computerVision.js

const cv = require('opencv4nodejs');
const jimp = require('jimp');
const ImgDownload = require('image-downloader');
const fs = require('fs');

const classifiers = {
    FACE: "face",
    EYE: "eye",
    BODY: "body",
    SMILE:"smile"
}

async function faceReplace(path){   // pretty much exactly zachs code except for like one tiny change 
    const faces = detect(path, classifiers.FACE);
    let img = await jimp.read(path);
    if(faces.length > 0){
        for(let i = 0; i < faces.length; i++){
            let face = faces[i];
            const length = fs.readdirSync('./images').length;
            let file_id = Math.round(Math.random() * (length -1));
            let image_filename = 'images/face' + file_id + '.png';
            console.log(image_filename);
            const insertedImage = await jimp.read(image_filename);

            img = img.composite(insertedImage.resize(face.width,face.height),face.x, face.y);
        }
    }
    else{
        const length = fs.readdirSync('./images').length;
        let file_id = Math.round(Math.random() * (length -1));
        let image_filename = 'images/face' + file_id + '.png';
        console.log(image_filename);
        const insertedImage = await jimp.read(image_filename);

        img = img.composite(insertedImage.resize(Math.round(img.bitmap.width / 2), Math.round(img.bitmap.height / 2)), Math.round(img.bitmap.width / 4), Math.round(img.bitmap.height / 4));
    }
    img.write(path);
    return 0;
}

async function downloadImage(url, path){
    const options = {
        url: url,
        dest: path
    }
    
    filename = '';
    try{
        filename = (await ImgDownload.image(options)).filename;
            console.log('Saved to', filename)  // Saved to /path/to/dest/photo.jpg
            return filename;
    }
    catch(e){
        console.error(e);
        return 1;
    }
}

function detect(path, classifier){
    switch(classifier){
        case classifiers.FACE:
            classifier = new cv.CascadeClassifier(cv.HAAR_FRONTALFACE_DEFAULT);
            break;
        case classifiers.EYE:
            classifier = new cv.CascadeClassifier(cv.HAAR_EYE);
            break;
        case classifiers.BODY:
            classifier = new cv.CascadeClassifier(cv.HAAR_FULLBODY);
            break;
        case classifiers.SMILE:
            classifier = new cv.CascadeClassifier(cv.HAAR_SMILE);
            console.log('smile selected');
            break;
        default:
            classifier = new cv.CascadeClassifier(cv.HAAR_FRONTALFACE_DEFAULT);
            console.log('face selected');
            break;
    }
    const mat = cv.imread(path);
    const matGray = mat.bgrToGray();
    return (classifier.detectMultiScale(matGray)).objects;
}

function drawDick(mat, point,size){
    const ballSize = size * 0.2;
    const center = point;
    let leftBall = new cv.Point(center.x - ballSize, center.y +  size * 0.3);
    let rightBall = new cv.Point(center.x + ballSize, center.y + size * 0.3);
    let shaftPos = new cv.Point(center.x,center.y - size * 0.1);
    mat.drawCircle(leftBall, ballSize, new cv.Vec(0, 255, 0), 5);
    mat.drawCircle(rightBall, ballSize, new cv.Vec(0, 255, 0), 5);
    let shaft = new cv.RotatedRect(shaftPos,new cv.Size(ballSize,size * 0.9), 0);
    mat.drawEllipse(shaft, new cv.Vec(0, 255, 0), 5);
    return mat
}

function dickhead(path){
    let points = detect(path, classifiers.FACE);
    const mat = cv.imread(path);
    if(points == 0){
        drawDick(mat, new cv.Point(mat.cols/2.0,mat.rows/2.0), mat.rows);
    }
    else{
        for(let i = 0; i < points.length; i++){
            drawDick(mat, new cv.Point(points[i].x + points[i].width/2.0,points[i].y + points[i].height/2.0), points[i].height);
        }
    }
    cv.imwrite(path,mat);
}

module.exports = {
    downloadImage:downloadImage,
    dickhead: dickhead,
    faceReplace:faceReplace,
    detect:detect,
    classifiers:classifiers
}