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{
"cells": [
{
"cell_type": "markdown",
"source": [
"This notebook scans for labelled audio samples in a directory,\n",
"extracts the spectrum of the samples and creates dataset files\n",
"with the spectrum data to train the audio detection model."
],
"metadata": {
"collapsed": false
}
},
{
"cell_type": "code",
"execution_count": 1,
"metadata": {
"collapsed": true
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"DEBUG:matplotlib:(private) matplotlib data path: /usr/lib/python3.8/site-packages/matplotlib/mpl-data\n",
"DEBUG:matplotlib:matplotlib data path: /usr/lib/python3.8/site-packages/matplotlib/mpl-data\n",
"DEBUG:matplotlib:CONFIGDIR=/home/blacklight/.config/matplotlib\n",
"DEBUG:matplotlib:matplotlib version 3.3.2\n",
"DEBUG:matplotlib:interactive is False\n",
"DEBUG:matplotlib:platform is linux\n",
"DEBUG:matplotlib:loaded modules: ['sys', 'builtins', '_frozen_importlib', '_imp', '_warnings', '_frozen_importlib_external', '_io', 'marshal', 'posix', '_thread', '_weakref', 'time', 'zipimport', '_codecs', 'codecs', 'encodings.aliases', 'encodings', 'encodings.utf_8', '_signal', '__main__', 'encodings.latin_1', '_abc', 'abc', 'io', '_stat', 'stat', '_collections_abc', 'genericpath', 'posixpath', 'os.path', 'os', '_sitebuiltins', '_locale', '_bootlocale', 'types', 'importlib._bootstrap', 'importlib._bootstrap_external', 'warnings', 'importlib', 'importlib.machinery', 'importlib.abc', '_operator', 'operator', 'keyword', '_heapq', 'heapq', 'itertools', 'reprlib', '_collections', 'collections', '_functools', 'functools', 'contextlib', 'importlib.util', 'google', 'google.assistant', 'google.assistant.embedded', 'googlesamples', 'googlesamples.assistant', 'google.cloud', 'google.logging', 'google.iam', 'mpl_toolkits', 'ruamel', 'sphinxcontrib', 'zope', 'site', '_weakrefset', 'weakref', 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'ipykernel.eventloops', 'ipykernel.ipkernel', 'ipykernel.parentpoller', 'ipykernel.kernelapp', 'netifaces', 'faulthandler', 'ipykernel.codeutil', 'ipykernel.pickleutil', 'ipykernel.serialize', 'ipykernel.datapub', 'IPython.core.completerlib', 'storemagic', 'micmon', 'micmon.audio', 'micmon.audio.directory', 'micmon.audio.segment', 'numpy._globals', 'numpy.__config__', 'numpy.version', 'numpy._distributor_init', 'numpy.core._multiarray_umath', 'numpy.compat._inspect', 'numpy.compat.py3k', 'numpy.compat', 'numpy.core.overrides', 'numpy.core.multiarray', 'numpy.core.umath', 'numpy.core._string_helpers', 'numpy.core._dtype', 'numpy.core._type_aliases', 'numpy.core.numerictypes', 'numpy.core._asarray', 'numpy.core._exceptions', 'numpy.core._methods', 'numpy.core.fromnumeric', 'numpy.core.shape_base', 'numpy.core._ufunc_config', 'numpy.core.arrayprint', 'numpy.core.numeric', 'numpy.core.defchararray', 'numpy.core.records', 'numpy.core.memmap', 'numpy.core.function_base', 'numpy.core.machar', 'numpy.core.getlimits', 'numpy.core.einsumfunc', 'numpy.core._multiarray_tests', 'numpy.core._add_newdocs', 'numpy.core._dtype_ctypes', 'numpy.core._internal', 'numpy._pytesttester', 'numpy.core', 