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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 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("<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("\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) |