Full Code of xiongyihui/tdoa for AI

Repository: xiongyihui/tdoa
Branch: master
Commit: e71681429fd2
Files: 13
Total size: 30.0 KB

Directory structure:
gitextract_nckaehmj/

├── .gitignore
├── LICENSE
├── README.md
├── bar_widget.py
├── echo_delay.py
├── gcc_phat.py
├── octave/
│   ├── gcc_phat.m
│   ├── test.m
│   └── view_cc.m
├── realtime_tdoa.py
├── vad.py
├── view.py
└── view_with_band_pass_filter.py

================================================
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================================================
FILE: LICENSE
================================================
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================================================
FILE: README.md
================================================
# TDOA

TDOA (Time Difference of Arrival) is estimated using GCC-PHAT.
A realtime DOA (Direction Of Arrival) is also elstimated using 2 microphones.


## Requirements
+ NumPy
+ PyAudio
+ WebRTCVAD

## Get started
```
python realtime_tdoa.py
```



================================================
FILE: bar_widget.py
================================================

from PySide import QtGui


class BarWidget(QtGui.QWidget):
    def __init__(self):
        super(BarWidget, self).__init__()

        self.bars_number = 16
        self.bars = [1] * self.bars_number
        self.padding = 2
        self.resolution = 255

        self.setMinimumSize(240, 320)

    def setBars(self, bars):
        self.bars_number = len(bars)
        for index, value in enumerate(bars):
            if value > self.resolution:
                bars[index] = self.resolution
        self.bars = bars
        self.update()

    def paintEvent(self, e):

        painter = QtGui.QPainter()
        painter.begin(self)
        self.drawBars(painter)
        painter.end()

    def drawBars(self, painter):
        size = self.size()
        width = size.width()
        height = size.height()

        bar_width = float(width - self.padding) / self.bars_number

        color = QtGui.QColor(0, 0, 0)
        painter.setPen(color)
        painter.setBrush(color)
        painter.drawRect(0, 0, width, height)
        for bar, value in enumerate(self.bars):
            bar_height = (height - self.padding) * value / self.resolution
            if not bar_height:
                bar_height = 1
            painter.setBrush(self.barColor(bar))
            painter.drawRect(
                bar * bar_width + self.padding,
                height - bar_height,
                bar_width - self.padding,
                bar_height - self.padding)

    def barColor(self, bar):
        position = int((bar + 0.5) * 255 / self.bars_number)
        return self.palette(position)

    def blue2red(self, position):
        position &= 0xFF
        if position < 128:
            return QtGui.QColor(0, position * 2, 255 - position * 2)
        else:
            position -= 128
            return QtGui.QColor(position * 2, 255 - position * 2, 0)

    palette = blue2red


def main():
    import sys
    app = QtGui.QApplication(sys.argv)
    BarWidget().show()
    sys.exit(app.exec_())


if __name__ == '__main__':
    main()


================================================
FILE: echo_delay.py
================================================

import sys
import wave
import numpy as np
from gcc_phat import gcc_phat


if len(sys.argv) != 3:
    print('Usage: {} near.wav far.wav'.format(sys.argv[0]))
    sys.exit(1)


near = wave.open(sys.argv[1], 'rb')
far = wave.open(sys.argv[2], 'rb')
rate = near.getframerate()

N = rate

window = np.hanning(N)

while True:
    sig = near.readframes(N)
    if len(sig) != 2 * N:
        break

    ref = far.readframes(N)
    sig_buf = np.fromstring(sig, dtype='int16')
    ref_buf = np.fromstring(ref, dtype='int16')
    tau, _ = gcc_phat(sig_buf * window, ref_buf * window, fs=rate, max_tau=1)
    # tau, _ = gcc_phat(sig_buf, ref_buf, fs=rate, max_tau=1)
    print(tau * 1000)



================================================
FILE: gcc_phat.py
================================================
"""
 Estimate time delay using GCC-PHAT 
 Copyright (c) 2017 Yihui Xiong

