arundasan91

Freshly brewed !

With the availability of huge amount of data for research and powerfull machines to run your code on, Machine Learning and Neural Networks is gaining their foot again and impacting us more than ever in our everyday lives. With huge players like Google opensourcing part of their Machine Learning systems like the TensorFlow software library for numerical computation, there are many options for someone interested in starting off with Machine Learning/Neural Nets to choose from. Caffe, a deep learning framework developed by the Berkeley Vision and Learning Center (BVLC) and its contributors, comes to the play with a fresh cup of coffee.

Installation Instructions (Ubuntu 14 Trusty)

The following section is divided in to two parts. Caffe's documentation suggest

clungzta

#!/usr/bin/env python
#ROS Node to convert a GPS waypoint published on the topic "waypoint" into a 2D Navigation Goal in SLAM to achieve autonomous navigation to a GPS Waypoint
#Converts Decimal GPS Coordinates of waypoint to ROS Position Vector relative to the current gps position of the robot
#Accounts for curvature of the earth using haversine formula

#Depends rospy, std_msgs, geographic_msgs, sensor_msgs, numpy
#Written by Alex McClung, 2015, alex.mcclung@hotmail.com, To be Released Open Source under Creative Commons Attribution Share-Alike Licence

import roslib
import rospy

liantian-cn

#!/usr/bin/env python
# -*- coding: utf-8 -*-


from ctypes import *
from ctypes.wintypes import *

INVALID_HANDLE_VALUE = -1
CREATE_UNICODE_ENVIRONMENT = 0x00000400

axel-angel

#!/usr/bin/python
# -*- coding: utf-8 -*-

# Author: Axel Angel, copyright 2015, license GPLv3.

import sys
import caffe
import numpy as np
import lmdb
import argparse

nad2000

/* Example of embedding Python in another program */
// to compile run:
//  gcc -o test $(python-config --cflags) test.c $(python-config --ldflags) && ./test

#include<stdio.h>
#include "Python.h"

void initxyzzy(void); /* Forward */

main(int argc, char **argv)

Rod-Persky

# _______  __   __  _______  ______   _______  _______  _______  ______  #
#|       ||  | |  ||       ||      | |   _   ||       ||       ||      | #
#|   _   ||  | |  ||_     _||  _    ||  |_|  ||_     _||    ___||  _    |#
#|  | |  ||  |_|  |  |   |  | | |   ||       |  |   |  |   |___ | | |   |#
#|  |_|  ||       |  |   |  | |_|   ||       |  |   |  |    ___|| |_|   |#
#|       ||       |  |   |  |       ||   _   |  |   |  |   |___ |       |#
#|_______||_______|  |___|  |______| |__| |__|  |___|  |_______||______| #
#                                                                        #
#  Modern CMake practices and importing the QT scripts by adding it to   #
#    your module path makes things a lot better than it used to be       #

MarcDiethelm

This text now lives at https://github.com/MarcDiethelm/contributing/blob/master/README.md. I turned it into a Github repo so you can, you know, contribute to it by making pull requests.

---

Contributing

If you want to contribute to a project and make it better, your help is very welcome. Contributing is also a great way to learn more about social coding on Github, new technologies and and their ecosystems and how to make constructive, helpful bug reports, feature requests and the noblest of all contributions: a good, clean pull request.

bluebanboom

#include <Python.h>
#include <stdio.h>
/*
 * gcc embpython.c -I/usr/include/python2.7 -lpython 
 **/
void loadModule()
{
    /* run objects with low-level calls */
    char *arg1="sir", *arg2="robin", *cstr;
    printf("Load Module err!\n");

filsinger

#include <regex>
#include <string>
#include <vector>

std::vector<std::string> Split(const std::string& str, const std::string& regex)
{
	return {std::sregex_token_iterator(str.begin(), str.end(), std::regex(regex), -1), std::sregex_token_iterator()};
}

MohamedAlaa

tmux shortcuts & cheatsheet

start new:

tmux

start new with session name:

tmux new -s myname