feat(ui): txt2img & img2img graphs

invokeai/frontend/web/src/app/store/middleware/listenerMiddleware/listeners/enqueueRequestedLinear.ts

@@ -3,9 +3,10 @@ import type { AppStartListening } from 'app/store/middleware/listenerMiddleware'
 import { getNodeManager } from 'features/controlLayers/konva/nodeManager';
 import { isImageViewerOpenChanged } from 'features/gallery/store/gallerySlice';
 import { prepareLinearUIBatch } from 'features/nodes/util/graph/buildLinearBatchConfig';
-import { buildGenerationTabGraph } from 'features/nodes/util/graph/generation/buildGenerationTabGraph';
-import { buildGenerationTabSDXLGraph } from 'features/nodes/util/graph/generation/buildGenerationTabSDXLGraph';
+import { buildSD1Graph } from 'features/nodes/util/graph/generation/buildSD1Graph';
+import { buildSDXLGraph } from 'features/nodes/util/graph/generation/buildSDXLGraph';
 import { queueApi } from 'services/api/endpoints/queue';
+import { assert } from 'tsafe';
 
 export const addEnqueueRequestedLinear = (startAppListening: AppStartListening) => {
   startAppListening({
@@ -20,13 +21,15 @@ export const addEnqueueRequestedLinear = (startAppListening: AppStartListening)
       let graph;
 
       const manager = getNodeManager();
+      assert(model, 'No model found in state');
+      const base = model.base;
 
-      console.log('generation mode', manager.util.getGenerationMode());
-
-      if (model?.base === 'sdxl') {
-        graph = await buildGenerationTabSDXLGraph(state, manager);
+      if (base === 'sdxl') {
+        graph = await buildSDXLGraph(state, manager);
+      } else if (base === 'sd-1' || base === 'sd-2') {
+        graph = await buildSD1Graph(state, manager);
       } else {
-        graph = await buildGenerationTabGraph(state, manager);
+        assert(false, `No graph builders for base ${base}`);
       }
 
       const batchConfig = prepareLinearUIBatch(state, graph, prepend);

invokeai/frontend/web/src/features/nodes/util/graph/generation/addNSFWChecker.ts

@@ -10,7 +10,7 @@ import type { Invocation } from 'services/api/types';
  */
 export const addNSFWChecker = (
   g: Graph,
-  imageOutput: Invocation<'l2i'> | Invocation<'img_nsfw'> | Invocation<'img_watermark'>
+  imageOutput: Invocation<'l2i'> | Invocation<'img_nsfw'> | Invocation<'img_watermark'> | Invocation<'img_resize'>
 ): Invocation<'img_nsfw'> => {
   const nsfw = g.addNode({
     id: NSFW_CHECKER,

invokeai/frontend/web/src/features/nodes/util/graph/generation/addSDXLLoRAs.ts

@@ -4,7 +4,7 @@ import { LORA_LOADER } from 'features/nodes/util/graph/constants';
 import type { Graph } from 'features/nodes/util/graph/generation/Graph';
 import type { Invocation, S } from 'services/api/types';
 
-export const addSDXLLoRas = (
+export const addSDXLLoRAs = (
   state: RootState,
   g: Graph,
   denoise: Invocation<'denoise_latents'> | Invocation<'tiled_multi_diffusion_denoise_latents'>,

invokeai/frontend/web/src/features/nodes/util/graph/generation/addWatermarker.ts

@@ -10,7 +10,7 @@ import type { Invocation } from 'services/api/types';
  */
 export const addWatermarker = (
   g: Graph,
-  imageOutput: Invocation<'l2i'> | Invocation<'img_nsfw'> | Invocation<'img_watermark'>
+  imageOutput: Invocation<'l2i'> | Invocation<'img_nsfw'> | Invocation<'img_watermark'> | Invocation<'img_resize'>
 ): Invocation<'img_watermark'> => {
   const watermark = g.addNode({
     id: WATERMARKER,

invokeai/frontend/web/src/features/nodes/util/graph/generation/buildImageToImageSDXLGraph.ts

