guitar_tab / guitar_tab.py
vladsaveliev
Add full dataset, with instrument field
cefd971
raw
history blame
7.87 kB
import itertools
import os
from pathlib import Path
import datasets
from typing import Optional
from tqdm import tqdm
from pathlib import Path
import re
datasets.logging.set_verbosity_info()
_DESCRIPTION = """\
Dataset of music tablature, in alphaTex (https://alphatab.net/docs/alphatex)
format, converted from Guitar Pro files (gp3, gp4, gp5, which are downloaded
from https://rutracker.org/forum/viewtopic.php?t=2888130
"""
INSTRUMENT_MAP = {
0: "Acoustic Grand Piano",
1: "Bright Grand Piano",
2: "Electric Grand Piano",
3: "Honky tonk Piano",
4: "Electric Piano 1",
5: "Electric Piano 2",
6: "Harpsichord",
7: "Clavinet",
8: "Celesta",
9: "Glockenspiel",
10: "Musicbox",
11: "Vibraphone",
12: "Marimba",
13: "Xylophone",
14: "Tubularbells",
15: "Dulcimer",
16: "Drawbar Organ",
17: "Percussive Organ",
18: "Rock Organ",
19: "Church Organ",
20: "Reed Organ",
21: "Accordion",
22: "Harmonica",
23: "Tango Accordion",
24: "Acoustic Guitar Nylon",
25: "Acoustic Guitar Steel",
26: "Electric Guitar Jazz",
27: "Electric Guitar Clean",
28: "Electric Guitar Muted",
29: "Overdriven Guitar",
30: "Distortion Guitar",
31: "Guitar Harmonics",
32: "Acoustic Bass",
33: "Electric Bass Finger",
34: "Electric Bass Pick",
35: "Fretless Bass",
36: "Slap Bass 1",
37: "Slap Bass 2",
38: "Synth Bass 1",
39: "Synth Bass 2",
40: "Violin",
41: "Viola",
42: "Cello",
43: "Contrabass",
44: "Tremolo Strings",
45: "Pizzicato Strings",
46: "Orchestral Harp",
47: "Timpani",
48: "String Ensemble 1",
49: "String Ensemble 2",
50: "Synth Strings 1",
51: "Synth Strings 2",
52: "Choir Aahs",
53: "Voice Oohs",
54: "Synth Voice",
55: "Orchestra Hit",
56: "Trumpet",
57: "Trombone",
58: "Tuba",
59: "Muted Trumpet",
60: "French Horn",
61: "Brass Section",
62: "Synth Brass 1",
63: "Synth Brass 2",
64: "Soprano Sax",
65: "Alto Sax",
66: "Tenor Sax",
67: "Baritone Sax",
68: "Oboe",
69: "English Horn",
70: "Bassoon",
71: "Clarinet",
72: "Piccolo",
73: "Flute",
74: "Recorder",
75: "Pan Flute",
76: "Blown bottle",
77: "Shakuhachi",
78: "Whistle",
79: "Ocarina",
80: "Lead 1 Square",
81: "Lead 2 Sawtooth",
82: "Lead 3 Calliope",
83: "Lead 4 Chiff",
84: "Lead 5 Charang",
85: "Lead 6 Voice",
86: "Lead 7 Fifths",
87: "Lead 8 Bass and Lead",
88: "Pad 1 newage",
89: "Pad 2 warm",
90: "Pad 3 polysynth",
91: "Pad 4 choir",
92: "Pad 5 bowed",
93: "Pad 6 metallic",
94: "Pad 7 halo",
95: "Pad 8 sweep",
96: "Fx 1 rain",
97: "Fx 2 soundtrack",
98: "Fx 3 crystal",
99: "Fx 4 atmosphere",
100: "Fx 5 brightness",
101: "Fx 6 goblins",
102: "Fx 7 echoes",
103: "Fx 8 scifi",
104: "Sitar",
105: "Banjo",
106: "Shamisen",
107: "Koto",
108: "Kalimba",
109: "Bag pipe",
110: "Fiddle",
111: "Shanai",
112: "Tinkle Bell",
113: "Agogo",
114: "Steel Drums",
115: "Woodblock",
116: "Taiko Drum",
117: "Melodic Tom",
118: "Synth Drum",
119: "Reverse Cymbal",
120: "Guitar Fret Noise",
121: "Breath Noise",
122: "Seashore",
123: "Bird Tweet",
124: "Telephone Ring",
