605 lines
19 KiB
TypeScript
605 lines
19 KiB
TypeScript
import { mkdir, writeFile } from "node:fs/promises";
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import { resolve } from "node:path";
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import sharp from "sharp";
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import { fetchImageBufferFromUrl } from "@/lib/ai/rmbg/service";
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import {
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type CanvasGenerateImageRequest,
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generateCanvasImage,
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} from "@/lib/canvas/generate-image";
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import { hasScaleAdjustPositionMoved } from "@/lib/canvas/scale-adjust-geometry";
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import {
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buildScaleAdjustProductLockAssets,
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type CanvasScaleAdjustIntentRegion,
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type CanvasScaleAdjustRect,
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} from "@/lib/canvas/scale-adjust-product-lock";
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import { applyScaleAdjustModelRelight } from "@/lib/canvas/scale-adjust-model-relight";
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import {
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buildSemanticScaleAdjustCleanupPrompt,
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buildSemanticScaleAdjustCompositeRegions,
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buildSemanticScaleAdjustExtractionPrompt,
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} from "@/lib/canvas/scale-adjust-semantic";
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import { createStorageUploadSession } from "@/lib/storage/service";
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type VerificationCase = {
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expectedError?: string;
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id: string;
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rect: CanvasScaleAdjustRect;
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scalePercent?: number;
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source: string;
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target?: CanvasScaleAdjustRect;
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};
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const cases: VerificationCase[] = [
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{
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id: "01-chair-cutout",
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rect: { height: 0.76, width: 0.6, x: 0.2, y: 0.2 },
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source: "https://scqny.jiansun.vip/uploads/1783578430745-dqst30.png",
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target: { height: 0.418, width: 0.33, x: 0.34, y: 0.38 },
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},
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{
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id: "02-office-chair",
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rect: { height: 0.72, width: 0.64, x: 0.18, y: 0.25 },
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source: "https://scqny.jiansun.vip/uploads/1783562931574-tj4zst.png",
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target: { height: 0.45, width: 0.4, x: 0.31, y: 0.38 },
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},
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{
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id: "03-cabinet",
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rect: { height: 0.91, width: 0.72, x: 0.13, y: 0.03 },
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scalePercent: -25,
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source: "https://scqny.jiansun.vip/uploads/1783562287046-gpie6r.png",
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},
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{
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id: "04-bookshelf-with-person",
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rect: { height: 0.88, width: 0.29, x: 0.37, y: 0.07 },
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scalePercent: -25,
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source: "https://scqny.jiansun.vip/uploads/1783687809170-vmnsea.png",
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},
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{
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id: "05-cabinet-room",
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rect: { height: 0.91, width: 0.72, x: 0.13, y: 0.03 },
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scalePercent: -25,
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source: "https://scqny.jiansun.vip/uploads/1783561235528-gv6es4.jpg",
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},
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{
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id: "06-standing-desk-a",
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rect: { height: 0.61, width: 0.43, x: 0.27, y: 0.32 },
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scalePercent: -25,
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source: "https://scqny.jiansun.vip/uploads/1783558912572-dkkmmf.png",
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},
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{
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id: "07-clothes-rack",
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rect: { height: 0.7, width: 0.53, x: 0.32, y: 0.23 },
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scalePercent: -25,
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source: "https://scqny.jiansun.vip/uploads/1783689789549-wu4br1.png",
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},
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{
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id: "08-desk",
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rect: { height: 0.7, width: 0.9, x: 0.03, y: 0.26 },
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scalePercent: -30,
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source: "https://scqny.jiansun.vip/uploads/1783556368653-aizsul.png",
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},
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{
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id: "09-coffee-cart",
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rect: { height: 0.54, width: 0.5, x: 0.22, y: 0.36 },
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scalePercent: -30,
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source: "https://scqny.jiansun.vip/uploads/1783555598917-8w4a6t.png",
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},
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{
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id: "10-standing-desk-c",
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rect: { height: 0.69, width: 0.73, x: 0.23, y: 0.23 },
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scalePercent: -30,
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source: "https://scqny.jiansun.vip/uploads/1783555294804-qdykhy.png",
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},
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{
