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Merge branch 'main' into stalker-modular_inpaint-2

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This commit is contained in:
Ryan Dick 2024-07-29 10:14:45 -04:00
commit 693a3eaff5
172 changed files with 5752 additions and 2851 deletions
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1
docker/Dockerfile
View File

@ -55,6 +55,7 @@ RUN --mount=type=cache,target=/root/.cache/pip \
FROM node:20-slim AS web-builder
ENV PNPM_HOME="/pnpm"
ENV PATH="$PNPM_HOME:$PATH"
RUN corepack use pnpm@8.x
RUN corepack enable
WORKDIR /build

29
invokeai/app/api/routers/model_manager.py
View File

@ -6,7 +6,7 @@ import pathlib
import traceback
from copy import deepcopy
from tempfile import TemporaryDirectory
from typing import Any, Dict, List, Optional, Type
from typing import List, Optional, Type
from fastapi import Body, Path, Query, Response, UploadFile
from fastapi.responses import FileResponse, HTMLResponse
@ -430,13 +430,11 @@ async def delete_model_image(
async def install_model(
source: str = Query(description="Model source to install, can be a local path, repo_id, or remote URL"),
inplace: Optional[bool] = Query(description="Whether or not to install a local model in place", default=False),
# TODO(MM2): Can we type this?
config: Optional[Dict[str, Any]] = Body(
description="Dict of fields that override auto-probed values in the model config record, such as name, description and prediction_type ",
default=None,
access_token: Optional[str] = Query(description="access token for the remote resource", default=None),
config: ModelRecordChanges = Body(
description="Object containing fields that override auto-probed values in the model config record, such as name, description and prediction_type ",
example={"name": "string", "description": "string"},
),
access_token: Optional[str] = None,
) -> ModelInstallJob:
"""Install a model using a string identifier.
@ -451,8 +449,9 @@ async def install_model(
- model/name:fp16:path/to/model.safetensors
- model/name::path/to/model.safetensors
`config` is an optional dict containing model configuration values that will override
the ones that are probed automatically.
`config` is a ModelRecordChanges object. Fields in this object will override
the ones that are probed automatically. Pass an empty object to accept
all the defaults.
`access_token` is an optional access token for use with Urls that require
authentication.
@ -737,7 +736,7 @@ async def convert_model(
# write the converted file to the convert path
raw_model = converted_model.model
assert hasattr(raw_model, "save_pretrained")
raw_model.save_pretrained(convert_path)
raw_model.save_pretrained(convert_path) # type: ignore
assert convert_path.exists()
# temporarily rename the original safetensors file so that there is no naming conflict
@ -750,12 +749,12 @@ async def convert_model(
try:
new_key = installer.install_path(
convert_path,
config={
"name": original_name,
"description": model_config.description,
"hash": model_config.hash,
"source": model_config.source,
},
config=ModelRecordChanges(
name=original_name,
description=model_config.description,
hash=model_config.hash,
source=model_config.source,
),
)
except Exception as e:
logger.error(str(e))

120
invokeai/app/invocations/denoise_latents.py
View File

@ -39,7 +39,7 @@ from invokeai.backend.ip_adapter.ip_adapter import IPAdapter
from invokeai.backend.lora import LoRAModelRaw
from invokeai.backend.model_manager import BaseModelType, ModelVariantType
from invokeai.backend.model_patcher import ModelPatcher
from invokeai.backend.stable_diffusion import PipelineIntermediateState, set_seamless
from invokeai.backend.stable_diffusion import PipelineIntermediateState
from invokeai.backend.stable_diffusion.denoise_context import DenoiseContext, DenoiseInputs
from invokeai.backend.stable_diffusion.diffusers_pipeline import (
ControlNetData,
@ -58,9 +58,14 @@ from invokeai.backend.stable_diffusion.diffusion.conditioning_data import (
from invokeai.backend.stable_diffusion.diffusion.custom_atttention import CustomAttnProcessor2_0
from invokeai.backend.stable_diffusion.diffusion_backend import StableDiffusionBackend
from invokeai.backend.stable_diffusion.extension_callback_type import ExtensionCallbackType
from invokeai.backend.stable_diffusion.extensions.controlnet import ControlNetExt
from invokeai.backend.stable_diffusion.extensions.freeu import FreeUExt
from invokeai.backend.stable_diffusion.extensions.inpaint import InpaintExt
from invokeai.backend.stable_diffusion.extensions.inpaint_model import InpaintModelExt
from invokeai.backend.stable_diffusion.extensions.preview import PreviewExt
from invokeai.backend.stable_diffusion.extensions.rescale_cfg import RescaleCFGExt
from invokeai.backend.stable_diffusion.extensions.seamless import SeamlessExt
from invokeai.backend.stable_diffusion.extensions.t2i_adapter import T2IAdapterExt
from invokeai.backend.stable_diffusion.extensions_manager import ExtensionsManager
from invokeai.backend.stable_diffusion.schedulers import SCHEDULER_MAP
from invokeai.backend.stable_diffusion.schedulers.schedulers import SCHEDULER_NAME_VALUES
@ -465,6 +470,65 @@ class DenoiseLatentsInvocation(BaseInvocation):
return controlnet_data
@staticmethod
def parse_controlnet_field(
exit_stack: ExitStack,
context: InvocationContext,
control_input: ControlField | list[ControlField] | None,
ext_manager: ExtensionsManager,
) -> None:
# Normalize control_input to a list.
control_list: list[ControlField]
if isinstance(control_input, ControlField):
control_list = [control_input]
elif isinstance(control_input, list):
control_list = control_input
elif control_input is None:
control_list = []
else:
raise ValueError(f"Unexpected control_input type: {type(control_input)}")
for control_info in control_list:
model = exit_stack.enter_context(context.models.load(control_info.control_model))
ext_manager.add_extension(
ControlNetExt(
model=model,
image=context.images.get_pil(control_info.image.image_name),
weight=control_info.control_weight,
begin_step_percent=control_info.begin_step_percent,
end_step_percent=control_info.end_step_percent,
control_mode=control_info.control_mode,
resize_mode=control_info.resize_mode,
)
)
@staticmethod
def parse_t2i_adapter_field(
exit_stack: ExitStack,
context: InvocationContext,
t2i_adapters: Optional[Union[T2IAdapterField, list[T2IAdapterField]]],
ext_manager: ExtensionsManager,
) -> None:
if t2i_adapters is None:
return
# Handle the possibility that t2i_adapters could be a list or a single T2IAdapterField.
if isinstance(t2i_adapters, T2IAdapterField):
t2i_adapters = [t2i_adapters]
for t2i_adapter_field in t2i_adapters:
ext_manager.add_extension(
T2IAdapterExt(
node_context=context,
model_id=t2i_adapter_field.t2i_adapter_model,
image=context.images.get_pil(t2i_adapter_field.image.image_name),
weight=t2i_adapter_field.weight,
begin_step_percent=t2i_adapter_field.begin_step_percent,
end_step_percent=t2i_adapter_field.end_step_percent,
resize_mode=t2i_adapter_field.resize_mode,
)
)
def prep_ip_adapter_image_prompts(
self,
context: InvocationContext,
@ -773,6 +837,18 @@ class DenoiseLatentsInvocation(BaseInvocation):
ext_manager.add_extension(PreviewExt(step_callback))
### cfg rescale
if self.cfg_rescale_multiplier > 0:
ext_manager.add_extension(RescaleCFGExt(self.cfg_rescale_multiplier))
### freeu
if self.unet.freeu_config:
ext_manager.add_extension(FreeUExt(self.unet.freeu_config))
### seamless
if self.unet.seamless_axes:
ext_manager.add_extension(SeamlessExt(self.unet.seamless_axes))
### inpaint
mask, masked_latents, is_gradient_mask = self.prep_inpaint_mask(context, latents)
# NOTE: We used to identify inpainting models by inpecting the shape of the loaded UNet model weights. Now we
@ -788,7 +864,6 @@ class DenoiseLatentsInvocation(BaseInvocation):
latents = latents.to(device=device, dtype=dtype)
if noise is not None:
noise = noise.to(device=device, dtype=dtype)
denoise_ctx = DenoiseContext(
inputs=DenoiseInputs(
orig_latents=latents,
@ -804,22 +879,31 @@ class DenoiseLatentsInvocation(BaseInvocation):
scheduler=scheduler,
)
# ext: t2i/ip adapter
ext_manager.run_callback(ExtensionCallbackType.SETUP, denoise_ctx)
# context for loading additional models
with ExitStack() as exit_stack:
# later should be smth like:
# for extension_field in self.extensions:
# ext = extension_field.to_extension(exit_stack, context, ext_manager)
# ext_manager.add_extension(ext)
self.parse_controlnet_field(exit_stack, context, self.control, ext_manager)
self.parse_t2i_adapter_field(exit_stack, context, self.t2i_adapter, ext_manager)
unet_info = context.models.load(self.unet.unet)
assert isinstance(unet_info.model, UNet2DConditionModel)
with (
unet_info.model_on_device() as (model_state_dict, unet),
ModelPatcher.patch_unet_attention_processor(unet, denoise_ctx.inputs.attention_processor_cls),
# ext: controlnet
ext_manager.patch_extensions(unet),
# ext: freeu, seamless, ip adapter, lora
ext_manager.patch_unet(model_state_dict, unet),
):
sd_backend = StableDiffusionBackend(unet, scheduler)
denoise_ctx.unet = unet
result_latents = sd_backend.latents_from_embeddings(denoise_ctx, ext_manager)
# ext: t2i/ip adapter
ext_manager.run_callback(ExtensionCallbackType.SETUP, denoise_ctx)
unet_info = context.models.load(self.unet.unet)
assert isinstance(unet_info.model, UNet2DConditionModel)
with (
unet_info.model_on_device() as (cached_weights, unet),
ModelPatcher.patch_unet_attention_processor(unet, denoise_ctx.inputs.attention_processor_cls),
# ext: controlnet
ext_manager.patch_extensions(denoise_ctx),
# ext: freeu, seamless, ip adapter, lora
ext_manager.patch_unet(unet, cached_weights),
):
sd_backend = StableDiffusionBackend(unet, scheduler)
denoise_ctx.unet = unet
result_latents = sd_backend.latents_from_embeddings(denoise_ctx, ext_manager)
# https://discuss.huggingface.co/t/memory-usage-by-later-pipeline-stages/23699
result_latents = result_latents.detach().to("cpu")
@ -882,7 +966,7 @@ class DenoiseLatentsInvocation(BaseInvocation):
ExitStack() as exit_stack,
unet_info.model_on_device() as (model_state_dict, unet),
ModelPatcher.apply_freeu(unet, self.unet.freeu_config),
set_seamless(unet, self.unet.seamless_axes), # FIXME
SeamlessExt.static_patch_model(unet, self.unet.seamless_axes), # FIXME
# Apply the LoRA after unet has been moved to its target device for faster patching.
ModelPatcher.apply_lora_unet(
unet,

4
invokeai/app/invocations/latents_to_image.py
View File

@ -24,7 +24,7 @@ from invokeai.app.invocations.fields import (
from invokeai.app.invocations.model import VAEField
from invokeai.app.invocations.primitives import ImageOutput
from invokeai.app.services.shared.invocation_context import InvocationContext
from invokeai.backend.stable_diffusion import set_seamless
from invokeai.backend.stable_diffusion.extensions.seamless import SeamlessExt
from invokeai.backend.stable_diffusion.vae_tiling import patch_vae_tiling_params
from invokeai.backend.util.devices import TorchDevice
@ -59,7 +59,7 @@ class LatentsToImageInvocation(BaseInvocation, WithMetadata, WithBoard):
vae_info = context.models.load(self.vae.vae)
assert isinstance(vae_info.model, (AutoencoderKL, AutoencoderTiny))
with set_seamless(vae_info.model, self.vae.seamless_axes), vae_info as vae:
with SeamlessExt.static_patch_model(vae_info.model, self.vae.seamless_axes), vae_info as vae:
assert isinstance(vae, (AutoencoderKL, AutoencoderTiny))
latents = latents.to(vae.device)
if self.fp32:

221
invokeai/app/invocations/spandrel_image_to_image.py
View File

@ -1,3 +1,5 @@
from typing import Callable
import numpy as np
import torch
from PIL import Image
@ -21,7 +23,7 @@ from invokeai.backend.tiles.tiles import calc_tiles_min_overlap
from invokeai.backend.tiles.utils import TBLR, Tile
@invocation("spandrel_image_to_image", title="Image-to-Image", tags=["upscale"], category="upscale", version="1.1.0")
@invocation("spandrel_image_to_image", title="Image-to-Image", tags=["upscale"], category="upscale", version="1.3.0")
class SpandrelImageToImageInvocation(BaseInvocation, WithMetadata, WithBoard):
"""Run any spandrel image-to-image model (https://github.com/chaiNNer-org/spandrel)."""
@ -35,7 +37,8 @@ class SpandrelImageToImageInvocation(BaseInvocation, WithMetadata, WithBoard):
default=512, description="The tile size for tiled image-to-image. Set to 0 to disable tiling."
)
def _scale_tile(self, tile: Tile, scale: int) -> Tile:
@classmethod
def scale_tile(cls, tile: Tile, scale: int) -> Tile:
return Tile(
coords=TBLR(
top=tile.coords.top * scale,
@ -51,20 +54,22 @@ class SpandrelImageToImageInvocation(BaseInvocation, WithMetadata, WithBoard):
),
)
@torch.inference_mode()
def invoke(self, context: InvocationContext) -> ImageOutput:
# Images are converted to RGB, because most models don't support an alpha channel. In the future, we may want to
# revisit this.
image = context.images.get_pil(self.image.image_name, mode="RGB")
@classmethod
def upscale_image(
cls,
image: Image.Image,
tile_size: int,
spandrel_model: SpandrelImageToImageModel,
is_canceled: Callable[[], bool],
) -> Image.Image:
# Compute the image tiles.
if self.tile_size > 0:
if tile_size > 0:
min_overlap = 20
tiles = calc_tiles_min_overlap(
image_height=image.height,
image_width=image.width,
tile_height=self.tile_size,
tile_width=self.tile_size,
tile_height=tile_size,
tile_width=tile_size,
min_overlap=min_overlap,
)
else:
@ -85,60 +90,164 @@ class SpandrelImageToImageInvocation(BaseInvocation, WithMetadata, WithBoard):
# Prepare input image for inference.
image_tensor = SpandrelImageToImageModel.pil_to_tensor(image)
# Load the model.
spandrel_model_info = context.models.load(self.image_to_image_model)
# Scale the tiles for re-assembling the final image.
scale = spandrel_model.scale
scaled_tiles = [cls.scale_tile(tile, scale=scale) for tile in tiles]
# Prepare the output tensor.
_, channels, height, width = image_tensor.shape
output_tensor = torch.zeros(
(height * scale, width * scale, channels), dtype=torch.uint8, device=torch.device("cpu")
)
image_tensor = image_tensor.to(device=spandrel_model.device, dtype=spandrel_model.dtype)
# Run the model on each tile.
with spandrel_model_info as spandrel_model:
assert isinstance(spandrel_model, SpandrelImageToImageModel)
for tile, scaled_tile in tqdm(list(zip(tiles, scaled_tiles, strict=True)), desc="Upscaling Tiles"):
# Exit early if the invocation has been canceled.
if is_canceled():
raise CanceledException
# Scale the tiles for re-assembling the final image.
scale = spandrel_model.scale
scaled_tiles = [self._scale_tile(tile, scale=scale) for tile in tiles]
# Extract the current tile from the input tensor.
input_tile = image_tensor[
:, :, tile.coords.top : tile.coords.bottom, tile.coords.left : tile.coords.right
].to(device=spandrel_model.device, dtype=spandrel_model.dtype)
# Prepare the output tensor.
_, channels, height, width = image_tensor.shape
output_tensor = torch.zeros(
(height * scale, width * scale, channels), dtype=torch.uint8, device=torch.device("cpu")
)
# Run the model on the tile.
output_tile = spandrel_model.run(input_tile)
image_tensor = image_tensor.to(device=spandrel_model.device, dtype=spandrel_model.dtype)
# Convert the output tile into the output tensor's format.
# (N, C, H, W) -> (C, H, W)
output_tile = output_tile.squeeze(0)
# (C, H, W) -> (H, W, C)
output_tile = output_tile.permute(1, 2, 0)
output_tile = output_tile.clamp(0, 1)
output_tile = (output_tile * 255).to(dtype=torch.uint8, device=torch.device("cpu"))
for tile, scaled_tile in tqdm(list(zip(tiles, scaled_tiles, strict=True)), desc="Upscaling Tiles"):
# Exit early if the invocation has been canceled.
if context.util.is_canceled():
raise CanceledException
# Extract the current tile from the input tensor.
input_tile = image_tensor[
:, :, tile.coords.top : tile.coords.bottom, tile.coords.left : tile.coords.right
].to(device=spandrel_model.device, dtype=spandrel_model.dtype)
# Run the model on the tile.
output_tile = spandrel_model.run(input_tile)
# Convert the output tile into the output tensor's format.
# (N, C, H, W) -> (C, H, W)
output_tile = output_tile.squeeze(0)
# (C, H, W) -> (H, W, C)
output_tile = output_tile.permute(1, 2, 0)
output_tile = output_tile.clamp(0, 1)
output_tile = (output_tile * 255).to(dtype=torch.uint8, device=torch.device("cpu"))
# Merge the output tile into the output tensor.
# We only keep half of the overlap on the top and left side of the tile. We do this in case there are
# edge artifacts. We don't bother with any 'blending' in the current implementation - for most upscalers
# it seems unnecessary, but we may find a need in the future.
top_overlap = scaled_tile.overlap.top // 2
left_overlap = scaled_tile.overlap.left // 2
output_tensor[
scaled_tile.coords.top + top_overlap : scaled_tile.coords.bottom,
scaled_tile.coords.left + left_overlap : scaled_tile.coords.right,
:,
] = output_tile[top_overlap:, left_overlap:, :]
# Merge the output tile into the output tensor.
# We only keep half of the overlap on the top and left side of the tile. We do this in case there are
# edge artifacts. We don't bother with any 'blending' in the current implementation - for most upscalers
# it seems unnecessary, but we may find a need in the future.
top_overlap = scaled_tile.overlap.top // 2
left_overlap = scaled_tile.overlap.left // 2
output_tensor[
scaled_tile.coords.top + top_overlap : scaled_tile.coords.bottom,
scaled_tile.coords.left + left_overlap : scaled_tile.coords.right,
:,
] = output_tile[top_overlap:, left_overlap:, :]
# Convert the output tensor to a PIL image.
np_image = output_tensor.detach().numpy().astype(np.uint8)
pil_image = Image.fromarray(np_image)
return pil_image
@torch.inference_mode()
def invoke(self, context: InvocationContext) -> ImageOutput:
# Images are converted to RGB, because most models don't support an alpha channel. In the future, we may want to
# revisit this.
image = context.images.get_pil(self.image.image_name, mode="RGB")
# Load the model.
spandrel_model_info = context.models.load(self.image_to_image_model)
# Do the upscaling.
with spandrel_model_info as spandrel_model:
assert isinstance(spandrel_model, SpandrelImageToImageModel)
# Upscale the image
pil_image = self.upscale_image(image, self.tile_size, spandrel_model, context.util.is_canceled)
image_dto = context.images.save(image=pil_image)
return ImageOutput.build(image_dto)
@invocation(
"spandrel_image_to_image_autoscale",
title="Image-to-Image (Autoscale)",
tags=["upscale"],
category="upscale",
version="1.0.0",
)
class SpandrelImageToImageAutoscaleInvocation(SpandrelImageToImageInvocation):
"""Run any spandrel image-to-image model (https://github.com/chaiNNer-org/spandrel) until the target scale is reached."""
scale: float = InputField(
default=4.0,
gt=0.0,
le=16.0,
description="The final scale of the output image. If the model does not upscale the image, this will be ignored.",
)
fit_to_multiple_of_8: bool = InputField(
default=False,
description="If true, the output image will be resized to the nearest multiple of 8 in both dimensions.",
)
@torch.inference_mode()
def invoke(self, context: InvocationContext) -> ImageOutput:
# Images are converted to RGB, because most models don't support an alpha channel. In the future, we may want to
# revisit this.
image = context.images.get_pil(self.image.image_name, mode="RGB")
# Load the model.
spandrel_model_info = context.models.load(self.image_to_image_model)
# The target size of the image, determined by the provided scale. We'll run the upscaler until we hit this size.
# Later, we may mutate this value if the model doesn't upscale the image or if the user requested a multiple of 8.
target_width = int(image.width * self.scale)
target_height = int(image.height * self.scale)
# Do the upscaling.
with spandrel_model_info as spandrel_model:
assert isinstance(spandrel_model, SpandrelImageToImageModel)
# First pass of upscaling. Note: `pil_image` will be mutated.
pil_image = self.upscale_image(image, self.tile_size, spandrel_model, context.util.is_canceled)
# Some models don't upscale the image, but we have no way to know this in advance. We'll check if the model
# upscaled the image and run the loop below if it did. We'll require the model to upscale both dimensions
# to be considered an upscale model.
is_upscale_model = pil_image.width > image.width and pil_image.height > image.height
if is_upscale_model:
# This is an upscale model, so we should keep upscaling until we reach the target size.
iterations = 1
while pil_image.width < target_width or pil_image.height < target_height:
pil_image = self.upscale_image(pil_image, self.tile_size, spandrel_model, context.util.is_canceled)
iterations += 1
# Sanity check to prevent excessive or infinite loops. All known upscaling models are at least 2x.
# Our max scale is 16x, so with a 2x model, we should never exceed 16x == 2^4 -> 4 iterations.
# We'll allow one extra iteration "just in case" and bail at 5 upscaling iterations. In practice,
# we should never reach this limit.
if iterations >= 5:
context.logger.warning(
"Upscale loop reached maximum iteration count of 5, stopping upscaling early."
)
break
else:
# This model doesn't upscale the image. We should ignore the scale parameter, modifying the output size
# to be the same as the processed image size.
# The output size is now the size of the processed image.
target_width = pil_image.width
target_height = pil_image.height
# Warn the user if they requested a scale greater than 1.
if self.scale > 1:
context.logger.warning(
"Model does not increase the size of the image, but a greater scale than 1 was requested. Image will not be scaled."
)
# We may need to resize the image to a multiple of 8. Use floor division to ensure we don't scale the image up
# in the final resize
if self.fit_to_multiple_of_8:
target_width = int(target_width // 8 * 8)
target_height = int(target_height // 8 * 8)
# Final resize. Per PIL documentation, Lanczos provides the best quality for both upscale and downscale.
# See: https://pillow.readthedocs.io/en/stable/handbook/concepts.html#filters-comparison-table
pil_image = pil_image.resize((target_width, target_height), resample=Image.Resampling.LANCZOS)
image_dto = context.images.save(image=pil_image)
return ImageOutput.build(image_dto)

18
invokeai/app/services/model_install/model_install_base.py
View File

@ -3,7 +3,7 @@
from abc import ABC, abstractmethod
from pathlib import Path
from typing import Any, Dict, List, Optional, Union
from typing import List, Optional, Union
from pydantic.networks import AnyHttpUrl
@ -12,7 +12,7 @@ from invokeai.app.services.download import DownloadQueueServiceBase
from invokeai.app.services.events.events_base import EventServiceBase
from invokeai.app.services.invoker import Invoker
from invokeai.app.services.model_install.model_install_common import ModelInstallJob, ModelSource
from invokeai.app.services.model_records import ModelRecordServiceBase
from invokeai.app.services.model_records import ModelRecordChanges, ModelRecordServiceBase
from invokeai.backend.model_manager import AnyModelConfig
@ -64,7 +64,7 @@ class ModelInstallServiceBase(ABC):
def register_path(
self,
model_path: Union[Path, str],
config: Optional[Dict[str, Any]] = None,
config: Optional[ModelRecordChanges] = None,
) -> str:
"""
Probe and register the model at model_path.
@ -72,7 +72,7 @@ class ModelInstallServiceBase(ABC):
This keeps the model in its current location.
:param model_path: Filesystem Path to the model.
:param config: Dict of attributes that will override autoassigned values.
:param config: ModelRecordChanges object that will override autoassigned model record values.
:returns id: The string ID of the registered model.
"""
@ -92,7 +92,7 @@ class ModelInstallServiceBase(ABC):
def install_path(
self,
model_path: Union[Path, str],
config: Optional[Dict[str, Any]] = None,
config: Optional[ModelRecordChanges] = None,
) -> str:
"""
Probe, register and install the model in the models directory.
@ -101,7 +101,7 @@ class ModelInstallServiceBase(ABC):
the models directory handled by InvokeAI.
:param model_path: Filesystem Path to the model.
:param config: Dict of attributes that will override autoassigned values.
:param config: ModelRecordChanges object that will override autoassigned model record values.
:returns id: The string ID of the registered model.
"""
@ -109,14 +109,14 @@ class ModelInstallServiceBase(ABC):
def heuristic_import(
self,
source: str,
config: Optional[Dict[str, Any]] = None,
config: Optional[ModelRecordChanges] = None,
access_token: Optional[str] = None,
inplace: Optional[bool] = False,
) -> ModelInstallJob:
r"""Install the indicated model using heuristics to interpret user intentions.
:param source: String source
:param config: Optional dict. Any fields in this dict
:param config: Optional ModelRecordChanges object. Any fields in this object
will override corresponding autoassigned probe fields in the
model's config record as described in `import_model()`.
:param access_token: Optional access token for remote sources.
@ -147,7 +147,7 @@ class ModelInstallServiceBase(ABC):
def import_model(
self,
source: ModelSource,
config: Optional[Dict[str, Any]] = None,
config: Optional[ModelRecordChanges] = None,
) -> ModelInstallJob:
"""Install the indicated model.

8
invokeai/app/services/model_install/model_install_common.py
View File

@ -2,13 +2,14 @@ import re
import traceback
from enum import Enum
from pathlib import Path
from typing import Any, Dict, Literal, Optional, Set, Union
from typing import Literal, Optional, Set, Union
from pydantic import BaseModel, Field, PrivateAttr, field_validator
from pydantic.networks import AnyHttpUrl
from typing_extensions import Annotated
from invokeai.app.services.download import DownloadJob, MultiFileDownloadJob
from invokeai.app.services.model_records import ModelRecordChanges
from invokeai.backend.model_manager import AnyModelConfig, ModelRepoVariant
from invokeai.backend.model_manager.config import ModelSourceType
from invokeai.backend.model_manager.metadata import AnyModelRepoMetadata
@ -133,8 +134,9 @@ class ModelInstallJob(BaseModel):
id: int = Field(description="Unique ID for this job")
status: InstallStatus = Field(default=InstallStatus.WAITING, description="Current status of install process")
error_reason: Optional[str] = Field(default=None, description="Information about why the job failed")
config_in: Dict[str, Any] = Field(
default_factory=dict, description="Configuration information (e.g. 'description') to apply to model."
config_in: ModelRecordChanges = Field(
default_factory=ModelRecordChanges,
description="Configuration information (e.g. 'description') to apply to model.",
)
config_out: Optional[AnyModelConfig] = Field(
default=None, description="After successful installation, this will hold the configuration object."

60
invokeai/app/services/model_install/model_install_default.py
View File

@ -163,26 +163,27 @@ class ModelInstallService(ModelInstallServiceBase):
def register_path(
self,
model_path: Union[Path, str],
config: Optional[Dict[str, Any]] = None,
config: Optional[ModelRecordChanges] = None,
) -> str: # noqa D102
model_path = Path(model_path)
config = config or {}
if not config.get("source"):
config["source"] = model_path.resolve().as_posix()
config["source_type"] = ModelSourceType.Path
config = config or ModelRecordChanges()
if not config.source:
config.source = model_path.resolve().as_posix()
config.source_type = ModelSourceType.Path
return self._register(model_path, config)
def install_path(
self,
model_path: Union[Path, str],
config: Optional[Dict[str, Any]] = None,
config: Optional[ModelRecordChanges] = None,
) -> str: # noqa D102
model_path = Path(model_path)
config = config or {}
config = config or ModelRecordChanges()
info: AnyModelConfig = ModelProbe.probe(
Path(model_path), config.model_dump(), hash_algo=self._app_config.hashing_algorithm
) # type: ignore
info: AnyModelConfig = ModelProbe.probe(Path(model_path), config, hash_algo=self._app_config.hashing_algorithm)
if preferred_name := config.get("name"):
if preferred_name := config.name:
preferred_name = Path(preferred_name).with_suffix(model_path.suffix)
dest_path = (
@ -204,7 +205,7 @@ class ModelInstallService(ModelInstallServiceBase):
def heuristic_import(
self,
source: str,
config: Optional[Dict[str, Any]] = None,
config: Optional[ModelRecordChanges] = None,
access_token: Optional[str] = None,
inplace: Optional[bool] = False,
) -> ModelInstallJob:
@ -216,7 +217,7 @@ class ModelInstallService(ModelInstallServiceBase):
source_obj.access_token = access_token
return self.import_model(source_obj, config)
def import_model(self, source: ModelSource, config: Optional[Dict[str, Any]] = None) -> ModelInstallJob: # noqa D102
def import_model(self, source: ModelSource, config: Optional[ModelRecordChanges] = None) -> ModelInstallJob: # noqa D102
similar_jobs = [x for x in self.list_jobs() if x.source == source and not x.in_terminal_state]
if similar_jobs:
self._logger.warning(f"There is already an active install job for {source}. Not enqueuing.")
@ -318,16 +319,17 @@ class ModelInstallService(ModelInstallServiceBase):
model_path = self._app_config.models_path / model_path
model_path = model_path.resolve()
config: dict[str, Any] = {}
config["name"] = model_name
config["description"] = stanza.get("description")
config = ModelRecordChanges(
name=model_name,
description=stanza.get("description"),
)
legacy_config_path = stanza.get("config")
if legacy_config_path:
# In v3, these paths were relative to the root. Migrate them to be relative to the legacy_conf_dir.
legacy_config_path = self._app_config.root_path / legacy_config_path
if legacy_config_path.is_relative_to(self._app_config.legacy_conf_path):
legacy_config_path = legacy_config_path.relative_to(self._app_config.legacy_conf_path)
config["config_path"] = str(legacy_config_path)
config.config_path = str(legacy_config_path)
try:
id = self.register_path(model_path=model_path, config=config)
self._logger.info(f"Migrated {model_name} with id {id}")
@ -500,11 +502,11 @@ class ModelInstallService(ModelInstallServiceBase):
job.total_bytes = self._stat_size(job.local_path)
job.bytes = job.total_bytes
self._signal_job_running(job)
job.config_in["source"] = str(job.source)
job.config_in["source_type"] = MODEL_SOURCE_TO_TYPE_MAP[job.source.__class__]
job.config_in.source = str(job.source)
job.config_in.source_type = MODEL_SOURCE_TO_TYPE_MAP[job.source.__class__]
# enter the metadata, if there is any
if isinstance(job.source_metadata, (HuggingFaceMetadata)):
job.config_in["source_api_response"] = job.source_metadata.api_response
job.config_in.source_api_response = job.source_metadata.api_response
if job.inplace:
key = self.register_path(job.local_path, job.config_in)
@ -639,11 +641,11 @@ class ModelInstallService(ModelInstallServiceBase):
return new_path
def _register(
self, model_path: Path, config: Optional[Dict[str, Any]] = None, info: Optional[AnyModelConfig] = None
self, model_path: Path, config: Optional[ModelRecordChanges] = None, info: Optional[AnyModelConfig] = None
) -> str:
config = config or {}
config = config or ModelRecordChanges()
info = info or ModelProbe.probe(model_path, config, hash_algo=self._app_config.hashing_algorithm)
info = info or ModelProbe.probe(model_path, config.model_dump(), hash_algo=self._app_config.hashing_algorithm) # type: ignore
model_path = model_path.resolve()
@ -674,11 +676,13 @@ class ModelInstallService(ModelInstallServiceBase):
precision = TorchDevice.choose_torch_dtype()
return ModelRepoVariant.FP16 if precision == torch.float16 else None
def _import_local_model(self, source: LocalModelSource, config: Optional[Dict[str, Any]]) -> ModelInstallJob:
def _import_local_model(
self, source: LocalModelSource, config: Optional[ModelRecordChanges] = None
) -> ModelInstallJob:
return ModelInstallJob(
id=self._next_id(),
source=source,
config_in=config or {},
config_in=config or ModelRecordChanges(),
local_path=Path(source.path),
inplace=source.inplace or False,
)
@ -686,7 +690,7 @@ class ModelInstallService(ModelInstallServiceBase):
def _import_from_hf(
self,
source: HFModelSource,
config: Optional[Dict[str, Any]] = None,
config: Optional[ModelRecordChanges] = None,
) -> ModelInstallJob:
# Add user's cached access token to HuggingFace requests
if source.access_token is None:
@ -702,7 +706,7 @@ class ModelInstallService(ModelInstallServiceBase):
def _import_from_url(
self,
source: URLModelSource,
config: Optional[Dict[str, Any]],
config: Optional[ModelRecordChanges] = None,
) -> ModelInstallJob:
remote_files, metadata = self._remote_files_from_source(source)
return self._import_remote_model(
@ -717,7 +721,7 @@ class ModelInstallService(ModelInstallServiceBase):
source: HFModelSource | URLModelSource,
remote_files: List[RemoteModelFile],
metadata: Optional[AnyModelRepoMetadata],
config: Optional[Dict[str, Any]],
config: Optional[ModelRecordChanges],
) -> ModelInstallJob:
if len(remote_files) == 0:
raise ValueError(f"{source}: No downloadable files found")
@ -730,7 +734,7 @@ class ModelInstallService(ModelInstallServiceBase):
install_job = ModelInstallJob(
id=self._next_id(),
source=source,
config_in=config or {},
config_in=config or ModelRecordChanges(),
source_metadata=metadata,
local_path=destdir, # local path may change once the download has started due to content-disposition handling
bytes=0,

7
invokeai/app/services/model_records/model_records_base.py
View File

@ -18,6 +18,7 @@ from invokeai.backend.model_manager.config import (
ControlAdapterDefaultSettings,
MainModelDefaultSettings,
ModelFormat,
ModelSourceType,
ModelType,
ModelVariantType,
SchedulerPredictionType,
@ -66,10 +67,16 @@ class ModelRecordChanges(BaseModelExcludeNull):
"""A set of changes to apply to a model."""
# Changes applicable to all models
source: Optional[str] = Field(description="original source of the model", default=None)
source_type: Optional[ModelSourceType] = Field(description="type of model source", default=None)
source_api_response: Optional[str] = Field(description="metadata from remote source", default=None)
name: Optional[str] = Field(description="Name of the model.", default=None)
path: Optional[str] = Field(description="Path to the model.", default=None)
description: Optional[str] = Field(description="Model description", default=None)
base: Optional[BaseModelType] = Field(description="The base model.", default=None)
type: Optional[ModelType] = Field(description="Type of model", default=None)
key: Optional[str] = Field(description="Database ID for this model", default=None)
hash: Optional[str] = Field(description="hash of model file", default=None)
trigger_phrases: Optional[set[str]] = Field(description="Set of trigger phrases for this model", default=None)
default_settings: Optional[MainModelDefaultSettings | ControlAdapterDefaultSettings] = Field(
description="Default settings for this model", default=None

1430
invokeai/app/services/workflow_records/default_workflows/MultiDiffusion SD1.5.json Normal file
View File

File diff suppressed because it is too large Load Diff

1568
invokeai/app/services/workflow_records/default_workflows/MultiDiffusion SDXL (Beta).json → invokeai/app/services/workflow_records/default_workflows/MultiDiffusion SDXL.json
View File

File diff suppressed because it is too large Load Diff

4
invokeai/backend/model_manager/config.py
View File

@ -354,7 +354,7 @@ class CLIPVisionDiffusersConfig(DiffusersConfigBase):
"""Model config for CLIPVision."""
type: Literal[ModelType.CLIPVision] = ModelType.CLIPVision
format: Literal[ModelFormat.Diffusers]
format: Literal[ModelFormat.Diffusers] = ModelFormat.Diffusers
@staticmethod
def get_tag() -> Tag:
@ -365,7 +365,7 @@ class T2IAdapterConfig(DiffusersConfigBase, ControlAdapterConfigBase):
"""Model config for T2I."""
type: Literal[ModelType.T2IAdapter] = ModelType.T2IAdapter
format: Literal[ModelFormat.Diffusers]
format: Literal[ModelFormat.Diffusers] = ModelFormat.Diffusers
@staticmethod
def get_tag() -> Tag:

3
invokeai/backend/model_manager/load/model_loaders/stable_diffusion.py
View File

@ -98,6 +98,9 @@ class StableDiffusionDiffusersModel(GenericDiffusersLoader):
ModelVariantType.Normal: StableDiffusionXLPipeline,
ModelVariantType.Inpaint: StableDiffusionXLInpaintPipeline,
},
BaseModelType.StableDiffusionXLRefiner: {
ModelVariantType.Normal: StableDiffusionXLPipeline,
},
}
assert isinstance(config, MainCheckpointConfig)
try:

73
invokeai/backend/model_manager/starter_models.py
View File

@ -187,164 +187,171 @@ STARTER_MODELS: list[StarterModel] = [
# endregion
# region ControlNet
StarterModel(
name="QRCode Monster",
name="QRCode Monster v2 (SD1.5)",
base=BaseModelType.StableDiffusion1,
source="monster-labs/control_v1p_sd15_qrcode_monster",
description="Controlnet model that generates scannable creative QR codes",
source="monster-labs/control_v1p_sd15_qrcode_monster::v2",
description="ControlNet model that generates scannable creative QR codes",
type=ModelType.ControlNet,
),
StarterModel(
name="QRCode Monster (SDXL)",
base=BaseModelType.StableDiffusionXL,
source="monster-labs/control_v1p_sdxl_qrcode_monster",
description="ControlNet model that generates scannable creative QR codes",
type=ModelType.ControlNet,
),
StarterModel(
name="canny",
base=BaseModelType.StableDiffusion1,
source="lllyasviel/control_v11p_sd15_canny",
description="Controlnet weights trained on sd-1.5 with canny conditioning.",
description="ControlNet weights trained on sd-1.5 with canny conditioning.",
type=ModelType.ControlNet,
),
StarterModel(
name="inpaint",
base=BaseModelType.StableDiffusion1,
source="lllyasviel/control_v11p_sd15_inpaint",
description="Controlnet weights trained on sd-1.5 with canny conditioning, inpaint version",
description="ControlNet weights trained on sd-1.5 with canny conditioning, inpaint version",
type=ModelType.ControlNet,
),
StarterModel(
name="mlsd",
base=BaseModelType.StableDiffusion1,
source="lllyasviel/control_v11p_sd15_mlsd",
description="Controlnet weights trained on sd-1.5 with canny conditioning, MLSD version",
description="ControlNet weights trained on sd-1.5 with canny conditioning, MLSD version",
type=ModelType.ControlNet,
),
StarterModel(
name="depth",
base=BaseModelType.StableDiffusion1,
source="lllyasviel/control_v11f1p_sd15_depth",
description="Controlnet weights trained on sd-1.5 with depth conditioning",
description="ControlNet weights trained on sd-1.5 with depth conditioning",
type=ModelType.ControlNet,
),
StarterModel(
name="normal_bae",
base=BaseModelType.StableDiffusion1,
source="lllyasviel/control_v11p_sd15_normalbae",
description="Controlnet weights trained on sd-1.5 with normalbae image conditioning",
description="ControlNet weights trained on sd-1.5 with normalbae image conditioning",
type=ModelType.ControlNet,
),
StarterModel(
name="seg",
base=BaseModelType.StableDiffusion1,
source="lllyasviel/control_v11p_sd15_seg",
description="Controlnet weights trained on sd-1.5 with seg image conditioning",
description="ControlNet weights trained on sd-1.5 with seg image conditioning",
type=ModelType.ControlNet,
),
StarterModel(
name="lineart",
base=BaseModelType.StableDiffusion1,
source="lllyasviel/control_v11p_sd15_lineart",
description="Controlnet weights trained on sd-1.5 with lineart image conditioning",
description="ControlNet weights trained on sd-1.5 with lineart image conditioning",
type=ModelType.ControlNet,
),
StarterModel(
name="lineart_anime",
base=BaseModelType.StableDiffusion1,
source="lllyasviel/control_v11p_sd15s2_lineart_anime",
description="Controlnet weights trained on sd-1.5 with anime image conditioning",
description="ControlNet weights trained on sd-1.5 with anime image conditioning",
type=ModelType.ControlNet,
),
StarterModel(
name="openpose",
base=BaseModelType.StableDiffusion1,
source="lllyasviel/control_v11p_sd15_openpose",
description="Controlnet weights trained on sd-1.5 with openpose image conditioning",
description="ControlNet weights trained on sd-1.5 with openpose image conditioning",
type=ModelType.ControlNet,
),
StarterModel(
name="scribble",
base=BaseModelType.StableDiffusion1,
source="lllyasviel/control_v11p_sd15_scribble",
description="Controlnet weights trained on sd-1.5 with scribble image conditioning",
description="ControlNet weights trained on sd-1.5 with scribble image conditioning",
type=ModelType.ControlNet,
),
StarterModel(
name="softedge",
base=BaseModelType.StableDiffusion1,
source="lllyasviel/control_v11p_sd15_softedge",
description="Controlnet weights trained on sd-1.5 with soft edge conditioning",
description="ControlNet weights trained on sd-1.5 with soft edge conditioning",
type=ModelType.ControlNet,
),
StarterModel(
name="shuffle",
base=BaseModelType.StableDiffusion1,
source="lllyasviel/control_v11e_sd15_shuffle",
description="Controlnet weights trained on sd-1.5 with shuffle image conditioning",
description="ControlNet weights trained on sd-1.5 with shuffle image conditioning",
type=ModelType.ControlNet,
),
StarterModel(
name="tile",
base=BaseModelType.StableDiffusion1,
source="lllyasviel/control_v11f1e_sd15_tile",
description="Controlnet weights trained on sd-1.5 with tiled image conditioning",
description="ControlNet weights trained on sd-1.5 with tiled image conditioning",
type=ModelType.ControlNet,
),
StarterModel(
name="ip2p",
base=BaseModelType.StableDiffusion1,
source="lllyasviel/control_v11e_sd15_ip2p",
description="Controlnet weights trained on sd-1.5 with ip2p conditioning.",
description="ControlNet weights trained on sd-1.5 with ip2p conditioning.",
type=ModelType.ControlNet,
),
StarterModel(
name="canny-sdxl",
base=BaseModelType.StableDiffusionXL,
source="xinsir/controlnet-canny-sdxl-1.0",
description="Controlnet weights trained on sdxl-1.0 with canny conditioning, by Xinsir.",
source="xinsir/controlNet-canny-sdxl-1.0",
description="ControlNet weights trained on sdxl-1.0 with canny conditioning, by Xinsir.",
type=ModelType.ControlNet,
),
StarterModel(
name="depth-sdxl",
base=BaseModelType.StableDiffusionXL,
source="diffusers/controlnet-depth-sdxl-1.0",
description="Controlnet weights trained on sdxl-1.0 with depth conditioning.",
source="diffusers/controlNet-depth-sdxl-1.0",
description="ControlNet weights trained on sdxl-1.0 with depth conditioning.",
type=ModelType.ControlNet,
),
StarterModel(
name="softedge-dexined-sdxl",
base=BaseModelType.StableDiffusionXL,
source="SargeZT/controlnet-sd-xl-1.0-softedge-dexined",
description="Controlnet weights trained on sdxl-1.0 with dexined soft edge preprocessing.",
source="SargeZT/controlNet-sd-xl-1.0-softedge-dexined",
description="ControlNet weights trained on sdxl-1.0 with dexined soft edge preprocessing.",
type=ModelType.ControlNet,
),
StarterModel(
name="depth-16bit-zoe-sdxl",
base=BaseModelType.StableDiffusionXL,
source="SargeZT/controlnet-sd-xl-1.0-depth-16bit-zoe",
description="Controlnet weights trained on sdxl-1.0 with Zoe's preprocessor (16 bits).",
source="SargeZT/controlNet-sd-xl-1.0-depth-16bit-zoe",
description="ControlNet weights trained on sdxl-1.0 with Zoe's preprocessor (16 bits).",
type=ModelType.ControlNet,
),
StarterModel(
name="depth-zoe-sdxl",
base=BaseModelType.StableDiffusionXL,
source="diffusers/controlnet-zoe-depth-sdxl-1.0",
description="Controlnet weights trained on sdxl-1.0 with Zoe's preprocessor (32 bits).",
source="diffusers/controlNet-zoe-depth-sdxl-1.0",
description="ControlNet weights trained on sdxl-1.0 with Zoe's preprocessor (32 bits).",
type=ModelType.ControlNet,
),
StarterModel(
name="openpose-sdxl",
base=BaseModelType.StableDiffusionXL,
source="xinsir/controlnet-openpose-sdxl-1.0",
description="Controlnet weights trained on sdxl-1.0 compatible with the DWPose processor by Xinsir.",
source="xinsir/controlNet-openpose-sdxl-1.0",
description="ControlNet weights trained on sdxl-1.0 compatible with the DWPose processor by Xinsir.",
type=ModelType.ControlNet,
),
StarterModel(
name="scribble-sdxl",
base=BaseModelType.StableDiffusionXL,
source="xinsir/controlnet-scribble-sdxl-1.0",
description="Controlnet weights trained on sdxl-1.0 compatible with various lineart processors and black/white sketches by Xinsir.",
source="xinsir/controlNet-scribble-sdxl-1.0",
description="ControlNet weights trained on sdxl-1.0 compatible with various lineart processors and black/white sketches by Xinsir.",
type=ModelType.ControlNet,
),
StarterModel(
name="tile-sdxl",
base=BaseModelType.StableDiffusionXL,
source="xinsir/controlnet-tile-sdxl-1.0",
description="Controlnet weights trained on sdxl-1.0 with tiled image conditioning",
source="xinsir/controlNet-tile-sdxl-1.0",
description="ControlNet weights trained on sdxl-1.0 with tiled image conditioning",
type=ModelType.ControlNet,
),
# endregion

2
invokeai/backend/stable_diffusion/__init__.py
View File

@ -7,11 +7,9 @@ from invokeai.backend.stable_diffusion.diffusers_pipeline import ( # noqa: F401
StableDiffusionGeneratorPipeline,
)
from invokeai.backend.stable_diffusion.diffusion import InvokeAIDiffuserComponent # noqa: F401
from invokeai.backend.stable_diffusion.seamless import set_seamless # noqa: F401
__all__ = [
"PipelineIntermediateState",
"StableDiffusionGeneratorPipeline",
"InvokeAIDiffuserComponent",
"set_seamless",
]

20
invokeai/backend/stable_diffusion/denoise_context.py
View File

@ -83,47 +83,47 @@ class DenoiseContext:
unet: Optional[UNet2DConditionModel] = None
# Current state of latent-space image in denoising process.
# None until `pre_denoise_loop` callback.
# None until `PRE_DENOISE_LOOP` callback.
# Shape: [batch, channels, latent_height, latent_width]
latents: Optional[torch.Tensor] = None
# Current denoising step index.
# None until `pre_step` callback.
# None until `PRE_STEP` callback.
step_index: Optional[int] = None
# Current denoising step timestep.
# None until `pre_step` callback.
# None until `PRE_STEP` callback.
timestep: Optional[torch.Tensor] = None
# Arguments which will be passed to UNet model.
# Available in `pre_unet`/`post_unet` callbacks, otherwise will be None.
# Available in `PRE_UNET`/`POST_UNET` callbacks, otherwise will be None.
unet_kwargs: Optional[UNetKwargs] = None
# SchedulerOutput class returned from step function(normally, generated by scheduler).
# Supposed to be used only in `post_step` callback, otherwise can be None.
# Supposed to be used only in `POST_STEP` callback, otherwise can be None.
step_output: Optional[SchedulerOutput] = None
# Scaled version of `latents`, which will be passed to unet_kwargs initialization.
# Available in events inside step(between `pre_step` and `post_stop`).
# Available in events inside step(between `PRE_STEP` and `POST_STEP`).
# Shape: [batch, channels, latent_height, latent_width]
latent_model_input: Optional[torch.Tensor] = None
# [TMP] Defines on which conditionings current unet call will be runned.
# Available in `pre_unet`/`post_unet` callbacks, otherwise will be None.
# Available in `PRE_UNET`/`POST_UNET` callbacks, otherwise will be None.
conditioning_mode: Optional[ConditioningMode] = None
# [TMP] Noise predictions from negative conditioning.
# Available in `apply_cfg` and `post_apply_cfg` callbacks, otherwise will be None.
# Available in `POST_COMBINE_NOISE_PREDS` callback, otherwise will be None.
# Shape: [batch, channels, latent_height, latent_width]
negative_noise_pred: Optional[torch.Tensor] = None
# [TMP] Noise predictions from positive conditioning.
# Available in `apply_cfg` and `post_apply_cfg` callbacks, otherwise will be None.
# Available in `POST_COMBINE_NOISE_PREDS` callback, otherwise will be None.
# Shape: [batch, channels, latent_height, latent_width]
positive_noise_pred: Optional[torch.Tensor] = None
# Combined noise prediction from passed conditionings.
# Available in `apply_cfg` and `post_apply_cfg` callbacks, otherwise will be None.
# Available in `POST_COMBINE_NOISE_PREDS` callback, otherwise will be None.
# Shape: [batch, channels, latent_height, latent_width]
noise_pred: Optional[torch.Tensor] = None

14
invokeai/backend/stable_diffusion/diffusion_backend.py
View File

@ -76,12 +76,12 @@ class StableDiffusionBackend:
both_noise_pred = self.run_unet(ctx, ext_manager, ConditioningMode.Both)
ctx.negative_noise_pred, ctx.positive_noise_pred = both_noise_pred.chunk(2)
# ext: override apply_cfg
ctx.noise_pred = self.apply_cfg(ctx)
# ext: override combine_noise_preds
ctx.noise_pred = self.combine_noise_preds(ctx)
# ext: cfg_rescale [modify_noise_prediction]
# TODO: rename
ext_manager.run_callback(ExtensionCallbackType.POST_APPLY_CFG, ctx)
ext_manager.run_callback(ExtensionCallbackType.POST_COMBINE_NOISE_PREDS, ctx)
# compute the previous noisy sample x_t -> x_t-1
step_output = ctx.scheduler.step(ctx.noise_pred, ctx.timestep, ctx.latents, **ctx.inputs.scheduler_step_kwargs)
@ -95,13 +95,15 @@ class StableDiffusionBackend:
return step_output
@staticmethod
def apply_cfg(ctx: DenoiseContext) -> torch.Tensor:
def combine_noise_preds(ctx: DenoiseContext) -> torch.Tensor:
guidance_scale = ctx.inputs.conditioning_data.guidance_scale
if isinstance(guidance_scale, list):
guidance_scale = guidance_scale[ctx.step_index]
return torch.lerp(ctx.negative_noise_pred, ctx.positive_noise_pred, guidance_scale)
# return ctx.negative_noise_pred + guidance_scale * (ctx.positive_noise_pred - ctx.negative_noise_pred)
# Note: Although this `torch.lerp(...)` line is logically equivalent to the current CFG line, it seems to result
# in slightly different outputs. It is suspected that this is caused by small precision differences.
# return torch.lerp(ctx.negative_noise_pred, ctx.positive_noise_pred, guidance_scale)
return ctx.negative_noise_pred + guidance_scale * (ctx.positive_noise_pred - ctx.negative_noise_pred)
def run_unet(self, ctx: DenoiseContext, ext_manager: ExtensionsManager, conditioning_mode: ConditioningMode):
sample = ctx.latent_model_input

2
invokeai/backend/stable_diffusion/extension_callback_type.py
View File

@ -9,4 +9,4 @@ class ExtensionCallbackType(Enum):
POST_STEP = "post_step"
PRE_UNET = "pre_unet"
POST_UNET = "post_unet"
POST_APPLY_CFG = "post_apply_cfg"
POST_COMBINE_NOISE_PREDS = "post_combine_noise_preds"

6
invokeai/backend/stable_diffusion/extensions/base.py
View File

@ -2,7 +2,7 @@ from __future__ import annotations
from contextlib import contextmanager
from dataclasses import dataclass
from typing import TYPE_CHECKING, Callable, Dict, List
from typing import TYPE_CHECKING, Callable, Dict, List, Optional
import torch
from diffusers import UNet2DConditionModel
@ -52,9 +52,9 @@ class ExtensionBase:
return self._callbacks
@contextmanager
def patch_extension(self, context: DenoiseContext):
def patch_extension(self, ctx: DenoiseContext):
yield None
@contextmanager
def patch_unet(self, state_dict: Dict[str, torch.Tensor], unet: UNet2DConditionModel):
def patch_unet(self, unet: UNet2DConditionModel, cached_weights: Optional[Dict[str, torch.Tensor]] = None):
yield None

158
invokeai/backend/stable_diffusion/extensions/controlnet.py Normal file
View File

@ -0,0 +1,158 @@
from __future__ import annotations
import math
from contextlib import contextmanager
from typing import TYPE_CHECKING, List, Optional, Union
import torch
from PIL.Image import Image
from invokeai.app.invocations.constants import LATENT_SCALE_FACTOR
from invokeai.app.util.controlnet_utils import CONTROLNET_MODE_VALUES, CONTROLNET_RESIZE_VALUES, prepare_control_image
from invokeai.backend.stable_diffusion.denoise_context import UNetKwargs
from invokeai.backend.stable_diffusion.diffusion.conditioning_data import ConditioningMode
from invokeai.backend.stable_diffusion.extension_callback_type import ExtensionCallbackType
from invokeai.backend.stable_diffusion.extensions.base import ExtensionBase, callback
if TYPE_CHECKING:
from invokeai.backend.stable_diffusion.denoise_context import DenoiseContext
from invokeai.backend.util.hotfixes import ControlNetModel
class ControlNetExt(ExtensionBase):
def __init__(
self,
model: ControlNetModel,
image: Image,
weight: Union[float, List[float]],
begin_step_percent: float,
end_step_percent: float,
control_mode: CONTROLNET_MODE_VALUES,
resize_mode: CONTROLNET_RESIZE_VALUES,
):
super().__init__()
self._model = model
self._image = image
self._weight = weight
self._begin_step_percent = begin_step_percent
self._end_step_percent = end_step_percent
self._control_mode = control_mode
self._resize_mode = resize_mode
self._image_tensor: Optional[torch.Tensor] = None
@contextmanager
def patch_extension(self, ctx: DenoiseContext):
original_processors = self._model.attn_processors
try:
self._model.set_attn_processor(ctx.inputs.attention_processor_cls())
yield None
finally:
self._model.set_attn_processor(original_processors)
@callback(ExtensionCallbackType.PRE_DENOISE_LOOP)
def resize_image(self, ctx: DenoiseContext):
_, _, latent_height, latent_width = ctx.latents.shape
image_height = latent_height * LATENT_SCALE_FACTOR
image_width = latent_width * LATENT_SCALE_FACTOR
self._image_tensor = prepare_control_image(
image=self._image,
do_classifier_free_guidance=False,
width=image_width,
height=image_height,
device=ctx.latents.device,
dtype=ctx.latents.dtype,
control_mode=self._control_mode,
resize_mode=self._resize_mode,
)
@callback(ExtensionCallbackType.PRE_UNET)
def pre_unet_step(self, ctx: DenoiseContext):
# skip if model not active in current step
total_steps = len(ctx.inputs.timesteps)
first_step = math.floor(self._begin_step_percent * total_steps)
last_step = math.ceil(self._end_step_percent * total_steps)
if ctx.step_index < first_step or ctx.step_index > last_step:
return
# convert mode to internal flags
soft_injection = self._control_mode in ["more_prompt", "more_control"]
cfg_injection = self._control_mode in ["more_control", "unbalanced"]
# no negative conditioning in cfg_injection mode
if cfg_injection:
if ctx.conditioning_mode == ConditioningMode.Negative:
return
down_samples, mid_sample = self._run(ctx, soft_injection, ConditioningMode.Positive)
if ctx.conditioning_mode == ConditioningMode.Both:
# add zeros as samples for negative conditioning
down_samples = [torch.cat([torch.zeros_like(d), d]) for d in down_samples]
mid_sample = torch.cat([torch.zeros_like(mid_sample), mid_sample])
else:
down_samples, mid_sample = self._run(ctx, soft_injection, ctx.conditioning_mode)
if (
ctx.unet_kwargs.down_block_additional_residuals is None
and ctx.unet_kwargs.mid_block_additional_residual is None
):
ctx.unet_kwargs.down_block_additional_residuals = down_samples
ctx.unet_kwargs.mid_block_additional_residual = mid_sample
else:
# add controlnet outputs together if have multiple controlnets
ctx.unet_kwargs.down_block_additional_residuals = [
samples_prev + samples_curr
for samples_prev, samples_curr in zip(
ctx.unet_kwargs.down_block_additional_residuals, down_samples, strict=True
)
]
ctx.unet_kwargs.mid_block_additional_residual += mid_sample
def _run(self, ctx: DenoiseContext, soft_injection: bool, conditioning_mode: ConditioningMode):
total_steps = len(ctx.inputs.timesteps)
model_input = ctx.latent_model_input
image_tensor = self._image_tensor
if conditioning_mode == ConditioningMode.Both:
model_input = torch.cat([model_input] * 2)
image_tensor = torch.cat([image_tensor] * 2)
cn_unet_kwargs = UNetKwargs(
sample=model_input,
timestep=ctx.timestep,
encoder_hidden_states=None, # set later by conditioning
cross_attention_kwargs=dict( # noqa: C408
percent_through=ctx.step_index / total_steps,
),
)
ctx.inputs.conditioning_data.to_unet_kwargs(cn_unet_kwargs, conditioning_mode=conditioning_mode)
# get static weight, or weight corresponding to current step
weight = self._weight
if isinstance(weight, list):
weight = weight[ctx.step_index]
tmp_kwargs = vars(cn_unet_kwargs)
# Remove kwargs not related to ControlNet unet
# ControlNet guidance fields
del tmp_kwargs["down_block_additional_residuals"]
del tmp_kwargs["mid_block_additional_residual"]
# T2i Adapter guidance fields
del tmp_kwargs["down_intrablock_additional_residuals"]
# controlnet(s) inference
down_samples, mid_sample = self._model(
controlnet_cond=image_tensor,
conditioning_scale=weight, # controlnet specific, NOT the guidance scale
guess_mode=soft_injection, # this is still called guess_mode in diffusers ControlNetModel
return_dict=False,
**vars(cn_unet_kwargs),
)
return down_samples, mid_sample

35
invokeai/backend/stable_diffusion/extensions/freeu.py Normal file
View File

@ -0,0 +1,35 @@
from __future__ import annotations
from contextlib import contextmanager
from typing import TYPE_CHECKING, Dict, Optional
import torch
from diffusers import UNet2DConditionModel
from invokeai.backend.stable_diffusion.extensions.base import ExtensionBase
if TYPE_CHECKING:
from invokeai.app.shared.models import FreeUConfig
class FreeUExt(ExtensionBase):
def __init__(
self,
freeu_config: FreeUConfig,
):
super().__init__()
self._freeu_config = freeu_config
@contextmanager
def patch_unet(self, unet: UNet2DConditionModel, cached_weights: Optional[Dict[str, torch.Tensor]] = None):
unet.enable_freeu(
b1=self._freeu_config.b1,
b2=self._freeu_config.b2,
s1=self._freeu_config.s1,
s2=self._freeu_config.s2,
)
try:
yield
finally:
unet.disable_freeu()

36
invokeai/backend/stable_diffusion/extensions/rescale_cfg.py Normal file
View File

@ -0,0 +1,36 @@
from __future__ import annotations
from typing import TYPE_CHECKING
import torch
from invokeai.backend.stable_diffusion.extension_callback_type import ExtensionCallbackType
from invokeai.backend.stable_diffusion.extensions.base import ExtensionBase, callback
if TYPE_CHECKING:
from invokeai.backend.stable_diffusion.denoise_context import DenoiseContext
class RescaleCFGExt(ExtensionBase):
def __init__(self, rescale_multiplier: float):
super().__init__()
self._rescale_multiplier = rescale_multiplier
@staticmethod
def _rescale_cfg(total_noise_pred: torch.Tensor, pos_noise_pred: torch.Tensor, multiplier: float = 0.7):
"""Implementation of Algorithm 2 from https://arxiv.org/pdf/2305.08891.pdf."""
ro_pos = torch.std(pos_noise_pred, dim=(1, 2, 3), keepdim=True)
ro_cfg = torch.std(total_noise_pred, dim=(1, 2, 3), keepdim=True)
x_rescaled = total_noise_pred * (ro_pos / ro_cfg)
x_final = multiplier * x_rescaled + (1.0 - multiplier) * total_noise_pred
return x_final
@callback(ExtensionCallbackType.POST_COMBINE_NOISE_PREDS)
def rescale_noise_pred(self, ctx: DenoiseContext):
if self._rescale_multiplier > 0:
ctx.noise_pred = self._rescale_cfg(
ctx.noise_pred,
ctx.positive_noise_pred,
self._rescale_multiplier,
)

71
invokeai/backend/stable_diffusion/extensions/seamless.py Normal file
View File

@ -0,0 +1,71 @@
from __future__ import annotations
from contextlib import contextmanager
from typing import Callable, Dict, List, Optional, Tuple
import torch
import torch.nn as nn
from diffusers import UNet2DConditionModel
from diffusers.models.lora import LoRACompatibleConv
from invokeai.backend.stable_diffusion.extensions.base import ExtensionBase
class SeamlessExt(ExtensionBase):
def __init__(
self,
seamless_axes: List[str],
):
super().__init__()
self._seamless_axes = seamless_axes
@contextmanager
def patch_unet(self, unet: UNet2DConditionModel, cached_weights: Optional[Dict[str, torch.Tensor]] = None):
with self.static_patch_model(
model=unet,
seamless_axes=self._seamless_axes,
):
yield
@staticmethod
@contextmanager
def static_patch_model(
model: torch.nn.Module,
seamless_axes: List[str],
):
if not seamless_axes:
yield
return
x_mode = "circular" if "x" in seamless_axes else "constant"
y_mode = "circular" if "y" in seamless_axes else "constant"
# override conv_forward
# https://github.com/huggingface/diffusers/issues/556#issuecomment-1993287019
def _conv_forward_asymmetric(
self, input: torch.Tensor, weight: torch.Tensor, bias: Optional[torch.Tensor] = None
):
self.paddingX = (self._reversed_padding_repeated_twice[0], self._reversed_padding_repeated_twice[1], 0, 0)
self.paddingY = (0, 0, self._reversed_padding_repeated_twice[2], self._reversed_padding_repeated_twice[3])
working = torch.nn.functional.pad(input, self.paddingX, mode=x_mode)
working = torch.nn.functional.pad(working, self.paddingY, mode=y_mode)
return torch.nn.functional.conv2d(
working, weight, bias, self.stride, torch.nn.modules.utils._pair(0), self.dilation, self.groups
)
original_layers: List[Tuple[nn.Conv2d, Callable]] = []
try:
for layer in model.modules():
if not isinstance(layer, torch.nn.Conv2d):
continue
if isinstance(layer, LoRACompatibleConv) and layer.lora_layer is None:
layer.lora_layer = lambda *x: 0
original_layers.append((layer, layer._conv_forward))
layer._conv_forward = _conv_forward_asymmetric.__get__(layer, torch.nn.Conv2d)
yield
finally:
for layer, orig_conv_forward in original_layers:
layer._conv_forward = orig_conv_forward

120
invokeai/backend/stable_diffusion/extensions/t2i_adapter.py Normal file
View File

@ -0,0 +1,120 @@
from __future__ import annotations
import math
from typing import TYPE_CHECKING, List, Optional, Union
import torch
from diffusers import T2IAdapter
from PIL.Image import Image
from invokeai.app.util.controlnet_utils import prepare_control_image
from invokeai.backend.model_manager import BaseModelType
from invokeai.backend.stable_diffusion.diffusion.conditioning_data import ConditioningMode
from invokeai.backend.stable_diffusion.extension_callback_type import ExtensionCallbackType
from invokeai.backend.stable_diffusion.extensions.base import ExtensionBase, callback
if TYPE_CHECKING:
from invokeai.app.invocations.model import ModelIdentifierField
from invokeai.app.services.shared.invocation_context import InvocationContext
from invokeai.app.util.controlnet_utils import CONTROLNET_RESIZE_VALUES
from invokeai.backend.stable_diffusion.denoise_context import DenoiseContext
class T2IAdapterExt(ExtensionBase):
def __init__(
self,
node_context: InvocationContext,
model_id: ModelIdentifierField,
image: Image,
weight: Union[float, List[float]],
begin_step_percent: float,
end_step_percent: float,
resize_mode: CONTROLNET_RESIZE_VALUES,
):
super().__init__()
self._node_context = node_context
self._model_id = model_id
self._image = image
self._weight = weight
self._resize_mode = resize_mode
self._begin_step_percent = begin_step_percent
self._end_step_percent = end_step_percent
self._adapter_state: Optional[List[torch.Tensor]] = None
# The max_unet_downscale is the maximum amount that the UNet model downscales the latent image internally.
model_config = self._node_context.models.get_config(self._model_id.key)
if model_config.base == BaseModelType.StableDiffusion1:
self._max_unet_downscale = 8
elif model_config.base == BaseModelType.StableDiffusionXL:
self._max_unet_downscale = 4
else:
raise ValueError(f"Unexpected T2I-Adapter base model type: '{model_config.base}'.")
@callback(ExtensionCallbackType.SETUP)
def setup(self, ctx: DenoiseContext):
t2i_model: T2IAdapter
with self._node_context.models.load(self._model_id) as t2i_model:
_, _, latents_height, latents_width = ctx.inputs.orig_latents.shape
self._adapter_state = self._run_model(
model=t2i_model,
image=self._image,
latents_height=latents_height,
latents_width=latents_width,
)
def _run_model(
self,
model: T2IAdapter,
image: Image,
latents_height: int,
latents_width: int,
):
# Resize the T2I-Adapter input image.
# We select the resize dimensions so that after the T2I-Adapter's total_downscale_factor is applied, the
# result will match the latent image's dimensions after max_unet_downscale is applied.
input_height = latents_height // self._max_unet_downscale * model.total_downscale_factor
input_width = latents_width // self._max_unet_downscale * model.total_downscale_factor
# Note: We have hard-coded `do_classifier_free_guidance=False`. This is because we only want to prepare
# a single image. If CFG is enabled, we will duplicate the resultant tensor after applying the
# T2I-Adapter model.
#
# Note: We re-use the `prepare_control_image(...)` from ControlNet for T2I-Adapter, because it has many
# of the same requirements (e.g. preserving binary masks during resize).
t2i_image = prepare_control_image(
image=image,
do_classifier_free_guidance=False,
width=input_width,
height=input_height,
num_channels=model.config["in_channels"],
device=model.device,
dtype=model.dtype,
resize_mode=self._resize_mode,
)
return model(t2i_image)
@callback(ExtensionCallbackType.PRE_UNET)
def pre_unet_step(self, ctx: DenoiseContext):
# skip if model not active in current step
total_steps = len(ctx.inputs.timesteps)
first_step = math.floor(self._begin_step_percent * total_steps)
last_step = math.ceil(self._end_step_percent * total_steps)
if ctx.step_index < first_step or ctx.step_index > last_step:
return
weight = self._weight
if isinstance(weight, list):
weight = weight[ctx.step_index]
adapter_state = self._adapter_state
if ctx.conditioning_mode == ConditioningMode.Both:
adapter_state = [torch.cat([v] * 2) for v in adapter_state]
if ctx.unet_kwargs.down_intrablock_additional_residuals is None:
ctx.unet_kwargs.down_intrablock_additional_residuals = [v * weight for v in adapter_state]
else:
for i, value in enumerate(adapter_state):
ctx.unet_kwargs.down_intrablock_additional_residuals[i] += value * weight

14
invokeai/backend/stable_diffusion/extensions_manager.py
View File

@ -52,20 +52,24 @@ class ExtensionsManager:
cb.function(ctx)
@contextmanager
def patch_extensions(self, context: DenoiseContext):
def patch_extensions(self, ctx: DenoiseContext):
if self._is_canceled and self._is_canceled():
raise CanceledException
with ExitStack() as exit_stack:
for ext in self._extensions:
exit_stack.enter_context(ext.patch_extension(context))
exit_stack.enter_context(ext.patch_extension(ctx))
yield None
@contextmanager
def patch_unet(self, state_dict: Dict[str, torch.Tensor], unet: UNet2DConditionModel):
def patch_unet(self, unet: UNet2DConditionModel, cached_weights: Optional[Dict[str, torch.Tensor]] = None):
if self._is_canceled and self._is_canceled():
raise CanceledException
# TODO: create logic in PR with extension which uses it
yield None
# TODO: create weight patch logic in PR with extension which uses it
with ExitStack() as exit_stack:
for ext in self._extensions:
exit_stack.enter_context(ext.patch_unet(unet, cached_weights))
yield None

51
invokeai/backend/stable_diffusion/seamless.py
View File

@ -1,51 +0,0 @@
from contextlib import contextmanager
from typing import Callable, List, Optional, Tuple, Union
import torch
import torch.nn as nn
from diffusers.models.autoencoders.autoencoder_kl import AutoencoderKL
from diffusers.models.autoencoders.autoencoder_tiny import AutoencoderTiny
from diffusers.models.lora import LoRACompatibleConv
from diffusers.models.unets.unet_2d_condition import UNet2DConditionModel
@contextmanager
def set_seamless(model: Union[UNet2DConditionModel, AutoencoderKL, AutoencoderTiny], seamless_axes: List[str]):
if not seamless_axes:
yield
return
# override conv_forward
# https://github.com/huggingface/diffusers/issues/556#issuecomment-1993287019
def _conv_forward_asymmetric(self, input: torch.Tensor, weight: torch.Tensor, bias: Optional[torch.Tensor] = None):
self.paddingX = (self._reversed_padding_repeated_twice[0], self._reversed_padding_repeated_twice[1], 0, 0)
self.paddingY = (0, 0, self._reversed_padding_repeated_twice[2], self._reversed_padding_repeated_twice[3])
working = torch.nn.functional.pad(input, self.paddingX, mode=x_mode)
working = torch.nn.functional.pad(working, self.paddingY, mode=y_mode)
return torch.nn.functional.conv2d(
working, weight, bias, self.stride, torch.nn.modules.utils._pair(0), self.dilation, self.groups
)
original_layers: List[Tuple[nn.Conv2d, Callable]] = []
try:
x_mode = "circular" if "x" in seamless_axes else "constant"
y_mode = "circular" if "y" in seamless_axes else "constant"
conv_layers: List[torch.nn.Conv2d] = []
for module in model.modules():
if isinstance(module, torch.nn.Conv2d):
conv_layers.append(module)
for layer in conv_layers:
if isinstance(layer, LoRACompatibleConv) and layer.lora_layer is None:
layer.lora_layer = lambda *x: 0
original_layers.append((layer, layer._conv_forward))
layer._conv_forward = _conv_forward_asymmetric.__get__(layer, torch.nn.Conv2d)
yield
finally:
for layer, orig_conv_forward in original_layers:
layer._conv_forward = orig_conv_forward

3
invokeai/frontend/web/package.json
View File

@ -155,5 +155,8 @@
"vite-plugin-eslint": "^1.8.1",
"vite-tsconfig-paths": "^4.3.2",
"vitest": "^1.6.0"
},
"engines": {
"pnpm": "8"
}
}

6
invokeai/frontend/web/public/locales/ar.json
View File

@ -77,10 +77,6 @@
"title": "استعادة الوجوه",
"desc": "استعادة الصورة الحالية"
},
"upscale": {
"title": "تحسين الحجم",
"desc": "تحسين حجم الصورة الحالية"
},
"showInfo": {
"title": "عرض المعلومات",
"desc": "عرض معلومات البيانات الخاصة بالصورة الحالية"
@ -255,8 +251,6 @@
"type": "نوع",
"strength": "قوة",
"upscaling": "تصغير",
"upscale": "تصغير",
"upscaleImage": "تصغير الصورة",
"scale": "مقياس",
"imageFit": "ملائمة الصورة الأولية لحجم الخرج",
"scaleBeforeProcessing": "تحجيم قبل المعالجة",

6
invokeai/frontend/web/public/locales/de.json
View File

@ -187,10 +187,6 @@
"title": "Gesicht restaurieren",
"desc": "Das aktuelle Bild restaurieren"
},
"upscale": {
"title": "Hochskalieren",
"desc": "Das aktuelle Bild hochskalieren"
},
"showInfo": {
"title": "Info anzeigen",
"desc": "Metadaten des aktuellen Bildes anzeigen"
@ -433,8 +429,6 @@
"type": "Art",
"strength": "Stärke",
"upscaling": "Hochskalierung",
"upscale": "Hochskalieren (Shift + U)",
"upscaleImage": "Bild hochskalieren",
"scale": "Maßstab",
"imageFit": "Ausgangsbild an Ausgabegröße anpassen",
"scaleBeforeProcessing": "Skalieren vor der Verarbeitung",

