Merge remote-tracking branch 'origin/main' into release/3.4

Author: Millu

docs/nodes/communityNodes.md

@@ -32,6 +32,7 @@ To use a community workflow, download the the `.json` node graph file and load i
     + [Size Stepper Nodes](#size-stepper-nodes)
     + [Text font to Image](#text-font-to-image)
     + [Thresholding](#thresholding)
+    + [Unsharp Mask](#unsharp-mask)
     + [XY Image to Grid and Images to Grids nodes](#xy-image-to-grid-and-images-to-grids-nodes)
 - [Example Node Template](#example-node-template)
 - [Disclaimer](#disclaimer)
@@ -316,6 +317,13 @@ Highlights/Midtones/Shadows (with LUT blur enabled):
 <img src="https://github.com/invoke-ai/InvokeAI/assets/34005131/0a440e43-697f-4d17-82ee-f287467df0a5" width="300" />
 <img src="https://github.com/invoke-ai/InvokeAI/assets/34005131/0701fd0f-2ca7-4fe2-8613-2b52547bafce" width="300" />
 
+--------------------------------
+### Unsharp Mask
+
+**Description:** Applies an unsharp mask filter to an image, preserving its alpha channel in the process.
+
+**Node Link:** https://github.com/JPPhoto/unsharp-mask-node
+
 --------------------------------
 ### XY Image to Grid and Images to Grids nodes
 

invokeai/app/invocations/image.py

@@ -8,7 +8,7 @@
 from PIL import Image, ImageChops, ImageFilter, ImageOps
 
 from invokeai.app.invocations.primitives import BoardField, ColorField, ImageField, ImageOutput
-from invokeai.app.services.image_records.image_records_common import ImageCategory, ResourceOrigin
+from invokeai.app.services.image_records.image_records_common import ImageCategory, ImageRecordChanges, ResourceOrigin
 from invokeai.app.shared.fields import FieldDescriptions
 from invokeai.backend.image_util.invisible_watermark import InvisibleWatermark
 from invokeai.backend.image_util.safety_checker import SafetyChecker
@@ -1017,3 +1017,35 @@ def invoke(self, context: InvocationContext) -> ImageOutput:
             width=image_dto.width,
             height=image_dto.height,
         )
+
+
+@invocation(
+    "linear_ui_output",
+    title="Linear UI Image Output",
+    tags=["primitives", "image"],
+    category="primitives",
+    version="1.0.1",
+    use_cache=False,
+)
+class LinearUIOutputInvocation(BaseInvocation, WithWorkflow, WithMetadata):
+    """Handles Linear UI Image Outputting tasks."""
+
+    image: ImageField = InputField(description=FieldDescriptions.image)
+    board: Optional[BoardField] = InputField(default=None, description=FieldDescriptions.board, input=Input.Direct)
+
+    def invoke(self, context: InvocationContext) -> ImageOutput:
+        image_dto = context.services.images.get_dto(self.image.image_name)
+
+        if self.board:
+            context.services.board_images.add_image_to_board(self.board.board_id, self.image.image_name)
+
+        if image_dto.is_intermediate != self.is_intermediate:
+            context.services.images.update(
+                self.image.image_name, changes=ImageRecordChanges(is_intermediate=self.is_intermediate)
+            )
+
+        return ImageOutput(
+            image=ImageField(image_name=self.image.image_name),
+            width=image_dto.width,
+            height=image_dto.height,
+        )

invokeai/app/invocations/metadata.py

@@ -112,7 +112,7 @@ def invoke(self, context: InvocationContext) -> MetadataOutput:
 ]
 
 
-@invocation("core_metadata", title="Core Metadata", tags=["metadata"], category="metadata", version="1.0.0")
+@invocation("core_metadata", title="Core Metadata", tags=["metadata"], category="metadata", version="1.0.1")
 class CoreMetadataInvocation(BaseInvocation):
     """Collects core generation metadata into a MetadataField"""
 
@@ -160,7 +160,7 @@ class CoreMetadataInvocation(BaseInvocation):
     )
 
     # High resolution fix metadata.
-    hrf_enabled: Optional[float] = InputField(
+    hrf_enabled: Optional[bool] = InputField(
         default=None,
         description="Whether or not high resolution fix was enabled.",
     )

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

@@ -1222,7 +1222,8 @@
         "seamless": "无缝",
         "fit": "图生图匹配",
         "recallParameters": "召回参数",
-        "noRecallParameters": "未找到要召回的参数"
+        "noRecallParameters": "未找到要召回的参数",
+        "vae": "VAE"
     },
     "models": {
         "noMatchingModels": "无相匹配的模型",
@@ -1501,5 +1502,18 @@
         "clear": "清除",
         "maxCacheSize": "最大缓存大小",
         "cacheSize": "缓存大小"
+    },
+    "hrf": {
+        "enableHrf": "启用高分辨率修复",
+        "upscaleMethod": "放大方法",
+        "enableHrfTooltip": "使用较低的分辨率进行初始生成，放大到基础分辨率后进行图生图。",
+        "metadata": {
+            "strength": "高分辨率修复强度",
+            "enabled": "高分辨率修复已启用",
+            "method": "高分辨率修复方法"
+        },
+        "hrf": "高分辨率修复",
+        "hrfStrength": "高分辨率修复强度",
+        "strengthTooltip": "值越低细节越少，但可以减少部分潜在的伪影。"
     }
 }

