Merge branch 'main' into lstein/config-management-fixes

docs/features/LOGGING.md

@@ -0,0 +1,171 @@
+---
+title: Controlling Logging
+---
+
+# :material-image-off: Controlling Logging
+
+## Controlling How InvokeAI Logs Status Messages
+
+InvokeAI logs status messages using a configurable logging system. You
+can log to the terminal window, to a designated file on the local
+machine, to the syslog facility on a Linux or Mac, or to a properly
+configured web server. You can configure several logs at the same
+time, and control the level of message logged and the logging format
+(to a limited extent).
+
+Three command-line options control logging:
+
+### `--log_handlers <handler1> <handler2> ...`
+
+This option activates one or more log handlers. Options are "console",
+"file", "syslog" and "http". To specify more than one, separate them
+by spaces:
+
+```bash
+invokeai-web --log_handlers console syslog=/dev/log file=C:\Users\fred\invokeai.log
+```
+
+The format of these options is described below.
+
+### `--log_format {plain|color|legacy|syslog}`
+
+This controls the format of log messages written to the console. Only
+the "console" log handler is currently affected by this setting.
+
+* "plain" provides formatted messages like this:
+
+```bash
+
+[2023-05-24 23:18:2[2023-05-24 23:18:50,352]::[InvokeAI]::DEBUG --> this is a debug message
+[2023-05-24 23:18:50,352]::[InvokeAI]::INFO --> this is an informational messages
+[2023-05-24 23:18:50,352]::[InvokeAI]::WARNING --> this is a warning
+[2023-05-24 23:18:50,352]::[InvokeAI]::ERROR --> this is an error
+[2023-05-24 23:18:50,352]::[InvokeAI]::CRITICAL --> this is a critical error
+```
+
+* "color" produces similar output, but the text will be color coded to
+indicate the severity of the message.
+
+* "legacy" produces output similar to InvokeAI versions 2.3 and earlier:
+
+```bash
+### this is a critical error
+*** this is an error
+** this is a warning
+>> this is an informational messages
+   | this is a debug message
+```
+
+* "syslog" produces messages suitable for syslog entries:
+
+```bash
+InvokeAI [2691178] <CRITICAL> this is a critical error
+InvokeAI [2691178] <ERROR> this is an error
+InvokeAI [2691178] <WARNING> this is a warning
+InvokeAI [2691178] <INFO> this is an informational messages
+InvokeAI [2691178] <DEBUG> this is a debug message
+```
+
+(note that the date, time and hostname will be added by the syslog
+system)
+
+### `--log_level {debug|info|warning|error|critical}`
+
+Providing this command-line option will cause only messages at the
+specified level or above to be emitted.
+
+## Console logging
+
+When "console" is provided to `--log_handlers`, messages will be
+written to the command line window in which InvokeAI was launched. By
+default, the color formatter will be used unless overridden by
+`--log_format`.
+
+## File logging
+
+When "file" is provided to `--log_handlers`, entries will be written
+to the file indicated in the path argument. By default, the "plain"
+format will be used:
+
+```bash
+invokeai-web --log_handlers file=/var/log/invokeai.log
+```
+
+## Syslog logging
+
+When "syslog" is requested, entries will be sent to the syslog
+system. There are a variety of ways to control where the log message
+is sent:
+
+* Send to the local machine using the `/dev/log` socket:
+
+```
+invokeai-web --log_handlers syslog=/dev/log
+```
+
+* Send to the local machine using a UDP message:
+
+```
+invokeai-web --log_handlers syslog=localhost
+```
+
+* Send to the local machine using a UDP message on a nonstandard
+  port:
+
+```
+invokeai-web --log_handlers syslog=localhost:512
+```
+
+* Send to a remote machine named "loghost" on the local LAN using
+  facility LOG_USER and UDP packets:
+
+```
+invokeai-web --log_handlers syslog=loghost,facility=LOG_USER,socktype=SOCK_DGRAM
+```
+
+This can be abbreviated `syslog=loghost`, as LOG_USER and SOCK_DGRAM
+are defaults.
+
+* Send to a remote machine named "loghost" using the facility LOCAL0
+  and using a TCP socket:
+
+```
+invokeai-web --log_handlers syslog=loghost,facility=LOG_LOCAL0,socktype=SOCK_STREAM
+```
+
+If no arguments are specified (just a bare "syslog"), then the logging
+system will look for a UNIX socket named `/dev/log`, and if not found
+try to send a UDP message to `localhost`. The Macintosh OS used to
+support logging to a socket named `/var/run/syslog`, but this feature
+has since been disabled.
+
+## Web logging
+
+If you have access to a web server that is configured to log messages
+when a particular URL is requested, you can log using the "http"
+method:
+
+```
+invokeai-web --log_handlers http=http://my.server/path/to/logger,method=POST
+```
+
+The optional [,method=] part can be used to specify whether the URL
+accepts GET (default) or POST messages.
+
+Currently password authentication and SSL are not supported.
+
+## Using the configuration file
+
+You can set and forget logging options by adding a "Logging" section
+to `invokeai.yaml`:
+
+```
+InvokeAI:
+  [... other settings...]
+  Logging:
+    log_handlers:
+       - console
+       - syslog=/dev/log
+    log_level: info
+    log_format: color
+```

docs/features/index.md

@@ -57,6 +57,9 @@ Personalize models by adding your own style or subjects.
 ## * [The NSFW Checker](NSFW.md)
 Prevent InvokeAI from displaying unwanted racy images.
 
+## * [Controlling Logging](LOGGING.md)
+Control how InvokeAI logs status messages.
+
 ## * [Miscellaneous](OTHER.md)
 Run InvokeAI on Google Colab, generate images with repeating patterns,
 batch process a file of prompts, increase the "creativity" of image

invokeai/app/invocations/compel.py

@@ -3,6 +3,7 @@ from pydantic import BaseModel, Field
 
 from invokeai.app.invocations.util.choose_model import choose_model
 from .baseinvocation import BaseInvocation, BaseInvocationOutput, InvocationContext, InvocationConfig
+from ...backend.prompting.conditioning import try_parse_legacy_blend
 
 from ...backend.util.devices import choose_torch_device, torch_dtype
 from ...backend.stable_diffusion.diffusion import InvokeAIDiffuserComponent
@@ -13,7 +14,7 @@ from compel.prompt_parser import (
     Blend,
     CrossAttentionControlSubstitute,
     FlattenedPrompt,
-    Fragment,
+    Fragment, Conjunction,
 )
 
 
@@ -93,25 +94,22 @@ class CompelInvocation(BaseInvocation):
             text_encoder=text_encoder,
             textual_inversion_manager=pipeline.textual_inversion_manager,
             dtype_for_device_getter=torch_dtype,
-            truncate_long_prompts=True, # TODO:
+            truncate_long_prompts=False,
         )
 
-        # TODO: support legacy blend?
-
+        legacy_blend = try_parse_legacy_blend(prompt_str, skip_normalize=False)
+        if legacy_blend is not None:
+            conjunction = legacy_blend
+        else:
             conjunction = Compel.parse_prompt_string(prompt_str)
-        prompt: Union[FlattenedPrompt, Blend] = conjunction.prompts[0]
 
         if context.services.configuration.log_tokenization:
-            log_tokenization_for_prompt_object(prompt, tokenizer)
+            log_tokenization_for_conjunction(conjunction, tokenizer)
 
-        c, options = compel.build_conditioning_tensor_for_prompt_object(prompt)
-
-        # TODO: long prompt support
-        #if not self.truncate_long_prompts:
-        #    [c, uc] = compel.pad_conditioning_tensors_to_same_length([c, uc])
+        c, options = compel.build_conditioning_tensor_for_conjunction(conjunction)
 
         ec = InvokeAIDiffuserComponent.ExtraConditioningInfo(
-            tokens_count_including_eos_bos=get_max_token_count(tokenizer, prompt),
+            tokens_count_including_eos_bos=get_max_token_count(tokenizer, conjunction),
             cross_attention_control_args=options.get("cross_attention_control", None),
         )
 
@@ -128,14 +126,22 @@ class CompelInvocation(BaseInvocation):
 
 
 def get_max_token_count(
-    tokenizer, prompt: Union[FlattenedPrompt, Blend], truncate_if_too_long=False
+    tokenizer, prompt: Union[FlattenedPrompt, Blend, Conjunction], truncate_if_too_long=False
 ) -> int:
     if type(prompt) is Blend:
         blend: Blend = prompt
         return max(
             [
-                get_max_token_count(tokenizer, c, truncate_if_too_long)
-                for c in blend.prompts
+                get_max_token_count(tokenizer, p, truncate_if_too_long)
+                for p in blend.prompts
+            ]
+        )
+    elif type(prompt) is Conjunction:
+        conjunction: Conjunction = prompt
+        return sum(
+            [
+                get_max_token_count(tokenizer, p, truncate_if_too_long)
+                for p in conjunction.prompts
             ]
         )
     else:
@@ -170,6 +176,22 @@ def get_tokens_for_prompt_object(
     return tokens
 
 
+def log_tokenization_for_conjunction(
+    c: Conjunction, tokenizer, display_label_prefix=None
+):
+    display_label_prefix = display_label_prefix or ""
+    for i, p in enumerate(c.prompts):
+        if len(c.prompts)>1:
+            this_display_label_prefix = f"{display_label_prefix}(conjunction part {i + 1}, weight={c.weights[i]})"
+        else:
+            this_display_label_prefix = display_label_prefix
+        log_tokenization_for_prompt_object(
+            p,
+            tokenizer,
+            display_label_prefix=this_display_label_prefix
+        )
+
+
 def log_tokenization_for_prompt_object(
     p: Union[Blend, FlattenedPrompt], tokenizer, display_label_prefix=None
 ):

invokeai/app/invocations/controlnet_image_processors.py

@@ -94,13 +94,13 @@ CONTROLNET_DEFAULT_MODELS = [
 CONTROLNET_NAME_VALUES = Literal[tuple(CONTROLNET_DEFAULT_MODELS)]
 
 class ControlField(BaseModel):
-    image: ImageField = Field(default=None, description="processed image")
-    control_model: Optional[str] = Field(default=None, description="control model used")
-    control_weight: Optional[float] = Field(default=1, description="weight given to controlnet")
+    image: ImageField = Field(default=None, description="The control image")
+    control_model: Optional[str] = Field(default=None, description="The ControlNet model to use")
+    control_weight: Optional[float] = Field(default=1, description="The weight given to the ControlNet")
     begin_step_percent: float = Field(default=0, ge=0, le=1,
-                                                description="% of total steps at which controlnet is first applied")
+                                                description="When the ControlNet is first applied (% of total steps)")
     end_step_percent: float = Field(default=1, ge=0, le=1,
-                                    description="% of total steps at which controlnet is last applied")
+                                    description="When the ControlNet is last applied (% of total steps)")
 
     class Config:
         schema_extra = {
@@ -112,7 +112,7 @@ class ControlOutput(BaseInvocationOutput):
     """node output for ControlNet info"""
     # fmt: off
     type: Literal["control_output"] = "control_output"
-    control: ControlField = Field(default=None, description="The control info dict")
+    control: ControlField = Field(default=None, description="The output control image")
     # fmt: on
 
 
@@ -121,15 +121,15 @@ class ControlNetInvocation(BaseInvocation):
     # fmt: off
     type: Literal["controlnet"] = "controlnet"
     # Inputs
-    image: ImageField = Field(default=None, description="image to process")
+    image: ImageField = Field(default=None, description="The control image")
     control_model: CONTROLNET_NAME_VALUES = Field(default="lllyasviel/sd-controlnet-canny",
-                                                  description="control model used")
-    control_weight: float = Field(default=1.0, ge=0, le=1, description="weight given to controlnet")
+                                                  description="The ControlNet model to use")
+    control_weight: float = Field(default=1.0, ge=0, le=1, description="The weight given to the ControlNet")
     # TODO: add support in backend core for begin_step_percent, end_step_percent, guess_mode
     begin_step_percent: float = Field(default=0, ge=0, le=1,
-                                        description="% of total steps at which controlnet is first applied")
+                                        description="When the ControlNet is first applied (% of total steps)")
     end_step_percent: float = Field(default=1, ge=0, le=1,
-                                      description="% of total steps at which controlnet is last applied")
+                                      description="When the ControlNet is last applied (% of total steps)")
     # fmt: on
 
 
@@ -152,7 +152,7 @@ class ImageProcessorInvocation(BaseInvocation, PILInvocationConfig):
     # fmt: off
     type: Literal["image_processor"] = "image_processor"
     # Inputs
-    image: ImageField = Field(default=None, description="image to process")
+    image: ImageField = Field(default=None, description="The image to process")
     # fmt: on
 
 
@@ -204,8 +204,8 @@ class CannyImageProcessorInvocation(ImageProcessorInvocation, PILInvocationConfi
     # fmt: off
     type: Literal["canny_image_processor"] = "canny_image_processor"
     # Input
-    low_threshold: float = Field(default=100, ge=0, description="low threshold of Canny pixel gradient")
-    high_threshold: float = Field(default=200, ge=0, description="high threshold of Canny pixel gradient")
+    low_threshold: int = Field(default=100, ge=0, le=255, description="The low threshold of the Canny pixel gradient (0-255)")
+    high_threshold: int = Field(default=200, ge=0, le=255, description="The high threshold of the Canny pixel gradient (0-255)")
     # fmt: on
 
     def run_processor(self, image):
@@ -214,16 +214,16 @@ class CannyImageProcessorInvocation(ImageProcessorInvocation, PILInvocationConfi
         return processed_image
 
 
-class HedImageprocessorInvocation(ImageProcessorInvocation, PILInvocationConfig):
+class HedImageProcessorInvocation(ImageProcessorInvocation, PILInvocationConfig):
     """Applies HED edge detection to image"""
     # fmt: off
     type: Literal["hed_image_processor"] = "hed_image_processor"
     # Inputs
-    detect_resolution: int = Field(default=512, ge=0, description="pixel resolution for edge detection")
-    image_resolution: int = Field(default=512, ge=0, description="pixel resolution for output image")
+    detect_resolution: int = Field(default=512, ge=0, description="The pixel resolution for detection")
+    image_resolution: int = Field(default=512, ge=0, description="The pixel resolution for the output image")
     # safe not supported in controlnet_aux v0.0.3
     # safe: bool = Field(default=False, description="whether to use safe mode")
-    scribble: bool = Field(default=False, description="whether to use scribble mode")
+    scribble: bool = Field(default=False, description="Whether to use scribble mode")
     # fmt: on
 
     def run_processor(self, image):
@@ -243,9 +243,9 @@ class LineartImageProcessorInvocation(ImageProcessorInvocation, PILInvocationCon
     # fmt: off
     type: Literal["lineart_image_processor"] = "lineart_image_processor"
     # Inputs
-    detect_resolution: int = Field(default=512, ge=0, description="pixel resolution for edge detection")
-    image_resolution: int = Field(default=512, ge=0, description="pixel resolution for output image")
-    coarse: bool = Field(default=False, description="whether to use coarse mode")
+    detect_resolution: int = Field(default=512, ge=0, description="The pixel resolution for detection")
+    image_resolution: int = Field(default=512, ge=0, description="The pixel resolution for the output image")
+    coarse: bool = Field(default=False, description="Whether to use coarse mode")
     # fmt: on
 
     def run_processor(self, image):
@@ -262,8 +262,8 @@ class LineartAnimeImageProcessorInvocation(ImageProcessorInvocation, PILInvocati
     # fmt: off
     type: Literal["lineart_anime_image_processor"] = "lineart_anime_image_processor"
     # Inputs
-    detect_resolution: int = Field(default=512, ge=0, description="pixel resolution for edge detection")
-    image_resolution: int = Field(default=512, ge=0, description="pixel resolution for output image")
+    detect_resolution: int = Field(default=512, ge=0, description="The pixel resolution for detection")
+    image_resolution: int = Field(default=512, ge=0, description="The pixel resolution for the output image")
     # fmt: on
 
     def run_processor(self, image):
@@ -280,9 +280,9 @@ class OpenposeImageProcessorInvocation(ImageProcessorInvocation, PILInvocationCo
     # fmt: off
     type: Literal["openpose_image_processor"] = "openpose_image_processor"
     # Inputs
-    hand_and_face: bool = Field(default=False, description="whether to use hands and face mode")
-    detect_resolution: int = Field(default=512, ge=0, description="pixel resolution for edge detection")
-    image_resolution: int = Field(default=512, ge=0, description="pixel resolution for output image")
+    hand_and_face: bool = Field(default=False, description="Whether to use hands and face mode")
+    detect_resolution: int = Field(default=512, ge=0, description="The pixel resolution for detection")
+    image_resolution: int = Field(default=512, ge=0, description="The pixel resolution for the output image")
     # fmt: on
 
     def run_processor(self, image):
@@ -300,8 +300,8 @@ class MidasDepthImageProcessorInvocation(ImageProcessorInvocation, PILInvocation
     # fmt: off
     type: Literal["midas_depth_image_processor"] = "midas_depth_image_processor"
     # Inputs
-    a_mult: float = Field(default=2.0, ge=0, description="Midas parameter a = amult * PI")
-    bg_th: float = Field(default=0.1, ge=0, description="Midas parameter bg_th")
+    a_mult: float = Field(default=2.0, ge=0, description="Midas parameter `a_mult` (a = a_mult * PI)")
+    bg_th: float = Field(default=0.1, ge=0, description="Midas parameter `bg_th`")
     # depth_and_normal not supported in controlnet_aux v0.0.3
     # depth_and_normal: bool = Field(default=False, description="whether to use depth and normal mode")
     # fmt: on
@@ -322,8 +322,8 @@ class NormalbaeImageProcessorInvocation(ImageProcessorInvocation, PILInvocationC
     # fmt: off
     type: Literal["normalbae_image_processor"] = "normalbae_image_processor"
     # Inputs
-    detect_resolution: int = Field(default=512, ge=0, description="pixel resolution for edge detection")
-    image_resolution: int = Field(default=512, ge=0, description="pixel resolution for output image")
+    detect_resolution: int = Field(default=512, ge=0, description="The pixel resolution for detection")
+    image_resolution: int = Field(default=512, ge=0, description="The pixel resolution for the output image")
     # fmt: on
 
     def run_processor(self, image):
@@ -339,10 +339,10 @@ class MlsdImageProcessorInvocation(ImageProcessorInvocation, PILInvocationConfig
     # fmt: off
     type: Literal["mlsd_image_processor"] = "mlsd_image_processor"
     # Inputs
-    detect_resolution: int = Field(default=512, ge=0, description="pixel resolution for edge detection")
-    image_resolution: int = Field(default=512, ge=0, description="pixel resolution for output image")
-    thr_v: float = Field(default=0.1, ge=0, description="MLSD parameter thr_v")
-    thr_d: float = Field(default=0.1, ge=0, description="MLSD parameter thr_d")
+    detect_resolution: int = Field(default=512, ge=0, description="The pixel resolution for detection")
+    image_resolution: int = Field(default=512, ge=0, description="The pixel resolution for the output image")
+    thr_v: float = Field(default=0.1, ge=0, description="MLSD parameter `thr_v`")
+    thr_d: float = Field(default=0.1, ge=0, description="MLSD parameter `thr_d`")
     # fmt: on
 
     def run_processor(self, image):
@@ -360,10 +360,10 @@ class PidiImageProcessorInvocation(ImageProcessorInvocation, PILInvocationConfig
     # fmt: off
     type: Literal["pidi_image_processor"] = "pidi_image_processor"
     # Inputs
-    detect_resolution: int = Field(default=512, ge=0, description="pixel resolution for edge detection")
-    image_resolution: int = Field(default=512, ge=0, description="pixel resolution for output image")
-    safe: bool = Field(default=False, description="whether to use safe mode")
-    scribble: bool = Field(default=False, description="whether to use scribble mode")
+    detect_resolution: int = Field(default=512, ge=0, description="The pixel resolution for detection")
+    image_resolution: int = Field(default=512, ge=0, description="The pixel resolution for the output image")
+    safe: bool = Field(default=False, description="Whether to use safe mode")
+    scribble: bool = Field(default=False, description="Whether to use scribble mode")
     # fmt: on
 
     def run_processor(self, image):
@@ -381,11 +381,11 @@ class ContentShuffleImageProcessorInvocation(ImageProcessorInvocation, PILInvoca
     # fmt: off
     type: Literal["content_shuffle_image_processor"] = "content_shuffle_image_processor"
     # Inputs
-    detect_resolution: int = Field(default=512, ge=0, description="pixel resolution for edge detection")
-    image_resolution: int = Field(default=512, ge=0, description="pixel resolution for output image")
-    h: Union[int | None] = Field(default=512, ge=0, description="content shuffle h parameter")
-    w: Union[int | None] = Field(default=512, ge=0, description="content shuffle w parameter")
-    f: Union[int | None] = Field(default=256, ge=0, description="cont")
+    detect_resolution: int = Field(default=512, ge=0, description="The pixel resolution for detection")
+    image_resolution: int = Field(default=512, ge=0, description="The pixel resolution for the output image")
+    h: Union[int, None] = Field(default=512, ge=0, description="Content shuffle `h` parameter")
+    w: Union[int, None] = Field(default=512, ge=0, description="Content shuffle `w` parameter")
+    f: Union[int, None] = Field(default=256, ge=0, description="Content shuffle `f` parameter")
     # fmt: on
 
     def run_processor(self, image):
@@ -418,8 +418,8 @@ class MediapipeFaceProcessorInvocation(ImageProcessorInvocation, PILInvocationCo
     # fmt: off
     type: Literal["mediapipe_face_processor"] = "mediapipe_face_processor"
     # Inputs
-    max_faces: int = Field(default=1, ge=1, description="maximum number of faces to detect")
-    min_confidence: float = Field(default=0.5, ge=0, le=1, description="minimum confidence for face detection")
+    max_faces: int = Field(default=1, ge=1, description="Maximum number of faces to detect")
+    min_confidence: float = Field(default=0.5, ge=0, le=1, description="Minimum confidence for face detection")
     # fmt: on
 
     def run_processor(self, image):

invokeai/app/invocations/latent.py

@@ -4,6 +4,7 @@ import random
 import einops
 from typing import Literal, Optional, Union, List
 
+from compel import Compel
 from diffusers.pipelines.stable_diffusion.pipeline_stable_diffusion_controlnet import MultiControlNetModel
 
 from pydantic import BaseModel, Field, validator
@@ -233,6 +234,15 @@ class TextToLatentsInvocation(BaseInvocation):
         c, extra_conditioning_info = context.services.latents.get(self.positive_conditioning.conditioning_name)
         uc, _ = context.services.latents.get(self.negative_conditioning.conditioning_name)
 
+        compel = Compel(
+            tokenizer=model.tokenizer,
+            text_encoder=model.text_encoder,
+            textual_inversion_manager=model.textual_inversion_manager,
+            dtype_for_device_getter=torch_dtype,
+            truncate_long_prompts=False,
+        )
+        [c, uc] = compel.pad_conditioning_tensors_to_same_length([c, uc])
+
         conditioning_data = ConditioningData(
             uc,
             c,

invokeai/app/services/config.py

@@ -165,14 +165,13 @@ two configs are kept in separate sections of the config file:
 from __future__ import annotations
 import argparse
 import pydoc
-import typing
 import os
 import sys
 from argparse import ArgumentParser
 from omegaconf import OmegaConf, DictConfig
 from pathlib import Path
 from pydantic import BaseSettings, Field, parse_obj_as
-from typing import Any, ClassVar, Dict, List, Literal, Type, Union, get_origin, get_type_hints, get_args
+from typing import ClassVar, Dict, List, Literal, Type, Union, get_origin, get_type_hints, get_args
 
 INIT_FILE = Path('invokeai.yaml')
 LEGACY_INIT_FILE = Path('invokeai.init')
@@ -187,7 +186,7 @@ class InvokeAISettings(BaseSettings):
 
     def parse_args(self, argv: list=sys.argv[1:]):
         parser = self.get_parser()
-        opt, _ = parser.parse_known_args(argv)
+        opt = parser.parse_args(argv)
         for name in self.__fields__:
             if name not in self._excluded():
                 setattr(self, name, getattr(opt,name))
@@ -389,6 +388,11 @@ setting environment variables INVOKEAI_<setting>.
 
     model               : str = Field(default='stable-diffusion-1.5', description='Initial model name', category='Models')
     embeddings          : bool = Field(default=True, description='Load contents of embeddings directory', category='Models')
+
+    log_handlers        : List[str] = Field(default=["console"], description='Log handler. Valid options are "console", "file=<path>", "syslog=path|address:host:port", "http=<url>"', category="Logging")
+    # note - would be better to read the log_format values from logging.py, but this creates circular dependencies issues
+    log_format          : Literal[tuple(['plain','color','syslog','legacy'])] = Field(default="color", description='Log format. Use "plain" for text-only, "color" for colorized output, "legacy" for 2.3-style logging and "syslog" for syslog-style', category="Logging")
+    log_level           : Literal[tuple(["debug","info","warning","error","critical"])] = Field(default="debug", description="Emit logging messages at this level or  higher", category="Logging")
     #fmt: on
 
     def parse_args(self, argv: List[str]=None, conf: DictConfig = None, clobber=False):

invokeai/backend/config/invokeai_configure.py

@@ -35,15 +35,19 @@ from transformers import (
     CLIPTextModel,
     CLIPTokenizer,
 )
-
 import invokeai.configs as configs
 
+from invokeai.app.services.config import (
+    get_invokeai_config,
+    InvokeAIAppConfig,
+)
 from invokeai.frontend.install.model_install import addModelsForm, process_and_execute
 from invokeai.frontend.install.widgets import (
     CenteredButtonPress,
     IntTitleSlider,
     set_min_terminal_size,
 )
+
 from invokeai.backend.config.legacy_arg_parsing import legacy_parser
 from invokeai.backend.config.model_install_backend import (
     default_dataset,
@@ -51,6 +55,7 @@ from invokeai.backend.config.model_install_backend import (
     hf_download_with_resume,
     recommended_datasets,
 )
+
 from invokeai.app.services.config import InvokeAIAppConfig
 
 warnings.filterwarnings("ignore")
@@ -59,6 +64,7 @@ transformers.logging.set_verbosity_error()
 
 
 # --------------------------globals-----------------------
+
 config = InvokeAIAppConfig.get_config()
 
 Model_dir = "models"
@@ -817,6 +823,7 @@ def main():
         if old_init_file.exists() and not new_init_file.exists():
             print('** Migrating invokeai.init to invokeai.yaml')
             migrate_init_file(old_init_file)
+
             # Load new init file into config
             config.parse_args(argv=[],conf=OmegaConf.load(new_init_file))
 

invokeai/backend/config/model_install_backend.py

@@ -28,6 +28,7 @@ warnings.filterwarnings("ignore")
 
