fix(nodes): fix metadata test

- make metadata a service
- rip out pydantic validation, implement metadata parsing as simple functions
- update tests
- address other minor feedback items

.dockerignore

@@ -1,3 +1,25 @@
+# use this file as a whitelist
 *
-!environment*.yml
-!docker-build
+!invokeai
+!ldm
+!pyproject.toml
+
+# ignore frontend/web but whitelist dist
+invokeai/frontend/web/
+!invokeai/frontend/web/dist/
+
+# ignore invokeai/assets but whitelist invokeai/assets/web
+invokeai/assets/
+!invokeai/assets/web/
+
+# Guard against pulling in any models that might exist in the directory tree
+**/*.pt*
+**/*.ckpt
+
+# Byte-compiled / optimized / DLL files
+**/__pycache__/
+**/*.py[cod]
+
+# Distribution / packaging
+**/*.egg-info/
+**/*.egg

.editorconfig

@@ -0,0 +1,12 @@
+# All files
+[*]
+charset = utf-8
+end_of_line = lf
+indent_size = 2
+indent_style = space
+insert_final_newline = true
+trim_trailing_whitespace = true
+
+# Python
+[*.py]
+indent_size = 4

.git-blame-ignore-revs

@@ -0,0 +1 @@
+b3dccfaeb636599c02effc377cdd8a87d658256c

.gitattributes

@@ -1,4 +1,4 @@
 # Auto normalizes line endings on commit so devs don't need to change local settings.
-# Only affects text files and ignores other file types. 
+# Only affects text files and ignores other file types.
 # For more info see: https://www.aleksandrhovhannisyan.com/blog/crlf-vs-lf-normalizing-line-endings-in-git/
 * text=auto

.github/CODEOWNERS

@@ -1,4 +1,34 @@
-ldm/invoke/pngwriter.py @CapableWeb
-ldm/invoke/server_legacy.py @CapableWeb
-scripts/legacy_api.py @CapableWeb
-tests/legacy_tests.sh @CapableWeb
+# continuous integration
+/.github/workflows/ @mauwii @lstein @blessedcoolant
+
+# documentation
+/docs/ @lstein @mauwii @tildebyte @blessedcoolant
+/mkdocs.yml @lstein @mauwii @blessedcoolant
+
+# nodes
+/invokeai/app/ @Kyle0654 @blessedcoolant
+
+# installation and configuration
+/pyproject.toml @mauwii @lstein @blessedcoolant
+/docker/ @mauwii @lstein @blessedcoolant
+/scripts/ @ebr @lstein
+/installer/ @lstein @ebr
+/invokeai/assets @lstein @ebr
+/invokeai/configs @lstein
+/invokeai/version @lstein @blessedcoolant
+
+# web ui
+/invokeai/frontend @blessedcoolant @psychedelicious @lstein
+/invokeai/backend @blessedcoolant @psychedelicious @lstein
+
+# generation, model management, postprocessing
+/invokeai/backend @keturn @damian0815 @lstein @blessedcoolant @jpphoto
+
+# front ends
+/invokeai/frontend/CLI @lstein
+/invokeai/frontend/install @lstein @ebr @mauwii 
+/invokeai/frontend/merge @lstein @blessedcoolant @hipsterusername
+/invokeai/frontend/training @lstein @blessedcoolant @hipsterusername
+/invokeai/frontend/web @psychedelicious @blessedcoolant
+
+

.github/ISSUE_TEMPLATE/BUG_REPORT.yml

@@ -0,0 +1,112 @@
+name: 🐞 Bug Report
+
+description: File a bug report
+
+title: '[bug]: '
+
+labels: ['bug']
+
+# assignees:
+#   - moderator_bot
+#   - lstein
+
+body:
+  - type: markdown
+    attributes:
+      value: |
+        Thanks for taking the time to fill out this Bug Report!
+
+  - type: checkboxes
+    attributes:
+      label: Is there an existing issue for this?
+      description: |
+        Please use the [search function](https://github.com/invoke-ai/InvokeAI/issues?q=is%3Aissue+is%3Aopen+label%3Abug)
+        irst to see if an issue already exists for the bug you encountered.
+      options:
+        - label: I have searched the existing issues
+          required: true
+
+  - type: markdown
+    attributes:
+      value: __Describe your environment__
+
+  - type: dropdown
+    id: os_dropdown
+    attributes:
+      label: OS
+      description: Which operating System did you use when the bug occured
+      multiple: false
+      options:
+        - 'Linux'
+        - 'Windows'
+        - 'macOS'
+    validations:
+      required: true
+
+  - type: dropdown
+    id: gpu_dropdown
+    attributes:
+      label: GPU
+      description: Which kind of Graphic-Adapter is your System using
+      multiple: false
+      options:
+        - 'cuda'
+        - 'amd'
+        - 'mps'
+        - 'cpu'
+    validations:
+      required: true
+
+  - type: input
+    id: vram
+    attributes:
+      label: VRAM
+      description: Size of the VRAM if known
+      placeholder: 8GB
+    validations:
+      required: false
+      
+  - type: input
+    id: version-number
+    attributes:
+      label: What version did you experience this issue on?
+      description: |
+        Please share the version of Invoke AI that you experienced the issue on. If this is not the latest version, please update first to confirm the issue still exists. If you are testing main, please include the commit hash instead.
+      placeholder: X.X.X
+    validations:
+      required: true
+
+  - type: textarea
+    id: what-happened
+    attributes:
+      label: What happened?
+      description: |
+        Briefly describe what happened, what you expected to happen and how to reproduce this bug.
+      placeholder: When using the webinterface and right-clicking on button X instead of the popup-menu there error Y appears
+    validations:
+      required: true
+
+  - type: textarea
+    attributes:
+      label: Screenshots
+      description: If applicable, add screenshots to help explain your problem
+      placeholder: this is what the result looked like <screenshot>
+    validations:
+      required: false
+
+  - type: textarea
+    attributes:
+      label: Additional context
+      description: Add any other context about the problem here
+      placeholder: Only happens when there is full moon and Friday the 13th on Christmas Eve 🎅🏻
+    validations:
+      required: false
+
+  - type: input
+    id: contact
+    attributes:
+      label: Contact Details
+      description: __OPTIONAL__ How can we get in touch with you if we need more info (besides this issue)?
+      placeholder: ex. email@example.com, discordname, twitter, ...
+    validations:
+      required: false

.github/ISSUE_TEMPLATE/FEATURE_REQUEST.yml

@@ -0,0 +1,56 @@
+name: Feature Request
+description: Commit a idea or Request a new feature
+title: '[enhancement]: '
+labels: ['enhancement']
+# assignees:
+#   - lstein
+#   - tildebyte
+body:
+  - type: markdown
+    attributes:
+      value: |
+        Thanks for taking the time to fill out this Feature request!
+
+  - type: checkboxes
+    attributes:
+      label: Is there an existing issue for this?
+      description: |
+        Please make use of the [search function](https://github.com/invoke-ai/InvokeAI/labels/enhancement)
+        to see if a simmilar issue already exists for the feature you want to request
+      options:
+        - label: I have searched the existing issues
+          required: true
+
+  - type: input
+    id: contact
+    attributes:
+      label: Contact Details
+      description: __OPTIONAL__ How could we get in touch with you if we need more info (besides this issue)?
+      placeholder: ex. email@example.com, discordname, twitter, ...
+    validations:
+      required: false
+
+  - type: textarea
+    id: whatisexpected
+    attributes:
+      label: What should this feature add?
+      description: Please try to explain the functionality this feature should add
+      placeholder: |
+        Instead of one huge textfield, it would be nice to have forms for bug-reports, feature-requests, ...
+        Great benefits with automatic labeling, assigning and other functionalitys not available in that form
+        via old-fashioned markdown-templates. I would also love to see the use of a moderator bot 🤖 like
+        https://github.com/marketplace/actions/issue-moderator-with-commands to auto close old issues and other things
+    validations:
+      required: true
+
+  - type: textarea
+    attributes:
+      label: Alternatives
+      description: Describe alternatives you've considered
+      placeholder: A clear and concise description of any alternative solutions or features you've considered.
+
+  - type: textarea
+    attributes:
+      label: Aditional Content
+      description: Add any other context or screenshots about the feature request here.
+      placeholder: This is a Mockup of the design how I imagine it <screenshot>

.github/ISSUE_TEMPLATE/bug_report.md

@@ -1,36 +0,0 @@
----
-name: Bug report
-about: Create a report to help us improve
-title: ''
-labels: ''
-assignees: ''
-
----
-
-**Describe your environment**
-- GPU: [cuda/amd/mps/cpu]
-- VRAM: [if known]
-- CPU arch: [x86/arm]
-- OS: [Linux/Windows/macOS]
-- Python: [Anaconda/miniconda/miniforge/pyenv/other (explain)]
-- Branch: [if `git status` says anything other than "On branch main" paste it here]
-- Commit: [run `git show` and paste the line that starts with "Merge" here]
-
-**Describe the bug**
-A clear and concise description of what the bug is.
-
-**To Reproduce**
-Steps to reproduce the behavior:
-1. Go to '...'
-2. Click on '....'
-3. Scroll down to '....'
-4. See error
-
-**Expected behavior**
-A clear and concise description of what you expected to happen.
-
-**Screenshots**
-If applicable, add screenshots to help explain your problem.
-
-**Additional context**
-Add any other context about the problem here.

.github/ISSUE_TEMPLATE/config.yml

@@ -0,0 +1,14 @@
+blank_issues_enabled: false
+contact_links:
+  - name: Project-Documentation
+    url: https://invoke-ai.github.io/InvokeAI/
+    about: Should be your first place to go when looking for manuals/FAQs regarding our InvokeAI Toolkit
+  - name: Discord
+    url: https://discord.gg/ZmtBAhwWhy
+    about: Our Discord Community could maybe help you out via live-chat
+  - name: GitHub Community Support
+    url: https://github.com/orgs/community/discussions
+    about: Please ask and answer questions regarding the GitHub Platform here.
+  - name: GitHub Security Bug Bounty
+    url: https://bounty.github.com/
+    about: Please report security vulnerabilities of the GitHub Platform here.

.github/ISSUE_TEMPLATE/feature_request.md

@@ -1,20 +0,0 @@
----
-name: Feature request
-about: Suggest an idea for this project
-title: ''
-labels: ''
-assignees: ''
-
----
-
-**Is your feature request related to a problem? Please describe.**
-A clear and concise description of what the problem is. Ex. I'm always frustrated when [...]
-
-**Describe the solution you'd like**
-A clear and concise description of what you want to happen.
-
-**Describe alternatives you've considered**
-A clear and concise description of any alternative solutions or features you've considered.
-
-**Additional context**
-Add any other context or screenshots about the feature request here.

.github/stale.yaml

@@ -0,0 +1,19 @@
+# Number of days of inactivity before an issue becomes stale
+daysUntilStale: 28
+# Number of days of inactivity before a stale issue is closed
+daysUntilClose: 14
+# Issues with these labels will never be considered stale
+exemptLabels:
+  - pinned
+  - security
+# Label to use when marking an issue as stale
+staleLabel: stale
+# Comment to post when marking an issue as stale. Set to `false` to disable
+markComment: >
+  This issue has been automatically marked as stale because it has not had
+  recent activity. It will be closed if no further activity occurs. Please
+  update the ticket if this is still a problem on the latest release.
+# Comment to post when closing a stale issue. Set to `false` to disable
+closeComment: >
+  Due to inactivity, this issue has been automatically closed. If this is
+  still a problem on the latest release, please recreate the issue.

.github/workflows/build-container.yml

@@ -1,42 +1,114 @@
-# Building the Image without pushing to confirm it is still buildable
-# confirum functionality would unfortunately need way more resources
 name: build container image
 on:
   push:
     branches:
       - 'main'
-      - 'development'
-  pull_request:
-    branches:
-      - 'main'
-      - 'development'
+      - 'update/ci/docker/*'
+      - 'update/docker/*'
+      - 'dev/ci/docker/*'
+      - 'dev/docker/*'
+    paths:
+      - 'pyproject.toml'
+      - '.dockerignore'
+      - 'invokeai/**'
+      - 'docker/Dockerfile'
+    tags:
+      - 'v*.*.*'
+  workflow_dispatch:
+
+permissions:
+  contents: write
+  packages: write
 
 jobs:
   docker:
+    if: github.event.pull_request.draft == false
+    strategy:
+      fail-fast: false
+      matrix:
+        flavor:
+          - rocm
+          - cuda
+          - cpu
+        include:
+          - flavor: rocm
+            pip-extra-index-url: 'https://download.pytorch.org/whl/rocm5.2'
+          - flavor: cuda
+            pip-extra-index-url: ''
+          - flavor: cpu
+            pip-extra-index-url: 'https://download.pytorch.org/whl/cpu'
     runs-on: ubuntu-latest
+    name: ${{ matrix.flavor }}
+    env:
+      PLATFORMS: 'linux/amd64,linux/arm64'
+      DOCKERFILE: 'docker/Dockerfile'
     steps:
-      - name: prepare docker-tag
-        env:
-          repository: ${{ github.repository }}
-        run: echo "dockertag=${repository,,}" >> $GITHUB_ENV
       - name: Checkout
         uses: actions/checkout@v3
+
+      - name: Docker meta
+        id: meta
+        uses: docker/metadata-action@v4
+        with:
+          github-token: ${{ secrets.GITHUB_TOKEN }}
+          images: |
+            ghcr.io/${{ github.repository }}
+            ${{ vars.DOCKERHUB_REPOSITORY }}
+          tags: |
+            type=ref,event=branch
+            type=ref,event=tag
+            type=pep440,pattern={{version}}
+            type=pep440,pattern={{major}}.{{minor}}
+            type=pep440,pattern={{major}}
+            type=sha,enable=true,prefix=sha-,format=short
+          flavor: |
+            latest=${{ matrix.flavor == 'cuda' && github.ref == 'refs/heads/main' }}
+            suffix=-${{ matrix.flavor }},onlatest=false
+
       - name: Set up QEMU
         uses: docker/setup-qemu-action@v2
+
       - name: Set up Docker Buildx
         uses: docker/setup-buildx-action@v2
-      - name: Cache Docker layers
-        uses: actions/cache@v2
         with:
-          path: /tmp/.buildx-cache
-          key: buildx-${{ hashFiles('docker-build/Dockerfile') }}
+          platforms: ${{ env.PLATFORMS }}
+
+      - name: Login to GitHub Container Registry
+        if: github.event_name != 'pull_request'
+        uses: docker/login-action@v2
+        with:
+          registry: ghcr.io
+          username: ${{ github.repository_owner }}
+          password: ${{ secrets.GITHUB_TOKEN }}
+
+      - name: Login to Docker Hub
+        if: github.event_name != 'pull_request' && vars.DOCKERHUB_REPOSITORY != ''
+        uses: docker/login-action@v2
+        with:
+          username: ${{ secrets.DOCKERHUB_USERNAME }}
+          password: ${{ secrets.DOCKERHUB_TOKEN }}
+
       - name: Build container
-        uses: docker/build-push-action@v3
+        id: docker_build
+        uses: docker/build-push-action@v4
         with:
           context: .
-          file: docker-build/Dockerfile
-          platforms: linux/amd64
-          push: false
-          tags: ${{ env.dockertag }}:latest
-          cache-from: type=local,src=/tmp/.buildx-cache
-          cache-to: type=local,dest=/tmp/.buildx-cache
+          file: ${{ env.DOCKERFILE }}
+          platforms: ${{ env.PLATFORMS }}
+          push: ${{ github.ref == 'refs/heads/main' || github.ref_type == 'tag' }}
+          tags: ${{ steps.meta.outputs.tags }}
+          labels: ${{ steps.meta.outputs.labels }}
+          build-args: PIP_EXTRA_INDEX_URL=${{ matrix.pip-extra-index-url }}
+          cache-from: |
+            type=gha,scope=${{ github.ref_name }}-${{ matrix.flavor }}
+            type=gha,scope=main-${{ matrix.flavor }}
+          cache-to: type=gha,mode=max,scope=${{ github.ref_name }}-${{ matrix.flavor }}
+
+      - name: Docker Hub Description
+        if: github.ref == 'refs/heads/main' || github.ref == 'refs/tags/*' && vars.DOCKERHUB_REPOSITORY != ''
+        uses: peter-evans/dockerhub-description@v3
+        with:
+          username: ${{ secrets.DOCKERHUB_USERNAME }}
+          password: ${{ secrets.DOCKERHUB_TOKEN }}
+          repository: ${{ vars.DOCKERHUB_REPOSITORY }}
+          short-description: ${{ github.event.repository.description }}

.github/workflows/clean-caches.yml

@@ -0,0 +1,34 @@
+name: cleanup caches by a branch
+on:
+  pull_request:
+    types:
+      - closed
+  workflow_dispatch:
+
+jobs:
+  cleanup:
+    runs-on: ubuntu-latest
+    steps:
+      - name: Check out code
+        uses: actions/checkout@v3
+
+      - name: Cleanup
+        run: |
+          gh extension install actions/gh-actions-cache
+
+          REPO=${{ github.repository }}
+          BRANCH=${{ github.ref }}
+
+          echo "Fetching list of cache key"
+          cacheKeysForPR=$(gh actions-cache list -R $REPO -B $BRANCH | cut -f 1 )
+
+          ## Setting this to not fail the workflow while deleting cache keys.
+          set +e
+          echo "Deleting caches..."
+          for cacheKey in $cacheKeysForPR
+          do
+              gh actions-cache delete $cacheKey -R $REPO -B $BRANCH --confirm
+          done
+          echo "Done"
+        env:
+          GH_TOKEN: ${{ secrets.GITHUB_TOKEN }}

.github/workflows/close-inactive-issues.yml

@@ -0,0 +1,27 @@
+name: Close inactive issues
+on:
+  schedule:
+    - cron: "00 6 * * *"
+
+env:
+  DAYS_BEFORE_ISSUE_STALE: 14
+  DAYS_BEFORE_ISSUE_CLOSE: 28
+
+jobs:
+  close-issues:
+    runs-on: ubuntu-latest
+    permissions:
+      issues: write
+      pull-requests: write
+    steps:
+      - uses: actions/stale@v5
+        with:
+          days-before-issue-stale: ${{ env.DAYS_BEFORE_ISSUE_STALE }}
+          days-before-issue-close: ${{ env.DAYS_BEFORE_ISSUE_CLOSE }}
+          stale-issue-label: "Inactive Issue"
+          stale-issue-message: "There has been no activity in this issue for ${{ env.DAYS_BEFORE_ISSUE_STALE }} days. If this issue is still being experienced, please reply with an updated confirmation that the issue is still being experienced with the latest release."
+          close-issue-message: "Due to inactivity, this issue was automatically closed. If you are still experiencing the issue, please recreate the issue."
+          days-before-pr-stale: -1
+          days-before-pr-close: -1
+          repo-token: ${{ secrets.GITHUB_TOKEN }}
+          operations-per-run: 500

.github/workflows/create-caches.yml

@@ -1,80 +0,0 @@
-name: Create Caches
-
-on: workflow_dispatch
-
-jobs:
-  os_matrix:
-    strategy:
-      matrix:
-        os: [ubuntu-latest, macos-latest]
-        include:
-          - os: ubuntu-latest
-            environment-file: environment.yml
-            default-shell: bash -l {0}
-          - os: macos-latest
-            environment-file: environment-mac.yml
-            default-shell: bash -l {0}
-    name: Test invoke.py on ${{ matrix.os }} with conda
-    runs-on: ${{ matrix.os }}
-    defaults:
-      run:
-        shell: ${{ matrix.default-shell }}
-    steps:
-      - name: Checkout sources
-        uses: actions/checkout@v3
-
-      - name: setup miniconda
-        uses: conda-incubator/setup-miniconda@v2
-        with:
-          auto-activate-base: false
-          auto-update-conda: false
-          miniconda-version: latest
-
-      - name: set environment
-        run: |
-          [[ "$GITHUB_REF" == 'refs/heads/main' ]] \
-            && echo "TEST_PROMPTS=tests/preflight_prompts.txt" >> $GITHUB_ENV \
-            || echo "TEST_PROMPTS=tests/dev_prompts.txt" >> $GITHUB_ENV
-          echo "CONDA_ROOT=$CONDA" >> $GITHUB_ENV
-          echo "CONDA_ENV_NAME=invokeai" >> $GITHUB_ENV
-
-      - name: Use Cached Stable Diffusion v1.4 Model
-        id: cache-sd-v1-4
-        uses: actions/cache@v3
-        env:
-          cache-name: cache-sd-v1-4
-        with:
-          path: models/ldm/stable-diffusion-v1/model.ckpt
-          key: ${{ env.cache-name }}
-          restore-keys: ${{ env.cache-name }}
-
-      - name: Download Stable Diffusion v1.4 Model
-        if: ${{ steps.cache-sd-v1-4.outputs.cache-hit != 'true' }}
-        run: |
-          [[ -d models/ldm/stable-diffusion-v1 ]] \
-            || mkdir -p models/ldm/stable-diffusion-v1
-          [[ -r models/ldm/stable-diffusion-v1/model.ckpt ]] \
-            || curl \
-              -H "Authorization: Bearer ${{ secrets.HUGGINGFACE_TOKEN }}" \
-              -o models/ldm/stable-diffusion-v1/model.ckpt \
-              -L https://huggingface.co/CompVis/stable-diffusion-v-1-4-original/resolve/main/sd-v1-4.ckpt
-
-      - name: Activate Conda Env
-        uses: conda-incubator/setup-miniconda@v2
-        with:
-          activate-environment: ${{ env.CONDA_ENV_NAME }}
-          environment-file: ${{ matrix.environment-file }}
-
-      - name: Use Cached Huggingface and Torch models
-        id: cache-hugginface-torch
-        uses: actions/cache@v3
-        env:
-          cache-name: cache-hugginface-torch
-        with:
-          path: ~/.cache
-          key: ${{ env.cache-name }}
-          restore-keys: |
-            ${{ env.cache-name }}-${{ hashFiles('scripts/preload_models.py') }}
-
-      - name: run preload_models.py
-        run: python scripts/preload_models.py

.github/workflows/lint-frontend.yml

@@ -0,0 +1,37 @@
+name: Lint frontend
+
+on:
+  pull_request:
+    paths:
+      - 'invokeai/frontend/web/**'
+    types:
+      - 'ready_for_review'
+      - 'opened'
+      - 'synchronize'
+  push:
+    branches:
+      - 'main'
+    paths:
+      - 'invokeai/frontend/web/**'
+  merge_group:
+  workflow_dispatch:
+
+defaults:
+  run:
+    working-directory: invokeai/frontend/web
+
+jobs:
+  lint-frontend:
+    if: github.event.pull_request.draft == false
+    runs-on: ubuntu-22.04
+    steps:
+      - name: Setup Node 18
+        uses: actions/setup-node@v3
+        with:
+          node-version: '18'
+      - uses: actions/checkout@v3
+      - run: 'yarn install --frozen-lockfile'
+      - run: 'yarn run lint:tsc'
+      - run: 'yarn run lint:madge'
+      - run: 'yarn run lint:eslint'
+      - run: 'yarn run lint:prettier'

.github/workflows/mkdocs-flow.yml

@@ -1,28 +0,0 @@
-name: Deploy
-on:
-  push:
-    branches:
-      - main
-  # pull_request:
-  #   branches:
-  #     - main
-jobs:
-  build:
-    name: Deploy docs to GitHub Pages
-    runs-on: ubuntu-latest
-    steps:
-      - name: Checkout
-        uses: actions/checkout@v3
-        with:
-          fetch-depth: 0
-      - name: Build
-        uses: Tiryoh/actions-mkdocs@v0
-        with:
-          mkdocs_version: 'latest' # option
-          requirements: '/requirements-mkdocs.txt' # option
-          configfile: '/mkdocs.yml' # option
-      - name: Deploy
-        uses: peaceiris/actions-gh-pages@v3
-        with:
-          github_token: ${{ secrets.GITHUB_TOKEN }}
-          publish_dir: ./site

.github/workflows/mkdocs-material.yml

@@ -5,8 +5,12 @@ on:
       - 'main'
       - 'development'
 
+permissions:
+    contents: write
+
 jobs:
   mkdocs-material:
+    if: github.event.pull_request.draft == false
     runs-on: ubuntu-latest
     steps:
       - name: checkout sources
@@ -22,7 +26,7 @@ jobs:
       - name: install requirements
         run: |
           python -m \
-            pip install -r requirements-mkdocs.txt
+            pip install -r docs/requirements-mkdocs.txt
 
       - name: confirm buildability
         run: |

.github/workflows/pyflakes.yml

@@ -0,0 +1,20 @@
+on:
+  pull_request:
+  push:
+    branches:
+      - main
+      - development
+      - 'release-candidate-*'
+
+jobs:
+  pyflakes:
+    name: runner / pyflakes
+    if: github.event.pull_request.draft == false
+    runs-on: ubuntu-latest
+    steps:
+      - uses: actions/checkout@v2
+      - name: pyflakes
+        uses: reviewdog/action-pyflakes@v1
+        with:
+          github_token: ${{ secrets.GITHUB_TOKEN }}
+          reporter: github-pr-review

.github/workflows/pypi-release.yml

@@ -0,0 +1,41 @@
+name: PyPI Release
+
+on:
+  push:
+    paths:
+      - 'invokeai/version/invokeai_version.py'
+  workflow_dispatch:
+
+jobs:
+  release:
+    if: github.repository == 'invoke-ai/InvokeAI'
+    runs-on: ubuntu-22.04
+    env:
+      TWINE_USERNAME: __token__
+      TWINE_PASSWORD: ${{ secrets.PYPI_API_TOKEN }}
+      TWINE_NON_INTERACTIVE: 1
+    steps:
+      - name: checkout sources
+        uses: actions/checkout@v3
+
+      - name: install deps
+        run: pip install --upgrade build twine
+
+      - name: build package
+        run: python3 -m build
+
+      - name: check distribution
+        run: twine check dist/*
+
+      - name: check PyPI versions
+        if: github.ref == 'refs/heads/main' || github.ref == 'refs/heads/v2.3'
+        run: |
+          pip install --upgrade requests
+          python -c "\
+          import scripts.pypi_helper; \
+          EXISTS=scripts.pypi_helper.local_on_pypi(); \
+          print(f'PACKAGE_EXISTS={EXISTS}')" >> $GITHUB_ENV
+
+      - name: upload package
+        if: env.PACKAGE_EXISTS == 'False' && env.TWINE_PASSWORD != ''
+        run: twine upload dist/*

.github/workflows/test-invoke-conda.yml

@@ -1,109 +0,0 @@
-name: Test invoke.py
-on:
-  push:
-    branches:
-      - 'main'
-      - 'development'
-  pull_request:
-    branches:
-      - 'main'
-      - 'development'
-
-jobs:
-  matrix:
-    strategy:
-      fail-fast: false
-      matrix:
-        stable-diffusion-model:
-          - 'https://huggingface.co/CompVis/stable-diffusion-v-1-4-original/resolve/main/sd-v1-4.ckpt'
-          - 'https://huggingface.co/runwayml/stable-diffusion-v1-5/resolve/main/v1-5-pruned-emaonly.ckpt'
-        os:
-          - ubuntu-latest
-          - macOS-12
-        include:
-          - os: ubuntu-latest
-            environment-file: environment.yml
-            default-shell: bash -l {0}
-          - os: macOS-12
-            environment-file: environment-mac.yml
-            default-shell: bash -l {0}
-          - stable-diffusion-model: https://huggingface.co/CompVis/stable-diffusion-v-1-4-original/resolve/main/sd-v1-4.ckpt
-            stable-diffusion-model-dl-path: models/ldm/stable-diffusion-v1/model.ckpt
-            stable-diffusion-model-switch: stable-diffusion-1.4
-          - stable-diffusion-model: https://huggingface.co/runwayml/stable-diffusion-v1-5/resolve/main/v1-5-pruned-emaonly.ckpt
-            stable-diffusion-model-dl-path: models/ldm/stable-diffusion-v1/v1-5-pruned-emaonly.ckpt
-            stable-diffusion-model-switch: stable-diffusion-1.5
-    name: ${{ matrix.os }} with ${{ matrix.stable-diffusion-model-switch }}
-    runs-on: ${{ matrix.os }}
-    env:
-      CONDA_ENV_NAME: invokeai
-    defaults:
-      run:
-        shell: ${{ matrix.default-shell }}
-    steps:
-      - name: Checkout sources
-        id: checkout-sources
-        uses: actions/checkout@v3
-
-      - name: Use cached conda packages
-        id: use-cached-conda-packages
-        uses: actions/cache@v3
-        with:
-          path: ~/conda_pkgs_dir
-          key: conda-pkgs-${{ runner.os }}-${{ runner.arch }}-${{ hashFiles(matrix.environment-file) }}
-
-      - name: Activate Conda Env
-        id: activate-conda-env
-        uses: conda-incubator/setup-miniconda@v2
-        with:
-          activate-environment: ${{ env.CONDA_ENV_NAME }}
-          environment-file: ${{ matrix.environment-file }}
-          miniconda-version: latest
-
-      - name: set test prompt to main branch validation
-        if: ${{ github.ref == 'refs/heads/main' }}
-        run: echo "TEST_PROMPTS=tests/preflight_prompts.txt" >> $GITHUB_ENV
-
-      - name: set test prompt to development branch validation
-        if: ${{ github.ref == 'refs/heads/development' }}
-        run: echo "TEST_PROMPTS=tests/dev_prompts.txt" >> $GITHUB_ENV
-
-      - name: set test prompt to Pull Request validation
-        if: ${{ github.ref != 'refs/heads/main' && github.ref != 'refs/heads/development' }}
-        run: echo "TEST_PROMPTS=tests/validate_pr_prompt.txt" >> $GITHUB_ENV
-
-      - name: Download ${{ matrix.stable-diffusion-model-switch }}
-        id: download-stable-diffusion-model
-        run: |
-          [[ -d models/ldm/stable-diffusion-v1 ]] \
-            || mkdir -p models/ldm/stable-diffusion-v1
-          curl \
-            -H "Authorization: Bearer ${{ secrets.HUGGINGFACE_TOKEN }}" \
-            -o ${{ matrix.stable-diffusion-model-dl-path }} \
-            -L ${{ matrix.stable-diffusion-model }}
-
-      - name: run preload_models.py
-        id: run-preload-models
-        run: |
-          python scripts/preload_models.py \
-            --no-interactive
-
-      - name: Run the tests
-        id: run-tests
-        run: |
-          time python scripts/invoke.py \
-            --model ${{ matrix.stable-diffusion-model-switch }} \
-            --from_file ${{ env.TEST_PROMPTS }}
-
-      - name: export conda env
-        id: export-conda-env
-        run: |
-          mkdir -p outputs/img-samples
-          conda env export --name ${{ env.CONDA_ENV_NAME }} > outputs/img-samples/environment-${{ runner.os }}-${{ runner.arch }}.yml
-
-      - name: Archive results
-        id: archive-results
-        uses: actions/upload-artifact@v3
-        with:
-          name: results_${{ matrix.os }}_${{ matrix.stable-diffusion-model-switch }}
-          path: outputs/img-samples

.github/workflows/test-invoke-pip-skip.yml

@@ -0,0 +1,66 @@
+name: Test invoke.py pip
+on:
+  pull_request:
+    paths:
+      - '**'
+      - '!pyproject.toml'
+      - '!invokeai/**'
+      - 'invokeai/frontend/web/**'
+  merge_group:
+  workflow_dispatch:
+
+concurrency:
+  group: ${{ github.workflow }}-${{ github.head_ref || github.run_id }}
+  cancel-in-progress: true
+
+jobs:
+  matrix:
+    if: github.event.pull_request.draft == false
+    strategy:
+      matrix:
+        python-version:
+          # - '3.9'
+          - '3.10'
+        pytorch:
+          # - linux-cuda-11_6
+          - linux-cuda-11_7
+          - linux-rocm-5_2
+          - linux-cpu
+          - macos-default
+          - windows-cpu
+          # - windows-cuda-11_6
+          # - windows-cuda-11_7
+        include:
+          # - pytorch: linux-cuda-11_6
+          #   os: ubuntu-22.04
+          #   extra-index-url: 'https://download.pytorch.org/whl/cu116'
+          #   github-env: $GITHUB_ENV
+          - pytorch: linux-cuda-11_7
+            os: ubuntu-22.04
+            github-env: $GITHUB_ENV
+          - pytorch: linux-rocm-5_2
+            os: ubuntu-22.04
+            extra-index-url: 'https://download.pytorch.org/whl/rocm5.2'
+            github-env: $GITHUB_ENV
+          - pytorch: linux-cpu
+            os: ubuntu-22.04
+            extra-index-url: 'https://download.pytorch.org/whl/cpu'
+            github-env: $GITHUB_ENV
+          - pytorch: macos-default
+            os: macOS-12
+            github-env: $GITHUB_ENV
+          - pytorch: windows-cpu
+            os: windows-2022
+            github-env: $env:GITHUB_ENV
+          # - pytorch: windows-cuda-11_6
+          #   os: windows-2022
+          #   extra-index-url: 'https://download.pytorch.org/whl/cu116'
+          #   github-env: $env:GITHUB_ENV
+          # - pytorch: windows-cuda-11_7
+          #   os: windows-2022
+          #   extra-index-url: 'https://download.pytorch.org/whl/cu117'
+          #   github-env: $env:GITHUB_ENV
+    name: ${{ matrix.pytorch }} on ${{ matrix.python-version }}
+    runs-on: ${{ matrix.os }}
+    steps:
+      - run: 'echo "No build required"'

.github/workflows/test-invoke-pip.yml

@@ -0,0 +1,144 @@
+name: Test invoke.py pip
+on:
+  push:
+    branches:
+      - 'main'
+    paths:
+      - 'pyproject.toml'
+      - 'invokeai/**'
+      - '!invokeai/frontend/web/**'
+  pull_request:
+    paths:
+      - 'pyproject.toml'
+      - 'invokeai/**'
+      - '!invokeai/frontend/web/**'
+    types:
+      - 'ready_for_review'
+      - 'opened'
+      - 'synchronize'
+  merge_group:
+  workflow_dispatch:
+
+concurrency:
+  group: ${{ github.workflow }}-${{ github.head_ref || github.run_id }}
+  cancel-in-progress: true
+
+jobs:
+  matrix:
+    if: github.event.pull_request.draft == false
+    strategy:
+      matrix:
+        python-version:
+          # - '3.9'
+          - '3.10'
+        pytorch:
+          # - linux-cuda-11_6
+          - linux-cuda-11_7
+          - linux-rocm-5_2
+          - linux-cpu
+          - macos-default
+          - windows-cpu
+          # - windows-cuda-11_6
+          # - windows-cuda-11_7
+        include:
+          # - pytorch: linux-cuda-11_6
+          #   os: ubuntu-22.04
+          #   extra-index-url: 'https://download.pytorch.org/whl/cu116'
+          #   github-env: $GITHUB_ENV
+          - pytorch: linux-cuda-11_7
+            os: ubuntu-22.04
+            github-env: $GITHUB_ENV
+          - pytorch: linux-rocm-5_2
+            os: ubuntu-22.04
+            extra-index-url: 'https://download.pytorch.org/whl/rocm5.2'
+            github-env: $GITHUB_ENV
+          - pytorch: linux-cpu
+            os: ubuntu-22.04
+            extra-index-url: 'https://download.pytorch.org/whl/cpu'
+            github-env: $GITHUB_ENV
+          - pytorch: macos-default
+            os: macOS-12
+            github-env: $GITHUB_ENV
+          - pytorch: windows-cpu
+            os: windows-2022
+            github-env: $env:GITHUB_ENV
+          # - pytorch: windows-cuda-11_6
+          #   os: windows-2022
+          #   extra-index-url: 'https://download.pytorch.org/whl/cu116'
+          #   github-env: $env:GITHUB_ENV
+          # - pytorch: windows-cuda-11_7
+          #   os: windows-2022
+          #   extra-index-url: 'https://download.pytorch.org/whl/cu117'
+          #   github-env: $env:GITHUB_ENV
+    name: ${{ matrix.pytorch }} on ${{ matrix.python-version }}
+    runs-on: ${{ matrix.os }}
+    env:
+      PIP_USE_PEP517: '1'
+    steps:
+      - name: Checkout sources
+        id: checkout-sources
+        uses: actions/checkout@v3
+
+      - name: set test prompt to main branch validation
+        if: ${{ github.ref == 'refs/heads/main' }}
+        run: echo "TEST_PROMPTS=tests/preflight_prompts.txt" >> ${{ matrix.github-env }}
+
+      - name: set test prompt to Pull Request validation
+        if: ${{ github.ref != 'refs/heads/main' }}
+        run: echo "TEST_PROMPTS=tests/validate_pr_prompt.txt" >> ${{ matrix.github-env }}
+
+      - name: setup python
+        uses: actions/setup-python@v4
+        with:
+          python-version: ${{ matrix.python-version }}
+          cache: pip
+          cache-dependency-path: pyproject.toml
+
+      - name: install invokeai
+        env:
+          PIP_EXTRA_INDEX_URL: ${{ matrix.extra-index-url }}
+        run: >
+          pip3 install
+          --editable=".[test]"
+
+      - name: run pytest
+        id: run-pytest
+        run: pytest
+
+      - name: set INVOKEAI_OUTDIR
+        run: >
+          python -c
+          "import os;from invokeai.backend.globals import Globals;OUTDIR=os.path.join(Globals.root,str('outputs'));print(f'INVOKEAI_OUTDIR={OUTDIR}')"
+          >> ${{ matrix.github-env }}
+
+      - name: run invokeai-configure
+        id: run-preload-models
+        env:
+          HUGGING_FACE_HUB_TOKEN: ${{ secrets.HUGGINGFACE_TOKEN }}
+        run: >
+          invokeai-configure
+          --yes
+          --default_only
+          --full-precision
+        # can't use fp16 weights without a GPU
+
+      - name: run invokeai
+        id: run-invokeai
+        env:
+          # Set offline mode to make sure configure preloaded successfully.
+          HF_HUB_OFFLINE: 1
+          HF_DATASETS_OFFLINE: 1
+          TRANSFORMERS_OFFLINE: 1
+        run: >
+          invokeai
+          --no-patchmatch
+          --no-nsfw_checker
+          --from_file ${{ env.TEST_PROMPTS }}
+          --outdir ${{ env.INVOKEAI_OUTDIR }}/${{ matrix.python-version }}/${{ matrix.pytorch }}
+
+      - name: Archive results
+        id: archive-results
+        uses: actions/upload-artifact@v3
+        with:
+          name: results
+          path: ${{ env.INVOKEAI_OUTDIR }}

