使用GPU硬件加速FFmpeg视频转码及排坑-创新互联
Author: dongdong
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本文内容包括:
- 在Linux环境下安装FFmpeg
- 通过命令行实现视频格式识别和转码
- 有Nvidia显卡的情况下,在Linux下使用GPU进行视频转码加速的方法
FFmpeg编译安装
在FFmpeg官网https://ffmpeg.org/download.html可以下载到ubunto/debian的发行包,其他Linux发行版需自行编译。同时,如果要使用GPU进行硬件加速的话,也是必须自己编译FFmpeg的,所以本节将介绍从源码编译安装FFmpeg的方法(基于RHEL/Centos)
安装依赖工具
yum install autoconf automake bzip2 cmake freetype-devel gcc gcc-c++ git libtool make mercurial pkgconfig zlib-devel
准备工作
在$HOME下创建ffmpeg_sources目录
我自己定义的HOME=/home/local/
编译并安装依赖库
本节中的依赖库基本都是必须的,建议全部安装
nasm
汇编编译器,编译某些依赖库的时候需要
cd /home/local/ffmpeg_sources
curl -O -L http://www.nasm.us/pub/nasm/releasebuilds/2.13.02/nasm-2.13.02.tar.bz2
tar xjvf nasm-2.13.02.tar.bz2
cd nasm-2.13.02
./autogen.sh
./configure --prefix="/home/local/ffmpeg_build" --bindir="/home/local/bin"
make
make install
yasm
汇编编译器,编译某些依赖库的时候需要
cd /home/local/ffmpeg_sources
curl -O -L http://www.tortall.net/projects/yasm/releases/yasm-1.3.0.tar.gz
tar xzvf yasm-1.3.0.tar.gz
cd yasm-1.3.0
./configure --prefix="/home/local/ffmpeg_build" --bindir="/home/local/bin"
make
make install
libx264
H.264视频编码器,如果需要输出H.264编码的视频就需要此库,所以可以说是必备
cd /home/local/ffmpeg_sources
git clone --depth 1 http://git.videolan.org/git/x264
cd x264
PKG_CONFIG_PATH="/home/local/ffmpeg_build/lib/pkgconfig" ./configure --prefix="/home/local/ffmpeg_build" --bindir="/home/local/bin" --enable-static
make
make install
libx265
H.265/HEVC视频编码器。
如果不需要此编码器,可以跳过,并在ffmpeg的configure命令中移除--enable-libx265
cd /home/local/ffmpeg_sources
hg clone https://bitbucket.org/multicoreware/x265
cd ~/ffmpeg_sources/x265/build/linux
cmake -G "Unix Makefiles" -DCMAKE_INSTALL_PREFIX="/home/local/ffmpeg_build" -DENABLE_SHARED:bool=off ../../source
make
make install
libfdk_acc
AAC音频编码器,必备
cd /home/local/ffmpeg_sources
git clone --depth 1 --branch v0.1.6 https://github.com/mstorsjo/fdk-aac.git
cd fdk-aac
autoreconf -fiv
./configure --prefix="/home/local/ffmpeg_build" --disable-shared
make
make install
libmp3lame
MP3音频编码器,必备
cd /home/local/ffmpeg_sources
curl -O -L http://downloads.sourceforge.net/project/lame/lame/3.100/lame-3.100.tar.gz
tar xzvf lame-3.100.tar.gz
cd lame-3.100
./configure --prefix="/home/local/ffmpeg_build" --bindir="/home/local/bin" --disable-shared --enable-nasm
make
make install
libops
OPUS音频编码器
如果不需要此编码器,可以跳过,并在ffmpeg的configure命令中移除--enable-libopus
cd /home/local/ffmpeg_sources
curl -O -L https://archive.mozilla.org/pub/opus/opus-1.2.1.tar.gz
tar xzvf opus-1.2.1.tar.gz
cd opus-1.2.1
./configure --prefix="/home/local/ffmpeg_build" --disable-shared
make
make install
libogg
被libvorbis依赖
cd /home/local/ffmpeg_sources
curl -O -L http://downloads.xiph.org/releases/ogg/libogg-1.3.3.tar.gz
tar xzvf libogg-1.3.3.tar.gz
cd libogg-1.3.3
./configure --prefix="/home/local/ffmpeg_build" --disable-shared
