merge with main

.github/workflows/mkdocs-material.yml

@@ -2,8 +2,7 @@ name: mkdocs-material
 on:
   push:
     branches:
-      - 'main'
+      - 'refs/heads/v2.3'
-      - 'development'
 
 permissions:
     contents: write
@@ -12,6 +11,10 @@ jobs:
   mkdocs-material:
     if: github.event.pull_request.draft == false
     runs-on: ubuntu-latest
+    env:
+      REPO_URL: '${{ github.server_url }}/${{ github.repository }}'
+      REPO_NAME: '${{ github.repository }}'
+      SITE_URL: 'https://${{ github.repository_owner }}.github.io/InvokeAI'
     steps:
       - name: checkout sources
         uses: actions/checkout@v3
@@ -22,11 +25,15 @@ jobs:
         uses: actions/setup-python@v4
         with:
           python-version: '3.10'
+          cache: pip
+          cache-dependency-path: pyproject.toml
 
       - name: install requirements
+        env:
+          PIP_USE_PEP517: 1
         run: |
           python -m \
-            pip install -r docs/requirements-mkdocs.txt
+            pip install ".[docs]"
 
       - name: confirm buildability
         run: |

installer/lib/installer.py

@@ -247,8 +247,8 @@ class InvokeAiInstance:
             pip[
                 "install",
                 "--require-virtualenv",
-                "torch",
+                "torch~=2.0.0",
-                "torchvision",
+                "torchvision>=0.14.1",
                 "--force-reinstall",
                 "--find-links" if find_links is not None else None,
                 find_links,

invokeai/app/api/routers/images.py

@@ -83,7 +83,7 @@ async def get_thumbnail(
     status_code=201,
 )
 async def upload_image(
-    file: UploadFile, request: Request, response: Response
+    file: UploadFile, image_type: ImageType, request: Request, response: Response
 ) -> ImageResponse:
     if not file.content_type.startswith("image"):
         raise HTTPException(status_code=415, detail="Not an image")
@@ -99,21 +99,21 @@ async def upload_image(
     filename = f"{uuid.uuid4()}_{str(int(datetime.now(timezone.utc).timestamp()))}.png"
 
     saved_image = ApiDependencies.invoker.services.images.save(
-        ImageType.UPLOAD, filename, img
+        image_type, filename, img
     )
 
     invokeai_metadata = ApiDependencies.invoker.services.metadata.get_metadata(img)
 
     image_url = ApiDependencies.invoker.services.images.get_uri(
-        ImageType.UPLOAD, saved_image.image_name
+        image_type, saved_image.image_name
     )
 
     thumbnail_url = ApiDependencies.invoker.services.images.get_uri(
-        ImageType.UPLOAD, saved_image.image_name, True
+        image_type, saved_image.image_name, True
     )
 
     res = ImageResponse(
-        image_type=ImageType.UPLOAD,
+        image_type=image_type,
         image_name=saved_image.image_name,
         image_url=image_url,
         thumbnail_url=thumbnail_url,

invokeai/app/api_app.py

@@ -122,7 +122,6 @@ app.openapi = custom_openapi
 # Override API doc favicons
 app.mount("/static", StaticFiles(directory="static/dream_web"), name="static")
 
-
 @app.get("/docs", include_in_schema=False)
 def overridden_swagger():
     return get_swagger_ui_html(
@@ -140,6 +139,8 @@ def overridden_redoc():
         redoc_favicon_url="/static/favicon.ico",
     )
 
+# Must mount *after* the other routes else it borks em
+app.mount("/", StaticFiles(directory="invokeai/frontend/web/dist", html=True), name="ui")
 
 def invoke_api():
     global web_config

invokeai/app/invocations/collections.py

@@ -3,12 +3,12 @@
 from typing import Literal, Optional
 
 import numpy as np
-import numpy.random
 from pydantic import Field
 
+from invokeai.app.util.misc import SEED_MAX, get_random_seed
+
 from .baseinvocation import (
     BaseInvocation,
-    InvocationConfig,
     InvocationContext,
     BaseInvocationOutput,
 )
@@ -50,11 +50,11 @@ class RandomRangeInvocation(BaseInvocation):
         default=np.iinfo(np.int32).max, description="The exclusive high value"
     )
     size: int = Field(default=1, description="The number of values to generate")
-    seed: Optional[int] = Field(
+    seed: int = Field(
         ge=0,
-        le=np.iinfo(np.int32).max,
+        le=SEED_MAX,
-        description="The seed for the RNG",
+        description="The seed for the RNG (omit for random)",
-        default_factory=lambda: numpy.random.randint(0, np.iinfo(np.int32).max),
+        default_factory=get_random_seed,
     )
 
     def invoke(self, context: InvocationContext) -> IntCollectionOutput:

invokeai/app/invocations/generate.py

@@ -1,15 +1,17 @@
 # Copyright (c) 2022 Kyle Schouviller (https://github.com/kyle0654)
 
 from functools import partial
-from typing import Literal, Optional, Union
+from typing import Literal, Optional, Union, get_args
 
 import numpy as np
 from torch import Tensor
 
 from pydantic import BaseModel, Field
 
-from invokeai.app.models.image import ImageField, ImageType
+from invokeai.app.models.image import ColorField, ImageField, ImageType
 from invokeai.app.invocations.util.choose_model import choose_model
+from invokeai.app.util.misc import SEED_MAX, get_random_seed
+from invokeai.backend.generator.inpaint import infill_methods
 from .baseinvocation import BaseInvocation, InvocationContext, InvocationConfig
 from .image import ImageOutput, build_image_output
 from ...backend.generator import Txt2Img, Img2Img, Inpaint, InvokeAIGenerator
@@ -17,7 +19,8 @@ from ...backend.stable_diffusion import PipelineIntermediateState
 from ..util.step_callback import stable_diffusion_step_callback
 
 SAMPLER_NAME_VALUES = Literal[tuple(InvokeAIGenerator.schedulers())]
-
+INFILL_METHODS = Literal[tuple(infill_methods())]
+DEFAULT_INFILL_METHOD = 'patchmatch' if 'patchmatch' in get_args(INFILL_METHODS) else 'tile'
 
 class SDImageInvocation(BaseModel):
     """Helper class to provide all Stable Diffusion raster image invocations with additional config"""
@@ -44,15 +47,13 @@ class TextToImageInvocation(BaseInvocation, SDImageInvocation):
     # TODO: consider making prompt optional to enable providing prompt through a link
     # fmt: off
     prompt: Optional[str] = Field(description="The prompt to generate an image from")
-    seed:        int = Field(default=-1,ge=-1, le=np.iinfo(np.uint32).max, description="The seed to use (-1 for a random seed)", )
+    seed:        int = Field(ge=0, le=SEED_MAX, description="The seed to use (omit for random)", default_factory=get_random_seed)
-    steps:       int = Field(default=10, gt=0, description="The number of steps to use to generate the image")
+    steps:       int = Field(default=30, gt=0, description="The number of steps to use to generate the image")
     width:       int = Field(default=512, multiple_of=8, gt=0, description="The width of the resulting image", )
     height:      int = Field(default=512, multiple_of=8, gt=0, description="The height of the resulting image", )
-    cfg_scale: float = Field(default=7.5, gt=0, description="The Classifier-Free Guidance, higher values may result in a result closer to the prompt", )
+    cfg_scale: float = Field(default=7.5, ge=1, description="The Classifier-Free Guidance, higher values may result in a result closer to the prompt", )
-    scheduler: SAMPLER_NAME_VALUES = Field(default="k_lms", description="The scheduler to use" )
+    scheduler: SAMPLER_NAME_VALUES = Field(default="lms", description="The scheduler to use" )
-    seamless:   bool = Field(default=False, description="Whether or not to generate an image that can tile without seams", )
     model:       str = Field(default="", description="The model to use (currently ignored)")
-    progress_images: bool = Field(default=False, description="Whether or not to produce progress images during generation",  )
     # fmt: on
 
     # TODO: pass this an emitter method or something? or a session for dispatching?
@@ -148,7 +149,6 @@ class ImageToImageInvocation(TextToImageInvocation):
                 self.image.image_type, self.image.image_name
             )
         )
-        mask = None
 
         if self.fit:
             image = image.resize((self.width, self.height))
@@ -165,7 +165,6 @@ class ImageToImageInvocation(TextToImageInvocation):
         outputs = Img2Img(model).generate(
             prompt=self.prompt,
             init_image=image,
-            init_mask=mask,
             step_callback=partial(self.dispatch_progress, context, source_node_id),
             **self.dict(
                 exclude={"prompt", "image", "mask"}
@@ -197,7 +196,6 @@ class ImageToImageInvocation(TextToImageInvocation):
             image=result_image,
         )
 
-
 class InpaintInvocation(ImageToImageInvocation):
     """Generates an image using inpaint."""
 
@@ -205,6 +203,17 @@ class InpaintInvocation(ImageToImageInvocation):
 
     # Inputs
     mask: Union[ImageField, None] = Field(description="The mask")
+    seam_size: int = Field(default=96, ge=1, description="The seam inpaint size (px)")
+    seam_blur: int = Field(default=16, ge=0, description="The seam inpaint blur radius (px)")
+    seam_strength: float = Field(
+        default=0.75, gt=0, le=1, description="The seam inpaint strength"
+    )
+    seam_steps: int = Field(default=30, ge=1, description="The number of steps to use for seam inpaint")
+    tile_size: int = Field(default=32, ge=1, description="The tile infill method size (px)")
+    infill_method: INFILL_METHODS = Field(default=DEFAULT_INFILL_METHOD, description="The method used to infill empty regions (px)")
+    inpaint_width:       Optional[int] = Field(default=None, multiple_of=8, gt=0, description="The width of the inpaint region (px)")
+    inpaint_height:      Optional[int] = Field(default=None, multiple_of=8, gt=0, description="The height of the inpaint region (px)")
+    inpaint_fill: Optional[ColorField] = Field(default=ColorField(r=127, g=127, b=127, a=255), description="The solid infill method color")
     inpaint_replace: float = Field(
         default=0.0,
         ge=0.0,

invokeai/app/invocations/image.py

@@ -1,5 +1,6 @@
 # Copyright (c) 2022 Kyle Schouviller (https://github.com/kyle0654)
 
+import io
 from typing import Literal, Optional
 
 import numpy
@@ -32,14 +33,12 @@ class ImageOutput(BaseInvocationOutput):
     # fmt: off
     type: Literal["image"] = "image"
     image:      ImageField = Field(default=None, description="The output image")
-    width:   Optional[int] = Field(default=None, description="The width of the image in pixels")
+    width:             int = Field(description="The width of the image in pixels")
-    height:  Optional[int] = Field(default=None, description="The height of the image in pixels")
+    height:            int = Field(description="The height of the image in pixels")
     # fmt: on
 
     class Config:
-        schema_extra = {
+        schema_extra = {"required": ["type", "image", "width", "height"]}
-            "required": ["type", "image", "width", "height", "mode"]
-        }
 
 
 def build_image_output(
@@ -54,7 +53,6 @@ def build_image_output(
         image=image_field,
         width=image.width,
         height=image.height,
-        mode=image.mode,
     )
 
 

invokeai/app/invocations/infill.py

@@ -0,0 +1,233 @@
+# Copyright (c) 2022 Kyle Schouviller (https://github.com/kyle0654)
+
+from typing import Literal, Optional, Union, get_args
+
+import numpy as np
+import math
+from PIL import Image, ImageOps
+from pydantic import Field
+
+from invokeai.app.invocations.image import ImageOutput, build_image_output
+from invokeai.app.util.misc import SEED_MAX, get_random_seed
+from invokeai.backend.image_util.patchmatch import PatchMatch
+
+from ..models.image import ColorField, ImageField, ImageType
+from .baseinvocation import (
+    BaseInvocation,
+    InvocationContext,
+)
+
+
+def infill_methods() -> list[str]:
+    methods = [
+        "tile",
+        "solid",
+    ]
+    if PatchMatch.patchmatch_available():
+        methods.insert(0, "patchmatch")
+    return methods
+
+
+INFILL_METHODS = Literal[tuple(infill_methods())]
+DEFAULT_INFILL_METHOD = (
+    "patchmatch" if "patchmatch" in get_args(INFILL_METHODS) else "tile"
+)
+
+
+def infill_patchmatch(im: Image.Image) -> Image.Image:
+    if im.mode != "RGBA":
+        return im
+
+    # Skip patchmatch if patchmatch isn't available
+    if not PatchMatch.patchmatch_available():
+        return im
+
+    # Patchmatch (note, we may want to expose patch_size? Increasing it significantly impacts performance though)
+    im_patched_np = PatchMatch.inpaint(
+        im.convert("RGB"), ImageOps.invert(im.split()[-1]), patch_size=3
+    )
+    im_patched = Image.fromarray(im_patched_np, mode="RGB")
+    return im_patched
+
+
+def get_tile_images(image: np.ndarray, width=8, height=8):
+    _nrows, _ncols, depth = image.shape
+    _strides = image.strides
+
+    nrows, _m = divmod(_nrows, height)
+    ncols, _n = divmod(_ncols, width)
+    if _m != 0 or _n != 0:
+        return None
+
+    return np.lib.stride_tricks.as_strided(
+        np.ravel(image),
+        shape=(nrows, ncols, height, width, depth),
+        strides=(height * _strides[0], width * _strides[1], *_strides),
+        writeable=False,
+    )
+
+
+def tile_fill_missing(
+    im: Image.Image, tile_size: int = 16, seed: Union[int, None] = None
+) -> Image.Image:
+    # Only fill if there's an alpha layer
+    if im.mode != "RGBA":
+        return im
+
+    a = np.asarray(im, dtype=np.uint8)
+
+    tile_size_tuple = (tile_size, tile_size)
+
+    # Get the image as tiles of a specified size
+    tiles = get_tile_images(a, *tile_size_tuple).copy()
+
+    # Get the mask as tiles
+    tiles_mask = tiles[:, :, :, :, 3]
+
+    # Find any mask tiles with any fully transparent pixels (we will be replacing these later)
+    tmask_shape = tiles_mask.shape
+    tiles_mask = tiles_mask.reshape(math.prod(tiles_mask.shape))
+    n, ny = (math.prod(tmask_shape[0:2])), math.prod(tmask_shape[2:])
+    tiles_mask = tiles_mask > 0
+    tiles_mask = tiles_mask.reshape((n, ny)).all(axis=1)
+
+    # Get RGB tiles in single array and filter by the mask
+    tshape = tiles.shape
+    tiles_all = tiles.reshape((math.prod(tiles.shape[0:2]), *tiles.shape[2:]))
+    filtered_tiles = tiles_all[tiles_mask]
+
+    if len(filtered_tiles) == 0:
+        return im
+
+    # Find all invalid tiles and replace with a random valid tile
+    replace_count = (tiles_mask == False).sum()
+    rng = np.random.default_rng(seed=seed)
+    tiles_all[np.logical_not(tiles_mask)] = filtered_tiles[
+        rng.choice(filtered_tiles.shape[0], replace_count), :, :, :
+    ]
+
+    # Convert back to an image
+    tiles_all = tiles_all.reshape(tshape)
+    tiles_all = tiles_all.swapaxes(1, 2)
+    st = tiles_all.reshape(
+        (
+            math.prod(tiles_all.shape[0:2]),
+            math.prod(tiles_all.shape[2:4]),
+            tiles_all.shape[4],
+        )
+    )
+    si = Image.fromarray(st, mode="RGBA")
+
+    return si
+
+
+class InfillColorInvocation(BaseInvocation):
+    """Infills transparent areas of an image with a solid color"""
+
+    type: Literal["infill_rgba"] = "infill_rgba"
+    image: Optional[ImageField] = Field(default=None, description="The image to infill")
+    color: Optional[ColorField] = Field(
+        default=ColorField(r=127, g=127, b=127, a=255),
+        description="The color to use to infill",
+    )
+
+    def invoke(self, context: InvocationContext) -> ImageOutput:
+        image = context.services.images.get(
+            self.image.image_type, self.image.image_name
+        )
+
+        solid_bg = Image.new("RGBA", image.size, self.color.tuple())
+        infilled = Image.alpha_composite(solid_bg, image)
+
+        infilled.paste(image, (0, 0), image.split()[-1])
+
+        image_type = ImageType.RESULT
+        image_name = context.services.images.create_name(
+            context.graph_execution_state_id, self.id
+        )
+
+        metadata = context.services.metadata.build_metadata(
+            session_id=context.graph_execution_state_id, node=self
+        )
+
+        context.services.images.save(image_type, image_name, infilled, metadata)
+        return build_image_output(
+            image_type=image_type,
+            image_name=image_name,
+            image=image,
+        )
+
+
+class InfillTileInvocation(BaseInvocation):
+    """Infills transparent areas of an image with tiles of the image"""
+
+    type: Literal["infill_tile"] = "infill_tile"
+
+    image: Optional[ImageField] = Field(default=None, description="The image to infill")
+    tile_size: int = Field(default=32, ge=1, description="The tile size (px)")
+    seed: int = Field(
+        ge=0,
+        le=SEED_MAX,
+        description="The seed to use for tile generation (omit for random)",
+        default_factory=get_random_seed,
+    )
+
+    def invoke(self, context: InvocationContext) -> ImageOutput:
+        image = context.services.images.get(
+            self.image.image_type, self.image.image_name
+        )
+
+        infilled = tile_fill_missing(
+            image.copy(), seed=self.seed, tile_size=self.tile_size
+        )
+        infilled.paste(image, (0, 0), image.split()[-1])
+
+        image_type = ImageType.RESULT
+        image_name = context.services.images.create_name(
+            context.graph_execution_state_id, self.id
+        )
+
+        metadata = context.services.metadata.build_metadata(
+            session_id=context.graph_execution_state_id, node=self
+        )
+
+        context.services.images.save(image_type, image_name, infilled, metadata)
+        return build_image_output(
+            image_type=image_type,
+            image_name=image_name,
+            image=image,
+        )
+
+
+class InfillPatchMatchInvocation(BaseInvocation):
+    """Infills transparent areas of an image using the PatchMatch algorithm"""
+
+    type: Literal["infill_patchmatch"] = "infill_patchmatch"
+
+    image: Optional[ImageField] = Field(default=None, description="The image to infill")
+
+    def invoke(self, context: InvocationContext) -> ImageOutput:
+        image = context.services.images.get(
+            self.image.image_type, self.image.image_name
+        )
+
+        if PatchMatch.patchmatch_available():
+            infilled = infill_patchmatch(image.copy())
+        else:
+            raise ValueError("PatchMatch is not available on this system")
+
+        image_type = ImageType.RESULT
+        image_name = context.services.images.create_name(
+            context.graph_execution_state_id, self.id
+        )
+
+        metadata = context.services.metadata.build_metadata(
+            session_id=context.graph_execution_state_id, node=self
+        )
+
+        context.services.images.save(image_type, image_name, infilled, metadata)
+        return build_image_output(
+            image_type=image_type,
+            image_name=image_name,
+            image=image,
+        )

invokeai/app/invocations/latent.py

@@ -1,11 +1,13 @@
 # Copyright (c) 2023 Kyle Schouviller (https://github.com/kyle0654)
 
 import random
-from typing import Literal, Optional
+from typing import Literal, Optional, Union
+import einops
 from pydantic import BaseModel, Field
 import torch
 
 from invokeai.app.invocations.util.choose_model import choose_model
+from invokeai.app.util.misc import SEED_MAX, get_random_seed
 
 from invokeai.app.util.step_callback import stable_diffusion_step_callback
 
@@ -13,7 +15,9 @@ from ...backend.model_management.model_manager import ModelManager
 from ...backend.util.devices import choose_torch_device, torch_dtype
 from ...backend.stable_diffusion.diffusion.shared_invokeai_diffusion import PostprocessingSettings
 from ...backend.image_util.seamless import configure_model_padding
-from ...backend.stable_diffusion.diffusers_pipeline import ConditioningData, StableDiffusionGeneratorPipeline
+from ...backend.prompting.conditioning import get_uc_and_c_and_ec
+from ...backend.stable_diffusion.diffusers_pipeline import ConditioningData, StableDiffusionGeneratorPipeline, image_resized_to_grid_as_tensor
+from ...backend.stable_diffusion.schedulers import SCHEDULER_MAP
 from .baseinvocation import BaseInvocation, BaseInvocationOutput, InvocationContext, InvocationConfig
 import numpy as np
 from ..services.image_storage import ImageType
@@ -37,41 +41,55 @@ class LatentsField(BaseModel):
 class LatentsOutput(BaseInvocationOutput):
     """Base class for invocations that output latents"""
     #fmt: off
-    type: Literal["latent_output"] = "latent_output"
+    type: Literal["latents_output"] = "latents_output"
+
+    # Inputs
     latents: LatentsField          = Field(default=None, description="The output latents")
+    width:                     int = Field(description="The width of the latents in pixels")
+    height:                    int = Field(description="The height of the latents in pixels")
     #fmt: on
 
+
+def build_latents_output(latents_name: str, latents: torch.Tensor):
+      return LatentsOutput(
+          latents=LatentsField(latents_name=latents_name),
+          width=latents.size()[3] * 8,
+          height=latents.size()[2] * 8,
+      )
+
 class NoiseOutput(BaseInvocationOutput):
     """Invocation noise output"""
     #fmt: off
     type:  Literal["noise_output"] = "noise_output"
+
+    # Inputs
     noise: LatentsField            = Field(default=None, description="The output noise")
+    width:                     int = Field(description="The width of the noise in pixels")
+    height:                    int = Field(description="The height of the noise in pixels")
     #fmt: on
 
-
+def build_noise_output(latents_name: str, latents: torch.Tensor):
-# TODO: this seems like a hack
+      return NoiseOutput(
-scheduler_map = dict(
+          noise=LatentsField(latents_name=latents_name),
-    ddim=diffusers.DDIMScheduler,
+          width=latents.size()[3] * 8,
-    dpmpp_2=diffusers.DPMSolverMultistepScheduler,
+          height=latents.size()[2] * 8,
-    k_dpm_2=diffusers.KDPM2DiscreteScheduler,
+      )
-    k_dpm_2_a=diffusers.KDPM2AncestralDiscreteScheduler,
-    k_dpmpp_2=diffusers.DPMSolverMultistepScheduler,
-    k_euler=diffusers.EulerDiscreteScheduler,
-    k_euler_a=diffusers.EulerAncestralDiscreteScheduler,
-    k_heun=diffusers.HeunDiscreteScheduler,
-    k_lms=diffusers.LMSDiscreteScheduler,
-    plms=diffusers.PNDMScheduler,
-)
 
 
 SAMPLER_NAME_VALUES = Literal[
-    tuple(list(scheduler_map.keys()))
+    tuple(list(SCHEDULER_MAP.keys()))
 ]
 
 
 def get_scheduler(scheduler_name:str, model: StableDiffusionGeneratorPipeline)->Scheduler:
-    scheduler_class = scheduler_map.get(scheduler_name,'ddim')
+    scheduler_class, scheduler_extra_config = SCHEDULER_MAP.get(scheduler_name, SCHEDULER_MAP['ddim'])
-    scheduler = scheduler_class.from_config(model.scheduler.config)
+    
+    scheduler_config = model.scheduler.config
+    if "_backup" in scheduler_config:
+        scheduler_config = scheduler_config["_backup"]
+    scheduler_config = {**scheduler_config, **scheduler_extra_config, "_backup": scheduler_config}
+    scheduler = scheduler_class.from_config(scheduler_config)
+    
     # hack copied over from generate.py
     if not hasattr(scheduler, 'uses_inpainting_model'):
         scheduler.uses_inpainting_model = lambda: False
@@ -102,17 +120,13 @@ def get_noise(width:int, height:int, device:torch.device, seed:int = 0, latent_c
     return x
 
 
-def random_seed():
-    return random.randint(0, np.iinfo(np.uint32).max)
-
-
 class NoiseInvocation(BaseInvocation):
     """Generates latent noise."""
 
     type: Literal["noise"] = "noise"
 
     # Inputs
-    seed:        int = Field(ge=0, le=np.iinfo(np.uint32).max, description="The seed to use", default_factory=random_seed)
+    seed:       int = Field(ge=0, le=SEED_MAX, description="The seed to use", default_factory=get_random_seed)
     width:       int = Field(default=512, multiple_of=8, gt=0, description="The width of the resulting noise", )
     height:      int = Field(default=512, multiple_of=8, gt=0, description="The height of the resulting noise", )
 
@@ -131,9 +145,7 @@ class NoiseInvocation(BaseInvocation):
 
         name = f'{context.graph_execution_state_id}__{self.id}'
         context.services.latents.set(name, noise)
-        return NoiseOutput(
+        return build_noise_output(latents_name=name, latents=noise)
-            noise=LatentsField(latents_name=name)
-        )
 
 
 # Text to image
@@ -149,11 +161,10 @@ class TextToLatentsInvocation(BaseInvocation):
     noise: Optional[LatentsField] = Field(description="The noise to use")
     steps:       int = Field(default=10, gt=0, description="The number of steps to use to generate the image")
     cfg_scale: float = Field(default=7.5, gt=0, description="The Classifier-Free Guidance, higher values may result in a result closer to the prompt", )
-    scheduler: SAMPLER_NAME_VALUES = Field(default="k_lms", description="The scheduler to use" )
+    scheduler: SAMPLER_NAME_VALUES = Field(default="lms", description="The scheduler to use" )
+    model:       str = Field(default="", description="The model to use (currently ignored)")
     seamless:   bool = Field(default=False, description="Whether or not to generate an image that can tile without seams", )
     seamless_axes: str = Field(default="", description="The axes to tile the image on, 'x' and/or 'y'")
-    model:       str = Field(default="", description="The model to use (currently ignored)")
-    progress_images: bool = Field(default=False, description="Whether or not to produce progress images during generation",  )
     # fmt: on
 
     # Schema customisation
@@ -218,7 +229,7 @@ class TextToLatentsInvocation(BaseInvocation):
                 h_symmetry_time_pct=None,#h_symmetry_time_pct,
                 v_symmetry_time_pct=None#v_symmetry_time_pct,
             ),
-        ).add_scheduler_args_if_applicable(model.scheduler, eta=None)#ddim_eta)
+        ).add_scheduler_args_if_applicable(model.scheduler, eta=0.0)#ddim_eta)
         return conditioning_data
 
 
@@ -250,9 +261,7 @@ class TextToLatentsInvocation(BaseInvocation):
 
         name = f'{context.graph_execution_state_id}__{self.id}'
         context.services.latents.set(name, result_latents)
-        return LatentsOutput(
+        return build_latents_output(latents_name=name, latents=result_latents)
-            latents=LatentsField(latents_name=name)
-        )
 
 
 class LatentsToLatentsInvocation(TextToLatentsInvocation):
@@ -260,6 +269,10 @@ class LatentsToLatentsInvocation(TextToLatentsInvocation):
 
     type: Literal["l2l"] = "l2l"
 
+    # Inputs
+    latents: Optional[LatentsField] = Field(description="The latents to use as a base image")
+    strength: float = Field(default=0.5, description="The strength of the latents to use")
+
     # Schema customisation
     class Config(InvocationConfig):
         schema_extra = {
@@ -271,10 +284,6 @@ class LatentsToLatentsInvocation(TextToLatentsInvocation):
             },
         }
 
