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Miscellaneous fixes (0.17 beta) (#21350)
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Browse Source 
* Fix genai callbacks in MQTT

* Cleanup cursor pointer for classification cards

* Cleanup

* Handle unknown SOCs for RKNN converter by only using known SOCs

* don't allow "none" as a classification class name

* change internal port user to admin and default unspecified username to viewer

* keep 5000 as anonymous user

* suppress tensorflow logging during classification training

* Always apply base log level suppressions for noisy third-party libraries even if no specific logConfig is provided

* remove decorator and specifically suppress TFLite delegate creation messages

---------

Co-authored-by: Josh Hawkins <32435876+hawkeye217@users.noreply.github.com>
This commit is contained in:
Nicolas Mowen
2025-12-18 15:12:10 -07:00
committed by GitHub
co-authored by Josh Hawkins
parent 6a0e31dcf9
commit e636449d56
20 changed files with 156 additions and 67 deletions
Download Patch File Download Diff File Expand all files Collapse all files
frigate/data_processing/real_time/bird.py
+8 -7
View File
@@ -13,7 +13,7 @@ from frigate.comms.event_metadata_updater import (
)
from frigate.config import FrigateConfig
from frigate.const import MODEL_CACHE_DIR
from frigate.log import redirect_output_to_logger
from frigate.log import suppress_stderr_during
from frigate.util.object import calculate_region
from ..types import DataProcessorMetrics
@@ -80,13 +80,14 @@ class BirdRealTimeProcessor(RealTimeProcessorApi):
except Exception as e:
logger.error(f"Failed to download {path}: {e}")
@redirect_output_to_logger(logger, logging.DEBUG)
def __build_detector(self) -> None:
self.interpreter = Interpreter(
model_path=os.path.join(MODEL_CACHE_DIR, "bird/bird.tflite"),
num_threads=2,
)
self.interpreter.allocate_tensors()
# Suppress TFLite delegate creation messages that bypass Python logging
with suppress_stderr_during("tflite_interpreter_init"):
self.interpreter = Interpreter(
model_path=os.path.join(MODEL_CACHE_DIR, "bird/bird.tflite"),
num_threads=2,
)
self.interpreter.allocate_tensors()
self.tensor_input_details = self.interpreter.get_input_details()
self.tensor_output_details = self.interpreter.get_output_details()
frigate/data_processing/real_time/custom_classification.py
+15 -13
View File
@@ -21,7 +21,7 @@ from frigate.config.classification import (
ObjectClassificationType,
)
from frigate.const import CLIPS_DIR, MODEL_CACHE_DIR
from frigate.log import redirect_output_to_logger
from frigate.log import suppress_stderr_during
from frigate.types import TrackedObjectUpdateTypesEnum
from frigate.util.builtin import EventsPerSecond, InferenceSpeed, load_labels
from frigate.util.object import box_overlaps, calculate_region
@@ -72,7 +72,6 @@ class CustomStateClassificationProcessor(RealTimeProcessorApi):
self.last_run = datetime.datetime.now().timestamp()
self.__build_detector()
@redirect_output_to_logger(logger, logging.DEBUG)
def __build_detector(self) -> None:
try:
from tflite_runtime.interpreter import Interpreter
@@ -89,11 +88,13 @@ class CustomStateClassificationProcessor(RealTimeProcessorApi):
self.labelmap = {}
return
self.interpreter = Interpreter(
model_path=model_path,
num_threads=2,
)
self.interpreter.allocate_tensors()
# Suppress TFLite delegate creation messages that bypass Python logging
with suppress_stderr_during("tflite_interpreter_init"):
self.interpreter = Interpreter(
model_path=model_path,
num_threads=2,
)
self.interpreter.allocate_tensors()
self.tensor_input_details = self.interpreter.get_input_details()
self.tensor_output_details = self.interpreter.get_output_details()
self.labelmap = load_labels(labelmap_path, prefill=0)
@@ -377,7 +378,6 @@ class CustomObjectClassificationProcessor(RealTimeProcessorApi):
self.__build_detector()
@redirect_output_to_logger(logger, logging.DEBUG)
def __build_detector(self) -> None:
model_path = os.path.join(self.model_dir, "model.tflite")
labelmap_path = os.path.join(self.model_dir, "labelmap.txt")
@@ -389,11 +389,13 @@ class CustomObjectClassificationProcessor(RealTimeProcessorApi):
self.labelmap = {}
return
self.interpreter = Interpreter(
model_path=model_path,
num_threads=2,
)
self.interpreter.allocate_tensors()
# Suppress TFLite delegate creation messages that bypass Python logging
with suppress_stderr_during("tflite_interpreter_init"):
self.interpreter = Interpreter(
model_path=model_path,
num_threads=2,
)
self.interpreter.allocate_tensors()
self.tensor_input_details = self.interpreter.get_input_details()
self.tensor_output_details = self.interpreter.get_output_details()
self.labelmap = load_labels(labelmap_path, prefill=0)