Configure the NSFW checker at install time with default on (#1624)

* configure the NSFW checker at install time with default on

1. Changes the --safety_checker argument to --nsfw_checker and
--no-nsfw_checker. The original argument is recognized for backward
compatibility.

2. The configure script asks users whether to enable the checker
(default yes). Also offers users ability to select default sampler and
number of generation steps.

3.Enables the pasting of the caution icon on blurred images when
InvokeAI is installed into the package directory.

4. Adds documentation for the NSFW checker, including caveats about
accuracy, memory requirements, and intermediate image dispaly.

* use better fitting icon

* NSFW defaults false for testing

* set default back to nsfw active

Co-authored-by: Matthias Wild <40327258+mauwii@users.noreply.github.com>
Co-authored-by: mauwii <Mauwii@outlook.de>

.dockerignore

@@ -0,0 +1,12 @@
+*
+!backend
+!configs
+!environments-and-requirements
+!frontend
+!installer
+!ldm
+!main.py
+!scripts
+!server
+!static
+!setup.py

.editorconfig

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

.github/CODEOWNERS

@@ -2,3 +2,6 @@ ldm/invoke/pngwriter.py @CapableWeb
 ldm/invoke/server_legacy.py @CapableWeb
 scripts/legacy_api.py @CapableWeb
 tests/legacy_tests.sh @CapableWeb
+installer/ @tildebyte
+.github/workflows/ @mauwii
+docker_build/ @mauwii

.github/ISSUE_TEMPLATE/BUG_REPORT.yml

@@ -0,0 +1,102 @@
+name: 🐞 Bug Report
+
+description: File a bug report
+
+title: '[bug]: '
+
+labels: ['bug']
+
+# assignees:
+#   - moderator_bot
+#   - lstein
+
+body:
+  - type: markdown
+    attributes:
+      value: |
+        Thanks for taking the time to fill out this Bug Report!
+
+  - type: checkboxes
+    attributes:
+      label: Is there an existing issue for this?
+      description: |
+        Please use the [search function](https://github.com/invoke-ai/InvokeAI/issues?q=is%3Aissue+is%3Aopen+label%3Abug)
+        irst to see if an issue already exists for the bug you encountered.
+      options:
+        - label: I have searched the existing issues
+          required: true
+
+  - type: markdown
+    attributes:
+      value: __Describe your environment__
+
+  - type: dropdown
+    id: os_dropdown
+    attributes:
+      label: OS
+      description: Which operating System did you use when the bug occured
+      multiple: false
+      options:
+        - 'Linux'
+        - 'Windows'
+        - 'macOS'
+    validations:
+      required: true
+
+  - type: dropdown
+    id: gpu_dropdown
+    attributes:
+      label: GPU
+      description: Which kind of Graphic-Adapter is your System using
+      multiple: false
+      options:
+        - 'cuda'
+        - 'amd'
+        - 'mps'
+        - 'cpu'
+    validations:
+      required: true
+
+  - type: input
+    id: vram
+    attributes:
+      label: VRAM
+      description: Size of the VRAM if known
+      placeholder: 8GB
+    validations:
+      required: false
+
+  - type: textarea
+    id: what-happened
+    attributes:
+      label: What happened?
+      description: |
+        Briefly describe what happened, what you expected to happen and how to reproduce this bug.
+      placeholder: When using the webinterface and right-clicking on button X instead of the popup-menu there error Y appears
+    validations:
+      required: true
+
+  - type: textarea
+    attributes:
+      label: Screenshots
+      description: If applicable, add screenshots to help explain your problem
+      placeholder: this is what the result looked like <screenshot>
+    validations:
+      required: false
+
+  - type: textarea
+    attributes:
+      label: Additional context
+      description: Add any other context about the problem here
+      placeholder: Only happens when there is full moon and Friday the 13th on Christmas Eve 🎅🏻
+    validations:
+      required: false
+
+  - type: input
+    id: contact
+    attributes:
+      label: Contact Details
+      description: __OPTIONAL__ How can we get in touch with you if we need more info (besides this issue)?
+      placeholder: ex. email@example.com, discordname, twitter, ...
+    validations:
+      required: false

.github/ISSUE_TEMPLATE/FEATURE_REQUEST.yml

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

.github/ISSUE_TEMPLATE/bug_report.md

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

.github/ISSUE_TEMPLATE/config.yml

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

.github/ISSUE_TEMPLATE/feature_request.md

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

.github/workflows/build-container.yml

@@ -0,0 +1,43 @@
+# Building the Image without pushing to confirm it is still buildable
+# confirum functionality would unfortunately need way more resources
+name: build container image
+on:
+  push:
+    branches:
+      - 'main'
+      - 'development'
+      - 'update-dockerfile'
+
+jobs:
+  docker:
+    strategy:
+      fail-fast: false
+      matrix:
+        arch:
+          - x86_64
+          - aarch64
+        pip-requirements:
+          - requirements-lin-amd.txt
+          - requirements-lin-cuda.txt
+    runs-on: ubuntu-latest
+    name: ${{ matrix.pip-requirements }} ${{ matrix.arch }}
+    steps:
+      - name: prepare docker-tag
+        env:
+          repository: ${{ github.repository }}
+        run: echo "dockertag=${repository,,}" >> $GITHUB_ENV
+      - name: Checkout
+        uses: actions/checkout@v3
+      - name: Set up QEMU
+        uses: docker/setup-qemu-action@v2
+      - name: Set up Docker Buildx
+        uses: docker/setup-buildx-action@v2
+      - name: Build container
+        uses: docker/build-push-action@v3
+        with:
+          context: .
+          file: docker-build/Dockerfile
+          platforms: Linux/${{ matrix.arch }}
+          push: false
+          tags: ${{ env.dockertag }}:${{ matrix.pip-requirements }}-${{ matrix.arch }}
+          build-args: pip_requirements=${{ matrix.pip-requirements }}

.github/workflows/create-caches.yml

@@ -1,97 +0,0 @@
-name: Create Caches
-
-on: workflow_dispatch
-
-jobs:
-  os_matrix:
-    strategy:
-      matrix:
-        os: [ubuntu-latest, macos-latest]
-        include:
-          - os: ubuntu-latest
-            environment-file: environment.yml
-            default-shell: bash -l {0}
-          - os: macos-latest
-            environment-file: environment-mac.yml
-            default-shell: bash -l {0}
-    name: Test invoke.py on ${{ matrix.os }} with conda
-    runs-on: ${{ matrix.os }}
-    defaults:
-      run:
-        shell: ${{ matrix.default-shell }}
-    steps:
-      - name: Checkout sources
-        uses: actions/checkout@v3
-
-      - name: setup miniconda
-        uses: conda-incubator/setup-miniconda@v2
-        with:
-          auto-activate-base: false
-          auto-update-conda: false
-          miniconda-version: latest
-
-      - name: set environment
-        run: |
-          [[ "$GITHUB_REF" == 'refs/heads/main' ]] \
-            && echo "TEST_PROMPTS=tests/preflight_prompts.txt" >> $GITHUB_ENV \
-            || echo "TEST_PROMPTS=tests/dev_prompts.txt" >> $GITHUB_ENV
-          echo "CONDA_ROOT=$CONDA" >> $GITHUB_ENV
-          echo "CONDA_ENV_NAME=invokeai" >> $GITHUB_ENV
-
-      - name: Use Cached Stable Diffusion v1.4 Model
-        id: cache-sd-v1-4
-        uses: actions/cache@v3
-        env:
-          cache-name: cache-sd-v1-4
-        with:
-          path: models/ldm/stable-diffusion-v1/model.ckpt
-          key: ${{ env.cache-name }}
-          restore-keys: ${{ env.cache-name }}
-
-      - name: Download Stable Diffusion v1.4 Model
-        if: ${{ steps.cache-sd-v1-4.outputs.cache-hit != 'true' }}
-        run: |
-          [[ -d models/ldm/stable-diffusion-v1 ]] \
-            || mkdir -p models/ldm/stable-diffusion-v1
-          [[ -r models/ldm/stable-diffusion-v1/model.ckpt ]] \
-            || curl -o models/ldm/stable-diffusion-v1/model.ckpt ${{ secrets.SD_V1_4_URL }}
-
-      - name: Use cached Conda Environment
-        uses: actions/cache@v3
-        env:
-          cache-name: cache-conda-env-${{ env.CONDA_ENV_NAME }}
-          conda-env-file: ${{ matrix.environment-file }}
-        with:
-          path: ${{ env.CONDA_ROOT }}/envs/${{ env.CONDA_ENV_NAME }}
-          key: ${{ env.cache-name }}
-          restore-keys: ${{ env.cache-name }}-${{ runner.os }}-${{ hashFiles(env.conda-env-file) }}
-
-      - name: Use cached Conda Packages
-        uses: actions/cache@v3
-        env:
-          cache-name: cache-conda-env-${{ env.CONDA_ENV_NAME }}
-          conda-env-file: ${{ matrix.environment-file }}
-        with:
-          path: ${{ env.CONDA_PKGS_DIR }}
-          key: ${{ env.cache-name }}
-          restore-keys: ${{ env.cache-name }}-${{ runner.os }}-${{ hashFiles(env.conda-env-file) }}
-
-      - 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/mkdocs-material.yml

@@ -22,7 +22,7 @@ jobs:
       - name: install requirements
         run: |
           python -m \
-            pip install -r requirements-mkdocs.txt
+            pip install -r docs/requirements-mkdocs.txt
 
       - name: confirm buildability
         run: |

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

@@ -1,4 +1,4 @@
-name: Test Invoke with Conda
+name: Test invoke.py
 on:
   push:
     branches:
@@ -11,31 +11,63 @@ on:
       - 'development'
 
 jobs:
-  os_matrix:
+  matrix:
     strategy:
       matrix:
-        os: [ubuntu-latest, macos-latest]
+        stable-diffusion-model:
+          - 'stable-diffusion-1.5'
+        environment-yaml:
+          - environment-lin-amd.yml
+          - environment-lin-cuda.yml
+          - environment-mac.yml
         include:
-          - os: ubuntu-latest
-            environment-file: environment.yml
+          - environment-yaml: environment-lin-amd.yml
+            os: ubuntu-latest
             default-shell: bash -l {0}
-          - os: macos-latest
-            environment-file: environment-mac.yml
+          - environment-yaml: environment-lin-cuda.yml
+            os: ubuntu-latest
             default-shell: bash -l {0}
-    name: Test invoke.py on ${{ matrix.os }} with conda
+          - environment-yaml: environment-mac.yml
+            os: macos-12
+            default-shell: bash -l {0}
+          - stable-diffusion-model: stable-diffusion-1.5
+            stable-diffusion-model-url: 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
+            stable-diffusion-model-dl-name: v1-5-pruned-emaonly.ckpt
+    name: ${{ matrix.environment-yaml }} on ${{ matrix.os }}
     runs-on: ${{ matrix.os }}
+    env:
+      CONDA_ENV_NAME: invokeai
+      INVOKEAI_ROOT: '${{ github.workspace }}/invokeai'
     defaults:
       run:
         shell: ${{ matrix.default-shell }}
     steps:
       - name: Checkout sources
+        id: checkout-sources
         uses: actions/checkout@v3
 
-      - name: setup miniconda
+      - name: create models.yaml from example
+        run: |
+          mkdir -p ${{ env.INVOKEAI_ROOT }}/configs
+          cp configs/models.yaml.example ${{ env.INVOKEAI_ROOT }}/configs/models.yaml
+
+      - name: create environment.yml
+        run: cp "environments-and-requirements/${{ matrix.environment-yaml }}" environment.yml
+
+      - 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-yaml) }}
+
+      - name: Activate Conda Env
+        id: activate-conda-env
         uses: conda-incubator/setup-miniconda@v2
         with:
-          auto-activate-base: false
-          auto-update-conda: false
+          activate-environment: ${{ env.CONDA_ENV_NAME }}
+          environment-file: environment.yml
           miniconda-version: latest
 
       - name: set test prompt to main branch validation
@@ -48,79 +80,56 @@ jobs:
 
       - name: set test prompt to Pull Request validation
         if: ${{ github.ref != 'refs/heads/main' && github.ref != 'refs/heads/development' }}
-        run: echo "TEST_PROMPTS=tests/pr_prompt.txt" >> $GITHUB_ENV
+        run: echo "TEST_PROMPTS=tests/validate_pr_prompt.txt" >> $GITHUB_ENV
 
-      - name: set conda environment name
-        run: echo "CONDA_ENV_NAME=invokeai" >> $GITHUB_ENV
-
-      - name: Use Cached Stable Diffusion v1.4 Model
-        id: cache-sd-v1-4
+      - name: Use Cached Stable Diffusion Model
+        id: cache-sd-model
         uses: actions/cache@v3
         env:
-          cache-name: cache-sd-v1-4
+          cache-name: cache-${{ matrix.stable-diffusion-model }}
         with:
-          path: models/ldm/stable-diffusion-v1/model.ckpt
+          path: ${{ env.INVOKEAI_ROOT }}/${{ matrix.stable-diffusion-model-dl-path }}
           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' }}
+      - name: Download ${{ matrix.stable-diffusion-model }}
+        id: download-stable-diffusion-model
+        if: ${{ steps.cache-sd-model.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 -o models/ldm/stable-diffusion-v1/model.ckpt ${{ secrets.SD_V1_4_URL }}
+          mkdir -p "${{ env.INVOKEAI_ROOT }}/${{ matrix.stable-diffusion-model-dl-path }}"
+          curl \
+            -H "Authorization: Bearer ${{ secrets.HUGGINGFACE_TOKEN }}" \
+            -o "${{ env.INVOKEAI_ROOT }}/${{ matrix.stable-diffusion-model-dl-path }}/${{ matrix.stable-diffusion-model-dl-name }}" \
+            -L ${{ matrix.stable-diffusion-model-url }}
 
-      - name: Use cached Conda Environment
-        uses: actions/cache@v3
-        env:
-          cache-name: cache-conda-env-${{ env.CONDA_ENV_NAME }}
-          conda-env-file: ${{ matrix.environment-file }}
-        with:
-          path: ${{ env.CONDA }}/envs/${{ env.CONDA_ENV_NAME }}
-          key: env-${{ env.cache-name }}-${{ runner.os }}-${{ hashFiles(env.conda-env-file) }}
+      - name: run configure_invokeai.py
+        id: run-preload-models
+        run: |
+          python scripts/configure_invokeai.py --no-interactive --yes
 
-      - name: Use cached Conda Packages
-        uses: actions/cache@v3
-        env:
-          cache-name: cache-conda-pkgs-${{ env.CONDA_ENV_NAME }}
-          conda-env-file: ${{ matrix.environment-file }}
-        with:
-          path: ${{ env.CONDA_PKGS_DIR }}
-          key: pkgs-${{ env.cache-name }}-${{ runner.os }}-${{ hashFiles(env.conda-env-file) }}
-
-      - 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
+      - name: cat ~/.invokeai
+        id: cat-invokeai
+        run: cat ~/.invokeai
 
       - name: Run the tests
+        id: run-tests
         run: |
           time python scripts/invoke.py \
-            --from_file ${{ env.TEST_PROMPTS }}
+            --no-patchmatch \
+            --no-nsfw_checker \
+            --model ${{ matrix.stable-diffusion-model }} \
+            --from_file ${{ env.TEST_PROMPTS }} \
+            --root="${{ env.INVOKEAI_ROOT }}" \
+            --outdir="${{ env.INVOKEAI_ROOT }}/outputs"
 
       - 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 }}.yml
+          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_${{ matrix.os }}
-          path: outputs/img-samples
+          name: results_${{ matrix.requirements-file }}_${{ matrix.python-version }}
+          path: ${{ env.INVOKEAI_ROOT }}/outputs