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id: "11-office-chair-move-right",
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rect: { height: 0.72, width: 0.64, x: 0.18, y: 0.25 },
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source: "https://scqny.jiansun.vip/uploads/1783562931574-tj4zst.png",
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target: { height: 0.72, width: 0.64, x: 0.31, y: 0.25 },
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},
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{
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id: "12-bookshelf-person-move-shrink",
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expectedError: "目标产品被人物遮挡",
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rect: { height: 0.88, width: 0.29, x: 0.37, y: 0.07 },
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source: "https://scqny.jiansun.vip/uploads/1783687809170-vmnsea.png",
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target: { height: 0.704, width: 0.232, x: 0.54, y: 0.246 },
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},
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{
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id: "13-coffee-cart-move-left",
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rect: { height: 0.54, width: 0.5, x: 0.22, y: 0.36 },
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source: "https://scqny.jiansun.vip/uploads/1783555598917-8w4a6t.png",
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target: { height: 0.54, width: 0.5, x: 0.05, y: 0.36 },
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},
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{
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id: "14-side-table-person-scene-move-left",
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rect: { height: 0.235, width: 0.225, x: 0.77, y: 0.72 },
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source: "https://scqny.jiansun.vip/uploads/1783927690517-8uhlqu.jpg",
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target: { height: 0.235, width: 0.225, x: 0.55, y: 0.72 },
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},
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{
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id: "15-user-coat-rack",
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rect: { height: 0.515, width: 0.215, x: 0.295, y: 0.225 },
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scalePercent: -25,
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source: "https://scqny.jiansun.vip/uploads/1783943425127-artezr.png",
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},
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];
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const aspectRatios = [
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"1:1",
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"1:4",
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"1:8",
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"2:3",
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"3:2",
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"3:4",
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"4:1",
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"4:3",
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"4:5",
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"5:4",
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"8:1",
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"9:16",
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"16:9",
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"21:9",
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] as const;
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function toArrayBuffer(buffer: Buffer) {
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return buffer.buffer.slice(
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buffer.byteOffset,
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buffer.byteOffset + buffer.byteLength
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) as ArrayBuffer;
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}
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function targetAroundCenter(item: VerificationCase): CanvasScaleAdjustRect {
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if (item.target) return item.target;
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const factor = 1 + (item.scalePercent || 0) / 100;
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return {
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height: item.rect.height * factor,
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width: item.rect.width * factor,
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x: item.rect.x + (item.rect.width * (1 - factor)) / 2,
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y: item.rect.y + (item.rect.height * (1 - factor)) / 2,
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};
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}
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function resolveAspectRatio(width: number, height: number) {
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const ratio = width / height;
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return aspectRatios.reduce((best, candidate) => {
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const [candidateWidth, candidateHeight] = candidate
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.split(":")
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.map(Number);
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const bestParts = best.split(":").map(Number);
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const candidateDiff = Math.abs(candidateWidth / candidateHeight - ratio);
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const bestDiff = Math.abs(bestParts[0] / bestParts[1] - ratio);
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return candidateDiff < bestDiff ? candidate : best;
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}, aspectRatios[0]);
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}
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async function addLabel(input: Buffer, label: string) {
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const metadata = await sharp(input).metadata();
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const width = metadata.width || 420;
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const height = metadata.height || 320;
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return sharp(input)
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.composite([
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{
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input: Buffer.from(`
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<svg width="${width}" height="${height}" xmlns="http://www.w3.org/2000/svg">
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<rect width="${Math.min(width, 18 * (label.length * 0.62 + 1))}" height="34" fill="#111111" fill-opacity="0.9" />
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<text x="8" y="24" fill="#ffffff" font-family="Arial, Helvetica, sans-serif" font-size="20" font-weight="700">${label}</text>
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</svg>
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`),
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},
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])
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.flatten({ background: "#ffffff" })
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.jpeg({ quality: 88 })
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.toBuffer();
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}
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async function runCase(params: {
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item: VerificationCase;
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outputDir: string;
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upload: Awaited<ReturnType<typeof createStorageUploadSession>>;
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}) {
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const { item, outputDir, upload } = params;
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const startedAt = Date.now();
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const sourceBuffer = await fetchImageBufferFromUrl(item.source);
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const sourceMetadata = await sharp(sourceBuffer, { failOn: "none" }).metadata();
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const sourceWidth = Number(sourceMetadata.width || 0);
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const sourceHeight = Number(sourceMetadata.height || 0);
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if (sourceWidth <= 0 || sourceHeight <= 0) {
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throw new Error("无法读取测试原图尺寸");
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}
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const regions: CanvasScaleAdjustIntentRegion[] = [
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{ index: 1, rect: item.rect, targetRect: targetAroundCenter(item) },
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];
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const hasPositionMove = regions.some((region) =>
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hasScaleAdjustPositionMoved(region.rect, region.targetRect)
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);
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const assets = await buildScaleAdjustProductLockAssets({
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protectPeople: hasPositionMove,
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regions,
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sourceBuffer,
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sourceHeight,
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sourceImageUrl: item.source,
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sourceWidth,
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userId:
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process.env.SCALE_ADJUST_USER_ID ||
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"00000000-0000-0000-0000-000000000000",
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});
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await Promise.all([
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writeFile(resolve(outputDir, `${item.id}-source.png`), sourceBuffer),
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writeFile(resolve(outputDir, `${item.id}-model-mask.png`), assets.modelMaskBuffer),
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writeFile(resolve(outputDir, `${item.id}-overlay.png`), assets.overlayBuffer),
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writeFile(
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resolve(outputDir, `${item.id}-repair-mask.png`),
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assets.repairMaskBuffer
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),
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...assets.semanticSourceCropBuffers.map((buffer, index) =>
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writeFile(
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resolve(outputDir, `${item.id}-semantic-source-${index + 1}.png`),
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buffer
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)
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),
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writeFile(
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resolve(outputDir, `${item.id}-source-subject-mask.png`),
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assets.sourceSubjectMaskBuffer
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),
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...(assets.backgroundPlateBuffer
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? [
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writeFile(
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resolve(outputDir, `${item.id}-background-plate.png`),
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assets.backgroundPlateBuffer
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),
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]
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: []),
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...(assets.personExclusionMaskBuffer
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? [
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writeFile(
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resolve(outputDir, `${item.id}-person-exclusion-mask.png`),
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assets.personExclusionMaskBuffer
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),
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]
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: []),
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]);
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if (process.env.SCALE_ADJUST_ASSETS_ONLY === "1") {
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const result = {
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elapsedMs: Date.now() - startedAt,
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id: item.id,
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mode: "assets-only",
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ok: true,
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personExclusionApplied: assets.personExclusionApplied,
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rect: item.rect,
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semanticFallbackRegionIndexes: assets.semanticFallbackRegionIndexes,
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semanticFallbackSuggested: assets.semanticFallbackSuggested,
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source: item.source,
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targetRect: regions[0].targetRect,
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};
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console.log(`SCALE_VERIFY_CASE ${JSON.stringify(result)}`);
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return result;
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}
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const suffix = `${item.id}-${Date.now()}`;
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const useSemanticScaleAdjust =
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!hasPositionMove && assets.semanticFallbackSuggested;
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const semanticCompositeRegions = useSemanticScaleAdjust
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? buildSemanticScaleAdjustCompositeRegions(regions)
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: [];
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const [
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modelMaskUpload,
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overlayUpload,
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repairMaskUpload,
