[init]

README.md

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+= Redilysis = Redis + Audio Analysis 
+
+Redilysis sends audio analysis to a redis install. What's the use? Using that information for multiple visualizations, of course!
+
+== Installation 
+
+```python
+git clone https://git.interhacker.space/tmplab/redilysis.git
+cd redilysis
+pip install -r requirements.txt
+python3 redilysis.py --help
+```
+
+== Guide
+
+There are two available modes.
+
+**One is the slow mode with BPM recognition:**
+
+python3 redilysis.py -m bpm -s 1 -f 44100
+
+Pushes following keys in redis:
+
+  * onset 
+  * bpm
+  * beats
+
+
+**The other is a fast mode with spectrogram analysis**
+
+python3 redilysis.py -m spectrum -s 0.1 -f 4410
+
+
+Pushes following keys in redis:
+
+  * rms
+  * spectrum
+  * tuning

redilysis.py

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+"""
+Sends live audio analysis to the terminal.
+
+Based on musicinformationretrieval.com/realtime_spectrogram.py
+
+For more examples using PyAudio:
+    https://github.com/mwickert/scikit-dsp-comm/blob/master/sk_dsp_comm/pyaudio_helper.py
+"""
+
+import argparse
+import json
+import librosa
+import numpy
+import os
+import pyaudio
+import redis
+import time
+
+
+
+def list_devices():
+    # List all audio input devices
+    p = pyaudio.PyAudio()
+    i = 0
+    n = p.get_device_count()
+    print("\nFound {} devices\n".format(n))
+    print ("  {}     {}".format('ID', 'Device name'))
+    while i < n:
+        dev = p.get_device_info_by_index(i)
+        if dev['maxInputChannels'] > 0:
+            print ("  {}      {}".format(i, dev['name']))
+        i += 1
+
+# Define default variables.
+_BAND_RANGE = 96
+_CHANNELS = 1
+_ENERGY_THRESHOLD = 0.4
+_FRAMES_PER_BUFFER = 4410
+_N_FFT = 4096
+_RATE = 44100
+_SAMPLING_FREQUENCY = 0.1
+
+
+# Argument parsing
+parser = argparse.ArgumentParser(prog='realtime_redis')
+parser.add_argument('--list-devices','-L', action='store_true', help='Which devices are detected by pyaudio')
+parser.add_argument('--mode','-m', required=False, default='spectrum', choices=['spectrum', 'bpm'], type=str, help='Which mode to use. Default=spectrum')
+parser.add_argument('--device','-d', required=False, type=int, help='Which pyaudio device to use')
+parser.add_argument('--frames','-f', required=False, default=4410, type=int, help='How many frames per buffer. Default={}'.format(_FRAMES_PER_BUFFER))
+parser.add_argument('--sampling-frequency','-s', required=False, default=0.1, type=float, help='Which frequency, in seconds. Default={}f '.format(_SAMPLING_FREQUENCY))
+parser.add_argument('--channels','-c', required=False, default=_CHANNELS, type=int, help='How many channels. Default={} '.format(_CHANNELS))
+parser.add_argument('--rate','-r', required=False, default=44100, type=int, help='Which rate. Default={} '.format(_RATE))
+parser.add_argument('--energy-threshold','-e', required=False, default=0.4, type=float, help='Which energy triggers spectrum detection flag. Default={} '.format(_ENERGY_THRESHOLD))
+args = parser.parse_args()
+
+# Set real variables
+BAND_RANGE = _BAND_RANGE
+CHANNELS = args.channels
+DEVICE = args.device
+ENERGY_THRESHOLD = args.energy_threshold
+FRAMES_PER_BUFFER = args.frames
+LIST_DEVICES = args.list_devices
+MODE = args.mode
+N_FFT = _N_FFT
+RATE = args.rate