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

@@ -0,0 +1,128 @@
+name: Test invoke.py pip
+on:
+  push:
+    branches:
+      - 'main'
+      - 'development'
+  pull_request:
+    branches:
+      - 'main'
+      - 'development'
+
+jobs:
+  matrix:
+    strategy:
+      matrix:
+        stable-diffusion-model:
+          - stable-diffusion-1.5
+        requirements-file:
+          - requirements-lin-cuda.txt
+          - requirements-lin-amd.txt
+          - requirements-mac-mps-cpu.txt
+        python-version:
+          # - '3.9'
+          - '3.10'
+        include:
+          - requirements-file: requirements-lin-cuda.txt
+            os: ubuntu-latest
+            default-shell: bash -l {0}
+          - requirements-file: requirements-lin-amd.txt
+            os: ubuntu-latest
+            default-shell: bash -l {0}
+          - requirements-file: requirements-mac-mps-cpu.txt
+            os: macOS-12
+            default-shell: bash -l {0}
+          - stable-diffusion-model: stable-diffusion-1.5
+            stable-diffusion-model-url: 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
+            stable-diffusion-model-dl-name: v1-5-pruned-emaonly.ckpt
+    name: ${{ matrix.requirements-file }} on ${{ matrix.python-version }}
+    runs-on: ${{ matrix.os }}
+    defaults:
+      run:
+        shell: ${{ matrix.default-shell }}
+    env:
+      INVOKEAI_ROOT: '${{ github.workspace }}/invokeai'
+    steps:
+      - name: Checkout sources
+        id: checkout-sources
+        uses: actions/checkout@v3
+
+      - name: create models.yaml from example
+        run: |
+          mkdir -p ${{ env.INVOKEAI_ROOT }}/configs
+          cp configs/models.yaml.example ${{ env.INVOKEAI_ROOT }}/configs/models.yaml
+
+      - 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" >> $GITHUB_ENV
+
+      - name: create requirements.txt
+        run: cp 'environments-and-requirements/${{ matrix.requirements-file }}' '${{ matrix.requirements-file }}'
+
+      - name: setup python
+        uses: actions/setup-python@v4
+        with:
+          python-version: ${{ matrix.python-version }}
+          cache: 'pip'
+          cache-dependency-path: ${{ matrix.requirements-file }}
+
+      # - name: install dependencies
+      #   run: ${{ env.pythonLocation }}/bin/pip install --upgrade pip setuptools wheel
+
+      - name: install requirements
+        run: ${{ env.pythonLocation }}/bin/pip install -r '${{ matrix.requirements-file }}'
+
+      - name: Use Cached Stable Diffusion Model
+        id: cache-sd-model
+        uses: actions/cache@v3
+        env:
+          cache-name: cache-${{ matrix.stable-diffusion-model }}
+        with:
+          path: ${{ env.INVOKEAI_ROOT }}/${{ matrix.stable-diffusion-model-dl-path }}
+          key: ${{ env.cache-name }}
+
+      - name: Download ${{ matrix.stable-diffusion-model }}
+        id: download-stable-diffusion-model
+        if: ${{ steps.cache-sd-model.outputs.cache-hit != 'true' }}
+        run: |
+          mkdir -p "${{ env.INVOKEAI_ROOT }}/${{ matrix.stable-diffusion-model-dl-path }}"
+          curl \
+            -H "Authorization: Bearer ${{ secrets.HUGGINGFACE_TOKEN }}" \
+            -o "${{ env.INVOKEAI_ROOT }}/${{ matrix.stable-diffusion-model-dl-path }}/${{ matrix.stable-diffusion-model-dl-name }}" \
+            -L ${{ matrix.stable-diffusion-model-url }}
+
+      - name: run configure_invokeai.py
+        id: run-preload-models
+        run: |
+          ${{ env.pythonLocation }}/bin/python scripts/configure_invokeai.py --no-interactive --yes
+
+      - name: cat ~/.invokeai
+        id: cat-invokeai
+        run: cat ~/.invokeai
+
+      - name: Run the tests
+        id: run-tests
+        run: |
+          time ${{ env.pythonLocation }}/bin/python scripts/invoke.py \
+            --no-patchmatch \
+            --no-nsfw_checker \
+            --model ${{ matrix.stable-diffusion-model }} \
+            --from_file ${{ env.TEST_PROMPTS }} \
+            --root="${{ env.INVOKEAI_ROOT }}" \
+            --outdir="${{ env.INVOKEAI_ROOT }}/outputs"
+
+      - name: Archive results
+        id: archive-results
+        uses: actions/upload-artifact@v3
+        with:
+          name: results_${{ matrix.requirements-file }}_${{ matrix.python-version }}
+          path: ${{ env.INVOKEAI_ROOT }}/outputs

.gitignore

@@ -3,6 +3,10 @@ outputs/
 models/ldm/stable-diffusion-v1/model.ckpt
 **/restoration/codeformer/weights
 
+# ignore user models config
+configs/models.user.yaml
+config/models.user.yml
+
 # ignore the Anaconda/Miniconda installer used while building Docker image
 anaconda.sh
 
@@ -195,7 +199,38 @@ checkpoints
 .scratch/
 .vscode/
 gfpgan/
-models/ldm/stable-diffusion-v1/model.sha256
+models/ldm/stable-diffusion-v1/*.sha256
+
 
 # GFPGAN model files
 gfpgan/
+
+# config file (will be created by installer)
+configs/models.yaml
+
+# weights (will be created by installer)
+models/ldm/stable-diffusion-v1/*.ckpt
+models/clipseg
+models/gfpgan
+
+# ignore initfile
+.invokeai
+
+# ignore environment.yml and requirements.txt
+# these are links to the real files in environments-and-requirements
+environment.yml
+requirements.txt
+
+# source installer files
+source_installer/*zip
+source_installer/invokeAI
+install.bat
+install.sh
+update.bat
+update.sh
+
+# this may be present if the user created a venv
+invokeai
+
+# no longer stored in source directory
+models

CODE_OF_CONDUCT.md

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

InvokeAI_Statement_of_Values.md

@@ -0,0 +1,85 @@
+<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**, and **keturn**. 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.  
+

README.md

@@ -2,7 +2,7 @@
 
 # InvokeAI: A Stable Diffusion Toolkit
 
-_Formally known as lstein/stable-diffusion_
+_Formerly known as lstein/stable-diffusion_
 
 ![project logo](docs/assets/logo.png)
 
@@ -42,7 +42,7 @@ generation process. It runs on Windows, Mac and Linux machines, with
 GPU cards with as little as 4 GB of RAM. It provides both a polished
 Web interface (see below), and an easy-to-use command-line interface.
 
-**Quick links**: [<a href="https://discord.gg/NwVCmKwY">Discord Server</a>] [<a href="https://invoke-ai.github.io/InvokeAI/">Documentation and Tutorials</a>] [<a href="https://github.com/invoke-ai/InvokeAI/">Code and Downloads</a>] [<a href="https://github.com/invoke-ai/InvokeAI/issues">Bug Reports</a>] [<a href="https://github.com/invoke-ai/InvokeAI/discussions">Discussion, Ideas & Q&A</a>]
+**Quick links**: [<a href="https://discord.gg/ZmtBAhwWhy">Discord Server</a>] [<a href="https://invoke-ai.github.io/InvokeAI/">Documentation and Tutorials</a>] [<a href="https://github.com/invoke-ai/InvokeAI/">Code and Downloads</a>] [<a href="https://github.com/invoke-ai/InvokeAI/issues">Bug Reports</a>] [<a href="https://github.com/invoke-ai/InvokeAI/discussions">Discussion, Ideas & Q&A</a>]
 
 <div align="center"><img src="docs/assets/invoke-web-server-1.png" width=640></div>
 
@@ -65,14 +65,11 @@ requests. Be sure to use the provided templates. They will help aid diagnose iss
 
 ### Installation
 
-This fork is supported across multiple platforms. You can find individual installation instructions
-below.
-
-- #### [Linux](https://invoke-ai.github.io/InvokeAI/installation/INSTALL_LINUX/)
-
-- #### [Windows](https://invoke-ai.github.io/InvokeAI/installation/INSTALL_WINDOWS/)
-
-- #### [Macintosh](https://invoke-ai.github.io/InvokeAI/installation/INSTALL_MAC/)
+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/)
 
 ### Hardware Requirements
 
@@ -175,15 +172,22 @@ problems and other issues.
 # Contributing
 
 Anyone who wishes to contribute to this project, whether documentation, features, bug fixes, code
-cleanup, testing, or code reviews, is very much encouraged to do so. If you are unfamiliar with how
-to contribute to GitHub projects, here is a
-[Getting Started Guide](https://opensource.com/article/19/7/create-pull-request-github).
+cleanup, testing, or code reviews, is very much encouraged to do so. To join, just raise your hand on the InvokeAI
+Discord server or discussion board. 
 
-A full set of contribution guidelines, along with templates, are in progress, but for now the most
+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, but for now the most
 important thing is to **make your pull request against the "development" branch**, and not against
 "main". This will help keep public breakage to a minimum and will allow you to propose more radical
 changes.
 
+We hope you enjoy using our software as much as we enjoy creating it,
+and we hope that some of those of you who are reading this will elect
+to become part of our community.
+
+Welcome to InvokeAI!
+
 ### Contributors
 
 This fork is a combined effort of various people from across the world.

backend/modules/get_canvas_generation_mode.py

@@ -0,0 +1,117 @@
+from PIL import Image, ImageChops
+from PIL.Image import Image as ImageType
+from typing import Union, Literal
+
+# https://stackoverflow.com/questions/43864101/python-pil-check-if-image-is-transparent
+def check_for_any_transparency(img: Union[ImageType, str]) -> bool:
+    if type(img) is str:
+        img = Image.open(str)
+
+    if img.info.get("transparency", None) is not None:
+        return True
+    if img.mode == "P":
+        transparent = img.info.get("transparency", -1)
+        for _, index in img.getcolors():
+            if index == transparent:
+                return True
+    elif img.mode == "RGBA":
+        extrema = img.getextrema()
+        if extrema[3][0] < 255:
+            return True
+    return False
+
+
+def get_canvas_generation_mode(
+    init_img: Union[ImageType, str], init_mask: Union[ImageType, str]
+) -> Literal["txt2img", "outpainting", "inpainting", "img2img",]:
+    if type(init_img) is str:
+        init_img = Image.open(init_img)
+
+    if type(init_mask) is str:
+        init_mask = Image.open(init_mask)
+
+    init_img = init_img.convert("RGBA")
+
+    # Get alpha from init_img
+    init_img_alpha = init_img.split()[-1]
+    init_img_alpha_mask = init_img_alpha.convert("L")
+    init_img_has_transparency = check_for_any_transparency(init_img)
+
+    if init_img_has_transparency:
+        init_img_is_fully_transparent = (
+            True if init_img_alpha_mask.getbbox() is None else False
+        )
+
+    """
+    Mask images are white in areas where no change should be made, black where changes 
+    should be made.
+    """
+
+    # Fit the mask to init_img's size and convert it to greyscale
+    init_mask = init_mask.resize(init_img.size).convert("L")
+
+    """
+    PIL.Image.getbbox() returns the bounding box of non-zero areas of the image, so we first
+    invert the mask image so that masked areas are white and other areas black == zero.
+    getbbox() now tells us if the are any masked areas.
+    """
+    init_mask_bbox = ImageChops.invert(init_mask).getbbox()
+    init_mask_exists = False if init_mask_bbox is None else True
+
+    if init_img_has_transparency:
+        if init_img_is_fully_transparent:
+            return "txt2img"
+        else:
+            return "outpainting"
+    else:
+        if init_mask_exists:
+            return "inpainting"
+        else:
+            return "img2img"
+
+
+def main():
+    # Testing
+    init_img_opaque = "test_images/init-img_opaque.png"
+    init_img_partial_transparency = "test_images/init-img_partial_transparency.png"
+    init_img_full_transparency = "test_images/init-img_full_transparency.png"
+    init_mask_no_mask = "test_images/init-mask_no_mask.png"
+    init_mask_has_mask = "test_images/init-mask_has_mask.png"
+
+    print(
+        "OPAQUE IMAGE, NO MASK, expect img2img, got ",
+        get_canvas_generation_mode(init_img_opaque, init_mask_no_mask),
+    )
+
+    print(
+        "IMAGE WITH TRANSPARENCY, NO MASK, expect outpainting, got ",
+        get_canvas_generation_mode(
+            init_img_partial_transparency, init_mask_no_mask
+        ),
+    )
+
+    print(
+        "FULLY TRANSPARENT IMAGE NO MASK, expect txt2img, got ",
+        get_canvas_generation_mode(init_img_full_transparency, init_mask_no_mask),
+    )
+
+    print(
+        "OPAQUE IMAGE, WITH MASK, expect inpainting, got ",
+        get_canvas_generation_mode(init_img_opaque, init_mask_has_mask),
+    )
+
+    print(
+        "IMAGE WITH TRANSPARENCY, WITH MASK, expect outpainting, got ",
+        get_canvas_generation_mode(
+            init_img_partial_transparency, init_mask_has_mask
+        ),
+    )
+
+    print(
+        "FULLY TRANSPARENT IMAGE WITH MASK, expect txt2img, got ",
+        get_canvas_generation_mode(init_img_full_transparency, init_mask_has_mask),
+    )
+
+
+if __name__ == "__main__":
+    main()

backend/modules/parameters.py

@@ -5,6 +5,8 @@ SAMPLER_CHOICES = [
     "ddim",
     "k_dpm_2_a",
     "k_dpm_2",
+    "k_dpmpp_2_a",
+    "k_dpmpp_2",
     "k_euler_a",
     "k_euler",
     "k_heun",

