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74 commits

Author SHA1 Message Date
2dcdd5643b Add raw song buffer constructor 2023-01-24 22:43:47 -05:00
4db79db51f Update fork information 2023-01-11 19:20:09 -05:00
2c76cf0328 Upgrade to symphonia v0.5 2023-01-11 19:17:21 -05:00
66e7333ff1 Convert ffmpeg functionality to symphonia and fix some related tests 2023-01-11 19:15:53 -05:00
Polochon-street
08aba11e39 Add library::update_* change to changelog 2022-10-16 23:01:42 +02:00
Polochon-street
8391095198
Merge pull request #52 from toofar/feat/faster_update_setup_again
Use set for paths-to-update comparison
2022-10-16 22:59:35 +02:00
Polochon-street
4097fcce6b
Merge pull request #53 from Polochon-street/prettify-json
library: pretty-print json config file
2022-10-16 21:59:22 +02:00
Polochon-street
e51c242a48 library: pretty-print json config file 2022-10-16 21:50:52 +02:00
toofar
eef648bda5 Use set for paths-to-update comparison
With about 140k tracks the update operation takes a long time. A
flamegraph shows update_library_convert_extra_info as taking almost all
of that time and slice_contains in particular.

With the previous release 0.2.9 updates where very fast and got to the
actual analyzing part right away. With 0.3.2 it spends a lot of time
before it even gets to analyzing. And it seems to be slower to start up
the more songs you have analyzed.

Blissify 0.2.9 seemed to use a HashSet too :)
2022-10-15 16:02:01 +13:00
Polochon-street
10cddd64a3
Merge pull request #50 from Polochon-street/fix-readme
Describe the library module better in README.
2022-10-12 20:05:17 +02:00
Polochon-street
ad947643ee Describe the library module better in README. 2022-10-12 19:55:51 +02:00
Polochon-street
a3be133113
Merge pull request #49 from Polochon-street/fix-number-cpu
Fix a bug in CPU number
2022-10-09 14:21:59 +02:00
Polochon-street
1c40ac7673 Fix a bug in CPU number 2022-10-09 12:54:54 +02:00
Polochon-street
cd3fd54018
Merge pull request #48 from Polochon-street/add-number-cpus
Add number cores option to Library
2022-10-03 18:23:54 +02:00
Polochon-street
8d3e328cee Add number cores option to Library 2022-10-03 18:11:13 +02:00
Polochon-street
df976c3725 Fix Cargo.toml / changelog 2022-09-28 23:33:14 +02:00
Polochon-street
bf428a62af
Merge pull request #41 from Polochon-street/add-actually-useful-library-struct
Add a proper library / config example
2022-09-28 23:15:39 +02:00
Polochon-street
40f8e399c9 Final touches 2022-09-28 22:41:59 +02:00
Polochon-street
fa3d467536 Add CUE support to the library trait 2022-09-27 22:59:10 +02:00
Polochon-street
e6ad4c96a6 Add more generic sorting things 2022-09-27 18:12:11 +02:00
Polochon-street
661d848331 Add a proper library / config example 2022-09-27 18:12:11 +02:00
Polochon-street
c3f288eb71
Merge pull request #47 from Polochon-street/fix-wav-decoding
Fix a bug in WAV decoding
2022-09-27 17:37:35 +02:00
Polochon-street
8f36dd3ee8 Fix a bug in WAV decoding 2022-09-26 23:14:21 +02:00
Polochon-street
411cdb6ecf
Merge pull request #46 from Polochon-street/analyze-path-return-paths
Add analyze_paths_with_core, return proper path
2022-09-22 22:24:38 +02:00
Polochon-street
8d0d77da7d Add analyze_paths_with_core, return proper path 2022-09-22 22:11:47 +02:00
Polochon-street
701feb414d
Merge pull request #45 from Polochon-street/fix-decoding
fix decoding when a file is broken
2022-09-07 23:40:58 +02:00
Polochon-street
7420da5041 fix decoding when a file is broken 2022-09-06 19:11:09 +02:00
Polochon-street
c5ffb619bb
Merge pull request #43 from Polochon-street/minor-changes
Make distance functions coherent
2022-08-14 18:55:53 +02:00
Polochon-street
b3f9ef5fa3 Make distance functions coherent 2022-08-14 18:47:15 +02:00
Polochon-street
89e389e1c9
Merge pull request #42 from Polochon-street/bump-ffmpeg-version
Bump ffmpeg to 5.1
2022-08-14 16:04:52 +02:00
Polochon-street
774f4972c2 Bump ffmpeg to 5.1 2022-08-14 15:56:45 +02:00
Polochon-street
f3006e843c Change CUE to flac for size 2022-04-18 19:45:07 +02:00
Polochon-street
a0fe109b96
Merge pull request #40 from Polochon-street/add-rcue-support
Add a `BlissCue` / `BlissCueFile` struct
2022-04-18 19:18:39 +02:00
Polochon-street
7498cf4620 Make analyze_paths use CUE support. 2022-04-18 19:03:03 +02:00
Polochon-street
0227c9596a Add a BlissCue / BlissCueFile struct 2022-04-14 20:42:29 +02:00
Polochon-street
5302e1e45c
Merge pull request #39 from Polochon-street/minor-fixes
Add album_artist and duration to song.
2022-04-12 22:21:13 +02:00
Polochon-street
b61c0e0b62 Add album_artist and duration to song. 2022-04-12 22:12:26 +02:00
Polochon-street
c08fd3d703
Merge pull request #37 from Polochon-street/fix-empty-chroma
Fix bug leading to empty chroma errors
2022-04-11 18:09:22 +02:00
Polochon-street
43fbafa80b Fix bug leading to empty chroma errors 2022-04-11 18:02:01 +02:00
Polochon-street
b12773d52d
Merge pull request #33 from Polochon-street/remove-library-trait
Remove library trait; move things in `playlist.rs`
2022-04-04 23:36:35 +02:00
Polochon-street
d2124a3b2c Remove library trait; move things in playlist.rs 2022-04-04 23:27:42 +02:00
Polochon-street
3a4bac5a34
Merge pull request #32 from Polochon-street/rename-song-new
Replace Song::new by Song::from_path
2022-04-03 16:57:31 +02:00
Polochon-street
c9342d7226 Replace Song::new by Song::from_path 2022-04-02 20:36:28 +02:00
Polochon-street
ef263c1eb1
Merge pull request #31 from Polochon-street/fix-analyse-vs-analyze
Replace occurences of `analyse` by `analyze`
2022-04-02 00:57:35 +02:00
Polochon-street
5930d2bc93 Replace occurences of analyse by analyze 2022-04-02 00:19:11 +02:00
Polochon-street
5f366b0d80 Merge pull request #30 from Polochon-street/some-windows-support
Add some words about windows cross-compilation
2022-02-19 20:25:30 +01:00
Polochon-street
51e8cf9344 Some fixes for the new CI 2022-02-17 22:43:28 +01:00
Polochon-street
80f4ed11aa Add some words about windows cross-compilation 2022-02-17 22:13:34 +01:00
Polochon-street
85e13251ae
Merge pull request #29 from Polochon-street/use-ffmpeg-5
Use ffmpeg 5.0
2022-02-16 19:48:14 +01:00
Polochon-street
0f3e209202 Use ffmpeg 5.0 2022-02-16 19:37:59 +01:00
Polochon-street
a4f2dd6a96 Merge pull request #28 from Polochon-street/export-feature-version
Add a features' version number
2022-01-18 18:27:03 +01:00
Polochon-street
8468a9ab8f Add a features' version number 2022-01-05 19:19:50 +01:00
Polochon-street
a27b91c6fd Merge pull request #27 from Polochon-street/example-playlist-3
Polish the playlist example a bit more
2021-11-27 16:51:49 +01:00
Polochon-street
80b8541f8f Polish the playlist example a bit more 2021-11-27 13:19:06 +01:00
Polochon-street
eee2bf612c
Merge pull request #26 from Polochon-street/example-playlist-save-results
Playlist example: save analysis to a file
2021-11-20 15:00:58 +01:00
Polochon-street
68d1d9d71b Playlist example: save analysis to a file 2021-11-15 21:41:59 +01:00
Polochon-street
13899e6b58
Merge pull request #25 from Polochon-street/add-binary-example
Add binary example to make playlist from a folder
2021-11-04 18:59:08 +01:00
Polochon-street
fac5579a66 Add binary example to make playlist from a folder 2021-11-03 19:59:23 +01:00
Polochon-street
d2442260da
Merge pull request #24 from Polochon-street/add-album-playlist
Add an option to make a playlist of albums
2021-10-02 21:35:26 +02:00
Polochon-street
be0a3e5290 Add an option to make a playlist of albums 2021-10-02 20:26:46 +02:00
Polochon-street
80a9e7c446
Merge pull request #23 from Polochon-street/update-packages
Run `cargo update`
2021-08-23 19:57:22 +02:00
Polochon-street
1805ff8161 Run cargo update 2021-08-23 19:51:03 +02:00
Polochon-street
5107bc6087
Merge pull request #22 from Polochon-street/add-dedup-method
Add playlist dedup methods
2021-08-23 19:47:49 +02:00
Polochon-street
23d4d36cb4 Add playlist dedup methods 2021-08-23 19:38:56 +02:00
Polochon-street
a3fcccbf2a
Merge pull request #21 from Polochon-street/fix-path-to-path-speed
Make the song-to-song method faster
2021-08-23 18:32:04 +02:00
Polochon-street
dd997510d3 Fix speed of "song to song" sorting method 2021-08-23 18:16:32 +02:00
Polochon-street
833d8b020b Merge pull request #20 from Polochon-street/add-custom-sorting-playlist
Add custom sorting for playlists
2021-07-28 22:20:49 +02:00
Polochon-street
e9e63f961c Add custom sorting for playlists 2021-07-28 22:10:32 +02:00
Polochon-street
82d229346b Merge pull request #19 from Polochon-street/bump-ffmpeg
Bump ffmpeg version to avoid always rebuilding it
2021-07-10 23:03:28 +02:00
Polochon-street
b7a6812e92 Bump ffmpeg version to avoid always rebuilding it 2021-07-07 18:12:06 +02:00
Polochon-street
3ed0d7126a
Merge pull request #18 from Polochon-street/add-streaming-analyze
Add an `analyze_paths_streaming` function
2021-07-05 16:17:05 +02:00
Polochon-street
0975fa1fd4 Add an analyze_paths_streaming function 2021-07-05 15:44:41 +02:00
Polochon-street
bd6ff422a7
Merge pull request #17 from Polochon-street/tentative-thread-safing
Tentative of thread safing stuff
2021-06-30 19:03:06 +02:00
Polochon-street
59b09129f4 Tentaive of thread safing stuff 2021-06-30 17:52:28 +02:00
27 changed files with 6557 additions and 1161 deletions

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@ -10,7 +10,7 @@ env:
CARGO_TERM_COLOR: always
jobs:
build:
build-test-lint-linux:
runs-on: ubuntu-latest
@ -20,17 +20,61 @@ jobs:
submodules: recursive
- uses: actions-rs/toolchain@v1
with:
toolchain: nightly-2021-04-01
toolchain: nightly-2022-02-16
override: false
- name: Packages
run: sudo apt-get install build-essential yasm libavutil-dev libavcodec-dev libavformat-dev libavfilter-dev libavfilter-dev libavdevice-dev libswresample-dev libfftw3-dev ffmpeg
run: sudo apt-get update && sudo apt-get install build-essential yasm libavutil-dev libavcodec-dev libavformat-dev libavfilter-dev libavfilter-dev libavdevice-dev libswresample-dev libfftw3-dev ffmpeg
- name: Check format
run: cargo fmt -- --check
- name: Build
run: cargo build --verbose
- name: Run tests
run: cargo test --verbose
- name: Run library tests
run: cargo test --verbose --features=library
- name: Run example tests
run: cargo test --verbose --examples
- name: Build benches
run: cargo +nightly-2021-04-01 bench --verbose --features=bench --no-run
run: cargo +nightly-2022-02-16 bench --verbose --features=bench --no-run
- name: Build examples
run: cargo build --examples --verbose
run: cargo build --examples --verbose --features=serde,library
- name: Lint
run: cargo clippy --examples --features=serde,library -- -D warnings
build-test-lint-windows:
name: Windows - build, test and lint
runs-on: windows-latest
strategy:
matrix:
include:
- ffmpeg_version: latest
ffmpeg_download_url: https://www.gyan.dev/ffmpeg/builds/ffmpeg-release-full-shared.7z
fail-fast: false
env:
FFMPEG_DOWNLOAD_URL: ${{ matrix.ffmpeg_download_url }}
steps:
- uses: actions/checkout@v2
- name: Install dependencies
run: |
$VCINSTALLDIR = $(& "${env:ProgramFiles(x86)}\Microsoft Visual Studio\Installer\vswhere.exe" -latest -property installationPath)
Add-Content $env:GITHUB_ENV "LIBCLANG_PATH=${VCINSTALLDIR}\VC\Tools\LLVM\x64\bin`n"
Invoke-WebRequest "${env:FFMPEG_DOWNLOAD_URL}" -OutFile ffmpeg-release-full-shared.7z
7z x ffmpeg-release-full-shared.7z
mkdir ffmpeg
mv ffmpeg-*/* ffmpeg/
Add-Content $env:GITHUB_ENV "FFMPEG_DIR=${pwd}\ffmpeg`n"
Add-Content $env:GITHUB_PATH "${pwd}\ffmpeg\bin`n"
- name: Set up Rust
uses: actions-rs/toolchain@v1
with:
toolchain: stable
override: true
components: rustfmt, clippy
- name: Build
run: cargo build --examples
- name: Test
run: cargo test --examples --features=serde
- name: Lint
run: cargo clippy --examples --features=serde -- -D warnings
- name: Check format
run: cargo fmt -- --check

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@ -1,5 +1,76 @@
#Changelog
## bliss 0.6.5
* Fix library update performance issues.
* Pretty-print JSON in the config file.
## bliss 0.6.4
* Fix a bug in the customizable CPU number option in `library`.
## bliss 0.6.3
* Add customizable CPU number in the `library` module.
## bliss 0.6.2
* Add a `library` module, that greatly helps when making player plug-ins.
## bliss 0.6.1
* Fix a decoding bug while decoding certain WAV files.
## bliss 0.6.0
* Change String to PathBuf in `analyze_paths`.
* Add `analyze_paths_with_cores`.
## bliss 0.5.2
* Fix a bug with some broken MP3 files.
* Bump ffmpeg to 5.1.0.
## bliss 0.5.0
* Add support for CUE files.
* Add `album_artist` and `duration` to `Song`.
* Fix a bug in `estimate_tuning` that led to empty chroma errors.
* Remove the unusued Library trait, and extract a few useful functions from
there (`analyze_paths`, `closest_to_album_group`).
* Rename `distance` module to `playlist`.
* Remove all traces of the "analyse" word vs "analyze" to make the codebase
more coherent.
* Rename `Song::new` to `Song::from_path`.
## bliss 0.4.6
* Bump ffmpeg crate version to allow for cross-compilation.
## bliss 0.4.5
* Bump ffmpeg crate version.
* Add an "ffmpeg-static" option.
## bliss 0.4.4
* Make features' version public.
## bliss 0.4.3
* Add features' version on each Song instance.
## bliss 0.4.2
* Add a binary example to easily make playlists.
## bliss 0.4.1
* Add a function to make album playlists.
## bliss 0.4.0
* Make the song-to-song custom sorting method faster.
* Rename `to_vec` and `to_arr1` to `as_vec` and `as_arr1` .
* Add a playlist_dedup function.
## bliss 0.3.5
* Add custom sorting methods for playlist-making.
## bliss 0.3.4
* Bump ffmpeg's version to avoid building ffmpeg when building bliss.
## bliss 0.3.3
* Add a streaming analysis function, to help libraries displaying progress.
## bliss 0.3.2
* Fixed a rare ffmpeg multithreading bug.
## bliss 0.3.1
* Show error message when song storage fails in the Library trait.
* Added a `distance` module containing euclidean and cosine distance.

1078
Cargo.lock generated

File diff suppressed because it is too large Load diff

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@ -1,30 +1,32 @@
[package]
name = "bliss-audio"
version = "0.3.1"
authors = ["Polochon-street <polochonstreet@gmx.fr>"]
name = "bliss-audio-symphonia"
version = "0.6.5"
authors = ["Polochon-street <polochonstreet@gmx.fr>", "NGnius (Graham) <ngniusness@gmail.com>"]
edition = "2018"
license = "GPL-3.0-only"
description = "A song analysis library for making playlists"
homepage = "https://lelele.io/bliss.html"
repository = "https://github.com/Polochon-street/bliss-rs"
repository = "https://github.com/NGnius/bliss-rs"
keywords = ["audio", "analysis", "MIR", "playlist", "similarity"]
readme = "README.md"
[package.metadata.docs.rs]
features = ["bliss-audio-aubio-rs/rustdoc"]
features = ["bliss-audio-aubio-rs/rustdoc", "library"]
no-default-features = true
[features]
# Building ffmpeg until either
# https://github.com/zmwangx/rust-ffmpeg/pull/60
# or https://github.com/zmwangx/rust-ffmpeg/pull/62 is in
default = ["bliss-audio-aubio-rs/static", "build-ffmpeg"]
default = ["bliss-audio-aubio-rs/static"]
# Build ffmpeg instead of using the host's.
build-ffmpeg = ["ffmpeg-next/build"]
# Use if you want to build python bindings with maturin.
python-bindings = ["bliss-audio-aubio-rs/fftw3"]
# Enable the benchmarks with `cargo +nightly bench --features=bench`
bench = []
library = [
"serde", "dep:rusqlite", "dep:dirs", "dep:tempdir",
"dep:anyhow", "dep:serde_ini", "dep:serde_json",
"dep:indicatif",
]
serde = ["dep:serde"]
[dependencies]
ripemd160 = "0.9.0"
@ -37,7 +39,8 @@ lazy_static = "1.4.0"
rayon = "1.5.0"
crossbeam = "0.8.0"
noisy_float = "0.2.0"
ffmpeg-next = "4.3.8"
symphonia = { version = "0.5", features = ["mp3", "aac", "alac"]}
rubato = { version = "0.12" }
log = "0.4.14"
env_logger = "0.8.3"
thiserror = "1.0.24"
@ -46,4 +49,35 @@ thiserror = "1.0.24"
bliss-audio-aubio-rs = "0.2.0"
strum = "0.21"
strum_macros = "0.21"
rcue = "0.1.1"
# Deps for the library feature
serde = { version = "1.0", optional = true, features = ["derive"] }
serde_json = { version = "1.0.59", optional = true }
serde_ini = { version = "0.2.0", optional = true }
tempdir = { version = "0.3.7", optional = true }
rusqlite = { version = "0.27.0", optional = true }
dirs = { version = "4.0.0", optional = true }
anyhow = { version = "1.0.58", optional = true }
indicatif = { version = "0.17.0", optional = true }
[dev-dependencies]
mime_guess = "2.0.3"
glob = "0.3.0"
anyhow = "1.0.45"
clap = "2.33.3"
pretty_assertions = "1.2.1"
serde_json = "1.0.59"
[[example]]
name = "library"
required-features = ["library"]
[[example]]
name = "library_extra_info"
required-features = ["library"]
[[example]]
name = "playlist"
required-features = ["serde"]

View file

@ -1,8 +1,10 @@
A modified version of the bliss-audio to remove ffmpeg and replace it with Rust's symphonia library.
