Deploy LeeChard

app/api/v1/endpoints/photos.py

@@ -42,6 +42,17 @@ ALLOWED_MIME = {"image/jpeg", "image/png", "image/webp"}
 MAX_BYTES = 20 * 1024 * 1024
 LOCAL_HOSTS = {"localhost", "127.0.0.1", "0.0.0.0", "::1"}
 
+# Operator gender pick (upload screen) -> canonical "man"/"woman". Anything else
+# (blank, "auto", garbage) -> None so the engine falls back to InsightFace auto-detect.
+_GENDER_ALIASES = {
+    "man": "man", "male": "man", "m": "man", "남": "man", "남자": "man", "남성": "man",
+    "woman": "woman", "female": "woman", "f": "woman", "여": "woman", "여자": "woman", "여성": "woman",
+}
+
+
+def _normalize_gender(value: str | None) -> str | None:
+    return _GENDER_ALIASES.get((value or "").strip().lower())
+
 
 def _utcnow() -> datetime:
     return datetime.now(timezone.utc)
@@ -141,6 +152,7 @@ async def upload_photo(
     qr_delivery_allowed: bool = Form(default=True),
     marketing_allowed: bool = Form(default=False),
     client_name: str | None = Form(default="Guest"),
+    gender: str | None = Form(default=None),
     access_code: str | None = Form(default=None),
     idempotency_key: str | None = Header(default=None, alias="Idempotency-Key"),
     db: Session = Depends(get_db),
@@ -186,6 +198,7 @@ async def upload_photo(
             shop_id=effective_shop,
             tablet_id=tablet_id,
             idempotency_key=idempotency_key,
+            requested_gender=_normalize_gender(gender),
         )
     except IntegrityError:
         db.rollback()

app/models/photo_task.py

@@ -76,6 +76,10 @@ class PhotoTask(Base):
         TaskStatusType, default=TaskStatus.UPLOADED, nullable=False, index=True
     )
 
+    # 직원이 업로드 화면에서 고른 성별("man"/"woman"). NULL=자동판정.
+    # InsightFace 오판(여성→남성 등)으로 잘못된 성별 경로/프롬프트가 적용되는 것을 막는다.
+    requested_gender: Mapped[str | None] = mapped_column(String(8), nullable=True)
+
     # ── 디스패치 / enqueue 복구 ──────────────────────────
     celery_job_id: Mapped[str | None] = mapped_column(String(64), nullable=True)
 

app/services/comfyui_client.py

@@ -93,6 +93,9 @@ class FaceSwapRequest:
     mood: str | None = None
     prompt: str | None = None
     simulate: str | None = None
+    # Operator-picked gender ("man"/"woman") from the upload screen; None -> auto-detect.
+    # Overrides InsightFace so a misread face still gets the correct gender-locked route.
+    requested_gender: str | None = None
 
 
 @dataclass

app/services/falinpaint_beautify.py

@@ -535,7 +535,9 @@ def nanobanana_prompt_for(gender: str) -> str:
     )
 
 
-def beautify_with_nanobanana_fal(source_bytes: bytes, *, prompt: str | None = None, **_opts):
+def beautify_with_nanobanana_fal(
+    source_bytes: bytes, *, prompt: str | None = None, gender: str | None = None, **_opts
+):
     """APPROVED production engine: fal Nano Banana instruction-edit beautify.
 
     Full-frame (no mask): the model itself keeps hair/clothing/background because the
@@ -544,6 +546,9 @@ def beautify_with_nanobanana_fal(source_bytes: bytes, *, prompt: str | None = No
     (final_png_bytes, metrics). Raises FalUnavailable when FAL_KEY is absent or the
     hosted call fails. Extra **_opts are accepted/ignored so the worker can pass the
     shared settings dict unchanged.
+
+    `gender` ("man"/"woman") lets the operator pin the gender; when given it overrides
+    auto-detection so a misread face still gets the correct gender-locked prompt.
     """
     from PIL import Image
 