70
invokeai/frontend/web/public/locales/en.json
View File

@ -32,12 +32,14 @@
"deleteBoardAndImages": "Delete Board and Images",
"deleteBoardOnly": "Delete Board Only",
"deletedBoardsCannotbeRestored": "Deleted boards cannot be restored",
"hideBoards": "Hide Boards",
"loading": "Loading...",
"menuItemAutoAdd": "Auto-add to this Board",
"move": "Move",
"movingImagesToBoard_one": "Moving {{count}} image to board:",
"movingImagesToBoard_other": "Moving {{count}} images to board:",
"myBoard": "My Board",
"noBoards": "No {{boardType}} Boards",
"noMatching": "No matching Boards",
"private": "Private Boards",
"searchBoard": "Search Boards...",
@ -46,6 +48,7 @@
"topMessage": "This board contains images used in the following features:",
"unarchiveBoard": "Unarchive Board",
"uncategorized": "Uncategorized",
"viewBoards": "View Boards",
"downloadBoard": "Download Board",
"imagesWithCount_one": "{{count}} image",
"imagesWithCount_other": "{{count}} images",
@ -102,6 +105,7 @@
"negativePrompt": "Negative Prompt",
"discordLabel": "Discord",
"dontAskMeAgain": "Don't ask me again",
"dontShowMeThese": "Don't show me these",
"editor": "Editor",
"error": "Error",
"file": "File",
@ -373,10 +377,14 @@
"displayBoardSearch": "Display Board Search",
"displaySearch": "Display Search",
"download": "Download",
"exitBoardSearch": "Exit Board Search",
"exitSearch": "Exit Search",
"featuresWillReset": "If you delete this image, those features will immediately be reset.",
"galleryImageSize": "Image Size",
"gallerySettings": "Gallery Settings",
"go": "Go",
"image": "image",
"jump": "Jump",
"loading": "Loading",
"loadMore": "Load More",
"newestFirst": "Newest First",
@ -636,9 +644,9 @@
"title": "Undo Stroke"
},
"unifiedCanvasHotkeys": "Unified Canvas",
"upscale": {
"desc": "Upscale the current image",
"title": "Upscale"
"postProcess": {
"desc": "Process the current image using the selected post-processing model",
"title": "Process Image"
},
"toggleViewer": {
"desc": "Switches between the Image Viewer and workspace for the current tab.",
@ -1027,6 +1035,7 @@
"imageActions": "Image Actions",
"sendToImg2Img": "Send to Image to Image",
"sendToUnifiedCanvas": "Send To Unified Canvas",
"sendToUpscale": "Send To Upscale",
"showOptionsPanel": "Show Side Panel (O or T)",
"shuffle": "Shuffle Seed",
"steps": "Steps",
@ -1034,8 +1043,8 @@
"symmetry": "Symmetry",
"tileSize": "Tile Size",
"type": "Type",
"upscale": "Upscale (Shift + U)",
"upscaleImage": "Upscale Image",
"postProcessing": "Post-Processing (Shift + U)",
"processImage": "Process Image",
"upscaling": "Upscaling",
"useAll": "Use All",
"useSize": "Use Size",
@ -1091,6 +1100,8 @@
"displayInProgress": "Display Progress Images",
"enableImageDebugging": "Enable Image Debugging",
"enableInformationalPopovers": "Enable Informational Popovers",
"informationalPopoversDisabled": "Informational Popovers Disabled",
"informationalPopoversDisabledDesc": "Informational popovers have been disabled. Enable them in Settings.",
"enableInvisibleWatermark": "Enable Invisible Watermark",
"enableNSFWChecker": "Enable NSFW Checker",
"general": "General",
@ -1498,6 +1509,30 @@
"seamlessTilingYAxis": {
"heading": "Seamless Tiling Y Axis",
"paragraphs": ["Seamlessly tile an image along the vertical axis."]
},
"upscaleModel": {
"heading": "Upscale Model",
"paragraphs": [
"The upscale model scales the image to the output size before details are added. Any supported upscale model may be used, but some are specialized for different kinds of images, like photos or line drawings."
]
},
"scale": {
"heading": "Scale",
"paragraphs": [
"Scale controls the output image size, and is based on a multiple of the input image resolution. For example a 2x upscale on a 1024x1024 image would produce a 2048 x 2048 output."
]
},
"creativity": {
"heading": "Creativity",
"paragraphs": [
"Creativity controls the amount of freedom granted to the model when adding details. Low creativity stays close to the original image, while high creativity allows for more change. When using a prompt, high creativity increases the influence of the prompt."
]
},
"structure": {
"heading": "Structure",
"paragraphs": [
"Structure controls how closely the output image will keep to the layout of the original. Low structure allows major changes, while high structure strictly maintains the original composition and layout."
]
}
},
"unifiedCanvas": {
@ -1640,6 +1675,27 @@
"layers_one": "Layer",
"layers_other": "Layers"
},
"upscaling": {
"creativity": "Creativity",
"structure": "Structure",
"upscaleModel": "Upscale Model",
"postProcessingModel": "Post-Processing Model",
"scale": "Scale",
"postProcessingMissingModelWarning": "Visit the <LinkComponent>Model Manager</LinkComponent> to install a post-processing (image to image) model.",
"missingModelsWarning": "Visit the <LinkComponent>Model Manager</LinkComponent> to install the required models:",
"mainModelDesc": "Main model (SD1.5 or SDXL architecture)",
"tileControlNetModelDesc": "Tile ControlNet model for the chosen main model architecture",
"upscaleModelDesc": "Upscale (image to image) model",
"missingUpscaleInitialImage": "Missing initial image for upscaling",
"missingUpscaleModel": "Missing upscale model",
"missingTileControlNetModel": "No valid tile ControlNet models installed"
},
"upsell": {
"inviteTeammates": "Invite Teammates",
"professional": "Professional",
"professionalUpsell": "Available in Invoke’s Professional Edition. Click here or visit invoke.com/pricing for more details.",
"shareAccess": "Share Access"
},
"ui": {
"tabs": {
"generation": "Generation",
@ -1651,7 +1707,9 @@
"models": "Models",
"modelsTab": "$t(ui.tabs.models) $t(common.tab)",
"queue": "Queue",
"queueTab": "$t(ui.tabs.queue) $t(common.tab)"
"queueTab": "$t(ui.tabs.queue) $t(common.tab)",
"upscaling": "Upscaling",
"upscalingTab": "$t(ui.tabs.upscaling) $t(common.tab)"
}
}
}

51
invokeai/frontend/web/public/locales/es.json
View File

@ -151,10 +151,6 @@
"title": "Restaurar rostros",
"desc": "Restaurar rostros en la imagen actual"
},
"upscale": {
"title": "Aumentar resolución",
"desc": "Aumentar la resolución de la imagen actual"
},
"showInfo": {
"title": "Mostrar información",
"desc": "Mostar metadatos de la imagen actual"
@ -360,8 +356,6 @@
"type": "Tipo",
"strength": "Fuerza",
"upscaling": "Aumento de resolución",
"upscale": "Aumentar resolución",
"upscaleImage": "Aumentar la resolución de la imagen",
"scale": "Escala",
"imageFit": "Ajuste tamaño de imagen inicial al tamaño objetivo",
"scaleBeforeProcessing": "Redimensionar antes de procesar",
@ -408,7 +402,12 @@
"showProgressInViewer": "Mostrar las imágenes del progreso en el visor",
"ui": "Interfaz del usuario",
"generation": "Generación",
"beta": "Beta"
"beta": "Beta",
"reloadingIn": "Recargando en",
"intermediatesClearedFailed": "Error limpiando los intermediarios",
"intermediatesCleared_one": "Borrado {{count}} intermediario",
"intermediatesCleared_many": "Borrados {{count}} intermediarios",
"intermediatesCleared_other": "Borrados {{count}} intermediarios"
},
"toast": {
"uploadFailed": "Error al subir archivo",
@ -426,7 +425,12 @@
"parameterSet": "Conjunto de parámetros",
"parameterNotSet": "Parámetro no configurado",
"problemCopyingImage": "No se puede copiar la imagen",
"errorCopied": "Error al copiar"
"errorCopied": "Error al copiar",
"baseModelChanged": "Modelo base cambiado",
"addedToBoard": "Añadido al tablero",
"baseModelChangedCleared_one": "Borrado o desactivado {{count}} submodelo incompatible",
"baseModelChangedCleared_many": "Borrados o desactivados {{count}} submodelos incompatibles",
"baseModelChangedCleared_other": "Borrados o desactivados {{count}} submodelos incompatibles"
},
"tooltip": {
"feature": {
@ -540,7 +544,13 @@
"downloadBoard": "Descargar panel",
"deleteBoardOnly": "Borrar solo el panel",
"myBoard": "Mi panel",
"noMatching": "No hay paneles que coincidan"
"noMatching": "No hay paneles que coincidan",
"imagesWithCount_one": "{{count}} imagen",
"imagesWithCount_many": "{{count}} imágenes",
"imagesWithCount_other": "{{count}} imágenes",
"assetsWithCount_one": "{{count}} activo",
"assetsWithCount_many": "{{count}} activos",
"assetsWithCount_other": "{{count}} activos"
},
"accordions": {
"compositing": {
@ -590,6 +600,27 @@
"balanced": "Equilibrado",
"beginEndStepPercent": "Inicio / Final Porcentaje de pasos",
"detectResolution": "Detectar resolución",
"beginEndStepPercentShort": "Inicio / Final %"
"beginEndStepPercentShort": "Inicio / Final %",
"t2i_adapter": "$t(controlnet.controlAdapter_one) #{{number}} ($t(common.t2iAdapter))",
"controlnet": "$t(controlnet.controlAdapter_one) #{{number}} ($t(common.controlNet))",
"ip_adapter": "$t(controlnet.controlAdapter_one) #{{number}} ($t(common.ipAdapter))",
"addControlNet": "Añadir $t(common.controlNet)",
"addIPAdapter": "Añadir $t(common.ipAdapter)",
"controlAdapter_one": "Adaptador de control",
"controlAdapter_many": "Adaptadores de control",
"controlAdapter_other": "Adaptadores de control",
"addT2IAdapter": "Añadir $t(common.t2iAdapter)"
},
"queue": {
"back": "Atrás",
"front": "Delante",
"batchQueuedDesc_one": "Se agregó {{count}} sesión a {{direction}} la cola",
"batchQueuedDesc_many": "Se agregaron {{count}} sesiones a {{direction}} la cola",
"batchQueuedDesc_other": "Se agregaron {{count}} sesiones a {{direction}} la cola"
},
"upsell": {
"inviteTeammates": "Invitar compañeros de equipo",
"shareAccess": "Compartir acceso",
"professionalUpsell": "Disponible en la edición profesional de Invoke. Haz clic aquí o visita invoke.com/pricing para obtener más detalles."
}
}

6
invokeai/frontend/web/public/locales/fr.json
View File

@ -130,10 +130,6 @@
"title": "Restaurer les visages",
"desc": "Restaurer l'image actuelle"
},
"upscale": {
"title": "Agrandir",
"desc": "Agrandir l'image actuelle"
},
"showInfo": {
"title": "Afficher les informations",
"desc": "Afficher les informations de métadonnées de l'image actuelle"
@ -308,8 +304,6 @@
"type": "Type",
"strength": "Force",
"upscaling": "Agrandissement",
"upscale": "Agrandir",
"upscaleImage": "Image en Agrandissement",
"scale": "Echelle",
"imageFit": "Ajuster Image Initiale à la Taille de Sortie",
"scaleBeforeProcessing": "Echelle Avant Traitement",

6
invokeai/frontend/web/public/locales/he.json
View File

@ -90,10 +90,6 @@
"desc": "שחזור התמונה הנוכחית",
"title": "שחזור פרצופים"
},
"upscale": {
"title": "הגדלת קנה מידה",
"desc": "הגדל את התמונה הנוכחית"
},
"showInfo": {
"title": "הצג מידע",
"desc": "הצגת פרטי מטא-נתונים של התמונה הנוכחית"
@ -263,8 +259,6 @@
"seed": "זרע",
"type": "סוג",
"strength": "חוזק",
"upscale": "הגדלת קנה מידה",
"upscaleImage": "הגדלת קנה מידת התמונה",
"denoisingStrength": "חוזק מנטרל הרעש",
"scaleBeforeProcessing": "שנה קנה מידה לפני עיבוד",
"scaledWidth": "קנה מידה לאחר שינוי W",

51
invokeai/frontend/web/public/locales/it.json
View File

@ -150,7 +150,11 @@
"showArchivedBoards": "Mostra le bacheche archiviate",
"searchImages": "Ricerca per metadati",
"displayBoardSearch": "Mostra la ricerca nelle Bacheche",
"displaySearch": "Mostra la ricerca"
"displaySearch": "Mostra la ricerca",
"selectAllOnPage": "Seleziona tutto nella pagina",
"selectAllOnBoard": "Seleziona tutto nella bacheca",
"exitBoardSearch": "Esci da Ricerca bacheca",
"exitSearch": "Esci dalla ricerca"
},
"hotkeys": {
"keyboardShortcuts": "Tasti di scelta rapida",
@ -210,10 +214,6 @@
"title": "Restaura volti",
"desc": "Restaura l'immagine corrente"
},
"upscale": {
"title": "Amplia",
"desc": "Amplia l'immagine corrente"
},
"showInfo": {
"title": "Mostra informazioni",
"desc": "Mostra le informazioni sui metadati dell'immagine corrente"
@ -377,6 +377,10 @@
"toggleViewer": {
"title": "Attiva/disattiva il visualizzatore di immagini",
"desc": "Passa dal visualizzatore immagini all'area di lavoro per la scheda corrente."
},
"postProcess": {
"desc": "Elabora l'immagine corrente utilizzando il modello di post-elaborazione selezionato",
"title": "Elabora immagine"
}
},
"modelManager": {
@ -505,8 +509,6 @@
"type": "Tipo",
"strength": "Forza",
"upscaling": "Ampliamento",
"upscale": "Amplia (Shift + U)",
"upscaleImage": "Amplia Immagine",
"scale": "Scala",
"imageFit": "Adatta l'immagine iniziale alle dimensioni di output",
"scaleBeforeProcessing": "Scala prima dell'elaborazione",
@ -591,7 +593,10 @@
"infillColorValue": "Colore di riempimento",
"globalSettings": "Impostazioni globali",
"globalPositivePromptPlaceholder": "Prompt positivo globale",
"globalNegativePromptPlaceholder": "Prompt negativo globale"
"globalNegativePromptPlaceholder": "Prompt negativo globale",
"processImage": "Elabora Immagine",
"sendToUpscale": "Invia a Ampliare",
"postProcessing": "Post-elaborazione (Shift + U)"
},
"settings": {
"models": "Modelli",
@ -964,7 +969,10 @@
"boards": "Bacheche",
"private": "Bacheche private",
"shared": "Bacheche condivise",
"addPrivateBoard": "Aggiungi una Bacheca Privata"
"addPrivateBoard": "Aggiungi una Bacheca Privata",
"noBoards": "Nessuna bacheca {{boardType}}",
"hideBoards": "Nascondi bacheche",
"viewBoards": "Visualizza bacheche"
},
"controlnet": {
"contentShuffleDescription": "Rimescola il contenuto di un'immagine",
@ -1684,7 +1692,30 @@
"models": "Modelli",
"modelsTab": "$t(ui.tabs.models) $t(common.tab)",
"queue": "Coda",
"queueTab": "$t(ui.tabs.queue) $t(common.tab)"
"queueTab": "$t(ui.tabs.queue) $t(common.tab)",
"upscaling": "Ampliamento",
"upscalingTab": "$t(ui.tabs.upscaling) $t(common.tab)"
}
},
"upscaling": {
"creativity": "Creatività",
"structure": "Struttura",
"upscaleModel": "Modello di Ampliamento",
"scale": "Scala",
"missingModelsWarning": "Visita <LinkComponent>Gestione modelli</LinkComponent> per installare i modelli richiesti:",
"mainModelDesc": "Modello principale (architettura SD1.5 o SDXL)",
"tileControlNetModelDesc": "Modello Tile ControlNet per l'architettura del modello principale scelto",
"upscaleModelDesc": "Modello per l'ampliamento (da immagine a immagine)",
"missingUpscaleInitialImage": "Immagine iniziale mancante per l'ampliamento",
"missingUpscaleModel": "Modello per l’ampliamento mancante",
"missingTileControlNetModel": "Nessun modello ControlNet Tile valido installato",
"postProcessingModel": "Modello di post-elaborazione",
"postProcessingMissingModelWarning": "Visita <LinkComponent>Gestione modelli</LinkComponent> per installare un modello di post-elaborazione (da immagine a immagine)."
},
"upsell": {
"inviteTeammates": "Invita collaboratori",
"shareAccess": "Condividi l'accesso",
"professional": "Professionale",
"professionalUpsell": "Disponibile nell'edizione Professional di Invoke. Fai clic qui o visita invoke.com/pricing per ulteriori dettagli."
}
}

6
invokeai/frontend/web/public/locales/ja.json
View File

@ -199,10 +199,6 @@
"title": "顔の修復",
"desc": "現在の画像を修復"
},
"upscale": {
"title": "アップスケール",
"desc": "現在の画像をアップスケール"
},
"showInfo": {
"title": "情報を見る",
"desc": "現在の画像のメタデータ情報を表示"
@ -427,8 +423,6 @@
"shuffle": "シャッフル",
"strength": "強度",
"upscaling": "アップスケーリング",
"upscale": "アップスケール",
"upscaleImage": "画像をアップスケール",
"scale": "Scale",
"scaleBeforeProcessing": "処理前のスケール",
"scaledWidth": "幅のスケール",

4
invokeai/frontend/web/public/locales/ko.json
View File

@ -258,10 +258,6 @@
"desc": "캔버스 브러시를 선택",
"title": "브러시 선택"
},
"upscale": {
"desc": "현재 이미지를 업스케일",
"title": "업스케일"
},
"previousImage": {
"title": "이전 이미지",
"desc": "갤러리에 이전 이미지 표시"

6
invokeai/frontend/web/public/locales/nl.json
View File

@ -168,10 +168,6 @@
"title": "Herstel gezichten",
"desc": "Herstelt de huidige afbeelding"
},
"upscale": {
"title": "Schaal op",
"desc": "Schaalt de huidige afbeelding op"
},
"showInfo": {
"title": "Toon info",
"desc": "Toont de metagegevens van de huidige afbeelding"
@ -412,8 +408,6 @@
"type": "Soort",
"strength": "Sterkte",
"upscaling": "Opschalen",
"upscale": "Vergroot (Shift + U)",
"upscaleImage": "Schaal afbeelding op",
"scale": "Schaal",
"imageFit": "Pas initiële afbeelding in uitvoergrootte",
"scaleBeforeProcessing": "Schalen voor verwerking",

6
invokeai/frontend/web/public/locales/pl.json
View File

@ -78,10 +78,6 @@
"title": "Popraw twarze",
"desc": "Uruchamia proces poprawiania twarzy dla aktywnego obrazu"
},
"upscale": {
"title": "Powiększ",
"desc": "Uruchamia proces powiększania aktywnego obrazu"
},
"showInfo": {
"title": "Pokaż informacje",
"desc": "Pokazuje metadane zapisane w aktywnym obrazie"
@ -232,8 +228,6 @@
"type": "Metoda",
"strength": "Siła",
"upscaling": "Powiększanie",
"upscale": "Powiększ",
"upscaleImage": "Powiększ obraz",
"scale": "Skala",
"imageFit": "Przeskaluj oryginalny obraz",
"scaleBeforeProcessing": "Tryb skalowania",

6
invokeai/frontend/web/public/locales/pt.json
View File

@ -160,10 +160,6 @@
"title": "Restaurar Rostos",
"desc": "Restaurar a imagem atual"
},
"upscale": {
"title": "Redimensionar",
"desc": "Redimensionar a imagem atual"
},
"showInfo": {
"title": "Mostrar Informações",
"desc": "Mostrar metadados de informações da imagem atual"
@ -275,8 +271,6 @@
"showOptionsPanel": "Mostrar Painel de Opções",
"strength": "Força",
"upscaling": "Redimensionando",
"upscale": "Redimensionar",
"upscaleImage": "Redimensionar Imagem",
"scaleBeforeProcessing": "Escala Antes do Processamento",
"images": "Imagems",
"steps": "Passos",

6
invokeai/frontend/web/public/locales/pt_BR.json
View File

@ -80,10 +80,6 @@
"title": "Restaurar Rostos",
"desc": "Restaurar a imagem atual"
},
"upscale": {
"title": "Redimensionar",
"desc": "Redimensionar a imagem atual"
},
"showInfo": {
"title": "Mostrar Informações",
"desc": "Mostrar metadados de informações da imagem atual"
@ -268,8 +264,6 @@
"type": "Tipo",
"strength": "Força",
"upscaling": "Redimensionando",
"upscale": "Redimensionar",
"upscaleImage": "Redimensionar Imagem",
"scale": "Escala",
"imageFit": "Caber Imagem Inicial No Tamanho de Saída",
"scaleBeforeProcessing": "Escala Antes do Processamento",

6
invokeai/frontend/web/public/locales/ru.json
View File

@ -214,10 +214,6 @@
"title": "Восстановить лица",
"desc": "Восстановить лица на текущем изображении"
},
"upscale": {
"title": "Увеличение",
"desc": "Увеличить текущеее изображение"
},
"showInfo": {
"title": "Показать метаданные",
"desc": "Показать метаданные из текущего изображения"
@ -512,8 +508,6 @@
"type": "Тип",
"strength": "Сила",
"upscaling": "Увеличение",
"upscale": "Увеличить",
"upscaleImage": "Увеличить изображение",
"scale": "Масштаб",
"imageFit": "Уместить изображение",
"scaleBeforeProcessing": "Масштабировать",

4
invokeai/frontend/web/public/locales/sv.json
View File

@ -90,10 +90,6 @@
"title": "Återskapa ansikten",
"desc": "Återskapa nuvarande bild"
},
"upscale": {
"title": "Skala upp",
"desc": "Skala upp nuvarande bild"
},
"showInfo": {
"title": "Visa info",
"desc": "Visa metadata för nuvarande bild"

6
invokeai/frontend/web/public/locales/tr.json
View File

@ -416,10 +416,6 @@
"desc": "Maske/Taban katmanları arasında geçiş yapar",
"title": "Katmanı Gizle-Göster"
},
"upscale": {
"title": "Büyüt",
"desc": "Seçili görseli büyüt"
},
"setSeed": {
"title": "Tohumu Kullan",
"desc": "Seçili görselin tohumunu kullan"
@ -641,7 +637,6 @@
"copyImage": "Görseli Kopyala",
"height": "Boy",
"width": "En",
"upscale": "Büyüt (Shift + U)",
"useSize": "Boyutu Kullan",
"symmetry": "Bakışım",
"tileSize": "Döşeme Boyutu",
@ -657,7 +652,6 @@
"showOptionsPanel": "Yan Paneli Göster (O ya da T)",
"shuffle": "Kar",
"usePrompt": "İstemi Kullan",
"upscaleImage": "Görseli Büyüt",
"setToOptimalSizeTooSmall": "$t(parameters.setToOptimalSize) (çok küçük olabilir)",
"setToOptimalSizeTooLarge": "$t(parameters.setToOptimalSize) (çok büyük olabilir)",
"cfgRescaleMultiplier": "CFG Rescale Çarpanı",

6
invokeai/frontend/web/public/locales/uk.json
View File

@ -85,10 +85,6 @@
"title": "Відновити обличчя",
"desc": "Відновити обличчя на поточному зображенні"
},
"upscale": {
"title": "Збільшення",
"desc": "Збільшити поточне зображення"
},
"showInfo": {
"title": "Показати метадані",
"desc": "Показати метадані з поточного зображення"
@ -276,8 +272,6 @@
"type": "Тип",
"strength": "Сила",
"upscaling": "Збільшення",
"upscale": "Збільшити",
"upscaleImage": "Збільшити зображення",
"scale": "Масштаб",
"imageFit": "Вмістити зображення",
"scaleBeforeProcessing": "Масштабувати",

6
invokeai/frontend/web/public/locales/zh_CN.json
View File

@ -193,10 +193,6 @@
"title": "面部修复",
"desc": "对当前图像进行面部修复"
},
"upscale": {
"title": "放大",
"desc": "对当前图像进行放大"
},
"showInfo": {
"title": "显示信息",
"desc": "显示当前图像的元数据"
@ -422,8 +418,6 @@
"type": "种类",
"strength": "强度",
"upscaling": "放大",
"upscale": "放大 (Shift + U)",
"upscaleImage": "放大图像",
"scale": "等级",
"imageFit": "使生成图像长宽适配初始图像",
"scaleBeforeProcessing": "处理前缩放",

6
invokeai/frontend/web/src/app/store/middleware/listenerMiddleware/index.ts
View File

@ -1,5 +1,6 @@
import type { TypedStartListening } from '@reduxjs/toolkit';
import { createListenerMiddleware } from '@reduxjs/toolkit';
import { addAdHocPostProcessingRequestedListener } from 'app/store/middleware/listenerMiddleware/listeners/addAdHocPostProcessingRequestedListener';
import { addCommitStagingAreaImageListener } from 'app/store/middleware/listenerMiddleware/listeners/addCommitStagingAreaImageListener';
import { addAnyEnqueuedListener } from 'app/store/middleware/listenerMiddleware/listeners/anyEnqueued';
import { addAppConfigReceivedListener } from 'app/store/middleware/listenerMiddleware/listeners/appConfigReceived';
@ -47,11 +48,11 @@ import { addModelLoadEventListener } from 'app/store/middleware/listenerMiddlewa
import { addSocketQueueItemStatusChangedEventListener } from 'app/store/middleware/listenerMiddleware/listeners/socketio/socketQueueItemStatusChanged';
import { addStagingAreaImageSavedListener } from 'app/store/middleware/listenerMiddleware/listeners/stagingAreaImageSaved';
import { addUpdateAllNodesRequestedListener } from 'app/store/middleware/listenerMiddleware/listeners/updateAllNodesRequested';
import { addUpscaleRequestedListener } from 'app/store/middleware/listenerMiddleware/listeners/upscaleRequested';
import { addWorkflowLoadRequestedListener } from 'app/store/middleware/listenerMiddleware/listeners/workflowLoadRequested';
import type { AppDispatch, RootState } from 'app/store/store';
import { addArchivedOrDeletedBoardListener } from './listeners/addArchivedOrDeletedBoardListener';
import { addEnqueueRequestedUpscale } from './listeners/enqueueRequestedUpscale';
export const listenerMiddleware = createListenerMiddleware();
@ -85,6 +86,7 @@ addGalleryOffsetChangedListener(startAppListening);
addEnqueueRequestedCanvasListener(startAppListening);
addEnqueueRequestedNodes(startAppListening);
addEnqueueRequestedLinear(startAppListening);
addEnqueueRequestedUpscale(startAppListening);
addAnyEnqueuedListener(startAppListening);
addBatchEnqueuedListener(startAppListening);
@ -140,7 +142,7 @@ addModelsLoadedListener(startAppListening);
addAppConfigReceivedListener(startAppListening);
// Ad-hoc upscale workflwo
addUpscaleRequestedListener(startAppListening);
addAdHocPostProcessingRequestedListener(startAppListening);
// Prompts
addDynamicPromptsListener(startAppListening);

