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import argparse
import glob
import os.path
import gradio as gr
import pickle
import tqdm
import json
import MIDI
from midi_synthesizer import synthesis
from fuzzywuzzy import process
import copy
from collections import Counter
import random
import statistics
import matplotlib.pyplot as plt
#==========================================================================================================
in_space = os.getenv("SYSTEM") == "spaces"
#==========================================================================================================
def find_midi(title, artist):
print('=' * 70)
print('Loading MIDI file...')
#==================================================
print('Searching titles...Please wait...')
random.shuffle(AUX_DATA)
titles_index = []
for A in AUX_DATA:
titles_index.append(A[0])
search_string = ''
if title != '' and artist != '':
search_string = title + ' --- ' + artist
else:
search_string = title + artist
search_match = process.extract(query=search_string, choices=titles_index, limit=1)
search_index = titles_index.index(search_match[0][0])
print('Done!')
print('=' * 70)
print('Selected title:', AUX_DATA[search_index][0])
print('=' * 70)
outy = AUX_DATA[search_index][1]
print('Sample INTs', outy[:12])
print('=' * 70)
if len(outy) != 0:
song = outy
song_f = []
time = 0
dur = 0
vel = 90
pitch = 0
channel = 0
patches = [-1] * 16
channels = [0] * 16
channels[9] = 1
for ss in song:
if 0 <= ss < 256:
time += ss * 16
if 256 <= ss < 2304:
dur = ((ss-256) // 8) * 16
vel = (((ss-256) % 8)+1) * 15
if 2304 <= ss < 18945:
patch = (ss-2304) // 129
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-2304) % 129
song_f.append(['note', time, dur, channel, pitch, vel, patch ])
x = []
y = []
c = []
colors = ['red', 'yellow', 'green', 'cyan',
'blue', 'pink', 'orange', 'purple',
'gray', 'white', 'gold', 'silver',
'lightgreen', 'indigo', 'maroon', 'turquoise']
for s in [m for m in song_f if m[0] == 'note']:
x.append(s[1])
y.append(s[4])
c.append(colors[s[3]])
plt.close()
plt.figure(figsize=(14,5))
ax=plt.axes(title='MIDI Match Plot')
ax.set_facecolor('black')
plt.scatter(x,y, c=c)
plt.xlabel("Time in MIDI ticks")
plt.ylabel("MIDI Pitch")
with open(f"MIDI-Match-Sample.mid", 'wb') as f:
f.write(MIDI.score2midi([1000, song_f]))
audio = synthesis(MIDI.score2opus([1000, song_f]), soundfont_path)
yield txt_mdata, "MIDI-Match-Sample.mid", (44100, audio), plt
#==========================================================================================================
if __name__ == "__main__":
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")
parser.add_argument("--max-gen", type=int, default=1024, help="max")
opt = parser.parse_args()
soundfont_path = "SGM-v2.01-YamahaGrand-Guit-Bass-v2.7.sf2"
meta_data_path = "Giant_Music_Transformer_Aux_Data.pickle"
print('Loading meta-data...')
with open(meta_data_path, 'rb') as f:
AUX_DATA = pickle.load(f)
print('Done!')
app = gr.Blocks()
with app:
gr.Markdown("<h1 style='text-align: center; margin-bottom: 1rem'>MIDI Search</h1>")
gr.Markdown("<h1 style='text-align: center; margin-bottom: 1rem'>Upload any MIDI file to find its closest match</h1>")
gr.Markdown("![Visitors](https://api.visitorbadge.io/api/visitors?path=asigalov61.MIDI-Match&style=flat)\n\n"
"Los Angeles MIDI Dataset Search and Explore 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 faster execution"
)
gr.Markdown("# Upload MIDI")
title = gr.Textbox()
artist = gr.Textbox()
submit = gr.Button()
gr.Markdown("# Match results")
output_audio = gr.Audio(label="Output MIDI match sample audio", format="mp3", elem_id="midi_audio")
output_plot = gr.Plot(label="Output MIDI match sample plot")
output_midi = gr.File(label="Output MIDI match sample MIDI", file_types=[".mid"])
output_midi_seq = gr.Textbox(label="Output MIDI match metadata")
run_event = submit.click(find_midi, [title, artist],
[output_midi_seq, output_midi, output_audio, output_plot])
app.queue(1).launch(server_port=opt.port, share=opt.share, inbrowser=True) |