diff --git a/README.md b/README.md index 5ad2b47509..393cb34782 100644 --- a/README.md +++ b/README.md @@ -132,8 +132,10 @@ and go to http://localhost:9090. ### Command-Line Installation (for developers and users familiar with Terminals) -You must have Python 3.9 or 3.10 installed on your machine. Earlier or later versions are -not supported. +You must have Python 3.9 or 3.10 installed on your machine. Earlier or +later versions are not supported. +Node.js also needs to be installed along with yarn (can be installed with +the command `npm install -g yarn` if needed) 1. Open a command-line window on your machine. The PowerShell is recommended for Windows. 2. Create a directory to install InvokeAI into. You'll need at least 15 GB of free space: @@ -197,11 +199,18 @@ not supported. 7. Launch the web server (do it every time you run InvokeAI): ```terminal - invokeai --web + invokeai-web ``` -8. Point your browser to http://localhost:9090 to bring up the web interface. -9. Type `banana sushi` in the box on the top left and click `Invoke`. +8. Build Node.js assets + + ```terminal + cd invokeai/frontend/web/ + yarn vite build + ``` + +9. Point your browser to http://localhost:9090 to bring up the web interface. +10. Type `banana sushi` in the box on the top left and click `Invoke`. Be sure to activate the virtual environment each time before re-launching InvokeAI, using `source .venv/bin/activate` or `.venv\Scripts\activate`. diff --git a/docs/contributing/LOCAL_DEVELOPMENT.md b/docs/contributing/LOCAL_DEVELOPMENT.md index 956ef5ec03..b2a5cd581d 100644 --- a/docs/contributing/LOCAL_DEVELOPMENT.md +++ b/docs/contributing/LOCAL_DEVELOPMENT.md @@ -81,3 +81,193 @@ pytest --cov; open ./coverage/html/index.html --8<-- "invokeai/frontend/web/README.md" + +## Developing InvokeAI in VSCode + +VSCode offers some nice tools: + +- python debugger +- automatic `venv` activation +- remote dev (e.g. run InvokeAI on a beefy linux desktop while you type in + comfort on your macbook) + +### Setup + +You'll need the +[Python](https://marketplace.visualstudio.com/items?itemName=ms-python.python) +and +[Pylance](https://marketplace.visualstudio.com/items?itemName=ms-python.vscode-pylance) +extensions installed first. + +It's also really handy to install the `Jupyter` extensions: + +- [Jupyter](https://marketplace.visualstudio.com/items?itemName=ms-toolsai.jupyter) +- [Jupyter Cell Tags](https://marketplace.visualstudio.com/items?itemName=ms-toolsai.vscode-jupyter-cell-tags) +- [Jupyter Notebook Renderers](https://marketplace.visualstudio.com/items?itemName=ms-toolsai.jupyter-renderers) +- [Jupyter Slide Show](https://marketplace.visualstudio.com/items?itemName=ms-toolsai.vscode-jupyter-slideshow) + +#### InvokeAI workspace + +Creating a VSCode workspace for working on InvokeAI is highly recommended. It +can hold InvokeAI-specific settings and configs. + +To make a workspace: + +- Open the InvokeAI repo dir in VSCode +- `File` > `Save Workspace As` > save it _outside_ the repo + +#### Default python interpreter (i.e. automatic virtual environment activation) + +- Use command palette to run command + `Preferences: Open Workspace Settings (JSON)` +- Add `python.defaultInterpreterPath` to `settings`, pointing to your `venv`'s + python + +Should look something like this: + +```jsonc +{ + // I like to have all InvokeAI-related folders in my workspace + "folders": [ + { + // repo root + "path": "InvokeAI" + }, + { + // InvokeAI root dir, where `invokeai.yaml` lives + "path": "/path/to/invokeai_root" + } + ], + "settings": { + // Where your InvokeAI `venv`'s python executable lives + "python.defaultInterpreterPath": "/path/to/invokeai_root/.venv/bin/python" + } +} +``` + +Now when you open the VSCode integrated terminal, or do anything that needs to +run python, it will automatically be in your InvokeAI virtual environment. + +Bonus: When you create a Jupyter notebook, when you run it, you'll be prompted +for the python interpreter to run in. This will default to your `venv` python, +and so you'll have access to the same python environment as the InvokeAI app. + +This is _super_ handy. + +#### Debugging configs with `launch.json` + +Debugging configs are managed in a `launch.json` file. Like most VSCode configs, +these can be scoped to a workspace or folder. + +Follow the [official guide](https://code.visualstudio.com/docs/python/debugging) +to set up your `launch.json` and try it out. + +Now we can create the InvokeAI debugging configs: + +```jsonc +{ + // Use IntelliSense to learn about possible attributes. + // Hover to view descriptions of existing attributes. + // For more information, visit: https://go.microsoft.com/fwlink/?linkid=830387 + "version": "0.2.0", + "configurations": [ + { + // Run the InvokeAI backend & serve the pre-built UI + "name": "InvokeAI Web", + "type": "python", + "request": "launch", + "program": "scripts/invokeai-web.py", + "args": [ + // Your InvokeAI root dir (where `invokeai.yaml` lives) + "--root", + "/path/to/invokeai_root", + // Access the app from anywhere on your local network + "--host", + "0.0.0.0" + ], + "justMyCode": true + }, + { + // Run the nodes-based CLI + "name": "InvokeAI CLI", + "type": "python", + "request": "launch", + "program": "scripts/invokeai-cli.py", + "justMyCode": true + }, + { + // Run tests + "name": "InvokeAI Test", + "type": "python", + "request": "launch", + "module": "pytest", + "args": ["--capture=no"], + "justMyCode": true + }, + { + // Run a single test + "name": "InvokeAI Single Test", + "type": "python", + "request": "launch", + "module": "pytest", + "args": [ + // Change this to point to the specific test you are working on + "tests/nodes/test_invoker.py" + ], + "justMyCode": true + }, + { + // This is the default, useful to just run a single file + "name": "Python: File", + "type": "python", + "request": "launch", + "program": "${file}", + "justMyCode": true + } + ] +} +``` + +You'll see these configs in the debugging configs drop down. Running them will +start InvokeAI with attached debugger, in the correct environment, and work just +like the normal app. + +Enjoy debugging InvokeAI with ease (not that we have any bugs of course). + +#### Remote dev + +This is very easy to set up and provides the same very smooth experience as +local development. Environments and debugging, as set up above, just work, +though you'd need to recreate the workspace and debugging configs on the remote. + +Consult the +[official guide](https://code.visualstudio.com/docs/remote/remote-overview) to +get it set up. + +Suggest using VSCode's included settings sync so that your remote dev host has +all the same app settings and extensions automagically. + +##### One remote dev gotcha + +I've found the automatic port forwarding to be very flakey. You can disable it +in `Preferences: Open Remote Settings (ssh: hostname)`. Search for +`remote.autoForwardPorts` and untick the box. + +To forward ports very reliably, use SSH on the remote dev client (e.g. your +macbook). Here's how to forward both backend API port (`9090`) and the frontend +live dev server port (`5173`): + +```bash +ssh \ + -L 9090:localhost:9090 \ + -L 5173:localhost:5173 \ + user@remote-dev-host +``` + +The forwarding stops when you close the terminal window, so suggest to do this +_outside_ the VSCode integrated terminal in case you need to restart VSCode for +an extension update or something + +Now, on your remote dev client, you can open `localhost:9090` and access the UI, +now served from the remote dev host, just the same as if it was running on the +client. diff --git a/docs/features/NODES.md b/docs/features/NODES.md index 1cd788b8aa..1f276d2012 100644 --- a/docs/features/NODES.md +++ b/docs/features/NODES.md @@ -1,4 +1,8 @@ -# Nodes Editor (Experimental Beta) +# Nodes Editor (Experimental) + +🚨 +*The node editor is experimental. We've made it accessible because we use it to develop the application, but we have not addressed the many known rough edges. It's very easy to shoot yourself in the foot, and we cannot offer support for it until it sees full release (ETA v3.1). Everything is subject to change without warning.* +🚨 The nodes editor is a blank canvas allowing for the use of individual functions and image transformations to control the image generation workflow. The node processing flow is usually done from left (inputs) to right (outputs), though linearity can become abstracted the more complex the node graph becomes. Nodes inputs and outputs are connected by dragging connectors from node to node. diff --git a/installer/create_installer.sh b/installer/create_installer.sh index eac0028493..1ab82254a4 100755 --- a/installer/create_installer.sh +++ b/installer/create_installer.sh @@ -24,7 +24,8 @@ read -e -p "Tag this repo with '${VERSION}' and '${LATEST_TAG}'? [n]: " input RESPONSE=${input:='n'} if [ "$RESPONSE" == 'y' ]; then - if ! git tag $VERSION ; then + git push origin :refs/tags/$VERSION + if ! git tag -fa $VERSION ; then echo "Existing/invalid tag" exit -1 fi diff --git a/installer/install.bat.in b/installer/install.bat.in index 8f729e758d..ffe96d4355 100644 --- a/installer/install.bat.in +++ b/installer/install.bat.in @@ -38,7 +38,7 @@ echo https://learn.microsoft.com/en-US/cpp/windows/latest-supported-vc-redist echo. echo See %INSTRUCTIONS% for more details. echo. -echo "For the best user experience we suggest enlarging or maximizing this window now." +echo FOR THE BEST USER EXPERIENCE WE SUGGEST MAXIMIZING THIS WINDOW NOW. pause @rem ---------------------------- check Python version --------------- diff --git a/installer/templates/invoke.bat.in b/installer/templates/invoke.bat.in index 7900eac1cf..5c6465ee3a 100644 --- a/installer/templates/invoke.bat.in +++ b/installer/templates/invoke.bat.in @@ -19,7 +19,7 @@ echo 8. Open the developer console echo 9. Update InvokeAI echo 10. Command-line help echo Q - Quit -set /P choice="Please enter 1-10, Q: [2] " +set /P choice="Please enter 1-10, Q: [1] " if not defined choice set choice=1 IF /I "%choice%" == "1" ( echo Starting the InvokeAI browser-based UI.. diff --git a/invokeai/app/api/dependencies.py b/invokeai/app/api/dependencies.py index cb867354a5..555c60a383 100644 --- a/invokeai/app/api/dependencies.py +++ b/invokeai/app/api/dependencies.py @@ -11,6 +11,7 @@ from invokeai.app.services.board_images import ( ) from invokeai.app.services.board_record_storage import SqliteBoardRecordStorage from invokeai.app.services.boards import BoardService, BoardServiceDependencies +from invokeai.app.services.config import InvokeAIAppConfig from invokeai.app.services.image_record_storage import SqliteImageRecordStorage from invokeai.app.services.images import ImageService, ImageServiceDependencies from invokeai.app.services.resource_name import SimpleNameService @@ -20,7 +21,6 @@ from invokeai.version.invokeai_version import __version__ from ..services.default_graphs import create_system_graphs from ..services.latent_storage import DiskLatentsStorage, ForwardCacheLatentsStorage -from ..services.restoration_services import RestorationServices from ..services.graph import GraphExecutionState, LibraryGraph from ..services.image_file_storage import DiskImageFileStorage from ..services.invocation_queue import MemoryInvocationQueue @@ -57,8 +57,8 @@ class ApiDependencies: invoker: Invoker = None @staticmethod - def initialize(config, event_handler_id: int, logger: Logger = logger): - logger.debug(f'InvokeAI version {__version__}') + def initialize(config: InvokeAIAppConfig, event_handler_id: int, logger: Logger = logger): + logger.debug(f"InvokeAI version {__version__}") logger.debug(f"Internet connectivity is {config.internet_available}") events = FastAPIEventService(event_handler_id) @@ -117,7 +117,7 @@ class ApiDependencies: ) services = InvocationServices( - model_manager=ModelManagerService(config,logger), + model_manager=ModelManagerService(config, logger), events=events, latents=latents, images=images, @@ -129,7 +129,6 @@ class ApiDependencies: ), graph_execution_manager=graph_execution_manager, processor=DefaultInvocationProcessor(), - restoration=RestorationServices(config, logger), configuration=config, logger=logger, ) diff --git a/invokeai/app/api/routers/models.py b/invokeai/app/api/routers/models.py index a320c88858..cc6d09f761 100644 --- a/invokeai/app/api/routers/models.py +++ b/invokeai/app/api/routers/models.py @@ -13,8 +13,11 @@ from invokeai.backend import BaseModelType, ModelType from invokeai.backend.model_management.models import ( OPENAPI_MODEL_CONFIGS, SchedulerPredictionType, + ModelNotFoundException, + InvalidModelException, ) from invokeai.backend.model_management import MergeInterpolationMethod + from ..dependencies import ApiDependencies models_router = APIRouter(prefix="/v1/models", tags=["models"]) @@ -51,8 +54,9 @@ async def list_models( "/{base_model}/{model_type}/{model_name}", operation_id="update_model", responses={200: {"description" : "The model was updated successfully"}, + 400: {"description" : "Bad request"}, 404: {"description" : "The model could not be found"}, - 400: {"description" : "Bad request"} + 409: {"description" : "There is already a model corresponding to the new name"}, }, status_code = 200, response_model = UpdateModelResponse, @@ -63,23 +67,58 @@ async def update_model( model_name: str = Path(description="model name"), info: Union[tuple(OPENAPI_MODEL_CONFIGS)] = Body(description="Model configuration"), ) -> UpdateModelResponse: - """ Add Model """ + """ Update model contents with a new config. If the model name or base fields are changed, then the model is renamed. """ + logger = ApiDependencies.invoker.services.logger + + try: + previous_info = ApiDependencies.invoker.services.model_manager.list_model( + model_name=model_name, + base_model=base_model, + model_type=model_type, + ) + + # rename operation requested + if info.model_name != model_name or info.base_model != base_model: + ApiDependencies.invoker.services.model_manager.rename_model( + base_model = base_model, + model_type = model_type, + model_name = model_name, + new_name = info.model_name, + new_base = info.base_model, + ) + logger.info(f'Successfully renamed {base_model}/{model_name}=>{info.base_model}/{info.model_name}') + # update information to support an update of attributes + model_name = info.model_name + base_model = info.base_model + new_info = ApiDependencies.invoker.services.model_manager.list_model( + model_name=model_name, + base_model=base_model, + model_type=model_type, + ) + if new_info.get('path') != previous_info.get('path'): # model manager moved model path during rename - don't overwrite it + info.path = new_info.get('path') + ApiDependencies.invoker.services.model_manager.update_model( model_name=model_name, base_model=base_model, model_type=model_type, model_attributes=info.dict() ) + model_raw = ApiDependencies.invoker.services.model_manager.list_model( model_name=model_name, base_model=base_model, model_type=model_type, ) model_response = parse_obj_as(UpdateModelResponse, model_raw) - except KeyError as e: + except ModelNotFoundException as e: raise HTTPException(status_code=404, detail=str(e)) except ValueError as e: + logger.error(str(e)) + raise HTTPException(status_code=409, detail=str(e)) + except Exception as e: + logger.error(str(e)) raise HTTPException(status_code=400, detail=str(e)) return model_response @@ -90,6 +129,7 @@ async def update_model( responses= { 201: {"description" : "The model imported successfully"}, 404: {"description" : "The model could not be found"}, + 415: {"description" : "Unrecognized file/folder format"}, 424: {"description" : "The model appeared to import successfully, but could not be found in the model manager"}, 409: {"description" : "There is already a model corresponding to this path or repo_id"}, }, @@ -116,7 +156,7 @@ async def import_model( if not info: logger.error("Import failed") - raise HTTPException(status_code=424) + raise HTTPException(status_code=415) logger.info(f'Successfully imported {location}, got {info}') model_raw = ApiDependencies.invoker.services.model_manager.list_model( @@ -126,9 +166,12 @@ async def import_model( ) return parse_obj_as(ImportModelResponse, model_raw) - except KeyError as e: + except ModelNotFoundException as e: logger.error(str(e)) raise HTTPException(status_code=404, detail=str(e)) + except InvalidModelException as e: + logger.error(str(e)) + raise HTTPException(status_code=415) except ValueError as e: logger.error(str(e)) raise HTTPException(status_code=409, detail=str(e)) @@ -166,57 +209,13 @@ async def add_model( model_type=info.model_type ) return parse_obj_as(ImportModelResponse, model_raw) - except KeyError as e: + except ModelNotFoundException as e: logger.error(str(e)) raise HTTPException(status_code=404, detail=str(e)) except ValueError as e: logger.error(str(e)) raise HTTPException(status_code=409, detail=str(e)) -@models_router.post( - "/rename/{base_model}/{model_type}/{model_name}", - operation_id="rename_model", - responses= { - 201: {"description" : "The model was renamed successfully"}, - 404: {"description" : "The model could not be found"}, - 409: {"description" : "There is already a model corresponding to the new name"}, - }, - status_code=201, - response_model=ImportModelResponse -) -async def rename_model( - base_model: BaseModelType = Path(description="Base model"), - model_type: ModelType = Path(description="The type of model"), - model_name: str = Path(description="current model name"), - new_name: Optional[str] = Query(description="new model name", default=None), - new_base: Optional[BaseModelType] = Query(description="new model base", default=None), -) -> ImportModelResponse: - """ Rename a model""" - - logger = ApiDependencies.invoker.services.logger - - try: - result = ApiDependencies.invoker.services.model_manager.rename_model( - base_model = base_model, - model_type = model_type, - model_name = model_name, - new_name = new_name, - new_base = new_base, - ) - logger.debug(result) - logger.info(f'Successfully renamed {model_name}=>{new_name}') - model_raw = ApiDependencies.invoker.services.model_manager.list_model( - model_name=new_name or model_name, - base_model=new_base or base_model, - model_type=model_type - ) - return parse_obj_as(ImportModelResponse, model_raw) - except KeyError as e: - logger.error(str(e)) - raise HTTPException(status_code=404, detail=str(e)) - except ValueError as e: - logger.error(str(e)) - raise HTTPException(status_code=409, detail=str(e)) @models_router.delete( "/{base_model}/{model_type}/{model_name}", @@ -243,9 +242,9 @@ async def delete_model( ) logger.info(f"Deleted model: {model_name}") return Response(status_code=204) - except KeyError: - logger.error(f"Model not found: {model_name}") - raise HTTPException(status_code=404, detail=f"Model '{model_name}' not found") + except ModelNotFoundException as e: + logger.error(str(e)) + raise HTTPException(status_code=404, detail=str(e)) @models_router.put( "/convert/{base_model}/{model_type}/{model_name}", @@ -278,8 +277,8 @@ async def convert_model( base_model = base_model, model_type = model_type) response = parse_obj_as(ConvertModelResponse, model_raw) - except KeyError: - raise HTTPException(status_code=404, detail=f"Model '{model_name}' not found") + except ModelNotFoundException as e: + raise HTTPException(status_code=404, detail=f"Model '{model_name}' not found: {str(e)}") except ValueError as e: raise HTTPException(status_code=400, detail=str(e)) return response @@ -369,8 +368,55 @@ async def merge_models( model_type = ModelType.Main, ) response = parse_obj_as(ConvertModelResponse, model_raw) - except KeyError: + except ModelNotFoundException: raise HTTPException(status_code=404, detail=f"One or more of the models '{model_names}' not found") except ValueError as e: raise HTTPException(status_code=400, detail=str(e)) return response + +# The rename operation is now supported by update_model and no longer needs to be +# a standalone route. +# @models_router.post( +# "/rename/{base_model}/{model_type}/{model_name}", +# operation_id="rename_model", +# responses= { +# 201: {"description" : "The model was renamed successfully"}, +# 404: {"description" : "The model could not be found"}, +# 409: {"description" : "There is already a model corresponding to the new name"}, +# }, +# status_code=201, +# response_model=ImportModelResponse +# ) +# async def rename_model( +# base_model: BaseModelType = Path(description="Base model"), +# model_type: ModelType = Path(description="The type of model"), +# model_name: str = Path(description="current model name"), +# new_name: Optional[str] = Query(description="new model name", default=None), +# new_base: Optional[BaseModelType] = Query(description="new model base", default=None), +# ) -> ImportModelResponse: +# """ Rename a model""" + +# logger = ApiDependencies.invoker.services.logger + +# try: +# result = ApiDependencies.invoker.services.model_manager.rename_model( +# base_model = base_model, +# model_type = model_type, +# model_name = model_name, +# new_name = new_name, +# new_base = new_base, +# ) +# logger.debug(result) +# logger.info(f'Successfully renamed {model_name}=>{new_name}') +# model_raw = ApiDependencies.invoker.services.model_manager.list_model( +# model_name=new_name or model_name, +# base_model=new_base or base_model, +# model_type=model_type +# ) +# return parse_obj_as(ImportModelResponse, model_raw) +# except ModelNotFoundException as e: +# logger.error(str(e)) +# raise HTTPException(status_code=404, detail=str(e)) +# except ValueError as e: +# logger.error(str(e)) +# raise HTTPException(status_code=409, detail=str(e)) diff --git a/invokeai/app/api_app.py b/invokeai/app/api_app.py index 9bcded1c49..4afa3aa161 100644 --- a/invokeai/app/api_app.py +++ b/invokeai/app/api_app.py @@ -39,6 +39,7 @@ from .invocations.baseinvocation import BaseInvocation import torch +import invokeai.backend.util.hotfixes if torch.backends.mps.is_available(): import invokeai.backend.util.mps_fixes diff --git a/invokeai/app/cli_app.py b/invokeai/app/cli_app.py index 888d36c4bf..341e9e5b7e 100644 --- a/invokeai/app/cli_app.py +++ b/invokeai/app/cli_app.py @@ -54,10 +54,10 @@ from .services.invocation_services import InvocationServices from .services.invoker import Invoker from .services.model_manager_service import ModelManagerService from .services.processor import DefaultInvocationProcessor -from .services.restoration_services import RestorationServices from .services.sqlite import SqliteItemStorage import torch +import invokeai.backend.util.hotfixes if torch.backends.mps.is_available(): import invokeai.backend.util.mps_fixes @@ -295,7 +295,6 @@ def invoke_cli(): ), graph_execution_manager=graph_execution_manager, processor=DefaultInvocationProcessor(), - restoration=RestorationServices(config,logger=logger), logger=logger, configuration=config, ) diff --git a/invokeai/app/invocations/compel.py b/invokeai/app/invocations/compel.py index a916e59507..39c5514148 100644 --- a/invokeai/app/invocations/compel.py +++ b/invokeai/app/invocations/compel.py @@ -86,10 +86,10 @@ class CompelInvocation(BaseInvocation): @torch.no_grad() def invoke(self, context: InvocationContext) -> CompelOutput: tokenizer_info = context.services.model_manager.get_model( - **self.clip.tokenizer.dict(), + **self.clip.tokenizer.dict(), context=context, ) text_encoder_info = context.services.model_manager.get_model( - **self.clip.text_encoder.dict(), + **self.clip.text_encoder.dict(), context=context, ) def _lora_loader(): @@ -111,6 +111,7 @@ class CompelInvocation(BaseInvocation): model_name=name, base_model=self.clip.text_encoder.base_model, model_type=ModelType.TextualInversion, + context=context, ).context.model ) except ModelNotFoundException: @@ -129,7 +130,7 @@ class CompelInvocation(BaseInvocation): text_encoder=text_encoder, textual_inversion_manager=ti_manager, dtype_for_device_getter=torch_dtype, - truncate_long_prompts=False, + truncate_long_prompts=True, ) conjunction = Compel.parse_prompt_string(self.prompt) @@ -438,7 +439,7 @@ class SDXLRefinerCompelPromptInvocation(BaseInvocation, SDXLPromptInvocationBase ) class SDXLRawPromptInvocation(BaseInvocation, SDXLPromptInvocationBase): - """Parse prompt using compel package to conditioning.""" + """Pass unmodified prompt to conditioning without compel processing.""" type: Literal["sdxl_raw_prompt"] = "sdxl_raw_prompt" diff --git a/invokeai/app/invocations/generate.py b/invokeai/app/invocations/generate.py index c5967e4074..7d72d61ea1 100644 --- a/invokeai/app/invocations/generate.py +++ b/invokeai/app/invocations/generate.py @@ -161,13 +161,13 @@ class InpaintInvocation(BaseInvocation): def _lora_loader(): for lora in self.unet.loras: lora_info = context.services.model_manager.get_model( - **lora.dict(exclude={"weight"})) + **lora.dict(exclude={"weight"}), context=context,) yield (lora_info.context.model, lora.weight) del lora_info return - unet_info = context.services.model_manager.get_model(**self.unet.unet.dict()) - vae_info = context.services.model_manager.get_model(**self.vae.vae.dict()) + unet_info = context.services.model_manager.get_model(**self.unet.unet.dict(), context=context,) + vae_info = context.services.model_manager.get_model(**self.vae.vae.dict(), context=context,) with vae_info as vae,\ ModelPatcher.apply_lora_unet(unet_info.context.model, _lora_loader()),\ diff --git a/invokeai/app/invocations/latent.py b/invokeai/app/invocations/latent.py index 8af5a943a8..575ba28c49 100644 --- a/invokeai/app/invocations/latent.py +++ b/invokeai/app/invocations/latent.py @@ -83,7 +83,7 @@ def get_scheduler( scheduler_name, SCHEDULER_MAP['ddim'] ) orig_scheduler_info = context.services.model_manager.get_model( - **scheduler_info.dict() + **scheduler_info.dict(), context=context, ) with orig_scheduler_info as orig_scheduler: scheduler_config = orig_scheduler.config @@ -270,6 +270,7 @@ class TextToLatentsInvocation(BaseInvocation): model_name=control_info.control_model.model_name, model_type=ModelType.ControlNet, base_model=control_info.control_model.base_model, + context=context, ) ) @@ -321,14 +322,14 @@ class TextToLatentsInvocation(BaseInvocation): def _lora_loader(): for lora in self.unet.loras: lora_info = context.services.model_manager.get_model( - **lora.dict(exclude={"weight"}) + **lora.dict(exclude={"weight"}), context=context, ) yield (lora_info.context.model, lora.weight) del lora_info return unet_info = context.services.model_manager.get_model( - **self.unet.unet.dict() + **self.unet.unet.dict(), context=context, ) with ExitStack() as exit_stack,\ ModelPatcher.apply_lora_unet(unet_info.context.model, _lora_loader()),\ @@ -414,14 +415,14 @@ class LatentsToLatentsInvocation(TextToLatentsInvocation): def _lora_loader(): for lora in self.unet.loras: lora_info = context.services.model_manager.get_model( - **lora.dict(exclude={"weight"}) + **lora.dict(exclude={"weight"}), context=context, ) yield (lora_info.context.model, lora.weight) del lora_info return unet_info = context.services.model_manager.get_model( - **self.unet.unet.dict() + **self.unet.unet.dict(), context=context, ) with ExitStack() as exit_stack,\ ModelPatcher.apply_lora_unet(unet_info.context.model, _lora_loader()),\ @@ -506,7 +507,7 @@ class LatentsToImageInvocation(BaseInvocation): latents = context.services.latents.get(self.latents.latents_name) vae_info = context.services.model_manager.get_model( - **self.vae.vae.dict(), + **self.vae.vae.dict(), context=context, ) with vae_info as vae: @@ -687,7 +688,7 @@ class ImageToLatentsInvocation(BaseInvocation): #vae_info = context.services.model_manager.get_model(**self.vae.vae.dict()) vae_info = context.services.model_manager.get_model( - **self.vae.vae.dict(), + **self.vae.vae.dict(), context=context, ) image_tensor = image_resized_to_grid_as_tensor(image.convert("RGB")) diff --git a/invokeai/app/invocations/prompt.py b/invokeai/app/invocations/prompt.py index 9af87e1ed4..c4c0c38a63 100644 --- a/invokeai/app/invocations/prompt.py +++ b/invokeai/app/invocations/prompt.py @@ -1,6 +1,8 @@ -from typing import Literal +from os.path import exists +from typing import Literal, Optional -from pydantic.fields import Field +import numpy as np +from pydantic import Field, validator from .baseinvocation import BaseInvocation, BaseInvocationOutput, InvocationContext from dynamicprompts.generators import RandomPromptGenerator, CombinatorialPromptGenerator @@ -55,3 +57,41 @@ class DynamicPromptInvocation(BaseInvocation): prompts = generator.generate(self.prompt, num_images=self.max_prompts) return PromptCollectionOutput(prompt_collection=prompts, count=len(prompts)) + + +class PromptsFromFileInvocation(BaseInvocation): + '''Loads prompts from a text file''' + # fmt: off + type: Literal['prompt_from_file'] = 'prompt_from_file' + + # Inputs + file_path: str = Field(description="Path to prompt text file") + pre_prompt: Optional[str] = Field(description="String to prepend to each prompt") + post_prompt: Optional[str] = Field(description="String to append to each prompt") + start_line: int = Field(default=1, ge=1, description="Line in the file to start start from") + max_prompts: int = Field(default=1, ge=0, description="Max lines to read from file (0=all)") + #fmt: on + + @validator("file_path") + def file_path_exists(cls, v): + if not exists(v): + raise ValueError(FileNotFoundError) + return v + + def promptsFromFile(self, file_path: str, pre_prompt: str, post_prompt: str, start_line: int, max_prompts: int): + prompts = [] + start_line -= 1 + end_line = start_line + max_prompts + if max_prompts <= 0: + end_line = np.iinfo(np.int32).max + with open(file_path) as f: + for i, line in enumerate(f): + if i >= start_line and i < end_line: + prompts.append((pre_prompt or '') + line.strip() + (post_prompt or '')) + if i >= end_line: + break + return prompts + + def invoke(self, context: InvocationContext) -> PromptCollectionOutput: + prompts = self.promptsFromFile(self.file_path, self.pre_prompt, self.post_prompt, self.start_line, self.max_prompts) + return PromptCollectionOutput(prompt_collection=prompts, count=len(prompts)) diff --git a/invokeai/app/invocations/reconstruct.py b/invokeai/app/invocations/reconstruct.py deleted file mode 100644 index 84ace2eefe..0000000000 --- a/invokeai/app/invocations/reconstruct.py +++ /dev/null @@ -1,55 +0,0 @@ -from typing import Literal, Optional - -from pydantic import Field - -from invokeai.app.models.image import ImageCategory, ImageField, ResourceOrigin - -from .baseinvocation import BaseInvocation, InvocationContext, InvocationConfig -from .image import ImageOutput - - -class RestoreFaceInvocation(BaseInvocation): - """Restores faces in an image.""" - - # fmt: off - type: Literal["restore_face"] = "restore_face" - - # Inputs - image: Optional[ImageField] = Field(description="The input image") - strength: float = Field(default=0.75, gt=0, le=1, description="The strength of the restoration" ) - # fmt: on - - # Schema customisation - class Config(InvocationConfig): - schema_extra = { - "ui": { - "tags": ["restoration", "image"], - }, - } - - def invoke(self, context: InvocationContext) -> ImageOutput: - image = context.services.images.get_pil_image(self.image.image_name) - results = context.services.restoration.upscale_and_reconstruct( - image_list=[[image, 0]], - upscale=None, - strength=self.strength, # GFPGAN strength - save_original=False, - image_callback=None, - ) - - # Results are image and seed, unwrap for now - # TODO: can this return multiple results? - image_dto = context.services.images.create( - image=results[0][0], - image_origin=ResourceOrigin.INTERNAL, - image_category=ImageCategory.GENERAL, - node_id=self.id, - session_id=context.graph_execution_state_id, - is_intermediate=self.is_intermediate, - ) - - return ImageOutput( - image=ImageField(image_name=image_dto.image_name), - width=image_dto.width, - height=image_dto.height, - ) diff --git a/invokeai/app/invocations/upscale.py b/invokeai/app/invocations/upscale.py index 15497343ae..9fa208fb31 100644 --- a/invokeai/app/invocations/upscale.py +++ b/invokeai/app/invocations/upscale.py @@ -1,48 +1,112 @@ -# Copyright (c) 2022 Kyle Schouviller (https://github.com/kyle0654) - -from typing import Literal, Optional +# Copyright (c) 2022 Kyle Schouviller (https://github.com/kyle0654) & the InvokeAI Team +from pathlib import Path, PosixPath +from typing import Literal, Union, cast +import cv2 as cv +import numpy as np +from basicsr.archs.rrdbnet_arch import RRDBNet +from PIL import Image from pydantic import Field +from realesrgan import RealESRGANer from invokeai.app.models.image import ImageCategory, ImageField, ResourceOrigin -from .baseinvocation import BaseInvocation, InvocationContext, InvocationConfig + +from .baseinvocation import BaseInvocation, InvocationContext from .image import ImageOutput +# TODO: Populate this from disk? +# TODO: Use model manager to load? +REALESRGAN_MODELS = Literal[ + "RealESRGAN_x4plus.pth", + "RealESRGAN_x4plus_anime_6B.pth", + "ESRGAN_SRx4_DF2KOST_official-ff704c30.pth", +] -class UpscaleInvocation(BaseInvocation): - """Upscales an image.""" - # fmt: off - type: Literal["upscale"] = "upscale" +class RealESRGANInvocation(BaseInvocation): + """Upscales an image using RealESRGAN.""" - # Inputs - image: Optional[ImageField] = Field(description="The input image", default=None) - strength: float = Field(default=0.75, gt=0, le=1, description="The strength") - level: Literal[2, 4] = Field(default=2, description="The upscale level") - # fmt: on - - # Schema customisation - class Config(InvocationConfig): - schema_extra = { - "ui": { - "tags": ["upscaling", "image"], - }, - } + type: Literal["realesrgan"] = "realesrgan" + image: Union[ImageField, None] = Field(default=None, description="The input image") + model_name: REALESRGAN_MODELS = Field( + default="RealESRGAN_x4plus.pth", description="The Real-ESRGAN model to use" + ) def invoke(self, context: InvocationContext) -> ImageOutput: image = context.services.images.get_pil_image(self.image.image_name) - results = context.services.restoration.upscale_and_reconstruct( - image_list=[[image, 0]], - upscale=(self.level, self.strength), - strength=0.0, # GFPGAN strength - save_original=False, - image_callback=None, + models_path = context.services.configuration.models_path + + rrdbnet_model = None + netscale = None + esrgan_model_path = None + + if self.model_name in [ + "RealESRGAN_x4plus.pth", + "ESRGAN_SRx4_DF2KOST_official-ff704c30.pth", + ]: + # x4 RRDBNet model + rrdbnet_model = RRDBNet( + num_in_ch=3, + num_out_ch=3, + num_feat=64, + num_block=23, + num_grow_ch=32, + scale=4, + ) + netscale = 4 + elif self.model_name in ["RealESRGAN_x4plus_anime_6B.pth"]: + # x4 RRDBNet model, 6 blocks + rrdbnet_model = RRDBNet( + num_in_ch=3, + num_out_ch=3, + num_feat=64, + num_block=6, # 6 blocks + num_grow_ch=32, + scale=4, + ) + netscale = 4 + # TODO: add x2 models handling? + # elif self.model_name in ["RealESRGAN_x2plus"]: + # # x2 RRDBNet model + # model = RRDBNet( + # num_in_ch=3, + # num_out_ch=3, + # num_feat=64, + # num_block=23, + # num_grow_ch=32, + # scale=2, + # ) + # model_path = Path() + # netscale = 2 + else: + msg = f"Invalid RealESRGAN model: {self.model_name}" + context.services.logger.error(msg) + raise ValueError(msg) + + esrgan_model_path = Path(f"core/upscaling/realesrgan/{self.model_name}") + + upsampler = RealESRGANer( + scale=netscale, + model_path=str(models_path / esrgan_model_path), + model=rrdbnet_model, + half=False, ) - # Results are image and seed, unwrap for now - # TODO: can this return multiple results? + # prepare image - Real-ESRGAN uses cv2 internally, and cv2 uses BGR vs RGB for PIL + cv_image = cv.cvtColor(np.array(image.convert("RGB")), cv.COLOR_RGB2BGR) + + # We can pass an `outscale` value here, but it just resizes the image by that factor after + # upscaling, so it's kinda pointless for our purposes. If you want something other than 4x + # upscaling, you'll need to add a resize node after this one. + upscaled_image, img_mode = upsampler.enhance(cv_image) + + # back to PIL + pil_image = Image.fromarray( + cv.cvtColor(upscaled_image, cv.COLOR_BGR2RGB) + ).convert("RGBA") + image_dto = context.services.images.create( - image=results[0][0], + image=pil_image, image_origin=ResourceOrigin.INTERNAL, image_category=ImageCategory.GENERAL, node_id=self.id, diff --git a/invokeai/app/services/config.py b/invokeai/app/services/config.py index cebfd61e29..0a70c1dd5d 100644 --- a/invokeai/app/services/config.py +++ b/invokeai/app/services/config.py @@ -271,13 +271,13 @@ class InvokeAISettings(BaseSettings): @classmethod def _excluded(self)->List[str]: - # combination of deprecated parameters and internal ones that shouldn't be exposed + # internal fields that shouldn't be exposed as command line options return ['type','initconf'] @classmethod def _excluded_from_yaml(self)->List[str]: - # combination of deprecated parameters and internal ones that shouldn't be exposed - return ['type','initconf', 'gpu_mem_reserved', 'max_loaded_models', 'version', 'from_file', 'model'] + # combination of deprecated parameters and internal ones that shouldn't be exposed as invokeai.yaml options + return ['type','initconf', 'gpu_mem_reserved', 'max_loaded_models', 'version', 'from_file', 'model', 'restore'] class Config: env_file_encoding = 'utf-8' @@ -366,7 +366,7 @@ setting environment variables INVOKEAI_. log_tokenization : bool = Field(default=False, description="Enable logging of parsed prompt tokens.", category='Features') nsfw_checker : bool = Field(default=True, description="Enable/disable the NSFW checker", category='Features') patchmatch : bool = Field(default=True, description="Enable/disable patchmatch inpaint code", category='Features') - restore : bool = Field(default=True, description="Enable/disable face restoration code", category='Features') + restore : bool = Field(default=True, description="Enable/disable face restoration code (DEPRECATED)", category='DEPRECATED') always_use_cpu : bool = Field(default=False, description="If true, use the CPU for rendering even if a GPU is available.", category='Memory/Performance') free_gpu_mem : bool = Field(default=False, description="If true, purge model from GPU after each generation.", category='Memory/Performance') diff --git a/invokeai/app/services/events.py b/invokeai/app/services/events.py index 6c516c9b74..30d1b5e7a9 100644 --- a/invokeai/app/services/events.py +++ b/invokeai/app/services/events.py @@ -105,8 +105,6 @@ class EventServiceBase: def emit_model_load_started ( self, graph_execution_state_id: str, - node: dict, - source_node_id: str, model_name: str, base_model: BaseModelType, model_type: ModelType, @@ -117,8 +115,6 @@ class EventServiceBase: event_name="model_load_started", payload=dict( graph_execution_state_id=graph_execution_state_id, - node=node, - source_node_id=source_node_id, model_name=model_name, base_model=base_model, model_type=model_type, @@ -129,8 +125,6 @@ class EventServiceBase: def emit_model_load_completed( self, graph_execution_state_id: str, - node: dict, - source_node_id: str, model_name: str, base_model: BaseModelType, model_type: ModelType, @@ -142,12 +136,12 @@ class EventServiceBase: event_name="model_load_completed", payload=dict( graph_execution_state_id=graph_execution_state_id, - node=node, - source_node_id=source_node_id, model_name=model_name, base_model=base_model, model_type=model_type, submodel=submodel, - model_info=model_info, + hash=model_info.hash, + location=model_info.location, + precision=str(model_info.precision), ), ) diff --git a/invokeai/app/services/invocation_services.py b/invokeai/app/services/invocation_services.py index 4e1da3b040..8af17c7643 100644 --- a/invokeai/app/services/invocation_services.py +++ b/invokeai/app/services/invocation_services.py @@ -10,10 +10,9 @@ if TYPE_CHECKING: from invokeai.app.services.model_manager_service import ModelManagerServiceBase from invokeai.app.services.events import EventServiceBase from invokeai.app.services.latent_storage import LatentsStorageBase - from invokeai.app.services.restoration_services import RestorationServices from invokeai.app.services.invocation_queue import InvocationQueueABC from invokeai.app.services.item_storage import ItemStorageABC - from invokeai.app.services.config import InvokeAISettings + from invokeai.app.services.config import InvokeAIAppConfig from invokeai.app.services.graph import GraphExecutionState, LibraryGraph from invokeai.app.services.invoker import InvocationProcessorABC @@ -24,7 +23,7 @@ class InvocationServices: # TODO: Just forward-declared everything due to circular dependencies. Fix structure. board_images: "BoardImagesServiceABC" boards: "BoardServiceABC" - configuration: "InvokeAISettings" + configuration: "InvokeAIAppConfig" events: "EventServiceBase" graph_execution_manager: "ItemStorageABC"["GraphExecutionState"] graph_library: "ItemStorageABC"["LibraryGraph"] @@ -34,13 +33,12 @@ class InvocationServices: model_manager: "ModelManagerServiceBase" processor: "InvocationProcessorABC" queue: "InvocationQueueABC" - restoration: "RestorationServices" def __init__( self, board_images: "BoardImagesServiceABC", boards: "BoardServiceABC", - configuration: "InvokeAISettings", + configuration: "InvokeAIAppConfig", events: "EventServiceBase", graph_execution_manager: "ItemStorageABC"["GraphExecutionState"], graph_library: "ItemStorageABC"["LibraryGraph"], @@ -50,7 +48,6 @@ class InvocationServices: model_manager: "ModelManagerServiceBase", processor: "InvocationProcessorABC", queue: "InvocationQueueABC", - restoration: "RestorationServices", ): self.board_images = board_images self.boards = boards @@ -65,4 +62,3 @@ class InvocationServices: self.model_manager = model_manager self.processor = processor self.queue = queue - self.restoration = restoration diff --git a/invokeai/app/services/model_manager_service.py b/invokeai/app/services/model_manager_service.py index 67db5c9478..37a497aa5d 100644 --- a/invokeai/app/services/model_manager_service.py +++ b/invokeai/app/services/model_manager_service.py @@ -18,6 +18,7 @@ from invokeai.backend.model_management import ( SchedulerPredictionType, ModelMerger, MergeInterpolationMethod, + ModelNotFoundException, ) from invokeai.backend.model_management.model_search import FindModels @@ -145,7 +146,7 @@ class ModelManagerServiceBase(ABC): ) -> AddModelResult: """ Update the named model with a dictionary of attributes. Will fail with a - KeyErrorException if the name does not already exist. + ModelNotFoundException if the name does not already exist. On a successful update, the config will be changed in memory. Will fail with an assertion error if provided attributes are incorrect or @@ -338,7 +339,6 @@ class ModelManagerService(ModelManagerServiceBase): base_model: BaseModelType, model_type: ModelType, submodel: Optional[SubModelType] = None, - node: Optional[BaseInvocation] = None, context: Optional[InvocationContext] = None, ) -> ModelInfo: """ @@ -346,11 +346,9 @@ class ModelManagerService(ModelManagerServiceBase): part (such as the vae) of a diffusers mode. """ - # if we are called from within a node, then we get to emit - # load start and complete events - if node and context: + # we can emit model loading events if we are executing with access to the invocation context + if context: self._emit_load_event( - node=node, context=context, model_name=model_name, base_model=base_model, @@ -365,9 +363,8 @@ class ModelManagerService(ModelManagerServiceBase): submodel, ) - if node and context: + if context: self._emit_load_event( - node=node, context=context, model_name=model_name, base_model=base_model, @@ -451,14 +448,14 @@ class ModelManagerService(ModelManagerServiceBase): ) -> AddModelResult: """ Update the named model with a dictionary of attributes. Will fail with a - KeyError exception if the name does not already exist. + ModelNotFoundException exception if the name does not already exist. On a successful update, the config will be changed in memory. Will fail with an assertion error if provided attributes are incorrect or the model name is missing. Call commit() to write changes to disk. """ self.logger.debug(f'update model {model_name}') if not self.model_exists(model_name, base_model, model_type): - raise KeyError(f"Unknown model {model_name}") + raise ModelNotFoundException(f"Unknown model {model_name}") return self.add_model(model_name, base_model, model_type, model_attributes, clobber=True) def del_model( @@ -509,23 +506,19 @@ class ModelManagerService(ModelManagerServiceBase): def _emit_load_event( self, - node, context, model_name: str, base_model: BaseModelType, model_type: ModelType, - submodel: SubModelType, + submodel: Optional[SubModelType] = None, model_info: Optional[ModelInfo] = None, ): if context.services.queue.is_canceled(context.graph_execution_state_id): raise CanceledException() - graph_execution_state = context.services.graph_execution_manager.get(context.graph_execution_state_id) - source_node_id = graph_execution_state.prepared_source_mapping[node.id] + if model_info: context.services.events.emit_model_load_completed( graph_execution_state_id=context.graph_execution_state_id, - node=node.dict(), - source_node_id=source_node_id, model_name=model_name, base_model=base_model, model_type=model_type, @@ -535,8 +528,6 @@ class ModelManagerService(ModelManagerServiceBase): else: context.services.events.emit_model_load_started( graph_execution_state_id=context.graph_execution_state_id, - node=node.dict(), - source_node_id=source_node_id, model_name=model_name, base_model=base_model, model_type=model_type, diff --git a/invokeai/app/services/restoration_services.py b/invokeai/app/services/restoration_services.py deleted file mode 100644 index 5ff0195ca5..0000000000 --- a/invokeai/app/services/restoration_services.py +++ /dev/null @@ -1,113 +0,0 @@ -import sys -import traceback -import torch -from typing import types -from ...backend.restoration import Restoration -from ...backend.util import choose_torch_device, CPU_DEVICE, MPS_DEVICE - -# This should be a real base class for postprocessing functions, -# but right now we just instantiate the existing gfpgan, esrgan -# and codeformer functions. -class RestorationServices: - '''Face restoration and upscaling''' - - def __init__(self,args,logger:types.ModuleType): - try: - gfpgan, codeformer, esrgan = None, None, None - if args.restore or args.esrgan: - restoration = Restoration() - # TODO: redo for new model structure - if False and args.restore: - gfpgan, codeformer = restoration.load_face_restore_models( - args.gfpgan_model_path - ) - else: - logger.info("Face restoration disabled") - if False and args.esrgan: - esrgan = restoration.load_esrgan(args.esrgan_bg_tile) - else: - logger.info("Upscaling disabled") - else: - logger.info("Face restoration and upscaling disabled") - except (ModuleNotFoundError, ImportError): - print(traceback.format_exc(), file=sys.stderr) - logger.info("You may need to install the ESRGAN and/or GFPGAN modules") - self.device = torch.device(choose_torch_device()) - self.gfpgan = gfpgan - self.codeformer = codeformer - self.esrgan = esrgan - self.logger = logger - self.logger.info('Face restoration initialized') - - # note that this one method does gfpgan and codepath reconstruction, as well as - # esrgan upscaling - # TO DO: refactor into separate methods - def upscale_and_reconstruct( - self, - image_list, - facetool="gfpgan", - upscale=None, - upscale_denoise_str=0.75, - strength=0.0, - codeformer_fidelity=0.75, - save_original=False, - image_callback=None, - prefix=None, - ): - results = [] - for r in image_list: - image, seed = r - try: - if strength > 0: - if self.gfpgan is not None or self.codeformer is not None: - if facetool == "gfpgan": - if self.gfpgan is None: - self.logger.info( - "GFPGAN not found. Face restoration is disabled." - ) - else: - image = self.gfpgan.process(image, strength, seed) - if facetool == "codeformer": - if self.codeformer is None: - self.logger.info( - "CodeFormer not found. Face restoration is disabled." - ) - else: - cf_device = ( - CPU_DEVICE if self.device == MPS_DEVICE else self.device - ) - image = self.codeformer.process( - image=image, - strength=strength, - device=cf_device, - seed=seed, - fidelity=codeformer_fidelity, - ) - else: - self.logger.info("Face Restoration is disabled.") - if upscale is not None: - if self.esrgan is not None: - if len(upscale) < 2: - upscale.append(0.75) - image = self.esrgan.process( - image, - upscale[1], - seed, - int(upscale[0]), - denoise_str=upscale_denoise_str, - ) - else: - self.logger.info("ESRGAN is disabled. Image not upscaled.") - except Exception as e: - self.logger.info( - f"Error running RealESRGAN or GFPGAN. Your image was not upscaled.