Remove unused check_internet() function.

README.md

@@ -12,7 +12,7 @@
 
 Invoke is a leading creative engine built to empower professionals and enthusiasts alike. Generate and create stunning visual media using the latest AI-driven technologies. Invoke offers an industry leading web-based UI, and serves as the foundation for multiple commercial products.
 
-[Installation and Updates][installation docs] - [Documentation and Tutorials][docs home] - [Bug Reports][github issues] - [Contributing][contributing docs]
+[Installation][installation docs] - [Documentation and Tutorials][docs home] - [Bug Reports][github issues] - [Contributing][contributing docs]
 
 <div align="center">
 

docs/features/CONFIGURATION.md

@@ -51,11 +51,13 @@ The settings in this file will override the defaults. You only need
 to change this file if the default for a particular setting doesn't
 work for you.
 
-You'll find an example file next to `invokeai.yaml` that shows the default values.
-
 Some settings, like [Model Marketplace API Keys], require the YAML
 to be formatted correctly. Here is a [basic guide to YAML files].
 
+You can fix a broken `invokeai.yaml` by deleting it and running the
+configuration script again -- option [6] in the launcher, "Re-run the
+configure script".
+
 #### Custom Config File Location
 
 You can use any config file with the `--config` CLI arg. Pass in the path to the `invokeai.yaml` file you want to use.

docs/features/TRAINING.md

@@ -4,6 +4,278 @@ title: Training
 
 # :material-file-document: Training
 
-Invoke Training has moved to its own repository, with a dedicated UI for accessing common scripts like Textual Inversion and LoRA training.
+# Textual Inversion Training
+## **Personalizing Text-to-Image Generation**
 
-You can find more by visiting the repo at https://github.com/invoke-ai/invoke-training
+You may personalize the generated images to provide your own styles or objects
+by training a new LDM checkpoint and introducing a new vocabulary to the fixed
+model as a (.pt) embeddings file. Alternatively, you may use or train
+HuggingFace Concepts embeddings files (.bin) from
+<https://huggingface.co/sd-concepts-library> and its associated
+notebooks.
+
+## **Hardware and Software Requirements**
+
+You will need a GPU to perform training in a reasonable length of
+time, and at least 12 GB of VRAM. We recommend using the [`xformers`
+library](../installation/070_INSTALL_XFORMERS.md) to accelerate the
+training process further. During training, about ~8 GB is temporarily
+needed in order to store intermediate models, checkpoints and logs.
+
+## **Preparing for Training**
+
+To train, prepare a folder that contains 3-5 images that illustrate
+the object or concept. It is good to provide a variety of examples or
+poses to avoid overtraining the system. Format these images as PNG
+(preferred) or JPG. You do not need to resize or crop the images in
+advance, but for more control you may wish to do so.
+
+Place the training images in a directory on the machine InvokeAI runs
+on. We recommend placing them in a subdirectory of the
+`text-inversion-training-data` folder located in the InvokeAI root
+directory, ordinarily `~/invokeai` (Linux/Mac), or
+`C:\Users\your_name\invokeai` (Windows). For example, to create an
+embedding for the "psychedelic" style, you'd place the training images
+into the directory
+`~invokeai/text-inversion-training-data/psychedelic`.
+
+## **Launching Training Using the Console Front End**
+
+InvokeAI 2.3 and higher comes with a text console-based training front
+end. From within the `invoke.sh`/`invoke.bat` Invoke launcher script,
+start training tool selecting choice (3):
+
+```sh
+1 "Generate images with a browser-based interface"
+2 "Explore InvokeAI nodes using a command-line interface"
+3 "Textual inversion training"
+4 "Merge models (diffusers type only)"
+5 "Download and install models"
+6 "Change InvokeAI startup options"
+7 "Re-run the configure script to fix a broken install or to complete a major upgrade"
+8 "Open the developer console"
+9 "Update InvokeAI"
+```
+
+Alternatively, you can select option (8) or from the command line, with the InvokeAI virtual environment active,
+you can then launch the front end with the command `invokeai-ti --gui`.
+
+This will launch a text-based front end that will look like this:
+
+<figure markdown>
+![ti-frontend](../assets/textual-inversion/ti-frontend.png)
+</figure>
+
+The interface is keyboard-based. Move from field to field using
+control-N (^N) to move to the next field and control-P (^P) to the
+previous one. <Tab> and <shift-TAB> work as well. Once a field is
+active, use the cursor keys. In a checkbox group, use the up and down
+cursor keys to move from choice to choice, and <space> to select a
+choice. In a scrollbar, use the left and right cursor keys to increase
+and decrease the value of the scroll. In textfields, type the desired
+values.
+
+The number of parameters may look intimidating, but in most cases the
+predefined defaults work fine. The red circled fields in the above
+illustration are the ones you will adjust most frequently.
+
+### Model Name
+
+This will list all the diffusers models that are currently
+installed. Select the one you wish to use as the basis for your
+embedding. Be aware that if you use a SD-1.X-based model for your
+training, you will only be able to use this embedding with other
+SD-1.X-based models. Similarly, if you train on SD-2.X, you will only
+be able to use the embeddings with models based on SD-2.X.
+
+### Trigger Term
+
+This is the prompt term you will use to trigger the embedding. Type a
+single word or phrase you wish to use as the trigger, example
+"psychedelic" (without angle brackets). Within InvokeAI, you will then
+be able to activate the trigger using the syntax `<psychedelic>`.
+
+### Initializer
+
+This is a single character that is used internally during the training
+process as a placeholder for the trigger term. It defaults to "*" and
+can usually be left alone.
+
+### Resume from last saved checkpoint
+
+As training proceeds, textual inversion will write a series of
+intermediate files that can be used to resume training from where it
+was left off in the case of an interruption. This checkbox will be
+automatically selected if you provide a previously used trigger term
+and at least one checkpoint file is found on disk.
+
+Note that as of 20 January 2023, resume does not seem to be working
+properly due to an issue with the upstream code.
+
+### Data Training Directory
+
+This is the location of the images to be used for training. When you
+select a trigger term like "my-trigger", the frontend will prepopulate
+this field with `~/invokeai/text-inversion-training-data/my-trigger`,
+but you can change the path to wherever you want.
+
+### Output Destination Directory
+
+This is the location of the logs, checkpoint files, and embedding
+files created during training. When you select a trigger term like
+"my-trigger", the frontend will prepopulate this field with
+`~/invokeai/text-inversion-output/my-trigger`, but you can change the
+path to wherever you want.
+
+### Image resolution
+
+The images in the training directory will be automatically scaled to
+the value you use here. For best results, you will want to use the
+same default resolution of the underlying model (512 pixels for
+SD-1.5, 768 for the larger version of SD-2.1).
+
+### Center crop images
+
+If this is selected, your images will be center cropped to make them
+square before resizing them to the desired resolution. Center cropping
+can indiscriminately cut off the top of subjects' heads for portrait
+aspect images, so if you have images like this, you may wish to use a
+photoeditor to manually crop them to a square aspect ratio.
+
+### Mixed precision
+
+Select the floating point precision for the embedding. "no" will
+result in a full 32-bit precision, "fp16" will provide 16-bit
+precision, and "bf16" will provide mixed precision (only available
+when XFormers is used).
+
+### Max training steps
+
+How many steps the training will take before the model converges. Most
+training sets will converge with 2000-3000 steps.
+
+### Batch size
+
+This adjusts how many training images are processed simultaneously in
+each step. Higher values will cause the training process to run more
+quickly, but use more memory. The default size will run with GPUs with
+as little as 12 GB.
+
+### Learning rate
+
+The rate at which the system adjusts its internal weights during
+training. Higher values risk overtraining (getting the same image each
+time), and lower values will take more steps to train a good
+model. The default of 0.0005 is conservative; you may wish to increase
+it to 0.005 to speed up training.
+
+### Scale learning rate by number of GPUs, steps and batch size
+
+If this is selected (the default) the system will adjust the provided
+learning rate to improve performance.
+
+### Use xformers acceleration
+
+This will activate XFormers memory-efficient attention. You need to
+have XFormers installed for this to have an effect.
+
+### Learning rate scheduler
+
+This adjusts how the learning rate changes over the course of
+training. The default "constant" means to use a constant learning rate
+for the entire training session. The other values scale the learning
+rate according to various formulas.
+
+Only "constant" is supported by the XFormers library.
+
+### Gradient accumulation steps
+
+This is a parameter that allows you to use bigger batch sizes than
+your GPU's VRAM would ordinarily accommodate, at the cost of some
+performance.
+
+### Warmup steps
+
+If "constant_with_warmup" is selected in the learning rate scheduler,
+then this provides the number of warmup steps. Warmup steps have a
+very low learning rate, and are one way of preventing early
+overtraining.
+
+## The training run
+
+Start the training run by advancing to the OK button (bottom right)
+and pressing <enter>. A series of progress messages will be displayed
+as the training process proceeds. This may take an hour or two,
+depending on settings and the speed of your system. Various log and
+checkpoint files will be written into the output directory (ordinarily
+`~/invokeai/text-inversion-output/my-model/`)
+
+At the end of successful training, the system will copy the file
+`learned_embeds.bin` into the InvokeAI root directory's `embeddings`
+directory, using a subdirectory named after the trigger token. For
+example, if the trigger token was `psychedelic`, then look for the
+embeddings file in
+`~/invokeai/embeddings/psychedelic/learned_embeds.bin`
+
+You may now launch InvokeAI and try out a prompt that uses the trigger
+term. For example `a plate of banana sushi in <psychedelic> style`.
+
+## **Training with the Command-Line Script**
+
+Training can also be done using a traditional command-line script. It
+can be launched from within the "developer's console", or from the
+command line after activating InvokeAI's virtual environment.
+
+It accepts a large number of arguments, which can be summarized by
+passing the `--help` argument:
+
+```sh
+invokeai-ti --help
+```
+
+Typical usage is shown here:
+```sh
+invokeai-ti \
+       --model=stable-diffusion-1.5 \
+       --resolution=512 \
+       --learnable_property=style \
+       --initializer_token='*' \
+       --placeholder_token='<psychedelic>' \
+       --train_data_dir=/home/lstein/invokeai/training-data/psychedelic \
+       --output_dir=/home/lstein/invokeai/text-inversion-training/psychedelic \
+       --scale_lr \
+       --train_batch_size=8 \
+       --gradient_accumulation_steps=4 \
+       --max_train_steps=3000 \
+       --learning_rate=0.0005 \
+       --resume_from_checkpoint=latest \
+       --lr_scheduler=constant \
+       --mixed_precision=fp16 \
+       --only_save_embeds
+```
+
+## Troubleshooting
+
+### `Cannot load embedding for <trigger>. It was trained on a model with token dimension 1024, but the current model has token dimension 768`
+
+Messages like this indicate you trained the embedding on a different base model than the currently selected one.
+
+For example, in the error above, the training was done on SD2.1 (768x768) but it was used on SD1.5 (512x512).
+
+## Reading
+
+For more information on textual inversion, please see the following
+resources:
+
+* The [textual inversion repository](https://github.com/rinongal/textual_inversion) and
+  associated paper for details and limitations.
+* [HuggingFace's textual inversion training
+  page](https://huggingface.co/docs/diffusers/training/text_inversion)
+* [HuggingFace example script
+  documentation](https://github.com/huggingface/diffusers/tree/main/examples/textual_inversion)
+  (Note that this script is similar to, but not identical, to
+  `textual_inversion`, but produces embed files that are completely compatible.
+
+---
+
+copyright (c) 2023, Lincoln Stein and the InvokeAI Development Team

docs/installation/010_INSTALL_AUTOMATED.md

@@ -1,10 +1,8 @@
-# Automatic Install & Updates
+# Automatic Install
 
-**The same packaged installer file can be used for both new installs and updates.**
-Using the installer for updates will leave everything you've added since installation, and just update the core libraries used to run Invoke.
-Simply use the same path you installed to originally.
+The installer is used for both new installs and updates.
 
-Both release and pre-release versions can be installed using the installer. It also supports install through a wheel if needed.
+Both release and pre-release versions can be installed using it. It also supports install a wheel if needed.
 
 Be sure to review the [installation requirements] and ensure your system has everything it needs to install Invoke.
 

docs/installation/INSTALLATION.md

@@ -1,4 +1,4 @@
-# Installation and Updating Overview
+# Installation Overview
 
 Before installing, review the [installation requirements] to ensure your system is set up properly.
 
@@ -6,21 +6,14 @@ See the [FAQ] for frequently-encountered installation issues.
 
 If you need more help, join our [discord] or [create an issue].
 
-<h2>Automatic Install & Updates </h2>
+<h2>Automatic Install</h2>
 
 ✅ The automatic install is the best way to run InvokeAI. Check out the [installation guide] to get started.
 
-⬆️ The same installer is also the best way to update InvokeAI - Simply rerun it for the same folder you installed to.
-
-The installation process simply manages installation for the core libraries & application dependencies that run Invoke.
-Any models, images, or other assets in the Invoke root folder won't be affected by the installation process.
-
 <h2>Manual Install</h2>
 
 If you are familiar with python and want more control over the packages that are installed, you can [install InvokeAI manually via PyPI].
 
-Updates are managed by reinstalling the latest version through PyPi.
-
 <h2>Developer Install</h2>
 
 If you want to contribute to InvokeAI, consult the [developer install guide].

invokeai/app/api/dependencies.py

@@ -35,23 +35,6 @@ from ..services.urls.urls_default import LocalUrlService
 from ..services.workflow_records.workflow_records_sqlite import SqliteWorkflowRecordsStorage
 from .events import FastAPIEventService
 
-
-# TODO: is there a better way to achieve this?
-def check_internet() -> bool:
-    """
-    Return true if the internet is reachable.
-    It does this by pinging huggingface.co.
-    """
-    import urllib.request
-
-    host = "http://huggingface.co"
-    try:
-        urllib.request.urlopen(host, timeout=1)
-        return True
-    except Exception:
-        return False
-
-
 logger = InvokeAILogger.get_logger()
 
 

invokeai/app/api_app.py

@@ -2,6 +2,7 @@ import asyncio
 import logging
 import mimetypes
 import socket
+import time
 from contextlib import asynccontextmanager
 from inspect import signature
 from pathlib import Path
@@ -20,13 +21,10 @@ from fastapi_events.middleware import EventHandlerASGIMiddleware
 from pydantic.json_schema import models_json_schema
 from torch.backends.mps import is_available as is_mps_available
 
-# for PyCharm:
-# noinspection PyUnresolvedReferences
-import invokeai.backend.util.hotfixes  # noqa: F401 (monkeypatching on import)
 import invokeai.frontend.web as web_dir
 from invokeai.app.api.no_cache_staticfiles import NoCacheStaticFiles
 from invokeai.app.invocations.model import ModelIdentifierField
-from invokeai.app.services.config.config_default import get_config
+from invokeai.app.services.config.config_default import InvokeAIAppConfig, get_config
 from invokeai.app.services.session_processor.session_processor_common import ProgressImage
 from invokeai.backend.util.devices import TorchDevice
 
@@ -44,188 +42,189 @@ from .api.routers import (
     workflows,
 )
 from .api.sockets import SocketIO
-from .invocations.baseinvocation import (
-    BaseInvocation,
-    UIConfigBase,
-)
+from .invocations.baseinvocation import BaseInvocation, UIConfigBase
 from .invocations.fields import InputFieldJSONSchemaExtra, OutputFieldJSONSchemaExtra
 
-app_config = get_config()
+
+# TODO(ryand): Search for imports from api_app.py in the rest of the codebase and make sure I didn't break any of them.
+def build_app(app_config: InvokeAIAppConfig, logger: logging.Logger) -> FastAPI:
+    @asynccontextmanager
+    async def lifespan(app: FastAPI):
+        # Add startup event to load dependencies
+        ApiDependencies.initialize(config=app_config, event_handler_id=event_handler_id, logger=logger)
+        yield
+        # Shut down threads
+        ApiDependencies.shutdown()
+
+    app = FastAPI(
+        title="Invoke - Community Edition",
+        docs_url=None,
+        redoc_url=None,
+        separate_input_output_schemas=False,
+        lifespan=lifespan,
+    )
+
+    # Add event handler
+    event_handler_id: int = id(app)
+    app.add_middleware(
+        EventHandlerASGIMiddleware,
+        handlers=[local_handler],  # TODO: consider doing this in services to support different configurations
+        middleware_id=event_handler_id,
+    )
+
+    socket_io = SocketIO(app)
+
+    app.add_middleware(
+        CORSMiddleware,
+        allow_origins=app_config.allow_origins,
+        allow_credentials=app_config.allow_credentials,
+        allow_methods=app_config.allow_methods,
+        allow_headers=app_config.allow_headers,
+    )
+
+    app.add_middleware(GZipMiddleware, minimum_size=1000)
+
+    # Include all routers
+    app.include_router(utilities.utilities_router, prefix="/api")
+    app.include_router(model_manager.model_manager_router, prefix="/api")
+    app.include_router(download_queue.download_queue_router, prefix="/api")
+    app.include_router(images.images_router, prefix="/api")
+    app.include_router(boards.boards_router, prefix="/api")
+    app.include_router(board_images.board_images_router, prefix="/api")
+    app.include_router(app_info.app_router, prefix="/api")
+    app.include_router(session_queue.session_queue_router, prefix="/api")
+    app.include_router(workflows.workflows_router, prefix="/api")
+
+    add_custom_openapi(app)
+
+    @app.get("/docs", include_in_schema=False)
+    def overridden_swagger() -> HTMLResponse:
+        return get_swagger_ui_html(
+            openapi_url=app.openapi_url,  # type: ignore [arg-type] # this is always a string
+            title=f"{app.title} - Swagger UI",
+            swagger_favicon_url="static/docs/invoke-favicon-docs.svg",
+        )
+
+    @app.get("/redoc", include_in_schema=False)
+    def overridden_redoc() -> HTMLResponse:
+        return get_redoc_html(
+            openapi_url=app.openapi_url,  # type: ignore [arg-type] # this is always a string
+            title=f"{app.title} - Redoc",
+            redoc_favicon_url="static/docs/invoke-favicon-docs.svg",
+        )
+
+    web_root_path = Path(list(web_dir.__path__)[0])
+
+    try:
+        app.mount("/", NoCacheStaticFiles(directory=Path(web_root_path, "dist"), html=True), name="ui")
+    except RuntimeError:
+        logger.warn(f"No UI found at {web_root_path}/dist, skipping UI mount")
+
+    app.mount(
+        "/static", NoCacheStaticFiles(directory=Path(web_root_path, "static/")), name="static"
+    )  # docs favicon is in here
+
+    return app
 
 
-if is_mps_available():
-    import invokeai.backend.util.mps_fixes  # noqa: F401 (monkeypatching on import)
+def apply_monkeypatches() -> None:
+    # TODO(ryand): Don't monkeypatch on import!
+    if is_mps_available():
+        import invokeai.backend.util.mps_fixes  # noqa: F401 (monkeypatching on import)
+    import invokeai.backend.util.hotfixes  # noqa: F401 (monkeypatching on import)
 
 
-logger = InvokeAILogger.get_logger(config=app_config)
-# fix for windows mimetypes registry entries being borked
-# see https://github.com/invoke-ai/InvokeAI/discussions/3684#discussioncomment-6391352
-mimetypes.add_type("application/javascript", ".js")
-mimetypes.add_type("text/css", ".css")
-
-torch_device_name = TorchDevice.get_torch_device_name()
-logger.info(f"Using torch device: {torch_device_name}")
+def fix_mimetypes():
+    # fix for windows mimetypes registry entries being borked
+    # see https://github.com/invoke-ai/InvokeAI/discussions/3684#discussioncomment-6391352
+    mimetypes.add_type("application/javascript", ".js")
+    mimetypes.add_type("text/css", ".css")
 
 
-@asynccontextmanager
-async def lifespan(app: FastAPI):
-    # Add startup event to load dependencies
-    ApiDependencies.initialize(config=app_config, event_handler_id=event_handler_id, logger=logger)
-    yield
-    # Shut down threads
-    ApiDependencies.shutdown()
+def add_custom_openapi(app: FastAPI) -> None:
+    """Add a custom .openapi() method to the FastAPI app.
 
+    This is done based on the guidance here:
+    https://fastapi.tiangolo.com/how-to/extending-openapi/#normal-fastapi
+    """
 
-# Create the app
-# TODO: create this all in a method so configuration/etc. can be passed in?
-app = FastAPI(
-    title="Invoke - Community Edition",
-    docs_url=None,
-    redoc_url=None,
-    separate_input_output_schemas=False,
-    lifespan=lifespan,
-)
+    # Build a custom OpenAPI to include all outputs
+    # TODO: can outputs be included on metadata of invocation schemas somehow?
+    def custom_openapi() -> dict[str, Any]:
+        if app.openapi_schema:
+            return app.openapi_schema
+        openapi_schema = get_openapi(
+            title=app.title,
+            description="An API for invoking AI image operations",
+            version="1.0.0",
+            routes=app.routes,
+            separate_input_output_schemas=False,  # https://fastapi.tiangolo.com/how-to/separate-openapi-schemas/
+        )
 
-# Add event handler
-event_handler_id: int = id(app)
-app.add_middleware(
-    EventHandlerASGIMiddleware,
-    handlers=[local_handler],  # TODO: consider doing this in services to support different configurations
-    middleware_id=event_handler_id,
-)
+        # Add all outputs
+        all_invocations = BaseInvocation.get_invocations()
+        output_types = set()
+        output_type_titles = {}
+        for invoker in all_invocations:
+            output_type = signature(invoker.invoke).return_annotation
+            output_types.add(output_type)
 
-socket_io = SocketIO(app)
+        output_schemas = models_json_schema(
+            models=[(o, "serialization") for o in output_types], ref_template="#/components/schemas/{model}"
+        )
+        for schema_key, output_schema in output_schemas[1]["$defs"].items():
+            # TODO: note that we assume the schema_key here is the TYPE.__name__
+            # This could break in some cases, figure out a better way to do it
+            output_type_titles[schema_key] = output_schema["title"]
+            openapi_schema["components"]["schemas"][schema_key] = output_schema
+            openapi_schema["components"]["schemas"][schema_key]["class"] = "output"
 
-app.add_middleware(
-    CORSMiddleware,
-    allow_origins=app_config.allow_origins,
-    allow_credentials=app_config.allow_credentials,
-    allow_methods=app_config.allow_methods,
-    allow_headers=app_config.allow_headers,
-)
+        # Some models don't end up in the schemas as standalone definitions
+        additional_schemas = models_json_schema(
+            [
+                (UIConfigBase, "serialization"),
+                (InputFieldJSONSchemaExtra, "serialization"),
+                (OutputFieldJSONSchemaExtra, "serialization"),
+                (ModelIdentifierField, "serialization"),
+                (ProgressImage, "serialization"),
+            ],
+            ref_template="#/components/schemas/{model}",
+        )
+        for schema_key, schema_json in additional_schemas[1]["$defs"].items():
+            openapi_schema["components"]["schemas"][schema_key] = schema_json
 
-app.add_middleware(GZipMiddleware, minimum_size=1000)
+        # Add a reference to the output type to additionalProperties of the invoker schema
+        for invoker in all_invocations:
+            invoker_name = invoker.__name__  # type: ignore [attr-defined] # this is a valid attribute
+            output_type = signature(obj=invoker.invoke).return_annotation
+            output_type_title = output_type_titles[output_type.__name__]
+            invoker_schema = openapi_schema["components"]["schemas"][f"{invoker_name}"]
+            outputs_ref = {"$ref": f"#/components/schemas/{output_type_title}"}
+            invoker_schema["output"] = outputs_ref
+            invoker_schema["class"] = "invocation"
 
+        # This code no longer seems to be necessary?
+        # Leave it here just in case
+        #
+        # from invokeai.backend.model_manager import get_model_config_formats
+        # formats = get_model_config_formats()
+        # for model_config_name, enum_set in formats.items():
 
-# Include all routers
-app.include_router(utilities.utilities_router, prefix="/api")
-app.include_router(model_manager.model_manager_router, prefix="/api")
-app.include_router(download_queue.download_queue_router, prefix="/api")
-app.include_router(images.images_router, prefix="/api")
-app.include_router(boards.boards_router, prefix="/api")
-app.include_router(board_images.board_images_router, prefix="/api")
-app.include_router(app_info.app_router, prefix="/api")
-app.include_router(session_queue.session_queue_router, prefix="/api")
-app.include_router(workflows.workflows_router, prefix="/api")
+        #     if model_config_name in openapi_schema["components"]["schemas"]:
+        #         # print(f"Config with name {name} already defined")
+        #         continue
 
+        #     openapi_schema["components"]["schemas"][model_config_name] = {
+        #         "title": model_config_name,
+        #         "description": "An enumeration.",
+        #         "type": "string",
+        #         "enum": [v.value for v in enum_set],
+        #     }
 
-# Build a custom OpenAPI to include all outputs
-# TODO: can outputs be included on metadata of invocation schemas somehow?
-def custom_openapi() -> dict[str, Any]:
-    if app.openapi_schema:
+        app.openapi_schema = openapi_schema
         return app.openapi_schema
-    openapi_schema = get_openapi(
-        title=app.title,
-        description="An API for invoking AI image operations",
-        version="1.0.0",
-        routes=app.routes,
-        separate_input_output_schemas=False,  # https://fastapi.tiangolo.com/how-to/separate-openapi-schemas/
-    )
 
-    # Add all outputs
-    all_invocations = BaseInvocation.get_invocations()
-    output_types = set()
-    output_type_titles = {}
-    for invoker in all_invocations:
-        output_type = signature(invoker.invoke).return_annotation
-        output_types.add(output_type)
-
-    output_schemas = models_json_schema(
-        models=[(o, "serialization") for o in output_types], ref_template="#/components/schemas/{model}"
-    )
-    for schema_key, output_schema in output_schemas[1]["$defs"].items():
-        # TODO: note that we assume the schema_key here is the TYPE.__name__
-        # This could break in some cases, figure out a better way to do it
-        output_type_titles[schema_key] = output_schema["title"]
-        openapi_schema["components"]["schemas"][schema_key] = output_schema
-        openapi_schema["components"]["schemas"][schema_key]["class"] = "output"
-
-    # Some models don't end up in the schemas as standalone definitions
-    additional_schemas = models_json_schema(
-        [
-            (UIConfigBase, "serialization"),
-            (InputFieldJSONSchemaExtra, "serialization"),
-            (OutputFieldJSONSchemaExtra, "serialization"),
-            (ModelIdentifierField, "serialization"),
-            (ProgressImage, "serialization"),
-        ],
-        ref_template="#/components/schemas/{model}",
-    )
-    for schema_key, schema_json in additional_schemas[1]["$defs"].items():
-        openapi_schema["components"]["schemas"][schema_key] = schema_json
-
-    # Add a reference to the output type to additionalProperties of the invoker schema
-    for invoker in all_invocations:
-        invoker_name = invoker.__name__  # type: ignore [attr-defined] # this is a valid attribute
-        output_type = signature(obj=invoker.invoke).return_annotation
-        output_type_title = output_type_titles[output_type.__name__]
-        invoker_schema = openapi_schema["components"]["schemas"][f"{invoker_name}"]
-        outputs_ref = {"$ref": f"#/components/schemas/{output_type_title}"}
-        invoker_schema["output"] = outputs_ref
-        invoker_schema["class"] = "invocation"
-
-    # This code no longer seems to be necessary?
-    # Leave it here just in case
-    #
-    # from invokeai.backend.model_manager import get_model_config_formats
-    # formats = get_model_config_formats()
-    # for model_config_name, enum_set in formats.items():
-
-    #     if model_config_name in openapi_schema["components"]["schemas"]:
-    #         # print(f"Config with name {name} already defined")
-    #         continue
-
-    #     openapi_schema["components"]["schemas"][model_config_name] = {
-    #         "title": model_config_name,
-    #         "description": "An enumeration.",
-    #         "type": "string",
-    #         "enum": [v.value for v in enum_set],
-    #     }
-
-    app.openapi_schema = openapi_schema
-    return app.openapi_schema
-
-
-app.openapi = custom_openapi  # type: ignore [method-assign] # this is a valid assignment
-
-
-@app.get("/docs", include_in_schema=False)
-def overridden_swagger() -> HTMLResponse:
-    return get_swagger_ui_html(
-        openapi_url=app.openapi_url,  # type: ignore [arg-type] # this is always a string
-        title=f"{app.title} - Swagger UI",
-        swagger_favicon_url="static/docs/invoke-favicon-docs.svg",
-    )
-
-
-@app.get("/redoc", include_in_schema=False)
-def overridden_redoc() -> HTMLResponse:
-    return get_redoc_html(
-        openapi_url=app.openapi_url,  # type: ignore [arg-type] # this is always a string
-        title=f"{app.title} - Redoc",
-        redoc_favicon_url="static/docs/invoke-favicon-docs.svg",
-    )
-
-
-web_root_path = Path(list(web_dir.__path__)[0])
-
-try:
-    app.mount("/", NoCacheStaticFiles(directory=Path(web_root_path, "dist"), html=True), name="ui")
-except RuntimeError:
-    logger.warn(f"No UI found at {web_root_path}/dist, skipping UI mount")
-app.mount(
-    "/static", NoCacheStaticFiles(directory=Path(web_root_path, "static/")), name="static"
-)  # docs favicon is in here
+    app.openapi = custom_openapi  # type: ignore [method-assign] # this is a valid assignment
 
 
 def check_cudnn(logger: logging.Logger) -> None:
@@ -244,27 +243,39 @@ def check_cudnn(logger: logging.Logger) -> None:
             )
 
 
+def find_port(port: int) -> int:
+    """Find a port not in use starting at given port"""
+    # Taken from https://waylonwalker.com/python-find-available-port/, thanks Waylon!
+    # https://github.com/WaylonWalker
+    with socket.socket(socket.AF_INET, socket.SOCK_STREAM) as s:
+        if s.connect_ex(("localhost", port)) == 0:
+            return find_port(port=port + 1)
+        else:
+            return port
+
+
+def init_dev_reload(logger: logging.Logger) -> None:
+    try:
+        import jurigged
+    except ImportError as e:
+        logger.error(
+            'Can\'t start `--dev_reload` because jurigged is not found; `pip install -e ".[dev]"` to include development dependencies.',
+            exc_info=e,
+        )
+    else:
+        jurigged.watch(logger=InvokeAILogger.get_logger(name="jurigged").info)
+
+
 def invoke_api() -> None:
-    def find_port(port: int) -> int:
-        """Find a port not in use starting at given port"""
-        # Taken from https://waylonwalker.com/python-find-available-port/, thanks Waylon!
-        # https://github.com/WaylonWalker
-        with socket.socket(socket.AF_INET, socket.SOCK_STREAM) as s:
-            if s.connect_ex(("localhost", port)) == 0:
-                return find_port(port=port + 1)
-            else:
-                return port
+    start = time.time()
+    app_config = get_config()
+    logger = InvokeAILogger.get_logger(config=app_config)
+
+    apply_monkeypatches()
+    fix_mimetypes()
 
     if app_config.dev_reload:
-        try:
-            import jurigged
-        except ImportError as e:
-            logger.error(
-                'Can\'t start `--dev_reload` because jurigged is not found; `pip install -e ".[dev]"` to include development dependencies.',
-                exc_info=e,
-            )
-        else:
-            jurigged.watch(logger=InvokeAILogger.get_logger(name="jurigged").info)
+        init_dev_reload(logger)
 
     port = find_port(app_config.port)
     if port != app_config.port:
@@ -272,6 +283,11 @@ def invoke_api() -> None:
 
     check_cudnn(logger)
 
+    torch_device_name = TorchDevice.get_torch_device_name()
+    logger.info(f"Using torch device: {torch_device_name}")
+
+    app = build_app(app_config, logger)
+
     # Start our own event loop for eventing usage
     loop = asyncio.new_event_loop()
     config = uvicorn.Config(
@@ -291,6 +307,7 @@ def invoke_api() -> None:
         log.handlers.clear()
         for ch in logger.handlers:
             log.addHandler(ch)
+    logger.info(f"API started in {time.time() - start:.2f} seconds")
 
     loop.run_until_complete(server.serve())
 

invokeai/app/invocations/controlnet_image_processors.py

@@ -35,16 +35,15 @@ from invokeai.app.invocations.model import ModelIdentifierField
 from invokeai.app.invocations.primitives import ImageOutput
 from invokeai.app.invocations.util import validate_begin_end_step, validate_weights
 from invokeai.app.services.shared.invocation_context import InvocationContext
-from invokeai.app.util.controlnet_utils import CONTROLNET_MODE_VALUES, CONTROLNET_RESIZE_VALUES, heuristic_resize
+from invokeai.app.util.controlnet_utils import CONTROLNET_MODE_VALUES, CONTROLNET_RESIZE_VALUES
 from invokeai.backend.image_util.canny import get_canny_edges
 from invokeai.backend.image_util.depth_anything import DepthAnythingDetector
 from invokeai.backend.image_util.dw_openpose import DWOpenposeDetector
 from invokeai.backend.image_util.hed import HEDProcessor
 from invokeai.backend.image_util.lineart import LineartProcessor
 from invokeai.backend.image_util.lineart_anime import LineartAnimeProcessor
-from invokeai.backend.image_util.util import np_to_pil, pil_to_np
 
-from .baseinvocation import BaseInvocation, BaseInvocationOutput, Classification, invocation, invocation_output
+from .baseinvocation import BaseInvocation, BaseInvocationOutput, invocation, invocation_output
 
 
 class ControlField(BaseModel):
@@ -165,13 +164,13 @@ class ImageProcessorInvocation(BaseInvocation, WithMetadata, WithBoard):
     title="Canny Processor",
     tags=["controlnet", "canny"],
     category="controlnet",
-    version="1.3.3",
+    version="1.3.2",
 )
 class CannyImageProcessorInvocation(ImageProcessorInvocation):
     """Canny edge detection for ControlNet"""
 
-    detect_resolution: int = InputField(default=512, ge=1, description=FieldDescriptions.detect_res)
-    image_resolution: int = InputField(default=512, ge=1, description=FieldDescriptions.image_res)
+    detect_resolution: int = InputField(default=512, ge=0, description=FieldDescriptions.detect_res)
+    image_resolution: int = InputField(default=512, ge=0, description=FieldDescriptions.image_res)
     low_threshold: int = InputField(
         default=100, ge=0, le=255, description="The low threshold of the Canny pixel gradient (0-255)"
     )
@@ -199,13 +198,13 @@ class CannyImageProcessorInvocation(ImageProcessorInvocation):
     title="HED (softedge) Processor",
     tags=["controlnet", "hed", "softedge"],
     category="controlnet",
-    version="1.2.3",
+    version="1.2.2",
 )
 class HedImageProcessorInvocation(ImageProcessorInvocation):
     """Applies HED edge detection to image"""
 
-    detect_resolution: int = InputField(default=512, ge=1, description=FieldDescriptions.detect_res)
-    image_resolution: int = InputField(default=512, ge=1, description=FieldDescriptions.image_res)
+    detect_resolution: int = InputField(default=512, ge=0, description=FieldDescriptions.detect_res)
+    image_resolution: int = InputField(default=512, ge=0, description=FieldDescriptions.image_res)
     # safe not supported in controlnet_aux v0.0.3
     # safe: bool = InputField(default=False, description=FieldDescriptions.safe_mode)
     scribble: bool = InputField(default=False, description=FieldDescriptions.scribble_mode)
@@ -228,13 +227,13 @@ class HedImageProcessorInvocation(ImageProcessorInvocation):
     title="Lineart Processor",
     tags=["controlnet", "lineart"],
     category="controlnet",
-    version="1.2.3",
+    version="1.2.2",
 )
 class LineartImageProcessorInvocation(ImageProcessorInvocation):
     """Applies line art processing to image"""
 
-    detect_resolution: int = InputField(default=512, ge=1, description=FieldDescriptions.detect_res)
-    image_resolution: int = InputField(default=512, ge=1, description=FieldDescriptions.image_res)
+    detect_resolution: int = InputField(default=512, ge=0, description=FieldDescriptions.detect_res)
+    image_resolution: int = InputField(default=512, ge=0, description=FieldDescriptions.image_res)
     coarse: bool = InputField(default=False, description="Whether to use coarse mode")
 
     def run_processor(self, image: Image.Image) -> Image.Image:
@@ -250,13 +249,13 @@ class LineartImageProcessorInvocation(ImageProcessorInvocation):
     title="Lineart Anime Processor",
     tags=["controlnet", "lineart", "anime"],
     category="controlnet",
-    version="1.2.3",
+    version="1.2.2",
 )
 class LineartAnimeImageProcessorInvocation(ImageProcessorInvocation):
     """Applies line art anime processing to image"""
 
-    detect_resolution: int = InputField(default=512, ge=1, description=FieldDescriptions.detect_res)
-    image_resolution: int = InputField(default=512, ge=1, description=FieldDescriptions.image_res)
+    detect_resolution: int = InputField(default=512, ge=0, description=FieldDescriptions.detect_res)
+    image_resolution: int = InputField(default=512, ge=0, description=FieldDescriptions.image_res)
 
     def run_processor(self, image: Image.Image) -> Image.Image:
         processor = LineartAnimeProcessor()
@@ -273,15 +272,15 @@ class LineartAnimeImageProcessorInvocation(ImageProcessorInvocation):
     title="Midas Depth Processor",
     tags=["controlnet", "midas"],
     category="controlnet",
-    version="1.2.4",
+    version="1.2.3",
 )
 class MidasDepthImageProcessorInvocation(ImageProcessorInvocation):
     """Applies Midas depth processing to image"""
 
     a_mult: float = InputField(default=2.0, ge=0, description="Midas parameter `a_mult` (a = a_mult * PI)")
     bg_th: float = InputField(default=0.1, ge=0, description="Midas parameter `bg_th`")
-    detect_resolution: int = InputField(default=512, ge=1, description=FieldDescriptions.detect_res)
-    image_resolution: int = InputField(default=512, ge=1, description=FieldDescriptions.image_res)
+    detect_resolution: int = InputField(default=512, ge=0, description=FieldDescriptions.detect_res)
+    image_resolution: int = InputField(default=512, ge=0, description=FieldDescriptions.image_res)
     # depth_and_normal not supported in controlnet_aux v0.0.3
     # depth_and_normal: bool = InputField(default=False, description="whether to use depth and normal mode")
 
@@ -304,13 +303,13 @@ class MidasDepthImageProcessorInvocation(ImageProcessorInvocation):
     title="Normal BAE Processor",
     tags=["controlnet"],
     category="controlnet",
-    version="1.2.3",
+    version="1.2.2",
 )
 class NormalbaeImageProcessorInvocation(ImageProcessorInvocation):
     """Applies NormalBae processing to image"""
 
-    detect_resolution: int = InputField(default=512, ge=1, description=FieldDescriptions.detect_res)
-    image_resolution: int = InputField(default=512, ge=1, description=FieldDescriptions.image_res)
+    detect_resolution: int = InputField(default=512, ge=0, description=FieldDescriptions.detect_res)
+    image_resolution: int = InputField(default=512, ge=0, description=FieldDescriptions.image_res)
 
     def run_processor(self, image):
         normalbae_processor = NormalBaeDetector.from_pretrained("lllyasviel/Annotators")
@@ -321,13 +320,13 @@ class NormalbaeImageProcessorInvocation(ImageProcessorInvocation):
 
 
 @invocation(
-    "mlsd_image_processor", title="MLSD Processor", tags=["controlnet", "mlsd"], category="controlnet", version="1.2.3"
+    "mlsd_image_processor", title="MLSD Processor", tags=["controlnet", "mlsd"], category="controlnet", version="1.2.2"
 )
 class MlsdImageProcessorInvocation(ImageProcessorInvocation):
     """Applies MLSD processing to image"""
 
-    detect_resolution: int = InputField(default=512, ge=1, description=FieldDescriptions.detect_res)
-    image_resolution: int = InputField(default=512, ge=1, description=FieldDescriptions.image_res)
+    detect_resolution: int = InputField(default=512, ge=0, description=FieldDescriptions.detect_res)
+    image_resolution: int = InputField(default=512, ge=0, description=FieldDescriptions.image_res)
     thr_v: float = InputField(default=0.1, ge=0, description="MLSD parameter `thr_v`")
     thr_d: float = InputField(default=0.1, ge=0, description="MLSD parameter `thr_d`")
 
@@ -344,13 +343,13 @@ class MlsdImageProcessorInvocation(ImageProcessorInvocation):
 
 
 @invocation(
-    "pidi_image_processor", title="PIDI Processor", tags=["controlnet", "pidi"], category="controlnet", version="1.2.3"
+    "pidi_image_processor", title="PIDI Processor", tags=["controlnet", "pidi"], category="controlnet", version="1.2.2"
 )
 class PidiImageProcessorInvocation(ImageProcessorInvocation):
     """Applies PIDI processing to image"""
 
-    detect_resolution: int = InputField(default=512, ge=1, description=FieldDescriptions.detect_res)
-    image_resolution: int = InputField(default=512, ge=1, description=FieldDescriptions.image_res)
+    detect_resolution: int = InputField(default=512, ge=0, description=FieldDescriptions.detect_res)
+    image_resolution: int = InputField(default=512, ge=0, description=FieldDescriptions.image_res)
     safe: bool = InputField(default=False, description=FieldDescriptions.safe_mode)
     scribble: bool = InputField(default=False, description=FieldDescriptions.scribble_mode)
 
@@ -371,13 +370,13 @@ class PidiImageProcessorInvocation(ImageProcessorInvocation):
     title="Content Shuffle Processor",
     tags=["controlnet", "contentshuffle"],
     category="controlnet",
-    version="1.2.3",
+    version="1.2.2",
 )
 class ContentShuffleImageProcessorInvocation(ImageProcessorInvocation):
     """Applies content shuffle processing to image"""
 
-    detect_resolution: int = InputField(default=512, ge=1, description=FieldDescriptions.detect_res)
-    image_resolution: int = InputField(default=512, ge=1, description=FieldDescriptions.image_res)
+    detect_resolution: int = InputField(default=512, ge=0, description=FieldDescriptions.detect_res)
+    image_resolution: int = InputField(default=512, ge=0, description=FieldDescriptions.image_res)
     h: int = InputField(default=512, ge=0, description="Content shuffle `h` parameter")
     w: int = InputField(default=512, ge=0, description="Content shuffle `w` parameter")
     f: int = InputField(default=256, ge=0, description="Content shuffle `f` parameter")
@@ -401,7 +400,7 @@ class ContentShuffleImageProcessorInvocation(ImageProcessorInvocation):
     title="Zoe (Depth) Processor",
     tags=["controlnet", "zoe", "depth"],
     category="controlnet",
-    version="1.2.3",
+    version="1.2.2",
 )
 class ZoeDepthImageProcessorInvocation(ImageProcessorInvocation):
     """Applies Zoe depth processing to image"""
@@ -417,15 +416,15 @@ class ZoeDepthImageProcessorInvocation(ImageProcessorInvocation):
     title="Mediapipe Face Processor",
     tags=["controlnet", "mediapipe", "face"],
     category="controlnet",
-    version="1.2.4",
+    version="1.2.3",
 )
 class MediapipeFaceProcessorInvocation(ImageProcessorInvocation):
     """Applies mediapipe face processing to image"""
 
     max_faces: int = InputField(default=1, ge=1, description="Maximum number of faces to detect")
     min_confidence: float = InputField(default=0.5, ge=0, le=1, description="Minimum confidence for face detection")
-    detect_resolution: int = InputField(default=512, ge=1, description=FieldDescriptions.detect_res)
-    image_resolution: int = InputField(default=512, ge=1, description=FieldDescriptions.image_res)
+    detect_resolution: int = InputField(default=512, ge=0, description=FieldDescriptions.detect_res)
+    image_resolution: int = InputField(default=512, ge=0, description=FieldDescriptions.image_res)
 
     def run_processor(self, image):
         mediapipe_face_processor = MediapipeFaceDetector()
@@ -444,7 +443,7 @@ class MediapipeFaceProcessorInvocation(ImageProcessorInvocation):
     title="Leres (Depth) Processor",
     tags=["controlnet", "leres", "depth"],
     category="controlnet",
-    version="1.2.3",
+    version="1.2.2",
 )
 class LeresImageProcessorInvocation(ImageProcessorInvocation):
     """Applies leres processing to image"""
@@ -452,8 +451,8 @@ class LeresImageProcessorInvocation(ImageProcessorInvocation):
     thr_a: float = InputField(default=0, description="Leres parameter `thr_a`")
     thr_b: float = InputField(default=0, description="Leres parameter `thr_b`")
     boost: bool = InputField(default=False, description="Whether to use boost mode")
-    detect_resolution: int = InputField(default=512, ge=1, description=FieldDescriptions.detect_res)
-    image_resolution: int = InputField(default=512, ge=1, description=FieldDescriptions.image_res)
+    detect_resolution: int = InputField(default=512, ge=0, description=FieldDescriptions.detect_res)
+    image_resolution: int = InputField(default=512, ge=0, description=FieldDescriptions.image_res)
 
     def run_processor(self, image):
         leres_processor = LeresDetector.from_pretrained("lllyasviel/Annotators")
@@ -473,7 +472,7 @@ class LeresImageProcessorInvocation(ImageProcessorInvocation):
     title="Tile Resample Processor",
     tags=["controlnet", "tile"],
     category="controlnet",
-    version="1.2.3",
+    version="1.2.2",
 )
 class TileResamplerProcessorInvocation(ImageProcessorInvocation):
     """Tile resampler processor"""
@@ -513,13 +512,13 @@ class TileResamplerProcessorInvocation(ImageProcessorInvocation):
     title="Segment Anything Processor",
     tags=["controlnet", "segmentanything"],
     category="controlnet",
-    version="1.2.4",
+    version="1.2.3",
 )
 class SegmentAnythingProcessorInvocation(ImageProcessorInvocation):
     """Applies segment anything processing to image"""
 
