previous detection

class ObjectDetector:
    def __init__(self, overlayFile):
        self._overlayFile = overlayFile
        self._contoursImage = None
        self._contours = None

    def createContourOverlay(self):
        kernel = np.ones((2,2),np.uint8)

        self._contoursImage = cv2.imread(self._overlayFile)

        lower = [1, 0 ,20]
        upper = [60, 40, 200]
        lower = np.array(lower, dtype="uint8")
        upper = np.array(upper, dtype="uint8")

        mask = cv2.inRange(self._contoursImage, lower, upper)
        output = cv2.bitwise_and(self._contoursImage, self._contoursImage, mask=mask)

        dilation = cv2.dilate(mask, kernel, iterations=3)
        closing = cv2.morphologyEx(dilation, cv2.MORPH_GRADIENT, kernel)
        closing = cv2.morphologyEx(dilation, cv2.MORPH_CLOSE, kernel)
        edges = cv2.Canny(self._contoursImage, 175, 175)
        lines = cv2.HoughLinesP(edges, 1, np.pi/180, 20)
        for line in lines:
            x1,y1, x2, y2 = line[0]
            cv2.line(self._contoursImage, (x1, y1) , (x2, y2), (0, 255, 0), 3)

        self._contours, hierarchy = cv2.findContours(edges, cv2.RETR_TREE, cv2.CHAIN_APPROX_SIMPLE)

    def detectObject(self, img, detectCallback, noDetectCallback=None):
        kernel = np.ones((2,2),np.uint8)

        widthAlert = np.size(img, 1)
        heightAlert = np.size(img, 0)
        yAlert = int((heightAlert / 2)) + 100


        lower = [0, 0 ,0]
        upper = [122, 122, 122]
        lower = np.array(lower, dtype="uint8")
        upper = np.array(upper, dtype="uint8")

        mask = cv2.inRange(img, lower, upper)
        output = cv2.bitwise_and(img, img, mask=mask)

        dilation = cv2.dilate(mask, kernel, iterations=3)
        #closing = cv2.morphologyEx(dilation, cv2.MORPH_GRADIENT, kernel)
        closing = cv2.morphologyEx(dilation, cv2.MORPH_CLOSE, kernel)
        edge = cv2.Canny(closing, 175, 175)

        contours, hierarchy = cv2.findContours(edge, cv2.RETR_TREE, cv2.CHAIN_APPROX_SIMPLE)

        threshold_area = 50
        centers = []

        if len(contours) !=0:
            for x in contours:
                #find the area of each contour
                area = cv2.contourArea(x)
                #find the center of each contour
                moments = cv2.moments(x)
                #weed out the contours that are less than our threshold
                if area > threshold_area:
                    (x,y,w,h) = cv2.boundingRect(x)

                    centerX = int((x+x+w)/2)
                    centerY = int((y+y+h)/2)

                    cv2.circle(img,(centerX, centerY), 7, (255, 255, 255), -1)

                    # Verify if the center of the circle is inside the countours
                    isInside = False
                    for cnt in self._contours:
                        dist = cv2.pointPolygonTest(cnt,(centerX, centerY),True)
                        if dist > 0:
                            isInside = True
                            break

                    if isInside:
                        logging.info("DETECT")
                        detectCallback()
                        #cv2.putText(img, "DENTRO", (centerX, centerY), cv2.FONT_HERSHEY_SIMPLEX, 0.5, (255,255,255),2)
                    else:
                        logging.info("NO DETECT")
                        if noDetectCallback != None:
                            noDetectCallback()
                        #cv2.putText(img, "FUERA", (centerX, centerY), cv2.FONT_HERSHEY_SIMPLEX, 0.5, (255,255,255),2)

        #return cv2.addWeighted(img_overlay,0.5,img,0.5,0)