def __init__(self, root_dir, transform=None, binarize=True, delta=1):
"""
Args:
root_dir (string): Directory with all the csv
transform (callable, optional): Optional transform to be applied
on a sample.
"""
super(pianoroll_dataset_chunks, self).__init__()
self.root_dir = root_dir
self.transform = transform
self.tags = datp.load_all_dataset_names(self.root_dir)
self.tags_ids = dict(
zip(np.unique(self.tags), range(np.unique(self.tags).size)))
self.fulldata = datp.load_all_dataset(self.root_dir, binarize)
self.fulldata = tuple(
self.convert_fulldata(i, delta) for i in range(len(self.tags)))
self.indexes = [(0, 0)]
def __init__(self,
root_dir,
transform=None,
name_as_tag=True,
binarize=True):
"""
Args:
root_dir (string): Directory with all the csv
transform (callable, optional): Optional transform to be applied
on a sample.
"""
super(pianoroll_dataset_batch, self).__init__()
self.root_dir = root_dir
self.transform = transform
if (name_as_tag):
self.tags = datp.load_all_dataset_names(self.root_dir)
self.tags_ids = dict(
zip(np.unique(self.tags), range(np.unique(self.tags).size)))
self.data = datp.load_all_dataset(self.root_dir, binarize)
def main():
path = 'C:/Users/Phi Thien/PycharmProjects/TDT76/'
dataset = 'piano_roll_fs5'
training_data = dataprep.load_all_dataset('datasets/training/' + dataset,
binarize=True)
names = dataprep.load_all_dataset_names('datasets/training/' + dataset)
test = dataprep.test_piano_roll(training_data[0], 15, fs=5)
# dataprep.piano_roll_to_mid_file(training_data[0], 'test1.mid', fs=5)
# dataprep.visualize_piano_roll(training_data[0], fs=5)
generalist = Generalist([128, 31, 31, 31, 128], training_data)
generalist.train_network(250)
generalist.save_network('generalist.h5')
generalist_result = generalist.gen_music(test.T)
dataprep.visualize_piano_roll(generalist_result, fs=5)
dataprep.piano_roll_to_mid_file(generalist_result, 'gen_res.mid', fs=5)