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| import streamlit as st | |
| from PIL import Image, ImageDraw | |
| import numpy as np | |
| #@title Standard/Simple Continuation | |
| #@markdown Text-To-Music Settings | |
| #@markdown NOTE: You can enter any desired title or artist, or both | |
| enter_desired_song_title = "Family Guy" #@param {type:"string"} | |
| enter_desired_artist = "TV Themes" #@param {type:"string"} | |
| #@markdown Generation Settings | |
| number_of_tokens_to_generate = 426 #@param {type:"slider", min:30, max:2046, step:33} | |
| number_of_batches_to_generate = 4 #@param {type:"slider", min:1, max:16, step:1} | |
| temperature = 0.9 #@param {type:"slider", min:0.1, max:1, step:0.1} | |
| allow_model_to_stop_generation_if_needed = False #@param {type:"boolean"} | |
| print('=' * 70) | |
| print('Euterpe X TTM Model Generator') | |
| print('=' * 70) | |
| 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) | |
| if allow_model_to_stop_generation_if_needed: | |
| min_stop_token = 3343 | |
| else: | |
| min_stop_token = None | |
| # Velocities | |
| velocities_map = [80, 80, 70, 100, 90, 80, 100, 100, 100, 90, 110, 100] | |
| vel_map = AUX_DATA[search_index][1] | |
| for i in range(12): | |
| if vel_map[i] != 0: | |
| velocities_map[i] = vel_map[i] | |
| # Loading data... | |
| outy = AUX_DATA[search_index][2][3:] | |
| block_marker = sum([(y * 8) for y in outy if y < 256]) / 1000 | |
| inp = [outy] * number_of_batches_to_generate | |
| inp = torch.LongTensor(inp).cuda() | |
| out = model.module.generate(inp, | |
| number_of_tokens_to_generate, | |
| temperature=temperature, | |
| return_prime=True, | |
| eos_token=min_stop_token, | |
| verbose=True) | |
| out0 = out.tolist() | |
| print('=' * 70) | |
| print('Done!') | |
| print('=' * 70) | |
| #====================================================================== | |
| print('Rendering results...') | |
| for i in range(number_of_batches_to_generate): | |
| print('=' * 70) | |
| print('Batch #', i) | |
| print('=' * 70) | |
| out1 = out0[i] | |
| print('Sample INTs', out1[:12]) | |
| print('=' * 70) | |
| if len(out) != 0: | |
| song = out1 | |
| song_f = [] | |
| time = 0 | |
| dur = 0 | |
| channel = 0 | |
| pitch = 0 | |
| vel = 90 | |
| for ss in song: | |
| if ss > 0 and ss < 256: | |
| time += ss * 8 | |
| if ss >= 256 and ss < 256+(12*128): | |
| dur = ((ss-256) % 128) * 30 | |
| if ss >= 256+(12*128) and ss < 256+(12*128)+(12*128): | |
| channel = (ss-(256+(12*128))) // 128 | |
| pitch = (ss-(256+(12*128))) % 128 | |
| vel = velocities_map[channel] | |
| song_f.append(['note', time, dur, channel, pitch, vel ]) | |
| detailed_stats = TMIDIX.Tegridy_SONG_to_MIDI_Converter(song_f, | |
| output_signature = 'Euterpe X', | |
| output_file_name = '/content/Euterpe-X-Music-Composition_'+str(i), | |
| track_name='Project Los Angeles', | |
| list_of_MIDI_patches=[0, 24, 32, 40, 42, 46, 56, 71, 73, 0, 53, 19, 0, 0, 0, 0], | |
| number_of_ticks_per_quarter=500) | |
| print('=' * 70) | |
| print('Displaying resulting composition...') | |
| print('=' * 70) | |
| fname = '/content/Euterpe-X-Music-Composition_'+str(i) | |
| x = [] | |
| y =[] | |
| c = [] | |
| colors = ['red', 'yellow', 'green', 'cyan', 'blue', 'pink', 'orange', 'purple', 'gray', 'white', 'gold', 'silver'] | |
| for s in song_f: | |
| x.append(s[1] / 1000) | |
| y.append(s[4]) | |
| c.append(colors[s[3]]) | |
| FluidSynth("/usr/share/sounds/sf2/FluidR3_GM.sf2", 16000).midi_to_audio(str(fname + '.mid'), str(fname + '.wav')) | |
| display(Audio(str(fname + '.wav'), rate=16000)) | |
| plt.figure(figsize=(14,5)) | |
| ax=plt.axes(title=fname) | |
| ax.set_facecolor('black') | |
| plt.scatter(x,y, c=c) | |
| ax.axvline(x=block_marker, c='w') | |
