Mirrored_Repos/InvokeAI
1
0
Fork 0
mirror of https://github.com/invoke-ai/InvokeAI synced 2024-08-30 20:32:17 +00:00
Code Issues Packages Projects Releases Wiki Activity

Merge branch 'main' into maryhipp/preselected-image

Browse Source
This commit is contained in:
blessedcoolant
2023-08-29 01:12:09 +12:00
parent e60af40c8d 502570e083
commit 3c37245804
54 changed files with 1395 additions and 705 deletions
Download Patch File Download Diff File Expand all files Collapse all files

20
invokeai/frontend/install/widgets.py
View File

@ -177,6 +177,8 @@ class FloatTitleSlider(npyscreen.TitleText):
class SelectColumnBase:
"""Base class for selection widget arranged in columns."""
def make_contained_widgets(self):
self._my_widgets = []
column_width = self.width // self.columns
@ -253,6 +255,7 @@ class MultiSelectColumns(SelectColumnBase, npyscreen.MultiSelect):
class SingleSelectWithChanged(npyscreen.SelectOne):
def __init__(self, *args, **kwargs):
super().__init__(*args, **kwargs)
self.on_changed = None
def h_select(self, ch):
super().h_select(ch)
@ -260,7 +263,9 @@ class SingleSelectWithChanged(npyscreen.SelectOne):
self.on_changed(self.value)
class SingleSelectColumns(SelectColumnBase, SingleSelectWithChanged):
class SingleSelectColumnsSimple(SelectColumnBase, SingleSelectWithChanged):
"""Row of radio buttons. Spacebar to select."""
def __init__(self, screen, columns: int = 1, values: list = [], **keywords):
self.columns = columns
self.value_cnt = len(values)
@ -268,12 +273,6 @@ class SingleSelectColumns(SelectColumnBase, SingleSelectWithChanged):
self.on_changed = None
super().__init__(screen, values=values, **keywords)
def when_value_edited(self):
self.h_select(self.cursor_line)
def when_cursor_moved(self):
self.h_select(self.cursor_line)
def h_cursor_line_right(self, ch):
self.h_exit_down("bye bye")
@ -281,6 +280,13 @@ class SingleSelectColumns(SelectColumnBase, SingleSelectWithChanged):
self.h_exit_up("bye bye")
class SingleSelectColumns(SingleSelectColumnsSimple):
"""Row of radio buttons. When tabbing over a selection, it is auto selected."""
def when_cursor_moved(self):
self.h_select(self.cursor_line)
class TextBoxInner(npyscreen.MultiLineEdit):
def __init__(self, *args, **kwargs):
super().__init__(*args, **kwargs)

14
invokeai/frontend/web/src/features/nodes/components/flow/nodes/Invocation/fields/InputFieldRenderer.tsx
View File

@ -10,6 +10,7 @@ import ColorInputField from './inputs/ColorInputField';
import ConditioningInputField from './inputs/ConditioningInputField';
import ControlInputField from './inputs/ControlInputField';
import ControlNetModelInputField from './inputs/ControlNetModelInputField';
import DenoiseMaskInputField from './inputs/DenoiseMaskInputField';
import EnumInputField from './inputs/EnumInputField';
import ImageCollectionInputField from './inputs/ImageCollectionInputField';
import ImageInputField from './inputs/ImageInputField';
@ -105,6 +106,19 @@ const InputFieldRenderer = ({ nodeId, fieldName }: InputFieldProps) => {
);
}
if (
field?.type === 'DenoiseMaskField' &&
fieldTemplate?.type === 'DenoiseMaskField'
) {
return (
<DenoiseMaskInputField
nodeId={nodeId}
field={field}
fieldTemplate={fieldTemplate}
/>
);
}
if (
field?.type === 'ConditioningField' &&
fieldTemplate?.type === 'ConditioningField'

17
invokeai/frontend/web/src/features/nodes/components/flow/nodes/Invocation/fields/inputs/DenoiseMaskInputField.tsx Normal file
View File

@ -0,0 +1,17 @@
import {
DenoiseMaskInputFieldTemplate,
DenoiseMaskInputFieldValue,
FieldComponentProps,
} from 'features/nodes/types/types';
import { memo } from 'react';
const DenoiseMaskInputFieldComponent = (
_props: FieldComponentProps<
DenoiseMaskInputFieldValue,
DenoiseMaskInputFieldTemplate
>
) => {
return null;
};
export default memo(DenoiseMaskInputFieldComponent);

5
invokeai/frontend/web/src/features/nodes/types/constants.ts
View File

@ -59,6 +59,11 @@ export const FIELDS: Record<FieldType, FieldUIConfig> = {
description: 'Images may be passed between nodes.',
color: 'purple.500',
},
DenoiseMaskField: {
title: 'Denoise Mask',
description: 'Denoise Mask may be passed between nodes',
color: 'red.700',
},
LatentsField: {
title: 'Latents',
description: 'Latents may be passed between nodes.',

