品質ラダーで主観評価をキャリブレーションするワークショップ手法

{ "image":"hero_ui", "candidate":"cq42", "rater":"anon-7c2", "time":1725601112 }

interface Vote { image:string; candidate:string; rater:string; time:number }
export function consolidate(votes:Vote[]){
  const by = new Map<string, Vote[]>();
  for (const v of votes){ if(!by.has(v.image)) by.set(v.image,[]); by.get(v.image)!.push(v); }
  return [...by].map(([image, vs])=>{
    const counts = Object.entries(vs.reduce((a,c)=> (a[c.candidate]=(a[c.candidate]||0)+1, a), {} as Record<string,number>)).sort((a,b)=>b[1]-a[1]);
    return { image, top: counts[0][0], spread: counts[0][1] - (counts[1]?.[1]||0), total: vs.length };
  });
}

export function outlierImages(votes:Vote[], threshold=2){
  const by = new Map<string, Vote[]>();
  for (const v of votes){ if(!by.has(v.image)) by.set(v.image,[]); by.get(v.image)!.push(v); }
  return [...by].filter(([img, vs])=>{
    const counts = Object.values(vs.reduce((a,c)=> (a[c.candidate]=(a[c.candidate]||0)+1, a), {} as Record<string,number>));
    const sorted = counts.slice().sort((a,b)=>b-a);
    return (sorted[0] - (sorted[1]||0)) < threshold;
  }).map(([img])=>img);
}

// scripts/export-golden.ts
import fs from 'node:fs';
import cp from 'node:child_process';
const ladder = JSON.parse(fs.readFileSync('votes-consolidated.json','utf-8'));
for (const r of ladder){
  const src = `renders/${r.image}_${r.top}.png`;
  const dest = `golden/quality-ladder/${r.image}.png`;
  cp.execSync('cp '+src+' '+dest);
}

node scripts/ladder-q-pick.js --image hero_ui.png --out current.json
node scripts/ladder-diff.js golden/quality-ladder/hero_ui.png current.json --delta-q 1