testX, testY = func_utils.reshape_function_data(test_set)
to_test_net = Net.Mlp(model_file=conf['model_path'], framework="keras")
elif data_type == "Vectors_dataset":
parameters, test_set = vect_utils.read_vector_data(conf['data_path'])
gap = parameters.iloc[0]['gap']
dim = None
print('Puting the test data into the right shape...')
testX, testY = vect_utils.reshape_vector_data(test_set)
if net_type == "NOREC":
to_test_net = Net.Convolution1D(model_file=conf['model_path'],
framework="keras")
else:
to_test_net = Net.Lstm(model_file=conf['model_path'],
framework="keras")
else: # data_type == "Frames_dataset
sample_type = conf['data_path'].split('/')[-1]
data_type = data_type + "_" + sample_type
samples_dir = conf['data_path'].split('/')[5]
dim = (int(samples_dir.split('_')[-2]),
int(samples_dir.split('_')[-1]))
if sample_type == "raw_samples":
if net_type == "NOREC":
print('Puting the test data into the right shape...')
parameters, testX, testY = frame_utils.read_frame_data(
conf['data_path'], sample_type)
to_test_net = Net.Convolution2D(model_file=conf['model_path'],
framework="keras")
else:
# Put the validation data into the right shape
valX, valY = vect_utils.reshape_vector_data(val_set)
train_data = [trainX, trainY]
val_data = [valX, valY]
# Model settings
in_dim = trainX.shape[1:]
out_dim = np.prod(in_dim[1:])
if net_type == "NoRec":
to_train_net = Net.Convolution1D(activation=activation, loss=loss, dropout=dropout,
drop_percentage=drop_percentage, input_shape=in_dim,
output_shape=out_dim, framework="keras")
else: # net_type == "Rec"
to_train_net = Net.Lstm(activation=activation, loss=loss, dropout=dropout,
drop_percentage=drop_percentage, input_shape=in_dim,
output_shape=out_dim, data_type="Vector", framework="keras")
else: # data_type == 'Frames_dataset':
print('Training with frames')
data_model = conf['data_model']
samples_dir = data_dir.split('/')[5]
dim = (int(samples_dir.split('_')[-2]), int(samples_dir.split('_')[-1]))
complexity = conf['complexity']
# Load data
channels = False
if data_model == "raw":
loss = conf['raw_frame_loss']
print("Raw images")