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docs/features/LOGGING.md Normal file
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@ -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
```

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@ -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

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@ -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?
conjunction = Compel.parse_prompt_string(prompt_str)
prompt: Union[FlattenedPrompt, Blend] = conjunction.prompts[0]
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)
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
):

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@ -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):

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@ -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,

View File

@ -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):

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@ -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))

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

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@ -39,8 +39,8 @@ def get_uc_and_c_and_ec(prompt_string,
textual_inversion_manager=model.textual_inversion_manager,
dtype_for_device_getter=torch_dtype,
truncate_long_prompts=False,
)
)
# get rid of any newline characters
prompt_string = prompt_string.replace("\n", " ")
positive_prompt_string, negative_prompt_string = split_prompt_to_positive_and_negative(prompt_string)
@ -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))

View File

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

View File

@ -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.addHandler(ch)
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)

View File

@ -26,10 +26,10 @@ 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.
2. Generate the API client.
```bash
# from invokeai/frontend/web/

View File

@ -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.

View File

@ -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",

View File

@ -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);

View File

@ -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);

View File

@ -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>
<App
config={config}
headerComponent={headerComponent}
setIsReady={setIsReady}
/>
<ImageDndContext>
<App
config={config}
headerComponent={headerComponent}
setIsReady={setIsReady}
/>
</ImageDndContext>
</ThemeLocaleProvider>
</React.Suspense>
</Provider>

View File

@ -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,
};

View File

@ -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) => {

View File

@ -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();

View File

@ -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 }));
},
});
};

View File

@ -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,
})
);
}
},
});
};

View File

@ -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({

View File

@ -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',
];

View File

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

View File

@ -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);

View File

@ -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>

View File

@ -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' }}>
<Text
sx={{
fontSize: 'sm',
fontWeight: 500,
color: 'base.100',
whiteSpace: 'nowrap',
overflow: 'hidden',
textOverflow: 'ellipsis',
direction: labelTextDirection,
}}
>
{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',
@ -118,61 +151,72 @@ const IAICustomSelect = (props: IAICustomSelectProps) => {
px: 0,
h: 'fit-content',
maxH: 64,
minW: 48,
}}
>
<OverlayScrollbarsComponent>
{items.map((item, index) => (
<Tooltip
isDisabled={!itemTooltips}
key={`${item}${index}`}
label={itemTooltips?.[item]}
hasArrow
placement="right"
>
<ListItem
sx={{
bg: highlightedIndex === index ? 'base.700' : undefined,
py: 1,
paddingInlineStart: 3,
paddingInlineEnd: 6,
cursor: 'pointer',
transitionProperty: 'common',
transitionDuration: '0.15s',
}}
{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}`}
{...getItemProps({ item, index })}
label={itemTooltips?.[item]}
hasArrow
placement="right"
>
{withCheckIcon ? (
<Grid gridTemplateColumns="1.25rem auto">
<GridItem>
{selectedItem === item && <CheckIcon boxSize={2} />}
</GridItem>
<GridItem>
<Text
sx={{
fontSize: 'sm',
color: 'base.100',
fontWeight: 500,
}}
>
{item}
</Text>
</GridItem>
</Grid>
) : (
<Text
sx={{
fontSize: 'sm',
color: 'base.100',
fontWeight: 500,
}}
>
{item}
</Text>
)}
</ListItem>
</Tooltip>
))}
<ListItem
sx={{
bg,
py: 1,
paddingInlineStart: 3,
paddingInlineEnd: 6,
cursor: 'pointer',
transitionProperty: 'common',
transitionDuration: '0.15s',
}}
key={`${item}${index}`}
{...getItemProps({ item, index })}
>
{withCheckIcon ? (
<Grid gridTemplateColumns="1.25rem auto">
<GridItem>
{isSelected && <CheckIcon boxSize={2} />}
</GridItem>
<GridItem>
<Text
sx={{
fontSize: 'sm',
color: 'base.100',
fontWeight,
}}
>
{item}
</Text>
</GridItem>
</Grid>
) : (
<Text
sx={{
fontSize: 'sm',
color: 'base.50',
fontWeight,
}}
>
{item}
</Text>
)}
</ListItem>
</Tooltip>
);
})}
</OverlayScrollbarsComponent>
</List>
)}