.gitignore

@@ -1,11 +1,14 @@
 # ignore default image save location and model symbolic link
+.idea/
+embeddings/
 outputs/
 models/ldm/stable-diffusion-v1/model.ckpt
-ldm/invoke/restoration/codeformer/weights
+**/restoration/codeformer/weights
 
 # ignore user models config
 configs/models.user.yaml
 config/models.user.yml
+invokeai.init
 
 # ignore the Anaconda/Miniconda installer used while building Docker image
 anaconda.sh
@@ -60,16 +63,20 @@ pip-delete-this-directory.txt
 htmlcov/
 .tox/
 .nox/
+.coveragerc
 .coverage
 .coverage.*
 .cache
 nosetests.xml
 coverage.xml
+cov.xml
 *.cover
 *.py,cover
 .hypothesis/
 .pytest_cache/
+.pytest.ini
 cover/
+junit/
 
 # Translations
 *.mo
@@ -184,7 +191,7 @@ src
 **/__pycache__/
 outputs
 
-# Logs and associated folders 
+# Logs and associated folders
 # created from generated embeddings.
 logs
 testtube
@@ -193,7 +200,7 @@ checkpoints
 .DS_Store
 
 # Let the frontend manage its own gitignore
-!frontend/*
+!invokeai/frontend/web/*
 
 # Scratch folder
 .scratch/
@@ -201,11 +208,24 @@ checkpoints
 gfpgan/
 models/ldm/stable-diffusion-v1/*.sha256
 
+
 # GFPGAN model files
 gfpgan/
 
 # config file (will be created by installer)
 configs/models.yaml
 
-# weights (will be created by installer)
-models/ldm/stable-diffusion-v1/*.ckpt
+# ignore initfile
+.invokeai
+
+# ignore environment.yml and requirements.txt
+# these are links to the real files in environments-and-requirements
+environment.yml
+requirements.txt
+
+# source installer files
+installer/*zip
+installer/install.bat
+installer/install.sh
+installer/update.bat
+installer/update.sh

CODE_OF_CONDUCT.md

@@ -0,0 +1,128 @@
+# Contributor Covenant Code of Conduct
+
+## Our Pledge
+
+We as members, contributors, and leaders pledge to make participation in our
+community a harassment-free experience for everyone, regardless of age, body
+size, visible or invisible disability, ethnicity, sex characteristics, gender
+identity and expression, level of experience, education, socio-economic status,
+nationality, personal appearance, race, religion, or sexual identity
+and orientation.
+
+We pledge to act and interact in ways that contribute to an open, welcoming,
+diverse, inclusive, and healthy community.
+
+## Our Standards
+
+Examples of behavior that contributes to a positive environment for our
+community include:
+
+* Demonstrating empathy and kindness toward other people
+* Being respectful of differing opinions, viewpoints, and experiences
+* Giving and gracefully accepting constructive feedback
+* Accepting responsibility and apologizing to those affected by our mistakes,
+  and learning from the experience
+* Focusing on what is best not just for us as individuals, but for the
+  overall community
+
+Examples of unacceptable behavior include:
+
+* The use of sexualized language or imagery, and sexual attention or
+  advances of any kind
+* Trolling, insulting or derogatory comments, and personal or political attacks
+* Public or private harassment
+* Publishing others' private information, such as a physical or email
+  address, without their explicit permission
+* Other conduct which could reasonably be considered inappropriate in a
+  professional setting
+
+## Enforcement Responsibilities
+
+Community leaders are responsible for clarifying and enforcing our standards of
+acceptable behavior and will take appropriate and fair corrective action in
+response to any behavior that they deem inappropriate, threatening, offensive,
+or harmful.
+
+Community leaders have the right and responsibility to remove, edit, or reject
+comments, commits, code, wiki edits, issues, and other contributions that are
+not aligned to this Code of Conduct, and will communicate reasons for moderation
+decisions when appropriate.
+
+## Scope
+
+This Code of Conduct applies within all community spaces, and also applies when
+an individual is officially representing the community in public spaces.
+Examples of representing our community include using an official e-mail address,
+posting via an official social media account, or acting as an appointed
+representative at an online or offline event.
+
+## Enforcement
+
+Instances of abusive, harassing, or otherwise unacceptable behavior
+may be reported to the community leaders responsible for enforcement
+at https://github.com/invoke-ai/InvokeAI/issues.  All complaints will
+be reviewed and investigated promptly and fairly.
+
+All community leaders are obligated to respect the privacy and security of the
+reporter of any incident.
+
+## Enforcement Guidelines
+
+Community leaders will follow these Community Impact Guidelines in determining
+the consequences for any action they deem in violation of this Code of Conduct:
+
+### 1. Correction
+
+**Community Impact**: Use of inappropriate language or other behavior deemed
+unprofessional or unwelcome in the community.
+
+**Consequence**: A private, written warning from community leaders, providing
+clarity around the nature of the violation and an explanation of why the
+behavior was inappropriate. A public apology may be requested.
+
+### 2. Warning
+
+**Community Impact**: A violation through a single incident or series
+of actions.
+
+**Consequence**: A warning with consequences for continued behavior. No
+interaction with the people involved, including unsolicited interaction with
+those enforcing the Code of Conduct, for a specified period of time. This
+includes avoiding interactions in community spaces as well as external channels
+like social media. Violating these terms may lead to a temporary or
+permanent ban.
+
+### 3. Temporary Ban
+
+**Community Impact**: A serious violation of community standards, including
+sustained inappropriate behavior.
+
+**Consequence**: A temporary ban from any sort of interaction or public
+communication with the community for a specified period of time. No public or
+private interaction with the people involved, including unsolicited interaction
+with those enforcing the Code of Conduct, is allowed during this period.
+Violating these terms may lead to a permanent ban.
+
+### 4. Permanent Ban
+
+**Community Impact**: Demonstrating a pattern of violation of community
+standards, including sustained inappropriate behavior,  harassment of an
+individual, or aggression toward or disparagement of classes of individuals.
+
+**Consequence**: A permanent ban from any sort of public interaction within
+the community.
+
+## Attribution
+
+This Code of Conduct is adapted from the [Contributor Covenant][homepage],
+version 2.0, available at
+https://www.contributor-covenant.org/version/2/0/code_of_conduct.html.
+
+Community Impact Guidelines were inspired by [Mozilla's code of conduct
+enforcement ladder](https://github.com/mozilla/diversity).
+
+[homepage]: https://www.contributor-covenant.org
+
+For answers to common questions about this code of conduct, see the FAQ at
+https://www.contributor-covenant.org/faq. Translations are available at
+https://www.contributor-covenant.org/translations.

InvokeAI_Statement_of_Values.md

@@ -0,0 +1,84 @@
+<img src="docs/assets/invoke_ai_banner.png" align="center">
+
+Invoke-AI is a community of software developers, researchers, and user
+interface experts who have come together on a voluntary basis to build
+software tools which support cutting edge AI text-to-image
+applications. This community is open to anyone who wishes to
+contribute to the effort and has the skill and time to do so.
+
+# Our Values
+
+The InvokeAI team is a diverse community which includes individuals
+from various parts of the world and many walks of life. Despite our
+differences, we share a number of core values which we ask prospective
+contributors to understand and respect. We believe:
+
+1. That Open Source Software is a positive force in the world. We
+create software that can be used, reused, and redistributed, without
+restrictions, under a straightforward Open Source license (MIT). We
+believe that Open Source benefits society as a whole by increasing the
+availability of high quality software to all.
+
+2. That those who create software should receive proper attribution
+for their creative work. While we support the exchange and reuse of
+Open Source Software, we feel strongly that the original authors of a
+piece of code should receive credit for their contribution, and we
+endeavor to do so whenever possible.
+
+3. That there is moral ambiguity surrounding AI-assisted art. We are
+aware of the moral and ethical issues surrounding the release of the
+Stable Diffusion model and similar products. We are aware that, due to
+the composition of their training sets, current AI-generated image
+models are biased against certain ethnic groups, cultural concepts of
+beauty, ethnic stereotypes, and gender roles.
+
+      1. We recognize the potential for harm to these groups that these biases
+       represent and trust that future AI models will take steps towards
+       reducing or eliminating the biases noted above, respect and give due
+       credit to the artists whose work is sourced, and call on developers
+       and users to favor these models over the older ones as they become
+       available.
+
+4. We are deeply committed to ensuring that this technology benefits
+everyone, including artists. We see AI art not as a replacement for
+the artist, but rather as a tool to empower them. With that
+in mind, we are constantly debating how to build systems that put
+artists’ needs first: tools which can be readily integrated into an
+artist’s existing workflows and practices, enhancing their work and
+helping them to push it further. Every decision we take as a team,
+which includes several artists, aims to build towards that goal.
+
+5. That artificial intelligence can be a force for good in the world,
+but must be used responsibly. Artificial intelligence technologies
+have the potential to improve society, in everything from cancer care,
+to customer service, to creative writing.
+
+     1. While we do not believe that software should arbitrarily limit what
+     users can do with it, we recognize that when used irresponsibly, AI
+     has the potential to do much harm. Our Discord server is actively
+     moderated in order to minimize the potential of harm from
+     user-contributed images. In addition, we ask users of our software to
+     refrain from using it in any way that would cause mental, emotional or
+     physical harm to individuals and vulnerable populations including (but
+     not limited to) women; minors; ethnic minorities; religious groups;
+     members of LGBTQIA communities; and people with disabilities or
+     impairments.
+
+     2. Note that some of the image generation AI models which the Invoke-AI
+     toolkit supports carry licensing agreements which impose restrictions
+     on how the model is used. We ask that our users read and agree to
+     these terms if they wish to make use of these models. These agreements
+     are distinct from the MIT license which applies to the InvokeAI
+     software and source code.
+
+6. That mutual respect is key to a healthy software development
+community. Members of the InvokeAI community are expected to treat
+each other with respect, beneficence, and empathy. Each of us has a
+different background and a unique set of skills. We strive to help
+each other grow and gain new skills, and we apportion expectations in
+a way that balances the members' time, skillset, and interest
+area. Disputes are resolved by open and honest communication.
+
+## Signature
+
+This document has been collectively crafted and approved by the current InvokeAI team members, as of 28 Nov 2022: **lstein** (Lincoln Stein), **blessedcoolant**, **hipsterusername** (Kent Keirsey), **Kyle0654** (Kyle Schouviller), **damian0815**, **mauwii** (Matthias Wild), **Netsvetaev** (Artur Netsvetaev), **psychedelicious**, **tildebyte**, **keturn**, and **ebr** (Eugene Brodsky). Although individuals within the group may hold differing views on particular details and/or their implications, we are all in agreement about its fundamental statements, as well as their significance and importance to this project moving forward.

LICENSE

@@ -1,17 +1,6 @@
 MIT License
 
-Copyright (c) 2022 Lincoln Stein and InvokeAI Organization
-
-This software is derived from a fork of the source code available from
-https://github.com/pesser/stable-diffusion and
-https://github.com/CompViz/stable-diffusion. They carry the following
-copyrights:
-
-Copyright (c) 2022 Machine Vision and Learning Group, LMU Munich
-Copyright (c) 2022 Robin Rombach and Patrick Esser and contributors
-
-Please see individual source code files for copyright and authorship
-attributions.
+Copyright (c) 2022 InvokeAI Team
 
 Permission is hereby granted, free of charge, to any person obtaining a copy
 of this software and associated documentation files (the "Software"), to deal

README.md

@@ -1,23 +1,19 @@
 <div align="center">
 
+![project logo](https://github.com/invoke-ai/InvokeAI/raw/main/docs/assets/invoke_ai_banner.png)
+
 # InvokeAI: A Stable Diffusion Toolkit
 
-_Formerly known as lstein/stable-diffusion_
-
-![project logo](docs/assets/logo.png)
-
 [![discord badge]][discord link]
 
 [![latest release badge]][latest release link] [![github stars badge]][github stars link] [![github forks badge]][github forks link]
 
-[![CI checks on main badge]][CI checks on main link] [![CI checks on dev badge]][CI checks on dev link] [![latest commit to dev badge]][latest commit to dev link]
+[![CI checks on main badge]][CI checks on main link] [![latest commit to main badge]][latest commit to main link]
 
-[![github open issues badge]][github open issues link] [![github open prs badge]][github open prs link]
+[![github open issues badge]][github open issues link] [![github open prs badge]][github open prs link] [![translation status badge]][translation status link]
 
-[CI checks on dev badge]: https://flat.badgen.net/github/checks/invoke-ai/InvokeAI/development?label=CI%20status%20on%20dev&cache=900&icon=github
-[CI checks on dev link]: https://github.com/invoke-ai/InvokeAI/actions?query=branch%3Adevelopment
 [CI checks on main badge]: https://flat.badgen.net/github/checks/invoke-ai/InvokeAI/main?label=CI%20status%20on%20main&cache=900&icon=github
-[CI checks on main link]: https://github.com/invoke-ai/InvokeAI/actions/workflows/test-invoke-conda.yml
+[CI checks on main link]:https://github.com/invoke-ai/InvokeAI/actions?query=branch%3Amain
 [discord badge]: https://flat.badgen.net/discord/members/ZmtBAhwWhy?icon=discord
 [discord link]: https://discord.gg/ZmtBAhwWhy
 [github forks badge]: https://flat.badgen.net/github/forks/invoke-ai/InvokeAI?icon=github
@@ -28,178 +24,264 @@ _Formerly known as lstein/stable-diffusion_
 [github open prs link]: https://github.com/invoke-ai/InvokeAI/pulls?q=is%3Apr+is%3Aopen
 [github stars badge]: https://flat.badgen.net/github/stars/invoke-ai/InvokeAI?icon=github
 [github stars link]: https://github.com/invoke-ai/InvokeAI/stargazers
-[latest commit to dev badge]: https://flat.badgen.net/github/last-commit/invoke-ai/InvokeAI/development?icon=github&color=yellow&label=last%20dev%20commit&cache=900
-[latest commit to dev link]: https://github.com/invoke-ai/InvokeAI/commits/development
+[latest commit to main badge]: https://flat.badgen.net/github/last-commit/invoke-ai/InvokeAI/main?icon=github&color=yellow&label=last%20dev%20commit&cache=900
+[latest commit to main link]: https://github.com/invoke-ai/InvokeAI/commits/main
 [latest release badge]: https://flat.badgen.net/github/release/invoke-ai/InvokeAI/development?icon=github
 [latest release link]: https://github.com/invoke-ai/InvokeAI/releases
+[translation status badge]: https://hosted.weblate.org/widgets/invokeai/-/svg-badge.svg
+[translation status link]: https://hosted.weblate.org/engage/invokeai/
+
 </div>
 
-This is a fork of
-[CompVis/stable-diffusion](https://github.com/CompVis/stable-diffusion),
-the open source text-to-image generator. It provides a streamlined
-process with various new features and options to aid the image
-generation process. It runs on Windows, Mac and Linux machines, with
-GPU cards with as little as 4 GB of RAM. It provides both a polished
-Web interface (see below), and an easy-to-use command-line interface.
+InvokeAI is a leading creative engine built to empower professionals and enthusiasts alike. Generate and create stunning visual media using the latest AI-driven technologies. InvokeAI offers an industry leading Web Interface, interactive Command Line Interface, and also serves as the foundation for multiple commercial products.
 
-**Quick links**: [<a href="https://discord.gg/NwVCmKwY">Discord Server</a>] [<a href="https://invoke-ai.github.io/InvokeAI/">Documentation and Tutorials</a>] [<a href="https://github.com/invoke-ai/InvokeAI/">Code and Downloads</a>] [<a href="https://github.com/invoke-ai/InvokeAI/issues">Bug Reports</a>] [<a href="https://github.com/invoke-ai/InvokeAI/discussions">Discussion, Ideas & Q&A</a>]
+**Quick links**: [[How to Install](https://invoke-ai.github.io/InvokeAI/#installation)] [<a href="https://discord.gg/ZmtBAhwWhy">Discord Server</a>] [<a href="https://invoke-ai.github.io/InvokeAI/">Documentation and Tutorials</a>] [<a href="https://github.com/invoke-ai/InvokeAI/">Code and Downloads</a>] [<a href="https://github.com/invoke-ai/InvokeAI/issues">Bug Reports</a>] [<a href="https://github.com/invoke-ai/InvokeAI/discussions">Discussion, Ideas & Q&A</a>]
 
-<div align="center"><img src="docs/assets/invoke-web-server-1.png" width=640></div>
-
-
-_Note: This fork is rapidly evolving. Please use the
+_Note: InvokeAI is rapidly evolving. Please use the
 [Issues](https://github.com/invoke-ai/InvokeAI/issues) tab to report bugs and make feature
-requests. Be sure to use the provided templates. They will help aid diagnose issues faster._
+requests. Be sure to use the provided templates. They will help us diagnose issues faster._
+
+<div align="center">
+
+![canvas preview](https://github.com/invoke-ai/InvokeAI/raw/main/docs/assets/canvas_preview.png)
+
+</div>
 
 ## Table of Contents
 
-1. [Installation](#installation)
-2. [Hardware Requirements](#hardware-requirements)
-3. [Features](#features)
-4. [Latest Changes](#latest-changes)
-5. [Troubleshooting](#troubleshooting)
-6. [Contributing](#contributing)
-7. [Contributors](#contributors)
-8. [Support](#support)
-9. [Further Reading](#further-reading)
+1. [Quick Start](#getting-started-with-invokeai)
+2. [Installation](#detailed-installation-instructions)
+3. [Hardware Requirements](#hardware-requirements)
+4. [Features](#features)
+5. [Latest Changes](#latest-changes)
+6. [Troubleshooting](#troubleshooting)
+7. [Contributing](#contributing)
+8. [Contributors](#contributors)
+9. [Support](#support)
+10. [Further Reading](#further-reading)
 
-### Installation
+## Getting Started with InvokeAI
 
-This fork is supported across multiple platforms. You can find individual installation instructions
-below.
+For full installation and upgrade instructions, please see:
+[InvokeAI Installation Overview](https://invoke-ai.github.io/InvokeAI/installation/)
 
-- #### [Linux](docs/installation/INSTALL_LINUX.md)
+### Automatic Installer (suggested for 1st time users)
 
-- #### [Windows](docs/installation/INSTALL_WINDOWS.md)
+1. Go to the bottom of the [Latest Release Page](https://github.com/invoke-ai/InvokeAI/releases/latest)
 
-- #### [Macintosh](docs/installation/INSTALL_MAC.md)
+2. Download the .zip file for your OS (Windows/macOS/Linux).
 
-### Hardware Requirements
+3. Unzip the file.
 
-#### System
+4. If you are on Windows, double-click on the `install.bat` script. On
+macOS, open a Terminal window, drag the file `install.sh` from Finder
+into the Terminal, and press return. On Linux, run `install.sh`.
 
-You wil need one of the following:
+5. You'll be asked to confirm the location of the folder in which
+to install InvokeAI and its image generation model files. Pick a
+location with at least 15 GB of free memory. More if you plan on
+installing lots of models.
+
+6. Wait while the installer does its thing. After installing the software,
+the installer will launch a script that lets you configure InvokeAI and
+select a set of starting image generation models.
+
+7. Find the folder that InvokeAI was installed into (it is not the
+same as the unpacked zip file directory!) The default location of this
+folder (if you didn't change it in step 5) is `~/invokeai` on
+Linux/Mac systems, and `C:\Users\YourName\invokeai` on Windows. This directory will contain launcher scripts named `invoke.sh` and `invoke.bat`.
+
+8. On Windows systems, double-click on the `invoke.bat` file. On
+macOS, open a Terminal window, drag `invoke.sh` from the folder into
+the Terminal, and press return. On Linux, run `invoke.sh`
+
+9. Press 2 to open the "browser-based UI", press enter/return, wait a
+minute or two for Stable Diffusion to start up, then open your browser
+and go to http://localhost:9090.
+
+10. Type `banana sushi` in the box on the top left and click `Invoke`
+
+### Command-Line Installation (for users familiar with Terminals)
+
+You must have Python 3.9 or 3.10 installed on your machine. Earlier or later versions are
+not supported.
+
+1. Open a command-line window on your machine. The PowerShell is recommended for Windows.
+2. Create a directory to install InvokeAI into. You'll need at least 15 GB of free space:
+
+    ```terminal
+    mkdir invokeai
+    ````
+
+3. Create a virtual environment named `.venv` inside this directory and activate it:
+
+    ```terminal
+    cd invokeai
+    python -m venv .venv --prompt InvokeAI
+    ```
+
+4. Activate the virtual environment (do it every time you run InvokeAI)
+
+    _For Linux/Mac users:_
+
+    ```sh
+    source .venv/bin/activate
+    ```
+
+    _For Windows users:_
+
+    ```ps
+    .venv\Scripts\activate
+    ```
+
+5. Install the InvokeAI module and its dependencies. Choose the command suited for your platform & GPU.
+
+    _For Windows/Linux with an NVIDIA GPU:_
+
+    ```terminal
+    pip install "InvokeAI[xformers]" --use-pep517 --extra-index-url https://download.pytorch.org/whl/cu117
+    ```
+
+    _For Linux with an AMD GPU:_
+
+    ```sh
+    pip install InvokeAI --use-pep517 --extra-index-url https://download.pytorch.org/whl/rocm5.4.2
+    ```
+
+    _For Macintoshes, either Intel or M1/M2:_
+
+    ```sh
+    pip install InvokeAI --use-pep517
+    ```
+
+6. Configure InvokeAI and install a starting set of image generation models (you only need to do this once):
+
+    ```terminal
+    invokeai-configure
+    ```
+
+7. Launch the web server (do it every time you run InvokeAI):
+
+    ```terminal
+    invokeai --web
+    ```
+
+8. Point your browser to http://localhost:9090 to bring up the web interface.
+9. Type `banana sushi` in the box on the top left and click `Invoke`.
+
+Be sure to activate the virtual environment each time before re-launching InvokeAI,
+using `source .venv/bin/activate` or `.venv\Scripts\activate`.
+
+### Detailed Installation Instructions
+
+This fork is supported across Linux, Windows and Macintosh. Linux
+users can use either an Nvidia-based card (with CUDA support) or an
+AMD card (using the ROCm driver). For full installation and upgrade
+instructions, please see:
+[InvokeAI Installation Overview](https://invoke-ai.github.io/InvokeAI/installation/INSTALL_SOURCE/)
+
+## Hardware Requirements
+
+InvokeAI is supported across Linux, Windows and macOS. Linux
+users can use either an Nvidia-based card (with CUDA support) or an
+AMD card (using the ROCm driver).
+
+### System
+
+You will need one of the following:
 
 - An NVIDIA-based graphics card with 4 GB or more VRAM memory.
 - An Apple computer with an M1 chip.
+- An AMD-based graphics card with 4GB or more VRAM memory. (Linux only)
 
-#### Memory
+We do not recommend the GTX 1650 or 1660 series video cards. They are
+unable to run in half-precision mode and do not have sufficient VRAM
+to render 512x512 images.
+
+### Memory
 
 - At least 12 GB Main Memory RAM.
 
-#### Disk
+### Disk
 
 - At least 12 GB of free disk space for the machine learning model, Python, and all its dependencies.
 
-**Note**
+## Features
 
-If you have a Nvidia 10xx series card (e.g. the 1080ti), please
-run the dream script in full-precision mode as shown below.
+Feature documentation can be reviewed by navigating to [the InvokeAI Documentation page](https://invoke-ai.github.io/InvokeAI/features/)
 
-Similarly, specify full-precision mode on Apple M1 hardware.
+### *Web Server & UI*
 
-Precision is auto configured based on the device. If however you encounter
-errors like 'expected type Float but found Half' or 'not implemented for Half'
-you can try starting `invoke.py` with the `--precision=float32` flag:
+InvokeAI offers a locally hosted Web Server & React Frontend, with an industry leading user experience. The Web-based UI allows for simple and intuitive workflows, and is responsive for use on mobile devices and tablets accessing the web server.
 
-```bash
-(ldm) ~/stable-diffusion$ python scripts/invoke.py --precision=float32
-```
+### *Unified Canvas*
 
-### Features
+The Unified Canvas is a fully integrated canvas implementation with support for all core generation capabilities, in/outpainting, brush tools, and more. This creative tool unlocks the capability for artists to create with AI as a creative collaborator, and can be used to augment AI-generated imagery, sketches, photography, renders, and more.
 
-#### Major Features
+### *Advanced Prompt Syntax*
 
-- [Web Server](docs/features/WEB.md)
-- [Interactive Command Line Interface](docs/features/CLI.md)
-- [Image To Image](docs/features/IMG2IMG.md)
-- [Inpainting Support](docs/features/INPAINTING.md)
-- [Outpainting Support](docs/features/OUTPAINTING.md)
-- [Upscaling, face-restoration and outpainting](docs/features/POSTPROCESS.md)
-- [Seamless Tiling](docs/features/OTHER.md#seamless-tiling)
-- [Google Colab](docs/features/OTHER.md#google-colab)
-- [Reading Prompts From File](docs/features/PROMPTS.md#reading-prompts-from-a-file)
-- [Shortcut: Reusing Seeds](docs/features/OTHER.md#shortcuts-reusing-seeds)
-- [Prompt Blending](docs/features/PROMPTS.md#prompt-blending)
-- [Thresholding and Perlin Noise Initialization Options](/docs/features/OTHER.md#thresholding-and-perlin-noise-initialization-options)
-- [Negative/Unconditioned Prompts](docs/features/PROMPTS.md#negative-and-unconditioned-prompts)
-- [Variations](docs/features/VARIATIONS.md)
-- [Personalizing Text-to-Image Generation](docs/features/TEXTUAL_INVERSION.md)
-- [Simplified API for text to image generation](docs/features/OTHER.md#simplified-api)
+InvokeAI's advanced prompt syntax allows for token weighting, cross-attention control, and prompt blending, allowing for fine-tuned tweaking of your invocations and exploration of the latent space.
 
-#### Other Features
+### *Command Line Interface*
 
-- [Creating Transparent Regions for Inpainting](docs/features/INPAINTING.md#creating-transparent-regions-for-inpainting)
-- [Preload Models](docs/features/OTHER.md#preload-models)
+For users utilizing a terminal-based environment, or who want to take advantage of CLI features, InvokeAI offers an extensive and actively supported command-line interface that provides the full suite of generation functionality available in the tool.
+
+### Other features
+
+- *Support for both ckpt and diffusers models*
+- *SD 2.0, 2.1 support*
+- *Noise Control & Tresholding*
+- *Popular Sampler Support*
+- *Upscaling & Face Restoration Tools*
+- *Embedding Manager & Support*
+- *Model Manager & Support*
+
+### Coming Soon
+
+- *Node-Based Architecture & UI*
+- And more...
 
 ### Latest Changes
 
-- v2.0.1 (13 October 2022)
-  - fix noisy images at high step count when using k* samplers
-  - dream.py script now calls invoke.py module directly rather than
-    via a new python process (which could break the environment)
+For our latest changes, view our [Release
+Notes](https://github.com/invoke-ai/InvokeAI/releases) and the
+[CHANGELOG](docs/CHANGELOG.md).
 
-- v2.0.0 (9 October 2022)
+## Troubleshooting
 
-  - `dream.py` script renamed `invoke.py`. A `dream.py` script wrapper remains
-    for backward compatibility.
-  - Completely new WebGUI - launch with `python3 scripts/invoke.py --web`
-  - Support for <a href="https://github.com/invoke-ai/InvokeAI/blob/main/docs/features/INPAINTING.md">inpainting</a> and <a href="https://github.com/invoke-ai/InvokeAI/blob/main/docs/features/OUTPAINTING.md">outpainting</a>
-  - img2img runs on all k* samplers
-  - Support for <a href="https://github.com/invoke-ai/InvokeAI/blob/main/docs/features/PROMPTS.md#negative-and-unconditioned-prompts">negative prompts</a>
-  - Support for CodeFormer face reconstruction
-  - Support for Textual Inversion on Macintoshes
-  - Support in both WebGUI and CLI for <a href="https://github.com/invoke-ai/InvokeAI/blob/main/docs/features/POSTPROCESS.md">post-processing of previously-generated images</a>
-    using facial reconstruction, ESRGAN upscaling, outcropping (similar to DALL-E infinite canvas),
-    and "embiggen" upscaling. See the `!fix` command.
-  - New `--hires` option on `invoke>` line allows <a href="https://github.com/invoke-ai/InvokeAI/blob/main/docs/features/CLI.md#this-is-an-example-of-txt2img">larger images to be created without duplicating elements</a>, at the cost of some performance.
-  - New `--perlin` and `--threshold` options allow you to add and control variation
-    during image generation (see <a href="https://github.com/invoke-ai/InvokeAI/blob/main/docs/features/OTHER.md#thresholding-and-perlin-noise-initialization-options">Thresholding and Perlin Noise Initialization</a>
-  - Extensive metadata now written into PNG files, allowing reliable regeneration of images
-    and tweaking of previous settings.
-  - Command-line completion in `invoke.py` now works on Windows, Linux and Mac platforms.
-  - Improved <a href="https://github.com/invoke-ai/InvokeAI/blob/main/docs/features/CLI.md">command-line completion behavior</a>.
-    New commands added:
-       * List command-line history with `!history`
-       * Search command-line history with `!search`
-       * Clear history with `!clear`
-  - Deprecated `--full_precision` / `-F`. Simply omit it and `invoke.py` will auto
-    configure. To switch away from auto use the new flag like `--precision=float32`.
-
-For older changelogs, please visit the **[CHANGELOG](docs/features/CHANGELOG.md)**.
-
-### Troubleshooting
-
-Please check out our **[Q&A](docs/help/TROUBLESHOOT.md)** to get solutions for common installation
+Please check out our **[Q&A](https://invoke-ai.github.io/InvokeAI/help/TROUBLESHOOT/#faq)** to get solutions for common installation
 problems and other issues.
 
-# Contributing
+## Contributing
 
 Anyone who wishes to contribute to this project, whether documentation, features, bug fixes, code
-cleanup, testing, or code reviews, is very much encouraged to do so. If you are unfamiliar with how
-to contribute to GitHub projects, here is a
-[Getting Started Guide](https://opensource.com/article/19/7/create-pull-request-github).
+cleanup, testing, or code reviews, is very much encouraged to do so.
 
-A full set of contribution guidelines, along with templates, are in progress, but for now the most
-important thing is to **make your pull request against the "development" branch**, and not against
-"main". This will help keep public breakage to a minimum and will allow you to propose more radical
-changes.
+To join, just raise your hand on the InvokeAI Discord server (#dev-chat) or the GitHub discussion board.
+
+If you'd like to help with translation, please see our [translation guide](docs/other/TRANSLATION.md).
+
+If you are unfamiliar with how
+to contribute to GitHub projects, here is a
+[Getting Started Guide](https://opensource.com/article/19/7/create-pull-request-github). A full set of contribution guidelines, along with templates, are in progress. You can **make your pull request against the "main" branch**.
+
+We hope you enjoy using our software as much as we enjoy creating it,
+and we hope that some of those of you who are reading this will elect
+to become part of our community.
+
+Welcome to InvokeAI!
 
 ### Contributors
 
 This fork is a combined effort of various people from across the world.
-[Check out the list of all these amazing people](docs/other/CONTRIBUTORS.md). We thank them for
+[Check out the list of all these amazing people](https://invoke-ai.github.io/InvokeAI/other/CONTRIBUTORS/). We thank them for
 their time, hard work and effort.
 
+Thanks to [Weblate](https://weblate.org/) for generously providing translation services to this project.
+
 ### Support
 
-For support, please use this repository's GitHub Issues tracking service. Feel free to send me an
-email if you use and like the script.
+For support, please use this repository's GitHub Issues tracking service, or join the Discord.
 
-Original portions of the software are Copyright (c) 2020
-[Lincoln D. Stein](https://github.com/lstein)
+Original portions of the software are Copyright (c) 2023 by respective contributors.
 
-### Further Reading
-
-Please see the original README for more information on this software and underlying algorithm,
-located in the file [README-CompViz.md](docs/other/README-CompViz.md).

Stable_Diffusion_v1_Model_Card.md

@@ -21,7 +21,7 @@ This model card focuses on the model associated with the Stable Diffusion model,
 
 # Uses
 
-## Direct Use 
+## Direct Use
 The model is intended for research purposes only. Possible research areas and
 tasks include
 
@@ -68,11 +68,11 @@ Using the model to generate content that is cruel to individuals is a misuse of
   considerations.
 
 ### Bias
-While the capabilities of image generation models are impressive, they can also reinforce or exacerbate social biases. 
-Stable Diffusion v1 was trained on subsets of [LAION-2B(en)](https://laion.ai/blog/laion-5b/), 
-which consists of images that are primarily limited to English descriptions. 
-Texts and images from communities and cultures that use other languages are likely to be insufficiently accounted for. 
-This affects the overall output of the model, as white and western cultures are often set as the default. Further, the 
+While the capabilities of image generation models are impressive, they can also reinforce or exacerbate social biases.
+Stable Diffusion v1 was trained on subsets of [LAION-2B(en)](https://laion.ai/blog/laion-5b/),
+which consists of images that are primarily limited to English descriptions.
+Texts and images from communities and cultures that use other languages are likely to be insufficiently accounted for.
+This affects the overall output of the model, as white and western cultures are often set as the default. Further, the
 ability of the model to generate content with non-English prompts is significantly worse than with English-language prompts.
 
