Bad argument in function 'rectangle'

[cabarini]

I could not run the project. I ran all the steps but when i try to run some samples i received always the same message error.

error: (-5:Bad argument) in function 'rectangle'

File "J:_Profissional\plate\core\utils.py", line 262, in draw_bbox cv2.rectangle(image, c1, (np.float32(c3[0]), np.float32(c3[1])), bbox_color, -1) #filled cv2.error: OpenCV(4.5.2) :-1: error: (-5:Bad argument) in function 'rectangle'

Overload resolution failed:

• Can't parse 'pt1'. Sequence item with index 0 has a wrong type
• Can't parse 'pt1'. Sequence item with index 0 has a wrong type
• Can't parse 'rec'. Expected sequence length 4, got 2
• Can't parse 'rec'. Expected sequence length 4, got 2

Some could help me?

[cabarini]

I solved my issue parsing to int all the arguments in 'rectangle' and 'put_text' functions.

[MohammedZayn]

can you show me how

[adeayopy]

Can you explain more please,I am running to same issue here

[anzharip]

For anyone having issues, try to modify this function inside core/utils.py into this:

def draw_bbox(image, bboxes, info = False, counted_classes = None, show_label=True, allowed_classes=list(read_class_names(cfg.YOLO.CLASSES).values()), read_plate = False):
    classes = read_class_names(cfg.YOLO.CLASSES)
    num_classes = len(classes)
    image_h, image_w, _ = image.shape
    hsv_tuples = [(1.0 * x / num_classes, 1., 1.) for x in range(num_classes)]
    colors = list(map(lambda x: colorsys.hsv_to_rgb(*x), hsv_tuples))
    colors = list(map(lambda x: (int(x[0] * 255), int(x[1] * 255), int(x[2] * 255)), colors))

    random.seed(0)
    random.shuffle(colors)
    random.seed(None)

    out_boxes, out_scores, out_classes, num_boxes = bboxes
    for i in range(num_boxes):
        if int(out_classes[i]) < 0 or int(out_classes[i]) > num_classes: continue
        coor = out_boxes[i]
        fontScale = 0.5
        score = out_scores[i]
        class_ind = int(out_classes[i])
        class_name = classes[class_ind]
        if class_name not in allowed_classes:
            continue
        else:
            if read_plate:
                height_ratio = int(image_h / 25)
                plate_number = recognize_plate(image, coor)
                if plate_number != None:
                    cv2.putText(image, plate_number, (int(coor[0]), int(coor[1]-height_ratio)), 
                            cv2.FONT_HERSHEY_SIMPLEX, 1.25, (255,255,0), 2)

            bbox_color = colors[class_ind]
            bbox_thick = int(0.6 * (image_h + image_w) / 600)
            c1, c2 = (int(coor[0]), int(coor[1])), (int(coor[2]), int(coor[3]))
            cv2.rectangle(img=image, pt1=c1, pt2=c2, color=bbox_color, thickness=bbox_thick)

            if info:
                print("Object found: {}, Confidence: {:.2f}, BBox Coords (xmin, ymin, xmax, ymax): {}, {}, {}, {} ".format(class_name, score, coor[0], coor[1], coor[2], coor[3]))

            if show_label:
                bbox_mess = '%s: %.2f' % (class_name, score)
                t_size = cv2.getTextSize(bbox_mess, 0, fontScale, thickness=bbox_thick // 2)[0]
                c3 = (c1[0] + t_size[0], c1[1] - t_size[1] - 3)
                cv2.rectangle(img=image, pt1=c1, pt2=(int(c3[0]), int(c3[1])), color=bbox_color, thickness=-1) #filled

                cv2.putText(image, bbox_mess, (int(c1[0]), int(c1[1] - 2)), cv2.FONT_HERSHEY_SIMPLEX,
                        fontScale, (0, 0, 0), bbox_thick // 2, lineType=cv2.LINE_AA)

            if counted_classes != None:
                height_ratio = int(image_h / 25)
                offset = 15
                for key, value in counted_classes.items():
                    cv2.putText(image, "{}s detected: {}".format(key, value), (5, offset),
                            cv2.FONT_HERSHEY_COMPLEX_SMALL, 1, (0, 255, 0), 2)
                    offset += height_ratio
    return image