simdra2D canvas. In a Worker.

import { __initSync, microsharp } from 'simdra/wasm';
import wasm from 'simdra/wasm/simdra.wasm';
__initSync(wasm);

export default {
  async fetch(request: Request) {
    const out = await microsharp(request.body)
      .resize(800, 600, { fit: 'cover', kernel: 'lanczos3' })
      .jpeg({ quality: 85 })
      .toBuffer();
    return new Response(out, {
      headers: { 'content-type': 'image/jpeg' },
    });
  },
};

// worker.ts
import { __initSync, createCanvas } from 'simdra/wasm';
import wasm from 'simdra/wasm/simdra.wasm';
__initSync(wasm);

self.onmessage = (e) => {
  const canvas = createCanvas(e.data.width, e.data.height);
  const ctx = canvas.getContext('2d');
  ctx.fillStyle = '#10b981';
  ctx.fillRect(0, 0, canvas.width, canvas.height);
  ctx.fillStyle = '#fff';
  ctx.font = '24px sans-serif';
  ctx.fillText('Hello, Worker', 20, 40);
  const png = canvas.toBytes();
  self.postMessage(png, [png.buffer]);
};

import { __init, microsharp } from 'simdra/wasm';
import wasmUrl from 'simdra/wasm/simdra.wasm?url';
await __init(fetch(wasmUrl));

async function autoCrop(file: File) {
  const out = await microsharp(file)
    .rotate()                                  // autoOrient via EXIF
    .resize(1200, 800, { fit: 'cover', position: 'attention' })
    .modulate({ brightness: 1.1, saturation: 1.2 })
    .sharpen()
    .jpeg({ quality: 90 })
    .toBuffer();
  return new Blob([out], { type: 'image/jpeg' });
}

const out = await microsharp(input)
  .rotate(90)                                  // 90° / 180° / 270° byte-exact
  .flip().flop()                               // mirrors
  .affine([1, 0.3, 0.1, 0.7])                  // affine transform
  .blur(2)                                     // separable Gaussian
  .sharpen({ sigma: 1, m1: 1, m2: 2 })         // libvips USM
  .median(3).dilate(1).erode(1)                // morphology
  .convolve({ width: 3, height: 3, kernel: [-1,0,1,-2,0,2,-1,0,1] })
  .gamma(2.2).negate({ alpha: false })         // tone curves
  .linear(1.2, -10).threshold(128)             // levels
  .normalise().clahe({ width: 16, height: 16 })
  .modulate({ brightness: 1.1, hue: 30 })
  .tint('#ff8800').greyscale()
  .png()
  .toBuffer();

import { createCanvas, Path2D } from 'simdra';
import { writeFileSync } from 'node:fs';

const canvas = createCanvas(400, 300);
const ctx = canvas.getContext('2d');

// Background
const grad = ctx.createLinearGradient(0, 0, 0, 300);
grad.addColorStop(0, '#1e3a8a');
grad.addColorStop(1, '#0f172a');
ctx.fillStyle = grad;
ctx.fillRect(0, 0, 400, 300);

// Path with stroke + fill
const path = new Path2D();
path.moveTo(200, 50);
path.lineTo(350, 250);
path.lineTo(50, 250);
path.closePath();

ctx.fillStyle = '#fbbf24';
ctx.fill(path);
ctx.lineWidth = 4;
ctx.strokeStyle = '#fff';
ctx.stroke(path);

writeFileSync('out.png', canvas.toBytes());