload the models.
-
-# 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 [ "$1" = "use-cache" ]; then
-        export no_cache_dir=""
-    fi
-fi
-
-
-OS_NAME=$(uname -s)
-case "${OS_NAME}" in
-    Linux*)     OS_NAME="linux";;
-    Darwin*)    OS_NAME="darwin";;
-    *)          echo -e "\n----- Unknown OS: $OS_NAME! This script runs only on Linux or macOS -----\n" && exit
-esac
-
-OS_ARCH=$(uname -m)
-case "${OS_ARCH}" in
-    x86_64*)    ;;
-    arm64*)     ;;
-    *)          echo -e "\n----- Unknown system architecture: $OS_ARCH! This script runs only on x86_64 or arm64 -----\n" && exit
-esac
-
-# https://mamba.readthedocs.io/en/latest/installation.html
-MAMBA_OS_NAME=$OS_NAME
-MAMBA_ARCH=$OS_ARCH
-if [ "$OS_NAME" == "darwin" ]; then
-    MAMBA_OS_NAME="osx"
-fi
-
-if [ "$OS_ARCH" == "linux" ]; then
-    MAMBA_ARCH="aarch64"
-fi
-
-if [ "$OS_ARCH" == "x86_64" ]; then
-    MAMBA_ARCH="64"
-fi
-
-PY_ARCH=$OS_ARCH
-if [ "$OS_ARCH" == "arm64" ]; then
-    PY_ARCH="aarch64"
-fi
-
-# Compute device ('cd' segment of reqs files) detect goes here
-# This needs a ton of work
-# Suggestions:
-#   - lspci
-#   - check $PATH for nvidia-smi, gtt CUDA/GPU version from output
-#   - Surely there's a similar utility for AMD?
-CD="cuda"
-if [ "$OS_NAME" == "darwin" ] && [ "$OS_ARCH" == "arm64" ]; then
-    CD="mps"
-fi
-
-# config
-INSTALL_ENV_DIR="$(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
-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 $RELEASE_URL"
-
-PACKAGES_TO_INSTALL=""
-
-if ! hash "git" &>/dev/null; then PACKAGES_TO_INSTALL="$PACKAGES_TO_INSTALL git"; fi
-
-# (if necessary) install git and conda into a contained environment
-if [ "$PACKAGES_TO_INSTALL" != "" ]; then
-    # download micromamba
-    echo -e "\n***** Downloading micromamba from $MICROMAMBA_DOWNLOAD_URL to micromamba *****\n"
-
-    curl -L "$MICROMAMBA_DOWNLOAD_URL" | tar -xvjO bin/micromamba > micromamba
-
-    chmod u+x ./micromamba
-
-    # test the mamba binary
-    echo -e "\n***** Micromamba version: *****\n"
-    ./micromamba --version
-
-    # create the installer env
-    if [ ! -e "$INSTALL_ENV_DIR" ]; then
-        ./micromamba create -y --prefix "$INSTALL_ENV_DIR"
-    fi
-
-    echo -e "\n***** Packages to install:$PACKAGES_TO_INSTALL *****\n"
-
-    ./micromamba install -y --prefix "$INSTALL_ENV_DIR" -c conda-forge "$PACKAGES_TO_INSTALL"
-
-    if [ ! -e "$INSTALL_ENV_DIR" ]; then
-        echo -e "\n----- There was a problem while initializing micromamba. Cannot continue. -----\n"
-        exit
-    fi
-fi
-
-rm -f micromamba.exe
-
-export PATH="$INSTALL_ENV_DIR/bin:$PATH"
-
-# Download/unpack/clean up InvokeAI release sourceball
-_err_msg="\n----- InvokeAI source download failed -----\n"
-curl -L $RELEASE_URL/$RELEASE_SOURCEBALL --output InvokeAI.tgz
-_err_exit $? _err_msg
-_err_msg="\n----- InvokeAI source unpack failed -----\n"
-tar -zxf InvokeAI.tgz
-_err_exit $? _err_msg
-
-rm -f InvokeAI.tgz
-
-_err_msg="\n----- InvokeAI source copy failed -----\n"
-cd InvokeAI-*
-cp -r . ..
-_err_exit $? _err_msg
-cd ..
-
-# cleanup
-rm -rf InvokeAI-*/
-rm -rf .dev_scripts/ .github/ docker-build/ tests/ requirements.in requirements-mkdocs.txt shell.nix
-
-echo -e "\n***** Unpacked InvokeAI source *****\n"
-
-# Download/unpack/clean up python-build-standalone
-_err_msg="\n----- Python download failed -----\n"
-curl -L $PYTHON_BUILD_STANDALONE_URL/$PYTHON_BUILD_STANDALONE --output python.tgz
-_err_exit $? _err_msg
-_err_msg="\n----- Python unpack failed -----\n"
-tar -zxf python.tgz
-_err_exit $? _err_msg
-
-rm -f python.tgz
-
-echo -e "\n***** Unpacked python-build-standalone *****\n"
-
-# create venv
-_err_msg="\n----- problem creating venv -----\n"
-
-if [ "$OS_NAME" == "darwin" ]; then
-    # patch sysconfig so that extensions can build properly
-    # adapted from https://github.com/cashapp/hermit-packages/commit/fcba384663892f4d9cfb35e8639ff7a28166ee43
-    PYTHON_INSTALL_DIR="$(pwd)/python"
-    SYSCONFIG="$(echo python/lib/python*/_sysconfigdata_*.py)"
-    TMPFILE="$(mktemp)"
-    chmod +w "${SYSCONFIG}"
-    cp "${SYSCONFIG}" "${TMPFILE}"
-    sed "s,'/install,'${PYTHON_INSTALL_DIR},g" "${TMPFILE}" > "${SYSCONFIG}"
-    rm -f "${TMPFILE}"
-fi
-
-./python/bin/python3 -E -s -m venv .venv
-_err_exit $? _err_msg
-source .venv/bin/activate
-
-echo -e "\n***** Created Python virtual environment *****\n"
-
-# Print venv's Python version
-_err_msg="\n----- problem calling venv's python -----\n"
-echo -e "We're running under"
-.venv/bin/python3 --version
-_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
-_err_exit $? _err_msg
-
-echo -e "\n***** Updated pip *****\n"
-
-_err_msg="\n----- requirements file copy failed -----\n"
-cp binary_installer/py3.10-${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
-_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 .
-_err_exit $? _err_msg
-
-echo -e "\n***** Installed InvokeAI *****\n"
-
-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 binary_installer/ installer_files/
-
-# preload the models
-.venv/bin/python3 scripts/configure_invokeai.py
-_err_msg="\n----- model download clone failed -----\n"
-_err_exit $? _err_msg
-deactivate
-
-echo -e "\n***** Finished downloading models *****\n"
-
-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.bat.in

@@ -1,36 +0,0 @@
-@echo off
-
-PUSHD "%~dp0"
-call .venv\Scripts\activate.bat
-
-echo Do you want to generate images using the
-echo 1. command-line
-echo 2. browser-based UI
-echo OR
-echo 3. open the developer console
-set /p choice="Please enter 1, 2 or 3: "
-if /i "%choice%" == "1" (
-    echo Starting the InvokeAI command-line.
-    .venv\Scripts\python scripts\invoke.py %*
-) else if /i "%choice%" == "2" (
-    echo Starting the InvokeAI browser-based UI.
-    .venv\Scripts\python scripts\invoke.py --web %*
-) else if /i "%choice%" == "3" (
-    echo Developer Console
-    echo Python command is:
-    where python
-    echo Python version is:
-    python --version
-    echo *************************
-    echo You are now in the system shell, with the local InvokeAI Python virtual environment activated,
-    echo so that you can troubleshoot this InvokeAI installation as necessary.
-    echo *************************
-    echo *** Type `exit` to quit this shell and deactivate the Python virtual environment ***
-    call cmd /k
-) else (
-    echo Invalid selection
-    pause
-    exit /b
-)
-
-deactivate

binary_installer/invoke.sh.in

@@ -1,46 +0,0 @@
-#!/usr/bin/env sh
-
-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"
-echo "OR"
-echo "3. open the developer console"
-echo "Please enter 1, 2, or 3:"
-read choice
-
-case $choice in
-    1)
-        printf "\nStarting the InvokeAI command-line..\n";
-        .venv/bin/python scripts/invoke.py $*;
-    ;;
-    2)
-        printf "\nStarting the InvokeAI browser-based UI..\n";
-        .venv/bin/python scripts/invoke.py --web $*;
-    ;;
-    3)
-        printf "\nDeveloper Console:\n";
-        printf "Python command is:\n\t";
-        which python;
-        printf "Python version is:\n\t";
-        python --version;
-        echo "*************************"
-        echo "You are now in your user shell ($SHELL) with the local InvokeAI Python virtual environment activated,";
-        echo "so that you can troubleshoot this InvokeAI installation as necessary.";
-        printf "*************************\n"
-        echo "*** Type \`exit\` to quit this shell and deactivate the Python virtual environment *** ";
-        /usr/bin/env "$SHELL";
-    ;;
-    *)
-        echo "Invalid selection";
-        exit
-    ;;
-esac

binary_installer/readme.txt

@@ -1,17 +0,0 @@
-InvokeAI
-
-Project homepage: https://github.com/invoke-ai/InvokeAI
-
-Installation on Windows:
-    NOTE: You might need to enable Windows Long Paths. If you're not sure,
-    then you almost certainly need to. Simply double-click the 'WinLongPathsEnabled.reg'
-    file. Note that you will need to have admin privileges in order to
-    do this.
-
-    Please double-click the 'install.bat' file (while keeping it inside the invokeAI folder).
-
-Installation on Linux and Mac:
-    Please open the terminal, and run './install.sh' (while keeping it inside the invokeAI folder).
-
-After installation, please run the 'invoke.bat' file (on Windows) or 'invoke.sh'
-file (on Linux/Mac) to start InvokeAI.

binary_installer/requirements.in

@@ -1,33 +0,0 @@
---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~=0.15
-albumentations
-diffusers[torch]~=0.11
-einops
-eventlet
-flask_cors
-flask_socketio
-flaskwebgui==1.0.3
-getpass_asterisk
-imageio-ffmpeg
-pyreadline3
-realesrgan
-send2trash
-streamlit
-taming-transformers-rom1504
-test-tube
-torch-fidelity
-torch==1.12.1 ; platform_system == 'Darwin'
-torch==1.12.0+cu116 ; platform_system == 'Linux' or platform_system == 'Windows'
-torchvision==0.13.1 ; platform_system == 'Darwin'
-torchvision==0.13.0+cu116 ; platform_system == 'Linux' or platform_system == 'Windows'
-transformers
-picklescan
-https://github.com/openai/CLIP/archive/d50d76daa670286dd6cacf3bcd80b5e4823fc8e1.zip
-https://github.com/invoke-ai/clipseg/archive/1f754751c85d7d4255fa681f4491ff5711c1c288.zip
-https://github.com/invoke-ai/GFPGAN/archive/3f5d2397361199bc4a91c08bb7d80f04d7805615.zip ; platform_system=='Windows'
-https://github.com/invoke-ai/GFPGAN/archive/c796277a1cf77954e5fc0b288d7062d162894248.zip ; platform_system=='Linux' or platform_system=='Darwin'
-https://github.com/Birch-san/k-diffusion/archive/363386981fee88620709cf8f6f2eea167bd6cd74.zip
-https://github.com/invoke-ai/PyPatchMatch/archive/129863937a8ab37f6bbcec327c994c0f932abdbc.zip

docs/installation/010_INSTALL_AUTOMATED.md

@@ -221,7 +221,10 @@ experimental versions later.
 
     - ***NSFW checker***
       If checked, InvokeAI will test images for potential sexual content
-      and blur them out if found.
+      and blur them out if found. Note that the NSFW checker consumes
+      an additional 0.6 GB of VRAM on top of the 2-3 GB of VRAM used
+      by most image models. If you have a low VRAM GPU (4-6 GB), you
+      can reduce out of memory errors by disabling the checker.
 
     - ***HuggingFace Access Token***
       InvokeAI has the ability to download embedded styles and subjects
@@ -440,6 +443,52 @@ the [InvokeAI Issues](https://github.com/invoke-ai/InvokeAI/issues) section, or
 visit our [Discord Server](https://discord.gg/ZmtBAhwWhy) for interactive
 assistance.
 
