final documentation fixes prior to release

this will help the readability of issues a lot 🤓

.dockerignore

@@ -1,9 +1,3 @@
 *
-!invokeai
+!environment*.yml
-!pyproject.toml
+!docker-build
-!docker/docker-entrypoint.sh
-!LICENSE
-
-**/node_modules
-**/__pycache__
-**/*.egg-info

.editorconfig

@@ -1,12 +0,0 @@
-# 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

@@ -1 +0,0 @@
-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

@@ -1,34 +1,4 @@
-# continuous integration
+ldm/invoke/pngwriter.py @CapableWeb
-/.github/workflows/  @lstein @blessedcoolant
+ldm/invoke/server_legacy.py @CapableWeb
-
+scripts/legacy_api.py @CapableWeb
-# documentation
+tests/legacy_tests.sh @CapableWeb
-/docs/ @lstein @blessedcoolant @hipsterusername
-/mkdocs.yml @lstein  @blessedcoolant
-
-# nodes
-/invokeai/app/ @Kyle0654 @blessedcoolant
-
-# installation and configuration
-/pyproject.toml  @lstein @blessedcoolant
-/docker/  @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 @maryhipp
-/invokeai/backend @blessedcoolant @psychedelicious @lstein @maryhipp
-
-# generation, model management, postprocessing
-/invokeai/backend  @damian0815 @lstein @blessedcoolant @jpphoto @gregghelt2 @StAlKeR7779
-
-# front ends
-/invokeai/frontend/CLI @lstein
-/invokeai/frontend/install @lstein @ebr  
-/invokeai/frontend/merge @lstein @blessedcoolant 
-/invokeai/frontend/training @lstein @blessedcoolant 
-/invokeai/frontend/web @psychedelicious @blessedcoolant @maryhipp 
-
-

.github/ISSUE_TEMPLATE/BUG_REPORT.yml

@@ -65,16 +65,6 @@ body:
       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

.github/stale.yaml

@@ -1,19 +0,0 @@
-# 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

@@ -1,115 +1,42 @@
+# 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'
-    paths:
+      - 'development'
-      - 'pyproject.toml'
+  pull_request:
-      - '.dockerignore'
+    branches:
-      - 'invokeai/**'
+      - 'main'
-      - 'docker/Dockerfile'
+      - 'development'
-      - 'docker/docker-entrypoint.sh'
-      - 'workflows/build-container.yml'
-    tags:
-      - 'v*'
-  workflow_dispatch:
-
-permissions:
-  contents: write
-  packages: write
 
 jobs:
   docker:
-    if: github.event.pull_request.draft == false
-    strategy:
-      fail-fast: false
-      matrix:
-        gpu-driver:
-        - cuda
-        - cpu
-        - rocm
     runs-on: ubuntu-latest
-    name: ${{ matrix.gpu-driver }}
-    env:
-      # torch/arm64 does not support GPU currently, so arm64 builds
-      # would not be GPU-accelerated.
-      # re-enable arm64 if there is sufficient demand.
-      # PLATFORMS: 'linux/amd64,linux/arm64'
-      PLATFORMS: 'linux/amd64'
     steps:
-      - name: Free up more disk space on the runner
+      - name: prepare docker-tag
-        # https://github.com/actions/runner-images/issues/2840#issuecomment-1284059930
+        env:
-        run: |
+          repository: ${{ github.repository }}
-          sudo rm -rf /usr/share/dotnet
+        run: echo "dockertag=${repository,,}" >> $GITHUB_ENV
-          sudo rm -rf "$AGENT_TOOLSDIRECTORY"
-          sudo swapoff /mnt/swapfile
-          sudo rm -rf /mnt/swapfile
-
       - 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 }}
-            ${{ env.DOCKERHUB_REPOSITORY }}
-          tags: |
-            type=ref,event=branch
-            type=ref,event=tag
-            type=pep440,pattern={{version}}
-            type=pep440,pattern={{major}}.{{minor}}
-            type=pep440,pattern={{major}}
-            type=sha,enable=true,prefix=sha-,format=short
-          flavor: |
-            latest=${{ matrix.gpu-driver == 'cuda' && github.ref == 'refs/heads/main' }}
-            suffix=-${{ matrix.gpu-driver }},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:
-          platforms: ${{ env.PLATFORMS }}
+          path: /tmp/.buildx-cache
-
+          key: buildx-${{ hashFiles('docker-build/Dockerfile') }}
-      - 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
-        id: docker_build
+        uses: docker/build-push-action@v3
-        uses: docker/build-push-action@v4
         with:
           context: .
-          file: docker/Dockerfile
+          file: docker-build/Dockerfile
-          platforms: ${{ env.PLATFORMS }}
+          platforms: linux/amd64
-          push: ${{ github.ref == 'refs/heads/main' || github.ref_type == 'tag' }}
+          push: false
-          tags: ${{ steps.meta.outputs.tags }}
+          tags: ${{ env.dockertag }}:latest
-          labels: ${{ steps.meta.outputs.labels }}
+          cache-from: type=local,src=/tmp/.buildx-cache
-          cache-from: |
+          cache-to: type=local,dest=/tmp/.buildx-cache
-            type=gha,scope=${{ github.ref_name }}-${{ matrix.gpu-driver }}
-            type=gha,scope=main-${{ matrix.gpu-driver }}
-          cache-to: type=gha,mode=max,scope=${{ github.ref_name }}-${{ matrix.gpu-driver }}
-
-      # - 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

@@ -1,34 +0,0 @@
-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

@@ -1,27 +0,0 @@
-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

@@ -0,0 +1,80 @@
+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

@@ -1,37 +0,0 @@
-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-material.yml

@@ -2,19 +2,12 @@ name: mkdocs-material
 on:
   push:
     branches:
-      - 'refs/heads/v2.3'
+      - 'main'
-
+      - 'development'
-permissions:
-    contents: write
 
 jobs:
   mkdocs-material:
-    if: github.event.pull_request.draft == false
     runs-on: ubuntu-latest
-    env:
-      REPO_URL: '${{ github.server_url }}/${{ github.repository }}'
-      REPO_NAME: '${{ github.repository }}'
-      SITE_URL: 'https://${{ github.repository_owner }}.github.io/InvokeAI'
     steps:
       - name: checkout sources
         uses: actions/checkout@v3
@@ -25,15 +18,11 @@ jobs:
         uses: actions/setup-python@v4
         with:
           python-version: '3.10'
-          cache: pip
-          cache-dependency-path: pyproject.toml
 
       - name: install requirements
-        env:
-          PIP_USE_PEP517: 1
         run: |
           python -m \
-            pip install ".[docs]"
+            pip install -r requirements-mkdocs.txt
 
       - name: confirm buildability
         run: |
@@ -43,7 +32,7 @@ jobs:
             --verbose
 
       - name: deploy to gh-pages
-        if: ${{ github.ref == 'refs/heads/v2.3' }}
+        if: ${{ github.ref == 'refs/heads/main' }}
         run: |
           python -m \
             mkdocs gh-deploy \

.github/workflows/pyflakes.yml

@@ -1,20 +0,0 @@
-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

@@ -1,41 +0,0 @@
-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

@@ -0,0 +1,113 @@
+name: Test invoke.py
+on:
+  push:
+    branches:
+      - 'main'
+      - 'development'
+      - 'fix-gh-actions-fork'
+  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/sd-v1-4.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: ${{ matrix.default-shell }}
+    steps:
+      - name: Checkout sources
+        id: checkout-sources
+        uses: actions/checkout@v3
+
+      - name: create models.yaml from example
+        run: cp configs/models.yaml.example configs/models.yaml
+
+      - name: Use cached conda packages
+        id: use-cached-conda-packages
+        uses: actions/cache@v3
+        with:
+          path: ~/conda_pkgs_dir
+          key: conda-pkgs-${{ 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

@@ -1,50 +0,0 @@
-name: Test invoke.py pip
-
-# This is a dummy stand-in for the actual tests
-# we don't need to run python tests on non-Python changes
-# But PRs require passing tests to be mergeable
-
-on:
-  pull_request:
-    paths:
-      - '**'
-      - '!pyproject.toml'
-      - '!invokeai/**'
-      - '!tests/**'
-      - '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:
-          - '3.10'
-        pytorch:
-          - linux-cuda-11_7
-          - linux-rocm-5_2
-          - linux-cpu
-          - macos-default
-          - windows-cpu
-        include:
-          - pytorch: linux-cuda-11_7
-            os: ubuntu-22.04
-          - pytorch: linux-rocm-5_2
-            os: ubuntu-22.04
-          - pytorch: linux-cpu
-            os: ubuntu-22.04
-          - pytorch: macos-default
-            os: macOS-12
-          - pytorch: windows-cpu
-            os: windows-2022
-    name: ${{ matrix.pytorch }} on ${{ matrix.python-version }}
-    runs-on: ${{ matrix.os }}
-    steps:
-      - name: skip
-        run: echo "no build required"

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

@@ -1,123 +0,0 @@
-name: Test invoke.py pip
-on:
-  push:
-    branches:
-      - 'main'
-    paths:
-      - 'pyproject.toml'
-      - 'invokeai/**'
-      - '!invokeai/frontend/web/**'
-  pull_request:
-    paths:
-      - 'pyproject.toml'
-      - 'invokeai/**'
-      - 'tests/**'
-      - '!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_7
-          - linux-rocm-5_2
-          - linux-cpu
-          - macos-default
-          - windows-cpu
-        include:
-          - 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
-    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
-        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: run invokeai-configure
-      #   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
-      #     INVOKEAI_OUTDIR: ${{ github.workspace }}/results
-      #   run: >
-      #     invokeai
-      #     --no-patchmatch
-      #     --no-nsfw_checker
-      #     --precision=float32
-      #     --always_use_cpu
-      #     --use_memory_db
-      #     --outdir ${{ env.INVOKEAI_OUTDIR }}/${{ matrix.python-version }}/${{ matrix.pytorch }}
-      #     --from_file ${{ env.TEST_PROMPTS }}
-
-      # - name: Archive results
-      #   env:
-      #     INVOKEAI_OUTDIR: ${{ github.workspace }}/results
-      #   uses: actions/upload-artifact@v3
-      #   with:
-      #     name: results
-      #     path: ${{ env.INVOKEAI_OUTDIR }}

.gitignore

@@ -1,16 +1,10 @@
 # ignore default image save location and model symbolic link
-.idea/
-embeddings/
 outputs/
 models/ldm/stable-diffusion-v1/model.ckpt
-**/restoration/codeformer/weights
+ldm/invoke/restoration/codeformer/weights
-
 # ignore user models config
 configs/models.user.yaml
 config/models.user.yml
-invokeai.init
-.version
-.last_model
 
