Audio events (#6848)
* Initial audio classification model implementation * fix mypy * Keep audio labelmap local * Cleanup * Start adding config for audio * Add the detector * Add audio detection process keypoints * Build out base config * Load labelmap correctly * Fix config bugs * Start audio process * Fix startup issues * Try to cleanup restarting * Add ffmpeg input args * Get audio detection working * Save event to db * End events if not heard for 30 seconds * Use not heard config * Stop ffmpeg when shutting down * Fixes * End events correctly * Use api instead of event queue to save audio events * Get events working * Close threads when stop event is sent * remove unused * Only start audio process if at least one camera is enabled * Add const for float * Cleanup labelmap * Add audio icon in frontend * Add ability to toggle audio with mqtt * Set initial audio value * Fix audio enabling * Close logpipe * Isort * Formatting * Fix web tests * Fix web tests * Handle cases where args are a string * Remove log * Cleanup process close * Use correct field * Simplify if statement * Use var for localhost * Add audio detectors docs * Add restream docs to mention audio detection * Add full config docs * Fix links to other docs --------- Co-authored-by: Jason Hunter <hunterjm@gmail.com>pull/6978/head
Nicolas Mowen
11 months ago
committed by
GitHub
parent
f1dc3a639c
commit
c3b313a70d
28 changed files with 1090 additions and 69 deletions
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speech |
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speech |
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speech |
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speech |
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babbling |
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speech |
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yell |
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bellow |
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whoop |
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yell |
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yell |
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yell |
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whispering |
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laughter |
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laughter |
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laughter |
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snicker |
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laughter |
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laughter |
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crying |
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crying |
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crying |
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yell |
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sigh |
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singing |
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choir |
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sodeling |
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chant |
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mantra |
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child_singing |
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synthetic_singing |
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rapping |
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humming |
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groan |
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grunt |
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whistling |
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breathing |
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wheeze |
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snoring |
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gasp |
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pant |
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snort |
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cough |
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throat_clearing |
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sneeze |
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sniff |
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run |
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shuffle |
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footsteps |
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chewing |
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biting |
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gargling |
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stomach_rumble |
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burping |
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hiccup |
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fart |
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hands |
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finger_snapping |
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clapping |
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heartbeat |
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heart_murmur |
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cheering |
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applause |
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chatter |
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crowd |
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speech |
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children_playing |
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animal |
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pets |
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dog |
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bark |
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yip |
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howl |
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bow-wow |
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growling |
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whimper_dog |
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cat |
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purr |
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meow |
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hiss |
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caterwaul |
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livestock |
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horse |
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clip-clop |
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neigh |
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cattle |
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moo |
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cowbell |
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pig |
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oink |
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goat |
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bleat |
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sheep |
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fowl |
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chicken |
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cluck |
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cock-a-doodle-doo |
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turkey |
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gobble |
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duck |
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quack |
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goose |
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honk |
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wild_animals |
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roaring_cats |
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roar |
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bird |
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chird |
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chirp |
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squawk |
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pigeon |
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coo |
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crow |
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caw |
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owl |
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hoot |
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flapping_wings |
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dogs |
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rats |
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mouse |
