install, nodes, ui: restore ad-hoc upscaling

invokeai/app/invocations/image.py

@@ -518,8 +518,8 @@ class ImageScaleInvocation(BaseInvocation, PILInvocationConfig):
     type: Literal["img_scale"] = "img_scale"
 
     # Inputs
-    image:       Optional[ImageField] = Field(default=None, description="The image to scale")
-    scale_factor:                  float = Field(gt=0, description="The factor by which to scale the image")
+    image:          Optional[ImageField] = Field(default=None, description="The image to scale")
+    scale_factor:        Optional[float] = Field(default=2.0, gt=0, description="The factor by which to scale the image")
     resample_mode:  PIL_RESAMPLING_MODES = Field(default="bicubic", description="The resampling mode")
     # fmt: on
 

invokeai/app/invocations/upscale.py

@@ -1,6 +1,6 @@
 # Copyright (c) 2022 Kyle Schouviller (https://github.com/kyle0654) & the InvokeAI Team
-from pathlib import Path, PosixPath
-from typing import Literal, Union, cast
+from pathlib import Path
+from typing import Literal, Union
 
 import cv2 as cv
 import numpy as np
@@ -16,19 +16,20 @@
 
 # TODO: Populate this from disk?
 # TODO: Use model manager to load?
-REALESRGAN_MODELS = Literal[
+ESRGAN_MODELS = Literal[
     "RealESRGAN_x4plus.pth",
     "RealESRGAN_x4plus_anime_6B.pth",
     "ESRGAN_SRx4_DF2KOST_official-ff704c30.pth",
+    "RealESRGAN_x2plus.pth",
 ]
 
 
-class RealESRGANInvocation(BaseInvocation):
+class ESRGANInvocation(BaseInvocation):
     """Upscales an image using RealESRGAN."""
 
-    type: Literal["realesrgan"] = "realesrgan"
+    type: Literal["esrgan"] = "esrgan"
     image: Union[ImageField, None] = Field(default=None, description="The input image")
-    model_name: REALESRGAN_MODELS = Field(
+    model_name: ESRGAN_MODELS = Field(
         default="RealESRGAN_x4plus.pth", description="The Real-ESRGAN model to use"
     )
 
@@ -73,19 +74,17 @@ def invoke(self, context: InvocationContext) -> ImageOutput:
                 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
+        elif self.model_name in ["RealESRGAN_x2plus.pth"]:
+            # x2 RRDBNet model
+            rrdbnet_model = RRDBNet(
+                num_in_ch=3,
+                num_out_ch=3,
+                num_feat=64,
+                num_block=23,
+                num_grow_ch=32,
+                scale=2,
+            )
+            netscale = 2
         else:
             msg = f"Invalid RealESRGAN model: {self.model_name}"
             context.services.logger.error(msg)

invokeai/backend/install/invokeai_configure.py

@@ -222,7 +222,7 @@ def download_conversion_models():
 
 # ---------------------------------------------
 def download_realesrgan():
-    logger.info("Installing RealESRGAN models...")
+    logger.info("Installing ESRGAN Upscaling models...")
     URLs = [
         dict(
             url = "https://github.com/xinntao/Real-ESRGAN/releases/download/v0.1.0/RealESRGAN_x4plus.pth",
@@ -239,6 +239,11 @@ def download_realesrgan():
             dest= "core/upscaling/realesrgan/ESRGAN_SRx4_DF2KOST_official-ff704c30.pth",
             description = "ESRGAN_SRx4_DF2KOST_official.pth",
         ),
+        dict(
+            url= "https://github.com/xinntao/Real-ESRGAN/releases/download/v0.2.1/RealESRGAN_x2plus.pth",
+            dest= "core/upscaling/realesrgan/RealESRGAN_x2plus.pth",
+            description = "RealESRGAN_x2plus.pth",
+        ),
     ]
     for model in URLs:
         download_with_progress_bar(model['url'], config.models_path / model['dest'], model['description'])

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

@@ -59,15 +59,8 @@ export const SCHEDULER_LABEL_MAP: Record<SchedulerParam, string> = {
 
 export type Scheduler = (typeof SCHEDULER_NAMES)[number];
 
-// Valid upscaling levels
-export const UPSCALING_LEVELS: Array<{ label: string; value: string }> = [
-  { label: '2x', value: '2' },
-  { label: '4x', value: '4' },
-];
 export const NUMPY_RAND_MIN = 0;
 
 export const NUMPY_RAND_MAX = 2147483647;
 
-export const FACETOOL_TYPES = ['gfpgan', 'codeformer'] as const;
-
 export const NODE_MIN_WIDTH = 250;

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

@@ -90,6 +90,7 @@ import { addUserInvokedNodesListener } from './listeners/userInvokedNodes';
 import { addUserInvokedTextToImageListener } from './listeners/userInvokedTextToImage';
 import { addModelLoadStartedEventListener } from './listeners/socketio/socketModelLoadStarted';
 import { addModelLoadCompletedEventListener } from './listeners/socketio/socketModelLoadCompleted';
+import { addUpscaleRequestedListener } from './listeners/upscaleRequested';
 
 export const listenerMiddleware = createListenerMiddleware();
 
@@ -228,3 +229,5 @@ addModelSelectedListener();
 addAppStartedListener();
 addModelsLoadedListener();
 addAppConfigReceivedListener();
+
+addUpscaleRequestedListener();

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

@@ -1,7 +1,7 @@
 import { log } from 'app/logging/useLogger';
-import { startAppListening } from '..';
-import { sessionCreated } from 'services/api/thunks/session';
 import { serializeError } from 'serialize-error';
+import { sessionCreated } from 'services/api/thunks/session';
+import { startAppListening } from '..';
 
 const moduleLog = log.child({ namespace: 'session' });
 

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

@@ -0,0 +1,37 @@
+import { createAction } from '@reduxjs/toolkit';
+import { log } from 'app/logging/useLogger';
+import { buildAdHocUpscaleGraph } from 'features/nodes/util/graphBuilders/buildAdHocUpscaleGraph';
+import { sessionReadyToInvoke } from 'features/system/store/actions';
+import { sessionCreated } from 'services/api/thunks/session';
+import { startAppListening } from '..';
+
+const moduleLog = log.child({ namespace: 'upscale' });
+
+export const upscaleRequested = createAction<{ image_name: string }>(
+  `upscale/upscaleRequested`
+);
+
+export const addUpscaleRequestedListener = () => {
+  startAppListening({
+    actionCreator: upscaleRequested,
+    effect: async (
+      action,
+      { dispatch, getState, take, unsubscribe, subscribe }
+    ) => {
+      const { image_name } = action.payload;
+      const { esrganModelName } = getState().postprocessing;
+
+      const graph = buildAdHocUpscaleGraph({
+        image_name,
+        esrganModelName,
+      });
+
+      // Create a session to run the graph & wait til it's ready to invoke
+      dispatch(sessionCreated({ graph }));
+
+      await take(sessionCreated.fulfilled.match);
+
+      dispatch(sessionReadyToInvoke());
+    },
+  });
+};

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

@@ -11,7 +11,7 @@ interface ItemProps extends React.ComponentPropsWithoutRef<'div'> {
 
 const IAIMantineSelectItemWithTooltip = forwardRef<HTMLDivElement, ItemProps>(
   ({ label, tooltip, description, disabled, ...others }: ItemProps, ref) => (
-    <Tooltip label={tooltip} placement="top" hasArrow>
+    <Tooltip label={tooltip} placement="top" hasArrow openDelay={500}>
       <Box ref={ref} {...others}>
         <Box>
           <Text>{label}</Text>