 # ignore the Anaconda/Miniconda installer used while building Docker image
 anaconda.sh
@@ -34,7 +28,7 @@ __pycache__/
 .Python
 build/
 develop-eggs/
-# dist/
+dist/
 downloads/
 eggs/
 .eggs/
@@ -65,21 +59,16 @@ 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/
-notes/
 
 # Translations
 *.mo
@@ -202,11 +191,8 @@ checkpoints
 # If it's a Mac
 .DS_Store
 
-invokeai/frontend/yarn.lock
-invokeai/frontend/node_modules
-
 # Let the frontend manage its own gitignore
-!invokeai/frontend/web/*
+!frontend/*
 
 # Scratch folder
 .scratch/
@@ -214,24 +200,11 @@ invokeai/frontend/node_modules
 gfpgan/
 models/ldm/stable-diffusion-v1/*.sha256
 
-
 # GFPGAN model files
 gfpgan/
 
 # config file (will be created by installer)
 configs/models.yaml
 
-# ignore initfile
+# weights (will be created by installer)
-.invokeai
+models/ldm/stable-diffusion-v1/*.ckpt
-
-# 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

@@ -1,128 +0,0 @@
-# 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

@@ -1,84 +0,0 @@
-<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

@@ -1,176 +1,21 @@
-                                 Apache License
+MIT License
-                           Version 2.0, January 2004
-                        http://www.apache.org/licenses/
 
-   TERMS AND CONDITIONS FOR USE, REPRODUCTION, AND DISTRIBUTION
+Copyright (c) 2022 InvokeAI Team
 
-   1. Definitions.
+Permission is hereby granted, free of charge, to any person obtaining a copy
+of this software and associated documentation files (the "Software"), to deal
+in the Software without restriction, including without limitation the rights
+to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
+copies of the Software, and to permit persons to whom the Software is
+furnished to do so, subject to the following conditions:
 
-      "License" shall mean the terms and conditions for use, reproduction,
+The above copyright notice and this permission notice shall be included in all
-      and distribution as defined by Sections 1 through 9 of this document.
+copies or substantial portions of the Software.
 
-      "Licensor" shall mean the copyright owner or entity authorized by
+THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
-      the copyright owner that is granting the License.
+IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
-
+FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
-      "Legal Entity" shall mean the union of the acting entity and all
+AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
-      other entities that control, are controlled by, or are under common
+LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
-      control with that entity. For the purposes of this definition,
+OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
-      "control" means (i) the power, direct or indirect, to cause the
+SOFTWARE.
-      direction or management of such entity, whether by contract or
-      otherwise, or (ii) ownership of fifty percent (50%) or more of the
-      outstanding shares, or (iii) beneficial ownership of such entity.
-
-      "You" (or "Your") shall mean an individual or Legal Entity
-      exercising permissions granted by this License.
-
-      "Source" form shall mean the preferred form for making modifications,
-      including but not limited to software source code, documentation
-      source, and configuration files.
-
-      "Object" form shall mean any form resulting from mechanical
-      transformation or translation of a Source form, including but
-      not limited to compiled object code, generated documentation,
-      and conversions to other media types.
-
-      "Work" shall mean the work of authorship, whether in Source or
-      Object form, made available under the License, as indicated by a
-      copyright notice that is included in or attached to the work
-      (an example is provided in the Appendix below).
-
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-      form, that is based on (or derived from) the Work and for which the
-      editorial revisions, annotations, elaborations, or other modifications
-      represent, as a whole, an original work of authorship. For the purposes
-      of this License, Derivative Works shall not include works that remain
-      separable from, or merely link (or bind by name) to the interfaces of,
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-      whether in tort (including negligence), contract, or otherwise,
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-      Work (including but not limited to damages for loss of goodwill,
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-   9. Accepting Warranty or Additional Liability. While redistributing
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-
-   

README.md

@@ -1,22 +1,23 @@
 <div align="center">
 
-![project hero](https://github.com/invoke-ai/InvokeAI/assets/31807370/1a917d94-e099-4fa1-a70f-7dd8d0691018)
+# InvokeAI: A Stable Diffusion Toolkit
 
-# Invoke AI - Generative AI for Professional Creatives
+_Formerly known as lstein/stable-diffusion_
-## Professional Creative Tools for Stable Diffusion, Custom-Trained Models, and more. 
-  To learn more about Invoke AI, get started instantly, or implement our Business solutions, visit [invoke.ai](https://invoke.ai)
 
+![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] [![latest commit to main badge]][latest commit to main 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]
 
-[![github open issues badge]][github open issues link] [![github open prs badge]][github open prs link] [![translation status badge]][translation status link]
+[![github open issues badge]][github open issues link] [![github open prs badge]][github open prs 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?query=branch%3Amain
+[CI checks on main link]: https://github.com/invoke-ai/InvokeAI/actions/workflows/test-invoke-conda.yml
 [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
@@ -27,356 +28,174 @@
 [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 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 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 main link]: https://github.com/invoke-ai/InvokeAI/commits/main
+[latest commit to dev link]: https://github.com/invoke-ai/InvokeAI/commits/development
 [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>
 
-_**Note: This is an alpha release. Bugs are expected and not all
+This is a fork of
-features are fully implemented. Please use the GitHub [Issues
+[CompVis/stable-diffusion](https://github.com/CompVis/stable-diffusion),
-pages](https://github.com/invoke-ai/InvokeAI/issues?q=is%3Aissue+is%3Aopen)
+the open source text-to-image generator. It provides a streamlined
-to report unexpected problems. Also note that InvokeAI root directory
+process with various new features and options to aid the image
-which contains models, outputs and configuration files, has changed
+generation process. It runs on Windows, Mac and Linux machines, with
-between the 2.x and 3.x release. If you wish to use your v2.3 root
+GPU cards with as little as 4 GB of RAM. It provides both a polished
-directory with v3.0, please follow the directions in [Migrating a 2.3
+Web interface (see below), and an easy-to-use command-line interface.
-root directory to 3.0](#migrating-to-3).**_
 
-InvokeAI is a leading creative engine built to empower professionals
+**Quick links**: [<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>]
-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**: [[How to
+<div align="center"><img src="docs/assets/invoke-web-server-1.png" width=640></div>
-  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">
 
-![canvas preview](https://github.com/invoke-ai/InvokeAI/raw/main/docs/assets/canvas_preview.png)
+_Note: This fork is rapidly evolving. Please use the
-
+[Issues](https://github.com/invoke-ai/InvokeAI/issues) tab to report bugs and make feature
-</div>
+requests. Be sure to use the provided templates. They will help aid diagnose issues faster._
 
 ## Table of Contents
 
-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)
 
-**Getting Started**
+### Installation
-1. 🏁 [Quick Start](#quick-start) 
-3. 🖥️ [Hardware Requirements](#hardware-requirements) 
 
-**More About Invoke**
+This fork is supported across multiple platforms. You can find individual installation instructions
-1. 🌟 [Features](#features) 
+below.
-2. 📣 [Latest Changes](#latest-changes) 
-3. 🛠️ [Troubleshooting](#troubleshooting) 
 
-**Supporting the Project**
+- #### [Linux](https://invoke-ai.github.io/InvokeAI/installation/INSTALL_LINUX/)
-1. 🤝 [Contributing](#contributing) 
-2. 👥 [Contributors](#contributors) 
-3. 💕 [Support](#support) 
 
-## Quick Start
+- #### [Windows](https://invoke-ai.github.io/InvokeAI/installation/INSTALL_WINDOWS/)
 
-For full installation and upgrade instructions, please see:
+- #### [Macintosh](https://invoke-ai.github.io/InvokeAI/installation/INSTALL_MAC/)
-[InvokeAI Installation Overview](https://invoke-ai.github.io/InvokeAI/installation/)
 
-If upgrading from version 2.3, please read [Migrating a 2.3 root
+### Hardware Requirements
-directory to 3.0](#migrating-to-3) first.
 
-### Automatic Installer (suggested for 1st time users)
+#### System
 
-1. Go to the bottom of the [Latest Release Page](https://github.com/invoke-ai/InvokeAI/releases/latest)
+You wil need one of the following:
-
-2. Download the .zip file for your OS (Windows/macOS/Linux).
-
-3. Unzip the file.
-
-4. **Windows:** double-click on the `install.bat` script. **macOS:** Open a Terminal window, drag the file `install.sh` from Finder
-into the Terminal, and press return. **Linux:** run `install.sh`.
-
-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 developers and 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 non-GPU systems:_
-    ```terminal
-    pip install InvokeAI --use-pep517 --extra-index-url https://download.pytorch.org/whl/cpu
-    ``` 
-
-    _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/)
-
-<a name="migrating-to-3"></a>
-### Migrating a v2.3 InvokeAI root directory
-
-The InvokeAI root directory is where the InvokeAI startup file,
-installed models, and generated images are stored. It is ordinarily
-named `invokeai` and located in your home directory. The contents and
-layout of this directory has changed between versions 2.3 and 3.0 and
-cannot be used directly.
-
-We currently recommend that you use the installer to create a new root
-directory named differently from the 2.3 one, e.g. `invokeai-3` and
-then use a migration script to copy your 2.3 models into the new
-location. However, if you choose, you can upgrade this directory in
-place.  This section gives both recipes.
-
-#### Creating a new root directory and migrating old models
-
-This is the safer recipe because it leaves your old root directory in
-place to fall back on.
-
-1. Follow the instructions above to create and install InvokeAI in a
-directory that has a different name from the 2.3 invokeai directory.
-In this example, we will use "invokeai-3"
-
-2. When you are prompted to select models to install, select a minimal
-set of models, such as stable-diffusion-v1.5 only.
-
-3. After installation is complete launch `invokeai.sh` (Linux/Mac) or
-`invokeai.bat` and select option 8 "Open the developers console". This
-will take you to the command line.
-
-4. Issue the command `invokeai-migrate3 --from /path/to/v2.3-root --to
-/path/to/invokeai-3-root`. Provide the correct `--from` and `--to`
-paths for your v2.3 and v3.0 root directories respectively.
-
-This will copy and convert your old models from 2.3 format to 3.0
-format and create a new `models` directory in the 3.0 directory. The
-old models directory (which contains the models selected at install
-time) will be renamed `models.orig` and can be deleted once you have
-confirmed that the migration was successful.
-
-#### Migrating in place
-
-For the adventurous, you may do an in-place upgrade from 2.3 to 3.0
-without touching the command line. The recipe is as follows>
-
-1. Launch the InvokeAI launcher script in your current v2.3 root directory.
-
-2. Select option [9] "Update InvokeAI" to bring up the updater dialog.
-
-3a. During the alpha release phase, select option [3] and manually
-enter the tag name `v3.0.0+a2`.
-
-3b. Once 3.0 is released, select option [1] to upgrade to the latest release.
-
-4. Once the upgrade is finished you will be returned to the launcher
-menu. Select option [7] "Re-run the configure script to fix a broken
-install or to complete a major upgrade".
-
-This will run the configure script against the v2.3 directory and
-update it to the 3.0 format. The following files will be replaced:
-
-  - The invokeai.init file, replaced by invokeai.yaml
-  - The models directory
-  - The configs/models.yaml model index
-  
-The original versions of these files will be saved with the suffix
-".orig" appended to the end. Once you have confirmed that the upgrade
-worked, you can safely remove these files. Alternatively you can
-restore a working v2.3 directory by removing the new files and
-restoring the ".orig" files' original names.
-
-#### Migration Caveats
-
-The migration script will migrate your invokeai settings and models,
-including textual inversion models, LoRAs and merges that you may have
-installed previously. However it does **not** migrate the generated
-images stored in your 2.3-format outputs directory. The released
-version of 3.0 is expected to have an interface for importing an
-entire directory of image files as a batch.
-
-## 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)
 
-We do not recommend the GTX 1650 or 1660 series video cards. They are
+#### Memory
-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.
+- At least 12 GB Main Memory RAM.
 
