Incorrect bounding box centre detection during object recognition, OpenCV, Python

Question

I have a problem with defining the centre of an object using OpenCV (I'm using version 4.5.5.64). I am using "coco.names" for object recognition, and I have a function "show_distance" in my code, which is designed to calculate the centre of the bounding box of the recognised object. But the centre is calculated completely wrong. If the object is on the left side of the screen, the centre of the box is almost correctly positioned, but as the object moves to the right, the centre also shifts. Below I provide the project code, the project file on GitHub, and screenshots.

Code:

import cv2

thres = 0.45  # Threshold to detect object

cap = cv2.VideoCapture(0)

CLASS_FILE = "coco.names"
CONFIG_PATH = 'ssd_mobilenet_v3_large_coco_2020_01_14.pbtxt'
WEIGHTS_PATH = 'frozen_inference_graph.pb'
TEST_OBJECT = 'person'

cap.set(3, 1280)
cap.set(4, 720)
cap.set(10, 70)

def show_distance(img, box, screen_center_x, screen_center_y):
    obj_center_x = (box[0] + box[2]) // 2
    obj_center_y = (box[1] + box[3]) // 2
    distance_x = obj_center_x - screen_center_x
    distance_y = obj_center_y - screen_center_y
    
    text = f"Dist X: {distance_x}, Dist Y: {distance_y}"
    cv2.putText(img, text, (box[0] + 10, box[1] - 10),
        cv2.FONT_HERSHEY_COMPLEX, 0.5, (0, 255, 0), 1)
    
    cv2.circle(img, (obj_center_x, obj_center_y), 10, (0, 255, 0), -1)
    cv2.circle(img, (screen_center_x, screen_center_y), 10, (0, 0, 255))

def add_one_object(img, box, current_obj, confidence):
    color = (0, 255, 0)
    cv2.rectangle(img, box, color, thickness=2)
    cv2.putText(
        img, current_obj.upper(), (box[0] + 10, box[1] + 30),
        cv2.FONT_HERSHEY_COMPLEX, 1, (0, 255, 0), 2)

def main():
    classNames = []

    with open(CLASS_FILE, 'rt') as f:
        classNames = f.read().rstrip('\n').split('\n')

    net = cv2.dnn_DetectionModel(WEIGHTS_PATH, CONFIG_PATH)
    net.setInputSize(320, 320)
    net.setInputScale(1.0 / 127.5)
    net.setInputMean((127.5, 127.5, 127.5))
    net.setInputSwapRB(True)

    entered_name=TEST_OBJECT

    while True:
        success, img = cap.read()
        classIds, confs, bbox = net.detect(img, confThreshold=thres)

        if len(classIds) != 0:
            screen_center_x = img.shape[1] // 2
            screen_center_y = img.shape[0] // 2

            for classId, confidence, box in zip(classIds.flatten(), confs.flatten(), bbox):
                if classNames[classId - 1].lower() == entered_name:
                    add_one_object(img, box, classNames[classId - 1], confidence)
                    show_distance(img, box, screen_center_x, screen_center_y)
                    break

        cv2.imshow('Output', img)
        if cv2.waitKey(1) & 0xFF == ord('q'):
            break

    cap.release()
    cv2.destroyAllWindows()

if __name__ == "__main__":
    main()

The problematic part on GitHub:

https://github.com/OlegQm/coco_objects_recognition/tree/main/stackoverflow_test

Screenshots (generalised: the problem is that the green circle is almost never inside the green box, although it should be. The red circle is the centre of the window.

The object on the left side

The object on the middle

The object on the right side

I've tried changing the OpenCV version and checking the maths. It would be interesting to know at least if this problem is caused by any technical issues or my mistake, but a solution would be ideal.

Answer 1

My mistake was that I misunderstood the coordinates of the boundary box.

You'll need to replace:

obj_center_x = (box[0] + box[2]) // 2
obj_center_y = (box[1] + box[3]) // 2

with:

obj_center_x = (box[0] + box[2] // 2)
obj_center_y = (box[1] + box[3] // 2)