-    detect_resolution: int = InputField(default=512, ge=1, description=FieldDescriptions.detect_res)
-    image_resolution: int = InputField(default=512, ge=1, description=FieldDescriptions.image_res)
+    detect_resolution: int = InputField(default=512, ge=0, description=FieldDescriptions.detect_res)
+    image_resolution: int = InputField(default=512, ge=0, description=FieldDescriptions.image_res)
 
     def run_processor(self, image):
         # segment_anything_processor = SamDetector.from_pretrained("ybelkada/segment-anything", subfolder="checkpoints")
@@ -560,12 +559,12 @@ class SamDetectorReproducibleColors(SamDetector):
     title="Color Map Processor",
     tags=["controlnet"],
     category="controlnet",
-    version="1.2.3",
+    version="1.2.2",
 )
 class ColorMapImageProcessorInvocation(ImageProcessorInvocation):
     """Generates a color map from the provided image"""
 
-    color_map_tile_size: int = InputField(default=64, ge=1, description=FieldDescriptions.tile_size)
+    color_map_tile_size: int = InputField(default=64, ge=0, description=FieldDescriptions.tile_size)
 
     def run_processor(self, image: Image.Image):
         np_image = np.array(image, dtype=np.uint8)
@@ -592,7 +591,7 @@ DEPTH_ANYTHING_MODEL_SIZES = Literal["large", "base", "small"]
     title="Depth Anything Processor",
     tags=["controlnet", "depth", "depth anything"],
     category="controlnet",
-    version="1.1.2",
+    version="1.1.1",
 )
 class DepthAnythingImageProcessorInvocation(ImageProcessorInvocation):
     """Generates a depth map based on the Depth Anything algorithm"""
@@ -600,7 +599,7 @@ class DepthAnythingImageProcessorInvocation(ImageProcessorInvocation):
     model_size: DEPTH_ANYTHING_MODEL_SIZES = InputField(
         default="small", description="The size of the depth model to use"
     )
-    resolution: int = InputField(default=512, ge=1, description=FieldDescriptions.image_res)
+    resolution: int = InputField(default=512, ge=64, multiple_of=64, description=FieldDescriptions.image_res)
 
     def run_processor(self, image: Image.Image):
         depth_anything_detector = DepthAnythingDetector()
@@ -615,7 +614,7 @@ class DepthAnythingImageProcessorInvocation(ImageProcessorInvocation):
     title="DW Openpose Image Processor",
     tags=["controlnet", "dwpose", "openpose"],
     category="controlnet",
-    version="1.1.1",
+    version="1.1.0",
 )
 class DWOpenposeImageProcessorInvocation(ImageProcessorInvocation):
     """Generates an openpose pose from an image using DWPose"""
@@ -623,7 +622,7 @@ class DWOpenposeImageProcessorInvocation(ImageProcessorInvocation):
     draw_body: bool = InputField(default=True)
     draw_face: bool = InputField(default=False)
     draw_hands: bool = InputField(default=False)
-    image_resolution: int = InputField(default=512, ge=1, description=FieldDescriptions.image_res)
+    image_resolution: int = InputField(default=512, ge=0, description=FieldDescriptions.image_res)
 
     def run_processor(self, image: Image.Image):
         dw_openpose = DWOpenposeDetector()
@@ -635,27 +634,3 @@ class DWOpenposeImageProcessorInvocation(ImageProcessorInvocation):
             resolution=self.image_resolution,
         )
         return processed_image
-
-
-@invocation(
-    "heuristic_resize",
-    title="Heuristic Resize",
-    tags=["image, controlnet"],
-    category="image",
-    version="1.0.1",
-    classification=Classification.Prototype,
-)
-class HeuristicResizeInvocation(BaseInvocation):
-    """Resize an image using a heuristic method. Preserves edge maps."""
-
-    image: ImageField = InputField(description="The image to resize")
-    width: int = InputField(default=512, ge=1, description="The width to resize to (px)")
-    height: int = InputField(default=512, ge=1, description="The height to resize to (px)")
-
-    def invoke(self, context: InvocationContext) -> ImageOutput:
-        image = context.images.get_pil(self.image.image_name, "RGB")
-        np_img = pil_to_np(image)
-        np_resized = heuristic_resize(np_img, (self.width, self.height))
-        resized = np_to_pil(np_resized)
-        image_dto = context.images.save(image=resized)
-        return ImageOutput.build(image_dto)

invokeai/app/invocations/latent.py

@@ -3,7 +3,7 @@ import inspect
 import math
 from contextlib import ExitStack
 from functools import singledispatchmethod
-from typing import Any, Dict, Iterator, List, Literal, Optional, Tuple, Union
+from typing import Any, Iterator, List, Literal, Optional, Tuple, Union
 
 import einops
 import numpy as np
@@ -11,6 +11,7 @@ import numpy.typing as npt
 import torch
 import torchvision
 import torchvision.transforms as T
+from diffusers import AutoencoderKL, AutoencoderTiny
 from diffusers.configuration_utils import ConfigMixin
 from diffusers.image_processor import VaeImageProcessor
 from diffusers.models.adapter import T2IAdapter
@@ -20,12 +21,9 @@ from diffusers.models.attention_processor import (
     LoRAXFormersAttnProcessor,
     XFormersAttnProcessor,
 )
-from diffusers.models.autoencoders.autoencoder_kl import AutoencoderKL
-from diffusers.models.autoencoders.autoencoder_tiny import AutoencoderTiny
 from diffusers.models.unets.unet_2d_condition import UNet2DConditionModel
-from diffusers.schedulers.scheduling_dpmsolver_sde import DPMSolverSDEScheduler
-from diffusers.schedulers.scheduling_tcd import TCDScheduler
-from diffusers.schedulers.scheduling_utils import SchedulerMixin as Scheduler
+from diffusers.schedulers import DPMSolverSDEScheduler
+from diffusers.schedulers import SchedulerMixin as Scheduler
 from PIL import Image, ImageFilter
 from pydantic import field_validator
 from torchvision.transforms.functional import resize as tv_resize
@@ -343,7 +341,7 @@ class DenoiseLatentsInvocation(BaseInvocation):
     )
     steps: int = InputField(default=10, gt=0, description=FieldDescriptions.steps)
     cfg_scale: Union[float, List[float]] = InputField(
-        default=7.5, description=FieldDescriptions.cfg_scale, title="CFG Scale"
+        default=7.5, ge=1, description=FieldDescriptions.cfg_scale, title="CFG Scale"
     )
     denoising_start: float = InputField(
         default=0.0,
@@ -523,10 +521,9 @@ class DenoiseLatentsInvocation(BaseInvocation):
             )
 
         if is_sdxl:
-            return (
-                SDXLConditioningInfo(embeds=text_embedding, pooled_embeds=pooled_embedding, add_time_ids=add_time_ids),
-                regions,
-            )
+            return SDXLConditioningInfo(
+                embeds=text_embedding, pooled_embeds=pooled_embedding, add_time_ids=add_time_ids
+            ), regions
         return BasicConditioningInfo(embeds=text_embedding), regions
 
     def get_conditioning_data(
@@ -566,11 +563,6 @@ class DenoiseLatentsInvocation(BaseInvocation):
             dtype=unet.dtype,
         )
 
-        if isinstance(self.cfg_scale, list):
-            assert (
-                len(self.cfg_scale) == self.steps
-            ), "cfg_scale (list) must have the same length as the number of steps"
-
         conditioning_data = TextConditioningData(
             uncond_text=uncond_text_embedding,
             cond_text=cond_text_embedding,
@@ -828,7 +820,7 @@ class DenoiseLatentsInvocation(BaseInvocation):
         denoising_start: float,
         denoising_end: float,
         seed: int,
-    ) -> Tuple[int, List[int], int, Dict[str, Any]]:
+    ) -> Tuple[int, List[int], int]:
         assert isinstance(scheduler, ConfigMixin)
         if scheduler.config.get("cpu_only", False):
             scheduler.set_timesteps(steps, device="cpu")
@@ -856,15 +848,13 @@ class DenoiseLatentsInvocation(BaseInvocation):
         timesteps = timesteps[t_start_idx : t_start_idx + t_end_idx]
         num_inference_steps = len(timesteps) // scheduler.order
 
-        scheduler_step_kwargs: Dict[str, Any] = {}
+        scheduler_step_kwargs = {}
         scheduler_step_signature = inspect.signature(scheduler.step)
         if "generator" in scheduler_step_signature.parameters:
             # At some point, someone decided that schedulers that accept a generator should use the original seed with
             # all bits flipped. I don't know the original rationale for this, but now we must keep it like this for
             # reproducibility.
-            scheduler_step_kwargs.update({"generator": torch.Generator(device=device).manual_seed(seed ^ 0xFFFFFFFF)})
-        if isinstance(scheduler, TCDScheduler):
-            scheduler_step_kwargs.update({"eta": 1.0})
+            scheduler_step_kwargs = {"generator": torch.Generator(device=device).manual_seed(seed ^ 0xFFFFFFFF)}
 
         return num_inference_steps, timesteps, init_timestep, scheduler_step_kwargs
 

invokeai/app/services/download/download_default.py

@@ -318,8 +318,10 @@ class DownloadQueueService(DownloadQueueServiceBase):
         in_progress_path.rename(job.download_path)
 
     def _validate_filename(self, directory: str, filename: str) -> bool:
-        pc_name_max = get_pc_name_max(directory)
-        pc_path_max = get_pc_path_max(directory)
+        pc_name_max = os.pathconf(directory, "PC_NAME_MAX") if hasattr(os, "pathconf") else 260  # hardcoded for windows
+        pc_path_max = (
+            os.pathconf(directory, "PC_PATH_MAX") if hasattr(os, "pathconf") else 32767
+        )  # hardcoded for windows with long names enabled
         if "/" in filename:
             return False
         if filename.startswith(".."):
@@ -417,26 +419,6 @@ class DownloadQueueService(DownloadQueueServiceBase):
             self._logger.warning(excp)
 
 
-def get_pc_name_max(directory: str) -> int:
-    if hasattr(os, "pathconf"):
-        try:
-            return os.pathconf(directory, "PC_NAME_MAX")
-        except OSError:
-            # macOS w/ external drives raise OSError
-            pass
-    return 260  # hardcoded for windows
-
-
-def get_pc_path_max(directory: str) -> int:
-    if hasattr(os, "pathconf"):
-        try:
-            return os.pathconf(directory, "PC_PATH_MAX")
-        except OSError:
-            # some platforms may not have this value
-            pass
-    return 32767  # hardcoded for windows with long names enabled
-
-
 # Example on_progress event handler to display a TQDM status bar
 # Activate with:
 #   download_service.download(DownloadJob('http://foo.bar/baz', '/tmp', on_progress=TqdmProgress().update))

invokeai/backend/image_util/util.py

@@ -144,8 +144,10 @@ def resize_image_to_resolution(input_image: np.ndarray, resolution: int) -> np.n
     h = float(input_image.shape[0])
     w = float(input_image.shape[1])
     scaling_factor = float(resolution) / min(h, w)
-    h = int(h * scaling_factor)
-    w = int(w * scaling_factor)
+    h *= scaling_factor
+    w *= scaling_factor
+    h = int(np.round(h / 64.0)) * 64
+    w = int(np.round(w / 64.0)) * 64
     if scaling_factor > 1:
         return cv2.resize(input_image, (w, h), interpolation=cv2.INTER_LANCZOS4)
     else:

invokeai/backend/model_manager/probe.py

@@ -51,7 +51,6 @@ LEGACY_CONFIGS: Dict[BaseModelType, Dict[ModelVariantType, Union[str, Dict[Sched
     },
     BaseModelType.StableDiffusionXL: {
         ModelVariantType.Normal: "sd_xl_base.yaml",
-        ModelVariantType.Inpaint: "sd_xl_inpaint.yaml",
     },
     BaseModelType.StableDiffusionXLRefiner: {
         ModelVariantType.Normal: "sd_xl_refiner.yaml",

invokeai/backend/stable_diffusion/schedulers/schedulers.py

@@ -13,7 +13,6 @@ from diffusers import (
     LCMScheduler,
     LMSDiscreteScheduler,
     PNDMScheduler,
-    TCDScheduler,
     UniPCMultistepScheduler,
 )
 
@@ -41,5 +40,4 @@ SCHEDULER_MAP = {
     "dpmpp_sde_k": (DPMSolverSDEScheduler, {"use_karras_sigmas": True, "noise_sampler_seed": 0}),
     "unipc": (UniPCMultistepScheduler, {"cpu_only": True}),
     "lcm": (LCMScheduler, {}),
-    "tcd": (TCDScheduler, {}),
 }

invokeai/configs/stable-diffusion/sd_xl_inpaint.yaml

@@ -1,98 +0,0 @@
-model:
-  target: sgm.models.diffusion.DiffusionEngine
-  params:
-    scale_factor: 0.13025
-    disable_first_stage_autocast: True
-
-    denoiser_config:
-      target: sgm.modules.diffusionmodules.denoiser.DiscreteDenoiser
-      params:
-        num_idx: 1000
-
-        weighting_config:
-          target: sgm.modules.diffusionmodules.denoiser_weighting.EpsWeighting
-        scaling_config:
-          target: sgm.modules.diffusionmodules.denoiser_scaling.EpsScaling
-        discretization_config:
-          target: sgm.modules.diffusionmodules.discretizer.LegacyDDPMDiscretization
-
-    network_config:
-      target: sgm.modules.diffusionmodules.openaimodel.UNetModel
-      params:
-        adm_in_channels: 2816
-        num_classes: sequential
-        use_checkpoint: True
-        in_channels: 9
-        out_channels: 4
-        model_channels: 320
-        attention_resolutions: [4, 2]
-        num_res_blocks: 2
-        channel_mult: [1, 2, 4]
-        num_head_channels: 64
-        use_spatial_transformer: True
-        use_linear_in_transformer: True
-        transformer_depth: [1, 2, 10]  # note: the first is unused (due to attn_res starting at 2) 32, 16, 8 --> 64, 32, 16
-        context_dim: 2048
-        spatial_transformer_attn_type: softmax-xformers
-        legacy: False
-
-    conditioner_config:
-      target: sgm.modules.GeneralConditioner
-      params:
-        emb_models:
-          # crossattn cond
-          - is_trainable: False
-            input_key: txt
-            target: sgm.modules.encoders.modules.FrozenCLIPEmbedder
-            params:
-              layer: hidden
-              layer_idx: 11
-          # crossattn and vector cond
-          - is_trainable: False
-            input_key: txt
-            target: sgm.modules.encoders.modules.FrozenOpenCLIPEmbedder2
-            params:
-              arch: ViT-bigG-14
-              version: laion2b_s39b_b160k
-              freeze: True
-              layer: penultimate
-              always_return_pooled: True
-              legacy: False
-          # vector cond
-          - is_trainable: False
-            input_key: original_size_as_tuple
-            target: sgm.modules.encoders.modules.ConcatTimestepEmbedderND
-            params:
-              outdim: 256  # multiplied by two
-          # vector cond
-          - is_trainable: False
-            input_key: crop_coords_top_left
-            target: sgm.modules.encoders.modules.ConcatTimestepEmbedderND
-            params:
-              outdim: 256  # multiplied by two
-          # vector cond
-          - is_trainable: False
-            input_key: target_size_as_tuple
-            target: sgm.modules.encoders.modules.ConcatTimestepEmbedderND
-            params:
-              outdim: 256  # multiplied by two
-
-    first_stage_config:
-      target: sgm.models.autoencoder.AutoencoderKLInferenceWrapper
-      params:
-        embed_dim: 4
-        monitor: val/rec_loss
-        ddconfig:
-          attn_type: vanilla-xformers
-          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

invokeai/frontend/web/package.json

@@ -25,7 +25,7 @@
     "typegen": "node scripts/typegen.js",
     "preview": "vite preview",
     "lint:knip": "knip",
-    "lint:dpdm": "dpdm --no-warning --no-tree --transform --exit-code circular:1 src/main.tsx",
+    "lint:dpdm": "dpdm --no-warning --no-tree --transform --exit-code circular:0 src/main.tsx",
     "lint:eslint": "eslint --max-warnings=0 .",
     "lint:prettier": "prettier --check .",
     "lint:tsc": "tsc --noEmit",
@@ -52,48 +52,47 @@
   },
   "dependencies": {
     "@chakra-ui/react-use-size": "^2.1.0",
-    "@dagrejs/dagre": "^1.1.2",
-    "@dagrejs/graphlib": "^2.2.2",
+    "@dagrejs/dagre": "^1.1.1",
+    "@dagrejs/graphlib": "^2.2.1",
     "@dnd-kit/core": "^6.1.0",
     "@dnd-kit/sortable": "^8.0.0",
     "@dnd-kit/utilities": "^3.2.2",
-    "@fontsource-variable/inter": "^5.0.18",
-    "@invoke-ai/ui-library": "^0.0.25",
+    "@fontsource-variable/inter": "^5.0.17",
+    "@invoke-ai/ui-library": "^0.0.21",
     "@nanostores/react": "^0.7.2",
-    "@reduxjs/toolkit": "2.2.3",
+    "@reduxjs/toolkit": "2.2.2",
     "@roarr/browser-log-writer": "^1.3.0",
     "chakra-react-select": "^4.7.6",
     "compare-versions": "^6.1.0",
     "dateformat": "^5.0.3",
-    "fracturedjsonjs": "^4.0.1",
-    "framer-motion": "^11.1.8",
-    "i18next": "^23.11.3",
-    "i18next-http-backend": "^2.5.1",
+    "framer-motion": "^11.0.22",
+    "i18next": "^23.10.1",
+    "i18next-http-backend": "^2.5.0",
     "idb-keyval": "^6.2.1",
     "jsondiffpatch": "^0.6.0",
     "konva": "^9.3.6",
     "lodash-es": "^4.17.21",
-    "nanostores": "^0.10.3",
+    "nanostores": "^0.10.0",
     "new-github-issue-url": "^1.0.0",
-    "overlayscrollbars": "^2.7.3",
-    "overlayscrollbars-react": "^0.5.6",
+    "overlayscrollbars": "^2.6.1",
+    "overlayscrollbars-react": "^0.5.5",
     "query-string": "^9.0.0",
-    "react": "^18.3.1",
+    "react": "^18.2.0",
     "react-colorful": "^5.6.1",
-    "react-dom": "^18.3.1",
+    "react-dom": "^18.2.0",
     "react-dropzone": "^14.2.3",
     "react-error-boundary": "^4.0.13",
-    "react-hook-form": "^7.51.4",
+    "react-hook-form": "^7.51.2",
     "react-hotkeys-hook": "4.5.0",
-    "react-i18next": "^14.1.1",
-    "react-icons": "^5.2.0",
+    "react-i18next": "^14.1.0",
+    "react-icons": "^5.0.1",
     "react-konva": "^18.2.10",
-    "react-redux": "9.1.2",
-    "react-resizable-panels": "^2.0.19",
+    "react-redux": "9.1.0",
+    "react-resizable-panels": "^2.0.16",
     "react-select": "5.8.0",
     "react-use": "^17.5.0",
-    "react-virtuoso": "^4.7.10",
-    "reactflow": "^11.11.3",
+    "react-virtuoso": "^4.7.5",
+    "reactflow": "^11.10.4",
     "redux-dynamic-middlewares": "^2.2.0",
     "redux-remember": "^5.1.0",
     "redux-undo": "^1.1.0",
@@ -102,11 +101,10 @@
     "serialize-error": "^11.0.3",
     "socket.io-client": "^4.7.5",
     "use-debounce": "^10.0.0",
-    "use-device-pixel-ratio": "^1.1.2",
     "use-image": "^1.1.1",
     "uuid": "^9.0.1",
-    "zod": "^3.23.6",
-    "zod-validation-error": "^3.2.0"
+    "zod": "^3.22.4",
+    "zod-validation-error": "^3.0.3"
   },
   "peerDependencies": {
     "@chakra-ui/react": "^2.8.2",
@@ -117,19 +115,19 @@
   "devDependencies": {
     "@invoke-ai/eslint-config-react": "^0.0.14",
     "@invoke-ai/prettier-config-react": "^0.0.7",
-    "@storybook/addon-essentials": "^8.0.10",
-    "@storybook/addon-interactions": "^8.0.10",
-    "@storybook/addon-links": "^8.0.10",
-    "@storybook/addon-storysource": "^8.0.10",
-    "@storybook/manager-api": "^8.0.10",
-    "@storybook/react": "^8.0.10",
-    "@storybook/react-vite": "^8.0.10",
-    "@storybook/theming": "^8.0.10",
+    "@storybook/addon-essentials": "^8.0.4",
+    "@storybook/addon-interactions": "^8.0.4",
+    "@storybook/addon-links": "^8.0.4",
+    "@storybook/addon-storysource": "^8.0.4",
+    "@storybook/manager-api": "^8.0.4",
+    "@storybook/react": "^8.0.4",
+    "@storybook/react-vite": "^8.0.4",
+    "@storybook/theming": "^8.0.4",
     "@types/dateformat": "^5.0.2",
     "@types/lodash-es": "^4.17.12",
-    "@types/node": "^20.12.10",
-    "@types/react": "^18.3.1",
-    "@types/react-dom": "^18.3.0",
+    "@types/node": "^20.11.30",
+    "@types/react": "^18.2.73",
+    "@types/react-dom": "^18.2.22",
     "@types/uuid": "^9.0.8",
     "@vitejs/plugin-react-swc": "^3.6.0",
     "concurrently": "^8.2.2",
@@ -137,20 +135,20 @@
     "eslint": "^8.57.0",
     "eslint-plugin-i18next": "^6.0.3",
     "eslint-plugin-path": "^1.3.0",
-    "knip": "^5.12.3",
+    "knip": "^5.6.1",
     "openapi-types": "^12.1.3",
     "openapi-typescript": "^6.7.5",
     "prettier": "^3.2.5",
     "rollup-plugin-visualizer": "^5.12.0",
-    "storybook": "^8.0.10",
+    "storybook": "^8.0.4",
     "ts-toolbelt": "^9.6.0",
     "tsafe": "^1.6.6",
-    "typescript": "^5.4.5",
-    "vite": "^5.2.11",
-    "vite-plugin-css-injected-by-js": "^3.5.1",
-    "vite-plugin-dts": "^3.9.1",
+    "typescript": "^5.4.3",
+    "vite": "^5.2.6",
+    "vite-plugin-css-injected-by-js": "^3.5.0",
+    "vite-plugin-dts": "^3.8.0",
     "vite-plugin-eslint": "^1.8.1",
     "vite-tsconfig-paths": "^4.3.2",
-    "vitest": "^1.6.0"
+    "vitest": "^1.4.0"
   }
 }

invokeai/frontend/web/public/locales/en.json

@@ -88,13 +88,11 @@
         "negativePrompt": "Negative Prompt",
         "discordLabel": "Discord",
         "dontAskMeAgain": "Don't ask me again",
-        "editor": "Editor",
         "error": "Error",
         "file": "File",
         "folder": "Folder",
         "format": "format",
         "githubLabel": "Github",
-        "goTo": "Go to",
         "hotkeysLabel": "Hotkeys",
         "imageFailedToLoad": "Unable to Load Image",
         "img2img": "Image To Image",
@@ -142,11 +140,7 @@
         "blue": "Blue",
         "alpha": "Alpha",
         "selected": "Selected",
-        "tab": "Tab",
-        "viewing": "Viewing",
-        "viewingDesc": "Review images in a large gallery view",
-        "editing": "Editing",
-        "editingDesc": "Edit on the Control Layers canvas"
+        "viewer": "Viewer"
     },
     "controlnet": {
         "controlAdapter_one": "Control Adapter",
@@ -162,7 +156,6 @@
         "balanced": "Balanced",
         "base": "Base",
         "beginEndStepPercent": "Begin / End Step Percentage",
-        "beginEndStepPercentShort": "Begin/End %",
         "bgth": "bg_th",
         "canny": "Canny",
         "cannyDescription": "Canny edge detection",
@@ -231,11 +224,10 @@
         "composition": "Composition Only",
         "safe": "Safe",
         "saveControlImage": "Save Control Image",
-        "scribble": "Scribble",
+        "scribble": "scribble",
         "selectModel": "Select a model",
         "selectCLIPVisionModel": "Select a CLIP Vision model",
-        "setControlImageDimensions": "Copy size to W/H (optimize for model)",
-        "setControlImageDimensionsForce": "Copy size to W/H (ignore model)",
+        "setControlImageDimensions": "Set Control Image Dimensions To W/H",
         "showAdvanced": "Show Advanced",
         "small": "Small",
         "toggleControlNet": "Toggle this ControlNet",
@@ -590,10 +582,6 @@
         "upscale": {
             "desc": "Upscale the current image",
             "title": "Upscale"
-        },
-        "toggleViewer": {
-            "desc": "Switches between the Image Viewer and workspace for the current tab.",
-            "title": "Toggle Image Viewer"
         }
     },
     "metadata": {
@@ -927,7 +915,6 @@
             "missingInputForField": "{{nodeLabel}} -> {{fieldLabel}} missing input",
             "missingNodeTemplate": "Missing node template",
             "noControlImageForControlAdapter": "Control Adapter #{{number}} has no control image",
-            "imageNotProcessedForControlAdapter": "Control Adapter #{{number}}'s image is not processed",
             "noInitialImageSelected": "No initial image selected",
             "noModelForControlAdapter": "Control Adapter #{{number}} has no model selected.",
             "incompatibleBaseModelForControlAdapter": "Control Adapter #{{number}} model is incompatible with main model.",
@@ -938,12 +925,10 @@
         },
         "maskBlur": "Mask Blur",
         "negativePromptPlaceholder": "Negative Prompt",
-        "globalNegativePromptPlaceholder": "Global Negative Prompt",
         "noiseThreshold": "Noise Threshold",
         "patchmatchDownScaleSize": "Downscale",
         "perlinNoise": "Perlin Noise",
         "positivePromptPlaceholder": "Positive Prompt",
-        "globalPositivePromptPlaceholder": "Global Positive Prompt",
         "iterations": "Iterations",
         "iterationsWithCount_one": "{{count}} Iteration",
         "iterationsWithCount_other": "{{count}} Iterations",
@@ -1526,7 +1511,7 @@
     "app": {
         "storeNotInitialized": "Store is not initialized"
     },
-    "controlLayers": {
+    "regionalPrompts": {
         "deleteAll": "Delete All",
         "addLayer": "Add Layer",
         "moveToFront": "Move to Front",
@@ -1534,7 +1519,8 @@
         "moveForward": "Move Forward",
         "moveBackward": "Move Backward",
         "brushSize": "Brush Size",
-        "controlLayers": "Control Layers",
+        "regionalControl": "Regional Control (ALPHA)",
+        "enableRegionalPrompts": "Enable $t(regionalPrompts.regionalPrompts)",
         "globalMaskOpacity": "Global Mask Opacity",
         "autoNegative": "Auto Negative",
         "toggleVisibility": "Toggle Layer Visibility",
@@ -1545,35 +1531,6 @@
         "maskPreviewColor": "Mask Preview Color",
         "addPositivePrompt": "Add $t(common.positivePrompt)",
         "addNegativePrompt": "Add $t(common.negativePrompt)",
-        "addIPAdapter": "Add $t(common.ipAdapter)",
-        "regionalGuidance": "Regional Guidance",
-        "regionalGuidanceLayer": "$t(controlLayers.regionalGuidance) $t(unifiedCanvas.layer)",
-        "opacity": "Opacity",
-        "globalControlAdapter": "Global $t(controlnet.controlAdapter_one)",
-        "globalControlAdapterLayer": "Global $t(controlnet.controlAdapter_one) $t(unifiedCanvas.layer)",
-        "globalIPAdapter": "Global $t(common.ipAdapter)",
-        "globalIPAdapterLayer": "Global $t(common.ipAdapter) $t(unifiedCanvas.layer)",
-        "globalInitialImage": "Global Initial Image",
-        "globalInitialImageLayer": "$t(controlLayers.globalInitialImage) $t(unifiedCanvas.layer)",
-        "opacityFilter": "Opacity Filter",
-        "clearProcessor": "Clear Processor",
-        "resetProcessor": "Reset Processor to Defaults",
-        "noLayersAdded": "No Layers Added",
-        "layers_one": "Layer",
-        "layers_other": "Layers"
-    },
-    "ui": {
-        "tabs": {
-            "generation": "Generation",
-            "generationTab": "$t(ui.tabs.generation) $t(common.tab)",
-            "canvas": "Canvas",
-            "canvasTab": "$t(ui.tabs.canvas) $t(common.tab)",
-            "workflows": "Workflows",
-            "workflowsTab": "$t(ui.tabs.workflows) $t(common.tab)",
-            "models": "Models",
-            "modelsTab": "$t(ui.tabs.models) $t(common.tab)",
-            "queue": "Queue",
-            "queueTab": "$t(ui.tabs.queue) $t(common.tab)"
-        }
+        "addIPAdapter": "Add $t(common.ipAdapter)"
     }
 }

invokeai/frontend/web/src/app/logging/logger.ts

@@ -20,14 +20,15 @@ export type LoggerNamespace =
   | 'models'
   | 'config'
   | 'canvas'
-  | 'generation'
+  | 'txt2img'
+  | 'img2img'
   | 'nodes'
   | 'system'
   | 'socketio'
   | 'session'
   | 'queue'
   | 'dnd'
-  | 'controlLayers';
+  | 'regionalPrompts';
 
 export const logger = (namespace: LoggerNamespace) => $logger.get().child({ namespace });
 

invokeai/frontend/web/src/app/store/middleware/listenerMiddleware/index.ts

@@ -16,7 +16,6 @@ import { addCanvasMaskSavedToGalleryListener } from 'app/store/middleware/listen
 import { addCanvasMaskToControlNetListener } from 'app/store/middleware/listenerMiddleware/listeners/canvasMaskToControlNet';
 import { addCanvasMergedListener } from 'app/store/middleware/listenerMiddleware/listeners/canvasMerged';
 import { addCanvasSavedToGalleryListener } from 'app/store/middleware/listenerMiddleware/listeners/canvasSavedToGallery';
-import { addControlAdapterPreprocessor } from 'app/store/middleware/listenerMiddleware/listeners/controlAdapterPreprocessor';
 import { addControlNetAutoProcessListener } from 'app/store/middleware/listenerMiddleware/listeners/controlNetAutoProcess';
 import { addControlNetImageProcessedListener } from 'app/store/middleware/listenerMiddleware/listeners/controlNetImageProcessed';
 import { addEnqueueRequestedCanvasListener } from 'app/store/middleware/listenerMiddleware/listeners/enqueueRequestedCanvas';
@@ -32,6 +31,7 @@ import { addImagesStarredListener } from 'app/store/middleware/listenerMiddlewar
 import { addImagesUnstarredListener } from 'app/store/middleware/listenerMiddleware/listeners/imagesUnstarred';
 import { addImageToDeleteSelectedListener } from 'app/store/middleware/listenerMiddleware/listeners/imageToDeleteSelected';
 import { addImageUploadedFulfilledListener } from 'app/store/middleware/listenerMiddleware/listeners/imageUploaded';
+import { addInitialImageSelectedListener } from 'app/store/middleware/listenerMiddleware/listeners/initialImageSelected';
 import { addModelSelectedListener } from 'app/store/middleware/listenerMiddleware/listeners/modelSelected';
 import { addModelsLoadedListener } from 'app/store/middleware/listenerMiddleware/listeners/modelsLoaded';
 import { addDynamicPromptsListener } from 'app/store/middleware/listenerMiddleware/listeners/promptChanged';
@@ -72,6 +72,9 @@ const startAppListening = listenerMiddleware.startListening as AppStartListening
 // Image uploaded
 addImageUploadedFulfilledListener(startAppListening);
 
+// Image selected
+addInitialImageSelectedListener(startAppListening);
+
 // Image deleted
 addRequestedSingleImageDeletionListener(startAppListening);
 addDeleteBoardAndImagesFulfilledListener(startAppListening);
@@ -154,4 +157,3 @@ addUpscaleRequestedListener(startAppListening);
 addDynamicPromptsListener(startAppListening);
 
 addSetDefaultSettingsListener(startAppListening);
-addControlAdapterPreprocessor(startAppListening);

invokeai/frontend/web/src/app/store/middleware/listenerMiddleware/listeners/boardAndImagesDeleted.ts

@@ -1,9 +1,9 @@
 import type { AppStartListening } from 'app/store/middleware/listenerMiddleware';
 import { resetCanvas } from 'features/canvas/store/canvasSlice';
 import { controlAdaptersReset } from 'features/controlAdapters/store/controlAdaptersSlice';
-import { allLayersDeleted } from 'features/controlLayers/store/controlLayersSlice';
 import { getImageUsage } from 'features/deleteImageModal/store/selectors';
 import { nodeEditorReset } from 'features/nodes/store/nodesSlice';
+import { clearInitialImage } from 'features/parameters/store/generationSlice';
 import { imagesApi } from 'services/api/endpoints/images';
 
 export const addDeleteBoardAndImagesFulfilledListener = (startAppListening: AppStartListening) => {
@@ -14,14 +14,19 @@ export const addDeleteBoardAndImagesFulfilledListener = (startAppListening: AppS
 
       // Remove all deleted images from the UI
 
+      let wasInitialImageReset = false;
       let wasCanvasReset = false;
       let wasNodeEditorReset = false;
       let wereControlAdaptersReset = false;
-      let wereControlLayersReset = false;
 
-      const { canvas, nodes, controlAdapters, controlLayers } = getState();
+      const { generation, canvas, nodes, controlAdapters } = getState();
       deleted_images.forEach((image_name) => {
-        const imageUsage = getImageUsage(canvas, nodes, controlAdapters, controlLayers.present, image_name);
+        const imageUsage = getImageUsage(generation, canvas, nodes, controlAdapters, image_name);
+
+        if (imageUsage.isInitialImage && !wasInitialImageReset) {
+          dispatch(clearInitialImage());
+          wasInitialImageReset = true;
+        }
 
         if (imageUsage.isCanvasImage && !wasCanvasReset) {
           dispatch(resetCanvas());
@@ -37,11 +42,6 @@ export const addDeleteBoardAndImagesFulfilledListener = (startAppListening: AppS
           dispatch(controlAdaptersReset());
           wereControlAdaptersReset = true;
         }
-
-        if (imageUsage.isControlLayerImage && !wereControlLayersReset) {
-          dispatch(allLayersDeleted());
-          wereControlLayersReset = true;
-        }
       });
     },
   });

invokeai/frontend/web/src/app/store/middleware/listenerMiddleware/listeners/controlAdapterPreprocessor.ts

@@ -1,156 +0,0 @@
-import { isAnyOf } from '@reduxjs/toolkit';
-import { logger } from 'app/logging/logger';
-import type { AppStartListening } from 'app/store/middleware/listenerMiddleware';
-import { parseify } from 'common/util/serialize';
-import {
-  caLayerImageChanged,
-  caLayerIsProcessingImageChanged,
-  caLayerModelChanged,
-  caLayerProcessedImageChanged,
-  caLayerProcessorConfigChanged,
-  caLayerRecalled,
-  isControlAdapterLayer,
-} from 'features/controlLayers/store/controlLayersSlice';
-import { CA_PROCESSOR_DATA } from 'features/controlLayers/util/controlAdapters';
-import { isImageOutput } from 'features/nodes/types/common';
-import { addToast } from 'features/system/store/systemSlice';
-import { t } from 'i18next';
-import { isEqual } from 'lodash-es';
-import { imagesApi } from 'services/api/endpoints/images';
-import { queueApi } from 'services/api/endpoints/queue';
-import type { BatchConfig, ImageDTO } from 'services/api/types';
-import { socketInvocationComplete } from 'services/events/actions';
-
-const matcher = isAnyOf(caLayerImageChanged, caLayerProcessorConfigChanged, caLayerModelChanged, caLayerRecalled);
-
-const DEBOUNCE_MS = 300;
-const log = logger('session');
-
-export const addControlAdapterPreprocessor = (startAppListening: AppStartListening) => {
-  startAppListening({
-    matcher,
-    effect: async (action, { dispatch, getState, getOriginalState, cancelActiveListeners, delay, take }) => {
-      const layerId = caLayerRecalled.match(action) ? action.payload.id : action.payload.layerId;
-      const precheckLayerOriginal = getOriginalState()
-        .controlLayers.present.layers.filter(isControlAdapterLayer)
-        .find((l) => l.id === layerId);
-      const precheckLayer = getState()
-        .controlLayers.present.layers.filter(isControlAdapterLayer)
-        .find((l) => l.id === layerId);
-
-      // Conditions to bail
-      const layerDoesNotExist = !precheckLayer;
-      const layerHasNoImage = !precheckLayer?.controlAdapter.image;
-      const layerHasNoProcessorConfig = !precheckLayer?.controlAdapter.processorConfig;
-      const layerIsAlreadyProcessingImage = precheckLayer?.controlAdapter.isProcessingImage;
-      const areImageAndProcessorUnchanged =
-        isEqual(precheckLayer?.controlAdapter.image, precheckLayerOriginal?.controlAdapter.image) &&
-        isEqual(precheckLayer?.controlAdapter.processorConfig, precheckLayerOriginal?.controlAdapter.processorConfig);
-
-      if (
-        layerDoesNotExist ||
-        layerHasNoImage ||
-        layerHasNoProcessorConfig ||
-        areImageAndProcessorUnchanged ||
-        layerIsAlreadyProcessingImage
-      ) {
-        return;
-      }
-
-      // Cancel any in-progress instances of this listener
-      cancelActiveListeners();
-      log.trace('Control Layer CA auto-process triggered');
-
-      // Delay before starting actual work
-      await delay(DEBOUNCE_MS);
-      dispatch(caLayerIsProcessingImageChanged({ layerId, isProcessingImage: true }));
-
-      // Double-check that we are still eligible for processing
-      const state = getState();
-      const layer = state.controlLayers.present.layers.filter(isControlAdapterLayer).find((l) => l.id === layerId);
-      const image = layer?.controlAdapter.image;
-      const config = layer?.controlAdapter.processorConfig;
-
-      // If we have no image or there is no processor config, bail
-      if (!layer || !image || !config) {
-        return;
-      }
-
-      // @ts-expect-error: TS isn't able to narrow the typing of buildNode and `config` will error...
-      const processorNode = CA_PROCESSOR_DATA[config.type].buildNode(image, config);
-      const enqueueBatchArg: BatchConfig = {
-        prepend: true,
-        batch: {
-          graph: {
-            nodes: {
-              [processorNode.id]: { ...processorNode, is_intermediate: true },
-            },
-            edges: [],
-          },
-          runs: 1,
-        },
-      };
-
-      try {
-        const req = dispatch(
-          queueApi.endpoints.enqueueBatch.initiate(enqueueBatchArg, {
-            fixedCacheKey: 'enqueueBatch',
-          })
-        );
-        const enqueueResult = await req.unwrap();
-        req.reset();
-        log.debug({ enqueueResult: parseify(enqueueResult) }, t('queue.graphQueued'));
-
-        const [invocationCompleteAction] = await take(
-          (action): action is ReturnType<typeof socketInvocationComplete> =>
-            socketInvocationComplete.match(action) &&
-            action.payload.data.queue_batch_id === enqueueResult.batch.batch_id &&
-            action.payload.data.source_node_id === processorNode.id
-        );
-
-        // We still have to check the output type
-        if (isImageOutput(invocationCompleteAction.payload.data.result)) {
-          const { image_name } = invocationCompleteAction.payload.data.result.image;
-
-          // Wait for the ImageDTO to be received
-          const [{ payload }] = await take(
-            (action) =>
-              imagesApi.endpoints.getImageDTO.matchFulfilled(action) && action.payload.image_name === image_name
-          );
-
-          const imageDTO = payload as ImageDTO;
-
-          log.debug({ layerId, imageDTO }, 'ControlNet image processed');
-
-          // Update the processed image in the store
-          dispatch(
-            caLayerProcessedImageChanged({
-              layerId,
-              imageDTO,
-            })
-          );
-          dispatch(caLayerIsProcessingImageChanged({ layerId, isProcessingImage: false }));
-        }
-      } catch (error) {
-        log.error({ enqueueBatchArg: parseify(enqueueBatchArg) }, t('queue.graphFailedToQueue'));
-        dispatch(caLayerIsProcessingImageChanged({ layerId, isProcessingImage: false }));
-
-        if (error instanceof Object) {
-          if ('data' in error && 'status' in error) {
-            if (error.status === 403) {
-              dispatch(caLayerImageChanged({ layerId, imageDTO: null }));
-              return;
-            }
-          }
-        }
-
-        dispatch(
-          addToast({
-            title: t('queue.graphFailedToQueue'),
-            status: 'error',
-          })
-        );
-      }
-    },
-  });
-};

invokeai/frontend/web/src/app/store/middleware/listenerMiddleware/listeners/enqueueRequestedCanvas.ts

@@ -30,7 +30,7 @@ import type { ImageDTO } from 'services/api/types';
 export const addEnqueueRequestedCanvasListener = (startAppListening: AppStartListening) => {
   startAppListening({
     predicate: (action): action is ReturnType<typeof enqueueRequested> =>
-      enqueueRequested.match(action) && action.payload.tabName === 'canvas',
+      enqueueRequested.match(action) && action.payload.tabName === 'unifiedCanvas',
     effect: async (action, { getState, dispatch }) => {
       const log = logger('queue');
       const { prepend } = action.payload;

invokeai/frontend/web/src/app/store/middleware/listenerMiddleware/listeners/enqueueRequestedLinear.ts

@@ -1,27 +1,35 @@
 import { enqueueRequested } from 'app/store/actions';
 import type { AppStartListening } from 'app/store/middleware/listenerMiddleware';
-import { isImageViewerOpenChanged } from 'features/gallery/store/gallerySlice';
-import { buildGenerationTabGraph } from 'features/nodes/util/graph/buildGenerationTabGraph';
-import { buildGenerationTabSDXLGraph } from 'features/nodes/util/graph/buildGenerationTabSDXLGraph';
 import { prepareLinearUIBatch } from 'features/nodes/util/graph/buildLinearBatchConfig';
+import { buildLinearImageToImageGraph } from 'features/nodes/util/graph/buildLinearImageToImageGraph';
+import { buildLinearSDXLImageToImageGraph } from 'features/nodes/util/graph/buildLinearSDXLImageToImageGraph';
+import { buildLinearSDXLTextToImageGraph } from 'features/nodes/util/graph/buildLinearSDXLTextToImageGraph';
+import { buildLinearTextToImageGraph } from 'features/nodes/util/graph/buildLinearTextToImageGraph';
 import { queueApi } from 'services/api/endpoints/queue';
 
 export const addEnqueueRequestedLinear = (startAppListening: AppStartListening) => {
   startAppListening({
     predicate: (action): action is ReturnType<typeof enqueueRequested> =>
-      enqueueRequested.match(action) && action.payload.tabName === 'generation',
+      enqueueRequested.match(action) && (action.payload.tabName === 'txt2img' || action.payload.tabName === 'img2img'),
     effect: async (action, { getState, dispatch }) => {
       const state = getState();
-      const { shouldShowProgressInViewer } = state.ui;
       const model = state.generation.model;
       const { prepend } = action.payload;
 
       let graph;
 
       if (model && model.base === 'sdxl') {
-        graph = await buildGenerationTabSDXLGraph(state);
+        if (action.payload.tabName === 'txt2img') {
+          graph = await buildLinearSDXLTextToImageGraph(state);
+        } else {
+          graph = await buildLinearSDXLImageToImageGraph(state);
+        }
       } else {
-        graph = await buildGenerationTabGraph(state);
+        if (action.payload.tabName === 'txt2img') {
+          graph = await buildLinearTextToImageGraph(state);
+        } else {
+          graph = await buildLinearImageToImageGraph(state);
+        }
       }
 
       const batchConfig = prepareLinearUIBatch(state, graph, prepend);
@@ -31,14 +39,7 @@ export const addEnqueueRequestedLinear = (startAppListening: AppStartListening)
           fixedCacheKey: 'enqueueBatch',
         })
       );
-      try {
-        req.unwrap();
-        if (shouldShowProgressInViewer) {
-          dispatch(isImageViewerOpenChanged(true));
-        }
-      } finally {
-        req.reset();
-      }
+      req.reset();
     },
   });
 };

invokeai/frontend/web/src/app/store/middleware/listenerMiddleware/listeners/enqueueRequestedNodes.ts

@@ -8,7 +8,7 @@ import type { BatchConfig } from 'services/api/types';
 export const addEnqueueRequestedNodes = (startAppListening: AppStartListening) => {
   startAppListening({
     predicate: (action): action is ReturnType<typeof enqueueRequested> =>
-      enqueueRequested.match(action) && action.payload.tabName === 'workflows',
+      enqueueRequested.match(action) && action.payload.tabName === 'nodes',
     effect: async (action, { getState, dispatch }) => {
       const state = getState();
       const { nodes, edges } = state.nodes;

invokeai/frontend/web/src/app/store/middleware/listenerMiddleware/listeners/imageDeleted.ts

@@ -1,6 +1,5 @@
 import { logger } from 'app/logging/logger';
 import type { AppStartListening } from 'app/store/middleware/listenerMiddleware';
-import type { AppDispatch, RootState } from 'app/store/store';
 import { resetCanvas } from 'features/canvas/store/canvasSlice';
 import {
   controlAdapterImageChanged,
@@ -8,13 +7,6 @@ import {
   selectControlAdapterAll,
 } from 'features/controlAdapters/store/controlAdaptersSlice';
 import { isControlNetOrT2IAdapter } from 'features/controlAdapters/store/types';
-import {
-  isControlAdapterLayer,
-  isInitialImageLayer,
-  isIPAdapterLayer,
-  isRegionalGuidanceLayer,
-  layerDeleted,
-} from 'features/controlLayers/store/controlLayersSlice';
 import { imageDeletionConfirmed } from 'features/deleteImageModal/store/actions';
 import { isModalOpenChanged } from 'features/deleteImageModal/store/slice';
 import { selectListImagesQueryArgs } from 'features/gallery/store/gallerySelectors';
@@ -22,82 +14,12 @@ import { imageSelected } from 'features/gallery/store/gallerySlice';
 import { fieldImageValueChanged } from 'features/nodes/store/nodesSlice';
 import { isImageFieldInputInstance } from 'features/nodes/types/field';
 import { isInvocationNode } from 'features/nodes/types/invocation';
+import { clearInitialImage } from 'features/parameters/store/generationSlice';
 import { clamp, forEach } from 'lodash-es';
 import { api } from 'services/api';
 import { imagesApi } from 'services/api/endpoints/images';
-import type { ImageDTO } from 'services/api/types';
 import { imagesSelectors } from 'services/api/util';
 
-const deleteNodesImages = (state: RootState, dispatch: AppDispatch, imageDTO: ImageDTO) => {
-  state.nodes.nodes.forEach((node) => {
-    if (!isInvocationNode(node)) {
-      return;
-    }
-
-    forEach(node.data.inputs, (input) => {
-      if (isImageFieldInputInstance(input) && input.value?.image_name === imageDTO.image_name) {
-        dispatch(
-          fieldImageValueChanged({
-            nodeId: node.data.id,
-            fieldName: input.name,
-            value: undefined,
-          })
-        );
-      }
-    });
-  });
-};
-
-const deleteControlAdapterImages = (state: RootState, dispatch: AppDispatch, imageDTO: ImageDTO) => {
-  forEach(selectControlAdapterAll(state.controlAdapters), (ca) => {
-    if (
-      ca.controlImage === imageDTO.image_name ||
-      (isControlNetOrT2IAdapter(ca) && ca.processedControlImage === imageDTO.image_name)
-    ) {
-      dispatch(
-        controlAdapterImageChanged({
-          id: ca.id,
-          controlImage: null,
-        })
-      );
-      dispatch(
-        controlAdapterProcessedImageChanged({
-          id: ca.id,
-          processedControlImage: null,
-        })
-      );
-    }
-  });
-};
-
-const deleteControlLayerImages = (state: RootState, dispatch: AppDispatch, imageDTO: ImageDTO) => {
-  state.controlLayers.present.layers.forEach((l) => {
-    if (isRegionalGuidanceLayer(l)) {
-      if (l.ipAdapters.some((ipa) => ipa.image?.name === imageDTO.image_name)) {
-        dispatch(layerDeleted(l.id));
-      }
-    }
-    if (isControlAdapterLayer(l)) {
-      if (
-        l.controlAdapter.image?.name === imageDTO.image_name ||
-        l.controlAdapter.processedImage?.name === imageDTO.image_name
-      ) {
-        dispatch(layerDeleted(l.id));
-      }
-    }
-    if (isIPAdapterLayer(l)) {
-      if (l.ipAdapter.image?.name === imageDTO.image_name) {
-        dispatch(layerDeleted(l.id));
-      }
-    }
-    if (isInitialImageLayer(l)) {
-      if (l.image?.name === imageDTO.image_name) {
-        dispatch(layerDeleted(l.id));
-      }
-    }
-  });
-};
-
 export const addRequestedSingleImageDeletionListener = (startAppListening: AppStartListening) => {
   startAppListening({
     actionCreator: imageDeletionConfirmed,
@@ -151,9 +73,50 @@ export const addRequestedSingleImageDeletionListener = (startAppListening: AppSt
       }
 
       imageDTOs.forEach((imageDTO) => {
-        deleteControlAdapterImages(state, dispatch, imageDTO);
-        deleteNodesImages(state, dispatch, imageDTO);
-        deleteControlLayerImages(state, dispatch, imageDTO);
+        // reset init image if we deleted it
+        if (getState().generation.initialImage?.imageName === imageDTO.image_name) {
+          dispatch(clearInitialImage());
+        }
+
+        // reset control adapters that use the deleted images
+        forEach(selectControlAdapterAll(getState().controlAdapters), (ca) => {
+          if (
+            ca.controlImage === imageDTO.image_name ||
+            (isControlNetOrT2IAdapter(ca) && ca.processedControlImage === imageDTO.image_name)
+          ) {
+            dispatch(
+              controlAdapterImageChanged({
+                id: ca.id,
+                controlImage: null,
+              })
+            );
+            dispatch(
+              controlAdapterProcessedImageChanged({
+                id: ca.id,
+                processedControlImage: null,
+              })
+            );
+          }
+        });
+
+        // reset nodes that use the deleted images
+        getState().nodes.nodes.forEach((node) => {
+          if (!isInvocationNode(node)) {
+            return;
+          }
+
+          forEach(node.data.inputs, (input) => {
+            if (isImageFieldInputInstance(input) && input.value?.image_name === imageDTO.image_name) {
+              dispatch(
+                fieldImageValueChanged({
+                  nodeId: node.data.id,
+                  fieldName: input.name,
+                  value: undefined,
+                })
+              );
+            }
+          });
+        });
       });
 
       // Delete from server
@@ -205,9 +168,50 @@ export const addRequestedSingleImageDeletionListener = (startAppListening: AppSt
         }
 
         imageDTOs.forEach((imageDTO) => {
-          deleteControlAdapterImages(state, dispatch, imageDTO);
-          deleteNodesImages(state, dispatch, imageDTO);
-          deleteControlLayerImages(state, dispatch, imageDTO);
+          // reset init image if we deleted it
+          if (getState().generation.initialImage?.imageName === imageDTO.image_name) {
+            dispatch(clearInitialImage());
+          }
+
+          // reset control adapters that use the deleted images
+          forEach(selectControlAdapterAll(getState().controlAdapters), (ca) => {
+            if (
+              ca.controlImage === imageDTO.image_name ||
+              (isControlNetOrT2IAdapter(ca) && ca.processedControlImage === imageDTO.image_name)
+            ) {
+              dispatch(
+                controlAdapterImageChanged({
+                  id: ca.id,
+                  controlImage: null,
+                })
+              );
+              dispatch(
+                controlAdapterProcessedImageChanged({
+                  id: ca.id,
+                  processedControlImage: null,
+                })
+              );
+            }
+          });
+
+          // reset nodes that use the deleted images
+          getState().nodes.nodes.forEach((node) => {
+            if (!isInvocationNode(node)) {
+              return;
+            }
+
+            forEach(node.data.inputs, (input) => {
+              if (isImageFieldInputInstance(input) && input.value?.image_name === imageDTO.image_name) {
+                dispatch(
+                  fieldImageValueChanged({
+                    nodeId: node.data.id,
+                    fieldName: input.name,
+                    value: undefined,
+                  })
+                );
+              }
+            });
+          });
         });
       } catch {
         // no-op

invokeai/frontend/web/src/app/store/middleware/listenerMiddleware/listeners/imageDropped.ts

@@ -7,16 +7,10 @@ import {
   controlAdapterImageChanged,
   controlAdapterIsEnabledChanged,
 } from 'features/controlAdapters/store/controlAdaptersSlice';
-import {
-  caLayerImageChanged,
-  iiLayerImageChanged,
-  ipaLayerImageChanged,
-  rgLayerIPAdapterImageChanged,
-} from 'features/controlLayers/store/controlLayersSlice';
 import type { TypesafeDraggableData, TypesafeDroppableData } from 'features/dnd/types';
 import { imageSelected } from 'features/gallery/store/gallerySlice';
 import { fieldImageValueChanged } from 'features/nodes/store/nodesSlice';
-import { selectOptimalDimension } from 'features/parameters/store/generationSlice';
+import { initialImageChanged, selectOptimalDimension } from 'features/parameters/store/generationSlice';
 import { imagesApi } from 'services/api/endpoints/images';
 
 export const dndDropped = createAction<{
@@ -53,6 +47,18 @@ export const addImageDroppedListener = (startAppListening: AppStartListening) =>
         return;
       }
 
+      /**
+       * Image dropped on initial image
+       */
+      if (
+        overData.actionType === 'SET_INITIAL_IMAGE' &&
+        activeData.payloadType === 'IMAGE_DTO' &&
+        activeData.payload.imageDTO
+      ) {
+        dispatch(initialImageChanged(activeData.payload.imageDTO));
+        return;
+      }
+
       /**
        * Image dropped on ControlNet
        */
@@ -77,79 +83,6 @@ export const addImageDroppedListener = (startAppListening: AppStartListening) =>
         return;
       }
 
-      /**
-       * Image dropped on Control Adapter Layer
-       */
-      if (
-        overData.actionType === 'SET_CA_LAYER_IMAGE' &&
-        activeData.payloadType === 'IMAGE_DTO' &&
-        activeData.payload.imageDTO
-      ) {
-        const { layerId } = overData.context;
-        dispatch(
-          caLayerImageChanged({
-            layerId,
-            imageDTO: activeData.payload.imageDTO,
-          })
-        );
-        return;
-      }
-
-      /**
-       * Image dropped on IP Adapter Layer
-       */
-      if (
-        overData.actionType === 'SET_IPA_LAYER_IMAGE' &&
-        activeData.payloadType === 'IMAGE_DTO' &&
-        activeData.payload.imageDTO
-      ) {
-        const { layerId } = overData.context;
-        dispatch(
-          ipaLayerImageChanged({
-            layerId,
-            imageDTO: activeData.payload.imageDTO,
-          })
-        );
-        return;
-      }
-
-      /**
-       * Image dropped on RG Layer IP Adapter
-       */
-      if (
-        overData.actionType === 'SET_RG_LAYER_IP_ADAPTER_IMAGE' &&
-        activeData.payloadType === 'IMAGE_DTO' &&
-        activeData.payload.imageDTO
-      ) {
-        const { layerId, ipAdapterId } = overData.context;
-        dispatch(
-          rgLayerIPAdapterImageChanged({
-            layerId,
-            ipAdapterId,
-            imageDTO: activeData.payload.imageDTO,
-          })
-        );
-        return;
-      }
-
-      /**
-       * Image dropped on II Layer Image
-       */
-      if (
-        overData.actionType === 'SET_II_LAYER_IMAGE' &&
-        activeData.payloadType === 'IMAGE_DTO' &&
-        activeData.payload.imageDTO
-      ) {
-        const { layerId } = overData.context;
-        dispatch(
-          iiLayerImageChanged({
-            layerId,
-            imageDTO: activeData.payload.imageDTO,
-          })
-        );
-        return;
-      }
-
       /**
        * Image dropped on Canvas
        */

invokeai/frontend/web/src/app/store/middleware/listenerMiddleware/listeners/imageToDeleteSelected.ts

@@ -14,6 +14,7 @@ export const addImageToDeleteSelectedListener = (startAppListening: AppStartList
 
       const isImageInUse =
         imagesUsage.some((i) => i.isCanvasImage) ||
+        imagesUsage.some((i) => i.isInitialImage) ||
         imagesUsage.some((i) => i.isControlImage) ||
         imagesUsage.some((i) => i.isNodesImage);
 

invokeai/frontend/web/src/app/store/middleware/listenerMiddleware/listeners/imageUploaded.ts

@@ -6,14 +6,8 @@ import {
   controlAdapterImageChanged,
   controlAdapterIsEnabledChanged,
 } from 'features/controlAdapters/store/controlAdaptersSlice';
-import {
-  caLayerImageChanged,
-  iiLayerImageChanged,
-  ipaLayerImageChanged,
-  rgLayerIPAdapterImageChanged,
-} from 'features/controlLayers/store/controlLayersSlice';
 import { fieldImageValueChanged } from 'features/nodes/store/nodesSlice';
-import { selectOptimalDimension } from 'features/parameters/store/generationSlice';
+import { initialImageChanged, selectOptimalDimension } from 'features/parameters/store/generationSlice';
 import { addToast } from 'features/system/store/systemSlice';
 import { t } from 'i18next';
 import { omit } from 'lodash-es';
@@ -114,48 +108,15 @@ export const addImageUploadedFulfilledListener = (startAppListening: AppStartLis
         return;
       }
 
-      if (postUploadAction?.type === 'SET_CA_LAYER_IMAGE') {
-        const { layerId } = postUploadAction;
-        dispatch(caLayerImageChanged({ layerId, imageDTO }));
+      if (postUploadAction?.type === 'SET_INITIAL_IMAGE') {
+        dispatch(initialImageChanged(imageDTO));
         dispatch(
           addToast({
             ...DEFAULT_UPLOADED_TOAST,
-            description: t('toast.setControlImage'),
-          })
-        );
-      }
-
-      if (postUploadAction?.type === 'SET_IPA_LAYER_IMAGE') {
-        const { layerId } = postUploadAction;
-        dispatch(ipaLayerImageChanged({ layerId, imageDTO }));
-        dispatch(
-          addToast({
-            ...DEFAULT_UPLOADED_TOAST,
-            description: t('toast.setControlImage'),
-          })
-        );
-      }
-
-      if (postUploadAction?.type === 'SET_RG_LAYER_IP_ADAPTER_IMAGE') {
-        const { layerId, ipAdapterId } = postUploadAction;
-        dispatch(rgLayerIPAdapterImageChanged({ layerId, ipAdapterId, imageDTO }));
-        dispatch(
-          addToast({
-            ...DEFAULT_UPLOADED_TOAST,
-            description: t('toast.setControlImage'),
-          })
-        );
-      }
-
-      if (postUploadAction?.type === 'SET_II_LAYER_IMAGE') {
-        const { layerId } = postUploadAction;
-        dispatch(iiLayerImageChanged({ layerId, imageDTO }));
-        dispatch(
-          addToast({
-            ...DEFAULT_UPLOADED_TOAST,
-            description: t('toast.setControlImage'),
+            description: t('toast.setInitialImage'),
           })
         );
+        return;
       }
 
       if (postUploadAction?.type === 'SET_NODES_IMAGE') {

invokeai/frontend/web/src/app/store/middleware/listenerMiddleware/listeners/initialImageSelected.ts

@@ -0,0 +1,21 @@
+import type { AppStartListening } from 'app/store/middleware/listenerMiddleware';
+import { initialImageSelected } from 'features/parameters/store/actions';
+import { initialImageChanged } from 'features/parameters/store/generationSlice';
+import { addToast } from 'features/system/store/systemSlice';
+import { makeToast } from 'features/system/util/makeToast';
+import { t } from 'i18next';
+
+export const addInitialImageSelectedListener = (startAppListening: AppStartListening) => {
+  startAppListening({
+    actionCreator: initialImageSelected,
+    effect: (action, { dispatch }) => {
+      if (!action.payload) {
+        dispatch(addToast(makeToast({ title: t('toast.imageNotLoadedDesc'), status: 'error' })));
+        return;
+      }
+
+      dispatch(initialImageChanged(action.payload));
+      dispatch(addToast(makeToast(t('toast.sentToImageToImage'))));
+    },
+  });
+};

invokeai/frontend/web/src/app/store/middleware/listenerMiddleware/listeners/modelsLoaded.ts

@@ -6,10 +6,9 @@ import {
   controlAdapterModelCleared,
   selectControlAdapterAll,
 } from 'features/controlAdapters/store/controlAdaptersSlice';
-import { heightChanged, widthChanged } from 'features/controlLayers/store/controlLayersSlice';
 import { loraRemoved } from 'features/lora/store/loraSlice';
 import { calculateNewSize } from 'features/parameters/components/ImageSize/calculateNewSize';
-import { modelChanged, vaeSelected } from 'features/parameters/store/generationSlice';
+import { heightChanged, modelChanged, vaeSelected, widthChanged } from 'features/parameters/store/generationSlice';
 import { zParameterModel, zParameterVAEModel } from 'features/parameters/types/parameterSchemas';
 import { getIsSizeOptimal, getOptimalDimension } from 'features/parameters/util/optimalDimension';
 import { refinerModelChanged } from 'features/sdxl/store/sdxlSlice';
@@ -70,22 +69,16 @@ const handleMainModels: ModelHandler = (models, state, dispatch, log) => {
       dispatch(modelChanged(defaultModelInList, currentModel));
 
       const optimalDimension = getOptimalDimension(defaultModelInList);
-      if (
-        getIsSizeOptimal(
-          state.controlLayers.present.size.width,
-          state.controlLayers.present.size.height,
-          optimalDimension
-        )
-      ) {
+      if (getIsSizeOptimal(state.generation.width, state.generation.height, optimalDimension)) {
         return;
       }
       const { width, height } = calculateNewSize(
-        state.controlLayers.present.size.aspectRatio.value,
+        state.generation.aspectRatio.value,
         optimalDimension * optimalDimension
       );
 
-      dispatch(widthChanged({ width }));
-      dispatch(heightChanged({ height }));
+      dispatch(widthChanged(width));
+      dispatch(heightChanged(height));
       return;
     }
   }

invokeai/frontend/web/src/app/store/middleware/listenerMiddleware/listeners/promptChanged.ts

@@ -1,6 +1,5 @@
 import { isAnyOf } from '@reduxjs/toolkit';
 import type { AppStartListening } from 'app/store/middleware/listenerMiddleware';
-import { positivePromptChanged } from 'features/controlLayers/store/controlLayersSlice';
 import {
   combinatorialToggled,
   isErrorChanged,
@@ -11,16 +10,11 @@ import {
   promptsChanged,
 } from 'features/dynamicPrompts/store/dynamicPromptsSlice';
 import { getShouldProcessPrompt } from 'features/dynamicPrompts/util/getShouldProcessPrompt';
+import { setPositivePrompt } from 'features/parameters/store/generationSlice';
 import { utilitiesApi } from 'services/api/endpoints/utilities';
 import { socketConnected } from 'services/events/actions';
 
-const matcher = isAnyOf(
-  positivePromptChanged,
-  combinatorialToggled,
-  maxPromptsChanged,
-  maxPromptsReset,
-  socketConnected
-);
+const matcher = isAnyOf(setPositivePrompt, combinatorialToggled, maxPromptsChanged, maxPromptsReset, socketConnected);
 
 export const addDynamicPromptsListener = (startAppListening: AppStartListening) => {
   startAppListening({
@@ -28,7 +22,7 @@ export const addDynamicPromptsListener = (startAppListening: AppStartListening)
     effect: async (action, { dispatch, getState, cancelActiveListeners, delay }) => {
       cancelActiveListeners();
       const state = getState();
-      const { positivePrompt } = state.controlLayers.present;
+      const { positivePrompt } = state.generation;
       const { maxPrompts } = state.dynamicPrompts;
 
       if (state.config.disabledFeatures.includes('dynamicPrompting')) {
@@ -38,7 +32,7 @@ export const addDynamicPromptsListener = (startAppListening: AppStartListening)
       const cachedPrompts = utilitiesApi.endpoints.dynamicPrompts.select({
         prompt: positivePrompt,
         max_prompts: maxPrompts,
-      })(state).data;
+      })(getState()).data;
 
       if (cachedPrompts) {
         dispatch(promptsChanged(cachedPrompts.prompts));
@@ -46,8 +40,8 @@ export const addDynamicPromptsListener = (startAppListening: AppStartListening)
         return;
       }
 
-      if (!getShouldProcessPrompt(positivePrompt)) {
-        dispatch(promptsChanged([positivePrompt]));
+      if (!getShouldProcessPrompt(state.generation.positivePrompt)) {
+        dispatch(promptsChanged([state.generation.positivePrompt]));
         dispatch(parsingErrorChanged(undefined));
         dispatch(isErrorChanged(false));
         return;

invokeai/frontend/web/src/app/store/middleware/listenerMiddleware/listeners/setDefaultSettings.ts

@@ -1,13 +1,14 @@
 import type { AppStartListening } from 'app/store/middleware/listenerMiddleware';
-import { heightChanged, widthChanged } from 'features/controlLayers/store/controlLayersSlice';
 import { setDefaultSettings } from 'features/parameters/store/actions';
 import {
+  heightRecalled,
   setCfgRescaleMultiplier,
   setCfgScale,
   setScheduler,
   setSteps,
   vaePrecisionChanged,
   vaeSelected,
+  widthRecalled,
 } from 'features/parameters/store/generationSlice';
 import {
   isParameterCFGRescaleMultiplier,
@@ -96,16 +97,16 @@ export const addSetDefaultSettingsListener = (startAppListening: AppStartListeni
             dispatch(setScheduler(scheduler));
           }
         }
-        const setSizeOptions = { updateAspectRatio: true, clamp: true };
+
         if (width) {
           if (isParameterWidth(width)) {
-            dispatch(widthChanged({ width, ...setSizeOptions }));
+            dispatch(widthRecalled(width));
           }
         }
 
         if (height) {
           if (isParameterHeight(height)) {
-            dispatch(heightChanged({ height, ...setSizeOptions }));
+            dispatch(heightRecalled(height));
           }
         }
 

invokeai/frontend/web/src/app/store/middleware/listenerMiddleware/listeners/socketio/socketInvocationComplete.ts

@@ -2,12 +2,7 @@ import { logger } from 'app/logging/logger';
 import type { AppStartListening } from 'app/store/middleware/listenerMiddleware';
 import { parseify } from 'common/util/serialize';
 import { addImageToStagingArea } from 'features/canvas/store/canvasSlice';
-import {
-  boardIdSelected,
-  galleryViewChanged,
-  imageSelected,
-  isImageViewerOpenChanged,
-} from 'features/gallery/store/gallerySlice';
+import { boardIdSelected, galleryViewChanged, imageSelected } from 'features/gallery/store/gallerySlice';
 import { IMAGE_CATEGORIES } from 'features/gallery/store/types';
 import { isImageOutput } from 'features/nodes/types/common';
 import { CANVAS_OUTPUT } from 'features/nodes/util/graph/constants';
@@ -106,7 +101,6 @@ export const addInvocationCompleteEventListener = (startAppListening: AppStartLi
             }
 
             dispatch(imageSelected(imageDTO));
-            dispatch(isImageViewerOpenChanged(true));
           }
         }
       }

invokeai/frontend/web/src/app/store/store.ts

@@ -10,11 +10,6 @@ import {
   controlAdaptersPersistConfig,
   controlAdaptersSlice,
 } from 'features/controlAdapters/store/controlAdaptersSlice';
-import {
-  controlLayersPersistConfig,
-  controlLayersSlice,
-  controlLayersUndoableConfig,
-} from 'features/controlLayers/store/controlLayersSlice';
 import { deleteImageModalSlice } from 'features/deleteImageModal/store/slice';
 import { dynamicPromptsPersistConfig, dynamicPromptsSlice } from 'features/dynamicPrompts/store/dynamicPromptsSlice';
 import { galleryPersistConfig, gallerySlice } from 'features/gallery/store/gallerySlice';
@@ -26,6 +21,11 @@ import { workflowPersistConfig, workflowSlice } from 'features/nodes/store/workf
 import { generationPersistConfig, generationSlice } from 'features/parameters/store/generationSlice';
 import { postprocessingPersistConfig, postprocessingSlice } from 'features/parameters/store/postprocessingSlice';
 import { queueSlice } from 'features/queue/store/queueSlice';
+import {
+  regionalPromptsPersistConfig,
+  regionalPromptsSlice,
+  regionalPromptsUndoableConfig,
+} from 'features/regionalPrompts/store/regionalPromptsSlice';
 import { sdxlPersistConfig, sdxlSlice } from 'features/sdxl/store/sdxlSlice';
 import { configSlice } from 'features/system/store/configSlice';
 import { systemPersistConfig, systemSlice } from 'features/system/store/systemSlice';
@@ -65,7 +65,7 @@ const allReducers = {
   [queueSlice.name]: queueSlice.reducer,
   [workflowSlice.name]: workflowSlice.reducer,
   [hrfSlice.name]: hrfSlice.reducer,
-  [controlLayersSlice.name]: undoable(controlLayersSlice.reducer, controlLayersUndoableConfig),
+  [regionalPromptsSlice.name]: undoable(regionalPromptsSlice.reducer, regionalPromptsUndoableConfig),
   [api.reducerPath]: api.reducer,
 };
 
@@ -110,7 +110,7 @@ const persistConfigs: { [key in keyof typeof allReducers]?: PersistConfig } = {
   [loraPersistConfig.name]: loraPersistConfig,
   [modelManagerV2PersistConfig.name]: modelManagerV2PersistConfig,
   [hrfPersistConfig.name]: hrfPersistConfig,
-  [controlLayersPersistConfig.name]: controlLayersPersistConfig,
+  [regionalPromptsPersistConfig.name]: regionalPromptsPersistConfig,
 };
 
 const unserialize: UnserializeFunction = (data, key) => {

invokeai/frontend/web/src/common/components/IAIDndImage.tsx

@@ -70,7 +70,6 @@ const IAIDndImage = (props: IAIDndImageProps) => {
     onMouseOver,
     onMouseOut,
     dataTestId,
-    ...rest
   } = props;
 
   const [isHovered, setIsHovered] = useState(false);
@@ -139,7 +138,6 @@ const IAIDndImage = (props: IAIDndImageProps) => {
           minH={minSize ? minSize : undefined}
           userSelect="none"
           cursor={isDragDisabled || !imageDTO ? 'default' : 'pointer'}
-          {...rest}
         >
           {imageDTO && (
             <Flex

invokeai/frontend/web/src/common/hooks/useFullscreenDropzone.ts

@@ -17,10 +17,14 @@ const accept: Accept = {
 const selectPostUploadAction = createMemoizedSelector(activeTabNameSelector, (activeTabName) => {
   let postUploadAction: PostUploadAction = { type: 'TOAST' };
 
-  if (activeTabName === 'canvas') {
+  if (activeTabName === 'unifiedCanvas') {
     postUploadAction = { type: 'SET_CANVAS_INITIAL_IMAGE' };
   }
 
+  if (activeTabName === 'img2img') {
+    postUploadAction = { type: 'SET_INITIAL_IMAGE' };
+  }
+
   return postUploadAction;
 });
 

invokeai/frontend/web/src/common/hooks/useGlobalHotkeys.ts

@@ -67,7 +67,7 @@ export const useGlobalHotkeys = () => {
   useHotkeys(
     '1',
     () => {
-      dispatch(setActiveTab('generation'));
+      dispatch(setActiveTab('txt2img'));
     },
     [dispatch]
   );
@@ -75,7 +75,7 @@ export const useGlobalHotkeys = () => {
   useHotkeys(
     '2',
     () => {
-      dispatch(setActiveTab('canvas'));
+      dispatch(setActiveTab('img2img'));
     },
     [dispatch]
   );
@@ -83,23 +83,31 @@ export const useGlobalHotkeys = () => {
   useHotkeys(
     '3',
     () => {
-      dispatch(setActiveTab('workflows'));
+      dispatch(setActiveTab('unifiedCanvas'));
     },
     [dispatch]
   );
 
   useHotkeys(
     '4',
+    () => {
+      dispatch(setActiveTab('nodes'));
+    },
+    [dispatch]
+  );
+
+  useHotkeys(
+    '5',
     () => {
       if (isModelManagerEnabled) {
-        dispatch(setActiveTab('models'));
+        dispatch(setActiveTab('modelManager'));
       }
     },
     [dispatch, isModelManagerEnabled]
   );
 
   useHotkeys(
-    isModelManagerEnabled ? '5' : '4',
+    isModelManagerEnabled ? '6' : '5',
     () => {
       dispatch(setActiveTab('queue'));
     },

invokeai/frontend/web/src/common/hooks/useIsReadyToEnqueue.ts

@@ -5,7 +5,6 @@ import {
   selectControlAdaptersSlice,
 } from 'features/controlAdapters/store/controlAdaptersSlice';
 import { isControlNetOrT2IAdapter } from 'features/controlAdapters/store/types';
-import { selectControlLayersSlice } from 'features/controlLayers/store/controlLayersSlice';
 import { selectDynamicPromptsSlice } from 'features/dynamicPrompts/store/dynamicPromptsSlice';
 import { getShouldProcessPrompt } from 'features/dynamicPrompts/util/getShouldProcessPrompt';
 import { selectNodesSlice } from 'features/nodes/store/nodesSlice';
@@ -24,12 +23,10 @@ const selector = createMemoizedSelector(
     selectSystemSlice,
     selectNodesSlice,
     selectDynamicPromptsSlice,
-    selectControlLayersSlice,
     activeTabNameSelector,
   ],
-  (controlAdapters, generation, system, nodes, dynamicPrompts, controlLayers, activeTabName) => {
-    const { model } = generation;
-    const { positivePrompt } = controlLayers.present;
+  (controlAdapters, generation, system, nodes, dynamicPrompts, activeTabName) => {
+    const { initialImage, model, positivePrompt } = generation;
 
     const { isConnected } = system;
 
@@ -40,7 +37,11 @@ const selector = createMemoizedSelector(
       reasons.push(i18n.t('parameters.invoke.systemDisconnected'));
     }
 
-    if (activeTabName === 'workflows') {
+    if (activeTabName === 'img2img' && !initialImage) {
+      reasons.push(i18n.t('parameters.invoke.noInitialImageSelected'));
+    }
+
+    if (activeTabName === 'nodes') {
       if (nodes.shouldValidateGraph) {
         if (!nodes.nodes.length) {
           reasons.push(i18n.t('parameters.invoke.noNodesInGraph'));
@@ -93,93 +94,37 @@ const selector = createMemoizedSelector(
         reasons.push(i18n.t('parameters.invoke.noModelSelected'));
       }
 
-      if (activeTabName === 'generation') {
-        // Handling for generation tab
-        controlLayers.present.layers
-          .filter((l) => l.isEnabled)
-          .flatMap((l) => {
-            if (l.type === 'control_adapter_layer') {
-              return l.controlAdapter;
-            } else if (l.type === 'ip_adapter_layer') {
-              return l.ipAdapter;
-            } else if (l.type === 'regional_guidance_layer') {
-              return l.ipAdapters;
-            }
-            return [];
-          })
-          .forEach((ca, i) => {
-            const hasNoModel = !ca.model;
-            const mismatchedModelBase = ca.model?.base !== model?.base;
-            const hasNoImage = !ca.image;
-            const imageNotProcessed =
-              (ca.type === 'controlnet' || ca.type === 't2i_adapter') && !ca.processedImage && ca.processorConfig;
+      selectControlAdapterAll(controlAdapters).forEach((ca, i) => {
+        if (!ca.isEnabled) {
+          return;
+        }
 
-            if (hasNoModel) {
-              reasons.push(
-                i18n.t('parameters.invoke.noModelForControlAdapter', {
-                  number: i + 1,
-                })
-              );
-            }
-            if (mismatchedModelBase) {
-              // This should never happen, just a sanity check
-              reasons.push(
-                i18n.t('parameters.invoke.incompatibleBaseModelForControlAdapter', {
-                  number: i + 1,
-                })
-              );
-            }
-            if (hasNoImage) {
-              reasons.push(
-                i18n.t('parameters.invoke.noControlImageForControlAdapter', {
-                  number: i + 1,
-                })
-              );
-            }
-            if (imageNotProcessed) {
-              reasons.push(
-                i18n.t('parameters.invoke.imageNotProcessedForControlAdapter', {
-                  number: i + 1,
-                })
-              );
-            }
-          });
-      } else {
-        // Handling for all other tabs
-        selectControlAdapterAll(controlAdapters)
-          .filter((ca) => ca.isEnabled)
-          .forEach((ca, i) => {
-            if (!ca.isEnabled) {
-              return;
-            }
+        if (!ca.model) {
+          reasons.push(
+            i18n.t('parameters.invoke.noModelForControlAdapter', {
+              number: i + 1,
+            })
+          );
+        } else if (ca.model.base !== model?.base) {
+          // This should never happen, just a sanity check
+          reasons.push(
+            i18n.t('parameters.invoke.incompatibleBaseModelForControlAdapter', {
+              number: i + 1,
+            })
+          );
+        }
 
-            if (!ca.model) {
-              reasons.push(
-                i18n.t('parameters.invoke.noModelForControlAdapter', {
-                  number: i + 1,
-                })
-              );
-            } else if (ca.model.base !== model?.base) {
-              // This should never happen, just a sanity check
-              reasons.push(
-                i18n.t('parameters.invoke.incompatibleBaseModelForControlAdapter', {
-                  number: i + 1,
-                })
-              );
-            }
-
-            if (
-              !ca.controlImage ||
-              (isControlNetOrT2IAdapter(ca) && !ca.processedControlImage && ca.processorType !== 'none')
-            ) {
-              reasons.push(
-                i18n.t('parameters.invoke.noControlImageForControlAdapter', {
-                  number: i + 1,
-                })
-              );
-            }
-          });
-      }
+        if (
+          !ca.controlImage ||
+          (isControlNetOrT2IAdapter(ca) && !ca.processedControlImage && ca.processorType !== 'none')
+        ) {
+          reasons.push(
+            i18n.t('parameters.invoke.noControlImageForControlAdapter', {
+              number: i + 1,
+            })
+          );
+        }
+      });
     }
 
     return { isReady: !reasons.length, reasons };

invokeai/frontend/web/src/common/util/stopPropagation.ts

@@ -1,3 +0,0 @@
-export const stopPropagation = (e: React.MouseEvent) => {
-  e.stopPropagation();
-};

invokeai/frontend/web/src/features/canvas/hooks/useCanvasHotkeys.ts

@@ -75,7 +75,7 @@ const useInpaintingCanvasHotkeys = () => {
 
   const onKeyDown = useCallback(
     (e: KeyboardEvent) => {
-      if (e.repeat || e.key !== ' ' || isInteractiveTarget(e.target) || activeTabName !== 'canvas') {
+      if (e.repeat || e.key !== ' ' || isInteractiveTarget(e.target) || activeTabName !== 'unifiedCanvas') {
         return;
       }
       if ($toolStash.get() || $tool.get() === 'move') {
@@ -90,7 +90,7 @@ const useInpaintingCanvasHotkeys = () => {
   );
   const onKeyUp = useCallback(
     (e: KeyboardEvent) => {
-      if (e.repeat || e.key !== ' ' || isInteractiveTarget(e.target) || activeTabName !== 'canvas') {
+      if (e.repeat || e.key !== ' ' || isInteractiveTarget(e.target) || activeTabName !== 'unifiedCanvas') {
         return;
       }
       if (!$toolStash.get() || $tool.get() !== 'move') {

invokeai/frontend/web/src/features/canvas/store/canvasSlice.ts

@@ -8,7 +8,6 @@ import calculateScale from 'features/canvas/util/calculateScale';
 import { STAGE_PADDING_PERCENTAGE } from 'features/canvas/util/constants';
 import floorCoordinates from 'features/canvas/util/floorCoordinates';
 import getScaledBoundingBoxDimensions from 'features/canvas/util/getScaledBoundingBoxDimensions';
-import { calculateNewSize } from 'features/parameters/components/ImageSize/calculateNewSize';
 import { initialAspectRatioState } from 'features/parameters/components/ImageSize/constants';
 import type { AspectRatioState } from 'features/parameters/components/ImageSize/types';
 import { modelChanged } from 'features/parameters/store/generationSlice';
@@ -589,9 +588,8 @@ export const canvasSlice = createSlice({
   },
   extraReducers: (builder) => {
     builder.addCase(modelChanged, (state, action) => {
-      const newModel = action.payload;
-      if (!newModel || action.meta.previousModel?.base === newModel.base) {
-        // Model was cleared or the base didn't change
+      if (action.meta.previousModel?.base === action.payload?.base) {
+        // The base model hasn't changed, we don't need to optimize the size
         return;
       }
       const optimalDimension = getOptimalDimension(action.payload);
@@ -599,8 +597,14 @@ export const canvasSlice = createSlice({
       if (getIsSizeOptimal(width, height, optimalDimension)) {
         return;
       }
-      const newSize = calculateNewSize(state.aspectRatio.value, optimalDimension * optimalDimension);
-      setBoundingBoxDimensionsReducer(state, newSize, optimalDimension);
+      setBoundingBoxDimensionsReducer(
+        state,
+        {
+          width,
+          height,
+        },
+        optimalDimension
+      );
     });
 
     builder.addCase(socketQueueItemStatusChanged, (state, action) => {

invokeai/frontend/web/src/features/controlAdapters/components/ControlAdapterConfig.tsx

@@ -76,7 +76,7 @@ const ControlAdapterConfig = (props: { id: string; number: number }) => {
         <Box minW={0} w="full" transitionProperty="common" transitionDuration="0.1s">
           <ParamControlAdapterModel id={id} />
         </Box>
-        {activeTabName === 'canvas' && <ControlNetCanvasImageImports id={id} />}
+        {activeTabName === 'unifiedCanvas' && <ControlNetCanvasImageImports id={id} />}
         <IconButton
           size="sm"
           tooltip={t('controlnet.duplicate')}

invokeai/frontend/web/src/features/controlAdapters/components/ControlAdapterImagePreview.tsx

@@ -13,10 +13,9 @@ import {
   controlAdapterImageChanged,
   selectControlAdaptersSlice,
 } from 'features/controlAdapters/store/controlAdaptersSlice';
-import { heightChanged, widthChanged } from 'features/controlLayers/store/controlLayersSlice';
 import type { TypesafeDraggableData, TypesafeDroppableData } from 'features/dnd/types';
 import { calculateNewSize } from 'features/parameters/components/ImageSize/calculateNewSize';
-import { selectOptimalDimension } from 'features/parameters/store/generationSlice';
+import { heightChanged, selectOptimalDimension, widthChanged } from 'features/parameters/store/generationSlice';
 import { activeTabNameSelector } from 'features/ui/store/uiSelectors';
 import { memo, useCallback, useEffect, useMemo, useState } from 'react';
 import { useTranslation } from 'react-i18next';
@@ -93,16 +92,15 @@ const ControlAdapterImagePreview = ({ isSmall, id }: Props) => {
       return;
     }
 
-    if (activeTabName === 'canvas') {
+    if (activeTabName === 'unifiedCanvas') {
       dispatch(setBoundingBoxDimensions({ width: controlImage.width, height: controlImage.height }, optimalDimension));
     } else {
-      const options = { updateAspectRatio: true, clamp: true };
       const { width, height } = calculateNewSize(
         controlImage.width / controlImage.height,
         optimalDimension * optimalDimension
       );
-      dispatch(widthChanged({ width, ...options }));
-      dispatch(heightChanged({ height, ...options }));
+      dispatch(widthChanged(width));
+      dispatch(heightChanged(height));
     }
   }, [controlImage, activeTabName, dispatch, optimalDimension]);
 

invokeai/frontend/web/src/features/controlAdapters/components/parameters/ParamControlAdapterIPMethod.tsx

@@ -52,7 +52,7 @@ const ParamControlAdapterIPMethod = ({ id }: Props) => {
 
   return (
     <FormControl>
-      <InformationalPopover feature="controlNetResizeMode">
+      <InformationalPopover feature="ipAdapterMethod">
         <FormLabel>{t('controlnet.ipAdapterMethod')}</FormLabel>
       </InformationalPopover>
       <Combobox value={value} options={options} isDisabled={!isEnabled} onChange={handleIPMethodChanged} />

invokeai/frontend/web/src/features/controlAdapters/store/controlAdaptersSlice.ts

@@ -1,11 +1,12 @@
 import type { PayloadAction, Update } from '@reduxjs/toolkit';
-import { createEntityAdapter, createSlice } from '@reduxjs/toolkit';
+import { createEntityAdapter, createSlice, isAnyOf } from '@reduxjs/toolkit';
 import { getSelectorsOptions } from 'app/store/createMemoizedSelector';
 import type { PersistConfig, RootState } from 'app/store/store';
 import { deepClone } from 'common/util/deepClone';
 import { buildControlAdapter } from 'features/controlAdapters/util/buildControlAdapter';
 import { buildControlAdapterProcessor } from 'features/controlAdapters/util/buildControlAdapterProcessor';
 import { zModelIdentifierField } from 'features/nodes/types/common';
+import { maskLayerIPAdapterAdded } from 'features/regionalPrompts/store/regionalPromptsSlice';
 import { merge, uniq } from 'lodash-es';
 import type { ControlNetModelConfig, IPAdapterModelConfig, T2IAdapterModelConfig } from 'services/api/types';
 import { socketInvocationError } from 'services/events/actions';
@@ -382,6 +383,10 @@ export const controlAdaptersSlice = createSlice({
     builder.addCase(socketInvocationError, (state) => {
       state.pendingControlImages = [];
     });
+
+    builder.addCase(maskLayerIPAdapterAdded, (state, action) => {
+      caAdapter.addOne(state, buildControlAdapter(action.meta.uuid, 'ip_adapter'));
+    });
   },
 });
 
@@ -412,6 +417,8 @@ export const {
   t2iAdaptersReset,
 } = controlAdaptersSlice.actions;
 
+export const isAnyControlAdapterAdded = isAnyOf(controlAdapterAdded, controlAdapterRecalled);
+
 export const selectControlAdaptersSlice = (state: RootState) => state.controlAdapters;
 
 /* eslint-disable-next-line @typescript-eslint/no-explicit-any */

invokeai/frontend/web/src/features/controlLayers/components/AddLayerButton.tsx

@@ -1,47 +0,0 @@
-import { Button, Menu, MenuButton, MenuItem, MenuList } from '@invoke-ai/ui-library';
-import { useAppDispatch } from 'app/store/storeHooks';
-import { useAddCALayer, useAddIILayer, useAddIPALayer } from 'features/controlLayers/hooks/addLayerHooks';
-import { rgLayerAdded } from 'features/controlLayers/store/controlLayersSlice';
-import { memo, useCallback } from 'react';
-import { useTranslation } from 'react-i18next';
-import { PiPlusBold } from 'react-icons/pi';
-
-export const AddLayerButton = memo(() => {
-  const { t } = useTranslation();
-  const dispatch = useAppDispatch();
-  const [addCALayer, isAddCALayerDisabled] = useAddCALayer();
-  const [addIPALayer, isAddIPALayerDisabled] = useAddIPALayer();
-  const [addIILayer, isAddIILayerDisabled] = useAddIILayer();
-  const addRGLayer = useCallback(() => {
-    dispatch(rgLayerAdded());
-  }, [dispatch]);
-
-  return (
-    <Menu>
-      <MenuButton
-        as={Button}
-        leftIcon={<PiPlusBold />}
-        variant="ghost"
-        data-testid="control-layers-add-layer-menu-button"
-      >
-        {t('controlLayers.addLayer')}
-      </MenuButton>
-      <MenuList>
-        <MenuItem icon={<PiPlusBold />} onClick={addRGLayer}>
-          {t('controlLayers.regionalGuidanceLayer')}
-        </MenuItem>
-        <MenuItem icon={<PiPlusBold />} onClick={addCALayer} isDisabled={isAddCALayerDisabled}>
-          {t('controlLayers.globalControlAdapterLayer')}
-        </MenuItem>
-        <MenuItem icon={<PiPlusBold />} onClick={addIPALayer} isDisabled={isAddIPALayerDisabled}>
-          {t('controlLayers.globalIPAdapterLayer')}
-        </MenuItem>
-        <MenuItem icon={<PiPlusBold />} onClick={addIILayer} isDisabled={isAddIILayerDisabled}>
-          {t('controlLayers.globalInitialImageLayer')}
-        </MenuItem>
-      </MenuList>
-    </Menu>
-  );
-});
-
-AddLayerButton.displayName = 'AddLayerButton';

invokeai/frontend/web/src/features/controlLayers/components/CALayer/CALayer.tsx

@@ -1,45 +0,0 @@
-import { Flex, Spacer, useDisclosure } from '@invoke-ai/ui-library';
-import { useAppDispatch, useAppSelector } from 'app/store/storeHooks';
-import { CALayerControlAdapterWrapper } from 'features/controlLayers/components/CALayer/CALayerControlAdapterWrapper';
-import { LayerDeleteButton } from 'features/controlLayers/components/LayerCommon/LayerDeleteButton';
-import { LayerMenu } from 'features/controlLayers/components/LayerCommon/LayerMenu';
-import { LayerTitle } from 'features/controlLayers/components/LayerCommon/LayerTitle';
-import { LayerVisibilityToggle } from 'features/controlLayers/components/LayerCommon/LayerVisibilityToggle';
-import { LayerWrapper } from 'features/controlLayers/components/LayerCommon/LayerWrapper';
-import { layerSelected, selectCALayerOrThrow } from 'features/controlLayers/store/controlLayersSlice';
-import { memo, useCallback } from 'react';
-
-import CALayerOpacity from './CALayerOpacity';
-
-type Props = {
-  layerId: string;
-};
-
-export const CALayer = memo(({ layerId }: Props) => {
-  const dispatch = useAppDispatch();
-  const isSelected = useAppSelector((s) => selectCALayerOrThrow(s.controlLayers.present, layerId).isSelected);
-  const onClick = useCallback(() => {
-    dispatch(layerSelected(layerId));
-  }, [dispatch, layerId]);
-  const { isOpen, onToggle } = useDisclosure({ defaultIsOpen: true });
-
-  return (
-    <LayerWrapper onClick={onClick} borderColor={isSelected ? 'base.400' : 'base.800'}>
-      <Flex gap={3} alignItems="center" p={3} cursor="pointer" onDoubleClick={onToggle}>
-        <LayerVisibilityToggle layerId={layerId} />
-        <LayerTitle type="control_adapter_layer" />
-        <Spacer />
-        <CALayerOpacity layerId={layerId} />
-        <LayerMenu layerId={layerId} />
-        <LayerDeleteButton layerId={layerId} />
-      </Flex>
-      {isOpen && (
-        <Flex flexDir="column" gap={3} px={3} pb={3}>
-          <CALayerControlAdapterWrapper layerId={layerId} />
-        </Flex>
-      )}
-    </LayerWrapper>
-  );
-});
-
-CALayer.displayName = 'CALayer';

invokeai/frontend/web/src/features/controlLayers/components/CALayer/CALayerControlAdapterWrapper.tsx