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patter |
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insect |
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cricket |
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mosquito |
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fly |
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buzz |
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buzz |
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frog |
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croak |
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snake |
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rattle |
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whale_vocalization |
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music |
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musical_instrument |
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plucked_string_instrument |
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guitar |
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electric_guitar |
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bass_guitar |
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acoustic_guitar |
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steel_guitar |
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tapping |
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strum |
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banjo |
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sitar |
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mandolin |
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zither |
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ukulele |
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keyboard |
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piano |
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electric_piano |
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organ |
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electronic_organ |
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hammond_organ |
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synthesizer |
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sampler |
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harpsichord |
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percussion |
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drum_kit |
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drum_machine |
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drum |
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snare_drum |
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rimshot |
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drum_roll |
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bass_drum |
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timpani |
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tabla |
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cymbal |
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hi-hat |
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wood_block |
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tambourine |
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rattle |
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maraca |
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gong |
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tubular_bells |
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mallet_percussion |
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marimba |
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glockenspiel |
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vibraphone |
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steelpan |
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orchestra |
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brass_instrument |
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french_horn |
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trumpet |
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trombone |
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bowed_string_instrument |
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string_section |
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violin |
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pizzicato |
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cello |
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double_bass |
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wind_instrument |
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flute |
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saxophone |
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clarinet |
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harp |
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bell |
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church_bell |
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jingle_bell |
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bicycle_bell |
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tuning_fork |
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chime |
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wind_chime |
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change_ringing |
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harmonica |
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accordion |
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bagpipes |
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didgeridoo |
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shofar |
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theremin |
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singing_bowl |
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scratching |
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pop_music |
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hip_hop_music |
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beatboxing |
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rock_music |
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heavy_metal |
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punk_rock |
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grunge |
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progressive_rock |
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rock_and_roll |
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psychedelic_rock |
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rhythm_and_blues |
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soul_music |
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reggae |
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country |
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swing_music |
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bluegrass |
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funk |
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folk_music |
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middle_eastern_music |
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jazz |
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disco |
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classical_music |
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opera |
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electronic_music |
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house_music |
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techno |
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dubstep |
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drum_and_bass |
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electronica |
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electronic_dance_music |
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ambient_music |
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trance_music |
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music_of_latin_america |
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salsa_music |
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flamenco |
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blues |
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music_for_children |
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new-age_music |
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vocal_music |
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a_capella |
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music_of_africa |
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afrobeat |
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christian_music |
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gospel_music |