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

@@ -8,7 +8,6 @@ import {
   selectControlAdapterById,
 } from 'features/controlAdapters/store/controlAdaptersSlice';
 import { isControlNetOrT2IAdapter } from 'features/controlAdapters/store/types';
-import { SAVE_IMAGE } from 'features/nodes/util/graphBuilders/constants';
 import { addToast } from 'features/system/store/systemSlice';
 import { t } from 'i18next';
 import { imagesApi } from 'services/api/endpoints/images';
@@ -38,6 +37,7 @@ export const addControlNetImageProcessedListener = () => {
       // ControlNet one-off procressing graph is just the processor node, no edges.
       // Also we need to grab the image.
 
+      const nodeId = ca.processorNode.id;
       const enqueueBatchArg: BatchConfig = {
         prepend: true,
         batch: {
@@ -46,27 +46,10 @@ export const addControlNetImageProcessedListener = () => {
               [ca.processorNode.id]: {
                 ...ca.processorNode,
                 is_intermediate: true,
-                image: { image_name: ca.controlImage },
-              },
-              [SAVE_IMAGE]: {
-                id: SAVE_IMAGE,
-                type: 'save_image',
-                is_intermediate: true,
                 use_cache: false,
+                image: { image_name: ca.controlImage },
               },
             },
-            edges: [
-              {
-                source: {
-                  node_id: ca.processorNode.id,
-                  field: 'image',
-                },
-                destination: {
-                  node_id: SAVE_IMAGE,
-                  field: 'image',
-                },
-              },
-            ],
           },
           runs: 1,
         },
@@ -90,7 +73,7 @@ export const addControlNetImageProcessedListener = () => {
             socketInvocationComplete.match(action) &&
             action.payload.data.queue_batch_id ===
               enqueueResult.batch.batch_id &&
-            action.payload.data.source_node_id === SAVE_IMAGE
+            action.payload.data.source_node_id === nodeId
         );
 
         // We still have to check the output type

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

@@ -7,7 +7,10 @@ import {
   imageSelected,
 } from 'features/gallery/store/gallerySlice';
 import { IMAGE_CATEGORIES } from 'features/gallery/store/types';
-import { CANVAS_OUTPUT } from 'features/nodes/util/graphBuilders/constants';
+import {
+  LINEAR_UI_OUTPUT,
+  nodeIDDenyList,
+} from 'features/nodes/util/graphBuilders/constants';
 import { boardsApi } from 'services/api/endpoints/boards';
 import { imagesApi } from 'services/api/endpoints/images';
 import { isImageOutput } from 'services/api/guards';
@@ -19,7 +22,7 @@ import {
 import { startAppListening } from '../..';
 
 // These nodes output an image, but do not actually *save* an image, so we don't want to handle the gallery logic on them
-const nodeDenylist = ['load_image', 'image'];
+const nodeTypeDenylist = ['load_image', 'image'];
 
 export const addInvocationCompleteEventListener = () => {
   startAppListening({
@@ -32,22 +35,31 @@ export const addInvocationCompleteEventListener = () => {
         `Invocation complete (${action.payload.data.node.type})`
       );
 
-      const { result, node, queue_batch_id } = data;
+      const { result, node, queue_batch_id, source_node_id } = data;
 
       // This complete event has an associated image output
-      if (isImageOutput(result) && !nodeDenylist.includes(node.type)) {
+      if (
+        isImageOutput(result) &&
+        !nodeTypeDenylist.includes(node.type) &&
+        !nodeIDDenyList.includes(source_node_id)
+      ) {
         const { image_name } = result.image;
         const { canvas, gallery } = getState();
 
         // This populates the `getImageDTO` cache
-        const imageDTO = await dispatch(
-          imagesApi.endpoints.getImageDTO.initiate(image_name)
-        ).unwrap();
+        const imageDTORequest = dispatch(
+          imagesApi.endpoints.getImageDTO.initiate(image_name, {
+            forceRefetch: true,
+          })
+        );
+
+        const imageDTO = await imageDTORequest.unwrap();
+        imageDTORequest.unsubscribe();
 
         // Add canvas images to the staging area
         if (
           canvas.batchIds.includes(queue_batch_id) &&
-          [CANVAS_OUTPUT].includes(data.source_node_id)
+          [LINEAR_UI_OUTPUT].includes(data.source_node_id)
         ) {
           dispatch(addImageToStagingArea(imageDTO));
         }

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

@@ -157,6 +157,8 @@ const ImageMetadataActions = (props: Props) => {
     return null;
   }
 
