else: labelled_rectangle_to_compare = Rectangle(int(labelled_rect[0]),int(labelled_rect[1]), int(labelled_rect[2]), int(labelled_rect[3])) #many labels else: if iteration == 0: if classifier_type == "S" and dataset =="training": relabel_x = int(labRect[0]) + int((110-100)/2) relabel_y = int(labRect[1]) + int((110-40)/2) closest_labelled_rectangle = Rectangle(relabel_x,relabel_y, int(labelled_rect[2]), int(labelled_rect[3])) else: closest_labelled_rectangle = Rectangle(int(labelled_rect[0]),int(labelled_rect[1]), int(labelled_rect[2]), int(labelled_rect[3])) # define first labelled rectangle as closest current_path = Line(detected_rectangle.getCenter(), closest_labelled_rectangle.getCenter()) closest_distance = current_path.getDistance() labelled_rectangle_to_compare = closest_labelled_rectangle else: if classifier_type == "S" and dataset =="training": relabel_x = int(labRect[0]) + int((110-100)/2) relabel_y = int(labRect[1]) + int((110-40)/2) labelled_rectangle = Rectangle(relabel_x,relabel_y, int(labelled_rect[2]), int(labelled_rect[3])) else: labelled_rectangle = Rectangle(int(labelled_rect[0]),int(labelled_rect[1]), int(labelled_rect[2]), int(labelled_rect[3])) # get straight line distance between the center of labelled and detection rectangles. current_path = Line(detected_rectangle.getCenter(), labelled_rectangle.getCenter()) current_distance = current_path.getDistance()