# ================================================================================================= # https://huggingface.co/spaces/asigalov61/Chords-Progressions-Generator # ================================================================================================= import os import time as reqtime import datetime from pytz import timezone import gradio as gr import numpy as np import os import random from collections import Counter import math from tqdm import tqdm import TMIDIX # ================================================================================================= def Generate_Chords_Progression(minimum_song_length_in_chords_chunks, chords_chunks_memory_ratio, chord_time_step, merge_chords_notes, melody_MIDI_patch_number, chords_progression_MIDI_patch_number, base_MIDI_patch_number, add_drums, output_as_solo_piano ): print('=' * 70) print('Req start time: {:%Y-%m-%d %H:%M:%S}'.format(datetime.datetime.now(PDT))) start_time = reqtime.time() print('=' * 70) print('Requested settings:') print('-' * 70) print('Minimum song length in chords chunks:', minimum_song_length_in_chords_chunks) print('Chords chunks memory ratio:', chords_chunks_memory_ratio) print('Chord time step:', chord_time_step) print('Merge chords notes max time:', merge_chords_notes) print('Melody MIDI patch number:', melody_MIDI_patch_number) print('Chords progression MIDI patch number:', chords_progression_MIDI_patch_number) print('Base MIDI patch number:', base_MIDI_patch_number) print('Add drum track:', add_drums) print('Output as solo Piano:', output_as_solo_piano) print('-' * 70) #================================================================== print('=' * 70) print('Pitches Chords Progressions Generator') print('=' * 70) print('=' * 70) print('Chunk-by-chunk generation') print('=' * 70) print('Generating...') print('=' * 70) matching_long_chords_chunks = [] ridx = random.randint(0, len(all_long_chords_tokens_chunks)-1) matching_long_chords_chunks.append(ridx) max_song_len = 0 tries = 0 while len(matching_long_chords_chunks) < minimum_song_length_in_chords_chunks: matching_long_chords_chunks = [] ridx = random.randint(0, len(all_long_chords_tokens_chunks)-1) matching_long_chords_chunks.append(ridx) seen = [ridx] gseen = [ridx] for a in range(minimum_song_length_in_chords_chunks * 10): if not matching_long_chords_chunks: break if len(matching_long_chords_chunks) > minimum_song_length_in_chords_chunks: break schunk = all_long_chords_tokens_chunks[matching_long_chords_chunks[-1]] trg_long_chunk = np.array(schunk[-chunk_size:]) idxs = np.where((src_long_chunks == trg_long_chunk).all(axis=1))[0].tolist() if len(idxs) > 1: random.shuffle(idxs) eidxs = [i for i in idxs if i not in seen] if eidxs: eidx = eidxs[0] matching_long_chords_chunks.append(eidx) seen.append(eidx) gseen.append(eidx) if 0 < chords_chunks_memory_ratio < 1: seen = random.choices(gseen, k=math.ceil(len(gseen) * chords_chunks_memory_ratio)) elif chords_chunks_memory_ratio == 0: seen = [] else: gseen.pop() matching_long_chords_chunks.pop() else: gseen.pop() matching_long_chords_chunks.pop() if len(matching_long_chords_chunks) > max_song_len: print('Current song length:', len(matching_long_chords_chunks), 'chords chunks') print('=' * 70) final_song = matching_long_chords_chunks max_song_len = max(max_song_len, len(matching_long_chords_chunks)) tries += 1 if tries % 500 == 0: print('Number of passed tries:', tries) print('=' * 70) if len(matching_long_chords_chunks) > max_song_len: print('Current song length:', len(matching_long_chords_chunks), 'chords chunks') print('=' * 70) final_song = matching_long_chords_chunks f_song = [] for mat in final_song: f_song.extend(all_long_good_chords_chunks[mat][:-chunk_size]) f_song.extend(all_long_good_chords_chunks[mat][-chunk_size:]) print('Generated final song after', tries, 'tries with', len(final_song), 'chords chunks and', len(f_song), 'chords') print('=' * 70) print('Done!') print('=' * 70) #=============================================================================== print('Rendering results...') print('=' * 70) output_score = [] time = 0 patches = [0] * 16 patches[0] = chords_progression_MIDI_patch_number if base_MIDI_patch_number > -1: patches[2] = base_MIDI_patch_number if melody_MIDI_patch_number > -1: patches[3] = melody_MIDI_patch_number chords_labels = [] for i, s in enumerate(f_song): time += chord_time_step dur = chord_time_step chord_str = str(i+1) for t in sorted(set([t % 12 for t in s])): chord_str += '-' + str(t) chords_labels.append(['text_event', time, chord_str]) for p in s: output_score.append(['note', time, dur, 0, p, max(40, p), chords_progression_MIDI_patch_number]) if base_MIDI_patch_number > -1: output_score.append(['note', time, dur, 2, (s[-1] % 12)+24, 120-(s[-1] % 12), base_MIDI_patch_number]) if melody_MIDI_patch_number > -1: output_score = TMIDIX.add_melody_to_enhanced_score_notes(output_score, melody_patch=melody_MIDI_patch_number, melody_notes_max_duration=max(merge_chords_notes, chord_time_step) ) if merge_chords_notes > 0: escore_matrix = TMIDIX.escore_notes_to_escore_matrix(output_score) output_score = TMIDIX.escore_matrix_to_merged_escore_notes(escore_matrix, max_note_duration=merge_chords_notes) if add_drums and not output_as_solo_piano: output_score = TMIDIX.augment_enhanced_score_notes(output_score) output_score = TMIDIX.advanced_add_drums_to_escore_notes(output_score) for e in output_score: e[1] *= 16 e[2] *= 16 ctimes = sorted(set([e[1] for e in output_score if e[3] != 9])) for i, e in enumerate(chords_labels[:len(ctimes)]): e[1] = ctimes[i] if output_as_solo_piano: output_score = TMIDIX.solo_piano_escore_notes(output_score) midi_score = sorted(chords_labels + output_score, key=lambda x: x[1]) fn1 = "MuseCraft-Chords-Progression-Composition" detailed_stats = TMIDIX.Tegridy_ms_SONG_to_MIDI_Converter(midi_score, output_signature = 'MuseCraft Chords Progression', output_file_name = fn1, track_name='Project Los Angeles', list_of_MIDI_patches=patches ) new_fn = fn1+'.mid' #======================================================== output_midi = str(new_fn) print('Done!') print('=' * 70) #======================================================== print('-' * 70) print('Req end time: {:%Y-%m-%d %H:%M:%S}'.format(datetime.datetime.now(PDT))) print('-' * 70) print('Req execution time:', (reqtime.time() - start_time), 'sec') return output_midi # ================================================================================================= if __name__ == "__main__": PDT = timezone('US/Pacific') print('=' * 70) print('App start time: {:%Y-%m-%d %H:%M:%S}'.format(datetime.datetime.now(PDT))) print('=' * 70) #=============================================================================== soundfont = "SGM-v2.01-YamahaGrand-Guit-Bass-v2.7.sf2" print('Loading processed Pitches Chords Progressions dataset data...') print('=' * 70) long_tones_chords_dict, all_long_chords_tokens_chunks, all_long_good_chords_chunks = TMIDIX.Tegridy_Any_Pickle_File_Reader('processed_chords_progressions_chunks_data') print('=' * 70) print('Resulting chords dictionary size:', len(long_tones_chords_dict)) print('=' * 70) print('Loading chords chunks...') chunk_size = 6 src_long_chunks = np.array([a[:chunk_size] for a in all_long_chords_tokens_chunks]) print('Done!') print('=' * 70) print('Total chords chunks count:', len(all_long_good_chords_chunks)) print('=' * 70) #=============================================================================== app = gr.Blocks() with app: gr.Markdown("

