From 2f674a0323879096ce5c0c4e06a04d597021b922 Mon Sep 17 00:00:00 2001 From: emeric Date: Tue, 4 Jun 2019 00:31:06 +0200 Subject: [PATCH] Updated README for Raspberry Pi 3B+ --- README.md | 17 +++++++++-------- 1 file changed, 9 insertions(+), 8 deletions(-) diff --git a/README.md b/README.md index 55d72afa..0fd5d6c6 100644 --- a/README.md +++ b/README.md @@ -1,6 +1,6 @@ # LMS - Lightweight Music Server -LMS is a self-hosted music streaming software: access your music files from anywhere using a web interface! +LMS is a self-hosted music streaming software: access your music collection from anywhere using a web interface! A [demo](http://lms.demo.poupon.io) instance is available, with the following limitations: - Settings cannot be saved @@ -8,6 +8,7 @@ A [demo](http://lms.demo.poupon.io) instance is available, with the following li - No administration panel ## Main features +- Low memory requirement (the demo instance runs on a Raspberry Pi3B+, using less than 10% of total memory even when transcoding) - User management - Recommendation engine - Audio transcode for maximum interoperability and low bandwith requirements @@ -21,7 +22,7 @@ A [demo](http://lms.demo.poupon.io) instance is available, with the following li ## Recommendation engine LMS provides several ways to help you find the music you like: -- Tag-based filters (ex: "Metal" and "Aggressive", "Electronic" and "Relaxed", ...) +- Tag-based filters (ex: "Rock", "Metal" and "Aggressive", "Electronic" and "Relaxed", ...) - Recommendations for similar artists and albums - Radio mode - Searches in album, artist and track names @@ -29,23 +30,23 @@ LMS provides several ways to help you find the music you like: The recommendation engine makes use of [Self-Organizing Maps](https://en.wikipedia.org/wiki/Self-organizing_map).
Please note this engine: -- may require some significant computation time on very large datasets -- makes use of computed data available on [AcousticBrainz](https://acousticbrainz.org/). Therefore your music must contain the [MusicBrainz Identifier](https://musicbrainz.org/doc/MusicBrainz_Identifier) for the recommendation engine to work properly (otherwise, only tag-based recommendations are provided) +- may require some significant computation time on very large collections +- makes use of computed data available on [AcousticBrainz](https://acousticbrainz.org/). Therefore your music files must contain the [MusicBrainz Identifier](https://musicbrainz.org/doc/MusicBrainz_Identifier) for the recommendation engine to work properly (otherwise, only tag-based recommendations are provided) ## Subsonic API -For now, the API version implemented is 1.12.0 and has been tested on Android using the official application, Ultrasonic and DSub. +The API version implemented is 1.12.0 and has been tested on Android using the official application, Ultrasonic and DSub. -As LMS does not aim to implement all the features of Subsonic, some commands are missing. Since LMS uses metadata tags to organize data, a compatibility mode is used to navigate through the collection using the directory browsing commands. +Since LMS uses metadata tags to organize data, a compatibility mode is used to navigate through the collection using the directory browsing commands. The Subsonic API is enabled by default. ## Installation Here are the required packages to build LMS on Debian Stretch: ```sh -apt-get install g++ autoconf automake libboost-filesystem-dev libboost-system-dev libavcodec-dev libavutil-dev libavformat-dev libav-tools libmagick++-dev libpstreams-dev libconfig++-dev libpstreams-dev ffmpeg libtag1-dev +apt-get install g++ autoconf automake libboost-filesystem-dev libboost-system-dev libavcodec-dev libavutil-dev libavformat-dev libav-tools libmagick++-dev libpstreams-dev libconfig++-dev libpstreams-dev ffmpeg libtag1-dev libcurl4-openssl-dev ``` -You also need wt4, that is not packaged yet on Debian. See [installation instructions](https://www.webtoolkit.eu/wt/doc/reference/html/InstallationUnix.html). +You also need wt4, that is not packaged yet on Debian. See [installation instructions](https://www.webtoolkit.eu/wt/doc/reference/html/InstallationUnix.html). You may need to build Wt4 in "Release" mode if you want to compile it natively on a Raspberry Pi3B+. ```sh git clone https://github.com/epoupon/lms.git lms