22
invokeai/frontend/web/src/features/nodes/types/types.ts
View File

@ -64,6 +64,7 @@ export const zFieldType = z.enum([
'string',
'array',
'ImageField',
'DenoiseMaskField',
'LatentsField',
'ConditioningField',
'ControlField',
@ -120,6 +121,7 @@ export type InputFieldTemplate =
| StringInputFieldTemplate
| BooleanInputFieldTemplate
| ImageInputFieldTemplate
| DenoiseMaskInputFieldTemplate
| LatentsInputFieldTemplate
| ConditioningInputFieldTemplate
| UNetInputFieldTemplate
@ -205,6 +207,12 @@ export const zConditioningField = z.object({
});
export type ConditioningField = z.infer<typeof zConditioningField>;
export const zDenoiseMaskField = z.object({
mask_name: z.string().trim().min(1),
masked_latents_name: z.string().trim().min(1).optional(),
});
export type DenoiseMaskFieldValue = z.infer<typeof zDenoiseMaskField>;
export const zIntegerInputFieldValue = zInputFieldValueBase.extend({
type: z.literal('integer'),
value: z.number().optional(),
@ -241,6 +249,14 @@ export const zLatentsInputFieldValue = zInputFieldValueBase.extend({
});
export type LatentsInputFieldValue = z.infer<typeof zLatentsInputFieldValue>;
export const zDenoiseMaskInputFieldValue = zInputFieldValueBase.extend({
type: z.literal('DenoiseMaskField'),
value: zDenoiseMaskField.optional(),
});
export type DenoiseMaskInputFieldValue = z.infer<
typeof zDenoiseMaskInputFieldValue
>;
export const zConditioningInputFieldValue = zInputFieldValueBase.extend({
type: z.literal('ConditioningField'),
value: zConditioningField.optional(),
@ -459,6 +475,7 @@ export const zInputFieldValue = z.discriminatedUnion('type', [
zBooleanInputFieldValue,
zImageInputFieldValue,
zLatentsInputFieldValue,
zDenoiseMaskInputFieldValue,
zConditioningInputFieldValue,
zUNetInputFieldValue,
zClipInputFieldValue,
@ -532,6 +549,11 @@ export type ImageCollectionInputFieldTemplate = InputFieldTemplateBase & {
type: 'ImageCollection';
};
export type DenoiseMaskInputFieldTemplate = InputFieldTemplateBase & {
default: undefined;
type: 'DenoiseMaskField';
};
export type LatentsInputFieldTemplate = InputFieldTemplateBase & {
default: string;
type: 'LatentsField';

20
invokeai/frontend/web/src/features/nodes/util/fieldTemplateBuilders.ts
View File

@ -8,6 +8,7 @@ import {
ConditioningInputFieldTemplate,
ControlInputFieldTemplate,
ControlNetModelInputFieldTemplate,
DenoiseMaskInputFieldTemplate,
EnumInputFieldTemplate,
FieldType,
FloatInputFieldTemplate,
@ -263,6 +264,19 @@ const buildImageCollectionInputFieldTemplate = ({
return template;
};
const buildDenoiseMaskInputFieldTemplate = ({
schemaObject,
baseField,
}: BuildInputFieldArg): DenoiseMaskInputFieldTemplate => {
const template: DenoiseMaskInputFieldTemplate = {
...baseField,
type: 'DenoiseMaskField',
default: schemaObject.default ?? undefined,
};
return template;
};
const buildLatentsInputFieldTemplate = ({
schemaObject,
baseField,
@ -498,6 +512,12 @@ export const buildInputFieldTemplate = (
baseField,
});
}
if (fieldType === 'DenoiseMaskField') {
return buildDenoiseMaskInputFieldTemplate({
schemaObject: fieldSchema,
baseField,
});
}
if (fieldType === 'LatentsField') {
return buildLatentsInputFieldTemplate({
schemaObject: fieldSchema,

4
invokeai/frontend/web/src/features/nodes/util/fieldValueBuilders.ts
View File

@ -49,6 +49,10 @@ export const buildInputFieldValue = (
fieldValue.value = [];
}
if (template.type === 'DenoiseMaskField') {
fieldValue.value = undefined;
}
if (template.type === 'LatentsField') {
fieldValue.value = undefined;
}

18
invokeai/frontend/web/src/features/nodes/util/graphBuilders/addVAEToGraph.ts
View File

@ -9,6 +9,7 @@ import {
CANVAS_TEXT_TO_IMAGE_GRAPH,
IMAGE_TO_IMAGE_GRAPH,
IMAGE_TO_LATENTS,
INPAINT_CREATE_MASK,
INPAINT_IMAGE,
LATENTS_TO_IMAGE,
MAIN_MODEL_LOADER,
@ -30,6 +31,11 @@ export const addVAEToGraph = (
modelLoaderNodeId: string = MAIN_MODEL_LOADER
): void => {
const { vae } = state.generation;
const { boundingBoxScaleMethod } = state.canvas;
const isUsingScaledDimensions = ['auto', 'manual'].includes(
boundingBoxScaleMethod
);
const isAutoVae = !vae;
const metadataAccumulator = graph.nodes[METADATA_ACCUMULATOR] as
@ -76,7 +82,7 @@ export const addVAEToGraph = (
field: isAutoVae && isOnnxModel ? 'vae_decoder' : 'vae',
},
destination: {
node_id: CANVAS_OUTPUT,
node_id: isUsingScaledDimensions ? LATENTS_TO_IMAGE : CANVAS_OUTPUT,
field: 'vae',
},
});
@ -117,6 +123,16 @@ export const addVAEToGraph = (
field: 'vae',
},
},
{
source: {
node_id: isAutoVae ? modelLoaderNodeId : VAE_LOADER,
field: isAutoVae && isOnnxModel ? 'vae_decoder' : 'vae',
},
destination: {
node_id: INPAINT_CREATE_MASK,
field: 'vae',
},
},
{
source: {
node_id: isAutoVae ? modelLoaderNodeId : VAE_LOADER,

160
invokeai/frontend/web/src/features/nodes/util/graphBuilders/buildCanvasImageToImageGraph.ts
View File