 # --------------------------globals-----------------------
 config = InvokeAIAppConfig.get_config()
+
 Model_dir = "models"
 Weights_dir = "ldm/stable-diffusion-v1/"
 

invokeai/backend/prompting/conditioning.py

@@ -282,6 +282,8 @@ def split_weighted_subprompts(text, skip_normalize=False) -> list:
         (match.group("prompt").replace("\\:", ":"), float(match.group("weight") or 1))
         for match in re.finditer(prompt_parser, text)
     ]
+    if len(parsed_prompts) == 0:
+        return []
     if skip_normalize:
         return parsed_prompts
     weight_sum = sum(map(lambda x: x[1], parsed_prompts))

invokeai/backend/util/__init__.py

@@ -17,3 +17,5 @@ from .util import (
     instantiate_from_config,
     url_attachment_name,
 )
+
+

invokeai/backend/util/logging.py

@@ -31,7 +31,20 @@ IAILogger.debug('this is a debugging message')
 """
 
 import logging
+import logging.handlers
+import socket
+import urllib.parse
 
+from abc import abstractmethod
+from pathlib import Path
+
+from invokeai.app.services.config import InvokeAIAppConfig, get_invokeai_config
+
+try:
+    import syslog
+    SYSLOG_AVAILABLE = True
+except:
+    SYSLOG_AVAILABLE = False
 
 # module level functions
 def debug(msg, *args, **kwargs):
@@ -62,11 +75,77 @@ def getLogger(name: str = None) -> logging.Logger:
     return InvokeAILogger.getLogger(name)
 
 
-class InvokeAILogFormatter(logging.Formatter):
+_FACILITY_MAP = dict(
+    LOG_KERN = syslog.LOG_KERN,
+    LOG_USER = syslog.LOG_USER,
+    LOG_MAIL = syslog.LOG_MAIL,
+    LOG_DAEMON = syslog.LOG_DAEMON,
+    LOG_AUTH = syslog.LOG_AUTH,
+    LOG_LPR = syslog.LOG_LPR,
+    LOG_NEWS = syslog.LOG_NEWS,
+    LOG_UUCP = syslog.LOG_UUCP,
+    LOG_CRON = syslog.LOG_CRON,
+    LOG_SYSLOG = syslog.LOG_SYSLOG,
+    LOG_LOCAL0 = syslog.LOG_LOCAL0,
+    LOG_LOCAL1 = syslog.LOG_LOCAL1,
+    LOG_LOCAL2 = syslog.LOG_LOCAL2,
+    LOG_LOCAL3 = syslog.LOG_LOCAL3,
+    LOG_LOCAL4 = syslog.LOG_LOCAL4,
+    LOG_LOCAL5 = syslog.LOG_LOCAL5,
+    LOG_LOCAL6 = syslog.LOG_LOCAL6,
+    LOG_LOCAL7 = syslog.LOG_LOCAL7,
+) if SYSLOG_AVAILABLE else dict()
+
+_SOCK_MAP = dict(
+    SOCK_STREAM = socket.SOCK_STREAM,
+    SOCK_DGRAM = socket.SOCK_DGRAM,
+)
+
+class InvokeAIFormatter(logging.Formatter):
+    '''
+    Base class for logging formatter
+
+    '''
+    def format(self, record):
+        formatter = logging.Formatter(self.log_fmt(record.levelno))
+        return formatter.format(record)
+
+    @abstractmethod
+    def log_fmt(self, levelno: int)->str:
+        pass
+    
+class InvokeAISyslogFormatter(InvokeAIFormatter):
+    '''
+    Formatting for syslog
+    '''
+    def log_fmt(self, levelno: int)->str:
+        return '%(name)s [%(process)d] <%(levelname)s> %(message)s'
+
+class InvokeAILegacyLogFormatter(InvokeAIFormatter):
+    '''
+    Formatting for the InvokeAI Logger (legacy version)
+    '''
+    FORMATS = {
+        logging.DEBUG: "   | %(message)s",
+        logging.INFO: ">> %(message)s",
+        logging.WARNING: "** %(message)s",
+        logging.ERROR: "*** %(message)s",
+        logging.CRITICAL: "### %(message)s",
+    }
+    def log_fmt(self,levelno:int)->str:
+        return self.FORMATS.get(levelno)
+
+class InvokeAIPlainLogFormatter(InvokeAIFormatter):
+    '''
+    Custom Formatting for the InvokeAI Logger (plain version)
+    '''
+    def log_fmt(self, levelno: int)->str:
+        return "[%(asctime)s]::[%(name)s]::%(levelname)s --> %(message)s"
+
+class InvokeAIColorLogFormatter(InvokeAIFormatter):
     '''
     Custom Formatting for the InvokeAI Logger
     '''
-
     # Color Codes
     grey = "\x1b[38;20m"
     yellow = "\x1b[33;20m"
@@ -88,23 +167,109 @@ class InvokeAILogFormatter(logging.Formatter):
         logging.CRITICAL: bold_red + log_format + reset
     }
 
-    def format(self, record):
-        log_fmt = self.FORMATS.get(record.levelno)
-        formatter = logging.Formatter(log_fmt, datefmt="%d-%m-%Y %H:%M:%S")
-        return formatter.format(record)
+    def log_fmt(self, levelno: int)->str:
+        return self.FORMATS.get(levelno)
 
+LOG_FORMATTERS = {
+    'plain': InvokeAIPlainLogFormatter,
+    'color': InvokeAIColorLogFormatter,
+    'syslog': InvokeAISyslogFormatter,
+    'legacy': InvokeAILegacyLogFormatter,
+}
 
 class InvokeAILogger(object):
     loggers = dict()
 
     @classmethod
     def getLogger(cls, name: str = 'InvokeAI') -> logging.Logger:
+        config = get_invokeai_config()
+        
         if name not in cls.loggers:
             logger = logging.getLogger(name)
-            logger.setLevel(logging.DEBUG)
-            ch = logging.StreamHandler()
-            fmt = InvokeAILogFormatter()
-            ch.setFormatter(fmt)
+            logger.setLevel(config.log_level.upper()) # yes, strings work here
+            for ch in cls.getLoggers(config):
                 logger.addHandler(ch)
             cls.loggers[name] = logger
         return cls.loggers[name]
+
+    @classmethod
+    def getLoggers(cls, config: InvokeAIAppConfig) -> list[logging.Handler]:
+        handler_strs = config.log_handlers
+        print(f'handler_strs={handler_strs}')
+        handlers = list()
+        for handler in handler_strs:
+            handler_name,*args = handler.split('=',2)
+            args = args[0] if len(args) > 0 else None
+
+            # console is the only handler that gets a custom formatter
+            if handler_name=='console':
+                formatter = LOG_FORMATTERS[config.log_format]
+                ch = logging.StreamHandler()
+                ch.setFormatter(formatter())
+                handlers.append(ch)
+                
+            elif handler_name=='syslog':
+                ch = cls._parse_syslog_args(args)
+                ch.setFormatter(InvokeAISyslogFormatter())
+                handlers.append(ch)
+                
+            elif handler_name=='file':
+                handlers.append(cls._parse_file_args(args))
+                
+            elif handler_name=='http':
+                handlers.append(cls._parse_http_args(args))
+        return handlers
+
+    @staticmethod
+    def _parse_syslog_args(
+            args: str=None
+    )-> logging.Handler:
+        if not SYSLOG_AVAILABLE:
+            raise ValueError("syslog is not available on this system")
+        if not args:
+            args='/dev/log' if Path('/dev/log').exists() else 'address:localhost:514'
+        syslog_args = dict()
+        try:
+            for a in args.split(','):
+                arg_name,*arg_value = a.split(':',2)
+                if arg_name=='address':
+                    host,*port = arg_value
+                    port = 514 if len(port)==0 else int(port[0])
+                    syslog_args['address'] = (host,port)
+                elif arg_name=='facility':
+                    syslog_args['facility'] = _FACILITY_MAP[arg_value[0]]
+                elif arg_name=='socktype':
+                    syslog_args['socktype'] = _SOCK_MAP[arg_value[0]]
+                else:
+                    syslog_args['address'] = arg_name
+        except:
+            raise ValueError(f"{args} is not a value argument list for syslog logging")
+        return logging.handlers.SysLogHandler(**syslog_args)
+            
+    @staticmethod
+    def _parse_file_args(args: str=None)-> logging.Handler:
+        if not args:
+            raise ValueError("please provide filename for file logging using format 'file=/path/to/logfile.txt'")
+        return logging.FileHandler(args)
+
+    @staticmethod
+    def _parse_http_args(args: str=None)-> logging.Handler:
+        if not args:
+            raise ValueError("please provide destination for http logging using format 'http=url'")
+        arg_list = args.split(',')
+        url = urllib.parse.urlparse(arg_list.pop(0))
+        if url.scheme != 'http':
+            raise ValueError(f"the http logging module can only log to HTTP URLs, but {url.scheme} was specified")
+        host = url.hostname
+        path = url.path
+        port = url.port or 80
+        
+        syslog_args = dict()
+        for a in arg_list:
+            arg_name, *arg_value = a.split(':',2)
+            if arg_name=='method':
+                arg_value = arg_value[0] if len(arg_value)>0 else 'GET'
+                syslog_args[arg_name] = arg_value
+            else:  # TODO: Provide support for SSL context and credentials
+                pass
+        return logging.handlers.HTTPHandler(f'{host}:{port}',path,**syslog_args)

invokeai/frontend/web/docs/API_CLIENT.md

@@ -26,7 +26,7 @@ We need to start the nodes web server, which serves the OpenAPI schema to the ge
 
 ```bash
 # from the repo root
-python scripts/invoke-new.py --web
+python scripts/invokeai-web.py
 ```
 
 2. Generate the API client. 

invokeai/frontend/web/docs/README.md

@@ -12,7 +12,14 @@ Code in `invokeai/frontend/web/` if you want to have a look.
 
 ## Stack
 
-State management is Redux via [Redux Toolkit](https://github.com/reduxjs/redux-toolkit). Communication with server is a mix of HTTP and [socket.io](https://github.com/socketio/socket.io-client) (with a custom redux middleware to help).
+State management is Redux via [Redux Toolkit](https://github.com/reduxjs/redux-toolkit). We lean heavily on RTK:
+- `createAsyncThunk` for HTTP requests
+- `createEntityAdapter` for fetching images and models
+- `createListenerMiddleware` for workflows
+
+The API client and associated types are generated from the OpenAPI schema. See API_CLIENT.md.
+
+Communication with server is a mix of HTTP and [socket.io](https://github.com/socketio/socket.io-client) (with a simple socket.io redux middleware to help).
 
 [Chakra-UI](https://github.com/chakra-ui/chakra-ui) for components and styling.
 
@@ -37,9 +44,15 @@ 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 Nodes backend: `python scripts/invokeai-new.py --web # run from the repo root`
+2. Start the InvokeAI Nodes backend: `python scripts/invokeai-web.py # run from the repo root`
 3. Point your browser to the dev server address e.g. <http://localhost:5173/>
 
+#### VSCode Remote Dev
+
+We've noticed an intermittent issue with the VSCode Remote Dev port forwarding. If you use this feature of VSCode, you may intermittently click the Invoke button and then get nothing until the request times out. Suggest disabling the IDE's port forwarding feature and doing it manually via SSH:
+
+`ssh -L 9090:localhost:9090 -L 5173:localhost:5173 user@host`
+
 ### Production builds
 
 For a number of technical and logistical reasons, we need to commit UI build artefacts to the repo.

invokeai/frontend/web/package.json

@@ -60,6 +60,8 @@
     "@chakra-ui/styled-system": "^2.9.0",
     "@chakra-ui/theme-tools": "^2.0.16",
     "@dagrejs/graphlib": "^2.1.12",
+    "@dnd-kit/core": "^6.0.8",
+    "@dnd-kit/modifiers": "^6.0.1",
     "@emotion/react": "^11.10.6",
     "@emotion/styled": "^11.10.6",
     "@floating-ui/react-dom": "^2.0.0",
@@ -87,7 +89,7 @@
     "react-dropzone": "^14.2.3",
     "react-hotkeys-hook": "4.4.0",
     "react-i18next": "^12.2.2",
-    "react-icons": "^4.7.1",
+    "react-icons": "^4.9.0",
     "react-konva": "^18.2.7",
     "react-redux": "^8.0.5",
     "react-resizable-panels": "^0.0.42",

invokeai/frontend/web/src/app/components/ImageDnd/ImageDndContext.tsx

@@ -0,0 +1,68 @@
+import {
+  DndContext,
+  DragEndEvent,
+  DragOverlay,
+  DragStartEvent,
+  KeyboardSensor,
+  MouseSensor,
+  TouchSensor,
+  pointerWithin,
+  useSensor,
+  useSensors,
+} from '@dnd-kit/core';
+import { PropsWithChildren, memo, useCallback, useState } from 'react';
+import OverlayDragImage from './OverlayDragImage';
+import { ImageDTO } from 'services/api';
+import { isImageDTO } from 'services/types/guards';
+import { snapCenterToCursor } from '@dnd-kit/modifiers';
+
+type ImageDndContextProps = PropsWithChildren;
+
+const ImageDndContext = (props: ImageDndContextProps) => {
+  const [draggedImage, setDraggedImage] = useState<ImageDTO | null>(null);
+
+  const handleDragStart = useCallback((event: DragStartEvent) => {
+    const dragData = event.active.data.current;
+    if (dragData && 'image' in dragData && isImageDTO(dragData.image)) {
+      setDraggedImage(dragData.image);
+    }
+  }, []);
+
+  const handleDragEnd = useCallback(
+    (event: DragEndEvent) => {
+      const handleDrop = event.over?.data.current?.handleDrop;
+      if (handleDrop && typeof handleDrop === 'function' && draggedImage) {
+        handleDrop(draggedImage);
+      }
+      setDraggedImage(null);
+    },
+    [draggedImage]
+  );
+
+  const mouseSensor = useSensor(MouseSensor, {
+    activationConstraint: { distance: 15 },
+  });
+
+  const touchSensor = useSensor(TouchSensor, {
+    activationConstraint: { distance: 15 },
+  });
+  const keyboardSensor = useSensor(KeyboardSensor);
+
+  const sensors = useSensors(mouseSensor, touchSensor, keyboardSensor);
+
+  return (
+    <DndContext
+      onDragStart={handleDragStart}
+      onDragEnd={handleDragEnd}
+      sensors={sensors}
+      collisionDetection={pointerWithin}
+    >
+      {props.children}
+      <DragOverlay dropAnimation={null} modifiers={[snapCenterToCursor]}>
+        {draggedImage && <OverlayDragImage image={draggedImage} />}
+      </DragOverlay>
+    </DndContext>
+  );
+};
+
+export default memo(ImageDndContext);

invokeai/frontend/web/src/app/components/ImageDnd/OverlayDragImage.tsx

@@ -0,0 +1,36 @@
+import { Box, Image } from '@chakra-ui/react';
+import { memo } from 'react';
+import { ImageDTO } from 'services/api';
+
+type OverlayDragImageProps = {
+  image: ImageDTO;
+};
+
+const OverlayDragImage = (props: OverlayDragImageProps) => {
+  return (
+    <Box
+      style={{
+        width: '100%',
+        height: '100%',
+        display: 'flex',
+        alignItems: 'center',
+        justifyContent: 'center',
+        userSelect: 'none',
+        cursor: 'grabbing',
+        opacity: 0.5,
+      }}
+    >
+      <Image
+        sx={{
+          maxW: 36,
+          maxH: 36,
+          borderRadius: 'base',
+          shadow: 'dark-lg',
+        }}
+        src={props.image.thumbnail_url}
+      />
+    </Box>
+  );
+};
+
+export default memo(OverlayDragImage);

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

@@ -16,6 +16,7 @@ import { PartialAppConfig } from 'app/types/invokeai';
 import '../../i18n';
 import { socketMiddleware } from 'services/events/middleware';
 import { Middleware } from '@reduxjs/toolkit';
+import ImageDndContext from './ImageDnd/ImageDndContext';
 
 const App = lazy(() => import('./App'));
 const ThemeLocaleProvider = lazy(() => import('./ThemeLocaleProvider'));
@@ -69,11 +70,13 @@ const InvokeAIUI = ({
       <Provider store={store}>
         <React.Suspense fallback={<Loading />}>
           <ThemeLocaleProvider>
+            <ImageDndContext>
               <App
                 config={config}
                 headerComponent={headerComponent}
                 setIsReady={setIsReady}
               />
+            </ImageDndContext>
           </ThemeLocaleProvider>
         </React.Suspense>
       </Provider>

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

@@ -1,4 +1,5 @@
 import { canvasPersistDenylist } from 'features/canvas/store/canvasPersistDenylist';
+import { controlNetDenylist } from 'features/controlNet/store/controlNetDenylist';
 import { galleryPersistDenylist } from 'features/gallery/store/galleryPersistDenylist';
 import { lightboxPersistDenylist } from 'features/lightbox/store/lightboxPersistDenylist';
 import { nodesPersistDenylist } from 'features/nodes/store/nodesPersistDenylist';
@@ -23,6 +24,7 @@ const serializationDenylist: {
   system: systemPersistDenylist,
   // config: configPersistDenyList,
   ui: uiPersistDenylist,
+  controlNet: controlNetDenylist,
   // hotkeys: hotkeysPersistDenylist,
 };
 

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

@@ -1,4 +1,5 @@
 import { initialCanvasState } from 'features/canvas/store/canvasSlice';
+import { initialControlNetState } from 'features/controlNet/store/controlNetSlice';
 import { initialGalleryState } from 'features/gallery/store/gallerySlice';
 import { initialImagesState } from 'features/gallery/store/imagesSlice';
 import { initialLightboxState } from 'features/lightbox/store/lightboxSlice';
@@ -28,6 +29,7 @@ const initialStates: {
   ui: initialUIState,
   hotkeys: initialHotkeysState,
   images: initialImagesState,
+  controlNet: initialControlNetState,
 };
 
 export const unserialize: UnserializeFunction = (data, key) => {

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

@@ -70,6 +70,8 @@ import {
 import { addStagingAreaImageSavedListener } from './listeners/stagingAreaImageSaved';
 import { addCommitStagingAreaImageListener } from './listeners/addCommitStagingAreaImageListener';
 import { addImageCategoriesChangedListener } from './listeners/imageCategoriesChanged';
+import { addControlNetImageProcessedListener } from './listeners/controlNetImageProcessed';
+import { addControlNetAutoProcessListener } from './listeners/controlNetAutoProcess';
 
 export const listenerMiddleware = createListenerMiddleware();
 
@@ -173,3 +175,7 @@ addReceivedPageOfImagesRejectedListener();
 
 // Gallery
 addImageCategoriesChangedListener();
+
+// ControlNet
+addControlNetImageProcessedListener();
+addControlNetAutoProcessListener();

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

@@ -0,0 +1,59 @@
+import { AnyAction } from '@reduxjs/toolkit';
+import { startAppListening } from '..';
+import { log } from 'app/logging/useLogger';
+import { controlNetImageProcessed } from 'features/controlNet/store/actions';
+import {
+  controlNetImageChanged,
+  controlNetProcessorParamsChanged,
+  controlNetProcessorTypeChanged,
+} from 'features/controlNet/store/controlNetSlice';
+import { RootState } from 'app/store/store';
+
+const moduleLog = log.child({ namespace: 'controlNet' });
+
+const predicate = (action: AnyAction, state: RootState) => {
+  const isActionMatched =
+    controlNetProcessorParamsChanged.match(action) ||
+    controlNetImageChanged.match(action) ||
+    controlNetProcessorTypeChanged.match(action);
+
+  if (!isActionMatched) {
+    return false;
+  }
+
+  const { controlImage, processorType } =
+    state.controlNet.controlNets[action.payload.controlNetId];
+
+  const isProcessorSelected = processorType !== 'none';
+
+  const isBusy = state.system.isProcessing;
+
+  const hasControlImage = Boolean(controlImage);
+
+  return isProcessorSelected && !isBusy && hasControlImage;
+};
+
+/**
+ * Listener that automatically processes a ControlNet image when its processor parameters are changed.
+ *
+ * The network request is debounced by 1 second.
+ */
+export const addControlNetAutoProcessListener = () => {
+  startAppListening({
+    predicate,
+    effect: async (
+      action,
+      { dispatch, getState, cancelActiveListeners, delay }
+    ) => {
+      const { controlNetId } = action.payload;
+
+      // Cancel any in-progress instances of this listener
+      cancelActiveListeners();
+
+      // Delay before starting actual work
+      await delay(300);
+
+      dispatch(controlNetImageProcessed({ controlNetId }));
+    },
+  });
+};

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

@@ -0,0 +1,93 @@
+import { startAppListening } from '..';
+import { imageMetadataReceived } from 'services/thunks/image';
+import { log } from 'app/logging/useLogger';
+import { controlNetImageProcessed } from 'features/controlNet/store/actions';
+import { Graph } from 'services/api';
+import { sessionCreated } from 'services/thunks/session';
+import { sessionReadyToInvoke } from 'features/system/store/actions';
+import { socketInvocationComplete } from 'services/events/actions';
+import { isImageOutput } from 'services/types/guards';
+import { controlNetProcessedImageChanged } from 'features/controlNet/store/controlNetSlice';
+import { pick } from 'lodash-es';
+
+const moduleLog = log.child({ namespace: 'controlNet' });
+
+export const addControlNetImageProcessedListener = () => {
+  startAppListening({
+    actionCreator: controlNetImageProcessed,
+    effect: async (
+      action,
+      { dispatch, getState, take, unsubscribe, subscribe }
+    ) => {
+      const { controlNetId } = action.payload;
+      const controlNet = getState().controlNet.controlNets[controlNetId];
+
+      if (!controlNet.controlImage) {
+        moduleLog.error('Unable to process ControlNet image');
+        return;
+      }
+
+      // ControlNet one-off procressing graph is just the processor node, no edges.
+      // Also we need to grab the image.
+      const graph: Graph = {
+        nodes: {
+          [controlNet.processorNode.id]: {
+            ...controlNet.processorNode,
+            is_intermediate: true,
+            image: pick(controlNet.controlImage, [
+              'image_name',
+              'image_origin',
+            ]),
+          },
+        },
+      };
+
+      // Create a session to run the graph & wait til it's ready to invoke
+      const sessionCreatedAction = dispatch(sessionCreated({ graph }));
+      const [sessionCreatedFulfilledAction] = await take(
+        (action): action is ReturnType<typeof sessionCreated.fulfilled> =>
+          sessionCreated.fulfilled.match(action) &&
+          action.meta.requestId === sessionCreatedAction.requestId
+      );
+
+      const sessionId = sessionCreatedFulfilledAction.payload.id;
+
+      // Invoke the session & wait til it's complete
+      dispatch(sessionReadyToInvoke());
+      const [invocationCompleteAction] = await take(
+        (action): action is ReturnType<typeof socketInvocationComplete> =>
+          socketInvocationComplete.match(action) &&
+          action.payload.data.graph_execution_state_id === sessionId
+      );
+
+      // We still have to check the output type
+      if (isImageOutput(invocationCompleteAction.payload.data.result)) {
+        const { image_name } =
+          invocationCompleteAction.payload.data.result.image;
+
+        // Wait for the ImageDTO to be received
+        const [imageMetadataReceivedAction] = await take(
+          (
+            action
+          ): action is ReturnType<typeof imageMetadataReceived.fulfilled> =>
+            imageMetadataReceived.fulfilled.match(action) &&
+            action.payload.image_name === image_name
+        );
+        const processedControlImage = imageMetadataReceivedAction.payload;
+
+        moduleLog.debug(
+          { data: { arg: action.payload, processedControlImage } },
+          'ControlNet image processed'
+        );
+
+        // Update the processed image in the store
+        dispatch(
+          controlNetProcessedImageChanged({
+            controlNetId,
+            processedControlImage,
+          })
+        );
+      }
+    },
+  });
+};

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

@@ -2,12 +2,10 @@ import { initialImageChanged } from 'features/parameters/store/generationSlice';
 import { t } from 'i18next';
 import { addToast } from 'features/system/store/systemSlice';
 import { startAppListening } from '..';
-import {
-  initialImageSelected,
-  isImageDTO,
-} from 'features/parameters/store/actions';
+import { initialImageSelected } from 'features/parameters/store/actions';
 import { makeToast } from 'app/components/Toaster';
 import { selectImagesById } from 'features/gallery/store/imagesSlice';
+import { isImageDTO } from 'services/types/guards';
 
 export const addInitialImageSelectedListener = () => {
   startAppListening({

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

@@ -13,6 +13,7 @@ import galleryReducer from 'features/gallery/store/gallerySlice';
 import imagesReducer from 'features/gallery/store/imagesSlice';
 import lightboxReducer from 'features/lightbox/store/lightboxSlice';
 import generationReducer from 'features/parameters/store/generationSlice';
+import controlNetReducer from 'features/controlNet/store/controlNetSlice';
 import postprocessingReducer from 'features/parameters/store/postprocessingSlice';
 import systemReducer from 'features/system/store/systemSlice';
 // import sessionReducer from 'features/system/store/sessionSlice';
@@ -45,6 +46,7 @@ const allReducers = {
   ui: uiReducer,
   hotkeys: hotkeysReducer,
   images: imagesReducer,
+  controlNet: controlNetReducer,
   // session: sessionReducer,
 };
 
@@ -62,6 +64,7 @@ const rememberedKeys: (keyof typeof allReducers)[] = [
   'postprocessing',
   'system',
   'ui',
+  'controlNet',
   // 'hotkeys',
   // 'config',
 ];

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

@@ -95,6 +95,7 @@ export type AppFeature =
  * A disable-able Stable Diffusion feature
  */
 export type SDFeature =
+  | 'controlNet'
   | 'noise'
   | 'variation'
   | 'symmetry'

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

@@ -1,17 +0,0 @@
-import { Checkbox, CheckboxProps } from '@chakra-ui/react';
-import { memo, ReactNode } from 'react';
-
-type IAICheckboxProps = CheckboxProps & {
-  label: string | ReactNode;
-};
-
-const IAICheckbox = (props: IAICheckboxProps) => {
-  const { label, ...rest } = props;
-  return (
-    <Checkbox colorScheme="accent" {...rest}>
-      {label}
-    </Checkbox>
-  );
-};
-
-export default memo(IAICheckbox);

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

@@ -49,7 +49,7 @@ const IAICollapse = (props: IAIToggleCollapseProps) => {
           />
         )}
       </Flex>
-      <Collapse in={isOpen} animateOpacity>
+      <Collapse in={isOpen} animateOpacity style={{ overflow: 'unset' }}>
         <Box sx={{ p: 4, borderBottomRadius: 'base', bg: 'base.800' }}>
           {children}
         </Box>

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

@@ -1,4 +1,4 @@
-import { CheckIcon } from '@chakra-ui/icons';
+import { CheckIcon, ChevronUpIcon } from '@chakra-ui/icons';
 import {
   Box,
   Flex,
@@ -10,7 +10,6 @@ import {
   GridItem,
   List,
   ListItem,
-  Select,
   Text,
   Tooltip,
   TooltipProps,
@@ -19,7 +18,8 @@ import { autoUpdate, offset, shift, useFloating } from '@floating-ui/react-dom';
 import { useSelect } from 'downshift';
 import { OverlayScrollbarsComponent } from 'overlayscrollbars-react';
 
-import { memo } from 'react';
+import { memo, useMemo } from 'react';
+import { getInputOutlineStyles } from 'theme/util/getInputOutlineStyles';
 
 export type ItemTooltips = { [key: string]: string };
 
