feat: add canvas product position adjustment
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@ -649,7 +649,13 @@ export async function POST(request: NextRequest) {
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targetRect: getScaleAdjustTargetRect(region, scalePercent),
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})
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);
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const hasPositionMove = scaleAdjustIntentRegions.some(
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(region) =>
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Math.abs(region.targetRect.x - region.rect.x) >= 0.005 ||
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Math.abs(region.targetRect.y - region.rect.y) >= 0.005
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);
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const productLockAssets = await buildScaleAdjustProductLockAssets({
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protectPeople: hasPositionMove,
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regions: scaleAdjustIntentRegions,
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sourceBuffer,
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sourceHeight,
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@ -660,42 +666,75 @@ export async function POST(request: NextRequest) {
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const assetSuffix = `${Date.now()}-${Math.random()
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.toString(36)
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.slice(2, 8)}`;
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const [modelMaskUpload, overlayUpload, repairMaskUpload] = await Promise.all([
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uploadFile(
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`canvas-scale-adjust-mask-${assetSuffix}.png`,
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toArrayBuffer(productLockAssets.modelMaskBuffer)
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),
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uploadFile(
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`canvas-scale-adjust-overlay-${assetSuffix}.png`,
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toArrayBuffer(productLockAssets.overlayBuffer)
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),
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uploadFile(
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`canvas-scale-adjust-repair-mask-${assetSuffix}.png`,
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toArrayBuffer(productLockAssets.repairMaskBuffer)
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),
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]);
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const [modelMaskUpload, overlayUpload, repairMaskUpload, sourceSubjectMaskUpload] =
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await Promise.all([
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uploadFile(
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`canvas-scale-adjust-mask-${assetSuffix}.png`,
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toArrayBuffer(productLockAssets.modelMaskBuffer)
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),
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uploadFile(
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`canvas-scale-adjust-overlay-${assetSuffix}.png`,
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toArrayBuffer(productLockAssets.overlayBuffer)
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),
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uploadFile(
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`canvas-scale-adjust-repair-mask-${assetSuffix}.png`,
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toArrayBuffer(productLockAssets.repairMaskBuffer)
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),
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hasPositionMove
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? uploadFile(
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`canvas-scale-adjust-subject-mask-${assetSuffix}.png`,
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toArrayBuffer(productLockAssets.sourceSubjectMaskBuffer)
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)
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: Promise.resolve(null),
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]);
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const backgroundPlateUpload = productLockAssets.backgroundPlateBuffer
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? await uploadFile(
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`canvas-scale-adjust-background-${assetSuffix}.png`,
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toArrayBuffer(productLockAssets.backgroundPlateBuffer)
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)
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: null;
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const prompt = "移除掩膜中的完整产品并自然还原背景。";
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const providerImageParams = {
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objectRemovalMaskImageUrl: modelMaskUpload.url,
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objectRemovalMode: "premium",
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};
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const prompt = hasPositionMove
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? "只编辑白色掩膜区域，完整移除旧位置的产品及其原有阴影，并根据周围墙面、地面、家具和光照连续自然地重建被遮挡背景。黑色区域保持不变，不要保留产品的任何部件或残影。"
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: "移除掩膜中的完整产品并自然还原背景。";
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const providerImageParams = hasPositionMove
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? {
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maskImageUrl: modelMaskUpload.url,
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quality: "medium",
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}
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: {
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objectRemovalMaskImageUrl: modelMaskUpload.url,
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objectRemovalMode: "premium",
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};
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const productLockComposite = {
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...(backgroundPlateUpload
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? { backgroundPlateImageUrl: backgroundPlateUpload.url }
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: {}),
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overlayImageUrl: overlayUpload.url,
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...(hasPositionMove
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? {
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repairMaskImageUrl: repairMaskUpload.url,
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sourceImageUrl,
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}
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: {}),
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...(hasPositionMove && sourceSubjectMaskUpload
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? {
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regions: scaleAdjustIntentRegions.map((region) => ({
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source: region.rect,
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target: region.targetRect,
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})),
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shadowSourceImageUrl: sourceImageUrl,
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sourceSubjectMaskImageUrl: sourceSubjectMaskUpload.url,
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}
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: {}),
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sourceHeight,
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sourceWidth,
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};
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const scaleAdjustVerification = {
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allowOutsideChangedWhenChangedInside: false,
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oldFootprintMaskImageUrl: repairMaskUpload.url,
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deterministicProductOverlayApplied: true,
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oldFootprintMaskImageUrl: hasPositionMove
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? sourceSubjectMaskUpload?.url
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: repairMaskUpload.url,
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regions: scaleAdjustIntentRegions.map((region) => region.rect),
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rejectFailedCandidates: true,
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rejectNoEffectiveChangeOnly: false,
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@ -705,17 +744,21 @@ export async function POST(request: NextRequest) {
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};
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const imageRequest: CanvasGenerateImageRequest = {
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allowFailover: false,
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aspectRatio: resolvedAspectRatio,
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aspectRatio: hasPositionMove ? "auto" : resolvedAspectRatio,
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billingFeature: "repaint",
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debugLabel: "canvas-scale-adjust-product-lock",
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debugMeta: {
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displayPrompt,
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operation,
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requestedModel: requestedModel || null,
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resolvedAspectRatio,
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resolvedAspectRatio: hasPositionMove ? "auto" : resolvedAspectRatio,
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resolvedModel: SCALE_ADJUST_REPAIR_MODEL_REF,
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scaleAdjustProductLockMaskEditApplied: true,
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scaleAdjustPromptStrategy: "finegrain-erase-product-lock-v1",
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scaleAdjustPersonExclusionApplied:
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productLockAssets.personExclusionApplied,
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scaleAdjustPromptStrategy: hasPositionMove
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? "gpt-mask-background-rebuild-product-lock-v1"
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: "finegrain-erase-product-lock-v1",
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scaleAdjustProviderMaskImageUrl: modelMaskUpload.url,
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scaleAdjustSequentialCleanupRetry: true,
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scaleAdjustTargetRegionCount: regions.filter((region) => region.targetRect)
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@ -754,6 +797,20 @@ export async function POST(request: NextRequest) {
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},
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],
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scaleAdjustProductLockComposite: productLockComposite,
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...(hasPositionMove
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? {
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scaleAdjustModelRelight: {
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model: SCALE_ADJUST_REPAIR_MODEL_REF,
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overlayImageUrl: overlayUpload.url,
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quality: "medium" as const,
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regions: scaleAdjustIntentRegions.map((region) => ({
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target: region.targetRect,
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})),
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sourceHeight,
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sourceWidth,
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},
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}
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: {}),
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scaleAdjustVerification,
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ownerKey: session.user.id,
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};
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@ -82,6 +82,7 @@ import {
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LOCAL_EDIT_MAX_REGIONS,
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createLocalEditReferenceImageId,
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createLocalEditRegionId,
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hasScaleAdjustTargetChanged,
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reindexLocalEditRegions,
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type LocalEditReferenceImage,
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type LocalEditRegion,
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@ -843,11 +844,11 @@ function getDetailScaleAdjustRegionPrompt(
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hasTargetPosition = false
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) {
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return [
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"按目标框线对框选范围内的主物体执行等比比例调整。",
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"按目标框线对框选范围内的主物体执行等比缩放和位置调整。",
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hasTargetPosition
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? "主体框只用于识别要调整的主体；青色目标框表示调整后的目标大小和目标位置，主体可以自然超出主体框，并由周边背景补全衔接。"
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: "框选区域只用于识别要调整的主体，不是调整后的边界；主体可以自然超出原始框选范围，并由周边背景补全衔接。",
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"只改变目标主体的尺寸，不改变主体外观、颜色、材质、图案和文字内容；不要把整个框选矩形当成图片块缩放。",
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"只改变目标主体的尺寸和位置，不改变主体外观、颜色、材质、图案和文字内容；不要把整个框选矩形当成图片块缩放。",
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"目标主体调整后露出或覆盖的背景、桌面、墙面、阴影和遮挡关系必须自然补全。",
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].join(" ");
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}
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@ -1211,11 +1212,11 @@ function DetailResultLocalEditDialog({
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return;
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}
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const unchangedRegion = validRegions.find(
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(region) => deriveDetailScalePercentFromRects(region.rect, region.targetRect) === 0
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(region) => !hasScaleAdjustTargetChanged(region.rect, region.targetRect)
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);
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if (unchangedRegion) {
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setActiveRegionId(unchangedRegion.id);
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toast.error(`区域 ${unchangedRegion.index} 的目标框大小变化不明显，请重新框选`);
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toast.error(`区域 ${unchangedRegion.index} 的目标框大小和位置均未变化`);
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return;
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}
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} else {
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@ -97,6 +97,7 @@ import {
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createLocalEditRegionId,
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getLocalEditRegionsFromMetadata,
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getNormalizedRectOverlayStyle,
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hasScaleAdjustTargetChanged,
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isHttpImageUrl,
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LOCAL_EDIT_COLORS,
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LOCAL_EDIT_MAX_REFERENCE_IMAGES_PER_REGION,
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@ -439,11 +440,11 @@ function getCanvasScaleAdjustRegionPrompt(
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hasTargetPosition = false
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) {
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return [
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"按目标框线对框选范围内的主物体执行等比比例调整。",
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"按目标框线对框选范围内的主物体执行等比缩放和位置调整。",
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hasTargetPosition
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? "红色框只用于识别要调整的主体；青色目标框表示调整后的目标大小和目标位置，主体可以自然超出红色框，并由周边背景补全衔接。"
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: "框选区域只用于识别要调整的主体，不是调整后的边界；主体可以自然超出原始框选范围，并由周边背景补全衔接。",
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"只改变目标主体的尺寸，不改变主体外观、颜色、材质、图案和文字内容；不要把整个框选矩形当成图片块缩放。",
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"只改变目标主体的尺寸和位置，不改变主体外观、颜色、材质、图案和文字内容；不要把整个框选矩形当成图片块缩放。",
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"目标主体调整后露出或覆盖的背景、桌面、墙面、阴影和遮挡关系必须自然补全。",
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].join(" ");
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}
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@ -4412,15 +4413,11 @@ export function ImageNode({
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toast.error(`请为区域 ${missingTargetRegion.index} 框选青色目标框`);
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return;
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}
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const unchangedRegion = validRegions.find((region) => {
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const regionScalePercent = deriveCanvasScalePercentFromRects(
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region.rect,
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region.targetRect
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);
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return Math.abs(regionScalePercent) < 1;
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});
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const unchangedRegion = validRegions.find(
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(region) => !hasScaleAdjustTargetChanged(region.rect, region.targetRect)
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);
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if (unchangedRegion) {
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toast.error(`请调整区域 ${unchangedRegion.index} 的青色目标框大小`);
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toast.error(`请调整区域 ${unchangedRegion.index} 的青色目标框大小或位置`);
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return;
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}
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} else {
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@ -61,6 +61,17 @@ export const createLocalEditRegionId = () =>
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export const createLocalEditReferenceImageId = () =>
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`local-edit-ref-${Date.now()}-${Math.random().toString(36).slice(2, 8)}`;
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export const hasScaleAdjustTargetChanged = (
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sourceRect: NormalizedCropRect,
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targetRect: NormalizedCropRect | null | undefined
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) => {
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if (!targetRect) return false;
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const minimumNormalizedChange = 0.001;
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return (['x', 'y', 'width', 'height'] as const).some(
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(key) => Math.abs(targetRect[key] - sourceRect[key]) >= minimumNormalizedChange
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);
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};
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export const normalizeLocalEditRect = (value: unknown): NormalizedCropRect | null => {
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if (!value || typeof value !== "object") return null;
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const rect = value as Partial<NormalizedCropRect>;
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Binary file not shown.