@ -2,11 +2,7 @@ import { logger } from 'app/logging/logger';
import { RootState } from 'app/store/store';
import { NonNullableGraph } from 'features/nodes/types/types';
import { initialGenerationState } from 'features/parameters/store/generationSlice';
import {
ImageDTO,
ImageResizeInvocation,
ImageToLatentsInvocation,
} from 'services/api/types';
import { ImageDTO, ImageToLatentsInvocation } from 'services/api/types';
import { addControlNetToLinearGraph } from './addControlNetToLinearGraph';
import { addDynamicPromptsToGraph } from './addDynamicPromptsToGraph';
import { addLoRAsToGraph } from './addLoRAsToGraph';
@ -19,12 +15,13 @@ import {
CLIP_SKIP,
DENOISE_LATENTS,
IMAGE_TO_LATENTS,
IMG2IMG_RESIZE,
LATENTS_TO_IMAGE,
MAIN_MODEL_LOADER,
METADATA_ACCUMULATOR,
NEGATIVE_CONDITIONING,
NOISE,
POSITIVE_CONDITIONING,
RESIZE,
} from './constants';
/**
@ -43,6 +40,7 @@ export const buildCanvasImageToImageGraph = (
scheduler,
steps,
img2imgStrength: strength,
vaePrecision,
clipSkip,
shouldUseCpuNoise,
shouldUseNoiseSettings,
@ -51,7 +49,15 @@ export const buildCanvasImageToImageGraph = (
// The bounding box determines width and height, not the width and height params
const { width, height } = state.canvas.boundingBoxDimensions;
const { shouldAutoSave } = state.canvas;
const {
scaledBoundingBoxDimensions,
boundingBoxScaleMethod,
shouldAutoSave,
} = state.canvas;
const isUsingScaledDimensions = ['auto', 'manual'].includes(
boundingBoxScaleMethod
);
if (!model) {
log.error('No model found in state');
@ -104,15 +110,17 @@ export const buildCanvasImageToImageGraph = (
id: NOISE,
is_intermediate: true,
use_cpu,
width: !isUsingScaledDimensions
? width
: scaledBoundingBoxDimensions.width,
height: !isUsingScaledDimensions
? height
: scaledBoundingBoxDimensions.height,
},
[IMAGE_TO_LATENTS]: {
type: 'i2l',
id: IMAGE_TO_LATENTS,
is_intermediate: true,
// must be set manually later, bc `fit` parameter may require a resize node inserted
// image: {
// image_name: initialImage.image_name,
// },
},
[DENOISE_LATENTS]: {
type: 'denoise_latents',
@ -214,82 +222,84 @@ export const buildCanvasImageToImageGraph = (
field: 'latents',
},
},
// Decode the denoised latents to an image
],
};
// Decode Latents To Image & Handle Scaled Before Processing
if (isUsingScaledDimensions) {
graph.nodes[IMG2IMG_RESIZE] = {
id: IMG2IMG_RESIZE,
type: 'img_resize',
is_intermediate: true,
image: initialImage,
width: scaledBoundingBoxDimensions.width,
height: scaledBoundingBoxDimensions.height,
};
graph.nodes[LATENTS_TO_IMAGE] = {
id: LATENTS_TO_IMAGE,
type: 'l2i',
is_intermediate: true,
fp32: vaePrecision === 'fp32' ? true : false,
};
graph.nodes[CANVAS_OUTPUT] = {
id: CANVAS_OUTPUT,
type: 'img_resize',
is_intermediate: !shouldAutoSave,
width: width,
height: height,
};
graph.edges.push(
{
source: {
node_id: IMG2IMG_RESIZE,
field: 'image',
},
destination: {
node_id: IMAGE_TO_LATENTS,
field: 'image',
},
},
{
source: {
node_id: DENOISE_LATENTS,
field: 'latents',
},
destination: {
node_id: CANVAS_OUTPUT,
node_id: LATENTS_TO_IMAGE,
field: 'latents',
},
},
],
};
// handle `fit`
if (initialImage.width !== width || initialImage.height !== height) {
// The init image needs to be resized to the specified width and height before being passed to `IMAGE_TO_LATENTS`
// Create a resize node, explicitly setting its image
const resizeNode: ImageResizeInvocation = {
id: RESIZE,
type: 'img_resize',
image: {
image_name: initialImage.image_name,
},
is_intermediate: true,
width,
height,
};
graph.nodes[RESIZE] = resizeNode;
// The `RESIZE` node then passes its image to `IMAGE_TO_LATENTS`
graph.edges.push({
source: { node_id: RESIZE, field: 'image' },
destination: {
node_id: IMAGE_TO_LATENTS,
field: 'image',
},
});
// The `RESIZE` node also passes its width and height to `NOISE`
graph.edges.push({
source: { node_id: RESIZE, field: 'width' },
destination: {
node_id: NOISE,
field: 'width',
},
});
graph.edges.push({
source: { node_id: RESIZE, field: 'height' },
destination: {
node_id: NOISE,
field: 'height',
},
});
{
source: {
node_id: LATENTS_TO_IMAGE,
field: 'image',
},
destination: {
node_id: CANVAS_OUTPUT,
field: 'image',
},
}
);
} else {
// We are not resizing, so we need to set the image on the `IMAGE_TO_LATENTS` node explicitly
(graph.nodes[IMAGE_TO_LATENTS] as ImageToLatentsInvocation).image = {
image_name: initialImage.image_name,
graph.nodes[CANVAS_OUTPUT] = {
type: 'l2i',
id: CANVAS_OUTPUT,
is_intermediate: !shouldAutoSave,
fp32: vaePrecision === 'fp32' ? true : false,
};
// Pass the image's dimensions to the `NOISE` node
(graph.nodes[IMAGE_TO_LATENTS] as ImageToLatentsInvocation).image =
initialImage;
graph.edges.push({
source: { node_id: IMAGE_TO_LATENTS, field: 'width' },
destination: {
node_id: NOISE,
field: 'width',
source: {
node_id: DENOISE_LATENTS,
field: 'latents',
},
});
graph.edges.push({
source: { node_id: IMAGE_TO_LATENTS, field: 'height' },
destination: {
node_id: NOISE,
field: 'height',
node_id: CANVAS_OUTPUT,
field: 'latents',
},
});
}
@ -300,8 +310,10 @@ export const buildCanvasImageToImageGraph = (
type: 'metadata_accumulator',
generation_mode: 'img2img',
cfg_scale,
height,
width,
width: !isUsingScaledDimensions ? width : scaledBoundingBoxDimensions.width,
height: !isUsingScaledDimensions
? height
: scaledBoundingBoxDimensions.height,
positive_prompt: '', // set in addDynamicPromptsToGraph
negative_prompt: negativePrompt,
model,