\n{e}" - ) - - if image_callback is not None: - image_callback(image, seed, upscaled=True, use_prefix=prefix) - else: - r[0] = image - - results.append([image, seed]) - - return results diff --git a/invokeai/backend/install/invokeai_configure.py b/invokeai/backend/install/invokeai_configure.py index adc985c655..1e5b4984bf 100755 --- a/invokeai/backend/install/invokeai_configure.py +++ b/invokeai/backend/install/invokeai_configure.py @@ -30,8 +30,6 @@ from huggingface_hub import login as hf_hub_login from omegaconf import OmegaConf from tqdm import tqdm from transformers import ( - AutoProcessor, - CLIPSegForImageSegmentation, CLIPTextModel, CLIPTokenizer, AutoFeatureExtractor, @@ -45,7 +43,6 @@ from invokeai.app.services.config import ( from invokeai.backend.util.logging import InvokeAILogger from invokeai.frontend.install.model_install import addModelsForm, process_and_execute from invokeai.frontend.install.widgets import ( - SingleSelectColumns, CenteredButtonPress, IntTitleSlider, set_min_terminal_size, @@ -72,7 +69,6 @@ transformers.logging.set_verbosity_error() config = InvokeAIAppConfig.get_config() Model_dir = "models" -Weights_dir = "ldm/stable-diffusion-v1/" Default_config_file = config.model_conf_path SD_Configs = config.legacy_conf_path @@ -226,64 +222,30 @@ def download_conversion_models(): # --------------------------------------------- def download_realesrgan(): - logger.info("Installing models from RealESRGAN...") - model_url = "https://github.com/xinntao/Real-ESRGAN/releases/download/v0.2.5.0/realesr-general-x4v3.pth" - wdn_model_url = "https://github.com/xinntao/Real-ESRGAN/releases/download/v0.2.5.0/realesr-general-wdn-x4v3.pth" - - model_dest = config.root_path / "models/core/upscaling/realesrgan/realesr-general-x4v3.pth" - wdn_model_dest = config.root_path / "models/core/upscaling/realesrgan/realesr-general-wdn-x4v3.pth" - - download_with_progress_bar(model_url, str(model_dest), "RealESRGAN") - download_with_progress_bar(wdn_model_url, str(wdn_model_dest), "RealESRGANwdn") - - -def download_gfpgan(): - logger.info("Installing GFPGAN models...") - for model in ( - [ - "https://github.com/TencentARC/GFPGAN/releases/download/v1.3.0/GFPGANv1.4.pth", - "./models/core/face_restoration/gfpgan/GFPGANv1.4.pth", - ], - [ - "https://github.com/xinntao/facexlib/releases/download/v0.1.0/detection_Resnet50_Final.pth", - "./models/core/face_restoration/gfpgan/weights/detection_Resnet50_Final.pth", - ], - [ - "https://github.com/xinntao/facexlib/releases/download/v0.2.2/parsing_parsenet.pth", - "./models/core/face_restoration/gfpgan/weights/parsing_parsenet.pth", - ], - ): - model_url, model_dest = model[0], config.root_path / model[1] - download_with_progress_bar(model_url, str(model_dest), "GFPGAN weights") - + logger.info("Installing RealESRGAN models...") + URLs = [ + dict( + url = "https://github.com/xinntao/Real-ESRGAN/releases/download/v0.1.0/RealESRGAN_x4plus.pth", + dest = "core/upscaling/realesrgan/RealESRGAN_x4plus.pth", + description = "RealESRGAN_x4plus.pth", + ), + dict( + url = "https://github.com/xinntao/Real-ESRGAN/releases/download/v0.2.2.4/RealESRGAN_x4plus_anime_6B.pth", + dest = "core/upscaling/realesrgan/RealESRGAN_x4plus_anime_6B.pth", + description = "RealESRGAN_x4plus_anime_6B.pth", + ), + dict( + url= "https://github.com/xinntao/Real-ESRGAN/releases/download/v0.1.1/ESRGAN_SRx4_DF2KOST_official-ff704c30.pth", + dest= "core/upscaling/realesrgan/ESRGAN_SRx4_DF2KOST_official-ff704c30.pth", + description = "ESRGAN_SRx4_DF2KOST_official.pth", + ), + ] + for model in URLs: + download_with_progress_bar(model['url'], config.models_path / model['dest'], model['description']) # --------------------------------------------- -def download_codeformer(): - logger.info("Installing CodeFormer model file...") - model_url = ( - "https://github.com/sczhou/CodeFormer/releases/download/v0.1.0/codeformer.pth" - ) - model_dest = config.root_path / "models/core/face_restoration/codeformer/codeformer.pth" - download_with_progress_bar(model_url, str(model_dest), "CodeFormer") - - -# --------------------------------------------- -def download_clipseg(): - logger.info("Installing clipseg model for text-based masking...") - CLIPSEG_MODEL = "CIDAS/clipseg-rd64-refined" - try: - hf_download_from_pretrained(AutoProcessor, CLIPSEG_MODEL, config.root_path / 'models/core/misc/clipseg') - hf_download_from_pretrained(CLIPSegForImageSegmentation, CLIPSEG_MODEL, config.root_path / 'models/core/misc/clipseg') - except Exception: - logger.info("Error installing clipseg model:") - logger.info(traceback.format_exc()) - - def download_support_models(): download_realesrgan() - download_gfpgan() - download_codeformer() - download_clipseg() download_conversion_models() # ------------------------------------- @@ -666,7 +628,7 @@ def run_console_ui( # The third argument is needed in the Windows 11 environment to # launch a console window running this program. - set_min_terminal_size(MIN_COLS, MIN_LINES,'invokeai-configure') + set_min_terminal_size(MIN_COLS, MIN_LINES) # the install-models application spawns a subprocess to install # models, and will crash unless this is set before running. @@ -743,7 +705,7 @@ def migrate_if_needed(opt: Namespace, root: Path)->bool: old_init_file = root / 'invokeai.init' new_init_file = root / 'invokeai.yaml' old_hub = root / 'models/hub' - migration_needed = old_init_file.exists() and not new_init_file.exists() or old_hub.exists() + migration_needed = (old_init_file.exists() and not new_init_file.exists()) and old_hub.exists() if migration_needed: if opt.yes_to_all or \ @@ -858,9 +820,9 @@ def main(): download_support_models() if opt.skip_sd_weights: - logger.info("\n** SKIPPING DIFFUSION WEIGHTS DOWNLOAD PER USER REQUEST **") + logger.warning("SKIPPING DIFFUSION WEIGHTS DOWNLOAD PER USER REQUEST") elif models_to_download: - logger.info("\n** DOWNLOADING DIFFUSION WEIGHTS **") + logger.info("DOWNLOADING DIFFUSION WEIGHTS") process_and_execute(opt, models_to_download) postscript(errors=errors) diff --git a/invokeai/backend/install/model_install_backend.py b/invokeai/backend/install/model_install_backend.py index 2e537313ac..fb44c38e67 100644 --- a/invokeai/backend/install/model_install_backend.py +++ b/invokeai/backend/install/model_install_backend.py @@ -117,6 +117,7 @@ class ModelInstall(object): # supplement with entries in models.yaml installed_models = self.mgr.list_models() + for md in installed_models: base = md['base_model'] model_type = md['model_type'] @@ -134,6 +135,12 @@ class ModelInstall(object): ) return {x : model_dict[x] for x in sorted(model_dict.keys(),key=lambda y: model_dict[y].name.lower())} + def list_models(self, model_type): + installed = self.mgr.list_models(model_type=model_type) + print(f'Installed models of type `{model_type}`:') + for i in installed: + print(f"{i['model_name']}\t{i['base_model']}\t{i['path']}") + def starter_models(self)->Set[str]: models = set() for key, value in self.datasets.items(): @@ -205,7 +212,7 @@ class ModelInstall(object): {'config.json','model_index.json','learned_embeds.bin','pytorch_lora_weights.bin'} ] ): - models_installed.update(self._install_path(path)) + models_installed.update({str(model_path_id_or_url): self._install_path(path)}) # recursive scan elif path.is_dir(): diff --git a/invokeai/backend/model_management/__init__.py b/invokeai/backend/model_management/__init__.py index e31085acef..086a8721a1 100644 --- a/invokeai/backend/model_management/__init__.py +++ b/invokeai/backend/model_management/__init__.py @@ -3,6 +3,6 @@ Initialization file for invokeai.backend.model_management """ from .model_manager import ModelManager, ModelInfo, AddModelResult, SchedulerPredictionType from .model_cache import ModelCache -from .models import BaseModelType, ModelType, SubModelType, ModelVariantType +from .models import BaseModelType, ModelType, SubModelType, ModelVariantType, ModelNotFoundException from .model_merge import ModelMerger, MergeInterpolationMethod diff --git a/invokeai/backend/model_management/model_manager.py b/invokeai/backend/model_management/model_manager.py index 55f6de9b5b..30eecbd26f 100644 --- a/invokeai/backend/model_management/model_manager.py +++ b/invokeai/backend/model_management/model_manager.py @@ -552,7 +552,7 @@ class ModelManager(object): model_config = self.models.get(model_key) if not model_config: self.logger.error(f'Unknown model {model_name}') - raise KeyError(f'Unknown model {model_name}') + raise ModelNotFoundException(f'Unknown model {model_name}') cur_model_name, cur_base_model, cur_model_type = self.parse_key(model_key) if base_model is not None and cur_base_model != base_model: @@ -568,6 +568,9 @@ class ModelManager(object): model_type=cur_model_type, ) + # expose paths as absolute to help web UI + if path := model_dict.get('path'): + model_dict['path'] = str(self.app_config.root_path / path) models.append(model_dict) return models @@ -596,7 +599,7 @@ class ModelManager(object): model_cfg = self.models.pop(model_key, None) if model_cfg is None: - raise KeyError(f"Unknown model {model_key}") + raise ModelNotFoundException(f"Unknown model {model_key}") # note: it not garantie to release memory(model can has other references) cache_ids = self.cache_keys.pop(model_key, []) @@ -635,6 +638,10 @@ class ModelManager(object): The returned dict has the same format as the dict returned by model_info(). """ + # relativize paths as they go in - this makes it easier to move the root directory around + if path := model_attributes.get('path'): + if Path(path).is_relative_to(self.app_config.root_path): + model_attributes['path'] = str(Path(path).relative_to(self.app_config.root_path)) model_class = MODEL_CLASSES[base_model][model_type] model_config = model_class.create_config(**model_attributes) @@ -689,7 +696,7 @@ class ModelManager(object): model_key = self.create_key(model_name, base_model, model_type) model_cfg = self.models.get(model_key, None) if not model_cfg: - raise KeyError(f"Unknown model: {model_key}") + raise ModelNotFoundException(f"Unknown model: {model_key}") old_path = self.app_config.root_path / model_cfg.path new_name = new_name or model_name @@ -700,7 +707,7 @@ class ModelManager(object): # if this is a model file/directory that we manage ourselves, we need to move it if old_path.is_relative_to(self.app_config.models_path): - new_path = self.app_config.root_path / 'models' / new_base.value / model_type.value / new_name + new_path = self.app_config.root_path / 'models' / BaseModelType(new_base).value / ModelType(model_type).value / new_name move(old_path, new_path) model_cfg.path = str(new_path.relative_to(self.app_config.root_path)) @@ -908,7 +915,6 @@ class ModelManager(object): from invokeai.backend.install.model_install_backend import ModelInstall from invokeai.frontend.install.model_install import ask_user_for_prediction_type - class ScanAndImport(ModelSearch): def __init__(self, directories, logger, ignore: Set[Path], installer: ModelInstall): super().__init__(directories, logger) @@ -965,7 +971,7 @@ class ModelManager(object): that model. May return the following exceptions: - - KeyError - one or more of the items to import is not a valid path, repo_id or URL + - ModelNotFoundException - one or more of the items to import is not a valid path, repo_id or URL - ValueError - a corresponding model already exists ''' # avoid circular import here diff --git a/invokeai/backend/model_management/model_probe.py b/invokeai/backend/model_management/model_probe.py index 094992ddda..c8e33db393 100644 --- a/invokeai/backend/model_management/model_probe.py +++ b/invokeai/backend/model_management/model_probe.py @@ -12,6 +12,7 @@ from picklescan.scanner import scan_file_path from .models import ( BaseModelType, ModelType, ModelVariantType, SchedulerPredictionType, SilenceWarnings, + InvalidModelException ) from .models.base import read_checkpoint_meta @@ -61,7 +62,7 @@ class ModelProbe(object): elif isinstance(model,(dict,ModelMixin,ConfigMixin)): return cls.probe(model_path=None, model=model, prediction_type_helper=prediction_type_helper) else: - raise ValueError("model parameter {model} is neither a Path, nor a model") + raise InvalidModelException("model parameter {model} is neither a Path, nor a model") @classmethod def probe(cls, @@ -141,7 +142,7 @@ class ModelProbe(object): if len(ckpt) < 10 and all(isinstance(v, torch.Tensor) for v in ckpt.values()): return ModelType.TextualInversion - raise ValueError(f"Unable to determine model type for {model_path}") + raise InvalidModelException(f"Unable to determine model type for {model_path}") @classmethod def get_model_type_from_folder(cls, folder_path: Path, model: ModelMixin)->ModelType: @@ -171,7 +172,7 @@ class ModelProbe(object): return type # give up - raise ValueError(f"Unable to determine model type for {folder_path}") + raise InvalidModelException(f"Unable to determine model type for {folder_path}") @classmethod def _scan_and_load_checkpoint(cls,model_path: Path)->dict: @@ -240,7 +241,7 @@ class CheckpointProbeBase(ProbeBase): elif in_channels == 4: return ModelVariantType.Normal else: - raise ValueError(f"Cannot determine variant type (in_channels={in_channels}) at {self.checkpoint_path}") + raise InvalidModelException(f"Cannot determine variant type (in_channels={in_channels}) at {self.checkpoint_path}") class PipelineCheckpointProbe(CheckpointProbeBase): def get_base_type(self)->BaseModelType: @@ -254,7 +255,7 @@ class PipelineCheckpointProbe(CheckpointProbeBase): # TODO: Verify that this is correct! Need an XL checkpoint file for this. if key_name in state_dict and state_dict[key_name].shape[-1] == 2048: return BaseModelType.StableDiffusionXL - raise ValueError("Cannot determine base type") + raise InvalidModelException("Cannot determine base type") def get_scheduler_prediction_type(self)->SchedulerPredictionType: type = self.get_base_type() @@ -335,7 +336,7 @@ class ControlNetCheckpointProbe(CheckpointProbeBase): return BaseModelType.StableDiffusion2 elif self.checkpoint_path and self.helper: return self.helper(self.checkpoint_path) - raise ValueError("Unable to determine base type for {self.checkpoint_path}") + raise InvalidModelException("Unable to determine base type for {self.checkpoint_path}") ######################################################## # classes for probing folders @@ -371,7 +372,7 @@ class PipelineFolderProbe(FolderProbeBase): elif unet_conf['cross_attention_dim'] == 2048: return BaseModelType.StableDiffusionXL else: - raise ValueError(f'Unknown base model for {self.folder_path}') + raise InvalidModelException(f'Unknown base model for {self.folder_path}') def get_scheduler_prediction_type(self)->SchedulerPredictionType: if self.model: @@ -428,7 +429,7 @@ class ControlNetFolderProbe(FolderProbeBase): def get_base_type(self)->BaseModelType: config_file = self.folder_path / 'config.json' if not config_file.exists(): - raise ValueError(f"Cannot determine base type for {self.folder_path}") + raise InvalidModelException(f"Cannot determine base type for {self.folder_path}") with open(config_file,'r') as file: config = json.load(file) # no obvious way to distinguish between sd2-base and sd2-768 @@ -445,7 +446,7 @@ class LoRAFolderProbe(FolderProbeBase): model_file = base_file break if not model_file: - raise ValueError('Unknown LoRA format encountered') + raise InvalidModelException('Unknown LoRA format encountered') return LoRACheckpointProbe(model_file,None).get_base_type() ############## register probe classes ###### diff --git a/invokeai/backend/model_management/models/textual_inversion.py b/invokeai/backend/model_management/models/textual_inversion.py index 9cd62bb417..eea0e85245 100644 --- a/invokeai/backend/model_management/models/textual_inversion.py +++ b/invokeai/backend/model_management/models/textual_inversion.py @@ -68,7 +68,7 @@ class TextualInversionModel(ModelBase): return None # diffusers-ti if os.path.isfile(path): - if any([path.endswith(f".{ext}") for ext in ["safetensors", "ckpt", "pt"]]): + if any([path.endswith(f".{ext}") for ext in ["safetensors", "ckpt", "pt", "bin"]]): return None raise InvalidModelException(f"Not a valid model: {path}") diff --git a/invokeai/backend/model_management/models/vae.py b/invokeai/backend/model_management/models/vae.py index 2a5b7cff24..f740615509 100644 --- a/invokeai/backend/model_management/models/vae.py +++ b/invokeai/backend/model_management/models/vae.py @@ -16,6 +16,7 @@ from .base import ( calc_model_size_by_data, classproperty, InvalidModelException, + ModelNotFoundException, ) from invokeai.app.services.config import InvokeAIAppConfig from diffusers.utils import is_safetensors_available diff --git a/invokeai/backend/restoration/__init__.py b/invokeai/backend/restoration/__init__.py deleted file mode 100644 index 165ef080b3..0000000000 --- a/invokeai/backend/restoration/__init__.py +++ /dev/null @@ -1,4 +0,0 @@ -""" -Initialization file for the invokeai.backend.restoration package -""" -from .base import Restoration diff --git a/invokeai/backend/restoration/base.py b/invokeai/backend/restoration/base.py deleted file mode 100644 index 956f99cf16..0000000000 --- a/invokeai/backend/restoration/base.py +++ /dev/null @@ -1,45 +0,0 @@ -import invokeai.backend.util.logging as logger - -class Restoration: - def __init__(self) -> None: - pass - - def load_face_restore_models( - self, gfpgan_model_path="./models/core/face_restoration/gfpgan/GFPGANv1.4.pth" - ): - # Load GFPGAN - gfpgan = self.load_gfpgan(gfpgan_model_path) - if gfpgan.gfpgan_model_exists: - logger.info("GFPGAN Initialized") - else: - logger.info("GFPGAN Disabled") - gfpgan = None - - # Load CodeFormer - codeformer = self.load_codeformer() - if codeformer.codeformer_model_exists: - logger.info("CodeFormer Initialized") - else: - logger.info("CodeFormer Disabled") - codeformer = None - - return gfpgan, codeformer - - # Face Restore Models - def load_gfpgan(self, gfpgan_model_path): - from .gfpgan import GFPGAN - - return GFPGAN(gfpgan_model_path) - - def load_codeformer(self): - from .codeformer import CodeFormerRestoration - - return CodeFormerRestoration() - - # Upscale Models - def load_esrgan(self, esrgan_bg_tile=400): - from .realesrgan import ESRGAN - - esrgan = ESRGAN(esrgan_bg_tile) - logger.info("ESRGAN Initialized") - return esrgan diff --git a/invokeai/backend/restoration/codeformer.py b/invokeai/backend/restoration/codeformer.py deleted file mode 100644 index 92fcd06e0b..0000000000 --- a/invokeai/backend/restoration/codeformer.py +++ /dev/null @@ -1,120 +0,0 @@ -import os -import sys -import warnings - -import numpy as np -import torch - -import invokeai.backend.util.logging as logger -from invokeai.app.services.config import InvokeAIAppConfig - -pretrained_model_url = ( - "https://github.com/sczhou/CodeFormer/releases/download/v0.1.0/codeformer.pth" -) - - -class CodeFormerRestoration: - def __init__( - self, codeformer_dir="./models/core/face_restoration/codeformer", codeformer_model_path="codeformer.pth" - ) -> None: - - self.globals = InvokeAIAppConfig.get_config() - codeformer_dir = self.globals.root_dir / codeformer_dir - self.model_path = codeformer_dir / codeformer_model_path - self.codeformer_model_exists = self.model_path.exists() - - if not self.codeformer_model_exists: - logger.error(f"NOT FOUND: CodeFormer model not found at {self.model_path}") - sys.path.append(os.path.abspath(codeformer_dir)) - - def process(self, image, strength, device, seed=None, fidelity=0.75): - if seed is not None: - logger.info(f"CodeFormer - Restoring Faces for image seed:{seed}") - with warnings.catch_warnings(): - warnings.filterwarnings("ignore", category=DeprecationWarning) - warnings.filterwarnings("ignore", category=UserWarning) - - from basicsr.utils import img2tensor, tensor2img - from basicsr.utils.download_util import load_file_from_url - from facexlib.utils.face_restoration_helper import FaceRestoreHelper - from PIL import Image - from torchvision.transforms.functional import normalize - - from .codeformer_arch import CodeFormer - - cf_class = CodeFormer - - cf = cf_class( - dim_embd=512, - codebook_size=1024, - n_head=8, - n_layers=9, - connect_list=["32", "64", "128", "256"], - ).to(device) - - # note that this file should already be downloaded and cached at - # this point - checkpoint_path = load_file_from_url( - url=pretrained_model_url, - model_dir=os.path.abspath(os.path.dirname(self.model_path)), - progress=True, - ) - checkpoint = torch.load(checkpoint_path)["params_ema"] - cf.load_state_dict(checkpoint) - cf.eval() - - image = image.convert("RGB") - # Codeformer expects a BGR np array; make array and flip channels - bgr_image_array = np.array(image, dtype=np.uint8)[..., ::-1] - - face_helper = FaceRestoreHelper( - upscale_factor=1, - use_parse=True, - device=device, - model_rootpath = self.globals.model_path / 'core/face_restoration/gfpgan/weights' - ) - face_helper.clean_all() - face_helper.read_image(bgr_image_array) - face_helper.get_face_landmarks_5(resize=640, eye_dist_threshold=5) - face_helper.align_warp_face() - - for idx, cropped_face in enumerate(face_helper.cropped_faces): - cropped_face_t = img2tensor( - cropped_face / 255.0, bgr2rgb=True, float32=True - ) - normalize( - cropped_face_t, (0.5, 0.5, 0.5), (0.5, 0.5, 0.5), inplace=True - ) - cropped_face_t = cropped_face_t.unsqueeze(0).to(device) - - try: - with torch.no_grad(): - output = cf(cropped_face_t, w=fidelity, adain=True)[0] - restored_face = tensor2img( - output.squeeze(0), rgb2bgr=True, min_max=(-1, 1) - ) - del output - torch.cuda.empty_cache() - except RuntimeError as error: - logger.error(f"Failed inference for CodeFormer: {error}.") - restored_face = cropped_face - - restored_face = restored_face.astype("uint8") - face_helper.add_restored_face(restored_face) - - face_helper.get_inverse_affine(None) - - restored_img = face_helper.paste_faces_to_input_image() - - # Flip the channels back to RGB - res = Image.fromarray(restored_img[..., ::-1]) - - if strength < 1.0: - # Resize the image to the new image if the sizes have changed - if restored_img.size != image.size: - image = image.resize(res.size) - res = Image.blend(image, res, strength) - - cf = None - - return res diff --git a/invokeai/backend/restoration/codeformer_arch.py b/invokeai/backend/restoration/codeformer_arch.py deleted file mode 100644 index 0f6b881020..0000000000 --- a/invokeai/backend/restoration/codeformer_arch.py +++ /dev/null @@ -1,325 +0,0 @@ -import math -from typing import List, Optional - -import numpy as np -import torch -import torch.nn.functional as F -from basicsr.utils import get_root_logger -from basicsr.utils.registry import ARCH_REGISTRY -from torch import Tensor, nn - -from .vqgan_arch import * - - -def calc_mean_std(feat, eps=1e-5): - """Calculate mean and std for adaptive_instance_normalization. - - Args: - feat (Tensor): 4D tensor. - eps (float): A small value added to the variance to avoid - divide-by-zero. Default: 1e-5. - """ - size = feat.size() - assert len(size) == 4, "The input feature should be 4D tensor." - b, c = size[:2] - feat_var = feat.view(b, c, -1).var(dim=2) + eps - feat_std = feat_var.sqrt().view(b, c, 1, 1) - feat_mean = feat.view(b, c, -1).mean(dim=2).view(b, c, 1, 1) - return feat_mean, feat_std - - -def adaptive_instance_normalization(content_feat, style_feat): - """Adaptive instance normalization. - - Adjust the reference features to have the similar color and illuminations - as those in the degradate features. - - Args: - content_feat (Tensor): The reference feature. - style_feat (Tensor): The degradate features. - """ - size = content_feat.size() - style_mean, style_std = calc_mean_std(style_feat) - content_mean, content_std = calc_mean_std(content_feat) - normalized_feat = (content_feat - content_mean.expand(size)) / content_std.expand( - size - ) - return normalized_feat * style_std.expand(size) + style_mean.expand(size) - - -class PositionEmbeddingSine(nn.Module): - """ - This is a more standard version of the position embedding, very similar to the one - used by the Attention is all you need paper, generalized to work on images. - """ - - def __init__( - self, num_pos_feats=64, temperature=10000, normalize=False, scale=None - ): - super().__init__() - self.num_pos_feats = num_pos_feats - self.temperature = temperature - self.normalize = normalize - if scale is not None and normalize is False: - raise ValueError("normalize should be True if scale is passed") - if scale is None: - scale = 2 * math.pi - self.scale = scale - - def forward(self, x, mask=None): - if mask is None: - mask = torch.zeros( - (x.size(0), x.size(2), x.size(3)), device=x.device, dtype=torch.bool - ) - not_mask = ~mask - y_embed = not_mask.cumsum(1, dtype=torch.float32) - x_embed = not_mask.cumsum(2, dtype=torch.float32) - if self.normalize: - eps = 1e-6 - y_embed = y_embed / (y_embed[:, -1:, :] + eps) * self.scale - x_embed = x_embed / (x_embed[:, :, -1:] + eps) * self.scale - - dim_t = torch.arange(self.num_pos_feats, dtype=torch.float32, device=x.device) - dim_t = self.temperature ** (2 * (dim_t // 2) / self.num_pos_feats) - - pos_x = x_embed[:, :, :, None] / dim_t - pos_y = y_embed[:, :, :, None] / dim_t - pos_x = torch.stack( - (pos_x[:, :, :, 0::2].sin(), pos_x[:, :, :, 1::2].cos()), dim=4 - ).flatten(3) - pos_y = torch.stack( - (pos_y[:, :, :, 0::2].sin(), pos_y[:, :, :, 1::2].cos()), dim=4 - ).flatten(3) - pos = torch.cat((pos_y, pos_x), dim=3).permute(0, 3, 1, 2) - return pos - - -def _get_activation_fn(activation): - """Return an activation function given a string""" - if activation == "relu": - return F.relu - if activation == "gelu": - return F.gelu - if activation == "glu": - return F.glu - raise RuntimeError(f"activation should be relu/gelu, not {activation}.") - - -class TransformerSALayer(nn.Module): - def __init__( - self, embed_dim, nhead=8, dim_mlp=2048, dropout=0.0, activation="gelu" - ): - super().__init__() - self.self_attn = nn.MultiheadAttention(embed_dim, nhead, dropout=dropout) - # Implementation of Feedforward model - MLP - self.linear1 = nn.Linear(embed_dim, dim_mlp) - self.dropout = nn.Dropout(dropout) - self.linear2 = nn.Linear(dim_mlp, embed_dim) - - self.norm1 = nn.LayerNorm(embed_dim) - self.norm2 = nn.LayerNorm(embed_dim) - self.dropout1 = nn.Dropout(dropout) - self.dropout2 = nn.Dropout(dropout) - - self.activation = _get_activation_fn(activation) - - def with_pos_embed(self, tensor, pos: Optional[Tensor]): - return tensor if pos is None else tensor + pos - - def forward( - self, - tgt, - tgt_mask: Optional[Tensor] = None, - tgt_key_padding_mask: Optional[Tensor] = None, - query_pos: Optional[Tensor] = None, - ): - # self attention - tgt2 = self.norm1(tgt) - q = k = self.with_pos_embed(tgt2, query_pos) - tgt2 = self.self_attn( - q, k, value=tgt2, attn_mask=tgt_mask, key_padding_mask=tgt_key_padding_mask - )[0] - tgt = tgt + self.dropout1(tgt2) - - # ffn - tgt2 = self.norm2(tgt) - tgt2 = self.linear2(self.dropout(self.activation(self.linear1(tgt2)))) - tgt = tgt + self.dropout2(tgt2) - return tgt - - -class Fuse_sft_block(nn.Module): - def __init__(self, in_ch, out_ch): - super().__init__() - self.encode_enc = ResBlock(2 * in_ch, out_ch) - - self.scale = nn.Sequential( - nn.Conv2d(in_ch, out_ch, kernel_size=3, padding=1), - nn.LeakyReLU(0.2, True), - nn.Conv2d(out_ch, out_ch, kernel_size=3, padding=1), - ) - - self.shift = nn.Sequential( - nn.Conv2d(in_ch, out_ch, kernel_size=3, padding=1), - nn.LeakyReLU(0.2, True), - nn.Conv2d(out_ch, out_ch, kernel_size=3, padding=1), - ) - - def forward(self, enc_feat, dec_feat, w=1): - enc_feat = self.encode_enc(torch.cat([enc_feat, dec_feat], dim=1)) - scale = self.scale(enc_feat) - shift = self.shift(enc_feat) - residual = w * (dec_feat * scale + shift) - out = dec_feat + residual - return out - - -@ARCH_REGISTRY.register() -class CodeFormer(VQAutoEncoder): - def __init__( - self, - dim_embd=512, - n_head=8, - n_layers=9, - codebook_size=1024, - latent_size=256, - connect_list=["32", "64", "128", "256"], - fix_modules=["quantize", "generator"], - ): - super(CodeFormer, self).__init__( - 512, 64, [1, 2, 2, 4, 4, 8], "nearest", 2, [16], codebook_size - ) - - if fix_modules is not None: - for module in fix_modules: - for param in getattr(self, module).parameters(): - param.requires_grad = False - - self.connect_list = connect_list - self.n_layers = n_layers - self.dim_embd = dim_embd - self.dim_mlp = dim_embd * 2 - - self.position_emb = nn.Parameter(torch.zeros(latent_size, self.dim_embd)) - self.feat_emb = nn.Linear(256, self.dim_embd) - - # transformer - self.ft_layers = nn.Sequential( - *[ - TransformerSALayer( - embed_dim=dim_embd, nhead=n_head, dim_mlp=self.dim_mlp, dropout=0.0 - ) - for _ in range(self.n_layers) - ] - ) - - # logits_predict head - self.idx_pred_layer = nn.Sequential( - nn.LayerNorm(dim_embd), nn.Linear(dim_embd, codebook_size, bias=False) - ) - - self.channels = { - "16": 512, - "32": 256, - "64": 256, - "128": 128, - "256": 128, - "512": 64, - } - - # after second residual block for > 16, before attn layer for ==16 - self.fuse_encoder_block = { - "512": 2, - "256": 5, - "128": 8, - "64": 11, - "32": 14, - "16": 18, - } - # after first residual block for > 16, before attn layer for ==16 - self.fuse_generator_block = { - "16": 6, - "32": 9, - "64": 12, - "128": 15, - "256": 18, - "512": 21, - } - - # fuse_convs_dict - self.fuse_convs_dict = nn.ModuleDict() - for f_size in self.connect_list: - in_ch = self.channels[f_size] - self.fuse_convs_dict[f_size] = Fuse_sft_block(in_ch, in_ch) - - def _init_weights(self, module): - if isinstance(module, (nn.Linear, nn.Embedding)): - module.weight.data.normal_(mean=0.0, std=0.02) - if isinstance(module, nn.Linear) and module.bias is not None: - module.bias.data.zero_() - elif isinstance(module, nn.LayerNorm): - module.bias.data.zero_() - module.weight.data.fill_(1.0) - - def forward(self, x, w=0, detach_16=True, code_only=False, adain=False): - # ################### Encoder ##################### - enc_feat_dict = {} - out_list = [self.fuse_encoder_block[f_size] for f_size in self.connect_list] - for i, block in enumerate(self.encoder.blocks): - x = block(x) - if i in out_list: - enc_feat_dict[str(x.shape[-1])] = x.clone() - - lq_feat = x - # ################# Transformer ################### - # quant_feat, codebook_loss, quant_stats = self.quantize(lq_feat) - pos_emb = self.position_emb.unsqueeze(1).repeat(1, x.shape[0], 1) - # BCHW -> BC(HW) -> (HW)BC - feat_emb = self.feat_emb(lq_feat.flatten(2).permute(2, 0, 1)) - query_emb = feat_emb - # Transformer encoder - for layer in self.ft_layers: - query_emb = layer(query_emb, query_pos=pos_emb) - - # output logits - logits = self.idx_pred_layer(query_emb) # (hw)bn - logits = logits.permute(1, 0, 2) # (hw)bn -> b(hw)n - - if code_only: # for training stage II - # logits doesn't need softmax before cross_entropy loss - return logits, lq_feat - - # ################# Quantization ################### - # if self.training: - # quant_feat = torch.einsum('btn,nc->btc', [soft_one_hot, self.quantize.embedding.weight]) - # # b(hw)c -> bc(hw) -> bchw - # quant_feat = quant_feat.permute(0,2,1).view(lq_feat.shape) - # ------------ - soft_one_hot = F.softmax(logits, dim=2) - _, top_idx = torch.topk(soft_one_hot, 1, dim=2) - quant_feat = self.quantize.get_codebook_feat( - top_idx, shape=[x.shape[0], 16, 16, 256] - ) - # preserve gradients - # quant_feat = lq_feat + (quant_feat - lq_feat).detach() - - if detach_16: - quant_feat = quant_feat.detach() # for training stage III - if adain: - quant_feat = adaptive_instance_normalization(quant_feat, lq_feat) - - # ################## Generator #################### - x = quant_feat - fuse_list = [self.fuse_generator_block[f_size] for f_size in self.connect_list] - - for i, block in enumerate(self.generator.blocks): - x = block(x) - if i in fuse_list: # fuse after i-th block - f_size = str(x.shape[-1]) - if w > 0: - x = self.fuse_convs_dict[f_size]( - enc_feat_dict[f_size].detach(), x, w - ) - out = x - # logits doesn't need softmax before cross_entropy loss - return out, logits, lq_feat diff --git a/invokeai/backend/restoration/gfpgan.py b/invokeai/backend/restoration/gfpgan.py deleted file mode 100644 index 927d026c0c..0000000000 --- a/invokeai/backend/restoration/gfpgan.py +++ /dev/null @@ -1,84 +0,0 @@ -import os -import sys -import warnings - -import numpy as np -import torch -from PIL import Image - -import invokeai.backend.util.logging as logger -from invokeai.app.services.config import InvokeAIAppConfig - -class GFPGAN: - def __init__(self, gfpgan_model_path="models/gfpgan/GFPGANv1.4.pth") -> None: - self.globals = InvokeAIAppConfig.get_config() - if not os.path.isabs(gfpgan_model_path): - gfpgan_model_path = self.globals.root_dir / gfpgan_model_path - self.model_path = gfpgan_model_path - self.gfpgan_model_exists = os.path.isfile(self.model_path) - - if not self.gfpgan_model_exists: - logger.error(f"NOT FOUND: GFPGAN model not found at {self.model_path}") - return None - - def model_exists(self): - return os.path.isfile(self.model_path) - - def process(self, image, strength: float, seed: str = None): - if seed is not None: - logger.info(f"GFPGAN - Restoring Faces for image seed:{seed}") - - with warnings.catch_warnings(): - warnings.filterwarnings("ignore", category=DeprecationWarning) - warnings.filterwarnings("ignore", category=UserWarning) - cwd = os.getcwd() - os.chdir(self.globals.root_dir / 'models') - try: - from gfpgan import GFPGANer - - self.gfpgan = GFPGANer( - model_path=self.model_path, - upscale=1, - arch="clean", - channel_multiplier=2, - bg_upsampler=None, - ) - except Exception: - import traceback - - logger.error("Error loading GFPGAN:", file=sys.stderr) - print(traceback.format_exc(), file=sys.stderr) - os.chdir(cwd) - - if self.gfpgan is None: - logger.warning("WARNING: GFPGAN not initialized.") - logger.warning( - f"Download https://github.com/TencentARC/GFPGAN/releases/download/v1.3.0/GFPGANv1.4.pth to {self.model_path}" - ) - - image = image.convert("RGB") - - # GFPGAN expects a BGR np array; make array and flip channels - bgr_image_array = np.array(image, dtype=np.uint8)[..., ::-1] - - _, _, restored_img = self.gfpgan.enhance( - bgr_image_array, - has_aligned=False, - only_center_face=False, - paste_back=True, - ) - - # Flip the channels back to RGB - res = Image.fromarray(restored_img[..., ::-1]) - - if strength < 1.0: - # Resize the image to the new image if the sizes have changed - if restored_img.size != image.size: - image = image.resize(res.size) - res = Image.blend(image, res, strength) - - if torch.cuda.is_available(): - torch.cuda.empty_cache() - self.gfpgan = None - - return res diff --git a/invokeai/backend/restoration/outcrop.py b/invokeai/backend/restoration/outcrop.py deleted file mode 100644 index 07f76d6bf9..0000000000 --- a/invokeai/backend/restoration/outcrop.py +++ /dev/null @@ -1,118 +0,0 @@ -import math - -from PIL import Image -import invokeai.backend.util.logging as logger - -class Outcrop(object): - def __init__( - self, - image, - generate, # current generate object - ): - self.image = image - self.generate = generate - - def process( - self, - extents: dict, - opt, # current options - orig_opt, # ones originally used to generate the image - image_callback=None, - prefix=None, - ): - # grow and mask the image - extended_image = self._extend_all(extents) - - # switch samplers temporarily - curr_sampler = self.generate.sampler - self.generate.sampler_name = opt.sampler_name - self.generate._set_scheduler() - - def wrapped_callback(img, seed, **kwargs): - preferred_seed = ( - orig_opt.seed - if orig_opt.seed is not None and orig_opt.seed >= 0 - else seed - ) - image_callback(img, preferred_seed, use_prefix=prefix, **kwargs) - - result = self.generate.prompt2image( - opt.prompt, - seed=opt.seed or orig_opt.seed, - sampler=self.generate.sampler, - steps=opt.steps, - cfg_scale=opt.cfg_scale, - ddim_eta=self.generate.ddim_eta, - width=extended_image.width, - height=extended_image.height, - init_img=extended_image, - strength=0.90, - image_callback=wrapped_callback if image_callback else None, - seam_size=opt.seam_size or 96, - seam_blur=opt.seam_blur or 16, - seam_strength=opt.seam_strength or 0.7, - seam_steps=20, - tile_size=32, - color_match=True, - force_outpaint=True, # this just stops the warning about erased regions - ) - - # swap sampler back - self.generate.sampler = curr_sampler - return result - - def _extend_all( - self, - extents: dict, - ) -> Image: - """ - Extend the image in direction ('top','bottom','left','right') by - the indicated value. The image canvas is extended, and the empty - rectangular section will be filled with a blurred copy of the - adjacent image. - """ - image = self.image - for direction in extents: - assert direction in [ - "top", - "left", - "bottom", - "right", - ], 'Direction must be one of "top", "left", "bottom", "right"' - pixels = extents[direction] - # round pixels up to the nearest 64 - pixels = math.ceil(pixels / 64) * 64 - logger.info(f"extending image {direction}ward by {pixels} pixels") - image = self._rotate(image, direction) - image = self._extend(image, pixels) - image = self._rotate(image, direction, reverse=True) - return image - - def _rotate(self, image: Image, direction: str, reverse=False) -> Image: - """ - Rotates image so that the area to extend is always at the top top. - Simplifies logic later. The reverse argument, if true, will undo the - previous transpose. - """ - transposes = { - "right": ["ROTATE_90", "ROTATE_270"], - "bottom": ["ROTATE_180", "ROTATE_180"], - "left": ["ROTATE_270", "ROTATE_90"], - } - if direction not in transposes: - return image - transpose = transposes[direction][1 if reverse else 0] - return image.transpose(Image.Transpose.__dict__[transpose]) - - def _extend(self, image: Image, pixels: int) -> Image: - extended_img = Image.new("RGBA", (image.width, image.height + pixels)) - - extended_img.paste((0, 0, 0), [0, 0, image.width, image.height + pixels]) - extended_img.paste(image, box=(0, pixels)) - - # now make the top part transparent to use as a mask - alpha = extended_img.getchannel("A") - alpha.paste(0, (0, 0, extended_img.width, pixels)) - extended_img.putalpha(alpha) - - return extended_img diff --git a/invokeai/backend/restoration/outpaint.py b/invokeai/backend/restoration/outpaint.py deleted file mode 100644 index 184db10fa3..0000000000 --- a/invokeai/backend/restoration/outpaint.py +++ /dev/null @@ -1,102 +0,0 @@ -import math -import warnings - -from PIL import Image, ImageFilter - - -class Outpaint(object): - def __init__(self, image, generate): - self.image = image - self.generate = generate - - def process(self, opt, old_opt, image_callback=None, prefix=None): - image = self._create_outpaint_image(self.image, opt.out_direction) - - seed = old_opt.seed - prompt = old_opt.prompt - - def wrapped_callback(img, seed, **kwargs): - image_callback(img, seed, use_prefix=prefix, **kwargs) - - return self.generate.prompt2image( - prompt, - seed=seed, - sampler=self.generate.sampler, - steps=opt.steps, - cfg_scale=opt.cfg_scale, - ddim_eta=self.generate.ddim_eta, - width=opt.width, - height=opt.height, - init_img=image, - strength=0.83, - image_callback=wrapped_callback, - prefix=prefix, - ) - - def _create_outpaint_image(self, image, direction_args): - assert len(direction_args) in [ - 1, - 2, - ], "Direction (-D) must have exactly one or two arguments." - - if len(direction_args) == 1: - direction = direction_args[0] - pixels = None - elif len(direction_args) == 2: - direction = direction_args[0] - pixels = int(direction_args[1]) - - assert direction in [ - "top", - "left", - "bottom", - "right", - ], 'Direction (-D) must be one of "top", "left", "bottom", "right"' - - image = image.convert("RGBA") - # we always extend top, but rotate to extend along the requested side - if direction == "left": - image = image.transpose(Image.Transpose.ROTATE_270) - elif direction == "bottom": - image = image.transpose(Image.Transpose.ROTATE_180) - elif direction == "right": - image = image.transpose(Image.Transpose.ROTATE_90) - - pixels = image.height // 2 if pixels is None else int(pixels) - assert ( - 0 < pixels < image.height - ), "Direction (-D) pixels length must be in the range 0 - image.size" - - # the top part of the image is taken from the source image mirrored - # coordinates (0,0) are the upper left corner of an image - top = image.transpose(Image.Transpose.FLIP_TOP_BOTTOM).convert("RGBA") - top = top.crop((0, top.height - pixels, top.width, top.height)) - - # setting all alpha of the top part to 0 - alpha = top.getchannel("A") - alpha.paste(0, (0, 0, top.width, top.height)) - top.putalpha(alpha) - - # taking the bottom from the original image - bottom = image.crop((0, 0, image.width, image.height - pixels)) - - new_img = image.copy() - new_img.paste(top, (0, 0)) - new_img.paste(bottom, (0, pixels)) - - # create a 10% dither in the middle - dither = min(image.height // 10, pixels) - for x in range(0, image.width, 2): - for y in range(pixels - dither, pixels + dither): - (r, g, b, a) = new_img.getpixel((x, y)) - new_img.putpixel((x, y), (r, g, b, 0)) - - # let's rotate back again - if direction == "left": - new_img = new_img.transpose(Image.Transpose.ROTATE_90) - elif direction == "bottom": - new_img = new_img.transpose(Image.Transpose.ROTATE_180) - elif direction == "right": - new_img = new_img.transpose(Image.Transpose.ROTATE_270) - - return new_img diff --git a/invokeai/backend/restoration/realesrgan.py b/invokeai/backend/restoration/realesrgan.py deleted file mode 100644 index 1f29ceadba..0000000000 --- a/invokeai/backend/restoration/realesrgan.py +++ /dev/null @@ -1,104 +0,0 @@ -import warnings - -import numpy as np -import torch -from PIL import Image -from PIL.Image import Image as ImageType - -import invokeai.backend.util.logging as logger -from invokeai.app.services.config import InvokeAIAppConfig -config = InvokeAIAppConfig.get_config() - -class ESRGAN: - def __init__(self, bg_tile_size=400) -> None: - self.bg_tile_size = bg_tile_size - - def load_esrgan_bg_upsampler(self, denoise_str): - if not torch.cuda.is_available(): # CPU or MPS on M1 - use_half_precision = False - else: - use_half_precision = True - - from realesrgan import RealESRGANer - from realesrgan.archs.srvgg_arch import SRVGGNetCompact - - model = SRVGGNetCompact( - num_in_ch=3, - num_out_ch=3, - num_feat=64, - num_conv=32, - upscale=4, - act_type="prelu", - ) - model_path = config.models_path / "core/upscaling/realesrgan/realesr-general-x4v3.pth" - wdn_model_path = config.models_path / "core/upscaling/realesrgan/realesr-general-wdn-x4v3.pth" - scale = 4 - - bg_upsampler = RealESRGANer( - scale=scale, - model_path=[model_path, wdn_model_path], - model=model, - tile=self.bg_tile_size, - dni_weight=[denoise_str, 1 - denoise_str], - tile_pad=10, - pre_pad=0, - half=use_half_precision, - ) - - return bg_upsampler - - def process( - self, - image: ImageType, - strength: float, - seed: str = None, - upsampler_scale: int = 2, - denoise_str: float = 0.75, - ): - with warnings.catch_warnings(): - warnings.filterwarnings("ignore", category=DeprecationWarning) - warnings.filterwarnings("ignore", category=UserWarning) - - try: - upsampler = self.load_esrgan_bg_upsampler(denoise_str) - except Exception: - import sys - import traceback - - logger.error("Error loading Real-ESRGAN:") - print(traceback.format_exc(), file=sys.stderr) - - if upsampler_scale == 0: - logger.warning("Real-ESRGAN: Invalid scaling option. Image not upscaled.") - return image - - if seed is not None: - logger.info( - f"Real-ESRGAN Upscaling seed:{seed}, scale:{upsampler_scale}x, tile:{self.bg_tile_size}, denoise:{denoise_str}" - ) - # ESRGAN outputs images with partial transparency if given RGBA images; convert to RGB - image = image.convert("RGB") - - # REALSRGAN expects a BGR np array; make array and flip channels - bgr_image_array = np.array(image, dtype=np.uint8)[..., ::-1] - - output, _ = upsampler.enhance( - bgr_image_array, - outscale=upsampler_scale, - alpha_upsampler="realesrgan", - ) - - # Flip the channels back to RGB - res = Image.fromarray(output[..., ::-1]) - - if strength < 1.0: - # Resize the image to the new image if the sizes have changed - if output.size != image.size: - image = image.resize(res.size) - res = Image.blend(image, res, strength) - - if torch.cuda.is_available(): - torch.cuda.empty_cache() - upsampler = None - - return res diff --git a/invokeai/backend/restoration/vqgan_arch.py b/invokeai/backend/restoration/vqgan_arch.py deleted file mode 100644 index 96d5f04eee..0000000000 --- a/invokeai/backend/restoration/vqgan_arch.py +++ /dev/null @@ -1,514 +0,0 @@ -""" -VQGAN code, adapted from the original created by the Unleashing Transformers authors: -https://github.com/samb-t/unleashing-transformers/blob/master/models/vqgan.py - -""" -import copy - -import numpy as np -import torch -import torch.nn as nn -import torch.nn.functional as F -from basicsr.utils import get_root_logger -from basicsr.utils.registry import ARCH_REGISTRY - - -def normalize(in_channels): - return torch.nn.GroupNorm( - num_groups=32, num_channels=in_channels, eps=1e-6, affine=True - ) - - -@torch.jit.script -def swish(x): - return x * torch.sigmoid(x) - - -# Define VQVAE classes -class VectorQuantizer(nn.Module): - def __init__(self, codebook_size, emb_dim, beta): - super(VectorQuantizer, self).__init__() - self.codebook_size = codebook_size # number of embeddings - self.emb_dim = emb_dim # dimension of embedding - self.beta = beta # commitment cost used in loss term, beta * ||z_e(x)-sg[e]||^2 - self.embedding = nn.Embedding(self.codebook_size, self.emb_dim) - self.embedding.weight.data.uniform_( - -1.0 / self.codebook_size, 1.0 / self.codebook_size - ) - - def forward(self, z): - # reshape z -> (batch, height, width, channel) and flatten - z = z.permute(0, 2, 3, 1).contiguous() - z_flattened = z.view(-1, self.emb_dim) - - # distances from z to embeddings e_j (z - e)^2 = z^2 + e^2 - 2 e * z - d = ( - (z_flattened**2).sum(dim=1, keepdim=True) - + (self.embedding.weight**2).sum(1) - - 2 * torch.matmul(z_flattened, self.embedding.weight.t()) - ) - - mean_distance = torch.mean(d) - # find closest encodings - # min_encoding_indices = torch.argmin(d, dim=1).unsqueeze(1) - min_encoding_scores, min_encoding_indices = torch.topk( - d, 1, dim=1, largest=False - ) - # [0-1], higher score, higher confidence - min_encoding_scores = torch.exp(-min_encoding_scores / 10) - - min_encodings = torch.zeros( - min_encoding_indices.shape[0], self.codebook_size - ).to(z) - min_encodings.scatter_(1, min_encoding_indices, 1) - - # get quantized latent vectors - z_q = torch.matmul(min_encodings, self.embedding.weight).view(z.shape) - # compute loss for embedding - loss = torch.mean((z_q.detach() - z) ** 2) + self.beta * torch.mean( - (z_q - z.detach()) ** 2 - ) - # preserve gradients - z_q = z + (z_q - z).detach() - - # perplexity - e_mean = torch.mean(min_encodings, dim=0) - perplexity = torch.exp(-torch.sum(e_mean * torch.log(e_mean + 1e-10))) - # reshape back to match original input shape - z_q = z_q.permute(0, 3, 1, 2).contiguous() - - return ( - z_q, - loss, - { - "perplexity": perplexity, - "min_encodings": min_encodings, - "min_encoding_indices": min_encoding_indices, - "min_encoding_scores": min_encoding_scores, - "mean_distance": mean_distance, - }, - ) - - def get_codebook_feat(self, indices, shape): - # input indices: batch*token_num -> (batch*token_num)*1 - # shape: batch, height, width, channel - indices = indices.view(-1, 1) - min_encodings = torch.zeros(indices.shape[0], self.codebook_size).to(indices) - min_encodings.scatter_(1, indices, 1) - # get quantized latent vectors - z_q = torch.matmul(min_encodings.float(), self.embedding.weight) - - if shape is not None: # reshape back to match original input shape - z_q = z_q.view(shape).permute(0, 3, 1, 2).contiguous() - - return z_q - - -class GumbelQuantizer(nn.Module): - def __init__( - self, - codebook_size, - emb_dim, - num_hiddens, - straight_through=False, - kl_weight=5e-4, - temp_init=1.0, - ): - super().__init__() - self.codebook_size = codebook_size # number of embeddings - self.emb_dim = emb_dim # dimension of embedding - self.straight_through = straight_through - self.temperature = temp_init - self.kl_weight = kl_weight - self.proj = nn.Conv2d( - num_hiddens, codebook_size, 1 - ) # projects last encoder layer to quantized logits - self.embed = nn.Embedding(codebook_size, emb_dim) - - def forward(self, z): - hard = self.straight_through if self.training else True - - logits = self.proj(z) - - soft_one_hot = F.gumbel_softmax(logits, tau=self.temperature, dim=1, hard=hard) - - z_q = torch.einsum("b n h w, n d -> b d h w", soft_one_hot, self.embed.weight) - - # + kl divergence to the prior loss - qy = F.softmax(logits, dim=1) - diff = ( - self.kl_weight - * torch.sum(qy * torch.log(qy * self.codebook_size + 1e-10), dim=1).mean() - ) - min_encoding_indices = soft_one_hot.argmax(dim=1) - - return z_q, diff, {"min_encoding_indices": min_encoding_indices} - - -class Downsample(nn.Module): - def __init__(self, in_channels): - super().