[![crate](https://img.shields.io/crates/v/bliss-audio.svg)](https://crates.io/crates/bliss-audio)
[![build](https://github.com/Polochon-street/bliss-rs/workflows/Rust/badge.svg)](https://github.com/Polochon-street/bliss-rs/actions)
[![doc](https://docs.rs/bliss-rs/badge.svg)](https://docs.rs/bliss-audio/)
[![doc](https://docs.rs/bliss-audio/badge.svg)](https://docs.rs/bliss-audio/)
# bliss music analyser - Rust version
# bliss music analyzer - Rust version
bliss-rs is the Rust improvement of [bliss](https://github.com/Polochon-street/bliss), a
library used to make playlists by analyzing songs, and computing distance between them.
@ -23,18 +25,33 @@ different, more accurate values, based on
[actual literature](https://lelele.io/thesis.pdf). It is also faster.
## Examples
For simple analysis / distance computing, a look at `examples/distance.rs` and
`examples/analyse.rs`.
For simple analysis / distance computing, take a look at `examples/distance.rs` and
`examples/analyze.rs`.
Ready to use examples:
If you simply want to try out making playlists from a folder containing songs,
[this example](https://github.com/Polochon-street/bliss-rs/blob/master/examples/playlist.rs)
contains all you need. Usage:
cargo run --features=serde --release --example=playlist /path/to/folder /path/to/first/song
Don't forget the `--release` flag!
By default, it outputs the playlist to stdout, but you can use `-o <path>`
to output it to a specific path.
To avoid having to analyze the entire folder
several times, it also stores the analysis in `/tmp/analysis.json`. You can customize
this behavior by using `-a <path>` to store this file in a specific place.
Ready to use code examples:
### Compute the distance between two songs
```
use bliss_audio::{BlissError, Song};
fn main() -> Result<(), BlissError> {
let song1 = Song::new("/path/to/song1")?;
let song2 = Song::new("/path/to/song2")?;
let song1 = Song::from_path("/path/to/song1")?;
let song2 = Song::from_path("/path/to/song2")?;
println!("Distance between song1 and song2 is {}", song1.distance(&song2));
Ok(())
@ -50,7 +67,7 @@ fn main() -> Result<(), BlissError> {
let paths = vec!["/path/to/song1", "/path/to/song2", "/path/to/song3"];
let mut songs: Vec<Song> = paths
.iter()
.map(|path| Song::new(path))
.map(|path| Song::from_path(path))
.collect::<Result<Vec<Song>, BlissError>>()?;
// Assuming there is a first song
@ -72,16 +89,42 @@ fn main() -> Result<(), BlissError> {
Instead of reinventing ways to fetch a user library, play songs, etc,
and embed that into bliss, it is easier to look at the
[Library](https://github.com/Polochon-street/bliss-rs/blob/master/src/library.rs#L12)
trait.
By implementing a few functions to get songs from a media library, and store
the resulting analysis, you get access to functions to analyze an entire
library (with multithreading), and to make playlists easily.
[library](https://docs.rs/bliss-audio/latest/bliss_audio/library/index.html) module.
It implements common analysis functions, and allows analyzed songs to be put
in a sqlite database seamlessly.
See [blissify](https://crates.io/crates/blissify) for a reference
implementation.
## Cross-compilation
To cross-compile bliss-rs from linux to x86_64 windows, install the
`x86_64-pc-windows-gnu` target via:
rustup target add x86_64-pc-windows-gnu
Make sure you have `x86_64-w64-mingw32-gcc` installed on your computer.
Then run:
cargo build --target x86_64-pc-windows-gnu --release
Will produce a `.rlib` library file. If you want to generate a shared `.dll`
library, add:
[lib]
crate-type = ["cdylib"]
to `Cargo.toml` before compiling, and if you want to generate a `.lib` static
library, add:
[lib]
crate-type = ["staticlib"]
You can of course test the examples yourself by compiling them as .exe:
cargo build --target x86_64-pc-windows-gnu --release --examples
## Acknowledgements
* This library relies heavily on [aubio](https://aubio.org/)'s

29
data/empty.cue Normal file
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@ -0,0 +1,29 @@
REM GENRE Random
REM DATE 2022
PERFORMER "Polochon_street"
TITLE "Album for CUE test"
FILE "empty.wav" WAVE
TRACK 01 AUDIO
TITLE "Renaissance"
PERFORMER "David TMX"
INDEX 01 0:00:00
TRACK 02 AUDIO
TITLE "Piano"
PERFORMER "Polochon_street"
INDEX 01 0:11:05
TRACK 03 AUDIO
TITLE "Tone"
PERFORMER "Polochon_street"
INDEX 01 0:16:69
FILE "not-existing.wav" WAVE
TRACK 01 AUDIO
TITLE "Nope"
PERFORMER "Charlie"
INDEX 01 0:00:00
TRACK 02 AUDIO
TITLE "Nope"
PERFORMER "Charlie"
INDEX 01 0:10:00

BIN
data/empty.wav Normal file

Binary file not shown.

BIN
data/piano.wav Normal file

Binary file not shown.

Binary file not shown.

Binary file not shown.

29
data/testcue.cue Normal file
View file

@ -0,0 +1,29 @@
REM GENRE Random
REM DATE 2022
PERFORMER "Polochon_street"
TITLE "Album for CUE test"
FILE "testcue.flac" WAVE
TRACK 01 AUDIO
TITLE "Renaissance"
PERFORMER "David TMX"
INDEX 01 0:00:00
TRACK 02 AUDIO
TITLE "Piano"
PERFORMER "Polochon_street"
INDEX 01 0:11:05
TRACK 03 AUDIO
TITLE "Tone"
PERFORMER "Polochon_street"
INDEX 01 0:16:69
FILE "not-existing.wav" WAVE
TRACK 01 AUDIO
TITLE "Nope"
PERFORMER "Charlie"
INDEX 01 0:00:00
TRACK 02 AUDIO
TITLE "Nope"
PERFORMER "Charlie"
INDEX 01 0:10:00

BIN
data/testcue.flac Normal file

Binary file not shown.

View file

@ -1,15 +1,15 @@
use bliss_audio::Song;
use bliss_audio_symphonia::Song;
use std::env;
/**
* Simple utility to print the result of an Analysis.
*
* Takes a list of files to analyse an the result of the corresponding Analysis.
* Takes a list of files to analyze an the result of the corresponding Analysis.
*/
fn main() {
let args: Vec<String> = env::args().skip(1).collect();
for path in &args {
match Song::new(&path) {
match Song::from_path(&path) {
Ok(song) => println!("{}: {:?}", path, song.analysis),
Err(e) => println!("{}: {}", path, e),
}

View file

@ -1,10 +1,10 @@
use bliss_audio::Song;
use bliss_audio_symphonia::Song;
use std::env;
/**
* Simple utility to print distance between two songs according to bliss.
*
* Takes two file paths, and analyse the corresponding songs, printing
* Takes two file paths, and analyze the corresponding songs, printing
* the distance between the two files according to bliss.
*/
fn main() -> Result<(), String> {
@ -13,8 +13,8 @@ fn main() -> Result<(), String> {
let first_path = paths.next().ok_or("Help: ./distance <song1> <song2>")?;
let second_path = paths.next().ok_or("Help: ./distance <song1> <song2>")?;
let song1 = Song::new(&first_path).map_err(|x| x.to_string())?;
let song2 = Song::new(&second_path).map_err(|x| x.to_string())?;
let song1 = Song::from_path(&first_path).map_err(|x| x.to_string())?;
let song2 = Song::from_path(&second_path).map_err(|x| x.to_string())?;
println!(
"d({:?}, {:?}) = {}",

204
examples/library.rs Normal file
View file

@ -0,0 +1,204 @@
/// Basic example of how one would combine bliss with an "audio player",
/// through [Library].
///
/// For simplicity's sake, this example recursively gets songs from a folder
/// to emulate an audio player library, without handling CUE files.
use anyhow::Result;
use bliss_audio::library::{AppConfigTrait, BaseConfig, Library};
use clap::{App, Arg, SubCommand};
use glob::glob;
use serde::{Deserialize, Serialize};
use std::fs;
use std::num::NonZeroUsize;
use std::path::{Path, PathBuf};
#[derive(Serialize, Deserialize, Clone, Debug)]
// A config structure, that will be serialized as a
// JSON file upon Library creation.
pub struct Config {
#[serde(flatten)]
// The base configuration, containing both the config file
// path, as well as the database path.
pub base_config: BaseConfig,
// An extra field, to store the music library path. Any number
// of arbitrary fields (even Serializable structures) can
// of course be added.
pub music_library_path: PathBuf,
}
impl Config {
pub fn new(
music_library_path: PathBuf,
config_path: Option<PathBuf>,
database_path: Option<PathBuf>,
number_cores: Option<NonZeroUsize>,
) -> Result<Self> {
let base_config = BaseConfig::new(config_path, database_path, number_cores)?;
Ok(Self {
base_config,
music_library_path,
})
}
}
// The AppConfigTrait must know how to access the base config.
impl AppConfigTrait for Config {
fn base_config(&self) -> &BaseConfig {
&self.base_config
}
fn base_config_mut(&mut self) -> &mut BaseConfig {
&mut self.base_config
}
}
// A trait allowing to implement methods for the Library,
// useful if you don't need to store extra information in fields.
// Otherwise, doing
// ```
// struct CustomLibrary {
// library: Library<Config>,
// extra_field: ...,
// }
// ```
// and implementing functions for that struct would be the way to go.
// That's what the [reference](https://github.com/Polochon-street/blissify-rs)
// implementation does.
trait CustomLibrary {
fn song_paths(&self) -> Result<Vec<String>>;
}
impl CustomLibrary for Library<Config> {
/// Get all songs in the player library
fn song_paths(&self) -> Result<Vec<String>> {
let music_path = &self.config.music_library_path;
let pattern = Path::new(&music_path).join("**").join("*");
Ok(glob(&pattern.to_string_lossy())?
.map(|e| fs::canonicalize(e.unwrap()).unwrap())
.filter(|e| match mime_guess::from_path(e).first() {
Some(m) => m.type_() == "audio",
None => false,
})
.map(|x| x.to_string_lossy().to_string())
.collect::<Vec<String>>())
}
}
// A simple example of what a CLI-app would look.
//
// Note that `Library::new` is used only on init, and subsequent
// commands use `Library::from_path`.
fn main() -> Result<()> {
let matches = App::new("library-example")
.version(env!("CARGO_PKG_VERSION"))
.author("Polochon_street")
.about("Example binary implementing bliss for an audio player.")
.subcommand(
SubCommand::with_name("init")
.about(
"Initialize a Library, both storing the config and analyzing folders
containing songs.",
)
.arg(
Arg::with_name("FOLDER")
.help("A folder containing the music library to analyze.")
.required(true),
)
.arg(
Arg::with_name("database-path")
.short("d")
.long("database-path")
.help(
"Optional path where to store the database file containing
the songs' analysis. Defaults to XDG_DATA_HOME/bliss-rs/bliss.db.",
)
.takes_value(true),
)
.arg(
Arg::with_name("config-path")
.short("c")
.long("config-path")
.help(
"Optional path where to store the config file containing
the library setup. Defaults to XDG_DATA_HOME/bliss-rs/config.json.",
)
.takes_value(true),
),
)
.subcommand(
SubCommand::with_name("update")
.about(
"Update a Library's songs, trying to analyze failed songs,
as well as songs not in the library.",
)
.arg(
Arg::with_name("config-path")
.short("c")
.long("config-path")
.help(
"Optional path where to load the config file containing
the library setup. Defaults to XDG_DATA_HOME/bliss-rs/config.json.",
)
.takes_value(true),
),
)
.subcommand(
SubCommand::with_name("playlist")
.about(
"Make a playlist, starting with the song at SONG_PATH, returning
the songs' paths.",
)
.arg(Arg::with_name("SONG_PATH").takes_value(true))
.arg(
Arg::with_name("config-path")
.short("c")
.long("config-path")
.help(
"Optional path where to load the config file containing
the library setup. Defaults to XDG_DATA_HOME/bliss-rs/config.json.",
)
.takes_value(true),
)
.arg(
Arg::with_name("playlist-length")
.short("l")
.long("playlist-length")
.help("Optional playlist length. Defaults to 20.")
.takes_value(true),
),
)
.get_matches();
if let Some(sub_m) = matches.subcommand_matches("init") {
let folder = PathBuf::from(sub_m.value_of("FOLDER").unwrap());
let config_path = sub_m.value_of("config-path").map(PathBuf::from);
let database_path = sub_m.value_of("database-path").map(PathBuf::from);
let config = Config::new(folder, config_path, database_path, None)?;
let mut library = Library::new(config)?;
library.analyze_paths(library.song_paths()?, true)?;
} else if let Some(sub_m) = matches.subcommand_matches("update") {
let config_path = sub_m.value_of("config-path").map(PathBuf::from);
let mut library: Library<Config> = Library::from_config_path(config_path)?;
library.update_library(library.song_paths()?, true)?;
} else if let Some(sub_m) = matches.subcommand_matches("playlist") {
let song_path = sub_m.value_of("SONG_PATH").unwrap();
let config_path = sub_m.value_of("config-path").map(PathBuf::from);
let playlist_length = sub_m
.value_of("playlist-length")
.unwrap_or("20")
.parse::<usize>()?;
let library: Library<Config> = Library::from_config_path(config_path)?;
let songs = library.playlist_from::<()>(song_path, playlist_length)?;
let song_paths = songs
.into_iter()
.map(|s| s.bliss_song.path.to_string_lossy().to_string())
.collect::<Vec<String>>();
for song in song_paths {
println!("{:?}", song);
}
}
Ok(())
}

View file

@ -0,0 +1,227 @@
/// Basic example of how one would combine bliss with an "audio player",
/// through [Library], showing how to put extra info in the database for
/// each song.
///
/// For simplicity's sake, this example recursively gets songs from a folder
/// to emulate an audio player library, without handling CUE files.
use anyhow::Result;
use bliss_audio::library::{AppConfigTrait, BaseConfig, Library};
use clap::{App, Arg, SubCommand};
use glob::glob;
use serde::{Deserialize, Serialize};
use std::fs;
use std::num::NonZeroUsize;
use std::path::{Path, PathBuf};
#[derive(Serialize, Deserialize, Clone, Debug)]
/// A config structure, that will be serialized as a
/// JSON file upon Library creation.
pub struct Config {
#[serde(flatten)]
/// The base configuration, containing both the config file
/// path, as well as the database path.
pub base_config: BaseConfig,
/// An extra field, to store the music library path. Any number
/// of arbitrary fields (even Serializable structures) can
/// of course be added.
pub music_library_path: PathBuf,
}
impl Config {
pub fn new(
music_library_path: PathBuf,
config_path: Option<PathBuf>,
database_path: Option<PathBuf>,
number_cores: Option<NonZeroUsize>,
) -> Result<Self> {
let base_config = BaseConfig::new(config_path, database_path, number_cores)?;
Ok(Self {
base_config,
music_library_path,
})
}
}
// The AppConfigTrait must know how to access the base config.
impl AppConfigTrait for Config {
fn base_config(&self) -> &BaseConfig {
&self.base_config
}
fn base_config_mut(&mut self) -> &mut BaseConfig {
&mut self.base_config
}
}
// A trait allowing to implement methods for the Library,
// useful if you don't need to store extra information in fields.
// Otherwise, doing
// ```
// struct CustomLibrary {
// library: Library<Config>,
// extra_field: ...,
// }
// ```
// and implementing functions for that struct would be the way to go.
// That's what the [reference](https://github.com/Polochon-street/blissify-rs)
// implementation does.
trait CustomLibrary {
fn song_paths_info(&self) -> Result<Vec<(String, ExtraInfo)>>;
}
impl CustomLibrary for Library<Config> {
/// Get all songs in the player library, along with the extra info
/// one would want to store along with each song.
fn song_paths_info(&self) -> Result<Vec<(String, ExtraInfo)>> {
let music_path = &self.config.music_library_path;
let pattern = Path::new(&music_path).join("**").join("*");
Ok(glob(&pattern.to_string_lossy())?
.map(|e| fs::canonicalize(e.unwrap()).unwrap())
.filter_map(|e| {
mime_guess::from_path(&e).first().map(|m| {
(
e.to_string_lossy().to_string(),
ExtraInfo {
extension: e.extension().map(|e| e.to_string_lossy().to_string()),
file_name: e.file_name().map(|e| e.to_string_lossy().to_string()),
mime_type: format!("{}/{}", m.type_(), m.subtype()),
},
)
})
})
.collect::<Vec<(String, ExtraInfo)>>())
}
}
#[derive(Deserialize, Serialize, Debug, PartialEq, Clone, Default)]
// An (somewhat simple) example of what extra metadata one would put, along
// with song analysis data.
struct ExtraInfo {
extension: Option<String>,
file_name: Option<String>,
mime_type: String,
}
// A simple example of what a CLI-app would look.