 
@@ -84,7 +84,7 @@ The model developers used the following dataset for training the model:
 - LAION-2B (en) and subsets thereof (see next section)
 
 **Training Procedure**
-Stable Diffusion v1 is a latent diffusion model which combines an autoencoder with a diffusion model that is trained in the latent space of the autoencoder. During training, 
+Stable Diffusion v1 is a latent diffusion model which combines an autoencoder with a diffusion model that is trained in the latent space of the autoencoder. During training,
 
 - Images are encoded through an encoder, which turns images into latent representations. The autoencoder uses a relative downsampling factor of 8 and maps images of shape H x W x 3 to latents of shape H/f x W/f x 4
 - Text prompts are encoded through a ViT-L/14 text-encoder.
@@ -108,12 +108,12 @@ filtered to images with an original size `>= 512x512`, estimated aesthetics scor
 - **Batch:** 32 x 8 x 2 x 4 = 2048
 - **Learning rate:** warmup to 0.0001 for 10,000 steps and then kept constant
 
-## Evaluation Results 
+## Evaluation Results
 Evaluations with different classifier-free guidance scales (1.5, 2.0, 3.0, 4.0,
 5.0, 6.0, 7.0, 8.0) and 50 PLMS sampling
 steps show the relative improvements of the checkpoints:
 
-![pareto](assets/v1-variants-scores.jpg) 
+![pareto](assets/v1-variants-scores.jpg)
 
 Evaluated using 50 PLMS steps and 10000 random prompts from the COCO2017 validation set, evaluated at 512x512 resolution.  Not optimized for FID scores.
 ## Environmental Impact

backend/modules/create_cmd_parser.py

@@ -1,55 +0,0 @@
-import argparse
-import os
-from ldm.invoke.args import PRECISION_CHOICES
-
-
-def create_cmd_parser():
-    parser = argparse.ArgumentParser(description="InvokeAI web UI")
-    parser.add_argument(
-        "--host",
-        type=str,
-        help="The host to serve on",
-        default="localhost",
-    )
-    parser.add_argument("--port", type=int, help="The port to serve on", default=9090)
-    parser.add_argument(
-        "--cors",
-        nargs="*",
-        type=str,
-        help="Additional allowed origins, comma-separated",
-    )
-    parser.add_argument(
-        "--embedding_path",
-        type=str,
-        help="Path to a pre-trained embedding manager checkpoint - can only be set on command line",
-    )
-    # TODO: Can't get flask to serve images from any dir (saving to the dir does work when specified)
-    # parser.add_argument(
-    #     "--output_dir",
-    #     default="outputs/",
-    #     type=str,
-    #     help="Directory for output images",
-    # )
-    parser.add_argument(
-        "-v",
-        "--verbose",
-        action="store_true",
-        help="Enables verbose logging",
-    )
-    parser.add_argument(
-        "--precision",
-        dest="precision",
-        type=str,
-        choices=PRECISION_CHOICES,
-        metavar="PRECISION",
-        help=f'Set model precision. Defaults to auto selected based on device. Options: {", ".join(PRECISION_CHOICES)}',
-        default="auto",
-    )
-    parser.add_argument(
-        '--free_gpu_mem',
-        dest='free_gpu_mem',
-        action='store_true',
-        help='Force free gpu memory before final decoding',
-    )
-
-    return parser

backend/modules/parameters.py

@@ -1,69 +0,0 @@
-from backend.modules.parse_seed_weights import parse_seed_weights
-import argparse
-
-SAMPLER_CHOICES = [
-    "ddim",
-    "k_dpm_2_a",
-    "k_dpm_2",
-    "k_euler_a",
-    "k_euler",
-    "k_heun",
-    "k_lms",
-    "plms",
-]
-
-
-def parameters_to_command(params):
-    """
-    Converts dict of parameters into a `invoke.py` REPL command.
-    """
-
-    switches = list()
-
-    if "prompt" in params:
-        switches.append(f'"{params["prompt"]}"')
-    if "steps" in params:
-        switches.append(f'-s {params["steps"]}')
-    if "seed" in params:
-        switches.append(f'-S {params["seed"]}')
-    if "width" in params:
-        switches.append(f'-W {params["width"]}')
-    if "height" in params:
-        switches.append(f'-H {params["height"]}')
-    if "cfg_scale" in params:
-        switches.append(f'-C {params["cfg_scale"]}')
-    if "sampler_name" in params:
-        switches.append(f'-A {params["sampler_name"]}')
-    if "seamless" in params and params["seamless"] == True:
-        switches.append(f"--seamless")
-    if "hires_fix" in params and params["hires_fix"] == True:
-        switches.append(f"--hires")
-    if "init_img" in params and len(params["init_img"]) > 0:
-        switches.append(f'-I {params["init_img"]}')
-    if "init_mask" in params and len(params["init_mask"]) > 0:
-        switches.append(f'-M {params["init_mask"]}')
-    if "init_color" in params and len(params["init_color"]) > 0:
-        switches.append(f'--init_color {params["init_color"]}')
-    if "strength" in params and "init_img" in params:
-        switches.append(f'-f {params["strength"]}')
-        if "fit" in params and params["fit"] == True:
-            switches.append(f"--fit")
-    if "facetool" in params:
-        switches.append(f'-ft {params["facetool"]}')
-    if "facetool_strength" in params and params["facetool_strength"]:
-        switches.append(f'-G {params["facetool_strength"]}')
-    elif "gfpgan_strength" in params and params["gfpgan_strength"]:
-        switches.append(f'-G {params["gfpgan_strength"]}')
-    if "codeformer_fidelity" in params:
-        switches.append(f'-cf {params["codeformer_fidelity"]}')
-    if "upscale" in params and params["upscale"]:
-        switches.append(f'-U {params["upscale"][0]} {params["upscale"][1]}')
-    if "variation_amount" in params and params["variation_amount"] > 0:
-        switches.append(f'-v {params["variation_amount"]}')
-        if "with_variations" in params:
-            seed_weight_pairs = ",".join(
-                f"{seed}:{weight}" for seed, weight in params["with_variations"]
-            )
-            switches.append(f"-V {seed_weight_pairs}")
-
-    return " ".join(switches)

binary_installer/install.bat.in

@@ -0,0 +1,164 @@
+@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

@@ -0,0 +1,235 @@
+#!/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

@@ -0,0 +1,36 @@
+@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

@@ -0,0 +1,46 @@
+#!/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

@@ -0,0 +1,17 @@
+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

@@ -0,0 +1,33 @@
+--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

configs/models.yaml

@@ -1,36 +0,0 @@
-# This file describes the alternative machine learning models
-# available to InvokeAI script.
-#
-# To add a new model, follow the examples below. Each
-# model requires a model config file, a weights file,
-# and the width and height of the images it
-# was trained on.
-stable-diffusion-1.4:
-  config: ./configs/stable-diffusion/v1-inference.yaml
-  weights: ./models/ldm/stable-diffusion-v1/sd-v1-4.ckpt
-  vae: ./models/ldm/stable-diffusion-v1/vae-ft-mse-840000-ema-pruned.ckpt
-  description: The original Stable Diffusion version 1.4 weight file (4.27 GB)
-  width: 512
-  height: 512
-stable-diffusion-1.5:
-  description: The newest Stable Diffusion version 1.5 weight file (4.27 GB)
-  weights: ./models/ldm/stable-diffusion-v1/v1-5-pruned-emaonly.ckpt
-  config: ./configs/stable-diffusion/v1-inference.yaml
-  width: 512
-  height: 512
-  vae: ./models/ldm/stable-diffusion-v1/vae-ft-mse-840000-ema-pruned.ckpt
-  default: true
-inpainting-1.5:
-  description: RunwayML SD 1.5 model optimized for inpainting (4.27 GB)
-  weights: ./models/ldm/stable-diffusion-v1/sd-v1-5-inpainting.ckpt
-  config: ./configs/stable-diffusion/v1-inpainting-inference.yaml
-  width: 512
-  height: 512
-  vae: ./models/ldm/stable-diffusion-v1/vae-ft-mse-840000-ema-pruned.ckpt
-waifu-diffusion-1.3:
-  description: Stable Diffusion 1.4 fine tuned on anime-styled images (4.27)
-  weights: ./models/ldm/stable-diffusion-v1/model-epoch09-float32.ckpt
-  config: ./configs/stable-diffusion/v1-inference.yaml
-  width: 512
-  height: 512
-  vae: ./models/ldm/stable-diffusion-v1/vae-ft-mse-840000-ema-pruned.ckpt

configs/stable-diffusion/v1-finetune.yaml

@@ -1,110 +0,0 @@
-model:
-  base_learning_rate: 5.0e-03
-  target: ldm.models.diffusion.ddpm.LatentDiffusion
-  params:
-    linear_start: 0.00085
-    linear_end: 0.0120
-    num_timesteps_cond: 1
-    log_every_t: 200
-    timesteps: 1000
-    first_stage_key: image
-    cond_stage_key: caption
-    image_size: 64
-    channels: 4
-    cond_stage_trainable: true   # Note: different from the one we trained before
-    conditioning_key: crossattn
-    monitor: val/loss_simple_ema
-    scale_factor: 0.18215
-    use_ema: False
-    embedding_reg_weight: 0.0
-
-    personalization_config:
-      target: ldm.modules.embedding_manager.EmbeddingManager
-      params:
-        placeholder_strings: ["*"]
-        initializer_words: ["sculpture"]
-        per_image_tokens: false
-        num_vectors_per_token: 1
-        progressive_words: False
-
-    unet_config:
-      target: ldm.modules.diffusionmodules.openaimodel.UNetModel
-      params:
-        image_size: 32 # unused
-        in_channels: 4
-        out_channels: 4
-        model_channels: 320
-        attention_resolutions: [ 4, 2, 1 ]
-        num_res_blocks: 2
-        channel_mult: [ 1, 2, 4, 4 ]
-        num_heads: 8
-        use_spatial_transformer: True
-        transformer_depth: 1
-        context_dim: 768
-        use_checkpoint: True
-        legacy: False
-
-    first_stage_config:
-      target: ldm.models.autoencoder.AutoencoderKL
-      params:
-        embed_dim: 4
-        monitor: val/rec_loss
-        ddconfig:
-          double_z: true
-          z_channels: 4
-          resolution: 256
-          in_channels: 3
-          out_ch: 3
-          ch: 128
-          ch_mult:
-          - 1
-          - 2
-          - 4
-          - 4
-          num_res_blocks: 2
-          attn_resolutions: []
-          dropout: 0.0
-        lossconfig:
-          target: torch.nn.Identity
-
-    cond_stage_config:
-      target: ldm.modules.encoders.modules.FrozenCLIPEmbedder
-
-data:
-  target: main.DataModuleFromConfig
-  params:
-    batch_size: 1
-    num_workers: 2
-    wrap: false
-    train:
-      target: ldm.data.personalized.PersonalizedBase
-      params:
-        size: 512
-        set: train
-        per_image_tokens: false
-        repeats: 100
-    validation:
-      target: ldm.data.personalized.PersonalizedBase
-      params:
-        size: 512
-        set: val
-        per_image_tokens: false
-        repeats: 10
-
-lightning:
-  modelcheckpoint:
-    params:
-      every_n_train_steps: 500
-  callbacks:
-    image_logger:
-      target: main.ImageLogger
-      params:
-        batch_frequency: 500
-        max_images: 8
-        increase_log_steps: False
-
-  trainer:
-    benchmark: True
-    max_steps: 4000000
-#    max_steps: 4000
-    

configs/stable-diffusion/v1-finetune_style.yaml

@@ -1,103 +0,0 @@
-model:
-  base_learning_rate: 5.0e-03
-  target: ldm.models.diffusion.ddpm.LatentDiffusion
-  params:
-    linear_start: 0.00085
-    linear_end: 0.0120
-    num_timesteps_cond: 1
-    log_every_t: 200
-    timesteps: 1000
-    first_stage_key: image
-    cond_stage_key: caption
-    image_size: 64
-    channels: 4
-    cond_stage_trainable: true   # Note: different from the one we trained before
-    conditioning_key: crossattn
-    monitor: val/loss_simple_ema
-    scale_factor: 0.18215
-    use_ema: False
-    embedding_reg_weight: 0.0
-
-    personalization_config:
-      target: ldm.modules.embedding_manager.EmbeddingManager
-      params:
-        placeholder_strings: ["*"]
-        initializer_words: ["painting"]
-        per_image_tokens: false
-        num_vectors_per_token: 1
-
-    unet_config:
-      target: ldm.modules.diffusionmodules.openaimodel.UNetModel
-      params:
-        image_size: 32 # unused
-        in_channels: 4
-        out_channels: 4
-        model_channels: 320
-        attention_resolutions: [ 4, 2, 1 ]
-        num_res_blocks: 2
-        channel_mult: [ 1, 2, 4, 4 ]
-        num_heads: 8
-        use_spatial_transformer: True
-        transformer_depth: 1
-        context_dim: 768
-        use_checkpoint: True
-        legacy: False
-
-    first_stage_config:
-      target: ldm.models.autoencoder.AutoencoderKL
-      params:
-        embed_dim: 4
-        monitor: val/rec_loss
-        ddconfig:
-          double_z: true
-          z_channels: 4
-          resolution: 256
-          in_channels: 3
-          out_ch: 3
-          ch: 128
-          ch_mult:
-          - 1
-          - 2
-          - 4
-          - 4
-          num_res_blocks: 2
-          attn_resolutions: []
-          dropout: 0.0
-        lossconfig:
-          target: torch.nn.Identity
-
-    cond_stage_config:
-      target: ldm.modules.encoders.modules.FrozenCLIPEmbedder
-
-data:
-  target: main.DataModuleFromConfig
-  params:
-    batch_size: 2
-    num_workers: 16
-    wrap: false
-    train:
-      target: ldm.data.personalized_style.PersonalizedBase
-      params:
-        size: 512
-        set: train
-        per_image_tokens: false
-        repeats: 100
-    validation:
-      target: ldm.data.personalized_style.PersonalizedBase
-      params:
-        size: 512
-        set: val
-        per_image_tokens: false
-        repeats: 10
-
-lightning:
-  callbacks:
-    image_logger:
-      target: main.ImageLogger
-      params:
-        batch_frequency: 500
-        max_images: 8
-        increase_log_steps: False
-
-  trainer:
-    benchmark: True

configs/stable-diffusion/v1-inference.yaml

@@ -1,79 +0,0 @@
-model:
-  base_learning_rate: 1.0e-04
-  target: ldm.models.diffusion.ddpm.LatentDiffusion
-  params:
-    linear_start: 0.00085
-    linear_end: 0.0120
-    num_timesteps_cond: 1
-    log_every_t: 200
-    timesteps: 1000
-    first_stage_key: "jpg"
-    cond_stage_key: "txt"
-    image_size: 64
-    channels: 4
-    cond_stage_trainable: false   # Note: different from the one we trained before
-    conditioning_key: crossattn
-    monitor: val/loss_simple_ema
-    scale_factor: 0.18215
-    use_ema: False
-
-    scheduler_config: # 10000 warmup steps
-      target: ldm.lr_scheduler.LambdaLinearScheduler
-      params:
-        warm_up_steps: [ 10000 ]
-        cycle_lengths: [ 10000000000000 ] # incredibly large number to prevent corner cases
-        f_start: [ 1.e-6 ]
-        f_max: [ 1. ]
-        f_min: [ 1. ]
-
-    personalization_config:
-      target: ldm.modules.embedding_manager.EmbeddingManager
-      params:
-        placeholder_strings: ["*"]
-        initializer_words: ['face', 'man', 'photo', 'africanmale']
-        per_image_tokens: false
-        num_vectors_per_token: 1
-        progressive_words: False
-
-    unet_config:
-      target: ldm.modules.diffusionmodules.openaimodel.UNetModel
-      params:
-        image_size: 32 # unused
-        in_channels: 4
-        out_channels: 4
-        model_channels: 320
-        attention_resolutions: [ 4, 2, 1 ]
-        num_res_blocks: 2
-        channel_mult: [ 1, 2, 4, 4 ]
-        num_heads: 8
-        use_spatial_transformer: True
-        transformer_depth: 1
-        context_dim: 768
-        use_checkpoint: True
-        legacy: False
-
-    first_stage_config:
-      target: ldm.models.autoencoder.AutoencoderKL
-      params:
-        embed_dim: 4
-        monitor: val/rec_loss
-        ddconfig:
-          double_z: true
-          z_channels: 4
-          resolution: 256
-          in_channels: 3
-          out_ch: 3
-          ch: 128
-          ch_mult:
-          - 1
-          - 2
-          - 4
-          - 4
-          num_res_blocks: 2
-          attn_resolutions: []
-          dropout: 0.0
-        lossconfig:
-          target: torch.nn.Identity
-
-    cond_stage_config:
-      target: ldm.modules.encoders.modules.WeightedFrozenCLIPEmbedder

configs/stable-diffusion/v1-inpainting-inference.yaml

@@ -1,79 +0,0 @@
-model:
-  base_learning_rate: 7.5e-05
-  target: ldm.models.diffusion.ddpm.LatentInpaintDiffusion
-  params:
-    linear_start: 0.00085
-    linear_end: 0.0120
-    num_timesteps_cond: 1
-    log_every_t: 200
-    timesteps: 1000
-    first_stage_key: "jpg"
-    cond_stage_key: "txt"
-    image_size: 64
-    channels: 4
-    cond_stage_trainable: false   # Note: different from the one we trained before
-    conditioning_key: hybrid   # important
-    monitor: val/loss_simple_ema
-    scale_factor: 0.18215
-    finetune_keys: null
-
-    scheduler_config: # 10000 warmup steps
-      target: ldm.lr_scheduler.LambdaLinearScheduler
-      params:
-        warm_up_steps: [ 2500 ] # NOTE for resuming. use 10000 if starting from scratch
-        cycle_lengths: [ 10000000000000 ] # incredibly large number to prevent corner cases
-        f_start: [ 1.e-6 ]
-        f_max: [ 1. ]
-        f_min: [ 1. ]
-
-    personalization_config:
-      target: ldm.modules.embedding_manager.EmbeddingManager
-      params:
-        placeholder_strings: ["*"]
-        initializer_words: ['face', 'man', 'photo', 'africanmale']
-        per_image_tokens: false
-        num_vectors_per_token: 1
-        progressive_words: False
-
-    unet_config:
-      target: ldm.modules.diffusionmodules.openaimodel.UNetModel
-      params:
-        image_size: 32 # unused
-        in_channels: 9  # 4 data + 4 downscaled image + 1 mask
-        out_channels: 4
-        model_channels: 320
-        attention_resolutions: [ 4, 2, 1 ]
-        num_res_blocks: 2
-        channel_mult: [ 1, 2, 4, 4 ]
-        num_heads: 8
-        use_spatial_transformer: True
-        transformer_depth: 1
-        context_dim: 768
-        use_checkpoint: True
-        legacy: False
-
-    first_stage_config:
-      target: ldm.models.autoencoder.AutoencoderKL
-      params:
-        embed_dim: 4
-        monitor: val/rec_loss
-        ddconfig:
-          double_z: true
-          z_channels: 4
-          resolution: 256
-          in_channels: 3
-          out_ch: 3
-          ch: 128
-          ch_mult:
-          - 1
-          - 2
-          - 4
-          - 4
-          num_res_blocks: 2
-          attn_resolutions: []
-          dropout: 0.0
-        lossconfig:
-          target: torch.nn.Identity
-
-    cond_stage_config:
-      target: ldm.modules.encoders.modules.WeightedFrozenCLIPEmbedder

configs/stable-diffusion/v1-m1-finetune.yaml

@@ -1,110 +0,0 @@
-model:
-  base_learning_rate: 5.0e-03
-  target: ldm.models.diffusion.ddpm.LatentDiffusion
-  params:
-    linear_start: 0.00085
-    linear_end: 0.0120
-    num_timesteps_cond: 1
-    log_every_t: 200
-    timesteps: 1000
-    first_stage_key: image
-    cond_stage_key: caption
-    image_size: 64
-    channels: 4
-    cond_stage_trainable: true   # Note: different from the one we trained before
-    conditioning_key: crossattn
-    monitor: val/loss_simple_ema
-    scale_factor: 0.18215
-    use_ema: False
-    embedding_reg_weight: 0.0
-
-    personalization_config:
-      target: ldm.modules.embedding_manager.EmbeddingManager
-      params:
-        placeholder_strings: ["*"]
-        initializer_words: ['face', 'man', 'photo', 'africanmale']
-        per_image_tokens: false
-        num_vectors_per_token: 6
-        progressive_words: False
-
-    unet_config:
-      target: ldm.modules.diffusionmodules.openaimodel.UNetModel
-      params:
-        image_size: 32 # unused
-        in_channels: 4
-        out_channels: 4
-        model_channels: 320
-        attention_resolutions: [ 4, 2, 1 ]
-        num_res_blocks: 2
-        channel_mult: [ 1, 2, 4, 4 ]
-        num_heads: 8
-        use_spatial_transformer: True
-        transformer_depth: 1
-        context_dim: 768
-        use_checkpoint: True
-        legacy: False
-
-    first_stage_config:
-      target: ldm.models.autoencoder.AutoencoderKL
-      params:
-        embed_dim: 4
-        monitor: val/rec_loss
-        ddconfig:
-          double_z: true
-          z_channels: 4
-          resolution: 256
-          in_channels: 3
-          out_ch: 3
-          ch: 128
-          ch_mult:
-          - 1
-          - 2
-          - 4
-          - 4
-          num_res_blocks: 2
-          attn_resolutions: []
-          dropout: 0.0
-        lossconfig:
-          target: torch.nn.Identity
-
-    cond_stage_config:
-      target: ldm.modules.encoders.modules.FrozenCLIPEmbedder
-
-data:
-  target: main.DataModuleFromConfig
-  params:
-    batch_size: 1
-    num_workers: 2
-    wrap: false
-    train:
-      target: ldm.data.personalized.PersonalizedBase
-      params:
-        size: 512
-        set: train
-        per_image_tokens: false
-        repeats: 100
-    validation:
-      target: ldm.data.personalized.PersonalizedBase
-      params:
-        size: 512
-        set: val
-        per_image_tokens: false
-        repeats: 10
-
-lightning:
-  modelcheckpoint:
-    params:
-      every_n_train_steps: 500
-  callbacks:
-    image_logger:
-      target: main.ImageLogger
-      params:
-        batch_frequency: 500
-        max_images: 5
-        increase_log_steps: False
-
-  trainer:
-    benchmark: False
-    max_steps: 6200
-#    max_steps: 4000
-    

coverage/.gitignore

@@ -0,0 +1,4 @@
+# Ignore everything in this directory
+*
+# Except this file
+!.gitignore

docker-build/Dockerfile

@@ -1,74 +0,0 @@
-FROM ubuntu AS get_miniconda
-
-SHELL ["/bin/bash", "-c"]
-
-# install wget
-RUN apt-get update \
-  && apt-get install -y \
-    wget \
-  && apt-get clean \
-  && rm -rf /var/lib/apt/lists/*
-
-# download and install miniconda
-ARG conda_version=py39_4.12.0-Linux-x86_64
-ARG conda_prefix=/opt/conda
-RUN wget --progress=dot:giga -O /miniconda.sh \
-  https://repo.anaconda.com/miniconda/Miniconda3-${conda_version}.sh \
-  && bash /miniconda.sh -b -p ${conda_prefix} \
-  && rm -f /miniconda.sh
-
-FROM ubuntu AS invokeai
-
-# use bash
-SHELL [ "/bin/bash", "-c" ]
-
-# clean bashrc
-RUN echo "" > ~/.bashrc
-
-# Install necesarry packages
-RUN apt-get update \
-  && apt-get install -y \
-    --no-install-recommends \
-    gcc \
-    git \
-    libgl1-mesa-glx \
-    libglib2.0-0 \
-    pip \
-    python3 \
-    python3-dev \
-  && apt-get clean \
-  && rm -rf /var/lib/apt/lists/*
-
-# clone repository and create symlinks
-ARG invokeai_git=https://github.com/invoke-ai/InvokeAI.git
-ARG project_name=invokeai
-RUN git clone ${invokeai_git} /${project_name} \
-  && mkdir /${project_name}/models/ldm/stable-diffusion-v1 \
-  && ln -s /data/models/sd-v1-4.ckpt /${project_name}/models/ldm/stable-diffusion-v1/model.ckpt \
-  && ln -s /data/outputs/ /${project_name}/outputs
-
-# set workdir
-WORKDIR /${project_name}
-
-# install conda env and preload models
-ARG conda_prefix=/opt/conda
-ARG conda_env_file=environment.yml
-COPY --from=get_miniconda ${conda_prefix} ${conda_prefix}
-RUN source ${conda_prefix}/etc/profile.d/conda.sh \
-  && conda init bash \
-  && source ~/.bashrc \
-  && conda env create \
-    --name ${project_name} \
-    --file ${conda_env_file} \
-  && rm -Rf ~/.cache \
-  && conda clean -afy \
-  && echo "conda activate ${project_name}" >> ~/.bashrc \
-  && ln -s /data/models/GFPGANv1.4.pth ./src/gfpgan/experiments/pretrained_models/GFPGANv1.4.pth \
-  && conda activate ${project_name} \
-  && python scripts/preload_models.py
-
-# Copy entrypoint and set env
-ENV CONDA_PREFIX=${conda_prefix}
-ENV PROJECT_NAME=${project_name}
-COPY docker-build/entrypoint.sh /
-ENTRYPOINT [ "/entrypoint.sh" ]

docker-build/build.sh

@@ -1,81 +0,0 @@
-#!/usr/bin/env bash
-set -e
-# IMPORTANT: You need to have a token on huggingface.co to be able to download the checkpoint!!!
-# configure values by using env when executing build.sh
-# f.e. env ARCH=aarch64 GITHUB_INVOKE_AI=https://github.com/yourname/yourfork.git ./build.sh
-
-source ./docker-build/env.sh || echo "please run from repository root" || exit 1
-
-invokeai_conda_version=${INVOKEAI_CONDA_VERSION:-py39_4.12.0-${platform/\//-}}
-invokeai_conda_prefix=${INVOKEAI_CONDA_PREFIX:-\/opt\/conda}
-invokeai_conda_env_file=${INVOKEAI_CONDA_ENV_FILE:-environment.yml}
-invokeai_git=${INVOKEAI_GIT:-https://github.com/invoke-ai/InvokeAI.git}
-huggingface_token=${HUGGINGFACE_TOKEN?}
-
-# print the settings
-echo "You are using these values:"
-echo -e "project_name:\t\t ${project_name}"
-echo -e "volumename:\t\t ${volumename}"
-echo -e "arch:\t\t\t ${arch}"
-echo -e "platform:\t\t ${platform}"
-echo -e "invokeai_conda_version:\t ${invokeai_conda_version}"
-echo -e "invokeai_conda_prefix:\t ${invokeai_conda_prefix}"
-echo -e "invokeai_conda_env_file: ${invokeai_conda_env_file}"
-echo -e "invokeai_git:\t\t ${invokeai_git}"
-echo -e "invokeai_tag:\t\t ${invokeai_tag}\n"
-
-_runAlpine() {
-  docker run \
-    --rm \
-    --interactive \
-    --tty \
-    --mount source="$volumename",target=/data \
-    --workdir /data \
-    alpine "$@"
-}
-
-_copyCheckpoints() {
-  echo "creating subfolders for models and outputs"
-  _runAlpine mkdir models
-  _runAlpine mkdir outputs
-  echo -n "downloading sd-v1-4.ckpt"
-  _runAlpine wget --header="Authorization: Bearer ${huggingface_token}" -O models/sd-v1-4.ckpt https://huggingface.co/CompVis/stable-diffusion-v-1-4-original/resolve/main/sd-v1-4.ckpt
-  echo "done"
-  echo "downloading GFPGANv1.4.pth"
-  _runAlpine wget -O models/GFPGANv1.4.pth https://github.com/TencentARC/GFPGAN/releases/download/v1.3.0/GFPGANv1.4.pth
-}
-
-_checkVolumeContent() {
-  _runAlpine ls -lhA /data/models
-}
-
-_getModelMd5s() {
-  _runAlpine  \
-    alpine sh -c "md5sum /data/models/*"
-}
-
-if [[ -n "$(docker volume ls -f name="${volumename}" -q)" ]]; then
-  echo "Volume already exists"
-  if [[ -z "$(_checkVolumeContent)" ]]; then
-    echo "looks empty, copying checkpoint"
-    _copyCheckpoints
-  fi
-  echo "Models in ${volumename}:"
-  _checkVolumeContent
-else
-  echo -n "createing docker volume "
-  docker volume create "${volumename}"
-  _copyCheckpoints
-fi
-
-# Build Container
-docker build \
-  --platform="${platform}" \
-  --tag "${invokeai_tag}" \
-  --build-arg project_name="${project_name}" \
-  --build-arg conda_version="${invokeai_conda_version}" \
-  --build-arg conda_prefix="${invokeai_conda_prefix}" \
-  --build-arg conda_env_file="${invokeai_conda_env_file}" \
-  --build-arg invokeai_git="${invokeai_git}" \
-  --file ./docker-build/Dockerfile \
-  .

docker-build/entrypoint.sh

@@ -1,8 +0,0 @@
-#!/bin/bash
-set -e
-
-source "${CONDA_PREFIX}/etc/profile.d/conda.sh"
-conda activate "${PROJECT_NAME}"
-
-python scripts/invoke.py \
-  ${@:---web --host=0.0.0.0}

docker-build/env.sh

@@ -1,13 +0,0 @@
-#!/usr/bin/env bash
-
-project_name=${PROJECT_NAME:-invokeai}
-volumename=${VOLUMENAME:-${project_name}_data}
-arch=${ARCH:-x86_64}
-platform=${PLATFORM:-Linux/${arch}}
-invokeai_tag=${INVOKEAI_TAG:-${project_name}-${arch}}
-
-export project_name
-export volumename
-export arch
-export platform
-export invokeai_tag

docker-build/run.sh

@@ -1,15 +0,0 @@
-#!/usr/bin/env bash
-set -e
-
-source ./docker-build/env.sh || echo "please run from repository root" || exit 1
-
-docker run \
-  --interactive \
-  --tty \
-  --rm \
-  --platform "$platform" \
-  --name "$project_name" \
-  --hostname "$project_name" \
-  --mount source="$volumename",target=/data \
-  --publish 9090:9090 \
-  "$invokeai_tag" ${1:+$@}

docker/Dockerfile

@@ -0,0 +1,107 @@
+# syntax=docker/dockerfile:1
+
+ARG PYTHON_VERSION=3.9
+##################
+##  base image  ##
+##################
+FROM --platform=${TARGETPLATFORM} python:${PYTHON_VERSION}-slim AS python-base
+
+LABEL org.opencontainers.image.authors="mauwii@outlook.de"
+
+# Prepare apt for buildkit cache
+RUN rm -f /etc/apt/apt.conf.d/docker-clean \
+  && echo 'Binary::apt::APT::Keep-Downloaded-Packages "true";' >/etc/apt/apt.conf.d/keep-cache
+
+# Install dependencies
+RUN \
+  --mount=type=cache,target=/var/cache/apt,sharing=locked \
+  --mount=type=cache,target=/var/lib/apt,sharing=locked \
+  apt-get update \
+  && apt-get install -y \
+    --no-install-recommends \
+    libgl1-mesa-glx=20.3.* \
+    libglib2.0-0=2.66.* \
+    libopencv-dev=4.5.*
+
+# Set working directory and env
+ARG APPDIR=/usr/src
+ARG APPNAME=InvokeAI
+WORKDIR ${APPDIR}
+ENV PATH ${APPDIR}/${APPNAME}/bin:$PATH
+# Keeps Python from generating .pyc files in the container
+ENV PYTHONDONTWRITEBYTECODE 1
+# Turns off buffering for easier container logging
+ENV PYTHONUNBUFFERED 1
+# Don't fall back to legacy build system
+ENV PIP_USE_PEP517=1
+
+#######################
+##  build pyproject  ##
+#######################
+FROM python-base AS pyproject-builder
+
+# Install build dependencies
+RUN \
+  --mount=type=cache,target=/var/cache/apt,sharing=locked \
+  --mount=type=cache,target=/var/lib/apt,sharing=locked \
+  apt-get update \
+  && apt-get install -y \
+    --no-install-recommends \
+    build-essential=12.9 \
+    gcc=4:10.2.* \
+    python3-dev=3.9.*
+
+# Prepare pip for buildkit cache
+ARG PIP_CACHE_DIR=/var/cache/buildkit/pip
+ENV PIP_CACHE_DIR ${PIP_CACHE_DIR}
+RUN mkdir -p ${PIP_CACHE_DIR}
+
+# Create virtual environment
+RUN --mount=type=cache,target=${PIP_CACHE_DIR} \
+  python3 -m venv "${APPNAME}" \
+  --upgrade-deps
+
+# Install requirements
+COPY --link pyproject.toml .
+COPY --link invokeai/version/invokeai_version.py invokeai/version/__init__.py invokeai/version/
+ARG PIP_EXTRA_INDEX_URL
+ENV PIP_EXTRA_INDEX_URL ${PIP_EXTRA_INDEX_URL}
+RUN --mount=type=cache,target=${PIP_CACHE_DIR} \
+  "${APPNAME}"/bin/pip install .
+
+# Install pyproject.toml
+COPY --link . .
+RUN --mount=type=cache,target=${PIP_CACHE_DIR} \
+  "${APPNAME}/bin/pip" install .
+
+# Build patchmatch
+RUN python3 -c "from patchmatch import patch_match"
+
+#####################
+##  runtime image  ##
+#####################
+FROM python-base AS runtime
+
+# Create a new user
+ARG UNAME=appuser
+RUN useradd \
+  --no-log-init \
+  -m \
+  -U \
+  "${UNAME}"
+
+# Create volume directory
+ARG VOLUME_DIR=/data
+RUN mkdir -p "${VOLUME_DIR}" \
+  && chown -hR "${UNAME}:${UNAME}" "${VOLUME_DIR}"
+
+# Setup runtime environment
+USER ${UNAME}:${UNAME}
+COPY --chown=${UNAME}:${UNAME} --from=pyproject-builder ${APPDIR}/${APPNAME} ${APPNAME}
+ENV INVOKEAI_ROOT ${VOLUME_DIR}
+ENV TRANSFORMERS_CACHE ${VOLUME_DIR}/.cache
+ENV INVOKE_MODEL_RECONFIGURE "--yes --default_only"
+EXPOSE 9090
+ENTRYPOINT [ "invokeai" ]
+CMD [ "--web", "--host", "0.0.0.0", "--port", "9090" ]
+VOLUME [ "${VOLUME_DIR}" ]

docker/build.sh

@@ -0,0 +1,51 @@
+#!/usr/bin/env bash
+set -e
+
+# If you want to build a specific flavor, set the CONTAINER_FLAVOR environment variable
+#   e.g. CONTAINER_FLAVOR=cpu ./build.sh
+#   Possible Values are:
+#     - cpu
+#     - cuda
+#     - rocm
+#   Don't forget to also set it when executing run.sh
+#   if it is not set, the script will try to detect the flavor by itself.
+#
+# Doc can be found here:
+#   https://invoke-ai.github.io/InvokeAI/installation/040_INSTALL_DOCKER/
+
+SCRIPTDIR=$(dirname "${BASH_SOURCE[0]}")
+cd "$SCRIPTDIR" || exit 1
+
+source ./env.sh
+
+DOCKERFILE=${INVOKE_DOCKERFILE:-./Dockerfile}
+
+# print the settings
+echo -e "You are using these values:\n"
+echo -e "Dockerfile:\t\t${DOCKERFILE}"
+echo -e "index-url:\t\t${PIP_EXTRA_INDEX_URL:-none}"
+echo -e "Volumename:\t\t${VOLUMENAME}"
+echo -e "Platform:\t\t${PLATFORM}"
+echo -e "Container Registry:\t${CONTAINER_REGISTRY}"
+echo -e "Container Repository:\t${CONTAINER_REPOSITORY}"
+echo -e "Container Tag:\t\t${CONTAINER_TAG}"
+echo -e "Container Flavor:\t${CONTAINER_FLAVOR}"
+echo -e "Container Image:\t${CONTAINER_IMAGE}\n"
+
+# Create docker volume
+if [[ -n "$(docker volume ls -f name="${VOLUMENAME}" -q)" ]]; then
+    echo -e "Volume already exists\n"
+else
+    echo -n "creating docker volume "
+    docker volume create "${VOLUMENAME}"
+fi
+
+# Build Container
+docker build \
+    --platform="${PLATFORM:-linux/amd64}" \
+    --tag="${CONTAINER_IMAGE:-invokeai}" \
+    ${CONTAINER_FLAVOR:+--build-arg="CONTAINER_FLAVOR=${CONTAINER_FLAVOR}"} \
+    ${PIP_EXTRA_INDEX_URL:+--build-arg="PIP_EXTRA_INDEX_URL=${PIP_EXTRA_INDEX_URL}"} \
+    ${PIP_PACKAGE:+--build-arg="PIP_PACKAGE=${PIP_PACKAGE}"} \
+    --file="${DOCKERFILE}" \
+    ..

docker/env.sh

@@ -0,0 +1,54 @@
+#!/usr/bin/env bash
+
+# This file is used to set environment variables for the build.sh and run.sh scripts.
+
+# Try to detect the container flavor if no PIP_EXTRA_INDEX_URL got specified
+if [[ -z "$PIP_EXTRA_INDEX_URL" ]]; then
+
+  # Activate virtual environment if not already activated and exists
+  if [[ -z $VIRTUAL_ENV ]]; then
+    [[ -e "$(dirname "${BASH_SOURCE[0]}")/../.venv/bin/activate" ]] \
+      && source "$(dirname "${BASH_SOURCE[0]}")/../.venv/bin/activate" \
+      && echo "Activated virtual environment: $VIRTUAL_ENV"
+  fi
+
+  # Decide which container flavor to build if not specified
+  if [[ -z "$CONTAINER_FLAVOR" ]] && python -c "import torch" &>/dev/null; then
+    # Check for CUDA and ROCm
+    CUDA_AVAILABLE=$(python -c "import torch;print(torch.cuda.is_available())")
+    ROCM_AVAILABLE=$(python -c "import torch;print(torch.version.hip is not None)")
+    if [[ "${CUDA_AVAILABLE}" == "True" ]]; then
+      CONTAINER_FLAVOR="cuda"
+    elif [[ "${ROCM_AVAILABLE}" == "True" ]]; then
+      CONTAINER_FLAVOR="rocm"
+    else
+      CONTAINER_FLAVOR="cpu"
+    fi
+  fi
+
+  # Set PIP_EXTRA_INDEX_URL based on container flavor
+  if [[ "$CONTAINER_FLAVOR" == "rocm" ]]; then
+    PIP_EXTRA_INDEX_URL="https://download.pytorch.org/whl/rocm"
+  elif [[ "$CONTAINER_FLAVOR" == "cpu" ]]; then
+    PIP_EXTRA_INDEX_URL="https://download.pytorch.org/whl/cpu"
+  # elif [[ -z "$CONTAINER_FLAVOR" || "$CONTAINER_FLAVOR" == "cuda" ]]; then
+  #   PIP_PACKAGE=${PIP_PACKAGE-".[xformers]"}
+  fi
+fi
+
+# Variables shared by build.sh and run.sh
+REPOSITORY_NAME="${REPOSITORY_NAME-$(basename "$(git rev-parse --show-toplevel)")}"
+REPOSITORY_NAME="${REPOSITORY_NAME,,}"
+VOLUMENAME="${VOLUMENAME-"${REPOSITORY_NAME}_data"}"
+ARCH="${ARCH-$(uname -m)}"
+PLATFORM="${PLATFORM-linux/${ARCH}}"
+INVOKEAI_BRANCH="${INVOKEAI_BRANCH-$(git branch --show)}"
+CONTAINER_REGISTRY="${CONTAINER_REGISTRY-"ghcr.io"}"
+CONTAINER_REPOSITORY="${CONTAINER_REPOSITORY-"$(whoami)/${REPOSITORY_NAME}"}"
+CONTAINER_FLAVOR="${CONTAINER_FLAVOR-cuda}"
+CONTAINER_TAG="${CONTAINER_TAG-"${INVOKEAI_BRANCH##*/}-${CONTAINER_FLAVOR}"}"
+CONTAINER_IMAGE="${CONTAINER_REGISTRY}/${CONTAINER_REPOSITORY}:${CONTAINER_TAG}"
+CONTAINER_IMAGE="${CONTAINER_IMAGE,,}"
+
+# enable docker buildkit
+export DOCKER_BUILDKIT=1

docker/run.sh

@@ -0,0 +1,41 @@
+#!/usr/bin/env bash
+set -e
+
+# How to use: https://invoke-ai.github.io/InvokeAI/installation/040_INSTALL_DOCKER/
+
+SCRIPTDIR=$(dirname "${BASH_SOURCE[0]}")
+cd "$SCRIPTDIR" || exit 1
+
+source ./env.sh
+
+# Create outputs directory if it does not exist
+[[ -d ./outputs ]] || mkdir ./outputs
+
+echo -e "You are using these values:\n"
+echo -e "Volumename:\t${VOLUMENAME}"
+echo -e "Invokeai_tag:\t${CONTAINER_IMAGE}"
+echo -e "local Models:\t${MODELSPATH:-unset}\n"
+
+docker run \
+  --interactive \
+  --tty \
+  --rm \
+  --platform="${PLATFORM}" \
+  --name="${REPOSITORY_NAME}" \
+  --hostname="${REPOSITORY_NAME}" \
+  --mount type=volume,volume-driver=local,source="${VOLUMENAME}",target=/data \
+  --mount type=bind,source="$(pwd)"/outputs/,target=/data/outputs/ \
+  ${MODELSPATH:+--mount="type=bind,source=${MODELSPATH},target=/data/models"} \
+  ${HUGGING_FACE_HUB_TOKEN:+--env="HUGGING_FACE_HUB_TOKEN=${HUGGING_FACE_HUB_TOKEN}"} \
+  --publish=9090:9090 \
+  --cap-add=sys_nice \
+  ${GPU_FLAGS:+--gpus="${GPU_FLAGS}"} \
+  "${CONTAINER_IMAGE}" ${@:+$@}
+
+echo -e "\nCleaning trash folder ..."
+for f in outputs/.Trash*; do
+  if [ -e "$f" ]; then
+    rm -Rf "$f"
+    break
+  fi
+done

