feat: persist and display detected face crop thumbnails in workbench

src/rights_filter/server/http_app.py

@@ -60,6 +60,8 @@ def build_server(
                     self._file(store.knowledge_media_path(unquote(path.removeprefix("/knowledge-media/"))), untrusted=True)
                 elif path.startswith("/collected-media/"):
                     self._file(store.collected_media_path(unquote(path.removeprefix("/collected-media/"))), untrusted=True)
+                elif path.startswith("/face-crop-media/"):
+                    self._file(store.face_crop_media_path(unquote(path.removeprefix("/face-crop-media/"))), untrusted=True)
                 else:
                     self._static(path, static_root)
             except KeyError:

src/rights_filter/server/sqlite_store.py

@@ -7,6 +7,7 @@ import json
 import mimetypes
 import os
 import re
+import shutil
 import sqlite3
 from html.parser import HTMLParser
 from dataclasses import replace
@@ -402,6 +403,8 @@ class CopyrighterStore:
             else self.db_path.parent / "collections" / "images"
         )
         self.collection_public_prefix = collection_public_prefix.rstrip("/")
+        self.face_crop_image_dir = self.db_path.parent / "face-crops"
+        self.face_crop_public_prefix = "/face-crop-media"
         self.coverage_thresholds = {
             "coverageGoodRate": _bounded_int_env(
                 os.environ.get("COPYRIGHTER_COVERAGE_GOOD_THRESHOLD"),
@@ -675,6 +678,9 @@ class CopyrighterStore:
         self._normalize_saved_google_weak_labels_and_rescore(queue_id=queue_id)
         self._refresh_existing_submission_file_facts(image_store, queue_id=queue_id)
         self._refresh_existing_local_face_evidence(image_store, queue_id=queue_id)
+        for submission in self._all("submissions", queue_id=queue_id):
+            if "faceCrops" not in submission:
+                self._sync_face_crops(str(submission["id"]), image_store)
         self._rescore_all_submissions(queue_id=queue_id)
         self._ensure_llm_summaries_for_existing_source_evidence(queue_id=queue_id)
         self._sync_submission_provider_state(queue_id=queue_id)
@@ -730,6 +736,7 @@ class CopyrighterStore:
             ]
             self._sync_similar_reference_images(record["id"], run.evidence)
             self._sync_search_result_image_similarity(record["id"], run.evidence, image_store)
+            self._sync_face_crops(record["id"], image_store)
             self._auto_naver_search(record["id"], query_source_evidence, image_store)
             self._auto_google_custom_search(record["id"], query_source_evidence, image_store)
             self._ensure_llm_summary(record["id"])
@@ -779,6 +786,11 @@ class CopyrighterStore:
                 [(submission_id, queue_id) for submission_id in missing_ids],
             )
 
+        for submission_id in missing_ids:
+            crop_dir = self.face_crop_image_dir / submission_id
+            if crop_dir.exists():
+                shutil.rmtree(crop_dir, ignore_errors=True)
+
         for submission_id in missing_ids:
             self.add_audit_event(
                 actor="system",
@@ -1771,6 +1783,13 @@ class CopyrighterStore:
             raise ValueError("collected media path points outside image store")
         return path
 
+    def face_crop_media_path(self, relative_path: str) -> Path:
+        root = self.face_crop_image_dir.resolve()
+        path = (root / relative_path.lstrip("/")).resolve()
+        if path != root and root not in path.parents:
+            raise ValueError("face crop media path points outside image store")
+        return path
+
     def add_audit_event(self, actor: str, event: str, object_id: str, change: str) -> None:
         payload = {
             "timestamp": _now_label(),
@@ -1891,6 +1910,44 @@ class CopyrighterStore:
             )
             self._rescore_submission(submission_id)
 