//
// Note that `Library::new` is used only on init, and subsequent
// commands use `Library::from_path`.
fn main() -> Result<()> {
let matches = App::new("library-example")
.version(env!("CARGO_PKG_VERSION"))
.author("Polochon_street")
.about("Example binary implementing bliss for an audio player.")
.subcommand(
SubCommand::with_name("init")
.about(
"Initialize a Library, both storing the config and analyzing folders
containing songs.",
)
.arg(
Arg::with_name("FOLDER")
.help("A folder containing the music library to analyze.")
.required(true),
)
.arg(
Arg::with_name("database-path")
.short("d")
.long("database-path")
.help(
"Optional path where to store the database file containing
the songs' analysis. Defaults to XDG_DATA_HOME/bliss-rs/bliss.db.",
)
.takes_value(true),
)
.arg(
Arg::with_name("config-path")
.short("c")
.long("config-path")
.help(
"Optional path where to store the config file containing
the library setup. Defaults to XDG_DATA_HOME/bliss-rs/config.json.",
)
.takes_value(true),
),
)
.subcommand(
SubCommand::with_name("update")
.about(
"Update a Library's songs, trying to analyze failed songs,
as well as songs not in the library.",
)
.arg(
Arg::with_name("config-path")
.short("c")
.long("config-path")
.help(
"Optional path where to load the config file containing
the library setup. Defaults to XDG_DATA_HOME/bliss-rs/config.json.",
)
.takes_value(true),
),
)
.subcommand(
SubCommand::with_name("playlist")
.about(
"Make a playlist, starting with the song at SONG_PATH, returning
the songs' paths.",
)
.arg(Arg::with_name("SONG_PATH").takes_value(true))
.arg(
Arg::with_name("config-path")
.short("c")
.long("config-path")
.help(
"Optional path where to load the config file containing
the library setup. Defaults to XDG_DATA_HOME/bliss-rs/config.json.",
)
.takes_value(true),
)
.arg(
Arg::with_name("playlist-length")
.short("l")
.long("playlist-length")
.help("Optional playlist length. Defaults to 20.")
.takes_value(true),
),
)
.get_matches();
if let Some(sub_m) = matches.subcommand_matches("init") {
let folder = PathBuf::from(sub_m.value_of("FOLDER").unwrap());
let config_path = sub_m.value_of("config-path").map(PathBuf::from);
let database_path = sub_m.value_of("database-path").map(PathBuf::from);
let config = Config::new(folder, config_path, database_path, None)?;
let mut library = Library::new(config)?;
library.analyze_paths_extra_info(library.song_paths_info()?, true)?;
} else if let Some(sub_m) = matches.subcommand_matches("update") {
let config_path = sub_m.value_of("config-path").map(PathBuf::from);
let mut library: Library<Config> = Library::from_config_path(config_path)?;
library.update_library_extra_info(library.song_paths_info()?, true)?;
} else if let Some(sub_m) = matches.subcommand_matches("playlist") {
let song_path = sub_m.value_of("SONG_PATH").unwrap();
let config_path = sub_m.value_of("config-path").map(PathBuf::from);
let playlist_length = sub_m
.value_of("playlist-length")
.unwrap_or("20")
.parse::<usize>()?;
let library: Library<Config> = Library::from_config_path(config_path)?;
let songs = library.playlist_from::<ExtraInfo>(song_path, playlist_length)?;
let playlist = songs
.into_iter()
.map(|s| {
(
s.bliss_song.path.to_string_lossy().to_string(),
s.extra_info.mime_type,
)
})
.collect::<Vec<(String, String)>>();
for (path, mime_type) in playlist {
println!("{} <{}>", path, mime_type,);
}
}
Ok(())
}

95
examples/playlist.rs Normal file
View file

@ -0,0 +1,95 @@
use anyhow::Result;
use bliss_audio_symphonia::playlist::{closest_to_first_song, dedup_playlist, euclidean_distance};
use bliss_audio_symphonia::{analyze_paths, Song};
use clap::{App, Arg};
use glob::glob;
use std::env;
use std::fs;
use std::io::BufReader;
use std::path::{Path, PathBuf};
/* Analyzes a folder recursively, and make a playlist out of the file
* provided by the user. */
// How to use: ./playlist [-o file.m3u] [-a analysis.json] <folder> <file to start the playlist from>
fn main() -> Result<()> {
let matches = App::new("playlist")
.version(env!("CARGO_PKG_VERSION"))
.author("Polochon_street")
.about("Analyze a folder and make a playlist from a target song")
.arg(Arg::with_name("output-playlist").short("o").long("output-playlist")
.value_name("PLAYLIST.M3U")
.help("Outputs the playlist to a file.")
.takes_value(true))
.arg(Arg::with_name("analysis-file").short("a").long("analysis-file")
.value_name("ANALYSIS.JSON")
.help("Use the songs that have been analyzed in <analysis-file>, and appends newly analyzed songs to it. Defaults to /tmp/analysis.json.")
.takes_value(true))
.arg(Arg::with_name("FOLDER").help("Folders containing some songs.").required(true))
.arg(Arg::with_name("FIRST-SONG").help("Song to start from (can be outside of FOLDER).").required(true))
.get_matches();
let folder = matches.value_of("FOLDER").unwrap();
let file = fs::canonicalize(matches.value_of("FIRST-SONG").unwrap())?;
let pattern = Path::new(folder).join("**").join("*");
let mut songs: Vec<Song> = Vec::new();
let analysis_path = matches
.value_of("analysis-file")
.unwrap_or("/tmp/analysis.json");
let analysis_file = fs::File::open(analysis_path);
if let Ok(f) = analysis_file {
let reader = BufReader::new(f);
songs = serde_json::from_reader(reader)?;
}
let analyzed_paths = songs
.iter()
.map(|s| s.path.to_owned())
.collect::<Vec<PathBuf>>();
let paths = glob(&pattern.to_string_lossy())?
.map(|e| fs::canonicalize(e.unwrap()).unwrap())
.filter(|e| match mime_guess::from_path(e).first() {
Some(m) => m.type_() == "audio",
None => false,
})
.map(|x| x.to_string_lossy().to_string())
.collect::<Vec<String>>();
let song_iterator = analyze_paths(
paths
.iter()
.filter(|p| !analyzed_paths.contains(&PathBuf::from(p)))
.map(|p| p.to_owned())
.collect::<Vec<String>>(),
);
let first_song = Song::from_path(file)?;
let mut analyzed_songs = vec![first_song.to_owned()];
for (path, result) in song_iterator {
match result {
Ok(song) => analyzed_songs.push(song),
Err(e) => println!("error analyzing {}: {}", path.display(), e),
};
}
analyzed_songs.extend_from_slice(&songs);
let serialized = serde_json::to_string(&analyzed_songs).unwrap();
let mut songs_to_chose_from: Vec<_> = analyzed_songs
.into_iter()
.filter(|x| x == &first_song || paths.contains(&x.path.to_string_lossy().to_string()))
.collect();
closest_to_first_song(&first_song, &mut songs_to_chose_from, euclidean_distance);
dedup_playlist(&mut songs_to_chose_from, None);
fs::write(analysis_path, serialized)?;
let playlist = songs_to_chose_from
.iter()
.map(|s| s.path.to_string_lossy().to_string())
.collect::<Vec<String>>()
.join("\n");
if let Some(m) = matches.value_of("output-playlist") {
fs::write(m, playlist)?;
} else {
println!("{}", playlist);
}
Ok(())
}

View file

@ -180,7 +180,7 @@ fn chroma_filter(
}),
);
let mut d: Array2<f64> = Array::zeros((n_chroma as usize, (&freq_bins).len()));
let mut d: Array2<f64> = Array::zeros((n_chroma as usize, (freq_bins).len()));
for (idx, mut row) in d.rows_mut().into_iter().enumerate() {
row.fill(idx as f64);
}
@ -207,13 +207,13 @@ fn chroma_filter(
wts *= &freq_bins;
// np.roll(), np bro
let mut uninit: Vec<f64> = Vec::with_capacity((&wts).len());
let mut uninit: Vec<f64> = vec![0.; (wts).len()];
unsafe {
uninit.set_len(wts.len());
}
let mut b = Array::from(uninit)
.into_shape(wts.dim())
.map_err(|e| BlissError::AnalysisError(format!("in chroma: {}", e.to_string())))?;
.map_err(|e| BlissError::AnalysisError(format!("in chroma: {}", e)))?;
b.slice_mut(s![-3.., ..]).assign(&wts.slice(s![..3, ..]));
b.slice_mut(s![..-3, ..]).assign(&wts.slice(s![3.., ..]));
@ -308,7 +308,7 @@ fn pitch_tuning(
}
let max_index = counts
.argmax()
.map_err(|e| BlissError::AnalysisError(format!("in chroma: {}", e.to_string())))?;
.map_err(|e| BlissError::AnalysisError(format!("in chroma: {}", e)))?;
// Return the bin with the most reoccuring frequency.
Ok((-50. + (100. * resolution * max_index as f64)) / 100.)
@ -321,7 +321,7 @@ fn estimate_tuning(
resolution: f64,
bins_per_octave: u32,
) -> BlissResult<f64> {
let (pitch, mag) = pip_track(sample_rate, &spectrum, n_fft)?;
let (pitch, mag) = pip_track(sample_rate, spectrum, n_fft)?;
let (filtered_pitch, filtered_mag): (Vec<N64>, Vec<N64>) = pitch
.iter()
@ -330,11 +330,14 @@ fn estimate_tuning(
.map(|(x, y)| (n64(*x), n64(*y)))
.unzip();
if pitch.is_empty() {
return Ok(0.);
}
let threshold: N64 = Array::from(filtered_mag.to_vec())
.quantile_axis_mut(Axis(0), n64(0.5), &Midpoint)
.map_err(|e| BlissError::AnalysisError(format!("in chroma: {}", e.to_string())))?
.map_err(|e| BlissError::AnalysisError(format!("in chroma: {}", e)))?
.into_scalar();
let mut pitch = filtered_pitch
.iter()
.zip(&filtered_mag)
@ -486,6 +489,11 @@ mod test {
assert!(0.000001 > (-0.09999999999999998 - tuning).abs());
}
#[test]
fn test_chroma_estimate_tuning_empty_fix() {
assert!(0. == estimate_tuning(22050, &Array2::zeros((8192, 1)), 8192, 0.01, 12).unwrap());
}
#[test]
fn test_estimate_tuning_decode() {
let signal = Song::decode(Path::new("data/s16_mono_22_5kHz.flac"))

338
src/cue.rs Normal file
View file

@ -0,0 +1,338 @@
//! CUE-handling module.
//!
//! Using [BlissCue::songs_from_path] is most likely what you want.
use crate::{Analysis, BlissError, BlissResult, Song, FEATURES_VERSION, SAMPLE_RATE};
use rcue::cue::{Cue, Track};
use rcue::parser::parse_from_file;
use std::path::{Path, PathBuf};
use std::time::Duration;
#[cfg_attr(feature = "serde", derive(Serialize, Deserialize))]
#[derive(Default, Debug, PartialEq, Eq, Clone)]
/// A struct populated when the corresponding [Song] has been extracted from an
/// audio file split with the help of a CUE sheet.
pub struct CueInfo {
/// The path of the original CUE sheet, e.g. `/path/to/album_name.cue`.
pub cue_path: PathBuf,
/// The path of the audio file the song was extracted from, e.g.
/// `/path/to/album_name.wav`. Used because one CUE sheet can refer to
/// several audio files.
pub audio_file_path: PathBuf,
}
/// A struct to handle CUEs with bliss.
/// Use either [analyze_paths](crate::analyze_paths) with CUE files or
/// [songs_from_path](BlissCue::songs_from_path) to return a list of [Song]s
/// from CUE files.
pub struct BlissCue {
cue: Cue,
cue_path: PathBuf,
}
#[allow(missing_docs)]
#[derive(Default, Debug, PartialEq, Clone)]
struct BlissCueFile {
sample_array: Vec<f32>,
album: Option<String>,
artist: Option<String>,
genre: Option<String>,
tracks: Vec<Track>,
cue_path: PathBuf,
audio_file_path: PathBuf,
}
impl BlissCue {
/// Analyze songs from a CUE file, extracting individual [Song] objects
/// for each individual song.
///
/// Each returned [Song] has a populated [cue_info](Song::cue_info) object, that can be
/// be used to retrieve which CUE sheet was used to extract it, as well
/// as the corresponding audio file.
pub fn songs_from_path<P: AsRef<Path>>(path: P) -> BlissResult<Vec<BlissResult<Song>>> {
let cue = BlissCue::from_path(&path)?;
let cue_files = cue.files();
let mut songs = Vec::new();
for cue_file in cue_files.into_iter() {
match cue_file {
Ok(f) => {
if !f.sample_array.is_empty() {
songs.extend_from_slice(&f.get_songs());
} else {
songs.push(Err(BlissError::DecodingError(
"empty audio file associated to CUE sheet".into(),
)));
}
}
Err(e) => songs.push(Err(e)),
}
}
Ok(songs)
}
// Extract a BlissCue from a given path.
fn from_path<P: AsRef<Path>>(path: P) -> BlissResult<Self> {
let cue = parse_from_file(&path.as_ref().to_string_lossy(), false).map_err(|e| {
BlissError::DecodingError(format!(
"when opening CUE file '{:?}': {:?}",
path.as_ref(),
e
))
})?;
Ok(BlissCue {
cue,
cue_path: path.as_ref().to_owned(),
})
}
// List all BlissCueFile from a BlissCue.
fn files(&self) -> Vec<BlissResult<BlissCueFile>> {
let mut cue_files = Vec::new();
for cue_file in self.cue.files.iter() {
let audio_file_path = match &self.cue_path.parent() {
Some(parent) => parent.join(Path::new(&cue_file.file)),
None => PathBuf::from(cue_file.file.to_owned()),
};
let genre = self
.cue
.comments
.iter()
.find(|(c, _)| c == "GENRE")
.map(|(_, v)| v.to_owned());
let raw_song = Song::decode(Path::new(&audio_file_path));
if let Ok(song) = raw_song {
let bliss_cue_file = BlissCueFile {
sample_array: song.sample_array,
genre,
artist: self.cue.performer.to_owned(),
album: self.cue.title.to_owned(),
tracks: cue_file.tracks.to_owned(),
audio_file_path,
cue_path: self.cue_path.to_owned(),
};
cue_files.push(Ok(bliss_cue_file))
} else {
cue_files.push(Err(raw_song.unwrap_err()));
}
}
cue_files
}
}
impl BlissCueFile {
fn create_song(
&self,
analysis: BlissResult<Analysis>,
current_track: &Track,
duration: Duration,
index: usize,
) -> BlissResult<Song> {
if let Ok(a) = analysis {
let song = Song {
path: PathBuf::from(format!(
"{}/CUE_TRACK{:03}",
self.cue_path.to_string_lossy(),
index,
)),
album: self.album.to_owned(),
artist: current_track.performer.to_owned(),
album_artist: self.artist.to_owned(),
analysis: a,
duration,
genre: self.genre.to_owned(),
title: current_track.title.to_owned(),
track_number: Some(current_track.no.to_owned()),
features_version: FEATURES_VERSION,
cue_info: Some(CueInfo {
cue_path: self.cue_path.to_owned(),
audio_file_path: self.audio_file_path.to_owned(),
}),
};
Ok(song)
} else {
Err(analysis.unwrap_err())
}
}
// Get all songs from a BlissCueFile, using Song::analyze, each song being
// located using the sample_array and the timestamp delimiter.
fn get_songs(&self) -> Vec<BlissResult<Song>> {
let mut songs = Vec::new();
for (index, tuple) in (self.tracks[..]).windows(2).enumerate() {
let (current_track, next_track) = (tuple[0].to_owned(), tuple[1].to_owned());
if let Some((_, start_current)) = current_track.indices.get(0) {
if let Some((_, end_current)) = next_track.indices.get(0) {
let start_current = (start_current.as_secs_f32() * SAMPLE_RATE as f32) as usize;
let end_current = (end_current.as_secs_f32() * SAMPLE_RATE as f32) as usize;
let duration = Duration::from_secs_f32(
(end_current - start_current) as f32 / SAMPLE_RATE as f32,
);
let analysis = Song::analyze(&self.sample_array[start_current..end_current]);
let song = self.create_song(analysis, &current_track, duration, index + 1);
songs.push(song);
}
}
}
// Take care of the last track, since the windows iterator doesn't.