-    # Inputs
-    latents: Optional[LatentsField] = Field(description="The latents to use as a base image")
-    strength: float = Field(default=0.5, description="The strength of the latents to use")
-
     def invoke(self, context: InvocationContext) -> LatentsOutput:
         noise = context.services.latents.get(self.noise.latents_name)
         latent = context.services.latents.get(self.latents.latents_name)
@@ -287,7 +296,7 @@ class LatentsToLatentsInvocation(TextToLatentsInvocation):
             self.dispatch_progress(context, source_node_id, state)
 
         model = self.get_model(context.services.model_manager)
-        conditioning_data = self.get_conditioning_data(model)
+        conditioning_data = self.get_conditioning_data(context, model)
 
         # TODO: Verify the noise is the right size
 
@@ -295,11 +304,7 @@ class LatentsToLatentsInvocation(TextToLatentsInvocation):
             latent, device=model.device, dtype=latent.dtype
         )
 
-        timesteps, _ = model.get_img2img_timesteps(
+        timesteps, _ = model.get_img2img_timesteps(self.steps, self.strength)
-            self.steps,
-            self.strength,
-            device=model.device,
-        )
 
         result_latents, result_attention_map_saver = model.latents_from_embeddings(
             latents=initial_latents,
@@ -315,9 +320,7 @@ class LatentsToLatentsInvocation(TextToLatentsInvocation):
 
         name = f'{context.graph_execution_state_id}__{self.id}'
         context.services.latents.set(name, result_latents)
-        return LatentsOutput(
+        return build_latents_output(latents_name=name, latents=result_latents)
-            latents=LatentsField(latents_name=name)
-        )
 
 
 # Latent to image
@@ -384,8 +387,8 @@ class ResizeLatentsInvocation(BaseInvocation):
     latents:    Optional[LatentsField] = Field(description="The latents to resize")
     width:                         int = Field(ge=64, multiple_of=8, description="The width to resize to (px)")
     height:                        int = Field(ge=64, multiple_of=8, description="The height to resize to (px)")
-    mode: Optional[LATENTS_INTERPOLATION_MODE]  = Field(default="bilinear", description="The interpolation mode")
+    mode:   LATENTS_INTERPOLATION_MODE = Field(default="bilinear", description="The interpolation mode")
-    antialias: Optional[bool]                   = Field(default=False, description="Whether or not to antialias (applied in bilinear and bicubic modes only)")
+    antialias:                    bool = Field(default=False, description="Whether or not to antialias (applied in bilinear and bicubic modes only)")
 
     def invoke(self, context: InvocationContext) -> LatentsOutput:
         latents = context.services.latents.get(self.latents.latents_name)
@@ -402,7 +405,7 @@ class ResizeLatentsInvocation(BaseInvocation):
 
         name = f"{context.graph_execution_state_id}__{self.id}"
         context.services.latents.set(name, resized_latents)
-        return LatentsOutput(latents=LatentsField(latents_name=name))
+        return build_latents_output(latents_name=name, latents=resized_latents)
 
 
 class ScaleLatentsInvocation(BaseInvocation):
@@ -413,8 +416,8 @@ class ScaleLatentsInvocation(BaseInvocation):
     # Inputs
     latents:   Optional[LatentsField] = Field(description="The latents to scale")
     scale_factor:               float = Field(gt=0, description="The factor by which to scale the latents")
-    mode: Optional[LATENTS_INTERPOLATION_MODE]  = Field(default="bilinear", description="The interpolation mode")
+    mode:  LATENTS_INTERPOLATION_MODE = Field(default="bilinear", description="The interpolation mode")
-    antialias: Optional[bool]                   = Field(default=False, description="Whether or not to antialias (applied in bilinear and bicubic modes only)")
+    antialias:                   bool = Field(default=False, description="Whether or not to antialias (applied in bilinear and bicubic modes only)")
 
     def invoke(self, context: InvocationContext) -> LatentsOutput:
         latents = context.services.latents.get(self.latents.latents_name)
@@ -432,4 +435,48 @@ class ScaleLatentsInvocation(BaseInvocation):
 
         name = f"{context.graph_execution_state_id}__{self.id}"
         context.services.latents.set(name, resized_latents)
-        return LatentsOutput(latents=LatentsField(latents_name=name))
+        return build_latents_output(latents_name=name, latents=resized_latents)
+
+
+class ImageToLatentsInvocation(BaseInvocation):
+    """Encodes an image into latents."""
+
+    type: Literal["i2l"] = "i2l"
+
+    # Inputs
+    image: Union[ImageField, None] = Field(description="The image to encode")
+    model: str = Field(default="", description="The model to use")
+
+    # Schema customisation
+    class Config(InvocationConfig):
+        schema_extra = {
+            "ui": {
+                "tags": ["latents", "image"],
+                "type_hints": {"model": "model"},
+            },
+        }
+
+    @torch.no_grad()
+    def invoke(self, context: InvocationContext) -> LatentsOutput:
+        image = context.services.images.get(
+            self.image.image_type, self.image.image_name
+        )
+
+        # TODO: this only really needs the vae
+        model_info = choose_model(context.services.model_manager, self.model)
+        model: StableDiffusionGeneratorPipeline = model_info["model"]
+
+        image_tensor = image_resized_to_grid_as_tensor(image.convert("RGB"))
+
+        if image_tensor.dim() == 3:
+            image_tensor = einops.rearrange(image_tensor, "c h w -> 1 c h w")
+
+        latents = model.non_noised_latents_from_image(
+            image_tensor,
+            device=model._model_group.device_for(model.unet),
+            dtype=model.unet.dtype,
+        )
+
+        name = f"{context.graph_execution_state_id}__{self.id}"
+        context.services.latents.set(name, latents)
+        return build_latents_output(latents_name=name, latents=latents)

invokeai/app/invocations/math.py

@@ -3,6 +3,7 @@
 from typing import Literal
 
 from pydantic import BaseModel, Field
+import numpy as np
 
 from .baseinvocation import BaseInvocation, BaseInvocationOutput, InvocationContext, InvocationConfig
 
@@ -73,3 +74,12 @@ class DivideInvocation(BaseInvocation, MathInvocationConfig):
 
     def invoke(self, context: InvocationContext) -> IntOutput:
         return IntOutput(a=int(self.a / self.b))
+
+
+class RandomIntInvocation(BaseInvocation):
+    """Outputs a single random integer."""
+    #fmt: off
+    type: Literal["rand_int"] = "rand_int"
+    #fmt: on
+    def invoke(self, context: InvocationContext) -> IntOutput:
+        return IntOutput(a=np.random.randint(0, np.iinfo(np.int32).max))

invokeai/app/invocations/util/choose_model.py

@@ -4,10 +4,11 @@ from invokeai.backend.model_management.model_manager import ModelManager
 def choose_model(model_manager: ModelManager, model_name: str):
     """Returns the default model if the `model_name` not a valid model, else returns the selected model."""
     logger = model_manager.logger
-    if model_manager.valid_model(model_name):
+    if model_name and not model_manager.valid_model(model_name):
-        model = model_manager.get_model(model_name)
+        default_model_name = model_manager.default_model()
-    else:
+        logger.warning(f"\'{model_name}\' is not a valid model name. Using default model \'{default_model_name}\' instead.")
         model = model_manager.get_model()
-        logger.warning(f"{model_name}' is not a valid model name. Using default model \'{model['model_name']}\' instead.")
+    else:
+        model = model_manager.get_model(model_name)
 
     return model

invokeai/app/models/image.py

@@ -1,5 +1,5 @@
 from enum import Enum
-from typing import Optional
+from typing import Optional, Tuple
 from pydantic import BaseModel, Field
 
 
@@ -27,3 +27,13 @@ class ImageField(BaseModel):
 
     class Config:
         schema_extra = {"required": ["image_type", "image_name"]}
+
+
+class ColorField(BaseModel):
+    r: int = Field(ge=0, le=255, description="The red component")
+    g: int = Field(ge=0, le=255, description="The green component")
+    b: int = Field(ge=0, le=255, description="The blue component")
+    a: int = Field(ge=0, le=255, description="The alpha component")
+
+    def tuple(self) -> Tuple[int, int, int, int]:
+        return (self.r, self.g, self.b, self.a)

invokeai/app/services/default_graphs.py

@@ -49,12 +49,13 @@ def create_text_to_image() -> LibraryGraph:
 def create_system_graphs(graph_library: ItemStorageABC[LibraryGraph]) -> list[LibraryGraph]:
     """Creates the default system graphs, or adds new versions if the old ones don't match"""
     
+    # TODO: Uncomment this when we are ready to fix this up to prevent breaking changes
     graphs: list[LibraryGraph] = list()
 
-    text_to_image = graph_library.get(default_text_to_image_graph_id)
+    # text_to_image = graph_library.get(default_text_to_image_graph_id)
     
-    # TODO: Check if the graph is the same as the default one, and if not, update it
+    # # TODO: Check if the graph is the same as the default one, and if not, update it
-    #if text_to_image is None:
+    # #if text_to_image is None:
     text_to_image = create_text_to_image()
     graph_library.set(text_to_image)
 

invokeai/app/services/image_storage.py

@@ -270,4 +270,5 @@ class DiskImageStorage(ImageStorageBase):
             )  # TODO: this should refresh position for LRU cache
             if len(self.__cache) > self.__max_cache_size:
                 cache_id = self.__cache_ids.get()
+                if cache_id in self.__cache:
                     del self.__cache[cache_id]

invokeai/app/services/metadata.py

@@ -20,9 +20,18 @@ class MetadataLatentsField(TypedDict):
     latents_name: str
 
 
+class MetadataColorField(TypedDict):
+    """Pydantic-less ColorField, used for metadata parsing"""
+    r: int
+    g: int
+    b: int
+    a: int
+
+
+
 # TODO: This is a placeholder for `InvocationsUnion` pending resolution of circular imports
 NodeMetadata = Dict[
-    str, str | int | float | bool | MetadataImageField | MetadataLatentsField
+    str, None | str | int | float | bool | MetadataImageField | MetadataLatentsField | MetadataColorField
 ]
 
 

invokeai/app/services/processor.py

@@ -1,3 +1,4 @@
+import time
 import traceback
 from threading import Event, Thread, BoundedSemaphore
 
@@ -6,6 +7,7 @@ from .invocation_queue import InvocationQueueItem
 from .invoker import InvocationProcessorABC, Invoker
 from ..models.exceptions import CanceledException
 
+import invokeai.backend.util.logging as logger
 class DefaultInvocationProcessor(InvocationProcessorABC):
     __invoker_thread: Thread
     __stop_event: Event
@@ -34,8 +36,14 @@ class DefaultInvocationProcessor(InvocationProcessorABC):
         try:
             self.__threadLimit.acquire()
             while not stop_event.is_set():
+                try:
                     queue_item: InvocationQueueItem = self.__invoker.services.queue.get()
+                except Exception as e:
+                    logger.debug("Exception while getting from queue: %s" % e)
+
                 if not queue_item:  # Probably stopping
+                    # do not hammer the queue
+                    time.sleep(0.5)
                     continue
 
                 graph_execution_state = (
@@ -124,7 +132,16 @@ class DefaultInvocationProcessor(InvocationProcessorABC):
                 # Queue any further commands if invoking all
                 is_complete = graph_execution_state.is_complete()
                 if queue_item.invoke_all and not is_complete:
+                    try:
                         self.__invoker.invoke(graph_execution_state, invoke_all=True)
+                    except Exception as e:
+                        logger.error("Error while invoking: %s" % e)
+                        self.__invoker.services.events.emit_invocation_error(
+                            graph_execution_state_id=graph_execution_state.id,
+                            node=invocation.dict(),
+                            source_node_id=source_node_id,
+                            error=traceback.format_exc()
+                        )
                 elif is_complete:
                     self.__invoker.services.events.emit_graph_execution_complete(
                         graph_execution_state.id

invokeai/app/util/misc.py

@@ -1,5 +1,13 @@
 import datetime
+import numpy as np
 
 
 def get_timestamp():
     return int(datetime.datetime.now(datetime.timezone.utc).timestamp())
+
+
+SEED_MAX = np.iinfo(np.int32).max
+
+
+def get_random_seed():
+    return np.random.randint(0, SEED_MAX)

invokeai/backend/generator/base.py

@@ -31,6 +31,7 @@ from ..util.util import rand_perlin_2d
 from ..safety_checker import SafetyChecker
 from ..prompting.conditioning import get_uc_and_c_and_ec
 from ..stable_diffusion.diffusers_pipeline import StableDiffusionGeneratorPipeline
+from ..stable_diffusion.schedulers import SCHEDULER_MAP
 
 downsampling = 8
 
@@ -71,19 +72,6 @@ class InvokeAIGeneratorOutput:
 # we are interposing a wrapper around the original Generator classes so that
 # old code that calls Generate will continue to work.
 class InvokeAIGenerator(metaclass=ABCMeta):
-    scheduler_map = dict(
-        ddim=diffusers.DDIMScheduler,
-        dpmpp_2=diffusers.DPMSolverMultistepScheduler,
-        k_dpm_2=diffusers.KDPM2DiscreteScheduler,
-        k_dpm_2_a=diffusers.KDPM2AncestralDiscreteScheduler,
-        k_dpmpp_2=diffusers.DPMSolverMultistepScheduler,
-        k_euler=diffusers.EulerDiscreteScheduler,
-        k_euler_a=diffusers.EulerAncestralDiscreteScheduler,
-        k_heun=diffusers.HeunDiscreteScheduler,
-        k_lms=diffusers.LMSDiscreteScheduler,
-        plms=diffusers.PNDMScheduler,
-    )
-
     def __init__(self,
                  model_info: dict,
                  params: InvokeAIGeneratorBasicParams=InvokeAIGeneratorBasicParams(),
@@ -175,14 +163,20 @@ class InvokeAIGenerator(metaclass=ABCMeta):
         '''
         Return list of all the schedulers that we currently handle.
         '''
-        return list(self.scheduler_map.keys())
+        return list(SCHEDULER_MAP.keys())
 
     def load_generator(self, model: StableDiffusionGeneratorPipeline, generator_class: Type[Generator]):
         return generator_class(model, self.params.precision)
 
     def get_scheduler(self, scheduler_name:str, model: StableDiffusionGeneratorPipeline)->Scheduler:
-        scheduler_class = self.scheduler_map.get(scheduler_name,'ddim')
+        scheduler_class, scheduler_extra_config = SCHEDULER_MAP.get(scheduler_name, SCHEDULER_MAP['ddim'])
-        scheduler = scheduler_class.from_config(model.scheduler.config)
+        
+        scheduler_config = model.scheduler.config
+        if "_backup" in scheduler_config:
+            scheduler_config = scheduler_config["_backup"]
+        scheduler_config = {**scheduler_config, **scheduler_extra_config, "_backup": scheduler_config}
+        scheduler = scheduler_class.from_config(scheduler_config)
+        
         # hack copied over from generate.py
         if not hasattr(scheduler, 'uses_inpainting_model'):
             scheduler.uses_inpainting_model = lambda: False
@@ -226,10 +220,10 @@ class Inpaint(Img2Img):
     def generate(self,
                  mask_image: Image.Image | torch.FloatTensor,
                  # Seam settings - when 0, doesn't fill seam
-                 seam_size: int = 0,
+                 seam_size: int = 96,
-                 seam_blur: int = 0,
+                 seam_blur: int = 16,
                  seam_strength: float = 0.7,
-                 seam_steps: int = 10,
+                 seam_steps: int = 30,
                  tile_size: int = 32,
                  inpaint_replace=False,
                  infill_method=None,

invokeai/backend/generator/inpaint.py

@@ -4,6 +4,7 @@ invokeai.backend.generator.inpaint descends from .generator
 from __future__ import annotations
 
 import math
+from typing import Tuple, Union
 
 import cv2
 import numpy as np
@@ -59,7 +60,7 @@ class Inpaint(Img2Img):
             writeable=False,
         )
 
-    def infill_patchmatch(self, im: Image.Image) -> Image:
+    def infill_patchmatch(self, im: Image.Image) -> Image.Image:
         if im.mode != "RGBA":
             return im
 
@@ -75,18 +76,18 @@ class Inpaint(Img2Img):
         return im_patched
 
     def tile_fill_missing(
-        self, im: Image.Image, tile_size: int = 16, seed: int = None
+        self, im: Image.Image, tile_size: int = 16, seed: Union[int, None] = None
-    ) -> Image:
+    ) -> Image.Image:
         # Only fill if there's an alpha layer
         if im.mode != "RGBA":
             return im
 
         a = np.asarray(im, dtype=np.uint8)
 
-        tile_size = (tile_size, tile_size)
+        tile_size_tuple = (tile_size, tile_size)
 
         # Get the image as tiles of a specified size
-        tiles = self.get_tile_images(a, *tile_size).copy()
+        tiles = self.get_tile_images(a, *tile_size_tuple).copy()
 
         # Get the mask as tiles
         tiles_mask = tiles[:, :, :, :, 3]
@@ -127,7 +128,9 @@ class Inpaint(Img2Img):
 
         return si
 
-    def mask_edge(self, mask: Image, edge_size: int, edge_blur: int) -> Image:
+    def mask_edge(
+        self, mask: Image.Image, edge_size: int, edge_blur: int
+    ) -> Image.Image:
         npimg = np.asarray(mask, dtype=np.uint8)
 
         # Detect any partially transparent regions
@@ -206,15 +209,15 @@ class Inpaint(Img2Img):
         cfg_scale,
         ddim_eta,
         conditioning,
-        init_image: PIL.Image.Image | torch.FloatTensor,
+        init_image: Image.Image | torch.FloatTensor,
-        mask_image: PIL.Image.Image | torch.FloatTensor,
+        mask_image: Image.Image | torch.FloatTensor,
         strength: float,
         mask_blur_radius: int = 8,
         # Seam settings - when 0, doesn't fill seam
-        seam_size: int = 0,
+        seam_size: int = 96,
-        seam_blur: int = 0,
+        seam_blur: int = 16,
         seam_strength: float = 0.7,
-        seam_steps: int = 10,
+        seam_steps: int = 30,
         tile_size: int = 32,
         step_callback=None,
         inpaint_replace=False,
@@ -222,7 +225,7 @@ class Inpaint(Img2Img):
         infill_method=None,
         inpaint_width=None,
         inpaint_height=None,
-        inpaint_fill: tuple(int) = (0x7F, 0x7F, 0x7F, 0xFF),
+        inpaint_fill: Tuple[int, int, int, int] = (0x7F, 0x7F, 0x7F, 0xFF),
         attention_maps_callback=None,
         **kwargs,
     ):
@@ -239,7 +242,7 @@ class Inpaint(Img2Img):
         self.inpaint_width = inpaint_width
         self.inpaint_height = inpaint_height
 
-        if isinstance(init_image, PIL.Image.Image):
+        if isinstance(init_image, Image.Image):
             self.pil_image = init_image.copy()
 
             # Do infill
@@ -250,8 +253,8 @@ class Inpaint(Img2Img):
                     self.pil_image.copy(), seed=self.seed, tile_size=tile_size
                 )
             elif infill_method == "solid":
-                solid_bg = PIL.Image.new("RGBA", init_image.size, inpaint_fill)
+                solid_bg = Image.new("RGBA", init_image.size, inpaint_fill)
-                init_filled = PIL.Image.alpha_composite(solid_bg, init_image)
+                init_filled = Image.alpha_composite(solid_bg, init_image)
             else:
                 raise ValueError(
                     f"Non-supported infill type {infill_method}", infill_method
@@ -269,7 +272,7 @@ class Inpaint(Img2Img):
             # Create init tensor
             init_image = image_resized_to_grid_as_tensor(init_filled.convert("RGB"))
 
-        if isinstance(mask_image, PIL.Image.Image):
+        if isinstance(mask_image, Image.Image):
             self.pil_mask = mask_image.copy()
             debug_image(
                 mask_image,

invokeai/backend/model_management/convert_ckpt_to_diffusers.py

@@ -47,6 +47,7 @@ from diffusers import (
     LDMTextToImagePipeline,
     LMSDiscreteScheduler,
     PNDMScheduler,
+    UniPCMultistepScheduler,
     StableDiffusionPipeline,
     UNet2DConditionModel,
 )
@@ -1208,6 +1209,8 @@ def load_pipeline_from_original_stable_diffusion_ckpt(
             scheduler = EulerAncestralDiscreteScheduler.from_config(scheduler.config)
         elif scheduler_type == "dpm":
             scheduler = DPMSolverMultistepScheduler.from_config(scheduler.config)
+        elif scheduler_type == 'unipc':
+            scheduler = UniPCMultistepScheduler.from_config(scheduler.config)
         elif scheduler_type == "ddim":
             scheduler = scheduler
         else:

invokeai/backend/model_management/model_manager.py

@@ -1214,7 +1214,7 @@ class ModelManager(object):
                         sha.update(chunk)
         hash = sha.hexdigest()
         toc = time.time()
-        self.logger.debug(f"sha256 = {hash} ({count} files hashed in", "%4.2fs)" % (toc - tic))
+        self.logger.debug(f"sha256 = {hash} ({count} files hashed in {toc - tic:4.2f}s)")
         with open(hashpath, "w") as f:
             f.write(hash)
         return hash

invokeai/backend/stable_diffusion/diffusers_pipeline.py

@@ -509,10 +509,13 @@ class StableDiffusionGeneratorPipeline(StableDiffusionPipeline):
         run_id=None,
         callback: Callable[[PipelineIntermediateState], None] = None,
     ) -> tuple[torch.Tensor, Optional[AttentionMapSaver]]:
+        if self.scheduler.config.get("cpu_only", False):
+            scheduler_device = torch.device('cpu')
+        else:
+            scheduler_device = self._model_group.device_for(self.unet)
+
         if timesteps is None:
-            self.scheduler.set_timesteps(
+            self.scheduler.set_timesteps(num_inference_steps, device=scheduler_device)
-                num_inference_steps, device=self._model_group.device_for(self.unet)
-            )
             timesteps = self.scheduler.timesteps
         infer_latents_from_embeddings = GeneratorToCallbackinator(
             self.generate_latents_from_embeddings, PipelineIntermediateState
@@ -726,11 +729,7 @@ class StableDiffusionGeneratorPipeline(StableDiffusionPipeline):
         run_id=None,
         callback=None,
     ) -> InvokeAIStableDiffusionPipelineOutput:        
-        timesteps, _ = self.get_img2img_timesteps(
+        timesteps, _ = self.get_img2img_timesteps(num_inference_steps, strength)
-            num_inference_steps,
-            strength,
-            device=self._model_group.device_for(self.unet),
-        )
         result_latents, result_attention_maps = self.latents_from_embeddings(
             latents=initial_latents if strength < 1.0 else torch.zeros_like(
                 initial_latents, device=initial_latents.device, dtype=initial_latents.dtype
@@ -756,13 +755,19 @@ class StableDiffusionGeneratorPipeline(StableDiffusionPipeline):
             return self.check_for_safety(output, dtype=conditioning_data.dtype)
 
     def get_img2img_timesteps(
-        self, num_inference_steps: int, strength: float, device
+        self, num_inference_steps: int, strength: float, device=None
     ) -> (torch.Tensor, int):
         img2img_pipeline = StableDiffusionImg2ImgPipeline(**self.components)
         assert img2img_pipeline.scheduler is self.scheduler
-        img2img_pipeline.scheduler.set_timesteps(num_inference_steps, device=device)
+
+        if self.scheduler.config.get("cpu_only", False):
+            scheduler_device = torch.device('cpu')
+        else:
+            scheduler_device = self._model_group.device_for(self.unet)
+
+        img2img_pipeline.scheduler.set_timesteps(num_inference_steps, device=scheduler_device)
         timesteps, adjusted_steps = img2img_pipeline.get_timesteps(
-            num_inference_steps, strength, device=device
+            num_inference_steps, strength, device=scheduler_device
         )
         # Workaround for low strength resulting in zero timesteps.
         # TODO: submit upstream fix for zero-step img2img
@@ -796,9 +801,7 @@ class StableDiffusionGeneratorPipeline(StableDiffusionPipeline):
         if init_image.dim() == 3:
             init_image = init_image.unsqueeze(0)
 
-        timesteps, _ = self.get_img2img_timesteps(
+        timesteps, _ = self.get_img2img_timesteps(num_inference_steps, strength)
-            num_inference_steps, strength, device=device
-        )
 
         # 6. Prepare latent variables
         # can't quite use upstream StableDiffusionImg2ImgPipeline.prepare_latents

invokeai/backend/stable_diffusion/schedulers/__init__.py

@@ -0,0 +1 @@
+from .schedulers import SCHEDULER_MAP

invokeai/backend/stable_diffusion/schedulers/schedulers.py

@@ -0,0 +1,22 @@
+from diffusers import DDIMScheduler, DPMSolverMultistepScheduler, KDPM2DiscreteScheduler, \
+    KDPM2AncestralDiscreteScheduler, EulerDiscreteScheduler, EulerAncestralDiscreteScheduler, \
+    HeunDiscreteScheduler, LMSDiscreteScheduler, PNDMScheduler, UniPCMultistepScheduler, \
+    DPMSolverSinglestepScheduler, DEISMultistepScheduler, DDPMScheduler
+
+SCHEDULER_MAP = dict(
+    ddim=(DDIMScheduler, dict()),
+    ddpm=(DDPMScheduler, dict()),
+    deis=(DEISMultistepScheduler, dict()),
+    lms=(LMSDiscreteScheduler, dict()),
+    pndm=(PNDMScheduler, dict()),
+    heun=(HeunDiscreteScheduler, dict()),
+    euler=(EulerDiscreteScheduler, dict(use_karras_sigmas=False)),
+    euler_k=(EulerDiscreteScheduler, dict(use_karras_sigmas=True)),
+    euler_a=(EulerAncestralDiscreteScheduler, dict()),
+    kdpm_2=(KDPM2DiscreteScheduler, dict()),
+    kdpm_2_a=(KDPM2AncestralDiscreteScheduler, dict()),
+    dpmpp_2s=(DPMSolverSinglestepScheduler, dict()),
+    dpmpp_2m=(DPMSolverMultistepScheduler, dict(use_karras_sigmas=False)),
+    dpmpp_2m_k=(DPMSolverMultistepScheduler, dict(use_karras_sigmas=True)),
+    unipc=(UniPCMultistepScheduler, dict(cpu_only=True))
+)

invokeai/backend/web/modules/parameters.py

@@ -4,17 +4,20 @@ from .parse_seed_weights import parse_seed_weights
 
 SAMPLER_CHOICES = [
     "ddim",
-    "k_dpm_2_a",
+    "ddpm",
-    "k_dpm_2",
+    "deis",
-    "k_dpmpp_2_a",
+    "lms",
-    "k_dpmpp_2",
-    "k_euler_a",
-    "k_euler",
-    "k_heun",
-    "k_lms",
-    "plms",
-    # diffusers:
     "pndm",
+    "heun",
+    "euler",
+    "euler_k",
+    "euler_a",
+    "kdpm_2",
+    "kdpm_2_a",
+    "dpmpp_2s",
+    "dpmpp_2m",
+    "dpmpp_2m_k",
+    "unipc",
 ]
 