39
invokeai/frontend/web/src/features/nodes/util/graphBuilders/buildCanvasInpaintGraph.ts
View File

@ -2,6 +2,7 @@ import { logger } from 'app/logging/logger';
import { RootState } from 'app/store/store';
import { NonNullableGraph } from 'features/nodes/types/types';
import {
CreateDenoiseMaskInvocation,
ImageBlurInvocation,
ImageDTO,
ImageToLatentsInvocation,
@ -15,13 +16,14 @@ import { addNSFWCheckerToGraph } from './addNSFWCheckerToGraph';
import { addVAEToGraph } from './addVAEToGraph';
import { addWatermarkerToGraph } from './addWatermarkerToGraph';
import {
CANVAS_INPAINT_GRAPH,
CANVAS_OUTPUT,
CANVAS_COHERENCE_DENOISE_LATENTS,
CANVAS_COHERENCE_NOISE,
CANVAS_COHERENCE_NOISE_INCREMENT,
CANVAS_INPAINT_GRAPH,
CANVAS_OUTPUT,
CLIP_SKIP,
DENOISE_LATENTS,
INPAINT_CREATE_MASK,
INPAINT_IMAGE,
INPAINT_IMAGE_RESIZE_DOWN,
INPAINT_IMAGE_RESIZE_UP,
@ -127,6 +129,12 @@ export const buildCanvasInpaintGraph = (
is_intermediate: true,
fp32: vaePrecision === 'fp32' ? true : false,
},
[INPAINT_CREATE_MASK]: {
type: 'create_denoise_mask',
id: INPAINT_CREATE_MASK,
is_intermediate: true,
fp32: vaePrecision === 'fp32' ? true : false,
},
[NOISE]: {
type: 'noise',
id: NOISE,
@ -276,16 +284,27 @@ export const buildCanvasInpaintGraph = (
field: 'latents',
},
},
// Create Inpaint Mask
{
source: {
node_id: MASK_BLUR,
field: 'image',
},
destination: {
node_id: DENOISE_LATENTS,
node_id: INPAINT_CREATE_MASK,
field: 'mask',
},
},
{
source: {
node_id: INPAINT_CREATE_MASK,
field: 'denoise_mask',
},
destination: {
node_id: DENOISE_LATENTS,
field: 'denoise_mask',
},
},
// Iterate
{
source: {
@ -459,6 +478,16 @@ export const buildCanvasInpaintGraph = (
field: 'image',
},
},
{
source: {
node_id: INPAINT_IMAGE_RESIZE_UP,
field: 'image',
},
destination: {
node_id: INPAINT_CREATE_MASK,
field: 'image',
},
},
// Color Correct The Inpainted Result
{
source: {
@ -516,6 +545,10 @@ export const buildCanvasInpaintGraph = (
...(graph.nodes[MASK_BLUR] as ImageBlurInvocation),
image: canvasMaskImage,
};
graph.nodes[INPAINT_CREATE_MASK] = {
...(graph.nodes[INPAINT_CREATE_MASK] as CreateDenoiseMaskInvocation),
image: canvasInitImage,
};
graph.edges.push(
// Color Correct The Inpainted Result

44
invokeai/frontend/web/src/features/nodes/util/graphBuilders/buildCanvasOutpaintGraph.ts
View File

@ -17,13 +17,14 @@ import { addNSFWCheckerToGraph } from './addNSFWCheckerToGraph';
import { addVAEToGraph } from './addVAEToGraph';
import { addWatermarkerToGraph } from './addWatermarkerToGraph';
import {
CANVAS_OUTPAINT_GRAPH,
CANVAS_OUTPUT,
CANVAS_COHERENCE_DENOISE_LATENTS,
CANVAS_COHERENCE_NOISE,
CANVAS_COHERENCE_NOISE_INCREMENT,
CANVAS_OUTPAINT_GRAPH,
CANVAS_OUTPUT,
CLIP_SKIP,
DENOISE_LATENTS,
INPAINT_CREATE_MASK,
INPAINT_IMAGE,
INPAINT_IMAGE_RESIZE_DOWN,
INPAINT_IMAGE_RESIZE_UP,
@ -153,6 +154,12 @@ export const buildCanvasOutpaintGraph = (
use_cpu,
is_intermediate: true,
},
[INPAINT_CREATE_MASK]: {
type: 'create_denoise_mask',
id: INPAINT_CREATE_MASK,
is_intermediate: true,
fp32: vaePrecision === 'fp32' ? true : false,
},
[DENOISE_LATENTS]: {
type: 'denoise_latents',
id: DENOISE_LATENTS,
@ -317,16 +324,27 @@ export const buildCanvasOutpaintGraph = (
field: 'latents',
},
},
// Create Inpaint Mask
{
source: {
node_id: MASK_BLUR,
field: 'image',
},
destination: {
node_id: DENOISE_LATENTS,
node_id: INPAINT_CREATE_MASK,
field: 'mask',
},
},
{
source: {
node_id: INPAINT_CREATE_MASK,
field: 'denoise_mask',
},
destination: {
node_id: DENOISE_LATENTS,
field: 'denoise_mask',
},
},
// Iterate
{
source: {
@ -522,6 +540,16 @@ export const buildCanvasOutpaintGraph = (
field: 'image',
},
},
{
source: {
node_id: INPAINT_INFILL,
field: 'image',
},
destination: {
node_id: INPAINT_CREATE_MASK,
field: 'image',
},
},
// Take combined mask and resize and then blur
{
source: {
@ -640,6 +668,16 @@ export const buildCanvasOutpaintGraph = (
field: 'image',
},
},
{
source: {
node_id: INPAINT_INFILL,
field: 'image',
},
destination: {
node_id: INPAINT_CREATE_MASK,
field: 'image',
},
},
// Color Correct The Inpainted Result
{
source: {