@@ -551,7 +556,13 @@ def beautify_with_nanobanana_fal(source_bytes: bytes, *, prompt: str | None = No
         raise FalUnavailable("FAL_KEY not set; no network call made")
     src = normalize_image_orientation_bytes(source_bytes)
     # Gender for a gender-locked prompt (best-effort; full-frame edit needs no mask).
-    _box, gender, _eyes = detect_face_and_gender(_downscale(src, int(DEFAULTS["max_size"])))
+    # Operator-supplied gender wins; otherwise fall back to InsightFace auto-detect.
+    known = (gender or "").strip().lower()
+    if known in ("man", "woman"):
+        gender, gender_source = known, "operator"
+    else:
+        _box, gender, _eyes = detect_face_and_gender(_downscale(src, int(DEFAULTS["max_size"])))
+        gender_source = "auto"
     used_prompt = prompt or nanobanana_prompt_for(gender)
 
     raw = run_fal_nanobanana_edit(src, used_prompt)
@@ -568,6 +579,7 @@ def beautify_with_nanobanana_fal(source_bytes: bytes, *, prompt: str | None = No
         "engine": "fal-nanobanana-beautify",
         "hosted_model": fal_nanobanana_model(),
         "gender_detected": gender or "unknown",
+        "gender_source": gender_source,
         "edit_mode": "full_frame_instruction_edit",
         "human_qa_required": "YES",
         "pilot_ready": "NOT CONFIRMED",
@@ -575,7 +587,9 @@ def beautify_with_nanobanana_fal(source_bytes: bytes, *, prompt: str | None = No
     return final, metrics
 
 
-def beautify_with_kontext_composite(source_bytes: bytes, *, prompt: str | None = None, **_opts):
+def beautify_with_kontext_composite(
+    source_bytes: bytes, *, prompt: str | None = None, gender: str | None = None, **_opts
+):
     """SALON engine: strong FLUX-Kontext face transform, then composite the ORIGINAL
     hair / background / clothing / glasses back over it so they are preserved 100%.
 
@@ -583,13 +597,20 @@ def beautify_with_kontext_composite(source_bytes: bytes, *, prompt: str | None =
     Nano Banana leaves unchanged) but it restyles hair/background — so we keep only
     the new face-skin region and take everything else from the original. Returns
     (final_png_bytes, metrics). Raises FalUnavailable if FAL_KEY is absent / the call
-    fails. If segmentation is unavailable the Kontext image is returned as-is."""
+    fails. If segmentation is unavailable the Kontext image is returned as-is.
+
+    `gender` ("man"/"woman") pins the gender (operator override); otherwise auto-detect."""
     from PIL import Image
 
     if not fal_real_enabled():
         raise FalUnavailable("FAL_KEY not set; no network call made")
     src = normalize_image_orientation_bytes(source_bytes)
-    _box, gender, _eyes = detect_face_and_gender(_downscale(src, int(DEFAULTS["max_size"])))
+    known = (gender or "").strip().lower()
+    if known in ("man", "woman"):
+        gender, gender_source = known, "operator"
+    else:
+        _box, gender, _eyes = detect_face_and_gender(_downscale(src, int(DEFAULTS["max_size"])))
+        gender_source = "auto"
     used_prompt = prompt or nanobanana_prompt_for(gender)
 
     raw = run_fal_kontext_edit(src, used_prompt)  # strong face transform (may restyle hair/bg)
@@ -609,6 +630,7 @@ def beautify_with_kontext_composite(source_bytes: bytes, *, prompt: str | None =
         "engine": "fal-kontext-composite",
         "hosted_model": fal_kontext_model(),
         "gender_detected": gender or "unknown",
+        "gender_source": gender_source,
         "edit_mode": "kontext_face_then_original_hair_composite",
         "human_qa_required": "YES",
         "pilot_ready": "NOT CONFIRMED",
@@ -632,19 +654,31 @@ KONTEXT_MAN_NATURAL_PROMPT = (
 )
 