30
invokeai/frontend/web/src/app/store/middleware/listenerMiddleware/listeners/upscaleRequested.ts → invokeai/frontend/web/src/app/store/middleware/listenerMiddleware/listeners/addAdHocPostProcessingRequestedListener.ts
View File

@ -2,46 +2,28 @@ import { createAction } from '@reduxjs/toolkit';
import { logger } from 'app/logging/logger';
import type { AppStartListening } from 'app/store/middleware/listenerMiddleware';
import { parseify } from 'common/util/serialize';
import { buildAdHocUpscaleGraph } from 'features/nodes/util/graph/buildAdHocUpscaleGraph';
import { createIsAllowedToUpscaleSelector } from 'features/parameters/hooks/useIsAllowedToUpscale';
import { buildAdHocPostProcessingGraph } from 'features/nodes/util/graph/buildAdHocPostProcessingGraph';
import { toast } from 'features/toast/toast';
import { t } from 'i18next';
import { queueApi } from 'services/api/endpoints/queue';
import type { BatchConfig, ImageDTO } from 'services/api/types';
export const upscaleRequested = createAction<{ imageDTO: ImageDTO }>(`upscale/upscaleRequested`);
export const adHocPostProcessingRequested = createAction<{ imageDTO: ImageDTO }>(`upscaling/postProcessingRequested`);
export const addUpscaleRequestedListener = (startAppListening: AppStartListening) => {
export const addAdHocPostProcessingRequestedListener = (startAppListening: AppStartListening) => {
startAppListening({
actionCreator: upscaleRequested,
actionCreator: adHocPostProcessingRequested,
effect: async (action, { dispatch, getState }) => {
const log = logger('session');
const { imageDTO } = action.payload;
const { image_name } = imageDTO;
const state = getState();
const { isAllowedToUpscale, detailTKey } = createIsAllowedToUpscaleSelector(imageDTO)(state);
// if we can't upscale, show a toast and return
if (!isAllowedToUpscale) {
log.error(
{ imageDTO },
t(detailTKey ?? 'parameters.isAllowedToUpscale.tooLarge') // should never coalesce
);
toast({
id: 'NOT_ALLOWED_TO_UPSCALE',
title: t(detailTKey ?? 'parameters.isAllowedToUpscale.tooLarge'), // should never coalesce
status: 'error',
});
return;
}
const enqueueBatchArg: BatchConfig = {
prepend: true,
batch: {
graph: buildAdHocUpscaleGraph({
image_name,
graph: await buildAdHocPostProcessingGraph({
image: imageDTO,
state,
}),
runs: 1,

40
invokeai/frontend/web/src/app/store/middleware/listenerMiddleware/listeners/addArchivedOrDeletedBoardListener.ts
View File

@ -10,32 +10,32 @@ import {
import { boardsApi } from 'services/api/endpoints/boards';
import { imagesApi } from 'services/api/endpoints/images';
// Type inference doesn't work for this if you inline it in the listener for some reason
const matchAnyBoardDeleted = isAnyOf(
imagesApi.endpoints.deleteBoard.matchFulfilled,
imagesApi.endpoints.deleteBoardAndImages.matchFulfilled
);
export const addArchivedOrDeletedBoardListener = (startAppListening: AppStartListening) => {
/**
* The auto-add board shouldn't be set to an archived board or deleted board. When we archive a board, delete
* a board, or change a the archived board visibility flag, we may need to reset the auto-add board.
*/
startAppListening({
matcher: isAnyOf(
// If a board is deleted, we'll need to reset the auto-add board
imagesApi.endpoints.deleteBoard.matchFulfilled,
imagesApi.endpoints.deleteBoardAndImages.matchFulfilled
),
matcher: matchAnyBoardDeleted,
effect: async (action, { dispatch, getState }) => {
const state = getState();
const queryArgs = selectListBoardsQueryArgs(state);
const queryResult = boardsApi.endpoints.listAllBoards.select(queryArgs)(state);
const deletedBoardId = action.meta.arg.originalArgs;
const { autoAddBoardId, selectedBoardId } = state.gallery;
if (!queryResult.data) {
return;
}
if (!queryResult.data.find((board) => board.board_id === selectedBoardId)) {
// If the deleted board was currently selected, we should reset the selected board to uncategorized
if (deletedBoardId === selectedBoardId) {
dispatch(boardIdSelected({ boardId: 'none' }));
dispatch(galleryViewChanged('images'));
}
if (!queryResult.data.find((board) => board.board_id === autoAddBoardId)) {
// If the deleted board was selected for auto-add, we should reset the auto-add board to uncategorized
if (deletedBoardId === autoAddBoardId) {
dispatch(autoAddBoardIdChanged('none'));
}
},
@ -46,14 +46,8 @@ export const addArchivedOrDeletedBoardListener = (startAppListening: AppStartLis
matcher: boardsApi.endpoints.updateBoard.matchFulfilled,
effect: async (action, { dispatch, getState }) => {
const state = getState();
const queryArgs = selectListBoardsQueryArgs(state);
const queryResult = boardsApi.endpoints.listAllBoards.select(queryArgs)(state);
const { shouldShowArchivedBoards } = state.gallery;
if (!queryResult.data) {
return;
}
const wasArchived = action.meta.arg.originalArgs.changes.archived === true;
if (wasArchived && !shouldShowArchivedBoards) {
@ -71,7 +65,7 @@ export const addArchivedOrDeletedBoardListener = (startAppListening: AppStartLis
const shouldShowArchivedBoards = action.payload;
// We only need to take action if we have just hidden archived boards.
if (!shouldShowArchivedBoards) {
if (shouldShowArchivedBoards) {
return;
}
@ -86,14 +80,16 @@ export const addArchivedOrDeletedBoardListener = (startAppListening: AppStartLis
// Handle the case where selected board is archived
const selectedBoard = queryResult.data.find((b) => b.board_id === selectedBoardId);
if (selectedBoard && selectedBoard.archived) {
if (!selectedBoard || selectedBoard.archived) {
// If we can't find the selected board or it's archived, we should reset the selected board to uncategorized
dispatch(boardIdSelected({ boardId: 'none' }));
dispatch(galleryViewChanged('images'));
}
// Handle the case where auto-add board is archived
const autoAddBoard = queryResult.data.find((b) => b.board_id === autoAddBoardId);
if (autoAddBoard && autoAddBoard.archived) {
if (!autoAddBoard || autoAddBoard.archived) {
// If we can't find the auto-add board or it's archived, we should reset the selected board to uncategorized
dispatch(autoAddBoardIdChanged('none'));
}
},

36
invokeai/frontend/web/src/app/store/middleware/listenerMiddleware/listeners/enqueueRequestedUpscale.ts Normal file
View File

@ -0,0 +1,36 @@
import { enqueueRequested } from 'app/store/actions';
import type { AppStartListening } from 'app/store/middleware/listenerMiddleware';
import { isImageViewerOpenChanged } from 'features/gallery/store/gallerySlice';
import { prepareLinearUIBatch } from 'features/nodes/util/graph/buildLinearBatchConfig';
import { buildMultidiffusionUpscaleGraph } from 'features/nodes/util/graph/buildMultidiffusionUpscaleGraph';
import { queueApi } from 'services/api/endpoints/queue';
export const addEnqueueRequestedUpscale = (startAppListening: AppStartListening) => {
startAppListening({
predicate: (action): action is ReturnType<typeof enqueueRequested> =>
enqueueRequested.match(action) && action.payload.tabName === 'upscaling',
effect: async (action, { getState, dispatch }) => {
const state = getState();
const { shouldShowProgressInViewer } = state.ui;
const { prepend } = action.payload;
const graph = await buildMultidiffusionUpscaleGraph(state);
const batchConfig = prepareLinearUIBatch(state, graph, prepend);
const req = dispatch(
queueApi.endpoints.enqueueBatch.initiate(batchConfig, {
fixedCacheKey: 'enqueueBatch',
})
);
try {
await req.unwrap();
if (shouldShowProgressInViewer) {
dispatch(isImageViewerOpenChanged(true));
}
} finally {
req.reset();
}
},
});
};

15
invokeai/frontend/web/src/app/store/middleware/listenerMiddleware/listeners/imageDropped.ts
View File

@ -23,6 +23,7 @@ import {
} from 'features/gallery/store/gallerySlice';
import { fieldImageValueChanged } from 'features/nodes/store/nodesSlice';
import { selectOptimalDimension } from 'features/parameters/store/generationSlice';
import { upscaleInitialImageChanged } from 'features/parameters/store/upscaleSlice';
import { imagesApi } from 'services/api/endpoints/images';
export const dndDropped = createAction<{
@ -243,6 +244,20 @@ export const addImageDroppedListener = (startAppListening: AppStartListening) =>
return;
}
/**
* Image dropped on upscale initial image
*/
if (
overData.actionType === 'SET_UPSCALE_INITIAL_IMAGE' &&
activeData.payloadType === 'IMAGE_DTO' &&
activeData.payload.imageDTO
) {
const { imageDTO } = activeData.payload;
dispatch(upscaleInitialImageChanged(imageDTO));
return;
}
/**
* Multiple images dropped on user board
*/

10
invokeai/frontend/web/src/app/store/middleware/listenerMiddleware/listeners/imageUploaded.ts
View File

@ -14,6 +14,7 @@ import {
import { selectListBoardsQueryArgs } from 'features/gallery/store/gallerySelectors';
import { fieldImageValueChanged } from 'features/nodes/store/nodesSlice';
import { selectOptimalDimension } from 'features/parameters/store/generationSlice';
import { upscaleInitialImageChanged } from 'features/parameters/store/upscaleSlice';
import { toast } from 'features/toast/toast';
import { t } from 'i18next';
import { omit } from 'lodash-es';
@ -89,6 +90,15 @@ export const addImageUploadedFulfilledListener = (startAppListening: AppStartLis
return;
}
if (postUploadAction?.type === 'SET_UPSCALE_INITIAL_IMAGE') {
dispatch(upscaleInitialImageChanged(imageDTO));
toast({
...DEFAULT_UPLOADED_TOAST,
description: 'set as upscale initial image',
});
return;
}
if (postUploadAction?.type === 'SET_CONTROL_ADAPTER_IMAGE') {
const { id } = postUploadAction;
dispatch(

31
invokeai/frontend/web/src/app/store/middleware/listenerMiddleware/listeners/modelsLoaded.ts
View File

@ -10,6 +10,7 @@ import { heightChanged, widthChanged } from 'features/controlLayers/store/contro
import { loraRemoved } from 'features/lora/store/loraSlice';
import { calculateNewSize } from 'features/parameters/components/ImageSize/calculateNewSize';
import { modelChanged, vaeSelected } from 'features/parameters/store/generationSlice';
import { postProcessingModelChanged, upscaleModelChanged } from 'features/parameters/store/upscaleSlice';
import { zParameterModel, zParameterVAEModel } from 'features/parameters/types/parameterSchemas';
import { getIsSizeOptimal, getOptimalDimension } from 'features/parameters/util/optimalDimension';
import { refinerModelChanged } from 'features/sdxl/store/sdxlSlice';
@ -17,7 +18,12 @@ import { forEach } from 'lodash-es';
import type { Logger } from 'roarr';
import { modelConfigsAdapterSelectors, modelsApi } from 'services/api/endpoints/models';
import type { AnyModelConfig } from 'services/api/types';
import { isNonRefinerMainModelConfig, isRefinerMainModelModelConfig, isVAEModelConfig } from 'services/api/types';
import {
isNonRefinerMainModelConfig,
isRefinerMainModelModelConfig,
isSpandrelImageToImageModelConfig,
isVAEModelConfig,
} from 'services/api/types';
export const addModelsLoadedListener = (startAppListening: AppStartListening) => {
startAppListening({
@ -36,6 +42,7 @@ export const addModelsLoadedListener = (startAppListening: AppStartListening) =>
handleVAEModels(models, state, dispatch, log);
handleLoRAModels(models, state, dispatch, log);
handleControlAdapterModels(models, state, dispatch, log);
handleSpandrelImageToImageModels(models, state, dispatch, log);
},
});
};
@ -177,3 +184,25 @@ const handleControlAdapterModels: ModelHandler = (models, state, dispatch, _log)
dispatch(controlAdapterModelCleared({ id: ca.id }));
});
};
const handleSpandrelImageToImageModels: ModelHandler = (models, state, dispatch, _log) => {
const { upscaleModel: currentUpscaleModel, postProcessingModel: currentPostProcessingModel } = state.upscale;
const upscaleModels = models.filter(isSpandrelImageToImageModelConfig);
const firstModel = upscaleModels[0] || null;
const isCurrentUpscaleModelAvailable = currentUpscaleModel
? upscaleModels.some((m) => m.key === currentUpscaleModel.key)
: false;
if (!isCurrentUpscaleModelAvailable) {
dispatch(upscaleModelChanged(firstModel));
}
const isCurrentPostProcessingModelAvailable = currentPostProcessingModel
? upscaleModels.some((m) => m.key === currentPostProcessingModel.key)
: false;
if (!isCurrentPostProcessingModelAvailable) {
dispatch(postProcessingModelChanged(firstModel));
}
};

6
invokeai/frontend/web/src/app/store/store.ts
View File

@ -25,7 +25,7 @@ import { nodesPersistConfig, nodesSlice, nodesUndoableConfig } from 'features/no
import { workflowSettingsPersistConfig, workflowSettingsSlice } from 'features/nodes/store/workflowSettingsSlice';
import { workflowPersistConfig, workflowSlice } from 'features/nodes/store/workflowSlice';
import { generationPersistConfig, generationSlice } from 'features/parameters/store/generationSlice';
import { postprocessingPersistConfig, postprocessingSlice } from 'features/parameters/store/postprocessingSlice';
import { upscalePersistConfig, upscaleSlice } from 'features/parameters/store/upscaleSlice';
import { queueSlice } from 'features/queue/store/queueSlice';
import { sdxlPersistConfig, sdxlSlice } from 'features/sdxl/store/sdxlSlice';
import { configSlice } from 'features/system/store/configSlice';
@ -52,7 +52,6 @@ const allReducers = {
[gallerySlice.name]: gallerySlice.reducer,
[generationSlice.name]: generationSlice.reducer,
[nodesSlice.name]: undoable(nodesSlice.reducer, nodesUndoableConfig),
[postprocessingSlice.name]: postprocessingSlice.reducer,
[systemSlice.name]: systemSlice.reducer,
[configSlice.name]: configSlice.reducer,
[uiSlice.name]: uiSlice.reducer,
@ -69,6 +68,7 @@ const allReducers = {
[controlLayersSlice.name]: undoable(controlLayersSlice.reducer, controlLayersUndoableConfig),
[workflowSettingsSlice.name]: workflowSettingsSlice.reducer,
[api.reducerPath]: api.reducer,
[upscaleSlice.name]: upscaleSlice.reducer,
};
const rootReducer = combineReducers(allReducers);
@ -102,7 +102,6 @@ const persistConfigs: { [key in keyof typeof allReducers]?: PersistConfig } = {
[galleryPersistConfig.name]: galleryPersistConfig,
[generationPersistConfig.name]: generationPersistConfig,
[nodesPersistConfig.name]: nodesPersistConfig,
[postprocessingPersistConfig.name]: postprocessingPersistConfig,
[systemPersistConfig.name]: systemPersistConfig,
[workflowPersistConfig.name]: workflowPersistConfig,
[uiPersistConfig.name]: uiPersistConfig,
@ -114,6 +113,7 @@ const persistConfigs: { [key in keyof typeof allReducers]?: PersistConfig } = {
[hrfPersistConfig.name]: hrfPersistConfig,
[controlLayersPersistConfig.name]: controlLayersPersistConfig,
[workflowSettingsPersistConfig.name]: workflowSettingsPersistConfig,
[upscalePersistConfig.name]: upscalePersistConfig,
};
const unserialize: UnserializeFunction = (data, key) => {

1
invokeai/frontend/web/src/app/types/invokeai.ts
View File

@ -72,7 +72,6 @@ export type AppConfig = {
canRestoreDeletedImagesFromBin: boolean;
nodesAllowlist: string[] | undefined;
nodesDenylist: string[] | undefined;
maxUpscalePixels?: number;
metadataFetchDebounce?: number;
workflowFetchDebounce?: number;
isLocal?: boolean;

45
invokeai/frontend/web/src/common/components/InformationalPopover/InformationalPopover.tsx
View File

@ -10,9 +10,12 @@ import {
PopoverContent,
PopoverTrigger,
Portal,
Spacer,
Text,
} from '@invoke-ai/ui-library';
import { useAppSelector } from 'app/store/storeHooks';
import { useAppDispatch, useAppSelector } from 'app/store/storeHooks';
import { setShouldEnableInformationalPopovers } from 'features/system/store/systemSlice';
import { toast } from 'features/toast/toast';
import { merge, omit } from 'lodash-es';
import type { ReactElement } from 'react';
import { memo, useCallback, useMemo } from 'react';
@ -71,7 +74,7 @@ type ContentProps = {
const Content = ({ data, feature }: ContentProps) => {
const { t } = useTranslation();
const dispatch = useAppDispatch();
const heading = useMemo<string | undefined>(() => t(`popovers.${feature}.heading`), [feature, t]);
const paragraphs = useMemo<string[]>(
@ -82,16 +85,25 @@ const Content = ({ data, feature }: ContentProps) => {
[feature, t]
);
const handleClick = useCallback(() => {
const onClickLearnMore = useCallback(() => {
if (!data?.href) {
return;
}
window.open(data.href);
}, [data?.href]);
const onClickDontShowMeThese = useCallback(() => {
dispatch(setShouldEnableInformationalPopovers(false));
toast({
title: t('settings.informationalPopoversDisabled'),
description: t('settings.informationalPopoversDisabledDesc'),
status: 'info',
});
}, [dispatch, t]);
return (
<PopoverContent w={96}>
<PopoverCloseButton />
<PopoverContent maxW={300}>
<PopoverCloseButton top={2} />
<PopoverBody>
<Flex gap={2} flexDirection="column" alignItems="flex-start">
{heading && (
@ -116,20 +128,19 @@ const Content = ({ data, feature }: ContentProps) => {
{paragraphs.map((p) => (
<Text key={p}>{p}</Text>
))}
{data?.href && (
<>
<Divider />
<Button
pt={1}
onClick={handleClick}
leftIcon={<PiArrowSquareOutBold />}
alignSelf="flex-end"
variant="link"
>
<Divider />
<Flex alignItems="center" justifyContent="space-between" w="full">
<Button onClick={onClickDontShowMeThese} variant="link" size="sm">
{t('common.dontShowMeThese')}
</Button>
<Spacer />
{data?.href && (
<Button onClick={onClickLearnMore} leftIcon={<PiArrowSquareOutBold />} variant="link" size="sm">
{t('common.learnMore') ?? heading}
</Button>
</>
)}
)}
</Flex>
</Flex>
</PopoverBody>
</PopoverContent>

6
invokeai/frontend/web/src/common/components/InformationalPopover/constants.ts
View File

@ -53,7 +53,11 @@ export type Feature =
| 'refinerCfgScale'
| 'scaleBeforeProcessing'
| 'seamlessTilingXAxis'
| 'seamlessTilingYAxis';
| 'seamlessTilingYAxis'
| 'upscaleModel'
| 'scale'
| 'creativity'
| 'structure';
export type PopoverData = PopoverProps & {
image?: string;

18
invokeai/frontend/web/src/common/hooks/useAssertSingleton.ts Normal file
View File

@ -0,0 +1,18 @@
import { useEffect } from 'react';
import { assert } from 'tsafe';
const IDS = new Set<string>();
/**
* Asserts that there is only one instance of a singleton entity. It can be a hook or a component.
* @param id The ID of the singleton entity.
*/
export function useAssertSingleton(id: string) {
useEffect(() => {
assert(!IDS.has(id), `There should be only one instance of ${id}`);
IDS.add(id);
return () => {
IDS.delete(id);
};
}, [id]);
}

4
invokeai/frontend/web/src/common/hooks/useFullscreenDropzone.ts
View File

@ -21,6 +21,10 @@ const selectPostUploadAction = createMemoizedSelector(activeTabNameSelector, (ac
postUploadAction = { type: 'SET_CANVAS_INITIAL_IMAGE' };
}
if (activeTabName === 'upscaling') {
postUploadAction = { type: 'SET_UPSCALE_INITIAL_IMAGE' };
}
return postUploadAction;
});

24
invokeai/frontend/web/src/common/hooks/useIsReadyToEnqueue.ts
View File

@ -15,6 +15,7 @@ import type { Templates } from 'features/nodes/store/types';
import { selectWorkflowSettingsSlice } from 'features/nodes/store/workflowSettingsSlice';
import { isInvocationNode } from 'features/nodes/types/invocation';
import { selectGenerationSlice } from 'features/parameters/store/generationSlice';
import { selectUpscalelice } from 'features/parameters/store/upscaleSlice';
import { selectSystemSlice } from 'features/system/store/systemSlice';
import { activeTabNameSelector } from 'features/ui/store/uiSelectors';
import i18n from 'i18next';
@ -40,8 +41,19 @@ const createSelector = (templates: Templates) =>
selectDynamicPromptsSlice,
selectControlLayersSlice,
activeTabNameSelector,
selectUpscalelice,
],
(controlAdapters, generation, system, nodes, workflowSettings, dynamicPrompts, controlLayers, activeTabName) => {
(
controlAdapters,
generation,
system,
nodes,
workflowSettings,
dynamicPrompts,
controlLayers,
activeTabName,
upscale
) => {
const { model } = generation;
const { size } = controlLayers.present;
const { positivePrompt } = controlLayers.present;
@ -194,6 +206,16 @@ const createSelector = (templates: Templates) =>
reasons.push({ prefix, content });
}
});
} else if (activeTabName === 'upscaling') {
if (!upscale.upscaleInitialImage) {
reasons.push({ content: i18n.t('upscaling.missingUpscaleInitialImage') });
}
if (!upscale.upscaleModel) {
reasons.push({ content: i18n.t('upscaling.missingUpscaleModel') });
}
if (!upscale.tileControlnetModel) {
reasons.push({ content: i18n.t('upscaling.missingTileControlNetModel') });
}
} else {
// Handling for all other tabs
selectControlAdapterAll(controlAdapters)

7
invokeai/frontend/web/src/features/dnd/types/index.ts
View File

@ -62,6 +62,10 @@ export type CanvasInitialImageDropData = BaseDropData & {
actionType: 'SET_CANVAS_INITIAL_IMAGE';
};
type UpscaleInitialImageDropData = BaseDropData & {
actionType: 'SET_UPSCALE_INITIAL_IMAGE';
};
type NodesImageDropData = BaseDropData & {
actionType: 'SET_NODES_IMAGE';
context: {
@ -98,7 +102,8 @@ export type TypesafeDroppableData =
| IPALayerImageDropData
| RGLayerIPAdapterImageDropData
| IILayerImageDropData
| SelectForCompareDropData;
| SelectForCompareDropData
| UpscaleInitialImageDropData;
type BaseDragData = {
id: string;

2
invokeai/frontend/web/src/features/dnd/util/isValidDrop.ts
View File

@ -27,6 +27,8 @@ export const isValidDrop = (overData?: TypesafeDroppableData | null, activeData?
return payloadType === 'IMAGE_DTO';
case 'SET_CANVAS_INITIAL_IMAGE':
return payloadType === 'IMAGE_DTO';
case 'SET_UPSCALE_INITIAL_IMAGE':
return payloadType === 'IMAGE_DTO';
case 'SET_NODES_IMAGE':
return payloadType === 'IMAGE_DTO';
case 'SELECT_FOR_COMPARE':

47
invokeai/frontend/web/src/features/gallery/components/Boards/BoardsList/BoardTooltip.tsx Normal file
View File

@ -0,0 +1,47 @@
import { Flex, Image, Text } from '@invoke-ai/ui-library';
import { skipToken } from '@reduxjs/toolkit/query';
import { useTranslation } from 'react-i18next';
import { useGetBoardAssetsTotalQuery, useGetBoardImagesTotalQuery } from 'services/api/endpoints/boards';
import { useGetImageDTOQuery } from 'services/api/endpoints/images';
import type { BoardDTO } from 'services/api/types';
type Props = {
board: BoardDTO | null;
};
export const BoardTooltip = ({ board }: Props) => {
const { t } = useTranslation();
const { imagesTotal } = useGetBoardImagesTotalQuery(board?.board_id || 'none', {
selectFromResult: ({ data }) => {
return { imagesTotal: data?.total ?? 0 };
},
});
const { assetsTotal } = useGetBoardAssetsTotalQuery(board?.board_id || 'none', {
selectFromResult: ({ data }) => {
return { assetsTotal: data?.total ?? 0 };
},
});
const { currentData: coverImage } = useGetImageDTOQuery(board?.cover_image_name ?? skipToken);
return (
<Flex flexDir="column" alignItems="center" gap={1}>
{coverImage && (
<Image
src={coverImage.thumbnail_url}
draggable={false}
objectFit="cover"
maxW={150}
aspectRatio="1/1"
borderRadius="base"
borderBottomRadius="lg"
/>
)}
<Flex flexDir="column" alignItems="center">
<Text noOfLines={1}>
{t('boards.imagesWithCount', { count: imagesTotal })}, {t('boards.assetsWithCount', { count: assetsTotal })}
</Text>
{board?.archived && <Text>({t('boards.archived')})</Text>}
</Flex>
</Flex>
);
};