docs/CHANGELOG.md

@@ -4,66 +4,447 @@ title: Changelog
 
 # :octicons-log-16: **Changelog**
 
-## v2.0.1 (13 October 2022)
+## v2.3.0 <small>(15 January 2023)</small>
 
-  - fix noisy images at high step count when using k* samplers
-  - dream.py script now calls invoke.py module directly rather than
-    via a new python process (which could break the environment)
+**Transition to diffusers
+
+Version 2.3 provides support for both the traditional `.ckpt` weight
+checkpoint files as well as the HuggingFace `diffusers` format. This
+introduces several changes you should know about.
+
+1. The models.yaml format has been updated. There are now two
+   different type of configuration stanza. The traditional ckpt
+   one will look like this, with a `format` of `ckpt` and a
+   `weights` field that points to the absolute or ROOTDIR-relative
+   location of the ckpt file.
+
+   ```
+   inpainting-1.5:
+      description: RunwayML SD 1.5 model optimized for inpainting (4.27 GB)
+      repo_id: runwayml/stable-diffusion-inpainting
+      format: ckpt
+      width: 512
+      height: 512
+      weights: models/ldm/stable-diffusion-v1/sd-v1-5-inpainting.ckpt
+      config: configs/stable-diffusion/v1-inpainting-inference.yaml
+      vae: models/ldm/stable-diffusion-v1/vae-ft-mse-840000-ema-pruned.ckpt
+   ```
+
+  A configuration stanza for a diffusers model hosted at HuggingFace will look like this,
+  with a `format` of `diffusers` and a `repo_id` that points to the
+  repository ID of the model on HuggingFace:
+
+  ```
+  stable-diffusion-2.1:
+  description: Stable Diffusion version 2.1 diffusers model (5.21 GB)
+  repo_id: stabilityai/stable-diffusion-2-1
+  format: diffusers
+  ```
+
+  A configuration stanza for a diffuers model stored locally should
+  look like this, with a `format` of `diffusers`, but a `path` field
+  that points at the directory that contains `model_index.json`:
+
+  ```
+  waifu-diffusion:
+  description: Latest waifu diffusion 1.4
+  format: diffusers
+  path: models/diffusers/hakurei-haifu-diffusion-1.4
+  ```
+
+2. In order of precedence, InvokeAI will now use HF_HOME, then
+   XDG_CACHE_HOME, then finally default to `ROOTDIR/models` to
+   store HuggingFace diffusers models.
+
+   Consequently, the format of the models directory has changed to
+   mimic the HuggingFace cache directory. When HF_HOME and XDG_HOME
+   are not set, diffusers models are now automatically downloaded
+   and retrieved from the directory `ROOTDIR/models/diffusers`,
+   while other models are stored in the directory
+   `ROOTDIR/models/hub`. This organization is the same as that used
+   by HuggingFace for its cache management.
+
+   This allows you to share diffusers and ckpt model files easily with
+   other machine learning applications that use the HuggingFace
+   libraries. To do this, set the environment variable HF_HOME
+   before starting up InvokeAI to tell it what directory to
+   cache models in. To tell InvokeAI to use the standard HuggingFace
+   cache directory, you would set HF_HOME like this (Linux/Mac):
+
+   `export HF_HOME=~/.cache/huggingface`
+
+   Both HuggingFace and InvokeAI will fall back to the XDG_CACHE_HOME
+   environment variable if HF_HOME is not set; this path
+   takes precedence over `ROOTDIR/models` to allow for the same sharing
+   with other machine learning applications that use HuggingFace
+   libraries.
+
+3. If you upgrade to InvokeAI 2.3.* from an earlier version, there
+   will be a one-time migration from the old models directory format
+   to the new one. You will see a message about this the first time
+   you start `invoke.py`.
+
+4. Both the front end back ends of the model manager have been
+   rewritten to accommodate diffusers. You can import models using
+   their local file path, using their URLs, or their HuggingFace
+   repo_ids. On the command line, all these syntaxes work:
+
+   ```
+   !import_model stabilityai/stable-diffusion-2-1-base
+   !import_model /opt/sd-models/sd-1.4.ckpt
+   !import_model https://huggingface.co/Fictiverse/Stable_Diffusion_PaperCut_Model/blob/main/PaperCut_v1.ckpt
+   ```
+
+**KNOWN BUGS (15 January 2023)
+
+1. On CUDA systems, the 768 pixel stable-diffusion-2.0 and
+   stable-diffusion-2.1 models can only be run as `diffusers` models
+   when the `xformer` library is installed and configured. Without
+   `xformers`, InvokeAI returns black images.
+
+2. Inpainting and outpainting have regressed in quality.
+
+Both these issues are being actively worked on.
+
+## v2.2.4 <small>(11 December 2022)</small>
+
+**the `invokeai` directory**
+
+Previously there were two directories to worry about, the directory that
+contained the InvokeAI source code and the launcher scripts, and the `invokeai`
+directory that contained the models files, embeddings, configuration and
+outputs. With the 2.2.4 release, this dual system is done away with, and
+everything, including the `invoke.bat` and `invoke.sh` launcher scripts, now
+live in a directory named `invokeai`. By default this directory is located in
+your home directory (e.g. `\Users\yourname` on Windows), but you can select
+where it goes at install time.
+
+After installation, you can delete the install directory (the one that the zip
+file creates when it unpacks). Do **not** delete or move the `invokeai`
+directory!
+
+**Initialization file `invokeai/invokeai.init`**
+
+You can place frequently-used startup options in this file, such as the default
+number of steps or your preferred sampler. To keep everything in one place, this
+file has now been moved into the `invokeai` directory and is named
+`invokeai.init`.
+
+**To update from Version 2.2.3**
+
+The easiest route is to download and unpack one of the 2.2.4 installer files.
+When it asks you for the location of the `invokeai` runtime directory, respond
+with the path to the directory that contains your 2.2.3 `invokeai`. That is, if
+`invokeai` lives at `C:\Users\fred\invokeai`, then answer with `C:\Users\fred`
+and answer "Y" when asked if you want to reuse the directory.
+
+The `update.sh` (`update.bat`) script that came with the 2.2.3 source installer
+does not know about the new directory layout and won't be fully functional.
+
+**To update to 2.2.5 (and beyond) there's now an update path**
+
+As they become available, you can update to more recent versions of InvokeAI
+using an `update.sh` (`update.bat`) script located in the `invokeai` directory.
+Running it without any arguments will install the most recent version of
+InvokeAI. Alternatively, you can get set releases by running the `update.sh`
+script with an argument in the command shell. This syntax accepts the path to
+the desired release's zip file, which you can find by clicking on the green
+"Code" button on this repository's home page.
+
+**Other 2.2.4 Improvements**
+
+- Fix InvokeAI GUI initialization by @addianto in #1687
+- fix link in documentation by @lstein in #1728
+- Fix broken link by @ShawnZhong in #1736
+- Remove reference to binary installer by @lstein in #1731
+- documentation fixes for 2.2.3 by @lstein in #1740
+- Modify installer links to point closer to the source installer by @ebr in
+  #1745
+- add documentation warning about 1650/60 cards by @lstein in #1753
+- Fix Linux source URL in installation docs by @andybearman in #1756
+- Make install instructions discoverable in readme by @damian0815 in #1752
+- typo fix by @ofirkris in #1755
+- Non-interactive model download (support HUGGINGFACE_TOKEN) by @ebr in #1578
+- fix(srcinstall): shell installer - cp scripts instead of linking by @tildebyte
+  in #1765
+- stability and usage improvements to binary & source installers by @lstein in
+  #1760
+- fix off-by-one bug in cross-attention-control by @damian0815 in #1774
+- Eventually update APP_VERSION to 2.2.3 by @spezialspezial in #1768
+- invoke script cds to its location before running by @lstein in #1805
+- Make PaperCut and VoxelArt models load again by @lstein in #1730
+- Fix --embedding_directory / --embedding_path not working by @blessedcoolant in
+  #1817
+- Clean up readme by @hipsterusername in #1820
+- Optimized Docker build with support for external working directory by @ebr in
+  #1544
+- disable pushing the cloud container by @mauwii in #1831
+- Fix docker push github action and expand with additional metadata by @ebr in
+  #1837
+- Fix Broken Link To Notebook by @VedantMadane in #1821
+- Account for flat models by @spezialspezial in #1766
+- Update invoke.bat.in isolate environment variables by @lynnewu in #1833
+- Arch Linux Specific PatchMatch Instructions & fixing conda install on linux by
+  @SammCheese in #1848
+- Make force free GPU memory work in img2img by @addianto in #1844
+- New installer by @lstein
+
+## v2.2.3 <small>(2 December 2022)</small>
+
+!!! Note
+
+    This point release removes references to the binary installer from the
+    installation guide. The binary installer is not stable at the current
+    time. First time users are encouraged to use the "source" installer as
+    described in [Installing InvokeAI with the Source Installer](installation/deprecated_documentation/INSTALL_SOURCE.md)
+
+With InvokeAI 2.2, this project now provides enthusiasts and professionals a
+robust workflow solution for creating AI-generated and human facilitated
+compositions. Additional enhancements have been made as well, improving safety,
+ease of use, and installation.
+
+Optimized for efficiency, InvokeAI needs only ~3.5GB of VRAM to generate a
+512x768 image (and less for smaller images), and is compatible with
+Windows/Linux/Mac (M1 & M2).
+
+You can see the [release video](https://youtu.be/hIYBfDtKaus) here, which
+introduces the main WebUI enhancement for version 2.2 -
+[The Unified Canvas](features/UNIFIED_CANVAS.md). This new workflow is the
+biggest enhancement added to the WebUI to date, and unlocks a stunning amount of
+potential for users to create and iterate on their creations. The following
+sections describe what's new for InvokeAI.
+
+## v2.2.2 <small>(30 November 2022)</small>
+
+!!! note
+
+    The binary installer is not ready for prime time. First time users are recommended to install via the "source" installer accessible through the links at the bottom of this page.****
+
+With InvokeAI 2.2, this project now provides enthusiasts and professionals a
+robust workflow solution for creating AI-generated and human facilitated
+compositions. Additional enhancements have been made as well, improving safety,
+ease of use, and installation.
+
+Optimized for efficiency, InvokeAI needs only ~3.5GB of VRAM to generate a
+512x768 image (and less for smaller images), and is compatible with
+Windows/Linux/Mac (M1 & M2).
+
+You can see the [release video](https://youtu.be/hIYBfDtKaus) here, which
+introduces the main WebUI enhancement for version 2.2 -
+[The Unified Canvas](https://invoke-ai.github.io/InvokeAI/features/UNIFIED_CANVAS/).
+This new workflow is the biggest enhancement added to the WebUI to date, and
+unlocks a stunning amount of potential for users to create and iterate on their
+creations. The following sections describe what's new for InvokeAI.
+
+## v2.2.0 <small>(2 December 2022)</small>
+
+With InvokeAI 2.2, this project now provides enthusiasts and professionals a
+robust workflow solution for creating AI-generated and human facilitated
+compositions. Additional enhancements have been made as well, improving safety,
+ease of use, and installation.
+
+Optimized for efficiency, InvokeAI needs only ~3.5GB of VRAM to generate a
+512x768 image (and less for smaller images), and is compatible with
+Windows/Linux/Mac (M1 & M2).
+
+You can see the [release video](https://youtu.be/hIYBfDtKaus) here, which
+introduces the main WebUI enhancement for version 2.2 -
+[The Unified Canvas](features/UNIFIED_CANVAS.md). This new workflow is the
+biggest enhancement added to the WebUI to date, and unlocks a stunning amount of
+potential for users to create and iterate on their creations. The following
+sections describe what's new for InvokeAI.
+
+## v2.1.3 <small>(13 November 2022)</small>
+
+- A choice of installer scripts that automate installation and configuration.
+  See
+  [Installation](installation/index.md).
+- A streamlined manual installation process that works for both Conda and
+  PIP-only installs. See
+  [Manual Installation](installation/020_INSTALL_MANUAL.md).
+- The ability to save frequently-used startup options (model to load, steps,
+  sampler, etc) in a `.invokeai` file. See
+  [Client](features/CLI.md)
+- Support for AMD GPU cards (non-CUDA) on Linux machines.
+- Multiple bugs and edge cases squashed.
+
+## v2.1.0 <small>(2 November 2022)</small>
+
+- update mac instructions to use invokeai for env name by @willwillems in #1030
+- Update .gitignore by @blessedcoolant in #1040
+- reintroduce fix for m1 from #579 missing after merge by @skurovec in #1056
+- Update Stable_Diffusion_AI_Notebook.ipynb (Take 2) by @ChloeL19 in #1060
+- Print out the device type which is used by @manzke in #1073
+- Hires Addition by @hipsterusername in #1063
+- fix for "1 leaked semaphore objects to clean up at shutdown" on M1 by
+  @skurovec in #1081
+- Forward dream.py to invoke.py using the same interpreter, add deprecation
+  warning by @db3000 in #1077
+- fix noisy images at high step counts by @lstein in #1086
+- Generalize facetool strength argument by @db3000 in #1078
+- Enable fast switching among models at the invoke> command line by @lstein in
+  #1066
+- Fix Typo, committed changing ldm environment to invokeai by @jdries3 in #1095
+- Update generate.py by @unreleased in #1109
+- Update 'ldm' env to 'invokeai' in troubleshooting steps by @19wolf in #1125
+- Fixed documentation typos and resolved merge conflicts by @rupeshs in #1123
+- Fix broken doc links, fix malaprop in the project subtitle by @majick in #1131
+- Only output facetool parameters if enhancing faces by @db3000 in #1119
+- Update gitignore to ignore codeformer weights at new location by
+  @spezialspezial in #1136
+- fix links to point to invoke-ai.github.io #1117 by @mauwii in #1143
+- Rework-mkdocs by @mauwii in #1144
+- add option to CLI and pngwriter that allows user to set PNG compression level
+  by @lstein in #1127
+- Fix img2img DDIM index out of bound by @wfng92 in #1137
+- Fix gh actions by @mauwii in #1128
+- update mac instructions to use invokeai for env name by @willwillems in #1030
+- Update .gitignore by @blessedcoolant in #1040
+- reintroduce fix for m1 from #579 missing after merge by @skurovec in #1056
+- Update Stable_Diffusion_AI_Notebook.ipynb (Take 2) by @ChloeL19 in #1060
+- Print out the device type which is used by @manzke in #1073
+- Hires Addition by @hipsterusername in #1063
+- fix for "1 leaked semaphore objects to clean up at shutdown" on M1 by
+  @skurovec in #1081
+- Forward dream.py to invoke.py using the same interpreter, add deprecation
+  warning by @db3000 in #1077
+- fix noisy images at high step counts by @lstein in #1086
+- Generalize facetool strength argument by @db3000 in #1078
+- Enable fast switching among models at the invoke> command line by @lstein in
+  #1066
+- Fix Typo, committed changing ldm environment to invokeai by @jdries3 in #1095
+- Fixed documentation typos and resolved merge conflicts by @rupeshs in #1123
+- Only output facetool parameters if enhancing faces by @db3000 in #1119
+- add option to CLI and pngwriter that allows user to set PNG compression level
+  by @lstein in #1127
+- Fix img2img DDIM index out of bound by @wfng92 in #1137
+- Add text prompt to inpaint mask support by @lstein in #1133
+- Respect http[s] protocol when making socket.io middleware by @damian0815 in
+  #976
+- WebUI: Adds Codeformer support by @psychedelicious in #1151
+- Skips normalizing prompts for web UI metadata by @psychedelicious in #1165
+- Add Asymmetric Tiling by @carson-katri in #1132
+- Web UI: Increases max CFG Scale to 200 by @psychedelicious in #1172
+- Corrects color channels in face restoration; Fixes #1167 by @psychedelicious
+  in #1175
+- Flips channels using array slicing instead of using OpenCV by @psychedelicious
+  in #1178
+- Fix typo in docs: s/Formally/Formerly by @noodlebox in #1176
+- fix clipseg loading problems by @lstein in #1177
+- Correct color channels in upscale using array slicing by @wfng92 in #1181
+- Web UI: Filters existing images when adding new images; Fixes #1085 by
+  @psychedelicious in #1171
+- fix a number of bugs in textual inversion by @lstein in #1190
+- Improve !fetch, add !replay command by @ArDiouscuros in #882
+- Fix generation of image with s>1000 by @holstvoogd in #951
+- Web UI: Gallery improvements by @psychedelicious in #1198
+- Update CLI.md by @krummrey in #1211
+- outcropping improvements by @lstein in #1207
+- add support for loading VAE autoencoders by @lstein in #1216
+- remove duplicate fix_func for MPS by @wfng92 in #1210
+- Metadata storage and retrieval fixes by @lstein in #1204
+- nix: add shell.nix file by @Cloudef in #1170
+- Web UI: Changes vite dist asset paths to relative by @psychedelicious in #1185
+- Web UI: Removes isDisabled from PromptInput by @psychedelicious in #1187
+- Allow user to generate images with initial noise as on M1 / mps system by
+  @ArDiouscuros in #981
+- feat: adding filename format template by @plucked in #968
+- Web UI: Fixes broken bundle by @psychedelicious in #1242
+- Support runwayML custom inpainting model by @lstein in #1243
+- Update IMG2IMG.md by @talitore in #1262
+- New dockerfile - including a build- and a run- script as well as a GH-Action
+  by @mauwii in #1233
+- cut over from karras to model noise schedule for higher steps by @lstein in
+  #1222
+- Prompt tweaks by @lstein in #1268
+- Outpainting implementation by @Kyle0654 in #1251
+- fixing aspect ratio on hires by @tjennings in #1249
+- Fix-build-container-action by @mauwii in #1274
+- handle all unicode characters by @damian0815 in #1276
+- adds models.user.yml to .gitignore by @JakeHL in #1281
+- remove debug branch, set fail-fast to false by @mauwii in #1284
+- Protect-secrets-on-pr by @mauwii in #1285
+- Web UI: Adds initial inpainting implementation by @psychedelicious in #1225
+- fix environment-mac.yml - tested on x64 and arm64 by @mauwii in #1289
+- Use proper authentication to download model by @mauwii in #1287
+- Prevent indexing error for mode RGB by @spezialspezial in #1294
+- Integrate sd-v1-5 model into test matrix (easily expandable), remove
+  unecesarry caches by @mauwii in #1293
+- add --no-interactive to configure_invokeai step by @mauwii in #1302
+- 1-click installer and updater. Uses micromamba to install git and conda into a
+  contained environment (if necessary) before running the normal installation
+  script by @cmdr2 in #1253
+- configure_invokeai.py script downloads the weight files by @lstein in #1290
+
+## v2.0.1 <small>(13 October 2022)</small>
+
+- fix noisy images at high step count when using k\* samplers
+- dream.py script now calls invoke.py module directly rather than via a new
+  python process (which could break the environment)
 
 ## v2.0.0 <small>(9 October 2022)</small>
 
-  - `dream.py` script renamed `invoke.py`. A `dream.py` script wrapper remains
-    for backward compatibility.
-  - Completely new WebGUI - launch with `python3 scripts/invoke.py --web`
-  - Support for <a href="https://github.com/invoke-ai/InvokeAI/blob/main/docs/features/INPAINTING.md">inpainting</a> and <a href="https://github.com/invoke-ai/InvokeAI/blob/main/docs/features/OUTPAINTING.md">outpainting</a>
-  - img2img runs on all k* samplers
-  - Support for <a href="https://github.com/invoke-ai/InvokeAI/blob/main/docs/features/PROMPTS.md#negative-and-unconditioned-prompts">negative prompts</a>
-  - Support for CodeFormer face reconstruction
-  - Support for Textual Inversion on Macintoshes
-  - Support in both WebGUI and CLI for <a href="https://github.com/invoke-ai/InvokeAI/blob/main/docs/features/POSTPROCESS.md">post-processing of previously-generated images</a>
-    using facial reconstruction, ESRGAN upscaling, outcropping (similar to DALL-E infinite canvas),
-    and "embiggen" upscaling. See the `!fix` command.
-  - New `--hires` option on `invoke>` line allows <a href="https://github.com/invoke-ai/InvokeAI/blob/main/docs/features/CLI.m#this-is-an-example-of-txt2img">larger images to be created without duplicating elements</a>, at the cost of some performance.
-  - New `--perlin` and `--threshold` options allow you to add and control variation
-    during image generation (see <a href="https://github.com/invoke-ai/InvokeAI/blob/main/docs/features/OTHER.md#thresholding-and-perlin-noise-initialization-options">Thresholding and Perlin Noise Initialization</a>
-  - Extensive metadata now written into PNG files, allowing reliable regeneration of images
-    and tweaking of previous settings.
-  - Command-line completion in `invoke.py` now works on Windows, Linux and Mac platforms.
-  - Improved <a href="https://github.com/invoke-ai/InvokeAI/blob/main/docs/features/CLI.m">command-line completion behavior</a>.
-    New commands added:
-       * List command-line history with `!history`
-       * Search command-line history with `!search`
-       * Clear history with `!clear`
-  - Deprecated `--full_precision` / `-F`. Simply omit it and `invoke.py` will auto
-    configure. To switch away from auto use the new flag like `--precision=float32`.
+- `dream.py` script renamed `invoke.py`. A `dream.py` script wrapper remains for
+  backward compatibility.
+- Completely new WebGUI - launch with `python3 scripts/invoke.py --web`
+- Support for [inpainting](features/INPAINTING.md) and
+  [outpainting](features/OUTPAINTING.md)
+- img2img runs on all k\* samplers
+- Support for
+  [negative prompts](features/PROMPTS.md#negative-and-unconditioned-prompts)
+- Support for CodeFormer face reconstruction
+- Support for Textual Inversion on Macintoshes
+- Support in both WebGUI and CLI for
+  [post-processing of previously-generated images](features/POSTPROCESS.md)
+  using facial reconstruction, ESRGAN upscaling, outcropping (similar to DALL-E
+  infinite canvas), and "embiggen" upscaling. See the `!fix` command.
+- New `--hires` option on `invoke>` line allows
+  [larger images to be created without duplicating elements](features/CLI.md#this-is-an-example-of-txt2img),
+  at the cost of some performance.
+- New `--perlin` and `--threshold` options allow you to add and control
+  variation during image generation (see
+  [Thresholding and Perlin Noise Initialization](features/OTHER.md#thresholding-and-perlin-noise-initialization-options))
+- Extensive metadata now written into PNG files, allowing reliable regeneration
+  of images and tweaking of previous settings.
+- Command-line completion in `invoke.py` now works on Windows, Linux and Mac
+  platforms.
+- Improved [command-line completion behavior](features/CLI.md) New commands
+  added:
+  - List command-line history with `!history`
+  - Search command-line history with `!search`
+  - Clear history with `!clear`
+- Deprecated `--full_precision` / `-F`. Simply omit it and `invoke.py` will auto
+  configure. To switch away from auto use the new flag like
+  `--precision=float32`.
 
 ## v1.14 <small>(11 September 2022)</small>
 
-  - Memory optimizations for small-RAM cards. 512x512 now possible on 4 GB GPUs.
-  - Full support for Apple hardware with M1 or M2 chips.
-  - Add "seamless mode" for circular tiling of image. Generates beautiful effects.
-    ([prixt](https://github.com/prixt)).
-  - Inpainting support.
-  - Improved web server GUI.
-  - Lots of code and documentation cleanups.
+- Memory optimizations for small-RAM cards. 512x512 now possible on 4 GB GPUs.
+- Full support for Apple hardware with M1 or M2 chips.
+- Add "seamless mode" for circular tiling of image. Generates beautiful effects.
+  ([prixt](https://github.com/prixt)).
+- Inpainting support.
+- Improved web server GUI.
+- Lots of code and documentation cleanups.
 
 ## v1.13 <small>(3 September 2022)</small>
 
-  - Support image variations (see [VARIATIONS](features/VARIATIONS.md)
-    ([Kevin Gibbons](https://github.com/bakkot) and many contributors and reviewers)
-  - Supports a Google Colab notebook for a standalone server running on Google hardware
-    [Arturo Mendivil](https://github.com/artmen1516)
-  - WebUI supports GFPGAN/ESRGAN facial reconstruction and upscaling
-    [Kevin Gibbons](https://github.com/bakkot)
-  - WebUI supports incremental display of in-progress images during generation
-    [Kevin Gibbons](https://github.com/bakkot)
-  - A new configuration file scheme that allows new models (including upcoming
-    stable-diffusion-v1.5) to be added without altering the code.
-    ([David Wager](https://github.com/maddavid12))
-  - Can specify --grid on invoke.py command line as the default.
-  - Miscellaneous internal bug and stability fixes.
-  - Works on M1 Apple hardware.
-  - Multiple bug fixes.
+- Support image variations (see [VARIATIONS](features/VARIATIONS.md)
+  ([Kevin Gibbons](https://github.com/bakkot) and many contributors and
+  reviewers)
+- Supports a Google Colab notebook for a standalone server running on Google
+  hardware [Arturo Mendivil](https://github.com/artmen1516)
+- WebUI supports GFPGAN/ESRGAN facial reconstruction and upscaling
+  [Kevin Gibbons](https://github.com/bakkot)
+- WebUI supports incremental display of in-progress images during generation
+  [Kevin Gibbons](https://github.com/bakkot)
+- A new configuration file scheme that allows new models (including upcoming
+  stable-diffusion-v1.5) to be added without altering the code.
+  ([David Wager](https://github.com/maddavid12))
+- Can specify --grid on invoke.py command line as the default.
+- Miscellaneous internal bug and stability fixes.
+- Works on M1 Apple hardware.
+- Multiple bug fixes.
 
 ---
 
@@ -71,49 +452,59 @@ title: Changelog
 
 - Improved file handling, including ability to read prompts from standard input.
   (kudos to [Yunsaki](https://github.com/yunsaki)
-- The web server is now integrated with the invoke.py script. Invoke by adding --web to
-  the invoke.py command arguments.
+- The web server is now integrated with the invoke.py script. Invoke by adding
+  --web to the invoke.py command arguments.
 - Face restoration and upscaling via GFPGAN and Real-ESGAN are now automatically
   enabled if the GFPGAN directory is located as a sibling to Stable Diffusion.
-  VRAM requirements are modestly reduced. Thanks to both [Blessedcoolant](https://github.com/blessedcoolant) and
+  VRAM requirements are modestly reduced. Thanks to both
+  [Blessedcoolant](https://github.com/blessedcoolant) and
   [Oceanswave](https://github.com/oceanswave) for their work on this.
-- You can now swap samplers on the invoke> command line. [Blessedcoolant](https://github.com/blessedcoolant)
+- You can now swap samplers on the invoke> command line.
+  [Blessedcoolant](https://github.com/blessedcoolant)
 
 ---
 
 ## v1.11 <small>(26 August 2022)</small>
 
-- NEW FEATURE: Support upscaling and face enhancement using the GFPGAN module. (kudos to [Oceanswave](https://github.com/Oceanswave)
-- You now can specify a seed of -1 to use the previous image's seed, -2 to use the seed for the image generated before that, etc.
-  Seed memory only extends back to the previous command, but will work on all images generated with the -n# switch.
+- NEW FEATURE: Support upscaling and face enhancement using the GFPGAN module.
+  (kudos to [Oceanswave](https://github.com/Oceanswave)
+- You now can specify a seed of -1 to use the previous image's seed, -2 to use
+  the seed for the image generated before that, etc. Seed memory only extends
+  back to the previous command, but will work on all images generated with the
+  -n# switch.
 - Variant generation support temporarily disabled pending more general solution.
-- Created a feature branch named **yunsaki-morphing-invoke** which adds experimental support for
-  iteratively modifying the prompt and its parameters. Please see[ Pull Request #86](https://github.com/lstein/stable-diffusion/pull/86)
-  for a synopsis of how this works. Note that when this feature is eventually added to the main branch, it will may be modified
-  significantly.
+- Created a feature branch named **yunsaki-morphing-invoke** which adds
+  experimental support for iteratively modifying the prompt and its parameters.
+  Please
+  see[Pull Request #86](https://github.com/lstein/stable-diffusion/pull/86) for
+  a synopsis of how this works. Note that when this feature is eventually added
+  to the main branch, it will may be modified significantly.
 
 ---
 
 ## v1.10 <small>(25 August 2022)</small>
 
-- A barebones but fully functional interactive web server for online generation of txt2img and img2img.
+- A barebones but fully functional interactive web server for online generation
+  of txt2img and img2img.
 
 ---
 
 ## v1.09 <small>(24 August 2022)</small>
 
 - A new -v option allows you to generate multiple variants of an initial image
-  in img2img mode. (kudos to [Oceanswave](https://github.com/Oceanswave). [
-  See this discussion in the PR for examples and details on use](https://github.com/lstein/stable-diffusion/pull/71#issuecomment-1226700810))
-- Added ability to personalize text to image generation (kudos to [Oceanswave](https://github.com/Oceanswave) and [nicolai256](https://github.com/nicolai256))
+  in img2img mode. (kudos to [Oceanswave](https://github.com/Oceanswave).
+  [ See this discussion in the PR for examples and details on use](https://github.com/lstein/stable-diffusion/pull/71#issuecomment-1226700810))
+- Added ability to personalize text to image generation (kudos to
+  [Oceanswave](https://github.com/Oceanswave) and
+  [nicolai256](https://github.com/nicolai256))
 - Enabled all of the samplers from k_diffusion
 
 ---
 
 ## v1.08 <small>(24 August 2022)</small>
 
-- Escape single quotes on the invoke> command before trying to parse. This avoids
-  parse errors.
+- Escape single quotes on the invoke> command before trying to parse. This
+  avoids parse errors.
 - Removed instruction to get Python3.8 as first step in Windows install.
   Anaconda3 does it for you.
 - Added bounds checks for numeric arguments that could cause crashes.
@@ -123,34 +514,36 @@ title: Changelog
 
 ## v1.07 <small>(23 August 2022)</small>
 
-- Image filenames will now never fill gaps in the sequence, but will be assigned the
-  next higher name in the chosen directory. This ensures that the alphabetic and chronological
-  sort orders are the same.
+- Image filenames will now never fill gaps in the sequence, but will be assigned
+  the next higher name in the chosen directory. This ensures that the alphabetic
+  and chronological sort orders are the same.
 
 ---
 
 ## v1.06 <small>(23 August 2022)</small>
 
-- Added weighted prompt support contributed by [xraxra](https://github.com/xraxra)
-- Example of using weighted prompts to tweak a demonic figure contributed by [bmaltais](https://github.com/bmaltais)
+- Added weighted prompt support contributed by
+  [xraxra](https://github.com/xraxra)
+- Example of using weighted prompts to tweak a demonic figure contributed by
+  [bmaltais](https://github.com/bmaltais)
 
 ---
 
 ## v1.05 <small>(22 August 2022 - after the drop)</small>
 
-- Filenames now use the following formats:
-  000010.95183149.png -- Two files produced by the same command (e.g. -n2),
-  000010.26742632.png -- distinguished by a different seed.
+- Filenames now use the following formats: 000010.95183149.png -- Two files
+  produced by the same command (e.g. -n2), 000010.26742632.png -- distinguished
+  by a different seed.
 
   000011.455191342.01.png -- Two files produced by the same command using
   000011.455191342.02.png -- a batch size>1 (e.g. -b2). They have the same seed.
 
-  000011.4160627868.grid#1-4.png -- a grid of four images (-g); the whole grid can
-  be regenerated with the indicated key
+  000011.4160627868.grid#1-4.png -- a grid of four images (-g); the whole grid
+  can be regenerated with the indicated key
 
 - It should no longer be possible for one image to overwrite another
-- You can use the "cd" and "pwd" commands at the invoke> prompt to set and retrieve
-  the path of the output directory.
+- You can use the "cd" and "pwd" commands at the invoke> prompt to set and
+  retrieve the path of the output directory.
 
 ---
 
@@ -164,26 +557,28 @@ title: Changelog
 
 ## v1.03 <small>(22 August 2022)</small>
 
-- The original txt2img and img2img scripts from the CompViz repository have been moved into
-  a subfolder named "orig_scripts", to reduce confusion.
+- The original txt2img and img2img scripts from the CompViz repository have been
+  moved into a subfolder named "orig_scripts", to reduce confusion.
 
 ---
 
 ## v1.02 <small>(21 August 2022)</small>
 
-- A copy of the prompt and all of its switches and options is now stored in the corresponding
-  image in a tEXt metadata field named "Dream". You can read the prompt using scripts/images2prompt.py,
-  or an image editor that allows you to explore the full metadata.
-  **Please run "conda env update" to load the k_lms dependencies!!**
+- A copy of the prompt and all of its switches and options is now stored in the
+  corresponding image in a tEXt metadata field named "Dream". You can read the
+  prompt using scripts/images2prompt.py, or an image editor that allows you to
+  explore the full metadata. **Please run "conda env update" to load the k_lms
+  dependencies!!**
 
 ---
 
 ## v1.01 <small>(21 August 2022)</small>
 
-- added k_lms sampling.
-  **Please run "conda env update" to load the k_lms dependencies!!**
-- use half precision arithmetic by default, resulting in faster execution and lower memory requirements
-  Pass argument --full_precision to invoke.py to get slower but more accurate image generation
+- added k_lms sampling. **Please run "conda env update" to load the k_lms
+  dependencies!!**
+- use half precision arithmetic by default, resulting in faster execution and
+  lower memory requirements Pass argument --full_precision to invoke.py to get
+  slower but more accurate image generation
 
 ---
 

docs/contributing/ARCHITECTURE.md

@@ -0,0 +1,93 @@
+# Invoke.AI Architecture
+
+```mermaid
+flowchart TB
+
+  subgraph apps[Applications]
+    webui[WebUI]
+    cli[CLI]
+
+  subgraph webapi[Web API]
+    api[HTTP API]
+    sio[Socket.IO]
+  end
+
+  end
+
+  subgraph invoke[Invoke]
+    direction LR
+    invoker
+    services
+    sessions
+    invocations
+  end
+
+  subgraph core[AI Core]
+    Generate
+  end
+
+  webui --> webapi
+  webapi --> invoke
+  cli --> invoke
+
+  invoker --> services & sessions
+  invocations --> services
+  sessions --> invocations
+
+  services --> core
+
+  %% Styles
+  classDef sg fill:#5028C8,font-weight:bold,stroke-width:2,color:#fff,stroke:#14141A
+  classDef default stroke-width:2px,stroke:#F6B314,color:#fff,fill:#14141A
+
+  class apps,webapi,invoke,core sg
+
+```
+
+## Applications
+
+Applications are built on top of the invoke framework. They should construct `invoker` and then interact through it. They should avoid interacting directly with core code in order to support a variety of configurations.
+
+### Web UI
+
+The Web UI is built on top of an HTTP API built with [FastAPI](https://fastapi.tiangolo.com/) and [Socket.IO](https://socket.io/). The frontend code is found in `/frontend` and the backend code is found in `/ldm/invoke/app/api_app.py` and `/ldm/invoke/app/api/`. The code is further organized as such:
+
+| Component | Description |
+| --- | --- |
+| api_app.py | Sets up the API app, annotates the OpenAPI spec with additional data, and runs the API |
+| dependencies | Creates all invoker services and the invoker, and provides them to the API |
+| events | An eventing system that could in the future be adapted to support horizontal scale-out |
+| sockets | The Socket.IO interface - handles listening to and emitting session events (events are defined in the events service module) |
+| routers | API definitions for different areas of API functionality |
+
+### CLI
+
+The CLI is built automatically from invocation metadata, and also supports invocation piping and auto-linking. Code is available in `/ldm/invoke/app/cli_app.py`.
+
+## Invoke
+
+The Invoke framework provides the interface to the underlying AI systems and is built with flexibility and extensibility in mind. There are four major concepts: invoker, sessions, invocations, and services.
+
+### Invoker
+
+The invoker (`/ldm/invoke/app/services/invoker.py`) is the primary interface through which applications interact with the framework. Its primary purpose is to create, manage, and invoke sessions. It also maintains two sets of services:
+- **invocation services**, which are used by invocations to interact with core functionality.
+- **invoker services**, which are used by the invoker to manage sessions and manage the invocation queue.
+
+### Sessions
+
+Invocations and links between them form a graph, which is maintained in a session. Sessions can be queued for invocation, which will execute their graph (either the next ready invocation, or all invocations). Sessions also maintain execution history for the graph (including storage of any outputs). An invocation may be added to a session at any time, and there is capability to add and entire graph at once, as well as to automatically link new invocations to previous invocations. Invocations can not be deleted or modified once added.
+
+The session graph does not support looping. This is left as an application problem to prevent additional complexity in the graph.
+
+### Invocations
+
+Invocations represent individual units of execution, with inputs and outputs. All invocations are located in `/ldm/invoke/app/invocations`, and are all automatically discovered and made available in the applications. These are the primary way to expose new functionality in Invoke.AI, and the [implementation guide](INVOCATIONS.md) explains how to add new invocations.
+
+### Services
+
+Services provide invocations access AI Core functionality and other necessary functionality (e.g. image storage). These are available in `/ldm/invoke/app/services`. As a general rule, new services should provide an interface as an abstract base class, and may provide a lightweight local implementation by default in their module. The goal for all services should be to enable the usage of different implementations (e.g. using cloud storage for image storage), but should not load any module dependencies unless that implementation has been used (i.e. don't import anything that won't be used, especially if it's expensive to import).
+
+## AI Core
+
+The AI Core is represented by the rest of the code base (i.e. the code outside of `/ldm/invoke/app/`).

