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webgpu-waveform

v1.1.0

Published

Render waveforms to `<canvas />` using [WebGPU](https://developer.mozilla.org/en-US/docs/Web/API/WebGPU_API)

Downloads

782

Readme

webgpu-waveform

Render waveforms to <canvas /> using WebGPU

Examples

Visit https://aykev.dev/webgpu-waveform/ for examples

Usage

This package is distributed for both usage with ESM and UMD. It inclused TypeScript types too. Install from the npm registry:

npm i webgpu-waveform

There's three ways to use this library:

  • as a class: GPUWaveformRenderer (vanilla JS)
  • as a hook: useWaveformRenderer (React)
  • as a component: GPUWaveform (React)

The class GPUWaveformRenderer is initialized using the static method .create(...). It has the following definition:

static async create(
  canvas: HTMLCanvasElement,
  channelData: Float32Array
): GPUWaveformRenderer

It takes in the following arguments:

  • canvas: HTMLCanvasElement — the canvas element to render to
  • channelData: Float32Array — the array of PCM samples to render

Example:

async function example(canvas, audioBuffer) {
  const channelData = audioBuffer.getChannelData(0);
  const renderer = await GPUWaveformRenderer.create(canvas, channelData);

  renderer?.render(800, 0, canvas.width, canvas.height);
}

The hook useWaveformRenderer has the following signature:

function useWaveformRenderer(
  canvasRef: React.RefObject<HTMLCanvasElement>,
  audioBuffer: AudioBuffer
): RendererStatus;

It takes in the following arguments:

  • canvasRef: React.RefObject<HTMLCanvasElement> — the canvas element to render to
  • audioBuffer: AudioBuffer — the buffer to render

And returns an object of the following type:

type RendererStatus =
  | { status: "initializing" }
  | { status: "error"; error: any }
  | { status: "ready"; instance: GPUWaveformRenderer };

The objects are returned during the following stages of initialization:

  • { status: "initializing" } — during setup, when connecting to the GPU device
  • { status: "error"; error: any } — if an error happens at initalization
  • { status: "ready"; instance: GPUWaveformRenderer } — if the webgpu device could be initialized, setup was successful, and a renderer for audioBuffer on canvas could be successfully created.

Example:

function Example({ audioBuffer, width, height }) {
  const canvasRef = useRef < HTMLCanvasElement > null;
  const renderer = useWaveformRenderer(canvasRef, audioBuffer);

  useEffect(() => {
    if (renderer.status !== "ready") {
      return;
    }

    renderer?.render(audioBuffer.length / width, 0, width, height);
  }, [renderer, audioBuffer, width, height]);

  return <canvas ref={canvasRef} width={width} height={height} />;
}

The component GPUWaveform takes the following properties:

  • audioBuffer: AudioBuffer; — the buffer to render
  • scale?: number; — the "zoom" level. Namely, number of samples per pixel in the x axis
  • offset?: number; — the number of samples to skip from the beggining of the buffer
  • ...and all the props of React.CanvasHTMLAttributes<HTMLCanvasElement> — these are passed directly to the rendered canvas

Example:

export function Example({ audioBuffer }) {
  return (
    <GPUWaveform
      audioBuffer={audioBuffer}
      scale={800}
      width={300}
      height={100}
    />
  );
}

Contributions

Feedback and PRs are welcome! If you send a PR, feel free to add yourself to the list of contributors below:

Contributors: