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import collections
import io
import pandas as pd
import matplotlib.pyplot as plt
from matplotlib.patches import Rectangle
from PIL import Image
import note_seq
import copy
# Value of BPM for 1 second
BPM_1_SECOND = 60
# Variables to change based on the time signature
numerator = ""
denominator = ""
def token_sequence_to_note_sequence(token_sequence,
use_program=True,
use_drums=False,
instrument_mapper=None,
only_guitar=True):
if isinstance(token_sequence, str):
token_sequence = token_sequence.split()
note_sequence = empty_note_sequence()
# Render all notes.
current_program = 1
current_is_drum = False
current_instrument = 0
track_count = 0
for token_index, token in enumerate(token_sequence):
if token == "PIECE_START":
pass
elif token == "PIECE_END":
print("The end.")
break
elif token.startswith("TIME_SIGNATURE="):
time_signature_str = token.split("=")[-1]
numerator = int(time_signature_str.split("_")[0])
denominator = int(time_signature_str.split("_")[-1])
time_signature = note_sequence.time_signatures.add()
time_signature.numerator = numerator
time_signature.denominator = denominator
elif token.startswith("BPM="):
bpm_str = token.split("=")[-1]
bpm = int(bpm_str)
note_sequence.tempos[0].qpm = bpm
pulse_duration, bar_duration = duration_in_sec(
bpm, numerator, denominator
)
elif token == "TRACK_START":
current_bar_index = 0
track_count += 1
pass
elif token == "TRACK_END":
pass
elif token == "KEYS_START":
pass
elif token == "KEYS_END":
pass
elif token.startswith("KEY="):
pass
elif token.startswith("INST"):
instrument = token.split("=")[-1]
if instrument != "DRUMS" and use_program:
if instrument_mapper is not None:
if instrument in instrument_mapper:
instrument = instrument_mapper[instrument]
current_program = int(instrument)
current_instrument = track_count
current_is_drum = False
if instrument == "DRUMS" and use_drums:
current_instrument = 0
current_program = 0
current_is_drum = True
elif token == "BAR_START":
current_time = (current_bar_index * bar_duration)
current_notes = {}
elif token == "BAR_END":
current_bar_index += 1
pass
elif token.startswith("NOTE_ON"):
pitch = int(token.split("=")[-1])
note = note_sequence.notes.add()
note.start_time = current_time
note.end_time = current_time + denominator * pulse_duration
note.pitch = pitch
note.instrument = current_instrument
note.program = current_program
note.velocity = 80
note.is_drum = current_is_drum
current_notes[pitch] = note
elif token.startswith("NOTE_OFF"):
pitch = int(token.split("=")[-1])
if pitch in current_notes:
note = current_notes[pitch]
note.end_time = current_time
elif token.startswith("TIME_DELTA"):
delta = float(token.split("=")[-1]) * (0.25) * pulse_duration
current_time += delta
elif token.startswith("DENSITY="):
pass
elif token == "[PAD]":
pass
else:
#print(f"Ignored token {token}.")
pass
# Make the instruments right.
instruments_drums = []
for note in note_sequence.notes:
pair = [note.program, note.is_drum]
if pair not in instruments_drums:
instruments_drums += [pair]
note.instrument = instruments_drums.index(pair)
if only_guitar:
for note in note_sequence.notes:
if not note.is_drum:
# Midi number for guitar is 23
note.instrument = 24
note.program = 24
return note_sequence
# Calculate the duration in seconds of pulse and bar
def duration_in_sec(bpm, numerator, denominator):
pulse_duration = BPM_1_SECOND / bpm
number_of_quarters_per_bar = (4 / denominator) * numerator
bar_duration = pulse_duration * number_of_quarters_per_bar
return pulse_duration, bar_duration
def empty_note_sequence(qpm=120, total_time=0.0):
note_sequence = note_seq.protobuf.music_pb2.NoteSequence()
note_sequence.tempos.add().qpm = qpm
#note_sequence.ticks_per_quarter = note_seq.constants.STANDARD_PPQ
note_sequence.total_time = total_time
return note_sequence
# Generate piano_roll
def sequence_to_pandas_dataframe(sequence):
pd_dict = collections.defaultdict(list)
for note in sequence.notes:
pd_dict["start_time"].append(note.start_time)
pd_dict["end_time"].append(note.end_time)
pd_dict["duration"].append(note.end_time - note.start_time)
pd_dict["pitch"].append(note.pitch)
return pd.DataFrame(pd_dict)
def dataframe_to_pianoroll_img(df):
fig = plt.figure(figsize=(8, 5))
ax = fig.add_subplot(111)
ax.scatter(df.start_time, df.pitch, c="white")
for _, row in df.iterrows():
ax.add_patch(Rectangle((row["start_time"], row["pitch"]-0.4), row["duration"], 0.4, color="black"))
plt.xlabel('time (sec.)', fontsize=18)
plt.ylabel('pitch (MIDI)', fontsize=16)
return fig
def fig2img(fig):
"""Convert a Matplotlib figure to a PIL Image and return it"""
import io
buf = io.BytesIO()
fig.savefig(buf, format="png")
buf.seek(0)
img = Image.open(buf)
return img
def create_image_from_note_sequence(sequence):
df_sequence = sequence_to_pandas_dataframe(sequence)
fig = dataframe_to_pianoroll_img(df_sequence)
img = fig2img(fig)
return img |