+### Out of Memory Issues
+
+The models are large, VRAM is expensive, and you may find yourself
+faced with Out of Memory errors when generating images. Here are some
+tips to reduce the problem:
+
+* **4 GB of VRAM**
+
+This should be adequate for 512x512 pixel images using Stable Diffusion 1.5
+and derived models, provided that you **disable** the NSFW checker. To
+disable the filter, do one of the following:
+
+   * Select option (6) "_change InvokeAI startup options_" from the
+     launcher. This will bring up the console-based startup settings
+     dialogue and allow you to unselect the "NSFW Checker" option.
+   * Start the startup settings dialogue directly by running
+     `invokeai-configure --skip-sd-weights --skip-support-models`
+     from the command line.
+   * Find the `invokeai.init` initialization file in the InvokeAI root
+     directory, open it in a text editor, and change `--nsfw_checker`
+     to `--no-nsfw_checker`
+
+If you are on a CUDA system, you can realize significant memory
+savings by activating the `xformers` library as described above. The
+downside is `xformers` introduces non-deterministic behavior, such
+that images generated with exactly the same prompt and settings will
+be slightly different from each other. See above for more information.
+
+* **6 GB of VRAM**
+
+This is a border case. Using the SD 1.5 series you should be able to
+generate images up to 640x640 with the NSFW checker enabled, and up to
+1024x1024 with it disabled and `xformers` activated. 
+
+If you run into persistent memory issues there are a series of
+environment variables that you can set before launching InvokeAI that
+alter how the PyTorch machine learning library manages memory.  See
+https://pytorch.org/docs/stable/notes/cuda.html#memory-management for
+a list of these tweaks.
+
+* **12 GB of VRAM**
+
+This should be sufficient to generate larger images up to about
+1280x1280. If you wish to push further, consider activating
+`xformers`.
+
 ### Other Problems
 
 If you run into problems during or after installation, the InvokeAI team is

docs/installation/050_INSTALLING_MODELS.md

@@ -43,25 +43,31 @@ InvokeAI comes with support for a good set of starter models. You'll
 find them listed in the master models file
 `configs/INITIAL_MODELS.yaml` in the InvokeAI root directory. The
 subset that are currently installed are found in
-`configs/models.yaml`. The current list is:
+`configs/models.yaml`. As of v2.3.1, the list of starter models is:
 
-| Model                | HuggingFace Repo ID               | Description                                                | URL
-| -------------------- | --------------------------------- | ---------------------------------------------------------- | -------------------------------------------------------------- |
-| stable-diffusion-1.5 | runwayml/stable-diffusion-v1-5    | Most recent version of base Stable Diffusion model         | https://huggingface.co/runwayml/stable-diffusion-v1-5          |
-| stable-diffusion-1.4 | runwayml/stable-diffusion-v1-4    | Previous version of base Stable Diffusion model         | https://huggingface.co/runwayml/stable-diffusion-v1-4          |
-| inpainting-1.5       | runwayml/stable-diffusion-inpainting  | Stable diffusion 1.5 optimized for inpainting          | https://huggingface.co/runwayml/stable-diffusion-inpainting    |
-| stable-diffusion-2.1-base |stabilityai/stable-diffusion-2-1-base | Stable Diffusion version 2.1 trained on 512 pixel images | https://huggingface.co/stabilityai/stable-diffusion-2-1-base |
-| stable-diffusion-2.1-768 |stabilityai/stable-diffusion-2-1 | Stable Diffusion version 2.1 trained on 768 pixel images | https://huggingface.co/stabilityai/stable-diffusion-2-1        |
-| dreamlike-diffusion-1.0  | dreamlike-art/dreamlike-diffusion-1.0  | An SD 1.5 model finetuned on high quality art    | https://huggingface.co/dreamlike-art/dreamlike-diffusion-1.0   |
-| dreamlike-photoreal-2.0  | dreamlike-art/dreamlike-photoreal-2.0  | A photorealistic model trained on 768 pixel images| https://huggingface.co/dreamlike-art/dreamlike-photoreal-2.0   |
-| openjourney-4.0      | prompthero/openjourney              | An SD 1.5 model finetuned on Midjourney images prompt with "mdjrny-v4 style"   | https://huggingface.co/prompthero/openjourney  |
-| nitro-diffusion-1.0  | nitrosocke/Nitro-Diffusion          | An SD 1.5 model finetuned on three styles, prompt with "archer style", "arcane style" or "modern disney style" | https://huggingface.co/nitrosocke/Nitro-Diffusion|
-| trinart-2.0          | naclbit/trinart_stable_diffusion_v2 | An SD 1.5 model finetuned with ~40,000 assorted high resolution manga/anime-style pictures | https://huggingface.co/naclbit/trinart_stable_diffusion_v2|
-| trinart-characters-2_0 | naclbit/trinart_derrida_characters_v2_stable_diffusion | An SD 1.5 model finetuned with 19.2M manga/anime-style pictures | https://huggingface.co/naclbit/trinart_derrida_characters_v2_stable_diffusion|
+|Model Name | HuggingFace Repo ID | Description | URL |
+|---------- | ---------- | ----------- | --- |
+|stable-diffusion-1.5|runwayml/stable-diffusion-v1-5|Stable Diffusion version 1.5 diffusers model (4.27 GB)|https://huggingface.co/runwayml/stable-diffusion-v1-5 |
+|sd-inpainting-1.5|runwayml/stable-diffusion-inpainting|RunwayML SD 1.5 model optimized for inpainting, diffusers version (4.27 GB)|https://huggingface.co/runwayml/stable-diffusion-inpainting |
+|stable-diffusion-2.1|stabilityai/stable-diffusion-2-1|Stable Diffusion version 2.1 diffusers model, trained on 768 pixel images (5.21 GB)|https://huggingface.co/stabilityai/stable-diffusion-2-1 |
+|sd-inpainting-2.0|stabilityai/stable-diffusion-2-1|Stable Diffusion version 2.0 inpainting model (5.21 GB)|https://huggingface.co/stabilityai/stable-diffusion-2-1 |
+|analog-diffusion-1.0|wavymulder/Analog-Diffusion|An SD-1.5 model trained on diverse analog photographs (2.13 GB)|https://huggingface.co/wavymulder/Analog-Diffusion |
+|deliberate-1.0|XpucT/Deliberate|Versatile model that produces detailed images up to 768px (4.27 GB)|https://huggingface.co/XpucT/Deliberate |
+|d&d-diffusion-1.0|0xJustin/Dungeons-and-Diffusion|Dungeons & Dragons characters (2.13 GB)|https://huggingface.co/0xJustin/Dungeons-and-Diffusion |
+|dreamlike-photoreal-2.0|dreamlike-art/dreamlike-photoreal-2.0|A photorealistic model trained on 768 pixel images based on SD 1.5 (2.13 GB)|https://huggingface.co/dreamlike-art/dreamlike-photoreal-2.0 |
+|inkpunk-1.0|Envvi/Inkpunk-Diffusion|Stylized illustrations inspired by Gorillaz, FLCL and Shinkawa; prompt with "nvinkpunk" (4.27 GB)|https://huggingface.co/Envvi/Inkpunk-Diffusion |
+|openjourney-4.0|prompthero/openjourney|An SD 1.5 model fine tuned on Midjourney; prompt with "mdjrny-v4 style" (2.13 GB)|https://huggingface.co/prompthero/openjourney |
+|portrait-plus-1.0|wavymulder/portraitplus|An SD-1.5 model trained on close range portraits of people; prompt with "portrait+" (2.13 GB)|https://huggingface.co/wavymulder/portraitplus |
+|seek-art-mega-1.0|coreco/seek.art_MEGA|A general use SD-1.5 "anything" model that supports multiple styles (2.1 GB)|https://huggingface.co/coreco/seek.art_MEGA |
+|trinart-2.0|naclbit/trinart_stable_diffusion_v2|An SD-1.5 model finetuned with ~40K assorted high resolution manga/anime-style images (2.13 GB)|https://huggingface.co/naclbit/trinart_stable_diffusion_v2 |
+|waifu-diffusion-1.4|hakurei/waifu-diffusion|An SD-1.5 model trained on 680k anime/manga-style images (2.13 GB)|https://huggingface.co/hakurei/waifu-diffusion |
 
-Note that these files are covered by an "Ethical AI" license which forbids
-certain uses. When you initially download them, you are asked to
-accept the license terms.
+Note that these files are covered by an "Ethical AI" license which
+forbids certain uses. When you initially download them, you are asked
+to accept the license terms. In addition, some of these models carry
+additional license terms that limit their use in commercial
+applications or on public servers. Be sure to familiarize yourself
+with the model terms by visiting the URLs in the table above.
 
 ## Community-Contributed Models
 

installer/create_installer.sh

@@ -20,10 +20,9 @@ echo Building installer for version $VERSION
 echo "Be certain that you're in the 'installer' directory before continuing."
 read -p "Press any key to continue, or CTRL-C to exit..."
 
-read -e -p "Commit and tag this repo with '${VERSION}' and '${LATEST_TAG}'? [n]: " input
+read -e -p "Tag this repo with '${VERSION}' and '${LATEST_TAG}'? [n]: " input
 RESPONSE=${input:='n'}
 if [ "$RESPONSE" == 'y' ]; then
-    git commit -a
 
     if ! git tag $VERSION ; then
 	    echo "Existing/invalid tag"
@@ -32,6 +31,8 @@ if [ "$RESPONSE" == 'y' ]; then
 
     git push origin :refs/tags/$LATEST_TAG
     git tag -fa $LATEST_TAG
+
+    echo "remember to push --tags!"
 fi
 
 # ----------------------

invokeai/configs/INITIAL_MODELS.yaml

@@ -6,53 +6,83 @@ stable-diffusion-1.5:
      repo_id: stabilityai/sd-vae-ft-mse
    recommended: True
    default: True
-inpainting-1.5:
+sd-inpainting-1.5:
   description: RunwayML SD 1.5 model optimized for inpainting, diffusers version (4.27 GB)
   repo_id: runwayml/stable-diffusion-inpainting
   format: diffusers
   vae:
     repo_id: stabilityai/sd-vae-ft-mse
   recommended: True
-dreamlike-diffusion-1.0:
-  description: An SD 1.5 model fine tuned on high quality art by dreamlike.art, diffusers version (2.13 BG)
-  format: diffusers
-  repo_id: dreamlike-art/dreamlike-diffusion-1.0
-  vae:
-     repo_id: stabilityai/sd-vae-ft-mse
-  recommended: True
-dreamlike-photoreal-2.0:
-  description: A photorealistic model trained on 768 pixel images based on SD 1.5 (2.13 GB)
-  format: diffusers
-  repo_id: dreamlike-art/dreamlike-photoreal-2.0
-  recommended: False
 stable-diffusion-2.1-768:
    description: Stable Diffusion version 2.1 diffusers model, trained on 768 pixel images (5.21 GB)
    repo_id: stabilityai/stable-diffusion-2-1
    format: diffusers
    recommended: True
 stable-diffusion-2.1-base:
-   description: Stable Diffusion version 2.1 diffusers base model, trained on 512 pixel images (5.21 GB)
+   description: Stable Diffusion version 2.1 diffusers model, trained on 512 pixel images (5.21 GB)
    repo_id: stabilityai/stable-diffusion-2-1-base
    format: diffusers
    recommended: False
+sd-inpainting-2.0:
+   description: Stable Diffusion version 2.0 inpainting model (5.21 GB)
+   repo_id: stabilityai/stable-diffusion-2-inpainting
+   format: diffusers
+   recommended: False
+analog-diffusion-1.0:
+   description: An SD-1.5 model trained on diverse analog photographs (2.13 GB)
+   repo_id: wavymulder/Analog-Diffusion
+   format: diffusers
+   recommended: false
+deliberate-1.0:
+   description: Versatile model that produces detailed images up to 768px (4.27 GB)
+   format: diffusers
+   repo_id: XpucT/Deliberate
+   recommended: False
+d&d-diffusion-1.0:
+   description: Dungeons & Dragons characters (2.13 GB)
+   format: diffusers
+   repo_id: 0xJustin/Dungeons-and-Diffusion
+   recommended: False
+dreamlike-photoreal-2.0:
+   description: A photorealistic model trained on 768 pixel images based on SD 1.5 (2.13 GB)
+   format: diffusers
+   repo_id: dreamlike-art/dreamlike-photoreal-2.0
+   recommended: False
+inkpunk-1.0:
+   description: Stylized illustrations inspired by Gorillaz, FLCL and Shinkawa; prompt with "nvinkpunk" (4.27 GB)
+   format: diffusers
+   repo_id: Envvi/Inkpunk-Diffusion
+   recommended: False
 openjourney-4.0:
-  description: An SD 1.5 model fine tuned on Midjourney images by PromptHero - include "mdjrny-v4 style" in your prompts (2.13 GB)
-  format: diffusers
-  repo_id: prompthero/openjourney
-  vae:
+   description: An SD 1.5 model fine tuned on Midjourney; prompt with "mdjrny-v4 style" (2.13 GB)
+   format: diffusers
+   repo_id: prompthero/openjourney
+   vae:
      repo_id: stabilityai/sd-vae-ft-mse
-  recommended: False
-nitro-diffusion-1.0:
-   description: A SD 1.5 model trained on three artstyles - prompt with "archer style", "arcane style" and/or "modern disney style" (2.13 GB)
-   repo_id: nitrosocke/Nitro-Diffusion
+   recommended: False
+portrait-plus-1.0:
+   description: An SD-1.5 model trained on close range portraits of people; prompt with "portrait+" (2.13 GB)
+   format: diffusers
+   repo_id: wavymulder/portraitplus
+   recommended: False
+seek-art-mega-1.0:
+   description: A general use SD-1.5 "anything" model that supports multiple styles (2.1 GB)
+   repo_id: coreco/seek.art_MEGA
    format: diffusers
    vae:
      repo_id: stabilityai/sd-vae-ft-mse
    recommended: False
 trinart-2.0:
-   description: An SD model finetuned with ~40,000 assorted high resolution manga/anime-style pictures, diffusers version (2.13 GB)
+   description: An SD-1.5 model finetuned with ~40K assorted high resolution manga/anime-style images (2.13 GB)
    repo_id: naclbit/trinart_stable_diffusion_v2
    format: diffusers
    vae:
      repo_id: stabilityai/sd-vae-ft-mse
    recommended: False
+waifu-diffusion-1.4:
+   description: An SD-1.5 model trained on 680k anime/manga-style images (2.13 GB)
+   repo_id: hakurei/waifu-diffusion
+   format: diffusers
+   vae:
+     repo_id: stabilityai/sd-vae-ft-mse
+   recommended: False

invokeai/frontend/dist/index.html

@@ -5,7 +5,7 @@
     <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-0e39fbc4.js"></script>
+    <script type="module" crossorigin src="./assets/index-c33fa9da.js"></script>
     <link rel="stylesheet" href="./assets/index-14cb2922.css">
   </head>
 

invokeai/frontend/dist/locales/en.json

@@ -63,7 +63,8 @@
         "statusConvertingModel": "Converting Model",
         "statusModelConverted": "Model Converted",
         "statusMergingModels": "Merging Models",
-        "statusMergedModels": "Models Merged"
+        "statusMergedModels": "Models Merged",
+        "pinOptionsPanel": "Pin Options Panel"
     },
     "gallery": {
         "generations": "Generations",
@@ -393,7 +394,9 @@
         "modelMergeInterpAddDifferenceHelp": "In this mode, Model 3 is first subtracted from Model 2. The resulting version is blended with Model 1 with the alpha rate set above.",
         "inverseSigmoid": "Inverse Sigmoid",
         "sigmoid": "Sigmoid",
-        "weightedSum": "Weighted Sum"
+        "weightedSum": "Weighted Sum",
+        "none": "none",
+        "addDifference": "Add Difference"
     },
     "parameters": {
         "general": "General",