backend/server.py

@@ -1,822 +0,0 @@
-import mimetypes
-import transformers
-import json
-import os
-import traceback
-import eventlet
-import glob
-import shlex
-import math
-import shutil
-import sys
-
-sys.path.append(".")
-
-from argparse import ArgumentTypeError
-from modules.create_cmd_parser import create_cmd_parser
-
-parser = create_cmd_parser()
-opt = parser.parse_args()
-
-
-from flask_socketio import SocketIO
-from flask import Flask, send_from_directory, url_for, jsonify
-from pathlib import Path
-from PIL import Image
-from pytorch_lightning import logging
-from threading import Event
-from uuid import uuid4
-from send2trash import send2trash
-
-
-from ldm.generate import Generate
-from ldm.invoke.restoration import Restoration
-from ldm.invoke.pngwriter import PngWriter, retrieve_metadata
-from ldm.invoke.args import APP_ID, APP_VERSION, calculate_init_img_hash
-from ldm.invoke.conditioning import split_weighted_subprompts
-
-from modules.parameters import parameters_to_command
-
-
-"""
-USER CONFIG
-"""
-if opt.cors and "*" in opt.cors:
-    raise ArgumentTypeError('"*" is not an allowed CORS origin')
-
-
-output_dir = "outputs/"  # Base output directory for images
-host = opt.host  # Web & socket.io host
-port = opt.port  # Web & socket.io port
-verbose = opt.verbose  # enables copious socket.io logging
-precision = opt.precision
-free_gpu_mem = opt.free_gpu_mem
-embedding_path = opt.embedding_path
-additional_allowed_origins = (
-    opt.cors if opt.cors else []
-)  # additional CORS allowed origins
-model = "stable-diffusion-1.4"
-
-"""
-END USER CONFIG
-"""
-
-
-print("* Initializing, be patient...\n")
-
-
-"""
-SERVER SETUP
-"""
-
-
-# fix missing mimetypes on windows due to registry wonkiness
-mimetypes.add_type("application/javascript", ".js")
-mimetypes.add_type("text/css", ".css")
-
-app = Flask(__name__, static_url_path="", static_folder="../frontend/dist/")
-
-
-app.config["OUTPUTS_FOLDER"] = "../outputs"
-
-
-@app.route("/outputs/<path:filename>")
-def outputs(filename):
-    return send_from_directory(app.config["OUTPUTS_FOLDER"], filename)
-
-
-@app.route("/", defaults={"path": ""})
-def serve(path):
-    return send_from_directory(app.static_folder, "index.html")
-
-
-logger = True if verbose else False
-engineio_logger = True if verbose else False
-
-# default 1,000,000, needs to be higher for socketio to accept larger images
-max_http_buffer_size = 10000000
-
-cors_allowed_origins = [f"http://{host}:{port}"] + additional_allowed_origins
-
-socketio = SocketIO(
-    app,
-    logger=logger,
-    engineio_logger=engineio_logger,
-    max_http_buffer_size=max_http_buffer_size,
-    cors_allowed_origins=cors_allowed_origins,
-    ping_interval=(50, 50),
-    ping_timeout=60,
-)
-
-
-"""
-END SERVER SETUP
-"""
-
-
-"""
-APP SETUP
-"""
-
-
-class CanceledException(Exception):
-    pass
-
-
-try:
-    gfpgan, codeformer, esrgan = None, None, None
-    from ldm.invoke.restoration.base import Restoration
-
-    restoration = Restoration()
-    gfpgan, codeformer = restoration.load_face_restore_models()
-    esrgan = restoration.load_esrgan()
-
-    # coreformer.process(self, image, strength, device, seed=None, fidelity=0.75)
-
-except (ModuleNotFoundError, ImportError):
-    print(traceback.format_exc(), file=sys.stderr)
-    print(">> You may need to install the ESRGAN and/or GFPGAN modules")
-
-canceled = Event()
-
-# reduce logging outputs to error
-transformers.logging.set_verbosity_error()
-logging.getLogger("pytorch_lightning").setLevel(logging.ERROR)
-
-# Initialize and load model
-generate = Generate(
-    model,
-    precision=precision,
-    embedding_path=embedding_path,
-)
-generate.free_gpu_mem = free_gpu_mem
-generate.load_model()
-
-
-# location for "finished" images
-result_path = os.path.join(output_dir, "img-samples/")
-
-# temporary path for intermediates
-intermediate_path = os.path.join(result_path, "intermediates/")
-
-# path for user-uploaded init images and masks
-init_image_path = os.path.join(result_path, "init-images/")
-mask_image_path = os.path.join(result_path, "mask-images/")
-
-# txt log
-log_path = os.path.join(result_path, "invoke_log.txt")
-
-# make all output paths
-[
-    os.makedirs(path, exist_ok=True)
-    for path in [result_path, intermediate_path, init_image_path, mask_image_path]
-]
-
-
-"""
-END APP SETUP
-"""
-
-
-"""
-SOCKET.IO LISTENERS
-"""
-
-
-@socketio.on("requestSystemConfig")
-def handle_request_capabilities():
-    print(f">> System config requested")
-    config = get_system_config()
-    socketio.emit("systemConfig", config)
-
-
-@socketio.on("requestImages")
-def handle_request_images(page=1, offset=0, last_mtime=None):
-    chunk_size = 50
-
-    if last_mtime:
-        print(f">> Latest images requested")
-    else:
-        print(
-            f">> Page {page} of images requested (page size {chunk_size} offset {offset})"
-        )
-
-    paths = glob.glob(os.path.join(result_path, "*.png"))
-    sorted_paths = sorted(paths, key=lambda x: os.path.getmtime(x), reverse=True)
-
-    if last_mtime:
-        image_paths = filter(lambda x: os.path.getmtime(x) > last_mtime, sorted_paths)
-    else:
-
-        image_paths = sorted_paths[
-            slice(chunk_size * (page - 1) + offset, chunk_size * page + offset)
-        ]
-        page = page + 1
-
-    image_array = []
-
-    for path in image_paths:
-        metadata = retrieve_metadata(path)
-        image_array.append(
-            {
-                "url": path,
-                "mtime": os.path.getmtime(path),
-                "metadata": metadata["sd-metadata"],
-            }
-        )
-
-    socketio.emit(
-        "galleryImages",
-        {
-            "images": image_array,
-            "nextPage": page,
-            "offset": offset,
-            "onlyNewImages": True if last_mtime else False,
-        },
-    )
-
-
-@socketio.on("generateImage")
-def handle_generate_image_event(
-    generation_parameters, esrgan_parameters, gfpgan_parameters
-):
-    print(
-        f">> Image generation requested: {generation_parameters}\nESRGAN parameters: {esrgan_parameters}\nGFPGAN parameters: {gfpgan_parameters}"
-    )
-    generate_images(generation_parameters, esrgan_parameters, gfpgan_parameters)
-
-
-@socketio.on("runESRGAN")
-def handle_run_esrgan_event(original_image, esrgan_parameters):
-    print(
-        f'>> ESRGAN upscale requested for "{original_image["url"]}": {esrgan_parameters}'
-    )
-    progress = {
-        "currentStep": 1,
-        "totalSteps": 1,
-        "currentIteration": 1,
-        "totalIterations": 1,
-        "currentStatus": "Preparing",
-        "isProcessing": True,
-        "currentStatusHasSteps": False,
-    }
-
-    socketio.emit("progressUpdate", progress)
-    eventlet.sleep(0)
-
-    image = Image.open(original_image["url"])
-
-    seed = (
-        original_image["metadata"]["seed"]
-        if "seed" in original_image["metadata"]
-        else "unknown_seed"
-    )
-
-    progress["currentStatus"] = "Upscaling"
-    socketio.emit("progressUpdate", progress)
-    eventlet.sleep(0)
-
-    image = esrgan.process(
-        image=image,
-        upsampler_scale=esrgan_parameters["upscale"][0],
-        strength=esrgan_parameters["upscale"][1],
-        seed=seed,
-    )
-
-    progress["currentStatus"] = "Saving image"
-    socketio.emit("progressUpdate", progress)
-    eventlet.sleep(0)
-
-    esrgan_parameters["seed"] = seed
-    metadata = parameters_to_post_processed_image_metadata(
-        parameters=esrgan_parameters,
-        original_image_path=original_image["url"],
-        type="esrgan",
-    )
-    command = parameters_to_command(esrgan_parameters)
-
-    path = save_image(image, command, metadata, result_path, postprocessing="esrgan")
-
-    write_log_message(f'[Upscaled] "{original_image["url"]}" > "{path}": {command}')
-
-    progress["currentStatus"] = "Finished"
-    progress["currentStep"] = 0
-    progress["totalSteps"] = 0
-    progress["currentIteration"] = 0
-    progress["totalIterations"] = 0
-    progress["isProcessing"] = False
-    socketio.emit("progressUpdate", progress)
-    eventlet.sleep(0)
-
-    socketio.emit(
-        "esrganResult",
-        {
-            "url": os.path.relpath(path),
-            "mtime": os.path.getmtime(path),
-            "metadata": metadata,
-        },
-    )
-
-
-@socketio.on("runGFPGAN")
-def handle_run_gfpgan_event(original_image, gfpgan_parameters):
-    print(
-        f'>> GFPGAN face fix requested for "{original_image["url"]}": {gfpgan_parameters}'
-    )
-    progress = {
-        "currentStep": 1,
-        "totalSteps": 1,
-        "currentIteration": 1,
-        "totalIterations": 1,
-        "currentStatus": "Preparing",
-        "isProcessing": True,
-        "currentStatusHasSteps": False,
-    }
-
-    socketio.emit("progressUpdate", progress)
-    eventlet.sleep(0)
-
-    image = Image.open(original_image["url"])
-
-    seed = (
-        original_image["metadata"]["seed"]
-        if "seed" in original_image["metadata"]
-        else "unknown_seed"
-    )
-
-    progress["currentStatus"] = "Fixing faces"
-    socketio.emit("progressUpdate", progress)
-    eventlet.sleep(0)
-
-    image = gfpgan.process(
-        image=image, strength=gfpgan_parameters["facetool_strength"], seed=seed
-    )
-
-    progress["currentStatus"] = "Saving image"
-    socketio.emit("progressUpdate", progress)
-    eventlet.sleep(0)
-
-    gfpgan_parameters["seed"] = seed
-    metadata = parameters_to_post_processed_image_metadata(
-        parameters=gfpgan_parameters,
-        original_image_path=original_image["url"],
-        type="gfpgan",
-    )
-    command = parameters_to_command(gfpgan_parameters)
-
-    path = save_image(image, command, metadata, result_path, postprocessing="gfpgan")
-
-    write_log_message(f'[Fixed faces] "{original_image["url"]}" > "{path}": {command}')
-
-    progress["currentStatus"] = "Finished"
-    progress["currentStep"] = 0
-    progress["totalSteps"] = 0
-    progress["currentIteration"] = 0
-    progress["totalIterations"] = 0
-    progress["isProcessing"] = False
-    socketio.emit("progressUpdate", progress)
-    eventlet.sleep(0)
-
-    socketio.emit(
-        "gfpganResult",
-        {
-            "url": os.path.relpath(path),
-            "mtime": os.path.mtime(path),
-            "metadata": metadata,
-        },
-    )
-
-
-@socketio.on("cancel")
-def handle_cancel():
-    print(f">> Cancel processing requested")
-    canceled.set()
-    socketio.emit("processingCanceled")
-
-
-# TODO: I think this needs a safety mechanism.
-@socketio.on("deleteImage")
-def handle_delete_image(path, uuid):
-    print(f'>> Delete requested "{path}"')
-    send2trash(path)
-    socketio.emit("imageDeleted", {"url": path, "uuid": uuid})
-
-
-# TODO: I think this needs a safety mechanism.
-@socketio.on("uploadInitialImage")
-def handle_upload_initial_image(bytes, name):
-    print(f'>> Init image upload requested "{name}"')
-    uuid = uuid4().hex
-    split = os.path.splitext(name)
-    name = f"{split[0]}.{uuid}{split[1]}"
-    file_path = os.path.join(init_image_path, name)
-    os.makedirs(os.path.dirname(file_path), exist_ok=True)
-    newFile = open(file_path, "wb")
-    newFile.write(bytes)
-    socketio.emit("initialImageUploaded", {"url": file_path, "uuid": ""})
-
-
-# TODO: I think this needs a safety mechanism.
-@socketio.on("uploadMaskImage")
-def handle_upload_mask_image(bytes, name):
-    print(f'>> Mask image upload requested "{name}"')
-    uuid = uuid4().hex
-    split = os.path.splitext(name)
-    name = f"{split[0]}.{uuid}{split[1]}"
-    file_path = os.path.join(mask_image_path, name)
-    os.makedirs(os.path.dirname(file_path), exist_ok=True)
-    newFile = open(file_path, "wb")
-    newFile.write(bytes)
-    socketio.emit("maskImageUploaded", {"url": file_path, "uuid": ""})
-
-
-"""
-END SOCKET.IO LISTENERS
-"""
-
-
-"""
-ADDITIONAL FUNCTIONS
-"""
-
-
-def get_system_config():
-    return {
-        "model": "stable diffusion",
-        "model_id": model,
-        "model_hash": generate.model_hash,
-        "app_id": APP_ID,
-        "app_version": APP_VERSION,
-    }
-
-
-def parameters_to_post_processed_image_metadata(parameters, original_image_path, type):
-    # top-level metadata minus `image` or `images`
-    metadata = get_system_config()
-
-    orig_hash = calculate_init_img_hash(original_image_path)
-
-    image = {"orig_path": original_image_path, "orig_hash": orig_hash}
-
-    if type == "esrgan":
-        image["type"] = "esrgan"
-        image["scale"] = parameters["upscale"][0]
-        image["strength"] = parameters["upscale"][1]
-    elif type == "gfpgan":
-        image["type"] = "gfpgan"
-        image["strength"] = parameters["facetool_strength"]
-    else:
-        raise TypeError(f"Invalid type: {type}")
-
-    metadata["image"] = image
-    return metadata
-
-
-def parameters_to_generated_image_metadata(parameters):
-    # top-level metadata minus `image` or `images`
-
-    metadata = get_system_config()
-    # remove any image keys not mentioned in RFC #266
-    rfc266_img_fields = [
-        "type",
-        "postprocessing",
-        "sampler",
-        "prompt",
-        "seed",
-        "variations",
-        "steps",
-        "cfg_scale",
-        "threshold",
-        "perlin",
-        "step_number",
-        "width",
-        "height",
-        "extra",
-        "seamless",
-        "hires_fix",
-    ]
-
-    rfc_dict = {}
-
-    for item in parameters.items():
-        key, value = item
-        if key in rfc266_img_fields:
-            rfc_dict[key] = value
-
-    postprocessing = []
-
-    # 'postprocessing' is either null or an
-    if "facetool_strength" in parameters:
-
-        postprocessing.append(
-            {"type": "gfpgan", "strength": float(parameters["facetool_strength"])}
-        )
-
-    if "upscale" in parameters:
-        postprocessing.append(
-            {
-                "type": "esrgan",
-                "scale": int(parameters["upscale"][0]),
-                "strength": float(parameters["upscale"][1]),
-            }
-        )
-
-    rfc_dict["postprocessing"] = postprocessing if len(postprocessing) > 0 else None
-
-    # semantic drift
-    rfc_dict["sampler"] = parameters["sampler_name"]
-
-    # display weighted subprompts (liable to change)
-    subprompts = split_weighted_subprompts(parameters["prompt"])
-    subprompts = [{"prompt": x[0], "weight": x[1]} for x in subprompts]
-    rfc_dict["prompt"] = subprompts
-
-    # 'variations' should always exist and be an array, empty or consisting of {'seed': seed, 'weight': weight} pairs
-    variations = []
-
-    if "with_variations" in parameters:
-        variations = [
-            {"seed": x[0], "weight": x[1]} for x in parameters["with_variations"]
-        ]
-
-    rfc_dict["variations"] = variations
-
-    if "init_img" in parameters:
-        rfc_dict["type"] = "img2img"
-        rfc_dict["strength"] = parameters["strength"]
-        rfc_dict["fit"] = parameters["fit"]  # TODO: Noncompliant
-        rfc_dict["orig_hash"] = calculate_init_img_hash(parameters["init_img"])
-        rfc_dict["init_image_path"] = parameters["init_img"]  # TODO: Noncompliant
-        rfc_dict["sampler"] = "ddim"  # TODO: FIX ME WHEN IMG2IMG SUPPORTS ALL SAMPLERS
-        if "init_mask" in parameters:
-            rfc_dict["mask_hash"] = calculate_init_img_hash(
-                parameters["init_mask"]
-            )  # TODO: Noncompliant
-            rfc_dict["mask_image_path"] = parameters["init_mask"]  # TODO: Noncompliant
-    else:
-        rfc_dict["type"] = "txt2img"
-
-    metadata["image"] = rfc_dict
-
-    return metadata
-
-
-def make_unique_init_image_filename(name):
-    uuid = uuid4().hex
-    split = os.path.splitext(name)
-    name = f"{split[0]}.{uuid}{split[1]}"
-    return name
-
-
-def write_log_message(message, log_path=log_path):
-    """Logs the filename and parameters used to generate or process that image to log file"""
-    message = f"{message}\n"
-    with open(log_path, "a", encoding="utf-8") as file:
-        file.writelines(message)
-
-
-def save_image(
-    image, command, metadata, output_dir, step_index=None, postprocessing=False
-):
-    pngwriter = PngWriter(output_dir)
-    prefix = pngwriter.unique_prefix()
-
-    seed = "unknown_seed"
-
-    if "image" in metadata:
-        if "seed" in metadata["image"]:
-            seed = metadata["image"]["seed"]
-
-    filename = f"{prefix}.{seed}"
-
-    if step_index:
-        filename += f".{step_index}"
-    if postprocessing:
-        filename += f".postprocessed"
-
-    filename += ".png"
-
-    path = pngwriter.save_image_and_prompt_to_png(
-        image=image, dream_prompt=command, metadata=metadata, name=filename
-    )
-
-    return path
-
-
-def calculate_real_steps(steps, strength, has_init_image):
-    return math.floor(strength * steps) if has_init_image else steps
-
-
-def generate_images(generation_parameters, esrgan_parameters, gfpgan_parameters):
-    canceled.clear()
-
-    step_index = 1
-    prior_variations = (
-        generation_parameters["with_variations"]
-        if "with_variations" in generation_parameters
-        else []
-    )
-    """
-    If a result image is used as an init image, and then deleted, we will want to be
-    able to use it as an init image in the future. Need to copy it.
-
-    If the init/mask image doesn't exist in the init_image_path/mask_image_path,
-    make a unique filename for it and copy it there.
-    """
-    if "init_img" in generation_parameters:
-        filename = os.path.basename(generation_parameters["init_img"])
-        if not os.path.exists(os.path.join(init_image_path, filename)):
-            unique_filename = make_unique_init_image_filename(filename)
-            new_path = os.path.join(init_image_path, unique_filename)
-            shutil.copy(generation_parameters["init_img"], new_path)
-            generation_parameters["init_img"] = new_path
-        if "init_mask" in generation_parameters:
-            filename = os.path.basename(generation_parameters["init_mask"])
-            if not os.path.exists(os.path.join(mask_image_path, filename)):
-                unique_filename = make_unique_init_image_filename(filename)
-                new_path = os.path.join(init_image_path, unique_filename)
-                shutil.copy(generation_parameters["init_img"], new_path)
-                generation_parameters["init_mask"] = new_path
-
-    totalSteps = calculate_real_steps(
-        steps=generation_parameters["steps"],
-        strength=generation_parameters["strength"]
-        if "strength" in generation_parameters
-        else None,
-        has_init_image="init_img" in generation_parameters,
-    )
-
-    progress = {
-        "currentStep": 1,
-        "totalSteps": totalSteps,
-        "currentIteration": 1,
-        "totalIterations": generation_parameters["iterations"],
-        "currentStatus": "Preparing",
-        "isProcessing": True,
-        "currentStatusHasSteps": False,
-    }
-
-    socketio.emit("progressUpdate", progress)
-    eventlet.sleep(0)
-
-    def image_progress(sample, step):
-        if canceled.is_set():
-            raise CanceledException
-
-        nonlocal step_index
-        nonlocal generation_parameters
-        nonlocal progress
-
-        progress["currentStep"] = step + 1
-        progress["currentStatus"] = "Generating"
-        progress["currentStatusHasSteps"] = True
-
-        if (
-            generation_parameters["progress_images"]
-            and step % 5 == 0
-            and step < generation_parameters["steps"] - 1
-        ):
-            image = generate.sample_to_image(sample)
-
-            metadata = parameters_to_generated_image_metadata(generation_parameters)
-            command = parameters_to_command(generation_parameters)
-            path = save_image(image, command, metadata, intermediate_path, step_index=step_index, postprocessing=False)
-
-            step_index += 1
-            socketio.emit(
-                "intermediateResult",
-                {
-                    "url": os.path.relpath(path),
-                    "mtime": os.path.getmtime(path),
-                    "metadata": metadata,
-                },
-            )
-        socketio.emit("progressUpdate", progress)
-        eventlet.sleep(0)
-
-    def image_done(image, seed, first_seed):
-        nonlocal generation_parameters
-        nonlocal esrgan_parameters
-        nonlocal gfpgan_parameters
-        nonlocal progress
-
-        step_index = 1
-        nonlocal prior_variations
-
-        progress["currentStatus"] = "Generation complete"
-        socketio.emit("progressUpdate", progress)
-        eventlet.sleep(0)
-
-        all_parameters = generation_parameters
-        postprocessing = False
-
-        if (
-            "variation_amount" in all_parameters
-            and all_parameters["variation_amount"] > 0
-        ):
-            first_seed = first_seed or seed
-            this_variation = [[seed, all_parameters["variation_amount"]]]
-            all_parameters["with_variations"] = prior_variations + this_variation
-            all_parameters["seed"] = first_seed
-        elif ("with_variations" in all_parameters):
-            all_parameters["seed"] = first_seed
-        else:
-            all_parameters["seed"] = seed
-
-        if esrgan_parameters:
-            progress["currentStatus"] = "Upscaling"
-            progress["currentStatusHasSteps"] = False
-            socketio.emit("progressUpdate", progress)
-            eventlet.sleep(0)
-
-            image = esrgan.process(
-                image=image,
-                upsampler_scale=esrgan_parameters["level"],
-                strength=esrgan_parameters["strength"],
-                seed=seed,
-            )
-
-            postprocessing = True
-            all_parameters["upscale"] = [
-                esrgan_parameters["level"],
-                esrgan_parameters["strength"],
-            ]
-
-        if gfpgan_parameters:
-            progress["currentStatus"] = "Fixing faces"
-            progress["currentStatusHasSteps"] = False
-            socketio.emit("progressUpdate", progress)
-            eventlet.sleep(0)
-
-            image = gfpgan.process(
-                image=image, strength=gfpgan_parameters["strength"], seed=seed
-            )
-            postprocessing = True
-            all_parameters["facetool_strength"] = gfpgan_parameters["strength"]
-
-        progress["currentStatus"] = "Saving image"
-        socketio.emit("progressUpdate", progress)
-        eventlet.sleep(0)
-
-        metadata = parameters_to_generated_image_metadata(all_parameters)
-        command = parameters_to_command(all_parameters)
-
-        path = save_image(
-            image, command, metadata, result_path, postprocessing=postprocessing
-        )
-
-        print(f'>> Image generated: "{path}"')
-        write_log_message(f'[Generated] "{path}": {command}')
-
-        if progress["totalIterations"] > progress["currentIteration"]:
-            progress["currentStep"] = 1
-            progress["currentIteration"] += 1
-            progress["currentStatus"] = "Iteration finished"
-            progress["currentStatusHasSteps"] = False
-        else:
-            progress["currentStep"] = 0
-            progress["totalSteps"] = 0
-            progress["currentIteration"] = 0
-            progress["totalIterations"] = 0
-            progress["currentStatus"] = "Finished"
-            progress["isProcessing"] = False
-
-        socketio.emit("progressUpdate", progress)
-        eventlet.sleep(0)
-
-        socketio.emit(
-            "generationResult",
-            {
-                "url": os.path.relpath(path),
-                "mtime": os.path.getmtime(path),
-                "metadata": metadata,
-            },
-        )
-        eventlet.sleep(0)
-
-    try:
-        generate.prompt2image(
-            **generation_parameters,
-            step_callback=image_progress,
-            image_callback=image_done,
-        )
-
-    except KeyboardInterrupt:
-        raise
-    except CanceledException:
-        pass
-    except Exception as e:
-        socketio.emit("error", {"message": (str(e))})
-        print("\n")
-        traceback.print_exc()
-        print("\n")
-
-
-"""
-END ADDITIONAL FUNCTIONS
-"""
-
-
-if __name__ == "__main__":
-    print(f">> Starting server at http://{host}:{port}")
-    socketio.run(app, host=host, port=port)

