I2P匿名网络使用扫盲

韩国|咪乐|直播ios 她说,当时是下午5时多点儿,爱人带着她骑着电动车从西向东行驶,这是回家的路,快到土门公交站的时候,一辆302中巴车进站停靠,把两人的电动车“挤”到了马路沿。

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Docker安装火狐/Chrome浏览器

  • 有啥用呢? 一般情况没啥用。
  • 如果在外网调整路由器设置,你需要安装vpn才能进入内网。
  • 现在通过这个,只要能进入群晖,开启下 该映像,以后就不用这么麻烦了。
  • 效果图 

应用实例

  • 有网友让我给他调群晖。我用群晖id登陆后台。
  • 然后发现问题出在路由器上,需要进入路由器管理台。 咋办呢?
  • 只能让他开电脑,用向日葵远程他电脑进行。
  • 但不能总开电脑吧,要远程好几天。这时候就需要这个用到这个功能了。
  • 远程他电脑的时候,设置好群晖浏览器的外网访问。然后他就可以关电脑了。
  • 需要远程的时候,就进入后台开启群晖浏览器。不用的时候就关上。

安装教程

通过官网安装

  • 安装教程:
    • 1. 打开 docker , 注册表内搜索“oldiy”,然后双击 “oldiy/chrome-novnc” 。等待下载中
    • 2. 下载完成后,在映像内可以看到该套件。双击创建该映像。
    • 3. 设置关键点如下:
    • 4. 访问。在浏览器中输入: http://192.168.10.111.cosmeticsurgeryasia.com:8083/vnc.html 。将192.168.10.111换成你群晖的IP.

直接导入镜像

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    黑群晖折腾记录

    黑群晖折腾记录。

    最近,权游第八季上映,下载好的资源,如何在众多播放设备:IPad、小米盒子、Android手机以及多台电脑之间共享成了一个问题。
    想到之前折腾过树莓派做过NAS,实现过文件共享,但受制性能,导致实用性不高,这次准备弄个X86迷你主机折腾黑群晖。

    出于实际需求和学习,运用所学知识开始折腾之旅。

    1.硬件篇

    先说说黑群晖的概念,黑群晖就是在普通主机上运行Synology DSM系统,对应的白群晖就是使用官方提供的主机运行Synology DSM系统,因此售卖主机成了Synology的主要收入来源。
    Synology两个盘位的服务器主机价格在1000元以上,只从硬件成本角度看,价格太高了,但Synology还有系统、软件成本,这个价位也可以理解。Synology对待盗版的举措有点像微软,用盗版先培养用户使用习惯,等市场占有率提高,用户成长起来,体会到存储安全的重要性,了解群晖正版产品的便利性后,逐步转为白群晖。

    1.1 硬件成本


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    DeOldify使用说明

    DeOldify

    Quick Start: The easiest way to colorize images using DeOldify (for free!) is here: DeOldify Image Colorization on DeepAI

    The most advanced version of DeOldify image colorization is available here, exclusively. Try a few images for free! MyHeritiage In Color


    Image (artistic)  | Video 

    NEW Having trouble with the default image colorizer, aka "artistic"? Try the "stable" one below. It generally won't produce colors that are as interesting as "artistic", but the glitches are noticeably reduced.

    Image (stable) 

    Instructions on how to use the Colabs above have been kindly provided in video tutorial form by Old Ireland in Colour's John Breslin. It's great! Click video image below to watch.

    Get more updates on Twitter .

    Table of Contents

    About DeOldify

    Simply put, the mission of this project is to colorize and restore old images and film footage. We'll get into the details in a bit, but first let's see some pretty pictures and videos!

    New and Exciting Stuff in DeOldify

    • Glitches and artifacts are almost entirely eliminated

    • Better skin (less zombies)

    • More highly detailed and photorealistic renders

    • Much less "blue bias"

    • Video - it actually looks good!

    • NoGAN - a new and weird but highly effective way to do GAN training for image to image.

    Example Videos

    Note: Click images to watch

    Facebook F8 Demo

    Silent Movie Examples

    Example Images

    "Migrant Mother" by Dorothea Lange (1936)

    Migrant Mother

    Woman relaxing in her livingroom in Sweden (1920)

    Sweden Living Room

    "Toffs and Toughs" by Jimmy Sime (1937)

    Class Divide

    Thanksgiving Maskers (1911)

    Thanksgiving Maskers

    Glen Echo Madame Careta Gypsy Camp in Maryland (1925)

    Gypsy Camp

    "Mr. and Mrs. Lemuel Smith and their younger children in their farm house, Carroll County, Georgia." (1941)

    Georgia Farmhouse

    "Building the Golden Gate Bridge" (est 1937)

    Golden Gate Bridge

    Note: What you might be wondering is while this render looks cool, are the colors accurate? The original photo certainly makes it look like the towers of the bridge could be white. We looked into this and it turns out the answer is no - the towers were already covered in red primer by this time. So that's something to keep in mind- historical accuracy remains a huge challenge!

