Canvas + Custom Vision

gistfile1.txt

module.exports = async function (context, req) {
    context.log('JavaScript HTTP trigger function processed a request.');

    const { createCanvas, loadImage } = require('canvas');
    const fs = require('fs');

    const rawImage = req.body.image;
    const w = rawImage.width;
    const h = rawImage.height;
    console.log(w, h);
    const predictions = req.body.predictions.filter(e => e.probability > MIN_CONFIDENCE);
    console.log(predictions);

    // Confidence threshold for the analysis
    const MIN_CONFIDENCE = 0.75;

    const canvas = createCanvas(w, h);
    const ctx = canvas.getContext('2d');
    ctx.drawImage(img, 0, 0, w, h);
    ctx.strokeStyle = 'red';
    ctx.lineWidth = 2;

    for (const e of predictions) {
        const left = e.boundingBox.left * w;
        const top = e.boundingBox.top * h;
        const width = e.boundingBox.width * w;
        const height = e.boundingBox.height * h;
        ctx.strokeRect(left, top, width, height);
    };

    const buffer = await canvas.toBuffer("image/png");

    // send back bounded image
    context.res = {
        status: 200,
        body: buffer
    };
}