2023年3月7日 19:11:03go评论135阅读模式

英文:

Building FFmpeg with NVIDIA GPU Hardware Acceleration in docker image, cannot load libnvcuvid.so.1 and libnvidia-encode.so.1

问题

我正在尝试按照这些说明使用NVIDIA GPU硬件加速构建FFmpeg：https://docs.nvidia.com/video-technologies/video-codec-sdk/ffmpeg-with-nvidia-gpu/index.html#compiling-for-linux。我正在使用的Docker镜像是nvidia/cuda:12.0.1-devel-ubuntu20.04

运行测试命令ffmpeg -y -vsync 0 -hwaccel cuda -hwaccel_output_format cuda -i bbb.mp4 -c:a copy -c:v h264_nvenc -b:v 5M output.mp4，我得到以下输出：

ffmpeg版本 N-109965-ge50a02b0f6 版权所有 (c) 2000-2023年FFmpeg开发人员
  使用gcc 9构建（Ubuntu 9.4.0-1ubuntu1~20.04.1）
  配置：--enable-nonfree --enable-cuda-nvcc --enable-libnpp --extra-cflags=-I/usr/local/cuda/include --extra-ldflags=-L/usr/local/cuda/lib64 --disable-static --enable-shared
  libavutil      58.  3.100 / 58.  3.100
  libavcodec     60.  6.100 / 60.  6.100
  libavformat    60.  4.100 / 60.  4.100
  libavdevice    60.  2.100 / 60.  2.100
  libavfilter     9.  4.100 /  9.  4.100
  libswscale      7.  2.100 /  7.  2.100
  libswresample   4. 11.100 /  4. 11.100
-vsync已被弃用。使用-fps_mode
将数字传递给-vsync已被弃用，使用手册中描述的字符串参数。
输入＃0，mov，mp4，m4a，3gp，3g2，mj2，来自'bbb.mp4'：
  元数据：
    major_brand     : isom
    minor_version   : 1
    compatible_brands: isomavc1
    creation_time   : 2013-12-16T17:44:39.000000Z
    title           : Big Buck Bunny, Sunflower version
    artist          : Blender Foundation 2008, Janus Bager Kristensen 2013
    comment         : Creative Commons Attribution 3.0 - http://bbb3d.renderfarming.net
    genre           : Animation
    composer        : Sacha Goedegebure
  时长：00:10:34.60，开始：0.000000，比特率：3481 kb/s
  流＃0:0[0x1](und)：视频：h264（High）（avc1 / 0x31637661），yuv420p（渐进式），1920x1080 [SAR 1:1 DAR 16:9]，2998 kb/s，30 fps，30 tbr，30k tbn（默认）
    元数据：
      creation_time   : 2013-12-16T17:44:39.000000Z
      handler_name    : GPAC ISO Video Handler
      vendor_id       : [0][0][0][0]
  流＃0:1[0x2](und)：音频：mp3（mp4a / 0x6134706D），48000 Hz，立体声，fltp，160 kb/s（默认）
    元数据：
      creation_time   : 2013-12-16T17:44:42.000000Z
      handler_name    : GPAC ISO Audio Handler
      vendor_id       : [0][0][0][0]
  流＃0:2[0x3](und)：音频：ac3（ac-3 / 0x332D6361），48000 Hz，5.1（side），fltp，320 kb/s（默认）
    元数据：
      creation_time   : 2013-12-16T17:44:42.000000Z
      handler_name    : GPAC ISO Audio Handler
      vendor_id       : [0][0][0][0]
    附加数据：
      音频服务类型：主要
流映射：
  流＃0:0 -&gt; #0:0（h264（本机） -&gt; h264（h264_nvenc））
  流＃0:2 -&gt; #0:1（复制）
按[q]停止，[?]以获取帮助
[h264 @ 0x55bd878c2d80] 无法加载libnvcuvid.so.1
[h264 @ 0x55bd878c2d80] 加载nvcuvid失败。
[h264 @ 0x55bd878c2d80] cuda格式的hwaccel初始化返回错误。
[h264_nvenc @ 0x55bd86f5e680] 无法加载libnvidia-encode.so.1
[h264_nvenc @ 0x55bd86f5e680] nvenc所需的最低Nvidia驱动程序为520.56.06或更高
[vost#0:0/h264_nvenc @ 0x55bd86f5e1c0] 初始化输出流时发生错误：打开输出流＃0:0的编码器时出现错误，可能是比特率、速率、宽度或高度等参数不正确
转换失败！

