| /* | |
| * tiny_IRremote | |
| * Version 0.2 July, 2016 | |
| * Christian D'Abrera | |
| * Fixed what was originally rather broken code from http://www.gammon.com.au/Arduino/ | |
| * ...itself based on work by Ken Shirriff. | |
| * | |
| * This code was tested for both sending and receiving IR on an ATtiny85 DIP-8 chip. | |
| * IMPORTANT: IRsend only works from PB4 ("pin 4" according to Arduino). You will need to | |
| * determine which physical pin this corresponds to for your chip, and connect your transmitter |
この投稿では、iOSのファイルシステムについて理解し、データを永続化(iCloud含む)する方法を紹介する。尚、サンプルコードは動かない可能性もあるので参考程度にして下さい。
アプリがファイルシステムとやり取り出来る場所は、ほぼアプリのサンドボックス内のディレクトリに制限されている。新しいアプリがインストールされる際、インストーラーはサンドボックス内に複数のコンテナを作成し、図1に示す構成をとる。各コンテナには役割があり、Bundle Containerはアプリのバンドルを保持し、Data Containerはアプリとユーザ両方のデータを保持する。Data Containerは用途毎に、さらに複数のディレクトリに分けられる。アプリは、例えばiCloud Containerのように、実行時に追加のコンテナへのアクセスをリクエストすることもある。
図1. An iOS app operating within its own sandbox
#neural-style with Cuda7.5 + cuDNN5 in EC2
if you want to skip installing nvidia driver and cuda7.5,
use this Ubuntu 14 AMI.
https://aws.amazon.com/marketplace/pp/B01EYKBEQ0
(Nvidia Drivers, Cuda 7.5 Toolkit, cuDNN pre-installed with Nvidia Drivers, Cuda 7.5 Toolkit, cuDNN 4, TensorFlow, and Jupyter to leverage Nvidia GRID instances)
g2.2xlarge or better (GPU instance)
Don't forget to make your root partition size bigger.
In case you want to install everything by yourself
| /* | |
| * Read video frame with FFmpeg and convert to OpenCV image | |
| * | |
| * Copyright (c) 2016 yohhoy | |
| */ | |
| #include <iostream> | |
| #include <vector> | |
| // FFmpeg | |
| extern "C" { | |
| #include <libavformat/avformat.h> |
| public class UVWorld : MonoBehaviour { | |
| Mesh _mesh; | |
| Vector3[] _vertices; | |
| int[] _triangles; | |
| Vector2[] _uvs; | |
| Vector3[] _normals; | |
| Triangle2D[] _uvTris; | |
| void Awake() { | |
| _mesh = GetComponent<MeshFilter>().sharedMesh; |
| #!/bin/bash | |
| apt-get -y update | |
| apt-get -y install nginx-extras build-essential libpcre3-dev libssl-dev libgeoip-dev libpq-dev libxslt1-dev libgd2-xpm-dev | |
| wget -c https://openresty.org/download/openresty-1.13.6.2.tar.gz | |
| tar zxvf openresty-1.13.6.2.tar.gz | |
| cd openresty-1.13.6.2 | |
| ./configure \ | |
| --sbin-path=/usr/sbin/nginx \ | |
| --conf-path=/etc/nginx/nginx.conf \ |
| # IMPORTANT: make sure no animation is assigned | |
| # to the rig before you run this script, | |
| # otherwise linked animation data will be corrupted. | |
| import bpy | |
| # ---------------------------------- | |
| # Mixamo left/right bone names start with 'Left'/'Right' | |
| # Instead we apply Blender's standard .L/.R suffix | |
| # and get rid of long suffix |
The following instructions are for creating your own animations using the style transfer technique described by Gatys, Ecker, and Bethge, and implemented by Justin Johnson. To see an example of such an animation, see this video of Alice in Wonderland re-styled by 17 paintings.
The easiest way to set up the environment is to simply load Samim's a pre-built Terminal.com snap or use another cloud service like Amazon EC2. Unfortunately the g2.2xlarge GPU instances cost $0.99 per hour, and depending on parameters selected, it may take 10-15 minutes to produce a 512px-wide image, so it can cost $2-3 to generate 1 sec of video at 12fps.
If you do load the
| import cairo,argparse,random | |
| #TEST: https://jcmellado.github.io/js-aruco/getusermedia/getusermedia.html | |
| #http://terpconnect.umd.edu/~jwelsh12/enes100/markergen.html | |
| #http://terpconnect.umd.edu/~jwelsh12/enes100/markers.js | |
| markers_opts = [[False,True,True,True,True],[False,True,False,False,False] | |
| ,[True,False,True,True,False],[True,False,False,False,True]]; | |
| import string | |
| digs = string.digits + string.letters |
