We utilise the docker manifest for multi-platform awareness. More information is available from docker here and our announcement here.
Simply pulling lscr.io/linuxserver/kdenlive:latest should retrieve the correct image for your arch, but you can also pull specific arch images via tags.
In order to perform hardware transcoding you will need to mount a video device into the container. Some of the default hardware rendering/transcode profiles will point to devices in /dev/dri for vaapi_device. Make sure the profile you are using points to the correct device in the container. IE if you have intel integrated graphics along with an Nvdia or AMD video card you might have renderD128, renderD129, etc. To check which device is which use vainfo from inside the container: (right click the desktop and open xterm)
We utilise the docker manifest for multi-platform awareness. More information is available from docker here and our announcement here.
Simply pulling lscr.io/linuxserver/kdenlive:latest should retrieve the correct image for your arch, but you can also pull specific arch images via tags.
In order to perform hardware transcoding you will need to mount a video device into the container. Some of the default hardware rendering/transcode profiles will point to devices in /dev/dri for vaapi_device. Make sure the profile you are using points to the correct device in the container. IE if you have intel integrated graphics along with an Nvdia or AMD video card you might have renderD128, renderD129, etc. To check which device is which use vainfo from inside the container: (right click the desktop and open xterm)
Hardware acceleration users for Nvidia will need to install the container runtime provided by Nvidia on their host, instructions can be found here: https://github.com/NVIDIA/nvidia-docker
We automatically add the necessary environment variable that will utilise all the features available on a GPU on the host. Once nvidia-docker is installed on your host you will need to re/create the docker container with the nvidia container runtime --runtime=nvidia and add an environment variable -e NVIDIA_VISIBLE_DEVICES=all (can also be set to a specific gpu's UUID, this can be discovered by running nvidia-smi --query-gpu=gpu_name,gpu_uuid --format=csv ). NVIDIA automatically mounts the GPU and drivers from your host into the container.
This container is based on Docker Baseimage KasmVNC which means there are additional environment variables and run configurations to enable or disable specific functionality.
Will start a Docker in Docker (DinD) setup inside the container to use docker in an isolated environment. For increased performance mount the Docker directory inside the container to the host IE -v /home/user/docker-data:/var/lib/docker.
-v /var/run/docker.sock:/var/run/docker.sock
Mount in the host level Docker socket to either interact with it via CLI or use Docker enabled applications.
--device /dev/dri:/dev/dri
Mount a GPU into the container, this can be used in conjunction with the DRINODE environment variable to leverage a host video card for GPU accelerated appplications. Only Open Source drivers are supported IE (Intel,AMDGPU,Radeon,ATI,Nouveau)
This container is capable of delivering a true lossless image at a high framerate to your web browser by changing the Stream Quality preset to "Lossless", more information here. In order to use this mode from a non localhost endpoint the HTTPS port on 3001 needs to be used. If using a reverse proxy to port 3000 specific headers will need to be set as outlined here.
24.04.23: - Ensure application launches in fullscreen.
18.03.23: - Rebase to KasmVNC base image.
16.09.22: - Migrate to s6v3.
09.03.22: - Update seccomp explanation.
07.03.22: - Initial release.
Last update: November 20, 2023 Created: February 5, 2019
\ No newline at end of file
diff --git a/sitemap.xml.gz b/sitemap.xml.gz
index ca2ff8a2f3..944d986df0 100644
Binary files a/sitemap.xml.gz and b/sitemap.xml.gz differ