 Licensed under the Apache License, Version 2.0 (the "License");
 you may not use this file except in compliance with the License.
 You may obtain a copy of the License at

     http://www.apache.org/licenses/LICENSE-2.0

 Unless required by applicable law or agreed to in writing, software
 distributed under the License is distributed on an "AS IS" BASIS,
 WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
 See the License for the specific language governing permissions and
 limitations under the License.
"""

import numpy as np


def gcc_phat(sig, refsig, fs=1, max_tau=None, interp=16):
    '''
    This function computes the offset between the signal sig and the reference signal refsig
    using the Generalized Cross Correlation - Phase Transform (GCC-PHAT)method.
    '''
    
    # make sure the length for the FFT is larger or equal than len(sig) + len(refsig)
    n = sig.shape[0] + refsig.shape[0]

    # Generalized Cross Correlation Phase Transform
    SIG = np.fft.rfft(sig, n=n)
    REFSIG = np.fft.rfft(refsig, n=n)
    R = SIG * np.conj(REFSIG)

    cc = np.fft.irfft(R / np.abs(R), n=(interp * n))

    max_shift = int(interp * n / 2)
    if max_tau:
        max_shift = np.minimum(int(interp * fs * max_tau), max_shift)

    cc = np.concatenate((cc[-max_shift:], cc[:max_shift+1]))

    # find max cross correlation index
    shift = np.argmax(cc) - max_shift

    # Sometimes, there is a 180-degree phase difference between the two microphones.
    # shift = np.argmax(np.abs(cc)) - max_shift

    tau = shift / float(interp * fs)
    
    return tau, cc


def main():
    
    refsig = np.linspace(1, 10, 10)

    for i in range(0, 10):
        sig = np.concatenate((np.linspace(0, 0, i), refsig, np.linspace(0, 0, 10 - i)))
        offset, _ = gcc_phat(sig, refsig)
        print(offset)


if __name__ == "__main__":
    main()






================================================
FILE: octave/gcc_phat.m
================================================
function [tau, cc] = gcc_phat(sig, refsig, fs, max_tau, interp)

n = length(sig) + length(refsig);
max_shift = floor(n / 2);

if nargin < 3
  fs = 1;
end

if nargin >= 4
  max_shift = min(floor(fs * max_tau), max_shift);
end

if nargin < 5
  interp = 1;
end

max_shift = max_shift * interp;

X1 = fft(sig, n);
X2 = fft(refsig, n);
R = X1 .* conj(X2);

cc = ifft(R ./ (abs(R)), n * interp);
N = length(cc);
cc = [cc((N - max_shift + 1):N)(:); cc(1:(max_shift + 1))(:)];
cc = abs(cc);

[max_cc, shift] = max(cc);
shift -= max_shift + 1;

tau = shift / (interp * fs);

end





================================================
FILE: octave/test.m
================================================


x1 = 0:1:10;

for i = 1:10
  x2 = [zeros(1, i), x1];

  delay = gcc_phat(x2, x1)
end

================================================
FILE: octave/view_cc.m
================================================




[far, fs] = audioread('../audio/alexa-01.wav');
[near, fs] = audioread('../audio/alexa-02.wav');

% 0.14 m is the distance of the two microphones 
% 340 m/s as the sound speech 
max_tau = 0.14 / 340;
audio_length = length(far);
block_length = floor(fs / 2);
n = floor(audio_length / block_length);
samples = floor(max_tau * fs) * 2 + 1;
z = zeros(samples, n);
window = hanning(block_length);

for k = 1:n
  i = (k - 1) * block_length + 1;
  sig = near(i:(i + block_length - 1)) .* window;
  refsig = far(i:(i + block_length - 1)) .* window;
  [tau, cc] = gcc_phat(sig, refsig, fs, max_tau);
  z(:,k) = abs(cc);
end

surf(z);
colormap(hot)



