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Testing onnx in new ui updates

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This commit is contained in:
Brandon Rising 2023-07-14 14:24:15 -04:00
parent 524888bf3b
commit bd7b59910d
28 changed files with 698 additions and 385 deletions
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115
invokeai/app/invocations/onnx.py
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@ -430,3 +430,118 @@ class ONNXSD1ModelLoaderInvocation(BaseInvocation):
),
)
)
class OnnxModelField(BaseModel):
"""Onnx model field"""
model_name: str = Field(description="Name of the model")
base_model: BaseModelType = Field(description="Base model")
class OnnxModelLoaderInvocation(BaseInvocation):
"""Loads a main model, outputting its submodels."""
type: Literal["onnx_model_loader"] = "onnx_model_loader"
model: OnnxModelField = Field(description="The model to load")
# TODO: precision?
# Schema customisation
class Config(InvocationConfig):
schema_extra = {
"ui": {
"title": "Onnx Model Loader",
"tags": ["model", "loader"],
"type_hints": {"model": "model"},
},
}
def invoke(self, context: InvocationContext) -> ONNXModelLoaderOutput:
base_model = self.model.base_model
model_name = self.model.model_name
model_type = ModelType.ONNX
# TODO: not found exceptions
if not context.services.model_manager.model_exists(
model_name=model_name,
base_model=base_model,
model_type=model_type,
):
raise Exception(f"Unknown {base_model} {model_type} model: {model_name}")
"""
if not context.services.model_manager.model_exists(
model_name=self.model_name,
model_type=SDModelType.Diffusers,
submodel=SDModelType.Tokenizer,
):
raise Exception(
f"Failed to find tokenizer submodel in {self.model_name}! Check if model corrupted"
)
if not context.services.model_manager.model_exists(
model_name=self.model_name,
model_type=SDModelType.Diffusers,
submodel=SDModelType.TextEncoder,
):
raise Exception(
f"Failed to find text_encoder submodel in {self.model_name}! Check if model corrupted"
)
if not context.services.model_manager.model_exists(
model_name=self.model_name,
model_type=SDModelType.Diffusers,
submodel=SDModelType.UNet,
):
raise Exception(
f"Failed to find unet submodel from {self.model_name}! Check if model corrupted"
)
"""
return ONNXModelLoaderOutput(
unet=UNetField(
unet=ModelInfo(
model_name=model_name,
base_model=base_model,
model_type=model_type,
submodel=SubModelType.UNet,
),
scheduler=ModelInfo(
model_name=model_name,
base_model=base_model,
model_type=model_type,
submodel=SubModelType.Scheduler,
),
loras=[],
),
clip=ClipField(
tokenizer=ModelInfo(
model_name=model_name,
base_model=base_model,
model_type=model_type,
submodel=SubModelType.Tokenizer,
),
text_encoder=ModelInfo(
model_name=model_name,
base_model=base_model,
model_type=model_type,
submodel=SubModelType.TextEncoder,
),
loras=[],
),
vae_decoder=VaeField(
vae=ModelInfo(
model_name=model_name,
base_model=base_model,
model_type=model_type,
submodel=SubModelType.VaeDecoder,
),
),
vae_encoder=VaeField(
vae=ModelInfo(
model_name=model_name,
base_model=base_model,
model_type=model_type,
submodel=SubModelType.VaeEncoder,
),
)
)

2
invokeai/backend/model_management/model_probe.py
View File

@ -22,7 +22,7 @@ class ModelProbeInfo(object):
variant_type: ModelVariantType
prediction_type: SchedulerPredictionType
upcast_attention: bool
format: Literal['diffusers','checkpoint', 'lycoris']
format: Literal['diffusers','checkpoint', 'lycoris', 'olive']
image_size: int
class ProbeBase(object):

199
invokeai/frontend/web/dist/assets/App-a44d46fe.js vendored
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199
invokeai/frontend/web/dist/assets/App-e42b1b26.js vendored Normal file
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2
invokeai/frontend/web/dist/assets/MantineProvider-8988d217.js → invokeai/frontend/web/dist/assets/MantineProvider-ffc3d7ba.js vendored
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File diff suppressed because one or more lines are too long

2
invokeai/frontend/web/dist/assets/ThemeLocaleProvider-3cf60466.js → invokeai/frontend/web/dist/assets/ThemeLocaleProvider-f28934f1.js vendored
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@ -1,4 +1,4 @@
import{v as S,ga as Ze,q as k,M as Et,gb as Dt,ae as bt,ag as c,gc as v,gd as jt,ge as a,gf as Rt,gg as p,gh as vt,gi as Ht,gj as Wt,aX as Vt,gk as Lt,Z as Ot,gl as qt,gm as Nt,gn as Gt,go as Ut,aV as Xt}from"./index-078526aa.js";import{M as Yt}from"./MantineProvider-8988d217.js";var ut=String.raw,ft=ut`
import{v as S,gn as Ze,q as k,M as Et,go as Dt,ae as bt,ag as c,gp as v,gq as jt,gr as a,gs as Rt,gt as p,gu as vt,gv as Ht,gw as Wt,aX as Vt,gx as Lt,Z as Ot,gy as qt,gz as Nt,gA as Gt,gB as Ut,aV as Xt}from"./index-63d3e2f4.js";import{M as Yt}from"./MantineProvider-ffc3d7ba.js";var ut=String.raw,ft=ut`
:root,
:host {
--chakra-vh: 100vh;

125
invokeai/frontend/web/dist/assets/index-078526aa.js vendored
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125
invokeai/frontend/web/dist/assets/index-63d3e2f4.js vendored Normal file
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2
invokeai/frontend/web/dist/index.html vendored
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@ -12,7 +12,7 @@
margin: 0;
}
</style>
<script type="module" crossorigin src="./assets/index-078526aa.js"></script>
<script type="module" crossorigin src="./assets/index-63d3e2f4.js"></script>
</head>
<body dir="ltr">

17
invokeai/frontend/web/dist/locales/en.json vendored
View File

@ -102,7 +102,8 @@
"openInNewTab": "Open in New Tab",
"dontAskMeAgain": "Don't ask me again",
"areYouSure": "Are you sure?",
"imagePrompt": "Image Prompt"
"imagePrompt": "Image Prompt",
"clearNodes": "Are you sure you want to clear all nodes?"
},
"gallery": {
"generations": "Generations",
@ -528,7 +529,7 @@
"hidePreview": "Hide Preview",
"showPreview": "Show Preview",
"controlNetControlMode": "Control Mode",
"clipSkip": "Clip Skip",
"clipSkip": "CLIP Skip",
"aspectRatio": "Ratio"
},
"settings": {
@ -593,7 +594,11 @@
"metadataLoadFailed": "Failed to load metadata",
"initialImageSet": "Initial Image Set",
"initialImageNotSet": "Initial Image Not Set",
"initialImageNotSetDesc": "Could not load initial image"
"initialImageNotSetDesc": "Could not load initial image",
"nodesSaved": "Nodes Saved",
"nodesLoaded": "Nodes Loaded",
"nodesLoadedFailed": "Failed To Load Nodes",
"nodesCleared": "Nodes Cleared"
},
"tooltip": {
"feature": {
@ -674,5 +679,11 @@
"showProgressImages": "Show Progress Images",
"hideProgressImages": "Hide Progress Images",
"swapSizes": "Swap Sizes"
},
"nodes": {
"reloadSchema": "Reload Schema",
"saveNodes": "Save Nodes",
"loadNodes": "Load Nodes",
"clearNodes": "Clear Nodes"
}
}