@@ -1,121 +0,0 @@
-import { useAppDispatch, useAppSelector } from 'app/store/storeHooks';
-import { ControlAdapter } from 'features/controlLayers/components/ControlAndIPAdapter/ControlAdapter';
-import {
-  caLayerControlModeChanged,
-  caLayerImageChanged,
-  caLayerModelChanged,
-  caLayerProcessorConfigChanged,
-  caOrIPALayerBeginEndStepPctChanged,
-  caOrIPALayerWeightChanged,
-  selectCALayerOrThrow,
-} from 'features/controlLayers/store/controlLayersSlice';
-import type { ControlModeV2, ProcessorConfig } from 'features/controlLayers/util/controlAdapters';
-import type { CALayerImageDropData } from 'features/dnd/types';
-import { memo, useCallback, useMemo } from 'react';
-import type {
-  CALayerImagePostUploadAction,
-  ControlNetModelConfig,
-  ImageDTO,
-  T2IAdapterModelConfig,
-} from 'services/api/types';
-
-type Props = {
-  layerId: string;
-};
-
-export const CALayerControlAdapterWrapper = memo(({ layerId }: Props) => {
-  const dispatch = useAppDispatch();
-  const controlAdapter = useAppSelector((s) => selectCALayerOrThrow(s.controlLayers.present, layerId).controlAdapter);
-
-  const onChangeBeginEndStepPct = useCallback(
-    (beginEndStepPct: [number, number]) => {
-      dispatch(
-        caOrIPALayerBeginEndStepPctChanged({
-          layerId,
-          beginEndStepPct,
-        })
-      );
-    },
-    [dispatch, layerId]
-  );
-
-  const onChangeControlMode = useCallback(
-    (controlMode: ControlModeV2) => {
-      dispatch(
-        caLayerControlModeChanged({
-          layerId,
-          controlMode,
-        })
-      );
-    },
-    [dispatch, layerId]
-  );
-
-  const onChangeWeight = useCallback(
-    (weight: number) => {
-      dispatch(caOrIPALayerWeightChanged({ layerId, weight }));
-    },
-    [dispatch, layerId]
-  );
-
-  const onChangeProcessorConfig = useCallback(
-    (processorConfig: ProcessorConfig | null) => {
-      dispatch(caLayerProcessorConfigChanged({ layerId, processorConfig }));
-    },
-    [dispatch, layerId]
-  );
-
-  const onChangeModel = useCallback(
-    (modelConfig: ControlNetModelConfig | T2IAdapterModelConfig) => {
-      dispatch(
-        caLayerModelChanged({
-          layerId,
-          modelConfig,
-        })
-      );
-    },
-    [dispatch, layerId]
-  );
-
-  const onChangeImage = useCallback(
-    (imageDTO: ImageDTO | null) => {
-      dispatch(caLayerImageChanged({ layerId, imageDTO }));
-    },
-    [dispatch, layerId]
-  );
-
-  const droppableData = useMemo<CALayerImageDropData>(
-    () => ({
-      actionType: 'SET_CA_LAYER_IMAGE',
-      context: {
-        layerId,
-      },
-      id: layerId,
-    }),
-    [layerId]
-  );
-
-  const postUploadAction = useMemo<CALayerImagePostUploadAction>(
-    () => ({
-      layerId,
-      type: 'SET_CA_LAYER_IMAGE',
-    }),
-    [layerId]
-  );
-
-  return (
-    <ControlAdapter
-      controlAdapter={controlAdapter}
-      onChangeBeginEndStepPct={onChangeBeginEndStepPct}
-      onChangeControlMode={onChangeControlMode}
-      onChangeWeight={onChangeWeight}
-      onChangeProcessorConfig={onChangeProcessorConfig}
-      onChangeModel={onChangeModel}
-      onChangeImage={onChangeImage}
-      droppableData={droppableData}
-      postUploadAction={postUploadAction}
-    />
-  );
-});
-
-CALayerControlAdapterWrapper.displayName = 'CALayerControlAdapterWrapper';

invokeai/frontend/web/src/features/controlLayers/components/CALayer/CALayerOpacity.tsx

@@ -1,98 +0,0 @@
-import {
-  CompositeNumberInput,
-  CompositeSlider,
-  Flex,
-  FormControl,
-  FormLabel,
-  IconButton,
-  Popover,
-  PopoverArrow,
-  PopoverBody,
-  PopoverContent,
-  PopoverTrigger,
-  Switch,
-} from '@invoke-ai/ui-library';
-import { useAppDispatch } from 'app/store/storeHooks';
-import { stopPropagation } from 'common/util/stopPropagation';
-import { useLayerOpacity } from 'features/controlLayers/hooks/layerStateHooks';
-import { caLayerIsFilterEnabledChanged, caLayerOpacityChanged } from 'features/controlLayers/store/controlLayersSlice';
-import type { ChangeEvent } from 'react';
-import { memo, useCallback } from 'react';
-import { useTranslation } from 'react-i18next';
-import { PiDropHalfFill } from 'react-icons/pi';
-
-type Props = {
-  layerId: string;
-};
-
-const marks = [0, 25, 50, 75, 100];
-const formatPct = (v: number | string) => `${v} %`;
-
-const CALayerOpacity = ({ layerId }: Props) => {
-  const { t } = useTranslation();
-  const dispatch = useAppDispatch();
-  const { opacity, isFilterEnabled } = useLayerOpacity(layerId);
-  const onChangeOpacity = useCallback(
-    (v: number) => {
-      dispatch(caLayerOpacityChanged({ layerId, opacity: v / 100 }));
-    },
-    [dispatch, layerId]
-  );
-  const onChangeFilter = useCallback(
-    (e: ChangeEvent<HTMLInputElement>) => {
-      dispatch(caLayerIsFilterEnabledChanged({ layerId, isFilterEnabled: e.target.checked }));
-    },
-    [dispatch, layerId]
-  );
-  return (
-    <Popover isLazy>
-      <PopoverTrigger>
-        <IconButton
-          aria-label={t('controlLayers.opacity')}
-          size="sm"
-          icon={<PiDropHalfFill size={16} />}
-          variant="ghost"
-          onDoubleClick={stopPropagation}
-        />
-      </PopoverTrigger>
-      <PopoverContent onDoubleClick={stopPropagation}>
-        <PopoverArrow />
-        <PopoverBody>
-          <Flex direction="column" gap={2}>
-            <FormControl orientation="horizontal" w="full">
-              <FormLabel m={0} flexGrow={1} cursor="pointer">
-                {t('controlLayers.opacityFilter')}
-              </FormLabel>
-              <Switch isChecked={isFilterEnabled} onChange={onChangeFilter} />
-            </FormControl>
-            <FormControl orientation="horizontal">
-              <FormLabel m={0}>{t('controlLayers.opacity')}</FormLabel>
-              <CompositeSlider
-                min={0}
-                max={100}
-                step={1}
-                value={opacity}
-                defaultValue={100}
-                onChange={onChangeOpacity}
-                marks={marks}
-                w={48}
-              />
-              <CompositeNumberInput
-                min={0}
-                max={100}
-                step={1}
-                value={opacity}
-                defaultValue={100}
-                onChange={onChangeOpacity}
-                w={24}
-                format={formatPct}
-              />
-            </FormControl>
-          </Flex>
-        </PopoverBody>
-      </PopoverContent>
-    </Popover>
-  );
-};
-
-export default memo(CALayerOpacity);

invokeai/frontend/web/src/features/controlLayers/components/ControlAndIPAdapter/ControlAdapter.tsx

@@ -1,117 +0,0 @@
-import { Box, Divider, Flex, Icon, IconButton } from '@invoke-ai/ui-library';
-import { ControlAdapterModelCombobox } from 'features/controlLayers/components/ControlAndIPAdapter/ControlAdapterModelCombobox';
-import type {
-  ControlModeV2,
-  ControlNetConfigV2,
-  ProcessorConfig,
-  T2IAdapterConfigV2,
-} from 'features/controlLayers/util/controlAdapters';
-import type { TypesafeDroppableData } from 'features/dnd/types';
-import { memo } from 'react';
-import { useTranslation } from 'react-i18next';
-import { PiCaretUpBold } from 'react-icons/pi';
-import { useToggle } from 'react-use';
-import type { ControlNetModelConfig, ImageDTO, PostUploadAction, T2IAdapterModelConfig } from 'services/api/types';
-
-import { ControlAdapterBeginEndStepPct } from './ControlAdapterBeginEndStepPct';
-import { ControlAdapterControlModeSelect } from './ControlAdapterControlModeSelect';
-import { ControlAdapterImagePreview } from './ControlAdapterImagePreview';
-import { ControlAdapterProcessorConfig } from './ControlAdapterProcessorConfig';
-import { ControlAdapterProcessorTypeSelect } from './ControlAdapterProcessorTypeSelect';
-import { ControlAdapterWeight } from './ControlAdapterWeight';
-
-type Props = {
-  controlAdapter: ControlNetConfigV2 | T2IAdapterConfigV2;
-  onChangeBeginEndStepPct: (beginEndStepPct: [number, number]) => void;
-  onChangeControlMode: (controlMode: ControlModeV2) => void;
-  onChangeWeight: (weight: number) => void;
-  onChangeProcessorConfig: (processorConfig: ProcessorConfig | null) => void;
-  onChangeModel: (modelConfig: ControlNetModelConfig | T2IAdapterModelConfig) => void;
-  onChangeImage: (imageDTO: ImageDTO | null) => void;
-  droppableData: TypesafeDroppableData;
-  postUploadAction: PostUploadAction;
-};
-
-export const ControlAdapter = memo(
-  ({
-    controlAdapter,
-    onChangeBeginEndStepPct,
-    onChangeControlMode,
-    onChangeWeight,
-    onChangeProcessorConfig,
-    onChangeModel,
-    onChangeImage,
-    droppableData,
-    postUploadAction,
-  }: Props) => {
-    const { t } = useTranslation();
-    const [isExpanded, toggleIsExpanded] = useToggle(false);
-
-    return (
-      <Flex flexDir="column" gap={3} position="relative" w="full">
-        <Flex gap={3} alignItems="center" w="full">
-          <Box minW={0} w="full" transitionProperty="common" transitionDuration="0.1s">
-            <ControlAdapterModelCombobox modelKey={controlAdapter.model?.key ?? null} onChange={onChangeModel} />
-          </Box>
-
-          <IconButton
-            size="sm"
-            tooltip={isExpanded ? t('controlnet.hideAdvanced') : t('controlnet.showAdvanced')}
-            aria-label={isExpanded ? t('controlnet.hideAdvanced') : t('controlnet.showAdvanced')}
-            onClick={toggleIsExpanded}
-            variant="ghost"
-            icon={
-              <Icon
-                boxSize={4}
-                as={PiCaretUpBold}
-                transform={isExpanded ? 'rotate(0deg)' : 'rotate(180deg)'}
-                transitionProperty="common"
-                transitionDuration="normal"
-              />
-            }
-          />
-        </Flex>
-        <Flex gap={3} w="full">
-          <Flex flexDir="column" gap={3} w="full" h="full">
-            {controlAdapter.type === 'controlnet' && (
-              <ControlAdapterControlModeSelect
-                controlMode={controlAdapter.controlMode}
-                onChange={onChangeControlMode}
-              />
-            )}
-            <ControlAdapterWeight weight={controlAdapter.weight} onChange={onChangeWeight} />
-            <ControlAdapterBeginEndStepPct
-              beginEndStepPct={controlAdapter.beginEndStepPct}
-              onChange={onChangeBeginEndStepPct}
-            />
-          </Flex>
-          <Flex alignItems="center" justifyContent="center" h={36} w={36} aspectRatio="1/1">
-            <ControlAdapterImagePreview
-              controlAdapter={controlAdapter}
-              onChangeImage={onChangeImage}
-              droppableData={droppableData}
-              postUploadAction={postUploadAction}
-            />
-          </Flex>
-        </Flex>
-        {isExpanded && (
-          <>
-            <Divider />
-            <Flex flexDir="column" gap={3} w="full">
-              <ControlAdapterProcessorTypeSelect
-                config={controlAdapter.processorConfig}
-                onChange={onChangeProcessorConfig}
-              />
-              <ControlAdapterProcessorConfig
-                config={controlAdapter.processorConfig}
-                onChange={onChangeProcessorConfig}
-              />
-            </Flex>
-          </>
-        )}
-      </Flex>
-    );
-  }
-);
-
-ControlAdapter.displayName = 'ControlAdapter';

invokeai/frontend/web/src/features/controlLayers/components/ControlAndIPAdapter/ControlAdapterBeginEndStepPct.tsx

@@ -1,43 +0,0 @@
-import { CompositeRangeSlider, FormControl, FormLabel } from '@invoke-ai/ui-library';
-import { InformationalPopover } from 'common/components/InformationalPopover/InformationalPopover';
-import { memo, useCallback } from 'react';
-import { useTranslation } from 'react-i18next';
-
-type Props = {
-  beginEndStepPct: [number, number];
-  onChange: (beginEndStepPct: [number, number]) => void;
-};
-
-const formatPct = (v: number) => `${Math.round(v * 100)}%`;
-const ariaLabel = ['Begin Step %', 'End Step %'];
-
-export const ControlAdapterBeginEndStepPct = memo(({ beginEndStepPct, onChange }: Props) => {
-  const { t } = useTranslation();
-  const onReset = useCallback(() => {
-    onChange([0, 1]);
-  }, [onChange]);
-
-  return (
-    <FormControl orientation="horizontal">
-      <InformationalPopover feature="controlNetBeginEnd">
-        <FormLabel m={0}>{t('controlnet.beginEndStepPercentShort')}</FormLabel>
-      </InformationalPopover>
-      <CompositeRangeSlider
-        aria-label={ariaLabel}
-        value={beginEndStepPct}
-        onChange={onChange}
-        onReset={onReset}
-        min={0}
-        max={1}
-        step={0.05}
-        fineStep={0.01}
-        minStepsBetweenThumbs={1}
-        formatValue={formatPct}
-        marks
-        withThumbTooltip
-      />
-    </FormControl>
-  );
-});
-
-ControlAdapterBeginEndStepPct.displayName = 'ControlAdapterBeginEndStepPct';

invokeai/frontend/web/src/features/controlLayers/components/ControlAndIPAdapter/ControlAdapterControlModeSelect.tsx

@@ -1,60 +0,0 @@
-import type { ComboboxOnChange } from '@invoke-ai/ui-library';
-import { Combobox, FormControl, FormLabel } from '@invoke-ai/ui-library';
-import { InformationalPopover } from 'common/components/InformationalPopover/InformationalPopover';
-import type { ControlModeV2 } from 'features/controlLayers/util/controlAdapters';
-import { isControlModeV2 } from 'features/controlLayers/util/controlAdapters';
-import { memo, useCallback, useMemo } from 'react';
-import { useTranslation } from 'react-i18next';
-import { assert } from 'tsafe';
-
-type Props = {
-  controlMode: ControlModeV2;
-  onChange: (controlMode: ControlModeV2) => void;
-};
-
-export const ControlAdapterControlModeSelect = memo(({ controlMode, onChange }: Props) => {
-  const { t } = useTranslation();
-  const CONTROL_MODE_DATA = useMemo(
-    () => [
-      { label: t('controlnet.balanced'), value: 'balanced' },
-      { label: t('controlnet.prompt'), value: 'more_prompt' },
-      { label: t('controlnet.control'), value: 'more_control' },
-      { label: t('controlnet.megaControl'), value: 'unbalanced' },
-    ],
-    [t]
-  );
-
-  const handleControlModeChange = useCallback<ComboboxOnChange>(
-    (v) => {
-      assert(isControlModeV2(v?.value));
-      onChange(v.value);
-    },
-    [onChange]
-  );
-
-  const value = useMemo(
-    () => CONTROL_MODE_DATA.filter((o) => o.value === controlMode)[0],
-    [CONTROL_MODE_DATA, controlMode]
-  );
-
-  if (!controlMode) {
-    return null;
-  }
-
-  return (
-    <FormControl>
-      <InformationalPopover feature="controlNetControlMode">
-        <FormLabel m={0}>{t('controlnet.control')}</FormLabel>
-      </InformationalPopover>
-      <Combobox
-        value={value}
-        options={CONTROL_MODE_DATA}
-        onChange={handleControlModeChange}
-        isClearable={false}
-        isSearchable={false}
-      />
-    </FormControl>
-  );
-});
-
-ControlAdapterControlModeSelect.displayName = 'ControlAdapterControlModeSelect';

invokeai/frontend/web/src/features/controlLayers/components/ControlAndIPAdapter/ControlAdapterImagePreview.tsx

@@ -1,217 +0,0 @@
-import type { SystemStyleObject } from '@invoke-ai/ui-library';
-import { Box, Flex, Spinner, useShiftModifier } from '@invoke-ai/ui-library';
-import { skipToken } from '@reduxjs/toolkit/query';
-import { useAppDispatch, useAppSelector } from 'app/store/storeHooks';
-import IAIDndImage from 'common/components/IAIDndImage';
-import IAIDndImageIcon from 'common/components/IAIDndImageIcon';
-import { setBoundingBoxDimensions } from 'features/canvas/store/canvasSlice';
-import { heightChanged, widthChanged } from 'features/controlLayers/store/controlLayersSlice';
-import type { ControlNetConfigV2, T2IAdapterConfigV2 } from 'features/controlLayers/util/controlAdapters';
-import type { ImageDraggableData, TypesafeDroppableData } from 'features/dnd/types';
-import { calculateNewSize } from 'features/parameters/components/ImageSize/calculateNewSize';
-import { selectOptimalDimension } from 'features/parameters/store/generationSlice';
-import { activeTabNameSelector } from 'features/ui/store/uiSelectors';
-import { memo, useCallback, useEffect, useMemo, useState } from 'react';
-import { useTranslation } from 'react-i18next';
-import { PiArrowCounterClockwiseBold, PiFloppyDiskBold, PiRulerBold } from 'react-icons/pi';
-import {
-  useAddImageToBoardMutation,
-  useChangeImageIsIntermediateMutation,
-  useGetImageDTOQuery,
-  useRemoveImageFromBoardMutation,
-} from 'services/api/endpoints/images';
-import type { ImageDTO, PostUploadAction } from 'services/api/types';
-
-type Props = {
-  controlAdapter: ControlNetConfigV2 | T2IAdapterConfigV2;
-  onChangeImage: (imageDTO: ImageDTO | null) => void;
-  droppableData: TypesafeDroppableData;
-  postUploadAction: PostUploadAction;
-};
-
-export const ControlAdapterImagePreview = memo(
-  ({ controlAdapter, onChangeImage, droppableData, postUploadAction }: Props) => {
-    const { t } = useTranslation();
-    const dispatch = useAppDispatch();
-    const autoAddBoardId = useAppSelector((s) => s.gallery.autoAddBoardId);
-    const isConnected = useAppSelector((s) => s.system.isConnected);
-    const activeTabName = useAppSelector(activeTabNameSelector);
-    const optimalDimension = useAppSelector(selectOptimalDimension);
-    const shift = useShiftModifier();
-
-    const [isMouseOverImage, setIsMouseOverImage] = useState(false);
-
-    const { currentData: controlImage, isError: isErrorControlImage } = useGetImageDTOQuery(
-      controlAdapter.image?.name ?? skipToken
-    );
-    const { currentData: processedControlImage, isError: isErrorProcessedControlImage } = useGetImageDTOQuery(
-      controlAdapter.processedImage?.name ?? skipToken
-    );
-
-    const [changeIsIntermediate] = useChangeImageIsIntermediateMutation();
-    const [addToBoard] = useAddImageToBoardMutation();
-    const [removeFromBoard] = useRemoveImageFromBoardMutation();
-    const handleResetControlImage = useCallback(() => {
-      onChangeImage(null);
-    }, [onChangeImage]);
-
-    const handleSaveControlImage = useCallback(async () => {
-      if (!processedControlImage) {
-        return;
-      }
-
-      await changeIsIntermediate({
-        imageDTO: processedControlImage,
-        is_intermediate: false,
-      }).unwrap();
-
-      if (autoAddBoardId !== 'none') {
-        addToBoard({
-          imageDTO: processedControlImage,
-          board_id: autoAddBoardId,
-        });
-      } else {
-        removeFromBoard({ imageDTO: processedControlImage });
-      }
-    }, [processedControlImage, changeIsIntermediate, autoAddBoardId, addToBoard, removeFromBoard]);
-
-    const handleSetControlImageToDimensions = useCallback(() => {
-      if (!controlImage) {
-        return;
-      }
-
-      if (activeTabName === 'canvas') {
-        dispatch(
-          setBoundingBoxDimensions({ width: controlImage.width, height: controlImage.height }, optimalDimension)
-        );
-      } else {
-        const options = { updateAspectRatio: true, clamp: true };
-
-        if (shift) {
-          const { width, height } = controlImage;
-          dispatch(widthChanged({ width, ...options }));
-          dispatch(heightChanged({ height, ...options }));
-        } else {
-          const { width, height } = calculateNewSize(
-            controlImage.width / controlImage.height,
-            optimalDimension * optimalDimension
-          );
-          dispatch(widthChanged({ width, ...options }));
-          dispatch(heightChanged({ height, ...options }));
-        }
-      }
-    }, [controlImage, activeTabName, dispatch, optimalDimension, shift]);
-
-    const handleMouseEnter = useCallback(() => {
-      setIsMouseOverImage(true);
-    }, []);
-
-    const handleMouseLeave = useCallback(() => {
-      setIsMouseOverImage(false);
-    }, []);
-
-    const draggableData = useMemo<ImageDraggableData | undefined>(() => {
-      if (controlImage) {
-        return {
-          id: controlAdapter.id,
-          payloadType: 'IMAGE_DTO',
-          payload: { imageDTO: controlImage },
-        };
-      }
-    }, [controlImage, controlAdapter.id]);
-
-    const shouldShowProcessedImage =
-      controlImage &&
-      processedControlImage &&
-      !isMouseOverImage &&
-      !controlAdapter.isProcessingImage &&
-      controlAdapter.processorConfig !== null;
-
-    useEffect(() => {
-      if (isConnected && (isErrorControlImage || isErrorProcessedControlImage)) {
-        handleResetControlImage();
-      }
-    }, [handleResetControlImage, isConnected, isErrorControlImage, isErrorProcessedControlImage]);
-
-    return (
-      <Flex
-        onMouseEnter={handleMouseEnter}
-        onMouseLeave={handleMouseLeave}
-        position="relative"
-        w="full"
-        h={36}
-        alignItems="center"
-        justifyContent="center"
-      >
-        <IAIDndImage
-          draggableData={draggableData}
-          droppableData={droppableData}
-          imageDTO={controlImage}
-          isDropDisabled={shouldShowProcessedImage}
-          postUploadAction={postUploadAction}
-        />
-
-        <Box
-          position="absolute"
-          top={0}
-          insetInlineStart={0}
-          w="full"
-          h="full"
-          opacity={shouldShowProcessedImage ? 1 : 0}
-          transitionProperty="common"
-          transitionDuration="normal"
-          pointerEvents="none"
-        >
-          <IAIDndImage
-            draggableData={draggableData}
-            droppableData={droppableData}
-            imageDTO={processedControlImage}
-            isUploadDisabled={true}
-          />
-        </Box>
-
-        <>
-          <IAIDndImageIcon
-            onClick={handleResetControlImage}
-            icon={controlImage ? <PiArrowCounterClockwiseBold size={16} /> : undefined}
-            tooltip={t('controlnet.resetControlImage')}
-          />
-          <IAIDndImageIcon
-            onClick={handleSaveControlImage}
-            icon={controlImage ? <PiFloppyDiskBold size={16} /> : undefined}
-            tooltip={t('controlnet.saveControlImage')}
-            styleOverrides={saveControlImageStyleOverrides}
-          />
-          <IAIDndImageIcon
-            onClick={handleSetControlImageToDimensions}
-            icon={controlImage ? <PiRulerBold size={16} /> : undefined}
-            tooltip={shift ? t('controlnet.setControlImageDimensionsForce') : t('controlnet.setControlImageDimensions')}
-            styleOverrides={setControlImageDimensionsStyleOverrides}
-          />
-        </>
-
-        {controlAdapter.isProcessingImage && (
-          <Flex
-            position="absolute"
-            top={0}
-            insetInlineStart={0}
-            w="full"
-            h="full"
-            alignItems="center"
-            justifyContent="center"
-            opacity={0.8}
-            borderRadius="base"
-            bg="base.900"
-          >
-            <Spinner size="xl" color="base.400" />
-          </Flex>
-        )}
-      </Flex>
-    );
-  }
-);
-
-ControlAdapterImagePreview.displayName = 'ControlAdapterImagePreview';
-
-const saveControlImageStyleOverrides: SystemStyleObject = { mt: 6 };
-const setControlImageDimensionsStyleOverrides: SystemStyleObject = { mt: 12 };

invokeai/frontend/web/src/features/controlLayers/components/ControlAndIPAdapter/ControlAdapterModelCombobox.tsx

@@ -1,62 +0,0 @@
-import { Combobox, FormControl, Tooltip } from '@invoke-ai/ui-library';
-import { useAppSelector } from 'app/store/storeHooks';
-import { useGroupedModelCombobox } from 'common/hooks/useGroupedModelCombobox';
-import { memo, useCallback, useMemo } from 'react';
-import { useTranslation } from 'react-i18next';
-import { useControlNetAndT2IAdapterModels } from 'services/api/hooks/modelsByType';
-import type { AnyModelConfig, ControlNetModelConfig, T2IAdapterModelConfig } from 'services/api/types';
-
-type Props = {
-  modelKey: string | null;
-  onChange: (modelConfig: ControlNetModelConfig | T2IAdapterModelConfig) => void;
-};
-
-export const ControlAdapterModelCombobox = memo(({ modelKey, onChange: onChangeModel }: Props) => {
-  const { t } = useTranslation();
-  const currentBaseModel = useAppSelector((s) => s.generation.model?.base);
-  const [modelConfigs, { isLoading }] = useControlNetAndT2IAdapterModels();
-  const selectedModel = useMemo(() => modelConfigs.find((m) => m.key === modelKey), [modelConfigs, modelKey]);
-
-  const _onChange = useCallback(
-    (modelConfig: ControlNetModelConfig | T2IAdapterModelConfig | null) => {
-      if (!modelConfig) {
-        return;
-      }
-      onChangeModel(modelConfig);
-    },
-    [onChangeModel]
-  );
-
-  const getIsDisabled = useCallback(
-    (model: AnyModelConfig): boolean => {
-      const isCompatible = currentBaseModel === model.base;
-      const hasMainModel = Boolean(currentBaseModel);
-      return !hasMainModel || !isCompatible;
-    },
-    [currentBaseModel]
-  );
-
-  const { options, value, onChange, noOptionsMessage } = useGroupedModelCombobox({
-    modelConfigs,
-    onChange: _onChange,
-    selectedModel,
-    getIsDisabled,
-    isLoading,
-  });
-
-  return (
-    <Tooltip label={selectedModel?.description}>
-      <FormControl isInvalid={!value || currentBaseModel !== selectedModel?.base} w="full">
-        <Combobox
-          options={options}
-          placeholder={t('controlnet.selectModel')}
-          value={value}
-          onChange={onChange}
-          noOptionsMessage={noOptionsMessage}
-        />
-      </FormControl>
-    </Tooltip>
-  );
-});
-
-ControlAdapterModelCombobox.displayName = 'ControlAdapterModelCombobox';

invokeai/frontend/web/src/features/controlLayers/components/ControlAndIPAdapter/ControlAdapterProcessorConfig.tsx

@@ -1,85 +0,0 @@
-import type { ProcessorConfig } from 'features/controlLayers/util/controlAdapters';
-import { memo } from 'react';
-
-import { CannyProcessor } from './processors/CannyProcessor';
-import { ColorMapProcessor } from './processors/ColorMapProcessor';
-import { ContentShuffleProcessor } from './processors/ContentShuffleProcessor';
-import { DepthAnythingProcessor } from './processors/DepthAnythingProcessor';
-import { DWOpenposeProcessor } from './processors/DWOpenposeProcessor';
-import { HedProcessor } from './processors/HedProcessor';
-import { LineartProcessor } from './processors/LineartProcessor';
-import { MediapipeFaceProcessor } from './processors/MediapipeFaceProcessor';
-import { MidasDepthProcessor } from './processors/MidasDepthProcessor';
-import { MlsdImageProcessor } from './processors/MlsdImageProcessor';
-import { PidiProcessor } from './processors/PidiProcessor';
-
-type Props = {
-  config: ProcessorConfig | null;
-  onChange: (config: ProcessorConfig | null) => void;
-};
-
-export const ControlAdapterProcessorConfig = memo(({ config, onChange }: Props) => {
-  if (!config) {
-    return null;
-  }
-
-  if (config.type === 'canny_image_processor') {
-    return <CannyProcessor onChange={onChange} config={config} />;
-  }
-
-  if (config.type === 'color_map_image_processor') {
-    return <ColorMapProcessor onChange={onChange} config={config} />;
-  }
-
-  if (config.type === 'depth_anything_image_processor') {
-    return <DepthAnythingProcessor onChange={onChange} config={config} />;
-  }
-
-  if (config.type === 'hed_image_processor') {
-    return <HedProcessor onChange={onChange} config={config} />;
-  }
-
-  if (config.type === 'lineart_image_processor') {
-    return <LineartProcessor onChange={onChange} config={config} />;
-  }
-
-  if (config.type === 'content_shuffle_image_processor') {
-    return <ContentShuffleProcessor onChange={onChange} config={config} />;
-  }
-
-  if (config.type === 'lineart_anime_image_processor') {
-    // No configurable options for this processor
-    return null;
-  }
-
-  if (config.type === 'mediapipe_face_processor') {
-    return <MediapipeFaceProcessor onChange={onChange} config={config} />;
-  }
-
-  if (config.type === 'midas_depth_image_processor') {
-    return <MidasDepthProcessor onChange={onChange} config={config} />;
-  }
-
-  if (config.type === 'mlsd_image_processor') {
-    return <MlsdImageProcessor onChange={onChange} config={config} />;
-  }
-
-  if (config.type === 'normalbae_image_processor') {
-    // No configurable options for this processor
-    return null;
-  }
-
-  if (config.type === 'dw_openpose_image_processor') {
-    return <DWOpenposeProcessor onChange={onChange} config={config} />;
-  }
-
-  if (config.type === 'pidi_image_processor') {
-    return <PidiProcessor onChange={onChange} config={config} />;
-  }
-
-  if (config.type === 'zoe_depth_image_processor') {
-    return null;
-  }
-});
-
-ControlAdapterProcessorConfig.displayName = 'ControlAdapterProcessorConfig';

invokeai/frontend/web/src/features/controlLayers/components/ControlAndIPAdapter/ControlAdapterProcessorTypeSelect.tsx

@@ -1,70 +0,0 @@
-import type { ComboboxOnChange } from '@invoke-ai/ui-library';
-import { Combobox, Flex, FormControl, FormLabel, IconButton } from '@invoke-ai/ui-library';
-import { createMemoizedSelector } from 'app/store/createMemoizedSelector';
-import { useAppSelector } from 'app/store/storeHooks';
-import { InformationalPopover } from 'common/components/InformationalPopover/InformationalPopover';
-import type { ProcessorConfig } from 'features/controlLayers/util/controlAdapters';
-import { CA_PROCESSOR_DATA, isProcessorTypeV2 } from 'features/controlLayers/util/controlAdapters';
-import { configSelector } from 'features/system/store/configSelectors';
-import { includes, map } from 'lodash-es';
-import { memo, useCallback, useMemo } from 'react';
-import { useTranslation } from 'react-i18next';
-import { PiXBold } from 'react-icons/pi';
-import { assert } from 'tsafe';
-
-type Props = {
-  config: ProcessorConfig | null;
-  onChange: (config: ProcessorConfig | null) => void;
-};
-
-const selectDisabledProcessors = createMemoizedSelector(
-  configSelector,
-  (config) => config.sd.disabledControlNetProcessors
-);
-
-export const ControlAdapterProcessorTypeSelect = memo(({ config, onChange }: Props) => {
-  const { t } = useTranslation();
-  const disabledProcessors = useAppSelector(selectDisabledProcessors);
-  const options = useMemo(() => {
-    return map(CA_PROCESSOR_DATA, ({ labelTKey }, type) => ({ value: type, label: t(labelTKey) })).filter(
-      (o) => !includes(disabledProcessors, o.value)
-    );
-  }, [disabledProcessors, t]);
-
-  const _onChange = useCallback<ComboboxOnChange>(
-    (v) => {
-      if (!v) {
-        onChange(null);
-      } else {
-        assert(isProcessorTypeV2(v.value));
-        onChange(CA_PROCESSOR_DATA[v.value].buildDefaults());
-      }
-    },
-    [onChange]
-  );
-  const clearProcessor = useCallback(() => {
-    onChange(null);
-  }, [onChange]);
-  const value = useMemo(() => options.find((o) => o.value === config?.type) ?? null, [options, config?.type]);
-
-  return (
-    <Flex gap={2}>
-      <FormControl>
-        <InformationalPopover feature="controlNetProcessor">
-          <FormLabel m={0}>{t('controlnet.processor')}</FormLabel>
-        </InformationalPopover>
-        <Combobox value={value} options={options} onChange={_onChange} isSearchable={false} isClearable={false} />
-      </FormControl>
-      <IconButton
-        aria-label={t('controlLayers.clearProcessor')}
-        onClick={clearProcessor}
-        isDisabled={!config}
-        icon={<PiXBold />}
-        variant="ghost"
-        size="sm"
-      />
-    </Flex>
-  );
-});
-
-ControlAdapterProcessorTypeSelect.displayName = 'ControlAdapterProcessorTypeSelect';

invokeai/frontend/web/src/features/controlLayers/components/ControlAndIPAdapter/ControlAdapterWeight.tsx

@@ -1,55 +0,0 @@
-import { CompositeNumberInput, CompositeSlider, FormControl, FormLabel } from '@invoke-ai/ui-library';
-import { useAppSelector } from 'app/store/storeHooks';
-import { InformationalPopover } from 'common/components/InformationalPopover/InformationalPopover';
-import { memo } from 'react';
-import { useTranslation } from 'react-i18next';
-
-type Props = {
-  weight: number;
-  onChange: (weight: number) => void;
-};
-
-const formatValue = (v: number) => v.toFixed(2);
-const marks = [0, 1, 2];
-
-export const ControlAdapterWeight = memo(({ weight, onChange }: Props) => {
-  const { t } = useTranslation();
-  const initial = useAppSelector((s) => s.config.sd.ca.weight.initial);
-  const sliderMin = useAppSelector((s) => s.config.sd.ca.weight.sliderMin);
-  const sliderMax = useAppSelector((s) => s.config.sd.ca.weight.sliderMax);
-  const numberInputMin = useAppSelector((s) => s.config.sd.ca.weight.numberInputMin);
-  const numberInputMax = useAppSelector((s) => s.config.sd.ca.weight.numberInputMax);
-  const coarseStep = useAppSelector((s) => s.config.sd.ca.weight.coarseStep);
-  const fineStep = useAppSelector((s) => s.config.sd.ca.weight.fineStep);
-
-  return (
-    <FormControl orientation="horizontal">
-      <InformationalPopover feature="controlNetWeight">
-        <FormLabel m={0}>{t('controlnet.weight')}</FormLabel>
-      </InformationalPopover>
-      <CompositeSlider
-        value={weight}
-        onChange={onChange}
-        defaultValue={initial}
-        min={sliderMin}
-        max={sliderMax}
-        step={coarseStep}
-        fineStep={fineStep}
-        marks={marks}
-        formatValue={formatValue}
-      />
-      <CompositeNumberInput
-        value={weight}
-        onChange={onChange}
-        min={numberInputMin}
-        max={numberInputMax}
-        step={coarseStep}
-        fineStep={fineStep}
-        maxW={20}
-        defaultValue={initial}
-      />
-    </FormControl>
-  );
-});
-
-ControlAdapterWeight.displayName = 'ControlAdapterWeight';

invokeai/frontend/web/src/features/controlLayers/components/ControlAndIPAdapter/IPAdapter.tsx

@@ -1,72 +0,0 @@
-import { Box, Flex } from '@invoke-ai/ui-library';
-import { ControlAdapterBeginEndStepPct } from 'features/controlLayers/components/ControlAndIPAdapter/ControlAdapterBeginEndStepPct';
-import { ControlAdapterWeight } from 'features/controlLayers/components/ControlAndIPAdapter/ControlAdapterWeight';
-import { IPAdapterImagePreview } from 'features/controlLayers/components/ControlAndIPAdapter/IPAdapterImagePreview';
-import { IPAdapterMethod } from 'features/controlLayers/components/ControlAndIPAdapter/IPAdapterMethod';
-import { IPAdapterModelSelect } from 'features/controlLayers/components/ControlAndIPAdapter/IPAdapterModelSelect';
-import type { CLIPVisionModelV2, IPAdapterConfigV2, IPMethodV2 } from 'features/controlLayers/util/controlAdapters';
-import type { TypesafeDroppableData } from 'features/dnd/types';
-import { memo } from 'react';
-import type { ImageDTO, IPAdapterModelConfig, PostUploadAction } from 'services/api/types';
-
-type Props = {
-  ipAdapter: IPAdapterConfigV2;
-  onChangeBeginEndStepPct: (beginEndStepPct: [number, number]) => void;
-  onChangeWeight: (weight: number) => void;
-  onChangeIPMethod: (method: IPMethodV2) => void;
-  onChangeModel: (modelConfig: IPAdapterModelConfig) => void;
-  onChangeCLIPVisionModel: (clipVisionModel: CLIPVisionModelV2) => void;
-  onChangeImage: (imageDTO: ImageDTO | null) => void;
-  droppableData: TypesafeDroppableData;
-  postUploadAction: PostUploadAction;
-};
-
-export const IPAdapter = memo(
-  ({
-    ipAdapter,
-    onChangeBeginEndStepPct,
-    onChangeWeight,
-    onChangeIPMethod,
-    onChangeModel,
-    onChangeCLIPVisionModel,
-    onChangeImage,
-    droppableData,
-    postUploadAction,
-  }: Props) => {
-    return (
-      <Flex flexDir="column" gap={4} position="relative" w="full">
-        <Flex gap={3} alignItems="center" w="full">
-          <Box minW={0} w="full" transitionProperty="common" transitionDuration="0.1s">
-            <IPAdapterModelSelect
-              modelKey={ipAdapter.model?.key ?? null}
-              onChangeModel={onChangeModel}
-              clipVisionModel={ipAdapter.clipVisionModel}
-              onChangeCLIPVisionModel={onChangeCLIPVisionModel}
-            />
-          </Box>
-        </Flex>
-        <Flex gap={4} w="full" alignItems="center">
-          <Flex flexDir="column" gap={3} w="full">
-            <IPAdapterMethod method={ipAdapter.method} onChange={onChangeIPMethod} />
-            <ControlAdapterWeight weight={ipAdapter.weight} onChange={onChangeWeight} />
-            <ControlAdapterBeginEndStepPct
-              beginEndStepPct={ipAdapter.beginEndStepPct}
-              onChange={onChangeBeginEndStepPct}
-            />
-          </Flex>
-          <Flex alignItems="center" justifyContent="center" h={36} w={36} aspectRatio="1/1">
-            <IPAdapterImagePreview
-              image={ipAdapter.image}
-              onChangeImage={onChangeImage}
-              ipAdapterId={ipAdapter.id}
-              droppableData={droppableData}
-              postUploadAction={postUploadAction}
-            />
-          </Flex>
-        </Flex>
-      </Flex>
-    );
-  }
-);
-
-IPAdapter.displayName = 'IPAdapter';

invokeai/frontend/web/src/features/controlLayers/components/ControlAndIPAdapter/IPAdapterImagePreview.tsx

@@ -1,113 +0,0 @@
-import type { SystemStyleObject } from '@invoke-ai/ui-library';
-import { Flex, useShiftModifier } from '@invoke-ai/ui-library';
-import { skipToken } from '@reduxjs/toolkit/query';
-import { useAppDispatch, useAppSelector } from 'app/store/storeHooks';
-import IAIDndImage from 'common/components/IAIDndImage';
-import IAIDndImageIcon from 'common/components/IAIDndImageIcon';
-import { setBoundingBoxDimensions } from 'features/canvas/store/canvasSlice';
-import { heightChanged, widthChanged } from 'features/controlLayers/store/controlLayersSlice';
-import type { ImageWithDims } from 'features/controlLayers/util/controlAdapters';
-import type { ImageDraggableData, TypesafeDroppableData } from 'features/dnd/types';
-import { calculateNewSize } from 'features/parameters/components/ImageSize/calculateNewSize';
-import { selectOptimalDimension } from 'features/parameters/store/generationSlice';
-import { activeTabNameSelector } from 'features/ui/store/uiSelectors';
-import { memo, useCallback, useEffect, useMemo } from 'react';
-import { useTranslation } from 'react-i18next';
-import { PiArrowCounterClockwiseBold, PiRulerBold } from 'react-icons/pi';
-import { useGetImageDTOQuery } from 'services/api/endpoints/images';
-import type { ImageDTO, PostUploadAction } from 'services/api/types';
-
-type Props = {
-  image: ImageWithDims | null;
-  onChangeImage: (imageDTO: ImageDTO | null) => void;
-  ipAdapterId: string; // required for the dnd/upload interactions
-  droppableData: TypesafeDroppableData;
-  postUploadAction: PostUploadAction;
-};
-
-export const IPAdapterImagePreview = memo(
-  ({ image, onChangeImage, ipAdapterId, droppableData, postUploadAction }: Props) => {
-    const { t } = useTranslation();
-    const dispatch = useAppDispatch();
-    const isConnected = useAppSelector((s) => s.system.isConnected);
-    const activeTabName = useAppSelector(activeTabNameSelector);
-    const optimalDimension = useAppSelector(selectOptimalDimension);
-    const shift = useShiftModifier();
-
-    const { currentData: controlImage, isError: isErrorControlImage } = useGetImageDTOQuery(image?.name ?? skipToken);
-    const handleResetControlImage = useCallback(() => {
-      onChangeImage(null);
-    }, [onChangeImage]);
-
-    const handleSetControlImageToDimensions = useCallback(() => {
-      if (!controlImage) {
-        return;
-      }
-
-      if (activeTabName === 'canvas') {
-        dispatch(
-          setBoundingBoxDimensions({ width: controlImage.width, height: controlImage.height }, optimalDimension)
-        );
-      } else {
-        const options = { updateAspectRatio: true, clamp: true };
-        if (shift) {
-          const { width, height } = controlImage;
-          dispatch(widthChanged({ width, ...options }));
-          dispatch(heightChanged({ height, ...options }));
-        } else {
-          const { width, height } = calculateNewSize(
-            controlImage.width / controlImage.height,
-            optimalDimension * optimalDimension
-          );
-          dispatch(widthChanged({ width, ...options }));
-          dispatch(heightChanged({ height, ...options }));
-        }
-      }
-    }, [controlImage, activeTabName, dispatch, optimalDimension, shift]);
-
-    const draggableData = useMemo<ImageDraggableData | undefined>(() => {
-      if (controlImage) {
-        return {
-          id: ipAdapterId,
-          payloadType: 'IMAGE_DTO',
-          payload: { imageDTO: controlImage },
-        };
-      }
-    }, [controlImage, ipAdapterId]);
-
-    useEffect(() => {
-      if (isConnected && isErrorControlImage) {
-        handleResetControlImage();
-      }
-    }, [handleResetControlImage, isConnected, isErrorControlImage]);
-
-    return (
-      <Flex position="relative" w="full" h={36} alignItems="center" justifyContent="center">
-        <IAIDndImage
-          draggableData={draggableData}
-          droppableData={droppableData}
-          imageDTO={controlImage}
-          postUploadAction={postUploadAction}
-        />
-
-        <>
-          <IAIDndImageIcon
-            onClick={handleResetControlImage}
-            icon={controlImage ? <PiArrowCounterClockwiseBold size={16} /> : undefined}
-            tooltip={t('controlnet.resetControlImage')}
-          />
-          <IAIDndImageIcon
-            onClick={handleSetControlImageToDimensions}
-            icon={controlImage ? <PiRulerBold size={16} /> : undefined}
-            tooltip={shift ? t('controlnet.setControlImageDimensionsForce') : t('controlnet.setControlImageDimensions')}
-            styleOverrides={setControlImageDimensionsStyleOverrides}
-          />
-        </>
-      </Flex>
-    );
-  }
-);
-
-IPAdapterImagePreview.displayName = 'IPAdapterImagePreview';
-
-const setControlImageDimensionsStyleOverrides: SystemStyleObject = { mt: 6 };

invokeai/frontend/web/src/features/controlLayers/components/ControlAndIPAdapter/IPAdapterMethod.tsx

@@ -1,44 +0,0 @@
-import type { ComboboxOnChange } from '@invoke-ai/ui-library';
-import { Combobox, FormControl, FormLabel } from '@invoke-ai/ui-library';
-import { InformationalPopover } from 'common/components/InformationalPopover/InformationalPopover';
-import type { IPMethodV2 } from 'features/controlLayers/util/controlAdapters';
-import { isIPMethodV2 } from 'features/controlLayers/util/controlAdapters';
-import { memo, useCallback, useMemo } from 'react';
-import { useTranslation } from 'react-i18next';
-import { assert } from 'tsafe';
-
-type Props = {
-  method: IPMethodV2;
-  onChange: (method: IPMethodV2) => void;
-};
-
-export const IPAdapterMethod = memo(({ method, onChange }: Props) => {
-  const { t } = useTranslation();
-  const options: { label: string; value: IPMethodV2 }[] = useMemo(
-    () => [
-      { label: t('controlnet.full'), value: 'full' },
-      { label: `${t('controlnet.style')} (${t('common.beta')})`, value: 'style' },
-      { label: `${t('controlnet.composition')} (${t('common.beta')})`, value: 'composition' },
-    ],
-    [t]
-  );
-  const _onChange = useCallback<ComboboxOnChange>(
-    (v) => {
-      assert(isIPMethodV2(v?.value));
-      onChange(v.value);
-    },
-    [onChange]
-  );
-  const value = useMemo(() => options.find((o) => o.value === method), [options, method]);
-
-  return (
-    <FormControl>
-      <InformationalPopover feature="ipAdapterMethod">
-        <FormLabel>{t('controlnet.ipAdapterMethod')}</FormLabel>
-      </InformationalPopover>
-      <Combobox value={value} options={options} onChange={_onChange} />
-    </FormControl>
-  );
-});
-
-IPAdapterMethod.displayName = 'IPAdapterMethod';

invokeai/frontend/web/src/features/controlLayers/components/ControlAndIPAdapter/IPAdapterModelSelect.tsx

