model_input.py 文件源码

def __init__(self, filename_provider):
        training_filenames = filename_provider()
        self.sequence_dirs = [os.path.join(self.BASE_DATA_DIR, filename) for filename in training_filenames]

        self.seq_dir_map = {}

        for seq_dir in self.sequence_dirs:
            associations = np.loadtxt(os.path.join(seq_dir, "associate.txt"), dtype="str", unpack=False)
            groundtruth = np.loadtxt(os.path.join(seq_dir , "groundtruth.txt"), dtype="str", unpack=False)
            if seq_dir not in self.seq_dir_map:
                self.seq_dir_map[seq_dir] = {}
            self.seq_dir_map[seq_dir]['associations'] = associations
            self.seq_dir_map[seq_dir]['groundtruth'] = groundtruth

            sequence_size = associations.shape[0]
            twist = np.zeros((sequence_size, 6))
            trans_old = np.zeros((4, 4))
            for i in range(sequence_size):
                quat = groundtruth[:, 1:][_find_label(groundtruth[:, 0], associations[i, 0])].astype(np.float32)
                trans_new = _quat_to_transformation(quat)
                if i > 0:
                    twist[i] = _trans_to_twist(trans_new)
                else:
                    twist[i] = np.zeros(6)
                trans_old = trans_new

            self.seq_dir_map[seq_dir]['relpos'] = twist