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| import gradio as gr | |
| from transformers import AutoTokenizer, TFGPT2LMHeadModel | |
| from transformers import pipeline | |
| import note_seq | |
| from utils import token_sequence_to_note_sequence, create_image_from_note_sequence | |
| SAMPLE_RATE=44100 | |
| # Feel free to change this, I am using only three notes here because the model | |
| # works better this way. | |
| notes = ["D3", "G3", "E4"] | |
| notes_to_midi = {"D3": 50, "G3": 55, "E4": 64} | |
| time_signatures = ["4/4", "3/4", "2/4", "6/8"] | |
| time_signature_to_tokens = {"4/4": "4_4", "3/4": "3_4", "2/4": "2_4", "6/8": "6_8"} | |
| # Mutopi model for music generation | |
| mutopia_model = TFGPT2LMHeadModel.from_pretrained("juancopi81/mutopia_guitar_mmm") | |
| mutopia_tokenizer = AutoTokenizer.from_pretrained("juancopi81/mutopia_guitar_mmm") | |
| pipe = pipeline( | |
| "text-generation", model=mutopia_model, tokenizer=mutopia_tokenizer, device=0 | |
| ) | |
| # Content for your demo: | |
| title = "Mutopia Guitar Composer" | |
| # I am adding here an image that I generated using DALL-E | |
| description = """ | |
| The bot was trained to compose guitar music using the | |
| [Mutopia Guitar Dataset](https://huggingface.co./datasets/juancopi81/mutopia_guitar_dataset). | |
| Change the controllers and receive a new guitar piece! | |
| <figure> | |
| <center> | |
| <img src="https://drive.google.com/uc?export=view&id=1F22ofTCeJAHqVag4lJvBZugAE1OyabVA" | |
| width=200px alt="Robot playing the guitar"> | |
| <figcaption>Image generated using DALL-E</figcaption> | |
| </center> | |
| </figure> | |
| """ | |
| article = """ | |
| For a complete tutorial on how to create this demo from scratch, check out this | |
| [GitHub Repo](https://github.com/juancopi81/MMM_Mutopia_Guitar). | |
| """ | |
| # Helper function to create the string seed | |
| def create_seed(time_signature: str, | |
| note: str, | |
| bpm: int, | |
| density: int) -> str: | |
| seed = (f"PIECE_START TIME_SIGNATURE={time_signature_to_tokens[time_signature]} " | |
| f"BPM={bpm} TRACK_START INST=0 DENSITY={density} " | |
| f"BAR_START NOTE_ON={notes_to_midi[note]} ") | |
| return seed | |
| def generate_guitar_piece(time_signature: str, | |
| note: str, | |
| bpm: int, | |
| density: int): | |
| seed = create_seed(time_signature, note, bpm, density) | |
| piece = pipe(seed, max_length=250)[0]["generated_text"] | |
| # Convert text of notes to audio | |
| note_sequence = token_sequence_to_note_sequence(piece) | |
| synth = note_seq.midi_synth.fluidsynth | |
| array_of_floats = synth(note_sequence, sample_rate=SAMPLE_RATE) | |
| int16_data = note_seq.audio_io.float_samples_to_int16(array_of_floats) | |
| piano_roll = create_image_from_note_sequence(note_sequence) | |
| return (SAMPLE_RATE, int16_data), piano_roll | |
| # Create a block object | |
| demo = gr.Blocks() | |
| # Use your Block object as a context | |
| with demo: | |
| gr.Markdown("<h1 style='text-align: center; margin-bottom: 1rem'>" | |
| + title | |
| + "</h1>") | |
| gr.Markdown(description) | |
| # UI for the inputs of the model | |
| gr.Markdown("Select the generation parameters.") | |
| with gr.Row(): | |
| time_signature = gr.Dropdown(time_signatures, value="4/4", label="Time signature") | |
| note = gr.Dropdown(notes, value="G3", label="First note") | |
| bpm = gr.Slider(minimum=60, maximum=140, step=10, value=90, label="Tempo") | |
| density = gr.Slider(minimum=0, maximum=4, step=1, value=2, label="Density") | |
| with gr.Row(): | |
| btn = gr.Button("Compose") | |
| with gr.Row(): | |
| audio_output = gr.Audio() | |
| image_output = gr.Image() | |
| btn.click(generate_guitar_piece, | |
| inputs = [ | |
| time_signature, | |
| note, | |
| bpm, | |
| density | |
| ], | |
| outputs=[audio_output, image_output]) | |
| gr.Markdown(article) | |
| # Launch your demo | |
| demo.launch(debug=False) |