Improve Face Library Management (#17213)

* Set maximum number of face images to be kept

* Fix vertical camera scaling

* adjust wording

* Add attributes to search data

* Add button to train face from event

* Handle event id saving in API

frigate/api/classification.py

@@ -6,6 +6,7 @@ import random
 import shutil
 import string
 
+import cv2
 from fastapi import APIRouter, Depends, Request, UploadFile
 from fastapi.responses import JSONResponse
 from pathvalidate import sanitize_filename
@@ -14,9 +15,11 @@ from playhouse.shortcuts import model_to_dict
 
 from frigate.api.auth import require_role
 from frigate.api.defs.tags import Tags
+from frigate.config.camera import DetectConfig
 from frigate.const import FACE_DIR
 from frigate.embeddings import EmbeddingsContext
 from frigate.models import Event
+from frigate.util.path import get_event_snapshot
 
 logger = logging.getLogger(__name__)
 
@@ -87,16 +90,27 @@ def train_face(request: Request, name: str, body: dict = None):
         )
 
     json: dict[str, any] = body or {}
-    training_file = os.path.join(
-        FACE_DIR, f"train/{sanitize_filename(json.get('training_file', ''))}"
-    )
+    training_file_name = sanitize_filename(json.get("training_file", ""))
+    training_file = os.path.join(FACE_DIR, f"train/{training_file_name}")
+    event_id = json.get("event_id")
 
-    if not training_file or not os.path.isfile(training_file):
+    if not training_file_name and not event_id:
         return JSONResponse(
             content=(
                 {
                     "success": False,
-                    "message": f"Invalid filename or no file exists: {training_file}",
+                    "message": "A training file or event_id must be passed.",
+                }
+            ),
+            status_code=400,
+        )
+
+    if training_file_name and not os.path.isfile(training_file):
+        return JSONResponse(
+            content=(
+                {
+                    "success": False,
+                    "message": f"Invalid filename or no file exists: {training_file_name}",
                 }
             ),
             status_code=404,
@@ -106,7 +120,36 @@ def train_face(request: Request, name: str, body: dict = None):
     rand_id = "".join(random.choices(string.ascii_lowercase + string.digits, k=6))
     new_name = f"{sanitized_name}-{rand_id}.webp"
     new_file = os.path.join(FACE_DIR, f"{sanitized_name}/{new_name}")
-    shutil.move(training_file, new_file)
+
+    if training_file_name:
+        shutil.move(training_file, new_file)
+    else:
+        try:
+            event: Event = Event.get(Event.id == event_id)
+        except DoesNotExist:
+            return JSONResponse(
+                content=(
+                    {
+                        "success": False,
+                        "message": f"Invalid event_id or no event exists: {event_id}",
+                    }
+                ),
+                status_code=404,
+            )
+
+        snapshot = get_event_snapshot(event)
+        face_box = event.data["attributes"][0]["box"]
+        detect_config: DetectConfig = request.app.frigate_config.cameras[
+            event.camera
+        ].detect
+
+        # crop onto the face box minus the bounding box itself
+        x1 = int(face_box[0] * detect_config.width) + 2
+        y1 = int(face_box[1] * detect_config.height) + 2
+        x2 = x1 + int(face_box[2] * detect_config.width) - 4
+        y2 = y1 + int(face_box[3] * detect_config.height) - 4
+        face = snapshot[y1:y2, x1:x2]
+        cv2.imwrite(new_file, face)
 
     context: EmbeddingsContext = request.app.embeddings
     context.clear_face_classifier()
@@ -115,7 +158,7 @@ def train_face(request: Request, name: str, body: dict = None):
         content=(
             {
                 "success": True,
-                "message": f"Successfully saved {training_file} as {new_name}.",
+                "message": f"Successfully saved {training_file_name} as {new_name}.",
             }
         ),
         status_code=200,