Spaces:
Running
Running
File size: 11,426 Bytes
0db4793 cdb1fca 97e80ab c68d210 97e80ab cdb1fca fec90c5 8979d67 1b639c6 c91ebe0 8979d67 1b639c6 8979d67 c91ebe0 8979d67 8e723a3 8979d67 8e723a3 8979d67 1b639c6 fec90c5 1b639c6 fec90c5 1b639c6 fec90c5 1b639c6 fec90c5 1b639c6 fec90c5 6435eef fec90c5 ff06030 fec90c5 1b639c6 fec90c5 1b639c6 ff06030 fec90c5 1b639c6 fec90c5 8979d67 cdb1fca 8979d67 cdb1fca fec90c5 cdb1fca fec90c5 cdb1fca fec90c5 cdb1fca fec90c5 cdb1fca fec90c5 8979d67 fec90c5 3ec16d6 94c87ef fec90c5 3ec16d6 94c87ef fe265e2 0db4793 fec90c5 3ec16d6 fec90c5 3ec16d6 fec90c5 3ec16d6 cdb1fca fec90c5 cdb1fca 9386e92 1b639c6 b8f21b1 da26062 1b639c6 b8f21b1 1b639c6 b8f21b1 1b639c6 9386e92 b8f21b1 9386e92 fec90c5 cdb1fca 9386e92 cdb1fca 9386e92 cdb1fca 9386e92 cdb1fca 3ec16d6 cdb1fca c68d210 4ce69a0 c68d210 cdb1fca 47bb3a8 cdb1fca 47bb3a8 cdb1fca 47bb3a8 cdb1fca 47bb3a8 cdb1fca 8979d67 cdb1fca c68d210 cdb1fca 8979d67 cdb1fca 8979d67 cdb1fca 8979d67 cdb1fca cf68a1c cdb1fca |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191 192 193 194 195 196 197 198 199 200 201 202 203 204 205 206 207 208 209 210 211 212 213 214 215 216 217 218 219 220 221 222 223 224 225 226 227 228 229 230 231 232 233 234 235 236 237 238 239 240 241 242 243 244 245 246 247 248 249 250 251 252 253 254 255 256 257 258 259 260 261 262 263 264 265 266 267 268 269 270 271 272 273 274 275 276 277 278 279 280 281 282 283 284 285 286 287 288 289 290 291 292 293 294 295 296 297 298 299 300 301 302 303 304 305 306 307 308 309 310 311 312 313 314 315 316 317 318 319 320 321 322 323 324 325 326 327 328 329 330 331 332 333 334 335 336 337 338 339 340 |
# https://huggingface.co/spaces/asigalov61/Harmonic-Melody-MIDI-Mixer
import os.path
import time as reqtime
import datetime
from pytz import timezone
from itertools import groupby
import copy
import gradio as gr
import random
from midi_to_colab_audio import midi_to_colab_audio
import TMIDIX
import matplotlib.pyplot as plt
in_space = os.getenv("SYSTEM") == "spaces"
# =================================================================================================
def pitches_counts(melody_score):
pitches = [p[4] for p in melody_score]
pcounts = []
count = 0
pp = -1
for p in pitches:
if p == pp:
count += 1
pcounts.append(count)
else:
count = 0
pcounts.append(count)
pp = p
return pcounts
# =================================================================================================
def find_similar_song(songs, src_melody):
src_pcount = pitches_counts(src_melody)
ratios = []
for s in songs:
patch = s[1]
trg_melody = [e for e in s[3] if e[6] == patch]
trg_pcount = pitches_counts(trg_melody)
pcount = 0
for i, c in enumerate(src_pcount):
if c == trg_pcount[i]:
pcount += 1
ratios.append(pcount / len(src_pcount))
max_ratio = max(ratios)
print(max_ratio)
print(ratios.count(1.0))
return songs[ratios.index(max_ratio)]
# =================================================================================================
def mix_chord(chord, tones_chord, mel_patch, mel_pitch, next_note_dtime):
cho = []
for k, g in groupby(sorted(chord, key=lambda x: x[6]), lambda x: x[6]):
if k != 128:
if k == mel_patch:
cg = list(g)
c = copy.deepcopy(cg[0])
c[4] = mel_pitch
c[5] = 105 + (mel_pitch % 12)
cho.append(c)
else:
cg = list(g)
tclen = len(tones_chord)
tchord = tones_chord
if len(cg) > tclen:
tchord = tones_chord + [random.choice(tones_chord) for _ in range(len(cg)-tclen)]