+    def _sync_face_crops(
+        self,
+        submission_id: str,
+        image_store: LocalSubmissionImageStore | None,
+    ) -> None:
+        if image_store is None:
+            return
+        try:
+            original = image_store.image_payload(submission_id)
+        except Exception:
+            return
+
+        signal = HeuristicFacePersonDetector().detect(original)
+        crop_dir = self.face_crop_image_dir / submission_id
+        if crop_dir.exists():
+            for stale in crop_dir.glob("crop-*.jpg"):
+                stale.unlink()
+
+        face_crops: list[dict[str, Any]] = []
+        for index, box in enumerate(signal.face_boxes[:3], start=1):
+            crops = build_face_crop_derivatives(original, [box])
+            if not crops:
+                continue
+            crop_dir.mkdir(parents=True, exist_ok=True)
+            crop_path = crop_dir / f"crop-{index}.jpg"
+            crop_path.write_bytes(crops[0].content)
+            face_crops.append(
+                {
+                    "index": index,
+                    "url": f"{self.face_crop_public_prefix}/{submission_id}/crop-{index}.jpg",
+                    "box": [int(value) for value in box],
+                }
+            )
+
+        submission = self._get("submissions", submission_id)
+        submission["faceCrops"] = face_crops
+        self._put("submissions", submission_id, submission)
+
     def _refresh_existing_submission_file_facts(
         self,
         image_store: LocalSubmissionImageStore,
@@ -1933,6 +1990,7 @@ class CopyrighterStore:
         self._sync_similar_reference_images(submission_id, domain_evidence)
         self._increment_knowledge_contribution_counts(submission_id, domain_evidence)
         self._rescore_submission(submission_id)
+        self._sync_face_crops(submission_id, image_store)
         return domain_evidence
 
     def _rerun_google_image_search(
@@ -1998,11 +2056,21 @@ class CopyrighterStore:
         if not self.provider_runtime.face_crop_web_detection_enabled:
             return [], 0
 
-        signal = HeuristicFacePersonDetector().detect(original_image)
-        if not signal.face_boxes:
+        submission = self._get("submissions", submission_id)
+        stored_crops = submission.get("faceCrops")
+        if stored_crops is None:
+            signal = HeuristicFacePersonDetector().detect(original_image)
+            face_boxes: tuple = signal.face_boxes
+        else:
+            face_boxes = tuple(
+                tuple(int(value) for value in item.get("box", []))
+                for item in stored_crops
+                if len(item.get("box", [])) == 4
+            )
+        if not face_boxes:
             return [], 0
 
-        crops = build_face_crop_derivatives(original_image, signal.face_boxes)
+        crops = build_face_crop_derivatives(original_image, face_boxes)
         evidence: list[Evidence] = []
         call_count = 0
         for crop_index, crop in enumerate(crops, start=1):

tests/operator_gui/test_static_workbench.py

@@ -831,3 +831,13 @@ def test_registered_knowledge_panel_supports_search_filter_edit_and_lifecycle():
     assert "data-reactivate-kb" in script
     assert "재활성 사유 메모" in script
     assert "data-toggle-kb" not in script
+
+
+def test_workbench_shows_detected_face_crop_strip():
+    html = _read(INDEX)
+    script = _read(APP_JS)
+
+    assert 'id="face-crop-strip"' in html
+    assert "faceCrops" in script
+    assert "얼굴 영역" in script
+    assert "동일 인물 판정 아님" in script

