pangyuteng

sudo su -
# go to system root, cd ..
mkdir /opt/anaconda3
# installed anaconda to /opt/anaconda3
bash /Temp/Anaconda3-5.1.0-Linux-x86_64.sh
# create py 3.6
/opt/anaconda3/bin/conda create -p /opt/envs/conda/py36 python=3.6
# activate py 3.6
source /opt/anaconda3/bin/activate /opt/envs/conda/py36
# install prebuilt vtk for offscreen rendering

jalola

class DepthToSpace(nn.Module):
    def __init__(self, block_size):
        super(DepthToSpace, self).__init__()
        self.block_size = block_size
        self.block_size_sq = block_size*block_size

    def forward(self, input):
        output = input.permute(0, 2, 3, 1)
        (batch_size, d_height, d_width, d_depth) = output.size()
        s_depth = int(d_depth / self.block_size_sq)

ronrest

"""
VISUALISE THE LIDAR DATA FROM THE KITTI DATASET

Based on the sample code from
    https://github.com/utiasSTARS/pykitti/blob/master/demos/demo_raw.py
And:
    http://stackoverflow.com/a/37863912

Contains two methods of visualizing lidar data interactively.
 - Matplotlib - very slow, and likely to crash, so only 1 out of every 100

jeiting

import gym
import numpy as np

env = gym.make('CartPole-v0')

x = env.reset()
# x, xdot, theta, thetadot

gamma = (4.0 / 3.0 - env.masspole / env.masscart)

awjuliani

Starefossen

Sessions

New Session

• tmux new [-s name] [cmd] (:new) - new session

Switch Session

• tmux ls (:ls) - list sessions
• tmux switch [-t name] (:switch) - switches to an existing session