@@ -34,6 +34,7 @@ type IAICustomSelectProps = {
   buttonProps?: FlexProps;
   tooltip?: string;
   tooltipProps?: Omit<TooltipProps, 'children'>;
+  ellipsisPosition?: 'start' | 'end';
 };
 
 const IAICustomSelect = (props: IAICustomSelectProps) => {
@@ -48,6 +49,7 @@ const IAICustomSelect = (props: IAICustomSelectProps) => {
     tooltip,
     buttonProps,
     tooltipProps,
+    ellipsisPosition = 'end',
   } = props;
 
   const {
@@ -69,6 +71,14 @@ const IAICustomSelect = (props: IAICustomSelectProps) => {
     middleware: [offset(4), shift({ crossAxis: true, padding: 8 })],
   });
 
+  const labelTextDirection = useMemo(() => {
+    if (ellipsisPosition === 'start') {
+      return document.dir === 'rtl' ? 'ltr' : 'rtl';
+    }
+
+    return document.dir;
+  }, [ellipsisPosition]);
+
   return (
     <FormControl sx={{ w: 'full' }} {...formControlProps}>
       {label && (
@@ -82,20 +92,44 @@ const IAICustomSelect = (props: IAICustomSelectProps) => {
         </FormLabel>
       )}
       <Tooltip label={tooltip} {...tooltipProps}>
-        <Select
+        <Flex
           {...getToggleButtonProps({ ref: refs.setReference })}
           {...buttonProps}
-          as={Flex}
           sx={{
             alignItems: 'center',
             userSelect: 'none',
             cursor: 'pointer',
+            overflow: 'hidden',
+            width: 'full',
+            py: 1,
+            px: 2,
+            gap: 2,
+            justifyContent: 'space-between',
+            ...getInputOutlineStyles(),
+          }}
+        >
+          <Text
+            sx={{
+              fontSize: 'sm',
+              fontWeight: 500,
+              color: 'base.100',
+              whiteSpace: 'nowrap',
+              overflow: 'hidden',
+              textOverflow: 'ellipsis',
+              direction: labelTextDirection,
             }}
           >
-          <Text sx={{ fontSize: 'sm', fontWeight: 500, color: 'base.100' }}>
             {selectedItem}
           </Text>
-        </Select>
+          <ChevronUpIcon
+            sx={{
+              color: 'base.300',
+              transform: isOpen ? 'rotate(0deg)' : 'rotate(180deg)',
+              transitionProperty: 'common',
+              transitionDuration: 'normal',
+            }}
+          />
+        </Flex>
       </Tooltip>
       <Box {...getMenuProps()}>
         {isOpen && (
@@ -104,11 +138,10 @@ const IAICustomSelect = (props: IAICustomSelectProps) => {
             ref={refs.setFloating}
             sx={{
               ...floatingStyles,
-              width: 'max-content',
               top: 0,
-              left: 0,
+              insetInlineStart: 0,
               flexDirection: 'column',
-              zIndex: 1,
+              zIndex: 2,
               bg: 'base.800',
               borderRadius: 'base',
               border: '1px',
@@ -118,10 +151,20 @@ const IAICustomSelect = (props: IAICustomSelectProps) => {
               px: 0,
               h: 'fit-content',
               maxH: 64,
+              minW: 48,
             }}
           >
             <OverlayScrollbarsComponent>
-              {items.map((item, index) => (
+              {items.map((item, index) => {
+                const isSelected = selectedItem === item;
+                const isHighlighted = highlightedIndex === index;
+                const fontWeight = isSelected ? 700 : 500;
+                const bg = isHighlighted
+                  ? 'base.700'
+                  : isSelected
+                  ? 'base.750'
+                  : undefined;
+                return (
                   <Tooltip
                     isDisabled={!itemTooltips}
                     key={`${item}${index}`}
@@ -131,7 +174,7 @@ const IAICustomSelect = (props: IAICustomSelectProps) => {
                   >
                     <ListItem
                       sx={{
-                      bg: highlightedIndex === index ? 'base.700' : undefined,
+                        bg,
                         py: 1,
                         paddingInlineStart: 3,
                         paddingInlineEnd: 6,
@@ -145,14 +188,14 @@ const IAICustomSelect = (props: IAICustomSelectProps) => {
                       {withCheckIcon ? (
                         <Grid gridTemplateColumns="1.25rem auto">
                           <GridItem>
-                          {selectedItem === item && <CheckIcon boxSize={2} />}
+                            {isSelected && <CheckIcon boxSize={2} />}
                           </GridItem>
                           <GridItem>
                             <Text
                               sx={{
                                 fontSize: 'sm',
                                 color: 'base.100',
-                              fontWeight: 500,
+                                fontWeight,
                               }}
                             >
                               {item}
@@ -163,8 +206,8 @@ const IAICustomSelect = (props: IAICustomSelectProps) => {
                         <Text
                           sx={{
                             fontSize: 'sm',
-                          color: 'base.100',
-                          fontWeight: 500,
+                            color: 'base.50',
+                            fontWeight,
                           }}
                         >
                           {item}
@@ -172,7 +215,8 @@ const IAICustomSelect = (props: IAICustomSelectProps) => {
                       )}
                     </ListItem>
                   </Tooltip>
-              ))}
+                );
+              })}
             </OverlayScrollbarsComponent>
           </List>
         )}

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

@@ -0,0 +1,258 @@
+import {
+  Box,
+  Flex,
+  Icon,
+  IconButtonProps,
+  Image,
+  Text,
+} from '@chakra-ui/react';
+import { useDraggable, useDroppable } from '@dnd-kit/core';
+import { useCombinedRefs } from '@dnd-kit/utilities';
+import IAIIconButton from 'common/components/IAIIconButton';
+import { IAIImageFallback } from 'common/components/IAIImageFallback';
+import ImageMetadataOverlay from 'common/components/ImageMetadataOverlay';
+import { useGetUrl } from 'common/util/getUrl';
+import { AnimatePresence, motion } from 'framer-motion';
+import { ReactElement, SyntheticEvent } from 'react';
+import { memo, useRef } from 'react';
+import { FaImage, FaTimes } from 'react-icons/fa';
+import { ImageDTO } from 'services/api';
+import { v4 as uuidv4 } from 'uuid';
+
+type IAIDndImageProps = {
+  image: ImageDTO | null | undefined;
+  onDrop: (droppedImage: ImageDTO) => void;
+  onReset?: () => void;
+  onError?: (event: SyntheticEvent<HTMLImageElement>) => void;
+  onLoad?: (event: SyntheticEvent<HTMLImageElement>) => void;
+  resetIconSize?: IconButtonProps['size'];
+  withResetIcon?: boolean;
+  withMetadataOverlay?: boolean;
+  isDragDisabled?: boolean;
+  isDropDisabled?: boolean;
+  fallback?: ReactElement;
+  payloadImage?: ImageDTO | null | undefined;
+  minSize?: number;
+};
+
+const IAIDndImage = (props: IAIDndImageProps) => {
+  const {
+    image,
+    onDrop,
+    onReset,
+    onError,
+    resetIconSize = 'md',
+    withResetIcon = false,
+    withMetadataOverlay = false,
+    isDropDisabled = false,
+    isDragDisabled = false,
+    fallback = <IAIImageFallback />,
+    payloadImage,
+    minSize = 24,
+  } = props;
+  const dndId = useRef(uuidv4());
+  const { getUrl } = useGetUrl();
+  const {
+    isOver,
+    setNodeRef: setDroppableRef,
+    active,
+  } = useDroppable({
+    id: dndId.current,
+    disabled: isDropDisabled,
+    data: {
+      handleDrop: onDrop,
+    },
+  });
+
+  const {
+    attributes,
+    listeners,
+    setNodeRef: setDraggableRef,
+  } = useDraggable({
+    id: dndId.current,
+    data: {
+      image: payloadImage ? payloadImage : image,
+    },
+    disabled: isDragDisabled,
+  });
+
+  const setNodeRef = useCombinedRefs(setDroppableRef, setDraggableRef);
+
+  return (
+    <Flex
+      sx={{
+        width: 'full',
+        height: 'full',
+        alignItems: 'center',
+        justifyContent: 'center',
+        position: 'relative',
+        minW: minSize,
+        minH: minSize,
+        userSelect: 'none',
+        cursor: 'grab',
+      }}
+      {...attributes}
+      {...listeners}
+      ref={setNodeRef}
+    >
+      {image && (
+        <Flex
+          sx={{
+            w: 'full',
+            h: 'full',
+            position: 'relative',
+            alignItems: 'center',
+            justifyContent: 'center',
+          }}
+        >
+          <Image
+            src={getUrl(image.image_url)}
+            fallbackStrategy="beforeLoadOrError"
+            fallback={fallback}
+            onError={onError}
+            objectFit="contain"
+            draggable={false}
+            sx={{
+              maxW: 'full',
+              maxH: 'full',
+              borderRadius: 'base',
+            }}
+          />
+          {withMetadataOverlay && <ImageMetadataOverlay image={image} />}
+          {onReset && withResetIcon && (
+            <Box
+              sx={{
+                position: 'absolute',
+                top: 0,
+                right: 0,
+                p: 2,
+              }}
+            >
+              <IAIIconButton
+                size={resetIconSize}
+                tooltip="Reset Image"
+                aria-label="Reset Image"
+                icon={<FaTimes />}
+                onClick={onReset}
+              />
+            </Box>
+          )}
+          <AnimatePresence>
+            {active && <DropOverlay isOver={isOver} />}
+          </AnimatePresence>
+        </Flex>
+      )}
+      {!image && (
+        <>
+          <Flex
+            sx={{
+              minH: minSize,
+              bg: 'base.850',
+              w: 'full',
+              h: 'full',
+              alignItems: 'center',
+              justifyContent: 'center',
+              borderRadius: 'base',
+            }}
+          >
+            <Icon
+              as={FaImage}
+              sx={{
+                boxSize: 24,
+                color: 'base.500',
+              }}
+            />
+          </Flex>
+          <AnimatePresence>
+            {active && <DropOverlay isOver={isOver} />}
+          </AnimatePresence>
+        </>
+      )}
+    </Flex>
+  );
+};
+
+export default memo(IAIDndImage);
+
+type DropOverlayProps = {
+  isOver: boolean;
+};
+
+const DropOverlay = (props: DropOverlayProps) => {
+  const { isOver } = props;
+  return (
+    <motion.div
+      key="statusText"
+      initial={{
+        opacity: 0,
+      }}
+      animate={{
+        opacity: 1,
+        transition: { duration: 0.1 },
+      }}
+      exit={{
+        opacity: 0,
+        transition: { duration: 0.1 },
+      }}
+    >
+      <Flex
+        sx={{
+          position: 'absolute',
+          top: 0,
+          left: 0,
+          w: 'full',
+          h: 'full',
+        }}
+      >
+        <Flex
+          sx={{
+            position: 'absolute',
+            top: 0,
+            left: 0,
+            w: 'full',
+            h: 'full',
+            bg: 'base.900',
+            opacity: 0.7,
+            borderRadius: 'base',
+            alignItems: 'center',
+            justifyContent: 'center',
+            transitionProperty: 'common',
+            transitionDuration: '0.1s',
+          }}
+        />
+
+        <Flex
+          sx={{
+            position: 'absolute',
+            top: 0,
+            left: 0,
+            w: 'full',
+            h: 'full',
+            opacity: 1,
+            borderWidth: 2,
+            borderColor: isOver ? 'base.200' : 'base.500',
+            borderRadius: 'base',
+            borderStyle: 'dashed',
+            transitionProperty: 'common',
+            transitionDuration: '0.1s',
+            alignItems: 'center',
+            justifyContent: 'center',
+          }}
+        >
+          <Text
+            sx={{
+              fontSize: '2xl',
+              fontWeight: 600,
+              transform: isOver ? 'scale(1.1)' : 'scale(1)',
+              color: isOver ? 'base.100' : 'base.500',
+              transitionProperty: 'common',
+              transitionDuration: '0.1s',
+            }}
+          >
+            Drop
+          </Text>
+        </Flex>
+      </Flex>
+    </motion.div>
+  );
+};

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

@@ -0,0 +1,25 @@
+import {
+  Checkbox,
+  CheckboxProps,
+  FormControl,
+  FormControlProps,
+  FormLabel,
+} from '@chakra-ui/react';
+import { memo, ReactNode } from 'react';
+
+type IAIFullCheckboxProps = CheckboxProps & {
+  label: string | ReactNode;
+  formControlProps?: FormControlProps;
+};
+
+const IAIFullCheckbox = (props: IAIFullCheckboxProps) => {
+  const { label, formControlProps, ...rest } = props;
+  return (
+    <FormControl {...formControlProps}>
+      <FormLabel>{label}</FormLabel>
+      <Checkbox colorScheme="accent" {...rest} />
+    </FormControl>
+  );
+};
+
+export default memo(IAIFullCheckbox);

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

@@ -0,0 +1,27 @@
+import { Flex, FlexProps, Spinner, SpinnerProps } from '@chakra-ui/react';
+
+type Props = FlexProps & {
+  spinnerProps?: SpinnerProps;
+};
+
+export const IAIImageFallback = (props: Props) => {
+  const { spinnerProps, ...rest } = props;
+  const { sx, ...restFlexProps } = rest;
+  return (
+    <Flex
+      sx={{
+        bg: 'base.900',
+        opacity: 0.7,
+        w: 'full',
+        h: 'full',
+        alignItems: 'center',
+        justifyContent: 'center',
+        borderRadius: 'base',
+        ...sx,
+      }}
+      {...restFlexProps}
+    >
+      <Spinner size="xl" {...spinnerProps} />
+    </Flex>
+  );
+};

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

@@ -0,0 +1,19 @@
+import { Checkbox, CheckboxProps, Text } from '@chakra-ui/react';
+import { memo, ReactElement } from 'react';
+
+type IAISimpleCheckboxProps = CheckboxProps & {
+  label: string | ReactElement;
+};
+
+const IAISimpleCheckbox = (props: IAISimpleCheckboxProps) => {
+  const { label, ...rest } = props;
+  return (
+    <Checkbox colorScheme="accent" {...rest}>
+      <Text color="base.200" fontSize="md">
+        {label}
+      </Text>
+    </Checkbox>
+  );
+};
+
+export default memo(IAISimpleCheckbox);

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

@@ -40,7 +40,7 @@ import IAIIconButton, { IAIIconButtonProps } from './IAIIconButton';
 import { roundDownToMultiple } from 'common/util/roundDownToMultiple';
 
 export type IAIFullSliderProps = {
-  label: string;
+  label?: string;
   value: number;
   min?: number;
   max?: number;
@@ -178,9 +178,11 @@ const IAISlider = (props: IAIFullSliderProps) => {
       isDisabled={isDisabled}
       {...sliderFormControlProps}
     >
+      {label && (
         <FormLabel {...sliderFormLabelProps} mb={-1}>
           {label}
         </FormLabel>
+      )}
 
       <HStack w="100%" gap={2} alignItems="center">
         <Slider
@@ -203,6 +205,7 @@ const IAISlider = (props: IAIFullSliderProps) => {
                 sx={{
                   insetInlineStart: '0 !important',
                   insetInlineEnd: 'unset !important',
+                  mt: 1.5,
                 }}
                 {...sliderMarkProps}
               >
@@ -213,6 +216,7 @@ const IAISlider = (props: IAIFullSliderProps) => {
                 sx={{
                   insetInlineStart: 'unset !important',
                   insetInlineEnd: '0 !important',
+                  mt: 1.5,
                 }}
                 {...sliderMarkProps}
               >

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

@@ -5,6 +5,7 @@ import {
   FormLabelProps,
   Switch,
   SwitchProps,
+  Tooltip,
 } from '@chakra-ui/react';
 import { memo } from 'react';
 
@@ -13,6 +14,7 @@ interface Props extends SwitchProps {
   width?: string | number;
   formControlProps?: FormControlProps;
   formLabelProps?: FormLabelProps;
+  tooltip?: string;
 }
 
 /**
@@ -25,9 +27,11 @@ const IAISwitch = (props: Props) => {
     width = 'auto',
     formControlProps,
     formLabelProps,
+    tooltip,
     ...rest
   } = props;
   return (
+    <Tooltip label={tooltip} hasArrow placement="top" isDisabled={!tooltip}>
       <FormControl
         isDisabled={isDisabled}
         width={width}
@@ -36,11 +40,14 @@ const IAISwitch = (props: Props) => {
         alignItems="center"
         {...formControlProps}
       >
+        {label && (
           <FormLabel my={1} flexGrow={1} {...formLabelProps}>
             {label}
           </FormLabel>
+        )}
         <Switch {...rest} />
       </FormControl>
+    </Tooltip>
   );
 };
 

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

@@ -1,5 +1,5 @@
 import { Badge, Flex } from '@chakra-ui/react';
-import { isNumber, isString } from 'lodash-es';
+import { isString } from 'lodash-es';
 import { useMemo } from 'react';
 import { ImageDTO } from 'services/api';
 
@@ -8,14 +8,6 @@ type ImageMetadataOverlayProps = {
 };
 
 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?.model)) {
       return;
@@ -31,17 +23,15 @@ const ImageMetadataOverlay = ({ image }: ImageMetadataOverlayProps) => {
         flexDirection: 'column',
         position: 'absolute',
         top: 0,
-        right: 0,
+        insetInlineStart: 0,
         p: 2,
-        alignItems: 'flex-end',
+        alignItems: 'flex-start',
         gap: 2,
       }}
     >
-      {dimensions && (
       <Badge variant="solid" colorScheme="base">
-          {dimensions}
+        {image.width} × {image.height}
       </Badge>
-      )}
       {model && (
         <Badge variant="solid" colorScheme="base">
           {model}

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

@@ -1,42 +0,0 @@
-import { ButtonGroup, Flex, Spacer, Text } from '@chakra-ui/react';
-import IAIIconButton from 'common/components/IAIIconButton';
-
-import { useTranslation } from 'react-i18next';
-import { FaUndo, FaUpload } from 'react-icons/fa';
-import { useAppDispatch } from 'app/store/storeHooks';
-import { useCallback } from 'react';
-import { clearInitialImage } from 'features/parameters/store/generationSlice';
-import useImageUploader from 'common/hooks/useImageUploader';
-
-const InitialImageButtons = () => {
-  const dispatch = useAppDispatch();
-  const { t } = useTranslation();
-  const { openUploader } = useImageUploader();
-
-  const handleResetInitialImage = useCallback(() => {
-    dispatch(clearInitialImage());
-  }, [dispatch]);
-
-  return (
-    <Flex w="full" alignItems="center">
-      <Text size="sm" fontWeight={500} color="base.300">
-        {t('parameters.initialImage')}
-      </Text>
-      <Spacer />
-      <ButtonGroup>
-        <IAIIconButton
-          icon={<FaUndo />}
-          aria-label={t('accessibility.reset')}
-          onClick={handleResetInitialImage}
-        />
-        <IAIIconButton
-          icon={<FaUpload />}
-          onClick={openUploader}
-          aria-label={t('common.upload')}
-        />
-      </ButtonGroup>
-    </Flex>
-  );
-};
-
-export default InitialImageButtons;

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

@@ -1,12 +1,12 @@
 import { createSelector } from '@reduxjs/toolkit';
+import { useAppSelector } from 'app/store/storeHooks';
 import { defaultSelectorOptions } from 'app/store/util/defaultMemoizeOptions';
 import { validateSeedWeights } from 'common/util/seedWeightPairs';
 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(
+const readinessSelector = createSelector(
   [generationSelector, systemSelector, activeTabNameSelector],
   (generation, system, activeTabName) => {
     const {
@@ -60,3 +60,8 @@ export const readinessSelector = createSelector(
   },
   defaultSelectorOptions
 );
+
+export const useIsReadyToInvoke = () => {
+  const { isReady } = useAppSelector(readinessSelector);
+  return isReady;
+};

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

@@ -2,7 +2,7 @@ import { ButtonGroup, Flex } from '@chakra-ui/react';
 import { createSelector } from '@reduxjs/toolkit';
 import { useAppDispatch, useAppSelector } from 'app/store/storeHooks';
 import IAIButton from 'common/components/IAIButton';
-import IAICheckbox from 'common/components/IAICheckbox';
+import IAISimpleCheckbox from 'common/components/IAISimpleCheckbox';
 import IAIColorPicker from 'common/components/IAIColorPicker';
 import IAIIconButton from 'common/components/IAIIconButton';
 import IAIPopover from 'common/components/IAIPopover';
@@ -117,12 +117,12 @@ const IAICanvasMaskOptions = () => {
       }
     >
       <Flex direction="column" gap={2}>
-        <IAICheckbox
+        <IAISimpleCheckbox
           label={`${t('unifiedCanvas.enableMask')} (H)`}
           isChecked={isMaskEnabled}
           onChange={handleToggleEnableMask}
         />
-        <IAICheckbox
+        <IAISimpleCheckbox
           label={t('unifiedCanvas.preserveMaskedArea')}
           isChecked={shouldPreserveMaskedArea}
           onChange={(e) =>

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

@@ -1,7 +1,7 @@
 import { Flex } from '@chakra-ui/react';
 import { createSelector } from '@reduxjs/toolkit';
 import { useAppDispatch, useAppSelector } from 'app/store/storeHooks';
-import IAICheckbox from 'common/components/IAICheckbox';
+import IAISimpleCheckbox from 'common/components/IAISimpleCheckbox';
 import IAIIconButton from 'common/components/IAIIconButton';
 import IAIPopover from 'common/components/IAIPopover';
 import { canvasSelector } from 'features/canvas/store/canvasSelectors';
@@ -102,50 +102,50 @@ const IAICanvasSettingsButtonPopover = () => {
       }
     >
       <Flex direction="column" gap={2}>
-        <IAICheckbox
+        <IAISimpleCheckbox
           label={t('unifiedCanvas.showIntermediates')}
           isChecked={shouldShowIntermediates}
           onChange={(e) =>
             dispatch(setShouldShowIntermediates(e.target.checked))
           }
         />
-        <IAICheckbox
+        <IAISimpleCheckbox
           label={t('unifiedCanvas.showGrid')}
           isChecked={shouldShowGrid}
           onChange={(e) => dispatch(setShouldShowGrid(e.target.checked))}
         />
-        <IAICheckbox
+        <IAISimpleCheckbox
           label={t('unifiedCanvas.snapToGrid')}
           isChecked={shouldSnapToGrid}
           onChange={handleChangeShouldSnapToGrid}
         />
-        <IAICheckbox
+        <IAISimpleCheckbox
           label={t('unifiedCanvas.darkenOutsideSelection')}
           isChecked={shouldDarkenOutsideBoundingBox}
           onChange={(e) =>
             dispatch(setShouldDarkenOutsideBoundingBox(e.target.checked))
           }
         />
-        <IAICheckbox
+        <IAISimpleCheckbox
           label={t('unifiedCanvas.autoSaveToGallery')}
           isChecked={shouldAutoSave}
           onChange={(e) => dispatch(setShouldAutoSave(e.target.checked))}
         />
-        <IAICheckbox
+        <IAISimpleCheckbox
           label={t('unifiedCanvas.saveBoxRegionOnly')}
           isChecked={shouldCropToBoundingBoxOnSave}
           onChange={(e) =>
             dispatch(setShouldCropToBoundingBoxOnSave(e.target.checked))
           }
         />
-        <IAICheckbox
+        <IAISimpleCheckbox
           label={t('unifiedCanvas.limitStrokesToBox')}
           isChecked={shouldRestrictStrokesToBox}
           onChange={(e) =>
             dispatch(setShouldRestrictStrokesToBox(e.target.checked))
           }
         />
-        <IAICheckbox
+        <IAISimpleCheckbox
           label={t('unifiedCanvas.showCanvasDebugInfo')}
           isChecked={shouldShowCanvasDebugInfo}
           onChange={(e) =>
@@ -153,7 +153,7 @@ const IAICanvasSettingsButtonPopover = () => {
           }
         />
 
