(self, pclouds, batch_size=100)
return np.vstack(critical_idxs)
Convenience wrapper of self.get_cirtical_idx to get the critical indices for a set of input point clouds.
        Args:
            pclouds (N, K, 3) numpy array of N point clouds with K points each.
            batch_size size of point clouds batch
Convenience wrapper of self.get_cirtical_idx to get the critical indices for a set of input point clouds.
        Args:
            pclouds (N, K, 3) numpy array of N point clouds with K points each.
            batch_size size of point clouds batch
Convenience wrapper of self . get_cirtical_idx to get the critical indices for a set of input point clouds . Args : pclouds ( N K 3 ) numpy array of N point clouds with K points each . batch_size size of point clouds batch
def get_critical_idxs(self, pclouds, batch_size=100):
        """ Convenience wrapper of self.get_cirtical_idx to get the critical indices for a set of input point clouds.
        Args:
            pclouds (N, K, 3) numpy array of N point clouds with K points each.
            batch_size size of point clouds batch
        """
        critical_idxs = []
        idx = np.arange(len(pclouds))
        for b in iterate_in_chunks(idx, batch_size):
            critical_curr = self.get_critical_idx(pclouds[b])
            critical_idxs.append(critical_curr)
        return np.vstack(critical_idxs)
def get_critical_idxs ( self , pclouds , batch_size = 100 ) : critical_idxs = [ ] idx = np . arange ( len ( pclouds ) ) for b in iterate_in_chunks ( idx , batch_size ) : critical_curr = self . get_critical_idx ( pclouds [ b ] ) critical_idxs . append ( critical_curr ) return np . vstack ( critical_idxs )