audioFlux
A library for audio and music analysis, feature extraction. (by libAudioFlux)
dejavu
Audio fingerprinting and recognition in Python (by worldveil)
| audioFlux | dejavu | |
|---|---|---|
| 57 | 15 | |
| 2,063 | 6,324 | |
| 1.8% | - | |
| 7.8 | 0.0 | |
| 29 days ago | 24 days ago | |
| C | Python | |
| MIT License | MIT License |
The number of mentions indicates the total number of mentions that we've tracked plus the number of user suggested alternatives.
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
audioFlux
Posts with mentions or reviews of audioFlux.
We have used some of these posts to build our list of alternatives
and similar projects. The last one was on 2023-05-29.
- AudioFlux: Open-source for audio and music analysis, feature extraction
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A library for audio processing , support Android platform
This is prebuilt android so library : https://github.com/libAudioFlux/audioFlux/releases/download/v0.1.6/libaudioflux-0.1.6-android.zip
- A library for DSP and audio analysis, support iOS and macOS
-
An audio analysis library in C
I utilize performance-optimized libraries such as I utilize performance-optimized libraries such as ML, OpenBLAS, and OpenMP for accelerating the performance. https://github.com/libAudioFlux/audioFlux/issues/22
- A High-Performance Library for Audio Analysis
- Benchmark for Audio Feature Extraction Libraries
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[P] A High-Performance Audio Library for Machine Learning
Project: https://github.com/libAudioFlux/audioFlux
- Benchmark for Audio Libraries: Audioflux, TorchAudio, Librosa, Essentia, etc
- Audio Library Benchmark: AudioFlux, TorchAudio, Librosa, Essentia etc.
dejavu
Posts with mentions or reviews of dejavu.
We have used some of these posts to build our list of alternatives
and similar projects. The last one was on 2024-04-14.
- Audio Fingerprinting and Recognition in Python
-
Contacting Collectors or Creating API to help with searching
This doesn't seem hard, you can use something like this to dwoanload the songs: https://stackoverflow.com/a/27481870/6151784 and something like this to calculate how much they match: https://github.com/worldveil/dejavu The question is would you create a (dedicated) server to do your work? Or your own pc? You could also create a very simple page where someone would paste you a YouTube profile URL and you would check all songs of this URL. Also to have a db and save information about the matching and which youtube profiles have alsready been checked. Something like that could work.
-
Tiny bit of experience but need to compile a Github program. What is the best video / resource to learn to do this quickly?
If you read the installation.md file it clearly states that it has only been tested on UNIX systems, so you might be on your own trying to get it to wor in windows.
- Help needed with school project
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Identification of all usages of OSTs in Made in Abyss (S1)
Using neural networks seems complicated, did you tried audio fingerprinting? I have been using this audio fingerprinting library to power this anime song synchronization script. You can check Panako and dejavu too.
- Dejavu – Audio fingerprinting and recognition algorithm
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fingerprinting sections of audio from file
I want to say these few seconds match these few seconds from a different audio track. Using dejavu raw has overhead I do not need/want and hence I've been fiddling around with the fingerprint script. When modifying the global variables I can get better hits or worse hits, I will admit that even after reading there recommended article and many other sources, I can't find some good explanations about the mathematics behind the filtering after the specgram has been applied. As far as a I am aware we first apply filters to find/make fine points across the spectrogram after that we only check the distance between points along the time axis not the frequency or a hypotenuse (weird).
- Some information and advice about DDoS, from someone who was there during #opPayback
- List of resources
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Uploading an audio dataset into a database for comparison
I used a repo called https://github.com/worldveil/dejavu to compare audio hashed fingerprints and distinguish the difference between them.
What are some alternatives?
When comparing audioFlux and dejavu you can also consider the following projects:
librosa - Python library for audio and music analysis
django-elastic-transcoder - Django + AWS Elastic Transcoder
essentia - C++ library for audio and music analysis, description and synthesis, including Python bindings
m3u8 - Python m3u8 Parser for HTTP Live Streaming (HLS) Transmissions
pydub - Manipulate audio with a simple and easy high level interface
audiolazy - Expressive Digital Signal Processing (DSP) package for Python
spleeter - Deezer source separation library including pretrained models.
speech-to-text-websockets-python
matchering - 🎚️ Open Source Audio Matching and Mastering
pyechonest - Python client for the Echo Nest API
mutagen - Python module for handling audio metadata
pyAudioAnalysis - Python Audio Analysis Library: Feature Extraction, Classification, Segmentation and Applications