_summary_ Args: skip_channels (int): channels for the incomming upsampled features fp_channels (_type_): channels for

Computes the accuracy over the k top predictions for the specified values of k

input: B x * x ... x * dim: 0 < scalar index: B x M

Build a dataset, defined by `dataset_name`. Args: cfg (eDICT): Returns: Dataset: a constructed dataset specified by data

Build a dataset, defined by `dataset_name`. Args: cfg (eDICT): Returns: Dataset: a constructed dataset specified by datas

Convert original dataset files to ply file (each line is XYZRGBL). We aggregated all the points from each instance in the room. :param an

Distributes the depth associated with each point to the discrete coordinates (image_height, image_width) in a region of size (size_x, size_y)

DropBlock. See https://arxiv.org/pdf/1810.12890.pdf DropBlock with an experimental gaussian noise option. This layer has been tested on a few tr

DropBlock. See https://arxiv.org/pdf/1810.12890.pdf DropBlock with an experimental gaussian noise option. Simplied from above without concern fo

Drop paths (Stochastic Depth) per sample (when applied in main path of residual blocks). This is the same as the DropConnect impl I created for E

Convert euler angles to rotation matrix. :param angle: [3] or [b, 3] :return rotmat: [3] or [b, 3, 3] source https://github.

Input: xyz: pointcloud data, [B, N, 3] npoint: number of samples Return: centroids: sampled pointcloud index, [B, npo

Args: xyz [point]: (B, N, 3) npoint [number of points]: int Return: centroids [sampled pointcloud index]: (B, n

FNV64-1A

:param pc: :return:

# chamfer distance. two options 1. chamfer distance on the merged point clouds. 2. chamfer distance per local patch

# chamfer distance. two options 1. chamfer distance on the merged point clouds. 2. chamfer distance per local patch

# chamfer distance. two options 1. chamfer distance on the merged point clouds. 2. chamfer distance per local patch