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import os.path |
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import time as reqtime |
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import datetime |
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from pytz import timezone |
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from itertools import groupby |
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import copy |
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import gradio as gr |
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import random |
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from midi_to_colab_audio import midi_to_colab_audio |
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import TMIDIX |
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import matplotlib.pyplot as plt |
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in_space = os.getenv("SYSTEM") == "spaces" |
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def pitches_counts(melody_score): |
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pitches = [p[4] for p in melody_score] |
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pcounts = [] |
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count = 0 |
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pp = -1 |
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for p in pitches: |
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if p == pp: |
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count += 1 |
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pcounts.append(count) |
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else: |
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count = 0 |
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pcounts.append(count) |
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pp = p |
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return pcounts |
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def find_similar_song(songs, src_melody): |
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src_pcount = pitches_counts(src_melody) |
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ratios = [] |
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for s in songs: |
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patch = s[1] |
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trg_melody = [e for e in s[3] if e[6] == patch] |
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trg_pcount = pitches_counts(trg_melody) |
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pcount = 0 |
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for i, c in enumerate(src_pcount): |
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if c == trg_pcount[i]: |
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pcount += 1 |
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ratios.append(pcount / len(src_pcount)) |
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max_ratio = max(ratios) |
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return songs[ratios.index(max_ratio)], max_ratio, ratios.count(max_ratio) |
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def mix_chord(chord, tones_chord, mel_patch, mel_pitch, next_note_dtime): |
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cho = [] |
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for k, g in groupby(sorted(chord, key=lambda x: x[6]), lambda x: x[6]): |
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if k != 128: |
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if k == mel_patch: |
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cg = list(g) |
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c = copy.deepcopy(cg[0]) |
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if cg[0][2] > next_note_dtime: |
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c[2] = next_note_dtime |
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c[4] = mel_pitch |
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c[5] = 105 + (mel_pitch % 12) |
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cho.append(c) |
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else: |
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cg = list(g) |
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tclen = len(tones_chord) |
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tchord = tones_chord |
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if len(cg) > tclen: |
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tchord = tones_chord + [random.choice(tones_chord) for _ in range(len(cg)-tclen)] |
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for i, cc in enumerate(cg): |
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c = copy.deepcopy(cc) |
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if cc[2] > next_note_dtime: |
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c[2] = next_note_dtime |
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c[4] = ((c[4] // 12) * 12) + tchord[i] |
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c[5] += c[4] % 12 |
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cho.append(c) |
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else: |
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cho.extend(list(g)) |
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return cho |
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def MixMelody(input_midi, input_find_best_match, input_adjust_melody_notes_durations, input_adjust_accompaniment_notes_durations): |
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print('=' * 70) |
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print('Req start time: {:%Y-%m-%d %H:%M:%S}'.format(datetime.datetime.now(PDT))) |
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start_time = reqtime.time() |
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print('=' * 70) |
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fn = os.path.basename(input_midi.name) |
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fn1 = fn.split('.')[0] |
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print('-' * 70) |
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print('Input file name:', fn) |
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print('Find best matches', input_find_best_match) |
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print('Adjust melody notes durations:', input_adjust_melody_notes_durations) |
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print('Adjust accompaniment notes durations:', input_adjust_accompaniment_notes_durations) |
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print('-' * 70) |
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raw_score = TMIDIX.midi2single_track_ms_score(input_midi.name) |
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raw_escore = TMIDIX.advanced_score_processor(raw_score, return_enhanced_score_notes=True)[0] |
