Высокая загрузка процессора и памяти - PullRequest
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Высокая загрузка процессора и памяти

0 голосов
/ 27 сентября 2019

Я использую opencv4nodejs в производстве, чтобы выяснить разницу между двумя скриншотами.Сначала я получаю снимки экрана с URL-адресов, а затем создаю растровое изображение, которое показывает разницу между ними.Но этот код потребляет много ресурсов процессора и накапливает память.Не могли бы вы помочь мне с этим?Есть ли утечка памяти или я что-то не так делаю?Пожалуйста, помогите !!

Это код, который я написал. 

    // main entry function



exports.calculateDiff = async (screenshotUrl, targetScreenshotUrl, request) => {
        let screenshot, targetScreenshot, bitmapImage, kernel, cannyImage, morphedImage, contours, coordinates, percentageDiff, screenshotBuf, targetScreenshotBuf
        try {
        let resp = await getScreenshotsBufs(screenshotUrl, targetScreenshotUrl)
        screenshotBuf = resp.screenshotBuf
        targetScreenshotBuf = resp.targetScreenshotBuf
        screenshot = cv.imdecode(screenshotBuf).bgrToGray()
        targetScreenshot = cv.imdecode(targetScreenshotBuf).bgrToGray()
        request.log([task],${seq_no}- Getting Bitmap Image)
        bitmapImage = await getBitmapImage(screenshot, targetScreenshot)
        kernel = cv.getStructuringElement(cv.MORPH_RECT, new cv.Size(20, 20), new cv.Point(-1,-1))
        request.log([task],${seq_no}- Detecting Edges of Bitmap Image)
        cannyImage = bitmapImage.canny(1, 254)
        morphedImage = cannyImage.morphologyEx(kernel, cv.MORPH_CLOSE, new cv.Point2(-1, -1), 1, cv.BORDER_CONSTANT)
        request.log([task],${seq_no}- Finding Contours)
        contours = morphedImage.findContours(cv.RETR_EXTERNAL, cv.CHAIN_APPROX_SIMPLE, new cv.Point2(0, 0))
        coordinates = new Array(contours.length)
        let diffArea = 0
        for (let iter=0; iter < contours.length; iter++) {
        let rect = contours[iter].boundingRect()
        diffArea += rect.width * rect.height
        let coordinate = new Array(rect.x, rect.y, rect.x + rect.width, rect.y + rect.height)
        coordinates[iter] = coordinate
        }
        percentageDiff = calPercentageDiff(diffArea, bitmapImage.cols, bitmapImage.rows)
        request.log([task],${seq_no}- Getting DiffImage)
        //let diffImage = await getDiffImage(screenshotBuf, targetScreenshotBuf)
        request.log([task],${seq_no}- Task Completed)
        screenshot.release()
        targetScreenshot.release()
        bitmapImage.release()
        cannyImage.release()
        morphedImage.release()
        return {
        //diffImage: diffImage.toString('base64'),
        coordinates: coordinates,
        percentageDiff: percentageDiff
        }
        } catch (err) {
        throw err
        }

        const getScreenshotsBufs = async (screenshotUrl, targetScreenshotUrl) => {
        let screenshotBuf, targetScreenshotBuf
        await axios.all([getScreenshot(screenshotUrl), getScreenshot(targetScreenshotUrl)])
        .then(axios.spread(function (screenshotResp, targetScreenshotResp) {
        screenshotBuf = screenshotResp.data
        targetScreenshotBuf = targetScreenshotResp.data
        }))
        return {
        screenshotBuf: screenshotBuf,
        targetScreenshotBuf: targetScreenshotBuf
        }
        }

        const getScreenshot = (url) => {
        return axios.get(url, {responseType: 'arraybuffer'})
        }

        const getBitmapImage = (screenshot, targetScreenshot) => {

        // this function will return a bitmap image. which denotes the differences between them.
        let bitmapRows, bitmapCols, intersectingRows, intersectingCols, bitmapPixels
        bitmapRows = Math.max(screenshot.rows, targetScreenshot.rows)
        bitmapCols = Math.max(screenshot.cols, targetScreenshot.cols)
        intersectingRows = Math.min(screenshot.rows, targetScreenshot.rows)
        intersectingCols = Math.min(screenshot.cols, targetScreenshot.cols)
        bitmapPixels = Array(bitmapRows).fill().map(() => Array(bitmapCols).fill(255))
        let screenshotPixels = new Uint8Array(screenshot.getData())
        let targetScreensohtPixels = new Uint8Array(targetScreenshot.getData())
        for( let row = 0; row < intersectingRows; row++) {
        for( let col = 0; col < intersectingCols; col++) {
        if (Math.abs(screenshotPixels[row * intersectingCols + col] - targetScreensohtPixels[row * intersectingCols + col]) < 5) {
        bitmapPixels[row][col] = 0
        }
        }
        }
        return new cv.Mat(bitmapPixels, cv.CV_8U)
        }
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