madratman

#include <ros/ros.h>
#include <actionlib/client/simple_action_client.h>
#include <control_msgs/FollowJointTrajectoryAction.h>
#include <descartes_moveit/moveit_state_adapter.h>
#include <descartes_planner/dense_planner.h>
#include <descartes_trajectory/axial_symmetric_pt.h>
#include <descartes_trajectory/cart_trajectory_pt.h>
#include <moveit/move_group_interface/move_group.h>
#include <moveit/robot_model_loader/robot_model_loader.h>
#include <moveit/robot_state/conversions.h>

madratman

#include <iostream>
#include <string>
#include <cstring>
#define xstr(a) str(a)
#define str(a) #a

int main()
{
    std::string name = "madratman";
    if( xstr(name) == "name" && !strcmp(xstr(name), "name") && "madratman"==name && "madratman"=="madratman" )

madratman

#include <iostream>
#include <string>
#include <cstring>
#define xstr(a) str(a)
#define str(a) #a

int main()
{
    char* name = "madratman";
    if( xstr(name) == "name"  )

madratman

mport cPickle as pickle
from datetime import datetime
import os
import sys

import matplotlib.pyplot as plt
import numpy as np
from lasagne import layers
from sklearn.utils import shuffle
import theano

madratman

FROM ubuntu:14.04
LABEL maintainer "NVIDIA CORPORATION <cudatools@nvidia.com>"

LABEL com.nvidia.volumes.needed="nvidia_driver"

RUN NVIDIA_GPGKEY_SUM=d1be581509378368edeec8c1eb2958702feedf3bc3d17011adbf24efacce4ab5 && \
    NVIDIA_GPGKEY_FPR=ae09fe4bbd223a84b2ccfce3f60f4b3d7fa2af80 && \
    apt-key adv --fetch-keys http://developer.download.nvidia.com/compute/cuda/repos/ubuntu1404/x86_64/7fa2af80.pub && \
    apt-key adv --export --no-emit-version -a $NVIDIA_GPGKEY_FPR | tail -n +2 > cudasign.pub && \
    echo "$NVIDIA_GPGKEY_SUM  cudasign.pub" | sha256sum -c --strict - && rm cudasign.pub && \

madratman

def add_dilated(**kwargs):
	# print kwargs['key']
	return "net['{0}'] = DilatedConv2DLayer(net['{1}'], num_filters={2}, filter_size={3}, dilation={4}, name='{0}')".format(
		kwargs['curr_layer_name'], kwargs['prev_layer_name'], kwargs['num_filters'], kwargs['filter_size'], kwargs['dilation'])

def add_vanilla(**kwargs):
	# print kwargs['key']
	return "net['{0}'] = ConvLayer(net['{1}'], num_filters={2}, filter_size={3}, pad={4}, name='{0}')".format(
		kwargs['curr_layer_name'], kwargs['prev_layer_name'], kwargs['num_filters'], kwargs['filter_size'], kwargs['pad'])

madratman

cmake -D CMAKE_BUILD_TYPE=RELEASE 
      -D INSTALL_C_EXAMPLES=ON
      -D INSTALL_PYTHON_EXAMPLES=OFF
      -D OPENCV_EXTRA_MODULES_PATH=/home/ratneshmadaan/software/opencv_contrib/modules 
      -D BUILD_EXAMPLES=ON ..

don't forget to checkout tags in contrib and main repo
lol @ -D CMAKE_INSTALL_PREFIX=/home/ratneshmadaan/software/opencv/build/install

madratman

Add this to dockerfile:

RUN apt-get update RUN apt-get install -qqy x11-apps ENV DISPLAY :0

Authorise current user first in host: xhost +si:localuser:$USER

madratman

# Kl = ( Mat_<float>(3,3) << Kl_[0], 0.0, Kl_[2],
                           # 0.0, Kl_[1], Kl_[3], 
                           # 0.0, 0.0, 1.0 );
cam0:
  Kl: [536.1659550000001, 536.538415, 317.456864, 261.798048] #fx, fy, cx, cy
  Kr: [535.427087, 535.775524, 314.884298, 261.374341]
  cam_bl: 0.17454185842
  cam_height: 512
  cam_model: Pinhole
  cam_width: 640

madratman

sudo chgrp -R GROUP_NAME PATH_TO_DIR
sudo chmod -R g+w PATH_TO_DIR #for write permission