如何使用Python Opencv检测特定区域内的移动？

import cv2
import numpy as np

cap = cv2.VideoCapture(0)  # 0表示默认摄像头

ret, frame = cap.read()
prev_frame = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)

while True:
    ret, frame = cap.read()
    gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
    
    # 计算当前帧与初始帧的差异
    frame_diff = cv2.absdiff(prev_frame, gray)
    
    # 对差异图像进行阈值处理
    _, thresh = cv2.threshold(frame_diff, 30, 255, cv2.THRESH_BINARY)
    
    # 对阈值图像进行腐蚀和膨胀操作，以去除噪声
    kernel = np.ones((5, 5), np.uint8)
    thresh = cv2.morphologyEx(thresh, cv2.MORPH_OPEN, kernel)
    
    # 在阈值图像中寻找轮廓
    contours, _ = cv2.findContours(thresh, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)
    
    # 遍历轮廓，筛选出位于特定区域内的移动物体
    for contour in contours:
        x, y, w, h = cv2.boundingRect(contour)
        
        # 判断轮廓的中心点是否在特定区域内
        if x > x_min and x + w < x_max and y > y_min and y + h < y_max:
            # 在移动物体周围绘制矩形框
            cv2.rectangle(frame, (x, y), (x + w, y + h), (0, 255, 0), 2)
    
    # 显示处理后的视频帧
    cv2.imshow('Motion Detection', frame)
    
    # 更新初始帧
    prev_frame = gray
    
    # 按下'q'键退出循环
    if cv2.waitKey(1) & 0xFF == ord('q'):
        break

# 释放摄像头并关闭窗口
cap.release()
cv2.destroyAllWindows()