{
"cells": [
{
"cell_type": "markdown",
"id": "7a9aa1cb",
"metadata": {},
"source": [
"## 미디 파일에 맞는 스타일 벡터 생성을 위한 곳"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "9c131428",
"metadata": {},
"outputs": [],
"source": [
"from music21 import note, chord\n",
"from music21.stream.base import Score\n",
"\n",
"def score_to_style_vector(score: Score) -> dict:\n",
" \"\"\"MIDI 파일(music21 score)을 분석하여 스타일 벡터를 생성하는 함수\"\"\"\n",
"\n",
" score.show('midi')\n",
"\n",
" # 1. Key & Mode\n",
" key_obj = score.analyze(\"key\")\n",
" key = key_obj.tonic.name # type: ignore\n",
" mode = key_obj.mode # type: ignore\n",
"\n",
" # 2. 멜로디 음표 리스트 추출\n",
" melody_notes = [n for n in score.flat.notes if isinstance(n, note.Note)]\n",
" pitches = [n.pitch.midi for n in melody_notes]\n",
" onsets = [n.offset for n in melody_notes]\n",
"\n",
" # 3. 코드 (화성) 분석\n",
" chords = [c for c in score.flat.getElementsByClass(chord.Chord)]\n",
" complex_chords = sum([1 for c in chords if len(c.pitches) > 3])\n",
" chord_complexity = complex_chords / (len(chords) + 1e-6) # 비율\n",
"\n",
" # 4. 멜로디 밀도 (단위 박자당 노트 수)\n",
" melody_density = len(melody_notes) / (score.highestTime + 1e-6) # type: ignore\n",
"\n",
" # 5. 싱코페이션 (off-beat 비율: 1/4 박자 단위 기준)\n",
" syncopation = sum([1 for o in onsets if (o % 1) != 0]) / (len(onsets) + 1e-6)\n",
"\n",
" # 6. 피치 범위\n",
" pitch_range = max(pitches) - min(pitches) if pitches else 0\n",
"\n",
" # 7. 사람이 생각하는 곡의 분위기\n",
" mood = input(\"분위기 입력 (이 중에서 선택: Happy, Chill, Emotional, Aggressive, Dreamy, Melodic): \")\n",
"\n",
" # 스타일 벡터 결과\n",
" style_vector = {\n",
" \"bpm\": 128, # 기본값 설정\n",
" \"key\": key,\n",
" \"mode\": mode,\n",
" \"chord_complexity\": round(chord_complexity, 3),\n",
" \"melody_density\": round(melody_density, 3),\n",
" \"syncopation\": round(syncopation, 3),\n",
" \"pitch_range\": pitch_range,\n",
" \"mood\": mood\n",
" }\n",
"\n",
" return style_vector"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "19ba84e1",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Skipping non-MIDI file: 0.mid\n",
"Skipping non-MIDI file: 1.mid\n",
"Skipping non-MIDI file: 10.mid\n",
"Skipping non-MIDI file: 11.mid\n",
"Skipping non-MIDI file: 12.mid\n",
"Skipping non-MIDI file: 13.mid\n",
"Skipping non-MIDI file: 14.mid\n",
"Skipping non-MIDI file: 15.mid\n",
"Skipping non-MIDI file: 16.mid\n",
"Skipping non-MIDI file: 17.mid\n",
"Skipping non-MIDI file: 18.mid\n",
"Skipping non-MIDI file: 19.mid\n",
"Skipping non-MIDI file: 2.mid\n",
"Skipping non-MIDI file: 20.mid\n",
"Skipping non-MIDI file: 21.mid\n",
"Skipping non-MIDI file: 22.mid\n",
"Skipping non-MIDI file: 23.mid\n",
"Skipping non-MIDI file: 24.mid\n",
"Skipping non-MIDI file: 25.mid\n",
"Skipping non-MIDI file: 26.mid\n",
"Skipping non-MIDI file: 27.mid\n",
"Skipping non-MIDI file: 28.mid\n",
"Skipping non-MIDI file: 29.mid\n",
"Skipping non-MIDI file: 3.mid\n",
"Skipping non-MIDI file: 30.mid\n",
"Skipping non-MIDI file: 31.mid\n",
"Skipping non-MIDI file: 32.mid\n",
"Skipping non-MIDI file: 33.mid\n",
"Skipping non-MIDI file: 4.mid\n",
"Skipping non-MIDI file: 5.mid\n",
"Skipping non-MIDI file: 6.mid\n",
"Skipping non-MIDI file: 7.mid\n",
"Skipping non-MIDI file: 8.mid\n",
"Skipping non-MIDI file: 9.mid\n"
]
}
],
"source": [
"from HarmonyMIDIToken import HarmonyMIDIToken as Tokenizer\n",
"import os\n",
"\n",
"#tokenized_data = []\n",
"\n",
"for filename in os.listdir(\"data\"):\n",
" if filename.endswith(\".mid\") and not filename in [i[\"name\"] for i in tokenized_data]:\n",
" MIDI = Tokenizer()\n",
" print(f\"file name: {filename}\")\n",
" MIDI.set_midi(os.path.join(\"data\", filename))\n",
" \n",
" vector = score_to_style_vector(MIDI.to_midi()) # type: ignore\n",
" \n",
" tokenized_data.append({\n",
" \"name\": filename,\n",
" \"vector\":vector,\n",
" \"token\":MIDI.token_id\n",
" })\n",
" else:\n",
" print(f\"Skipping non-MIDI or already Done file: {filename}\")\n",
" "
]
},
{
"cell_type": "code",
"execution_count": 2,
"id": "f79a6edf",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Tokenized MIDI data: 34\n"
]
}
],
"source": [
"print(\"Tokenized MIDI data:\", len(tokenized_data))"
]
},
{
"cell_type": "code",
"execution_count": 5,
"id": "21a9ba89",
"metadata": {},
"outputs": [],
"source": [
"import json # JSON 파일로 토크나이저 미디 데이터 저장\n",
"\n",
"with open('tokenized_midi_data.json', 'w') as f:\n",
" json.dump(tokenized_data, f, indent=4)"
]
},
{
"cell_type": "code",
"execution_count": 8,
"id": "dea532d4",
"metadata": {},
"outputs": [],
"source": [
"import json # JSON으로 저장한 토크나이저 미디 데이터 불러오기\n",
"\n",
"with open('tokenized_midi_data.json', 'r') as f:\n",
" tokenized_data = json.load(f)"
]
},
{
"cell_type": "markdown",
"id": "5a37da0b",
"metadata": {},
"source": [
"## 데이터 수정"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "995a6294",
"metadata": {},
"outputs": [
{
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"metadata": {},
"output_type": "display_data"
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],
"source": [
"from HarmonyMIDIToken import HarmonyMIDIToken as Tokenizer\n",
"\n",