+  console.log(metadata);
+
   return (
     <>
       {metadata.created_by && (

invokeai/frontend/web/src/features/nodes/util/graphBuilders/addHrfToGraph.ts

@@ -23,7 +23,7 @@ import {
   RESIZE_HRF,
   VAE_LOADER,
 } from './constants';
-import { upsertMetadata } from './metadata';
+import { setMetadataReceivingNode, upsertMetadata } from './metadata';
 
 // Copy certain connections from previous DENOISE_LATENTS to new DENOISE_LATENTS_HRF.
 function copyConnectionsToDenoiseLatentsHrf(graph: NonNullableGraph): void {
@@ -369,4 +369,5 @@ export const addHrfToGraph = (
     hrf_enabled: hrfEnabled,
     hrf_method: hrfMethod,
   });
+  setMetadataReceivingNode(graph, LATENTS_TO_IMAGE_HRF_HR);
 };

invokeai/frontend/web/src/features/nodes/util/graphBuilders/addSaveImageNode.ts renamed to invokeai/frontend/web/src/features/nodes/util/graphBuilders/addLinearUIOutputNode.ts

@@ -1,20 +1,20 @@
 import { RootState } from 'app/store/store';
 import { NonNullableGraph } from 'features/nodes/types/types';
 import { activeTabNameSelector } from 'features/ui/store/uiSelectors';
-import { SaveImageInvocation } from 'services/api/types';
+import { LinearUIOutputInvocation } from 'services/api/types';
 import {
   CANVAS_OUTPUT,
   LATENTS_TO_IMAGE,
   LATENTS_TO_IMAGE_HRF_HR,
+  LINEAR_UI_OUTPUT,
   NSFW_CHECKER,
-  SAVE_IMAGE,
   WATERMARKER,
 } from './constants';
 
 /**
  * Set the `use_cache` field on the linear/canvas graph's final image output node to False.
  */
-export const addSaveImageNode = (
+export const addLinearUIOutputNode = (
   state: RootState,
   graph: NonNullableGraph
 ): void => {
@@ -23,18 +23,18 @@ export const addSaveImageNode = (
     activeTabName === 'unifiedCanvas' ? !state.canvas.shouldAutoSave : false;
   const { autoAddBoardId } = state.gallery;
 
-  const saveImageNode: SaveImageInvocation = {
-    id: SAVE_IMAGE,
-    type: 'save_image',
+  const linearUIOutputNode: LinearUIOutputInvocation = {
+    id: LINEAR_UI_OUTPUT,
+    type: 'linear_ui_output',
     is_intermediate,
     use_cache: false,
     board: autoAddBoardId === 'none' ? undefined : { board_id: autoAddBoardId },
   };
 
-  graph.nodes[SAVE_IMAGE] = saveImageNode;
+  graph.nodes[LINEAR_UI_OUTPUT] = linearUIOutputNode;
 
   const destination = {
-    node_id: SAVE_IMAGE,
+    node_id: LINEAR_UI_OUTPUT,
     field: 'image',
   };
 

invokeai/frontend/web/src/features/nodes/util/graphBuilders/buildAdHocUpscaleGraph.ts

@@ -4,9 +4,9 @@ import { ESRGANModelName } from 'features/parameters/store/postprocessingSlice';
 import {
   ESRGANInvocation,
   Graph,
-  SaveImageInvocation,
+  LinearUIOutputInvocation,
 } from 'services/api/types';
-import { REALESRGAN as ESRGAN, SAVE_IMAGE } from './constants';
+import { ESRGAN, LINEAR_UI_OUTPUT } from './constants';
 import { addCoreMetadataNode, upsertMetadata } from './metadata';
 
 type Arg = {
@@ -28,9 +28,9 @@ export const buildAdHocUpscaleGraph = ({
     is_intermediate: true,
   };
 
-  const saveImageNode: SaveImageInvocation = {
-    id: SAVE_IMAGE,
-    type: 'save_image',
+  const linearUIOutputNode: LinearUIOutputInvocation = {
+    id: LINEAR_UI_OUTPUT,
+    type: 'linear_ui_output',
     use_cache: false,
     is_intermediate: false,
     board: autoAddBoardId === 'none' ? undefined : { board_id: autoAddBoardId },
@@ -40,7 +40,7 @@ export const buildAdHocUpscaleGraph = ({
     id: `adhoc-esrgan-graph`,
     nodes: {
       [ESRGAN]: realesrganNode,
-      [SAVE_IMAGE]: saveImageNode,
+      [LINEAR_UI_OUTPUT]: linearUIOutputNode,
     },
     edges: [
       {
@@ -49,14 +49,14 @@ export const buildAdHocUpscaleGraph = ({
           field: 'image',
         },
         destination: {
-          node_id: SAVE_IMAGE,
+          node_id: LINEAR_UI_OUTPUT,
           field: 'image',
         },
       },
     ],
   };
 
-  addCoreMetadataNode(graph, {});
+  addCoreMetadataNode(graph, {}, ESRGAN);
   upsertMetadata(graph, {
     esrgan_model: esrganModelName,
   });