invokeai/frontend/dist/locales/es.json

@@ -15,7 +15,7 @@
         "langSpanish": "Español",
         "nodesDesc": "Un sistema de generación de imágenes basado en nodos, actualmente se encuentra en desarrollo. Mantente pendiente a nuestras actualizaciones acerca de esta fabulosa funcionalidad.",
         "postProcessing": "Post-procesamiento",
-        "postProcessDesc1": "Invoke AI ofrece una gran variedad de funciones de post-procesamiento, El aumento de tamaño y Restauración de Rostros ya se encuentran disponibles en la interfaz web, puedes acceder desde el menú de Opciones Avanzadas en las pestañas de Texto a Imagen y de Imagen a Imagen. También puedes acceder a estas funciones directamente mediante el botón de acciones en el menú superior de la imagen actual o en el visualizador",
+        "postProcessDesc1": "Invoke AI ofrece una gran variedad de funciones de post-procesamiento, El aumento de tamaño y Restauración de Rostros ya se encuentran disponibles en la interfaz web, puedes acceder desde el menú de Opciones Avanzadas en las pestañas de Texto a Imagen y de Imagen a Imagen. También puedes acceder a estas funciones directamente mediante el botón de acciones en el menú superior de la imagen actual o en el visualizador.",
         "postProcessDesc2": "Una interfaz de usuario dedicada se lanzará pronto para facilitar flujos de trabajo de postprocesamiento más avanzado.",
         "postProcessDesc3": "La Interfaz de Línea de Comandos de Invoke AI ofrece muchas otras características, incluyendo -Embiggen-.",
         "training": "Entrenamiento",
@@ -44,7 +44,26 @@
         "statusUpscaling": "Aumentando Tamaño",
         "statusUpscalingESRGAN": "Restaurando Rostros(ESRGAN)",
         "statusLoadingModel": "Cargando Modelo",
-        "statusModelChanged": "Modelo cambiado"
+        "statusModelChanged": "Modelo cambiado",
+        "statusMergedModels": "Modelos combinados",
+        "githubLabel": "Github",
+        "discordLabel": "Discord",
+        "langEnglish": "Inglés",
+        "langDutch": "Holandés",
+        "langFrench": "Francés",
+        "langGerman": "Alemán",
+        "langItalian": "Italiano",
+        "langArabic": "Árabe",
+        "langJapanese": "Japones",
+        "langPolish": "Polaco",
+        "langBrPortuguese": "Portugués brasileño",
+        "langRussian": "Ruso",
+        "langSimplifiedChinese": "Chino simplificado",
+        "langUkranian": "Ucraniano",
+        "back": "Atrás",
+        "statusConvertingModel": "Convertir el modelo",
+        "statusModelConverted": "Modelo adaptado",
+        "statusMergingModels": "Fusionar modelos"
     },
     "gallery": {
         "generations": "Generaciones",
@@ -284,16 +303,16 @@
         "nameValidationMsg": "Introduce un nombre para tu modelo",
         "description": "Descripción",
         "descriptionValidationMsg": "Introduce una descripción para tu modelo",
-        "config": "Config",
-        "configValidationMsg": "Ruta del archivo de configuración del modelo",
+        "config": "Configurar",
+        "configValidationMsg": "Ruta del archivo de configuración del modelo.",
         "modelLocation": "Ubicación del Modelo",
-        "modelLocationValidationMsg": "Ruta del archivo de modelo",
+        "modelLocationValidationMsg": "Ruta del archivo de modelo.",
         "vaeLocation": "Ubicación VAE",
-        "vaeLocationValidationMsg": "Ruta del archivo VAE",
+        "vaeLocationValidationMsg": "Ruta del archivo VAE.",
         "width": "Ancho",
-        "widthValidationMsg": "Ancho predeterminado de tu modelo",
+        "widthValidationMsg": "Ancho predeterminado de tu modelo.",
         "height": "Alto",
-        "heightValidationMsg": "Alto predeterminado de tu modelo",
+        "heightValidationMsg": "Alto predeterminado de tu modelo.",
         "addModel": "Añadir Modelo",
         "updateModel": "Actualizar Modelo",
         "availableModels": "Modelos disponibles",
@@ -320,7 +339,61 @@
         "deleteModel": "Eliminar Modelo",
         "deleteConfig": "Eliminar Configuración",
         "deleteMsg1": "¿Estás seguro de querer eliminar esta entrada de modelo de InvokeAI?",
-        "deleteMsg2": "El checkpoint del modelo no se eliminará de tu disco. Puedes volver a añadirlo si lo deseas."
+        "deleteMsg2": "El checkpoint del modelo no se eliminará de tu disco. Puedes volver a añadirlo si lo deseas.",
+        "safetensorModels": "SafeTensors",
+        "addDiffuserModel": "Añadir difusores",
+        "inpainting": "v1 Repintado",
+        "repoIDValidationMsg": "Repositorio en línea de tu modelo",
+        "checkpointModels": "Puntos de control",
+        "convertToDiffusersHelpText4": "Este proceso se realiza una sola vez. Puede tardar entre 30 y 60 segundos dependiendo de las especificaciones de tu ordenador.",
+        "diffusersModels": "Difusores",
+        "addCheckpointModel": "Agregar modelo de punto de control/Modelo Safetensor",
+        "vaeRepoID": "Identificador del repositorio de VAE",
+        "vaeRepoIDValidationMsg": "Repositorio en línea de tú VAE",
+        "formMessageDiffusersModelLocation": "Difusores Modelo Ubicación",
+        "formMessageDiffusersModelLocationDesc": "Por favor, introduzca al menos uno.",
+        "formMessageDiffusersVAELocation": "Ubicación VAE",
+        "formMessageDiffusersVAELocationDesc": "Si no se proporciona, InvokeAI buscará el archivo VAE dentro de la ubicación del modelo indicada anteriormente.",
+        "convert": "Convertir",
+        "convertToDiffusers": "Convertir en difusores",
+        "convertToDiffusersHelpText1": "Este modelo se convertirá al formato 🧨 Difusores.",
+        "convertToDiffusersHelpText2": "Este proceso sustituirá su entrada del Gestor de Modelos por la versión de Difusores del mismo modelo.",
+        "convertToDiffusersHelpText3": "Su archivo de puntos de control en el disco NO será borrado ni modificado de ninguna manera. Puede volver a añadir su punto de control al Gestor de Modelos si lo desea.",
+        "convertToDiffusersHelpText5": "Asegúrese de que dispone de suficiente espacio en disco. Los modelos suelen variar entre 4 GB y 7 GB de tamaño.",
+        "convertToDiffusersHelpText6": "¿Desea transformar este modelo?",
+        "convertToDiffusersSaveLocation": "Guardar ubicación",
+        "v1": "v1",
+        "v2": "v2",
+        "statusConverting": "Adaptar",
+        "modelConverted": "Modelo adaptado",
+        "sameFolder": "La misma carpeta",
+        "invokeRoot": "Carpeta InvokeAI",
+        "custom": "Personalizado",
+        "customSaveLocation": "Ubicación personalizada para guardar",
+        "merge": "Fusión",
+        "modelsMerged": "Modelos fusionados",
+        "mergeModels": "Combinar modelos",
+        "modelOne": "Modelo 1",
+        "modelTwo": "Modelo 2",
+        "modelThree": "Modelo 3",
+        "mergedModelName": "Nombre del modelo combinado",
+        "alpha": "Alfa",
+        "interpolationType": "Tipo de interpolación",
+        "mergedModelSaveLocation": "Guardar ubicación",
+        "mergedModelCustomSaveLocation": "Ruta personalizada",
+        "invokeAIFolder": "Invocar carpeta de la inteligencia artificial",
+        "modelMergeHeaderHelp2": "Sólo se pueden fusionar difusores. Si desea fusionar un modelo de punto de control, conviértalo primero en difusores.",
+        "modelMergeAlphaHelp": "Alfa controla la fuerza de mezcla de los modelos. Los valores alfa más bajos reducen la influencia del segundo modelo.",
+        "modelMergeInterpAddDifferenceHelp": "En este modo, el Modelo 3 se sustrae primero del Modelo 2. La versión resultante se mezcla con el Modelo 1 con la tasa alfa establecida anteriormente. La versión resultante se mezcla con el Modelo 1 con la tasa alfa establecida anteriormente.",
+        "ignoreMismatch": "Ignorar discrepancias entre modelos seleccionados",
+        "modelMergeHeaderHelp1": "Puede combinar hasta tres modelos diferentes para crear una mezcla que se adapte a sus necesidades.",
+        "inverseSigmoid": "Sigmoideo inverso",
+        "weightedSum": "Modelo de suma ponderada",
+        "sigmoid": "Función sigmoide",
+        "allModels": "Todos los modelos",
+        "repo_id": "Identificador del repositorio",
+        "pathToCustomConfig": "Ruta a la configuración personalizada",
+        "customConfig": "Configuración personalizada"
     },
     "parameters": {
         "images": "Imágenes",
@@ -380,7 +453,22 @@
         "info": "Información",
         "deleteImage": "Eliminar Imagen",
         "initialImage": "Imagen Inicial",
-        "showOptionsPanel": "Mostrar panel de opciones"
+        "showOptionsPanel": "Mostrar panel de opciones",
+        "symmetry": "Simetría",
+        "vSymmetryStep": "Paso de simetría V",
+        "hSymmetryStep": "Paso de simetría H",
+        "cancel": {
+            "immediate": "Cancelar inmediatamente",
+            "schedule": "Cancelar tras la iteración actual",
+            "isScheduled": "Cancelando",
+            "setType": "Tipo de cancelación"
+        },
+        "copyImage": "Copiar la imagen",
+        "general": "General",
+        "negativePrompts": "Preguntas negativas",
+        "imageToImage": "Imagen a imagen",
+        "denoisingStrength": "Intensidad de la eliminación del ruido",
+        "hiresStrength": "Alta resistencia"
     },
     "settings": {
         "models": "Modelos",
@@ -393,7 +481,8 @@
         "resetWebUI": "Restablecer interfaz web",
         "resetWebUIDesc1": "Al restablecer la interfaz web, solo se restablece la caché local del navegador de sus imágenes y la configuración guardada. No se elimina ninguna imagen de su disco duro.",
         "resetWebUIDesc2": "Si las imágenes no se muestran en la galería o algo más no funciona, intente restablecer antes de reportar un incidente en GitHub.",
-        "resetComplete": "La interfaz web se ha restablecido. Actualice la página para recargarla."
+        "resetComplete": "La interfaz web se ha restablecido. Actualice la página para recargarla.",
+        "useSlidersForAll": "Utilice controles deslizantes para todas las opciones"
     },
     "toast": {
         "tempFoldersEmptied": "Directorio temporal vaciado",
@@ -431,12 +520,12 @@
         "feature": {
             "prompt": "Este campo tomará todo el texto de entrada, incluidos tanto los términos de contenido como los estilísticos. Si bien se pueden incluir pesos en la solicitud, los comandos/parámetros estándar de línea de comandos no funcionarán.",
             "gallery": "Conforme se generan nuevas invocaciones, los archivos del directorio de salida se mostrarán aquí. Las generaciones tienen opciones adicionales para configurar nuevas generaciones.",
-            "other": "Estas opciones habilitarán modos de procesamiento alternativos para Invoke. El modo sin costuras funciona para generar patrones repetitivos en la salida. La optimización de alta resolución realiza un ciclo de generación de dos pasos y debe usarse en resoluciones más altas cuando desee una imagen/composición más coherente.",
+            "other": "Estas opciones habilitarán modos de procesamiento alternativos para Invoke. 'Seamless mosaico' creará patrones repetitivos en la salida. 'Alta resolución' es la generación en dos pasos con img2img: use esta configuración cuando desee una imagen más grande y más coherente sin artefactos. tomar más tiempo de lo habitual txt2img.",
             "seed": "Los valores de semilla proporcionan un conjunto inicial de ruido que guían el proceso de eliminación de ruido y se pueden aleatorizar o rellenar con una semilla de una invocación anterior. La función Umbral se puede usar para mitigar resultados indeseables a valores CFG más altos (intente entre 0-10), y Perlin se puede usar para agregar ruido Perlin al proceso de eliminación de ruido. Ambos sirven para agregar variación a sus salidas.",
             "variations": "Pruebe una variación con una cantidad entre 0 y 1 para cambiar la imagen de salida para la semilla establecida. Se encuentran variaciones interesantes en la semilla entre 0.1 y 0.3.",
             "upscale": "Usando ESRGAN, puede aumentar la resolución de salida sin requerir un ancho/alto más alto en la generación inicial.",
             "faceCorrection": "Usando GFPGAN o Codeformer, la corrección de rostros intentará identificar rostros en las salidas y corregir cualquier defecto/anormalidad. Los valores de fuerza más altos aplicarán una presión correctiva más fuerte en las salidas, lo que resultará en rostros más atractivos. Con Codeformer, una mayor fidelidad intentará preservar la imagen original, a expensas de la fuerza de corrección de rostros.",
-            "imageToImage": "Imagen a Imagen permite cargar una imagen inicial, que InvokeAI usará para guiar el proceso de generación, junto con una solicitud. Un valor más bajo para esta configuración se parecerá más a la imagen original. Se aceptan valores entre 0-1, y se recomienda un rango de .25-.75.",
+            "imageToImage": "Imagen a Imagen permite cargar una imagen inicial, que InvokeAI usará para guiar el proceso de generación, junto con una solicitud. Un valor más bajo para esta configuración se parecerá más a la imagen original. Se aceptan valores entre 0-1, y se recomienda un rango de .25-.75",
             "boundingBox": "La caja delimitadora es análoga a las configuraciones de Ancho y Alto para Texto a Imagen o Imagen a Imagen. Solo se procesará el área en la caja.",
             "seamCorrection": "Controla el manejo de parches visibles que pueden ocurrir cuando se pega una imagen generada de nuevo en el lienzo.",
             "infillAndScaling": "Administra los métodos de relleno (utilizados en áreas enmascaradas o borradas del lienzo) y la escala (útil para tamaños de caja delimitadora pequeños)."

