#============================================================================================
# https://huggingface.co/spaces/asigalov61/Advanced-MIDI-Loops-Mixer
#============================================================================================
print('=' * 70)
print('Advanced MIDI Loops Mixer Gradio App')
print('=' * 70)
print('Loading core Advanced MIDI Loops Mixer modules...')
import os
import copy
import time as reqtime
import datetime
from pytz import timezone
print('=' * 70)
print('Loading main Advanced MIDI Loops Mixer modules...')
from huggingface_hub import hf_hub_download
import TMIDIX
from midi_to_colab_audio import midi_to_colab_audio
import numpy as np
import random
import tqdm
print('=' * 70)
print('Loading aux Advanced MIDI Loops Mixer modules...')
import matplotlib.pyplot as plt
import gradio as gr
print('=' * 70)
print('Done!')
print('Enjoy! :)')
print('=' * 70)
#==================================================================================
SOUNDFONT_PATH = 'SGM-v2.01-YamahaGrand-Guit-Bass-v2.7.sf2'
#==================================================================================
print('=' * 70)
print('Loading data...')
print('=' * 70)
sequences_data = hf_hub_download(repo_id='asigalov61/Advanced-MIDI-Loops',
filename='Advanced_MIDI_Loops_Sequences_CC_BY_NC_SA.npy',
repo_type='dataset'
)
print('=' * 70)
labels_data = hf_hub_download(repo_id='asigalov61/Advanced-MIDI-Loops',
filename='Advanced_MIDI_Loops_Labels_CC_BY_NC_SA.pickle',
repo_type='dataset'
)
print('=' * 70)
sims_indexes_data = hf_hub_download(repo_id='asigalov61/Advanced-MIDI-Loops',
filename='Advanced_MIDI_Loops_Sims_Indexes_CC_BY_NC_SA.npy',
repo_type='dataset'
)
print('=' * 70)
print('Done!')
print('=' * 70)
#==================================================================================
print('=' * 70)
print('Loading Advanced MIDI Loops dataset...')
print('=' * 70)
print('Loading loops sequences...')
loops_sequences = np.load(sequences_data, mmap_mode="r")
print(loops_sequences.shape)
print('=' * 70)
print('Loading loops labels...')
loops_labels = TMIDIX.Tegridy_Any_Pickle_File_Reader(labels_data, verbose=False)
print('=' * 70)
print('Loading loops sims indexes...')
loops_sims_indexes = np.load(sims_indexes_data)
print('=' * 70)
print('Done!')
print('=' * 70)
print('Loaded', len(loops_sequences), 'loops')
print('=' * 70)
#==================================================================================
def tokens_to_score(tokens, abs_time):
song_f = []
time = abs_time
dur = 1
vel = 90
pitch = 60
channel = 0
patch = 0
patches = [-1] * 16
channels = [0] * 16
channels[9] = 1
for ss in tokens:
if 0 <= ss < 256:
time += ss * 16
if 256 <= ss < 16768:
patch = (ss-256) // 128
if patch < 128:
if patch not in patches:
if 0 in channels:
cha = channels.index(0)
channels[cha] = 1
else:
cha = 15
patches[cha] = patch
channel = patches.index(patch)
else:
channel = patches.index(patch)
if patch == 128:
channel = 9
pitch = (ss-256) % 128
if 16768 <= ss < 18816:
dur = ((ss-16768) // 8) * 16
vel = (((ss-16768) % 8)+1) * 15
song_f.append(['note', time, dur, channel, pitch, vel, patch])
return song_f, time
#==================================================================================
def Mix_MIDI_Loops(num_loops_to_mix,
use_one_loop,
model_temperature,
model_sampling_top_k
):
#===============================================================================
print('=' * 70)
print('Req start time: {:%Y-%m-%d %H:%M:%S}'.format(datetime.datetime.now(PDT)))
start_time = reqtime.time()
print('=' * 70)
print('=' * 70)
print('Requested settings:')
print('=' * 70)
print('Num loops to mix:', num_loops_to_mix)
print('Use one loop:', use_one_loop)
print('Model temperature:', model_temperature)
print('Model top k:', model_sampling_top_k)
print('=' * 70)
#==================================================================
print('Generating...')