@@ -16,22 +16,23 @@ import {
 import { addControlAdapters } from 'features/nodes/util/graph/generation/addControlAdapters';
 import { addIPAdapters } from 'features/nodes/util/graph/generation/addIPAdapters';
 import { addNSFWChecker } from 'features/nodes/util/graph/generation/addNSFWChecker';
-import { addSDXLLoRas } from 'features/nodes/util/graph/generation/addSDXLLoRAs';
+import { addSDXLLoRAs } from 'features/nodes/util/graph/generation/addSDXLLoRAs';
 import { addSDXLRefiner } from 'features/nodes/util/graph/generation/addSDXLRefiner';
 import { addSeamless } from 'features/nodes/util/graph/generation/addSeamless';
 import { addWatermarker } from 'features/nodes/util/graph/generation/addWatermarker';
 import { Graph } from 'features/nodes/util/graph/generation/Graph';
-import { getBoardField, getPresetModifiedPrompts } from 'features/nodes/util/graph/graphBuilderUtils';
+import { getBoardField, getPresetModifiedPrompts , getSizes } from 'features/nodes/util/graph/graphBuilderUtils';
 import type { Invocation, NonNullableGraph } from 'services/api/types';
 import { isNonRefinerMainModelConfig } from 'services/api/types';
 import { assert } from 'tsafe';
 
 import { addRegions } from './addRegions';
 
-export const buildGenerationTabSDXLGraph = async (
+export const buildImageToImageSDXLGraph = async (
   state: RootState,
   manager: KonvaNodeManager
 ): Promise<NonNullableGraph> => {
+  const { bbox, params } = state.canvasV2;
   const {
     model,
     cfgScale: cfg_scale,
@@ -42,17 +43,17 @@ export const buildGenerationTabSDXLGraph = async (
     shouldUseCpuNoise,
     vaePrecision,
     vae,
-    positivePrompt,
-    negativePrompt,
     refinerModel,
     refinerStart,
     img2imgStrength,
-  } = state.canvasV2.params;
-  const { width, height } = state.canvasV2.bbox;
+  } = params;
 
   assert(model, 'No model found in state');
 
   const { positivePrompt, negativePrompt, positiveStylePrompt, negativeStylePrompt } = getPresetModifiedPrompts(state);
+  const { originalSize, scaledSize } = getSizes(bbox);
+
+
 
   const g = new Graph(SDXL_CONTROL_LAYERS_GRAPH);
   const modelLoader = g.addNode({
@@ -80,8 +81,14 @@ export const buildGenerationTabSDXLGraph = async (
     type: 'collect',
     id: NEGATIVE_CONDITIONING_COLLECT,
   });
-  const noise = g.addNode({ type: 'noise', id: NOISE, seed, width, height, use_cpu: shouldUseCpuNoise });
-  const i2l = g.addNode({ type: 'i2l', id: 'i2l' });
+  const noise = g.addNode({
+    type: 'noise',
+    id: NOISE,
+    seed,
+    width: scaledSize.width,
+    height: scaledSize.height,
+    use_cpu: shouldUseCpuNoise,
+  });
   const denoise = g.addNode({
     type: 'denoise_latents',
     id: SDXL_DENOISE_LATENTS,
@@ -110,7 +117,8 @@ export const buildGenerationTabSDXLGraph = async (
         })
       : null;
 
-  let imageOutput: Invocation<'l2i'> | Invocation<'img_nsfw'> | Invocation<'img_watermark'> = l2i;
+  let imageOutput: Invocation<'l2i'> | Invocation<'img_nsfw'> | Invocation<'img_watermark'> | Invocation<'img_resize'> =
+    l2i;
 
   g.addEdge(modelLoader, 'unet', denoise, 'unet');
   g.addEdge(modelLoader, 'clip', posCond, 'clip');
@@ -122,7 +130,6 @@ export const buildGenerationTabSDXLGraph = async (
   g.addEdge(posCondCollect, 'collection', denoise, 'positive_conditioning');
   g.addEdge(negCondCollect, 'collection', denoise, 'negative_conditioning');
   g.addEdge(noise, 'noise', denoise, 'noise');
-  g.addEdge(i2l, 'latents', denoise, 'latents');
   g.addEdge(denoise, 'latents', l2i, 'latents');
 
   const modelConfig = await fetchModelConfigWithTypeGuard(model.key, isNonRefinerMainModelConfig);
@@ -132,8 +139,8 @@ export const buildGenerationTabSDXLGraph = async (
     generation_mode: 'sdxl_txt2img',
     cfg_scale,
     cfg_rescale_multiplier,
-    height,
-    width,
+    width: scaledSize.width,
+    height: scaledSize.height,
     positive_prompt: positivePrompt,
     negative_prompt: negativePrompt,
     model: Graph.getModelMetadataField(modelConfig),
@@ -148,18 +155,19 @@ export const buildGenerationTabSDXLGraph = async (
 
   const seamless = addSeamless(state, g, denoise, modelLoader, vaeLoader);
 
-  addSDXLLoRas(state, g, denoise, modelLoader, seamless, posCond, negCond);
+  addSDXLLoRAs(state, g, denoise, modelLoader, seamless, posCond, negCond);
 
