import os import numpy as np def load_data(dataset, datatype, print_shape = True): assert dataset in ['CMU', 'SFU'] assert datatype in ['skel', 'hist', 'cloud'] datafile = '%s_%s.npz' % (dataset, datatype) print('') print(datafile) if os.path.isfile(datafile): loader = np.load(datafile) training, test_normal, test_abnormal = loader['train'], loader['test_normal'], loader['test_abnormal'] if print_shape: print('Training:', [datum.shape for datum in training], ' (%d frames)' % np.sum([len(datum) for datum in training])) print('Test_normal:', [datum.shape for datum in test_normal], ' (%d frames)' % np.sum([len(datum) for datum in test_normal])) print('Test_abnormal:', [datum.shape for datum in test_abnormal], ' (%d frames)' % np.sum([len(datum) for datum in test_abnormal])) return training, test_normal, test_abnormal print('File not found!') return None, None, None if __name__ == '__main__': # CMU point cloud load_data('CMU', 'cloud') # CMU skeleton load_data('CMU', 'skel') # CMU histogram load_data('CMU', 'hist') # SFU point cloud load_data('SFU', 'cloud') # SFU skeleton load_data('SFU', 'skel') # SFU histogram load_data('SFU', 'hist')