def merge(prefix, X): pr = prefix if (pr == "test"): pr = "valid" file_name = data_io.get_json()["feature_" + pr + "_path_matlab"] X = add_matlab_samples(X, "./Models/Matlab/" + prefix + "*.csv") print "Saving features with shape", X.shape, "at", file_name data_io.save(X, file_name) return file_name
def merge(prefix, X): pr = prefix if(pr == "test"): pr = "valid" file_name = data_io.get_json()["feature_" + pr + "_path_matlab"] X = add_matlab_samples(X, "./Models/Matlab/" + prefix + "*.csv") print "Saving features with shape", X.shape, "at", file_name data_io.save(X, file_name) return file_name
def main(): fp.n_threads = int(data_io.get_json()["feature_extraction_threads"]) print("extracting train data set features") X = data_io.load_train_features() if(X is None): extract_train_features() else: print("Feature already extracted!") print("extracting valid data set features") X = data_io.load_valid_features() if(X is None): extract_valid_features() else: print("Feature already extracted!")
def main(): fp.n_threads = int(data_io.get_json()["feature_extraction_threads"]) print("extracting train data set features") X = data_io.load_train_features() if (X is None): extract_train_features() else: print("Feature already extracted!") print("extracting valid data set features") X = data_io.load_valid_features() if (X is None): extract_valid_features() else: print("Feature already extracted!")