   // We might get the VAE from the main model, custom VAE, or seamless node.
   const vaeSource = seamless ?? vaeLoader ?? modelLoader;
   g.addEdge(vaeSource, 'vae', l2i, 'vae');
-  g.addEdge(vaeSource, 'vae', i2l, 'vae');
 
   // Add Refiner if enabled
   if (refinerModel) {
     await addSDXLRefiner(state, g, denoise, seamless, posCond, negCond, l2i);
   }
 
+
+
   const _addedCAs = addControlAdapters(state.canvasV2.controlAdapters.entities, g, denoise, modelConfig.base);
   const _addedIPAs = addIPAdapters(state.canvasV2.ipAdapters.entities, g, denoise, modelConfig.base);
   const _addedRegions = await addRegions(
@@ -175,9 +183,6 @@ export const buildGenerationTabSDXLGraph = async (
     posCondCollect,
     negCondCollect
   );
-  const { image_name } = await manager.util.getImageSourceImage({ bbox: state.canvasV2.bbox, preview: true });
-  await manager.util.getInpaintMaskImage({ bbox: state.canvasV2.bbox, preview: true });
-  i2l.image = { image_name };
 
   if (state.system.shouldUseNSFWChecker) {
     imageOutput = addNSFWChecker(g, imageOutput);

invokeai/frontend/web/src/features/nodes/util/graph/generation/buildSD1Graph.ts

@@ -0,0 +1,246 @@
+import type { RootState } from 'app/store/store';
+import type { KonvaNodeManager } from 'features/controlLayers/konva/nodeManager';
+import { fetchModelConfigWithTypeGuard } from 'features/metadata/util/modelFetchingHelpers';
+import {
+  CLIP_SKIP,
+  CONTROL_LAYERS_GRAPH,
+  DENOISE_LATENTS,
+  LATENTS_TO_IMAGE,
+  MAIN_MODEL_LOADER,
+  NEGATIVE_CONDITIONING,
+  NEGATIVE_CONDITIONING_COLLECT,
+  NOISE,
+  POSITIVE_CONDITIONING,
+  POSITIVE_CONDITIONING_COLLECT,
+  VAE_LOADER,
+} from 'features/nodes/util/graph/constants';
+import { addControlAdapters } from 'features/nodes/util/graph/generation/addControlAdapters';
+// import { addHRF } from 'features/nodes/util/graph/generation/addHRF';
+import { addIPAdapters } from 'features/nodes/util/graph/generation/addIPAdapters';
+import { addLoRAs } from 'features/nodes/util/graph/generation/addLoRAs';
+import { addNSFWChecker } from 'features/nodes/util/graph/generation/addNSFWChecker';
+import { addSeamless } from 'features/nodes/util/graph/generation/addSeamless';
+import { addWatermarker } from 'features/nodes/util/graph/generation/addWatermarker';
+import type { GraphType } from 'features/nodes/util/graph/generation/Graph';
+import { Graph } from 'features/nodes/util/graph/generation/Graph';
+import { getBoardField, getSizes } from 'features/nodes/util/graph/graphBuilderUtils';
+import { isEqual, pick } from 'lodash-es';
+import type { Invocation } from 'services/api/types';
+import { isNonRefinerMainModelConfig } from 'services/api/types';
+import { assert } from 'tsafe';
+
+import { addRegions } from './addRegions';
+
+export const buildSD1Graph = async (state: RootState, manager: KonvaNodeManager): Promise<GraphType> => {
+  const generationMode = manager.util.getGenerationMode();
+
+  const { bbox, params } = state.canvasV2;
+
+  const {
+    model,
+    cfgScale: cfg_scale,
+    cfgRescaleMultiplier: cfg_rescale_multiplier,
+    scheduler,
+    steps,
+    clipSkip: skipped_layers,
+    shouldUseCpuNoise,
+    vaePrecision,
+    seed,
+    vae,
+    positivePrompt,
+    negativePrompt,
+    img2imgStrength,
+  } = params;
+
+  assert(model, 'No model found in state');
+
+  const { originalSize, scaledSize } = getSizes(bbox);
+
+  const g = new Graph(CONTROL_LAYERS_GRAPH);
+  const modelLoader = g.addNode({
+    type: 'main_model_loader',
+    id: MAIN_MODEL_LOADER,
+    model,
+  });
+  const clipSkip = g.addNode({
+    type: 'clip_skip',
+    id: CLIP_SKIP,
+    skipped_layers,
+  });
+  const posCond = g.addNode({
+    type: 'compel',
+    id: POSITIVE_CONDITIONING,
+    prompt: positivePrompt,
+  });
+  const posCondCollect = g.addNode({
+    type: 'collect',
+    id: POSITIVE_CONDITIONING_COLLECT,
+  });
+  const negCond = g.addNode({
+    type: 'compel',
+    id: NEGATIVE_CONDITIONING,
+    prompt: negativePrompt,
+  });
+  const negCondCollect = g.addNode({
+    type: 'collect',
+    id: NEGATIVE_CONDITIONING_COLLECT,
+  });
+  const noise = g.addNode({
+    type: 'noise',
+    id: NOISE,
+    seed,
+    width: scaledSize.width,
+    height: scaledSize.height,
+    use_cpu: shouldUseCpuNoise,
+  });
+  const denoise = g.addNode({
+    type: 'denoise_latents',
+    id: DENOISE_LATENTS,
+    cfg_scale,
+    cfg_rescale_multiplier,
+    scheduler,
+    steps,
+    denoising_start: 0,
+    denoising_end: 1,
+  });
+  const l2i = g.addNode({
+    type: 'l2i',
+    id: LATENTS_TO_IMAGE,
+    fp32: vaePrecision === 'fp32',
+    board: getBoardField(state),
+    // This is the terminal node and must always save to gallery.
+    is_intermediate: false,
+    use_cache: false,
+  });
+  const vaeLoader =
+    vae?.base === model.base
+      ? g.addNode({
+          type: 'vae_loader',
+          id: VAE_LOADER,
+          vae_model: vae,
+        })
+      : null;
+
+  let imageOutput: Invocation<'l2i'> | Invocation<'img_nsfw'> | Invocation<'img_watermark'> | Invocation<'img_resize'> =
+    l2i;
+
+  g.addEdge(modelLoader, 'unet', denoise, 'unet');
+  g.addEdge(modelLoader, 'clip', clipSkip, 'clip');