@@ -1,100 +0,0 @@
-import type { ComboboxOnChange } from '@invoke-ai/ui-library';
-import { Combobox, Flex, FormControl, Tooltip } from '@invoke-ai/ui-library';
-import { useAppSelector } from 'app/store/storeHooks';
-import { useGroupedModelCombobox } from 'common/hooks/useGroupedModelCombobox';
-import type { CLIPVisionModelV2 } from 'features/controlLayers/util/controlAdapters';
-import { isCLIPVisionModelV2 } from 'features/controlLayers/util/controlAdapters';
-import { memo, useCallback, useMemo } from 'react';
-import { useTranslation } from 'react-i18next';
-import { useIPAdapterModels } from 'services/api/hooks/modelsByType';
-import type { AnyModelConfig, IPAdapterModelConfig } from 'services/api/types';
-import { assert } from 'tsafe';
-
-const CLIP_VISION_OPTIONS = [
-  { label: 'ViT-H', value: 'ViT-H' },
-  { label: 'ViT-G', value: 'ViT-G' },
-];
-
-type Props = {
-  modelKey: string | null;
-  onChangeModel: (modelConfig: IPAdapterModelConfig) => void;
-  clipVisionModel: CLIPVisionModelV2;
-  onChangeCLIPVisionModel: (clipVisionModel: CLIPVisionModelV2) => void;
-};
-
-export const IPAdapterModelSelect = memo(
-  ({ modelKey, onChangeModel, clipVisionModel, onChangeCLIPVisionModel }: Props) => {
-    const { t } = useTranslation();
-    const currentBaseModel = useAppSelector((s) => s.generation.model?.base);
-    const [modelConfigs, { isLoading }] = useIPAdapterModels();
-    const selectedModel = useMemo(() => modelConfigs.find((m) => m.key === modelKey), [modelConfigs, modelKey]);
-
-    const _onChangeModel = useCallback(
-      (modelConfig: IPAdapterModelConfig | null) => {
-        if (!modelConfig) {
-          return;
-        }
-        onChangeModel(modelConfig);
-      },
-      [onChangeModel]
-    );
-
-    const _onChangeCLIPVisionModel = useCallback<ComboboxOnChange>(
-      (v) => {
-        assert(isCLIPVisionModelV2(v?.value));
-        onChangeCLIPVisionModel(v.value);
-      },
-      [onChangeCLIPVisionModel]
-    );
-
-    const getIsDisabled = useCallback(
-      (model: AnyModelConfig): boolean => {
-        const isCompatible = currentBaseModel === model.base;
-        const hasMainModel = Boolean(currentBaseModel);
-        return !hasMainModel || !isCompatible;
-      },
-      [currentBaseModel]
-    );
-
-    const { options, value, onChange, noOptionsMessage } = useGroupedModelCombobox({
-      modelConfigs,
-      onChange: _onChangeModel,
-      selectedModel,
-      getIsDisabled,
-      isLoading,
-    });
-
-    const clipVisionModelValue = useMemo(
-      () => CLIP_VISION_OPTIONS.find((o) => o.value === clipVisionModel),
-      [clipVisionModel]
-    );
-
-    return (
-      <Flex gap={4}>
-        <Tooltip label={selectedModel?.description}>
-          <FormControl isInvalid={!value || currentBaseModel !== selectedModel?.base} w="full">
-            <Combobox
-              options={options}
-              placeholder={t('controlnet.selectModel')}
-              value={value}
-              onChange={onChange}
-              noOptionsMessage={noOptionsMessage}
-            />
-          </FormControl>
-        </Tooltip>
-        {selectedModel?.format === 'checkpoint' && (
-          <FormControl isInvalid={!value || currentBaseModel !== selectedModel?.base} width="max-content" minWidth={28}>
-            <Combobox
-              options={CLIP_VISION_OPTIONS}
-              placeholder={t('controlnet.selectCLIPVisionModel')}
-              value={clipVisionModelValue}
-              onChange={_onChangeCLIPVisionModel}
-            />
-          </FormControl>
-        )}
-      </Flex>
-    );
-  }
-);
-
-IPAdapterModelSelect.displayName = 'IPAdapterModelSelect';

invokeai/frontend/web/src/features/controlLayers/components/ControlAndIPAdapter/processors/CannyProcessor.tsx

@@ -1,67 +0,0 @@
-import { CompositeNumberInput, CompositeSlider, FormControl, FormLabel } from '@invoke-ai/ui-library';
-import type { ProcessorComponentProps } from 'features/controlLayers/components/ControlAndIPAdapter/processors/types';
-import { CA_PROCESSOR_DATA, type CannyProcessorConfig } from 'features/controlLayers/util/controlAdapters';
-import { useCallback } from 'react';
-import { useTranslation } from 'react-i18next';
-
-import ProcessorWrapper from './ProcessorWrapper';
-
-type Props = ProcessorComponentProps<CannyProcessorConfig>;
-const DEFAULTS = CA_PROCESSOR_DATA['canny_image_processor'].buildDefaults();
-
-export const CannyProcessor = ({ onChange, config }: Props) => {
-  const { t } = useTranslation();
-  const handleLowThresholdChanged = useCallback(
-    (v: number) => {
-      onChange({ ...config, low_threshold: v });
-    },
-    [onChange, config]
-  );
-  const handleHighThresholdChanged = useCallback(
-    (v: number) => {
-      onChange({ ...config, high_threshold: v });
-    },
-    [onChange, config]
-  );
-
-  return (
-    <ProcessorWrapper>
-      <FormControl>
-        <FormLabel m={0}>{t('controlnet.lowThreshold')}</FormLabel>
-        <CompositeSlider
-          value={config.low_threshold}
-          onChange={handleLowThresholdChanged}
-          defaultValue={DEFAULTS.low_threshold}
-          min={0}
-          max={255}
-        />
-        <CompositeNumberInput
-          value={config.low_threshold}
-          onChange={handleLowThresholdChanged}
-          defaultValue={DEFAULTS.low_threshold}
-          min={0}
-          max={255}
-        />
-      </FormControl>
-      <FormControl>
-        <FormLabel m={0}>{t('controlnet.highThreshold')}</FormLabel>
-        <CompositeSlider
-          value={config.high_threshold}
-          onChange={handleHighThresholdChanged}
-          defaultValue={DEFAULTS.high_threshold}
-          min={0}
-          max={255}
-        />
-        <CompositeNumberInput
-          value={config.high_threshold}
-          onChange={handleHighThresholdChanged}
-          defaultValue={DEFAULTS.high_threshold}
-          min={0}
-          max={255}
-        />
-      </FormControl>
-    </ProcessorWrapper>
-  );
-};
-
-CannyProcessor.displayName = 'CannyProcessor';

invokeai/frontend/web/src/features/controlLayers/components/ControlAndIPAdapter/processors/ColorMapProcessor.tsx

@@ -1,47 +0,0 @@
-import { CompositeNumberInput, CompositeSlider, FormControl, FormLabel } from '@invoke-ai/ui-library';
-import type { ProcessorComponentProps } from 'features/controlLayers/components/ControlAndIPAdapter/processors/types';
-import { CA_PROCESSOR_DATA, type ColorMapProcessorConfig } from 'features/controlLayers/util/controlAdapters';
-import { memo, useCallback } from 'react';
-import { useTranslation } from 'react-i18next';
-
-import ProcessorWrapper from './ProcessorWrapper';
-
-type Props = ProcessorComponentProps<ColorMapProcessorConfig>;
-const DEFAULTS = CA_PROCESSOR_DATA['color_map_image_processor'].buildDefaults();
-
-export const ColorMapProcessor = memo(({ onChange, config }: Props) => {
-  const { t } = useTranslation();
-  const handleColorMapTileSizeChanged = useCallback(
-    (v: number) => {
-      onChange({ ...config, color_map_tile_size: v });
-    },
-    [config, onChange]
-  );
-
-  return (
-    <ProcessorWrapper>
-      <FormControl>
-        <FormLabel m={0}>{t('controlnet.colorMapTileSize')}</FormLabel>
-        <CompositeSlider
-          value={config.color_map_tile_size}
-          defaultValue={DEFAULTS.color_map_tile_size}
-          onChange={handleColorMapTileSizeChanged}
-          min={1}
-          max={256}
-          step={1}
-          marks
-        />
-        <CompositeNumberInput
-          value={config.color_map_tile_size}
-          defaultValue={DEFAULTS.color_map_tile_size}
-          onChange={handleColorMapTileSizeChanged}
-          min={1}
-          max={4096}
-          step={1}
-        />
-      </FormControl>
-    </ProcessorWrapper>
-  );
-});
-
-ColorMapProcessor.displayName = 'ColorMapProcessor';

invokeai/frontend/web/src/features/controlLayers/components/ControlAndIPAdapter/processors/ContentShuffleProcessor.tsx

@@ -1,79 +0,0 @@
-import { CompositeNumberInput, CompositeSlider, FormControl, FormLabel } from '@invoke-ai/ui-library';
-import type { ProcessorComponentProps } from 'features/controlLayers/components/ControlAndIPAdapter/processors/types';
-import type { ContentShuffleProcessorConfig } from 'features/controlLayers/util/controlAdapters';
-import { CA_PROCESSOR_DATA } from 'features/controlLayers/util/controlAdapters';
-import { memo, useCallback } from 'react';
-import { useTranslation } from 'react-i18next';
-
-import ProcessorWrapper from './ProcessorWrapper';
-
-type Props = ProcessorComponentProps<ContentShuffleProcessorConfig>;
-const DEFAULTS = CA_PROCESSOR_DATA['content_shuffle_image_processor'].buildDefaults();
-
-export const ContentShuffleProcessor = memo(({ onChange, config }: Props) => {
-  const { t } = useTranslation();
-
-  const handleWChanged = useCallback(
-    (v: number) => {
-      onChange({ ...config, w: v });
-    },
-    [config, onChange]
-  );
-
-  const handleHChanged = useCallback(
-    (v: number) => {
-      onChange({ ...config, h: v });
-    },
-    [config, onChange]
-  );
-
-  const handleFChanged = useCallback(
-    (v: number) => {
-      onChange({ ...config, f: v });
-    },
-    [config, onChange]
-  );
-
-  return (
-    <ProcessorWrapper>
-      <FormControl>
-        <FormLabel m={0}>{t('controlnet.w')}</FormLabel>
-        <CompositeSlider
-          value={config.w}
-          defaultValue={DEFAULTS.w}
-          onChange={handleWChanged}
-          min={0}
-          max={4096}
-          marks
-        />
-        <CompositeNumberInput value={config.w} defaultValue={DEFAULTS.w} onChange={handleWChanged} min={0} max={4096} />
-      </FormControl>
-      <FormControl>
-        <FormLabel m={0}>{t('controlnet.h')}</FormLabel>
-        <CompositeSlider
-          value={config.h}
-          defaultValue={DEFAULTS.h}
-          onChange={handleHChanged}
-          min={0}
-          max={4096}
-          marks
-        />
-        <CompositeNumberInput value={config.h} defaultValue={DEFAULTS.h} onChange={handleHChanged} min={0} max={4096} />
-      </FormControl>
-      <FormControl>
-        <FormLabel m={0}>{t('controlnet.f')}</FormLabel>
-        <CompositeSlider
-          value={config.f}
-          defaultValue={DEFAULTS.f}
-          onChange={handleFChanged}
-          min={0}
-          max={4096}
-          marks
-        />
-        <CompositeNumberInput value={config.f} defaultValue={DEFAULTS.f} onChange={handleFChanged} min={0} max={4096} />
-      </FormControl>
-    </ProcessorWrapper>
-  );
-});
-
-ContentShuffleProcessor.displayName = 'ContentShuffleProcessor';

invokeai/frontend/web/src/features/controlLayers/components/ControlAndIPAdapter/processors/DWOpenposeProcessor.tsx

@@ -1,62 +0,0 @@
-import { Flex, FormControl, FormLabel, Switch } from '@invoke-ai/ui-library';
-import type { ProcessorComponentProps } from 'features/controlLayers/components/ControlAndIPAdapter/processors/types';
-import type { DWOpenposeProcessorConfig } from 'features/controlLayers/util/controlAdapters';
-import { CA_PROCESSOR_DATA } from 'features/controlLayers/util/controlAdapters';
-import type { ChangeEvent } from 'react';
-import { memo, useCallback } from 'react';
-import { useTranslation } from 'react-i18next';
-
-import ProcessorWrapper from './ProcessorWrapper';
-
-type Props = ProcessorComponentProps<DWOpenposeProcessorConfig>;
-const DEFAULTS = CA_PROCESSOR_DATA['dw_openpose_image_processor'].buildDefaults();
-
-export const DWOpenposeProcessor = memo(({ onChange, config }: Props) => {
-  const { t } = useTranslation();
-
-  const handleDrawBodyChanged = useCallback(
-    (e: ChangeEvent<HTMLInputElement>) => {
-      onChange({ ...config, draw_body: e.target.checked });
-    },
-    [config, onChange]
-  );
-
-  const handleDrawFaceChanged = useCallback(
-    (e: ChangeEvent<HTMLInputElement>) => {
-      onChange({ ...config, draw_face: e.target.checked });
-    },
-    [config, onChange]
-  );
-
-  const handleDrawHandsChanged = useCallback(
-    (e: ChangeEvent<HTMLInputElement>) => {
-      onChange({ ...config, draw_hands: e.target.checked });
-    },
-    [config, onChange]
-  );
-
-  return (
-    <ProcessorWrapper>
-      <Flex sx={{ flexDir: 'row', gap: 6 }}>
-        <FormControl w="max-content">
-          <FormLabel m={0}>{t('controlnet.body')}</FormLabel>
-          <Switch defaultChecked={DEFAULTS.draw_body} isChecked={config.draw_body} onChange={handleDrawBodyChanged} />
-        </FormControl>
-        <FormControl w="max-content">
-          <FormLabel m={0}>{t('controlnet.face')}</FormLabel>
-          <Switch defaultChecked={DEFAULTS.draw_face} isChecked={config.draw_face} onChange={handleDrawFaceChanged} />
-        </FormControl>
-        <FormControl w="max-content">
-          <FormLabel m={0}>{t('controlnet.hands')}</FormLabel>
-          <Switch
-            defaultChecked={DEFAULTS.draw_hands}
-            isChecked={config.draw_hands}
-            onChange={handleDrawHandsChanged}
-          />
-        </FormControl>
-      </Flex>
-    </ProcessorWrapper>
-  );
-});
-
-DWOpenposeProcessor.displayName = 'DWOpenposeProcessor';

invokeai/frontend/web/src/features/controlLayers/components/ControlAndIPAdapter/processors/DepthAnythingProcessor.tsx

@@ -1,52 +0,0 @@
-import type { ComboboxOnChange } from '@invoke-ai/ui-library';
-import { Combobox, FormControl, FormLabel } from '@invoke-ai/ui-library';
-import type { ProcessorComponentProps } from 'features/controlLayers/components/ControlAndIPAdapter/processors/types';
-import type { DepthAnythingModelSize, DepthAnythingProcessorConfig } from 'features/controlLayers/util/controlAdapters';
-import { CA_PROCESSOR_DATA, isDepthAnythingModelSize } from 'features/controlLayers/util/controlAdapters';
-import { memo, useCallback, useMemo } from 'react';
-import { useTranslation } from 'react-i18next';
-
-import ProcessorWrapper from './ProcessorWrapper';
-
-type Props = ProcessorComponentProps<DepthAnythingProcessorConfig>;
-const DEFAULTS = CA_PROCESSOR_DATA['depth_anything_image_processor'].buildDefaults();
-
-export const DepthAnythingProcessor = memo(({ onChange, config }: Props) => {
-  const { t } = useTranslation();
-  const handleModelSizeChange = useCallback<ComboboxOnChange>(
-    (v) => {
-      if (!isDepthAnythingModelSize(v?.value)) {
-        return;
-      }
-      onChange({ ...config, model_size: v.value });
-    },
-    [config, onChange]
-  );
-
-  const options: { label: string; value: DepthAnythingModelSize }[] = useMemo(
-    () => [
-      { label: t('controlnet.small'), value: 'small' },
-      { label: t('controlnet.base'), value: 'base' },
-      { label: t('controlnet.large'), value: 'large' },
-    ],
-    [t]
-  );
-
-  const value = useMemo(() => options.filter((o) => o.value === config.model_size)[0], [options, config.model_size]);
-
-  return (
-    <ProcessorWrapper>
-      <FormControl>
-        <FormLabel m={0}>{t('controlnet.modelSize')}</FormLabel>
-        <Combobox
-          value={value}
-          defaultInputValue={DEFAULTS.model_size}
-          options={options}
-          onChange={handleModelSizeChange}
-        />
-      </FormControl>
-    </ProcessorWrapper>
-  );
-});
-
-DepthAnythingProcessor.displayName = 'DepthAnythingProcessor';

invokeai/frontend/web/src/features/controlLayers/components/ControlAndIPAdapter/processors/HedProcessor.tsx

@@ -1,32 +0,0 @@
-import { FormControl, FormLabel, Switch } from '@invoke-ai/ui-library';
-import type { ProcessorComponentProps } from 'features/controlLayers/components/ControlAndIPAdapter/processors/types';
-import type { HedProcessorConfig } from 'features/controlLayers/util/controlAdapters';
-import type { ChangeEvent } from 'react';
-import { memo, useCallback } from 'react';
-import { useTranslation } from 'react-i18next';
-
-import ProcessorWrapper from './ProcessorWrapper';
-
-type Props = ProcessorComponentProps<HedProcessorConfig>;
-
-export const HedProcessor = memo(({ onChange, config }: Props) => {
-  const { t } = useTranslation();
-
-  const handleScribbleChanged = useCallback(
-    (e: ChangeEvent<HTMLInputElement>) => {
-      onChange({ ...config, scribble: e.target.checked });
-    },
-    [config, onChange]
-  );
-
-  return (
-    <ProcessorWrapper>
-      <FormControl>
-        <FormLabel m={0}>{t('controlnet.scribble')}</FormLabel>
-        <Switch isChecked={config.scribble} onChange={handleScribbleChanged} />
-      </FormControl>
-    </ProcessorWrapper>
-  );
-});
-
-HedProcessor.displayName = 'HedProcessor';

invokeai/frontend/web/src/features/controlLayers/components/ControlAndIPAdapter/processors/LineartProcessor.tsx

@@ -1,32 +0,0 @@
-import { FormControl, FormLabel, Switch } from '@invoke-ai/ui-library';
-import type { ProcessorComponentProps } from 'features/controlLayers/components/ControlAndIPAdapter/processors/types';
-import type { LineartProcessorConfig } from 'features/controlLayers/util/controlAdapters';
-import type { ChangeEvent } from 'react';
-import { memo, useCallback } from 'react';
-import { useTranslation } from 'react-i18next';
-
-import ProcessorWrapper from './ProcessorWrapper';
-
-type Props = ProcessorComponentProps<LineartProcessorConfig>;
-
-export const LineartProcessor = memo(({ onChange, config }: Props) => {
-  const { t } = useTranslation();
-
-  const handleCoarseChanged = useCallback(
-    (e: ChangeEvent<HTMLInputElement>) => {
-      onChange({ ...config, coarse: e.target.checked });
-    },
-    [config, onChange]
-  );
-
-  return (
-    <ProcessorWrapper>
-      <FormControl>
-        <FormLabel m={0}>{t('controlnet.coarse')}</FormLabel>
-        <Switch isChecked={config.coarse} onChange={handleCoarseChanged} />
-      </FormControl>
-    </ProcessorWrapper>
-  );
-});
-
-LineartProcessor.displayName = 'LineartProcessor';

invokeai/frontend/web/src/features/controlLayers/components/ControlAndIPAdapter/processors/MediapipeFaceProcessor.tsx

@@ -1,73 +0,0 @@
-import { CompositeNumberInput, CompositeSlider, FormControl, FormLabel } from '@invoke-ai/ui-library';
-import type { ProcessorComponentProps } from 'features/controlLayers/components/ControlAndIPAdapter/processors/types';
-import { CA_PROCESSOR_DATA, type MediapipeFaceProcessorConfig } from 'features/controlLayers/util/controlAdapters';
-import { memo, useCallback } from 'react';
-import { useTranslation } from 'react-i18next';
-
-import ProcessorWrapper from './ProcessorWrapper';
-
-type Props = ProcessorComponentProps<MediapipeFaceProcessorConfig>;
-const DEFAULTS = CA_PROCESSOR_DATA['mediapipe_face_processor'].buildDefaults();
-
-export const MediapipeFaceProcessor = memo(({ onChange, config }: Props) => {
-  const { t } = useTranslation();
-
-  const handleMaxFacesChanged = useCallback(
-    (v: number) => {
-      onChange({ ...config, max_faces: v });
-    },
-    [config, onChange]
-  );
-
-  const handleMinConfidenceChanged = useCallback(
-    (v: number) => {
-      onChange({ ...config, min_confidence: v });
-    },
-    [config, onChange]
-  );
-
-  return (
-    <ProcessorWrapper>
-      <FormControl>
-        <FormLabel m={0}>{t('controlnet.maxFaces')}</FormLabel>
-        <CompositeSlider
-          value={config.max_faces}
-          onChange={handleMaxFacesChanged}
-          defaultValue={DEFAULTS.max_faces}
-          min={1}
-          max={20}
-          marks
-        />
-        <CompositeNumberInput
-          value={config.max_faces}
-          onChange={handleMaxFacesChanged}
-          defaultValue={DEFAULTS.max_faces}
-          min={1}
-          max={20}
-        />
-      </FormControl>
-      <FormControl>
-        <FormLabel m={0}>{t('controlnet.minConfidence')}</FormLabel>
-        <CompositeSlider
-          value={config.min_confidence}
-          onChange={handleMinConfidenceChanged}
-          defaultValue={DEFAULTS.min_confidence}
-          min={0}
-          max={1}
-          step={0.01}
-          marks
-        />
-        <CompositeNumberInput
-          value={config.min_confidence}
-          onChange={handleMinConfidenceChanged}
-          defaultValue={DEFAULTS.min_confidence}
-          min={0}
-          max={1}
-          step={0.01}
-        />
-      </FormControl>
-    </ProcessorWrapper>
-  );
-});
-
-MediapipeFaceProcessor.displayName = 'MediapipeFaceProcessor';

invokeai/frontend/web/src/features/controlLayers/components/ControlAndIPAdapter/processors/MidasDepthProcessor.tsx

@@ -1,76 +0,0 @@
-import { CompositeNumberInput, CompositeSlider, FormControl, FormLabel } from '@invoke-ai/ui-library';
-import type { ProcessorComponentProps } from 'features/controlLayers/components/ControlAndIPAdapter/processors/types';
-import type { MidasDepthProcessorConfig } from 'features/controlLayers/util/controlAdapters';
-import { CA_PROCESSOR_DATA } from 'features/controlLayers/util/controlAdapters';
-import { memo, useCallback } from 'react';
-import { useTranslation } from 'react-i18next';
-
-import ProcessorWrapper from './ProcessorWrapper';
-
-type Props = ProcessorComponentProps<MidasDepthProcessorConfig>;
-const DEFAULTS = CA_PROCESSOR_DATA['midas_depth_image_processor'].buildDefaults();
-
-export const MidasDepthProcessor = memo(({ onChange, config }: Props) => {
-  const { t } = useTranslation();
-
-  const handleAMultChanged = useCallback(
-    (v: number) => {
-      onChange({ ...config, a_mult: v });
-    },
-    [config, onChange]
-  );
-
-  const handleBgThChanged = useCallback(
-    (v: number) => {
-      onChange({ ...config, bg_th: v });
-    },
-    [config, onChange]
-  );
-
-  return (
-    <ProcessorWrapper>
-      <FormControl>
-        <FormLabel m={0}>{t('controlnet.amult')}</FormLabel>
-        <CompositeSlider
-          value={config.a_mult}
-          onChange={handleAMultChanged}
-          defaultValue={DEFAULTS.a_mult}
-          min={0}
-          max={20}
-          step={0.01}
-          marks
-        />
-        <CompositeNumberInput
-          value={config.a_mult}
-          onChange={handleAMultChanged}
-          defaultValue={DEFAULTS.a_mult}
-          min={0}
-          max={20}
-          step={0.01}
-        />
-      </FormControl>
-      <FormControl>
-        <FormLabel m={0}>{t('controlnet.bgth')}</FormLabel>
-        <CompositeSlider
-          value={config.bg_th}
-          onChange={handleBgThChanged}
-          defaultValue={DEFAULTS.bg_th}
-          min={0}
-          max={20}
-          step={0.01}
-          marks
-        />
-        <CompositeNumberInput
-          value={config.bg_th}
-          onChange={handleBgThChanged}
-          defaultValue={DEFAULTS.bg_th}
-          min={0}
-          max={20}
-          step={0.01}
-        />
-      </FormControl>
-    </ProcessorWrapper>
-  );
-});
-
-MidasDepthProcessor.displayName = 'MidasDepthProcessor';

invokeai/frontend/web/src/features/controlLayers/components/ControlAndIPAdapter/processors/MlsdImageProcessor.tsx

@@ -1,76 +0,0 @@
-import { CompositeNumberInput, CompositeSlider, FormControl, FormLabel } from '@invoke-ai/ui-library';
-import type { ProcessorComponentProps } from 'features/controlLayers/components/ControlAndIPAdapter/processors/types';
-import type { MlsdProcessorConfig } from 'features/controlLayers/util/controlAdapters';
-import { CA_PROCESSOR_DATA } from 'features/controlLayers/util/controlAdapters';
-import { memo, useCallback } from 'react';
-import { useTranslation } from 'react-i18next';
-
-import ProcessorWrapper from './ProcessorWrapper';
-
-type Props = ProcessorComponentProps<MlsdProcessorConfig>;
-const DEFAULTS = CA_PROCESSOR_DATA['mlsd_image_processor'].buildDefaults();
-
-export const MlsdImageProcessor = memo(({ onChange, config }: Props) => {
-  const { t } = useTranslation();
-
-  const handleThrDChanged = useCallback(
-    (v: number) => {
-      onChange({ ...config, thr_d: v });
-    },
-    [config, onChange]
-  );
-
-  const handleThrVChanged = useCallback(
-    (v: number) => {
-      onChange({ ...config, thr_v: v });
-    },
-    [config, onChange]
-  );
-
-  return (
-    <ProcessorWrapper>
-      <FormControl>
-        <FormLabel m={0}>{t('controlnet.w')} </FormLabel>
-        <CompositeSlider
-          value={config.thr_d}
-          onChange={handleThrDChanged}
-          defaultValue={DEFAULTS.thr_d}
-          min={0}
-          max={1}
-          step={0.01}
-          marks
-        />
-        <CompositeNumberInput
-          value={config.thr_d}
-          onChange={handleThrDChanged}
-          defaultValue={DEFAULTS.thr_d}
-          min={0}
-          max={1}
-          step={0.01}
-        />
-      </FormControl>
-      <FormControl>
-        <FormLabel m={0}>{t('controlnet.h')} </FormLabel>
-        <CompositeSlider
-          value={config.thr_v}
-          onChange={handleThrVChanged}
-          defaultValue={DEFAULTS.thr_v}
-          min={0}
-          max={1}
-          step={0.01}
-          marks
-        />
-        <CompositeNumberInput
-          value={config.thr_v}
-          onChange={handleThrVChanged}
-          defaultValue={DEFAULTS.thr_v}
-          min={0}
-          max={1}
-          step={0.01}
-        />
-      </FormControl>
-    </ProcessorWrapper>
-  );
-});
-
-MlsdImageProcessor.displayName = 'MlsdImageProcessor';

invokeai/frontend/web/src/features/controlLayers/components/ControlAndIPAdapter/processors/PidiProcessor.tsx

@@ -1,43 +0,0 @@
-import { FormControl, FormLabel, Switch } from '@invoke-ai/ui-library';
-import type { ProcessorComponentProps } from 'features/controlLayers/components/ControlAndIPAdapter/processors/types';
-import type { PidiProcessorConfig } from 'features/controlLayers/util/controlAdapters';
-import type { ChangeEvent } from 'react';
-import { useCallback } from 'react';
-import { useTranslation } from 'react-i18next';
-
-import ProcessorWrapper from './ProcessorWrapper';
-
-type Props = ProcessorComponentProps<PidiProcessorConfig>;
-
-export const PidiProcessor = ({ onChange, config }: Props) => {
-  const { t } = useTranslation();
-
-  const handleScribbleChanged = useCallback(
-    (e: ChangeEvent<HTMLInputElement>) => {
-      onChange({ ...config, scribble: e.target.checked });
-    },
-    [config, onChange]
-  );
-
-  const handleSafeChanged = useCallback(
-    (e: ChangeEvent<HTMLInputElement>) => {
-      onChange({ ...config, safe: e.target.checked });
-    },
-    [config, onChange]
-  );
-
-  return (
-    <ProcessorWrapper>
-      <FormControl>
-        <FormLabel m={0}>{t('controlnet.scribble')}</FormLabel>
-        <Switch isChecked={config.scribble} onChange={handleScribbleChanged} />
-      </FormControl>
-      <FormControl>
-        <FormLabel m={0}>{t('controlnet.safe')}</FormLabel>
-        <Switch isChecked={config.safe} onChange={handleSafeChanged} />
-      </FormControl>
-    </ProcessorWrapper>
-  );
-};
-
-PidiProcessor.displayName = 'PidiProcessor';

invokeai/frontend/web/src/features/controlLayers/components/ControlAndIPAdapter/processors/ProcessorWrapper.tsx

@@ -1,15 +0,0 @@
-import { Flex } from '@invoke-ai/ui-library';
-import type { PropsWithChildren } from 'react';
-import { memo } from 'react';
-
-type Props = PropsWithChildren;
-
-const ProcessorWrapper = (props: Props) => {
-  return (
-    <Flex flexDir="column" gap={3}>
-      {props.children}
-    </Flex>
-  );
-};
-
-export default memo(ProcessorWrapper);

invokeai/frontend/web/src/features/controlLayers/components/ControlAndIPAdapter/processors/types.ts

@@ -1,6 +0,0 @@
-import type { ProcessorConfig } from 'features/controlLayers/util/controlAdapters';
-
-export type ProcessorComponentProps<T extends ProcessorConfig> = {
-  onChange: (config: T) => void;
-  config: T;
-};

invokeai/frontend/web/src/features/controlLayers/components/ControlLayersEditor.stories.tsx

@@ -1,24 +0,0 @@
-import { Flex } from '@invoke-ai/ui-library';
-import type { Meta, StoryObj } from '@storybook/react';
-import { ControlLayersEditor } from 'features/controlLayers/components/ControlLayersEditor';
-
-const meta: Meta<typeof ControlLayersEditor> = {
-  title: 'Feature/ControlLayers',
-  tags: ['autodocs'],
-  component: ControlLayersEditor,
-};
-
-export default meta;
-type Story = StoryObj<typeof ControlLayersEditor>;
-
-const Component = () => {
-  return (
-    <Flex w={1500} h={1500}>
-      <ControlLayersEditor />
-    </Flex>
-  );
-};
-
-export const Default: Story = {
-  render: Component,
-};

invokeai/frontend/web/src/features/controlLayers/components/ControlLayersPanelContent.tsx

@@ -1,69 +0,0 @@
-/* eslint-disable i18next/no-literal-string */
-import { Flex } from '@invoke-ai/ui-library';
-import { createMemoizedSelector } from 'app/store/createMemoizedSelector';
-import { useAppSelector } from 'app/store/storeHooks';
-import { IAINoContentFallback } from 'common/components/IAIImageFallback';
-import ScrollableContent from 'common/components/OverlayScrollbars/ScrollableContent';
-import { AddLayerButton } from 'features/controlLayers/components/AddLayerButton';
-import { CALayer } from 'features/controlLayers/components/CALayer/CALayer';
-import { DeleteAllLayersButton } from 'features/controlLayers/components/DeleteAllLayersButton';
-import { IILayer } from 'features/controlLayers/components/IILayer/IILayer';
-import { IPALayer } from 'features/controlLayers/components/IPALayer/IPALayer';
-import { RGLayer } from 'features/controlLayers/components/RGLayer/RGLayer';
-import { isRenderableLayer, selectControlLayersSlice } from 'features/controlLayers/store/controlLayersSlice';
-import type { Layer } from 'features/controlLayers/store/types';
-import { partition } from 'lodash-es';
-import { memo } from 'react';
-import { useTranslation } from 'react-i18next';
-
-const selectLayerIdTypePairs = createMemoizedSelector(selectControlLayersSlice, (controlLayers) => {
-  const [renderableLayers, ipAdapterLayers] = partition(controlLayers.present.layers, isRenderableLayer);
-  return [...ipAdapterLayers, ...renderableLayers].map((l) => ({ id: l.id, type: l.type })).reverse();
-});
-
-export const ControlLayersPanelContent = memo(() => {
-  const { t } = useTranslation();
-  const layerIdTypePairs = useAppSelector(selectLayerIdTypePairs);
-  return (
-    <Flex flexDir="column" gap={2} w="full" h="full">
-      <Flex justifyContent="space-around">
-        <AddLayerButton />
-        <DeleteAllLayersButton />
-      </Flex>
-      {layerIdTypePairs.length > 0 && (
-        <ScrollableContent>
-          <Flex flexDir="column" gap={2} data-testid="control-layers-layer-list">
-            {layerIdTypePairs.map(({ id, type }) => (
-              <LayerWrapper key={id} id={id} type={type} />
-            ))}
-          </Flex>
-        </ScrollableContent>
-      )}
-      {layerIdTypePairs.length === 0 && <IAINoContentFallback icon={null} label={t('controlLayers.noLayersAdded')} />}
-    </Flex>
-  );
-});
-
-ControlLayersPanelContent.displayName = 'ControlLayersPanelContent';
-
-type LayerWrapperProps = {
-  id: string;
-  type: Layer['type'];
-};
-
-const LayerWrapper = memo(({ id, type }: LayerWrapperProps) => {
-  if (type === 'regional_guidance_layer') {
-    return <RGLayer key={id} layerId={id} />;
-  }
-  if (type === 'control_adapter_layer') {
-    return <CALayer key={id} layerId={id} />;
-  }
-  if (type === 'ip_adapter_layer') {
-    return <IPALayer key={id} layerId={id} />;
-  }
-  if (type === 'initial_image_layer') {
-    return <IILayer key={id} layerId={id} />;
-  }
-});
-
-LayerWrapper.displayName = 'LayerWrapper';

invokeai/frontend/web/src/features/controlLayers/components/ControlLayersSettingsPopover.tsx

@@ -1,51 +0,0 @@
-import {
-  Checkbox,
-  Flex,
-  FormControl,
-  FormLabel,
-  IconButton,
-  Popover,
-  PopoverBody,
-  PopoverContent,
-  PopoverTrigger,
-} from '@invoke-ai/ui-library';
-import { useAppDispatch, useAppSelector } from 'app/store/storeHooks';
-import { setShouldInvertBrushSizeScrollDirection } from 'features/canvas/store/canvasSlice';
-import { GlobalMaskLayerOpacity } from 'features/controlLayers/components/GlobalMaskLayerOpacity';
-import type { ChangeEvent } from 'react';
-import { memo, useCallback } from 'react';
-import { useTranslation } from 'react-i18next';
-import { RiSettings4Fill } from 'react-icons/ri';
-
-const ControlLayersSettingsPopover = () => {
-  const { t } = useTranslation();
-  const dispatch = useAppDispatch();
-  const shouldInvertBrushSizeScrollDirection = useAppSelector((s) => s.canvas.shouldInvertBrushSizeScrollDirection);
-  const handleChangeShouldInvertBrushSizeScrollDirection = useCallback(
-    (e: ChangeEvent<HTMLInputElement>) => dispatch(setShouldInvertBrushSizeScrollDirection(e.target.checked)),
-    [dispatch]
-  );
-  return (
-    <Popover isLazy>
-      <PopoverTrigger>
-        <IconButton aria-label={t('common.settingsLabel')} icon={<RiSettings4Fill />} />
-      </PopoverTrigger>
-      <PopoverContent>
-        <PopoverBody>
-          <Flex direction="column" gap={2}>
-            <GlobalMaskLayerOpacity />
-            <FormControl w="full">
-              <FormLabel flexGrow={1}>{t('unifiedCanvas.invertBrushSizeScrollDirection')}</FormLabel>
-              <Checkbox
-                isChecked={shouldInvertBrushSizeScrollDirection}
-                onChange={handleChangeShouldInvertBrushSizeScrollDirection}
-              />
-            </FormControl>
-          </Flex>
-        </PopoverBody>
-      </PopoverContent>
-    </Popover>
-  );
-};
-
-export default memo(ControlLayersSettingsPopover);

invokeai/frontend/web/src/features/controlLayers/components/ControlLayersToolbar.tsx

@@ -1,34 +0,0 @@
-/* eslint-disable i18next/no-literal-string */
-import { Flex } from '@invoke-ai/ui-library';
-import { BrushSize } from 'features/controlLayers/components/BrushSize';
-import ControlLayersSettingsPopover from 'features/controlLayers/components/ControlLayersSettingsPopover';
-import { ToolChooser } from 'features/controlLayers/components/ToolChooser';
-import { UndoRedoButtonGroup } from 'features/controlLayers/components/UndoRedoButtonGroup';
-import { ToggleProgressButton } from 'features/gallery/components/ImageViewer/ToggleProgressButton';
-import { ViewerToggleMenu } from 'features/gallery/components/ImageViewer/ViewerToggleMenu';
-import { memo } from 'react';
-
-export const ControlLayersToolbar = memo(() => {
-  return (
-    <Flex w="full" gap={2}>
-      <Flex flex={1} justifyContent="center">
-        <Flex gap={2} marginInlineEnd="auto">
-          <ToggleProgressButton />
-        </Flex>
-      </Flex>
-      <Flex flex={1} gap={2} justifyContent="center">
-        <BrushSize />
-        <ToolChooser />
-        <UndoRedoButtonGroup />
-        <ControlLayersSettingsPopover />
-      </Flex>
-      <Flex flex={1} justifyContent="center">
-        <Flex gap={2} marginInlineStart="auto">
-          <ViewerToggleMenu />
-        </Flex>
-      </Flex>
-    </Flex>
-  );
-});
-
-ControlLayersToolbar.displayName = 'ControlLayersToolbar';

invokeai/frontend/web/src/features/controlLayers/components/GlobalMaskLayerOpacity.tsx

@@ -1,54 +0,0 @@
-import { CompositeNumberInput, CompositeSlider, Flex, FormControl, FormLabel } from '@invoke-ai/ui-library';
-import { useAppDispatch, useAppSelector } from 'app/store/storeHooks';
-import {
-  globalMaskLayerOpacityChanged,
-  initialControlLayersState,
-} from 'features/controlLayers/store/controlLayersSlice';
-import { memo, useCallback } from 'react';
-import { useTranslation } from 'react-i18next';
-
-const marks = [0, 25, 50, 75, 100];
-const formatPct = (v: number | string) => `${v} %`;
-
-export const GlobalMaskLayerOpacity = memo(() => {
-  const dispatch = useAppDispatch();
-  const { t } = useTranslation();
-  const globalMaskLayerOpacity = useAppSelector((s) =>
-    Math.round(s.controlLayers.present.globalMaskLayerOpacity * 100)
-  );
-  const onChange = useCallback(
-    (v: number) => {
-      dispatch(globalMaskLayerOpacityChanged(v / 100));
-    },
-    [dispatch]
-  );
-  return (
-    <FormControl orientation="vertical">
-      <FormLabel m={0}>{t('controlLayers.globalMaskOpacity')}</FormLabel>
-      <Flex gap={4}>
-        <CompositeSlider
-          min={0}
-          max={100}
-          step={1}
-          value={globalMaskLayerOpacity}
-          defaultValue={initialControlLayersState.globalMaskLayerOpacity * 100}
-          onChange={onChange}
-          marks={marks}
-          minW={48}
-        />
-        <CompositeNumberInput
-          min={0}
-          max={100}
-          step={1}
-          value={globalMaskLayerOpacity}
-          defaultValue={initialControlLayersState.globalMaskLayerOpacity * 100}
-          onChange={onChange}
-          w={28}
-          format={formatPct}
-        />
-      </Flex>
-    </FormControl>
-  );
-});
-
-GlobalMaskLayerOpacity.displayName = 'GlobalMaskLayerOpacity';

invokeai/frontend/web/src/features/controlLayers/components/IILayer/IILayer.tsx

@@ -1,91 +0,0 @@
-import { Flex, Spacer, useDisclosure } from '@invoke-ai/ui-library';
-import { useAppDispatch, useAppSelector } from 'app/store/storeHooks';
-import IILayerOpacity from 'features/controlLayers/components/IILayer/IILayerOpacity';
-import { InitialImagePreview } from 'features/controlLayers/components/IILayer/InitialImagePreview';
-import { LayerDeleteButton } from 'features/controlLayers/components/LayerCommon/LayerDeleteButton';
-import { LayerMenu } from 'features/controlLayers/components/LayerCommon/LayerMenu';
-import { LayerTitle } from 'features/controlLayers/components/LayerCommon/LayerTitle';
-import { LayerVisibilityToggle } from 'features/controlLayers/components/LayerCommon/LayerVisibilityToggle';
-import { LayerWrapper } from 'features/controlLayers/components/LayerCommon/LayerWrapper';
-import {
-  iiLayerDenoisingStrengthChanged,
-  iiLayerImageChanged,
-  layerSelected,
-  selectIILayerOrThrow,
-} from 'features/controlLayers/store/controlLayersSlice';
-import type { IILayerImageDropData } from 'features/dnd/types';
-import ImageToImageStrength from 'features/parameters/components/ImageToImage/ImageToImageStrength';
-import { memo, useCallback, useMemo } from 'react';
-import type { IILayerImagePostUploadAction, ImageDTO } from 'services/api/types';
-
-type Props = {
-  layerId: string;
-};
-
-export const IILayer = memo(({ layerId }: Props) => {
-  const dispatch = useAppDispatch();
-  const layer = useAppSelector((s) => selectIILayerOrThrow(s.controlLayers.present, layerId));
-  const onClick = useCallback(() => {
-    dispatch(layerSelected(layerId));
-  }, [dispatch, layerId]);
-  const { isOpen, onToggle } = useDisclosure({ defaultIsOpen: true });
-
-  const onChangeImage = useCallback(
-    (imageDTO: ImageDTO | null) => {
-      dispatch(iiLayerImageChanged({ layerId, imageDTO }));
-    },
-    [dispatch, layerId]
-  );
-
-  const onChangeDenoisingStrength = useCallback(
-    (denoisingStrength: number) => {
-      dispatch(iiLayerDenoisingStrengthChanged({ layerId, denoisingStrength }));
-    },
-    [dispatch, layerId]
-  );
-
-  const droppableData = useMemo<IILayerImageDropData>(
-    () => ({
-      actionType: 'SET_II_LAYER_IMAGE',
-      context: {
-        layerId,
-      },
-      id: layerId,
-    }),
-    [layerId]
-  );
-
-  const postUploadAction = useMemo<IILayerImagePostUploadAction>(
-    () => ({
-      layerId,
-      type: 'SET_II_LAYER_IMAGE',
-    }),
-    [layerId]
-  );
-
-  return (
-    <LayerWrapper onClick={onClick} borderColor={layer.isSelected ? 'base.400' : 'base.800'}>
-      <Flex gap={3} alignItems="center" p={3} cursor="pointer" onDoubleClick={onToggle}>
-        <LayerVisibilityToggle layerId={layerId} />
-        <LayerTitle type="initial_image_layer" />
-        <Spacer />
-        <IILayerOpacity layerId={layerId} />
-        <LayerMenu layerId={layerId} />
-        <LayerDeleteButton layerId={layerId} />
-      </Flex>
-      {isOpen && (
-        <Flex flexDir="column" gap={3} px={3} pb={3}>
-          <ImageToImageStrength value={layer.denoisingStrength} onChange={onChangeDenoisingStrength} />
-          <InitialImagePreview
-            image={layer.image}
-            onChangeImage={onChangeImage}
-            droppableData={droppableData}
-            postUploadAction={postUploadAction}
-          />
-        </Flex>
-      )}
-    </LayerWrapper>
-  );
-});
-
-IILayer.displayName = 'IILayer';

invokeai/frontend/web/src/features/controlLayers/components/IILayer/IILayerOpacity.tsx

@@ -1,98 +0,0 @@
-import {
-  CompositeNumberInput,
-  CompositeSlider,
-  Flex,
-  FormControl,
-  FormLabel,
-  IconButton,
-  Popover,
-  PopoverArrow,
-  PopoverBody,
-  PopoverContent,
-  PopoverTrigger,
-} from '@invoke-ai/ui-library';
-import { createSelector } from '@reduxjs/toolkit';
-import { useAppDispatch, useAppSelector } from 'app/store/storeHooks';
-import { stopPropagation } from 'common/util/stopPropagation';
-import {
-  iiLayerOpacityChanged,
-  isInitialImageLayer,
-  selectControlLayersSlice,
-} from 'features/controlLayers/store/controlLayersSlice';
-import { memo, useCallback, useMemo } from 'react';
-import { useTranslation } from 'react-i18next';
-import { PiDropHalfFill } from 'react-icons/pi';
-import { assert } from 'tsafe';
-
-type Props = {
-  layerId: string;
-};
-
-const marks = [0, 25, 50, 75, 100];
-const formatPct = (v: number | string) => `${v} %`;
-
-const IILayerOpacity = ({ layerId }: Props) => {
-  const { t } = useTranslation();
-  const dispatch = useAppDispatch();
-  const selectOpacity = useMemo(
-    () =>
-      createSelector(selectControlLayersSlice, (controlLayers) => {
-        const layer = controlLayers.present.layers.filter(isInitialImageLayer).find((l) => l.id === layerId);
-        assert(layer, `Layer ${layerId} not found`);
-        return Math.round(layer.opacity * 100);
-      }),
-    [layerId]
-  );
-  const opacity = useAppSelector(selectOpacity);
-  const onChangeOpacity = useCallback(
-    (v: number) => {
-      dispatch(iiLayerOpacityChanged({ layerId, opacity: v / 100 }));
-    },
-    [dispatch, layerId]
-  );
-  return (
-    <Popover isLazy>
-      <PopoverTrigger>
-        <IconButton
-          aria-label={t('controlLayers.opacity')}
-          size="sm"
-          icon={<PiDropHalfFill size={16} />}
-          variant="ghost"
-          onDoubleClick={stopPropagation}
-        />
-      </PopoverTrigger>
-      <PopoverContent onDoubleClick={stopPropagation}>
-        <PopoverArrow />
-        <PopoverBody>
-          <Flex direction="column" gap={2}>
-            <FormControl orientation="horizontal">
-              <FormLabel m={0}>{t('controlLayers.opacity')}</FormLabel>
-              <CompositeSlider
-                min={0}
-                max={100}
-                step={1}
-                value={opacity}
-                defaultValue={100}
-                onChange={onChangeOpacity}
-                marks={marks}
-                w={48}
-              />
-              <CompositeNumberInput
-                min={0}
-                max={100}
-                step={1}
-                value={opacity}
-                defaultValue={100}
-                onChange={onChangeOpacity}
-                w={24}
-                format={formatPct}
-              />
-            </FormControl>
-          </Flex>
-        </PopoverBody>
-      </PopoverContent>
-    </Popover>
-  );
-};
-
-export default memo(IILayerOpacity);

invokeai/frontend/web/src/features/controlLayers/components/IILayer/InitialImagePreview.tsx

