Issue with conversion about radarr-sma HOT 10 CLOSED

Conversion works fine if I go into my sonarr container and convert it manually there.

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This error would suggest that your build of FFMPEG in the radarr container is missing VAAPI

Can you check the binary and see if that's the case?

docker exec radarr bash

ffmpeg -hwaccels

On my latest pull I'm getting it

Hardware acceleration methods:
vdpau
vaapi
drm
vulkan

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Also not sure why you are manually installing INSTALL_PIP_PACKAGES=tmdbsimple|guessit|mutagen|qtfaststart those are all handled by the container already

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Hardware acceleration methods:
vdpau

It is missing vaapi, not sure why

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Not sure, I just did a fresh pull and used SMA_USE_REPO and mine has VAAPI. The container won't replace FFMPEG once its there so you might need a fresh container rebuild. FFMPEG is installed on first launch and maybe it pulled a different version.

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Adding this fixed the issue.

build:
context: https://github.com/mdhiggins/radarr-sma.git#build
args:
ffmpeg_tag: 4.4-vaapi2004

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Additionally the intel libva-intel-driver and mesa-va-gallium drivers (not the dri one though) are installed when the SMA_HWACCEL option is enabled

Any difference between mesa-dri-gallium? I can add that if its a valuable package

The fix you posted should not be needed since the repo does include VAAPI but the build version is a viable option as well

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None of those pip packages are needed at the system level as long as you use the correct python installation which may be why you were finding the need to manually add them, be cautious as future dependencies won't work since they are installed in the python virtual environment

/usr/loca/sma/venv/bin/python3

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Yah, I don't bother with the virtual environment when I console into the container to manually do conversions. Adding those packages just make it easier for me.

I had to add the gallium package previously to fix something, it might not be needed any longer.

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Eh I'll add it to the collection, can't hurt to have more hardware support

You shouldn't need to do anything special other than call that version of python but to each their own

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