def project(self, mean, covariance):
        """Project state distribution to measurement space.
        Parameters
        ----------
        mean : ndarray
            The state's mean vector (8 dimensional array).
        covariance : ndarray
            The state's covariance matrix (8x8 dimensional).
        Returns
        -------
        (ndarray, ndarray)
            Returns the projected mean and covariance matrix of the given state
            estimate.
        """
        std = [
            self._std_weight_position * mean[3],
            self._std_weight_position * mean[3],
            1e-1,
            self._std_weight_position * mean[3]]
        innovation_cov = np.diag(np.square(std))

        mean = np.dot(self._update_mat, mean)
        covariance = np.linalg.multi_dot((
            self._update_mat, covariance, self._update_mat.T))
        return mean, covariance + innovation_cov
Project state distribution to measurement space.
        Parameters
        ----------
        mean : ndarray
            The state's mean vector (8 dimensional array).
        covariance : ndarray
            The state's covariance matrix (8x8 dimensional).
        Returns
        -------
        (ndarray, ndarray)
            Returns the projected mean and covariance matrix of the given state
            estimate.
        
trackers/deepsort_tracker/kalman_filter.py