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music_of_asia |
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carnatic_music |
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music_of_bollywood |
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ska |
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traditional_music |
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independent_music |
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song |
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background_music |
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theme_music |
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jingle |
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soundtrack_music |
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lullaby |
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video_game_music |
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christmas_music |
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dance_music |
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wedding_music |
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happy_music |
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sad_music |
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tender_music |
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exciting_music |
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angry_music |
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scary_music |
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wind |
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rustling_leaves |
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wind_noise |
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thunderstorm |
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thunder |
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water |
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rain |
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raindrop |
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rain_on_surface |
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stream |
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waterfall |
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ocean |
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waves |
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steam |
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gurgling |
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fire |
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crackle |
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vehicle |
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boat |
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sailboat |
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rowboat |
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motorboat |
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ship |
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motor_vehicle |
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car |
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honk |
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toot |
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car_alarm |
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power_windows |
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skidding |
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tire_squeal |
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car_passing_by |
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race_car |
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truck |
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air_brake |
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air_horn |
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reversing_beeps |
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ice_cream_truck |
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bus |
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emergency_vehicle |
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police_car |
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ambulance |
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fire_engine |
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motorcycle |
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traffic_noise |
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rail_transport |
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train |
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train_whistle |
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train_horn |
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railroad_car |
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train_wheels_squealing |
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subway |
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aircraft |
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aircraft_engine |
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jet_engine |
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propeller |
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helicopter |
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fixed-wing_aircraft |
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bicycle |
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skateboard |
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engine |
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light_engine |
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dental_drill's_drill |
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lawn_mower |
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chainsaw |
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medium_engine |
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heavy_engine |
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engine_knocking |
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engine_starting |
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idling |
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accelerating |
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door |
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doorbell |
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ding-dong |
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sliding_door |
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slam |
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knock |
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tap |
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squeak |
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cupboard_open_or_close |
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drawer_open_or_close |
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dishes |
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cutlery |
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chopping |
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frying |
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microwave_oven |
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blender |
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water_tap |
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sink |
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bathtub |
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hair_dryer |
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toilet_flush |
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toothbrush |
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electric_toothbrush |
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vacuum_cleaner |
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zipper |
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keys_jangling |
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coin |
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scissors |
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electric_shaver |
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shuffling_cards |
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typing |
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typewriter |
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computer_keyboard |
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writing |
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alarm |
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telephone |
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telephone_bell_ringing |
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ringtone |
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telephone_dialing |
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dial_tone |
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busy_signal |
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alarm_clock |
