Music Generation.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Using TensorFlow backend.\n"
     ]
    }
   ],
   "source": [
    "from music21 import converter,instrument,note,chord,stream\n",
    "import glob\n",
    "import pickle\n",
    "import numpy as np\n",
    "import pandas as pd\n",
    "from keras.models import Sequential\n",
    "from keras.layers import *\n",
    "from keras.utils import to_categorical\n",
    "from keras.callbacks import EarlyStopping,ModelCheckpoint"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "midi = converter.parse(\"midi_songs/EyesOnMePiano.mid\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<music21.stream.Score 0x1f95f874ac8>\n"
     ]
    }
   ],
   "source": [
    "print(midi)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "\n",
       "                <div id='midiPlayerDiv15311'></div>\n",
       "                <link rel=\"stylesheet\" href=\"//cuthbertLab.github.io/music21j/css/m21.css\"\n",
       "                    type=\"text/css\" />\n",
       "                <script>\n",
       "                require.config({\n",
       "                    paths: {'music21': '//cuthbertLab.github.io/music21j/src/music21'}\n",
       "                });\n",
       "                require(['music21'], function() {\n",
       "                               mp = new music21.miditools.MidiPlayer();\n",
       "                               mp.addPlayer('#midiPlayerDiv15311');\n",
       "                               mp.base64Load('data:audio/midi;base64,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');\n",
       "                        });\n",
       "                </script>"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "midi.show('midi')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "#midi.show('text')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "elements_to_parse = midi.flat.notes"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "1421\n"
     ]
    }
   ],
   "source": [
    "print(len(elements_to_parse))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<music21.note.Note A> 0.0\n",
      "<music21.note.Note A> 0.0\n",
      "<music21.note.Note A> 0.0\n",
      "<music21.note.Note A> 0.25\n",
      "<music21.note.Note G> 2/3\n",
      "<music21.note.Note G> 2/3\n",
      "<music21.note.Note F#> 1.0\n",
      "<music21.note.Note F#> 1.25\n",
      "<music21.note.Note D> 1.5\n",
      "<music21.note.Note D> 1.5\n"
     ]
    }
   ],
   "source": [
    "i=0\n",
    "for elem in elements_to_parse:\n",
    "    print(elem,elem.offset)\n",
    "    i+=1\n",
    "    if i==10:\n",
    "        break"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "['A4', 'E5', 'C#4', 'F#4', 'A4', 'E5', 'C#4', 'F#4', 'C#5', 'A3', 'C#5', 'A3', 'F#4', 'B4', 'G3', 'E4', 'F#4', 'B4', 'G3', 'E4', 'C#5', 'A3', 'C#5', 'A3', 'D5', 'B3', 'D5', 'B3', '1+6', '9+2']\n"
     ]
    }
   ],
   "source": [
    "def generate_notes_and_chords(elements_to_parse,notes_demo=[]):\n",
    "    for elem in elements_to_parse:\n",
    "        if isinstance(elem,note.Note):\n",
    "            notes_demo.append(str(elem.pitch))\n",
    "        elif isinstance(elem,chord.Chord):\n",
    "            notes_demo.append('+'.join([str(e) for e in elem.normalOrder]))\n",
    "    return notes_demo\n",
    "print(generate_notes_and_chords(elements_to_parse,[])[40:70])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [],
   "source": [
    "notes = []\n",
    "for file in glob.glob(\"midi_songs/*.mid\"):\n",
    "    midi = converter.parse(file)\n",
    "    elements_to_parse = midi.flat.notes\n",