configs/INITIAL_MODELS.yaml

@@ -0,0 +1,80 @@
+stable-diffusion-1.5:
+   description: The newest Stable Diffusion version 1.5 weight file (4.27 GB)
+   repo_id: runwayml/stable-diffusion-v1-5
+   config: v1-inference.yaml
+   file: v1-5-pruned-emaonly.ckpt
+   recommended: true
+   width: 512
+   height: 512
+inpainting-1.5:
+   description: RunwayML SD 1.5 model optimized for inpainting (4.27 GB)
+   repo_id: runwayml/stable-diffusion-inpainting
+   config: v1-inpainting-inference.yaml
+   file: sd-v1-5-inpainting.ckpt
+   recommended: True
+   width: 512
+   height: 512
+ft-mse-improved-autoencoder-840000:
+   description: StabilityAI improved autoencoder fine-tuned for human faces (recommended; 335 MB)
+   repo_id: stabilityai/sd-vae-ft-mse-original
+   config: VAE/default
+   file: vae-ft-mse-840000-ema-pruned.ckpt
+   recommended: True
+   width: 512
+   height: 512
+stable-diffusion-1.4:
+   description: The original Stable Diffusion version 1.4 weight file (4.27 GB)
+   repo_id: CompVis/stable-diffusion-v-1-4-original
+   config: v1-inference.yaml
+   file: sd-v1-4.ckpt
+   recommended: False
+   width: 512
+   height: 512
+waifu-diffusion-1.3:
+   description: Stable Diffusion 1.4 fine tuned on anime-styled images (4.27)
+   repo_id: hakurei/waifu-diffusion-v1-3
+   config: v1-inference.yaml
+   file: model-epoch09-float32.ckpt
+   recommended: False
+   width: 512
+   height: 512
+trinart-2.0:
+   description: An SD model finetuned with ~40,000 assorted high resolution manga/anime-style pictures (2.13 GB)
+   repo_id: naclbit/trinart_stable_diffusion_v2
+   config: v1-inference.yaml
+   file: trinart2_step95000.ckpt
+   recommended: False
+   width: 512
+   height: 512
+trinart_characters-1.0:
+   description: An SD model finetuned with 19.2M anime/manga style images (2.13 GB)
+   repo_id: naclbit/trinart_characters_19.2m_stable_diffusion_v1
+   config: v1-inference.yaml
+   file: trinart_characters_it4_v1.ckpt
+   recommended: False
+   width: 512
+   height: 512
+trinart_vae:
+   description: Custom autoencoder for trinart_characters
+   repo_id: naclbit/trinart_characters_19.2m_stable_diffusion_v1
+   config: VAE/trinart
+   file: autoencoder_fix_kl-f8-trinart_characters.ckpt
+   recommended: False
+   width: 512
+   height: 512
+papercut-1.0:
+   description: SD 1.5 fine-tuned for papercut art (use "PaperCut" in your prompts) (2.13 GB)
+   repo_id: Fictiverse/Stable_Diffusion_PaperCut_Model
+   config: v1-inference.yaml
+   file: PaperCut_v1.ckpt
+   recommended: False
+   width: 512
+   height: 512
+voxel_art-1.0:
+   description: Stable Diffusion trained on voxel art (use "VoxelArt" in your prompts) (4.27 GB)
+   repo_id: Fictiverse/Stable_Diffusion_VoxelArt_Model
+   config: v1-inference.yaml
+   file: VoxelArt_v1.ckpt
+   recommended: False
+   width: 512
+   height: 512

configs/autoencoder/autoencoder_kl_16x16x16.yaml

@@ -1,54 +0,0 @@
-model:
-  base_learning_rate: 4.5e-6
-  target: ldm.models.autoencoder.AutoencoderKL
-  params:
-    monitor: "val/rec_loss"
-    embed_dim: 16
-    lossconfig:
-      target: ldm.modules.losses.LPIPSWithDiscriminator
-      params:
-        disc_start: 50001
-        kl_weight: 0.000001
-        disc_weight: 0.5
-
-    ddconfig:
-      double_z: True
-      z_channels: 16
-      resolution: 256
-      in_channels: 3
-      out_ch: 3
-      ch: 128
-      ch_mult: [ 1,1,2,2,4]  # num_down = len(ch_mult)-1
-      num_res_blocks: 2
-      attn_resolutions: [16]
-      dropout: 0.0
-
-
-data:
-  target: main.DataModuleFromConfig
-  params:
-    batch_size: 12
-    wrap: True
-    train:
-      target: ldm.data.imagenet.ImageNetSRTrain
-      params:
-        size: 256
-        degradation: pil_nearest
-    validation:
-      target: ldm.data.imagenet.ImageNetSRValidation
-      params:
-        size: 256
-        degradation: pil_nearest
-
-lightning:
-  callbacks:
-    image_logger:
-      target: main.ImageLogger
-      params:
-        batch_frequency: 1000
-        max_images: 8
-        increase_log_steps: True
-
-  trainer:
-    benchmark: True
-    accumulate_grad_batches: 2

configs/autoencoder/autoencoder_kl_32x32x4.yaml

@@ -1,53 +0,0 @@
-model:
-  base_learning_rate: 4.5e-6
-  target: ldm.models.autoencoder.AutoencoderKL
-  params:
-    monitor: "val/rec_loss"
-    embed_dim: 4
-    lossconfig:
-      target: ldm.modules.losses.LPIPSWithDiscriminator
-      params:
-        disc_start: 50001
-        kl_weight: 0.000001
-        disc_weight: 0.5
-
-    ddconfig:
-      double_z: True
-      z_channels: 4
-      resolution: 256
-      in_channels: 3
-      out_ch: 3
-      ch: 128
-      ch_mult: [ 1,2,4,4 ]  # num_down = len(ch_mult)-1
-      num_res_blocks: 2
-      attn_resolutions: [ ]
-      dropout: 0.0
-
-data:
-  target: main.DataModuleFromConfig
-  params:
-    batch_size: 12
-    wrap: True
-    train:
-      target: ldm.data.imagenet.ImageNetSRTrain
-      params:
-        size: 256
-        degradation: pil_nearest
-    validation:
-      target: ldm.data.imagenet.ImageNetSRValidation
-      params:
-        size: 256
-        degradation: pil_nearest
-
-lightning:
-  callbacks:
-    image_logger:
-      target: main.ImageLogger
-      params:
-        batch_frequency: 1000
-        max_images: 8
-        increase_log_steps: True
-
-  trainer:
-    benchmark: True
-    accumulate_grad_batches: 2

configs/autoencoder/autoencoder_kl_64x64x3.yaml

@@ -1,54 +0,0 @@
-model:
-  base_learning_rate: 4.5e-6
-  target: ldm.models.autoencoder.AutoencoderKL
-  params:
-    monitor: "val/rec_loss"
-    embed_dim: 3
-    lossconfig:
-      target: ldm.modules.losses.LPIPSWithDiscriminator
-      params:
-        disc_start: 50001
-        kl_weight: 0.000001
-        disc_weight: 0.5
-
-    ddconfig:
-      double_z: True
-      z_channels: 3
-      resolution: 256
-      in_channels: 3
-      out_ch: 3
-      ch: 128
-      ch_mult: [ 1,2,4 ]  # num_down = len(ch_mult)-1
-      num_res_blocks: 2
-      attn_resolutions: [ ]
-      dropout: 0.0
-
-
-data:
-  target: main.DataModuleFromConfig
-  params:
-    batch_size: 12
-    wrap: True
-    train:
-      target: ldm.data.imagenet.ImageNetSRTrain
-      params:
-        size: 256
-        degradation: pil_nearest
-    validation:
-      target: ldm.data.imagenet.ImageNetSRValidation
-      params:
-        size: 256
-        degradation: pil_nearest
-
-lightning:
-  callbacks:
-    image_logger:
-      target: main.ImageLogger
-      params:
-        batch_frequency: 1000
-        max_images: 8
-        increase_log_steps: True
-
-  trainer:
-    benchmark: True
-    accumulate_grad_batches: 2

configs/autoencoder/autoencoder_kl_8x8x64.yaml

@@ -1,53 +0,0 @@
-model:
-  base_learning_rate: 4.5e-6
-  target: ldm.models.autoencoder.AutoencoderKL
-  params:
-    monitor: "val/rec_loss"
-    embed_dim: 64
-    lossconfig:
-      target: ldm.modules.losses.LPIPSWithDiscriminator
-      params:
-        disc_start: 50001
-        kl_weight: 0.000001
-        disc_weight: 0.5
-
-    ddconfig:
-      double_z: True
-      z_channels: 64
-      resolution: 256
-      in_channels: 3
-      out_ch: 3
-      ch: 128
-      ch_mult: [ 1,1,2,2,4,4]  # num_down = len(ch_mult)-1
-      num_res_blocks: 2
-      attn_resolutions: [16,8]
-      dropout: 0.0
-
-data:
-  target: main.DataModuleFromConfig
-  params:
-    batch_size: 12
-    wrap: True
-    train:
-      target: ldm.data.imagenet.ImageNetSRTrain
-      params:
-        size: 256
-        degradation: pil_nearest
-    validation:
-      target: ldm.data.imagenet.ImageNetSRValidation
-      params:
-        size: 256
-        degradation: pil_nearest
-
-lightning:
-  callbacks:
-    image_logger:
-      target: main.ImageLogger
-      params:
-        batch_frequency: 1000
-        max_images: 8
-        increase_log_steps: True
-
-  trainer:
-    benchmark: True
-    accumulate_grad_batches: 2

configs/latent-diffusion/celebahq-ldm-vq-4.yaml

@@ -1,86 +0,0 @@
-model:
-  base_learning_rate: 2.0e-06
-  target: ldm.models.diffusion.ddpm.LatentDiffusion
-  params:
-    linear_start: 0.0015
-    linear_end: 0.0195
-    num_timesteps_cond: 1
-    log_every_t: 200
-    timesteps: 1000
-    first_stage_key: image
-    image_size: 64
-    channels: 3
-    monitor: val/loss_simple_ema
-
-    unet_config:
-      target: ldm.modules.diffusionmodules.openaimodel.UNetModel
-      params:
-        image_size: 64
-        in_channels: 3
-        out_channels: 3
-        model_channels: 224
-        attention_resolutions:
-        # note: this isn\t actually the resolution but
-        # the downsampling factor, i.e. this corresnponds to
-        # attention on spatial resolution 8,16,32, as the
-        # spatial reolution of the latents is 64 for f4
-        - 8
-        - 4
-        - 2
-        num_res_blocks: 2
-        channel_mult:
-        - 1
-        - 2
-        - 3
-        - 4
-        num_head_channels: 32
-    first_stage_config:
-      target: ldm.models.autoencoder.VQModelInterface
-      params:
-        embed_dim: 3
-        n_embed: 8192
-        ckpt_path: models/first_stage_models/vq-f4/model.ckpt
-        ddconfig:
-          double_z: false
-          z_channels: 3
-          resolution: 256
-          in_channels: 3
-          out_ch: 3
-          ch: 128
-          ch_mult:
-          - 1
-          - 2
-          - 4
-          num_res_blocks: 2
-          attn_resolutions: []
-          dropout: 0.0
-        lossconfig:
-          target: torch.nn.Identity
-    cond_stage_config: __is_unconditional__
-data:
-  target: main.DataModuleFromConfig
-  params:
-    batch_size: 48
-    num_workers: 5
-    wrap: false
-    train:
-      target: taming.data.faceshq.CelebAHQTrain
-      params:
-        size: 256
-    validation:
-      target: taming.data.faceshq.CelebAHQValidation
-      params:
-        size: 256
-
-
-lightning:
-  callbacks:
-    image_logger:
-      target: main.ImageLogger
-      params:
-        batch_frequency: 5000
-        max_images: 8
-        increase_log_steps: False
-
-  trainer:
-    benchmark: True

configs/latent-diffusion/cin-ldm-vq-f8.yaml

@@ -1,98 +0,0 @@
-model:
-  base_learning_rate: 1.0e-06
-  target: ldm.models.diffusion.ddpm.LatentDiffusion
-  params:
-    linear_start: 0.0015
-    linear_end: 0.0195
-    num_timesteps_cond: 1
-    log_every_t: 200
-    timesteps: 1000
-    first_stage_key: image
-    cond_stage_key: class_label
-    image_size: 32
-    channels: 4
-    cond_stage_trainable: true
-    conditioning_key: crossattn
-    monitor: val/loss_simple_ema
-    unet_config:
-      target: ldm.modules.diffusionmodules.openaimodel.UNetModel
-      params:
-        image_size: 32
-        in_channels: 4
-        out_channels: 4
-        model_channels: 256
-        attention_resolutions:
-        #note: this isn\t actually the resolution but
-        # the downsampling factor, i.e. this corresnponds to
-        # attention on spatial resolution 8,16,32, as the
-        # spatial reolution of the latents is 32 for f8
-        - 4
-        - 2
-        - 1
-        num_res_blocks: 2
-        channel_mult:
-        - 1
-        - 2
-        - 4
-        num_head_channels: 32
-        use_spatial_transformer: true
-        transformer_depth: 1
-        context_dim: 512
-    first_stage_config:
-      target: ldm.models.autoencoder.VQModelInterface
-      params:
-        embed_dim: 4
-        n_embed: 16384
-        ckpt_path: configs/first_stage_models/vq-f8/model.yaml
-        ddconfig:
-          double_z: false
-          z_channels: 4
-          resolution: 256
-          in_channels: 3
-          out_ch: 3
-          ch: 128
-          ch_mult:
-          - 1
-          - 2
-          - 2
-          - 4
-          num_res_blocks: 2
-          attn_resolutions:
-          - 32
-          dropout: 0.0
-        lossconfig:
-          target: torch.nn.Identity
-    cond_stage_config:
-      target: ldm.modules.encoders.modules.ClassEmbedder
-      params:
-        embed_dim: 512
-        key: class_label
-data:
-  target: main.DataModuleFromConfig
-  params:
-    batch_size: 64
-    num_workers: 12
-    wrap: false
-    train:
-      target: ldm.data.imagenet.ImageNetTrain
-      params:
-        config:
-          size: 256
-    validation:
-      target: ldm.data.imagenet.ImageNetValidation
-      params:
-        config:
-          size: 256
-
-
-lightning:
-  callbacks:
-    image_logger:
-      target: main.ImageLogger
-      params:
-        batch_frequency: 5000
-        max_images: 8
-        increase_log_steps: False
-
-  trainer:
-    benchmark: True

configs/latent-diffusion/cin256-v2.yaml

@@ -1,68 +0,0 @@
-model:
-  base_learning_rate: 0.0001
-  target: ldm.models.diffusion.ddpm.LatentDiffusion
-  params:
-    linear_start: 0.0015
-    linear_end: 0.0195
-    num_timesteps_cond: 1
-    log_every_t: 200
-    timesteps: 1000
-    first_stage_key: image
-    cond_stage_key: class_label
-    image_size: 64
-    channels: 3
-    cond_stage_trainable: true
-    conditioning_key: crossattn
-    monitor: val/loss
-    use_ema: False
-    
-    unet_config:
-      target: ldm.modules.diffusionmodules.openaimodel.UNetModel
-      params:
-        image_size: 64
-        in_channels: 3
-        out_channels: 3
-        model_channels: 192
-        attention_resolutions:
-        - 8
-        - 4
-        - 2
-        num_res_blocks: 2
-        channel_mult:
-        - 1
-        - 2
-        - 3
-        - 5
-        num_heads: 1
-        use_spatial_transformer: true
-        transformer_depth: 1
-        context_dim: 512
-    
-    first_stage_config:
-      target: ldm.models.autoencoder.VQModelInterface
-      params:
-        embed_dim: 3
-        n_embed: 8192
-        ddconfig:
-          double_z: false
-          z_channels: 3
-          resolution: 256
-          in_channels: 3
-          out_ch: 3
-          ch: 128
-          ch_mult:
-          - 1
-          - 2
-          - 4
-          num_res_blocks: 2
-          attn_resolutions: []
-          dropout: 0.0
-        lossconfig:
-          target: torch.nn.Identity
-    
-    cond_stage_config:
-      target: ldm.modules.encoders.modules.ClassEmbedder
-      params:
-        n_classes: 1001
-        embed_dim: 512
-        key: class_label

configs/latent-diffusion/ffhq-ldm-vq-4.yaml

@@ -1,85 +0,0 @@
-model:
-  base_learning_rate: 2.0e-06
-  target: ldm.models.diffusion.ddpm.LatentDiffusion
-  params:
-    linear_start: 0.0015
-    linear_end: 0.0195
-    num_timesteps_cond: 1
-    log_every_t: 200
-    timesteps: 1000
-    first_stage_key: image
-    image_size: 64
-    channels: 3
-    monitor: val/loss_simple_ema
-    unet_config:
-      target: ldm.modules.diffusionmodules.openaimodel.UNetModel
-      params:
-        image_size: 64
-        in_channels: 3
-        out_channels: 3
-        model_channels: 224
-        attention_resolutions:
-        # note: this isn\t actually the resolution but
-        # the downsampling factor, i.e. this corresnponds to
-        # attention on spatial resolution 8,16,32, as the
-        # spatial reolution of the latents is 64 for f4
-        - 8
-        - 4
-        - 2
-        num_res_blocks: 2
-        channel_mult:
-        - 1
-        - 2
-        - 3
-        - 4
-        num_head_channels: 32
-    first_stage_config:
-      target: ldm.models.autoencoder.VQModelInterface
-      params:
-        embed_dim: 3
-        n_embed: 8192
-        ckpt_path: configs/first_stage_models/vq-f4/model.yaml
-        ddconfig:
-          double_z: false
-          z_channels: 3
-          resolution: 256
-          in_channels: 3
-          out_ch: 3
-          ch: 128
-          ch_mult:
-          - 1
-          - 2
-          - 4
-          num_res_blocks: 2
-          attn_resolutions: []
-          dropout: 0.0
-        lossconfig:
-          target: torch.nn.Identity
-    cond_stage_config: __is_unconditional__
-data:
-  target: main.DataModuleFromConfig
-  params:
-    batch_size: 42
-    num_workers: 5
-    wrap: false
-    train:
-      target: taming.data.faceshq.FFHQTrain
-      params:
-        size: 256
-    validation:
-      target: taming.data.faceshq.FFHQValidation
-      params:
-        size: 256
-
-
-lightning:
-  callbacks:
-    image_logger:
-      target: main.ImageLogger
-      params:
-        batch_frequency: 5000
-        max_images: 8
-        increase_log_steps: False
-
-  trainer:
-    benchmark: True

configs/latent-diffusion/lsun_bedrooms-ldm-vq-4.yaml

@@ -1,85 +0,0 @@
-model:
-  base_learning_rate: 2.0e-06
-  target: ldm.models.diffusion.ddpm.LatentDiffusion
-  params:
-    linear_start: 0.0015
-    linear_end: 0.0195
-    num_timesteps_cond: 1
-    log_every_t: 200
-    timesteps: 1000
-    first_stage_key: image
-    image_size: 64
-    channels: 3
-    monitor: val/loss_simple_ema
-    unet_config:
-      target: ldm.modules.diffusionmodules.openaimodel.UNetModel
-      params:
-        image_size: 64
-        in_channels: 3
-        out_channels: 3
-        model_channels: 224
-        attention_resolutions:
-        # note: this isn\t actually the resolution but
-        # the downsampling factor, i.e. this corresnponds to
-        # attention on spatial resolution 8,16,32, as the
-        # spatial reolution of the latents is 64 for f4
-        - 8
-        - 4
-        - 2
-        num_res_blocks: 2
-        channel_mult:
-        - 1
-        - 2
-        - 3
-        - 4
-        num_head_channels: 32
-    first_stage_config:
-      target: ldm.models.autoencoder.VQModelInterface
-      params:
-        ckpt_path: configs/first_stage_models/vq-f4/model.yaml
-        embed_dim: 3
-        n_embed: 8192
-        ddconfig:
-          double_z: false
-          z_channels: 3
-          resolution: 256
-          in_channels: 3
-          out_ch: 3
-          ch: 128
-          ch_mult:
-          - 1
-          - 2
-          - 4
-          num_res_blocks: 2
-          attn_resolutions: []
-          dropout: 0.0
-        lossconfig:
-          target: torch.nn.Identity
-    cond_stage_config: __is_unconditional__
-data:
-  target: main.DataModuleFromConfig
-  params:
-    batch_size: 48
-    num_workers: 5
-    wrap: false
-    train:
-      target: ldm.data.lsun.LSUNBedroomsTrain
-      params:
-        size: 256
-    validation:
-      target: ldm.data.lsun.LSUNBedroomsValidation
-      params:
-        size: 256
-
-
-lightning:
-  callbacks:
-    image_logger:
-      target: main.ImageLogger
-      params:
-        batch_frequency: 5000
-        max_images: 8
-        increase_log_steps: False
-
-  trainer:
-    benchmark: True

configs/latent-diffusion/lsun_churches-ldm-kl-8.yaml

@@ -1,91 +0,0 @@
-model:
-  base_learning_rate: 5.0e-5   # set to target_lr by starting main.py with '--scale_lr False'
-  target: ldm.models.diffusion.ddpm.LatentDiffusion
-  params:
-    linear_start: 0.0015
-    linear_end: 0.0155
-    num_timesteps_cond: 1
-    log_every_t: 200
-    timesteps: 1000
-    loss_type: l1
-    first_stage_key: "image"
-    cond_stage_key: "image"
-    image_size: 32
-    channels: 4
-    cond_stage_trainable: False
-    concat_mode: False
-    scale_by_std: True
-    monitor: 'val/loss_simple_ema'
-
-    scheduler_config: # 10000 warmup steps
-      target: ldm.lr_scheduler.LambdaLinearScheduler
-      params:
-        warm_up_steps: [10000]
-        cycle_lengths: [10000000000000]
-        f_start: [1.e-6]
-        f_max: [1.]
-        f_min: [ 1.]
-
-    unet_config:
-      target: ldm.modules.diffusionmodules.openaimodel.UNetModel
-      params:
-        image_size: 32
-        in_channels: 4
-        out_channels: 4
-        model_channels: 192
-        attention_resolutions: [ 1, 2, 4, 8 ]   # 32, 16, 8, 4
-        num_res_blocks: 2
-        channel_mult: [ 1,2,2,4,4 ]  # 32, 16, 8, 4, 2
-        num_heads: 8
-        use_scale_shift_norm: True
-        resblock_updown: True
-
-    first_stage_config:
-      target: ldm.models.autoencoder.AutoencoderKL
-      params:
-        embed_dim: 4
-        monitor: "val/rec_loss"
-        ckpt_path: "models/first_stage_models/kl-f8/model.ckpt"
-        ddconfig:
-          double_z: True
-          z_channels: 4
-          resolution: 256
-          in_channels: 3
-          out_ch: 3
-          ch: 128
-          ch_mult: [ 1,2,4,4 ]  # num_down = len(ch_mult)-1
-          num_res_blocks: 2
-          attn_resolutions: [ ]
-          dropout: 0.0
-        lossconfig:
-          target: torch.nn.Identity
-
-    cond_stage_config: "__is_unconditional__"
-
-data:
-  target: main.DataModuleFromConfig
-  params:
-    batch_size: 96
-    num_workers: 5
-    wrap: False
-    train:
-      target: ldm.data.lsun.LSUNChurchesTrain
-      params:
-        size: 256
-    validation:
-      target: ldm.data.lsun.LSUNChurchesValidation
-      params:
-        size: 256
-
-lightning:
-  callbacks:
-    image_logger:
-      target: main.ImageLogger
-      params:
-        batch_frequency: 5000
-        max_images: 8
-        increase_log_steps: False
-
-
-  trainer:
-    benchmark: True

configs/latent-diffusion/txt2img-1p4B-eval.yaml

@@ -1,71 +0,0 @@
-model:
-  base_learning_rate: 5.0e-05
-  target: ldm.models.diffusion.ddpm.LatentDiffusion
-  params:
-    linear_start: 0.00085
-    linear_end: 0.012
-    num_timesteps_cond: 1
-    log_every_t: 200
-    timesteps: 1000
-    first_stage_key: image
-    cond_stage_key: caption
-    image_size: 32
-    channels: 4
-    cond_stage_trainable: true
-    conditioning_key: crossattn
-    monitor: val/loss_simple_ema
-    scale_factor: 0.18215
-    use_ema: False
-
-    unet_config:
-      target: ldm.modules.diffusionmodules.openaimodel.UNetModel
-      params:
-        image_size: 32
-        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: 1280
-        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.BERTEmbedder
-      params:
-        n_embed: 1280
-        n_layer: 32

configs/models.yaml

@@ -1,20 +0,0 @@
-# This file describes the alternative machine learning models
-#  available to the dream 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.
-
-laion400m:
-    config:  configs/latent-diffusion/txt2img-1p4B-eval.yaml
-    weights: models/ldm/text2img-large/model.ckpt
-    description: Latent Diffusion LAION400M model
-    width: 256
-    height: 256
-stable-diffusion-1.4:
-    config:  configs/stable-diffusion/v1-inference.yaml
-    weights: models/ldm/stable-diffusion-v1/model.ckpt
-    description: Stable Diffusion inference model version 1.4
-    width: 512
-    height: 512

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/retrieval-augmented-diffusion/768x768.yaml

@@ -1,68 +0,0 @@
-model:
-  base_learning_rate: 0.0001
-  target: ldm.models.diffusion.ddpm.LatentDiffusion
-  params:
-    linear_start: 0.0015
-    linear_end: 0.015
-    num_timesteps_cond: 1
-    log_every_t: 200
-    timesteps: 1000
-    first_stage_key: jpg
-    cond_stage_key: nix
-    image_size: 48
-    channels: 16
-    cond_stage_trainable: false
-    conditioning_key: crossattn
-    monitor: val/loss_simple_ema
-    scale_by_std: false
-    scale_factor: 0.22765929
-    unet_config:
-      target: ldm.modules.diffusionmodules.openaimodel.UNetModel
-      params:
-        image_size: 48
-        in_channels: 16
-        out_channels: 16
-        model_channels: 448
-        attention_resolutions:
-        - 4
-        - 2
-        - 1
-        num_res_blocks: 2
-        channel_mult:
-        - 1
-        - 2
-        - 3
-        - 4
-        use_scale_shift_norm: false
-        resblock_updown: false
-        num_head_channels: 32
-        use_spatial_transformer: true
-        transformer_depth: 1
-        context_dim: 768
-        use_checkpoint: true
-    first_stage_config:
-      target: ldm.models.autoencoder.AutoencoderKL
-      params:
-        monitor: val/rec_loss
-        embed_dim: 16
-        ddconfig:
-          double_z: true
-          z_channels: 16
-          resolution: 256
-          in_channels: 3
-          out_ch: 3
-          ch: 128
-          ch_mult:
-          - 1
-          - 1
-          - 2
-          - 2
-          - 4
-          num_res_blocks: 2
-          attn_resolutions:
-          - 16
-          dropout: 0.0
-        lossconfig:
-          target: torch.nn.Identity
-    cond_stage_config:
-      target: torch.nn.Identity

