Chordy v.0.5

Chordyzer v0.5 - Musical analyzer from localfile songs & YouTube links

Chord Extraction & Database & Analysis Tool

A python and HTML/CSS/JS based tool to extract chords from any song,
which creates a database to analyze and show chord-key data by different criteria as title, artist, by chord type, number of times a chord appears; by song, by a group of songs or globally.

REQUIREMENTS

• Python 3.9.x
• sudo apt install ffmpeg
• pip install numpy librosa chord-extractor json yt-dlp

USAGE

• Run an analisys:

$ python Chordy.py

• Generate a chord list

$ python Library.py

• Manage your database:

$ ./chords_database.html

INCLUDES

• Chord extracting from any MP3, WAV, MIDI file, or directly a Youtube link.
• Chord Visualizer with GUITAR diagrams, HTML5-webkit compatible.
• Chord carts transposing with live changing diagrams.
• Bar/Time Signatures counting, Tempo/BPM analyzer tool & live rhythm change.
• Keynote analysis on each bar, A4 referencial frequency identifier.
• A database generation for analysing purposses capable of sorting chords, how many times used, the most and least used chords; by song, globally, ....
• Modular functions, python based, can be easilly added ... my framework works over numbers, and numbers, and their analyse.
• The fewer external libraries and dependences used here, the better. Only chord-extractor and librosa for the audio analysing and controls. NumPy for anything numbers related. jQuery, Chart.js are also used for scripting database support.

The program generates:

1. Artist_Title.html file. The visualizer of each song.
2. chord_database.html and chord_db.json files. A full database of all the song's with data analysis tools. Both files are updated automatically.

In order to generatethe files both, you are told to provide some info as:
- ARTIST NAME
- SONG TITLE

(Development in progress)

2024 September, 16th.