translationBot(ui): update translation files

Updated by "Cleanup translation files" hook in Weblate.

Co-authored-by: Hosted Weblate <hosted@weblate.org>
Translate-URL: https://hosted.weblate.org/projects/invokeai/web-ui/
Translation: InvokeAI/Web UI

docs/help/FAQ.md

@@ -40,6 +40,25 @@ Follow the same steps to scan and import the missing models.
 - Check the `ram` setting in `invokeai.yaml`. This setting tells Invoke how much of your system RAM can be used to cache models. Having this too high or too low can slow things down. That said, it's generally safest to not set this at all and instead let Invoke manage it.
 - Check the `vram` setting in `invokeai.yaml`. This setting tells Invoke how much of your GPU VRAM can be used to cache models. Counter-intuitively, if this setting is too high, Invoke will need to do a lot of shuffling of models as it juggles the VRAM cache and the currently-loaded model. The default value of 0.25 is generally works well for GPUs without 16GB or more VRAM. Even on a 24GB card, the default works well.
 - Check that your generations are happening on your GPU (if you have one). InvokeAI will log what is being used for generation upon startup. If your GPU isn't used, re-install to ensure the correct versions of torch get installed.
+- If you are on Windows, you may have exceeded your GPU's VRAM capacity and are using slower [shared GPU memory](#shared-gpu-memory-windows). There's a guide to opt out of this behaviour in the linked FAQ entry.
+
+## Shared GPU Memory (Windows)
+
+!!! tip "Nvidia GPUs with driver 536.40"
+
+    This only applies to current Nvidia cards with driver 536.40 or later, released in June 2023.
+
+When the GPU doesn't have enough VRAM for a task, Windows is able to allocate some of its CPU RAM to the GPU. This is much slower than VRAM, but it does allow the system to generate when it otherwise might no have enough VRAM.
+
+When shared GPU memory is used, generation slows down dramatically - but at least it doesn't crash.
+
+If you'd like to opt out of this behavior and instead get an error when you exceed your GPU's VRAM, follow [this guide from Nvidia](https://nvidia.custhelp.com/app/answers/detail/a_id/5490).
+
+Here's how to get the python path required in the linked guide:
+
+- Run `invoke.bat`.
+- Select option 2 for developer console.
+- At least one python path will be printed. Copy the path that includes your invoke installation directory (typically the first).
 
 ## Installer cannot find python (Windows)
 

invokeai/app/invocations/ip_adapter.py

@@ -67,7 +67,7 @@ class IPAdapterInvocation(BaseInvocation):
     )
     clip_vision_model: Literal["ViT-H", "ViT-G"] = InputField(
         description="CLIP Vision model to use. Overrides model settings. Mandatory for checkpoint models.",
-        default="auto",
+        default="ViT-H",
         ui_order=2,
     )
     weight: Union[float, List[float]] = InputField(

invokeai/app/services/model_manager/model_manager_default.py

@@ -80,6 +80,7 @@ class ModelManagerService(ModelManagerServiceBase):
         ram_cache = ModelCache(
             max_cache_size=app_config.ram,
             max_vram_cache_size=app_config.vram,
+            lazy_offloading=app_config.lazy_offload,
             logger=logger,
             execution_device=execution_device,
         )

invokeai/backend/model_manager/load/model_cache/model_cache_base.py

@@ -117,7 +117,7 @@ class ModelCacheBase(ABC, Generic[T]):
 
     @property
     @abstractmethod
-    def stats(self) -> CacheStats:
+    def stats(self) -> Optional[CacheStats]:
         """Return collected CacheStats object."""
         pass
 

invokeai/backend/model_manager/load/model_cache/model_cache_default.py

@@ -269,9 +269,6 @@ class ModelCache(ModelCacheBase[AnyModel]):
         if torch.device(source_device).type == torch.device(target_device).type:
             return
 
-        # may raise an exception here if insufficient GPU VRAM
-        self._check_free_vram(target_device, cache_entry.size)
-
         start_model_to_time = time.time()
         snapshot_before = self._capture_memory_snapshot()
         cache_entry.model.to(target_device)
@@ -329,11 +326,11 @@ class ModelCache(ModelCacheBase[AnyModel]):
                     f" {in_ram_models}/{in_vram_models}({locked_in_vram_models})"
                 )
 
