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A docker container, with ffmpeg that supports scale_cuda among other things

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docker-nvidia-cuda-ffmpeg

A docker container, with ffmpeg that supports scale_cuda among other things

Options

To see the options for specific filters use:

scale_cuda

docker run -it --rm --gpus=all -e NVIDIA_VISIBLE_DEVICES=all -e NVIDIA_DRIVER_CAPABILITIES=all ghcr.io/aperim/nvidia-cuda-ffmpeg:latest -h filter=scale_cuda

overlay_cuda

docker run -it --rm --gpus=all -e NVIDIA_VISIBLE_DEVICES=all -e NVIDIA_DRIVER_CAPABILITIES=all ghcr.io/aperim/nvidia-cuda-ffmpeg:latest -h filter=overlay_cuda

hevc_nvenc

docker run -it --rm --gpus=all -e NVIDIA_VISIBLE_DEVICES=all -e NVIDIA_DRIVER_CAPABILITIES=all ghcr.io/aperim/nvidia-cuda-ffmpeg:latest -h encoder=hevc_nvenc

h264_nvenc

docker run -it --rm --gpus=all -e NVIDIA_VISIBLE_DEVICES=all -e NVIDIA_DRIVER_CAPABILITIES=all ghcr.io/aperim/nvidia-cuda-ffmpeg:latest -h encoder=h264_nvenc

Getting it working

The NVIDIA CUDA drivers are badly broken. To get encoding/decoding working currently - you must apply a patch/hack by keylase

More information here

# Ensure secure boot is disabled - ie mokutil --disable-validation
sudo systemctl stop docker
sudo apt-get -y remove nvidia-docker2 # If you are using it
sudo apt-get -y install build-essential curl dkms linux-headers-$(uname -r)
sudo rm -f /etc/modprobe.d/blacklist-nvidia-nouveau.conf /etc/modprobe.d/nvidia-unsupported-gpu.conf
echo blacklist nouveau | sudo tee /etc/modprobe.d/blacklist-nvidia-nouveau.conf && \
	echo options nouveau modeset=0 | sudo tee -a /etc/modprobe.d/blacklist-nvidia-nouveau.conf && \
	echo options nvidia NVreg_OpenRmEnableUnsupportedGpus=1 | sudo tee /etc/modprobe.d/nvidia-unsupported-gpu.conf && \
	sudo update-initramfs -u && \
	sudo /sbin/reboot
git clone https://github.com/keylase/nvidia-patch.git && \
	curl -LO https://developer.download.nvidia.com/compute/cuda/11.7.1/local_installers/cuda_11.7.1_515.65.01_linux.run && \
	chmod +x ./cuda_11.7.1_515.65.01_linux.run && \
	sudo ./cuda_11.7.1_515.65.01_linux.run -m=kernel-open
sudo /sbin/reboot
# Confirm working
nvidia-smi
cd nvidia-patch
sudo bash ./patch.sh
cd ..
rm -Rf ./nvidia-patch ./cuda_*.run
sudo /sbin/reboot
# Check can encode now
curl -LO http://commondatastorage.googleapis.com/gtv-videos-bucket/sample/BigBuckBunny.mp4
ffmpeg -i BigBuckBunny.mp4 -c:v h264_nvenc  output.mp4

Extras

Mosaic Generate a video mosaic using overlays. Easily create 4, 6 and 9 input mosaics.

Camera Shortcut for transcoding rtsp camera streams.

Mosaic

Generate a 4, 6 or 9 panel mosaic / overlay.

You can use the mosaic command to generate the ffmpeg command you need, or just let it generate the mosaic and stream it for you.

Just pass the environment variables (details below) and use a command of mosaic

Required environment variables

Variable Use Default Notes
INPUT0 The background image. / etc / mosaic / 1920x1080-black.png The default is a black png that ships with the container
INPUT1 The first panel URL /etc/mosaic/1920x1080.png Supply anything ffmpeg can process
INPUT2 The second panel URL " "
INPUT3 The third panel URL " "
INPUT4 The forth panel URL " "
INPUT5 The fifth panel URL " Only supply these if you are using a 6 panel mosaic
INPUT6 The sixth panel URL " "
INPUT7 The seventh panel URL " Only supply these if you are using a 9 panel mosaic
INPUT8 The eight panel URL " "
INPUT9 The night panel URL " "
CONTAINER The output container mpegts passed to -f ie -f mpegts or -f flv
OUTPUT The output destination udp://224.0.51.1:1234?pkt_size=188 Where the data should go
BITRATE The output bitrate 8M
ENCODER The encoder to use hevc h264 or hevc
ENCODE_PRESET The encoder preset veryfast
RESOLUTION Select from a list of defaults FHD Select nHD,qHD,HD,HD+,FHD,DCI 2K,QHD,QHD+,4K UHD to auto set width and height
WIDTH The output mosaic width 1920
HEIGHT The output mosaic height 1080
FFMPEG_THREAD_QUEUE_SIZE Thread queue size 512 Tweak this only if you need
FFMPEG_CUDA_FORMAT The format inside cuda processing nv12 Tweak this only if you need
GENCMD Generate the ffmpeg command if not 0 0 Set this to 1 to generate an example command with your settings so that you can tweak it as you desire and run the mosaic yourself