22
invokeai/frontend/web/src/features/gallery/components/Boards/BoardsList/BoardTotalsTooltip.tsx
View File

@ -1,22 +0,0 @@
import { useTranslation } from 'react-i18next';
import { useGetBoardAssetsTotalQuery, useGetBoardImagesTotalQuery } from 'services/api/endpoints/boards';
type Props = {
board_id: string;
isArchived: boolean;
};
export const BoardTotalsTooltip = ({ board_id, isArchived }: Props) => {
const { t } = useTranslation();
const { imagesTotal } = useGetBoardImagesTotalQuery(board_id, {
selectFromResult: ({ data }) => {
return { imagesTotal: data?.total ?? 0 };
},
});
const { assetsTotal } = useGetBoardAssetsTotalQuery(board_id, {
selectFromResult: ({ data }) => {
return { assetsTotal: data?.total ?? 0 };
},
});
return `${t('boards.imagesWithCount', { count: imagesTotal })}, ${t('boards.assetsWithCount', { count: assetsTotal })}${isArchived ? ` (${t('boards.archived')})` : ''}`;
};

191
invokeai/frontend/web/src/features/gallery/components/Boards/BoardsList/BoardsList.tsx
View File

@ -1,13 +1,10 @@
import { Box, Flex, Text } from '@invoke-ai/ui-library';
import { Button, Collapse, Flex, Icon, Text, useDisclosure } from '@invoke-ai/ui-library';
import { EMPTY_ARRAY } from 'app/store/constants';
import { useAppSelector } from 'app/store/storeHooks';
import { overlayScrollbarsParams } from 'common/components/OverlayScrollbars/constants';
import DeleteBoardModal from 'features/gallery/components/Boards/DeleteBoardModal';
import { selectListBoardsQueryArgs } from 'features/gallery/store/gallerySelectors';
import { OverlayScrollbarsComponent } from 'overlayscrollbars-react';
import type { CSSProperties } from 'react';
import { memo, useMemo, useState } from 'react';
import { useMemo } from 'react';
import { useTranslation } from 'react-i18next';
import { PiCaretDownBold } from 'react-icons/pi';
import { useListAllBoardsQuery } from 'services/api/endpoints/boards';
import type { BoardDTO } from 'services/api/types';
@ -15,101 +12,111 @@ import AddBoardButton from './AddBoardButton';
import GalleryBoard from './GalleryBoard';
import NoBoardBoard from './NoBoardBoard';
const overlayScrollbarsStyles: CSSProperties = {
height: '100%',
width: '100%',
type Props = {
isPrivate: boolean;
setBoardToDelete: (board?: BoardDTO) => void;
};
const BoardsList = () => {
export const BoardsList = ({ isPrivate, setBoardToDelete }: Props) => {
const { t } = useTranslation();
const selectedBoardId = useAppSelector((s) => s.gallery.selectedBoardId);
const boardSearchText = useAppSelector((s) => s.gallery.boardSearchText);
const allowPrivateBoards = useAppSelector((s) => s.config.allowPrivateBoards);
const queryArgs = useAppSelector(selectListBoardsQueryArgs);
const { data: boards } = useListAllBoardsQuery(queryArgs);
const [boardToDelete, setBoardToDelete] = useState<BoardDTO>();
const { t } = useTranslation();
const allowPrivateBoards = useAppSelector((s) => s.config.allowPrivateBoards);
const { isOpen, onToggle } = useDisclosure({ defaultIsOpen: true });
const { filteredPrivateBoards, filteredSharedBoards } = useMemo(() => {
const filteredBoards = boardSearchText
? boards?.filter((board) => board.board_name.toLowerCase().includes(boardSearchText.toLowerCase()))
: boards;
const filteredPrivateBoards = filteredBoards?.filter((board) => board.is_private) ?? EMPTY_ARRAY;
const filteredSharedBoards = filteredBoards?.filter((board) => !board.is_private) ?? EMPTY_ARRAY;
return { filteredPrivateBoards, filteredSharedBoards };
}, [boardSearchText, boards]);
const filteredBoards = useMemo(() => {
if (!boards) {
return EMPTY_ARRAY;
}
return boards.filter((board) => {
if (boardSearchText.length) {
return board.is_private === isPrivate && board.board_name.toLowerCase().includes(boardSearchText.toLowerCase());
} else {
return board.is_private === isPrivate;
}
});
}, [boardSearchText, boards, isPrivate]);
const boardElements = useMemo(() => {
const elements = [];
if (allowPrivateBoards && isPrivate && !boardSearchText.length) {
elements.push(<NoBoardBoard key="none" isSelected={selectedBoardId === 'none'} />);
}
if (!allowPrivateBoards && !boardSearchText.length) {
elements.push(<NoBoardBoard key="none" isSelected={selectedBoardId === 'none'} />);
}
filteredBoards.forEach((board) => {
elements.push(
<GalleryBoard
board={board}
isSelected={selectedBoardId === board.board_id}
setBoardToDelete={setBoardToDelete}
key={board.board_id}
/>
);
});
return elements;
}, [allowPrivateBoards, isPrivate, boardSearchText.length, filteredBoards, selectedBoardId, setBoardToDelete]);
const boardListTitle = useMemo(() => {
if (allowPrivateBoards) {
return isPrivate ? t('boards.private') : t('boards.shared');
} else {
return t('boards.boards');
}
}, [isPrivate, allowPrivateBoards, t]);
return (
<>
<Box position="relative" w="full" h="full">
<Box position="absolute" top={0} right={0} bottom={0} left={0}>
<OverlayScrollbarsComponent defer style={overlayScrollbarsStyles} options={overlayScrollbarsParams.options}>
{allowPrivateBoards && (
<Flex direction="column" gap={1}>
<Flex
position="sticky"
w="full"
justifyContent="space-between"
alignItems="center"
ps={2}
pb={1}
pt={2}
zIndex={1}
top={0}
bg="base.900"
>
<Text fontSize="md" fontWeight="semibold" userSelect="none">
{t('boards.private')}
</Text>
<AddBoardButton isPrivateBoard={true} />
</Flex>
<Flex direction="column" gap={1}>
<NoBoardBoard isSelected={selectedBoardId === 'none'} />
{filteredPrivateBoards.map((board) => (
<GalleryBoard
board={board}
isSelected={selectedBoardId === board.board_id}
setBoardToDelete={setBoardToDelete}
key={board.board_id}
/>
))}
</Flex>
</Flex>
)}
<Flex direction="column" gap={1}>
<Flex
position="sticky"
w="full"
justifyContent="space-between"
alignItems="center"
ps={2}
pb={1}
pt={2}
zIndex={1}
top={0}
bg="base.900"
>
<Text fontSize="md" fontWeight="semibold" userSelect="none">
{allowPrivateBoards ? t('boards.shared') : t('boards.boards')}
</Text>
<AddBoardButton isPrivateBoard={false} />
</Flex>
<Flex direction="column" gap={1}>
{!allowPrivateBoards && <NoBoardBoard isSelected={selectedBoardId === 'none'} />}
{filteredSharedBoards.map((board) => (
<GalleryBoard
board={board}
isSelected={selectedBoardId === board.board_id}
setBoardToDelete={setBoardToDelete}
key={board.board_id}
/>
))}
</Flex>
<Flex direction="column">
<Flex
position="sticky"
w="full"
justifyContent="space-between"
alignItems="center"
ps={2}
py={1}
zIndex={1}
top={0}
bg="base.900"
>
{allowPrivateBoards ? (
<Button variant="unstyled" onClick={onToggle}>
<Flex gap="2" alignItems="center">
<Icon
boxSize={4}
as={PiCaretDownBold}
transform={isOpen ? undefined : 'rotate(-90deg)'}
fill="base.500"
/>
<Text fontSize="sm" fontWeight="semibold" userSelect="none" color="base.500">
{boardListTitle}
</Text>
</Flex>
</OverlayScrollbarsComponent>
</Box>
</Box>
<DeleteBoardModal boardToDelete={boardToDelete} setBoardToDelete={setBoardToDelete} />
</>
</Button>
) : (
<Text fontSize="sm" fontWeight="semibold" userSelect="none" color="base.500">
{boardListTitle}
</Text>
)}
<AddBoardButton isPrivateBoard={isPrivate} />
</Flex>
<Collapse in={isOpen}>
<Flex direction="column" gap={1}>
{boardElements.length ? (
boardElements
) : (
<Text variant="subtext" textAlign="center">
{t('boards.noBoards', { boardType: boardSearchText.length ? 'Matching' : '' })}
</Text>
)}
</Flex>
</Collapse>
</Flex>
);
};
export default memo(BoardsList);

35
invokeai/frontend/web/src/features/gallery/components/Boards/BoardsList/BoardsListWrapper.tsx Normal file
View File

@ -0,0 +1,35 @@
import { Box } from '@invoke-ai/ui-library';
import { useAppSelector } from 'app/store/storeHooks';
import { overlayScrollbarsParams } from 'common/components/OverlayScrollbars/constants';
import DeleteBoardModal from 'features/gallery/components/Boards/DeleteBoardModal';
import { OverlayScrollbarsComponent } from 'overlayscrollbars-react';
import type { CSSProperties } from 'react';
import { memo, useState } from 'react';
import type { BoardDTO } from 'services/api/types';
import { BoardsList } from './BoardsList';
const overlayScrollbarsStyles: CSSProperties = {
height: '100%',
width: '100%',
};
const BoardsListWrapper = () => {
const allowPrivateBoards = useAppSelector((s) => s.config.allowPrivateBoards);
const [boardToDelete, setBoardToDelete] = useState<BoardDTO>();
return (
<>
<Box position="relative" w="full" h="full">
<Box position="absolute" top={0} right={0} bottom={0} left={0}>
<OverlayScrollbarsComponent defer style={overlayScrollbarsStyles} options={overlayScrollbarsParams.options}>
{allowPrivateBoards && <BoardsList isPrivate={true} setBoardToDelete={setBoardToDelete} />}
<BoardsList isPrivate={false} setBoardToDelete={setBoardToDelete} />
</OverlayScrollbarsComponent>
</Box>
</Box>
<DeleteBoardModal boardToDelete={boardToDelete} setBoardToDelete={setBoardToDelete} />
</>
);
};
export default memo(BoardsListWrapper);

2
invokeai/frontend/web/src/features/gallery/components/Boards/BoardsList/BoardsSearch.tsx
View File

@ -40,7 +40,7 @@ const BoardsSearch = () => {
);
return (
<InputGroup pt={2}>
<InputGroup>
<Input
placeholder={t('boards.searchBoard')}
value={boardSearchText}

31
invokeai/frontend/web/src/features/gallery/components/Boards/BoardsList/GalleryBoard.tsx
View File

@ -17,7 +17,7 @@ import IAIDroppable from 'common/components/IAIDroppable';
import type { AddToBoardDropData } from 'features/dnd/types';
import { AutoAddBadge } from 'features/gallery/components/Boards/AutoAddBadge';
import BoardContextMenu from 'features/gallery/components/Boards/BoardContextMenu';
import { BoardTotalsTooltip } from 'features/gallery/components/Boards/BoardsList/BoardTotalsTooltip';
import { BoardTooltip } from 'features/gallery/components/Boards/BoardsList/BoardTooltip';
import { autoAddBoardIdChanged, boardIdSelected } from 'features/gallery/store/gallerySlice';
import type { MouseEvent, MouseEventHandler, MutableRefObject } from 'react';
import { memo, useCallback, useEffect, useMemo, useRef, useState } from 'react';
@ -115,12 +115,7 @@ const GalleryBoard = ({ board, isSelected, setBoardToDelete }: GalleryBoardProps
return (
<BoardContextMenu board={board} setBoardToDelete={setBoardToDelete}>
{(ref) => (
<Tooltip
label={<BoardTotalsTooltip board_id={board.board_id} isArchived={Boolean(board.archived)} />}
openDelay={1000}
placement="left"
closeOnScroll
>
<Tooltip label={<BoardTooltip board={board} />} openDelay={1000} placement="left" closeOnScroll p={2}>
<Flex
position="relative"
ref={ref}
@ -131,10 +126,12 @@ const GalleryBoard = ({ board, isSelected, setBoardToDelete }: GalleryBoardProps
borderRadius="base"
cursor="pointer"
py={1}
px={2}
gap={2}
ps={1}
pe={4}
gap={4}
bg={isSelected ? 'base.850' : undefined}
_hover={_hover}
h={12}
>
<CoverImage board={board} />
<Editable
@ -149,17 +146,17 @@ const GalleryBoard = ({ board, isSelected, setBoardToDelete }: GalleryBoardProps
onChange={onChange}
onSubmit={onSubmit}
isPreviewFocusable={false}
fontSize="sm"
>
<EditablePreview
cursor="pointer"
p={0}
fontSize="md"
fontSize="sm"
textOverflow="ellipsis"
noOfLines={1}
w="fit-content"
wordBreak="break-all"
color={isSelected ? 'base.100' : 'base.400'}
fontWeight={isSelected ? 'semibold' : 'normal'}
fontWeight={isSelected ? 'bold' : 'normal'}
/>
<EditableInput sx={editableInputStyles} />
<JankEditableHijack onStartEditingRef={onStartEditingRef} />
@ -168,7 +165,7 @@ const GalleryBoard = ({ board, isSelected, setBoardToDelete }: GalleryBoardProps
{board.archived && !editingDisclosure.isOpen && <Icon as={PiArchiveBold} fill="base.300" />}
{!editingDisclosure.isOpen && <Text variant="subtext">{board.image_count}</Text>}
<IAIDroppable data={droppableData} dropLabel={<Text fontSize="md">{t('unifiedCanvas.move')}</Text>} />
<IAIDroppable data={droppableData} dropLabel={<Text fontSize="lg">{t('unifiedCanvas.move')}</Text>} />
</Flex>
</Tooltip>
)}
@ -197,8 +194,8 @@ const CoverImage = ({ board }: { board: BoardDTO }) => {
src={coverImage.thumbnail_url}
draggable={false}
objectFit="cover"
w={8}
h={8}
w={10}
h={10}
borderRadius="base"
borderBottomRadius="lg"
/>
@ -206,8 +203,8 @@ const CoverImage = ({ board }: { board: BoardDTO }) => {
}
return (
<Flex w={8} h={8} justifyContent="center" alignItems="center">
<Icon boxSize={8} as={PiImageSquare} opacity={0.7} color="base.500" />
<Flex w={10} h={10} justifyContent="center" alignItems="center">
<Icon boxSize={10} as={PiImageSquare} opacity={0.7} color="base.500" />
</Flex>
);
};

35
invokeai/frontend/web/src/features/gallery/components/Boards/BoardsList/NoBoardBoard.tsx
View File

@ -4,7 +4,7 @@ import { useAppDispatch, useAppSelector } from 'app/store/storeHooks';
import IAIDroppable from 'common/components/IAIDroppable';
import type { RemoveFromBoardDropData } from 'features/dnd/types';
import { AutoAddBadge } from 'features/gallery/components/Boards/AutoAddBadge';
import { BoardTotalsTooltip } from 'features/gallery/components/Boards/BoardsList/BoardTotalsTooltip';
import { BoardTooltip } from 'features/gallery/components/Boards/BoardsList/BoardTooltip';
import NoBoardBoardContextMenu from 'features/gallery/components/Boards/NoBoardBoardContextMenu';
import { autoAddBoardIdChanged, boardIdSelected } from 'features/gallery/store/gallerySlice';
import { memo, useCallback, useMemo } from 'react';
@ -46,25 +46,16 @@ const NoBoardBoard = memo(({ isSelected }: Props) => {
[]
);
const filteredOut = useMemo(() => {
return boardSearchText ? !boardName.toLowerCase().includes(boardSearchText.toLowerCase()) : false;
}, [boardName, boardSearchText]);
const { t } = useTranslation();
if (filteredOut) {
if (boardSearchText.length) {
return null;
}
return (
<NoBoardBoardContextMenu>
{(ref) => (
<Tooltip
label={<BoardTotalsTooltip board_id="none" isArchived={false} />}
openDelay={1000}
placement="left"
closeOnScroll
>
<Tooltip label={<BoardTooltip board={null} />} openDelay={1000} placement="left" closeOnScroll>
<Flex
position="relative"
ref={ref}
@ -73,15 +64,17 @@ const NoBoardBoard = memo(({ isSelected }: Props) => {
alignItems="center"
borderRadius="base"
cursor="pointer"
px={2}
py={1}
gap={2}
ps={1}
pe={4}
gap={4}
bg={isSelected ? 'base.850' : undefined}
_hover={_hover}
h={12}
>
<Flex w={8} h={8} justifyContent="center" alignItems="center">
<Flex w="10" justifyContent="space-around">
{/* iconified from public/assets/images/invoke-symbol-wht-lrg.svg */}
<Icon boxSize={6} opacity={1} stroke="base.500" viewBox="0 0 66 66" fill="none">
<Icon boxSize={8} opacity={1} stroke="base.500" viewBox="0 0 66 66" fill="none">
<path
d="M43.9137 16H63.1211V3H3.12109V16H22.3285L43.9137 50H63.1211V63H3.12109V50H22.3285"
strokeWidth="5"
@ -89,18 +82,12 @@ const NoBoardBoard = memo(({ isSelected }: Props) => {
</Icon>
</Flex>
<Text
fontSize="md"
color={isSelected ? 'base.100' : 'base.400'}
fontWeight={isSelected ? 'semibold' : 'normal'}
noOfLines={1}
flexGrow={1}
>
<Text fontSize="sm" fontWeight={isSelected ? 'bold' : 'normal'} noOfLines={1} flexGrow={1}>
{boardName}
</Text>
{autoAddBoardId === 'none' && <AutoAddBadge />}
<Text variant="subtext">{imagesTotal}</Text>
<IAIDroppable data={droppableData} dropLabel={<Text fontSize="md">{t('unifiedCanvas.move')}</Text>} />
<IAIDroppable data={droppableData} dropLabel={<Text fontSize="lg">{t('unifiedCanvas.move')}</Text>} />
</Flex>
</Tooltip>
)}

105
invokeai/frontend/web/src/features/gallery/components/Gallery.tsx Normal file
View File

@ -0,0 +1,105 @@
import type { ChakraProps } from '@invoke-ai/ui-library';
import {
Box,
Collapse,
Flex,
IconButton,
Spacer,
Tab,
TabList,
Tabs,
Text,
useDisclosure,
} from '@invoke-ai/ui-library';
import { useAppDispatch, useAppSelector } from 'app/store/storeHooks';
import { useGallerySearchTerm } from 'features/gallery/components/ImageGrid/useGallerySearchTerm';
import { galleryViewChanged } from 'features/gallery/store/gallerySlice';
import type { CSSProperties } from 'react';
import { useCallback } from 'react';
import { useTranslation } from 'react-i18next';
import { PiMagnifyingGlassBold } from 'react-icons/pi';
import { useBoardName } from 'services/api/hooks/useBoardName';
import GalleryImageGrid from './ImageGrid/GalleryImageGrid';
import { GalleryPagination } from './ImageGrid/GalleryPagination';
import { GallerySearch } from './ImageGrid/GallerySearch';
const BASE_STYLES: ChakraProps['sx'] = {
fontWeight: 'semibold',
fontSize: 'sm',
color: 'base.300',
};
const SELECTED_STYLES: ChakraProps['sx'] = {
borderColor: 'base.800',
borderBottomColor: 'base.900',
color: 'invokeBlue.300',
};
const COLLAPSE_STYLES: CSSProperties = { flexShrink: 0, minHeight: 0 };
export const Gallery = () => {
const { t } = useTranslation();
const dispatch = useAppDispatch();
const galleryView = useAppSelector((s) => s.gallery.galleryView);
const initialSearchTerm = useAppSelector((s) => s.gallery.searchTerm);
const searchDisclosure = useDisclosure({ defaultIsOpen: initialSearchTerm.length > 0 });
const [searchTerm, onChangeSearchTerm, onResetSearchTerm] = useGallerySearchTerm();
const handleClickImages = useCallback(() => {
dispatch(galleryViewChanged('images'));
}, [dispatch]);
const handleClickAssets = useCallback(() => {
dispatch(galleryViewChanged('assets'));
}, [dispatch]);
const handleClickSearch = useCallback(() => {
searchDisclosure.onToggle();
onResetSearchTerm();
}, [onResetSearchTerm, searchDisclosure]);
const selectedBoardId = useAppSelector((s) => s.gallery.selectedBoardId);
const boardName = useBoardName(selectedBoardId);
return (
<Flex flexDirection="column" alignItems="center" justifyContent="space-between" h="full" w="full" pt={1}>
<Tabs index={galleryView === 'images' ? 0 : 1} variant="enclosed" display="flex" flexDir="column" w="full">
<TabList gap={2} fontSize="sm" borderColor="base.800" alignItems="center" w="full">
<Text fontSize="sm" fontWeight="semibold" noOfLines={1} px="2">
{boardName}
</Text>
<Spacer />
<Tab sx={BASE_STYLES} _selected={SELECTED_STYLES} onClick={handleClickImages} data-testid="images-tab">
{t('parameters.images')}
</Tab>
<Tab sx={BASE_STYLES} _selected={SELECTED_STYLES} onClick={handleClickAssets} data-testid="assets-tab">
{t('gallery.assets')}
</Tab>
<IconButton
onClick={handleClickSearch}
tooltip={searchDisclosure.isOpen ? `${t('gallery.exitSearch')}` : `${t('gallery.displaySearch')}`}
aria-label={t('gallery.displaySearch')}
icon={<PiMagnifyingGlassBold />}
colorScheme={searchDisclosure.isOpen ? 'invokeBlue' : 'base'}
variant="link"
/>
</TabList>
</Tabs>
<Box w="full">
<Collapse in={searchDisclosure.isOpen} style={COLLAPSE_STYLES}>
<Box w="full" pt={2}>
<GallerySearch
searchTerm={searchTerm}
onChangeSearchTerm={onChangeSearchTerm}
onResetSearchTerm={onResetSearchTerm}
/>
</Box>
</Collapse>
</Box>
<GalleryImageGrid />
<GalleryPagination />
</Flex>
);
};

33
invokeai/frontend/web/src/features/gallery/components/GalleryBoardName.tsx
View File

@ -1,33 +0,0 @@
import { Flex, Text } from '@invoke-ai/ui-library';
import { useAppSelector } from 'app/store/storeHooks';
import { memo } from 'react';
import { useBoardName } from 'services/api/hooks/useBoardName';
type Props = {
onClick: () => void;
};
const GalleryBoardName = (props: Props) => {
const selectedBoardId = useAppSelector((s) => s.gallery.selectedBoardId);
const boardName = useBoardName(selectedBoardId);
return (
<Flex
onClick={props.onClick}
as="button"
h="full"
w="full"
borderWidth={1}
borderRadius="base"
alignItems="center"
justifyContent="center"
px={2}
>
<Text fontWeight="semibold" fontSize="md" noOfLines={1} wordBreak="break-all" color="base.200">
{boardName}
</Text>
</Flex>
);
};
export default memo(GalleryBoardName);

17
invokeai/frontend/web/src/features/gallery/components/GalleryHeader.tsx
View File

@ -3,32 +3,21 @@ import { useStore } from '@nanostores/react';
import { $projectName, $projectUrl } from 'app/store/nanostores/projectId';
import { memo } from 'react';
import GalleryBoardName from './GalleryBoardName';
type Props = {
onClickBoardName: () => void;
};
export const GalleryHeader = memo((props: Props) => {
export const GalleryHeader = memo(() => {
const projectName = useStore($projectName);
const projectUrl = useStore($projectUrl);
if (projectName && projectUrl) {
return (
<Flex gap={2} w="full" alignItems="center" justifyContent="space-evenly" pe={2}>
<Text fontSize="md" fontWeight="semibold" noOfLines={1} w="full" textAlign="center">
<Text fontSize="md" fontWeight="semibold" noOfLines={1} wordBreak="break-all" w="full" textAlign="center">
<Link href={projectUrl}>{projectName}</Link>
</Text>
<GalleryBoardName onClick={props.onClickBoardName} />
</Flex>
);
}
return (
<Flex w="full" pe={2}>
<GalleryBoardName onClick={props.onClickBoardName} />
</Flex>
);
return null;
});
GalleryHeader.displayName = 'GalleryHeader';

9
invokeai/frontend/web/src/features/gallery/components/ImageContextMenu/SingleSelectionMenuItems.tsx
View File