    "    generate_notes_and_chords(elements_to_parse,notes)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "['4+9', 'E2', '4+9', '4+9', '4+9', '4+9', '4+9', '4+9', '4+9', '11+4', '4+9', '11+4', '4+9', '4+9', '4+9', '4+9', '4+9', '0+4', 'E2', '4+9', '0+4', '4+9', '4+9', '4+9', '4+9', '4+9', '9+2', '4+9', '9+2', '9+2', '4+9', '4+9', '4+9', '4+9', '4+9', '4+9', 'E2', '4+9', '4+9', '4+9', '4+9', '4+9', 'E5', 'F5', 'G#5', 'A5', '4+9', '4+9', '5+11', '4+9', '5+11', '4+9', '4+9', '4+9', 'E5', 'F5', 'G#5', 'A5', '4+9', '4+9', '9+0', 'E2', '4+9', '9+0', '4+9', '4+9', '4+9', 'E5', 'F5', 'G#5', 'A5', '4+9', '4+9', '11+2', '4+9', '11+2', '11+2', '4+9', '4+9', '4+9', 'E5', 'F5', 'G#5', 'A5', '4+9', '4+9', '3+7+11', 'E-2', '3+7+11', 'B2', 'G2', '1+5+9', 'F#2', '1+5+9', '3+7+11', 'E-2', '3+7+11', 'G2', 'B2', 'E-3']\n"
     ]
    }
   ],
   "source": [
    "print(notes[:100])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "60498"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(notes)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [],
   "source": [
    "pd.DataFrame(notes).to_csv(\"all_notes.csv\",index=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [],
   "source": [
    "notes = pd.read_csv(\"all_notes.csv\").iloc[:,0].values"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [],
   "source": [
    "vocab = set(notes)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "359\n"
     ]
    }
   ],
   "source": [
    "n_vocab = len(vocab)\n",
    "print(n_vocab)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Total notes-  60498\n",
      "Unique notes-  359\n"
     ]
    }
   ],
   "source": [
    "print(\"Total notes- \", len(notes))\n",
    "print(\"Unique notes- \",  len(vocab))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [],
   "source": [
    "sequence_length =100"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [],
   "source": [
    "pitch_name = sorted(vocab)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [],
   "source": [
    "ele_to_int = dict((ele,num) for num,ele in enumerate(pitch_name))\n",
    "int_to_ele = dict((num,ele) for num,ele in enumerate(pitch_name))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [],
   "source": [
    "network_input = []\n",
    "network_output = []\n",
    "for i in range(len(notes)-sequence_length):\n",
    "    seq_in = notes[i:i+sequence_length]\n",
    "    seq_out = notes[i+sequence_length]\n",
    "    network_input.append([ele_to_int[ch] for ch in seq_in])\n",
    "    network_output.append([ele_to_int[seq_out]])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "60398\n"
     ]
    }
   ],
   "source": [
    "n_patterns = len(network_input)\n",
    "print(n_patterns)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(60398, 100, 1)\n",
      "(60398, 359)\n"
     ]
    }
   ],
   "source": [
    "network_input = np.reshape(network_input,(n_patterns,sequence_length,1))\n",
    "print(network_input.shape)\n",
    "network_output = to_categorical(network_output)\n",
    "print(network_output.shape)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [],
   "source": [
    "normalized_network_input = network_input/float(n_vocab)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Model: \"sequential_1\"\n",
      "_________________________________________________________________\n",
      "Layer (type)                 Output Shape              Param #   \n",
      "=================================================================\n",
      "lstm_1 (LSTM)                (None, 100, 512)          1052672   \n",
      "_________________________________________________________________\n",
      "dropout_1 (Dropout)          (None, 100, 512)          0         \n",
      "_________________________________________________________________\n",
      "lstm_2 (LSTM)                (None, 100, 512)          2099200   \n",