 

invokeai/frontend/web/.babelrc

@@ -1,13 +0,0 @@
-{
-  "plugins": [
-    [
-      "transform-imports",
-      {
-        "lodash": {
-          "transform": "lodash/${member}",
-          "preventFullImport": true
-        }
-      }
-    ]
-  ]
-}

invokeai/frontend/web/.gitignore

@@ -35,3 +35,7 @@ stats.html
 !.yarn/releases
 !.yarn/sdks
 !.yarn/versions
+
+# Yalc
+.yalc
+yalc.lock

invokeai/frontend/web/config/vite.package.config.ts

@@ -5,6 +5,7 @@ import { PluginOption, UserConfig } from 'vite';
 import dts from 'vite-plugin-dts';
 import eslint from 'vite-plugin-eslint';
 import tsconfigPaths from 'vite-tsconfig-paths';
+import cssInjectedByJsPlugin from 'vite-plugin-css-injected-by-js';
 
 export const packageConfig: UserConfig = {
   base: './',
@@ -16,9 +17,10 @@ export const packageConfig: UserConfig = {
     dts({
       insertTypesEntry: true,
     }),
+    cssInjectedByJsPlugin(),
   ],
   build: {
-    chunkSizeWarningLimit: 1500,
+    cssCodeSplit: true,
     lib: {
       entry: path.resolve(__dirname, '../src/index.ts'),
       name: 'InvokeAIUI',
@@ -30,6 +32,7 @@ export const packageConfig: UserConfig = {
         globals: {
           react: 'React',
           'react-dom': 'ReactDOM',
+          '@emotion/react': 'EmotionReact',
         },
       },
     },

invokeai/frontend/web/docs/README.md

@@ -37,7 +37,7 @@ From `invokeai/frontend/web/` run `yarn install` to get everything set up.
 Start everything in dev mode:
 
 1. Start the dev server: `yarn dev`
-2. Start the InvokeAI UI per usual: `invokeai --web`
+2. Start the InvokeAI Nodes backend: `python scripts/invokeai-new.py --web # run from the repo root`
 3. Point your browser to the dev server address e.g. <http://localhost:5173/>
 
 ### Production builds

invokeai/frontend/web/package.json

@@ -21,7 +21,6 @@
   "scripts": {
     "prepare": "cd ../../../ && husky install invokeai/frontend/web/.husky",
     "dev": "concurrently \"vite dev\" \"yarn run theme:watch\"",
-    "dev:nodes": "concurrently \"vite dev --mode nodes\" \"yarn run theme:watch\"",
     "dev:host": "concurrently \"vite dev --host\" \"yarn run theme:watch\"",
     "build": "yarn run lint && vite build",
     "api:web": "openapi -i http://localhost:9090/openapi.json -o src/services/api --client axios --useOptions --useUnionTypes --exportSchemas true --indent 2 --request src/services/fixtures/request.ts",
@@ -90,6 +89,7 @@
     "react-konva": "^18.2.7",
     "react-konva-utils": "^1.0.4",
     "react-redux": "^8.0.5",
+    "react-resizable-panels": "^0.0.42",
     "react-rnd": "^10.4.1",
     "react-transition-group": "^4.4.5",
     "react-use": "^17.4.0",
@@ -99,6 +99,7 @@
     "redux-deep-persist": "^1.0.7",
     "redux-dynamic-middlewares": "^2.2.0",
     "redux-persist": "^6.0.0",
+    "redux-remember": "^3.3.1",
     "roarr": "^7.15.0",
     "serialize-error": "^11.0.0",
     "socket.io-client": "^4.6.0",
@@ -118,6 +119,7 @@
     "@types/node": "^18.16.2",
     "@types/react": "^18.2.0",
     "@types/react-dom": "^18.2.1",
+    "@types/react-redux": "^7.1.25",
     "@types/react-transition-group": "^4.4.5",
     "@types/uuid": "^9.0.0",
     "@typescript-eslint/eslint-plugin": "^5.59.1",
@@ -143,6 +145,7 @@
     "terser": "^5.17.1",
     "ts-toolbelt": "^9.6.0",
     "vite": "^4.3.3",
+    "vite-plugin-css-injected-by-js": "^3.1.1",
     "vite-plugin-dts": "^2.3.0",
     "vite-plugin-eslint": "^1.8.1",
     "vite-tsconfig-paths": "^4.2.0",

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

@@ -25,7 +25,7 @@
     "common": {
         "hotkeysLabel": "Hotkeys",
         "themeLabel": "Theme",
-        "languagePickerLabel": "Language Picker",
+        "languagePickerLabel": "Language",
         "reportBugLabel": "Report Bug",
         "githubLabel": "Github",
         "discordLabel": "Discord",
@@ -54,7 +54,7 @@
         "img2img": "Image To Image",
         "unifiedCanvas": "Unified Canvas",
         "linear": "Linear",
-        "nodes": "Nodes",
+        "nodes": "Node Editor",
         "postprocessing": "Post Processing",
         "nodesDesc": "A node based system for the generation of images is under development currently. Stay tuned for updates about this amazing feature.",
         "postProcessing": "Post Processing",
@@ -102,7 +102,8 @@
         "generate": "Generate",
         "openInNewTab": "Open in New Tab",
         "dontAskMeAgain": "Don't ask me again",
-        "areYouSure": "Are you sure?"
+        "areYouSure": "Are you sure?",
+        "imagePrompt": "Image Prompt"
     },
     "gallery": {
         "generations": "Generations",
@@ -453,9 +454,10 @@
         "seed": "Seed",
         "imageToImage": "Image to Image",
         "randomizeSeed": "Randomize Seed",
-        "shuffle": "Shuffle",
+        "shuffle": "Shuffle Seed",
         "noiseThreshold": "Noise Threshold",
         "perlinNoise": "Perlin Noise",
+        "noiseSettings": "Noise",
         "variations": "Variations",
         "variationAmount": "Variation Amount",
         "seedWeights": "Seed Weights",
@@ -470,6 +472,8 @@
         "scale": "Scale",
         "otherOptions": "Other Options",
         "seamlessTiling": "Seamless Tiling",
+        "seamlessXAxis": "X Axis",
+        "seamlessYAxis": "Y Axis",
         "hiresOptim": "High Res Optimization",
         "hiresStrength": "High Res Strength",
         "imageFit": "Fit Initial Image To Output Size",
@@ -527,7 +531,8 @@
         "useCanvasBeta": "Use Canvas Beta Layout",
         "enableImageDebugging": "Enable Image Debugging",
         "useSlidersForAll": "Use Sliders For All Options",
-        "autoShowProgress": "Auto Show Progress Images",
+        "showProgressInViewer": "Show Progress Images in Viewer",
+        "antialiasProgressImages": "Antialias Progress Images",
         "resetWebUI": "Reset Web UI",
         "resetWebUIDesc1": "Resetting the web UI only resets the browser's local cache of your images and remembered settings. It does not delete any images from disk.",
         "resetWebUIDesc2": "If images aren't showing up in the gallery or something else isn't working, please try resetting before submitting an issue on GitHub.",
@@ -549,8 +554,9 @@
         "downloadImageStarted": "Image Download Started",
         "imageCopied": "Image Copied",
         "imageLinkCopied": "Image Link Copied",
+        "problemCopyingImageLink": "Unable to Copy Image Link",
         "imageNotLoaded": "No Image Loaded",
-        "imageNotLoadedDesc": "No image found to send to image to image module",
+        "imageNotLoadedDesc": "Could not find image",
         "imageSavedToGallery": "Image Saved to Gallery",
         "canvasMerged": "Canvas Merged",
         "sentToImageToImage": "Sent To Image To Image",
@@ -645,7 +651,8 @@
         "betaClear": "Clear",
         "betaDarkenOutside": "Darken Outside",
         "betaLimitToBox": "Limit To Box",
-        "betaPreserveMasked": "Preserve Masked"
+        "betaPreserveMasked": "Preserve Masked",
+        "antialiasing": "Antialiasing"
     },
     "ui": {
         "showProgressImages": "Show Progress Images",

invokeai/frontend/web/src/app/components/App.tsx

@@ -1,24 +1,18 @@
 import ImageUploader from 'common/components/ImageUploader';
-import ProgressBar from 'features/system/components/ProgressBar';
 import SiteHeader from 'features/system/components/SiteHeader';
+import ProgressBar from 'features/system/components/ProgressBar';
 import InvokeTabs from 'features/ui/components/InvokeTabs';
 
 import useToastWatcher from 'features/system/hooks/useToastWatcher';
 
 import FloatingGalleryButton from 'features/ui/components/FloatingGalleryButton';
 import FloatingParametersPanelButtons from 'features/ui/components/FloatingParametersPanelButtons';
-import { Box, Flex, Grid, Portal, useColorMode } from '@chakra-ui/react';
+import { Box, Flex, Grid, Portal } from '@chakra-ui/react';
 import { APP_HEIGHT, APP_WIDTH } from 'theme/util/constants';
-import ImageGalleryPanel from 'features/gallery/components/ImageGalleryPanel';
+import GalleryDrawer from 'features/gallery/components/ImageGalleryPanel';
 import Lightbox from 'features/lightbox/components/Lightbox';
 import { useAppDispatch, useAppSelector } from 'app/store/storeHooks';
-import {
+import { memo, ReactNode, useCallback, useEffect, useState } from 'react';
-  memo,
-  PropsWithChildren,
-  useCallback,
-  useEffect,
-  useState,
-} from 'react';
 import { motion, AnimatePresence } from 'framer-motion';
 import Loading from 'common/components/Loading/Loading';
 import { useIsApplicationReady } from 'features/system/hooks/useIsApplicationReady';
@@ -27,20 +21,24 @@ import { useGlobalHotkeys } from 'common/hooks/useGlobalHotkeys';
 import { configChanged } from 'features/system/store/configSlice';
 import { useFeatureStatus } from 'features/system/hooks/useFeatureStatus';
 import { useLogger } from 'app/logging/useLogger';
-import ProgressImagePreview from 'features/parameters/components/ProgressImagePreview';
+import ParametersDrawer from 'features/ui/components/ParametersDrawer';
+import { languageSelector } from 'features/system/store/systemSelectors';
+import i18n from 'i18n';
 
 const DEFAULT_CONFIG = {};
 
-interface Props extends PropsWithChildren {
+interface Props {
   config?: PartialAppConfig;
+  headerComponent?: ReactNode;
 }
 
-const App = ({ config = DEFAULT_CONFIG, children }: Props) => {
+const App = ({ config = DEFAULT_CONFIG, headerComponent }: Props) => {
   useToastWatcher();
   useGlobalHotkeys();
-  const log = useLogger();
 
-  const currentTheme = useAppSelector((state) => state.ui.currentTheme);
+  const language = useAppSelector(languageSelector);
+
+  const log = useLogger();
 
   const isLightboxEnabled = useFeatureStatus('lightbox').isFeatureEnabled;
 
@@ -48,18 +46,17 @@ const App = ({ config = DEFAULT_CONFIG, children }: Props) => {
 
   const [loadingOverridden, setLoadingOverridden] = useState(false);
 
-  const { setColorMode } = useColorMode();
   const dispatch = useAppDispatch();
 
+  useEffect(() => {
+    i18n.changeLanguage(language);
+  }, [language]);
+
   useEffect(() => {
     log.info({ namespace: 'App', data: config }, 'Received config');
     dispatch(configChanged(config));
   }, [dispatch, config, log]);
 
-  useEffect(() => {
-    setColorMode(['light'].includes(currentTheme) ? 'light' : 'dark');
-  }, [setColorMode, currentTheme]);
-
   const handleOverrideClicked = useCallback(() => {
     setLoadingOverridden(true);
   }, []);
@@ -76,7 +73,7 @@ const App = ({ config = DEFAULT_CONFIG, children }: Props) => {
           w={APP_WIDTH}
           h={APP_HEIGHT}
         >
-          {children || <SiteHeader />}
+          {headerComponent || <SiteHeader />}
           <Flex
             gap={4}
             w={{ base: '100vw', xl: 'full' }}
@@ -84,11 +81,13 @@ const App = ({ config = DEFAULT_CONFIG, children }: Props) => {
             flexDir={{ base: 'column', xl: 'row' }}
           >
             <InvokeTabs />
-            <ImageGalleryPanel />
           </Flex>
         </Grid>
       </ImageUploader>
 
+      <GalleryDrawer />
+      <ParametersDrawer />
+
       <AnimatePresence>
         {!isApplicationReady && !loadingOverridden && (
           <motion.div
@@ -121,7 +120,6 @@ const App = ({ config = DEFAULT_CONFIG, children }: Props) => {
       <Portal>
         <FloatingGalleryButton />
       </Portal>
-      <ProgressImagePreview />
     </Grid>
   );
 };

invokeai/frontend/web/src/app/components/InvokeAIUI.tsx

@@ -1,18 +1,13 @@
-import React, { lazy, memo, PropsWithChildren, useEffect } from 'react';
+import React, {
+  lazy,
+  memo,
+  PropsWithChildren,
+  ReactNode,
+  useEffect,
+} from 'react';
 import { Provider } from 'react-redux';
-import { PersistGate } from 'redux-persist/integration/react';
 import { store } from 'app/store/store';
-import { persistor } from '../store/persistor';
 import { OpenAPI } from 'services/api';
-import '@fontsource/inter/100.css';
-import '@fontsource/inter/200.css';
-import '@fontsource/inter/300.css';
-import '@fontsource/inter/400.css';
-import '@fontsource/inter/500.css';
-import '@fontsource/inter/600.css';
-import '@fontsource/inter/700.css';
-import '@fontsource/inter/800.css';
-import '@fontsource/inter/900.css';
 
 import Loading from '../../common/components/Loading/Loading';
 import { addMiddleware, resetMiddlewares } from 'redux-dynamic-middlewares';
@@ -28,9 +23,10 @@ interface Props extends PropsWithChildren {
   apiUrl?: string;
   token?: string;
   config?: PartialAppConfig;
+  headerComponent?: ReactNode;
 }
 
-const InvokeAIUI = ({ apiUrl, token, config, children }: Props) => {
+const InvokeAIUI = ({ apiUrl, token, config, headerComponent }: Props) => {
   useEffect(() => {
     // configure API client token
     if (token) {
@@ -57,13 +53,11 @@ const InvokeAIUI = ({ apiUrl, token, config, children }: Props) => {
   return (
     <React.StrictMode>
       <Provider store={store}>
-        <PersistGate loading={<Loading />} persistor={persistor}>
         <React.Suspense fallback={<Loading />}>
           <ThemeLocaleProvider>
-              <App config={config}>{children}</App>
+            <App config={config} headerComponent={headerComponent} />
           </ThemeLocaleProvider>
         </React.Suspense>
-        </PersistGate>
       </Provider>
     </React.StrictMode>
   );

invokeai/frontend/web/src/app/components/ThemeLocaleProvider.tsx

@@ -1,4 +1,8 @@
-import { ChakraProvider, extendTheme } from '@chakra-ui/react';
+import {
+  ChakraProvider,
+  createLocalStorageManager,
+  extendTheme,
+} from '@chakra-ui/react';
 import { ReactNode, useEffect } from 'react';
 import { useTranslation } from 'react-i18next';
 import { theme as invokeAITheme } from 'theme/theme';
@@ -9,15 +13,8 @@ import { greenTeaThemeColors } from 'theme/colors/greenTea';
 import { invokeAIThemeColors } from 'theme/colors/invokeAI';
 import { lightThemeColors } from 'theme/colors/lightTheme';
 import { oceanBlueColors } from 'theme/colors/oceanBlue';
-import '@fontsource/inter/100.css';
+
-import '@fontsource/inter/200.css';
+import '@fontsource/inter/variable.css';
-import '@fontsource/inter/300.css';
-import '@fontsource/inter/400.css';
-import '@fontsource/inter/500.css';
-import '@fontsource/inter/600.css';
-import '@fontsource/inter/700.css';
-import '@fontsource/inter/800.css';
-import '@fontsource/inter/900.css';
 import 'overlayscrollbars/overlayscrollbars.css';
 import 'theme/css/overlayscrollbars.css';
 
@@ -32,6 +29,8 @@ const THEMES = {
   ocean: oceanBlueColors,
 };
 
+const manager = createLocalStorageManager('@@invokeai-color-mode');
+
 function ThemeLocaleProvider({ children }: ThemeLocaleProviderProps) {
   const { i18n } = useTranslation();
 
@@ -51,7 +50,11 @@ function ThemeLocaleProvider({ children }: ThemeLocaleProviderProps) {
     document.body.dir = direction;
   }, [direction]);
 
-  return <ChakraProvider theme={theme}>{children}</ChakraProvider>;
+  return (
+    <ChakraProvider theme={theme} colorModeManager={manager}>
+      {children}
+    </ChakraProvider>
+  );
 }
 
 export default ThemeLocaleProvider;

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

@@ -2,17 +2,28 @@
 
 export const DIFFUSERS_SCHEDULERS: Array<string> = [
   'ddim',
-  'plms',
+  'ddpm',
-  'k_lms',
+  'deis',
-  'dpmpp_2',
+  'lms',
-  'k_dpm_2',
+  'pndm',
-  'k_dpm_2_a',
+  'heun',
-  'k_dpmpp_2',
+  'euler',
-  'k_euler',
+  'euler_k',
-  'k_euler_a',
+  'euler_a',
-  'k_heun',
+  'kdpm_2',
+  'kdpm_2_a',
+  'dpmpp_2s',
+  'dpmpp_2m',
+  'dpmpp_2m_k',
+  'unipc',
 ];
 
+export const IMG2IMG_DIFFUSERS_SCHEDULERS = DIFFUSERS_SCHEDULERS.filter(
+  (scheduler) => {
+    return scheduler !== 'dpmpp_2s';
+  }
+);
+
 // Valid image widths
 export const WIDTHS: Array<number> = Array.from(Array(64)).map(
   (_x, i) => (i + 1) * 64

invokeai/frontend/web/src/app/selectors/readinessSelector.ts

@@ -1,26 +1,20 @@
 import { createSelector } from '@reduxjs/toolkit';
+import { defaultSelectorOptions } from 'app/store/util/defaultMemoizeOptions';
 import { validateSeedWeights } from 'common/util/seedWeightPairs';
-import { initialCanvasImageSelector } from 'features/canvas/store/canvasSelectors';
 import { generationSelector } from 'features/parameters/store/generationSelectors';
 import { systemSelector } from 'features/system/store/systemSelectors';
 import { activeTabNameSelector } from 'features/ui/store/uiSelectors';
 import { isEqual } from 'lodash-es';
 
 export const readinessSelector = createSelector(
-  [
+  [generationSelector, systemSelector, activeTabNameSelector],
-    generationSelector,
+  (generation, system, activeTabName) => {
-    systemSelector,
-    initialCanvasImageSelector,
-    activeTabNameSelector,
-  ],
-  (generation, system, initialCanvasImage, activeTabName) => {
     const {
       prompt,
       shouldGenerateVariations,
       seedWeights,
       initialImage,
       seed,
-      isImageToImageEnabled,
     } = generation;
 
     const { isProcessing, isConnected } = system;
@@ -34,7 +28,7 @@ export const readinessSelector = createSelector(
       reasonsWhyNotReady.push('Missing prompt');
     }
 
-    if (isImageToImageEnabled && !initialImage) {
+    if (activeTabName === 'img2img' && !initialImage) {
       isReady = false;
       reasonsWhyNotReady.push('No initial image selected');
     }
@@ -64,10 +58,5 @@ export const readinessSelector = createSelector(
     // All good
     return { isReady, reasonsWhyNotReady };
   },
-  {
+  defaultSelectorOptions
-    memoizeOptions: {
-      equalityCheck: isEqual,
-      resultEqualityCheck: isEqual,
-    },
-  }
 );

invokeai/frontend/web/src/app/socketio/emitters.ts

@@ -1,209 +1,209 @@
-// import { AnyAction, Dispatch, MiddlewareAPI } from '@reduxjs/toolkit';
+import { AnyAction, Dispatch, MiddlewareAPI } from '@reduxjs/toolkit';
-// import * as InvokeAI from 'app/types/invokeai';
+import * as InvokeAI from 'app/types/invokeai';
-// import type { RootState } from 'app/store/store';
+import type { RootState } from 'app/store/store';
-// import {
+import {
-//   frontendToBackendParameters,
+  frontendToBackendParameters,
-//   FrontendToBackendParametersConfig,
+  FrontendToBackendParametersConfig,
-// } from 'common/util/parameterTranslation';
+} from 'common/util/parameterTranslation';
-// import dateFormat from 'dateformat';
+import dateFormat from 'dateformat';
-// import {
+import {
-//   GalleryCategory,
+  GalleryCategory,
-//   GalleryState,
+  GalleryState,
-//   removeImage,
+  removeImage,
-// } from 'features/gallery/store/gallerySlice';
+} from 'features/gallery/store/gallerySlice';
-// import {
+import {
-//   generationRequested,
+  generationRequested,
-//   modelChangeRequested,
+  modelChangeRequested,
-//   modelConvertRequested,
+  modelConvertRequested,
-//   modelMergingRequested,
+  modelMergingRequested,
-//   setIsProcessing,
+  setIsProcessing,
-// } from 'features/system/store/systemSlice';
+} from 'features/system/store/systemSlice';
-// import { InvokeTabName } from 'features/ui/store/tabMap';
+import { InvokeTabName } from 'features/ui/store/tabMap';
-// import { Socket } from 'socket.io-client';
+import { Socket } from 'socket.io-client';
 
-// /**
+/**
-//  * Returns an object containing all functions which use `socketio.emit()`.
+ * Returns an object containing all functions which use `socketio.emit()`.
-//  * i.e. those which make server requests.
+ * i.e. those which make server requests.
-//  */
+ */
-// const makeSocketIOEmitters = (
+const makeSocketIOEmitters = (
-//   store: MiddlewareAPI<Dispatch<AnyAction>, RootState>,
+  store: MiddlewareAPI<Dispatch<AnyAction>, RootState>,
-//   socketio: Socket
+  socketio: Socket
-// ) => {
+) => {
-//   // We need to dispatch actions to redux and get pieces of state from the store.
+  // We need to dispatch actions to redux and get pieces of state from the store.
-//   const { dispatch, getState } = store;
+  const { dispatch, getState } = store;
 
-//   return {
+  return {
-//     emitGenerateImage: (generationMode: InvokeTabName) => {
+    emitGenerateImage: (generationMode: InvokeTabName) => {
-//       dispatch(setIsProcessing(true));
+      dispatch(setIsProcessing(true));
 
-//       const state: RootState = getState();
+      const state: RootState = getState();
 
-//       const {
+      const {
-//         generation: generationState,
+        generation: generationState,
-//         postprocessing: postprocessingState,
+        postprocessing: postprocessingState,
-//         system: systemState,
+        system: systemState,
-//         canvas: canvasState,
+        canvas: canvasState,
-//       } = state;
+      } = state;
 
-//       const frontendToBackendParametersConfig: FrontendToBackendParametersConfig =
+      const frontendToBackendParametersConfig: FrontendToBackendParametersConfig =
-//         {
+        {
-//           generationMode,
+          generationMode,
-//           generationState,
+          generationState,
-//           postprocessingState,
+          postprocessingState,
-//           canvasState,
+          canvasState,
-//           systemState,
+          systemState,
-//         };
+        };
 
-//       dispatch(generationRequested());
+      dispatch(generationRequested());
 
-//       const { generationParameters, esrganParameters, facetoolParameters } =
+      const { generationParameters, esrganParameters, facetoolParameters } =
-//         frontendToBackendParameters(frontendToBackendParametersConfig);
+        frontendToBackendParameters(frontendToBackendParametersConfig);
 
-//       socketio.emit(
+      socketio.emit(
-//         'generateImage',
+        'generateImage',
-//         generationParameters,
+        generationParameters,
-//         esrganParameters,
+        esrganParameters,
-//         facetoolParameters
+        facetoolParameters
-//       );
+      );
 
-//       // we need to truncate the init_mask base64 else it takes up the whole log
+      // we need to truncate the init_mask base64 else it takes up the whole log
-//       // TODO: handle maintaining masks for reproducibility in future
+      // TODO: handle maintaining masks for reproducibility in future
-//       if (generationParameters.init_mask) {
+      if (generationParameters.init_mask) {
-//         generationParameters.init_mask = generationParameters.init_mask
+        generationParameters.init_mask = generationParameters.init_mask
-//           .substr(0, 64)
+          .substr(0, 64)
-//           .concat('...');
+          .concat('...');
-//       }
+      }
-//       if (generationParameters.init_img) {
+      if (generationParameters.init_img) {
-//         generationParameters.init_img = generationParameters.init_img
+        generationParameters.init_img = generationParameters.init_img
-//           .substr(0, 64)
+          .substr(0, 64)
-//           .concat('...');
+          .concat('...');
-//       }
+      }
 
-//       dispatch(
+      dispatch(
-//         addLogEntry({
+        addLogEntry({
-//           timestamp: dateFormat(new Date(), 'isoDateTime'),
+          timestamp: dateFormat(new Date(), 'isoDateTime'),
-//           message: `Image generation requested: ${JSON.stringify({
+          message: `Image generation requested: ${JSON.stringify({
-//             ...generationParameters,
+            ...generationParameters,
-//             ...esrganParameters,
+            ...esrganParameters,
-//             ...facetoolParameters,
+            ...facetoolParameters,
-//           })}`,
+          })}`,
-//         })
+        })
-//       );
+      );
-//     },
+    },
-//     emitRunESRGAN: (imageToProcess: InvokeAI._Image) => {
+    emitRunESRGAN: (imageToProcess: InvokeAI._Image) => {
-//       dispatch(setIsProcessing(true));
+      dispatch(setIsProcessing(true));
 
-//       const {
+      const {
-//         postprocessing: {
+        postprocessing: {
-//           upscalingLevel,
+          upscalingLevel,
-//           upscalingDenoising,
+          upscalingDenoising,
-//           upscalingStrength,
+          upscalingStrength,
-//         },
+        },
-//       } = getState();
+      } = getState();
 
-//       const esrganParameters = {
+      const esrganParameters = {
-//         upscale: [upscalingLevel, upscalingDenoising, upscalingStrength],
+        upscale: [upscalingLevel, upscalingDenoising, upscalingStrength],
-//       };
+      };
-//       socketio.emit('runPostprocessing', imageToProcess, {
+      socketio.emit('runPostprocessing', imageToProcess, {
-//         type: 'esrgan',
+        type: 'esrgan',
-//         ...esrganParameters,
+        ...esrganParameters,
-//       });
+      });
-//       dispatch(
+      dispatch(
-//         addLogEntry({
+        addLogEntry({
-//           timestamp: dateFormat(new Date(), 'isoDateTime'),
+          timestamp: dateFormat(new Date(), 'isoDateTime'),
-//           message: `ESRGAN upscale requested: ${JSON.stringify({
+          message: `ESRGAN upscale requested: ${JSON.stringify({
-//             file: imageToProcess.url,
+            file: imageToProcess.url,
-//             ...esrganParameters,
+            ...esrganParameters,
-//           })}`,
+          })}`,
-//         })
+        })
-//       );
+      );
-//     },
+    },
-//     emitRunFacetool: (imageToProcess: InvokeAI._Image) => {
+    emitRunFacetool: (imageToProcess: InvokeAI._Image) => {
-//       dispatch(setIsProcessing(true));
+      dispatch(setIsProcessing(true));
 
