import random import PIL import numpy as np class MIDITokenizer: def __init__(self): self.vocab_size = 0 def allocate_ids(size): ids = [self.vocab_size + i for i in range(size)] self.vocab_size += size return ids self.pad_id = allocate_ids(1)[0] self.bos_id = allocate_ids(1)[0] self.eos_id = allocate_ids(1)[0] self.events = { "note": ["time1", "time2", "track", "duration", "channel", "pitch", "velocity"], "patch_change": ["time1", "time2", "track", "channel", "patch"], "control_change": ["time1", "time2", "track", "channel", "controller", "value"], "set_tempo": ["time1", "time2", "track", "bpm"], } self.event_parameters = { "time1": 128, "time2": 16, "duration": 2048, "track": 128, "channel": 16, "pitch": 128, "velocity": 128, "patch": 128, "controller": 128, "value": 128, "bpm": 256 } self.event_ids = {e: allocate_ids(1)[0] for e in self.events.keys()} self.id_events = {i: e for e, i in self.event_ids.items()} self.parameter_ids = {p: allocate_ids(s) for p, s in self.event_parameters.items()} self.max_token_seq = max([len(ps) for ps in self.events.values()]) + 1 def tempo2bpm(self, tempo): tempo = tempo / 10 ** 6 # us to s bpm = 60 / tempo return bpm def bpm2tempo(self, bpm): if bpm == 0: bpm = 1 tempo = int((60 / bpm) * 10 ** 6) return tempo def tokenize(self, midi_score, add_bos_eos=True, cc_eps=4, tempo_eps=4): ticks_per_beat = midi_score[0] event_list = {} for track_idx, track in enumerate(midi_score[1:129]): last_notes = {} patch_dict = {} control_dict = {} last_tempo = 0 for event in track: if event[0] not in self.events: continue t = round(16 * event[1] / ticks_per_beat) # quantization new_event = [event[0], t // 16, t % 16, track_idx] + event[2:] if event[0] == "note": new_event[4] = max(1, round(16 * new_event[4] / ticks_per_beat)) elif event[0] == "set_tempo": if new_event[4] == 0: # invalid tempo continue bpm = int(self.tempo2bpm(new_event[4])) new_event[4] = min(bpm, 255) if event[0] == "note": key = tuple(new_event[:4] + new_event[5:-1]) else: key = tuple(new_event[:-1]) if event[0] == "patch_change": c, p = event[2:] last_p = patch_dict.setdefault(c, None) if last_p == p: continue patch_dict[c] = p elif event[0] == "control_change": c, cc, v = event[2:] last_v = control_dict.setdefault((c, cc), 0) if abs(last_v - v) < cc_eps: continue control_dict[(c, cc)] = v elif event[0] == "set_tempo": tempo = new_event[-1] if abs(last_tempo - tempo) < tempo_eps: continue last_tempo = tempo if event[0] == "note": # to eliminate note overlap due to quantization cp = tuple(new_event[5:7]) if cp in last_notes: last_note_key, last_note = last_notes[cp] last_t = last_note[1] * 16 + last_note[2] last_note[4] = max(0, min(last_note[4], t - last_t)) if last_note[4] == 0: event_list.pop(last_note_key) last_notes[cp] = (key, new_event) event_list[key] = new_event event_list = list(event_list.values()) event_list = sorted(event_list, key=lambda e: e[1:4]) midi_seq = [] setup_events = {} notes_in_setup = False for i, event in enumerate(event_list): # optimise setup new_event = [*event] if event[0] != "note": new_event[1] = 0 new_event[2] = 0 has_next = False has_pre = False if i < len(event_list) - 1: next_event = event_list[i + 1] has_next = event[1] + event[2] == next_event[1] + next_event[2] if notes_in_setup and i > 0: pre_event = event_list[i - 1] has_pre = event[1] + event[2] == pre_event[1] + pre_event[2] if (event[0] == "note" and not has_next) or (notes_in_setup and not has_pre) : event_list = sorted(setup_events.values(), key=lambda e: 1 if e[0] == "note" else 0) + event_list[i:] break else: if event[0] == "note": notes_in_setup = True key = tuple(event[3:-1]) setup_events[key] = new_event last_t1 = 0 for event in event_list: cur_t1 = event[1] event[1] = event[1] - last_t1 tokens = self.event2tokens(event) if not tokens: continue midi_seq.append(tokens) last_t1 = cur_t1 if add_bos_eos: bos = [self.bos_id] + [self.pad_id] * (self.max_token_seq - 1) eos = [self.eos_id] + [self.pad_id] * (self.max_token_seq - 1) midi_seq = [bos] + midi_seq + [eos] return midi_seq def event2tokens(self, event): name = event[0] params = event[1:] if not all([0 <= params[i] < self.event_parameters[p] for i, p in enumerate(self.events[name])]): return [] tokens = [self.event_ids[name]] + [self.parameter_ids[p][params[i]] for i, p in enumerate(self.events[name])] tokens += [self.pad_id] * (self.max_token_seq - len(tokens)) return tokens def tokens2event(self, tokens): if tokens[0] in self.id_events: name = self.id_events[tokens[0]] if len(tokens) <= len(self.events[name]): return [] params = tokens[1:] params = [params[i] - self.parameter_ids[p][0] for i, p in enumerate(self.events[name])] if not all([0 <= params[i] < self.event_parameters[p] for i, p in enumerate(self.events[name])]): return [] event = [name] + params return event return [] def detokenize(self, midi_seq): ticks_per_beat = 480 tracks_dict = {} t1 = 0 for tokens in midi_seq: if tokens[0] in self.id_events: event = self.tokens2event(tokens) if not event: continue name = event[0] if name == "set_tempo": event[4] = self.bpm2tempo(event[4]) if event[0] == "note": event[4] = int(event[4] * ticks_per_beat / 16) t1 += event[1] t = t1 * 16 + event[2] t = int(t * ticks_per_beat / 16) track_idx = event[3] if track_idx not in tracks_dict: tracks_dict[track_idx] = [] tracks_dict[track_idx].append([event[0], t] + event[4:]) tracks = list(tracks_dict.values()) for i in range(len(tracks)): # to eliminate note overlap track = tracks[i] track = sorted(track, key=lambda e: e[1]) last_note_t = {} zero_len_notes = [] for e in reversed(track): if e[0] == "note": t, d, c, p = e[1:5] key = (c, p) if key in last_note_t: d = min(d, max(last_note_t[key] - t, 0)) last_note_t[key] = t e[2] = d if d == 0: zero_len_notes.append(e) for e in zero_len_notes: track.remove(e) tracks[i] = track return [ticks_per_beat, *tracks] def midi2img(self, midi_score): ticks_per_beat = midi_score[0] notes = [] max_time = 1 track_num = len(midi_score[1:]) for track_idx, track in enumerate(midi_score[1:]): for event in track: t = round(16 * event[1] / ticks_per_beat) if event[0] == "note": d = max(1, round(16 * event[2] / ticks_per_beat)) c, p = event[3:5] max_time = max(max_time, t + d + 1) notes.append((track_idx, c, p, t, d)) img = np.zeros((128, max_time, 3), dtype=np.uint8) colors = {(i, j): np.random.randint(50, 256, 3) for i in range(track_num) for j in range(16)} for note in notes: tr, c, p, t, d = note img[p, t: t + d] = colors[(tr, c)] img = PIL.Image.fromarray(np.flip(img, 0)) return img def augment(self, midi_seq, max_pitch_shift=4, max_vel_shift=10, max_cc_val_shift=10, max_bpm_shift=10, max_track_shift=0, max_channel_shift=16): pitch_shift = random.randint(-max_pitch_shift, max_pitch_shift) vel_shift = random.randint(-max_vel_shift, max_vel_shift) cc_val_shift = random.randint(-max_cc_val_shift, max_cc_val_shift) bpm_shift = random.randint(-max_bpm_shift, max_bpm_shift) track_shift = random.randint(0, max_track_shift) channel_shift = random.randint(0, max_channel_shift) midi_seq_new = [] for tokens in midi_seq: tokens_new = [*tokens] if tokens[0] in self.id_events: name = self.id_events[tokens[0]] for i, pn in enumerate(self.events[name]): if pn == "track": tr = tokens[1 + i] - self.parameter_ids[pn][0] tr += track_shift tr = tr % self.event_parameters[pn] tokens_new[1 + i] = self.parameter_ids[pn][tr] elif pn == "channel": c = tokens[1 + i] - self.parameter_ids[pn][0] c0 = c c += channel_shift c = c % self.event_parameters[pn] if c0 == 9: c = 9 elif c == 9: c = (9 + channel_shift) % self.event_parameters[pn] tokens_new[1 + i] = self.parameter_ids[pn][c] if name == "note": c = tokens[5] - self.parameter_ids["channel"][0] p = tokens[6] - self.parameter_ids["pitch"][0] v = tokens[7] - self.parameter_ids["velocity"][0] if c != 9: # no shift for drums p += pitch_shift if not 0 <= p < 128: return midi_seq v += vel_shift v = max(1, min(127, v)) tokens_new[6] = self.parameter_ids["pitch"][p] tokens_new[7] = self.parameter_ids["velocity"][v] elif name == "control_change": cc = tokens[5] - self.parameter_ids["controller"][0] val = tokens[6] - self.parameter_ids["value"][0] if cc in [1, 2, 7, 11]: val += cc_val_shift val = max(1, min(127, val)) tokens_new[6] = self.parameter_ids["value"][val] elif name == "set_tempo": bpm = tokens[4] - self.parameter_ids["bpm"][0] bpm += bpm_shift bpm = max(1, min(255, bpm)) tokens_new[4] = self.parameter_ids["bpm"][bpm] midi_seq_new.append(tokens_new) return midi_seq_new def check_quality(self, midi_seq, alignment_min=0.4, tonality_min=0.8, piano_max=0.7, notes_bandwidth_min=3, notes_density_max=30, notes_density_min=2.5, total_notes_max=10000, total_notes_min=500, note_window_size=16): total_notes = 0 channels = [] time_hist = [0] * 16 note_windows = {} notes_sametime = [] notes_density_list = [] tonality_list = [] notes_bandwidth_list = [] instruments = {} piano_channels = [] undef_instrument = False abs_t1 = 0 last_t = 0 for tsi, tokens in enumerate(midi_seq): event = self.tokens2event(tokens) if not event: continue t1, t2, tr = event[1:4] abs_t1 += t1 t = abs_t1 * 16 + t2 c = None if event[0] == "note": d, c, p, v = event[4:] total_notes += 1 time_hist[t2] += 1 if c != 9: # ignore drum channel if c not in instruments: undef_instrument = True note_windows.setdefault(abs_t1 // note_window_size, []).append(p) if last_t != t: notes_sametime = [(et, p_) for et, p_ in notes_sametime if et > last_t] notes_sametime_p = [p_ for _, p_ in notes_sametime] if len(notes_sametime) > 0: notes_bandwidth_list.append(max(notes_sametime_p) - min(notes_sametime_p)) notes_sametime.append((t + d - 1, p)) elif event[0] == "patch_change": c, p = event[4:] instruments[c] = p if p == 0 and c not in piano_channels: piano_channels.append(c) if c is not None and c not in channels: channels.append(c) last_t = t reasons = [] if total_notes < total_notes_min: reasons.append("total_min") if total_notes > total_notes_max: reasons.append("total_max") if undef_instrument: reasons.append("undef_instr") if len(note_windows) == 0 and total_notes > 0: reasons.append("drum_only") if reasons: return False, reasons time_hist = sorted(time_hist, reverse=True) alignment = sum(time_hist[:2]) / total_notes for notes in note_windows.values(): key_hist = [0] * 12 for p in notes: key_hist[p % 12] += 1 key_hist = sorted(key_hist, reverse=True) tonality_list.append(sum(key_hist[:7]) / len(notes)) notes_density_list.append(len(notes) / note_window_size) tonality_list = sorted(tonality_list) tonality = sum(tonality_list)/len(tonality_list) notes_bandwidth = sum(notes_bandwidth_list)/len(notes_bandwidth_list) if notes_bandwidth_list else 0 notes_density = max(notes_density_list) if notes_density_list else 0 piano_ratio = len(piano_channels) / len(channels) if len(channels) <=3: # ignore piano threshold if it is a piano solo midi piano_max = 1 if alignment < alignment_min: # check weather the notes align to the bars (because some midi files are recorded) reasons.append("alignment") if tonality < tonality_min: # check whether the music is tonal reasons.append("tonality") if notes_bandwidth < notes_bandwidth_min: # check whether music is melodic line only reasons.append("bandwidth") if not notes_density_min < notes_density < notes_density_max: reasons.append("density") if piano_ratio > piano_max: # check whether most instruments is piano (because some midi files don't have instruments assigned correctly) reasons.append("piano") return not reasons, reasons