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https://github.com/m1k1o/hls-restream
Restream live content as HLS using ffmpeg in docker. Also with NVIDIA GPU hardware acceleration.
https://github.com/m1k1o/hls-restream
docker ffmpeg hls-live-streaming hls-restream nvidia-cuda restream
Last synced: 3 months ago
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Restream live content as HLS using ffmpeg in docker. Also with NVIDIA GPU hardware acceleration.
- Host: GitHub
- URL: https://github.com/m1k1o/hls-restream
- Owner: m1k1o
- Created: 2020-07-27T20:56:31.000Z (over 4 years ago)
- Default Branch: master
- Last Pushed: 2022-10-04T16:26:30.000Z (over 2 years ago)
- Last Synced: 2024-08-07T23:48:37.488Z (6 months ago)
- Topics: docker, ffmpeg, hls-live-streaming, hls-restream, nvidia-cuda, restream
- Language: Shell
- Homepage:
- Size: 45.9 KB
- Stars: 33
- Watchers: 8
- Forks: 25
- Open Issues: 2
-
Metadata Files:
- Readme: README.md
Awesome Lists containing this project
README
# hls-restream
Restream live content as HLS using ffmpeg in docker.
# Usage
You need to have docker & docker-compose installed.
1. Clone this repository:
```sh
git clone https://github.com/m1k1o/hls-restream
cd hls-restream
```
2. Modify `docker-compose.yml` and add your own sources:
```yml
version: "3.4"
services:
hls:
build: "./"
container_name: "hls"
restart: "always"
tmpfs:
- "/var/www/html:mode=777,size=128M,uid=1000,gid=1000"
ports:
- "80:80"
environment:
PROFILE: passthrough
SOURCES: |
# SD Channels:
ch1 rtsp://192.168.1.5:554/ch1
ch2 rtsp://192.168.1.5:554/ch2
# HD Channels:
ch1_hd http://192.168.1.6/stream/channelid/8967896?profile=pass
ch2_hd http://192.168.1.6/stream/channelid/4969639?profile=pass
```
Profiles can you find in `profiles/` folder.
* passthrough - default, no transcoding.
H264 adaptive bitrate transcoding:
* abr_transcoding_sd - 360p and 480p
* abr_transcoding_hd - 360p, 480p and 720p
* abr_transcoding_hd_1080p - 360p, 480p, 720p and 1080p
H264 transcoding:
* transcoding_hd - 720p only
* transcoding_sd - 480p only
3. Start docker compose (run this everytime you modify stream sources):
```sh
docker-compose up -d --build
```
4. Watch streams:
```
http://localhost/ch1.m3u8
http://localhost/ch2.m3u8
http://localhost/ch1_hd.m3u8
http://localhost/ch2_hd.m3u8
```
In case of error, troubleshoot:
```sh
docker logs hls
docker exec -it hls sh -c 'cd /var/log/supervisor && /bin/bash'
```
# NVIDIA GPU hardware acceleration
You will need to have [nvidia-docker](https://github.com/NVIDIA/nvidia-docker) installed.
```
docker build -t hls_nvidia -f Dockerfile.nvidia .
docker run -d --gpus=all \
--name hls_nvidia \
--tmpfs /var/www/html:mode=777,size=128M,uid=1000,gid=1000 \
-p 80:80 \
-e 'PROFILE=transcoding_sd' \
-e 'SOURCES=
# SD Channels:
ch1 rtsp://192.168.1.5:554/ch1
ch2 rtsp://192.168.1.5:554/ch2
# HD Channels:
ch1_hd http://192.168.1.6/stream/channelid/8967896?profile=pass
ch2_hd http://192.168.1.6/stream/channelid/4969639?profile=pass
' \
hls_nvidia
```
## Supported inputs
Input codec will be automatically determined from given stream. Please check your graphic card's supported codec and maximum concurrent sessions [here](https://developer.nvidia.com/video-encode-decode-gpu-support-matrix).
| Codec | CUVID | Codec Name |
| ---------- | ----------- | ----------------------------------------- |
| h264 | h264_cuvid | H.264 / AVC / MPEG-4 AVC / MPEG-4 part 10 |
| hevc | hevc_cuvid | H.265 / HEVC |
| mjpeg | mjpeg_cuvid | Motion JPEG |
| mpeg1video | mpeg1_cuvid | MPEG-1 video |
| mpeg2video | mpeg2_cuvid | MPEG-2 video |
| mpeg4 | mpeg4_cuvid | MPEG-4 part 2 |
| vc1 | vc1_cuvid | SMPTE VC-1 |
| vp8 | vp8_cuvid | On2 VP8 |
| vp9 | vp9_cuvid | Google VP9 |