msaf/algorithms/vmo/segmenter.py
def processFlat(self):
        """Main process.
        Returns
        -------
        est_idxs : np.array(N)
            Estimated indeces the segment boundaries in frame indeces.
        est_labels : np.array(N-1)
            Estimated labels for the segments.
        """
        # Preprocess to obtain features (array(n_frames, n_features))

        F = self._preprocess()
        F = librosa.util.normalize(F, axis=0)
        F = librosa.feature.stack_memory(F.T).T

        self.config["hier"] = False
        my_bounds, my_labels, _ = main.scluster_segment(F, self.config, self.in_bound_idxs)

        # Post process estimations
        est_idxs, est_labels = self._postprocess(my_bounds, my_labels)

        assert est_idxs[0] == 0 and est_idxs[-1] == F.shape[0] - 1
        # We're done!
        return est_idxs, est_labels
def processFlat(self):
        """Main process.
        Returns
        -------
        est_idxs : np.array(N)
            Estimated indeces the segment boundaries in frame indeces.
        est_labels : np.array(N-1)
            Estimated labels for the segments.
        """
        # Preprocess to obtain features (array(n_frames, n_features))

        F = self._preprocess()
        F = librosa.util.normalize(F, axis=0)
        F = librosa.feature.stack_memory(F.T).T

        self.config["hier"] = False
        my_bounds, my_labels, _ = main.scluster_segment(F, self.config, self.in_bound_idxs)

        # Post process estimations
        est_idxs, est_labels = self._postprocess(my_bounds, my_labels)

        assert est_idxs[0] == 0 and est_idxs[-1] == F.shape[0] - 1
        # We're done!
        return est_idxs, est_labels
Main process.
        Returns
        -------
        est_idxs : np.array(N)
            Estimated indeces the segment boundaries in frame indeces.
        est_labels : np.array(N-1)
            Estimated labels for the segments.