make
make install
libvorbis
Vorbis音频编码器
如果不需要此编码器,可以跳过,并在ffmpeg的configure命令中移除--enable-libvorbis
cd /home/local/ffmpeg_sources
curl -O -L http://downloads.xiph.org/releases/vorbis/libvorbis-1.3.5.tar.gz
tar xzvf libvorbis-1.3.5.tar.gz
cd libvorbis-1.3.5
./configure --prefix="/home/local/ffmpeg_build" --with-ogg="/home/local/ffmpeg_build" --disable-shared
make
make install
libvpx
VP8/VP9视频编/解码器
如果不需要此编/解码器,可以跳过,并在ffmpeg的configure命令中移除--enable-libvpx
cd /home/local/ffmpeg_sources
git clone --depth 1 https://github.com/webmproject/libvpx.git
cd libvpx
./configure --prefix="/home/local/ffmpeg_build" --disable-examples --disable-unit-tests --enable-vp9-highbitdepth --as=yasm
make
make install
编译安装ffmpeg 3.3.8
cd /home/local/ffmpeg_sources
curl -O -L https://ffmpeg.org/releases/ffmpeg-3.3.8.tar.bz2
tar xjvf ffmpeg-3.3.8.tar.bz2
cd ffmpeg-3.3.8
PATH="/home/local/ffmpeg_sources/bin:$PATH" PKG_CONFIG_PATH="/home/local/ffmpeg_sources/ffmpeg_build/lib/pkgconfig" ./configure --prefix="/home/local/ffmpeg_sources/ffmpeg_build" --pkg-config-flags="--static" --extra-cflags="-I /home/local/ffmpeg_sources/ffmpeg_build/include" --extra-ldflags="-L /home/local/ffmpeg_sources/ffmpeg_build/lib" --extra-libs=-lpthread --extra-libs=-lm --bindir="$HOME/bin" --enable-gpl --enable-libfdk_aac --enable-libfreetype --enable-libmp3lame --enable-libopus --enable-libvorbis --enable-libvpx --enable-libx264 --enable-libx265 --enable-nonfree --enable-libfreetype
make
make install
hash -r
验证安装
ffmpeg -h
使用FFmpeg
识别视频信息
通过ffprobe命令识别并输出视频信息
ffprobe -v error -show_streams -print_format json
为方便程序解析,将视频信息输出为json格式,样例如下:
{
"streams": [
{
"index": 0,
"codec_name": "h364",
"codec_long_name": "H.264 / AVC / MPEG-4 AVC / MPEG-4 part 10",
"profile": "High",
"codec_type": "video",
"codec_time_base": "61127/3668400",
"codec_tag_string": "avc1",
"codec_tag": "0x31637661",
"width": 1920,
"height": 1080,
"coded_width": 1920,
"coded_height": 1080,
"has_b_frames": 0,
"sample_aspect_ratio": "0:1",
"display_aspect_ratio": "0:1",
"pix_fmt": "yuv420p",
"level": 40,
"color_range": "tv",
"color_space": "bt709",
"color_transfer": "bt709",
"color_primaries": "bt709",
"chroma_location": "left",
"refs": 1,
"is_avc": "true",
"nal_length_size": "4",
"r_frame_rate": "30/1",
"avg_frame_rate": "1834200/61127",
"time_base": "1/600",
"start_pts": 0,
"start_time": "0.000000",
"duration_ts": 61127,
"duration": "101.878333",
"bit_rate": "16279946",
"bits_per_raw_sample": "8",
"nb_frames": "3057",
"disposition": {
"default": 1,
"dub": 0,
"original": 0,
"comment": 0,
"lyrics": 0,
"karaoke": 0,
"forced": 0,
"hearing_impaired": 0,
"visual_impaired": 0,
"clean_effects": 0,
"attached_pic": 0,
"timed_thumbnails": 0
},
"tags": {
"rotate": "90",
"creation_time": "2018-08-09T09:13:33.000000Z",
"language": "und",