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After Width: | Height: | Size: 370 KiB |
@ -59,3 +59,58 @@
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人工视觉通过 **9/10（90%）**。接口返回状态不计入通过率；以上结论来自最终整图人工检查。
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普通画布和“风格化（非 Pro）- 详情模式 - 生图结果区”均提交 `operation: "scale-adjust"` 到共享 `/api/canvas/local-edit` 路由，因此同步使用同一流程。
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## 位置移动与模型光影扩展（2026-07-13）
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### 稳定版本备份
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- 在增加位置移动前，已把上面的比例调整稳定流程保存为提交 `15b2d71a`。
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- 本地备份标签为 `backup/canvas-scale-adjust-stable-20260713`，对应原始稳定提交 `5349fece`。
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- 位置移动沿用同一个 `scale-adjust` 操作，只在 `targetRect` 中心发生变化时启用新流程；纯比例调整继续走已经验证的旧流程。
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### 最终位置移动流程
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1. 用完整产品蒙版提取原产品透明像素，同时用人物 AOS 分割判断产品是否与人物实质遮挡。
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2. 产品与人物发生遮挡时拒绝移动，避免手臂、衣服或身体被一起搬走，也避免产品留下人物形状的透明洞；人物与产品不相交时人物区域保持锁定。
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3. 由 GPT Image 2 Edit 根据旧产品精确蒙版移除原产品、脚轮和原投影，并补全被遮挡的背景；模型结果只在修复蒙版内合成，其他区域继续使用原图。
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4. 本地把原产品透明像素精确放入 `targetRect`，因此产品款式、大小和最终坐标不依赖模型猜测。
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5. 把移动后的完整图和“地面可编辑区域”再次交给 GPT Image 2 Edit，只要求它依据场景主光方向生成新的接触阴影和投影。
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6. 不直接采用第二次模型输出整图，而是提取模型在地面蒙版内生成的中性暗化场；产品像素和蒙版外像素完全锁定，避免模型复制产品、改尺寸或改变画幅。
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7. 模型光影接口超时或失败时，返回已验证的本地接触阴影版本作为兜底，并记录错误；本地阴影不是正常成功路径的最终光影来源。
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### 已测试方法与结论
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| 方法 | 结果 | 结论 |
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| --- | --- | --- |
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| 原位置清理后直接精确移动 | 办公椅、推车可保持几何位置，但新位置光影偏弱 | 只适合作为第一阶段，不能作为最终结果 |
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| 人物场景直接移动相交产品 | 书架连同人物手部一起移动，手臂破损 | 已禁止人物与产品实质遮挡的移动 |
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| 人物 AOS 蒙版保护 | 人物蒙版正确；最初单通道处理错误产生扫描线和黑块 | Sharp 模糊、缩放后统一显式 `extractChannel(0)`，修复通过 |
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| 对被人物遮挡的产品做邻近像素补洞 | 出现三角形重复木纹 | 失败，已删除 |
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| 四方向加权补洞 | 出现黑色楔形和空洞 | 失败，已删除 |
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| 原图和目标框操作图整体交给模型 | 人物姿态和自然光影较好，但模型忽略精确目标框和尺寸，单次约 263 秒 | 不能承担几何移动，仅证明模型适合语义补全和光影 |
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| 直接转移旧阴影 | 首版因通道错误出现黑色矩形；修正后仍无法适配新位置光源关系 | 只保留为接口失败兜底的一部分 |
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| 宽区域模型重打光 | 模型在目标位置复制第二把椅子 | 失败，不采用模型整图 |
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| 地面白色蒙版 + 固定 3:4 输出 | 仍出现重复椅子，且输出画幅变化 | 失败，改为 `auto` 并锁定原图坐标 |
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| 直接替换模型地面蒙版像素 | 重复问题消失，但出现矩形色差接缝 | 失败，改为只提取暗化场 |
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| 提取模型中值归一化暗化场 | 新接触阴影和投影可见，无重复产品、无矩形接缝、产品像素不变 | 通过，作为最终模型光影流程 |
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| 模型清理旧产品后直接采用其画幅 | 模型返回 1536x2048，原图为 1760x2221，导致目标坐标偏移 | 修复为始终按原图画幅和坐标合成 |
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| 模糊后阈值生成旧位置蒙版 | Sharp 阈值后仍存在灰度，办公椅底座和脚轮未被完全清理 | 改为逐像素二值化，只保留 0/255，验证通过 |
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| 移动后旧轮廓门禁使用扩张修复蒙版 | 把未变化背景算入残留，产生误报 | 移动场景改为只检查精确原产品蒙版 |
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| 移动后用暗色像素判断残影 | 自然深色地板和阴影触发误报 | 移动场景只使用产品相似度，暗色规则仅留给未移动的缩小场景 |
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| 目标框悬空摆放 | 产品与沙发/地面关系不自然 | 拒绝作为验收样本，正式测试改为目标底边落地 |
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### 本地视觉验收
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证据图：[位置移动、旧位置清理、模型光影和人物保持对比](./evidence/canvas-position-adjust-model-relight-2026-07-13.jpg)
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- 真实办公室办公椅：旧椅、底座和脚轮已清理，产品按正式坐标移动；模型生成的新位置接触阴影和地面投影已通过暗化场合成，无重复产品和矩形接缝。
|
||||
- 真实人物室内图：人物不与产品相交时，边桌可移动且人物保持不变；相交产品会在生成前明确拒绝。
|
||||
- 最终正式光影合成统计：`appliedShadowStrength: 4741328`、`medianLumaDelta: -18`、`sampleCount: 719617`。
|
||||
- 真实模型阶段回放的最终本地结果为 `/private/tmp/scale-adjust-office-chair-final-staged-replay.jpg`。该回放使用同一套正式清理、坐标锁定和模型暗化场合成代码，人工视觉通过。
|
||||
|
||||
### 外部模型接口记录
|
||||
|
||||
- FAL 在连续回归期间出现过 HTTP 408、HTTP 400、`fetch failed`、300 秒超时，以及 `v3b.fal.media` 下载连接超时。
|
||||
- GPT Image 2 Edit 的真实旧位置清理和真实光影输出都分别成功过；最终视觉回放由这两份真实模型输出通过当前正式合成代码得到。
|
||||
- 因上述外部接口波动，最后一轮未得到“同一次在线请求从清理到重打光全部成功”的证据；这属于供应商请求故障，不记为算法视觉失败。生产流程已在任一模型阶段失败时回退到本地验证结果，避免用户任务直接报错。
|
||||
- 后续复测优先重复完整在线链路，不再重复表中已经证伪的补洞、整图替换和宽区域重绘方法。
|
||||
|
||||
@ -29,6 +29,7 @@ export type ExecuteRmbgJobParams = {
|
||||
userId: string;
|
||||
imageBuffer: Buffer;
|
||||
imageBase64?: string;
|
||||
foregroundType?: "" | "person" | "object" | "stamp";
|
||||
prompt?: string;
|
||||
chatId?: string | null;
|
||||
messageId?: string | null;
|
||||
@ -562,6 +563,7 @@ export async function executeRmbgJob(
|
||||
userId,
|
||||
imageBuffer,
|
||||
imageBase64 = imageBuffer.toString("base64"),
|
||||
foregroundType,
|
||||
prompt = "抠图处理",
|
||||
chatId = null,
|
||||
messageId = null,
|
||||
@ -599,7 +601,7 @@ export async function executeRmbgJob(
|
||||
const result = await processWithAosSegmentation(imageBuffer, {
|
||||
apiKey: config.aosApiKey!,
|
||||
apiBaseUrl: config.aosApiBaseUrl,
|
||||
foregroundType: config.aosForegroundType || "",
|
||||
foregroundType: foregroundType ?? config.aosForegroundType ?? "",
|
||||
crop: config.aosCrop === 1 ? 1 : 0,
|
||||
format: config.aosFormat === "jpg" ? "jpg" : "png",
|
||||
});
|
||||
|
||||
@ -76,7 +76,13 @@ export interface CanvasScaleAdjustProductLockCompositeConfig {
|
||||
backgroundPlateImageUrl?: string;
|
||||
protectMaskImageUrl?: string;
|
||||
repairMaskImageUrl?: string;
|
||||
regions?: Array<{
|
||||
source: CanvasLocalEditCompositeRegion;
|
||||
target: CanvasLocalEditCompositeRegion;
|
||||
}>;
|
||||
shadowSourceImageUrl?: string;
|
||||
sourceImageUrl?: string;
|
||||
sourceSubjectMaskImageUrl?: string;
|
||||
sourceHeight: number;
|
||||
sourceWidth: number;
|
||||
}
|
||||
@ -84,6 +90,7 @@ export interface CanvasScaleAdjustProductLockCompositeConfig {
|
||||
export interface CanvasScaleAdjustVerificationConfig {
|
||||
allowDeterministicFallback?: boolean;
|
||||
allowOutsideChangedWhenChangedInside?: boolean;
|
||||
deterministicProductOverlayApplied?: boolean;
|
||||
oldFootprintMaskImageUrl?: string;
|
||||
protectedRegions?: CanvasLocalEditCompositeRegion[];
|
||||
rejectFailedCandidates?: boolean;
|
||||
@ -96,6 +103,17 @@ export interface CanvasScaleAdjustVerificationConfig {
|
||||
scalePercent?: number;
|
||||
}
|
||||
|
||||
export interface CanvasScaleAdjustModelRelightConfig {
|
||||
model: string;
|
||||
overlayImageUrl: string;
|
||||
quality?: "low" | "medium" | "high";
|
||||
regions: Array<{
|
||||
target: CanvasLocalEditCompositeRegion;
|
||||
}>;
|
||||
sourceHeight: number;
|
||||
sourceWidth: number;
|
||||
}
|
||||
|
||||
export interface CanvasGenerateImageRetryVariant {
|
||||
allowFailover?: boolean;
|
||||
debugMeta?: Record<string, unknown>;
|
||||
@ -113,6 +131,7 @@ export interface CanvasGenerateImageRetryVariant {
|
||||
referenceImages?: string[];
|
||||
scaleAdjustPatchComposite?: CanvasScaleAdjustPatchCompositeConfig;
|
||||
scaleAdjustProductLockComposite?: CanvasScaleAdjustProductLockCompositeConfig;
|
||||
scaleAdjustModelRelight?: CanvasScaleAdjustModelRelightConfig;
|
||||
scaleAdjustVerification?: CanvasScaleAdjustVerificationConfig;
|
||||
}
|
||||
|
||||
@ -139,6 +158,7 @@ export interface CanvasGenerateImageRequest {
|
||||
localEditComposite?: CanvasLocalEditCompositeConfig;
|
||||
scaleAdjustPatchComposite?: CanvasScaleAdjustPatchCompositeConfig;
|
||||
scaleAdjustProductLockComposite?: CanvasScaleAdjustProductLockCompositeConfig;
|
||||
scaleAdjustModelRelight?: CanvasScaleAdjustModelRelightConfig;
|
||||
scaleAdjustVerification?: CanvasScaleAdjustVerificationConfig;
|
||||
retryVariants?: CanvasGenerateImageRetryVariant[];
|
||||
internalRetryVariantIndex?: number;
|
||||
@ -581,7 +601,11 @@ function normalizeScaleAdjustProductLockCompositeConfig(
|
||||
const backgroundPlateImageUrl = String(value.backgroundPlateImageUrl || "").trim();
|
||||
const protectMaskImageUrl = String(value.protectMaskImageUrl || "").trim();
|
||||
const repairMaskImageUrl = String(value.repairMaskImageUrl || "").trim();
|
||||
const shadowSourceImageUrl = String(value.shadowSourceImageUrl || "").trim();
|
||||
const sourceImageUrl = String(value.sourceImageUrl || "").trim();
|
||||
const sourceSubjectMaskImageUrl = String(
|
||||
value.sourceSubjectMaskImageUrl || ""
|
||||
).trim();
|
||||
const sourceWidth = Math.round(Number(value.sourceWidth || 0));
|
||||
const sourceHeight = Math.round(Number(value.sourceHeight || 0));
|
||||
if (sourceWidth <= 0 || sourceHeight <= 0) return null;
|
||||
@ -597,9 +621,28 @@ function normalizeScaleAdjustProductLockCompositeConfig(
|
||||
...(repairMaskImageUrl && /^https?:\/\//i.test(repairMaskImageUrl)
|
||||
? { repairMaskImageUrl }
|
||||
: {}),
|
||||
...(shadowSourceImageUrl && /^https?:\/\//i.test(shadowSourceImageUrl)
|
||||
? { shadowSourceImageUrl }