@ -13,6 +13,7 @@ import { sentImageToCanvas, sentImageToImg2Img } from 'features/gallery/store/ac
import { imageToCompareChanged } from 'features/gallery/store/gallerySlice';
import { $templates } from 'features/nodes/store/nodesSlice';
import { selectOptimalDimension } from 'features/parameters/store/generationSlice';
import { upscaleInitialImageChanged } from 'features/parameters/store/upscaleSlice';
import { useFeatureStatus } from 'features/system/hooks/useFeatureStatus';
import { toast } from 'features/toast/toast';
import { setActiveTab } from 'features/ui/store/uiSlice';
@ -124,6 +125,11 @@ const SingleSelectionMenuItems = (props: SingleSelectionMenuItemsProps) => {
dispatch(imageToCompareChanged(imageDTO));
}, [dispatch, imageDTO]);
const handleSendToUpscale = useCallback(() => {
dispatch(upscaleInitialImageChanged(imageDTO));
dispatch(setActiveTab('upscaling'));
}, [dispatch, imageDTO]);
return (
<>
<MenuItem as="a" href={imageDTO.image_url} target="_blank" icon={<PiShareFatBold />}>
@ -185,6 +191,9 @@ const SingleSelectionMenuItems = (props: SingleSelectionMenuItemsProps) => {
{t('parameters.sendToUnifiedCanvas')}
</MenuItem>
)}
<MenuItem icon={<PiShareFatBold />} onClickCapture={handleSendToUpscale} id="send-to-upscale">
{t('parameters.sendToUpscale')}
</MenuItem>
<MenuDivider />
<MenuItem icon={<PiFoldersBold />} onClickCapture={handleChangeBoard}>
{t('boards.changeBoard')}

170
invokeai/frontend/web/src/features/gallery/components/ImageGalleryContent.tsx
View File

@ -1,57 +1,28 @@
import type { ChakraProps } from '@invoke-ai/ui-library';
import {
Box,
Collapse,
Divider,
Flex,
IconButton,
Spacer,
Tab,
TabList,
Tabs,
useDisclosure,
} from '@invoke-ai/ui-library';
import { Box, Button, Collapse, Divider, Flex, IconButton, useDisclosure } from '@invoke-ai/ui-library';
import { useAppDispatch, useAppSelector } from 'app/store/storeHooks';
import { GalleryHeader } from 'features/gallery/components/GalleryHeader';
import { galleryViewChanged } from 'features/gallery/store/gallerySlice';
import { boardSearchTextChanged } from 'features/gallery/store/gallerySlice';
import ResizeHandle from 'features/ui/components/tabs/ResizeHandle';
import { usePanel, type UsePanelOptions } from 'features/ui/hooks/usePanel';
import type { CSSProperties } from 'react';
import { memo, useCallback, useMemo, useRef } from 'react';
import { useTranslation } from 'react-i18next';
import { PiMagnifyingGlassBold } from 'react-icons/pi';
import { PiCaretDownBold, PiCaretUpBold, PiMagnifyingGlassBold } from 'react-icons/pi';
import type { ImperativePanelGroupHandle } from 'react-resizable-panels';
import { Panel, PanelGroup } from 'react-resizable-panels';
import BoardsList from './Boards/BoardsList/BoardsList';
import BoardsListWrapper from './Boards/BoardsList/BoardsListWrapper';
import BoardsSearch from './Boards/BoardsList/BoardsSearch';
import { Gallery } from './Gallery';
import GallerySettingsPopover from './GallerySettingsPopover/GallerySettingsPopover';
import GalleryImageGrid from './ImageGrid/GalleryImageGrid';
import { GalleryPagination } from './ImageGrid/GalleryPagination';
import { GallerySearch } from './ImageGrid/GallerySearch';
const COLLAPSE_STYLES: CSSProperties = { flexShrink: 0, minHeight: 0 };
const BASE_STYLES: ChakraProps['sx'] = {
fontWeight: 'semibold',
fontSize: 'sm',
color: 'base.300',
};
const SELECTED_STYLES: ChakraProps['sx'] = {
borderColor: 'base.800',
borderBottomColor: 'base.900',
color: 'invokeBlue.300',
};
const ImageGalleryContent = () => {
const { t } = useTranslation();
const galleryView = useAppSelector((s) => s.gallery.galleryView);
const searchTerm = useAppSelector((s) => s.gallery.searchTerm);
const boardSearchText = useAppSelector((s) => s.gallery.boardSearchText);
const dispatch = useAppDispatch();
const searchDisclosure = useDisclosure({ defaultIsOpen: false });
const boardSearchDisclosure = useDisclosure({ defaultIsOpen: false });
const boardSearchDisclosure = useDisclosure({ defaultIsOpen: !!boardSearchText.length });
const panelGroupRef = useRef<ImperativePanelGroupHandle>(null);
const boardsListPanelOptions = useMemo<UsePanelOptions>(
@ -67,42 +38,58 @@ const ImageGalleryContent = () => {
);
const boardsListPanel = usePanel(boardsListPanelOptions);
const handleClickImages = useCallback(() => {
dispatch(galleryViewChanged('images'));
}, [dispatch]);
const handleClickBoardSearch = useCallback(() => {
if (boardSearchText.length) {
dispatch(boardSearchTextChanged(''));
}
boardSearchDisclosure.onToggle();
boardsListPanel.expand();
}, [boardSearchText.length, boardSearchDisclosure, boardsListPanel, dispatch]);
const handleClickAssets = useCallback(() => {
dispatch(galleryViewChanged('assets'));
}, [dispatch]);
const handleToggleBoardPanel = useCallback(() => {
if (boardSearchText.length) {
dispatch(boardSearchTextChanged(''));
}
boardSearchDisclosure.onClose();
boardsListPanel.toggle();
}, [boardSearchText.length, boardSearchDisclosure, boardsListPanel, dispatch]);
return (
<Flex position="relative" flexDirection="column" h="full" w="full" pt={2}>
<Flex alignItems="center" gap={2}>
<GalleryHeader onClickBoardName={boardsListPanel.toggle} />
<GallerySettingsPopover />
<Box position="relative" h="full">
<IconButton
w="full"
h="full"
onClick={boardSearchDisclosure.onToggle}
tooltip={`${t('gallery.displayBoardSearch')}`}
aria-label={t('gallery.displayBoardSearch')}
icon={<PiMagnifyingGlassBold />}
variant="link"
/>
{boardSearchText && (
<Box
position="absolute"
w={2}
h={2}
bg="invokeBlue.300"
borderRadius="full"
insetBlockStart={2}
insetInlineEnd={2}
/>
)}
</Box>
<Flex alignItems="center" gap={0}>
<GalleryHeader />
<Flex alignItems="center" justifyContent="space-between" w="full">
<Button
w={112}
size="sm"
variant="ghost"
onClick={handleToggleBoardPanel}
rightIcon={boardsListPanel.isCollapsed ? <PiCaretDownBold /> : <PiCaretUpBold />}
>
{boardsListPanel.isCollapsed ? t('boards.viewBoards') : t('boards.hideBoards')}
</Button>
<Flex alignItems="center" justifyContent="space-between">
<GallerySettingsPopover />
<Flex>
<IconButton
w="full"
h="full"
onClick={handleClickBoardSearch}
tooltip={
boardSearchDisclosure.isOpen
? `${t('gallery.exitBoardSearch')}`
: `${t('gallery.displayBoardSearch')}`
}
aria-label={t('gallery.displayBoardSearch')}
icon={<PiMagnifyingGlassBold />}
colorScheme={boardSearchDisclosure.isOpen ? 'invokeBlue' : 'base'}
variant="link"
/>
</Flex>
</Flex>
</Flex>
</Flex>
<PanelGroup ref={panelGroupRef} direction="vertical">
<Panel
id="boards-list-panel"
@ -115,10 +102,12 @@ const ImageGalleryContent = () => {
>
<Flex flexDir="column" w="full" h="full">
<Collapse in={boardSearchDisclosure.isOpen} style={COLLAPSE_STYLES}>
<BoardsSearch />
<Box w="full" pt={2}>
<BoardsSearch />
</Box>
</Collapse>
<Divider pt={2} />
<BoardsList />
<BoardsListWrapper />
</Flex>
</Panel>
<ResizeHandle
@ -127,50 +116,7 @@ const ImageGalleryContent = () => {
onDoubleClick={boardsListPanel.onDoubleClickHandle}
/>
<Panel id="gallery-wrapper-panel" minSize={20}>
<Flex flexDirection="column" alignItems="center" justifyContent="space-between" h="full" w="full">
<Tabs index={galleryView === 'images' ? 0 : 1} variant="enclosed" display="flex" flexDir="column" w="full">
<TabList gap={2} fontSize="sm" borderColor="base.800">
<Tab sx={BASE_STYLES} _selected={SELECTED_STYLES} onClick={handleClickImages} data-testid="images-tab">
{t('parameters.images')}
</Tab>
<Tab sx={BASE_STYLES} _selected={SELECTED_STYLES} onClick={handleClickAssets} data-testid="assets-tab">
{t('gallery.assets')}
</Tab>
<Spacer />
<Box position="relative">
<IconButton
w="full"
h="full"
onClick={searchDisclosure.onToggle}
tooltip={`${t('gallery.displaySearch')}`}
aria-label={t('gallery.displaySearch')}
icon={<PiMagnifyingGlassBold />}
variant="link"
/>
{searchTerm && (
<Box
position="absolute"
w={2}
h={2}
bg="invokeBlue.300"
borderRadius="full"
insetBlockStart={2}
insetInlineEnd={2}
/>
)}
</Box>
</TabList>
</Tabs>
<Box w="full">
<Collapse in={searchDisclosure.isOpen} style={COLLAPSE_STYLES}>
<Box w="full" pt={2}>
<GallerySearch />
</Box>
</Collapse>
</Box>
<GalleryImageGrid />
<GalleryPagination />
</Flex>
<Gallery />
</Panel>
</PanelGroup>
</Flex>

48
invokeai/frontend/web/src/features/gallery/components/ImageGrid/GalleryPagination.tsx
View File

@ -3,6 +3,8 @@ import { ELLIPSIS, useGalleryPagination } from 'features/gallery/hooks/useGaller
import { useCallback } from 'react';
import { PiCaretLeftBold, PiCaretRightBold } from 'react-icons/pi';
import { JumpTo } from './JumpTo';
export const GalleryPagination = () => {
const { goPrev, goNext, isPrevEnabled, isNextEnabled, pageButtons, goToPage, currentPage, total } =
useGalleryPagination();
@ -20,7 +22,7 @@ export const GalleryPagination = () => {
}
return (
<Flex gap={2} alignItems="center" w="full">
<Flex justifyContent="center" alignItems="center" w="full" gap={1} pt={2}>
<IconButton
size="sm"
aria-label="prev"
@ -30,25 +32,9 @@ export const GalleryPagination = () => {
variant="ghost"
/>
<Spacer />
{pageButtons.map((page, i) => {
if (page === ELLIPSIS) {
return (
<Button size="sm" key={`ellipsis_${i}`} variant="link" isDisabled>
...
</Button>
);
}
return (
<Button
size="sm"
key={page}
onClick={goToPage.bind(null, page - 1)}
variant={currentPage === page - 1 ? 'solid' : 'outline'}
>
{page}
</Button>
);
})}
{pageButtons.map((page, i) => (
<PageButton key={`${page}_${i}`} page={page} currentPage={currentPage} goToPage={goToPage} />
))}
<Spacer />
<IconButton
size="sm"
@ -58,6 +44,28 @@ export const GalleryPagination = () => {
isDisabled={!isNextEnabled}
variant="ghost"
/>
<JumpTo />
</Flex>
);
};
type PageButtonProps = {
page: number | typeof ELLIPSIS;
currentPage: number;
goToPage: (page: number) => void;
};
const PageButton = ({ page, currentPage, goToPage }: PageButtonProps) => {
if (page === ELLIPSIS) {
return (
<Button size="sm" variant="link" isDisabled>
...
</Button>
);
}
return (
<Button size="sm" onClick={goToPage.bind(null, page - 1)} variant={currentPage === page - 1 ? 'solid' : 'outline'}>
{page}
</Button>
);
};

49
invokeai/frontend/web/src/features/gallery/components/ImageGrid/GallerySearch.tsx
View File

@ -1,59 +1,60 @@
import { IconButton, Input, InputGroup, InputRightElement, Spinner } from '@invoke-ai/ui-library';
import { useAppDispatch, useAppSelector } from 'app/store/storeHooks';
import { useAppSelector } from 'app/store/storeHooks';
import { selectListImagesQueryArgs } from 'features/gallery/store/gallerySelectors';
import { searchTermChanged } from 'features/gallery/store/gallerySlice';
import { debounce } from 'lodash-es';
import type { ChangeEvent } from 'react';
import { useCallback, useMemo, useState } from 'react';
import type { ChangeEvent, KeyboardEvent } from 'react';
import { useCallback } from 'react';
import { useTranslation } from 'react-i18next';
import { PiXBold } from 'react-icons/pi';
import { useListImagesQuery } from 'services/api/endpoints/images';
export const GallerySearch = () => {
const dispatch = useAppDispatch();
const searchTerm = useAppSelector((s) => s.gallery.searchTerm);
type Props = {
searchTerm: string;
onChangeSearchTerm: (value: string) => void;
onResetSearchTerm: () => void;
};
export const GallerySearch = ({ searchTerm, onChangeSearchTerm, onResetSearchTerm }: Props) => {
const { t } = useTranslation();
const [searchTermInput, setSearchTermInput] = useState(searchTerm);
const queryArgs = useAppSelector(selectListImagesQueryArgs);
const { isPending } = useListImagesQuery(queryArgs, {
selectFromResult: ({ isLoading, isFetching }) => ({ isPending: isLoading || isFetching }),
});
const debouncedSetSearchTerm = useMemo(() => {
return debounce((value: string) => {
dispatch(searchTermChanged(value));
}, 1000);
}, [dispatch]);
const handleChangeInput = useCallback(
(e: ChangeEvent<HTMLInputElement>) => {
setSearchTermInput(e.target.value);
debouncedSetSearchTerm(e.target.value);
onChangeSearchTerm(e.target.value);
},
[debouncedSetSearchTerm]
[onChangeSearchTerm]
);
const handleClearInput = useCallback(() => {
setSearchTermInput('');
dispatch(searchTermChanged(''));
}, [dispatch]);
const handleKeydown = useCallback(
(e: KeyboardEvent<HTMLInputElement>) => {
// exit search mode on escape
if (e.key === 'Escape') {
onResetSearchTerm();
}
},
[onResetSearchTerm]
);
return (
<InputGroup>
<Input
placeholder={t('gallery.searchImages')}
value={searchTermInput}
value={searchTerm}
onChange={handleChangeInput}
data-testid="image-search-input"
onKeyDown={handleKeydown}
/>
{isPending && (
<InputRightElement h="full" pe={2}>
<Spinner size="sm" opacity={0.5} />
</InputRightElement>
)}
{!isPending && searchTermInput.length && (
{!isPending && searchTerm.length && (
<InputRightElement h="full" pe={2}>
<IconButton
onClick={handleClearInput}
onClick={onResetSearchTerm}
size="sm"
variant="link"
aria-label={t('boards.clearSearch')}

97
invokeai/frontend/web/src/features/gallery/components/ImageGrid/JumpTo.tsx Normal file
View File

@ -0,0 +1,97 @@
import {
Button,
CompositeNumberInput,
Flex,
FormControl,
Popover,
PopoverArrow,
PopoverBody,
PopoverContent,
PopoverTrigger,
useDisclosure,
} from '@invoke-ai/ui-library';
import { useGalleryPagination } from 'features/gallery/hooks/useGalleryPagination';
import { useCallback, useEffect, useRef, useState } from 'react';
import { useHotkeys } from 'react-hotkeys-hook';
import { useTranslation } from 'react-i18next';
export const JumpTo = () => {
const { t } = useTranslation();
const { goToPage, currentPage, pages } = useGalleryPagination();
const [newPage, setNewPage] = useState(currentPage);
const { isOpen, onToggle, onClose } = useDisclosure();
const ref = useRef<HTMLInputElement>(null);
const onOpen = useCallback(() => {
setNewPage(currentPage);
setTimeout(() => {
const input = ref.current?.querySelector('input');
input?.focus();
input?.select();
}, 0);
}, [currentPage]);
const onChangeJumpTo = useCallback((v: number) => {
setNewPage(v - 1);
}, []);
const onClickGo = useCallback(() => {
goToPage(newPage);
onClose();
}, [newPage, goToPage, onClose]);
useHotkeys(
'enter',
() => {
onClickGo();
},
{ enabled: isOpen, enableOnFormTags: ['input'] },
[isOpen, onClickGo]
);
useHotkeys(
'esc',
() => {
setNewPage(currentPage);
onClose();
},
{ enabled: isOpen, enableOnFormTags: ['input'] },
[isOpen, onClose]
);
useEffect(() => {
setNewPage(currentPage);
}, [currentPage]);
return (
<Popover isOpen={isOpen} onClose={onClose} onOpen={onOpen}>
<PopoverTrigger>
<Button aria-label={t('gallery.jump')} size="sm" onClick={onToggle} variant="outline">
{t('gallery.jump')}
</Button>
</PopoverTrigger>
<PopoverContent>
<PopoverArrow />
<PopoverBody>
<Flex gap={2} alignItems="center">
<FormControl>
<CompositeNumberInput
ref={ref}
size="sm"
maxW="60px"
value={newPage + 1}
min={1}
max={pages}
step={1}
onChange={onChangeJumpTo}
/>
</FormControl>
<Button h="full" size="sm" onClick={onClickGo}>
{t('gallery.go')}
</Button>
</Flex>
</PopoverBody>
</PopoverContent>
</Popover>
);
};

37
invokeai/frontend/web/src/features/gallery/components/ImageGrid/useGallerySearchTerm.ts Normal file
View File

@ -0,0 +1,37 @@
import { useAppDispatch, useAppSelector } from 'app/store/storeHooks';
import { useAssertSingleton } from 'common/hooks/useAssertSingleton';
import { searchTermChanged } from 'features/gallery/store/gallerySlice';
import { debounce } from 'lodash-es';
import { useCallback, useMemo, useState } from 'react';
export const useGallerySearchTerm = () => {
// Highlander!
useAssertSingleton('gallery-search-state');
const dispatch = useAppDispatch();
const searchTerm = useAppSelector((s) => s.gallery.searchTerm);
const [localSearchTerm, setLocalSearchTerm] = useState(searchTerm);
const debouncedSetSearchTerm = useMemo(() => {
return debounce((val: string) => {
dispatch(searchTermChanged(val));
}, 1000);
}, [dispatch]);
const onChange = useCallback(
(val: string) => {
setLocalSearchTerm(val);
debouncedSetSearchTerm(val);
},
[debouncedSetSearchTerm]
);
const onReset = useCallback(() => {
debouncedSetSearchTerm.cancel();
setLocalSearchTerm('');
dispatch(searchTermChanged(''));
}, [debouncedSetSearchTerm, dispatch]);
return [localSearchTerm, onChange, onReset] as const;
};

8
invokeai/frontend/web/src/features/gallery/components/ImageViewer/CurrentImageButtons.tsx
View File

@ -2,7 +2,7 @@ import { ButtonGroup, IconButton, Menu, MenuButton, MenuList } from '@invoke-ai/
import { useStore } from '@nanostores/react';
import { createSelector } from '@reduxjs/toolkit';
import { skipToken } from '@reduxjs/toolkit/query';
import { upscaleRequested } from 'app/store/middleware/listenerMiddleware/listeners/upscaleRequested';
import { adHocPostProcessingRequested } from 'app/store/middleware/listenerMiddleware/listeners/addAdHocPostProcessingRequestedListener';
import { useAppDispatch, useAppSelector } from 'app/store/storeHooks';
import { iiLayerAdded } from 'features/controlLayers/store/controlLayersSlice';
import { DeleteImageButton } from 'features/deleteImageModal/components/DeleteImageButton';
@ -14,7 +14,7 @@ import { selectLastSelectedImage } from 'features/gallery/store/gallerySelectors
import { selectGallerySlice } from 'features/gallery/store/gallerySlice';
import { parseAndRecallImageDimensions } from 'features/metadata/util/handlers';
import { $templates } from 'features/nodes/store/nodesSlice';
import ParamUpscalePopover from 'features/parameters/components/Upscale/ParamUpscaleSettings';
import { PostProcessingPopover } from 'features/parameters/components/PostProcessing/PostProcessingPopover';
import { useIsQueueMutationInProgress } from 'features/queue/hooks/useIsQueueMutationInProgress';
import { useFeatureStatus } from 'features/system/hooks/useFeatureStatus';
import { selectSystemSlice } from 'features/system/store/systemSlice';
@ -97,7 +97,7 @@ const CurrentImageButtons = () => {
if (!imageDTO) {
return;
}
dispatch(upscaleRequested({ imageDTO }));
dispatch(adHocPostProcessingRequested({ imageDTO }));
}, [dispatch, imageDTO]);
const handleDelete = useCallback(() => {
@ -193,7 +193,7 @@ const CurrentImageButtons = () => {
{isUpscalingEnabled && (
<ButtonGroup isDisabled={isQueueMutationInProgress}>
{isUpscalingEnabled && <ParamUpscalePopover imageDTO={imageDTO} />}
{isUpscalingEnabled && <PostProcessingPopover imageDTO={imageDTO} />}
</ButtonGroup>
)}

10
invokeai/frontend/web/src/features/gallery/components/ImageViewer/ViewerToolbar.tsx
View File

@ -9,7 +9,13 @@ import CurrentImageButtons from './CurrentImageButtons';
import { ViewerToggleMenu } from './ViewerToggleMenu';
export const ViewerToolbar = memo(() => {
const tab = useAppSelector(activeTabNameSelector);
const showToggle = useAppSelector((s) => {
const tab = activeTabNameSelector(s);
if (tab === 'upscaling' || tab === 'workflows') {
return false;
}
return true;
});
return (
<Flex w="full" gap={2}>
<Flex flex={1} justifyContent="center">
@ -23,7 +29,7 @@ export const ViewerToolbar = memo(() => {
</Flex>
<Flex flex={1} justifyContent="center">
<Flex gap={2} marginInlineStart="auto">
{tab !== 'workflows' && <ViewerToggleMenu />}
{showToggle && <ViewerToggleMenu />}
</Flex>
</Flex>
</Flex>

30
invokeai/frontend/web/src/features/gallery/hooks/useGalleryPagination.ts
View File

@ -1,6 +1,7 @@
import { useAppDispatch, useAppSelector } from 'app/store/storeHooks';
import { selectListImagesQueryArgs } from 'features/gallery/store/gallerySelectors';
import { offsetChanged } from 'features/gallery/store/gallerySlice';
import { throttle } from 'lodash-es';
import { useCallback, useEffect, useMemo } from 'react';
import { useListImagesQuery } from 'services/api/endpoints/images';
@ -80,32 +81,41 @@ export const useGalleryPagination = () => {
return offset > 0;
}, [count, offset]);
const onOffsetChanged = useCallback(
(arg: Parameters<typeof offsetChanged>[0]) => {
dispatch(offsetChanged(arg));
},
[dispatch]
);
const throttledOnOffsetChanged = useMemo(() => throttle(onOffsetChanged, 500), [onOffsetChanged]);
const goNext = useCallback(
(withHotkey?: 'arrow' | 'alt+arrow') => {
dispatch(offsetChanged({ offset: offset + (limit || 0), withHotkey }));
throttledOnOffsetChanged({ offset: offset + (limit || 0), withHotkey });
},
[dispatch, offset, limit]
[throttledOnOffsetChanged, offset, limit]
);
const goPrev = useCallback(
(withHotkey?: 'arrow' | 'alt+arrow') => {
dispatch(offsetChanged({ offset: Math.max(offset - (limit || 0), 0), withHotkey }));
throttledOnOffsetChanged({ offset: Math.max(offset - (limit || 0), 0), withHotkey });
},
[dispatch, offset, limit]
[throttledOnOffsetChanged, offset, limit]
);
const goToPage = useCallback(
(page: number) => {
dispatch(offsetChanged({ offset: page * (limit || 0) }));
throttledOnOffsetChanged({ offset: page * (limit || 0) });
},
[dispatch, limit]
[throttledOnOffsetChanged, limit]
);
const goToFirst = useCallback(() => {
dispatch(offsetChanged({ offset: 0 }));
}, [dispatch]);
throttledOnOffsetChanged({ offset: 0 });
}, [throttledOnOffsetChanged]);
const goToLast = useCallback(() => {
dispatch(offsetChanged({ offset: (pages - 1) * (limit || 0) }));
}, [dispatch, pages, limit]);
throttledOnOffsetChanged({ offset: (pages - 1) * (limit || 0) });
}, [throttledOnOffsetChanged, pages, limit]);
// handle when total/pages decrease and user is on high page number (ie bulk removing or deleting)
useEffect(() => {

15
invokeai/frontend/web/src/features/modelManagerV2/hooks/useControlNetOrT2IAdapterDefaultSettings.ts
View File

@ -1,15 +1,10 @@
import { skipToken } from '@reduxjs/toolkit/query';
import { isNil } from 'lodash-es';
import { useMemo } from 'react';
import { useGetModelConfigWithTypeGuard } from 'services/api/hooks/useGetModelConfigWithTypeGuard';
import { isControlNetOrT2IAdapterModelConfig } from 'services/api/types';
export const useControlNetOrT2IAdapterDefaultSettings = (modelKey?: string | null) => {
const { modelConfig, isLoading } = useGetModelConfigWithTypeGuard(
modelKey ?? skipToken,
isControlNetOrT2IAdapterModelConfig
);
import type { ControlNetModelConfig, T2IAdapterModelConfig } from 'services/api/types';
export const useControlNetOrT2IAdapterDefaultSettings = (
modelConfig: ControlNetModelConfig | T2IAdapterModelConfig
) => {
const defaultSettingsDefaults = useMemo(() => {
return {
preprocessor: {
@ -19,5 +14,5 @@ export const useControlNetOrT2IAdapterDefaultSettings = (modelKey?: string | nul
};
}, [modelConfig?.default_settings]);
return { defaultSettingsDefaults, isLoading };
return defaultSettingsDefaults;
};

