有没有一种方法可以在比较图像时在opencv中设置阈值？

import cv2
import numpy as np

# 读取两幅图像
img1 = cv2.imread('image1.jpg', 0)
img2 = cv2.imread('image2.jpg', 0)

# 计算绝对差值
diff = cv2.absdiff(img1, img2)

# 应用阈值
_, thresh = cv2.threshold(diff, 30, 255, cv2.THRESH_BINARY)

cv2.imshow('Thresholded Difference', thresh)
cv2.waitKey(0)
cv2.destroyAllWindows()

from skimage.metrics import structural_similarity as ssim

# 计算SSIM指数
(score, diff) = ssim(img1, img2, full=True)
diff = (diff * 255).astype("uint8")

# 应用阈值
_, thresh = cv2.threshold(diff, 30, 255, cv2.THRESH_BINARY)

cv2.imshow('SSIM Difference', thresh)
cv2.waitKey(0)
cv2.destroyAllWindows()

def mse(img1, img2):
    return np.mean((img1 - img2) ** 2)

def psnr(img1, img2):
    mse_value = mse(img1, img2)
    if mse_value == 0:
        return float('inf')
    max_pixel = 255.0
    return 20 * np.log10(max_pixel / np.sqrt(mse_value))

mse_value = mse(img1, img2)
psnr_value = psnr(img1, img2)

print(f'MSE: {mse_value}')
print(f'PSNR: {psnr_value}')