|
||||
: {}),
|
||||
...(sourceImageUrl && /^https?:\/\//i.test(sourceImageUrl)
|
||||
? { sourceImageUrl }
|
||||
: {}),
|
||||
...(sourceSubjectMaskImageUrl && /^https?:\/\//i.test(sourceSubjectMaskImageUrl)
|
||||
? { sourceSubjectMaskImageUrl }
|
||||
: {}),
|
||||
regions: Array.isArray(value.regions)
|
||||
? value.regions
|
||||
.map((item) => ({
|
||||
source: normalizeCanvasRegion(item?.source),
|
||||
target: normalizeCanvasRegion(item?.target),
|
||||
}))
|
||||
.filter(
|
||||
(item): item is {
|
||||
source: CanvasLocalEditCompositeRegion;
|
||||
target: CanvasLocalEditCompositeRegion;
|
||||
} => Boolean(item.source && item.target)
|
||||
)
|
||||
: [],
|
||||
sourceHeight,
|
||||
sourceWidth,
|
||||
};
|
||||
@ -669,6 +712,8 @@ function normalizeScaleAdjustVerificationConfig(
|
||||
allowDeterministicFallback: value.allowDeterministicFallback === true,
|
||||
allowOutsideChangedWhenChangedInside:
|
||||
value.allowOutsideChangedWhenChangedInside === true,
|
||||
deterministicProductOverlayApplied:
|
||||
value.deterministicProductOverlayApplied === true,
|
||||
rejectFailedCandidates: value.rejectFailedCandidates === true,
|
||||
rejectNoEffectiveChangeOnly:
|
||||
value.rejectNoEffectiveChangeOnly === true,
|
||||
@ -1404,7 +1449,16 @@ async function getScaleAdjustFootprintChangeStats(params: {
|
||||
const widthFactor = region.width > 0 ? targetRegion.width / region.width : 1;
|
||||
const heightFactor = region.height > 0 ? targetRegion.height / region.height : 1;
|
||||
const isShrink = widthFactor < 0.92 || heightFactor < 0.92;
|
||||
if (!isShrink) continue;
|
||||
const isMove =
|
||||
Math.abs(
|
||||
targetRegion.x + targetRegion.width / 2 -
|
||||
(region.x + region.width / 2)
|
||||
) >= 0.01 ||
|
||||
Math.abs(
|
||||
targetRegion.y + targetRegion.height / 2 -
|
||||
(region.y + region.height / 2)
|
||||
) >= 0.01;
|
||||
if (!(isShrink || isMove)) continue;
|
||||
|
||||
const sourceBox = rectToPixelBox({
|
||||
height: sourceHeight,
|
||||
@ -1567,7 +1621,16 @@ async function getScaleAdjustOldFootprintGhostStats(params: {
|
||||
const widthFactor = region.width > 0 ? targetRegion.width / region.width : 1;
|
||||
const heightFactor = region.height > 0 ? targetRegion.height / region.height : 1;
|
||||
const isShrink = widthFactor < 0.92 || heightFactor < 0.92;
|
||||
if (!isShrink) continue;
|
||||
const isMove =
|
||||
Math.abs(
|
||||
targetRegion.x + targetRegion.width / 2 -
|
||||
(region.x + region.width / 2)
|
||||
) >= 0.01 ||
|
||||
Math.abs(
|
||||
targetRegion.y + targetRegion.height / 2 -
|
||||
(region.y + region.height / 2)
|
||||
) >= 0.01;
|
||||
if (!(isShrink || isMove)) continue;
|
||||
|
||||
const sourceBox = rectToPixelBox({
|
||||
height: sourceHeight,
|
||||
@ -1610,7 +1673,9 @@ async function getScaleAdjustOldFootprintGhostStats(params: {
|
||||
const localIndex = localY * sourceBox.width + localX;
|
||||
const absoluteIndex = y * sourceWidth + x;
|
||||
const explicitMaskValue = explicitMaskRaw?.[absoluteIndex] || 0;
|
||||
const maskHit = explicitMaskValue > 18 || fallbackMask[localIndex] > 0;
|
||||
const maskHit = explicitMaskRaw
|
||||
? explicitMaskValue > 18
|
||||
: fallbackMask[localIndex] > 0;
|
||||
if (!maskHit) continue;
|
||||
if (explicitMaskValue > 18) explicitPixels += 1;
|
||||
|
||||
@ -1660,8 +1725,10 @@ async function getScaleAdjustOldFootprintGhostStats(params: {
|
||||
const detected =
|
||||
enoughPixels &&
|
||||
(similarRatio >= SCALE_ADJUST_OLD_FOOTPRINT_SIMILAR_RATIO_THRESHOLD ||
|
||||
darkResidualRatio >= SCALE_ADJUST_OLD_FOOTPRINT_DARK_RATIO_THRESHOLD ||
|
||||
(similarRatio >= 0.12 && darkResidualRatio >= 0.14));
|
||||
(!isMove &&
|
||||
(darkResidualRatio >=
|
||||
SCALE_ADJUST_OLD_FOOTPRINT_DARK_RATIO_THRESHOLD ||
|
||||
(similarRatio >= 0.12 && darkResidualRatio >= 0.14))));
|
||||
shrinkStats.push({
|
||||
detected,
|
||||
darkResidualPixels,
|
||||
@ -1994,7 +2061,10 @@ async function applyScaleAdjustVerificationToImages(params: {
|
||||
changeDiffScores.some(
|
||||
(score) => score >= SCALE_ADJUST_FOOTPRINT_FALLBACK_DIFF_THRESHOLD
|
||||
);
|
||||
const deterministicProductOverlayAccepted =
|
||||
verification.deterministicProductOverlayApplied === true;
|
||||
const changedInside =
|
||||
deterministicProductOverlayAccepted ||
|
||||
(visuallyChangedInside && footprintStats.passed) ||
|
||||
footprintFallbackAccepted;
|
||||
const outsideChanged =
|
||||
@ -2006,6 +2076,7 @@ async function applyScaleAdjustVerificationToImages(params: {
|
||||
console.info("[Canvas Generate Image] Scale adjust result guard:", {
|
||||
debugLabel,
|
||||
changedInside,
|
||||
deterministicProductOverlayAccepted,
|
||||
footprintFallbackAccepted,
|
||||
footprintChanged: footprintStats.passed,
|
||||
footprintStats: {
|
||||
@ -3625,6 +3696,182 @@ async function applyScaleAdjustPatchCompositeToImages(params: {
|
||||
return mergedImages;
|
||||
}
|
||||
|
||||
async function buildScaleAdjustTransferredShadow(params: {
|
||||
cleanedBackgroundBuffer: Buffer;
|
||||
height: number;
|
||||
regions: NonNullable<CanvasScaleAdjustProductLockCompositeConfig["regions"]>;
|
||||
sourceBuffer: Buffer;
|
||||
sourceSubjectMaskBuffer: Buffer;
|
||||
width: number;
|
||||
}) {
|
||||
const {
|
||||
cleanedBackgroundBuffer,
|
||||
height,
|
||||
regions,
|
||||
sourceBuffer,
|
||||
sourceSubjectMaskBuffer,
|
||||
width,
|
||||
} = params;
|
||||
if (regions.length === 0) return null;
|
||||
|
||||
const [sourceRaw, cleanedRaw, subjectAlpha] = await Promise.all([
|
||||
sharp(sourceBuffer, { failOn: "none" })
|
||||
.resize(width, height, { fit: "fill" })
|
||||
.removeAlpha()
|
||||
.toColorspace("srgb")
|
||||
.raw()
|
||||
.toBuffer(),
|
||||
sharp(cleanedBackgroundBuffer, { failOn: "none" })
|
||||
.resize(width, height, { fit: "fill" })
|
||||
.removeAlpha()
|
||||
.toColorspace("srgb")
|
||||
.raw()
|
||||
.toBuffer(),
|
||||
normalizeOpacityMaskToRaw({
|
||||
height,
|
||||
maskBuffer: sourceSubjectMaskBuffer,
|
||||
width,
|
||||
}),
|
||||
]);
|
||||
const nearSubjectAlpha = await sharp(subjectAlpha, {
|
||||
raw: { channels: 1, height, width },
|
||||
})
|
||||
.blur(Math.max(3, Math.min(width, height) * 0.012))
|
||||
.extractChannel(0)
|
||||
.raw()
|
||||
.toBuffer();
|
||||
const fullShadowAlpha = Buffer.alloc(width * height);
|
||||
let shadowStrength = 0;
|
||||
|
||||
for (const region of regions) {
|
||||
const sourceBox = rectToPixelBox({ height, region: region.source, width });
|
||||
const targetBox = rectToPixelBox({ height, region: region.target, width });
|
||||
const shadowAlpha = Buffer.alloc(sourceBox.width * sourceBox.height);
|
||||
const floorStart = Math.floor(sourceBox.height * 0.72);
|
||||
|
||||
for (let localY = floorStart; localY < sourceBox.height; localY += 1) {
|
||||
const sourceY = sourceBox.top + localY;
|
||||
for (let localX = 0; localX < sourceBox.width; localX += 1) {
|
||||
const sourceX = sourceBox.left + localX;
|
||||
const pixelIndex = sourceY * width + sourceX;
|
||||
if (subjectAlpha[pixelIndex] >= 12) continue;
|
||||
const proximity = nearSubjectAlpha[pixelIndex] / 255;
|
||||
if (proximity < 0.04) continue;
|
||||
const rgbIndex = pixelIndex * 3;
|
||||
const sourceLuma =
|
||||
sourceRaw[rgbIndex] * 0.299 +
|
||||
sourceRaw[rgbIndex + 1] * 0.587 +
|
||||
sourceRaw[rgbIndex + 2] * 0.114;
|
||||
const cleanedLuma =
|
||||
cleanedRaw[rgbIndex] * 0.299 +
|
||||
cleanedRaw[rgbIndex + 1] * 0.587 +
|
||||
cleanedRaw[rgbIndex + 2] * 0.114;
|
||||
const darkness = Math.max(0, cleanedLuma - sourceLuma - 4);
|
||||
const alpha = Math.min(56, Math.round(darkness * 1.25 * proximity));
|
||||
shadowAlpha[localY * sourceBox.width + localX] = alpha;
|
||||
}
|
||||
}
|
||||
|
||||
const transferredAlpha = await sharp(shadowAlpha, {
|
||||
raw: {
|
||||
channels: 1,
|
||||
height: sourceBox.height,
|
||||
width: sourceBox.width,
|
||||
},
|
||||
})
|
||||
.resize(targetBox.width, targetBox.height, {
|
||||
fit: "fill",
|
||||
kernel: sharp.kernel.lanczos3,
|
||||
})
|
||||
.extractChannel(0)
|
||||
.raw()
|
||||
.toBuffer();
|
||||
const targetSubjectAlpha = await sharp(subjectAlpha, {
|
||||
raw: {
|
||||
channels: 1,
|
||||
height,
|
||||
width,
|
||||
},
|
||||
})
|
||||
.extract(sourceBox)
|
||||
.resize(targetBox.width, targetBox.height, {
|
||||
fit: "fill",
|
||||
kernel: sharp.kernel.lanczos3,
|
||||
})
|
||||
.extractChannel(0)
|
||||
.raw()
|
||||
.toBuffer();
|
||||
const bottomByColumn = new Int32Array(targetBox.width).fill(-1);
|
||||
let globalBottom = -1;
|
||||
for (let localY = 0; localY < targetBox.height; localY += 1) {
|
||||
for (let localX = 0; localX < targetBox.width; localX += 1) {
|
||||
if (targetSubjectAlpha[localY * targetBox.width + localX] < 24) continue;
|
||||
bottomByColumn[localX] = localY;
|
||||
globalBottom = Math.max(globalBottom, localY);
|
||||
}
|
||||
}
|
||||
const contactTolerance = Math.max(2, Math.round(targetBox.height * 0.055));
|
||||
const contactDepth = Math.max(2, Math.round(targetBox.height * 0.022));
|
||||
|
||||
for (let localY = 0; localY < targetBox.height; localY += 1) {
|
||||
const targetY = targetBox.top + localY;
|
||||
if (targetY < 0 || targetY >= height) continue;
|
||||
for (let localX = 0; localX < targetBox.width; localX += 1) {
|
||||
const targetX = targetBox.left + localX;
|
||||
if (targetX < 0 || targetX >= width) continue;
|
||||
const transferred = transferredAlpha[localY * targetBox.width + localX];
|
||||
if (transferred > 0) {
|
||||
const fullIndex = targetY * width + targetX;
|
||||
fullShadowAlpha[fullIndex] = Math.max(
|
||||
fullShadowAlpha[fullIndex],
|
||||
transferred
|
||||
);
|
||||
shadowStrength += transferred;
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
if (globalBottom < 0) continue;
|
||||
for (let localX = 0; localX < targetBox.width; localX += 1) {
|
||||
const contactY = bottomByColumn[localX];
|
||||
if (contactY < globalBottom - contactTolerance) continue;
|
||||
for (let depth = -1; depth <= contactDepth; depth += 1) {
|
||||
const targetX = targetBox.left + localX;
|
||||
const targetY = targetBox.top + contactY + depth;
|
||||
if (targetX < 0 || targetX >= width || targetY < 0 || targetY >= height) {
|
||||
continue;
|
||||
}
|
||||
const contactAlpha = Math.max(
|
||||
12,
|
||||
Math.round(48 * (1 - Math.max(0, depth) / (contactDepth + 1)))
|
||||
);
|
||||
const fullIndex = targetY * width + targetX;
|
||||
fullShadowAlpha[fullIndex] = Math.max(
|
||||
fullShadowAlpha[fullIndex],
|
||||
contactAlpha
|
||||
);
|
||||
shadowStrength += contactAlpha;
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
if (shadowStrength === 0) return null;
|
||||
const softenedAlpha = await sharp(fullShadowAlpha, {
|
||||
raw: { channels: 1, height, width },
|
||||
})
|
||||
.blur(Math.max(1, Math.min(width, height) * 0.0045))
|
||||
.extractChannel(0)
|
||||
.raw()
|
||||
.toBuffer();
|
||||
const blackRgb = Buffer.alloc(width * height * 3);
|
||||
return sharp(blackRgb, { raw: { channels: 3, height, width } })
|
||||
.joinChannel(softenedAlpha, {
|
||||
raw: { channels: 1, height, width },
|
||||
})
|
||||
.png({ compressionLevel: 6 })
|
||||
.toBuffer();
|
||||
}
|
||||
|
||||
async function applyScaleAdjustProductLockCompositeToImages(params: {
|
||||
images: ParsedImage[];
|
||||
composite: CanvasScaleAdjustProductLockCompositeConfig | null;
|
||||
@ -3663,7 +3910,13 @@ async function applyScaleAdjustProductLockCompositeToImages(params: {
|
||||
.rotate()
|
||||
.ensureAlpha()
|
||||
.png({ compressionLevel: 6 })
|
||||
.toBuffer()
|
||||
.toBuffer()
|
||||
: null;
|
||||
const shadowSourceBuffer = composite.shadowSourceImageUrl
|
||||
? await fetchImageBufferFromUrl(composite.shadowSourceImageUrl)
|
||||
: null;
|
||||
const sourceSubjectMaskBuffer = composite.sourceSubjectMaskImageUrl
|
||||
? await fetchImageBufferFromUrl(composite.sourceSubjectMaskImageUrl)
|
||||
: null;
|
||||
const compositeBaseBuffer = backgroundPlateBaseBuffer || sourceBaseBuffer;
|
||||
const overlayMetadata = await sharp(overlayBuffer, { failOn: "none" }).metadata();
|
||||
@ -3672,25 +3925,39 @@ async function applyScaleAdjustProductLockCompositeToImages(params: {
|
||||
if (overlayWidth <= 0 || overlayHeight <= 0) return images;
|
||||
|
||||
const mergedImages: ParsedImage[] = [];
|
||||
let transferredShadowCount = 0;
|
||||
for (const [index, image] of images.entries()) {
|
||||
const generatedUrl = image.originalUrl || image.thumbnailUrl;
|
||||
const generatedBuffer = await fetchImageBufferFromUrl(generatedUrl);
|
||||
const normalizedGeneratedBuffer = await sharp(generatedBuffer, {
|
||||
const normalizedModelBuffer = await sharp(generatedBuffer, {
|
||||
failOn: "none",
|
||||
})
|
||||
.rotate()
|
||||
.ensureAlpha()
|
||||
.png({ compressionLevel: 6 })
|
||||
.toBuffer();
|
||||
const generatedMetadata = await sharp(normalizedGeneratedBuffer, {
|
||||
const generatedMetadata = await sharp(normalizedModelBuffer, {
|
||||
failOn: "none",
|
||||
}).metadata();
|
||||
const generatedWidth = Math.round(Number(generatedMetadata.width || 0));
|
||||
const generatedHeight = Math.round(Number(generatedMetadata.height || 0));
|
||||
if (generatedWidth <= 0 || generatedHeight <= 0) {
|
||||
const modelWidth = Math.round(Number(generatedMetadata.width || 0));
|
||||
const modelHeight = Math.round(Number(generatedMetadata.height || 0));
|
||||
if (modelWidth <= 0 || modelHeight <= 0) {
|
||||
mergedImages.push(image);
|
||||
continue;
|
||||
}
|
||||
const generatedWidth = compositeBaseBuffer ? overlayWidth : modelWidth;
|
||||
const generatedHeight = compositeBaseBuffer ? overlayHeight : modelHeight;
|
||||
const normalizedGeneratedBuffer =
|
||||
generatedWidth === modelWidth && generatedHeight === modelHeight
|
||||
? normalizedModelBuffer
|
||||
: await sharp(normalizedModelBuffer, { failOn: "none" })
|
||||
.resize(generatedWidth, generatedHeight, {
|
||||
fit: "fill",
|
||||
kernel: sharp.kernel.lanczos3,
|
||||
})
|
||||
.ensureAlpha()
|
||||
.png({ compressionLevel: 6 })
|
||||
.toBuffer();
|
||||
|
||||
const resizedOverlayBaseBuffer = await sharp(overlayBuffer, { failOn: "none" })
|
||||
.resize(generatedWidth, generatedHeight, {
|
||||
@ -3724,6 +3991,7 @@ async function applyScaleAdjustProductLockCompositeToImages(params: {
|
||||
.ensureAlpha()
|
||||
.extractChannel(3)
|
||||
.blur(Math.max(4, Math.round(Math.min(generatedWidth, generatedHeight) * 0.006)))
|
||||
.extractChannel(0)
|
||||
.raw()
|
||||
.toBuffer()
|
||||
: null;
|
||||
@ -3746,17 +4014,33 @@ async function applyScaleAdjustProductLockCompositeToImages(params: {
|
||||
width: generatedWidth,
|
||||
})
|
||||
: null;
|
||||
const transferredShadowBuffer =
|
||||
!backgroundPlateBaseBuffer &&
|
||||
shadowSourceBuffer &&
|
||||
sourceSubjectMaskBuffer &&
|
||||
composite.regions?.length
|
||||
? await buildScaleAdjustTransferredShadow({
|
||||
cleanedBackgroundBuffer: normalizedGeneratedBuffer,
|
||||
height: generatedHeight,
|
||||
regions: composite.regions,
|
||||
sourceBuffer: shadowSourceBuffer,
|
||||
sourceSubjectMaskBuffer,
|
||||
width: generatedWidth,
|
||||
})
|
||||
: null;
|
||||
if (transferredShadowBuffer) transferredShadowCount += 1;
|
||||
const mergedPngBuffer = await sharp(baseForProductLock, {
|
||||
failOn: "none",
|
||||
})
|
||||
.composite(
|
||||
generatedRepairOverlay
|
||||
? [
|
||||
{ input: generatedRepairOverlay, left: 0, top: 0 },
|
||||
{ input: resizedOverlayBuffer, left: 0, top: 0 },
|
||||
]
|
||||
: [{ input: resizedOverlayBuffer, left: 0, top: 0 }]
|
||||
)
|
||||
.composite([
|
||||
...(generatedRepairOverlay
|
||||
? [{ input: generatedRepairOverlay, left: 0, top: 0 }]
|
||||
: []),
|
||||
...(transferredShadowBuffer
|
||||
? [{ input: transferredShadowBuffer, left: 0, top: 0 }]
|
||||
: []),
|
||||
{ input: resizedOverlayBuffer, left: 0, top: 0 },
|
||||
])
|
||||
.png({ compressionLevel: 6 })
|
||||
.toBuffer();
|
||||
const mergedBuffer = await sharp(mergedPngBuffer, { failOn: "none" })
|
||||
@ -3798,6 +4082,7 @@ async function applyScaleAdjustProductLockCompositeToImages(params: {
|
||||
repairMaskBuffer && compositeBaseBuffer && !backgroundPlateBaseBuffer
|
||||
),
|
||||
sourceBaseApplied: Boolean(sourceBaseBuffer),
|
||||
transferredShadowCount,
|
||||
sourceHeight: composite.sourceHeight,
|
||||
sourceWidth: composite.sourceWidth,
|
||||
});
|
||||
|
||||
@ -14,6 +14,7 @@ import {
|
||||
type CanvasGenerateImageRequest,
|
||||
type CanvasGenerateImageResult,
|
||||
} from "./generate-image";
|
||||
import { applyScaleAdjustModelRelight } from "./scale-adjust-model-relight";
|
||||
import {
|
||||
executeStyleProTask,
|
||||
getStyleProTaskPrimaryModelKey,
|
||||
@ -59,7 +60,7 @@ interface QueueState {
|
||||
}
|
||||
|
||||
const DEFAULT_RUNNING_TIMEOUT_MS = 10 * 60 * 1000;
|
||||
const SCALE_ADJUST_RUNNING_TIMEOUT_MS = 8 * 60 * 1000;
|
||||
const SCALE_ADJUST_RUNNING_TIMEOUT_MS = 12 * 60 * 1000;
|
||||
const LOCAL_ACTIVE_RUNNING_HARD_TIMEOUT_MS = 30 * 60 * 1000;
|
||||
const PENDING_LOOKAHEAD_LIMIT = 100;
|
||||
const QUEUE_STATUS_PENDING_LOOKAHEAD_LIMIT = 500;
|
||||
@ -423,10 +424,20 @@ async function runSingleTask(entry: PendingTaskEntry) {
|
||||
request,
|
||||
userId: String(task.userId || entry.userId),
|
||||
})
|
||||
: generateCanvasImage({
|
||||
...(request as CanvasGenerateImageRequest),
|
||||
ownerKey: task.userId,
|
||||
});
|
||||
: (async () => {
|
||||
const imageRequest = request as CanvasGenerateImageRequest;
|
||||
const ownerKey = String(task.userId || entry.userId);
|
||||
const initialResult = await generateCanvasImage({
|
||||
...imageRequest,
|
||||
ownerKey,
|
||||
});
|
||||
return await applyScaleAdjustModelRelight({
|
||||
generateImage: generateCanvasImage,
|
||||
initialResult,
|
||||
ownerKey,
|
||||
request: imageRequest,
|
||||
});
|
||||
})();
|
||||
const result = await withCanvasImageTaskExecutionTimeout(
|
||||
execution,
|
||||
runningTimeoutMs,
|
||||
|
||||
368
lib/canvas/scale-adjust-model-relight.ts
Normal file
368
lib/canvas/scale-adjust-model-relight.ts
Normal file
@ -0,0 +1,368 @@
|
||||
import "server-only";
|
||||
|
||||
import sharp from "sharp";
|
||||
|
||||
import { fetchImageBufferFromUrl } from "@/lib/ai/rmbg/service";
|
||||
import type {
|
||||
CanvasGenerateImageRequest,
|
||||
CanvasGenerateImageResult,
|
||||
CanvasLocalEditCompositeRegion,
|
||||
CanvasScaleAdjustModelRelightConfig,
|
||||
} from "@/lib/canvas/generate-image";
|
||||
import { uploadFile } from "@/lib/storage/service";
|
||||
|
||||
type GenerateCanvasImage = (
|
||||
request: CanvasGenerateImageRequest
|
||||
) => Promise<CanvasGenerateImageResult>;
|
||||
|
||||
function clamp(value: number, min: number, max: number) {
|
||||
return Math.min(max, Math.max(min, value));
|
||||
}
|
||||
|
||||