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siren |
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civil_defense_siren |
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buzzer |
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smoke_detector |
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fire_alarm |
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foghorn |
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whistle |
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steam_whistle |
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mechanisms |
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ratchet |
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clock |
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tick |
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tick-tock |
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gears |
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pulleys |
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sewing_machine |
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mechanical_fan |
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air_conditioning |
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cash_register |
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printer |
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camera |
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single-lens_reflex_camera |
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tools |
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hammer |
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jackhammer |
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sawing |
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filing |
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sanding |
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power_tool |
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drill |
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explosion |
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gunshot |
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machine_gun |
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fusillade |
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artillery_fire |
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cap_gun |
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fireworks |
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firecracker |
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burst |
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eruption |
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wood |
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pour |
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fill |
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boiling |
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arrow |
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whip |
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scrape |
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rub |
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roll |
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crushing |
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tearing |
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beep |
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ping |
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ding |
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clang |
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squeal |
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creak |
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rustle |
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whir |
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clatter |
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clicking |
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clickety-clack |
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zing |
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boing |
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crunch |
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silence |
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sine_wave |
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harmonic |
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sound_effect |
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pulse |
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inside |
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inside |
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inside |
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outside |
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outside |
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reverberation |
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echo |
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noise |
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environmental_noise |
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static |
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mains_hum |
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distortion |
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sidetone |
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cacophony |
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white_noise |
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pink_noise |
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throbbing |
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vibration |
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television |
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radio |
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field_recording |
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@ -0,0 +1,63 @@ |
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--- |
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id: audio_detectors |
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title: Audio Detectors |
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--- |
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|
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Frigate provides a builtin audio detector which runs on the CPU. Compared to object detection in images, audio detection is a relatively lightweight operation so the only option is to run the detection on a CPU. |
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|
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## Configuration |
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|
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Audio events work by detecting a type of audio and creating an event, the event will end once the type of audio has not been heard for the configured amount of time. Audio events save a snapshot at the beginning of the event as well as recordings throughout the event. The recordings are retained using the configured recording retention. |
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|
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### Enabling Audio Events |
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|
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Audio events can be enabled for all cameras or only for specific cameras. |
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|
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```yaml |
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|
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audio: # <- enable audio events for all camera |
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enabled: True |
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|
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cameras: |
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front_camera: |
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ffmpeg: |
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... |
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audio: |
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enabled: True # <- enable audio events for the front_camera |
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``` |
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|
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If you are using multiple streams then you must set the `audio` role on the stream that is going to be used for audio detection, this can be any stream but the stream must have audio included. |
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|
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:::note |
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|
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The ffmpeg process for capturing audio will be a separate connection to the camera along with the other roles assigned to the camera, for this reason it is recommended that the go2rtc restream is used for this purpose. See [the restream docs](/configuration/restream.md) for more information. |
