madmom | Python audio and music signal processing library | Audio Utils library

 by   CPJKU Python Version: 0.16.1 License: Non-SPDX

kandi X-RAY | madmom Summary

kandi X-RAY | madmom Summary

madmom is a Python library typically used in Audio, Audio Utils, Numpy applications. madmom has no bugs, it has no vulnerabilities, it has build file available and it has medium support. However madmom has a Non-SPDX License. You can install using 'pip install madmom' or download it from GitHub, PyPI.

Python audio and music signal processing library

            kandi-support Support

              madmom has a medium active ecosystem.
              It has 1092 star(s) with 172 fork(s). There are 43 watchers for this library.
              It had no major release in the last 12 months.
              There are 45 open issues and 211 have been closed. On average issues are closed in 527 days. There are 13 open pull requests and 0 closed requests.
              It has a neutral sentiment in the developer community.
              The latest version of madmom is 0.16.1

            kandi-Quality Quality

              madmom has 0 bugs and 0 code smells.

            kandi-Security Security

              madmom has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.
              madmom code analysis shows 0 unresolved vulnerabilities.
              There are 0 security hotspots that need review.

            kandi-License License

              madmom has a Non-SPDX License.
              Non-SPDX licenses can be open source with a non SPDX compliant license, or non open source licenses, and you need to review them closely before use.

            kandi-Reuse Reuse

              madmom releases are available to install and integrate.
              Deployable package is available in PyPI.
              Build file is available. You can build the component from source.
              madmom saves you 8191 person hours of effort in developing the same functionality from scratch.
              It has 16840 lines of code, 1586 functions and 71 files.
              It has medium code complexity. Code complexity directly impacts maintainability of the code.

            Top functions reviewed by kandi - BETA

            kandi has reviewed madmom and discovered the below as its top functions. This is intended to give you an instant insight into madmom implemented functionality, and help decide if they suit your requirements.
            • Add a parser to the argument parser
            • Evaluate an annotation file
            • Display the activations
            • Resets the HMM
            • Append another processor
            • Extend the list of processors
            • Process a list of activations
            • Thresholds the activations above the given threshold
            • Return a flat list of all the notes in the track
            • Given a list of notes compute the notes in each note
            • Process an audio stream
            • Process activations
            • Process the activations using the viterbi
            • Process the activations
            • Process pitch with HMM
            • Generate a histogram of an interval histogram
            • Process the spectrogram
            • Save activations to a text file
            • Activate the feature vector
            • Generate a stream of the events
            • String representation
            • Compute the similarity between predictions
            • Detect peaks in activations
            • Return a string representation of the TPF
            • Convert a list of evaluation objects into a tex file
            • Display the tempo histogram
            Get all kandi verified functions for this library.

            madmom Key Features

            No Key Features are available at this moment for madmom.

            madmom Examples and Code Snippets

            Structure,Pre-extracted features
            Pythondot img1Lines of Code : 28dot img1License : Permissive (Apache-2.0)
            copy iconCopy
            	"chroma_cens": numpy.ndarray,
            	"crema": numpy.ndarray,
            	"hpcp": numpy.ndarray,
            	"key_extractor": {
            		"key": numpy.str_,
            		"scale": numpy.str_,_
            		"strength": numpy.float64
            	"madmom_features": {
            		"novfn": numpy.ndarray, 
            		"onsets": numpy.ndar  
            copy iconCopy
            brew install ffmpeg
            add-apt-repository ppa:mc3man/trusty-media
            apt-get update
            apt-get dist-upgrade
            apt-get install ffmpeg
            yum install epel-release
            rpm --import
            rpm -Uvh  
            Sample CNN,Prerequisites,Installing ffmpeg
            Pythondot img3Lines of Code : 9dot img3License : Permissive (MIT)
            copy iconCopy
            brew install ffmpeg
            add-apt-repository ppa:mc3man/trusty-media
            apt-get update
            apt-get dist-upgrade
            apt-get install ffmpeg
            yum install epel-release
            rpm --import
            rpm -Uvh  
            Convert midi time to bars and beats
            Pythondot img4Lines of Code : 5dot img4License : Strong Copyleft (CC BY-SA 4.0)
            copy iconCopy
            import mido
            midi = mido.MidiFile('1079-02.mid')
            Python google cloud function deployment failure - Madmom pip package
            Pythondot img5Lines of Code : 4dot img5License : Strong Copyleft (CC BY-SA 4.0)
            copy iconCopy

            Community Discussions


            find the timestamp of a sound sample of an mp3 with linux or python
            Asked 2020-Jun-30 at 02:32

            I am slowly working on a project which where it would be very useful if the computer could find where in an mp3 file a certain sample occurs. I would restrict this problem to meaning a fairly exact snippet of the audio, not just for example the chorus in a song on a different recording by the same band where it would become more some kind of machine learning problem. Am thinking if it has no noise added and comes from the same file, it should somehow be possible to locate the time at which it occurs without machine learning, just like grep can find the lines in a textfile where a word occurs.

            In case you don't have an mp3 lying around, can set up the problem with some music available on the net which is in the public domain, so nobody complains:



            Answered 2020-Jun-25 at 15:55

            MP3 is an interesting format. The underlying data is stored in 'Frames', each 0.026 seconds long. Each frame is a Fast Fourier transform of the sound wave, encoded with varying degrees of quality depending on the size and bitrate, etc.. In your case, are you certain that the mp3s have matching bitrates? If they do, a relatively straightforward grep-style approach should be possible, given that you select on Frame boundaries. However, it is entirely likely and possible that this is not the case.

            For a true solution, you need to process the mp3 file to some degree, to abstract away the encoding. However, there is no guarantee that the resulting wave match even for matching sounds, as bitrates and possibly frame alignment may differ. This small degree of chance makes it much harder.

            I will give you my approach to this problem, but it is worth noting that this is not the perfect way to do things, just my best swing. Even though its the same file, there's no guarantee that frame boundaries are aligned, so I think you need to take a very wave-oriented approach, rather than a data-oriented one.

            First, convert the mp3s to waves. I know that it'd be great to leave it compressed, but again I think wave-oriented is our only hope. Then, use a high-pass filter to try to remove any artifacts of audio compression that would differ between samples. Once you have two waveforms, it should be relatively straight forward to find the wavelet in the wave. You can iterate through possible starting positions and subtract the waves. When you get close to zero, you know you're close.



            Convert midi time to bars and beats
            Asked 2020-Jun-12 at 01:09

            I am trying to figure out how to convert from midi time to bars and beats. Here is a sample midi file. If you download that and open the file in a program like GarageBand, you'll see the third track contains four notes in the first bar:

            Now if you load the file with mido in Python, you can see the first four notes in the same track:



            Answered 2020-Jun-12 at 01:09

            Praise all things good and holy, mido.MidiFile reads the ticks per beat metadata and stores it in mido.MidiFile.ticks_per_beat:


            Community Discussions, Code Snippets contain sources that include Stack Exchange Network


            No vulnerabilities reported

            Install madmom

            You can install using 'pip install madmom' or download it from GitHub, PyPI.
            You can use madmom like any standard Python library. You will need to make sure that you have a development environment consisting of a Python distribution including header files, a compiler, pip, and git installed. Make sure that your pip, setuptools, and wheel are up to date. When using pip it is generally recommended to install packages in a virtual environment to avoid changes to the system.


            For any new features, suggestions and bugs create an issue on GitHub. If you have any questions check and ask questions on community page Stack Overflow .
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            pip install madmom

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