-        <IAICheckbox
+        <IAISimpleCheckbox
           label={t('unifiedCanvas.antialiasing')}
           isChecked={shouldAntialias}
           onChange={(e) => dispatch(setShouldAntialias(e.target.checked))}

invokeai/frontend/web/src/features/controlNet/components/ControlNet.tsx

@@ -0,0 +1,258 @@
+import { memo, useCallback } from 'react';
+import {
+  ControlNetConfig,
+  controlNetAdded,
+  controlNetRemoved,
+  controlNetToggled,
+} from '../store/controlNetSlice';
+import { useAppDispatch } from 'app/store/storeHooks';
+import ParamControlNetModel from './parameters/ParamControlNetModel';
+import ParamControlNetWeight from './parameters/ParamControlNetWeight';
+import {
+  Checkbox,
+  Flex,
+  FormControl,
+  FormLabel,
+  HStack,
+  TabList,
+  TabPanels,
+  Tabs,
+  Tab,
+  TabPanel,
+  Box,
+} from '@chakra-ui/react';
+import { FaCopy, FaPlus, FaTrash, FaWrench } from 'react-icons/fa';
+
+import ParamControlNetBeginEnd from './parameters/ParamControlNetBeginEnd';
+import ControlNetImagePreview from './ControlNetImagePreview';
+import IAIIconButton from 'common/components/IAIIconButton';
+import { v4 as uuidv4 } from 'uuid';
+import { useToggle } from 'react-use';
+import ParamControlNetProcessorSelect from './parameters/ParamControlNetProcessorSelect';
+import ControlNetProcessorComponent from './ControlNetProcessorComponent';
+import ControlNetPreprocessButton from './ControlNetPreprocessButton';
+import IAIButton from 'common/components/IAIButton';
+import IAISwitch from 'common/components/IAISwitch';
+import { ChevronDownIcon, ChevronUpIcon } from '@chakra-ui/icons';
+
+type ControlNetProps = {
+  controlNet: ControlNetConfig;
+};
+
+const ControlNet = (props: ControlNetProps) => {
+  const {
+    controlNetId,
+    isEnabled,
+    model,
+    weight,
+    beginStepPct,
+    endStepPct,
+    controlImage,
+    processedControlImage,
+    processorNode,
+    processorType,
+  } = props.controlNet;
+  const dispatch = useAppDispatch();
+  const [shouldShowAdvanced, onToggleAdvanced] = useToggle(false);
+
+  const handleDelete = useCallback(() => {
+    dispatch(controlNetRemoved({ controlNetId }));
+  }, [controlNetId, dispatch]);
+
+  const handleDuplicate = useCallback(() => {
+    dispatch(
+      controlNetAdded({ controlNetId: uuidv4(), controlNet: props.controlNet })
+    );
+  }, [dispatch, props.controlNet]);
+
+  const handleToggleIsEnabled = useCallback(() => {
+    dispatch(controlNetToggled({ controlNetId }));
+  }, [controlNetId, dispatch]);
+
+  return (
+    <Flex
+      sx={{
+        flexDir: 'column',
+        gap: 2,
+        p: 3,
+        bg: 'base.850',
+        borderRadius: 'base',
+      }}
+    >
+      <Flex sx={{ gap: 2 }}>
+        <IAISwitch
+          tooltip="Toggle"
+          aria-label="Toggle"
+          isChecked={isEnabled}
+          onChange={handleToggleIsEnabled}
+        />
+        <Box
+          sx={{
+            w: 'full',
+            minW: 0,
+            opacity: isEnabled ? 1 : 0.5,
+            pointerEvents: isEnabled ? 'auto' : 'none',
+            transitionProperty: 'common',
+            transitionDuration: '0.1s',
+          }}
+        >
+          <ParamControlNetModel controlNetId={controlNetId} model={model} />
+        </Box>
+        <IAIIconButton
+          size="sm"
+          tooltip="Duplicate"
+          aria-label="Duplicate"
+          onClick={handleDuplicate}
+          icon={<FaCopy />}
+        />
+        <IAIIconButton
+          size="sm"
+          tooltip="Delete"
+          aria-label="Delete"
+          colorScheme="error"
+          onClick={handleDelete}
+          icon={<FaTrash />}
+        />
+        <IAIIconButton
+          size="sm"
+          aria-label="Expand"
+          onClick={onToggleAdvanced}
+          variant="link"
+          icon={
+            <ChevronUpIcon
+              sx={{
+                boxSize: 4,
+                color: 'base.300',
+                transform: shouldShowAdvanced
+                  ? 'rotate(0deg)'
+                  : 'rotate(180deg)',
+                transitionProperty: 'common',
+                transitionDuration: 'normal',
+              }}
+            />
+          }
+        />
+      </Flex>
+      {isEnabled && (
+        <>
+          <Flex sx={{ gap: 4 }}>
+            <Flex
+              sx={{
+                flexDir: 'column',
+                gap: 2,
+                w: 'full',
+                h: 24,
+                paddingInlineStart: 1,
+                paddingInlineEnd: shouldShowAdvanced ? 1 : 0,
+                pb: 2,
+                justifyContent: 'space-between',
+              }}
+            >
+              <ParamControlNetWeight
+                controlNetId={controlNetId}
+                weight={weight}
+                mini
+              />
+              <ParamControlNetBeginEnd
+                controlNetId={controlNetId}
+                beginStepPct={beginStepPct}
+                endStepPct={endStepPct}
+                mini
+              />
+            </Flex>
+            {!shouldShowAdvanced && (
+              <Flex
+                sx={{
+                  alignItems: 'center',
+                  justifyContent: 'center',
+                  h: 24,
+                  w: 24,
+                  aspectRatio: '1/1',
+                }}
+              >
+                <ControlNetImagePreview controlNet={props.controlNet} />
+              </Flex>
+            )}
+          </Flex>
+          {shouldShowAdvanced && (
+            <>
+              <Box pt={2}>
+                <ControlNetImagePreview controlNet={props.controlNet} />
+              </Box>
+              <ParamControlNetProcessorSelect
+                controlNetId={controlNetId}
+                processorNode={processorNode}
+              />
+              <ControlNetProcessorComponent
+                controlNetId={controlNetId}
+                processorNode={processorNode}
+              />
+            </>
+          )}
+        </>
+      )}
+    </Flex>
+  );
+
+  return (
+    <Flex sx={{ flexDir: 'column', gap: 3 }}>
+      <ControlNetImagePreview controlNet={props.controlNet} />
+      <ParamControlNetModel controlNetId={controlNetId} model={model} />
+      <Tabs
+        isFitted
+        orientation="horizontal"
+        variant="enclosed"
+        size="sm"
+        colorScheme="accent"
+      >
+        <TabList>
+          <Tab
+            sx={{ 'button&': { _selected: { borderBottomColor: 'base.800' } } }}
+          >
+            Model Config
+          </Tab>
+          <Tab
+            sx={{ 'button&': { _selected: { borderBottomColor: 'base.800' } } }}
+          >
+            Preprocess
+          </Tab>
+        </TabList>
+        <TabPanels sx={{ pt: 2 }}>
+          <TabPanel sx={{ p: 0 }}>
+            <ParamControlNetWeight
+              controlNetId={controlNetId}
+              weight={weight}
+            />
+            <ParamControlNetBeginEnd
+              controlNetId={controlNetId}
+              beginStepPct={beginStepPct}
+              endStepPct={endStepPct}
+            />
+          </TabPanel>
+          <TabPanel sx={{ p: 0 }}>
+            <ParamControlNetProcessorSelect
+              controlNetId={controlNetId}
+              processorNode={processorNode}
+            />
+            <ControlNetProcessorComponent
+              controlNetId={controlNetId}
+              processorNode={processorNode}
+            />
+            <ControlNetPreprocessButton controlNet={props.controlNet} />
+            {/* <IAIButton
+              size="sm"
+              leftIcon={<FaUndo />}
+              onClick={handleReset}
+              isDisabled={Boolean(!processedControlImage)}
+            >
+              Reset Processing
+            </IAIButton> */}
+          </TabPanel>
+        </TabPanels>
+      </Tabs>
+      <IAIButton onClick={handleDelete}>Remove ControlNet</IAIButton>
+    </Flex>
+  );
+};
+
+export default memo(ControlNet);

invokeai/frontend/web/src/features/controlNet/components/ControlNetImagePreview.tsx

@@ -0,0 +1,141 @@
+import { memo, useCallback, useRef, useState } from 'react';
+import { ImageDTO } from 'services/api';
+import {
+  ControlNetConfig,
+  controlNetImageChanged,
+  controlNetSelector,
+} from '../store/controlNetSlice';
+import { useAppDispatch, useAppSelector } from 'app/store/storeHooks';
+import { Box } from '@chakra-ui/react';
+import IAIDndImage from 'common/components/IAIDndImage';
+import { createSelector } from '@reduxjs/toolkit';
+import { defaultSelectorOptions } from 'app/store/util/defaultMemoizeOptions';
+import { AnimatePresence, motion } from 'framer-motion';
+import { IAIImageFallback } from 'common/components/IAIImageFallback';
+import { useHoverDirty } from 'react-use';
+
+const selector = createSelector(
+  controlNetSelector,
+  (controlNet) => {
+    const { isProcessingControlImage } = controlNet;
+    return { isProcessingControlImage };
+  },
+  defaultSelectorOptions
+);
+
+type Props = {
+  controlNet: ControlNetConfig;
+};
+
+const ControlNetImagePreview = (props: Props) => {
+  const { controlNetId, controlImage, processedControlImage, processorType } =
+    props.controlNet;
+  const dispatch = useAppDispatch();
+  const { isProcessingControlImage } = useAppSelector(selector);
+  const containerRef = useRef<HTMLDivElement>(null);
+
+  const isMouseOverImage = useHoverDirty(containerRef);
+
+  const handleDrop = useCallback(
+    (droppedImage: ImageDTO) => {
+      if (controlImage?.image_name === droppedImage.image_name) {
+        return;
+      }
+      dispatch(
+        controlNetImageChanged({ controlNetId, controlImage: droppedImage })
+      );
+    },
+    [controlImage, controlNetId, dispatch]
+  );
+
+  const shouldShowProcessedImageBackdrop =
+    Number(controlImage?.width) > Number(processedControlImage?.width) ||
+    Number(controlImage?.height) > Number(processedControlImage?.height);
+
+  const shouldShowProcessedImage =
+    controlImage &&
+    processedControlImage &&
+    !isMouseOverImage &&
+    !isProcessingControlImage &&
+    processorType !== 'none';
+
+  return (
+    <Box ref={containerRef} sx={{ position: 'relative', w: 'full', h: 'full' }}>
+      <IAIDndImage
+        image={controlImage}
+        onDrop={handleDrop}
+        isDropDisabled={Boolean(
+          processedControlImage && processorType !== 'none'
+        )}
+      />
+      <AnimatePresence>
+        {shouldShowProcessedImage && (
+          <motion.div
+            initial={{
+              opacity: 0,
+            }}
+            animate={{
+              opacity: 1,
+              transition: { duration: 0.1 },
+            }}
+            exit={{
+              opacity: 0,
+              transition: { duration: 0.1 },
+            }}
+          >
+            <Box
+              sx={{
+                position: 'absolute',
+                w: 'full',
+                h: 'full',
+                top: 0,
+                insetInlineStart: 0,
+              }}
+            >
+              {shouldShowProcessedImageBackdrop && (
+                <Box
+                  sx={{
+                    w: 'full',
+                    h: 'full',
+                    bg: 'base.900',
+                    opacity: 0.7,
+                  }}
+                />
+              )}
+              <Box
+                sx={{
+                  position: 'absolute',
+                  top: 0,
+                  insetInlineStart: 0,
+                  w: 'full',
+                  h: 'full',
+                }}
+              >
+                <IAIDndImage
+                  image={processedControlImage}
+                  onDrop={handleDrop}
+                  payloadImage={controlImage}
+                />
+              </Box>
+            </Box>
+          </motion.div>
+        )}
+      </AnimatePresence>
+      {isProcessingControlImage && (
+        <Box
+          sx={{
+            position: 'absolute',
+            top: 0,
+            insetInlineStart: 0,
+            w: 'full',
+            h: 'full',
+          }}
+        >
+          <IAIImageFallback />
+        </Box>
+      )}
+    </Box>
+  );
+};
+
+export default memo(ControlNetImagePreview);

invokeai/frontend/web/src/features/controlNet/components/ControlNetPreprocessButton.tsx

@@ -0,0 +1,36 @@
+import IAIButton from 'common/components/IAIButton';
+import { memo, useCallback } from 'react';
+import { ControlNetConfig } from '../store/controlNetSlice';
+import { useAppDispatch } from 'app/store/storeHooks';
+import { controlNetImageProcessed } from '../store/actions';
+import { useIsReadyToInvoke } from 'common/hooks/useIsReadyToInvoke';
+
+type Props = {
+  controlNet: ControlNetConfig;
+};
+
+const ControlNetPreprocessButton = (props: Props) => {
+  const { controlNetId, controlImage } = props.controlNet;
+  const dispatch = useAppDispatch();
+  const isReady = useIsReadyToInvoke();
+
+  const handleProcess = useCallback(() => {
+    dispatch(
+      controlNetImageProcessed({
+        controlNetId,
+      })
+    );
+  }, [controlNetId, dispatch]);
+
+  return (
+    <IAIButton
+      size="sm"
+      onClick={handleProcess}
+      isDisabled={Boolean(!controlImage) || !isReady}
+    >
+      Preprocess
+    </IAIButton>
+  );
+};
+
+export default memo(ControlNetPreprocessButton);

invokeai/frontend/web/src/features/controlNet/components/ControlNetProcessorComponent.tsx

@@ -0,0 +1,131 @@
+import { memo } from 'react';
+import { RequiredControlNetProcessorNode } from '../store/types';
+import CannyProcessor from './processors/CannyProcessor';
+import HedProcessor from './processors/HedProcessor';
+import LineartProcessor from './processors/LineartProcessor';
+import LineartAnimeProcessor from './processors/LineartAnimeProcessor';
+import ContentShuffleProcessor from './processors/ContentShuffleProcessor';
+import MediapipeFaceProcessor from './processors/MediapipeFaceProcessor';
+import MidasDepthProcessor from './processors/MidasDepthProcessor';
+import MlsdImageProcessor from './processors/MlsdImageProcessor';
+import NormalBaeProcessor from './processors/NormalBaeProcessor';
+import OpenposeProcessor from './processors/OpenposeProcessor';
+import PidiProcessor from './processors/PidiProcessor';
+import ZoeDepthProcessor from './processors/ZoeDepthProcessor';
+
+export type ControlNetProcessorProps = {
+  controlNetId: string;
+  processorNode: RequiredControlNetProcessorNode;
+};
+
+const ControlNetProcessorComponent = (props: ControlNetProcessorProps) => {
+  const { controlNetId, processorNode } = props;
+  if (processorNode.type === 'canny_image_processor') {
+    return (
+      <CannyProcessor
+        controlNetId={controlNetId}
+        processorNode={processorNode}
+      />
+    );
+  }
+
+  if (processorNode.type === 'hed_image_processor') {
+    return (
+      <HedProcessor controlNetId={controlNetId} processorNode={processorNode} />
+    );
+  }
+
+  if (processorNode.type === 'lineart_image_processor') {
+    return (
+      <LineartProcessor
+        controlNetId={controlNetId}
+        processorNode={processorNode}
+      />
+    );
+  }
+
+  if (processorNode.type === 'content_shuffle_image_processor') {
+    return (
+      <ContentShuffleProcessor
+        controlNetId={controlNetId}
+        processorNode={processorNode}
+      />
+    );
+  }
+
+  if (processorNode.type === 'lineart_anime_image_processor') {
+    return (
+      <LineartAnimeProcessor
+        controlNetId={controlNetId}
+        processorNode={processorNode}
+      />
+    );
+  }
+
+  if (processorNode.type === 'mediapipe_face_processor') {
+    return (
+      <MediapipeFaceProcessor
+        controlNetId={controlNetId}
+        processorNode={processorNode}
+      />
+    );
+  }
+
+  if (processorNode.type === 'midas_depth_image_processor') {
+    return (
+      <MidasDepthProcessor
+        controlNetId={controlNetId}
+        processorNode={processorNode}
+      />
+    );
+  }
+
+  if (processorNode.type === 'mlsd_image_processor') {
+    return (
+      <MlsdImageProcessor
+        controlNetId={controlNetId}
+        processorNode={processorNode}
+      />
+    );
+  }
+
+  if (processorNode.type === 'normalbae_image_processor') {
+    return (
+      <NormalBaeProcessor
+        controlNetId={controlNetId}
+        processorNode={processorNode}
+      />
+    );
+  }
+
+  if (processorNode.type === 'openpose_image_processor') {
+    return (
+      <OpenposeProcessor
+        controlNetId={controlNetId}
+        processorNode={processorNode}
+      />
+    );
+  }
+
+  if (processorNode.type === 'pidi_image_processor') {
+    return (
+      <PidiProcessor
+        controlNetId={controlNetId}
+        processorNode={processorNode}
+      />
+    );
+  }
+
+  if (processorNode.type === 'zoe_depth_image_processor') {
+    return (
+      <ZoeDepthProcessor
+        controlNetId={controlNetId}
+        processorNode={processorNode}
+      />
+    );
+  }
+
+  return null;
+};
+
+export default memo(ControlNetProcessorComponent);

invokeai/frontend/web/src/features/controlNet/components/hooks/useProcessorNodeChanged.ts

@@ -0,0 +1,20 @@
+import { useAppDispatch } from 'app/store/storeHooks';
+import { controlNetProcessorParamsChanged } from 'features/controlNet/store/controlNetSlice';
+import { ControlNetProcessorNode } from 'features/controlNet/store/types';
+import { useCallback } from 'react';
+
+export const useProcessorNodeChanged = () => {
+  const dispatch = useAppDispatch();
+  const handleProcessorNodeChanged = useCallback(
+    (controlNetId: string, changes: Partial<ControlNetProcessorNode>) => {
+      dispatch(
+        controlNetProcessorParamsChanged({
+          controlNetId,
+          changes,
+        })
+      );
+    },
+    [dispatch]
+  );
+  return handleProcessorNodeChanged;
+};

invokeai/frontend/web/src/features/controlNet/components/parameters/ParamControlNetBeginEnd.tsx

@@ -0,0 +1,130 @@
+import {
+  FormControl,
+  FormLabel,
+  HStack,
+  RangeSlider,
+  RangeSliderFilledTrack,
+  RangeSliderMark,
+  RangeSliderThumb,
+  RangeSliderTrack,
+  Tooltip,
+} from '@chakra-ui/react';
+import { useAppDispatch } from 'app/store/storeHooks';
+import IAIIconButton from 'common/components/IAIIconButton';
+import {
+  controlNetBeginStepPctChanged,
+  controlNetEndStepPctChanged,
+} from 'features/controlNet/store/controlNetSlice';
+import { memo, useCallback } from 'react';
+import { useTranslation } from 'react-i18next';
+import { BiReset } from 'react-icons/bi';
+
+type Props = {
+  controlNetId: string;
+  beginStepPct: number;
+  endStepPct: number;
+  mini?: boolean;
+};
+
+const formatPct = (v: number) => `${Math.round(v * 100)}%`;
+
+const ParamControlNetBeginEnd = (props: Props) => {
+  const { controlNetId, beginStepPct, endStepPct, mini = false } = props;
+  const dispatch = useAppDispatch();
+  const { t } = useTranslation();
+
+  const handleStepPctChanged = useCallback(
+    (v: number[]) => {
+      dispatch(
+        controlNetBeginStepPctChanged({ controlNetId, beginStepPct: v[0] })
+      );
+      dispatch(controlNetEndStepPctChanged({ controlNetId, endStepPct: v[1] }));
+    },
+    [controlNetId, dispatch]
+  );
+
+  const handleStepPctReset = useCallback(() => {
+    dispatch(controlNetBeginStepPctChanged({ controlNetId, beginStepPct: 0 }));
+    dispatch(controlNetEndStepPctChanged({ controlNetId, endStepPct: 1 }));
+  }, [controlNetId, dispatch]);
+
+  return (
+    <FormControl>
+      <FormLabel>Begin / End Step Percentage</FormLabel>
+      <HStack w="100%" gap={2} alignItems="center">
+        <RangeSlider
+          aria-label={['Begin Step %', 'End Step %']}
+          value={[beginStepPct, endStepPct]}
+          onChange={handleStepPctChanged}
+          min={0}
+          max={1}
+          step={0.01}
+          minStepsBetweenThumbs={5}
+        >
+          <RangeSliderTrack>
+            <RangeSliderFilledTrack />
+          </RangeSliderTrack>
+          <Tooltip label={formatPct(beginStepPct)} placement="top" hasArrow>
+            <RangeSliderThumb index={0} />
+          </Tooltip>
+          <Tooltip label={formatPct(endStepPct)} placement="top" hasArrow>
+            <RangeSliderThumb index={1} />
+          </Tooltip>
+          {!mini && (
+            <>
+              <RangeSliderMark
+                value={0}
+                sx={{
+                  fontSize: 'xs',
+                  fontWeight: '500',
+                  color: 'base.200',
+                  insetInlineStart: '0 !important',
+                  insetInlineEnd: 'unset !important',
+                  mt: 1.5,
+                }}
+              >
+                0%
+              </RangeSliderMark>
+              <RangeSliderMark
+                value={0.5}
+                sx={{
+                  fontSize: 'xs',
+                  fontWeight: '500',
+                  color: 'base.200',
+                  mt: 1.5,
+                }}
+              >
+                50%
+              </RangeSliderMark>
+              <RangeSliderMark
+                value={1}
+                sx={{
+                  fontSize: 'xs',
+                  fontWeight: '500',
+                  color: 'base.200',
+                  insetInlineStart: 'unset !important',
+                  insetInlineEnd: '0 !important',
+                  mt: 1.5,
+                }}
+              >
+                100%
+              </RangeSliderMark>
+            </>
+          )}
+        </RangeSlider>
+
+        {!mini && (
+          <IAIIconButton
+            size="sm"
+            aria-label={t('accessibility.reset')}
+            tooltip={t('accessibility.reset')}
+            icon={<BiReset />}
+            onClick={handleStepPctReset}
+          />
+        )}
+      </HStack>
+    </FormControl>
+  );
+};
+
+export default memo(ParamControlNetBeginEnd);

invokeai/frontend/web/src/features/controlNet/components/parameters/ParamControlNetIsEnabled.tsx

@@ -0,0 +1,28 @@
+import { useAppDispatch } from 'app/store/storeHooks';
+import IAISwitch from 'common/components/IAISwitch';
+import { controlNetToggled } from 'features/controlNet/store/controlNetSlice';
+import { memo, useCallback } from 'react';
+
+type ParamControlNetIsEnabledProps = {
+  controlNetId: string;
+  isEnabled: boolean;
+};
+
+const ParamControlNetIsEnabled = (props: ParamControlNetIsEnabledProps) => {
+  const { controlNetId, isEnabled } = props;
+  const dispatch = useAppDispatch();
+
+  const handleIsEnabledChanged = useCallback(() => {
+    dispatch(controlNetToggled({ controlNetId }));
+  }, [dispatch, controlNetId]);
+
+  return (
+    <IAISwitch
+      label="Enabled"
+      isChecked={isEnabled}
+      onChange={handleIsEnabledChanged}
+    />
+  );
+};
+
+export default memo(ParamControlNetIsEnabled);

invokeai/frontend/web/src/features/controlNet/components/parameters/ParamControlNetIsPreprocessed.tsx

@@ -0,0 +1,36 @@
+import { useAppDispatch } from 'app/store/storeHooks';
+import IAIFullCheckbox from 'common/components/IAIFullCheckbox';
+import IAISwitch from 'common/components/IAISwitch';
+import {
+  controlNetToggled,
+  isControlNetImagePreprocessedToggled,
+} from 'features/controlNet/store/controlNetSlice';
+import { memo, useCallback } from 'react';
+
+type ParamControlNetIsEnabledProps = {
+  controlNetId: string;
+  isControlImageProcessed: boolean;
+};
+
+const ParamControlNetIsEnabled = (props: ParamControlNetIsEnabledProps) => {
+  const { controlNetId, isControlImageProcessed } = props;
+  const dispatch = useAppDispatch();
+
+  const handleIsControlImageProcessedToggled = useCallback(() => {
+    dispatch(
+      isControlNetImagePreprocessedToggled({
+        controlNetId,
+      })
+    );
+  }, [controlNetId, dispatch]);
+
+  return (
+    <IAISwitch
+      label="Preprocess"
+      isChecked={isControlImageProcessed}
+      onChange={handleIsControlImageProcessedToggled}
+    />
+  );
+};
+
+export default memo(ParamControlNetIsEnabled);

invokeai/frontend/web/src/features/controlNet/components/parameters/ParamControlNetModel.tsx

@@ -0,0 +1,41 @@
+import { useAppDispatch } from 'app/store/storeHooks';
+import IAICustomSelect from 'common/components/IAICustomSelect';
+import {
+  CONTROLNET_MODELS,
+  ControlNetModel,
+} from 'features/controlNet/store/constants';
+import { controlNetModelChanged } from 'features/controlNet/store/controlNetSlice';
+import { memo, useCallback } from 'react';
+
+type ParamIsControlNetModelProps = {
+  controlNetId: string;
+  model: ControlNetModel;
+};
+
+const ParamIsControlNetModel = (props: ParamIsControlNetModelProps) => {
+  const { controlNetId, model } = props;
+  const dispatch = useAppDispatch();
+
+  const handleModelChanged = useCallback(
+    (val: string | null | undefined) => {
+      // TODO: do not cast
+      const model = val as ControlNetModel;
+      dispatch(controlNetModelChanged({ controlNetId, model }));
+    },
+    [controlNetId, dispatch]
+  );
+
+  return (
+    <IAICustomSelect
+      tooltip={model}
+      tooltipProps={{ placement: 'top', hasArrow: true }}
+      items={CONTROLNET_MODELS}
+      selectedItem={model}
+      setSelectedItem={handleModelChanged}
+      ellipsisPosition="start"
+      withCheckIcon
+    />
+  );
+};
+
+export default memo(ParamIsControlNetModel);

invokeai/frontend/web/src/features/controlNet/components/parameters/ParamControlNetProcessorSelect.tsx

@@ -0,0 +1,47 @@
+import IAICustomSelect from 'common/components/IAICustomSelect';
+import { memo, useCallback } from 'react';
+import {
+  ControlNetProcessorNode,
+  ControlNetProcessorType,
+} from '../../store/types';
+import { controlNetProcessorTypeChanged } from '../../store/controlNetSlice';
+import { useAppDispatch } from 'app/store/storeHooks';
+import { CONTROLNET_PROCESSORS } from '../../store/constants';
+
+type ParamControlNetProcessorSelectProps = {
+  controlNetId: string;
+  processorNode: ControlNetProcessorNode;
+};
+
+const CONTROLNET_PROCESSOR_TYPES = Object.keys(
+  CONTROLNET_PROCESSORS
+) as ControlNetProcessorType[];
+
+const ParamControlNetProcessorSelect = (
+  props: ParamControlNetProcessorSelectProps
+) => {
+  const { controlNetId, processorNode } = props;
+  const dispatch = useAppDispatch();
+  const handleProcessorTypeChanged = useCallback(
+    (v: string | null | undefined) => {
+      dispatch(
+        controlNetProcessorTypeChanged({
+          controlNetId,
+          processorType: v as ControlNetProcessorType,
+        })
+      );
+    },
+    [controlNetId, dispatch]
+  );
+  return (
+    <IAICustomSelect
+      label="Processor"
+      items={CONTROLNET_PROCESSOR_TYPES}
+      selectedItem={processorNode.type ?? 'canny_image_processor'}
+      setSelectedItem={handleProcessorTypeChanged}
+      withCheckIcon
+    />
+  );
+};
+
+export default memo(ParamControlNetProcessorSelect);

invokeai/frontend/web/src/features/controlNet/components/parameters/ParamControlNetWeight.tsx

@@ -0,0 +1,57 @@
+import { useAppDispatch } from 'app/store/storeHooks';
+import IAISlider from 'common/components/IAISlider';
+import { controlNetWeightChanged } from 'features/controlNet/store/controlNetSlice';
+import { memo, useCallback } from 'react';
+
+type ParamControlNetWeightProps = {
+  controlNetId: string;
+  weight: number;
+  mini?: boolean;
+};
+
+const ParamControlNetWeight = (props: ParamControlNetWeightProps) => {
+  const { controlNetId, weight, mini = false } = props;
+  const dispatch = useAppDispatch();
+
+  const handleWeightChanged = useCallback(
+    (weight: number) => {
+      dispatch(controlNetWeightChanged({ controlNetId, weight }));
+    },
+    [controlNetId, dispatch]
+  );
+
+  const handleWeightReset = () => {
+    dispatch(controlNetWeightChanged({ controlNetId, weight: 1 }));
+  };
+
+  if (mini) {
+    return (
+      <IAISlider
+        label={'Weight'}
+        sliderFormLabelProps={{ pb: 1 }}
+        value={weight}
+        onChange={handleWeightChanged}
+        min={0}
+        max={1}
+        step={0.01}
+      />
+    );
+  }
+
+  return (
+    <IAISlider
+      label="Weight"
+      value={weight}
+      onChange={handleWeightChanged}
+      withInput
+      withReset
+      handleReset={handleWeightReset}
+      withSliderMarks
+      min={0}
+      max={1}
+      step={0.01}
+    />
+  );
+};
+
+export default memo(ParamControlNetWeight);

invokeai/frontend/web/src/features/controlNet/components/processors/CannyProcessor.tsx

