Hello,
I would like to use a benchodroff code with the ReSpeaker 4 Mics Array; in the code, it is asked to specify the NUM_SAMPLES and SAMPLIN_RATE of the mic = do you know how I can get it ?
I thank you in advance for your help
#!/usr/bin/env python
#Tone detection shamelessly stolen from:
#https://benchodroff.com/2017/02/18/using-a-raspberry-pi-with-a-microphone-to-hear-an-audio-alarm-using-fft-in-python/
#
# this entire thing stolen from Sufficiently-Advanced (Allen Pan)
#
import pyaudio
from numpy import zeros,linspace,short,fromstring,hstack,transpose,log
from scipy import fft
from time import sleep
from collections import deque
import paho.mqtt.client as mqtt
import requests
import datetime
import time
import sys
import signal
from secrets import mqtthost, mqttuser, mqttpass
def terminateProcess(signalNumber, frame):
client.publish("sounddetector/state", "offline")
sys.exit()
if __name__ == '__main__':
# register the signals to be caught
signal.signal(signal.SIGTERM, terminateProcess)
#mqtt stuff
client = mqtt.Client(client_id="sounddetector")
client.username_pw_set(username=mqttuser,password=mqttpass)
client.connect(mqtthost,1883,300)
#Volume Sensitivity, 0.05: Extremely Sensitive, may give false alarms
# 0.1: Probably Ideal volume
# 1: Poorly sensitive, will only go off for relatively loud
SENSITIVITY= 1.0
#Bandwidth for detection (i.e., detect frequencies within this margin of error of the TONE)
BANDWIDTH = 20
#How many 46ms blips before we declare a beep? (Take the beep length in ms, divide by 46ms, subtract a bit)
beeplength=8
# How many beeps before we declare a tone?
tonelength=2
# How many false 46ms blips before we declare the alarm is not ringing
resetlength=6
# How many reset counts until we clear an active alarm?
clearlength=2
# Enable blip, beep, and reset debug output
debug=False
# Show the most intense frequency detected (useful for configuration)
frequencyoutput=True
blipcount=0
beepcount=0
resetcount=0
clearcount=0
tone=False
# what devices are we using
if debug:
pd = pyaudio.PyAudio()
info = pd.get_host_api_info_by_index(0)
numdevices = info.get('deviceCount')
for i in range(0, numdevices):
if (pd.get_device_info_by_host_api_device_index(0, i).get('maxInputChannels')) > 0:
print "Input Device id ", i, " - ", pd.get_device_info_by_host_api_device_index(0, i).get('name')
# Alarm frequencies (Hz) to detect (Use audacity to record a wave and then do Analyze->Plot Spectrum)
D1 = 530
D2 = 675
F = 755
G = 806
D5 = 1175
#frequency ranges for each note
'''rangeD1 = range(D1-BANDWIDTH,D4+BANDWIDTH)
rangeD2 = range(D2-BANDWIDTH,D2+BANDWIDTH)
rangeF = range(F-BANDWIDTH,F+BANDWIDTH)
rangeG = range(G-BANDWIDTH,G+BANDWIDTH)
rangeD5 = range(D5-BANDWIDTH,D5+BANDWIDTH)'''
#These numbers work for my ocarina in my house with a blue yeti, ymmv
minD1 = D1-BANDWIDTH
maxD1 = D1+BANDWIDTH
minD2 = D2-BANDWIDTH
maxD2 = D2+BANDWIDTH
minF = F-40
maxF = F+BANDWIDTH
minG = G-BANDWIDTH
maxG = G+BANDWIDTH
minD5 = D5-BANDWIDTH
maxD5 = D5+BANDWIDTH
# Song note sequences
doorbell = deque(['D1','D2'])
test = deque(['D2','F'])
#heard note sequence deque
notes = deque(['G','G'], maxlen=2)
# Show the most intense frequency detected (useful for configuration)
frequencyoutput=True
freqNow = 1.0
freqPast = 1.0
#Set up audio sampler -
NUM_SAMPLES = 2048
SAMPLING_RATE = 48000 #make sure this matches the sampling rate of your mic!