nvidia-smi的输出：

+-----------------------------------------------------------------------------+
| NVIDIA-SMI 525.85.05    驱动程序版本: 525.85.05    CUDA版本: 12.0     |
|-------------------------------+----------------------+----------------------+
| GPU  名称          持续性-M | 总线-ID        Disp.A | 不稳定的ECC错误 |
| 风扇 温度  性能  功耗:使用/Cap |         内存使用  | GPU-Util  Compute M. |
|                               |                      |               MIG M. |
|===============================+======================+======================|
|   0  NVIDIA GeForce ...  关闭  | 00000000:01:00.0  开启 |                  N/A |
| 27%   43摄氏度   P8    12瓦 / 250瓦 |    500兆字节 / 11264兆字节 |      1%      默认 |
|                              

<details>
<summary>英文:</summary>

I&#39;m trying to build FFmpeg with NVIDIA GPU Hardware Acceleration following these instructions: https://docs.nvidia.com/video-technologies/video-codec-sdk/ffmpeg-with-nvidia-gpu/index.html#compiling-for-linux.  The Docker image I&#39;m using is `nvidia/cuda:12.0.1-devel-ubuntu20.04`

Running the test command `ffmpeg -y -vsync 0 -hwaccel cuda -hwaccel_output_format cuda -i bbb.mp4 -c:a copy -c:v h264_nvenc -b:v 5M output.mp4`, I get the following output:

ffmpeg version N-109965-ge50a02b0f6 Copyright (c) 2000-2023 the FFmpeg developers
built with gcc 9 (Ubuntu 9.4.0-1ubuntu1~20.04.1)
configuration: --enable-nonfree --enable-cuda-nvcc --enable-libnpp --extra-cflags=-I/usr/local/cuda/include --extra-ldflags=-L/usr/local/cuda/lib64 --disable-static --enable-shared
libavutil 58. 3.100 / 58. 3.100
libavcodec 60. 6.100 / 60. 6.100
libavformat 60. 4.100 / 60. 4.100
libavdevice 60. 2.100 / 60. 2.100
libavfilter 9. 4.100 / 9. 4.100
libswscale 7. 2.100 / 7. 2.100
libswresample 4. 11.100 / 4. 11.100
-vsync is deprecated. Use -fps_mode
Passing a number to -vsync is deprecated, use a string argument as described in the manual.
Input #0, mov,mp4,m4a,3gp,3g2,mj2, from 'bbb.mp4':
Metadata:
major_brand : isom
minor_version : 1
compatible_brands: isomavc1
creation_time : 2013-12-16T17:44:39.000000Z
title : Big Buck Bunny, Sunflower version
artist : Blender Foundation 2008, Janus Bager Kristensen 2013
comment : Creative Commons Attribution 3.0 - http://bbb3d.renderfarming.net
genre : Animation
composer : Sacha Goedegebure
Duration: 00:10:34.60, start: 0.000000, bitrate: 3481 kb/s
Stream #0:00x1: Video: h264 (High) (avc1 / 0x31637661), yuv420p(progressive), 1920x1080 [SAR 1:1 DAR 16:9], 2998 kb/s, 30 fps, 30 tbr, 30k tbn (default)
Metadata:
creation_time : 2013-12-16T17:44:39.000000Z
handler_name : GPAC ISO Video Handler
vendor_id : [0][0][0][0]
Stream #0:10x2: Audio: mp3 (mp4a / 0x6134706D), 48000 Hz, stereo, fltp, 160 kb/s (default)
Metadata:
creation_time : 2013-12-16T17:44:42.000000Z
handler_name : GPAC ISO Audio Handler
vendor_id : [0][0][0][0]
Stream #0:20x3: Audio: ac3 (ac-3 / 0x332D6361), 48000 Hz, 5.1(side), fltp, 320 kb/s (default)
Metadata:
creation_time : 2013-12-16T17:44:42.000000Z
handler_name : GPAC ISO Audio Handler
vendor_id : [0][0][0][0]
Side data:
audio service type: main
Stream mapping:
Stream #0:0 -> #0:0 (h264 (native) -> h264 (h264_nvenc))
Stream #0:2 -> #0:1 (copy)
Press [q] to stop, [?] for help
[h264 @ 0x55bd878c2d80] Cannot load libnvcuvid.so.1
[h264 @ 0x55bd878c2d80] Failed loading nvcuvid.
[h264 @ 0x55bd878c2d80] Failed setup for format cuda: hwaccel initialisation returned error.
[h264_nvenc @ 0x55bd86f5e680] Cannot load libnvidia-encode.so.1
[h264_nvenc @ 0x55bd86f5e680] The minimum required Nvidia driver for nvenc is 520.56.06 or newer
[vost#0:0/h264_nvenc @ 0x55bd86f5e1c0] Error initializing output stream: Error while opening encoder for output stream #0:0 - maybe incorrect parameters such as bit_rate, rate, width or height
Conversion failed!

