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Hi @Max, Are you talking about the command from this post? If so, you need to either SSH into unraid (same IP address as webUI) or use the >_ terminal icon from the webGUI to bring up the command line interface. From there you can you paste in the command, but you need to edit the command to your personal server. First, find your Nvidia GPU UUID in the Nvidia plugin under settings in the Unraid UI. Lastly, you need to change the directory to where your videos for converting are, such as /mnt/user/myvideos/:input:rw.

My test video is a mpeg2, ts container, 2mins 30secs long. The codec you're decoding makes a difference in the FPS.

wow fancy, which turing you got? I want one because they can do B-frames, better file sizes at better quality levels.

Mobile GPU nvidia p3200

Here's my ending stats with my GPU: frame= 4505 fps=294 q=36.0 Lsize= 46690kB time=00:02:30.28 bitrate=2545.1kbits/s dup=22 drop=0 speed=9.81x

I did it with the quotes, you mainly need the quotes when there's spaces in between, in this case you don't need them. I ran your command and it started up the container, I don't have a file there so it didnt convert anything but I didn't get the docker error before it tried. @unraid:~# docker run --rm --runtime=nvidia -v "/mnt/user/Downloads/handbrake/watch:/input:rw" -e 'NVIDIA_DRIVER_CAPABILITIES'='all' -e 'NVIDIA_VISIBLE_DEVICES'='GPU-6315e2bf-1c81-cc19-bfb3-a24978448a5e' djaydev/ffmpeg-ccextractor \ > ffmpeg -hwaccel nvdec -i "/input/test.mkv" -c:v hevc_nvenc -c:a copy "/input/test1.mvk" ffmpeg version 4.0.3 Copyright (c) 2000-2018 the FFmpeg developers built with gcc 7 (Ubuntu 7.3.0-27ubuntu1~18.04) configuration: --disable-debug --disable-doc --disable-ffplay --enable-vaapi --enable-shared --enable-avresample --enable-libopencore-amrnb --enable-libopencore-amrwb --enable-gnutls --enable-gpl --enable-libass --enable-libfreetype --enable-libvidstab --enable-libmp3lame --enable-libopenjpeg --enable-libopus --enable-libtheora --enable-libvorbis --enable-libvpx --enable-libx265 --enable-libxvid --enable-libx264 --enable-libkvazaar --enable-libaom --extra-libs=-lpthread --enable-postproc --enable-cuvid --enable-nvenc --enable-version3 --extra-cflags=-I/opt/ffmpeg/include --extra-ldflags=-L/opt/ffmpeg/lib --extra-libs=-ldl --prefix=/opt/ffmpeg libavutil 56. 14.100 / 56. 14.100 libavcodec 58. 18.100 / 58. 18.100 libavformat 58. 12.100 / 58. 12.100 libavdevice 58. 3.100 / 58. 3.100 libavfilter 7. 16.100 / 7. 16.100 libavresample 4. 0. 0 / 4. 0. 0 libswscale 5. 1.100 / 5. 1.100 libswresample 3. 1.100 / 3. 1.100 libpostproc 55. 1.100 / 55. 1.100 /input/test.mkv: No such file or directory

Maybe try it all on one line? docker run --rm --runtime=nvidia -v /mnt/user/Downloads/handbrake/watch:/input:rw -e NVIDIA_DRIVER_CAPABILITIES=all -e NVIDIA_VISIBLE_DEVICES=GPU-6315e2bf-1c81-cc19-bfb3-a24978448a5e djaydev/ffmpeg-ccextractor ffmpeg -hwaccel nvdec -i /input/test.mkv -c:v hevc_nvenc -c:a copy /input/test1.mkv

I copied your command into my unraid server and it worked (I had to change the GPU ID of course). Do you have the nvidia plugin installed and the drivers loaded?

That error usually shows up when the container can't access the intel iGPU. You have to ensure the iGPU shows up in /dev/dri/ ls /dev/dri/ Might want to try https://www.reddit.com/r/unRAID/comments/9eyt8u/unraid_intel_quick_sync_setup_for_plex/

While not as easy as Handbrake, you can decode and encode with your GTX 750 on unraid with ffmpeg. docker run --rm --runtime=nvidia -v "/unraid/your/videos:/input:rw" -e 'NVIDIA_DRIVER_CAPABILITIES'='all' -e 'NVIDIA_VISIBLE_DEVICES'='GPU-UUID-from-nvidia-pluginXXXX' djaydev/ffmpeg-ccextractor \ ffmpeg -hwaccel nvdec -i "/input/oldvideo.ts" -c:v hevc_nvenc -c:a copy "/input/newvideo.mp4" Edit, I don't know if GTX 750 has nvdec components or not

After you've selected NVENC the speed is based on the decode speed of your CPU, encode performance of the GPU, and the quality settings used. When I change the settings to NVENC, the quality automatically changes to CQ: 15 which is pretty high. Try lowering to quality to CQ: 23 or so. If that doesn't help then I believe the bottleneck is one of the first two factors.