@@ -1,109 +0,0 @@
-import type { SystemStyleObject } from '@invoke-ai/ui-library';
-import { Flex, useShiftModifier } from '@invoke-ai/ui-library';
-import { skipToken } from '@reduxjs/toolkit/query';
-import { useAppDispatch, useAppSelector } from 'app/store/storeHooks';
-import IAIDndImage from 'common/components/IAIDndImage';
-import IAIDndImageIcon from 'common/components/IAIDndImageIcon';
-import { setBoundingBoxDimensions } from 'features/canvas/store/canvasSlice';
-import { heightChanged, widthChanged } from 'features/controlLayers/store/controlLayersSlice';
-import type { ImageWithDims } from 'features/controlLayers/util/controlAdapters';
-import type { ImageDraggableData, TypesafeDroppableData } from 'features/dnd/types';
-import { calculateNewSize } from 'features/parameters/components/ImageSize/calculateNewSize';
-import { selectOptimalDimension } from 'features/parameters/store/generationSlice';
-import { activeTabNameSelector } from 'features/ui/store/uiSelectors';
-import { memo, useCallback, useEffect, useMemo } from 'react';
-import { useTranslation } from 'react-i18next';
-import { PiArrowCounterClockwiseBold, PiRulerBold } from 'react-icons/pi';
-import { useGetImageDTOQuery } from 'services/api/endpoints/images';
-import type { ImageDTO, PostUploadAction } from 'services/api/types';
-
-type Props = {
-  image: ImageWithDims | null;
-  onChangeImage: (imageDTO: ImageDTO | null) => void;
-  droppableData: TypesafeDroppableData;
-  postUploadAction: PostUploadAction;
-};
-
-export const InitialImagePreview = memo(({ image, onChangeImage, droppableData, postUploadAction }: Props) => {
-  const { t } = useTranslation();
-  const dispatch = useAppDispatch();
-  const isConnected = useAppSelector((s) => s.system.isConnected);
-  const activeTabName = useAppSelector(activeTabNameSelector);
-  const optimalDimension = useAppSelector(selectOptimalDimension);
-  const shift = useShiftModifier();
-
-  const { currentData: imageDTO, isError: isErrorControlImage } = useGetImageDTOQuery(image?.name ?? skipToken);
-
-  const onReset = useCallback(() => {
-    onChangeImage(null);
-  }, [onChangeImage]);
-
-  const onUseSize = useCallback(() => {
-    if (!imageDTO) {
-      return;
-    }
-
-    if (activeTabName === 'canvas') {
-      dispatch(setBoundingBoxDimensions({ width: imageDTO.width, height: imageDTO.height }, optimalDimension));
-    } else {
-      const options = { updateAspectRatio: true, clamp: true };
-      if (shift) {
-        const { width, height } = imageDTO;
-        dispatch(widthChanged({ width, ...options }));
-        dispatch(heightChanged({ height, ...options }));
-      } else {
-        const { width, height } = calculateNewSize(
-          imageDTO.width / imageDTO.height,
-          optimalDimension * optimalDimension
-        );
-        dispatch(widthChanged({ width, ...options }));
-        dispatch(heightChanged({ height, ...options }));
-      }
-    }
-  }, [imageDTO, activeTabName, dispatch, optimalDimension, shift]);
-
-  const draggableData = useMemo<ImageDraggableData | undefined>(() => {
-    if (imageDTO) {
-      return {
-        id: 'initial_image_layer',
-        payloadType: 'IMAGE_DTO',
-        payload: { imageDTO: imageDTO },
-      };
-    }
-  }, [imageDTO]);
-
-  useEffect(() => {
-    if (isConnected && isErrorControlImage) {
-      onReset();
-    }
-  }, [onReset, isConnected, isErrorControlImage]);
-
-  return (
-    <Flex position="relative" w="full" h={36} alignItems="center" justifyContent="center">
-      <IAIDndImage
-        draggableData={draggableData}
-        droppableData={droppableData}
-        imageDTO={imageDTO}
-        postUploadAction={postUploadAction}
-      />
-
-      <>
-        <IAIDndImageIcon
-          onClick={onReset}
-          icon={imageDTO ? <PiArrowCounterClockwiseBold size={16} /> : undefined}
-          tooltip={t('controlnet.resetControlImage')}
-        />
-        <IAIDndImageIcon
-          onClick={onUseSize}
-          icon={imageDTO ? <PiRulerBold size={16} /> : undefined}
-          tooltip={shift ? t('controlnet.setControlImageDimensionsForce') : t('controlnet.setControlImageDimensions')}
-          styleOverrides={useSizeStyleOverrides}
-        />
-      </>
-    </Flex>
-  );
-});
-
-InitialImagePreview.displayName = 'InitialImagePreview';
-
-const useSizeStyleOverrides: SystemStyleObject = { mt: 6 };

invokeai/frontend/web/src/features/controlLayers/components/IPALayer/IPALayer.tsx

@@ -1,39 +0,0 @@
-import { Flex, Spacer, useDisclosure } from '@invoke-ai/ui-library';
-import { useAppDispatch, useAppSelector } from 'app/store/storeHooks';
-import { IPALayerIPAdapterWrapper } from 'features/controlLayers/components/IPALayer/IPALayerIPAdapterWrapper';
-import { LayerDeleteButton } from 'features/controlLayers/components/LayerCommon/LayerDeleteButton';
-import { LayerTitle } from 'features/controlLayers/components/LayerCommon/LayerTitle';
-import { LayerVisibilityToggle } from 'features/controlLayers/components/LayerCommon/LayerVisibilityToggle';
-import { LayerWrapper } from 'features/controlLayers/components/LayerCommon/LayerWrapper';
-import { layerSelected, selectIPALayerOrThrow } from 'features/controlLayers/store/controlLayersSlice';
-import { memo, useCallback } from 'react';
-
-type Props = {
-  layerId: string;
-};
-
-export const IPALayer = memo(({ layerId }: Props) => {
-  const dispatch = useAppDispatch();
-  const isSelected = useAppSelector((s) => selectIPALayerOrThrow(s.controlLayers.present, layerId).isSelected);
-  const { isOpen, onToggle } = useDisclosure({ defaultIsOpen: true });
-  const onClick = useCallback(() => {
-    dispatch(layerSelected(layerId));
-  }, [dispatch, layerId]);
-  return (
-    <LayerWrapper onClick={onClick} borderColor={isSelected ? 'base.400' : 'base.800'}>
-      <Flex gap={3} alignItems="center" p={3} cursor="pointer" onDoubleClick={onToggle}>
-        <LayerVisibilityToggle layerId={layerId} />
-        <LayerTitle type="ip_adapter_layer" />
-        <Spacer />
-        <LayerDeleteButton layerId={layerId} />
-      </Flex>
-      {isOpen && (
-        <Flex flexDir="column" gap={3} px={3} pb={3}>
-          <IPALayerIPAdapterWrapper layerId={layerId} />
-        </Flex>
-      )}
-    </LayerWrapper>
-  );
-});
-
-IPALayer.displayName = 'IPALayer';

invokeai/frontend/web/src/features/controlLayers/components/IPALayer/IPALayerIPAdapterWrapper.tsx

@@ -1,106 +0,0 @@
-import { useAppDispatch, useAppSelector } from 'app/store/storeHooks';
-import { IPAdapter } from 'features/controlLayers/components/ControlAndIPAdapter/IPAdapter';
-import {
-  caOrIPALayerBeginEndStepPctChanged,
-  caOrIPALayerWeightChanged,
-  ipaLayerCLIPVisionModelChanged,
-  ipaLayerImageChanged,
-  ipaLayerMethodChanged,
-  ipaLayerModelChanged,
-  selectIPALayerOrThrow,
-} from 'features/controlLayers/store/controlLayersSlice';
-import type { CLIPVisionModelV2, IPMethodV2 } from 'features/controlLayers/util/controlAdapters';
-import type { IPALayerImageDropData } from 'features/dnd/types';
-import { memo, useCallback, useMemo } from 'react';
-import type { ImageDTO, IPAdapterModelConfig, IPALayerImagePostUploadAction } from 'services/api/types';
-
-type Props = {
-  layerId: string;
-};
-
-export const IPALayerIPAdapterWrapper = memo(({ layerId }: Props) => {
-  const dispatch = useAppDispatch();
-  const ipAdapter = useAppSelector((s) => selectIPALayerOrThrow(s.controlLayers.present, layerId).ipAdapter);
-
-  const onChangeBeginEndStepPct = useCallback(
-    (beginEndStepPct: [number, number]) => {
-      dispatch(
-        caOrIPALayerBeginEndStepPctChanged({
-          layerId,
-          beginEndStepPct,
-        })
-      );
-    },
-    [dispatch, layerId]
-  );
-
-  const onChangeWeight = useCallback(
-    (weight: number) => {
-      dispatch(caOrIPALayerWeightChanged({ layerId, weight }));
-    },
-    [dispatch, layerId]
-  );
-
-  const onChangeIPMethod = useCallback(
-    (method: IPMethodV2) => {
-      dispatch(ipaLayerMethodChanged({ layerId, method }));
-    },
-    [dispatch, layerId]
-  );
-
-  const onChangeModel = useCallback(
-    (modelConfig: IPAdapterModelConfig) => {
-      dispatch(ipaLayerModelChanged({ layerId, modelConfig }));
-    },
-    [dispatch, layerId]
-  );
-
-  const onChangeCLIPVisionModel = useCallback(
-    (clipVisionModel: CLIPVisionModelV2) => {
-      dispatch(ipaLayerCLIPVisionModelChanged({ layerId, clipVisionModel }));
-    },
-    [dispatch, layerId]
-  );
-
-  const onChangeImage = useCallback(
-    (imageDTO: ImageDTO | null) => {
-      dispatch(ipaLayerImageChanged({ layerId, imageDTO }));
-    },
-    [dispatch, layerId]
-  );
-
-  const droppableData = useMemo<IPALayerImageDropData>(
-    () => ({
-      actionType: 'SET_IPA_LAYER_IMAGE',
-      context: {
-        layerId,
-      },
-      id: layerId,
-    }),
-    [layerId]
-  );
-
-  const postUploadAction = useMemo<IPALayerImagePostUploadAction>(
-    () => ({
-      type: 'SET_IPA_LAYER_IMAGE',
-      layerId,
-    }),
-    [layerId]
-  );
-
-  return (
-    <IPAdapter
-      ipAdapter={ipAdapter}
-      onChangeBeginEndStepPct={onChangeBeginEndStepPct}
-      onChangeWeight={onChangeWeight}
-      onChangeIPMethod={onChangeIPMethod}
-      onChangeModel={onChangeModel}
-      onChangeCLIPVisionModel={onChangeCLIPVisionModel}
-      onChangeImage={onChangeImage}
-      droppableData={droppableData}
-      postUploadAction={postUploadAction}
-    />
-  );
-});
-
-IPALayerIPAdapterWrapper.displayName = 'IPALayerIPAdapterWrapper';

invokeai/frontend/web/src/features/controlLayers/components/LayerCommon/LayerMenu.tsx

@@ -1,61 +0,0 @@
-import { IconButton, Menu, MenuButton, MenuDivider, MenuItem, MenuList } from '@invoke-ai/ui-library';
-import { useAppDispatch } from 'app/store/storeHooks';
-import { stopPropagation } from 'common/util/stopPropagation';
-import { LayerMenuArrangeActions } from 'features/controlLayers/components/LayerCommon/LayerMenuArrangeActions';
-import { LayerMenuRGActions } from 'features/controlLayers/components/LayerCommon/LayerMenuRGActions';
-import { useLayerType } from 'features/controlLayers/hooks/layerStateHooks';
-import { layerDeleted, layerReset } from 'features/controlLayers/store/controlLayersSlice';
-import { memo, useCallback } from 'react';
-import { useTranslation } from 'react-i18next';
-import { PiArrowCounterClockwiseBold, PiDotsThreeVerticalBold, PiTrashSimpleBold } from 'react-icons/pi';
-
-type Props = { layerId: string };
-
-export const LayerMenu = memo(({ layerId }: Props) => {
-  const dispatch = useAppDispatch();
-  const { t } = useTranslation();
-  const layerType = useLayerType(layerId);
-  const resetLayer = useCallback(() => {
-    dispatch(layerReset(layerId));
-  }, [dispatch, layerId]);
-  const deleteLayer = useCallback(() => {
-    dispatch(layerDeleted(layerId));
-  }, [dispatch, layerId]);
-  return (
-    <Menu>
-      <MenuButton
-        as={IconButton}
-        aria-label="Layer menu"
-        size="sm"
-        icon={<PiDotsThreeVerticalBold />}
-        onDoubleClick={stopPropagation} // double click expands the layer
-      />
-      <MenuList>
-        {layerType === 'regional_guidance_layer' && (
-          <>
-            <LayerMenuRGActions layerId={layerId} />
-            <MenuDivider />
-          </>
-        )}
-        {(layerType === 'regional_guidance_layer' ||
-          layerType === 'control_adapter_layer' ||
-          layerType === 'initial_image_layer') && (
-          <>
-            <LayerMenuArrangeActions layerId={layerId} />
-            <MenuDivider />
-          </>
-        )}
-        {layerType === 'regional_guidance_layer' && (
-          <MenuItem onClick={resetLayer} icon={<PiArrowCounterClockwiseBold />}>
-            {t('accessibility.reset')}
-          </MenuItem>
-        )}
-        <MenuItem onClick={deleteLayer} icon={<PiTrashSimpleBold />} color="error.300">
-          {t('common.delete')}
-        </MenuItem>
-      </MenuList>
-    </Menu>
-  );
-});
-
-LayerMenu.displayName = 'LayerMenu';

invokeai/frontend/web/src/features/controlLayers/components/LayerCommon/LayerMenuArrangeActions.tsx

@@ -1,69 +0,0 @@
-import { MenuItem } from '@invoke-ai/ui-library';
-import { createMemoizedSelector } from 'app/store/createMemoizedSelector';
-import { useAppDispatch, useAppSelector } from 'app/store/storeHooks';
-import {
-  isRenderableLayer,
-  layerMovedBackward,
-  layerMovedForward,
-  layerMovedToBack,
-  layerMovedToFront,
-  selectControlLayersSlice,
-} from 'features/controlLayers/store/controlLayersSlice';
-import { memo, useCallback, useMemo } from 'react';
-import { useTranslation } from 'react-i18next';
-import { PiArrowDownBold, PiArrowLineDownBold, PiArrowLineUpBold, PiArrowUpBold } from 'react-icons/pi';
-import { assert } from 'tsafe';
-
-type Props = { layerId: string };
-
-export const LayerMenuArrangeActions = memo(({ layerId }: Props) => {
-  const dispatch = useAppDispatch();
-  const { t } = useTranslation();
-  const selectValidActions = useMemo(
-    () =>
-      createMemoizedSelector(selectControlLayersSlice, (controlLayers) => {
-        const layer = controlLayers.present.layers.find((l) => l.id === layerId);
-        assert(isRenderableLayer(layer), `Layer ${layerId} not found or not an RP layer`);
-        const layerIndex = controlLayers.present.layers.findIndex((l) => l.id === layerId);
-        const layerCount = controlLayers.present.layers.length;
-        return {
-          canMoveForward: layerIndex < layerCount - 1,
-          canMoveBackward: layerIndex > 0,
-          canMoveToFront: layerIndex < layerCount - 1,
-          canMoveToBack: layerIndex > 0,
-        };
-      }),
-    [layerId]
-  );
-  const validActions = useAppSelector(selectValidActions);
-  const moveForward = useCallback(() => {
-    dispatch(layerMovedForward(layerId));
-  }, [dispatch, layerId]);
-  const moveToFront = useCallback(() => {
-    dispatch(layerMovedToFront(layerId));
-  }, [dispatch, layerId]);
-  const moveBackward = useCallback(() => {
-    dispatch(layerMovedBackward(layerId));
-  }, [dispatch, layerId]);
-  const moveToBack = useCallback(() => {
-    dispatch(layerMovedToBack(layerId));
-  }, [dispatch, layerId]);
-  return (
-    <>
-      <MenuItem onClick={moveToFront} isDisabled={!validActions.canMoveToFront} icon={<PiArrowLineUpBold />}>
-        {t('controlLayers.moveToFront')}
-      </MenuItem>
-      <MenuItem onClick={moveForward} isDisabled={!validActions.canMoveForward} icon={<PiArrowUpBold />}>
-        {t('controlLayers.moveForward')}
-      </MenuItem>
-      <MenuItem onClick={moveBackward} isDisabled={!validActions.canMoveBackward} icon={<PiArrowDownBold />}>
-        {t('controlLayers.moveBackward')}
-      </MenuItem>
-      <MenuItem onClick={moveToBack} isDisabled={!validActions.canMoveToBack} icon={<PiArrowLineDownBold />}>
-        {t('controlLayers.moveToBack')}
-      </MenuItem>
-    </>
-  );
-});
-
-LayerMenuArrangeActions.displayName = 'LayerMenuArrangeActions';

invokeai/frontend/web/src/features/controlLayers/components/LayerCommon/LayerMenuRGActions.tsx

@@ -1,56 +0,0 @@
-import { MenuItem } from '@invoke-ai/ui-library';
-import { createMemoizedSelector } from 'app/store/createMemoizedSelector';
-import { useAppDispatch, useAppSelector } from 'app/store/storeHooks';
-import { useAddIPAdapterToIPALayer } from 'features/controlLayers/hooks/addLayerHooks';
-import {
-  isRegionalGuidanceLayer,
-  rgLayerNegativePromptChanged,
-  rgLayerPositivePromptChanged,
-  selectControlLayersSlice,
-} from 'features/controlLayers/store/controlLayersSlice';
-import { memo, useCallback, useMemo } from 'react';
-import { useTranslation } from 'react-i18next';
-import { PiPlusBold } from 'react-icons/pi';
-import { assert } from 'tsafe';
-
-type Props = { layerId: string };
-
-export const LayerMenuRGActions = memo(({ layerId }: Props) => {
-  const dispatch = useAppDispatch();
-  const { t } = useTranslation();
-  const [addIPAdapter, isAddIPAdapterDisabled] = useAddIPAdapterToIPALayer(layerId);
-  const selectValidActions = useMemo(
-    () =>
-      createMemoizedSelector(selectControlLayersSlice, (controlLayers) => {
-        const layer = controlLayers.present.layers.find((l) => l.id === layerId);
-        assert(isRegionalGuidanceLayer(layer), `Layer ${layerId} not found or not an RP layer`);
-        return {
-          canAddPositivePrompt: layer.positivePrompt === null,
-          canAddNegativePrompt: layer.negativePrompt === null,
-        };
-      }),
-    [layerId]
-  );
-  const validActions = useAppSelector(selectValidActions);
-  const addPositivePrompt = useCallback(() => {
-    dispatch(rgLayerPositivePromptChanged({ layerId, prompt: '' }));
-  }, [dispatch, layerId]);
-  const addNegativePrompt = useCallback(() => {
-    dispatch(rgLayerNegativePromptChanged({ layerId, prompt: '' }));
-  }, [dispatch, layerId]);
-  return (
-    <>
-      <MenuItem onClick={addPositivePrompt} isDisabled={!validActions.canAddPositivePrompt} icon={<PiPlusBold />}>
-        {t('controlLayers.addPositivePrompt')}
-      </MenuItem>
-      <MenuItem onClick={addNegativePrompt} isDisabled={!validActions.canAddNegativePrompt} icon={<PiPlusBold />}>
-        {t('controlLayers.addNegativePrompt')}
-      </MenuItem>
-      <MenuItem onClick={addIPAdapter} icon={<PiPlusBold />} isDisabled={isAddIPAdapterDisabled}>
-        {t('controlLayers.addIPAdapter')}
-      </MenuItem>
-    </>
-  );
-});
-
-LayerMenuRGActions.displayName = 'LayerMenuRGActions';

invokeai/frontend/web/src/features/controlLayers/components/LayerCommon/LayerTitle.tsx

@@ -1,31 +0,0 @@
-import { Text } from '@invoke-ai/ui-library';
-import type { Layer } from 'features/controlLayers/store/types';
-import { memo, useMemo } from 'react';
-import { useTranslation } from 'react-i18next';
-
-type Props = {
-  type: Layer['type'];
-};
-
-export const LayerTitle = memo(({ type }: Props) => {
-  const { t } = useTranslation();
-  const title = useMemo(() => {
-    if (type === 'regional_guidance_layer') {
-      return t('controlLayers.regionalGuidance');
-    } else if (type === 'control_adapter_layer') {
-      return t('controlLayers.globalControlAdapter');
-    } else if (type === 'ip_adapter_layer') {
-      return t('controlLayers.globalIPAdapter');
-    } else if (type === 'initial_image_layer') {
-      return t('controlLayers.globalInitialImage');
-    }
-  }, [t, type]);
-
-  return (
-    <Text size="sm" fontWeight="semibold" userSelect="none" color="base.300">
-      {title}
-    </Text>
-  );
-});
-
-LayerTitle.displayName = 'LayerTitle';

invokeai/frontend/web/src/features/controlLayers/components/LayerCommon/LayerWrapper.tsx

@@ -1,30 +0,0 @@
-import type { ChakraProps } from '@invoke-ai/ui-library';
-import { Flex } from '@invoke-ai/ui-library';
-import type { PropsWithChildren } from 'react';
-import { memo } from 'react';
-
-type Props = PropsWithChildren<{
-  onClick?: () => void;
-  borderColor: ChakraProps['bg'];
-}>;
-
-export const LayerWrapper = memo(({ onClick, borderColor, children }: Props) => {
-  return (
-    <Flex
-      gap={2}
-      onClick={onClick}
-      bg={borderColor}
-      px={2}
-      borderRadius="base"
-      py="1px"
-      transitionProperty="all"
-      transitionDuration="0.2s"
-    >
-      <Flex flexDir="column" w="full" bg="base.850" borderRadius="base">
-        {children}
-      </Flex>
-    </Flex>
-  );
-});
-
-LayerWrapper.displayName = 'LayerWrapper';

invokeai/frontend/web/src/features/controlLayers/components/RGLayer/RGLayer.tsx

@@ -1,83 +0,0 @@
-import { Badge, Flex, Spacer, useDisclosure } from '@invoke-ai/ui-library';
-import { createMemoizedSelector } from 'app/store/createMemoizedSelector';
-import { useAppDispatch, useAppSelector } from 'app/store/storeHooks';
-import { rgbColorToString } from 'features/canvas/util/colorToString';
-import { AddPromptButtons } from 'features/controlLayers/components/AddPromptButtons';
-import { LayerDeleteButton } from 'features/controlLayers/components/LayerCommon/LayerDeleteButton';
-import { LayerMenu } from 'features/controlLayers/components/LayerCommon/LayerMenu';
-import { LayerTitle } from 'features/controlLayers/components/LayerCommon/LayerTitle';
-import { LayerVisibilityToggle } from 'features/controlLayers/components/LayerCommon/LayerVisibilityToggle';
-import { LayerWrapper } from 'features/controlLayers/components/LayerCommon/LayerWrapper';
-import {
-  isRegionalGuidanceLayer,
-  layerSelected,
-  selectControlLayersSlice,
-} from 'features/controlLayers/store/controlLayersSlice';
-import { memo, useCallback, useMemo } from 'react';
-import { useTranslation } from 'react-i18next';
-import { assert } from 'tsafe';
-
-import { RGLayerColorPicker } from './RGLayerColorPicker';
-import { RGLayerIPAdapterList } from './RGLayerIPAdapterList';
-import { RGLayerNegativePrompt } from './RGLayerNegativePrompt';
-import { RGLayerPositivePrompt } from './RGLayerPositivePrompt';
-import RGLayerSettingsPopover from './RGLayerSettingsPopover';
-
-type Props = {
-  layerId: string;
-};
-
-export const RGLayer = memo(({ layerId }: Props) => {
-  const { t } = useTranslation();
-  const dispatch = useAppDispatch();
-  const selector = useMemo(
-    () =>
-      createMemoizedSelector(selectControlLayersSlice, (controlLayers) => {
-        const layer = controlLayers.present.layers.find((l) => l.id === layerId);
-        assert(isRegionalGuidanceLayer(layer), `Layer ${layerId} not found or not an RP layer`);
-        return {
-          color: rgbColorToString(layer.previewColor),
-          hasPositivePrompt: layer.positivePrompt !== null,
-          hasNegativePrompt: layer.negativePrompt !== null,
-          hasIPAdapters: layer.ipAdapters.length > 0,
-          isSelected: layerId === controlLayers.present.selectedLayerId,
-          autoNegative: layer.autoNegative,
-        };
-      }),
-    [layerId]
-  );
-  const { autoNegative, color, hasPositivePrompt, hasNegativePrompt, hasIPAdapters, isSelected } =
-    useAppSelector(selector);
-  const { isOpen, onToggle } = useDisclosure({ defaultIsOpen: true });
-  const onClick = useCallback(() => {
-    dispatch(layerSelected(layerId));
-  }, [dispatch, layerId]);
-  return (
-    <LayerWrapper onClick={onClick} borderColor={isSelected ? color : 'base.800'}>
-      <Flex gap={3} alignItems="center" p={3} cursor="pointer" onDoubleClick={onToggle}>
-        <LayerVisibilityToggle layerId={layerId} />
-        <LayerTitle type="regional_guidance_layer" />
-        <Spacer />
-        {autoNegative === 'invert' && (
-          <Badge color="base.300" bg="transparent" borderWidth={1} userSelect="none">
-            {t('controlLayers.autoNegative')}
-          </Badge>
-        )}
-        <RGLayerColorPicker layerId={layerId} />
-        <RGLayerSettingsPopover layerId={layerId} />
-        <LayerMenu layerId={layerId} />
-        <LayerDeleteButton layerId={layerId} />
-      </Flex>
-      {isOpen && (
-        <Flex flexDir="column" gap={3} px={3} pb={3}>
-          {!hasPositivePrompt && !hasNegativePrompt && !hasIPAdapters && <AddPromptButtons layerId={layerId} />}
-          {hasPositivePrompt && <RGLayerPositivePrompt layerId={layerId} />}
-          {hasNegativePrompt && <RGLayerNegativePrompt layerId={layerId} />}
-          {hasIPAdapters && <RGLayerIPAdapterList layerId={layerId} />}
-        </Flex>
-      )}
-    </LayerWrapper>
-  );
-});
-
-RGLayer.displayName = 'RGLayer';

invokeai/frontend/web/src/features/controlLayers/components/RGLayer/RGLayerIPAdapterList.tsx

@@ -1,45 +0,0 @@
-import { Divider, Flex } from '@invoke-ai/ui-library';
-import { createMemoizedSelector } from 'app/store/createMemoizedSelector';
-import { useAppSelector } from 'app/store/storeHooks';
-import { RGLayerIPAdapterWrapper } from 'features/controlLayers/components/RGLayer/RGLayerIPAdapterWrapper';
-import { isRegionalGuidanceLayer, selectControlLayersSlice } from 'features/controlLayers/store/controlLayersSlice';
-import { memo, useMemo } from 'react';
-import { assert } from 'tsafe';
-
-type Props = {
-  layerId: string;
-};
-
-export const RGLayerIPAdapterList = memo(({ layerId }: Props) => {
-  const selectIPAdapterIds = useMemo(
-    () =>
-      createMemoizedSelector(selectControlLayersSlice, (controlLayers) => {
-        const layer = controlLayers.present.layers.filter(isRegionalGuidanceLayer).find((l) => l.id === layerId);
-        assert(layer, `Layer ${layerId} not found`);
-        return layer.ipAdapters;
-      }),
-    [layerId]
-  );
-  const ipAdapters = useAppSelector(selectIPAdapterIds);
-
-  if (ipAdapters.length === 0) {
-    return null;
-  }
-
-  return (
-    <>
-      {ipAdapters.map(({ id }, index) => (
-        <Flex flexDir="column" key={id}>
-          {index > 0 && (
-            <Flex pb={3}>
-              <Divider />
-            </Flex>
-          )}
-          <RGLayerIPAdapterWrapper layerId={layerId} ipAdapterId={id} ipAdapterNumber={index + 1} />
-        </Flex>
-      ))}
-    </>
-  );
-});
-
-RGLayerIPAdapterList.displayName = 'RGLayerIPAdapterList';

invokeai/frontend/web/src/features/controlLayers/components/RGLayer/RGLayerIPAdapterWrapper.tsx

@@ -1,131 +0,0 @@
-import { Flex, IconButton, Spacer, Text } from '@invoke-ai/ui-library';
-import { useAppDispatch, useAppSelector } from 'app/store/storeHooks';
-import { IPAdapter } from 'features/controlLayers/components/ControlAndIPAdapter/IPAdapter';
-import {
-  rgLayerIPAdapterBeginEndStepPctChanged,
-  rgLayerIPAdapterCLIPVisionModelChanged,
-  rgLayerIPAdapterDeleted,
-  rgLayerIPAdapterImageChanged,
-  rgLayerIPAdapterMethodChanged,
-  rgLayerIPAdapterModelChanged,
-  rgLayerIPAdapterWeightChanged,
-  selectRGLayerIPAdapterOrThrow,
-} from 'features/controlLayers/store/controlLayersSlice';
-import type { CLIPVisionModelV2, IPMethodV2 } from 'features/controlLayers/util/controlAdapters';
-import type { RGLayerIPAdapterImageDropData } from 'features/dnd/types';
-import { memo, useCallback, useMemo } from 'react';
-import { PiTrashSimpleBold } from 'react-icons/pi';
-import type { ImageDTO, IPAdapterModelConfig, RGLayerIPAdapterImagePostUploadAction } from 'services/api/types';
-
-type Props = {
-  layerId: string;
-  ipAdapterId: string;
-  ipAdapterNumber: number;
-};
-
-export const RGLayerIPAdapterWrapper = memo(({ layerId, ipAdapterId, ipAdapterNumber }: Props) => {
-  const dispatch = useAppDispatch();
-  const onDeleteIPAdapter = useCallback(() => {
-    dispatch(rgLayerIPAdapterDeleted({ layerId, ipAdapterId }));
-  }, [dispatch, ipAdapterId, layerId]);
-  const ipAdapter = useAppSelector((s) => selectRGLayerIPAdapterOrThrow(s.controlLayers.present, layerId, ipAdapterId));
-
-  const onChangeBeginEndStepPct = useCallback(
-    (beginEndStepPct: [number, number]) => {
-      dispatch(
-        rgLayerIPAdapterBeginEndStepPctChanged({
-          layerId,
-          ipAdapterId,
-          beginEndStepPct,
-        })
-      );
-    },
-    [dispatch, ipAdapterId, layerId]
-  );
-
-  const onChangeWeight = useCallback(
-    (weight: number) => {
-      dispatch(rgLayerIPAdapterWeightChanged({ layerId, ipAdapterId, weight }));
-    },
-    [dispatch, ipAdapterId, layerId]
-  );
-
-  const onChangeIPMethod = useCallback(
-    (method: IPMethodV2) => {
-      dispatch(rgLayerIPAdapterMethodChanged({ layerId, ipAdapterId, method }));
-    },
-    [dispatch, ipAdapterId, layerId]
-  );
-
-  const onChangeModel = useCallback(
-    (modelConfig: IPAdapterModelConfig) => {
-      dispatch(rgLayerIPAdapterModelChanged({ layerId, ipAdapterId, modelConfig }));
-    },
-    [dispatch, ipAdapterId, layerId]
-  );
-
-  const onChangeCLIPVisionModel = useCallback(
-    (clipVisionModel: CLIPVisionModelV2) => {
-      dispatch(rgLayerIPAdapterCLIPVisionModelChanged({ layerId, ipAdapterId, clipVisionModel }));
-    },
-    [dispatch, ipAdapterId, layerId]
-  );
-
-  const onChangeImage = useCallback(
-    (imageDTO: ImageDTO | null) => {
-      dispatch(rgLayerIPAdapterImageChanged({ layerId, ipAdapterId, imageDTO }));
-    },
-    [dispatch, ipAdapterId, layerId]
-  );
-
-  const droppableData = useMemo<RGLayerIPAdapterImageDropData>(
-    () => ({
-      actionType: 'SET_RG_LAYER_IP_ADAPTER_IMAGE',
-      context: {
-        layerId,
-        ipAdapterId,
-      },
-      id: layerId,
-    }),
-    [ipAdapterId, layerId]
-  );
-
-  const postUploadAction = useMemo<RGLayerIPAdapterImagePostUploadAction>(
-    () => ({
-      type: 'SET_RG_LAYER_IP_ADAPTER_IMAGE',
-      layerId,
-      ipAdapterId,
-    }),
-    [ipAdapterId, layerId]
-  );
-
-  return (
-    <Flex flexDir="column" gap={3}>
-      <Flex alignItems="center" gap={3}>
-        <Text fontWeight="semibold" color="base.400">{`IP Adapter ${ipAdapterNumber}`}</Text>
-        <Spacer />
-        <IconButton
-          size="sm"
-          icon={<PiTrashSimpleBold />}
-          aria-label="Delete IP Adapter"
-          onClick={onDeleteIPAdapter}
-          variant="ghost"
-          colorScheme="error"
-        />
-      </Flex>
-      <IPAdapter
-        ipAdapter={ipAdapter}
-        onChangeBeginEndStepPct={onChangeBeginEndStepPct}
-        onChangeWeight={onChangeWeight}
-        onChangeIPMethod={onChangeIPMethod}
-        onChangeModel={onChangeModel}
-        onChangeCLIPVisionModel={onChangeCLIPVisionModel}
-        onChangeImage={onChangeImage}
-        droppableData={droppableData}
-        postUploadAction={postUploadAction}
-      />
-    </Flex>
-  );
-});
-
-RGLayerIPAdapterWrapper.displayName = 'RGLayerIPAdapterWrapper';

invokeai/frontend/web/src/features/controlLayers/components/StageComponent.tsx

@@ -1,258 +0,0 @@
-import { Flex } from '@invoke-ai/ui-library';
-import { useStore } from '@nanostores/react';
-import { createSelector } from '@reduxjs/toolkit';
-import { logger } from 'app/logging/logger';
-import { createMemoizedSelector } from 'app/store/createMemoizedSelector';
-import { useAppDispatch, useAppSelector } from 'app/store/storeHooks';
-import { useMouseEvents } from 'features/controlLayers/hooks/mouseEventHooks';
-import {
-  $lastCursorPos,
-  $lastMouseDownPos,
-  $tool,
-  isRegionalGuidanceLayer,
-  layerBboxChanged,
-  layerTranslated,
-  selectControlLayersSlice,
-} from 'features/controlLayers/store/controlLayersSlice';
-import { debouncedRenderers, renderers as normalRenderers } from 'features/controlLayers/util/renderers';
-import Konva from 'konva';
-import type { IRect } from 'konva/lib/types';
-import { memo, useCallback, useLayoutEffect, useMemo, useState } from 'react';
-import { useDevicePixelRatio } from 'use-device-pixel-ratio';
-import { v4 as uuidv4 } from 'uuid';
-
-// This will log warnings when layers > 5 - maybe use `import.meta.env.MODE === 'development'` instead?
-Konva.showWarnings = false;
-
-const log = logger('controlLayers');
-
-const selectSelectedLayerColor = createMemoizedSelector(selectControlLayersSlice, (controlLayers) => {
-  const layer = controlLayers.present.layers
-    .filter(isRegionalGuidanceLayer)
-    .find((l) => l.id === controlLayers.present.selectedLayerId);
-  return layer?.previewColor ?? null;
-});
-
-const selectSelectedLayerType = createSelector(selectControlLayersSlice, (controlLayers) => {
-  const selectedLayer = controlLayers.present.layers.find((l) => l.id === controlLayers.present.selectedLayerId);
-  return selectedLayer?.type ?? null;
-});
-
-const useStageRenderer = (
-  stage: Konva.Stage,
-  container: HTMLDivElement | null,
-  wrapper: HTMLDivElement | null,
-  asPreview: boolean
-) => {
-  const dispatch = useAppDispatch();
-  const state = useAppSelector((s) => s.controlLayers.present);
-  const tool = useStore($tool);
-  const mouseEventHandlers = useMouseEvents();
-  const lastCursorPos = useStore($lastCursorPos);
-  const lastMouseDownPos = useStore($lastMouseDownPos);
-  const selectedLayerIdColor = useAppSelector(selectSelectedLayerColor);
-  const selectedLayerType = useAppSelector(selectSelectedLayerType);
-  const layerIds = useMemo(() => state.layers.map((l) => l.id), [state.layers]);
-  const layerCount = useMemo(() => state.layers.length, [state.layers]);
-  const renderers = useMemo(() => (asPreview ? debouncedRenderers : normalRenderers), [asPreview]);
-  const dpr = useDevicePixelRatio({ round: false });
-
-  const onLayerPosChanged = useCallback(
-    (layerId: string, x: number, y: number) => {
-      dispatch(layerTranslated({ layerId, x, y }));
-    },
-    [dispatch]
-  );
-
-  const onBboxChanged = useCallback(
-    (layerId: string, bbox: IRect | null) => {
-      dispatch(layerBboxChanged({ layerId, bbox }));
-    },
-    [dispatch]
-  );
-
-  useLayoutEffect(() => {
-    log.trace('Initializing stage');
-    if (!container) {
-      return;
-    }
-    stage.container(container);
-    return () => {
-      log.trace('Cleaning up stage');
-      stage.destroy();
-    };
-  }, [container, stage]);
-
-  useLayoutEffect(() => {
-    log.trace('Adding stage listeners');
-    if (asPreview) {
-      return;
-    }
-    stage.on('mousedown', mouseEventHandlers.onMouseDown);
-    stage.on('mouseup', mouseEventHandlers.onMouseUp);
-    stage.on('mousemove', mouseEventHandlers.onMouseMove);
-    stage.on('mouseleave', mouseEventHandlers.onMouseLeave);
-    stage.on('wheel', mouseEventHandlers.onMouseWheel);
-
-    return () => {
-      log.trace('Cleaning up stage listeners');
-      stage.off('mousedown', mouseEventHandlers.onMouseDown);
-      stage.off('mouseup', mouseEventHandlers.onMouseUp);
-      stage.off('mousemove', mouseEventHandlers.onMouseMove);
-      stage.off('mouseleave', mouseEventHandlers.onMouseLeave);
-      stage.off('wheel', mouseEventHandlers.onMouseWheel);
-    };
-  }, [stage, asPreview, mouseEventHandlers]);
-
-  useLayoutEffect(() => {
-    log.trace('Updating stage dimensions');
-    if (!wrapper) {
-      return;
-    }
-
-    const fitStageToContainer = () => {
-      const newXScale = wrapper.offsetWidth / state.size.width;
-      const newYScale = wrapper.offsetHeight / state.size.height;
-      const newScale = Math.min(newXScale, newYScale, 1);
-      stage.width(state.size.width * newScale);
-      stage.height(state.size.height * newScale);
-      stage.scaleX(newScale);
-      stage.scaleY(newScale);
-    };
-
-    const resizeObserver = new ResizeObserver(fitStageToContainer);
-    resizeObserver.observe(wrapper);
-    fitStageToContainer();
-
-    return () => {
-      resizeObserver.disconnect();
-    };
-  }, [stage, state.size.width, state.size.height, wrapper]);
-
-  useLayoutEffect(() => {
-    if (asPreview) {
-      // Preview should not display tool
-      return;
-    }
-    log.trace('Rendering tool preview');
-    renderers.renderToolPreview(
-      stage,
-      tool,
-      selectedLayerIdColor,
-      selectedLayerType,
-      state.globalMaskLayerOpacity,
-      lastCursorPos,
-      lastMouseDownPos,
-      state.brushSize
-    );
-  }, [
-    asPreview,
-    stage,
-    tool,
-    selectedLayerIdColor,
-    selectedLayerType,
-    state.globalMaskLayerOpacity,
-    lastCursorPos,
-    lastMouseDownPos,
-    state.brushSize,
-    renderers,
-  ]);
-
-  useLayoutEffect(() => {
-    log.trace('Rendering layers');
-    renderers.renderLayers(stage, state.layers, state.globalMaskLayerOpacity, tool, onLayerPosChanged);
-  }, [
-    stage,
-    state.layers,
-    state.globalMaskLayerOpacity,
-    tool,
-    onLayerPosChanged,
-    renderers,
-    state.size.width,
-    state.size.height,
-  ]);
-
-  useLayoutEffect(() => {
-    log.trace('Rendering bbox');
-    if (asPreview) {
-      // Preview should not display bboxes
-      return;
-    }
-    renderers.renderBboxes(stage, state.layers, tool);
-  }, [stage, asPreview, state.layers, tool, onBboxChanged, renderers]);
-
-  useLayoutEffect(() => {
-    if (asPreview) {
-      // Preview should not check for transparency
-      return;
-    }
-    log.trace('Updating bboxes');
-    debouncedRenderers.updateBboxes(stage, state.layers, onBboxChanged);
-  }, [stage, asPreview, state.layers, onBboxChanged]);
-
-  useLayoutEffect(() => {
-    if (asPreview) {
-      // The preview should not have a background
-      return;
-    }
-    log.trace('Rendering background');
-    renderers.renderBackground(stage, state.size.width, state.size.height);
-  }, [stage, asPreview, state.size.width, state.size.height, renderers]);
-
-  useLayoutEffect(() => {
-    log.trace('Arranging layers');
-    renderers.arrangeLayers(stage, layerIds);
-  }, [stage, layerIds, renderers]);
-
-  useLayoutEffect(() => {
-    if (asPreview) {
-      // The preview should not display the no layers message
-      return;
-    }
-    log.trace('Rendering no layers message');
-    renderers.renderNoLayersMessage(stage, layerCount, state.size.width, state.size.height);
-  }, [stage, layerCount, renderers, asPreview, state.size.width, state.size.height]);
-
-  useLayoutEffect(() => {
-    Konva.pixelRatio = dpr;
-  }, [dpr]);
-};
-
-type Props = {
-  asPreview?: boolean;
-};
-
-export const StageComponent = memo(({ asPreview = false }: Props) => {
-  const [stage] = useState(
-    () => new Konva.Stage({ id: uuidv4(), container: document.createElement('div'), listening: !asPreview })
-  );
-  const [container, setContainer] = useState<HTMLDivElement | null>(null);
-  const [wrapper, setWrapper] = useState<HTMLDivElement | null>(null);
-
-  const containerRef = useCallback((el: HTMLDivElement | null) => {
-    setContainer(el);
-  }, []);
-
-  const wrapperRef = useCallback((el: HTMLDivElement | null) => {
-    setWrapper(el);
-  }, []);
-
-  useStageRenderer(stage, container, wrapper, asPreview);
-
-  return (
-    <Flex overflow="hidden" w="full" h="full">
-      <Flex ref={wrapperRef} w="full" h="full" alignItems="center" justifyContent="center">
-        <Flex
-          ref={containerRef}
-          tabIndex={-1}
-          bg="base.850"
-          borderRadius="base"
-          overflow="hidden"
-          data-testid="control-layers-canvas"
-        />
-      </Flex>
-    </Flex>
-  );
-});
-
-StageComponent.displayName = 'StageComponent';