    "Terrasse de café, Paris" (1925)

    Cafe Paris

    Norwegian Bride (est late 1890s)

    Norwegian Bride

    Zitkála-?á (Lakota: Red Bird), also known as Gertrude Simmons Bonnin (1898)

    Native Woman

    Chinese Opium Smokers (1880)

    Opium Real

    Stuff That Should Probably Be In A Paper

    How to Achieve Stable Video

    NoGAN training is crucial to getting the kind of stable and colorful images seen in this iteration of DeOldify. NoGAN training combines the benefits of GAN training (wonderful colorization) while eliminating the nasty side effects (like flickering objects in video). Believe it or not, video is rendered using isolated image generation without any sort of temporal modeling tacked on. The process performs 30-60 minutes of the GAN portion of "NoGAN" training, using 1% to 3% of imagenet data once. Then, as with still image colorization, we "DeOldify" individual frames before rebuilding the video.

    In addition to improved video stability, there is an interesting thing going on here worth mentioning. It turns out the models I run, even different ones and with different training structures, keep arriving at more or less the same solution. That's even the case for the colorization of things you may think would be arbitrary and unknowable, like the color of clothing, cars, and even special effects (as seen in "Metropolis").

    Metropolis Special FX

    My best guess is that the models are learning some interesting rules about how to colorize based on subtle cues present in the black and white images that I certainly wouldn't expect to exist. This result leads to nicely deterministic and consistent results, and that means you don't have track model colorization decisions because they're not arbitrary. Additionally, they seem remarkably robust so that even in moving scenes the renders are very consistent.

    Moving Scene Example

    Other ways to stabilize video add up as well. First, generally speaking rendering at a higher resolution (higher render_factor) will increase stability of colorization decisions. This stands to reason because the model has higher fidelity image information to work with and will have a greater chance of making the "right" decision consistently. Closely related to this is the use of resnet101 instead of resnet34 as the backbone of the generator- objects are detected more consistently and correctly with this. This is especially important for getting good, consistent skin rendering. It can be particularly visually jarring if you wind up with "zombie hands", for example.

    Zombie Hand Example

    Additionally, gaussian noise augmentation during training appears to help but at this point the conclusions as to just how much are bit more tenuous (I just haven't formally measured this yet). This is loosely based on work done in style transfer video, described here: https://medium.com/element-ai-research-lab/stabilizing-neural-style-transfer-for-video-62675e203e42.

    Special thanks go to Rani Horev for his contributions in implementing this noise augmentation.

    What is NoGAN?

    This is a new type of GAN training that I've developed to solve some key problems in the previous DeOldify model. It provides the benefits of GAN training while spending minimal time doing direct GAN training. Instead, most of the training time is spent pretraining the generator and critic separately with more straight-forward, fast and reliable conventional methods. A key insight here is that those more "conventional" methods generally get you most of the results you need, and that GANs can be used to close the gap on realism. During the very short amount of actual GAN training the generator not only gets the full realistic colorization capabilities that used to take days of progressively resized GAN training, but it also doesn't accrue nearly as much of the artifacts and other ugly baggage of GANs. In fact, you can pretty much eliminate glitches and artifacts almost entirely depending on your approach. As far as I know this is a new technique. And it's incredibly effective.


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    AI老照片修复

    GitHub地址:https://github.com/jantic/DeOldify/blob/master/README.md上色体验地址:https://colorize.cc/

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    2017黑帽大会兵工厂工具列表

     Android, iOS and Mobile HackingAndroid Tamerhttps://github.com/AndroidTamerTwitter: @AndroidTamer ?Presenter: Anant Shrivastava (@anantshri)BadIntent?—?Integrating Android with Burphttps://github.com/mateuszk87/BadIntentPres

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    极客DIY:如何构建一台属于自己的基站

    5.jpg

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    极客DIY:打造属于自己的无线移动渗透测试箱

    本文中介绍的工具、技术带有一定的攻击性,请合理合法使用。

    你想不想拥有一款属于自己的移动无线渗透测试箱,如果你感兴趣,下面介绍的设备将会对你很有帮助。这个箱子被称为“MiTM(中间人攻击)WiFi箱”,使用这个箱子可以完成一些无线审计工作,同时也可以伪造接入点并完成中间人攻击。

    工具要求

    如果你真的想要做这个箱子那么你需要如下工具:

    5或6mm的钻木/金属钻头
    开口扳手(规格8)
    钳子
    手术刀/裁纸刀
    尼龙扎带(俗称:勒死狗)

    箱子的选择

    这里有些建议,你选中的箱子最好是用过一次以上,另外需要注意的是一定不要选择扔掉设备之后留下的那种空箱子。

    箱子要求

    最好是黑色的

    尺寸大约是230 x 150 x 100mm

    必须是防水的(可以经受的起风吹日晒)

    价格自选


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    如何监听无线键盘

    前一段时间,我需要一个新的无线键盘,我选择了一个128bit AES无线加密接口的。但同时我很好奇,如果使用老款的无线键盘是否不安全?为了研究这个问题,我特地买了台2000年7月出产的罗技iTouch PS/2无线键盘,在那时候,无线台式机使用的还是27 MHz的SW波段,而现在的产品大多已转移到2.4 GHz。与现在的USB无线网卡相比,iTouch的无线接收器是巨大的,它并不是一个芯片而是包含了 PCB、多个晶体的振荡器和ICS解码器,根据谷歌搜索结果的摩托罗拉芯片,一个是FM接收

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    使用USRP探索无线世界 Part 1:USRP从入门到追踪飞机飞行轨迹

    0x00 前言


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