if let Some(last_track) = self.tracks.last() {
if let Some((_, start_current)) = last_track.indices.get(0) {
let start_current = (start_current.as_secs_f32() * SAMPLE_RATE as f32) as usize;
let duration = Duration::from_secs_f32(
(self.sample_array.len() - start_current) as f32 / SAMPLE_RATE as f32,
);
let analysis = Song::analyze(&self.sample_array[start_current..]);
let song = self.create_song(analysis, last_track, duration, self.tracks.len());
songs.push(song);
}
}
songs
}
}
#[cfg(test)]
mod tests {
use super::*;
use pretty_assertions::assert_eq;
#[test]
fn test_empty_cue() {
let songs = BlissCue::songs_from_path("data/empty.cue").unwrap();
let error = songs[0].to_owned().unwrap_err();
assert_eq!(
error,
BlissError::DecodingError("while opening format: DecodeError(\"wav: chunk length exceeds parent (list) chunk length\").".to_string())
);
}
#[test]
fn test_cue_analysis() {
let songs = BlissCue::songs_from_path("data/testcue.cue").unwrap();
let expected = vec![
Ok(Song {
path: Path::new("data/testcue.cue/CUE_TRACK001").to_path_buf(),
analysis: Analysis {
internal_analysis: [
0.38463724,
-0.85219246,
-0.761946,
-0.8904667,
-0.63892543,
-0.73945934,
-0.8004017,
-0.8237293,
0.33865356,
0.32481194,
-0.35692245,
-0.6355889,
-0.29584837,
0.06431806,
0.21875131,
-0.58104205,
-0.9466792,
-0.94811195,
-0.9820919,
-0.9596871,
],
},
album: Some(String::from("Album for CUE test")),
artist: Some(String::from("David TMX")),
title: Some(String::from("Renaissance")),
genre: Some(String::from("Random")),
track_number: Some(String::from("01")),
features_version: FEATURES_VERSION,
album_artist: Some(String::from("Polochon_street")),
duration: Duration::from_secs_f32(11.066666603),
cue_info: Some(CueInfo {
cue_path: PathBuf::from("data/testcue.cue"),
audio_file_path: PathBuf::from("data/testcue.flac"),
}),
..Default::default()
}),
Ok(Song {
path: Path::new("data/testcue.cue/CUE_TRACK002").to_path_buf(),
analysis: Analysis {
internal_analysis: [
0.18622077,
-0.5989029,
-0.5554645,
-0.6343865,
-0.24163479,
-0.25766593,
-0.40616858,
-0.23334873,
0.76875293,
0.7785741,
-0.5075115,
-0.5272629,
-0.56706166,
-0.568486,
-0.5639081,
-0.5706943,
-0.96501005,
-0.96501285,
-0.9649896,
-0.96498996,
],
},
features_version: FEATURES_VERSION,
album: Some(String::from("Album for CUE test")),
artist: Some(String::from("Polochon_street")),
title: Some(String::from("Piano")),
genre: Some(String::from("Random")),
track_number: Some(String::from("02")),
album_artist: Some(String::from("Polochon_street")),
duration: Duration::from_secs_f64(5.853333473),
cue_info: Some(CueInfo {
cue_path: PathBuf::from("data/testcue.cue"),
audio_file_path: PathBuf::from("data/testcue.flac"),
}),
..Default::default()
}),
Ok(Song {
path: Path::new("data/testcue.cue/CUE_TRACK003").to_path_buf(),
analysis: Analysis {
internal_analysis: [
0.0024261475,
0.9874661,
0.97330654,
-0.9724426,
0.99678576,
-0.9961549,
-0.9840142,
-0.9269961,
0.7498772,
0.22429907,
-0.8355152,
-0.9977258,
-0.9977849,
-0.997785,
-0.99778515,
-0.997785,
-0.99999976,
-0.99999976,
-0.99999976,
-0.99999976,
],
},
album: Some(String::from("Album for CUE test")),
artist: Some(String::from("Polochon_street")),
title: Some(String::from("Tone")),
genre: Some(String::from("Random")),
track_number: Some(String::from("03")),
features_version: FEATURES_VERSION,
album_artist: Some(String::from("Polochon_street")),
duration: Duration::from_secs_f32(5.586666584),
cue_info: Some(CueInfo {
cue_path: PathBuf::from("data/testcue.cue"),
audio_file_path: PathBuf::from("data/testcue.flac"),
}),
..Default::default()
}),
Err(BlissError::DecodingError(String::from(
"while opening song: Os { code: 2, kind: NotFound, message: \"No such file or directory\" }.",
))),
];
assert_eq!(expected, songs);
}
}

View file

@ -1,75 +0,0 @@
//! Module containing various distance metric functions.
//!
//! All of these functions are intended to be used with the
//! [custom_distance](Song::custom_distance) method, or with
//! [playlist_from_songs_custom_distance](Library::playlist_from_song_custom_distance).
//!
//! They will yield different styles of playlists, so don't hesitate to
//! experiment with them if the default (euclidean distance for now) doesn't
//! suit you.
use crate::NUMBER_FEATURES;
#[cfg(doc)]
use crate::{Library, Song};
use ndarray::{Array, Array1};
/// Convenience trait for user-defined distance metrics.
pub trait DistanceMetric: Fn(&Array1<f32>, &Array1<f32>) -> f32 {}
impl<F> DistanceMetric for F where F: Fn(&Array1<f32>, &Array1<f32>) -> f32 {}
/// Return the [euclidean
/// distance](https://en.wikipedia.org/wiki/Euclidean_distance#Higher_dimensions)
/// between two vectors.
pub fn euclidean_distance(a: &Array1<f32>, b: &Array1<f32>) -> f32 {
// Could be any square symmetric positive semi-definite matrix;
// just no metric learning has been done yet.
// See https://lelele.io/thesis.pdf chapter 4.
let m = Array::eye(NUMBER_FEATURES);
(a - b).dot(&m).dot(&(a - b)).sqrt()
}
/// Return the [cosine
/// distance](https://en.wikipedia.org/wiki/Cosine_similarity#Angular_distance_and_similarity)
/// between two vectors.
pub fn cosine_distance(a: &Array1<f32>, b: &Array1<f32>) -> f32 {
let similarity = a.dot(b) / (a.dot(a).sqrt() * b.dot(b).sqrt());
1. - similarity
}
#[cfg(test)]
mod test {
use super::*;
use ndarray::arr1;
#[test]
fn test_euclidean_distance() {
let a = arr1(&[
1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 0.,
]);
let b = arr1(&[
0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 1., 0., 0., 0.,
]);
assert_eq!(euclidean_distance(&a, &b), 4.242640687119285);
let a = arr1(&[0.5; 20]);
let b = arr1(&[0.5; 20]);
assert_eq!(euclidean_distance(&a, &b), 0.);
assert_eq!(euclidean_distance(&a, &b), 0.);
}
#[test]
fn test_cosine_distance() {
let a = arr1(&[
1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 0.,
]);
let b = arr1(&[
0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 1., 0., 0., 0.,
]);
assert_eq!(cosine_distance(&a, &b), 0.7705842661294382);
let a = arr1(&[0.5; 20]);
let b = arr1(&[0.5; 20]);
assert_eq!(cosine_distance(&a, &b), 0.);
assert_eq!(cosine_distance(&a, &b), 0.);
}
}

View file

@ -2,72 +2,75 @@
//!
//! bliss is a library for making "smart" audio playlists.
//!
//! The core of the library is the `Song` object, which relates to a
//! The core of the library is the [Song] object, which relates to a
//! specific analyzed song and contains its path, title, analysis, and
//! other metadata fields (album, genre...).
//! Analyzing a song is as simple as running `Song::new("/path/to/song")`.
//! Analyzing a song is as simple as running `Song::from_path("/path/to/song")`.
//!
//! The [analysis](Song::analysis) field of each song is an array of f32, which makes the
//! comparison between songs easy, by just using euclidean distance (see
//! [distance](Song::distance) for instance).
//! The [analysis](Song::analysis) field of each song is an array of f32, which
//! makes the comparison between songs easy, by just using e.g. euclidean
//! distance (see [distance](Song::distance) for instance).
//!
//! Once several songs have been analyzed, making a playlist from one Song
//! is as easy as computing distances between that song and the rest, and ordering
//! the songs by distance, ascending.
//!
//! It is also convenient to make plug-ins for existing audio players.
//! It should be as easy as implementing the necessary traits for [Library].
//! A reference implementation for the MPD player is available
//! [here](https://github.com/Polochon-street/blissify-rs)
//! If you want to implement a bliss plugin for an already existing audio
//! player, the [Library] struct is a collection of goodies that should prove
//! useful (it contains utilities to store analyzed songs in a self-contained
//! database file, to make playlists directly from the database, etc).
//! [blissify](https://github.com/Polochon-street/blissify-rs/) for both
//! an example of how the [Library] struct works, and a real-life demo of bliss
//! implemented for [MPD](https://www.musicpd.org/).
//!
//! # Examples
//!
//! ## Analyze & compute the distance between two songs
//! ### Analyze & compute the distance between two songs
//! ```no_run
//! use bliss_audio::{BlissResult, Song};
//!
//! fn main() -> BlissResult<()> {
//! let song1 = Song::new("/path/to/song1")?;
//! let song2 = Song::new("/path/to/song2")?;
//! let song1 = Song::from_path("/path/to/song1")?;
//! let song2 = Song::from_path("/path/to/song2")?;
//!
//! println!("Distance between song1 and song2 is {}", song1.distance(&song2));
//! Ok(())
//! }
//! ```
//!
//! ### Make a playlist from a song
//! ### Make a playlist from a song, discarding failed songs
//! ```no_run
//! use bliss_audio::{BlissResult, Song};
//! use noisy_float::prelude::n32;
//! use bliss_audio::{
//! analyze_paths,
//! playlist::{closest_to_first_song, euclidean_distance},
//! BlissResult, Song,
//! };
//!
//! fn main() -> BlissResult<()> {
//! let paths = vec!["/path/to/song1", "/path/to/song2", "/path/to/song3"];
//! let mut songs: Vec<Song> = paths
//! .iter()
//! .map(|path| Song::new(path))
//! .collect::<BlissResult<Vec<Song>>>()?;
//! let mut songs: Vec<Song> = analyze_paths(&paths).filter_map(|(_, s)| s.ok()).collect();
//!
//! // Assuming there is a first song
//! let first_song = songs.first().unwrap().to_owned();
//!
//! songs.sort_by_cached_key(|song| n32(first_song.distance(&song)));
//! println!(
//! "Playlist is: {:?}",
//! songs
//! .iter()
//! .map(|song| song.path.to_string_lossy().to_string())
//! .collect::<Vec<String>>()
//! );
//! closest_to_first_song(&first_song, &mut songs, euclidean_distance);
//!
//! println!("Playlist is:");
//! for song in songs {
//! println!("{}", song.path.display());
//! }
//! Ok(())
//! }
//! ```
#![cfg_attr(feature = "bench", feature(test))]
#![warn(missing_docs)]
#![warn(missing_doc_code_examples)]
#![warn(rustdoc::missing_doc_code_examples)]
mod chroma;
pub mod distance;
mod library;
pub mod cue;
#[cfg(feature = "library")]
pub mod library;
mod misc;
pub mod playlist;
mod song;
mod temporal;
mod timbral;
@ -78,71 +81,182 @@ extern crate num_cpus;
#[cfg(feature = "serde")]
#[macro_use]
extern crate serde;
use crate::cue::BlissCue;
use log::info;
use std::num::NonZeroUsize;
use std::path::{Path, PathBuf};
use std::sync::mpsc;
use std::thread;
use thiserror::Error;
pub use library::Library;
pub use song::{Analysis, AnalysisIndex, Song, NUMBER_FEATURES};
const CHANNELS: u16 = 1;
//const CHANNELS: u16 = 1;
const SAMPLE_RATE: u32 = 22050;
/// Stores the current version of bliss-rs' features.
/// It is bumped every time one or more feature is added, updated or removed,
/// so plug-ins can rescan libraries when there is a major change.
pub const FEATURES_VERSION: u16 = 1;
#[derive(Error, Clone, Debug, PartialEq)]
#[derive(Error, Clone, Debug, PartialEq, Eq)]
/// Umbrella type for bliss error types
pub enum BlissError {
#[error("error happened while decoding file {0}")]
/// An error happened while decoding an (audio) file
/// An error happened while decoding an (audio) file.
DecodingError(String),
#[error("error happened while analyzing file {0}")]
/// An error happened during the analysis of the samples by bliss
/// An error happened during the analysis of the song's samples by bliss.
AnalysisError(String),
#[error("error happened with the music library provider - {0}")]
/// An error happened with the music library provider.
/// Useful to report errors when you implement the [Library] trait.
/// Useful to report errors when you implement bliss for an audio player.
ProviderError(String),
}
/// bliss error type
pub type BlissResult<T> = Result<T, BlissError>;
/// Simple function to bulk analyze a set of songs represented by their
/// absolute paths.
/// Analyze songs in `paths`, and return the analyzed [Song] objects through an
/// [mpsc::IntoIter].
///
/// When making an extension for an audio player, prefer
/// implementing the `Library` trait.
#[doc(hidden)]
pub fn bulk_analyse(paths: Vec<String>) -> Vec<BlissResult<Song>> {
let mut songs = Vec::with_capacity(paths.len());
let num_cpus = num_cpus::get();
crossbeam::scope(|s| {
let mut handles = Vec::with_capacity(paths.len() / num_cpus);
let mut chunk_number = paths.len() / num_cpus;
if chunk_number == 0 {
chunk_number = paths.len();
}
for chunk in paths.chunks(chunk_number) {
handles.push(s.spawn(move |_| {
let mut result = Vec::with_capacity(chunk.len());
for path in chunk {
let song = Song::new(&path);
result.push(song);
}
result
}));
/// Returns an iterator, whose items are a tuple made of
/// the song path (to display to the user in case the analysis failed),
/// and a Result<Song>.
///
/// # Note
///
/// This function also works with CUE files - it finds the audio files
/// mentionned in the CUE sheet, and then runs the analysis on each song
/// defined by it, returning a proper [Song] object for each one of them.
///
/// Make sure that you don't submit both the audio file along with the CUE
/// sheet if your library uses them, otherwise the audio file will be
/// analyzed as one, single, long song. For instance, with a CUE sheet named
/// `cue-file.cue` with the corresponding audio files `album-1.wav` and
/// `album-2.wav` defined in the CUE sheet, you would just pass `cue-file.cue`
/// to `analyze_paths`, and it will return [Song]s from both files, with
/// more information about which file it is extracted from in the
/// [cue info field](Song::cue_info).
///
/// # Example:
/// ```no_run
/// use bliss_audio::{analyze_paths, BlissResult};
///
/// fn main() -> BlissResult<()> {
/// let paths = vec![String::from("/path/to/song1"), String::from("/path/to/song2")];
/// for (path, result) in analyze_paths(&paths) {
/// match result {
/// Ok(song) => println!("Do something with analyzed song {} with title {:?}", song.path.display(), song.title),
/// Err(e) => println!("Song at {} could not be analyzed. Failed with: {}", path.display(), e),
/// }
/// }
/// Ok(())
/// }
/// ```
pub fn analyze_paths<P: Into<PathBuf>, F: IntoIterator<Item = P>>(
paths: F,
) -> mpsc::IntoIter<(PathBuf, BlissResult<Song>)> {
let cores = NonZeroUsize::new(num_cpus::get()).unwrap();
analyze_paths_with_cores(paths, cores)
}
for handle in handles {
songs.extend(handle.join().unwrap());
/// Analyze songs in `paths`, and return the analyzed [Song] objects through an
/// [mpsc::IntoIter]. `number_cores` sets the number of cores the analysis
/// will use, capped by your system's capacity. Most of the time, you want to
/// use the simpler `analyze_paths` functions, which autodetects the number
/// of cores in your system.
///
/// Return an iterator, whose items are a tuple made of
/// the song path (to display to the user in case the analysis failed),
/// and a Result<Song>.
///
/// # Note
///
/// This function also works with CUE files - it finds the audio files
/// mentionned in the CUE sheet, and then runs the analysis on each song
/// defined by it, returning a proper [Song] object for each one of them.
///
/// Make sure that you don't submit both the audio file along with the CUE
/// sheet if your library uses them, otherwise the audio file will be
/// analyzed as one, single, long song. For instance, with a CUE sheet named
/// `cue-file.cue` with the corresponding audio files `album-1.wav` and
/// `album-2.wav` defined in the CUE sheet, you would just pass `cue-file.cue`
/// to `analyze_paths`, and it will return [Song]s from both files, with
/// more information about which file it is extracted from in the
/// [cue info field](Song::cue_info).
///
/// # Example:
/// ```no_run
/// use bliss_audio::{analyze_paths, BlissResult};
///
/// fn main() -> BlissResult<()> {
/// let paths = vec![String::from("/path/to/song1"), String::from("/path/to/song2")];
/// for (path, result) in analyze_paths(&paths) {
/// match result {
/// Ok(song) => println!("Do something with analyzed song {} with title {:?}", song.path.display(), song.title),
/// Err(e) => println!("Song at {} could not be analyzed. Failed with: {}", path.display(), e),
/// }
/// }
/// Ok(())
/// }
/// ```
pub fn analyze_paths_with_cores<P: Into<PathBuf>, F: IntoIterator<Item = P>>(
paths: F,
number_cores: NonZeroUsize,
) -> mpsc::IntoIter<(PathBuf, BlissResult<Song>)> {
let mut cores = NonZeroUsize::new(num_cpus::get()).unwrap();
if cores > number_cores {
cores = number_cores;
}
let paths: Vec<PathBuf> = paths.into_iter().map(|p| p.into()).collect();
#[allow(clippy::type_complexity)]
let (tx, rx): (
mpsc::Sender<(PathBuf, BlissResult<Song>)>,
mpsc::Receiver<(PathBuf, BlissResult<Song>)>,
) = mpsc::channel();
if paths.is_empty() {
return rx.into_iter();
}
let mut handles = Vec::new();
let mut chunk_length = paths.len() / cores;
if chunk_length == 0 {
chunk_length = paths.len();
}
for chunk in paths.chunks(chunk_length) {
let tx_thread = tx.clone();
let owned_chunk = chunk.to_owned();
let child = thread::spawn(move || {
for path in owned_chunk {
info!("Analyzing file '{:?}'", path);
if let Some(extension) = Path::new(&path).extension() {
let extension = extension.to_string_lossy().to_lowercase();
if extension == "cue" {
match BlissCue::songs_from_path(&path) {
Ok(songs) => {
for song in songs {
tx_thread.send((path.to_owned(), song)).unwrap();
}
}
Err(e) => tx_thread.send((path.to_owned(), Err(e))).unwrap(),
};
continue;
}
}
let song = Song::from_path(&path);
tx_thread.send((path.to_owned(), song)).unwrap();
}
});
handles.push(child);
}
})
.unwrap();
songs
rx.into_iter()
}
#[cfg(test)]
mod tests {
use super::*;
#[cfg(test)]
use pretty_assertions::assert_eq;
#[test]
fn test_send_song() {
@ -157,52 +271,59 @@ mod tests {
}
#[test]
fn test_bulk_analyse() {
let results = bulk_analyse(vec![
String::from("data/s16_mono_22_5kHz.flac"),
String::from("data/s16_mono_22_5kHz.flac"),
String::from("nonexistent"),
String::from("data/s16_stereo_22_5kHz.flac"),
String::from("nonexistent"),
String::from("nonexistent"),
String::from("nonexistent"),
String::from("nonexistent"),
String::from("nonexistent"),
String::from("nonexistent"),
String::from("nonexistent"),
]);
let mut errored_songs: Vec<String> = results
.iter()
.filter_map(|x| x.as_ref().err().map(|x| x.to_string()))
.collect();
errored_songs.sort_by(|a, b| a.cmp(b));
let mut analysed_songs: Vec<String> = results
.iter()
.filter_map(|x| {
x.as_ref()
.ok()
.map(|x| x.path.to_str().unwrap().to_string())
fn test_analyze_paths() {
let paths = vec![
"./data/s16_mono_22_5kHz.flac",
"./data/testcue.cue",
"./data/white_noise.flac",
"definitely-not-existing.foo",
"not-existing.foo",
];
let mut results = analyze_paths(&paths)
.map(|x| match &x.1 {
Ok(s) => (true, s.path.to_owned(), None),
Err(e) => (false, x.0.to_owned(), Some(e.to_string())),
})
.collect();
analysed_songs.sort_by(|a, b| a.cmp(b));
.collect::<Vec<_>>();
results.sort();
let expected_results = vec![
(
false,
PathBuf::from("./data/testcue.cue"),
Some(String::from(
"error happened while decoding file while opening song: Os { code: 2, kind: NotFound, message: \"No such file or directory\" }.",
)),
),
(
false,
PathBuf::from("definitely-not-existing.foo"),
Some(String::from(
"error happened while decoding file while opening song: Os { code: 2, kind: NotFound, message: \"No such file or directory\" }.",
)),
),
(
false,
PathBuf::from("not-existing.foo"),
Some(String::from(
"error happened while decoding file while opening song: Os { code: 2, kind: NotFound, message: \"No such file or directory\" }.",
)),
),
(true, PathBuf::from("./data/s16_mono_22_5kHz.flac"), None),
(true, PathBuf::from("./data/testcue.cue/CUE_TRACK001"), None),
(true, PathBuf::from("./data/testcue.cue/CUE_TRACK002"), None),
(true, PathBuf::from("./data/testcue.cue/CUE_TRACK003"), None),
(true, PathBuf::from("./data/white_noise.flac"), None),
];
assert_eq!(
vec![
String::from(
"error happened while decoding file while opening format: ffmpeg::Error(2: No such file or directory)."
);
8
],
errored_songs
);
assert_eq!(
vec![
String::from("data/s16_mono_22_5kHz.flac"),
String::from("data/s16_mono_22_5kHz.flac"),
String::from("data/s16_stereo_22_5kHz.flac"),
],
analysed_songs,
);
assert_eq!(results, expected_results);
let mut results = analyze_paths_with_cores(&paths, NonZeroUsize::new(1).unwrap())
.map(|x| match &x.1 {
Ok(s) => (true, s.path.to_owned(), None),
Err(e) => (false, x.0.to_owned(), Some(e.to_string())),
})
.collect::<Vec<_>>();
results.sort();
assert_eq!(results, expected_results);
}
}

File diff suppressed because it is too large Load diff

984
src/playlist.rs Normal file
View file

@ -0,0 +1,984 @@
//! Module containing various functions to build playlists, as well as various
//! distance metrics.
//!
//! All of the distance functions are intended to be used with the
//! [custom_distance](Song::custom_distance) method, or with
//!
//! They will yield different styles of playlists, so don't hesitate to
//! experiment with them if the default (euclidean distance for now) doesn't
//! suit you.
// TODO on the `by_key` functions: maybe Fn(&T) -> &Song is enough? Compared
// to -> Song
use crate::{BlissError, BlissResult, Song, NUMBER_FEATURES};
use ndarray::{Array, Array1, Array2, Axis};
use ndarray_stats::QuantileExt;
use noisy_float::prelude::*;
use std::collections::HashMap;
/// Convenience trait for user-defined distance metrics.
pub trait DistanceMetric: Fn(&Array1<f32>, &Array1<f32>) -> f32 {}
impl<F> DistanceMetric for F where F: Fn(&Array1<f32>, &Array1<f32>) -> f32 {}
/// Return the [euclidean
/// distance](https://en.wikipedia.org/wiki/Euclidean_distance#Higher_dimensions)
/// between two vectors.
pub fn euclidean_distance(a: &Array1<f32>, b: &Array1<f32>) -> f32 {
// Could be any square symmetric positive semi-definite matrix;
// just no metric learning has been done yet.
// See https://lelele.io/thesis.pdf chapter 4.
let m = Array::eye(NUMBER_FEATURES);
(a - b).dot(&m).dot(&(a - b)).sqrt()
}
/// Return the [cosine
/// distance](https://en.wikipedia.org/wiki/Cosine_similarity#Angular_distance_and_similarity)
/// between two vectors.
pub fn cosine_distance(a: &Array1<f32>, b: &Array1<f32>) -> f32 {
let similarity = a.dot(b) / (a.dot(a).sqrt() * b.dot(b).sqrt());
1. - similarity
}
/// Sort `songs` in place by putting songs close to `first_song` first
/// using the `distance` metric.
pub fn closest_to_first_song(
first_song: &Song,
#[allow(clippy::ptr_arg)] songs: &mut Vec<Song>,
distance: impl DistanceMetric,
) {
songs.sort_by_cached_key(|song| n32(first_song.custom_distance(song, &distance)));
}
/// Sort `songs` in place by putting songs close to `first_song` first
/// using the `distance` metric.
///
/// Sort songs with a key extraction function, useful for when you have a
/// structure like `CustomSong { bliss_song: Song, something_else: bool }`
pub fn closest_to_first_song_by_key<F, T>(
first_song: &T,
#[allow(clippy::ptr_arg)] songs: &mut Vec<T>,
distance: impl DistanceMetric,
key_fn: F,
) where
F: Fn(&T) -> Song,
{
let first_song = key_fn(first_song);
songs.sort_by_cached_key(|song| n32(first_song.custom_distance(&key_fn(song), &distance)));
}
/// Sort `songs` in place using the `distance` metric and ordering by
/// the smallest distance between each song.
///
/// If the generated playlist is `[song1, song2, song3, song4]`, it means
/// song2 is closest to song1, song3 is closest to song2, and song4 is closest
/// to song3.
///
/// Note that this has a tendency to go from one style to the other very fast,
/// and it can be slow on big libraries.
pub fn song_to_song(first_song: &Song, songs: &mut Vec<Song>, distance: impl DistanceMetric) {
let mut new_songs = Vec::with_capacity(songs.len());
let mut song = first_song.to_owned();
while !songs.is_empty() {
let distances: Array1<f32> =
Array::from_shape_fn(songs.len(), |i| song.custom_distance(&songs[i], &distance));
let idx = distances.argmin().unwrap();
song = songs[idx].to_owned();
new_songs.push(song.to_owned());
songs.retain(|s| s != &song);
}
*songs = new_songs;
}
/// Sort `songs` in place using the `distance` metric and ordering by
/// the smallest distance between each song.
///
/// If the generated playlist is `[song1, song2, song3, song4]`, it means
/// song2 is closest to song1, song3 is closest to song2, and song4 is closest
/// to song3.
///
/// Note that this has a tendency to go from one style to the other very fast,
/// and it can be slow on big libraries.
///
/// Sort songs with a key extraction function, useful for when you have a
/// structure like `CustomSong { bliss_song: Song, something_else: bool }`
// TODO: maybe Clone is not needed?
pub fn song_to_song_by_key<F, T: std::cmp::PartialEq + Clone>(
first_song: &T,
songs: &mut Vec<T>,
distance: impl DistanceMetric,
key_fn: F,
) where
F: Fn(&T) -> Song,
{
let mut new_songs: Vec<T> = Vec::with_capacity(songs.len());
let mut bliss_song = key_fn(&first_song.to_owned());
while !songs.is_empty() {
let distances: Array1<f32> = Array::from_shape_fn(songs.len(), |i| {
bliss_song.custom_distance(&key_fn(&songs[i]), &distance)
});
let idx = distances.argmin().unwrap();
let song = songs[idx].to_owned();
bliss_song = key_fn(&songs[idx]).to_owned();
new_songs.push(song.to_owned());
songs.retain(|s| s != &song);
}
*songs = new_songs;
}
/// Remove duplicate songs from a playlist, in place.
///
/// Two songs are considered duplicates if they either have the same,
/// non-empty title and artist name, or if they are close enough in terms
/// of distance.
///
/// # Arguments
///
/// * `songs`: The playlist to remove duplicates from.
/// * `distance_threshold`: The distance threshold under which two songs are
/// considered identical. If `None`, a default value of 0.05 will be used.
pub fn dedup_playlist(songs: &mut Vec<Song>, distance_threshold: Option<f32>) {
dedup_playlist_custom_distance(songs, distance_threshold, euclidean_distance);
}
/// Remove duplicate songs from a playlist, in place.
///
/// Two songs are considered duplicates if they either have the same,
/// non-empty title and artist name, or if they are close enough in terms
/// of distance.
///
/// Dedup songs with a key extraction function, useful for when you have a
/// structure like `CustomSong { bliss_song: Song, something_else: bool }` you
/// want to deduplicate.
///
/// # Arguments
///
/// * `songs`: The playlist to remove duplicates from.
/// * `distance_threshold`: The distance threshold under which two songs are
/// considered identical. If `None`, a default value of 0.05 will be used.
/// * `key_fn`: A function used to retrieve the bliss [Song] from `T`.
pub fn dedup_playlist_by_key<T, F>(songs: &mut Vec<T>, distance_threshold: Option<f32>, key_fn: F)
where
F: Fn(&T) -> Song,
{
dedup_playlist_custom_distance_by_key(songs, distance_threshold, euclidean_distance, key_fn);
}
/// Remove duplicate songs from a playlist, in place, using a custom distance
/// metric.
///
/// Two songs are considered duplicates if they either have the same,
/// non-empty title and artist name, or if they are close enough in terms
/// of distance.
///
/// # Arguments
///
/// * `songs`: The playlist to remove duplicates from.
/// * `distance_threshold`: The distance threshold under which two songs are
/// considered identical. If `None`, a default value of 0.05 will be used.
/// * `distance`: A custom distance metric.
pub fn dedup_playlist_custom_distance(
songs: &mut Vec<Song>,
distance_threshold: Option<f32>,
distance: impl DistanceMetric,
) {
songs.dedup_by(|s1, s2| {
n32(s1.custom_distance(s2, &distance)) < distance_threshold.unwrap_or(0.05)
|| (s1.title.is_some()
&& s2.title.is_some()
&& s1.artist.is_some()
&& s2.artist.is_some()
&& s1.title == s2.title
&& s1.artist == s2.artist)
});
}
/// Remove duplicate songs from a playlist, in place, using a custom distance
/// metric.
///
/// Two songs are considered duplicates if they either have the same,
/// non-empty title and artist name, or if they are close enough in terms
/// of distance.
///
/// Dedup songs with a key extraction function, useful for when you have a
/// structure like `CustomSong { bliss_song: Song, something_else: bool }`
/// you want to deduplicate.
///
/// # Arguments
///
/// * `songs`: The playlist to remove duplicates from.
/// * `distance_threshold`: The distance threshold under which two songs are
/// considered identical. If `None`, a default value of 0.05 will be used.
/// * `distance`: A custom distance metric.
/// * `key_fn`: A function used to retrieve the bliss [Song] from `T`.
pub fn dedup_playlist_custom_distance_by_key<F, T>(
songs: &mut Vec<T>,
distance_threshold: Option<f32>,
distance: impl DistanceMetric,
key_fn: F,
) where
F: Fn(&T) -> Song,
{
songs.dedup_by(|s1, s2| {
let s1 = key_fn(s1);
let s2 = key_fn(s2);
n32(s1.custom_distance(&s2, &distance)) < distance_threshold.unwrap_or(0.05)
|| (s1.title.is_some()
&& s2.title.is_some()
&& s1.artist.is_some()
&& s2.artist.is_some()
&& s1.title == s2.title
&& s1.artist == s2.artist)
});
}
/// Return a list of albums in a `pool` of songs that are similar to
/// songs in `group`, discarding songs that don't belong to an album.
/// It basically makes an "album" playlist from the `pool` of songs.
///
/// `group` should be ordered by track number.
///
/// Songs from `group` would usually just be songs from an album, but not
/// necessarily - they are discarded from `pool` no matter what.
///
/// # Arguments
///
/// * `group` - A small group of songs, e.g. an album.
/// * `pool` - A pool of songs to find similar songs in, e.g. a user's song
/// library.
///
/// # Returns
///
/// A vector of songs, including `group` at the beginning, that you
/// most likely want to plug in your audio player by using something like
/// `ret.map(|song| song.path.to_owned()).collect::<Vec<String>>()`.
pub fn closest_album_to_group(group: Vec<Song>, pool: Vec<Song>) -> BlissResult<Vec<Song>> {
let mut albums_analysis: HashMap<&str, Array2<f32>> = HashMap::new();
let mut albums = Vec::new();
// Remove songs from the group from the pool.
let pool = pool
.into_iter()
.filter(|s| !group.contains(s))
.collect::<Vec<_>>();
for song in &pool {
if let Some(album) = &song.album {
if let Some(analysis) = albums_analysis.get_mut(album as &str) {
analysis
.push_row(song.analysis.as_arr1().view())
.map_err(|e| {
BlissError::ProviderError(format!("while computing distances: {}", e))
})?;
} else {
let mut array = Array::zeros((1, song.analysis.as_arr1().len()));
array.assign(&song.analysis.as_arr1());
albums_analysis.insert(album, array);
}
}
}
let mut group_analysis = Array::zeros((group.len(), NUMBER_FEATURES));
for (song, mut column) in group.iter().zip(group_analysis.axis_iter_mut(Axis(0))) {
column.assign(&song.analysis.as_arr1());
}
let first_analysis = group_analysis
.mean_axis(Axis(0))
.ok_or_else(|| BlissError::ProviderError(String::from("Mean of empty slice")))?;
for (album, analysis) in albums_analysis.iter() {
let mean_analysis = analysis
.mean_axis(Axis(0))
.ok_or_else(|| BlissError::ProviderError(String::from("Mean of empty slice")))?;
let album = album.to_owned();
albums.push((album, mean_analysis.to_owned()));
}
albums.sort_by_key(|(_, analysis)| n32(euclidean_distance(&first_analysis, analysis)));
let mut playlist = group;
for (album, _) in albums {
let mut al = pool
.iter()
.filter(|s| s.album.is_some() && s.album.as_ref().unwrap() == &album.to_string())
.map(|s| s.to_owned())
.collect::<Vec<Song>>();
al.sort_by(|s1, s2| {
let track_number1 = s1
.track_number
.to_owned()
.unwrap_or_else(|| String::from(""));
let track_number2 = s2
.track_number
.to_owned()
.unwrap_or_else(|| String::from(""));
if let Ok(x) = track_number1.parse::<i32>() {
if let Ok(y) = track_number2.parse::<i32>() {
return x.cmp(&y);
}
}
s1.track_number.cmp(&s2.track_number)
});
playlist.extend_from_slice(&al);
}
Ok(playlist)
}
/// Return a list of albums in a `pool` of songs that are similar to
/// songs in `group`, discarding songs that don't belong to an album.
/// It basically makes an "album" playlist from the `pool` of songs.
///
/// `group` should be ordered by track number.
///
/// Songs from `group` would usually just be songs from an album, but not
/// necessarily - they are discarded from `pool` no matter what.
///
/// Order songs with a key extraction function, useful for when you have a
/// structure like `CustomSong { bliss_song: Song, something_else: bool }`
/// you want to order.
///
/// # Arguments
///
/// * `group` - A small group of songs, e.g. an album.
/// * `pool` - A pool of songs to find similar songs in, e.g. a user's song
/// library.
/// * `key_fn`: A function used to retrieve the bliss [Song] from `T`.
///
/// # Returns
///
/// A vector of T, including `group` at the beginning, that you
/// most likely want to plug in your audio player by using something like
/// `ret.map(|song| song.path.to_owned()).collect::<Vec<String>>()`.
