class EuglenaCounter {

    int roiX, roiY, roiWidth, roiHeight, lastMillis, avgTime;
    float previousAverage;
    boolean averageReady;

    OpenCV opencv;
    ArrayList<int> counts;

    EuglenaCounter(PApplet parent, int roiX, int roiY, int roiWidth, int roiHeight, int avgTime){
        this.counts = new ArrayList<int>();
        this.roiX = roiX;
        this.roiY = roiY;
        this.roiWidth = roiWidth;
        this.roiHeight = roiHeight;
        this.avgTime = avgTime;

        this.opencv = new OpenCV(parent, roiWidth, roiHeight);
        this.opencv.startBackgroundSubtraction(7, 3, .35);

        this.reset();
    }

    void reset(){
        this.lastMillis = millis();
        this.counts.clear();
        this.averageReady = false;
        this.previousAverage = -1;
    }

    void update() {
        pImage roiFrame = get(roiX, roiY, roiWidth, roiHeight); // Get pixels of interest and saves as image for valid image path
        this.opencv.loadImage(roiFrame);   // Input proper pixels into cv processing
        this.opencv.updateBackground();    //Necessary for background subtraction
        this.opencv.useGray();             //Create grayscale image
        this.opencv.dilate();              //Clean up image
        this.opencv.erode();
        this.opencv.blur(3);
        //dst = opencv.getOutput();     //Save computer vision as separate image path
        //Find outline of moving objects - euglena
        int count = opencv.findContours().size(); // Count number of outlines
        this.counts.add(count);

        int interval = millis() - this.lastMillis();
        if (interval > this.avgTime) {
            this.previousAverage = 0;
            for (int c : this.counts) {
                this.previousAverage = this.previousAverage + c;
            }
            this.previousAverage = this.previousAverage / this.counts.size();
            this.averageReady = true;
            this.counts.clear();

        }
    }
}