__init__() - self.conv = torch.nn.Conv2d( - in_channels, in_channels, kernel_size=3, stride=2, padding=0 - ) - - def forward(self, x): - pad = (0, 1, 0, 1) - x = torch.nn.functional.pad(x, pad, mode="constant", value=0) - x = self.conv(x) - return x - - -class Upsample(nn.Module): - def __init__(self, in_channels): - super().__init__() - self.conv = nn.Conv2d( - in_channels, in_channels, kernel_size=3, stride=1, padding=1 - ) - - def forward(self, x): - x = F.interpolate(x, scale_factor=2.0, mode="nearest") - x = self.conv(x) - - return x - - -class ResBlock(nn.Module): - def __init__(self, in_channels, out_channels=None): - super(ResBlock, self).__init__() - self.in_channels = in_channels - self.out_channels = in_channels if out_channels is None else out_channels - self.norm1 = normalize(in_channels) - self.conv1 = nn.Conv2d( - in_channels, out_channels, kernel_size=3, stride=1, padding=1 - ) - self.norm2 = normalize(out_channels) - self.conv2 = nn.Conv2d( - out_channels, out_channels, kernel_size=3, stride=1, padding=1 - ) - if self.in_channels != self.out_channels: - self.conv_out = nn.Conv2d( - in_channels, out_channels, kernel_size=1, stride=1, padding=0 - ) - - def forward(self, x_in): - x = x_in - x = self.norm1(x) - x = swish(x) - x = self.conv1(x) - x = self.norm2(x) - x = swish(x) - x = self.conv2(x) - if self.in_channels != self.out_channels: - x_in = self.conv_out(x_in) - - return x + x_in - - -class AttnBlock(nn.Module): - def __init__(self, in_channels): - super().__init__() - self.in_channels = in_channels - - self.norm = normalize(in_channels) - self.q = torch.nn.Conv2d( - in_channels, in_channels, kernel_size=1, stride=1, padding=0 - ) - self.k = torch.nn.Conv2d( - in_channels, in_channels, kernel_size=1, stride=1, padding=0 - ) - self.v = torch.nn.Conv2d( - in_channels, in_channels, kernel_size=1, stride=1, padding=0 - ) - self.proj_out = torch.nn.Conv2d( - in_channels, in_channels, kernel_size=1, stride=1, padding=0 - ) - - def forward(self, x): - h_ = x - h_ = self.norm(h_) - q = self.q(h_) - k = self.k(h_) - v = self.v(h_) - - # compute attention - b, c, h, w = q.shape - q = q.reshape(b, c, h * w) - q = q.permute(0, 2, 1) - k = k.reshape(b, c, h * w) - w_ = torch.bmm(q, k) - w_ = w_ * (int(c) ** (-0.5)) - w_ = F.softmax(w_, dim=2) - - # attend to values - v = v.reshape(b, c, h * w) - w_ = w_.permute(0, 2, 1) - h_ = torch.bmm(v, w_) - h_ = h_.reshape(b, c, h, w) - - h_ = self.proj_out(h_) - - return x + h_ - - -class Encoder(nn.Module): - def __init__( - self, - in_channels, - nf, - emb_dim, - ch_mult, - num_res_blocks, - resolution, - attn_resolutions, - ): - super().__init__() - self.nf = nf - self.num_resolutions = len(ch_mult) - self.num_res_blocks = num_res_blocks - self.resolution = resolution - self.attn_resolutions = attn_resolutions - - curr_res = self.resolution - in_ch_mult = (1,) + tuple(ch_mult) - - blocks = [] - # initial convultion - blocks.append(nn.Conv2d(in_channels, nf, kernel_size=3, stride=1, padding=1)) - - # residual and downsampling blocks, with attention on smaller res (16x16) - for i in range(self.num_resolutions): - block_in_ch = nf * in_ch_mult[i] - block_out_ch = nf * ch_mult[i] - for _ in range(self.num_res_blocks): - blocks.append(ResBlock(block_in_ch, block_out_ch)) - block_in_ch = block_out_ch - if curr_res in attn_resolutions: - blocks.append(AttnBlock(block_in_ch)) - - if i != self.num_resolutions - 1: - blocks.append(Downsample(block_in_ch)) - curr_res = curr_res // 2 - - # non-local attention block - blocks.append(ResBlock(block_in_ch, block_in_ch)) - blocks.append(AttnBlock(block_in_ch)) - blocks.append(ResBlock(block_in_ch, block_in_ch)) - - # normalise and convert to latent size - blocks.append(normalize(block_in_ch)) - blocks.append( - nn.Conv2d(block_in_ch, emb_dim, kernel_size=3, stride=1, padding=1) - ) - self.blocks = nn.ModuleList(blocks) - - def forward(self, x): - for block in self.blocks: - x = block(x) - - return x - - -class Generator(nn.Module): - def __init__(self, nf, emb_dim, ch_mult, res_blocks, img_size, attn_resolutions): - super().__init__() - self.nf = nf - self.ch_mult = ch_mult - self.num_resolutions = len(self.ch_mult) - self.num_res_blocks = res_blocks - self.resolution = img_size - self.attn_resolutions = attn_resolutions - self.in_channels = emb_dim - self.out_channels = 3 - block_in_ch = self.nf * self.ch_mult[-1] - curr_res = self.resolution // 2 ** (self.num_resolutions - 1) - - blocks = [] - # initial conv - blocks.append( - nn.Conv2d(self.in_channels, block_in_ch, kernel_size=3, stride=1, padding=1) - ) - - # non-local attention block - blocks.append(ResBlock(block_in_ch, block_in_ch)) - blocks.append(AttnBlock(block_in_ch)) - blocks.append(ResBlock(block_in_ch, block_in_ch)) - - for i in reversed(range(self.num_resolutions)): - block_out_ch = self.nf * self.ch_mult[i] - - for _ in range(self.num_res_blocks): - blocks.append(ResBlock(block_in_ch, block_out_ch)) - block_in_ch = block_out_ch - - if curr_res in self.attn_resolutions: - blocks.append(AttnBlock(block_in_ch)) - - if i != 0: - blocks.append(Upsample(block_in_ch)) - curr_res = curr_res * 2 - - blocks.append(normalize(block_in_ch)) - blocks.append( - nn.Conv2d( - block_in_ch, self.out_channels, kernel_size=3, stride=1, padding=1 - ) - ) - - self.blocks = nn.ModuleList(blocks) - - def forward(self, x): - for block in self.blocks: - x = block(x) - - return x - - -@ARCH_REGISTRY.register() -class VQAutoEncoder(nn.Module): - def __init__( - self, - img_size, - nf, - ch_mult, - quantizer="nearest", - res_blocks=2, - attn_resolutions=[16], - codebook_size=1024, - emb_dim=256, - beta=0.25, - gumbel_straight_through=False, - gumbel_kl_weight=1e-8, - model_path=None, - ): - super().__init__() - logger = get_root_logger() - self.in_channels = 3 - self.nf = nf - self.n_blocks = res_blocks - self.codebook_size = codebook_size - self.embed_dim = emb_dim - self.ch_mult = ch_mult - self.resolution = img_size - self.attn_resolutions = attn_resolutions - self.quantizer_type = quantizer - self.encoder = Encoder( - self.in_channels, - self.nf, - self.embed_dim, - self.ch_mult, - self.n_blocks, - self.resolution, - self.attn_resolutions, - ) - if self.quantizer_type == "nearest": - self.beta = beta # 0.25 - self.quantize = VectorQuantizer( - self.codebook_size, self.embed_dim, self.beta - ) - elif self.quantizer_type == "gumbel": - self.gumbel_num_hiddens = emb_dim - self.straight_through = gumbel_straight_through - self.kl_weight = gumbel_kl_weight - self.quantize = GumbelQuantizer( - self.codebook_size, - self.embed_dim, - self.gumbel_num_hiddens, - self.straight_through, - self.kl_weight, - ) - self.generator = Generator( - self.nf, - self.embed_dim, - self.ch_mult, - self.n_blocks, - self.resolution, - self.attn_resolutions, - ) - - if model_path is not None: - chkpt = torch.load(model_path, map_location="cpu") - if "params_ema" in chkpt: - self.load_state_dict( - torch.load(model_path, map_location="cpu")["params_ema"] - ) - logger.info(f"vqgan is loaded from: {model_path} [params_ema]") - elif "params" in chkpt: - self.load_state_dict( - torch.load(model_path, map_location="cpu")["params"] - ) - logger.info(f"vqgan is loaded from: {model_path} [params]") - else: - raise ValueError(f"Wrong params!") - - def forward(self, x): - x = self.encoder(x) - quant, codebook_loss, quant_stats = self.quantize(x) - x = self.generator(quant) - return x, codebook_loss, quant_stats - - -# patch based discriminator -@ARCH_REGISTRY.register() -class VQGANDiscriminator(nn.Module): - def __init__(self, nc=3, ndf=64, n_layers=4, model_path=None): - super().__init__() - - layers = [ - nn.Conv2d(nc, ndf, kernel_size=4, stride=2, padding=1), - nn.LeakyReLU(0.2, True), - ] - ndf_mult = 1 - ndf_mult_prev = 1 - for n in range(1, n_layers): # gradually increase the number of filters - ndf_mult_prev = ndf_mult - ndf_mult = min(2**n, 8) - layers += [ - nn.Conv2d( - ndf * ndf_mult_prev, - ndf * ndf_mult, - kernel_size=4, - stride=2, - padding=1, - bias=False, - ), - nn.BatchNorm2d(ndf * ndf_mult), - nn.LeakyReLU(0.2, True), - ] - - ndf_mult_prev = ndf_mult - ndf_mult = min(2**n_layers, 8) - - layers += [ - nn.Conv2d( - ndf * ndf_mult_prev, - ndf * ndf_mult, - kernel_size=4, - stride=1, - padding=1, - bias=False, - ), - nn.BatchNorm2d(ndf * ndf_mult), - nn.LeakyReLU(0.2, True), - ] - - layers += [ - nn.Conv2d(ndf * ndf_mult, 1, kernel_size=4, stride=1, padding=1) - ] # output 1 channel prediction map - self.main = nn.Sequential(*layers) - - if model_path is not None: - chkpt = torch.load(model_path, map_location="cpu") - if "params_d" in chkpt: - self.load_state_dict( - torch.load(model_path, map_location="cpu")["params_d"] - ) - elif "params" in chkpt: - self.load_state_dict( - torch.load(model_path, map_location="cpu")["params"] - ) - else: - raise ValueError(f"Wrong params!") - - def forward(self, x): - return self.main(x) diff --git a/invokeai/backend/stable_diffusion/diffusers_pipeline.py b/invokeai/backend/stable_diffusion/diffusers_pipeline.py index 1d701b21fd..228fbd0585 100644 --- a/invokeai/backend/stable_diffusion/diffusers_pipeline.py +++ b/invokeai/backend/stable_diffusion/diffusers_pipeline.py @@ -221,7 +221,7 @@ class ControlNetData: control_mode: str = Field(default="balanced") -@dataclass(frozen=True) +@dataclass class ConditioningData: unconditioned_embeddings: torch.Tensor text_embeddings: torch.Tensor @@ -422,7 +422,6 @@ class StableDiffusionGeneratorPipeline(StableDiffusionPipeline): noise: torch.Tensor, callback: Callable[[PipelineIntermediateState], None] = None, run_id=None, - **kwargs, ) -> InvokeAIStableDiffusionPipelineOutput: r""" Function invoked when calling the pipeline for generation. @@ -443,7 +442,6 @@ class StableDiffusionGeneratorPipeline(StableDiffusionPipeline): noise=noise, run_id=run_id, callback=callback, - **kwargs, ) # https://discuss.huggingface.co/t/memory-usage-by-later-pipeline-stages/23699 torch.cuda.empty_cache() @@ -469,7 +467,6 @@ class StableDiffusionGeneratorPipeline(StableDiffusionPipeline): run_id=None, callback: Callable[[PipelineIntermediateState], None] = None, control_data: List[ControlNetData] = None, - **kwargs, ) -> tuple[torch.Tensor, Optional[AttentionMapSaver]]: if self.scheduler.config.get("cpu_only", False): scheduler_device = torch.device('cpu') @@ -487,11 +484,11 @@ class StableDiffusionGeneratorPipeline(StableDiffusionPipeline): timesteps, conditioning_data, noise=noise, - additional_guidance=additional_guidance, run_id=run_id, - callback=callback, + additional_guidance=additional_guidance, control_data=control_data, - **kwargs, + + callback=callback, ) return result.latents, result.attention_map_saver @@ -505,7 +502,6 @@ class StableDiffusionGeneratorPipeline(StableDiffusionPipeline): run_id: str = None, additional_guidance: List[Callable] = None, control_data: List[ControlNetData] = None, - **kwargs, ): self._adjust_memory_efficient_attention(latents) if run_id is None: @@ -546,7 +542,6 @@ class StableDiffusionGeneratorPipeline(StableDiffusionPipeline): total_step_count=len(timesteps), additional_guidance=additional_guidance, control_data=control_data, - **kwargs, ) latents = step_output.prev_sample @@ -588,7 +583,6 @@ class StableDiffusionGeneratorPipeline(StableDiffusionPipeline): total_step_count: int, additional_guidance: List[Callable] = None, control_data: List[ControlNetData] = None, - **kwargs, ): # invokeai_diffuser has batched timesteps, but diffusers schedulers expect a single value timestep = t[0] @@ -632,9 +626,12 @@ class StableDiffusionGeneratorPipeline(StableDiffusionPipeline): if cfg_injection: # only applying ControlNet to conditional instead of in unconditioned encoder_hidden_states = conditioning_data.text_embeddings + encoder_attention_mask = None else: - encoder_hidden_states = torch.cat([conditioning_data.unconditioned_embeddings, - conditioning_data.text_embeddings]) + encoder_hidden_states, encoder_attention_mask = self.invokeai_diffuser._concat_conditionings_for_batch( + conditioning_data.unconditioned_embeddings, + conditioning_data.text_embeddings, + ) if isinstance(control_datum.weight, list): # if controlnet has multiple weights, use the weight for the current step controlnet_weight = control_datum.weight[step_index] @@ -649,6 +646,7 @@ class StableDiffusionGeneratorPipeline(StableDiffusionPipeline): encoder_hidden_states=encoder_hidden_states, controlnet_cond=control_datum.image_tensor, conditioning_scale=controlnet_weight, # controlnet specific, NOT the guidance scale + encoder_attention_mask=encoder_attention_mask, guess_mode=soft_injection, # this is still called guess_mode in diffusers ControlNetModel return_dict=False, ) diff --git a/invokeai/backend/stable_diffusion/diffusion/shared_invokeai_diffusion.py b/invokeai/backend/stable_diffusion/diffusion/shared_invokeai_diffusion.py index 307e949ef8..f44578cd47 100644 --- a/invokeai/backend/stable_diffusion/diffusion/shared_invokeai_diffusion.py +++ b/invokeai/backend/stable_diffusion/diffusion/shared_invokeai_diffusion.py @@ -237,11 +237,7 @@ class InvokeAIDiffuserComponent: ) return latents - # methods below are called from do_diffusion_step and should be considered private to this class. - - def _apply_standard_conditioning(self, x, sigma, unconditioning, conditioning, **kwargs): - # fast batched path - + def _concat_conditionings_for_batch(self, unconditioning, conditioning): def _pad_conditioning(cond, target_len, encoder_attention_mask): conditioning_attention_mask = torch.ones((cond.shape[0], cond.shape[1]), device=cond.device, dtype=cond.dtype) @@ -266,16 +262,24 @@ class InvokeAIDiffuserComponent: return cond, encoder_attention_mask - x_twice = torch.cat([x] * 2) - sigma_twice = torch.cat([sigma] * 2) - encoder_attention_mask = None if unconditioning.shape[1] != conditioning.shape[1]: max_len = max(unconditioning.shape[1], conditioning.shape[1]) unconditioning, encoder_attention_mask = _pad_conditioning(unconditioning, max_len, encoder_attention_mask) conditioning, encoder_attention_mask = _pad_conditioning(conditioning, max_len, encoder_attention_mask) - both_conditionings = torch.cat([unconditioning, conditioning]) + return torch.cat([unconditioning, conditioning]), encoder_attention_mask + + # methods below are called from do_diffusion_step and should be considered private to this class. + + def _apply_standard_conditioning(self, x, sigma, unconditioning, conditioning, **kwargs): + # fast batched path + x_twice = torch.cat([x] * 2) + sigma_twice = torch.cat([sigma] * 2) + + both_conditionings, encoder_attention_mask = self._concat_conditionings_for_batch( + unconditioning, conditioning + ) both_results = self.model_forward_callback( x_twice, sigma_twice, both_conditionings, encoder_attention_mask=encoder_attention_mask, @@ -293,8 +297,32 @@ class InvokeAIDiffuserComponent: **kwargs, ): # low-memory sequential path - unconditioned_next_x = self.model_forward_callback(x, sigma, unconditioning, **kwargs) - conditioned_next_x = self.model_forward_callback(x, sigma, conditioning, **kwargs) + uncond_down_block, cond_down_block = None, None + down_block_additional_residuals = kwargs.pop("down_block_additional_residuals", None) + if down_block_additional_residuals is not None: + uncond_down_block, cond_down_block = [], [] + for down_block in down_block_additional_residuals: + _uncond_down, _cond_down = down_block.chunk(2) + uncond_down_block.append(_uncond_down) + cond_down_block.append(_cond_down) + + uncond_mid_block, cond_mid_block = None, None + mid_block_additional_residual = kwargs.pop("mid_block_additional_residual", None) + if mid_block_additional_residual is not None: + uncond_mid_block, cond_mid_block = mid_block_additional_residual.chunk(2) + + unconditioned_next_x = self.model_forward_callback( + x, sigma, unconditioning, + down_block_additional_residuals=uncond_down_block, + mid_block_additional_residual=uncond_mid_block, + **kwargs, + ) + conditioned_next_x = self.model_forward_callback( + x, sigma, conditioning, + down_block_additional_residuals=cond_down_block, + mid_block_additional_residual=cond_mid_block, + **kwargs, + ) return unconditioned_next_x, conditioned_next_x # TODO: looks unused @@ -328,6 +356,20 @@ class InvokeAIDiffuserComponent: ): context: Context = self.cross_attention_control_context + uncond_down_block, cond_down_block = None, None + down_block_additional_residuals = kwargs.pop("down_block_additional_residuals", None) + if down_block_additional_residuals is not None: + uncond_down_block, cond_down_block = [], [] + for down_block in down_block_additional_residuals: + _uncond_down, _cond_down = down_block.chunk(2) + uncond_down_block.append(_uncond_down) + cond_down_block.append(_cond_down) + + uncond_mid_block, cond_mid_block = None, None + mid_block_additional_residual = kwargs.pop("mid_block_additional_residual", None) + if mid_block_additional_residual is not None: + uncond_mid_block, cond_mid_block = mid_block_additional_residual.chunk(2) + cross_attn_processor_context = SwapCrossAttnContext( modified_text_embeddings=context.arguments.edited_conditioning, index_map=context.cross_attention_index_map, @@ -340,6 +382,8 @@ class InvokeAIDiffuserComponent: sigma, unconditioning, {"swap_cross_attn_context": cross_attn_processor_context}, + down_block_additional_residuals=uncond_down_block, + mid_block_additional_residual=uncond_mid_block, **kwargs, ) @@ -352,6 +396,8 @@ class InvokeAIDiffuserComponent: sigma, conditioning, {"swap_cross_attn_context": cross_attn_processor_context}, + down_block_additional_residuals=cond_down_block, + mid_block_additional_residual=cond_mid_block, **kwargs, ) return unconditioned_next_x, conditioned_next_x diff --git a/invokeai/backend/util/hotfixes.py b/invokeai/backend/util/hotfixes.py new file mode 100644 index 0000000000..67e46a426f --- /dev/null +++ b/invokeai/backend/util/hotfixes.py @@ -0,0 +1,634 @@ +from typing import Any, Dict, List, Optional, Tuple, Union + +import torch +from torch import nn + +from diffusers.configuration_utils import ConfigMixin, register_to_config +from diffusers.models.attention_processor import AttentionProcessor, AttnProcessor +from diffusers.models.embeddings import TimestepEmbedding, Timesteps +from diffusers.models.modeling_utils import ModelMixin +from diffusers.models.unet_2d_blocks import ( + CrossAttnDownBlock2D, + DownBlock2D, + UNetMidBlock2DCrossAttn, + get_down_block, +) +from diffusers.models.unet_2d_condition import UNet2DConditionModel + +import diffusers +from diffusers.models.controlnet import ControlNetConditioningEmbedding, ControlNetOutput, zero_module + +# Modified ControlNetModel with encoder_attention_mask argument added + +class ControlNetModel(ModelMixin, ConfigMixin): + """ + A ControlNet model. + + Args: + in_channels (`int`, defaults to 4): + The number of channels in the input sample. + flip_sin_to_cos (`bool`, defaults to `True`): + Whether to flip the sin to cos in the time embedding. + freq_shift (`int`, defaults to 0): + The frequency shift to apply to the time embedding. + down_block_types (`tuple[str]`, defaults to `("CrossAttnDownBlock2D", "CrossAttnDownBlock2D", "CrossAttnDownBlock2D", "DownBlock2D")`): + The tuple of downsample blocks to use. + only_cross_attention (`Union[bool, Tuple[bool]]`, defaults to `False`): + block_out_channels (`tuple[int]`, defaults to `(320, 640, 1280, 1280)`): + The tuple of output channels for each block. + layers_per_block (`int`, defaults to 2): + The number of layers per block. + downsample_padding (`int`, defaults to 1): + The padding to use for the downsampling convolution. + mid_block_scale_factor (`float`, defaults to 1): + The scale factor to use for the mid block. + act_fn (`str`, defaults to "silu"): + The activation function to use. + norm_num_groups (`int`, *optional*, defaults to 32): + The number of groups to use for the normalization. If None, normalization and activation layers is skipped + in post-processing. + norm_eps (`float`, defaults to 1e-5): + The epsilon to use for the normalization. + cross_attention_dim (`int`, defaults to 1280): + The dimension of the cross attention features. + attention_head_dim (`Union[int, Tuple[int]]`, defaults to 8): + The dimension of the attention heads. + use_linear_projection (`bool`, defaults to `False`): + class_embed_type (`str`, *optional*, defaults to `None`): + The type of class embedding to use which is ultimately summed with the time embeddings. Choose from None, + `"timestep"`, `"identity"`, `"projection"`, or `"simple_projection"`. + num_class_embeds (`int`, *optional*, defaults to 0): + Input dimension of the learnable embedding matrix to be projected to `time_embed_dim`, when performing + class conditioning with `class_embed_type` equal to `None`. + upcast_attention (`bool`, defaults to `False`): + resnet_time_scale_shift (`str`, defaults to `"default"`): + Time scale shift config for ResNet blocks (see `ResnetBlock2D`). Choose from `default` or `scale_shift`. + projection_class_embeddings_input_dim (`int`, *optional*, defaults to `None`): + The dimension of the `class_labels` input when `class_embed_type="projection"`. Required when + `class_embed_type="projection"`. + controlnet_conditioning_channel_order (`str`, defaults to `"rgb"`): + The channel order of conditional image. Will convert to `rgb` if it's `bgr`. + conditioning_embedding_out_channels (`tuple[int]`, *optional*, defaults to `(16, 32, 96, 256)`): + The tuple of output channel for each block in the `conditioning_embedding` layer. + global_pool_conditions (`bool`, defaults to `False`): + """ + + _supports_gradient_checkpointing = True + + @register_to_config + def __init__( + self, + in_channels: int = 4, + conditioning_channels: int = 3, + flip_sin_to_cos: bool = True, + freq_shift: int = 0, + down_block_types: Tuple[str] = ( + "CrossAttnDownBlock2D", + "CrossAttnDownBlock2D", + "CrossAttnDownBlock2D", + "DownBlock2D", + ), + only_cross_attention: Union[bool, Tuple[bool]] = False, + block_out_channels: Tuple[int] = (320, 640, 1280, 1280), + layers_per_block: int = 2, + downsample_padding: int = 1, + mid_block_scale_factor: float = 1, + act_fn: str = "silu", + norm_num_groups: Optional[int] = 32, + norm_eps: float = 1e-5, + cross_attention_dim: int = 1280, + attention_head_dim: Union[int, Tuple[int]] = 8, + num_attention_heads: Optional[Union[int, Tuple[int]]] = None, + use_linear_projection: bool = False, + class_embed_type: Optional[str] = None, + num_class_embeds: Optional[int] = None, + upcast_attention: bool = False, + resnet_time_scale_shift: str = "default", + projection_class_embeddings_input_dim: Optional[int] = None, + controlnet_conditioning_channel_order: str = "rgb", + conditioning_embedding_out_channels: Optional[Tuple[int]] = (16, 32, 96, 256), + global_pool_conditions: bool = False, + ): + super().__init__() + + # If `num_attention_heads` is not defined (which is the case for most models) + # it will default to `attention_head_dim`. This looks weird upon first reading it and it is. + # The reason for this behavior is to correct for incorrectly named variables that were introduced + # when this library was created. The incorrect naming was only discovered much later in https://github.com/huggingface/diffusers/issues/2011#issuecomment-1547958131 + # Changing `attention_head_dim` to `num_attention_heads` for 40,000+ configurations is too backwards breaking + # which is why we correct for the naming here. + num_attention_heads = num_attention_heads or attention_head_dim + + # Check inputs + if len(block_out_channels) != len(down_block_types): + raise ValueError( + f"Must provide the same number of `block_out_channels` as `down_block_types`. `block_out_channels`: {block_out_channels}. `down_block_types`: {down_block_types}." + ) + + if not isinstance(only_cross_attention, bool) and len(only_cross_attention) != len(down_block_types): + raise ValueError( + f"Must provide the same number of `only_cross_attention` as `down_block_types`. `only_cross_attention`: {only_cross_attention}. `down_block_types`: {down_block_types}." + ) + + if not isinstance(num_attention_heads, int) and len(num_attention_heads) != len(down_block_types): + raise ValueError( + f"Must provide the same number of `num_attention_heads` as `down_block_types`. `num_attention_heads`: {num_attention_heads}. `down_block_types`: {down_block_types}." + ) + + # input + conv_in_kernel = 3 + conv_in_padding = (conv_in_kernel - 1) // 2 + self.conv_in = nn.Conv2d( + in_channels, block_out_channels[0], kernel_size=conv_in_kernel, padding=conv_in_padding + ) + + # time + time_embed_dim = block_out_channels[0] * 4 + + self.time_proj = Timesteps(block_out_channels[0], flip_sin_to_cos, freq_shift) + timestep_input_dim = block_out_channels[0] + + self.time_embedding = TimestepEmbedding( + timestep_input_dim, + time_embed_dim, + act_fn=act_fn, + ) + + # class embedding + if class_embed_type is None and num_class_embeds is not None: + self.class_embedding = nn.Embedding(num_class_embeds, time_embed_dim) + elif class_embed_type == "timestep": + self.class_embedding = TimestepEmbedding(timestep_input_dim, time_embed_dim) + elif class_embed_type == "identity": + self.class_embedding = nn.Identity(time_embed_dim, time_embed_dim) + elif class_embed_type == "projection": + if projection_class_embeddings_input_dim is None: + raise ValueError( + "`class_embed_type`: 'projection' requires `projection_class_embeddings_input_dim` be set" + ) + # The projection `class_embed_type` is the same as the timestep `class_embed_type` except + # 1. the `class_labels` inputs are not first converted to sinusoidal embeddings + # 2. it projects from an arbitrary input dimension. + # + # Note that `TimestepEmbedding` is quite general, being mainly linear layers and activations. + # When used for embedding actual timesteps, the timesteps are first converted to sinusoidal embeddings. + # As a result, `TimestepEmbedding` can be passed arbitrary vectors. + self.class_embedding = TimestepEmbedding(projection_class_embeddings_input_dim, time_embed_dim) + else: + self.class_embedding = None + + # control net conditioning embedding + self.controlnet_cond_embedding = ControlNetConditioningEmbedding( + conditioning_embedding_channels=block_out_channels[0], + block_out_channels=conditioning_embedding_out_channels, + conditioning_channels=conditioning_channels, + ) + + self.down_blocks = nn.ModuleList([]) + self.controlnet_down_blocks = nn.ModuleList([]) + + if isinstance(only_cross_attention, bool): + only_cross_attention = [only_cross_attention] * len(down_block_types) + + if isinstance(attention_head_dim, int): + attention_head_dim = (attention_head_dim,) * len(down_block_types) + + if isinstance(num_attention_heads, int): + num_attention_heads = (num_attention_heads,) * len(down_block_types) + + # down + output_channel = block_out_channels[0] + + controlnet_block = nn.Conv2d(output_channel, output_channel, kernel_size=1) + controlnet_block = zero_module(controlnet_block) + self.controlnet_down_blocks.append(controlnet_block) + + for i, down_block_type in enumerate(down_block_types): + input_channel = output_channel + output_channel = block_out_channels[i] + is_final_block = i == len(block_out_channels) - 1 + + down_block = get_down_block( + down_block_type, + num_layers=layers_per_block, + in_channels=input_channel, + out_channels=output_channel, + temb_channels=time_embed_dim, + add_downsample=not is_final_block, + resnet_eps=norm_eps, + resnet_act_fn=act_fn, + resnet_groups=norm_num_groups, + cross_attention_dim=cross_attention_dim, + num_attention_heads=num_attention_heads[i], + attention_head_dim=attention_head_dim[i] if attention_head_dim[i] is not None else output_channel, + downsample_padding=downsample_padding, + use_linear_projection=use_linear_projection, + only_cross_attention=only_cross_attention[i], + upcast_attention=upcast_attention, + resnet_time_scale_shift=resnet_time_scale_shift, + ) + self.down_blocks.append(down_block) + + for _ in range(layers_per_block): + controlnet_block = nn.Conv2d(output_channel, output_channel, kernel_size=1) + controlnet_block = zero_module(controlnet_block) + self.controlnet_down_blocks.append(controlnet_block) + + if not is_final_block: + controlnet_block = nn.Conv2d(output_channel, output_channel, kernel_size=1) + controlnet_block = zero_module(controlnet_block) + self.controlnet_down_blocks.append(controlnet_block) + + # mid + mid_block_channel = block_out_channels[-1] + + controlnet_block = nn.Conv2d(mid_block_channel, mid_block_channel, kernel_size=1) + controlnet_block = zero_module(controlnet_block) + self.controlnet_mid_block = controlnet_block + + self.mid_block = UNetMidBlock2DCrossAttn( + in_channels=mid_block_channel, + temb_channels=time_embed_dim, + resnet_eps=norm_eps, + resnet_act_fn=act_fn, + output_scale_factor=mid_block_scale_factor, + resnet_time_scale_shift=resnet_time_scale_shift, + cross_attention_dim=cross_attention_dim, + num_attention_heads=num_attention_heads[-1], + resnet_groups=norm_num_groups, + use_linear_projection=use_linear_projection, + upcast_attention=upcast_attention, + ) + + @classmethod + def from_unet( + cls, + unet: UNet2DConditionModel, + controlnet_conditioning_channel_order: str = "rgb", + conditioning_embedding_out_channels: Optional[Tuple[int]] = (16, 32, 96, 256), + load_weights_from_unet: bool = True, + ): + r""" + Instantiate a [`ControlNetModel`] from [`UNet2DConditionModel`]. + + Parameters: + unet (`UNet2DConditionModel`): + The UNet model weights to copy to the [`ControlNetModel`]. All configuration options are also copied + where applicable. + """ + controlnet = cls( + in_channels=unet.config.in_channels, + flip_sin_to_cos=unet.config.flip_sin_to_cos, + freq_shift=unet.config.freq_shift, + down_block_types=unet.config.down_block_types, + only_cross_attention=unet.config.only_cross_attention, + block_out_channels=unet.config.block_out_channels, + layers_per_block=unet.config.layers_per_block, + downsample_padding=unet.config.downsample_padding, + mid_block_scale_factor=unet.config.mid_block_scale_factor, + act_fn=unet.config.act_fn, + norm_num_groups=unet.config.norm_num_groups, + norm_eps=unet.config.norm_eps, + cross_attention_dim=unet.config.cross_attention_dim, + attention_head_dim=unet.config.attention_head_dim, + num_attention_heads=unet.config.num_attention_heads, + use_linear_projection=unet.config.use_linear_projection, + class_embed_type=unet.config.class_embed_type, + num_class_embeds=unet.config.num_class_embeds, + upcast_attention=unet.config.upcast_attention, + resnet_time_scale_shift=unet.config.resnet_time_scale_shift, + projection_class_embeddings_input_dim=unet.config.projection_class_embeddings_input_dim, + controlnet_conditioning_channel_order=controlnet_conditioning_channel_order, + conditioning_embedding_out_channels=conditioning_embedding_out_channels, + ) + + if load_weights_from_unet: + controlnet.conv_in.load_state_dict(unet.conv_in.state_dict()) + controlnet.time_proj.load_state_dict(unet.time_proj.state_dict()) + controlnet.time_embedding.load_state_dict(unet.time_embedding.state_dict()) + + if controlnet.class_embedding: + controlnet.class_embedding.load_state_dict(unet.class_embedding.state_dict()) + + controlnet.down_blocks.load_state_dict(unet.down_blocks.state_dict()) + controlnet.mid_block.load_state_dict(unet.mid_block.state_dict()) + + return controlnet + + @property + # Copied from diffusers.models.unet_2d_condition.UNet2DConditionModel.attn_processors + def attn_processors(self) -> Dict[str, AttentionProcessor]: + r""" + Returns: + `dict` of attention processors: A dictionary containing all attention processors used in the model with + indexed by its weight name. + """ + # set recursively + processors = {} + + def fn_recursive_add_processors(name: str, module: torch.nn.Module, processors: Dict[str, AttentionProcessor]): + if hasattr(module, "set_processor"): + processors[f"{name}.processor"] = module.processor + + for sub_name, child in module.named_children(): + fn_recursive_add_processors(f"{name}.{sub_name}", child, processors) + + return processors + + for name, module in self.named_children(): + fn_recursive_add_processors(name, module, processors) + + return processors + + # Copied from diffusers.models.unet_2d_condition.UNet2DConditionModel.set_attn_processor + def set_attn_processor(self, processor: Union[AttentionProcessor, Dict[str, AttentionProcessor]]): + r""" + Sets the attention processor to use to compute attention. + + Parameters: + processor (`dict` of `AttentionProcessor` or only `AttentionProcessor`): + The instantiated processor class or a dictionary of processor classes that will be set as the processor + for **all** `Attention` layers. + + If `processor` is a dict, the key needs to define the path to the corresponding cross attention + processor. This is strongly recommended when setting trainable attention processors. + + """ + count = len(self.attn_processors.keys()) + + if isinstance(processor, dict) and len(processor) != count: + raise ValueError( + f"A dict of processors was passed, but the number of processors {len(processor)} does not match the" + f" number of attention layers: {count}. Please make sure to pass {count} processor classes." + ) + + def fn_recursive_attn_processor(name: str, module: torch.nn.Module, processor): + if hasattr(module, "set_processor"): + if not isinstance(processor, dict): + module.set_processor(processor) + else: + module.set_processor(processor.pop(f"{name}.processor")) + + for sub_name, child in module.named_children(): + fn_recursive_attn_processor(f"{name}.{sub_name}", child, processor) + + for name, module in self.named_children(): + fn_recursive_attn_processor(name, module, processor) + + # Copied from diffusers.models.unet_2d_condition.UNet2DConditionModel.set_default_attn_processor + def set_default_attn_processor(self): + """ + Disables custom attention processors and sets the default attention implementation. + """ + self.set_attn_processor(AttnProcessor()) + + # Copied from diffusers.models.unet_2d_condition.UNet2DConditionModel.set_attention_slice + def set_attention_slice(self, slice_size): + r""" + Enable sliced attention computation. + + When this option is enabled, the attention module splits the input tensor in slices to compute attention in + several steps. This is useful for saving some memory in exchange for a small decrease in speed. + + Args: + slice_size (`str` or `int` or `list(int)`, *optional*, defaults to `"auto"`): + When `"auto"`, input to the attention heads is halved, so attention is computed in two steps. If + `"max"`, maximum amount of memory is saved by running only one slice at a time. If a number is + provided, uses as many slices as `attention_head_dim // slice_size`. In this case, `attention_head_dim` + must be a multiple of `slice_size`. + """ + sliceable_head_dims = [] + + def fn_recursive_retrieve_sliceable_dims(module: torch.nn.Module): + if hasattr(module, "set_attention_slice"): + sliceable_head_dims.append(module.sliceable_head_dim) + + for child in module.children(): + fn_recursive_retrieve_sliceable_dims(child) + + # retrieve number of attention layers + for module in self.children(): + fn_recursive_retrieve_sliceable_dims(module) + + num_sliceable_layers = len(sliceable_head_dims) + + if slice_size == "auto": + # half the attention head size is usually a good trade-off between + # speed and memory + slice_size = [dim // 2 for dim in sliceable_head_dims] + elif slice_size == "max": + # make smallest slice possible + slice_size = num_sliceable_layers * [1] + + slice_size = num_sliceable_layers * [slice_size] if not isinstance(slice_size, list) else slice_size + + if len(slice_size) != len(sliceable_head_dims): + raise ValueError( + f"You have provided {len(slice_size)}, but {self.config} has {len(sliceable_head_dims)} different" + f" attention layers. Make sure to match `len(slice_size)` to be {len(sliceable_head_dims)}." + ) + + for i in range(len(slice_size)): + size = slice_size[i] + dim = sliceable_head_dims[i] + if size is not None and size > dim: + raise ValueError(f"size {size} has to be smaller or equal to {dim}.") + + # Recursively walk through all the children. + # Any children which exposes the set_attention_slice method + # gets the message + def fn_recursive_set_attention_slice(module: torch.nn.Module, slice_size: List[int]): + if hasattr(module, "set_attention_slice"): + module.set_attention_slice(slice_size.pop()) + + for child in module.children(): + fn_recursive_set_attention_slice(child, slice_size) + + reversed_slice_size = list(reversed(slice_size)) + for module in self.children(): + fn_recursive_set_attention_slice(module, reversed_slice_size) + + def _set_gradient_checkpointing(self, module, value=False): + if isinstance(module, (CrossAttnDownBlock2D, DownBlock2D)): + module.gradient_checkpointing = value + + def forward( + self, + sample: torch.FloatTensor, + timestep: Union[torch.Tensor, float, int], + encoder_hidden_states: torch.Tensor, + controlnet_cond: torch.FloatTensor, + conditioning_scale: float = 1.0, + class_labels: Optional[torch.Tensor] = None, + timestep_cond: Optional[torch.Tensor] = None, + attention_mask: Optional[torch.Tensor] = None, + cross_attention_kwargs: Optional[Dict[str, Any]] = None, + encoder_attention_mask: Optional[torch.Tensor] = None, + guess_mode: bool = False, + return_dict: bool = True, + ) -> Union[ControlNetOutput, Tuple]: + """ + The [`ControlNetModel`] forward method. + + Args: + sample (`torch.FloatTensor`): + The noisy input tensor. + timestep (`Union[torch.Tensor, float, int]`): + The number of timesteps to denoise an input. + encoder_hidden_states (`torch.Tensor`): + The encoder hidden states. + controlnet_cond (`torch.FloatTensor`): + The conditional input tensor of shape `(batch_size, sequence_length, hidden_size)`. + conditioning_scale (`float`, defaults to `1.0`): + The scale factor for ControlNet outputs. + class_labels (`torch.Tensor`, *optional*, defaults to `None`): + Optional class labels for conditioning. Their embeddings will be summed with the timestep embeddings. + timestep_cond (`torch.Tensor`, *optional*, defaults to `None`): + attention_mask (`torch.Tensor`, *optional*, defaults to `None`): + cross_attention_kwargs(`dict[str]`, *optional*, defaults to `None`): + A kwargs dictionary that if specified is passed along to the `AttnProcessor`. + encoder_attention_mask (`torch.Tensor`): + A cross-attention mask of shape `(batch, sequence_length)` is applied to `encoder_hidden_states`. If + `True` the mask is kept, otherwise if `False` it is discarded. Mask will be converted into a bias, + which adds large negative values to the attention scores corresponding to "discard" tokens. + guess_mode (`bool`, defaults to `False`): + In this mode, the ControlNet encoder tries its best to recognize the input content of the input even if + you remove all prompts. A `guidance_scale` between 3.0 and 5.0 is recommended. + return_dict (`bool`, defaults to `True`): + Whether or not to return a [`~models.controlnet.ControlNetOutput`] instead of a plain tuple. + + Returns: + [`~models.controlnet.ControlNetOutput`] **or** `tuple`: + If `return_dict` is `True`, a [`~models.controlnet.ControlNetOutput`] is returned, otherwise a tuple is + returned where the first element is the sample tensor. + """ + # check channel order + channel_order = self.config.controlnet_conditioning_channel_order + + if channel_order == "rgb": + # in rgb order by default + ... + elif channel_order == "bgr": + controlnet_cond = torch.flip(controlnet_cond, dims=[1]) + else: + raise ValueError(f"unknown `controlnet_conditioning_channel_order`: {channel_order}") + + # prepare attention_mask + if attention_mask is not None: + attention_mask = (1 - attention_mask.to(sample.dtype)) * -10000.0 + attention_mask = attention_mask.unsqueeze(1) + + # convert encoder_attention_mask to a bias the same way we do for attention_mask + if encoder_attention_mask is not None: + encoder_attention_mask = (1 - encoder_attention_mask.to(sample.dtype)) * -10000.0 + encoder_attention_mask = encoder_attention_mask.unsqueeze(1) + + # 1. time + timesteps = timestep + if not torch.is_tensor(timesteps): + # TODO: this requires sync between CPU and GPU. So try to pass timesteps as tensors if you can + # This would be a good case for the `match` statement (Python 3.10+) + is_mps = sample.device.type == "mps" + if isinstance(timestep, float): + dtype = torch.float32 if is_mps else torch.float64 + else: + dtype = torch.int32 if is_mps else torch.int64 + timesteps = torch.tensor([timesteps], dtype=dtype, device=sample.device) + elif len(timesteps.shape) == 0: + timesteps = timesteps[None].to(sample.device) + + # broadcast to batch dimension in a way that's compatible with ONNX/Core ML + timesteps = timesteps.expand(sample.shape[0]) + + t_emb = self.time_proj(timesteps) + + # timesteps does not contain any weights and will always return f32 tensors + # but time_embedding might actually be running in fp16. so we need to cast here. + # there might be better ways to encapsulate this. + t_emb = t_emb.to(dtype=sample.dtype) + + emb = self.time_embedding(t_emb, timestep_cond) + + if self.class_embedding is not None: + if class_labels is None: + raise ValueError("class_labels should be provided when num_class_embeds > 0") + + if self.config.class_embed_type == "timestep": + class_labels = self.time_proj(class_labels) + + class_emb = self.class_embedding(class_labels).to(dtype=self.dtype) + emb = emb + class_emb + + # 2. pre-process + sample = self.conv_in(sample) + + controlnet_cond = self.controlnet_cond_embedding(controlnet_cond) + + sample = sample + controlnet_cond + + # 3. down + down_block_res_samples = (sample,) + for downsample_block in self.down_blocks: + if hasattr(downsample_block, "has_cross_attention") and downsample_block.has_cross_attention: + sample, res_samples = downsample_block( + hidden_states=sample, + temb=emb, + encoder_hidden_states=encoder_hidden_states, + attention_mask=attention_mask, + cross_attention_kwargs=cross_attention_kwargs, + encoder_attention_mask=encoder_attention_mask, + ) + else: + sample, res_samples = downsample_block(hidden_states=sample, temb=emb) + + down_block_res_samples += res_samples + + # 4. mid + if self.mid_block is not None: + sample = self.mid_block( + sample, + emb, + encoder_hidden_states=encoder_hidden_states, + attention_mask=attention_mask, + cross_attention_kwargs=cross_attention_kwargs, + encoder_attention_mask=encoder_attention_mask, + ) + + # 5. Control net blocks + + controlnet_down_block_res_samples = () + + for down_block_res_sample, controlnet_block in zip(down_block_res_samples, self.controlnet_down_blocks): + down_block_res_sample = controlnet_block(down_block_res_sample) + controlnet_down_block_res_samples = controlnet_down_block_res_samples + (down_block_res_sample,) + + down_block_res_samples = controlnet_down_block_res_samples + + mid_block_res_sample = self.controlnet_mid_block(sample) + + # 6. scaling + if guess_mode and not self.config.global_pool_conditions: + scales = torch.logspace(-1, 0, len(down_block_res_samples) + 1, device=sample.device) # 0.1 to 1.0 + + scales = scales * conditioning_scale + down_block_res_samples = [sample * scale for sample, scale in zip(down_block_res_samples, scales)] + mid_block_res_sample = mid_block_res_sample * scales[-1] # last one + else: + down_block_res_samples = [sample * conditioning_scale for sample in down_block_res_samples] + mid_block_res_sample = mid_block_res_sample * conditioning_scale + + if self.config.global_pool_conditions: + down_block_res_samples = [ + torch.mean(sample, dim=(2, 3), keepdim=True) for sample in down_block_res_samples + ] + mid_block_res_sample = torch.mean(mid_block_res_sample, dim=(2, 3), keepdim=True) + + if not return_dict: + return (down_block_res_samples, mid_block_res_sample) + + return ControlNetOutput( + down_block_res_samples=down_block_res_samples, mid_block_res_sample=mid_block_res_sample + ) + +diffusers.ControlNetModel = ControlNetModel +diffusers.models.controlnet.ControlNetModel = ControlNetModel \ No newline at end of file diff --git a/invokeai/configs/INITIAL_MODELS.yaml b/invokeai/configs/INITIAL_MODELS.yaml index f7f6ce7b17..a733bd1bd9 100644 --- a/invokeai/configs/INITIAL_MODELS.yaml +++ b/invokeai/configs/INITIAL_MODELS.yaml @@ -64,22 +64,29 @@ sd-1/main/waifu-diffusion: recommended: False sd-1/controlnet/canny: repo_id: lllyasviel/control_v11p_sd15_canny + recommended: True sd-1/controlnet/inpaint: repo_id: lllyasviel/control_v11p_sd15_inpaint sd-1/controlnet/mlsd: repo_id: lllyasviel/control_v11p_sd15_mlsd sd-1/controlnet/depth: repo_id: lllyasviel/control_v11f1p_sd15_depth + recommended: True sd-1/controlnet/normal_bae: repo_id: lllyasviel/control_v11p_sd15_normalbae sd-1/controlnet/seg: repo_id: lllyasviel/control_v11p_sd15_seg sd-1/controlnet/lineart: repo_id: lllyasviel/control_v11p_sd15_lineart + recommended: True sd-1/controlnet/lineart_anime: repo_id: lllyasviel/control_v11p_sd15s2_lineart_anime +sd-1/controlnet/openpose: + repo_id: lllyasviel/control_v11p_sd15_openpose + recommended: True sd-1/controlnet/scribble: repo_id: lllyasviel/control_v11p_sd15_scribble + recommended: False sd-1/controlnet/softedge: repo_id: lllyasviel/control_v11p_sd15_softedge sd-1/controlnet/shuffle: @@ -90,9 +97,11 @@ sd-1/controlnet/ip2p: repo_id: lllyasviel/control_v11e_sd15_ip2p sd-1/embedding/EasyNegative: path: https://huggingface.co/embed/EasyNegative/resolve/main/EasyNegative.safetensors + recommended: True sd-1/embedding/ahx-beta-453407d: repo_id: sd-concepts-library/ahx-beta-453407d sd-1/lora/LowRA: path: https://civitai.com/api/download/models/63006 + recommended: True sd-1/lora/Ink scenery: path: https://civitai.com/api/download/models/83390 diff --git a/invokeai/frontend/install/model_install.py b/invokeai/frontend/install/model_install.py index 736d27a321..c4b19157a4 100644 --- a/invokeai/frontend/install/model_install.py +++ b/invokeai/frontend/install/model_install.py @@ -256,6 +256,8 @@ class addModelsForm(CyclingForm, npyscreen.FormMultiPage): widgets = dict() model_list = [x for x in self.all_models if self.all_models[x].model_type==model_type and not x in exclude] model_labels = [self.model_labels[x] for x in model_list] + + show_recommended = len(self.installed_models)==0 if len(model_list) > 0: max_width = max([len(x) for x in model_labels]) columns = window_width // (max_width+8) # 8 characters for "[x] " and padding @@ -280,7 +282,8 @@ class addModelsForm(CyclingForm, npyscreen.FormMultiPage): value=[ model_list.index(x) for x in model_list - if self.all_models[x].installed + if (show_recommended and self.all_models[x].recommended) \ + or self.all_models[x].installed ], max_height=len(model_list)//columns + 1, relx=4, @@ -672,7 +675,9 @@ def select_and_download_models(opt: Namespace): # pass installer = ModelInstall(config, prediction_type_helper=helper) - if opt.add or opt.delete: + if opt.list_models: + installer.list_models(opt.list_models) + elif opt.add or opt.delete: selections = InstallSelections( install_models = opt.add or [], remove_models = opt.delete or [] @@ -696,7 +701,7 @@ def select_and_download_models(opt: Namespace): # the third argument is needed in the Windows 11 environment in # order to launch and resize a console window running this program - set_min_terminal_size(MIN_COLS, MIN_LINES,'invokeai-model-install') + set_min_terminal_size(MIN_COLS, MIN_LINES) installApp = AddModelApplication(opt) try: installApp.run() @@ -745,7 +750,7 @@ def main(): ) parser.add_argument( "--list-models", - choices=["diffusers","loras","controlnets","tis"], + choices=[x.value for x in ModelType], help="list installed models", ) parser.add_argument( @@ -773,7 +778,7 @@ def main(): config.parse_args(invoke_args) logger = InvokeAILogger().getLogger(config=config) - if not (config.conf_path / 'models.yaml').exists(): + if not config.model_conf_path.exists(): logger.info( "Your InvokeAI root directory is not set up. Calling invokeai-configure." ) diff --git a/invokeai/frontend/install/widgets.py b/invokeai/frontend/install/widgets.py index c3bb3542ae..82d3753eb4 100644 --- a/invokeai/frontend/install/widgets.py +++ b/invokeai/frontend/install/widgets.py @@ -17,28 +17,20 @@ from shutil import get_terminal_size from curses import BUTTON2_CLICKED,BUTTON3_CLICKED # minimum size for UIs -MIN_COLS = 130 +MIN_COLS = 136 MIN_LINES = 45 # ------------------------------------- -def set_terminal_size(columns: int, lines: int, launch_command: str=None): +def set_terminal_size(columns: int, lines: int): ts = get_terminal_size() width = max(columns,ts.columns) height = max(lines,ts.lines) OS = platform.uname().system if OS == "Windows": - # The new Windows Terminal doesn't resize, so we relaunch in a CMD window. - # Would prefer to use execvpe() here, but somehow it is not working properly - # in the Windows 10 environment. - if 'IA_RELAUNCHED' not in os.environ: - args=['conhost'] - args.extend([launch_command] if launch_command else [sys.argv[0]]) - args.extend(sys.argv[1:]) - os.environ['IA_RELAUNCHED'] = 'True' - os.execvp('conhost',args) - else: - _set_terminal_size_powershell(width,height) + pass + # not working reliably - ask user to adjust the window + #_set_terminal_size_powershell(width,height) elif OS in ["Darwin", "Linux"]: _set_terminal_size_unix(width,height) @@ -84,20 +76,14 @@ def _set_terminal_size_unix(width: int, height: int): sys.stdout.write("\x1b[8;{height};{width}t".format(height=height, width=width)) sys.stdout.flush() -def set_min_terminal_size(min_cols: int, min_lines: int, launch_command: str=None): +def set_min_terminal_size(min_cols: int, min_lines: int): # make sure there's enough room for the ui term_cols, term_lines = get_terminal_size() if term_cols >= min_cols and term_lines >= min_lines: return cols = max(term_cols, min_cols) lines = max(term_lines, min_lines) - set_terminal_size(cols, lines, launch_command) - - # did it work? - term_cols, term_lines = get_terminal_size() - if term_cols < cols or term_lines < lines: - print(f'This window is too small for optimal display. For best results please enlarge it.') - input('After resizing, press any key to continue...') + set_terminal_size(cols, lines) class IntSlider(npyscreen.Slider): def translate_value(self): diff --git a/invokeai/frontend/web/dist/assets/App-c8b96e06.js b/invokeai/frontend/web/dist/assets/App-c8b96e06.js deleted file mode 100644 index 59752b30c9..0000000000 --- a/invokeai/frontend/web/dist/assets/App-c8b96e06.js +++ /dev/null @@ -1,169 +0,0 @@ -import{t as s0,b as mE,r as gE,i as vE,a as yE,c as bE,d as I4,e as E4,f as O4,g as xE,h as SE,j as wE,k as CE,l as _E,m as kE,n as jE,o as PE,s as IE,p as EE,q as f,u as rt,v as a,I as oo,w as ar,x as Wn,y as Ue,z as Ot,A as ku,B as xt,C as ju,D as Os,E as vo,F as Yr,G as vr,H as OE,J as gv,K as RE,L as Ja,M as tu,N as Xi,O as sn,P as ja,Q as th,R as vv,S as Al,T as yv,U as lc,_ as Jn,V as ME,W as z,X as R4,Y as M4,Z as nx,$ as D4,a0 as nh,a1 as bv,a2 as cc,a3 as DE,a4 as TE,a5 as AE,a6 as NE,a7 as T4,a8 as A4,a9 as rh,aa as Ef,ab as $E,ac as 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f.useEffect(()=>{const E=async I=>{var R,O;k.current&&(R=I.clipboardData)!