blakeblackshear.frigate/frigate/api/classification.py
Nicolas Mowen cedd082b30 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
2024-11-19 12:11:07 -07:00

57 lines
1.6 KiB
Python

"""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,
)