"for item in tokenized_data:\n",
" if item['vector']['mood'] == \"IDK\":\n",
" MIDI = Tokenizer()\n",
" \n",
" MIDI.set_id(item['token'])\n",
" MIDI.to_midi().show('midi')\n",
" item['vector']['mood'] = input(\"분위기 재 입력\")"
]
},
{
"cell_type": "code",
"execution_count": 4,
"id": "68c42254",
"metadata": {},
"outputs": [],
"source": [
"for item in tokenized_data:\n",
" if not \"name\" in item.keys():\n",
" print(item)\n",
" item['name'] = item['vector']\n",
" item.pop('vector')"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "8cba97a6",
"metadata": {},
"outputs": [
{
"ename": "ValueError",
"evalue": "min() arg is an empty sequence",
"output_type": "error",
"traceback": [
"\u001b[31m---------------------------------------------------------------------------\u001b[39m",
"\u001b[31mValueError\u001b[39m Traceback (most recent call last)",
"\u001b[36mCell\u001b[39m\u001b[36m \u001b[39m\u001b[32mIn[7]\u001b[39m\u001b[32m, line 10\u001b[39m\n\u001b[32m 7\u001b[39m MIDI = Tokenizer()\n\u001b[32m 8\u001b[39m MIDI.set_midi(os.path.join(\u001b[33m\"\u001b[39m\u001b[33mdata\u001b[39m\u001b[33m\"\u001b[39m, filename))\n\u001b[32m---> \u001b[39m\u001b[32m10\u001b[39m item[\u001b[33m'\u001b[39m\u001b[33mtoken\u001b[39m\u001b[33m'\u001b[39m] = \u001b[43mMIDI\u001b[49m\u001b[43m.\u001b[49m\u001b[43mtoken_id\u001b[49m\n\u001b[32m 11\u001b[39m \u001b[38;5;66;03m# try:\u001b[39;00m\n\u001b[32m 12\u001b[39m \u001b[38;5;66;03m# except:\u001b[39;00m\n\u001b[32m 13\u001b[39m \u001b[38;5;66;03m# print(f\"{item['name']} 을 토크나이즈 하는데 실패함.\")\u001b[39;00m\n",
"\u001b[36mFile \u001b[39m\u001b[32mc:\\Users\\rrayy\\anaconda3\\envs\\diva\\Lib\\site-packages\\HarmonyMIDIToken\\tokenizer.py:164\u001b[39m, in \u001b[36mHarmonyMIDIToken.token_id\u001b[39m\u001b[34m(self)\u001b[39m\n\u001b[32m 161\u001b[39m durs = \u001b[38;5;28mlist\u001b[39m(\u001b[38;5;28mset\u001b[39m([m_dur, c_dur, b_dur]))\n\u001b[32m 162\u001b[39m durs = [item \u001b[38;5;28;01mfor\u001b[39;00m item \u001b[38;5;129;01min\u001b[39;00m durs \u001b[38;5;28;01mif\u001b[39;00m item != \u001b[32m0\u001b[39m]\n\u001b[32m--> \u001b[39m\u001b[32m164\u001b[39m main_time += \u001b[38;5;28;43mmin\u001b[39;49m\u001b[43m(\u001b[49m\u001b[43mdurs\u001b[49m\u001b[43m)\u001b[49m\n\u001b[32m 166\u001b[39m melody_time += m_dur\n\u001b[32m 167\u001b[39m chord_time += c_dur\n",
"\u001b[31mValueError\u001b[39m: min() arg is an empty sequence"
]
}
],
"source": [
"from HarmonyMIDIToken import HarmonyMIDIToken as Tokenizer\n",
"import os\n",
"\n",
"for item in tokenized_data:\n",