Chords Progressions Generator

") gr.Markdown("

Generate unique chords progressions

") gr.HTML(""" Check out MuseCraft project on GitHub

Duplicate in Hugging Face

""") gr.Markdown("## Select generation options") minimum_song_length_in_chords_chunks = gr.Slider(4, 60, value=30, step=1, label="Minimum song length in chords chunks") chords_chunks_memory_ratio = gr.Slider(0, 1, value=1, step=0.1, label="Chords chunks memory ratio") chord_time_step = gr.Slider(100, 1000, value=250, step=50, label="Chord time step") merge_chords_notes = gr.Slider(0, 4000, value=2000, step=100, label="Merged chords notes max time") melody_MIDI_patch_number = gr.Slider(0, 127, value=40, step=1, label="Melody MIDI patch number") chords_progression_MIDI_patch_number = gr.Slider(0, 127, value=0, step=1, label="Chords progression MIDI patch number") base_MIDI_patch_number = gr.Slider(0, 127, value=35, step=1, label="Base MIDI patch number") add_drums = gr.Checkbox(value=True, label="Add drum track") output_as_solo_piano = gr.Checkbox(value=False, label="Output as solo Piano") run_btn = gr.Button("generate", variant="primary") gr.Markdown("## Generation results") output_midi = gr.File(label="Output MIDI file", file_types=[".mid"]) run_event = run_btn.click(Generate_Chords_Progression, [minimum_song_length_in_chords_chunks, chords_chunks_memory_ratio, chord_time_step, merge_chords_notes, melody_MIDI_patch_number, chords_progression_MIDI_patch_number, base_MIDI_patch_number, add_drums, output_as_solo_piano ], [output_midi] ) app.queue().launch()