 
-def beautify_hybrid(source_bytes: bytes, *, prompt: str | None = None, **_opts):
+def beautify_hybrid(
+    source_bytes: bytes, *, prompt: str | None = None, gender: str | None = None, **_opts
+):
     """Per-gender routing (Option 1: keep hair/glasses + natural light glow-up):
     - MEN  -> Kontext composite with a NATURAL prompt (nano-banana barely moves male faces;
               a strong prompt melts the composite, so men stay photoreal + subtle).
     - WOMEN/unknown -> nano-banana (more dynamic + natural on female faces).
-    Both preserve the original hair/glasses. Returns (final_png_bytes, metrics)."""
+    Both preserve the original hair/glasses. Returns (final_png_bytes, metrics).
+
+    `gender` ("man"/"woman") is the operator's pick from the upload screen. When given it
+    decides the route AND the prompt — so a face InsightFace misreads (e.g. a woman read as
+    a man, then masculinized by the man prompt) no longer happens. Empty/None -> auto-detect."""
     if not fal_real_enabled():
         raise FalUnavailable("FAL_KEY not set; no network call made")
     src = normalize_image_orientation_bytes(source_bytes)
-    _box, gender, _eyes = detect_face_and_gender(_downscale(src, int(DEFAULTS["max_size"])))
-    if gender == "man":
-        return beautify_with_kontext_composite(source_bytes, prompt=prompt or KONTEXT_MAN_NATURAL_PROMPT)
-    return beautify_with_nanobanana_fal(source_bytes, prompt=prompt)
+    known = (gender or "").strip().lower()
+    if known in ("man", "woman"):
+        routed = known
+    else:
+        _box, routed, _eyes = detect_face_and_gender(_downscale(src, int(DEFAULTS["max_size"])))
+    if routed == "man":
+        return beautify_with_kontext_composite(
+            source_bytes, prompt=prompt or KONTEXT_MAN_NATURAL_PROMPT, gender=routed
+        )
+    return beautify_with_nanobanana_fal(source_bytes, prompt=prompt, gender=routed)
 
 
 def settings_from_env() -> dict:

app/services/hybrid_client.py

@@ -40,7 +40,7 @@ class HybridBeautifyClient(AIClient):
             )
 
         try:
-            final, metrics = beautify_hybrid(req.image_bytes)
+            final, metrics = beautify_hybrid(req.image_bytes, gender=req.requested_gender)
         except FalUnavailable as exc:
             raise AIProviderError(f"Hybrid beautify failed: {exc}", code="FAL_ERROR") from exc
 
@@ -59,6 +59,7 @@ class HybridBeautifyClient(AIClient):
                 "denied_operations": DENIED_OPERATIONS,
                 "engine_used": metrics.get("engine"),
                 "gender_detected": metrics.get("gender_detected"),
+                "gender_source": metrics.get("gender_source"),
             },
             qa=qa,
         )

app/services/kontext_client.py

@@ -41,7 +41,9 @@ class KontextCompositeClient(AIClient):
             )
 
         try:
-            final, metrics = beautify_with_kontext_composite(req.image_bytes)
+            final, metrics = beautify_with_kontext_composite(
+                req.image_bytes, gender=req.requested_gender
+            )
         except FalUnavailable as exc:
             raise AIProviderError(f"Kontext beautify failed: {exc}", code="FAL_ERROR") from exc
 

app/services/nanobanana_client.py

@@ -43,7 +43,9 @@ class NanoBananaFalClient(AIClient):
             )
 
         try:
-            final, metrics = beautify_with_nanobanana_fal(req.image_bytes)
+            final, metrics = beautify_with_nanobanana_fal(
+                req.image_bytes, gender=req.requested_gender
+            )
         except FalUnavailable as exc:
             raise AIProviderError(f"Nano Banana beautify failed: {exc}", code="FAL_ERROR") from exc
 

app/services/task_repo.py

@@ -129,6 +129,7 @@ def create_task(
     tablet_id: str | None = None,
     idempotency_key: str | None = None,
     task_id: str | None = None,
+    requested_gender: str | None = None,
 ) -> PhotoTask:
     """task + outbox 이벤트를 같은 트랜잭션에서 생성.
 
@@ -144,6 +145,7 @@ def create_task(
         shop_id=shop_id or salon_id,
         tablet_id=tablet_id,
         idempotency_key=idempotency_key,
+        requested_gender=requested_gender,
         original_key=original_key,
         original_mime=original_mime,
         original_expires_at=_utcnow() + timedelta(hours=settings.original_ttl_hours),

app/workers/tasks.py

@@ -112,6 +112,7 @@ def process_photo(self, task_id: str, dispatch_version: int = 0) -> str:
                     image_bytes=original,
                     mime=task.original_mime or "image/jpeg",
                     face_boxes=in_qc.face_boxes,
+                    requested_gender=task.requested_gender,
                 )
             )
         except Exception as exc:  # noqa: BLE001

static/css/styles.css

@@ -98,6 +98,13 @@ body {
 .chip { background: var(--card); border: 1px solid var(--line); color: var(--muted); font-size: 12.5px; padding: 7px 13px; border-radius: 999px; }
 .chip.gold { color: var(--gold-deep); border-color: #e7d6c4; background: #fbf3ea; font-weight: 600; }
 
