windows下创建vp9的VS版本

本文详细介绍如何在Windows环境下搭建WebM及VP9的编解码环境,包括下载并配置必要的组件如yasm、cygwin等,以及安装VP9的具体步骤。通过这些步骤,读者可以顺利地在自己的开发环境中实现WebM和VP9的编解码功能。

1. webm官网

 

下载版本:
创建过程这里有比较详细的英文说明:
懒得翻译的话就继续往下看吧。
 
2. yasm和cygwin
 
a. yasm
第一步, 按照需要下载所需yasm,32位或64位;VS的Microsoft Visual Studio x.0/VC/bin 在 Program Files (x86) 还是Program Files 中,前者放32bit就可以,后者放64bit,并将yasm的任意下载版本改名为yasm.exe。
第二步, 将yasm源文件中的yasm.rules放在Microsoft Visual Studio x.0/VC/VCProjectDefaults下。
附件,yasm.rules.
 
b. cygwin
安装过程参见:
第一次安装在windows下的童鞋,还要安装下make,如果不知道是哪些,就把所有带make的都选上吧,否则后面无法使用哦。
 
c. 另外如果需要安装文档,需要PHP和Doxygen
PHP下载地址:http://php.net/
Doxygen下载地址:http://www.doxygen.org/
 
3. vp9安装
 
a. 将vp9的安装包解压在某个目录下,如D:\test\vpx,并在D:\test下新建一个build目录,即D:\test\build;
b. 双击cygwin,进入所在目录
在命令行输入,
$ cd \cygdrive\d\build
$ ../vpx/configure --target=x86-win32-vs8 --enable-static-msvcrt --disable-install-docs
vs9---VS2008;
vs8----VS2005;
--disable-install-docs表示不安装文档;
注意:vpx下面也有一个build目录,所以不要进错了,是D:\test\build目录。
c. 配置正确后,命令行
$ make
命令行下显示内容不一定完全相同。
等待创建VS工程。
e. 编译VS工程
打开VS工程,在需要编译的项目右键Custom Build Rules,在弹出框里选择yasm,OK,编译就可以了。
 

先打开vs2013命令行:

在vs2013命令行中启动msys:
C:\Program Files\Microsoft Visual Studio 12.0\VC>c:\mingw\msys\1.0\msys.bat

进入libvpx源码根目录,建立build文件夹:

mkdir build

cd build

../configure --disable-shared --enable-static --enable-static-msvcrt  --disable-docs --disable-examples --target=x86-win32-vs17--prefix=D:\dev2\libvpx\slns

 

 

../configure --disable-shared --enable-static --enable-static-msvcrt  --disable-docs --disable-examples --target=x86-win32-vs17--prefix=/usr/local/msvc #配置用vs2013工程

参数说明:

--disable-shared --enable-static --enable-static-msvcrt :允许静态库

--target:生成指定的目标工程

make   #会自动用vs2013编译工具进行编译

 

 

 

 

