(self, pclouds, batch_size=50)
return np.vstack(reconstructions)
Get the reconstructions for a set of sampled point clouds.
        Args:
            pclouds (N, K, 3) numpy array of N point clouds with K points each.
            batch_size size of point clouds batch
Get the reconstructions for a set of sampled point clouds.
        Args:
            pclouds (N, K, 3) numpy array of N point clouds with K points each.
            batch_size size of point clouds batch
Get the reconstructions for a set of sampled 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_reconstructions_from_sampled(self, pclouds, batch_size=50):
        """ Get the reconstructions for a set of sampled point clouds.
        Args:
            pclouds (N, K, 3) numpy array of N point clouds with K points each.
            batch_size size of point clouds batch
        """
        reconstructions = []
        idx = np.arange(len(pclouds))
        for b in iterate_in_chunks(idx, batch_size):
            feed_dict = {self.s: pclouds[b]}
            rcon = self.sess.run(self.x_reconstr, feed_dict=feed_dict)
            reconstructions.append(rcon)
        return np.vstack(reconstructions)
def get_reconstructions_from_sampled ( self , pclouds , batch_size = 50 ) : reconstructions = [ ] idx = np . arange ( len ( pclouds ) ) for b in iterate_in_chunks ( idx , batch_size ) : feed_dict = { self . s : pclouds [ b ] } rcon = self . sess . run ( self . x_reconstr , feed_dict = feed_dict ) reconstructions . append ( rcon ) return np . vstack ( reconstructions )