Example Docker Compose

---
version: '3.8'

services:
  ffmpeg:
    image: ghcr.io/aperim/nvidia-cuda-ffmpeg:latest
    deploy:
      resources:
        reservations:
          devices:
            - driver: nvidia
              count: 1
              capabilities: [gpu]
    restart: unless-stopped              
    environment:
      PUID: 1000
      PGID: 1000
      TZ: Australia/Sydney
      NVIDIA_VISIBLE_DEVICES: all
      NVIDIA_DRIVER_CAPABILITIES: all
      NVIDIA_REQUIRE_CUDA: cuda>=11.4
      INPUT1: https://cph-p2p-msl.akamaized.net/hls/live/2000341/test/master.m3u8
      INPUT2: https://d3rlna7iyyu8wu.cloudfront.net/skip_armstrong/skip_armstrong_multichannel_subs.m3u8
      INPUT3: http://amssamples.streaming.mediaservices.windows.net/634cd01c-6822-4630-8444-8dd6279f94c6/CaminandesLlamaDrama4K.ism/manifest(format=m3u8-aapl)
      INPUT4: https://devimages.apple.com.edgekey.net/iphone/samples/bipbop/bipbopall.m3u8
    volumes:
      - "/etc/timezone:/etc/timezone:ro"
      - "/etc/localtime:/etc/localtime:ro"
    command: mosaic

Example To Generate Your Own Command

Running the command below:

docker run -it --rm \
    -e GENCMD=1 \
    -e INPUT1=https://cph-p2p-msl.akamaized.net/hls/live/2000341/test/master.m3u8 \
    -e INPUT2=https://d3rlna7iyyu8wu.cloudfront.net/skip_armstrong/skip_armstrong_multichannel_subs.m3u8 \
    -e INPUT3=http://amssamples.streaming.mediaservices.windows.net/634cd01c-6822-4630-8444-8dd6279f94c6/CaminandesLlamaDrama4K.ism/manifest\(format=m3u8-aapl\) \
    -e INPUT4=https://devimages.apple.com.edgekey.net/iphone/samples/bipbop/bipbopall.m3u8 \
    ghcr.io/aperim/nvidia-cuda-ffmpeg:latest mosaic

Would generate this example output

🖥️ mosaic command
docker run -it --rm --gpus=all -e NVIDIA_VISIBLE_DEVICES=all -e NVIDIA_DRIVER_CAPABILITIES=all \
        -e INPUT0="/etc/mosaic/1920x1080-black.png" \
        -e INPUT1="https://cph-p2p-msl.akamaized.net/hls/live/2000341/test/master.m3u8" \
        -e INPUT2="https://d3rlna7iyyu8wu.cloudfront.net/skip_armstrong/skip_armstrong_multichannel_subs.m3u8" \
        -e INPUT3="http://amssamples.streaming.mediaservices.windows.net/634cd01c-6822-4630-8444-8dd6279f94c6/CaminandesLlamaDrama4K.ism/manifest(format=m3u8-aapl)" \
        -e INPUT4="https://devimages.apple.com.edgekey.net/iphone/samples/bipbop/bipbopall.m3u8" \
        -e CONTAINER="mpegts" \
        -e OUTPUT="udp://224.0.51.1:1234?pkt_size=188" \
        -e BITRATE="8M" \
        -e ENCODER="hevc" \
        -e WIDTH="1920" \
        -e HEIGHT="1080" \
        -e FFMPEG_THREAD_QUEUE_SIZE="512" \
        -e FFMPEG_CUDA_FORMAT="nv12" \
        ghcr.io/aperim/nvidia-cuda-ffmpeg:latest mosaic

