open3d.ml.tf.models.DataProcessing

class open3d.ml.tf.models.DataProcessing
static IoU_from_confusions(confusions)

Computes IoU from confusion matrices. :param confusions: ([…, n_c, n_c] np.int32). Can be any dimension, the confusion matrices should be described by the last axes. n_c = number of classes :return: ([…, n_c] np.float32) IoU score

__init__()

Initialize self. See help(type(self)) for accurate signature.

static data_aug(xyz, color, labels, idx, num_out)
static get_class_weights(num_per_class)
static grid_subsampling(points, features=None, labels=None, grid_size=0.1, verbose=0)

CPP wrapper for a grid subsampling (method = barycenter for points and features) :param points: (N, 3) matrix of input points :param features: optional (N, d) matrix of features (floating number) :param labels: optional (N,) matrix of integer labels :param sampleDl: parameter defining the size of grid voxels :param verbose: 1 to display :return: subsampled points, with features and/or labels depending of the input

Parameters

  • support_pts – points you have, B*N1*3

  • query_pts – points you want to know the neighbour index, B*N2*3

  • k – Number of neighbours in knn search

Returns

neighbor_idx: neighboring points indexes, B*N2*k

static load_label_kitti(label_path, remap_lut)
static load_label_semantic3d(filename)
static load_pc_kitti(pc_path)
static load_pc_semantic3d(filename)
static shuffle_idx(x)
static shuffle_list(data_list)