@@ -0,0 +1,72 @@
+import IAISlider from 'common/components/IAISlider';
+import { CONTROLNET_PROCESSORS } from 'features/controlNet/store/constants';
+import { RequiredCannyImageProcessorInvocation } from 'features/controlNet/store/types';
+import { memo, useCallback } from 'react';
+import { useProcessorNodeChanged } from '../hooks/useProcessorNodeChanged';
+import ProcessorWrapper from './common/ProcessorWrapper';
+
+const DEFAULTS = CONTROLNET_PROCESSORS.canny_image_processor.default;
+
+type CannyProcessorProps = {
+  controlNetId: string;
+  processorNode: RequiredCannyImageProcessorInvocation;
+};
+
+const CannyProcessor = (props: CannyProcessorProps) => {
+  const { controlNetId, processorNode } = props;
+  const { low_threshold, high_threshold } = processorNode;
+  const processorChanged = useProcessorNodeChanged();
+
+  const handleLowThresholdChanged = useCallback(
+    (v: number) => {
+      processorChanged(controlNetId, { low_threshold: v });
+    },
+    [controlNetId, processorChanged]
+  );
+
+  const handleLowThresholdReset = useCallback(() => {
+    processorChanged(controlNetId, {
+      low_threshold: DEFAULTS.low_threshold,
+    });
+  }, [controlNetId, processorChanged]);
+
+  const handleHighThresholdChanged = useCallback(
+    (v: number) => {
+      processorChanged(controlNetId, { high_threshold: v });
+    },
+    [controlNetId, processorChanged]
+  );
+
+  const handleHighThresholdReset = useCallback(() => {
+    processorChanged(controlNetId, {
+      high_threshold: DEFAULTS.high_threshold,
+    });
+  }, [controlNetId, processorChanged]);
+
+  return (
+    <ProcessorWrapper>
+      <IAISlider
+        label="Low Threshold"
+        value={low_threshold}
+        onChange={handleLowThresholdChanged}
+        handleReset={handleLowThresholdReset}
+        withReset
+        min={0}
+        max={255}
+        withInput
+      />
+      <IAISlider
+        label="High Threshold"
+        value={high_threshold}
+        onChange={handleHighThresholdChanged}
+        handleReset={handleHighThresholdReset}
+        withReset
+        min={0}
+        max={255}
+        withInput
+      />
+    </ProcessorWrapper>
+  );
+};
+
+export default memo(CannyProcessor);

invokeai/frontend/web/src/features/controlNet/components/processors/ContentShuffleProcessor.tsx

@@ -0,0 +1,141 @@
+import IAISlider from 'common/components/IAISlider';
+import { CONTROLNET_PROCESSORS } from 'features/controlNet/store/constants';
+import { RequiredContentShuffleImageProcessorInvocation } from 'features/controlNet/store/types';
+import { memo, useCallback } from 'react';
+import { useProcessorNodeChanged } from '../hooks/useProcessorNodeChanged';
+import ProcessorWrapper from './common/ProcessorWrapper';
+
+const DEFAULTS = CONTROLNET_PROCESSORS.content_shuffle_image_processor.default;
+
+type Props = {
+  controlNetId: string;
+  processorNode: RequiredContentShuffleImageProcessorInvocation;
+};
+
+const ContentShuffleProcessor = (props: Props) => {
+  const { controlNetId, processorNode } = props;
+  const { image_resolution, detect_resolution, w, h, f } = processorNode;
+  const processorChanged = useProcessorNodeChanged();
+
+  const handleDetectResolutionChanged = useCallback(
+    (v: number) => {
+      processorChanged(controlNetId, { detect_resolution: v });
+    },
+    [controlNetId, processorChanged]
+  );
+
+  const handleDetectResolutionReset = useCallback(() => {
+    processorChanged(controlNetId, {
+      detect_resolution: DEFAULTS.detect_resolution,
+    });
+  }, [controlNetId, processorChanged]);
+
+  const handleImageResolutionChanged = useCallback(
+    (v: number) => {
+      processorChanged(controlNetId, { image_resolution: v });
+    },
+    [controlNetId, processorChanged]
+  );
+
+  const handleImageResolutionReset = useCallback(() => {
+    processorChanged(controlNetId, {
+      image_resolution: DEFAULTS.image_resolution,
+    });
+  }, [controlNetId, processorChanged]);
+
+  const handleWChanged = useCallback(
+    (v: number) => {
+      processorChanged(controlNetId, { w: v });
+    },
+    [controlNetId, processorChanged]
+  );
+
+  const handleWReset = useCallback(() => {
+    processorChanged(controlNetId, {
+      w: DEFAULTS.w,
+    });
+  }, [controlNetId, processorChanged]);
+
+  const handleHChanged = useCallback(
+    (v: number) => {
+      processorChanged(controlNetId, { h: v });
+    },
+    [controlNetId, processorChanged]
+  );
+
+  const handleHReset = useCallback(() => {
+    processorChanged(controlNetId, {
+      h: DEFAULTS.h,
+    });
+  }, [controlNetId, processorChanged]);
+
+  const handleFChanged = useCallback(
+    (v: number) => {
+      processorChanged(controlNetId, { f: v });
+    },
+    [controlNetId, processorChanged]
+  );
+
+  const handleFReset = useCallback(() => {
+    processorChanged(controlNetId, {
+      f: DEFAULTS.f,
+    });
+  }, [controlNetId, processorChanged]);
+
+  return (
+    <ProcessorWrapper>
+      <IAISlider
+        label="Detect Resolution"
+        value={detect_resolution}
+        onChange={handleDetectResolutionChanged}
+        handleReset={handleDetectResolutionReset}
+        withReset
+        min={0}
+        max={4096}
+        withInput
+      />
+      <IAISlider
+        label="Image Resolution"
+        value={image_resolution}
+        onChange={handleImageResolutionChanged}
+        handleReset={handleImageResolutionReset}
+        withReset
+        min={0}
+        max={4096}
+        withInput
+      />
+      <IAISlider
+        label="W"
+        value={w}
+        onChange={handleWChanged}
+        handleReset={handleWReset}
+        withReset
+        min={0}
+        max={4096}
+        withInput
+      />
+      <IAISlider
+        label="H"
+        value={h}
+        onChange={handleHChanged}
+        handleReset={handleHReset}
+        withReset
+        min={0}
+        max={4096}
+        withInput
+      />
+      <IAISlider
+        label="F"
+        value={f}
+        onChange={handleFChanged}
+        handleReset={handleFReset}
+        withReset
+        min={0}
+        max={4096}
+        withInput
+      />
+    </ProcessorWrapper>
+  );
+};
+
+export default memo(ContentShuffleProcessor);

invokeai/frontend/web/src/features/controlNet/components/processors/HedProcessor.tsx

@@ -0,0 +1,88 @@
+import IAISlider from 'common/components/IAISlider';
+import IAISwitch from 'common/components/IAISwitch';
+import { CONTROLNET_PROCESSORS } from 'features/controlNet/store/constants';
+import { RequiredHedImageProcessorInvocation } from 'features/controlNet/store/types';
+import { ChangeEvent, memo, useCallback } from 'react';
+import { useProcessorNodeChanged } from '../hooks/useProcessorNodeChanged';
+import ProcessorWrapper from './common/ProcessorWrapper';
+
+const DEFAULTS = CONTROLNET_PROCESSORS.hed_image_processor.default;
+
+type HedProcessorProps = {
+  controlNetId: string;
+  processorNode: RequiredHedImageProcessorInvocation;
+};
+
+const HedPreprocessor = (props: HedProcessorProps) => {
+  const {
+    controlNetId,
+    processorNode: { detect_resolution, image_resolution, scribble },
+  } = props;
+
+  const processorChanged = useProcessorNodeChanged();
+
+  const handleDetectResolutionChanged = useCallback(
+    (v: number) => {
+      processorChanged(controlNetId, { detect_resolution: v });
+    },
+    [controlNetId, processorChanged]
+  );
+
+  const handleImageResolutionChanged = useCallback(
+    (v: number) => {
+      processorChanged(controlNetId, { image_resolution: v });
+    },
+    [controlNetId, processorChanged]
+  );
+
+  const handleScribbleChanged = useCallback(
+    (e: ChangeEvent<HTMLInputElement>) => {
+      processorChanged(controlNetId, { scribble: e.target.checked });
+    },
+    [controlNetId, processorChanged]
+  );
+
+  const handleDetectResolutionReset = useCallback(() => {
+    processorChanged(controlNetId, {
+      detect_resolution: DEFAULTS.detect_resolution,
+    });
+  }, [controlNetId, processorChanged]);
+
+  const handleImageResolutionReset = useCallback(() => {
+    processorChanged(controlNetId, {
+      image_resolution: DEFAULTS.image_resolution,
+    });
+  }, [controlNetId, processorChanged]);
+
+  return (
+    <ProcessorWrapper>
+      <IAISlider
+        label="Detect Resolution"
+        value={detect_resolution}
+        onChange={handleDetectResolutionChanged}
+        handleReset={handleDetectResolutionReset}
+        withReset
+        min={0}
+        max={4096}
+        withInput
+      />
+      <IAISlider
+        label="Image Resolution"
+        value={image_resolution}
+        onChange={handleImageResolutionChanged}
+        handleReset={handleImageResolutionReset}
+        withReset
+        min={0}
+        max={4096}
+        withInput
+      />
+      <IAISwitch
+        label="Scribble"
+        isChecked={scribble}
+        onChange={handleScribbleChanged}
+      />
+    </ProcessorWrapper>
+  );
+};
+
+export default memo(HedPreprocessor);

invokeai/frontend/web/src/features/controlNet/components/processors/LineartAnimeProcessor.tsx

@@ -0,0 +1,72 @@
+import IAISlider from 'common/components/IAISlider';
+import { CONTROLNET_PROCESSORS } from 'features/controlNet/store/constants';
+import { RequiredLineartAnimeImageProcessorInvocation } from 'features/controlNet/store/types';
+import { memo, useCallback } from 'react';
+import { useProcessorNodeChanged } from '../hooks/useProcessorNodeChanged';
+import ProcessorWrapper from './common/ProcessorWrapper';
+
+const DEFAULTS = CONTROLNET_PROCESSORS.lineart_anime_image_processor.default;
+
+type Props = {
+  controlNetId: string;
+  processorNode: RequiredLineartAnimeImageProcessorInvocation;
+};
+
+const LineartAnimeProcessor = (props: Props) => {
+  const { controlNetId, processorNode } = props;
+  const { image_resolution, detect_resolution } = processorNode;
+  const processorChanged = useProcessorNodeChanged();
+
+  const handleDetectResolutionChanged = useCallback(
+    (v: number) => {
+      processorChanged(controlNetId, { detect_resolution: v });
+    },
+    [controlNetId, processorChanged]
+  );
+
+  const handleImageResolutionChanged = useCallback(
+    (v: number) => {
+      processorChanged(controlNetId, { image_resolution: v });
+    },
+    [controlNetId, processorChanged]
+  );
+
+  const handleDetectResolutionReset = useCallback(() => {
+    processorChanged(controlNetId, {
+      detect_resolution: DEFAULTS.detect_resolution,
+    });
+  }, [controlNetId, processorChanged]);
+
+  const handleImageResolutionReset = useCallback(() => {
+    processorChanged(controlNetId, {
+      image_resolution: DEFAULTS.image_resolution,
+    });
+  }, [controlNetId, processorChanged]);
+
+  return (
+    <ProcessorWrapper>
+      <IAISlider
+        label="Detect Resolution"
+        value={detect_resolution}
+        onChange={handleDetectResolutionChanged}
+        handleReset={handleDetectResolutionReset}
+        withReset
+        min={0}
+        max={4096}
+        withInput
+      />
+      <IAISlider
+        label="Image Resolution"
+        value={image_resolution}
+        onChange={handleImageResolutionChanged}
+        handleReset={handleImageResolutionReset}
+        withReset
+        min={0}
+        max={4096}
+        withInput
+      />
+    </ProcessorWrapper>
+  );
+};
+
+export default memo(LineartAnimeProcessor);

invokeai/frontend/web/src/features/controlNet/components/processors/LineartProcessor.tsx

@@ -0,0 +1,85 @@
+import IAISlider from 'common/components/IAISlider';
+import IAISwitch from 'common/components/IAISwitch';
+import { CONTROLNET_PROCESSORS } from 'features/controlNet/store/constants';
+import { RequiredLineartImageProcessorInvocation } from 'features/controlNet/store/types';
+import { ChangeEvent, memo, useCallback } from 'react';
+import { useProcessorNodeChanged } from '../hooks/useProcessorNodeChanged';
+import ProcessorWrapper from './common/ProcessorWrapper';
+
+const DEFAULTS = CONTROLNET_PROCESSORS.lineart_image_processor.default;
+
+type LineartProcessorProps = {
+  controlNetId: string;
+  processorNode: RequiredLineartImageProcessorInvocation;
+};
+
+const LineartProcessor = (props: LineartProcessorProps) => {
+  const { controlNetId, processorNode } = props;
+  const { image_resolution, detect_resolution, coarse } = processorNode;
+  const processorChanged = useProcessorNodeChanged();
+
+  const handleDetectResolutionChanged = useCallback(
+    (v: number) => {
+      processorChanged(controlNetId, { detect_resolution: v });
+    },
+    [controlNetId, processorChanged]
+  );
+
+  const handleImageResolutionChanged = useCallback(
+    (v: number) => {
+      processorChanged(controlNetId, { image_resolution: v });
+    },
+    [controlNetId, processorChanged]
+  );
+
+  const handleDetectResolutionReset = useCallback(() => {
+    processorChanged(controlNetId, {
+      detect_resolution: DEFAULTS.detect_resolution,
+    });
+  }, [controlNetId, processorChanged]);
+
+  const handleImageResolutionReset = useCallback(() => {
+    processorChanged(controlNetId, {
+      image_resolution: DEFAULTS.image_resolution,
+    });
+  }, [controlNetId, processorChanged]);
+
+  const handleCoarseChanged = useCallback(
+    (e: ChangeEvent<HTMLInputElement>) => {
+      processorChanged(controlNetId, { coarse: e.target.checked });
+    },
+    [controlNetId, processorChanged]
+  );
+
+  return (
+    <ProcessorWrapper>
+      <IAISlider
+        label="Detect Resolution"
+        value={detect_resolution}
+        onChange={handleDetectResolutionChanged}
+        handleReset={handleDetectResolutionReset}
+        withReset
+        min={0}
+        max={4096}
+        withInput
+      />
+      <IAISlider
+        label="Image Resolution"
+        value={image_resolution}
+        onChange={handleImageResolutionChanged}
+        handleReset={handleImageResolutionReset}
+        withReset
+        min={0}
+        max={4096}
+        withInput
+      />
+      <IAISwitch
+        label="Coarse"
+        isChecked={coarse}
+        onChange={handleCoarseChanged}
+      />
+    </ProcessorWrapper>
+  );
+};
+
+export default memo(LineartProcessor);

invokeai/frontend/web/src/features/controlNet/components/processors/MediapipeFaceProcessor.tsx

@@ -0,0 +1,69 @@
+import IAISlider from 'common/components/IAISlider';
+import { CONTROLNET_PROCESSORS } from 'features/controlNet/store/constants';
+import { RequiredMediapipeFaceProcessorInvocation } from 'features/controlNet/store/types';
+import { memo, useCallback } from 'react';
+import { useProcessorNodeChanged } from '../hooks/useProcessorNodeChanged';
+import ProcessorWrapper from './common/ProcessorWrapper';
+
+const DEFAULTS = CONTROLNET_PROCESSORS.mediapipe_face_processor.default;
+
+type Props = {
+  controlNetId: string;
+  processorNode: RequiredMediapipeFaceProcessorInvocation;
+};
+
+const MediapipeFaceProcessor = (props: Props) => {
+  const { controlNetId, processorNode } = props;
+  const { max_faces, min_confidence } = processorNode;
+  const processorChanged = useProcessorNodeChanged();
+
+  const handleMaxFacesChanged = useCallback(
+    (v: number) => {
+      processorChanged(controlNetId, { max_faces: v });
+    },
+    [controlNetId, processorChanged]
+  );
+
+  const handleMinConfidenceChanged = useCallback(
+    (v: number) => {
+      processorChanged(controlNetId, { min_confidence: v });
+    },
+    [controlNetId, processorChanged]
+  );
+
+  const handleMaxFacesReset = useCallback(() => {
+    processorChanged(controlNetId, { max_faces: DEFAULTS.max_faces });
+  }, [controlNetId, processorChanged]);
+
+  const handleMinConfidenceReset = useCallback(() => {
+    processorChanged(controlNetId, { min_confidence: DEFAULTS.min_confidence });
+  }, [controlNetId, processorChanged]);
+
+  return (
+    <ProcessorWrapper>
+      <IAISlider
+        label="Max Faces"
+        value={max_faces}
+        onChange={handleMaxFacesChanged}
+        handleReset={handleMaxFacesReset}
+        withReset
+        min={1}
+        max={20}
+        withInput
+      />
+      <IAISlider
+        label="Min Confidence"
+        value={min_confidence}
+        onChange={handleMinConfidenceChanged}
+        handleReset={handleMinConfidenceReset}
+        withReset
+        min={0}
+        max={1}
+        step={0.01}
+        withInput
+      />
+    </ProcessorWrapper>
+  );
+};
+
+export default memo(MediapipeFaceProcessor);

invokeai/frontend/web/src/features/controlNet/components/processors/MidasDepthProcessor.tsx

@@ -0,0 +1,70 @@
+import IAISlider from 'common/components/IAISlider';
+import { CONTROLNET_PROCESSORS } from 'features/controlNet/store/constants';
+import { RequiredMidasDepthImageProcessorInvocation } from 'features/controlNet/store/types';
+import { memo, useCallback } from 'react';
+import { useProcessorNodeChanged } from '../hooks/useProcessorNodeChanged';
+import ProcessorWrapper from './common/ProcessorWrapper';
+
+const DEFAULTS = CONTROLNET_PROCESSORS.midas_depth_image_processor.default;
+
+type Props = {
+  controlNetId: string;
+  processorNode: RequiredMidasDepthImageProcessorInvocation;
+};
+
+const MidasDepthProcessor = (props: Props) => {
+  const { controlNetId, processorNode } = props;
+  const { a_mult, bg_th } = processorNode;
+  const processorChanged = useProcessorNodeChanged();
+
+  const handleAMultChanged = useCallback(
+    (v: number) => {
+      processorChanged(controlNetId, { a_mult: v });
+    },
+    [controlNetId, processorChanged]
+  );
+
+  const handleBgThChanged = useCallback(
+    (v: number) => {
+      processorChanged(controlNetId, { bg_th: v });
+    },
+    [controlNetId, processorChanged]
+  );
+
+  const handleAMultReset = useCallback(() => {
+    processorChanged(controlNetId, { a_mult: DEFAULTS.a_mult });
+  }, [controlNetId, processorChanged]);
+
+  const handleBgThReset = useCallback(() => {
+    processorChanged(controlNetId, { bg_th: DEFAULTS.bg_th });
+  }, [controlNetId, processorChanged]);
+
+  return (
+    <ProcessorWrapper>
+      <IAISlider
+        label="a_mult"
+        value={a_mult}
+        onChange={handleAMultChanged}
+        handleReset={handleAMultReset}
+        withReset
+        min={0}
+        max={20}
+        step={0.01}
+        withInput
+      />
+      <IAISlider
+        label="bg_th"
+        value={bg_th}
+        onChange={handleBgThChanged}
+        handleReset={handleBgThReset}
+        withReset
+        min={0}
+        max={20}
+        step={0.01}
+        withInput
+      />
+    </ProcessorWrapper>
+  );
+};
+
+export default memo(MidasDepthProcessor);

invokeai/frontend/web/src/features/controlNet/components/processors/MlsdImageProcessor.tsx

@@ -0,0 +1,116 @@
+import IAISlider from 'common/components/IAISlider';
+import { CONTROLNET_PROCESSORS } from 'features/controlNet/store/constants';
+import { RequiredMlsdImageProcessorInvocation } from 'features/controlNet/store/types';
+import { memo, useCallback } from 'react';
+import { useProcessorNodeChanged } from '../hooks/useProcessorNodeChanged';
+import ProcessorWrapper from './common/ProcessorWrapper';
+
+const DEFAULTS = CONTROLNET_PROCESSORS.mlsd_image_processor.default;
+
+type Props = {
+  controlNetId: string;
+  processorNode: RequiredMlsdImageProcessorInvocation;
+};
+
+const MlsdImageProcessor = (props: Props) => {
+  const { controlNetId, processorNode } = props;
+  const { image_resolution, detect_resolution, thr_d, thr_v } = processorNode;
+  const processorChanged = useProcessorNodeChanged();
+
+  const handleDetectResolutionChanged = useCallback(
+    (v: number) => {
+      processorChanged(controlNetId, { detect_resolution: v });
+    },
+    [controlNetId, processorChanged]
+  );
+
+  const handleImageResolutionChanged = useCallback(
+    (v: number) => {
+      processorChanged(controlNetId, { image_resolution: v });
+    },
+    [controlNetId, processorChanged]
+  );
+
+  const handleThrDChanged = useCallback(
+    (v: number) => {
+      processorChanged(controlNetId, { thr_d: v });
+    },
+    [controlNetId, processorChanged]
+  );
+
+  const handleThrVChanged = useCallback(
+    (v: number) => {
+      processorChanged(controlNetId, { thr_v: v });
+    },
+    [controlNetId, processorChanged]
+  );
+
+  const handleDetectResolutionReset = useCallback(() => {
+    processorChanged(controlNetId, {
+      detect_resolution: DEFAULTS.detect_resolution,
+    });
+  }, [controlNetId, processorChanged]);
+
+  const handleImageResolutionReset = useCallback(() => {
+    processorChanged(controlNetId, {
+      image_resolution: DEFAULTS.image_resolution,
+    });
+  }, [controlNetId, processorChanged]);
+
+  const handleThrDReset = useCallback(() => {
+    processorChanged(controlNetId, { thr_d: DEFAULTS.thr_d });
+  }, [controlNetId, processorChanged]);
+
+  const handleThrVReset = useCallback(() => {
+    processorChanged(controlNetId, { thr_v: DEFAULTS.thr_v });
+  }, [controlNetId, processorChanged]);
+
+  return (
+    <ProcessorWrapper>
+      <IAISlider
+        label="Detect Resolution"
+        value={detect_resolution}
+        onChange={handleDetectResolutionChanged}
+        handleReset={handleDetectResolutionReset}
+        withReset
+        min={0}
+        max={4096}
+        withInput
+      />
+      <IAISlider
+        label="Image Resolution"
+        value={image_resolution}
+        onChange={handleImageResolutionChanged}
+        handleReset={handleImageResolutionReset}
+        withReset
+        min={0}
+        max={4096}
+        withInput
+      />
+      <IAISlider
+        label="W"
+        value={thr_d}
+        onChange={handleThrDChanged}
+        handleReset={handleThrDReset}
+        withReset
+        min={0}
+        max={1}
+        step={0.01}
+        withInput
+      />
+      <IAISlider
+        label="H"
+        value={thr_v}
+        onChange={handleThrVChanged}
+        handleReset={handleThrVReset}
+        withReset
+        min={0}
+        max={1}
+        step={0.01}
+        withInput
+      />
+    </ProcessorWrapper>
+  );
+};
+
+export default memo(MlsdImageProcessor);

invokeai/frontend/web/src/features/controlNet/components/processors/NormalBaeProcessor.tsx

@@ -0,0 +1,72 @@
+import IAISlider from 'common/components/IAISlider';
+import { CONTROLNET_PROCESSORS } from 'features/controlNet/store/constants';
+import { RequiredNormalbaeImageProcessorInvocation } from 'features/controlNet/store/types';
+import { memo, useCallback } from 'react';
+import { useProcessorNodeChanged } from '../hooks/useProcessorNodeChanged';
+import ProcessorWrapper from './common/ProcessorWrapper';
+
+const DEFAULTS = CONTROLNET_PROCESSORS.normalbae_image_processor.default;
+
+type Props = {
+  controlNetId: string;
+  processorNode: RequiredNormalbaeImageProcessorInvocation;
+};
+
+const NormalBaeProcessor = (props: Props) => {
+  const { controlNetId, processorNode } = props;
+  const { image_resolution, detect_resolution } = processorNode;
+  const processorChanged = useProcessorNodeChanged();
+
+  const handleDetectResolutionChanged = useCallback(
+    (v: number) => {
+      processorChanged(controlNetId, { detect_resolution: v });
+    },
+    [controlNetId, processorChanged]
+  );
+
+  const handleImageResolutionChanged = useCallback(
+    (v: number) => {
+      processorChanged(controlNetId, { image_resolution: v });
+    },
+    [controlNetId, processorChanged]
+  );
+
+  const handleDetectResolutionReset = useCallback(() => {
+    processorChanged(controlNetId, {
+      detect_resolution: DEFAULTS.detect_resolution,
+    });
+  }, [controlNetId, processorChanged]);
+
+  const handleImageResolutionReset = useCallback(() => {
+    processorChanged(controlNetId, {
+      image_resolution: DEFAULTS.image_resolution,
+    });
+  }, [controlNetId, processorChanged]);
+
+  return (
+    <ProcessorWrapper>
+      <IAISlider
+        label="Detect Resolution"
+        value={detect_resolution}
+        onChange={handleDetectResolutionChanged}
+        handleReset={handleDetectResolutionReset}
+        withReset
+        min={0}
+        max={4096}
+        withInput
+      />
+      <IAISlider
+        label="Image Resolution"
+        value={image_resolution}
+        onChange={handleImageResolutionChanged}
+        handleReset={handleImageResolutionReset}
+        withReset
+        min={0}
+        max={4096}
+        withInput
+      />
+    </ProcessorWrapper>
+  );
+};
+
+export default memo(NormalBaeProcessor);

invokeai/frontend/web/src/features/controlNet/components/processors/OpenposeProcessor.tsx

@@ -0,0 +1,85 @@
+import IAISlider from 'common/components/IAISlider';
+import IAISwitch from 'common/components/IAISwitch';
+import { CONTROLNET_PROCESSORS } from 'features/controlNet/store/constants';
+import { RequiredOpenposeImageProcessorInvocation } from 'features/controlNet/store/types';
+import { ChangeEvent, memo, useCallback } from 'react';
+import { useProcessorNodeChanged } from '../hooks/useProcessorNodeChanged';
+import ProcessorWrapper from './common/ProcessorWrapper';
+
+const DEFAULTS = CONTROLNET_PROCESSORS.openpose_image_processor.default;
+
+type Props = {
+  controlNetId: string;
+  processorNode: RequiredOpenposeImageProcessorInvocation;
+};
+
+const OpenposeProcessor = (props: Props) => {
+  const { controlNetId, processorNode } = props;
+  const { image_resolution, detect_resolution, hand_and_face } = processorNode;
+  const processorChanged = useProcessorNodeChanged();
+
+  const handleDetectResolutionChanged = useCallback(
+    (v: number) => {
+      processorChanged(controlNetId, { detect_resolution: v });
+    },
+    [controlNetId, processorChanged]
+  );
+
+  const handleImageResolutionChanged = useCallback(
+    (v: number) => {
+      processorChanged(controlNetId, { image_resolution: v });
+    },
+    [controlNetId, processorChanged]
+  );
+
+  const handleDetectResolutionReset = useCallback(() => {
+    processorChanged(controlNetId, {
+      detect_resolution: DEFAULTS.detect_resolution,
+    });
+  }, [controlNetId, processorChanged]);
+
+  const handleImageResolutionReset = useCallback(() => {
+    processorChanged(controlNetId, {
+      image_resolution: DEFAULTS.image_resolution,
+    });
+  }, [controlNetId, processorChanged]);
+
+  const handleHandAndFaceChanged = useCallback(
+    (e: ChangeEvent<HTMLInputElement>) => {
+      processorChanged(controlNetId, { hand_and_face: e.target.checked });
+    },
+    [controlNetId, processorChanged]
+  );
+
+  return (
+    <ProcessorWrapper>
+      <IAISlider
+        label="Detect Resolution"
+        value={detect_resolution}
+        onChange={handleDetectResolutionChanged}
+        handleReset={handleDetectResolutionReset}
+        withReset
+        min={0}
+        max={4096}
+        withInput
+      />
+      <IAISlider
+        label="Image Resolution"
+        value={image_resolution}
+        onChange={handleImageResolutionChanged}
+        handleReset={handleImageResolutionReset}
+        withReset
+        min={0}
+        max={4096}
+        withInput
+      />
+      <IAISwitch
+        label="Hand and Face"
+        isChecked={hand_and_face}
+        onChange={handleHandAndFaceChanged}
+      />
+    </ProcessorWrapper>
+  );
+};
+
+export default memo(OpenposeProcessor);

invokeai/frontend/web/src/features/controlNet/components/processors/PidiProcessor.tsx

@@ -0,0 +1,93 @@
+import IAISlider from 'common/components/IAISlider';
+import IAISwitch from 'common/components/IAISwitch';
+import { CONTROLNET_PROCESSORS } from 'features/controlNet/store/constants';
+import { RequiredPidiImageProcessorInvocation } from 'features/controlNet/store/types';
+import { ChangeEvent, memo, useCallback } from 'react';
+import { useProcessorNodeChanged } from '../hooks/useProcessorNodeChanged';
+import ProcessorWrapper from './common/ProcessorWrapper';
+
+const DEFAULTS = CONTROLNET_PROCESSORS.pidi_image_processor.default;
+
+type Props = {
+  controlNetId: string;
+  processorNode: RequiredPidiImageProcessorInvocation;
+};
+
+const PidiProcessor = (props: Props) => {
+  const { controlNetId, processorNode } = props;
+  const { image_resolution, detect_resolution, scribble, safe } = processorNode;
+  const processorChanged = useProcessorNodeChanged();
+
+  const handleDetectResolutionChanged = useCallback(
+    (v: number) => {
+      processorChanged(controlNetId, { detect_resolution: v });
+    },
+    [controlNetId, processorChanged]
+  );
+
+  const handleImageResolutionChanged = useCallback(
+    (v: number) => {
+      processorChanged(controlNetId, { image_resolution: v });
+    },
+    [controlNetId, processorChanged]
+  );
+
+  const handleDetectResolutionReset = useCallback(() => {
+    processorChanged(controlNetId, {
+      detect_resolution: DEFAULTS.detect_resolution,
+    });
+  }, [controlNetId, processorChanged]);
+
+  const handleImageResolutionReset = useCallback(() => {
+    processorChanged(controlNetId, {
+      image_resolution: DEFAULTS.image_resolution,
+    });
+  }, [controlNetId, processorChanged]);
+
+  const handleScribbleChanged = useCallback(
+    (e: ChangeEvent<HTMLInputElement>) => {
+      processorChanged(controlNetId, { scribble: e.target.checked });
+    },
+    [controlNetId, processorChanged]
+  );
+
+  const handleSafeChanged = useCallback(
+    (e: ChangeEvent<HTMLInputElement>) => {
+      processorChanged(controlNetId, { safe: e.target.checked });
+    },
+    [controlNetId, processorChanged]
+  );
+
+  return (
+    <ProcessorWrapper>
+      <IAISlider
+        label="Detect Resolution"
+        value={detect_resolution}
+        onChange={handleDetectResolutionChanged}
+        handleReset={handleDetectResolutionReset}
+        withReset
+        min={0}
+        max={4096}
+        withInput
+      />
+      <IAISlider
+        label="Image Resolution"
+        value={image_resolution}
+        onChange={handleImageResolutionChanged}
+        handleReset={handleImageResolutionReset}
+        withReset
+        min={0}
+        max={4096}
+        withInput
+      />
+      <IAISwitch
+        label="Scribble"
+        isChecked={scribble}
+        onChange={handleScribbleChanged}
+      />
+      <IAISwitch label="Safe" isChecked={safe} onChange={handleSafeChanged} />
+    </ProcessorWrapper>
+  );
+};
+
+export default memo(PidiProcessor);

invokeai/frontend/web/src/features/controlNet/components/processors/ZoeDepthProcessor.tsx

@@ -0,0 +1,14 @@
+import { RequiredZoeDepthImageProcessorInvocation } from 'features/controlNet/store/types';
+import { memo } from 'react';
+
+type Props = {
+  controlNetId: string;
+  processorNode: RequiredZoeDepthImageProcessorInvocation;
+};
+
+const ZoeDepthProcessor = (props: Props) => {
+  // Has no parameters?
+  return null;
+};
+
+export default memo(ZoeDepthProcessor);

invokeai/frontend/web/src/features/controlNet/components/processors/common/ProcessorWrapper.tsx

@@ -0,0 +1,8 @@
+import { Flex } from '@chakra-ui/react';
+import { PropsWithChildren } from 'react';
+
+type Props = PropsWithChildren;
+
+export default function ProcessorWrapper(props: Props) {
+  return <Flex sx={{ flexDirection: 'column', gap: 2 }}>{props.children}</Flex>;
+}

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

@@ -0,0 +1,5 @@
+import { createAction } from '@reduxjs/toolkit';
+
+export const controlNetImageProcessed = createAction<{
+  controlNetId: string;
+}>('controlNet/imageProcessed');

invokeai/frontend/web/src/features/controlNet/store/constants.ts

@@ -0,0 +1,212 @@
+import {
+  ControlNetProcessorType,
+  RequiredCannyImageProcessorInvocation,
+  RequiredControlNetProcessorNode,
+} from './types';
+
+type ControlNetProcessorsDict = Record<
+  ControlNetProcessorType,
+  {
+    type: ControlNetProcessorType;
+    label: string;
+    description: string;
+    default: RequiredControlNetProcessorNode;
+  }
+>;
+
+/**
+ * A dict of ControlNet processors, including:
+ * - type
+ * - label
+ * - description
+ * - default values
+ *
+ * TODO: Generate from the OpenAPI schema
+ */
+export const CONTROLNET_PROCESSORS = {
+  none: {
+    type: 'none',
+    label: 'None',
+    description: '',
+    default: {
+      type: 'none',
+    },
+  },
+  canny_image_processor: {
+    type: 'canny_image_processor',
+    label: 'Canny',
+    description: '',
+    default: {
+      id: 'canny_image_processor',
+      type: 'canny_image_processor',
+      low_threshold: 100,
+      high_threshold: 200,
+    },
+  },
+  content_shuffle_image_processor: {
+    type: 'content_shuffle_image_processor',
+    label: 'Content Shuffle',
+    description: '',
+    default: {
+      id: 'content_shuffle_image_processor',
+      type: 'content_shuffle_image_processor',
+      detect_resolution: 512,
+      image_resolution: 512,
+      h: 512,
+      w: 512,
+      f: 256,
+    },
+  },
+  hed_image_processor: {
+    type: 'hed_image_processor',
+    label: 'HED',
+    description: '',
+    default: {
+      id: 'hed_image_processor',
+      type: 'hed_image_processor',
+      detect_resolution: 512,
+      image_resolution: 512,
+      scribble: false,
+    },
+  },
+  lineart_anime_image_processor: {
+    type: 'lineart_anime_image_processor',
+    label: 'Lineart Anime',
+    description: '',
+    default: {
+      id: 'lineart_anime_image_processor',
+      type: 'lineart_anime_image_processor',
+      detect_resolution: 512,
+      image_resolution: 512,
+    },
+  },
+  lineart_image_processor: {
+    type: 'lineart_image_processor',
+    label: 'Lineart',
+    description: '',
+    default: {
+      id: 'lineart_image_processor',
+      type: 'lineart_image_processor',
+      detect_resolution: 512,
+      image_resolution: 512,
+      coarse: false,
+    },
+  },
+  mediapipe_face_processor: {
+    type: 'mediapipe_face_processor',
+    label: 'Mediapipe Face',
+    description: '',
+    default: {
+      id: 'mediapipe_face_processor',
+      type: 'mediapipe_face_processor',
+      max_faces: 1,
+      min_confidence: 0.5,
+    },
+  },
+  midas_depth_image_processor: {
+    type: 'midas_depth_image_processor',
+    label: 'Depth (Midas)',
+    description: '',
+    default: {
+      id: 'midas_depth_image_processor',
+      type: 'midas_depth_image_processor',
+      a_mult: 2,
+      bg_th: 0.1,
+    },
+  },
+  mlsd_image_processor: {
+    type: 'mlsd_image_processor',
+    label: 'MLSD',
+    description: '',
+    default: {
+      id: 'mlsd_image_processor',
+      type: 'mlsd_image_processor',
+      detect_resolution: 512,
+      image_resolution: 512,
+      thr_d: 0.1,
+      thr_v: 0.1,
+    },
+  },
+  normalbae_image_processor: {
+    type: 'normalbae_image_processor',
+    label: 'NormalBae',
+    description: '',
+    default: {
+      id: 'normalbae_image_processor',
+      type: 'normalbae_image_processor',
+      detect_resolution: 512,
+      image_resolution: 512,
+    },
+  },
+  openpose_image_processor: {
+    type: 'openpose_image_processor',
+    label: 'Openpose',
+    description: '',
+    default: {
+      id: 'openpose_image_processor',
+      type: 'openpose_image_processor',
+      detect_resolution: 512,
+      image_resolution: 512,
+      hand_and_face: false,
+    },
+  },
+  pidi_image_processor: {
+    type: 'pidi_image_processor',
+    label: 'PIDI',
+    description: '',
+    default: {
+      id: 'pidi_image_processor',
+      type: 'pidi_image_processor',
+      detect_resolution: 512,
+      image_resolution: 512,
+      scribble: false,
+      safe: false,
+    },
+  },
+  zoe_depth_image_processor: {
+    type: 'zoe_depth_image_processor',
+    label: 'Depth (Zoe)',
+    description: '',
+    default: {
+      id: 'zoe_depth_image_processor',
+      type: 'zoe_depth_image_processor',
+    },
+  },
+};
+
+export const CONTROLNET_MODELS = [
+  'lllyasviel/control_v11p_sd15_canny',
+  'lllyasviel/control_v11p_sd15_inpaint',
+  'lllyasviel/control_v11p_sd15_mlsd',
+  'lllyasviel/control_v11f1p_sd15_depth',
+  'lllyasviel/control_v11p_sd15_normalbae',
+  'lllyasviel/control_v11p_sd15_seg',
+  'lllyasviel/control_v11p_sd15_lineart',
+  'lllyasviel/control_v11p_sd15s2_lineart_anime',
+  'lllyasviel/control_v11p_sd15_scribble',
+  'lllyasviel/control_v11p_sd15_softedge',
+  'lllyasviel/control_v11e_sd15_shuffle',
+  'lllyasviel/control_v11p_sd15_openpose',
+  'lllyasviel/control_v11f1e_sd15_tile',
+  'lllyasviel/control_v11e_sd15_ip2p',
+  'CrucibleAI/ControlNetMediaPipeFace',
+];
+
+export type ControlNetModel = (typeof CONTROLNET_MODELS)[number];
+
+export const CONTROLNET_MODEL_MAP: Record<
+  ControlNetModel,
+  ControlNetProcessorType
+> = {
+  'lllyasviel/control_v11p_sd15_canny': 'canny_image_processor',
+  'lllyasviel/control_v11p_sd15_mlsd': 'mlsd_image_processor',
+  'lllyasviel/control_v11f1p_sd15_depth': 'midas_depth_image_processor',
+  'lllyasviel/control_v11p_sd15_normalbae': 'normalbae_image_processor',
+  'lllyasviel/control_v11p_sd15_lineart': 'lineart_image_processor',
+  'lllyasviel/control_v11p_sd15s2_lineart_anime':
+    'lineart_anime_image_processor',
+  'lllyasviel/control_v11p_sd15_softedge': 'hed_image_processor',
+  'lllyasviel/control_v11e_sd15_shuffle': 'content_shuffle_image_processor',
+  'lllyasviel/control_v11p_sd15_openpose': 'openpose_image_processor',
+  'CrucibleAI/ControlNetMediaPipeFace': 'mediapipe_face_processor',
+};

invokeai/frontend/web/src/features/controlNet/store/controlNetDenylist.ts

@@ -0,0 +1,8 @@
+import { ControlNetState } from './controlNetSlice';
+
+/**
+ * ControlNet slice persist denylist
+ */
+export const controlNetDenylist: (keyof ControlNetState)[] = [
+  'isProcessingControlImage',
+];

invokeai/frontend/web/src/features/controlNet/store/controlNetSlice.ts

@@ -0,0 +1,218 @@
+import { PayloadAction } from '@reduxjs/toolkit';
+import { createSlice } from '@reduxjs/toolkit';
+import { RootState } from 'app/store/store';
+import { ImageDTO } from 'services/api';
+import {
+  ControlNetProcessorType,
+  RequiredCannyImageProcessorInvocation,
+  RequiredControlNetProcessorNode,
+} from './types';
+import {
+  CONTROLNET_MODELS,
+  CONTROLNET_PROCESSORS,
+  ControlNetModel,
+} from './constants';
+import { controlNetImageProcessed } from './actions';
+
+export const initialControlNet: Omit<ControlNetConfig, 'controlNetId'> = {
+  isEnabled: true,
+  model: CONTROLNET_MODELS[0],
+  weight: 1,
+  beginStepPct: 0,
+  endStepPct: 1,
+  controlImage: null,
+  processedControlImage: null,
+  processorType: 'canny_image_processor',
+  processorNode: CONTROLNET_PROCESSORS.canny_image_processor
+    .default as RequiredCannyImageProcessorInvocation,
+};
+
+export type ControlNetConfig = {
+  controlNetId: string;
+  isEnabled: boolean;
+  model: ControlNetModel;
+  weight: number;
+  beginStepPct: number;
+  endStepPct: number;
+  controlImage: ImageDTO | null;
+  processedControlImage: ImageDTO | null;
+  processorType: ControlNetProcessorType;
+  processorNode: RequiredControlNetProcessorNode;
+};
+
+export type ControlNetState = {
+  controlNets: Record<string, ControlNetConfig>;
+  isEnabled: boolean;
+  isProcessingControlImage: boolean;
+};
+
+export const initialControlNetState: ControlNetState = {
+  controlNets: {},
+  isEnabled: false,
+  isProcessingControlImage: false,
+};
+
+export const controlNetSlice = createSlice({
+  name: 'controlNet',
+  initialState: initialControlNetState,
+  reducers: {
+    isControlNetEnabledToggled: (state) => {
+      state.isEnabled = !state.isEnabled;
+    },
+    controlNetAdded: (
+      state,
+      action: PayloadAction<{
+        controlNetId: string;
+        controlNet?: ControlNetConfig;
+      }>
+    ) => {
+      const { controlNetId, controlNet } = action.payload;
+      state.controlNets[controlNetId] = {
+        ...(controlNet ?? initialControlNet),
+        controlNetId,
+      };
+    },
+    controlNetAddedFromImage: (
+      state,
+      action: PayloadAction<{ controlNetId: string; controlImage: ImageDTO }>
+    ) => {
+      const { controlNetId, controlImage } = action.payload;
+      state.controlNets[controlNetId] = {
+        ...initialControlNet,
+        controlNetId,
+        controlImage,
+      };
+    },
+    controlNetRemoved: (
+      state,
+      action: PayloadAction<{ controlNetId: string }>
+    ) => {
+      const { controlNetId } = action.payload;
+      delete state.controlNets[controlNetId];
+    },
+    controlNetToggled: (
+      state,
+      action: PayloadAction<{ controlNetId: string }>
+    ) => {
+      const { controlNetId } = action.payload;
+      state.controlNets[controlNetId].isEnabled =
+        !state.controlNets[controlNetId].isEnabled;
+    },
+    controlNetImageChanged: (
+      state,
+      action: PayloadAction<{
+        controlNetId: string;
+        controlImage: ImageDTO | null;
+      }>
+    ) => {
+      const { controlNetId, controlImage } = action.payload;
+      state.controlNets[controlNetId].controlImage = controlImage;
+      state.controlNets[controlNetId].processedControlImage = null;
+      if (
+        controlImage !== null &&
+        state.controlNets[controlNetId].processorType !== 'none'
+      ) {
+        state.isProcessingControlImage = true;
+      }
+    },
+    controlNetProcessedImageChanged: (
+      state,
+      action: PayloadAction<{
+        controlNetId: string;
+        processedControlImage: ImageDTO | null;
+      }>
+    ) => {
+      const { controlNetId, processedControlImage } = action.payload;
+      state.controlNets[controlNetId].processedControlImage =
+        processedControlImage;
+      state.isProcessingControlImage = false;
+    },
+    controlNetModelChanged: (
+      state,
+      action: PayloadAction<{ controlNetId: string; model: ControlNetModel }>
+    ) => {
+      const { controlNetId, model } = action.payload;
+      state.controlNets[controlNetId].model = model;
+    },
+    controlNetWeightChanged: (
+      state,
+      action: PayloadAction<{ controlNetId: string; weight: number }>
+    ) => {
+      const { controlNetId, weight } = action.payload;
+      state.controlNets[controlNetId].weight = weight;
+    },
+    controlNetBeginStepPctChanged: (
+      state,
+      action: PayloadAction<{ controlNetId: string; beginStepPct: number }>
+    ) => {
+      const { controlNetId, beginStepPct } = action.payload;
+      state.controlNets[controlNetId].beginStepPct = beginStepPct;
+    },
+    controlNetEndStepPctChanged: (
+      state,
+      action: PayloadAction<{ controlNetId: string; endStepPct: number }>
+    ) => {
+      const { controlNetId, endStepPct } = action.payload;
+      state.controlNets[controlNetId].endStepPct = endStepPct;
+    },
+    controlNetProcessorParamsChanged: (
+      state,
+      action: PayloadAction<{
+        controlNetId: string;
+        changes: Omit<
+          Partial<RequiredControlNetProcessorNode>,
+          'id' | 'type' | 'is_intermediate'
+        >;
+      }>
+    ) => {
+      const { controlNetId, changes } = action.payload;
+      const processorNode = state.controlNets[controlNetId].processorNode;
+      state.controlNets[controlNetId].processorNode = {
+        ...processorNode,
+        ...changes,
+      };
+    },
+    controlNetProcessorTypeChanged: (
+      state,
+      action: PayloadAction<{
+        controlNetId: string;
+        processorType: ControlNetProcessorType;
+      }>
+    ) => {
+      const { controlNetId, processorType } = action.payload;
+      state.controlNets[controlNetId].processorType = processorType;
+      state.controlNets[controlNetId].processorNode = CONTROLNET_PROCESSORS[
+        processorType
+      ].default as RequiredControlNetProcessorNode;
+    },
+  },
+  extraReducers: (builder) => {
+    builder.addCase(controlNetImageProcessed, (state, action) => {
+      if (
+        state.controlNets[action.payload.controlNetId].controlImage !== null
+      ) {
+        state.isProcessingControlImage = true;
+      }
+    });
+  },
+});
+
+export const {
+  isControlNetEnabledToggled,
+  controlNetAdded,
+  controlNetAddedFromImage,
+  controlNetRemoved,
+  controlNetImageChanged,
+  controlNetProcessedImageChanged,
+  controlNetToggled,
+  controlNetModelChanged,
+  controlNetWeightChanged,
+  controlNetBeginStepPctChanged,
+  controlNetEndStepPctChanged,
+  controlNetProcessorParamsChanged,
+  controlNetProcessorTypeChanged,
+} = controlNetSlice.actions;
+
+export default controlNetSlice.reducer;
+
+export const controlNetSelector = (state: RootState) => state.controlNet;

invokeai/frontend/web/src/features/controlNet/store/types.ts

@@ -0,0 +1,329 @@
+import { isObject } from 'lodash-es';
+import {
+  CannyImageProcessorInvocation,
+  ContentShuffleImageProcessorInvocation,
+  HedImageProcessorInvocation,
+  LineartAnimeImageProcessorInvocation,
+  LineartImageProcessorInvocation,
+  MediapipeFaceProcessorInvocation,
+  MidasDepthImageProcessorInvocation,
+  MlsdImageProcessorInvocation,
+  NormalbaeImageProcessorInvocation,
+  OpenposeImageProcessorInvocation,
+  PidiImageProcessorInvocation,
+  ZoeDepthImageProcessorInvocation,
+} from 'services/api';
+import { O } from 'ts-toolbelt';
+
+/**
+ * Any ControlNet processor node
+ */
+export type ControlNetProcessorNode =
+  | CannyImageProcessorInvocation
+  | ContentShuffleImageProcessorInvocation
+  | HedImageProcessorInvocation
+  | LineartAnimeImageProcessorInvocation
+  | LineartImageProcessorInvocation
+  | MediapipeFaceProcessorInvocation
+  | MidasDepthImageProcessorInvocation
+  | MlsdImageProcessorInvocation
+  | NormalbaeImageProcessorInvocation
+  | OpenposeImageProcessorInvocation
+  | PidiImageProcessorInvocation
+  | ZoeDepthImageProcessorInvocation;
+
+/**
+ * Any ControlNet processor type
+ */
+export type ControlNetProcessorType = NonNullable<
+  ControlNetProcessorNode['type'] | 'none'
+>;
+
+/**
+ * The Canny processor node, with parameters flagged as required
+ */
+export type RequiredCannyImageProcessorInvocation = O.Required<
+  CannyImageProcessorInvocation,
+  'type' | 'low_threshold' | 'high_threshold'
+>;
+
+/**
+ * The ContentShuffle processor node, with parameters flagged as required
+ */
+export type RequiredContentShuffleImageProcessorInvocation = O.Required<
+  ContentShuffleImageProcessorInvocation,
+  'type' | 'detect_resolution' | 'image_resolution' | 'w' | 'h' | 'f'
+>;
+
+/**
+ * The HED processor node, with parameters flagged as required
+ */
+export type RequiredHedImageProcessorInvocation = O.Required<
+  HedImageProcessorInvocation,
+  'type' | 'detect_resolution' | 'image_resolution' | 'scribble'
+>;
+
+/**
+ * The Lineart Anime processor node, with parameters flagged as required
+ */
+export type RequiredLineartAnimeImageProcessorInvocation = O.Required<
+  LineartAnimeImageProcessorInvocation,
+  'type' | 'detect_resolution' | 'image_resolution'
+>;
+
+/**
+ * The Lineart processor node, with parameters flagged as required
+ */
+export type RequiredLineartImageProcessorInvocation = O.Required<
+  LineartImageProcessorInvocation,
+  'type' | 'detect_resolution' | 'image_resolution' | 'coarse'
+>;
+
+/**
+ * The MediapipeFace processor node, with parameters flagged as required
+ */
+export type RequiredMediapipeFaceProcessorInvocation = O.Required<
+  MediapipeFaceProcessorInvocation,
+  'type' | 'max_faces' | 'min_confidence'
+>;
+
+/**
+ * The MidasDepth processor node, with parameters flagged as required
+ */
+export type RequiredMidasDepthImageProcessorInvocation = O.Required<
+  MidasDepthImageProcessorInvocation,
+  'type' | 'a_mult' | 'bg_th'
+>;
+
+/**
+ * The MLSD processor node, with parameters flagged as required
+ */
+export type RequiredMlsdImageProcessorInvocation = O.Required<
+  MlsdImageProcessorInvocation,
+  'type' | 'detect_resolution' | 'image_resolution' | 'thr_v' | 'thr_d'
+>;
+
+/**
+ * The NormalBae processor node, with parameters flagged as required
+ */
+export type RequiredNormalbaeImageProcessorInvocation = O.Required<
+  NormalbaeImageProcessorInvocation,
+  'type' | 'detect_resolution' | 'image_resolution'
+>;
+
+/**
+ * The Openpose processor node, with parameters flagged as required
+ */
+export type RequiredOpenposeImageProcessorInvocation = O.Required<
+  OpenposeImageProcessorInvocation,
+  'type' | 'detect_resolution' | 'image_resolution' | 'hand_and_face'
+>;
+
+/**
+ * The Pidi processor node, with parameters flagged as required
+ */
+export type RequiredPidiImageProcessorInvocation = O.Required<
+  PidiImageProcessorInvocation,
+  'type' | 'detect_resolution' | 'image_resolution' | 'safe' | 'scribble'
+>;
+
+/**
+ * The ZoeDepth processor node, with parameters flagged as required
+ */
+export type RequiredZoeDepthImageProcessorInvocation = O.Required<
+  ZoeDepthImageProcessorInvocation,
+  'type'
+>;
+
+/**
+ * Any ControlNet Processor node, with its parameters flagged as required
+ */
+export type RequiredControlNetProcessorNode =
+  | RequiredCannyImageProcessorInvocation
+  | RequiredContentShuffleImageProcessorInvocation
+  | RequiredHedImageProcessorInvocation
+  | RequiredLineartAnimeImageProcessorInvocation
+  | RequiredLineartImageProcessorInvocation
+  | RequiredMediapipeFaceProcessorInvocation
+  | RequiredMidasDepthImageProcessorInvocation
+  | RequiredMlsdImageProcessorInvocation
+  | RequiredNormalbaeImageProcessorInvocation
+  | RequiredOpenposeImageProcessorInvocation
+  | RequiredPidiImageProcessorInvocation
+  | RequiredZoeDepthImageProcessorInvocation;
+
+/**
+ * Type guard for CannyImageProcessorInvocation
+ */
+export const isCannyImageProcessorInvocation = (
+  obj: unknown
+): obj is CannyImageProcessorInvocation => {
+  if (isObject(obj) && 'type' in obj && obj.type === 'canny_image_processor') {
+    return true;
+  }
+  return false;
+};
+
+/**
+ * Type guard for ContentShuffleImageProcessorInvocation
+ */
+export const isContentShuffleImageProcessorInvocation = (
+  obj: unknown
+): obj is ContentShuffleImageProcessorInvocation => {
+  if (
+    isObject(obj) &&
+    'type' in obj &&
+    obj.type === 'content_shuffle_image_processor'
+  ) {
+    return true;
+  }
+  return false;
+};
+
+/**
+ * Type guard for HedImageprocessorInvocation
+ */
+export const isHedImageprocessorInvocation = (
+  obj: unknown
+): obj is HedImageProcessorInvocation => {
+  if (isObject(obj) && 'type' in obj && obj.type === 'hed_image_processor') {
+    return true;
+  }
+  return false;
+};
+
+/**
+ * Type guard for LineartAnimeImageProcessorInvocation
+ */
+export const isLineartAnimeImageProcessorInvocation = (
+  obj: unknown
+): obj is LineartAnimeImageProcessorInvocation => {
+  if (
+    isObject(obj) &&
+    'type' in obj &&
+    obj.type === 'lineart_anime_image_processor'
+  ) {
+    return true;
+  }
+  return false;
+};
+
+/**
+ * Type guard for LineartImageProcessorInvocation
+ */
+export const isLineartImageProcessorInvocation = (
+  obj: unknown
+): obj is LineartImageProcessorInvocation => {
+  if (
+    isObject(obj) &&
+    'type' in obj &&
+    obj.type === 'lineart_image_processor'
+  ) {
+    return true;
+  }
+  return false;
+};
+
+/**
+ * Type guard for MediapipeFaceProcessorInvocation
+ */
+export const isMediapipeFaceProcessorInvocation = (
+  obj: unknown
+): obj is MediapipeFaceProcessorInvocation => {
+  if (
+    isObject(obj) &&
+    'type' in obj &&
+    obj.type === 'mediapipe_face_processor'
+  ) {
+    return true;
+  }
+  return false;
+};
+
+/**
+ * Type guard for MidasDepthImageProcessorInvocation
+ */
+export const isMidasDepthImageProcessorInvocation = (
+  obj: unknown
+): obj is MidasDepthImageProcessorInvocation => {
+  if (
+    isObject(obj) &&
+    'type' in obj &&
+    obj.type === 'midas_depth_image_processor'
+  ) {
+    return true;
+  }
+  return false;
+};
+
+/**
+ * Type guard for MlsdImageProcessorInvocation
+ */
+export const isMlsdImageProcessorInvocation = (
+  obj: unknown
+): obj is MlsdImageProcessorInvocation => {
+  if (isObject(obj) && 'type' in obj && obj.type === 'mlsd_image_processor') {
+    return true;
+  }
+  return false;
+};
+
+/**
+ * Type guard for NormalbaeImageProcessorInvocation
+ */
+export const isNormalbaeImageProcessorInvocation = (
+  obj: unknown
+): obj is NormalbaeImageProcessorInvocation => {
+  if (
+    isObject(obj) &&
+    'type' in obj &&
+    obj.type === 'normalbae_image_processor'
+  ) {
+    return true;
+  }
+  return false;
+};
+
+/**
+ * Type guard for OpenposeImageProcessorInvocation
+ */
+export const isOpenposeImageProcessorInvocation = (
+  obj: unknown
+): obj is OpenposeImageProcessorInvocation => {
+  if (
+    isObject(obj) &&
+    'type' in obj &&
+    obj.type === 'openpose_image_processor'
+  ) {
+    return true;
+  }
+  return false;
+};
+
+/**
+ * Type guard for PidiImageProcessorInvocation
+ */
+export const isPidiImageProcessorInvocation = (
+  obj: unknown
+): obj is PidiImageProcessorInvocation => {
+  if (isObject(obj) && 'type' in obj && obj.type === 'pidi_image_processor') {
+    return true;
+  }
+  return false;
+};
+
+/**
+ * Type guard for ZoeDepthImageProcessorInvocation
+ */
+export const isZoeDepthImageProcessorInvocation = (
+  obj: unknown
+): obj is ZoeDepthImageProcessorInvocation => {
+  if (
+    isObject(obj) &&
+    'type' in obj &&
+    obj.type === 'zoe_depth_image_processor'
+  ) {
+    return true;
+  }
+  return false;
+};