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if len(raw_escore) > 0: |
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src_escore = TMIDIX.recalculate_score_timings(TMIDIX.augment_enhanced_score_notes([e for e in raw_escore if e[6] < 80])) |
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src_cscore = TMIDIX.chordify_score([1000, src_escore]) |
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src_melody = [c[0] for c in src_cscore][:256] |
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src_melody_pitches = [p[4] for p in src_melody] |
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src_harm_tones_chords = TMIDIX.harmonize_enhanced_melody_score_notes(src_melody) |
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matched_songs = [a for a in all_songs if a[2] == max(32, len(src_melody))] |
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random.shuffle(matched_songs) |
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max_match_ratio = -1 |
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max_match_ratios_count = len(matched_songs) |
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if input_find_best_match: |
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new_song, max_match_ratio, max_match_ratios_count = find_similar_song(matched_songs, src_melody) |
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else: |
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new_song = random.choice(matched_songs) |
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print('Selected Monster Mono Melodies MIDI:', new_song[0]) |
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print('Selected melody match ratio:', max_match_ratio) |
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print('Selected melody instrument:', TMIDIX.Number2patch[new_song[1]], '(', new_song[1], ')') |
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print('Melody notes count:', new_song[2]) |
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print('Matched melodies pool count', max_match_ratios_count) |
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MIDI_Summary = 'Selected Monster Mono Melodies MIDI: ' + str(new_song[0]) + '\n' |
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MIDI_Summary += 'Selected melody match ratio: ' + str(max_match_ratio) + '\n' |
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MIDI_Summary += 'Selected melody instrument: ' + str(TMIDIX.Number2patch[new_song[1]]) + ' (' + str(new_song[1]) + ')' + '\n' |
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MIDI_Summary += 'Melody notes count: ' + str(new_song[2]) + '\n' |
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MIDI_Summary += 'Matched melodies pool count: ' + str(max_match_ratios_count) |
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fn1 += '_' + str(new_song[0]) + '_' + str(TMIDIX.Number2patch[new_song[1]]) + '_' + str(new_song[1]) + '_' + str(new_song[2]) |
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trg_patch = new_song[1] |
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trg_song = copy.deepcopy(new_song[3]) |
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TMIDIX.adjust_score_velocities(trg_song, 95) |
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cscore = TMIDIX.chordify_score([1000, trg_song]) |
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print('=' * 70) |
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print('Done loading source and target MIDIs...!') |
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print('=' * 70) |
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print('Mixing...') |
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mixed_song = [] |
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midx = 0 |
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next_note_dtime = 255 |
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for i, c in enumerate(cscore): |
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cho = copy.deepcopy(c) |
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patches = sorted(set([e[6] for e in c])) |
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if trg_patch in patches: |
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if input_adjust_melody_notes_durations: |
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if midx < len(src_melody)-1: |
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next_note_dtime = src_melody[midx+1][1] - src_melody[midx][1] |
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else: |
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next_note_dtime = 255 |
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mixed_song.extend(mix_chord(c, src_harm_tones_chords[midx], trg_patch, src_melody_pitches[midx], next_note_dtime)) |
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midx += 1 |
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else: |
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if input_adjust_accompaniment_notes_durations: |
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if i < len(cscore)-1: |
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next_note_dtime = cscore[i+1][0][1] - cscore[i][0][1] |
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else: |
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next_note_dtime = 255 |
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mixed_song.extend(mix_chord(cho, src_harm_tones_chords[midx], trg_patch, src_melody_pitches[midx], next_note_dtime)) |
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if midx == len(src_melody): |
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break |
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print('=' * 70) |
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print('Done!') |
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print('=' * 70) |
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print('Rendering results...') |
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print('=' * 70) |
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print('Sample INTs', mixed_song[:5]) |
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print('=' * 70) |
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output_score, patches, overflow_patches = TMIDIX.patch_enhanced_score_notes(mixed_song) |
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detailed_stats = TMIDIX.Tegridy_ms_SONG_to_MIDI_Converter(output_score, |
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output_signature = 'Harmonic Melody MIDI Mixer', |
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output_file_name = fn1, |
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track_name='Project Los Angeles', |
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list_of_MIDI_patches=patches, |
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timings_multiplier=16 |