Output from `nvidia-smi`:

+-----------------------------------------------------------------------------+
| Processes: |
| GPU GI CI PID Type Process name GPU Memory |
| ID ID Usage |
|=============================================================================|
+-----------------------------------------------------------------------------+

The shared libraries are not part of the docker image.  What are my options to add them?

</details>


# 答案1
**得分**: 3

检查您的nvidia-container-runtime参数。对于NVENC，您需要启用```video```功能。示例docker运行命令如下：

docker run --gpu all,capabilities=video -it nvidia/cuda:12.0.1-devel-ubuntu20.04 /bin/bash


在docker-compose.yml中，在`deploy/resources/reservations/devices/capabilities`下必须包括值```video```：

version: '2.2'
services:
name_of_your_service:
deploy:
resources:
reservations:
devices:
- driver: nvidia
device_ids: ['0']
capabilities: [gpu,video]


空（或仅包含值gpu）将不会链接NVENC，从而导致上述错误。我认为特权模式也将启用所有GPU功能。默认的apt预构建的ffmpeg ubuntu包在NVENC上可以工作，但在docker中需要进行与功能相关的相同步骤。否则，您将会遇到以下错误：

Cannot load libnvidia-encode.so.1
The minimum required Nvidia driver for nvenc is 470.57.02 or newer
Error initializing output stream 0:0 -- Error while opening encoder for output stream #0:0 - maybe incorrect parameters such as bit_rate, rate, width or height


请参阅https://github.com/NVIDIA/nvidia-container-runtime以获取更多信息。

<details>
<summary>英文:</summary>

Check your nvidia-container-runtime parameters. For NVENC you need to enable the ```video``` capability. Example for docker run:

    docker run --gpu all,capabilities=video -it nvidia/cuda:12.0.1-devel-ubuntu20.04 /bin/bash

In docker-compose.yml under your deploy/resources/reservations/devices/capabilities must include the value ```video```:

    version: &#39;2.2&#39;
    services:
      name_of_your_service:
        deploy:
          resources:
            reservations:
              devices:
                - driver: nvidia
                  device_ids: [&#39;0&#39;]
                  capabilities: [gpu,video]

Empty (or only the value gpu) will NOT link NVENC resulting in the error above. I think privileged mode will also enable all gpu capabilities. The default apt pre-build ffmpeg ubunutu package does work with NVENC but the same steps regarding capabilities are needed in docker. Otherwise you get this error:

    Cannot load libnvidia-encode.so.1
    The minimum required Nvidia driver for nvenc is 470.57.02 or newer
    Error initializing output stream 0:0 -- Error while opening encoder for output stream #0:0 - maybe incorrect parameters such as bit_rate, rate, width or height

See https://github.com/NVIDIA/nvidia-container-runtime for more info.

</details>

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Building FFmpeg with NVIDIA GPU Hardware Acceleration in docker image, cannot load libnvcuvid.so.1 and libnvidia-encode.so.1

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