" filename = item['name']\n",
"\n",
" MIDI = Tokenizer()\n",
" MIDI.set_midi(os.path.join(\"data\", filename))\n",
"\n",
" try:\n",
" item['token'] = MIDI.token_id\n",
" except:\n",
" print(f\"{item['name']} 을 토크나이즈 하는데 실패함.\")"
]
},
{
"cell_type": "markdown",
"id": "df4c74b3",
"metadata": {},
"source": [
"## 데이터 전처리"
]
},
{
"cell_type": "code",
"execution_count": 9,
"id": "f7b77c0c",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"[[[81, 3, 65, 1, 3, 53, 3], [0, 1, 0, 1, 1, 0, 1], [81, 2, 65, 1, 2, 53, 2], [0, 1, 0, 1, 1, 0, 1], [81, 1, 65, 1, 1, 53, 1], [0, 1, 0, 1, 1, 0, 1], [79, 2, 65, 1, 2, 53, 2], [0, 1, 0, 1, 1, 0, 1], [79, 2, 65, 1, 2, 53, 2], [0, 1, 0, 1, 1, 0, 1], [84, 1, 60, 8, 1, 55, 1], [84, 2, 60, 8, 2, 55, 2], [0, 2, 0, 1, 2, 0, 2], [84, 2, 60, 8, 2, 55, 2], [83, 1, 60, 8, 1, 55, 1], [84, 2, 60, 8, 2, 55, 2], [79, 1, 60, 8, 2, 55, 2], [0, 1, 0, 1, 0, 0, 0], [83, 2, 0, 1, 1, 0, 1], [0, 0, 60, 8, 2, 55, 2], [0, 2, 0, 1, 2, 48, 2], [84, 3, 69, 5, 3, 57, 3], [0, 1, 0, 1, 1, 0, 1], [84, 2, 69, 5, 2, 57, 2], [83, 1, 69, 5, 1, 57, 1], [84, 2, 69, 5, 2, 57, 2], [79, 1, 69, 5, 1, 57, 1], [0, 1, 0, 1, 1, 0, 1], [83, 2, 69, 5, 2, 57, 2], [0, 2, 0, 1, 2, 50, 2], [81, 2, 67, 1, 2, 55, 2], [0, 1, 0, 1, 1, 0, 1], [81, 2, 67, 1, 2, 55, 2], [83, 1, 67, 1, 1, 55, 1], [84, 2, 67, 1, 2, 55, 2], [83, 2, 67, 1, 2, 55, 2], [0, 1, 0, 1, 1, 0, 1], [83, 2, 67, 1, 2, 55, 2], [0, 2, 0, 1, 2, 48, 2], [81, 3, 65, 1, 3, 53, 3], 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[0, 2, 0, 1, 2, 0, 2], [89, 1, 65, 1, 1, 53, 1], [88, 2, 65, 1, 2, 53, 2], [84, 3, 65, 1, 2, 53, 2], [0, 0, 0, 1, 3, 0, 3], [0, 2, 65, 1, 2, 53, 2], [79, 2, 65, 1, 2, 53, 2], [77, 2, 65, 1, 2, 48, 2], [77, 2, 0, 1, 2, 0, 2], [0, 2, 65, 1, 1, 48, 1], [89, 1, 65, 1, 2, 48, 2], [88, 2, 0, 1, 0, 0, 0], [84, 3, 65, 1, 2, 48, 2], [79, 2, 0, 1, 1, 0, 1], [0, 0, 65, 1, 2, 48, 2], [76, 2, 65, 1, 2, 48, 2], [77, 2, 65, 1, 2, 48, 2], [77, 2, 62, 2, 2, 50, 2], [0, 2, 0, 1, 2, 0, 2], [89, 1, 62, 2, 1, 50, 1], [88, 2, 62, 2, 2, 50, 2], [84, 3, 62, 2, 3, 50, 3], [0, 2, 0, 1, 2, 0, 2], [79, 2, 62, 2, 2, 50, 2], [84, 2, 62, 2, 2, 50, 2], [81, 2, 65, 1, 2, 45, 2], [0, 2, 0, 1, 2, 0, 2], [81, 1, 65, 1, 1, 45, 1], [79, 2, 65, 1, 2, 45, 2], [84, 3, 65, 1, 3, 45, 3], [79, 2, 65, 1, 2, 45, 2], [79, 2, 65, 1, 2, 45, 2], [77, 2, 65, 1, 2, 45, 2]], [[78, 2, 63, 2, 2, 51, 2], [0, 2, 0, 1, 2, 0, 2], [78, 1, 63, 2, 1, 51, 2], [78, 1, 63, 2, 1, 0, 0], [78, 1, 63, 2, 1, 0, 1], [85, 2, 63, 2, 2, 51, 2], [0, 3, 0, 1, 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2, 