サムネイルの見た目が少しずつズレていた — pHash と SSIM で画像アセットの回帰をエージェント運用に組み込む

import numpy as np
from PIL import Image
from skimage.metrics import structural_similarity as ssim
 
def ssim_score(path_a: str, path_b: str) -> float:
    """2枚の画像の SSIM を返す。1.0=完全一致。"""
    img_a = Image.open(path_a).convert("L")
    img_b = Image.open(path_b).convert("L")
    # SSIM は同一サイズが前提。候補側をベースラインに合わせる
    if img_b.size != img_a.size:
        img_b = img_b.resize(img_a.size, Image.LANCZOS)
    arr_a = np.asarray(img_a)
    arr_b = np.asarray(img_b)
    return float(ssim(arr_a, arr_b))
 
if __name__ == "__main__":
    s = ssim_score("baseline/thumb_001.jpg", "candidate/thumb_001.jpg")
    print(f"SSIM = {s:.4f}")

#!/usr/bin/env python3
"""image_gate.py — ベースラインと候補の画像アセットを知覚的に比較する。"""
import sys
import json
from pathlib import Path
import numpy as np
from PIL import Image
import imagehash
from skimage.metrics import structural_similarity as ssim
 
# しきい値（自分のデータで測り直すこと）
PHASH_WARN, PHASH_FAIL = 3, 7
SSIM_WARN, SSIM_FAIL = 0.99, 0.95
 
def compare(base: Path, cand: Path) -> dict:
    a, b = Image.open(base), Image.open(cand)
    dist = imagehash.phash(a) - imagehash.phash(b)
    ga = np.asarray(a.convert("L"))
    gb_img = b.convert("L")
    if gb_img.size != a.size:
        gb_img = gb_img.resize(a.size, Image.LANCZOS)
    score = float(ssim(ga, np.asarray(gb_img)))
    if dist >= PHASH_FAIL or score < SSIM_FAIL:
        verdict = "fail"
    elif dist >= PHASH_WARN or score < SSIM_WARN:
        verdict = "warn"
    else:
        verdict = "pass"
    return {"name": base.name, "phash": dist, "ssim": round(score, 4), "verdict": verdict}
 
def main(baseline_dir: str, candidate_dir: str) -> int:
    base_root, cand_root = Path(baseline_dir), Path(candidate_dir)
    results, worst = [], "pass"
    for base in sorted(base_root.glob("*.jpg")):
        cand = cand_root / base.name
        if not cand.exists():
            results.append({"name": base.name, "verdict": "missing"})
            worst = "fail"
            continue
        r = compare(base, cand)
        results.append(r)
        if r["verdict"] == "fail":
            worst = "fail"
        elif r["verdict"] == "warn" and worst != "fail":
            worst = "warn"
    Path("image_gate_report.json").write_text(json.dumps(results, indent=2, ensure_ascii=False))
    for r in results:
        print(f"{r['verdict']:>7}  {r['name']}  phash={r.get('phash','-')}  ssim={r.get('ssim','-')}")
    print(f"\n=== overall: {worst} ===")
    return 1 if worst == "fail" else 0
 
if __name__ == "__main__":
    sys.exit(main(sys.argv[1], sys.argv[2]))

## 画像パイプラインを変更したときのルール
 
`scripts/generate_thumbnails.py` や Pillow のリサンプリング・品質設定に
触れた場合は、変更後に必ず次を実行すること:
 
    python scripts/generate_thumbnails.py --out candidate/
    python image_gate.py baseline/ candidate/
 
overall が fail のときはマージ用の差分を作らず、image_gate_report.json を
読んで原因を説明し、しきい値ではなく生成側の設定を見直すこと。
baseline/ の更新は人間の承認なしに行わないこと。

name: image-asset-gate
on: [pull_request]
jobs:
  gate:
    runs-on: ubuntu-latest
    steps:
      - uses: actions/checkout@v4
      - uses: actions/setup-python@v5
        with:
          python-version: "3.12"
      - run: pip install pillow imagehash scikit-image numpy
      - run: python scripts/generate_thumbnails.py --out candidate/
      - run: python image_gate.py baseline/ candidate/
      - if: always()
        uses: actions/upload-artifact@v4
        with:
          name: image-gate-report
          path: image_gate_report.json