43
invokeai/frontend/web/src/features/nodes/components/fields/ModelInputFieldComponent.tsx
View File

@ -11,7 +11,10 @@ import { MODEL_TYPE_MAP as BASE_MODEL_NAME_MAP } from 'features/system/component
import { forEach, isString } from 'lodash-es';
import { memo, useCallback, useEffect, useMemo } from 'react';
import { useTranslation } from 'react-i18next';
import { useGetMainModelsQuery } from 'services/api/endpoints/models';
import {
useGetMainModelsQuery,
useGetOnnxModelsQuery,
} from 'services/api/endpoints/models';
import { FieldComponentProps } from './types';
const ModelInputFieldComponent = (
@ -23,6 +26,7 @@ const ModelInputFieldComponent = (
const { t } = useTranslation();
const { data: mainModels } = useGetMainModelsQuery();
const { data: onnxModels } = useGetOnnxModelsQuery();
const data = useMemo(() => {
if (!mainModels) {
@ -43,12 +47,33 @@ const ModelInputFieldComponent = (
});
});
if (onnxModels) {
forEach(onnxModels.entities, (model, id) => {
if (!model) {
return;
}
data.push({
value: id,
label: model.model_name,
group: BASE_MODEL_NAME_MAP[model.base_model],
});
});
}
return data;
}, [mainModels]);
}, [mainModels, onnxModels]);
const selectedModel = useMemo(
() => mainModels?.entities[field.value ?? mainModels.ids[0]],
[mainModels?.entities, mainModels?.ids, field.value]
() =>
mainModels?.entities[field.value ?? mainModels.ids[0]] ||
onnxModels?.entities[field.value ?? onnxModels.ids[0]],
[
mainModels?.entities,
mainModels?.ids,
onnxModels?.entities,
onnxModels?.ids,
field.value,
]
);
const handleValueChanged = useCallback(
@ -69,18 +94,22 @@ const ModelInputFieldComponent = (
);
useEffect(() => {
if (field.value && mainModels?.ids.includes(field.value)) {
if (
field.value &&
(mainModels?.ids.includes(field.value) ||
onnxModels?.ids.includes(field.value))
) {
return;
}
const firstModel = mainModels?.ids[0];
const firstModel = mainModels?.ids[0] || onnxModels?.ids[0];
if (!isString(firstModel)) {
return;
}
handleValueChanged(firstModel);
}, [field.value, handleValueChanged, mainModels?.ids]);
}, [field.value, handleValueChanged, mainModels?.ids, onnxModels?.ids]);
return (
<IAIMantineSelect

10
invokeai/frontend/web/src/features/nodes/util/graphBuilders/addLoRAsToGraph.ts
View File

@ -10,6 +10,7 @@ import {
CLIP_SKIP,
LORA_LOADER,
MAIN_MODEL_LOADER,
ONNX_MODEL_LOADER,
METADATA_ACCUMULATOR,
NEGATIVE_CONDITIONING,
POSITIVE_CONDITIONING,
@ -41,6 +42,10 @@ export const addLoRAsToGraph = (
!(
e.source.node_id === MAIN_MODEL_LOADER &&
['unet'].includes(e.source.field)
) &&
!(
e.source.node_id === ONNX_MODEL_LOADER &&
['unet'].includes(e.source.field)
)
);
// Remove CLIP_SKIP connections to conditionings to feed it through LoRAs
@ -77,11 +82,14 @@ export const addLoRAsToGraph = (
// add to graph
graph.nodes[currentLoraNodeId] = loraLoaderNode;
const model_loader = id.includes('onnx')
? ONNX_MODEL_LOADER
: MAIN_MODEL_LOADER;
if (currentLoraIndex === 0) {
// first lora = start the lora chain, attach directly to model loader
graph.edges.push({
source: {
node_id: MAIN_MODEL_LOADER,
node_id: model_loader,
field: 'unet',
},
destination: {

11
invokeai/frontend/web/src/features/nodes/util/graphBuilders/addVAEToGraph.ts
View File

@ -10,6 +10,7 @@ import {
LATENTS_TO_IMAGE,
MAIN_MODEL_LOADER,
METADATA_ACCUMULATOR,
ONNX_MODEL_LOADER,
TEXT_TO_IMAGE_GRAPH,
VAE_LOADER,
} from './constants';
@ -33,11 +34,13 @@ export const addVAEToGraph = (
vae_model,
};
}
const model_loader = vae?.id.includes('onnx')
? ONNX_MODEL_LOADER
: MAIN_MODEL_LOADER;
if (graph.id === TEXT_TO_IMAGE_GRAPH || graph.id === IMAGE_TO_IMAGE_GRAPH) {
graph.edges.push({
source: {
node_id: isAutoVae ? MAIN_MODEL_LOADER : VAE_LOADER,
node_id: isAutoVae ? model_loader : VAE_LOADER,
field: 'vae',
},
destination: {
@ -50,7 +53,7 @@ export const addVAEToGraph = (
if (graph.id === IMAGE_TO_IMAGE_GRAPH) {
graph.edges.push({
source: {
node_id: isAutoVae ? MAIN_MODEL_LOADER : VAE_LOADER,
node_id: isAutoVae ? model_loader : VAE_LOADER,
field: 'vae',
},
destination: {
@ -63,7 +66,7 @@ export const addVAEToGraph = (
if (graph.id === INPAINT_GRAPH) {
graph.edges.push({
source: {
node_id: isAutoVae ? MAIN_MODEL_LOADER : VAE_LOADER,
node_id: isAutoVae ? model_loader : VAE_LOADER,
field: 'vae',
},
destination: {

17
invokeai/frontend/web/src/features/nodes/util/graphBuilders/buildCanvasImageToImageGraph.ts
View File

@ -18,6 +18,7 @@ import {
LATENTS_TO_IMAGE,
LATENTS_TO_LATENTS,
MAIN_MODEL_LOADER,
ONNX_MODEL_LOADER,
METADATA_ACCUMULATOR,
NEGATIVE_CONDITIONING,
NOISE,
@ -59,6 +60,11 @@ export const buildCanvasImageToImageGraph = (
? shouldUseCpuNoise
: initialGenerationState.shouldUseCpuNoise;
console.log(model);
const model_loader = model.model_name.includes('onnx')
? ONNX_MODEL_LOADER
: MAIN_MODEL_LOADER;
/**
* The easiest way to build linear graphs is to do it in the node editor, then copy and paste the
* full graph here as a template. Then use the parameters from app state and set friendlier node
@ -69,6 +75,7 @@ export const buildCanvasImageToImageGraph = (
*/
// copy-pasted graph from node editor, filled in with state values & friendly node ids
// TODO: Actually create the graph correctly for ONNX
const graph: NonNullableGraph = {
id: IMAGE_TO_IMAGE_GRAPH,
nodes: {
@ -87,9 +94,9 @@ export const buildCanvasImageToImageGraph = (
id: NOISE,
use_cpu,
},
[MAIN_MODEL_LOADER]: {
type: 'main_model_loader',
id: MAIN_MODEL_LOADER,
[model_loader]: {
type: model_loader,
id: model_loader,
model,
},
[CLIP_SKIP]: {
@ -121,7 +128,7 @@ export const buildCanvasImageToImageGraph = (
edges: [
{
source: {
node_id: MAIN_MODEL_LOADER,
node_id: model_loader,
field: 'clip',
},
destination: {
@ -181,7 +188,7 @@ export const buildCanvasImageToImageGraph = (
},
{
source: {
node_id: MAIN_MODEL_LOADER,
node_id: model_loader,
field: 'unet',
},
destination: {

17
invokeai/frontend/web/src/features/nodes/util/graphBuilders/buildCanvasInpaintGraph.ts
View File

@ -15,6 +15,7 @@ import {
INPAINT_GRAPH,
ITERATE,
MAIN_MODEL_LOADER,
ONNX_MODEL_LOADER,
NEGATIVE_CONDITIONING,
POSITIVE_CONDITIONING,
RANDOM_INT,
@ -63,6 +64,12 @@ export const buildCanvasInpaintGraph = (
// We may need to set the inpaint width and height to scale the image
const { scaledBoundingBoxDimensions, boundingBoxScaleMethod } = state.canvas;
console.log(model);
const model_loader = model.model_name.includes('onnx')
? ONNX_MODEL_LOADER
: MAIN_MODEL_LOADER;
// TODO: Actually create the graph correctly for ONNX
const graph: NonNullableGraph = {
id: INPAINT_GRAPH,
nodes: {
@ -107,9 +114,9 @@ export const buildCanvasInpaintGraph = (
id: NEGATIVE_CONDITIONING,
prompt: negativePrompt,
},
[MAIN_MODEL_LOADER]: {
type: 'main_model_loader',
id: MAIN_MODEL_LOADER,
[model_loader]: {
type: model_loader,
id: model_loader,
model,
},
[CLIP_SKIP]: {
@ -133,7 +140,7 @@ export const buildCanvasInpaintGraph = (
edges: [
{
source: {
node_id: MAIN_MODEL_LOADER,
node_id: model_loader,
field: 'unet',
},
destination: {
@ -143,7 +150,7 @@ export const buildCanvasInpaintGraph = (
},
{
source: {
node_id: MAIN_MODEL_LOADER,
node_id: model_loader,
field: 'clip',
},
destination: {

17
invokeai/frontend/web/src/features/nodes/util/graphBuilders/buildCanvasTextToImageGraph.ts
View File

@ -10,6 +10,7 @@ import {
CLIP_SKIP,
LATENTS_TO_IMAGE,
MAIN_MODEL_LOADER,
ONNX_MODEL_LOADER,
METADATA_ACCUMULATOR,
NEGATIVE_CONDITIONING,
NOISE,
@ -49,7 +50,10 @@ export const buildCanvasTextToImageGraph = (
const use_cpu = shouldUseNoiseSettings
? shouldUseCpuNoise
: initialGenerationState.shouldUseCpuNoise;
console.log(model);
const model_loader = model.model_name.includes('onnx')
? ONNX_MODEL_LOADER
: MAIN_MODEL_LOADER;
/**
* The easiest way to build linear graphs is to do it in the node editor, then copy and paste the
* full graph here as a template. Then use the parameters from app state and set friendlier node
@ -60,6 +64,7 @@ export const buildCanvasTextToImageGraph = (
*/
// copy-pasted graph from node editor, filled in with state values & friendly node ids
// TODO: Actually create the graph correctly for ONNX
const graph: NonNullableGraph = {
id: TEXT_TO_IMAGE_GRAPH,
nodes: {
@ -87,9 +92,9 @@ export const buildCanvasTextToImageGraph = (
scheduler,
steps,
},
[MAIN_MODEL_LOADER]: {
type: 'main_model_loader',
id: MAIN_MODEL_LOADER,
[model_loader]: {
type: model_loader,
id: model_loader,
model,
},
[CLIP_SKIP]: {
@ -125,7 +130,7 @@ export const buildCanvasTextToImageGraph = (
},
{
source: {
node_id: MAIN_MODEL_LOADER,
node_id: model_loader,
field: 'clip',
},
destination: {
@ -155,7 +160,7 @@ export const buildCanvasTextToImageGraph = (
},
{
source: {
node_id: MAIN_MODEL_LOADER,
node_id: model_loader,
field: 'unet',
},
destination: {

17
invokeai/frontend/web/src/features/nodes/util/graphBuilders/buildLinearImageToImageGraph.ts
View File

@ -17,6 +17,7 @@ import {
LATENTS_TO_IMAGE,
LATENTS_TO_LATENTS,
MAIN_MODEL_LOADER,
ONNX_MODEL_LOADER,
METADATA_ACCUMULATOR,
NEGATIVE_CONDITIONING,
NOISE,
@ -82,13 +83,19 @@ export const buildLinearImageToImageGraph = (
? shouldUseCpuNoise
: initialGenerationState.shouldUseCpuNoise;
console.log(model);
const model_loader = model.model_name.includes('onnx')
? ONNX_MODEL_LOADER
: MAIN_MODEL_LOADER;
// copy-pasted graph from node editor, filled in with state values & friendly node ids
// TODO: Actually create the graph correctly for ONNX
const graph: NonNullableGraph = {
id: IMAGE_TO_IMAGE_GRAPH,
nodes: {
[MAIN_MODEL_LOADER]: {
type: 'main_model_loader',
id: MAIN_MODEL_LOADER,
[model_loader]: {
type: model_loader,
id: model_loader,
model,
},
[CLIP_SKIP]: {
@ -135,7 +142,7 @@ export const buildLinearImageToImageGraph = (
edges: [
{
source: {
node_id: MAIN_MODEL_LOADER,
node_id: model_loader,
field: 'unet',
},
destination: {
@ -145,7 +152,7 @@ export const buildLinearImageToImageGraph = (
},
{
source: {
node_id: MAIN_MODEL_LOADER,
node_id: model_loader,
field: 'clip',
},
destination: {

17
invokeai/frontend/web/src/features/nodes/util/graphBuilders/buildLinearTextToImageGraph.ts
View File

@ -10,6 +10,7 @@ import {
CLIP_SKIP,
LATENTS_TO_IMAGE,
MAIN_MODEL_LOADER,
ONNX_MODEL_LOADER,
METADATA_ACCUMULATOR,
NEGATIVE_CONDITIONING,
NOISE,
@ -46,6 +47,10 @@ export const buildLinearTextToImageGraph = (
throw new Error('No model found in state');
}
console.log(model);
const model_loader = model.model_name.includes('onnx')
? ONNX_MODEL_LOADER
: MAIN_MODEL_LOADER;
/**
* The easiest way to build linear graphs is to do it in the node editor, then copy and paste the
* full graph here as a template. Then use the parameters from app state and set friendlier node
@ -56,12 +61,14 @@ export const buildLinearTextToImageGraph = (
*/
// copy-pasted graph from node editor, filled in with state values & friendly node ids
// TODO: Actually create the graph correctly for ONNX
const graph: NonNullableGraph = {
id: TEXT_TO_IMAGE_GRAPH,
nodes: {
[MAIN_MODEL_LOADER]: {
type: 'main_model_loader',
id: MAIN_MODEL_LOADER,
[model_loader]: {
type: model_loader,
id: model_loader,
model,
},
[CLIP_SKIP]: {
@ -101,7 +108,7 @@ export const buildLinearTextToImageGraph = (
edges: [
{
source: {
node_id: MAIN_MODEL_LOADER,
node_id: model_loader,
field: 'clip',
},
destination: {
@ -111,7 +118,7 @@ export const buildLinearTextToImageGraph = (
},
{
source: {
node_id: MAIN_MODEL_LOADER,
node_id: model_loader,
field: 'unet',
},
destination: {

1
invokeai/frontend/web/src/features/nodes/util/graphBuilders/constants.ts
View File

@ -8,6 +8,7 @@ export const RANDOM_INT = 'rand_int';
export const RANGE_OF_SIZE = 'range_of_size';
export const ITERATE = 'iterate';
export const MAIN_MODEL_LOADER = 'main_model_loader';
export const ONNX_MODEL_LOADER = 'onnx_model_loader';
export const VAE_LOADER = 'vae_loader';
export const LORA_LOADER = 'lora_loader';
export const CLIP_SKIP = 'clip_skip';

16
invokeai/frontend/web/src/features/nodes/util/modelIdToOnnxModelField.ts Normal file
View File

@ -0,0 +1,16 @@
import { BaseModelType, OnnxModelField } from 'services/api/types';
/**
* Crudely converts a model id to a main model field
* TODO: Make better
*/
export const modelIdToOnnxModelField = (modelId: string): OnnxModelField => {
const [base_model, model_type, model_name] = modelId.split('/');
const field: OnnxModelField = {
base_model: base_model as BaseModelType,
model_name,
};
return field;
};

4
invokeai/frontend/web/src/features/parameters/store/actions.ts
View File

@ -1,10 +1,10 @@
import { createAction } from '@reduxjs/toolkit';
import { ImageDTO, MainModelField } from 'services/api/types';
import { ImageDTO, MainModelField, OnnxModelField } from 'services/api/types';
export const initialImageSelected = createAction<ImageDTO | string | undefined>(
'generation/initialImageSelected'
);
export const modelSelected = createAction<MainModelField>(
export const modelSelected = createAction<MainModelField | OnnxModelField>(
'generation/modelSelected'
);

9
invokeai/frontend/web/src/features/parameters/store/generationSlice.ts
View File

@ -8,7 +8,7 @@ import {
setShouldShowAdvancedOptions,
} from 'features/ui/store/uiSlice';
import { clamp } from 'lodash-es';
import { ImageDTO, MainModelField } from 'services/api/types';
import { ImageDTO, MainModelField, OnnxModelField } from 'services/api/types';
import { clipSkipMap } from '../components/Parameters/Advanced/ParamClipSkip';
import {
CfgScaleParam,
@ -53,7 +53,7 @@ export interface GenerationState {
shouldUseSymmetry: boolean;
horizontalSymmetrySteps: number;
verticalSymmetrySteps: number;
model: MainModelField | null;
model: MainModelField | OnnxModelField | null;
vae: VaeModelParam | null;
seamlessXAxis: boolean;
seamlessYAxis: boolean;
@ -226,7 +226,10 @@ export const generationSlice = createSlice({
const { image_name, width, height } = action.payload;
state.initialImage = { imageName: image_name, width, height };
},
modelChanged: (state, action: PayloadAction<MainModelField | null>) => {
modelChanged: (
state,
action: PayloadAction<MainModelField | OnnxModelField | null>
) => {
if (!action.payload) {
state.model = null;
}

33
invokeai/frontend/web/src/features/system/components/ModelSelect.tsx
View File

@ -11,7 +11,11 @@ import { defaultSelectorOptions } from 'app/store/util/defaultMemoizeOptions';
import { modelIdToMainModelField } from 'features/nodes/util/modelIdToMainModelField';
import { modelSelected } from 'features/parameters/store/actions';
import { forEach } from 'lodash-es';
import { useGetMainModelsQuery } from 'services/api/endpoints/models';
import {
useGetMainModelsQuery,
useGetOnnxModelsQuery,
} from 'services/api/endpoints/models';
import { modelIdToOnnxModelField } from 'features/nodes/util/modelIdToOnnxModelField';
export const MODEL_TYPE_MAP = {
'sd-1': 'Stable Diffusion 1.x',
@ -31,6 +35,7 @@ const ModelSelect = () => {
const { currentModel } = useAppSelector(selector);
const { data: mainModels, isLoading } = useGetMainModelsQuery();
const { data: onnxModels, isLoading: onnxLoading } = useGetOnnxModelsQuery();
const data = useMemo(() => {
if (!mainModels) {
@ -50,16 +55,30 @@ const ModelSelect = () => {
group: MODEL_TYPE_MAP[model.base_model],
});
});
forEach(onnxModels?.entities, (model, id) => {
if (!model) {
return;
}
data.push({
value: id,
label: model.model_name,
group: MODEL_TYPE_MAP[model.base_model],
});
});
return data;
}, [mainModels]);
}, [mainModels, onnxModels]);
const selectedModel = useMemo(
() =>
mainModels?.entities[
`${currentModel?.base_model}/main/${currentModel?.model_name}`
] ||
onnxModels?.entities[
`${currentModel?.base_model}/onnx/${currentModel?.model_name}`
],
[mainModels?.entities, currentModel]
[mainModels?.entities, onnxModels?.entities, currentModel]
);
const handleChangeModel = useCallback(
@ -67,14 +86,16 @@ const ModelSelect = () => {
if (!v) {
return;
}
const modelField = modelIdToMainModelField(v);
let modelField = modelIdToMainModelField(v);
if (v.includes('onnx')) {
modelField = modelIdToOnnxModelField(v);
}
dispatch(modelSelected(modelField));
},
[dispatch]
);
return isLoading ? (
return isLoading || onnxLoading ? (
<IAIMantineSelect
label={t('modelManager.model')}
placeholder="Loading..."