-**Disk** - At least 12 GB of free disk space for the machine learning model, Python, and all its dependencies.
+#### Disk
 
-## Features
+- At least 12 GB of free disk space for the machine learning model, Python, and all its dependencies.
 
-Feature documentation can be reviewed by navigating to [the InvokeAI Documentation page](https://invoke-ai.github.io/InvokeAI/features/)
+**Note**
 
-### *Web Server & UI*
+If you have a Nvidia 10xx series card (e.g. the 1080ti), please
+run the dream script in full-precision mode as shown below.
 
-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.
+Similarly, specify full-precision mode on Apple M1 hardware.
 
-### *Unified Canvas*
+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:
 
-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.
+```bash
+(invokeai) ~/InvokeAI$ python scripts/invoke.py --precision=float32
+```
 
-### *Node Architecture & Editor (Beta)*
+### Features
 
-Invoke AI's backend is built on a graph-based execution architecture. This allows for customizable generation pipelines to be developed by professional users looking to create specific workflows to support their production use-cases, and will be extended in the future with additional capabilities.
+#### Major Features
 
-### *Board & Gallery Management*
+- [Web Server](https://invoke-ai.github.io/InvokeAI/features/WEB/)
+- [Interactive Command Line Interface](https://invoke-ai.github.io/InvokeAI/features/CLI/)
+- [Image To Image](https://invoke-ai.github.io/InvokeAI/features/IMG2IMG/)
+- [Inpainting Support](https://invoke-ai.github.io/InvokeAI/features/INPAINTING/)
+- [Outpainting Support](https://invoke-ai.github.io/InvokeAI/features/OUTPAINTING/)
+- [Upscaling, face-restoration and outpainting](https://invoke-ai.github.io/InvokeAI/features/POSTPROCESS/)
+- [Reading Prompts From File](https://invoke-ai.github.io/InvokeAI/features/PROMPTS/#reading-prompts-from-a-file)
+- [Prompt Blending](https://invoke-ai.github.io/InvokeAI/features/PROMPTS/#prompt-blending)
+- [Thresholding and Perlin Noise Initialization Options](https://invoke-ai.github.io/InvokeAI/features/OTHER/#thresholding-and-perlin-noise-initialization-options)
+- [Negative/Unconditioned Prompts](https://invoke-ai.github.io/InvokeAI/features/PROMPTS/#negative-and-unconditioned-prompts)
+- [Variations](https://invoke-ai.github.io/InvokeAI/features/VARIATIONS/)
+- [Personalizing Text-to-Image Generation](https://invoke-ai.github.io/InvokeAI/features/TEXTUAL_INVERSION/)
+- [Simplified API for text to image generation](https://invoke-ai.github.io/InvokeAI/features/OTHER/#simplified-api)
 
-Invoke AI provides an organized gallery system for easily storing, accessing, and remixing your content in the Invoke workspace. Images can be dragged/dropped onto any Image-base UI element in the application, and rich metadata within the Image allows for easy recall of key prompts or settings used in your workflow. 
+#### Other Features
 
-### Other features
+- [Google Colab](https://invoke-ai.github.io/InvokeAI/features/OTHER/#google-colab)
-
+- [Seamless Tiling](https://invoke-ai.github.io/InvokeAI/features/OTHER/#seamless-tiling)
-- *Support for both ckpt and diffusers models*
+- [Shortcut: Reusing Seeds](https://invoke-ai.github.io/InvokeAI/features/OTHER/#shortcuts-reusing-seeds)
-- *SD 2.0, 2.1 support*
+- [Preload Models](https://invoke-ai.github.io/InvokeAI/features/OTHER/#preload-models)
-- *Upscaling Tools*
-- *Embedding Manager & Support*
-- *Model Manager & Support*
-- *Node-Based Architecture*
-- *Node-Based Plug-&-Play UI (Beta)*
-- *SDXL Support* (Coming soon)
 
 ### Latest Changes
 
-For our latest changes, view our [Release
+### v2.1.0 major changes <small>(2 November 2022)</small> 
-Notes](https://github.com/invoke-ai/InvokeAI/releases) and the
+
-[CHANGELOG](docs/CHANGELOG.md).
+    - [Inpainting](https://invoke-ai.github.io/InvokeAI/features/INPAINTING/) support in the WebGUI
+    - Greatly improved navigation and user experience in the [WebGUI](https://invoke-ai.github.io/InvokeAI/features/WEB/)
+    - The prompt syntax has been enhanced with [prompt weighting, cross-attention and prompt merging](https://invoke-ai.github.io/InvokeAI/features/PROMPTS/).
+    - You can now load [multiple models and switch among them quickly](https://docs.google.com/presentation/d/1WywGA1rny7bpFh7CLSdTr4nNpVKdlUeT0Bj0jCsILyU/edit?usp=sharing) without leaving the CLI.
+    - The installation process (via `scripts/preload_models.py`) now lets you select among several popular [Stable Diffusion models](https://invoke-ai.github.io/InvokeAI/installation/INSTALLING_MODELS/) and downloads and installs them on your behalf. Among other models, this script will install the current Stable Diffusion 1.5 model as well as a StabilityAI variable autoencoder (VAE) which improves face generation.
+    -  Tired of struggling with photoeditors to get the masked region of for inpainting just right? Let the AI make the mask for you using [text masking](https://docs.google.com/presentation/d/1pWoY510hCVjz0M6X9CBbTznZgW2W5BYNKrmZm7B45q8/edit#slide=id.p). This feature allows you to specify the part of the image to paint over using just English-language phrases.
+    -  Tired of seeing the head of your subjects cropped off? Uncrop them in the CLI with the [outcrop feature](https://invoke-ai.github.io/InvokeAI/features/OUTPAINTING/#outcrop).
+    - Tired of seeing your subject's bodies duplicated or mangled when generating larger-dimension images? Check out the `--hires` option in the CLI, or select the corresponding toggle in the WebGUI.
+    - We now support textual inversion and fine-tune .bin styles and subjects from the Hugging Face archive of [SD Concepts](https://huggingface.co/sd-concepts-library). Load the .bin file using the `--embedding_path` option. (The next version will support merging and loading of multiple simultaneous models).
+    <a href="https://invoke-ai.github.io/InvokeAI/CHANGELOG/>Complete Changelog</a>
+
+- 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)
+
+- v2.0.0 (9 October 2022)
+
+  - `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://invoke-ai.github.io/InvokeAI/features/INPAINTING/">inpainting</a> and <a href="https://invoke-ai.github.io/InvokeAI/features/OUTPAINTING/">outpainting</a>
+  - img2img runs on all k* samplers
+  - Support for <a href="https://invoke-ai.github.io/InvokeAI/features/PROMPTS/#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://invoke-ai.github.io/InvokeAI/features/POSTPROCESS/">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://invoke-ai.github.io/InvokeAI/features/CLI/#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://invoke-ai.github.io/InvokeAI/features/CLI/">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](https://invoke-ai.github.io/InvokeAI/CHANGELOG#v114-11-september-2022)**.
 
 ### Troubleshooting
 
 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.
+cleanup, testing, or code reviews, is very much encouraged to do so. If you are unfamiliar with how
-
-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**.
+[Getting Started Guide](https://opensource.com/article/19/7/create-pull-request-github).
 
-We hope you enjoy using our software as much as we enjoy creating it,
+A full set of contribution guidelines, along with templates, are in progress, but for now the most
-and we hope that some of those of you who are reading this will elect
+important thing is to **make your pull request against the "development" branch**, and not against
-to become part of our community.
+"main". This will help keep public breakage to a minimum and will allow you to propose more radical
-
+changes.
-Welcome to InvokeAI!
 
 ### Contributors
 
@@ -386,7 +205,13 @@ their time, hard work and effort.
 
 ### Support
 
-For support, please use this repository's GitHub Issues tracking service, or join the Discord.
+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.
 
-Original portions of the software are Copyright (c) 2023 by respective contributors.
+Original portions of the software are Copyright (c) 2020
+[Lincoln D. Stein](https://github.com/lstein)
 
+### Further Reading
+
+Please see the original README for more information on this software and underlying algorithm,
+located in the file [README-CompViz.md](https://invoke-ai.github.io/InvokeAI/other/README-CompViz/).

