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fix(ui): fix generation graphs

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This commit is contained in:
psychedelicious 2024-06-20 11:12:28 +10:00
parent ce8a7bc178
commit c47e02c309
5 changed files with 24 additions and 15 deletions
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4
invokeai/frontend/web/src/common/hooks/useIsReadyToEnqueue.ts
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@ -141,9 +141,9 @@ const createSelector = (templates: Templates) =>
problems.push(i18n.t('parameters.invoke.layer.controlAdapterIncompatibleBaseModel'));
}
// Must have a control image OR, if it has a processor, it must have a processed image
if (!ca.image) {
if (!ca.imageObject) {
problems.push(i18n.t('parameters.invoke.layer.controlAdapterNoImageSelected'));
} else if (ca.processorConfig && !ca.processedImage) {
} else if (ca.processorConfig && !ca.processedImageObject) {
problems.push(i18n.t('parameters.invoke.layer.controlAdapterImageNotProcessed'));
}
// T2I Adapters require images have dimensions that are multiples of 64 (SD1.5) or 32 (SDXL)

18
invokeai/frontend/web/src/features/nodes/util/graph/generation/addControlAdapters.ts
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@ -46,9 +46,13 @@ const addControlNetCollectorSafe = (g: Graph, denoise: Invocation<'denoise_laten
};
const addControlNetToGraph = (ca: ControlNetData, g: Graph, denoise: Invocation<'denoise_latents'>) => {
const { id, beginEndStepPct, controlMode, image, model, processedImage, processorConfig, weight } = ca;
const { id, beginEndStepPct, controlMode, imageObject, model, processedImageObject, processorConfig, weight } = ca;
assert(model, 'ControlNet model is required');
const controlImage = buildControlImage(image, processedImage, processorConfig);
const controlImage = buildControlImage(
imageObject?.image ?? null,
processedImageObject?.image ?? null,
processorConfig
);
const controlNetCollect = addControlNetCollectorSafe(g, denoise);
const controlNet = g.addNode({
@ -84,9 +88,13 @@ const addT2IAdapterCollectorSafe = (g: Graph, denoise: Invocation<'denoise_laten
};
const addT2IAdapterToGraph = (ca: T2IAdapterData, g: Graph, denoise: Invocation<'denoise_latents'>) => {
const { id, beginEndStepPct, image, model, processedImage, processorConfig, weight } = ca;
const { id, beginEndStepPct, imageObject, model, processedImageObject, processorConfig, weight } = ca;
assert(model, 'T2I Adapter model is required');
const controlImage = buildControlImage(image, processedImage, processorConfig);
const controlImage = buildControlImage(
imageObject?.image ?? null,
processedImageObject?.image ?? null,
processorConfig
);
const t2iAdapterCollect = addT2IAdapterCollectorSafe(g, denoise);
const t2iAdapter = g.addNode({
@ -126,6 +134,6 @@ const isValidControlAdapter = (ca: ControlAdapterEntity, base: BaseModelType): b
// Must be have a model that matches the current base and must have a control image
const hasModel = Boolean(ca.model);
const modelMatchesBase = ca.model?.base === base;
const hasControlImage = Boolean(ca.image || (ca.processedImage && ca.processorConfig));
const hasControlImage = Boolean(ca.imageObject || (ca.processedImageObject && ca.processorConfig));
return hasModel && modelMatchesBase && hasControlImage;
};

6
invokeai/frontend/web/src/features/nodes/util/graph/generation/addIPAdapters.ts
View File

@ -34,8 +34,8 @@ export const addIPAdapterCollectorSafe = (g: Graph, denoise: Invocation<'denoise
};
const addIPAdapter = (ipa: IPAdapterEntity, g: Graph, denoise: Invocation<'denoise_latents'>) => {
const { id, weight, model, clipVisionModel, method, beginEndStepPct, imageObject: image } = ipa;
assert(image, 'IP Adapter image is required');
const { id, weight, model, clipVisionModel, method, beginEndStepPct, imageObject } = ipa;
assert(imageObject, 'IP Adapter image is required');
assert(model, 'IP Adapter model is required');
const ipAdapterCollect = addIPAdapterCollectorSafe(g, denoise);
@ -49,7 +49,7 @@ const addIPAdapter = (ipa: IPAdapterEntity, g: Graph, denoise: Invocation<'denoi
begin_step_percent: beginEndStepPct[0],
end_step_percent: beginEndStepPct[1],
image: {
image_name: image.name,
image_name: imageObject.image.name,
},
});
g.addEdge(ipAdapter, 'ip_adapter', ipAdapterCollect, 'item');

9
invokeai/frontend/web/src/features/nodes/util/graph/generation/addRegions.ts
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@ -2,6 +2,7 @@ import { getStore } from 'app/store/nanostores/store';
import { deepClone } from 'common/util/deepClone';
import openBase64ImageInTab from 'common/util/openBase64ImageInTab';
import { RG_LAYER_NAME } from 'features/controlLayers/konva/naming';
import { KonvaNodeManager } from 'features/controlLayers/konva/nodeManager';
import { renderRegions } from 'features/controlLayers/konva/renderers/regions';
import { blobToDataURL } from 'features/controlLayers/konva/util';
import { rgMaskImageUploaded } from 'features/controlLayers/store/canvasV2Slice';
@ -190,9 +191,9 @@ export const addRegions = async (
for (const ipa of validRGIPAdapters) {
const ipAdapterCollect = addIPAdapterCollectorSafe(g, denoise);
const { id, weight, model, clipVisionModel, method, beginEndStepPct, imageObject: image } = ipa;
const { id, weight, model, clipVisionModel, method, beginEndStepPct, imageObject } = ipa;
assert(model, 'IP Adapter model is required');
assert(image, 'IP Adapter image is required');
assert(imageObject, 'IP Adapter image is required');
const ipAdapter = g.addNode({
id: `ip_adapter_${id}`,
@ -204,7 +205,7 @@ export const addRegions = async (
begin_step_percent: beginEndStepPct[0],
end_step_percent: beginEndStepPct[1],
image: {
image_name: image.name,
image_name: imageObject.image.name,
},
});
@ -260,7 +261,7 @@ export const getRGMaskBlobs = async (
): Promise<Record<string, Blob>> => {
const container = document.createElement('div');
const stage = new Konva.Stage({ container, ...documentSize });
renderRegions(stage, regions, 1, 'brush', null);
renderRegions(new KonvaNodeManager(stage), regions, 1, 'brush', null);
const konvaLayers = stage.find<Konva.Layer>(`.${RG_LAYER_NAME}`);
const blobs: Record<string, Blob> = {};

2
invokeai/frontend/web/src/features/nodes/util/graph/generation/buildGenerationTabSDXLGraph.ts
View File

@ -43,7 +43,7 @@ export const buildGenerationTabSDXLGraph = async (state: RootState): Promise<Non
refinerModel,
refinerStart,
} = state.canvasV2.params;
const { width, height } = state.canvasV2.document;
const { width, height } = state.canvasV2.bbox;
assert(model, 'No model found in state');