2
invokeai/frontend/web/src/features/ui/components/tabs/ModelManager/subpanels/ModelManagerPanel/ModelList.tsx
View File

@ -50,7 +50,7 @@ const ModelList = () => {
const [searchText, setSearchText] = useState<string>('');
const [isSelectedFilter, setIsSelectedFilter] = useState<
'all' | 'ckpt' | 'diffusers'
'all' | 'ckpt' | 'diffusers' | 'olive'
>('all');
const [_, startTransition] = useTransition();

41
invokeai/frontend/web/src/services/api/endpoints/models.ts
View File

@ -5,6 +5,7 @@ import {
ControlNetModelConfig,
LoRAModelConfig,
MainModelConfig,
OnnxModelConfig,
TextualInversionModelConfig,
VaeModelConfig,
} from 'services/api/types';
@ -13,6 +14,8 @@ import { ApiFullTagDescription, LIST_TAG, api } from '..';
export type MainModelConfigEntity = MainModelConfig & { id: string };
export type OnnxModelConfigEntity = OnnxModelConfig & { id: string };
export type LoRAModelConfigEntity = LoRAModelConfig & { id: string };
export type ControlNetModelConfigEntity = ControlNetModelConfig & {
@ -27,6 +30,7 @@ export type VaeModelConfigEntity = VaeModelConfig & { id: string };
type AnyModelConfigEntity =
| MainModelConfigEntity
| OnnxModelConfigEntity
| LoRAModelConfigEntity
| ControlNetModelConfigEntity
| TextualInversionModelConfigEntity
@ -35,6 +39,10 @@ type AnyModelConfigEntity =
const mainModelsAdapter = createEntityAdapter<MainModelConfigEntity>({
sortComparer: (a, b) => a.model_name.localeCompare(b.model_name),
});
const onnxModelsAdapter = createEntityAdapter<OnnxModelConfigEntity>({
sortComparer: (a, b) => a.model_name.localeCompare(b.model_name),
});
const loraModelsAdapter = createEntityAdapter<LoRAModelConfigEntity>({
sortComparer: (a, b) => a.model_name.localeCompare(b.model_name),
});
@ -72,6 +80,38 @@ const createModelEntities = <T extends AnyModelConfigEntity>(
export const modelsApi = api.injectEndpoints({
endpoints: (build) => ({
getOnnxModels: build.query<EntityState<OnnxModelConfigEntity>, void>({
query: () => ({ url: 'models/', params: { model_type: 'onnx' } }),
providesTags: (result, error, arg) => {
const tags: ApiFullTagDescription[] = [
{ id: 'OnnxModel', type: LIST_TAG },
];
if (result) {
tags.push(
...result.ids.map((id) => ({
type: 'OnnxModel' as const,
id,
}))
);
}
return tags;
},
transformResponse: (
response: { models: OnnxModelConfig[] },
meta,
arg
) => {
const entities = createModelEntities<OnnxModelConfigEntity>(
response.models
);
return onnxModelsAdapter.setAll(
onnxModelsAdapter.getInitialState(),
entities
);
},
}),
getMainModels: build.query<EntityState<MainModelConfigEntity>, void>({
query: () => ({ url: 'models/', params: { model_type: 'main' } }),
providesTags: (result, error, arg) => {
@ -243,6 +283,7 @@ export const modelsApi = api.injectEndpoints({
export const {
useGetMainModelsQuery,
useGetOnnxModelsQuery,
useGetControlNetModelsQuery,
useGetLoRAModelsQuery,
useGetTextualInversionModelsQuery,

1
invokeai/frontend/web/src/services/api/models/ONNXStableDiffusion1ModelConfig.ts
View File

@ -12,7 +12,6 @@ export type ONNXStableDiffusion1ModelConfig = {
type: 'onnx';
path: string;
description?: string;
model_format: null;
error?: ModelError;
variant: ModelVariantType;
};

