4/5/2023 0 Comments Numpy .vstack![]() ![]() ![]() Tmp2 = bob.io.base.load(fs.d_same_value_file(t_model_id, group)) Tmp = bob.io.base.load(fs.d_file(t_model_id, group)) """Compute normalized D scores for the given T-model ids""" (, self.subspace_dim)į = bob.io.base.HDF5File(projector_file, "w")ĭef _scores_d_normalize(t_model_ids, group): Keeping %d PCA dimensions", self.subspace_dim) # compute variance percentage, if desiredĬummulated = numpy.cumsum(self.variances) / numpy.sum(self.variances) Self.machine, self.variances = t.train(data) Training_features : Ī list of 1D training arrays (vectors) to train the PCA projection matrix with.Ī writable file, into which the PCA projection matrix (as a :py:class:``) and the eigenvalues will be written. """Generates the PCA covariance matrix and writes it into the given projector_file. Return numpy.vstack(f.flatten() for f in enroll_features)ĭef train_projector(self, training_features, projector_file): The list of projected features to enroll the model from. If self.k_models!=None and len(self.k_models) modelĮnrolls the model by storing all given input vectors.Įnroll_features : Waveform = f.valueĭef _extract_signals(self, data, metadata, lazy):Īrr = numpy.vstack(self._extract_array(data, channel_index)įor channel_index in range(metadata, metadata + 1)) Gridheight = (height - 2 * crop) // grid # should be 6 for our dataĬell = source Height = source.shape # should be 224 for our data Model = Nystrom(k, n_components=embedding_dim) Print("Average size: %.2f" % np.mean(lens)) Print("Number of communities: ", len(communities)) Graphs, labels = load_data(ds_name, use_node_labels)Ĭommunities, subgraphs = compute_communities(graphs, use_node_labels, community_detection_method) # OpenCVKLT.draw_tracks(self, vis, colored=colored, max_track_length=10)ĭef compute_nystrom(ds_name, use_node_labels, embedding_dim, community_detection_method, kernels): ![]() Vis = super(BoundingBoxKLT, self).viz(vis, colored=colored) M = np.bitwise_and(np.isfinite(fx), np.isfinite(fy)) You can also save this page to your account. You can vote up the examples you like or vote down the exmaples you don’t like. They are extracted from open source Python projects. The following are code examples for showing how to use. ![]()
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