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|
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::: |
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|
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```yaml |
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cameras: |
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front_camera: |
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ffmpeg: |
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inputs: |
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- path: rtsp://.../main_stream |
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roles: |
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- record |
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- path: rtsp://.../sub_stream # <- this stream must have audio enabled |
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roles: |
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- audio |
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- detect |
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``` |
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|
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### Configuring Audio Events |
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|
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The included audio model has over 500 different types of audio that can be detected, many of which are not practical. By default `bark`, `speech`, `yell`, and `scream` are enabled but these can be customized. |
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|
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```yaml |
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audio: |
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enabled: True |
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listen: |
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- bark |
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- scream |
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- speech |
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- yell |
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``` |
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@ -0,0 +1,247 @@ |
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"""Handle creating audio events.""" |
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|
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import datetime |
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import logging |
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import multiprocessing as mp |
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import os |
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import signal |
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import threading |
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from types import FrameType |
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from typing import Optional |
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|
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import numpy as np |
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import requests |
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from setproctitle import setproctitle |
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|
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from frigate.config import CameraConfig, FrigateConfig |
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from frigate.const import ( |
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AUDIO_DURATION, |
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AUDIO_FORMAT, |
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AUDIO_MAX_BIT_RANGE, |
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AUDIO_SAMPLE_RATE, |
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CACHE_DIR, |
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FRIGATE_LOCALHOST, |
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) |
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from frigate.ffmpeg_presets import parse_preset_input |
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from frigate.log import LogPipe |
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from frigate.object_detection import load_labels |
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from frigate.types import FeatureMetricsTypes |
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from frigate.util import get_ffmpeg_arg_list, listen |
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from frigate.video import start_or_restart_ffmpeg, stop_ffmpeg |
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|
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try: |
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from tflite_runtime.interpreter import Interpreter |
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except ModuleNotFoundError: |
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from tensorflow.lite.python.interpreter import Interpreter |
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logger = logging.getLogger(__name__) |
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|
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|
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def get_ffmpeg_command(input_args: list[str], input_path: str, pipe: str) -> list[str]: |
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return get_ffmpeg_arg_list( |
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f"ffmpeg {{}} -i {{}} -f {AUDIO_FORMAT} -ar {AUDIO_SAMPLE_RATE} -ac 1 -y {{}}".format( |
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" ".join(input_args), |
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input_path, |
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pipe, |
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) |
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) |
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|
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|
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def listen_to_audio( |
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config: FrigateConfig, |
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process_info: dict[str, FeatureMetricsTypes], |
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) -> None: |
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stop_event = mp.Event() |
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audio_threads: list[threading.Thread] = [] |
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|
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def exit_process() -> None: |
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for thread in audio_threads: |
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thread.join() |
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|
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logger.info("Exiting audio detector...") |
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|
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def receiveSignal(signalNumber: int, frame: Optional[FrameType]) -> None: |
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stop_event.set() |
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exit_process() |
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|
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signal.signal(signal.SIGTERM, receiveSignal) |
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signal.signal(signal.SIGINT, receiveSignal) |
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|
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threading.current_thread().name = "process:audio_manager" |
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setproctitle("frigate.audio_manager") |
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listen() |
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|
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for camera in config.cameras.values(): |
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if camera.enabled and camera.audio.enabled_in_config: |
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audio = AudioEventMaintainer(camera, process_info, stop_event) |
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audio_threads.append(audio) |
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audio.start() |
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|
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|
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class AudioTfl: |
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def __init__(self, stop_event: mp.Event): |
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self.stop_event = stop_event |