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semanticSourceCropUploads,
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sourceSubjectMaskUpload,
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] = await Promise.all([
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upload(`verify-scale-mask-${suffix}.png`, toArrayBuffer(assets.modelMaskBuffer)),
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upload(`verify-scale-overlay-${suffix}.png`, toArrayBuffer(assets.overlayBuffer)),
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upload(
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`verify-scale-repair-mask-${suffix}.png`,
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toArrayBuffer(assets.repairMaskBuffer)
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),
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Promise.all(
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assets.semanticSourceCropBuffers.map((buffer, index) =>
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upload(
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`verify-scale-semantic-source-${suffix}-${index + 1}.png`,
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toArrayBuffer(buffer)
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)
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)
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),
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upload(
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`verify-scale-subject-mask-${suffix}.png`,
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toArrayBuffer(assets.sourceSubjectMaskBuffer)
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),
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]);
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const backgroundPlateUpload = assets.backgroundPlateBuffer
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? await upload(
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`verify-scale-background-${suffix}.png`,
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toArrayBuffer(assets.backgroundPlateBuffer)
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)
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: null;
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const providerImageParams = useSemanticScaleAdjust
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? { quality: "high" }
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: hasPositionMove
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? { maskImageUrl: modelMaskUpload.url, quality: "medium" }
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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: item.source,
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}
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: {}),
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...(hasPositionMove
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? {
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regions: regions.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: item.source,
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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 verification = {
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allowOutsideChangedWhenChangedInside: false,
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deterministicProductOverlayApplied: true,
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oldFootprintMaskImageUrl: useSemanticScaleAdjust
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? sourceSubjectMaskUpload.url
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: hasPositionMove
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? sourceSubjectMaskUpload.url
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: repairMaskUpload.url,
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regions: [item.rect],
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rejectFailedCandidates: true,
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rejectNoEffectiveChangeOnly: false,
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rejectOldFootprintOnly: true,
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sourceImageUrl: item.source,
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targetRegions: [regions[0].targetRect],
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};
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const prompt = useSemanticScaleAdjust
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? buildSemanticScaleAdjustExtractionPrompt()
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: 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 request: CanvasGenerateImageRequest = {
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allowFailover: false,
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aspectRatio: hasPositionMove
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? "auto"
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: resolveAspectRatio(sourceWidth, sourceHeight),
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debugLabel: `verify-scale-final-${item.id}`,
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debugMeta: {
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operation: "scale-adjust",
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scaleAdjustPromptStrategy: useSemanticScaleAdjust
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? "gpt-extract-product-lock-v2"
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: 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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scaleAdjustSemanticFallbackRegionIndexes:
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assets.semanticFallbackRegionIndexes,
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scaleAdjustSemanticFallbackSuggested: assets.semanticFallbackSuggested,
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scaleAdjustSequentialCleanupRetry: !useSemanticScaleAdjust,
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sourceHeight,
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sourceWidth,
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},
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displayPrompt: "比例调整",
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imageCount: 1,
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imageSize: "1K",
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model:
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process.env.SCALE_ADJUST_MODEL ||
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"e03d3341-cecd-425e-b88b-9350cbbce18f",
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prompt,
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promptExtend: false,
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providerImageParams,
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referenceImages: [item.source],
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...(useSemanticScaleAdjust
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? {
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localEditComposite: {
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expandRegions: false,
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featherMaxPx: 28,
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featherMinPx: 12,
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featherRatio: 0.012,
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maskMode: "region" as const,
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regions: semanticCompositeRegions,