"handler_name": "Core Media Data Handler",
"encoder": "H.264"
},
"side_data_list": [
{
"side_data_type": "Display Matrix",
"displaymatrix": "\n00000000: 0 65536 0\n00000001: -65536 0 0\n00000002: 70778880 0 1073741824\n",
"rotation": -90
}
]
},
{
"index": 1,
"codec_name": "aac",
"codec_long_name": "AAC (Advanced Audio Coding)",
"profile": "LC",
"codec_type": "audio",
"codec_time_base": "1/44100",
"codec_tag_string": "mp4a",
"codec_tag": "0x6134706d",
"sample_fmt": "fltp",
"sample_rate": "44100",
"channels": 1,
"channel_layout": "mono",
"bits_per_sample": 0,
"r_frame_rate": "0/0",
"avg_frame_rate": "0/0",
"time_base": "1/44100",
"start_pts": 0,
"start_time": "0.000000",
"duration_ts": 4492835,
"duration": "101.878345",
"bit_rate": "91595",
"max_bit_rate": "96000",
"nb_frames": "4390",
"disposition": {
"default": 1,
"dub": 0,
"original": 0,
"comment": 0,
"lyrics": 0,
"karaoke": 0,
"forced": 0,
"hearing_impaired": 0,
"visual_impaired": 0,
"clean_effects": 0,
"attached_pic": 0,
"timed_thumbnails": 0
},
"tags": {
"creation_time": "2018-08-09T09:13:33.000000Z",
"language": "und",
"handler_name": "Core Media Data Handler"
}
},
{
"index": 2,
"codec_type": "data",
"codec_tag_string": "mebx",
"codec_tag": "0x7862656d",
"r_frame_rate": "0/0",
"avg_frame_rate": "0/0",
"time_base": "1/600",
"start_pts": 0,
"start_time": "0.000000",
"duration_ts": 61127,
"duration": "101.878333",
"bit_rate": "119",
"nb_frames": "17",
"disposition": {
"default": 1,
"dub": 0,
"original": 0,
"comment": 0,
"lyrics": 0,
"karaoke": 0,
"forced": 0,
"hearing_impaired": 0,
"visual_impaired": 0,
"clean_effects": 0,
"attached_pic": 0,
"timed_thumbnails": 0
},
"tags": {
"creation_time": "2018-08-09T09:13:33.000000Z",
"language": "und",
"handler_name": "Core Media Data Handler"
}
},
{
"index": 3,
"codec_type": "data",
"codec_tag_string": "mebx",
"codec_tag": "0x7862656d",
"r_frame_rate": "0/0",
"avg_frame_rate": "0/0",
"time_base": "1/600",
"start_pts": 0,
"start_time": "0.000000",
"duration_ts": 61127,
"duration": "101.878333",
"nb_frames": "1",
"disposition": {
"default": 1,
"dub": 0,
"original": 0,
"comment": 0,
"lyrics": 0,
"karaoke": 0,
"forced": 0,
"hearing_impaired": 0,
"visual_impaired": 0,
"clean_effects": 0,
"attached_pic": 0,
"timed_thumbnails": 0
},
"tags": {
"creation_time": "2018-08-09T09:13:33.000000Z",
"language": "und",
"handler_name": "Core Media Data Handler"
}
}
]
}
可以看到一共返回了4个流,其中第0个是视频流,1是音频流,2和3是附加数据,没什么用
如果想指定分析视频流或音频流的话,可以加上参数-show_streams -v
或-show_streams -a
,这样就会只输出视频/音频流的分析结果
视频转码
ffmpeg -i -c:v libx264 -b:v 2048k -vf scale=1280:-1 -y
上述命令将输入视频转码为h364编码的视频
- -c:v:指定编码器,编码器列表可以使用ffmpeg -codecs查看
- -vf scale:指定输出视频的宽高,高-1代表按照比例自动适应
- -b:v:指定输出视频的码率,即输出视频每秒的bit数
- libx264支持的其他参数请使用
ffmpeg -h encoder=libx264
命令查询,如转码为其他编码,也可使用类似命令查询可用参数
使用Nvidia显卡GPU进行转码
