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import argparse
import glob
import os.path
import hashlib
import time
import datetime
from pytz import timezone
import gradio as gr
import pickle
import tqdm
import json
import TMIDIX
from midi_to_colab_audio import midi_to_colab_audio
import copy
from collections import Counter
import random
import statistics
import matplotlib.pyplot as plt
#==========================================================================================================
in_space = os.getenv("SYSTEM") == "spaces"
#==========================================================================================================
def render_midi(input_midi, render_options):
print('=' * 70)
print('Req start time: {:%Y-%m-%d %H:%M:%S}'.format(datetime.datetime.now(PDT)))
start_time = time.time()
print('=' * 70)
print('Loading MIDI...')
fn = os.path.basename(input_midi)
fn1 = fn.split('.')[0]
fdata = open(input_midi, 'rb').read()
input_midi_md5hash = hashlib.md5(fdata).hexdigest()
print('=' * 70)
print('Input MIDI file name:', fn)
print('Input MIDI md5 hash', input_midi_md5hash)
print('Render options:', render_options)
print('=' * 70)
print('Processing MIDI...Please wait...')
#=======================================================
# START PROCESSING
raw_score = TMIDIX.midi2single_track_ms_score(fdata, recalculate_channels=False)
escore = TMIDIX.advanced_score_processor(raw_score, return_score_analysis=False, return_enhanced_score_notes=True)[0]
first_note_index = raw_score[1].index(escore[0][:6])
for e in escore:
e[1] = int(e[1] / 16)
e[2] = int(e[2] / 16)
# Sorting by patch, pitch, then by start-time
escore.sort(key=lambda x: x[6])
escore.sort(key=lambda x: x[4], reverse=True)
escore.sort(key=lambda x: x[1])
cscore = TMIDIX.chordify_score([1000, escore])
meta_data = raw_score[1][:first_note_index] + [escore[0]] + [escore[-1]] + [raw_score[1][-1]]
print('Done!')
print('=' * 70)
print('Input MIDI metadata:', meta_data)
print('=' * 70)
new_fn = fn1+'.mid'
patches = [0] * 16
detailed_stats = TMIDIX.Tegridy_ms_SONG_to_MIDI_Converter(escore,
output_signature = 'Advanced MIDI Renderer',
output_file_name = new_fn,
track_name='Project Los Angeles',
list_of_MIDI_patches=patches
)
audio = midi_to_colab_audio(new_fn,
soundfont_path=soundfonts[0],
sample_rate=16000, # 44100
volume_scale=10,
output_for_gradio=True
)
print('Sample INTs', escore[:5])
print('=' * 70)
x = []
y = []
c = []
colors = ['red', 'yellow', 'green', 'cyan',
'blue', 'pink', 'orange', 'purple',
'gray', 'white', 'gold', 'silver',
'lightgreen', 'indigo', 'maroon', 'turquoise']
for s in escore:
x.append(s[1])
y.append(s[4])
c.append(colors[s[3]])
plt.close()
plt.figure(figsize=(14,5))
ax=plt.axes(title=title)
ax.set_facecolor('black')
plt.scatter(x,y, s=10, c=c)
plt.xlabel("Time in ms")
plt.ylabel("MIDI Pitch")
print('Req end time: {:%Y-%m-%d %H:%M:%S}'.format(datetime.datetime.now(PDT)))
print('-' * 70)
print('Req execution time:', (time.time() - start_time), 'sec')
yield AUX_DATA[search_match_index][0], AUX_DATA[search_match_index][1], AUX_DATA[search_match_index][2], AUX_DATA[search_match_index][3], fn+'.mid', (16000, audio), plt
#==========================================================================================================
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)
parser = argparse.ArgumentParser()
parser.add_argument("--share", action="store_true", default=False, help="share gradio app")
parser.add_argument("--port", type=int, default=7860, help="gradio server port")
opt = parser.parse_args()
soundfonts = ["SGM-v2.01-YamahaGrand-Guit-Bass-v2.7.sf2", "Nice-Strings-PlusOrchestra-v1.6.sf2", "KBH-Real-Choir-V2.5.sf2"]
app = gr.Blocks()
with app:
gr.Markdown("<h1 style='text-align: center; margin-bottom: 1rem'>Advanced MIDI Renderer</h1>")
gr.Markdown("<h1 style='text-align: center; margin-bottom: 1rem'>Transform and render any MIDI</h1>")
gr.Markdown("\n\n"
"Los Angeles MIDI Dataset Demo\n\n"
"Please see [Los Angeles MIDI Dataset](https://github.com/asigalov61/Los-Angeles-MIDI-Dataset) for more information and features\n\n"
"[Open In Colab]"
"(https://colab.research.google.com/github/asigalov61/Los-Angeles-MIDI-Dataset/blob/main/Los_Angeles_MIDI_Dataset_Search_and_Explore.ipynb)"
" for all features\n\n"
)
gr.Markdown("## Upload your MIDI")
input_midi = gr.File(label="Input MIDI", file_types=[".midi", ".mid", ".kar"], type="binary")
gr.Markdown("## Select desired render options")
render_as_is = gr.Checkbox(label="Render as-is")
extract_melody = gr.Checkbox(label="Extract melody")
transform = gr.Checkbox(label="Transform")
submit = gr.Button()
gr.Markdown("## Render results")
output_midi_md5 = gr.Textbox(label="Output MIDI md5 hash")
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_lyric = gr.Textbox(label="Output Karaoke MIDI lyric")
output_midi = gr.File(label="Output MIDI file", file_types=[".mid"])
render_options = [render_as_is, extract_melody, transform]
run_event = submit.click(render_midi, [input_midi, render_options],
[output_midi_md5, output_midi_title, output_midi_lyric, output_midi_summary, output_midi, output_audio, output_plot])
app.queue(1).launch(server_port=opt.port, share=opt.share, inbrowser=True) |