for i, cc in enumerate(cg):
c = copy.deepcopy(cc)
if cc[2] > next_note_dtime:
cc[2] == next_note_dtime
c[4] = ((c[4] // 12) * 12) + tchord[i]
c[5] += c[4] % 12
cho.append(c)
else:
cho.extend(list(g))
return cho
# =================================================================================================
def MixMelody(input_midi, input_find_best_match):
print('=' * 70)
print('Req start time: {:%Y-%m-%d %H:%M:%S}'.format(datetime.datetime.now(PDT)))
start_time = reqtime.time()
print('=' * 70)
fn = os.path.basename(input_midi.name)
fn1 = fn.split('.')[0]
print('-' * 70)
print('Input file name:', fn)
print('Find best matches', input_find_best_match)
print('-' * 70)
#===============================================================================
raw_score = TMIDIX.midi2single_track_ms_score(input_midi.name)
#===============================================================================
# Enhanced score notes
raw_escore = TMIDIX.advanced_score_processor(raw_score, return_enhanced_score_notes=True)[0]
if len(raw_escore) > 0:
#===============================================================================
# Augmented enhanced score notes
src_escore = TMIDIX.recalculate_score_timings(TMIDIX.augment_enhanced_score_notes([e for e in raw_escore if e[6] < 80]))
src_cscore = TMIDIX.chordify_score([1000, src_escore])
src_melody = [c[0] for c in src_cscore][:256]
src_melody_pitches = [p[4] for p in src_melody]
src_harm_tones_chords = TMIDIX.harmonize_enhanced_melody_score_notes(src_melody)
#===============================================================================
matched_songs = [a for a in all_songs if a[2] == max(32, len(src_melody))]
random.shuffle(matched_songs)
if input_find_best_match:
new_song = find_similar_song(matched_songs, src_melody)
else:
new_song = random.choice(matched_songs)
print('Selected Monster Mono Melodies MIDI:', new_song[0])
print('Selected melody instrument:', TMIDIX.Number2patch[new_song[1]], '(', new_song[1], ')')
print('Melody notes count:', new_song[2])
print('Matched melodies pool count', len(matched_songs))
MIDI_Summary = 'Selected Monster Mono Melodies MIDI: ' + str(new_song[0]) + '\n'
MIDI_Summary += 'Selected melody instrument: ' + str(TMIDIX.Number2patch[new_song[1]]) + ' (' + str(new_song[1]) + ')' + '\n'
MIDI_Summary += 'Melody notes count: ' + str(new_song[2]) + '\n'
MIDI_Summary += 'Matched melodies pool count: ' + str(len(matched_songs))
fn1 += '_' + str(new_song[0]) + '_' + str(TMIDIX.Number2patch[new_song[1]]) + '_' + str(new_song[1]) + '_' + str(new_song[2])
trg_patch = new_song[1]
trg_song = copy.deepcopy(new_song[3])
TMIDIX.adjust_score_velocities(trg_song, 95)
cscore = TMIDIX.chordify_score([1000, trg_song])
print('=' * 70)
print('Done loading source and target MIDIs...!')
print('=' * 70)
print('Mixing...')
mixed_song = []
midx = 0
for i, c in enumerate(cscore):
cho = copy.deepcopy(c)
patches = sorted(set([e[6] for e in c]))
if trg_patch in patches:
if midx < len(src_melody):
next_note_dtime = src_melody[midx+1][1] - src_melody[midx][1]
mixed_song.extend(mix_chord(c, src_harm_tones_chords[midx], trg_patch, src_melody_pitches[midx], next_note_dtime))
midx += 1
else:
if i < len(cscore)
next_note_dtime = cscore[i+1][0][1] - cscore[i][0][1]
mixed_song.extend(mix_chord(cho, src_harm_tones_chords[midx], trg_patch, src_melody_pitches[midx], next_note_dtime))
if midx == len(src_melody):
break
print('=' * 70)
print('Done!')