=null&&R.files&&(k.current.files=I.clipboardData.files,(O=k.current)==null||O.dispatchEvent(new Event("change",{bubbles:!0})))};return p(P),document.addEventListener("paste",E),()=>{document.removeEventListener("paste",E),p(()=>{})}},[k,P,p]),a.jsxs(Be,{...b({style:{}}),onKeyDown:E=>{E.key},children:[a.jsx("input",{...w()}),t,_&&u&&a.jsx(HN,{isDragAccept:S,isDragReject:C,setIsHandlingUpload:d})]})},UN=f.memo(WN),GN=hR(e=>{e(B4(!0))},300),js=()=>(e,t)=>{yr(t())==="unifiedCanvas"&&GN(e)};var qN=globalThis&&globalThis.__extends||function(){var e=function(t,n){return e=Object.setPrototypeOf||{__proto__:[]}instanceof Array&&function(r,o){r.__proto__=o}||function(r,o){for(var s in o)Object.prototype.hasOwnProperty.call(o,s)&&(r[s]=o[s])},e(t,n)};return function(t,n){e(t,n);function r(){this.constructor=t}t.prototype=n===null?Object.create(n):(r.prototype=n.prototype,new 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o=r.parentNode;if(!o)return null;var s=r.window.document.createElement("div");return s.style.width="100%",s.style.height="100%",s.style.position="absolute",s.style.transform="scale(0, 0)",s.style.left="0",s.style.flex="0 0 100%",s.classList?s.classList.add(z2):s.className+=z2,o.appendChild(s),s},r.removeBase=function(o){var s=r.parentNode;s&&s.removeChild(o)},r.ref=function(o){o&&(r.resizable=o)},r.state={isResizing:!1,width:typeof(r.propsSize&&r.propsSize.width)>"u"?"auto":r.propsSize&&r.propsSize.width,height:typeof(r.propsSize&&r.propsSize.height)>"u"?"auto":r.propsSize&&r.propsSize.height,direction:"right",original:{x:0,y:0,width:0,height:0},backgroundStyle:{height:"100%",width:"100%",backgroundColor:"rgba(0,0,0,0)",cursor:"auto",opacity:0,position:"fixed",zIndex:9999,top:"0",left:"0",bottom:"0",right:"0"},flexBasis:void 0},r.onResizeStart=r.onResizeStart.bind(r),r.onMouseMove=r.onMouseMove.bind(r),r.onMouseUp=r.onMouseUp.bind(r),r}return Object.defineProperty(t.prototype,"parentNode",{get:function(){return this.resizable?this.resizable.parentNode:null},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"window",{get:function(){return!this.resizable||!this.resizable.ownerDocument?null:this.resizable.ownerDocument.defaultView},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"propsSize",{get:function(){return this.props.size||this.props.defaultSize||XN},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"size",{get:function(){var n=0,r=0;if(this.resizable&&this.window){var o=this.resizable.offsetWidth,s=this.resizable.offsetHeight,i=this.resizable.style.position;i!=="relative"&&(this.resizable.style.position="relative"),n=this.resizable.style.width!=="auto"?this.resizable.offsetWidth:o,r=this.resizable.style.height!=="auto"?this.resizable.offsetHeight:s,this.resizable.style.position=i}return{width:n,height:r}},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"sizeStyle",{get:function(){var n=this,r=this.props.size,o=function(u){if(typeof n.state[u]>"u"||n.state[u]==="auto")return"auto";if(n.propsSize&&n.propsSize[u]&&n.propsSize[u].toString().endsWith("%")){if(n.state[u].toString().endsWith("%"))return n.state[u].toString();var d=n.getParentSize(),p=Number(n.state[u].toString().replace("px","")),m=p/d[u]*100;return m+"%"}return kg(n.state[u])},s=r&&typeof r.width<"u"&&!this.state.isResizing?kg(r.width):o("width"),i=r&&typeof r.height<"u"&&!this.state.isResizing?kg(r.height):o("height");return{width:s,height:i}},enumerable:!1,configurable:!0}),t.prototype.getParentSize=function(){if(!this.parentNode)return this.window?{width:this.window.innerWidth,height:this.window.innerHeight}:{width:0,height:0};var n=this.appendBase();if(!n)return{width:0,height:0};var r=!1,o=this.parentNode.style.flexWrap;o!=="wrap"&&(r=!0,this.parentNode.style.flexWrap="wrap"),n.style.position="relative",n.style.minWidth="100%",n.style.minHeight="100%";var s={width:n.offsetWidth,height:n.offsetHeight};return r&&(this.parentNode.style.flexWrap=o),this.removeBase(n),s},t.prototype.bindEvents=function(){this.window&&(this.window.addEventListener("mouseup",this.onMouseUp),this.window.addEventListener("mousemove",this.onMouseMove),this.window.addEventListener("mouseleave",this.onMouseUp),this.window.addEventListener("touchmove",this.onMouseMove,{capture:!0,passive:!1}),this.window.addEventListener("touchend",this.onMouseUp))},t.prototype.unbindEvents=function(){this.window&&(this.window.removeEventListener("mouseup",this.onMouseUp),this.window.removeEventListener("mousemove",this.onMouseMove),this.window.removeEventListener("mouseleave",this.onMouseUp),this.window.removeEventListener("touchmove",this.onMouseMove,!0),this.window.removeEventListener("touchend",this.onMouseUp))},t.prototype.componentDidMount=function(){if(!(!this.resizable||!this.window)){var n=this.window.getComputedStyle(this.resizable);this.setState({width:this.state.width||this.size.width,height:this.state.height||this.size.height,flexBasis:n.flexBasis!=="auto"?n.flexBasis:void 0})}},t.prototype.componentWillUnmount=function(){this.window&&this.unbindEvents()},t.prototype.createSizeForCssProperty=function(n,r){var o=this.propsSize&&this.propsSize[r];return this.state[r]==="auto"&&this.state.original[r]===n&&(typeof o>"u"||o==="auto")?"auto":n},t.prototype.calculateNewMaxFromBoundary=function(n,r){var o=this.props.boundsByDirection,s=this.state.direction,i=o&&Cl("left",s),u=o&&Cl("top",s),d,p;if(this.props.bounds==="parent"){var m=this.parentNode;m&&(d=i?this.resizableRight-this.parentLeft:m.offsetWidth+(this.parentLeft-this.resizableLeft),p=u?this.resizableBottom-this.parentTop:m.offsetHeight+(this.parentTop-this.resizableTop))}else this.props.bounds==="window"?this.window&&(d=i?this.resizableRight:this.window.innerWidth-this.resizableLeft,p=u?this.resizableBottom:this.window.innerHeight-this.resizableTop):this.props.bounds&&(d=i?this.resizableRight-this.targetLeft:this.props.bounds.offsetWidth+(this.targetLeft-this.resizableLeft),p=u?this.resizableBottom-this.targetTop:this.props.bounds.offsetHeight+(this.targetTop-this.resizableTop));return d&&Number.isFinite(d)&&(n=n&&n"u"?10:s.width,h=typeof o.width>"u"||o.width<0?n:o.width,v=typeof s.height>"u"?10:s.height,b=typeof o.height>"u"||o.height<0?r:o.height,w=d||0,S=p||0;if(u){var C=(v-w)*this.ratio+S,_=(b-w)*this.ratio+S,k=(m-S)/this.ratio+w,P=(h-S)/this.ratio+w,E=Math.max(m,C),I=Math.min(h,_),R=Math.max(v,k),O=Math.min(b,P);n=Bd(n,E,I),r=Bd(r,R,O)}else n=Bd(n,m,h),r=Bd(r,v,b);return{newWidth:n,newHeight:r}},t.prototype.setBoundingClientRect=function(){if(this.props.bounds==="parent"){var n=this.parentNode;if(n){var r=n.getBoundingClientRect();this.parentLeft=r.left,this.parentTop=r.top}}if(this.props.bounds&&typeof this.props.bounds!="string"){var o=this.props.bounds.getBoundingClientRect();this.targetLeft=o.left,this.targetTop=o.top}if(this.resizable){var s=this.resizable.getBoundingClientRect(),i=s.left,u=s.top,d=s.right,p=s.bottom;this.resizableLeft=i,this.resizableRight=d,this.resizableTop=u,this.resizableBottom=p}},t.prototype.onResizeStart=function(n,r){if(!(!this.resizable||!this.window)){var o=0,s=0;if(n.nativeEvent&&ZN(n.nativeEvent)?(o=n.nativeEvent.clientX,s=n.nativeEvent.clientY):n.nativeEvent&&Hd(n.nativeEvent)&&(o=n.nativeEvent.touches[0].clientX,s=n.nativeEvent.touches[0].clientY),this.props.onResizeStart&&this.resizable){var i=this.props.onResizeStart(n,r,this.resizable);if(i===!1)return}this.props.size&&(typeof this.props.size.height<"u"&&this.props.size.height!==this.state.height&&this.setState({height:this.props.size.height}),typeof this.props.size.width<"u"&&this.props.size.width!==this.state.width&&this.setState({width:this.props.size.width})),this.ratio=typeof this.props.lockAspectRatio=="number"?this.props.lockAspectRatio:this.size.width/this.size.height;var u,d=this.window.getComputedStyle(this.resizable);if(d.flexBasis!=="auto"){var p=this.parentNode;if(p){var m=this.window.getComputedStyle(p).flexDirection;this.flexDir=m.startsWith("row")?"row":"column",u=d.flexBasis}}this.setBoundingClientRect(),this.bindEvents();var h={original:{x:o,y:s,width:this.size.width,height:this.size.height},isResizing:!0,backgroundStyle:Bs(Bs({},this.state.backgroundStyle),{cursor:this.window.getComputedStyle(n.target).cursor||"auto"}),direction:r,flexBasis:u};this.setState(h)}},t.prototype.onMouseMove=function(n){var r=this;if(!(!this.state.isResizing||!this.resizable||!this.window)){if(this.window.TouchEvent&&Hd(n))try{n.preventDefault(),n.stopPropagation()}catch{}var o=this.props,s=o.maxWidth,i=o.maxHeight,u=o.minWidth,d=o.minHeight,p=Hd(n)?n.touches[0].clientX:n.clientX,m=Hd(n)?n.touches[0].clientY:n.clientY,h=this.state,v=h.direction,b=h.original,w=h.width,S=h.height,C=this.getParentSize(),_=JN(C,this.window.innerWidth,this.window.innerHeight,s,i,u,d);s=_.maxWidth,i=_.maxHeight,u=_.minWidth,d=_.minHeight;var k=this.calculateNewSizeFromDirection(p,m),P=k.newHeight,E=k.newWidth,I=this.calculateNewMaxFromBoundary(s,i);this.props.snap&&this.props.snap.x&&(E=$2(E,this.props.snap.x,this.props.snapGap)),this.props.snap&&this.props.snap.y&&(P=$2(P,this.props.snap.y,this.props.snapGap));var R=this.calculateNewSizeFromAspectRatio(E,P,{width:I.maxWidth,height:I.maxHeight},{width:u,height:d});if(E=R.newWidth,P=R.newHeight,this.props.grid){var O=N2(E,this.props.grid[0]),D=N2(P,this.props.grid[1]),T=this.props.snapGap||0;E=T===0||Math.abs(O-E)<=T?O:E,P=T===0||Math.abs(D-P)<=T?D:P}var $={width:E-b.width,height:P-b.height};if(w&&typeof w=="string"){if(w.endsWith("%")){var B=E/C.width*100;E=B+"%"}else if(w.endsWith("vw")){var ee=E/this.window.innerWidth*100;E=ee+"vw"}else if(w.endsWith("vh")){var F=E/this.window.innerHeight*100;E=F+"vh"}}if(S&&typeof S=="string"){if(S.endsWith("%")){var B=P/C.height*100;P=B+"%"}else if(S.endsWith("vw")){var ee=P/this.window.innerWidth*100;P=ee+"vw"}else if(S.endsWith("vh")){var F=P/this.window.innerHeight*100;P=F+"vh"}}var N={width:this.createSizeForCssProperty(E,"width"),height:this.createSizeForCssProperty(P,"height")};this.flexDir==="row"?N.flexBasis=N.width:this.flexDir==="column"&&(N.flexBasis=N.height),dc.flushSync(function(){r.setState(N)}),this.props.onResize&&this.props.onResize(n,v,this.resizable,$)}},t.prototype.onMouseUp=function(n){var r=this.state,o=r.isResizing,s=r.direction,i=r.original;if(!(!o||!this.resizable)){var u={width:this.size.width-i.width,height:this.size.height-i.height};this.props.onResizeStop&&this.props.onResizeStop(n,s,this.resizable,u),this.props.size&&this.setState(this.props.size),this.unbindEvents(),this.setState({isResizing:!1,backgroundStyle:Bs(Bs({},this.state.backgroundStyle),{cursor:"auto"})})}},t.prototype.updateSize=function(n){this.setState({width:n.width,height:n.height})},t.prototype.renderResizer=function(){var n=this,r=this.props,o=r.enable,s=r.handleStyles,i=r.handleClasses,u=r.handleWrapperStyle,d=r.handleWrapperClass,p=r.handleComponent;if(!o)return null;var m=Object.keys(o).map(function(h){return o[h]!==!1?f.createElement(YN,{key:h,direction:h,onResizeStart:n.onResizeStart,replaceStyles:s&&s[h],className:i&&i[h]},p&&p[h]?p[h]:null):null});return f.createElement("div",{className:d,style:u},m)},t.prototype.render=function(){var n=this,r=Object.keys(this.props).reduce(function(i,u){return e$.indexOf(u)!==-1||(i[u]=n.props[u]),i},{}),o=Bs(Bs(Bs({position:"relative",userSelect:this.state.isResizing?"none":"auto"},this.props.style),this.sizeStyle),{maxWidth:this.props.maxWidth,maxHeight:this.props.maxHeight,minWidth:this.props.minWidth,minHeight:this.props.minHeight,boxSizing:"border-box",flexShrink:0});this.state.flexBasis&&(o.flexBasis=this.state.flexBasis);var s=this.props.as||"div";return f.createElement(s,Bs({ref:this.ref,style:o,className:this.props.className},r),this.state.isResizing&&f.createElement("div",{style:this.state.backgroundStyle}),this.props.children,this.renderResizer())},t.defaultProps={as:"div",onResizeStart:function(){},onResize:function(){},onResizeStop:function(){},enable:{top:!0,right:!0,bottom:!0,left:!0,topRight:!0,bottomRight:!0,bottomLeft:!0,topLeft:!0},style:{},grid:[1,1],lockAspectRatio:!1,lockAspectRatioExtraWidth:0,lockAspectRatioExtraHeight:0,scale:1,resizeRatio:1,snapGap:0},t}(f.PureComponent);const n$=({direction:e,langDirection:t})=>({top:e==="bottom",right:t!=="rtl"&&e==="left"||t==="rtl"&&e==="right",bottom:e==="top",left:t!=="rtl"&&e==="right"||t==="rtl"&&e==="left"}),r$=({direction:e,minWidth:t,maxWidth:n,minHeight:r,maxHeight:o})=>{const s=t??(["left","right"].includes(e)?10:void 0),i=n??(["left","right"].includes(e)?"95vw":void 0),u=r??(["top","bottom"].includes(e)?10:void 0),d=o??(["top","bottom"].includes(e)?"95vh":void 0);return{...s?{minWidth:s}:{},...i?{maxWidth:i}:{},...u?{minHeight:u}:{},...d?{maxHeight:d}:{}}},la="0.75rem",Wd="1rem",Lc="5px",o$=({isResizable:e,direction:t})=>{const n=`calc((2 * ${la} + ${Lc}) / -2)`;return t==="top"?{containerStyles:{borderBottomWidth:Lc,paddingBottom:Wd},handleStyles:e?{top:{paddingTop:la,paddingBottom:la,bottom:n}}:{}}:t==="left"?{containerStyles:{borderInlineEndWidth:Lc,paddingInlineEnd:Wd},handleStyles:e?{right:{paddingInlineStart:la,paddingInlineEnd:la,insetInlineEnd:n}}:{}}:t==="bottom"?{containerStyles:{borderTopWidth:Lc,paddingTop:Wd},handleStyles:e?{bottom:{paddingTop:la,paddingBottom:la,top:n}}:{}}:t==="right"?{containerStyles:{borderInlineStartWidth:Lc,paddingInlineStart:Wd},handleStyles:e?{left:{paddingInlineStart:la,paddingInlineEnd:la,insetInlineStart:n}}:{}}:{containerStyles:{},handleStyles:{}}},s$=(e,t)=>["top","bottom"].includes(e)?e:e==="left"?t==="rtl"?"right":"left":e==="right"?t==="rtl"?"left":"right":"left",Pe=(e,t)=>n=>n==="light"?e:t,a$=Ue(t$,{shouldForwardProp:e=>!["sx"].includes(e)}),U5=({direction:e="left",isResizable:t,isOpen:n,onClose:r,children:o,initialWidth:s,minWidth:i,maxWidth:u,initialHeight:d,minHeight:p,maxHeight:m,onResizeStart:h,onResizeStop:v,onResize:b,sx:w={}})=>{const 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bie(){return{animate:ja(!0),whileInView:ja(),whileHover:ja(),whileTap:ja(),whileDrag:ja(),whileFocus:ja(),exit:ja()}}class Sie extends Oa{constructor(t){super(t),t.animationState||(t.animationState=yie(t))}updateAnimationControlsSubscription(){const{animate:t}=this.node.getProps();this.unmount(),Dv(t)&&(this.unmount=t.subscribe(this.node))}mount(){this.updateAnimationControlsSubscription()}update(){const{animate:t}=this.node.getProps(),{animate:n}=this.node.prevProps||{};t!==n&&this.updateAnimationControlsSubscription()}unmount(){}}let _ie=0;class wie extends Oa{constructor(){super(...arguments),this.id=_ie++}update(){if(!this.node.presenceContext)return;const{isPresent:t,onExitComplete:n,custom:r}=this.node.presenceContext,{isPresent:i}=this.node.prevPresenceContext||{};if(!this.node.animationState||t===i)return;const 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i&&(Bs(r.x,i.offset.x),Bs(r.y,i.offset.y)),r}const jie=new WeakMap;class Vie{constructor(t){this.openGlobalLock=null,this.isDragging=!1,this.currentDirection=null,this.originPoint={x:0,y:0},this.constraints=!1,this.hasMutatedConstraints=!1,this.elastic=tn(),this.visualElement=t}start(t,{snapToCursor:n=!1}={}){const{presenceContext:r}=this.visualElement;if(r&&r.isPresent===!1)return;const i=l=>{this.stopAnimation(),n&&this.snapToCursor(Fv(l,"page").point)},o=(l,u)=>{const{drag:c,dragPropagation:d,onDragStart:f}=this.getProps();if(c&&!d&&(this.openGlobalLock&&this.openGlobalLock(),this.openGlobalLock=xM(c),!this.openGlobalLock))return;this.isDragging=!0,this.currentDirection=null,this.resolveConstraints(),this.visualElement.projection&&(this.visualElement.projection.isAnimationBlocked=!0,this.visualElement.projection.target=void 0),Ki(p=>{let m=this.getAxisMotionValue(p).get()||0;if(bo.test(m)){const{projection:S}=this.visualElement;if(S&&S.layout){const v=S.layout.layoutBox[p];v&&(m=Gr(v)*(parseFloat(m)/100))}}this.originPoint[p]=m}),f&&kt.update(()=>f(l,u),!1,!0);const{animationState:h}=this.visualElement;h&&h.setActive("whileDrag",!0)},s=(l,u)=>{const{dragPropagation:c,dragDirectionLock:d,onDirectionLock:f,onDrag:h}=this.getProps();if(!c&&!this.openGlobalLock)return;const{offset:p}=u;if(d&&this.currentDirection===null){this.currentDirection=zie(p),this.currentDirection!==null&&f&&f(this.currentDirection);return}this.updateAxis("x",u.point,p),this.updateAxis("y",u.point,p),this.visualElement.render(),h&&h(l,u)},a=(l,u)=>this.stop(l,u);this.panSession=new sN(t,{onSessionStart:i,onStart:o,onMove:s,onSessionEnd:a},{transformPagePoint:this.visualElement.getTransformPagePoint()})}stop(t,n){const r=this.isDragging;if(this.cancel(),!r)return;const{velocity:i}=n;this.startAnimation(i);const{onDragEnd:o}=this.getProps();o&&kt.update(()=>o(t,n))}cancel(){this.isDragging=!1;const{projection:t,animationState:n}=this.visualElement;t&&(t.isAnimationBlocked=!1),this.panSession&&this.panSession.end(),this.panSession=void 0;const{dragPropagation:r}=this.getProps();!r&&this.openGlobalLock&&(this.openGlobalLock(),this.openGlobalLock=null),n&&n.setActive("whileDrag",!1)}updateAxis(t,n,r){const{drag:i}=this.getProps();if(!r||!mg(t,i,this.currentDirection))return;const o=this.getAxisMotionValue(t);let s=this.originPoint[t]+r[t];this.constraints&&this.constraints[t]&&(s=kie(s,this.constraints[t],this.elastic[t])),o.set(s)}resolveConstraints(){const{dragConstraints:t,dragElastic:n}=this.getProps(),{layout:r}=this.visualElement.projection||{},i=this.constraints;t&&Lu(t)?this.constraints||(this.constraints=this.resolveRefConstraints()):t&&r?this.constraints=Aie(r.layoutBox,t):this.constraints=!1,this.elastic=Mie(n),i!==this.constraints&&r&&this.constraints&&!this.hasMutatedConstraints&&Ki(o=>{this.getAxisMotionValue(o)&&(this.constraints[o]=Iie(r.layoutBox[o],this.constraints[o]))})}resolveRefConstraints(){const{dragConstraints:t,onMeasureDragConstraints:n}=this.getProps();if(!t||!Lu(t))return!1;const r=t.current,{projection:i}=this.visualElement;if(!i||!i.layout)return!1;const o=Bie(r,i.root,this.visualElement.getTransformPagePoint());let s=Oie(i.layout.layoutBox,o);if(n){const a=n(Nie(s));this.hasMutatedConstraints=!!a,a&&(s=lN(a))}return s}startAnimation(t){const{drag:n,dragMomentum:r,dragElastic:i,dragTransition:o,dragSnapToOrigin:s,onDragTransitionEnd:a}=this.getProps(),l=this.constraints||{},u=Ki(c=>{if(!mg(c,n,this.currentDirection))return;let d=l&&l[c]||{};s&&(d={min:0,max:0});const f=i?200:1e6,h=i?40:1e7,p={type:"inertia",velocity:r?t[c]:0,bounceStiffness:f,bounceDamping:h,timeConstant:750,restDelta:1,restSpeed:10,...o,...d};return this.startAxisValueAnimation(c,p)});return Promise.all(u).then(a)}startAxisValueAnimation(t,n){const r=this.getAxisMotionValue(t);return r.start(z5(t,r,0,n))}stopAnimation(){Ki(t=>this.getAxisMotionValue(t).stop())}getAxisMotionValue(t){const n="_drag"+t.toUpperCase(),r=this.visualElement.getProps(),i=r[n];return i||this.visualElement.getValue(t,(r.initial?r.initial[t]:void 0)||0)}snapToCursor(t){Ki(n=>{const{drag:r}=this.getProps();if(!mg(n,r,this.currentDirection))return;const{projection:i}=this.visualElement,o=this.getAxisMotionValue(n);if(i&&i.layout){const{min:s,max:a}=i.layout.layoutBox[n];o.set(t[n]-Lt(s,a,.5))}})}scalePositionWithinConstraints(){if(!this.visualElement.current)return;const{drag:t,dragConstraints:n}=this.getProps(),{projection:r}=this.visualElement;if(!Lu(n)||!r||!this.constraints)return;this.stopAnimation();const i={x:0,y:0};Ki(s=>{const a=this.getAxisMotionValue(s);if(a){const l=a.get();i[s]=Rie({min:l,max:l},this.constraints[s])}});const{transformTemplate:o}=this.visualElement.getProps();this.visualElement.current.style.transform=o?o({},""):"none",r.root&&r.root.updateScroll(),r.updateLayout(),this.resolveConstraints(),Ki(s=>{if(!mg(s,t,null))return;const a=this.getAxisMotionValue(s),{min:l,max:u}=this.constraints[s];a.set(Lt(l,u,i[s]))})}addListeners(){if(!this.visualElement.current)return;jie.set(this.visualElement,this);const t=this.visualElement.current,n=rs(t,"pointerdown",l=>{const{drag:u,dragListener:c=!0}=this.getProps();u&&c&&this.start(l)}),r=()=>{const{dragConstraints:l}=this.getProps();Lu(l)&&(this.constraints=this.resolveRefConstraints())},{projection:i}=this.visualElement,o=i.addEventListener("measure",r);i&&!i.layout&&(i.root&&i.root.updateScroll(),i.updateLayout()),r();const s=es(window,"resize",()=>this.scalePositionWithinConstraints()),a=i.addEventListener("didUpdate",({delta:l,hasLayoutChanged:u})=>{this.isDragging&&u&&(Ki(c=>{const d=this.getAxisMotionValue(c);d&&(this.originPoint[c]+=l[c].translate,d.set(d.get()+l[c].translate))}),this.visualElement.render())});return()=>{s(),n(),o(),a&&a()}}getProps(){const t=this.visualElement.getProps(),{drag:n=!1,dragDirectionLock:r=!1,dragPropagation:i=!1,dragConstraints:o=!1,dragElastic:s=ww,dragMomentum:a=!0}=t;return{...t,drag:n,dragDirectionLock:r,dragPropagation:i,dragConstraints:o,dragElastic:s,dragMomentum:a}}}function mg(e,t,n){return(t===!0||t===e)&&(n===null||n===e)}function zie(e,t=10){let n=null;return Math.abs(e.y)>t?n="y":Math.abs(e.x)>t&&(n="x"),n}class Uie extends Oa{constructor(t){super(t),this.removeGroupControls=dn,this.removeListeners=dn,this.controls=new Vie(t)}mount(){const{dragControls:t}=this.node.getProps();t&&(this.removeGroupControls=t.subscribe(this.controls)),this.removeListeners=this.controls.addListeners()||dn}unmount(){this.removeGroupControls(),this.removeListeners()}}const GP=e=>(t,n)=>{e&&kt.update(()=>e(t,n))};class Gie extends Oa{constructor(){super(...arguments),this.removePointerDownListener=dn}onPointerDown(t){this.session=new sN(t,this.createPanHandlers(),{transformPagePoint:this.node.getTransformPagePoint()})}createPanHandlers(){const{onPanSessionStart:t,onPanStart:n,onPan:r,onPanEnd:i}=this.node.getProps();return{onSessionStart:GP(t),onStart:GP(n),onMove:r,onEnd:(o,s)=>{delete this.session,i&&kt.update(()=>i(o,s))}}}mount(){this.removePointerDownListener=rs(this.node.current,"pointerdown",t=>this.onPointerDown(t))}update(){this.session&&this.session.updateHandlers(this.createPanHandlers())}unmount(){this.removePointerDownListener(),this.session&&this.session.end()}}function Hie(){const e=E.useContext(fp);if(e===null)return[!0,null];const{isPresent:t,onExitComplete:n,register:r}=e,i=E.useId();return E.useEffect(()=>r(i),[]),!t&&n?[!1,()=>n&&n(i)]:[!0]}function qie(){return Wie(E.useContext(fp))}function Wie(e){return e===null?!0:e.isPresent}const pm={hasAnimatedSinceResize:!0,hasEverUpdated:!1};function HP(e,t){return t.max===t.min?0:e/(t.max-t.min)*100}const Cd={correct:(e,t)=>{if(!t.target)return e;if(typeof e=="string")if(_e.test(e))e=parseFloat(e);else return e;const n=HP(e,t.target.x),r=HP(e,t.target.y);return`${n}% ${r}%`}},Kie={correct:(e,{treeScale:t,projectionDelta:n})=>{const r=e,i=va.parse(e);if(i.length>5)return r;const o=va.createTransformer(e),s=typeof i[0]!="number"?1:0,a=n.x.scale*t.x,l=n.y.scale*t.y;i[0+s]/=a,i[1+s]/=l;const u=Lt(a,l,.5);return typeof i[2+s]=="number"&&(i[2+s]/=u),typeof i[3+s]=="number"&&(i[3+s]/=u),o(i)}};class Yie extends Ve.Component{componentDidMount(){const{visualElement:t,layoutGroup:n,switchLayoutGroup:r,layoutId:i}=this.props,{projection:o}=t;ene(Xie),o&&(n.group&&n.group.add(o),r&&r.register&&i&&r.register(o),o.root.didUpdate(),o.addEventListener("animationComplete",()=>{this.safeToRemove()}),o.setOptions({...o.options,onExitComplete:()=>this.safeToRemove()})),pm.hasEverUpdated=!0}getSnapshotBeforeUpdate(t){const{layoutDependency:n,visualElement:r,drag:i,isPresent:o}=this.props,s=r.projection;return s&&(s.isPresent=o,i||t.layoutDependency!==n||n===void 0?s.willUpdate():this.safeToRemove(),t.isPresent!==o&&(o?s.promote():s.relegate()||kt.postRender(()=>{const a=s.getStack();(!a||!a.members.length)&&this.safeToRemove()}))),null}componentDidUpdate(){const{projection:t}=this.props.visualElement;t&&(t.root.didUpdate(),queueMicrotask(()=>{!t.currentAnimation&&t.isLead()&&this.safeToRemove()}))}componentWillUnmount(){const{visualElement:t,layoutGroup:n,switchLayoutGroup:r}=this.props,{projection:i}=t;i&&(i.scheduleCheckAfterUnmount(),n&&n.group&&n.group.remove(i),r&&r.deregister&&r.deregister(i))}safeToRemove(){const{safeToRemove:t}=this.props;t&&t()}render(){return null}}function fN(e){const[t,n]=Hie(),r=E.useContext(k5);return Ve.createElement(Yie,{...e,layoutGroup:r,switchLayoutGroup:E.useContext(sM),isPresent:t,safeToRemove:n})}const Xie={borderRadius:{...Cd,applyTo:["borderTopLeftRadius","borderTopRightRadius","borderBottomLeftRadius","borderBottomRightRadius"]},borderTopLeftRadius:Cd,borderTopRightRadius:Cd,borderBottomLeftRadius:Cd,borderBottomRightRadius:Cd,boxShadow:Kie},hN=["TopLeft","TopRight","BottomLeft","BottomRight"],Qie=hN.length,qP=e=>typeof e=="string"?parseFloat(e):e,WP=e=>typeof e=="number"||_e.test(e);function Zie(e,t,n,r,i,o){i?(e.opacity=Lt(0,n.opacity!==void 0?n.opacity:1,Jie(r)),e.opacityExit=Lt(t.opacity!==void 0?t.opacity:1,0,eoe(r))):o&&(e.opacity=Lt(t.opacity!==void 0?t.opacity:1,n.opacity!==void 0?n.opacity:1,r));for(let s=0;srt?1:n(ah(e,t,r))}function YP(e,t){e.min=t.min,e.max=t.max}function Jr(e,t){YP(e.x,t.x),YP(e.y,t.y)}function XP(e,t,n,r,i){return e-=t,e=Iy(e,1/n,r),i!==void 0&&(e=Iy(e,1/i,r)),e}function toe(e,t=0,n=1,r=.5,i,o=e,s=e){if(bo.test(t)&&(t=parseFloat(t),t=Lt(s.min,s.max,t/100)-s.min),typeof t!="number")return;let a=Lt(o.min,o.max,r);e===o&&(a-=t),e.min=XP(e.min,t,n,a,i),e.max=XP(e.max,t,n,a,i)}function QP(e,t,[n,r,i],o,s){toe(e,t[n],t[r],t[i],t.scale,o,s)}const noe=["x","scaleX","originX"],roe=["y","scaleY","originY"];function ZP(e,t,n,r){QP(e.x,t,noe,n?n.x:void 0,r?r.x:void 0),QP(e.y,t,roe,n?n.y:void 0,r?r.y:void 0)}function JP(e){return e.translate===0&&e.scale===1}function gN(e){return JP(e.x)&&JP(e.y)}function Tw(e,t){return e.x.min===t.x.min&&e.x.max===t.x.max&&e.y.min===t.y.min&&e.y.max===t.y.max}function e6(e){return Gr(e.x)/Gr(e.y)}class ioe{constructor(){this.members=[]}add(t){U5(this.members,t),t.scheduleRender()}remove(t){if(G5(this.members,t),t===this.prevLead&&(this.prevLead=void 0),t===this.lead){const n=this.members[this.members.length-1];n&&this.promote(n)}}relegate(t){const n=this.members.findIndex(i=>t===i);if(n===0)return!1;let r;for(let i=n;i>=0;i--){const o=this.members[i];if(o.isPresent!==!1){r=o;break}}return r?(this.promote(r),!0):!1}promote(t,n){const r=this.lead;if(t!==r&&(this.prevLead=r,this.lead=t,t.show(),r)){r.instance&&r.scheduleRender(),t.scheduleRender(),t.resumeFrom=r,n&&(t.resumeFrom.preserveOpacity=!0),r.snapshot&&(t.snapshot=r.snapshot,t.snapshot.latestValues=r.animationValues||r.latestValues),t.root&&t.root.isUpdating&&(t.isLayoutDirty=!0);const{crossfade:i}=t.options;i===!1&&r.hide()}}exitAnimationComplete(){this.members.forEach(t=>{const{options:n,resumingFrom:r}=t;n.onExitComplete&&n.onExitComplete(),r&&r.options.onExitComplete&&r.options.onExitComplete()})}scheduleRender(){this.members.forEach(t=>{t.instance&&t.scheduleRender(!1)})}removeLeadSnapshot(){this.lead&&this.lead.snapshot&&(this.lead.snapshot=void 0)}}function t6(e,t,n){let r="";const i=e.x.translate/t.x,o=e.y.translate/t.y;if((i||o)&&(r=`translate3d(${i}px, ${o}px, 0) `),(t.x!==1||t.y!==1)&&(r+=`scale(${1/t.x}, ${1/t.y}) `),n){const{rotate:l,rotateX:u,rotateY:c}=n;l&&(r+=`rotate(${l}deg) `),u&&(r+=`rotateX(${u}deg) `),c&&(r+=`rotateY(${c}deg) `)}const s=e.x.scale*t.x,a=e.y.scale*t.y;return(s!==1||a!==1)&&(r+=`scale(${s}, ${a})`),r||"none"}const ooe=(e,t)=>e.depth-t.depth;class soe{constructor(){this.children=[],this.isDirty=!1}add(t){U5(this.children,t),this.isDirty=!0}remove(t){G5(this.children,t),this.isDirty=!0}forEach(t){this.isDirty&&this.children.sort(ooe),this.isDirty=!1,this.children.forEach(t)}}function aoe(e,t){const n=performance.now(),r=({timestamp:i})=>{const o=i-n;o>=t&&(hs(r),e(o-t))};return kt.read(r,!0),()=>hs(r)}function loe(e){window.MotionDebug&&window.MotionDebug.record(e)}function uoe(e){return e instanceof SVGElement&&e.tagName!=="svg"}function coe(e,t,n){const r=Ir(e)?e:Ec(e);return r.start(z5("",r,t,n)),r.animation}const n6=["","X","Y","Z"],r6=1e3;let doe=0;const Ka={type:"projectionFrame",totalNodes:0,resolvedTargetDeltas:0,recalculatedProjection:0};function mN({attachResizeListener:e,defaultParent:t,measureScroll:n,checkIsScrollRoot:r,resetTransform:i}){return class{constructor(s={},a=t==null?void 0:t()){this.id=doe++,this.animationId=0,this.children=new Set,this.options={},this.isTreeAnimating=!1,this.isAnimationBlocked=!1,this.isLayoutDirty=!1,this.isProjectionDirty=!1,this.isSharedProjectionDirty=!1,this.isTransformDirty=!1,this.updateManuallyBlocked=!1,this.updateBlockedByResize=!1,this.isUpdating=!1,this.isSVG=!1,this.needsReset=!1,this.shouldResetTransform=!1,this.treeScale={x:1,y:1},this.eventHandlers=new Map,this.hasTreeAnimated=!1,this.updateScheduled=!1,this.checkUpdateFailed=()=>{this.isUpdating&&(this.isUpdating=!1,this.clearAllSnapshots())},this.updateProjection=()=>{Ka.totalNodes=Ka.resolvedTargetDeltas=Ka.recalculatedProjection=0,this.nodes.forEach(poe),this.nodes.forEach(boe),this.nodes.forEach(Soe),this.nodes.forEach(goe),loe(Ka)},this.hasProjected=!1,this.isVisible=!0,this.animationProgress=0,this.sharedNodes=new Map,this.latestValues=s,this.root=a?a.root||a:this,this.path=a?[...a.path,a]:[],this.parent=a,this.depth=a?a.depth+1:0;for(let l=0;lthis.root.updateBlockedByResize=!1;e(s,()=>{this.root.updateBlockedByResize=!0,d&&d(),d=aoe(f,250),pm.hasAnimatedSinceResize&&(pm.hasAnimatedSinceResize=!1,this.nodes.forEach(o6))})}l&&this.root.registerSharedNode(l,this),this.options.animate!==!1&&c&&(l||u)&&this.addEventListener("didUpdate",({delta:d,hasLayoutChanged:f,hasRelativeTargetChanged:h,layout:p})=>{if(this.isTreeAnimationBlocked()){this.target=void 0,this.relativeTarget=void 0;return}const m=this.options.transition||c.getDefaultTransition()||Toe,{onLayoutAnimationStart:S,onLayoutAnimationComplete:v}=c.getProps(),y=!this.targetLayout||!Tw(this.targetLayout,p)||h,g=!f&&h;if(this.options.layoutRoot||this.resumeFrom&&this.resumeFrom.instance||g||f&&(y||!this.currentAnimation)){this.resumeFrom&&(this.resumingFrom=this.resumeFrom,this.resumingFrom.resumingFrom=void 0),this.setAnimationOrigin(d,g);const b={...nN(m,"layout"),onPlay:S,onComplete:v};(c.shouldReduceMotion||this.options.layoutRoot)&&(b.delay=0,b.type=!1),this.startAnimation(b)}else f||o6(this),this.isLead()&&this.options.onExitComplete&&this.options.onExitComplete();this.targetLayout=p})}unmount(){this.options.layoutId&&this.willUpdate(),this.root.nodes.remove(this);const s=this.getStack();s&&s.remove(this),this.parent&&this.parent.children.delete(this),this.instance=void 0,hs(this.updateProjection)}blockUpdate(){this.updateManuallyBlocked=!0}unblockUpdate(){this.updateManuallyBlocked=!1}isUpdateBlocked(){return this.updateManuallyBlocked||this.updateBlockedByResize}isTreeAnimationBlocked(){return this.isAnimationBlocked||this.parent&&this.parent.isTreeAnimationBlocked()||!1}startUpdate(){this.isUpdateBlocked()||(this.isUpdating=!0,this.nodes&&this.nodes.forEach(_oe),this.animationId++)}getTransformTemplate(){const{visualElement:s}=this.options;return s&&s.getProps().transformTemplate}willUpdate(s=!0){if(this.root.hasTreeAnimated=!0,this.root.isUpdateBlocked()){this.options.onExitComplete&&this.options.onExitComplete();return}if(!this.root.isUpdating&&this.root.startUpdate(),this.isLayoutDirty)return;this.isLayoutDirty=!0;for(let c=0;cthis.update()))}clearAllSnapshots(){this.nodes.forEach(moe),this.sharedNodes.forEach(woe)}scheduleUpdateProjection(){kt.preRender(this.updateProjection,!1,!0)}scheduleCheckAfterUnmount(){kt.postRender(()=>{this.isLayoutDirty?this.root.didUpdate():this.root.checkUpdateFailed()})}updateSnapshot(){this.snapshot||!this.instance||(this.snapshot=this.measure())}updateLayout(){if(!this.instance||(this.updateScroll(),!(this.options.alwaysMeasureLayout&&this.isLead())&&!this.isLayoutDirty))return;if(this.resumeFrom&&!this.resumeFrom.instance)for(let l=0;l{const _=b/1e3;s6(d.x,s.x,_),s6(d.y,s.y,_),this.setTargetDelta(d),this.relativeTarget&&this.relativeTargetOrigin&&this.layout&&this.relativeParent&&this.relativeParent.layout&&(mf(f,this.layout.layoutBox,this.relativeParent.layout.layoutBox),xoe(this.relativeTarget,this.relativeTargetOrigin,f,_),g&&Tw(this.relativeTarget,g)&&(this.isProjectionDirty=!1),g||(g=tn()),Jr(g,this.relativeTarget)),m&&(this.animationValues=c,Zie(c,u,this.latestValues,_,y,v)),this.root.scheduleUpdateProjection(),this.scheduleRender(),this.animationProgress=_},this.mixTargetDelta(this.options.layoutRoot?1e3:0)}startAnimation(s){this.notifyListeners("animationStart"),this.currentAnimation&&this.currentAnimation.stop(),this.resumingFrom&&this.resumingFrom.currentAnimation&&this.resumingFrom.currentAnimation.stop(),this.pendingAnimation&&(hs(this.pendingAnimation),this.pendingAnimation=void 0),this.pendingAnimation=kt.update(()=>{pm.hasAnimatedSinceResize=!0,this.currentAnimation=coe(0,r6,{...s,onUpdate:a=>{this.mixTargetDelta(a),s.onUpdate&&s.onUpdate(a)},onComplete:()=>{s.onComplete&&s.onComplete(),this.completeAnimation()}}),this.resumingFrom&&(this.resumingFrom.currentAnimation=this.currentAnimation),this.pendingAnimation=void 0})}completeAnimation(){this.resumingFrom&&(this.resumingFrom.currentAnimation=void 0,this.resumingFrom.preserveOpacity=void 0);const s=this.getStack();s&&s.exitAnimationComplete(),this.resumingFrom=this.currentAnimation=this.animationValues=void 0,this.notifyListeners("animationComplete")}finishAnimation(){this.currentAnimation&&(this.mixTargetDelta&&this.mixTargetDelta(r6),this.currentAnimation.stop()),this.completeAnimation()}applyTransformsToTarget(){const s=this.getLead();let{targetWithTransforms:a,target:l,layout:u,latestValues:c}=s;if(!(!a||!l||!u)){if(this!==s&&this.layout&&u&&yN(this.options.animationType,this.layout.layoutBox,u.layoutBox)){l=this.target||tn();const d=Gr(this.layout.layoutBox.x);l.x.min=s.target.x.min,l.x.max=l.x.min+d;const f=Gr(this.layout.layoutBox.y);l.y.min=s.target.y.min,l.y.max=l.y.min+f}Jr(a,l),Bu(a,c),gf(this.projectionDeltaWithTransform,this.layoutCorrected,a,c)}}registerSharedNode(s,a){this.sharedNodes.has(s)||this.sharedNodes.set(s,new ioe),this.sharedNodes.get(s).add(a);const u=a.options.initialPromotionConfig;a.promote({transition:u?u.transition:void 0,preserveFollowOpacity:u&&u.shouldPreserveFollowOpacity?u.shouldPreserveFollowOpacity(a):void 0})}isLead(){const s=this.getStack();return s?s.lead===this:!0}getLead(){var s;const{layoutId:a}=this.options;return a?((s=this.getStack())===null||s===void 0?void 0:s.lead)||this:this}getPrevLead(){var s;const{layoutId:a}=this.options;return a?(s=this.getStack())===null||s===void 0?void 0:s.prevLead:void 0}getStack(){const{layoutId:s}=this.options;if(s)return this.root.sharedNodes.get(s)}promote({needsReset:s,transition:a,preserveFollowOpacity:l}={}){const u=this.getStack();u&&u.promote(this,l),s&&(this.projectionDelta=void 0,this.needsReset=!0),a&&this.setOptions({transition:a})}relegate(){const s=this.getStack();return s?s.relegate(this):!1}resetRotation(){const{visualElement:s}=this.options;if(!s)return;let a=!1;const{latestValues:l}=s;if((l.rotate||l.rotateX||l.rotateY||l.rotateZ)&&(a=!0),!a)return;const u={};for(let c=0;c{var a;return(a=s.currentAnimation)===null||a===void 0?void 0:a.stop()}),this.root.nodes.forEach(i6),this.root.sharedNodes.clear()}}}function foe(e){e.updateLayout()}function hoe(e){var t;const n=((t=e.resumeFrom)===null||t===void 0?void 0:t.snapshot)||e.snapshot;if(e.isLead()&&e.layout&&n&&e.hasListeners("didUpdate")){const{layoutBox:r,measuredBox:i}=e.layout,{animationType:o}=e.options,s=n.source!==e.layout.source;o==="size"?Ki(d=>{const f=s?n.measuredBox[d]:n.layoutBox[d],h=Gr(f);f.min=r[d].min,f.max=f.min+h}):yN(o,n.layoutBox,r)&&Ki(d=>{const f=s?n.measuredBox[d]:n.layoutBox[d],h=Gr(r[d]);f.max=f.min+h,e.relativeTarget&&!e.currentAnimation&&(e.isProjectionDirty=!0,e.relativeTarget[d].max=e.relativeTarget[d].min+h)});const a=Fu();gf(a,r,n.layoutBox);const l=Fu();s?gf(l,e.applyTransform(i,!0),n.measuredBox):gf(l,r,n.layoutBox);const u=!gN(a);let c=!1;if(!e.resumeFrom){const d=e.getClosestProjectingParent();if(d&&!d.resumeFrom){const{snapshot:f,layout:h}=d;if(f&&h){const p=tn();mf(p,n.layoutBox,f.layoutBox);const m=tn();mf(m,r,h.layoutBox),Tw(p,m)||(c=!0),d.options.layoutRoot&&(e.relativeTarget=m,e.relativeTargetOrigin=p,e.relativeParent=d)}}}e.notifyListeners("didUpdate",{layout:r,snapshot:n,delta:l,layoutDelta:a,hasLayoutChanged:u,hasRelativeTargetChanged:c})}else if(e.isLead()){const{onExitComplete:r}=e.options;r&&r()}e.options.transition=void 0}function poe(e){Ka.totalNodes++,e.parent&&(e.isProjecting()||(e.isProjectionDirty=e.parent.isProjectionDirty),e.isSharedProjectionDirty||(e.isSharedProjectionDirty=!!(e.isProjectionDirty||e.parent.isProjectionDirty||e.parent.isSharedProjectionDirty)),e.isTransformDirty||(e.isTransformDirty=e.parent.isTransformDirty))}function goe(e){e.isProjectionDirty=e.isSharedProjectionDirty=e.isTransformDirty=!1}function moe(e){e.clearSnapshot()}function i6(e){e.clearMeasurements()}function yoe(e){e.isLayoutDirty=!1}function voe(e){const{visualElement:t}=e.options;t&&t.getProps().onBeforeLayoutMeasure&&t.notify("BeforeLayoutMeasure"),e.resetTransform()}function o6(e){e.finishAnimation(),e.targetDelta=e.relativeTarget=e.target=void 0,e.isProjectionDirty=!0}function boe(e){e.resolveTargetDelta()}function Soe(e){e.calcProjection()}function _oe(e){e.resetRotation()}function woe(e){e.removeLeadSnapshot()}function s6(e,t,n){e.translate=Lt(t.translate,0,n),e.scale=Lt(t.scale,1,n),e.origin=t.origin,e.originPoint=t.originPoint}function a6(e,t,n,r){e.min=Lt(t.min,n.min,r),e.max=Lt(t.max,n.max,r)}function xoe(e,t,n,r){a6(e.x,t.x,n.x,r),a6(e.y,t.y,n.y,r)}function Coe(e){return e.animationValues&&e.animationValues.opacityExit!==void 0}const Toe={duration:.45,ease:[.4,0,.1,1]};function l6(e){e.min=Math.round(e.min),e.max=Math.round(e.max)}function Eoe(e){l6(e.x),l6(e.y)}function yN(e,t,n){return e==="position"||e==="preserve-aspect"&&!_w(e6(t),e6(n),.2)}const Poe=mN({attachResizeListener:(e,t)=>es(e,"resize",t),measureScroll:()=>({x:document.documentElement.scrollLeft||document.body.scrollLeft,y:document.documentElement.scrollTop||document.body.scrollTop}),checkIsScrollRoot:()=>!0}),XS={current:void 0},vN=mN({measureScroll:e=>({x:e.scrollLeft,y:e.scrollTop}),defaultParent:()=>{if(!XS.current){const e=new Poe({});e.mount(window),e.setOptions({layoutScroll:!0}),XS.current=e}return XS.current},resetTransform:(e,t)=>{e.style.transform=t!==void 0?t:"none"},checkIsScrollRoot:e=>window.getComputedStyle(e).position==="fixed"}),koe={pan:{Feature:Gie},drag:{Feature:Uie,ProjectionNode:vN,MeasureLayout:fN}},Aoe=/var\((--[a-zA-Z0-9-_]+),? ?([a-zA-Z0-9 ()%#.,-]+)?\)/;function Ooe(e){const t=Aoe.exec(e);if(!t)return[,];const[,n,r]=t;return[n,r]}function Ew(e,t,n=1){const[r,i]=Ooe(e);if(!r)return;const o=window.getComputedStyle(t).getPropertyValue(r);return o?o.trim():hw(i)?Ew(i,t,n+1):i}function Roe(e,{...t},n){const r=e.current;if(!(r instanceof 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xo{constructor(t,n,r,i){this._cachedPath=[],this.parent=t,this.data=n,this._path=r,this._key=i}get path(){return this._cachedPath.length||(this._key instanceof Array?this._cachedPath.push(...this._path,...this._key):this._cachedPath.push(...this._path,this._key)),this._cachedPath}}const U6=(e,t)=>{if(Ly(t))return{success:!0,data:t.value};if(!e.common.issues.length)throw new Error("Validation failed but no issues detected.");return{success:!1,get error(){if(this._error)return this._error;const n=new Ni(e.common.issues);return this._error=n,this._error}}};function Ae(e){if(!e)return{};const{errorMap:t,invalid_type_error:n,required_error:r,description:i}=e;if(t&&(n||r))throw new Error(`Can't use "invalid_type_error" or "required_error" in conjunction with custom error map.`);return t?{errorMap:t,description:i}:{errorMap:(s,a)=>s.code!=="invalid_type"?{message:a.defaultError}:typeof a.data>"u"?{message:r??a.defaultError}:{message:n??a.defaultError},description:i}}class Oe{constructor(t){this.spa=this.safeParseAsync,this._def=t,this.parse=this.parse.bind(this),this.safeParse=this.safeParse.bind(this),this.parseAsync=this.parseAsync.bind(this),this.safeParseAsync=this.safeParseAsync.bind(this),this.spa=this.spa.bind(this),this.refine=this.refine.bind(this),this.refinement=this.refinement.bind(this),this.superRefine=this.superRefine.bind(this),this.optional=this.optional.bind(this),this.nullable=this.nullable.bind(this),this.nullish=this.nullish.bind(this),this.array=this.array.bind(this),this.promise=this.promise.bind(this),this.or=this.or.bind(this),this.and=this.and.bind(this),this.transform=this.transform.bind(this),this.brand=this.brand.bind(this),this.default=this.default.bind(this),this.catch=this.catch.bind(this),this.describe=this.describe.bind(this),this.pipe=this.pipe.bind(this),this.isNullable=this.isNullable.bind(this),this.isOptional=this.isOptional.bind(this)}get description(){return this._def.description}_getType(t){return qs(t.data)}_getOrReturnCtx(t,n){return n||{common:t.parent.common,data:t.data,parsedType:qs(t.data),schemaErrorMap:this._def.errorMap,path:t.path,parent:t.parent}}_processInputParams(t){return{status:new Qn,ctx:{common:t.parent.common,data:t.data,parsedType:qs(t.data),schemaErrorMap:this._def.errorMap,path:t.path,parent:t.parent}}}_parseSync(t){const n=this._parse(t);if($y(n))throw new Error("Synchronous parse encountered promise.");return n}_parseAsync(t){const n=this._parse(t);return Promise.resolve(n)}parse(t,n){const r=this.safeParse(t,n);if(r.success)return r.data;throw r.error}safeParse(t,n){var r;const i={common:{issues:[],async:(r=n==null?void 0:n.async)!==null&&r!==void 0?r:!1,contextualErrorMap:n==null?void 0:n.errorMap},path:(n==null?void 0:n.path)||[],schemaErrorMap:this._def.errorMap,parent:null,data:t,parsedType:qs(t)},o=this._parseSync({data:t,path:i.path,parent:i});return U6(i,o)}async parseAsync(t,n){const r=await this.safeParseAsync(t,n);if(r.success)return r.data;throw r.error}async safeParseAsync(t,n){const r={common:{issues:[],contextualErrorMap:n==null?void 0:n.errorMap,async:!0},path:(n==null?void 0:n.path)||[],schemaErrorMap:this._def.errorMap,parent:null,data:t,parsedType:qs(t)},i=this._parse({data:t,path:r.path,parent:r}),o=await($y(i)?i:Promise.resolve(i));return U6(r,o)}refine(t,n){const r=i=>typeof n=="string"||typeof n>"u"?{message:n}:typeof n=="function"?n(i):n;return this._refinement((i,o)=>{const s=t(i),a=()=>o.addIssue({code:re.custom,...r(i)});return typeof Promise<"u"&&s instanceof Promise?s.then(l=>l?!0:(a(),!1)):s?!0:(a(),!1)})}refinement(t,n){return this._refinement((r,i)=>t(r)?!0:(i.addIssue(typeof n=="function"?n(r,i):n),!1))}_refinement(t){return new ji({schema:this,typeName:we.ZodEffects,effect:{type:"refinement",refinement:t}})}superRefine(t){return this._refinement(t)}optional(){return os.create(this,this._def)}nullable(){return Tl.create(this,this._def)}nullish(){return this.nullable().optional()}array(){return Di.create(this,this._def)}promise(){return Ic.create(this,this._def)}or(t){return ph.create([this,t],this._def)}and(t){return gh.create(this,t,this._def)}transform(t){return new ji({...Ae(this._def),schema:this,typeName:we.ZodEffects,effect:{type:"transform",transform:t}})}default(t){const n=typeof t=="function"?t:()=>t;return new Sh({...Ae(this._def),innerType:this,defaultValue:n,typeName:we.ZodDefault})}brand(){return new PD({typeName:we.ZodBranded,type:this,...Ae(this._def)})}catch(t){const n=typeof t=="function"?t:()=>t;return new Vy({...Ae(this._def),innerType:this,catchValue:n,typeName:we.ZodCatch})}describe(t){const n=this.constructor;return new n({...this._def,description:t})}pipe(t){return Sp.create(this,t)}isOptional(){return this.safeParse(void 0).success}isNullable(){return this.safeParse(null).success}}const Mue=/^c[^\s-]{8,}$/i,Nue=/^[a-z][a-z0-9]*$/,Due=/[0-9A-HJKMNP-TV-Z]{26}/,Lue=/^([a-f0-9]{8}-[a-f0-9]{4}-[1-5][a-f0-9]{3}-[a-f0-9]{4}-[a-f0-9]{12}|00000000-0000-0000-0000-000000000000)$/i,$ue=/^(([^<>()[\]\\.,;:\s@\"]+(\.[^<>()[\]\\.,;:\s@\"]+)*)|(\".+\"))@((\[(((25[0-5])|(2[0-4][0-9])|(1[0-9]{2})|([0-9]{1,2}))\.){3}((25[0-5])|(2[0-4][0-9])|(1[0-9]{2})|([0-9]{1,2}))\])|(\[IPv6:(([a-f0-9]{1,4}:){7}|::([a-f0-9]{1,4}:){0,6}|([a-f0-9]{1,4}:){1}:([a-f0-9]{1,4}:){0,5}|([a-f0-9]{1,4}:){2}:([a-f0-9]{1,4}:){0,4}|([a-f0-9]{1,4}:){3}:([a-f0-9]{1,4}:){0,3}|([a-f0-9]{1,4}:){4}:([a-f0-9]{1,4}:){0,2}|([a-f0-9]{1,4}:){5}:([a-f0-9]{1,4}:){0,1})([a-f0-9]{1,4}|(((25[0-5])|(2[0-4][0-9])|(1[0-9]{2})|([0-9]{1,2}))\.){3}((25[0-5])|(2[0-4][0-9])|(1[0-9]{2})|([0-9]{1,2})))\])|([A-Za-z0-9]([A-Za-z0-9-]*[A-Za-z0-9])*(\.[A-Za-z]{2,})+))$/,Fue=/^(\p{Extended_Pictographic}|\p{Emoji_Component})+$/u,Bue=/^(((25[0-5])|(2[0-4][0-9])|(1[0-9]{2})|([0-9]{1,2}))\.){3}((25[0-5])|(2[0-4][0-9])|(1[0-9]{2})|([0-9]{1,2}))$/,jue=/^(([a-f0-9]{1,4}:){7}|::([a-f0-9]{1,4}:){0,6}|([a-f0-9]{1,4}:){1}:([a-f0-9]{1,4}:){0,5}|([a-f0-9]{1,4}:){2}:([a-f0-9]{1,4}:){0,4}|([a-f0-9]{1,4}:){3}:([a-f0-9]{1,4}:){0,3}|([a-f0-9]{1,4}:){4}:([a-f0-9]{1,4}:){0,2}|([a-f0-9]{1,4}:){5}:([a-f0-9]{1,4}:){0,1})([a-f0-9]{1,4}|(((25[0-5])|(2[0-4][0-9])|(1[0-9]{2})|([0-9]{1,2}))\.){3}((25[0-5])|(2[0-4][0-9])|(1[0-9]{2})|([0-9]{1,2})))$/,Vue=e=>e.precision?e.offset?new RegExp(`^\\d{4}-\\d{2}-\\d{2}T\\d{2}:\\d{2}:\\d{2}\\.\\d{${e.precision}}(([+-]\\d{2}(:?\\d{2})?)|Z)$`):new RegExp(`^\\d{4}-\\d{2}-\\d{2}T\\d{2}:\\d{2}:\\d{2}\\.\\d{${e.precision}}Z$`):e.precision===0?e.offset?new RegExp("^\\d{4}-\\d{2}-\\d{2}T\\d{2}:\\d{2}:\\d{2}(([+-]\\d{2}(:?\\d{2})?)|Z)$"):new RegExp("^\\d{4}-\\d{2}-\\d{2}T\\d{2}:\\d{2}:\\d{2}Z$"):e.offset?new RegExp("^\\d{4}-\\d{2}-\\d{2}T\\d{2}:\\d{2}:\\d{2}(\\.\\d+)?(([+-]\\d{2}(:?\\d{2})?)|Z)$"):new RegExp("^\\d{4}-\\d{2}-\\d{2}T\\d{2}:\\d{2}:\\d{2}(\\.\\d+)?Z$");function zue(e,t){return!!((t==="v4"||!t)&&Bue.test(e)||(t==="v6"||!t)&&jue.test(e))}class Oi extends Oe{constructor(){super(...arguments),this._regex=(t,n,r)=>this.refinement(i=>t.test(i),{validation:n,code:re.invalid_string,...ve.errToObj(r)}),this.nonempty=t=>this.min(1,ve.errToObj(t)),this.trim=()=>new Oi({...this._def,checks:[...this._def.checks,{kind:"trim"}]}),this.toLowerCase=()=>new Oi({...this._def,checks:[...this._def.checks,{kind:"toLowerCase"}]}),this.toUpperCase=()=>new Oi({...this._def,checks:[...this._def.checks,{kind:"toUpperCase"}]})}_parse(t){if(this._def.coerce&&(t.data=String(t.data)),this._getType(t)!==le.string){const o=this._getOrReturnCtx(t);return ce(o,{code:re.invalid_type,expected:le.string,received:o.parsedType}),xe}const r=new Qn;let i;for(const o of this._def.checks)if(o.kind==="min")t.data.lengtho.value&&(i=this._getOrReturnCtx(t,i),ce(i,{code:re.too_big,maximum:o.value,type:"string",inclusive:!0,exact:!1,message:o.message}),r.dirty());else if(o.kind==="length"){const s=t.data.length>o.value,a=t.data.length"u"?null:t==null?void 0:t.precision,offset:(n=t==null?void 0:t.offset)!