+  g.addEdge(clipSkip, 'clip', posCond, 'clip');
+  g.addEdge(clipSkip, 'clip', negCond, 'clip');
+  g.addEdge(posCond, 'conditioning', posCondCollect, 'item');
+  g.addEdge(negCond, 'conditioning', negCondCollect, 'item');
+  g.addEdge(posCondCollect, 'collection', denoise, 'positive_conditioning');
+  g.addEdge(negCondCollect, 'collection', denoise, 'negative_conditioning');
+  g.addEdge(noise, 'noise', denoise, 'noise');
+  g.addEdge(denoise, 'latents', l2i, 'latents');
+
+  const modelConfig = await fetchModelConfigWithTypeGuard(model.key, isNonRefinerMainModelConfig);
+  assert(modelConfig.base === 'sd-1' || modelConfig.base === 'sd-2');
+
+  g.upsertMetadata({
+    generation_mode: 'txt2img',
+    cfg_scale,
+    cfg_rescale_multiplier,
+    width: scaledSize.width,
+    height: scaledSize.height,
+    positive_prompt: positivePrompt,
+    negative_prompt: negativePrompt,
+    model: Graph.getModelMetadataField(modelConfig),
+    seed,
+    steps,
+    rand_device: shouldUseCpuNoise ? 'cpu' : 'cuda',
+    scheduler,
+    clip_skip: skipped_layers,
+    vae: vae ?? undefined,
+  });
+
+  const seamless = addSeamless(state, g, denoise, modelLoader, vaeLoader);
+
+  addLoRAs(state, g, denoise, modelLoader, seamless, clipSkip, posCond, negCond);
+
+  // We might get the VAE from the main model, custom VAE, or seamless node.
+  const vaeSource = seamless ?? vaeLoader ?? modelLoader;
+  g.addEdge(vaeSource, 'vae', l2i, 'vae');
+
+  if (generationMode === 'txt2img') {
+    if (!isEqual(scaledSize, originalSize)) {
+      // We are using scaled bbox and need to resize the output image back to the original size.
+      imageOutput = g.addNode({
+        id: 'img_resize',
+        type: 'img_resize',
+        ...originalSize,
+        is_intermediate: false,
+        use_cache: false,
+      });
+      g.addEdge(l2i, 'image', imageOutput, 'image');
+    }
+  } else if (generationMode === 'img2img') {
+    const { image_name } = await manager.util.getImageSourceImage({
+      bbox: pick(bbox, ['x', 'y', 'width', 'height']),
+      preview: true,
+    });
+
+    denoise.denoising_start = 1 - img2imgStrength;
+
+    if (!isEqual(scaledSize, originalSize)) {
+      // We are using scaled bbox and need to resize the output image back to the original size.
+      const initialImageResize = g.addNode({
+        id: 'initial_image_resize',
+        type: 'img_resize',
+        ...scaledSize,
+        image: { image_name },
+      });
+      const i2l = g.addNode({ id: 'i2l', type: 'i2l' });
+
+      g.addEdge(vaeSource, 'vae', i2l, 'vae');
+      g.addEdge(initialImageResize, 'image', i2l, 'image');
+      g.addEdge(i2l, 'latents', denoise, 'latents');
+
+      imageOutput = g.addNode({
+        id: 'img_resize',
+        type: 'img_resize',
+        ...originalSize,
+        is_intermediate: false,
+        use_cache: false,
+      });
+      g.addEdge(l2i, 'image', imageOutput, 'image');
+    } else {
+      const i2l = g.addNode({ id: 'i2l', type: 'i2l', image: { image_name } });
+      g.addEdge(vaeSource, 'vae', i2l, 'vae');
+      g.addEdge(i2l, 'latents', denoise, 'latents');
+    }
+  }
+
+  const _addedCAs = addControlAdapters(state.canvasV2.controlAdapters.entities, g, denoise, modelConfig.base);
+  const _addedIPAs = addIPAdapters(state.canvasV2.ipAdapters.entities, g, denoise, modelConfig.base);
+  const _addedRegions = await addRegions(
+    manager,
+    state.canvasV2.regions.entities,
+    g,
+    state.canvasV2.document,
+    state.canvasV2.bbox,
+    modelConfig.base,
+    denoise,
+    posCond,
+    negCond,
+    posCondCollect,
+    negCondCollect
+  );
+
+  // const isHRFAllowed = !addedLayers.some((l) => isInitialImageLayer(l) || isRegionalGuidanceLayer(l));
+  // if (isHRFAllowed && state.hrf.hrfEnabled) {
+  //   imageOutput = addHRF(state, g, denoise, noise, l2i, vaeSource);
+  // }
+
+  if (state.system.shouldUseNSFWChecker) {
+    imageOutput = addNSFWChecker(g, imageOutput);
+  }
+
+  if (state.system.shouldUseWatermarker) {
+    imageOutput = addWatermarker(g, imageOutput);
+  }
+
+  g.setMetadataReceivingNode(imageOutput);
+  return g.getGraph();
+};

invokeai/frontend/web/src/features/nodes/util/graph/generation/buildSDXLGraph.ts

@@ -0,0 +1,246 @@
+import type { RootState } from 'app/store/store';
+import type { KonvaNodeManager } from 'features/controlLayers/konva/nodeManager';
+import { fetchModelConfigWithTypeGuard } from 'features/metadata/util/modelFetchingHelpers';
+import {
+  LATENTS_TO_IMAGE,
+  NEGATIVE_CONDITIONING,
+  NEGATIVE_CONDITIONING_COLLECT,
+  NOISE,
+  POSITIVE_CONDITIONING,
+  POSITIVE_CONDITIONING_COLLECT,
+  SDXL_CONTROL_LAYERS_GRAPH,
+  SDXL_DENOISE_LATENTS,
+  SDXL_MODEL_LOADER,
+  VAE_LOADER,
+} from 'features/nodes/util/graph/constants';
+import { addControlAdapters } from 'features/nodes/util/graph/generation/addControlAdapters';
+import { addIPAdapters } from 'features/nodes/util/graph/generation/addIPAdapters';
+import { addNSFWChecker } from 'features/nodes/util/graph/generation/addNSFWChecker';
+import { addSDXLLoRAs } from 'features/nodes/util/graph/generation/addSDXLLoRAs';
+import { addSDXLRefiner } from 'features/nodes/util/graph/generation/addSDXLRefiner';
+import { addSeamless } from 'features/nodes/util/graph/generation/addSeamless';
+import { addWatermarker } from 'features/nodes/util/graph/generation/addWatermarker';
+import { Graph } from 'features/nodes/util/graph/generation/Graph';
+import { getBoardField, getSDXLStylePrompts, getSizes } from 'features/nodes/util/graph/graphBuilderUtils';
+import { isEqual, pick } from 'lodash-es';
+import type { Invocation, NonNullableGraph } from 'services/api/types';
+import { isNonRefinerMainModelConfig } from 'services/api/types';
+import { assert } from 'tsafe';
+
+import { addRegions } from './addRegions';
+
+export const buildSDXLGraph = async (state: RootState, manager: KonvaNodeManager): Promise<NonNullableGraph> => {
+  const generationMode = manager.util.getGenerationMode();
+
+  const { bbox, params } = state.canvasV2;
+
+  const {
+    model,
+    cfgScale: cfg_scale,
+    cfgRescaleMultiplier: cfg_rescale_multiplier,
+    scheduler,
+    seed,
+    steps,
+    shouldUseCpuNoise,
+    vaePrecision,
+    vae,
+    positivePrompt,
+    negativePrompt,
+    refinerModel,
+    refinerStart,
+    img2imgStrength,
+  } = params;
+
+  assert(model, 'No model found in state');
+
+  const { originalSize, scaledSize } = getSizes(bbox);
+
+  const { positiveStylePrompt, negativeStylePrompt } = getSDXLStylePrompts(state);
+
+  const g = new Graph(SDXL_CONTROL_LAYERS_GRAPH);
+  const modelLoader = g.addNode({
+    type: 'sdxl_model_loader',
+    id: SDXL_MODEL_LOADER,
+    model,
+  });
+  const posCond = g.addNode({
+    type: 'sdxl_compel_prompt',
+    id: POSITIVE_CONDITIONING,
+    prompt: positivePrompt,
+    style: positiveStylePrompt,
+  });
+  const posCondCollect = g.addNode({
+    type: 'collect',
+    id: POSITIVE_CONDITIONING_COLLECT,
+  });
+  const negCond = g.addNode({
+    type: 'sdxl_compel_prompt',
+    id: NEGATIVE_CONDITIONING,
+    prompt: negativePrompt,
+    style: negativeStylePrompt,
+  });
+  const negCondCollect = g.addNode({
+    type: 'collect',
+    id: NEGATIVE_CONDITIONING_COLLECT,
+  });
+  const noise = g.addNode({
+    type: 'noise',
+    id: NOISE,
+    seed,
+    width: scaledSize.width,
+    height: scaledSize.height,
+    use_cpu: shouldUseCpuNoise,
+  });
+  const denoise = g.addNode({
+    type: 'denoise_latents',
+    id: SDXL_DENOISE_LATENTS,
+    cfg_scale,
+    cfg_rescale_multiplier,
+    scheduler,
+    steps,
+    denoising_start: 0,
+    denoising_end: refinerModel ? refinerStart : 1,
+  });
+  const l2i = g.addNode({
+    type: 'l2i',
+    id: LATENTS_TO_IMAGE,
+    fp32: vaePrecision === 'fp32',
+    board: getBoardField(state),
+    // This is the terminal node and must always save to gallery.
+    is_intermediate: false,
+    use_cache: false,
+  });
+  const vaeLoader =
+    vae?.base === model.base
+      ? g.addNode({
+          type: 'vae_loader',
+          id: VAE_LOADER,
+          vae_model: vae,
+        })
+      : null;
+
+  let imageOutput: Invocation<'l2i'> | Invocation<'img_nsfw'> | Invocation<'img_watermark'> | Invocation<'img_resize'> =
+    l2i;
+
+  g.addEdge(modelLoader, 'unet', denoise, 'unet');
+  g.addEdge(modelLoader, 'clip', posCond, 'clip');