转载于:https://www.cnblogs.com/endv/p/6866947.html

世界上最快的VP9视频解码器 As before , I was very excited when Google released VP9 – for one, because I was one of the people involved in creating it back when I worked for Google (I no longer do). How good is it, and how much better can it be? To evaluate that question, Clément Bœsch and I set out to write a VP9 decoder from scratch for FFmpeg. The goals never changed from the original ffvp8 situation (community-developed, fast, free from the beginning). We also wanted to answer new questions: how does a well-written decoder compare, speed-wise, with a well-written decoder for other codecs? TLDR (see rest of post for details): as a codec, VP9 is quite impressive – it beats x264 in many cases. However, the encoder is slow, very slow. At higher speed settings, the quality gain melts away. This seems to be similar to what people report about HEVC (using e.g. x265 as an encoder). single-threaded decoding speed of libvpx isn’t great. FFvp9 beats it by 25-50% on a variety of machines. FFvp9 is somewhat slower than ffvp8, and somewhat faster than ffh264 decoding speed (for files encoded to matching SSIM scores). Multi-threading performance in libvpx is deplorable, it gains virtually nothing from its loopfilter-mt algorithm. FFvp9 multi-threading gains nearly as much as ffh264/ffvp8 multithreading, but there’s a cap (material-, settings- and resolution-dependent, we found it to be around 3 threads in one of our clips although it’s typically higher) after which further threads don’t cause any more gain. The codec itself To start, we did some tests on the encoder itself. The direct goal here was to identify bitrates at which encodings would give matching SSIM-scores so we could do same-quality decoder performance measurements. However, as such, it also allows us to compare encoder performance in itself. We used settings very close to recommended settings forVP8,VP9andx264, optimized for SSIM as a metric. As source clips, we chose Sintel (1920×1080 CGI content, source ), a 2-minute clip from Tears of Steel (1920×800 cinematic content, source ), and a 3-minute clip from Enter the Void (1920×818 high-grain/noise content,screenshot). For each, we encoded at various bitrates and plotted effective bitrate versus SSIM . sintel_ssimtos_ssimetv_ssim You’ll notice that in most cases, VP9 can indeed beat x264, but, there’s some big caveats: VP9 encoding (using libvpx) is horrendously slow – like, 50x slower than VP8/x264 encoding. This means that encoding a 3-minute 1080p clip takes several days on a high-end machine. Higher –cpu-used=X parameters make the quality gains melt away. libvpx’ VP9 encodes miss the target bitrates by a long shot (100% off) for the ETV clip, possibly because of our use of –aq-mode=1. libvpx tends to slowly crumble at higher bitrates for hard content – again, look at the ETV clip, where x264 shows some serious mature killer instinct at the high bitrate end of things. Overall, these results are promising, although the lack-of-speed is a serious issue. Decoder performance For decoding performance measurements, we chose (Sintel)500 (VP9), 1200 (VP8) and 700 (x264) kbps (SSIM=19.8); Tears of Steel4.0 (VP9), 7.9 (VP8) and 6.3 (x264) mbps (SSIM=19.2); and Enter the Void 9.7 (VP9), 16.6 (VP8) and 10.7 (x264) mbps (SSIM=16.2). We used FFmpeg to decode each of these files, either using the built-in decoder (to compare between codecs), or using libvpx-vp9 (to compare ffvp9 versus libvpx). Decoding time was measured in seconds using “time ffmpeg -threads 1 [-c:v libvpx-vp9] -i $file -f null -v 0 -nostats – 2>&1 | grep user”, with this FFmpeg and this libvpx revision (downloaded on Feb 20th, 2014). sintel_archs tos_archsetv_archs A few notes on ffvp9 vs. libvpx-vp9 performance: ffvp9 beats libvpx consistently by 25-50%. In practice, this means that typical middle- to high-end hardware will be able to playback 4K content using ffvp9, but not using libvpx. Low-end hardware will struggle to playback even 720p content using libvpx (but do so fine using ffvp9). on Haswell, the difference is significantly smaller than on sandybridge, likely because libvpx has some AVX2 optimizations (e.g. for MC and loop filtering), whereas ffvp9 doesn’t have that yet; this means this difference might grow over time as ffvp9 gets AVX2 optimizations also. on the Atom, the differences are significantly smaller than on other systems; the reason for this is likely that we haven’t done any significant work on Atom-performance yet. Atom has unusually large latencies between GPRs and XMM registers, which means you need to take special care in ordering your instructions to prevent unnecessary halts – we haven’t done anything in that area yet (for ffvp9). Some users may find that ffvp9 is a lot slower than advertised on 32bit; this is correct, most of our SIMD only works on 64bit machines. If you have 32bit software, port it to 64bit. Can’t port it? Ditch it. Nobody owns 32bit x86 hardware anymore these days. So how does VP9 decoding performance compare to that of other codecs? There’s basically two ways to measure this: same-bitrate (e.g. a 500kbps VP8 file vs. a 500kbps VP9 file, where the VP9 file likely looks much better), or same-quality (e.g. a VP8 file with SSIM=19.2 vs. a VP9 file with SSIM=19.2, where the VP9 file likely has a much lower bitrate). We did same-quality measurements, and found: ffvp9 tends to beat ffh264 by a tiny bit (10%), except on Atom (which is likely because ffh264 has received more Atom-specific attention than ffvp9). ffvp9 tends to be quite a bit slower than ffvp8 (15%), although the massive bitrate differences in Enter the Void actually makes it win for that clip (by about 15%, except on Atom). Given that Google promised VP9 would be no more than 40% more complex than VP8, it seems they kept that promise. we did some same-bitrate comparisons, and found that x264 and ffvp9 are essentially identical in that scenario (with x264 having slightly lower SSIM scores); vp8 tends to be about 50% faster, but looks significantly worse. Multithreading One of the killer-features in FFmpeg is frame-level multithreading, which allows multiple cores to decode different video frames in parallel. Libvpx also supports multithreading. So which is better?
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