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

@@ -1,4 +1,4 @@
-import { Flex, Icon } from '@chakra-ui/react';
+import { Box, Flex } from '@chakra-ui/react';
 import { createSelector } from '@reduxjs/toolkit';
 import { useAppSelector } from 'app/store/storeHooks';
 import { systemSelector } from 'features/system/store/systemSelectors';
@@ -7,7 +7,7 @@ import { isEqual } from 'lodash-es';
 import { gallerySelector } from '../store/gallerySelectors';
 import CurrentImageButtons from './CurrentImageButtons';
 import CurrentImagePreview from './CurrentImagePreview';
-import { FaImage } from 'react-icons/fa';
+import { defaultSelectorOptions } from 'app/store/util/defaultMemoizeOptions';
 
 export const currentImageDisplaySelector = createSelector(
   [systemSelector, gallerySelector],
@@ -15,21 +15,20 @@ export const currentImageDisplaySelector = createSelector(
     const { progressImage } = system;
 
     return {
-      hasAnImageToDisplay: gallery.selectedImage || progressImage,
+      hasSelectedImage: Boolean(gallery.selectedImage),
+      hasProgressImage: Boolean(progressImage),
     };
   },
-  {
-    memoizeOptions: {
-      resultEqualityCheck: isEqual,
-    },
-  }
+  defaultSelectorOptions
 );
 
 /**
  * Displays the current image if there is one, plus associated actions.
  */
 const CurrentImageDisplay = () => {
-  const { hasAnImageToDisplay } = useAppSelector(currentImageDisplaySelector);
+  const { hasSelectedImage, hasProgressImage } = useAppSelector(
+    currentImageDisplaySelector
+  );
 
   return (
     <Flex
@@ -54,21 +53,13 @@ const CurrentImageDisplay = () => {
           gap: 4,
         }}
       >
-        {hasAnImageToDisplay ? (
-          <>
-            <CurrentImageButtons />
         <CurrentImagePreview />
-          </>
-        ) : (
-          <Icon
-            as={FaImage}
-            sx={{
-              boxSize: 24,
-              color: 'base.500',
-            }}
-          />
-        )}
       </Flex>
+      {hasSelectedImage && (
+        <Box sx={{ position: 'absolute', top: 0 }}>
+          <CurrentImageButtons />
+        </Box>
+      )}
     </Flex>
   );
 };

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

@@ -1,20 +1,20 @@
 import { Box, Flex, Image } from '@chakra-ui/react';
 import { createSelector } from '@reduxjs/toolkit';
 import { useAppDispatch, useAppSelector } from 'app/store/storeHooks';
-import { useGetUrl } from 'common/util/getUrl';
 import { uiSelector } from 'features/ui/store/uiSelectors';
 import { isEqual } from 'lodash-es';
 
 import { gallerySelector } from '../store/gallerySelectors';
 import ImageMetadataViewer from './ImageMetaDataViewer/ImageMetadataViewer';
 import NextPrevImageButtons from './NextPrevImageButtons';
-import { DragEvent, memo, useCallback } from 'react';
+import { memo, useCallback } from 'react';
 import { systemSelector } from 'features/system/store/systemSelectors';
-import ImageFallbackSpinner from './ImageFallbackSpinner';
-import ImageMetadataOverlay from 'common/components/ImageMetadataOverlay';
 import { configSelector } from '../../system/store/configSelectors';
 import { useAppToaster } from 'app/components/Toaster';
 import { imageSelected } from '../store/gallerySlice';
+import IAIDndImage from 'common/components/IAIDndImage';
+import { ImageDTO } from 'services/api';
+import { IAIImageFallback } from 'common/components/IAIImageFallback';
 
 export const imagesSelector = createSelector(
   [uiSelector, gallerySelector, systemSelector],
@@ -46,27 +46,14 @@ const CurrentImagePreview = () => {
   const {
     shouldShowImageDetails,
     image,
-    shouldHidePreview,
     progressImage,
     shouldShowProgressInViewer,
     shouldAntialiasProgressImage,
   } = useAppSelector(imagesSelector);
   const { shouldFetchImages } = useAppSelector(configSelector);
-  const { getUrl } = useGetUrl();
   const toaster = useAppToaster();
   const dispatch = useAppDispatch();
 
-  const handleDragStart = useCallback(
-    (e: DragEvent<HTMLDivElement>) => {
-      if (!image) {
-        return;
-      }
-      e.dataTransfer.setData('invokeai/imageName', image.image_name);
-      e.dataTransfer.effectAllowed = 'move';
-    },
-    [image]
-  );
-
   const handleError = useCallback(() => {
     dispatch(imageSelected());
     if (shouldFetchImages) {
@@ -78,11 +65,21 @@ const CurrentImagePreview = () => {
     }
   }, [dispatch, toaster, shouldFetchImages]);
 
+  const handleDrop = useCallback(
+    (droppedImage: ImageDTO) => {
+      if (droppedImage.image_name === image?.image_name) {
+        return;
+      }
+      dispatch(imageSelected(droppedImage));
+    },
+    [dispatch, image?.image_name]
+  );
+
   return (
     <Flex
       sx={{
-        width: '100%',
-        height: '100%',
+        width: 'full',
+        height: 'full',
         position: 'relative',
         alignItems: 'center',
         justifyContent: 'center',
@@ -95,8 +92,8 @@ const CurrentImagePreview = () => {
           height={progressImage.height}
           sx={{
             objectFit: 'contain',
-            maxWidth: '100%',
-            maxHeight: '100%',
+            maxWidth: 'full',
+            maxHeight: 'full',
             height: 'auto',
             position: 'absolute',
             borderRadius: 'base',
@@ -104,34 +101,29 @@ const CurrentImagePreview = () => {
           }}
         />
       ) : (
-        image && (
-          <>
-            <Image
-              src={getUrl(image.image_url)}
-              fallbackStrategy="beforeLoadOrError"
-              fallback={<ImageFallbackSpinner />}
-              onDragStart={handleDragStart}
+        <Flex
           sx={{
-                objectFit: 'contain',
-                maxWidth: '100%',
-                maxHeight: '100%',
-                height: 'auto',
-                position: 'absolute',
-                borderRadius: 'base',
+            width: 'full',
+            height: 'full',
+            alignItems: 'center',
+            justifyContent: 'center',
           }}
+        >
+          <IAIDndImage
+            image={image}
+            onDrop={handleDrop}
             onError={handleError}
+            fallback={<IAIImageFallback sx={{ bg: 'none' }} />}
           />
-            <ImageMetadataOverlay image={image} />
-          </>
-        )
+        </Flex>
       )}
-      {shouldShowImageDetails && image && 'metadata' in image && (
+      {shouldShowImageDetails && image && image.metadata && (
         <Box
           sx={{
             position: 'absolute',
             top: '0',
-            width: '100%',
-            height: '100%',
+            width: 'full',
+            height: 'full',
             borderRadius: 'base',
             overflow: 'scroll',
           }}
@@ -139,7 +131,19 @@ const CurrentImagePreview = () => {
           <ImageMetadataViewer image={image} />
         </Box>
       )}
-      {!shouldShowImageDetails && <NextPrevImageButtons />}
+      {!shouldShowImageDetails && image && (
+        <Box
+          sx={{
+            position: 'absolute',
+            top: '0',
+            width: 'full',
+            height: 'full',
+            pointerEvents: 'none',
+          }}
+        >
+          <NextPrevImageButtons />
+        </Box>
+      )}
     </Flex>
   );
 };

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

@@ -39,6 +39,7 @@ import {
 } from '../store/actions';
 import { useAppToaster } from 'app/components/Toaster';
 import { ImageDTO } from 'services/api';
+import { useDraggable } from '@dnd-kit/core';
 
 export const selector = createSelector(
   [gallerySelector, systemSelector, lightboxSelector, activeTabNameSelector],
@@ -117,6 +118,13 @@ const HoverableImage = memo((props: HoverableImageProps) => {
   const { recallBothPrompts, recallSeed, recallAllParameters } =
     useRecallParameters();
 
+  const { attributes, listeners, setNodeRef } = useDraggable({
+    id: `galleryImage_${image_name}`,
+    data: {
+      image,
+    },
+  });
+
   const handleMouseOver = () => setIsHovered(true);
   const handleMouseOut = () => setIsHovered(false);
 
@@ -144,14 +152,6 @@ const HoverableImage = memo((props: HoverableImageProps) => {
     dispatch(imageSelected(image));
   }, [image, dispatch]);
 
-  const handleDragStart = useCallback(
-    (e: DragEvent<HTMLDivElement>) => {
-      e.dataTransfer.setData('invokeai/imageName', image.image_name);
-      e.dataTransfer.effectAllowed = 'move';
-    },
-    [image]
-  );
-
   // Recall parameters handlers
   const handleRecallPrompt = useCallback(() => {
     recallBothPrompts(
@@ -212,7 +212,12 @@ const HoverableImage = memo((props: HoverableImageProps) => {
   };
 
   return (
-    <>
+    <Box
+      ref={setNodeRef}
+      {...listeners}
+      {...attributes}
+      sx={{ w: 'full', h: 'full', touchAction: 'none' }}
+    >
       <ContextMenu<HTMLDivElement>
         menuProps={{ size: 'sm', isLazy: true }}
         renderMenu={() => (
@@ -291,8 +296,8 @@ const HoverableImage = memo((props: HoverableImageProps) => {
             onMouseOver={handleMouseOver}
             onMouseOut={handleMouseOut}
             userSelect="none"
-            draggable={true}
-            onDragStart={handleDragStart}
+            // draggable={true}
+            // onDragStart={handleDragStart}
             onClick={handleSelectImage}
             ref={ref}
             sx={{
@@ -373,7 +378,7 @@ const HoverableImage = memo((props: HoverableImageProps) => {
         onClose={onDeleteDialogClose}
         handleDelete={handleDelete}
       />
-    </>
+    </Box>
   );
 }, memoEqualityCheck);
 

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

@@ -14,6 +14,8 @@ const ImageFallbackSpinner = (props: ImageFallbackSpinnerProps) => {
         justifyContent: 'center',
         position: 'absolute',
         color: 'base.400',
+        minH: 36,
+        minW: 36,
       }}
     >
       <Spinner size={size} {...rest} />

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

@@ -10,7 +10,7 @@ import {
 } from '@chakra-ui/react';
 import { useAppDispatch, useAppSelector } from 'app/store/storeHooks';
 import IAIButton from 'common/components/IAIButton';
-import IAICheckbox from 'common/components/IAICheckbox';
+import IAISimpleCheckbox from 'common/components/IAISimpleCheckbox';
 import IAIIconButton from 'common/components/IAIIconButton';
 import IAIPopover from 'common/components/IAIPopover';
 import IAISlider from 'common/components/IAISlider';
@@ -233,7 +233,7 @@ const ImageGalleryContent = () => {
                 withReset
                 handleReset={() => dispatch(setGalleryImageMinimumWidth(64))}
               />
-              <IAICheckbox
+              <IAISimpleCheckbox
                 label={t('gallery.maintainAspectRatio')}
                 isChecked={galleryImageObjectFit === 'contain'}
                 onChange={() =>
@@ -244,14 +244,14 @@ const ImageGalleryContent = () => {
                   )
                 }
               />
-              <IAICheckbox
+              <IAISimpleCheckbox
                 label={t('gallery.autoSwitchNewImages')}
                 isChecked={shouldAutoSwitchToNewImages}
                 onChange={(e: ChangeEvent<HTMLInputElement>) =>
                   dispatch(setShouldAutoSwitchToNewImages(e.target.checked))
                 }
               />
-              <IAICheckbox
+              <IAISimpleCheckbox
                 label={t('gallery.singleColumnLayout')}
                 isChecked={shouldUseSingleGalleryColumn}
                 onChange={(e: ChangeEvent<HTMLInputElement>) =>

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

@@ -50,7 +50,10 @@ export const gallerySlice = createSlice({
   },
   extraReducers: (builder) => {
     builder.addCase(imageUpserted, (state, action) => {
-      if (state.shouldAutoSwitchToNewImages) {
+      if (
+        state.shouldAutoSwitchToNewImages &&
+        action.payload.image_category === 'general'
+      ) {
         state.selectedImage = action.payload;
       }
     });

invokeai/frontend/web/src/features/nodes/components/fields/ImageInputFieldComponent.tsx

@@ -1,54 +1,67 @@
-import { Box, Image } from '@chakra-ui/react';
 import { useAppDispatch } from 'app/store/storeHooks';
-import SelectImagePlaceholder from 'common/components/SelectImagePlaceholder';
-import { useGetUrl } from 'common/util/getUrl';
-import useGetImageByName from 'features/gallery/hooks/useGetImageByName';
 
 import { fieldValueChanged } from 'features/nodes/store/nodesSlice';
 import {
   ImageInputFieldTemplate,
   ImageInputFieldValue,
 } from 'features/nodes/types/types';
-import { DragEvent, memo, useCallback, useState } from 'react';
+import { memo, useCallback } from 'react';
 
 import { FieldComponentProps } from './types';
+import IAIDndImage from 'common/components/IAIDndImage';
+import { ImageDTO } from 'services/api';
+import { Flex } from '@chakra-ui/react';
 
 const ImageInputFieldComponent = (
   props: FieldComponentProps<ImageInputFieldValue, ImageInputFieldTemplate>
 ) => {
   const { nodeId, field } = props;
 
-  const getImageByName = useGetImageByName();
   const dispatch = useAppDispatch();
-  const [url, setUrl] = useState<string | undefined>(field.value?.image_url);
-  const { getUrl } = useGetUrl();
 
   const handleDrop = useCallback(
-    (e: DragEvent<HTMLDivElement>) => {
-      const name = e.dataTransfer.getData('invokeai/imageName');
-      const image = getImageByName(name);
-
-      if (!image) {
+    (droppedImage: ImageDTO) => {
+      if (field.value?.image_name === droppedImage.image_name) {
         return;
       }
 
-      setUrl(image.image_url);
-
       dispatch(
         fieldValueChanged({
           nodeId,
           fieldName: field.name,
-          value: image,
+          value: droppedImage,
         })
       );
     },
-    [getImageByName, dispatch, field.name, nodeId]
+    [dispatch, field.name, field.value?.image_name, nodeId]
   );
 
+  const handleReset = useCallback(() => {
+    dispatch(
+      fieldValueChanged({
+        nodeId,
+        fieldName: field.name,
+        value: undefined,
+      })
+    );
+  }, [dispatch, field.name, nodeId]);
+
   return (
-    <Box onDrop={handleDrop}>
-      <Image src={getUrl(url)} fallback={<SelectImagePlaceholder />} />
-    </Box>
+    <Flex
+      sx={{
+        w: 'full',
+        h: 'full',
+        alignItems: 'center',
+        justifyContent: 'center',
+      }}
+    >
+      <IAIDndImage
+        image={field.value}
+        onDrop={handleDrop}
+        onReset={handleReset}
+        resetIconSize="sm"
+      />
+    </Flex>
   );
 };
 

invokeai/frontend/web/src/features/nodes/components/ui/NodeInvokeButton.tsx

@@ -1,11 +1,11 @@
 import { Box } from '@chakra-ui/react';
-import { readinessSelector } from 'app/selectors/readinessSelector';
 import { userInvoked } from 'app/store/actions';
 import { useAppDispatch, useAppSelector } from 'app/store/storeHooks';
 import IAIButton, { IAIButtonProps } from 'common/components/IAIButton';
 import IAIIconButton, {
   IAIIconButtonProps,
 } from 'common/components/IAIIconButton';
+import { useIsReadyToInvoke } from 'common/hooks/useIsReadyToInvoke';
 import ProgressBar from 'features/system/components/ProgressBar';
 import { activeTabNameSelector } from 'features/ui/store/uiSelectors';
 import { useCallback } from 'react';
@@ -21,9 +21,8 @@ interface InvokeButton
 export default function NodeInvokeButton(props: InvokeButton) {
   const { iconButton = false, ...rest } = props;
   const dispatch = useAppDispatch();
-  const { isReady } = useAppSelector(readinessSelector);
   const activeTabName = useAppSelector(activeTabNameSelector);
-
+  const isReady = useIsReadyToInvoke();
   const handleInvoke = useCallback(() => {
     dispatch(userInvoked('nodes'));
   }, [dispatch]);

invokeai/frontend/web/src/features/nodes/util/addControlNetToLinearGraph.ts

@@ -0,0 +1,99 @@
+import { RootState } from 'app/store/store';
+import { forEach, size } from 'lodash-es';
+import { CollectInvocation, ControlNetInvocation } from 'services/api';
+import { NonNullableGraph } from '../types/types';
+
+const CONTROL_NET_COLLECT = 'control_net_collect';
+
+export const addControlNetToLinearGraph = (
+  graph: NonNullableGraph,
+  baseNodeId: string,
+  state: RootState
+): void => {
+  const { isEnabled: isControlNetEnabled, controlNets } = state.controlNet;
+
+  // Add ControlNet
+  if (isControlNetEnabled) {
+    if (size(controlNets) > 1) {
+      const controlNetIterateNode: CollectInvocation = {
+        id: CONTROL_NET_COLLECT,
+        type: 'collect',
+      };
+      graph.nodes[controlNetIterateNode.id] = controlNetIterateNode;
+      graph.edges.push({
+        source: { node_id: controlNetIterateNode.id, field: 'collection' },
+        destination: {
+          node_id: baseNodeId,
+          field: 'control',
+        },
+      });
+    }
+
+    forEach(controlNets, (controlNet, index) => {
+      const {
+        controlNetId,
+        isEnabled,
+        controlImage,
+        processedControlImage,
+        beginStepPct,
+        endStepPct,
+        model,
+        processorType,
+        weight,
+      } = controlNet;
+
+      if (!isEnabled) {
+        // Skip disabled ControlNets
+        return;
+      }
+
+      const controlNetNode: ControlNetInvocation = {
+        id: `control_net_${controlNetId}`,
+        type: 'controlnet',
+        begin_step_percent: beginStepPct,
+        end_step_percent: endStepPct,
+        control_model: model as ControlNetInvocation['control_model'],
+        control_weight: weight,
+      };
+
+      if (processedControlImage && processorType !== 'none') {
+        // We've already processed the image in the app, so we can just use the processed image
+        const { image_name, image_origin } = processedControlImage;
+        controlNetNode.image = {
+          image_name,
+          image_origin,
+        };
+      } else if (controlImage && processorType !== 'none') {
+        // The control image is preprocessed
+        const { image_name, image_origin } = controlImage;
+        controlNetNode.image = {
+          image_name,
+          image_origin,
+        };
+      } else {
+        // Skip ControlNets without an unprocessed image - should never happen if everything is working correctly
+        return;
+      }
+
+      graph.nodes[controlNetNode.id] = controlNetNode;
+
+      if (size(controlNets) > 1) {
+        graph.edges.push({
+          source: { node_id: controlNetNode.id, field: 'control' },
+          destination: {
+            node_id: CONTROL_NET_COLLECT,
+            field: 'item',
+          },
+        });
+      } else {
+        graph.edges.push({
+          source: { node_id: controlNetNode.id, field: 'control' },
+          destination: {
+            node_id: baseNodeId,
+            field: 'control',
+          },
+        });
+      }
+    });
+  }
+};

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

@@ -14,6 +14,7 @@ import {
 import { NonNullableGraph } from 'features/nodes/types/types';
 import { log } from 'app/logging/useLogger';
 import { set } from 'lodash-es';
+import { addControlNetToLinearGraph } from '../addControlNetToLinearGraph';
 
 const moduleLog = log.child({ namespace: 'nodes' });
 
@@ -408,5 +409,7 @@ export const buildImageToImageGraph = (state: RootState): Graph => {
     });
   }
 
+  addControlNetToLinearGraph(graph, LATENTS_TO_LATENTS, state);
+
   return graph;
 };

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

@@ -10,6 +10,7 @@ import {
   TextToLatentsInvocation,
 } from 'services/api';
 import { NonNullableGraph } from 'features/nodes/types/types';
+import { addControlNetToLinearGraph } from '../addControlNetToLinearGraph';
 
 const POSITIVE_CONDITIONING = 'positive_conditioning';
 const NEGATIVE_CONDITIONING = 'negative_conditioning';
@@ -308,5 +309,8 @@ export const buildTextToImageGraph = (state: RootState): Graph => {
       },
     });
   }
+
+  addControlNetToLinearGraph(graph, TEXT_TO_LATENTS, state);
+
   return graph;
 };

invokeai/frontend/web/src/features/parameters/components/Parameters/ControlNet/ParamControlNetCollapse.tsx

@@ -0,0 +1,69 @@
+import { Divider, Flex } from '@chakra-ui/react';
+import { useTranslation } from 'react-i18next';
+import IAICollapse from 'common/components/IAICollapse';
+import { Fragment, memo, useCallback } from 'react';
+import { useAppDispatch, useAppSelector } from 'app/store/storeHooks';
+import { createSelector } from '@reduxjs/toolkit';
+import {
+  controlNetAdded,
+  controlNetSelector,
+  isControlNetEnabledToggled,
+} from 'features/controlNet/store/controlNetSlice';
+import { defaultSelectorOptions } from 'app/store/util/defaultMemoizeOptions';
+import { map } from 'lodash-es';
+import { v4 as uuidv4 } from 'uuid';
+import { useFeatureStatus } from 'features/system/hooks/useFeatureStatus';
+import IAIButton from 'common/components/IAIButton';
+import ControlNet from 'features/controlNet/components/ControlNet';
+
+const selector = createSelector(
+  controlNetSelector,
+  (controlNet) => {
+    const { controlNets, isEnabled } = controlNet;
+
+    return { controlNetsArray: map(controlNets), isEnabled };
+  },
+  defaultSelectorOptions
+);
+
+const ParamControlNetCollapse = () => {
+  const { t } = useTranslation();
+  const { controlNetsArray, isEnabled } = useAppSelector(selector);
+  const isControlNetDisabled = useFeatureStatus('controlNet').isFeatureDisabled;
+  const dispatch = useAppDispatch();
+
+  const handleClickControlNetToggle = useCallback(() => {
+    dispatch(isControlNetEnabledToggled());
+  }, [dispatch]);
+
+  const handleClickedAddControlNet = useCallback(() => {
+    dispatch(controlNetAdded({ controlNetId: uuidv4() }));
+  }, [dispatch]);
+
+  if (isControlNetDisabled) {
+    return null;
+  }
+
+  return (
+    <IAICollapse
+      label={'ControlNet'}
+      isOpen={isEnabled}
+      onToggle={handleClickControlNetToggle}
+      withSwitch
+    >
+      <Flex sx={{ flexDir: 'column', gap: 3 }}>
+        {controlNetsArray.map((c, i) => (
+          <Fragment key={c.controlNetId}>
+            {i > 0 && <Divider />}
+            <ControlNet controlNet={c} />
+          </Fragment>
+        ))}
+        <IAIButton flexGrow={1} onClick={handleClickedAddControlNet}>
+          Add ControlNet
+        </IAIButton>
+      </Flex>
+    </IAICollapse>
+  );
+};
+
+export default memo(ParamControlNetCollapse);

invokeai/frontend/web/src/features/parameters/components/Parameters/Core/ParamPositiveConditioning.tsx

@@ -4,7 +4,6 @@ import { useAppDispatch, useAppSelector } from 'app/store/storeHooks';
 import { ChangeEvent, KeyboardEvent, useCallback, useRef } from 'react';
 
 import { createSelector } from '@reduxjs/toolkit';
-import { readinessSelector } from 'app/selectors/readinessSelector';
 import {
   GenerationState,
   clampSymmetrySteps,
@@ -17,6 +16,7 @@ import { useHotkeys } from 'react-hotkeys-hook';
 import { useTranslation } from 'react-i18next';
 import { userInvoked } from 'app/store/actions';
 import IAITextarea from 'common/components/IAITextarea';
+import { useIsReadyToInvoke } from 'common/hooks/useIsReadyToInvoke';
 
 const promptInputSelector = createSelector(
   [(state: RootState) => state.generation, activeTabNameSelector],
@@ -39,7 +39,7 @@ const promptInputSelector = createSelector(
 const ParamPositiveConditioning = () => {
   const dispatch = useAppDispatch();
   const { prompt, activeTabName } = useAppSelector(promptInputSelector);
-  const { isReady } = useAppSelector(readinessSelector);
+  const isReady = useIsReadyToInvoke();
 
   const promptRef = useRef<HTMLTextAreaElement>(null);
 

invokeai/frontend/web/src/features/parameters/components/Parameters/ImageToImage/InitialImageDisplay.tsx