+  g.addEdge(modelLoader, 'clip', negCond, 'clip');
+  g.addEdge(modelLoader, 'clip2', posCond, 'clip2');
+  g.addEdge(modelLoader, 'clip2', negCond, 'clip2');
+  g.addEdge(posCond, 'conditioning', posCondCollect, 'item');
+  g.addEdge(negCond, 'conditioning', negCondCollect, 'item');
+  g.addEdge(posCondCollect, 'collection', denoise, 'positive_conditioning');
+  g.addEdge(negCondCollect, 'collection', denoise, 'negative_conditioning');
+  g.addEdge(noise, 'noise', denoise, 'noise');
+  g.addEdge(denoise, 'latents', l2i, 'latents');
+
+  const modelConfig = await fetchModelConfigWithTypeGuard(model.key, isNonRefinerMainModelConfig);
+  assert(modelConfig.base === 'sdxl');
+
+  g.upsertMetadata({
+    generation_mode: 'sdxl_txt2img',
+    cfg_scale,
+    cfg_rescale_multiplier,
+    width: scaledSize.width,
+    height: scaledSize.height,
+    positive_prompt: positivePrompt,
+    negative_prompt: negativePrompt,
+    model: Graph.getModelMetadataField(modelConfig),
+    seed,
+    steps,
+    rand_device: shouldUseCpuNoise ? 'cpu' : 'cuda',
+    scheduler,
+    positive_style_prompt: positiveStylePrompt,
+    negative_style_prompt: negativeStylePrompt,
+    vae: vae ?? undefined,
+  });
+
+  const seamless = addSeamless(state, g, denoise, modelLoader, vaeLoader);
+
+  addSDXLLoRAs(state, g, denoise, modelLoader, seamless, posCond, negCond);
+
+  // We might get the VAE from the main model, custom VAE, or seamless node.
+  const vaeSource = seamless ?? vaeLoader ?? modelLoader;
+  g.addEdge(vaeSource, 'vae', l2i, 'vae');
+
+  // Add Refiner if enabled
+  if (refinerModel) {
+    await addSDXLRefiner(state, g, denoise, seamless, posCond, negCond, l2i);
+  }
+
+  if (generationMode === 'txt2img') {
+    if (!isEqual(scaledSize, originalSize)) {
+      // We are using scaled bbox and need to resize the output image back to the original size.
+      imageOutput = g.addNode({
+        id: 'img_resize',
+        type: 'img_resize',
+        ...originalSize,
+        is_intermediate: false,
+        use_cache: false,
+      });
+      g.addEdge(l2i, 'image', imageOutput, 'image');
+    }
+  } else if (generationMode === 'img2img') {
+    denoise.denoising_start = refinerModel ? Math.min(refinerStart, 1 - img2imgStrength) : 1 - img2imgStrength;
+
+    const { image_name } = await manager.util.getImageSourceImage({
+      bbox: pick(bbox, ['x', 'y', 'width', 'height']),
+      preview: true,
+    });
+
+    if (!isEqual(scaledSize, originalSize)) {
+      // We are using scaled bbox and need to resize the output image back to the original size.
+      const initialImageResize = g.addNode({
+        id: 'initial_image_resize',
+        type: 'img_resize',
+        ...scaledSize,
+        image: { image_name },
+      });
+      const i2l = g.addNode({ id: 'i2l', type: 'i2l' });
+
+      g.addEdge(vaeSource, 'vae', i2l, 'vae');
+      g.addEdge(initialImageResize, 'image', i2l, 'image');
+      g.addEdge(i2l, 'latents', denoise, 'latents');
+
+      imageOutput = g.addNode({
+        id: 'img_resize',
+        type: 'img_resize',
+        ...originalSize,
+        is_intermediate: false,
+        use_cache: false,
+      });
+      g.addEdge(l2i, 'image', imageOutput, 'image');
+    } else {
+      const i2l = g.addNode({ id: 'i2l', type: 'i2l', image: { image_name } });
+      g.addEdge(vaeSource, 'vae', i2l, 'vae');
+      g.addEdge(i2l, 'latents', denoise, 'latents');
+    }
+  }
+
+  const _addedCAs = addControlAdapters(state.canvasV2.controlAdapters.entities, g, denoise, modelConfig.base);
+  const _addedIPAs = addIPAdapters(state.canvasV2.ipAdapters.entities, g, denoise, modelConfig.base);
+  const _addedRegions = await addRegions(
+    manager,
+    state.canvasV2.regions.entities,
+    g,
+    state.canvasV2.document,
+    state.canvasV2.bbox,
+    modelConfig.base,
+    denoise,
+    posCond,
+    negCond,
+    posCondCollect,
+    negCondCollect
+  );
+
+  if (state.system.shouldUseNSFWChecker) {
+    imageOutput = addNSFWChecker(g, imageOutput);
+  }
+
+  if (state.system.shouldUseWatermarker) {
+    imageOutput = addWatermarker(g, imageOutput);
+  }
+
+  g.setMetadataReceivingNode(imageOutput);
+  return g.getGraph();
+};

