def generate(model, seed, mid_name, temperature=1.0, length=512):
'''Generate sequence using model, seed, and temperature.'''
generated = []
phrase = seed
phrase_array = decode(phrase)
for j in range(length):
x = np.zeros((1, PHRASE_LEN, SYMBOL_DIM))
for t, config_id in enumerate(phrase):
x[0, t, config_id] = 1
preds = model.predict(x, verbose=0)[0]
next_id = sample(preds, temperature)
generated += [next_id]
phrase = phrase[1:] + [next_id]
mid = array_to_midi(unfold(decode(generated), OUT_PITCHES), mid_name)
mid.save(os.path.join(MIDI_OUT_DIR, mid_name))
return mid
def generate(model, seed, mid_name, temperature=1.0, length=512):
'''Generate sequence using model, seed, and temperature.'''
generated = []
phrase = seed
phrase_array = decode(phrase)
for j in range(length):
x = np.zeros((1, PHRASE_LEN, SYMBOL_DIM))
for t, config_id in enumerate(phrase):
x[0, t, config_id] = 1
preds = model.predict(x, verbose=0)[0]
next_id = sample(preds, temperature)
generated += [next_id]
phrase = phrase[1:] + [next_id]
mid = array_to_midi(unfold(decode(generated), OUT_PITCHES), mid_name)
mid.save(os.path.join(MIDI_OUT_DIR, mid_name))
return mid
model.load_weights(path)
return model
windows, X, y = prepare_data()
model = train_model(X, y, path='models/accompaniment/model')
#model = load_model('models/accompaniment/model')
in_pattern = np.zeros(32)
in_pattern[::8] = 1
in_pattern[2::8] = 1
in_pattern[::5] = 1
x = features(in_pattern)[np.newaxis, :]
y = model.predict(x)
print(y)
y_amplitude = y[:, :32]
y_phase = y[:, 32:]
y_complex = y_amplitude + 1j * y_phase
out_pattern = np.abs(np.fft.ifft(y_complex))
print(out_pattern)
out_pattern[out_pattern < 0.05] = 0
print(out_pattern)
out_pattern = (128 * out_pattern).astype(int)
print(out_pattern)
combined_pattern = np.vstack([in_pattern, out_pattern])
print(combined_pattern)
mid = midi_util.array_to_midi(combined_pattern.transpose(),
'test',
quantization=5)
mid.save('beatzzz.mid')
model.load_weights(path)
return model
windows, X, y = prepare_data()
model = train_model(X, y, path='models/accompaniment/model')
#model = load_model('models/accompaniment/model')
in_pattern = np.zeros(32)
in_pattern[::8] = 1
in_pattern[2::8] = 1
in_pattern[::5] = 1
x = features(in_pattern)[np.newaxis, :]
y = model.predict(x)
print y
y_amplitude = y[:,:32]
y_phase = y[:,32:]
y_complex = y_amplitude + 1j * y_phase
out_pattern = np.abs(np.fft.ifft(y_complex))
print out_pattern
out_pattern[out_pattern < 0.05] = 0
print out_pattern
out_pattern = (128 * out_pattern).astype(int)
print out_pattern
combined_pattern = np.vstack([in_pattern, out_pattern])
print combined_pattern
mid = midi_util.array_to_midi(combined_pattern.transpose(),
'test', quantization=5)
mid.save('beatzzz.mid')