invokeai/frontend/dist/locales/pt_BR.json

@@ -44,7 +44,26 @@
         "statusUpscaling": "Redimensinando",
         "statusUpscalingESRGAN": "Redimensinando (ESRGAN)",
         "statusLoadingModel": "Carregando Modelo",
-        "statusModelChanged": "Modelo Alterado"
+        "statusModelChanged": "Modelo Alterado",
+        "githubLabel": "Github",
+        "discordLabel": "Discord",
+        "langArabic": "Árabe",
+        "langEnglish": "Inglês",
+        "langDutch": "Holandês",
+        "langFrench": "Francês",
+        "langGerman": "Alemão",
+        "langItalian": "Italiano",
+        "langJapanese": "Japonês",
+        "langPolish": "Polonês",
+        "langSimplifiedChinese": "Chinês",
+        "langUkranian": "Ucraniano",
+        "back": "Voltar",
+        "statusConvertingModel": "Convertendo Modelo",
+        "statusModelConverted": "Modelo Convertido",
+        "statusMergingModels": "Mesclando Modelos",
+        "statusMergedModels": "Modelos Mesclados",
+        "langRussian": "Russo",
+        "langSpanish": "Espanhol"
     },
     "gallery": {
         "generations": "Gerações",
@@ -237,7 +256,7 @@
             "desc": "Salva a tela atual na galeria"
         },
         "copyToClipboard": {
-            "title": "Copiar Para a Área de Transferência ",
+            "title": "Copiar para a Área de Transferência",
             "desc": "Copia a tela atual para a área de transferência"
         },
         "downloadImage": {
@@ -284,7 +303,7 @@
         "nameValidationMsg": "Insira um nome para o seu modelo",
         "description": "Descrição",
         "descriptionValidationMsg": "Adicione uma descrição para o seu modelo",
-        "config": "Config",
+        "config": "Configuração",
         "configValidationMsg": "Caminho para o arquivo de configuração do seu modelo.",
         "modelLocation": "Localização do modelo",
         "modelLocationValidationMsg": "Caminho para onde seu modelo está localizado.",
@@ -317,7 +336,52 @@
         "deleteModel": "Excluir modelo",
         "deleteConfig": "Excluir Config",
         "deleteMsg1": "Tem certeza de que deseja excluir esta entrada do modelo de InvokeAI?",
-        "deleteMsg2": "Isso não vai excluir o arquivo de modelo checkpoint do seu disco. Você pode lê-los, se desejar."
+        "deleteMsg2": "Isso não vai excluir o arquivo de modelo checkpoint do seu disco. Você pode lê-los, se desejar.",
+        "checkpointModels": "Checkpoints",
+        "diffusersModels": "Diffusers",
+        "safetensorModels": "SafeTensors",
+        "addCheckpointModel": "Adicionar Modelo de Checkpoint/Safetensor",
+        "addDiffuserModel": "Adicionar Diffusers",
+        "repo_id": "Repo ID",
+        "vaeRepoID": "VAE Repo ID",
+        "vaeRepoIDValidationMsg": "Repositório Online do seu VAE",
+        "scanAgain": "Digitalize Novamente",
+        "selectAndAdd": "Selecione e Adicione Modelos Listados Abaixo",
+        "noModelsFound": "Nenhum Modelo Encontrado",
+        "formMessageDiffusersModelLocation": "Localização dos Modelos Diffusers",
+        "formMessageDiffusersModelLocationDesc": "Por favor entre com ao menos um.",
+        "formMessageDiffusersVAELocation": "Localização do VAE",
+        "formMessageDiffusersVAELocationDesc": "Se não provido, InvokeAI irá procurar pelo arquivo VAE dentro do local do modelo.",
+        "convertToDiffusers": "Converter para Diffusers",
+        "convertToDiffusersHelpText1": "Este modelo será convertido para o formato 🧨 Diffusers.",
+        "convertToDiffusersHelpText5": "Por favor, certifique-se de que você tenha espaço suficiente em disco. Os modelos geralmente variam entre 4GB e 7GB de tamanho.",
+        "convertToDiffusersHelpText6": "Você deseja converter este modelo?",
+        "convertToDiffusersSaveLocation": "Local para Salvar",
+        "v1": "v1",
+        "v2": "v2",
+        "inpainting": "v1 Inpainting",
+        "customConfig": "Configuração personalizada",
+        "pathToCustomConfig": "Caminho para configuração personalizada",
+        "convertToDiffusersHelpText3": "Seu arquivo de ponto de verificação no disco NÃO será excluído ou modificado de forma alguma. Você pode adicionar seu ponto de verificação ao Gerenciador de modelos novamente, se desejar.",
+        "convertToDiffusersHelpText4": "Este é um processo único. Pode levar cerca de 30 a 60s, dependendo das especificações do seu computador.",
+        "merge": "Mesclar",
+        "modelsMerged": "Modelos mesclados",
+        "mergeModels": "Mesclar modelos",
+        "modelOne": "Modelo 1",
+        "modelTwo": "Modelo 2",
+        "modelThree": "Modelo 3",
+        "statusConverting": "Convertendo",
+        "modelConverted": "Modelo Convertido",
+        "sameFolder": "Mesma pasta",
+        "invokeRoot": "Pasta do InvokeAI",
+        "custom": "Personalizado",
+        "customSaveLocation": "Local de salvamento personalizado",
+        "mergedModelName": "Nome do modelo mesclado",
+        "alpha": "Alpha",
+        "allModels": "Todos os Modelos",
+        "repoIDValidationMsg": "Repositório Online do seu Modelo",
+        "convert": "Converter",
+        "convertToDiffusersHelpText2": "Este processo irá substituir sua entrada de Gerenciador de Modelos por uma versão Diffusers do mesmo modelo."
     },
     "parameters": {
         "images": "Imagems",
@@ -442,14 +506,14 @@
         "move": "Mover",
         "resetView": "Resetar Visualização",
         "mergeVisible": "Fundir Visível",
-        "saveToGallery": "Save To Gallery",
+        "saveToGallery": "Salvar na Galeria",
         "copyToClipboard": "Copiar para a Área de Transferência",
         "downloadAsImage": "Baixar Como Imagem",
         "undo": "Desfazer",
         "redo": "Refazer",
         "clearCanvas": "Limpar Tela",
         "canvasSettings": "Configurações de Tela",
-        "showIntermediates": "Show Intermediates",
+        "showIntermediates": "Mostrar Intermediários",
         "showGrid": "Mostrar Grade",
         "snapToGrid": "Encaixar na Grade",
         "darkenOutsideSelection": "Escurecer Seleção Externa",

invokeai/frontend/dist/locales/ro.json

@@ -0,0 +1 @@
+{}

invokeai/frontend/public/locales/en.json

@@ -63,7 +63,8 @@
         "statusConvertingModel": "Converting Model",
         "statusModelConverted": "Model Converted",
         "statusMergingModels": "Merging Models",
-        "statusMergedModels": "Models Merged"
+        "statusMergedModels": "Models Merged",
+        "pinOptionsPanel": "Pin Options Panel"
     },
     "gallery": {
         "generations": "Generations",
@@ -393,7 +394,9 @@
         "modelMergeInterpAddDifferenceHelp": "In this mode, Model 3 is first subtracted from Model 2. The resulting version is blended with Model 1 with the alpha rate set above.",
         "inverseSigmoid": "Inverse Sigmoid",
         "sigmoid": "Sigmoid",
-        "weightedSum": "Weighted Sum"
+        "weightedSum": "Weighted Sum",
+        "none": "none",
+        "addDifference": "Add Difference"
     },
     "parameters": {
         "general": "General",