View File

@ -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>
);
};

View File

@ -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);

View File

@ -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>
);
};

View File

@ -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);

View File

@ -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}
>
<FormLabel {...sliderFormLabelProps} mb={-1}>
{label}
</FormLabel>
{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}
>

View File

@ -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;
}
/**
@ -25,22 +27,27 @@ const IAISwitch = (props: Props) => {
width = 'auto',
formControlProps,
formLabelProps,
tooltip,
...rest
} = props;
return (
<FormControl
isDisabled={isDisabled}
width={width}
display="flex"
gap={4}
alignItems="center"
{...formControlProps}
>
<FormLabel my={1} flexGrow={1} {...formLabelProps}>
{label}
</FormLabel>
<Switch {...rest} />
</FormControl>
<Tooltip label={tooltip} hasArrow placement="top" isDisabled={!tooltip}>
<FormControl
isDisabled={isDisabled}
width={width}
display="flex"
gap={4}
alignItems="center"
{...formControlProps}
>
{label && (
<FormLabel my={1} flexGrow={1} {...formLabelProps}>
{label}
</FormLabel>
)}
<Switch {...rest} />
</FormControl>
</Tooltip>
);
};

View File

@ -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}
</Badge>
)}
<Badge variant="solid" colorScheme="base">
{image.width} × {image.height}
</Badge>
{model && (
<Badge variant="solid" colorScheme="base">
{model}

View File

@ -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;

View File

@ -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;
};

View File

@ -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) =>

View File

@ -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))}

View File

@ -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);

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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);

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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);

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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);

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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;
};

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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);

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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);

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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);

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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);

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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);

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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);

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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);

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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);

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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);

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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);

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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);

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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);

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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);

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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);

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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);

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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);

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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);

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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);

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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>;
}

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

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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',
};

View File

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

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@ -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;

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@ -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;
};

View File

@ -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',
}}
/>
)}
<CurrentImagePreview />
</Flex>
{hasSelectedImage && (
<Box sx={{ position: 'absolute', top: 0 }}>
<CurrentImageButtons />
</Box>
)}
</Flex>
);
};

View File

@ -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}
sx={{
objectFit: 'contain',
maxWidth: '100%',
maxHeight: '100%',
height: 'auto',
position: 'absolute',
borderRadius: 'base',
}}
onError={handleError}
/>
<ImageMetadataOverlay image={image} />
</>
)
<Flex
sx={{
width: 'full',
height: 'full',
alignItems: 'center',
justifyContent: 'center',
}}
>
<IAIDndImage
image={image}
onDrop={handleDrop}
onError={handleError}
fallback={<IAIImageFallback sx={{ bg: 'none' }} />}
/>
</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>
);
};

View File

@ -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);

View File

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

View File

@ -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>) =>

View File

@ -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;
}
});

View File

@ -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>
);
};

View File

@ -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]);

View File

@ -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',
},
});
}
});
}
};

View File

@ -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;
};

View File

@ -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;
};

View File

@ -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);

View File

@ -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);

View File

@ -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>

View File

@ -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',
}}
/>
<ImageMetadataOverlay image={initialImage} />
</>
)}
{!initialImage?.image_url && (
<Icon
as={FaImage}
sx={{
boxSize: 24,
color: 'base.500',
}}
/>
)}
<IAIDndImage
image={initialImage}
onDrop={handleDrop}
onReset={handleReset}
fallback={<IAIImageFallback sx={{ bg: 'none' }} />}
/>
</Flex>
);
};

View File

@ -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);