tests/rights_filter/server/test_http_app.py

@@ -1208,3 +1208,44 @@ def test_knowledge_entry_update_deactivate_reactivate_lifecycle(tmp_path: Path):
         assert "Knowledge entry reactivated" in event_names
     finally:
         server.shutdown()
+
+
+class OneFaceBoxDetector:
+    def detect(self, image):
+        return FacePersonSignal(face_count=1, person_count=1, face_boxes=((40, 40, 120, 120),))
+
+
+def test_face_crops_are_persisted_served_and_listed_in_review(tmp_path: Path, monkeypatch):
+    monkeypatch.setattr(sqlite_store_module, "HeuristicFacePersonDetector", lambda: OneFaceBoxDetector())
+    static_dir, image_store, store = _png_fixtures(tmp_path)
+    server = build_server(host="127.0.0.1", port=0, store=store, image_store=image_store, static_dir=static_dir)
+    _start(server)
+    base = f"http://127.0.0.1:{server.server_port}"
+
+    try:
+        review = _json(base + "/api/submissions/SUB-API1/review")
+        assert review["faceCrops"], "face crops should be listed for a face submission"
+        crop = review["faceCrops"][0]
+        assert crop["index"] == 1
+        assert crop["box"] == [40, 40, 120, 120]
+        assert crop["url"].startswith("/face-crop-media/SUB-API1/")
+
+        with urlopen(base + crop["url"], timeout=5) as response:
+            content = response.read()
+        assert content[:3] == b"\xff\xd8\xff"  # JPEG magic bytes
+    finally:
+        server.shutdown()
+
+
+def test_face_crops_are_empty_for_undetectable_images(tmp_path: Path):
+    # autouse OneFaceDetector는 face_boxes를 반환하지 않고, SVG는 PIL로 크롭할 수 없다.
+    static_dir, image_store, store = _fixtures(tmp_path)
+    server = build_server(host="127.0.0.1", port=0, store=store, image_store=image_store, static_dir=static_dir)
+    _start(server)
+    base = f"http://127.0.0.1:{server.server_port}"
+
+    try:
+        review = _json(base + "/api/submissions/SUB-API1/review")
+        assert review.get("faceCrops", []) == []
+    finally:
+        server.shutdown()

web/operator-gui/app.js

@@ -1226,6 +1226,7 @@ function renderNoSelectedCase() {
   document.getElementById("floating-case-score").textContent = "대기";
   document.getElementById("file-facts").innerHTML = "";
   document.getElementById("similar-strip").innerHTML = "";
+  document.getElementById("face-crop-strip").innerHTML = "";
   document.getElementById("case-reasons").innerHTML = `<div class="empty-state">표시할 케이스가 없습니다.</div>`;
   document.getElementById("evidence-groups").innerHTML = `<div class="empty-state">API 연결 실패 또는 제출 이미지 없음 상태입니다.</div>`;
   document.getElementById("recommendation-box").innerHTML = `<span class="muted">실제 API 데이터가 로드될 때까지 판정하지 않습니다.</span>`;
@@ -1289,7 +1290,16 @@ function renderCaseReview() {
 
     .join("");
 
-
+  document.getElementById("face-crop-strip").innerHTML = (submission.faceCrops || [])
+    .map(
+      (crop) => `
+        <div class="similar-item face-crop-item">
+          <img src="${escapeHtml(crop.url)}" alt="얼굴 영역 ${escapeHtml(String(crop.index))} 크롭">
+          <span>얼굴 영역 ${escapeHtml(String(crop.index))} · 동일 인물 판정 아님</span>
+        </div>
+      `,
+    )
+    .join("");
 
   document.getElementById("case-reasons").innerHTML = renderEvidenceSummary(submission);
 

web/operator-gui/index.html

@@ -235,6 +235,7 @@
                 </figure>
                 <div class="fact-grid" id="file-facts"></div>
                 <div class="similar-strip" id="similar-strip" aria-label="유사 이미지"></div>
+                <div class="similar-strip face-crop-strip" id="face-crop-strip" aria-label="감지된 얼굴 영역"></div>
               </section>
 
               <section class="pane evidence-pane" aria-labelledby="evidence-pane-title">

web/operator-gui/styles.css

@@ -2789,3 +2789,8 @@ tbody tr.selected-row,
   display: flex;
   gap: 8px;
 }
+
+.face-crop-strip .face-crop-item img {
+  border: 1px solid #d4d4d8;
+  border-radius: 6px;
+}