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https://github.com/blakeblackshear/frigate.git
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Ersa Oktavian RamadanandNicolas Mowen
fd76eb6c6f
Allow audio classes to be grouped under a shared configured label. Keep audio overrides separate from object labels and retain only the highest-scoring grouped detection. Refs #23967
76 lines
2.3 KiB
Python
76 lines
2.3 KiB
Python
"""Tests for audio label mapping."""
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import threading
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import unittest
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from unittest.mock import Mock
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import numpy as np
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from frigate.events.audio import AudioTfl
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class TestAudioTfl(unittest.TestCase):
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def setUp(self):
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self.detector = AudioTfl.__new__(AudioTfl)
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self.detector.stop_event = threading.Event()
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self.detector._default_labels = {
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69: "dog",
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70: "bark",
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75: "whimper_dog",
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117: "dogs",
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}
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def test_update_labelmap_replaces_and_resets_overrides(self):
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self.detector.update_labelmap({69: "dogs", 70: "dogs"})
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assert self.detector.labels == {
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69: "dogs",
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70: "dogs",
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75: "whimper_dog",
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117: "dogs",
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}
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self.detector.update_labelmap({75: "whimper"})
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assert self.detector.labels == {
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69: "dog",
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70: "bark",
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75: "whimper",
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117: "dogs",
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}
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def test_detect_returns_highest_scoring_detection_for_grouped_label(self):
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self.detector.update_labelmap({69: "dogs", 70: "dogs", 75: "dogs"})
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self.detector._detect_raw = Mock(
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return_value=np.array(
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[
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[117, 0.95, -1, -1, -1, -1],
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[70, 0.9, -1, -1, -1, -1],
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[69, 0.8, -1, -1, -1, -1],
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[75, 0.7, -1, -1, -1, -1],
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],
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dtype=np.float32,
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)
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)
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detections = self.detector.detect(np.array([], dtype=np.float32))
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assert len(detections) == 1
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assert detections[0][0] == "dogs"
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self.assertAlmostEqual(detections[0][1], 0.95)
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def test_each_dog_audio_label_maps_to_grouped_label(self):
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self.detector.update_labelmap({69: "dogs", 70: "dogs", 75: "dogs"})
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for class_id in (69, 70, 75):
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with self.subTest(class_id=class_id):
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self.detector._detect_raw = Mock(
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return_value=np.array(
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[[class_id, 0.9, -1, -1, -1, -1]], dtype=np.float32
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)
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)
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detections = self.detector.detect(np.array([], dtype=np.float32))
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assert len(detections) == 1
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assert detections[0][0] == "dogs"
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self.assertAlmostEqual(detections[0][1], 0.9)
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