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Update app.py
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app.py
CHANGED
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@@ -47,6 +47,7 @@ SOUDFONT_PATH = 'SGM-v2.01-YamahaGrand-Guit-Bass-v2.7.sf2'
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#==================================================================================
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print('Loading MIDI Loops Small Dataset...')
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midi_loops_dataset = TMIDIX.Tegridy_Any_Pickle_File_Reader('MIDI-Loops-Dataset-Small-CC-BY-NC-SA.pickle')
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@@ -68,6 +69,7 @@ def find_matches(src_array, trg_array):
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#==================================================================================
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def find_closest_tuple(tuples_list, src_tuple):
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def euclidean_distance(t1, t2):
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return sum((a - b) ** 2 for a, b in zip(t1, t2)) ** 0.5
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@@ -119,10 +121,6 @@ def Mix_Loops(input_midi,
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model_temperature
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):
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#===============================================================================
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#===============================================================================
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print('=' * 70)
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@@ -143,22 +141,199 @@ def Mix_Loops(input_midi,
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print('=' * 70)
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#==================================================================
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print('=' * 70)
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print('Generating...')
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-
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print('=' * 70)
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print('Done!')
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print('=' * 70)
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#===============================================================================
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print('Rendering results...')
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@@ -172,7 +347,7 @@ def Mix_Loops(input_midi,
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fn1 = "MIDI-Loops-Mixer-Composition"
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detailed_stats = TMIDIX.Tegridy_ms_SONG_to_MIDI_Converter(
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output_signature = 'MIDI Loops Mixer',
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output_file_name = fn1,
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track_name='Project Los Angeles',
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@@ -194,6 +369,7 @@ def Mix_Loops(input_midi,
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#========================================================
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output_midi = str(new_fn)
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output_audio = (16000, audio)
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@@ -204,6 +380,7 @@ def Mix_Loops(input_midi,
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)
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print('Output MIDI file name:', output_midi)
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print('=' * 70)
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#========================================================
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@@ -213,7 +390,7 @@ def Mix_Loops(input_midi,
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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_audio, output_plot, output_midi
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#==================================================================================
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@@ -256,18 +433,22 @@ with gr.Blocks() as demo:
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generate_btn = gr.Button("Generate", variant="primary")
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gr.Markdown("## Generation results")
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output_audio = gr.Audio(label="MIDI audio", format="wav", elem_id="midi_audio")
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output_plot = gr.Plot(label="MIDI score plot")
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output_midi = gr.File(label="MIDI file", file_types=[".mid"])
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generate_btn.click(Mix_Loops,
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[
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generation_type,
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melody_patch,
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model_temperature
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],
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[
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output_plot,
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output_midi
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]
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#==================================================================================
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print('Loading MIDI Loops Small Dataset...')
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print('-' * 70)
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midi_loops_dataset = TMIDIX.Tegridy_Any_Pickle_File_Reader('MIDI-Loops-Dataset-Small-CC-BY-NC-SA.pickle')
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#==================================================================================
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def find_closest_tuple(tuples_list, src_tuple):
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def euclidean_distance(t1, t2):
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return sum((a - b) ** 2 for a, b in zip(t1, t2)) ** 0.5
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model_temperature
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):
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#===============================================================================
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print('=' * 70)
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print('=' * 70)
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#===============================================================================
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chunk_len = 5
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chunk_chords_set = 13
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all_chords_chunks = []
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midi_loops = [l for l in midi_loops_dataset if len(set(l[1][0])) >= chunk_chords_set]
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for loop in tqdm.tqdm(midi_loops):
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fn = loop[0]
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chords = loop[1]
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score = loop[2]
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for c in chords:
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all_chords_chunks.append(c[:chunk_len])
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all_chords_chunks = np.array(all_chords_chunks)
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#==================================================================
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print('=' * 70)
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print('Generating...')
