app.py

import gradio as gr
from tensorflow.keras.models import load_model
import numpy as np
import pretty_midi
import tensorflow as tf


model = load_model('model/')


def predict_next_note(notes, keras_model, temperature=1.0):
    assert temperature > 0
    inputs = tf.expand_dims(notes, 0)
    predictions = model.predict(inputs)
    pitch_logits = predictions['pitch']
    step = predictions['step']
    duration = predictions['duration']

    pitch_logits /= temperature
    pitch = tf.random.categorical(pitch_logits, num_samples=1)
    pitch = tf.squeeze(pitch, axis=-1)
    duration = tf.squeeze(duration, axis=-1)
    step = tf.squeeze(step, axis=-1)

    step = tf.maximum(0, step)
    duration = tf.maximum(0, duration)

    return int(pitch.numpy()), float(step.numpy()), float(duration.numpy())


def notes_to_midi(notes, out_file, instrument_name="Acoustic Grand Piano"):
    pm = pretty_midi.PrettyMIDI()
    instrument = pretty_midi.Instrument(program=pretty_midi.instrument_name_to_program(instrument_name))

    for note_data in notes:
        note = pretty_midi.Note(velocity=100, pitch=int(note_data[0]), start=note_data[3], end=note_data[4])
        instrument.notes.append(note)

    pm.instruments.append(instrument)
    pm.write(out_file)
    return out_file


def generate_music(input_text):
    input_sequence = np.fromstring(input_text, sep=',')
    temperature = 2.0
    num_predictions = 120
    generated_notes = []
    prev_start = 0

    for _ in range(num_predictions):
        pitch, step, duration = predict_next_note(input_sequence[-3:], model, temperature)
        start = prev_start + step
        end = start + duration
        generated_notes.append([pitch, step, duration, start, end])
        input_sequence = np.append(input_sequence, [pitch, step, duration])
        prev_start = start

    output_file_name = 'output.mid'
    notes_to_midi(generated_notes, output_file_name)

    return output_file_name


# Gradioインターフェースの定義
iface = gr.Interface(fn=generate_music, inputs='text', outputs='audio')
iface.launch()