docs/contributing/INVOCATIONS.md

@@ -0,0 +1,202 @@
+# Invocations
+
+Invocations represent a single operation, its inputs, and its outputs. These
+operations and their outputs can be chained together to generate and modify
+images.
+
+## Creating a new invocation
+
+To create a new invocation, either find the appropriate module file in
+`/ldm/invoke/app/invocations` to add your invocation to, or create a new one in
+that folder. All invocations in that folder will be discovered and made
+available to the CLI and API automatically. Invocations make use of
+[typing](https://docs.python.org/3/library/typing.html) and
+[pydantic](https://pydantic-docs.helpmanual.io/) for validation and integration
+into the CLI and API.
+
+An invocation looks like this:
+
+```py
+class UpscaleInvocation(BaseInvocation):
+    """Upscales an image."""
+    type: Literal['upscale'] = 'upscale'
+
+    # Inputs
+    image: Union[ImageField,None] = Field(description="The input image")
+    strength: float               = Field(default=0.75, gt=0, le=1, description="The strength")
+    level: Literal[2,4]           = Field(default=2, description = "The upscale level")
+
+    def invoke(self, context: InvocationContext) -> ImageOutput:
+        image = context.services.images.get(self.image.image_type, self.image.image_name)
+        results = context.services.generate.upscale_and_reconstruct(
+            image_list     = [[image, 0]],
+            upscale        = (self.level, self.strength),
+            strength       = 0.0, # GFPGAN strength
+            save_original  = False,
+            image_callback = None,
+        )
+
+        # Results are image and seed, unwrap for now
+        # TODO: can this return multiple results?
+        image_type = ImageType.RESULT
+        image_name = context.services.images.create_name(context.graph_execution_state_id, self.id)
+        context.services.images.save(image_type, image_name, results[0][0])
+        return ImageOutput(
+            image = ImageField(image_type = image_type, image_name = image_name)
+        )
+```
+
+Each portion is important to implement correctly.
+
+### Class definition and type
+
+```py
+class UpscaleInvocation(BaseInvocation):
+    """Upscales an image."""
+    type: Literal['upscale'] = 'upscale'
+```
+
+All invocations must derive from `BaseInvocation`. They should have a docstring
+that declares what they do in a single, short line. They should also have a
+`type` with a type hint that's `Literal["command_name"]`, where `command_name`
+is what the user will type on the CLI or use in the API to create this
+invocation. The `command_name` must be unique. The `type` must be assigned to
+the value of the literal in the type hint.
+
+### Inputs
+
+```py
+    # Inputs
+    image: Union[ImageField,None] = Field(description="The input image")
+    strength: float               = Field(default=0.75, gt=0, le=1, description="The strength")
+    level: Literal[2,4]           = Field(default=2, description="The upscale level")
+```
+
+Inputs consist of three parts: a name, a type hint, and a `Field` with default,
+description, and validation information. For example:
+
+| Part      | Value                                                         | Description                                                                                                               |
+| --------- | ------------------------------------------------------------- | ------------------------------------------------------------------------------------------------------------------------- |
+| Name      | `strength`                                                    | This field is referred to as `strength`                                                                                   |
+| Type Hint | `float`                                                       | This field must be of type `float`                                                                                        |
+| Field     | `Field(default=0.75, gt=0, le=1, description="The strength")` | The default value is `0.75`, the value must be in the range (0,1], and help text will show "The strength" for this field. |
+
+Notice that `image` has type `Union[ImageField,None]`. The `Union` allows this
+field to be parsed with `None` as a value, which enables linking to previous
+invocations. All fields should either provide a default value or allow `None` as
+a value, so that they can be overwritten with a linked output from another
+invocation.
+
+The special type `ImageField` is also used here. All images are passed as
+`ImageField`, which protects them from pydantic validation errors (since images
+only ever come from links).
+
+Finally, note that for all linking, the `type` of the linked fields must match.
+If the `name` also matches, then the field can be **automatically linked** to a
+previous invocation by name and matching.
+
+### Invoke Function
+
+```py
+    def invoke(self, context: InvocationContext) -> ImageOutput:
+        image = context.services.images.get(self.image.image_type, self.image.image_name)
+        results = context.services.generate.upscale_and_reconstruct(
+            image_list     = [[image, 0]],
+            upscale        = (self.level, self.strength),
+            strength       = 0.0, # GFPGAN strength
+            save_original  = False,
+            image_callback = None,
+        )
+
+        # Results are image and seed, unwrap for now
+        image_type = ImageType.RESULT
+        image_name = context.services.images.create_name(context.graph_execution_state_id, self.id)
+        context.services.images.save(image_type, image_name, results[0][0])
+        return ImageOutput(
+            image = ImageField(image_type = image_type, image_name = image_name)
+        )
+```
+
+The `invoke` function is the last portion of an invocation. It is provided an
+`InvocationContext` which contains services to perform work as well as a
+`session_id` for use as needed. It should return a class with output values that
+derives from `BaseInvocationOutput`.
+
+Before being called, the invocation will have all of its fields set from
+defaults, inputs, and finally links (overriding in that order).
+
+Assume that this invocation may be running simultaneously with other
+invocations, may be running on another machine, or in other interesting
+scenarios. If you need functionality, please provide it as a service in the
+`InvocationServices` class, and make sure it can be overridden.
+
+### Outputs
+
+```py
+class ImageOutput(BaseInvocationOutput):
+    """Base class for invocations that output an image"""
+    type: Literal['image'] = 'image'
+
+    image: ImageField = Field(default=None, description="The output image")
+```
+
+Output classes look like an invocation class without the invoke method. Prefer
+to use an existing output class if available, and prefer to name inputs the same
+as outputs when possible, to promote automatic invocation linking.
+
+## Schema Generation
+
+Invocation, output and related classes are used to generate an OpenAPI schema.
+
+### Required Properties
+
+The schema generation treat all properties with default values as optional. This
+makes sense internally, but when when using these classes via the generated
+schema, we end up with e.g. the `ImageOutput` class having its `image` property
+marked as optional.
+
+We know that this property will always be present, so the additional logic
+needed to always check if the property exists adds a lot of extraneous cruft.
+
+To fix this, we can leverage `pydantic`'s
+[schema customisation](https://docs.pydantic.dev/usage/schema/#schema-customization)
+to mark properties that we know will always be present as required.
+
+Here's that `ImageOutput` class, without the needed schema customisation:
+
+```python
+class ImageOutput(BaseInvocationOutput):
+    """Base class for invocations that output an image"""
+
+    type: Literal["image"] = "image"
+    image:      ImageField = Field(default=None, description="The output image")
+```
+
+The generated OpenAPI schema, and all clients/types generated from it, will have
+the `type` and `image` properties marked as optional, even though we know they
+will always have a value by the time we can interact with them via the API.
+
+Here's the same class, but with the schema customisation added:
+
+```python
+class ImageOutput(BaseInvocationOutput):
+    """Base class for invocations that output an image"""
+
+    type: Literal["image"] = "image"
+    image:      ImageField = Field(default=None, description="The output image")
+
+    class Config:
+        schema_extra = {
+            'required': [
+                'type',
+                'image',
+            ]
+        }
+```
+
+The resultant schema (and any API client or types generated from it) will now
+have see `type` as string literal `"image"` and `image` as an `ImageField`
+object.
+
+See this `pydantic` issue for discussion on this solution:
+<https://github.com/pydantic/pydantic/discussions/4577>

docs/contributing/LOCAL_DEVELOPMENT.md

@@ -0,0 +1,83 @@
+# Local Development
+
+If you are looking to contribute you will need to have a local development
+environment. See the
+[Developer Install](../installation/020_INSTALL_MANUAL.md#developer-install) for
+full details.
+
+Broadly this involves cloning the repository, installing the pre-reqs, and
+InvokeAI (in editable form). Assuming this is working, choose your area of
+focus.
+
+## Documentation
+
+We use [mkdocs](https://www.mkdocs.org) for our documentation with the
+[material theme](https://squidfunk.github.io/mkdocs-material/). Documentation is
+written in markdown files under the `./docs` folder and then built into a static
+website for hosting with GitHub Pages at
+[invoke-ai.github.io/InvokeAI](https://invoke-ai.github.io/InvokeAI).
+
+To contribute to the documentation you'll need to install the dependencies. Note
+the use of `"`.
+
+```zsh
+pip install ".[docs]"
+```
+
+Now, to run the documentation locally with hot-reloading for changes made.
+
+```zsh
+mkdocs serve
+```
+
+You'll then be prompted to connect to `http://127.0.0.1:8080` in order to
+access.
+
+## Backend
+
+The backend is contained within the `./invokeai/backend` folder structure. To
+get started however please install the development dependencies.
+
+From the root of the repository run the following command. Note the use of `"`.
+
+```zsh
+pip install ".[test]"
+```
+
+This in an optional group of packages which is defined within the
+`pyproject.toml` and will be required for testing the changes you make the the
+code.
+
+### Running Tests
+
+We use [pytest](https://docs.pytest.org/en/7.2.x/) for our test suite. Tests can
+be found under the `./tests` folder and can be run with a single `pytest`
+command. Optionally, to review test coverage you can append `--cov`.
+
+```zsh
+pytest --cov
+```
+
+Test outcomes and coverage will be reported in the terminal. In addition a more
+detailed report is created in both XML and HTML format in the `./coverage`
+folder. The HTML one in particular can help identify missing statements
+requiring tests to ensure coverage. This can be run by opening
+`./coverage/html/index.html`.
+
+For example.
+
+```zsh
+pytest --cov; open ./coverage/html/index.html
+```
+
+??? info "HTML coverage report output"
+
+    ![html-overview](../assets/contributing/html-overview.png)
+
+    ![html-detail](../assets/contributing/html-detail.png)
+
+## Front End
+
+<!--#TODO: get input from blessedcoolant here, for the moment inserted the frontend README via snippets extension.-->
+
+--8<-- "invokeai/frontend/web/README.md"

docs/features/CHANGELOG.md

@@ -1,143 +0,0 @@
----
-title: Changelog
----
-
-# :octicons-log-16: Changelog
-
-## v1.13
-
-- Supports a Google Colab notebook for a standalone server running on Google
-  hardware [Arturo Mendivil](https://github.com/artmen1516)
-- WebUI supports GFPGAN/ESRGAN facial reconstruction and upscaling
-  [Kevin Gibbons](https://github.com/bakkot)
-- WebUI supports incremental display of in-progress images during generation
-  [Kevin Gibbons](https://github.com/bakkot)
-- Output directory can be specified on the invoke> command line.
-- The grid was displaying duplicated images when not enough images to fill the
-  final row [Muhammad Usama](https://github.com/SMUsamaShah)
-- Can specify --grid on invoke.py command line as the default.
-- Miscellaneous internal bug and stability fixes.
-
----
-
-## v1.12 <small>(28 August 2022)</small>
-
-- Improved file handling, including ability to read prompts from standard input.
-  (kudos to [Yunsaki](https://github.com/yunsaki)
-- The web server is now integrated with the invoke.py script. Invoke by adding
-  --web to the invoke.py command arguments.
-- Face restoration and upscaling via GFPGAN and Real-ESGAN are now automatically
-  enabled if the GFPGAN directory is located as a sibling to Stable Diffusion.
-  VRAM requirements are modestly reduced. Thanks to both
-  [Blessedcoolant](https://github.com/blessedcoolant) and
-  [Oceanswave](https://github.com/oceanswave) for their work on this.
-- You can now swap samplers on the invoke> command line.
-  [Blessedcoolant](https://github.com/blessedcoolant)
-
----
-
-## v1.11 <small>(26 August 2022)</small>
-
-- NEW FEATURE: Support upscaling and face enhancement using the GFPGAN module.
-  (kudos to [Oceanswave](https://github.com/Oceanswave))
-- You now can specify a seed of -1 to use the previous image's seed, -2 to use
-  the seed for the image generated before that, etc. Seed memory only extends
-  back to the previous command, but will work on all images generated with the
-  -n# switch.
-- Variant generation support temporarily disabled pending more general solution.
-- Created a feature branch named **yunsaki-morphing-invoke** which adds
-  experimental support for iteratively modifying the prompt and its parameters.
-  Please
-  see[ Pull Request #86](https://github.com/lstein/stable-diffusion/pull/86) for
-  a synopsis of how this works. Note that when this feature is eventually added
-  to the main branch, it will may be modified significantly.
-
----
-
-## v1.10 <small>(25 August 2022)</small>
-
-- A barebones but fully functional interactive web server for online generation
-  of txt2img and img2img.
-
----
-
-## v1.09 <small>(24 August 2022)</small>
-
-- A new -v option allows you to generate multiple variants of an initial image
-  in img2img mode. (kudos to [Oceanswave](https://github.com/Oceanswave).
-- [See this discussion in the PR for examples and details on use](https://github.com/lstein/stable-diffusion/pull/71#issuecomment-1226700810))
-- Added ability to personalize text to image generation (kudos to
-  [Oceanswave](https://github.com/Oceanswave) and
-  [nicolai256](https://github.com/nicolai256))
-- Enabled all of the samplers from k_diffusion
-
----
-
-## v1.08 <small>(24 August 2022)</small>
-
-- Escape single quotes on the invoke> command before trying to parse. This avoids
-  parse errors.
-- Removed instruction to get Python3.8 as first step in Windows install.
-  Anaconda3 does it for you.
-- Added bounds checks for numeric arguments that could cause crashes.
-- Cleaned up the copyright and license agreement files.
-
----
-
-## v1.07 <small>(23 August 2022)</small>
-
-- Image filenames will now never fill gaps in the sequence, but will be assigned
-  the next higher name in the chosen directory. This ensures that the alphabetic
-  and chronological sort orders are the same.
-
----
-
-## v1.06 <small>(23 August 2022)</small>
-
-- Added weighted prompt support contributed by
-  [xraxra](https://github.com/xraxra)
-- Example of using weighted prompts to tweak a demonic figure contributed by
-  [bmaltais](https://github.com/bmaltais)
-
----
-
-## v1.05 <small>(22 August 2022 - after the drop)</small>
-
-- Filenames now use the following formats: 000010.95183149.png -- Two files
-  produced by the same command (e.g. -n2), 000010.26742632.png -- distinguished
-  by a different seed.
-    000011.455191342.01.png -- Two files produced by the same command using
-    000011.455191342.02.png -- a batch size>1 (e.g. -b2). They have the same seed.
-    000011.4160627868.grid#1-4.png -- a grid of four images (-g); the whole grid
-  can be regenerated with the indicated key
-
-- It should no longer be possible for one image to overwrite another
-- You can use the "cd" and "pwd" commands at the invoke> prompt to set and
-  retrieve the path of the output directory.
-
-## v1.04 <small>(22 August 2022 - after the drop)</small>
-
-- Updated README to reflect installation of the released weights.
-- Suppressed very noisy and inconsequential warning when loading the frozen CLIP
-  tokenizer.
-
-## v1.03 <small>(22 August 2022)</small>
-
-- The original txt2img and img2img scripts from the CompViz repository have been
-  moved into a subfolder named "orig_scripts", to reduce confusion.
-
-## v1.02 <small>(21 August 2022)</small>
-
-- A copy of the prompt and all of its switches and options is now stored in the
-  corresponding image in a tEXt metadata field named "Dream". You can read the
-  prompt using scripts/images2prompt.py, or an image editor that allows you to
-  explore the full metadata. **Please run "conda env update -f environment.yaml"
-  to load the k_lms dependencies!!**
-
-## v1.01 <small>(21 August 2022)</small>
-
-- added k_lms sampling. **Please run "conda env update -f environment.yaml" to
-  load the k_lms dependencies!!**
-- use half precision arithmetic by default, resulting in faster execution and
-  lower memory requirements Pass argument --full_precision to invoke.py to get
-  slower but more accurate image generation

docs/features/CLI.md

@@ -1,45 +1,56 @@
 ---
-title: CLI
-hide:
-  - toc
+title: Command-Line Interface
 ---
 
 # :material-bash: CLI
 
 ## **Interactive Command Line Interface**
 
-The `invoke.py` script, located in `scripts/`, provides an interactive
-interface to image generation similar to the "invoke mothership" bot that Stable
-AI provided on its Discord server.
+The InvokeAI command line interface (CLI) provides scriptable access
+to InvokeAI's features.Some advanced features are only available
+through the CLI, though they eventually find their way into the WebUI.
 
-Unlike the `txt2img.py` and `img2img.py` scripts provided in the original
-[CompVis/stable-diffusion](https://github.com/CompVis/stable-diffusion) source
-code repository, the time-consuming initialization of the AI model
-initialization only happens once. After that image generation from the
-command-line interface is very fast.
+The CLI is accessible from the `invoke.sh`/`invoke.bat` launcher by
+selecting option (1). Alternatively, it can be launched directly from
+the command line by activating the InvokeAI environment and giving the
+command:
+
+```bash
+invokeai
+```
+
+After some startup messages, you will be presented with the `invoke> `
+prompt. Here you can type prompts to generate images and issue other
+commands to load and manipulate generative models. The CLI has a large
+number of command-line options that control its behavior. To get a
+concise summary of the options, call `invokeai` with the `--help` argument:
+
+```bash
+invokeai --help
+```
 
 The script uses the readline library to allow for in-line editing, command
 history (++up++ and ++down++), autocompletion, and more. To help keep track of
 which prompts generated which images, the script writes a log file of image
 names and prompts to the selected output directory.
 
-In addition, as of version 1.02, it also writes the prompt into the PNG file's
-metadata where it can be retrieved using `scripts/images2prompt.py`
-
-The script is confirmed to work on Linux, Windows and Mac systems.
-
-!!! note
-
-    This script runs from the command-line or can be used as a Web application. The Web GUI is
-    currently rudimentary, but a much better replacement is on its way.
+Here is a typical session
 
 ```bash
-(invokeai) ~/stable-diffusion$ python3 ./scripts/invoke.py
+PS1:C:\Users\fred> invokeai
 * Initializing, be patient...
-Loading model from models/ldm/text2img-large/model.ckpt
-(...more initialization messages...)
-
-* Initialization done! Awaiting your command...
+* Initializing, be patient...
+>> Initialization file /home/lstein/invokeai/invokeai.init found. Loading...
+>> Internet connectivity is True
+>> InvokeAI, version 2.3.0-rc5
+>> InvokeAI runtime directory is "/home/lstein/invokeai"
+>> GFPGAN Initialized
+>> CodeFormer Initialized
+>> ESRGAN Initialized
+>> Using device_type cuda
+>> xformers memory-efficient attention is available and enabled
+     (...more initialization messages...)
+* Initialization done! Awaiting your command (-h for help, 'q' to quit)
 invoke> ashley judd riding a camel -n2 -s150
 Outputs:
    outputs/img-samples/00009.png: "ashley judd riding a camel" -n2 -s150 -S 416354203
@@ -49,33 +60,22 @@ invoke> "there's a fly in my soup" -n6 -g
     outputs/img-samples/00011.png: "there's a fly in my soup" -n6 -g -S 2685670268
     seeds for individual rows: [2685670268, 1216708065, 2335773498, 822223658, 714542046, 3395302430]
 invoke> q
-
-# this shows how to retrieve the prompt stored in the saved image's metadata
-(invokeai) ~/stable-diffusion$ python ./scripts/images2prompt.py outputs/img_samples/*.png
-00009.png: "ashley judd riding a camel" -s150 -S 416354203
-00010.png: "ashley judd riding a camel" -s150 -S 1362479620
-00011.png: "there's a fly in my soup" -n6 -g -S 2685670268
 ```
 
 ![invoke-py-demo](../assets/dream-py-demo.png)
 
-The `invoke>` prompt's arguments are pretty much identical to those used in the
-Discord bot, except you don't need to type `!invoke` (it doesn't hurt if you do).
-A significant change is that creation of individual images is now the default
-unless `--grid` (`-g`) is given. A full list is given in
-[List of prompt arguments](#list-of-prompt-arguments).
-
 ## Arguments
 
-The script itself also recognizes a series of command-line switches that will
-change important global defaults, such as the directory for image outputs and
-the location of the model weight files.
+The script recognizes a series of command-line switches that will
+change important global defaults, such as the directory for image
+outputs and the location of the model weight files.
 
 ### List of arguments recognized at the command line
 
 These command-line arguments can be passed to `invoke.py` when you first run it
 from the Windows, Mac or Linux command line. Some set defaults that can be
-overridden on a per-prompt basis (see [List of prompt arguments](#list-of-prompt-arguments). Others
+overridden on a per-prompt basis (see
+[List of prompt arguments](#list-of-prompt-arguments). Others
 
 | Argument <img width="240" align="right"/> | Shortcut <img width="100" align="right"/> | Default <img width="320" align="right"/>       | Description                                                                                          |
 | ----------------------------------------- | ----------------------------------------- | ---------------------------------------------- | ---------------------------------------------------------------------------------------------------- |
@@ -83,33 +83,39 @@ overridden on a per-prompt basis (see [List of prompt arguments](#list-of-prompt
 | `--outdir <path>`                         | `-o<path>`                                | `outputs/img_samples`                          | Location for generated images.                                                                       |
 | `--prompt_as_dir`                         | `-p`                                      | `False`                                        | Name output directories using the prompt text.                                                       |
 | `--from_file <path>`                      |                                           | `None`                                         | Read list of prompts from a file. Use `-` to read from standard input                                |
-| `--model <modelname>`                     |                                           | `stable-diffusion-1.4`                         | Loads model specified in configs/models.yaml. Currently one of "stable-diffusion-1.4" or "laion400m" |
-| `--full_precision`                        | `-F`                                      | `False`                                        | Run in slower full-precision mode. Needed for Macintosh M1/M2 hardware and some older video cards.   |
-| `--png_compression <0-9>`                 | `-z<0-9>`                                 |  6                                             | Select level of compression for output files, from 0 (no compression) to 9 (max compression)         |
-| `--safety-checker`                        |                                           |  False                                         | Activate safety checker for NSFW and other potentially disturbing imagery                            |
+| `--model <modelname>`                     |                                           | `stable-diffusion-1.5`                         | Loads the initial model specified in configs/models.yaml. |
+| `--ckpt_convert `           |                                                         | `False`                                        | If provided both .ckpt and .safetensors files will be auto-converted into diffusers format in memory |
+| `--autoconvert <path>`                    |                          | `None`                                        | On startup, scan the indicated directory for new .ckpt/.safetensor files and automatically convert and import them |
+| `--precision`                             |                                           | `fp16`                                         | Provide `fp32` for full precision mode, `fp16` for half-precision. `fp32` needed for Macintoshes and some NVidia cards. |
+| `--png_compression <0-9>`                 | `-z<0-9>`                                 | `6`                                            | Select level of compression for output files, from 0 (no compression) to 9 (max compression)         |
+| `--safety-checker`                        |                                           | `False`                                        | Activate safety checker for NSFW and other potentially disturbing imagery                            |
+| `--patchmatch`, `--no-patchmatch`                 |                                   | `--patchmatch`                                        | Load/Don't load the PatchMatch inpainting extension    |
+| `--xformers`, `--no-xformers`                 |                                   | `--xformers`                                        | Load/Don't load the Xformers memory-efficient attention module (CUDA only)    |
 | `--web`                                   |                                           | `False`                                        | Start in web server mode                                                                             |
 | `--host <ip addr>`                        |                                           | `localhost`                                    | Which network interface web server should listen on. Set to 0.0.0.0 to listen on any.                |
 | `--port <port>`                           |                                           | `9090`                                         | Which port web server should listen for requests on.                                                 |
 | `--config <path>`                         |                                           | `configs/models.yaml`                          | Configuration file for models and their weights.                                                     |
 | `--iterations <int>`                      | `-n<int>`                                 | `1`                                            | How many images to generate per prompt.                                                              |
+| `--width <int>`                           | `-W<int>`                                 | `512`                                    | Width of generated image                                                                                                                                                                                                                         |
+| `--height <int>`                          | `-H<int>`                                 | `512`                                    | Height of generated image                                                                                                        | `--steps <int>`                           | `-s<int>`                                 | `50`                                     | How many steps of refinement to apply                                                                                                                                                                                                            |
+| `--strength <float>`                      | `-s<float>` | `0.75`  | For img2img: how hard to try to match the prompt to the initial image. Ranges from 0.0-0.99, with higher values replacing the initial image completely. |
+| `--fit`                                   | `-F`        | `False` | For img2img: scale the init image to fit into the specified -H and -W dimensions                                                                             |
 | `--grid`                                  | `-g`                                      | `False`                                        | Save all image series as a grid rather than individually.                                            |
 | `--sampler <sampler>`                     | `-A<sampler>`                             | `k_lms`                                        | Sampler to use. Use `-h` to get list of available samplers.                                          |
 | `--seamless`                              |                                           | `False`                                        | Create interesting effects by tiling elements of the image.                                          |
 | `--embedding_path <path>`                 |                                           | `None`                                         | Path to pre-trained embedding manager checkpoints, for custom models                                 |
-| `--gfpgan_dir`                            |                                           | `src/gfpgan`                                   | Path to where GFPGAN is installed.                                                                   |
-| `--gfpgan_model_path`                     |                                           | `experiments/pretrained_models/GFPGANv1.4.pth` | Path to GFPGAN model file, relative to `--gfpgan_dir`.                                               |
+| `--gfpgan_model_path`                     |                                           | `experiments/pretrained_models/GFPGANv1.4.pth` | Path to GFPGAN model file.                                              |
 | `--free_gpu_mem`                          |                                           | `False`                                        | Free GPU memory after sampling, to allow image decoding and saving in low VRAM conditions            |
 | `--precision`                             |                                           | `auto`                                         | Set model precision, default is selected by device. Options: auto, float32, float16, autocast        |
 
-!!! warning deprecated
-
-    These arguments are deprecated but still work:
+!!! warning "These arguments are deprecated but still work"
 
     <div align="center" markdown>
 
     | Argument           |  Shortcut  |  Default            |  Description |
     |--------------------|------------|---------------------|--------------|
-    | `--weights <path>`   |            | `None`                | Pth to weights file; use `--model stable-diffusion-1.4` instead |
+    | `--full_precision`  |             | `False`                | Same as `--precision=fp32`|
+    | `--weights <path>`   |            | `None`                | Path to weights file; use `--model stable-diffusion-1.4` instead |
     | `--laion400m`        | `-l`         | `False`               | Use older LAION400m weights; use `--model=laion400m` instead |
 
     </div>
@@ -122,17 +128,54 @@ overridden on a per-prompt basis (see [List of prompt arguments](#list-of-prompt
       You can either double your slashes (ick): `C:\\path\\to\\my\\file`, or
       use Linux/Mac style forward slashes (better): `C:/path/to/my/file`.
 
+## The .invokeai initialization file
+
+To start up invoke.py with your preferred settings, place your desired
+startup options in a file in your home directory named `.invokeai` The
+file should contain the startup options as you would type them on the
+command line (`--steps=10 --grid`), one argument per line, or a
+mixture of both using any of the accepted command switch formats:
+
+!!! example "my unmodified initialization file"
+
+    ```bash title="~/.invokeai" linenums="1"
+    # InvokeAI initialization file
+    # This is the InvokeAI initialization file, which contains command-line default values.
+    # Feel free to edit. If anything goes wrong, you can re-initialize this file by deleting
+    # or renaming it and then running invokeai-configure again.
+
+    # The --root option below points to the folder in which InvokeAI stores its models, configs and outputs.
+    --root="/Users/mauwii/invokeai"
+
+    # the --outdir option controls the default location of image files.
+    --outdir="/Users/mauwii/invokeai/outputs"
+
+    # You may place other  frequently-used startup commands here, one or more per line.
+    # Examples:
+    # --web --host=0.0.0.0
+    # --steps=20
+    # -Ak_euler_a -C10.0
+    ```
+
+!!! note
+
+    The  initialization file only accepts the command line arguments.
+    There are additional arguments that you can provide on the `invoke>` command
+    line (such as `-n` or `--iterations`) that cannot be entered into this file.
+    Also be alert for empty blank lines at the end of the file, which will cause
+    an arguments error at startup time.
+
 ## List of prompt arguments
 
-After the invoke.py script initializes, it will present you with a
-`invoke>` prompt. Here you can enter information to generate images
-from text ([txt2img](#txt2img)), to embellish an existing image or sketch
+After the invoke.py script initializes, it will present you with a `invoke>`
+prompt. Here you can enter information to generate images from text
+([txt2img](#txt2img)), to embellish an existing image or sketch
 ([img2img](#img2img)), or to selectively alter chosen regions of the image
 ([inpainting](#inpainting)).
 
 ### txt2img
 
-!!! example
+!!! example ""
 
     ```bash
     invoke> waterfall and rainbow -W640 -H480
@@ -143,64 +186,67 @@ from text ([txt2img](#txt2img)), to embellish an existing image or sketch
 
 Here are the invoke> command that apply to txt2img:
 
-| Argument <img width="680" align="right"/> | Shortcut <img width="420" align="right"/> | Default <img width="480" align="right"/> | Description |
-|--------------------|------------|---------------------|--------------|
-| "my prompt"        |            |                    | Text prompt to use. The quotation marks are optional. |
-| --width <int>      | -W<int>   | 512                 | Width of generated image |
-| --height <int>     | -H<int>   | 512                 | Height of generated image |
-| --iterations <int> | -n<int>   | 1                   | How many images to generate from this prompt |
-| --steps <int>      | -s<int>   | 50                  | How many steps of refinement to apply |
-| --cfg_scale <float>| -C<float> | 7.5                 | How hard to try to match the prompt to the generated image; any number greater than 1.0 works, but the useful range is roughly 5.0 to 20.0 |
-| --seed <int>       | -S<int>   | None                | Set the random seed for the next series of images. This can be used to recreate an image generated previously.|
-| --sampler <sampler>| -A<sampler>| k_lms              | Sampler to use. Use -h to get list of available samplers. |
-| --karras_max <int> |           | 29                  | When using k_* samplers, set the maximum number of steps before shifting from using the Karras noise schedule (good for low step counts) to the LatentDiffusion noise schedule (good for high step counts) This value is sticky. [29] |
-| --hires_fix        |           |                     | Larger images often have duplication artefacts. This option suppresses duplicates by generating the image at low res, and then using img2img to increase the resolution |
-| --png_compression <0-9> | -z<0-9> |  6           | Select level of compression for output files, from 0 (no compression) to 9 (max compression)         |
-| --grid             | -g        | False               | Turn on grid mode to return a single image combining all the images generated by this prompt |
-| --individual       | -i        | True                | Turn off grid mode (deprecated; leave off --grid instead) |
-| --outdir <path>    |  -o<path> | outputs/img_samples  | Temporarily change the location of these images |
-| --seamless         |           | False               | Activate seamless tiling for interesting effects |
-| --seamless_axes    |           | x,y                 | Specify which axes to use circular convolution on. |
-| --log_tokenization | -t        | False               | Display a color-coded list of the parsed tokens derived from the prompt |
-| --skip_normalization| -x       | False               | Weighted subprompts will not be normalized. See [Weighted Prompts](./OTHER.md#weighted-prompts) |
-| --upscale <int> <float> | -U <int> <float> | -U 1 0.75| Upscale image by magnification factor (2, 4), and set strength of upscaling (0.0-1.0). If strength not set, will default to 0.75. |
-| --facetool_strength <float>  | -G <float> | -G0        | Fix faces (defaults to using the GFPGAN algorithm); argument indicates how hard the algorithm should try (0.0-1.0) |
-| --facetool <name> | -ft <name> | -ft gfpgan | Select face restoration algorithm to use: gfpgan, codeformer |
-| --codeformer_fidelity | -cf <float> | 0.75 | Used along with CodeFormer. Takes values between 0 and 1. 0 produces high quality but low accuracy. 1 produces high accuracy but low quality |
-| --save_original    | -save_orig| False               | When upscaling or fixing faces, this will cause the original image to be saved rather than replaced. |
-| --variation <float>  |-v<float>| 0.0                 | Add a bit of noise (0.0=none, 1.0=high) to the image in order to generate a series of variations. Usually used in combination with -S<seed> and -n<int> to generate a series a riffs on a starting image. See [Variations](./VARIATIONS.md). |
-| --with_variations <pattern> |    | None              | Combine two or more variations. See [Variations](./VARIATIONS.md) for now to use this. |
-| --save_intermediates <n>    |    | None              | Save the image from every nth step into an "intermediates" folder inside the output directory |
+| Argument <img width="680" align="right"/> | Shortcut <img width="420" align="right"/> | Default <img width="480" align="right"/> | Description                                                                                                                                                                                                                                      |
+| ----------------------------------------- | ----------------------------------------- | ---------------------------------------- | ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------ |
+| "my prompt"                               |                                           |                                          | Text prompt to use. The quotation marks are optional.                                                                                                                                                                                            |
+| `--width <int>`                           | `-W<int>`                                 | `512`                                    | Width of generated image                                                                                                                                                                                                                         |
+| `--height <int>`                          | `-H<int>`                                 | `512`                                    | Height of generated image                                                                                                                                                                                                                        |
+| `--iterations <int>`                      | `-n<int>`                                 | `1`                                      | How many images to generate from this prompt                                                                                                                                                                                                     |
+| `--steps <int>`                           | `-s<int>`                                 | `50`                                     | How many steps of refinement to apply                                                                                                                                                                                                            |
+| `--cfg_scale <float>`                     | `-C<float>`                               | `7.5`                                    | How hard to try to match the prompt to the generated image; any number greater than 1.0 works, but the useful range is roughly 5.0 to 20.0                                                                                                       |
+| `--seed <int>`                            | `-S<int>`                                 | `None`                                   | Set the random seed for the next series of images. This can be used to recreate an image generated previously.                                                                                                                                   |
+| `--sampler <sampler>`                     | `-A<sampler>`                             | `k_lms`                                  | Sampler to use. Use -h to get list of available samplers.                                                                                                                                                                                        |
+| `--karras_max <int>`                      |                                           | `29`                                     | When using k\_\* samplers, set the maximum number of steps before shifting from using the Karras noise schedule (good for low step counts) to the LatentDiffusion noise schedule (good for high step counts) This value is sticky. [29]          |
+| `--hires_fix`                             |                                           |                                          | Larger images often have duplication artefacts. This option suppresses duplicates by generating the image at low res, and then using img2img to increase the resolution                                                                          |
+| `--png_compression <0-9>`                 | `-z<0-9>`                                 | `6`                                      | Select level of compression for output files, from 0 (no compression) to 9 (max compression)                                                                                                                                                     |
+| `--grid`                                  | `-g`                                      | `False`                                  | Turn on grid mode to return a single image combining all the images generated by this prompt                                                                                                                                                     |
+| `--individual`                            | `-i`                                      | `True`                                   | Turn off grid mode (deprecated; leave off --grid instead)                                                                                                                                                                                        |
+| `--outdir <path>`                         | `-o<path>`                                | `outputs/img_samples`                    | Temporarily change the location of these images                                                                                                                                                                                                  |
+| `--seamless`                              |                                           | `False`                                  | Activate seamless tiling for interesting effects                                                                                                                                                                                                 |
+| `--seamless_axes`                         |                                           | `x,y`                                    | Specify which axes to use circular convolution on.                                                                                                                                                                                               |
+| `--log_tokenization`                      | `-t`                                      | `False`                                  | Display a color-coded list of the parsed tokens derived from the prompt                                                                                                                                                                          |
+| `--skip_normalization`                    | `-x`                                      | `False`                                  | Weighted subprompts will not be normalized. See [Weighted Prompts](./OTHER.md#weighted-prompts)                                                                                                                                                  |
+| `--upscale <int> <float>`                 | `-U <int> <float>`                        | `-U 1 0.75`                              | Upscale image by magnification factor (2, 4), and set strength of upscaling (0.0-1.0). If strength not set, will default to 0.75.                                                                                                                |
+| `--facetool_strength <float>`             | `-G <float> `                             | `-G0`                                    | Fix faces (defaults to using the GFPGAN algorithm); argument indicates how hard the algorithm should try (0.0-1.0)                                                                                                                               |
+| `--facetool <name>`                       | `-ft <name>`                              | `-ft gfpgan`                             | Select face restoration algorithm to use: gfpgan, codeformer                                                                                                                                                                                     |
+| `--codeformer_fidelity`                   | `-cf <float>`                             | `0.75`                                   | Used along with CodeFormer. Takes values between 0 and 1. 0 produces high quality but low accuracy. 1 produces high accuracy but low quality                                                                                                     |
+| `--save_original`                         | `-save_orig`                              | `False`                                  | When upscaling or fixing faces, this will cause the original image to be saved rather than replaced.                                                                                                                                             |
+| `--variation <float>`                     | `-v<float>`                               | `0.0`                                    | Add a bit of noise (0.0=none, 1.0=high) to the image in order to generate a series of variations. Usually used in combination with `-S<seed>` and `-n<int>` to generate a series a riffs on a starting image. See [Variations](./VARIATIONS.md). |
+| `--with_variations <pattern>`             |                                           | `None`                                   | Combine two or more variations. See [Variations](./VARIATIONS.md) for now to use this.                                                                                                                                                           |
+| `--save_intermediates <n>`                |                                           | `None`                                   | Save the image from every nth step into an "intermediates" folder inside the output directory                                                                                                                                                    |
+| `--h_symmetry_time_pct <float>`           |                                           | `None`                                   | Create symmetry along the X axis at the desired percent complete of the generation process. (Must be between 0.0 and 1.0; set to a very small number like 0.0001 for just after the first step of generation.)                                   |
+| `--v_symmetry_time_pct <float>`           |                                           | `None`                                   | Create symmetry along the Y axis at the desired percent complete of the generation process. (Must be between 0.0 and 1.0; set to a very small number like 0.0001 for just after the first step of generation.)                                   |
 
-Note that the width and height of the image must be multiples of
-64. You can provide different values, but they will be rounded down to
-the nearest multiple of 64.
+!!! note
 
+    the width and height of the image must be multiples of 64. You can
+    provide different values, but they will be rounded down to the nearest multiple
+    of 64.
 
-### This is an example of img2img:	
+!!! example "This is a example of img2img"
 
-~~~~
-invoke> waterfall and rainbow -I./vacation-photo.png -W640 -H480 --fit
-~~~~
+    ```bash
+    invoke> waterfall and rainbow -I./vacation-photo.png -W640 -H480 --fit
+    ```
 
-This will modify the indicated vacation photograph by making it more
-like the prompt. Results will vary greatly depending on what is in the
-image. We also ask to --fit the image into a box no bigger than
-640x480. Otherwise the image size will be identical to the provided
-photo and you may run out of memory if it is large.
+This will modify the indicated vacation photograph by making it more like the
+prompt. Results will vary greatly depending on what is in the image. We also ask
+to --fit the image into a box no bigger than 640x480. Otherwise the image size
+will be identical to the provided photo and you may run out of memory if it is
+large.
 
-In addition to the command-line options recognized by txt2img, img2img
-accepts additional options:
+In addition to the command-line options recognized by txt2img, img2img accepts
+additional options:
 
-| Argument <img width="160" align="right"/> |  Shortcut   |  Default        |  Description |
-|----------------------|-------------|-----------------|--------------|
-| `--init_img <path>`  | `-I<path>`  | `None`          | Path to the initialization image |
-| `--fit`              | `-F`        | `False`         | Scale the image to fit into the specified -H and -W dimensions |
-| `--strength <float>` | `-s<float>` | `0.75`          | How hard to try to match the prompt to the initial image. Ranges from 0.0-0.99, with higher values replacing the initial image completely.|
+| Argument <img width="160" align="right"/> | Shortcut    | Default | Description                                                                                                                                |
+| ----------------------------------------- | ----------- | ------- | ------------------------------------------------------------------------------------------------------------------------------------------ |
+| `--init_img <path>`                       | `-I<path>`  | `None`  | Path to the initialization image                                                                                                           |
+| `--fit`                                   | `-F`        | `False` | Scale the image to fit into the specified -H and -W dimensions                                                                             |
+| `--strength <float>`                      | `-s<float>` | `0.75`  | How hard to try to match the prompt to the initial image. Ranges from 0.0-0.99, with higher values replacing the initial image completely. |
 
 ### inpainting
 
-!!! example
+!!! example ""
 
     ```bash
     invoke> waterfall and rainbow -I./vacation-photo.png -M./vacation-mask.png -W640 -H480 --fit
@@ -213,73 +259,72 @@ accepts additional options:
     the pixels underneath when you create the transparent areas. See
     [Inpainting](./INPAINTING.md) for details.
 
-inpainting accepts all the arguments used for txt2img and img2img, as
-well as the --mask (-M) and --text_mask (-tm) arguments:
+inpainting accepts all the arguments used for txt2img and img2img, as well as
+the --mask (-M) and --text_mask (-tm) arguments:
 
-| Argument <img width="100" align="right"/> |  Shortcut  |  Default            |  Description |
-|--------------------|------------|---------------------|--------------|
-| `--init_mask <path>` | `-M<path>`   | `None`                |Path to an image the same size as the initial_image, with areas for inpainting made transparent.|
-| `--invert_mask   ` |                | False                 |If true, invert the mask so that transparent areas are opaque and vice versa.|
-| `--text_mask <prompt> [<float>]` | `-tm <prompt> [<float>]` | <none>  | Create a mask from a text prompt describing part of the image|
+| Argument <img width="100" align="right"/> | Shortcut                 | Default | Description                                                                                      |
+| ----------------------------------------- | ------------------------ | ------- | ------------------------------------------------------------------------------------------------ |
+| `--init_mask <path>`                      | `-M<path>`               | `None`  | Path to an image the same size as the initial_image, with areas for inpainting made transparent. |
+| `--invert_mask `                          |                          | False   | If true, invert the mask so that transparent areas are opaque and vice versa.                    |
+| `--text_mask <prompt> [<float>]`          | `-tm <prompt> [<float>]` | <none>  | Create a mask from a text prompt describing part of the image                                    |
 
-The mask may either be an image with transparent areas, in which case
-the inpainting will occur in the transparent areas only, or a black
-and white image, in which case all black areas will be painted into.
+The mask may either be an image with transparent areas, in which case the
+inpainting will occur in the transparent areas only, or a black and white image,
+in which case all black areas will be painted into.
 