song = []
song_indexes = []
song_titles = []
song_parts = []
while len(song) <= 512:
lidx = random.randint(0, len(loops_data)-1)
song = loops_data[lidx][1]
song_indexes.append(lidx)
song_titles.append(loops_data[lidx][0])
song_parts.append(loops_data[lidx][1])
for i in tqdm.tqdm(range(num_loops_to_mix-1)):
left_chunk = [1] + loops_data[lidx][1][2:]
if use_one_loop:
right_chunk = [1] + loops_data[lidx][1][2:]
else:
right_chunk = []
ridx = [-1]
rlen = -1
while ridx and rlen <= 512:
rlen = len(loops_data[ridx[0]][1])
ridx = [l for l in loops_data[lidx][2] if l not in song_indexes]
if ridx:
ridx = ridx[0]
right_chunk = [1] + loops_data[ridx][1][2:]
lidx = ridx
song_titles.append(loops_data[lidx][0])
song_indexes.append(lidx)
else:
break
seq = [18815] + left_chunk[-512:] + [18816] + right_chunk[:512] + [18817] + left_chunk[-64:]
x = torch.LongTensor(seq).cuda()
y_val = []
rcount = 0
while y_val != right_chunk[:64]:
with ctx:
out = model.generate(x,
576,
temperature=model_temperature,
filter_logits_fn=top_k,
filter_kwargs={'k': model_sampling_top_k},
eos_token=18818,
return_prime=False,
verbose=False)
y = out.tolist()
y_val = y[-64:]
if y_val != right_chunk[:64]:
rcount += 1
print('Regenerating attempt #', rcount)
if rcount == 3:
break
song = song + y[:-64] + right_chunk
song_parts.append(y[:-64])
song_parts.append(right_chunk)
#==================================================================
print('=' * 70)
print('Done!')
print('=' * 70)
#===============================================================================
print('Rendering results...')
used_loops_titles = 'Composition used ' + str(len(song_titles)) + ' loops from the following titles:\n\n'
for i, t in enumerate(song_titles):
used_loops_titles += 'Loop #' + str(i+1) + ': ' + str(t) + '\n'
#===============================================================================
print('=' * 70)
print('Sample INTs', song[:15])
print('=' * 70)
output_score = []
abs_time = 1000
for i, part in enumerate(song_parts):
if i == 0:
part = part[1:]
if not use_one_loop:
part_idx = song_indexes[i // 2]
else:
part_idx = song_indexes[0]
if i % 2 == 0:
if not use_one_loop:
part_title = song_titles[i // 2]
else:
part_title = song_titles[0]
output_score.append(['text_event', abs_time + (part[0] * 16), 'Loop #' + str((i // 2)+1) + ' / IDX #' + str(part_idx) + ' / ' + part_title])
else:
tidx = [i for i in range(20) if part[i] < 256][0]
output_score.append(['text_event', abs_time + (part[tidx] * 16), 'AI-generated bridge'])
score, abs_time= tokens_to_score(part, abs_time)
output_score.extend(score)
#===============================================================================
patched_score, patches, overflow_patches = TMIDIX.patch_enhanced_score_notes(output_score)
fn1 = "Advanced-MIDI-Loops-Mixer-Composition"
detailed_stats = TMIDIX.Tegridy_ms_SONG_to_MIDI_Converter(patched_score,
output_signature = 'Advanced MIDI Loops Mixer',
output_file_name = fn1,
track_name='Project Los Angeles',
list_of_MIDI_patches=patches
)
#===============================================================================
new_fn = fn1+'.mid'
#===============================================================================
audio = midi_to_colab_audio(new_fn,
soundfont_path=SOUDFONT_PATH,
sample_rate=16000,
volume_scale=10,
output_for_gradio=True
)
#===============================================================================
print('Done!')
print('=' * 70)
#========================================================
output_midi = str(new_fn)
output_audio = (16000, audio)
output_plot = TMIDIX.plot_ms_SONG(patched_score,
plot_title=output_midi,
return_plt=True
)
#===============================================================================
print(used_loops_titles)
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 used_loops_titles, output_audio, output_plot, output_midi
#==================================================================================
PDT = timezone('US/Pacific')
print('=' * 70)
print('App start time: {:%Y-%m-%d %H:%M:%S}'.format(datetime.datetime.now(PDT)))
print('=' * 70)
#==================================================================================
with gr.Blocks() as demo:
#==================================================================================
gr.Markdown("Advanced MIDI Loops Mixer
")
gr.Markdown("Seamless and fast MIDI loops mixing based on similarity
")
gr.HTML("""
for faster execution and endless generation!
""")
#==================================================================================
gr.Markdown("## Generation options")
num_loops_to_mix = gr.Slider(2, 10, value=5, step=1, label="Number of loops to mix")
use_one_loop = gr.Checkbox(value=False, label="Use only one randomly selected loop")
model_temperature = gr.Slider(0.1, 1, value=1.0, step=0.01, label="Model temperature")
model_sampling_top_k = gr.Slider(1, 100, value=5, step=1, label="Model sampling top k value")
generate_btn = gr.Button("Mix Loops", variant="primary")
gr.Markdown("## Generation results")
used_loops_titles = gr.Textbox(label="MIDI loops titles")
output_audio = gr.Audio(label="MIDI audio", format="wav", elem_id="midi_audio")
output_plot = gr.Plot(label="MIDI score plot")
output_midi = gr.File(label="MIDI file", file_types=[".mid"])
generate_btn.click(Mix_MIDI_Loops,
[num_loops_to_mix,
use_one_loop,
model_temperature,
model_sampling_top_k
],
[used_loops_titles,
output_audio,
output_plot,
output_midi
]
)
#==================================================================================
demo.launch()
#==================================================================================