================================================
FILE: realtime_tdoa.py
================================================
"""
 Estimate realtime DoA (Direction of Arrival) using two mic
 Copyright (c) 2017 Yihui Xiong

 Licensed under the Apache License, Version 2.0 (the "License");
 you may not use this file except in compliance with the License.
 You may obtain a copy of the License at

     http://www.apache.org/licenses/LICENSE-2.0

 Unless required by applicable law or agreed to in writing, software
 distributed under the License is distributed on an "AS IS" BASIS,
 WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
 See the License for the specific language governing permissions and
 limitations under the License.
"""

import pyaudio
import webrtcvad
import numpy as np
import collections
import Queue
import threading
import signal
import sys
import math
import audioop
from gcc_phat import gcc_phat
from vad import vad


class Microphone:

    def __init__(self, rate=16000, channels=2):
        self.pyaudio_instance = pyaudio.PyAudio()
        self.queue = Queue.Queue()
        self.quit_event = threading.Event()
        self.channels = channels
        self.sample_rate = rate

    def _callback(self, in_data, frame_count, time_info, status):
        self.queue.put(in_data)
        return None, pyaudio.paContinue

    def read_chunks(self, size):
        device_index = None
        # for i in range(self.pyaudio_instance.get_device_count()):
        #     dev = self.pyaudio_instance.get_device_info_by_index(i)
        #     name = dev['name'].encode('utf-8')
        #     print(i, name, dev['maxInputChannels'], dev['maxOutputChannels'])
        #     if dev['maxInputChannels'] >= self.channels:
        #         print('Use {}'.format(name))
        #         device_index = i
        #         break

        # if not device_index:
        #     print('can not find input device with {} channel(s)'.format(self.channels))
        #     return

        stream = self.pyaudio_instance.open(
            input=True,
            format=pyaudio.paInt16,
            channels=self.channels,
            rate=self.sample_rate,
            frames_per_buffer=size,
            stream_callback=self._callback,
            input_device_index = device_index,
        )

        while not self.quit_event.is_set():
            frames = self.queue.get()
            if not frames:
                break
            yield frames
        
        stream.close()

    def close(self):
        self.quit_event.set()
        self.queue.put('')


def main():
    sample_rate = 48000
    channels = 2
    N = 4096 * 4

    mic = Microphone(sample_rate, channels)
    window = np.hanning(N)

    sound_speed = 343.2
    distance = 0.14

    max_tau = distance / sound_speed

    def signal_handler(sig, num):
        print('Quit')
        mic.close()

    signal.signal(signal.SIGINT, signal_handler)

    for data in mic.read_chunks(N):
        buf = np.fromstring(data, dtype='int16')
        mono = buf[0::channels].tostring()
        if sample_rate != 16000:
            mono, _ = audioop.ratecv(mono, 2, 1, sample_rate, 16000, None)

        if vad.is_speech(mono):
            tau, _ = gcc_phat(buf[0::channels]*window, buf[1::channels]*window, fs=sample_rate, max_tau=max_tau)
            theta = math.asin(tau / max_tau) * 180 / math.pi
            print('\ntheta: {}'.format(int(theta)))

        
if __name__ == '__main__':
    main()


================================================
FILE: vad.py
================================================
"""
 Voice Activity Detector based on WebRTC VAD (https://github.com/wiseman/py-webrtcvad)
 Copyright (c) 2016 Seeed Technology Limited.