重头戏来了,这块的资料相当少,我也是费了一番力气才搞定
CUDA
CUDA是Nvidia出的一个GPU计算库,让程序员可以驱动Nvidia显卡的GPU进行各种工作,其中就包含了视频的编解码
安装CUDA
首先验证一下显卡驱动是否装好
nvidia-smi
如果驱动正常的话,此命令会输出显卡的型号、驱动版本、现存/GPU占用等信息。如何安装显卡驱动本文不描述,请参考其他资料。
到CUDA官网https://developer.nvidia.com/cuda-downloads下载对应平台的发行包,这里我选择
wget http://developer.download.nvidia.com/compute/cuda/10.2/Prod/local_installers/cuda-repo-rhel7-10-2-local-10.2.89-440.33.01-1.0-1.x86_64.rpm
sudo rpm -i cuda-repo-rhel7-10-2-local-10.2.89-440.33.01-1.0-1.x86_64.rpm
sudo yum clean all
sudo yum -y install nvidia-driver-latest-dkms cuda
sudo yum -y install cuda-drivers
一共大概要安装90多个依赖库,注意一下安装完成后的报告,我首次安装时有一个库不知道为什么安装失败了,又单独yum install
了该库一次才成功
验证安装
/usr/local/cuda-9.2/bin/nvcc -V
安装成功的话,会输出类似文本:
nvcc: NVIDIA (R) Cuda compiler driver
Copyright (c) 2005-2018 NVIDIA Corporation
Built on Tue_Jun_12_23:07:04_CDT_2018
Cuda compilation tools, release 9.2, V9.2.148
重新编译ffmpeg
要让ffmpeg能够使用CUDA提供的GPU编解码器,必须重新编译ffmpeg,让其能够通过动态链接调用CUDA的能力
首先要编译安装nv-codec-headers库
git clone https://git.videolan.org/git/ffmpeg/nv-codec-headers.git
make PREFIX="/home/local/ffmpeg_build" BINDDIR="/home/local/bin"
make install PREFIX="/home/local/ffmpeg_build" BINDDIR="/home/local/bin"
进入/home/local/ffmepg_sources/ffmpeg-3.3.8/
目录重新执行ffmpeg的编译和安装
注意configure命令参数和之前configure命令参数的区别
PATH="/home/local/ffmpeg_sources/bin:$PATH" PKG_CONFIG_PATH="/home/local/ffmpeg_sources/ffmpeg_build/lib/pkgconfig" ./configure --prefix="/home/local/ffmpeg_sources/ffmpeg_build" --pkg-config-flags="--static" --extra-cflags="-I /home/local/ffmpeg_sources/ffmpeg_build/include -I/usr/local/cuda/include" --extra-ldflags="-L /home/local/ffmpeg_sources/ffmpeg_build/lib -L/usr/local/cuda/lib64" --extra-libs=-lpthread --extra-libs=-lm --bindir="$HOME/bin" --enable-gpl --enable-libfdk_aac --enable-libfreetype --enable-libmp3lame --enable-libopus --enable-libvorbis --enable-libvpx --enable-libx264 --enable-libx265 --enable-nonfree --enable-libfreetype --enable-cuda --enable-cuvid --enable-nvenc --enable-libnpp
验证安装
重新安装完ffmpeg,使用ffmpeg -hwaccels
命令查看支持的硬件加速选项
Hardware acceleration methods:
cuvid
可以看到多出来一种叫做cuvid的硬件加速选项,这就是CUDA提供的GPU视频编解码加速选项
然后查看cuvid提供的GPU编解码器ffmpeg -codecs | grep cuvid
DEV.LS h364 H.264 / AVC / MPEG-4 AVC / MPEG-4 part 10 (decoders: h364 h364_cuvid ) (encoders: libx264 libx264rgb h364_nvenc nvenc nvenc_h364 )
DEV.L. hevc H.265 / HEVC (High Efficiency Video Coding) (decoders: hevc hevc_cuvid ) (encoders: libx265 nvenc_hevc hevc_nvenc )
DEVIL. mjpeg Motion JPEG (decoders: mjpeg mjpeg_cuvid )
DEV.L. mpeg1video MPEG-1 video (decoders: mpeg1video mpeg1_cuvid )
DEV.L. mpeg2video MPEG-2 video (decoders: mpeg2video mpegvideo mpeg2_cuvid )
DEV.L. mpeg4 MPEG-4 part 2 (decoders: mpeg4 mpeg4_cuvid )
D.V.L. vc1 SMPTE VC-1 (decoders: vc1 vc1_cuvid )
DEV.L. vp8 On2 VP8 (decoders: vp8 libvpx vp8_cuvid ) (encoders: libvpx )