-`--text_mask` (short form `-tm`) is a way to generate a mask using a
-text description of the part of the image to replace. For example, if
-you have an image of a breakfast plate with a bagel, toast and
-scrambled eggs, you can selectively mask the bagel and replace it with
-a piece of cake this way:
+`--text_mask` (short form `-tm`) is a way to generate a mask using a text
+description of the part of the image to replace. For example, if you have an
+image of a breakfast plate with a bagel, toast and scrambled eggs, you can
+selectively mask the bagel and replace it with a piece of cake this way:
 
-~~~
+```bash
 invoke> a piece of cake -I /path/to/breakfast.png -tm bagel
-~~~
+```
 
 The algorithm uses <a
-href="https://github.com/timojl/clipseg">clipseg</a> to classify
-different regions of the image. The classifier puts out a confidence
-score for each region it identifies. Generally regions that score
-above 0.5 are reliable, but if you are getting too much or too little
-masking you can adjust the threshold down (to get more mask), or up
-(to get less). In this example, by passing `-tm` a higher value, we
-are insisting on a more stringent classification.
+href="https://github.com/timojl/clipseg">clipseg</a> to classify different
+regions of the image. The classifier puts out a confidence score for each region
+it identifies. Generally regions that score above 0.5 are reliable, but if you
+are getting too much or too little masking you can adjust the threshold down (to
+get more mask), or up (to get less). In this example, by passing `-tm` a higher
+value, we are insisting on a more stringent classification.
 
-~~~
+```bash
 invoke> a piece of cake -I /path/to/breakfast.png -tm bagel 0.6
-~~~
+```
 
-# Other Commands
+### Custom Styles and Subjects
+
+You can load and use hundreds of community-contributed Textual
+Inversion models just by typing the appropriate trigger phrase. Please
+see [Concepts Library](CONCEPTS.md) for more details.
+
+## Other Commands
 
 The CLI offers a number of commands that begin with "!".
 
-## Postprocessing images
+### Postprocessing images
 
-To postprocess a file using face restoration or upscaling, use the
-`!fix` command.
+To postprocess a file using face restoration or upscaling, use the `!fix`
+command.
 
-### `!fix`
+#### `!fix`
 
-This command runs a post-processor on a previously-generated image. It
-takes a PNG filename or path and applies your choice of the `-U`, `-G`, or
-`--embiggen` switches in order to fix faces or upscale. If you provide a
-filename, the script will look for it in the current output
-directory. Otherwise you can provide a full or partial path to the
-desired file.
+This command runs a post-processor on a previously-generated image. It takes a
+PNG filename or path and applies your choice of the `-U`, `-G`, or `--embiggen`
+switches in order to fix faces or upscale. If you provide a filename, the script
+will look for it in the current output directory. Otherwise you can provide a
+full or partial path to the desired file.
 
 Some examples:
 
-!!! example ""
-
-    Upscale to 4X its original size and fix faces using codeformer:
+!!! example "Upscale to 4X its original size and fix faces using codeformer"
 
     ```bash
     invoke> !fix 0000045.4829112.png -G1 -U4 -ft codeformer
     ```
 
-!!! example ""
-
-    Use the GFPGAN algorithm to fix faces, then upscale to 3X using --embiggen:
+!!! example "Use the GFPGAN algorithm to fix faces, then upscale to 3X using --embiggen"
 
     ```bash
     invoke> !fix 0000045.4829112.png -G0.8 -ft gfpgan
@@ -288,138 +333,103 @@ Some examples:
     >> GFPGAN - Restoring Faces for image seed:4829112
     Outputs:
     [1] outputs/img-samples/000017.4829112.gfpgan-00.png: !fix "outputs/img-samples/0000045.4829112.png" -s 50 -S  -W 512 -H 512 -C 7.5 -A k_lms -G 0.8
+    ```
 
-### !mask
+#### `!mask`
 
-This command takes an image, a text prompt, and uses the `clipseg`
-algorithm to automatically generate a mask of the area that matches
-the text prompt. It is useful for debugging the text masking process
-prior to inpainting with the `--text_mask` argument. See
-[INPAINTING.md] for details.
+This command takes an image, a text prompt, and uses the `clipseg` algorithm to
+automatically generate a mask of the area that matches the text prompt. It is
+useful for debugging the text masking process prior to inpainting with the
+`--text_mask` argument. See [INPAINTING.md] for details.
 
-## Model selection and importation
+### Model selection and importation
 
 The CLI allows you to add new models on the fly, as well as to switch
-among them rapidly without leaving the script.
+among them rapidly without leaving the script. There are several
+different model formats, each described in the [Model Installation
+Guide](../installation/050_INSTALLING_MODELS.md).
 
-### !models
+#### `!models`
 
-This prints out a list of the models defined in `config/models.yaml'.
-The active model is bold-faced
+This prints out a list of the models defined in `config/models.yaml'. The active
+model is bold-faced
 
 Example:
-<pre>
-laion400m                 not loaded  <no description>
-<b>stable-diffusion-1.4          active  Stable Diffusion v1.4</b>
-waifu-diffusion           not loaded  Waifu Diffusion v1.3
-</pre>
-
-### !switch <model>
-
-This quickly switches from one model to another without leaving the 
-CLI script. `invoke.py` uses a memory caching system; once a model
-has been loaded, switching back and forth is quick. The following
-example shows this in action. Note how the second column of the 
-`!models` table changes to `cached` after a model is first loaded,
-and that the long initialization step is not needed when loading
-a cached model.
 
 <pre>
-invoke> !models
-laion400m                 not loaded  <no description>
-<b>stable-diffusion-1.4          cached  Stable Diffusion v1.4</b>
-waifu-diffusion               active  Waifu Diffusion v1.3
-
-invoke> !switch waifu-diffusion
->> Caching model stable-diffusion-1.4 in system RAM
->> Loading waifu-diffusion from models/ldm/stable-diffusion-v1/model-epoch08-float16.ckpt
-   | LatentDiffusion: Running in eps-prediction mode
-   | DiffusionWrapper has 859.52 M params.
-   | Making attention of type 'vanilla' with 512 in_channels
-   | Working with z of shape (1, 4, 32, 32) = 4096 dimensions.
-   | Making attention of type 'vanilla' with 512 in_channels
-   | Using faster float16 precision
->> Model loaded in 18.24s
->> Max VRAM used to load the model: 2.17G 
->> Current VRAM usage:2.17G
->> Setting Sampler to k_lms
-
-invoke> !models
-laion400m                 not loaded  <no description>
-stable-diffusion-1.4          cached  Stable Diffusion v1.4
-<b>waifu-diffusion               active  Waifu Diffusion v1.3</b>
-
-invoke> !switch stable-diffusion-1.4
->> Caching model waifu-diffusion in system RAM
->> Retrieving model stable-diffusion-1.4 from system RAM cache
->> Setting Sampler to k_lms
-
-invoke> !models
-laion400m                 not loaded  <no description>
-<b>stable-diffusion-1.4          active  Stable Diffusion v1.4</b>
-waifu-diffusion               cached  Waifu Diffusion v1.3
+inpainting-1.5            not loaded  Stable Diffusion inpainting model
+<b>stable-diffusion-1.5          active  Stable Diffusion v1.5</b>
+waifu-diffusion           not loaded  Waifu Diffusion v1.4
 </pre>
 
-### !import_model <path/to/model/weights>
+#### `!switch <model>`
 
-This command imports a new model weights file into InvokeAI, makes it
-available for image generation within the script, and writes out the
-configuration for the model into `config/models.yaml` for use in 
-subsequent sessions.
+This quickly switches from one model to another without leaving the CLI script.
+`invoke.py` uses a memory caching system; once a model has been loaded,
+switching back and forth is quick. The following example shows this in action.
+Note how the second column of the `!models` table changes to `cached` after a
+model is first loaded, and that the long initialization step is not needed when
+loading a cached model.
 
-Provide `!import_model` with the path to a weights file ending in
-`.ckpt`.  If you type a partial path and press tab, the CLI will
-autocomplete. Although it will also autocomplete to `.vae` files,
-these are not currenty supported (but will be soon).
+#### `!import_model <hugging_face_repo_ID>`
 
-When you hit return, the CLI will prompt you to fill in additional
-information about the model, including the short name you wish to use
-for it with the `!switch` command, a brief description of the model,
-the default image width and height to use with this model, and the
-model's configuration file. The latter three fields are automatically
-filled with reasonable defaults. In the example below, the bold-faced
-text shows what the user typed in with the exception of the width,
-height and configuration file paths, which were filled in
+This imports and installs a `diffusers`-style model that is stored on
+the [HuggingFace Web Site](https://huggingface.co). You can look up
+any [Stable Diffusion diffusers
+model](https://huggingface.co/models?library=diffusers) and install it
+with a command like the following:
+
+```bash
+!import_model prompthero/openjourney
+```
+
+#### `!import_model <path/to/diffusers/directory>`
+
+If you have a copy of a `diffusers`-style model saved to disk, you can
+import it by passing the path to model's top-level directory.
+
+#### `!import_model <url>`
+
+For a `.ckpt` or `.safetensors` file, if you have a direct download
+URL for the file, you can provide it to `!import_model` and the file
+will be downloaded and installed for you.
+
+#### `!import_model <path/to/model/weights.ckpt>`
+
+This command imports a new model weights file into InvokeAI, makes it available
+for image generation within the script, and writes out the configuration for the
+model into `config/models.yaml` for use in subsequent sessions.
+
+Provide `!import_model` with the path to a weights file ending in `.ckpt`. If
+you type a partial path and press tab, the CLI will autocomplete. Although it
+will also autocomplete to `.vae` files, these are not currenty supported (but
+will be soon).
+
+When you hit return, the CLI will prompt you to fill in additional information
+about the model, including the short name you wish to use for it with the
+`!switch` command, a brief description of the model, the default image width and
+height to use with this model, and the model's configuration file. The latter
+three fields are automatically filled with reasonable defaults. In the example
+below, the bold-faced text shows what the user typed in with the exception of
+the width, height and configuration file paths, which were filled in
 automatically.
 
-Example:
+#### `!import_model <path/to/directory_of_models>`
 
-<pre>
-invoke> <b>!import_model models/ldm/stable-diffusion-v1/model-epoch08-float16.ckpt</b>
->> Model import in process. Please enter the values needed to configure this model:
+If you provide the path of a directory that contains one or more
+`.ckpt` or `.safetensors` files, the CLI will scan the directory and
+interactively offer to import the models it finds there. Also see the
+`--autoconvert` command-line option.
 
-Name for this model: <b>waifu-diffusion</b>
-Description of this model: <b>Waifu Diffusion v1.3</b>
-Configuration file for this model: <b>configs/stable-diffusion/v1-inference.yaml</b>
-Default image width: <b>512</b>
-Default image height: <b>512</b>
->> New configuration:
-waifu-diffusion:
-  config: configs/stable-diffusion/v1-inference.yaml
-  description: Waifu Diffusion v1.3
-  height: 512
-  weights: models/ldm/stable-diffusion-v1/model-epoch08-float16.ckpt
-  width: 512
-OK to import [n]? <b>y</b>
->> Caching model stable-diffusion-1.4 in system RAM
->> Loading waifu-diffusion from models/ldm/stable-diffusion-v1/model-epoch08-float16.ckpt
-   | LatentDiffusion: Running in eps-prediction mode
-   | DiffusionWrapper has 859.52 M params.
-   | Making attention of type 'vanilla' with 512 in_channels
-   | Working with z of shape (1, 4, 32, 32) = 4096 dimensions.
-   | Making attention of type 'vanilla' with 512 in_channels
-   | Using faster float16 precision
-invoke> 
-</pre>
+#### `!edit_model <name_of_model>`
 
-###!edit_model <name_of_model>
-
-The `!edit_model` command can be used to modify a model that is
-already defined in `config/models.yaml`. Call it with the short
-name of the model you wish to modify, and it will allow you to
-modify the model's `description`, `weights` and other fields.
+The `!edit_model` command can be used to modify a model that is already defined
+in `config/models.yaml`. Call it with the short name of the model you wish to
+modify, and it will allow you to modify the model's `description`, `weights` and
+other fields.
 
 Example:
+
 <pre>
 invoke> <b>!edit_model waifu-diffusion</b>
 >> Editing model waifu-diffusion from configuration file ./configs/models.yaml
@@ -442,80 +452,79 @@ OK to import [n]? y
 >> Loading waifu-diffusion from models/ldm/stable-diffusion-v1/model-epoch10-float16.ckpt
 ...
 </pre>
-=======
-    invoke> !fix 000017.4829112.gfpgan-00.png --embiggen 3
-    ...lots of text...
-    Outputs:
-    [2] outputs/img-samples/000018.2273800735.embiggen-00.png: !fix "outputs/img-samples/000017.243781548.gfpgan-00.png" -s 50 -S 2273800735 -W 512 -H 512 -C 7.5 -A k_lms --embiggen 3.0 0.75 0.25
+
+### History processing
+
+The CLI provides a series of convenient commands for reviewing previous actions,
+retrieving them, modifying them, and re-running them.
+
+#### `!history`
+
+The invoke script keeps track of all the commands you issue during a session,
+allowing you to re-run them. On Mac and Linux systems, it also writes the
+command-line history out to disk, giving you access to the most recent 1000
+commands issued.
+
+The `!history` command will return a numbered list of all the commands issued
+during the session (Windows), or the most recent 1000 commands (Mac|Linux). You
+can then repeat a command by using the command `!NNN`, where "NNN" is the
+history line number. For example:
+
+!!! example ""
+
+    ```bash
+    invoke> !history
+    ...
+    [14] happy woman sitting under tree wearing broad hat and flowing garment
+    [15] beautiful woman sitting under tree wearing broad hat and flowing garment
+    [18] beautiful woman sitting under tree wearing broad hat and flowing garment -v0.2 -n6
+    [20] watercolor of beautiful woman sitting under tree wearing broad hat and flowing garment -v0.2 -n6 -S2878767194
+    [21] surrealist painting of beautiful woman sitting under tree wearing broad hat and flowing garment -v0.2 -n6 -S2878767194
+    ...
+    invoke> !20
+    invoke> watercolor of beautiful woman sitting under tree wearing broad hat and flowing garment -v0.2 -n6 -S2878767194
     ```
-## History processing
 
-The CLI provides a series of convenient commands for reviewing previous
-actions, retrieving them, modifying them, and re-running them.
+####`!fetch`
 
-### !history
+This command retrieves the generation parameters from a previously generated
+image and either loads them into the command line (Linux|Mac), or prints them
+out in a comment for copy-and-paste (Windows). You may provide either the name
+of a file in the current output directory, or a full file path. Specify path to
+a folder with image png files, and wildcard \*.png to retrieve the dream command
+used to generate the images, and save them to a file commands.txt for further
+processing.
 
-The invoke script keeps track of all the commands you issue during a
-session, allowing you to re-run them. On Mac and Linux systems, it
-also writes the command-line history out to disk, giving you access to
-the most recent 1000 commands issued.
+!!! example "load the generation command for a single png file"
 
-The `!history` command will return a numbered list of all the commands
-issued during the session (Windows), or the most recent 1000 commands
-(Mac|Linux). You can then repeat a command by using the command `!NNN`,
-where "NNN" is the history line number. For example:
+    ```bash
+    invoke> !fetch 0000015.8929913.png
+    # the script returns the next line, ready for editing and running:
+    invoke> a fantastic alien landscape -W 576 -H 512 -s 60 -A plms -C 7.5
+    ```
 
-```bash
-invoke> !history
-...
-[14] happy woman sitting under tree wearing broad hat and flowing garment
-[15] beautiful woman sitting under tree wearing broad hat and flowing garment
-[18] beautiful woman sitting under tree wearing broad hat and flowing garment -v0.2 -n6
-[20] watercolor of beautiful woman sitting under tree wearing broad hat and flowing garment -v0.2 -n6 -S2878767194
-[21] surrealist painting of beautiful woman sitting under tree wearing broad hat and flowing garment -v0.2 -n6 -S2878767194
-...
-invoke> !20
-invoke> watercolor of beautiful woman sitting under tree wearing broad hat and flowing garment -v0.2 -n6 -S2878767194
-```
+!!! example "fetch the generation commands from a batch of files and store them into `selected.txt`"
 
-### !fetch
+    ```bash
+    invoke> !fetch outputs\selected-imgs\*.png selected.txt
+    ```
 
-This command retrieves the generation parameters from a previously
-generated image and either loads them into the command line
-(Linux|Mac), or prints them out in a comment for copy-and-paste
-(Windows). You may provide either the name of a file in the current
-output directory, or a full file path.  Specify path to a folder with
-image png files, and wildcard *.png to retrieve the dream command used
-to generate the images, and save them to a file commands.txt for
-further processing.
-
-This example loads the generation command for a single png file:
-
-```bash
-invoke> !fetch 0000015.8929913.png
-# the script returns the next line, ready for editing and running:
-invoke> a fantastic alien landscape -W 576 -H 512 -s 60 -A plms -C 7.5
-```
-
-This one fetches the generation commands from a batch of files and
-stores them into `selected.txt`:
-
-```bash
-invoke> !fetch outputs\selected-imgs\*.png selected.txt
-```
-
-### !replay
+#### `!replay`
 
 This command replays a text file generated by !fetch or created manually
 
-~~~
-invoke> !replay outputs\selected-imgs\selected.txt
-~~~
+!!! example
 
-Note that these commands may behave unexpectedly if given a PNG file that
-was not generated by InvokeAI.
+    ```bash
+    invoke> !replay outputs\selected-imgs\selected.txt
+    ```
 
-### !search <search string>
+!!! note
+
+    These commands may behave unexpectedly if given a PNG file that was
+    not generated by InvokeAI.
+
+#### `!search <search string>`
 
 This is similar to !history but it only returns lines that contain
 `search string`. For example:
@@ -525,44 +534,49 @@ invoke> !search surreal
 [21] surrealist painting of beautiful woman sitting under tree wearing broad hat and flowing garment -v0.2 -n6 -S2878767194
 ```
 
-### `!clear`
+#### `!clear`
 
-This clears the search history from memory and disk. Be advised that
-this operation is irreversible and does not issue any warnings!
+This clears the search history from memory and disk. Be advised that this
+operation is irreversible and does not issue any warnings!
 
 ## Command-line editing and completion
 
-The command-line offers convenient history tracking, editing, and
-command completion.
+The command-line offers convenient history tracking, editing, and command
+completion.
 
-- To scroll through previous commands and potentially edit/reuse them, use the ++up++ and ++down++ keys.
-- To edit the current command, use the ++left++ and ++right++ keys to position the cursor, and then ++backspace++, ++delete++ or insert characters.
-- To move to the very beginning of the command, type ++ctrl+a++ (or ++command+a++ on the Mac)
+- To scroll through previous commands and potentially edit/reuse them, use the
+  ++up++ and ++down++ keys.
+- To edit the current command, use the ++left++ and ++right++ keys to position
+  the cursor, and then ++backspace++, ++delete++ or insert characters.
+- To move to the very beginning of the command, type ++ctrl+a++ (or
+  ++command+a++ on the Mac)
 - To move to the end of the command, type ++ctrl+e++.
-- To cut a section of the command, position the cursor where you want to start cutting and type ++ctrl+k++
-- To paste a cut section back in, position the cursor where you want to paste, and type ++ctrl+y++
+- To cut a section of the command, position the cursor where you want to start
+  cutting and type ++ctrl+k++
+- To paste a cut section back in, position the cursor where you want to paste,
+  and type ++ctrl+y++
 
-Windows users can get similar, but more limited, functionality if they
-launch `invoke.py` with the `winpty` program and have the `pyreadline3`
-library installed:
+Windows users can get similar, but more limited, functionality if they launch
+`invoke.py` with the `winpty` program and have the `pyreadline3` library
+installed:
 
 ```batch
 > winpty python scripts\invoke.py
 ```
 
-On the Mac and Linux platforms, when you exit invoke.py, the last 1000
-lines of your command-line history will be saved. When you restart
-`invoke.py`, you can access the saved history using the ++up++ key.
+On the Mac and Linux platforms, when you exit invoke.py, the last 1000 lines of
+your command-line history will be saved. When you restart `invoke.py`, you can
+access the saved history using the ++up++ key.
 
-In addition, limited command-line completion is installed. In various
-contexts, you can start typing your command and press ++tab++. A list of
-potential completions will be presented to you. You can then type a
-little more, hit ++tab++ again, and eventually autocomplete what you want.
+In addition, limited command-line completion is installed. In various contexts,
+you can start typing your command and press ++tab++. A list of potential
+completions will be presented to you. You can then type a little more, hit
+++tab++ again, and eventually autocomplete what you want.
 
-When specifying file paths using the one-letter shortcuts, the CLI
-will attempt to complete pathnames for you. This is most handy for the
-`-I` (init image) and `-M` (init mask) paths. To initiate completion, start
-the path with a slash (`/`) or `./`. For example:
+When specifying file paths using the one-letter shortcuts, the CLI will attempt
+to complete pathnames for you. This is most handy for the `-I` (init image) and
+`-M` (init mask) paths. To initiate completion, start the path with a slash
+(`/`) or `./`. For example:
 
 ```bash
 invoke> zebra with a mustache -I./test-pictures<TAB>

docs/features/CONCEPTS.md

@@ -0,0 +1,131 @@
+---
+title: Concepts Library
+---
+
+# :material-library-shelves: The Hugging Face Concepts Library and Importing Textual Inversion files
+
+## Using Textual Inversion Files
+
+Textual inversion (TI) files are small models that customize the output of
+Stable Diffusion image generation. They can augment SD with specialized subjects
+and artistic styles. They are also known as "embeds" in the machine learning
+world.
+
+Each TI file introduces one or more vocabulary terms to the SD model. These are
+known in InvokeAI as "triggers." Triggers are often, but not always, denoted
+using angle brackets as in "<trigger-phrase>". The two most common type of
+TI files that you'll encounter are `.pt` and `.bin` files, which are produced by
+different TI training packages. InvokeAI supports both formats, but its
+[built-in TI training system](TEXTUAL_INVERSION.md) produces `.pt`.
+
+The [Hugging Face company](https://huggingface.co/sd-concepts-library) has
+amassed a large ligrary of >800 community-contributed TI files covering a
+broad range of subjects and styles. InvokeAI has built-in support for this
+library which downloads and merges TI files automatically upon request. You can
+also install your own or others' TI files by placing them in a designated
+directory.
+
+### An Example
+
+Here are a few examples to illustrate how it works. All these images were
+generated using the command-line client and the Stable Diffusion 1.5 model:
+
+|         Japanese gardener          | Japanese gardener <ghibli-face> | Japanese gardener <hoi4-leaders> | Japanese gardener <cartoona-animals> |
+| :--------------------------------: | :-----------------------------------: | :------------------------------------: | :----------------------------------------: |
+| ![](../assets/concepts/image1.png) |  ![](../assets/concepts/image2.png)   |   ![](../assets/concepts/image3.png)   |     ![](../assets/concepts/image4.png)     |
+
+You can also combine styles and concepts:
+
+<figure markdown>
+  | A portrait of &lt;alf&gt; in &lt;cartoona-animal&gt; style |
+  | :--------------------------------------------------------: |
+  | ![](../assets/concepts/image5.png)                         |
+</figure>
+## Using a Hugging Face Concept
+
+!!! warning "Authenticating to HuggingFace"
+
+    Some concepts require valid authentication to HuggingFace. Without it, they will not be downloaded
+    and will be silently ignored.
+
+    If you used an installer to install InvokeAI, you may have already set a HuggingFace token.
+    If you skipped this step, you can:
+
+    - run the InvokeAI configuration script again (if you used a manual installer): `invokeai-configure`
+    - set one of the `HUGGINGFACE_TOKEN` or `HUGGING_FACE_HUB_TOKEN` environment variables to contain your token
+
+    Finally, if you already used any HuggingFace library on your computer, you might already have a token
+    in your local cache. Check for a hidden `.huggingface` directory in your home folder. If it
+    contains a `token` file, then you are all set.
+
+
+Hugging Face TI concepts are downloaded and installed automatically as you
+require them. This requires your machine to be connected to the Internet. To
+find out what each concept is for, you can browse the
+[Hugging Face concepts library](https://huggingface.co/sd-concepts-library) and
+look at examples of what each concept produces.
+
+When you have an idea of a concept you wish to try, go to the command-line
+client (CLI) and type a `<` character and the beginning of the Hugging Face
+concept name you wish to load. Press ++tab++, and the CLI will show you all
+matching concepts. You can also type `<` and hit ++tab++ to get a listing of all
+~800 concepts, but be prepared to scroll up to see them all! If there is more
+than one match you can continue to type and ++tab++ until the concept is
+completed.
+
+!!! example
+
+    if you type in `<x` and hit ++tab++, you'll be prompted with the completions:
+
+    ```py
+    <xatu2>        <xatu>         <xbh>          <xi>           <xidiversity>  <xioboma>      <xuna>         <xyz>
+    ```
+
+    Now type `id` and press ++tab++. It will be autocompleted to `<xidiversity>`
+    because this is a unique match.
+
+    Finish your prompt and generate as usual. You may include multiple concept terms
+    in the prompt.
+
+If you have never used this concept before, you will see a message that the TI
+model is being downloaded and installed. After this, the concept will be saved
+locally (in the `models/sd-concepts-library` directory) for future use.
+
+Several steps happen during downloading and installation, including a scan of
+the file for malicious code. Should any errors occur, you will be warned and the
+concept will fail to load. Generation will then continue treating the trigger
+term as a normal string of characters (e.g. as literal `<ghibli-face>`).
+
+You can also use `<concept-names>` in the WebGUI's prompt textbox. There is no
+autocompletion at this time.
+
+## Installing your Own TI Files
+
+You may install any number of `.pt` and `.bin` files simply by copying them into
+the `embeddings` directory of the InvokeAI runtime directory (usually `invokeai`
+in your home directory). You may create subdirectories in order to organize the
+files in any way you wish. Be careful not to overwrite one file with another.
+For example, TI files generated by the Hugging Face toolkit share the named
+`learned_embedding.bin`. You can use subdirectories to keep them distinct.
+
+At startup time, InvokeAI will scan the `embeddings` directory and load any TI
+files it finds there. At startup you will see a message similar to this one:
+
+```bash
+>> Current embedding manager terms: *, <HOI4-Leader>, <princess-knight>
+```
+
+Note the `*` trigger term. This is a placeholder term that many early TI
+tutorials taught people to use rather than a more descriptive term.
+Unfortunately, if you have multiple TI files that all use this term, only the
+first one loaded will be triggered by use of the term.
+
+To avoid this problem, you can use the `merge_embeddings.py` script to merge two
+or more TI files together. If it encounters a collision of terms, the script
+will prompt you to select new terms that do not collide. See
+[Textual Inversion](TEXTUAL_INVERSION.md) for details.
+
+## Further Reading
+
+Please see [the repository](https://github.com/rinongal/textual_inversion) and
+associated paper for details and limitations.

docs/features/EMBIGGEN.md

@@ -85,7 +85,7 @@ increasing size, every tile after the first in a row or column
 effectively only covers an extra `1 - overlap_ratio` on each axis. If
 the input/`--init_img` is same size as a tile, the ideal (for time)
 scaling factors with the default overlap (0.25) are 1.75, 2.5, 3.25,
-4.0 etc..
+4.0, etc.
 
 `-embiggen_tiles <spaced list of tiles>`
 
@@ -100,6 +100,15 @@ Tiles are numbered starting with one, and left-to-right,
 top-to-bottom.  So, if you are generating a 3x3 tiled image, the
 middle row would be `4 5 6`.
 
+`-embiggen_strength <strength>`
+
+Another advanced option if you want to experiment with the strength parameter
+that embiggen uses when it calls Img2Img. Values range from 0.0 to 1.0
+and lower values preserve more of the character of the initial image.
+Values that are too high will result in a completely different end image,
+while values that are too low will result in an image not dissimilar to one
+you would get with ESRGAN upscaling alone. The default value is 0.4.
+
 ### Examples
 
 !!! example ""

docs/features/IMG2IMG.md

@@ -4,172 +4,242 @@ title: Image-to-Image
 
 # :material-image-multiple: Image-to-Image
 
-## `img2img`
+Both the Web and command-line interfaces provide an "img2img" feature
+that lets you seed your creations with an initial drawing or
+photo. This is a really cool feature that tells stable diffusion to
+build the prompt on top of the image you provide, preserving the
+original's basic shape and layout.
 
-This script also provides an `img2img` feature that lets you seed your creations with an initial
-drawing or photo. This is a really cool feature that tells stable diffusion to build the prompt on
-top of the image you provide, preserving the original's basic shape and layout. To use it, provide
-the `--init_img` option as shown here:
+See the [WebUI Guide](WEB.md) for a walkthrough of the img2img feature
+in the InvokeAI web server. This document describes how to use img2img
+in the command-line tool.
 
-```commandline
-tree on a hill with a river, nature photograph, national geographic -I./test-pictures/tree-and-river-sketch.png -f 0.85
-```
+## Basic Usage
 
-This will take the original image shown here:
+Launch the command-line client by launching `invoke.sh`/`invoke.bat`
+and choosing option (1). Alternative, activate the InvokeAI
+environment and issue the command `invokeai`.
 
-<div align="center" markdown>
-<img src="https://user-images.githubusercontent.com/50542132/193946000-c42a96d8-5a74-4f8a-b4c3-5213e6cadcce.png" width=350>
-</div>
+Once the `invoke> ` prompt appears, you can start an img2img render by
+pointing to a seed file with the `-I` option as shown here:
 
-and generate a new image based on it as shown here:
+!!! example ""
 
-<div align="center" markdown>
-<img src="https://user-images.githubusercontent.com/111189/194135515-53d4c060-e994-4016-8121-7c685e281ac9.png" width=350>
-</div>
+    ```commandline
+    tree on a hill with a river, nature photograph, national geographic -I./test-pictures/tree-and-river-sketch.png -f 0.85
+    ```
 
-The `--init_img` (`-I`) option gives the path to the seed picture. `--strength` (`-f`) controls how much
-the original will be modified, ranging from `0.0` (keep the original intact), to `1.0` (ignore the
-original completely). The default is `0.75`, and ranges from `0.25-0.90` give interesting results. 
-Other relevant options include `-C` (classification free guidance scale), and `-s` (steps). Unlike `txt2img`, 
-adding steps will continuously change the resulting image and it will not converge.
+    <figure markdown>
 
-You may also pass a `-v<variation_amount>` option to generate `-n<iterations>` count variants on
-the original image. This is done by passing the first generated image
-back into img2img the requested number of times. It generates
+    | original image | generated image |
+    | :------------: | :-------------: |
+    | ![original-image](https://user-images.githubusercontent.com/50542132/193946000-c42a96d8-5a74-4f8a-b4c3-5213e6cadcce.png){ width=320 } | ![generated-image](https://user-images.githubusercontent.com/111189/194135515-53d4c060-e994-4016-8121-7c685e281ac9.png){ width=320 } |
+
+    </figure>
+
+The `--init_img` (`-I`) option gives the path to the seed picture. `--strength`
+(`-f`) controls how much the original will be modified, ranging from `0.0` (keep
+the original intact), to `1.0` (ignore the original completely). The default is
+`0.75`, and ranges from `0.25-0.90` give interesting results. Other relevant
+options include `-C` (classification free guidance scale), and `-s` (steps).
+Unlike `txt2img`, adding steps will continuously change the resulting image and
+it will not converge.
+
+You may also pass a `-v<variation_amount>` option to generate `-n<iterations>`
+count variants on the original image. This is done by passing the first
+generated image back into img2img the requested number of times. It generates
 interesting variants.
 
-Note that the prompt makes a big difference. For example, this slight variation on the prompt produces
-a very different image:
+Note that the prompt makes a big difference. For example, this slight variation
+on the prompt produces a very different image:
 
-`photograph of a tree on a hill with a river`
-
-<div align="center" markdown>
-<img src="https://user-images.githubusercontent.com/111189/194135220-16b62181-b60c-4248-8989-4834a8fd7fbd.png" width=350>
-</div>
+<figure markdown>
+![](https://user-images.githubusercontent.com/111189/194135220-16b62181-b60c-4248-8989-4834a8fd7fbd.png){ width=320 }
+<caption markdown>photograph of a tree on a hill with a river</caption>
+</figure>
 
 !!! tip
 
-    When designing prompts, think about how the images scraped from the internet were captioned. Very few photographs will
-    be labeled "photograph" or "photorealistic." They will, however, be captioned with the publication, photographer, camera
-    model, or film settings.
+    When designing prompts, think about how the images scraped from the internet were
+    captioned. Very few photographs will be labeled "photograph" or "photorealistic."
+    They will, however, be captioned with the publication, photographer, camera model,
+    or film settings.
 
-If the initial image contains transparent regions, then Stable Diffusion will only draw within the
-transparent regions, a process called [`inpainting`](./INPAINTING.md#creating-transparent-regions-for-inpainting). However, for this to work correctly, the color
-information underneath the transparent needs to be preserved, not erased.
+If the initial image contains transparent regions, then Stable Diffusion will
+only draw within the transparent regions, a process called
+[`inpainting`](./INPAINTING.md#creating-transparent-regions-for-inpainting).
+However, for this to work correctly, the color information underneath the
+transparent needs to be preserved, not erased.
 
-!!! warning
+!!! warning "**IMPORTANT ISSUE** "
 
-**IMPORTANT ISSUE** `img2img` does not work properly on initial images smaller than 512x512. Please scale your
-image to at least 512x512 before using it. Larger images are not a problem, but may run out of VRAM on your
-GPU card. To fix this, use the --fit option, which downscales the initial image to fit within the box specified
-by width x height:
-~~~
-tree on a hill with a river, national geographic -I./test-pictures/big-sketch.png -H512 -W512 --fit
-~~~
+    `img2img` does not work properly on initial images smaller
+    than 512x512. Please scale your image to at least 512x512 before using it.
+    Larger images are not a problem, but may run out of VRAM on your GPU card. To
+    fix this, use the --fit option, which downscales the initial image to fit within
+    the box specified by width x height:
+
+    ```
+    tree on a hill with a river, national geographic -I./test-pictures/big-sketch.png -H512 -W512 --fit
+    ```
 
 ## How does it actually work, though?
 
-The main difference between `img2img` and `prompt2img` is the starting point. While `prompt2img` always starts with pure
-gaussian noise and progressively refines it over the requested number of steps, `img2img` skips some of these earlier steps
-(how many it skips is indirectly controlled by the `--strength` parameter), and uses instead your initial image mixed with gaussian noise as the starting image.
+The main difference between `img2img` and `prompt2img` is the starting point.
+While `prompt2img` always starts with pure gaussian noise and progressively
+refines it over the requested number of steps, `img2img` skips some of these
+earlier steps (how many it skips is indirectly controlled by the `--strength`
+parameter), and uses instead your initial image mixed with gaussian noise as the
+starting image.
 
-**Let's start** by thinking about vanilla `prompt2img`, just generating an image from a prompt. If the step count is 10, then the "latent space" (Stable Diffusion's internal representation of the image) for the prompt "fire" with seed `1592514025` develops something like this:
+**Let's start** by thinking about vanilla `prompt2img`, just generating an image
+from a prompt. If the step count is 10, then the "latent space" (Stable
+Diffusion's internal representation of the image) for the prompt "fire" with
+seed `1592514025` develops something like this:
 
-```commandline
-invoke> "fire" -s10 -W384 -H384 -S1592514025
-```
+!!! example ""
 
-<div align="center" markdown>
-![latent steps](../assets/img2img/000019.steps.png)
-</div>
+    ```bash
+    invoke> "fire" -s10 -W384 -H384 -S1592514025
+    ```
 
-Put simply: starting from a frame of fuzz/static, SD finds details in each frame that it thinks look like "fire" and brings them a little bit more into focus, gradually scrubbing out the fuzz until a clear image remains.
+    <figure markdown>
+    ![latent steps](../assets/img2img/000019.steps.png){ width=720 }
+    </figure>
 
-**When you use `img2img`** some of the earlier steps are cut, and instead an initial image of your choice is used. But because of how the maths behind Stable Diffusion works, this image needs to be mixed with just the right amount of noise (fuzz/static) for where it is being inserted. This is where the strength parameter comes in. Depending on the set strength, your image will be inserted into the sequence at the appropriate point, with just the right amount of noise.
+Put simply: starting from a frame of fuzz/static, SD finds details in each frame
+that it thinks look like "fire" and brings them a little bit more into focus,
+gradually scrubbing out the fuzz until a clear image remains.
+
+**When you use `img2img`** some of the earlier steps are cut, and instead an
+initial image of your choice is used. But because of how the maths behind Stable
+Diffusion works, this image needs to be mixed with just the right amount of
+noise (fuzz/static) for where it is being inserted. This is where the strength
+parameter comes in. Depending on the set strength, your image will be inserted
+into the sequence at the appropriate point, with just the right amount of noise.
 
 ### A concrete example
 
-I want SD to draw a fire based on this hand-drawn image:
+!!! example "I want SD to draw a fire based on this hand-drawn image"
 
-<div align="center" markdown>
-![drawing of a fireplace](../assets/img2img/fire-drawing.png)
-</div>
+    ![drawing of a fireplace](../assets/img2img/fire-drawing.png){ align=left }
 
-Let's only do 10 steps, to make it easier to see what's happening. If strength is `0.7`, this is what the internal steps the algorithm has to take will look like:
+    Let's only do 10 steps, to make it easier to see what's happening. If strength
+    is `0.7`, this is what the internal steps the algorithm has to take will look
+    like:
 
-<div align="center" markdown>
-![gravity32](../assets/img2img/000032.steps.gravity.png)
-</div>
+    <figure markdown>
+    ![gravity32](../assets/img2img/000032.steps.gravity.png)
+    </figure>
 
-With strength `0.4`, the steps look more like this:
+    With strength `0.4`, the steps look more like this:
 
-<div align="center" markdown>
-![gravity30](../assets/img2img/000030.steps.gravity.png)
-</div>
+    <figure markdown>
+    ![gravity30](../assets/img2img/000030.steps.gravity.png)
+    </figure>
 
-Notice how much more fuzzy the starting image is for strength `0.7` compared to `0.4`, and notice also how much longer the sequence is with `0.7`:
+Notice how much more fuzzy the starting image is for strength `0.7` compared to
+`0.4`, and notice also how much longer the sequence is with `0.7`:
 
-|  | strength = 0.7 | strength = 0.4 |
-| -- | -- | -- |
-| initial image that SD sees | ![](../assets/img2img/000032.step-0.png) | ![](../assets/img2img/000030.step-0.png) |
-| steps argument to `invoke>` | `-S10` | `-S10` |
-| steps actually taken | 7 | 4 |
-| latent space at each step | ![gravity32](../assets/img2img/000032.steps.gravity.png) | ![gravity30](../assets/img2img/000030.steps.gravity.png) |
-| output | ![000032.1592514025](../assets/img2img/000032.1592514025.png) | ![000030.1592514025](../assets/img2img/000030.1592514025.png) |
+|                             | strength = 0.7                                                | strength = 0.4                                                |
+| --------------------------- | ------------------------------------------------------------- | ------------------------------------------------------------- |
+| initial image that SD sees  | ![step-0](../assets/img2img/000032.step-0.png)                | ![step-0](../assets/img2img/000030.step-0.png)                |
+| steps argument to `invoke>` | `-S10`                                                        | `-S10`                                                        |
+| steps actually taken        | `7`                                                           | `4`                                                           |
+| latent space at each step   | ![gravity32](../assets/img2img/000032.steps.gravity.png)      | ![gravity30](../assets/img2img/000030.steps.gravity.png)      |
+| output                      | ![000032.1592514025](../assets/img2img/000032.1592514025.png) | ![000030.1592514025](../assets/img2img/000030.1592514025.png) |
 
-Both of the outputs look kind of like what I was thinking of. With the strength higher, my input becomes more vague, *and* Stable Diffusion has more steps to refine its output. But it's not really making what I want, which is a picture of cheery open fire. With the strength lower, my input is more clear, *but* Stable Diffusion has less chance to refine itself, so the result ends up inheriting all the problems of my bad drawing.
+Both of the outputs look kind of like what I was thinking of. With the strength
+higher, my input becomes more vague, _and_ Stable Diffusion has more steps to
+refine its output. But it's not really making what I want, which is a picture of
+cheery open fire. With the strength lower, my input is more clear, _but_ Stable
+Diffusion has less chance to refine itself, so the result ends up inheriting all
+the problems of my bad drawing.
 
-If you want to try this out yourself, all of these are using a seed of `1592514025` with a width/height of `384`, step count `10`, the default sampler (`k_lms`), and the single-word prompt `"fire"`:
+If you want to try this out yourself, all of these are using a seed of
+`1592514025` with a width/height of `384`, step count `10`, the default sampler
+(`k_lms`), and the single-word prompt `"fire"`:
 
-```commandline
+```bash
 invoke> "fire" -s10 -W384 -H384 -S1592514025 -I /tmp/fire-drawing.png --strength 0.7
 ```
 
-The code for rendering intermediates is on my (damian0815's) branch [document-img2img](https://github.com/damian0815/InvokeAI/tree/document-img2img) - run `invoke.py` and check your `outputs/img-samples/intermediates` folder while generating an image. 
+The code for rendering intermediates is on my (damian0815's) branch
+[document-img2img](https://github.com/damian0815/InvokeAI/tree/document-img2img) -
+run `invoke.py` and check your `outputs/img-samples/intermediates` folder while
+generating an image.
 
 ### Compensating for the reduced step count
 
-After putting this guide together I was curious to see how the difference would be if I increased the step count to compensate, so that SD could have the same amount of steps to develop the image regardless of the strength. So I ran the generation again using the same seed, but this time adapting the step count to give each generation 20 steps.
+After putting this guide together I was curious to see how the difference would
+be if I increased the step count to compensate, so that SD could have the same
+amount of steps to develop the image regardless of the strength. So I ran the
+generation again using the same seed, but this time adapting the step count to
+give each generation 20 steps.
 
-Here's strength `0.4` (note step count `50`, which is `20 ÷ 0.4` to make sure SD does `20` steps from my image):
+Here's strength `0.4` (note step count `50`, which is `20 ÷ 0.4` to make sure SD
+does `20` steps from my image):
 
-```commandline
+```bash
 invoke> "fire" -s50 -W384 -H384 -S1592514025 -I /tmp/fire-drawing.png -f 0.4
 ```
 
-<div align="center" markdown>
+<figure markdown>
 ![000035.1592514025](../assets/img2img/000035.1592514025.png)
-</div>
+</figure>
 
-and here is strength `0.7` (note step count `30`, which is roughly `20 ÷ 0.7` to make sure SD does `20` steps from my image):
+and here is strength `0.7` (note step count `30`, which is roughly `20 ÷ 0.7` to
+make sure SD does `20` steps from my image):
 
 ```commandline
 invoke> "fire" -s30 -W384 -H384 -S1592514025 -I /tmp/fire-drawing.png -f 0.7
 ```
 
-<div align="center" markdown>
+<figure markdown>
 ![000046.1592514025](../assets/img2img/000046.1592514025.png)
-</div>
+</figure>
 
-In both cases the image is nice and clean and "finished", but because at strength `0.7` Stable Diffusion has been give so much more freedom to improve on my badly-drawn flames, they've come out looking much better. You can really see the difference when looking at the latent steps. There's more noise on the first image with strength `0.7`:
+In both cases the image is nice and clean and "finished", but because at
+strength `0.7` Stable Diffusion has been give so much more freedom to improve on
+my badly-drawn flames, they've come out looking much better. You can really see
+the difference when looking at the latent steps. There's more noise on the first
+image with strength `0.7`:
 
+<figure markdown>
 ![gravity46](../assets/img2img/000046.steps.gravity.png)
+</figure>
 
 than there is for strength `0.4`:
 
+<figure markdown>
 ![gravity35](../assets/img2img/000035.steps.gravity.png)
+</figure>
 
-and that extra noise gives the algorithm more choices when it is evaluating how to denoise any particular pixel in the image.
+and that extra noise gives the algorithm more choices when it is evaluating how
+to denoise any particular pixel in the image.
 
-Unfortunately, it seems that `img2img` is very sensitive to the step count. Here's strength `0.7` with a step count of `29` (SD did 19 steps from my image):
+Unfortunately, it seems that `img2img` is very sensitive to the step count.
+Here's strength `0.7` with a step count of `29` (SD did 19 steps from my image):
 
-<div align="center" markdown>
+<figure markdown>
 ![gravity45](../assets/img2img/000045.1592514025.png)
-</div>
+</figure>
 
-By comparing the latents we can sort of see that something got interpreted differently enough on the third or fourth step to lead to a rather different interpretation of the flames.
+By comparing the latents we can sort of see that something got interpreted
+differently enough on the third or fourth step to lead to a rather different
+interpretation of the flames.
 
+<figure markdown>
 ![gravity46](../assets/img2img/000046.steps.gravity.png)
-![gravity45](../assets/img2img/000045.steps.gravity.png)
+</figure>
 
-This is the result of a difference in the de-noising "schedule" - basically the noise has to be cleaned by a certain degree each step or the model won't "converge" on the image properly (see [stable diffusion blog](https://huggingface.co/blog/stable_diffusion) for more about that). A different step count means a different schedule, which means things get interpreted slightly differently at every step.
+<figure markdown>
+![gravity45](../assets/img2img/000045.steps.gravity.png)
+</figure>
+
+This is the result of a difference in the de-noising "schedule" - basically the
+noise has to be cleaned by a certain degree each step or the model won't
+"converge" on the image properly (see
+[stable diffusion blog](https://huggingface.co/blog/stable_diffusion) for more
+about that). A different step count means a different schedule, which means
+things get interpreted slightly differently at every step.

docs/features/INPAINTING.md

@@ -6,29 +6,27 @@ title: Inpainting
 
 ## **Creating Transparent Regions for Inpainting**
 
-Inpainting is really cool. To do it, you start with an initial image
-and use a photoeditor to make one or more regions transparent
-(i.e. they have a "hole" in them). You then provide the path to this
-image at the dream> command line using the `-I` switch. Stable
-Diffusion will only paint within the transparent region.
+Inpainting is really cool. To do it, you start with an initial image and use a
+photoeditor to make one or more regions transparent (i.e. they have a "hole" in
+them). You then provide the path to this image at the dream> command line using
+the `-I` switch. Stable Diffusion will only paint within the transparent region.
 
-There's a catch. In the current implementation, you have to prepare
-the initial image correctly so that the underlying colors are
-preserved under the transparent area. Many imaging editing
-applications will by default erase the color information under the
-transparent pixels and replace them with white or black, which will
-lead to suboptimal inpainting. It often helps to apply incomplete
-transparency, such as any value between 1 and 99%
+There's a catch. In the current implementation, you have to prepare the initial
+image correctly so that the underlying colors are preserved under the
+transparent area. Many imaging editing applications will by default erase the
+color information under the transparent pixels and replace them with white or
+black, which will lead to suboptimal inpainting. It often helps to apply
+incomplete transparency, such as any value between 1 and 99%
 
-You also must take care to export the PNG file in such a way that the
-color information is preserved. There is often an option in the export
-dialog that lets you specify this.
+You also must take care to export the PNG file in such a way that the color
+information is preserved. There is often an option in the export dialog that
+lets you specify this.
 
-If your photoeditor is erasing the underlying color information,
-`dream.py` will give you a big fat warning. If you can't find a way to
-coax your photoeditor to retain color values under transparent areas,
-then you can combine the `-I` and `-M` switches to provide both the
-original unedited image and the masked (partially transparent) image:
+If your photoeditor is erasing the underlying color information, `dream.py` will
+give you a big fat warning. If you can't find a way to coax your photoeditor to
+retain color values under transparent areas, then you can combine the `-I` and
+`-M` switches to provide both the original unedited image and the masked
+(partially transparent) image:
 
 ```bash
 invoke> "man with cat on shoulder" -I./images/man.png -M./images/man-transparent.png
@@ -36,47 +34,47 @@ invoke> "man with cat on shoulder" -I./images/man.png -M./images/man-transparent
 
 ## **Masking using Text**
 
-You can also create a mask using a text prompt to select the part of
-the image you want to alter, using the <a
-href="https://github.com/timojl/clipseg">clipseg</a> algorithm. This
-works on any image, not just ones generated by InvokeAI.
+You can also create a mask using a text prompt to select the part of the image
+you want to alter, using the [clipseg](https://github.com/timojl/clipseg)
+algorithm. This works on any image, not just ones generated by InvokeAI.
 
-The `--text_mask` (short form `-tm`) option takes two arguments. The
-first argument is a text description of the part of the image you wish
-to mask (paint over). If the text description contains a space, you must
-surround it with quotation marks. The optional second argument is the
-minimum threshold for the mask classifier's confidence score, described
-in more detail below.
+The `--text_mask` (short form `-tm`) option takes two arguments. The first
+argument is a text description of the part of the image you wish to mask (paint
+over). If the text description contains a space, you must surround it with
+quotation marks. The optional second argument is the minimum threshold for the
+mask classifier's confidence score, described in more detail below.
 
-To see how this works in practice, here's an image of a still life
-painting that I got off the web.
+To see how this works in practice, here's an image of a still life painting that
+I got off the web.
 
-<img src="../assets/still-life-scaled.jpg">
+<figure markdown>
+![still life scaled](../assets/still-life-scaled.jpg)
+</figure>
 
-You can selectively mask out the
-orange and replace it with a baseball in this way:
+You can selectively mask out the orange and replace it with a baseball in this
+way:
 
-~~~
+```bash
 invoke> a baseball -I /path/to/still_life.png -tm orange
-~~~
+```
 
-<img src="../assets/still-life-inpainted.png">
+<figure markdown>
+![](../assets/still-life-inpainted.png)
+</figure>
 
 The clipseg classifier produces a confidence score for each region it
-identifies. Generally regions that score above 0.5 are reliable, but
-if you are getting too much or too little masking you can adjust the
-threshold down (to get more mask), or up (to get less). In this
-example, by passing `-tm` a higher value, we are insisting on a tigher
-mask. However, if you make it too high, the orange may not be picked
-up at all!
+identifies. Generally regions that score above 0.5 are reliable, but if you are
+getting too much or too little masking you can adjust the threshold down (to get
+more mask), or up (to get less). In this example, by passing `-tm` a higher
+value, we are insisting on a tigher mask. However, if you make it too high, the
+orange may not be picked up at all!
 
-~~~
+```bash
 invoke> a baseball -I /path/to/breakfast.png -tm orange 0.6
-~~~
+```
 
-The `!mask` command may be useful for debugging problems with the
-text2mask feature. The syntax is `!mask /path/to/image.png -tm <text>
-<threshold>`
+The `!mask` command may be useful for debugging problems with the text2mask
+feature. The syntax is `!mask /path/to/image.png -tm <text> <threshold>`
 
 It will generate three files:
 
@@ -84,19 +82,18 @@ It will generate three files:
   - it will be named XXXXX.<imagename>.<prompt>.selected.png
 - The image with the un-selected area highlighted.
   - it will be named XXXXX.<imagename>.<prompt>.deselected.png
-- The image with the selected area converted into a black and white
-  image according to the threshold level
+- The image with the selected area converted into a black and white image
+  according to the threshold level
   - it will be named XXXXX.<imagename>.<prompt>.masked.png
 
-The `.masked.png` file can then be directly passed to the `invoke>`
-prompt in the CLI via the `-M` argument. Do not attempt this with
-the `selected.png` or `deselected.png` files, as they contain some
-transparency throughout the image and will not produce the desired
-results.
+The `.masked.png` file can then be directly passed to the `invoke>` prompt in
+the CLI via the `-M` argument. Do not attempt this with the `selected.png` or
+`deselected.png` files, as they contain some transparency throughout the image
+and will not produce the desired results.
 
 Here is an example of how `!mask` works:
 
-```
+```bash
 invoke> !mask ./test-pictures/curly.png -tm hair 0.5
 >> generating masks from ./test-pictures/curly.png
 >> Initializing clipseg model for text to mask inference
@@ -106,23 +103,30 @@ Outputs:
 [941.3] outputs/img-samples/000019.curly.hair.masked.png: !mask ./test-pictures/curly.png -tm hair 0.5
 ```
 
-**Original image "curly.png"**
-<img src="../assets/outpainting/curly.png">
+<figure markdown>
+![curly](../assets/outpainting/curly.png)
+<figcaption>Original image "curly.png"</figcaption>
+</figure>
 
-**000019.curly.hair.selected.png**
-<img src="../assets/inpainting/000019.curly.hair.selected.png">
+<figure markdown>
+![curly hair selected](../assets/inpainting/000019.curly.hair.selected.png)
+<figcaption>000019.curly.hair.selected.png</figcaption>
+</figure>
 
-**000019.curly.hair.deselected.png**
-<img src="../assets/inpainting/000019.curly.hair.deselected.png">
+<figure markdown>
+![curly hair deselected](../assets/inpainting/000019.curly.hair.deselected.png)
+<figcaption>000019.curly.hair.deselected.png</figcaption>
+</figure>
 
-**000019.curly.hair.masked.png**
-<img src="../assets/inpainting/000019.curly.hair.masked.png">
+<figure markdown>
+![curly hair masked](../assets/inpainting/000019.curly.hair.masked.png)
+<figcaption>000019.curly.hair.masked.png</figcaption>
+</figure>
 
-It looks like we selected the hair pretty well at the 0.5 threshold
-(which is the default, so we didn't actually have to specify it), so
-let's have some fun:
+It looks like we selected the hair pretty well at the 0.5 threshold (which is
+the default, so we didn't actually have to specify it), so let's have some fun:
 
-```
+```bash
 invoke> medusa with cobras -I ./test-pictures/curly.png -M 000019.curly.hair.masked.png -C20
 >> loaded input image of size 512x512 from ./test-pictures/curly.png
 ...
@@ -130,86 +134,87 @@ Outputs:
 [946] outputs/img-samples/000024.801380492.png: "medusa with cobras" -s 50 -S 801380492 -W 512 -H 512 -C 20.0 -I ./test-pictures/curly.png -A k_lms -f 0.75
 ```
 
-<img src="../assets/inpainting/000024.801380492.png">
+<figure markdown>
+![](../assets/inpainting/000024.801380492.png)
+</figure>
 
 You can also skip the `!mask` creation step and just select the masked
 
 region directly:
-```
+
+```bash
 invoke> medusa with cobras -I ./test-pictures/curly.png -tm hair -C20
 ```
 
 ## Using the RunwayML inpainting model
 
-The [RunwayML Inpainting Model
-v1.5](https://huggingface.co/runwayml/stable-diffusion-inpainting) is
-a specialized version of [Stable Diffusion
-v1.5](https://huggingface.co/spaces/runwayml/stable-diffusion-v1-5)
-that contains extra channels specifically designed to enhance
-inpainting and outpainting. While it can do regular `txt2img` and
-`img2img`, it really shines when filling in missing regions. It has an
-almost uncanny ability to blend the new regions with existing ones in
-a semantically coherent way.
+The
+[RunwayML Inpainting Model v1.5](https://huggingface.co/runwayml/stable-diffusion-inpainting)
+is a specialized version of
+[Stable Diffusion v1.5](https://huggingface.co/spaces/runwayml/stable-diffusion-v1-5)
+that contains extra channels specifically designed to enhance inpainting and
+outpainting. While it can do regular `txt2img` and `img2img`, it really shines
+when filling in missing regions. It has an almost uncanny ability to blend the
+new regions with existing ones in a semantically coherent way.
 
 To install the inpainting model, follow the
-[instructions](INSTALLING-MODELS.md) for installing a new model. You
-may use either the CLI (`invoke.py` script) or directly edit the
-`configs/models.yaml` configuration file to do this. The main thing to
-watch out for is that the the model `config` option must be set up to
-use `v1-inpainting-inference.yaml` rather than the `v1-inference.yaml`
-file that is used by Stable Diffusion 1.4 and 1.5.
+[instructions](../installation/050_INSTALLING_MODELS.md) for installing a new model.
+You may use either the CLI (`invoke.py` script) or directly edit the
+`configs/models.yaml` configuration file to do this. The main thing to watch out
+for is that the the model `config` option must be set up to use
+`v1-inpainting-inference.yaml` rather than the `v1-inference.yaml` file that is
+used by Stable Diffusion 1.4 and 1.5.
 
-After installation, your `models.yaml` should contain an entry that
-looks like this one:
+After installation, your `models.yaml` should contain an entry that looks like
+this one:
 
- inpainting-1.5:
-   weights: models/ldm/stable-diffusion-v1/sd-v1-5-inpainting.ckpt
-   description: SD inpainting v1.5
-   config: configs/stable-diffusion/v1-inpainting-inference.yaml
-   vae: models/ldm/stable-diffusion-v1/vae-ft-mse-840000-ema-pruned.ckpt
-   width: 512
-   height: 512
+```yml
+inpainting-1.5:
+  weights: models/ldm/stable-diffusion-v1/sd-v1-5-inpainting.ckpt
+  description: SD inpainting v1.5
+  config: configs/stable-diffusion/v1-inpainting-inference.yaml
+  vae: models/ldm/stable-diffusion-v1/vae-ft-mse-840000-ema-pruned.ckpt
+  width: 512
+  height: 512
+```
 
-As shown in the example, you may include a VAE fine-tuning weights
-file as well. This is strongly recommended.
+As shown in the example, you may include a VAE fine-tuning weights file as well.
+This is strongly recommended.
 
-To use the custom inpainting model, launch `invoke.py` with the
-argument `--model inpainting-1.5` or alternatively from within the
-script use the `!switch inpainting-1.5` command to load and switch to
-the inpainting model.
+To use the custom inpainting model, launch `invoke.py` with the argument
+`--model inpainting-1.5` or alternatively from within the script use the
+`!switch inpainting-1.5` command to load and switch to the inpainting model.
 
-You can now do inpainting and outpainting exactly as described above,
-but there will (likely) be a noticeable improvement in
-coherence. Txt2img and Img2img will work as well.
+You can now do inpainting and outpainting exactly as described above, but there
+will (likely) be a noticeable improvement in coherence. Txt2img and Img2img will
+work as well.
 
 There are a few caveats to be aware of:
 
-1. The inpainting model is larger than the standard model, and will
-   use nearly 4 GB of GPU VRAM. This makes it unlikely to run on
-   a 4 GB graphics card.
+1. The inpainting model is larger than the standard model, and will use nearly 4
+   GB of GPU VRAM. This makes it unlikely to run on a 4 GB graphics card.
 
-2. When operating in Img2img mode, the inpainting model is much less
-   steerable than the standard model. It is great for making small
-   changes, such as changing the pattern of a fabric, or slightly
-   changing a subject's expression or hair, but the model will
-   resist making the dramatic alterations that the standard
-   model lets you do.
+2. When operating in Img2img mode, the inpainting model is much less steerable
+   than the standard model. It is great for making small changes, such as
+   changing the pattern of a fabric, or slightly changing a subject's expression
+   or hair, but the model will resist making the dramatic alterations that the
+   standard model lets you do.
 
-3. While the `--hires` option works fine with the inpainting model,
-   some special features, such as `--embiggen` are disabled.
+3. While the `--hires` option works fine with the inpainting model, some special
+   features, such as `--embiggen` are disabled.
 
-4. Prompt weighting (`banana++ sushi`) and merging work well with
-   the inpainting model, but prompt swapping (a ("fluffy cat").swap("smiling dog") eating a hotdog`)
-   will not have any effect due to the way the model is set up.
-   You may use text masking (with `-tm thing-to-mask`) as an
-   effective replacement.
+4. Prompt weighting (`banana++ sushi`) and merging work well with the inpainting
+   model, but prompt swapping
+   (`a ("fluffy cat").swap("smiling dog") eating a hotdog`) will not have any
+   effect due to the way the model is set up. You may use text masking (with
+   `-tm thing-to-mask`) as an effective replacement.
 
-5. The model tends to oversharpen image if you use high step or CFG
-   values. If you need to do large steps, use the standard model.
+5. The model tends to oversharpen image if you use high step or CFG values. If
+   you need to do large steps, use the standard model.
 
-6. The `--strength` (`-f`) option has no effect on the inpainting
-   model due to its fundamental differences with the standard
-   model. It will always take the full number of steps you specify.
+6. The `--strength` (`-f`) option has no effect on the inpainting model due to
+   its fundamental differences with the standard model. It will always take the
+   full number of steps you specify.
 
 ## Troubleshooting
 
@@ -217,23 +222,21 @@ Here are some troubleshooting tips for inpainting and outpainting.
 
 ## Inpainting is not changing the masked region enough!
 
-One of the things to understand about how inpainting works is that it
-is equivalent to running img2img on just the masked (transparent)
-area. img2img builds on top of the existing image data, and therefore
-will attempt to preserve colors, shapes and textures to the best of
-its ability. Unfortunately this means that if you want to make a
-dramatic change in the inpainted region, for example replacing a red
-wall with a blue one, the algorithm will fight you.
+One of the things to understand about how inpainting works is that it is
+equivalent to running img2img on just the masked (transparent) area. img2img
+builds on top of the existing image data, and therefore will attempt to preserve
+colors, shapes and textures to the best of its ability. Unfortunately this means
+that if you want to make a dramatic change in the inpainted region, for example
+replacing a red wall with a blue one, the algorithm will fight you.
 
-You have a couple of options. The first is to increase the values of
-the requested steps (`-sXXX`), strength (`-f0.XX`), and/or
-condition-free guidance (`-CXX.X`). If this is not working for you, a
-more extreme step is to provide the `--inpaint_replace 0.X` (`-r0.X`)
-option. This value ranges from 0.0 to 1.0. The higher it is the less
-attention the algorithm will pay to the data underneath the masked
-region. At high values this will enable you to replace colored regions
-entirely, but beware that the masked region mayl not blend in with the
-surrounding unmasked regions as well.
+You have a couple of options. The first is to increase the values of the
+requested steps (`-sXXX`), strength (`-f0.XX`), and/or condition-free guidance
+(`-CXX.X`). If this is not working for you, a more extreme step is to provide
+the `--inpaint_replace 0.X` (`-r0.X`) option. This value ranges from 0.0 to 1.0.
+The higher it is the less attention the algorithm will pay to the data
+underneath the masked region. At high values this will enable you to replace
+colored regions entirely, but beware that the masked region mayl not blend in
+with the surrounding unmasked regions as well.
 
 ---
 
@@ -248,8 +251,8 @@ surrounding unmasked regions as well.
 5. Open the Layers toolbar (^L) and select "Floating Selection"
 6. Set opacity to a value between 0% and 99%
 7. Export as PNG
-8. In the export dialogue, Make sure the "Save colour values from
-   transparent pixels" checkbox is selected.
+8. In the export dialogue, Make sure the "Save colour values from transparent
+   pixels" checkbox is selected.
 
 ---
 
@@ -257,28 +260,51 @@ surrounding unmasked regions as well.
 
 1. Open image in Photoshop
 
-    <div align="center" markdown>![step1](../assets/step1.png)</div>
+    <figure markdown>
+    ![step1](../assets/step1.png)
+    </figure>
 
-2. Use any of the selection tools (Marquee, Lasso, or Wand) to select the area you desire to inpaint.
+2. Use any of the selection tools (Marquee, Lasso, or Wand) to select the area
+   you desire to inpaint.
 
-    <div align="center" markdown>![step2](../assets/step2.png)</div>
+    <figure markdown>
+    ![step2](../assets/step2.png)
+    </figure>
 
-3. Because we'll be applying a mask over the area we want to preserve, you should now select the inverse by using the ++shift+ctrl+i++ shortcut, or right clicking and using the "Select Inverse" option.
+3. Because we'll be applying a mask over the area we want to preserve, you
+   should now select the inverse by using the ++shift+ctrl+i++ shortcut, or
+   right clicking and using the "Select Inverse" option.
 
-4. You'll now create a mask by selecting the image layer, and Masking the selection. Make sure that you don't delete any of the underlying image, or your inpainting results will be dramatically impacted.
+4. You'll now create a mask by selecting the image layer, and Masking the
+   selection. Make sure that you don't delete any of the underlying image, or
+   your inpainting results will be dramatically impacted.
 
-    <div align="center" markdown>![step4](../assets/step4.png)</div>
+    <figure markdown>
+    ![step4](../assets/step4.png)
+    </figure>
 
-5. Make sure to hide any background layers that are present. You should see the mask applied to your image layer, and the image on your canvas should display the checkered background.
+5. Make sure to hide any background layers that are present. You should see the
+   mask applied to your image layer, and the image on your canvas should display
+   the checkered background.
 
-    <div align="center" markdown>![step5](../assets/step5.png)</div>
+    <figure markdown>
+    ![step5](../assets/step5.png)
+    </figure>
 
-6. Save the image as a transparent PNG by using `File`-->`Save a Copy` from the menu bar, or by using the keyboard shortcut ++alt+ctrl+s++
+6. Save the image as a transparent PNG by using `File`-->`Save a Copy` from the
+   menu bar, or by using the keyboard shortcut ++alt+ctrl+s++
 
-    <div align="center" markdown>![step6](../assets/step6.png)</div>
+    <figure markdown>
+    ![step6](../assets/step6.png)
+    </figure>
 
-7. After following the inpainting instructions above (either through the CLI or the Web UI), marvel at your newfound ability to selectively invoke. Lookin' good!
+7. After following the inpainting instructions above (either through the CLI or
+   the Web UI), marvel at your newfound ability to selectively invoke. Lookin'
+   good!
 
-    <div align="center" markdown>![step7](../assets/step7.png)</div>
+    <figure markdown>
+   ![step7](../assets/step7.png)
+    </figure>
 
-8. In the export dialogue, Make sure the "Save colour values from transparent pixels" checkbox is selected.  
+8. In the export dialogue, Make sure the "Save colour values from transparent
+   pixels" checkbox is selected.

docs/features/MODEL_MERGING.md

@@ -0,0 +1,76 @@
+---
+title: Model Merging
+---
+
+# :material-image-off: Model Merging
+
+## How to Merge Models
+
+As of version 2.3, InvokeAI comes with a script that allows you to
+merge two or three diffusers-type models into a new merged model. The
+resulting model will combine characteristics of the original, and can
+be used to teach an old model new tricks.
+
+You may run the merge script by starting the invoke launcher
+(`invoke.sh` or `invoke.bat`) and choosing the option for _merge
+models_. This will launch a text-based interactive user interface that
+prompts you to select the models to merge, how to merge them, and the
+merged model name.
+
+Alternatively you may activate InvokeAI's virtual environment from the
+command line, and call the script via `merge_models --gui` to open up
+a version that has a nice graphical front end. To get the commandline-
+only version, omit `--gui`.
+
+The user interface for the text-based interactive script is
+straightforward. It shows you a series of setting fields. Use control-N (^N)
+to move to the next field, and control-P (^P) to move to the previous
+one. You can also use TAB and shift-TAB to move forward and
+backward. Once you are in a multiple choice field, use the up and down
+cursor arrows to move to your desired selection, and press <SPACE> or
+<ENTER> to select it. Change text fields by typing in them, and adjust
+scrollbars using the left and right arrow keys.
+
+Once you are happy with your settings, press the OK button. Note that
+there may be two pages of settings, depending on the height of your
+screen, and the OK button may be on the second page. Advance past the
+last field of the first page to get to the second page, and reverse
+this to get back.
+
+If the merge runs successfully, it will create a new diffusers model
+under the selected name and register it with InvokeAI.
+
+## The Settings
+
+* Model Selection -- there are three multiple choice fields that
+  display all the diffusers-style models that InvokeAI knows about.
+  If you do not see the model you are looking for, then it is probably
+  a legacy checkpoint model and needs to be converted using the
+  `invoke` command-line client and its `!optimize` command. You
+  must select at least two models to merge. The third can be left at
+  "None" if you desire.
+
+* Alpha -- This is the ratio to use when combining models. It ranges
+  from 0 to 1. The higher the value, the more weight is given to the
+  2d and (optionally) 3d models. So if you have two models named "A"
+  and "B", an alpha value of 0.25 will give you a merged model that is
+  25% A and 75% B.
+
+* Interpolation Method -- This is the method used to combine
+  weights. The options are "weighted_sum" (the default), "sigmoid",
+  "inv_sigmoid" and "add_difference". Each produces slightly different
+  results. When three models are in use, only "add_difference" is
+  available. (TODO: cite a reference that describes what these
+  interpolation methods actually do and how to decide among them).
+
+* Force -- Not all models are compatible with each other. The merge
+  script will check for compatibility and refuse to merge ones that
+  are incompatible. Set this checkbox to try merging anyway.
+
+* Name for merged model - This is the name for the new model. Please
+  use InvokeAI conventions - only alphanumeric letters and the
+  characters ".+-".
+
+## Caveats
+
+This is a new script and may contain bugs.

docs/features/NSFW.md

@@ -0,0 +1,89 @@
+---
+title: The NSFW Checker
+---
+
+# :material-image-off: NSFW Checker
+
+## The NSFW ("Safety") Checker
+
+The Stable Diffusion image generation models will produce sexual
+imagery if deliberately prompted, and will occasionally produce such
+images when this is not intended. Such images are colloquially known
+as "Not Safe for Work" (NSFW). This behavior is due to the nature of
+the training set that Stable Diffusion was trained on, which culled
+millions of "aesthetic" images from the Internet.
+
+You may not wish to be exposed to these images, and in some
+jurisdictions it may be illegal to publicly distribute such imagery,
+including mounting a publicly-available server that provides
+unfiltered images to the public. Furthermore, the [Stable Diffusion
+weights
+License](https://github.com/invoke-ai/InvokeAI/blob/main/LICENSE-ModelWeights.txt)
+forbids the model from being used to "exploit any of the
+vulnerabilities of a specific group of persons."
+
+For these reasons Stable Diffusion offers a "safety checker," a
+machine learning model trained to recognize potentially disturbing
+imagery. When a potentially NSFW image is detected, the checker will
+blur the image and paste a warning icon on top. The checker can be
+turned on and off on the command line using `--nsfw_checker` and
+`--no-nsfw_checker`.
+
+At installation time, InvokeAI will ask whether the checker should be
+activated by default (neither argument given on the command line). The
+response is stored in the InvokeAI initialization file (usually
+`.invokeai` in your home directory). You can change the default at any
+time by opening this file in a text editor and commenting or
+uncommenting the line `--nsfw_checker`.
+
+## Caveats
+
+There are a number of caveats that you need to be aware of.
+
+### Accuracy
+
+The checker is [not perfect](https://arxiv.org/abs/2210.04610).It will
+occasionally flag innocuous images (false positives), and will
+frequently miss violent and gory imagery (false negatives). It rarely
+fails to flag sexual imagery, but this has been known to happen. For
+these reasons, the InvokeAI team prefers to refer to the software as a
+"NSFW Checker" rather than "safety checker."
+
+### Memory Usage and Performance
+
+The NSFW checker consumes an additional 1.2G of GPU VRAM on top of the
+3.4G of VRAM used by Stable Diffusion v1.5 (this is with
+half-precision arithmetic). This means that the checker will not run
+successfully on GPU cards with less than 6GB VRAM, and will reduce the
+size of the images that you can produce.
+
+The checker also introduces a slight performance penalty. Images will
+take ~1 second longer to generate when the checker is
+activated. Generally this is not noticeable.
+
+### Intermediate Images in the Web UI
+
+The checker only operates on the final image produced by the Stable
+Diffusion algorithm. If you are using the Web UI and have enabled the
+display of intermediate images, you will briefly be exposed to a
+low-resolution (mosaicized) version of the final image before it is
+flagged by the checker and replaced by a fully blurred version. You
+are encouraged to turn **off** intermediate image rendering when you
+are using the checker. Future versions of InvokeAI will apply
+additional blurring to intermediate images when the checker is active.
+
+### Watermarking
+
+InvokeAI does not apply any sort of watermark to images it
+generates. However, it does write metadata into the PNG data area,
+including the prompt used to generate the image and relevant parameter
+settings. These fields can be examined using the `sd-metadata.py`
+script that comes with the InvokeAI package.
+
+Note that several other Stable Diffusion distributions offer
+wavelet-based "invisible" watermarking. We have experimented with the
+library used to generate these watermarks and have reached the
+conclusion that while the watermarking library may be adding
+watermarks to PNG images, the currently available version is unable to
+retrieve them successfully. If and when a functioning version of the
+library becomes available, we will offer this feature as well.

docs/features/OTHER.md

@@ -133,29 +133,6 @@ outputs = g.txt2img("a unicorn in manhattan")
 
 Outputs is a list of lists in the format [filename1,seed1],[filename2,seed2]...].
 
-Please see ldm/generate.py for more information. A set of example scripts is coming RSN.
+Please see the documentation in ldm/generate.py for more information.
 
 ---
-
-## **Preload Models**
-
-In situations where you have limited internet connectivity or are blocked behind a firewall, you can
-use the preload script to preload the required files for Stable Diffusion to run.
-
-The preload script `scripts/preload_models.py` needs to be run once at least while connected to the
-internet. In the following runs, it will load up the cached versions of the required files from the
-`.cache` directory of the system.
-
-```bash
-(invokeai) ~/stable-diffusion$ python3 ./scripts/preload_models.py
-preloading bert tokenizer...
-Downloading: 100%|██████████████████████████████████| 28.0/28.0 [00:00<00:00, 49.3kB/s]
-Downloading: 100%|██████████████████████████████████| 226k/226k [00:00<00:00, 2.79MB/s]
-Downloading: 100%|██████████████████████████████████| 455k/455k [00:00<00:00, 4.36MB/s]
-Downloading: 100%|██████████████████████████████████| 570/570 [00:00<00:00, 477kB/s]
-...success
-preloading kornia requirements...
-Downloading: "https://github.com/DagnyT/hardnet/raw/master/pretrained/train_liberty_with_aug/checkpoint_liberty_with_aug.pth" to /u/lstein/.cache/torch/hub/checkpoints/checkpoint_liberty_with_aug.pth
-100%|███████████████████████████████████████████████| 5.10M/5.10M [00:00<00:00, 101MB/s]
-...success
-```

docs/features/OUTPAINTING.md

@@ -6,100 +6,166 @@ title: Outpainting
 
 ## Outpainting and outcropping
 
-Outpainting is a process by which the AI generates parts of the image
-that are outside its original frame. It can be used to fix up images
-in which the subject is off center, or when some detail (often the top
-of someone's head!) is cut off.
+Outpainting is a process by which the AI generates parts of the image that are
+outside its original frame. It can be used to fix up images in which the subject
+is off center, or when some detail (often the top of someone's head!) is cut
+off.
 
-InvokeAI supports two versions of outpainting, one called "outpaint"
-and the other "outcrop." They work slightly differently and each has
-its advantages and drawbacks.
+InvokeAI supports two versions of outpainting, one called "outpaint" and the
+other "outcrop." They work slightly differently and each has its advantages and
+drawbacks.
 
 ### Outpainting
 
-Outpainting is the same as inpainting, except that the painting occurs
-in the regions outside of the original image. To outpaint using the
-`invoke.py` command line script, prepare an image in which the borders
-to be extended are pure black. Add an alpha channel (if there isn't one
-already), and make the borders completely transparent and the interior
-completely opaque. If you wish to modify the interior as well, you may
-create transparent holes in the transparency layer, which `img2img` will
-paint into as usual.
+Outpainting is the same as inpainting, except that the painting occurs in the
+regions outside of the original image. To outpaint using the `invoke.py` command
+line script, prepare an image in which the borders to be extended are pure
+black. Add an alpha channel (if there isn't one already), and make the borders
+completely transparent and the interior completely opaque. If you wish to modify
+the interior as well, you may create transparent holes in the transparency
+layer, which `img2img` will paint into as usual.
 
-Pass the image as the argument to the `-I` switch as you would for
-regular inpainting:
+Pass the image as the argument to the `-I` switch as you would for regular
+inpainting:
 
- invoke> a stream by a river -I /path/to/transparent_img.png
+```bash
+invoke> a stream by a river -I /path/to/transparent_img.png
+```
 
 You'll likely be delighted by the results.
 
 ### Tips
 
-1. Do not try to expand the image too much at once. Generally it is best
-   to expand the margins in 64-pixel increments. 128 pixels often works,
-   but your mileage may vary depending on the nature of the image you are
-   trying to outpaint into.
+1. Do not try to expand the image too much at once. Generally it is best to
+   expand the margins in 64-pixel increments. 128 pixels often works, but your
+   mileage may vary depending on the nature of the image you are trying to
+   outpaint into.
 