| plt.xlabel("Time") | |
| plt.ylabel("Pitch") | |
| plt.show()#@title Standard/Simple Continuation | |
| #@markdown Text-To-Music Settings | |
| #@markdown NOTE: You can enter any desired title or artist, or both | |
| enter_desired_song_title = "Family Guy" #@param {type:"string"} | |
| enter_desired_artist = "TV Themes" #@param {type:"string"} | |
| #@markdown Generation Settings | |
| number_of_tokens_to_generate = 426 #@param {type:"slider", min:30, max:2046, step:33} | |
| number_of_batches_to_generate = 4 #@param {type:"slider", min:1, max:16, step:1} | |
| temperature = 0.9 #@param {type:"slider", min:0.1, max:1, step:0.1} | |
| allow_model_to_stop_generation_if_needed = False #@param {type:"boolean"} | |
| print('=' * 70) | |
| print('Euterpe X TTM Model Generator') | |
| print('=' * 70) | |
| 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) | |
| if allow_model_to_stop_generation_if_needed: | |
| min_stop_token = 3343 | |
| else: | |
| min_stop_token = None | |
| # Velocities | |
| velocities_map = [80, 80, 70, 100, 90, 80, 100, 100, 100, 90, 110, 100] | |
| vel_map = AUX_DATA[search_index][1] | |
| for i in range(12): | |
| if vel_map[i] != 0: | |
| velocities_map[i] = vel_map[i] | |
| # Loading data... | |
| outy = AUX_DATA[search_index][2][3:] | |
| block_marker = sum([(y * 8) for y in outy if y < 256]) / 1000 | |
| inp = [outy] * number_of_batches_to_generate | |
| inp = torch.LongTensor(inp).cuda() | |
| out = model.module.generate(inp, | |
| number_of_tokens_to_generate, | |
| temperature=temperature, | |
| return_prime=True, | |
| eos_token=min_stop_token, | |
| verbose=True) | |
| out0 = out.tolist() | |
| print('=' * 70) | |
| print('Done!') | |
| print('=' * 70) | |
| #====================================================================== | |
| print('Rendering results...') | |
| for i in range(number_of_batches_to_generate): | |
| print('=' * 70) | |
| print('Batch #', i) | |
| print('=' * 70) | |
| out1 = out0[i] | |
| print('Sample INTs', out1[:12]) | |
| print('=' * 70) | |
| if len(out) != 0: | |
| song = out1 | |
| song_f = [] | |
| time = 0 | |
| dur = 0 | |
| channel = 0 | |
| pitch = 0 | |
| vel = 90 | |
| for ss in song: | |
| if ss > 0 and ss < 256: | |
| time += ss * 8 | |
| if ss >= 256 and ss < 256+(12*128): | |
| dur = ((ss-256) % 128) * 30 | |
| if ss >= 256+(12*128) and ss < 256+(12*128)+(12*128): | |
| channel = (ss-(256+(12*128))) // 128 | |
| pitch = (ss-(256+(12*128))) % 128 | |
| vel = velocities_map[channel] | |
| song_f.append(['note', time, dur, channel, pitch, vel ]) | |
| detailed_stats = TMIDIX.Tegridy_SONG_to_MIDI_Converter(song_f, | |
| output_signature = 'Euterpe X', | |
| output_file_name = '/content/Euterpe-X-Music-Composition_'+str(i), | |
| track_name='Project Los Angeles', | |
| list_of_MIDI_patches=[0, 24, 32, 40, 42, 46, 56, 71, 73, 0, 53, 19, 0, 0, 0, 0], | |
| number_of_ticks_per_quarter=500) | |
| print('=' * 70) | |
| print('Displaying resulting composition...') | |
| print('=' * 70) | |
| fname = '/content/Euterpe-X-Music-Composition_'+str(i) | |
| x = [] | |
| y =[] | |
| c = [] | |
| colors = ['red', 'yellow', 'green', 'cyan', 'blue', 'pink', 'orange', 'purple', 'gray', 'white', 'gold', 'silver'] | |
| for s in song_f: | |
| x.append(s[1] / 1000) | |
| y.append(s[4]) | |
| c.append(colors[s[3]]) | |
| FluidSynth("/usr/share/sounds/sf2/FluidR3_GM.sf2", 16000).midi_to_audio(str(fname + '.mid'), str(fname + '.wav')) | |
| display(Audio(str(fname + '.wav'), rate=16000)) | |
| plt.figure(figsize=(14,5)) | |
| ax=plt.axes(title=fname) | |
| ax.set_facecolor('black') | |
| plt.scatter(x,y, c=c) | |
| ax.axvline(x=block_marker, c='w') | |
| plt.xlabel("Time") | |
| plt.ylabel("Pitch") | |
| plt.show() | |