configs/sd-concepts.txt

@@ -0,0 +1,803 @@
+sd-concepts-library/001glitch-core
+sd-concepts-library/2814-roth
+sd-concepts-library/3d-female-cyborgs
+sd-concepts-library/4tnght
+sd-concepts-library/80s-anime-ai
+sd-concepts-library/80s-anime-ai-being
+sd-concepts-library/852style-girl
+sd-concepts-library/8bit
+sd-concepts-library/8sconception
+sd-concepts-library/Aflac-duck
+sd-concepts-library/Akitsuki
+sd-concepts-library/Atako
+sd-concepts-library/Exodus-Styling
+sd-concepts-library/RINGAO
+sd-concepts-library/a-female-hero-from-the-legend-of-mir
+sd-concepts-library/a-hat-kid
+sd-concepts-library/a-tale-of-two-empires
+sd-concepts-library/aadhav-face
+sd-concepts-library/aavegotchi
+sd-concepts-library/abby-face
+sd-concepts-library/abstract-concepts
+sd-concepts-library/accurate-angel
+sd-concepts-library/agm-style-nao
+sd-concepts-library/aj-fosik
+sd-concepts-library/alberto-mielgo
+sd-concepts-library/alex-portugal
+sd-concepts-library/alex-thumbnail-object-2000-steps
+sd-concepts-library/aleyna-tilki
+sd-concepts-library/alf
+sd-concepts-library/alicebeta
+sd-concepts-library/alien-avatar
+sd-concepts-library/alisa
+sd-concepts-library/all-rings-albuns
+sd-concepts-library/altvent
+sd-concepts-library/altyn-helmet
+sd-concepts-library/amine
+sd-concepts-library/amogus
+sd-concepts-library/anders-zorn
+sd-concepts-library/angus-mcbride-style
+sd-concepts-library/animalve3-1500seq
+sd-concepts-library/anime-background-style
+sd-concepts-library/anime-background-style-v2
+sd-concepts-library/anime-boy
+sd-concepts-library/anime-girl
+sd-concepts-library/anyXtronXredshift
+sd-concepts-library/anya-forger
+sd-concepts-library/apex-wingman
+sd-concepts-library/apulian-rooster-v0-1
+sd-concepts-library/arcane-face
+sd-concepts-library/arcane-style-jv
+sd-concepts-library/arcimboldo-style
+sd-concepts-library/armando-reveron-style
+sd-concepts-library/armor-concept
+sd-concepts-library/arq-render
+sd-concepts-library/art-brut
+sd-concepts-library/arthur1
+sd-concepts-library/artist-yukiko-kanagai
+sd-concepts-library/arwijn
+sd-concepts-library/ashiok
+sd-concepts-library/at-wolf-boy-object
+sd-concepts-library/atm-ant
+sd-concepts-library/atm-ant-2
+sd-concepts-library/axe-tattoo
+sd-concepts-library/ayush-spider-spr
+sd-concepts-library/azura-from-vibrant-venture
+sd-concepts-library/ba-shiroko
+sd-concepts-library/babau
+sd-concepts-library/babs-bunny
+sd-concepts-library/babushork
+sd-concepts-library/backrooms
+sd-concepts-library/bad_Hub_Hugh
+sd-concepts-library/bada-club
+sd-concepts-library/baldi
+sd-concepts-library/baluchitherian
+sd-concepts-library/bamse
+sd-concepts-library/bamse-og-kylling
+sd-concepts-library/bee
+sd-concepts-library/beholder
+sd-concepts-library/beldam
+sd-concepts-library/belen
+sd-concepts-library/bella-goth
+sd-concepts-library/belle-delphine
+sd-concepts-library/bert-muppet
+sd-concepts-library/better-collage3
+sd-concepts-library/between2-mt-fade
+sd-concepts-library/birb-style
+sd-concepts-library/black-and-white-design
+sd-concepts-library/black-waifu
+sd-concepts-library/bloo
+sd-concepts-library/blue-haired-boy
+sd-concepts-library/blue-zombie
+sd-concepts-library/blue-zombiee
+sd-concepts-library/bluebey
+sd-concepts-library/bluebey-2
+sd-concepts-library/bobs-burgers
+sd-concepts-library/boissonnard
+sd-concepts-library/bonzi-monkey
+sd-concepts-library/borderlands
+sd-concepts-library/bored-ape-textual-inversion
+sd-concepts-library/boris-anderson
+sd-concepts-library/bozo-22
+sd-concepts-library/breakcore
+sd-concepts-library/brittney-williams-art
+sd-concepts-library/bruma
+sd-concepts-library/brunnya
+sd-concepts-library/buddha-statue
+sd-concepts-library/bullvbear
+sd-concepts-library/button-eyes
+sd-concepts-library/canadian-goose
+sd-concepts-library/canary-cap
+sd-concepts-library/cancer_style
+sd-concepts-library/captain-haddock
+sd-concepts-library/captainkirb
+sd-concepts-library/car-toy-rk
+sd-concepts-library/carasibana
+sd-concepts-library/carlitos-el-mago
+sd-concepts-library/carrascharacter
+sd-concepts-library/cartoona-animals
+sd-concepts-library/cat-toy
+sd-concepts-library/centaur
+sd-concepts-library/cgdonny1
+sd-concepts-library/cham
+sd-concepts-library/chandra-nalaar
+sd-concepts-library/char-con
+sd-concepts-library/character-pingu
+sd-concepts-library/cheburashka
+sd-concepts-library/chen-1
+sd-concepts-library/child-zombie
+sd-concepts-library/chillpill
+sd-concepts-library/chonkfrog
+sd-concepts-library/chop
+sd-concepts-library/christo-person
+sd-concepts-library/chuck-walton
+sd-concepts-library/chucky
+sd-concepts-library/chungus-poodl-pet
+sd-concepts-library/cindlop
+sd-concepts-library/collage-cutouts
+sd-concepts-library/collage14
+sd-concepts-library/collage3
+sd-concepts-library/collage3-hubcity
+sd-concepts-library/cologne
+sd-concepts-library/color-page
+sd-concepts-library/colossus
+sd-concepts-library/command-and-conquer-remastered-cameos
+sd-concepts-library/concept-art
+sd-concepts-library/conner-fawcett-style
+sd-concepts-library/conway-pirate
+sd-concepts-library/coop-himmelblau
+sd-concepts-library/coraline
+sd-concepts-library/cornell-box
+sd-concepts-library/cortana
+sd-concepts-library/covid-19-rapid-test
+sd-concepts-library/cow-uwu
+sd-concepts-library/cowboy
+sd-concepts-library/crazy-1
+sd-concepts-library/crazy-2
+sd-concepts-library/crb-portraits
+sd-concepts-library/crb-surrealz
+sd-concepts-library/crbart
+sd-concepts-library/crested-gecko
+sd-concepts-library/crinos-form-garou
+sd-concepts-library/cry-baby-style
+sd-concepts-library/crybaby-style-2-0
+sd-concepts-library/csgo-awp-object
+sd-concepts-library/csgo-awp-texture-map
+sd-concepts-library/cubex
+sd-concepts-library/cumbia-peruana
+sd-concepts-library/cute-bear
+sd-concepts-library/cute-cat
+sd-concepts-library/cute-game-style
+sd-concepts-library/cyberpunk-lucy
+sd-concepts-library/dabotap
+sd-concepts-library/dan-mumford
+sd-concepts-library/dan-seagrave-art-style
+sd-concepts-library/dark-penguin-pinguinanimations
+sd-concepts-library/darkpenguinanimatronic
+sd-concepts-library/darkplane
+sd-concepts-library/david-firth-artstyle
+sd-concepts-library/david-martinez-cyberpunk
+sd-concepts-library/david-martinez-edgerunners
+sd-concepts-library/david-moreno-architecture
+sd-concepts-library/daycare-attendant-sun-fnaf
+sd-concepts-library/ddattender
+sd-concepts-library/degods
+sd-concepts-library/degodsheavy
+sd-concepts-library/depthmap
+sd-concepts-library/depthmap-style
+sd-concepts-library/design
+sd-concepts-library/detectivedinosaur1
+sd-concepts-library/diaosu-toy
+sd-concepts-library/dicoo
+sd-concepts-library/dicoo2
+sd-concepts-library/dishonored-portrait-styles
+sd-concepts-library/disquieting-muses
+sd-concepts-library/ditko
+sd-concepts-library/dlooak
+sd-concepts-library/doc
+sd-concepts-library/doener-red-line-art
+sd-concepts-library/dog
+sd-concepts-library/dog-django
+sd-concepts-library/doge-pound
+sd-concepts-library/dong-ho
+sd-concepts-library/dong-ho2
+sd-concepts-library/doose-s-realistic-art-style
+sd-concepts-library/dq10-anrushia
+sd-concepts-library/dr-livesey
+sd-concepts-library/dr-strange
+sd-concepts-library/dragonborn
+sd-concepts-library/dreamcore
+sd-concepts-library/dreamy-painting
+sd-concepts-library/drive-scorpion-jacket
+sd-concepts-library/dsmuses
+sd-concepts-library/dtv-pkmn
+sd-concepts-library/dullboy-caricature
+sd-concepts-library/duranduran
+sd-concepts-library/durer-style
+sd-concepts-library/dyoudim-style
+sd-concepts-library/early-mishima-kurone
+sd-concepts-library/eastward
+sd-concepts-library/eddie
+sd-concepts-library/edgerunners-style
+sd-concepts-library/edgerunners-style-v2
+sd-concepts-library/el-salvador-style-style
+sd-concepts-library/elegant-flower
+sd-concepts-library/elspeth-tirel
+sd-concepts-library/eru-chitanda-casual
+sd-concepts-library/erwin-olaf-style
+sd-concepts-library/ettblackteapot
+sd-concepts-library/explosions-cat
+sd-concepts-library/eye-of-agamotto
+sd-concepts-library/f-22
+sd-concepts-library/facadeplace
+sd-concepts-library/fairy-tale-painting-style
+sd-concepts-library/fairytale
+sd-concepts-library/fang-yuan-001
+sd-concepts-library/faraon-love-shady
+sd-concepts-library/fasina
+sd-concepts-library/felps
+sd-concepts-library/female-kpop-singer
+sd-concepts-library/fergal-cat
+sd-concepts-library/filename-2
+sd-concepts-library/fileteado-porteno
+sd-concepts-library/final-fantasy-logo
+sd-concepts-library/fireworks-over-water
+sd-concepts-library/fish
+sd-concepts-library/flag-ussr
+sd-concepts-library/flatic
+sd-concepts-library/floral
+sd-concepts-library/fluid-acrylic-jellyfish-creatures-style-of-carl-ingram-art
+sd-concepts-library/fnf-boyfriend
+sd-concepts-library/fold-structure
+sd-concepts-library/fox-purple
+sd-concepts-library/fractal
+sd-concepts-library/fractal-flame
+sd-concepts-library/fractal-temple-style
+sd-concepts-library/frank-frazetta
+sd-concepts-library/franz-unterberger
+sd-concepts-library/freddy-fazbear
+sd-concepts-library/freefonix-style
+sd-concepts-library/furrpopasthetic
+sd-concepts-library/fursona
+sd-concepts-library/fzk
+sd-concepts-library/galaxy-explorer
+sd-concepts-library/ganyu-genshin-impact
+sd-concepts-library/garcon-the-cat
+sd-concepts-library/garfield-pizza-plush
+sd-concepts-library/garfield-pizza-plush-v2
+sd-concepts-library/gba-fe-class-cards
+sd-concepts-library/gba-pokemon-sprites
+sd-concepts-library/geggin
+sd-concepts-library/ggplot2
+sd-concepts-library/ghost-style
+sd-concepts-library/ghostproject-men
+sd-concepts-library/gibasachan-v0
+sd-concepts-library/gim
+sd-concepts-library/gio
+sd-concepts-library/giygas
+sd-concepts-library/glass-pipe
+sd-concepts-library/glass-prism-cube
+sd-concepts-library/glow-forest
+sd-concepts-library/goku
+sd-concepts-library/gram-tops
+sd-concepts-library/green-blue-shanshui
+sd-concepts-library/green-tent
+sd-concepts-library/grifter
+sd-concepts-library/grisstyle
+sd-concepts-library/grit-toy
+sd-concepts-library/gt-color-paint-2
+sd-concepts-library/gta5-artwork
+sd-concepts-library/guttestreker
+sd-concepts-library/gymnastics-leotard-v2
+sd-concepts-library/half-life-2-dog
+sd-concepts-library/handstand
+sd-concepts-library/hanfu-anime-style
+sd-concepts-library/happy-chaos
+sd-concepts-library/happy-person12345
+sd-concepts-library/happy-person12345-assets
+sd-concepts-library/harley-quinn
+sd-concepts-library/harmless-ai-1
+sd-concepts-library/harmless-ai-house-style-1
+sd-concepts-library/hd-emoji
+sd-concepts-library/heather
+sd-concepts-library/henjo-techno-show
+sd-concepts-library/herge-style
+sd-concepts-library/hiten-style-nao
+sd-concepts-library/hitokomoru-style-nao
+sd-concepts-library/hiyuki-chan
+sd-concepts-library/hk-bamboo
+sd-concepts-library/hk-betweenislands
+sd-concepts-library/hk-bicycle
+sd-concepts-library/hk-blackandwhite
+sd-concepts-library/hk-breakfast
+sd-concepts-library/hk-buses
+sd-concepts-library/hk-clouds
+sd-concepts-library/hk-goldbuddha
+sd-concepts-library/hk-goldenlantern
+sd-concepts-library/hk-hkisland
+sd-concepts-library/hk-leaves
+sd-concepts-library/hk-market
+sd-concepts-library/hk-oldcamera
+sd-concepts-library/hk-opencamera
+sd-concepts-library/hk-peach
+sd-concepts-library/hk-phonevax
+sd-concepts-library/hk-streetpeople
+sd-concepts-library/hk-vintage
+sd-concepts-library/hoi4
+sd-concepts-library/hoi4-leaders
+sd-concepts-library/homestuck-sprite
+sd-concepts-library/homestuck-troll
+sd-concepts-library/hours-sentry-fade
+sd-concepts-library/hours-style
+sd-concepts-library/hrgiger-drmacabre
+sd-concepts-library/huang-guang-jian
+sd-concepts-library/huatli
+sd-concepts-library/huayecai820-greyscale
+sd-concepts-library/hub-city
+sd-concepts-library/hubris-oshri
+sd-concepts-library/huckleberry
+sd-concepts-library/hydrasuit
+sd-concepts-library/i-love-chaos
+sd-concepts-library/ibere-thenorio
+sd-concepts-library/ic0n
+sd-concepts-library/ie-gravestone
+sd-concepts-library/ikea-fabler
+sd-concepts-library/illustration-style
+sd-concepts-library/ilo-kunst
+sd-concepts-library/ilya-shkipin
+sd-concepts-library/im-poppy
+sd-concepts-library/ina-art
+sd-concepts-library/indian-watercolor-portraits
+sd-concepts-library/indiana
+sd-concepts-library/ingmar-bergman
+sd-concepts-library/insidewhale
+sd-concepts-library/interchanges
+sd-concepts-library/inuyama-muneto-style-nao
+sd-concepts-library/irasutoya
+sd-concepts-library/iridescent-illustration-style
+sd-concepts-library/iridescent-photo-style
+sd-concepts-library/isabell-schulte-pv-pvii-3000steps
+sd-concepts-library/isabell-schulte-pviii-1-image-style
+sd-concepts-library/isabell-schulte-pviii-1024px-1500-steps-style
+sd-concepts-library/isabell-schulte-pviii-12tiles-3000steps-style
+sd-concepts-library/isabell-schulte-pviii-4-tiles-1-lr-3000-steps-style
+sd-concepts-library/isabell-schulte-pviii-4-tiles-3-lr-5000-steps-style
+sd-concepts-library/isabell-schulte-pviii-4tiles-500steps
+sd-concepts-library/isabell-schulte-pviii-4tiles-6000steps
+sd-concepts-library/isabell-schulte-pviii-style
+sd-concepts-library/isometric-tile-test
+sd-concepts-library/jacqueline-the-unicorn
+sd-concepts-library/james-web-space-telescope
+sd-concepts-library/jamie-hewlett-style
+sd-concepts-library/jamiels
+sd-concepts-library/jang-sung-rak-style
+sd-concepts-library/jetsetdreamcastcovers
+sd-concepts-library/jin-kisaragi
+sd-concepts-library/jinjoon-lee-they
+sd-concepts-library/jm-bergling-monogram
+sd-concepts-library/joe-mad
+sd-concepts-library/joe-whiteford-art-style
+sd-concepts-library/joemad
+sd-concepts-library/john-blanche
+sd-concepts-library/johnny-silverhand
+sd-concepts-library/jojo-bizzare-adventure-manga-lineart
+sd-concepts-library/jos-de-kat
+sd-concepts-library/junji-ito-artstyle
+sd-concepts-library/kaleido
+sd-concepts-library/kaneoya-sachiko
+sd-concepts-library/kanovt
+sd-concepts-library/kanv1
+sd-concepts-library/karan-gloomy
+sd-concepts-library/karl-s-lzx-1
+sd-concepts-library/kasumin
+sd-concepts-library/kawaii-colors
+sd-concepts-library/kawaii-girl-plus-object
+sd-concepts-library/kawaii-girl-plus-style
+sd-concepts-library/kawaii-girl-plus-style-v1-1
+sd-concepts-library/kay
+sd-concepts-library/kaya-ghost-assasin
+sd-concepts-library/ki
+sd-concepts-library/kinda-sus
+sd-concepts-library/kings-quest-agd
+sd-concepts-library/kiora
+sd-concepts-library/kira-sensei
+sd-concepts-library/kirby
+sd-concepts-library/klance
+sd-concepts-library/kodakvision500t
+sd-concepts-library/kogatan-shiny
+sd-concepts-library/kogecha
+sd-concepts-library/kojima-ayami
+sd-concepts-library/koko-dog
+sd-concepts-library/kuvshinov
+sd-concepts-library/kysa-v-style
+sd-concepts-library/laala-character
+sd-concepts-library/larrette
+sd-concepts-library/lavko
+sd-concepts-library/lazytown-stephanie
+sd-concepts-library/ldr
+sd-concepts-library/ldrs
+sd-concepts-library/led-toy
+sd-concepts-library/lego-astronaut
+sd-concepts-library/leica
+sd-concepts-library/leif-jones
+sd-concepts-library/lex
+sd-concepts-library/liliana
+sd-concepts-library/liliana-vess
+sd-concepts-library/liminal-spaces-2-0
+sd-concepts-library/liminalspaces
+sd-concepts-library/line-art
+sd-concepts-library/line-style
+sd-concepts-library/linnopoke
+sd-concepts-library/liquid-light
+sd-concepts-library/liqwid-aquafarmer
+sd-concepts-library/lizardman
+sd-concepts-library/loab-character
+sd-concepts-library/loab-style
+sd-concepts-library/lofa
+sd-concepts-library/logo-with-face-on-shield
+sd-concepts-library/lolo
+sd-concepts-library/looney-anime
+sd-concepts-library/lost-rapper
+sd-concepts-library/lphr-style
+sd-concepts-library/lucario
+sd-concepts-library/lucky-luke
+sd-concepts-library/lugal-ki-en
+sd-concepts-library/luinv2
+sd-concepts-library/lula-13
+sd-concepts-library/lumio
+sd-concepts-library/lxj-o4
+sd-concepts-library/m-geo
+sd-concepts-library/m-geoo
+sd-concepts-library/madhubani-art
+sd-concepts-library/mafalda-character
+sd-concepts-library/magic-pengel
+sd-concepts-library/malika-favre-art-style
+sd-concepts-library/manga-style
+sd-concepts-library/marbling-art
+sd-concepts-library/margo
+sd-concepts-library/marty
+sd-concepts-library/marty6
+sd-concepts-library/mass
+sd-concepts-library/masyanya
+sd-concepts-library/masyunya
+sd-concepts-library/mate
+sd-concepts-library/matthew-stone
+sd-concepts-library/mattvidpro
+sd-concepts-library/maurice-quentin-de-la-tour-style
+sd-concepts-library/maus
+sd-concepts-library/max-foley
+sd-concepts-library/mayor-richard-irvin
+sd-concepts-library/mechasoulall
+sd-concepts-library/medazzaland
+sd-concepts-library/memnarch-mtg
+sd-concepts-library/metagabe
+sd-concepts-library/meyoco
+sd-concepts-library/meze-audio-elite-headphones
+sd-concepts-library/midjourney-style
+sd-concepts-library/mikako-method
+sd-concepts-library/mikako-methodi2i
+sd-concepts-library/miko-3-robot
+sd-concepts-library/milady
+sd-concepts-library/mildemelwe-style
+sd-concepts-library/million-live-akane-15k
+sd-concepts-library/million-live-akane-3k
+sd-concepts-library/million-live-akane-shifuku-3k
+sd-concepts-library/million-live-spade-q-object-3k
+sd-concepts-library/million-live-spade-q-style-3k
+sd-concepts-library/minecraft-concept-art
+sd-concepts-library/mishima-kurone
+sd-concepts-library/mizkif
+sd-concepts-library/moeb-style
+sd-concepts-library/moebius
+sd-concepts-library/mokoko
+sd-concepts-library/mokoko-seed
+sd-concepts-library/monster-girl
+sd-concepts-library/monster-toy
+sd-concepts-library/monte-novo
+sd-concepts-library/moo-moo
+sd-concepts-library/morino-hon-style
+sd-concepts-library/moxxi
+sd-concepts-library/msg
+sd-concepts-library/mtg-card
+sd-concepts-library/mtl-longsky
+sd-concepts-library/mu-sadr
+sd-concepts-library/munch-leaks-style
+sd-concepts-library/museum-by-coop-himmelblau
+sd-concepts-library/muxoyara
+sd-concepts-library/my-hero-academia-style
+sd-concepts-library/my-mug
+sd-concepts-library/mycat
+sd-concepts-library/mystical-nature
+sd-concepts-library/naf
+sd-concepts-library/nahiri
+sd-concepts-library/namine-ritsu
+sd-concepts-library/naoki-saito
+sd-concepts-library/nard-style
+sd-concepts-library/naruto
+sd-concepts-library/natasha-johnston
+sd-concepts-library/nathan-wyatt
+sd-concepts-library/naval-portrait
+sd-concepts-library/nazuna
+sd-concepts-library/nebula
+sd-concepts-library/ned-flanders
+sd-concepts-library/neon-pastel
+sd-concepts-library/new-priests
+sd-concepts-library/nic-papercuts
+sd-concepts-library/nikodim
+sd-concepts-library/nissa-revane
+sd-concepts-library/nixeu
+sd-concepts-library/noggles
+sd-concepts-library/nomad
+sd-concepts-library/nouns-glasses
+sd-concepts-library/obama-based-on-xi
+sd-concepts-library/obama-self-2
+sd-concepts-library/og-mox-style
+sd-concepts-library/ohisashiburi-style
+sd-concepts-library/oleg-kuvaev
+sd-concepts-library/olli-olli
+sd-concepts-library/on-kawara
+sd-concepts-library/one-line-drawing
+sd-concepts-library/onepunchman
+sd-concepts-library/onzpo
+sd-concepts-library/orangejacket
+sd-concepts-library/ori
+sd-concepts-library/ori-toor
+sd-concepts-library/orientalist-art
+sd-concepts-library/osaka-jyo
+sd-concepts-library/osaka-jyo2
+sd-concepts-library/osrsmini2
+sd-concepts-library/osrstiny
+sd-concepts-library/other-mother
+sd-concepts-library/ouroboros
+sd-concepts-library/outfit-items
+sd-concepts-library/overprettified
+sd-concepts-library/owl-house
+sd-concepts-library/painted-by-silver-of-999
+sd-concepts-library/painted-by-silver-of-999-2
+sd-concepts-library/painted-student
+sd-concepts-library/painting
+sd-concepts-library/pantone-milk
+sd-concepts-library/paolo-bonolis
+sd-concepts-library/party-girl
+sd-concepts-library/pascalsibertin
+sd-concepts-library/pastelartstyle
+sd-concepts-library/paul-noir
+sd-concepts-library/pen-ink-portraits-bennorthen
+sd-concepts-library/phan
+sd-concepts-library/phan-s-collage
+sd-concepts-library/phc
+sd-concepts-library/phoenix-01
+sd-concepts-library/pineda-david
+sd-concepts-library/pink-beast-pastelae-style
+sd-concepts-library/pintu
+sd-concepts-library/pion-by-august-semionov
+sd-concepts-library/piotr-jablonski
+sd-concepts-library/pixel-mania
+sd-concepts-library/pixel-toy
+sd-concepts-library/pjablonski-style
+sd-concepts-library/plant-style
+sd-concepts-library/plen-ki-mun
+sd-concepts-library/pokemon-conquest-sprites
+sd-concepts-library/pool-test
+sd-concepts-library/poolrooms
+sd-concepts-library/poring-ragnarok-online
+sd-concepts-library/poutine-dish
+sd-concepts-library/princess-knight-art
+sd-concepts-library/progress-chip
+sd-concepts-library/puerquis-toy
+sd-concepts-library/purplefishli
+sd-concepts-library/pyramidheadcosplay
+sd-concepts-library/qpt-atrium
+sd-concepts-library/quiesel
+sd-concepts-library/r-crumb-style
+sd-concepts-library/rahkshi-bionicle
+sd-concepts-library/raichu
+sd-concepts-library/rail-scene
+sd-concepts-library/rail-scene-style
+sd-concepts-library/ralph-mcquarrie
+sd-concepts-library/ransom
+sd-concepts-library/rayne-weynolds
+sd-concepts-library/rcrumb-portraits-style
+sd-concepts-library/rd-chaos
+sd-concepts-library/rd-paintings
+sd-concepts-library/red-glasses
+sd-concepts-library/reeducation-camp
+sd-concepts-library/reksio-dog
+sd-concepts-library/rektguy
+sd-concepts-library/remert
+sd-concepts-library/renalla
+sd-concepts-library/repeat
+sd-concepts-library/retro-girl
+sd-concepts-library/retro-mecha-rangers
+sd-concepts-library/retropixelart-pinguin
+sd-concepts-library/rex-deno
+sd-concepts-library/rhizomuse-machine-bionic-sculpture
+sd-concepts-library/ricar
+sd-concepts-library/rickyart
+sd-concepts-library/rico-face
+sd-concepts-library/riker-doll
+sd-concepts-library/rikiart
+sd-concepts-library/rikiboy-art
+sd-concepts-library/rilakkuma
+sd-concepts-library/rishusei-style
+sd-concepts-library/rj-palmer
+sd-concepts-library/rl-pkmn-test
+sd-concepts-library/road-to-ruin
+sd-concepts-library/robertnava
+sd-concepts-library/roblox-avatar
+sd-concepts-library/roy-lichtenstein
+sd-concepts-library/ruan-jia
+sd-concepts-library/russian
+sd-concepts-library/s1m-naoto-ohshima
+sd-concepts-library/saheeli-rai
+sd-concepts-library/sakimi-style
+sd-concepts-library/salmonid
+sd-concepts-library/sam-yang
+sd-concepts-library/sanguo-guanyu
+sd-concepts-library/sas-style
+sd-concepts-library/scarlet-witch
+sd-concepts-library/schloss-mosigkau
+sd-concepts-library/scrap-style
+sd-concepts-library/scratch-project
+sd-concepts-library/sculptural-style
+sd-concepts-library/sd-concepts-library-uma-meme
+sd-concepts-library/seamless-ground
+sd-concepts-library/selezneva-alisa
+sd-concepts-library/sem-mac2n
+sd-concepts-library/senneca
+sd-concepts-library/seraphimmoonshadow-art
+sd-concepts-library/sewerslvt
+sd-concepts-library/she-hulk-law-art
+sd-concepts-library/she-mask
+sd-concepts-library/sherhook-painting
+sd-concepts-library/sherhook-painting-v2
+sd-concepts-library/shev-linocut
+sd-concepts-library/shigure-ui-style
+sd-concepts-library/shiny-polyman
+sd-concepts-library/shrunken-head
+sd-concepts-library/shu-doll
+sd-concepts-library/shvoren-style
+sd-concepts-library/sims-2-portrait
+sd-concepts-library/singsing
+sd-concepts-library/singsing-doll
+sd-concepts-library/sintez-ico
+sd-concepts-library/skyfalls
+sd-concepts-library/slm
+sd-concepts-library/smarties
+sd-concepts-library/smiling-friend-style
+sd-concepts-library/smooth-pencils
+sd-concepts-library/smurf-style
+sd-concepts-library/smw-map
+sd-concepts-library/society-finch
+sd-concepts-library/sorami-style
+sd-concepts-library/spider-gwen
+sd-concepts-library/spritual-monsters
+sd-concepts-library/stable-diffusion-conceptualizer
+sd-concepts-library/star-tours-posters
+sd-concepts-library/stardew-valley-pixel-art
+sd-concepts-library/starhavenmachinegods
+sd-concepts-library/sterling-archer
+sd-concepts-library/stretch-re1-robot
+sd-concepts-library/stuffed-penguin-toy
+sd-concepts-library/style-of-marc-allante
+sd-concepts-library/summie-style
+sd-concepts-library/sunfish
+sd-concepts-library/super-nintendo-cartridge
+sd-concepts-library/supitcha-mask
+sd-concepts-library/sushi-pixel
+sd-concepts-library/swamp-choe-2
+sd-concepts-library/t-skrang
+sd-concepts-library/takuji-kawano
+sd-concepts-library/tamiyo
+sd-concepts-library/tangles
+sd-concepts-library/tb303
+sd-concepts-library/tcirle
+sd-concepts-library/teelip-ir-landscape
+sd-concepts-library/teferi
+sd-concepts-library/tela-lenca
+sd-concepts-library/tela-lenca2
+sd-concepts-library/terraria-style
+sd-concepts-library/tesla-bot
+sd-concepts-library/test
+sd-concepts-library/test-epson
+sd-concepts-library/test2
+sd-concepts-library/testing
+sd-concepts-library/thalasin
+sd-concepts-library/thegeneral
+sd-concepts-library/thorneworks
+sd-concepts-library/threestooges
+sd-concepts-library/thunderdome-cover
+sd-concepts-library/thunderdome-covers
+sd-concepts-library/ti-junglepunk-v0
+sd-concepts-library/tili-concept
+sd-concepts-library/titan-robot
+sd-concepts-library/tnj
+sd-concepts-library/toho-pixel
+sd-concepts-library/tomcat
+sd-concepts-library/tonal1
+sd-concepts-library/tony-diterlizzi-s-planescape-art
+sd-concepts-library/towerplace
+sd-concepts-library/toy
+sd-concepts-library/toy-bonnie-plush
+sd-concepts-library/toyota-sera
+sd-concepts-library/transmutation-circles
+sd-concepts-library/trash-polka-artstyle
+sd-concepts-library/travis-bedel
+sd-concepts-library/trigger-studio
+sd-concepts-library/trust-support
+sd-concepts-library/trypophobia
+sd-concepts-library/ttte
+sd-concepts-library/tubby
+sd-concepts-library/tubby-cats
+sd-concepts-library/tudisco
+sd-concepts-library/turtlepics
+sd-concepts-library/type
+sd-concepts-library/ugly-sonic
+sd-concepts-library/uliana-kudinova
+sd-concepts-library/uma
+sd-concepts-library/uma-clean-object
+sd-concepts-library/uma-meme
+sd-concepts-library/uma-meme-style
+sd-concepts-library/uma-style-classic
+sd-concepts-library/unfinished-building
+sd-concepts-library/urivoldemort
+sd-concepts-library/uzumaki
+sd-concepts-library/valorantstyle
+sd-concepts-library/vb-mox
+sd-concepts-library/vcr-classique
+sd-concepts-library/venice
+sd-concepts-library/vespertine
+sd-concepts-library/victor-narm
+sd-concepts-library/vietstoneking
+sd-concepts-library/vivien-reid
+sd-concepts-library/vkuoo1
+sd-concepts-library/vraska
+sd-concepts-library/w3u
+sd-concepts-library/walter-wick-photography
+sd-concepts-library/warhammer-40k-drawing-style
+sd-concepts-library/waterfallshadow
+sd-concepts-library/wayne-reynolds-character
+sd-concepts-library/wedding
+sd-concepts-library/wedding-HandPainted
+sd-concepts-library/werebloops
+sd-concepts-library/wheatland
+sd-concepts-library/wheatland-arknight
+sd-concepts-library/wheelchair
+sd-concepts-library/wildkat
+sd-concepts-library/willy-hd
+sd-concepts-library/wire-angels
+sd-concepts-library/wish-artist-stile
+sd-concepts-library/wlop-style
+sd-concepts-library/wojak
+sd-concepts-library/wojaks-now
+sd-concepts-library/wojaks-now-now-now
+sd-concepts-library/xatu
+sd-concepts-library/xatu2
+sd-concepts-library/xbh
+sd-concepts-library/xi
+sd-concepts-library/xidiversity
+sd-concepts-library/xioboma
+sd-concepts-library/xuna
+sd-concepts-library/xyz
+sd-concepts-library/yb-anime
+sd-concepts-library/yerba-mate
+sd-concepts-library/yesdelete
+sd-concepts-library/yf21
+sd-concepts-library/yilanov2
+sd-concepts-library/yinit
+sd-concepts-library/yoji-shinkawa-style
+sd-concepts-library/yolandi-visser
+sd-concepts-library/yoshi
+sd-concepts-library/youpi2
+sd-concepts-library/youtooz-candy
+sd-concepts-library/yuji-himukai-style
+sd-concepts-library/zaney
+sd-concepts-library/zaneypixelz
+sd-concepts-library/zdenek-art
+sd-concepts-library/zero
+sd-concepts-library/zero-bottle
+sd-concepts-library/zero-suit-samus
+sd-concepts-library/zillertal-can
+sd-concepts-library/zizigooloo
+sd-concepts-library/zk
+sd-concepts-library/zoroark