165
invokeai/frontend/web/src/features/nodes/util/graphBuilders/buildCanvasSDXLImageToImageGraph.ts
View File

@ -2,11 +2,7 @@ import { logger } from 'app/logging/logger';
import { RootState } from 'app/store/store';
import { NonNullableGraph } from 'features/nodes/types/types';
import { initialGenerationState } from 'features/parameters/store/generationSlice';
import {
ImageDTO,
ImageResizeInvocation,
ImageToLatentsInvocation,
} from 'services/api/types';
import { ImageDTO, ImageToLatentsInvocation } from 'services/api/types';
import { addControlNetToLinearGraph } from './addControlNetToLinearGraph';
import { addDynamicPromptsToGraph } from './addDynamicPromptsToGraph';
import { addNSFWCheckerToGraph } from './addNSFWCheckerToGraph';
@ -17,11 +13,12 @@ import { addWatermarkerToGraph } from './addWatermarkerToGraph';
import {
CANVAS_OUTPUT,
IMAGE_TO_LATENTS,
IMG2IMG_RESIZE,
LATENTS_TO_IMAGE,
METADATA_ACCUMULATOR,
NEGATIVE_CONDITIONING,
NOISE,
POSITIVE_CONDITIONING,
RESIZE,
SDXL_CANVAS_IMAGE_TO_IMAGE_GRAPH,
SDXL_DENOISE_LATENTS,
SDXL_MODEL_LOADER,
@ -59,7 +56,15 @@ export const buildCanvasSDXLImageToImageGraph = (
// The bounding box determines width and height, not the width and height params
const { width, height } = state.canvas.boundingBoxDimensions;
const { shouldAutoSave } = state.canvas;
const {
scaledBoundingBoxDimensions,
boundingBoxScaleMethod,
shouldAutoSave,
} = state.canvas;
const isUsingScaledDimensions = ['auto', 'manual'].includes(
boundingBoxScaleMethod
);
if (!model) {
log.error('No model found in state');
@ -109,16 +114,18 @@ export const buildCanvasSDXLImageToImageGraph = (
id: NOISE,
is_intermediate: true,
use_cpu,
width: !isUsingScaledDimensions
? width
: scaledBoundingBoxDimensions.width,
height: !isUsingScaledDimensions
? height
: scaledBoundingBoxDimensions.height,
},
[IMAGE_TO_LATENTS]: {
type: 'i2l',
id: IMAGE_TO_LATENTS,
is_intermediate: true,
fp32: vaePrecision === 'fp32' ? true : false,
// must be set manually later, bc `fit` parameter may require a resize node inserted
// image: {
// image_name: initialImage.image_name,
// },
},
[SDXL_DENOISE_LATENTS]: {
type: 'denoise_latents',
@ -132,12 +139,6 @@ export const buildCanvasSDXLImageToImageGraph = (
: 1 - strength,
denoising_end: shouldUseSDXLRefiner ? refinerStart : 1,
},
[CANVAS_OUTPUT]: {
type: 'l2i',
id: CANVAS_OUTPUT,
is_intermediate: !shouldAutoSave,
fp32: vaePrecision === 'fp32' ? true : false,
},
},
edges: [
// Connect Model Loader To UNet & CLIP
@ -232,82 +233,84 @@ export const buildCanvasSDXLImageToImageGraph = (
field: 'latents',
},
},
// Decode denoised latents to an image
],
};
// Decode Latents To Image & Handle Scaled Before Processing
if (isUsingScaledDimensions) {
graph.nodes[IMG2IMG_RESIZE] = {
id: IMG2IMG_RESIZE,
type: 'img_resize',
is_intermediate: true,
image: initialImage,
width: scaledBoundingBoxDimensions.width,
height: scaledBoundingBoxDimensions.height,
};
graph.nodes[LATENTS_TO_IMAGE] = {
id: LATENTS_TO_IMAGE,
type: 'l2i',
is_intermediate: true,
fp32: vaePrecision === 'fp32' ? true : false,
};
graph.nodes[CANVAS_OUTPUT] = {
id: CANVAS_OUTPUT,
type: 'img_resize',
is_intermediate: !shouldAutoSave,
width: width,
height: height,
};
graph.edges.push(
{
source: {
node_id: IMG2IMG_RESIZE,
field: 'image',
},
destination: {
node_id: IMAGE_TO_LATENTS,
field: 'image',
},
},
{
source: {
node_id: SDXL_DENOISE_LATENTS,
field: 'latents',
},
destination: {
node_id: CANVAS_OUTPUT,
node_id: LATENTS_TO_IMAGE,
field: 'latents',
},
},
],
};
// handle `fit`
if (initialImage.width !== width || initialImage.height !== height) {
// The init image needs to be resized to the specified width and height before being passed to `IMAGE_TO_LATENTS`
// Create a resize node, explicitly setting its image
const resizeNode: ImageResizeInvocation = {
id: RESIZE,
type: 'img_resize',
image: {
image_name: initialImage.image_name,
},
is_intermediate: true,
width,
height,
};
graph.nodes[RESIZE] = resizeNode;
// The `RESIZE` node then passes its image to `IMAGE_TO_LATENTS`
graph.edges.push({
source: { node_id: RESIZE, field: 'image' },
destination: {
node_id: IMAGE_TO_LATENTS,
field: 'image',
},
});
// The `RESIZE` node also passes its width and height to `NOISE`
graph.edges.push({
source: { node_id: RESIZE, field: 'width' },
destination: {
node_id: NOISE,
field: 'width',
},
});
graph.edges.push({
source: { node_id: RESIZE, field: 'height' },
destination: {
node_id: NOISE,
field: 'height',
},
});
{
source: {
node_id: LATENTS_TO_IMAGE,
field: 'image',
},
destination: {
node_id: CANVAS_OUTPUT,
field: 'image',
},
}
);
} else {
// We are not resizing, so we need to set the image on the `IMAGE_TO_LATENTS` node explicitly
(graph.nodes[IMAGE_TO_LATENTS] as ImageToLatentsInvocation).image = {
image_name: initialImage.image_name,
graph.nodes[CANVAS_OUTPUT] = {
type: 'l2i',
id: CANVAS_OUTPUT,
is_intermediate: !shouldAutoSave,
fp32: vaePrecision === 'fp32' ? true : false,
};
// Pass the image's dimensions to the `NOISE` node
(graph.nodes[IMAGE_TO_LATENTS] as ImageToLatentsInvocation).image =
initialImage;
graph.edges.push({
source: { node_id: IMAGE_TO_LATENTS, field: 'width' },
destination: {
node_id: NOISE,
field: 'width',
source: {
node_id: SDXL_DENOISE_LATENTS,
field: 'latents',
},
});
graph.edges.push({
source: { node_id: IMAGE_TO_LATENTS, field: 'height' },
destination: {
node_id: NOISE,
field: 'height',
node_id: CANVAS_OUTPUT,
field: 'latents',
},
});
}
@ -318,8 +321,10 @@ export const buildCanvasSDXLImageToImageGraph = (
type: 'metadata_accumulator',
generation_mode: 'img2img',
cfg_scale,
height,
width,
width: !isUsingScaledDimensions ? width : scaledBoundingBoxDimensions.width,
height: !isUsingScaledDimensions
? height
: scaledBoundingBoxDimensions.height,
positive_prompt: '', // set in addDynamicPromptsToGraph
negative_prompt: negativePrompt,
model,