-//       const {
+      const {
-//         postprocessing: { facetoolType, facetoolStrength, codeformerFidelity },
+        postprocessing: { facetoolType, facetoolStrength, codeformerFidelity },
-//       } = getState();
+      } = getState();
 
-//       const facetoolParameters: Record<string, unknown> = {
+      const facetoolParameters: Record<string, unknown> = {
-//         facetool_strength: facetoolStrength,
+        facetool_strength: facetoolStrength,
-//       };
+      };
 
-//       if (facetoolType === 'codeformer') {
+      if (facetoolType === 'codeformer') {
-//         facetoolParameters.codeformer_fidelity = codeformerFidelity;
+        facetoolParameters.codeformer_fidelity = codeformerFidelity;
-//       }
+      }
 
-//       socketio.emit('runPostprocessing', imageToProcess, {
+      socketio.emit('runPostprocessing', imageToProcess, {
-//         type: facetoolType,
+        type: facetoolType,
-//         ...facetoolParameters,
+        ...facetoolParameters,
-//       });
+      });
-//       dispatch(
+      dispatch(
-//         addLogEntry({
+        addLogEntry({
-//           timestamp: dateFormat(new Date(), 'isoDateTime'),
+          timestamp: dateFormat(new Date(), 'isoDateTime'),
-//           message: `Face restoration (${facetoolType}) requested: ${JSON.stringify(
+          message: `Face restoration (${facetoolType}) requested: ${JSON.stringify(
-//             {
+            {
-//               file: imageToProcess.url,
+              file: imageToProcess.url,
-//               ...facetoolParameters,
+              ...facetoolParameters,
-//             }
+            }
-//           )}`,
+          )}`,
-//         })
+        })
-//       );
+      );
-//     },
+    },
-//     emitDeleteImage: (imageToDelete: InvokeAI._Image) => {
+    emitDeleteImage: (imageToDelete: InvokeAI._Image) => {
-//       const { url, uuid, category, thumbnail } = imageToDelete;
+      const { url, uuid, category, thumbnail } = imageToDelete;
-//       dispatch(removeImage(imageToDelete));
+      dispatch(removeImage(imageToDelete));
-//       socketio.emit('deleteImage', url, thumbnail, uuid, category);
+      socketio.emit('deleteImage', url, thumbnail, uuid, category);
-//     },
+    },
-//     emitRequestImages: (category: GalleryCategory) => {
+    emitRequestImages: (category: GalleryCategory) => {
-//       const gallery: GalleryState = getState().gallery;
+      const gallery: GalleryState = getState().gallery;
-//       const { earliest_mtime } = gallery.categories[category];
+      const { earliest_mtime } = gallery.categories[category];
-//       socketio.emit('requestImages', category, earliest_mtime);
+      socketio.emit('requestImages', category, earliest_mtime);
-//     },
+    },
-//     emitRequestNewImages: (category: GalleryCategory) => {
+    emitRequestNewImages: (category: GalleryCategory) => {
-//       const gallery: GalleryState = getState().gallery;
+      const gallery: GalleryState = getState().gallery;
-//       const { latest_mtime } = gallery.categories[category];
+      const { latest_mtime } = gallery.categories[category];
-//       socketio.emit('requestLatestImages', category, latest_mtime);
+      socketio.emit('requestLatestImages', category, latest_mtime);
-//     },
+    },
-//     emitCancelProcessing: () => {
+    emitCancelProcessing: () => {
-//       socketio.emit('cancel');
+      socketio.emit('cancel');
-//     },
+    },
-//     emitRequestSystemConfig: () => {
+    emitRequestSystemConfig: () => {
-//       socketio.emit('requestSystemConfig');
+      socketio.emit('requestSystemConfig');
-//     },
+    },
-//     emitSearchForModels: (modelFolder: string) => {
+    emitSearchForModels: (modelFolder: string) => {
-//       socketio.emit('searchForModels', modelFolder);
+      socketio.emit('searchForModels', modelFolder);
-//     },
+    },
-//     emitAddNewModel: (modelConfig: InvokeAI.InvokeModelConfigProps) => {
+    emitAddNewModel: (modelConfig: InvokeAI.InvokeModelConfigProps) => {
-//       socketio.emit('addNewModel', modelConfig);
+      socketio.emit('addNewModel', modelConfig);
-//     },
+    },
-//     emitDeleteModel: (modelName: string) => {
+    emitDeleteModel: (modelName: string) => {
-//       socketio.emit('deleteModel', modelName);
+      socketio.emit('deleteModel', modelName);
-//     },
+    },
-//     emitConvertToDiffusers: (
+    emitConvertToDiffusers: (
-//       modelToConvert: InvokeAI.InvokeModelConversionProps
+      modelToConvert: InvokeAI.InvokeModelConversionProps
-//     ) => {
+    ) => {
-//       dispatch(modelConvertRequested());
+      dispatch(modelConvertRequested());
-//       socketio.emit('convertToDiffusers', modelToConvert);
+      socketio.emit('convertToDiffusers', modelToConvert);
-//     },
+    },
-//     emitMergeDiffusersModels: (
+    emitMergeDiffusersModels: (
-//       modelMergeInfo: InvokeAI.InvokeModelMergingProps
+      modelMergeInfo: InvokeAI.InvokeModelMergingProps
-//     ) => {
+    ) => {
-//       dispatch(modelMergingRequested());
+      dispatch(modelMergingRequested());
-//       socketio.emit('mergeDiffusersModels', modelMergeInfo);
+      socketio.emit('mergeDiffusersModels', modelMergeInfo);
-//     },
+    },
-//     emitRequestModelChange: (modelName: string) => {
+    emitRequestModelChange: (modelName: string) => {
-//       dispatch(modelChangeRequested());
+      dispatch(modelChangeRequested());
-//       socketio.emit('requestModelChange', modelName);
+      socketio.emit('requestModelChange', modelName);
-//     },
+    },
-//     emitSaveStagingAreaImageToGallery: (url: string) => {
+    emitSaveStagingAreaImageToGallery: (url: string) => {
-//       socketio.emit('requestSaveStagingAreaImageToGallery', url);
+      socketio.emit('requestSaveStagingAreaImageToGallery', url);
-//     },
+    },
-//     emitRequestEmptyTempFolder: () => {
+    emitRequestEmptyTempFolder: () => {
-//       socketio.emit('requestEmptyTempFolder');
+      socketio.emit('requestEmptyTempFolder');
-//     },
+    },
-//   };
+  };
-// };
+};
 
-// export default makeSocketIOEmitters;
+export default makeSocketIOEmitters;
 
 export default {};

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

@@ -0,0 +1,4 @@
+import { createAction } from '@reduxjs/toolkit';
+import { InvokeTabName } from 'features/ui/store/tabMap';
+
+export const userInvoked = createAction<InvokeTabName>('app/userInvoked');

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

@@ -0,0 +1,8 @@
+export const LOCALSTORAGE_KEYS = [
+  'chakra-ui-color-mode',
+  'i18nextLng',
+  'ROARR_FILTER',
+  'ROARR_LOG',
+];
+
+export const LOCALSTORAGE_PREFIX = '@@invokeai-';

invokeai/frontend/web/src/app/store/enhancers/reduxRemember/serialize.ts

@@ -0,0 +1,36 @@
+import { canvasPersistDenylist } from 'features/canvas/store/canvasPersistDenylist';
+import { galleryPersistDenylist } from 'features/gallery/store/galleryPersistDenylist';
+import { resultsPersistDenylist } from 'features/gallery/store/resultsPersistDenylist';
+import { uploadsPersistDenylist } from 'features/gallery/store/uploadsPersistDenylist';
+import { lightboxPersistDenylist } from 'features/lightbox/store/lightboxPersistDenylist';
+import { nodesPersistDenylist } from 'features/nodes/store/nodesPersistDenylist';
+import { generationPersistDenylist } from 'features/parameters/store/generationPersistDenylist';
+import { postprocessingPersistDenylist } from 'features/parameters/store/postprocessingPersistDenylist';
+import { modelsPersistDenylist } from 'features/system/store/modelsPersistDenylist';
+import { systemPersistDenylist } from 'features/system/store/systemPersistDenylist';
+import { uiPersistDenylist } from 'features/ui/store/uiPersistDenylist';
+import { omit } from 'lodash-es';
+import { SerializeFunction } from 'redux-remember';
+
+const serializationDenylist: {
+  [key: string]: string[];
+} = {
+  canvas: canvasPersistDenylist,
+  gallery: galleryPersistDenylist,
+  generation: generationPersistDenylist,
+  lightbox: lightboxPersistDenylist,
+  models: modelsPersistDenylist,
+  nodes: nodesPersistDenylist,
+  postprocessing: postprocessingPersistDenylist,
+  results: resultsPersistDenylist,
+  system: systemPersistDenylist,
+  // config: configPersistDenyList,
+  ui: uiPersistDenylist,
+  uploads: uploadsPersistDenylist,
+  // hotkeys: hotkeysPersistDenylist,
+};
+
+export const serialize: SerializeFunction = (data, key) => {
+  const result = omit(data, serializationDenylist[key]);
+  return JSON.stringify(result);
+};

invokeai/frontend/web/src/app/store/enhancers/reduxRemember/unserialize.ts

@@ -0,0 +1,38 @@
+import { initialCanvasState } from 'features/canvas/store/canvasSlice';
+import { initialGalleryState } from 'features/gallery/store/gallerySlice';
+import { initialResultsState } from 'features/gallery/store/resultsSlice';
+import { initialUploadsState } from 'features/gallery/store/uploadsSlice';
+import { initialLightboxState } from 'features/lightbox/store/lightboxSlice';
+import { initialNodesState } from 'features/nodes/store/nodesSlice';
+import { initialGenerationState } from 'features/parameters/store/generationSlice';
+import { initialPostprocessingState } from 'features/parameters/store/postprocessingSlice';
+import { initialConfigState } from 'features/system/store/configSlice';
+import { initialModelsState } from 'features/system/store/modelSlice';
+import { initialSystemState } from 'features/system/store/systemSlice';
+import { initialHotkeysState } from 'features/ui/store/hotkeysSlice';
+import { initialUIState } from 'features/ui/store/uiSlice';
+import { defaultsDeep } from 'lodash-es';
+import { UnserializeFunction } from 'redux-remember';
+
+const initialStates: {
+  [key: string]: any;
+} = {
+  canvas: initialCanvasState,
+  gallery: initialGalleryState,
+  generation: initialGenerationState,
+  lightbox: initialLightboxState,
+  models: initialModelsState,
+  nodes: initialNodesState,
+  postprocessing: initialPostprocessingState,
+  results: initialResultsState,
+  system: initialSystemState,
+  config: initialConfigState,
+  ui: initialUIState,
+  uploads: initialUploadsState,
+  hotkeys: initialHotkeysState,
+};
+
+export const unserialize: UnserializeFunction = (data, key) => {
+  const result = defaultsDeep(JSON.parse(data), initialStates[key]);
+  return result;
+};

invokeai/frontend/web/src/app/store/middleware/devtools/actionSanitizer.ts

@@ -0,0 +1,30 @@
+import { AnyAction } from '@reduxjs/toolkit';
+import { isAnyGraphBuilt } from 'features/nodes/store/actions';
+import { forEach } from 'lodash-es';
+import { Graph } from 'services/api';
+
+export const actionSanitizer = <A extends AnyAction>(action: A): A => {
+  if (isAnyGraphBuilt(action)) {
+    if (action.payload.nodes) {
+      const sanitizedNodes: Graph['nodes'] = {};
+
+      // Sanitize nodes as needed
+      forEach(action.payload.nodes, (node, key) => {
+        // Don't log the whole freaking dataURL
+        if (node.type === 'dataURL_image') {
+          const { dataURL, ...rest } = node;
+          sanitizedNodes[key] = { ...rest, dataURL: '<dataURL>' };
+        } else {
+          sanitizedNodes[key] = { ...node };
+        }
+      });
+
+      return {
+        ...action,
+        payload: { ...action.payload, nodes: sanitizedNodes },
+      };
+    }
+  }
+
+  return action;
+};

invokeai/frontend/web/src/app/store/middleware/devtools/actionsDenylist.ts

@@ -0,0 +1,11 @@
+export const actionsDenylist = [
+  'canvas/setCursorPosition',
+  'canvas/setStageCoordinates',
+  'canvas/setStageScale',
+  'canvas/setIsDrawing',
+  'canvas/setBoundingBoxCoordinates',
+  'canvas/setBoundingBoxDimensions',
+  'canvas/setIsDrawing',
+  'canvas/addPointToCurrentLine',
+  'socket/generatorProgress',
+];

invokeai/frontend/web/src/app/store/middleware/devtools/stateSanitizer.ts

@@ -0,0 +1,3 @@
+export const stateSanitizer = <S>(state: S): S => {
+  return state;
+};

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

@@ -0,0 +1,45 @@
+import {
+  createListenerMiddleware,
+  addListener,
+  ListenerEffect,
+  AnyAction,
+} from '@reduxjs/toolkit';
+import type { TypedStartListening, TypedAddListener } from '@reduxjs/toolkit';
+
+import type { RootState, AppDispatch } from '../../store';
+import { addInitialImageSelectedListener } from './listeners/initialImageSelected';
+import { addImageResultReceivedListener } from './listeners/invocationComplete';
+import { addImageUploadedListener } from './listeners/imageUploaded';
+import { addRequestedImageDeletionListener } from './listeners/imageDeleted';
+import { addUserInvokedCanvasListener } from './listeners/userInvokedCanvas';
+import { addUserInvokedNodesListener } from './listeners/userInvokedNodes';
+import { addUserInvokedTextToImageListener } from './listeners/userInvokedTextToImage';
+import { addUserInvokedImageToImageListener } from './listeners/userInvokedImageToImage';
+
+export const listenerMiddleware = createListenerMiddleware();
+
+export type AppStartListening = TypedStartListening<RootState, AppDispatch>;
+
+export const startAppListening =
+  listenerMiddleware.startListening as AppStartListening;
+
+export const addAppListener = addListener as TypedAddListener<
+  RootState,
+  AppDispatch
+>;
+
+export type AppListenerEffect = ListenerEffect<
+  AnyAction,
+  RootState,
+  AppDispatch
+>;
+
+addImageUploadedListener();
+addInitialImageSelectedListener();
+addImageResultReceivedListener();
+addRequestedImageDeletionListener();
+
+addUserInvokedCanvasListener();
+addUserInvokedNodesListener();
+addUserInvokedTextToImageListener();
+addUserInvokedImageToImageListener();

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

@@ -0,0 +1,31 @@
+import { canvasGraphBuilt } from 'features/nodes/store/actions';
+import { startAppListening } from '..';
+import {
+  canvasSessionIdChanged,
+  stagingAreaInitialized,
+} from 'features/canvas/store/canvasSlice';
+import { sessionInvoked } from 'services/thunks/session';
+
+export const addCanvasGraphBuiltListener = () =>
+  startAppListening({
+    actionCreator: canvasGraphBuilt,
+    effect: async (action, { dispatch, getState, take }) => {
+      const [{ meta }] = await take(sessionInvoked.fulfilled.match);
+      const { sessionId } = meta.arg;
+      const state = getState();
+
+      if (!state.canvas.layerState.stagingArea.boundingBox) {
+        dispatch(
+          stagingAreaInitialized({
+            sessionId,
+            boundingBox: {
+              ...state.canvas.boundingBoxCoordinates,
+              ...state.canvas.boundingBoxDimensions,
+            },
+          })
+        );
+      }
+
+      dispatch(canvasSessionIdChanged(sessionId));
+    },
+  });

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

@@ -0,0 +1,59 @@
+import { requestedImageDeletion } from 'features/gallery/store/actions';
+import { startAppListening } from '..';
+import { imageDeleted } from 'services/thunks/image';
+import { log } from 'app/logging/useLogger';
+import { clamp } from 'lodash-es';
+import { imageSelected } from 'features/gallery/store/gallerySlice';
+
+const moduleLog = log.child({ namespace: 'addRequestedImageDeletionListener' });
+
+export const addRequestedImageDeletionListener = () => {
+  startAppListening({
+    actionCreator: requestedImageDeletion,
+    effect: (action, { dispatch, getState }) => {
+      const image = action.payload;
+      if (!image) {
+        moduleLog.warn('No image provided');
+        return;
+      }
+
+      const { name, type } = image;
+
+      if (type !== 'uploads' && type !== 'results') {
+        moduleLog.warn({ data: image }, `Invalid image type ${type}`);
+        return;
+      }
+
+      const selectedImageName = getState().gallery.selectedImage?.name;
+
+      if (selectedImageName === name) {
+        const allIds = getState()[type].ids;
+        const allEntities = getState()[type].entities;
+
+        const deletedImageIndex = allIds.findIndex(
+          (result) => result.toString() === name
+        );
+
+        const filteredIds = allIds.filter((id) => id.toString() !== name);
+
+        const newSelectedImageIndex = clamp(
+          deletedImageIndex,
+          0,
+          filteredIds.length - 1
+        );
+
+        const newSelectedImageId = filteredIds[newSelectedImageIndex];
+
+        const newSelectedImage = allEntities[newSelectedImageId];
+
+        if (newSelectedImageId) {
+          dispatch(imageSelected(newSelectedImage));
+        } else {
+          dispatch(imageSelected());
+        }
+      }
+
+      dispatch(imageDeleted({ imageName: name, imageType: type }));
+    },
+  });
+};

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

@@ -0,0 +1,25 @@
+import { deserializeImageResponse } from 'services/util/deserializeImageResponse';
+import { startAppListening } from '..';
+import { uploadAdded } from 'features/gallery/store/uploadsSlice';
+import { imageSelected } from 'features/gallery/store/gallerySlice';
+import { imageUploaded } from 'services/thunks/image';
+
+export const addImageUploadedListener = () => {
+  startAppListening({
+    predicate: (action): action is ReturnType<typeof imageUploaded.fulfilled> =>
+      imageUploaded.fulfilled.match(action) &&
+      action.payload.response.image_type !== 'intermediates',
+    effect: (action, { dispatch, getState }) => {
+      const { response } = action.payload;
+
+      const state = getState();
+      const image = deserializeImageResponse(response);
+
+      dispatch(uploadAdded(image));
+
+      if (state.gallery.shouldAutoSwitchToNewImages) {
+        dispatch(imageSelected(image));
+      }
+    },
+  });
+};

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

@@ -0,0 +1,54 @@
+import { initialImageChanged } from 'features/parameters/store/generationSlice';
+import { Image, isInvokeAIImage } from 'app/types/invokeai';
+import { selectResultsById } from 'features/gallery/store/resultsSlice';
+import { selectUploadsById } from 'features/gallery/store/uploadsSlice';
+import { makeToast } from 'features/system/hooks/useToastWatcher';
+import { t } from 'i18next';
+import { addToast } from 'features/system/store/systemSlice';
+import { startAppListening } from '..';
+import { initialImageSelected } from 'features/parameters/store/actions';
+
+export const addInitialImageSelectedListener = () => {
+  startAppListening({
+    actionCreator: initialImageSelected,
+    effect: (action, { getState, dispatch }) => {
+      if (!action.payload) {
+        dispatch(
+          addToast(
+            makeToast({ title: t('toast.imageNotLoadedDesc'), status: 'error' })
+          )
+        );
+        return;
+      }
+
+      if (isInvokeAIImage(action.payload)) {
+        dispatch(initialImageChanged(action.payload));
+        dispatch(addToast(makeToast(t('toast.sentToImageToImage'))));
+        return;
+      }
+
+      const { name, type } = action.payload;
+
+      let image: Image | undefined;
+      const state = getState();
+
+      if (type === 'results') {
+        image = selectResultsById(state, name);
+      } else if (type === 'uploads') {
+        image = selectUploadsById(state, name);
+      }
+
+      if (!image) {
+        dispatch(
+          addToast(
+            makeToast({ title: t('toast.imageNotLoadedDesc'), status: 'error' })
+          )
+        );
+        return;
+      }
+
+      dispatch(initialImageChanged(image));
+      dispatch(addToast(makeToast(t('toast.sentToImageToImage'))));
+    },
+  });
+};

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

@@ -0,0 +1,88 @@
+import { invocationComplete } from 'services/events/actions';
+import { isImageOutput } from 'services/types/guards';
+import {
+  buildImageUrls,
+  extractTimestampFromImageName,
+} from 'services/util/deserializeImageField';
+import { Image } from 'app/types/invokeai';
+import { resultAdded } from 'features/gallery/store/resultsSlice';
+import { imageReceived, thumbnailReceived } from 'services/thunks/image';
+import { startAppListening } from '..';
+import { imageSelected } from 'features/gallery/store/gallerySlice';
+import { addImageToStagingArea } from 'features/canvas/store/canvasSlice';
+
+const nodeDenylist = ['dataURL_image'];
+
+export const addImageResultReceivedListener = () => {
+  startAppListening({
+    predicate: (action) => {
+      if (
+        invocationComplete.match(action) &&
+        isImageOutput(action.payload.data.result)
+      ) {
+        return true;
+      }
+      return false;
+    },
+    effect: (action, { getState, dispatch }) => {
+      if (!invocationComplete.match(action)) {
+        return;
+      }
+
+      const { data, shouldFetchImages } = action.payload;
+      const { result, node, graph_execution_state_id } = data;
+
+      if (isImageOutput(result) && !nodeDenylist.includes(node.type)) {
+        const name = result.image.image_name;
+        const type = result.image.image_type;
+        const state = getState();
+
+        // if we need to refetch, set URLs to placeholder for now
+        const { url, thumbnail } = shouldFetchImages
+          ? { url: '', thumbnail: '' }
+          : buildImageUrls(type, name);
+
+        const timestamp = extractTimestampFromImageName(name);
+
+        const image: Image = {
+          name,
+          type,
+          url,
+          thumbnail,
+          metadata: {
+            created: timestamp,
+            width: result.width,
+            height: result.height,
+            invokeai: {
+              session_id: graph_execution_state_id,
+              ...(node ? { node } : {}),
+            },
+          },
+        };
+
+        dispatch(resultAdded(image));
+
+        if (state.gallery.shouldAutoSwitchToNewImages) {
+          dispatch(imageSelected(image));
+        }
+
+        if (state.config.shouldFetchImages) {
+          dispatch(imageReceived({ imageName: name, imageType: type }));
+          dispatch(
+            thumbnailReceived({
+              thumbnailName: name,
+              thumbnailType: type,
+            })
+          );
+        }
+
+        if (
+          graph_execution_state_id ===
+          state.canvas.layerState.stagingArea.sessionId
+        ) {
+          dispatch(addImageToStagingArea(image));
+        }
+      }
+    },
+  });
+};

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

@@ -0,0 +1,126 @@
+import { startAppListening } from '..';
+import { sessionCreated, sessionInvoked } from 'services/thunks/session';
+import { buildCanvasGraphAndBlobs } from 'features/nodes/util/graphBuilders/buildCanvasGraph';
+import { log } from 'app/logging/useLogger';
+import { canvasGraphBuilt } from 'features/nodes/store/actions';
+import { imageUploaded } from 'services/thunks/image';
+import { v4 as uuidv4 } from 'uuid';
+import { Graph } from 'services/api';
+import {
+  canvasSessionIdChanged,
+  stagingAreaInitialized,
+} from 'features/canvas/store/canvasSlice';
+import { userInvoked } from 'app/store/actions';
+
+const moduleLog = log.child({ namespace: 'invoke' });
+
+export const addUserInvokedCanvasListener = () => {
+  startAppListening({
+    predicate: (action): action is ReturnType<typeof userInvoked> =>
+      userInvoked.match(action) && action.payload === 'unifiedCanvas',
+    effect: async (action, { getState, dispatch, take }) => {
+      const state = getState();
+
+      const data = await buildCanvasGraphAndBlobs(state);
+
+      if (!data) {
+        moduleLog.error('Problem building graph');
+        return;
+      }
+
+      const {
+        rangeNode,
+        iterateNode,
+        baseNode,
+        edges,
+        baseBlob,
+        maskBlob,
+        generationMode,
+      } = data;
+
+      const baseFilename = `${uuidv4()}.png`;
+      const maskFilename = `${uuidv4()}.png`;
+
+      dispatch(
+        imageUploaded({
+          imageType: 'intermediates',
+          formData: {
+            file: new File([baseBlob], baseFilename, { type: 'image/png' }),
+          },
+        })
+      );
+
+      if (baseNode.type === 'img2img' || baseNode.type === 'inpaint') {
+        const [{ payload: basePayload }] = await take(
+          (action): action is ReturnType<typeof imageUploaded.fulfilled> =>
+            imageUploaded.fulfilled.match(action) &&
+            action.meta.arg.formData.file.name === baseFilename
+        );
+
+        const { image_name: baseName, image_type: baseType } =
+          basePayload.response;
+
+        baseNode.image = {
+          image_name: baseName,
+          image_type: baseType,
+        };
+      }
+
+      if (baseNode.type === 'inpaint') {
+        dispatch(
+          imageUploaded({
+            imageType: 'intermediates',
+            formData: {
+              file: new File([maskBlob], maskFilename, { type: 'image/png' }),
+            },
+          })
+        );
+
+        const [{ payload: maskPayload }] = await take(
+          (action): action is ReturnType<typeof imageUploaded.fulfilled> =>
+            imageUploaded.fulfilled.match(action) &&
+            action.meta.arg.formData.file.name === maskFilename
+        );
+
+        const { image_name: maskName, image_type: maskType } =
+          maskPayload.response;
+
+        baseNode.mask = {
+          image_name: maskName,
+          image_type: maskType,
+        };
+      }
+
+      // Assemble!
+      const nodes: Graph['nodes'] = {
+        [rangeNode.id]: rangeNode,
+        [iterateNode.id]: iterateNode,
+        [baseNode.id]: baseNode,
+      };
+
+      const graph = { nodes, edges };
+
+      dispatch(canvasGraphBuilt(graph));
+      moduleLog({ data: graph }, 'Canvas graph built');
+
+      dispatch(sessionCreated({ graph }));
+
+      const [{ meta }] = await take(sessionInvoked.fulfilled.match);
+      const { sessionId } = meta.arg;
+
+      if (!state.canvas.layerState.stagingArea.boundingBox) {
+        dispatch(
+          stagingAreaInitialized({
+            sessionId,
+            boundingBox: {
+              ...state.canvas.boundingBoxCoordinates,
+              ...state.canvas.boundingBoxDimensions,
+            },
+          })
+        );
+      }
+
+      dispatch(canvasSessionIdChanged(sessionId));
+    },
+  });
+};