+SAMPLING_FREQUENCY = args.sampling_frequency
+
+
+# Define the frequency range of the log-spectrogram.
+F_LO = librosa.note_to_hz('C2')
+F_HI = librosa.note_to_hz('C9')
+M = librosa.filters.mel(RATE, N_FFT, BAND_RANGE, fmin=F_LO, fmax=F_HI)
+
+
+r = redis.Redis(
+        host='localhost',
+        port=6379)
+
+# Early exit to list devices
+if( LIST_DEVICES ):
+  list_devices()
+  os._exit(1)
+
+p = pyaudio.PyAudio()
+
+
+# global
+bpm = 120.0
+
+def m_bpm(audio_data):
+    """
+    This function saves slow analysis to redis
+      * beat
+    """
+    global bpm
+
+    # Get RMS
+    rms = librosa.feature.rmse( audio_data )
+
+    onset = librosa.onset.onset_detect(
+        y=audio_data,
+        sr=RATE)
+    new_bpm, beats = librosa.beat.beat_track(
+        y=audio_data,
+        sr=RATE,
+        trim=False,
+        start_bpm=bpm,
+        units="time"
+        )
+    print ( bpm, new_bpm)
+    #  Save spectrum
+    r.set( 'onset', json.dumps( onset.tolist() ) )
+    r.set( 'bpm', json.dumps( new_bpm ) )
+    r.set( 'beats', json.dumps( beats.tolist() ) )
+    bpm = new_bpm
+    return True
+
+def m_spectrum(audio_data):
+    """
+    This function saves fast analysis to redis
+      * spectrum
+      * RMS
+    """
+
+    # Compute real FFT.
+    x_fft = numpy.fft.rfft(audio_data, n=N_FFT)
+
+    # Compute mel spectrum.
+    melspectrum = M.dot(abs(x_fft))
+
+    # Get RMS
+    rms = librosa.feature.rmse( S=melspectrum, frame_length=FRAMES_PER_BUFFER )
+
+    # Initialize output characters to display.
+    bit_list = [0]*BAND_RANGE
+    count = 0
+
+    highest_index = -1
+    highest_value = 0
+
+    for i in range(BAND_RANGE):
+        val = melspectrum[i]
+
+        # If this is the highest tune, record it
+        if( val > highest_value ) :
+          highest_index = i
+          highest_value = val
+
+        # If there is energy in this frequency, mark it
+        if val > ENERGY_THRESHOLD:
+            count += 1
+            bit_list[i] = 1
+
+    #  Save to redis
+    r.set( 'rms', "{}".format(rms.tolist()) )
+    r.set( 'spectrum', json.dumps( bit_list ) )
+    r.set( 'tuning', highest_index )
+    return True
+
+
+def callback(in_data, frame_count, time_info, status):
+    audio_data = numpy.fromstring(in_data, dtype=numpy.float32)
+
+    start = time.time()
+    if MODE == 'spectrum':
+      m_spectrum(audio_data)
+    elif MODE == 'bpm':
+      m_bpm( audio_data)
+    else:
+      print( "Unknown mode. Exiting")
+      os._exit(2)
+    end = time.time()
+    print ("\rLoop took {:.2}s on {}s    ".format(end - start, SAMPLING_FREQUENCY), end="")
+    return (in_data, pyaudio.paContinue)
+
+
+print( "\n\nRunning! Using mode {}.\n\n".format(MODE))
+
+stream = p.open(format=pyaudio.paFloat32,
+                channels=CHANNELS,
+                rate=RATE,
+                input=True,   # Do record input.
+                output=False, # Do not play back output.
+                frames_per_buffer=FRAMES_PER_BUFFER,
+                input_device_index = DEVICE,
+                stream_callback=callback)
+
+stream.start_stream()
+
+while stream.is_active():
+    time.sleep(SAMPLING_FREQUENCY)
+
+stream.stop_stream()
+stream.close()
+
+p.terminate()

requirements.txt

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+Redilysis
+librosa=0.6.1
+numpy=1.14.2
+pyaudio
+redis