==null&&n!==void 0?n:!1,...ve.errToObj(t==null?void 0:t.message)})}regex(t,n){return this._addCheck({kind:"regex",regex:t,...ve.errToObj(n)})}includes(t,n){return this._addCheck({kind:"includes",value:t,position:n==null?void 0:n.position,...ve.errToObj(n==null?void 0:n.message)})}startsWith(t,n){return this._addCheck({kind:"startsWith",value:t,...ve.errToObj(n)})}endsWith(t,n){return this._addCheck({kind:"endsWith",value:t,...ve.errToObj(n)})}min(t,n){return this._addCheck({kind:"min",value:t,...ve.errToObj(n)})}max(t,n){return this._addCheck({kind:"max",value:t,...ve.errToObj(n)})}length(t,n){return this._addCheck({kind:"length",value:t,...ve.errToObj(n)})}get isDatetime(){return!!this._def.checks.find(t=>t.kind==="datetime")}get isEmail(){return!!this._def.checks.find(t=>t.kind==="email")}get isURL(){return!!this._def.checks.find(t=>t.kind==="url")}get isEmoji(){return!!this._def.checks.find(t=>t.kind==="emoji")}get isUUID(){return!!this._def.checks.find(t=>t.kind==="uuid")}get isCUID(){return!!this._def.checks.find(t=>t.kind==="cuid")}get isCUID2(){return!!this._def.checks.find(t=>t.kind==="cuid2")}get isULID(){return!!this._def.checks.find(t=>t.kind==="ulid")}get isIP(){return!!this._def.checks.find(t=>t.kind==="ip")}get minLength(){let t=null;for(const n of this._def.checks)n.kind==="min"&&(t===null||n.value>t)&&(t=n.value);return t}get maxLength(){let t=null;for(const n of this._def.checks)n.kind==="max"&&(t===null||n.value{var t;return new Oi({checks:[],typeName:we.ZodString,coerce:(t=e==null?void 0:e.coerce)!==null&&t!==void 0?t:!1,...Ae(e)})};function Uue(e,t){const n=(e.toString().split(".")[1]||"").length,r=(t.toString().split(".")[1]||"").length,i=n>r?n:r,o=parseInt(e.toFixed(i).replace(".","")),s=parseInt(t.toFixed(i).replace(".",""));return o%s/Math.pow(10,i)}class ba extends Oe{constructor(){super(...arguments),this.min=this.gte,this.max=this.lte,this.step=this.multipleOf}_parse(t){if(this._def.coerce&&(t.data=Number(t.data)),this._getType(t)!==le.number){const o=this._getOrReturnCtx(t);return ce(o,{code:re.invalid_type,expected:le.number,received:o.parsedType}),xe}let r;const i=new Qn;for(const o of this._def.checks)o.kind==="int"?Xe.isInteger(t.data)||(r=this._getOrReturnCtx(t,r),ce(r,{code:re.invalid_type,expected:"integer",received:"float",message:o.message}),i.dirty()):o.kind==="min"?(o.inclusive?t.datao.value:t.data>=o.value)&&(r=this._getOrReturnCtx(t,r),ce(r,{code:re.too_big,maximum:o.value,type:"number",inclusive:o.inclusive,exact:!1,message:o.message}),i.dirty()):o.kind==="multipleOf"?Uue(t.data,o.value)!==0&&(r=this._getOrReturnCtx(t,r),ce(r,{code:re.not_multiple_of,multipleOf:o.value,message:o.message}),i.dirty()):o.kind==="finite"?Number.isFinite(t.data)||(r=this._getOrReturnCtx(t,r),ce(r,{code:re.not_finite,message:o.message}),i.dirty()):Xe.assertNever(o);return{status:i.value,value:t.data}}gte(t,n){return this.setLimit("min",t,!0,ve.toString(n))}gt(t,n){return this.setLimit("min",t,!1,ve.toString(n))}lte(t,n){return this.setLimit("max",t,!0,ve.toString(n))}lt(t,n){return this.setLimit("max",t,!1,ve.toString(n))}setLimit(t,n,r,i){return new ba({...this._def,checks:[...this._def.checks,{kind:t,value:n,inclusive:r,message:ve.toString(i)}]})}_addCheck(t){return new ba({...this._def,checks:[...this._def.checks,t]})}int(t){return this._addCheck({kind:"int",message:ve.toString(t)})}positive(t){return this._addCheck({kind:"min",value:0,inclusive:!1,message:ve.toString(t)})}negative(t){return this._addCheck({kind:"max",value:0,inclusive:!1,message:ve.toString(t)})}nonpositive(t){return this._addCheck({kind:"max",value:0,inclusive:!0,message:ve.toString(t)})}nonnegative(t){return this._addCheck({kind:"min",value:0,inclusive:!0,message:ve.toString(t)})}multipleOf(t,n){return this._addCheck({kind:"multipleOf",value:t,message:ve.toString(n)})}finite(t){return this._addCheck({kind:"finite",message:ve.toString(t)})}safe(t){return this._addCheck({kind:"min",inclusive:!0,value:Number.MIN_SAFE_INTEGER,message:ve.toString(t)})._addCheck({kind:"max",inclusive:!0,value:Number.MAX_SAFE_INTEGER,message:ve.toString(t)})}get minValue(){let t=null;for(const n of this._def.checks)n.kind==="min"&&(t===null||n.value>t)&&(t=n.value);return t}get maxValue(){let t=null;for(const n of this._def.checks)n.kind==="max"&&(t===null||n.valuet.kind==="int"||t.kind==="multipleOf"&&Xe.isInteger(t.value))}get isFinite(){let t=null,n=null;for(const r of this._def.checks){if(r.kind==="finite"||r.kind==="int"||r.kind==="multipleOf")return!0;r.kind==="min"?(n===null||r.value>n)&&(n=r.value):r.kind==="max"&&(t===null||r.valuenew ba({checks:[],typeName:we.ZodNumber,coerce:(e==null?void 0:e.coerce)||!1,...Ae(e)});class Sa extends Oe{constructor(){super(...arguments),this.min=this.gte,this.max=this.lte}_parse(t){if(this._def.coerce&&(t.data=BigInt(t.data)),this._getType(t)!==le.bigint){const o=this._getOrReturnCtx(t);return ce(o,{code:re.invalid_type,expected:le.bigint,received:o.parsedType}),xe}let r;const i=new Qn;for(const o of this._def.checks)o.kind==="min"?(o.inclusive?t.datao.value:t.data>=o.value)&&(r=this._getOrReturnCtx(t,r),ce(r,{code:re.too_big,type:"bigint",maximum:o.value,inclusive:o.inclusive,message:o.message}),i.dirty()):o.kind==="multipleOf"?t.data%o.value!==BigInt(0)&&(r=this._getOrReturnCtx(t,r),ce(r,{code:re.not_multiple_of,multipleOf:o.value,message:o.message}),i.dirty()):Xe.assertNever(o);return{status:i.value,value:t.data}}gte(t,n){return this.setLimit("min",t,!0,ve.toString(n))}gt(t,n){return this.setLimit("min",t,!1,ve.toString(n))}lte(t,n){return this.setLimit("max",t,!0,ve.toString(n))}lt(t,n){return this.setLimit("max",t,!1,ve.toString(n))}setLimit(t,n,r,i){return new Sa({...this._def,checks:[...this._def.checks,{kind:t,value:n,inclusive:r,message:ve.toString(i)}]})}_addCheck(t){return new Sa({...this._def,checks:[...this._def.checks,t]})}positive(t){return this._addCheck({kind:"min",value:BigInt(0),inclusive:!1,message:ve.toString(t)})}negative(t){return this._addCheck({kind:"max",value:BigInt(0),inclusive:!1,message:ve.toString(t)})}nonpositive(t){return this._addCheck({kind:"max",value:BigInt(0),inclusive:!0,message:ve.toString(t)})}nonnegative(t){return this._addCheck({kind:"min",value:BigInt(0),inclusive:!0,message:ve.toString(t)})}multipleOf(t,n){return this._addCheck({kind:"multipleOf",value:t,message:ve.toString(n)})}get minValue(){let t=null;for(const n of this._def.checks)n.kind==="min"&&(t===null||n.value>t)&&(t=n.value);return t}get maxValue(){let t=null;for(const n of this._def.checks)n.kind==="max"&&(t===null||n.value{var t;return new Sa({checks:[],typeName:we.ZodBigInt,coerce:(t=e==null?void 0:e.coerce)!==null&&t!==void 0?t:!1,...Ae(e)})};class dh extends Oe{_parse(t){if(this._def.coerce&&(t.data=!!t.data),this._getType(t)!==le.boolean){const r=this._getOrReturnCtx(t);return ce(r,{code:re.invalid_type,expected:le.boolean,received:r.parsedType}),xe}return dr(t.data)}}dh.create=e=>new dh({typeName:we.ZodBoolean,coerce:(e==null?void 0:e.coerce)||!1,...Ae(e)});class xl extends Oe{_parse(t){if(this._def.coerce&&(t.data=new Date(t.data)),this._getType(t)!==le.date){const o=this._getOrReturnCtx(t);return ce(o,{code:re.invalid_type,expected:le.date,received:o.parsedType}),xe}if(isNaN(t.data.getTime())){const o=this._getOrReturnCtx(t);return ce(o,{code:re.invalid_date}),xe}const r=new Qn;let i;for(const o of this._def.checks)o.kind==="min"?t.data.getTime()o.value&&(i=this._getOrReturnCtx(t,i),ce(i,{code:re.too_big,message:o.message,inclusive:!0,exact:!1,maximum:o.value,type:"date"}),r.dirty()):Xe.assertNever(o);return{status:r.value,value:new Date(t.data.getTime())}}_addCheck(t){return new xl({...this._def,checks:[...this._def.checks,t]})}min(t,n){return this._addCheck({kind:"min",value:t.getTime(),message:ve.toString(n)})}max(t,n){return this._addCheck({kind:"max",value:t.getTime(),message:ve.toString(n)})}get minDate(){let t=null;for(const n of this._def.checks)n.kind==="min"&&(t===null||n.value>t)&&(t=n.value);return t!=null?new Date(t):null}get maxDate(){let t=null;for(const n of this._def.checks)n.kind==="max"&&(t===null||n.valuenew xl({checks:[],coerce:(e==null?void 0:e.coerce)||!1,typeName:we.ZodDate,...Ae(e)});class Fy extends Oe{_parse(t){if(this._getType(t)!==le.symbol){const r=this._getOrReturnCtx(t);return ce(r,{code:re.invalid_type,expected:le.symbol,received:r.parsedType}),xe}return dr(t.data)}}Fy.create=e=>new Fy({typeName:we.ZodSymbol,...Ae(e)});class fh extends Oe{_parse(t){if(this._getType(t)!==le.undefined){const r=this._getOrReturnCtx(t);return ce(r,{code:re.invalid_type,expected:le.undefined,received:r.parsedType}),xe}return dr(t.data)}}fh.create=e=>new fh({typeName:we.ZodUndefined,...Ae(e)});class hh extends Oe{_parse(t){if(this._getType(t)!==le.null){const r=this._getOrReturnCtx(t);return ce(r,{code:re.invalid_type,expected:le.null,received:r.parsedType}),xe}return dr(t.data)}}hh.create=e=>new hh({typeName:we.ZodNull,...Ae(e)});class Rc extends Oe{constructor(){super(...arguments),this._any=!0}_parse(t){return dr(t.data)}}Rc.create=e=>new Rc({typeName:we.ZodAny,...Ae(e)});class cl extends Oe{constructor(){super(...arguments),this._unknown=!0}_parse(t){return dr(t.data)}}cl.create=e=>new cl({typeName:we.ZodUnknown,...Ae(e)});class gs extends Oe{_parse(t){const n=this._getOrReturnCtx(t);return ce(n,{code:re.invalid_type,expected:le.never,received:n.parsedType}),xe}}gs.create=e=>new gs({typeName:we.ZodNever,...Ae(e)});class By extends Oe{_parse(t){if(this._getType(t)!==le.undefined){const r=this._getOrReturnCtx(t);return ce(r,{code:re.invalid_type,expected:le.void,received:r.parsedType}),xe}return dr(t.data)}}By.create=e=>new By({typeName:we.ZodVoid,...Ae(e)});class Di extends Oe{_parse(t){const{ctx:n,status:r}=this._processInputParams(t),i=this._def;if(n.parsedType!==le.array)return ce(n,{code:re.invalid_type,expected:le.array,received:n.parsedType}),xe;if(i.exactLength!==null){const s=n.data.length>i.exactLength.value,a=n.data.lengthi.maxLength.value&&(ce(n,{code:re.too_big,maximum:i.maxLength.value,type:"array",inclusive:!0,exact:!1,message:i.maxLength.message}),r.dirty()),n.common.async)return Promise.all([...n.data].map((s,a)=>i.type._parseAsync(new xo(n,s,n.path,a)))).then(s=>Qn.mergeArray(r,s));const o=[...n.data].map((s,a)=>i.type._parseSync(new xo(n,s,n.path,a)));return Qn.mergeArray(r,o)}get element(){return this._def.type}min(t,n){return new Di({...this._def,minLength:{value:t,message:ve.toString(n)}})}max(t,n){return new Di({...this._def,maxLength:{value:t,message:ve.toString(n)}})}length(t,n){return new Di({...this._def,exactLength:{value:t,message:ve.toString(n)}})}nonempty(t){return this.min(1,t)}}Di.create=(e,t)=>new Di({type:e,minLength:null,maxLength:null,exactLength:null,typeName:we.ZodArray,...Ae(t)});function vu(e){if(e instanceof Mt){const t={};for(const n in e.shape){const r=e.shape[n];t[n]=os.create(vu(r))}return new Mt({...e._def,shape:()=>t})}else return e instanceof Di?new Di({...e._def,type:vu(e.element)}):e instanceof os?os.create(vu(e.unwrap())):e instanceof Tl?Tl.create(vu(e.unwrap())):e instanceof Co?Co.create(e.items.map(t=>vu(t))):e}class Mt extends Oe{constructor(){super(...arguments),this._cached=null,this.nonstrict=this.passthrough,this.augment=this.extend}_getCached(){if(this._cached!==null)return this._cached;const t=this._def.shape(),n=Xe.objectKeys(t);return this._cached={shape:t,keys:n}}_parse(t){if(this._getType(t)!==le.object){const u=this._getOrReturnCtx(t);return ce(u,{code:re.invalid_type,expected:le.object,received:u.parsedType}),xe}const{status:r,ctx:i}=this._processInputParams(t),{shape:o,keys:s}=this._getCached(),a=[];if(!(this._def.catchall instanceof gs&&this._def.unknownKeys==="strip"))for(const u in i.data)s.includes(u)||a.push(u);const l=[];for(const u of s){const c=o[u],d=i.data[u];l.push({key:{status:"valid",value:u},value:c._parse(new xo(i,d,i.path,u)),alwaysSet:u in i.data})}if(this._def.catchall instanceof gs){const u=this._def.unknownKeys;if(u==="passthrough")for(const c of a)l.push({key:{status:"valid",value:c},value:{status:"valid",value:i.data[c]}});else if(u==="strict")a.length>0&&(ce(i,{code:re.unrecognized_keys,keys:a}),r.dirty());else if(u!=="strip")throw new Error("Internal ZodObject error: invalid unknownKeys value.")}else{const u=this._def.catchall;for(const c of a){const d=i.data[c];l.push({key:{status:"valid",value:c},value:u._parse(new xo(i,d,i.path,c)),alwaysSet:c in i.data})}}return i.common.async?Promise.resolve().then(async()=>{const u=[];for(const c of l){const d=await c.key;u.push({key:d,value:await c.value,alwaysSet:c.alwaysSet})}return u}).then(u=>Qn.mergeObjectSync(r,u)):Qn.mergeObjectSync(r,l)}get shape(){return this._def.shape()}strict(t){return ve.errToObj,new Mt({...this._def,unknownKeys:"strict",...t!==void 0?{errorMap:(n,r)=>{var i,o,s,a;const l=(s=(o=(i=this._def).errorMap)===null||o===void 0?void 0:o.call(i,n,r).message)!==null&&s!==void 0?s:r.defaultError;return n.code==="unrecognized_keys"?{message:(a=ve.errToObj(t).message)!==null&&a!==void 0?a:l}:{message:l}}}:{}})}strip(){return new Mt({...this._def,unknownKeys:"strip"})}passthrough(){return new Mt({...this._def,unknownKeys:"passthrough"})}extend(t){return new Mt({...this._def,shape:()=>({...this._def.shape(),...t})})}merge(t){return new Mt({unknownKeys:t._def.unknownKeys,catchall:t._def.catchall,shape:()=>({...this._def.shape(),...t._def.shape()}),typeName:we.ZodObject})}setKey(t,n){return this.augment({[t]:n})}catchall(t){return new Mt({...this._def,catchall:t})}pick(t){const n={};return Xe.objectKeys(t).forEach(r=>{t[r]&&this.shape[r]&&(n[r]=this.shape[r])}),new Mt({...this._def,shape:()=>n})}omit(t){const n={};return Xe.objectKeys(this.shape).forEach(r=>{t[r]||(n[r]=this.shape[r])}),new Mt({...this._def,shape:()=>n})}deepPartial(){return vu(this)}partial(t){const n={};return Xe.objectKeys(this.shape).forEach(r=>{const i=this.shape[r];t&&!t[r]?n[r]=i:n[r]=i.optional()}),new Mt({...this._def,shape:()=>n})}required(t){const n={};return Xe.objectKeys(this.shape).forEach(r=>{if(t&&!t[r])n[r]=this.shape[r];else{let o=this.shape[r];for(;o instanceof os;)o=o._def.innerType;n[r]=o}}),new Mt({...this._def,shape:()=>n})}keyof(){return ED(Xe.objectKeys(this.shape))}}Mt.create=(e,t)=>new Mt({shape:()=>e,unknownKeys:"strip",catchall:gs.create(),typeName:we.ZodObject,...Ae(t)});Mt.strictCreate=(e,t)=>new Mt({shape:()=>e,unknownKeys:"strict",catchall:gs.create(),typeName:we.ZodObject,...Ae(t)});Mt.lazycreate=(e,t)=>new Mt({shape:e,unknownKeys:"strip",catchall:gs.create(),typeName:we.ZodObject,...Ae(t)});class ph extends Oe{_parse(t){const{ctx:n}=this._processInputParams(t),r=this._def.options;function i(o){for(const a of o)if(a.result.status==="valid")return a.result;for(const a of o)if(a.result.status==="dirty")return n.common.issues.push(...a.ctx.common.issues),a.result;const s=o.map(a=>new Ni(a.ctx.common.issues));return ce(n,{code:re.invalid_union,unionErrors:s}),xe}if(n.common.async)return Promise.all(r.map(async o=>{const s={...n,common:{...n.common,issues:[]},parent:null};return{result:await o._parseAsync({data:n.data,path:n.path,parent:s}),ctx:s}})).then(i);{let o;const s=[];for(const l of r){const u={...n,common:{...n.common,issues:[]},parent:null},c=l._parseSync({data:n.data,path:n.path,parent:u});if(c.status==="valid")return c;c.status==="dirty"&&!o&&(o={result:c,ctx:u}),u.common.issues.length&&s.push(u.common.issues)}if(o)return n.common.issues.push(...o.ctx.common.issues),o.result;const a=s.map(l=>new Ni(l));return ce(n,{code:re.invalid_union,unionErrors:a}),xe}}get options(){return this._def.options}}ph.create=(e,t)=>new ph({options:e,typeName:we.ZodUnion,...Ae(t)});const _m=e=>e instanceof yh?_m(e.schema):e instanceof ji?_m(e.innerType()):e instanceof vh?[e.value]:e instanceof _a?e.options:e instanceof bh?Object.keys(e.enum):e instanceof Sh?_m(e._def.innerType):e instanceof fh?[void 0]:e instanceof hh?[null]:null;class Wv extends Oe{_parse(t){const{ctx:n}=this._processInputParams(t);if(n.parsedType!==le.object)return ce(n,{code:re.invalid_type,expected:le.object,received:n.parsedType}),xe;const r=this.discriminator,i=n.data[r],o=this.optionsMap.get(i);return o?n.common.async?o._parseAsync({data:n.data,path:n.path,parent:n}):o._parseSync({data:n.data,path:n.path,parent:n}):(ce(n,{code:re.invalid_union_discriminator,options:Array.from(this.optionsMap.keys()),path:[r]}),xe)}get discriminator(){return this._def.discriminator}get options(){return this._def.options}get optionsMap(){return this._def.optionsMap}static create(t,n,r){const i=new Map;for(const o of n){const s=_m(o.shape[t]);if(!s)throw new Error(`A discriminator value for key \`${t}\` could not be extracted from all schema options`);for(const a of s){if(i.has(a))throw new Error(`Discriminator property ${String(t)} has duplicate value ${String(a)}`);i.set(a,o)}}return new Wv({typeName:we.ZodDiscriminatedUnion,discriminator:t,options:n,optionsMap:i,...Ae(r)})}}function Vw(e,t){const n=qs(e),r=qs(t);if(e===t)return{valid:!0,data:e};if(n===le.object&&r===le.object){const i=Xe.objectKeys(t),o=Xe.objectKeys(e).filter(a=>i.indexOf(a)!==-1),s={...e,...t};for(const a of o){const l=Vw(e[a],t[a]);if(!l.valid)return{valid:!1};s[a]=l.data}return{valid:!0,data:s}}else if(n===le.array&&r===le.array){if(e.length!==t.length)return{valid:!1};const i=[];for(let o=0;o{if(Bw(o)||Bw(s))return xe;const a=Vw(o.value,s.value);return a.valid?((jw(o)||jw(s))&&n.dirty(),{status:n.value,value:a.data}):(ce(r,{code:re.invalid_intersection_types}),xe)};return r.common.async?Promise.all([this._def.left._parseAsync({data:r.data,path:r.path,parent:r}),this._def.right._parseAsync({data:r.data,path:r.path,parent:r})]).then(([o,s])=>i(o,s)):i(this._def.left._parseSync({data:r.data,path:r.path,parent:r}),this._def.right._parseSync({data:r.data,path:r.path,parent:r}))}}gh.create=(e,t,n)=>new gh({left:e,right:t,typeName:we.ZodIntersection,...Ae(n)});class Co extends Oe{_parse(t){const{status:n,ctx:r}=this._processInputParams(t);if(r.parsedType!==le.array)return ce(r,{code:re.invalid_type,expected:le.array,received:r.parsedType}),xe;if(r.data.lengththis._def.items.length&&(ce(r,{code:re.too_big,maximum:this._def.items.length,inclusive:!0,exact:!1,type:"array"}),n.dirty());const o=[...r.data].map((s,a)=>{const l=this._def.items[a]||this._def.rest;return l?l._parse(new xo(r,s,r.path,a)):null}).filter(s=>!!s);return r.common.async?Promise.all(o).then(s=>Qn.mergeArray(n,s)):Qn.mergeArray(n,o)}get items(){return this._def.items}rest(t){return new Co({...this._def,rest:t})}}Co.create=(e,t)=>{if(!Array.isArray(e))throw new Error("You must pass an array of schemas to z.tuple([ ... ])");return new Co({items:e,typeName:we.ZodTuple,rest:null,...Ae(t)})};class mh extends Oe{get keySchema(){return this._def.keyType}get valueSchema(){return this._def.valueType}_parse(t){const{status:n,ctx:r}=this._processInputParams(t);if(r.parsedType!==le.object)return ce(r,{code:re.invalid_type,expected:le.object,received:r.parsedType}),xe;const i=[],o=this._def.keyType,s=this._def.valueType;for(const a in r.data)i.push({key:o._parse(new xo(r,a,r.path,a)),value:s._parse(new xo(r,r.data[a],r.path,a))});return r.common.async?Qn.mergeObjectAsync(n,i):Qn.mergeObjectSync(n,i)}get element(){return this._def.valueType}static create(t,n,r){return n instanceof Oe?new mh({keyType:t,valueType:n,typeName:we.ZodRecord,...Ae(r)}):new mh({keyType:Oi.create(),valueType:t,typeName:we.ZodRecord,...Ae(n)})}}class jy extends Oe{_parse(t){const{status:n,ctx:r}=this._processInputParams(t);if(r.parsedType!==le.map)return ce(r,{code:re.invalid_type,expected:le.map,received:r.parsedType}),xe;const i=this._def.keyType,o=this._def.valueType,s=[...r.data.entries()].map(([a,l],u)=>({key:i._parse(new xo(r,a,r.path,[u,"key"])),value:o._parse(new xo(r,l,r.path,[u,"value"]))}));if(r.common.async){const a=new Map;return Promise.resolve().then(async()=>{for(const l of s){const u=await l.key,c=await l.value;if(u.status==="aborted"||c.status==="aborted")return xe;(u.status==="dirty"||c.status==="dirty")&&n.dirty(),a.set(u.value,c.value)}return{status:n.value,value:a}})}else{const a=new Map;for(const l of s){const u=l.key,c=l.value;if(u.status==="aborted"||c.status==="aborted")return xe;(u.status==="dirty"||c.status==="dirty")&&n.dirty(),a.set(u.value,c.value)}return{status:n.value,value:a}}}}jy.create=(e,t,n)=>new jy({valueType:t,keyType:e,typeName:we.ZodMap,...Ae(n)});class Cl extends Oe{_parse(t){const{status:n,ctx:r}=this._processInputParams(t);if(r.parsedType!==le.set)return ce(r,{code:re.invalid_type,expected:le.set,received:r.parsedType}),xe;const i=this._def;i.minSize!==null&&r.data.sizei.maxSize.value&&(ce(r,{code:re.too_big,maximum:i.maxSize.value,type:"set",inclusive:!0,exact:!1,message:i.maxSize.message}),n.dirty());const o=this._def.valueType;function s(l){const u=new Set;for(const c of l){if(c.status==="aborted")return xe;c.status==="dirty"&&n.dirty(),u.add(c.value)}return{status:n.value,value:u}}const a=[...r.data.values()].map((l,u)=>o._parse(new xo(r,l,r.path,u)));return r.common.async?Promise.all(a).then(l=>s(l)):s(a)}min(t,n){return new Cl({...this._def,minSize:{value:t,message:ve.toString(n)}})}max(t,n){return new Cl({...this._def,maxSize:{value:t,message:ve.toString(n)}})}size(t,n){return this.min(t,n).max(t,n)}nonempty(t){return this.min(1,t)}}Cl.create=(e,t)=>new Cl({valueType:e,minSize:null,maxSize:null,typeName:we.ZodSet,...Ae(t)});class rc extends Oe{constructor(){super(...arguments),this.validate=this.implement}_parse(t){const{ctx:n}=this._processInputParams(t);if(n.parsedType!==le.function)return ce(n,{code:re.invalid_type,expected:le.function,received:n.parsedType}),xe;function r(a,l){return Dy({data:a,path:n.path,errorMaps:[n.common.contextualErrorMap,n.schemaErrorMap,Ny(),ch].filter(u=>!!u),issueData:{code:re.invalid_arguments,argumentsError:l}})}function i(a,l){return Dy({data:a,path:n.path,errorMaps:[n.common.contextualErrorMap,n.schemaErrorMap,Ny(),ch].filter(u=>!!u),issueData:{code:re.invalid_return_type,returnTypeError:l}})}const o={errorMap:n.common.contextualErrorMap},s=n.data;return this._def.returns instanceof Ic?dr(async(...a)=>{const l=new Ni([]),u=await this._def.args.parseAsync(a,o).catch(f=>{throw l.addIssue(r(a,f)),l}),c=await s(...u);return await this._def.returns._def.type.parseAsync(c,o).catch(f=>{throw l.addIssue(i(c,f)),l})}):dr((...a)=>{const l=this._def.args.safeParse(a,o);if(!l.success)throw new Ni([r(a,l.error)]);const u=s(...l.data),c=this._def.returns.safeParse(u,o);if(!c.success)throw new Ni([i(u,c.error)]);return c.data})}parameters(){return this._def.args}returnType(){return this._def.returns}args(...t){return new rc({...this._def,args:Co.create(t).rest(cl.create())})}returns(t){return new rc({...this._def,returns:t})}implement(t){return this.parse(t)}strictImplement(t){return this.parse(t)}static create(t,n,r){return new rc({args:t||Co.create([]).rest(cl.create()),returns:n||cl.create(),typeName:we.ZodFunction,...Ae(r)})}}class yh extends Oe{get schema(){return this._def.getter()}_parse(t){const{ctx:n}=this._processInputParams(t);return this._def.getter()._parse({data:n.data,path:n.path,parent:n})}}yh.create=(e,t)=>new yh({getter:e,typeName:we.ZodLazy,...Ae(t)});class vh extends Oe{_parse(t){if(t.data!==this._def.value){const n=this._getOrReturnCtx(t);return ce(n,{received:n.data,code:re.invalid_literal,expected:this._def.value}),xe}return{status:"valid",value:t.data}}get value(){return this._def.value}}vh.create=(e,t)=>new vh({value:e,typeName:we.ZodLiteral,...Ae(t)});function ED(e,t){return new _a({values:e,typeName:we.ZodEnum,...Ae(t)})}class _a extends Oe{_parse(t){if(typeof t.data!="string"){const n=this._getOrReturnCtx(t),r=this._def.values;return ce(n,{expected:Xe.joinValues(r),received:n.parsedType,code:re.invalid_type}),xe}if(this._def.values.indexOf(t.data)===-1){const n=this._getOrReturnCtx(t),r=this._def.values;return ce(n,{received:n.data,code:re.invalid_enum_value,options:r}),xe}return dr(t.data)}get options(){return this._def.values}get enum(){const t={};for(const n of this._def.values)t[n]=n;return t}get Values(){const t={};for(const n of this._def.values)t[n]=n;return t}get Enum(){const t={};for(const n of this._def.values)t[n]=n;return t}extract(t){return _a.create(t)}exclude(t){return _a.create(this.options.filter(n=>!t.includes(n)))}}_a.create=ED;class bh extends Oe{_parse(t){const n=Xe.getValidEnumValues(this._def.values),r=this._getOrReturnCtx(t);if(r.parsedType!==le.string&&r.parsedType!==le.number){const i=Xe.objectValues(n);return ce(r,{expected:Xe.joinValues(i),received:r.parsedType,code:re.invalid_type}),xe}if(n.indexOf(t.data)===-1){const i=Xe.objectValues(n);return ce(r,{received:r.data,code:re.invalid_enum_value,options:i}),xe}return dr(t.data)}get enum(){return this._def.values}}bh.create=(e,t)=>new bh({values:e,typeName:we.ZodNativeEnum,...Ae(t)});class Ic extends Oe{unwrap(){return this._def.type}_parse(t){const{ctx:n}=this._processInputParams(t);if(n.parsedType!==le.promise&&n.common.async===!1)return ce(n,{code:re.invalid_type,expected:le.promise,received:n.parsedType}),xe;const r=n.parsedType===le.promise?n.data:Promise.resolve(n.data);return dr(r.then(i=>this._def.type.parseAsync(i,{path:n.path,errorMap:n.common.contextualErrorMap})))}}Ic.create=(e,t)=>new Ic({type:e,typeName:we.ZodPromise,...Ae(t)});class ji extends Oe{innerType(){return this._def.schema}sourceType(){return this._def.schema._def.typeName===we.ZodEffects?this._def.schema.sourceType():this._def.schema}_parse(t){const{status:n,ctx:r}=this._processInputParams(t),i=this._def.effect||null;if(i.type==="preprocess"){const s=i.transform(r.data);return r.common.async?Promise.resolve(s).then(a=>this._def.schema._parseAsync({data:a,path:r.path,parent:r})):this._def.schema._parseSync({data:s,path:r.path,parent:r})}const o={addIssue:s=>{ce(r,s),s.fatal?n.abort():n.dirty()},get path(){return r.path}};if(o.addIssue=o.addIssue.bind(o),i.type==="refinement"){const s=a=>{const l=i.refinement(a,o);if(r.common.async)return Promise.resolve(l);if(l instanceof Promise)throw new Error("Async refinement encountered during synchronous parse operation. Use .parseAsync instead.");return a};if(r.common.async===!1){const a=this._def.schema._parseSync({data:r.data,path:r.path,parent:r});return a.status==="aborted"?xe:(a.status==="dirty"&&n.dirty(),s(a.value),{status:n.value,value:a.value})}else return this._def.schema._parseAsync({data:r.data,path:r.path,parent:r}).then(a=>a.status==="aborted"?xe:(a.status==="dirty"&&n.dirty(),s(a.value).then(()=>({status:n.value,value:a.value}))))}if(i.type==="transform")if(r.common.async===!1){const s=this._def.schema._parseSync({data:r.data,path:r.path,parent:r});if(!Ly(s))return s;const a=i.transform(s.value,o);if(a instanceof Promise)throw new Error("Asynchronous transform encountered during synchronous parse operation. 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n.count!="string",x=c0.hasDefaultValue(n),C=w?this.pluralResolver.getSuffix(u,n.count,n):"",k=n.ordinal&&w?this.pluralResolver.getSuffix(u,n.count,{ordinal:!1}):"",P=n[`defaultValue${C}`]||n[`defaultValue${k}`]||n.defaultValue;!this.isValidLookup(f)&&x&&(b=!0,f=P),this.isValidLookup(f)||(_=!0,f=s);const $=(n.missingKeyNoValueFallbackToKey||this.options.missingKeyNoValueFallbackToKey)&&_?void 0:f,N=x&&P!==f&&this.options.updateMissing;if(_||b||N){if(this.logger.log(N?"updateKey":"missingKey",u,l,s,N?P:f),o){const M=this.resolve(s,{...n,keySeparator:!1});M&&M.res&&this.logger.warn("Seems the loaded translations were in flat JSON format instead of nested. Either set keySeparator: false on init or make sure your translations are published in nested format.")}let T=[];const O=this.languageUtils.getFallbackCodes(this.options.fallbackLng,n.lng||this.language);if(this.options.saveMissingTo==="fallback"&&O&&O[0])for(let M=0;M{const L=x&&D!==f?D:$;this.options.missingKeyHandler?this.options.missingKeyHandler(M,l,R,L,N,n):this.backendConnector&&this.backendConnector.saveMissing&&this.backendConnector.saveMissing(M,l,R,L,N,n),this.emit("missingKey",M,l,R,f)};this.options.saveMissing&&(this.options.saveMissingPlurals&&w?T.forEach(M=>{this.pluralResolver.getSuffixes(M,n).forEach(R=>{I([M],s+R,n[`defaultValue${R}`]||P)})}):I(T,s,P))}f=this.extendTranslation(f,t,n,d,r),_&&f===s&&this.options.appendNamespaceToMissingKey&&(f=`${l}:${s}`),(_||b)&&this.options.parseMissingKeyHandler&&(this.options.compatibilityAPI!=="v1"?f=this.options.parseMissingKeyHandler(this.options.appendNamespaceToMissingKey?`${l}:${s}`:s,b?f:void 0):f=this.options.parseMissingKeyHandler(f))}return i?(d.res=f,d):f}extendTranslation(t,n,r,i,o){var s=this;if(this.i18nFormat&&this.i18nFormat.parse)t=this.i18nFormat.parse(t,{...this.options.interpolation.defaultVariables,...r},i.usedLng,i.usedNS,i.usedKey,{resolved:i});else if(!r.skipInterpolation){r.interpolation&&this.interpolator.init({...r,interpolation:{...this.options.interpolation,...r.interpolation}});const u=typeof t=="string"&&(r&&r.interpolation&&r.interpolation.skipOnVariables!==void 0?r.interpolation.skipOnVariables:this.options.interpolation.skipOnVariables);let c;if(u){const f=t.match(this.interpolator.nestingRegexp);c=f&&f.length}let d=r.replace&&typeof r.replace!="string"?r.replace:r;if(this.options.interpolation.defaultVariables&&(d={...this.options.interpolation.defaultVariables,...d}),t=this.interpolator.interpolate(t,d,r.lng||this.language,r),u){const f=t.match(this.interpolator.nestingRegexp),h=f&&f.length;c1&&arguments[1]!==void 0?arguments[1]:{},r,i,o,s,a;return typeof t=="string"&&(t=[t]),t.forEach(l=>{if(this.isValidLookup(r))return;const u=this.extractFromKey(l,n),c=u.key;i=c;let d=u.namespaces;this.options.fallbackNS&&(d=d.concat(this.options.fallbackNS));const f=n.count!==void 0&&typeof n.count!="string",h=f&&!n.ordinal&&n.count===0&&this.pluralResolver.shouldUseIntlApi(),p=n.context!==void 0&&(typeof n.context=="string"||typeof n.context=="number")&&n.context!=="",m=n.lngs?n.lngs:this.languageUtils.toResolveHierarchy(n.lng||this.language,n.fallbackLng);d.forEach(S=>{this.isValidLookup(r)||(a=S,!Tk[`${m[0]}-${S}`]&&this.utils&&this.utils.hasLoadedNamespace&&!this.utils.hasLoadedNamespace(a)&&(Tk[`${m[0]}-${S}`]=!0,this.logger.warn(`key "${i}" for languages "${m.join(", ")}" won't get resolved as namespace "${a}" was not yet loaded`,"This means something IS WRONG in your setup. You access the t function before i18next.init / i18next.loadNamespace / i18next.changeLanguage was done. Wait for the callback or Promise to resolve before accessing it!!!")),m.forEach(v=>{if(this.isValidLookup(r))return;s=v;const y=[c];if(this.i18nFormat&&this.i18nFormat.addLookupKeys)this.i18nFormat.addLookupKeys(y,c,v,S,n);else{let b;f&&(b=this.pluralResolver.getSuffix(v,n.count,n));const _=`${this.options.pluralSeparator}zero`,w=`${this.options.pluralSeparator}ordinal${this.options.pluralSeparator}`;if(f&&(y.push(c+b),n.ordinal&&b.indexOf(w)===0&&y.push(c+b.replace(w,this.options.pluralSeparator)),h&&y.push(c+_)),p){const x=`${c}${this.options.contextSeparator}${n.context}`;y.push(x),f&&(y.push(x+b),n.ordinal&&b.indexOf(w)===0&&y.push(x+b.replace(w,this.options.pluralSeparator)),h&&y.push(x+_))}}let g;for(;g=y.pop();)this.isValidLookup(r)||(o=g,r=this.getResource(v,S,g,n))}))})}),{res:r,usedKey:i,exactUsedKey:o,usedLng:s,usedNS:a}}isValidLookup(t){return t!==void 0&&!(!this.options.returnNull&&t===null)&&!(!this.options.returnEmptyString&&t==="")}getResource(t,n,r){let i=arguments.length>3&&arguments[3]!==void 0?arguments[3]:{};return this.i18nFormat&&this.i18nFormat.getResource?this.i18nFormat.getResource(t,n,r,i):this.resourceStore.getResource(t,n,r,i)}static hasDefaultValue(t){const n="defaultValue";for(const r in t)if(Object.prototype.hasOwnProperty.call(t,r)&&n===r.substring(0,n.length)&&t[r]!==void 0)return!0;return!1}}function x_(e){return e.charAt(0).toUpperCase()+e.slice(1)}class Ek{constructor(t){this.options=t,this.supportedLngs=this.options.supportedLngs||!1,this.logger=fo.create("languageUtils")}getScriptPartFromCode(t){if(t=gx(t),!t||t.indexOf("-")<0)return null;const n=t.split("-");return n.length===2||(n.pop(),n[n.length-1].toLowerCase()==="x")?null:this.formatLanguageCode(n.join("-"))}getLanguagePartFromCode(t){if(t=gx(t),!t||t.indexOf("-")<0)return t;const n=t.split("-");return this.formatLanguageCode(n[0])}formatLanguageCode(t){if(typeof t=="string"&&t.indexOf("-")>-1){const n=["hans","hant","latn","cyrl","cans","mong","arab"];let r=t.split("-");return this.options.lowerCaseLng?r=r.map(i=>i.toLowerCase()):r.length===2?(r[0]=r[0].toLowerCase(),r[1]=r[1].toUpperCase(),n.indexOf(r[1].toLowerCase())>-1&&(r[1]=x_(r[1].toLowerCase()))):r.length===3&&(r[0]=r[0].toLowerCase(),r[1].length===2&&(r[1]=r[1].toUpperCase()),r[0]!=="sgn"&&r[2].length===2&&(r[2]=r[2].toUpperCase()),n.indexOf(r[1].toLowerCase())>-1&&(r[1]=x_(r[1].toLowerCase())),n.indexOf(r[2].toLowerCase())>-1&&(r[2]=x_(r[2].toLowerCase()))),r.join("-")}return this.options.cleanCode||this.options.lowerCaseLng?t.toLowerCase():t}isSupportedCode(t){return(this.options.load==="languageOnly"||this.options.nonExplicitSupportedLngs)&&(t=this.getLanguagePartFromCode(t)),!this.supportedLngs||!this.supportedLngs.length||this.supportedLngs.indexOf(t)>-1}getBestMatchFromCodes(t){if(!t)return null;let n;return t.forEach(r=>{if(n)return;const i=this.formatLanguageCode(r);(!this.options.supportedLngs||this.isSupportedCode(i))&&(n=i)}),!n&&this.options.supportedLngs&&t.forEach(r=>{if(n)return;const i=this.getLanguagePartFromCode(r);if(this.isSupportedCode(i))return n=i;n=this.options.supportedLngs.find(o=>{if(o===i)return o;if(!(o.indexOf("-")<0&&i.indexOf("-")<0)&&o.indexOf(i)===0)return o})}),n||(n=this.getFallbackCodes(this.options.fallbackLng)[0]),n}getFallbackCodes(t,n){if(!t)return[];if(typeof t=="function"&&(t=t(n)),typeof t=="string"&&(t=[t]),Object.prototype.toString.apply(t)==="[object Array]")return t;if(!n)return t.default||[];let r=t[n];return r||(r=t[this.getScriptPartFromCode(n)]),r||(r=t[this.formatLanguageCode(n)]),r||(r=t[this.getLanguagePartFromCode(n)]),r||(r=t.default),r||[]}toResolveHierarchy(t,n){const r=this.getFallbackCodes(n||this.options.fallbackLng||[],t),i=[],o=s=>{s&&(this.isSupportedCode(s)?i.push(s):this.logger.warn(`rejecting language code not found in supportedLngs: ${s}`))};return typeof t=="string"&&(t.indexOf("-")>-1||t.indexOf("_")>-1)?(this.options.load!=="languageOnly"&&o(this.formatLanguageCode(t)),this.options.load!=="languageOnly"&&this.options.load!=="currentOnly"&&o(this.getScriptPartFromCode(t)),this.options.load!=="currentOnly"&&o(this.getLanguagePartFromCode(t))):typeof t=="string"&&o(this.formatLanguageCode(t)),r.forEach(s=>{i.indexOf(s)<0&&o(this.formatLanguageCode(s))}),i}}let $1e=[{lngs:["ach","ak","am","arn","br","fil","gun","ln","mfe","mg","mi","oc","pt","pt-BR","tg","tl","ti","tr","uz","wa"],nr:[1,2],fc:1},{lngs:["af","an","ast","az","bg","bn","ca","da","de","dev","el","en","eo","es","et","eu","fi","fo","fur","fy","gl","gu","ha","hi","hu","hy","ia","it","kk","kn","ku","lb","mai","ml","mn","mr","nah","nap","nb","ne","nl","nn","no","nso","pa","pap","pms","ps","pt-PT","rm","sco","se","si","so","son","sq","sv","sw","ta","te","tk","ur","yo"],nr:[1,2],fc:2},{lngs:["ay","bo","cgg","fa","ht","id","ja","jbo","ka","km","ko","ky","lo","ms","sah","su","th","tt","ug","vi","wo","zh"],nr:[1],fc:3},{lngs:["be","bs","cnr","dz","hr","ru","sr","uk"],nr:[1,2,5],fc:4},{lngs:["ar"],nr:[0,1,2,3,11,100],fc:5},{lngs:["cs","sk"],nr:[1,2,5],fc:6},{lngs:["csb","pl"],nr:[1,2,5],fc:7},{lngs:["cy"],nr:[1,2,3,8],fc:8},{lngs:["fr"],nr:[1,2],fc:9},{lngs:["ga"],nr:[1,2,3,7,11],fc:10},{lngs:["gd"],nr:[1,2,3,20],fc:11},{lngs:["is"],nr:[1,2],fc:12},{lngs:["jv"],nr:[0,1],fc:13},{lngs:["kw"],nr:[1,2,3,4],fc:14},{lngs:["lt"],nr:[1,2,10],fc:15},{lngs:["lv"],nr:[1,2,0],fc:16},{lngs:["mk"],nr:[1,2],fc:17},{lngs:["mnk"],nr:[0,1,2],fc:18},{lngs:["mt"],nr:[1,2,11,20],fc:19},{lngs:["or"],nr:[2,1],fc:2},{lngs:["ro"],nr:[1,2,20],fc:20},{lngs:["sl"],nr:[5,1,2,3],fc:21},{lngs:["he","iw"],nr:[1,2,20,21],fc:22}],F1e={1:function(e){return+(e>1)},2:function(e){return+(e!=1)},3:function(e){return 0},4:function(e){return e%10==1&&e%100!=11?0:e%10>=2&&e%10<=4&&(e%100<10||e%100>=20)?1:2},5:function(e){return e==0?0:e==1?1:e==2?2:e%100>=3&&e%100<=10?3:e%100>=11?4:5},6:function(e){return e==1?0:e>=2&&e<=4?1:2},7:function(e){return e==1?0:e%10>=2&&e%10<=4&&(e%100<10||e%100>=20)?1:2},8:function(e){return e==1?0:e==2?1:e!=8&&e!=11?2:3},9:function(e){return+(e>=2)},10:function(e){return e==1?0:e==2?1:e<7?2:e<11?3:4},11:function(e){return e==1||e==11?0:e==2||e==12?1:e>2&&e<20?2:3},12:function(e){return+(e%10!=1||e%100==11)},13:function(e){return+(e!==0)},14:function(e){return e==1?0:e==2?1:e==3?2:3},15:function(e){return e%10==1&&e%100!=11?0:e%10>=2&&(e%100<10||e%100>=20)?1:2},16:function(e){return e%10==1&&e%100!=11?0:e!==0?1:2},17:function(e){return e==1||e%10==1&&e%100!=11?0:1},18:function(e){return e==0?0:e==1?1:2},19:function(e){return e==1?0:e==0||e%100>1&&e%100<11?1:e%100>10&&e%100<20?2:3},20:function(e){return e==1?0:e==0||e%100>0&&e%100<20?1:2},21:function(e){return e%100==1?1:e%100==2?2:e%100==3||e%100==4?3:0},22:function(e){return e==1?0:e==2?1:(e<0||e>10)&&e%10==0?2:3}};const B1e=["v1","v2","v3"],j1e=["v4"],Pk={zero:0,one:1,two:2,few:3,many:4,other:5};function V1e(){const e={};return $1e.forEach(t=>{t.lngs.forEach(n=>{e[n]={numbers:t.nr,plurals:F1e[t.fc]}})}),e}class z1e{constructor(t){let n=arguments.length>1&&arguments[1]!==void 0?arguments[1]:{};this.languageUtils=t,this.options=n,this.logger=fo.create("pluralResolver"),(!this.options.compatibilityJSON||j1e.includes(this.options.compatibilityJSON))&&(typeof Intl>"u"||!Intl.PluralRules)&&(this.options.compatibilityJSON="v3",this.logger.error("Your environment seems not to be Intl API compatible, use an Intl.PluralRules polyfill. Will fallback to the compatibilityJSON v3 format handling.")),this.rules=V1e()}addRule(t,n){this.rules[t]=n}getRule(t){let n=arguments.length>1&&arguments[1]!==void 0?arguments[1]:{};if(this.shouldUseIntlApi())try{return new Intl.PluralRules(gx(t),{type:n.ordinal?"ordinal":"cardinal"})}catch{return}return this.rules[t]||this.rules[this.languageUtils.getLanguagePartFromCode(t)]}needsPlural(t){let n=arguments.length>1&&arguments[1]!==void 0?arguments[1]:{};const r=this.getRule(t,n);return this.shouldUseIntlApi()?r&&r.resolvedOptions().pluralCategories.length>1:r&&r.numbers.length>1}getPluralFormsOfKey(t,n){let r=arguments.length>2&&arguments[2]!==void 0?arguments[2]:{};return this.getSuffixes(t,r).map(i=>`${n}${i}`)}getSuffixes(t){let n=arguments.length>1&&arguments[1]!==void 0?arguments[1]:{};const r=this.getRule(t,n);return r?this.shouldUseIntlApi()?r.resolvedOptions().pluralCategories.sort((i,o)=>Pk[i]-Pk[o]).map(i=>`${this.options.prepend}${n.ordinal?`ordinal${this.options.prepend}`:""}${i}`):r.numbers.map(i=>this.getSuffix(t,i,n)):[]}getSuffix(t,n){let r=arguments.length>2&&arguments[2]!==void 0?arguments[2]:{};const i=this.getRule(t,r);return i?this.shouldUseIntlApi()?`${this.options.prepend}${r.ordinal?`ordinal${this.options.prepend}`:""}${i.select(n)}`:this.getSuffixRetroCompatible(i,n):(this.logger.warn(`no plural rule found for: ${t}`),"")}getSuffixRetroCompatible(t,n){const r=t.noAbs?t.plurals(n):t.plurals(Math.abs(n));let i=t.numbers[r];this.options.simplifyPluralSuffix&&t.numbers.length===2&&t.numbers[0]===1&&(i===2?i="plural":i===1&&(i=""));const o=()=>this.options.prepend&&i.toString()?this.options.prepend+i.toString():i.toString();return this.options.compatibilityJSON==="v1"?i===1?"":typeof i=="number"?`_plural_${i.toString()}`:o():this.options.compatibilityJSON==="v2"||this.options.simplifyPluralSuffix&&t.numbers.length===2&&t.numbers[0]===1?o():this.options.prepend&&r.toString()?this.options.prepend+r.toString():r.toString()}shouldUseIntlApi(){return!B1e.includes(this.options.compatibilityJSON)}}function kk(e,t,n){let r=arguments.length>3&&arguments[3]!==void 0?arguments[3]:".",i=arguments.length>4&&arguments[4]!==void 0?arguments[4]:!0,o=I1e(e,t,n);return!o&&i&&typeof n=="string"&&(o=u0(e,n,r),o===void 0&&(o=u0(t,n,r))),o}class U1e{constructor(){let t=arguments.length>0&&arguments[0]!==void 0?arguments[0]:{};this.logger=fo.create("interpolator"),this.options=t,this.format=t.interpolation&&t.interpolation.format||(n=>n),this.init(t)}init(){let t=arguments.length>0&&arguments[0]!==void 0?arguments[0]:{};t.interpolation||(t.interpolation={escapeValue:!0});const n=t.interpolation;this.escape=n.escape!==void 0?n.escape:N1e,this.escapeValue=n.escapeValue!==void 0?n.escapeValue:!0,this.useRawValueToEscape=n.useRawValueToEscape!==void 0?n.useRawValueToEscape:!1,this.prefix=n.prefix?du(n.prefix):n.prefixEscaped||"{{",this.suffix=n.suffix?du(n.suffix):n.suffixEscaped||"}}",this.formatSeparator=n.formatSeparator?n.formatSeparator:n.formatSeparator||",",this.unescapePrefix=n.unescapeSuffix?"":n.unescapePrefix||"-",this.unescapeSuffix=this.unescapePrefix?"":n.unescapeSuffix||"",this.nestingPrefix=n.nestingPrefix?du(n.nestingPrefix):n.nestingPrefixEscaped||du("$t("),this.nestingSuffix=n.nestingSuffix?du(n.nestingSuffix):n.nestingSuffixEscaped||du(")"),this.nestingOptionsSeparator=n.nestingOptionsSeparator?n.nestingOptionsSeparator:n.nestingOptionsSeparator||",",this.maxReplaces=n.maxReplaces?n.maxReplaces:1e3,this.alwaysFormat=n.alwaysFormat!==void 0?n.alwaysFormat:!1,this.resetRegExp()}reset(){this.options&&this.init(this.options)}resetRegExp(){const t=`${this.prefix}(.+?)${this.suffix}`;this.regexp=new RegExp(t,"g");const n=`${this.prefix}${this.unescapePrefix}(.+?)${this.unescapeSuffix}${this.suffix}`;this.regexpUnescape=new RegExp(n,"g");const r=`${this.nestingPrefix}(.+?)${this.nestingSuffix}`;this.nestingRegexp=new RegExp(r,"g")}interpolate(t,n,r,i){let o,s,a;const l=this.options&&this.options.interpolation&&this.options.interpolation.defaultVariables||{};function u(p){return p.replace(/\$/g,"$$$$")}const c=p=>{if(p.indexOf(this.formatSeparator)<0){const y=kk(n,l,p,this.options.keySeparator,this.options.ignoreJSONStructure);return this.alwaysFormat?this.format(y,void 0,r,{...i,...n,interpolationkey:p}):y}const m=p.split(this.formatSeparator),S=m.shift().trim(),v=m.join(this.formatSeparator).trim();return this.format(kk(n,l,S,this.options.keySeparator,this.options.ignoreJSONStructure),v,r,{...i,...n,interpolationkey:S})};this.resetRegExp();const d=i&&i.missingInterpolationHandler||this.options.missingInterpolationHandler,f=i&&i.interpolation&&i.interpolation.skipOnVariables!==void 0?i.interpolation.skipOnVariables:this.options.interpolation.skipOnVariables;return[{regex:this.regexpUnescape,safeValue:p=>u(p)},{regex:this.regexp,safeValue:p=>this.escapeValue?u(this.escape(p)):u(p)}].forEach(p=>{for(a=0;o=p.regex.exec(t);){const m=o[1].trim();if(s=c(m),s===void 0)if(typeof d=="function"){const v=d(t,o,i);s=typeof v=="string"?v:""}else if(i&&Object.prototype.hasOwnProperty.call(i,m))s="";else if(f){s=o[0];continue}else this.logger.warn(`missed to pass in variable ${m} for interpolating ${t}`),s="";else typeof s!="string"&&!this.useRawValueToEscape&&(s=wk(s));const S=p.safeValue(s);if(t=t.replace(o[0],S),f?(p.regex.lastIndex+=s.length,p.regex.lastIndex-=o[0].length):p.regex.lastIndex=0,a++,a>=this.maxReplaces)break}}),t}nest(t,n){let r=arguments.length>2&&arguments[2]!==void 0?arguments[2]:{},i,o,s;function a(l,u){const c=this.nestingOptionsSeparator;if(l.indexOf(c)<0)return l;const d=l.split(new RegExp(`${c}[ ]*{`));let f=`{${d[1]}`;l=d[0],f=this.interpolate(f,s);const h=f.match(/'/g),p=f.match(/"/g);(h&&h.length%2===0&&!p||p.length%2!==0)&&(f=f.replace(/'/g,'"'));try{s=JSON.parse(f),u&&(s={...u,...s})}catch(m){return this.logger.warn(`failed parsing options string in nesting for key ${l}`,m),`${l}${c}${f}`}return delete s.defaultValue,l}for(;i=this.nestingRegexp.exec(t);){let l=[];s={...r},s=s.replace&&typeof s.replace!="string"?s.replace:s,s.applyPostProcessor=!1,delete s.defaultValue;let u=!1;if(i[0].indexOf(this.formatSeparator)!==-1&&!/{.*}/.test(i[1])){const c=i[1].split(this.formatSeparator).map(d=>d.trim());i[1]=c.shift(),l=c,u=!0}if(o=n(a.call(this,i[1].trim(),s),s),o&&i[0]===t&&typeof o!="string")return o;typeof o!="string"&&(o=wk(o)),o||(this.logger.warn(`missed to resolve ${i[1]} for nesting ${t}`),o=""),u&&(o=l.reduce((c,d)=>this.format(c,d,r.lng,{...r,interpolationkey:i[1].trim()}),o.trim())),t=t.replace(i[0],o),this.regexp.lastIndex=0}return t}}function G1e(e){let t=e.toLowerCase().trim();const n={};if(e.indexOf("(")>-1){const r=e.split("(");t=r[0].toLowerCase().trim();const i=r[1].substring(0,r[1].length-1);t==="currency"&&i.indexOf(":")<0?n.currency||(n.currency=i.trim()):t==="relativetime"&&i.indexOf(":")<0?n.range||(n.range=i.trim()):i.split(";").forEach(s=>{if(!s)return;const[a,...l]=s.split(":"),u=l.join(":").trim().replace(/^'+|'+$/g,"");n[a.trim()]||(n[a.trim()]=u),u==="false"&&(n[a.trim()]=!1),u==="true"&&(n[a.trim()]=!0),isNaN(u)||(n[a.trim()]=parseInt(u,10))})}return{formatName:t,formatOptions:n}}function fu(e){const t={};return function(r,i,o){const s=i+JSON.stringify(o);let a=t[s];return a||(a=e(i,o),t[s]=a),a(r)}}class H1e{constructor(){let t=arguments.length>0&&arguments[0]!==void 0?arguments[0]:{};this.logger=fo.create("formatter"),this.options=t,this.formats={number:fu((n,r)=>{const i=new Intl.NumberFormat(n,{...r});return o=>i.format(o)}),currency:fu((n,r)=>{const i=new Intl.NumberFormat(n,{...r,style:"currency"});return 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0&&(l[d]=!0)))}),c||(a[u]=!0)}),(Object.keys(o).length||Object.keys(s).length)&&this.queue.push({pending:s,pendingCount:Object.keys(s).length,loaded:{},errors:[],callback:i}),{toLoad:Object.keys(o),pending:Object.keys(s),toLoadLanguages:Object.keys(a),toLoadNamespaces:Object.keys(l)}}loaded(t,n,r){const i=t.split("|"),o=i[0],s=i[1];n&&this.emit("failedLoading",o,s,n),r&&this.store.addResourceBundle(o,s,r),this.state[t]=n?-1:2;const a={};this.queue.forEach(l=>{R1e(l.loaded,[o],s),q1e(l,t),n&&l.errors.push(n),l.pendingCount===0&&!l.done&&(Object.keys(l.loaded).forEach(u=>{a[u]||(a[u]={});const c=l.loaded[u];c.length&&c.forEach(d=>{a[u][d]===void 0&&(a[u][d]=!0)})}),l.done=!0,l.errors.length?l.callback(l.errors):l.callback())}),this.emit("loaded",a),this.queue=this.queue.filter(l=>!l.done)}read(t,n,r){let i=arguments.length>3&&arguments[3]!==void 0?arguments[3]:0,o=arguments.length>4&&arguments[4]!==void 0?arguments[4]:this.retryTimeout,s=arguments.length>5?arguments[5]:void 0;if(!t.length)return s(null,{});if(this.readingCalls>=this.maxParallelReads){this.waitingReads.push({lng:t,ns:n,fcName:r,tried:i,wait:o,callback:s});return}this.readingCalls++;const a=(u,c)=>{if(this.readingCalls--,this.waitingReads.length>0){const d=this.waitingReads.shift();this.read(d.lng,d.ns,d.fcName,d.tried,d.wait,d.callback)}if(u&&c&&i{this.read.call(this,t,n,r,i+1,o*2,s)},o);return}s(u,c)},l=this.backend[r].bind(this.backend);if(l.length===2){try{const u=l(t,n);u&&typeof u.then=="function"?u.then(c=>a(null,c)).catch(a):a(null,u)}catch(u){a(u)}return}return l(t,n,a)}prepareLoading(t,n){let r=arguments.length>2&&arguments[2]!==void 0?arguments[2]:{},i=arguments.length>3?arguments[3]:void 0;if(!this.backend)return this.logger.warn("No backend was added via i18next.use. Will not load resources."),i&&i();typeof t=="string"&&(t=this.languageUtils.toResolveHierarchy(t)),typeof n=="string"&&(n=[n]);const o=this.queueLoad(t,n,r,i);if(!o.toLoad.length)return o.pending.length||i(),null;o.toLoad.forEach(s=>{this.loadOne(s)})}load(t,n,r){this.prepareLoading(t,n,{},r)}reload(t,n,r){this.prepareLoading(t,n,{reload:!0},r)}loadOne(t){let n=arguments.length>1&&arguments[1]!==void 0?arguments[1]:"";const r=t.split("|"),i=r[0],o=r[1];this.read(i,o,"read",void 0,void 0,(s,a)=>{s&&this.logger.warn(`${n}loading namespace ${o} for language ${i} failed`,s),!s&&a&&this.logger.log(`${n}loaded namespace ${o} for language ${i}`,a),this.loaded(t,s,a)})}saveMissing(t,n,r,i,o){let s=arguments.length>5&&arguments[5]!==void 0?arguments[5]:{},a=arguments.length>6&&arguments[6]!==void 0?arguments[6]:()=>{};if(this.services.utils&&this.services.utils.hasLoadedNamespace&&!this.services.utils.hasLoadedNamespace(n)){this.logger.warn(`did not save key "${r}" as the namespace "${n}" was not yet loaded`,"This means something IS WRONG in your setup. You access the t function before i18next.init / i18next.loadNamespace / i18next.changeLanguage was done. Wait for the callback or Promise to resolve before accessing it!!!");return}if(!