'numpy.lib.mixins', 'numpy.lib.ufunclike', 'numpy.lib.type_check', 'numpy.lib.scimath', 'numpy.lib.twodim_base', 'numpy.linalg.lapack_lite', 'numpy.linalg._umath_linalg', 'numpy.linalg.linalg', 'numpy.linalg', 'numpy.matrixlib.defmatrix', 'numpy.matrixlib', 'numpy.lib.histograms', 'numpy.lib.function_base', 'numpy.lib.stride_tricks', 'numpy.lib.index_tricks', 'numpy.lib.nanfunctions', 'numpy.lib.shape_base', 'numpy.lib.polynomial', 'numpy.lib.utils', 'numpy.lib.arraysetops', 'numpy.lib.format', 'numpy.lib._datasource', 'numpy.lib._iotools', 'numpy.lib.npyio', 'numpy.lib.financial', 'numpy.lib.arrayterator', 'numpy.lib.arraypad', 'numpy.lib._version', 'numpy.lib', 'numpy.fft._pocketfft_internal', 'numpy.fft._pocketfft', 'numpy.fft.helper', 'numpy.fft', 'numpy.polynomial.polyutils', 'numpy.polynomial._polybase', 'numpy.polynomial.polynomial', 'numpy.polynomial.chebyshev', 'numpy.polynomial.legendre', 'numpy.polynomial.hermite', 'numpy.polynomial.hermite_e', 'numpy.polynomial.laguerre', 'numpy.polynomial', '_cython_0_29_21', 'numpy.random._common', 'secrets', 'numpy.random.bit_generator', 'numpy.random._bounded_integers', 'numpy.random._mt19937', 'numpy.random.mtrand', 'numpy.random._philox', 'numpy.random._pcg64', 'numpy.random._sfc64', 'numpy.random._generator', 'numpy.random._pickle', 'numpy.random', 'numpy.ctypeslib', 'numpy.ma.core', 'numpy.ma.extras', 'numpy.ma', 'numpy', 'matplotlib', 'gzip', 'matplotlib.cbook.deprecation', 'matplotlib.cbook', 'matplotlib._animation_data', 'matplotlib.animation', 'pyparsing', 'matplotlib.fontconfig_pattern', 'matplotlib.docstring', 'matplotlib._color_data', 'matplotlib.colors', 'cycler', 'matplotlib.rcsetup', 'matplotlib._version', 'matplotlib.ft2font', 'kiwisolver']\n",
"DEBUG:matplotlib:CACHEDIR=/home/blacklight/.cache/matplotlib\n",
"DEBUG:matplotlib.font_manager:Using fontManager instance from /home/blacklight/.cache/matplotlib/fontlist-v330.json\n",
"DEBUG:matplotlib.pyplot:Loaded backend module://ipykernel.pylab.backend_inline version unknown.\n",
"DEBUG:matplotlib.pyplot:Loaded backend module://ipykernel.pylab.backend_inline version unknown.\n"
]
}
],
"source": [
"import os\n",
"\n",
"from micmon.audio import AudioDirectory, AudioPlayer, AudioFile\n",
"from micmon.dataset import DatasetWriter\n",
"\n",
"basedir = os.path.expanduser(os.path.join('~', 'projects', 'baby-monitor'))\n",
"audio_dir = os.path.join(basedir, 'data', 'audio')\n",
"datasets_dir = os.path.join(basedir, 'data', 'datasets')\n",
"audio_dirs = AudioDirectory.scan(audio_dir)\n",
"cutoff_frequencies = [250, 7500]"
]
},
{
"cell_type": "markdown",
"source": [
"Play some audio samples"
],
"metadata": {
"collapsed": false
}
},
{
"cell_type": "code",
"execution_count": 3,
"outputs": [],
"source": [
"for audio in audio_dirs:\n",
" with AudioFile(audio, start='19:40', duration=10) as reader, \\\n",
" AudioPlayer() as player:\n",
" for sample in reader:\n",
" player.play(sample)"
],
"metadata": {
"collapsed": false,
"pycharm": {
"name": "#%%\n"
}
}
},
{
"cell_type": "markdown",
"source": [
"Plot the spectrum of the audio samples in the first 10 seconds of each audio file."
],
"metadata": {
"collapsed": false
}
},
{
"cell_type": "code",
"execution_count": 2,
"outputs": [
{
"data": {
"text/plain": "<Figure size 432x288 with 1 Axes>",
"image/png": "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\n"
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
},
{
"data": {
"text/plain": "<Figure size 432x288 with 1 Axes>",
"image/png": 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SL9BbSvuJJH9C22NeBBar6pP97Q/QC/iWx/yTwANVtVRVXwNuB36Itsd83kpjHEuuTWOgd3krgqmXJPTWVe+rqj8Y2HUceH3/9uuBD1/s2jZKVb2lqnZU1S56P9e/qqrX0PaY/xU4k+R5/aaXA/fS8JjpLbVcleRJ/ef5y+kdI2p5zOetNMbjwIEkT0yym97/lviHNd97VU3dB723Gfgc8M/AWze7ng0a48vo/cl1N/Cp/sc1wNPpHR3/fP/z0za71g0a/9XAR/q3mx4z8EJgvv+z/hDw1BkY828DnwXuAf4YeGJrYwbeT+8YwdfozcDfsNoYgbf2M+00sG89j+ml/5LUiGlccpEkLcNAl6RGGOiS1AgDXZIaYaBLUiMMdElqhIEuSY34PyxfSs5oHNsuAAAAAElFTkSuQmCC\n"
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
},
{
"data": {
"text/plain": "<Figure size 432x288 with 1 Axes>",
"image/png": 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bgZn+n/XngPPWwJp/H/gK8Cjwp8ArW1szcCe93xF8k94Z+AcWWyPwoX7TDgPbT+Y+fem/JDViNV5ykSSNYNAlqREGXZIaYdAlqREGXZIaYdAlqREGXZIa8f8yWyYAEz/RQQAAAABJRU5ErkJggg==\n"
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
},
{
"data": {
"text/plain": "<Figure size 432x288 with 1 Axes>",
"image/png": 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vAQ8Cfwq8sLU1A3cy+B3BNxmcgb9zqTUC7xk27TiweyVf06f+S1Ij1uMlF0nSAgy6JDXCoEtSIwy6JDXCoEtSIwy6JDXCoEtSI/4fMKk150RNm9wAAAAASUVORK5CYII=\n"
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
},
{
"data": {
"text/plain": "<Figure size 432x288 with 1 Axes>",
"image/png": "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\n"
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
},
{
"data": {
"text/plain": "<Figure size 432x288 with 1 Axes>",
"image/png": 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ReFvXtJPA3rP5nr70X5IaMYuXXCRJYxh0SWqEQZekRhh0SWqEQZekRhh0SWqEQZekRvw/vnkd6OJQg1oAAAAASUVORK5CYII=\n"
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"for audio in audio_dirs:\n",
" with AudioFile(audio, start=0, duration=4) as reader:\n",
" for sample in reader:\n",
" sample.plot_spectrum(low_freq=cutoff_frequencies[0],\n",
" high_freq=cutoff_frequencies[1])"
],
"metadata": {
"collapsed": false,
"pycharm": {
"name": "#%%\n"
}
}
},
{
"cell_type": "markdown",
"source": [
"Save the spectrum information and labels of the samples to a\n",
"different compressed file for each audio file."
],
"metadata": {
"collapsed": false
}
},
{
"cell_type": "code",
"execution_count": 2,
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Processing audio sample /home/blacklight/projects/baby-monitor/data/audio/2020-10-25_16-36-00\n",
"Processing audio sample /home/blacklight/projects/baby-monitor/data/audio/2020-10-24_19-53-00\n",
"Processing audio sample /home/blacklight/projects/baby-monitor/data/audio/2020-10-24_17-25-00\n"
]
}
],
"source": [
"for audio in audio_dirs:\n",
" dataset_file = os.path.join(datasets_dir, os.path.basename(audio.path) + '.npz')\n",
" print(f'Processing audio sample {audio.path}')\n",
"\n",
" with AudioFile(audio) as reader, \\\n",
" DatasetWriter(dataset_file,\n",
" low_freq=cutoff_frequencies[0],\n",
" high_freq=cutoff_frequencies[1]) as writer:\n",
" for sample in reader:\n",
" writer += sample"
],
"metadata": {
"collapsed": false,
"pycharm": {
"name": "#%%\n"
}
}
}
],
"metadata": {
"kernelspec": {
"display_name": "Python 3",
"language": "python",
"name": "python3"
},
"language_info": {
"codemirror_mode": {
"name": "ipython",
"version": 2
},
"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython2",
"version": "2.7.6"
}
},
"nbformat": 4,
"nbformat_minor": 0
}
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