configs/stable-diffusion/v1-inference.yaml

@@ -30,9 +30,9 @@ model:
       target: ldm.modules.embedding_manager.EmbeddingManager
       params:
         placeholder_strings: ["*"]
-        initializer_words: ['face', 'man', 'photo', 'africanmale']
+        initializer_words: ['sculpture']
         per_image_tokens: false
-        num_vectors_per_token: 1
+        num_vectors_per_token: 8
         progressive_words: False
 
     unet_config:
@@ -76,4 +76,4 @@ model:
           target: torch.nn.Identity
 
     cond_stage_config:
-      target: ldm.modules.encoders.modules.FrozenCLIPEmbedder
+      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: ['sculpture']
+        per_image_tokens: false
+        num_vectors_per_token: 8
+        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

@@ -22,7 +22,7 @@ model:
       target: ldm.modules.embedding_manager.EmbeddingManager
       params:
         placeholder_strings: ["*"]
-        initializer_words: ['face', 'man', 'photo', 'africanmale']
+        initializer_words: ['sculpture']
         per_image_tokens: false
         num_vectors_per_token: 6
         progressive_words: False

docker-build/Dockerfile

@@ -1,57 +1,34 @@
-FROM        debian 
+FROM ubuntu:22.10
 
-ARG         gsd
-ENV         GITHUB_STABLE_DIFFUSION $gsd
+# use bash
+SHELL [ "/bin/bash", "-c" ]
 
-ARG         rsd
-ENV         REQS $rsd
+# Install necesarry packages
+RUN apt-get update \
+  && apt-get install -y \
+    --no-install-recommends \
+    build-essential \
+    gcc \
+    git \
+    libgl1-mesa-glx \
+    libglib2.0-0 \
+    pip \
+    python3 \
+    python3-dev \
+  && apt-get clean \
+  && rm -rf /var/lib/apt/lists/*
 
-ARG         cs
-ENV         CONDA_SUBDIR $cs
+# set workdir and copy sources
+WORKDIR /invokeai
+ARG PIP_REQUIREMENTS=requirements-lin-cuda.txt
+COPY . ./environments-and-requirements/${PIP_REQUIREMENTS} ./
 
-ENV         PIP_EXISTS_ACTION="w"
+# install requirements and link outputs folder
+RUN pip install \
+  --no-cache-dir \
+  -r ${PIP_REQUIREMENTS}
 
-# TODO: Optimize image size
-
-SHELL       ["/bin/bash", "-c"]
-
-WORKDIR     /
-RUN         apt update && apt upgrade -y \
-            && apt install -y \
-            git \
-            libgl1-mesa-glx \
-            libglib2.0-0 \
-            pip \
-            python3 \
-            && git clone $GITHUB_STABLE_DIFFUSION
-
-# Install Anaconda or Miniconda
-COPY        anaconda.sh .
-RUN         bash anaconda.sh -b -u -p /anaconda && /anaconda/bin/conda init bash
-
-# SD 
-WORKDIR     /stable-diffusion 
-RUN         source ~/.bashrc \
-            && conda create -y --name ldm && conda activate ldm \
-            && conda config --env --set subdir $CONDA_SUBDIR \
-            && pip3 install -r $REQS \   
-            && pip3 install basicsr facexlib realesrgan \          
-            && mkdir models/ldm/stable-diffusion-v1 \
-            && ln -s "/data/sd-v1-4.ckpt" models/ldm/stable-diffusion-v1/model.ckpt 
-
-# Face restoreation
-# by default expected in a sibling directory to stable-diffusion
-WORKDIR     /       
-RUN         git clone https://github.com/TencentARC/GFPGAN.git 
-
-WORKDIR     /GFPGAN 
-RUN         pip3 install -r requirements.txt \
-            && python3 setup.py develop \
-            && ln -s "/data/GFPGANv1.4.pth" experiments/pretrained_models/GFPGANv1.4.pth
-
-WORKDIR     /stable-diffusion 
-RUN         python3 scripts/preload_models.py         
-
-WORKDIR     /
-COPY        entrypoint.sh .
-ENTRYPOINT ["/entrypoint.sh"]
+# set Environment, Entrypoint and default CMD
+ENV INVOKEAI_ROOT /data
+ENTRYPOINT [ "python3", "scripts/invoke.py", "--outdir=/data/outputs" ]
+CMD [ "--web", "--host=0.0.0.0" ]

docker-build/build.sh

@@ -0,0 +1,49 @@
+#!/usr/bin/env bash
+set -e
+
+# IMPORTANT: You need to have a token on huggingface.co to be able to download the checkpoints!!!
+# configure values by using env when executing build.sh f.e. `env ARCH=aarch64 ./build.sh`
+
+source ./docker-build/env.sh \
+  || echo "please execute docker-build/build.sh from repository root" \
+  || exit 1
+
+pip_requirements=${PIP_REQUIREMENTS:-requirements-lin-cuda.txt}
+dockerfile=${INVOKE_DOCKERFILE:-docker-build/Dockerfile}
+
+# print the settings
+echo "You are using these values:"
+echo -e "Dockerfile:\t\t ${dockerfile}"
+echo -e "requirements:\t\t ${pip_requirements}"
+echo -e "volumename:\t\t ${volumename}"
+echo -e "arch:\t\t\t ${arch}"
+echo -e "platform:\t\t ${platform}"
+echo -e "invokeai_tag:\t\t ${invokeai_tag}\n"
+
+if [[ -n "$(docker volume ls -f name="${volumename}" -q)" ]]; then
+  echo "Volume already exists"
+  echo
+else
+  echo -n "createing docker volume "
+  docker volume create "${volumename}"
+fi
+
+# Build Container
+docker build \
+  --platform="${platform}" \
+  --tag="${invokeai_tag}" \
+  --build-arg="PIP_REQUIREMENTS=${pip_requirements}" \
+  --file="${dockerfile}" \
+  .
+
+docker run \
+  --rm \
+  --platform="$platform" \
+  --name="$project_name" \
+  --hostname="$project_name" \
+  --mount="source=$volumename,target=/data" \
+  --mount="type=bind,source=$HOME/.huggingface,target=/root/.huggingface" \
+  --env="HUGGINGFACE_TOKEN=${HUGGINGFACE_TOKEN}" \
+  --entrypoint="python3" \
+  "${invokeai_tag}" \
+  scripts/configure_invokeai.py --yes

docker-build/entrypoint.sh

@@ -1,10 +0,0 @@
-#!/bin/bash
-
-cd /stable-diffusion
-
-if [ $# -eq 0 ]; then
-    python3 scripts/dream.py --full_precision -o /data
-    # bash
-else
-    python3 scripts/dream.py --full_precision -o /data "$@"
-fi

