def main(array):
    for x, value in enumerate(array):
        img = cv2.imread(value)

        lower_red = numpy.array([255,255,255])
        upper_red = numpy.array([255,255,255])
        mask = cv2.inRange(img, lower_red, upper_red)

        contours, hierarchy = cv2.findContours(mask, cv2.RETR_LIST, cv2.CHAIN_APPROX_SIMPLE)

        # area1 and area2 are the range of contour area, change accordingly
        area1 = 100
        area2 = 1000
        totalDots = []

        # Count the total number of contours
        for cnt in contours:
            if area1 < cv2.contourArea(cnt) < area2:
                totalDots.append(cnt)

        i = 0
        for c in contours:
            i += 1
            # compute the center of the contour
            M = cv2.moments(c)
            cX = int(M["m10"] / M["m00"])
            cY = int(M["m01"] / M["m00"])

            # draw the contour and center of the shape on the image
            #cv2.drawContours(img, [c], -1, (0, 255, 0), 2)
            cv2.circle(img, (cX, cY), 2, (255, 0, 0), -1)
            cv2.putText(img, str(i), (cX - 20, cY - 20),
                cv2.FONT_HERSHEY_SIMPLEX, 0.5, (0, 0, 255), 2)

        text = "Wszystkich obiektow na zdjeciu: {} ".format(len(totalDots))
        cv2.putText(img, text, (50, 20),  cv2.FONT_HERSHEY_SIMPLEX, 0.7, (200, 255, 255), 2)
        if len(percentage) > 0:
            text1 = "Udzial procentowy obiektow: {} %".format(percentage[x])
            cv2.putText(img, text1, (50, 40),  cv2.FONT_HERSHEY_SIMPLEX, 0.7, (200, 255, 255), 2)
        cv2.imshow(value, img)
        cv2.waitKey(0)