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

@@ -0,0 +1,24 @@
+import { startAppListening } from '..';
+import { buildImageToImageGraph } from 'features/nodes/util/graphBuilders/buildImageToImageGraph';
+import { sessionCreated } from 'services/thunks/session';
+import { log } from 'app/logging/useLogger';
+import { imageToImageGraphBuilt } from 'features/nodes/store/actions';
+import { userInvoked } from 'app/store/actions';
+
+const moduleLog = log.child({ namespace: 'invoke' });
+
+export const addUserInvokedImageToImageListener = () => {
+  startAppListening({
+    predicate: (action): action is ReturnType<typeof userInvoked> =>
+      userInvoked.match(action) && action.payload === 'img2img',
+    effect: (action, { getState, dispatch }) => {
+      const state = getState();
+
+      const graph = buildImageToImageGraph(state);
+      dispatch(imageToImageGraphBuilt(graph));
+      moduleLog({ data: graph }, 'Image to Image graph built');
+
+      dispatch(sessionCreated({ graph }));
+    },
+  });
+};

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

@@ -0,0 +1,24 @@
+import { startAppListening } from '..';
+import { sessionCreated } from 'services/thunks/session';
+import { buildNodesGraph } from 'features/nodes/util/graphBuilders/buildNodesGraph';
+import { log } from 'app/logging/useLogger';
+import { nodesGraphBuilt } from 'features/nodes/store/actions';
+import { userInvoked } from 'app/store/actions';
+
+const moduleLog = log.child({ namespace: 'invoke' });
+
+export const addUserInvokedNodesListener = () => {
+  startAppListening({
+    predicate: (action): action is ReturnType<typeof userInvoked> =>
+      userInvoked.match(action) && action.payload === 'nodes',
+    effect: (action, { getState, dispatch }) => {
+      const state = getState();
+
+      const graph = buildNodesGraph(state);
+      dispatch(nodesGraphBuilt(graph));
+      moduleLog({ data: graph }, 'Nodes graph built');
+
+      dispatch(sessionCreated({ graph }));
+    },
+  });
+};

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

@@ -0,0 +1,24 @@
+import { startAppListening } from '..';
+import { buildTextToImageGraph } from 'features/nodes/util/graphBuilders/buildTextToImageGraph';
+import { sessionCreated } from 'services/thunks/session';
+import { log } from 'app/logging/useLogger';
+import { textToImageGraphBuilt } from 'features/nodes/store/actions';
+import { userInvoked } from 'app/store/actions';
+
+const moduleLog = log.child({ namespace: 'invoke' });
+
+export const addUserInvokedTextToImageListener = () => {
+  startAppListening({
+    predicate: (action): action is ReturnType<typeof userInvoked> =>
+      userInvoked.match(action) && action.payload === 'txt2img',
+    effect: (action, { getState, dispatch }) => {
+      const state = getState();
+
+      const graph = buildTextToImageGraph(state);
+      dispatch(textToImageGraphBuilt(graph));
+      moduleLog({ data: graph }, 'Text to Image graph built');
+
+      dispatch(sessionCreated({ graph }));
+    },
+  });
+};

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

@@ -1,4 +0,0 @@
-import { store } from 'app/store/store';
-import { persistStore } from 'redux-persist';
-
-export const persistor = persistStore(store);

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

@@ -1,9 +1,12 @@
-import { combineReducers, configureStore } from '@reduxjs/toolkit';
+import {
+  AnyAction,
+  ThunkDispatch,
+  combineReducers,
+  configureStore,
+} from '@reduxjs/toolkit';
 
-import { persistReducer } from 'redux-persist';
+import { rememberReducer, rememberEnhancer } from 'redux-remember';
-import storage from 'redux-persist/lib/storage'; // defaults to localStorage for web
 import dynamicMiddlewares from 'redux-dynamic-middlewares';
-import { getPersistConfig } from 'redux-deep-persist';
 
 import canvasReducer from 'features/canvas/store/canvasSlice';
 import galleryReducer from 'features/gallery/store/gallerySlice';
@@ -19,33 +22,17 @@ import hotkeysReducer from 'features/ui/store/hotkeysSlice';
 import modelsReducer from 'features/system/store/modelSlice';
 import nodesReducer from 'features/nodes/store/nodesSlice';
 
-import { canvasDenylist } from 'features/canvas/store/canvasPersistDenylist';
+import { listenerMiddleware } from './middleware/listenerMiddleware';
-import { galleryDenylist } from 'features/gallery/store/galleryPersistDenylist';
-import { generationDenylist } from 'features/parameters/store/generationPersistDenylist';
-import { lightboxDenylist } from 'features/lightbox/store/lightboxPersistDenylist';
-import { modelsDenylist } from 'features/system/store/modelsPersistDenylist';
-import { nodesDenylist } from 'features/nodes/store/nodesPersistDenylist';
-import { postprocessingDenylist } from 'features/parameters/store/postprocessingPersistDenylist';
-import { systemDenylist } from 'features/system/store/systemPersistDenylist';
-import { uiDenylist } from 'features/ui/store/uiPersistDenylist';
-import { resultsDenylist } from 'features/gallery/store/resultsPersistDenylist';
-import { uploadsDenylist } from 'features/gallery/store/uploadsPersistDenylist';
 
-/**
+import { actionSanitizer } from './middleware/devtools/actionSanitizer';
- * redux-persist provides an easy and reliable way to persist state across reloads.
+import { stateSanitizer } from './middleware/devtools/stateSanitizer';
- *
+import { actionsDenylist } from './middleware/devtools/actionsDenylist';
- * While we definitely want generation parameters to be persisted, there are a number
- * of things we do *not* want to be persisted across reloads:
- *   - Gallery/selected image (user may add/delete images from disk between page loads)
- *   - Connection/processing status
- *   - Availability of external libraries like ESRGAN/GFPGAN
- *
- * These can be denylisted in redux-persist.
- *
- * The necesssary nested persistors with denylists are configured below.
- */
 
-const rootReducer = combineReducers({
+import { serialize } from './enhancers/reduxRemember/serialize';
+import { unserialize } from './enhancers/reduxRemember/unserialize';
+import { LOCALSTORAGE_PREFIX } from './constants';
+
+const allReducers = {
   canvas: canvasReducer,
   gallery: galleryReducer,
   generation: generationReducer,
@@ -59,65 +46,54 @@ const rootReducer = combineReducers({
   ui: uiReducer,
   uploads: uploadsReducer,
   hotkeys: hotkeysReducer,
-});
+};
 
-const rootPersistConfig = getPersistConfig({
+const rootReducer = combineReducers(allReducers);
-  key: 'root',
-  storage,
-  rootReducer,
-  blacklist: [
-    ...canvasDenylist,
-    ...galleryDenylist,
-    ...generationDenylist,
-    ...lightboxDenylist,
-    ...modelsDenylist,
-    ...nodesDenylist,
-    ...postprocessingDenylist,
-    // ...resultsDenylist,
-    'results',
-    ...systemDenylist,
-    ...uiDenylist,
-    // ...uploadsDenylist,
-    'uploads',
-    'hotkeys',
-    'config',
-  ],
-});
 
-const persistedReducer = persistReducer(rootPersistConfig, rootReducer);
+const rememberedRootReducer = rememberReducer(rootReducer);
 
-// TODO: rip the old middleware out when nodes is complete
+const rememberedKeys: (keyof typeof allReducers)[] = [
-// export function buildMiddleware() {
+  'canvas',
-//   if (import.meta.env.MODE === 'nodes' || import.meta.env.MODE === 'package') {
+  'gallery',
-//     return socketMiddleware();
+  'generation',
-//   } else {
+  'lightbox',
-//     return socketioMiddleware();
+  // 'models',
-//   }
+  'nodes',
-// }
+  'postprocessing',
+  'system',
+  'ui',
+  // 'hotkeys',
+  // 'results',
+  // 'uploads',
+  // 'config',
+];
 
 export const store = configureStore({
-  reducer: persistedReducer,
+  reducer: rememberedRootReducer,
+  enhancers: [
+    rememberEnhancer(window.localStorage, rememberedKeys, {
+      persistDebounce: 300,
+      serialize,
+      unserialize,
+      prefix: LOCALSTORAGE_PREFIX,
+    }),
+  ],
   middleware: (getDefaultMiddleware) =>
     getDefaultMiddleware({
       immutableCheck: false,
       serializableCheck: false,
-    }).concat(dynamicMiddlewares),
+    })
+      .concat(dynamicMiddlewares)
+      .prepend(listenerMiddleware.middleware),
   devTools: {
-    // Uncommenting these very rapidly called actions makes the redux dev tools output much more readable
+    actionsDenylist,
-    actionsDenylist: [
+    actionSanitizer,
-      'canvas/setCursorPosition',
+    stateSanitizer,
-      'canvas/setStageCoordinates',
+    trace: true,
-      'canvas/setStageScale',
-      'canvas/setIsDrawing',
-      'canvas/setBoundingBoxCoordinates',
-      'canvas/setBoundingBoxDimensions',
-      'canvas/setIsDrawing',
-      'canvas/addPointToCurrentLine',
-      'socket/generatorProgress',
-    ],
   },
 });
 
 export type AppGetState = typeof store.getState;
 export type RootState = ReturnType<typeof store.getState>;
+export type AppThunkDispatch = ThunkDispatch<RootState, any, AnyAction>;
 export type AppDispatch = typeof store.dispatch;

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

@@ -1,6 +1,6 @@
 import { TypedUseSelectorHook, useDispatch, useSelector } from 'react-redux';
-import { AppDispatch, RootState } from 'app/store/store';
+import { AppThunkDispatch, RootState } from 'app/store/store';
 
 // Use throughout your app instead of plain `useDispatch` and `useSelector`
-export const useAppDispatch: () => AppDispatch = useDispatch;
+export const useAppDispatch = () => useDispatch<AppThunkDispatch>();
 export const useAppSelector: TypedUseSelectorHook<RootState> = useSelector;

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

@@ -0,0 +1,7 @@
+import { isEqual } from 'lodash-es';
+
+export const defaultSelectorOptions = {
+  memoizeOptions: {
+    resultEqualityCheck: isEqual,
+  },
+};

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

@@ -12,12 +12,10 @@
  * 'gfpgan'.
  */
 
-import { GalleryCategory } from 'features/gallery/store/gallerySlice';
+import { SelectedImage } from 'features/parameters/store/actions';
-import { FacetoolType } from 'features/parameters/store/postprocessingSlice';
 import { InvokeTabName } from 'features/ui/store/tabMap';
 import { IRect } from 'konva/lib/types';
 import { ImageResponseMetadata, ImageType } from 'services/api';
-import { AnyInvocation } from 'services/events/types';
 import { O } from 'ts-toolbelt';
 
 /**
@@ -49,15 +47,20 @@ export type CommonGeneratedImageMetadata = {
   postprocessing: null | Array<ESRGANMetadata | FacetoolMetadata>;
   sampler:
     | 'ddim'
-    | 'k_dpm_2_a'
+    | 'ddpm'
-    | 'k_dpm_2'
+    | 'deis'
-    | 'k_dpmpp_2_a'
+    | 'lms'
-    | 'k_dpmpp_2'
+    | 'pndm'
-    | 'k_euler_a'
+    | 'heun'
-    | 'k_euler'
+    | 'euler'
-    | 'k_heun'
+    | 'euler_k'
-    | 'k_lms'
+    | 'euler_a'
-    | 'plms';
+    | 'kdpm_2'
+    | 'kdpm_2_a'
+    | 'dpmpp_2s'
+    | 'dpmpp_2m'
+    | 'dpmpp_2m_k'
+    | 'unipc';
   prompt: Prompt;
   seed: number;
   variations: SeedWeights;
@@ -126,6 +129,14 @@ export type Image = {
   metadata: ImageResponseMetadata;
 };
 
+export const isInvokeAIImage = (obj: Image | SelectedImage): obj is Image => {
+  if ('url' in obj && 'thumbnail' in obj) {
+    return true;
+  }
+
+  return false;
+};
+
 /**
  * Types related to the system status.
  */
@@ -270,7 +281,7 @@ export type FoundModelResponse = {
 
 // export type SystemConfigResponse = SystemConfig;
 
-export type ImageResultResponse = Omit<_Image, 'uuid'> & {
+export type ImageResultResponse = Omit<Image, 'uuid'> & {
   boundingBox?: IRect;
   generationMode: InvokeTabName;
 };
@@ -315,11 +326,11 @@ export type AppFeature =
 /**
  * A disable-able Stable Diffusion feature
  */
-export type StableDiffusionFeature =
+export type SDFeature =
-  | 'noiseConfig'
+  | 'noise'
-  | 'variations'
+  | 'variation'
   | 'symmetry'
-  | 'tiling'
+  | 'seamless'
   | 'hires';
 
 /**
@@ -337,6 +348,7 @@ export type AppConfig = {
   shouldFetchImages: boolean;
   disabledTabs: InvokeTabName[];
   disabledFeatures: AppFeature[];
+  disabledSDFeatures: SDFeature[];
   canRestoreDeletedImagesFromBin: boolean;
   sd: {
     iterations: {

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

@@ -0,0 +1,61 @@
+import { ChevronUpIcon } from '@chakra-ui/icons';
+import { Box, Collapse, Flex, Spacer, Switch } from '@chakra-ui/react';
+import { PropsWithChildren, memo } from 'react';
+
+export type IAIToggleCollapseProps = PropsWithChildren & {
+  label: string;
+  isOpen: boolean;
+  onToggle: () => void;
+  withSwitch?: boolean;
+};
+
+const IAICollapse = (props: IAIToggleCollapseProps) => {
+  const { label, isOpen, onToggle, children, withSwitch = false } = props;
+  return (
+    <Box>
+      <Flex
+        onClick={onToggle}
+        sx={{
+          alignItems: 'center',
+          p: 2,
+          px: 4,
+          borderTopRadius: 'base',
+          borderBottomRadius: isOpen ? 0 : 'base',
+          bg: isOpen ? 'base.750' : 'base.800',
+          color: 'base.100',
+          _hover: {
+            bg: isOpen ? 'base.700' : 'base.750',
+          },
+          fontSize: 'sm',
+          fontWeight: 600,
+          cursor: 'pointer',
+          transitionProperty: 'common',
+          transitionDuration: 'normal',
+          userSelect: 'none',
+        }}
+      >
+        {label}
+        <Spacer />
+        {withSwitch && <Switch isChecked={isOpen} pointerEvents="none" />}
+        {!withSwitch && (
+          <ChevronUpIcon
+            sx={{
+              w: '1rem',
+              h: '1rem',
+              transform: isOpen ? 'rotate(0deg)' : 'rotate(180deg)',
+              transitionProperty: 'common',
+              transitionDuration: 'normal',
+            }}
+          />
+        )}
+      </Flex>
+      <Collapse in={isOpen} animateOpacity>
+        <Box sx={{ p: 4, borderBottomRadius: 'base', bg: 'base.800' }}>
+          {children}
+        </Box>
+      </Collapse>
+    </Box>
+  );
+};
+
+export default memo(IAICollapse);

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

@@ -27,7 +27,7 @@ const IAIPopover = (props: IAIPopoverProps) => {
   return (
     <Popover isLazy={isLazy} {...rest}>
       <PopoverTrigger>{triggerComponent}</PopoverTrigger>
-      <PopoverContent>
+      <PopoverContent shadow="dark-lg">
         {hasArrow && <PopoverArrow />}
         {children}
       </PopoverContent>

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

@@ -0,0 +1,54 @@
+import { Badge, Flex } from '@chakra-ui/react';
+import { Image } from 'app/types/invokeai';
+import { isNumber, isString } from 'lodash-es';
+import { useMemo } from 'react';
+
+type ImageMetadataOverlayProps = {
+  image: Image;
+};
+
+const ImageMetadataOverlay = ({ image }: ImageMetadataOverlayProps) => {
+  const dimensions = useMemo(() => {
+    if (!isNumber(image.metadata?.width) || isNumber(!image.metadata?.height)) {
+      return;
+    }
+
+    return `${image.metadata?.width} × ${image.metadata?.height}`;
+  }, [image.metadata]);
+
+  const model = useMemo(() => {
+    if (!isString(image.metadata?.invokeai?.node?.model)) {
+      return;
+    }
+
+    return image.metadata?.invokeai?.node?.model;
+  }, [image.metadata]);
+
+  return (
+    <Flex
+      sx={{
+        pointerEvents: 'none',
+        flexDirection: 'column',
+        position: 'absolute',
+        top: 0,
+        right: 0,
+        p: 2,
+        alignItems: 'flex-end',
+        gap: 2,
+      }}
+    >
+      {dimensions && (
+        <Badge variant="solid" colorScheme="base">
+          {dimensions}
+        </Badge>
+      )}
+      {model && (
+        <Badge variant="solid" colorScheme="base">
+          {model}
+        </Badge>
+      )}
+    </Flex>
+  );
+};
+
+export default ImageMetadataOverlay;

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

@@ -7,7 +7,7 @@ import { useAppDispatch } from 'app/store/storeHooks';
 import { useCallback } from 'react';
 import { clearInitialImage } from 'features/parameters/store/generationSlice';
 
-const ImageToImageSettingsHeader = () => {
+const InitialImageButtons = () => {
   const dispatch = useAppDispatch();
   const { t } = useTranslation();
 
@@ -18,24 +18,19 @@ const ImageToImageSettingsHeader = () => {
   return (
     <Flex w="full" alignItems="center">
       <Text size="sm" fontWeight={500} color="base.300">
-        Image to Image
+        {t('parameters.initialImage')}
       </Text>
       <Spacer />
       <ButtonGroup>
         <IAIIconButton
-          size="sm"
           icon={<FaUndo />}
           aria-label={t('accessibility.reset')}
           onClick={handleResetInitialImage}
         />
-        <IAIIconButton
+        <IAIIconButton icon={<FaUpload />} aria-label={t('common.upload')} />
-          size="sm"
-          icon={<FaUpload />}
-          aria-label={t('common.upload')}
-        />
       </ButtonGroup>
     </Flex>
   );
 };
 
-export default ImageToImageSettingsHeader;
+export default InitialImageButtons;

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

@@ -1,36 +0,0 @@
-import { Badge, Box, Flex } from '@chakra-ui/react';
-import { Image } from 'app/types/invokeai';
-
-type ImageToImageOverlayProps = {
-  image: Image;
-};
-
-const ImageToImageOverlay = ({ image }: ImageToImageOverlayProps) => {
-  return (
-    <Box
-      sx={{
-        top: 0,
-        left: 0,
-        w: 'full',
-        h: 'full',
-        position: 'absolute',
-      }}
-    >
-      <Flex
-        sx={{
-          position: 'absolute',
-          top: 0,
-          right: 0,
-          p: 2,
-          alignItems: 'flex-start',
-        }}
-      >
-        <Badge variant="solid" colorScheme="base">
-          {image.metadata?.width} × {image.metadata?.height}
-        </Badge>
-      </Flex>
-    </Box>
-  );
-};
-
-export default ImageToImageOverlay;

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

@@ -49,7 +49,7 @@ const ImageUploader = (props: ImageUploaderProps) => {
 
   const fileAcceptedCallback = useCallback(
     async (file: File) => {
-      dispatch(imageUploaded({ formData: { file } }));
+      dispatch(imageUploaded({ imageType: 'uploads', formData: { file } }));
     },
     [dispatch]
   );
@@ -124,7 +124,7 @@ const ImageUploader = (props: ImageUploaderProps) => {
         return;
       }
 
-      dispatch(imageUploaded({ formData: { file } }));
+      dispatch(imageUploaded({ imageType: 'uploads', formData: { file } }));
     };
     document.addEventListener('paste', pasteImageListener);
     return () => {

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

@@ -7,7 +7,7 @@ const SelectImagePlaceholder = () => {
       sx={{
         w: 'full',
         h: 'full',
-        bg: 'base.800',
+        // bg: 'base.800',
         borderRadius: 'base',
         alignItems: 'center',
         justifyContent: 'center',

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

@@ -2,6 +2,13 @@ import { createSelector } from '@reduxjs/toolkit';
 import { RootState } from 'app/store/store';
 import { useAppDispatch, useAppSelector } from 'app/store/storeHooks';
 import { shiftKeyPressed } from 'features/ui/store/hotkeysSlice';
+import {
+  setActiveTab,
+  toggleGalleryPanel,
+  toggleParametersPanel,
+  togglePinGalleryPanel,
+  togglePinParametersPanel,
+} from 'features/ui/store/uiSlice';
 import { isEqual } from 'lodash-es';
 import { isHotkeyPressed, useHotkeys } from 'react-hotkeys-hook';
 
@@ -36,4 +43,36 @@ export const useGlobalHotkeys = () => {
     { keyup: true, keydown: true },
     [shift]
   );
+
+  useHotkeys('o', () => {
+    dispatch(toggleParametersPanel());
+  });
+
+  useHotkeys(['shift+o'], () => {
+    dispatch(togglePinParametersPanel());
+  });
+
+  useHotkeys('g', () => {
+    dispatch(toggleGalleryPanel());
+  });
+
+  useHotkeys(['shift+g'], () => {
+    dispatch(togglePinGalleryPanel());
+  });
+
+  useHotkeys('1', () => {
+    dispatch(setActiveTab('txt2img'));
+  });
+
+  useHotkeys('2', () => {
+    dispatch(setActiveTab('img2img'));
+  });
+
+  useHotkeys('3', () => {
+    dispatch(setActiveTab('unifiedCanvas'));
+  });
+
+  useHotkeys('4', () => {
+    dispatch(setActiveTab('nodes'));
+  });
 };

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

@@ -0,0 +1,33 @@
+export const getImageDataTransparency = (pixels: Uint8ClampedArray) => {
+  let isFullyTransparent = true;
+  let isPartiallyTransparent = false;
+  const len = pixels.length;
+  let i = 3;
+  for (i; i < len; i += 4) {
+    if (pixels[i] === 255) {
+      isFullyTransparent = false;
+    } else {
+      isPartiallyTransparent = true;
+    }
+    if (!isFullyTransparent && isPartiallyTransparent) {
+      return { isFullyTransparent, isPartiallyTransparent };
+    }
+  }
+  return { isFullyTransparent, isPartiallyTransparent };
+};
+
+export const areAnyPixelsBlack = (pixels: Uint8ClampedArray) => {
+  const len = pixels.length;
+  let i = 0;
+  for (i; i < len; ) {
+    if (
+      pixels[i++] === 0 &&
+      pixels[i++] === 0 &&
+      pixels[i++] === 0 &&
+      pixels[i++] === 255
+    ) {
+      return true;
+    }
+  }
+  return false;
+};

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

@@ -19,6 +19,7 @@ import { InvokeTabName } from 'features/ui/store/tabMap';
 import openBase64ImageInTab from './openBase64ImageInTab';
 import randomInt from './randomInt';
 import { stringToSeedWeightsArray } from './seedWeightPairs';
+import { getIsImageDataTransparent, getIsImageDataWhite } from './arrayBuffer';
 
 export type FrontendToBackendParametersConfig = {
   generationMode: InvokeTabName;
@@ -256,7 +257,7 @@ export const frontendToBackendParameters = (
       ...boundingBoxDimensions,
     };
 
-    const maskDataURL = generateMask(
+    const { dataURL: maskDataURL, imageData: maskImageData } = generateMask(
       isMaskEnabled ? objects.filter(isCanvasMaskLine) : [],
       boundingBox
     );
@@ -287,6 +288,17 @@ export const frontendToBackendParameters = (
       height: boundingBox.height,
     });
 
+    const ctx = canvasBaseLayer.getContext();
+    const imageData = ctx.getImageData(
+      boundingBox.x + absPos.x,
+      boundingBox.y + absPos.y,
+      boundingBox.width,
+      boundingBox.height
+    );
+
+    const doesBaseHaveTransparency = getIsImageDataTransparent(imageData);
+    const doesMaskHaveTransparency = getIsImageDataWhite(maskImageData);
+
     if (enableImageDebugging) {
       openBase64ImageInTab([
         { base64: maskDataURL, caption: 'mask sent as init_mask' },

invokeai/frontend/web/src/features/canvas/components/IAICanvas.tsx

@@ -34,6 +34,7 @@ import IAICanvasStagingAreaToolbar from './IAICanvasStagingAreaToolbar';
 import IAICanvasStatusText from './IAICanvasStatusText';
 import IAICanvasBoundingBox from './IAICanvasToolbar/IAICanvasBoundingBox';
 import IAICanvasToolPreview from './IAICanvasToolPreview';
+import { defaultSelectorOptions } from 'app/store/util/defaultMemoizeOptions';
 
 const selector = createSelector(
   [canvasSelector, isStagingSelector],
@@ -52,6 +53,7 @@ const selector = createSelector(
       shouldShowIntermediates,
       shouldShowGrid,
       shouldRestrictStrokesToBox,
+      shouldAntialias,
     } = canvas;
 
     let stageCursor: string | undefined = 'none';
@@ -80,13 +82,10 @@ const selector = createSelector(
       tool,
       isStaging,
       shouldShowIntermediates,
+      shouldAntialias,
     };
   },
-  {
+  defaultSelectorOptions
-    memoizeOptions: {
-      resultEqualityCheck: isEqual,
-    },
-  }
 );
 
 const ChakraStage = chakra(Stage, {
@@ -106,6 +105,7 @@ const IAICanvas = () => {
     tool,
     isStaging,
     shouldShowIntermediates,
+    shouldAntialias,
   } = useAppSelector(selector);
   useCanvasHotkeys();
 
@@ -190,7 +190,7 @@ const IAICanvas = () => {
             id="base"
             ref={canvasBaseLayerRefCallback}
             listening={false}
-            imageSmoothingEnabled={false}
+            imageSmoothingEnabled={shouldAntialias}
           >
             <IAICanvasObjectRenderer />
           </Layer>
@@ -201,7 +201,7 @@ const IAICanvas = () => {
           <Layer>
             <IAICanvasBoundingBoxOverlay />
           </Layer>
-          <Layer id="preview" imageSmoothingEnabled={false}>
+          <Layer id="preview" imageSmoothingEnabled={shouldAntialias}>
             {!isStaging && (
               <IAICanvasToolPreview
                 visible={tool !== 'move'}

invokeai/frontend/web/src/features/canvas/components/IAICanvasStagingArea.tsx

@@ -12,18 +12,20 @@ const selector = createSelector(
   [canvasSelector],
   (canvas) => {
     const {
-      layerState: {
+      layerState,
-        stagingArea: { images, selectedImageIndex },
-      },
       shouldShowStagingImage,
       shouldShowStagingOutline,
       boundingBoxCoordinates: { x, y },
       boundingBoxDimensions: { width, height },
     } = canvas;
 
+    const { selectedImageIndex, images } = layerState.stagingArea;
+
     return {
       currentStagingAreaImage:
-        images.length > 0 ? images[selectedImageIndex] : undefined,
+        images.length > 0 && selectedImageIndex !== undefined
+          ? images[selectedImageIndex]
+          : undefined,
       isOnFirstImage: selectedImageIndex === 0,
       isOnLastImage: selectedImageIndex === images.length - 1,
       shouldShowStagingImage,

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

@@ -6,6 +6,7 @@ import IAIIconButton from 'common/components/IAIIconButton';
 import IAIPopover from 'common/components/IAIPopover';
 import { canvasSelector } from 'features/canvas/store/canvasSelectors';
 import {
+  setShouldAntialias,
   setShouldAutoSave,
   setShouldCropToBoundingBoxOnSave,
   setShouldDarkenOutsideBoundingBox,
@@ -36,6 +37,7 @@ export const canvasControlsSelector = createSelector(
       shouldShowIntermediates,
       shouldSnapToGrid,
       shouldRestrictStrokesToBox,
+      shouldAntialias,
     } = canvas;
 
     return {
@@ -47,6 +49,7 @@ export const canvasControlsSelector = createSelector(
       shouldShowIntermediates,
       shouldSnapToGrid,
       shouldRestrictStrokesToBox,
+      shouldAntialias,
     };
   },
   {
@@ -69,6 +72,7 @@ const IAICanvasSettingsButtonPopover = () => {
     shouldShowIntermediates,
     shouldSnapToGrid,
     shouldRestrictStrokesToBox,
+    shouldAntialias,
   } = useAppSelector(canvasControlsSelector);
 
   useHotkeys(
@@ -148,6 +152,12 @@ const IAICanvasSettingsButtonPopover = () => {
             dispatch(setShouldShowCanvasDebugInfo(e.target.checked))
           }
         />
+
+        <IAICheckbox
+          label={t('unifiedCanvas.antialiasing')}
+          isChecked={shouldAntialias}
+          onChange={(e) => dispatch(setShouldAntialias(e.target.checked))}
+        />
         <ClearCanvasHistoryButtonModal />
         <EmptyTempFolderButtonModal />
       </Flex>

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

@@ -9,6 +9,12 @@ const itemsToDenylist: (keyof CanvasState)[] = [
   'doesCanvasNeedScaling',
 ];
 
+export const canvasPersistDenylist: (keyof CanvasState)[] = [
+  'cursorPosition',
+  'isCanvasInitialized',
+  'doesCanvasNeedScaling',
+];
+
 export const canvasDenylist = itemsToDenylist.map(
   (denylistItem) => `canvas.${denylistItem}`
 );

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

@@ -38,7 +38,7 @@ export const initialLayerState: CanvasLayerState = {
   },
 };
 
-const initialCanvasState: CanvasState = {
+export const initialCanvasState: CanvasState = {
   boundingBoxCoordinates: { x: 0, y: 0 },
   boundingBoxDimensions: { width: 512, height: 512 },
   boundingBoxPreviewFill: { r: 0, g: 0, b: 0, a: 0.5 },
@@ -66,6 +66,7 @@ const initialCanvasState: CanvasState = {
   minimumStageScale: 1,
   pastLayerStates: [],
   scaledBoundingBoxDimensions: { width: 512, height: 512 },
+  shouldAntialias: true,
   shouldAutoSave: false,
   shouldCropToBoundingBoxOnSave: false,
   shouldDarkenOutsideBoundingBox: false,
@@ -156,22 +157,20 @@ export const canvasSlice = createSlice({
     setCursorPosition: (state, action: PayloadAction<Vector2d | null>) => {
       state.cursorPosition = action.payload;
     },
-    setInitialCanvasImage: (state, action: PayloadAction<InvokeAI._Image>) => {
+    setInitialCanvasImage: (state, action: PayloadAction<InvokeAI.Image>) => {
       const image = action.payload;
+      const { width, height } = image.metadata;
       const { stageDimensions } = state;
 
       const newBoundingBoxDimensions = {
-        width: roundDownToMultiple(clamp(image.width, 64, 512), 64),
+        width: roundDownToMultiple(clamp(width, 64, 512), 64),
-        height: roundDownToMultiple(clamp(image.height, 64, 512), 64),
+        height: roundDownToMultiple(clamp(height, 64, 512), 64),
       };
 
       const newBoundingBoxCoordinates = {
-        x: roundToMultiple(
+        x: roundToMultiple(width / 2 - newBoundingBoxDimensions.width / 2, 64),
-          image.width / 2 - newBoundingBoxDimensions.width / 2,
-          64
-        ),
         y: roundToMultiple(
-          image.height / 2 - newBoundingBoxDimensions.height / 2,
+          height / 2 - newBoundingBoxDimensions.height / 2,
           64
         ),
       };
@@ -196,8 +195,8 @@ export const canvasSlice = createSlice({
             layer: 'base',
             x: 0,
             y: 0,
-            width: image.width,
+            width: width,
-            height: image.height,
+            height: height,
             image: image,
           },
         ],
@@ -208,8 +207,8 @@ export const canvasSlice = createSlice({
       const newScale = calculateScale(
         stageDimensions.width,
         stageDimensions.height,
-        image.width,
+        width,
-        image.height,
+        height,
         STAGE_PADDING_PERCENTAGE
       );
 
@@ -218,8 +217,8 @@ export const canvasSlice = createSlice({
         stageDimensions.height,
         0,
         0,
-        image.width,
+        width,
-        image.height,
+        height,
         newScale
       );
       state.stageScale = newScale;
@@ -287,16 +286,28 @@ export const canvasSlice = createSlice({
     setIsMoveStageKeyHeld: (state, action: PayloadAction<boolean>) => {
       state.isMoveStageKeyHeld = action.payload;
     },
-    addImageToStagingArea: (
+    canvasSessionIdChanged: (state, action: PayloadAction<string>) => {
+      state.layerState.stagingArea.sessionId = action.payload;
+    },
+    stagingAreaInitialized: (
       state,
-      action: PayloadAction<{
+      action: PayloadAction<{ sessionId: string; boundingBox: IRect }>
-        boundingBox: IRect;
-        image: InvokeAI._Image;
-      }>
     ) => {
-      const { boundingBox, image } = action.payload;
+      const { sessionId, boundingBox } = action.payload;
 
-      if (!boundingBox || !image) return;
+      state.layerState.stagingArea = {
+        boundingBox,
+        sessionId,
+        images: [],
+        selectedImageIndex: -1,
+      };
+    },
+    addImageToStagingArea: (state, action: PayloadAction<InvokeAI.Image>) => {
+      const image = action.payload;
+
+      if (!image || !state.layerState.stagingArea.boundingBox) {
+        return;
+      }
 
       state.pastLayerStates.push(cloneDeep(state.layerState));
 
@@ -307,7 +318,7 @@ export const canvasSlice = createSlice({
       state.layerState.stagingArea.images.push({
         kind: 'image',
         layer: 'base',
-        ...boundingBox,
+        ...state.layerState.stagingArea.boundingBox,
         image,
       });
 
@@ -323,9 +334,7 @@ export const canvasSlice = createSlice({
         state.pastLayerStates.shift();
       }
 
-      state.layerState.stagingArea = {
+      state.layerState.stagingArea = { ...initialLayerState.stagingArea };
-        ...initialLayerState.stagingArea,
-      };
 
       state.futureLayerStates = [];
       state.shouldShowStagingOutline = true;
@@ -663,6 +672,10 @@ export const canvasSlice = createSlice({
       }
     },
     nextStagingAreaImage: (state) => {
+      if (!state.layerState.stagingArea.images.length) {
+        return;
+      }
+
       const currentIndex = state.layerState.stagingArea.selectedImageIndex;
       const length = state.layerState.stagingArea.images.length;
 
@@ -672,6 +685,10 @@ export const canvasSlice = createSlice({
       );
     },
     prevStagingAreaImage: (state) => {
+      if (!state.layerState.stagingArea.images.length) {
+        return;
+      }
+
       const currentIndex = state.layerState.stagingArea.selectedImageIndex;
 
       state.layerState.stagingArea.selectedImageIndex = Math.max(
@@ -680,6 +697,10 @@ export const canvasSlice = createSlice({
       );
     },
     commitStagingAreaImage: (state) => {
+      if (!state.layerState.stagingArea.images.length) {
+        return;
+      }
+
       const { images, selectedImageIndex } = state.layerState.stagingArea;
 
       state.pastLayerStates.push(cloneDeep(state.layerState));
@@ -776,6 +797,9 @@ export const canvasSlice = createSlice({
     setShouldRestrictStrokesToBox: (state, action: PayloadAction<boolean>) => {
       state.shouldRestrictStrokesToBox = action.payload;
     },
+    setShouldAntialias: (state, action: PayloadAction<boolean>) => {
+      state.shouldAntialias = action.payload;
+    },
     setShouldCropToBoundingBoxOnSave: (
       state,
       action: PayloadAction<boolean>
@@ -885,6 +909,9 @@ export const {
   undo,
   setScaledBoundingBoxDimensions,
   setShouldRestrictStrokesToBox,
+  stagingAreaInitialized,
+  canvasSessionIdChanged,
+  setShouldAntialias,
 } = canvasSlice.actions;
 
 export default canvasSlice.reducer;

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

@@ -37,7 +37,7 @@ export type CanvasImage = {
   y: number;
   width: number;
   height: number;
-  image: InvokeAI._Image;
+  image: InvokeAI.Image;
 };
 
 export type CanvasMaskLine = {
@@ -90,9 +90,16 @@ export type CanvasLayerState = {
   stagingArea: {
     images: CanvasImage[];
     selectedImageIndex: number;
+    sessionId?: string;
+    boundingBox?: IRect;
   };
 };
 
+export type CanvasSession = {
+  sessionId: string;
+  boundingBox: IRect;
+};
+
 // type guards
 export const isCanvasMaskLine = (obj: CanvasObject): obj is CanvasMaskLine =>
   obj.kind === 'line' && obj.layer === 'mask';
@@ -125,7 +132,7 @@ export interface CanvasState {
   cursorPosition: Vector2d | null;
   doesCanvasNeedScaling: boolean;
   futureLayerStates: CanvasLayerState[];
-  intermediateImage?: InvokeAI._Image;
+  intermediateImage?: InvokeAI.Image;
   isCanvasInitialized: boolean;
   isDrawing: boolean;
   isMaskEnabled: boolean;
@@ -142,6 +149,7 @@ export interface CanvasState {
   minimumStageScale: number;
   pastLayerStates: CanvasLayerState[];
   scaledBoundingBoxDimensions: Dimensions;
+  shouldAntialias: boolean;
   shouldAutoSave: boolean;
   shouldCropToBoundingBoxOnSave: boolean;
   shouldDarkenOutsideBoundingBox: boolean;

invokeai/frontend/web/src/features/canvas/util/canvasToBlob.ts

@@ -0,0 +1,13 @@
+/**
+ * Gets a Blob from a canvas.
+ */
+export const canvasToBlob = async (canvas: HTMLCanvasElement): Promise<Blob> =>
+  new Promise((resolve, reject) => {
+    canvas.toBlob((blob) => {
+      if (blob) {
+        resolve(blob);
+        return;
+      }
+      reject('Unable to create Blob');
+    });
+  });

invokeai/frontend/web/src/features/canvas/util/dataURLToImageData.ts

@@ -0,0 +1,29 @@
+/**
+ * Gets an ImageData object from an image dataURL by drawing it to a canvas.
+ */
+export const dataURLToImageData = async (
+  dataURL: string,
+  width: number,
+  height: number
+): Promise<ImageData> =>
+  new Promise((resolve, reject) => {
+    const canvas = document.createElement('canvas');
+    canvas.width = width;
+    canvas.height = height;
+    const ctx = canvas.getContext('2d');
+    const image = new Image();
+
+    if (!ctx) {
+      canvas.remove();
+      reject('Unable to get context');
+      return;
+    }
+
+    image.onload = function () {
+      ctx.drawImage(image, 0, 0);
+      canvas.remove();
+      resolve(ctx.getImageData(0, 0, width, height));
+    };
+
+    image.src = dataURL;
+  });

invokeai/frontend/web/src/features/canvas/util/generateMask.ts

@@ -1,6 +1,110 @@
+// import { CanvasMaskLine } from 'features/canvas/store/canvasTypes';
+// import Konva from 'konva';
+// import { Stage } from 'konva/lib/Stage';
+// import { IRect } from 'konva/lib/types';
+
+// /**
+//  * Generating a mask image from InpaintingCanvas.tsx is not as simple
+//  * as calling toDataURL() on the canvas, because the mask may be represented
+//  * by colored lines or transparency, or the user may have inverted the mask
+//  * display.
+//  *
+//  * So we need to regenerate the mask image by creating an offscreen canvas,
+//  * drawing the mask and compositing everything correctly to output a valid
+//  * mask image.
+//  */
+// export const getStageDataURL = (stage: Stage, boundingBox: IRect): string => {
+//   // create an offscreen canvas and add the mask to it
+//   // const { stage, offscreenContainer } = buildMaskStage(lines, boundingBox);
+
+//   const dataURL = stage.toDataURL({ ...boundingBox });
+
+//   // const imageData = stage
+//   //   .toCanvas()
+//   //   .getContext('2d')
+//   //   ?.getImageData(
+//   //     boundingBox.x,
+//   //     boundingBox.y,
+//   //     boundingBox.width,
+//   //     boundingBox.height
+//   //   );
+
+//   // offscreenContainer.remove();
+
+//   // return { dataURL, imageData };
+
+//   return dataURL;
+// };
+
+// export const getStageImageData = (
+//   stage: Stage,
+//   boundingBox: IRect
+// ): ImageData | undefined => {
+//   const imageData = stage
+//     .toCanvas()
+//     .getContext('2d')
+//     ?.getImageData(
+//       boundingBox.x,
+//       boundingBox.y,
+//       boundingBox.width,
+//       boundingBox.height
+//     );
+
+//   return imageData;
+// };
+
+// export const buildMaskStage = (
+//   lines: CanvasMaskLine[],
+//   boundingBox: IRect
+// ): { stage: Stage; offscreenContainer: HTMLDivElement } => {
+//   // create an offscreen canvas and add the mask to it
+//   const { width, height } = boundingBox;
+
+//   const offscreenContainer = document.createElement('div');
+
+//   const stage = new Konva.Stage({
+//     container: offscreenContainer,
+//     width: width,
+//     height: height,
+//   });
+
+//   const baseLayer = new Konva.Layer();
+//   const maskLayer = new Konva.Layer();
+
+//   // composite the image onto the mask layer
+//   baseLayer.add(
+//     new Konva.Rect({
+//       ...boundingBox,
+//       fill: 'white',
+//     })
+//   );
+
+//   lines.forEach((line) =>
+//     maskLayer.add(
+//       new Konva.Line({
+//         points: line.points,
+//         stroke: 'black',
+//         strokeWidth: line.strokeWidth * 2,
+//         tension: 0,
+//         lineCap: 'round',
+//         lineJoin: 'round',
+//         shadowForStrokeEnabled: false,
+//         globalCompositeOperation:
+//           line.tool === 'brush' ? 'source-over' : 'destination-out',
+//       })
+//     )
+//   );
+
+//   stage.add(baseLayer);
+//   stage.add(maskLayer);
+
+//   return { stage, offscreenContainer };
+// };
+
 import { CanvasMaskLine } from 'features/canvas/store/canvasTypes';
 import Konva from 'konva';
 import { IRect } from 'konva/lib/types';
+import { canvasToBlob } from './canvasToBlob';
 
 /**
  * Generating a mask image from InpaintingCanvas.tsx is not as simple
@@ -12,7 +116,7 @@ import { IRect } from 'konva/lib/types';
  * drawing the mask and compositing everything correctly to output a valid
  * mask image.
  */
-const generateMask = (lines: CanvasMaskLine[], boundingBox: IRect): string => {
+const generateMask = async (lines: CanvasMaskLine[], boundingBox: IRect) => {
   // create an offscreen canvas and add the mask to it
   const { width, height } = boundingBox;
 
@@ -54,11 +158,13 @@ const generateMask = (lines: CanvasMaskLine[], boundingBox: IRect): string => {
   stage.add(baseLayer);
   stage.add(maskLayer);
 
-  const dataURL = stage.toDataURL({ ...boundingBox });
+  const maskDataURL = stage.toDataURL(boundingBox);
+
+  const maskBlob = await canvasToBlob(stage.toCanvas(boundingBox));
 
   offscreenContainer.remove();
 
-  return dataURL;
+  return { maskDataURL, maskBlob };
 };
 
 export default generateMask;

invokeai/frontend/web/src/features/canvas/util/getCanvasData.ts

@@ -0,0 +1,128 @@
+import { RootState } from 'app/store/store';
+import { getCanvasBaseLayer, getCanvasStage } from './konvaInstanceProvider';
+import { isCanvasMaskLine } from '../store/canvasTypes';
+import { log } from 'app/logging/useLogger';
+import {
+  areAnyPixelsBlack,
+  getImageDataTransparency,
+} from 'common/util/arrayBuffer';
+import openBase64ImageInTab from 'common/util/openBase64ImageInTab';
+import generateMask from './generateMask';
+import { dataURLToImageData } from './dataURLToImageData';
+import { canvasToBlob } from './canvasToBlob';
+
+const moduleLog = log.child({ namespace: 'getCanvasDataURLs' });
+
+export const getCanvasData = async (state: RootState) => {
+  const canvasBaseLayer = getCanvasBaseLayer();
+  const canvasStage = getCanvasStage();
+
+  if (!canvasBaseLayer || !canvasStage) {
+    moduleLog.error('Unable to find canvas / stage');
+    return;
+  }
+
+  const {
+    layerState: { objects },
+    boundingBoxCoordinates,
+    boundingBoxDimensions,
+    stageScale,
+    isMaskEnabled,
+    shouldPreserveMaskedArea,
+    boundingBoxScaleMethod: boundingBoxScale,
+    scaledBoundingBoxDimensions,
+  } = state.canvas;
+
+  const boundingBox = {
+    ...boundingBoxCoordinates,
+    ...boundingBoxDimensions,
+  };
+
+  // generationParameters.fit = false;
+
+  // generationParameters.strength = img2imgStrength;
+
+  // generationParameters.invert_mask = shouldPreserveMaskedArea;
+
+  // generationParameters.bounding_box = boundingBox;
+
+  const tempScale = canvasBaseLayer.scale();
+
+  canvasBaseLayer.scale({
+    x: 1 / stageScale,
+    y: 1 / stageScale,
+  });
+
+  const absPos = canvasBaseLayer.getAbsolutePosition();
+
+  const offsetBoundingBox = {
+    x: boundingBox.x + absPos.x,
+    y: boundingBox.y + absPos.y,
+    width: boundingBox.width,
+    height: boundingBox.height,
+  };
+
+  const baseDataURL = canvasBaseLayer.toDataURL(offsetBoundingBox);
+  const baseBlob = await canvasToBlob(
+    canvasBaseLayer.toCanvas(offsetBoundingBox)
+  );
+
+  canvasBaseLayer.scale(tempScale);
+
+  const { maskDataURL, maskBlob } = await generateMask(
+    isMaskEnabled ? objects.filter(isCanvasMaskLine) : [],
+    boundingBox
+  );
+
+  const baseImageData = await dataURLToImageData(
+    baseDataURL,
+    boundingBox.width,
+    boundingBox.height
+  );
+
+  const maskImageData = await dataURLToImageData(
+    maskDataURL,
+    boundingBox.width,
+    boundingBox.height
+  );
+
+  const {
+    isPartiallyTransparent: baseIsPartiallyTransparent,
+    isFullyTransparent: baseIsFullyTransparent,
+  } = getImageDataTransparency(baseImageData.data);
+
+  const doesMaskHaveBlackPixels = areAnyPixelsBlack(maskImageData.data);
+
+  if (state.system.enableImageDebugging) {
+    openBase64ImageInTab([
+      { base64: maskDataURL, caption: 'mask b64' },
+      { base64: baseDataURL, caption: 'image b64' },
+    ]);
+  }
+
+  // generationParameters.init_img = imageDataURL;
+  // generationParameters.progress_images = false;
+
+  // if (boundingBoxScale !== 'none') {
+  //   generationParameters.inpaint_width = scaledBoundingBoxDimensions.width;
+  //   generationParameters.inpaint_height = scaledBoundingBoxDimensions.height;
+  // }
+
+  // generationParameters.seam_size = seamSize;
+  // generationParameters.seam_blur = seamBlur;
+  // generationParameters.seam_strength = seamStrength;
+  // generationParameters.seam_steps = seamSteps;
+  // generationParameters.tile_size = tileSize;
+  // generationParameters.infill_method = infillMethod;
+  // generationParameters.force_outpaint = false;
+
+  return {
+    baseDataURL,
+    baseBlob,
+    maskDataURL,
+    maskBlob,
+    baseIsPartiallyTransparent,
+    baseIsFullyTransparent,
+    doesMaskHaveBlackPixels,
+  };
+};

invokeai/frontend/web/src/features/gallery/components/CurrentImageButtons.tsx

@@ -1,12 +1,17 @@
 import { createSelector } from '@reduxjs/toolkit';
-import { get, isEqual, isNumber, isString } from 'lodash-es';
+import { isEqual, isString } from 'lodash-es';
 
 import {
   ButtonGroup,
   Flex,
   FlexProps,
-  FormControl,
+  IconButton,
   Link,
+  Menu,
+  MenuButton,
+  MenuItemOption,
+  MenuList,
+  MenuOptionGroup,
   useDisclosure,
   useToast,
 } from '@chakra-ui/react';
@@ -15,21 +20,12 @@ import { useAppDispatch, useAppSelector } from 'app/store/storeHooks';
 import IAIButton from 'common/components/IAIButton';
 import IAIIconButton from 'common/components/IAIIconButton';
 import IAIPopover from 'common/components/IAIPopover';
-import { setInitialCanvasImage } from 'features/canvas/store/canvasSlice';
+
-import { GalleryState } from 'features/gallery/store/gallerySlice';
 import { lightboxSelector } from 'features/lightbox/store/lightboxSelectors';
 import { setIsLightboxOpen } from 'features/lightbox/store/lightboxSlice';
-import FaceRestoreSettings from 'features/parameters/components/AdvancedParameters/FaceRestore/FaceRestoreSettings';
-import UpscaleSettings from 'features/parameters/components/AdvancedParameters/Upscale/UpscaleSettings';
-import {
-  initialImageSelected,
-  setAllParameters,
-  // setInitialImage,
-  setSeed,
-} from 'features/parameters/store/generationSlice';
 import { postprocessingSelector } from 'features/parameters/store/postprocessingSelectors';
 import { systemSelector } from 'features/system/store/systemSelectors';
-import { SystemState } from 'features/system/store/systemSlice';
+
 import {
   activeTabNameSelector,
   uiSelector,
@@ -56,6 +52,7 @@ import {
   FaShare,
   FaShareAlt,
   FaTrash,
+  FaWrench,
 } from 'react-icons/fa';
 import {
   gallerySelector,
@@ -66,8 +63,13 @@ import { useCallback } from 'react';
 import { requestCanvasRescale } from 'features/canvas/store/thunks/requestCanvasScale';
 import { useGetUrl } from 'common/util/getUrl';
 import { useFeatureStatus } from 'features/system/hooks/useFeatureStatus';
-import { imageDeleted } from 'services/thunks/image';
 import { useParameters } from 'features/parameters/hooks/useParameters';
+import { initialImageSelected } from 'features/parameters/store/actions';
+import { requestedImageDeletion } from '../store/actions';
+import FaceRestoreSettings from 'features/parameters/components/Parameters/FaceRestore/FaceRestoreSettings';
+import UpscaleSettings from 'features/parameters/components/Parameters/Upscale/UpscaleSettings';
+import { allParametersSet } from 'features/parameters/store/generationSlice';
+import DeleteImageButton from './ImageActionButtons/DeleteImageButton';
 
 const currentImageButtonsSelector = createSelector(
   [
@@ -150,6 +152,7 @@ const CurrentImageButtons = (props: CurrentImageButtonsProps) => {
   } = useAppSelector(currentImageButtonsSelector);
 
   const isLightboxEnabled = useFeatureStatus('lightbox').isFeatureEnabled;
+  const isCanvasEnabled = useFeatureStatus('unifiedCanvas').isFeatureEnabled;
   const isUpscalingEnabled = useFeatureStatus('upscaling').isFeatureEnabled;
   const isFaceRestoreEnabled = useFeatureStatus('faceRestore').isFeatureEnabled;
 
@@ -164,40 +167,59 @@ const CurrentImageButtons = (props: CurrentImageButtonsProps) => {
   const toast = useToast();
   const { t } = useTranslation();
 
-  const { recallPrompt, recallSeed, sendToImageToImage } = useParameters();
+  const { recallPrompt, recallSeed, recallAllParameters } = useParameters();
 
-  const handleCopyImage = useCallback(async () => {
+  // const handleCopyImage = useCallback(async () => {
-    if (!image?.url) {
+  //   if (!image?.url) {
+  //     return;
+  //   }
+
+  //   const url = getUrl(image.url);
+
+  //   if (!url) {
+  //     return;
+  //   }
+
+  //   const blob = await fetch(url).then((res) => res.blob());
+  //   const data = [new ClipboardItem({ [blob.type]: blob })];
+
+  //   await navigator.clipboard.write(data);
+
+  //   toast({
+  //     title: t('toast.imageCopied'),
+  //     status: 'success',
+  //     duration: 2500,
+  //     isClosable: true,
+  //   });
+  // }, [getUrl, t, image?.url, toast]);
+
+  const handleCopyImageLink = useCallback(() => {
+    const getImageUrl = () => {
+      if (!image) {
         return;
       }
 
-    const url = getUrl(image.url);
+      if (shouldTransformUrls) {
+        return getUrl(image.url);
+      }
+
+      if (image.url.startsWith('http')) {
+        return image.url;
+      }
+
+      return window.location.toString() + image.url;
+    };
+
+    const url = getImageUrl();
 
     if (!url) {
-      return;
-    }
-
-    const blob = await fetch(url).then((res) => res.blob());
-    const data = [new ClipboardItem({ [blob.type]: blob })];
-
-    await navigator.clipboard.write(data);
-
       toast({
-      title: t('toast.imageCopied'),
+        title: t('toast.problemCopyingImageLink'),
-      status: 'success',
+        status: 'error',
         duration: 2500,
         isClosable: true,
       });
-  }, [getUrl, t, image?.url, toast]);
 
-  const handleCopyImageLink = useCallback(() => {
-    const url = image
-      ? shouldTransformUrls
-        ? getUrl(image.url)
-        : window.location.toString() + image.url
-      : '';
-
-    if (!url) {
       return;
     }
 
@@ -216,39 +238,15 @@ const CurrentImageButtons = (props: CurrentImageButtonsProps) => {
   }, [dispatch, shouldHidePreview]);
 
   const handleClickUseAllParameters = useCallback(() => {
-    if (!image) return;
+    recallAllParameters(image);
-    // selectedImage.metadata &&
+  }, [image, recallAllParameters]);
-    //   dispatch(setAllParameters(selectedImage.metadata));
-    // if (selectedImage.metadata?.image.type === 'img2img') {
-    //   dispatch(setActiveTab('img2img'));
-    // } else if (selectedImage.metadata?.image.type === 'txt2img') {
-    //   dispatch(setActiveTab('txt2img'));
-    // }
-  }, [image]);
 
   useHotkeys(
     'a',
     () => {
-      const type = image?.metadata?.invokeai?.node?.types;
+      handleClickUseAllParameters;
-      if (isString(type) && ['txt2img', 'img2img'].includes(type)) {
-        handleClickUseAllParameters();
-        toast({
-          title: t('toast.parametersSet'),
-          status: 'success',
-          duration: 2500,
-          isClosable: true,
-        });
-      } else {
-        toast({
-          title: t('toast.parametersNotSet'),
-          description: t('toast.parametersNotSetDesc'),
-          status: 'error',
-          duration: 2500,
-          isClosable: true,
-        });
-      }
     },
-    [image]
+    [image, recallAllParameters]
   );
 
   const handleUseSeed = useCallback(() => {
@@ -264,8 +262,8 @@ const CurrentImageButtons = (props: CurrentImageButtonsProps) => {
   useHotkeys('p', handleUsePrompt, [image]);
 
   const handleSendToImageToImage = useCallback(() => {
-    sendToImageToImage(image);
+    dispatch(initialImageSelected(image));
-  }, [image, sendToImageToImage]);
+  }, [dispatch, image]);
 
   useHotkeys('shift+i', handleSendToImageToImage, [image]);
 