-    def make_room(self, model_size: int) -> None:
+    def make_room(self, size: int) -> None:
         """Make enough room in the cache to accommodate a new model of indicated size."""
         # calculate how much memory this model will require
         # multiplier = 2 if self.precision==torch.float32 else 1
-        bytes_needed = model_size
+        bytes_needed = size
         maximum_size = self.max_cache_size * GIG  # stored in GB, convert to bytes
         current_size = self.cache_size()
 
@@ -388,7 +385,7 @@ class ModelCache(ModelCacheBase[AnyModel]):
             # 1 from onnx runtime object
             if not cache_entry.locked and refs <= (3 if "onnx" in model_key else 2):
                 self.logger.debug(
-                    f"Removing {model_key} from RAM cache to free at least {(model_size/GIG):.2f} GB (-{(cache_entry.size/GIG):.2f} GB)"
+                    f"Removing {model_key} from RAM cache to free at least {(size/GIG):.2f} GB (-{(cache_entry.size/GIG):.2f} GB)"
                 )
                 current_size -= cache_entry.size
                 models_cleared += 1
@@ -420,17 +417,3 @@ class ModelCache(ModelCacheBase[AnyModel]):
             mps.empty_cache()
 
         self.logger.debug(f"After making room: cached_models={len(self._cached_models)}")
-
-    def _check_free_vram(self, target_device: torch.device, needed_size: int) -> None:
-        if target_device.type != "cuda":
-            return
-        vram_device = (  # mem_get_info() needs an indexed device
-            target_device if target_device.index is not None else torch.device(str(target_device), index=0)
-        )
-        free_mem, _ = torch.cuda.mem_get_info(torch.device(vram_device))
-        if needed_size > free_mem:
-            needed_gb = round(needed_size / GIG, 2)
-            free_gb = round(free_mem / GIG, 2)
-            raise torch.cuda.OutOfMemoryError(
-                f"Insufficient VRAM to load model, requested {needed_gb}GB but only had {free_gb}GB free"
-            )

invokeai/backend/model_manager/load/model_cache/model_locker.py

@@ -34,7 +34,6 @@ class ModelLocker(ModelLockerBase):
 
         # NOTE that the model has to have the to() method in order for this code to move it into GPU!
         self._cache_entry.lock()
-
         try:
             if self._cache.lazy_offloading:
                 self._cache.offload_unlocked_models(self._cache_entry.size)
@@ -51,6 +50,7 @@ class ModelLocker(ModelLockerBase):
         except Exception:
             self._cache_entry.unlock()
             raise
+
         return self.model
 
     def unlock(self) -> None:

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

@@ -291,7 +291,6 @@
         "canvasMerged": "تم دمج الخط",
         "sentToImageToImage": "تم إرسال إلى صورة إلى صورة",
         "sentToUnifiedCanvas": "تم إرسال إلى لوحة موحدة",
-        "parametersSet": "تم تعيين المعلمات",
         "parametersNotSet": "لم يتم تعيين المعلمات",
         "metadataLoadFailed": "فشل تحميل البيانات الوصفية"
     },

