Miscellaneous fixes (#23394)

* serialize OpenVINO inference per process to prevent concurrent-inference segfault

* clean up

* add max scaling meta to login page

* add more detect section field messages

* fix icon layout in settings field messages

* tweak edit icon color
This commit is contained in:
Josh Hawkins
2026-06-04 12:48:58 -06:00
committed by GitHub
parent b751025339
commit a4f077b128
7 changed files with 114 additions and 32 deletions
+16 -13
View File
@@ -15,6 +15,9 @@ from frigate.util.rknn_converter import auto_convert_model, is_rknn_compatible
logger = logging.getLogger(__name__)
# Process-wide lock serializing all OpenVINO compile/inference calls
_OPENVINO_LOCK = threading.Lock()
def is_arm64_platform() -> bool:
"""Check if we're running on an ARM platform."""
@@ -326,19 +329,17 @@ class OpenVINOModelRunner(BaseModelRunner):
except Exception as e:
logger.debug(f"NPU_TURBO not supported by driver: {e}")
# Compile model
self.compiled_model = self.ov_core.compile_model(
model=model_path, device_name=device
)
# Compile model under the shared lock
with _OPENVINO_LOCK:
self.compiled_model = self.ov_core.compile_model(
model=model_path, device_name=device
)
# Create reusable inference request
self.infer_request = self.compiled_model.create_infer_request()
# Create reusable inference request
self.infer_request = self.compiled_model.create_infer_request()
self.input_tensor: ov.Tensor | None = None
# Thread lock to prevent concurrent inference (needed for JinaV2 which shares
# one runner between text and vision embeddings called from different threads)
self._inference_lock = threading.Lock()
if not self.complex_model:
try:
input_shape = self.compiled_model.inputs[0].get_shape()
@@ -382,9 +383,11 @@ class OpenVINOModelRunner(BaseModelRunner):
Returns:
List of output tensors
"""
# Lock prevents concurrent access to infer_request
# Needed for JinaV2: genai thread (text) + embeddings thread (vision)
with self._inference_lock:
# Shared lock serializes inference across every OpenVINO runner in this
# process — both the shared-runner JinaV2 case (genai text thread +
# embeddings vision thread) and distinct runners running on separate
# threads (e.g. the ArcFace face-model build vs the LPR detector).
with _OPENVINO_LOCK:
from frigate.embeddings.types import EnrichmentModelTypeEnum
if self.model_type in [EnrichmentModelTypeEnum.arcface.value]: