Start up a container (whichever Linux flavour takes your fancy):
docker run -it ubuntu /bin/bash
docker run -it centos /bin/bash
#include <stdio.h> | |
// | |
// Nearly minimal CUDA example. | |
// Compile with: | |
// | |
// nvcc -o example example.cu | |
// | |
#define N 1000 |
OS=`echo \`uname\` | tr '[:upper:]' '[:lower:]'` | |
AURL="https://gist.githubusercontent.com/hightemp/5071909/raw/" | |
ANAME=".bash_aliases" | |
TMPAPATH="/tmp/$ANAME" | |
HOMEAPATH="~/$ANAME" | |
[ "$OS" = "windowsnt" ] && OS_WIN="yes" | |
[ "$OS" = "darwin" ] && OS_MAC="yes" | |
[ "$OS" = "linux" ] && OS_LIN="yes" |
import requests | |
import logging | |
import httplib | |
# Debug logging | |
httplib.HTTPConnection.debuglevel = 1 | |
logging.basicConfig() | |
logging.getLogger().setLevel(logging.DEBUG) | |
req_log = logging.getLogger('requests.packages.urllib3') | |
req_log.setLevel(logging.DEBUG) |
First of all, we are going to store all the data in a Docker shared volume, called openvpn_data
.
To initialise the OpenVPN configuration and CA:
$ docker run -v openvpn_data:/etc/openvpn --rm evolvedm/openvpn-rpi ovpn_genconfig -u udp://your-vpn.address.com
$ docker run -v openvpn_data:/etc/openvpn --rm -it evolvedm/openvpn-rpi ovpn_initpki
To start daemon (and auto-restart it):
from __future__ import print_function | |
import requests | |
import json | |
import cv2 | |
addr = 'http://localhost:5000' | |
test_url = addr + '/api/test' | |
# prepare headers for http request | |
content_type = 'image/jpeg' |
#!/usr/bin/env bash | |
git branch -r | grep -v '\->' | while read remote; do git branch --track "${remote#origin/}" "$remote"; done | |
git fetch --all | |
git pull --all |
{ | |
"categories": [ | |
{ | |
"name": "Movies", | |
"videos": [ | |
{ | |
"description": "Big Buck Bunny tells the story of a giant rabbit with a heart bigger than himself. When one sunny day three rodents rudely harass him, something snaps... and the rabbit ain't no bunny anymore! In the typical cartoon tradition he prepares the nasty rodents a comical revenge.\n\nLicensed under the Creative Commons Attribution license\nhttp://www.bigbuckbunny.org", | |
"sources": [ | |
"http://commondatastorage.googleapis.com/gtv-videos-bucket/sample/BigBuckBunny.mp4" | |
], |
# This is an example of using | |
# https://github.com/tensorflow/models/blob/master/research/object_detection/dataset_tools/create_pascal_tf_record.py | |
# The structure should be like PASCAL VOC format dataset | |
# +Dataset | |
# +Annotations | |
# +JPEGImages | |
# python create_tfrecords_from_xml.py --image_dir=dataset/JPEGImages | |
# --annotations_dir=dataset/Annotations | |
# --label_map_path=object-detection.pbtxt | |
# --output_path=data.record |
import 'package:flutter/material.dart'; | |
import 'dart:ui' as ui; | |
import 'package:flutter/services.dart' show rootBundle; | |
import 'dart:async'; | |
import 'dart:typed_data'; | |
void main() => runApp(new MyApp()); | |
class MyApp extends StatelessWidget { | |
// This widget is the root of your application. |