3-MAESTRO2numpy.ipynb

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    "## Converts to numpy arrays the chords and durations of the MAESTRO dataset\n",
    "\n",
    "Data MAESTRO v3.0.0: https://magenta.tensorflow.org/datasets/maestro\n",
    "\n",
    "Curtis Hawthorne, Andriy Stasyuk, Adam Roberts, Ian Simon, Cheng-Zhi Anna Huang,\n",
    "  Sander Dieleman, Erich Elsen, Jesse Engel, and Douglas Eck. \"Enabling\n",
    "  Factorized Piano Music Modeling and Generation with the MAESTRO Dataset.\"\n",
    "  In International Conference on Learning Representations, 2019."
   ]
  },
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   "source": [
    "import os\n",
    "import pickle\n",
    "import numpy as np\n",
    "from music21 import note, chord, corpus, converter, stream, instrument\n",
    "import glob\n",
    "from tqdm.notebook import tqdm"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "_kl_Lci1gfPV"
   },
   "source": [
    "## Get Dataset"
   ]
  },
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   "source": [
    "data_dir = '## YOUR FOLDER PATH TO THE MAESTRO DATASET ##'\n",
    "\n",
    "# list of files\n",
    "midi_list = os.listdir(data_dir)\n",
    "\n",
    "# Load and make list of stream objects\n",
    "original_scores = []\n",
    "for midi in tqdm(midi_list):\n",
    "    score = converter.parse(os.path.join(data_dir,midi))\n",
    "    original_scores.append(score)"
   ]
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       " 'ORIG-MIDI_01_7_6_13_Group__MID--AUDIO_01_R1_2013_wav--1.midi']"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
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   ],
   "source": [
    "midi_list"
   ]
  },
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   "execution_count": 5,
   "metadata": {
    "scrolled": true
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    {
     "data": {
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       "127"
      ]
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     "execution_count": 5,
     "metadata": {},
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   "source": [
    "len(midi_list)"
   ]
  },
  {
   "cell_type": "markdown",
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    "id": "Y2vw2pFbhAYF"
   },
   "source": [
    "## Merge Notes to Chords"
   ]
  },
  {
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   "outputs": [
    {
     "data": {
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       "  0%|          | 0/127 [00:00<?, ?it/s]"
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   ],
   "source": [
    "# Merge notes into chords\n",
    "original_scores = [midi.chordify() for midi in tqdm(original_scores)]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
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   "outputs": [
    {
     "data": {
      "text/plain": [
       "<music21.chord.Chord G#3 F4 C#5>"
      ]
     },
     "execution_count": 7,
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    "## Get Notes and Duration Information"
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    "original_chords = [[] for _ in original_scores]\n",
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    "original_durations_saved= np.array(original_durations, dtype=object)\n",
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    "np.save('original_chords_MAESTRO', original_chords_saved)\n",
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