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

@@ -75,7 +75,8 @@
         "copy": "Kopieren",
         "aboutHeading": "Nutzen Sie Ihre kreative Energie",
         "toResolve": "Lösen",
-        "add": "Hinzufügen"
+        "add": "Hinzufügen",
+        "loglevel": "Protokoll Stufe"
     },
     "gallery": {
         "galleryImageSize": "Bildgröße",
@@ -388,7 +389,14 @@
         "vaePrecision": "VAE-Präzision",
         "variant": "Variante",
         "modelDeleteFailed": "Modell konnte nicht gelöscht werden",
-        "noModelSelected": "Kein Modell ausgewählt"
+        "noModelSelected": "Kein Modell ausgewählt",
+        "huggingFace": "HuggingFace",
+        "defaultSettings": "Standardeinstellungen",
+        "edit": "Bearbeiten",
+        "cancel": "Stornieren",
+        "defaultSettingsSaved": "Standardeinstellungen gespeichert",
+        "addModels": "Model hinzufügen",
+        "deleteModelImage": "Lösche Model Bild"
     },
     "parameters": {
         "images": "Bilder",
@@ -472,7 +480,6 @@
         "canvasMerged": "Leinwand zusammengeführt",
         "sentToImageToImage": "Gesendet an Bild zu Bild",
         "sentToUnifiedCanvas": "Gesendet an Leinwand",
-        "parametersSet": "Parameter festlegen",
         "parametersNotSet": "Parameter nicht festgelegt",
         "metadataLoadFailed": "Metadaten konnten nicht geladen werden",
         "setCanvasInitialImage": "Ausgangsbild setzen",
@@ -677,7 +684,8 @@
         "body": "Körper",
         "hands": "Hände",
         "dwOpenpose": "DW Openpose",
-        "dwOpenposeDescription": "Posenschätzung mit DW Openpose"
+        "dwOpenposeDescription": "Posenschätzung mit DW Openpose",
+        "selectCLIPVisionModel": "Wähle ein CLIP Vision Model aus"
     },
     "queue": {
         "status": "Status",
@@ -765,7 +773,10 @@
         "recallParameters": "Parameter wiederherstellen",
         "cfgRescaleMultiplier": "$t(parameters.cfgRescaleMultiplier)",
         "allPrompts": "Alle Prompts",
-        "imageDimensions": "Bilder Auslösungen"
+        "imageDimensions": "Bilder Auslösungen",
+        "parameterSet": "Parameter {{parameter}} setzen",
+        "recallParameter": "{{label}} Abrufen",
+        "parsingFailed": "Parsing Fehlgeschlagen"
     },
     "popovers": {
         "noiseUseCPU": {
@@ -1030,7 +1041,8 @@
             "title": "Bild"
         },
         "advanced": {
-            "title": "Erweitert"
+            "title": "Erweitert",
+            "options": "$t(accordions.advanced.title) Optionen"
         },
         "control": {
             "title": "Kontrolle"

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

@@ -1041,10 +1041,10 @@
         "metadataLoadFailed": "Failed to load metadata",
         "modelAddedSimple": "Model Added to Queue",
         "modelImportCanceled": "Model Import Canceled",
+        "parameters": "Parameters",
         "parameterNotSet": "{{parameter}} not set",
         "parameterSet": "{{parameter}} set",
         "parametersNotSet": "Parameters Not Set",
-        "parametersSet": "Parameters Set",
         "problemCopyingCanvas": "Problem Copying Canvas",
         "problemCopyingCanvasDesc": "Unable to export base layer",
         "problemCopyingImage": "Unable to Copy Image",
@@ -1423,6 +1423,7 @@
         "eraseBoundingBox": "Erase Bounding Box",
         "eraser": "Eraser",
         "fillBoundingBox": "Fill Bounding Box",
+        "initialFitImageSize": "Fit Image Size on Drop",
         "invertBrushSizeScrollDirection": "Invert Scroll for Brush Size",
         "layer": "Layer",
         "limitStrokesToBox": "Limit Strokes to Box",

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

@@ -363,7 +363,6 @@
         "canvasMerged": "Lienzo consolidado",
         "sentToImageToImage": "Enviar hacia Imagen a Imagen",
         "sentToUnifiedCanvas": "Enviar hacia Lienzo Consolidado",
-        "parametersSet": "Parámetros establecidos",
         "parametersNotSet": "Parámetros no establecidos",
         "metadataLoadFailed": "Error al cargar metadatos",
         "serverError": "Error en el servidor",

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

@@ -298,7 +298,6 @@
         "canvasMerged": "Canvas fusionné",
         "sentToImageToImage": "Envoyé à Image à Image",
         "sentToUnifiedCanvas": "Envoyé à Canvas unifié",
-        "parametersSet": "Paramètres définis",
         "parametersNotSet": "Paramètres non définis",
         "metadataLoadFailed": "Échec du chargement des métadonnées"
     },

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

@@ -306,7 +306,6 @@
         "canvasMerged": "קנבס מוזג",
         "sentToImageToImage": "נשלח לתמונה לתמונה",
         "sentToUnifiedCanvas": "נשלח אל קנבס מאוחד",
-        "parametersSet": "הגדרת פרמטרים",
         "parametersNotSet": "פרמטרים לא הוגדרו",
         "metadataLoadFailed": "טעינת מטא-נתונים נכשלה"
     },