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sourceImageUrl: item.source,
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},
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}
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: {}),
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...(useSemanticScaleAdjust
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? {
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semanticScaleAdjustPreparation: {
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cleanupImageSize: "2K",
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cleanupModel: "5198c20f-b4cc-402c-bc73-eeabacd086b4",
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cleanupPrompt: buildSemanticScaleAdjustCleanupPrompt(),
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extractionPrompt: buildSemanticScaleAdjustExtractionPrompt(),
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regions: regions.map((region, index) => ({
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source: region.rect,
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sourceCropImageUrl:
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semanticSourceCropUploads[index]?.url || "",
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target: region.targetRect,
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})),
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relightModel:
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process.env.SCALE_ADJUST_MODEL ||
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"e03d3341-cecd-425e-b88b-9350cbbce18f",
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sourceImageUrl: item.source,
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},
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}
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: {}),
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retryVariants: useSemanticScaleAdjust ? [] : [
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{
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label: "finegrain-cleanup-pass",
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prompt,
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providerImageParams,
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referenceImages: [item.source],
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scaleAdjustProductLockComposite: productLockComposite,
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scaleAdjustVerification: {
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...verification,
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rejectNoEffectiveChangeOnly: true,
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rejectOldFootprintOnly: false,
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},
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},
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],
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...(hasPositionMove
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? {
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scaleAdjustModelRelight: {
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model:
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process.env.SCALE_ADJUST_MODEL ||
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"e03d3341-cecd-425e-b88b-9350cbbce18f",
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overlayImageUrl: overlayUpload.url,
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quality: "medium" as const,
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regions: regions.map((region) => ({ target: region.targetRect })),
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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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...(useSemanticScaleAdjust
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? {}
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: { scaleAdjustProductLockComposite: productLockComposite }),
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scaleAdjustVerification: verification,
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};
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const initialGenerated = await generateCanvasImage(request);
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const generated = await applyScaleAdjustModelRelight({
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generateImage: generateCanvasImage,
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initialResult: initialGenerated,
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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(
|
|
resolve(outputDir, `${item.id}-result.png`),
|
|
await fetchImageBufferFromUrl(resultUrl)
|
|
);
|
|
|
|
const result = {
|
|
elapsedMs: Date.now() - startedAt,
|
|
id: item.id,
|
|
ok: true,
|
|
personExclusionApplied: assets.personExclusionApplied,
|
|
rect: item.rect,
|
|
resultUrl,
|
|
source: item.source,
|
|
targetRect: regions[0].targetRect,
|
|
};
|
|
console.log(`SCALE_VERIFY_CASE ${JSON.stringify(result)}`);
|
|
return result;
|
|
}
|
|
|
|
async function main() {
|
|
const outputDir = resolve(
|
|
process.env.SCALE_ADJUST_OUTPUT_DIR ||
|
|
"/private/tmp/scale-adjust-final-verification"
|
|
);
|
|
const requestedIds = new Set(
|
|
String(process.env.SCALE_ADJUST_CASES || "")
|
|
.split(",")
|
|
.map((value) => value.trim())
|
|
.filter(Boolean)
|
|
);
|
|
const selectedCases = requestedIds.size
|
|
? cases.filter((item) => requestedIds.has(item.id))
|
|
: cases;
|
|
const concurrency = Math.max(
|
|
1,
|
|
Math.min(3, Number(process.env.SCALE_ADJUST_CONCURRENCY || 3))
|
|
);
|
|
await mkdir(outputDir, { recursive: true });
|
|
const upload = await createStorageUploadSession();
|
|
const results: Array<Record<string, unknown>> = [];
|
|
let cursor = 0;
|
|
|
|
await Promise.all(
|
|
Array.from({ length: concurrency }, async () => {
|
|
while (cursor < selectedCases.length) {
|
|
const item = selectedCases[cursor];
|
|
cursor += 1;
|
|
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: errorMessage,
|
|
id: item.id,
|
|
ok: false,
|
|
source: item.source,
|
|
};
|
|
results.push(failure);
|
|
console.error(`SCALE_VERIFY_CASE ${JSON.stringify(failure)}`);
|
|
}
|
|
}
|
|
})
|
|
);
|
|
results.sort((left, right) => String(left.id).localeCompare(String(right.id)));
|
|
await writeFile(
|
|
resolve(outputDir, "results.json"),
|
|
JSON.stringify(results, null, 2)
|
|
);
|
|
|
|
const panels: Buffer[] = [];
|
|
for (const item of selectedCases) {
|
|
for (const suffix of ["source", "model-mask", "overlay", "result"]) {
|
|
try {
|
|
const panel = await sharp(resolve(outputDir, `${item.id}-${suffix}.png`))
|
|
.resize(420, 320, { background: "#ffffff", fit: "contain" })
|
|
.png()
|
|
.toBuffer();
|
|
panels.push(await addLabel(panel, `${item.id} ${suffix}`));
|
|
} catch {
|
|
// Failed cases remain visible in results.json.
|
|
}
|
|
}
|
|
}
|
|
if (panels.length) {
|
|
const rows = Math.ceil(panels.length / 4);
|
|
await sharp({
|
|
create: {
|
|
background: "#e8e8e8",
|
|
channels: 3,
|
|
height: rows * 320,
|
|
width: 4 * 420,
|
|
},
|
|
})
|
|
.composite(
|
|
panels.map((input, index) => ({
|
|
input,
|
|
left: (index % 4) * 420,
|
|
top: Math.floor(index / 4) * 320,
|
|
}))
|
|
)
|
|
.jpeg({ quality: 88 })
|
|
.toFile(resolve(outputDir, "full-results.jpg"));
|
|
}
|
|
|
|
const passed = results.filter((result) => result.ok === true).length;
|
|
console.log(
|
|
`SCALE_VERIFY_SUMMARY ${JSON.stringify({ failed: results.length - passed, outputDir, passed, total: results.length })}`
|
|
);
|
|
}
|
|
|
|
main().catch((error) => {
|
|
console.error(error);
|
|
process.exitCode = 1;
|
|
});
|