34
invokeai/frontend/web/src/services/api/schema.d.ts vendored
View File

@ -1174,7 +1174,7 @@ export type components = {
* @description The nodes in this graph
*/
nodes?: {
[key: string]: (components["schemas"]["LoadImageInvocation"] | components["schemas"]["ShowImageInvocation"] | components["schemas"]["ImageCropInvocation"] | components["schemas"]["ImagePasteInvocation"] | components["schemas"]["MaskFromAlphaInvocation"] | components["schemas"]["ImageMultiplyInvocation"] | components["schemas"]["ImageChannelInvocation"] | components["schemas"]["ImageConvertInvocation"] | components["schemas"]["ImageBlurInvocation"] | components["schemas"]["ImageResizeInvocation"] | components["schemas"]["ImageScaleInvocation"] | components["schemas"]["ImageLerpInvocation"] | components["schemas"]["ImageInverseLerpInvocation"] | components["schemas"]["ControlNetInvocation"] | components["schemas"]["ImageProcessorInvocation"] | components["schemas"]["MainModelLoaderInvocation"] | components["schemas"]["LoraLoaderInvocation"] | components["schemas"]["VaeLoaderInvocation"] | components["schemas"]["MetadataAccumulatorInvocation"] | components["schemas"]["DynamicPromptInvocation"] | components["schemas"]["CompelInvocation"] | components["schemas"]["ClipSkipInvocation"] | components["schemas"]["AddInvocation"] | components["schemas"]["SubtractInvocation"] | components["schemas"]["MultiplyInvocation"] | components["schemas"]["DivideInvocation"] | components["schemas"]["RandomIntInvocation"] | components["schemas"]["ParamIntInvocation"] | components["schemas"]["ParamFloatInvocation"] | components["schemas"]["TextToLatentsInvocation"] | components["schemas"]["LatentsToImageInvocation"] | components["schemas"]["ResizeLatentsInvocation"] | components["schemas"]["ScaleLatentsInvocation"] | components["schemas"]["ImageToLatentsInvocation"] | components["schemas"]["CvInpaintInvocation"] | components["schemas"]["RangeInvocation"] | components["schemas"]["RangeOfSizeInvocation"] | components["schemas"]["RandomRangeInvocation"] | components["schemas"]["ImageCollectionInvocation"] | components["schemas"]["FloatLinearRangeInvocation"] | components["schemas"]["StepParamEasingInvocation"] | components["schemas"]["NoiseInvocation"] | components["schemas"]["UpscaleInvocation"] | components["schemas"]["RestoreFaceInvocation"] | components["schemas"]["InpaintInvocation"] | components["schemas"]["InfillColorInvocation"] | components["schemas"]["InfillTileInvocation"] | components["schemas"]["InfillPatchMatchInvocation"] | components["schemas"]["GraphInvocation"] | components["schemas"]["IterateInvocation"] | components["schemas"]["CollectInvocation"] | components["schemas"]["CannyImageProcessorInvocation"] | components["schemas"]["HedImageProcessorInvocation"] | components["schemas"]["LineartImageProcessorInvocation"] | components["schemas"]["LineartAnimeImageProcessorInvocation"] | components["schemas"]["OpenposeImageProcessorInvocation"] | components["schemas"]["MidasDepthImageProcessorInvocation"] | components["schemas"]["NormalbaeImageProcessorInvocation"] | components["schemas"]["MlsdImageProcessorInvocation"] | components["schemas"]["PidiImageProcessorInvocation"] | components["schemas"]["ContentShuffleImageProcessorInvocation"] | components["schemas"]["ZoeDepthImageProcessorInvocation"] | components["schemas"]["MediapipeFaceProcessorInvocation"] | components["schemas"]["LeresImageProcessorInvocation"] | components["schemas"]["TileResamplerProcessorInvocation"] | components["schemas"]["SegmentAnythingProcessorInvocation"] | components["schemas"]["LatentsToLatentsInvocation"]) | undefined;
[key: string]: (components["schemas"]["LoadImageInvocation"] | components["schemas"]["ShowImageInvocation"] | components["schemas"]["ImageCropInvocation"] | components["schemas"]["ImagePasteInvocation"] | components["schemas"]["MaskFromAlphaInvocation"] | components["schemas"]["ImageMultiplyInvocation"] | components["schemas"]["ImageChannelInvocation"] | components["schemas"]["ImageConvertInvocation"] | components["schemas"]["ImageBlurInvocation"] | components["schemas"]["ImageResizeInvocation"] | components["schemas"]["ImageScaleInvocation"] | components["schemas"]["ImageLerpInvocation"] | components["schemas"]["ImageInverseLerpInvocation"] | components["schemas"]["ControlNetInvocation"] | components["schemas"]["ImageProcessorInvocation"] | components["schemas"]["MainModelLoaderInvocation"] | components["schemas"]["OnnxModelLoaderInvocation"] | components["schemas"]["LoraLoaderInvocation"] | components["schemas"]["VaeLoaderInvocation"] | components["schemas"]["MetadataAccumulatorInvocation"] | components["schemas"]["DynamicPromptInvocation"] | components["schemas"]["CompelInvocation"] | components["schemas"]["ClipSkipInvocation"] | components["schemas"]["AddInvocation"] | components["schemas"]["SubtractInvocation"] | components["schemas"]["MultiplyInvocation"] | components["schemas"]["DivideInvocation"] | components["schemas"]["RandomIntInvocation"] | components["schemas"]["ParamIntInvocation"] | components["schemas"]["ParamFloatInvocation"] | components["schemas"]["TextToLatentsInvocation"] | components["schemas"]["LatentsToImageInvocation"] | components["schemas"]["ResizeLatentsInvocation"] | components["schemas"]["ScaleLatentsInvocation"] | components["schemas"]["ImageToLatentsInvocation"] | components["schemas"]["CvInpaintInvocation"] | components["schemas"]["RangeInvocation"] | components["schemas"]["RangeOfSizeInvocation"] | components["schemas"]["RandomRangeInvocation"] | components["schemas"]["ImageCollectionInvocation"] | components["schemas"]["FloatLinearRangeInvocation"] | components["schemas"]["StepParamEasingInvocation"] | components["schemas"]["NoiseInvocation"] | components["schemas"]["UpscaleInvocation"] | components["schemas"]["RestoreFaceInvocation"] | components["schemas"]["InpaintInvocation"] | components["schemas"]["InfillColorInvocation"] | components["schemas"]["InfillTileInvocation"] | components["schemas"]["InfillPatchMatchInvocation"] | components["schemas"]["GraphInvocation"] | components["schemas"]["IterateInvocation"] | components["schemas"]["CollectInvocation"] | components["schemas"]["CannyImageProcessorInvocation"] | components["schemas"]["HedImageProcessorInvocation"] | components["schemas"]["LineartImageProcessorInvocation"] | components["schemas"]["LineartAnimeImageProcessorInvocation"] | components["schemas"]["OpenposeImageProcessorInvocation"] | components["schemas"]["MidasDepthImageProcessorInvocation"] | components["schemas"]["NormalbaeImageProcessorInvocation"] | components["schemas"]["MlsdImageProcessorInvocation"] | components["schemas"]["PidiImageProcessorInvocation"] | components["schemas"]["ContentShuffleImageProcessorInvocation"] | components["schemas"]["ZoeDepthImageProcessorInvocation"] | components["schemas"]["MediapipeFaceProcessorInvocation"] | components["schemas"]["LeresImageProcessorInvocation"] | components["schemas"]["TileResamplerProcessorInvocation"] | components["schemas"]["SegmentAnythingProcessorInvocation"] | components["schemas"]["LatentsToLatentsInvocation"]) | undefined;
};
/**
* Edges
@ -2904,6 +2904,34 @@ export type components = {
*/
model: components["schemas"]["MainModelField"];
};
/**
* OnnxModelLoaderInvocation
* @description Loads an onnx model, outputting its submodels.
*/
OnnxModelLoaderInvocation: {
/**
* Id
* @description The id of this node. Must be unique among all nodes.
*/
id: string;
/**
* Is Intermediate
* @description Whether or not this node is an intermediate node.
* @default false
*/
is_intermediate?: boolean;
/**
* Type
* @default onnx_model_loader
* @enum {string}
*/
type?: "onnx_model_loader";
/**
* Model
* @description The model to load
*/
model: components["schemas"]["OnnxModelField"];
};
/**
* MaskFromAlphaInvocation
* @description Extracts the alpha channel of an image as a mask.
@ -4727,7 +4755,7 @@ export type operations = {
};
requestBody: {
content: {
"application/json": components["schemas"]["LoadImageInvocation"] | components["schemas"]["ShowImageInvocation"] | components["schemas"]["ImageCropInvocation"] | components["schemas"]["ImagePasteInvocation"] | components["schemas"]["MaskFromAlphaInvocation"] | components["schemas"]["ImageMultiplyInvocation"] | components["schemas"]["ImageChannelInvocation"] | components["schemas"]["ImageConvertInvocation"] | components["schemas"]["ImageBlurInvocation"] | components["schemas"]["ImageResizeInvocation"] | components["schemas"]["ImageScaleInvocation"] | components["schemas"]["ImageLerpInvocation"] | components["schemas"]["ImageInverseLerpInvocation"] | components["schemas"]["ControlNetInvocation"] | components["schemas"]["ImageProcessorInvocation"] | components["schemas"]["MainModelLoaderInvocation"] | components["schemas"]["LoraLoaderInvocation"] | components["schemas"]["VaeLoaderInvocation"] | components["schemas"]["MetadataAccumulatorInvocation"] | components["schemas"]["DynamicPromptInvocation"] | components["schemas"]["CompelInvocation"] | components["schemas"]["ClipSkipInvocation"] | components["schemas"]["AddInvocation"] | components["schemas"]["SubtractInvocation"] | components["schemas"]["MultiplyInvocation"] | components["schemas"]["DivideInvocation"] | components["schemas"]["RandomIntInvocation"] | components["schemas"]["ParamIntInvocation"] | components["schemas"]["ParamFloatInvocation"] | components["schemas"]["TextToLatentsInvocation"] | components["schemas"]["LatentsToImageInvocation"] | components["schemas"]["ResizeLatentsInvocation"] | components["schemas"]["ScaleLatentsInvocation"] | components["schemas"]["ImageToLatentsInvocation"] | components["schemas"]["CvInpaintInvocation"] | components["schemas"]["RangeInvocation"] | components["schemas"]["RangeOfSizeInvocation"] | components["schemas"]["RandomRangeInvocation"] | components["schemas"]["ImageCollectionInvocation"] | components["schemas"]["FloatLinearRangeInvocation"] | components["schemas"]["StepParamEasingInvocation"] | components["schemas"]["NoiseInvocation"] | components["schemas"]["UpscaleInvocation"] | components["schemas"]["RestoreFaceInvocation"] | components["schemas"]["InpaintInvocation"] | components["schemas"]["InfillColorInvocation"] | components["schemas"]["InfillTileInvocation"] | components["schemas"]["InfillPatchMatchInvocation"] | components["schemas"]["GraphInvocation"] | components["schemas"]["IterateInvocation"] | components["schemas"]["CollectInvocation"] | components["schemas"]["CannyImageProcessorInvocation"] | components["schemas"]["HedImageProcessorInvocation"] | components["schemas"]["LineartImageProcessorInvocation"] | components["schemas"]["LineartAnimeImageProcessorInvocation"] | components["schemas"]["OpenposeImageProcessorInvocation"] | components["schemas"]["MidasDepthImageProcessorInvocation"] | components["schemas"]["NormalbaeImageProcessorInvocation"] | components["schemas"]["MlsdImageProcessorInvocation"] | components["schemas"]["PidiImageProcessorInvocation"] | components["schemas"]["ContentShuffleImageProcessorInvocation"] | components["schemas"]["ZoeDepthImageProcessorInvocation"] | components["schemas"]["MediapipeFaceProcessorInvocation"] | components["schemas"]["LeresImageProcessorInvocation"] | components["schemas"]["TileResamplerProcessorInvocation"] | components["schemas"]["SegmentAnythingProcessorInvocation"] | components["schemas"]["LatentsToLatentsInvocation"];
