我正在尝试按照以下说明使用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，得到以下输出：
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 #0:0[0x1](und): 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 #0:1[0x2](und): 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 #0:2[0x3](und): 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!nvidia-smi的输出：
+-----------------------------------------------------------------------------+
| NVIDIA-SMI 525.85.05 Driver Version: 525.85.05 CUDA Version: 12.0 |
|-------------------------------+----------------------+----------------------+
| GPU Name Persistence-M| Bus-Id Disp.A | Volatile Uncorr. ECC |
| Fan Temp Perf Pwr:Usage/Cap| Memory-Usage | GPU-Util Compute M. |
| | | MIG M. |
|===============================+======================+======================|
| 0 NVIDIA GeForce ... Off | 00000000:01:00.0 On | N/A |
| 27% 43C P8 12W / 250W | 500MiB / 11264MiB | 1% Default |
| | | N/A |
+-------------------------------+----------------------+----------------------+
+-----------------------------------------------------------------------------+
| Processes: |
| GPU GI CI PID Type Process name GPU Memory |
| ID ID Usage |
|=============================================================================|
+-----------------------------------------------------------------------------+共享库不是docker镜像的一部分。我有什么选项可以添加它们？
1条答案
按热度按时间mu0hgdu01#
检查您的nvidia-container-runtime参数。对于NVENC，您需要启用
video功能。docker运行示例：在docker-compose.yml中，deploy/resources/reservations/devices/capabilities下必须包含值
video：Empty（或者只有gpu值）将无法链接NVENC，导致上面的错误。我认为特权模式也会启用所有gpu功能。默认的apt pre-build ffmpeg ubunutu包确实可以与NVENC一起使用，但在docker中需要相同的功能步骤。否则，您会得到此错误：
有关详细信息，请参见https://github.com/NVIDIA/nvidia-container-runtime。