View File

@ -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={{

View File

@ -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"

View File

@ -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(() => {

View File

@ -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'
);

View File

@ -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)}

View File

@ -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)}

View File

@ -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={() =>

View File

@ -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

View File

@ -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 (
<Flex
sx={{
flexDirection: 'column',
gap: 2,
bg: 'base.800',
p: 4,
borderRadius: 'base',
}}
>
{shouldUseSliders ? (
<Flex sx={{ gap: 3, flexDirection: 'column' }}>
<ParamIterations />
<ParamSteps />
<ParamCFGScale />
<ParamWidth isDisabled={!shouldFitToWidthHeight} />
<ParamHeight isDisabled={!shouldFitToWidthHeight} />
<ImageToImageStrength />
<ImageToImageFit />
<ParamSchedulerAndModel />
</Flex>
) : (
<Flex sx={{ gap: 2, flexDirection: 'column' }}>
<Flex gap={3}>
<IAICollapse label={'General'} isOpen={isOpen} onToggle={onToggle}>
<Flex
sx={{
flexDirection: 'column',
gap: 3,
}}
>
{shouldUseSliders ? (
<>
<ParamSchedulerAndModel />
<Box pt={2}>
<ParamSeedFull />
</Box>
<ParamIterations />
<ParamSteps />
<ParamCFGScale />
</Flex>
<ParamSchedulerAndModel />
<ParamWidth isDisabled={!shouldFitToWidthHeight} />
<ParamHeight isDisabled={!shouldFitToWidthHeight} />
<ImageToImageStrength />
<ImageToImageFit />
</Flex>
)}
</Flex>
<ParamWidth isDisabled={!shouldFitToWidthHeight} />
<ParamHeight isDisabled={!shouldFitToWidthHeight} />
</>
) : (
<>
<Flex gap={3}>
<ParamIterations />
<ParamSteps />
<ParamCFGScale />
</Flex>
<ParamSchedulerAndModel />
<Box pt={2}>
<ParamSeedFull />
</Box>
<ParamWidth isDisabled={!shouldFitToWidthHeight} />
<ParamHeight isDisabled={!shouldFitToWidthHeight} />
</>
)}
<ImageToImageStrength />
<ImageToImageFit />
</Flex>
</IAICollapse>
);
};

View File

@ -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 />

View File

@ -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 (
<Flex
sx={{
flexDirection: 'column',
gap: 2,
bg: 'base.800',
p: 4,
borderRadius: 'base',
}}
>
{shouldUseSliders ? (
<Flex sx={{ gap: 3, flexDirection: 'column' }}>
<ParamIterations />
<ParamSteps />
<ParamCFGScale />
<ParamWidth />
<ParamHeight />
<ParamSchedulerAndModel />
</Flex>
) : (
<Flex sx={{ gap: 2, flexDirection: 'column' }}>
<Flex gap={3}>
<IAICollapse label={'General'} isOpen={isOpen} onToggle={onToggle}>
<Flex
sx={{
flexDirection: 'column',
gap: 3,
}}
>
{shouldUseSliders ? (
<>
<ParamSchedulerAndModel />
<Box pt={2}>
<ParamSeedFull />
</Box>
<ParamIterations />
<ParamSteps />
<ParamCFGScale />
</Flex>
<ParamSchedulerAndModel />
<ParamWidth />
<ParamHeight />
</Flex>
)}
</Flex>
<ParamWidth />
<ParamHeight />
</>
) : (
<>
<Flex gap={3}>
<ParamIterations />
<ParamSteps />
<ParamCFGScale />
</Flex>
<ParamSchedulerAndModel />
<Box pt={2}>
<ParamSeedFull />
</Box>
<ParamWidth />
<ParamHeight />
</>
)}
</Flex>
</IAICollapse>
);
};

View File

@ -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 />

View File

@ -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) =>

View File

@ -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}

View File

@ -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) =>

View File

@ -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))}

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