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) |
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new_fn = fn1+'.mid' |
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audio = midi_to_colab_audio(new_fn, |
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soundfont_path=soundfont, |
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sample_rate=16000, |
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volume_scale=10, |
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output_for_gradio=True |
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) |
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print('Done!') |
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print('=' * 70) |
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output_midi_title = str(fn1) |
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output_midi_summary = str(MIDI_Summary) |
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output_midi = str(new_fn) |
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output_audio = (16000, audio) |
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for o in output_score: |
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o[1] *= 16 |
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o[2] *= 16 |
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output_plot = TMIDIX.plot_ms_SONG(output_score, plot_title=output_midi_title, return_plt=True) |
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print('Output MIDI file name:', output_midi) |
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print('Output MIDI title:', output_midi_title) |
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print('Output MIDI summary:', MIDI_Summary) |
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print('=' * 70) |
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print('-' * 70) |
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print('Req end time: {:%Y-%m-%d %H:%M:%S}'.format(datetime.datetime.now(PDT))) |
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print('-' * 70) |
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print('Req execution time:', (reqtime.time() - start_time), 'sec') |
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return output_midi_title, output_midi_summary, output_midi, output_audio, output_plot |
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if __name__ == "__main__": |
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PDT = timezone('US/Pacific') |
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print('=' * 70) |
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print('App start time: {:%Y-%m-%d %H:%M:%S}'.format(datetime.datetime.now(PDT))) |
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print('=' * 70) |
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soundfont = "ProtoSquare_.sf2" |
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all_songs = TMIDIX.Tegridy_Any_Pickle_File_Reader('Monster_Mono_Melodies_MIDI_Dataset_65536_32_256') |
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print('=' * 70) |
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app = gr.Blocks() |
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with app: |
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gr.Markdown("<h1 style='text-align: center; margin-bottom: 1rem'>Harmonic Melody MIDI Mixer</h1>") |
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gr.Markdown("<h1 style='text-align: center; margin-bottom: 1rem'>Harmonize and mix any MIDI melody</h1>") |
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gr.Markdown( |
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"\n\n" |
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"This is a demo for TMIDIX Python module from tegridy-tools and Monster Mono Melodies MIDI Dataset\n\n" |
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"Check out [tegridy-tools](https://github.com/asigalov61/tegridy-tools) on GitHub!\n\n" |
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"Check out [Monster-MIDI-Dataset](https://github.com/asigalov61/Monster-MIDI-Dataset) on GitHub!\n\n" |
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) |
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gr.Markdown("## Upload your MIDI or select a sample example MIDI below") |
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input_midi = gr.File(label="Input MIDI", file_types=[".midi", ".mid", ".kar"]) |
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input_find_best_match = gr.Checkbox(label="Find best match", value=True) |
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input_adjust_melody_notes_durations = gr.Checkbox(label="Adjust melody notes durations", value=True) |
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input_adjust_accompaniment_notes_durations = gr.Checkbox(label="Adjust accompaniment notes durations", value=True) |
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run_btn = gr.Button("mix melody", variant="primary") |
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gr.Markdown("## Output results") |
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output_midi_title = gr.Textbox(label="Output MIDI title") |
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output_midi_summary = gr.Textbox(label="Output MIDI summary") |
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output_audio = gr.Audio(label="Output MIDI audio", format="wav", elem_id="midi_audio") |
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output_plot = gr.Plot(label="Output MIDI score plot") |
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output_midi = gr.File(label="Output MIDI file", file_types=[".mid"]) |
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run_event = run_btn.click(MixMelody, [input_midi, input_find_best_match, input_adjust_melody_notes_durations, input_adjust_accompaniment_notes_durations], |
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[output_midi_title, output_midi_summary, output_midi, output_audio, output_plot]) |
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gr.Examples( |
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[["Abracadabra-Sample-Melody.mid", True, True, True], |
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["Sparks-Fly-Sample-Melody.mid", True, True, True], |
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], |
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[input_midi, input_find_best_match, input_adjust_melody_notes_durations, input_adjust_accompaniment_notes_durations], |
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[output_midi_title, output_midi_summary, output_midi, output_audio, output_plot], |
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MixMelody, |
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cache_examples=True, |
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) |
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app.queue().launch() |