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

@@ -366,7 +366,7 @@
         "modelConverted": "Modello convertito",
         "alpha": "Alpha",
         "convertToDiffusersHelpText1": "Questo modello verrà convertito nel formato 🧨 Diffusori.",
-        "convertToDiffusersHelpText3": "Il file Checkpoint su disco verrà eliminato se si trova nella cartella principale di InvokeAI. Se si trova invece in una posizione personalizzata, NON verrà eliminato.",
+        "convertToDiffusersHelpText3": "Il file del modello su disco verrà eliminato se si trova nella cartella principale di InvokeAI. Se si trova invece in una posizione personalizzata, NON verrà eliminato.",
         "v2_base": "v2 (512px)",
         "v2_768": "v2 (768px)",
         "none": "nessuno",
@@ -443,7 +443,8 @@
         "noModelsInstalled": "Nessun modello installato",
         "hfTokenInvalidErrorMessage2": "Aggiornalo in ",
         "main": "Principali",
-        "noModelsInstalledDesc1": "Installa i modelli con"
+        "noModelsInstalledDesc1": "Installa i modelli con",
+        "ipAdapters": "Adattatori IP"
     },
     "parameters": {
         "images": "Immagini",
@@ -568,7 +569,6 @@
         "canvasMerged": "Tela unita",
         "sentToImageToImage": "Inviato a Immagine a Immagine",
         "sentToUnifiedCanvas": "Inviato a Tela Unificata",
-        "parametersSet": "Parametri impostati",
         "parametersNotSet": "Parametri non impostati",
         "metadataLoadFailed": "Impossibile caricare i metadati",
         "serverError": "Errore del Server",
@@ -937,7 +937,8 @@
         "controlnet": "$t(controlnet.controlAdapter_one) #{{number}} ($t(common.controlNet))",
         "mediapipeFace": "Mediapipe Volto",
         "ip_adapter": "$t(controlnet.controlAdapter_one) #{{number}} ($t(common.ipAdapter))",
-        "t2i_adapter": "$t(controlnet.controlAdapter_one) #{{number}} ($t(common.t2iAdapter))"
+        "t2i_adapter": "$t(controlnet.controlAdapter_one) #{{number}} ($t(common.t2iAdapter))",
+        "selectCLIPVisionModel": "Seleziona un modello CLIP Vision"
     },
     "queue": {
         "queueFront": "Aggiungi all'inizio della coda",

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

@@ -420,7 +420,6 @@
         "canvasMerged": "Canvas samengevoegd",
         "sentToImageToImage": "Gestuurd naar Afbeelding naar afbeelding",
         "sentToUnifiedCanvas": "Gestuurd naar Centraal canvas",
-        "parametersSet": "Parameters ingesteld",
         "parametersNotSet": "Parameters niet ingesteld",
         "metadataLoadFailed": "Fout bij laden metagegevens",
         "serverError": "Serverfout",

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

@@ -267,7 +267,6 @@
         "canvasMerged": "Scalono widoczne warstwy",
         "sentToImageToImage": "Wysłano do Obraz na obraz",
         "sentToUnifiedCanvas": "Wysłano do trybu uniwersalnego",
-        "parametersSet": "Ustawiono parametry",
         "parametersNotSet": "Nie ustawiono parametrów",
         "metadataLoadFailed": "Błąd wczytywania metadanych"
     },

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

@@ -310,7 +310,6 @@
         "canvasMerged": "Tela Fundida",
         "sentToImageToImage": "Mandar Para Imagem Para Imagem",
         "sentToUnifiedCanvas": "Enviada para a Tela Unificada",
-        "parametersSet": "Parâmetros Definidos",
         "parametersNotSet": "Parâmetros Não Definidos",
         "metadataLoadFailed": "Falha ao tentar carregar metadados"
     },

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

@@ -307,7 +307,6 @@
         "canvasMerged": "Tela Fundida",
         "sentToImageToImage": "Mandar Para Imagem Para Imagem",
         "sentToUnifiedCanvas": "Enviada para a Tela Unificada",
-        "parametersSet": "Parâmetros Definidos",
         "parametersNotSet": "Parâmetros Não Definidos",
         "metadataLoadFailed": "Falha ao tentar carregar metadados"
     },

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

@@ -575,7 +575,6 @@
         "canvasMerged": "Холст объединен",
         "sentToImageToImage": "Отправить в img2img",
         "sentToUnifiedCanvas": "Отправлено на Единый холст",
-        "parametersSet": "Параметры заданы",
         "parametersNotSet": "Параметры не заданы",
         "metadataLoadFailed": "Не удалось загрузить метаданные",
         "serverError": "Ошибка сервера",