Please visit:

Did you install nvidia plugin and load the drivers? If not please visit

Libvirt runs a DNS server on interface virbr0 that can be disabled with "virsh net-edit default" and adding <dns enable='no'/> to the XML. What is the best way to make this the default at start up? Thanks

A recommendation for better file sizes: In Handbrake GUI video tab select Video Encoder H.265 NVenc, Profile main, and Level 5.0. Lastly, The slider to the right of Video Encoder set to CQ: 23. With hardware encoding you lose a bit of quality, so if those settings don't look good to you in the new video, slide CQ:22 and on down until you're happy with the quality.

The CPU load you saw is from Handbrake using software decoding. Handbrake only uses the GPU for encoding. If you want to experience Nvidia hardware decoding and encoding you can try ffmpeg directly: docker run --rm --runtime=nvidia -v "/unraid/videos:/input:rw" -e 'NVIDIA_DRIVER_CAPABILITIES'='all' -e 'NVIDIA_VISIBLE_DEVICES'='GPU-UUID-from-nvidia-pluginXXXX' djaydev/ffmpeg-ccextractor \ ffmpeg -hwaccel nvdec -i "/input/oldvideo.ts" -c:v hevc_nvenc -c:a copy "/input/newvideo.mp4" Running that from Unraid's command line, and changing the "/videos/test" to the folder where your video for transcoding resides should produce a new mp4 with much less CPU load. Using ffmpeg directly can get annoying when trying to control the file size, video quality, deinterlacing etc., which is what makes Handbrake so awesome popular (Handbrake uses ffmpeg).

Connected to the console of the container and installed the intel GPU driver just as a test. That won't work for long term use since every time the container is updated the driver won't be there. I believe the linuxserver jellyfin has intel support.

Your UUID entry has a space, return, or some invisible string on the end. delete and readd: Switch the handbrake docker template to advanced mode in the unraid GUI Click remove next to the UUID Click on Add another Path, Port, Variable, Label or Device and change config type to variable. then add in the KEY field add to KEY field NVIDIA_VISIBLE_DEVICES add to the value field your UUID but ensure you only copy and paste the text only, or type it in manually. click save, it should start up

My apologies, when navigating using windows share it shows up as "flash" but it won't show up if you aren't sharing the flash. A different way: ssh or access the unraid CLI cat /boot/config/plugins/dockerMan/templates-user/my-HandBrake.xml copy paste that text here. Keep in mind "my-HandBrake" is the name you gave the docker , case sensitive.

Please navigate to flash\config\plugins\dockerMan\templates-user and then post your my-handbrake.xml here or direct message me.

When you say " I did a test and noticed it was not using nVidia" what do you mean? You have to select the nvidia codec in order for it to use the Nvidia GPU.

Not only the instructions for installing the nvidia plugin, but setting the UUID as well. The Handbrake template already includes the runtime and "NVIDIA_VISIBLE_DEVICES" so just ensure you haven't adjusted those.

Follow the instructions here:

There's no way to disable the webserver/VNC server but with so little resources it uses there's really no reason to do so. If you're worried about outside access the best bet is to not assign any ports to the container, you can just delete those entries from the container config in the WebGUI. If you're still set on not running the webserver/VNC servers, I recommend not bothering with prebuilt containers and just building your own locally. Save the following text to a file called "Dockerfile" FROM debian RUN apt-get update && \ apt-get install intel-gpu-tools bash -y && \ rm -rf /var/lib/apt/lists/* /tmp/* /var/tmp/* Change directory to where the Dockerfile is saved and run the cli command: docker build -t myfavdockerimage . That will create your customized docker image. Replace "myfavdockerimage" with whatever you want the name to be. Now whenever you want to run your image from CLI: docker run --rm -ti --privileged=true --device /dev/dri:/dev/dri myfavdockerimage intel_gpu_tools

No worries, glad you got it going and enjoy