(r==null||r==="")){if(this.backend&&this.backend.create){const l={...s,isUpdate:o},u=this.backend.create.bind(this.backend);if(u.length<6)try{let c;u.length===5?c=u(t,n,r,i,l):c=u(t,n,r,i),c&&typeof c.then=="function"?c.then(d=>a(null,d)).catch(a):a(null,c)}catch(c){a(c)}else u(t,n,r,i,a,l)}!t||!t[0]||this.store.addResource(t[0],n,r,i)}}}function Ak(){return{debug:!1,initImmediate:!0,ns:["translation"],defaultNS:["translation"],fallbackLng:["dev"],fallbackNS:!1,supportedLngs:!1,nonExplicitSupportedLngs:!1,load:"all",preload:!1,simplifyPluralSuffix:!0,keySeparator:".",nsSeparator:":",pluralSeparator:"_",contextSeparator:"_",partialBundledLanguages:!1,saveMissing:!1,updateMissing:!1,saveMissingTo:"fallback",saveMissingPlurals:!0,missingKeyHandler:!1,missingInterpolationHandler:!1,postProcess:!1,postProcessPassResolved:!1,returnNull:!1,returnEmptyString:!0,returnObjects:!1,joinArrays:!1,returnedObjectHandler:!1,parseMissingKeyHandler:!1,appendNamespaceToMissingKey:!1,appendNamespaceToCIMode:!1,overloadTranslationOptionHandler:function(t){let n={};if(typeof t[1]=="object"&&(n=t[1]),typeof t[1]=="string"&&(n.defaultValue=t[1]),typeof t[2]=="string"&&(n.tDescription=t[2]),typeof t[2]=="object"||typeof t[3]=="object"){const r=t[3]||t[2];Object.keys(r).forEach(i=>{n[i]=r[i]})}return n},interpolation:{escapeValue:!0,format:(e,t,n,r)=>e,prefix:"{{",suffix:"}}",formatSeparator:",",unescapePrefix:"-",nestingPrefix:"$t(",nestingSuffix:")",nestingOptionsSeparator:",",maxReplaces:1e3,skipOnVariables:!0}}}function Ok(e){return typeof e.ns=="string"&&(e.ns=[e.ns]),typeof e.fallbackLng=="string"&&(e.fallbackLng=[e.fallbackLng]),typeof e.fallbackNS=="string"&&(e.fallbackNS=[e.fallbackNS]),e.supportedLngs&&e.supportedLngs.indexOf("cimode")<0&&(e.supportedLngs=e.supportedLngs.concat(["cimode"])),e}function Dg(){}function K1e(e){Object.getOwnPropertyNames(Object.getPrototypeOf(e)).forEach(n=>{typeof e[n]=="function"&&(e[n]=e[n].bind(e))})}class Lh extends T1{constructor(){let t=arguments.length>0&&arguments[0]!==void 0?arguments[0]:{},n=arguments.length>1?arguments[1]:void 0;if(super(),this.options=Ok(t),this.services={},this.logger=fo,this.modules={external:[]},K1e(this),n&&!this.isInitialized&&!t.isClone){if(!this.options.initImmediate)return this.init(t,n),this;setTimeout(()=>{this.init(t,n)},0)}}init(){var t=this;let n=arguments.length>0&&arguments[0]!==void 0?arguments[0]:{},r=arguments.length>1?arguments[1]:void 0;typeof n=="function"&&(r=n,n={}),!n.defaultNS&&n.defaultNS!==!1&&n.ns&&(typeof n.ns=="string"?n.defaultNS=n.ns:n.ns.indexOf("translation")<0&&(n.defaultNS=n.ns[0]));const i=Ak();this.options={...i,...this.options,...Ok(n)},this.options.compatibilityAPI!=="v1"&&(this.options.interpolation={...i.interpolation,...this.options.interpolation}),n.keySeparator!==void 0&&(this.options.userDefinedKeySeparator=n.keySeparator),n.nsSeparator!==void 0&&(this.options.userDefinedNsSeparator=n.nsSeparator);function o(c){return c?typeof c=="function"?new c:c:null}if(!this.options.isClone){this.modules.logger?fo.init(o(this.modules.logger),this.options):fo.init(null,this.options);let c;this.modules.formatter?c=this.modules.formatter:typeof Intl<"u"&&(c=H1e);const d=new Ek(this.options);this.store=new Ck(this.options.resources,this.options);const f=this.services;f.logger=fo,f.resourceStore=this.store,f.languageUtils=d,f.pluralResolver=new z1e(d,{prepend:this.options.pluralSeparator,compatibilityJSON:this.options.compatibilityJSON,simplifyPluralSuffix:this.options.simplifyPluralSuffix}),c&&(!this.options.interpolation.format||this.options.interpolation.format===i.interpolation.format)&&(f.formatter=o(c),f.formatter.init(f,this.options),this.options.interpolation.format=f.formatter.format.bind(f.formatter)),f.interpolator=new U1e(this.options),f.utils={hasLoadedNamespace:this.hasLoadedNamespace.bind(this)},f.backendConnector=new W1e(o(this.modules.backend),f.resourceStore,f,this.options),f.backendConnector.on("*",function(h){for(var p=arguments.length,m=new Array(p>1?p-1:0),S=1;S1?p-1:0),S=1;S{h.init&&h.init(this)})}if(this.format=this.options.interpolation.format,r||(r=Dg),this.options.fallbackLng&&!this.services.languageDetector&&!this.options.lng){const c=this.services.languageUtils.getFallbackCodes(this.options.fallbackLng);c.length>0&&c[0]!=="dev"&&(this.options.lng=c[0])}!this.services.languageDetector&&!this.options.lng&&this.logger.warn("init: no languageDetector is used and no lng is defined"),["getResource","hasResourceBundle","getResourceBundle","getDataByLanguage"].forEach(c=>{this[c]=function(){return t.store[c](...arguments)}}),["addResource","addResources","addResourceBundle","removeResourceBundle"].forEach(c=>{this[c]=function(){return t.store[c](...arguments),t}});const l=Md(),u=()=>{const c=(d,f)=>{this.isInitialized&&!this.initializedStoreOnce&&this.logger.warn("init: i18next is already initialized. 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Please check the object you are passing to i18next.use()");if(!t.type)throw new Error("You are passing a wrong module! Please check the object you are passing to i18next.use()");return t.type==="backend"&&(this.modules.backend=t),(t.type==="logger"||t.log&&t.warn&&t.error)&&(this.modules.logger=t),t.type==="languageDetector"&&(this.modules.languageDetector=t),t.type==="i18nFormat"&&(this.modules.i18nFormat=t),t.type==="postProcessor"&&$F.addPostProcessor(t),t.type==="formatter"&&(this.modules.formatter=t),t.type==="3rdParty"&&this.modules.external.push(t),this}setResolvedLanguage(t){if(!(!t||!this.languages)&&!(["cimode","dev"].indexOf(t)>-1))for(let n=0;n-1)&&this.store.hasLanguageSomeTranslations(r)){this.resolvedLanguage=r;break}}}changeLanguage(t,n){var r=this;this.isLanguageChangingTo=t;const i=Md();this.emit("languageChanging",t);const o=l=>{this.language=l,this.languages=this.services.languageUtils.toResolveHierarchy(l),this.resolvedLanguage=void 0,this.setResolvedLanguage(l)},s=(l,u)=>{u?(o(u),this.translator.changeLanguage(u),this.isLanguageChangingTo=void 0,this.emit("languageChanged",u),this.logger.log("languageChanged",u)):this.isLanguageChangingTo=void 0,i.resolve(function(){return r.t(...arguments)}),n&&n(l,function(){return r.t(...arguments)})},a=l=>{!t&&!l&&this.services.languageDetector&&(l=[]);const u=typeof l=="string"?l:this.services.languageUtils.getBestMatchFromCodes(l);u&&(this.language||o(u),this.translator.language||this.translator.changeLanguage(u),this.services.languageDetector&&this.services.languageDetector.cacheUserLanguage&&this.services.languageDetector.cacheUserLanguage(u)),this.loadResources(u,c=>{s(c,u)})};return!t&&this.services.languageDetector&&!this.services.languageDetector.async?a(this.services.languageDetector.detect()):!t&&this.services.languageDetector&&this.services.languageDetector.async?this.services.languageDetector.detect.length===0?this.services.languageDetector.detect().then(a):this.services.languageDetector.detect(a):a(t),i}getFixedT(t,n,r){var i=this;const o=function(s,a){let l;if(typeof a!="object"){for(var u=arguments.length,c=new Array(u>2?u-2:0),d=2;d`${l.keyPrefix}${f}${p}`):h=l.keyPrefix?`${l.keyPrefix}${f}${s}`:s,i.t(h,l)};return typeof t=="string"?o.lng=t:o.lngs=t,o.ns=n,o.keyPrefix=r,o}t(){return this.translator&&this.translator.translate(...arguments)}exists(){return this.translator&&this.translator.exists(...arguments)}setDefaultNamespace(t){this.options.defaultNS=t}hasLoadedNamespace(t){let n=arguments.length>1&&arguments[1]!==void 0?arguments[1]:{};if(!this.isInitialized)return this.logger.warn("hasLoadedNamespace: i18next was not initialized",this.languages),!1;if(!this.languages||!this.languages.length)return this.logger.warn("hasLoadedNamespace: i18n.languages were undefined or empty",this.languages),!1;const r=n.lng||this.resolvedLanguage||this.languages[0],i=this.options?this.options.fallbackLng:!1,o=this.languages[this.languages.length-1];if(r.toLowerCase()==="cimode")return!0;const s=(a,l)=>{const u=this.services.backendConnector.state[`${a}|${l}`];return u===-1||u===2};if(n.precheck){const a=n.precheck(this,s);if(a!==void 0)return a}return!!(this.hasResourceBundle(r,t)||!this.services.backendConnector.backend||this.options.resources&&!this.options.partialBundledLanguages||s(r,t)&&(!i||s(o,t)))}loadNamespaces(t,n){const r=Md();return this.options.ns?(typeof t=="string"&&(t=[t]),t.forEach(i=>{this.options.ns.indexOf(i)<0&&this.options.ns.push(i)}),this.loadResources(i=>{r.resolve(),n&&n(i)}),r):(n&&n(),Promise.resolve())}loadLanguages(t,n){const r=Md();typeof t=="string"&&(t=[t]);const i=this.options.preload||[],o=t.filter(s=>i.indexOf(s)<0);return o.length?(this.options.preload=i.concat(o),this.loadResources(s=>{r.resolve(),n&&n(s)}),r):(n&&n(),Promise.resolve())}dir(t){if(t||(t=this.resolvedLanguage||(this.languages&&this.languages.length>0?this.languages[0]:this.language)),!t)return"rtl";const 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E.useCallback(n=>e(Wt(ho(n))),[e])},FF={isConnected:!1,isProcessing:!1,shouldDisplayGuides:!0,isGFPGANAvailable:!0,isESRGANAvailable:!0,shouldConfirmOnDelete:!0,currentStep:0,totalSteps:0,currentIteration:0,totalIterations:0,currentStatusHasSteps:!1,isCancelable:!0,enableImageDebugging:!1,toastQueue:[],searchFolder:null,foundModels:null,progressImage:null,shouldAntialiasProgressImage:!1,sessionId:null,cancelType:"immediate",isCancelScheduled:!1,subscribedNodeIds:[],wereModelsReceived:!1,wasSchemaParsed:!1,consoleLogLevel:"debug",shouldLogToConsole:!0,statusTranslationKey:"common.statusDisconnected",canceledSession:"",isPersisted:!1,language:"en",isUploading:!1},BF=qt({name:"system",initialState:FF,reducers:{setIsProcessing:(e,t)=>{e.isProcessing=t.payload},setCurrentStatus:(e,t)=>{e.statusTranslationKey=t.payload},setShouldConfirmOnDelete:(e,t)=>{e.shouldConfirmOnDelete=t.payload},setShouldDisplayGuides:(e,t)=>{e.shouldDisplayGuides=t.payload},setIsCancelable:(e,t)=>{e.isCancelable=t.payload},setEnableImageDebugging:(e,t)=>{e.enableImageDebugging=t.payload},addToast:(e,t)=>{e.toastQueue.push(t.payload)},clearToastQueue:e=>{e.toastQueue=[]},setSearchFolder:(e,t)=>{e.searchFolder=t.payload},setFoundModels:(e,t)=>{e.foundModels=t.payload},cancelScheduled:e=>{e.isCancelScheduled=!0},scheduledCancelAborted:e=>{e.isCancelScheduled=!1},cancelTypeChanged:(e,t)=>{e.cancelType=t.payload},subscribedNodeIdsSet:(e,t)=>{e.subscribedNodeIds=t.payload},consoleLogLevelChanged:(e,t)=>{e.consoleLogLevel=t.payload},shouldLogToConsoleChanged:(e,t)=>{e.shouldLogToConsole=t.payload},shouldAntialiasProgressImageChanged:(e,t)=>{e.shouldAntialiasProgressImage=t.payload},isPersistedChanged:(e,t)=>{e.isPersisted=t.payload},languageChanged:(e,t)=>{e.language=t.payload},progressImageSet(e,t){e.progressImage=t.payload}},extraReducers(e){e.addCase(UL,(t,n)=>{t.sessionId=n.payload.sessionId,t.boardIdToAddTo=n.payload.boardId,t.canceledSession=""}),e.addCase(HL,t=>{t.sessionId=null,t.boardIdToAddTo=void 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r=n(),{sessionId:i,isProcessing:o}=r.system,s=e.payload;if(o){if(!s){Rk.debug("No canvas session, skipping cancel");return}if(s!==i){Rk.debug({data:{canvasSessionId:s,session_id:i}},"Canvas session does not match global session, skipping cancel");return}t(zl({session_id:i}))}}})},jF=Eo.injectEndpoints({endpoints:e=>({getAppVersion:e.query({query:()=>({url:"app/version",method:"GET"}),keepUnusedDataFor:864e5}),getAppConfig:e.query({query:()=>({url:"app/config",method:"GET"}),keepUnusedDataFor:864e5})})}),{useGetAppVersionQuery:oke,useGetAppConfigQuery:ske}=jF,J1e=()=>{fe({matcher:jF.endpoints.getAppConfig.matchFulfilled,effect:async(e,{getState:t,dispatch:n})=>{const{infill_methods:r}=e.payload,i=t().generation.infillMethod;r.includes(i)||n(Bce(r[0]))}})},ebe=ye("app/appStarted"),tbe=()=>{fe({actionCreator:ebe,effect:async(e,{getState:t,dispatch:n,unsubscribe:r,cancelActiveListeners:i})=>{i(),r(),await n(ua({categories:g1,is_intermediate:!1,offset:0,limit:T8})),await 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c=kL(a).reduce((p,m)=>(m.board_id===s&&p.push(m.image_name),p),[]);t(wpe(c)),t(Eh.endpoints.deleteBoardAndImages.initiate(s));const d=Eh.endpoints.deleteBoardAndImages.select(s)(a),{isSuccess:f}=d;await r(()=>!!f,3e4)&&t(Eo.util.invalidateTags([{type:"Board",id:s},{type:"Image",id:ar}]))}})},ibe=ye("canvas/canvasSavedToGallery"),obe=ye("canvas/canvasCopiedToClipboard"),sbe=ye("canvas/canvasDownloadedAsImage"),abe=ye("canvas/canvasMerged"),lbe=ye("canvas/stagingAreaImageSaved");let zF=null,UF=null;const uke=e=>{zF=e},E1=()=>zF,cke=e=>{UF=e},ube=()=>UF,cbe=async e=>new Promise((t,n)=>{e.toBlob(r=>{if(r){t(r);return}n("Unable to create Blob")})}),d0=async(e,t)=>await cbe(e.toCanvas(t)),U3=async e=>{const t=E1();if(!t)return;const{shouldCropToBoundingBoxOnSave:n,boundingBoxCoordinates:r,boundingBoxDimensions:i}=e.canvas,o=t.clone();o.scale({x:1,y:1});const s=o.getAbsolutePosition(),a=n?{x:r.x+s.x,y:r.y+s.y,width:i.width,height:i.height}:o.getClientRect();return d0(o,a)},dbe=e=>{navigator.clipboard.write([new ClipboardItem({[e.type]:e})])},fbe=be.child({namespace:"canvasCopiedToClipboardListener"}),hbe=()=>{fe({actionCreator:obe,effect:async(e,{dispatch:t,getState:n})=>{const r=n(),i=await U3(r);if(!i){fbe.error("Problem getting base layer blob"),t(Wt({title:"Problem Copying Canvas",description:"Unable to export base layer",status:"error"}));return}dbe(i),t(Wt({title:"Canvas Copied to Clipboard",status:"success"}))}})},pbe=(e,t)=>{const n=URL.createObjectURL(e),r=document.createElement("a");r.href=n,r.download=t,document.body.appendChild(r),r.click(),document.body.removeChild(r),r.remove()},gbe=be.child({namespace:"canvasSavedToGalleryListener"}),mbe=()=>{fe({actionCreator:sbe,effect:async(e,{dispatch:t,getState:n})=>{const r=n(),i=await U3(r);if(!i){gbe.error("Problem getting base layer blob"),t(Wt({title:"Problem Downloading Canvas",description:"Unable to export base layer",status:"error"}));return}pbe(i,"canvas.png"),t(Wt({title:"Canvas Downloaded",status:"success"}))}})},ybe=async()=>{const e=E1();if(!e)return;const t=e.clone();return t.scale({x:1,y:1}),d0(t,t.getClientRect())},Ik=be.child({namespace:"canvasCopiedToClipboardListener"}),vbe=()=>{fe({actionCreator:abe,effect:async(e,{dispatch:t,getState:n,take:r})=>{const i=await ybe();if(!i){Ik.error("Problem getting base layer blob"),t(Wt({title:"Problem Merging Canvas",description:"Unable to export base layer",status:"error"}));return}const o=E1();if(!o){Ik.error("Problem getting canvas base layer"),t(Wt({title:"Problem Merging Canvas",description:"Unable to export base layer",status:"error"}));return}const s=o.getClientRect({relativeTo:o.getParent()}),a=t(Br({file:new File([i],"mergedCanvas.png",{type:"image/png"}),image_category:"general",is_intermediate:!0,postUploadAction:{type:"TOAST_CANVAS_MERGED"}})),[{payload:l}]=await r(c=>Br.fulfilled.match(c)&&c.meta.requestId===a.requestId),{image_name:u}=l;t(yhe({kind:"image",layer:"base",imageName:u,...s})),t(Wt({title:"Canvas Merged",status:"success"}))}})},bbe=be.child({namespace:"canvasSavedToGalleryListener"}),Sbe=()=>{fe({actionCreator:ibe,effect:async(e,{dispatch:t,getState:n,take:r})=>{const i=n(),o=await U3(i);if(!o){bbe.error("Problem getting base layer blob"),t(Wt({title:"Problem Saving Canvas",description:"Unable to export base layer",status:"error"}));return}const s=t(Br({file:new File([o],"savedCanvas.png",{type:"image/png"}),image_category:"general",is_intermediate:!1,postUploadAction:{type:"TOAST_CANVAS_SAVED_TO_GALLERY"}})),[{payload:a}]=await 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r(S=>Ph.fulfilled.match(S)&&S.payload.image_name===h),m=p.payload;Mk.debug({data:{arg:e.payload,processedControlImage:m}},"ControlNet image processed"),t(Bpe({controlNetId:s,processedControlImage:m.image_name}))}}})},oi=Eo.injectEndpoints({endpoints:e=>({listBoardImages:e.query({query:({board_id:t,offset:n,limit:r})=>({url:`board_images/${t}`,method:"GET"}),providesTags:(t,n,r)=>{const i=[{type:"BoardImage",id:`${r.board_id}_${ar}`}];return t&&i.push(...t.items.map(({board_id:o,image_name:s})=>({type:"BoardImage",id:`${o}_${s}`}))),i}}),addImageToBoard:e.mutation({query:({board_id:t,image_name:n})=>({url:"board_images/",method:"POST",body:{board_id:t,image_name:n}}),invalidatesTags:(t,n,r)=>[{type:"BoardImage"},{type:"Board",id:r.board_id}]}),removeImageFromBoard:e.mutation({query:({board_id:t,image_name:n})=>({url:"board_images/",method:"DELETE",body:{board_id:t,image_name:n}}),invalidatesTags:(t,n,r)=>[{type:"BoardImage"},{type:"Board",id:r.board_id}]})})}),{useAddImageToBoardMutation:Pbe,useRemoveImageFromBoardMutation:fke,useListBoardImagesQuery:hke}=oi,HF=be.child({namespace:"boards"}),kbe=()=>{fe({matcher:oi.endpoints.addImageToBoard.matchFulfilled,effect:(e,{getState:t,dispatch:n})=>{const{board_id:r,image_name:i}=e.meta.arg.originalArgs;HF.debug({data:{board_id:r,image_name:i}},"Image added to 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r(d=>Dc.fulfilled.match(d)&&d.meta.requestId===u,3e4)&&t(Eo.util.invalidateTags([{type:"Board",id:i.board_id}]))}})},Rbe=()=>{fe({actionCreator:Dc.pending,effect:(e,{dispatch:t,getState:n})=>{}})},Ibe=()=>{fe({actionCreator:Dc.fulfilled,effect:(e,{dispatch:t,getState:n})=>{qF.debug({data:{image:e.meta.arg}},"Image deleted")}})},Mbe=()=>{fe({actionCreator:Dc.rejected,effect:(e,{dispatch:t,getState:n})=>{qF.debug({data:{image:e.meta.arg}},"Unable to delete image")}})},Nbe=be.child({namespace:"dnd"}),WF=ye("dnd/dndDropped"),Dbe=()=>{fe({actionCreator:WF,effect:async(e,{dispatch:t,getState:n,take:r})=>{const{activeData:i,overData:o}=e.payload;if(n(),Nbe.debug({data:{activeData:i,overData:o}},"Image or selection 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Look at Konva change log for more information.";o.prototype[u]=function(){t.Util.error(c);var d=this.attrs[s];return d===void 0?a:d},e.Factory.addSetter(o,s,l,function(){t.Util.error(c)}),e.Factory.addOverloadedGetterSetter(o,s)},backCompat(o,s){t.Util.each(s,function(a,l){var u=o.prototype[l],c=r+t.Util._capitalize(a),d=i+t.Util._capitalize(a);function f(){u.apply(this,arguments),t.Util.error('"'+a+'" method is deprecated and will be removed soon. Use ""'+l+'" instead.')}o.prototype[a]=f,o.prototype[c]=f,o.prototype[d]=f})},afterSetFilter(){this._filterUpToDate=!1}}})(Re);var Li={},ss={};Object.defineProperty(ss,"__esModule",{value:!0});ss.HitContext=ss.SceneContext=ss.Context=void 0;const dB=jt,R_e=De;function I_e(e){var t=[],n=e.length,r=dB.Util,i,o;for(i=0;itypeof c=="number"?Math.floor(c):c)),o+=M_e+u.join(Hk)+N_e)):(o+=a.property,t||(o+=B_e+a.val)),o+=$_e;return o}clearTrace(){this.traceArr=[]}_trace(t){var n=this.traceArr,r;n.push(t),r=n.length,r>=V_e&&n.shift()}reset(){var t=this.getCanvas().getPixelRatio();this.setTransform(1*t,0,0,1*t,0,0)}getCanvas(){return this.canvas}clear(t){var n=this.getCanvas();t?this.clearRect(t.x||0,t.y||0,t.width||0,t.height||0):this.clearRect(0,0,n.getWidth()/n.pixelRatio,n.getHeight()/n.pixelRatio)}_applyLineCap(t){const n=t.attrs.lineCap;n&&this.setAttr("lineCap",n)}_applyOpacity(t){var n=t.getAbsoluteOpacity();n!==1&&this.setAttr("globalAlpha",n)}_applyLineJoin(t){const n=t.attrs.lineJoin;n&&this.setAttr("lineJoin",n)}setAttr(t,n){this._context[t]=n}arc(t,n,r,i,o,s){this._context.arc(t,n,r,i,o,s)}arcTo(t,n,r,i,o){this._context.arcTo(t,n,r,i,o)}beginPath(){this._context.beginPath()}bezierCurveTo(t,n,r,i,o,s){this._context.bezierCurveTo(t,n,r,i,o,s)}clearRect(t,n,r,i){this._context.clearRect(t,n,r,i)}clip(...t){this._context.clip.apply(this._context,t)}closePath(){this._context.closePath()}createImageData(t,n){var r=arguments;if(r.length===2)return this._context.createImageData(t,n);if(r.length===1)return this._context.createImageData(t)}createLinearGradient(t,n,r,i){return this._context.createLinearGradient(t,n,r,i)}createPattern(t,n){return this._context.createPattern(t,n)}createRadialGradient(t,n,r,i,o,s){return this._context.createRadialGradient(t,n,r,i,o,s)}drawImage(t,n,r,i,o,s,a,l,u){var c=arguments,d=this._context;c.length===3?d.drawImage(t,n,r):c.length===5?d.drawImage(t,n,r,i,o):c.length===9&&d.drawImage(t,n,r,i,o,s,a,l,u)}ellipse(t,n,r,i,o,s,a,l){this._context.ellipse(t,n,r,i,o,s,a,l)}isPointInPath(t,n,r,i){return r?this._context.isPointInPath(r,t,n,i):this._context.isPointInPath(t,n,i)}fill(...t){this._context.fill.apply(this._context,t)}fillRect(t,n,r,i){this._context.fillRect(t,n,r,i)}strokeRect(t,n,r,i){this._context.strokeRect(t,n,r,i)}fillText(t,n,r,i){i?this._context.fillText(t,n,r,i):this._context.fillText(t,n,r)}measureText(t){return this._context.measureText(t)}getImageData(t,n,r,i){return this._context.getImageData(t,n,r,i)}lineTo(t,n){this._context.lineTo(t,n)}moveTo(t,n){this._context.moveTo(t,n)}rect(t,n,r,i){this._context.rect(t,n,r,i)}putImageData(t,n,r){this._context.putImageData(t,n,r)}quadraticCurveTo(t,n,r,i){this._context.quadraticCurveTo(t,n,r,i)}restore(){this._context.restore()}rotate(t){this._context.rotate(t)}save(){this._context.save()}scale(t,n){this._context.scale(t,n)}setLineDash(t){this._context.setLineDash?this._context.setLineDash(t):"mozDash"in this._context?this._context.mozDash=t:"webkitLineDash"in this._context&&(this._context.webkitLineDash=t)}getLineDash(){return this._context.getLineDash()}setTransform(t,n,r,i,o,s){this._context.setTransform(t,n,r,i,o,s)}stroke(t){t?this._context.stroke(t):this._context.stroke()}strokeText(t,n,r,i){this._context.strokeText(t,n,r,i)}transform(t,n,r,i,o,s){this._context.transform(t,n,r,i,o,s)}translate(t,n){this._context.translate(t,n)}_enableTrace(){var t=this,n=qk.length,r=this.setAttr,i,o,s=function(a){var l=t[a],u;t[a]=function(){return o=I_e(Array.prototype.slice.call(arguments,0)),u=l.apply(t,arguments),t._trace({method:a,args:o}),u}};for(i=0;i{i.dragStatus==="dragging"&&(r=!0)}),r},justDragged:!1,get node(){var r;return e.DD._dragElements.forEach(i=>{r=i.node}),r},_dragElements:new Map,_drag(r){const i=[];e.DD._dragElements.forEach((o,s)=>{const{node:a}=o,l=a.getStage();l.setPointersPositions(r),o.pointerId===void 0&&(o.pointerId=n.Util._getFirstPointerId(r));const u=l._changedPointerPositions.find(f=>f.id===o.pointerId);if(u){if(o.dragStatus!=="dragging"){var c=a.dragDistance(),d=Math.max(Math.abs(u.x-o.startPointerPos.x),Math.abs(u.y-o.startPointerPos.y));if(d{o.fire("dragmove",{type:"dragmove",target:o,evt:r},!0)})},_endDragBefore(r){const i=[];e.DD._dragElements.forEach(o=>{const{node:s}=o,a=s.getStage();if(r&&a.setPointersPositions(r),!a._changedPointerPositions.find(c=>c.id===o.pointerId))return;(o.dragStatus==="dragging"||o.dragStatus==="stopped")&&(e.DD.justDragged=!0,t.Konva._mouseListenClick=!1,t.Konva._touchListenClick=!1,t.Konva._pointerListenClick=!1,o.dragStatus="stopped");const u=o.node.getLayer()||o.node instanceof t.Konva.Stage&&o.node;u&&i.indexOf(u)===-1&&i.push(u)}),i.forEach(o=>{o.draw()})},_endDragAfter(r){e.DD._dragElements.forEach((i,o)=>{i.dragStatus==="stopped"&&i.node.fire("dragend",{type:"dragend",target:i.node,evt:r},!0),i.dragStatus!=="dragging"&&e.DD._dragElements.delete(o)})}},t.Konva.isBrowser&&(window.addEventListener("mouseup",e.DD._endDragBefore,!0),window.addEventListener("touchend",e.DD._endDragBefore,!0),window.addEventListener("mousemove",e.DD._drag),window.addEventListener("touchmove",e.DD._drag),window.addEventListener("mouseup",e.DD._endDragAfter,!1),window.addEventListener("touchend",e.DD._endDragAfter,!1))})(M1);Object.defineProperty(At,"__esModule",{value:!0});At.Node=void 0;const Be=jt,Np=Re,Fg=Li,za=De,ei=M1,Xt=he;var Om="absoluteOpacity",Bg="allEventListeners",qo="absoluteTransform",Wk="absoluteScale",Ua="canvas",Y_e="Change",X_e="children",Q_e="konva",bx="listening",Kk="mouseenter",Yk="mouseleave",Xk="set",Qk="Shape",Rm=" ",Zk="stage",Ls="transform",Z_e="Stage",Sx="visible",J_e=["xChange.konva","yChange.konva","scaleXChange.konva","scaleYChange.konva","skewXChange.konva","skewYChange.konva","rotationChange.konva","offsetXChange.konva","offsetYChange.konva","transformsEnabledChange.konva"].join(Rm);let e2e=1,Ee=class _x{constructor(t){this._id=e2e++,this.eventListeners={},this.attrs={},this.index=0,this._allEventListeners=null,this.parent=null,this._cache=new Map,this._attachedDepsListeners=new Map,this._lastPos=null,this._batchingTransformChange=!1,this._needClearTransformCache=!1,this._filterUpToDate=!1,this._isUnderCache=!1,this._dragEventId=null,this._shouldFireChangeEvents=!1,this.setAttrs(t),this._shouldFireChangeEvents=!0}hasChildren(){return!1}_clearCache(t){(t===Ls||t===qo)&&this._cache.get(t)?this._cache.get(t).dirty=!0:t?this._cache.delete(t):this._cache.clear()}_getCache(t,n){var r=this._cache.get(t),i=t===Ls||t===qo,o=r===void 0||i&&r.dirty===!0;return o&&(r=n.call(this),this._cache.set(t,r)),r}_calculate(t,n,r){if(!this._attachedDepsListeners.get(t)){const i=n.map(o=>o+"Change.konva").join(Rm);this.on(i,()=>{this._clearCache(t)}),this._attachedDepsListeners.set(t,!0)}return this._getCache(t,r)}_getCanvasCache(){return this._cache.get(Ua)}_clearSelfAndDescendantCache(t){this._clearCache(t),t===qo&&this.fire("absoluteTransformChange")}clearCache(){if(this._cache.has(Ua)){const{scene:t,filter:n,hit:r}=this._cache.get(Ua);Be.Util.releaseCanvas(t,n,r),this._cache.delete(Ua)}return this._clearSelfAndDescendantCache(),this._requestDraw(),this}cache(t){var n=t||{},r={};(n.x===void 0||n.y===void 0||n.width===void 0||n.height===void 0)&&(r=this.getClientRect({skipTransform:!0,relativeTo:this.getParent()}));var i=Math.ceil(n.width||r.width),o=Math.ceil(n.height||r.height),s=n.pixelRatio,a=n.x===void 0?Math.floor(r.x):n.x,l=n.y===void 0?Math.floor(r.y):n.y,u=n.offset||0,c=n.drawBorder||!1,d=n.hitCanvasPixelRatio||1;if(!i||!o){Be.Util.error("Can not cache the node. Width or height of the node equals 0. Caching is skipped.");return}i+=u*2+1,o+=u*2+1,a-=u,l-=u;var f=new Fg.SceneCanvas({pixelRatio:s,width:i,height:o}),h=new Fg.SceneCanvas({pixelRatio:s,width:0,height:0,willReadFrequently:!0}),p=new Fg.HitCanvas({pixelRatio:d,width:i,height:o}),m=f.getContext(),S=p.getContext();return p.isCache=!0,f.isCache=!0,this._cache.delete(Ua),this._filterUpToDate=!1,n.imageSmoothingEnabled===!1&&(f.getContext()._context.imageSmoothingEnabled=!1,h.getContext()._context.imageSmoothingEnabled=!1),m.save(),S.save(),m.translate(-a,-l),S.translate(-a,-l),this._isUnderCache=!0,this._clearSelfAndDescendantCache(Om),this._clearSelfAndDescendantCache(Wk),this.drawScene(f,this),this.drawHit(p,this),this._isUnderCache=!1,m.restore(),S.restore(),c&&(m.save(),m.beginPath(),m.rect(0,0,i,o),m.closePath(),m.setAttr("strokeStyle","red"),m.setAttr("lineWidth",5),m.stroke(),m.restore()),this._cache.set(Ua,{scene:f,filter:h,hit:p,x:a,y:l}),this._requestDraw(),this}isCached(){return this._cache.has(Ua)}getClientRect(t){throw new Error('abstract "getClientRect" method call')}_transformedRect(t,n){var r=[{x:t.x,y:t.y},{x:t.x+t.width,y:t.y},{x:t.x+t.width,y:t.y+t.height},{x:t.x,y:t.y+t.height}],i,o,s,a,l=this.getAbsoluteTransform(n);return r.forEach(function(u){var c=l.point(u);i===void 0&&(i=s=c.x,o=a=c.y),i=Math.min(i,c.x),o=Math.min(o,c.y),s=Math.max(s,c.x),a=Math.max(a,c.y)}),{x:i,y:o,width:s-i,height:a-o}}_drawCachedSceneCanvas(t){t.save(),t._applyOpacity(this),t._applyGlobalCompositeOperation(this);const n=this._getCanvasCache();t.translate(n.x,n.y);var r=this._getCachedSceneCanvas(),i=r.pixelRatio;t.drawImage(r._canvas,0,0,r.width/i,r.height/i),t.restore()}_drawCachedHitCanvas(t){var n=this._getCanvasCache(),r=n.hit;t.save(),t.translate(n.x,n.y),t.drawImage(r._canvas,0,0,r.width/r.pixelRatio,r.height/r.pixelRatio),t.restore()}_getCachedSceneCanvas(){var t=this.filters(),n=this._getCanvasCache(),r=n.scene,i=n.filter,o=i.getContext(),s,a,l,u;if(t){if(!this._filterUpToDate){var c=r.pixelRatio;i.setSize(r.width/r.pixelRatio,r.height/r.pixelRatio);try{for(s=t.length,o.clear(),o.drawImage(r._canvas,0,0,r.getWidth()/c,r.getHeight()/c),a=o.getImageData(0,0,i.getWidth(),i.getHeight()),l=0;l{var n,r;if(!t)return this;for(n in t)n!==X_e&&(r=Xk+Be.Util._capitalize(n),Be.Util._isFunction(this[r])?this[r](t[n]):this._setAttr(n,t[n]))}),this}isListening(){return this._getCache(bx,this._isListening)}_isListening(t){if(!this.listening())return!1;const r=this.getParent();return r&&r!==t&&this!==t?r._isListening(t):!0}isVisible(){return this._getCache(Sx,this._isVisible)}_isVisible(t){if(!this.visible())return!1;const r=this.getParent();return r&&r!==t&&this!==t?r._isVisible(t):!0}shouldDrawHit(t,n=!1){if(t)return this._isVisible(t)&&this._isListening(t);var r=this.getLayer(),i=!1;ei.DD._dragElements.forEach(s=>{s.dragStatus==="dragging"&&(s.node.nodeType==="Stage"||s.node.getLayer()===r)&&(i=!0)});var o=!n&&!za.Konva.hitOnDragEnabled&&i;return this.isListening()&&this.isVisible()&&!o}show(){return this.visible(!0),this}hide(){return this.visible(!1),this}getZIndex(){return this.index||0}getAbsoluteZIndex(){var t=this.getDepth(),n=this,r=0,i,o,s,a;function l(u){for(i=[],o=u.length,s=0;s0&&i[0].getDepth()<=t&&l(i)}return n.nodeType!==Z_e&&l(n.getStage().getChildren()),r}getDepth(){for(var t=0,n=this.parent;n;)t++,n=n.parent;return t}_batchTransformChanges(t){this._batchingTransformChange=!0,t(),this._batchingTransformChange=!1,this._needClearTransformCache&&(this._clearCache(Ls),this._clearSelfAndDescendantCache(qo)),this._needClearTransformCache=!1}setPosition(t){return this._batchTransformChanges(()=>{this.x(t.x),this.y(t.y)}),this}getPosition(){return{x:this.x(),y:this.y()}}getRelativePointerPosition(){if(!this.getStage())return null;var t=this.getStage().getPointerPosition();if(!t)return null;var n=this.getAbsoluteTransform().copy();return n.invert(),n.point(t)}getAbsolutePosition(t){let n=!1,r=this.parent;for(;r;){if(r.isCached()){n=!0;break}r=r.parent}n&&!t&&(t=!0);var i=this.getAbsoluteTransform(t).getMatrix(),o=new Be.Transform,s=this.offset();return o.m=i.slice(),o.translate(s.x,s.y),o.getTranslation()}setAbsolutePosition(t){var n=this._clearTransform();this.attrs.x=n.x,this.attrs.y=n.y,delete n.x,delete n.y,this._clearCache(Ls);var r=this._getAbsoluteTransform().copy();return r.invert(),r.translate(t.x,t.y),t={x:this.attrs.x+r.getTranslation().x,y:this.attrs.y+r.getTranslation().y},this._setTransform(n),this.setPosition({x:t.x,y:t.y}),this._clearCache(Ls),this._clearSelfAndDescendantCache(qo),this}_setTransform(t){var n;for(n in t)this.attrs[n]=t[n]}_clearTransform(){var t={x:this.x(),y:this.y(),rotation:this.rotation(),scaleX:this.scaleX(),scaleY:this.scaleY(),offsetX:this.offsetX(),offsetY:this.offsetY(),skewX:this.skewX(),skewY:this.skewY()};return this.attrs.x=0,this.attrs.y=0,this.attrs.rotation=0,this.attrs.scaleX=1,this.attrs.scaleY=1,this.attrs.offsetX=0,this.attrs.offsetY=0,this.attrs.skewX=0,this.attrs.skewY=0,t}move(t){var n=t.x,r=t.y,i=this.x(),o=this.y();return n!==void 0&&(i+=n),r!==void 0&&(o+=r),this.setPosition({x:i,y:o}),this}_eachAncestorReverse(t,n){var r=[],i=this.getParent(),o,s;if(!(n&&n._id===this._id)){for(r.unshift(this);i&&(!n||i._id!==n._id);)r.unshift(i),i=i.parent;for(o=r.length,s=0;s0?(this.parent.children.splice(t,1),this.parent.children.splice(t-1,0,this),this.parent._setChildrenIndices(),!0):!1}moveToBottom(){if(!this.parent)return Be.Util.warn("Node has no parent. moveToBottom function is ignored."),!1;var t=this.index;return t>0?(this.parent.children.splice(t,1),this.parent.children.unshift(this),this.parent._setChildrenIndices(),!0):!1}setZIndex(t){if(!this.parent)return Be.Util.warn("Node has no parent. zIndex parameter is ignored."),this;(t<0||t>=this.parent.children.length)&&Be.Util.warn("Unexpected value "+t+" for zIndex property. zIndex is just index of a node in children of its parent. Expected value is from 0 to "+(this.parent.children.length-1)+".");var n=this.index;return this.parent.children.splice(n,1),this.parent.children.splice(t,0,this),this.parent._setChildrenIndices(),this}getAbsoluteOpacity(){return this._getCache(Om,this._getAbsoluteOpacity)}_getAbsoluteOpacity(){var t=this.opacity(),n=this.getParent();return n&&!n._isUnderCache&&(t*=n.getAbsoluteOpacity()),t}moveTo(t){return this.getParent()!==t&&(this._remove(),t.add(this)),this}toObject(){var t={},n=this.getAttrs(),r,i,o,s,a;t.attrs={};for(r in n)i=n[r],a=Be.Util.isObject(i)&&!Be.Util._isPlainObject(i)&&!Be.Util._isArray(i),!a&&(o=typeof this[r]=="function"&&this[r],delete n[r],s=o?o.call(this):null,n[r]=i,s!==i&&(t.attrs[r]=i));return t.className=this.getClassName(),Be.Util._prepareToStringify(t)}toJSON(){return JSON.stringify(this.toObject())}getParent(){return this.parent}findAncestors(t,n,r){var i=[];n&&this._isMatch(t)&&i.push(this);for(var o=this.parent;o;){if(o===r)return i;o._isMatch(t)&&i.push(o),o=o.parent}return i}isAncestorOf(t){return!1}findAncestor(t,n,r){return this.findAncestors(t,n,r)[0]}_isMatch(t){if(!t)return!1;if(typeof t=="function")return t(this);var n=t.replace(/ /g,"").split(","),r=n.length,i,o;for(i=0;i{try{const i=t==null?void 0:t.callback;i&&delete t.callback,Be.Util._urlToImage(this.toDataURL(t),function(o){n(o),i==null||i(o)})}catch(i){r(i)}})}toBlob(t){return new Promise((n,r)=>{try{const i=t==null?void 0:t.callback;i&&delete t.callback,this.toCanvas(t).toBlob(o=>{n(o),i==null||i(o)})}catch(i){r(i)}})}setSize(t){return this.width(t.width),this.height(t.height),this}getSize(){return{width:this.width(),height:this.height()}}getClassName(){return this.className||this.nodeType}getType(){return this.nodeType}getDragDistance(){return this.attrs.dragDistance!==void 0?this.attrs.dragDistance:this.parent?this.parent.getDragDistance():za.Konva.dragDistance}_off(t,n,r){var i=this.eventListeners[t],o,s,a;for(o=0;o=0;if(r&&!this.isDragging()){var i=!1;ei.DD._dragElements.forEach(o=>{this.isAncestorOf(o.node)&&(i=!0)}),i||this._createDragElement(t)}})}_dragChange(){if(this.attrs.draggable)this._listenDrag();else{this._dragCleanup();var t=this.getStage();if(!t)return;const n=ei.DD._dragElements.get(this._id),r=n&&n.dragStatus==="dragging",i=n&&n.dragStatus==="ready";r?this.stopDrag():i&&ei.DD._dragElements.delete(this._id)}}_dragCleanup(){this.off("mousedown.konva"),this.off("touchstart.konva")}isClientRectOnScreen(t={x:0,y:0}){const n=this.getStage();if(!n)return!1;const r={x:-t.x,y:-t.y,width:n.width()+2*t.x,height:n.height()+2*t.y};return Be.Util.haveIntersection(r,this.getClientRect())}static create(t,n){return Be.Util._isString(t)&&(t=JSON.parse(t)),this._createNode(t,n)}static _createNode(t,n){var r=_x.prototype.getClassName.call(t),i=t.children,o,s,a;n&&(t.attrs.container=n),za.Konva[r]||(Be.Util.warn('Can not find a node with class name "'+r+'". Fallback to "Shape".'),r="Shape");const l=za.Konva[r];if(o=new l(t.attrs),i)for(s=i.length,a=0;a0}removeChildren(){return this.getChildren().forEach(t=>{t.parent=null,t.index=0,t.remove()}),this.children=[],this._requestDraw(),this}destroyChildren(){return this.getChildren().forEach(t=>{t.parent=null,t.index=0,t.destroy()}),this.children=[],this._requestDraw(),this}add(...t){if(t.length===0)return this;if(t.length>1){for(var n=0;n0?n[0]:void 0}_generalFind(t,n){var r=[];return this._descendants(i=>{const o=i._isMatch(t);return o&&r.push(i),!!(o&&n)}),r}_descendants(t){let n=!1;const r=this.getChildren();for(const i of r){if(n=t(i),n)return!0;if(i.hasChildren()&&(n=i._descendants(t),n))return!0}return!1}toObject(){var t=P_.Node.prototype.toObject.call(this);return t.children=[],this.getChildren().forEach(n=>{t.children.push(n.toObject())}),t}isAncestorOf(t){for(var n=t.getParent();n;){if(n._id===this._id)return!0;n=n.getParent()}return!1}clone(t){var n=P_.Node.prototype.clone.call(this,t);return this.getChildren().forEach(function(r){n.add(r.clone())}),n}getAllIntersections(t){var n=[];return this.find("Shape").forEach(function(r){r.isVisible()&&r.intersects(t)&&n.push(r)}),n}_clearSelfAndDescendantCache(t){var n;super._clearSelfAndDescendantCache(t),!this.isCached()&&((n=this.children)===null||n===void 0||n.forEach(function(r){r._clearSelfAndDescendantCache(t)}))}_setChildrenIndices(){var t;(t=this.children)===null||t===void 0||t.forEach(function(n,r){n.index=r}),this._requestDraw()}drawScene(t,n){var r=this.getLayer(),i=t||r&&r.getCanvas(),o=i&&i.getContext(),s=this._getCanvasCache(),a=s&&s.scene,l=i&&i.isCache;if(!this.isVisible()&&!l)return this;if(a){o.save();var u=this.getAbsoluteTransform(n).getMatrix();o.transform(u[0],u[1],u[2],u[3],u[4],u[5]),this._drawCachedSceneCanvas(o),o.restore()}else this._drawChildren("drawScene",i,n);return this}drawHit(t,n){if(!this.shouldDrawHit(n))return this;var r=this.getLayer(),i=t||r&&r.hitCanvas,o=i&&i.getContext(),s=this._getCanvasCache(),a=s&&s.hit;if(a){o.save();var l=this.getAbsoluteTransform(n).getMatrix();o.transform(l[0],l[1],l[2],l[3],l[4],l[5]),this._drawCachedHitCanvas(o),o.restore()}else this._drawChildren("drawHit",i,n);return this}_drawChildren(t,n,r){var i,o=n&&n.getContext(),s=this.clipWidth(),a=this.clipHeight(),l=this.clipFunc(),u=s&&a||l;const c=r===this;if(u){o.save();var d=this.getAbsoluteTransform(r),f=d.getMatrix();o.transform(f[0],f[1],f[2],f[3],f[4],f[5]),o.beginPath();let S;if(l)S=l.call(this,o,this);else{var h=this.clipX(),p=this.clipY();o.rect(h,p,s,a)}o.clip.apply(o,S),f=d.copy().invert().getMatrix(),o.transform(f[0],f[1],f[2],f[3],f[4],f[5])}var m=!c&&this.globalCompositeOperation()!=="source-over"&&t==="drawScene";m&&(o.save(),o._applyGlobalCompositeOperation(this)),(i=this.children)===null||i===void 0||i.forEach(function(S){S[t](n,r)}),m&&o.restore(),u&&o.restore()}getClientRect(t){var n;t=t||{};var r=t.skipTransform,i=t.relativeTo,o,s,a,l,u={x:1/0,y:1/0,width:0,height:0},c=this;(n=this.children)===null||n===void 0||n.forEach(function(m){if(m.visible()){var S=m.getClientRect({relativeTo:c,skipShadow:t.skipShadow,skipStroke:t.skipStroke});S.width===0&&S.height===0||(o===void 0?(o=S.x,s=S.y,a=S.x+S.width,l=S.y+S.height):(o=Math.min(o,S.x),s=Math.min(s,S.y),a=Math.max(a,S.x+S.width),l=Math.max(l,S.y+S.height)))}});for(var d=this.find("Shape"),f=!1,h=0;hX.indexOf("pointer")>=0?"pointer":X.indexOf("touch")>=0?"touch":"mouse",z=X=>{const F=V(X);if(F==="pointer")return i.Konva.pointerEventsEnabled&&L.pointer;if(F==="touch")return L.touch;if(F==="mouse")return L.mouse};function U(X={}){return(X.clipFunc||X.clipWidth||X.clipHeight)&&t.Util.warn("Stage does not support clipping. Please use clip for Layers or Groups."),X}const K="Pointer position is missing and not registered by the stage. Looks like it is outside of the stage container. You can set it manually from event: stage.setPointersPositions(event);";e.stages=[];class W extends r.Container{constructor(F){super(U(F)),this._pointerPositions=[],this._changedPointerPositions=[],this._buildDOM(),this._bindContentEvents(),e.stages.push(this),this.on("widthChange.konva heightChange.konva",this._resizeDOM),this.on("visibleChange.konva",this._checkVisibility),this.on("clipWidthChange.konva clipHeightChange.konva clipFuncChange.konva",()=>{U(this.attrs)}),this._checkVisibility()}_validateAdd(F){const q=F.getType()==="Layer",Q=F.getType()==="FastLayer";q||Q||t.Util.throw("You may only add layers to the stage.")}_checkVisibility(){if(!this.content)return;const F=this.visible()?"":"none";this.content.style.display=F}setContainer(F){if(typeof F===c){if(F.charAt(0)==="."){var q=F.slice(1);F=document.getElementsByClassName(q)[0]}else{var Q;F.charAt(0)!=="#"?Q=F:Q=F.slice(1),F=document.getElementById(Q)}if(!F)throw"Can not find container in document with id "+Q}return this._setAttr("container",F),this.content&&(this.content.parentElement&&this.content.parentElement.removeChild(this.content),F.appendChild(this.content)),this}shouldDrawHit(){return!0}clear(){var F=this.children,q=F.length,Q;for(Q=0;Q-1&&e.stages.splice(q,1),t.Util.releaseCanvas(this.bufferCanvas._canvas,this.bufferHitCanvas._canvas),this}getPointerPosition(){const F=this._pointerPositions[0]||this._changedPointerPositions[0];return F?{x:F.x,y:F.y}:(t.Util.warn(K),null)}_getPointerById(F){return this._pointerPositions.find(q=>q.id===F)}getPointersPositions(){return this._pointerPositions}getStage(){return this}getContent(){return this.content}_toKonvaCanvas(F){F=F||{},F.x=F.x||0,F.y=F.y||0,F.width=F.width||this.width(),F.height=F.height||this.height();var q=new o.SceneCanvas({width:F.width,height:F.height,pixelRatio:F.pixelRatio||1}),Q=q.getContext()._context,J=this.children;return(F.x||F.y)&&Q.translate(-1*F.x,-1*F.y),J.forEach(function(ne){if(ne.isVisible()){var Z=ne._toKonvaCanvas(F);Q.drawImage(Z._canvas,F.x,F.y,Z.getWidth()/Z.getPixelRatio(),Z.getHeight()/Z.getPixelRatio())}}),q}getIntersection(F){if(!F)return null;var q=this.children,Q=q.length,J=Q-1,ne;for(ne=J;ne>=0;ne--){const Z=q[ne].getIntersection(F);if(Z)return Z}return null}_resizeDOM(){var F=this.width(),q=this.height();this.content&&(this.content.style.width=F+d,this.content.style.height=q+d),this.bufferCanvas.setSize(F,q),this.bufferHitCanvas.setSize(F,q),this.children.forEach(Q=>{Q.setSize({width:F,height:q}),Q.draw()})}add(F,...q){if(arguments.length>1){for(var Q=0;QR&&t.Util.warn("The stage has "+J+" layers. Recommended maximum number of layers is 3-5. Adding more layers into the stage may drop the performance. Rethink your tree structure, you can use Konva.Group."),F.setSize({width:this.width(),height:this.height()}),F.draw(),i.Konva.isBrowser&&this.content.appendChild(F.canvas._canvas),this}getParent(){return null}getLayer(){return null}hasPointerCapture(F){return l.hasPointerCapture(F,this)}setPointerCapture(F){l.setPointerCapture(F,this)}releaseCapture(F){l.releaseCapture(F,this)}getLayers(){return this.children}_bindContentEvents(){i.Konva.isBrowser&&D.forEach(([F,q])=>{this.content.addEventListener(F,Q=>{this[q](Q)},{passive:!1})})}_pointerenter(F){this.setPointersPositions(F);const q=z(F.type);this._fire(q.pointerenter,{evt:F,target:this,currentTarget:this})}_pointerover(F){this.setPointersPositions(F);const q=z(F.type);this._fire(q.pointerover,{evt:F,target:this,currentTarget:this})}_getTargetShape(F){let q=this[F+"targetShape"];return q&&!q.getStage()&&(q=null),q}_pointerleave(F){const q=z(F.type),Q=V(F.type);if(q){this.setPointersPositions(F);var J=this._getTargetShape(Q),ne=!s.DD.isDragging||i.Konva.hitOnDragEnabled;J&&ne?(J._fireAndBubble(q.pointerout,{evt:F}),J._fireAndBubble(q.pointerleave,{evt:F}),this._fire(q.pointerleave,{evt:F,target:this,currentTarget:this}),this[Q+"targetShape"]=null):ne&&(this._fire(q.pointerleave,{evt:F,target:this,currentTarget:this}),this._fire(q.pointerout,{evt:F,target:this,currentTarget:this})),this.pointerPos=void 0,this._pointerPositions=[]}}_pointerdown(F){const q=z(F.type),Q=V(F.type);if(q){this.setPointersPositions(F);var J=!1;this._changedPointerPositions.forEach(ne=>{var Z=this.getIntersection(ne);if(s.DD.justDragged=!1,i.Konva["_"+Q+"ListenClick"]=!0,!(Z&&Z.isListening()))return;i.Konva.capturePointerEventsEnabled&&Z.setPointerCapture(ne.id),this[Q+"ClickStartShape"]=Z,Z._fireAndBubble(q.pointerdown,{evt:F,pointerId:ne.id}),J=!0;const ae=F.type.indexOf("touch")>=0;Z.preventDefault()&&F.cancelable&&ae&&F.preventDefault()}),J||this._fire(q.pointerdown,{evt:F,target:this,currentTarget:this,pointerId:this._pointerPositions[0].id})}}_pointermove(F){const q=z(F.type),Q=V(F.type);if(!q)return;s.DD.isDragging&&s.DD.node.preventDefault()&&F.cancelable&&F.preventDefault(),this.setPointersPositions(F);var J=!s.DD.isDragging||i.Konva.hitOnDragEnabled;if(!J)return;var ne={};let Z=!1;var ge=this._getTargetShape(Q);this._changedPointerPositions.forEach(ae=>{const oe=l.getCapturedShape(ae.id)||this.getIntersection(ae),Ce=ae.id,se={evt:F,pointerId:Ce};var qe=ge!==oe;if(qe&&ge&&(ge._fireAndBubble(q.pointerout,Object.assign({},se),oe),ge._fireAndBubble(q.pointerleave,Object.assign({},se),oe)),oe){if(ne[oe._id])return;ne[oe._id]=!0}oe&&oe.isListening()?(Z=!0,qe&&(oe._fireAndBubble(q.pointerover,Object.assign({},se),ge),oe._fireAndBubble(q.pointerenter,Object.assign({},se),ge),this[Q+"targetShape"]=oe),oe._fireAndBubble(q.pointermove,Object.assign({},se))):ge&&(this._fire(q.pointerover,{evt:F,target:this,currentTarget:this,pointerId:Ce}),this[Q+"targetShape"]=null)}),Z||this._fire(q.pointermove,{evt:F,target:this,currentTarget:this,pointerId:this._changedPointerPositions[0].id})}_pointerup(F){const q=z(F.type),Q=V(F.type);if(!q)return;this.setPointersPositions(F);const J=this[Q+"ClickStartShape"],ne=this[Q+"ClickEndShape"];var Z={};let ge=!1;this._changedPointerPositions.forEach(ae=>{const oe=l.getCapturedShape(ae.id)||this.getIntersection(ae);if(oe){if(oe.releaseCapture(ae.id),Z[oe._id])return;Z[oe._id]=!0}const Ce=ae.id,se={evt:F,pointerId:Ce};let qe=!1;i.Konva["_"+Q+"InDblClickWindow"]?(qe=!0,clearTimeout(this[Q+"DblTimeout"])):s.DD.justDragged||(i.Konva["_"+Q+"InDblClickWindow"]=!0,clearTimeout(this[Q+"DblTimeout"])),this[Q+"DblTimeout"]=setTimeout(function(){i.Konva["_"+Q+"InDblClickWindow"]=!1},i.Konva.dblClickWindow),oe&&oe.isListening()?(ge=!0,this[Q+"ClickEndShape"]=oe,oe._fireAndBubble(q.pointerup,Object.assign({},se)),i.Konva["_"+Q+"ListenClick"]&&J&&J===oe&&(oe._fireAndBubble(q.pointerclick,Object.assign({},se)),qe&&ne&&ne===oe&&oe._fireAndBubble(q.pointerdblclick,Object.assign({},se)))):(this[Q+"ClickEndShape"]=null,i.Konva["_"+Q+"ListenClick"]&&this._fire(q.pointerclick,{evt:F,target:this,currentTarget:this,pointerId:Ce}),qe&&this._fire(q.pointerdblclick,{evt:F,target:this,currentTarget:this,pointerId:Ce}))}),ge||this._fire(q.pointerup,{evt:F,target:this,currentTarget:this,pointerId:this._changedPointerPositions[0].id}),i.Konva["_"+Q+"ListenClick"]=!1,F.cancelable&&Q!=="touch"&&F.preventDefault()}_contextmenu(F){this.setPointersPositions(F);var q=this.getIntersection(this.getPointerPosition());q&&q.isListening()?q._fireAndBubble($,{evt:F}):this._fire($,{evt:F,target:this,currentTarget:this})}_wheel(F){this.setPointersPositions(F);var q=this.getIntersection(this.getPointerPosition());q&&q.isListening()?q._fireAndBubble(M,{evt:F}):this._fire(M,{evt:F,target:this,currentTarget:this})}_pointercancel(F){this.setPointersPositions(F);const q=l.getCapturedShape(F.pointerId)||this.getIntersection(this.getPointerPosition());q&&q._fireAndBubble(_,l.createEvent(F)),l.releaseCapture(F.pointerId)}_lostpointercapture(F){l.releaseCapture(F.pointerId)}setPointersPositions(F){var q=this._getContentPosition(),Q=null,J=null;F=F||window.event,F.touches!==void 0?(this._pointerPositions=[],this._changedPointerPositions=[],Array.prototype.forEach.call(F.touches,ne=>{this._pointerPositions.push({id:ne.identifier,x:(ne.clientX-q.left)/q.scaleX,y:(ne.clientY-q.top)/q.scaleY})}),Array.prototype.forEach.call(F.changedTouches||F.touches,ne=>{this._changedPointerPositions.push({id:ne.identifier,x:(ne.clientX-q.left)/q.scaleX,y:(ne.clientY-q.top)/q.scaleY})})):(Q=(F.clientX-q.left)/q.scaleX,J=(F.clientY-q.top)/q.scaleY,this.pointerPos={x:Q,y:J},this._pointerPositions=[{x:Q,y:J,id:t.Util._getFirstPointerId(F)}],this._changedPointerPositions=[{x:Q,y:J,id:t.Util._getFirstPointerId(F)}])}_setPointerPosition(F){t.Util.warn('Method _setPointerPosition is deprecated. Use "stage.setPointersPositions(event)" instead.'),this.setPointersPositions(F)}_getContentPosition(){if(!this.content||!this.content.getBoundingClientRect)return{top:0,left:0,scaleX:1,scaleY:1};var F=this.content.getBoundingClientRect();return{top:F.top,left:F.left,scaleX:F.width/this.content.clientWidth||1,scaleY:F.height/this.content.clientHeight||1}}_buildDOM(){if(this.bufferCanvas=new o.SceneCanvas({width:this.width(),height:this.height()}),this.bufferHitCanvas=new o.HitCanvas({pixelRatio:1,width:this.width(),height:this.height()}),!!i.Konva.isBrowser){var F=this.container();if(!F)throw"Stage has no container. A container is required.";F.innerHTML="",this.content=document.createElement("div"),this.content.style.position="relative",this.content.style.userSelect="none",this.content.className="konvajs-content",this.content.setAttribute("role","presentation"),F.appendChild(this.content),this._resizeDOM()}}cache(){return t.Util.warn("Cache function is not allowed for stage. You may use cache only for layers, groups and shapes."),this}clearCache(){return this}batchDraw(){return this.getChildren().forEach(function(F){F.batchDraw()}),this}}e.Stage=W,W.prototype.nodeType=u,(0,a._registerNode)(W),n.Factory.addGetterSetter(W,"container")})(pB);var Dp={},mn={};(function(e){Object.defineProperty(e,"__esModule",{value:!0}),e.Shape=e.shapes=void 0;const t=De,n=jt,r=Re,i=At,o=he,s=De,a=$r;var l="hasShadow",u="shadowRGBA",c="patternImage",d="linearGradient",f="radialGradient";let h;function p(){return h||(h=n.Util.createCanvasElement().getContext("2d"),h)}e.shapes={};function m(k){const P=this.attrs.fillRule;P?k.fill(P):k.fill()}function S(k){k.stroke()}function v(k){k.fill()}function y(k){k.stroke()}function g(){this._clearCache(l)}function b(){this._clearCache(u)}function _(){this._clearCache(c)}function w(){this._clearCache(d)}function x(){this._clearCache(f)}class C extends i.Node{constructor(P){super(P);let A;for(;A=n.Util.getRandomColor(),!(A&&!(A in e.shapes)););this.colorKey=A,e.shapes[A]=this}getContext(){return n.Util.warn("shape.getContext() method is deprecated. Please do not use it."),this.getLayer().getContext()}getCanvas(){return n.Util.warn("shape.getCanvas() method is deprecated. Please do not use it."),this.getLayer().getCanvas()}getSceneFunc(){return this.attrs.sceneFunc||this._sceneFunc}getHitFunc(){return this.attrs.hitFunc||this._hitFunc}hasShadow(){return this._getCache(l,this._hasShadow)}_hasShadow(){return this.shadowEnabled()&&this.shadowOpacity()!