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

@@ -315,7 +315,6 @@
         "canvasMerged": "Полотно об'єднане",
         "sentToImageToImage": "Надіслати до img2img",
         "sentToUnifiedCanvas": "Надіслати на полотно",
-        "parametersSet": "Параметри задані",
         "parametersNotSet": "Параметри не задані",
         "metadataLoadFailed": "Не вдалося завантажити метадані",
         "serverError": "Помилка сервера",

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

@@ -487,7 +487,6 @@
         "canvasMerged": "画布已合并",
         "sentToImageToImage": "已发送到图生图",
         "sentToUnifiedCanvas": "已发送到统一画布",
-        "parametersSet": "参数已设定",
         "parametersNotSet": "参数未设定",
         "metadataLoadFailed": "加载元数据失败",
         "uploadFailedInvalidUploadDesc": "必须是单张的 PNG 或 JPEG 图片",

invokeai/frontend/web/src/features/canvas/components/IAICanvasToolbar/IAICanvasSettingsButtonPopover.tsx

@@ -18,6 +18,7 @@ import {
   setShouldAutoSave,
   setShouldCropToBoundingBoxOnSave,
   setShouldDarkenOutsideBoundingBox,
+  setShouldFitImageSize,
   setShouldInvertBrushSizeScrollDirection,
   setShouldRestrictStrokesToBox,
   setShouldShowCanvasDebugInfo,
@@ -48,6 +49,7 @@ const IAICanvasSettingsButtonPopover = () => {
   const shouldSnapToGrid = useAppSelector((s) => s.canvas.shouldSnapToGrid);
   const shouldRestrictStrokesToBox = useAppSelector((s) => s.canvas.shouldRestrictStrokesToBox);
   const shouldAntialias = useAppSelector((s) => s.canvas.shouldAntialias);
+  const shouldFitImageSize = useAppSelector((s) => s.canvas.shouldFitImageSize);
 
   useHotkeys(
     ['n'],
@@ -102,6 +104,10 @@ const IAICanvasSettingsButtonPopover = () => {
     (e: ChangeEvent<HTMLInputElement>) => dispatch(setShouldAntialias(e.target.checked)),
     [dispatch]
   );
+  const handleChangeShouldFitImageSize = useCallback(
+    (e: ChangeEvent<HTMLInputElement>) => dispatch(setShouldFitImageSize(e.target.checked)),
+    [dispatch]
+  );
 
   return (
     <Popover>
@@ -165,6 +171,10 @@ const IAICanvasSettingsButtonPopover = () => {
                 <FormLabel>{t('unifiedCanvas.antialiasing')}</FormLabel>
                 <Checkbox isChecked={shouldAntialias} onChange={handleChangeShouldAntialias} />
               </FormControl>
+              <FormControl>
+                <FormLabel>{t('unifiedCanvas.initialFitImageSize')}</FormLabel>
+                <Checkbox isChecked={shouldFitImageSize} onChange={handleChangeShouldFitImageSize} />
+              </FormControl>
             </FormControlGroup>
             <ClearCanvasHistoryButtonModal />
           </Flex>

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

@@ -66,6 +66,7 @@ const initialCanvasState: CanvasState = {
   shouldAutoSave: false,
   shouldCropToBoundingBoxOnSave: false,
   shouldDarkenOutsideBoundingBox: false,
+  shouldFitImageSize: true,
   shouldInvertBrushSizeScrollDirection: false,
   shouldLockBoundingBox: false,
   shouldPreserveMaskedArea: false,
@@ -144,12 +145,20 @@ export const canvasSlice = createSlice({
       reducer: (state, action: PayloadActionWithOptimalDimension<ImageDTO>) => {
         const { width, height, image_name } = action.payload;
         const { optimalDimension } = action.meta;
-        const { stageDimensions } = state;
+        const { stageDimensions, shouldFitImageSize } = state;
 