48, 2], [74, 2, 0, 1, 2, 48, 2], [75, 2, 0, 1, 2, 48, 2], [82, 2, 0, 1, 2, 48, 2], [0, 2, 0, 1, 2, 0, 2], [84, 2, 0, 1, 2, 48, 2], [0, 1, 0, 1, 1, 0, 1], [79, 1, 63, 1, 1, 55, 1], [79, 1, 63, 1, 1, 55, 1], [0, 5, 0, 1, 5, 0, 5], [75, 2, 63, 1, 2, 55, 2], [82, 2, 63, 1, 2, 55, 2], [0, 2, 0, 1, 2, 0, 2], [84, 2, 63, 1, 2, 55, 2], [0, 1, 0, 1, 1, 0, 1], [79, 1, 70, 1, 1, 50, 1], [79, 1, 70, 1, 1, 50, 1], [0, 1, 0, 1, 1, 0, 1], [75, 2, 70, 1, 2, 50, 2], [0, 2, 0, 1, 2, 0, 2], [75, 2, 70, 1, 2, 50, 2], [82, 2, 70, 1, 2, 50, 2], [75, 2, 70, 1, 2, 50, 2], [74, 2, 70, 1, 2, 50, 2], [75, 2, 70, 1, 2, 50, 2]], [[77, 2, 65, 1, 2, 53, 2], [0, 4, 0, 1, 4, 0, 4], [84, 2, 65, 1, 2, 53, 2], [84, 2, 65, 1, 2, 53, 2], [81, 2, 65, 1, 2, 53, 2], [81, 2, 65, 1, 2, 53, 2], [0, 2, 0, 1, 2, 0, 2], [79, 2, 60, 1, 4, 55, 4], [84, 1, 0, 1, 0, 0, 0], [76, 2, 0, 1, 0, 0, 0], [77, 2, 60, 1, 2, 55, 2], [0, 1, 0, 1, 2, 0, 2], [79, 2, 60, 1, 4, 55, 4], [84, 1, 0, 1, 0, 0, 0], [76, 2, 0, 1, 0, 0, 0], [77, 2, 60, 1, 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2], [0, 2, 0, 1, 0, 0, 0], [75, 2, 0, 1, 1, 0, 1], [0, 0, 68, 2, 2, 56, 2], [78, 2, 68, 2, 2, 56, 2], [83, 2, 66, 1, 2, 54, 4], [0, 5, 0, 1, 5, 0, 0], [83, 1, 66, 1, 1, 0, 1], [0, 1, 0, 1, 1, 54, 1], [83, 1, 66, 1, 1, 54, 1], [0, 2, 0, 1, 2, 54, 1], [85, 2, 66, 1, 2, 0, 1], [0, 0, 0, 1, 0, 54, 2], [87, 2, 66, 1, 2, 0, 0], [87, 2, 66, 1, 2, 54, 2], [87, 2, 66, 1, 2, 54, 2]], [[78, 2, 66, 1, 4, 54, 4], [0, 2, 0, 1, 0, 0, 0], [78, 2, 66, 1, 2, 54, 2], [75, 2, 0, 1, 2, 0, 2], [78, 2, 66, 1, 4, 49, 4], [80, 2, 0, 1, 0, 0, 0], [82, 2, 66, 1, 2, 49, 2], [82, 2, 0, 1, 2, 0, 2], [0, 2, 63, 2, 4, 51, 4], [78, 2, 0, 1, 0, 0, 0], [78, 2, 63, 2, 2, 51, 2], [75, 2, 0, 1, 2, 0, 2], [78, 2, 71, 1, 4, 47, 4], [80, 2, 0, 1, 0, 0, 0], [82, 2, 71, 1, 2, 47, 2], [82, 2, 0, 1, 2, 0, 2], [0, 2, 66, 1, 4, 54, 4], [78, 2, 0, 1, 0, 0, 0], [78, 2, 66, 1, 2, 54, 2], [75, 2, 0, 1, 2, 0, 2], [78, 2, 66, 1, 4, 49, 4], [75, 2, 0, 1, 0, 0, 0], [73, 2, 66, 1, 2, 49, 2], [83, 2, 0, 1, 2, 0, 2], [0, 2, 71, 1, 4, 47, 4], 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2, 50, 2], [77, 2, 62, 2, 2, 50, 2], [77, 1, 65, 1, 1, 53, 1], [0, 1, 0, 1, 1, 0, 1], [74, 1, 65, 1, 1, 53, 1], [81, 1, 65, 1, 1, 53, 1], [0, 1, 0, 1, 1, 0, 1], [74, 2, 65, 1, 2, 53, 2], [0, 1, 0, 1, 1, 0, 1], [74, 2, 62, 2, 2, 57, 2], [0, 2, 0, 1, 2, 0, 2], [76, 2, 62, 2, 2, 57, 2], [77, 2, 62, 2, 2, 57, 2], [77, 1, 67, 2, 1, 55, 1], [0, 1, 0, 1, 1, 0, 1], [74, 1, 67, 2, 1, 55, 1], [84, 1, 67, 2, 1, 