first commit

app.py

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+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()

requirements.txt

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+gradio
+pyfluidsynth
+pretty-midi
+tensorflow