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self.labels = load_labels("/audio-labelmap.txt") |
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self.interpreter = Interpreter( |
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model_path="/cpu_audio_model.tflite", |
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num_threads=2, |
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) |
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|
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self.interpreter.allocate_tensors() |
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|
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self.tensor_input_details = self.interpreter.get_input_details() |
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self.tensor_output_details = self.interpreter.get_output_details() |
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|
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def _detect_raw(self, tensor_input): |
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self.interpreter.set_tensor(self.tensor_input_details[0]["index"], tensor_input) |
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self.interpreter.invoke() |
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detections = np.zeros((20, 6), np.float32) |
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|
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res = self.interpreter.get_tensor(self.tensor_output_details[0]["index"])[0] |
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non_zero_indices = res > 0 |
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class_ids = np.argpartition(-res, 20)[:20] |
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class_ids = class_ids[np.argsort(-res[class_ids])] |
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class_ids = class_ids[non_zero_indices[class_ids]] |
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scores = res[class_ids] |
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boxes = np.full((scores.shape[0], 4), -1, np.float32) |
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count = len(scores) |
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|
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for i in range(count): |
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if scores[i] < 0.4 or i == 20: |
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break |
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detections[i] = [ |
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class_ids[i], |
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float(scores[i]), |
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boxes[i][0], |
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boxes[i][1], |
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boxes[i][2], |
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boxes[i][3], |
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] |
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|
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return detections |
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|
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def detect(self, tensor_input, threshold=0.8): |
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detections = [] |
||||
|
||||
if self.stop_event.is_set(): |
||||
return detections |
||||
|
||||
raw_detections = self._detect_raw(tensor_input) |
||||
|
||||
for d in raw_detections: |
||||
if d[1] < threshold: |
||||
break |
||||
detections.append( |
||||
(self.labels[int(d[0])], float(d[1]), (d[2], d[3], d[4], d[5])) |
||||
) |
||||
return detections |
||||
|
||||
|
||||
class AudioEventMaintainer(threading.Thread): |
||||
def __init__( |
||||
self, |
||||
camera: CameraConfig, |
||||
feature_metrics: dict[str, FeatureMetricsTypes], |
||||
stop_event: mp.Event, |
||||
) -> None: |
||||
threading.Thread.__init__(self) |
||||
self.name = f"{camera.name}_audio_event_processor" |
||||
self.config = camera |
||||
self.feature_metrics = feature_metrics |
||||
self.detections: dict[dict[str, any]] = feature_metrics |
||||
self.stop_event = stop_event |
||||
self.detector = AudioTfl(stop_event) |
||||
self.shape = (int(round(AUDIO_DURATION * AUDIO_SAMPLE_RATE)),) |
||||
self.chunk_size = int(round(AUDIO_DURATION * AUDIO_SAMPLE_RATE * 2)) |
||||
self.pipe = f"{CACHE_DIR}/{self.config.name}-audio" |
||||
self.ffmpeg_cmd = get_ffmpeg_command( |
||||
get_ffmpeg_arg_list(self.config.ffmpeg.global_args) |
||||
+ parse_preset_input("preset-rtsp-audio-only", 1), |
||||
[i.path for i in self.config.ffmpeg.inputs if "audio" in i.roles][0], |
||||
self.pipe, |
||||
) |
||||
self.pipe_file = None |
||||
self.logpipe = LogPipe(f"ffmpeg.{self.config.name}.audio") |
||||
self.audio_listener = None |
||||
|
||||
def detect_audio(self, audio) -> None: |
||||
if not self.feature_metrics[self.config.name]["audio_enabled"].value: |
||||
return |
||||
|
||||
waveform = (audio / AUDIO_MAX_BIT_RANGE).astype(np.float32) |
||||
model_detections = self.detector.detect(waveform) |
||||
|
||||
for label, score, _ in model_detections: |
||||
if label not in self.config.audio.listen: |
||||
continue |
||||
|
||||
self.handle_detection(label, score) |
||||
|
||||
self.expire_detections() |
||||
|
||||
def handle_detection(self, label: str, score: float) -> None: |
||||
if self.detections.get(label): |
||||
self.detections[label][ |
||||
"last_detection" |
||||
] = datetime.datetime.now().timestamp() |
||||
else: |
||||
resp = requests.post( |
||||
f"{FRIGATE_LOCALHOST}/api/events/{self.config.name}/{label}/create", |
||||
json={"duration": None}, |
||||
) |
||||
|
||||
if resp.status_code == 200: |
||||
event_id = resp.json()[0]["event_id"] |
||||
self.detections[label] = { |
||||
"id": event_id, |
||||
"label": label, |
||||
"last_detection": datetime.datetime.now().timestamp(), |
||||
} |
||||
|
||||
def expire_detections(self) -> None: |
||||
now = datetime.datetime.now().timestamp() |
||||
|
||||
for detection in self.detections.values(): |
||||
if ( |
||||
now - detection.get("last_detection", now) |
||||
> self.config.audio.max_not_heard |
||||
): |
||||
self.detections[detection["label"]] = None |
||||
requests.put( |
||||
f"{FRIGATE_LOCALHOST}/api/events/{detection['id']}/end", |
||||
json={ |
||||
"end_time": detection["last_detection"] |
||||
+ self.config.record.events.post_capture |
||||
}, |
||||
) |
||||
|
||||
def restart_audio_pipe(self) -> None: |
||||
try: |
||||
os.mkfifo(self.pipe) |
||||
except FileExistsError: |
||||
pass |
||||
|
||||
self.audio_listener = start_or_restart_ffmpeg( |
||||
self.ffmpeg_cmd, logger, self.logpipe, None, self.audio_listener |
||||
) |
||||
|
||||
def read_audio(self) -> None: |
||||
if self.pipe_file is None: |
||||
self.pipe_file = open(self.pipe, "rb") |
||||
|
||||
try: |
||||
audio = np.frombuffer(self.pipe_file.read(self.chunk_size), dtype=np.int16) |
||||
self.detect_audio(audio) |
||||
except BrokenPipeError: |
||||
self.logpipe.dump() |
||||
self.restart_audio_pipe() |
||||
|
||||
def run(self) -> None: |
||||
self.restart_audio_pipe() |
||||
|
||||
while not self.stop_event.is_set(): |
||||
self.read_audio() |
||||
|
||||
self.pipe_file.close() |
||||
stop_ffmpeg(self.audio_listener, logger) |
||||
self.logpipe.close() |
||||
@ -0,0 +1,36 @@ |
||||
import { h } from 'preact'; |
||||
import { memo } from 'preact/compat'; |
||||
|
||||
export function Snapshot({ className = 'h-6 w-6', stroke = 'currentColor', onClick = () => {} }) { |
||||
return ( |
||||
<svg |
||||
xmlns="http://www.w3.org/2000/svg" |
||||
className={className} |
||||
fill="none" |
||||
viewBox="0 0 32 32" |
||||
stroke={stroke} |
||||
onClick={onClick} |
||||
> |
||||
<path |
||||
stroke-linecap="round" |
||||
stroke-linejoin="round" |
||||
stroke-width="2" |
||||
d="M18 30v-2a10.011 10.011 0 0010-10h2a12.013 12.013 0 01-12 12z" |
||||
/> |
||||
<path |
||||
stroke-linecap="round" |
||||
stroke-linejoin="round" |
||||
stroke-width="2" |
||||
d="M18 22v-2a2.002 2.002 0 002-2h2a4.004 4.004 0 01-4 4zM10 2a9.01 9.01 0 00-9 9h2a7 7 0 0114 0 7.09 7.09 0 01-3.501 6.135l-.499.288v3.073a2.935 2.935 0 01-.9 2.151 4.182 4.182 0 01-4.633 1.03A4.092 4.092 0 015 20H3a6.116 6.116 0 003.67 5.512 5.782 5.782 0 002.314.486 6.585 6.585 0 004.478-1.888A4.94 4.94 0 0015 20.496v-1.942A9.108 9.108 0 0019 11a9.01 9.01 0 00-9-9z" |
||||
/> |
||||
<path |
||||
stroke-linecap="round" |
||||
stroke-linejoin="round" |
||||
stroke-width="2" |
||||
d="M9.28 8.082A3.006 3.006 0 0113 11h2a4.979 4.979 0 00-1.884-3.911 5.041 5.041 0 00-4.281-.957 4.95 4.95 0 00-3.703 3.703 5.032 5.032 0 002.304 5.458A3.078 3.078 0 019 17.924V20h2v-2.077a5.06 5.06 0 00-2.537-4.346 3.002 3.002 0 01.817-5.494z" |
||||
/> |
||||
</svg> |
||||
); |
||||
} |
||||
|
||||
export default memo(Snapshot); |
||||
Loading…
Reference in new issue