-2. There are a series of switches that can be used to adjust how the
-   inpainting algorithm operates. In particular, you can use these to
-   minimize the seam that sometimes appears between the original image
-   and the extended part. These switches are:
+2. There are a series of switches that can be used to adjust how the inpainting
+   algorithm operates. In particular, you can use these to minimize the seam
+   that sometimes appears between the original image and the extended part.
+   These switches are:
 
-  --seam_size SEAM_SIZE    Size of the mask around the seam between original and outpainted image (0)
-  --seam_blur SEAM_BLUR    The amount to blur the seam inwards (0)
-  --seam_strength STRENGTH The img2img strength to use when filling the seam (0.7)
-  --seam_steps SEAM_STEPS  The number of steps to use to fill the seam. (10)
-  --tile_size TILE_SIZE    The tile size to use for filling outpaint areas (32)
+| switch                     | default | description                                                            |
+| -------------------------- | ------- | ---------------------------------------------------------------------- |
+| `--seam_size SEAM_SIZE `   | `0`     | Size of the mask around the seam between original and outpainted image |
+| `--seam_blur SEAM_BLUR`    | `0`     | The amount to blur the seam inwards                                    |
+| `--seam_strength STRENGTH` | `0.7`   | The img2img strength to use when filling the seam                      |
+| `--seam_steps SEAM_STEPS`  | `10`    | The number of steps to use to fill the seam.                           |
+| `--tile_size TILE_SIZE`    | `32`    | The tile size to use for filling outpaint areas                        |
 
 ### Outcrop
 
-The `outcrop` extension gives you a convenient `!fix` postprocessing
-command that allows you to extend a previously-generated image in 64
-pixel increments in any direction. You can apply the module to any
-image previously-generated by InvokeAI. Note that it works with
-arbitrary PNG photographs, but not currently with JPG or other
-formats. Outcropping is particularly effective when combined with the
-[runwayML custom inpainting
-model](INPAINTING.md#using-the-runwayml-inpainting-model).
+The `outcrop` extension gives you a convenient `!fix` postprocessing command
+that allows you to extend a previously-generated image in 64 pixel increments in
+any direction. You can apply the module to any image previously-generated by
+InvokeAI. Note that it works with arbitrary PNG photographs, but not currently
+with JPG or other formats. Outcropping is particularly effective when combined
+with the
+[runwayML custom inpainting model](INPAINTING.md#using-the-runwayml-inpainting-model).
 
 Consider this image:
 
-<div align="center" markdown>
+<figure markdown>
 ![curly_woman](../assets/outpainting/curly.png)
-</div>
+</figure>
 
-Pretty nice, but it's annoying that the top of her head is cut
-off. She's also a bit off center. Let's fix that!
+Pretty nice, but it's annoying that the top of her head is cut off. She's also a
+bit off center. Let's fix that!
 
 ```bash
-invoke> !fix images/curly.png --outcrop top 64 right 64
+invoke> !fix images/curly.png --outcrop top 128 right 64 bottom 64
 ```
 
-This is saying to apply the `outcrop` extension by extending the top
-of the image by 64 pixels, and the right of the image by the same
-amount. You can use any combination of top|left|right|bottom, and
-specify any number of pixels to extend. You can also abbreviate
-`--outcrop` to `-c`.
+This is saying to apply the `outcrop` extension by extending the top of the
+image by 128 pixels, and the right and bottom of the image by 64 pixels. You can
+use any combination of top|left|right|bottom, and specify any number of pixels
+to extend. You can also abbreviate `--outcrop` to `-c`.
 
 The result looks like this:
 
-<div align="center" markdown>
-![curly_woman_outcrop](../assets/outpainting/curly-outcrop.png)
-</div>
+<figure markdown>
+![curly_woman_outcrop](../assets/outpainting/curly-outcrop-2.png)
+</figure>
 
-The new image is actually slightly larger than the original (576x576,
-because 64 pixels were added to the top and right sides.)
+The new image is larger than the original (576x704) because 64 pixels were added
+to the top and right sides. You will need enough VRAM to process an image of
+this size.
+
+#### Outcropping non-InvokeAI images
+
+You can outcrop an arbitrary image that was not generated by InvokeAI,
+but your results will vary. The `inpainting-1.5` model is highly
+recommended, but if not feasible, then you may be able to improve the
+output by conditioning the outcropping with a text prompt that
+describes the scene using the `--new_prompt` argument:
+
+```bash
+invoke> !fix images/vacation.png --outcrop top 128 --new_prompt "family vacation"
+```
+
+You may also provide a different seed for outcropping to use by passing
+`-S<seed>`. A negative seed will generate a new random seed.
 
 A number of caveats:
 
-1. Although you can specify any pixel values, they will be rounded up
-to the nearest multiple of 64. Smaller values are better. Larger
-extensions are more likely to generate artefacts. However, if you wish
-you can run the !fix command repeatedly to cautiously expand the
-image.
+1. Although you can specify any pixel values, they will be rounded up to the
+   nearest multiple of 64. Smaller values are better. Larger extensions are more
+   likely to generate artefacts. However, if you wish you can run the !fix
+   command repeatedly to cautiously expand the image.
 
-2. The extension is stochastic, meaning that each time you run it
-you'll get a slightly different result. You can run it repeatedly
-until you get an image you like. Unfortunately `!fix` does not
-currently respect the `-n` (`--iterations`) argument.
+2. The extension is stochastic, meaning that each time you run it you'll get a
+   slightly different result. You can run it repeatedly until you get an image
+   you like. Unfortunately `!fix` does not currently respect the `-n`
+   (`--iterations`) argument.
 
+3. Your results will be _much_ better if you use the `inpaint-1.5` model
+   released by runwayML and installed by default by `invokeai-configure`.
+   This model was trained specifically to harmoniously fill in image gaps. The
+   standard model will work as well, but you may notice color discontinuities at
+   the border.
+
+4. When using the `inpaint-1.5` model, you may notice subtle changes to the area
+   outside the masked region. This is because the model performs an
+   encoding/decoding on the image as a whole. This does not occur with the
+   standard model.
+
+## Outpaint
+
+The `outpaint` extension does the same thing, but with subtle differences.
+Starting with the same image, here is how we would add an additional 64 pixels
+to the top of the image:
+
+```bash
+invoke> !fix images/curly.png --out_direction top 64
+```
+
+(you can abbreviate `--out_direction` as `-D`.
+
+The result is shown here:
+
+<figure markdown>
+![curly_woman_outpaint](../assets/outpainting/curly-outpaint.png)
+</figure>
+
+Although the effect is similar, there are significant differences from
+outcropping:
+
+- You can only specify one direction to extend at a time.
+- The image is **not** resized. Instead, the image is shifted by the specified
+  number of pixels. If you look carefully, you'll see that less of the lady's
+  torso is visible in the image.
+- Because the image dimensions remain the same, there's no rounding to multiples
+  of 64.
+- Attempting to outpaint larger areas will frequently give rise to ugly ghosting
+  effects.
+- For best results, try increasing the step number.
+- If you don't specify a pixel value in `-D`, it will default to half of the
+  whole image, which is likely not what you want.
+
+!!! tip
+
+    Neither `outpaint` nor `outcrop` are perfect, but we continue to tune
+    and improve them. If one doesn't work, try the other. You may also
+    wish to experiment with other `img2img` arguments, such as `-C`, `-f`
+    and `-s`.

docs/features/POSTPROCESS.md

@@ -6,53 +6,39 @@ title: Postprocessing
 
 ## Intro
 
-This extension provides the ability to restore faces and upscale
-images.
+This extension provides the ability to restore faces and upscale images.
 
-Face restoration and upscaling can be applied at the time you generate
-the images, or at any later time against a previously-generated PNG
-file, using the [!fix](#fixing-previously-generated-images)
-command. [Outpainting and outcropping](OUTPAINTING.md) can only be
-applied after the fact.
+Face restoration and upscaling can be applied at the time you generate the
+images, or at any later time against a previously-generated PNG file, using the
+[!fix](#fixing-previously-generated-images) command.
+[Outpainting and outcropping](OUTPAINTING.md) can only be applied after the
+fact.
 
 ## Face Fixing
 
 The default face restoration module is GFPGAN. The default upscale is
-Real-ESRGAN. For an alternative face restoration module, see [CodeFormer
-Support] below.
+Real-ESRGAN. For an alternative face restoration module, see
+[CodeFormer Support](#codeformer-support) below.
 
-As of version 1.14, environment.yaml will install the Real-ESRGAN
-package into the standard install location for python packages, and
-will put GFPGAN into a subdirectory of "src" in the InvokeAI
-directory. Upscaling with Real-ESRGAN should "just work" without
-further intervention. Simply pass the --upscale (-U) option on the
-invoke> command line, or indicate the desired scale on the popup in
-the Web GUI.
+As of version 1.14, environment.yaml will install the Real-ESRGAN package into
+the standard install location for python packages, and will put GFPGAN into a
+subdirectory of "src" in the InvokeAI directory. Upscaling with Real-ESRGAN
+should "just work" without further intervention. Simply pass the `--upscale`
+(`-U`) option on the `invoke>` command line, or indicate the desired scale on
+the popup in the Web GUI.
 
-**GFPGAN** requires a series of downloadable model files to
-work. These are loaded when you run `scripts/preload_models.py`. If
-GFPAN is failing with an error, please run the following from the
-InvokeAI directory:
+**GFPGAN** requires a series of downloadable model files to work. These are
+loaded when you run `invokeai-configure`. If GFPAN is failing with an
+error, please run the following from the InvokeAI directory:
 
 ```bash
-python scripts/preload_models.py
+invokeai-configure
 ```
 
-If you do not run this script in advance, the GFPGAN module will attempt
-to download the models files the first time you try to perform facial
+If you do not run this script in advance, the GFPGAN module will attempt to
+download the models files the first time you try to perform facial
 reconstruction.
 
-Alternatively, if you have GFPGAN installed elsewhere, or if you are
-using an earlier version of this package which asked you to install
-GFPGAN in a sibling directory, you may use the `--gfpgan_dir` argument
-with `invoke.py` to set a custom path to your GFPGAN directory. _There
-are other GFPGAN related boot arguments if you wish to customize
-further._
-
-## Usage
-
-You will now have access to two new prompt arguments.
-
 ### Upscaling
 
 `-U : <upscaling_factor> <upscaling_strength>`
@@ -119,17 +105,17 @@ actions.
 This repo also allows you to perform face restoration using
 [CodeFormer](https://github.com/sczhou/CodeFormer).
 
-In order to setup CodeFormer to work, you need to download the models
-like with GFPGAN. You can do this either by running
-`preload_models.py` or by manually downloading the [model
-file](https://github.com/sczhou/CodeFormer/releases/download/v0.1.0/codeformer.pth)
+In order to setup CodeFormer to work, you need to download the models like with
+GFPGAN. You can do this either by running `invokeai-configure` or by manually
+downloading the
+[model file](https://github.com/sczhou/CodeFormer/releases/download/v0.1.0/codeformer.pth)
 and saving it to `ldm/invoke/restoration/codeformer/weights` folder.
 
-You can use `-ft` prompt argument to swap between CodeFormer and the
-default GFPGAN. The above mentioned `-G` prompt argument will allow
-you to control the strength of the restoration effect.
+You can use `-ft` prompt argument to swap between CodeFormer and the default
+GFPGAN. The above mentioned `-G` prompt argument will allow you to control the
+strength of the restoration effect.
 
-### Usage
+### CodeFormer Usage
 
 The following command will perform face restoration with CodeFormer instead of
 the default gfpgan.
@@ -157,9 +143,9 @@ situations when there is very little facial data to work with.
 ## Fixing Previously-Generated Images
 
 It is easy to apply face restoration and/or upscaling to any
-previously-generated file. Just use the syntax `!fix path/to/file.png
-<options>`. For example, to apply GFPGAN at strength 0.8 and upscale
-2X for a file named `./outputs/img-samples/000044.2945021133.png`,
+previously-generated file. Just use the syntax
+`!fix path/to/file.png <options>`. For example, to apply GFPGAN at strength 0.8
+and upscale 2X for a file named `./outputs/img-samples/000044.2945021133.png`,
 just run:
 
 ```bash
@@ -170,7 +156,7 @@ A new file named `000044.2945021133.fixed.png` will be created in the output
 directory. Note that the `!fix` command does not replace the original file,
 unlike the behavior at generate time.
 
-### Disabling
+## How to disable
 
 If, for some reason, you do not wish to load the GFPGAN and/or ESRGAN libraries,
 you can disable them on the invoke.py command line with the `--no_restore` and

docs/features/PROMPTS.md

@@ -6,40 +6,82 @@ title: Prompting-Features
 
 ## **Reading Prompts from a File**
 
-You can automate `invoke.py` by providing a text file with the prompts you want to run, one line per
-prompt. The text file must be composed with a text editor (e.g. Notepad) and not a word processor.
-Each line should look like what you would type at the invoke> prompt:
+You can automate `invoke.py` by providing a text file with the prompts you want
+to run, one line per prompt. The text file must be composed with a text editor
+(e.g. Notepad) and not a word processor. Each line should look like what you
+would type at the invoke> prompt:
 
 ```bash
-a beautiful sunny day in the park, children playing -n4 -C10
-stormy weather on a mountain top, goats grazing     -s100
-innovative packaging for a squid's dinner           -S137038382
+"a beautiful sunny day in the park, children playing" -n4 -C10
+"stormy weather on a mountain top, goats grazing" -s100
+"innovative packaging for a squid's dinner" -S137038382
 ```
 
 Then pass this file's name to `invoke.py` when you invoke it:
 
 ```bash
-(invokeai) ~/stable-diffusion$ python3 scripts/invoke.py --from_file "path/to/prompts.txt"
+python scripts/invoke.py --from_file "/path/to/prompts.txt"
 ```
 
-You may read a series of prompts from standard input by providing a filename of `-`:
+You may also read a series of prompts from standard input by providing
+a filename of `-`. For example, here is a python script that creates a
+matrix of prompts, each one varying slightly:
 
 ```bash
-(invokeai) ~/stable-diffusion$ echo "a beautiful day" | python3 scripts/invoke.py --from_file -
+#!/usr/bin/env python
+
+adjectives = ['sunny','rainy','overcast']
+samplers = ['k_lms','k_euler_a','k_heun']
+cfg = [7.5, 9, 11]
+
+for adj in adjectives:
+    for samp in samplers:
+        for cg in cfg:
+            print(f'a {adj} day -A{samp} -C{cg}')
 ```
 
+Its output looks like this (abbreviated):
+
+```bash
+a sunny day -Aklms -C7.5
+a sunny day -Aklms -C9
+a sunny day -Aklms -C11
+a sunny day -Ak_euler_a -C7.5
+a sunny day -Ak_euler_a -C9
+...
+a overcast day -Ak_heun -C9
+a overcast day -Ak_heun -C11
+```
+
+To feed it to invoke.py, pass the filename of "-"
+
+```bash
+python matrix.py | python scripts/invoke.py --from_file -
+```
+
+When the script is finished, each of the 27 combinations
+of adjective, sampler and CFG will be executed.
+
+The command-line interface provides `!fetch` and `!replay` commands
+which allow you to read the prompts from a single previously-generated
+image or a whole directory of them, write the prompts to a file, and
+then replay them. Or you can create your own file of prompts and feed
+them to the command-line client from within an interactive session.
+See [Command-Line Interface](CLI.md) for details.
+
 ---
 
 ## **Negative and Unconditioned Prompts**
 
-Any words between a pair of square brackets will instruct Stable
-Diffusion to attempt to ban the concept from the generated image.
+Any words between a pair of square brackets will instruct Stable Diffusion to
+attempt to ban the concept from the generated image.
 
 ```text
 this is a test prompt [not really] to make you understand [cool] how this works.
 ```
 
-In the above statement, the words 'not really cool` will be ignored by Stable Diffusion.
+In the above statement, the words 'not really cool` will be ignored by Stable
+Diffusion.
 
 Here's a prompt that depicts what it does.
 
@@ -47,33 +89,45 @@ original prompt:
 
 `#!bash "A fantastical translucent pony made of water and foam, ethereal, radiant, hyperalism, scottish folklore, digital painting, artstation, concept art, smooth, 8 k frostbite 3 engine, ultra detailed, art by artgerm and greg rutkowski and magali villeneuve" -s 20 -W 512 -H 768 -C 7.5 -A k_euler_a -S 1654590180`
 
-<div align="center" markdown>
-![step1](../assets/negative_prompt_walkthru/step1.png)
-</div>
+<figure markdown>
 
-That image has a woman, so if we want the horse without a rider, we can influence the image not to have a woman by putting [woman] in the prompt, like this:
+![step1](../assets/negative_prompt_walkthru/step1.png)
+
+</figure>
+
+That image has a woman, so if we want the horse without a rider, we can
+influence the image not to have a woman by putting [woman] in the prompt, like
+this:
 
 `#!bash "A fantastical translucent poney made of water and foam, ethereal, radiant, hyperalism, scottish folklore, digital painting, artstation, concept art, smooth, 8 k frostbite 3 engine, ultra detailed, art by artgerm and greg rutkowski and magali villeneuve [woman]" -s 20 -W 512 -H 768 -C 7.5 -A k_euler_a -S 1654590180`
 
-<div align="center" markdown>
-![step2](../assets/negative_prompt_walkthru/step2.png)
-</div>
+<figure markdown>
 
-That's nice - but say we also don't want the image to be quite so blue. We can add "blue" to the list of negative prompts, so it's now [woman blue]:
+![step2](../assets/negative_prompt_walkthru/step2.png)
+
+</figure>
+
+That's nice - but say we also don't want the image to be quite so blue. We can
+add "blue" to the list of negative prompts, so it's now [woman blue]:
 
 `#!bash "A fantastical translucent poney made of water and foam, ethereal, radiant, hyperalism, scottish folklore, digital painting, artstation, concept art, smooth, 8 k frostbite 3 engine, ultra detailed, art by artgerm and greg rutkowski and magali villeneuve [woman blue]" -s 20 -W 512 -H 768 -C 7.5 -A k_euler_a -S 1654590180`
 
-<div align="center" markdown>
-![step3](../assets/negative_prompt_walkthru/step3.png)
-</div>
+<figure markdown>
 
-Getting close - but there's no sense in having a saddle when our horse doesn't have a rider, so we'll add one more negative prompt: [woman blue saddle].
+![step3](../assets/negative_prompt_walkthru/step3.png)
+
+</figure>
+
+Getting close - but there's no sense in having a saddle when our horse doesn't
+have a rider, so we'll add one more negative prompt: [woman blue saddle].
 
 `#!bash "A fantastical translucent poney made of water and foam, ethereal, radiant, hyperalism, scottish folklore, digital painting, artstation, concept art, smooth, 8 k frostbite 3 engine, ultra detailed, art by artgerm and greg rutkowski and magali villeneuve [woman blue saddle]" -s 20 -W 512 -H 768 -C 7.5 -A k_euler_a -S 1654590180`
 
-<div align="center" markdown>
+<figure markdown>
+
 ![step4](../assets/negative_prompt_walkthru/step4.png)
-</div>
+
+</figure>
 
 !!! notes "Notes about this feature:"
 
@@ -88,92 +142,133 @@ Getting close - but there's no sense in having a saddle when our horse doesn't h
 
 The InvokeAI prompting language has the following features:
 
-### Attention weighting 
-Append a word or phrase with `-` or `+`, or a weight between `0` and `2` (`1`=default), to decrease or increase "attention" (= a mix of per-token CFG weighting multiplier and, for `-`, a weighted blend with the prompt without the term).
+### Attention weighting
+
+Append a word or phrase with `-` or `+`, or a weight between `0` and `2`
+(`1`=default), to decrease or increase "attention" (= a mix of per-token CFG
+weighting multiplier and, for `-`, a weighted blend with the prompt without the
+term).
 
 The following syntax is recognised:
-  * single words without parentheses: `a tall thin man picking apricots+`
-  * single or multiple words with parentheses: `a tall thin man picking (apricots)+` `a tall thin man picking (apricots)-` `a tall thin man (picking apricots)+` `a tall thin man (picking apricots)-` 
-  * more effect with more symbols `a tall thin man (picking apricots)++`
-  * nesting `a tall thin man (picking apricots+)++` (`apricots` effectively gets `+++`)
-  * all of the above with explicit numbers `a tall thin man picking (apricots)1.1` `a tall thin man (picking (apricots)1.3)1.1`. (`+` is equivalent to 1.1, `++` is pow(1.1,2), `+++` is pow(1.1,3), etc; `-` means 0.9, `--` means pow(0.9,2), etc.)
-  * attention also applies to `[unconditioning]` so `a tall thin man picking apricots [(ladder)0.01]` will *very gently* nudge SD away from trying to draw the man on a ladder
 
-You can use this to increase or decrease the amount of something. Starting from this prompt of `a man picking apricots from a tree`, let's see what happens if we increase and decrease how much attention we want Stable Diffusion to pay to the word `apricots`:
+- single words without parentheses: `a tall thin man picking apricots+`
+- single or multiple words with parentheses:
+  `a tall thin man picking (apricots)+` `a tall thin man picking (apricots)-`
+  `a tall thin man (picking apricots)+` `a tall thin man (picking apricots)-`
+- more effect with more symbols `a tall thin man (picking apricots)++`
+- nesting `a tall thin man (picking apricots+)++` (`apricots` effectively gets
+  `+++`)
+- all of the above with explicit numbers `a tall thin man picking (apricots)1.1`
+  `a tall thin man (picking (apricots)1.3)1.1`. (`+` is equivalent to 1.1, `++`
+  is pow(1.1,2), `+++` is pow(1.1,3), etc; `-` means 0.9, `--` means pow(0.9,2),
+  etc.)
+- attention also applies to `[unconditioning]` so
+  `a tall thin man picking apricots [(ladder)0.01]` will _very gently_ nudge SD
+  away from trying to draw the man on a ladder
+
+You can use this to increase or decrease the amount of something. Starting from
+this prompt of `a man picking apricots from a tree`, let's see what happens if
+we increase and decrease how much attention we want Stable Diffusion to pay to
+the word `apricots`:
+
+<figure markdown>
 
 ![an AI generated image of a man picking apricots from a tree](../assets/prompt_syntax/apricots-0.png)
 
+</figure>
+
 Using `-` to reduce apricot-ness:
 
-| `a man picking apricots- from a tree` | `a man picking apricots-- from a tree` | `a man picking apricots--- from a tree` |
-| -- | -- | -- |
+| `a man picking apricots- from a tree`                                                                                          | `a man picking apricots-- from a tree`                                                                                                        | `a man picking apricots--- from a tree`                                                                                                    |
+| ------------------------------------------------------------------------------------------------------------------------------ | --------------------------------------------------------------------------------------------------------------------------------------------- | ------------------------------------------------------------------------------------------------------------------------------------------ |
 | ![an AI generated image of a man picking apricots from a tree, with smaller apricots](../assets/prompt_syntax/apricots--1.png) | ![an AI generated image of a man picking apricots from a tree, with even smaller and fewer apricots](../assets/prompt_syntax/apricots--2.png) | ![an AI generated image of a man picking apricots from a tree, with very few very small apricots](../assets/prompt_syntax/apricots--3.png) |
 
 Using `+` to increase apricot-ness:
 
-| `a man picking apricots+ from a tree` | `a man picking apricots++ from a tree` | `a man picking apricots+++ from a tree` | `a man picking apricots++++ from a tree` | `a man picking apricots+++++ from a tree` |
-| -- | -- | -- | -- | -- |
+| `a man picking apricots+ from a tree`                                                                                                      | `a man picking apricots++ from a tree`                                                                                                              | `a man picking apricots+++ from a tree`                                                                                                                     | `a man picking apricots++++ from a tree`                                                                                                                                           | `a man picking apricots+++++ from a tree`                                                                                                                                                                           |
+| ------------------------------------------------------------------------------------------------------------------------------------------ | --------------------------------------------------------------------------------------------------------------------------------------------------- | ----------------------------------------------------------------------------------------------------------------------------------------------------------- | ---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
 | ![an AI generated image of a man picking apricots from a tree, with larger, more vibrant apricots](../assets/prompt_syntax/apricots-1.png) | ![an AI generated image of a man picking apricots from a tree with even larger, even more vibrant apricots](../assets/prompt_syntax/apricots-2.png) | ![an AI generated image of a man picking apricots from a tree, but the man has been replaced by a pile of apricots](../assets/prompt_syntax/apricots-3.png) | ![an AI generated image of a man picking apricots from a tree, but the man has been replaced by a mound of giant melting-looking apricots](../assets/prompt_syntax/apricots-4.png) | ![an AI generated image of a man picking apricots from a tree, but the man and the leaves and parts of the ground have all been replaced by giant melting-looking apricots](../assets/prompt_syntax/apricots-5.png) |
 
-You can also change the balance between different parts of a prompt. For example, below is a `mountain man`:
+You can also change the balance between different parts of a prompt. For
+example, below is a `mountain man`:
+
+<figure markdown>
 
 ![an AI generated image of a mountain man](../assets/prompt_syntax/mountain-man.png)
 
+</figure>
+
 And here he is with more mountain:
 
-| `mountain+ man` | `mountain++ man` | `mountain+++ man` | 
-| -- | -- | -- |
+| `mountain+ man`                                | `mountain++ man`                               | `mountain+++ man`                              |
+| ---------------------------------------------- | ---------------------------------------------- | ---------------------------------------------- |
 | ![](../assets/prompt_syntax/mountain1-man.png) | ![](../assets/prompt_syntax/mountain2-man.png) | ![](../assets/prompt_syntax/mountain3-man.png) |
 
 Or, alternatively, with more man:
 
-| `mountain man+` | `mountain man++` | `mountain man+++` | `mountain man++++` | 
-| -- | -- | -- | -- |
+| `mountain man+`                                | `mountain man++`                               | `mountain man+++`                              | `mountain man++++`                             |
+| ---------------------------------------------- | ---------------------------------------------- | ---------------------------------------------- | ---------------------------------------------- |
 | ![](../assets/prompt_syntax/mountain-man1.png) | ![](../assets/prompt_syntax/mountain-man2.png) | ![](../assets/prompt_syntax/mountain-man3.png) | ![](../assets/prompt_syntax/mountain-man4.png) |
 
 ### Blending between prompts
 
-* `("a tall thin man picking apricots", "a tall thin man picking pears").blend(1,1)`
-* The existing prompt blending using `:<weight>` will continue to be supported - `("a tall thin man picking apricots", "a tall thin man picking pears").blend(1,1)` is equivalent to `a tall thin man picking apricots:1 a tall thin man picking pears:1` in the old syntax.
-* Attention weights can be nested inside blends.
-* Non-normalized blends are supported by passing `no_normalize` as an additional argument to the blend weights, eg `("a tall thin man picking apricots", "a tall thin man picking pears").blend(1,-1,no_normalize)`. very fun to explore local maxima in the feature space, but also easy to produce garbage output.
+- `("a tall thin man picking apricots", "a tall thin man picking pears").blend(1,1)`
+- The existing prompt blending using `:<weight>` will continue to be supported -
+  `("a tall thin man picking apricots", "a tall thin man picking pears").blend(1,1)`
+  is equivalent to
+  `a tall thin man picking apricots:1 a tall thin man picking pears:1` in the
+  old syntax.
+- Attention weights can be nested inside blends.
+- Non-normalized blends are supported by passing `no_normalize` as an additional
+  argument to the blend weights, eg
+  `("a tall thin man picking apricots", "a tall thin man picking pears").blend(1,-1,no_normalize)`.
+  very fun to explore local maxima in the feature space, but also easy to
+  produce garbage output.
 
-See the section below on "Prompt Blending" for more information about how this works.
+See the section below on "Prompt Blending" for more information about how this
+works.
 
 ### Cross-Attention Control ('prompt2prompt')
 
-Sometimes an image you generate is almost right, and you just want to
-change one detail without affecting the rest. You could use a photo editor and inpainting
-to overpaint the area, but that's a pain. Here's where `prompt2prompt`
-comes in handy.
+Sometimes an image you generate is almost right, and you just want to change one
+detail without affecting the rest. You could use a photo editor and inpainting
+to overpaint the area, but that's a pain. Here's where `prompt2prompt` comes in
+handy.
 
-Generate an image with a given prompt, record the seed of the image,
-and then use the `prompt2prompt` syntax to substitute words in the
-original prompt for words in a new prompt. This works for `img2img` as well.
+Generate an image with a given prompt, record the seed of the image, and then
+use the `prompt2prompt` syntax to substitute words in the original prompt for
+words in a new prompt. This works for `img2img` as well.
 
-* `a ("fluffy cat").swap("smiling dog") eating a hotdog`.
-  * quotes optional: `a (fluffy cat).swap(smiling dog) eating a hotdog`.
-  * for single word substitutions parentheses are also optional: `a cat.swap(dog) eating a hotdog`.
-* Supports options `s_start`, `s_end`, `t_start`, `t_end` (each 0-1) loosely corresponding to bloc97's `prompt_edit_spatial_start/_end` and `prompt_edit_tokens_start/_end` but with the math swapped to make it easier to intuitively understand.
-  * Example usage:`a (cat).swap(dog, s_end=0.3) eating a hotdog` - the `s_end` argument means that the "spatial" (self-attention) edit will stop having any effect after 30% (=0.3) of the steps have been done, leaving Stable Diffusion with 70% of the steps where it is free to decide for itself how to reshape the cat-form into a dog form. 
-  * The numbers represent a percentage through the step sequence where the edits should happen. 0 means the start (noisy starting image), 1 is the end (final image).
-    * For img2img, the step sequence does not start at 0 but instead at (1-strength) - so if strength is 0.7, s_start and s_end must both be greater than 0.3 (1-0.7) to have any effect. 
-* Convenience option `shape_freedom` (0-1) to specify how much "freedom" Stable Diffusion should have to change the shape of the subject being swapped. 
-  * `a (cat).swap(dog, shape_freedom=0.5) eating a hotdog`.
+For example, consider the prompt `a cat.swap(dog) playing with a ball in the forest`. Normally, because of the word words interact with each other when doing a stable diffusion image generation, these two prompts would generate different compositions:
+  - `a cat playing with a ball in the forest`
+  - `a dog playing with a ball in the forest`
+
+| `a cat playing with a ball in the forest` | `a dog playing with a ball in the forest` |
+| --- | --- |
+| img | img |
 
 
+      - For multiple word swaps, use parentheses: `a (fluffy cat).swap(barking dog) playing with a ball in the forest`.
+      - To swap a comma, use quotes: `a ("fluffy, grey cat").swap("big, barking dog") playing with a ball in the forest`.
+- Supports options `t_start` and `t_end` (each 0-1) loosely corresponding to bloc97's `prompt_edit_tokens_start/_end` but with the math swapped to make it easier to
+  intuitively understand. `t_start` and `t_end` are used to control on which steps cross-attention control should run. With the default values `t_start=0` and `t_end=1`, cross-attention control is active on every step of image generation. Other values can be used to turn cross-attention control off for part of the image generation process.
+    - For example, if doing a diffusion with 10 steps for the prompt is `a cat.swap(dog, t_start=0.3, t_end=1.0) playing with a ball in the forest`, the first 3 steps will be run as `a cat playing with a ball in the forest`, while the last 7 steps will run as `a dog playing with a ball in the forest`, but the pixels that represent `dog` will be locked to the pixels that would have represented `cat` if the `cat` prompt had been used instead.
+    - Conversely, for `a cat.swap(dog, t_start=0, t_end=0.7) playing with a ball in the forest`, the first 7 steps will run as `a dog playing with a ball in the forest` with the pixels that represent `dog` locked to the same pixels that would have represented `cat` if the `cat` prompt was being used instead. The final 3 steps will just run `a cat playing with a ball in the forest`.
+    > For img2img, the step sequence does not start at 0 but instead at `(1.0-strength)` - so if the img2img `strength` is `0.7`, `t_start` and `t_end` must both be greater than `0.3` (`1.0-0.7`) to have any effect.
 
-The `prompt2prompt` code is based off [bloc97's
-colab](https://github.com/bloc97/CrossAttentionControl).
+Prompt2prompt `.swap()` is not compatible with xformers, which will be temporarily disabled when doing a `.swap()` - so you should expect to use more VRAM and run slower that with xformers enabled.
 
-Note that `prompt2prompt` is not currently working with the runwayML
-inpainting model, and may never work due to the way this model is set
-up. If you attempt to use `prompt2prompt` you will get the original
-image back. However, since this model is so good at inpainting, a
-good substitute is to use the `clipseg` text masking option:
+The `prompt2prompt` code is based off
+[bloc97's colab](https://github.com/bloc97/CrossAttentionControl).
 
-```
-invoke> a fluffy cat eating a hotdot
+Note that `prompt2prompt` is not currently working with the runwayML inpainting
+model, and may never work due to the way this model is set up. If you attempt to
+use `prompt2prompt` you will get the original image back. However, since this
+model is so good at inpainting, a good substitute is to use the `clipseg` text
+masking option:
+
+```bash
+invoke> a fluffy cat eating a hotdog
 Outputs:
 [1010] outputs/000025.2182095108.png: a fluffy cat eating a hotdog
 invoke> a smiling dog eating a hotdog -I 000025.2182095108.png -tm cat
@@ -181,94 +276,104 @@ invoke> a smiling dog eating a hotdog -I 000025.2182095108.png -tm cat
 
 ### Escaping parantheses () and speech marks ""
 
-If the model you are using has parentheses () or speech marks "" as
-part of its syntax, you will need to "escape" these using a backslash,
-so that`(my_keyword)` becomes `\(my_keyword\)`. Otherwise, the prompt
-parser will attempt to interpret the parentheses as part of the prompt
-syntax and it will get confused.
+If the model you are using has parentheses () or speech marks "" as part of its
+syntax, you will need to "escape" these using a backslash, so that`(my_keyword)`
+becomes `\(my_keyword\)`. Otherwise, the prompt parser will attempt to interpret
+the parentheses as part of the prompt syntax and it will get confused.
+
+---
 
 ## **Prompt Blending**
 
-You may blend together different sections of the prompt to explore the
-AI's latent semantic space and generate interesting (and often
-surprising!) variations. The syntax is:
+You may blend together different sections of the prompt to explore the AI's
+latent semantic space and generate interesting (and often surprising!)
+variations. The syntax is:
 
 ```bash
 blue sphere:0.25 red cube:0.75 hybrid
 ```
 
-This will tell the sampler to blend 25% of the concept of a blue
-sphere with 75% of the concept of a red cube. The blend weights can
-use any combination of integers and floating point numbers, and they
-do not need to add up to 1. Everything to the left of the `:XX` up to
-the previous `:XX` is used for merging, so the overall effect is:
+This will tell the sampler to blend 25% of the concept of a blue sphere with 75%
+of the concept of a red cube. The blend weights can use any combination of
+integers and floating point numbers, and they do not need to add up to 1.
+Everything to the left of the `:XX` up to the previous `:XX` is used for
+merging, so the overall effect is:
 
 ```bash
 0.25 * "blue sphere" + 0.75 * "white duck" + hybrid
 ```
 
-Because you are exploring the "mind" of the AI, the AI's way of mixing
-two concepts may not match yours, leading to surprising effects. To
-illustrate, here are three images generated using various combinations
-of blend weights. As usual, unless you fix the seed, the prompts will give you
-different results each time you run them.
+Because you are exploring the "mind" of the AI, the AI's way of mixing two
+concepts may not match yours, leading to surprising effects. To illustrate, here
+are three images generated using various combinations of blend weights. As
+usual, unless you fix the seed, the prompts will give you different results each
+time you run them.
 
----
+<figure markdown>
 
-<div align="center" markdown>
 ### "blue sphere, red cube, hybrid"
-</div>
 
-This example doesn't use melding at all and represents the default way
-of mixing concepts.
+</figure>
+
+This example doesn't use melding at all and represents the default way of mixing
+concepts.
+
+<figure markdown>
 
-<div align="center" markdown>
 ![blue-sphere-red-cube-hyprid](../assets/prompt-blending/blue-sphere-red-cube-hybrid.png)
-</div>
 
-It's interesting to see how the AI expressed the concept of "cube" as
-the four quadrants of the enclosing frame. If you look closely, there
-is depth there, so the enclosing frame is actually a cube.
+</figure>
+
+It's interesting to see how the AI expressed the concept of "cube" as the four
+quadrants of the enclosing frame. If you look closely, there is depth there, so
+the enclosing frame is actually a cube.
+
+<figure markdown>
 
-<div align="center" markdown>
 ### "blue sphere:0.25 red cube:0.75 hybrid"
 
 ![blue-sphere-25-red-cube-75](../assets/prompt-blending/blue-sphere-0.25-red-cube-0.75-hybrid.png)
-</div>
 
-Now that's interesting. We get neither a blue sphere nor a red cube,
-but a red sphere embedded in a brick wall, which represents a melding
-of concepts within the AI's "latent space" of semantic
-representations. Where is Ludwig Wittgenstein when you need him?
+</figure>
+
+Now that's interesting. We get neither a blue sphere nor a red cube, but a red
+sphere embedded in a brick wall, which represents a melding of concepts within
+the AI's "latent space" of semantic representations. Where is Ludwig
+Wittgenstein when you need him?
+
+<figure markdown>
 
-<div align="center" markdown>
 ### "blue sphere:0.75 red cube:0.25 hybrid"
 
 ![blue-sphere-75-red-cube-25](../assets/prompt-blending/blue-sphere-0.75-red-cube-0.25-hybrid.png)
-</div>
 
-Definitely more blue-spherey. The cube is gone entirely, but it's
-really cool abstract art.
+</figure>
+
+Definitely more blue-spherey. The cube is gone entirely, but it's really cool
+abstract art.
+
+<figure markdown>
 
-<div align="center" markdown>
 ### "blue sphere:0.5 red cube:0.5 hybrid"
 
 ![blue-sphere-5-red-cube-5-hybrid](../assets/prompt-blending/blue-sphere-0.5-red-cube-0.5-hybrid.png)
-</div>
 
-Whoa...! I see blue and red, but no spheres or cubes. Is the word
-"hybrid" summoning up the concept of some sort of scifi creature?
-Let's find out.
+</figure>
+
+Whoa...! I see blue and red, but no spheres or cubes. Is the word "hybrid"
+summoning up the concept of some sort of scifi creature? Let's find out.
+
+<figure markdown>
 
-<div align="center" markdown>
 ### "blue sphere:0.5 red cube:0.5"
 
 ![blue-sphere-5-red-cube-5](../assets/prompt-blending/blue-sphere-0.5-red-cube-0.5.png)
-</div>
 
-Indeed, removing the word "hybrid" produces an image that is more like
-what we'd expect.
+</figure>
 
-In conclusion, prompt blending is great for exploring creative space,
-but can be difficult to direct. A forthcoming release of InvokeAI will
-feature more deterministic prompt weighting.
+Indeed, removing the word "hybrid" produces an image that is more like what we'd
+expect.
+
+In conclusion, prompt blending is great for exploring creative space, but can be
+difficult to direct. A forthcoming release of InvokeAI will feature more
+deterministic prompt weighting.