print('=' * 70)
#===============================================================================
print('Rendering results...')
print('=' * 70)
print('Sample INTs', mixed_song[:5])
print('=' * 70)
output_score, patches, overflow_patches = TMIDIX.patch_enhanced_score_notes(mixed_song)
detailed_stats = TMIDIX.Tegridy_ms_SONG_to_MIDI_Converter(output_score,
output_signature = 'Harmonic Melody MIDI Mixer',
output_file_name = fn1,
track_name='Project Los Angeles',
list_of_MIDI_patches=patches,
timings_multiplier=16
)
new_fn = fn1+'.mid'
audio = midi_to_colab_audio(new_fn,
soundfont_path=soundfont,
sample_rate=16000,
volume_scale=10,
output_for_gradio=True
)
print('Done!')
print('=' * 70)
#========================================================
output_midi_title = str(fn1)
output_midi_summary = str(MIDI_Summary)
output_midi = str(new_fn)
output_audio = (16000, audio)
for o in output_score:
o[1] *= 16
o[2] *= 16
output_plot = TMIDIX.plot_ms_SONG(output_score, plot_title=output_midi_title, return_plt=True)
print('Output MIDI file name:', output_midi)
print('Output MIDI title:', output_midi_title)
print('Output MIDI summary:', '')
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_title, output_midi_summary, output_midi, output_audio, output_plot
# =================================================================================================
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"
all_songs = TMIDIX.Tegridy_Any_Pickle_File_Reader('Monster_Mono_Melodies_MIDI_Dataset_65536_32_256')
print('=' * 70)
app = gr.Blocks()
with app:
gr.Markdown("<h1 style='text-align: center; margin-bottom: 1rem'>Harmonic Melody MIDI Mixer</h1>")
gr.Markdown("<h1 style='text-align: center; margin-bottom: 1rem'>Harmonize and mix any MIDI melody</h1>")
gr.Markdown(
"![Visitors](https://api.visitorbadge.io/api/visitors?path=asigalov61.Harmonic-Melody-MIDI-Mixer&style=flat)\n\n"
"This is a demo for TMIDIX Python module from tegridy-tools and Monster Mono Melodies MIDI Dataset\n\n"
"Check out [tegridy-tools](https://github.com/asigalov61/tegridy-tools) on GitHub!\n\n"
"Check out [Monster-MIDI-Dataset](https://github.com/asigalov61/Monster-MIDI-Dataset) on GitHub!\n\n"
)
gr.Markdown("## Upload your MIDI or select a sample example MIDI below")
input_midi = gr.File(label="Input MIDI", file_types=[".midi", ".mid", ".kar"])
input_find_best_match = gr.Checkbox(label="Find best match", value=True)
run_btn = gr.Button("mix melody", variant="primary")
gr.Markdown("## Output results")
output_midi_title = gr.Textbox(label="Output MIDI title")
output_midi_summary = gr.Textbox(label="Output MIDI summary")
output_audio = gr.Audio(label="Output MIDI audio", format="wav", elem_id="midi_audio")
output_plot = gr.Plot(label="Output MIDI score plot")
output_midi = gr.File(label="Output MIDI file", file_types=[".mid"])
run_event = run_btn.click(MixMelody, [input_midi, input_find_best_match],
[output_midi_title, output_midi_summary, output_midi, output_audio, output_plot])
gr.Examples(
[["Abracadabra-Sample-Melody.mid", True],
["Sparks-Fly-Sample-Melody.mid", True],
],
[input_midi, input_find_best_match],
[output_midi_title, output_midi_summary, output_midi, output_audio, output_plot],
MixMelody,
cache_examples=True,
)
app.queue().launch() |