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remove face embeddings

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This commit is contained in:
Nicolas Mowen 2024-11-21 17:10:08 -07:00
parent 503244fdd7
commit 646d878ccf
2 changed files with 3 additions and 62 deletions
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17
frigate/db/sqlitevecq.py
View File

@ -29,10 +29,6 @@ class SqliteVecQueueDatabase(SqliteQueueDatabase):
ids = ",".join(["?" for _ in event_ids]) ids = ",".join(["?" for _ in event_ids])
self.execute_sql(f"DELETE FROM vec_descriptions WHERE id IN ({ids})", event_ids) self.execute_sql(f"DELETE FROM vec_descriptions WHERE id IN ({ids})", event_ids)
def delete_embeddings_face(self, face_ids: list[str]) -> None:
ids = ",".join(["?" for _ in face_ids])
self.execute_sql(f"DELETE FROM vec_faces WHERE id IN ({ids})", face_ids)
def drop_embeddings_tables(self) -> None: def drop_embeddings_tables(self) -> None:
self.execute_sql(""" self.execute_sql("""
DROP TABLE vec_descriptions; DROP TABLE vec_descriptions;
@ -40,11 +36,8 @@ class SqliteVecQueueDatabase(SqliteQueueDatabase):
self.execute_sql(""" self.execute_sql("""
DROP TABLE vec_thumbnails; DROP TABLE vec_thumbnails;
""") """)
self.execute_sql("""
DROP TABLE vec_faces;
""")
def create_embeddings_tables(self, face_recognition: bool) -> None: def create_embeddings_tables(self) -> None:
"""Create vec0 virtual table for embeddings""" """Create vec0 virtual table for embeddings"""
self.execute_sql(""" self.execute_sql("""
CREATE VIRTUAL TABLE IF NOT EXISTS vec_thumbnails USING vec0( CREATE VIRTUAL TABLE IF NOT EXISTS vec_thumbnails USING vec0(
@ -58,11 +51,3 @@ class SqliteVecQueueDatabase(SqliteQueueDatabase):
description_embedding FLOAT[768] distance_metric=cosine description_embedding FLOAT[768] distance_metric=cosine
); );
""") """)
if face_recognition:
self.execute_sql("""
CREATE VIRTUAL TABLE IF NOT EXISTS vec_faces USING vec0(
id TEXT PRIMARY KEY,
face_embedding FLOAT[512] distance_metric=cosine
);
""")

48
frigate/embeddings/embeddings.py
View File

@ -68,7 +68,7 @@ class Embeddings:
self.requestor = InterProcessRequestor() self.requestor = InterProcessRequestor()
# Create tables if they don't exist # Create tables if they don't exist
self.db.create_embeddings_tables(self.config.face_recognition.enabled) self.db.create_embeddings_tables()
models = [ models = [
"jinaai/jina-clip-v1-text_model_fp16.onnx", "jinaai/jina-clip-v1-text_model_fp16.onnx",
@ -126,22 +126,6 @@ class Embeddings:
device="GPU" if config.semantic_search.model_size == "large" else "CPU", device="GPU" if config.semantic_search.model_size == "large" else "CPU",
) )
self.face_embedding = None
if self.config.face_recognition.enabled:
self.face_embedding = GenericONNXEmbedding(
model_name="facenet",
model_file="facenet.onnx",
download_urls={
"facenet.onnx": "https://github.com/NickM-27/facenet-onnx/releases/download/v1.0/facenet.onnx",
"facedet.onnx": "https://github.com/opencv/opencv_zoo/raw/refs/heads/main/models/face_detection_yunet/face_detection_yunet_2023mar_int8.onnx",
},
model_size="large",
model_type=ModelTypeEnum.face,
requestor=self.requestor,
device="GPU",
)
self.lpr_detection_model = None self.lpr_detection_model = None
self.lpr_classification_model = None self.lpr_classification_model = None
self.lpr_recognition_model = None self.lpr_recognition_model = None
@ -277,40 +261,12 @@ class Embeddings:
return embeddings return embeddings
def embed_face(self, label: str, thumbnail: bytes, upsert: bool = False) -> ndarray:
embedding = self.face_embedding(thumbnail)[0]
if upsert:
rand_id = "".join(
random.choices(string.ascii_lowercase + string.digits, k=6)
)
id = f"{label}-{rand_id}"
# write face to library
folder = os.path.join(FACE_DIR, label)
file = os.path.join(folder, f"{id}.webp")
os.makedirs(folder, exist_ok=True)
# save face image
with open(file, "wb") as output:
output.write(thumbnail)
self.db.execute_sql(
"""
INSERT OR REPLACE INTO vec_faces(id, face_embedding)
VALUES(?, ?)
""",
(id, serialize(embedding)),
)
return embedding
def reindex(self) -> None: def reindex(self) -> None:
logger.info("Indexing tracked object embeddings...") logger.info("Indexing tracked object embeddings...")
self.db.drop_embeddings_tables() self.db.drop_embeddings_tables()
logger.debug("Dropped embeddings tables.") logger.debug("Dropped embeddings tables.")
self.db.create_embeddings_tables(self.config.face_recognition.enabled) self.db.create_embeddings_tables()
logger.debug("Created embeddings tables.") logger.debug("Created embeddings tables.")
# Delete the saved stats file # Delete the saved stats file