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.
+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/),
+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.
+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.
+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
+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

@@ -0,0 +1,55 @@
+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

@@ -0,0 +1,69 @@
+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)

configs/models.yaml.example

@@ -0,0 +1,27 @@
+# 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-1.5:
+  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
+stable-diffusion-1.4:
+  description: Stable Diffusion inference model version 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
+  width: 512
+  height: 512
+inpainting-1.5:
+  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
+  description: RunwayML SD 1.5 model optimized for inpainting

configs/stable-diffusion/v1-finetune.yaml

@@ -0,0 +1,110 @@
+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

@@ -0,0 +1,103 @@
+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

@@ -0,0 +1,79 @@
+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

@@ -0,0 +1,79 @@
+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

@@ -0,0 +1,110 @@
+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

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

docker-build/Dockerfile

@@ -0,0 +1,74 @@
+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

@@ -0,0 +1,81 @@
+#!/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

@@ -0,0 +1,8 @@
+#!/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

@@ -0,0 +1,13 @@
+#!/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

@@ -0,0 +1,15 @@
+#!/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/.env.sample

@@ -1,13 +0,0 @@
-## Make a copy of this file named `.env` and fill in the values below.
-## Any environment variables supported by InvokeAI can be specified here.
-
-# INVOKEAI_ROOT is the path to a path on the local filesystem where InvokeAI will store data.
-# Outputs will also be stored here by default.
-# This **must** be an absolute path.
-INVOKEAI_ROOT=
-
-HUGGINGFACE_TOKEN=
-
-## optional variables specific to the docker setup
-# GPU_DRIVER=cuda
-# CONTAINER_UID=1000

docker/Dockerfile

@@ -1,129 +0,0 @@
-# syntax=docker/dockerfile:1.4
-
-## Builder stage
-
-FROM library/ubuntu:22.04 AS builder
-
-ARG DEBIAN_FRONTEND=noninteractive
-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
-RUN --mount=type=cache,target=/var/cache/apt,sharing=locked \
-    --mount=type=cache,target=/var/lib/apt,sharing=locked \
-    apt update && apt-get install -y \
-        git \
-        python3.10-venv \
-        python3-pip \
-        build-essential
-
-ENV INVOKEAI_SRC=/opt/invokeai
-ENV VIRTUAL_ENV=/opt/venv/invokeai
-
-ENV PATH="$VIRTUAL_ENV/bin:$PATH"
-ARG TORCH_VERSION=2.0.1
-ARG TORCHVISION_VERSION=0.15.2
-ARG GPU_DRIVER=cuda
-ARG TARGETPLATFORM="linux/amd64"
-# unused but available
-ARG BUILDPLATFORM
-
-WORKDIR ${INVOKEAI_SRC}
-
-# Install pytorch before all other pip packages
-# NOTE: there are no pytorch builds for arm64 + cuda, only cpu
-# x86_64/CUDA is default
-RUN --mount=type=cache,target=/root/.cache/pip \
-    python3 -m venv ${VIRTUAL_ENV} &&\
-    if [ "$TARGETPLATFORM" = "linux/arm64" ] || [ "$GPU_DRIVER" = "cpu" ]; then \
-        extra_index_url_arg="--extra-index-url https://download.pytorch.org/whl/cpu"; \
-    elif [ "$GPU_DRIVER" = "rocm" ]; then \
-        extra_index_url_arg="--extra-index-url https://download.pytorch.org/whl/rocm5.4.2"; \
-    else \
-        extra_index_url_arg="--extra-index-url https://download.pytorch.org/whl/cu118"; \
-    fi &&\
-    pip install $extra_index_url_arg \
-        torch==$TORCH_VERSION \
-        torchvision==$TORCHVISION_VERSION
-
-# Install the local package.
-# Editable mode helps use the same image for development:
-# the local working copy can be bind-mounted into the image
-# at path defined by ${INVOKEAI_SRC}
-COPY invokeai ./invokeai
-COPY pyproject.toml ./
-RUN --mount=type=cache,target=/root/.cache/pip \
-    # xformers + triton fails to install on arm64
-    if [ "$GPU_DRIVER" = "cuda" ] && [ "$TARGETPLATFORM" = "linux/amd64" ]; then \
-        pip install -e ".[xformers]"; \
-    else \
-        pip install -e "."; \
-    fi
-
-# #### Build the Web UI ------------------------------------
-
-FROM node:18 AS web-builder
-WORKDIR /build
-COPY invokeai/frontend/web/ ./
-RUN --mount=type=cache,target=/usr/lib/node_modules \
-    npm install --include dev
-RUN --mount=type=cache,target=/usr/lib/node_modules \
-    yarn vite build
-
-
-#### Runtime stage ---------------------------------------
-
-FROM library/ubuntu:22.04 AS runtime
-
-ARG DEBIAN_FRONTEND=noninteractive
-ENV PYTHONUNBUFFERED=1
-ENV PYTHONDONTWRITEBYTECODE=1
-
-RUN apt update && apt install -y --no-install-recommends \
-        git \
-        curl \
-        vim \
-        tmux \
-        ncdu \
-        iotop \
-        bzip2 \
-        gosu \
-        libglib2.0-0 \
-        libgl1-mesa-glx \
-        python3-venv \
-        python3-pip \
-        build-essential \
-        libopencv-dev \
-        libstdc++-10-dev &&\
-    apt-get clean && apt-get autoclean
-
-# globally add magic-wormhole
-# for ease of transferring data to and from the container
-# when running in sandboxed cloud environments; e.g. Runpod etc.
-RUN pip install magic-wormhole
-
-ENV INVOKEAI_SRC=/opt/invokeai
-ENV VIRTUAL_ENV=/opt/venv/invokeai
-ENV INVOKEAI_ROOT=/invokeai
-ENV PATH="$VIRTUAL_ENV/bin:$INVOKEAI_SRC:$PATH"
-
-# --link requires buldkit w/ dockerfile syntax 1.4
-COPY --link --from=builder ${INVOKEAI_SRC} ${INVOKEAI_SRC}
-COPY --link --from=builder ${VIRTUAL_ENV} ${VIRTUAL_ENV}
-COPY --link --from=web-builder /build/dist ${INVOKEAI_SRC}/invokeai/frontend/web/dist
-
-# Link amdgpu.ids for ROCm builds
-# contributed by https://github.com/Rubonnek
-RUN mkdir -p "/opt/amdgpu/share/libdrm" &&\
-  ln -s "/usr/share/libdrm/amdgpu.ids" "/opt/amdgpu/share/libdrm/amdgpu.ids"
-
-WORKDIR ${INVOKEAI_SRC}
-
-# build patchmatch
-RUN cd /usr/lib/$(uname -p)-linux-gnu/pkgconfig/ && ln -sf opencv4.pc opencv.pc
-RUN python3 -c "from patchmatch import patch_match"
-
-# Create unprivileged user and make the local dir
-RUN useradd --create-home --shell /bin/bash -u 1000 --comment "container local user" invoke
-RUN mkdir -p ${INVOKEAI_ROOT} && chown -R invoke:invoke ${INVOKEAI_ROOT}
-
-COPY docker/docker-entrypoint.sh ./
-ENTRYPOINT ["/opt/invokeai/docker-entrypoint.sh"]
-CMD ["invokeai-web", "--host", "0.0.0.0"]

docker/README.md

@@ -1,77 +0,0 @@
-# InvokeAI Containerized
-
-All commands are to be run from the `docker` directory: `cd docker`
-
-#### Linux
-
-1. Ensure builkit is enabled in the Docker daemon settings (`/etc/docker/daemon.json`)
-2. Install the `docker compose` plugin using your package manager, or follow a [tutorial](https://www.digitalocean.com/community/tutorials/how-to-install-and-use-docker-compose-on-ubuntu-22-04).
-    - The deprecated `docker-compose` (hyphenated) CLI continues to work for now.
-3. Ensure docker daemon is able to access the GPU.
-    - You may need to install [nvidia-container-toolkit](https://docs.nvidia.com/datacenter/cloud-native/container-toolkit/latest/install-guide.html)
-
-#### macOS
-
-1. Ensure Docker has at least 16GB RAM
-2. Enable VirtioFS for file sharing
-3. Enable `docker compose` V2 support
-
-This is done via Docker Desktop preferences
-
-## Quickstart
-
-
-1. Make a copy of `env.sample` and name it `.env` (`cp env.sample .env` (Mac/Linux) or `copy example.env .env` (Windows)). Make changes as necessary. Set `INVOKEAI_ROOT` to an absolute path to:
-    a. the desired location of the InvokeAI runtime directory, or
-    b. an existing, v3.0.0 compatible runtime directory.
-1. `docker compose up`
-
-The image will be built automatically if needed.
-
-The runtime directory (holding models and outputs) will be created in the location specified by `INVOKEAI_ROOT`. The default location is `~/invokeai`. The runtime directory will be populated with the base configs and models necessary to start generating.
-
-### Use a GPU
-
-- Linux is *recommended* for GPU support in Docker.
-- WSL2 is *required* for Windows.
-- only `x86_64` architecture is supported.
-
-The Docker daemon on the system must be already set up to use the GPU. In case of Linux, this involves installing `nvidia-docker-runtime` and configuring the `nvidia` runtime as default. Steps will be different for AMD. Please see Docker documentation for the most up-to-date instructions for using your GPU with Docker.
-
-## Customize
-
-Check the `.env.sample` file. It contains some environment variables for running in Docker. Copy it, name it `.env`, and fill it in with your own values. Next time you run `docker compose up`, your custom values will be used.
-
-You can also set these values in `docker compose.yml` directly, but `.env` will help avoid conflicts when code is updated.
-
-Example (most values are optional):
-
-```
-INVOKEAI_ROOT=/Volumes/WorkDrive/invokeai
-HUGGINGFACE_TOKEN=the_actual_token
-CONTAINER_UID=1000
-GPU_DRIVER=cuda
-```
-
-## Even Moar Customizing!
-
-See the `docker compose.yaml` file. The `command` instruction can be uncommented and used to run arbitrary startup commands. Some examples below.
-
-### Reconfigure the runtime directory
-
-Can be used to download additional models from the supported model list
-
-In conjunction with `INVOKEAI_ROOT` can be also used to initialize a runtime directory
-
-```
-command:
-  - invokeai-configure
-  - --yes
-```
-
-Or install models:
-
-```
-command:
-  - invokeai-model-install
-```

docker/build.sh

@@ -1,11 +0,0 @@
-#!/usr/bin/env bash
-set -e
-
-build_args=""
-
-[[ -f ".env" ]] && build_args=$(awk '$1 ~ /\=[^$]/ {print "--build-arg " $0 " "}' .env)
-
-echo "docker-compose build args:"
-echo $build_args
-
-docker-compose build $build_args

docker/docker-compose.yml

@@ -1,48 +0,0 @@
-# Copyright (c) 2023 Eugene Brodsky https://github.com/ebr
-
-version: '3.8'
-
-services:
-  invokeai:
-    image: "local/invokeai:latest"
-    # edit below to run on a container runtime other than nvidia-container-runtime.
-    # not yet tested with rocm/AMD GPUs
-    # Comment out the "deploy" section to run on CPU only
-    deploy:
-      resources:
-        reservations:
-          devices:
-            - driver: nvidia
-              count: 1
-              capabilities: [gpu]
-    build:
-      context: ..
-      dockerfile: docker/Dockerfile
-
-    # variables without a default will automatically inherit from the host environment
-    environment:
-      - INVOKEAI_ROOT
-      - HF_HOME
-
-    # Create a .env file in the same directory as this docker-compose.yml file
-    # and populate it with environment variables. See .env.sample
-    env_file:
-      - .env
-
-    ports:
-      - "${INVOKEAI_PORT:-9090}:9090"
-    volumes:
-      - ${INVOKEAI_ROOT:-~/invokeai}:${INVOKEAI_ROOT:-/invokeai}
-      - ${HF_HOME:-~/.cache/huggingface}:${HF_HOME:-/invokeai/.cache/huggingface}
-      # - ${INVOKEAI_MODELS_DIR:-${INVOKEAI_ROOT:-/invokeai/models}}
-      # - ${INVOKEAI_MODELS_CONFIG_PATH:-${INVOKEAI_ROOT:-/invokeai/configs/models.yaml}}
-    tty: true
-    stdin_open: true
-
-    # # Example of running alternative commands/scripts in the container
-    # command:
-    #   - bash
-    #   - -c
-    #   - |
-    #     invokeai-model-install --yes --default-only --config_file ${INVOKEAI_ROOT}/config_custom.yaml
-    #     invokeai-nodes-web --host 0.0.0.0

