Skully

skully.py

from scipy.io import wavfile
import matplotlib.pyplot as plt
import numpy as np
import pyfirmata
import pyaudio
import wave
import time

vocals = '/Users/gbischof/Downloads/Bush-Machinehead-Isolated-Vocals.wav'
full = '/Users/gbischof/Downloads/Bush-Machinehead.wav'

def plot_wav(wav_path='/Users/gbischof/Downloads/Bush-Machinehead-Isolated-Vocals.wav'):
    rate, data = wavfile.read(wav_path)
    length = data.shape[0] / rate
    time = np.linspace(0., length, data.shape[0])
    normalized_data = np.absolute(data_np)
    plt.plot(time, normalized_data, label="Audio")
    plt.legend()
    plt.xlabel("Time [s]")
    plt.ylabel("Amplitude")
    plt.show()



def plot_data(data):
    length = data.shape[0]
    time = np.linspace(0., length, data.shape[0])
    plt.plot(time, data, label="Audio")
    plt.legend()
    plt.xlabel("Time [s]")
    plt.ylabel("Amplitude")
    plt.show()


def normalize(data):
    # Use only second collumn of wav data.
    data = data[:,1]
    data = np.absolute(data)
    mean = np.mean(data[data>0])
    std = np.std(data[data>0])

    max_val = mean + (std * 5)
    trunc = np.frompyfunc(lambda x: max_val if x >= max_val else x, 1, 1)
    data = trunc(data)

    # Convert to float.
    data = data.astype(float)
    return data / max_val


def load_np(wav_path):
    rate, data = wavfile.read(wav_path)
    return data


def sing(vocals_path=vocals, wav_path=full, offset=575):

    data_np = load_np(vocals_path)
    data_np = normalize(data_np)

    # Setup audrino.
    board=pyfirmata.Arduino('/dev/cu.usbmodem14101')
    it=pyfirmata.util.Iterator(board)
    it.start()

    # Assign servo to variable.
    masseter = board.get_pin('d:9:s')

    #open a wav format music
    f = wave.open(wav_path,"rb")
    #instantiate PyAudio
    p = pyaudio.PyAudio()
    #open stream
    stream = p.open(format = p.get_format_from_width(f.getsampwidth()),
                    channels = f.getnchannels(),
                    rate = f.getframerate(),
                    output = True)

    #read data
    chunk = 1024
    for i in range(offset):
        data = f.readframes(chunk)

    print("START")
    #play stream
    i = 0
    while data:
        amplitude = max(data_np[i*chunk:(i+1)*chunk]) * 50
        # Move masseter.
        masseter.write(amplitude)
        stream.write(data)
        print(i)
        data = f.readframes(chunk)
        i += 1

    #stop stream
    stream.stop_stream()
    stream.close()

    #close PyAudio
    p.terminate()