-        const newBoundingBoxDimensions = {
-          width: roundDownToMultiple(clamp(width, CANVAS_GRID_SIZE_FINE, optimalDimension), CANVAS_GRID_SIZE_FINE),
-          height: roundDownToMultiple(clamp(height, CANVAS_GRID_SIZE_FINE, optimalDimension), CANVAS_GRID_SIZE_FINE),
-        };
+        const newBoundingBoxDimensions = shouldFitImageSize
+          ? {
+              width: roundDownToMultiple(width, CANVAS_GRID_SIZE_FINE),
+              height: roundDownToMultiple(height, CANVAS_GRID_SIZE_FINE),
+            }
+          : {
+              width: roundDownToMultiple(clamp(width, CANVAS_GRID_SIZE_FINE, optimalDimension), CANVAS_GRID_SIZE_FINE),
+              height: roundDownToMultiple(
+                clamp(height, CANVAS_GRID_SIZE_FINE, optimalDimension),
+                CANVAS_GRID_SIZE_FINE
+              ),
+            };
 
         const newBoundingBoxCoordinates = {
           x: roundToMultiple(width / 2 - newBoundingBoxDimensions.width / 2, CANVAS_GRID_SIZE_FINE),
@@ -582,6 +591,9 @@ export const canvasSlice = createSlice({
     setShouldAntialias: (state, action: PayloadAction<boolean>) => {
       state.shouldAntialias = action.payload;
     },
+    setShouldFitImageSize: (state, action: PayloadAction<boolean>) => {
+      state.shouldFitImageSize = action.payload;
+    },
     setShouldCropToBoundingBoxOnSave: (state, action: PayloadAction<boolean>) => {
       state.shouldCropToBoundingBoxOnSave = action.payload;
     },
@@ -692,6 +704,7 @@ export const {
   setShouldRestrictStrokesToBox,
   stagingAreaInitialized,
   setShouldAntialias,
+  setShouldFitImageSize,
   canvasResized,
   canvasBatchIdAdded,
   canvasBatchIdsReset,

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

@@ -120,6 +120,7 @@ export interface CanvasState {
   shouldAutoSave: boolean;
   shouldCropToBoundingBoxOnSave: boolean;
   shouldDarkenOutsideBoundingBox: boolean;
+  shouldFitImageSize: boolean;
   shouldInvertBrushSizeScrollDirection: boolean;
   shouldLockBoundingBox: boolean;
   shouldPreserveMaskedArea: boolean;

invokeai/frontend/web/src/features/gallery/components/ImageMetadataViewer/ImageMetadataActions.tsx

@@ -33,6 +33,7 @@ const ImageMetadataActions = (props: Props) => {
       <MetadataItem metadata={metadata} handlers={handlers.scheduler} />
       <MetadataItem metadata={metadata} handlers={handlers.cfgScale} />
       <MetadataItem metadata={metadata} handlers={handlers.cfgRescaleMultiplier} />
+      <MetadataItem metadata={metadata} handlers={handlers.initialImage} />
       <MetadataItem metadata={metadata} handlers={handlers.strength} />
       <MetadataItem metadata={metadata} handlers={handlers.hrfEnabled} />
       <MetadataItem metadata={metadata} handlers={handlers.hrfMethod} />

invokeai/frontend/web/src/features/metadata/util/handlers.ts

@@ -189,6 +189,12 @@ export const handlers = {
     recaller: recallers.cfgScale,
   }),
   height: buildHandlers({ getLabel: () => t('metadata.height'), parser: parsers.height, recaller: recallers.height }),
+  initialImage: buildHandlers({
+    getLabel: () => t('metadata.initImage'),
+    parser: parsers.initialImage,
+    recaller: recallers.initialImage,
+    renderValue: async (imageDTO) => imageDTO.image_name,
+  }),
   negativePrompt: buildHandlers({
     getLabel: () => t('metadata.negativePrompt'),
     parser: parsers.negativePrompt,
@@ -405,6 +411,6 @@ export const parseAndRecallAllMetadata = async (metadata: unknown, skip: (keyof
       })
   );
   if (results.some((result) => result.status === 'fulfilled')) {
-    parameterSetToast(t('toast.parametersSet'));
+    parameterSetToast(t('toast.parameters'));
   }
 };

invokeai/frontend/web/src/features/metadata/util/parsers.ts

@@ -1,3 +1,4 @@
+import { getStore } from 'app/store/nanostores/store';
 import {
   initialControlNet,
   initialIPAdapter,
@@ -57,6 +58,8 @@ import {
   isParameterWidth,
 } from 'features/parameters/types/parameterSchemas';
 import { get, isArray, isString } from 'lodash-es';
+import { imagesApi } from 'services/api/endpoints/images';
+import type { ImageDTO } from 'services/api/types';
 import {
   isControlNetModelConfig,
   isIPAdapterModelConfig,
@@ -135,6 +138,14 @@ const parseCFGRescaleMultiplier: MetadataParseFunc<ParameterCFGRescaleMultiplier
 const parseScheduler: MetadataParseFunc<ParameterScheduler> = (metadata) =>
   getProperty(metadata, 'scheduler', isParameterScheduler);
 
