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 enter_desired_song_title != '' and enter_desired_artist != '': search_string = enter_desired_song_title + ' --- ' + enter_desired_artist else: search_string = enter_desired_song_title + enter_desired_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 ]) patches = [0 if x==-1 else x for x in patches] detailed_stats = TMIDIX.Tegridy_ms_SONG_to_MIDI_Converter(song_f, output_signature = 'Giant Music Transformer', output_file_name = '/content/Giant-Music-Transformer-Music-Composition_'+str(i), track_name='Project Los Angeles', list_of_MIDI_patches=patches ) 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 mid_seq 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([mid_seq_ticks, mid_seq])) audio = synthesis(MIDI.score2opus([mid_seq_ticks, mid_seq]), 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("

MIDI Search

") gr.Markdown("

Upload any MIDI file to find its closest match

") 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") artist = gr.Textbox() title = gr.Textbox() 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 = input_midi.upload(match_midi, [input_midi, maximum_match_ratio], [output_midi_seq, output_midi, output_audio, output_plot]) app.queue(1).launch(server_port=opt.port, share=opt.share, inbrowser=True)