docker/docker-entrypoint.sh

@@ -1,65 +0,0 @@
-#!/bin/bash
-set -e -o pipefail
-
-### Container entrypoint
-# Runs the CMD as defined by the Dockerfile or passed to `docker run`
-# Can be used to configure the runtime dir
-# Bypass by using ENTRYPOINT or `--entrypoint`
-
-### Set INVOKEAI_ROOT pointing to a valid runtime directory
-# Otherwise configure the runtime dir first.
-
-### Configure the InvokeAI runtime directory (done by default)):
-# docker run --rm -it <this image> --configure
-# or skip with --no-configure
-
-### Set the CONTAINER_UID envvar to match your user.
-# Ensures files created in the container are owned by you:
-#   docker run --rm -it -v /some/path:/invokeai -e CONTAINER_UID=$(id -u) <this image>
-# Default UID: 1000 chosen due to popularity on Linux systems. Possibly 501 on MacOS.
-
-USER_ID=${CONTAINER_UID:-1000}
-USER=invoke
-usermod -u ${USER_ID} ${USER} 1>/dev/null
-
-configure() {
-    # Configure the runtime directory
-    if [[ -f ${INVOKEAI_ROOT}/invokeai.yaml ]]; then
-        echo "${INVOKEAI_ROOT}/invokeai.yaml exists. InvokeAI is already configured."
-        echo "To reconfigure InvokeAI, delete the above file."
-        echo "======================================================================"
-    else
-        mkdir -p ${INVOKEAI_ROOT}
-        chown --recursive ${USER} ${INVOKEAI_ROOT}
-        gosu ${USER} invokeai-configure --yes --default_only
-    fi
-}
-
-## Skip attempting to configure.
-## Must be passed first, before any other args.
-if [[ $1 != "--no-configure" ]]; then
-    configure
-else
-    shift
-fi
-
-### Set the $PUBLIC_KEY env var to enable SSH access.
-# We do not install openssh-server in the image by default to avoid bloat.
-# but it is useful to have the full SSH server e.g. on Runpod.
-# (use SCP to copy files to/from the image, etc)
-if [[ -v "PUBLIC_KEY" ]] && [[ ! -d "${HOME}/.ssh" ]]; then
-    apt-get update
-    apt-get install -y openssh-server
-    pushd $HOME
-    mkdir -p .ssh
-    echo ${PUBLIC_KEY} > .ssh/authorized_keys
-    chmod -R 700 .ssh
-    popd
-    service ssh start
-fi
-
-
-cd ${INVOKEAI_ROOT}
-
-# Run the CMD as the Container User (not root).
-exec gosu ${USER} "$@"

docker/run.sh

@@ -1,8 +0,0 @@
-#!/usr/bin/env bash
-set -e
-
-SCRIPTDIR=$(dirname "${BASH_SOURCE[0]}")
-cd "$SCRIPTDIR" || exit 1
-
-docker-compose up --build -d
-docker-compose logs -f

docker/runpod-readme.md

@@ -1,60 +0,0 @@
-# InvokeAI - A Stable Diffusion Toolkit
-
-Stable Diffusion distribution by InvokeAI: https://github.com/invoke-ai
-
-The Docker image tracks the `main` branch of the InvokeAI project, which means it includes the latest features, but may contain some bugs.
-
-Your working directory is mounted under the `/workspace` path inside the pod. The models are in `/workspace/invokeai/models`, and outputs are in `/workspace/invokeai/outputs`.
-
-> **Only the /workspace directory will persist between pod restarts!**
-
-> **If you _terminate_ (not just _stop_) the pod, the /workspace will be lost.**
-
-## Quickstart
-
-1. Launch a pod from this template. **It will take about 5-10 minutes to run through the initial setup**. Be patient.
-1. Wait for the application to load.
-    - TIP: you know it's ready when the CPU usage goes idle
-    - You can also check the logs for a line that says "_Point your browser at..._"
-1. Open the Invoke AI web UI: click the `Connect` => `connect over  HTTP` button.
-1. Generate some art!
-
-## Other things you can do
-
-At any point you may edit the pod configuration and set an arbitrary Docker command. For example, you could run a command to downloads some models using `curl`, or fetch some images and place them into your outputs to continue a working session.
-
-If you need to run *multiple commands*, define them in the Docker Command field like this:
-
-`bash -c "cd ${INVOKEAI_ROOT}/outputs; wormhole receive 2-foo-bar; invoke.py --web --host 0.0.0.0"`
-
-### Copying your data in and out of the pod
-
-This image includes a couple of handy tools to help you get the data into the pod (such as your custom models or embeddings), and out of the pod (such as downloading your outputs). Here are your options for getting your data in and out of the pod:
-
-- **SSH server**:
-    1. Make sure to create and set your Public Key in the RunPod settings (follow the official instructions)
-    1. Add an exposed port 22 (TCP) in the pod settings!
-    1. When your pod restarts, you will see a new entry in the `Connect` dialog. Use this SSH server to `scp` or `sftp` your files as necessary, or SSH into the pod using the fully fledged SSH server.
-
-- [**Magic Wormhole**](https://magic-wormhole.readthedocs.io/en/latest/welcome.html):
-    1. On your computer, `pip install magic-wormhole` (see above instructions for details)
-    1. Connect to the command line **using the "light" SSH client** or the browser-based console. _Currently there's a bug where `wormhole` isn't available when connected to "full" SSH server, as described above_.
-    1. `wormhole send /workspace/invokeai/outputs` will send the entire `outputs` directory. You can also send individual files.
-    1. Once packaged, you will see a `wormhole receive <123-some-words>` command. Copy it
-    1. Paste this command into the terminal on your local machine to securely download the payload.
-    1. It works the same in reverse: you can `wormhole send` some models from your computer to the pod. Again, save your files somewhere in `/workspace` or they will be lost when the pod is stopped.
-
-- **RunPod's Cloud Sync feature** may be used to sync the persistent volume to cloud storage. You could, for example, copy the entire `/workspace` to S3, add some custom models to it, and copy it back from S3 when launching new pod configurations. Follow the Cloud Sync instructions.
-
-
-### Disable the NSFW checker
-
-The NSFW checker is enabled by default. To disable it, edit the pod configuration and set the following command:
-
-```
-invoke --web --host 0.0.0.0 --no-nsfw_checker
-```
-
----
-
-Template ©2023 Eugene Brodsky [ebr](https://github.com/ebr)