+const parseInitialImage: MetadataParseFunc<ImageDTO> = async (metadata) => {
+  const imageName = await getProperty(metadata, 'init_image', isString);
+  const imageDTORequest = getStore().dispatch(imagesApi.endpoints.getImageDTO.initiate(imageName));
+  const imageDTO = await imageDTORequest.unwrap();
+  imageDTORequest.unsubscribe();
+  return imageDTO;
+};
+
 const parseWidth: MetadataParseFunc<ParameterWidth> = (metadata) => getProperty(metadata, 'width', isParameterWidth);
 
 const parseHeight: MetadataParseFunc<ParameterHeight> = (metadata) =>
@@ -402,6 +413,7 @@ export const parsers = {
   cfgScale: parseCFGScale,
   cfgRescaleMultiplier: parseCFGRescaleMultiplier,
   scheduler: parseScheduler,
+  initialImage: parseInitialImage,
   width: parseWidth,
   height: parseHeight,
   steps: parseSteps,

invokeai/frontend/web/src/features/metadata/util/recallers.ts

@@ -17,6 +17,7 @@ import type {
 import { modelSelected } from 'features/parameters/store/actions';
 import {
   heightRecalled,
+  initialImageChanged,
   setCfgRescaleMultiplier,
   setCfgScale,
   setImg2imgStrength,
@@ -61,6 +62,7 @@ import {
   setRefinerStart,
   setRefinerSteps,
 } from 'features/sdxl/store/sdxlSlice';
+import type { ImageDTO } from 'services/api/types';
 
 const recallPositivePrompt: MetadataRecallFunc<ParameterPositivePrompt> = (positivePrompt) => {
   getStore().dispatch(setPositivePrompt(positivePrompt));
@@ -94,6 +96,10 @@ const recallScheduler: MetadataRecallFunc<ParameterScheduler> = (scheduler) => {
   getStore().dispatch(setScheduler(scheduler));
 };
 
+const recallInitialImage: MetadataRecallFunc<ImageDTO> = async (imageDTO) => {
+  getStore().dispatch(initialImageChanged(imageDTO));
+};
+
 const recallWidth: MetadataRecallFunc<ParameterWidth> = (width) => {
   getStore().dispatch(widthRecalled(width));
 };
@@ -235,6 +241,7 @@ export const recallers = {
   cfgScale: recallCFGScale,
   cfgRescaleMultiplier: recallCFGRescaleMultiplier,
   scheduler: recallScheduler,
+  initialImage: recallInitialImage,
   width: recallWidth,
   height: recallHeight,
   steps: recallSteps,

invokeai/frontend/web/src/features/ui/store/uiSlice.ts

@@ -1,6 +1,7 @@
 import type { PayloadAction } from '@reduxjs/toolkit';
 import { createSlice } from '@reduxjs/toolkit';
 import type { PersistConfig, RootState } from 'app/store/store';
+import { workflowLoadRequested } from 'features/nodes/store/actions';
 import { initialImageChanged } from 'features/parameters/store/generationSlice';
 
 import type { InvokeTabName } from './tabMap';
@@ -45,6 +46,9 @@ export const uiSlice = createSlice({
     builder.addCase(initialImageChanged, (state) => {
       state.activeTab = 'img2img';
     });
+    builder.addCase(workflowLoadRequested, (state) => {
+      state.activeTab = 'nodes';
+    });
   },
 });
 

invokeai/invocation_api/__init__.py

@@ -27,6 +27,7 @@ from invokeai.app.invocations.fields import (
     OutputField,
     UIComponent,
     UIType,
+    WithBoard,
     WithMetadata,
     WithWorkflow,
 )
@@ -105,6 +106,7 @@ __all__ = [
     "OutputField",
     "UIComponent",
     "UIType",
+    "WithBoard",
     "WithMetadata",
     "WithWorkflow",
     # invokeai.app.invocations.latent

invokeai/version/invokeai_version.py

@@ -1 +1 @@
-__version__ = "4.0.2"
+__version__ = "4.0.4"