"application/json": components["schemas"]["LoadImageInvocation"] | components["schemas"]["ShowImageInvocation"] | components["schemas"]["ImageCropInvocation"] | components["schemas"]["ImagePasteInvocation"] | components["schemas"]["MaskFromAlphaInvocation"] | components["schemas"]["ImageMultiplyInvocation"] | components["schemas"]["ImageChannelInvocation"] | components["schemas"]["ImageConvertInvocation"] | components["schemas"]["ImageBlurInvocation"] | components["schemas"]["ImageResizeInvocation"] | components["schemas"]["ImageScaleInvocation"] | components["schemas"]["ImageLerpInvocation"] | components["schemas"]["ImageInverseLerpInvocation"] | components["schemas"]["ControlNetInvocation"] | components["schemas"]["ImageProcessorInvocation"] | components["schemas"]["MainModelLoaderInvocation"] | components["schemas"]["OnnxModelLoaderInvocation"] | components["schemas"]["LoraLoaderInvocation"] | components["schemas"]["VaeLoaderInvocation"] | components["schemas"]["MetadataAccumulatorInvocation"] | components["schemas"]["DynamicPromptInvocation"] | components["schemas"]["CompelInvocation"] | components["schemas"]["ClipSkipInvocation"] | components["schemas"]["AddInvocation"] | components["schemas"]["SubtractInvocation"] | components["schemas"]["MultiplyInvocation"] | components["schemas"]["DivideInvocation"] | components["schemas"]["RandomIntInvocation"] | components["schemas"]["ParamIntInvocation"] | components["schemas"]["ParamFloatInvocation"] | components["schemas"]["TextToLatentsInvocation"] | components["schemas"]["LatentsToImageInvocation"] | components["schemas"]["ResizeLatentsInvocation"] | components["schemas"]["ScaleLatentsInvocation"] | components["schemas"]["ImageToLatentsInvocation"] | components["schemas"]["CvInpaintInvocation"] | components["schemas"]["RangeInvocation"] | components["schemas"]["RangeOfSizeInvocation"] | components["schemas"]["RandomRangeInvocation"] | components["schemas"]["ImageCollectionInvocation"] | components["schemas"]["FloatLinearRangeInvocation"] | components["schemas"]["StepParamEasingInvocation"] | components["schemas"]["NoiseInvocation"] | components["schemas"]["UpscaleInvocation"] | components["schemas"]["RestoreFaceInvocation"] | components["schemas"]["InpaintInvocation"] | components["schemas"]["InfillColorInvocation"] | components["schemas"]["InfillTileInvocation"] | components["schemas"]["InfillPatchMatchInvocation"] | components["schemas"]["GraphInvocation"] | components["schemas"]["IterateInvocation"] | components["schemas"]["CollectInvocation"] | components["schemas"]["CannyImageProcessorInvocation"] | components["schemas"]["HedImageProcessorInvocation"] | components["schemas"]["LineartImageProcessorInvocation"] | components["schemas"]["LineartAnimeImageProcessorInvocation"] | components["schemas"]["OpenposeImageProcessorInvocation"] | components["schemas"]["MidasDepthImageProcessorInvocation"] | components["schemas"]["NormalbaeImageProcessorInvocation"] | components["schemas"]["MlsdImageProcessorInvocation"] | components["schemas"]["PidiImageProcessorInvocation"] | components["schemas"]["ContentShuffleImageProcessorInvocation"] | components["schemas"]["ZoeDepthImageProcessorInvocation"] | components["schemas"]["MediapipeFaceProcessorInvocation"] | components["schemas"]["LeresImageProcessorInvocation"] | components["schemas"]["TileResamplerProcessorInvocation"] | components["schemas"]["SegmentAnythingProcessorInvocation"] | components["schemas"]["LatentsToLatentsInvocation"];
};
};
responses: {
@ -4764,7 +4792,7 @@ export type operations = {
};
requestBody: {
content: {
"application/json": components["schemas"]["LoadImageInvocation"] | components["schemas"]["ShowImageInvocation"] | components["schemas"]["ImageCropInvocation"] | components["schemas"]["ImagePasteInvocation"] | components["schemas"]["MaskFromAlphaInvocation"] | components["schemas"]["ImageMultiplyInvocation"] | components["schemas"]["ImageChannelInvocation"] | components["schemas"]["ImageConvertInvocation"] | components["schemas"]["ImageBlurInvocation"] | components["schemas"]["ImageResizeInvocation"] | components["schemas"]["ImageScaleInvocation"] | components["schemas"]["ImageLerpInvocation"] | components["schemas"]["ImageInverseLerpInvocation"] | components["schemas"]["ControlNetInvocation"] | components["schemas"]["ImageProcessorInvocation"] | components["schemas"]["MainModelLoaderInvocation"] | components["schemas"]["LoraLoaderInvocation"] | components["schemas"]["VaeLoaderInvocation"] | components["schemas"]["MetadataAccumulatorInvocation"] | components["schemas"]["DynamicPromptInvocation"] | components["schemas"]["CompelInvocation"] | components["schemas"]["ClipSkipInvocation"] | components["schemas"]["AddInvocation"] | components["schemas"]["SubtractInvocation"] | components["schemas"]["MultiplyInvocation"] | components["schemas"]["DivideInvocation"] | components["schemas"]["RandomIntInvocation"] | components["schemas"]["ParamIntInvocation"] | components["schemas"]["ParamFloatInvocation"] | components["schemas"]["TextToLatentsInvocation"] | components["schemas"]["LatentsToImageInvocation"] | components["schemas"]["ResizeLatentsInvocation"] | components["schemas"]["ScaleLatentsInvocation"] | components["schemas"]["ImageToLatentsInvocation"] | components["schemas"]["CvInpaintInvocation"] | components["schemas"]["RangeInvocation"] | components["schemas"]["RangeOfSizeInvocation"] | components["schemas"]["RandomRangeInvocation"] | components["schemas"]["ImageCollectionInvocation"] | components["schemas"]["FloatLinearRangeInvocation"] | components["schemas"]["StepParamEasingInvocation"] | components["schemas"]["NoiseInvocation"] | components["schemas"]["UpscaleInvocation"] | components["schemas"]["RestoreFaceInvocation"] | components["schemas"]["InpaintInvocation"] | components["schemas"]["InfillColorInvocation"] | components["schemas"]["InfillTileInvocation"] | components["schemas"]["InfillPatchMatchInvocation"] | components["schemas"]["GraphInvocation"] | components["schemas"]["IterateInvocation"] | components["schemas"]["CollectInvocation"] | components["schemas"]["CannyImageProcessorInvocation"] | components["schemas"]["HedImageProcessorInvocation"] | components["schemas"]["LineartImageProcessorInvocation"] | components["schemas"]["LineartAnimeImageProcessorInvocation"] | components["schemas"]["OpenposeImageProcessorInvocation"] | components["schemas"]["MidasDepthImageProcessorInvocation"] | components["schemas"]["NormalbaeImageProcessorInvocation"] | components["schemas"]["MlsdImageProcessorInvocation"] | components["schemas"]["PidiImageProcessorInvocation"] | components["schemas"]["ContentShuffleImageProcessorInvocation"] | components["schemas"]["ZoeDepthImageProcessorInvocation"] | components["schemas"]["MediapipeFaceProcessorInvocation"] | components["schemas"]["LeresImageProcessorInvocation"] | components["schemas"]["TileResamplerProcessorInvocation"] | components["schemas"]["SegmentAnythingProcessorInvocation"] | components["schemas"]["LatentsToLatentsInvocation"];
"application/json": components["schemas"]["LoadImageInvocation"] | components["schemas"]["ShowImageInvocation"] | components["schemas"]["ImageCropInvocation"] | components["schemas"]["ImagePasteInvocation"] | components["schemas"]["MaskFromAlphaInvocation"] | components["schemas"]["ImageMultiplyInvocation"] | components["schemas"]["ImageChannelInvocation"] | components["schemas"]["ImageConvertInvocation"] | components["schemas"]["ImageBlurInvocation"] | components["schemas"]["ImageResizeInvocation"] | components["schemas"]["ImageScaleInvocation"] | components["schemas"]["ImageLerpInvocation"] | components["schemas"]["ImageInverseLerpInvocation"] | components["schemas"]["ControlNetInvocation"] | components["schemas"]["ImageProcessorInvocation"] | components["schemas"]["MainModelLoaderInvocation"] | components["schemas"]["OnnxModelLoaderInvocation"] | components["schemas"]["LoraLoaderInvocation"] | components["schemas"]["VaeLoaderInvocation"] | components["schemas"]["MetadataAccumulatorInvocation"] | components["schemas"]["DynamicPromptInvocation"] | components["schemas"]["CompelInvocation"] | components["schemas"]["ClipSkipInvocation"] | components["schemas"]["AddInvocation"] | components["schemas"]["SubtractInvocation"] | components["schemas"]["MultiplyInvocation"] | components["schemas"]["DivideInvocation"] | components["schemas"]["RandomIntInvocation"] | components["schemas"]["ParamIntInvocation"] | components["schemas"]["ParamFloatInvocation"] | components["schemas"]["TextToLatentsInvocation"] | components["schemas"]["LatentsToImageInvocation"] | components["schemas"]["ResizeLatentsInvocation"] | components["schemas"]["ScaleLatentsInvocation"] | components["schemas"]["ImageToLatentsInvocation"] | components["schemas"]["CvInpaintInvocation"] | components["schemas"]["RangeInvocation"] | components["schemas"]["RangeOfSizeInvocation"] | components["schemas"]["RandomRangeInvocation"] | components["schemas"]["ImageCollectionInvocation"] | components["schemas"]["FloatLinearRangeInvocation"] | components["schemas"]["StepParamEasingInvocation"] | components["schemas"]["NoiseInvocation"] | components["schemas"]["UpscaleInvocation"] | components["schemas"]["RestoreFaceInvocation"] | components["schemas"]["InpaintInvocation"] | components["schemas"]["InfillColorInvocation"] | components["schemas"]["InfillTileInvocation"] | components["schemas"]["InfillPatchMatchInvocation"] | components["schemas"]["GraphInvocation"] | components["schemas"]["IterateInvocation"] | components["schemas"]["CollectInvocation"] | components["schemas"]["CannyImageProcessorInvocation"] | components["schemas"]["HedImageProcessorInvocation"] | components["schemas"]["LineartImageProcessorInvocation"] | components["schemas"]["LineartAnimeImageProcessorInvocation"] | components["schemas"]["OpenposeImageProcessorInvocation"] | components["schemas"]["MidasDepthImageProcessorInvocation"] | components["schemas"]["NormalbaeImageProcessorInvocation"] | components["schemas"]["MlsdImageProcessorInvocation"] | components["schemas"]["PidiImageProcessorInvocation"] | components["schemas"]["ContentShuffleImageProcessorInvocation"] | components["schemas"]["ZoeDepthImageProcessorInvocation"] | components["schemas"]["MediapipeFaceProcessorInvocation"] | components["schemas"]["LeresImageProcessorInvocation"] | components["schemas"]["TileResamplerProcessorInvocation"] | components["schemas"]["SegmentAnythingProcessorInvocation"] | components["schemas"]["LatentsToLatentsInvocation"];
};
};
responses: {