125: "Helicopter",
126: "Applause",
127: "Gunshot",
}
class Builder(datasets.GeneratorBasedBuilder):
VERSION = datasets.Version("1.2.1")
def _info(self):
return datasets.DatasetInfo(
description=_DESCRIPTION,
features=datasets.Features(
{
"file": datasets.Value("string"),
"tex": datasets.Value("string"),
"title": datasets.Value("string"),
"track_name": datasets.Value("string"),
"track_number": datasets.Value("int32"),
"instrument": datasets.Value("string"),
"tempo": datasets.Value("int32"),
"tuning": datasets.Value("string"),
"frets": datasets.Value("int32"),
# "subtitle": datasets.Value("string"),
# "artist": datasets.Value("string"),
# "album": datasets.Value("string"),
# "words": datasets.Value("string"),
# "music": datasets.Value("string"),
# "copyright": datasets.Value("string"),
# "tab": datasets.Value("string"),
# "instructions": datasets.Value("string"),
}
),
)
def _split_generators(self, dl_manager: datasets.DownloadManager):
data_dir = dl_manager.download_and_extract("data.zip")
if paths := list(Path(data_dir).glob("**/*.tex")):
print(f"Found {len(paths)} AlphaTex files")
else:
raise ValueError(f"No GP files found in {data_dir}")
return [
datasets.SplitGenerator(
name=datasets.Split.TRAIN,
gen_kwargs={
"filepaths": [p for p in paths],
},
),
]
def _generate_examples(self, filepaths):
for idx, path in enumerate(filepaths):
with open(path) as f:
examples = _parse_examples(f.read())
for example in examples:
example["file"] = path.name
yield f"{idx}-{example['track_number']}", example
def _parse_examples(tex):
"""
Returns a dictionary for each track
"""
tmpl = {
"file": None,
"tex": None,
"title": None,
"track_name": None,
"track_number": None,
"instrument": None,
"tempo": None,
"tuning": None,
"frets": None,
}
tracks = [tmpl.copy()]
def _parse_track_header(k, v):
if k == "instrument":
tracks[-1][k] = INSTRUMENT_MAP.get(int(v), "unknown")
elif k == "tuning":
tracks[-1][k] = v.split(" ")
elif k == "frets":
tracks[-1][k] = int(v)
lines = (l.strip() for l in tex.splitlines() if l.strip())
for line in itertools.takewhile(lambda l: l != ".", lines):
assert line.startswith("\\")
line = line.lstrip("\\")
kv = line.split(" ", 1)
if len(kv) == 1:
continue
k, v = kv
if k in [
"title",
# "subtitle",
# "artist",
# "album",
# "words",
# "music",
# "copyright",
# "tab",
# "instructions",
]:
tracks[-1][k] = v.strip('"').strip("'")
elif k == "tempo":
tracks[-1][k] = int(v)
else:
_parse_track_header(k, v)
track_lines = []
for line in lines:
if line.startswith("\\"):
line = line.lstrip("\\")
kv = line.split(" ", 1)
if len(kv) == 2:
k = kv[0]
v = kv[1].strip('"').strip("'")
else:
k = kv[0]
v = None
if k == "track":
if track_lines:
tracks[-1]["tex"] = " ".join(track_lines)
track_lines = []
tracks.append(tmpl.copy())
track_number = len(tracks) + 1
tracks[-1]["track_number"] = track_number
tracks[-1]["track_name"] = v if v else f"Track {track_number}"
else:
_parse_track_header(k, v)
else:
track_lines.append(line)
if track_lines:
tracks[-1]["tex"] = " ".join(track_lines)
return tracks