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" ${1:+$@}

docs/CHANGELOG.md

@@ -4,45 +4,228 @@ title: Changelog
 
 # :octicons-log-16: **Changelog**
 
-## v2.0.1 (13 October 2022)
+## v2.1.0 <small>(2 November 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)
+- update mac instructions to use invokeai for env name by @willwillems in
+  https://github.com/invoke-ai/InvokeAI/pull/1030
+- 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
+- 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
+- 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
+- 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
+- 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
+- Fix Typo, committed changing ldm environment to invokeai by @jdries3 in
+  https://github.com/invoke-ai/InvokeAI/pull/1095
+- Update generate.py by @unreleased in
+  https://github.com/invoke-ai/InvokeAI/pull/1109
+- Update 'ldm' env to 'invokeai' in troubleshooting steps by @19wolf in
+  https://github.com/invoke-ai/InvokeAI/pull/1125
+- Fixed documentation typos and resolved merge conflicts by @rupeshs in
+  https://github.com/invoke-ai/InvokeAI/pull/1123
+- Fix broken doc links, fix malaprop in the project subtitle by @majick in
+  https://github.com/invoke-ai/InvokeAI/pull/1131
+- Only output facetool parameters if enhancing faces by @db3000 in
+  https://github.com/invoke-ai/InvokeAI/pull/1119
+- Update gitignore to ignore codeformer weights at new location by
+  @spezialspezial in https://github.com/invoke-ai/InvokeAI/pull/1136
+- 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
+- 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
+- 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
+- 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
+- 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
+- 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
+- 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
+- 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
+- Fix Typo, committed changing ldm environment to invokeai by @jdries3 in
+  https://github.com/invoke-ai/InvokeAI/pull/1095
+- 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
+- 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
+- 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
+- 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 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
+- Corrects color channels in face restoration; Fixes #1167 by @psychedelicious
+  in https://github.com/invoke-ai/InvokeAI/pull/1175
+- Flips channels using array slicing instead of using OpenCV by @psychedelicious
+  in https://github.com/invoke-ai/InvokeAI/pull/1178
+- 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
+- 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
+- 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
+- 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
+- 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
+- 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
+- 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
+- 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
+- Allow user to generate images with initial noise as on M1 / mps system by
+  @ArDiouscuros in https://github.com/invoke-ai/InvokeAI/pull/981
+- 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
+- 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
+- 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
+- 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
+- fixing aspect ratio on hires by @tjennings in
+  https://github.com/invoke-ai/InvokeAI/pull/1249
+- 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
+- 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
+- Web UI: Adds initial inpainting implementation by @psychedelicious in
+  https://github.com/invoke-ai/InvokeAI/pull/1225
+- 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
+- Prevent indexing error for mode RGB by @spezialspezial in
+  https://github.com/invoke-ai/InvokeAI/pull/1294
+- 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
+- 1-click installer and updater. Uses micromamba to install git and conda into a
+  contained environment (if necessary) before running the normal installation
+  script by @cmdr2 in https://github.com/invoke-ai/InvokeAI/pull/1253
+- preload_models.py script downloads the weight files by @lstein in
+  https://github.com/invoke-ai/InvokeAI/pull/1290
+
+## v2.0.1 <small>(13 October 2022)</small>
+
+- fix noisy images at high step count when using k\* samplers
+- dream.py script now calls invoke.py module directly rather than via a new
+  python process (which could break the environment)
 
 ## v2.0.0 <small>(9 October 2022)</small>
 
-- `dream.py` script renamed `invoke.py`. A `dream.py` script wrapper remains
-    for backward compatibility.
+- `dream.py` script renamed `invoke.py`. A `dream.py` script wrapper remains for
+  backward compatibility.
 - Completely new WebGUI - launch with `python3 scripts/invoke.py --web`
-- Support for [inpainting](features/INPAINTING.md) and [outpainting](features/OUTPAINTING.md)
-- img2img runs on all k* samplers
-- Support for [negative prompts](features/PROMPTS.md#negative-and-unconditioned-prompts)
+- Support for [inpainting](features/INPAINTING.md) and
+  [outpainting](features/OUTPAINTING.md)
+- img2img runs on all k\* samplers
+- Support for
+  [negative prompts](features/PROMPTS.md#negative-and-unconditioned-prompts)
 - Support for CodeFormer face reconstruction
 - Support for Textual Inversion on Macintoshes
-- Support in both WebGUI and CLI for [post-processing of previously-generated images](features/POSTPROCESS.md)
-    using facial reconstruction, ESRGAN upscaling, outcropping (similar to DALL-E infinite canvas),
-    and "embiggen" upscaling. See the `!fix` command.
-- New `--hires` option on `invoke>` line allows [larger images to be created without duplicating elements](features/CLI.md#this-is-an-example-of-txt2img), at the cost of some performance.
-- New `--perlin` and `--threshold` options allow you to add and control variation
-    during image generation (see [Thresholding and Perlin Noise Initialization](features/OTHER.md#thresholding-and-perlin-noise-initialization-options))
-- Extensive metadata now written into PNG files, allowing reliable regeneration of images
-    and tweaking of previous settings.
-- Command-line completion in `invoke.py` now works on Windows, Linux and Mac platforms.
-- Improved [command-line completion behavior](features/CLI.md)
-    New commands added:
+- Support in both WebGUI and CLI for
+  [post-processing of previously-generated images](features/POSTPROCESS.md)
+  using facial reconstruction, ESRGAN upscaling, outcropping (similar to DALL-E
+  infinite canvas), and "embiggen" upscaling. See the `!fix` command.
+- New `--hires` option on `invoke>` line allows
+  [larger images to be created without duplicating elements](features/CLI.md#this-is-an-example-of-txt2img),
+  at the cost of some performance.
+- New `--perlin` and `--threshold` options allow you to add and control
+  variation during image generation (see
+  [Thresholding and Perlin Noise Initialization](features/OTHER.md#thresholding-and-perlin-noise-initialization-options))
+- Extensive metadata now written into PNG files, allowing reliable regeneration
+  of images and tweaking of previous settings.
+- Command-line completion in `invoke.py` now works on Windows, Linux and Mac
+  platforms.
+- Improved [command-line completion behavior](features/CLI.md) New commands
+  added:
   - List command-line history with `!history`
   - Search command-line history with `!search`
   - Clear history with `!clear`
 - Deprecated `--full_precision` / `-F`. Simply omit it and `invoke.py` will auto
-    configure. To switch away from auto use the new flag like `--precision=float32`.
+  configure. To switch away from auto use the new flag like
+  `--precision=float32`.
 
 ## v1.14 <small>(11 September 2022)</small>
 
 - Memory optimizations for small-RAM cards. 512x512 now possible on 4 GB GPUs.
 - Full support for Apple hardware with M1 or M2 chips.
 - Add "seamless mode" for circular tiling of image. Generates beautiful effects.
-    ([prixt](https://github.com/prixt)).
+  ([prixt](https://github.com/prixt)).
 - Inpainting support.
 - Improved web server GUI.
 - Lots of code and documentation cleanups.
@@ -50,16 +233,17 @@ title: Changelog
 ## v1.13 <small>(3 September 2022)</small>
 
 - Support image variations (see [VARIATIONS](features/VARIATIONS.md)
-    ([Kevin Gibbons](https://github.com/bakkot) and many contributors and reviewers)
-- Supports a Google Colab notebook for a standalone server running on Google hardware
-    [Arturo Mendivil](https://github.com/artmen1516)
+  ([Kevin Gibbons](https://github.com/bakkot) and many contributors and
+  reviewers)
+- Supports a Google Colab notebook for a standalone server running on Google
+  hardware [Arturo Mendivil](https://github.com/artmen1516)
 - WebUI supports GFPGAN/ESRGAN facial reconstruction and upscaling
-    [Kevin Gibbons](https://github.com/bakkot)
+  [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.
-    ([David Wager](https://github.com/maddavid12))
+  stable-diffusion-v1.5) to be added without altering the code.
+  ([David Wager](https://github.com/maddavid12))
 - Can specify --grid on invoke.py command line as the default.
 - Miscellaneous internal bug and stability fixes.
 - Works on M1 Apple hardware.
@@ -71,49 +255,59 @@ title: Changelog
 
 - Improved file handling, including ability to read prompts from standard input.
   (kudos to [Yunsaki](https://github.com/yunsaki)
-- The web server is now integrated with the invoke.py script. Invoke by adding --web to
-  the invoke.py command arguments.
+- The web server is now integrated with the invoke.py script. Invoke by adding
+  --web to the invoke.py command arguments.
 - Face restoration and upscaling via GFPGAN and Real-ESGAN are now automatically
   enabled if the GFPGAN directory is located as a sibling to Stable Diffusion.
-  VRAM requirements are modestly reduced. Thanks to both [Blessedcoolant](https://github.com/blessedcoolant) and
+  VRAM requirements are modestly reduced. Thanks to both
+  [Blessedcoolant](https://github.com/blessedcoolant) and
   [Oceanswave](https://github.com/oceanswave) for their work on this.
-- You can now swap samplers on the invoke> command line. [Blessedcoolant](https://github.com/blessedcoolant)
+- You can now swap samplers on the invoke> command line.
+  [Blessedcoolant](https://github.com/blessedcoolant)
 
 ---
 
 ## v1.11 <small>(26 August 2022)</small>
 
-- NEW FEATURE: Support upscaling and face enhancement using the GFPGAN module. (kudos to [Oceanswave](https://github.com/Oceanswave)
-- You now can specify a seed of -1 to use the previous image's seed, -2 to use the seed for the image generated before that, etc.
-  Seed memory only extends back to the previous command, but will work on all images generated with the -n# switch.
+- NEW FEATURE: Support upscaling and face enhancement using the GFPGAN module.
+  (kudos to [Oceanswave](https://github.com/Oceanswave)
+- You now can specify a seed of -1 to use the previous image's seed, -2 to use
+  the seed for the image generated before that, etc. Seed memory only extends
+  back to the previous command, but will work on all images generated with the
+  -n# switch.
 - Variant generation support temporarily disabled pending more general solution.
-- Created a feature branch named **yunsaki-morphing-invoke** which adds experimental support for
-  iteratively modifying the prompt and its parameters. Please see[Pull Request #86](https://github.com/lstein/stable-diffusion/pull/86)
-  for a synopsis of how this works. Note that when this feature is eventually added to the main branch, it will may be modified
-  significantly.
+- Created a feature branch named **yunsaki-morphing-invoke** which adds
+  experimental support for iteratively modifying the prompt and its parameters.
+  Please
+  see[Pull Request #86](https://github.com/lstein/stable-diffusion/pull/86) for
+  a synopsis of how this works. Note that when this feature is eventually added
+  to the main branch, it will may be modified significantly.
 
 ---
 
 ## v1.10 <small>(25 August 2022)</small>
 
-- A barebones but fully functional interactive web server for online generation of txt2img and img2img.
+- A barebones but fully functional interactive web server for online generation
+  of txt2img and img2img.
 
 ---
 
 ## v1.09 <small>(24 August 2022)</small>
 
 - A new -v option allows you to generate multiple variants of an initial image
-  in img2img mode. (kudos to [Oceanswave](https://github.com/Oceanswave). [
-  See this discussion in the PR for examples and details on use](https://github.com/lstein/stable-diffusion/pull/71#issuecomment-1226700810))
-- Added ability to personalize text to image generation (kudos to [Oceanswave](https://github.com/Oceanswave) and [nicolai256](https://github.com/nicolai256))
+  in img2img mode. (kudos to [Oceanswave](https://github.com/Oceanswave).
+  [ See this discussion in the PR for examples and details on use](https://github.com/lstein/stable-diffusion/pull/71#issuecomment-1226700810))
+- Added ability to personalize text to image generation (kudos to
+  [Oceanswave](https://github.com/Oceanswave) and
+  [nicolai256](https://github.com/nicolai256))
 - Enabled all of the samplers from k_diffusion
 
 ---
 
 ## v1.08 <small>(24 August 2022)</small>
 
-- Escape single quotes on the invoke> command before trying to parse. This avoids
-  parse errors.
+- Escape single quotes on the invoke> command before trying to parse. This
+  avoids parse errors.
 - Removed instruction to get Python3.8 as first step in Windows install.
   Anaconda3 does it for you.
 - Added bounds checks for numeric arguments that could cause crashes.
@@ -123,34 +317,36 @@ title: Changelog
 
 ## v1.07 <small>(23 August 2022)</small>
 
-- Image filenames will now never fill gaps in the sequence, but will be assigned the
-  next higher name in the chosen directory. This ensures that the alphabetic and chronological
-  sort orders are the same.
+- Image filenames will now never fill gaps in the sequence, but will be assigned
+  the next higher name in the chosen directory. This ensures that the alphabetic
+  and chronological sort orders are the same.
 
 ---
 
 ## v1.06 <small>(23 August 2022)</small>
 
-- Added weighted prompt support contributed by [xraxra](https://github.com/xraxra)
-- Example of using weighted prompts to tweak a demonic figure contributed by [bmaltais](https://github.com/bmaltais)
+- Added weighted prompt support contributed by
+  [xraxra](https://github.com/xraxra)
+- Example of using weighted prompts to tweak a demonic figure contributed by
+  [bmaltais](https://github.com/bmaltais)
 
 ---
 
 ## v1.05 <small>(22 August 2022 - after the drop)</small>
 
-- Filenames now use the following formats:
-  000010.95183149.png -- Two files produced by the same command (e.g. -n2),
-  000010.26742632.png -- distinguished by a different seed.
+- Filenames now use the following formats: 000010.95183149.png -- Two files
+  produced by the same command (e.g. -n2), 000010.26742632.png -- distinguished
+  by a different seed.
 
   000011.455191342.01.png -- Two files produced by the same command using
   000011.455191342.02.png -- a batch size>1 (e.g. -b2). They have the same seed.
 
-  000011.4160627868.grid#1-4.png -- a grid of four images (-g); the whole grid can
-  be regenerated with the indicated key
+  000011.4160627868.grid#1-4.png -- a grid of four images (-g); the whole grid
+  can be regenerated with the indicated key
 
 - It should no longer be possible for one image to overwrite another
-- You can use the "cd" and "pwd" commands at the invoke> prompt to set and retrieve
-  the path of the output directory.
+- You can use the "cd" and "pwd" commands at the invoke> prompt to set and
+  retrieve the path of the output directory.
 
 ---
 
@@ -164,26 +360,28 @@ title: Changelog
 
 ## v1.03 <small>(22 August 2022)</small>
 
-- The original txt2img and img2img scripts from the CompViz repository have been moved into
-  a subfolder named "orig_scripts", to reduce confusion.
+- The original txt2img and img2img scripts from the CompViz repository have been
+  moved into a subfolder named "orig_scripts", to reduce confusion.
 
 ---
 
 ## v1.02 <small>(21 August 2022)</small>
 
-- A copy of the prompt and all of its switches and options is now stored in the corresponding
-  image in a tEXt metadata field named "Dream". You can read the prompt using scripts/images2prompt.py,
-  or an image editor that allows you to explore the full metadata.
-  **Please run "conda env update" to load the k_lms dependencies!!**
+- A copy of the prompt and all of its switches and options is now stored in the
+  corresponding image in a tEXt metadata field named "Dream". You can read the
+  prompt using scripts/images2prompt.py, or an image editor that allows you to
+  explore the full metadata. **Please run "conda env update" to load the k_lms
+  dependencies!!**
 
 ---
 
 ## v1.01 <small>(21 August 2022)</small>
 
-- added k_lms sampling.
-  **Please run "conda env update" to load the k_lms dependencies!!**
-- use half precision arithmetic by default, resulting in faster execution and lower memory requirements
-  Pass argument --full_precision to invoke.py to get slower but more accurate image generation
+- added k_lms sampling. **Please run "conda env update" to load the k_lms
+  dependencies!!**
+- use half precision arithmetic by default, resulting in faster execution and
+  lower memory requirements Pass argument --full_precision to invoke.py to get
+  slower but more accurate image generation
 
 ---