@@ -375,7 +373,7 @@ const CurrentImageButtons = (props: CurrentImageButtonsProps) => {
 
   const handleDelete = useCallback(() => {
     if (canDeleteImage && image) {
-      dispatch(imageDeleted({ imageType: image.type, imageName: image.name }));
+      dispatch(requestedImageDeletion(image));
     }
   }, [image, canDeleteImage, dispatch]);
 
@@ -432,6 +430,7 @@ const CurrentImageButtons = (props: CurrentImageButtonsProps) => {
               >
                 {t('parameters.sendToImg2Img')}
               </IAIButton>
+              {isCanvasEnabled && (
                 <IAIButton
                   size="sm"
                   onClick={handleSendToCanvas}
@@ -439,14 +438,15 @@ const CurrentImageButtons = (props: CurrentImageButtonsProps) => {
                 >
                   {t('parameters.sendToUnifiedCanvas')}
                 </IAIButton>
+              )}
 
-              <IAIButton
+              {/* <IAIButton
                 size="sm"
                 onClick={handleCopyImage}
                 leftIcon={<FaCopy />}
               >
                 {t('parameters.copyImage')}
-              </IAIButton>
+              </IAIButton> */}
               <IAIButton
                 size="sm"
                 onClick={handleCopyImageLink}
@@ -462,7 +462,7 @@ const CurrentImageButtons = (props: CurrentImageButtonsProps) => {
               </Link>
             </Flex>
           </IAIPopover>
-          <IAIIconButton
+          {/* <IAIIconButton
             icon={shouldHidePreview ? <FaEyeSlash /> : <FaEye />}
             tooltip={
               !shouldHidePreview
@@ -476,7 +476,7 @@ const CurrentImageButtons = (props: CurrentImageButtonsProps) => {
             }
             isChecked={shouldHidePreview}
             onClick={handlePreviewVisibility}
-          />
+          /> */}
           {isLightboxEnabled && (
             <IAIIconButton
               icon={<FaExpand />}
@@ -518,8 +518,8 @@ const CurrentImageButtons = (props: CurrentImageButtonsProps) => {
             tooltip={`${t('parameters.useAll')} (A)`}
             aria-label={`${t('parameters.useAll')} (A)`}
             isDisabled={
-              !['txt2img', 'img2img'].includes(
+              !['txt2img', 'img2img', 'inpaint'].includes(
-                image?.metadata?.sd_metadata?.type
+                String(image?.metadata?.invokeai?.node?.type)
               )
             }
             onClick={handleClickUseAllParameters}
@@ -602,22 +602,10 @@ const CurrentImageButtons = (props: CurrentImageButtonsProps) => {
           />
         </ButtonGroup>
 
-        <IAIIconButton
+        <ButtonGroup isAttached={true}>
-          onClick={handleInitiateDelete}
+          <DeleteImageButton image={image} />
-          icon={<FaTrash />}
+        </ButtonGroup>
-          tooltip={`${t('gallery.deleteImage')} (Del)`}
-          aria-label={`${t('gallery.deleteImage')} (Del)`}
-          isDisabled={!image || !isConnected}
-          colorScheme="error"
-        />
       </Flex>
-      {image && (
-        <DeleteImageModal
-          isOpen={isDeleteDialogOpen}
-          onClose={onDeleteDialogClose}
-          handleDelete={handleDelete}
-        />
-      )}
     </>
   );
 };

invokeai/frontend/web/src/features/gallery/components/CurrentImagePreview.tsx

@@ -2,26 +2,35 @@ import { Box, Flex, Image } from '@chakra-ui/react';
 import { createSelector } from '@reduxjs/toolkit';
 import { useAppSelector } from 'app/store/storeHooks';
 import { useGetUrl } from 'common/util/getUrl';
-import { systemSelector } from 'features/system/store/systemSelectors';
 import { uiSelector } from 'features/ui/store/uiSelectors';
 import { isEqual } from 'lodash-es';
 
-import { selectedImageSelector } from '../store/gallerySelectors';
+import { gallerySelector } from '../store/gallerySelectors';
-import CurrentImageFallback from './CurrentImageFallback';
 import ImageMetadataViewer from './ImageMetaDataViewer/ImageMetadataViewer';
 import NextPrevImageButtons from './NextPrevImageButtons';
 import CurrentImageHidden from './CurrentImageHidden';
-import { memo } from 'react';
+import { DragEvent, memo, useCallback } from 'react';
+import { systemSelector } from 'features/system/store/systemSelectors';
+import ImageFallbackSpinner from './ImageFallbackSpinner';
+import ImageMetadataOverlay from 'common/components/ImageMetadataOverlay';
 
 export const imagesSelector = createSelector(
-  [uiSelector, selectedImageSelector, systemSelector],
+  [uiSelector, gallerySelector, systemSelector],
-  (ui, selectedImage, system) => {
+  (ui, gallery, system) => {
-    const { shouldShowImageDetails, shouldHidePreview } = ui;
+    const {
-
+      shouldShowImageDetails,
+      shouldHidePreview,
+      shouldShowProgressInViewer,
+    } = ui;
+    const { selectedImage } = gallery;
+    const { progressImage, shouldAntialiasProgressImage } = system;
     return {
       shouldShowImageDetails,
       shouldHidePreview,
       image: selectedImage,
+      progressImage,
+      shouldShowProgressInViewer,
+      shouldAntialiasProgressImage,
     };
   },
   {
@@ -32,26 +41,61 @@ export const imagesSelector = createSelector(
 );
 
 const CurrentImagePreview = () => {
-  const { shouldShowImageDetails, image, shouldHidePreview } =
+  const {
-    useAppSelector(imagesSelector);
+    shouldShowImageDetails,
+    image,
+    shouldHidePreview,
+    progressImage,
+    shouldShowProgressInViewer,
+    shouldAntialiasProgressImage,
+  } = useAppSelector(imagesSelector);
   const { getUrl } = useGetUrl();
 
+  const handleDragStart = useCallback(
+    (e: DragEvent<HTMLDivElement>) => {
+      if (!image) {
+        return;
+      }
+      e.dataTransfer.setData('invokeai/imageName', image.name);
+      e.dataTransfer.setData('invokeai/imageType', image.type);
+      e.dataTransfer.effectAllowed = 'move';
+    },
+    [image]
+  );
+
   return (
     <Flex
       sx={{
-        position: 'relative',
-        justifyContent: 'center',
-        alignItems: 'center',
         width: '100%',
         height: '100%',
+        position: 'relative',
+        alignItems: 'center',
+        justifyContent: 'center',
       }}
     >
-      {image && (
+      {progressImage && shouldShowProgressInViewer ? (
         <Image
-          src={shouldHidePreview ? undefined : getUrl(image.url)}
+          src={progressImage.dataURL}
-          width={image.metadata.width}
+          width={progressImage.width}
-          height={image.metadata.height}
+          height={progressImage.height}
-          fallback={shouldHidePreview ? <CurrentImageHidden /> : undefined}
+          sx={{
+            objectFit: 'contain',
+            maxWidth: '100%',
+            maxHeight: '100%',
+            height: 'auto',
+            position: 'absolute',
+            borderRadius: 'base',
+            imageRendering: shouldAntialiasProgressImage ? 'auto' : 'pixelated',
+          }}
+        />
+      ) : (
+        image && (
+          <>
+            <Image
+              src={getUrl(image.url)}
+              fallbackStrategy="beforeLoadOrError"
+              fallback={<ImageFallbackSpinner />}
+              onDragStart={handleDragStart}
               sx={{
                 objectFit: 'contain',
                 maxWidth: '100%',
@@ -61,6 +105,9 @@ const CurrentImagePreview = () => {
                 borderRadius: 'base',
               }}
             />
+            <ImageMetadataOverlay image={image} />
+          </>
+        )
       )}
       {shouldShowImageDetails && image && 'metadata' in image && (
         <Box

invokeai/frontend/web/src/features/gallery/components/GalleryProgressImage.tsx

@@ -0,0 +1,70 @@
+import { Flex, Image, Spinner } from '@chakra-ui/react';
+import { createSelector } from '@reduxjs/toolkit';
+import { useAppSelector } from 'app/store/storeHooks';
+import { defaultSelectorOptions } from 'app/store/util/defaultMemoizeOptions';
+import { systemSelector } from 'features/system/store/systemSelectors';
+import { memo } from 'react';
+import { gallerySelector } from '../store/gallerySelectors';
+
+const selector = createSelector(
+  [systemSelector, gallerySelector],
+  (system, gallery) => {
+    const { shouldUseSingleGalleryColumn, galleryImageObjectFit } = gallery;
+    const { progressImage, shouldAntialiasProgressImage } = system;
+
+    return {
+      progressImage,
+      shouldUseSingleGalleryColumn,
+      galleryImageObjectFit,
+      shouldAntialiasProgressImage,
+    };
+  },
+  defaultSelectorOptions
+);
+
+const GalleryProgressImage = () => {
+  const {
+    progressImage,
+    shouldUseSingleGalleryColumn,
+    galleryImageObjectFit,
+    shouldAntialiasProgressImage,
+  } = useAppSelector(selector);
+
+  if (!progressImage) {
+    return null;
+  }
+
+  return (
+    <Flex
+      sx={{
+        w: 'full',
+        h: 'full',
+        alignItems: 'center',
+        justifyContent: 'center',
+        aspectRatio: '1/1',
+        position: 'relative',
+      }}
+    >
+      <Image
+        draggable={false}
+        src={progressImage.dataURL}
+        width={progressImage.width}
+        height={progressImage.height}
+        sx={{
+          objectFit: shouldUseSingleGalleryColumn
+            ? 'contain'
+            : galleryImageObjectFit,
+          width: '100%',
+          height: '100%',
+          maxWidth: '100%',
+          maxHeight: '100%',
+          borderRadius: 'base',
+          imageRendering: shouldAntialiasProgressImage ? 'auto' : 'pixelated',
+        }}
+      />
+      <Spinner sx={{ position: 'absolute', top: 1, right: 1, opacity: 0.7 }} />
+    </Flex>
+  );
+};
+
+export default memo(GalleryProgressImage);

invokeai/frontend/web/src/features/gallery/components/HoverableImage.tsx

@@ -5,19 +5,20 @@ import {
   Image,
   MenuItem,
   MenuList,
-  Skeleton,
   useDisclosure,
-  useTheme,
   useToast,
 } from '@chakra-ui/react';
 import { useAppDispatch, useAppSelector } from 'app/store/storeHooks';
 import { imageSelected } from 'features/gallery/store/gallerySlice';
-import { DragEvent, memo, useCallback, useState } from 'react';
+import { DragEvent, MouseEvent, memo, useCallback, useState } from 'react';
 import { FaCheck, FaExpand, FaImage, FaShare, FaTrash } from 'react-icons/fa';
 import DeleteImageModal from './DeleteImageModal';
 import { ContextMenu } from 'chakra-ui-contextmenu';
 import * as InvokeAI from 'app/types/invokeai';
-import { resizeAndScaleCanvas } from 'features/canvas/store/canvasSlice';
+import {
+  resizeAndScaleCanvas,
+  setInitialCanvasImage,
+} from 'features/canvas/store/canvasSlice';
 import { gallerySelector } from 'features/gallery/store/gallerySelectors';
 import { setActiveTab } from 'features/ui/store/uiSlice';
 import { useTranslation } from 'react-i18next';
@@ -25,7 +26,6 @@ import IAIIconButton from 'common/components/IAIIconButton';
 import { useGetUrl } from 'common/util/getUrl';
 import { ExternalLinkIcon } from '@chakra-ui/icons';
 import { IoArrowUndoCircleOutline } from 'react-icons/io5';
-import { imageDeleted } from 'services/thunks/image';
 import { createSelector } from '@reduxjs/toolkit';
 import { systemSelector } from 'features/system/store/systemSelectors';
 import { lightboxSelector } from 'features/lightbox/store/lightboxSelectors';
@@ -33,6 +33,8 @@ import { activeTabNameSelector } from 'features/ui/store/uiSelectors';
 import { isEqual } from 'lodash-es';
 import { useFeatureStatus } from 'features/system/hooks/useFeatureStatus';
 import { useParameters } from 'features/parameters/hooks/useParameters';
+import { initialImageSelected } from 'features/parameters/store/actions';
+import { requestedImageDeletion } from '../store/actions';
 
 export const selector = createSelector(
   [gallerySelector, systemSelector, lightboxSelector, activeTabNameSelector],
@@ -94,16 +96,19 @@ const HoverableImage = memo((props: HoverableImageProps) => {
   } = useDisclosure();
 
   const { image, isSelected } = props;
-  const { url, thumbnail, name, metadata } = image;
+  const { url, thumbnail, name } = image;
   const { getUrl } = useGetUrl();
 
   const [isHovered, setIsHovered] = useState<boolean>(false);
 
   const toast = useToast();
-  const { direction } = useTheme();
+
   const { t } = useTranslation();
-  const { isFeatureEnabled: isLightboxEnabled } = useFeatureStatus('lightbox');
+
-  const { recallSeed, recallPrompt, sendToImageToImage, recallInitialImage } =
+  const isLightboxEnabled = useFeatureStatus('lightbox').isFeatureEnabled;
+  const isCanvasEnabled = useFeatureStatus('unifiedCanvas').isFeatureEnabled;
+
+  const { recallSeed, recallPrompt, recallInitialImage, recallAllParameters } =
     useParameters();
 
   const handleMouseOver = () => setIsHovered(true);
@@ -112,18 +117,22 @@ const HoverableImage = memo((props: HoverableImageProps) => {
   // Immediately deletes an image
   const handleDelete = useCallback(() => {
     if (canDeleteImage && image) {
-      dispatch(imageDeleted({ imageType: image.type, imageName: image.name }));
+      dispatch(requestedImageDeletion(image));
     }
   }, [dispatch, image, canDeleteImage]);
 
   // Opens the alert dialog to check if user is sure they want to delete
-  const handleInitiateDelete = useCallback(() => {
+  const handleInitiateDelete = useCallback(
+    (e: MouseEvent) => {
+      e.stopPropagation();
       if (shouldConfirmOnDelete) {
         onDeleteDialogOpen();
       } else {
         handleDelete();
       }
-  }, [handleDelete, onDeleteDialogOpen, shouldConfirmOnDelete]);
+    },
+    [handleDelete, onDeleteDialogOpen, shouldConfirmOnDelete]
+  );
 
   const handleSelectImage = useCallback(() => {
     dispatch(imageSelected(image));
@@ -148,8 +157,8 @@ const HoverableImage = memo((props: HoverableImageProps) => {
   }, [image, recallSeed]);
 
   const handleSendToImageToImage = useCallback(() => {
-    sendToImageToImage(image);
+    dispatch(initialImageSelected(image));
-  }, [image, sendToImageToImage]);
+  }, [dispatch, image]);
 
   const handleRecallInitialImage = useCallback(() => {
     recallInitialImage(image.metadata.invokeai?.node?.image);
@@ -159,7 +168,7 @@ const HoverableImage = memo((props: HoverableImageProps) => {
    * TODO: the rest of these
    */
   const handleSendToCanvas = () => {
-    // dispatch(setInitialCanvasImage(image));
+    dispatch(setInitialCanvasImage(image));
 
     dispatch(resizeAndScaleCanvas());
 
@@ -175,16 +184,9 @@ const HoverableImage = memo((props: HoverableImageProps) => {
     });
   };
 
-  const handleUseAllParameters = () => {
+  const handleUseAllParameters = useCallback(() => {
-    // metadata.invokeai?.node &&
+    recallAllParameters(image);
-    //   dispatch(setAllParameters(metadata.invokeai?.node));
+  }, [image, recallAllParameters]);
-    // toast({
-    //   title: t('toast.parametersSet'),
-    //   status: 'success',
-    //   duration: 2500,
-    //   isClosable: true,
-    // });
-  };
 
   const handleLightBox = () => {
     // dispatch(setCurrentImage(image));
@@ -238,7 +240,7 @@ const HoverableImage = memo((props: HoverableImageProps) => {
               icon={<IoArrowUndoCircleOutline />}
               onClickCapture={handleUseAllParameters}
               isDisabled={
-                !['txt2img', 'img2img'].includes(
+                !['txt2img', 'img2img', 'inpaint'].includes(
                   String(image?.metadata?.invokeai?.node?.type)
                 )
               }
@@ -251,9 +253,11 @@ const HoverableImage = memo((props: HoverableImageProps) => {
             >
               {t('parameters.sendToImg2Img')}
             </MenuItem>
+            {isCanvasEnabled && (
               <MenuItem icon={<FaShare />} onClickCapture={handleSendToCanvas}>
                 {t('parameters.sendToUnifiedCanvas')}
               </MenuItem>
+            )}
             <MenuItem icon={<FaTrash />} onClickCapture={onDeleteDialogOpen}>
               {t('gallery.deleteImage')}
             </MenuItem>
@@ -279,6 +283,7 @@ const HoverableImage = memo((props: HoverableImageProps) => {
               h: 'full',
               transition: 'transform 0.2s ease-out',
               aspectRatio: '1/1',
+              cursor: 'pointer',
             }}
           >
             <Image
@@ -315,6 +320,8 @@ const HoverableImage = memo((props: HoverableImageProps) => {
                   sx={{
                     width: '50%',
                     height: '50%',
+                    maxWidth: '4rem',
+                    maxHeight: '4rem',
                     fill: 'ok.500',
                   }}
                 />

invokeai/frontend/web/src/features/gallery/components/ImageActionButtons/DeleteImageButton.tsx

@@ -0,0 +1,92 @@
+import { createSelector } from '@reduxjs/toolkit';
+
+import { useDisclosure } from '@chakra-ui/react';
+import { useAppDispatch, useAppSelector } from 'app/store/storeHooks';
+import IAIIconButton from 'common/components/IAIIconButton';
+import { systemSelector } from 'features/system/store/systemSelectors';
+
+import { useHotkeys } from 'react-hotkeys-hook';
+import { useTranslation } from 'react-i18next';
+import { FaTrash } from 'react-icons/fa';
+import { memo, useCallback } from 'react';
+import { defaultSelectorOptions } from 'app/store/util/defaultMemoizeOptions';
+import DeleteImageModal from '../DeleteImageModal';
+import { requestedImageDeletion } from 'features/gallery/store/actions';
+import { Image } from 'app/types/invokeai';
+
+const selector = createSelector(
+  [systemSelector],
+  (system) => {
+    const { isProcessing, isConnected, shouldConfirmOnDelete } = system;
+
+    return {
+      canDeleteImage: isConnected && !isProcessing,
+      shouldConfirmOnDelete,
+      isProcessing,
+      isConnected,
+    };
+  },
+  defaultSelectorOptions
+);
+
+type DeleteImageButtonProps = {
+  image: Image | undefined;
+};
+
+const DeleteImageButton = (props: DeleteImageButtonProps) => {
+  const { image } = props;
+  const dispatch = useAppDispatch();
+  const { isProcessing, isConnected, canDeleteImage, shouldConfirmOnDelete } =
+    useAppSelector(selector);
+
+  const {
+    isOpen: isDeleteDialogOpen,
+    onOpen: onDeleteDialogOpen,
+    onClose: onDeleteDialogClose,
+  } = useDisclosure();
+
+  const { t } = useTranslation();
+
+  const handleDelete = useCallback(() => {
+    if (canDeleteImage && image) {
+      dispatch(requestedImageDeletion(image));
+    }
+  }, [image, canDeleteImage, dispatch]);
+
+  const handleInitiateDelete = useCallback(() => {
+    if (shouldConfirmOnDelete) {
+      onDeleteDialogOpen();
+    } else {
+      handleDelete();
+    }
+  }, [shouldConfirmOnDelete, onDeleteDialogOpen, handleDelete]);
+
+  useHotkeys('delete', handleInitiateDelete, [
+    image,
+    shouldConfirmOnDelete,
+    isConnected,
+    isProcessing,
+  ]);
+
+  return (
+    <>
+      <IAIIconButton
+        onClick={handleInitiateDelete}
+        icon={<FaTrash />}
+        tooltip={`${t('gallery.deleteImage')} (Del)`}
+        aria-label={`${t('gallery.deleteImage')} (Del)`}
+        isDisabled={!image || !isConnected}
+        colorScheme="error"
+      />
+      {image && (
+        <DeleteImageModal
+          isOpen={isDeleteDialogOpen}
+          onClose={onDeleteDialogClose}
+          handleDelete={handleDelete}
+        />
+      )}
+    </>
+  );
+};
+
+export default memo(DeleteImageButton);

invokeai/frontend/web/src/features/gallery/components/ImageFallbackSpinner.tsx

@@ -1,8 +1,8 @@
 import { Flex, Spinner, SpinnerProps } from '@chakra-ui/react';
 
-type CurrentImageFallbackProps = SpinnerProps;
+type ImageFallbackSpinnerProps = SpinnerProps;
 
-const CurrentImageFallback = (props: CurrentImageFallbackProps) => {
+const ImageFallbackSpinner = (props: ImageFallbackSpinnerProps) => {
   const { size = 'xl', ...rest } = props;
 
   return (
@@ -21,4 +21,4 @@ const CurrentImageFallback = (props: CurrentImageFallbackProps) => {
   );
 };
 
-export default CurrentImageFallback;
+export default ImageFallbackSpinner;

invokeai/frontend/web/src/features/gallery/components/ImageGalleryContent.tsx

@@ -5,6 +5,7 @@ import {
   FlexProps,
   Grid,
   Icon,
+  Image,
   Text,
   forwardRef,
 } from '@chakra-ui/react';
@@ -14,7 +15,10 @@ import IAICheckbox from 'common/components/IAICheckbox';
 import IAIIconButton from 'common/components/IAIIconButton';
 import IAIPopover from 'common/components/IAIPopover';
 import IAISlider from 'common/components/IAISlider';
-import { imageGallerySelector } from 'features/gallery/store/gallerySelectors';
+import {
+  gallerySelector,
+  imageGallerySelector,
+} from 'features/gallery/store/gallerySelectors';
 import {
   setCurrentCategory,
   setGalleryImageMinimumWidth,
@@ -50,30 +54,42 @@ import { uploadsAdapter } from '../store/uploadsSlice';
 import { createSelector } from '@reduxjs/toolkit';
 import { RootState } from 'app/store/store';
 import { Virtuoso, VirtuosoGrid } from 'react-virtuoso';
+import { Image as ImageType } from 'app/types/invokeai';
+import { defaultSelectorOptions } from 'app/store/util/defaultMemoizeOptions';
+import GalleryProgressImage from './GalleryProgressImage';
 
 const GALLERY_SHOW_BUTTONS_MIN_WIDTH = 290;
+const PROGRESS_IMAGE_PLACEHOLDER = 'PROGRESS_IMAGE_PLACEHOLDER';
 
-const gallerySelector = createSelector(
+const selector = createSelector(
-  [
+  [(state: RootState) => state],
-    (state: RootState) => state.uploads,
+  (state) => {
-    (state: RootState) => state.results,
+    const { results, uploads, system, gallery } = state;
-    (state: RootState) => state.gallery,
-  ],
-  (uploads, results, gallery) => {
     const { currentCategory } = gallery;
 
-    return currentCategory === 'results'
+    if (currentCategory === 'results') {
-      ? {
+      const tempImages: (ImageType | typeof PROGRESS_IMAGE_PLACEHOLDER)[] = [];
-          images: resultsAdapter.getSelectors().selectAll(results),
+
+      if (system.progressImage) {
+        tempImages.push(PROGRESS_IMAGE_PLACEHOLDER);
+      }
+
+      return {
+        images: tempImages.concat(
+          resultsAdapter.getSelectors().selectAll(results)
+        ),
         isLoading: results.isLoading,
         areMoreImagesAvailable: results.page < results.pages - 1,
+      };
     }
-      : {
+
+    return {
       images: uploadsAdapter.getSelectors().selectAll(uploads),
       isLoading: uploads.isLoading,
       areMoreImagesAvailable: uploads.page < uploads.pages - 1,
     };
-  }
+  },
+  defaultSelectorOptions
 );
 
 const ImageGalleryContent = () => {
@@ -108,7 +124,7 @@ const ImageGalleryContent = () => {
   } = useAppSelector(imageGallerySelector);
 
   const { images, areMoreImagesAvailable, isLoading } =
-    useAppSelector(gallerySelector);
+    useAppSelector(selector);
 
   const handleClickLoadMore = () => {
     if (currentCategory === 'results') {
@@ -170,8 +186,24 @@ const ImageGalleryContent = () => {
     }
   }, []);
 
+  const handleEndReached = useCallback(() => {
+    if (currentCategory === 'results') {
+      dispatch(receivedResultImagesPage());
+    } else if (currentCategory === 'uploads') {
+      dispatch(receivedUploadImagesPage());
+    }
+  }, [dispatch, currentCategory]);
+
   return (
-    <Flex flexDirection="column" w="full" h="full" gap={4}>
+    <Flex
+      sx={{
+        gap: 2,
+        flexDirection: 'column',
+        h: 'full',
+        w: 'full',
+        borderRadius: 'base',
+      }}
+    >
       <Flex
         ref={resizeObserverRef}
         alignItems="center"
@@ -290,18 +322,27 @@ const ImageGalleryContent = () => {
                 <Virtuoso
                   style={{ height: '100%' }}
                   data={images}
+                  endReached={handleEndReached}
                   scrollerRef={(ref) => setScrollerRef(ref)}
                   itemContent={(index, image) => {
-                    const { name } = image;
+                    const isSelected =
-                    const isSelected = selectedImage?.name === name;
+                      image === PROGRESS_IMAGE_PLACEHOLDER
+                        ? false
+                        : selectedImage?.name === image?.name;
 
                     return (
                       <Flex sx={{ pb: 2 }}>
+                        {image === PROGRESS_IMAGE_PLACEHOLDER ? (
+                          <GalleryProgressImage
+                            key={PROGRESS_IMAGE_PLACEHOLDER}
+                          />
+                        ) : (
                           <HoverableImage
-                          key={`${name}-${image.thumbnail}`}
+                            key={`${image.name}-${image.thumbnail}`}
                             image={image}
                             isSelected={isSelected}
                           />
+                        )}
                       </Flex>
                     );
                   }}
@@ -310,18 +351,23 @@ const ImageGalleryContent = () => {
                 <VirtuosoGrid
                   style={{ height: '100%' }}
                   data={images}
+                  endReached={handleEndReached}
                   components={{
                     Item: ItemContainer,
                     List: ListContainer,
                   }}
                   scrollerRef={setScroller}
                   itemContent={(index, image) => {
-                    const { name } = image;
+                    const isSelected =
-                    const isSelected = selectedImage?.name === name;
+                      image === PROGRESS_IMAGE_PLACEHOLDER
+                        ? false
+                        : selectedImage?.name === image?.name;
 
