src/faces.rs

@@ -287,6 +287,16 @@ pub struct CreateFaceReq {
     /// box and immediately picks a name from the autocomplete.
     #[serde(default)]
     pub person_id: Option<i32>,
+    /// Skip the embedding step. Set when the user wants to tag a region
+    /// the detector can't find a face in (back of head, profile partly
+    /// occluded, etc.). The row is stored with a zero-vector embedding,
+    /// which the cluster suggester filters on `norm <= 0` and auto-bind
+    /// cosine resolves to 0 against — so the row participates only as a
+    /// browse-by-person tag, not in similarity matching. The frontend
+    /// only sets this after a 422 from a strict create plus an explicit
+    /// operator confirmation.
+    #[serde(default)]
+    pub force: bool,
 }
 
 #[derive(Deserialize, Debug)]
@@ -2023,7 +2033,10 @@ async fn create_face_handler<D: FaceDao>(
     let span = global_tracer().start_with_context("faces.create_manual", &context);
     let span_context = opentelemetry::Context::current_with_span(span);
 
-    if !face_client.is_enabled() {
+    // The force path doesn't need Apollo at all (no embed call); the
+    // strict path does. Surface the disabled state only when we'd
+    // actually use the client.
+    if !body.force && !face_client.is_enabled() {
         return HttpResponse::ServiceUnavailable().body("face client disabled");
     }
 
@@ -2049,56 +2062,73 @@ async fn create_face_handler<D: FaceDao>(
         }
     };
 
-    // 2. Read full image, crop to bbox, encode as JPEG for transport.
+    // 2 + 3. Crop + embed via Apollo (strict path), or skip both (force).
-    let abs_path = library.resolve(&normalized_path);
+    //
-    let crop_bytes = match crop_image_to_bbox(
+    // Force is the "tag a face the detector can't see" path — back of
-        &abs_path,
+    // head, heavily-occluded profile, etc. We store a zero-vector
-        body.bbox.x,
+    // embedding under a sentinel model_version so the row participates
-        body.bbox.y,
+    // only as a browse-by-person tag: clustering filters norm<=0 (see
-        body.bbox.w,
+    // face_clustering._decode_b64_embedding) and auto-bind cosine
-        body.bbox.h,
+    // resolves to 0 / NaN, never crossing the threshold. Cluster
-    ) {
+    // suggester also groups by model_version so this sentinel never
-        Ok(b) => b,
+    // mixes with real buffalo_l rows.
-        Err(e) => {
+    let (embedding_bytes, model_version, confidence) = if body.force {
-            warn!("crop_image_to_bbox failed for {:?}: {:?}", abs_path, e);
+        info!(
-            return HttpResponse::BadRequest().body(format!("cannot crop photo: {}", e));
+            "manual face (force): skipping detection for {:?} bbox=({},{},{},{})",
-        }
+            normalized_path, body.bbox.x, body.bbox.y, body.bbox.w, body.bbox.h
-    };
+        );
+        (vec![0u8; 2048], "manual_no_embed".to_string(), 0.0_f32)
+    } else {
+        let abs_path = library.resolve(&normalized_path);
+        let crop_bytes = match crop_image_to_bbox(
+            &abs_path,
+            body.bbox.x,
+            body.bbox.y,
+            body.bbox.w,
+            body.bbox.h,
+        ) {
+            Ok(b) => b,
+            Err(e) => {
+                warn!("crop_image_to_bbox failed for {:?}: {:?}", abs_path, e);
+                return HttpResponse::BadRequest().body(format!("cannot crop photo: {}", e));
+            }
+        };
 
-    // 3. Send the crop to Apollo for embedding extraction.
+        let meta = DetectMeta {
-    let meta = DetectMeta {
+            content_hash: hash.clone(),
-        content_hash: hash.clone(),
+            library_id: library.id,
-        library_id: library.id,
+            rel_path: normalized_path.clone(),
-        rel_path: normalized_path.clone(),
+            orientation: None,
-        orientation: None,
+            model_version: None,
-        model_version: None,
+        };
-    };
+        let detect = match face_client.embed(crop_bytes, meta).await {
-    let detect = match face_client.embed(crop_bytes, meta).await {
+            Ok(r) => r,
-        Ok(r) => r,
+            Err(FaceDetectError::Permanent(e)) => {
-        Err(FaceDetectError::Permanent(e)) => {
+                return HttpResponse::UnprocessableEntity().body(format!("{}", e));
-            return HttpResponse::UnprocessableEntity().body(format!("{}", e));
+            }
-        }
+            Err(FaceDetectError::Transient(e)) => {
-        Err(FaceDetectError::Transient(e)) => {
+                return HttpResponse::ServiceUnavailable().body(format!("{}", e));
-            return HttpResponse::ServiceUnavailable().body(format!("{}", e));
+            }
-        }
+            Err(FaceDetectError::Disabled) => {
-        Err(FaceDetectError::Disabled) => {
+                return HttpResponse::ServiceUnavailable().body("face client disabled");
-            return HttpResponse::ServiceUnavailable().body("face client disabled");
+            }
-        }
+        };
-    };
 
-    let detected = match detect.faces.first() {
+        let detected = match detect.faces.first() {
-        Some(f) => f.clone(),
+            Some(f) => f.clone(),
-        None => {
+            None => {
-            // Apollo would have returned 422 on no_face_in_crop; defensive.
+                // Apollo would have returned 422 on no_face_in_crop; defensive.
-            return HttpResponse::UnprocessableEntity().body("no face in crop");
+                return HttpResponse::UnprocessableEntity().body("no face in crop");
-        }
+            }
-    };
+        };
-    let embedding_bytes = match detected.decode_embedding() {
+        let bytes = match detected.decode_embedding() {
-        Ok(b) => b,
+            Ok(b) => b,
-        Err(e) => {
+            Err(e) => {
-            warn!("manual face: decode embedding failed: {:?}", e);
+                warn!("manual face: decode embedding failed: {:?}", e);
-            return HttpResponse::BadGateway().body("invalid embedding from face service");
+                return HttpResponse::BadGateway().body("invalid embedding from face service");
-        }
+            }
+        };
+        (bytes, detect.model_version, detected.confidence)
     };
 
     // 4. Insert the manual row using the bbox the user drew (NOT the
@@ -2114,11 +2144,11 @@ async fn create_face_handler<D: FaceDao>(
             rel_path: normalized_path,
             bbox: Some((body.bbox.x, body.bbox.y, body.bbox.w, body.bbox.h)),
             embedding: Some(embedding_bytes),
-            confidence: Some(detected.confidence),
+            confidence: Some(confidence),
             source: "manual".to_string(),
             person_id: body.person_id,
             status: "detected".to_string(),
-            model_version: detect.model_version,
+            model_version,
         },
     ) {
         Ok(r) => r,