Deno を始める - 第5回 (WebAssembly の利用)

const importObject = {
  imports: { imported_func: (arg) => console.log(arg) }
};

const obj = await WebAssembly.instantiateStreaming(
  fetch("https://mdn.github.io/webassembly-examples/js-api-examples/simple.wasm"),
  importObject
);

obj.instance.exports.exported_func()

(module
  (func $i (import "imports" "imported_func") (param i32))
  (func (export "exported_func")
    i32.const 42
    call $i
  )
)

$ deno run --allow-net use_wasm.ts
42

const worker1 = createWorker("worker1");
const worker2 = createWorker("worker2");

const mod = await WebAssembly.compileStreaming(
  fetch("https://mdn.github.io/webassembly-examples/js-api-examples/simple.wasm"),
);

worker1.postMessage({ module: mod });
worker2.postMessage({ module: mod });

function createWorker(name: string): worker {
  const worker = new Worker(new URL("./worker.ts", import.meta.url).href, {
    type: "module",
    name: name,
  });
  return worker;
}

const importObject = {
  imports: {
    imported_func: arg => {
      console.log(arg);
    }
  }
};

self.onmessage = async (e) => {
  console.log(self.name, "module received from main thread");
  const { module } = e.data;
  const instance = await WebAssembly.instantiate(module, importObject);
  instance.exports.exported_func();

  self.close();
};

$ deno run --allow-read --allow-net use_wasm.ts
worker1 module received from main thread
worker2 module received from main thread
42
42

import { createCanvas } from "https://deno.land/x/canvas/mod.ts";

const canvas = createCanvas(200, 200);
const ctx = canvas.getContext("2d");

ctx.fillStyle = "red";
ctx.fillRect(10, 10, 200 - 20, 200 - 20);

await Deno.writeFile("image.png", canvas.toBuffer());

deno run --allow-write --allow-env --allow-net use_canvas.ts

import { cv } from "https://deno.land/x/opencv@v4.3.0-10/mod.ts";
import Jimp from "npm:jimp";

const imageSource = await Jimp.read("./image-sample.png");
const imageTemplate = await Jimp.read("./image-sample-template.png");

let src = cv.matFromImageData(imageSource.bitmap);
let templ = cv.matFromImageData(imageTemplate.bitmap);
let processedImage = new cv.Mat();
let mask = new cv.Mat();

cv.matchTemplate(src, templ, processedImage, cv.TM_CCOEFF_NORMED, mask);
cv.threshold(processedImage, processedImage, 0.999, 1, cv.THRESH_BINARY);
processedImage.convertTo(processedImage, cv.CV_8UC1);

let contours = new cv.MatVector();
let hierarchy = new cv.Mat();

cv.findContours(processedImage, contours, hierarchy, cv.RETR_EXTERNAL, cv.CHAIN_APPROX_SIMPLE);
for (let i = 0; i < contours.size(); ++i) {
    let countour = contours.get(i).data32S; // Contains the points
    let x = countour[0];
    let y = countour[1];
    
    let color = new cv.Scalar(0, 255, 0, 255);
    let pointA = new cv.Point(x, y);
    let pointB = new cv.Point(x + templ.cols, y + templ.rows);
    cv.rectangle(src, pointA, pointB, color, 2, cv.LINE_8, 0);
}

new Jimp({
    width: src.cols,
    height: src.rows,
    data: src.data
}).write("template-matching.png");

deno run --allow-env --allow-net --allow-read --allow-write use_opencv.ts

import { DB } from "https://deno.land/x/sqlite/mod.ts";

// Open a database
const db = new DB("test.db");
db.execute(`
  CREATE TABLE IF NOT EXISTS people (
    id INTEGER PRIMARY KEY AUTOINCREMENT,
    name TEXT
  )
`);

// Run a simple query
for (const name of ["Peter Parker", "Clark Kent", "Bruce Wayne"]) {
  db.query("INSERT INTO people (name) VALUES (?)", [name]);
}

// Print out data in table
for (const [name] of db.query("SELECT name FROM people")) {
  console.log(name);
}

// Close connection
db.close();

$ deno run --unstable --allow-read --allow-write use_sqlite.ts
Peter Parker
Clark Kent
Bruce Wayne