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Miscellaneous fixes (0.17 beta) (#21826)

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* revert other changes

* fix verified icon overlay in debug view list

* Add classification object debug logs

* Formatting

---------

Co-authored-by: Nicolas Mowen <nickmowen213@gmail.com>
This commit is contained in:
Josh Hawkins
2026-01-29 13:42:06 -06:00
committed by GitHub
parent 3b6814fbc9
commit b4520d9e2f
5 changed files with 425 additions and 10 deletions
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35
frigate/data_processing/real_time/custom_classification.py
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@@ -419,14 +419,21 @@ class CustomObjectClassificationProcessor(RealTimeProcessorApi):
"""
if object_id not in self.classification_history:
self.classification_history[object_id] = []
logger.debug(f"Created new classification history for {object_id}")
self.classification_history[object_id].append(
(current_label, current_score, current_time)
)
history = self.classification_history[object_id]
logger.debug(
f"History for {object_id}: {len(history)} entries, latest=({current_label}, {current_score})"
)
if len(history) < 3:
logger.debug(
f"History for {object_id} has {len(history)} entries, need at least 3"
)
return None, 0.0
label_counts = {}
@@ -445,14 +452,27 @@ class CustomObjectClassificationProcessor(RealTimeProcessorApi):
best_count = label_counts[best_label]
consensus_threshold = total_attempts * 0.6
logger.debug(
f"Consensus calc for {object_id}: label_counts={label_counts}, "
f"best_label={best_label}, best_count={best_count}, "
f"total={total_attempts}, threshold={consensus_threshold}"
)
if best_count < consensus_threshold:
logger.debug(
f"No consensus for {object_id}: {best_count} < {consensus_threshold}"
)
return None, 0.0
avg_score = sum(label_scores[best_label]) / len(label_scores[best_label])
if best_label == "none":
logger.debug(f"Filtering 'none' label for {object_id}")
return None, 0.0
logger.debug(
f"Consensus reached for {object_id}: {best_label} with avg_score={avg_score}"
)
return best_label, avg_score
def process_frame(self, obj_data, frame):
@@ -560,17 +580,30 @@ class CustomObjectClassificationProcessor(RealTimeProcessorApi):
)
if score < self.model_config.threshold:
logger.debug(f"Score {score} is less than threshold.")
logger.debug(
f"{self.model_config.name}: Score {score} < threshold {self.model_config.threshold} for {object_id}, skipping"
)
return
sub_label = self.labelmap[best_id]
logger.debug(
f"{self.model_config.name}: Object {object_id} (label={obj_data['label']}) passed threshold with sub_label={sub_label}, score={score}"
)
consensus_label, consensus_score = self.get_weighted_score(
object_id, sub_label, score, now
)
logger.debug(
f"{self.model_config.name}: get_weighted_score returned consensus_label={consensus_label}, consensus_score={consensus_score} for {object_id}"
)
if consensus_label is not None:
camera = obj_data["camera"]
logger.info(
f"{self.model_config.name}: Publishing sub_label={consensus_label} for {obj_data['label']} object {object_id} on {camera}"
)
if (
self.model_config.object_config.classification_type