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Running
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Zero
File size: 2,886 Bytes
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import fluidsynth
import numpy as np
class MidiSynthesizer:
def __init__(self, soundfont_path, sample_rate=44100):
self.soundfont_path = soundfont_path
self.sample_rate = sample_rate
fl = fluidsynth.Synth(samplerate=float(sample_rate))
sfid = fl.sfload(soundfont_path)
self.devices = [[fl, sfid, False]]
def get_fluidsynth(self):
for device in self.devices:
if not device[2]:
device[2] = True
return device
fl = fluidsynth.Synth(samplerate=float(self.sample_rate))
sfid = fl.sfload(self.soundfont_path)
device = [fl, sfid, True]
self.devices.append(device)
return device
def release_fluidsynth(self, device):
device[0].get_samples(self.sample_rate*5) # wait for silence
device[0].system_reset()
device[2] = False
def synthesis(self, midi_opus):
ticks_per_beat = midi_opus[0]
event_list = []
for track_idx, track in enumerate(midi_opus[1:]):
abs_t = 0
for event in track:
abs_t += event[1]
event_new = [*event]
event_new[1] = abs_t
event_list.append(event_new)
event_list = sorted(event_list, key=lambda e: e[1])
tempo = int((60 / 120) * 10 ** 6) # default 120 bpm
ss = np.empty((0, 2), dtype=np.int16)
device = self.get_fluidsynth()
fl, sfid = device[:-1]
last_t = 0
for c in range(16):
fl.program_select(c, sfid, 128 if c == 9 else 0, 0)
for event in event_list:
name = event[0]
sample_len = int(((event[1] / ticks_per_beat) * tempo / (10 ** 6)) * self.sample_rate)
sample_len -= int(((last_t / ticks_per_beat) * tempo / (10 ** 6)) * self.sample_rate)
last_t = event[1]
if sample_len > 0:
sample = fl.get_samples(sample_len).reshape(sample_len, 2)
ss = np.concatenate([ss, sample])
if name == "set_tempo":
tempo = event[2]
elif name == "patch_change":
c, p = event[2:4]
fl.program_select(c, sfid, 128 if c == 9 else 0, p)
elif name == "control_change":
c, cc, v = event[2:5]
fl.cc(c, cc, v)
elif name == "note_on" and event[3] > 0:
c, p, v = event[2:5]
fl.noteon(c, p, v)
elif name == "note_off" or (name == "note_on" and event[3] == 0):
c, p = event[2:4]
fl.noteoff(c, p)
self.release_fluidsynth(device)
if ss.shape[0] > 0:
max_val = np.abs(ss).max()
if max_val != 0:
ss = (ss / max_val) * np.iinfo(np.int16).max
ss = ss.astype(np.int16)
return ss
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