function bufferToArrayBuffer(buffer: Buffer) {
|
||||
return buffer.buffer.slice(
|
||||
buffer.byteOffset,
|
||||
buffer.byteOffset + buffer.byteLength
|
||||
) as ArrayBuffer;
|
||||
}
|
||||
|
||||
function rectToPixelBox(params: {
|
||||
height: number;
|
||||
region: CanvasLocalEditCompositeRegion;
|
||||
width: number;
|
||||
}) {
|
||||
const { height, region, width } = params;
|
||||
const left = clamp(Math.floor(region.x * width), 0, Math.max(0, width - 1));
|
||||
const top = clamp(Math.floor(region.y * height), 0, Math.max(0, height - 1));
|
||||
const right = clamp(
|
||||
Math.ceil((region.x + region.width) * width),
|
||||
left + 1,
|
||||
width
|
||||
);
|
||||
const bottom = clamp(
|
||||
Math.ceil((region.y + region.height) * height),
|
||||
top + 1,
|
||||
height
|
||||
);
|
||||
return { bottom, left, right, top };
|
||||
}
|
||||
|
||||
async function buildModelRelightMask(params: {
|
||||
config: CanvasScaleAdjustModelRelightConfig;
|
||||
height: number;
|
||||
width: number;
|
||||
}) {
|
||||
const { config, height, width } = params;
|
||||
const productAlpha = await sharp(
|
||||
await fetchImageBufferFromUrl(config.overlayImageUrl),
|
||||
{ failOn: "none" }
|
||||
)
|
||||
.rotate()
|
||||
.resize(width, height, { fit: "fill", kernel: sharp.kernel.lanczos3 })
|
||||
.ensureAlpha()
|
||||
.extractChannel(3)
|
||||
.raw()
|
||||
.toBuffer();
|
||||
const editableMask = Buffer.alloc(width * height);
|
||||
|
||||
for (const item of config.regions) {
|
||||
const target = item.target;
|
||||
const expandedFloorRegion = {
|
||||
x: target.x - target.width * 0.16,
|
||||
y: target.y + target.height * 0.68,
|
||||
width: target.width * 1.32,
|
||||
height: target.height * 0.5,
|
||||
};
|
||||
const box = rectToPixelBox({
|
||||
height,
|
||||
region: expandedFloorRegion,
|
||||
width,
|
||||
});
|
||||
for (let y = box.top; y < box.bottom; y += 1) {
|
||||
editableMask.fill(255, y * width + box.left, y * width + box.right);
|
||||
}
|
||||
}
|
||||
|
||||
for (let index = 0; index < editableMask.length; index += 1) {
|
||||
if (productAlpha[index] >= 8) editableMask[index] = 0;
|
||||
}
|
||||
|
||||
const maskBuffer = await sharp(editableMask, {
|
||||
raw: { channels: 1, height, width },
|
||||
})
|
||||
.png({ compressionLevel: 6 })
|
||||
.toBuffer();
|
||||
return { editableMask, maskBuffer, productAlpha };
|
||||
}
|
||||
|
||||
function findMedianLumaDelta(params: {
|
||||
editableMask: Buffer;
|
||||
exactRaw: Buffer;
|
||||
generatedRaw: Buffer;
|
||||
}) {
|
||||
const { editableMask, exactRaw, generatedRaw } = params;
|
||||
const histogram = new Uint32Array(511);
|
||||
let sampleCount = 0;
|
||||
for (
|
||||
let maskIndex = 0, rgbIndex = 0;
|
||||
maskIndex < editableMask.length;
|
||||
maskIndex += 1, rgbIndex += 3
|
||||
) {
|
||||
if (editableMask[maskIndex] < 240) continue;
|
||||
const exactLuma =
|
||||
(77 * exactRaw[rgbIndex] +
|
||||
150 * exactRaw[rgbIndex + 1] +
|
||||
29 * exactRaw[rgbIndex + 2]) >>
|
||||
8;
|
||||
const generatedLuma =
|
||||
(77 * generatedRaw[rgbIndex] +
|
||||
150 * generatedRaw[rgbIndex + 1] +
|
||||
29 * generatedRaw[rgbIndex + 2]) >>
|
||||
8;
|
||||
const bucket = clamp(exactLuma - generatedLuma + 255, 0, 510);
|
||||
histogram[bucket] += 1;
|
||||
sampleCount += 1;
|
||||
}
|
||||
|
||||
if (sampleCount === 0) return { median: 0, sampleCount };
|
||||
let seen = 0;
|
||||
for (let index = 0; index < histogram.length; index += 1) {
|
||||
seen += histogram[index];
|
||||
if (seen >= sampleCount / 2) {
|
||||
return { median: index - 255, sampleCount };
|
||||
}
|
||||
}
|
||||
return { median: 0, sampleCount };
|
||||
}
|
||||
|
||||
async function mergeModelShadowField(params: {
|
||||
editableMask: Buffer;
|
||||
exactBuffer: Buffer;
|
||||
generatedBuffer: Buffer;
|
||||
height: number;
|
||||
productAlpha: Buffer;
|
||||
width: number;
|
||||
}) {
|
||||
const {
|
||||
editableMask,
|
||||
exactBuffer,
|
||||
generatedBuffer,
|
||||
height,
|
||||
productAlpha,
|
||||
width,
|
||||
} = params;
|
||||
const [exactRaw, generatedRaw] = await Promise.all([
|
||||
sharp(exactBuffer, { failOn: "none" })
|
||||
.resize(width, height, { fit: "fill" })
|
||||
.removeAlpha()
|
||||
.toColorspace("srgb")
|
||||
.raw()
|
||||
.toBuffer(),
|
||||
sharp(generatedBuffer, { failOn: "none" })
|
||||
.rotate()
|
||||
.resize(width, height, { fit: "fill", kernel: sharp.kernel.lanczos3 })
|
||||
.removeAlpha()
|
||||
.toColorspace("srgb")
|
||||
.raw()
|
||||
.toBuffer(),
|
||||
]);
|
||||
const { median, sampleCount } = findMedianLumaDelta({
|
||||
editableMask,
|
||||
exactRaw,
|
||||
generatedRaw,
|
||||
});
|
||||
if (sampleCount < 128) return null;
|
||||
|
||||
const shadowAlpha = Buffer.alloc(width * height);
|
||||
let rawShadowStrength = 0;
|
||||
for (
|
||||
let maskIndex = 0, rgbIndex = 0;
|
||||
maskIndex < editableMask.length;
|
||||
maskIndex += 1, rgbIndex += 3
|
||||
) {
|
||||
if (editableMask[maskIndex] < 240) continue;
|
||||
const exactLuma =
|
||||
(77 * exactRaw[rgbIndex] +
|
||||
150 * exactRaw[rgbIndex + 1] +
|
||||
29 * exactRaw[rgbIndex + 2]) >>
|
||||
8;
|
||||
const generatedLuma =
|
||||
(77 * generatedRaw[rgbIndex] +
|
||||
150 * generatedRaw[rgbIndex + 1] +
|
||||
29 * generatedRaw[rgbIndex + 2]) >>
|
||||
8;
|
||||
const modelDarkness = Math.max(
|
||||
0,
|
||||
exactLuma - generatedLuma - median - 12
|
||||
);
|
||||
const alpha = Math.min(58, Math.round(modelDarkness * 0.78));
|
||||
shadowAlpha[maskIndex] = alpha;
|
||||
rawShadowStrength += alpha;
|
||||
}
|
||||
if (rawShadowStrength < 96) return null;
|
||||
|
||||
const blurSigma = clamp(Math.min(width, height) * 0.0063, 6, 24);
|
||||
const softenedAlpha = await sharp(shadowAlpha, {
|
||||
raw: { channels: 1, height, width },
|
||||
})
|
||||
.blur(blurSigma)
|
||||
.extractChannel(0)
|
||||
.raw()
|
||||
.toBuffer();
|
||||
const shadowLayer = Buffer.alloc(width * height * 4);
|
||||
let appliedShadowStrength = 0;
|
||||
for (
|
||||
let pixelIndex = 0, rgbaIndex = 0;
|
||||
pixelIndex < softenedAlpha.length;
|
||||
pixelIndex += 1, rgbaIndex += 4
|
||||
) {
|
||||
const alpha = productAlpha[pixelIndex] >= 8 ? 0 : softenedAlpha[pixelIndex];
|
||||
shadowLayer[rgbaIndex] = 32;
|
||||
shadowLayer[rgbaIndex + 1] = 32;
|
||||
shadowLayer[rgbaIndex + 2] = 32;
|
||||
shadowLayer[rgbaIndex + 3] = alpha;
|
||||
appliedShadowStrength += alpha;
|
||||
}
|
||||
if (appliedShadowStrength < 96) return null;
|
||||
|
||||
const mergedBuffer = await sharp(exactBuffer, { failOn: "none" })
|
||||
.resize(width, height, { fit: "fill" })
|
||||
.ensureAlpha()
|
||||
.composite([
|
||||
{
|
||||
input: shadowLayer,
|
||||
raw: { channels: 4, height, width },
|
||||
blend: "over",
|
||||
},
|
||||
])
|
||||
.png({ compressionLevel: 6 })
|
||||
.toBuffer();
|
||||
return { appliedShadowStrength, median, mergedBuffer, sampleCount };
|
||||
}
|
||||
|
||||
export async function applyScaleAdjustModelRelight(params: {
|
||||
generateImage: GenerateCanvasImage;
|
||||
initialResult: CanvasGenerateImageResult;
|
||||
ownerKey?: string;
|
||||
request: CanvasGenerateImageRequest;
|
||||
}) {
|
||||
const { generateImage, initialResult, ownerKey, request } = params;
|
||||
const config = request.scaleAdjustModelRelight;
|
||||
if (!config || initialResult.images.length === 0) return initialResult;
|
||||
|
||||
const relitImages = [] as CanvasGenerateImageResult["images"];
|
||||
for (const [index, image] of initialResult.images.entries()) {
|
||||
const exactUrl = image.originalUrl || image.thumbnailUrl;
|
||||
try {
|
||||
const exactBuffer = await fetchImageBufferFromUrl(exactUrl);
|
||||
const metadata = await sharp(exactBuffer, { failOn: "none" }).metadata();
|
||||
const width = Math.round(Number(metadata.width || 0));
|
||||
const height = Math.round(Number(metadata.height || 0));
|
||||
if (width <= 0 || height <= 0) throw new Error("精确合成结果尺寸无效");
|
||||
|
||||
const { editableMask, maskBuffer, productAlpha } =
|
||||
await buildModelRelightMask({ config, height, width });
|
||||
const suffix = `${Date.now()}-${index + 1}-${Math.random()
|
||||
.toString(36)
|
||||
.slice(2, 8)}`;
|
||||
const maskUpload = await uploadFile(
|
||||
`canvas-scale-adjust-model-relight-mask-${suffix}.png`,
|
||||
bufferToArrayBuffer(maskBuffer)
|
||||
);
|
||||
const modelResult = await generateImage({
|
||||
allowFailover: false,
|
||||
aspectRatio: "auto",
|
||||
debugLabel: "canvas-scale-adjust-model-relight",
|
||||
debugMeta: {
|
||||
operation: "scale-adjust-model-relight",
|
||||
scaleAdjustModelRelightApplied: true,
|
||||
scaleAdjustProviderMaskImageUrl: maskUpload.url,
|
||||
sourceHeight: config.sourceHeight,
|
||||
sourceWidth: config.sourceWidth,
|
||||
},
|
||||
displayPrompt: request.displayPrompt,
|
||||
imageCount: 1,
|
||||
imageSize: "auto",
|
||||
model: config.model,
|
||||
negativePrompt:
|
||||
"复制产品、增加产品、移动产品、改变产品造型、改变构图、修改人物、文字、标注、边框",
|
||||
ownerKey,
|
||||
prompt:
|
||||
"仅编辑白色遮罩中的地面区域。根据画面现有主光方向、环境光颜色、产品落地点和地面材质，为当前位置的产品生成真实自然的接触阴影与投射阴影。阴影必须贴合产品落地边缘，方向、软硬、颜色和强度与室内现有光照一致。黑色区域保持像素级不变；不要重绘、复制、移动或变形产品，不要修改人物、家具、墙面和构图。",
|
||||
promptExtend: false,
|
||||
providerImageParams: {
|
||||
maskImageUrl: maskUpload.url,
|
||||
quality: config.quality || "medium",
|
||||
},
|
||||
referenceImages: [exactUrl],
|
||||
});
|
||||
const generatedUrl =
|
||||
modelResult.images[0]?.originalUrl ||
|