5
invokeai/frontend/web/src/services/api/types.d.ts vendored
View File

@ -30,6 +30,7 @@ export type OffsetPaginatedResults_ImageDTO_ =
export type ModelType = components['schemas']['ModelType'];
export type BaseModelType = components['schemas']['BaseModelType'];
export type MainModelField = components['schemas']['MainModelField'];
export type OnnxModelField = components['schemas']['OnnxModelField'];
export type VAEModelField = components['schemas']['VAEModelField'];
export type LoRAModelField = components['schemas']['LoRAModelField'];
export type ModelsList = components['schemas']['ModelsList'];
@ -47,6 +48,7 @@ export type MainModelConfig =
| components['schemas']['StableDiffusion1ModelDiffusersConfig']
| components['schemas']['StableDiffusion2ModelCheckpointConfig']
| components['schemas']['StableDiffusion2ModelDiffusersConfig'];
export type OnnxModelConfig = components['schemas']['ONNXStableDiffusion1ModelConfig']
export type AnyModelConfig =
| LoRAModelConfig
| VaeModelConfig
@ -107,6 +109,9 @@ export type ImageCollectionInvocation = TypeReq<
export type MainModelLoaderInvocation = TypeReq<
components['schemas']['MainModelLoaderInvocation']
>;
export type OnnxModelLoaderInvocation = TypeReq<
components['schemas']['OnnxModelLoaderInvocation']
>;
export type LoraLoaderInvocation = TypeReq<
components['schemas']['LoraLoaderInvocation']
>;