invokeai/frontend/public/locales/es.json

@@ -15,7 +15,7 @@
         "langSpanish": "Español",
         "nodesDesc": "Un sistema de generación de imágenes basado en nodos, actualmente se encuentra en desarrollo. Mantente pendiente a nuestras actualizaciones acerca de esta fabulosa funcionalidad.",
         "postProcessing": "Post-procesamiento",
-        "postProcessDesc1": "Invoke AI ofrece una gran variedad de funciones de post-procesamiento, El aumento de tamaño y Restauración de Rostros ya se encuentran disponibles en la interfaz web, puedes acceder desde el menú de Opciones Avanzadas en las pestañas de Texto a Imagen y de Imagen a Imagen. También puedes acceder a estas funciones directamente mediante el botón de acciones en el menú superior de la imagen actual o en el visualizador",
+        "postProcessDesc1": "Invoke AI ofrece una gran variedad de funciones de post-procesamiento, El aumento de tamaño y Restauración de Rostros ya se encuentran disponibles en la interfaz web, puedes acceder desde el menú de Opciones Avanzadas en las pestañas de Texto a Imagen y de Imagen a Imagen. También puedes acceder a estas funciones directamente mediante el botón de acciones en el menú superior de la imagen actual o en el visualizador.",
         "postProcessDesc2": "Una interfaz de usuario dedicada se lanzará pronto para facilitar flujos de trabajo de postprocesamiento más avanzado.",
         "postProcessDesc3": "La Interfaz de Línea de Comandos de Invoke AI ofrece muchas otras características, incluyendo -Embiggen-.",
         "training": "Entrenamiento",
@@ -44,7 +44,26 @@
         "statusUpscaling": "Aumentando Tamaño",
         "statusUpscalingESRGAN": "Restaurando Rostros(ESRGAN)",
         "statusLoadingModel": "Cargando Modelo",
-        "statusModelChanged": "Modelo cambiado"
+        "statusModelChanged": "Modelo cambiado",
+        "statusMergedModels": "Modelos combinados",
+        "githubLabel": "Github",
+        "discordLabel": "Discord",
+        "langEnglish": "Inglés",
+        "langDutch": "Holandés",
+        "langFrench": "Francés",
+        "langGerman": "Alemán",
+        "langItalian": "Italiano",
+        "langArabic": "Árabe",
+        "langJapanese": "Japones",
+        "langPolish": "Polaco",
+        "langBrPortuguese": "Portugués brasileño",
+        "langRussian": "Ruso",
+        "langSimplifiedChinese": "Chino simplificado",
+        "langUkranian": "Ucraniano",
+        "back": "Atrás",
+        "statusConvertingModel": "Convertir el modelo",
+        "statusModelConverted": "Modelo adaptado",
+        "statusMergingModels": "Fusionar modelos"
     },
     "gallery": {
         "generations": "Generaciones",
@@ -284,16 +303,16 @@
         "nameValidationMsg": "Introduce un nombre para tu modelo",
         "description": "Descripción",
         "descriptionValidationMsg": "Introduce una descripción para tu modelo",
-        "config": "Config",
-        "configValidationMsg": "Ruta del archivo de configuración del modelo",
+        "config": "Configurar",
+        "configValidationMsg": "Ruta del archivo de configuración del modelo.",
         "modelLocation": "Ubicación del Modelo",
-        "modelLocationValidationMsg": "Ruta del archivo de modelo",
+        "modelLocationValidationMsg": "Ruta del archivo de modelo.",
         "vaeLocation": "Ubicación VAE",
-        "vaeLocationValidationMsg": "Ruta del archivo VAE",
+        "vaeLocationValidationMsg": "Ruta del archivo VAE.",
         "width": "Ancho",
-        "widthValidationMsg": "Ancho predeterminado de tu modelo",
+        "widthValidationMsg": "Ancho predeterminado de tu modelo.",
         "height": "Alto",
-        "heightValidationMsg": "Alto predeterminado de tu modelo",
+        "heightValidationMsg": "Alto predeterminado de tu modelo.",
         "addModel": "Añadir Modelo",
         "updateModel": "Actualizar Modelo",
         "availableModels": "Modelos disponibles",
@@ -320,7 +339,61 @@
         "deleteModel": "Eliminar Modelo",
         "deleteConfig": "Eliminar Configuración",
         "deleteMsg1": "¿Estás seguro de querer eliminar esta entrada de modelo de InvokeAI?",
-        "deleteMsg2": "El checkpoint del modelo no se eliminará de tu disco. Puedes volver a añadirlo si lo deseas."
+        "deleteMsg2": "El checkpoint del modelo no se eliminará de tu disco. Puedes volver a añadirlo si lo deseas.",
+        "safetensorModels": "SafeTensors",
+        "addDiffuserModel": "Añadir difusores",
+        "inpainting": "v1 Repintado",
+        "repoIDValidationMsg": "Repositorio en línea de tu modelo",
+        "checkpointModels": "Puntos de control",
+        "convertToDiffusersHelpText4": "Este proceso se realiza una sola vez. Puede tardar entre 30 y 60 segundos dependiendo de las especificaciones de tu ordenador.",
+        "diffusersModels": "Difusores",
+        "addCheckpointModel": "Agregar modelo de punto de control/Modelo Safetensor",
+        "vaeRepoID": "Identificador del repositorio de VAE",
+        "vaeRepoIDValidationMsg": "Repositorio en línea de tú VAE",
+        "formMessageDiffusersModelLocation": "Difusores Modelo Ubicación",
+        "formMessageDiffusersModelLocationDesc": "Por favor, introduzca al menos uno.",
+        "formMessageDiffusersVAELocation": "Ubicación VAE",
+        "formMessageDiffusersVAELocationDesc": "Si no se proporciona, InvokeAI buscará el archivo VAE dentro de la ubicación del modelo indicada anteriormente.",
+        "convert": "Convertir",
+        "convertToDiffusers": "Convertir en difusores",
+        "convertToDiffusersHelpText1": "Este modelo se convertirá al formato 🧨 Difusores.",
+        "convertToDiffusersHelpText2": "Este proceso sustituirá su entrada del Gestor de Modelos por la versión de Difusores del mismo modelo.",
+        "convertToDiffusersHelpText3": "Su archivo de puntos de control en el disco NO será borrado ni modificado de ninguna manera. Puede volver a añadir su punto de control al Gestor de Modelos si lo desea.",
+        "convertToDiffusersHelpText5": "Asegúrese de que dispone de suficiente espacio en disco. Los modelos suelen variar entre 4 GB y 7 GB de tamaño.",
+        "convertToDiffusersHelpText6": "¿Desea transformar este modelo?",
+        "convertToDiffusersSaveLocation": "Guardar ubicación",
+        "v1": "v1",
+        "v2": "v2",
+        "statusConverting": "Adaptar",
+        "modelConverted": "Modelo adaptado",
+        "sameFolder": "La misma carpeta",
+        "invokeRoot": "Carpeta InvokeAI",
+        "custom": "Personalizado",
+        "customSaveLocation": "Ubicación personalizada para guardar",
+        "merge": "Fusión",
+        "modelsMerged": "Modelos fusionados",
+        "mergeModels": "Combinar modelos",
+        "modelOne": "Modelo 1",
+        "modelTwo": "Modelo 2",
+        "modelThree": "Modelo 3",
+        "mergedModelName": "Nombre del modelo combinado",
+        "alpha": "Alfa",
+        "interpolationType": "Tipo de interpolación",
+        "mergedModelSaveLocation": "Guardar ubicación",
+        "mergedModelCustomSaveLocation": "Ruta personalizada",
+        "invokeAIFolder": "Invocar carpeta de la inteligencia artificial",
+        "modelMergeHeaderHelp2": "Sólo se pueden fusionar difusores. Si desea fusionar un modelo de punto de control, conviértalo primero en difusores.",
+        "modelMergeAlphaHelp": "Alfa controla la fuerza de mezcla de los modelos. Los valores alfa más bajos reducen la influencia del segundo modelo.",
+        "modelMergeInterpAddDifferenceHelp": "En este modo, el Modelo 3 se sustrae primero del Modelo 2. La versión resultante se mezcla con el Modelo 1 con la tasa alfa establecida anteriormente. La versión resultante se mezcla con el Modelo 1 con la tasa alfa establecida anteriormente.",
+        "ignoreMismatch": "Ignorar discrepancias entre modelos seleccionados",
+        "modelMergeHeaderHelp1": "Puede combinar hasta tres modelos diferentes para crear una mezcla que se adapte a sus necesidades.",
+        "inverseSigmoid": "Sigmoideo inverso",
+        "weightedSum": "Modelo de suma ponderada",
+        "sigmoid": "Función sigmoide",
+        "allModels": "Todos los modelos",
+        "repo_id": "Identificador del repositorio",
+        "pathToCustomConfig": "Ruta a la configuración personalizada",
+        "customConfig": "Configuración personalizada"
     },
     "parameters": {
         "images": "Imágenes",
@@ -380,7 +453,22 @@
         "info": "Información",
         "deleteImage": "Eliminar Imagen",
         "initialImage": "Imagen Inicial",
-        "showOptionsPanel": "Mostrar panel de opciones"
+        "showOptionsPanel": "Mostrar panel de opciones",
+        "symmetry": "Simetría",
+        "vSymmetryStep": "Paso de simetría V",
+        "hSymmetryStep": "Paso de simetría H",
+        "cancel": {
+            "immediate": "Cancelar inmediatamente",
+            "schedule": "Cancelar tras la iteración actual",
+            "isScheduled": "Cancelando",
+            "setType": "Tipo de cancelación"
+        },
+        "copyImage": "Copiar la imagen",
+        "general": "General",
+        "negativePrompts": "Preguntas negativas",
+        "imageToImage": "Imagen a imagen",
+        "denoisingStrength": "Intensidad de la eliminación del ruido",
+        "hiresStrength": "Alta resistencia"
     },
     "settings": {
         "models": "Modelos",
@@ -393,7 +481,8 @@
         "resetWebUI": "Restablecer interfaz web",
         "resetWebUIDesc1": "Al restablecer la interfaz web, solo se restablece la caché local del navegador de sus imágenes y la configuración guardada. No se elimina ninguna imagen de su disco duro.",
         "resetWebUIDesc2": "Si las imágenes no se muestran en la galería o algo más no funciona, intente restablecer antes de reportar un incidente en GitHub.",
-        "resetComplete": "La interfaz web se ha restablecido. Actualice la página para recargarla."
+        "resetComplete": "La interfaz web se ha restablecido. Actualice la página para recargarla.",
+        "useSlidersForAll": "Utilice controles deslizantes para todas las opciones"
     },
     "toast": {
         "tempFoldersEmptied": "Directorio temporal vaciado",
@@ -431,12 +520,12 @@
         "feature": {
             "prompt": "Este campo tomará todo el texto de entrada, incluidos tanto los términos de contenido como los estilísticos. Si bien se pueden incluir pesos en la solicitud, los comandos/parámetros estándar de línea de comandos no funcionarán.",
             "gallery": "Conforme se generan nuevas invocaciones, los archivos del directorio de salida se mostrarán aquí. Las generaciones tienen opciones adicionales para configurar nuevas generaciones.",
-            "other": "Estas opciones habilitarán modos de procesamiento alternativos para Invoke. El modo sin costuras funciona para generar patrones repetitivos en la salida. La optimización de alta resolución realiza un ciclo de generación de dos pasos y debe usarse en resoluciones más altas cuando desee una imagen/composición más coherente.",
+            "other": "Estas opciones habilitarán modos de procesamiento alternativos para Invoke. 'Seamless mosaico' creará patrones repetitivos en la salida. 'Alta resolución' es la generación en dos pasos con img2img: use esta configuración cuando desee una imagen más grande y más coherente sin artefactos. tomar más tiempo de lo habitual txt2img.",
             "seed": "Los valores de semilla proporcionan un conjunto inicial de ruido que guían el proceso de eliminación de ruido y se pueden aleatorizar o rellenar con una semilla de una invocación anterior. La función Umbral se puede usar para mitigar resultados indeseables a valores CFG más altos (intente entre 0-10), y Perlin se puede usar para agregar ruido Perlin al proceso de eliminación de ruido. Ambos sirven para agregar variación a sus salidas.",
             "variations": "Pruebe una variación con una cantidad entre 0 y 1 para cambiar la imagen de salida para la semilla establecida. Se encuentran variaciones interesantes en la semilla entre 0.1 y 0.3.",
             "upscale": "Usando ESRGAN, puede aumentar la resolución de salida sin requerir un ancho/alto más alto en la generación inicial.",
             "faceCorrection": "Usando GFPGAN o Codeformer, la corrección de rostros intentará identificar rostros en las salidas y corregir cualquier defecto/anormalidad. Los valores de fuerza más altos aplicarán una presión correctiva más fuerte en las salidas, lo que resultará en rostros más atractivos. Con Codeformer, una mayor fidelidad intentará preservar la imagen original, a expensas de la fuerza de corrección de rostros.",
-            "imageToImage": "Imagen a Imagen permite cargar una imagen inicial, que InvokeAI usará para guiar el proceso de generación, junto con una solicitud. Un valor más bajo para esta configuración se parecerá más a la imagen original. Se aceptan valores entre 0-1, y se recomienda un rango de .25-.75.",
+            "imageToImage": "Imagen a Imagen permite cargar una imagen inicial, que InvokeAI usará para guiar el proceso de generación, junto con una solicitud. Un valor más bajo para esta configuración se parecerá más a la imagen original. Se aceptan valores entre 0-1, y se recomienda un rango de .25-.75",
             "boundingBox": "La caja delimitadora es análoga a las configuraciones de Ancho y Alto para Texto a Imagen o Imagen a Imagen. Solo se procesará el área en la caja.",
             "seamCorrection": "Controla el manejo de parches visibles que pueden ocurrir cuando se pega una imagen generada de nuevo en el lienzo.",
             "infillAndScaling": "Administra los métodos de relleno (utilizados en áreas enmascaradas o borradas del lienzo) y la escala (útil para tamaños de caja delimitadora pequeños)."

invokeai/frontend/public/locales/pt_BR.json

@@ -44,7 +44,26 @@
         "statusUpscaling": "Redimensinando",
         "statusUpscalingESRGAN": "Redimensinando (ESRGAN)",
         "statusLoadingModel": "Carregando Modelo",
-        "statusModelChanged": "Modelo Alterado"
+        "statusModelChanged": "Modelo Alterado",
+        "githubLabel": "Github",
+        "discordLabel": "Discord",
+        "langArabic": "Árabe",
+        "langEnglish": "Inglês",
+        "langDutch": "Holandês",
+        "langFrench": "Francês",
+        "langGerman": "Alemão",
+        "langItalian": "Italiano",
+        "langJapanese": "Japonês",
+        "langPolish": "Polonês",
+        "langSimplifiedChinese": "Chinês",
+        "langUkranian": "Ucraniano",
+        "back": "Voltar",
+        "statusConvertingModel": "Convertendo Modelo",
+        "statusModelConverted": "Modelo Convertido",
+        "statusMergingModels": "Mesclando Modelos",
+        "statusMergedModels": "Modelos Mesclados",
+        "langRussian": "Russo",
+        "langSpanish": "Espanhol"
     },
     "gallery": {
         "generations": "Gerações",
@@ -237,7 +256,7 @@
             "desc": "Salva a tela atual na galeria"
         },
         "copyToClipboard": {
-            "title": "Copiar Para a Área de Transferência ",
+            "title": "Copiar para a Área de Transferência",
             "desc": "Copia a tela atual para a área de transferência"
         },
         "downloadImage": {
@@ -284,7 +303,7 @@
         "nameValidationMsg": "Insira um nome para o seu modelo",
         "description": "Descrição",
         "descriptionValidationMsg": "Adicione uma descrição para o seu modelo",
-        "config": "Config",
+        "config": "Configuração",
         "configValidationMsg": "Caminho para o arquivo de configuração do seu modelo.",
         "modelLocation": "Localização do modelo",
         "modelLocationValidationMsg": "Caminho para onde seu modelo está localizado.",
@@ -317,7 +336,52 @@
         "deleteModel": "Excluir modelo",
         "deleteConfig": "Excluir Config",
         "deleteMsg1": "Tem certeza de que deseja excluir esta entrada do modelo de InvokeAI?",
-        "deleteMsg2": "Isso não vai excluir o arquivo de modelo checkpoint do seu disco. Você pode lê-los, se desejar."
+        "deleteMsg2": "Isso não vai excluir o arquivo de modelo checkpoint do seu disco. Você pode lê-los, se desejar.",
+        "checkpointModels": "Checkpoints",
+        "diffusersModels": "Diffusers",
+        "safetensorModels": "SafeTensors",
+        "addCheckpointModel": "Adicionar Modelo de Checkpoint/Safetensor",
+        "addDiffuserModel": "Adicionar Diffusers",
+        "repo_id": "Repo ID",
+        "vaeRepoID": "VAE Repo ID",
+        "vaeRepoIDValidationMsg": "Repositório Online do seu VAE",
+        "scanAgain": "Digitalize Novamente",
+        "selectAndAdd": "Selecione e Adicione Modelos Listados Abaixo",
+        "noModelsFound": "Nenhum Modelo Encontrado",
+        "formMessageDiffusersModelLocation": "Localização dos Modelos Diffusers",
+        "formMessageDiffusersModelLocationDesc": "Por favor entre com ao menos um.",
+        "formMessageDiffusersVAELocation": "Localização do VAE",
+        "formMessageDiffusersVAELocationDesc": "Se não provido, InvokeAI irá procurar pelo arquivo VAE dentro do local do modelo.",
+        "convertToDiffusers": "Converter para Diffusers",
+        "convertToDiffusersHelpText1": "Este modelo será convertido para o formato 🧨 Diffusers.",
+        "convertToDiffusersHelpText5": "Por favor, certifique-se de que você tenha espaço suficiente em disco. Os modelos geralmente variam entre 4GB e 7GB de tamanho.",
+        "convertToDiffusersHelpText6": "Você deseja converter este modelo?",
+        "convertToDiffusersSaveLocation": "Local para Salvar",
+        "v1": "v1",
+        "v2": "v2",
+        "inpainting": "v1 Inpainting",
+        "customConfig": "Configuração personalizada",
+        "pathToCustomConfig": "Caminho para configuração personalizada",
+        "convertToDiffusersHelpText3": "Seu arquivo de ponto de verificação no disco NÃO será excluído ou modificado de forma alguma. Você pode adicionar seu ponto de verificação ao Gerenciador de modelos novamente, se desejar.",
+        "convertToDiffusersHelpText4": "Este é um processo único. Pode levar cerca de 30 a 60s, dependendo das especificações do seu computador.",
+        "merge": "Mesclar",
+        "modelsMerged": "Modelos mesclados",
+        "mergeModels": "Mesclar modelos",
+        "modelOne": "Modelo 1",
+        "modelTwo": "Modelo 2",
+        "modelThree": "Modelo 3",
+        "statusConverting": "Convertendo",
+        "modelConverted": "Modelo Convertido",
+        "sameFolder": "Mesma pasta",
+        "invokeRoot": "Pasta do InvokeAI",
+        "custom": "Personalizado",
+        "customSaveLocation": "Local de salvamento personalizado",
+        "mergedModelName": "Nome do modelo mesclado",
+        "alpha": "Alpha",
+        "allModels": "Todos os Modelos",
+        "repoIDValidationMsg": "Repositório Online do seu Modelo",
+        "convert": "Converter",
+        "convertToDiffusersHelpText2": "Este processo irá substituir sua entrada de Gerenciador de Modelos por uma versão Diffusers do mesmo modelo."
     },
     "parameters": {
         "images": "Imagems",
@@ -442,14 +506,14 @@
         "move": "Mover",
         "resetView": "Resetar Visualização",
         "mergeVisible": "Fundir Visível",
-        "saveToGallery": "Save To Gallery",
+        "saveToGallery": "Salvar na Galeria",
         "copyToClipboard": "Copiar para a Área de Transferência",
         "downloadAsImage": "Baixar Como Imagem",
         "undo": "Desfazer",
         "redo": "Refazer",
         "clearCanvas": "Limpar Tela",
         "canvasSettings": "Configurações de Tela",
-        "showIntermediates": "Show Intermediates",
+        "showIntermediates": "Mostrar Intermediários",
         "showGrid": "Mostrar Grade",
         "snapToGrid": "Encaixar na Grade",
         "darkenOutsideSelection": "Escurecer Seleção Externa",

invokeai/frontend/public/locales/ro.json

@@ -0,0 +1 @@
+{}

invokeai/frontend/src/app/socketio/listeners.ts

@@ -392,7 +392,7 @@ const makeSocketIOListeners = (
         addLogEntry({
           timestamp: dateFormat(new Date(), 'isoDateTime'),
           message: `${i18n.t(
-            'modelmanager:modelAdded'
+            'modelManager.modelAdded'
           )}: ${deleted_model_name}`,
           level: 'info',
         })
@@ -400,7 +400,7 @@ const makeSocketIOListeners = (
       dispatch(
         addToast({
           title: `${i18n.t(
-            'modelmanager:modelEntryDeleted'
+            'modelManager.modelEntryDeleted'
           )}: ${deleted_model_name}`,
           status: 'success',
           duration: 2500,
@@ -424,7 +424,7 @@ const makeSocketIOListeners = (
       dispatch(
         addToast({
           title: `${i18n.t(
-            'modelmanager:modelConverted'
+            'modelManager.modelConverted'
           )}: ${converted_model_name}`,
           status: 'success',
           duration: 2500,

invokeai/frontend/src/common/util/parameterTranslation.ts

@@ -144,8 +144,8 @@ export const frontendToBackendParameters = (
     variationAmount,
     width,
     shouldUseSymmetry,
-    horizontalSymmetryTimePercentage,
-    verticalSymmetryTimePercentage,
+    horizontalSymmetrySteps,
+    verticalSymmetrySteps,
   } = generationState;
 
   const {
@@ -185,17 +185,17 @@ export const frontendToBackendParameters = (
 
   // Symmetry Settings
   if (shouldUseSymmetry) {
-    if (horizontalSymmetryTimePercentage > 0) {
+    if (horizontalSymmetrySteps > 0) {
       generationParameters.h_symmetry_time_pct = Math.max(
         0,
-        Math.min(1, horizontalSymmetryTimePercentage / steps)
+        Math.min(1, horizontalSymmetrySteps / steps)
       );
     }
 