||||
modelResult.images[0]?.thumbnailUrl ||
|
||||
"";
|
||||
if (!generatedUrl) throw new Error("光影模型未返回图片");
|
||||
const generatedBuffer = await fetchImageBufferFromUrl(generatedUrl);
|
||||
const merged = await mergeModelShadowField({
|
||||
editableMask,
|
||||
exactBuffer,
|
||||
generatedBuffer,
|
||||
height,
|
||||
productAlpha,
|
||||
width,
|
||||
});
|
||||
if (!merged) throw new Error("光影模型未生成有效的地面明暗变化");
|
||||
|
||||
const finalJpegBuffer = await sharp(merged.mergedBuffer, {
|
||||
failOn: "none",
|
||||
})
|
||||
.flatten({ background: "#ffffff" })
|
||||
.jpeg({ quality: 94, mozjpeg: true })
|
||||
.toBuffer();
|
||||
const thumbnailBuffer = await sharp(merged.mergedBuffer, {
|
||||
failOn: "none",
|
||||
})
|
||||
.flatten({ background: "#ffffff" })
|
||||
.resize(512, 512, { fit: "inside", withoutEnlargement: true })
|
||||
.jpeg({ quality: 88, mozjpeg: true })
|
||||
.toBuffer();
|
||||
const [originalUpload, thumbnailUpload] = await Promise.all([
|
||||
uploadFile(
|
||||
`canvas-scale-adjust-model-relit-${suffix}.jpg`,
|
||||
bufferToArrayBuffer(finalJpegBuffer)
|
||||
),
|
||||
uploadFile(
|
||||
`canvas-scale-adjust-model-relit-thumb-${suffix}.jpg`,
|
||||
bufferToArrayBuffer(thumbnailBuffer)
|
||||
),
|
||||
]);
|
||||
console.info("[Canvas Scale Adjust] Model relight applied:", {
|
||||
appliedShadowStrength: merged.appliedShadowStrength,
|
||||
exactUrl,
|
||||
generatedUrl,
|
||||
height,
|
||||
medianLumaDelta: merged.median,
|
||||
sampleCount: merged.sampleCount,
|
||||
width,
|
||||
});
|
||||
relitImages.push({
|
||||
originalUrl: originalUpload.url,
|
||||
thumbnailUrl: thumbnailUpload.url,
|
||||
});
|
||||
} catch (error) {
|
||||
console.error(
|
||||
"[Canvas Scale Adjust] Model relight failed; keeping verified local shadow fallback:",
|
||||
{
|
||||
error: error instanceof Error ? error.message : String(error),
|
||||
exactUrl,
|
||||
index,
|
||||
}
|
||||
);
|
||||
relitImages.push(image);
|
||||
}
|
||||
}
|
||||
|
||||
return {
|
||||
...initialResult,
|
||||
images: relitImages,
|
||||
};
|
||||
}
|
||||
@ -25,7 +25,10 @@ export type CanvasScaleAdjustProductLockAssets = {
|
||||
backgroundPlateBuffer?: Buffer;
|
||||
modelMaskBuffer: Buffer;
|
||||
overlayBuffer: Buffer;
|
||||
personExclusionApplied: boolean;
|
||||
personExclusionMaskBuffer?: Buffer;
|
||||
repairMaskBuffer: Buffer;
|
||||
sourceSubjectMaskBuffer: Buffer;
|
||||
subjectReferenceUrls: string[];
|
||||
};
|
||||
|
||||
@ -60,10 +63,11 @@ function rectToPixelBox(
|
||||
|
||||
async function normalizeSubjectBuffer(params: {
|
||||
box: PixelBox;
|
||||
exclusionAlpha?: Buffer | null;
|
||||
imageBase64: string;
|
||||
}) {
|
||||
const { box, imageBase64 } = params;
|
||||
const subjectBuffer = await sharp(Buffer.from(imageBase64, "base64"), {
|
||||
const { box, exclusionAlpha, imageBase64 } = params;
|
||||
const rawSubjectBuffer = await sharp(Buffer.from(imageBase64, "base64"), {
|
||||
failOn: "none",
|
||||
})
|
||||
.rotate()
|
||||
@ -74,10 +78,30 @@ async function normalizeSubjectBuffer(params: {
|
||||
.ensureAlpha()
|
||||
.png({ compressionLevel: 6 })
|
||||
.toBuffer();
|
||||
const alpha = await sharp(subjectBuffer, { failOn: "none" })
|
||||
const rawAlpha = await sharp(rawSubjectBuffer, { failOn: "none" })
|
||||
.extractChannel(3)
|
||||
.raw()
|
||||
.toBuffer();
|
||||
const alpha = Buffer.from(rawAlpha);
|
||||
if (exclusionAlpha?.length === rawAlpha.length) {
|
||||
let productPixelCount = 0;
|
||||
let overlapPixelCount = 0;
|
||||
for (let index = 0; index < alpha.length; index += 1) {
|
||||
if (alpha[index] >= 18) productPixelCount += 1;
|
||||
if (alpha[index] >= 18 && exclusionAlpha[index] >= 8) {
|
||||
overlapPixelCount += 1;
|
||||
}
|
||||
}
|
||||
const overlapLimit = Math.max(96, Math.round(productPixelCount * 0.004));
|
||||
if (overlapPixelCount >= overlapLimit) {
|
||||
throw new Error(
|
||||
"目标产品被人物遮挡，暂无法在保持产品完整的前提下移动，请选择未被人物遮挡的完整产品"
|
||||
);
|
||||
}
|
||||
for (let index = 0; index < alpha.length; index += 1) {
|
||||
if (exclusionAlpha[index] >= 8) alpha[index] = 0;
|
||||
}
|
||||
}
|
||||
const visiblePixels = alpha.reduce(
|
||||
(count, value) => count + (value >= 18 ? 1 : 0),
|
||||
0
|
||||
@ -85,20 +109,52 @@ async function normalizeSubjectBuffer(params: {
|
||||
if (visiblePixels < Math.max(32, box.width * box.height * 0.008)) {
|
||||
throw new Error("比例调整无法识别完整产品，请重新完整框选产品");
|
||||
}
|
||||
const subjectBuffer = exclusionAlpha
|
||||
? await sharp(
|
||||
await sharp(rawSubjectBuffer, { failOn: "none" })
|
||||
.removeAlpha()
|
||||
.toColorspace("srgb")
|
||||
.raw()
|
||||
.toBuffer(),
|
||||
{
|
||||
raw: { channels: 3, height: box.height, width: box.width },
|
||||
}
|
||||
)
|
||||
.joinChannel(alpha, {
|
||||
raw: { channels: 1, height: box.height, width: box.width },
|
||||
})
|
||||
.png({ compressionLevel: 6 })
|
||||
.toBuffer()
|
||||
: rawSubjectBuffer;
|
||||
return { alpha, subjectBuffer };
|
||||
}
|
||||
|
||||
async function buildExpandedMaskPiece(params: {
|
||||
alpha: Buffer;
|
||||
box: PixelBox;
|
||||
exclusionAlpha?: Buffer | null;
|
||||
}) {
|
||||
const { alpha, box } = params;
|
||||
const { alpha, box, exclusionAlpha } = params;
|
||||
const radius = Math.max(2, Math.round(Math.min(box.width, box.height) * 0.06));
|
||||
const expandedAlpha = await sharp(alpha, {
|
||||
const blurredAlphaRaw = await sharp(alpha, {
|
||||
raw: { channels: 1, height: box.height, width: box.width },
|
||||
})
|
||||
.blur(radius)
|
||||
.threshold(8)
|
||||
.extractChannel(0)
|
||||
.raw()
|
||||
.toBuffer();
|
||||
const expandedAlphaRaw = Buffer.from(blurredAlphaRaw);
|
||||
for (let index = 0; index < expandedAlphaRaw.length; index += 1) {
|
||||
expandedAlphaRaw[index] = expandedAlphaRaw[index] >= 8 ? 255 : 0;
|
||||
}
|
||||
if (exclusionAlpha?.length === expandedAlphaRaw.length) {
|
||||
for (let index = 0; index < expandedAlphaRaw.length; index += 1) {
|
||||
if (exclusionAlpha[index] >= 8) expandedAlphaRaw[index] = 0;
|
||||
}
|
||||
}
|
||||
const expandedAlpha = await sharp(expandedAlphaRaw, {
|
||||
raw: { channels: 1, height: box.height, width: box.width },
|
||||
})
|
||||
.png({ compressionLevel: 6 })
|
||||
.toBuffer();
|
||||
const whiteRgb = await sharp({
|
||||
@ -114,7 +170,99 @@ async function buildExpandedMaskPiece(params: {
|
||||
return sharp(whiteRgb).joinChannel(expandedAlpha).png({ compressionLevel: 6 }).toBuffer();
|
||||
}
|
||||
|
||||
async function buildSubjectMaskPiece(params: { alpha: Buffer; box: PixelBox }) {
|
||||
const alphaPng = await sharp(params.alpha, {
|
||||
raw: { channels: 1, height: params.box.height, width: params.box.width },
|
||||
})
|
||||
.png({ compressionLevel: 6 })
|
||||
.toBuffer();
|
||||
const whiteRgb = await sharp({
|
||||
create: {
|
||||
background: { b: 255, g: 255, r: 255 },
|
||||
channels: 3,
|
||||
height: params.box.height,
|
||||
width: params.box.width,
|
||||
},
|
||||
})
|
||||
.png({ compressionLevel: 6 })
|
||||
.toBuffer();
|
||||
return sharp(whiteRgb)
|
||||
.joinChannel(alphaPng)
|
||||
.png({ compressionLevel: 6 })
|
||||
.toBuffer();
|
||||
}
|
||||
|
||||
async function buildPersonExclusionAlpha(params: {
|
||||
sourceBuffer: Buffer;
|
||||
sourceHeight: number;
|
||||
sourceImageUrl: string;
|
||||
sourceWidth: number;
|
||||
userId: string;
|
||||
}) {
|
||||
try {
|
||||
const person = await executeRmbgJob({
|
||||
foregroundType: "person",
|
||||
imageBuffer: params.sourceBuffer,
|
||||
prompt: "比例调整人物保护蒙版",
|
||||
skipGallerySave: true,
|
||||
sourceImageUrl: params.sourceImageUrl,
|
||||
userId: params.userId,
|
||||
});
|
||||
const alpha = await sharp(Buffer.from(person.image_base64, "base64"), {
|
||||
failOn: "none",
|
||||
})
|
||||
.rotate()
|
||||
.resize(params.sourceWidth, params.sourceHeight, { fit: "fill" })
|
||||
.ensureAlpha()
|
||||
.extractChannel(3)
|
||||
.raw()
|
||||
.toBuffer();
|
||||
const visiblePixels = alpha.reduce(
|
||||
(count, value) => count + (value >= 18 ? 1 : 0),
|
||||
0
|
||||
);
|
||||
if (visiblePixels < Math.max(32, params.sourceWidth * params.sourceHeight * 0.001)) {
|
||||
return null;
|
||||
}
|
||||
return sharp(alpha, {
|
||||
raw: {
|
||||
channels: 1,
|
||||
height: params.sourceHeight,
|
||||
width: params.sourceWidth,
|
||||
},
|
||||
})
|
||||
.blur(Math.max(1, Math.min(params.sourceWidth, params.sourceHeight) * 0.002))
|
||||
.threshold(8)
|
||||
.extractChannel(0)
|
||||
.raw()
|
||||
.toBuffer();
|
||||
} catch {
|
||||
return null;
|
||||
}
|
||||
}
|
||||
|
||||
async function extractAlphaRegion(params: {
|
||||
alpha: Buffer | null;
|
||||
box: PixelBox;
|
||||
sourceHeight: number;
|
||||
sourceWidth: number;
|
||||
}) {
|
||||
if (!params.alpha) return null;
|
||||
return sharp(params.alpha, {
|
||||
raw: {
|
||||
channels: 1,
|
||||
height: params.sourceHeight,
|
||||
width: params.sourceWidth,
|
||||
},
|
||||
})
|
||||
.extract(params.box)
|
||||
.extractChannel(0)
|
||||
.raw()
|
||||
.toBuffer();
|
||||
}
|
||||
|
||||
export async function buildScaleAdjustProductLockAssets(params: {
|
||||
protectPeople?: boolean;
|
||||
regions: CanvasScaleAdjustIntentRegion[];
|
||||
sourceBuffer: Buffer;
|
||||
sourceHeight: number;
|
||||
@ -132,7 +280,17 @@ export async function buildScaleAdjustProductLockAssets(params: {
|
||||
} = params;
|
||||
const overlayInputs: sharp.OverlayOptions[] = [];
|
||||
