fisher.py 文件源码

def _fisher_vector(self, img_descriptors):
        """
        :param img_descriptors: X
        :return: fisher vector
        :rtype: np.array
        """
        means, covariances, weights = self.gmm.means, self.gmm.covariances, self.gmm.weights
        s0, s1, s2 = self._likelihood_statistics(img_descriptors)
        T = img_descriptors.shape[0]
        diagonal_covariances = np.float32([np.diagonal(covariances[k]) for k in range(0, covariances.shape[0])])
        """ Refer page 4, first column of reference [1] """
        g_weights = self._fisher_vector_weights(s0, s1, s2, means, diagonal_covariances, weights, T)
        g_means = self._fisher_vector_means(s0, s1, s2, means, diagonal_covariances, weights, T)
        g_sigma = self._fisher_vector_sigma(s0, s1, s2, means, diagonal_covariances, weights, T)
        fv = np.concatenate([np.concatenate(g_weights), np.concatenate(g_means), np.concatenate(g_sigma)])
        fv = self.normalize(fv)
        return fv