// TODO: maybe Clone is not needed?
pub fn closest_album_to_group_by_key<T: PartialEq + Clone, F>(
group: Vec<T>,
pool: Vec<T>,
key_fn: F,
) -> BlissResult<Vec<T>>
where
F: Fn(&T) -> Song,
{
let mut albums_analysis: HashMap<String, Array2<f32>> = HashMap::new();
let mut albums = Vec::new();
// Remove songs from the group from the pool.
let pool = pool
.into_iter()
.filter(|s| !group.contains(s))
.collect::<Vec<_>>();
for song in &pool {
let song = key_fn(song);
if let Some(album) = song.album {
if let Some(analysis) = albums_analysis.get_mut(&album as &str) {
analysis
.push_row(song.analysis.as_arr1().view())
.map_err(|e| {
BlissError::ProviderError(format!("while computing distances: {}", e))
})?;
} else {
let mut array = Array::zeros((1, song.analysis.as_arr1().len()));
array.assign(&song.analysis.as_arr1());
albums_analysis.insert(album.to_owned(), array);
}
}
}
let mut group_analysis = Array::zeros((group.len(), NUMBER_FEATURES));
for (song, mut column) in group.iter().zip(group_analysis.axis_iter_mut(Axis(0))) {
let song = key_fn(song);
column.assign(&song.analysis.as_arr1());
}
let first_analysis = group_analysis
.mean_axis(Axis(0))
.ok_or_else(|| BlissError::ProviderError(String::from("Mean of empty slice")))?;
for (album, analysis) in albums_analysis.iter() {
let mean_analysis = analysis
.mean_axis(Axis(0))
.ok_or_else(|| BlissError::ProviderError(String::from("Mean of empty slice")))?;
let album = album.to_owned();
albums.push((album, mean_analysis.to_owned()));
}
albums.sort_by_key(|(_, analysis)| n32(euclidean_distance(&first_analysis, analysis)));
let mut playlist = group;
for (album, _) in albums {
let mut al = pool
.iter()
.filter(|s| {
let s = key_fn(s);
s.album.is_some() && s.album.as_ref().unwrap() == &album.to_string()
})
.map(|s| s.to_owned())
.collect::<Vec<T>>();
al.sort_by(|s1, s2| {
let s1 = key_fn(s1);
let s2 = key_fn(s2);
let track_number1 = s1
.track_number
.to_owned()
.unwrap_or_else(|| String::from(""));
let track_number2 = s2
.track_number
.to_owned()
.unwrap_or_else(|| String::from(""));
if let Ok(x) = track_number1.parse::<i32>() {
if let Ok(y) = track_number2.parse::<i32>() {
return x.cmp(&y);
}
}
s1.track_number.cmp(&s2.track_number)
});
playlist.extend_from_slice(&al);
}
Ok(playlist)
}
#[cfg(test)]
mod test {
use super::*;
use crate::Analysis;
use ndarray::arr1;
use std::path::Path;
#[derive(Debug, Clone, PartialEq)]
struct CustomSong {
something: bool,
bliss_song: Song,
}
#[test]
fn test_dedup_playlist_custom_distance() {
let first_song = Song {
path: Path::new("path-to-first").to_path_buf(),
analysis: Analysis::new([
1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1.,
]),
..Default::default()
};
let first_song_dupe = Song {
path: Path::new("path-to-dupe").to_path_buf(),
analysis: Analysis::new([
1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1.,
]),
..Default::default()
};
let second_song = Song {
path: Path::new("path-to-second").to_path_buf(),
analysis: Analysis::new([
2., 2., 2., 2., 2., 2., 2., 2., 2., 2., 2., 2., 2., 2., 2., 2., 1.9, 1., 1., 1.,
]),
title: Some(String::from("dupe-title")),
artist: Some(String::from("dupe-artist")),
..Default::default()
};
let third_song = Song {
path: Path::new("path-to-third").to_path_buf(),
title: Some(String::from("dupe-title")),
artist: Some(String::from("dupe-artist")),
analysis: Analysis::new([
2., 2., 2., 2., 2., 2., 2., 2., 2., 2., 2., 2., 2., 2., 2., 2., 2.5, 1., 1., 1.,
]),
..Default::default()
};
let fourth_song = Song {
path: Path::new("path-to-fourth").to_path_buf(),
artist: Some(String::from("no-dupe-artist")),
title: Some(String::from("dupe-title")),
analysis: Analysis::new([
2., 2., 2., 2., 2., 2., 2., 2., 2., 2., 2., 2., 2., 2., 2., 2., 0., 1., 1., 1.,
]),
..Default::default()
};
let fifth_song = Song {
path: Path::new("path-to-fourth").to_path_buf(),
analysis: Analysis::new([
2., 2., 2., 2., 2., 2., 2., 2., 2., 2., 2., 2., 2., 2., 2., 2., 0.001, 1., 1., 1.,
]),
..Default::default()
};
let mut playlist = vec![
first_song.to_owned(),
first_song_dupe.to_owned(),
second_song.to_owned(),
third_song.to_owned(),
fourth_song.to_owned(),
fifth_song.to_owned(),
];
dedup_playlist_custom_distance(&mut playlist, None, euclidean_distance);
assert_eq!(
playlist,
vec![
first_song.to_owned(),
second_song.to_owned(),
fourth_song.to_owned(),
],
);
let mut playlist = vec![
first_song.to_owned(),
first_song_dupe.to_owned(),
second_song.to_owned(),
third_song.to_owned(),
fourth_song.to_owned(),
fifth_song.to_owned(),
];
dedup_playlist_custom_distance(&mut playlist, Some(20.), cosine_distance);
assert_eq!(playlist, vec![first_song.to_owned()]);
let mut playlist = vec![
first_song.to_owned(),
first_song_dupe.to_owned(),
second_song.to_owned(),
third_song.to_owned(),
fourth_song.to_owned(),
fifth_song.to_owned(),
];
dedup_playlist(&mut playlist, Some(20.));
assert_eq!(playlist, vec![first_song.to_owned()]);
let mut playlist = vec![
first_song.to_owned(),
first_song_dupe.to_owned(),
second_song.to_owned(),
third_song.to_owned(),
fourth_song.to_owned(),
fifth_song.to_owned(),
];
dedup_playlist(&mut playlist, None);
assert_eq!(
playlist,
vec![
first_song.to_owned(),
second_song.to_owned(),
fourth_song.to_owned(),
]
);
let first_song = CustomSong {
bliss_song: first_song,
something: true,
};
let second_song = CustomSong {
bliss_song: second_song,
something: true,
};
let first_song_dupe = CustomSong {
bliss_song: first_song_dupe,
something: true,
};
let third_song = CustomSong {
bliss_song: third_song,
something: true,
};
let fourth_song = CustomSong {
bliss_song: fourth_song,
something: true,
};
let fifth_song = CustomSong {
bliss_song: fifth_song,
something: true,
};
let mut playlist = vec![
first_song.to_owned(),
first_song_dupe.to_owned(),
second_song.to_owned(),
third_song.to_owned(),
fourth_song.to_owned(),
fifth_song.to_owned(),
];
dedup_playlist_custom_distance_by_key(&mut playlist, None, euclidean_distance, |s| {
s.bliss_song.to_owned()
});
assert_eq!(
playlist,
vec![
first_song.to_owned(),
second_song.to_owned(),
fourth_song.to_owned(),
],
);
let mut playlist = vec![
first_song.to_owned(),
first_song_dupe.to_owned(),
second_song.to_owned(),
third_song.to_owned(),
fourth_song.to_owned(),
fifth_song.to_owned(),
];
dedup_playlist_custom_distance_by_key(&mut playlist, Some(20.), cosine_distance, |s| {
s.bliss_song.to_owned()
});
assert_eq!(playlist, vec![first_song.to_owned()]);
let mut playlist = vec![
first_song.to_owned(),
first_song_dupe.to_owned(),
second_song.to_owned(),
third_song.to_owned(),
fourth_song.to_owned(),
fifth_song.to_owned(),
];
dedup_playlist_by_key(&mut playlist, Some(20.), |s| s.bliss_song.to_owned());
assert_eq!(playlist, vec![first_song.to_owned()]);
let mut playlist = vec![
first_song.to_owned(),
first_song_dupe.to_owned(),
second_song.to_owned(),
third_song.to_owned(),
fourth_song.to_owned(),
fifth_song.to_owned(),
];
dedup_playlist_by_key(&mut playlist, None, |s| s.bliss_song.to_owned());
assert_eq!(
playlist,
vec![
first_song.to_owned(),
second_song.to_owned(),
fourth_song.to_owned(),
]
);
}
#[test]
fn test_song_to_song() {
let first_song = Song {
path: Path::new("path-to-first").to_path_buf(),
analysis: Analysis::new([
1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1.,
]),
..Default::default()
};
let first_song_dupe = Song {
path: Path::new("path-to-dupe").to_path_buf(),
analysis: Analysis::new([
1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1.,
]),
..Default::default()
};
let second_song = Song {
path: Path::new("path-to-second").to_path_buf(),
analysis: Analysis::new([
2., 2., 2., 2., 2., 2., 2., 2., 2., 2., 2., 2., 2., 2., 2., 2., 1.9, 1., 1., 1.,
]),
..Default::default()
};
let third_song = Song {
path: Path::new("path-to-third").to_path_buf(),
analysis: Analysis::new([
2., 2., 2., 2., 2., 2., 2., 2., 2., 2., 2., 2., 2., 2., 2., 2., 2.5, 1., 1., 1.,
]),
..Default::default()
};
let fourth_song = Song {
path: Path::new("path-to-fourth").to_path_buf(),
analysis: Analysis::new([
2., 2., 2., 2., 2., 2., 2., 2., 2., 2., 2., 2., 2., 2., 2., 2., 0., 1., 1., 1.,
]),
..Default::default()
};
let mut songs = vec![
first_song.to_owned(),
third_song.to_owned(),
first_song_dupe.to_owned(),
second_song.to_owned(),
fourth_song.to_owned(),
];
song_to_song(&first_song, &mut songs, euclidean_distance);
assert_eq!(
songs,
vec![
first_song.to_owned(),
first_song_dupe.to_owned(),
second_song.to_owned(),
third_song.to_owned(),
fourth_song.to_owned(),
],
);
let first_song = CustomSong {
bliss_song: first_song,
something: true,
};
let second_song = CustomSong {
bliss_song: second_song,
something: true,
};
let first_song_dupe = CustomSong {
bliss_song: first_song_dupe,
something: true,
};
let third_song = CustomSong {
bliss_song: third_song,
something: true,
};
let fourth_song = CustomSong {
bliss_song: fourth_song,
something: true,
};
let mut songs: Vec<CustomSong> = vec![
first_song.to_owned(),
first_song_dupe.to_owned(),
third_song.to_owned(),
fourth_song.to_owned(),
second_song.to_owned(),
];
song_to_song_by_key(&first_song, &mut songs, euclidean_distance, |s| {
s.bliss_song.to_owned()
});
assert_eq!(
songs,
vec![
first_song,
first_song_dupe,
second_song,
third_song,
fourth_song,
],
);
}
#[test]
fn test_sort_closest_to_first_song() {
let first_song = Song {
path: Path::new("path-to-first").to_path_buf(),
analysis: Analysis::new([
1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1.,
]),
..Default::default()
};
let first_song_dupe = Song {
path: Path::new("path-to-dupe").to_path_buf(),
analysis: Analysis::new([
1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1.,
]),
..Default::default()
};
let second_song = Song {
path: Path::new("path-to-second").to_path_buf(),
analysis: Analysis::new([
2., 2., 2., 2., 2., 2., 2., 2., 2., 2., 2., 2., 2., 2., 2., 2., 1.9, 1., 1., 1.,
]),
..Default::default()
};
let third_song = Song {
path: Path::new("path-to-third").to_path_buf(),
analysis: Analysis::new([
2., 2., 2., 2., 2., 2., 2., 2., 2., 2., 2., 2., 2., 2., 2., 2., 2.5, 1., 1., 1.,
]),
..Default::default()
};
let fourth_song = Song {
path: Path::new("path-to-fourth").to_path_buf(),
analysis: Analysis::new([
2., 2., 2., 2., 2., 2., 2., 2., 2., 2., 2., 2., 2., 2., 2., 2., 0., 1., 1., 1.,
]),
..Default::default()
};
let fifth_song = Song {
path: Path::new("path-to-fifth").to_path_buf(),
analysis: Analysis::new([
2., 2., 2., 2., 2., 2., 2., 2., 2., 2., 2., 2., 2., 2., 2., 2., 0., 1., 1., 1.,
]),
..Default::default()
};
let mut songs = vec![
first_song.to_owned(),
first_song_dupe.to_owned(),
second_song.to_owned(),
third_song.to_owned(),
fourth_song.to_owned(),
fifth_song.to_owned(),
];
closest_to_first_song(&first_song, &mut songs, euclidean_distance);
let first_song = CustomSong {
bliss_song: first_song,
something: true,
};
let second_song = CustomSong {
bliss_song: second_song,
something: true,
};
let first_song_dupe = CustomSong {
bliss_song: first_song_dupe,
something: true,
};
let third_song = CustomSong {
bliss_song: third_song,
something: true,
};
let fourth_song = CustomSong {
bliss_song: fourth_song,
something: true,
};
let fifth_song = CustomSong {
bliss_song: fifth_song,
something: true,
};
let mut songs: Vec<CustomSong> = vec![
first_song.to_owned(),
first_song_dupe.to_owned(),
second_song.to_owned(),
third_song.to_owned(),
fourth_song.to_owned(),
fifth_song.to_owned(),
];
closest_to_first_song_by_key(&first_song, &mut songs, euclidean_distance, |s| {
s.bliss_song.to_owned()
});
assert_eq!(
songs,
vec![
first_song,
first_song_dupe,
second_song,
fourth_song,
fifth_song,
third_song
],
);
}
#[test]
fn test_euclidean_distance() {
let a = arr1(&[
1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 0.,
]);
let b = arr1(&[
0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 1., 0., 0., 0.,
]);
assert_eq!(euclidean_distance(&a, &b), 4.242640687119285);
let a = arr1(&[0.5; 20]);
let b = arr1(&[0.5; 20]);
assert_eq!(euclidean_distance(&a, &b), 0.);
assert_eq!(euclidean_distance(&a, &b), 0.);
}
#[test]
fn test_cosine_distance() {
let a = arr1(&[
1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 0.,
]);
let b = arr1(&[
0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 1., 0., 0., 0.,
]);
assert_eq!(cosine_distance(&a, &b), 0.7705842661294382);
let a = arr1(&[0.5; 20]);
let b = arr1(&[0.5; 20]);
assert_eq!(cosine_distance(&a, &b), 0.);
assert_eq!(cosine_distance(&a, &b), 0.);
}
#[test]
fn test_closest_to_group() {
let first_song = Song {
path: Path::new("path-to-first").to_path_buf(),
analysis: Analysis::new([0.; 20]),
album: Some(String::from("Album")),
artist: Some(String::from("Artist")),
track_number: Some(String::from("01")),
..Default::default()
};
let second_song = Song {
path: Path::new("path-to-second").to_path_buf(),
analysis: Analysis::new([0.1; 20]),
album: Some(String::from("Another Album")),
artist: Some(String::from("Artist")),
track_number: Some(String::from("10")),
..Default::default()
};
let third_song = Song {
path: Path::new("path-to-third").to_path_buf(),
analysis: Analysis::new([10.; 20]),
album: Some(String::from("Album")),
artist: Some(String::from("Another Artist")),
track_number: Some(String::from("02")),
..Default::default()
};
let fourth_song = Song {
path: Path::new("path-to-fourth").to_path_buf(),
analysis: Analysis::new([20.; 20]),
album: Some(String::from("Another Album")),
artist: Some(String::from("Another Artist")),
track_number: Some(String::from("01")),
..Default::default()
};
let fifth_song = Song {
path: Path::new("path-to-fifth").to_path_buf(),
analysis: Analysis::new([40.; 20]),
artist: Some(String::from("Third Artist")),
album: None,
..Default::default()
};
let pool = vec![
first_song.to_owned(),
fourth_song.to_owned(),
third_song.to_owned(),
second_song.to_owned(),
fifth_song.to_owned(),
];
let group = vec![first_song.to_owned(), third_song.to_owned()];
assert_eq!(
vec![
first_song.to_owned(),
third_song.to_owned(),
fourth_song.to_owned(),
second_song.to_owned()
],
closest_album_to_group(group, pool.to_owned()).unwrap(),
);
let first_song = CustomSong {
bliss_song: first_song,
something: true,
};
let second_song = CustomSong {
bliss_song: second_song,
something: true,
};
let third_song = CustomSong {
bliss_song: third_song,
something: true,
};
let fourth_song = CustomSong {
bliss_song: fourth_song,
something: true,
};
let fifth_song = CustomSong {
bliss_song: fifth_song,
something: true,
};
let pool = vec![
first_song.to_owned(),
fourth_song.to_owned(),
third_song.to_owned(),
second_song.to_owned(),
fifth_song.to_owned(),
];
let group = vec![first_song.to_owned(), third_song.to_owned()];
assert_eq!(
vec![
first_song.to_owned(),
third_song.to_owned(),
fourth_song.to_owned(),
second_song.to_owned()
],
closest_album_to_group_by_key(group, pool.to_owned(), |s| s.bliss_song.to_owned())
.unwrap(),
);
}
}

View file

@ -8,30 +8,32 @@
//! a look at Library is instead recommended.
extern crate crossbeam;
extern crate ffmpeg_next as ffmpeg;
//extern crate ffmpeg_next as ffmpeg;
extern crate symphonia;
extern crate ndarray;
extern crate ndarray_npy;
use super::CHANNELS;
use crate::chroma::ChromaDesc;
use crate::distance::{euclidean_distance, DistanceMetric};
use crate::cue::CueInfo;
use crate::misc::LoudnessDesc;
#[cfg(doc)]
use crate::playlist;
use crate::playlist::{closest_to_first_song, dedup_playlist, euclidean_distance, DistanceMetric};
use crate::temporal::BPMDesc;
use crate::timbral::{SpectralDesc, ZeroCrossingRateDesc};
use crate::{BlissError, BlissResult, SAMPLE_RATE};
use crate::{FEATURES_VERSION};
use ::log::warn;
use core::ops::Index;
use crossbeam::thread;
use ffmpeg_next::codec::threading::{Config, Type as ThreadingType};
use ffmpeg_next::software::resampling::context::Context;
use ffmpeg_next::util;
use ffmpeg_next::util::channel_layout::ChannelLayout;
use ffmpeg_next::util::error::Error;
use ffmpeg_next::util::error::EINVAL;
use ffmpeg_next::util::format::sample::{Sample, Type};
use ffmpeg_next::util::frame::audio::Audio;
use ffmpeg_next::util::log;
use ffmpeg_next::util::log::level::Level;
use symphonia::core::formats::{SeekMode, SeekTo};
use symphonia::core::io::MediaSourceStream;
use symphonia::core::probe::Hint;
use symphonia::core::errors::Error as SymphoniaError;
use symphonia::core::audio::{AudioBuffer, AudioBufferRef, Signal};
use symphonia::core::meta::{MetadataRevision, StandardTagKey};
use rubato::Resampler;
use rubato::FftFixedIn as ResamplerImpl;
use ndarray::{arr1, Array1};
use std::convert::TryInto;
use std::fmt;
@ -40,6 +42,7 @@ use std::path::PathBuf;
use std::sync::mpsc;
use std::sync::mpsc::Receiver;
use std::thread as std_thread;
use std::time::Duration;
use strum::{EnumCount, IntoEnumIterator};
use strum_macros::{EnumCount, EnumIter};
@ -56,12 +59,27 @@ pub struct Song {
pub title: Option<String>,
/// Song's album name, read from the metadata
pub album: Option<String>,
/// Song's album's artist name, read from the metadata
pub album_artist: Option<String>,
/// Song's tracked number, read from the metadata
/// TODO normalize this into an integer
pub track_number: Option<String>,
/// Song's genre, read from the metadata (`""` if empty)
pub genre: Option<String>,
/// bliss analysis results
pub analysis: Analysis,
/// The song's duration
pub duration: Duration,
/// Version of the features the song was analyzed with.
/// A simple integer that is bumped every time a breaking change
/// is introduced in the features.
pub features_version: u16,
/// Populated only if the song was extracted from a larger audio file,
/// through the use of a CUE sheet.
/// By default, such a song's path would be
/// `path/to/cue_file.wav/CUE_TRACK00<track_number>`. Using this field,
/// you can change `song.path` to fit your needs.
pub cue_info: Option<CueInfo>,
}
#[derive(Debug, EnumIter, EnumCount)]
@ -72,7 +90,7 @@ pub struct Song {
/// use bliss_audio::{AnalysisIndex, BlissResult, Song};
///
/// fn main() -> BlissResult<()> {
/// let song = Song::new("path/to/song")?;
/// let song = Song::from_path("path/to/song")?;
/// println!("{}", song.analysis[AnalysisIndex::Tempo]);
/// Ok(())
/// }
@ -115,7 +133,7 @@ pub const NUMBER_FEATURES: usize = AnalysisIndex::COUNT;
/// Only use it if you want to have an in-depth look of what is
/// happening behind the scene, or make a distance metric yourself.
