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Twitter 放出來的 Vireo,一套 Open Source 授權的 Video Processing Library

Twitter 放出 Vireo,一套以 MIT License 釋出的 Video Processing Library:「Introducing Vireo: A Lightweight and Versatile Video Processing Library」。專案庫在 GitHubtwitter/vireo 可以取得。

C++ 寫的,另外也已經提供 Scala 的接口,這應該是讓 Twitter 的人可以方便使用:

Vireo is a lightweight and versatile video processing library that powers our video transcoding service, deep learning recognition systems and more. It is written in C++11 and built with functional programming principles. It also optionally comes with Scala wrappers that enable us to build scalable video processing applications within our backend services.

在 Tools 的部份也可以看到很多功能,像是:

thumbnails: extracts keyframes from the input video and saves them as JPG images

viddiff: checks if two video files are functionally identical or not (does not compare data that does not affect the playback behavior)

另外要注意的是,預設不會將 GPL 的套件納入編譯,需要指定 --enable-gpl 才會編進去:

The following libraries are disabled by default. To enable GPL licensed components, they have to be present in your system and --enable-gpl flag have to be explicitly passed to configure

看起來主要就是最常見的那包... (libavformat / libavcodec / libavutil / libswscale / libx264)

AlphaGo 不是使用 GPU 加速...

Google 今天公佈的資料中說明了 AlphaGo 不是用一般常見的 GPU 加速運算:「Google supercharges machine learning tasks with TPU custom chip」。

這是特別為 TensorFlow 製作的 ASIC:

The result is called a Tensor Processing Unit (TPU), a custom ASIC we built specifically for machine learning — and tailored for TensorFlow.

而 AlphaGo 用的版本是 TPU 版:

AlphaGo was powered by TPUs in the matches against Go world champion, Lee Sedol, enabling it to "think" much faster and look farther ahead between moves.

放 AlphaGo 的機櫃長這樣:

通常 ASIC 特製的版本會比 FPGA 或是 GPU 快上許多,這代表目前這些沒有大公司撐腰的圍棋軟體要跟 AlphaGo 拼,除非演算法上有重大的突破,不然就得用更大量的設備跟他換...


Lyst 的「Image Background Removal」這篇在講圖片去背的方法。

Lyst 是把這個演算法用在上架自動分類的一環:圖片先去背,然後再用 classifier 綜合其他的 metadata 判斷要分到那一類。


其實 Lyst 這篇是在說「要怎麼打組合拳」:利用現有最簡單的技術去堆積木,想辦法找出一套合理的解。而不是像學術上的那樣要求做到極致。所以也有像這樣不是處理的很好的: