ComfyUI Audio Waveform Visualizer

A collection of custom nodes for ComfyUI designed to generate audio waveform visualizations. This package provides several methods to visualize audio, ranging from real-time workspace previews to high-resolution images for video synthesis.

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Preview

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Features

• Real-time Visualization: Waveform rendering directly on the ComfyUI canvas using JavaScript.
• Image Generation: Detailed waveform images using Matplotlib or FFmpeg.
• Customization: Control over dimensions, colors (hex supported), and mono/stereo channel handling.
• Performance Optimization: Audio decimation (downsampling) and offscreen buffering for handling long audio files.

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Installation

1. Prerequisites

FFmpeg (Required for FFMPEG Node)

• Windows: Download from gyan.dev, extract, and add the bin folder to your System PATH.
• Linux: sudo apt install ffmpeg
• macOS: brew install ffmpeg

Python Dependencies

Install the required libraries:

pip install -r requirements.txt

2. Manual Installation

1. Navigate to your ComfyUI custom nodes directory:

   cd ComfyUI/custom_nodes/

2. Clone this repository:

   git clone https://github.com/kaushiknishchay/ComfyUI-Audio-Waveform-Visualizer audio-visualizer

3. Restart ComfyUI.

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Visualization Methods

This suite provides three specialized nodes for different use cases.

1. Audio Waveform Visualizer (Frontend Canvas)

Renders a waveform directly on the node's UI using a JavaScript canvas.

• Usage: Quick inspection and real-time feedback during workflow development.
• Pros: Fast; minimal impact on generation time; responsive to resizing.
• Cons: No image output; visualization is lost on UI refresh.

2. Audio to Waveform Image (Matplotlib)

Generates a waveform image using the Matplotlib engine.

• Usage: Creating clean overlays for composites.
• Pros: Supports transparency (RGBA); generates a standard IMAGE tensor.
• Parameters: width, height, color (supports hex codes).

3. Audio Waveform (FFMPEG)

Uses the FFmpeg showwavespic filter to create a detailed visualization.

• Usage: Video production and accurate audio representation.
• Pros: Displays both Peak and RMS levels; supports stereo channel splitting.
• Parameters: bg_color, peak_color, rms_color, split_channels (stereo/mono).

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Workflow Examples

An example workflow is available in the workflows/ directory:

• AudioWaveform.json: Demonstrates all three visualization methods.

To use it: Drag and drop the JSON file into your ComfyUI workspace.

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Usage Notes

• Input: All nodes accept the standard ComfyUI AUDIO type.
• Output: Image-based nodes output a standard IMAGE tensor compatible with nodes like Preview Image or Save Image.
• Large Files: Automatic decimation is applied to manage memory and performance when processing long audio recordings.

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License

Distributed under the MIT License.

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Connect

• Website: nkaushik.in
• GitHub: @kaushiknishchay