37
invokeai/frontend/web/src/features/nodes/util/graphBuilders/buildCanvasSDXLInpaintGraph.ts
View File

@ -2,6 +2,7 @@ import { logger } from 'app/logging/logger';
import { RootState } from 'app/store/store';
import { NonNullableGraph } from 'features/nodes/types/types';
import {
CreateDenoiseMaskInvocation,
ImageBlurInvocation,
ImageDTO,
ImageToLatentsInvocation,
@ -16,10 +17,11 @@ import { addSDXLRefinerToGraph } from './addSDXLRefinerToGraph';
import { addVAEToGraph } from './addVAEToGraph';
import { addWatermarkerToGraph } from './addWatermarkerToGraph';
import {
CANVAS_OUTPUT,
CANVAS_COHERENCE_DENOISE_LATENTS,
CANVAS_COHERENCE_NOISE,
CANVAS_COHERENCE_NOISE_INCREMENT,
CANVAS_OUTPUT,
INPAINT_CREATE_MASK,
INPAINT_IMAGE,
INPAINT_IMAGE_RESIZE_DOWN,
INPAINT_IMAGE_RESIZE_UP,
@ -136,6 +138,12 @@ export const buildCanvasSDXLInpaintGraph = (
use_cpu,
is_intermediate: true,
},
[INPAINT_CREATE_MASK]: {
type: 'create_denoise_mask',
id: INPAINT_CREATE_MASK,
is_intermediate: true,
fp32: vaePrecision === 'fp32' ? true : false,
},
[SDXL_DENOISE_LATENTS]: {
type: 'denoise_latents',
id: SDXL_DENOISE_LATENTS,
@ -290,16 +298,27 @@ export const buildCanvasSDXLInpaintGraph = (
field: 'latents',
},
},
// Create Inpaint Mask
{
source: {
node_id: MASK_BLUR,
field: 'image',
},
destination: {
node_id: SDXL_DENOISE_LATENTS,
node_id: INPAINT_CREATE_MASK,
field: 'mask',
},
},
{
source: {
node_id: INPAINT_CREATE_MASK,
field: 'denoise_mask',
},
destination: {
node_id: SDXL_DENOISE_LATENTS,
field: 'denoise_mask',
},
},
// Iterate
{
source: {
@ -473,6 +492,16 @@ export const buildCanvasSDXLInpaintGraph = (
field: 'image',
},
},
{
source: {
node_id: INPAINT_IMAGE_RESIZE_UP,
field: 'image',
},
destination: {
node_id: INPAINT_CREATE_MASK,
field: 'image',
},
},
// Color Correct The Inpainted Result
{
source: {
@ -530,6 +559,10 @@ export const buildCanvasSDXLInpaintGraph = (
...(graph.nodes[MASK_BLUR] as ImageBlurInvocation),
image: canvasMaskImage,
};
graph.nodes[INPAINT_CREATE_MASK] = {
...(graph.nodes[INPAINT_CREATE_MASK] as CreateDenoiseMaskInvocation),
image: canvasInitImage,
};
graph.edges.push(
// Color Correct The Inpainted Result

42
invokeai/frontend/web/src/features/nodes/util/graphBuilders/buildCanvasSDXLOutpaintGraph.ts
View File

