Recherche avancée

Sur d’autres sites (9752)

• Stuck in deadend while compiling ffmpeg with nvidia CUDA support on Ubuntu 18.04 and GeForce GT 730

  24 février 2019, par Marko

  I want to compile ffmpeg with CUDA support, on Ubuntu 18.04, and my graphics card is GeForce GT 730 (so far I have not CUDA programming experience).
  Here nvidia claims that it has at least some transcoding support.

  I have cloned https://git.ffmpeg.org/ffmpeg.git and as I understand I also need to build and install nv-codec-headers.

  But there in the README, they say that minimum driver version for Linux is 418.30 or newer. So I went to nvidia site to download driver and after selecting my card I got this download link. So the driver version is high enough it seems. But when I try to install it I get message that this device will be ignored by that driver and that it is supported by legacy driver 390.xx (which is version I can install with apt).
  Is something wrong with nVidia, why are they offering me driver that is cannot be used for this device ?

  I’ve installed 390.xx driver using ubuntu-drivers autoinstall and built ffmpeg, but when I try to run it I get this error : Cannot load cuvidGetDecodeStatus [h264_cuvid @ 0x562a86dbc680] Failed loading nvcuvid.

  I suppose it is because of driver ?

  So, what can I do to unstuck myself ?

• NVIDIA Version Outdated Error when mine is updated

  21 février 2021, par Agent Merlot

  I'm trying to encode stuff with my NVIDIA GeForce MX150 (Driver Version : 461.09).

  


  import os
os.system(f'ffmpeg -i "Cells at Work Season 2 - Episode 07 - English Subbed.mp4" -c:a copy -c:v hevc_nvenc "07.mp4"')

  


  Whenever I'm trying to run it, I'm getting this error.

  


  [hevc_nvenc @ 0000017a8bdf7e40] Cannot load nvEncodeAPI64.dll
[hevc_nvenc @ 0000017a8bdf7e40] The minimum required Nvidia driver for nvenc is 436.15 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
Conversion failed!

  


  What bugs me is that it says that I need 436.15 or newer, and mine is 461.09. That means it should work, right ? Can anyone help ?

  


• Low GPU Utilization NVIDIA / FFMPEG

  16 septembre 2023, par parakeetdev

  I'm trying to run a Docker container on runpod.io to offset media transcoding via serverless GPU's. I have the container image based off of "nvidia/cuda:12.1.0-cudnn8-devel-ubuntu22.04".

  


  Here's the configuration for FFMPEG in my Dockerfile :

  


  git clone https://github.com/FFmpeg/nv-codec-headers.git && \
    make install -C ./nv-codec-headers && \
    git clone https://git.ffmpeg.org/ffmpeg.git ffmpeg_source/ && \
    /ffmpeg_source/configure --prefix=/usr --ld="g++" --enable-nonfree --enable-gpl --enable-gnutls --enable-cuda-nvcc --enable-cuda --enable-cuda-llvm --enable-cuvid --enable-nvenc --enable-ffnvcodec --enable-libnpp --enable-libmp3lame --enable-libx264 --enable-libx265 --enable-libvpx --enable-libfreetype --enable-libvorbis --enable-libfdk-aac --enable-libopus --extra-cflags=-I/usr/local/cuda/include --extra-ldflags=-L/usr/local/cuda/lib64 --disable-static --enable-shared --disable-stripping


  


  I have the capability for GPU in my compose.yml :

  


      deploy:
      resources:
        reservations:
          devices:
          - driver: nvidia
            count: 1
            capabilities: [gpu]


  


  I receive the CUDA boot up screen when the container deploys. It's running on an RTX A6000, which is capable of hardware accelerated encoding and decoding via NVIDIA for ffmpeg.

  


  My FFMPEG command goes as follows :

  


  command = "ffmpeg -y -hwaccel cuda -hwaccel_output_format cuda -i - "

command += f"-vf scale_npp=1920:1080 -c:v h264_nvenc -b:v 5M -preset p2 -tune ll -f mp4 -bufsize 5M -maxrate 10M -qmin 0 -g 250 -bf 3 -b_ref_mode middle -temporal-aq 1 -rc-lookahead 20 -i_qfactor 0.75 -b_qfactor 1.1 {tempfile_1080.name} "

command += f"-vf scale_npp=1280:720 -c:v h264_nvenc -b:v 3M -preset p2 -tune ll -f mp4 -bufsize 3M -maxrate 6M -qmin 0 -g 250 -bf 3 -b_ref_mode middle -temporal-aq 1 -rc-lookahead 20 -i_qfactor 0.75 -b_qfactor 1.1 {tempfile_720.name} "

command += f"-vf scale_npp=640:480 -c:v h264_nvenc -b:v 1M -preset p2 -tune ll -f mp4 -bufsize 1M -maxrate 2M -qmin 0 -g 250 -bf 3 -b_ref_mode middle -temporal-aq 1 -rc-lookahead 20 -i_qfactor 0.75 -b_qfactor 1.1 {tempfile_480.name}"


  


  I'm using Python and piping to stdin with bytes.

  


  The CPU stays at 100%, while I'm lucky if the GPU ever leaves 0%. I think I've seen it hit at most about 4% utilization, while the CPU is completely maxed out.

  


  I've tried simpler commands. I thought maybe it was due to the audio, so I dropped the audio, but it didn't change anything.

  


  I've tried different images, 11.8 cuda, 12.0 cuda, 12.1 cuda, 12.2 cuda.

  


  I've tried the runtime and devel images for each of those versions.

  


  The drivers are up to date.

  


  It clearly taps into the GPU, because it will slightly bump up to a few percents before going back down to zero. On top of this, the output is also wrong/corrupted, as no video player will open the file, stating that it can't be played.

  


  I have also swapped "-hwaccel cuda" for "-hwaccel nvdec".

  


  No errors thrown and nothing changes. I have also tried with hevc_nvenc for the encoder in x265, also made no difference.

  


  Not sure what I'm doing wrong. Maybe this can't be done via piping ?