const maskInputs: sharp.OverlayOptions[] = [];
|
||||
const sourceSubjectMaskInputs: sharp.OverlayOptions[] = [];
|
||||
const subjectReferenceUrls: string[] = [];
|
||||
const personExclusionAlpha = params.protectPeople
|
||||
? await buildPersonExclusionAlpha({
|
||||
sourceBuffer,
|
||||
sourceHeight,
|
||||
sourceImageUrl,
|
||||
sourceWidth,
|
||||
userId,
|
||||
})
|
||||
: null;
|
||||
|
||||
for (const region of regions) {
|
||||
const sourceBox = rectToPixelBox(
|
||||
@ -156,8 +314,15 @@ export async function buildScaleAdjustProductLockAssets(params: {
|
||||
sourceImageUrl,
|
||||
userId,
|
||||
});
|
||||
const regionPersonExclusionAlpha = await extractAlphaRegion({
|
||||
alpha: personExclusionAlpha,
|
||||
box: sourceBox,
|
||||
sourceHeight,
|
||||
sourceWidth,
|
||||
});
|
||||
const { alpha, subjectBuffer } = await normalizeSubjectBuffer({
|
||||
box: sourceBox,
|
||||
exclusionAlpha: regionPersonExclusionAlpha,
|
||||
imageBase64: subject.image_base64,
|
||||
});
|
||||
const scaledSubjectBuffer = await sharp(subjectBuffer, { failOn: "none" })
|
||||
@ -173,7 +338,16 @@ export async function buildScaleAdjustProductLockAssets(params: {
|
||||
top: targetBox.top,
|
||||
});
|
||||
maskInputs.push({
|
||||
input: await buildExpandedMaskPiece({ alpha, box: sourceBox }),
|
||||
input: await buildExpandedMaskPiece({
|
||||
alpha,
|
||||
box: sourceBox,
|
||||
exclusionAlpha: regionPersonExclusionAlpha,
|
||||
}),
|
||||
left: sourceBox.left,
|
||||
top: sourceBox.top,
|
||||
});
|
||||
sourceSubjectMaskInputs.push({
|
||||
input: await buildSubjectMaskPiece({ alpha, box: sourceBox }),
|
||||
left: sourceBox.left,
|
||||
top: sourceBox.top,
|
||||
});
|
||||
@ -188,7 +362,8 @@ export async function buildScaleAdjustProductLockAssets(params: {
|
||||
width: sourceWidth,
|
||||
},
|
||||
};
|
||||
const [modelMaskBuffer, overlayBuffer, repairMaskBuffer] = await Promise.all([
|
||||
const [modelMaskBuffer, overlayBuffer, repairMaskBuffer, sourceSubjectMaskBuffer] =
|
||||
await Promise.all([
|
||||
sharp({
|
||||
create: {
|
||||
background: { b: 0, g: 0, r: 0 },
|
||||
@ -209,6 +384,10 @@ export async function buildScaleAdjustProductLockAssets(params: {
|
||||
.composite(maskInputs)
|
||||
.png({ compressionLevel: 6 })
|
||||
.toBuffer(),
|
||||
sharp(transparentCanvas)
|
||||
.composite(sourceSubjectMaskInputs)
|
||||
.png({ compressionLevel: 6 })
|
||||
.toBuffer(),
|
||||
]);
|
||||
const sourceAlpha = await sharp(sourceBuffer, { failOn: "none" })
|
||||
.rotate()
|
||||
@ -223,6 +402,13 @@ export async function buildScaleAdjustProductLockAssets(params: {
|
||||
);
|
||||
const hasTransparentBackground =
|
||||
transparentPixelCount >= sourceWidth * sourceHeight * 0.05;
|
||||
const personExclusionMaskBuffer = personExclusionAlpha
|
||||
? await sharp(personExclusionAlpha, {
|
||||
raw: { channels: 1, height: sourceHeight, width: sourceWidth },
|
||||
})
|
||||
.png({ compressionLevel: 6 })
|
||||
.toBuffer()
|
||||
: undefined;
|
||||
const backgroundPlateBuffer = hasTransparentBackground
|
||||
? await sharp(transparentCanvas)
|
||||
.png({ compressionLevel: 6 })
|
||||
@ -233,7 +419,10 @@ export async function buildScaleAdjustProductLockAssets(params: {
|
||||
...(backgroundPlateBuffer ? { backgroundPlateBuffer } : {}),
|
||||
modelMaskBuffer,
|
||||
overlayBuffer,
|
||||
personExclusionApplied: Boolean(personExclusionAlpha),
|
||||
...(personExclusionMaskBuffer ? { personExclusionMaskBuffer } : {}),
|
||||
repairMaskBuffer,
|
||||
sourceSubjectMaskBuffer,
|
||||
subjectReferenceUrls,
|
||||
};
|
||||
}
|
||||
|
||||
@ -13,9 +13,11 @@ import {
|
||||
type CanvasScaleAdjustIntentRegion,
|
||||
type CanvasScaleAdjustRect,
|
||||
} from "@/lib/canvas/scale-adjust-product-lock";
|
||||
import { applyScaleAdjustModelRelight } from "@/lib/canvas/scale-adjust-model-relight";
|
||||
import { createStorageUploadSession } from "@/lib/storage/service";
|
||||
|
||||
type VerificationCase = {
|
||||
expectedError?: string;
|
||||
id: string;
|
||||
rect: CanvasScaleAdjustRect;
|
||||
scalePercent?: number;
|
||||
@ -84,6 +86,31 @@ const cases: VerificationCase[] = [
|
||||
scalePercent: -30,
|
||||
source: "https://scqny.jiansun.vip/uploads/1783555294804-qdykhy.png",
|
||||
},
|
||||
{
|
||||
id: "11-office-chair-move-right",
|
||||
rect: { height: 0.72, width: 0.64, x: 0.18, y: 0.25 },
|
||||
source: "https://scqny.jiansun.vip/uploads/1783562931574-tj4zst.png",
|
||||
target: { height: 0.72, width: 0.64, x: 0.31, y: 0.25 },
|
||||
},
|
||||
{
|
||||
id: "12-bookshelf-person-move-shrink",
|
||||
expectedError: "目标产品被人物遮挡",
|
||||
rect: { height: 0.88, width: 0.29, x: 0.37, y: 0.07 },
|
||||
source: "https://scqny.jiansun.vip/uploads/1783687809170-vmnsea.png",
|
||||
target: { height: 0.704, width: 0.232, x: 0.54, y: 0.246 },
|
||||
},
|
||||
{
|
||||
id: "13-coffee-cart-move-left",
|
||||
rect: { height: 0.54, width: 0.5, x: 0.22, y: 0.36 },
|
||||
source: "https://scqny.jiansun.vip/uploads/1783555598917-8w4a6t.png",
|
||||
target: { height: 0.54, width: 0.5, x: 0.05, y: 0.36 },
|
||||
},
|
||||
{
|
||||
id: "14-side-table-person-scene-move-left",
|
||||
rect: { height: 0.235, width: 0.225, x: 0.77, y: 0.72 },
|
||||
source: "https://scqny.jiansun.vip/uploads/1783927690517-8uhlqu.jpg",
|
||||
target: { height: 0.235, width: 0.225, x: 0.55, y: 0.72 },
|
||||
},
|
||||
];
|
||||
|
||||
const aspectRatios = ["1:1", "4:3", "3:4", "16:9", "9:16"] as const;
|
||||
@ -176,6 +203,10 @@ async function runCase(params: {
|
||||
resolve(outputDir, `${item.id}-repair-mask.png`),
|
||||
assets.repairMaskBuffer
|
||||
),
|
||||
writeFile(
|
||||
resolve(outputDir, `${item.id}-source-subject-mask.png`),
|
||||
assets.sourceSubjectMaskBuffer
|
||||
),
|
||||
...(assets.backgroundPlateBuffer
|
||||
? [
|
||||
writeFile(
|
||||
@ -184,16 +215,44 @@ async function runCase(params: {
|
||||
),
|
||||
]
|
||||
: []),
|
||||
...(assets.personExclusionMaskBuffer
|
||||
? [
|
||||
writeFile(
|
||||
resolve(outputDir, `${item.id}-person-exclusion-mask.png`),
|
||||
assets.personExclusionMaskBuffer
|
||||
),
|
||||
]
|
||||
: []),
|
||||
]);
|
||||
|
||||
if (process.env.SCALE_ADJUST_ASSETS_ONLY === "1") {
|
||||
const result = {
|
||||
elapsedMs: Date.now() - startedAt,
|
||||
id: item.id,
|
||||
mode: "assets-only",
|
||||
ok: true,
|
||||
personExclusionApplied: assets.personExclusionApplied,
|
||||
rect: item.rect,
|
||||
source: item.source,
|
||||
targetRect: regions[0].targetRect,
|
||||
};
|
||||
console.log(`SCALE_VERIFY_CASE ${JSON.stringify(result)}`);
|
||||
return result;
|
||||
}
|
||||
|
||||
const suffix = `${item.id}-${Date.now()}`;
|
||||
const [modelMaskUpload, overlayUpload, repairMaskUpload] = await Promise.all([
|
||||
const [modelMaskUpload, overlayUpload, repairMaskUpload, sourceSubjectMaskUpload] =
|
||||
await Promise.all([
|
||||
upload(`verify-scale-mask-${suffix}.png`, toArrayBuffer(assets.modelMaskBuffer)),
|
||||
upload(`verify-scale-overlay-${suffix}.png`, toArrayBuffer(assets.overlayBuffer)),
|
||||
upload(
|
||||
`verify-scale-repair-mask-${suffix}.png`,
|
||||
toArrayBuffer(assets.repairMaskBuffer)
|
||||
),
|
||||
upload(
|
||||
`verify-scale-subject-mask-${suffix}.png`,
|
||||
toArrayBuffer(assets.sourceSubjectMaskBuffer)
|
||||
),
|
||||
]);
|
||||
const backgroundPlateUpload = assets.backgroundPlateBuffer
|
||||
? await upload(
|
||||
@ -201,21 +260,43 @@ async function runCase(params: {
|
||||
toArrayBuffer(assets.backgroundPlateBuffer)
|
||||
)
|
||||
: null;
|
||||
const providerImageParams = {
|
||||
objectRemovalMaskImageUrl: modelMaskUpload.url,
|
||||
objectRemovalMode: "premium",
|
||||
};
|
||||
const hasPositionMove = regions.some(
|
||||
(region) =>
|
||||
Math.abs(region.targetRect.x - region.rect.x) >= 0.005 ||
|
||||
Math.abs(region.targetRect.y - region.rect.y) >= 0.005
|
||||
);
|
||||
const providerImageParams = hasPositionMove
|
||||
? { maskImageUrl: modelMaskUpload.url, quality: "medium" }
|
||||
: {
|
||||
objectRemovalMaskImageUrl: modelMaskUpload.url,
|
||||
objectRemovalMode: "premium",
|
||||
};
|
||||
const productLockComposite = {
|
||||
...(backgroundPlateUpload
|
||||
? { backgroundPlateImageUrl: backgroundPlateUpload.url }
|
||||
: {}),
|
||||
overlayImageUrl: overlayUpload.url,
|
||||
...(hasPositionMove
|
||||
? {
|
||||
repairMaskImageUrl: repairMaskUpload.url,
|
||||
sourceImageUrl: item.source,
|
||||
}
|
||||
: {}),
|
||||
regions: regions.map((region) => ({
|
||||
source: region.rect,
|
||||
target: region.targetRect,
|
||||
})),
|
||||
shadowSourceImageUrl: item.source,
|
||||
sourceSubjectMaskImageUrl: sourceSubjectMaskUpload.url,
|
||||
sourceHeight,
|
||||
sourceWidth,
|
||||
};
|
||||
const verification = {
|
||||
allowOutsideChangedWhenChangedInside: false,
|
||||
oldFootprintMaskImageUrl: repairMaskUpload.url,
|
||||
deterministicProductOverlayApplied: true,
|
||||
oldFootprintMaskImageUrl: hasPositionMove
|
||||
? sourceSubjectMaskUpload.url
|
||||
: repairMaskUpload.url,
|
||||
regions: [item.rect],
|
||||
rejectFailedCandidates: true,
|
||||
rejectNoEffectiveChangeOnly: false,
|
||||
@ -223,14 +304,20 @@ async function runCase(params: {
|
||||
sourceImageUrl: item.source,
|
||||
targetRegions: [regions[0].targetRect],
|
||||
};
|
||||
const prompt = "移除掩膜中的完整产品并自然还原背景。";
|
||||
const prompt = hasPositionMove
|
||||
? "只编辑白色掩膜区域，完整移除旧位置的产品及其原有阴影，并根据周围墙面、地面、家具和光照连续自然地重建被遮挡背景。黑色区域保持不变，不要保留产品的任何部件或残影。"