@ -18,10 +18,11 @@ import { addSDXLRefinerToGraph } from './addSDXLRefinerToGraph';
import { addVAEToGraph } from './addVAEToGraph';
import { addWatermarkerToGraph } from './addWatermarkerToGraph';
import {
CANVAS_OUTPUT,
CANVAS_COHERENCE_DENOISE_LATENTS,
CANVAS_COHERENCE_NOISE,
CANVAS_COHERENCE_NOISE_INCREMENT,
CANVAS_OUTPUT,
INPAINT_CREATE_MASK,
INPAINT_IMAGE,
INPAINT_IMAGE_RESIZE_DOWN,
INPAINT_IMAGE_RESIZE_UP,
@ -156,6 +157,12 @@ export const buildCanvasSDXLOutpaintGraph = (
use_cpu,
is_intermediate: true,
},
[INPAINT_CREATE_MASK]: {
type: 'create_denoise_mask',
id: INPAINT_CREATE_MASK,
is_intermediate: true,
fp32: vaePrecision === 'fp32' ? true : false,
},
[SDXL_DENOISE_LATENTS]: {
type: 'denoise_latents',
id: SDXL_DENOISE_LATENTS,
@ -331,16 +338,27 @@ export const buildCanvasSDXLOutpaintGraph = (
field: 'latents',
},
},
// Create Inpaint Mask
{
source: {
node_id: MASK_BLUR,
field: 'image',
},
destination: {
node_id: SDXL_DENOISE_LATENTS,
node_id: INPAINT_CREATE_MASK,
field: 'mask',
},
},
{
source: {
node_id: INPAINT_CREATE_MASK,
field: 'denoise_mask',
},
destination: {
node_id: SDXL_DENOISE_LATENTS,
field: 'denoise_mask',
},
},
// Iterate
{
source: {
@ -537,6 +555,16 @@ export const buildCanvasSDXLOutpaintGraph = (
field: 'image',
},
},
{
source: {
node_id: INPAINT_INFILL,
field: 'image',
},
destination: {
node_id: INPAINT_CREATE_MASK,
field: 'image',
},
},
// Take combined mask and resize and then blur
{
source: {
@ -655,6 +683,16 @@ export const buildCanvasSDXLOutpaintGraph = (
field: 'image',
},
},
{
source: {
node_id: INPAINT_INFILL,
field: 'image',
},
destination: {
node_id: INPAINT_CREATE_MASK,
field: 'image',
},
},
// Color Correct The Inpainted Result
{
source: {

87
invokeai/frontend/web/src/features/nodes/util/graphBuilders/buildCanvasSDXLTextToImageGraph.ts
View File

@ -15,6 +15,7 @@ import { addVAEToGraph } from './addVAEToGraph';
import { addWatermarkerToGraph } from './addWatermarkerToGraph';
import {
CANVAS_OUTPUT,
LATENTS_TO_IMAGE,
METADATA_ACCUMULATOR,
NEGATIVE_CONDITIONING,
NOISE,
@ -49,7 +50,15 @@ export const buildCanvasSDXLTextToImageGraph = (
// The bounding box determines width and height, not the width and height params
const { width, height } = state.canvas.boundingBoxDimensions;
const { shouldAutoSave } = state.canvas;
const {
scaledBoundingBoxDimensions,
boundingBoxScaleMethod,
shouldAutoSave,
} = state.canvas;
const isUsingScaledDimensions = ['auto', 'manual'].includes(
boundingBoxScaleMethod
);
const { shouldUseSDXLRefiner, refinerStart, shouldConcatSDXLStylePrompt } =
state.sdxl;
@ -136,17 +145,15 @@ export const buildCanvasSDXLTextToImageGraph = (
type: 'noise',
id: NOISE,
is_intermediate: true,
width,
height,
width: !isUsingScaledDimensions
? width
: scaledBoundingBoxDimensions.width,
height: !isUsingScaledDimensions
? height
: scaledBoundingBoxDimensions.height,
use_cpu,
},
[t2lNode.id]: t2lNode,
[CANVAS_OUTPUT]: {
type: isUsingOnnxModel ? 'l2i_onnx' : 'l2i',
id: CANVAS_OUTPUT,
is_intermediate: !shouldAutoSave,
fp32: vaePrecision === 'fp32' ? true : false,
},
},
edges: [
// Connect Model Loader to UNet and CLIP
@ -231,19 +238,67 @@ export const buildCanvasSDXLTextToImageGraph = (
field: 'noise',
},
},
// Decode Denoised Latents To Image
],
};
// Decode Latents To Image & Handle Scaled Before Processing
if (isUsingScaledDimensions) {
graph.nodes[LATENTS_TO_IMAGE] = {
id: LATENTS_TO_IMAGE,
type: isUsingOnnxModel ? 'l2i_onnx' : 'l2i',
is_intermediate: true,
fp32: vaePrecision === 'fp32' ? true : false,
};
graph.nodes[CANVAS_OUTPUT] = {
id: CANVAS_OUTPUT,
type: 'img_resize',
is_intermediate: !shouldAutoSave,
width: width,
height: height,
};
graph.edges.push(
{
source: {
node_id: SDXL_DENOISE_LATENTS,
field: 'latents',
},
destination: {
node_id: CANVAS_OUTPUT,
node_id: LATENTS_TO_IMAGE,
field: 'latents',
},
},
],
};
{
source: {
node_id: LATENTS_TO_IMAGE,
field: 'image',
},
destination: {
node_id: CANVAS_OUTPUT,
field: 'image',
},
}
);
} else {
graph.nodes[CANVAS_OUTPUT] = {
type: isUsingOnnxModel ? 'l2i_onnx' : 'l2i',
id: CANVAS_OUTPUT,
is_intermediate: !shouldAutoSave,
fp32: vaePrecision === 'fp32' ? true : false,
};
graph.edges.push({
source: {
node_id: SDXL_DENOISE_LATENTS,
field: 'latents',
},
destination: {
node_id: CANVAS_OUTPUT,
field: 'latents',
},
});
}
// add metadata accumulator, which is only mostly populated - some fields are added later
graph.nodes[METADATA_ACCUMULATOR] = {
@ -251,8 +306,10 @@ export const buildCanvasSDXLTextToImageGraph = (
type: 'metadata_accumulator',
generation_mode: 'txt2img',
cfg_scale,
height,
width,
width: !isUsingScaledDimensions ? width : scaledBoundingBoxDimensions.width,
height: !isUsingScaledDimensions
? height
: scaledBoundingBoxDimensions.height,
positive_prompt: '', // set in addDynamicPromptsToGraph
negative_prompt: negativePrompt,
model,

87
invokeai/frontend/web/src/features/nodes/util/graphBuilders/buildCanvasTextToImageGraph.ts
View File