invokeai/frontend/web/src/features/controlLayers/hooks/addLayerHooks.ts

@@ -1,111 +0,0 @@
-import { useAppDispatch, useAppSelector } from 'app/store/storeHooks';
-import {
-  caLayerAdded,
-  iiLayerAdded,
-  ipaLayerAdded,
-  isInitialImageLayer,
-  rgLayerIPAdapterAdded,
-} from 'features/controlLayers/store/controlLayersSlice';
-import {
-  buildControlNet,
-  buildIPAdapter,
-  buildT2IAdapter,
-  CA_PROCESSOR_DATA,
-  isProcessorTypeV2,
-} from 'features/controlLayers/util/controlAdapters';
-import { zModelIdentifierField } from 'features/nodes/types/common';
-import { useCallback, useMemo } from 'react';
-import { useControlNetAndT2IAdapterModels, useIPAdapterModels } from 'services/api/hooks/modelsByType';
-import type { ControlNetModelConfig, IPAdapterModelConfig, T2IAdapterModelConfig } from 'services/api/types';
-import { v4 as uuidv4 } from 'uuid';
-
-export const useAddCALayer = () => {
-  const dispatch = useAppDispatch();
-  const baseModel = useAppSelector((s) => s.generation.model?.base);
-  const [modelConfigs] = useControlNetAndT2IAdapterModels();
-  const model: ControlNetModelConfig | T2IAdapterModelConfig | null = useMemo(() => {
-    // prefer to use a model that matches the base model
-    const compatibleModels = modelConfigs.filter((m) => (baseModel ? m.base === baseModel : true));
-    return compatibleModels[0] ?? modelConfigs[0] ?? null;
-  }, [baseModel, modelConfigs]);
-  const isDisabled = useMemo(() => !model, [model]);
-  const addCALayer = useCallback(() => {
-    if (!model) {
-      return;
-    }
-
-    const id = uuidv4();
-    const defaultPreprocessor = model.default_settings?.preprocessor;
-    const processorConfig = isProcessorTypeV2(defaultPreprocessor)
-      ? CA_PROCESSOR_DATA[defaultPreprocessor].buildDefaults(baseModel)
-      : null;
-
-    const builder = model.type === 'controlnet' ? buildControlNet : buildT2IAdapter;
-    const controlAdapter = builder(id, {
-      model: zModelIdentifierField.parse(model),
-      processorConfig,
-    });
-
-    dispatch(caLayerAdded(controlAdapter));
-  }, [dispatch, model, baseModel]);
-
-  return [addCALayer, isDisabled] as const;
-};
-
-export const useAddIPALayer = () => {
-  const dispatch = useAppDispatch();
-  const baseModel = useAppSelector((s) => s.generation.model?.base);
-  const [modelConfigs] = useIPAdapterModels();
-  const model: IPAdapterModelConfig | null = useMemo(() => {
-    // prefer to use a model that matches the base model
-    const compatibleModels = modelConfigs.filter((m) => (baseModel ? m.base === baseModel : true));
-    return compatibleModels[0] ?? modelConfigs[0] ?? null;
-  }, [baseModel, modelConfigs]);
-  const isDisabled = useMemo(() => !model, [model]);
-  const addIPALayer = useCallback(() => {
-    if (!model) {
-      return;
-    }
-    const id = uuidv4();
-    const ipAdapter = buildIPAdapter(id, {
-      model: zModelIdentifierField.parse(model),
-    });
-    dispatch(ipaLayerAdded(ipAdapter));
-  }, [dispatch, model]);
-
-  return [addIPALayer, isDisabled] as const;
-};
-
-export const useAddIPAdapterToIPALayer = (layerId: string) => {
-  const dispatch = useAppDispatch();
-  const baseModel = useAppSelector((s) => s.generation.model?.base);
-  const [modelConfigs] = useIPAdapterModels();
-  const model: IPAdapterModelConfig | null = useMemo(() => {
-    // prefer to use a model that matches the base model
-    const compatibleModels = modelConfigs.filter((m) => (baseModel ? m.base === baseModel : true));
-    return compatibleModels[0] ?? modelConfigs[0] ?? null;
-  }, [baseModel, modelConfigs]);
-  const isDisabled = useMemo(() => !model, [model]);
-  const addIPAdapter = useCallback(() => {
-    if (!model) {
-      return;
-    }
-    const id = uuidv4();
-    const ipAdapter = buildIPAdapter(id, {
-      model: zModelIdentifierField.parse(model),
-    });
-    dispatch(rgLayerIPAdapterAdded({ layerId, ipAdapter }));
-  }, [dispatch, model, layerId]);
-
-  return [addIPAdapter, isDisabled] as const;
-};
-
-export const useAddIILayer = () => {
-  const dispatch = useAppDispatch();
-  const isDisabled = useAppSelector((s) => Boolean(s.controlLayers.present.layers.find(isInitialImageLayer)));
-  const addIILayer = useCallback(() => {
-    dispatch(iiLayerAdded(null));
-  }, [dispatch]);
-
-  return [addIILayer, isDisabled] as const;
-};

invokeai/frontend/web/src/features/controlLayers/hooks/layerStateHooks.ts

@@ -1,82 +0,0 @@
-import { createSelector } from '@reduxjs/toolkit';
-import { createMemoizedSelector } from 'app/store/createMemoizedSelector';
-import { useAppSelector } from 'app/store/storeHooks';
-import {
-  isControlAdapterLayer,
-  isRegionalGuidanceLayer,
-  selectControlLayersSlice,
-} from 'features/controlLayers/store/controlLayersSlice';
-import { useMemo } from 'react';
-import { assert } from 'tsafe';
-
-export const useLayerPositivePrompt = (layerId: string) => {
-  const selectLayer = useMemo(
-    () =>
-      createSelector(selectControlLayersSlice, (controlLayers) => {
-        const layer = controlLayers.present.layers.find((l) => l.id === layerId);
-        assert(isRegionalGuidanceLayer(layer), `Layer ${layerId} not found or not an RP layer`);
-        assert(layer.positivePrompt !== null, `Layer ${layerId} does not have a positive prompt`);
-        return layer.positivePrompt;
-      }),
-    [layerId]
-  );
-  const prompt = useAppSelector(selectLayer);
-  return prompt;
-};
-
-export const useLayerNegativePrompt = (layerId: string) => {
-  const selectLayer = useMemo(
-    () =>
-      createSelector(selectControlLayersSlice, (controlLayers) => {
-        const layer = controlLayers.present.layers.find((l) => l.id === layerId);
-        assert(isRegionalGuidanceLayer(layer), `Layer ${layerId} not found or not an RP layer`);
-        assert(layer.negativePrompt !== null, `Layer ${layerId} does not have a negative prompt`);
-        return layer.negativePrompt;
-      }),
-    [layerId]
-  );
-  const prompt = useAppSelector(selectLayer);
-  return prompt;
-};
-
-export const useLayerIsVisible = (layerId: string) => {
-  const selectLayer = useMemo(
-    () =>
-      createSelector(selectControlLayersSlice, (controlLayers) => {
-        const layer = controlLayers.present.layers.find((l) => l.id === layerId);
-        assert(layer, `Layer ${layerId} not found`);
-        return layer.isEnabled;
-      }),
-    [layerId]
-  );
-  const isVisible = useAppSelector(selectLayer);
-  return isVisible;
-};
-
-export const useLayerType = (layerId: string) => {
-  const selectLayer = useMemo(
-    () =>
-      createSelector(selectControlLayersSlice, (controlLayers) => {
-        const layer = controlLayers.present.layers.find((l) => l.id === layerId);
-        assert(layer, `Layer ${layerId} not found`);
-        return layer.type;
-      }),
-    [layerId]
-  );
-  const type = useAppSelector(selectLayer);
-  return type;
-};
-
-export const useLayerOpacity = (layerId: string) => {
-  const selectLayer = useMemo(
-    () =>
-      createMemoizedSelector(selectControlLayersSlice, (controlLayers) => {
-        const layer = controlLayers.present.layers.filter(isControlAdapterLayer).find((l) => l.id === layerId);
-        assert(layer, `Layer ${layerId} not found`);
-        return { opacity: Math.round(layer.opacity * 100), isFilterEnabled: layer.isFilterEnabled };
-      }),
-    [layerId]
-  );
-  const opacity = useAppSelector(selectLayer);
-  return opacity;
-};

invokeai/frontend/web/src/features/controlLayers/hooks/mouseEventHooks.ts

@@ -1,233 +0,0 @@
-import { $ctrl, $meta } from '@invoke-ai/ui-library';
-import { useStore } from '@nanostores/react';
-import { useAppDispatch, useAppSelector } from 'app/store/storeHooks';
-import { calculateNewBrushSize } from 'features/canvas/hooks/useCanvasZoom';
-import {
-  $isDrawing,
-  $lastCursorPos,
-  $lastMouseDownPos,
-  $tool,
-  brushSizeChanged,
-  rgLayerLineAdded,
-  rgLayerPointsAdded,
-  rgLayerRectAdded,
-} from 'features/controlLayers/store/controlLayersSlice';
-import type Konva from 'konva';
-import type { KonvaEventObject } from 'konva/lib/Node';
-import type { Vector2d } from 'konva/lib/types';
-import { clamp } from 'lodash-es';
-import { useCallback, useMemo, useRef } from 'react';
-
-const getIsFocused = (stage: Konva.Stage) => {
-  return stage.container().contains(document.activeElement);
-};
-const getIsMouseDown = (e: KonvaEventObject<MouseEvent>) => e.evt.buttons === 1;
-
-const SNAP_PX = 10;
-
-export const snapPosToStage = (pos: Vector2d, stage: Konva.Stage) => {
-  const snappedPos = { ...pos };
-  // Get the normalized threshold for snapping to the edge of the stage
-  const thresholdX = SNAP_PX / stage.scaleX();
-  const thresholdY = SNAP_PX / stage.scaleY();
-  const stageWidth = stage.width() / stage.scaleX();
-  const stageHeight = stage.height() / stage.scaleY();
-  // Snap to the edge of the stage if within threshold
-  if (pos.x - thresholdX < 0) {
-    snappedPos.x = 0;
-  } else if (pos.x + thresholdX > stageWidth) {
-    snappedPos.x = Math.floor(stageWidth);
-  }
-  if (pos.y - thresholdY < 0) {
-    snappedPos.y = 0;
-  } else if (pos.y + thresholdY > stageHeight) {
-    snappedPos.y = Math.floor(stageHeight);
-  }
-  return snappedPos;
-};
-
-export const getScaledFlooredCursorPosition = (stage: Konva.Stage) => {
-  const pointerPosition = stage.getPointerPosition();
-  const stageTransform = stage.getAbsoluteTransform().copy();
-  if (!pointerPosition) {
-    return;
-  }
-  const scaledCursorPosition = stageTransform.invert().point(pointerPosition);
-  return {
-    x: Math.floor(scaledCursorPosition.x),
-    y: Math.floor(scaledCursorPosition.y),
-  };
-};
-
-const syncCursorPos = (stage: Konva.Stage): Vector2d | null => {
-  const pos = getScaledFlooredCursorPosition(stage);
-  if (!pos) {
-    return null;
-  }
-  $lastCursorPos.set(pos);
-  return pos;
-};
-
-const BRUSH_SPACING_PCT = 10;
-const MIN_BRUSH_SPACING_PX = 5;
-const MAX_BRUSH_SPACING_PX = 15;
-
-export const useMouseEvents = () => {
-  const dispatch = useAppDispatch();
-  const selectedLayerId = useAppSelector((s) => s.controlLayers.present.selectedLayerId);
-  const selectedLayerType = useAppSelector((s) => {
-    const selectedLayer = s.controlLayers.present.layers.find((l) => l.id === s.controlLayers.present.selectedLayerId);
-    if (!selectedLayer) {
-      return null;
-    }
-    return selectedLayer.type;
-  });
-  const tool = useStore($tool);
-  const lastCursorPosRef = useRef<[number, number] | null>(null);
-  const shouldInvertBrushSizeScrollDirection = useAppSelector((s) => s.canvas.shouldInvertBrushSizeScrollDirection);
-  const brushSize = useAppSelector((s) => s.controlLayers.present.brushSize);
-  const brushSpacingPx = useMemo(
-    () => clamp(brushSize / BRUSH_SPACING_PCT, MIN_BRUSH_SPACING_PX, MAX_BRUSH_SPACING_PX),
-    [brushSize]
-  );
-
-  const onMouseDown = useCallback(
-    (e: KonvaEventObject<MouseEvent>) => {
-      const stage = e.target.getStage();
-      if (!stage) {
-        return;
-      }
-      const pos = syncCursorPos(stage);
-      if (!pos || !selectedLayerId || selectedLayerType !== 'regional_guidance_layer') {
-        return;
-      }
-      if (tool === 'brush' || tool === 'eraser') {
-        dispatch(
-          rgLayerLineAdded({
-            layerId: selectedLayerId,
-            points: [pos.x, pos.y, pos.x, pos.y],
-            tool,
-          })
-        );
-        $isDrawing.set(true);
-        $lastMouseDownPos.set(pos);
-      } else if (tool === 'rect') {
-        $lastMouseDownPos.set(snapPosToStage(pos, stage));
-      }
-    },
-    [dispatch, selectedLayerId, selectedLayerType, tool]
-  );
-
-  const onMouseUp = useCallback(
-    (e: KonvaEventObject<MouseEvent>) => {
-      const stage = e.target.getStage();
-      if (!stage) {
-        return;
-      }
-      const pos = $lastCursorPos.get();
-      if (!pos || !selectedLayerId || selectedLayerType !== 'regional_guidance_layer') {
-        return;
-      }
-      const lastPos = $lastMouseDownPos.get();
-      const tool = $tool.get();
-      if (lastPos && selectedLayerId && tool === 'rect') {
-        const snappedPos = snapPosToStage(pos, stage);
-        dispatch(
-          rgLayerRectAdded({
-            layerId: selectedLayerId,
-            rect: {
-              x: Math.min(snappedPos.x, lastPos.x),
-              y: Math.min(snappedPos.y, lastPos.y),
-              width: Math.abs(snappedPos.x - lastPos.x),
-              height: Math.abs(snappedPos.y - lastPos.y),
-            },
-          })
-        );
-      }
-      $isDrawing.set(false);
-      $lastMouseDownPos.set(null);
-    },
-    [dispatch, selectedLayerId, selectedLayerType]
-  );
-
-  const onMouseMove = useCallback(
-    (e: KonvaEventObject<MouseEvent>) => {
-      const stage = e.target.getStage();
-      if (!stage) {
-        return;
-      }
-      const pos = syncCursorPos(stage);
-      if (!pos || !selectedLayerId || selectedLayerType !== 'regional_guidance_layer') {
-        return;
-      }
-      if (getIsFocused(stage) && getIsMouseDown(e) && (tool === 'brush' || tool === 'eraser')) {
-        if ($isDrawing.get()) {
-          // Continue the last line
-          if (lastCursorPosRef.current) {
-            // Dispatching redux events impacts perf substantially - using brush spacing keeps dispatches to a reasonable number
-            if (Math.hypot(lastCursorPosRef.current[0] - pos.x, lastCursorPosRef.current[1] - pos.y) < brushSpacingPx) {
-              return;
-            }
-          }
-          lastCursorPosRef.current = [pos.x, pos.y];
-          dispatch(rgLayerPointsAdded({ layerId: selectedLayerId, point: lastCursorPosRef.current }));
-        } else {
-          // Start a new line
-          dispatch(rgLayerLineAdded({ layerId: selectedLayerId, points: [pos.x, pos.y, pos.x, pos.y], tool }));
-        }
-        $isDrawing.set(true);
-      }
-    },
-    [brushSpacingPx, dispatch, selectedLayerId, selectedLayerType, tool]
-  );
-
-  const onMouseLeave = useCallback(
-    (e: KonvaEventObject<MouseEvent>) => {
-      const stage = e.target.getStage();
-      if (!stage) {
-        return;
-      }
-      const pos = syncCursorPos(stage);
-      $isDrawing.set(false);
-      $lastCursorPos.set(null);
-      $lastMouseDownPos.set(null);
-      if (!pos || !selectedLayerId || selectedLayerType !== 'regional_guidance_layer') {
-        return;
-      }
-      if (getIsFocused(stage) && getIsMouseDown(e) && (tool === 'brush' || tool === 'eraser')) {
-        dispatch(rgLayerPointsAdded({ layerId: selectedLayerId, point: [pos.x, pos.y] }));
-      }
-    },
-    [selectedLayerId, selectedLayerType, tool, dispatch]
-  );
-
-  const onMouseWheel = useCallback(
-    (e: KonvaEventObject<WheelEvent>) => {
-      e.evt.preventDefault();
-
-      if (selectedLayerType !== 'regional_guidance_layer' || (tool !== 'brush' && tool !== 'eraser')) {
-        return;
-      }
-      // checking for ctrl key is pressed or not,
-      // so that brush size can be controlled using ctrl + scroll up/down
-
-      // Invert the delta if the property is set to true
-      let delta = e.evt.deltaY;
-      if (shouldInvertBrushSizeScrollDirection) {
-        delta = -delta;
-      }
-
-      if ($ctrl.get() || $meta.get()) {
-        dispatch(brushSizeChanged(calculateNewBrushSize(brushSize, delta)));
-      }
-    },
-    [selectedLayerType, tool, shouldInvertBrushSizeScrollDirection, dispatch, brushSize]
-  );
-
-  const handlers = useMemo(
-    () => ({ onMouseDown, onMouseUp, onMouseMove, onMouseLeave, onMouseWheel }),
-    [onMouseDown, onMouseUp, onMouseMove, onMouseLeave, onMouseWheel]
-  );
-
-  return handlers;
-};

invokeai/frontend/web/src/features/controlLayers/store/controlLayersSlice.ts

@@ -1,963 +0,0 @@
-import type { PayloadAction, UnknownAction } from '@reduxjs/toolkit';
-import { createSlice, isAnyOf } from '@reduxjs/toolkit';
-import type { PersistConfig, RootState } from 'app/store/store';
-import { moveBackward, moveForward, moveToBack, moveToFront } from 'common/util/arrayUtils';
-import { deepClone } from 'common/util/deepClone';
-import { roundDownToMultiple } from 'common/util/roundDownToMultiple';
-import type {
-  CLIPVisionModelV2,
-  ControlModeV2,
-  ControlNetConfigV2,
-  IPAdapterConfigV2,
-  IPMethodV2,
-  ProcessorConfig,
-  T2IAdapterConfigV2,
-} from 'features/controlLayers/util/controlAdapters';
-import {
-  buildControlAdapterProcessorV2,
-  controlNetToT2IAdapter,
-  imageDTOToImageWithDims,
-  t2iAdapterToControlNet,
-} from 'features/controlLayers/util/controlAdapters';
-import { zModelIdentifierField } from 'features/nodes/types/common';
-import { calculateNewSize } from 'features/parameters/components/ImageSize/calculateNewSize';
-import { initialAspectRatioState } from 'features/parameters/components/ImageSize/constants';
-import type { AspectRatioState } from 'features/parameters/components/ImageSize/types';
-import { modelChanged } from 'features/parameters/store/generationSlice';
-import type { ParameterAutoNegative } from 'features/parameters/types/parameterSchemas';
-import { getIsSizeOptimal, getOptimalDimension } from 'features/parameters/util/optimalDimension';
-import type { IRect, Vector2d } from 'konva/lib/types';
-import { isEqual, partition } from 'lodash-es';
-import { atom } from 'nanostores';
-import type { RgbColor } from 'react-colorful';
-import type { UndoableOptions } from 'redux-undo';
-import type { ControlNetModelConfig, ImageDTO, IPAdapterModelConfig, T2IAdapterModelConfig } from 'services/api/types';
-import { assert } from 'tsafe';
-import { v4 as uuidv4 } from 'uuid';
-
-import type {
-  ControlAdapterLayer,
-  ControlLayersState,
-  DrawingTool,
-  InitialImageLayer,
-  IPAdapterLayer,
-  Layer,
-  RegionalGuidanceLayer,
-  Tool,
-  VectorMaskLine,
-  VectorMaskRect,
-} from './types';
-
-export const initialControlLayersState: ControlLayersState = {
-  _version: 2,
-  selectedLayerId: null,
-  brushSize: 100,
-  layers: [],
-  globalMaskLayerOpacity: 0.3, // this globally changes all mask layers' opacity
-  positivePrompt: '',
-  negativePrompt: '',
-  positivePrompt2: '',
-  negativePrompt2: '',
-  shouldConcatPrompts: true,
-  size: {
-    width: 512,
-    height: 512,
-    aspectRatio: deepClone(initialAspectRatioState),
-  },
-};
-
-const isLine = (obj: VectorMaskLine | VectorMaskRect): obj is VectorMaskLine => obj.type === 'vector_mask_line';
-export const isRegionalGuidanceLayer = (layer?: Layer): layer is RegionalGuidanceLayer =>
-  layer?.type === 'regional_guidance_layer';
-export const isControlAdapterLayer = (layer?: Layer): layer is ControlAdapterLayer =>
-  layer?.type === 'control_adapter_layer';
-export const isIPAdapterLayer = (layer?: Layer): layer is IPAdapterLayer => layer?.type === 'ip_adapter_layer';
-export const isInitialImageLayer = (layer?: Layer): layer is InitialImageLayer => layer?.type === 'initial_image_layer';
-export const isRenderableLayer = (
-  layer?: Layer
-): layer is RegionalGuidanceLayer | ControlAdapterLayer | InitialImageLayer =>
-  layer?.type === 'regional_guidance_layer' ||
-  layer?.type === 'control_adapter_layer' ||
-  layer?.type === 'initial_image_layer';
-
-export const selectCALayerOrThrow = (state: ControlLayersState, layerId: string): ControlAdapterLayer => {
-  const layer = state.layers.find((l) => l.id === layerId);
-  assert(isControlAdapterLayer(layer));
-  return layer;
-};
-export const selectIPALayerOrThrow = (state: ControlLayersState, layerId: string): IPAdapterLayer => {
-  const layer = state.layers.find((l) => l.id === layerId);
-  assert(isIPAdapterLayer(layer));
-  return layer;
-};
-export const selectIILayerOrThrow = (state: ControlLayersState, layerId: string): InitialImageLayer => {
-  const layer = state.layers.find((l) => l.id === layerId);
-  assert(isInitialImageLayer(layer));
-  return layer;
-};
-const selectCAOrIPALayerOrThrow = (
-  state: ControlLayersState,
-  layerId: string
-): ControlAdapterLayer | IPAdapterLayer => {
-  const layer = state.layers.find((l) => l.id === layerId);
-  assert(isControlAdapterLayer(layer) || isIPAdapterLayer(layer));
-  return layer;
-};
-const selectRGLayerOrThrow = (state: ControlLayersState, layerId: string): RegionalGuidanceLayer => {
-  const layer = state.layers.find((l) => l.id === layerId);
-  assert(isRegionalGuidanceLayer(layer));
-  return layer;
-};
-export const selectRGLayerIPAdapterOrThrow = (
-  state: ControlLayersState,
-  layerId: string,
-  ipAdapterId: string
-): IPAdapterConfigV2 => {
-  const layer = state.layers.find((l) => l.id === layerId);
-  assert(isRegionalGuidanceLayer(layer));
-  const ipAdapter = layer.ipAdapters.find((ipAdapter) => ipAdapter.id === ipAdapterId);
-  assert(ipAdapter);
-  return ipAdapter;
-};
-const getVectorMaskPreviewColor = (state: ControlLayersState): RgbColor => {
-  const rgLayers = state.layers.filter(isRegionalGuidanceLayer);
-  const lastColor = rgLayers[rgLayers.length - 1]?.previewColor;
-  return LayerColors.next(lastColor);
-};
-const exclusivelySelectLayer = (state: ControlLayersState, layerId: string) => {
-  for (const layer of state.layers) {
-    layer.isSelected = layer.id === layerId;
-  }
-  state.selectedLayerId = layerId;
-};
-
-export const controlLayersSlice = createSlice({
-  name: 'controlLayers',
-  initialState: initialControlLayersState,
-  reducers: {
-    //#region Any Layer Type
-    layerSelected: (state, action: PayloadAction<string>) => {
-      exclusivelySelectLayer(state, action.payload);
-    },
-    layerVisibilityToggled: (state, action: PayloadAction<string>) => {
-      const layer = state.layers.find((l) => l.id === action.payload);
-      if (layer) {
-        layer.isEnabled = !layer.isEnabled;
-      }
-    },
-    layerTranslated: (state, action: PayloadAction<{ layerId: string; x: number; y: number }>) => {
-      const { layerId, x, y } = action.payload;
-      const layer = state.layers.find((l) => l.id === layerId);
-      if (isRenderableLayer(layer)) {
-        layer.x = x;
-        layer.y = y;
-      }
-      if (isRegionalGuidanceLayer(layer)) {
-        layer.uploadedMaskImage = null;
-      }
-    },
-    layerBboxChanged: (state, action: PayloadAction<{ layerId: string; bbox: IRect | null }>) => {
-      const { layerId, bbox } = action.payload;
-      const layer = state.layers.find((l) => l.id === layerId);
-      if (isRenderableLayer(layer)) {
-        layer.bbox = bbox;
-        layer.bboxNeedsUpdate = false;
-        if (bbox === null && layer.type === 'regional_guidance_layer') {
-          // The layer was fully erased, empty its objects to prevent accumulation of invisible objects
-          layer.maskObjects = [];
-          layer.uploadedMaskImage = null;
-        }
-      }
-    },
-    layerReset: (state, action: PayloadAction<string>) => {
-      const layer = state.layers.find((l) => l.id === action.payload);
-      // TODO(psyche): Should other layer types also have reset functionality?
-      if (isRegionalGuidanceLayer(layer)) {
-        layer.maskObjects = [];
-        layer.bbox = null;
-        layer.isEnabled = true;
-        layer.bboxNeedsUpdate = false;
-        layer.uploadedMaskImage = null;
-      }
-    },
-    layerDeleted: (state, action: PayloadAction<string>) => {
-      state.layers = state.layers.filter((l) => l.id !== action.payload);
-      state.selectedLayerId = state.layers[0]?.id ?? null;
-    },
-    layerMovedForward: (state, action: PayloadAction<string>) => {
-      const cb = (l: Layer) => l.id === action.payload;
-      const [renderableLayers, ipAdapterLayers] = partition(state.layers, isRenderableLayer);
-      moveForward(renderableLayers, cb);
-      state.layers = [...ipAdapterLayers, ...renderableLayers];
-    },
-    layerMovedToFront: (state, action: PayloadAction<string>) => {
-      const cb = (l: Layer) => l.id === action.payload;
-      const [renderableLayers, ipAdapterLayers] = partition(state.layers, isRenderableLayer);
-      // Because the layers are in reverse order, moving to the front is equivalent to moving to the back
-      moveToBack(renderableLayers, cb);
-      state.layers = [...ipAdapterLayers, ...renderableLayers];
-    },
-    layerMovedBackward: (state, action: PayloadAction<string>) => {
-      const cb = (l: Layer) => l.id === action.payload;
-      const [renderableLayers, ipAdapterLayers] = partition(state.layers, isRenderableLayer);
-      moveBackward(renderableLayers, cb);
-      state.layers = [...ipAdapterLayers, ...renderableLayers];
-    },
-    layerMovedToBack: (state, action: PayloadAction<string>) => {
-      const cb = (l: Layer) => l.id === action.payload;
-      const [renderableLayers, ipAdapterLayers] = partition(state.layers, isRenderableLayer);
-      // Because the layers are in reverse order, moving to the back is equivalent to moving to the front
-      moveToFront(renderableLayers, cb);
-      state.layers = [...ipAdapterLayers, ...renderableLayers];
-    },
-    selectedLayerDeleted: (state) => {
-      state.layers = state.layers.filter((l) => l.id !== state.selectedLayerId);
-      state.selectedLayerId = state.layers[0]?.id ?? null;
-    },
-    allLayersDeleted: (state) => {
-      state.layers = [];
-      state.selectedLayerId = null;
-    },
-    //#endregion
-
-    //#region CA Layers
-    caLayerAdded: {
-      reducer: (
-        state,
-        action: PayloadAction<{ layerId: string; controlAdapter: ControlNetConfigV2 | T2IAdapterConfigV2 }>
-      ) => {
-        const { layerId, controlAdapter } = action.payload;
-        const layer: ControlAdapterLayer = {
-          id: getCALayerId(layerId),
-          type: 'control_adapter_layer',
-          x: 0,
-          y: 0,
-          bbox: null,
-          bboxNeedsUpdate: false,
-          isEnabled: true,
-          opacity: 1,
-          isSelected: true,
-          isFilterEnabled: true,
-          controlAdapter,
-        };
-        state.layers.push(layer);
-        exclusivelySelectLayer(state, layer.id);
-      },
-      prepare: (controlAdapter: ControlNetConfigV2 | T2IAdapterConfigV2) => ({
-        payload: { layerId: uuidv4(), controlAdapter },
-      }),
-    },
-    caLayerRecalled: (state, action: PayloadAction<ControlAdapterLayer>) => {
-      state.layers.push({ ...action.payload, isSelected: true });
-      exclusivelySelectLayer(state, action.payload.id);
-    },
-    caLayerImageChanged: (state, action: PayloadAction<{ layerId: string; imageDTO: ImageDTO | null }>) => {
-      const { layerId, imageDTO } = action.payload;
-      const layer = selectCALayerOrThrow(state, layerId);
-      layer.bbox = null;
-      layer.bboxNeedsUpdate = true;
-      layer.isEnabled = true;
-      if (imageDTO) {
-        const newImage = imageDTOToImageWithDims(imageDTO);
-        if (isEqual(newImage, layer.controlAdapter.image)) {
-          return;
-        }
-        layer.controlAdapter.image = newImage;
-        layer.controlAdapter.processedImage = null;
-      } else {
-        layer.controlAdapter.image = null;
-        layer.controlAdapter.processedImage = null;
-      }
-    },
-    caLayerProcessedImageChanged: (state, action: PayloadAction<{ layerId: string; imageDTO: ImageDTO | null }>) => {
-      const { layerId, imageDTO } = action.payload;
-      const layer = selectCALayerOrThrow(state, layerId);
-      layer.bbox = null;
-      layer.bboxNeedsUpdate = true;
-      layer.isEnabled = true;
-      layer.controlAdapter.processedImage = imageDTO ? imageDTOToImageWithDims(imageDTO) : null;
-    },
-    caLayerModelChanged: (
-      state,
-      action: PayloadAction<{
-        layerId: string;
-        modelConfig: ControlNetModelConfig | T2IAdapterModelConfig | null;
-      }>
-    ) => {
-      const { layerId, modelConfig } = action.payload;
-      const layer = selectCALayerOrThrow(state, layerId);
-      if (!modelConfig) {
-        layer.controlAdapter.model = null;
-        return;
-      }
-      layer.controlAdapter.model = zModelIdentifierField.parse(modelConfig);
-
-      // We may need to convert the CA to match the model
-      if (layer.controlAdapter.type === 't2i_adapter' && layer.controlAdapter.model.type === 'controlnet') {
-        layer.controlAdapter = t2iAdapterToControlNet(layer.controlAdapter);
-      } else if (layer.controlAdapter.type === 'controlnet' && layer.controlAdapter.model.type === 't2i_adapter') {
-        layer.controlAdapter = controlNetToT2IAdapter(layer.controlAdapter);
-      }
-
-      const candidateProcessorConfig = buildControlAdapterProcessorV2(modelConfig);
-      if (candidateProcessorConfig?.type !== layer.controlAdapter.processorConfig?.type) {
-        // The processor has changed. For example, the previous model was a Canny model and the new model is a Depth
-        // model. We need to use the new processor.
-        layer.controlAdapter.processedImage = null;
-        layer.controlAdapter.processorConfig = candidateProcessorConfig;
-      }
-    },
-    caLayerControlModeChanged: (state, action: PayloadAction<{ layerId: string; controlMode: ControlModeV2 }>) => {
-      const { layerId, controlMode } = action.payload;
-      const layer = selectCALayerOrThrow(state, layerId);
-      assert(layer.controlAdapter.type === 'controlnet');
-      layer.controlAdapter.controlMode = controlMode;
-    },
-    caLayerProcessorConfigChanged: (
-      state,
-      action: PayloadAction<{ layerId: string; processorConfig: ProcessorConfig | null }>
-    ) => {
-      const { layerId, processorConfig } = action.payload;
-      const layer = selectCALayerOrThrow(state, layerId);
-      layer.controlAdapter.processorConfig = processorConfig;
-      if (!processorConfig) {
-        layer.controlAdapter.processedImage = null;
-      }
-    },
-    caLayerIsFilterEnabledChanged: (state, action: PayloadAction<{ layerId: string; isFilterEnabled: boolean }>) => {
-      const { layerId, isFilterEnabled } = action.payload;
-      const layer = selectCALayerOrThrow(state, layerId);
-      layer.isFilterEnabled = isFilterEnabled;
-    },
-    caLayerOpacityChanged: (state, action: PayloadAction<{ layerId: string; opacity: number }>) => {
-      const { layerId, opacity } = action.payload;
-      const layer = selectCALayerOrThrow(state, layerId);
-      layer.opacity = opacity;
-    },
-    caLayerIsProcessingImageChanged: (
-      state,
-      action: PayloadAction<{ layerId: string; isProcessingImage: boolean }>
-    ) => {
-      const { layerId, isProcessingImage } = action.payload;
-      const layer = selectCALayerOrThrow(state, layerId);
-      layer.controlAdapter.isProcessingImage = isProcessingImage;
-    },
-    //#endregion
-
-    //#region IP Adapter Layers
-    ipaLayerAdded: {
-      reducer: (state, action: PayloadAction<{ layerId: string; ipAdapter: IPAdapterConfigV2 }>) => {
-        const { layerId, ipAdapter } = action.payload;
-        const layer: IPAdapterLayer = {
-          id: getIPALayerId(layerId),
-          type: 'ip_adapter_layer',
-          isEnabled: true,
-          isSelected: true,
-          ipAdapter,
-        };
-        state.layers.push(layer);
-        exclusivelySelectLayer(state, layer.id);
-      },
-      prepare: (ipAdapter: IPAdapterConfigV2) => ({ payload: { layerId: uuidv4(), ipAdapter } }),
-    },
-    ipaLayerRecalled: (state, action: PayloadAction<IPAdapterLayer>) => {
-      state.layers.push(action.payload);
-    },
-    ipaLayerImageChanged: (state, action: PayloadAction<{ layerId: string; imageDTO: ImageDTO | null }>) => {
-      const { layerId, imageDTO } = action.payload;
-      const layer = selectIPALayerOrThrow(state, layerId);
-      layer.ipAdapter.image = imageDTO ? imageDTOToImageWithDims(imageDTO) : null;
-    },
-    ipaLayerMethodChanged: (state, action: PayloadAction<{ layerId: string; method: IPMethodV2 }>) => {
-      const { layerId, method } = action.payload;
-      const layer = selectIPALayerOrThrow(state, layerId);
-      layer.ipAdapter.method = method;
-    },
-    ipaLayerModelChanged: (
-      state,
-      action: PayloadAction<{
-        layerId: string;
-        modelConfig: IPAdapterModelConfig | null;
-      }>
-    ) => {
-      const { layerId, modelConfig } = action.payload;
-      const layer = selectIPALayerOrThrow(state, layerId);
-      if (!modelConfig) {
-        layer.ipAdapter.model = null;
-        return;
-      }
-      layer.ipAdapter.model = zModelIdentifierField.parse(modelConfig);
-    },
-    ipaLayerCLIPVisionModelChanged: (
-      state,
-      action: PayloadAction<{ layerId: string; clipVisionModel: CLIPVisionModelV2 }>
-    ) => {
-      const { layerId, clipVisionModel } = action.payload;
-      const layer = selectIPALayerOrThrow(state, layerId);
-      layer.ipAdapter.clipVisionModel = clipVisionModel;
-    },
-    //#endregion
-
-    //#region CA or IPA Layers
-    caOrIPALayerWeightChanged: (state, action: PayloadAction<{ layerId: string; weight: number }>) => {
-      const { layerId, weight } = action.payload;
-      const layer = selectCAOrIPALayerOrThrow(state, layerId);
-      if (layer.type === 'control_adapter_layer') {
-        layer.controlAdapter.weight = weight;
-      } else {
-        layer.ipAdapter.weight = weight;
-      }
-    },
-    caOrIPALayerBeginEndStepPctChanged: (
-      state,
-      action: PayloadAction<{ layerId: string; beginEndStepPct: [number, number] }>
-    ) => {
-      const { layerId, beginEndStepPct } = action.payload;
-      const layer = selectCAOrIPALayerOrThrow(state, layerId);
-      if (layer.type === 'control_adapter_layer') {
-        layer.controlAdapter.beginEndStepPct = beginEndStepPct;
-      } else {
-        layer.ipAdapter.beginEndStepPct = beginEndStepPct;
-      }
-    },
-    //#endregion
-
-    //#region RG Layers
-    rgLayerAdded: {
-      reducer: (state, action: PayloadAction<{ layerId: string }>) => {
-        const { layerId } = action.payload;
-        const layer: RegionalGuidanceLayer = {
-          id: getRGLayerId(layerId),
-          type: 'regional_guidance_layer',
-          isEnabled: true,
-          bbox: null,
-          bboxNeedsUpdate: false,
-          maskObjects: [],
-          previewColor: getVectorMaskPreviewColor(state),
-          x: 0,
-          y: 0,
-          autoNegative: 'invert',
-          positivePrompt: '',
-          negativePrompt: null,
-          ipAdapters: [],
-          isSelected: true,
-          uploadedMaskImage: null,
-        };
-        state.layers.push(layer);
-        exclusivelySelectLayer(state, layer.id);
-      },
-      prepare: () => ({ payload: { layerId: uuidv4() } }),
-    },
-    rgLayerRecalled: (state, action: PayloadAction<RegionalGuidanceLayer>) => {
-      state.layers.push({ ...action.payload, isSelected: true });
-      exclusivelySelectLayer(state, action.payload.id);
-    },
-    rgLayerPositivePromptChanged: (state, action: PayloadAction<{ layerId: string; prompt: string | null }>) => {
-      const { layerId, prompt } = action.payload;
-      const layer = selectRGLayerOrThrow(state, layerId);
-      layer.positivePrompt = prompt;
-    },
-    rgLayerNegativePromptChanged: (state, action: PayloadAction<{ layerId: string; prompt: string | null }>) => {
-      const { layerId, prompt } = action.payload;
-      const layer = selectRGLayerOrThrow(state, layerId);
-      layer.negativePrompt = prompt;
-    },
-    rgLayerPreviewColorChanged: (state, action: PayloadAction<{ layerId: string; color: RgbColor }>) => {
-      const { layerId, color } = action.payload;
-      const layer = selectRGLayerOrThrow(state, layerId);
-      layer.previewColor = color;
-    },
-    rgLayerLineAdded: {
-      reducer: (
-        state,
-        action: PayloadAction<{
-          layerId: string;
-          points: [number, number, number, number];
-          tool: DrawingTool;
-          lineUuid: string;
-        }>
-      ) => {
-        const { layerId, points, tool, lineUuid } = action.payload;
-        const layer = selectRGLayerOrThrow(state, layerId);
-        const lineId = getRGLayerLineId(layer.id, lineUuid);
-        layer.maskObjects.push({
-          type: 'vector_mask_line',
-          tool: tool,
-          id: lineId,
-          // Points must be offset by the layer's x and y coordinates
-          // TODO: Handle this in the event listener?
-          points: [points[0] - layer.x, points[1] - layer.y, points[2] - layer.x, points[3] - layer.y],
-          strokeWidth: state.brushSize,
-        });
-        layer.bboxNeedsUpdate = true;
-        layer.uploadedMaskImage = null;
-      },
-      prepare: (payload: { layerId: string; points: [number, number, number, number]; tool: DrawingTool }) => ({
-        payload: { ...payload, lineUuid: uuidv4() },
-      }),
-    },
-    rgLayerPointsAdded: (state, action: PayloadAction<{ layerId: string; point: [number, number] }>) => {
-      const { layerId, point } = action.payload;
-      const layer = selectRGLayerOrThrow(state, layerId);
-      const lastLine = layer.maskObjects.findLast(isLine);
-      if (!lastLine) {
-        return;
-      }
-      // Points must be offset by the layer's x and y coordinates
-      // TODO: Handle this in the event listener
-      lastLine.points.push(point[0] - layer.x, point[1] - layer.y);
-      layer.bboxNeedsUpdate = true;
-      layer.uploadedMaskImage = null;
-    },
-    rgLayerRectAdded: {
-      reducer: (state, action: PayloadAction<{ layerId: string; rect: IRect; rectUuid: string }>) => {
-        const { layerId, rect, rectUuid } = action.payload;
-        if (rect.height === 0 || rect.width === 0) {
-          // Ignore zero-area rectangles
-          return;
-        }
-        const layer = selectRGLayerOrThrow(state, layerId);
-        const id = getRGLayerRectId(layer.id, rectUuid);
-        layer.maskObjects.push({
-          type: 'vector_mask_rect',
-          id,
-          x: rect.x - layer.x,
-          y: rect.y - layer.y,
-          width: rect.width,
-          height: rect.height,
-        });
-        layer.bboxNeedsUpdate = true;
-        layer.uploadedMaskImage = null;
-      },
-      prepare: (payload: { layerId: string; rect: IRect }) => ({ payload: { ...payload, rectUuid: uuidv4() } }),
-    },
-    rgLayerMaskImageUploaded: (state, action: PayloadAction<{ layerId: string; imageDTO: ImageDTO }>) => {
-      const { layerId, imageDTO } = action.payload;
-      const layer = selectRGLayerOrThrow(state, layerId);
-      layer.uploadedMaskImage = imageDTOToImageWithDims(imageDTO);
-    },
-    rgLayerAutoNegativeChanged: (
-      state,
-      action: PayloadAction<{ layerId: string; autoNegative: ParameterAutoNegative }>
-    ) => {
-      const { layerId, autoNegative } = action.payload;
-      const layer = selectRGLayerOrThrow(state, layerId);
-      layer.autoNegative = autoNegative;
-    },
-    rgLayerIPAdapterAdded: (state, action: PayloadAction<{ layerId: string; ipAdapter: IPAdapterConfigV2 }>) => {
-      const { layerId, ipAdapter } = action.payload;
-      const layer = selectRGLayerOrThrow(state, layerId);
-      layer.ipAdapters.push(ipAdapter);
-    },
-    rgLayerIPAdapterDeleted: (state, action: PayloadAction<{ layerId: string; ipAdapterId: string }>) => {
-      const { layerId, ipAdapterId } = action.payload;
-      const layer = selectRGLayerOrThrow(state, layerId);
-      layer.ipAdapters = layer.ipAdapters.filter((ipAdapter) => ipAdapter.id !== ipAdapterId);
-    },
-    rgLayerIPAdapterImageChanged: (
-      state,
-      action: PayloadAction<{ layerId: string; ipAdapterId: string; imageDTO: ImageDTO | null }>
-    ) => {
-      const { layerId, ipAdapterId, imageDTO } = action.payload;
-      const ipAdapter = selectRGLayerIPAdapterOrThrow(state, layerId, ipAdapterId);
-      ipAdapter.image = imageDTO ? imageDTOToImageWithDims(imageDTO) : null;
-    },
-    rgLayerIPAdapterWeightChanged: (
-      state,
-      action: PayloadAction<{ layerId: string; ipAdapterId: string; weight: number }>
-    ) => {
-      const { layerId, ipAdapterId, weight } = action.payload;
-      const ipAdapter = selectRGLayerIPAdapterOrThrow(state, layerId, ipAdapterId);
-      ipAdapter.weight = weight;
-    },
-    rgLayerIPAdapterBeginEndStepPctChanged: (
-      state,
-      action: PayloadAction<{ layerId: string; ipAdapterId: string; beginEndStepPct: [number, number] }>
-    ) => {
-      const { layerId, ipAdapterId, beginEndStepPct } = action.payload;
-      const ipAdapter = selectRGLayerIPAdapterOrThrow(state, layerId, ipAdapterId);
-      ipAdapter.beginEndStepPct = beginEndStepPct;
-    },
-    rgLayerIPAdapterMethodChanged: (
-      state,
-      action: PayloadAction<{ layerId: string; ipAdapterId: string; method: IPMethodV2 }>
-    ) => {
-      const { layerId, ipAdapterId, method } = action.payload;
-      const ipAdapter = selectRGLayerIPAdapterOrThrow(state, layerId, ipAdapterId);
-      ipAdapter.method = method;
-    },
-    rgLayerIPAdapterModelChanged: (
-      state,
-      action: PayloadAction<{
-        layerId: string;
-        ipAdapterId: string;
-        modelConfig: IPAdapterModelConfig | null;
-      }>
-    ) => {
-      const { layerId, ipAdapterId, modelConfig } = action.payload;
-      const ipAdapter = selectRGLayerIPAdapterOrThrow(state, layerId, ipAdapterId);
-      if (!modelConfig) {
-        ipAdapter.model = null;
-        return;
-      }
-      ipAdapter.model = zModelIdentifierField.parse(modelConfig);
-    },
-    rgLayerIPAdapterCLIPVisionModelChanged: (
-      state,
-      action: PayloadAction<{ layerId: string; ipAdapterId: string; clipVisionModel: CLIPVisionModelV2 }>
-    ) => {
-      const { layerId, ipAdapterId, clipVisionModel } = action.payload;
-      const ipAdapter = selectRGLayerIPAdapterOrThrow(state, layerId, ipAdapterId);
-      ipAdapter.clipVisionModel = clipVisionModel;
-    },
-    //#endregion
-
-    //#region Initial Image Layer
-    iiLayerAdded: {
-      reducer: (state, action: PayloadAction<{ layerId: string; imageDTO: ImageDTO | null }>) => {
-        const { layerId, imageDTO } = action.payload;
-        // Highlander! There can be only one!
-        state.layers = state.layers.filter((l) => (isInitialImageLayer(l) ? false : true));
-        const layer: InitialImageLayer = {
-          id: layerId,
-          type: 'initial_image_layer',
-          opacity: 1,
-          x: 0,
-          y: 0,
-          bbox: null,
-          bboxNeedsUpdate: false,
-          isEnabled: true,
-          image: imageDTO ? imageDTOToImageWithDims(imageDTO) : null,
-          isSelected: true,
-          denoisingStrength: 0.75,
-        };
-        state.layers.push(layer);
-        exclusivelySelectLayer(state, layer.id);
-      },
-      prepare: (imageDTO: ImageDTO | null) => ({ payload: { layerId: INITIAL_IMAGE_LAYER_ID, imageDTO } }),
-    },
-    iiLayerRecalled: (state, action: PayloadAction<InitialImageLayer>) => {
-      state.layers = state.layers.filter((l) => (isInitialImageLayer(l) ? false : true));
-      state.layers.push({ ...action.payload, isSelected: true });
-      exclusivelySelectLayer(state, action.payload.id);
-    },
-    iiLayerImageChanged: (state, action: PayloadAction<{ layerId: string; imageDTO: ImageDTO | null }>) => {
-      const { layerId, imageDTO } = action.payload;
-      const layer = selectIILayerOrThrow(state, layerId);
-      layer.bbox = null;
-      layer.bboxNeedsUpdate = true;
-      layer.isEnabled = true;
-      layer.image = imageDTO ? imageDTOToImageWithDims(imageDTO) : null;
-    },
-    iiLayerOpacityChanged: (state, action: PayloadAction<{ layerId: string; opacity: number }>) => {
-      const { layerId, opacity } = action.payload;
-      const layer = selectIILayerOrThrow(state, layerId);
-      layer.opacity = opacity;
-    },
-    iiLayerDenoisingStrengthChanged: (state, action: PayloadAction<{ layerId: string; denoisingStrength: number }>) => {
-      const { layerId, denoisingStrength } = action.payload;
-      const layer = selectIILayerOrThrow(state, layerId);
-      layer.denoisingStrength = denoisingStrength;
-    },
-    //#endregion
-
-    //#region Globals
-    positivePromptChanged: (state, action: PayloadAction<string>) => {
-      state.positivePrompt = action.payload;
-    },
-    negativePromptChanged: (state, action: PayloadAction<string>) => {
-      state.negativePrompt = action.payload;
-    },
-    positivePrompt2Changed: (state, action: PayloadAction<string>) => {
-      state.positivePrompt2 = action.payload;
-    },
-    negativePrompt2Changed: (state, action: PayloadAction<string>) => {
-      state.negativePrompt2 = action.payload;
-    },
-    shouldConcatPromptsChanged: (state, action: PayloadAction<boolean>) => {
-      state.shouldConcatPrompts = action.payload;
-    },
-    widthChanged: (state, action: PayloadAction<{ width: number; updateAspectRatio?: boolean; clamp?: boolean }>) => {
-      const { width, updateAspectRatio, clamp } = action.payload;
-      state.size.width = clamp ? Math.max(roundDownToMultiple(width, 8), 64) : width;
-      if (updateAspectRatio) {
-        state.size.aspectRatio.value = state.size.width / state.size.height;
-        state.size.aspectRatio.id = 'Free';
-        state.size.aspectRatio.isLocked = false;
-      }
-    },
-    heightChanged: (state, action: PayloadAction<{ height: number; updateAspectRatio?: boolean; clamp?: boolean }>) => {
-      const { height, updateAspectRatio, clamp } = action.payload;
-      state.size.height = clamp ? Math.max(roundDownToMultiple(height, 8), 64) : height;
-      if (updateAspectRatio) {
-        state.size.aspectRatio.value = state.size.width / state.size.height;
-        state.size.aspectRatio.id = 'Free';
-        state.size.aspectRatio.isLocked = false;
-      }
-    },
-    aspectRatioChanged: (state, action: PayloadAction<AspectRatioState>) => {
-      state.size.aspectRatio = action.payload;
-    },
-    brushSizeChanged: (state, action: PayloadAction<number>) => {
-      state.brushSize = Math.round(action.payload);
-    },
-    globalMaskLayerOpacityChanged: (state, action: PayloadAction<number>) => {
-      state.globalMaskLayerOpacity = action.payload;
-    },
-    undo: (state) => {
-      // Invalidate the bbox for all layers to prevent stale bboxes
-      for (const layer of state.layers.filter(isRenderableLayer)) {
-        layer.bboxNeedsUpdate = true;
-      }
-    },
-    redo: (state) => {
-      // Invalidate the bbox for all layers to prevent stale bboxes
-      for (const layer of state.layers.filter(isRenderableLayer)) {
-        layer.bboxNeedsUpdate = true;
-      }
-    },
-    //#endregion
-  },
-  extraReducers(builder) {
-    builder.addCase(modelChanged, (state, action) => {
-      const newModel = action.payload;
-      if (!newModel || action.meta.previousModel?.base === newModel.base) {
-        // Model was cleared or the base didn't change
-        return;
-      }
-      const optimalDimension = getOptimalDimension(newModel);
-      if (getIsSizeOptimal(state.size.width, state.size.height, optimalDimension)) {
-        return;
-      }
-      const { width, height } = calculateNewSize(state.size.aspectRatio.value, optimalDimension * optimalDimension);
-      state.size.width = width;
-      state.size.height = height;
-    });
-
-    // // TODO: This is a temp fix to reduce issues with T2I adapter having a different downscaling
-    // // factor than the UNet. Hopefully we get an upstream fix in diffusers.
-    // builder.addMatcher(isAnyControlAdapterAdded, (state, action) => {
-    //   if (action.payload.type === 't2i_adapter') {
-    //     state.size.width = roundToMultiple(state.size.width, 64);
-    //     state.size.height = roundToMultiple(state.size.height, 64);
-    //   }
-    // });
-  },
-});
-
-/**
- * This class is used to cycle through a set of colors for the prompt region layers.
- */
-class LayerColors {
-  static COLORS: RgbColor[] = [
-    { r: 121, g: 157, b: 219 }, // rgb(121, 157, 219)
-    { r: 131, g: 214, b: 131 }, // rgb(131, 214, 131)
-    { r: 250, g: 225, b: 80 }, // rgb(250, 225, 80)
-    { r: 220, g: 144, b: 101 }, // rgb(220, 144, 101)
-    { r: 224, g: 117, b: 117 }, // rgb(224, 117, 117)
-    { r: 213, g: 139, b: 202 }, // rgb(213, 139, 202)
-    { r: 161, g: 120, b: 214 }, // rgb(161, 120, 214)
-  ];
-  static i = this.COLORS.length - 1;
-  /**
-   * Get the next color in the sequence. If a known color is provided, the next color will be the one after it.
-   */
-  static next(currentColor?: RgbColor): RgbColor {
-    if (currentColor) {
-      const i = this.COLORS.findIndex((c) => isEqual(c, currentColor));
-      if (i !== -1) {
-        this.i = i;
-      }
-    }
-    this.i = (this.i + 1) % this.COLORS.length;
-    const color = this.COLORS[this.i];
-    assert(color);
-    return color;
-  }
-}
-
-export const {
-  // Any Layer Type
-  layerSelected,
-  layerVisibilityToggled,
-  layerTranslated,
-  layerBboxChanged,
-  layerReset,
-  layerDeleted,
-  layerMovedForward,
-  layerMovedToFront,
-  layerMovedBackward,
-  layerMovedToBack,
-  selectedLayerDeleted,
-  allLayersDeleted,
-  // CA Layers
-  caLayerAdded,
-  caLayerRecalled,
-  caLayerImageChanged,
-  caLayerProcessedImageChanged,
-  caLayerModelChanged,
-  caLayerControlModeChanged,
-  caLayerProcessorConfigChanged,
-  caLayerIsFilterEnabledChanged,
-  caLayerOpacityChanged,
-  caLayerIsProcessingImageChanged,
-  // IPA Layers
-  ipaLayerAdded,
-  ipaLayerRecalled,
-  ipaLayerImageChanged,
-  ipaLayerMethodChanged,
-  ipaLayerModelChanged,
-  ipaLayerCLIPVisionModelChanged,
-  // CA or IPA Layers
-  caOrIPALayerWeightChanged,
-  caOrIPALayerBeginEndStepPctChanged,
-  // RG Layers
-  rgLayerAdded,
-  rgLayerRecalled,
-  rgLayerPositivePromptChanged,
-  rgLayerNegativePromptChanged,
-  rgLayerPreviewColorChanged,
-  rgLayerLineAdded,
-  rgLayerPointsAdded,
-  rgLayerRectAdded,
-  rgLayerMaskImageUploaded,
-  rgLayerAutoNegativeChanged,
-  rgLayerIPAdapterAdded,
-  rgLayerIPAdapterDeleted,
-  rgLayerIPAdapterImageChanged,
-  rgLayerIPAdapterWeightChanged,
-  rgLayerIPAdapterBeginEndStepPctChanged,
-  rgLayerIPAdapterMethodChanged,
-  rgLayerIPAdapterModelChanged,
-  rgLayerIPAdapterCLIPVisionModelChanged,
-  // II Layer
-  iiLayerAdded,
-  iiLayerRecalled,
-  iiLayerImageChanged,
-  iiLayerOpacityChanged,
-  iiLayerDenoisingStrengthChanged,
-  // Globals
-  positivePromptChanged,
-  negativePromptChanged,
-  positivePrompt2Changed,
-  negativePrompt2Changed,
-  shouldConcatPromptsChanged,
-  widthChanged,
-  heightChanged,
-  aspectRatioChanged,
-  brushSizeChanged,
-  globalMaskLayerOpacityChanged,
-  undo,
-  redo,
-} = controlLayersSlice.actions;
-
-export const selectControlLayersSlice = (state: RootState) => state.controlLayers;
-
-/* eslint-disable-next-line @typescript-eslint/no-explicit-any */
-const migrateControlLayersState = (state: any): any => {
-  if (state._version === 1) {
-    // Reset state for users on v1 (e.g. beta users), some changes could cause
-    return deepClone(initialControlLayersState);
-  }
-  return state;
-};
-
-export const $isDrawing = atom(false);
-export const $lastMouseDownPos = atom<Vector2d | null>(null);
-export const $tool = atom<Tool>('brush');
-export const $lastCursorPos = atom<Vector2d | null>(null);
-
-// IDs for singleton Konva layers and objects
-export const TOOL_PREVIEW_LAYER_ID = 'tool_preview_layer';
-export const TOOL_PREVIEW_BRUSH_GROUP_ID = 'tool_preview_layer.brush_group';
-export const TOOL_PREVIEW_BRUSH_FILL_ID = 'tool_preview_layer.brush_fill';
-export const TOOL_PREVIEW_BRUSH_BORDER_INNER_ID = 'tool_preview_layer.brush_border_inner';
-export const TOOL_PREVIEW_BRUSH_BORDER_OUTER_ID = 'tool_preview_layer.brush_border_outer';
-export const TOOL_PREVIEW_RECT_ID = 'tool_preview_layer.rect';
-export const BACKGROUND_LAYER_ID = 'background_layer';
-export const BACKGROUND_RECT_ID = 'background_layer.rect';
-export const NO_LAYERS_MESSAGE_LAYER_ID = 'no_layers_message';
-
-// Names (aka classes) for Konva layers and objects
-export const CA_LAYER_NAME = 'control_adapter_layer';
-export const CA_LAYER_IMAGE_NAME = 'control_adapter_layer.image';
-export const RG_LAYER_NAME = 'regional_guidance_layer';
-export const RG_LAYER_LINE_NAME = 'regional_guidance_layer.line';
-export const RG_LAYER_OBJECT_GROUP_NAME = 'regional_guidance_layer.object_group';
-export const RG_LAYER_RECT_NAME = 'regional_guidance_layer.rect';
-export const INITIAL_IMAGE_LAYER_ID = 'singleton_initial_image_layer';
-export const INITIAL_IMAGE_LAYER_NAME = 'initial_image_layer';
-export const INITIAL_IMAGE_LAYER_IMAGE_NAME = 'initial_image_layer.image';
-export const LAYER_BBOX_NAME = 'layer.bbox';
-export const COMPOSITING_RECT_NAME = 'compositing-rect';
-
-// Getters for non-singleton layer and object IDs
-export const getRGLayerId = (layerId: string) => `${RG_LAYER_NAME}_${layerId}`;
-const getRGLayerLineId = (layerId: string, lineId: string) => `${layerId}.line_${lineId}`;
-const getRGLayerRectId = (layerId: string, lineId: string) => `${layerId}.rect_${lineId}`;
-export const getRGLayerObjectGroupId = (layerId: string, groupId: string) => `${layerId}.objectGroup_${groupId}`;
-export const getLayerBboxId = (layerId: string) => `${layerId}.bbox`;
-export const getCALayerId = (layerId: string) => `control_adapter_layer_${layerId}`;
-export const getCALayerImageId = (layerId: string, imageName: string) => `${layerId}.image_${imageName}`;
-export const getIILayerImageId = (layerId: string, imageName: string) => `${layerId}.image_${imageName}`;
-export const getIPALayerId = (layerId: string) => `ip_adapter_layer_${layerId}`;
-
-export const controlLayersPersistConfig: PersistConfig<ControlLayersState> = {
-  name: controlLayersSlice.name,
-  initialState: initialControlLayersState,
-  migrate: migrateControlLayersState,
-  persistDenylist: [],
-};
-
-// These actions are _individually_ grouped together as single undoable actions
-const undoableGroupByMatcher = isAnyOf(
-  layerTranslated,
-  brushSizeChanged,
-  globalMaskLayerOpacityChanged,
-  positivePromptChanged,
-  negativePromptChanged,
-  positivePrompt2Changed,
-  negativePrompt2Changed,
-  rgLayerPositivePromptChanged,
-  rgLayerNegativePromptChanged,
-  rgLayerPreviewColorChanged
-);
-
-// These are used to group actions into logical lines below (hate typos)
-const LINE_1 = 'LINE_1';
-const LINE_2 = 'LINE_2';
-
-export const controlLayersUndoableConfig: UndoableOptions<ControlLayersState, UnknownAction> = {
-  limit: 64,
-  undoType: controlLayersSlice.actions.undo.type,
-  redoType: controlLayersSlice.actions.redo.type,
-  groupBy: (action, state, history) => {
-    // Lines are started with `rgLayerLineAdded` and may have any number of subsequent `rgLayerPointsAdded` events.
-    // We can use a double-buffer-esque trick to group each "logical" line as a single undoable action, without grouping
-    // separate logical lines as a single undo action.
-    if (rgLayerLineAdded.match(action)) {
-      return history.group === LINE_1 ? LINE_2 : LINE_1;
-    }
-    if (rgLayerPointsAdded.match(action)) {
-      if (history.group === LINE_1 || history.group === LINE_2) {
-        return history.group;
-      }
-    }
-    if (undoableGroupByMatcher(action)) {
-      return action.type;
-    }
-    return null;
-  },
-  filter: (action, _state, _history) => {
-    // Ignore all actions from other slices
-    if (!action.type.startsWith(controlLayersSlice.name)) {
-      return false;
-    }
-    // This action is triggered on state changes, including when we undo. If we do not ignore this action, when we
-    // undo, this action triggers and empties the future states array. Therefore, we must ignore this action.
-    if (layerBboxChanged.match(action)) {
-      return false;
-    }
-    return true;
-  },
-};