pa = pyaudio.PyAudio()
_stream = pa.open(format=pyaudio.paInt16,
channels=1, rate=SAMPLING_RATE,
input=True,
frames_per_buffer=NUM_SAMPLES)
if debug: print("Alarm detector working. Press CTRL-C to quit.")
client.publish("sounddetector/state", "online")
while True:
timeout = 30 # report in to mqtt every 30 seconds
timeout_start = time.time()
while time.time() < timeout_start + timeout:
test = 0
if test == 5:
break
test -= 1
while _stream.get_read_available()< NUM_SAMPLES: sleep(0.05)
audio_data = fromstring(_stream.read(
_stream.get_read_available()), dtype=short)[-NUM_SAMPLES:]
# Each data point is a signed 16 bit number, so we can normalize by dividing 32*1024
normalized_data = audio_data / 32768.0
intensity = abs(fft(normalized_data))[:NUM_SAMPLES/2]
frequencies = linspace(0.0, float(SAMPLING_RATE)/2, num=NUM_SAMPLES/2)
if frequencyoutput:
which = intensity[1:].argmax()+1
# use quadratic interpolation around the max
if which != len(intensity)-1:
y0,y1,y2 = log(intensity[which-1:which+2:])
x1 = (y2 - y0) * .5 / (2 * y1 - y2 - y0)
# find the frequency and output it
freqPast = freqNow
freqNow = (which+x1)*SAMPLING_RATE/NUM_SAMPLES
else:
freqNow = which*SAMPLING_RATE/NUM_SAMPLES
if debug: print "\t\t\t\tfreq=",freqNow,"\t",freqPast
if debug: print "\t\t\t\tnotes=",notes
if max(intensity[(frequencies < maxD5+BANDWIDTH) & (frequencies > minD1-BANDWIDTH )]) > max(intensity[(frequencies < maxD5-1000) & (frequencies > minD1-2000)]) + SENSITIVITY:
blipcount+=1
resetcount=0
if debug: print "\t\tBlip",blipcount
if (blipcount>=beeplength):
blipcount=0
resetcount=0
beepcount+=1
if debug: print "\tBeep",beepcount,freqNow
if (beepcount>=tonelength):
clearcount=0
tone=True
if debug: print "ToneDetected"
beepcount=0
else:
blipcount=0
resetcount+=1
if debug: print "\t\t\treset",resetcount
if (resetcount>=resetlength):
resetcount=0
beepcount=0
if tone:
clearcount+=1
if debug: print "\t\tclear",clearcount
if clearcount>=clearlength:
clearcount=0
if debug: print "Tone Too Short - Cleared"
tone=False
# if minD1 <= freqPast <= maxD5 and abs(freqNow-freqPast) <= 20:
if tone:
if minF<=freqPast<=maxF and minF<=freqNow<=maxF and notes[-1]!='F':
notes.append('F')
elif freqPast <= maxD1 and minD1 <= freqNow <= maxD1 and notes[-1]!='D1':
notes.append('D1')
if debug: print "You played D1!"
elif minD5 <= freqPast <= maxD5 and minD5 <= freqNow <= maxD5 and notes[-1]!='D5':
notes.append('D5')
elif minD2<=freqPast<=maxD2 and minD2<=freqNow<=maxD2 and notes[-1]!='D2':
notes.append('D2')
if debug: print "You played D2!"
elif minG<=freqPast<=maxG and minG<=freqNow<=maxG and notes[-1]!='G':
notes.append('G')
if debug: print "You played G!"
if notes==doorbell:
if debug: print "\t\t\t\tDoorbell song!"
now = datetime.datetime.now()
ringtime="{\"datetime\":\"" + now.strftime("%Y-%m-%d %H:%M:%S") + "\"}"
client.publish("sounddetector/doorbell", ringtime)
notes.append('G')#append with 'G' to 'reset' notes, this keeps the song from triggering constantly
if notes==test:
if debug: print "Test Sequence Activated!"
client.publish("sounddetector", "test")
notes.append('G')
client.publish("sounddetector/state", "online")