@@ -1,6 +1,5 @@
 import { Flex } from '@chakra-ui/react';
 import InitialImagePreview from './InitialImagePreview';
-import InitialImageButtons from 'common/components/InitialImageButtons';
 
 const InitialImageDisplay = () => {
   return (
@@ -28,7 +27,6 @@ const InitialImageDisplay = () => {
           gap: 4,
         }}
       >
-        <InitialImageButtons />
         <InitialImagePreview />
       </Flex>
     </Flex>

invokeai/frontend/web/src/features/parameters/components/Parameters/ImageToImage/InitialImagePreview.tsx

@@ -1,18 +1,20 @@
-import { Flex, Icon, Image } from '@chakra-ui/react';
+import { Flex } from '@chakra-ui/react';
 import { createSelector } from '@reduxjs/toolkit';
 import { useAppDispatch, useAppSelector } from 'app/store/storeHooks';
 import { useGetUrl } from 'common/util/getUrl';
-import { clearInitialImage } from 'features/parameters/store/generationSlice';
-import { DragEvent, useCallback } from 'react';
+import {
+  clearInitialImage,
+  initialImageChanged,
+} from 'features/parameters/store/generationSlice';
+import { useCallback } from 'react';
 import { useTranslation } from 'react-i18next';
-import ImageMetadataOverlay from 'common/components/ImageMetadataOverlay';
 import { generationSelector } from 'features/parameters/store/generationSelectors';
-import { initialImageSelected } from 'features/parameters/store/actions';
 import { defaultSelectorOptions } from 'app/store/util/defaultMemoizeOptions';
-import ImageFallbackSpinner from 'features/gallery/components/ImageFallbackSpinner';
-import { FaImage } from 'react-icons/fa';
 import { configSelector } from '../../../../system/store/configSelectors';
 import { useAppToaster } from 'app/components/Toaster';
+import IAIDndImage from 'common/components/IAIDndImage';
+import { ImageDTO } from 'services/api';
+import { IAIImageFallback } from 'common/components/IAIImageFallback';
 
 const selector = createSelector(
   [generationSelector],
@@ -52,13 +54,19 @@ const InitialImagePreview = () => {
   }, [dispatch, t, toaster, shouldFetchImages]);
 
   const handleDrop = useCallback(
-    (e: DragEvent<HTMLDivElement>) => {
-      const name = e.dataTransfer.getData('invokeai/imageName');
-      dispatch(initialImageSelected(name));
+    (droppedImage: ImageDTO) => {
+      if (droppedImage.image_name === initialImage?.image_name) {
+        return;
+      }
+      dispatch(initialImageChanged(droppedImage));
     },
-    [dispatch]
+    [dispatch, initialImage?.image_name]
   );
 
+  const handleReset = useCallback(() => {
+    dispatch(clearInitialImage());
+  }, [dispatch]);
+
   return (
     <Flex
       sx={{
@@ -68,36 +76,13 @@ const InitialImagePreview = () => {
         alignItems: 'center',
         justifyContent: 'center',
       }}
-      onDrop={handleDrop}
     >
-      {initialImage?.image_url && (
-        <>
-          <Image
-            src={getUrl(initialImage?.image_url)}
-            fallbackStrategy="beforeLoadOrError"
-            fallback={<ImageFallbackSpinner />}
-            onError={handleError}
-            sx={{
-              objectFit: 'contain',
-              maxWidth: '100%',
-              maxHeight: '100%',
-              height: 'auto',
-              position: 'absolute',
-              borderRadius: 'base',
-            }}
+      <IAIDndImage
+        image={initialImage}
+        onDrop={handleDrop}
+        onReset={handleReset}
+        fallback={<IAIImageFallback sx={{ bg: 'none' }} />}
       />
-          <ImageMetadataOverlay image={initialImage} />
-        </>
-      )}
-      {!initialImage?.image_url && (
-        <Icon
-          as={FaImage}
-          sx={{
-            boxSize: 24,
-            color: 'base.500',
-          }}
-        />
-      )}
     </Flex>
   );
 };

invokeai/frontend/web/src/features/parameters/components/Parameters/Seed/ParamSeedFull.tsx

@@ -0,0 +1,17 @@
+import { Flex } from '@chakra-ui/react';
+import { memo } from 'react';
+import ParamSeed from './ParamSeed';
+import ParamSeedShuffle from './ParamSeedShuffle';
+import ParamSeedRandomize from './ParamSeedRandomize';
+
+const ParamSeedFull = () => {
+  return (
+    <Flex sx={{ gap: 4, alignItems: 'center' }}>
+      <ParamSeed />
+      <ParamSeedShuffle />
+      <ParamSeedRandomize />
+    </Flex>
+  );
+};
+
+export default memo(ParamSeedFull);

invokeai/frontend/web/src/features/parameters/components/Parameters/Seed/ParamSeedRandomize.tsx

@@ -2,30 +2,10 @@ import { ChangeEvent, memo } from 'react';
 
 import { RootState } from 'app/store/store';
 import { useAppDispatch, useAppSelector } from 'app/store/storeHooks';
-import IAISwitch from 'common/components/IAISwitch';
 import { setShouldRandomizeSeed } from 'features/parameters/store/generationSlice';
 import { useTranslation } from 'react-i18next';
-import { FormControl, FormLabel, Switch } from '@chakra-ui/react';
-
-// export default function RandomizeSeed() {
-//   const dispatch = useAppDispatch();
-//   const { t } = useTranslation();
-
-//   const shouldRandomizeSeed = useAppSelector(
-//     (state: RootState) => state.generation.shouldRandomizeSeed
-//   );
-
-//   const handleChangeShouldRandomizeSeed = (e: ChangeEvent<HTMLInputElement>) =>
-//     dispatch(setShouldRandomizeSeed(e.target.checked));
-
-//   return (
-//     <Switch
-//       aria-label={t('parameters.randomizeSeed')}
-//       isChecked={shouldRandomizeSeed}
-//       onChange={handleChangeShouldRandomizeSeed}
-//     />
-//   );
-// }
+import { FormControl, FormLabel, Switch, Tooltip } from '@chakra-ui/react';
+import IAISwitch from 'common/components/IAISwitch';
 
 const ParamSeedRandomize = () => {
   const dispatch = useAppDispatch();
@@ -38,6 +18,14 @@ const ParamSeedRandomize = () => {
   const handleChangeShouldRandomizeSeed = (e: ChangeEvent<HTMLInputElement>) =>
     dispatch(setShouldRandomizeSeed(e.target.checked));
 
+  return (
+    <IAISwitch
+      label={t('common.random')}
+      isChecked={shouldRandomizeSeed}
+      onChange={handleChangeShouldRandomizeSeed}
+    />
+  );
+
   return (
     <FormControl
       sx={{

invokeai/frontend/web/src/features/parameters/components/Parameters/Seed/ParamSeedShuffle.tsx

@@ -3,9 +3,11 @@ import { NUMPY_RAND_MAX, NUMPY_RAND_MIN } from 'app/constants';
 import { RootState } from 'app/store/store';
 import { useAppDispatch, useAppSelector } from 'app/store/storeHooks';
 import IAIButton from 'common/components/IAIButton';
+import IAIIconButton from 'common/components/IAIIconButton';
 import randomInt from 'common/util/randomInt';
 import { setSeed } from 'features/parameters/store/generationSlice';
 import { useTranslation } from 'react-i18next';
+import { FaRandom } from 'react-icons/fa';
 
 export default function ParamSeedShuffle() {
   const dispatch = useAppDispatch();
@@ -17,6 +19,17 @@ export default function ParamSeedShuffle() {
   const handleClickRandomizeSeed = () =>
     dispatch(setSeed(randomInt(NUMPY_RAND_MIN, NUMPY_RAND_MAX)));
 
+  return (
+    <IAIIconButton
+      size="sm"
+      isDisabled={shouldRandomizeSeed}
+      aria-label={t('parameters.shuffle')}
+      tooltip={t('parameters.shuffle')}
+      onClick={handleClickRandomizeSeed}
+      icon={<FaRandom />}
+    />
+  );
+
   return (
     <IAIButton
       size="sm"

invokeai/frontend/web/src/features/parameters/components/ProcessButtons/InvokeButton.tsx

@@ -1,11 +1,11 @@
 import { Box } from '@chakra-ui/react';
-import { readinessSelector } from 'app/selectors/readinessSelector';
 import { userInvoked } from 'app/store/actions';
 import { useAppDispatch, useAppSelector } from 'app/store/storeHooks';
 import IAIButton, { IAIButtonProps } from 'common/components/IAIButton';
 import IAIIconButton, {
   IAIIconButtonProps,
 } from 'common/components/IAIIconButton';
+import { useIsReadyToInvoke } from 'common/hooks/useIsReadyToInvoke';
 import { clampSymmetrySteps } from 'features/parameters/store/generationSlice';
 import ProgressBar from 'features/system/components/ProgressBar';
 import { activeTabNameSelector } from 'features/ui/store/uiSelectors';
@@ -22,7 +22,7 @@ interface InvokeButton
 export default function InvokeButton(props: InvokeButton) {
   const { iconButton = false, ...rest } = props;
   const dispatch = useAppDispatch();
-  const { isReady } = useAppSelector(readinessSelector);
+  const isReady = useIsReadyToInvoke();
   const activeTabName = useAppSelector(activeTabNameSelector);
 
   const handleInvoke = useCallback(() => {

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

@@ -7,25 +7,6 @@ export type ImageNameAndOrigin = {
   image_origin: ResourceOrigin;
 };
 
-export const isImageDTO = (image: any): image is ImageDTO => {
-  return (
-    image &&
-    isObject(image) &&
-    'image_name' in image &&
-    image?.image_name !== undefined &&
-    'image_origin' in image &&
-    image?.image_origin !== undefined &&
-    'image_url' in image &&
-    image?.image_url !== undefined &&
-    'thumbnail_url' in image &&
-    image?.thumbnail_url !== undefined &&
-    'image_category' in image &&
-    image?.image_category !== undefined &&
-    'created_at' in image &&
-    image?.created_at !== undefined
-  );
-};
-
 export const initialImageSelected = createAction<ImageDTO | string | undefined>(
   'generation/initialImageSelected'
 );

invokeai/frontend/web/src/features/system/components/ModelManager/AddCheckpointModel.tsx

@@ -10,7 +10,7 @@ import {
 } from '@chakra-ui/react';
 
 import IAIButton from 'common/components/IAIButton';
-import IAICheckbox from 'common/components/IAICheckbox';
+import IAISimpleCheckbox from 'common/components/IAISimpleCheckbox';
 import IAIInput from 'common/components/IAIInput';
 import IAINumberInput from 'common/components/IAINumberInput';
 import React from 'react';
@@ -74,12 +74,12 @@ export default function AddCheckpointModel() {
   return (
     <VStack gap={2} alignItems="flex-start">
       <Flex columnGap={4}>
-        <IAICheckbox
+        <IAISimpleCheckbox
           isChecked={!addManually}
           label={t('modelManager.scanForModels')}
           onChange={() => setAddmanually(!addManually)}
         />
-        <IAICheckbox
+        <IAISimpleCheckbox
           label={t('modelManager.addManually')}
           isChecked={addManually}
           onChange={() => setAddmanually(!addManually)}

invokeai/frontend/web/src/features/system/components/ModelManager/MergeModels.tsx

@@ -24,7 +24,7 @@ import { useState } from 'react';
 import { useTranslation } from 'react-i18next';
 import * as InvokeAI from 'app/types/invokeai';
 import IAISlider from 'common/components/IAISlider';
-import IAICheckbox from 'common/components/IAICheckbox';
+import IAISimpleCheckbox from 'common/components/IAISimpleCheckbox';
 
 export default function MergeModels() {
   const dispatch = useAppDispatch();
@@ -286,7 +286,7 @@ export default function MergeModels() {
                 )}
               </Flex>
 
-              <IAICheckbox
+              <IAISimpleCheckbox
                 label={t('modelManager.ignoreMismatch')}
                 isChecked={modelMergeForce}
                 onChange={(e) => setModelMergeForce(e.target.checked)}

invokeai/frontend/web/src/features/system/components/ModelManager/SearchModels.tsx

@@ -1,5 +1,5 @@
 import IAIButton from 'common/components/IAIButton';
-import IAICheckbox from 'common/components/IAICheckbox';
+import IAISimpleCheckbox from 'common/components/IAISimpleCheckbox';
 import IAIIconButton from 'common/components/IAIIconButton';
 import React from 'react';
 
@@ -81,13 +81,13 @@ function SearchModelEntry({
       borderRadius={4}
     >
       <Flex gap={4} alignItems="center" justifyContent="space-between">
-        <IAICheckbox
+        <IAISimpleCheckbox
           value={model.name}
           label={<Text fontWeight={500}>{model.name}</Text>}
           isChecked={modelsToAdd.includes(model.name)}
           isDisabled={existingModels.includes(model.location)}
           onChange={foundModelsChangeHandler}
-        ></IAICheckbox>
+        ></IAISimpleCheckbox>
         {existingModels.includes(model.location) && (
           <Badge colorScheme="accent">{t('modelManager.modelExists')}</Badge>
         )}
@@ -324,7 +324,7 @@ export default function SearchModels() {
               >
                 {t('modelManager.deselectAll')}
               </IAIButton>
-              <IAICheckbox
+              <IAISimpleCheckbox
                 label={t('modelManager.showExisting')}
                 isChecked={shouldShowExistingModelsInSearch}
                 onChange={() =>

invokeai/frontend/web/src/features/system/hooks/useIsApplicationReady.ts

@@ -19,6 +19,9 @@ const isApplicationReadySelector = createSelector(
   }
 );
 
+/**
+ * Checks if the application is ready to be used, i.e. if the initial startup process is finished.
+ */
 export const useIsApplicationReady = () => {
   const { disabledTabs, wereModelsReceived, wasSchemaParsed } = useAppSelector(
     isApplicationReadySelector

invokeai/frontend/web/src/features/ui/components/tabs/ImageToImage/ImageToImageTabCoreParameters.tsx

@@ -1,5 +1,5 @@
 import { memo } from 'react';
-import { Flex } from '@chakra-ui/react';
+import { Box, Flex, useDisclosure } from '@chakra-ui/react';
 import { createSelector } from '@reduxjs/toolkit';
 import { uiSelector } from 'features/ui/store/uiSelectors';
 import { useAppSelector } from 'app/store/storeHooks';
@@ -13,6 +13,8 @@ import ImageToImageStrength from 'features/parameters/components/Parameters/Imag
 import ImageToImageFit from 'features/parameters/components/Parameters/ImageToImage/ImageToImageFit';
 import { generationSelector } from 'features/parameters/store/generationSelectors';
 import ParamSchedulerAndModel from 'features/parameters/components/Parameters/Core/ParamSchedulerAndModel';
+import ParamSeedFull from 'features/parameters/components/Parameters/Seed/ParamSeedFull';
+import IAICollapse from 'common/components/IAICollapse';
 
 const selector = createSelector(
   [uiSelector, generationSelector],
@@ -27,43 +29,47 @@ const selector = createSelector(
 
 const ImageToImageTabCoreParameters = () => {
   const { shouldUseSliders, shouldFitToWidthHeight } = useAppSelector(selector);
+  const { isOpen, onToggle } = useDisclosure({ defaultIsOpen: true });
 
   return (
+    <IAICollapse label={'General'} isOpen={isOpen} onToggle={onToggle}>
       <Flex
         sx={{
           flexDirection: 'column',
-        gap: 2,
-        bg: 'base.800',
-        p: 4,
-        borderRadius: 'base',
+          gap: 3,
         }}
       >
         {shouldUseSliders ? (
-        <Flex sx={{ gap: 3, flexDirection: 'column' }}>
+          <>
+            <ParamSchedulerAndModel />
+            <Box pt={2}>
+              <ParamSeedFull />
+            </Box>
             <ParamIterations />
             <ParamSteps />
             <ParamCFGScale />
             <ParamWidth isDisabled={!shouldFitToWidthHeight} />
             <ParamHeight isDisabled={!shouldFitToWidthHeight} />
-          <ImageToImageStrength />
-          <ImageToImageFit />
-          <ParamSchedulerAndModel />
-        </Flex>
+          </>
         ) : (
-        <Flex sx={{ gap: 2, flexDirection: 'column' }}>
+          <>
             <Flex gap={3}>
               <ParamIterations />
               <ParamSteps />
               <ParamCFGScale />
             </Flex>
             <ParamSchedulerAndModel />
+            <Box pt={2}>
+              <ParamSeedFull />
+            </Box>
             <ParamWidth isDisabled={!shouldFitToWidthHeight} />
             <ParamHeight isDisabled={!shouldFitToWidthHeight} />
+          </>
+        )}
         <ImageToImageStrength />
         <ImageToImageFit />
       </Flex>
-      )}
-    </Flex>
+    </IAICollapse>
   );
 };
 

invokeai/frontend/web/src/features/ui/components/tabs/ImageToImage/ImageToImageTabParameters.tsx

@@ -2,12 +2,12 @@ import { memo } from 'react';
 import ProcessButtons from 'features/parameters/components/ProcessButtons/ProcessButtons';
 import ParamPositiveConditioning from 'features/parameters/components/Parameters/Core/ParamPositiveConditioning';
 import ParamNegativeConditioning from 'features/parameters/components/Parameters/Core/ParamNegativeConditioning';
-import ParamSeedCollapse from 'features/parameters/components/Parameters/Seed/ParamSeedCollapse';
 import ParamVariationCollapse from 'features/parameters/components/Parameters/Variations/ParamVariationCollapse';
 import ParamNoiseCollapse from 'features/parameters/components/Parameters/Noise/ParamNoiseCollapse';
 import ParamSymmetryCollapse from 'features/parameters/components/Parameters/Symmetry/ParamSymmetryCollapse';
 import ParamSeamlessCollapse from 'features/parameters/components/Parameters/Seamless/ParamSeamlessCollapse';
 import ImageToImageTabCoreParameters from './ImageToImageTabCoreParameters';
+import ParamControlNetCollapse from 'features/parameters/components/Parameters/ControlNet/ParamControlNetCollapse';
 
 const ImageToImageTabParameters = () => {
   return (
@@ -16,7 +16,7 @@ const ImageToImageTabParameters = () => {
       <ParamNegativeConditioning />
       <ProcessButtons />
       <ImageToImageTabCoreParameters />
-      <ParamSeedCollapse />
+      <ParamControlNetCollapse />
       <ParamVariationCollapse />
       <ParamNoiseCollapse />
       <ParamSymmetryCollapse />

invokeai/frontend/web/src/features/ui/components/tabs/TextToImage/TextToImageTabCoreParameters.tsx

@@ -3,13 +3,15 @@ import ParamSteps from 'features/parameters/components/Parameters/Core/ParamStep
 import ParamCFGScale from 'features/parameters/components/Parameters/Core/ParamCFGScale';
 import ParamWidth from 'features/parameters/components/Parameters/Core/ParamWidth';
 import ParamHeight from 'features/parameters/components/Parameters/Core/ParamHeight';
-import { Flex } from '@chakra-ui/react';
+import { Box, Flex, useDisclosure } from '@chakra-ui/react';
 import { useAppSelector } from 'app/store/storeHooks';
 import { createSelector } from '@reduxjs/toolkit';
 import { uiSelector } from 'features/ui/store/uiSelectors';
 import { defaultSelectorOptions } from 'app/store/util/defaultMemoizeOptions';
 import { memo } from 'react';
 import ParamSchedulerAndModel from 'features/parameters/components/Parameters/Core/ParamSchedulerAndModel';
+import IAICollapse from 'common/components/IAICollapse';
+import ParamSeedFull from 'features/parameters/components/Parameters/Seed/ParamSeedFull';
 
 const selector = createSelector(
   uiSelector,
@@ -23,39 +25,45 @@ const selector = createSelector(
 
 const TextToImageTabCoreParameters = () => {
   const { shouldUseSliders } = useAppSelector(selector);
+  const { isOpen, onToggle } = useDisclosure({ defaultIsOpen: true });
 
   return (
+    <IAICollapse label={'General'} isOpen={isOpen} onToggle={onToggle}>
       <Flex
         sx={{
           flexDirection: 'column',
-        gap: 2,
-        bg: 'base.800',
-        p: 4,
-        borderRadius: 'base',
+          gap: 3,
         }}
       >
         {shouldUseSliders ? (
-        <Flex sx={{ gap: 3, flexDirection: 'column' }}>
+          <>
+            <ParamSchedulerAndModel />
+            <Box pt={2}>
+              <ParamSeedFull />
+            </Box>
             <ParamIterations />
             <ParamSteps />
             <ParamCFGScale />
             <ParamWidth />
             <ParamHeight />
-          <ParamSchedulerAndModel />
-        </Flex>
+          </>
         ) : (
-        <Flex sx={{ gap: 2, flexDirection: 'column' }}>
+          <>
             <Flex gap={3}>
               <ParamIterations />
               <ParamSteps />
               <ParamCFGScale />
             </Flex>
             <ParamSchedulerAndModel />
+            <Box pt={2}>
+              <ParamSeedFull />
+            </Box>
             <ParamWidth />
             <ParamHeight />
-        </Flex>
+          </>
         )}
       </Flex>
+    </IAICollapse>
   );
 };
 

invokeai/frontend/web/src/features/ui/components/tabs/TextToImage/TextToImageTabParameters.tsx

@@ -2,13 +2,13 @@ import ProcessButtons from 'features/parameters/components/ProcessButtons/Proces
 import { memo } from 'react';
 import ParamPositiveConditioning from 'features/parameters/components/Parameters/Core/ParamPositiveConditioning';
 import ParamNegativeConditioning from 'features/parameters/components/Parameters/Core/ParamNegativeConditioning';
-import ParamSeedCollapse from 'features/parameters/components/Parameters/Seed/ParamSeedCollapse';
 import ParamVariationCollapse from 'features/parameters/components/Parameters/Variations/ParamVariationCollapse';
 import ParamNoiseCollapse from 'features/parameters/components/Parameters/Noise/ParamNoiseCollapse';
 import ParamSymmetryCollapse from 'features/parameters/components/Parameters/Symmetry/ParamSymmetryCollapse';
 import ParamHiresCollapse from 'features/parameters/components/Parameters/Hires/ParamHiresCollapse';
 import ParamSeamlessCollapse from 'features/parameters/components/Parameters/Seamless/ParamSeamlessCollapse';
 import TextToImageTabCoreParameters from './TextToImageTabCoreParameters';
+import ParamControlNetCollapse from 'features/parameters/components/Parameters/ControlNet/ParamControlNetCollapse';
 
 const TextToImageTabParameters = () => {
   return (
@@ -17,7 +17,7 @@ const TextToImageTabParameters = () => {
       <ParamNegativeConditioning />
       <ProcessButtons />
       <TextToImageTabCoreParameters />
-      <ParamSeedCollapse />
+      <ParamControlNetCollapse />
       <ParamVariationCollapse />
       <ParamNoiseCollapse />
       <ParamSymmetryCollapse />

invokeai/frontend/web/src/features/ui/components/tabs/UnifiedCanvas/UnifiedCanvasBeta/UnifiedCanvasToolSettings/UnifiedCanvasDarkenOutsideSelection.tsx

@@ -1,6 +1,6 @@
 import { RootState } from 'app/store/store';
 import { useAppDispatch, useAppSelector } from 'app/store/storeHooks';
-import IAICheckbox from 'common/components/IAICheckbox';
+import IAISimpleCheckbox from 'common/components/IAISimpleCheckbox';
 import { setShouldDarkenOutsideBoundingBox } from 'features/canvas/store/canvasSlice';
 import { useTranslation } from 'react-i18next';
 
@@ -14,7 +14,7 @@ export default function UnifiedCanvasDarkenOutsideSelection() {
   const { t } = useTranslation();
 
   return (
-    <IAICheckbox
+    <IAISimpleCheckbox
       label={t('unifiedCanvas.betaDarkenOutside')}
       isChecked={shouldDarkenOutsideBoundingBox}
       onChange={(e) =>

invokeai/frontend/web/src/features/ui/components/tabs/UnifiedCanvas/UnifiedCanvasBeta/UnifiedCanvasToolSettings/UnifiedCanvasEnableMask.tsx

@@ -1,6 +1,6 @@
 import { RootState } from 'app/store/store';
 import { useAppDispatch, useAppSelector } from 'app/store/storeHooks';
-import IAICheckbox from 'common/components/IAICheckbox';
+import IAISimpleCheckbox from 'common/components/IAISimpleCheckbox';
 import { setIsMaskEnabled } from 'features/canvas/store/canvasSlice';
 import { useTranslation } from 'react-i18next';
 
@@ -16,7 +16,7 @@ export default function UnifiedCanvasEnableMask() {
     dispatch(setIsMaskEnabled(!isMaskEnabled));
 
   return (
-    <IAICheckbox
+    <IAISimpleCheckbox
       label={`${t('unifiedCanvas.enableMask')} (H)`}
       isChecked={isMaskEnabled}
       onChange={handleToggleEnableMask}

invokeai/frontend/web/src/features/ui/components/tabs/UnifiedCanvas/UnifiedCanvasBeta/UnifiedCanvasToolSettings/UnifiedCanvasLimitStrokesToBox.tsx

@@ -1,6 +1,6 @@
 import { RootState } from 'app/store/store';
 import { useAppDispatch, useAppSelector } from 'app/store/storeHooks';
-import IAICheckbox from 'common/components/IAICheckbox';
+import IAISimpleCheckbox from 'common/components/IAISimpleCheckbox';
 import { setShouldRestrictStrokesToBox } from 'features/canvas/store/canvasSlice';
 import { useTranslation } from 'react-i18next';
 
@@ -14,7 +14,7 @@ export default function UnifiedCanvasLimitStrokesToBox() {
   const { t } = useTranslation();
 
   return (
-    <IAICheckbox
+    <IAISimpleCheckbox
       label={t('unifiedCanvas.betaLimitToBox')}
       isChecked={shouldRestrictStrokesToBox}
       onChange={(e) =>

invokeai/frontend/web/src/features/ui/components/tabs/UnifiedCanvas/UnifiedCanvasBeta/UnifiedCanvasToolSettings/UnifiedCanvasPreserveMask.tsx

@@ -1,6 +1,6 @@
 import { RootState } from 'app/store/store';
 import { useAppDispatch, useAppSelector } from 'app/store/storeHooks';
-import IAICheckbox from 'common/components/IAICheckbox';
+import IAISimpleCheckbox from 'common/components/IAISimpleCheckbox';
 import { setShouldPreserveMaskedArea } from 'features/canvas/store/canvasSlice';
 import { useTranslation } from 'react-i18next';
 
@@ -13,7 +13,7 @@ export default function UnifiedCanvasPreserveMask() {
   );
 
   return (
-    <IAICheckbox
+    <IAISimpleCheckbox
       label={t('unifiedCanvas.betaPreserveMasked')}
       isChecked={shouldPreserveMaskedArea}
       onChange={(e) => dispatch(setShouldPreserveMaskedArea(e.target.checked))}