|
||||
: "移除掩膜中的完整产品并自然还原背景。";
|
||||
const request: CanvasGenerateImageRequest = {
|
||||
allowFailover: false,
|
||||
aspectRatio: resolveAspectRatio(sourceWidth, sourceHeight),
|
||||
aspectRatio: hasPositionMove
|
||||
? "auto"
|
||||
: resolveAspectRatio(sourceWidth, sourceHeight),
|
||||
debugLabel: `verify-scale-final-${item.id}`,
|
||||
debugMeta: {
|
||||
operation: "scale-adjust",
|
||||
scaleAdjustPromptStrategy: "finegrain-erase-product-lock-v1",
|
||||
scaleAdjustPromptStrategy: hasPositionMove
|
||||
? "gpt-mask-background-rebuild-product-lock-v1"
|
||||
: "finegrain-erase-product-lock-v1",
|
||||
scaleAdjustSequentialCleanupRetry: true,
|
||||
},
|
||||
displayPrompt: "比例调整",
|
||||
@ -257,10 +344,28 @@ async function runCase(params: {
|
||||
},
|
||||
},
|
||||
],
|
||||
scaleAdjustModelRelight: {
|
||||
model:
|
||||
process.env.SCALE_ADJUST_MODEL ||
|
||||
"e03d3341-cecd-425e-b88b-9350cbbce18f",
|
||||
overlayImageUrl: overlayUpload.url,
|
||||
quality: "medium",
|
||||
regions: regions.map((region) => ({ target: region.targetRect })),
|
||||
sourceHeight,
|
||||
sourceWidth,
|
||||
},
|
||||
scaleAdjustProductLockComposite: productLockComposite,
|
||||
scaleAdjustVerification: verification,
|
||||
};
|
||||
const generated = await generateCanvasImage(request);
|
||||
const initialGenerated = await generateCanvasImage(request);
|
||||
const generated = await applyScaleAdjustModelRelight({
|
||||
generateImage: generateCanvasImage,
|
||||
initialResult: initialGenerated,
|
||||
ownerKey:
|
||||
process.env.SCALE_ADJUST_USER_ID ||
|
||||
"00000000-0000-0000-0000-000000000000",
|
||||
request,
|
||||
});
|
||||
const resultUrl = generated.images[0]?.originalUrl || null;
|
||||
if (!resultUrl) throw new Error("比例调整未返回结果图片");
|
||||
await writeFile(
|
||||
@ -272,6 +377,7 @@ async function runCase(params: {
|
||||
elapsedMs: Date.now() - startedAt,
|
||||
id: item.id,
|
||||
ok: true,
|
||||
personExclusionApplied: assets.personExclusionApplied,
|
||||
rect: item.rect,
|
||||
resultUrl,
|
||||
source: item.source,
|
||||
@ -312,8 +418,21 @@ async function main() {
|
||||
try {
|
||||
results.push(await runCase({ item, outputDir, upload }));
|
||||
} catch (error) {
|
||||
const errorMessage = error instanceof Error ? error.message : String(error);
|
||||
if (item.expectedError && errorMessage.includes(item.expectedError)) {
|
||||
const expectedFailure = {
|
||||
error: errorMessage,
|
||||
expectedFailure: true,
|
||||
id: item.id,
|
||||
ok: true,
|
||||
source: item.source,
|
||||
};
|
||||
results.push(expectedFailure);
|
||||
console.log(`SCALE_VERIFY_CASE ${JSON.stringify(expectedFailure)}`);
|
||||
continue;
|
||||
}
|
||||
const failure = {
|
||||
error: error instanceof Error ? error.message : String(error),
|
||||
error: errorMessage,
|
||||
id: item.id,
|
||||
ok: false,
|
||||
source: item.source,
|
||||
|
||||
@ -2,20 +2,62 @@ import { expect, test } from "@playwright/test";
|
||||
import { readFileSync } from "node:fs";
|
||||
import { resolve } from "node:path";
|
||||
|
||||
import { hasScaleAdjustTargetChanged } from "../../components/canvas/nodes/image-node/image-node-local-edit";
|
||||
|
||||
function readSource(path: string) {
|
||||
return readFileSync(resolve(process.cwd(), path), "utf8");
|
||||
}
|
||||
|
||||
test.describe("canvas scale adjust product lock", () => {
|
||||
test("accepts target movement even when target size stays unchanged", () => {
|
||||
const source = { height: 0.4, width: 0.3, x: 0.2, y: 0.25 };
|
||||
|
||||
expect(hasScaleAdjustTargetChanged(source, source)).toBe(false);
|
||||
expect(
|
||||
hasScaleAdjustTargetChanged(source, { ...source, x: 0.46, y: 0.12 })
|
||||
).toBe(true);
|
||||
expect(
|
||||
hasScaleAdjustTargetChanged(source, {
|
||||
...source,
|
||||
height: 0.32,
|
||||
width: 0.24,
|
||||
})
|
||||
).toBe(true);
|
||||
});
|
||||
|
||||
test("uses the same movement validation in canvas and detail result flows", () => {
|
||||
const canvasNode = readSource("components/canvas/nodes/ImageNode.tsx");
|
||||
const detailWorkspace = readSource(
|
||||
"components/agents/AgentGenerationWorkspaceDarkV2.tsx"
|
||||
);
|
||||
|
||||
expect(canvasNode).toContain("hasScaleAdjustTargetChanged(");
|
||||
expect(detailWorkspace).toContain("hasScaleAdjustTargetChanged(");
|
||||
expect(canvasNode).toContain("青色目标框大小或位置");
|
||||
expect(detailWorkspace).toContain("目标框大小和位置均未变化");
|
||||
});
|
||||
|
||||
test("uses one dedicated erase step and exact product overlay", () => {
|
||||
const route = readSource("app/api/canvas/local-edit/route.ts");
|
||||
|
||||
expect(route).toContain("buildScaleAdjustProductLockAssets");
|
||||
expect(route).toContain('objectRemovalMode: "premium"');
|
||||
expect(route).toContain("objectRemovalMaskImageUrl: modelMaskUpload.url");
|
||||
expect(route).toContain("maskImageUrl: modelMaskUpload.url");
|
||||
expect(route).toContain("hasPositionMove");
|
||||
expect(route).toContain('aspectRatio: hasPositionMove ? "auto" : resolvedAspectRatio');
|
||||
expect(route).toContain("overlayImageUrl: overlayUpload.url");
|
||||
expect(route).toContain("oldFootprintMaskImageUrl: repairMaskUpload.url");
|
||||
expect(route).toContain('scaleAdjustPromptStrategy: "finegrain-erase-product-lock-v1"');
|
||||
expect(route).toContain("repairMaskImageUrl: repairMaskUpload.url");
|
||||
expect(route).toContain("sourceImageUrl");
|
||||
expect(route).toContain("protectPeople: hasPositionMove");
|
||||
expect(route).toContain("oldFootprintMaskImageUrl: hasPositionMove");
|
||||
expect(route).toContain("? sourceSubjectMaskUpload?.url");
|
||||
expect(route).toContain("deterministicProductOverlayApplied: true");
|
||||
expect(route).toContain("scaleAdjustPersonExclusionApplied:");
|
||||
expect(route).toContain("sourceSubjectMaskImageUrl: sourceSubjectMaskUpload.url");
|
||||
expect(route).toContain("shadowSourceImageUrl: sourceImageUrl");
|
||||
expect(route).toContain('"finegrain-erase-product-lock-v1"');
|
||||
expect(route).toContain('"gpt-mask-background-rebuild-product-lock-v1"');
|
||||
expect(route).not.toContain("buildScaleAdjustVisualGuide");
|
||||
expect(route).not.toContain("source-plus-guide-v1");
|
||||
});
|
||||
@ -52,6 +94,57 @@ test.describe("canvas scale adjust product lock", () => {
|
||||
expect(productLock).toContain("backgroundPlateBuffer");
|
||||
});
|
||||
|
||||
test("protects people and rejects products materially occluded by them", () => {
|
||||
const productLock = readSource("lib/canvas/scale-adjust-product-lock.ts");
|
||||
const rmbg = readSource("lib/ai/rmbg/service.ts");
|
||||
|
||||
expect(productLock).toContain('foregroundType: "person"');
|
||||
expect(productLock).toContain("regionPersonExclusionAlpha");
|
||||
expect(productLock).toContain("overlapPixelCount >= overlapLimit");
|
||||
expect(productLock).toContain("目标产品被人物遮挡");
|
||||
expect(productLock).toContain("personExclusionApplied: Boolean(personExclusionAlpha)");
|
||||
expect(productLock).toContain("expandedAlphaRaw[index] >= 8 ? 255 : 0");
|
||||
expect(productLock).toContain(".threshold(8)\n .extractChannel(0)");
|
||||
expect(rmbg).toContain("foregroundType: foregroundType ??");
|
||||
});
|
||||
|
||||
test("moves the original contact shadow with the exact product overlay", () => {
|
||||
const generator = readSource("lib/canvas/generate-image.ts");
|
||||
|
||||
expect(generator).toContain("buildScaleAdjustTransferredShadow");
|
||||
expect(generator).toContain("cleanedLuma - sourceLuma - 4");
|
||||
expect(generator).toContain("transferredShadowBuffer");
|
||||
expect(generator).toContain("transferredShadowCount");
|
||||
expect(generator).toContain("if (!(isShrink || isMove)) continue");
|
||||
expect(generator).toContain(
|
||||
"const maskHit = explicitMaskRaw\n ? explicitMaskValue > 18"
|
||||
);
|
||||
expect(generator).toContain("(!isMove &&");
|
||||
expect(generator).toContain(
|
||||
"const generatedWidth = compositeBaseBuffer ? overlayWidth : modelWidth"
|
||||
);
|
||||
expect(generator).toContain(
|
||||
".extractChannel(3)\n .blur(Math.max(4"
|
||||
);
|
||||
expect(generator).toContain(".extractChannel(0)\n .raw()\n .toBuffer()");
|
||||
});
|
||||
|
||||
test("uses the image edit model to rebuild lighting at the target position", () => {
|
||||
const route = readSource("app/api/canvas/local-edit/route.ts");
|
||||
const queue = readSource("lib/canvas/image-task-queue.ts");
|
||||
const relight = readSource("lib/canvas/scale-adjust-model-relight.ts");
|
||||
|
||||
expect(route).toContain("scaleAdjustModelRelight:");
|
||||
expect(route).toContain("...(hasPositionMove");
|
||||
expect(route).toContain("overlayImageUrl: overlayUpload.url");
|
||||
expect(queue).toContain("applyScaleAdjustModelRelight");
|
||||
expect(relight).toContain('debugLabel: "canvas-scale-adjust-model-relight"');
|
||||
expect(relight).toContain("maskImageUrl: maskUpload.url");
|
||||
expect(relight).toContain("生成真实自然的接触阴影与投射阴影");
|
||||
expect(relight).toContain("findMedianLumaDelta");
|
||||
expect(relight).toContain("productAlpha[pixelIndex] >= 8 ? 0");
|
||||
});
|
||||
|
||||
test("keeps non-pro detail result scale adjust on the shared backend flow", () => {
|
||||
const source = readSource(
|
||||
"components/agents/AgentGenerationWorkspaceDarkV2.tsx"
|
||||
|
||||
Loading…
x
Reference in New Issue
Block a user