usamec

import torch

class ResumableRandomSampler(torch.utils.data.Sampler):
    r"""Samples elements randomly. If without replacement, then sample from a shuffled dataset.
    If with replacement, then user can specify :attr:`num_samples` to draw.
    Arguments:
        data_source (Dataset): dataset to sample from
        replacement (bool): samples are drawn on-demand with replacement if ``True``, default=``False``
        num_samples (int): number of samples to draw, default=`len(dataset)`. This argument
            is supposed to be specified only when `replacement` is ``True``.

skyrocknroll

# Make sure you grab the latest version
curl -OL https://github.com/google/protobuf/releases/download/v3.4.0/protoc-3.4.0-linux-x86_64.zip

# Unzip
unzip protoc-3.4.0-linux-x86_64.zip -d protoc3

# Move protoc to /usr/local/bin/
sudo mv protoc3/bin/* /usr/local/bin/

# Move protoc3/include to /usr/local/include/

jinyu121

# -*- coding: utf-8 -*-

from __future__ import absolute_import
from __future__ import division
from __future__ import print_function

import argparse
import numpy as np
import os
import random

somada141

Assuming we have an .stl file under filenameSTL we can load the contents of that file using the vtkSTLReader class as such:

readerSTL = vtk.vtkSTLReader()
readerSTL.SetFileName(filenameSTL)
# 'update' the reader i.e. read the .stl file
readerSTL.Update()

polydata = readerSTL.GetOutput()