+/* --- gender pick (capture confirm) --- */
+.gender-pick { display: flex; align-items: center; gap: 12px; margin-bottom: 12px; }
+.gender-pick-label { font-size: 13px; color: var(--muted); font-weight: 600; flex: none; }
+.gender-seg { display: flex; flex: 1; gap: 6px; padding: 4px; background: var(--ivory); border: 1px solid var(--line); border-radius: 999px; }
+.gender-opt { flex: 1; padding: 9px 0; border: none; background: none; border-radius: 999px; font-family: var(--sans); font-size: 14px; font-weight: 600; color: var(--muted); cursor: pointer; transition: background .15s ease, color .15s ease; }
+.gender-opt.active { background: var(--gold); color: #fff; box-shadow: 0 3px 10px rgba(200, 169, 138, .35); }
+
 /* --- loading --- */
 #screen-loading { background: var(--charcoal); }
 .loading-bg { position: absolute; inset: 0; background-size: cover; background-position: center; filter: blur(26px) brightness(.5); transform: scale(1.15); }

static/index.html

@@ -70,6 +70,14 @@
             <button class="btn btn-text" id="btn-gallery">갤러리에서 선택</button>
           </div>
           <div id="capture-confirm" hidden>
+            <div class="gender-pick" id="gender-pick" role="group" aria-label="성별 선택">
+              <span class="gender-pick-label">성별</span>
+              <div class="gender-seg">
+                <button type="button" class="gender-opt active" data-gender="auto">자동</button>
+                <button type="button" class="gender-opt" data-gender="woman">여성</button>
+                <button type="button" class="gender-opt" data-gender="man">남성</button>
+              </div>
+            </div>
             <button class="btn btn-primary" id="btn-use">이 사진으로</button>
             <button class="btn btn-text" id="btn-retake">다시 찍기</button>
           </div>

static/js/app.js

@@ -11,6 +11,7 @@ const state = {
   shareUrl: null,
   deliveryAvailable: true,
   accessCode: "",
+  gender: "auto",     // operator pick on capture screen: "auto" | "woman" | "man"
   retryTo: "capture",
 };
 
@@ -86,6 +87,21 @@ $("#btn-shoot").addEventListener("click", () => { input.setAttribute("capture",
 $("#btn-gallery").addEventListener("click", () => { input.removeAttribute("capture"); input.click(); });
 $("#btn-retake").addEventListener("click", resetCapture);
 
+// operator picks gender (overrides auto-detect so a misread face routes correctly)
+document.querySelectorAll("#gender-pick .gender-opt").forEach((b) => {
+  b.addEventListener("click", () => {
+    document.querySelectorAll("#gender-pick .gender-opt").forEach((o) => o.classList.remove("active"));
+    b.classList.add("active");
+    state.gender = b.dataset.gender || "auto";
+  });
+});
+
+function resetGenderPick() {
+  state.gender = "auto";
+  document.querySelectorAll("#gender-pick .gender-opt").forEach((o) =>
+    o.classList.toggle("active", o.dataset.gender === "auto"));
+}
+
 input.addEventListener("change", (ev) => {
   const f = ev.target.files && ev.target.files[0];
   if (!f) return;
@@ -108,6 +124,7 @@ function resetCapture() {
   $("#capture-hint").textContent = "얼굴이 잘 보이게 정면으로 맞춰 주세요";
   $("#capture-actions").hidden = false;
   $("#capture-confirm").hidden = true;
+  resetGenderPick();
   input.value = "";
 }
 
@@ -125,6 +142,7 @@ async function startProcessing() {
   data.append("salon_id", "leechard_pro");
   data.append("qr_delivery_allowed", $("#c-qr").checked ? "true" : "false");
   data.append("marketing_allowed", $("#c-mkt").checked ? "true" : "false");
+  if (state.gender && state.gender !== "auto") data.append("gender", state.gender);
   data.append("access_code", state.accessCode || "");
   try {
     const up = await api(`${API}/upload`, { method: "POST", body: data });