File size: 11,818 Bytes
0db4793
cdb1fca
 
 
 
 
 
97e80ab
 
c68d210
97e80ab
cdb1fca
 
 
 
 
 
 
 
 
 
 
 
fec90c5
8979d67
 
 
 
 
 
 
1b639c6
c91ebe0
8979d67
 
 
1b639c6
8979d67
c91ebe0
8979d67
 
 
 
 
8e723a3
8979d67
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
ebd096a
8979d67
8e723a3
8979d67
1b639c6
fec90c5
 
 
 
 
 
 
1b639c6
fec90c5
1b639c6
fec90c5
1b639c6
3ec538e
57ac22f
3ec538e
fec90c5
 
1b639c6
fec90c5
 
 
 
 
 
 
6435eef
 
fec90c5
ff06030
fec90c5
 
1b639c6
fec90c5
1b639c6
 
57ac22f
1b639c6
ff06030
fec90c5
1b639c6
fec90c5
 
 
 
 
 
 
 
 
8979d67
cdb1fca
 
 
 
 
 
 
 
 
 
 
8979d67
cdb1fca
 
 
 
 
 
 
 
fec90c5
cdb1fca
fec90c5
cdb1fca
 
 
 
fec90c5
cdb1fca
fec90c5
 
 
 
 
 
 
cdb1fca
 
 
fec90c5
 
8979d67
 
ebd096a
 
8979d67
ebd096a
8979d67
 
fec90c5
3ec16d6
ebd096a
3ec16d6
 
94c87ef
fec90c5
3ec16d6
88ee285
3ec16d6
94c87ef
fe265e2
0db4793
 
fec90c5
3ec16d6
fec90c5
3ec16d6
 
fec90c5
3ec16d6
cdb1fca
 
fec90c5
cdb1fca
9386e92
 
 
 
 
 
1b639c6
b8f21b1
 
 
 
da26062
1b639c6
19ff4f4
1b639c6
19ff4f4
 
 
1b639c6
b8f21b1
 
 
 
1b639c6
19ff4f4
1b639c6
19ff4f4
 
1b639c6
 
9386e92
b8f21b1
 
9386e92
 
 
 
fec90c5
cdb1fca
 
 
 
9386e92
cdb1fca
 
9386e92
cdb1fca
 
9386e92
cdb1fca
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
3ec16d6
cdb1fca
 
 
 
 
 
 
 
 
 
 
ebd096a
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
341
342
343
344
345
346
347
348
# 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)

  return songs[ratios.index(max_ratio)], 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])
          
        if cg[0][2] > next_note_dtime:
            c[2] = next_note_dtime
            
        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:
              c[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)

        max_match_ratio = -1

        if input_find_best_match:
            new_song, max_match_ratio = 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 match ratio:', max_match_ratio)
        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 match ratio: ' + str(max_match_ratio) + '\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)-1:
                    next_note_dtime = src_melody[midx+1][1] - src_melody[midx][1]
                else:
                    next_note_dtime = 255
                    
                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)-1:
                    next_note_dtime = cscore[i+1][0][1] - cscore[i][0][1]
                else:
                    next_note_dtime = 255
                
                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:', 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()