      "_________________________________________________________________\n",
      "dropout_2 (Dropout)          (None, 100, 512)          0         \n",
      "_________________________________________________________________\n",
      "lstm_3 (LSTM)                (None, 512)               2099200   \n",
      "_________________________________________________________________\n",
      "dense_1 (Dense)              (None, 256)               131328    \n",
      "_________________________________________________________________\n",
      "dropout_3 (Dropout)          (None, 256)               0         \n",
      "_________________________________________________________________\n",
      "dense_2 (Dense)              (None, 359)               92263     \n",
      "=================================================================\n",
      "Total params: 5,474,663\n",
      "Trainable params: 5,474,663\n",
      "Non-trainable params: 0\n",
      "_________________________________________________________________\n"
     ]
    }
   ],
   "source": [
    "model = Sequential()\n",
    "model.add(LSTM(512,input_shape = (normalized_network_input.shape[1],normalized_network_input.shape[2]),return_sequences=True))\n",
    "model.add(Dropout(0.3))\n",
    "model.add(LSTM(512,return_sequences=True))\n",
    "model.add(Dropout(0.3))\n",
    "model.add(LSTM(512))\n",
    "model.add(Dense(256))\n",
    "model.add(Dropout(0.3))\n",
    "model.add(Dense(n_vocab,activation='softmax'))\n",
    "\n",
    "model.summary()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [],
   "source": [
    "model.compile(loss='categorical_crossentropy',optimizer='adam')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 1/100\n",
      " 8832/60398 [===>..........................] - ETA: 47:58 - loss: 4.8695"
     ]
    }
   ],
   "source": [
    "checkPoint = ModelCheckpoint(\"best_model.hdf5\",monitor='val_loss',verbose=False,save_best_only=True)\n",
    "earlyStop = EarlyStopping(monitor='val_loss',verbose=False,patience=10)\n",
    "history = model.fit(normalized_network_input,network_output,batch_size=64,epochs=100,callbacks=[checkPoint,earlyStop])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [],
   "source": [
    "model.load_weights(\"best_model.hdf5\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [],
   "source": [
    "network_input = []\n",
    "for i in range(len(notes)-sequence_length):\n",
    "    seq_in = notes[i:i+sequence_length]\n",
    "    network_input.append([ele_to_int[ch] for ch in seq_in])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [],
   "source": [
    "start = np.random.randint(len(network_input)-1)\n",
    "pattern = network_input[start]\n",
    "prediction_output = []\n",
    "\n",
    "for note_idx in range(300):\n",
    "    prediction_input = np.reshape(pattern,(1,len(pattern),1))\n",
    "    prediction_input = prediction_input/float(n_vocab)\n",
    "    \n",
    "    prediction = model.predict(prediction_input,verbose=0)\n",
    "    \n",
    "    idx = np.argmax(prediction)\n",
    "    result = int_to_ele[idx]\n",
    "    prediction_output.append(result)\n",
    "    \n",
    "    pattern.append(idx)\n",
    "    pattern = pattern[1:]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "['9', '9+2', '9', '4+9', 'E3', '0+4', '9', '9', '9', '9', 'E3', 'E3', 'E3', 'B3', '9', '9+0', '9+2', '9', '11', '9', 'A2', '11', '9', 'A2', '9', '9', '9', '9', '9+0+4', '9', '9+0+4', '9+0+4', '7+11+2', '7+11+2', '7+11+2', 'A2', '9', 'B3', '9+0+4', 'A2', '9+0+4', 'A2', '7+11+2', 'A2', '7+11+2', 'A2', '7+11+2', 'A2', '6+11+0', '8', '9+0+4', 'A2', '9+0+4', 'A2', '6+11+0', '8', 'D4', 'A2', 'A3', 'G5', '10+2+5', 'G2', 'A3', 'A3', '4+9', '9', '8', '0+3', '9+0+4', '9', '0+4', '9', 'C3', 'E3', '4+9', '9', 