55, 1], [0, 1, 0, 1, 1, 0, 1], [79, 2, 67, 2, 2, 55, 2], [0, 1, 0, 1, 1, 0, 1], [81, 2, 62, 2, 2, 50, 2], [0, 14, 0, 1, 14, 0, -2], [0, 0, 0, 1, 0, 50, 2], [0, 0, 0, 1, 0, 0, 2], [0, 0, 0, 1, 0, 50, 1], [0, 0, 0, 1, 0, 50, 1], [0, 0, 0, 1, 0, 50, 1], [0, 0, 0, 1, 0, 50, 1], [0, 0, 0, 1, 0, 50, 1], [0, 0, 0, 1, 0, 50, 1], [0, 0, 0, 1, 0, 50, 1], [0, 0, 0, 1, 0, 50, 1], [0, 0, 0, 1, 0, 50, 1], [0, 0, 0, 1, 0, 50, 1], [0, 0, 0, 1, 0, 50, 1], [0, 0, 0, 1, 0, 50, 1], [81, 2, 62, 2, 2, 50, 2], [81, 2, 62, 2, 2, 0, 2], [81, 2, 62, 2, 2, 50, 1], [0, 0, 0, 1, 0, 50, 1], [0, 0, 0, 1, 0, 50, 1], [0, 0, 0, 1, 0, 50, 1], [0, 0, 0, 1, 0, 50, 1], [0, 0, 0, 1, 0, 50, 1], [0, 0, 0, 1, 0, 50, 1], [0, 0, 0, 1, 0, 50, 1], [0, 0, 0, 1, 0, 50, 1], [0, 0, 0, 1, 0, 50, 1], [0, 0, 0, 1, 0, 50, 1], [0, 0, 0, 1, 0, 50, 1]], [[0, 4, 0, 1, 4, 53, 4], [91, 2, 0, 1, 2, 53, 2], [0, 2, 0, 1, 2, 0, 2], [91, 2, 0, 1, 2, 53, 2], [84, 2, 0, 1, 2, 53, 2], [0, 2, 0, 1, 2, 0, 2], [84, 2, 0, 1, 2, 53, 2], [0, 4, 60, 1, 4, 57, 4], [91, 2, 60, 1, 2, 57, 2], [0, 2, 0, 1, 2, 0, 2], [91, 2, 60, 1, 2, 57, 2], [84, 2, 60, 1, 2, 57, 2], [0, 2, 0, 1, 2, 0, 2], [88, 2, 60, 1, 2, 57, 2], [0, 4, 0, 1, 4, 55, 4], [91, 2, 0, 1, 2, 55, 2], [0, 2, 0, 1, 2, 0, 2], [91, 2, 0, 1, 2, 55, 2], [84, 2, 0, 1, 2, 55, 2], [0, 2, 0, 1, 2, 0, 2], [83, 2, 0, 1, 2, 55, 2], [0, 4, 60, 1, 4, 52, 4], [88, 2, 60, 1, 2, 52, 2], [0, 2, 0, 1, 2, 0, 2], [86, 2, 60, 1, 2, 52, 2], [83, 2, 60, 1, 2, 52, 2], [0, 2, 0, 1, 2, 0, 2], [84, 2, 60, 1, 2, 52, 2]], [[75, 2, 68, 1, 2, 51, 2], [0, 2, 0, 1, 2, 0, 2], [84, 2, 68, 1, 2, 51, 2], [0, 1, 0, 1, 1, 0, 1], [82, 2, 68, 1, 2, 51, 2], [0, 3, 0, 1, 3, 0, 3], [82, 2, 68, 1, 2, 51, 2], [75, 2, 68, 1, 2, 51, 2], [75, 2, 63, 1, 2, 46, 2], [0, 2, 0, 1, 2, 0, 2], [84, 2, 63, 1, 2, 46, 2], [0, 1, 0, 1, 1, 0, 1], [82, 2, 63, 1, 2, 46, 2], [0, 1, 0, 1, 1, 0, 1], [82, 2, 63, 1, 2, 46, 2], [80, 2, 63, 1, 2, 46, 2], [79, 2, 63, 1, 2, 46, 2], [79, 2, 60, 2, 2, 48, 2], [0, 2, 0, 1, 2, 0, 2], [79, 2, 60, 2, 2, 48, 2], [0, 1, 0, 1, 1, 0, 1], [79, 2, 60, 2, 2, 48, 2], [0, 3, 0, 1, 3, 0, 3], [82, 2, 60, 2, 2, 48, 2], [75, 2, 60, 2, 2, 48, 2], [79, 2, 70, 1, 2, 50, 2], [0, 2, 0, 1, 2, 0, 2], [79, 2, 70, 1, 2, 50, 2], [0, 1, 0, 1, 1, 0, 1], [75, 2, 70, 1, 2, 50, 2], [0, 1, 0, 1, 1, 0, 1], [82, 2, 70, 1, 2, 50, 2], [74, 2, 70, 1, 2, 50, 2], [75, 2, 70, 1, 2, 50, 2]]]\n"
]
}
],
"source": [
"from sklearn.preprocessing import OneHotEncoder, MinMaxScaler\n",
"from sklearn.compose import ColumnTransformer\n",
"import torch\n",
"import pandas as pd\n",
