轮廓检测，然后判断轮廓大小，识别位置

import cv2


def cv_show(img):  # 展示图片
    cv2.imshow("img", img)
    cv2.waitKey(0)
    cv2.destroyAllWindows()


img = cv2.imread("bg.png")
gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)  # 灰度图片

img2 = cv2.GaussianBlur(gray, (5, 5), 0)  # 高斯模糊
v1 = cv2.Canny(img2, 20, 80)  # 边缘检测， 20和80分别为两个阈值
cv_show(v1)

counts, _ = cv2.findContours(v1, cv2.RETR_TREE, cv2.CHAIN_APPROX_SIMPLE)  # 轮廓检测

result = img.copy()
color = (0, 255, 0)
for c in counts:
    area = cv2.contourArea(c, True)
    x, y, w, h = cv2.boundingRect(c)  # 计算x，y，宽，高
    if w > 100 or w < 50 or h > 70 or h < 50:  # 按照实际缺口的大小调整过滤条件
        continue

    print(x, y, w, h)
    cv2.rectangle(result, (x, y), (x + w, y + h), color, 1)  # 画出矩形框

cv_show(result)  # 展示最终结果图