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https://github.com/blakeblackshear/frigate.git
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Face recognition improvements (#17387)
* Increase frequency of updates when internal face detection is used * Adjust number of required faces based on detection type * Adjust min_score config to unknown_score * Only for person * Improve typing * Update face rec docs * Cleanup ui colors * Cleanup
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+16
-4
@@ -5,7 +5,7 @@ import logging
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import os
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import threading
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from collections import defaultdict
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from typing import Callable
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from typing import Any, Callable
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import cv2
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import numpy as np
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@@ -53,8 +53,19 @@ class CameraState:
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self.callbacks = defaultdict(list)
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self.ptz_autotracker_thread = ptz_autotracker_thread
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self.prev_enabled = self.camera_config.enabled
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self.requires_face_detection = (
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self.config.face_recognition.enabled
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and "face" not in self.config.objects.all_objects
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)
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def get_current_frame(self, draw_options={}):
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def get_max_update_frequency(self, obj: TrackedObject) -> int:
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return (
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1
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if self.requires_face_detection and obj.obj_data["label"] == "person"
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else 5
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)
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def get_current_frame(self, draw_options: dict[str, Any] = {}):
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with self.current_frame_lock:
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frame_copy = np.copy(self._current_frame)
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frame_time = self.current_frame_time
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@@ -283,11 +294,12 @@ class CameraState:
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updated_obj.last_updated = frame_time
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# if it has been more than 5 seconds since the last thumb update
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# if it has been more than max_update_frequency seconds since the last thumb update
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# and the last update is greater than the last publish or
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# the object has changed significantly
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if (
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frame_time - updated_obj.last_published > 5
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frame_time - updated_obj.last_published
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> self.get_max_update_frequency(updated_obj)
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and updated_obj.last_updated > updated_obj.last_published
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) or significant_update:
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# call event handlers
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