"\n",
"vector_df = pd.DataFrame([item['vector'] for item in tokenized_data])\n",
"\n",
"tokens = [item['token'] for item in tokenized_data]\n",
"\n",
"# 전처리 파이프라인\n",
"preprocessor = ColumnTransformer([\n",
" (\"cat\", OneHotEncoder(sparse_output=False), [\"mode\", \"mood\", \"key\"]),\n",
" (\"num\", MinMaxScaler(), [\"bpm\", \"chord_complexity\", \"melody_density\", \"syncopation\", \"pitch_range\"])\n",
"])\n",
"\n",
"X = preprocessor.fit_transform(vector_df)\n",
"\n",
"# # 토큰 시퀀스 패딩 (-1으로 뒤에 채우기)\n",
"# max_len = max(len(seq) for seq in tokens)\n",
"# padded_tokens = [seq + [-1]*(max_len - len(seq)) for seq in tokens]\n",
"\n",
"# # 각 샘플의 실제 길이\n",
"# lengths = torch.tensor([len(seq) for seq in tokens], dtype=torch.long)\n",
"\n",
"# Tensor 변환\n",
"#X_tensor = torch.tensor(X, dtype=torch.float32)\n",
"#Y_tensor = torch.tensor(padded_tokens, dtype=torch.long)\n",
"print(tokens)"
]
},
{
"cell_type": "code",
"execution_count": 5,
"id": "dd840788",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"X shape: torch.Size([34, 25])\n",
"X sample: tensor([1.0000, 0.0000, 0.0000, 0.0000, 0.0000, 0.0000, 1.0000, 0.0000, 0.0000,\n",
" 0.0000, 0.0000, 0.0000, 0.0000, 0.0000, 0.0000, 0.0000, 1.0000, 0.0000,\n",
" 0.0000, 0.0000, 0.0000, 1.0000, 0.1667, 1.0000, 0.1186])\n"
]
}
],
"source": [
"print(\"X shape:\", X_tensor.shape)\n",
"print(\"X sample:\", X_tensor[0])"
]
},
{
"cell_type": "code",
"execution_count": 6,
"id": "769af33a",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"min target: 0\n",
"unique values: tensor([ 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 16,\n",
" 22, 31, 35, 38, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52,\n",
" 53, 54, 55, 56, 57, 58, 59, 62, 63, 64, 65, 66, 67, 68,\n",
" 69, 70, 71, 72, 73, 75, 76, 77, 78, 79, 80, 81, 82, 83,\n",
" 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 100,\n",
" 102, 130, 202, 302])\n"
]
}
],
"source": [
"print(\"min target:\", Y_tensor.min().item())\n",
"print(\"unique values:\", torch.unique(Y_tensor))"
]
},
{
"cell_type": "code",
"execution_count": 9,
"id": "4f5f5dc1",
"metadata": {},
"outputs": [],
"source": [
"import torch\n",
"\n",
"torch.save({\n",
" \"X\": X_tensor,\n",
" \"Y\": Y_tensor,\n",
" \"lengths\": lengths\n",
"}, \"DIVA_dataset.pt\")"
]
},
{
"cell_type": "markdown",
"id": "224e349f",
"metadata": {},
"source": [
"## 전처리 끝!"
]
}
],
"metadata": {
"kernelspec": {
"display_name": "diva",
"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": "3.11.13"
}
},
"nbformat": 4,
"nbformat_minor": 5
}