-    if (horizontalSymmetryTimePercentage > 0) {
+    if (verticalSymmetrySteps > 0) {
       generationParameters.v_symmetry_time_pct = Math.max(
         0,
-        Math.min(1, verticalSymmetryTimePercentage / steps)
+        Math.min(1, verticalSymmetrySteps / steps)
       );
     }
   }

invokeai/frontend/src/features/canvas/components/IAICanvasStatusText.tsx

@@ -109,7 +109,7 @@ const IAICanvasStatusText = () => {
             color: boundingBoxColor,
           }}
         >{`${t(
-          'unifiedcanvas:boundingBox'
+          'unifiedCanvas.boundingBox'
         )}: ${boundingBoxDimensionsString}`}</div>
       )}
       {shouldShowScaledBoundingBox && (
@@ -118,19 +118,19 @@ const IAICanvasStatusText = () => {
             color: boundingBoxColor,
           }}
         >{`${t(
-          'unifiedcanvas:scaledBoundingBox'
+          'unifiedCanvas.scaledBoundingBox'
         )}: ${scaledBoundingBoxDimensionsString}`}</div>
       )}
       {shouldShowCanvasDebugInfo && (
         <>
           <div>{`${t(
-            'unifiedcanvas:boundingBoxPosition'
+            'unifiedCanvas.boundingBoxPosition'
           )}: ${boundingBoxCoordinatesString}`}</div>
           <div>{`${t(
-            'unifiedcanvas:canvasDimensions'
+            'unifiedCanvas.canvasDimensions'
           )}: ${canvasDimensionsString}`}</div>
           <div>{`${t(
-            'unifiedcanvas:canvasPosition'
+            'unifiedCanvas.canvasPosition'
           )}: ${canvasCoordinatesString}`}</div>
           <IAICanvasStatusTextCursorPos />
         </>

invokeai/frontend/src/features/canvas/components/IAICanvasStatusText/IAICanvasStatusTextCursorPos.tsx

@@ -34,7 +34,7 @@ export default function IAICanvasStatusTextCursorPos() {
 
   return (
     <div>{`${t(
-      'unifiedcanvas:cursorPosition'
+      'unifiedCanvas.cursorPosition'
     )}: ${cursorCoordinatesString}`}</div>
   );
 }

invokeai/frontend/src/features/parameters/components/AdvancedParameters/Output/SymmetrySettings.tsx

@@ -2,18 +2,18 @@ import { RootState } from 'app/store';
 import { useAppDispatch, useAppSelector } from 'app/storeHooks';
 import IAISlider from 'common/components/IAISlider';
 import {
-  setHorizontalSymmetryTimePercentage,
-  setVerticalSymmetryTimePercentage,
+  setHorizontalSymmetrySteps,
+  setVerticalSymmetrySteps,
 } from 'features/parameters/store/generationSlice';
 import { useTranslation } from 'react-i18next';
 
 export default function SymmetrySettings() {
-  const horizontalSymmetryTimePercentage = useAppSelector(
-    (state: RootState) => state.generation.horizontalSymmetryTimePercentage
+  const horizontalSymmetrySteps = useAppSelector(
+    (state: RootState) => state.generation.horizontalSymmetrySteps
   );
 
-  const verticalSymmetryTimePercentage = useAppSelector(
-    (state: RootState) => state.generation.verticalSymmetryTimePercentage
+  const verticalSymmetrySteps = useAppSelector(
+    (state: RootState) => state.generation.verticalSymmetrySteps
   );
 
   const steps = useAppSelector((state: RootState) => state.generation.steps);
@@ -26,28 +26,28 @@ export default function SymmetrySettings() {
     <>
       <IAISlider
         label={t('parameters.hSymmetryStep')}
-        value={horizontalSymmetryTimePercentage}
-        onChange={(v) => dispatch(setHorizontalSymmetryTimePercentage(v))}
+        value={horizontalSymmetrySteps}
+        onChange={(v) => dispatch(setHorizontalSymmetrySteps(v))}
         min={0}
         max={steps}
         step={1}
         withInput
         withSliderMarks
         withReset
-        handleReset={() => dispatch(setHorizontalSymmetryTimePercentage(0))}
+        handleReset={() => dispatch(setHorizontalSymmetrySteps(0))}
         sliderMarkRightOffset={-6}
       ></IAISlider>
       <IAISlider
         label={t('parameters.vSymmetryStep')}
-        value={verticalSymmetryTimePercentage}
-        onChange={(v) => dispatch(setVerticalSymmetryTimePercentage(v))}
+        value={verticalSymmetrySteps}
+        onChange={(v) => dispatch(setVerticalSymmetrySteps(v))}
         min={0}
         max={steps}
         step={1}
         withInput
         withSliderMarks
         withReset
-        handleReset={() => dispatch(setVerticalSymmetryTimePercentage(0))}
+        handleReset={() => dispatch(setVerticalSymmetrySteps(0))}
         sliderMarkRightOffset={-6}
       ></IAISlider>
     </>

invokeai/frontend/src/features/parameters/components/MainParameters/MainSteps.tsx

@@ -3,7 +3,10 @@ import { useAppDispatch, useAppSelector } from 'app/storeHooks';
 import IAINumberInput from 'common/components/IAINumberInput';
 
 import IAISlider from 'common/components/IAISlider';
-import { setSteps } from 'features/parameters/store/generationSlice';
+import {
+  clampSymmetrySteps,
+  setSteps,
+} from 'features/parameters/store/generationSlice';
 import { useTranslation } from 'react-i18next';
 
 export default function MainSteps() {
@@ -14,7 +17,13 @@ export default function MainSteps() {
   );
   const { t } = useTranslation();
 
-  const handleChangeSteps = (v: number) => dispatch(setSteps(v));
+  const handleChangeSteps = (v: number) => {
+    dispatch(setSteps(v));
+  };
+
+  const handleBlur = () => {
+    dispatch(clampSymmetrySteps());
+  };
 
   return shouldUseSliders ? (
     <IAISlider
@@ -41,6 +50,7 @@ export default function MainSteps() {
       width="auto"
       styleClass="main-settings-block"
       textAlign="center"
+      onBlur={handleBlur}
     />
   );
 }

invokeai/frontend/src/features/parameters/components/ProcessButtons/InvokeButton.tsx

@@ -5,6 +5,7 @@ import IAIButton, { IAIButtonProps } from 'common/components/IAIButton';
 import IAIIconButton, {
   IAIIconButtonProps,
 } from 'common/components/IAIIconButton';
+import { clampSymmetrySteps } from 'features/parameters/store/generationSlice';
 import { activeTabNameSelector } from 'features/ui/store/uiSelectors';
 import { useHotkeys } from 'react-hotkeys-hook';
 import { useTranslation } from 'react-i18next';
@@ -30,6 +31,7 @@ export default function InvokeButton(props: InvokeButton) {
   useHotkeys(
     ['ctrl+enter', 'meta+enter'],
     () => {
+      dispatch(clampSymmetrySteps());
       dispatch(generateImage(activeTabName));
     },
     {

invokeai/frontend/src/features/parameters/store/generationSlice.ts

@@ -4,6 +4,7 @@ import * as InvokeAI from 'app/invokeai';
 import { getPromptAndNegative } from 'common/util/getPromptAndNegative';
 import promptToString from 'common/util/promptToString';
 import { seedWeightsToString } from 'common/util/seedWeightPairs';
+import { clamp } from 'lodash';
 
 export interface GenerationState {
   cfgScale: number;
@@ -33,8 +34,8 @@ export interface GenerationState {
   variationAmount: number;
   width: number;
   shouldUseSymmetry: boolean;
-  horizontalSymmetryTimePercentage: number;
-  verticalSymmetryTimePercentage: number;
+  horizontalSymmetrySteps: number;
+  verticalSymmetrySteps: number;
 }
 
 const initialGenerationState: GenerationState = {
@@ -64,8 +65,8 @@ const initialGenerationState: GenerationState = {
   variationAmount: 0.1,
   width: 512,
   shouldUseSymmetry: false,
-  horizontalSymmetryTimePercentage: 0,
-  verticalSymmetryTimePercentage: 0,
+  horizontalSymmetrySteps: 0,
+  verticalSymmetrySteps: 0,
 };
 
 const initialState: GenerationState = initialGenerationState;
@@ -99,6 +100,18 @@ export const generationSlice = createSlice({
     setSteps: (state, action: PayloadAction<number>) => {
       state.steps = action.payload;
     },
+    clampSymmetrySteps: (state) => {
+      state.horizontalSymmetrySteps = clamp(
+        state.horizontalSymmetrySteps,
+        0,
+        state.steps
+      );
+      state.verticalSymmetrySteps = clamp(
+        state.verticalSymmetrySteps,
+        0,
+        state.steps
+      );
+    },
     setCfgScale: (state, action: PayloadAction<number>) => {
       state.cfgScale = action.payload;
     },
@@ -334,22 +347,17 @@ export const generationSlice = createSlice({
     setShouldUseSymmetry: (state, action: PayloadAction<boolean>) => {
       state.shouldUseSymmetry = action.payload;
     },
-    setHorizontalSymmetryTimePercentage: (
-      state,
-      action: PayloadAction<number>
-    ) => {
-      state.horizontalSymmetryTimePercentage = action.payload;
+    setHorizontalSymmetrySteps: (state, action: PayloadAction<number>) => {
+      state.horizontalSymmetrySteps = action.payload;
     },
-    setVerticalSymmetryTimePercentage: (
-      state,
-      action: PayloadAction<number>
-    ) => {
-      state.verticalSymmetryTimePercentage = action.payload;
+    setVerticalSymmetrySteps: (state, action: PayloadAction<number>) => {
+      state.verticalSymmetrySteps = action.payload;
     },
   },
 });
 
 export const {
+  clampSymmetrySteps,
   clearInitialImage,
   resetParametersState,
   resetSeed,
@@ -384,8 +392,8 @@ export const {
   setVariationAmount,
   setWidth,
   setShouldUseSymmetry,
-  setHorizontalSymmetryTimePercentage,
-  setVerticalSymmetryTimePercentage,
+  setHorizontalSymmetrySteps,
+  setVerticalSymmetrySteps,
 } = generationSlice.actions;
 
 export default generationSlice.reducer;

invokeai/frontend/src/features/system/components/ModelManager/MergeModels.tsx

@@ -57,19 +57,19 @@ export default function MergeModels() {
 
   const [modelMergeForce, setModelMergeForce] = useState<boolean>(false);
 
-  const modelOneList = Object.keys(diffusersModels).filter((model) => {
-    if (model !== modelTwo && model !== modelThree) return model;
-  });
+  const modelOneList = Object.keys(diffusersModels).filter(
+    (model) => model !== modelTwo && model !== modelThree
+  );
 
-  const modelTwoList = Object.keys(diffusersModels).filter((model) => {
-    if (model !== modelOne && model !== modelThree) return model;
-  });
+  const modelTwoList = Object.keys(diffusersModels).filter(
+    (model) => model !== modelOne && model !== modelThree
+  );
 
   const modelThreeList = [
-    'none',
-    ...Object.keys(diffusersModels).filter((model) => {
-      if (model !== modelOne && model !== modelTwo) return model;
-    }),
+    { key: t('modelManager.none'), value: 'none' },
+    ...Object.keys(diffusersModels)
+      .filter((model) => model !== modelOne && model !== modelTwo)
+      .map((model) => ({ key: model, value: model })),
   ];
 
   const isProcessing = useAppSelector(
@@ -209,18 +209,22 @@ export default function MergeModels() {
                 <Flex columnGap={4}>
                   {modelThree === 'none' ? (
                     <>
-                      <Radio value="weighted_sum">weighted_sum</Radio>
-                      <Radio value="sigmoid">sigmoid</Radio>
-                      <Radio value="inv_sigmoid">inv_sigmoid</Radio>
+                      <Radio value="weighted_sum">
+                        {t('modelManager.weightedSum')}
+                      </Radio>
+                      <Radio value="sigmoid">{t('modelManager.sigmoid')}</Radio>
+                      <Radio value="inv_sigmoid">
+                        {t('modelManager.inverseSigmoid')}
+                      </Radio>
                     </>
                   ) : (
                     <Radio value="add_difference">
                       <Tooltip
                         label={t(
-                          'modelmanager:modelMergeInterpAddDifferenceHelp'
+                          'modelManager.modelMergeInterpAddDifferenceHelp'
                         )}
                       >
-                        add_difference
+                        {t('modelManager.addDifference')}
                       </Tooltip>
                     </Radio>
                   )}

invokeai/frontend/src/features/ui/components/InvokeParametersPanel.tsx

@@ -18,6 +18,7 @@ import { setParametersPanelScrollPosition } from 'features/ui/store/uiSlice';
 import InvokeAILogo from 'assets/images/logo.png';
 import { isEqual } from 'lodash';
 import { uiSelector } from '../store/uiSelectors';
+import { useTranslation } from 'react-i18next';
 
 type Props = { children: ReactNode };
 
@@ -60,6 +61,8 @@ const InvokeOptionsPanel = (props: Props) => {
 
   const { children } = props;
 
+  const { t } = useTranslation();
+
   // Hotkeys
   useHotkeys(
     'o',
@@ -176,7 +179,7 @@ const InvokeOptionsPanel = (props: Props) => {
               }
             }}
           >
-            <Tooltip label="Pin Options Panel">
+            <Tooltip label={t('common.pinOptionsPanel')}>
               <div
                 className="parameters-panel-pin-button"
                 data-selected={shouldPinParametersPanel}

invokeai/frontend/src/i18.d.ts

@@ -1,11 +1,16 @@
 import 'i18next';
 
+import en from '../public/locales/en.json';
+
 declare module 'i18next' {
   // Extend CustomTypeOptions
   interface CustomTypeOptions {
     // Setting Default Namespace As English
     defaultNS: 'en';
     // Custom Types For Resources
+    resources: {
+      en: typeof en;
+    };
     // Never Return Null
     returnNull: false;
   }

ldm/generate.py

@@ -650,6 +650,8 @@ class Generate:
     def clear_cuda_cache(self):
         if self._has_cuda():
             self.gather_cuda_stats()
+            # Run garbage collection prior to emptying the CUDA cache
+            gc.collect()
             torch.cuda.empty_cache()
 
     def clear_cuda_stats(self):

ldm/invoke/CLI.py

@@ -625,7 +625,7 @@ def set_default_output_dir(opt: Args, completer: Completer):
     completer.set_default_dir(opt.outdir)
 
 
-def import_model(model_path: str, gen, opt, completer, convert=False) -> str:
+def import_model(model_path: str, gen, opt, completer, convert=False):
     """
     model_path can be (1) a URL to a .ckpt file; (2) a local .ckpt file path;
     (3) a huggingface repository id; or (4) a local directory containing a
@@ -679,7 +679,7 @@ def _verify_load(model_name: str, gen) -> bool:
     current_model = gen.model_name
     try:
         if not gen.set_model(model_name):
-            return False
+            return
     except Exception as e:
         print(f"** model failed to load: {str(e)}")
         print(
@@ -706,7 +706,7 @@ def _get_model_name_and_desc(
     )
     return model_name, model_description
 
-def convert_model(model_name_or_path: Union[Path, str], gen, opt, completer) -> str:
+def convert_model(model_name_or_path: Union[Path, str], gen, opt, completer):
     model_name_or_path = model_name_or_path.replace("\\", "/")  # windows
     manager = gen.model_manager
     ckpt_path = None
@@ -740,19 +740,14 @@ def convert_model(model_name_or_path: Union[Path, str], gen, opt, completer) ->
         )
     else:
         try:
-            model_name = import_model(model_name_or_path, gen, opt, completer, convert=True)
+            import_model(model_name_or_path, gen, opt, completer, convert=True)
         except KeyboardInterrupt:
             return
 
-    if not model_name:
-        print("** Conversion failed. Aborting.")
-        return
-
     manager.commit(opt.conf)    
     if click.confirm(f"Delete the original .ckpt file at {ckpt_path}?", default=False):
         ckpt_path.unlink(missing_ok=True)
         print(f"{ckpt_path} deleted")
-    return model_name
 
 
 def del_config(model_name: str, gen, opt, completer):

ldm/invoke/_version.py

@@ -1 +1 @@
-__version__='2.3.1+rc2'
+__version__='2.3.1.post2'

ldm/invoke/ckpt_to_diffuser.py

@@ -17,16 +17,15 @@
 # Original file at: https://github.com/huggingface/diffusers/blob/main/scripts/convert_ldm_original_checkpoint_to_diffusers.py
 """ Conversion script for the LDM checkpoints. """
 
-import os
 import re
 import torch
 import warnings
 from pathlib import Path
 from ldm.invoke.globals import (
-    Globals,
     global_cache_dir,
     global_config_dir,
     )
+from ldm.invoke.model_manager import ModelManager, SDLegacyType
 from safetensors.torch import load_file
 from typing import Union
 
@@ -760,7 +759,12 @@ def convert_open_clip_checkpoint(checkpoint):
 
     text_model_dict = {}
 
-    d_model = int(checkpoint["cond_stage_model.model.text_projection"].shape[0])
+    if 'cond_stage_model.model.text_projection' in keys:
+        d_model = int(checkpoint["cond_stage_model.model.text_projection"].shape[0])
+    elif 'cond_stage_model.model.ln_final.bias' in keys:
+        d_model = int(checkpoint['cond_stage_model.model.ln_final.bias'].shape[0])
+    else:
+        raise KeyError('Expected key "cond_stage_model.model.text_projection" not found in model')
 
     text_model_dict["text_model.embeddings.position_ids"] = text_model.text_model.embeddings.get_buffer("position_ids")
 
@@ -856,20 +860,23 @@ def load_pipeline_from_original_stable_diffusion_ckpt(
 
         upcast_attention = False
         if original_config_file is None:
-            key_name = "model.diffusion_model.input_blocks.2.1.transformer_blocks.0.attn2.to_k.weight"
-
-            if key_name in checkpoint and checkpoint[key_name].shape[-1] == 1024:
+            model_type = ModelManager.probe_model_type(checkpoint)
+            
+            if model_type == SDLegacyType.V2:
                 original_config_file = global_config_dir() / 'stable-diffusion' / 'v2-inference-v.yaml'
-
                 if global_step == 110000:
                     # v2.1 needs to upcast attention
                     upcast_attention = True
-            elif str(checkpoint_path).lower().find('inpaint') >= 0: # brittle - please pass original_config_file parameter!
-                print(f'  | checkpoint has "inpaint" in name, assuming an inpainting model')
+                    
+            elif model_type == SDLegacyType.V1_INPAINT:
                 original_config_file = global_config_dir() / 'stable-diffusion' / 'v1-inpainting-inference.yaml'
-            else:
+                
+            elif model_type == SDLegacyType.V1:
                 original_config_file = global_config_dir() / 'stable-diffusion' / 'v1-inference.yaml'
 
+            else:
+                raise Exception('Unknown checkpoint type')
+
         original_config = OmegaConf.load(original_config_file)
 
         if num_in_channels is not None:
@@ -960,7 +967,7 @@ def load_pipeline_from_original_stable_diffusion_ckpt(
             text_model = convert_open_clip_checkpoint(checkpoint)
             tokenizer = CLIPTokenizer.from_pretrained("stabilityai/stable-diffusion-2",
                                                       subfolder="tokenizer",
-                                                      cache_dir=global_cache_dir('diffusers')
+                                                      cache_dir=cache_dir,
                                                       )
             pipe = pipeline_class(
                 vae=vae,

ldm/invoke/conditioning.py

@@ -88,7 +88,7 @@ def get_prompt_structure(prompt_string, skip_normalize_legacy_blend: bool = Fals
 
     return positive_prompt, negative_prompt
 
-def get_max_token_count(tokenizer, prompt: FlattenedPrompt|Blend, truncate_if_too_long=True) -> int:
+def get_max_token_count(tokenizer, prompt: Union[FlattenedPrompt, Blend], truncate_if_too_long=True) -> int:
     if type(prompt) is Blend:
         blend: Blend = prompt
         return max([get_max_token_count(tokenizer, c, truncate_if_too_long) for c in blend.prompts])
@@ -129,8 +129,8 @@ def split_prompt_to_positive_and_negative(prompt_string_uncleaned):
     return prompt_string_cleaned, unconditioned_words
 
 
-def log_tokenization(positive_prompt: Blend | FlattenedPrompt,
-                     negative_prompt: Blend | FlattenedPrompt,
+def log_tokenization(positive_prompt: Union[Blend, FlattenedPrompt],
+                     negative_prompt: Union[Blend, FlattenedPrompt],
                      tokenizer):
     print(f"\n>> [TOKENLOG] Parsed Prompt: {positive_prompt}")
     print(f"\n>> [TOKENLOG] Parsed Negative Prompt: {negative_prompt}")
@@ -139,7 +139,7 @@ def log_tokenization(positive_prompt: Blend | FlattenedPrompt,
     log_tokenization_for_prompt_object(negative_prompt, tokenizer, display_label_prefix="(negative prompt)")
 
 
-def log_tokenization_for_prompt_object(p: Blend | FlattenedPrompt, tokenizer, display_label_prefix=None):
+def log_tokenization_for_prompt_object(p: Union[Blend, FlattenedPrompt], tokenizer, display_label_prefix=None):
     display_label_prefix = display_label_prefix or ""
     if type(p) is Blend:
         blend: Blend = p

ldm/invoke/config/invokeai_configure.py

@@ -191,14 +191,18 @@ def download_bert():
 
 
 # ---------------------------------------------
-def download_clip():
-    print("Installing CLIP model...", file=sys.stderr)
+def download_sd1_clip():
+    print("Installing SD1 clip model...", file=sys.stderr)
     version = "openai/clip-vit-large-patch14"
-    print("Tokenizer...", file=sys.stderr)
     download_from_hf(CLIPTokenizer, version)
-    print("Text model...", file=sys.stderr)
     download_from_hf(CLIPTextModel, version)
 
+# ---------------------------------------------
+def download_sd2_clip():
+    version = 'stabilityai/stable-diffusion-2'
+    print("Installing SD2 clip model...", file=sys.stderr)
+    download_from_hf(CLIPTokenizer, version, subfolder='tokenizer')
+    download_from_hf(CLIPTextModel, version, subfolder='text_encoder')
 
 # ---------------------------------------------
 def download_realesrgan():
@@ -708,8 +712,8 @@ def write_opts(opts: Namespace, init_file: Path):
                     out_file.write(line + "\n")
             out_file.write(
                 f"""
---outdir={opts.outdir}
---embedding_path={opts.embedding_path}
+--outdir="{opts.outdir}"
+--embedding_path="{opts.embedding_path}"
 --precision={opts.precision}
 --max_loaded_models={int(opts.max_loaded_models)}
 --{'no-' if not opts.safety_checker else ''}nsfw_checker
@@ -832,7 +836,8 @@ def main():
         else:
             print("\n** DOWNLOADING SUPPORT MODELS **")
             download_bert()
-            download_clip()
+            download_sd1_clip()
+            download_sd2_clip()
             download_realesrgan()
             download_gfpgan()
             download_codeformer()

ldm/invoke/config/invokeai_update.py

@@ -2,18 +2,16 @@
 Minimalist updater script. Prompts user for the tag or branch to update to and runs
 pip install <path_to_git_source>.
 '''
-
+import os
 import platform
 import requests
-import subprocess
 from rich import box, print
-from rich.console import Console, group
+from rich.console import Console, Group, group
 from rich.panel import Panel
 from rich.prompt import Prompt
 from rich.style import Style
+from rich.syntax import Syntax
 from rich.text import Text
-from rich.live import Live
-from rich.table import Table
 
 from ldm.invoke import __version__
 
@@ -23,19 +21,17 @@ INVOKE_AI_REL="https://api.github.com/repos/invoke-ai/InvokeAI/releases"
 OS = platform.uname().system
 ARCH = platform.uname().machine
 
-ORANGE_ON_DARK_GREY = Style(bgcolor="grey23", color="orange1")
-
 if OS == "Windows":
     # Windows terminals look better without a background colour
     console = Console(style=Style(color="grey74"))
 else:
-    console = Console(style=Style(color="grey74", bgcolor="grey23"))
+    console = Console(style=Style(color="grey74", bgcolor="grey19"))
 
 def get_versions()->dict:
     return requests.get(url=INVOKE_AI_REL).json()
 
 def welcome(versions: dict):
-
+    
     @group()
     def text():
         yield f'InvokeAI Version: [bold yellow]{__version__}'
@@ -48,55 +44,45 @@ def welcome(versions: dict):
 [3] Manually enter the tag or branch name you wish to update'''
 
     console.rule()
-    console.print(
+    print(
         Panel(
             title="[bold wheat1]InvokeAI Updater",
             renderable=text(),
             box=box.DOUBLE,
             expand=True,
             padding=(1, 2),
-            style=ORANGE_ON_DARK_GREY,
+            style=Style(bgcolor="grey23", color="orange1"),
             subtitle=f"[bold grey39]{OS}-{ARCH}",
         )
     )
-    # console.rule is used instead of console.line to maintain dark background
-    # on terminals where light background is the default
-    console.rule(characters=" ")
+    console.line()
 
 def main():
     versions = get_versions()
     welcome(versions)
 
     tag = None
-    choice = Prompt.ask(Text.from_markup(('[grey74 on grey23]Choice:')),choices=['1','2','3'],default='1')
-
+    choice = Prompt.ask('Choice:',choices=['1','2','3'],default='1')
+    
     if choice=='1':
         tag = versions[0]['tag_name']
     elif choice=='2':
         tag = 'main'
     elif choice=='3':
-        tag = Prompt.ask('[grey74 on grey23]Enter an InvokeAI tag or branch name')
-
-    console.print(Panel(f':crossed_fingers: Upgrading to [yellow]{tag}[/yellow]', box=box.MINIMAL, style=ORANGE_ON_DARK_GREY))
+        tag = Prompt.ask('Enter an InvokeAI tag or branch name')
 