///
/// Under the hood, it is just an array of f32 holding different numeric
/// Under the hood, it is just an array of f32 holding different nsrcumeric
/// features.
///
/// For more info on the different features, build the
@ -125,7 +143,7 @@ pub const NUMBER_FEATURES: usize = AnalysisIndex::COUNT;
/// on most of the features, except the chroma ones, which are documented
/// directly in this code.
pub struct Analysis {
internal_analysis: [f32; NUMBER_FEATURES],
pub(crate) internal_analysis: [f32; NUMBER_FEATURES],
}
impl Index<AnalysisIndex> for Analysis {
@ -143,7 +161,7 @@ impl fmt::Debug for Analysis {
debug_struct.field(&format!("{:?}", feature), &self[feature]);
}
debug_struct.finish()?;
f.write_str(&format!(" /* {:?} */", &self.to_vec()))
f.write_str(&format!(" /* {:?} */", &self.as_vec()))
}
}
@ -162,7 +180,7 @@ impl Analysis {
/// Return an ndarray `Array1` representing the analysis' features.
///
/// Particularly useful if you want to make a custom distance metric.
pub fn to_arr1(&self) -> Array1<f32> {
pub fn as_arr1(&self) -> Array1<f32> {
arr1(&self.internal_analysis)
}
@ -170,7 +188,7 @@ impl Analysis {
///
/// Particularly useful if you want iterate through the values to store
/// them somewhere.
pub fn to_vec(&self) -> Vec<f32> {
pub fn as_vec(&self) -> Vec<f32> {
self.internal_analysis.to_vec()
}
@ -188,7 +206,7 @@ impl Analysis {
/// Note that almost all distance metrics you will find obey these
/// properties, so don't sweat it too much.
pub fn custom_distance(&self, other: &Self, distance: impl DistanceMetric) -> f32 {
distance(&self.to_arr1(), &other.to_arr1())
distance(&self.as_arr1(), &other.as_arr1())
}
}
@ -225,12 +243,50 @@ impl Song {
self.analysis.custom_distance(&other.analysis, distance)
}
/// Returns a decoded Song given a file path, or an error if the song
/// Orders songs in `pool` by proximity to `self`, using the distance
/// metric `distance` to compute the order.
/// Basically return a playlist from songs in `pool`, starting
/// from `self`, using `distance` (some distance metrics can
/// be found in the [playlist] module).
///
/// Note that contrary to [Song::closest_from_pool], `self` is NOT added
/// to the beginning of the returned vector.
///
/// No deduplication is ran either; if you're looking for something easy
/// that works "out of the box", use [Song::closest_from_pool].
pub fn closest_from_pool_custom(
&self,
pool: Vec<Self>,
distance: impl DistanceMetric,
) -> Vec<Self> {
let mut pool = pool;
closest_to_first_song(self, &mut pool, distance);
pool
}
/// Order songs in `pool` by proximity to `self`.
/// Convenience method to return a playlist from songs in `pool`,
/// starting from `self`.
///
/// The distance is already chosen, deduplication is ran, and the first song
/// is added to the top of the playlist, to make everything easier.
///
/// If you want more control over which distance metric is chosen,
/// run deduplication manually, etc, use [Song::closest_from_pool_custom].
pub fn closest_from_pool(&self, pool: Vec<Self>) -> Vec<Self> {
let mut playlist = vec![self.to_owned()];
playlist.extend_from_slice(&pool);
closest_to_first_song(self, &mut playlist, euclidean_distance);
dedup_playlist(&mut playlist, None);
playlist
}
/// Returns a decoded [Song] given a file path, or an error if the song
/// could not be analyzed for some reason.
///
/// # Arguments
///
/// * `path` - A string holding a valid file path to a valid audio file.
/// * `path` - A [Path] holding a valid file path to a valid audio file.
///
/// # Errors
///
@ -241,22 +297,58 @@ impl Song {
/// The error type returned should give a hint as to whether it was a
/// decoding ([DecodingError](BlissError::DecodingError)) or an analysis
/// ([AnalysisError](BlissError::AnalysisError)) error.
pub fn new<P: AsRef<Path>>(path: P) -> BlissResult<Self> {
pub fn from_path<P: AsRef<Path>>(path: P) -> BlissResult<Self> {
let raw_song = Song::decode(path.as_ref())?;
Ok(Song {
path: raw_song.path,
artist: raw_song.artist,
album_artist: raw_song.album_artist,
title: raw_song.title,
album: raw_song.album,
track_number: raw_song.track_number,
genre: raw_song.genre,
analysis: Song::analyse(raw_song.sample_array)?,
duration: raw_song.duration,
analysis: Song::analyze(&raw_song.sample_array)?,
features_version: FEATURES_VERSION,
cue_info: None,
})
}
/// Returns a decoded [Song] given an array of samples, or an error if the song
/// could not be analyzed for some reason.
///
/// # Arguments
///
/// * `samples` - A [Vec] of samples at [SAMPLE_RATE].
///
/// # Errors
///
/// This function will return an error if the analysis could not be conducted for some reason.
///
/// The error type returned should give a hint as to whether it was a
/// decoding ([DecodingError](BlissError::DecodingError)) or an analysis
/// ([AnalysisError](BlissError::AnalysisError)) error.
pub fn from_samples(samples: Vec<f32>) -> BlissResult<Self> {
let raw_song = Song::decode_samples(samples)?;
Ok(Song {
path: raw_song.path,
artist: raw_song.artist,
album_artist: raw_song.album_artist,
title: raw_song.title,
album: raw_song.album,
track_number: raw_song.track_number,
genre: raw_song.genre,
duration: raw_song.duration,
analysis: Song::analyze(&raw_song.sample_array)?,
features_version: FEATURES_VERSION,
cue_info: None,
})
}
/**
* Analyse a song decoded in `sample_array`, with one channel @ 22050 Hz.
* Analyze a song decoded in `sample_array`, with one channel @ 22050 Hz.
*
* The current implementation doesn't make use of it,
* but the song can also be streamed wrt.
@ -266,7 +358,7 @@ impl Song {
* Useful in the rare cases where the full song is not
* completely available.
**/
fn analyse(sample_array: Vec<f32>) -> BlissResult<Analysis> {
pub(crate) fn analyze(sample_array: &[f32]) -> BlissResult<Analysis> {
let largest_window = vec![
BPMDesc::WINDOW_SIZE,
ChromaDesc::WINDOW_SIZE,
@ -290,14 +382,14 @@ impl Song {
.step_by(BPMDesc::HOP_SIZE);
for window in windows {
tempo_desc.do_(&window)?;
tempo_desc.do_(window)?;
}
Ok(tempo_desc.get_value())
});
let child_chroma: thread::ScopedJoinHandle<'_, BlissResult<Vec<f32>>> = s.spawn(|_| {
let mut chroma_desc = ChromaDesc::new(SAMPLE_RATE, 12);
chroma_desc.do_(&sample_array)?;
chroma_desc.do_(sample_array)?;
Ok(chroma_desc.get_values())
});
@ -311,7 +403,7 @@ impl Song {
.windows(SpectralDesc::WINDOW_SIZE)
.step_by(SpectralDesc::HOP_SIZE);
for window in windows {
spectral_desc.do_(&window)?;
spectral_desc.do_(window)?;
}
let centroid = spectral_desc.get_centroid();
let rolloff = spectral_desc.get_rolloff();
@ -321,7 +413,7 @@ impl Song {
let child_zcr: thread::ScopedJoinHandle<'_, BlissResult<f32>> = s.spawn(|_| {
let mut zcr_desc = ZeroCrossingRateDesc::default();
zcr_desc.do_(&sample_array);
zcr_desc.do_(sample_array);
Ok(zcr_desc.get_value())
});
@ -331,7 +423,7 @@ impl Song {
let windows = sample_array.chunks(LoudnessDesc::WINDOW_SIZE);
for window in windows {
loudness_desc.do_(&window);
loudness_desc.do_(window);
}
Ok(loudness_desc.get_value())
});
@ -361,170 +453,136 @@ impl Song {
.unwrap()
}
pub(crate) fn decode_samples(samples: Vec<f32>) -> BlissResult<InternalSong> {
let duration_seconds = samples.len() as f32 / SAMPLE_RATE as f32;
let song = InternalSong {
path: "".into(),
duration: Duration::from_nanos((duration_seconds * 1e9_f32).round() as u64),
sample_array: samples,
..Default::default()
};
Ok(song)
}
pub(crate) fn decode(path: &Path) -> BlissResult<InternalSong> {
ffmpeg::init()
.map_err(|e| BlissError::DecodingError(format!("ffmpeg init error: {:?}.", e)))?;
log::set_level(Level::Quiet);
let registry = symphonia::default::get_codecs();
let probe = symphonia::default::get_probe();
let mut song = InternalSong {
path: path.into(),
..Default::default()
};
let mut format = ffmpeg::format::input(&path)
let song_file = std::fs::File::open(path).map_err(|e| BlissError::DecodingError(format!("while opening song: {:?}.", e)))?;
let stream = MediaSourceStream::new(Box::new(song_file), Default::default());
let mut hint = Hint::new();
if let Some(ext) = path.extension().and_then(|x| x.to_str()) {
hint.with_extension(ext);
}
let mut probed = probe.format(&hint, stream, &Default::default(), &Default::default())
.map_err(|e| BlissError::DecodingError(format!("while opening format: {:?}.", e)))?;
let (mut codec, stream, expected_sample_number) = {
let stream = format
let format = &mut probed.format;
/*let mut format = ffmpeg::format::input(&path)
.map_err(|e| BlissError::DecodingError(format!("while opening format: {:?}.", e)))?;*/
let (mut codec, stream_id, expected_sample_number) = {
let track = format
.tracks()
.into_iter()
.find(|t| t.codec_params.codec != symphonia::core::codecs::CODEC_TYPE_NULL)
.ok_or_else(|| BlissError::DecodingError(String::from("No valid audio stream found.")))?;
let track_id = track.id;
/*let stream = format
.streams()
.find(|s| s.codec().medium() == ffmpeg::media::Type::Audio)
.ok_or_else(|| BlissError::DecodingError(String::from("No audio stream found.")))?;
stream.codec().set_threading(Config {
.ok_or_else(|| BlissError::DecodingError(String::from("No audio stream found.")))?;*/
/*stream.codec().set_threading(Config {
kind: ThreadingType::Frame,
count: 0,
safe: true,
});
let codec =
});*/
let mut decoder = registry
.make(&track.codec_params, &Default::default())
.map_err(|e| BlissError::DecodingError(format!("when finding codec: {:?}.", e)))?;
/*let codec =
stream.codec().decoder().audio().map_err(|e| {
BlissError::DecodingError(format!("when finding codec: {:?}.", e))
})?;
// Add SAMPLE_RATE to have one second margin to avoid reallocating if
// the duration is slightly more than estimated
// TODO>1.0 another way to get the exact number of samples is to decode
// everything once, compute the real number of samples from that,
// allocate the array with that number, and decode again. Check
// what's faster between reallocating, and just have one second
// leeway.
let expected_sample_number = (SAMPLE_RATE as f32 * stream.duration() as f32
/ stream.time_base().denominator() as f32)
.ceil()
+ SAMPLE_RATE as f32;
(codec, stream.index(), expected_sample_number)
};
let sample_array: Vec<f32> = Vec::with_capacity(expected_sample_number as usize);
if let Some(title) = format.metadata().get("title") {
song.title = match title {
"" => None,
t => Some(t.to_string()),
};
};
if let Some(artist) = format.metadata().get("artist") {
song.artist = match artist {
"" => None,
a => Some(a.to_string()),
};
};
if let Some(album) = format.metadata().get("album") {
song.album = match album {
"" => None,
a => Some(a.to_string()),
};
};
if let Some(genre) = format.metadata().get("genre") {
song.genre = match genre {
"" => None,
g => Some(g.to_string()),
};
};
if let Some(track_number) = format.metadata().get("track") {
song.track_number = match track_number {
"" => None,
t => Some(t.to_string()),
};
};
let in_channel_layout = {
if codec.channel_layout() == ChannelLayout::empty() {
ChannelLayout::default(codec.channels().into())
} else {
codec.channel_layout()
})?;*/
let mut expected_sample_number: usize = 0;
// decode once to find sample number
// previously, ffmpeg let us (roughly) calculate this
// symphonia does not make that easy so we just decode twice instead
while let Ok(packet) = format.next_packet() {
if packet.track_id() == track_id {
if let Ok(buffer) = decoder.decode(&packet) {
// errors will only be handled when actually decoding samples
expected_sample_number += sample_buffer_length(buffer);
}
} // else ignore packet
}
// reset decoding to start of audio
format.seek(SeekMode::Accurate, SeekTo::Time {
time: symphonia::core::units::Time {
seconds: 0,
frac: 0.0,
},
track_id: Some(track_id),
}).map_err(|e| BlissError::DecodingError(format!("while seeking to start: {}", e)))?;
decoder.reset();
(decoder, track_id, expected_sample_number)
};
codec.set_channel_layout(in_channel_layout);
let resample_context = ffmpeg::software::resampling::context::Context::get(
codec.format(),
in_channel_layout,
codec.rate(),
Sample::F32(Type::Packed),
ffmpeg::util::channel_layout::ChannelLayout::MONO,
SAMPLE_RATE,
)
.map_err(|e| {
BlissError::DecodingError(format!(
"while trying to allocate resampling context: {:?}",
e
))
})?;
let sample_array: Vec<f32> = Vec::with_capacity(expected_sample_number);
// populate song metadata from file's info tags
if let Some(revision) = format.metadata().current() {
// audio format's built-in tags
song.read_tags(revision);
}
if let Some(metadata) = probed.metadata.get() {
if let Some(revision) = metadata.current() {
// audio wrapper's tags
song.read_tags(revision);
}
}
let (tx, rx) = mpsc::channel();
let child = std_thread::spawn(move || resample_frame(rx, resample_context, sample_array));
for (s, packet) in format.packets() {
if s.index() != stream {
let child = std_thread::spawn(move || {
resample_buffer(
rx,
sample_array,
)
});
loop {
let packet = match format.next_packet() {
Err(SymphoniaError::IoError(_)) => break,
Ok(packet) => packet,
Err(e) => return Err(BlissError::DecodingError(format!("while reading packet: {}", e)))
};
if packet.track_id() != stream_id {
continue;
}
match codec.send_packet(&packet) {
Ok(_) => (),
Err(Error::Other { errno: EINVAL }) => {
return Err(BlissError::DecodingError(String::from(
"wrong codec opened.",
)))
}
Err(Error::Eof) => {
warn!("Premature EOF reached while decoding.");
drop(tx);
song.sample_array = child.join().unwrap()?;
return Ok(song);
}
Err(e) => warn!("decoding error: {}", e),
};
loop {
let mut decoded = ffmpeg::frame::Audio::empty();
match codec.receive_frame(&mut decoded) {
Ok(_) => {
tx.send(decoded).map_err(|e| {
match codec.decode(&packet) {
Ok(decoded) => {
tx.send(convert_sample_buffer(decoded)).map_err(|e| {
BlissError::DecodingError(format!(
"while sending decoded frame to the resampling thread: {:?}",
"while sending decoded frame to the resampling thread for file '{}': {:?}",
path.display(),
e
))
})?;
},
Err(SymphoniaError::Unsupported(s)) => {
return Err(BlissError::DecodingError(format!("unsupported: {}", s)))
}
Err(_) => break,
}
}
}
// Flush the stream
let packet = ffmpeg::codec::packet::Packet::empty();
match codec.send_packet(&packet) {
Ok(_) => (),
Err(Error::Other { errno: EINVAL }) => {
return Err(BlissError::DecodingError(String::from(
"wrong codec opened.",
)))
}
Err(Error::Eof) => {
warn!("Premature EOF reached while decoding.");
Err(SymphoniaError::IoError(e)) => {
warn!("IO error occured while decoding: {}", e);
drop(tx);
song.sample_array = child.join().unwrap()?;
return Ok(song);
}
Err(e) => warn!("decoding error: {}", e),
},
Err(e) => warn!("error while decoding {}: {}", path.display(), e),
};
loop {
let mut decoded = ffmpeg::frame::Audio::empty();
match codec.receive_frame(&mut decoded) {
Ok(_) => {
tx.send(decoded).map_err(|e| {
BlissError::DecodingError(format!(
"while sending decoded frame to the resampling thread: {:?}",
e
))
})?;
}
Err(_) => break,
}
}
drop(tx);
song.sample_array = child.join().unwrap()?;
song.sample_array = child.join().map_err(|_| BlissError::DecodingError(format!("resampler thread panic!")))??;
let duration_seconds = song.sample_array.len() as f32 / SAMPLE_RATE as f32;
song.duration = Duration::from_nanos((duration_seconds * 1e9_f32).round() as u64);
Ok(song)
}
}
@ -533,85 +591,190 @@ impl Song {
pub(crate) struct InternalSong {
pub path: PathBuf,
pub artist: Option<String>,
pub album_artist: Option<String>,
pub title: Option<String>,
pub album: Option<String>,
pub track_number: Option<String>,
pub genre: Option<String>,
pub duration: Duration,
pub sample_array: Vec<f32>,
}
fn resample_frame(
rx: Receiver<Audio>,
mut resample_context: Context,
mut sample_array: Vec<f32>,
) -> BlissResult<Vec<f32>> {
let mut resampled = ffmpeg::frame::Audio::empty();
for decoded in rx.iter() {
resampled = ffmpeg::frame::Audio::empty();
resample_context
.run(&decoded, &mut resampled)
.map_err(|e| {
BlissError::DecodingError(format!("while trying to resample song: {:?}", e))
})?;
push_to_sample_array(&resampled, &mut sample_array);
impl InternalSong {
#[inline]
fn read_tags(&mut self, metadata: &MetadataRevision) {
for tag in metadata.tags() {
if let Some(key) = tag.std_key {
match key {
StandardTagKey::Album => self.album = Some(tag.value.to_string()),
StandardTagKey::AlbumArtist => self.album_artist = Some(tag.value.to_string()),
StandardTagKey::TrackTitle => self.title = Some(tag.value.to_string()),
StandardTagKey::Artist => self.artist = Some(tag.value.to_string()),
StandardTagKey::Genre => self.genre = Some(tag.value.to_string()),
StandardTagKey::TrackNumber => self.track_number = Some(tag.value.to_string()),
_ => {},
}
// TODO when ffmpeg-next will be active again: shouldn't we allocate
// `resampled` again?