docs/CHANGELOG.md

@@ -4,655 +4,133 @@ title: Changelog
 
 # :octicons-log-16: **Changelog**
 
-## v2.3.5 <small>(22 May 2023)</small>
+## v2.1.0 (2 November 2022)
-
+- update mac instructions to use invokeai for env name by @willwillems in https://github.com/invoke-ai/InvokeAI/pull/1030
-This release (along with the post1 and post2 follow-on releases) expands support for additional LoRA and LyCORIS models, upgrades diffusers versions, and fixes a few bugs.
+- Update .gitignore by @blessedcoolant in https://github.com/invoke-ai/InvokeAI/pull/1040
-
+- reintroduce fix for m1 from https://github.com/invoke-ai/InvokeAI/pull/579 missing after merge by @skurovec in https://github.com/invoke-ai/InvokeAI/pull/1056
-### LoRA and LyCORIS Support Improvement
+- Update Stable_Diffusion_AI_Notebook.ipynb (Take 2) by @ChloeL19 in https://github.com/invoke-ai/InvokeAI/pull/1060
-
+- Print out the device type which is used by @manzke in https://github.com/invoke-ai/InvokeAI/pull/1073
-    A number of LoRA/LyCORIS fine-tune files (those which alter the text encoder as well as the unet model) were not having the desired effect in InvokeAI. This bug has now been fixed. Full documentation of LoRA support is available at InvokeAI LoRA Support.
+- Hires Addition by @hipsterusername in https://github.com/invoke-ai/InvokeAI/pull/1063
-    Previously, InvokeAI did not distinguish between LoRA/LyCORIS models based on Stable Diffusion v1.5 vs those based on v2.0 and 2.1, leading to a crash when an incompatible model was loaded. This has now been fixed. In addition, the web pulldown menus for LoRA and Textual Inversion selection have been enhanced to show only those files that are compatible with the currently-selected Stable Diffusion model.
+- fix for "1 leaked semaphore objects to clean up at shutdown" on M1 by @skurovec in https://github.com/invoke-ai/InvokeAI/pull/1081
-    Support for the newer LoKR LyCORIS files has been added.
+- Forward dream.py to invoke.py using the same interpreter, add deprecation warning by @db3000 in https://github.com/invoke-ai/InvokeAI/pull/1077
-
+- fix noisy images at high step counts by @lstein in https://github.com/invoke-ai/InvokeAI/pull/1086
-### Library Updates and Speed/Reproducibility Advancements
+- Generalize facetool strength argument by @db3000 in https://github.com/invoke-ai/InvokeAI/pull/1078
-The major enhancement in this version is that NVIDIA users no longer need to decide between speed and reproducibility. Previously, if you activated the Xformers library, you would see improvements in speed and memory usage, but multiple images generated with the same seed and other parameters would be slightly different from each other. This is no longer the case. Relative to 2.3.5 you will see improved performance when running without Xformers, and even better performance when Xformers is activated. In both cases, images generated with the same settings will be identical.
+- Enable fast switching among models at the invoke> command line by @lstein in https://github.com/invoke-ai/InvokeAI/pull/1066
-
+- Fix Typo, committed changing ldm environment to invokeai by @jdries3 in https://github.com/invoke-ai/InvokeAI/pull/1095
-Here are the new library versions:
+- Update generate.py by @unreleased in https://github.com/invoke-ai/InvokeAI/pull/1109
-Library 	Version
+- Update 'ldm' env to 'invokeai' in troubleshooting steps by @19wolf in https://github.com/invoke-ai/InvokeAI/pull/1125
-Torch 	2.0.0
+- Fixed documentation typos and resolved merge conflicts by @rupeshs in https://github.com/invoke-ai/InvokeAI/pull/1123
-Diffusers 	0.16.1
+- Fix broken doc links, fix malaprop in the project subtitle by @majick in https://github.com/invoke-ai/InvokeAI/pull/1131
-Xformers 	0.0.19
+- Only output facetool parameters if enhancing faces by @db3000 in https://github.com/invoke-ai/InvokeAI/pull/1119
-Compel 	1.1.5
+- Update gitignore to ignore codeformer weights at new location by @spezialspezial in https://github.com/invoke-ai/InvokeAI/pull/1136
-Other Improvements
+- fix links to point to invoke-ai.github.io #1117 by @mauwii in https://github.com/invoke-ai/InvokeAI/pull/1143
-
+- Rework-mkdocs by @mauwii in https://github.com/invoke-ai/InvokeAI/pull/1144
-### Performance Improvements
+- add option to CLI and pngwriter that allows user to set PNG compression level by @lstein in https://github.com/invoke-ai/InvokeAI/pull/1127
-
+- Fix img2img DDIM index out of bound by @wfng92 in https://github.com/invoke-ai/InvokeAI/pull/1137
-    When a model is loaded for the first time, InvokeAI calculates its checksum for incorporation into the PNG metadata. This process could take up to a minute on network-mounted disks and WSL mounts. This release noticeably speeds up the process.
+- Fix gh actions by @mauwii in https://github.com/invoke-ai/InvokeAI/pull/1128
-
+- update mac instructions to use invokeai for env name by @willwillems in https://github.com/invoke-ai/InvokeAI/pull/1030
-### Bug Fixes
+- Update .gitignore by @blessedcoolant in https://github.com/invoke-ai/InvokeAI/pull/1040
-
+- reintroduce fix for m1 from https://github.com/invoke-ai/InvokeAI/pull/579 missing after merge by @skurovec in https://github.com/invoke-ai/InvokeAI/pull/1056
-    The "import models from directory" and "import from URL" functionality in the console-based model installer has now been fixed.
+- Update Stable_Diffusion_AI_Notebook.ipynb (Take 2) by @ChloeL19 in https://github.com/invoke-ai/InvokeAI/pull/1060
-    When running the WebUI, we have reduced the number of times that InvokeAI reaches out to HuggingFace to fetch the list of embeddable Textual Inversion models. We have also caught and fixed a problem with the updater not correctly detecting when another instance of the updater is running 
+- Print out the device type which is used by @manzke in https://github.com/invoke-ai/InvokeAI/pull/1073
-
+- Hires Addition by @hipsterusername in https://github.com/invoke-ai/InvokeAI/pull/1063
-
+- fix for "1 leaked semaphore objects to clean up at shutdown" on M1 by @skurovec in https://github.com/invoke-ai/InvokeAI/pull/1081
-## v2.3.4 <small>(7 April 2023)</small>
+- Forward dream.py to invoke.py using the same interpreter, add deprecation warning by @db3000 in https://github.com/invoke-ai/InvokeAI/pull/1077
-
+- fix noisy images at high step counts by @lstein in https://github.com/invoke-ai/InvokeAI/pull/1086
-What's New in 2.3.4
+- Generalize facetool strength argument by @db3000 in https://github.com/invoke-ai/InvokeAI/pull/1078
-
+- Enable fast switching among models at the invoke> command line by @lstein in https://github.com/invoke-ai/InvokeAI/pull/1066
-This features release adds support for LoRA (Low-Rank Adaptation) and LyCORIS (Lora beYond Conventional) models, as well as some minor bug fixes.
+- Fix Typo, committed changing ldm environment to invokeai by @jdries3 in https://github.com/invoke-ai/InvokeAI/pull/1095
-### LoRA and LyCORIS Support
+- Fixed documentation typos and resolved merge conflicts by @rupeshs in https://github.com/invoke-ai/InvokeAI/pull/1123
-
+- Only output facetool parameters if enhancing faces by @db3000 in https://github.com/invoke-ai/InvokeAI/pull/1119
-LoRA files contain fine-tuning weights that enable particular styles, subjects or concepts to be applied to generated images. LyCORIS files are an extended variant of LoRA. InvokeAI supports the most common LoRA/LyCORIS format, which ends in the suffix .safetensors. You will find numerous LoRA and LyCORIS models for download at Civitai, and a small but growing number at Hugging Face. Full documentation of LoRA support is available at InvokeAI LoRA Support.( Pre-release note: this page will only be available after release)
+- add option to CLI and pngwriter that allows user to set PNG compression level by @lstein in https://github.com/invoke-ai/InvokeAI/pull/1127
-
+- Fix img2img DDIM index out of bound by @wfng92 in https://github.com/invoke-ai/InvokeAI/pull/1137
-To use LoRA/LyCORIS models in InvokeAI:
+- Add text prompt to inpaint mask support by @lstein in https://github.com/invoke-ai/InvokeAI/pull/1133
-
+- Respect http[s] protocol when making socket.io middleware by @damian0815 in https://github.com/invoke-ai/InvokeAI/pull/976
-    Download the .safetensors files of your choice and place in /path/to/invokeai/loras. This directory was not present in earlier version of InvokeAI but will be created for you the first time you run the command-line or web client. You can also create the directory manually.
+- WebUI: Adds Codeformer support by @psychedelicious in https://github.com/invoke-ai/InvokeAI/pull/1151
-
+- Skips normalizing prompts for web UI metadata by @psychedelicious in https://github.com/invoke-ai/InvokeAI/pull/1165
-    Add withLora(lora-file,weight) to your prompts. The weight is optional and will default to 1.0. A few examples, assuming that a LoRA file named loras/sushi.safetensors is present:
+- Add Asymmetric Tiling by @carson-katri in https://github.com/invoke-ai/InvokeAI/pull/1132
-
+- Web UI: Increases max CFG Scale to 200 by @psychedelicious in https://github.com/invoke-ai/InvokeAI/pull/1172
-family sitting at dinner table eating sushi withLora(sushi,0.9)
+- Corrects color channels in face restoration; Fixes #1167 by @psychedelicious in https://github.com/invoke-ai/InvokeAI/pull/1175
-family sitting at dinner table eating sushi withLora(sushi, 0.75)
+- Flips channels using array slicing instead of using OpenCV by @psychedelicious in https://github.com/invoke-ai/InvokeAI/pull/1178
-family sitting at dinner table eating sushi withLora(sushi)
+- Fix typo in docs: s/Formally/Formerly by @noodlebox in https://github.com/invoke-ai/InvokeAI/pull/1176
-
+- fix clipseg loading problems by @lstein in https://github.com/invoke-ai/InvokeAI/pull/1177
-Multiple withLora() prompt fragments are allowed. The weight can be arbitrarily large, but the useful range is roughly 0.5 to 1.0. Higher weights make the LoRA's influence stronger. Negative weights are also allowed, which can lead to some interesting effects.
+- Correct color channels in upscale using array slicing by @wfng92 in https://github.com/invoke-ai/InvokeAI/pull/1181
-
+- Web UI: Filters existing images when adding new images; Fixes #1085 by @psychedelicious in https://github.com/invoke-ai/InvokeAI/pull/1171
-    Generate as you usually would! If you find that the image is too "crisp" try reducing the overall CFG value or reducing individual LoRA weights. As is the case with all fine-tunes, you'll get the best results when running the LoRA on top of the model similar to, or identical with, the one that was used during the LoRA's training. Don't try to load a SD 1.x-trained LoRA into a SD 2.x model, and vice versa. This will trigger a non-fatal error message and generation will not proceed.
+- fix a number of bugs in textual inversion by @lstein in https://github.com/invoke-ai/InvokeAI/pull/1190
-
+- Improve !fetch, add !replay command by @ArDiouscuros in https://github.com/invoke-ai/InvokeAI/pull/882
-    You can change the location of the loras directory by passing the --lora_directory option to `invokeai.
+- Fix generation of image with s>1000 by @holstvoogd in https://github.com/invoke-ai/InvokeAI/pull/951
-
+- Web UI: Gallery improvements by @psychedelicious in https://github.com/invoke-ai/InvokeAI/pull/1198
-### New WebUI LoRA and Textual Inversion Buttons
+- Update CLI.md by @krummrey in https://github.com/invoke-ai/InvokeAI/pull/1211
-
+- outcropping improvements by @lstein in https://github.com/invoke-ai/InvokeAI/pull/1207
-This version adds two new web interface buttons for inserting LoRA and Textual Inversion triggers into the prompt as shown in the screenshot below.
+- add support for loading VAE autoencoders by @lstein in https://github.com/invoke-ai/InvokeAI/pull/1216
-
+- remove duplicate fix_func for MPS by @wfng92 in https://github.com/invoke-ai/InvokeAI/pull/1210
-Clicking on one or the other of the buttons will bring up a menu of available LoRA/LyCORIS or Textual Inversion trigger terms. Select a menu item to insert the properly-formatted withLora() or <textual-inversion> prompt fragment into the positive prompt. The number in parentheses indicates the number of trigger terms currently in the prompt. You may click the button again and deselect the LoRA or trigger to remove it from the prompt, or simply edit the prompt directly.
+- Metadata storage and retrieval fixes by @lstein in https://github.com/invoke-ai/InvokeAI/pull/1204
-
+- nix: add shell.nix file by @Cloudef in https://github.com/invoke-ai/InvokeAI/pull/1170
-Currently terms are inserted into the positive prompt textbox only. However, some textual inversion embeddings are designed to be used with negative prompts. To move a textual inversion trigger into the negative prompt, simply cut and paste it.
+- Web UI: Changes vite dist asset paths to relative by @psychedelicious in https://github.com/invoke-ai/InvokeAI/pull/1185
-
+- Web UI: Removes isDisabled from PromptInput by @psychedelicious in https://github.com/invoke-ai/InvokeAI/pull/1187
-By default the Textual Inversion menu only shows locally installed models found at startup time in /path/to/invokeai/embeddings. However, InvokeAI has the ability to dynamically download and install additional Textual Inversion embeddings from the HuggingFace Concepts Library. You may choose to display the most popular of these (with five or more likes) in the Textual Inversion menu by going to Settings and turning on "Show Textual Inversions from HF Concepts Library." When this option is activated, the locally-installed TI embeddings will be shown first, followed by uninstalled terms from Hugging Face. See The Hugging Face Concepts Library and Importing Textual Inversion files for more information.
+- Allow user to generate images with initial noise as on M1 / mps system by @ArDiouscuros in https://github.com/invoke-ai/InvokeAI/pull/981
-### Minor features and fixes
+- feat: adding filename format template by @plucked in https://github.com/invoke-ai/InvokeAI/pull/968
-
+- Web UI: Fixes broken bundle by @psychedelicious in https://github.com/invoke-ai/InvokeAI/pull/1242
-This release changes model switching behavior so that the command-line and Web UIs save the last model used and restore it the next time they are launched. It also improves the behavior of the installer so that the pip utility is kept up to date.
+- Support runwayML custom inpainting model by @lstein in https://github.com/invoke-ai/InvokeAI/pull/1243
-  
+- Update IMG2IMG.md by @talitore in https://github.com/invoke-ai/InvokeAI/pull/1262
-### Known Bugs in 2.3.4
+- New dockerfile - including a build- and a run- script as well as a GH-Action by @mauwii in https://github.com/invoke-ai/InvokeAI/pull/1233
-
+- cut over from karras to model noise schedule for higher steps by @lstein in https://github.com/invoke-ai/InvokeAI/pull/1222
-These are known bugs in the release.
+- Prompt tweaks by @lstein in https://github.com/invoke-ai/InvokeAI/pull/1268
-
+- Outpainting implementation by @Kyle0654 in https://github.com/invoke-ai/InvokeAI/pull/1251
-    The Ancestral DPMSolverMultistepScheduler (k_dpmpp_2a) sampler is not yet implemented for diffusers models and will disappear from the WebUI Sampler menu when a diffusers model is selected.
+- fixing aspect ratio on hires by @tjennings in https://github.com/invoke-ai/InvokeAI/pull/1249
-    Windows Defender will sometimes raise Trojan or backdoor alerts for the codeformer.pth face restoration model, as well as the CIDAS/clipseg and runwayml/stable-diffusion-v1.5 models. These are false positives and can be safely ignored. InvokeAI performs a malware scan on all models as they are loaded. For additional security, you should use safetensors models whenever they are available.
+- Fix-build-container-action by @mauwii in https://github.com/invoke-ai/InvokeAI/pull/1274
-
+- handle all unicode characters by @damian0815 in https://github.com/invoke-ai/InvokeAI/pull/1276
-
+- adds models.user.yml to .gitignore by @JakeHL in https://github.com/invoke-ai/InvokeAI/pull/1281
-## v2.3.3 <small>(28 March 2023)</small>
+- remove debug branch, set fail-fast to false by @mauwii in https://github.com/invoke-ai/InvokeAI/pull/1284
-
+- Protect-secrets-on-pr by @mauwii in https://github.com/invoke-ai/InvokeAI/pull/1285
-This is a bugfix and minor feature release.
+- Web UI: Adds initial inpainting implementation by @psychedelicious in https://github.com/invoke-ai/InvokeAI/pull/1225
-### Bugfixes
+- fix environment-mac.yml - tested on x64 and arm64 by @mauwii in https://github.com/invoke-ai/InvokeAI/pull/1289
-
+- Use proper authentication to download model by @mauwii in https://github.com/invoke-ai/InvokeAI/pull/1287
-Since version 2.3.2 the following bugs have been fixed:
