Music Visualizer Video Generator

A Python-based music visualizer that creates stunning bar-style visualizations and renders them to video files. Available as both a command-line tool and REST API service.

Features

• Bar-style visualization with frequency-responsive heights
• Beautiful color gradients from magenta through purple, blue, cyan, to red/orange
• High-quality video output with customizable resolution and frame rate
• Audio synchronization with automatic audio track addition
• Optimized rendering with pre-computed spectrum analysis
• REST API with background job processing

Installation

1. Install Python dependencies:

pip install -r requirements.txt

2. Install FFmpeg (required for audio integration):

• macOS: brew install ffmpeg
• Ubuntu/Debian: sudo apt install ffmpeg
• Windows: Download from https://ffmpeg.org/

Usage

Command Line Usage

Basic Usage

python video_visualizer.py input_audio.mp3

Advanced Options

python video_visualizer.py input_audio.mp3 -o my_visualization.mp4 -w 1920 -b 1080 -f 60

Parameters

• input_audio: Path to your audio file (MP3, WAV, FLAC, OGG supported)
• -o, --output: Output video filename (default: visualization.mp4)
• -w, --width: Video width in pixels (default: 1920)
• -b, --height: Video height in pixels (default: 1080)
• -f, --fps: Video frame rate (default: 50)
• --no-audio: Generate video without audio track

Examples

Create a 4K visualization at 60fps:

python video_visualizer.py song.mp3 -o song_4k.mp4 -w 3840 -b 2160 -f 60

Generate silent video (video only):

python video_visualizer.py song.mp3 -o silent_viz.mp4 --no-audio

REST API Usage

Start the Flask server:

python app.py

The API will be available at http://localhost:5000

API Endpoints

POST /api/visualize Create a visualization job from a local audio file.

Request body:

{
  "audio_path": "/path/to/audio.mp3",
  "output_path": "/path/to/output.mp4",
  "width": 1920,
  "height": 1080,
  "fps": 50,
  "include_audio": true
}

Response:

{
  "job_id": "uuid-string",
  "status": "pending",
  "message": "Visualization job started",
  "output_path": "/path/to/output.mp4"
}

GET /api/status/{job_id} Check the status of a visualization job.

Response:

{
  "job_id": "uuid-string",
  "status": "completed",
  "progress": 100,
  "message": "Visualization completed successfully",
  "output_file": "/path/to/output.mp4",
  "created_at": 1234567890
}

GET /api/jobs List all jobs.

GET /api/health Health check endpoint.

Job Status Values

• pending: Job created but not started
• processing: Job is currently running
• completed: Job finished successfully
• failed: Job encountered an error

How It Works

1. Audio Analysis: Uses librosa to perform Short-Time Fourier Transform (STFT) on the input audio
2. Frequency Mapping: Maps frequency data to visual bars with emphasis on lower frequencies (up to 8kHz)
3. Color Generation: Creates smooth color gradients across 120 bars
4. Frame Generation: Renders each video frame with PIL for precise drawing
5. Video Encoding: Uses OpenCV to encode frames and FFmpeg to add audio

Technical Details

• Bars: 30 frequency bars across the width
• Frequency Range: 0-8kHz (optimized for music visualization)
• Color Palette: White bars on black background with optional gradient support
• Audio Processing: 44.1kHz sample rate with 8192-point FFT
• Video Codec: MP4V with AAC audio

Troubleshooting

Common Issues

"Error: Could not open video writer"

• Ensure you have write permissions in the output directory
• Try a different output filename

"Warning: Could not add audio"

• Install FFmpeg: the visualizer needs it to combine video and audio
• Check that FFmpeg is in your system PATH

Slow rendering

• Reduce resolution with -w and -b parameters
• Lower frame rate with -f parameter
• Use shorter audio files for testing

Performance Tips

• Resolution vs Speed: 1920x1080 @ 50fps renders much faster than 4K @ 60fps
• Audio Length: 3-minute songs typically take 2-5 minutes to render
• Memory Usage: Longer songs require more RAM for spectrum analysis

License

This project is open source. Feel free to modify and distribute.