DEV.L. vp9 Google VP9 (decoders: vp9 libvpx-vp9 vp9_cuvid ) (encoders: libvpx-vp9 )
所有带有"cuvid"或"nvenc"的,都是CUDA提供的GPU编解码器
可以看到,我们现在可以进行h364/hevc/mjpeg/mpeg1/mpeg2/mpeg4/vc1/vp8/vp9格式的GPU解码,以及h364/hevc格式的GPU编码
使用GPU进行视频转码
用GPU进行转码的命令和软转码命令不太一样,CPU转码的时候,我们可以依赖ffmpeg识别输入视频的编码格式并选择对应的解码器,但ffmpeg只会自动选择CPU解码器,要让ffmpeg使用GPU解码器,必须先用ffprobe识别出输入视频的编码格式,然后在命令行中指定对应的GPU解码器。
例如,将h364编码的源视频转码为指定尺寸和码率的h364编码视频:
ffmpeg -hwaccel cuvid -c:v h364_cuvid -i -c:v h364_nvenc -b:v 2048k -vf scale_npp=1280:-1 -y
- -hwaccel cuvid:指定使用cuvid硬件加速
- -c:v h364_cuvid:使用h364_cuvid进行视频解码
- -c:v h364_nvenc:使用h364_nvenc进行视频编码
- -vf scale_npp=1280:-1:指定输出视频的宽高,注意,这里和软解码时使用的-vf scale=x:x不一样
转码期间使用nvidia-smi查看显卡状态,能够看到ffmpeg确实是在使用GPU进行转码:
+-----------------------------------------------------------------------------+
| Processes: GPU Memory |
| GPU PID Type Process name Usage |
|=============================================================================|
| 0 62543 C ffmpeg 193MiB |
+-----------------------------------------------------------------------------+
GPU转码效率测试
在配有两颗Intel-E5-2630v3 CPU和两块Nvidia Tesla M4显卡的服务器上,进行h364视频转码测试,成绩如下:
- GPU转码平均耗时:8s
- CPU转码平均耗时:25s
并行转码时,CPU软转的效率有所提高,3个转码任务并行时32颗核心全被占满,此时的成绩
- GPU转码平均耗时:8s
- CPU转码平均耗时:18s
不难看出,并行时GPU的转码速度并没有提高,可见一颗GPU同时只能执行一个转码任务。那么,如果服务器上插有多块显卡,ffmpeg是否会使用多颗GPU进行并行转码呢?
很遗憾,答案是否。
ffmpeg并不具备自动向不同GPU分配转码任务的能力,但经过一番调查后,发现可以通过-hwaccel_device参数指定转码任务使用的GPU!
向不同GPU提交转码任务
ffmpeg -hwaccel cuvid -hwaccel_device 0 -c:v h364_cuvid -i -c:v h364_nvenc -b:v 2048k -vf scale_npp=1280:-1 -y
- -hwaccel_device N:指定某颗GPU执行转码任务,N为数字
此时nvidia-smi显示:
+-----------------------------------------------------------------------------+
| Processes: GPU Memory |
| GPU PID Type Process name Usage |
|=============================================================================|
| 0 96931 C ffmpeg 193MiB |
| 1 96930 C ffmpeg 193MiB |
+-----------------------------------------------------------------------------+
可以进行并行GPU转码了!
那么在占满服务器资源时,GPU转码和CPU转码的效率如下:
- GPU转码平均耗时:4s
- CPU转码平均耗时:18s
GPU效率是CPU的4.5倍
排坑
一、错误: ./autogen.sh: 4: ./autogen.sh: autoreconf: not found
解决:yum -y install autoconf automake libtool
然后执行
二、 错误:ERROR: freetype2 not found using pkg-config
yum install -y bzip2
wget http://download.savannah.gnu.org/releases/freetype/freetype-2.10.0.tar.bz2
tar -jxvf freetype-2.10.0.tar.bz2
cd freetype-2.10.0
./configure --prefix= /home/local/ffmpeg_sources/ffmpeg_build
make
make install
三、错误: configure: error: C compiler cannot create executables See `config.log' for more details make: *** [setup] Error 77
解决:先卸载旧的c c++ gcc gcc++
然后重新安装
四、错误:make: *** [libavcodec/libfdk-aacenc.o] Error 1
因本身3.*带有BUG换成4.1 官网下载地址
(此步骤也可以使用git clone下载源码包,本质上是一样的 )
然后重新编译即可。
参考链接:https://www.jianshu.com/p/59da3d350488
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