aperimau/nvidia-cuda-ffmpeg Docker Image Overview

aperimau/nvidia-cuda-ffmpeg

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

bash
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

bash
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

bash
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

bash
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

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

yaml
---
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: [***]
      INPUT2: [***]
      INPUT3: [***]
      INPUT4: [***]
    volumes:
      - "/etc/timezone:/etc/timezone:ro"
      - "/etc/localtime:/etc/localtime:ro"
    command: mosaic

Example To Generate Your Own Command

Running the command below:

bash
docker run -it --rm \
    -e GENCMD=1 \
    -e INPUT1=[***] \
    -e INPUT2=[***] \
    -e INPUT3=[***]\(format=m3u8-aapl\) \
    -e INPUT4=[***] \
    ghcr.io/aperim/nvidia-cuda-ffmpeg:latest mosaic

Would generate this example output

text
🖥️ 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="[***]" \
        -e INPUT2="[***]" \
        -e INPUT3="[***]" \
        -e INPUT4="[***]" \
        -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 [***] \
        -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 [***] \
        -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 [***] \
        -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 [***] \
        -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.

bash
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

text
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
                ./ffmpeg/rootfs/usr/local/bin/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

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