'A2', '9', '9', '9', '9', '9+0+4', '9+0+4', '9+0+4', 'B3', '9+0+4', 'A3', '9+0+4', 'A2', 'B5', 'A2', 'A2', 'E2', 'G4', 'E2', '7+11+2', 'A2', '9+2', '9', '6+11+0', 'A2', '7+11+2', 'A2', '7+11+2', '7', '7', 'A2', '9+0+4', 'A2', '7', 'A2', '9+2', 'A2', '7', 'G3', '7', 'A2', '7', 'G3', '2+7', 'G3', '7', 'G3', '7+11', '4', '7', 'A2', '7', '7', '6+9', '4+8+11', 'C3', 'D4', '7', '7', 'D4', '9+2', '9', '7+11+2', '2', 'A2', '2+6+9', '0+4', '6+9', '2+6+9', '2', '6+9', '2+7', 'A2', '9+2', '9', '9+0+4', '9', '9+0+4', '9', 'B3', '9', 'B3', '9', '2+7', '7', '2+7', '7', '2+7', '7', '2+7', '7', '2+7', '7', '2+7', '7', '2+7', '7', '2+5+7', '7', '2+5+7', '7', '2+5+7', '7', '1+4+7', '7', '1+4+7', '1+4+7', '7', '0+3+7', '0+3+7', '7', '0+3+7', '2+7', '7', '2+7', '7', '2+7', '7', '2+7', '7', '2+7', '7', '2+7', '7', '2+5+7', '7', '2+5+7', '7', '2+5+7', '7', '1+4+7', '7', '1+4+7', '1+4+7', '7', '0+3+7', '0+3+7', '7', '0+3+7', '2+7', '7', '11+2+5', '7', '2+7', '7', '2+7', '7', '2+7', '7', '2+7', '7', '2+7', '7', '2+5+7', '7', '2+5+7', '7', '2+5+7', '7', '1+4+7', '7', '1+4+7', '1+4+7', '7', '0+3+7', '0+3+7', '7', '0+3+7', 'G4', '7', '7', 'D4', '7', '7', '7', '7', '2+7', '7', '7', '7', '7', '0+2+7', '7', '7', '7', '10+0+5', '7', '7', 'A4', '0+5', '7', '7', '7', '7', 'A3', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7']\n"
     ]
    }
   ],
   "source": [
    "print(prediction_output)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [],
   "source": [
    "offset = 0\n",
    "output_notes = []\n",
    "for pattern in prediction_output:\n",
    "    if ('+' in pattern) or (pattern.isdigit()):\n",
    "        notes_in_chord = pattern.split('+')\n",
    "        temp_notes = []\n",
    "        for current_node in notes_in_chord:\n",
    "            new_note = note.Note(int(current_node))\n",
    "            new_note.storedInstrument = instrument.Piano()\n",
    "            temp_notes.append(new_note)\n",
    "        \n",
    "        new_chord = chord.Chord(temp_notes)\n",
    "        new_chord.offset = offset\n",
    "        output_notes.append(new_chord)\n",
    "        \n",
    "    else:\n",
    "        new_note = note.Note(pattern)\n",
    "        new_note.offset = offset\n",
    "        new_note.storedInstrument = instrument.Piano()\n",
    "        output_notes.append(new_note)\n",
    "    offset+=float(np.random.randint(1,20))/20.0"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'new_song.mid'"
      ]
     },
     "execution_count": 36,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "midi_stream = stream.Stream(output_notes)\n",
    "midi_stream.write('midi',fp = 'new_song.mid')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "\n",
       "                <div id='midiPlayerDiv170595'></div>\n",
       "                <link rel=\"stylesheet\" href=\"//cuthbertLab.github.io/music21j/css/m21.css\"\n",
       "                    type=\"text/css\" />\n",
       "                <script>\n",
       "                require.config({\n",
       "                    paths: {'music21': '//cuthbertLab.github.io/music21j/src/music21'}\n",
       "                });\n",
       "                require(['music21'], function() {\n",
       "                               mp = new music21.miditools.MidiPlayer();\n",
       "                               mp.addPlayer('#midiPlayerDiv170595');\n",
       "                               mp.base64Load('data:audio/midi;base64,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');\n",
       "                        });\n",
       "                </script>"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "midi_stream.show('midi')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.7.7"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}