11
invokeai/frontend/web/src/features/modelManagerV2/hooks/useInstallModel.ts
View File

@ -1,11 +1,9 @@
import { toast } from 'features/toast/toast';
import { useCallback } from 'react';
import { useTranslation } from 'react-i18next';
import { useInstallModelMutation } from 'services/api/endpoints/models';
import { type InstallModelArg, useInstallModelMutation } from 'services/api/endpoints/models';
type InstallModelArg = {
source: string;
inplace?: boolean;
type InstallModelArgWithCallbacks = InstallModelArg & {
onSuccess?: () => void;
onError?: (error: unknown) => void;
};
@ -15,8 +13,9 @@ export const useInstallModel = () => {
const [_installModel, request] = useInstallModelMutation();
const installModel = useCallback(
({ source, inplace, onSuccess, onError }: InstallModelArg) => {
_installModel({ source, inplace })
({ source, inplace, config, onSuccess, onError }: InstallModelArgWithCallbacks) => {
config ||= {};
_installModel({ source, inplace, config })
.unwrap()
.then((_) => {
if (onSuccess) {

11
invokeai/frontend/web/src/features/modelManagerV2/hooks/useMainModelDefaultSettings.ts
View File

@ -1,12 +1,9 @@
import { skipToken } from '@reduxjs/toolkit/query';
import { createMemoizedSelector } from 'app/store/createMemoizedSelector';
import { useAppSelector } from 'app/store/storeHooks';
import { getOptimalDimension } from 'features/parameters/util/optimalDimension';
import { selectConfigSlice } from 'features/system/store/configSlice';
import { isNil } from 'lodash-es';
import { useMemo } from 'react';
import { useGetModelConfigWithTypeGuard } from 'services/api/hooks/useGetModelConfigWithTypeGuard';
import { isNonRefinerMainModelConfig } from 'services/api/types';
import type { MainModelConfig } from 'services/api/types';
const initialStatesSelector = createMemoizedSelector(selectConfigSlice, (config) => {
const { steps, guidance, scheduler, cfgRescaleMultiplier, vaePrecision, width, height } = config.sd;
@ -22,9 +19,7 @@ const initialStatesSelector = createMemoizedSelector(selectConfigSlice, (config)
};
});
export const useMainModelDefaultSettings = (modelKey?: string | null) => {
const { modelConfig, isLoading } = useGetModelConfigWithTypeGuard(modelKey ?? skipToken, isNonRefinerMainModelConfig);
export const useMainModelDefaultSettings = (modelConfig: MainModelConfig) => {
const {
initialSteps,
initialCfg,
@ -81,5 +76,5 @@ export const useMainModelDefaultSettings = (modelKey?: string | null) => {
initialHeight,
]);
return { defaultSettingsDefaults, isLoading, optimalDimension: getOptimalDimension(modelConfig) };
return defaultSettingsDefaults;
};

2
invokeai/frontend/web/src/features/modelManagerV2/hooks/useStarterModelsToast.tsx
View File

@ -1,5 +1,6 @@
import { Button, Text, useToast } from '@invoke-ai/ui-library';
import { useAppDispatch } from 'app/store/storeHooks';
import { $installModelsTab } from 'features/modelManagerV2/subpanels/InstallModels';
import { useFeatureStatus } from 'features/system/hooks/useFeatureStatus';
import { setActiveTab } from 'features/ui/store/uiSlice';
import { useCallback, useEffect, useState } from 'react';
@ -44,6 +45,7 @@ const ToastDescription = () => {
const onClick = useCallback(() => {
dispatch(setActiveTab('models'));
$installModelsTab.set(3);
toast.close(TOAST_ID);
}, [dispatch, toast]);

4
invokeai/frontend/web/src/features/modelManagerV2/store/modelManagerV2Slice.ts
View File

@ -1,6 +1,6 @@
import type { PayloadAction } from '@reduxjs/toolkit';
import { createSlice } from '@reduxjs/toolkit';
import type { PersistConfig } from 'app/store/store';
import type { PersistConfig, RootState } from 'app/store/store';
import type { ModelType } from 'services/api/types';
export type FilterableModelType = Exclude<ModelType, 'onnx' | 'clip_vision'> | 'refiner';
@ -50,6 +50,8 @@ export const modelManagerV2Slice = createSlice({
export const { setSelectedModelKey, setSearchTerm, setFilteredModelType, setSelectedModelMode, setScanPath } =
modelManagerV2Slice.actions;
export const selectModelManagerV2Slice = (state: RootState) => state.modelmanagerV2;
/* eslint-disable-next-line @typescript-eslint/no-explicit-any */
const migrateModelManagerState = (state: any): any => {
if (!('_version' in state)) {

8
invokeai/frontend/web/src/features/modelManagerV2/subpanels/AddModelPanel/HuggingFaceFolder/HuggingFaceForm.tsx
View File

@ -1,13 +1,13 @@
import { Button, Flex, FormControl, FormErrorMessage, FormHelperText, FormLabel, Input } from '@invoke-ai/ui-library';
import { useInstallModel } from 'features/modelManagerV2/hooks/useInstallModel';
import type { ChangeEventHandler } from 'react';
import { useCallback, useState } from 'react';
import { memo, useCallback, useState } from 'react';
import { useTranslation } from 'react-i18next';
import { useLazyGetHuggingFaceModelsQuery } from 'services/api/endpoints/models';
import { HuggingFaceResults } from './HuggingFaceResults';
export const HuggingFaceForm = () => {
export const HuggingFaceForm = memo(() => {
const [huggingFaceRepo, setHuggingFaceRepo] = useState('');
const [displayResults, setDisplayResults] = useState(false);
const [errorMessage, setErrorMessage] = useState('');
@ -66,4 +66,6 @@ export const HuggingFaceForm = () => {
{data && data.urls && displayResults && <HuggingFaceResults results={data.urls} />}
</Flex>
);
};
});
HuggingFaceForm.displayName = 'HuggingFaceForm';

8
invokeai/frontend/web/src/features/modelManagerV2/subpanels/AddModelPanel/HuggingFaceFolder/HuggingFaceResultItem.tsx
View File

@ -1,13 +1,13 @@
import { Flex, IconButton, Text } from '@invoke-ai/ui-library';
import { useInstallModel } from 'features/modelManagerV2/hooks/useInstallModel';
import { useCallback } from 'react';
import { memo, useCallback } from 'react';
import { useTranslation } from 'react-i18next';
import { PiPlusBold } from 'react-icons/pi';
type Props = {
result: string;
};
export const HuggingFaceResultItem = ({ result }: Props) => {
export const HuggingFaceResultItem = memo(({ result }: Props) => {
const { t } = useTranslation();
const [installModel] = useInstallModel();
@ -27,4 +27,6 @@ export const HuggingFaceResultItem = ({ result }: Props) => {
<IconButton aria-label={t('modelManager.install')} icon={<PiPlusBold />} onClick={onClick} size="sm" />
</Flex>
);
};
});
HuggingFaceResultItem.displayName = 'HuggingFaceResultItem';

8
invokeai/frontend/web/src/features/modelManagerV2/subpanels/AddModelPanel/HuggingFaceFolder/HuggingFaceResults.tsx
View File

@ -11,7 +11,7 @@ import {
import ScrollableContent from 'common/components/OverlayScrollbars/ScrollableContent';
import { useInstallModel } from 'features/modelManagerV2/hooks/useInstallModel';
import type { ChangeEventHandler } from 'react';
import { useCallback, useMemo, useState } from 'react';
import { memo, useCallback, useMemo, useState } from 'react';
import { useTranslation } from 'react-i18next';
import { PiXBold } from 'react-icons/pi';
@ -21,7 +21,7 @@ type HuggingFaceResultsProps = {
results: string[];
};
export const HuggingFaceResults = ({ results }: HuggingFaceResultsProps) => {
export const HuggingFaceResults = memo(({ results }: HuggingFaceResultsProps) => {
const { t } = useTranslation();
const [searchTerm, setSearchTerm] = useState('');
@ -93,4 +93,6 @@ export const HuggingFaceResults = ({ results }: HuggingFaceResultsProps) => {
</Flex>
</>
);
};
});
HuggingFaceResults.displayName = 'HuggingFaceResults';

8
invokeai/frontend/web/src/features/modelManagerV2/subpanels/AddModelPanel/InstallModelForm.tsx
View File

@ -1,7 +1,7 @@
import { Button, Checkbox, Flex, FormControl, FormHelperText, FormLabel, Input } from '@invoke-ai/ui-library';
import { useInstallModel } from 'features/modelManagerV2/hooks/useInstallModel';
import { t } from 'i18next';
import { useCallback } from 'react';
import { memo, useCallback } from 'react';
import type { SubmitHandler } from 'react-hook-form';
import { useForm } from 'react-hook-form';
@ -10,7 +10,7 @@ type SimpleImportModelConfig = {
inplace: boolean;
};
export const InstallModelForm = () => {
export const InstallModelForm = memo(() => {
const [installModel, { isLoading }] = useInstallModel();
const { register, handleSubmit, formState, reset } = useForm<SimpleImportModelConfig>({
@ -74,4 +74,6 @@ export const InstallModelForm = () => {
</Flex>
</form>
);
};
});
InstallModelForm.displayName = 'InstallModelForm';

8
invokeai/frontend/web/src/features/modelManagerV2/subpanels/AddModelPanel/ModelInstallQueue/ModelInstallQueue.tsx
View File

@ -2,12 +2,12 @@ import { Box, Button, Flex, Heading } from '@invoke-ai/ui-library';
import ScrollableContent from 'common/components/OverlayScrollbars/ScrollableContent';
import { toast } from 'features/toast/toast';
import { t } from 'i18next';
import { useCallback, useMemo } from 'react';
import { memo, useCallback, useMemo } from 'react';
import { useListModelInstallsQuery, usePruneCompletedModelInstallsMutation } from 'services/api/endpoints/models';
import { ModelInstallQueueItem } from './ModelInstallQueueItem';
export const ModelInstallQueue = () => {
export const ModelInstallQueue = memo(() => {
const { data } = useListModelInstallsQuery();
const [_pruneCompletedModelInstalls] = usePruneCompletedModelInstallsMutation();
@ -61,4 +61,6 @@ export const ModelInstallQueue = () => {
</Box>
</Flex>
);
};
});
ModelInstallQueue.displayName = 'ModelInstallQueue';

14
invokeai/frontend/web/src/features/modelManagerV2/subpanels/AddModelPanel/ModelInstallQueue/ModelInstallQueueItem.tsx
View File

@ -2,7 +2,7 @@ import { Flex, IconButton, Progress, Text, Tooltip } from '@invoke-ai/ui-library
import { toast } from 'features/toast/toast';
import { t } from 'i18next';
import { isNil } from 'lodash-es';
import { useCallback, useMemo } from 'react';
import { memo, useCallback, useMemo } from 'react';
import { PiXBold } from 'react-icons/pi';
import { useCancelModelInstallMutation } from 'services/api/endpoints/models';
import type { ModelInstallJob } from 'services/api/types';
@ -25,7 +25,7 @@ const formatBytes = (bytes: number) => {
return `${bytes.toFixed(2)} ${units[i]}`;
};
export const ModelInstallQueueItem = (props: ModelListItemProps) => {
export const ModelInstallQueueItem = memo((props: ModelListItemProps) => {
const { installJob } = props;
const [deleteImportModel] = useCancelModelInstallMutation();
@ -124,7 +124,9 @@ export const ModelInstallQueueItem = (props: ModelListItemProps) => {
/>
</Flex>
);
};
});
ModelInstallQueueItem.displayName = 'ModelInstallQueueItem';
type TooltipLabelProps = {
installJob: ModelInstallJob;
@ -132,7 +134,7 @@ type TooltipLabelProps = {
source: string;
};
const TooltipLabel = ({ name, source, installJob }: TooltipLabelProps) => {
const TooltipLabel = memo(({ name, source, installJob }: TooltipLabelProps) => {
const progressString = useMemo(() => {
if (installJob.status !== 'downloading' || installJob.bytes === undefined || installJob.total_bytes === undefined) {
return '';
@ -156,4 +158,6 @@ const TooltipLabel = ({ name, source, installJob }: TooltipLabelProps) => {
)}
</>
);
};
});
TooltipLabel.displayName = 'TooltipLabel';

8
invokeai/frontend/web/src/features/modelManagerV2/subpanels/AddModelPanel/ScanFolder/ScanFolderForm.tsx
View File

@ -2,13 +2,13 @@ import { Button, Flex, FormControl, FormErrorMessage, FormHelperText, FormLabel,
import { useAppDispatch, useAppSelector } from 'app/store/storeHooks';
import { setScanPath } from 'features/modelManagerV2/store/modelManagerV2Slice';
import type { ChangeEventHandler } from 'react';
import { useCallback, useState } from 'react';
import { memo, useCallback, useState } from 'react';
import { useTranslation } from 'react-i18next';
import { useLazyScanFolderQuery } from 'services/api/endpoints/models';
import { ScanModelsResults } from './ScanFolderResults';
export const ScanModelsForm = () => {
export const ScanModelsForm = memo(() => {
const scanPath = useAppSelector((state) => state.modelmanagerV2.scanPath);
const dispatch = useAppDispatch();
const [errorMessage, setErrorMessage] = useState('');
@ -56,4 +56,6 @@ export const ScanModelsForm = () => {
{data && <ScanModelsResults results={data} />}
</Flex>
);
};
});
ScanModelsForm.displayName = 'ScanModelsForm';

8
invokeai/frontend/web/src/features/modelManagerV2/subpanels/AddModelPanel/ScanFolder/ScanFolderResultItem.tsx
View File

@ -1,5 +1,5 @@
import { Badge, Box, Flex, IconButton, Text } from '@invoke-ai/ui-library';
import { useCallback } from 'react';
import { memo, useCallback } from 'react';
import { useTranslation } from 'react-i18next';
import { PiPlusBold } from 'react-icons/pi';
import type { ScanFolderResponse } from 'services/api/endpoints/models';
@ -8,7 +8,7 @@ type Props = {
result: ScanFolderResponse[number];
installModel: (source: string) => void;
};
export const ScanModelResultItem = ({ result, installModel }: Props) => {
export const ScanModelResultItem = memo(({ result, installModel }: Props) => {
const { t } = useTranslation();
const handleInstall = useCallback(() => {
@ -30,4 +30,6 @@ export const ScanModelResultItem = ({ result, installModel }: Props) => {
</Box>
</Flex>
);
};
});
ScanModelResultItem.displayName = 'ScanModelResultItem';

8
invokeai/frontend/web/src/features/modelManagerV2/subpanels/AddModelPanel/ScanFolder/ScanFolderResults.tsx
View File

@ -14,7 +14,7 @@ import {
import ScrollableContent from 'common/components/OverlayScrollbars/ScrollableContent';
import { useInstallModel } from 'features/modelManagerV2/hooks/useInstallModel';
import type { ChangeEvent, ChangeEventHandler } from 'react';
import { useCallback, useMemo, useState } from 'react';
import { memo, useCallback, useMemo, useState } from 'react';
import { useTranslation } from 'react-i18next';
import { PiXBold } from 'react-icons/pi';
import type { ScanFolderResponse } from 'services/api/endpoints/models';
@ -25,7 +25,7 @@ type ScanModelResultsProps = {
results: ScanFolderResponse;
};
export const ScanModelsResults = ({ results }: ScanModelResultsProps) => {
export const ScanModelsResults = memo(({ results }: ScanModelResultsProps) => {
const { t } = useTranslation();
const [searchTerm, setSearchTerm] = useState('');
const [inplace, setInplace] = useState(true);
@ -116,4 +116,6 @@ export const ScanModelsResults = ({ results }: ScanModelResultsProps) => {
</Flex>
</>
);
};
});
ScanModelsResults.displayName = 'ScanModelsResults';

20
invokeai/frontend/web/src/features/modelManagerV2/subpanels/AddModelPanel/StarterModels/StartModelsResultItem.tsx
View File

@ -1,7 +1,7 @@
import { Badge, Box, Flex, IconButton, Text } from '@invoke-ai/ui-library';
import { useInstallModel } from 'features/modelManagerV2/hooks/useInstallModel';
import ModelBaseBadge from 'features/modelManagerV2/subpanels/ModelManagerPanel/ModelBaseBadge';
import { useCallback, useMemo } from 'react';
import { memo, useCallback, useMemo } from 'react';
import { useTranslation } from 'react-i18next';
import { PiPlusBold } from 'react-icons/pi';
import type { GetStarterModelsResponse } from 'services/api/endpoints/models';
@ -9,20 +9,22 @@ import type { GetStarterModelsResponse } from 'services/api/endpoints/models';
type Props = {
result: GetStarterModelsResponse[number];
};
export const StarterModelsResultItem = ({ result }: Props) => {
export const StarterModelsResultItem = memo(({ result }: Props) => {
const { t } = useTranslation();
const allSources = useMemo(() => {
const _allSources = [result.source];
const _allSources = [{ source: result.source, config: { name: result.name, description: result.description } }];
if (result.dependencies) {
_allSources.push(...result.dependencies.map((d) => d.source));
for (const d of result.dependencies) {
_allSources.push({ source: d.source, config: { name: d.name, description: d.description } });
}
}
return _allSources;
}, [result]);
const [installModel] = useInstallModel();
const onClick = useCallback(() => {
for (const source of allSources) {
installModel({ source });
for (const { config, source } of allSources) {
installModel({ config, source });
}
}, [allSources, installModel]);
@ -30,7 +32,7 @@ export const StarterModelsResultItem = ({ result }: Props) => {
<Flex alignItems="center" justifyContent="space-between" w="100%" gap={3}>
<Flex fontSize="sm" flexDir="column">
<Flex gap={3}>
<Badge h="min-content">{result.type.replace('_', ' ')}</Badge>
<Badge h="min-content">{result.type.replaceAll('_', ' ')}</Badge>
<ModelBaseBadge base={result.base} />
<Text fontWeight="semibold">{result.name}</Text>
</Flex>
@ -45,4 +47,6 @@ export const StarterModelsResultItem = ({ result }: Props) => {
</Box>
</Flex>
);
};
});
StarterModelsResultItem.displayName = 'StarterModelsResultItem';

7
invokeai/frontend/web/src/features/modelManagerV2/subpanels/AddModelPanel/StarterModels/StarterModelsForm.tsx
View File

@ -1,10 +1,11 @@
import { Flex } from '@invoke-ai/ui-library';
import { FetchingModelsLoader } from 'features/modelManagerV2/subpanels/ModelManagerPanel/FetchingModelsLoader';
import { memo } from 'react';
import { useGetStarterModelsQuery } from 'services/api/endpoints/models';
import { StarterModelsResults } from './StarterModelsResults';
export const StarterModelsForm = () => {
export const StarterModelsForm = memo(() => {
const { isLoading, data } = useGetStarterModelsQuery();
return (
@ -13,4 +14,6 @@ export const StarterModelsForm = () => {
{data && <StarterModelsResults results={data} />}
</Flex>
);
};
});
StarterModelsForm.displayName = 'StarterModelsForm';

26
invokeai/frontend/web/src/features/modelManagerV2/subpanels/AddModelPanel/StarterModels/StarterModelsResults.tsx
View File

@ -1,7 +1,7 @@
import { Flex, IconButton, Input, InputGroup, InputRightElement } from '@invoke-ai/ui-library';
import ScrollableContent from 'common/components/OverlayScrollbars/ScrollableContent';
import type { ChangeEventHandler } from 'react';
import { useCallback, useMemo, useState } from 'react';
import { memo, useCallback, useMemo, useState } from 'react';
import { useTranslation } from 'react-i18next';
import { PiXBold } from 'react-icons/pi';
import type { GetStarterModelsResponse } from 'services/api/endpoints/models';
@ -12,20 +12,30 @@ type StarterModelsResultsProps = {
results: NonNullable<GetStarterModelsResponse>;
};
export const StarterModelsResults = ({ results }: StarterModelsResultsProps) => {
export const StarterModelsResults = memo(({ results }: StarterModelsResultsProps) => {
const { t } = useTranslation();
const [searchTerm, setSearchTerm] = useState('');
const filteredResults = useMemo(() => {
return results.filter((result) => {
const name = result.name.toLowerCase();
const type = result.type.toLowerCase();
return name.includes(searchTerm.toLowerCase()) || type.includes(searchTerm.toLowerCase());
const trimmedSearchTerm = searchTerm.trim().toLowerCase();
const matchStrings = [
result.name.toLowerCase(),
result.type.toLowerCase().replaceAll('_', ' '),
result.description.toLowerCase(),
];
if (result.type === 'spandrel_image_to_image') {
matchStrings.push('upscale');
matchStrings.push('post-processing');
matchStrings.push('postprocessing');
matchStrings.push('post processing');
}
return matchStrings.some((matchString) => matchString.includes(trimmedSearchTerm));
});
}, [results, searchTerm]);
const handleSearch: ChangeEventHandler<HTMLInputElement> = useCallback((e) => {
setSearchTerm(e.target.value.trim());
setSearchTerm(e.target.value);
}, []);
const clearSearch = useCallback(() => {
@ -69,4 +79,6 @@ export const StarterModelsResults = ({ results }: StarterModelsResultsProps) =>
</Flex>
</Flex>
);
};
});
StarterModelsResults.displayName = 'StarterModelsResults';

26
invokeai/frontend/web/src/features/modelManagerV2/subpanels/InstallModels.tsx
View File

@ -1,28 +1,28 @@
import { Box, Flex, Heading, Tab, TabList, TabPanel, TabPanels, Tabs } from '@invoke-ai/ui-library';
import { useStore } from '@nanostores/react';
import { StarterModelsForm } from 'features/modelManagerV2/subpanels/AddModelPanel/StarterModels/StarterModelsForm';
import { useMemo } from 'react';
import { atom } from 'nanostores';
import { memo, useCallback } from 'react';
import { useTranslation } from 'react-i18next';
import { useMainModels } from 'services/api/hooks/modelsByType';
import { HuggingFaceForm } from './AddModelPanel/HuggingFaceFolder/HuggingFaceForm';
import { InstallModelForm } from './AddModelPanel/InstallModelForm';
import { ModelInstallQueue } from './AddModelPanel/ModelInstallQueue/ModelInstallQueue';
import { ScanModelsForm } from './AddModelPanel/ScanFolder/ScanFolderForm';
export const InstallModels = () => {
export const $installModelsTab = atom(0);
export const InstallModels = memo(() => {
const { t } = useTranslation();
const [mainModels, { data }] = useMainModels();
const defaultIndex = useMemo(() => {
if (data && mainModels.length) {
return 0;
}
return 3;
}, [data, mainModels.length]);
const index = useStore($installModelsTab);
const onChange = useCallback((index: number) => {
$installModelsTab.set(index);
}, []);
return (
<Flex layerStyle="first" borderRadius="base" w="full" h="full" flexDir="column" gap={4}>
<Heading fontSize="xl">{t('modelManager.addModel')}</Heading>
<Tabs variant="collapse" height="50%" display="flex" flexDir="column" defaultIndex={defaultIndex}>
<Tabs variant="collapse" height="50%" display="flex" flexDir="column" index={index} onChange={onChange}>
<TabList>
<Tab>{t('modelManager.urlOrLocalPath')}</Tab>
<Tab>{t('modelManager.huggingFace')}</Tab>
@ -49,4 +49,6 @@ export const InstallModels = () => {
</Box>
</Flex>
);
};
});
InstallModels.displayName = 'InstallModels';

8
invokeai/frontend/web/src/features/modelManagerV2/subpanels/ModelManager.tsx
View File

@ -1,14 +1,14 @@
import { Button, Flex, Heading } from '@invoke-ai/ui-library';
import { useAppDispatch } from 'app/store/storeHooks';
import { setSelectedModelKey } from 'features/modelManagerV2/store/modelManagerV2Slice';
import { useCallback } from 'react';
import { memo, useCallback } from 'react';
import { useTranslation } from 'react-i18next';
import { PiPlusBold } from 'react-icons/pi';
import ModelList from './ModelManagerPanel/ModelList';
import { ModelListNavigation } from './ModelManagerPanel/ModelListNavigation';
export const ModelManager = () => {
export const ModelManager = memo(() => {
const { t } = useTranslation();
const dispatch = useAppDispatch();
const handleClickAddModel = useCallback(() => {
@ -29,4 +29,6 @@ export const ModelManager = () => {
</Flex>
</Flex>
);
};
});
ModelManager.displayName = 'ModelManager';

3
invokeai/frontend/web/src/features/modelManagerV2/subpanels/ModelManagerPanel/ModelList.tsx
View File

@ -21,7 +21,8 @@ import { FetchingModelsLoader } from './FetchingModelsLoader';
import { ModelListWrapper } from './ModelListWrapper';
const ModelList = () => {
const { searchTerm, filteredModelType } = useAppSelector((s) => s.modelmanagerV2);
const filteredModelType = useAppSelector((s) => s.modelmanagerV2.filteredModelType);
const searchTerm = useAppSelector((s) => s.modelmanagerV2.searchTerm);
const { t } = useTranslation();
const [mainModels, { isLoading: isLoadingMainModels }] = useMainModels();

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