invokeai/frontend/web/src/features/controlLayers/store/types.ts

@@ -1,131 +0,0 @@
-import {
-  zControlNetConfigV2,
-  zImageWithDims,
-  zIPAdapterConfigV2,
-  zT2IAdapterConfigV2,
-} from 'features/controlLayers/util/controlAdapters';
-import type { AspectRatioState } from 'features/parameters/components/ImageSize/types';
-import {
-  type ParameterHeight,
-  type ParameterNegativePrompt,
-  type ParameterNegativeStylePromptSDXL,
-  type ParameterPositivePrompt,
-  type ParameterPositiveStylePromptSDXL,
-  type ParameterWidth,
-  zAutoNegative,
-  zParameterNegativePrompt,
-  zParameterPositivePrompt,
-  zParameterStrength,
-} from 'features/parameters/types/parameterSchemas';
-import { z } from 'zod';
-
-const zTool = z.enum(['brush', 'eraser', 'move', 'rect']);
-export type Tool = z.infer<typeof zTool>;
-const zDrawingTool = zTool.extract(['brush', 'eraser']);
-export type DrawingTool = z.infer<typeof zDrawingTool>;
-
-const zPoints = z.array(z.number()).refine((points) => points.length % 2 === 0, {
-  message: 'Must have an even number of points',
-});
-const zVectorMaskLine = z.object({
-  id: z.string(),
-  type: z.literal('vector_mask_line'),
-  tool: zDrawingTool,
-  strokeWidth: z.number().min(1),
-  points: zPoints,
-});
-export type VectorMaskLine = z.infer<typeof zVectorMaskLine>;
-
-const zVectorMaskRect = z.object({
-  id: z.string(),
-  type: z.literal('vector_mask_rect'),
-  x: z.number(),
-  y: z.number(),
-  width: z.number().min(1),
-  height: z.number().min(1),
-});
-export type VectorMaskRect = z.infer<typeof zVectorMaskRect>;
-
-const zLayerBase = z.object({
-  id: z.string(),
-  isEnabled: z.boolean().default(true),
-  isSelected: z.boolean().default(true),
-});
-
-const zRect = z.object({
-  x: z.number(),
-  y: z.number(),
-  width: z.number().min(1),
-  height: z.number().min(1),
-});
-const zRenderableLayerBase = zLayerBase.extend({
-  x: z.number(),
-  y: z.number(),
-  bbox: zRect.nullable(),
-  bboxNeedsUpdate: z.boolean(),
-});
-
-const zControlAdapterLayer = zRenderableLayerBase.extend({
-  type: z.literal('control_adapter_layer'),
-  opacity: z.number().gte(0).lte(1),
-  isFilterEnabled: z.boolean(),
-  controlAdapter: z.discriminatedUnion('type', [zControlNetConfigV2, zT2IAdapterConfigV2]),
-});
-export type ControlAdapterLayer = z.infer<typeof zControlAdapterLayer>;
-
-const zIPAdapterLayer = zLayerBase.extend({
-  type: z.literal('ip_adapter_layer'),
-  ipAdapter: zIPAdapterConfigV2,
-});
-export type IPAdapterLayer = z.infer<typeof zIPAdapterLayer>;
-
-const zRgbColor = z.object({
-  r: z.number().int().min(0).max(255),
-  g: z.number().int().min(0).max(255),
-  b: z.number().int().min(0).max(255),
-});
-const zRegionalGuidanceLayer = zRenderableLayerBase.extend({
-  type: z.literal('regional_guidance_layer'),
-  maskObjects: z.array(z.discriminatedUnion('type', [zVectorMaskLine, zVectorMaskRect])),
-  positivePrompt: zParameterPositivePrompt.nullable(),
-  negativePrompt: zParameterNegativePrompt.nullable(),
-  ipAdapters: z.array(zIPAdapterConfigV2),
-  previewColor: zRgbColor,
-  autoNegative: zAutoNegative,
-  uploadedMaskImage: zImageWithDims.nullable(),
-});
-export type RegionalGuidanceLayer = z.infer<typeof zRegionalGuidanceLayer>;
-
-const zInitialImageLayer = zRenderableLayerBase.extend({
-  type: z.literal('initial_image_layer'),
-  opacity: z.number().gte(0).lte(1),
-  image: zImageWithDims.nullable(),
-  denoisingStrength: zParameterStrength,
-});
-export type InitialImageLayer = z.infer<typeof zInitialImageLayer>;
-
-export const zLayer = z.discriminatedUnion('type', [
-  zRegionalGuidanceLayer,
-  zControlAdapterLayer,
-  zIPAdapterLayer,
-  zInitialImageLayer,
-]);
-export type Layer = z.infer<typeof zLayer>;
-
-export type ControlLayersState = {
-  _version: 2;
-  selectedLayerId: string | null;
-  layers: Layer[];
-  brushSize: number;
-  globalMaskLayerOpacity: number;
-  positivePrompt: ParameterPositivePrompt;
-  negativePrompt: ParameterNegativePrompt;
-  positivePrompt2: ParameterPositiveStylePromptSDXL;
-  negativePrompt2: ParameterNegativeStylePromptSDXL;
-  shouldConcatPrompts: boolean;
-  size: {
-    width: ParameterWidth;
-    height: ParameterHeight;
-    aspectRatio: AspectRatioState;
-  };
-};

invokeai/frontend/web/src/features/controlLayers/util/controlAdapters.test.ts

@@ -1,77 +0,0 @@
-import type { S } from 'services/api/types';
-import type { Equals } from 'tsafe';
-import { assert } from 'tsafe';
-import { describe, test } from 'vitest';
-
-import type {
-  _CannyProcessorConfig,
-  _ColorMapProcessorConfig,
-  _ContentShuffleProcessorConfig,
-  _DepthAnythingProcessorConfig,
-  _DWOpenposeProcessorConfig,
-  _HedProcessorConfig,
-  _LineartAnimeProcessorConfig,
-  _LineartProcessorConfig,
-  _MediapipeFaceProcessorConfig,
-  _MidasDepthProcessorConfig,
-  _MlsdProcessorConfig,
-  _NormalbaeProcessorConfig,
-  _PidiProcessorConfig,
-  _ZoeDepthProcessorConfig,
-  CannyProcessorConfig,
-  CLIPVisionModelV2,
-  ColorMapProcessorConfig,
-  ContentShuffleProcessorConfig,
-  ControlModeV2,
-  DepthAnythingModelSize,
-  DepthAnythingProcessorConfig,
-  DWOpenposeProcessorConfig,
-  HedProcessorConfig,
-  IPMethodV2,
-  LineartAnimeProcessorConfig,
-  LineartProcessorConfig,
-  MediapipeFaceProcessorConfig,
-  MidasDepthProcessorConfig,
-  MlsdProcessorConfig,
-  NormalbaeProcessorConfig,
-  PidiProcessorConfig,
-  ProcessorConfig,
-  ProcessorTypeV2,
-  ZoeDepthProcessorConfig,
-} from './controlAdapters';
-
-describe('Control Adapter Types', () => {
-  test('ProcessorType', () => {
-    assert<Equals<ProcessorConfig['type'], ProcessorTypeV2>>();
-  });
-  test('IP Adapter Method', () => {
-    assert<Equals<NonNullable<S['IPAdapterInvocation']['method']>, IPMethodV2>>();
-  });
-  test('CLIP Vision Model', () => {
-    assert<Equals<NonNullable<S['IPAdapterInvocation']['clip_vision_model']>, CLIPVisionModelV2>>();
-  });
-  test('Control Mode', () => {
-    assert<Equals<NonNullable<S['ControlNetInvocation']['control_mode']>, ControlModeV2>>();
-  });
-  test('DepthAnything Model Size', () => {
-    assert<Equals<NonNullable<S['DepthAnythingImageProcessorInvocation']['model_size']>, DepthAnythingModelSize>>();
-  });
-  test('Processor Configs', () => {
-    // The processor configs are manually modeled zod schemas. This test ensures that the inferred types are correct.
-    // The types prefixed with `_` are types generated from OpenAPI, while the types without the prefix are manually modeled.
-    assert<Equals<_CannyProcessorConfig, CannyProcessorConfig>>();
-    assert<Equals<_ColorMapProcessorConfig, ColorMapProcessorConfig>>();
-    assert<Equals<_ContentShuffleProcessorConfig, ContentShuffleProcessorConfig>>();
-    assert<Equals<_DepthAnythingProcessorConfig, DepthAnythingProcessorConfig>>();
-    assert<Equals<_HedProcessorConfig, HedProcessorConfig>>();
-    assert<Equals<_LineartAnimeProcessorConfig, LineartAnimeProcessorConfig>>();
-    assert<Equals<_LineartProcessorConfig, LineartProcessorConfig>>();
-    assert<Equals<_MediapipeFaceProcessorConfig, MediapipeFaceProcessorConfig>>();
-    assert<Equals<_MidasDepthProcessorConfig, MidasDepthProcessorConfig>>();
-    assert<Equals<_MlsdProcessorConfig, MlsdProcessorConfig>>();
-    assert<Equals<_NormalbaeProcessorConfig, NormalbaeProcessorConfig>>();
-    assert<Equals<_DWOpenposeProcessorConfig, DWOpenposeProcessorConfig>>();
-    assert<Equals<_PidiProcessorConfig, PidiProcessorConfig>>();
-    assert<Equals<_ZoeDepthProcessorConfig, ZoeDepthProcessorConfig>>();
-  });
-});

invokeai/frontend/web/src/features/controlLayers/util/controlAdapters.ts

@@ -1,591 +0,0 @@
-import { deepClone } from 'common/util/deepClone';
-import { zModelIdentifierField } from 'features/nodes/types/common';
-import { merge, omit } from 'lodash-es';
-import type {
-  BaseModelType,
-  CannyImageProcessorInvocation,
-  ColorMapImageProcessorInvocation,
-  ContentShuffleImageProcessorInvocation,
-  ControlNetModelConfig,
-  DepthAnythingImageProcessorInvocation,
-  DWOpenposeImageProcessorInvocation,
-  Graph,
-  HedImageProcessorInvocation,
-  ImageDTO,
-  LineartAnimeImageProcessorInvocation,
-  LineartImageProcessorInvocation,
-  MediapipeFaceProcessorInvocation,
-  MidasDepthImageProcessorInvocation,
-  MlsdImageProcessorInvocation,
-  NormalbaeImageProcessorInvocation,
-  PidiImageProcessorInvocation,
-  T2IAdapterModelConfig,
-  ZoeDepthImageProcessorInvocation,
-} from 'services/api/types';
-import { z } from 'zod';
-
-const zId = z.string().min(1);
-
-const zCannyProcessorConfig = z.object({
-  id: zId,
-  type: z.literal('canny_image_processor'),
-  low_threshold: z.number().int().gte(0).lte(255),
-  high_threshold: z.number().int().gte(0).lte(255),
-});
-export type _CannyProcessorConfig = Required<
-  Pick<CannyImageProcessorInvocation, 'id' | 'type' | 'low_threshold' | 'high_threshold'>
->;
-export type CannyProcessorConfig = z.infer<typeof zCannyProcessorConfig>;
-
-const zColorMapProcessorConfig = z.object({
-  id: zId,
-  type: z.literal('color_map_image_processor'),
-  color_map_tile_size: z.number().int().gte(1),
-});
-export type _ColorMapProcessorConfig = Required<
-  Pick<ColorMapImageProcessorInvocation, 'id' | 'type' | 'color_map_tile_size'>
->;
-export type ColorMapProcessorConfig = z.infer<typeof zColorMapProcessorConfig>;
-
-const zContentShuffleProcessorConfig = z.object({
-  id: zId,
-  type: z.literal('content_shuffle_image_processor'),
-  w: z.number().int().gte(0),
-  h: z.number().int().gte(0),
-  f: z.number().int().gte(0),
-});
-export type _ContentShuffleProcessorConfig = Required<
-  Pick<ContentShuffleImageProcessorInvocation, 'id' | 'type' | 'w' | 'h' | 'f'>
->;
-export type ContentShuffleProcessorConfig = z.infer<typeof zContentShuffleProcessorConfig>;
-
-const zDepthAnythingModelSize = z.enum(['large', 'base', 'small']);
-export type DepthAnythingModelSize = z.infer<typeof zDepthAnythingModelSize>;
-export const isDepthAnythingModelSize = (v: unknown): v is DepthAnythingModelSize =>
-  zDepthAnythingModelSize.safeParse(v).success;
-const zDepthAnythingProcessorConfig = z.object({
-  id: zId,
-  type: z.literal('depth_anything_image_processor'),
-  model_size: zDepthAnythingModelSize,
-});
-export type _DepthAnythingProcessorConfig = Required<
-  Pick<DepthAnythingImageProcessorInvocation, 'id' | 'type' | 'model_size'>
->;
-export type DepthAnythingProcessorConfig = z.infer<typeof zDepthAnythingProcessorConfig>;
-
-const zHedProcessorConfig = z.object({
-  id: zId,
-  type: z.literal('hed_image_processor'),
-  scribble: z.boolean(),
-});
-export type _HedProcessorConfig = Required<Pick<HedImageProcessorInvocation, 'id' | 'type' | 'scribble'>>;
-export type HedProcessorConfig = z.infer<typeof zHedProcessorConfig>;
-
-const zLineartAnimeProcessorConfig = z.object({
-  id: zId,
-  type: z.literal('lineart_anime_image_processor'),
-});
-export type _LineartAnimeProcessorConfig = Required<Pick<LineartAnimeImageProcessorInvocation, 'id' | 'type'>>;
-export type LineartAnimeProcessorConfig = z.infer<typeof zLineartAnimeProcessorConfig>;
-
-const zLineartProcessorConfig = z.object({
-  id: zId,
-  type: z.literal('lineart_image_processor'),
-  coarse: z.boolean(),
-});
-export type _LineartProcessorConfig = Required<Pick<LineartImageProcessorInvocation, 'id' | 'type' | 'coarse'>>;
-export type LineartProcessorConfig = z.infer<typeof zLineartProcessorConfig>;
-
-const zMediapipeFaceProcessorConfig = z.object({
-  id: zId,
-  type: z.literal('mediapipe_face_processor'),
-  max_faces: z.number().int().gte(1),
-  min_confidence: z.number().gte(0).lte(1),
-});
-export type _MediapipeFaceProcessorConfig = Required<
-  Pick<MediapipeFaceProcessorInvocation, 'id' | 'type' | 'max_faces' | 'min_confidence'>
->;
-export type MediapipeFaceProcessorConfig = z.infer<typeof zMediapipeFaceProcessorConfig>;
-
-const zMidasDepthProcessorConfig = z.object({
-  id: zId,
-  type: z.literal('midas_depth_image_processor'),
-  a_mult: z.number().gte(0),
-  bg_th: z.number().gte(0),
-});
-export type _MidasDepthProcessorConfig = Required<
-  Pick<MidasDepthImageProcessorInvocation, 'id' | 'type' | 'a_mult' | 'bg_th'>
->;
-export type MidasDepthProcessorConfig = z.infer<typeof zMidasDepthProcessorConfig>;
-
-const zMlsdProcessorConfig = z.object({
-  id: zId,
-  type: z.literal('mlsd_image_processor'),
-  thr_v: z.number().gte(0),
-  thr_d: z.number().gte(0),
-});
-export type _MlsdProcessorConfig = Required<Pick<MlsdImageProcessorInvocation, 'id' | 'type' | 'thr_v' | 'thr_d'>>;
-export type MlsdProcessorConfig = z.infer<typeof zMlsdProcessorConfig>;
-
-const zNormalbaeProcessorConfig = z.object({
-  id: zId,
-  type: z.literal('normalbae_image_processor'),
-});
-export type _NormalbaeProcessorConfig = Required<Pick<NormalbaeImageProcessorInvocation, 'id' | 'type'>>;
-export type NormalbaeProcessorConfig = z.infer<typeof zNormalbaeProcessorConfig>;
-
-const zDWOpenposeProcessorConfig = z.object({
-  id: zId,
-  type: z.literal('dw_openpose_image_processor'),
-  draw_body: z.boolean(),
-  draw_face: z.boolean(),
-  draw_hands: z.boolean(),
-});
-export type _DWOpenposeProcessorConfig = Required<
-  Pick<DWOpenposeImageProcessorInvocation, 'id' | 'type' | 'draw_body' | 'draw_face' | 'draw_hands'>
->;
-export type DWOpenposeProcessorConfig = z.infer<typeof zDWOpenposeProcessorConfig>;
-
-const zPidiProcessorConfig = z.object({
-  id: zId,
-  type: z.literal('pidi_image_processor'),
-  safe: z.boolean(),
-  scribble: z.boolean(),
-});
-export type _PidiProcessorConfig = Required<Pick<PidiImageProcessorInvocation, 'id' | 'type' | 'safe' | 'scribble'>>;
-export type PidiProcessorConfig = z.infer<typeof zPidiProcessorConfig>;
-
-const zZoeDepthProcessorConfig = z.object({
-  id: zId,
-  type: z.literal('zoe_depth_image_processor'),
-});
-export type _ZoeDepthProcessorConfig = Required<Pick<ZoeDepthImageProcessorInvocation, 'id' | 'type'>>;
-export type ZoeDepthProcessorConfig = z.infer<typeof zZoeDepthProcessorConfig>;
-
-const zProcessorConfig = z.discriminatedUnion('type', [
-  zCannyProcessorConfig,
-  zColorMapProcessorConfig,
-  zContentShuffleProcessorConfig,
-  zDepthAnythingProcessorConfig,
-  zHedProcessorConfig,
-  zLineartAnimeProcessorConfig,
-  zLineartProcessorConfig,
-  zMediapipeFaceProcessorConfig,
-  zMidasDepthProcessorConfig,
-  zMlsdProcessorConfig,
-  zNormalbaeProcessorConfig,
-  zDWOpenposeProcessorConfig,
-  zPidiProcessorConfig,
-  zZoeDepthProcessorConfig,
-]);
-export type ProcessorConfig = z.infer<typeof zProcessorConfig>;
-
-export const zImageWithDims = z.object({
-  name: z.string(),
-  width: z.number().int().positive(),
-  height: z.number().int().positive(),
-});
-export type ImageWithDims = z.infer<typeof zImageWithDims>;
-
-const zBeginEndStepPct = z
-  .tuple([z.number().gte(0).lte(1), z.number().gte(0).lte(1)])
-  .refine(([begin, end]) => begin < end, {
-    message: 'Begin must be less than end',
-  });
-
-const zControlAdapterBase = z.object({
-  id: zId,
-  weight: z.number().gte(0).lte(1),
-  image: zImageWithDims.nullable(),
-  processedImage: zImageWithDims.nullable(),
-  isProcessingImage: z.boolean(),
-  processorConfig: zProcessorConfig.nullable(),
-  beginEndStepPct: zBeginEndStepPct,
-});
-
-const zControlModeV2 = z.enum(['balanced', 'more_prompt', 'more_control', 'unbalanced']);
-export type ControlModeV2 = z.infer<typeof zControlModeV2>;
-export const isControlModeV2 = (v: unknown): v is ControlModeV2 => zControlModeV2.safeParse(v).success;
-
-export const zControlNetConfigV2 = zControlAdapterBase.extend({
-  type: z.literal('controlnet'),
-  model: zModelIdentifierField.nullable(),
-  controlMode: zControlModeV2,
-});
-export type ControlNetConfigV2 = z.infer<typeof zControlNetConfigV2>;
-
-export const zT2IAdapterConfigV2 = zControlAdapterBase.extend({
-  type: z.literal('t2i_adapter'),
-  model: zModelIdentifierField.nullable(),
-});
-export type T2IAdapterConfigV2 = z.infer<typeof zT2IAdapterConfigV2>;
-
-const zCLIPVisionModelV2 = z.enum(['ViT-H', 'ViT-G']);
-export type CLIPVisionModelV2 = z.infer<typeof zCLIPVisionModelV2>;
-export const isCLIPVisionModelV2 = (v: unknown): v is CLIPVisionModelV2 => zCLIPVisionModelV2.safeParse(v).success;
-
-const zIPMethodV2 = z.enum(['full', 'style', 'composition']);
-export type IPMethodV2 = z.infer<typeof zIPMethodV2>;
-export const isIPMethodV2 = (v: unknown): v is IPMethodV2 => zIPMethodV2.safeParse(v).success;
-
-export const zIPAdapterConfigV2 = z.object({
-  id: zId,
-  type: z.literal('ip_adapter'),
-  weight: z.number().gte(0).lte(1),
-  method: zIPMethodV2,
-  image: zImageWithDims.nullable(),
-  model: zModelIdentifierField.nullable(),
-  clipVisionModel: zCLIPVisionModelV2,
-  beginEndStepPct: zBeginEndStepPct,
-});
-export type IPAdapterConfigV2 = z.infer<typeof zIPAdapterConfigV2>;
-
-const zProcessorTypeV2 = z.enum([
-  'canny_image_processor',
-  'color_map_image_processor',
-  'content_shuffle_image_processor',
-  'depth_anything_image_processor',
-  'hed_image_processor',
-  'lineart_anime_image_processor',
-  'lineart_image_processor',
-  'mediapipe_face_processor',
-  'midas_depth_image_processor',
-  'mlsd_image_processor',
-  'normalbae_image_processor',
-  'dw_openpose_image_processor',
-  'pidi_image_processor',
-  'zoe_depth_image_processor',
-]);
-export type ProcessorTypeV2 = z.infer<typeof zProcessorTypeV2>;
-export const isProcessorTypeV2 = (v: unknown): v is ProcessorTypeV2 => zProcessorTypeV2.safeParse(v).success;
-
-type ProcessorData<T extends ProcessorTypeV2> = {
-  type: T;
-  labelTKey: string;
-  descriptionTKey: string;
-  buildDefaults(baseModel?: BaseModelType): Extract<ProcessorConfig, { type: T }>;
-  buildNode(
-    image: ImageWithDims,
-    config: Extract<ProcessorConfig, { type: T }>
-  ): Extract<Graph['nodes'][string], { type: T }>;
-};
-
-const minDim = (image: ImageWithDims): number => Math.min(image.width, image.height);
-
-type CAProcessorsData = {
-  [key in ProcessorTypeV2]: ProcessorData<key>;
-};
-/**
- * A dict of ControlNet processors, including:
- * - label translation key
- * - description translation key
- * - a builder to create default values for the config
- * - a builder to create the node for the config
- *
- * TODO: Generate from the OpenAPI schema
- */
-export const CA_PROCESSOR_DATA: CAProcessorsData = {
-  canny_image_processor: {
-    type: 'canny_image_processor',
-    labelTKey: 'controlnet.canny',
-    descriptionTKey: 'controlnet.cannyDescription',
-    buildDefaults: () => ({
-      id: 'canny_image_processor',
-      type: 'canny_image_processor',
-      low_threshold: 100,
-      high_threshold: 200,
-    }),
-    buildNode: (image, config) => ({
-      ...config,
-      type: 'canny_image_processor',
-      image: { image_name: image.name },
-      detect_resolution: minDim(image),
-      image_resolution: minDim(image),
-    }),
-  },
-  color_map_image_processor: {
-    type: 'color_map_image_processor',
-    labelTKey: 'controlnet.colorMap',
-    descriptionTKey: 'controlnet.colorMapDescription',
-    buildDefaults: () => ({
-      id: 'color_map_image_processor',
-      type: 'color_map_image_processor',
-      color_map_tile_size: 64,
-    }),
-    buildNode: (image, config) => ({
-      ...config,
-      type: 'color_map_image_processor',
-      image: { image_name: image.name },
-    }),
-  },
-  content_shuffle_image_processor: {
-    type: 'content_shuffle_image_processor',
-    labelTKey: 'controlnet.contentShuffle',
-    descriptionTKey: 'controlnet.contentShuffleDescription',
-    buildDefaults: (baseModel) => ({
-      id: 'content_shuffle_image_processor',
-      type: 'content_shuffle_image_processor',
-      h: baseModel === 'sdxl' ? 1024 : 512,
-      w: baseModel === 'sdxl' ? 1024 : 512,
-      f: baseModel === 'sdxl' ? 512 : 256,
-    }),
-    buildNode: (image, config) => ({
-      ...config,
-      image: { image_name: image.name },
-      detect_resolution: minDim(image),
-      image_resolution: minDim(image),
-    }),
-  },
-  depth_anything_image_processor: {
-    type: 'depth_anything_image_processor',
-    labelTKey: 'controlnet.depthAnything',
-    descriptionTKey: 'controlnet.depthAnythingDescription',
-    buildDefaults: () => ({
-      id: 'depth_anything_image_processor',
-      type: 'depth_anything_image_processor',
-      model_size: 'small',
-    }),
-    buildNode: (image, config) => ({
-      ...config,
-      image: { image_name: image.name },
-      resolution: minDim(image),
-    }),
-  },
-  hed_image_processor: {
-    type: 'hed_image_processor',
-    labelTKey: 'controlnet.hed',
-    descriptionTKey: 'controlnet.hedDescription',
-    buildDefaults: () => ({
-      id: 'hed_image_processor',
-      type: 'hed_image_processor',
-      scribble: false,
-    }),
-    buildNode: (image, config) => ({
-      ...config,
-      image: { image_name: image.name },
-      detect_resolution: minDim(image),
-      image_resolution: minDim(image),
-    }),
-  },
-  lineart_anime_image_processor: {
-    type: 'lineart_anime_image_processor',
-    labelTKey: 'controlnet.lineartAnime',
-    descriptionTKey: 'controlnet.lineartAnimeDescription',
-    buildDefaults: () => ({
-      id: 'lineart_anime_image_processor',
-      type: 'lineart_anime_image_processor',
-    }),
-    buildNode: (image, config) => ({
-      ...config,
-      image: { image_name: image.name },
-      detect_resolution: minDim(image),
-      image_resolution: minDim(image),
-    }),
-  },
-  lineart_image_processor: {
-    type: 'lineart_image_processor',
-    labelTKey: 'controlnet.lineart',
-    descriptionTKey: 'controlnet.lineartDescription',
-    buildDefaults: () => ({
-      id: 'lineart_image_processor',
-      type: 'lineart_image_processor',
-      coarse: false,
-    }),
-    buildNode: (image, config) => ({
-      ...config,
-      image: { image_name: image.name },
-      detect_resolution: minDim(image),
-      image_resolution: minDim(image),
-    }),
-  },
-  mediapipe_face_processor: {
-    type: 'mediapipe_face_processor',
-    labelTKey: 'controlnet.mediapipeFace',
-    descriptionTKey: 'controlnet.mediapipeFaceDescription',
-    buildDefaults: () => ({
-      id: 'mediapipe_face_processor',
-      type: 'mediapipe_face_processor',
-      max_faces: 1,
-      min_confidence: 0.5,
-    }),
-    buildNode: (image, config) => ({
-      ...config,
-      image: { image_name: image.name },
-      detect_resolution: minDim(image),
-      image_resolution: minDim(image),
-    }),
-  },
-  midas_depth_image_processor: {
-    type: 'midas_depth_image_processor',
-    labelTKey: 'controlnet.depthMidas',
-    descriptionTKey: 'controlnet.depthMidasDescription',
-    buildDefaults: () => ({
-      id: 'midas_depth_image_processor',
-      type: 'midas_depth_image_processor',
-      a_mult: 2,
-      bg_th: 0.1,
-    }),
-    buildNode: (image, config) => ({
-      ...config,
-      image: { image_name: image.name },
-      detect_resolution: minDim(image),
-      image_resolution: minDim(image),
-    }),
-  },
-  mlsd_image_processor: {
-    type: 'mlsd_image_processor',
-    labelTKey: 'controlnet.mlsd',
-    descriptionTKey: 'controlnet.mlsdDescription',
-    buildDefaults: () => ({
-      id: 'mlsd_image_processor',
-      type: 'mlsd_image_processor',
-      thr_d: 0.1,
-      thr_v: 0.1,
-    }),
-    buildNode: (image, config) => ({
-      ...config,
-      image: { image_name: image.name },
-      detect_resolution: minDim(image),
-      image_resolution: minDim(image),
-    }),
-  },
-  normalbae_image_processor: {
-    type: 'normalbae_image_processor',
-    labelTKey: 'controlnet.normalBae',
-    descriptionTKey: 'controlnet.normalBaeDescription',
-    buildDefaults: () => ({
-      id: 'normalbae_image_processor',
-      type: 'normalbae_image_processor',
-    }),
-    buildNode: (image, config) => ({
-      ...config,
-      image: { image_name: image.name },
-      detect_resolution: minDim(image),
-      image_resolution: minDim(image),
-    }),
-  },
-  dw_openpose_image_processor: {
-    type: 'dw_openpose_image_processor',
-    labelTKey: 'controlnet.dwOpenpose',
-    descriptionTKey: 'controlnet.dwOpenposeDescription',
-    buildDefaults: () => ({
-      id: 'dw_openpose_image_processor',
-      type: 'dw_openpose_image_processor',
-      draw_body: true,
-      draw_face: false,
-      draw_hands: false,
-    }),
-    buildNode: (image, config) => ({
-      ...config,
-      image: { image_name: image.name },
-      image_resolution: minDim(image),
-    }),
-  },
-  pidi_image_processor: {
-    type: 'pidi_image_processor',
-    labelTKey: 'controlnet.pidi',
-    descriptionTKey: 'controlnet.pidiDescription',
-    buildDefaults: () => ({
-      id: 'pidi_image_processor',
-      type: 'pidi_image_processor',
-      scribble: false,
-      safe: false,
-    }),
-    buildNode: (image, config) => ({
-      ...config,
-      image: { image_name: image.name },
-      detect_resolution: minDim(image),
-      image_resolution: minDim(image),
-    }),
-  },
-  zoe_depth_image_processor: {
-    type: 'zoe_depth_image_processor',
-    labelTKey: 'controlnet.depthZoe',
-    descriptionTKey: 'controlnet.depthZoeDescription',
-    buildDefaults: () => ({
-      id: 'zoe_depth_image_processor',
-      type: 'zoe_depth_image_processor',
-    }),
-    buildNode: (image, config) => ({
-      ...config,
-      image: { image_name: image.name },
-    }),
-  },
-};
-
-export const initialControlNetV2: Omit<ControlNetConfigV2, 'id'> = {
-  type: 'controlnet',
-  model: null,
-  weight: 1,
-  beginEndStepPct: [0, 1],
-  controlMode: 'balanced',
-  image: null,
-  processedImage: null,
-  isProcessingImage: false,
-  processorConfig: CA_PROCESSOR_DATA.canny_image_processor.buildDefaults(),
-};
-
-export const initialT2IAdapterV2: Omit<T2IAdapterConfigV2, 'id'> = {
-  type: 't2i_adapter',
-  model: null,
-  weight: 1,
-  beginEndStepPct: [0, 1],
-  image: null,
-  processedImage: null,
-  isProcessingImage: false,
-  processorConfig: CA_PROCESSOR_DATA.canny_image_processor.buildDefaults(),
-};
-
-export const initialIPAdapterV2: Omit<IPAdapterConfigV2, 'id'> = {
-  type: 'ip_adapter',
-  image: null,
-  model: null,
-  beginEndStepPct: [0, 1],
-  method: 'full',
-  clipVisionModel: 'ViT-H',
-  weight: 1,
-};
-
-export const buildControlNet = (id: string, overrides?: Partial<ControlNetConfigV2>): ControlNetConfigV2 => {
-  return merge(deepClone(initialControlNetV2), { id, ...overrides });
-};
-
-export const buildT2IAdapter = (id: string, overrides?: Partial<T2IAdapterConfigV2>): T2IAdapterConfigV2 => {
-  return merge(deepClone(initialT2IAdapterV2), { id, ...overrides });
-};
-
-export const buildIPAdapter = (id: string, overrides?: Partial<IPAdapterConfigV2>): IPAdapterConfigV2 => {
-  return merge(deepClone(initialIPAdapterV2), { id, ...overrides });
-};
-
-export const buildControlAdapterProcessorV2 = (
-  modelConfig: ControlNetModelConfig | T2IAdapterModelConfig
-): ProcessorConfig | null => {
-  const defaultPreprocessor = modelConfig.default_settings?.preprocessor;
-  if (!isProcessorTypeV2(defaultPreprocessor)) {
-    return null;
-  }
-  const processorConfig = CA_PROCESSOR_DATA[defaultPreprocessor].buildDefaults(modelConfig.base);
-  return processorConfig;
-};
-
-export const imageDTOToImageWithDims = ({ image_name, width, height }: ImageDTO): ImageWithDims => ({
-  name: image_name,
-  width,
-  height,
-});
-
-export const t2iAdapterToControlNet = (t2iAdapter: T2IAdapterConfigV2): ControlNetConfigV2 => {
-  return {
-    ...deepClone(t2iAdapter),
-    type: 'controlnet',
-    controlMode: initialControlNetV2.controlMode,
-  };
-};
-
-export const controlNetToT2IAdapter = (controlNet: ControlNetConfigV2): T2IAdapterConfigV2 => {
-  return {
-    ...omit(deepClone(controlNet), 'controlMode'),
-    type: 't2i_adapter',
-  };
-};