-                    return (
+                    return image === PROGRESS_IMAGE_PLACEHOLDER ? (
+                      <GalleryProgressImage key={PROGRESS_IMAGE_PLACEHOLDER} />
+                    ) : (
                       <HoverableImage
-                        key={`${name}-${image.thumbnail}`}
+                        key={`${image.name}-${image.thumbnail}`}
                         image={image}
                         isSelected={isSelected}
                       />
@@ -334,6 +380,7 @@ const ImageGalleryContent = () => {
               onClick={handleClickLoadMore}
               isDisabled={!areMoreImagesAvailable}
               isLoading={isLoading}
+              loadingText="Loading"
               flexShrink={0}
             >
               {areMoreImagesAvailable

invokeai/frontend/web/src/features/gallery/components/ImageGalleryPanel.tsx

@@ -5,7 +5,6 @@ import {
   // selectPrevImage,
   setGalleryImageMinimumWidth,
 } from 'features/gallery/store/gallerySlice';
-import { InvokeTabName } from 'features/ui/store/tabMap';
 
 import { clamp, isEqual } from 'lodash-es';
 import { useHotkeys } from 'react-hotkeys-hook';
@@ -13,11 +12,7 @@ import { useHotkeys } from 'react-hotkeys-hook';
 import './ImageGallery.css';
 import ImageGalleryContent from './ImageGalleryContent';
 import ResizableDrawer from 'features/ui/components/common/ResizableDrawer/ResizableDrawer';
-import {
+import { setShouldShowGallery } from 'features/ui/store/uiSlice';
-  setShouldShowGallery,
-  toggleGalleryPanel,
-  togglePinGalleryPanel,
-} from 'features/ui/store/uiSlice';
 import { createSelector } from '@reduxjs/toolkit';
 import {
   activeTabNameSelector,
@@ -26,22 +21,20 @@ import {
 import { isStagingSelector } from 'features/canvas/store/canvasSelectors';
 import { requestCanvasRescale } from 'features/canvas/store/thunks/requestCanvasScale';
 import { lightboxSelector } from 'features/lightbox/store/lightboxSelectors';
-import useResolution from 'common/hooks/useResolution';
-import { Flex } from '@chakra-ui/react';
 import { memo } from 'react';
 
-const GALLERY_TAB_WIDTHS: Record<
+// const GALLERY_TAB_WIDTHS: Record<
-  InvokeTabName,
+//   InvokeTabName,
-  { galleryMinWidth: number; galleryMaxWidth: number }
+//   { galleryMinWidth: number; galleryMaxWidth: number }
-> = {
+// > = {
-  // txt2img: { galleryMinWidth: 200, galleryMaxWidth: 500 },
+// txt2img: { galleryMinWidth: 200, galleryMaxWidth: 500 },
-  // img2img: { galleryMinWidth: 200, galleryMaxWidth: 500 },
+// img2img: { galleryMinWidth: 200, galleryMaxWidth: 500 },
-  generate: { galleryMinWidth: 200, galleryMaxWidth: 500 },
+// generate: { galleryMinWidth: 200, galleryMaxWidth: 500 },
-  unifiedCanvas: { galleryMinWidth: 200, galleryMaxWidth: 200 },
+// unifiedCanvas: { galleryMinWidth: 200, galleryMaxWidth: 200 },
-  nodes: { galleryMinWidth: 200, galleryMaxWidth: 500 },
+// nodes: { galleryMinWidth: 200, galleryMaxWidth: 500 },
-  // postprocessing: { galleryMinWidth: 200, galleryMaxWidth: 500 },
+// postprocessing: { galleryMinWidth: 200, galleryMaxWidth: 500 },
-  // training: { galleryMinWidth: 200, galleryMaxWidth: 500 },
+// training: { galleryMinWidth: 200, galleryMaxWidth: 500 },
-};
+// };
 
 const galleryPanelSelector = createSelector(
   [
@@ -73,50 +66,50 @@ const galleryPanelSelector = createSelector(
   }
 );
 
-export const ImageGalleryPanel = () => {
+const GalleryDrawer = () => {
   const dispatch = useAppDispatch();
   const {
     shouldPinGallery,
     shouldShowGallery,
     galleryImageMinimumWidth,
-    activeTabName,
+    // activeTabName,
-    isStaging,
+    // isStaging,
-    isResizable,
+    // isResizable,
-    isLightboxOpen,
+    // isLightboxOpen,
   } = useAppSelector(galleryPanelSelector);
 
-  const handleSetShouldPinGallery = () => {
+  // const handleSetShouldPinGallery = () => {
-    dispatch(togglePinGalleryPanel());
+  //   dispatch(togglePinGalleryPanel());
-    dispatch(requestCanvasRescale());
+  //   dispatch(requestCanvasRescale());
-  };
+  // };
 
-  const handleToggleGallery = () => {
+  // const handleToggleGallery = () => {
-    dispatch(toggleGalleryPanel());
+  //   dispatch(toggleGalleryPanel());
-    shouldPinGallery && dispatch(requestCanvasRescale());
+  //   shouldPinGallery && dispatch(requestCanvasRescale());
-  };
+  // };
 
   const handleCloseGallery = () => {
     dispatch(setShouldShowGallery(false));
     shouldPinGallery && dispatch(requestCanvasRescale());
   };
 
-  const resolution = useResolution();
+  // const resolution = useResolution();
 
-  useHotkeys(
+  // useHotkeys(
-    'g',
+  //   'g',
-    () => {
+  //   () => {
-      handleToggleGallery();
+  //     handleToggleGallery();
-    },
+  //   },
-    [shouldPinGallery]
+  //   [shouldPinGallery]
-  );
+  // );
 
-  useHotkeys(
+  // useHotkeys(
-    'shift+g',
+  //   'shift+g',
-    () => {
+  //   () => {
-      handleSetShouldPinGallery();
+  //     handleSetShouldPinGallery();
-    },
+  //   },
-    [shouldPinGallery]
+  //   [shouldPinGallery]
-  );
+  // );
 
   useHotkeys(
     'esc',
@@ -162,55 +155,71 @@ export const ImageGalleryPanel = () => {
     [galleryImageMinimumWidth]
   );
 
-  const calcGalleryMinHeight = () => {
+  // const calcGalleryMinHeight = () => {
-    if (resolution === 'desktop') return;
+  //   if (resolution === 'desktop') return;
-    return 300;
+  //   return 300;
-  };
+  // };
 
-  const imageGalleryContent = () => {
+  // const imageGalleryContent = () => {
-    return (
+  //   return (
-      <Flex
+  //     <Flex
-        w="100vw"
+  //       w="100vw"
-        h={{ base: 300, xl: '100vh' }}
+  //       h={{ base: 300, xl: '100vh' }}
-        paddingRight={{ base: 8, xl: 0 }}
+  //       paddingRight={{ base: 8, xl: 0 }}
-        paddingBottom={{ base: 4, xl: 0 }}
+  //       paddingBottom={{ base: 4, xl: 0 }}
-      >
+  //     >
-        <ImageGalleryContent />
+  //       <ImageGalleryContent />
-      </Flex>
+  //     </Flex>
-    );
+  //   );
-  };
+  // };
+
+  // const resizableImageGalleryContent = () => {
+  //   return (
+  //     <ResizableDrawer
+  //       direction="right"
+  //       isResizable={isResizable || !shouldPinGallery}
+  //       isOpen={shouldShowGallery}
+  //       onClose={handleCloseGallery}
+  //       isPinned={shouldPinGallery && !isLightboxOpen}
+  //       minWidth={
+  //         shouldPinGallery
+  //           ? GALLERY_TAB_WIDTHS[activeTabName].galleryMinWidth
+  //           : 200
+  //       }
+  //       maxWidth={
+  //         shouldPinGallery
+  //           ? GALLERY_TAB_WIDTHS[activeTabName].galleryMaxWidth
+  //           : undefined
+  //       }
+  //       minHeight={calcGalleryMinHeight()}
+  //     >
+  //       <ImageGalleryContent />
+  //     </ResizableDrawer>
+  //   );
+  // };
+
+  // const renderImageGallery = () => {
+  //   if (['mobile', 'tablet'].includes(resolution)) return imageGalleryContent();
+  //   return resizableImageGalleryContent();
+  // };
+
+  if (shouldPinGallery) {
+    return null;
+  }
 
-  const resizableImageGalleryContent = () => {
   return (
     <ResizableDrawer
       direction="right"
-        isResizable={isResizable || !shouldPinGallery}
+      isResizable={true}
       isOpen={shouldShowGallery}
       onClose={handleCloseGallery}
-        isPinned={shouldPinGallery && !isLightboxOpen}
+      minWidth={200}
-        minWidth={
-          shouldPinGallery
-            ? GALLERY_TAB_WIDTHS[activeTabName].galleryMinWidth
-            : 200
-        }
-        maxWidth={
-          shouldPinGallery
-            ? GALLERY_TAB_WIDTHS[activeTabName].galleryMaxWidth
-            : undefined
-        }
-        minHeight={calcGalleryMinHeight()}
     >
       <ImageGalleryContent />
     </ResizableDrawer>
   );
-  };
 
-  const renderImageGallery = () => {
+  // return renderImageGallery();
-    if (['mobile', 'tablet'].includes(resolution)) return imageGalleryContent();
-    return resizableImageGalleryContent();
-  };
-
-  return renderImageGallery();
 };
 
-export default memo(ImageGalleryPanel);
+export default memo(GalleryDrawer);

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

@@ -3,7 +3,6 @@ import {
   Box,
   Center,
   Flex,
-  Heading,
   IconButton,
   Link,
   Text,
@@ -19,8 +18,6 @@ import {
   setCfgScale,
   setHeight,
   setImg2imgStrength,
-  // setInitialImage,
-  setMaskPath,
   setPerlin,
   setSampler,
   setSeamless,
@@ -31,21 +28,14 @@ import {
   setThreshold,
   setWidth,
 } from 'features/parameters/store/generationSlice';
-import {
+import { setHiresFix } from 'features/parameters/store/postprocessingSlice';
-  setCodeformerFidelity,
-  setFacetoolStrength,
-  setFacetoolType,
-  setHiresFix,
-  setUpscalingDenoising,
-  setUpscalingLevel,
-  setUpscalingStrength,
-} from 'features/parameters/store/postprocessingSlice';
 import { setShouldShowImageDetails } from 'features/ui/store/uiSlice';
 import { memo } from 'react';
 import { useHotkeys } from 'react-hotkeys-hook';
 import { useTranslation } from 'react-i18next';
 import { FaCopy } from 'react-icons/fa';
 import { IoArrowUndoCircleOutline } from 'react-icons/io5';
+import { OverlayScrollbarsComponent } from 'overlayscrollbars-react';
 
 type MetadataItemProps = {
   isLink?: boolean;
@@ -300,7 +290,7 @@ const ImageMetadataViewer = memo(({ image }: ImageMetadataViewerProps) => {
           </Text>
         </Center>
       )}
-      <Flex gap={2} direction="column">
+      <Flex gap={2} direction="column" overflow="auto">
         <Flex gap={2}>
           <Tooltip label="Copy metadata JSON">
             <IconButton
@@ -314,22 +304,19 @@ const ImageMetadataViewer = memo(({ image }: ImageMetadataViewerProps) => {
           </Tooltip>
           <Text fontWeight="semibold">Metadata JSON:</Text>
         </Flex>
+        <OverlayScrollbarsComponent defer>
           <Box
             sx={{
-            mt: 0,
-            mr: 2,
-            mb: 4,
-            ml: 2,
               padding: 4,
               borderRadius: 'base',
-            overflowX: 'scroll',
-            wordBreak: 'break-all',
               bg: 'whiteAlpha.500',
               _dark: { bg: 'blackAlpha.500' },
+              w: 'max-content',
             }}
           >
             <pre>{metadataJSON}</pre>
           </Box>
+        </OverlayScrollbarsComponent>
       </Flex>
     </Flex>
   );

invokeai/frontend/web/src/features/gallery/store/actions.ts

@@ -0,0 +1,7 @@
+import { createAction } from '@reduxjs/toolkit';
+import { Image } from 'app/types/invokeai';
+import { SelectedImage } from 'features/parameters/store/actions';
+
+export const requestedImageDeletion = createAction<
+  Image | SelectedImage | undefined
+>('gallery/requestedImageDeletion');

invokeai/frontend/web/src/features/gallery/store/galleryPersistDenylist.ts

@@ -4,12 +4,13 @@ import { GalleryState } from './gallerySlice';
  * Gallery slice persist denylist
  */
 const itemsToDenylist: (keyof GalleryState)[] = [
-  'categories',
   'currentCategory',
-  'currentImage',
-  'currentImageUuid',
   'shouldAutoSwitchToNewImages',
-  'intermediateImage',
+];
+
+export const galleryPersistDenylist: (keyof GalleryState)[] = [
+  'currentCategory',
+  'shouldAutoSwitchToNewImages',
 ];
 
 export const galleryDenylist = itemsToDenylist.map(

invokeai/frontend/web/src/features/gallery/store/gallerySelectors.ts

@@ -1,23 +1,14 @@
 import { createSelector } from '@reduxjs/toolkit';
 import { RootState } from 'app/store/store';
 import { lightboxSelector } from 'features/lightbox/store/lightboxSelectors';
-import { configSelector } from 'features/system/store/configSelectors';
+
-import { systemSelector } from 'features/system/store/systemSelectors';
 import {
   activeTabNameSelector,
   uiSelector,
 } from 'features/ui/store/uiSelectors';
 import { isEqual } from 'lodash-es';
-import {
+import { selectResultsById, selectResultsEntities } from './resultsSlice';
-  selectResultsAll,
+import { selectUploadsAll, selectUploadsById } from './uploadsSlice';
-  selectResultsById,
-  selectResultsEntities,
-} from './resultsSlice';
-import {
-  selectUploadsAll,
-  selectUploadsById,
-  selectUploadsEntities,
-} from './uploadsSlice';
 
 export const gallerySelector = (state: RootState) => state.gallery;
 
@@ -44,6 +35,11 @@ export const imageGallerySelector = createSelector(
 
     const { isLightboxOpen } = lightbox;
 
+    const images =
+      currentCategory === 'results'
+        ? selectResultsEntities(state)
+        : selectUploadsAll(state);
+
     return {
       shouldPinGallery,
       galleryImageMinimumWidth,
@@ -53,7 +49,7 @@ export const imageGallerySelector = createSelector(
         : `repeat(auto-fill, minmax(${galleryImageMinimumWidth}px, auto))`,
       shouldAutoSwitchToNewImages,
       currentCategory,
-      images: state[currentCategory].entities,
+      images,
       galleryWidth,
       shouldEnableResize:
         isLightboxOpen ||

invokeai/frontend/web/src/features/gallery/store/gallerySlice.ts

@@ -1,10 +1,11 @@
 import type { PayloadAction } from '@reduxjs/toolkit';
 import { createSlice } from '@reduxjs/toolkit';
-import { invocationComplete } from 'services/events/actions';
+import { Image } from 'app/types/invokeai';
-import { isImageOutput } from 'services/types/guards';
+import { imageReceived, thumbnailReceived } from 'services/thunks/image';
-import { deserializeImageResponse } from 'services/util/deserializeImageResponse';
+import {
-import { imageUploaded } from 'services/thunks/image';
+  receivedResultImagesPage,
-import { SelectedImage } from 'features/parameters/store/generationSlice';
+  receivedUploadImagesPage,
+} from '../../../services/thunks/gallery';
 
 type GalleryImageObjectFitType = 'contain' | 'cover';
 
@@ -12,7 +13,7 @@ export interface GalleryState {
   /**
    * The selected image
    */
-  selectedImage?: SelectedImage;
+  selectedImage?: Image;
   galleryImageMinimumWidth: number;
   galleryImageObjectFit: GalleryImageObjectFitType;
   shouldAutoSwitchToNewImages: boolean;
@@ -21,8 +22,7 @@ export interface GalleryState {
   currentCategory: 'results' | 'uploads';
 }
 
-const initialState: GalleryState = {
+export const initialGalleryState: GalleryState = {
-  selectedImage: undefined,
   galleryImageMinimumWidth: 64,
   galleryImageObjectFit: 'cover',
   shouldAutoSwitchToNewImages: true,
@@ -33,12 +33,9 @@ const initialState: GalleryState = {
 
 export const gallerySlice = createSlice({
   name: 'gallery',
-  initialState,
+  initialState: initialGalleryState,
   reducers: {
-    imageSelected: (
+    imageSelected: (state, action: PayloadAction<Image | undefined>) => {
-      state,
-      action: PayloadAction<SelectedImage | undefined>
-    ) => {
       state.selectedImage = action.payload;
       // TODO: if the user selects an image, disable the auto switch?
       // state.shouldAutoSwitchToNewImages = false;
@@ -72,27 +69,50 @@ export const gallerySlice = createSlice({
     },
   },
   extraReducers(builder) {
-    /**
+    builder.addCase(imageReceived.fulfilled, (state, action) => {
-     * Invocation Complete
+      // When we get an updated URL for an image, we need to update the selectedImage in gallery,
-     */
+      // which is currently its own object (instead of a reference to an image in results/uploads)
-    builder.addCase(invocationComplete, (state, action) => {
+      const { imagePath } = action.payload;
-      const { data } = action.payload;
+      const { imageName } = action.meta.arg;
-      if (isImageOutput(data.result) && state.shouldAutoSwitchToNewImages) {
+
-        state.selectedImage = {
+      if (state.selectedImage?.name === imageName) {
-          name: data.result.image.image_name,
+        state.selectedImage.url = imagePath;
-          type: 'results',
-        };
       }
     });
 
-    /**
+    builder.addCase(thumbnailReceived.fulfilled, (state, action) => {
-     * Upload Image - FULFILLED
+      // When we get an updated URL for an image, we need to update the selectedImage in gallery,
-     */
+      // which is currently its own object (instead of a reference to an image in results/uploads)
-    builder.addCase(imageUploaded.fulfilled, (state, action) => {
+      const { thumbnailPath } = action.payload;
-      const { response } = action.payload;
+      const { thumbnailName } = action.meta.arg;
 
-      const uploadedImage = deserializeImageResponse(response);
+      if (state.selectedImage?.name === thumbnailName) {
-      state.selectedImage = { name: uploadedImage.name, type: 'uploads' };
+        state.selectedImage.thumbnail = thumbnailPath;
+      }
+    });
+    builder.addCase(receivedResultImagesPage.fulfilled, (state, action) => {
+      // rehydrate selectedImage URL when results list comes in
+      // solves case when outdated URL is in local storage
+      if (state.selectedImage) {
+        const selectedImageInResults = action.payload.items.find(
+          (image) => image.image_name === state.selectedImage!.name
+        );
+        if (selectedImageInResults) {
+          state.selectedImage.url = selectedImageInResults.image_url;
+        }
+      }
+    });
+    builder.addCase(receivedUploadImagesPage.fulfilled, (state, action) => {
+      // rehydrate selectedImage URL when results list comes in
+      // solves case when outdated URL is in local storage
+      if (state.selectedImage) {
+        const selectedImageInResults = action.payload.items.find(
+          (image) => image.image_name === state.selectedImage!.name
+        );
+        if (selectedImageInResults) {
+          state.selectedImage.url = selectedImageInResults.image_url;
+        }
+      }
     });
   },
 });

invokeai/frontend/web/src/features/gallery/store/resultsPersistDenylist.ts

@@ -5,7 +5,9 @@ import { ResultsState } from './resultsSlice';
  *
  * Currently denylisting results slice entirely, see persist config in store.ts
  */
-const itemsToDenylist: (keyof ResultsState)[] = ['isLoading'];
+const itemsToDenylist: (keyof ResultsState)[] = [];
+
+export const resultsPersistDenylist: (keyof ResultsState)[] = [];
 
 export const resultsDenylist = itemsToDenylist.map(
   (denylistItem) => `results.${denylistItem}`

invokeai/frontend/web/src/features/gallery/store/resultsSlice.ts

@@ -1,17 +1,11 @@
 import { createEntityAdapter, createSlice } from '@reduxjs/toolkit';
 import { Image } from 'app/types/invokeai';
-import { invocationComplete } from 'services/events/actions';
 
 import { RootState } from 'app/store/store';
 import {
   receivedResultImagesPage,
   IMAGES_PER_PAGE,
 } from 'services/thunks/gallery';
-import { isImageOutput } from 'services/types/guards';
-import {
-  buildImageUrls,
-  extractTimestampFromImageName,
-} from 'services/util/deserializeImageField';
 import { deserializeImageResponse } from 'services/util/deserializeImageResponse';
 import {
   imageDeleted,
@@ -73,44 +67,6 @@ const resultsSlice = createSlice({
       state.isLoading = false;
     });
 
-    /**
-     * Invocation Complete
-     */
-    builder.addCase(invocationComplete, (state, action) => {
-      const { data, shouldFetchImages } = action.payload;
-      const { result, node, graph_execution_state_id } = data;
-
-      if (isImageOutput(result)) {
-        const name = result.image.image_name;
-        const type = result.image.image_type;
-
-        // if we need to refetch, set URLs to placeholder for now
-        const { url, thumbnail } = shouldFetchImages
-          ? { url: '', thumbnail: '' }
-          : buildImageUrls(type, name);
-
-        const timestamp = extractTimestampFromImageName(name);
-
-        const image: Image = {
-          name,
-          type,
-          url,
-          thumbnail,
-          metadata: {
-            created: timestamp,
-            width: result.width,
-            height: result.height,
-            invokeai: {
-              session_id: graph_execution_state_id,
-              ...(node ? { node } : {}),
-            },
-          },
-        };
-
-        resultsAdapter.setOne(state, image);
-      }
-    });
-
     /**
      * Image Received - FULFILLED
      */
@@ -142,9 +98,10 @@ const resultsSlice = createSlice({
     });
 
     /**
-     * Delete Image - FULFILLED
+     * Delete Image - PENDING
+     * Pre-emptively remove the image from the gallery
      */
-    builder.addCase(imageDeleted.fulfilled, (state, action) => {
+    builder.addCase(imageDeleted.pending, (state, action) => {
       const { imageType, imageName } = action.meta.arg;
 
       if (imageType === 'results') {

invokeai/frontend/web/src/features/gallery/store/uploadsPersistDenylist.ts

@@ -5,7 +5,8 @@ import { UploadsState } from './uploadsSlice';
  *
  * Currently denylisting uploads slice entirely, see persist config in store.ts
  */
-const itemsToDenylist: (keyof UploadsState)[] = ['isLoading'];
+const itemsToDenylist: (keyof UploadsState)[] = [];
+export const uploadsPersistDenylist: (keyof UploadsState)[] = [];
 
 export const uploadsDenylist = itemsToDenylist.map(
   (denylistItem) => `uploads.${denylistItem}`

invokeai/frontend/web/src/features/gallery/store/uploadsSlice.ts

@@ -6,7 +6,7 @@ import {
   receivedUploadImagesPage,
   IMAGES_PER_PAGE,
 } from 'services/thunks/gallery';
-import { imageDeleted, imageUploaded } from 'services/thunks/image';
+import { imageDeleted } from 'services/thunks/image';
 import { deserializeImageResponse } from 'services/util/deserializeImageResponse';
 
 export const uploadsAdapter = createEntityAdapter<Image>({
@@ -21,7 +21,7 @@ type AdditionalUploadsState = {
   nextPage: number;
 };
 
-const initialUploadsState =
+export const initialUploadsState =
   uploadsAdapter.getInitialState<AdditionalUploadsState>({
     page: 0,
     pages: 0,
@@ -35,7 +35,7 @@ const uploadsSlice = createSlice({
   name: 'uploads',
   initialState: initialUploadsState,
   reducers: {
-    uploadAdded: uploadsAdapter.addOne,
+    uploadAdded: uploadsAdapter.upsertOne,
   },
   extraReducers: (builder) => {
     /**
@@ -62,20 +62,10 @@ const uploadsSlice = createSlice({
     });
 
     /**
-     * Upload Image - FULFILLED
+     * Delete Image - pending
+     * Pre-emptively remove the image from the gallery
      */
-    builder.addCase(imageUploaded.fulfilled, (state, action) => {
+    builder.addCase(imageDeleted.pending, (state, action) => {
-      const { location, response } = action.payload;
-
-      const uploadedImage = deserializeImageResponse(response);
-
-      uploadsAdapter.setOne(state, uploadedImage);
-    });
-
-    /**
-     * Delete Image - FULFILLED
-     */
-    builder.addCase(imageDeleted.fulfilled, (state, action) => {
       const { imageType, imageName } = action.meta.arg;
 
       if (imageType === 'uploads') {

invokeai/frontend/web/src/features/lightbox/components/ReactPanZoomImage.tsx

@@ -4,7 +4,7 @@ import * as InvokeAI from 'app/types/invokeai';
 import { useGetUrl } from 'common/util/getUrl';
 
 type ReactPanZoomProps = {
-  image: InvokeAI._Image;
+  image: InvokeAI.Image;
   styleClass?: string;
   alt?: string;
   ref?: React.Ref<HTMLImageElement>;

invokeai/frontend/web/src/features/lightbox/store/lightboxPersistDenylist.ts

@@ -4,6 +4,9 @@ import { LightboxState } from './lightboxSlice';
  * Lightbox slice persist denylist
  */
 const itemsToDenylist: (keyof LightboxState)[] = ['isLightboxOpen'];
+export const lightboxPersistDenylist: (keyof LightboxState)[] = [
+  'isLightboxOpen',
+];
 
 export const lightboxDenylist = itemsToDenylist.map(
   (denylistItem) => `lightbox.${denylistItem}`

invokeai/frontend/web/src/features/lightbox/store/lightboxSlice.ts

@@ -5,7 +5,7 @@ export interface LightboxState {
   isLightboxOpen: boolean;
 }
 
-const initialLightboxState: LightboxState = {
+export const initialLightboxState: LightboxState = {
   isLightboxOpen: false,
 };
 

invokeai/frontend/web/src/features/nodes/components/AddNodeMenu.tsx

@@ -1,5 +1,3 @@
-import { v4 as uuidv4 } from 'uuid';
-
 import 'reactflow/dist/style.css';
 import { memo, useCallback } from 'react';
 import {
@@ -8,12 +6,11 @@ import {
   MenuButton,
   MenuList,
   MenuItem,
-  IconButton,
 } from '@chakra-ui/react';
-import { FaEllipsisV, FaPlus } from 'react-icons/fa';
+import { FaEllipsisV } from 'react-icons/fa';
 import { useAppDispatch, useAppSelector } from 'app/store/storeHooks';
 import { nodeAdded } from '../store/nodesSlice';
-import { cloneDeep, map } from 'lodash-es';
+import { map } from 'lodash-es';
 import { RootState } from 'app/store/store';
 import { useBuildInvocation } from '../hooks/useBuildInvocation';
 import { addToast } from 'features/system/store/systemSlice';