X, y, paths_train = data.get_all_sequences_in_memory('training', frame, seq,
initial)
print("X.shape", X.shape)
print("y.shape", y.shape)
X_val, y_val, paths_val = data.get_all_sequences_in_memory(
'testing', test_frame, seq, test_initial)
print("X_val.shape", X_val.shape)
print("Y_val.shape", y_val.shape)
# X_test, y_test,paths_test = data.get_all_sequences_in_memory('validation',test_frame, seq, test_initial)
# print("X_test.shape" ,X_test.shape)
# print("y_test.shape" ,y_test.shape)
print(data.get_classes())
features = 512
batch_size = 4
nb_epoch = 10
rm = ResearchModels(len(data.classes), 'lstm', data.seq_length, features)
print(rm.model.summary())
log_dir = "logs/model_mobface_512_new/fit/" + datetime.datetime.now().strftime(
"%Y%m%d-%H%M%S")
tensorboard_callback = TensorBoard(log_dir=log_dir, histogram_freq=1)
checkpointer = ModelCheckpoint(filepath='models/model_mobface_512_new.hdf5',
verbose=1,
save_best_only=True)
rm.model.fit(X,