+- Prevent indexing error for mode RGB by @spezialspezial in https://github.com/invoke-ai/InvokeAI/pull/1294
-Bugs
+- Integrate sd-v1-5 model into test matrix (easily expandable), remove unecesarry caches by @mauwii in https://github.com/invoke-ai/InvokeAI/pull/1293
-
+- add --no-interactive to preload_models step by @mauwii in https://github.com/invoke-ai/InvokeAI/pull/1302
-    When using legacy checkpoints with an external VAE, the VAE file is now scanned for malware prior to loading. Previously only the main model weights file was scanned.
+- 1-click installer and updater. Uses micromamba to install git and conda into a contained environment (if necessary) before running the normal installation script by @cmdr2 in https://github.com/invoke-ai/InvokeAI/pull/1253
-    Textual inversion will select an appropriate batchsize based on whether xformers is active, and will default to xformers enabled if the library is detected.
+- preload_models.py script downloads the weight files by @lstein in https://github.com/invoke-ai/InvokeAI/pull/1290
-    The batch script log file names have been fixed to be compatible with Windows.
+
-    Occasional corruption of the .next_prefix file (which stores the next output file name in sequence) on Windows systems is now detected and corrected.
+## v2.0.1 (13 October 2022)
-    Support loading of legacy config files that have no personalization (textual inversion) section.
+
-    An infinite loop when opening the developer's console from within the invoke.sh script has been corrected.
+- fix noisy images at high step count when using k* samplers
-    Documentation fixes, including a recipe for detecting and fixing problems with the AMD GPU ROCm driver.
+- dream.py script now calls invoke.py module directly rather than
-
+    via a new python process (which could break the environment)
-Enhancements
-
-    It is now possible to load and run several community-contributed SD-2.0 based models, including the often-requested "Illuminati" model.
-    The "NegativePrompts" embedding file, and others like it, can now be loaded by placing it in the InvokeAI embeddings directory.
-    If no --model is specified at launch time, InvokeAI will remember the last model used and restore it the next time it is launched.
-    On Linux systems, the invoke.sh launcher now uses a prettier console-based interface. To take advantage of it, install the dialog package using your package manager (e.g. sudo apt install dialog).
-    When loading legacy models (safetensors/ckpt) you can specify a custom config file and/or a VAE by placing like-named files in the same directory as the model following this example:
-
-my-favorite-model.ckpt
-my-favorite-model.yaml
-my-favorite-model.vae.pt      # or my-favorite-model.vae.safetensors
-
-### Known Bugs in 2.3.3
-
-These are known bugs in the release.
-
-    The Ancestral DPMSolverMultistepScheduler (k_dpmpp_2a) sampler is not yet implemented for diffusers models and will disappear from the WebUI Sampler menu when a diffusers model is selected.
-    Windows Defender will sometimes raise Trojan or backdoor alerts for the codeformer.pth face restoration model, as well as the CIDAS/clipseg and runwayml/stable-diffusion-v1.5 models. These are false positives and can be safely ignored. InvokeAI performs a malware scan on all models as they are loaded. For additional security, you should use safetensors models whenever they are available.
-
-
-## v2.3.2 <small>(11 March 2023)</small>
-This is a bugfix and minor feature release.
-
-### Bugfixes
-
-Since version 2.3.1 the following bugs have been fixed:
-
-    Black images appearing for potential NSFW images when generating with legacy checkpoint models and both --no-nsfw_checker and --ckpt_convert turned on.
-    Black images appearing when generating from models fine-tuned on Stable-Diffusion-2-1-base. When importing V2-derived models, you may be asked to select whether the model was derived from a "base" model (512 pixels) or the 768-pixel SD-2.1 model.
-    The "Use All" button was not restoring the Hi-Res Fix setting on the WebUI
-    When using the model installer console app, models failed to import correctly when importing from directories with spaces in their names. A similar issue with the output directory was also fixed.
-    Crashes that occurred during model merging.
-    Restore previous naming of Stable Diffusion base and 768 models.
-    Upgraded to latest versions of diffusers, transformers, safetensors and accelerate libraries upstream. We hope that this will fix the assertion NDArray > 2**32 issue that MacOS users have had when generating images larger than 768x768 pixels. Please report back.
-
-As part of the upgrade to diffusers, the location of the diffusers-based models has changed from models/diffusers to models/hub. When you launch InvokeAI for the first time, it will prompt you to OK a one-time move. This should be quick and harmless, but if you have modified your models/diffusers directory in some way, for example using symlinks, you may wish to cancel the migration and make appropriate adjustments.
-New "Invokeai-batch" script
-
-### Invoke AI Batch
-2.3.2 introduces a new command-line only script called invokeai-batch that can be used to generate hundreds of images from prompts and settings that vary systematically. This can be used to try the same prompt across multiple combinations of models, steps, CFG settings and so forth. It also allows you to template prompts and generate a combinatorial list like:
-
-a shack in the mountains, photograph
-a shack in the mountains, watercolor
-a shack in the mountains, oil painting
-a chalet in the mountains, photograph
-a chalet in the mountains, watercolor
-a chalet in the mountains, oil painting
-a shack in the desert, photograph
-...
-
-If you have a system with multiple GPUs, or a single GPU with lots of VRAM, you can parallelize generation across the combinatorial set, reducing wait times and using your system's resources efficiently (make sure you have good GPU cooling).
-
-To try invokeai-batch out. Launch the "developer's console" using the invoke launcher script, or activate the invokeai virtual environment manually. From the console, give the command invokeai-batch --help in order to learn how the script works and create your first template file for dynamic prompt generation.
-
-
-### Known Bugs in 2.3.2
-
-These are known bugs in the release.
-
-    The Ancestral DPMSolverMultistepScheduler (k_dpmpp_2a) sampler is not yet implemented for diffusers models and will disappear from the WebUI Sampler menu when a diffusers model is selected.
-    Windows Defender will sometimes raise a Trojan alert for the codeformer.pth face restoration model. As far as we have been able to determine, this is a false positive and can be safely whitelisted.
-
-
-## v2.3.1 <small>(22 February 2023)</small>
-This is primarily a bugfix release, but it does provide several new features that will improve the user experience.
-
-### Enhanced support for model management
-
-InvokeAI now makes it convenient to add, remove and modify models. You can individually import models that are stored on your local system, scan an entire folder and its subfolders for models and import them automatically, and even directly import models from the internet by providing their download URLs. You also have the option of designating a local folder to scan for new models each time InvokeAI is restarted.
-
-There are three ways of accessing the model management features:
-
-    From the WebUI, click on the cube to the right of the model selection menu. This will bring up a form that allows you to import models individually from your local disk or scan a directory for models to import.
-
-    Using the Model Installer App
-
-Choose option (5) download and install models from the invoke launcher script to start a new console-based application for model management. You can use this to select from a curated set of starter models, or import checkpoint, safetensors, and diffusers models from a local disk or the internet. The example below shows importing two checkpoint URLs from popular SD sites and a HuggingFace diffusers model using its Repository ID. It also shows how to designate a folder to be scanned at startup time for new models to import.
-
-Command-line users can start this app using the command invokeai-model-install.
-
-    Using the Command Line Client (CLI)
-
-The !install_model and !convert_model commands have been enhanced to allow entering of URLs and local directories to scan and import. The first command installs .ckpt and .safetensors files as-is. The second one converts them into the faster diffusers format before installation.
-
-Internally InvokeAI is able to probe the contents of a .ckpt or .safetensors file to distinguish among v1.x, v2.x and inpainting models. This means that you do not need to include "inpaint" in your model names to use an inpainting model. Note that Stable Diffusion v2.x models will be autoconverted into a diffusers model the first time you use it.
-
-Please see INSTALLING MODELS for more information on model management.
-
-### An Improved Installer Experience
-
-The installer now launches a console-based UI for setting and changing commonly-used startup options:
-
-After selecting the desired options, the installer installs several support models needed by InvokeAI's face reconstruction and upscaling features and then launches the interface for selecting and installing models shown earlier. At any time, you can edit the startup options by launching invoke.sh/invoke.bat and entering option (6) change InvokeAI startup options
-
-Command-line users can launch the new configure app using invokeai-configure.
-
-This release also comes with a renewed updater. To do an update without going through a whole reinstallation, launch invoke.sh or invoke.bat and choose option (9) update InvokeAI . This will bring you to a screen that prompts you to update to the latest released version, to the most current development version, or any released or unreleased version you choose by selecting the tag or branch of the desired version.
-
-Command-line users can run this interface by typing invokeai-configure
-
-### Image Symmetry Options
-
-There are now features to generate horizontal and vertical symmetry during generation. The way these work is to wait until a selected step in the generation process and then to turn on a mirror image effect. In addition to generating some cool images, you can also use this to make side-by-side comparisons of how an image will look with more or fewer steps. Access this option from the WebUI by selecting Symmetry from the image generation settings, or within the CLI by using the options --h_symmetry_time_pct and --v_symmetry_time_pct (these can be abbreviated to --h_sym and --v_sym like all other options).
-
-### A New Unified Canvas Look
-
-This release introduces a beta version of the WebUI Unified Canvas. To try it out, open up the settings dialogue in the WebUI (gear icon) and select Use Canvas Beta Layout:
-
-Refresh the screen and go to to Unified Canvas (left side of screen, third icon from the top). The new layout is designed to provide more space to work in and to keep the image controls close to the image itself:
-
-Model conversion and merging within the WebUI
-
-The WebUI now has an intuitive interface for model merging, as well as for permanent conversion of models from legacy .ckpt/.safetensors formats into diffusers format. These options are also available directly from the invoke.sh/invoke.bat scripts.
-An easier way to contribute translations to the WebUI
-
-We have migrated our translation efforts to Weblate, a FOSS translation product. Maintaining the growing project's translations is now far simpler for the maintainers and community. Please review our brief translation guide for more information on how to contribute.
-Numerous internal bugfixes and performance issues
-
-### Bug Fixes
-This releases quashes multiple bugs that were reported in 2.3.0. Major internal changes include upgrading to diffusers 0.13.0, and using the compel library for prompt parsing. See Detailed Change Log for a detailed list of bugs caught and squished.
-Summary of InvokeAI command line scripts (all accessible via the launcher menu)
-Command 	Description
-invokeai 	Command line interface
-invokeai --web 	Web interface
-invokeai-model-install 	Model installer with console forms-based front end
-invokeai-ti --gui 	Textual inversion, with a console forms-based front end
-invokeai-merge --gui 	Model merging, with a console forms-based front end
-invokeai-configure 	Startup configuration; can also be used to reinstall support models
-invokeai-update 	InvokeAI software updater
-
-### Known Bugs in 2.3.1
-
-These are known bugs in the release.
-    MacOS users generating 768x768 pixel images or greater using diffusers models may experience a hard crash with assertion NDArray > 2**32 This appears to be an issu...
-
-
-
-## v2.3.0 <small>(15 January 2023)</small>
-
-**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](deprecated/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
+- `dream.py` script renamed `invoke.py`. A `dream.py` script wrapper remains
-  backward compatibility.
+    for backward compatibility.
 - Completely new WebGUI - launch with `python3 scripts/invoke.py --web`
-- Support for [inpainting](deprecated/INPAINTING.md) and
+- Support for [inpainting](features/INPAINTING.md) and [outpainting](features/OUTPAINTING.md)
-  [outpainting](features/OUTPAINTING.md)
+- img2img runs on all k* samplers
-- img2img runs on all k\* samplers
+- Support for [negative prompts](features/PROMPTS.md#negative-and-unconditioned-prompts)
-- 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
+- Support in both WebGUI and CLI for [post-processing of previously-generated images](features/POSTPROCESS.md)
-  [post-processing of previously-generated images](features/POSTPROCESS.md)
+    using facial reconstruction, ESRGAN upscaling, outcropping (similar to DALL-E infinite canvas),
-  using facial reconstruction, ESRGAN upscaling, outcropping (similar to DALL-E
+    and "embiggen" upscaling. See the `!fix` command.
-  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 `--hires` option on `invoke>` line allows
+- New `--perlin` and `--threshold` options allow you to add and control variation
-  [larger images to be created without duplicating elements](deprecated/CLI.md#this-is-an-example-of-txt2img),
+    during image generation (see [Thresholding and Perlin Noise Initialization](features/OTHER.md#thresholding-and-perlin-noise-initialization-options))
-  at the cost of some performance.
+- Extensive metadata now written into PNG files, allowing reliable regeneration of images
-- New `--perlin` and `--threshold` options allow you to add and control
+    and tweaking of previous settings.
-  variation during image generation (see
+- Command-line completion in `invoke.py` now works on Windows, Linux and Mac platforms.
-  [Thresholding and Perlin Noise Initialization](features/OTHER.md#thresholding-and-perlin-noise-initialization-options))
+- Improved [command-line completion behavior](features/CLI.md)
-- Extensive metadata now written into PNG files, allowing reliable regeneration
+    New commands added:
-  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](deprecated/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
+    configure. To switch away from auto use the new flag like `--precision=float32`.
-  `--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)).
+    ([prixt](https://github.com/prixt)).
 - Inpainting support.
 - Improved web server GUI.
 - Lots of code and documentation cleanups.
@@ -660,17 +138,16 @@ sections describe what's new for InvokeAI.
 ## 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
+    ([Kevin Gibbons](https://github.com/bakkot) and many contributors and reviewers)
-  reviewers)
+- Supports a Google Colab notebook for a standalone server running on Google hardware
-- Supports a Google Colab notebook for a standalone server running on Google
+    [Arturo Mendivil](https://github.com/artmen1516)
-  hardware [Arturo Mendivil](https://github.com/artmen1516)
 - WebUI supports GFPGAN/ESRGAN facial reconstruction and upscaling
-  [Kevin Gibbons](https://github.com/bakkot)
+    [Kevin Gibbons](https://github.com/bakkot)
 - WebUI supports incremental display of in-progress images during generation
-  [Kevin Gibbons](https://github.com/bakkot)
+    [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.
+    stable-diffusion-v1.5) to be added without altering the code.
-  ([David Wager](https://github.com/maddavid12))
+    ([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.
@@ -682,59 +159,49 @@ sections describe what's new for InvokeAI.
 
