背景削除とマッティング：髪の毛も破綻しない切り抜き（実装/運用ガイド）

# docker-compose.yml — rembg（背景削除サービス）
version: "3.9"
services:
  rembg:
    image: ghcr.io/danielgatis/rembg:latest
    ports: ["7000:7000"]
    environment: [ "U2NET_HOME=/root/.u2net" ]
    restart: unless-stopped

// app/api/remove-bg/route.ts — Next.jsからrembgへ委譲
import { NextRequest, NextResponse } from "next/server";
export const runtime = "nodejs";
export const dynamic = "force-dynamic";
const REMBG = process.env.REMBG_URL ?? "http://localhost:7000";

export async function GET(req: NextRequest) {
  const { searchParams } = new URL(req.url);
  const src = searchParams.get("url");
  if (!src) return NextResponse.json({ error: "url is required" }, { status: 400 });

  const res = await fetch(src, { cache: "no-store" });
  if (!res.ok) return NextResponse.json({ error: "fetch failed" }, { status: 502 });
  const buf = Buffer.from(await res.arrayBuffer());

  const cut = await fetch(`${REMBG}/api/remove`, {
    method: "POST", headers: { "Content-Type": "application/octet-stream" }, body: buf,
  });
  if (!cut.ok) return NextResponse.json({ error: "rembg failed" }, { status: 502 });
  const png = Buffer.from(await cut.arrayBuffer());

  return new NextResponse(png, {
    headers: { "Content-Type": "image/png", "Cache-Control": "public, max-age=60, s-maxage=86400" },
  });
}

// scripts/composite-bg.ts — 色紙/グラデ/ぼかし合成
import sharp from "sharp";
import fs from "node:fs/promises";
import path from "node:path";

async function main() {
  const fgPath = process.argv[2];
  const out = process.argv[3] ?? "out";
  if (!fgPath) throw new Error("usage: tsx scripts/composite-bg.ts cutout.png [out]");
  const fg = sharp(fgPath).png();
  const { width, height } = await fg.metadata();
  if (!width || !height) throw new Error("invalid cutout");

  // 単色
  const solid = await sharp({ create: { width, height, channels: 3, background: "#0ea5e9" } }).jpeg({ quality: 92 }).toBuffer();
  // 擬似グラデ
  const grad = Buffer.alloc(width * height * 3);
  for (let y = 0; y < height; y++) {
    const t = y / (height - 1);
    const r = Math.round(14 + (255 - 14) * t);
    const g = Math.round(165 + (255 - 165) * t);
    const b = Math.round(233 + (255 - 233) * t);
    for (let x = 0; x < width; x++) { const i = (y * width + x) * 3; grad[i]=r; grad[i+1]=g; grad[i+2]=b; }
  }
  const gradImg = await sharp(grad, { raw: { width, height, channels: 3 } }).png().toBuffer();

  await sharp(solid).composite([{ input: await fg.toBuffer(), blend: "over" }]).toFile(out + "-solid.jpg");
  await sharp(gradImg).composite([{ input: await fg.toBuffer(), blend: "over" }]).toFile(out + "-grad.png");
  console.log("done:", out);
}
main().catch(e => { console.error(e); process.exit(1); });

// scripts/blurred-backdrop.ts — ぼかし背景合成
import sharp from "sharp";
export async function blurBackdrop(original: Buffer, cutout: Buffer) {
  const base = sharp(original).toColourspace("srgb");
  const meta = await base.metadata();
  if (!meta.width || !meta.height) throw new Error("invalid original");
  const bg = await base.clone().blur(25).toBuffer();
  return await sharp(bg).composite([{ input: cutout, blend: "over" }]).jpeg({ quality: 86, mozjpeg: true, progressive: true }).toBuffer();
}

// scripts/decontaminate-edge.ts — 縁の色かぶりを緩和（簡易）
import sharp from "sharp";
export async function decontaminate(input: Buffer) {
  const img = sharp(input).ensureAlpha();
  // 1) エッジ近傍を抽出（縮小→Sobel等が理想だが、ここではsigmaを使った近似）
  const edge = await img.clone().blur(1).toBuffer(); // 実務ではラプラシアンや距離場を利用
  // 2) 色相をわずかにニュートラルへ寄せる（過補正に注意）
  return await sharp(edge).modulate({ saturation: 0.9 }).toBuffer();
}