 Licensed under the Apache License, Version 2.0 (the "License");
 you may not use this file except in compliance with the License.
 You may obtain a copy of the License at

     http://www.apache.org/licenses/LICENSE-2.0

 Unless required by applicable law or agreed to in writing, software
 distributed under the License is distributed on an "AS IS" BASIS,
 WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
 See the License for the specific language governing permissions and
 limitations under the License.
"""

import collections
import sys

import webrtcvad


class WebRTCVAD:
    def __init__(self, sample_rate=16000, level=3):
        """

        Args:
            sample_rate: audio sample rate
            level: between 0 and 3. 0 is the least aggressive about filtering out non-speech, 3 is the most aggressive.
        """
        self.sample_rate = sample_rate

        self.frame_ms = 30
        self.frame_bytes = int(2 * self.frame_ms * self.sample_rate / 1000)   # S16_LE, 2 bytes width

        self.vad = webrtcvad.Vad(level)
        self.active = False
        self.data = b''
        self.history = collections.deque(maxlen=128)

    def is_speech(self, data):
        self.data += data
        while len(self.data) >= self.frame_bytes:
            frame = self.data[:self.frame_bytes]
            self.data = self.data[self.frame_bytes:]

            if self.vad.is_speech(frame, self.sample_rate):
                sys.stdout.write('1')
                self.history.append(1)
            else:
                sys.stdout.write('0')
                self.history.append(0)

            num_voiced = 0
            for i in range(-8, 0):
                try:
                    num_voiced += self.history[i]
                except IndexError:
                    continue

            if not self.active:
                if num_voiced >= 4:
                    sys.stdout.write('+')
                    self.active = True
                    break
                elif len(self.history) == self.history.maxlen and sum(self.history) == 0:
                    for _ in range(self.history.maxlen / 2):
                        self.history.popleft()

            else:
                if num_voiced < 1:
                    sys.stdout.write('-')
                    self.active = False
                elif sum(self.history) > self.history.maxlen * 0.9:
                    for _ in range(int(self.history.maxlen / 2)):
                        self.history.popleft()

        sys.stdout.flush()

        return self.active

    def reset(self):
        self.data = b''
        self.active = False
        self.history.clear()


vad = WebRTCVAD()



================================================
FILE: view.py
================================================


import sys
import threading
import Queue
import audioop
import math
import pyaudio
import numpy as np
from gcc_phat import gcc_phat


RATE = 48000
FRAMES = int(RATE / 4)

window = np.hanning(FRAMES)

sound_speed = 343.2
distance = 0.14

max_tau = distance / sound_speed
direction_n = int(max_tau * RATE)


class DOA:
    def __init__(self):
        self.pyaudio_instance = pyaudio.PyAudio()
        self.queue = Queue.Queue()
        self.event = threading.Event()

    def start(self, quit_event=None, show=None):
        stream = self.pyaudio_instance.open(
            rate=RATE,
            frames_per_buffer=FRAMES,
            format=pyaudio.paInt16,
            channels=2,
            input=True,
            # output_device_index=1,
            stream_callback=self._callback)

        self.event.clear()
        if not quit_event:
            quit_event = threading.Event()

        phat = [0] * (2 * direction_n + 1)
        while not (quit_event.is_set() or self.event.is_set()):
            try:
                data = self.queue.get()

                buf = np.fromstring(data, dtype='int16')
                tau, cc = gcc_phat(buf[0::2] * window, buf[1::2] * window, fs=RATE, max_tau=max_tau, interp=1)
                theta = math.asin(tau / max_tau) * 180 / math.pi
                print('\ntheta: {}'.format(int(theta)))

                for i, v in enumerate(cc):
                    phat[i] = int(v * 512)

                if show:
                    show(phat)
                # print [l for l in level]
            except KeyboardInterrupt:
                break

        stream.close()

    def _callback(self, in_data, frame_count, time_info, status):
        self.queue.put(in_data)

        return None, pyaudio.paContinue


def main():
    from PySide import QtGui
    from bar_widget import BarWidget

    app = QtGui.QApplication(sys.argv)
    widget = BarWidget()
    widget.setWindowTitle('Direction Of Arrival')
    widget.show()

    doa = DOA()

    quit_event = threading.Event()
    thread = threading.Thread(target=doa.start, args=(quit_event, widget.setBars))
    thread.start()

    app.exec_()

    quit_event.set()
    thread.join()

if __name__ == '__main__':
    main()



================================================
FILE: view_with_band_pass_filter.py
================================================


import sys
import threading
import Queue
import audioop
import math
import pyaudio
import numpy as np
from gcc_phat import gcc_phat


RATE = 48000
FRAMES = int(RATE / 4)

window = np.hanning(FRAMES)

sound_speed = 343.2
distance = 0.14

max_tau = distance / sound_speed
direction_n = int(max_tau * RATE)


def gcc_phat(sig, refsig, fs=1, max_tau=None, interp=1):
    '''
    This function computes the offset between the signal sig and the reference signal refsig
    using the Generalized Cross Correlation - Phase Transform (GCC-PHAT)method.
    '''

    # make sure the length for the FFT is larger or equal than len(sig) + len(refsig)
    n = sig.shape[0] + refsig.shape[0]

    low_cutoff_bin = int((250 * n) / RATE)
    high_cutoff_bin = int((4000 * n) / RATE)

    # Generalized Cross Correlation Phase Transform
    SIG = np.fft.rfft(sig, n=n)
    SIG[:low_cutoff_bin+1] = [0] * (low_cutoff_bin + 1)
    SIG[-high_cutoff_bin:] = [0] * high_cutoff_bin
    REFSIG = np.fft.rfft(refsig, n=n)

    REFSIG[:low_cutoff_bin+1] = [0] * (low_cutoff_bin + 1)
    REFSIG[-high_cutoff_bin:] = [0] * high_cutoff_bin

    T = SIG[low_cutoff_bin+1:-high_cutoff_bin] * np.conj(REFSIG[low_cutoff_bin+1:-high_cutoff_bin])
    T /= np.abs(T)
    SIG[low_cutoff_bin+1:-high_cutoff_bin] = T

    cc = np.fft.irfft(SIG, n=(interp * n))

    max_shift = int(interp * n / 2)
    if max_tau:
        max_shift = np.minimum(int(interp * fs * max_tau), max_shift)

    cc = np.concatenate((cc[-max_shift:], cc[:max_shift + 1]))

    # find max cross correlation index
    shift = np.argmax(np.abs(cc)) - max_shift

    tau = shift / float(interp * fs)

    return tau, cc


class DOA:
    def __init__(self):
        self.pyaudio_instance = pyaudio.PyAudio()
        self.queue = Queue.Queue()
        self.event = threading.Event()

    def start(self, quit_event=None, show=None):
        stream = self.pyaudio_instance.open(
            rate=RATE,
            frames_per_buffer=FRAMES,
            format=pyaudio.paInt16,
            channels=2,
            input=True,
            # output_device_index=1,
            stream_callback=self._callback)

        self.event.clear()
        if not quit_event:
            quit_event = threading.Event()

        phat = [0] * (2 * direction_n + 1)
        while not (quit_event.is_set() or self.event.is_set()):
            try:
                data = self.queue.get()

                buf = np.fromstring(data, dtype='int16')
                tau, cc = gcc_phat(buf[0::2] * window, buf[1::2] * window, fs=RATE, max_tau=max_tau, interp=1)
                theta = math.asin(tau / max_tau) * 180 / math.pi
                print('\ntheta: {}'.format(int(theta)))

                for i, v in enumerate(cc):
                    phat[i] = int(v * 512)

                if show:
                    show(phat)
                # print [l for l in level]
            except KeyboardInterrupt:
                break

        stream.close()

    def _callback(self, in_data, frame_count, time_info, status):
        self.queue.put(in_data)

        return None, pyaudio.paContinue


def main():
    from PySide import QtGui
    from bar_widget import BarWidget

    app = QtGui.QApplication(sys.argv)
    widget = BarWidget()
    widget.setWindowTitle('Direction Of Arrival')
    widget.show()

    doa = DOA()

    quit_event = threading.Event()
    thread = threading.Thread(target=doa.start, args=(quit_event, widget.setBars))
    thread.start()

    app.exec_()

    quit_event.set()
    thread.join()

if __name__ == '__main__':
    main()