openCV:如何提高图像处理性能？

import cv2
import numpy as np

# 使用OpenMP加速
cv2.setUseOptimized(True)
cv2.setNumThreads(4)

image = cv2.imread('path_to_image')
gray = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)

import cv2

# 初始化CUDA
cuda_available = cv2.cuda.getCudaEnabledDeviceCount() > 0

if cuda_available:
    image = cv2.imread('path_to_image')
    gpu_image = cv2.cuda_GpuMat()
    gpu_image.upload(image)
    
    gpu_gray = cv2.cuda.cvtColor(gpu_image, cv2.COLOR_BGR2GRAY)
    gray = gpu_gray.download()

import cv2

image = cv2.imread('path_to_image', cv2.IMREAD_GRAYSCALE)
integral_image = cv2.integral(image)

# 使用积分图像进行快速区域求和
def fast_sum(integral_img, x1, y1, x2, y2):
    return integral_img[x2+1, y2+1] - integral_img[x1, y2+1] - integral_img[x2+1, y1] + integral_img[x1, y1]

import cv2

image = cv2.imread('path_to_image')
gray = np.empty_like(image[:, :, 0])
cv2.cvtColor(image, cv2.COLOR_BGR2GRAY, gray)

import cv2

image = cv2.imread('path_to_image')
small_image = cv2.resize(image, (0, 0), fx=0.5, fy=0.5)
gray = cv2.cvtColor(small_image, cv2.COLOR_BGR2GRAY)