invokeai/frontend/web/src/features/nodes/util/graph/generation/buildTextToImageSD1SD2Graph.ts

@@ -23,14 +23,17 @@ import { addSeamless } from 'features/nodes/util/graph/generation/addSeamless';
 import { addWatermarker } from 'features/nodes/util/graph/generation/addWatermarker';
 import type { GraphType } from 'features/nodes/util/graph/generation/Graph';
 import { Graph } from 'features/nodes/util/graph/generation/Graph';
-import { getBoardField, getPresetModifiedPrompts } from 'features/nodes/util/graph/graphBuilderUtils';
+import { getBoardField, getPresetModifiedPrompts , getSizes } from 'features/nodes/util/graph/graphBuilderUtils';
+import { isEqual } from 'lodash-es';
 import type { Invocation } from 'services/api/types';
 import { isNonRefinerMainModelConfig } from 'services/api/types';
 import { assert } from 'tsafe';
 
 import { addRegions } from './addRegions';
 
-export const buildGenerationTabGraph = async (state: RootState, manager: KonvaNodeManager): Promise<GraphType> => {
+export const buildTextToImageSD1SD2Graph = async (state: RootState, manager: KonvaNodeManager): Promise<GraphType> => {
+  const { bbox, params } = state.canvasV2;
+
   const {
     model,
     cfgScale: cfg_scale,
@@ -42,14 +45,12 @@ export const buildGenerationTabGraph = async (state: RootState, manager: KonvaNo
     vaePrecision,
     seed,
     vae,
-    positivePrompt,
-    negativePrompt,
-  } = state.canvasV2.params;
-  const { width, height } = state.canvasV2.document;
+  } = params;
 
   assert(model, 'No model found in state');
 
   const { positivePrompt, negativePrompt } = getPresetModifiedPrompts(state);
+  const { originalSize, scaledSize } = getSizes(bbox);
 
   const g = new Graph(CONTROL_LAYERS_GRAPH);
   const modelLoader = g.addNode({
@@ -84,8 +85,8 @@ export const buildGenerationTabGraph = async (state: RootState, manager: KonvaNo
     type: 'noise',
     id: NOISE,
     seed,
-    width,
-    height,
+    width: scaledSize.width,
+    height: scaledSize.height,
     use_cpu: shouldUseCpuNoise,
   });
   const denoise = g.addNode({
@@ -116,7 +117,8 @@ export const buildGenerationTabGraph = async (state: RootState, manager: KonvaNo
         })
       : null;
 
-  let imageOutput: Invocation<'l2i'> | Invocation<'img_nsfw'> | Invocation<'img_watermark'> = l2i;
+  let imageOutput: Invocation<'l2i'> | Invocation<'img_nsfw'> | Invocation<'img_watermark'> | Invocation<'img_resize'> =
+    l2i;
 
   g.addEdge(modelLoader, 'unet', denoise, 'unet');
   g.addEdge(modelLoader, 'clip', clipSkip, 'clip');
@@ -136,8 +138,8 @@ export const buildGenerationTabGraph = async (state: RootState, manager: KonvaNo
     generation_mode: 'txt2img',
     cfg_scale,
     cfg_rescale_multiplier,
-    height,
-    width,
+    width: scaledSize.width,
+    height: scaledSize.height,
     positive_prompt: positivePrompt,
     negative_prompt: negativePrompt,
     model: Graph.getModelMetadataField(modelConfig),
@@ -157,6 +159,18 @@ export const buildGenerationTabGraph = async (state: RootState, manager: KonvaNo
   const vaeSource = seamless ?? vaeLoader ?? modelLoader;
   g.addEdge(vaeSource, 'vae', l2i, 'vae');
 
+  if (!isEqual(scaledSize, originalSize)) {
+    // We are using scaled bbox and need to resize the output image back to the original size.
+    imageOutput = g.addNode({
+      id: 'img_resize',
+      type: 'img_resize',
+      ...originalSize,
+      is_intermediate: false,
+      use_cache: false,
+    });
+    g.addEdge(l2i, 'image', imageOutput, 'image');
+  }
+
   const _addedCAs = addControlAdapters(state.canvasV2.controlAdapters.entities, g, denoise, modelConfig.base);
   const _addedIPAs = addIPAdapters(state.canvasV2.ipAdapters.entities, g, denoise, modelConfig.base);
   const _addedRegions = await addRegions(

invokeai/frontend/web/src/features/nodes/util/graph/graphBuilderUtils.ts

@@ -1,7 +1,9 @@
 import type { RootState } from 'app/store/store';
+import type { CanvasV2State } from 'features/controlLayers/store/types';
 import type { BoardField } from 'features/nodes/types/common';
 import { buildPresetModifiedPrompt } from 'features/stylePresets/hooks/usePresetModifiedPrompts';
 import { activeTabNameSelector } from 'features/ui/store/uiSelectors';
+import { pick } from 'lodash-es';
 import { stylePresetsApi } from 'services/api/endpoints/stylePresets';
 
 /**
@@ -22,7 +24,7 @@ export const getPresetModifiedPrompts = (
   state: RootState
 ): { positivePrompt: string; negativePrompt: string; positiveStylePrompt?: string; negativeStylePrompt?: string } => {
   const { positivePrompt, negativePrompt, positivePrompt2, negativePrompt2, shouldConcatPrompts } =
-    state.generation;
+    state.canvasV2.params;
   const { activeStylePresetId } = state.stylePreset;
 
   if (activeStylePresetId) {
@@ -68,3 +70,9 @@ export const getIsIntermediate = (state: RootState) => {
   }
   return false;
 };
+
+export const getSizes = (bboxState: CanvasV2State['bbox']) => {
+  const originalSize = pick(bboxState, 'width', 'height');
+  const scaledSize = ['auto', 'manual'].includes(bboxState.scaleMethod) ? bboxState.scaledSize : originalSize;
+  return { originalSize, scaledSize };
+};