106 lines
No EOL
4.1 KiB
Python
Executable file
106 lines
No EOL
4.1 KiB
Python
Executable file
#!/usr/bin/env python3
|
|
import os
|
|
import concurrent.futures
|
|
import datetime
|
|
import numpy as np
|
|
import matplotlib.pyplot as plt
|
|
import soundfile
|
|
import scipy.signal
|
|
from scipy.fft import rfft, rfftfreq
|
|
import shutil
|
|
|
|
RECORDINGS_DIR = "recordings"
|
|
PROCESSED_RECORDINGS_DIR = "recordings/processed"
|
|
DETECTIONS_DIR = "events"
|
|
|
|
DETECT_FREQUENCY = 211 # Hz
|
|
DETECT_FREQUENCY_TOLERANCE = 2 # Hz
|
|
DETECT_FREQUENCY_FROM = DETECT_FREQUENCY - DETECT_FREQUENCY_TOLERANCE # Hz
|
|
DETECT_FREQUENCY_TO = DETECT_FREQUENCY + DETECT_FREQUENCY_TOLERANCE # Hz
|
|
ADJACENCY_FACTOR = 2 # area to look for noise around the target frequency
|
|
AMPLITUDE_THRESHOLD = 200 # relative DB (rDB) (because not calibrated)
|
|
BLOCK_SECONDS = 3 # seconds (longer means more frequency resolution, but less time resolution)
|
|
DETECTION_DISTANCE = 30 # seconds (minimum time between detections)
|
|
BLOCK_OVERLAP = 0.8 # overlap between blocks (0.8 means 80% overlap)
|
|
|
|
|
|
def process_recording(filename):
|
|
print('processing', filename)
|
|
|
|
# get ISO 8601 nanosecond recording date from filename
|
|
date_string_from_filename = os.path.splitext(filename)[0]
|
|
recording_date = datetime.datetime.strptime(date_string_from_filename, "%Y-%m-%d_%H-%M-%S.%f%z")
|
|
|
|
# get data and metadata from recording
|
|
path = os.path.join(RECORDINGS_DIR, filename)
|
|
sound, samplerate = soundfile.read(path)
|
|
samples_per_block = int(BLOCK_SECONDS * samplerate)
|
|
overlap = int(samples_per_block * BLOCK_OVERLAP)
|
|
|
|
# get median amplitude for normalization
|
|
complex_amplitudes_global = rfft(sound)
|
|
median_amplitude = np.median(np.abs(complex_amplitudes_global))
|
|
print(f'median amplitude: {median_amplitude:.5f}rDB')
|
|
|
|
# initialize to a very old date
|
|
last_detection_at = datetime.datetime.min.replace(tzinfo=recording_date.tzinfo)
|
|
is_detecting = False
|
|
|
|
# read blocks of audio data with overlap from sound variable
|
|
for num in range(0, len(sound) // (samples_per_block - overlap)):
|
|
start = num * (samples_per_block - overlap)
|
|
end = start + samples_per_block
|
|
block = sound[start:end]
|
|
|
|
block_date = recording_date + datetime.timedelta(seconds=num * BLOCK_SECONDS)
|
|
labels = rfftfreq(len(block), d=1/samplerate)
|
|
complex_amplitudes = rfft(block)
|
|
absolute_amplitudes = np.abs(complex_amplitudes)
|
|
amplitudes = absolute_amplitudes / median_amplitude
|
|
|
|
# get amplitudes only between 100 and 1000 Hz
|
|
adjacent_amplitudes = amplitudes[(labels >= DETECT_FREQUENCY_FROM/ADJACENCY_FACTOR) & (labels <= DETECT_FREQUENCY_TO*ADJACENCY_FACTOR)]
|
|
adjacent_labels = labels[(labels >= DETECT_FREQUENCY_FROM/ADJACENCY_FACTOR) & (labels <= DETECT_FREQUENCY_TO*ADJACENCY_FACTOR)]
|
|
|
|
# get the frequency with the highest amplitude
|
|
max_amplitude = max(adjacent_amplitudes)
|
|
max_amplitude_index = np.argmax(adjacent_amplitudes)
|
|
max_freq = adjacent_labels[max_amplitude_index]
|
|
|
|
# get the average amplitude of the adjacent frequencies
|
|
noise = np.mean(adjacent_amplitudes)/max_amplitude
|
|
|
|
# check for detection criteria
|
|
max_freq_detected = DETECT_FREQUENCY_FROM <= max_freq <= DETECT_FREQUENCY_TO
|
|
amplitude_detected = max_amplitude > AMPLITUDE_THRESHOLD
|
|
low_noise_detected = noise < 0.1
|
|
no_recent_detection = is_detecting or (block_date - last_detection_at).total_seconds() > DETECTION_DISTANCE
|
|
|
|
# conclude detection
|
|
if (
|
|
max_freq_detected and
|
|
amplitude_detected and
|
|
low_noise_detected and
|
|
no_recent_detection
|
|
):
|
|
if not is_detecting:
|
|
is_detecting = True
|
|
last_detection_at = block_date
|
|
print("🔊")
|
|
|
|
print(f'{block_date}: {max_amplitude:.1f}rDB @ {max_freq:.1f}Hz (noise {noise:.3f}rDB)')
|
|
else:
|
|
is_detecting = False
|
|
|
|
|
|
def main():
|
|
os.makedirs(RECORDINGS_DIR, exist_ok=True)
|
|
os.makedirs(PROCESSED_RECORDINGS_DIR, exist_ok=True)
|
|
|
|
for filename in os.listdir(RECORDINGS_DIR):
|
|
if filename.endswith(".flac"):
|
|
process_recording(filename)
|
|
|
|
|
|
if __name__ == "__main__":
|
|
main() |