loop {
match resample_context.flush(&mut resampled).map_err(|e| {
BlissError::DecodingError(format!("while trying to resample song: {:?}", e))
})? {
Some(_) => {
push_to_sample_array(&resampled, &mut sample_array);
}
None => {
if resampled.samples() == 0 {
break;
}
push_to_sample_array(&resampled, &mut sample_array);
}
};
}
Ok(sample_array)
}
fn push_to_sample_array(frame: &ffmpeg::frame::Audio, sample_array: &mut Vec<f32>) {
if frame.samples() == 0 {
return;
fn convert_sample_buffer(buffer_in: AudioBufferRef) -> AudioBuffer<f32> {
match buffer_in {
AudioBufferRef::F32(buf) => buf.into_owned(),
AudioBufferRef::F64(buf) => {
let mut buffer_out = buf.make_equivalent::<f32>();
// symphonia expects frames to already exist (but since we know we're going to replace them right away, rendering doesn't have to do anything)
buffer_out.render(Some(buf.frames()), |_, _| Ok(())).unwrap_or(());
buf.convert(&mut buffer_out);
buffer_out
},
AudioBufferRef::S16(buf) => {
let mut buffer_out = buf.make_equivalent::<f32>();
// symphonia expects frames to already exist
buffer_out.render(Some(buf.frames()), |_, _| Ok(())).unwrap_or(());
buf.convert(&mut buffer_out);
buffer_out
},
AudioBufferRef::S24(buf) => {
let mut buffer_out = buf.make_equivalent::<f32>();
// symphonia expects frames to already exist
buffer_out.render(Some(buf.frames()), |_, _| Ok(())).unwrap_or(());
buf.convert(&mut buffer_out);
buffer_out
},
AudioBufferRef::S32(buf) => {
let mut buffer_out = buf.make_equivalent::<f32>();
// symphonia expects frames to already exist
buffer_out.render(Some(buf.frames()), |_, _| Ok(())).unwrap_or(());
buf.convert(&mut buffer_out);
buffer_out
},
AudioBufferRef::S8(buf) => {
let mut buffer_out = buf.make_equivalent::<f32>();
// symphonia expects frames to already exist
buffer_out.render(Some(buf.frames()), |_, _| Ok(())).unwrap_or(());
buf.convert(&mut buffer_out);
buffer_out
},
AudioBufferRef::U16(buf) => {
let mut buffer_out = buf.make_equivalent::<f32>();
// symphonia expects frames to already exist
buffer_out.render(Some(buf.frames()), |_, _| Ok(())).unwrap_or(());
buf.convert(&mut buffer_out);
buffer_out
},
AudioBufferRef::U24(buf) => {
let mut buffer_out = buf.make_equivalent::<f32>();
// symphonia expects frames to already exist
buffer_out.render(Some(buf.frames()), |_, _| Ok(())).unwrap_or(());
buf.convert(&mut buffer_out);
buffer_out
},
AudioBufferRef::U32(buf) => {
let mut buffer_out = buf.make_equivalent::<f32>();
// symphonia expects frames to already exist
buffer_out.render(Some(buf.frames()), |_, _| Ok(())).unwrap_or(());
buf.convert(&mut buffer_out);
buffer_out
},
AudioBufferRef::U8(buf) => {
let mut buffer_out = buf.make_equivalent::<f32>();
// symphonia expects frames to already exist
buffer_out.render(Some(buf.frames()), |_, _| Ok(())).unwrap_or(());
buf.convert(&mut buffer_out);
buffer_out
},
}
// Account for the padding
let actual_size = util::format::sample::Buffer::size(
Sample::F32(Type::Packed),
CHANNELS,
frame.samples(),
false,
);
let f32_frame: Vec<f32> = frame.data(0)[..actual_size]
.chunks_exact(4)
.map(|x| {
let mut a: [u8; 4] = [0; 4];
a.copy_from_slice(x);
f32::from_le_bytes(a)
})
.collect();
sample_array.extend_from_slice(&f32_frame);
}
fn sample_buffer_length(buffer_in: AudioBufferRef) -> usize {
match buffer_in {
AudioBufferRef::F32(buf) => buf.frames(),
AudioBufferRef::F64(buf) => buf.frames(),
AudioBufferRef::S16(buf) => buf.frames(),
AudioBufferRef::S24(buf) => buf.frames(),
AudioBufferRef::S32(buf) => buf.frames(),
AudioBufferRef::S8(buf) => buf.frames(),
AudioBufferRef::U16(buf) => buf.frames(),
AudioBufferRef::U24(buf) => buf.frames(),
AudioBufferRef::U32(buf) => buf.frames(),
AudioBufferRef::U8(buf) => buf.frames(),
}
}
fn resample_buffer(
rx: Receiver<AudioBuffer<f32>>,
mut sample_array: Vec<f32>,
) -> BlissResult<Vec<f32>> {
let mut resample_buffer = Vec::<f32>::new();
let mut resampler_cache = std::collections::HashMap::<(u32, usize), ResamplerImpl<f32>>::new();
let mut wave_out_buffer = [Vec::<f32>::new()];
for decoded in rx.iter() {
//dbg!(decoded.frames());
if decoded.planes().planes().is_empty() || decoded.frames() < 5 {
// buffers that are too small cause resampler to panic
// due to chunk rounding down to 0
continue;
}
resample_buffer.clear();
// do resampling ourselves since symphonia doesn't
let frame_count = decoded.frames();
let in_sample_rate = decoded.spec().rate;
let audio_planes = decoded.planes();
let planes = audio_planes.planes();
let planes_len = planes.len() as f32;
for i in 0..frame_count {
// average samples into Mono track
let mut avg_sample = 0.0;
for plane in planes {
avg_sample += plane[i] / planes_len;
}
resample_buffer.push(avg_sample);
}
// build resampler
let cache_key = (in_sample_rate, resample_buffer.len());
let resampler = if let Some(resampler) = resampler_cache.get_mut(&cache_key) {
resampler
} else {
let new_resampler = ResamplerImpl::new(
in_sample_rate as _,
SAMPLE_RATE as _,
resample_buffer.len(),
8,
1
).map_err(|e| BlissError::DecodingError(format!("Resampler init failure: {}", e)))?;
resampler_cache.insert(cache_key, new_resampler);
resampler_cache.get_mut(&cache_key).unwrap()
};
// resample
resampler.process_into_buffer(
&[resample_buffer.as_slice()],
&mut wave_out_buffer,
None,
).map_err(|e| BlissError::DecodingError(format!("Resampler processing error: {}", e)))?;
sample_array.append(&mut wave_out_buffer[0]);
}
Ok(sample_array)
}
#[cfg(test)]
mod tests {
use super::*;
use pretty_assertions::assert_eq;
use ripemd160::{Digest, Ripemd160};
use std::path::Path;
#[test]
fn test_analysis_too_small() {
let error = Song::analyse(vec![0.]).unwrap_err();
let error = Song::analyze(&[0.]).unwrap_err();
assert_eq!(
error,
BlissError::AnalysisError(String::from("empty or too short song."))
);
let error = Song::analyse(vec![]).unwrap_err();
let error = Song::analyze(&[]).unwrap_err();
assert_eq!(
error,
BlissError::AnalysisError(String::from("empty or too short song."))
@ -619,8 +782,8 @@ mod tests {
}
#[test]
fn test_analyse() {
let song = Song::new(Path::new("data/s16_mono_22_5kHz.flac")).unwrap();
fn test_analyze() {
let song = Song::from_path(Path::new("data/s16_mono_22_5kHz.flac")).unwrap();
let expected_analysis = vec![
0.3846389,
-0.849141,
@ -643,9 +806,10 @@ mod tests {
-0.9820945,
-0.95968974,
];
for (x, y) in song.analysis.to_vec().iter().zip(expected_analysis) {
for (x, y) in song.analysis.as_vec().iter().zip(expected_analysis) {
assert!(0.01 > (x - y).abs());
}
assert_eq!(FEATURES_VERSION, song.features_version);
}
fn _test_decode(path: &Path, expected_hash: &[u8]) {
@ -662,10 +826,17 @@ mod tests {
fn test_tags() {
let song = Song::decode(Path::new("data/s16_mono_22_5kHz.flac")).unwrap();
assert_eq!(song.artist, Some(String::from("David TMX")));
assert_eq!(
song.album_artist,
Some(String::from("David TMX - Album Artist"))
);
assert_eq!(song.title, Some(String::from("Renaissance")));
assert_eq!(song.album, Some(String::from("Renaissance")));
assert_eq!(song.track_number, Some(String::from("02")));
assert_eq!(song.genre, Some(String::from("Pop")));
// Test that there is less than 10ms of difference between what
// the song advertises and what we compute.
assert!((song.duration.as_millis() as f32 - 11070.).abs() < 10.);
}
#[test]
@ -788,25 +959,34 @@ mod tests {
assert_eq!(
Song::decode(Path::new("nonexistent")).unwrap_err(),
BlissError::DecodingError(String::from(
"while opening format: ffmpeg::Error(2: No such file or directory)."
"while opening song: Os { code: 2, kind: NotFound, message: \"No such file or directory\" }."
)),
);
assert_eq!(
Song::decode(Path::new("data/picture.png")).unwrap_err(),
BlissError::DecodingError(String::from("No audio stream found.")),
BlissError::DecodingError(String::from("while opening format: Unsupported(\"core (probe): no suitable format reader found\").")),
);
}
#[test]
fn test_index_analysis() {
let song = Song::new("data/s16_mono_22_5kHz.flac").unwrap();
let song = Song::from_path("data/s16_mono_22_5kHz.flac").unwrap();
assert_eq!(song.analysis[AnalysisIndex::Tempo], 0.3846389);
assert_eq!(song.analysis[AnalysisIndex::Chroma10], -0.95968974);
}
#[test]
fn test_decode_wav() {
let expected_hash = [
0xf0, 0xe0, 0x85, 0x4e, 0xf6, 0x53, 0x76, 0xfa, 0x7a, 0xa5, 0x65, 0x76, 0xf9, 0xe1,
0xe8, 0xe0, 0x81, 0xc8, 0xdc, 0x61,
];
_test_decode(Path::new("data/piano.wav"), &expected_hash);
}
#[test]
fn test_debug_analysis() {
let song = Song::new("data/s16_mono_22_5kHz.flac").unwrap();
let song = Song::from_path("data/s16_mono_22_5kHz.flac").unwrap();
assert_eq!(
"Analysis { Tempo: 0.3846389, Zcr: -0.849141, MeanSpectralCentroid: \
-0.75481045, StdDeviationSpectralCentroid: -0.8790748, MeanSpectralR\
@ -827,6 +1007,7 @@ mod tests {
fn dummy_distance(_: &Array1<f32>, _: &Array1<f32>) -> f32 {
0.
}
#[test]
fn test_custom_distance() {
let mut a = Song::default();
@ -844,6 +1025,84 @@ mod tests {
]);
assert_eq!(a.custom_distance(&b, dummy_distance), 0.);
}
#[test]
fn test_closest_from_pool() {
let song = Song {
path: Path::new("path-to-first").to_path_buf(),
analysis: Analysis::new([
1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1.,
]),
..Default::default()
};
let first_song_dupe = Song {
path: Path::new("path-to-dupe").to_path_buf(),
analysis: Analysis::new([
1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1.,
]),
..Default::default()
};
let second_song = Song {
path: Path::new("path-to-second").to_path_buf(),
analysis: Analysis::new([
2., 2., 2., 2., 2., 2., 2., 2., 2., 2., 2., 2., 2., 2., 2., 2., 1.9, 1., 1., 1.,
]),
..Default::default()
};
let third_song = Song {
path: Path::new("path-to-third").to_path_buf(),
analysis: Analysis::new([
2., 2., 2., 2., 2., 2., 2., 2., 2., 2., 2., 2., 2., 2., 2., 2., 2.5, 1., 1., 1.,
]),
..Default::default()
};
let fourth_song = Song {
path: Path::new("path-to-fourth").to_path_buf(),
analysis: Analysis::new([
2., 2., 2., 2., 2., 2., 2., 2., 2., 2., 2., 2., 2., 2., 2., 2., 0., 1., 1., 1.,
]),
..Default::default()
};
let fifth_song = Song {
path: Path::new("path-to-fifth").to_path_buf(),
analysis: Analysis::new([
2., 2., 2., 2., 2., 2., 2., 2., 2., 2., 2., 2., 2., 2., 2., 2., 0., 1., 1., 1.,
]),
..Default::default()
};
let songs = vec![
song.to_owned(),
first_song_dupe.to_owned(),
second_song.to_owned(),
third_song.to_owned(),
fourth_song.to_owned(),
fifth_song.to_owned(),
];
let playlist = song.closest_from_pool(songs.to_owned());
assert_eq!(
playlist,
vec![
song.to_owned(),
second_song.to_owned(),
fourth_song.to_owned(),
third_song.to_owned(),
],
);
let playlist = song.closest_from_pool_custom(songs, euclidean_distance);
assert_eq!(
playlist,
vec![
song,
first_song_dupe,
second_song,
fourth_song,
fifth_song,
third_song
],
);
}
}
#[cfg(all(feature = "bench", test))]

View file

@ -48,10 +48,7 @@ impl BPMDesc {
sample_rate,
)
.map_err(|e| {
BlissError::AnalysisError(format!(
"error while loading aubio tempo object: {}",
e.to_string()
))
BlissError::AnalysisError(format!("error while loading aubio tempo object: {}", e))
})?,
bpms: Vec::new(),
})
@ -59,10 +56,7 @@ impl BPMDesc {
pub fn do_(&mut self, chunk: &[f32]) -> BlissResult<()> {
let result = self.aubio_obj.do_result(chunk).map_err(|e| {
BlissError::AnalysisError(format!(
"aubio error while computing tempo {}",
e.to_string()
))
BlissError::AnalysisError(format!("aubio error while computing tempo {}", e))
})?;
if result > 0. {

View file

@ -126,21 +126,21 @@ impl SpectralDesc {
.map_err(|e| {
BlissError::AnalysisError(format!(
"error while loading aubio centroid object: {}",
e.to_string()
e
))
})?,
rolloff_aubio_desc: SpecDesc::new(SpecShape::Rolloff, SpectralDesc::WINDOW_SIZE)
.map_err(|e| {
BlissError::AnalysisError(format!(
"error while loading aubio rolloff object: {}",
e.to_string()
e
))
})?,
phase_vocoder: PVoc::new(SpectralDesc::WINDOW_SIZE, SpectralDesc::HOP_SIZE).map_err(
|e| {
BlissError::AnalysisError(format!(
"error while loading aubio pvoc object: {}",
e.to_string()
e
))
},
)?,
@ -163,10 +163,7 @@ impl SpectralDesc {
self.phase_vocoder
.do_(chunk, fftgrain.as_mut_slice())
.map_err(|e| {
BlissError::AnalysisError(format!(
"error while processing aubio pv object: {}",
e.to_string()
))
BlissError::AnalysisError(format!("error while processing aubio pv object: {}", e))
})?;
let bin = self
@ -175,7 +172,7 @@ impl SpectralDesc {
.map_err(|e| {
BlissError::AnalysisError(format!(
"error while processing aubio centroid object: {}",
e.to_string()
e
))
})?;
@ -204,12 +201,12 @@ impl SpectralDesc {
self.values_rolloff.push(freq);
let cvec: CVec = fftgrain.as_slice().into();
let geo_mean = geometric_mean(&cvec.norm());
let geo_mean = geometric_mean(cvec.norm());
if geo_mean == 0.0 {
self.values_flatness.push(0.0);
return Ok(());
}
let flatness = geo_mean / mean(&cvec.norm());
let flatness = geo_mean / mean(cvec.norm());
self.values_flatness.push(flatness);
Ok(())
}

View file

@ -3,7 +3,6 @@ use ndarray::{arr1, s, Array, Array1, Array2};
use rustfft::num_complex::Complex;
use rustfft::num_traits::Zero;
use rustfft::FftPlanner;
extern crate ffmpeg_next as ffmpeg;
use log::warn;
use std::f32::consts::PI;
@ -29,7 +28,7 @@ pub(crate) fn stft(signal: &[f32], window_length: usize, hop_length: usize) -> A
(signal.len() as f32 / hop_length as f32).ceil() as usize,
window_length / 2 + 1,
));
let signal = reflect_pad(&signal, window_length / 2);
let signal = reflect_pad(signal, window_length / 2);
// Periodic, so window_size + 1
let mut hann_window = Array::zeros(window_length + 1);
@ -45,7 +44,7 @@ pub(crate) fn stft(signal: &[f32], window_length: usize, hop_length: usize) -> A
.step_by(hop_length)
.zip(stft.rows_mut())
{
let mut signal = (arr1(&window) * &hann_window).mapv(|x| Complex::new(x, 0.));
let mut signal = (arr1(window) * &hann_window).mapv(|x| Complex::new(x, 0.));
match signal.as_slice_mut() {
Some(s) => fft.process(s),
None => {
@ -101,8 +100,7 @@ pub(crate) fn geometric_mean(input: &[f32]) -> f32 {
let mut exponents: i32 = 0;
let mut mantissas: f64 = 1.;
for ch in input.chunks_exact(8) {
let mut m;
m = (ch[0] as f64 * ch[1] as f64) * (ch[2] as f64 * ch[3] as f64);
let mut m = (ch[0] as f64 * ch[1] as f64) * (ch[2] as f64 * ch[3] as f64);
m *= 3.273390607896142e150; // 2^500 : avoid underflows and denormals
m *= (ch[4] as f64 * ch[5] as f64) * (ch[6] as f64 * ch[7] as f64);
if m == 0. {