 - 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
+- The web server is now integrated with the invoke.py script. Invoke by adding --web to
-  --web to the invoke.py command arguments.
+  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
+  VRAM requirements are modestly reduced. Thanks to both [Blessedcoolant](https://github.com/blessedcoolant) and
-  [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.
+- You can now swap samplers on the invoke> command line. [Blessedcoolant](https://github.com/blessedcoolant)
-  [Blessedcoolant](https://github.com/blessedcoolant)
 
 ---
 
 ## v1.11 <small>(26 August 2022)</small>
 
-- NEW FEATURE: Support upscaling and face enhancement using the GFPGAN module.
+- NEW FEATURE: Support upscaling and face enhancement using the GFPGAN module. (kudos to [Oceanswave](https://github.com/Oceanswave)
-  (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.
-- You now can specify a seed of -1 to use the previous image's seed, -2 to use
+  Seed memory only extends back to the previous command, but will work on all images generated with the -n# switch.
-  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
+- Created a feature branch named **yunsaki-morphing-invoke** which adds experimental support for
-  experimental support for iteratively modifying the prompt and its parameters.
+  iteratively modifying the prompt and its parameters. Please see[Pull Request #86](https://github.com/lstein/stable-diffusion/pull/86)
-  Please
+  for a synopsis of how this works. Note that when this feature is eventually added to the main branch, it will may be modified
-  see[Pull Request #86](https://github.com/lstein/stable-diffusion/pull/86) for
+  significantly.
-  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
+- A barebones but fully functional interactive web server for online generation of txt2img and img2img.
-  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).
+  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))
+  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
+- Added ability to personalize text to image generation (kudos to [Oceanswave](https://github.com/Oceanswave) and [nicolai256](https://github.com/nicolai256))
-  [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
+- Escape single quotes on the invoke> command before trying to parse. This avoids
-  avoids parse errors.
+  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.
@@ -744,36 +211,34 @@ sections describe what's new for InvokeAI.
 
 ## v1.07 <small>(23 August 2022)</small>
 
-- Image filenames will now never fill gaps in the sequence, but will be assigned
+- Image filenames will now never fill gaps in the sequence, but will be assigned the
-  the next higher name in the chosen directory. This ensures that the alphabetic
+  next higher name in the chosen directory. This ensures that the alphabetic and chronological
-  and chronological sort orders are the same.
+  sort orders are the same.
 
 ---
 
 ## v1.06 <small>(23 August 2022)</small>
 
-- Added weighted prompt support contributed by
+- Added weighted prompt support contributed by [xraxra](https://github.com/xraxra)
-  [xraxra](https://github.com/xraxra)
+- Example of using weighted prompts to tweak a demonic figure contributed by [bmaltais](https://github.com/bmaltais)
-- 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
+- Filenames now use the following formats:
-  produced by the same command (e.g. -n2), 000010.26742632.png -- distinguished
+  000010.95183149.png -- Two files produced by the same command (e.g. -n2),
-  by a different seed.
+  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
+  000011.4160627868.grid#1-4.png -- a grid of four images (-g); the whole grid can
-  can be regenerated with the indicated key
+  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
+- You can use the "cd" and "pwd" commands at the invoke> prompt to set and retrieve
-  retrieve the path of the output directory.
+  the path of the output directory.
 
 ---
 
@@ -787,28 +252,26 @@ sections describe what's new for InvokeAI.
 
 ## v1.03 <small>(22 August 2022)</small>
 
-- The original txt2img and img2img scripts from the CompViz repository have been
+- The original txt2img and img2img scripts from the CompViz repository have been moved into
-  moved into a subfolder named "orig_scripts", to reduce confusion.
+  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
+- A copy of the prompt and all of its switches and options is now stored in the corresponding
-  corresponding image in a tEXt metadata field named "Dream". You can read the
+  image in a tEXt metadata field named "Dream". You can read the prompt using scripts/images2prompt.py,
-  prompt using scripts/images2prompt.py, or an image editor that allows you to
+  or an image editor that allows you to explore the full metadata.
-  explore the full metadata. **Please run "conda env update" to load the k_lms
+  **Please run "conda env update" to load the k_lms dependencies!!**
-  dependencies!!**
 
 ---
 
 ## v1.01 <small>(21 August 2022)</small>
 
-- added k_lms sampling. **Please run "conda env update" to load the k_lms
+- added k_lms sampling.
-  dependencies!!**
+  **Please run "conda env update" to load the k_lms dependencies!!**
-- use half precision arithmetic by default, resulting in faster execution and
+- use half precision arithmetic by default, resulting in faster execution and lower memory requirements
-  lower memory requirements Pass argument --full_precision to invoke.py to get
+  Pass argument --full_precision to invoke.py to get slower but more accurate image generation
-  slower but more accurate image generation
 
 ---