Face recognition backend (#14495)

* Add basic config and face recognition table

* Reconfigure updates processing to handle face

* Crop frame to face box

* Implement face embedding calculation

* Get matching face embeddings

* Add support face recognition based on existing faces

* Use arcface face embeddings instead of generic embeddings model

* Add apis for managing faces

* Implement face uploading API

* Build out more APIs

* Add min area config

* Handle larger images

* Add more debug logs

* fix calculation

* Reduce timeout

* Small tweaks

* Use webp images

* Use facenet model

frigate/api/classification.py

@@ -0,0 +1,56 @@
+"""Object classification APIs."""
+
+import logging
+
+from fastapi import APIRouter, Request, UploadFile
+from fastapi.responses import JSONResponse
+
+from frigate.api.defs.tags import Tags
+from frigate.embeddings import EmbeddingsContext
+
+logger = logging.getLogger(__name__)
+
+router = APIRouter(tags=[Tags.events])
+
+
+@router.get("/faces")
+def get_faces():
+    return JSONResponse(content={"message": "there are faces"})
+
+
+@router.post("/faces/{name}")
+async def register_face(request: Request, name: str, file: UploadFile):
+    # if not file.content_type.startswith("image"):
+    #    return JSONResponse(
+    #        status_code=400,
+    #        content={
+    #            "success": False,
+    #            "message": "Only an image can be used to register a face.",
+    #        },
+    #    )
+
+    context: EmbeddingsContext = request.app.embeddings
+    context.register_face(name, await file.read())
+    return JSONResponse(
+        status_code=200,
+        content={"success": True, "message": "Successfully registered face."},
+    )
+
+
+@router.delete("/faces")
+def deregister_faces(request: Request, body: dict = None):
+    json: dict[str, any] = body or {}
+    list_of_ids = json.get("ids", "")
+
+    if not list_of_ids or len(list_of_ids) == 0:
+        return JSONResponse(
+            content=({"success": False, "message": "Not a valid list of ids"}),
+            status_code=404,
+        )
+
+    context: EmbeddingsContext = request.app.embeddings
+    context.delete_face_ids(list_of_ids)
+    return JSONResponse(
+        content=({"success": True, "message": "Successfully deleted faces."}),
+        status_code=200,
+    )