@ -17,6 +17,7 @@ import {
CANVAS_TEXT_TO_IMAGE_GRAPH,
CLIP_SKIP,
DENOISE_LATENTS,
LATENTS_TO_IMAGE,
MAIN_MODEL_LOADER,
METADATA_ACCUMULATOR,
NEGATIVE_CONDITIONING,
@ -39,6 +40,7 @@ export const buildCanvasTextToImageGraph = (
cfgScale: cfg_scale,
scheduler,
steps,
vaePrecision,
clipSkip,
shouldUseCpuNoise,
shouldUseNoiseSettings,
@ -47,7 +49,15 @@ export const buildCanvasTextToImageGraph = (
// The bounding box determines width and height, not the width and height params
const { width, height } = state.canvas.boundingBoxDimensions;
const { shouldAutoSave } = state.canvas;
const {
scaledBoundingBoxDimensions,
boundingBoxScaleMethod,
shouldAutoSave,
} = state.canvas;
const isUsingScaledDimensions = ['auto', 'manual'].includes(
boundingBoxScaleMethod
);
if (!model) {
log.error('No model found in state');
@ -131,16 +141,15 @@ export const buildCanvasTextToImageGraph = (
type: 'noise',
id: NOISE,
is_intermediate: true,
width,
height,
width: !isUsingScaledDimensions
? width
: scaledBoundingBoxDimensions.width,
height: !isUsingScaledDimensions
? height
: scaledBoundingBoxDimensions.height,
use_cpu,
},
[t2lNode.id]: t2lNode,
[CANVAS_OUTPUT]: {
type: isUsingOnnxModel ? 'l2i_onnx' : 'l2i',
id: CANVAS_OUTPUT,
is_intermediate: !shouldAutoSave,
},
},
edges: [
// Connect Model Loader to UNet & CLIP Skip
@ -216,19 +225,67 @@ export const buildCanvasTextToImageGraph = (
field: 'noise',
},
},
// Decode denoised latents to image
],
};
// Decode Latents To Image & Handle Scaled Before Processing
if (isUsingScaledDimensions) {
graph.nodes[LATENTS_TO_IMAGE] = {
id: LATENTS_TO_IMAGE,
type: isUsingOnnxModel ? 'l2i_onnx' : 'l2i',
is_intermediate: true,
fp32: vaePrecision === 'fp32' ? true : false,
};
graph.nodes[CANVAS_OUTPUT] = {
id: CANVAS_OUTPUT,
type: 'img_resize',
is_intermediate: !shouldAutoSave,
width: width,
height: height,
};
graph.edges.push(
{
source: {
node_id: DENOISE_LATENTS,
field: 'latents',
},
destination: {
node_id: CANVAS_OUTPUT,
node_id: LATENTS_TO_IMAGE,
field: 'latents',
},
},
],
};
{
source: {
node_id: LATENTS_TO_IMAGE,
field: 'image',
},
destination: {
node_id: CANVAS_OUTPUT,
field: 'image',
},
}
);
} else {
graph.nodes[CANVAS_OUTPUT] = {
type: isUsingOnnxModel ? 'l2i_onnx' : 'l2i',
id: CANVAS_OUTPUT,
is_intermediate: !shouldAutoSave,
fp32: vaePrecision === 'fp32' ? true : false,
};
graph.edges.push({
source: {
node_id: DENOISE_LATENTS,
field: 'latents',
},
destination: {
node_id: CANVAS_OUTPUT,
field: 'latents',
},
});
}
// add metadata accumulator, which is only mostly populated - some fields are added later
graph.nodes[METADATA_ACCUMULATOR] = {
@ -236,8 +293,10 @@ export const buildCanvasTextToImageGraph = (
type: 'metadata_accumulator',
generation_mode: 'txt2img',
cfg_scale,
height,
width,
width: !isUsingScaledDimensions ? width : scaledBoundingBoxDimensions.width,
height: !isUsingScaledDimensions
? height
: scaledBoundingBoxDimensions.height,
positive_prompt: '', // set in addDynamicPromptsToGraph
negative_prompt: negativePrompt,
model,

2
invokeai/frontend/web/src/features/nodes/util/graphBuilders/constants.ts
View File

@ -17,6 +17,7 @@ export const CLIP_SKIP = 'clip_skip';
export const IMAGE_TO_LATENTS = 'image_to_latents';
export const LATENTS_TO_LATENTS = 'latents_to_latents';
export const RESIZE = 'resize_image';
export const IMG2IMG_RESIZE = 'img2img_resize';
export const CANVAS_OUTPUT = 'canvas_output';
export const INPAINT_IMAGE = 'inpaint_image';
export const SCALED_INPAINT_IMAGE = 'scaled_inpaint_image';
@ -25,6 +26,7 @@ export const INPAINT_IMAGE_RESIZE_DOWN = 'inpaint_image_resize_down';
export const INPAINT_INFILL = 'inpaint_infill';
export const INPAINT_INFILL_RESIZE_DOWN = 'inpaint_infill_resize_down';
export const INPAINT_FINAL_IMAGE = 'inpaint_final_image';
export const INPAINT_CREATE_MASK = 'inpaint_create_mask';
export const CANVAS_COHERENCE_DENOISE_LATENTS =
'canvas_coherence_denoise_latents';
export const CANVAS_COHERENCE_NOISE = 'canvas_coherence_noise';

120
invokeai/frontend/web/src/services/api/schema.d.ts vendored
View File

File diff suppressed because one or more lines are too long

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

@ -111,6 +111,7 @@ export type ImageBlurInvocation = s['ImageBlurInvocation'];
export type ImageScaleInvocation = s['ImageScaleInvocation'];
export type InfillPatchMatchInvocation = s['InfillPatchMatchInvocation'];
export type InfillTileInvocation = s['InfillTileInvocation'];
export type CreateDenoiseMaskInvocation = s['CreateDenoiseMaskInvocation'];
export type RandomIntInvocation = s['RandomIntInvocation'];
export type CompelInvocation = s['CompelInvocation'];
export type DynamicPromptInvocation = s['DynamicPromptInvocation'];