==0&&!!(this.shadowColor()||this.shadowBlur()||this.shadowOffsetX()||this.shadowOffsetY())}_getFillPattern(){return this._getCache(c,this.__getFillPattern)}__getFillPattern(){if(this.fillPatternImage()){var P=p();const A=P.createPattern(this.fillPatternImage(),this.fillPatternRepeat()||"repeat");if(A&&A.setTransform){const $=new n.Transform;$.translate(this.fillPatternX(),this.fillPatternY()),$.rotate(t.Konva.getAngle(this.fillPatternRotation())),$.scale(this.fillPatternScaleX(),this.fillPatternScaleY()),$.translate(-1*this.fillPatternOffsetX(),-1*this.fillPatternOffsetY());const N=$.getMatrix(),T=typeof DOMMatrix>"u"?{a:N[0],b:N[1],c:N[2],d:N[3],e:N[4],f:N[5]}:new DOMMatrix(N);A.setTransform(T)}return A}}_getLinearGradient(){return this._getCache(d,this.__getLinearGradient)}__getLinearGradient(){var P=this.fillLinearGradientColorStops();if(P){for(var A=p(),$=this.fillLinearGradientStartPoint(),N=this.fillLinearGradientEndPoint(),T=A.createLinearGradient($.x,$.y,N.x,N.y),O=0;Othis.fillEnabled()&&!!(this.fill()||this.fillPatternImage()||this.fillLinearGradientColorStops()||this.fillRadialGradientColorStops()))}hasStroke(){return this._calculate("hasStroke",["strokeEnabled","strokeWidth","stroke","strokeLinearGradientColorStops"],()=>this.strokeEnabled()&&this.strokeWidth()&&!!(this.stroke()||this.strokeLinearGradientColorStops()))}hasHitStroke(){const P=this.hitStrokeWidth();return P==="auto"?this.hasStroke():this.strokeEnabled()&&!!P}intersects(P){var A=this.getStage(),$=A.bufferHitCanvas,N;return $.getContext().clear(),this.drawHit($,null,!0),N=$.context.getImageData(Math.round(P.x),Math.round(P.y),1,1).data,N[3]>0}destroy(){return i.Node.prototype.destroy.call(this),delete e.shapes[this.colorKey],delete this.colorKey,this}_useBufferCanvas(P){var A;if(!this.getStage()||!((A=this.attrs.perfectDrawEnabled)!==null&&A!==void 0?A:!0))return!1;const N=P||this.hasFill(),T=this.hasStroke(),O=this.getAbsoluteOpacity()!==1;if(N&&T&&O)return!0;const I=this.hasShadow(),M=this.shadowForStrokeEnabled();return!!(N&&T&&I&&M)}setStrokeHitEnabled(P){n.Util.warn("strokeHitEnabled property is deprecated. Please use hitStrokeWidth instead."),P?this.hitStrokeWidth("auto"):this.hitStrokeWidth(0)}getStrokeHitEnabled(){return this.hitStrokeWidth()!==0}getSelfRect(){var P=this.size();return{x:this._centroid?-P.width/2:0,y:this._centroid?-P.height/2:0,width:P.width,height:P.height}}getClientRect(P={}){const A=P.skipTransform,$=P.relativeTo,N=this.getSelfRect(),O=!P.skipStroke&&this.hasStroke()&&this.strokeWidth()||0,I=N.width+O,M=N.height+O,R=!P.skipShadow&&this.hasShadow(),D=R?this.shadowOffsetX():0,L=R?this.shadowOffsetY():0,V=I+Math.abs(D),z=M+Math.abs(L),U=R&&this.shadowBlur()||0,K=V+U*2,W=z+U*2,X={width:K,height:W,x:-(O/2+U)+Math.min(D,0)+N.x,y:-(O/2+U)+Math.min(L,0)+N.y};return A?X:this._transformedRect(X,$)}drawScene(P,A){var $=this.getLayer(),N=P||$.getCanvas(),T=N.getContext(),O=this._getCanvasCache(),I=this.getSceneFunc(),M=this.hasShadow(),R,D,L,V=N.isCache,z=A===this;if(!this.isVisible()&&!z)return this;if(O){T.save();var U=this.getAbsoluteTransform(A).getMatrix();return T.transform(U[0],U[1],U[2],U[3],U[4],U[5]),this._drawCachedSceneCanvas(T),T.restore(),this}if(!I)return this;if(T.save(),this._useBufferCanvas()&&!V){R=this.getStage(),D=R.bufferCanvas,L=D.getContext(),L.clear(),L.save(),L._applyLineJoin(this);var K=this.getAbsoluteTransform(A).getMatrix();L.transform(K[0],K[1],K[2],K[3],K[4],K[5]),I.call(this,L,this),L.restore();var W=D.pixelRatio;M&&T._applyShadow(this),T._applyOpacity(this),T._applyGlobalCompositeOperation(this),T.drawImage(D._canvas,0,0,D.width/W,D.height/W)}else{if(T._applyLineJoin(this),!z){var K=this.getAbsoluteTransform(A).getMatrix();T.transform(K[0],K[1],K[2],K[3],K[4],K[5]),T._applyOpacity(this),T._applyGlobalCompositeOperation(this)}M&&T._applyShadow(this),I.call(this,T,this)}return T.restore(),this}drawHit(P,A,$=!1){if(!this.shouldDrawHit(A,$))return this;var N=this.getLayer(),T=P||N.hitCanvas,O=T&&T.getContext(),I=this.hitFunc()||this.sceneFunc(),M=this._getCanvasCache(),R=M&&M.hit;if(this.colorKey||n.Util.warn("Looks like your canvas has a destroyed shape in it. Do not reuse shape after you destroyed it. If you want to reuse shape you should call remove() instead of destroy()"),R){O.save();var D=this.getAbsoluteTransform(A).getMatrix();return O.transform(D[0],D[1],D[2],D[3],D[4],D[5]),this._drawCachedHitCanvas(O),O.restore(),this}if(!I)return this;if(O.save(),O._applyLineJoin(this),!(this===A)){var V=this.getAbsoluteTransform(A).getMatrix();O.transform(V[0],V[1],V[2],V[3],V[4],V[5])}return I.call(this,O,this),O.restore(),this}drawHitFromCache(P=0){var A=this._getCanvasCache(),$=this._getCachedSceneCanvas(),N=A.hit,T=N.getContext(),O=N.getWidth(),I=N.getHeight(),M,R,D,L,V,z;T.clear(),T.drawImage($._canvas,0,0,O,I);try{for(M=T.getImageData(0,0,O,I),R=M.data,D=R.length,L=n.Util._hexToRgb(this.colorKey),V=0;VP?(R[V]=L.r,R[V+1]=L.g,R[V+2]=L.b,R[V+3]=255):R[V+3]=0;T.putImageData(M,0,0)}catch(U){n.Util.error("Unable to draw hit graph from cached scene canvas. "+U.message)}return this}hasPointerCapture(P){return a.hasPointerCapture(P,this)}setPointerCapture(P){a.setPointerCapture(P,this)}releaseCapture(P){a.releaseCapture(P,this)}}e.Shape=C,C.prototype._fillFunc=m,C.prototype._strokeFunc=S,C.prototype._fillFuncHit=v,C.prototype._strokeFuncHit=y,C.prototype._centroid=!1,C.prototype.nodeType="Shape",(0,s._registerNode)(C),C.prototype.eventListeners={},C.prototype.on.call(C.prototype,"shadowColorChange.konva shadowBlurChange.konva shadowOffsetChange.konva shadowOpacityChange.konva shadowEnabledChange.konva",g),C.prototype.on.call(C.prototype,"shadowColorChange.konva shadowOpacityChange.konva shadowEnabledChange.konva",b),C.prototype.on.call(C.prototype,"fillPriorityChange.konva fillPatternImageChange.konva fillPatternRepeatChange.konva fillPatternScaleXChange.konva fillPatternScaleYChange.konva fillPatternOffsetXChange.konva fillPatternOffsetYChange.konva fillPatternXChange.konva fillPatternYChange.konva fillPatternRotationChange.konva",_),C.prototype.on.call(C.prototype,"fillPriorityChange.konva fillLinearGradientColorStopsChange.konva fillLinearGradientStartPointXChange.konva fillLinearGradientStartPointYChange.konva fillLinearGradientEndPointXChange.konva fillLinearGradientEndPointYChange.konva",w),C.prototype.on.call(C.prototype,"fillPriorityChange.konva fillRadialGradientColorStopsChange.konva fillRadialGradientStartPointXChange.konva fillRadialGradientStartPointYChange.konva fillRadialGradientEndPointXChange.konva fillRadialGradientEndPointYChange.konva fillRadialGradientStartRadiusChange.konva fillRadialGradientEndRadiusChange.konva",x),r.Factory.addGetterSetter(C,"stroke",void 0,(0,o.getStringOrGradientValidator)()),r.Factory.addGetterSetter(C,"strokeWidth",2,(0,o.getNumberValidator)()),r.Factory.addGetterSetter(C,"fillAfterStrokeEnabled",!1),r.Factory.addGetterSetter(C,"hitStrokeWidth","auto",(0,o.getNumberOrAutoValidator)()),r.Factory.addGetterSetter(C,"strokeHitEnabled",!0,(0,o.getBooleanValidator)()),r.Factory.addGetterSetter(C,"perfectDrawEnabled",!0,(0,o.getBooleanValidator)()),r.Factory.addGetterSetter(C,"shadowForStrokeEnabled",!0,(0,o.getBooleanValidator)()),r.Factory.addGetterSetter(C,"lineJoin"),r.Factory.addGetterSetter(C,"lineCap"),r.Factory.addGetterSetter(C,"sceneFunc"),r.Factory.addGetterSetter(C,"hitFunc"),r.Factory.addGetterSetter(C,"dash"),r.Factory.addGetterSetter(C,"dashOffset",0,(0,o.getNumberValidator)()),r.Factory.addGetterSetter(C,"shadowColor",void 0,(0,o.getStringValidator)()),r.Factory.addGetterSetter(C,"shadowBlur",0,(0,o.getNumberValidator)()),r.Factory.addGetterSetter(C,"shadowOpacity",1,(0,o.getNumberValidator)()),r.Factory.addComponentsGetterSetter(C,"shadowOffset",["x","y"]),r.Factory.addGetterSetter(C,"shadowOffsetX",0,(0,o.getNumberValidator)()),r.Factory.addGetterSetter(C,"shadowOffsetY",0,(0,o.getNumberValidator)()),r.Factory.addGetterSetter(C,"fillPatternImage"),r.Factory.addGetterSetter(C,"fill",void 0,(0,o.getStringOrGradientValidator)()),r.Factory.addGetterSetter(C,"fillPatternX",0,(0,o.getNumberValidator)()),r.Factory.addGetterSetter(C,"fillPatternY",0,(0,o.getNumberValidator)()),r.Factory.addGetterSetter(C,"fillLinearGradientColorStops"),r.Factory.addGetterSetter(C,"strokeLinearGradientColorStops"),r.Factory.addGetterSetter(C,"fillRadialGradientStartRadius",0),r.Factory.addGetterSetter(C,"fillRadialGradientEndRadius",0),r.Factory.addGetterSetter(C,"fillRadialGradientColorStops"),r.Factory.addGetterSetter(C,"fillPatternRepeat","repeat"),r.Factory.addGetterSetter(C,"fillEnabled",!0),r.Factory.addGetterSetter(C,"strokeEnabled",!0),r.Factory.addGetterSetter(C,"shadowEnabled",!0),r.Factory.addGetterSetter(C,"dashEnabled",!0),r.Factory.addGetterSetter(C,"strokeScaleEnabled",!0),r.Factory.addGetterSetter(C,"fillPriority","color"),r.Factory.addComponentsGetterSetter(C,"fillPatternOffset",["x","y"]),r.Factory.addGetterSetter(C,"fillPatternOffsetX",0,(0,o.getNumberValidator)()),r.Factory.addGetterSetter(C,"fillPatternOffsetY",0,(0,o.getNumberValidator)()),r.Factory.addComponentsGetterSetter(C,"fillPatternScale",["x","y"]),r.Factory.addGetterSetter(C,"fillPatternScaleX",1,(0,o.getNumberValidator)()),r.Factory.addGetterSetter(C,"fillPatternScaleY",1,(0,o.getNumberValidator)()),r.Factory.addComponentsGetterSetter(C,"fillLinearGradientStartPoint",["x","y"]),r.Factory.addComponentsGetterSetter(C,"strokeLinearGradientStartPoint",["x","y"]),r.Factory.addGetterSetter(C,"fillLinearGradientStartPointX",0),r.Factory.addGetterSetter(C,"strokeLinearGradientStartPointX",0),r.Factory.addGetterSetter(C,"fillLinearGradientStartPointY",0),r.Factory.addGetterSetter(C,"strokeLinearGradientStartPointY",0),r.Factory.addComponentsGetterSetter(C,"fillLinearGradientEndPoint",["x","y"]),r.Factory.addComponentsGetterSetter(C,"strokeLinearGradientEndPoint",["x","y"]),r.Factory.addGetterSetter(C,"fillLinearGradientEndPointX",0),r.Factory.addGetterSetter(C,"strokeLinearGradientEndPointX",0),r.Factory.addGetterSetter(C,"fillLinearGradientEndPointY",0),r.Factory.addGetterSetter(C,"strokeLinearGradientEndPointY",0),r.Factory.addComponentsGetterSetter(C,"fillRadialGradientStartPoint",["x","y"]),r.Factory.addGetterSetter(C,"fillRadialGradientStartPointX",0),r.Factory.addGetterSetter(C,"fillRadialGradientStartPointY",0),r.Factory.addComponentsGetterSetter(C,"fillRadialGradientEndPoint",["x","y"]),r.Factory.addGetterSetter(C,"fillRadialGradientEndPointX",0),r.Factory.addGetterSetter(C,"fillRadialGradientEndPointY",0),r.Factory.addGetterSetter(C,"fillPatternRotation",0),r.Factory.addGetterSetter(C,"fillRule",void 0,(0,o.getStringValidator)()),r.Factory.backCompat(C,{dashArray:"dash",getDashArray:"getDash",setDashArray:"getDash",drawFunc:"sceneFunc",getDrawFunc:"getSceneFunc",setDrawFunc:"setSceneFunc",drawHitFunc:"hitFunc",getDrawHitFunc:"getHitFunc",setDrawHitFunc:"setHitFunc"})})(mn);Object.defineProperty(Dp,"__esModule",{value:!0});Dp.Layer=void 0;const Uo=jt,k_=Ul,hu=At,W3=Re,Jk=Li,o2e=he,s2e=mn,a2e=De;var l2e="#",u2e="beforeDraw",c2e="draw",yB=[{x:0,y:0},{x:-1,y:-1},{x:1,y:-1},{x:1,y:1},{x:-1,y:1}],d2e=yB.length;class td extends k_.Container{constructor(t){super(t),this.canvas=new Jk.SceneCanvas,this.hitCanvas=new Jk.HitCanvas({pixelRatio:1}),this._waitingForDraw=!1,this.on("visibleChange.konva",this._checkVisibility),this._checkVisibility(),this.on("imageSmoothingEnabledChange.konva",this._setSmoothEnabled),this._setSmoothEnabled()}createPNGStream(){return this.canvas._canvas.createPNGStream()}getCanvas(){return this.canvas}getNativeCanvasElement(){return this.canvas._canvas}getHitCanvas(){return this.hitCanvas}getContext(){return this.getCanvas().getContext()}clear(t){return this.getContext().clear(t),this.getHitCanvas().getContext().clear(t),this}setZIndex(t){super.setZIndex(t);var n=this.getStage();return n&&n.content&&(n.content.removeChild(this.getNativeCanvasElement()),t{this.draw(),this._waitingForDraw=!1})),this}getIntersection(t){if(!this.isListening()||!this.isVisible())return null;for(var n=1,r=!1;;){for(let i=0;i0)return{antialiased:!0};return{}}drawScene(t,n){var r=this.getLayer(),i=t||r&&r.getCanvas();return this._fire(u2e,{node:this}),this.clearBeforeDraw()&&i.getContext().clear(),k_.Container.prototype.drawScene.call(this,i,n),this._fire(c2e,{node:this}),this}drawHit(t,n){var r=this.getLayer(),i=t||r&&r.hitCanvas;return r&&r.clearBeforeDraw()&&r.getHitCanvas().getContext().clear(),k_.Container.prototype.drawHit.call(this,i,n),this}enableHitGraph(){return this.hitGraphEnabled(!0),this}disableHitGraph(){return this.hitGraphEnabled(!1),this}setHitGraphEnabled(t){Uo.Util.warn("hitGraphEnabled method is deprecated. Please use layer.listening() instead."),this.listening(t)}getHitGraphEnabled(t){return Uo.Util.warn("hitGraphEnabled method is deprecated. Please use layer.listening() instead."),this.listening()}toggleHitCanvas(){if(!(!this.parent||!this.parent.content)){var t=this.parent,n=!!this.hitCanvas._canvas.parentNode;n?t.content.removeChild(this.hitCanvas._canvas):t.content.appendChild(this.hitCanvas._canvas)}}destroy(){return Uo.Util.releaseCanvas(this.getNativeCanvasElement(),this.getHitCanvas()._canvas),super.destroy()}}Dp.Layer=td;td.prototype.nodeType="Layer";(0,a2e._registerNode)(td);W3.Factory.addGetterSetter(td,"imageSmoothingEnabled",!0);W3.Factory.addGetterSetter(td,"clearBeforeDraw",!0);W3.Factory.addGetterSetter(td,"hitGraphEnabled",!0,(0,o2e.getBooleanValidator)());var D1={};Object.defineProperty(D1,"__esModule",{value:!0});D1.FastLayer=void 0;const f2e=jt,h2e=Dp,p2e=De;class K3 extends h2e.Layer{constructor(t){super(t),this.listening(!1),f2e.Util.warn('Konva.Fast layer is deprecated. Please use "new Konva.Layer({ listening: false })" instead.')}}D1.FastLayer=K3;K3.prototype.nodeType="FastLayer";(0,p2e._registerNode)(K3);var nd={};Object.defineProperty(nd,"__esModule",{value:!0});nd.Group=void 0;const g2e=jt,m2e=Ul,y2e=De;class Y3 extends m2e.Container{_validateAdd(t){var n=t.getType();n!=="Group"&&n!=="Shape"&&g2e.Util.throw("You may only add groups and shapes to groups.")}}nd.Group=Y3;Y3.prototype.nodeType="Group";(0,y2e._registerNode)(Y3);var rd={};Object.defineProperty(rd,"__esModule",{value:!0});rd.Animation=void 0;const A_=De,eA=jt;var O_=function(){return A_.glob.performance&&A_.glob.performance.now?function(){return A_.glob.performance.now()}:function(){return new Date().getTime()}}();class ao{constructor(t,n){this.id=ao.animIdCounter++,this.frame={time:0,timeDiff:0,lastTime:O_(),frameRate:0},this.func=t,this.setLayers(n)}setLayers(t){var n=[];return t?t.length>0?n=t:n=[t]:n=[],this.layers=n,this}getLayers(){return this.layers}addLayer(t){var n=this.layers,r=n.length,i;for(i=0;ithis.duration?this.yoyo?(this._time=this.duration,this.reverse()):this.finish():p<0?this.yoyo?(this._time=0,this.play()):this.reset():(this._time=p,this.update())}getTime(){return this._time}setPosition(p){this.prevPos=this._pos,this.propFunc(p),this._pos=p}getPosition(p){return p===void 0&&(p=this._time),this.func(p,this.begin,this._change,this.duration)}play(){this.state=a,this._startTime=this.getTimer()-this._time,this.onEnterFrame(),this.fire("onPlay")}reverse(){this.state=l,this._time=this.duration-this._time,this._startTime=this.getTimer()-this._time,this.onEnterFrame(),this.fire("onReverse")}seek(p){this.pause(),this._time=p,this.update(),this.fire("onSeek")}reset(){this.pause(),this._time=0,this.update(),this.fire("onReset")}finish(){this.pause(),this._time=this.duration,this.update(),this.fire("onFinish")}update(){this.setPosition(this.getPosition(this._time)),this.fire("onUpdate")}onEnterFrame(){var p=this.getTimer()-this._startTime;this.state===a?this.setTime(p):this.state===l&&this.setTime(this.duration-p)}pause(){this.state=s,this.fire("onPause")}getTimer(){return new Date().getTime()}}class f{constructor(p){var m=this,S=p.node,v=S._id,y,g=p.easing||e.Easings.Linear,b=!!p.yoyo,_;typeof p.duration>"u"?y=.3:p.duration===0?y=.001:y=p.duration,this.node=S,this._id=u++;var w=S.getLayer()||(S instanceof i.Konva.Stage?S.getLayers():null);w||t.Util.error("Tween constructor have `node` that is not in a layer. Please add node into layer first."),this.anim=new n.Animation(function(){m.tween.onEnterFrame()},w),this.tween=new d(_,function(x){m._tweenFunc(x)},g,0,1,y*1e3,b),this._addListeners(),f.attrs[v]||(f.attrs[v]={}),f.attrs[v][this._id]||(f.attrs[v][this._id]={}),f.tweens[v]||(f.tweens[v]={});for(_ in p)o[_]===void 0&&this._addAttr(_,p[_]);this.reset(),this.onFinish=p.onFinish,this.onReset=p.onReset,this.onUpdate=p.onUpdate}_addAttr(p,m){var S=this.node,v=S._id,y,g,b,_,w,x,C,k;if(b=f.tweens[v][p],b&&delete f.attrs[v][b][p],y=S.getAttr(p),t.Util._isArray(m))if(g=[],w=Math.max(m.length,y.length),p==="points"&&m.length!==y.length&&(m.length>y.length?(C=y,y=t.Util._prepareArrayForTween(y,m,S.closed())):(x=m,m=t.Util._prepareArrayForTween(m,y,S.closed()))),p.indexOf("fill")===0)for(_=0;_{this.anim.start()},this.tween.onReverse=()=>{this.anim.start()},this.tween.onPause=()=>{this.anim.stop()},this.tween.onFinish=()=>{var p=this.node,m=f.attrs[p._id][this._id];m.points&&m.points.trueEnd&&p.setAttr("points",m.points.trueEnd),this.onFinish&&this.onFinish.call(this)},this.tween.onReset=()=>{var p=this.node,m=f.attrs[p._id][this._id];m.points&&m.points.trueStart&&p.points(m.points.trueStart),this.onReset&&this.onReset()},this.tween.onUpdate=()=>{this.onUpdate&&this.onUpdate.call(this)}}play(){return this.tween.play(),this}reverse(){return this.tween.reverse(),this}reset(){return this.tween.reset(),this}seek(p){return this.tween.seek(p*1e3),this}pause(){return this.tween.pause(),this}finish(){return this.tween.finish(),this}destroy(){var p=this.node._id,m=this._id,S=f.tweens[p],v;this.pause();for(v in S)delete f.tweens[p][v];delete f.attrs[p][m]}}e.Tween=f,f.attrs={},f.tweens={},r.Node.prototype.to=function(h){var p=h.onFinish;h.node=this,h.onFinish=function(){this.destroy(),p&&p()};var m=new f(h);m.play()},e.Easings={BackEaseIn(h,p,m,S){var v=1.70158;return m*(h/=S)*h*((v+1)*h-v)+p},BackEaseOut(h,p,m,S){var v=1.70158;return m*((h=h/S-1)*h*((v+1)*h+v)+1)+p},BackEaseInOut(h,p,m,S){var v=1.70158;return(h/=S/2)<1?m/2*(h*h*(((v*=1.525)+1)*h-v))+p:m/2*((h-=2)*h*(((v*=1.525)+1)*h+v)+2)+p},ElasticEaseIn(h,p,m,S,v,y){var g=0;return h===0?p:(h/=S)===1?p+m:(y||(y=S*.3),!v||v0?t:n),c=s*n,d=a*(a>0?t:n),f=l*(l>0?n:t);return{x:u,y:r?-1*f:d,width:c-u,height:f-d}}}L1.Arc=Cs;Cs.prototype._centroid=!0;Cs.prototype.className="Arc";Cs.prototype._attrsAffectingSize=["innerRadius","outerRadius"];(0,b2e._registerNode)(Cs);$1.Factory.addGetterSetter(Cs,"innerRadius",0,(0,F1.getNumberValidator)());$1.Factory.addGetterSetter(Cs,"outerRadius",0,(0,F1.getNumberValidator)());$1.Factory.addGetterSetter(Cs,"angle",0,(0,F1.getNumberValidator)());$1.Factory.addGetterSetter(Cs,"clockwise",!1,(0,F1.getBooleanValidator)());var B1={},Lp={};Object.defineProperty(Lp,"__esModule",{value:!0});Lp.Line=void 0;const j1=Re,S2e=mn,bB=he,_2e=De;function wx(e,t,n,r,i,o,s){var a=Math.sqrt(Math.pow(n-e,2)+Math.pow(r-t,2)),l=Math.sqrt(Math.pow(i-n,2)+Math.pow(o-r,2)),u=s*a/(a+l),c=s*l/(a+l),d=n-u*(i-e),f=r-u*(o-t),h=n+c*(i-e),p=r+c*(o-t);return[d,f,h,p]}function nA(e,t){var n=e.length,r=[],i,o;for(i=2;i4){for(a=this.getTensionPoints(),l=a.length,u=o?0:4,o||t.quadraticCurveTo(a[0],a[1],a[2],a[3]);u{let u,c,d;u=l/2,c=0;for(let h=0;h<20;h++)d=u*e.tValues[20][h]+u,c+=e.cValues[20][h]*r(s,a,d);return u*c};e.getCubicArcLength=t;const n=(s,a,l)=>{l===void 0&&(l=1);const u=s[0]-2*s[1]+s[2],c=a[0]-2*a[1]+a[2],d=2*s[1]-2*s[0],f=2*a[1]-2*a[0],h=4*(u*u+c*c),p=4*(u*d+c*f),m=d*d+f*f;if(h===0)return l*Math.sqrt(Math.pow(s[2]-s[0],2)+Math.pow(a[2]-a[0],2));const S=p/(2*h),v=m/h,y=l+S,g=v-S*S,b=y*y+g>0?Math.sqrt(y*y+g):0,_=S*S+g>0?Math.sqrt(S*S+g):0,w=S+Math.sqrt(S*S+g)!==0?g*Math.log(Math.abs((y+b)/(S+_))):0;return Math.sqrt(h)/2*(y*b-S*_+w)};e.getQuadraticArcLength=n;function r(s,a,l){const u=i(1,l,s),c=i(1,l,a),d=u*u+c*c;return Math.sqrt(d)}const i=(s,a,l)=>{const u=l.length-1;let c,d;if(u===0)return 0;if(s===0){d=0;for(let f=0;f<=u;f++)d+=e.binomialCoefficients[u][f]*Math.pow(1-a,u-f)*Math.pow(a,f)*l[f];return d}else{c=new Array(u);for(let f=0;f{let u=1,c=s/a,d=(s-l(c))/a,f=0;for(;u>.001;){const h=l(c+d),p=Math.abs(s-h)/a;if(p500)break}return c};e.t2length=o})(SB);Object.defineProperty(id,"__esModule",{value:!0});id.Path=void 0;const w2e=Re,x2e=mn,C2e=De,pu=SB;class ln extends x2e.Shape{constructor(t){super(t),this.dataArray=[],this.pathLength=0,this._readDataAttribute(),this.on("dataChange.konva",function(){this._readDataAttribute()})}_readDataAttribute(){this.dataArray=ln.parsePathData(this.data()),this.pathLength=ln.getPathLength(this.dataArray)}_sceneFunc(t){var n=this.dataArray;t.beginPath();for(var r=!1,i=0;ic?u:c,S=u>c?1:u/c,v=u>c?c/u:1;t.translate(a,l),t.rotate(h),t.scale(S,v),t.arc(0,0,m,d,d+f,1-p),t.scale(1/S,1/v),t.rotate(-h),t.translate(-a,-l);break;case"z":r=!0,t.closePath();break}}!r&&!this.hasFill()?t.strokeShape(this):t.fillStrokeShape(this)}getSelfRect(){var t=[];this.dataArray.forEach(function(u){if(u.command==="A"){var c=u.points[4],d=u.points[5],f=u.points[4]+d,h=Math.PI/180;if(Math.abs(c-f)f;p-=h){const m=ln.getPointOnEllipticalArc(u.points[0],u.points[1],u.points[2],u.points[3],p,0);t.push(m.x,m.y)}else for(let p=c+h;pn[i].pathLength;)t-=n[i].pathLength,++i;if(i===o)return r=n[i-1].points.slice(-2),{x:r[0],y:r[1]};if(t<.01)return r=n[i].points.slice(0,2),{x:r[0],y:r[1]};var s=n[i],a=s.points;switch(s.command){case"L":return ln.getPointOnLine(t,s.start.x,s.start.y,a[0],a[1]);case"C":return ln.getPointOnCubicBezier((0,pu.t2length)(t,ln.getPathLength(n),m=>(0,pu.getCubicArcLength)([s.start.x,a[0],a[2],a[4]],[s.start.y,a[1],a[3],a[5]],m)),s.start.x,s.start.y,a[0],a[1],a[2],a[3],a[4],a[5]);case"Q":return ln.getPointOnQuadraticBezier((0,pu.t2length)(t,ln.getPathLength(n),m=>(0,pu.getQuadraticArcLength)([s.start.x,a[0],a[2]],[s.start.y,a[1],a[3]],m)),s.start.x,s.start.y,a[0],a[1],a[2],a[3]);case"A":var l=a[0],u=a[1],c=a[2],d=a[3],f=a[4],h=a[5],p=a[6];return f+=h*t/s.pathLength,ln.getPointOnEllipticalArc(l,u,c,d,f,p)}return null}static getPointOnLine(t,n,r,i,o,s,a){s===void 0&&(s=n),a===void 0&&(a=r);var l=(o-r)/(i-n+1e-8),u=Math.sqrt(t*t/(1+l*l));i0&&!isNaN(p[0]);){var y=null,g=[],b=l,_=u,w,x,C,k,P,A,$,N,T,O;switch(h){case"l":l+=p.shift(),u+=p.shift(),y="L",g.push(l,u);break;case"L":l=p.shift(),u=p.shift(),g.push(l,u);break;case"m":var I=p.shift(),M=p.shift();if(l+=I,u+=M,y="M",s.length>2&&s[s.length-1].command==="z"){for(var R=s.length-2;R>=0;R--)if(s[R].command==="M"){l=s[R].points[0]+I,u=s[R].points[1]+M;break}}g.push(l,u),h="l";break;case"M":l=p.shift(),u=p.shift(),y="M",g.push(l,u),h="L";break;case"h":l+=p.shift(),y="L",g.push(l,u);break;case"H":l=p.shift(),y="L",g.push(l,u);break;case"v":u+=p.shift(),y="L",g.push(l,u);break;case"V":u=p.shift(),y="L",g.push(l,u);break;case"C":g.push(p.shift(),p.shift(),p.shift(),p.shift()),l=p.shift(),u=p.shift(),g.push(l,u);break;case"c":g.push(l+p.shift(),u+p.shift(),l+p.shift(),u+p.shift()),l+=p.shift(),u+=p.shift(),y="C",g.push(l,u);break;case"S":x=l,C=u,w=s[s.length-1],w.command==="C"&&(x=l+(l-w.points[2]),C=u+(u-w.points[3])),g.push(x,C,p.shift(),p.shift()),l=p.shift(),u=p.shift(),y="C",g.push(l,u);break;case"s":x=l,C=u,w=s[s.length-1],w.command==="C"&&(x=l+(l-w.points[2]),C=u+(u-w.points[3])),g.push(x,C,l+p.shift(),u+p.shift()),l+=p.shift(),u+=p.shift(),y="C",g.push(l,u);break;case"Q":g.push(p.shift(),p.shift()),l=p.shift(),u=p.shift(),g.push(l,u);break;case"q":g.push(l+p.shift(),u+p.shift()),l+=p.shift(),u+=p.shift(),y="Q",g.push(l,u);break;case"T":x=l,C=u,w=s[s.length-1],w.command==="Q"&&(x=l+(l-w.points[0]),C=u+(u-w.points[1])),l=p.shift(),u=p.shift(),y="Q",g.push(x,C,l,u);break;case"t":x=l,C=u,w=s[s.length-1],w.command==="Q"&&(x=l+(l-w.points[0]),C=u+(u-w.points[1])),l+=p.shift(),u+=p.shift(),y="Q",g.push(x,C,l,u);break;case"A":k=p.shift(),P=p.shift(),A=p.shift(),$=p.shift(),N=p.shift(),T=l,O=u,l=p.shift(),u=p.shift(),y="A",g=this.convertEndpointToCenterParameterization(T,O,l,u,$,N,k,P,A);break;case"a":k=p.shift(),P=p.shift(),A=p.shift(),$=p.shift(),N=p.shift(),T=l,O=u,l+=p.shift(),u+=p.shift(),y="A",g=this.convertEndpointToCenterParameterization(T,O,l,u,$,N,k,P,A);break}s.push({command:y||h,points:g,start:{x:b,y:_},pathLength:this.calcLength(b,_,y||h,g)})}(h==="z"||h==="Z")&&s.push({command:"z",points:[],start:void 0,pathLength:0})}return s}static calcLength(t,n,r,i){var o,s,a,l,u=ln;switch(r){case"L":return u.getLineLength(t,n,i[0],i[1]);case"C":return(0,pu.getCubicArcLength)([t,i[0],i[2],i[4]],[n,i[1],i[3],i[5]],1);case"Q":return(0,pu.getQuadraticArcLength)([t,i[0],i[2]],[n,i[1],i[3]],1);case"A":o=0;var c=i[4],d=i[5],f=i[4]+d,h=Math.PI/180;if(Math.abs(c-f)f;l-=h)a=u.getPointOnEllipticalArc(i[0],i[1],i[2],i[3],l,0),o+=u.getLineLength(s.x,s.y,a.x,a.y),s=a;else for(l=c+h;l1&&(a*=Math.sqrt(h),l*=Math.sqrt(h));var p=Math.sqrt((a*a*(l*l)-a*a*(f*f)-l*l*(d*d))/(a*a*(f*f)+l*l*(d*d)));o===s&&(p*=-1),isNaN(p)&&(p=0);var m=p*a*f/l,S=p*-l*d/a,v=(t+r)/2+Math.cos(c)*m-Math.sin(c)*S,y=(n+i)/2+Math.sin(c)*m+Math.cos(c)*S,g=function(P){return Math.sqrt(P[0]*P[0]+P[1]*P[1])},b=function(P,A){return(P[0]*A[0]+P[1]*A[1])/(g(P)*g(A))},_=function(P,A){return(P[0]*A[1]=1&&(k=0),s===0&&k>0&&(k=k-2*Math.PI),s===1&&k<0&&(k=k+2*Math.PI),[v,y,a,l,w,k,c,s]}}id.Path=ln;ln.prototype.className="Path";ln.prototype._attrsAffectingSize=["data"];(0,C2e._registerNode)(ln);w2e.Factory.addGetterSetter(ln,"data");Object.defineProperty(B1,"__esModule",{value:!0});B1.Arrow=void 0;const V1=Re,T2e=Lp,_B=he,E2e=De,rA=id;class Hl extends T2e.Line{_sceneFunc(t){super._sceneFunc(t);var n=Math.PI*2,r=this.points(),i=r,o=this.tension()!==0&&r.length>4;o&&(i=this.getTensionPoints());var s=this.pointerLength(),a=r.length,l,u;if(o){const f=[i[i.length-4],i[i.length-3],i[i.length-2],i[i.length-1],r[a-2],r[a-1]],h=rA.Path.calcLength(i[i.length-4],i[i.length-3],"C",f),p=rA.Path.getPointOnQuadraticBezier(Math.min(1,1-s/h),f[0],f[1],f[2],f[3],f[4],f[5]);l=r[a-2]-p.x,u=r[a-1]-p.y}else l=r[a-2]-r[a-4],u=r[a-1]-r[a-3];var c=(Math.atan2(u,l)+n)%n,d=this.pointerWidth();this.pointerAtEnding()&&(t.save(),t.beginPath(),t.translate(r[a-2],r[a-1]),t.rotate(c),t.moveTo(0,0),t.lineTo(-s,d/2),t.lineTo(-s,-d/2),t.closePath(),t.restore(),this.__fillStroke(t)),this.pointerAtBeginning()&&(t.save(),t.beginPath(),t.translate(r[0],r[1]),o?(l=(i[0]+i[2])/2-r[0],u=(i[1]+i[3])/2-r[1]):(l=r[2]-r[0],u=r[3]-r[1]),t.rotate((Math.atan2(-u,-l)+n)%n),t.moveTo(0,0),t.lineTo(-s,d/2),t.lineTo(-s,-d/2),t.closePath(),t.restore(),this.__fillStroke(t))}__fillStroke(t){var n=this.dashEnabled();n&&(this.attrs.dashEnabled=!1,t.setLineDash([])),t.fillStrokeShape(this),n&&(this.attrs.dashEnabled=!0)}getSelfRect(){const t=super.getSelfRect(),n=this.pointerWidth()/2;return{x:t.x-n,y:t.y-n,width:t.width+n*2,height:t.height+n*2}}}B1.Arrow=Hl;Hl.prototype.className="Arrow";(0,E2e._registerNode)(Hl);V1.Factory.addGetterSetter(Hl,"pointerLength",10,(0,_B.getNumberValidator)());V1.Factory.addGetterSetter(Hl,"pointerWidth",10,(0,_B.getNumberValidator)());V1.Factory.addGetterSetter(Hl,"pointerAtBeginning",!1);V1.Factory.addGetterSetter(Hl,"pointerAtEnding",!0);var z1={};Object.defineProperty(z1,"__esModule",{value:!0});z1.Circle=void 0;const P2e=Re,k2e=mn,A2e=he,O2e=De;class od extends k2e.Shape{_sceneFunc(t){t.beginPath(),t.arc(0,0,this.attrs.radius||0,0,Math.PI*2,!1),t.closePath(),t.fillStrokeShape(this)}getWidth(){return this.radius()*2}getHeight(){return this.radius()*2}setWidth(t){this.radius()!==t/2&&this.radius(t/2)}setHeight(t){this.radius()!==t/2&&this.radius(t/2)}}z1.Circle=od;od.prototype._centroid=!0;od.prototype.className="Circle";od.prototype._attrsAffectingSize=["radius"];(0,O2e._registerNode)(od);P2e.Factory.addGetterSetter(od,"radius",0,(0,A2e.getNumberValidator)());var U1={};Object.defineProperty(U1,"__esModule",{value:!0});U1.Ellipse=void 0;const X3=Re,R2e=mn,wB=he,I2e=De;class Na extends R2e.Shape{_sceneFunc(t){var n=this.radiusX(),r=this.radiusY();t.beginPath(),t.save(),n!==r&&t.scale(1,r/n),t.arc(0,0,n,0,Math.PI*2,!1),t.restore(),t.closePath(),t.fillStrokeShape(this)}getWidth(){return this.radiusX()*2}getHeight(){return this.radiusY()*2}setWidth(t){this.radiusX(t/2)}setHeight(t){this.radiusY(t/2)}}U1.Ellipse=Na;Na.prototype.className="Ellipse";Na.prototype._centroid=!0;Na.prototype._attrsAffectingSize=["radiusX","radiusY"];(0,I2e._registerNode)(Na);X3.Factory.addComponentsGetterSetter(Na,"radius",["x","y"]);X3.Factory.addGetterSetter(Na,"radiusX",0,(0,wB.getNumberValidator)());X3.Factory.addGetterSetter(Na,"radiusY",0,(0,wB.getNumberValidator)());var G1={};Object.defineProperty(G1,"__esModule",{value:!0});G1.Image=void 0;const R_=jt,ql=Re,M2e=mn,N2e=De,$p=he;let No=class xB extends M2e.Shape{constructor(t){super(t),this.on("imageChange.konva",()=>{this._setImageLoad()}),this._setImageLoad()}_setImageLoad(){const t=this.image();t&&t.complete||t&&t.readyState===4||t&&t.addEventListener&&t.addEventListener("load",()=>{this._requestDraw()})}_useBufferCanvas(){return super._useBufferCanvas(!0)}_sceneFunc(t){const n=this.getWidth(),r=this.getHeight(),i=this.cornerRadius(),o=this.attrs.image;let s;if(o){const a=this.attrs.cropWidth,l=this.attrs.cropHeight;a&&l?s=[o,this.cropX(),this.cropY(),a,l,0,0,n,r]:s=[o,0,0,n,r]}(this.hasFill()||this.hasStroke()||i)&&(t.beginPath(),i?R_.Util.drawRoundedRectPath(t,n,r,i):t.rect(0,0,n,r),t.closePath(),t.fillStrokeShape(this)),o&&(i&&t.clip(),t.drawImage.apply(t,s))}_hitFunc(t){var n=this.width(),r=this.height(),i=this.cornerRadius();t.beginPath(),i?R_.Util.drawRoundedRectPath(t,n,r,i):t.rect(0,0,n,r),t.closePath(),t.fillStrokeShape(this)}getWidth(){var t,n;return(t=this.attrs.width)!==null&&t!==void 0?t:(n=this.image())===null||n===void 0?void 0:n.width}getHeight(){var t,n;return(t=this.attrs.height)!==null&&t!==void 0?t:(n=this.image())===null||n===void 0?void 0:n.height}static fromURL(t,n,r=null){var i=R_.Util.createImageElement();i.onload=function(){var o=new xB({image:i});n(o)},i.onerror=r,i.crossOrigin="Anonymous",i.src=t}};G1.Image=No;No.prototype.className="Image";(0,N2e._registerNode)(No);ql.Factory.addGetterSetter(No,"cornerRadius",0,(0,$p.getNumberOrArrayOfNumbersValidator)(4));ql.Factory.addGetterSetter(No,"image");ql.Factory.addComponentsGetterSetter(No,"crop",["x","y","width","height"]);ql.Factory.addGetterSetter(No,"cropX",0,(0,$p.getNumberValidator)());ql.Factory.addGetterSetter(No,"cropY",0,(0,$p.getNumberValidator)());ql.Factory.addGetterSetter(No,"cropWidth",0,(0,$p.getNumberValidator)());ql.Factory.addGetterSetter(No,"cropHeight",0,(0,$p.getNumberValidator)());var Bc={};Object.defineProperty(Bc,"__esModule",{value:!0});Bc.Tag=Bc.Label=void 0;const H1=Re,D2e=mn,L2e=nd,Q3=he,CB=De;var TB=["fontFamily","fontSize","fontStyle","padding","lineHeight","text","width","height","pointerDirection","pointerWidth","pointerHeight"],$2e="Change.konva",F2e="none",xx="up",Cx="right",Tx="down",Ex="left",B2e=TB.length;class Z3 extends L2e.Group{constructor(t){super(t),this.on("add.konva",function(n){this._addListeners(n.child),this._sync()})}getText(){return this.find("Text")[0]}getTag(){return this.find("Tag")[0]}_addListeners(t){var n=this,r,i=function(){n._sync()};for(r=0;r{n=Math.min(n,s.x),r=Math.max(r,s.x),i=Math.min(i,s.y),o=Math.max(o,s.y)}),{x:n,y:i,width:r-n,height:o-i}}getWidth(){return this.radius()*2}getHeight(){return this.radius()*2}setWidth(t){this.radius(t/2)}setHeight(t){this.radius(t/2)}}W1.RegularPolygon=Kl;Kl.prototype.className="RegularPolygon";Kl.prototype._centroid=!0;Kl.prototype._attrsAffectingSize=["radius"];(0,q2e._registerNode)(Kl);EB.Factory.addGetterSetter(Kl,"radius",0,(0,PB.getNumberValidator)());EB.Factory.addGetterSetter(Kl,"sides",0,(0,PB.getNumberValidator)());var K1={};Object.defineProperty(K1,"__esModule",{value:!0});K1.Ring=void 0;const kB=Re,W2e=mn,AB=he,K2e=De;var iA=Math.PI*2;class Yl extends W2e.Shape{_sceneFunc(t){t.beginPath(),t.arc(0,0,this.innerRadius(),0,iA,!1),t.moveTo(this.outerRadius(),0),t.arc(0,0,this.outerRadius(),iA,0,!0),t.closePath(),t.fillStrokeShape(this)}getWidth(){return this.outerRadius()*2}getHeight(){return this.outerRadius()*2}setWidth(t){this.outerRadius(t/2)}setHeight(t){this.outerRadius(t/2)}}K1.Ring=Yl;Yl.prototype.className="Ring";Yl.prototype._centroid=!0;Yl.prototype._attrsAffectingSize=["innerRadius","outerRadius"];(0,K2e._registerNode)(Yl);kB.Factory.addGetterSetter(Yl,"innerRadius",0,(0,AB.getNumberValidator)());kB.Factory.addGetterSetter(Yl,"outerRadius",0,(0,AB.getNumberValidator)());var Y1={};Object.defineProperty(Y1,"__esModule",{value:!0});Y1.Sprite=void 0;const Xl=Re,Y2e=mn,X2e=rd,OB=he,Q2e=De;class Do extends Y2e.Shape{constructor(t){super(t),this._updated=!0,this.anim=new X2e.Animation(()=>{var n=this._updated;return this._updated=!1,n}),this.on("animationChange.konva",function(){this.frameIndex(0)}),this.on("frameIndexChange.konva",function(){this._updated=!0}),this.on("frameRateChange.konva",function(){this.anim.isRunning()&&(clearInterval(this.interval),this._setInterval())})}_sceneFunc(t){var n=this.animation(),r=this.frameIndex(),i=r*4,o=this.animations()[n],s=this.frameOffsets(),a=o[i+0],l=o[i+1],u=o[i+2],c=o[i+3],d=this.image();if((this.hasFill()||this.hasStroke())&&(t.beginPath(),t.rect(0,0,u,c),t.closePath(),t.fillStrokeShape(this)),d)if(s){var f=s[n],h=r*2;t.drawImage(d,a,l,u,c,f[h+0],f[h+1],u,c)}else t.drawImage(d,a,l,u,c,0,0,u,c)}_hitFunc(t){var n=this.animation(),r=this.frameIndex(),i=r*4,o=this.animations()[n],s=this.frameOffsets(),a=o[i+2],l=o[i+3];if(t.beginPath(),s){var u=s[n],c=r*2;t.rect(u[c+0],u[c+1],a,l)}else t.rect(0,0,a,l);t.closePath(),t.fillShape(this)}_useBufferCanvas(){return super._useBufferCanvas(!0)}_setInterval(){var t=this;this.interval=setInterval(function(){t._updateIndex()},1e3/this.frameRate())}start(){if(!this.isRunning()){var t=this.getLayer();this.anim.setLayers(t),this._setInterval(),this.anim.start()}}stop(){this.anim.stop(),clearInterval(this.interval)}isRunning(){return this.anim.isRunning()}_updateIndex(){var t=this.frameIndex(),n=this.animation(),r=this.animations(),i=r[n],o=i.length/4;t{t=t.trim();const n=t.indexOf(" ")>=0,r=t.indexOf('"')>=0||t.indexOf("'")>=0;return n&&!r&&(t=`"${t}"`),t}).join(", ")}var Vg;function M_(){return Vg||(Vg=Px.Util.createCanvasElement().getContext(iwe),Vg)}function gwe(e){e.fillText(this._partialText,this._partialTextX,this._partialTextY)}function mwe(e){e.setAttr("miterLimit",2),e.strokeText(this._partialText,this._partialTextX,this._partialTextY)}function ywe(e){return e=e||{},!e.fillLinearGradientColorStops&&!e.fillRadialGradientColorStops&&!e.fillPatternImage&&(e.fill=e.fill||"black"),e}class Qt extends ewe.Shape{constructor(t){super(ywe(t)),this._partialTextX=0,this._partialTextY=0;for(var n=0;n1&&(v+=s)}}}_hitFunc(t){var n=this.getWidth(),r=this.getHeight();t.beginPath(),t.rect(0,0,n,r),t.closePath(),t.fillStrokeShape(this)}setText(t){var n=Px.Util._isString(t)?t:t==null?"":t+"";return this._setAttr(owe,n),this}getWidth(){var t=this.attrs.width===gu||this.attrs.width===void 0;return t?this.getTextWidth()+this.padding()*2:this.attrs.width}getHeight(){var t=this.attrs.height===gu||this.attrs.height===void 0;return t?this.fontSize()*this.textArr.length*this.lineHeight()+this.padding()*2:this.attrs.height}getTextWidth(){return this.textWidth}getTextHeight(){return Px.Util.warn("text.getTextHeight() method is deprecated. Use text.height() - for full height and text.fontSize() - for one line height."),this.textHeight}measureSize(t){var n=M_(),r=this.fontSize(),i;return n.save(),n.font=this._getContextFont(),i=n.measureText(t),n.restore(),{width:i.width,height:r}}_getContextFont(){return this.fontStyle()+jg+this.fontVariant()+jg+(this.fontSize()+uwe)+pwe(this.fontFamily())}_addTextLine(t){this.align()===Ld&&(t=t.trim());var r=this._getTextWidth(t);return this.textArr.push({text:t,width:r,lastInParagraph:!1})}_getTextWidth(t){var n=this.letterSpacing(),r=t.length;return M_().measureText(t).width+(r?n*(r-1):0)}_setTextData(){var t=this.text().split(` -`),n=+this.fontSize(),r=0,i=this.lineHeight()*n,o=this.attrs.width,s=this.attrs.height,a=o!==gu&&o!==void 0,l=s!==gu&&s!==void 0,u=this.padding(),c=o-u*2,d=s-u*2,f=0,h=this.wrap(),p=h!==aA,m=h!==fwe&&p,S=this.ellipsis();this.textArr=[],M_().font=this._getContextFont();for(var v=S?this._getTextWidth(I_):0,y=0,g=t.length;yc)for(;b.length>0;){for(var w=0,x=b.length,C="",k=0;w>>1,A=b.slice(0,P+1),$=this._getTextWidth(A)+v;$<=c?(w=P+1,C=A,k=$):x=P}if(C){if(m){var N,T=b[C.length],O=T===jg||T===oA;O&&k<=c?N=C.length:N=Math.max(C.lastIndexOf(jg),C.lastIndexOf(oA))+1,N>0&&(w=N,C=C.slice(0,w),k=this._getTextWidth(C))}C=C.trimRight(),this._addTextLine(C),r=Math.max(r,k),f+=i;var I=this._shouldHandleEllipsis(f);if(I){this._tryToAddEllipsisToLastLine();break}if(b=b.slice(w),b=b.trimLeft(),b.length>0&&(_=this._getTextWidth(b),_<=c)){this._addTextLine(b),f+=i,r=Math.max(r,_);break}}else break}else this._addTextLine(b),f+=i,r=Math.max(r,_),this._shouldHandleEllipsis(f)&&yd)break}this.textHeight=n,this.textWidth=r}_shouldHandleEllipsis(t){var n=+this.fontSize(),r=this.lineHeight()*n,i=this.attrs.height,o=i!==gu&&i!==void 0,s=this.padding(),a=i-s*2,l=this.wrap(),u=l!==aA;return!u||o&&t+r>a}_tryToAddEllipsisToLastLine(){var t=this.attrs.width,n=t!==gu&&t!==void 0,r=this.padding(),i=t-r*2,o=this.ellipsis(),s=this.textArr[this.textArr.length-1];if(!(!s||!o)){if(n){var a=this._getTextWidth(s.text+I_)n?null:$d.Path.getPointAtLengthOfDataArray(t,this.dataArray)}_readDataAttribute(){this.dataArray=$d.Path.parsePathData(this.attrs.data),this.pathLength=this._getTextPathLength()}_sceneFunc(t){t.setAttr("font",this._getContextFont()),t.setAttr("textBaseline",this.textBaseline()),t.setAttr("textAlign","left"),t.save();var n=this.textDecoration(),r=this.fill(),i=this.fontSize(),o=this.glyphInfo;n==="underline"&&t.beginPath();for(var s=0;s=1){var r=n[0].p0;t.moveTo(r.x,r.y)}for(var i=0;ie+`.${BB}`).join(" "),cA="nodesRect",Twe=["widthChange","heightChange","scaleXChange","scaleYChange","skewXChange","skewYChange","rotationChange","offsetXChange","offsetYChange","transformsEnabledChange","strokeWidthChange"],Ewe={"top-left":-45,"top-center":0,"top-right":45,"middle-right":-90,"middle-left":90,"bottom-left":-135,"bottom-center":180,"bottom-right":135};const Pwe="ontouchstart"in xi.Konva._global;function kwe(e,t){if(e==="rotater")return"crosshair";t+=st.Util.degToRad(Ewe[e]||0);var n=(st.Util.radToDeg(t)%360+360)%360;return st.Util._inRange(n,315+22.5,360)||st.Util._inRange(n,0,22.5)?"ns-resize":st.Util._inRange(n,45-22.5,45+22.5)?"nesw-resize":st.Util._inRange(n,90-22.5,90+22.5)?"ew-resize":st.Util._inRange(n,135-22.5,135+22.5)?"nwse-resize":st.Util._inRange(n,180-22.5,180+22.5)?"ns-resize":st.Util._inRange(n,225-22.5,225+22.5)?"nesw-resize":st.Util._inRange(n,270-22.5,270+22.5)?"ew-resize":st.Util._inRange(n,315-22.5,315+22.5)?"nwse-resize":(st.Util.error("Transformer has unknown angle for cursor detection: "+n),"pointer")}var p0=["top-left","top-center","top-right","middle-right","middle-left","bottom-left","bottom-center","bottom-right"],dA=1e8;function Awe(e){return{x:e.x+e.width/2*Math.cos(e.rotation)+e.height/2*Math.sin(-e.rotation),y:e.y+e.height/2*Math.cos(e.rotation)+e.width/2*Math.sin(e.rotation)}}function jB(e,t,n){const r=n.x+(e.x-n.x)*Math.cos(t)-(e.y-n.y)*Math.sin(t),i=n.y+(e.x-n.x)*Math.sin(t)+(e.y-n.y)*Math.cos(t);return Object.assign(Object.assign({},e),{rotation:e.rotation+t,x:r,y:i})}function Owe(e,t){const n=Awe(e);return jB(e,t,n)}function Rwe(e,t,n){let r=t;for(let i=0;ii.isAncestorOf(this)?(st.Util.error("Konva.Transformer cannot be an a child of the node you are trying to attach"),!1):!0);this._nodes=t=n,t.length===1&&this.useSingleNodeRotation()?this.rotation(t[0].getAbsoluteRotation()):this.rotation(0),this._nodes.forEach(i=>{const o=()=>{this.nodes().length===1&&this.useSingleNodeRotation()&&this.rotation(this.nodes()[0].getAbsoluteRotation()),this._resetTransformCache(),!this._transforming&&!this.isDragging()&&this.update()},s=i._attrsAffectingSize.map(a=>a+"Change."+this._getEventNamespace()).join(" ");i.on(s,o),i.on(Twe.map(a=>a+`.${this._getEventNamespace()}`).join(" "),o),i.on(`absoluteTransformChange.${this._getEventNamespace()}`,o),this._proxyDrag(i)}),this._resetTransformCache();var r=!!this.findOne(".top-left");return r&&this.update(),this}_proxyDrag(t){let n;t.on(`dragstart.${this._getEventNamespace()}`,r=>{n=t.getAbsolutePosition(),!this.isDragging()&&t!==this.findOne(".back")&&this.startDrag(r,!1)}),t.on(`dragmove.${this._getEventNamespace()}`,r=>{if(!n)return;const i=t.getAbsolutePosition(),o=i.x-n.x,s=i.y-n.y;this.nodes().forEach(a=>{if(a===t||a.isDragging())return;const l=a.getAbsolutePosition();a.setAbsolutePosition({x:l.x+o,y:l.y+s}),a.startDrag(r)}),n=null})}getNodes(){return this._nodes||[]}getActiveAnchor(){return this._movingAnchorName}detach(){this._nodes&&this._nodes.forEach(t=>{t.off("."+this._getEventNamespace())}),this._nodes=[],this._resetTransformCache()}_resetTransformCache(){this._clearCache(cA),this._clearCache("transform"),this._clearSelfAndDescendantCache("absoluteTransform")}_getNodeRect(){return this._getCache(cA,this.__getNodeRect)}__getNodeShape(t,n=this.rotation(),r){var i=t.getClientRect({skipTransform:!0,skipShadow:!0,skipStroke:this.ignoreStroke()}),o=t.getAbsoluteScale(r),s=t.getAbsolutePosition(r),a=i.x*o.x-t.offsetX()*o.x,l=i.y*o.y-t.offsetY()*o.y;const u=(xi.Konva.getAngle(t.getAbsoluteRotation())+Math.PI*2)%(Math.PI*2),c={x:s.x+a*Math.cos(u)+l*Math.sin(-u),y:s.y+l*Math.cos(u)+a*Math.sin(u),width:i.width*o.x,height:i.height*o.y,rotation:u};return jB(c,-xi.Konva.getAngle(n),{x:0,y:0})}__getNodeRect(){var t=this.getNode();if(!t)return{x:-dA,y:-dA,width:0,height:0,rotation:0};const n=[];this.nodes().map(u=>{const c=u.getClientRect({skipTransform:!0,skipShadow:!0,skipStroke:this.ignoreStroke()});var d=[{x:c.x,y:c.y},{x:c.x+c.width,y:c.y},{x:c.x+c.width,y:c.y+c.height},{x:c.x,y:c.y+c.height}],f=u.getAbsoluteTransform();d.forEach(function(h){var p=f.point(h);n.push(p)})});const r=new st.Transform;r.rotate(-xi.Konva.getAngle(this.rotation()));var i,o,s,a;n.forEach(function(u){var c=r.point(u);i===void 0&&(i=s=c.x,o=a=c.y),i=Math.min(i,c.x),o=Math.min(o,c.y),s=Math.max(s,c.x),a=Math.max(a,c.y)}),r.invert();const l=r.point({x:i,y:o});return{x:l.x,y:l.y,width:s-i,height:a-o,rotation:xi.Konva.getAngle(this.rotation())}}getX(){return this._getNodeRect().x}getY(){return this._getNodeRect().y}getWidth(){return this._getNodeRect().width}getHeight(){return this._getNodeRect().height}_createElements(){this._createBack(),p0.forEach(function(t){this._createAnchor(t)}.bind(this)),this._createAnchor("rotater")}_createAnchor(t){var n=new wwe.Rect({stroke:"rgb(0, 161, 255)",fill:"white",strokeWidth:1,name:t+" _anchor",dragDistance:0,draggable:!0,hitStrokeWidth:Pwe?10:"auto"}),r=this;n.on("mousedown touchstart",function(i){r._handleMouseDown(i)}),n.on("dragstart",i=>{n.stopDrag(),i.cancelBubble=!0}),n.on("dragend",i=>{i.cancelBubble=!0}),n.on("mouseenter",()=>{var i=xi.Konva.getAngle(this.rotation()),o=kwe(t,i);n.getStage().content&&(n.getStage().content.style.cursor=o),this._cursorChange=!0}),n.on("mouseout",()=>{n.getStage().content&&(n.getStage().content.style.cursor=""),this._cursorChange=!1}),this.add(n)}_createBack(){var t=new _we.Shape({name:"back",width:0,height:0,draggable:!0,sceneFunc(n){var r=this.getParent(),i=r.padding();n.beginPath(),n.rect(-i,-i,this.width()+i*2,this.height()+i*2),n.moveTo(this.width()/2,-i),r.rotateEnabled()&&n.lineTo(this.width()/2,-r.rotateAnchorOffset()*st.Util._sign(this.height())-i),n.fillStrokeShape(this)},hitFunc:(n,r)=>{if(this.shouldOverdrawWholeArea()){var i=this.padding();n.beginPath(),n.rect(-i,-i,r.width()+i*2,r.height()+i*2),n.fillStrokeShape(r)}}});this.add(t),this._proxyDrag(t),t.on("dragstart",n=>{n.cancelBubble=!0}),t.on("dragmove",n=>{n.cancelBubble=!0}),t.on("dragend",n=>{n.cancelBubble=!0}),this.on("dragmove",n=>{this.update()})}_handleMouseDown(t){this._movingAnchorName=t.target.name().split(" ")[0];var n=this._getNodeRect(),r=n.width,i=n.height,o=Math.sqrt(Math.pow(r,2)+Math.pow(i,2));this.sin=Math.abs(i/o),this.cos=Math.abs(r/o),typeof window<"u"&&(window.addEventListener("mousemove",this._handleMouseMove),window.addEventListener("touchmove",this._handleMouseMove),window.addEventListener("mouseup",this._handleMouseUp,!0),window.addEventListener("touchend",this._handleMouseUp,!0)),this._transforming=!0;var s=t.target.getAbsolutePosition(),a=t.target.getStage().getPointerPosition();this._anchorDragOffset={x:a.x-s.x,y:a.y-s.y},this._fire("transformstart",{evt:t.evt,target:this.getNode()}),this._nodes.forEach(l=>{l._fire("transformstart",{evt:t.evt,target:l})})}_handleMouseMove(t){var n,r,i,o=this.findOne("."+this._movingAnchorName),s=o.getStage();s.setPointersPositions(t);const a=s.getPointerPosition();let l={x:a.x-this._anchorDragOffset.x,y:a.y-this._anchorDragOffset.y};const u=o.getAbsolutePosition();this.anchorDragBoundFunc()&&(l=this.anchorDragBoundFunc()(u,l,t)),o.setAbsolutePosition(l);const c=o.getAbsolutePosition();if(!(u.x===c.x&&u.y===c.y)){if(this._movingAnchorName==="rotater"){var d=this._getNodeRect();n=o.x()-d.width/2,r=-o.y()+d.height/2;let N=Math.atan2(-r,n)+Math.PI/2;d.height<0&&(N-=Math.PI);var f=xi.Konva.getAngle(this.rotation());const T=f+N,O=xi.Konva.getAngle(this.rotationSnapTolerance()),M=Rwe(this.rotationSnaps(),T,O)-d.rotation,R=Owe(d,M);this._fitNodesInto(R,t);return}var h=this.shiftBehavior(),p;h==="inverted"?p=this.keepRatio()&&!t.shiftKey:h==="none"?p=this.keepRatio():p=this.keepRatio()||t.shiftKey;var g=this.centeredScaling()||t.altKey;if(this._movingAnchorName==="top-left"){if(p){var m=g?{x:this.width()/2,y:this.height()/2}:{x:this.findOne(".bottom-right").x(),y:this.findOne(".bottom-right").y()};i=Math.sqrt(Math.pow(m.x-o.x(),2)+Math.pow(m.y-o.y(),2));var S=this.findOne(".top-left").x()>m.x?-1:1,v=this.findOne(".top-left").y()>m.y?-1:1;n=i*this.cos*S,r=i*this.sin*v,this.findOne(".top-left").x(m.x-n),this.findOne(".top-left").y(m.y-r)}}else if(this._movingAnchorName==="top-center")this.findOne(".top-left").y(o.y());else if(this._movingAnchorName==="top-right"){if(p){var m=g?{x:this.width()/2,y:this.height()/2}:{x:this.findOne(".bottom-left").x(),y:this.findOne(".bottom-left").y()};i=Math.sqrt(Math.pow(o.x()-m.x,2)+Math.pow(m.y-o.y(),2));var S=this.findOne(".top-right").x()m.y?-1:1;n=i*this.cos*S,r=i*this.sin*v,this.findOne(".top-right").x(m.x+n),this.findOne(".top-right").y(m.y-r)}var y=o.position();this.findOne(".top-left").y(y.y),this.findOne(".bottom-right").x(y.x)}else if(this._movingAnchorName==="middle-left")this.findOne(".top-left").x(o.x());else if(this._movingAnchorName==="middle-right")this.findOne(".bottom-right").x(o.x());else if(this._movingAnchorName==="bottom-left"){if(p){var m=g?{x:this.width()/2,y:this.height()/2}:{x:this.findOne(".top-right").x(),y:this.findOne(".top-right").y()};i=Math.sqrt(Math.pow(m.x-o.x(),2)+Math.pow(o.y()-m.y,2));var S=m.x{r._fire("transformend",{evt:t,target:r})}),this._movingAnchorName=null}}_fitNodesInto(t,n){var r=this._getNodeRect();const i=1;if(st.Util._inRange(t.width,-this.padding()*2-i,i)){this.update();return}if(st.Util._inRange(t.height,-this.padding()*2-i,i)){this.update();return}const o=this.flipEnabled();var s=new st.Transform;if(s.rotate(xi.Konva.getAngle(this.rotation())),this._movingAnchorName&&t.width<0&&this._movingAnchorName.indexOf("left")>=0){const d=s.point({x:-this.padding()*2,y:0});if(t.x+=d.x,t.y+=d.y,t.width+=this.padding()*2,this._movingAnchorName=this._movingAnchorName.replace("left","right"),this._anchorDragOffset.x-=d.x,this._anchorDragOffset.y-=d.y,!o){this.update();return}}else if(this._movingAnchorName&&t.width<0&&this._movingAnchorName.indexOf("right")>=0){const d=s.point({x:this.padding()*2,y:0});if(this._movingAnchorName=this._movingAnchorName.replace("right","left"),this._anchorDragOffset.x-=d.x,this._anchorDragOffset.y-=d.y,t.width+=this.padding()*2,!o){this.update();return}}if(this._movingAnchorName&&t.height<0&&this._movingAnchorName.indexOf("top")>=0){const d=s.point({x:0,y:-this.padding()*2});if(t.x+=d.x,t.y+=d.y,this._movingAnchorName=this._movingAnchorName.replace("top","bottom"),this._anchorDragOffset.x-=d.x,this._anchorDragOffset.y-=d.y,t.height+=this.padding()*2,!o){this.update();return}}else if(this._movingAnchorName&&t.height<0&&this._movingAnchorName.indexOf("bottom")>=0){const d=s.point({x:0,y:this.padding()*2});if(this._movingAnchorName=this._movingAnchorName.replace("bottom","top"),this._anchorDragOffset.x-=d.x,this._anchorDragOffset.y-=d.y,t.height+=this.padding()*2,!o){this.update();return}}if(this.boundBoxFunc()){const d=this.boundBoxFunc()(r,t);d?t=d:st.Util.warn("boundBoxFunc returned falsy. You should return new bound rect from it!")