⌨️ ffmpeg command
docker run -it --rm --gpus=all -e NVIDIA_VISIBLE_DEVICES=all -e NVIDIA_DRIVER_CAPABILITIES=all ghcr.io/aperim/nvidia-cuda-ffmpeg:latest \
        -nostats -y -hide_banner -loglevel warning -err_detect ignore_err \
        -thread_queue_size 512 -hwaccel cuda -hwaccel_output_format nv12 -i /etc/mosaic/1920x1080-black.png \
        -reconnect_on_network_error 1 -reconnect_on_http_error 1 -reconnect_streamed 1 -reconnect_delay_max 2000-thread_queue_size 512 -hwaccel cuda -hwaccel_output_format nv12 -i https://cph-p2p-msl.akamaized.net/hls/live/2000341/test/master.m3u8 \
        -reconnect_on_network_error 1 -reconnect_on_http_error 1 -reconnect_streamed 1 -reconnect_delay_max 2000-thread_queue_size 512 -hwaccel cuda -hwaccel_output_format nv12 -i https://d3rlna7iyyu8wu.cloudfront.net/skip_armstrong/skip_armstrong_multichannel_subs.m3u8 \
        -reconnect_on_network_error 1 -reconnect_on_http_error 1 -reconnect_streamed 1 -reconnect_delay_max 2000-thread_queue_size 512 -hwaccel cuda -hwaccel_output_format nv12 -i http://amssamples.streaming.mediaservices.windows.net/634cd01c-6822-4630-8444-8dd6279f94c6/CaminandesLlamaDrama4K.ism/manifest(format=m3u8-aapl) \
        -reconnect_on_network_error 1 -reconnect_on_http_error 1 -reconnect_streamed 1 -reconnect_delay_max 2000-thread_queue_size 512 -hwaccel cuda -hwaccel_output_format nv12 -i https://devimages.apple.com.edgekey.net/iphone/samples/bipbop/bipbopall.m3u8 \
        -filter_complex " \
         \
        [0:v]format=nv12,hwupload_cuda,scale_cuda=-2:w=1920:h=1080:format=nv12[base]; \
        [1:v]format=nv12,hwupload_cuda,scale_cuda=-2:w=960:h=540:format=nv12,fps=24,setpts=PTS-STARTPTS[panel1]; \
        [2:v]format=nv12,hwupload_cuda,scale_cuda=-2:w=960:h=540:format=nv12,fps=24,setpts=PTS-STARTPTS[panel2]; \
        [3:v]format=nv12,hwupload_cuda,scale_cuda=-2:w=960:h=540:format=nv12,fps=24,setpts=PTS-STARTPTS[panel3]; \
        [4:v]format=nv12,hwupload_cuda,scale_cuda=-2:w=960:h=540:format=nv12,fps=24,setpts=PTS-STARTPTS[panel4]; \
        [base][panel1]overlay_cuda=shortest=0:x=0:y=0[layer1]; \
        [layer1][panel2]overlay_cuda=shortest=0:x=960:y=0[layer2]; \
        [layer2][panel3]overlay_cuda=shortest=0:x=0:y=540[layer3]; \
        [layer3][panel4]overlay_cuda=shortest=0:x=960:y=540[final] \
         \
        " \
        -map "[final]" -c:v hevc_nvenc -preset fast -tune ull -zerolatency 1 -b:v 8M \
        -map 1:a:1\? -map 2:a:2\? -map 3:a:3\? -map 4:a:4\? \
        -f mpegts "udp://224.0.51.1:1234?pkt_size=188"

Camera

Using command, pass a source and destination and the script will generate the ffmpeg command to transcode and send your camera feed.

docker run -it --rm --gpus=all -e NVIDIA_VISIBLE_DEVICES=all -e NVIDIA_DRIVER_CAPABILITIES=all ghcr.io/aperim/nvidia-cuda-ffmpeg:latest camera \
	rtsp://user:pass@192.0.2.1/unicast/c1/s0/live rtsp://host.docker.internal:8554/camera1 16M h264 24
Camera Transcode
        Usage - pass the camera url and the destination
                camera <camera_url> <destination_url> [bitrate] [encoder] [framerate]
                        camera_url The url of your camera - with url encoded usernmame/password if needed
                        destination_url The destination URL
                        bitrate (optional) The output bitrate [default 8M]
                        encoder (optional) Either h264 or hevc [default hevc]
                        framerate (optional) The frame rate [no default]
        Example
                camera rtsp://admin@passw0rd:192.0.2.1/main/0 rtsp://streaming.server.example/camera1 16M h264 24
        Note
                The output url must be RTSP. It will be using TCP

Camera Reboot Box

Reboots the generic box style camera firmware being used by a lot of aliexpress type shippers.

docker run -it --rm --gpus=all -e NVIDIA_VISIBLE_DEVICES=all -e NVIDIA_DRIVER_CAPABILITIES=all ghcr.io/aperim/nvidia-cuda-ffmpeg:latest camera-reboot-box \
	--host camerahost.example.com \
  --username CAMERAUSERNAME \
  --password CAMERAPASSWORD \
  --timeout TIMEOUT_IN_SECONDS
Box Style Camera Reboot
      Usage - pass the host, username and password
            camera-box-reboot --host <host> --username <username> --password <password> [--timeout <timeout>]
                  host the hostname or ip of the camera
                  username the admin username for the camera
                  password the admin password for the camera
                  timeout seconds to wait for camera to reboot
      Example
            camera-box-reboot --host camera1.example.com --username admin --password s5cr3t
            camera-box-reboot --host 198.51.100.100 --username camerauser --password d4ng3R! --timeout 30
      Note
            This will reboot the camera, that's it.

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A docker container, with ffmpeg that supports scale_cuda among other things

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