+    print(f':crossed_fingers: Upgrading to [yellow]{tag}[/yellow]')
     cmd = f'pip install {INVOKE_AI_SRC}/{tag}.zip --use-pep517'
-
-    progress = Table.grid(expand=True)
-    progress_panel = Panel(progress, box=box.MINIMAL, style=ORANGE_ON_DARK_GREY)
-
-    with subprocess.Popen(['bash', '-c', cmd], stdout=subprocess.PIPE, stderr=subprocess.PIPE) as proc:
-        progress.add_column()
-        with Live(progress_panel, console=console, vertical_overflow='visible'):
-            while proc.poll() is None:
-                for l in iter(proc.stdout.readline, b''):
-                    progress.add_row(l.decode().strip(), style=ORANGE_ON_DARK_GREY)
-        if proc.returncode == 0:
-            console.rule(f':heavy_check_mark: Upgrade successful')
-        else:
-            console.rule(f':exclamation: [bold red]Upgrade failed[/red bold]')
-
+    print('')
+    print('')
+    if os.system(cmd)==0:
+        print(f':heavy_check_mark: Upgrade successful')
+    else:
+        print(f':exclamation: [bold red]Upgrade failed[/red bold]')
+    
 if __name__ == "__main__":
     try:
         main()
     except KeyboardInterrupt:
         pass
+

ldm/invoke/config/model_install.py

@@ -114,37 +114,37 @@ class addModelsForm(npyscreen.FormMultiPage):
                 relx=4,
             )
         self.nextrely += 1
-        self.add_widget_intelligent(
-            CenteredTitleText,
-            name="== STARTER MODELS (recommended ones selected) ==",
-            editable=False,
-            color="CONTROL",
-        )
-        self.nextrely -= 1
-        self.add_widget_intelligent(
-            CenteredTitleText,
-            name="Select from a starter set of Stable Diffusion models from HuggingFace:",
-            editable=False,
-            labelColor="CAUTION",
-        )
-
-        self.nextrely -= 1
-        # if user has already installed some initial models, then don't patronize them
-        # by showing more recommendations
-        show_recommended = not self.existing_models
-        self.models_selected = self.add_widget_intelligent(
-            npyscreen.MultiSelect,
-            name="Install Starter Models",
-            values=starter_model_labels,
-            value=[
-                self.starter_model_list.index(x)
-                for x in self.starter_model_list
-                if show_recommended and x in recommended_models
-            ],
-            max_height=len(starter_model_labels) + 1,
-            relx=4,
-            scroll_exit=True,
-        )
+        if len(self.starter_model_list) > 0:
+            self.add_widget_intelligent(
+                CenteredTitleText,
+                name="== STARTER MODELS (recommended ones selected) ==",
+                editable=False,
+                color="CONTROL",
+            )
+            self.nextrely -= 1
+            self.add_widget_intelligent(
+                CenteredTitleText,
+                name="Select from a starter set of Stable Diffusion models from HuggingFace.",
+                editable=False,
+                labelColor="CAUTION",
+            )
+            self.nextrely -= 1
+            # if user has already installed some initial models, then don't patronize them
+            # by showing more recommendations
+            show_recommended = not self.existing_models
+            self.models_selected = self.add_widget_intelligent(
+                npyscreen.MultiSelect,
+                name="Install Starter Models",
+                values=starter_model_labels,
+                value=[
+                    self.starter_model_list.index(x)
+                    for x in self.starter_model_list
+                    if show_recommended and x in recommended_models
+                ],
+                max_height=len(starter_model_labels) + 1,
+                relx=4,
+                scroll_exit=True,
+            )
         self.add_widget_intelligent(
             CenteredTitleText,
             name='== IMPORT LOCAL AND REMOTE MODELS ==',
@@ -166,7 +166,11 @@ class addModelsForm(npyscreen.FormMultiPage):
             )
             self.nextrely -= 1
         self.import_model_paths = self.add_widget_intelligent(
-            TextBox, max_height=5, scroll_exit=True, editable=True, relx=4
+            TextBox,
+            max_height=7,
+            scroll_exit=True,
+            editable=True,
+            relx=4
         )
         self.nextrely += 1
         self.show_directory_fields = self.add_widget_intelligent(
@@ -241,7 +245,8 @@ class addModelsForm(npyscreen.FormMultiPage):
 
     def resize(self):
         super().resize()
-        self.models_selected.values = self._get_starter_model_labels()
+        if hasattr(self,'models_selected'):
+            self.models_selected.values = self._get_starter_model_labels()
 
     def _clear_scan_directory(self):
         if not self.show_directory_fields.value:
@@ -320,11 +325,14 @@ class addModelsForm(npyscreen.FormMultiPage):
         selections = self.parentApp.user_selections
 
         # starter models to install/remove
-        starter_models = dict(
-            map(
-                lambda x: (self.starter_model_list[x], True), self.models_selected.value
+        if hasattr(self,'models_selected'):
+            starter_models = dict(
+                map(
+                    lambda x: (self.starter_model_list[x], True), self.models_selected.value
+                )
             )
-        )
+        else:
+            starter_models = dict()
         selections.purge_deleted_models = False
         if hasattr(self, "previously_installed_models"):
             unchecked = [

ldm/invoke/config/model_install_backend.py

@@ -126,7 +126,7 @@ def install_requested_models(
                 while line := input.readline():
                     if not line.startswith(argument):
                         output.writelines([line])
-                output.writelines([f'{argument} {directory}'])
+                output.writelines([f'{argument} "{directory}"'])
         os.replace(replacement,initfile)
 
 # -------------------------------------

ldm/invoke/generator/base.py

@@ -137,17 +137,9 @@ class Generator:
         Given samples returned from a sampler, converts
         it into a PIL Image
         """
-        x_samples = self.model.decode_first_stage(samples)
-        x_samples = torch.clamp((x_samples + 1.0) / 2.0, min=0.0, max=1.0)
-        if len(x_samples) != 1:
-            raise Exception(
-                f'>> expected to get a single image, but got {len(x_samples)}')
-        x_sample = 255.0 * rearrange(
-            x_samples[0].cpu().numpy(), 'c h w -> h w c'
-        )
-        return Image.fromarray(x_sample.astype(np.uint8))
-
-        # write an approximate RGB image from latent samples for a single step to PNG
+        with torch.inference_mode():
+            image = self.model.decode_latents(samples)
+        return self.model.numpy_to_pil(image)[0]
 
     def repaste_and_color_correct(self, result: Image.Image, init_image: Image.Image, init_mask: Image.Image, mask_blur_radius: int = 8) -> Image.Image:
         if init_image is None or init_mask is None:

ldm/invoke/globals.py

@@ -19,15 +19,7 @@ from typing import Union
 
 Globals = Namespace()
 
-# This is usually overwritten by the command line and/or environment variables
-if os.environ.get('INVOKEAI_ROOT'):
-    Globals.root = osp.abspath(os.environ.get('INVOKEAI_ROOT'))
-elif os.environ.get('VIRTUAL_ENV'):
-    Globals.root = osp.abspath(osp.join(os.environ.get('VIRTUAL_ENV'), '..'))
-else:
-    Globals.root = osp.abspath(osp.expanduser('~/invokeai'))
-
-# Where to look for the initialization file
+# Where to look for the initialization file and other key components
 Globals.initfile = 'invokeai.init'
 Globals.models_file = 'models.yaml'
 Globals.models_dir = 'models'
@@ -35,6 +27,20 @@ Globals.config_dir = 'configs'
 Globals.autoscan_dir = 'weights'
 Globals.converted_ckpts_dir = 'converted_ckpts'
 
+# Set the default root directory. This can be overwritten by explicitly
+# passing the `--root <directory>` argument on the command line.
+# logic is:
+# 1) use INVOKEAI_ROOT environment variable (no check for this being a valid directory)
+# 2) use VIRTUAL_ENV environment variable, with a check for initfile being there
+# 3) use ~/invokeai
+
+if os.environ.get('INVOKEAI_ROOT'):
+    Globals.root = osp.abspath(os.environ.get('INVOKEAI_ROOT'))
+elif os.environ.get('VIRTUAL_ENV') and Path(os.environ.get('VIRTUAL_ENV'),'..',Globals.initfile).exists():
+    Globals.root = osp.abspath(osp.join(os.environ.get('VIRTUAL_ENV'), '..'))
+else:
+    Globals.root = osp.abspath(osp.expanduser('~/invokeai'))
+
 # Try loading patchmatch
 Globals.try_patchmatch = True
 

ldm/invoke/model_manager.py

@@ -624,7 +624,7 @@ class ModelManager(object):
         self,
         repo_or_path: Union[str, Path],
         model_name: str = None,
-        model_description: str = None,
+        description: str = None,
         vae: dict = None,
         commit_to_conf: Path = None,
     ) -> bool:
@@ -640,7 +640,7 @@ class ModelManager(object):
         models.yaml file.
         """
         model_name = model_name or Path(repo_or_path).stem
-        model_description = model_description or f"Imported diffusers model {model_name}"
+        model_description = description or f"Imported diffusers model {model_name}"
         new_config = dict(
             description=model_description,
             vae=vae,
@@ -725,7 +725,7 @@ class ModelManager(object):
         SDLegacyType.V1
         SDLegacyType.V1_INPAINT
         SDLegacyType.V2
-        UNKNOWN
+        SDLegacyType.UNKNOWN
         """
         key_name = "model.diffusion_model.input_blocks.2.1.transformer_blocks.0.attn2.to_k.weight"
         if key_name in checkpoint and checkpoint[key_name].shape[-1] == 1024:
@@ -785,7 +785,7 @@ class ModelManager(object):
         print(f">> Probing {thing} for import")
 
         if thing.startswith(("http:", "https:", "ftp:")):
-            print(f"   | {thing} appears to be a URL")
+            print(f"  | {thing} appears to be a URL")
             model_path = self._resolve_path(
                 thing, "models/ldm/stable-diffusion-v1"
             )  # _resolve_path does a download if needed
@@ -793,15 +793,15 @@ class ModelManager(object):
         elif Path(thing).is_file() and thing.endswith((".ckpt", ".safetensors")):
             if Path(thing).stem in ["model", "diffusion_pytorch_model"]:
                 print(
-                    f"   | {Path(thing).name} appears to be part of a diffusers model. Skipping import"
+                    f"  | {Path(thing).name} appears to be part of a diffusers model. Skipping import"
                 )
                 return
             else:
-                print(f"   | {thing} appears to be a checkpoint file on disk")
+                print(f"  | {thing} appears to be a checkpoint file on disk")
                 model_path = self._resolve_path(thing, "models/ldm/stable-diffusion-v1")
 
         elif Path(thing).is_dir() and Path(thing, "model_index.json").exists():
-            print(f"   | {thing} appears to be a diffusers file on disk")
+            print(f"  | {thing} appears to be a diffusers file on disk")
             model_name = self.import_diffuser_model(
                 thing,
                 vae=dict(repo_id="stabilityai/sd-vae-ft-mse"),
@@ -812,13 +812,13 @@ class ModelManager(object):
 
         elif Path(thing).is_dir():
             if (Path(thing) / "model_index.json").exists():
-                print(f">> {thing} appears to be a diffusers model.")
+                print(f"  | {thing} appears to be a diffusers model.")
                 model_name = self.import_diffuser_model(
                     thing, commit_to_conf=commit_to_conf
                 )
             else:
                 print(
-                    f">> {thing} appears to be a directory. Will scan for models to import"
+                    f"  |{thing} appears to be a directory. Will scan for models to import"
                 )
                 for m in list(Path(thing).rglob("*.ckpt")) + list(
                     Path(thing).rglob("*.safetensors")
@@ -830,7 +830,7 @@ class ModelManager(object):
                 return model_name
 
         elif re.match(r"^[\w.+-]+/[\w.+-]+$", thing):
-            print(f"   | {thing} appears to be a HuggingFace diffusers repo_id")
+            print(f"  | {thing} appears to be a HuggingFace diffusers repo_id")
             model_name = self.import_diffuser_model(
                 thing, commit_to_conf=commit_to_conf
             )
@@ -847,7 +847,7 @@ class ModelManager(object):
             return
 
         if model_path.stem in self.config:  # already imported
-            print("   | Already imported. Skipping")
+            print("  | Already imported. Skipping")
             return
 
         # another round of heuristics to guess the correct config file.
@@ -860,18 +860,18 @@ class ModelManager(object):
 
         model_config_file = None
         if model_type == SDLegacyType.V1:
-            print("   | SD-v1 model detected")
+            print("  | SD-v1 model detected")
             model_config_file = Path(
                 Globals.root, "configs/stable-diffusion/v1-inference.yaml"
             )
         elif model_type == SDLegacyType.V1_INPAINT:
-            print("   | SD-v1 inpainting model detected")
+            print("  | SD-v1 inpainting model detected")
             model_config_file = Path(
                 Globals.root, "configs/stable-diffusion/v1-inpainting-inference.yaml"
             )
         elif model_type == SDLegacyType.V2:
             print(
-                "   | SD-v2 model detected; model will be converted to diffusers format"
+                "  | SD-v2 model detected; model will be converted to diffusers format"
             )
             model_config_file = Path(
                 Globals.root, "configs/stable-diffusion/v2-inference-v.yaml"
@@ -923,7 +923,7 @@ class ModelManager(object):
         vae=None,
         original_config_file: Path = None,
         commit_to_conf: Path = None,
-    ) -> dict:
+    ) -> str:
         """
         Convert a legacy ckpt weights file to diffuser model and import
         into models.yaml.

pyproject.toml

@@ -38,7 +38,7 @@ dependencies = [
   "albumentations",
   "click",
   "clip_anytorch",          # replacing "clip @ https://github.com/openai/CLIP/archive/eaa22acb90a5876642d0507623e859909230a52d.zip",
-  "compel>=0.1.6",
+  "compel==0.1.7",
   "datasets",
   "diffusers[torch]~=0.13",
   "dnspython==2.2.1",

scripts/make_models_markdown_table.py

@@ -0,0 +1,23 @@
+#!/usr/bin/env python
+
+'''
+This script is used at release time to generate a markdown table describing the
+starter models. This text is then manually copied into 050_INSTALL_MODELS.md.
+'''
+
+from omegaconf import OmegaConf
+from pathlib import Path
+
+
+def main():
+    initial_models_file = Path(__file__).parent / '../invokeai/configs/INITIAL_MODELS.yaml'
+    models = OmegaConf.load(initial_models_file)
+    print('|Model Name | HuggingFace Repo ID | Description | URL |')
+    print('|---------- | ---------- | ----------- | --- |')
+    for model in models:
+        repo_id = models[model].repo_id
+        url = f'https://huggingface.co/{repo_id}'
+        print(f'|{model}|{repo_id}|{models[model].description}|{url} |')
+
+if __name__ == '__main__':
+    main()