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max_num_loops = 4
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max_tries = 100
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loops_mult = 1
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song_loops_counter = 0
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stries = 0
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while song_loops_counter < max_num_loops:
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if stries % 25 == 0:
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print('Attempt', stries)
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stries += 1
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midxs = []
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sidxs = [-1]
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while not midxs:
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song_names = []
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song_chords = []
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song_scores = []
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song_idxs = []
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sidx = -1
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while sidx in sidxs:
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sidx = random.randint(0, len(midi_loops)-1)
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song_idxs.append(sidx)
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sidxs.append(sidx)
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song_names.append(midi_loops[sidx][0])
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song_chords.append(midi_loops[sidx][1][0][-chunk_len:]) #tv
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song_scores.append(midi_loops[sidx][2])
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song_midxs = [(song_idxs[-1]*loops_mult)+3]
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midxs = [song_midxs[-1]]
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midxs = find_matches(np.array(song_chords[-1]), all_chords_chunks)
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midxs = [midx for midx in midxs if midx != song_midxs[-1]]
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song_loops_counter = 1
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rtries = 0
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end = False
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while song_loops_counter < max_num_loops and not end:
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midxs = [song_midxs[-1]]
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midxs = []
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rmidxs = [-1]
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midxs = find_matches(np.array(song_chords[-1]), all_chords_chunks)
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midxs = [midx for midx in midxs if midx != song_midxs[-1]]
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if midxs:
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midx = find_best_midx(midxs, song_midxs[-1])
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else:
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midx = rmidxs[-1]
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if midx not in rmidxs and midx not in song_midxs:
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song_midxs.append(midx)
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sidx = int(midx // loops_mult)
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song_idxs.append(sidx)
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song = midi_loops[sidx]
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song_names.append(song[0])
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song_chords.append(song[1][0][-chunk_len:]) # tv
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song_scores.append(song[2])
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song_loops_counter += 1
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#print(song_loops_counter)
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else:
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if len(rmidxs) > 1 and rtries < max_tries:
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song_idxs.pop()
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song_midxs.pop()
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song_names.pop()
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song_chords.pop()
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song_scores.pop()
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#print('revert')
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song_loops_counter -= 1
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rtries += 1
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rmidxs.append(midx)
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else:
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#print('end')
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end = True
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break
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if end:
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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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#===============================================================================
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final_song = []
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last_max_dur = 0
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last_dtime = 0
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mode_dtime = 0
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mode_dur = 0
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for i, src_score in enumerate(song_scores):
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final_song.append(['text_event', 0, song_names[i]])
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score = copy.deepcopy(src_score)
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for j in range(2):
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if j == 1:
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if i > 0:
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last_chord = score[[e for e in range(len(score)) if score[e][0] > 0][-1]:]
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last_dtime = last_chord[0][0]
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last_max_dur = max([e[1] for e in last_chord])
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dtimes = [e[0] for e in score if e[0] != 0]
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durs = [e[1] for e in score]
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mode_dtime= statistics.mode(dtimes)
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mode_dur = statistics.mode(durs)
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score[0][0] = max(mode_dtime, mode_dur)
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rscore = list(reversed(score))
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ccount = 0
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for r in range(len(rscore)):
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if rscore[r][0] > 0:
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ccount += 1
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if ccount == chunk_len:
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break
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trimmed_score = score[:-(r+1)]
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extended_score = [['note'] + e for e in trimmed_score]
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final_song.extend(extended_score)
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else:
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if i > 0:
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last_chord = score[[e for e in range(len(score)) if score[e][0] > 0][-1]:]
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last_dtime = last_chord[0][0]
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last_max_dur = max([e[1] for e in last_chord])
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dtimes = [e[0] for e in score if e[0] != 0]
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durs = [e[1] for e in score]
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mode_dtime= statistics.mode(dtimes)
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mode_dur = statistics.mode(durs)
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score[0][0] = max(mode_dtime, mode_dur)
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extended_score = [['note'] + e for e in score]
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final_song.extend(extended_score)
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#===============================================================================
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print('Rendering results...')
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fn1 = "MIDI-Loops-Mixer-Composition"
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detailed_stats = TMIDIX.Tegridy_ms_SONG_to_MIDI_Converter(output_score,
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output_signature = 'MIDI Loops Mixer',
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output_file_name = fn1,
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track_name='Project Los Angeles',
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#========================================================
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output_midi_summary = ''
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output_midi = str(new_fn)
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output_audio = (16000, audio)
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)
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print('Output MIDI file name:', output_midi)
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print('Output MIDI summary:', output_midi_summary)
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print('=' * 70)
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#========================================================
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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_summary, output_audio, output_plot, output_midi
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#==================================================================================
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generate_btn = gr.Button("Generate", variant="primary")
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gr.Markdown("## Generation results")
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output_midi_summary = gr.Textbox(label="MIDI summary")
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output_audio = gr.Audio(label="MIDI audio", format="wav", elem_id="midi_audio")
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output_plot = gr.Plot(label="MIDI score plot")
|
| 440 |
output_midi = gr.File(label="MIDI file", file_types=[".mid"])
|
| 441 |
|
| 442 |
generate_btn.click(Mix_Loops,
|
| 443 |
+
[
|
| 444 |
+
input_midi,
|
| 445 |
generation_type,
|
| 446 |
melody_patch,
|
| 447 |
model_temperature
|
| 448 |
],
|
| 449 |
+
[
|
| 450 |
+
output_midi_summary,
|
| 451 |
+
output_audio,
|
| 452 |
output_plot,
|
| 453 |
output_midi
|
| 454 |
]
|