}const a=1e7,l=new st.Transform;l.translate(r.x,r.y),l.rotate(r.rotation),l.scale(r.width/a,r.height/a);const u=new st.Transform;u.translate(t.x,t.y),u.rotate(t.rotation),u.scale(t.width/a,t.height/a);const c=u.multiply(l.invert());this._nodes.forEach(d=>{var f;const h=d.getParent().getAbsoluteTransform(),p=d.getTransform().copy();p.translate(d.offsetX(),d.offsetY());const m=new st.Transform;m.multiply(h.copy().invert()).multiply(c).multiply(h).multiply(p);const S=m.decompose();d.setAttrs(S),this._fire("transform",{evt:n,target:d}),d._fire("transform",{evt:n,target:d}),(f=d.getLayer())===null||f===void 0||f.batchDraw()}),this.rotation(st.Util._getRotation(t.rotation)),this._resetTransformCache(),this.update(),this.getLayer().batchDraw()}forceUpdate(){this._resetTransformCache(),this.update()}_batchChangeChild(t,n){this.findOne(t).setAttrs(n)}update(){var t,n=this._getNodeRect();this.rotation(st.Util._getRotation(n.rotation));var r=n.width,i=n.height,o=this.enabledAnchors(),s=this.resizeEnabled(),a=this.padding(),l=this.anchorSize();const u=this.find("._anchor");u.forEach(d=>{d.setAttrs({width:l,height:l,offsetX:l/2,offsetY:l/2,stroke:this.anchorStroke(),strokeWidth:this.anchorStrokeWidth(),fill:this.anchorFill(),cornerRadius:this.anchorCornerRadius()})}),this._batchChangeChild(".top-left",{x:0,y:0,offsetX:l/2+a,offsetY:l/2+a,visible:s&&o.indexOf("top-left")>=0}),this._batchChangeChild(".top-center",{x:r/2,y:0,offsetY:l/2+a,visible:s&&o.indexOf("top-center")>=0}),this._batchChangeChild(".top-right",{x:r,y:0,offsetX:l/2-a,offsetY:l/2+a,visible:s&&o.indexOf("top-right")>=0}),this._batchChangeChild(".middle-left",{x:0,y:i/2,offsetX:l/2+a,visible:s&&o.indexOf("middle-left")>=0}),this._batchChangeChild(".middle-right",{x:r,y:i/2,offsetX:l/2-a,visible:s&&o.indexOf("middle-right")>=0}),this._batchChangeChild(".bottom-left",{x:0,y:i,offsetX:l/2+a,offsetY:l/2-a,visible:s&&o.indexOf("bottom-left")>=0}),this._batchChangeChild(".bottom-center",{x:r/2,y:i,offsetY:l/2-a,visible:s&&o.indexOf("bottom-center")>=0}),this._batchChangeChild(".bottom-right",{x:r,y:i,offsetX:l/2-a,offsetY:l/2-a,visible:s&&o.indexOf("bottom-right")>=0}),this._batchChangeChild(".rotater",{x:r/2,y:-this.rotateAnchorOffset()*st.Util._sign(i)-a,visible:this.rotateEnabled()}),this._batchChangeChild(".back",{width:r,height:i,visible:this.borderEnabled(),stroke:this.borderStroke(),strokeWidth:this.borderStrokeWidth(),dash:this.borderDash(),x:0,y:0});const c=this.anchorStyleFunc();c&&u.forEach(d=>{c(d)}),(t=this.getLayer())===null||t===void 0||t.batchDraw()}isTransforming(){return this._transforming}stopTransform(){if(this._transforming){this._removeEvents();var t=this.findOne("."+this._movingAnchorName);t&&t.stopDrag()}}destroy(){return this.getStage()&&this._cursorChange&&this.getStage().content&&(this.getStage().content.style.cursor=""),uA.Group.prototype.destroy.call(this),this.detach(),this._removeEvents(),this}toObject(){return lA.Node.prototype.toObject.call(this)}clone(t){var n=lA.Node.prototype.clone.call(this,t);return n}getClientRect(){return this.nodes().length>0?super.getClientRect():{x:0,y:0,width:0,height:0}}}Z1.Transformer=Ze;function Iwe(e){return e instanceof Array||st.Util.warn("enabledAnchors value should be an array"),e instanceof Array&&e.forEach(function(t){p0.indexOf(t)===-1&&st.Util.warn("Unknown anchor name: "+t+". 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location<"u"&&location.port?location.port:this.secure?"443":"80"),this.transports=n.transports||["polling","websocket","webtransport"],this.writeBuffer=[],this.prevBufferLen=0,this.opts=Object.assign({path:"/engine.io",agent:!1,withCredentials:!1,upgrade:!0,timestampParam:"t",rememberUpgrade:!1,addTrailingSlash:!0,rejectUnauthorized:!0,perMessageDeflate:{threshold:1024},transportOptions:{},closeOnBeforeunload:!0},n),this.opts.path=this.opts.path.replace(/\/$/,"")+(this.opts.addTrailingSlash?"/":""),typeof this.opts.query=="string"&&(this.opts.query=z5e(this.opts.query)),this.id=null,this.upgrades=null,this.pingInterval=null,this.pingTimeout=null,this.pingTimeoutTimer=null,typeof addEventListener=="function"&&(this.opts.closeOnBeforeunload&&(this.beforeunloadEventListener=()=>{this.transport&&(this.transport.removeAllListeners(),this.transport.close())},addEventListener("beforeunload",this.beforeunloadEventListener,!1)),this.hostname!=="localhost"&&(this.offlineEventListener=()=>{this.onClose("transport close",{description:"network connection lost"})},addEventListener("offline",this.offlineEventListener,!1))),this.open()}createTransport(t){const n=Object.assign({},this.opts.query);n.EIO=rj,n.transport=t,this.id&&(n.sid=this.id);const r=Object.assign({},this.opts.transportOptions[t],this.opts,{query:n,socket:this,hostname:this.hostname,secure:this.secure,port:this.port});return new J5e[t](r)}open(){let t;if(this.opts.rememberUpgrade&&wu.priorWebsocketSuccess&&this.transports.indexOf("websocket")!==-1)t="websocket";else if(this.transports.length===0){this.setTimeoutFn(()=>{this.emitReserved("error","No transports available")},0);return}else t=this.transports[0];this.readyState="opening";try{t=this.createTransport(t)}catch{this.transports.shift(),this.open();return}t.open(),this.setTransport(t)}setTransport(t){this.transport&&this.transport.removeAllListeners(),this.transport=t,t.on("drain",this.onDrain.bind(this)).on("packet",this.onPacket.bind(this)).on("error",this.onError.bind(this)).on("close",n=>this.onClose("transport close",n))}probe(t){let n=this.createTransport(t),r=!1;wu.priorWebsocketSuccess=!1;const i=()=>{r||(n.send([{type:"ping",data:"probe"}]),n.once("packet",d=>{if(!r)if(d.type==="pong"&&d.data==="probe"){if(this.upgrading=!0,this.emitReserved("upgrading",n),!n)return;wu.priorWebsocketSuccess=n.name==="websocket",this.transport.pause(()=>{r||this.readyState!=="closed"&&(c(),this.setTransport(n),n.send([{type:"upgrade"}]),this.emitReserved("upgrade",n),n=null,this.upgrading=!1,this.flush())})}else{const f=new Error("probe error");f.transport=n.name,this.emitReserved("upgradeError",f)}}))};function o(){r||(r=!0,c(),n.close(),n=null)}const s=d=>{const f=new Error("probe error: "+d);f.transport=n.name,o(),this.emitReserved("upgradeError",f)};function a(){s("transport closed")}function l(){s("socket closed")}function u(d){n&&d.name!==n.name&&o()}const c=()=>{n.removeListener("open",i),n.removeListener("error",s),n.removeListener("close",a),this.off("close",l),this.off("upgrading",u)};n.once("open",i),n.once("error",s),n.once("close",a),this.once("close",l),this.once("upgrading",u),this.upgrades.indexOf("webtransport")!==-1&&t!=="webtransport"?this.setTimeoutFn(()=>{r||n.open()},200):n.open()}onOpen(){if(this.readyState="open",wu.priorWebsocketSuccess=this.transport.name==="websocket",this.emitReserved("open"),this.flush(),this.readyState==="open"&&this.opts.upgrade){let t=0;const n=this.upgrades.length;for(;t{this.onClose("ping timeout")},this.pingInterval+this.pingTimeout),this.opts.autoUnref&&this.pingTimeoutTimer.unref()}onDrain(){this.writeBuffer.splice(0,this.prevBufferLen),this.prevBufferLen=0,this.writeBuffer.length===0?this.emitReserved("drain"):this.flush()}flush(){if(this.readyState!=="closed"&&this.transport.writable&&!this.upgrading&&this.writeBuffer.length){const t=this.getWritablePackets();this.transport.send(t),this.prevBufferLen=t.length,this.emitReserved("flush")}}getWritablePackets(){if(!(this.maxPayload&&this.transport.name==="polling"&&this.writeBuffer.length>1))return this.writeBuffer;let n=1;for(let r=0;r0&&n>this.maxPayload)return this.writeBuffer.slice(0,r);n+=2}return this.writeBuffer}write(t,n,r){return this.sendPacket("message",t,n,r),this}send(t,n,r){return this.sendPacket("message",t,n,r),this}sendPacket(t,n,r,i){if(typeof n=="function"&&(i=n,n=void 0),typeof r=="function"&&(i=r,r=null),this.readyState==="closing"||this.readyState==="closed")return;r=r||{},r.compress=r.compress!==!1;const o={type:t,data:n,options:r};this.emitReserved("packetCreate",o),this.writeBuffer.push(o),i&&this.once("flush",i),this.flush()}close(){const t=()=>{this.onClose("forced close"),this.transport.close()},n=()=>{this.off("upgrade",n),this.off("upgradeError",n),t()},r=()=>{this.once("upgrade",n),this.once("upgradeError",n)};return(this.readyState==="opening"||this.readyState==="open")&&(this.readyState="closing",this.writeBuffer.length?this.once("drain",()=>{this.upgrading?r():t()}):this.upgrading?r():t()),this}onError(t){wu.priorWebsocketSuccess=!1,this.emitReserved("error",t),this.onClose("transport error",t)}onClose(t,n){(this.readyState==="opening"||this.readyState==="open"||this.readyState==="closing")&&(this.clearTimeoutFn(this.pingTimeoutTimer),this.transport.removeAllListeners("close"),this.transport.close(),this.transport.removeAllListeners(),typeof removeEventListener=="function"&&(removeEventListener("beforeunload",this.beforeunloadEventListener,!1),removeEventListener("offline",this.offlineEventListener,!1)),this.readyState="closed",this.id=null,this.emitReserved("close",t,n),this.writeBuffer=[],this.prevBufferLen=0)}filterUpgrades(t){const n=[];let r=0;const i=t.length;for(;rtypeof ArrayBuffer.isView=="function"?ArrayBuffer.isView(e):e.buffer instanceof ArrayBuffer,cj=Object.prototype.toString,a3e=typeof Blob=="function"||typeof Blob<"u"&&cj.call(Blob)==="[object BlobConstructor]",l3e=typeof File=="function"||typeof File<"u"&&cj.call(File)==="[object FileConstructor]";function c4(e){return o3e&&(e instanceof ArrayBuffer||s3e(e))||a3e&&e instanceof Blob||l3e&&e instanceof File}function Nm(e,t){if(!e||typeof e!="object")return!1;if(Array.isArray(e)){for(let n=0,r=e.length;n=0&&e.num{delete this.acks[t];for(let s=0;s{this.io.clearTimeoutFn(o),n.apply(this,[null,...s])}}emitWithAck(t,...n){const r=this.flags.timeout!==void 0||this._opts.ackTimeout!==void 0;return new Promise((i,o)=>{n.push((s,a)=>r?s?o(s):i(a):i(s)),this.emit(t,...n)})}_addToQueue(t){let n;typeof t[t.length-1]=="function"&&(n=t.pop());const r={id:this._queueSeq++,tryCount:0,pending:!1,args:t,flags:Object.assign({fromQueue:!0},this.flags)};t.push((i,...o)=>r!==this._queue[0]?void 0:(i!==null?r.tryCount>this._opts.retries&&(this._queue.shift(),n&&n(i)):(this._queue.shift(),n&&n(null,...o)),r.pending=!1,this._drainQueue())),this._queue.push(r),this._drainQueue()}_drainQueue(t=!1){if(!this.connected||this._queue.length===0)return;const n=this._queue[0];n.pending&&!t||(n.pending=!0,n.tryCount++,this.flags=n.flags,this.emit.apply(this,n.args))}packet(t){t.nsp=this.nsp,this.io._packet(t)}onopen(){typeof this.auth=="function"?this.auth(t=>{this._sendConnectPacket(t)}):this._sendConnectPacket(this.auth)}_sendConnectPacket(t){this.packet({type:Ge.CONNECT,data:this._pid?Object.assign({pid:this._pid,offset:this._lastOffset},t):t})}onerror(t){this.connected||this.emitReserved("connect_error",t)}onclose(t,n){this.connected=!1,delete this.id,this.emitReserved("disconnect",t,n)}onpacket(t){if(t.nsp===this.nsp)switch(t.type){case Ge.CONNECT:t.data&&t.data.sid?this.onconnect(t.data.sid,t.data.pid):this.emitReserved("connect_error",new Error("It seems you are trying to reach a Socket.IO server in v2.x with a v3.x client, but they are not compatible (more information here: https://socket.io/docs/v3/migrating-from-2-x-to-3-0/)"));break;case Ge.EVENT:case Ge.BINARY_EVENT:this.onevent(t);break;case Ge.ACK:case Ge.BINARY_ACK:this.onack(t);break;case Ge.DISCONNECT:this.ondisconnect();break;case Ge.CONNECT_ERROR:this.destroy();const r=new Error(t.data.message);r.data=t.data.data,this.emitReserved("connect_error",r);break}}onevent(t){const n=t.data||[];t.id!=null&&n.push(this.ack(t.id)),this.connected?this.emitEvent(n):this.receiveBuffer.push(Object.freeze(n))}emitEvent(t){if(this._anyListeners&&this._anyListeners.length){const n=this._anyListeners.slice();for(const r of n)r.apply(this,t)}super.emit.apply(this,t),this._pid&&t.length&&typeof t[t.length-1]=="string"&&(this._lastOffset=t[t.length-1])}ack(t){const n=this;let r=!1;return function(...i){r||(r=!0,n.packet({type:Ge.ACK,id:t,data:i}))}}onack(t){const n=this.acks[t.id];typeof n=="function"&&(n.apply(this,t.data),delete this.acks[t.id])}onconnect(t,n){this.id=t,this.recovered=n&&this._pid===n,this._pid=n,this.connected=!0,this.emitBuffered(),this.emitReserved("connect"),this._drainQueue(!0)}emitBuffered(){this.receiveBuffer.forEach(t=>this.emitEvent(t)),this.receiveBuffer=[],this.sendBuffer.forEach(t=>{this.notifyOutgoingListeners(t),this.packet(t)}),this.sendBuffer=[]}ondisconnect(){this.destroy(),this.onclose("io server disconnect")}destroy(){this.subs&&(this.subs.forEach(t=>t()),this.subs=void 0),this.io._destroy(this)}disconnect(){return this.connected&&this.packet({type:Ge.DISCONNECT}),this.destroy(),this.connected&&this.onclose("io client disconnect"),this}close(){return this.disconnect()}compress(t){return this.flags.compress=t,this}get volatile(){return this.flags.volatile=!0,this}timeout(t){return this.flags.timeout=t,this}onAny(t){return this._anyListeners=this._anyListeners||[],this._anyListeners.push(t),this}prependAny(t){return this._anyListeners=this._anyListeners||[],this._anyListeners.unshift(t),this}offAny(t){if(!this._anyListeners)return this;if(t){const n=this._anyListeners;for(let r=0;r0&&e.jitter<=1?e.jitter:0,this.attempts=0}sd.prototype.duration=function(){var e=this.ms*Math.pow(this.factor,this.attempts++);if(this.jitter){var t=Math.random(),n=Math.floor(t*this.jitter*e);e=Math.floor(t*10)&1?e+n:e-n}return Math.min(e,this.max)|0};sd.prototype.reset=function(){this.attempts=0};sd.prototype.setMin=function(e){this.ms=e};sd.prototype.setMax=function(e){this.max=e};sd.prototype.setJitter=function(e){this.jitter=e};class Lx extends sn{constructor(t,n){var r;super(),this.nsps={},this.subs=[],t&&typeof t=="object"&&(n=t,t=void 0),n=n||{},n.path=n.path||"/socket.io",this.opts=n,wb(this,n),this.reconnection(n.reconnection!==!1),this.reconnectionAttempts(n.reconnectionAttempts||1/0),this.reconnectionDelay(n.reconnectionDelay||1e3),this.reconnectionDelayMax(n.reconnectionDelayMax||5e3),this.randomizationFactor((r=n.randomizationFactor)!==null&&r!==void 0?r:.5),this.backoff=new sd({min:this.reconnectionDelay(),max:this.reconnectionDelayMax(),jitter:this.randomizationFactor()}),this.timeout(n.timeout==null?2e4:n.timeout),this._readyState="closed",this.uri=t;const i=n.parser||g3e;this.encoder=new i.Encoder,this.decoder=new i.Decoder,this._autoConnect=n.autoConnect!==!1,this._autoConnect&&this.open()}reconnection(t){return arguments.length?(this._reconnection=!!t,this):this._reconnection}reconnectionAttempts(t){return t===void 0?this._reconnectionAttempts:(this._reconnectionAttempts=t,this)}reconnectionDelay(t){var n;return t===void 0?this._reconnectionDelay:(this._reconnectionDelay=t,(n=this.backoff)===null||n===void 0||n.setMin(t),this)}randomizationFactor(t){var n;return t===void 0?this._randomizationFactor:(this._randomizationFactor=t,(n=this.backoff)===null||n===void 0||n.setJitter(t),this)}reconnectionDelayMax(t){var n;return t===void 0?this._reconnectionDelayMax:(this._reconnectionDelayMax=t,(n=this.backoff)===null||n===void 0||n.setMax(t),this)}timeout(t){return arguments.length?(this._timeout=t,this):this._timeout}maybeReconnectOnOpen(){!this._reconnecting&&this._reconnection&&this.backoff.attempts===0&&this.reconnect()}open(t){if(~this._readyState.indexOf("open"))return this;this.engine=new uj(this.uri,this.opts);const n=this.engine,r=this;this._readyState="opening",this.skipReconnect=!1;const i=Ei(n,"open",function(){r.onopen(),t&&t()}),o=a=>{this.cleanup(),this._readyState="closed",this.emitReserved("error",a),t?t(a):this.maybeReconnectOnOpen()},s=Ei(n,"error",o);if(this._timeout!==!1){const a=this._timeout,l=this.setTimeoutFn(()=>{i(),o(new Error("timeout")),n.close()},a);this.opts.autoUnref&&l.unref(),this.subs.push(()=>{this.clearTimeoutFn(l)})}return this.subs.push(i),this.subs.push(s),this}connect(t){return this.open(t)}onopen(){this.cleanup(),this._readyState="open",this.emitReserved("open");const t=this.engine;this.subs.push(Ei(t,"ping",this.onping.bind(this)),Ei(t,"data",this.ondata.bind(this)),Ei(t,"error",this.onerror.bind(this)),Ei(t,"close",this.onclose.bind(this)),Ei(this.decoder,"decoded",this.ondecoded.bind(this)))}onping(){this.emitReserved("ping")}ondata(t){try{this.decoder.add(t)}catch(n){this.onclose("parse error",n)}}ondecoded(t){u4(()=>{this.emitReserved("packet",t)},this.setTimeoutFn)}onerror(t){this.emitReserved("error",t)}socket(t,n){let r=this.nsps[t];return r?this._autoConnect&&!r.active&&r.connect():(r=new dj(this,t,n),this.nsps[t]=r),r}_destroy(t){const n=Object.keys(this.nsps);for(const r of n)if(this.nsps[r].active)return;this._close()}_packet(t){const n=this.encoder.encode(t);for(let r=0;rt()),this.subs.length=0,this.decoder.destroy()}_close(){this.skipReconnect=!0,this._reconnecting=!1,this.onclose("forced close"),this.engine&&this.engine.close()}disconnect(){return this._close()}onclose(t,n){this.cleanup(),this.backoff.reset(),this._readyState="closed",this.emitReserved("close",t,n),this._reconnection&&!this.skipReconnect&&this.reconnect()}reconnect(){if(this._reconnecting||this.skipReconnect)return this;const t=this;if(this.backoff.attempts>=this._reconnectionAttempts)this.backoff.reset(),this.emitReserved("reconnect_failed"),this._reconnecting=!1;else{const n=this.backoff.duration();this._reconnecting=!0;const r=this.setTimeoutFn(()=>{t.skipReconnect||(this.emitReserved("reconnect_attempt",t.backoff.attempts),!t.skipReconnect&&t.open(i=>{i?(t._reconnecting=!1,t.reconnect(),this.emitReserved("reconnect_error",i)):t.onreconnect()}))},n);this.opts.autoUnref&&r.unref(),this.subs.push(()=>{this.clearTimeoutFn(r)})}}onreconnect(){const t=this.backoff.attempts;this._reconnecting=!1,this.backoff.reset(),this.emitReserved("reconnect",t)}}const jd={};function Dm(e,t){typeof e=="object"&&(t=e,e=void 0),t=t||{};const n=i3e(e,t.path||"/socket.io"),r=n.source,i=n.id,o=n.path,s=jd[i]&&o in jd[i].nsps,a=t.forceNew||t["force new connection"]||t.multiplex===!1||s;let l;return a?l=new Lx(r,t):(jd[i]||(jd[i]=new Lx(r,t)),l=jd[i]),n.query&&!t.query&&(t.query=n.queryKey),l.socket(n.path,t)}Object.assign(Dm,{Manager:Lx,Socket:dj,io:Dm,connect:Dm});var y3e=/d{1,4}|D{3,4}|m{1,4}|yy(?:yy)?|([HhMsTt])\1?|W{1,2}|[LlopSZN]|"[^"]*"|'[^']*'/g,v3e=/\b(?:[A-Z]{1,3}[A-Z][TC])(?:[-+]\d{4})?|((?:Australian 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S=t.code,{isTop:v,isRight:y,isLeft:g,isBottom:b,maxScroll:_,minScroll:w}=Sj(m),x=l4e(m),C={x:Math.min(S===gt.Right?x.right-x.width/2:x.right,Math.max(S===gt.Right?x.left:x.left+x.width/2,d.x)),y:Math.min(S===gt.Down?x.bottom-x.height/2:x.bottom,Math.max(S===gt.Down?x.top:x.top+x.height/2,d.y))},k=S===gt.Right&&!y||S===gt.Left&&!g,P=S===gt.Down&&!b||S===gt.Up&&!v;if(k&&C.x!==d.x){const A=m.scrollLeft+f.x,$=S===gt.Right&&A<=_.x||S===gt.Left&&A>=w.x;if($&&!f.y){m.scrollTo({left:A,behavior:a});return}$?h.x=m.scrollLeft-A:h.x=S===gt.Right?m.scrollLeft-_.x:m.scrollLeft-w.x,h.x&&m.scrollBy({left:-h.x,behavior:a});break}else if(P&&C.y!==d.y){const A=m.scrollTop+f.y,$=S===gt.Down&&A<=_.y||S===gt.Up&&A>=w.y;if($&&!f.x){m.scrollTo({top:A,behavior:a});return}$?h.y=m.scrollTop-A:h.y=S===gt.Down?m.scrollTop-_.y:m.scrollTop-w.y,h.y&&m.scrollBy({top:-h.y,behavior:a});break}}this.handleMove(t,dc(_0(d,this.referenceCoordinates),h))}}}handleMove(t,n){const{onMove:r}=this.props;t.preventDefault(),r(n)}handleEnd(t){const{onEnd:n}=this.props;t.preventDefault(),this.detach(),n()}handleCancel(t){const{onCancel:n}=this.props;t.preventDefault(),this.detach(),n()}detach(){this.listeners.removeAll(),this.windowListeners.removeAll()}}Cj.activators=[{eventName:"onKeyDown",handler:(e,t,n)=>{let{keyboardCodes:r=xj,onActivation:i}=t,{active:o}=n;const{code:s}=e.nativeEvent;if(r.start.includes(s)){const a=o.activatorNode.current;return a&&e.target!==a?!1:(e.preventDefault(),i==null||i({event:e.nativeEvent}),!0)}return!1}}];function QA(e){return!!(e&&"distance"in e)}function ZA(e){return!!(e&&"delay"in e)}class y4{constructor(t,n,r){var i;r===void 0&&(r=f4e(t.event.target)),this.props=void 0,this.events=void 0,this.autoScrollEnabled=!0,this.document=void 0,this.activated=!1,this.initialCoordinates=void 0,this.timeoutId=null,this.listeners=void 0,this.documentListeners=void 0,this.windowListeners=void 0,this.props=t,this.events=n;const{event:o}=t,{target:s}=o;this.props=t,this.events=n,this.document=ld(s),this.documentListeners=new bf(this.document),this.listeners=new bf(r),this.windowListeners=new bf(mr(s)),this.initialCoordinates=(i=zh(o))!=null?i:Vi,this.handleStart=this.handleStart.bind(this),this.handleMove=this.handleMove.bind(this),this.handleEnd=this.handleEnd.bind(this),this.handleCancel=this.handleCancel.bind(this),this.handleKeydown=this.handleKeydown.bind(this),this.removeTextSelection=this.removeTextSelection.bind(this),this.attach()}attach(){const{events:t,props:{options:{activationConstraint:n}}}=this;if(this.listeners.add(t.move.name,this.handleMove,{passive:!1}),this.listeners.add(t.end.name,this.handleEnd),this.windowListeners.add(ni.Resize,this.handleCancel),this.windowListeners.add(ni.DragStart,XA),this.windowListeners.add(ni.VisibilityChange,this.handleCancel),this.windowListeners.add(ni.ContextMenu,XA),this.documentListeners.add(ni.Keydown,this.handleKeydown),n){if(QA(n))return;if(ZA(n)){this.timeoutId=setTimeout(this.handleStart,n.delay);return}}this.handleStart()}detach(){this.listeners.removeAll(),this.windowListeners.removeAll(),setTimeout(this.documentListeners.removeAll,50),this.timeoutId!==null&&(clearTimeout(this.timeoutId),this.timeoutId=null)}handleStart(){const{initialCoordinates:t}=this,{onStart:n}=this.props;t&&(this.activated=!0,this.documentListeners.add(ni.Click,h4e,{capture:!0}),this.removeTextSelection(),this.documentListeners.add(ni.SelectionChange,this.removeTextSelection),n(t))}handleMove(t){var n;const{activated:r,initialCoordinates:i,props:o}=this,{onMove:s,options:{activationConstraint:a}}=o;if(!i)return;const l=(n=zh(t))!=null?n:Vi,u=_0(i,l);if(!r&&a){if(ZA(a))return z_(u,a.tolerance)?this.handleCancel():void 0;if(QA(a))return a.tolerance!=null&&z_(u,a.tolerance)?this.handleCancel():z_(u,a.distance)?this.handleStart():void 0}t.cancelable&&t.preventDefault(),s(l)}handleEnd(){const{onEnd:t}=this.props;this.detach(),t()}handleCancel(){const{onCancel:t}=this.props;this.detach(),t()}handleKeydown(t){t.code===gt.Esc&&this.handleCancel()}removeTextSelection(){var t;(t=this.document.getSelection())==null||t.removeAllRanges()}}const g4e={move:{name:"pointermove"},end:{name:"pointerup"}};class Tj extends y4{constructor(t){const{event:n}=t,r=ld(n.target);super(t,g4e,r)}}Tj.activators=[{eventName:"onPointerDown",handler:(e,t)=>{let{nativeEvent:n}=e,{onActivation:r}=t;return!n.isPrimary||n.button!==0?!1:(r==null||r({event:n}),!0)}}];const m4e={move:{name:"mousemove"},end:{name:"mouseup"}};var Fx;(function(e){e[e.RightClick=2]="RightClick"})(Fx||(Fx={}));class Ej extends y4{constructor(t){super(t,m4e,ld(t.event.target))}}Ej.activators=[{eventName:"onMouseDown",handler:(e,t)=>{let{nativeEvent:n}=e,{onActivation:r}=t;return n.button===Fx.RightClick?!1:(r==null||r({event:n}),!0)}}];const U_={move:{name:"touchmove"},end:{name:"touchend"}};class Pj extends y4{constructor(t){super(t,U_)}static setup(){return window.addEventListener(U_.move.name,t,{capture:!1,passive:!1}),function(){window.removeEventListener(U_.move.name,t)};function t(){}}}Pj.activators=[{eventName:"onTouchStart",handler:(e,t)=>{let{nativeEvent:n}=e,{onActivation:r}=t;const{touches:i}=n;return i.length>1?!1:(r==null||r({event:n}),!0)}}];var Sf;(function(e){e[e.Pointer=0]="Pointer",e[e.DraggableRect=1]="DraggableRect"})(Sf||(Sf={}));var x0;(function(e){e[e.TreeOrder=0]="TreeOrder",e[e.ReversedTreeOrder=1]="ReversedTreeOrder"})(x0||(x0={}));function y4e(e){let{acceleration:t,activator:n=Sf.Pointer,canScroll:r,draggingRect:i,enabled:o,interval:s=5,order:a=x0.TreeOrder,pointerCoordinates:l,scrollableAncestors:u,scrollableAncestorRects:c,delta:d,threshold:f}=e;const h=b4e({delta:d,disabled:!o}),[p,m]=P3e(),S=E.useRef({x:0,y:0}),v=E.useRef({x:0,y:0}),y=E.useMemo(()=>{switch(n){case Sf.Pointer:return l?{top:l.y,bottom:l.y,left:l.x,right:l.x}:null;case Sf.DraggableRect:return i}},[n,i,l]),g=E.useRef(null),b=E.useCallback(()=>{const w=g.current;if(!w)return;const x=S.current.x*v.current.x,C=S.current.y*v.current.y;w.scrollBy(x,C)},[]),_=E.useMemo(()=>a===x0.TreeOrder?[...u].reverse():u,[a,u]);E.useEffect(()=>{if(!o||!u.length||!y){m();return}for(const w of _){if((r==null?void 0:r(w))===!1)continue;const x=u.indexOf(w),C=c[x];if(!C)continue;const{direction:k,speed:P}=a4e(w,C,y,t,f);for(const A of["x","y"])h[A][k[A]]||(P[A]=0,k[A]=0);if(P.x>0||P.y>0){m(),g.current=w,p(b,s),S.current=P,v.current=k;return}}S.current={x:0,y:0},v.current={x:0,y:0},m()},[t,b,r,m,o,s,JSON.stringify(y),JSON.stringify(h),p,u,_,c,JSON.stringify(f)])}const v4e={x:{[Cn.Backward]:!1,[Cn.Forward]:!1},y:{[Cn.Backward]:!1,[Cn.Forward]:!1}};function b4e(e){let{delta:t,disabled:n}=e;const r=S0(t);return jp(i=>{if(n||!r||!i)return v4e;const o={x:Math.sign(t.x-r.x),y:Math.sign(t.y-r.y)};return{x:{[Cn.Backward]:i.x[Cn.Backward]||o.x===-1,[Cn.Forward]:i.x[Cn.Forward]||o.x===1},y:{[Cn.Backward]:i.y[Cn.Backward]||o.y===-1,[Cn.Forward]:i.y[Cn.Forward]||o.y===1}}},[n,t,r])}function S4e(e,t){const n=t!==null?e.get(t):void 0,r=n?n.node.current:null;return jp(i=>{var o;return t===null?null:(o=r??i)!=null?o:null},[r,t])}function _4e(e,t){return E.useMemo(()=>e.reduce((n,r)=>{const{sensor:i}=r,o=i.activators.map(s=>({eventName:s.eventName,handler:t(s.handler,r)}));return[...n,...o]},[]),[e,t])}var Gh;(function(e){e[e.Always=0]="Always",e[e.BeforeDragging=1]="BeforeDragging",e[e.WhileDragging=2]="WhileDragging"})(Gh||(Gh={}));var Bx;(function(e){e.Optimized="optimized"})(Bx||(Bx={}));const JA=new Map;function w4e(e,t){let{dragging:n,dependencies:r,config:i}=t;const[o,s]=E.useState(null),{frequency:a,measure:l,strategy:u}=i,c=E.useRef(e),d=S(),f=Vh(d),h=E.useCallback(function(v){v===void 0&&(v=[]),!f.current&&s(y=>y===null?v:y.concat(v.filter(g=>!y.includes(g))))},[f]),p=E.useRef(null),m=jp(v=>{if(d&&!n)return JA;if(!v||v===JA||c.current!==e||o!=null){const y=new Map;for(let g of e){if(!g)continue;if(o&&o.length>0&&!o.includes(g.id)&&g.rect.current){y.set(g.id,g.rect.current);continue}const b=g.node.current,_=b?new m4(l(b),b):null;g.rect.current=_,_&&y.set(g.id,_)}return y}return v},[e,o,n,d,l]);return E.useEffect(()=>{c.current=e},[e]),E.useEffect(()=>{d||h()},[n,d]),E.useEffect(()=>{o&&o.length>0&&s(null)},[JSON.stringify(o)]),E.useEffect(()=>{d||typeof a!="number"||p.current!==null||(p.current=setTimeout(()=>{h(),p.current=null},a))},[a,d,h,...r]),{droppableRects:m,measureDroppableContainers:h,measuringScheduled:o!=null};function S(){switch(u){case Gh.Always:return!1;case Gh.BeforeDragging:return n;default:return!n}}}function v4(e,t){return jp(n=>e?n||(typeof t=="function"?t(e):e):null,[t,e])}function x4e(e,t){return v4(e,t)}function C4e(e){let{callback:t,disabled:n}=e;const r=Cb(t),i=E.useMemo(()=>{if(n||typeof window>"u"||typeof window.MutationObserver>"u")return;const{MutationObserver:o}=window;return new o(r)},[r,n]);return E.useEffect(()=>()=>i==null?void 0:i.disconnect(),[i]),i}function Eb(e){let{callback:t,disabled:n}=e;const r=Cb(t),i=E.useMemo(()=>{if(n||typeof window>"u"||typeof window.ResizeObserver>"u")return;const{ResizeObserver:o}=window;return new o(r)},[n]);return E.useEffect(()=>()=>i==null?void 0:i.disconnect(),[i]),i}function T4e(e){return new m4(Vp(e),e)}function e9(e,t,n){t===void 0&&(t=T4e);const[r,i]=E.useReducer(a,null),o=C4e({callback(l){if(e)for(const u of l){const{type:c,target:d}=u;if(c==="childList"&&d instanceof HTMLElement&&d.contains(e)){i();break}}}}),s=Eb({callback:i});return ko(()=>{i(),e?(s==null||s.observe(e),o==null||o.observe(document.body,{childList:!0,subtree:!0})):(s==null||s.disconnect(),o==null||o.disconnect())},[e]),r;function a(l){if(!e)return null;if(e.isConnected===!1){var u;return(u=l??n)!=null?u:null}const c=t(e);return JSON.stringify(l)===JSON.stringify(c)?l:c}}function E4e(e){const t=v4(e);return pj(e,t)}const t9=[];function P4e(e){const t=E.useRef(e),n=jp(r=>e?r&&r!==t9&&e&&t.current&&e.parentNode===t.current.parentNode?r:g4(e):t9,[e]);return E.useEffect(()=>{t.current=e},[e]),n}function k4e(e){const[t,n]=E.useState(null),r=E.useRef(e),i=E.useCallback(o=>{const s=V_(o.target);s&&n(a=>a?(a.set(s,$x(s)),new Map(a)):null)},[]);return E.useEffect(()=>{const o=r.current;if(e!==o){s(o);const a=e.map(l=>{const u=V_(l);return u?(u.addEventListener("scroll",i,{passive:!0}),[u,$x(u)]):null}).filter(l=>l!=null);n(a.length?new Map(a):null),r.current=e}return()=>{s(e),s(o)};function s(a){a.forEach(l=>{const u=V_(l);u==null||u.removeEventListener("scroll",i)})}},[i,e]),E.useMemo(()=>e.length?t?Array.from(t.values()).reduce((o,s)=>dc(o,s),Vi):_j(e):Vi,[e,t])}function n9(e,t){t===void 0&&(t=[]);const n=E.useRef(null);return E.useEffect(()=>{n.current=null},t),E.useEffect(()=>{const r=e!==Vi;r&&!n.current&&(n.current=e),!r&&n.current&&(n.current=null)},[e]),n.current?_0(e,n.current):Vi}function A4e(e){E.useEffect(()=>{if(!xb)return;const t=e.map(n=>{let{sensor:r}=n;return r.setup==null?void 0:r.setup()});return()=>{for(const n of t)n==null||n()}},e.map(t=>{let{sensor:n}=t;return n}))}function O4e(e,t){return E.useMemo(()=>e.reduce((n,r)=>{let{eventName:i,handler:o}=r;return n[i]=s=>{o(s,t)},n},{}),[e,t])}function kj(e){return E.useMemo(()=>e?r4e(e):null,[e])}const G_=[];function R4e(e,t){t===void 0&&(t=Vp);const[n]=e,r=kj(n?mr(n):null),[i,o]=E.useReducer(a,G_),s=Eb({callback:o});return e.length>0&&i===G_&&o(),ko(()=>{e.length?e.forEach(l=>s==null?void 0:s.observe(l)):(s==null||s.disconnect(),o())},[e]),i;function a(){return e.length?e.map(l=>bj(l)?r:new m4(t(l),l)):G_}}function Aj(e){if(!e)return null;if(e.children.length>1)return e;const t=e.children[0];return Bp(t)?t:e}function I4e(e){let{measure:t}=e;const[n,r]=E.useState(null),i=E.useCallback(u=>{for(const{target:c}of u)if(Bp(c)){r(d=>{const f=t(c);return d?{...d,width:f.width,height:f.height}:f});break}},[t]),o=Eb({callback:i}),s=E.useCallback(u=>{const c=Aj(u);o==null||o.disconnect(),c&&(o==null||o.observe(c)),r(c?t(c):null)},[t,o]),[a,l]=b0(s);return E.useMemo(()=>({nodeRef:a,rect:n,setRef:l}),[n,a,l])}const M4e=[{sensor:Tj,options:{}},{sensor:Cj,options:{}}],N4e={current:{}},Lm={draggable:{measure:YA},droppable:{measure:YA,strategy:Gh.WhileDragging,frequency:Bx.Optimized},dragOverlay:{measure:Vp}};class _f extends Map{get(t){var n;return t!=null&&(n=super.get(t))!=null?n:void 0}toArray(){return Array.from(this.values())}getEnabled(){return this.toArray().filter(t=>{let{disabled:n}=t;return!n})}getNodeFor(t){var n,r;return(n=(r=this.get(t))==null?void 0:r.node.current)!=null?n:void 0}}const D4e={activatorEvent:null,active:null,activeNode:null,activeNodeRect:null,collisions:null,containerNodeRect:null,draggableNodes:new Map,droppableRects:new Map,droppableContainers:new _f,over:null,dragOverlay:{nodeRef:{current:null},rect:null,setRef:w0},scrollableAncestors:[],scrollableAncestorRects:[],measuringConfiguration:Lm,measureDroppableContainers:w0,windowRect:null,measuringScheduled:!1},Oj={activatorEvent:null,activators:[],active:null,activeNodeRect:null,ariaDescribedById:{draggable:""},dispatch:w0,draggableNodes:new Map,over:null,measureDroppableContainers:w0},zp=E.createContext(Oj),Rj=E.createContext(D4e);function L4e(){return{draggable:{active:null,initialCoordinates:{x:0,y:0},nodes:new Map,translate:{x:0,y:0}},droppable:{containers:new _f}}}function $4e(e,t){switch(t.type){case cn.DragStart:return{...e,draggable:{...e.draggable,initialCoordinates:t.initialCoordinates,active:t.active}};case cn.DragMove:return e.draggable.active?{...e,draggable:{...e.draggable,translate:{x:t.coordinates.x-e.draggable.initialCoordinates.x,y:t.coordinates.y-e.draggable.initialCoordinates.y}}}:e;case cn.DragEnd:case cn.DragCancel:return{...e,draggable:{...e.draggable,active:null,initialCoordinates:{x:0,y:0},translate:{x:0,y:0}}};case cn.RegisterDroppable:{const{element:n}=t,{id:r}=n,i=new _f(e.droppable.containers);return i.set(r,n),{...e,droppable:{...e.droppable,containers:i}}}case cn.SetDroppableDisabled:{const{id:n,key:r,disabled:i}=t,o=e.droppable.containers.get(n);if(!o||r!==o.key)return e;const s=new _f(e.droppable.containers);return s.set(n,{...o,disabled:i}),{...e,droppable:{...e.droppable,containers:s}}}case cn.UnregisterDroppable:{const{id:n,key:r}=t,i=e.droppable.containers.get(n);if(!i||r!==i.key)return e;const o=new _f(e.droppable.containers);return o.delete(n),{...e,droppable:{...e.droppable,containers:o}}}default:return e}}function F4e(e){let{disabled:t}=e;const{active:n,activatorEvent:r,draggableNodes:i}=E.useContext(zp),o=S0(r),s=S0(n==null?void 0:n.id);return E.useEffect(()=>{if(!t&&!r&&o&&s!=null){if(!p4(o)||document.activeElement===o.target)return;const a=i.get(s);if(!a)return;const{activatorNode:l,node:u}=a;if(!l.current&&!u.current)return;requestAnimationFrame(()=>{for(const c of[l.current,u.current]){if(!c)continue;const d=O3e(c);if(d){d.focus();break}}})}},[r,t,i,s,o]),null}function Ij(e,t){let{transform:n,...r}=t;return e!=null&&e.length?e.reduce((i,o)=>o({transform:i,...r}),n):n}function B4e(e){return E.useMemo(()=>({draggable:{...Lm.draggable,...e==null?void 0:e.draggable},droppable:{...Lm.droppable,...e==null?void 0:e.droppable},dragOverlay:{...Lm.dragOverlay,...e==null?void 0:e.dragOverlay}}),[e==null?void 0:e.draggable,e==null?void 0:e.droppable,e==null?void 0:e.dragOverlay])}function j4e(e){let{activeNode:t,measure:n,initialRect:r,config:i=!0}=e;const o=E.useRef(!1),{x:s,y:a}=typeof i=="boolean"?{x:i,y:i}:i;ko(()=>{if(!s&&!a||!t){o.current=!1;return}if(o.current||!r)return;const u=t==null?void 0:t.node.current;if(!u||u.isConnected===!1)return;const c=n(u),d=pj(c,r);if(s||(d.x=0),a||(d.y=0),o.current=!0,Math.abs(d.x)>0||Math.abs(d.y)>0){const f=mj(u);f&&f.scrollBy({top:d.y,left:d.x})}},[t,s,a,r,n])}const Pb=E.createContext({...Vi,scaleX:1,scaleY:1});var zs;(function(e){e[e.Uninitialized=0]="Uninitialized",e[e.Initializing=1]="Initializing",e[e.Initialized=2]="Initialized"})(zs||(zs={}));const V4e=E.memo(function(t){var n,r,i,o;let{id:s,accessibility:a,autoScroll:l=!0,children:u,sensors:c=M4e,collisionDetection:d=Y3e,measuring:f,modifiers:h,...p}=t;const m=E.useReducer($4e,void 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dc12c53df4..1215bc36df 100644 --- a/invokeai/frontend/web/dist/index.html +++ b/invokeai/frontend/web/dist/index.html @@ -12,7 +12,7 @@ margin: 0; } - + diff --git a/invokeai/frontend/web/public/locales/en.json b/invokeai/frontend/web/public/locales/en.json index a8f52742d4..32ff574925 100644 --- a/invokeai/frontend/web/public/locales/en.json +++ b/invokeai/frontend/web/public/locales/en.json @@ -399,6 +399,8 @@ "deleteModel": "Delete Model", "deleteConfig": "Delete Config", "deleteMsg1": "Are you sure you want to delete this model from InvokeAI?", + "modelDeleted": "Model Deleted", + "modelDeleteFailed": "Failed to delete model", "deleteMsg2": "This WILL delete the model from disk if it is in the InvokeAI root folder. If you are using a custom location, then the model WILL NOT be deleted from disk.", "formMessageDiffusersModelLocation": "Diffusers Model Location", "formMessageDiffusersModelLocationDesc": "Please enter at least one.", @@ -408,11 +410,13 @@ "convertToDiffusers": "Convert To Diffusers", "convertToDiffusersHelpText1": "This model will be converted to the 🧨 Diffusers format.", "convertToDiffusersHelpText2": "This process will replace your Model Manager entry with the Diffusers version of the same model.", - "convertToDiffusersHelpText3": "Your checkpoint file on the disk will NOT be deleted or modified in anyway. You can add your checkpoint to the Model Manager again if you want to.", + "convertToDiffusersHelpText3": "Your checkpoint file on disk WILL be deleted if it is in InvokeAI root folder. If it is in a custom location, then it WILL NOT be deleted.", "convertToDiffusersHelpText4": "This is a one time process only. It might take around 30s-60s depending on the specifications of your computer.", "convertToDiffusersHelpText5": "Please make sure you have enough disk space. Models generally vary between 2GB-7GB in size.", "convertToDiffusersHelpText6": "Do you wish to convert this model?", "convertToDiffusersSaveLocation": "Save Location", + "noCustomLocationProvided": "No Custom Location Provided", + "convertingModelBegin": "Converting Model. Please wait.", "v1": "v1", "v2_base": "v2 (512px)", "v2_768": "v2 (768px)", @@ -450,7 +454,8 @@ "none": "none", "addDifference": "Add Difference", "pickModelType": "Pick Model Type", - "selectModel": "Select Model" + "selectModel": "Select Model", + "importModels": "Import Models" }, "parameters": { "general": "General", @@ -572,6 +577,7 @@ "uploadFailedInvalidUploadDesc": "Must be single PNG or JPEG image", "downloadImageStarted": "Image Download Started", "imageCopied": "Image Copied", + "problemCopyingImage": "Unable to Copy Image", "imageLinkCopied": "Image Link Copied", "problemCopyingImageLink": "Unable to Copy Image Link", "imageNotLoaded": "No Image Loaded", @@ -688,6 +694,15 @@ "reloadSchema": "Reload Schema", "saveNodes": "Save Nodes", "loadNodes": "Load Nodes", - "clearNodes": "Clear Nodes" + "clearNodes": "Clear Nodes", + "zoomInNodes": "Zoom In", + "zoomOutNodes": "Zoom Out", + "fitViewportNodes": "Fit View", + "hideGraphNodes": "Hide Graph Overlay", + "showGraphNodes": "Show Graph Overlay", + "hideLegendNodes": "Hide Field Type Legend", + "showLegendNodes": "Show Field Type Legend", + "hideMinimapnodes": "Hide MiniMap", + "showMinimapnodes": "Show MiniMap" } } diff --git a/invokeai/frontend/web/src/app/components/GlobalHotkeys.ts b/invokeai/frontend/web/src/app/components/GlobalHotkeys.ts index c4660416bf..9827e7f2b3 100644 --- a/invokeai/frontend/web/src/app/components/GlobalHotkeys.ts +++ b/invokeai/frontend/web/src/app/components/GlobalHotkeys.ts @@ -1,7 +1,9 @@ import { createSelector } from '@reduxjs/toolkit'; import { RootState } from 'app/store/store'; import { useAppDispatch, useAppSelector } from 'app/store/storeHooks'; +import { requestCanvasRescale } from 'features/canvas/store/thunks/requestCanvasScale'; import { shiftKeyPressed } from 'features/ui/store/hotkeysSlice'; +import { activeTabNameSelector } from 'features/ui/store/uiSelectors'; import { setActiveTab, toggleGalleryPanel, @@ -14,10 +16,11 @@ import React, { memo } from 'react'; import { isHotkeyPressed, useHotkeys } from 'react-hotkeys-hook'; const globalHotkeysSelector = createSelector( - (state: RootState) => state.hotkeys, - (hotkeys) => { + [(state: RootState) => state.hotkeys, (state: RootState) => state.ui], + (hotkeys, ui) => { const { shift } = hotkeys; - return { shift }; + const { shouldPinParametersPanel, shouldPinGallery } = ui; + return { shift, shouldPinGallery, shouldPinParametersPanel }; }, { memoizeOptions: { @@ -34,7 +37,10 @@ const globalHotkeysSelector = createSelector( */ const GlobalHotkeys: React.FC = () => { const dispatch = useAppDispatch(); - const { shift } = useAppSelector(globalHotkeysSelector); + const { shift, shouldPinParametersPanel, shouldPinGallery } = useAppSelector( + globalHotkeysSelector + ); + const activeTabName = useAppSelector(activeTabNameSelector); useHotkeys( '*', @@ -51,18 +57,30 @@ const GlobalHotkeys: React.FC = () => { useHotkeys('o', () => { dispatch(toggleParametersPanel()); + if (activeTabName === 'unifiedCanvas' && shouldPinParametersPanel) { + dispatch(requestCanvasRescale()); + } }); useHotkeys(['shift+o'], () => { dispatch(togglePinParametersPanel()); + if (activeTabName === 'unifiedCanvas') { + dispatch(requestCanvasRescale()); + } }); useHotkeys('g', () => { dispatch(toggleGalleryPanel()); + if (activeTabName === 'unifiedCanvas' && shouldPinGallery) { + dispatch(requestCanvasRescale()); + } }); useHotkeys(['shift+g'], () => { dispatch(togglePinGalleryPanel()); + if (activeTabName === 'unifiedCanvas') { + dispatch(requestCanvasRescale()); + } }); useHotkeys('1', () => { diff --git a/invokeai/frontend/web/src/app/store/middleware/listenerMiddleware/index.ts b/invokeai/frontend/web/src/app/store/middleware/listenerMiddleware/index.ts index edeb156439..94044d3cc5 100644 --- a/invokeai/frontend/web/src/app/store/middleware/listenerMiddleware/index.ts +++ b/invokeai/frontend/web/src/app/store/middleware/listenerMiddleware/index.ts @@ -88,6 +88,8 @@ import { addUserInvokedCanvasListener } from './listeners/userInvokedCanvas'; import { addUserInvokedImageToImageListener } from './listeners/userInvokedImageToImage'; import { addUserInvokedNodesListener } from './listeners/userInvokedNodes'; import { addUserInvokedTextToImageListener } from './listeners/userInvokedTextToImage'; +import { addModelLoadStartedEventListener } from './listeners/socketio/socketModelLoadStarted'; +import { addModelLoadCompletedEventListener } from './listeners/socketio/socketModelLoadCompleted'; export const listenerMiddleware = createListenerMiddleware(); @@ -177,6 +179,8 @@ addSocketConnectedListener(); addSocketDisconnectedListener(); addSocketSubscribedListener(); addSocketUnsubscribedListener(); +addModelLoadStartedEventListener(); +addModelLoadCompletedEventListener(); // Session Created addSessionCreatedPendingListener(); diff --git a/invokeai/frontend/web/src/app/store/middleware/listenerMiddleware/listeners/socketio/socketModelLoadCompleted.ts b/invokeai/frontend/web/src/app/store/middleware/listenerMiddleware/listeners/socketio/socketModelLoadCompleted.ts new file mode 100644 index 0000000000..bc533b9178 --- /dev/null +++ b/invokeai/frontend/web/src/app/store/middleware/listenerMiddleware/listeners/socketio/socketModelLoadCompleted.ts @@ -0,0 +1,28 @@ +import { log } from 'app/logging/useLogger'; +import { + appSocketModelLoadCompleted, + socketModelLoadCompleted, +} from 'services/events/actions'; +import { startAppListening } from '../..'; + +const moduleLog = log.child({ namespace: 'socketio' }); + +export const addModelLoadCompletedEventListener = () => { + startAppListening({ + actionCreator: socketModelLoadCompleted, + effect: (action, { dispatch, getState }) => { + const { model_name, model_type, submodel } = action.payload.data; + + let modelString = `${model_type} model: ${model_name}`; + + if (submodel) { + modelString = modelString.concat(`, submodel: ${submodel}`); + } + + moduleLog.debug(action.payload, `Model load completed (${modelString})`); + + // pass along the socket event as an application action + dispatch(appSocketModelLoadCompleted(action.payload)); + }, + }); +}; diff --git a/invokeai/frontend/web/src/app/store/middleware/listenerMiddleware/listeners/socketio/socketModelLoadStarted.ts b/invokeai/frontend/web/src/app/store/middleware/listenerMiddleware/listeners/socketio/socketModelLoadStarted.ts new file mode 100644 index 0000000000..aa53a70cee --- /dev/null +++ b/invokeai/frontend/web/src/app/store/middleware/listenerMiddleware/listeners/socketio/socketModelLoadStarted.ts @@ -0,0 +1,28 @@ +import { log } from 'app/logging/useLogger'; +import { + appSocketModelLoadStarted, + socketModelLoadStarted, +} from 'services/events/actions'; +import { startAppListening } from '../..'; + +const moduleLog = log.child({ namespace: 'socketio' }); + +export const addModelLoadStartedEventListener = () => { + startAppListening({ + actionCreator: socketModelLoadStarted, + effect: (action, { dispatch, getState }) => { + const { model_name, model_type, submodel } = action.payload.data; + + let modelString = `${model_type} model: ${model_name}`; + + if (submodel) { + modelString = modelString.concat(`, submodel: ${submodel}`); + } + + moduleLog.debug(action.payload, `Model load started (${modelString})`); + + // pass along the socket event as an application action + dispatch(appSocketModelLoadStarted(action.payload)); + }, + }); +}; diff --git a/invokeai/frontend/web/src/app/store/store.ts b/invokeai/frontend/web/src/app/store/store.ts index 2bafd21a74..4725a2f921 100644 --- a/invokeai/frontend/web/src/app/store/store.ts +++ b/invokeai/frontend/web/src/app/store/store.ts @@ -21,6 +21,7 @@ import generationReducer from 'features/parameters/store/generationSlice'; import postprocessingReducer from 'features/parameters/store/postprocessingSlice'; import configReducer from 'features/system/store/configSlice'; import systemReducer from 'features/system/store/systemSlice'; +import modelmanagerReducer from 'features/ui/components/tabs/ModelManager/store/modelManagerSlice'; import hotkeysReducer from 'features/ui/store/hotkeysSlice'; import uiReducer from 'features/ui/store/uiSlice'; @@ -49,6 +50,7 @@ const allReducers = { dynamicPrompts: dynamicPromptsReducer, imageDeletion: imageDeletionReducer, lora: loraReducer, + modelmanager: modelmanagerReducer, [api.reducerPath]: api.reducer, }; @@ -67,6 +69,7 @@ const rememberedKeys: (keyof typeof allReducers)[] = [ 'controlNet', 'dynamicPrompts', 'lora', + 'modelmanager', ]; export const store = configureStore({ diff --git a/invokeai/frontend/web/src/common/components/IAIDndImage.tsx b/invokeai/frontend/web/src/common/components/IAIDndImage.tsx index 991398f5a0..c024622d2e 100644 --- a/invokeai/frontend/web/src/common/components/IAIDndImage.tsx +++ b/invokeai/frontend/web/src/common/components/IAIDndImage.tsx @@ -21,6 +21,7 @@ import { ImageDTO } from 'services/api/types'; import { mode } from 'theme/util/mode'; import IAIDraggable from './IAIDraggable'; import IAIDroppable from './IAIDroppable'; +import ImageContextMenu from 'features/gallery/components/ImageContextMenu/ImageContextMenu'; type IAIDndImageProps = { imageDTO: ImageDTO | undefined; @@ -96,119 +97,124 @@ const IAIDndImage = (props: IAIDndImageProps) => { }; return ( - - {imageDTO && ( + + {(ref) => ( - } - width={imageDTO.width} - height={imageDTO.height} - onError={onError} - draggable={false} - sx={{ - objectFit: 'contain', - maxW: 'full', - maxH: 'full', - borderRadius: 'base', - shadow: isSelected ? 'selected.light' : undefined, - _dark: { shadow: isSelected ? 'selected.dark' : undefined }, - ...imageSx, - }} - /> - {withMetadataOverlay && } - - )} - {!imageDTO && !isUploadDisabled && ( - <> - - - + } + width={imageDTO.width} + height={imageDTO.height} + onError={onError} + draggable={false} + sx={{ + objectFit: 'contain', + maxW: 'full', + maxH: 'full', + borderRadius: 'base', + shadow: isSelected ? 'selected.light' : undefined, + _dark: { shadow: isSelected ? 'selected.dark' : undefined }, + ...imageSx, + }} + /> + {withMetadataOverlay && } + + )} + {!imageDTO && !isUploadDisabled && ( + <> + + + + + + )} + {!imageDTO && isUploadDisabled && noContentFallback} + {!isDropDisabled && ( + + )} + {imageDTO && !isDragDisabled && ( + + )} + {onClickReset && withResetIcon && imageDTO && ( + - - + )} + )} - {!imageDTO && isUploadDisabled && noContentFallback} - {!isDropDisabled && ( - - )} - {imageDTO && !isDragDisabled && ( - - )} - {onClickReset && withResetIcon && imageDTO && ( - - )} - + ); }; diff --git a/invokeai/frontend/web/src/common/components/IAIInput.tsx b/invokeai/frontend/web/src/common/components/IAIInput.tsx index d114fc5968..31dac20998 100644 --- a/invokeai/frontend/web/src/common/components/IAIInput.tsx +++ b/invokeai/frontend/web/src/common/components/IAIInput.tsx @@ -8,19 +8,34 @@ import { import { useAppDispatch } from 'app/store/storeHooks'; import { stopPastePropagation } from 'common/util/stopPastePropagation'; import { shiftKeyPressed } from 'features/ui/store/hotkeysSlice'; -import { ChangeEvent, KeyboardEvent, memo, useCallback } from 'react'; +import { + CSSProperties, + ChangeEvent, + KeyboardEvent, + memo, + useCallback, +} from 'react'; interface IAIInputProps extends InputProps { label?: string; + labelPos?: 'top' | 'side'; value?: string; size?: string; onChange?: (e: ChangeEvent) => void; formControlProps?: Omit; } +const labelPosVerticalStyle: CSSProperties = { + display: 'flex', + flexDirection: 'row', + alignItems: 'center', + gap: 10, +}; + const IAIInput = (props: IAIInputProps) => { const { label = '', + labelPos = 'top', isDisabled = false, isInvalid, formControlProps, @@ -51,6 +66,7 @@ const IAIInput = (props: IAIInputProps) => { isInvalid={isInvalid} isDisabled={isDisabled} {...formControlProps} + style={labelPos === 'side' ? labelPosVerticalStyle : undefined} > {label !== '' && {label}} & { +export type IAISelectProps = Omit & { tooltip?: string; inputRef?: RefObject; label?: string; }; const IAIMantineSelect = (props: IAISelectProps) => { - const { tooltip, inputRef, label, disabled, ...rest } = props; + const { tooltip, inputRef, label, disabled, required, ...rest } = props; const styles = useMantineSelectStyles(); @@ -25,7 +25,7 @@ const IAIMantineSelect = (props: IAISelectProps) => {