Python与C++之间运行速度对比

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很多人说python语言运行速度慢，那么我用一个遍历图片像素的例子做对比。

准备工作

• 一张2048x1024大小的图片

  
  image.png

• opecv 2.0

• xcode 8.3

• python 2.7 PyCharm

C++代码

//处理边缘
Mat detectEdge(Mat &image)
{
    Mat resultImage = image.clone();
    int rows = resultImage.rows;
    int cols = resultImage.cols;
    for(int i = 0;i < rows;i++)
    {
        for(int j = 0;j < cols;j++)
        {
            //判断下边
            if(i!=rows-1&&resultImage.at<Vec4b>(i,j)!=resultImage.at<Vec4b>(i+1,j))
            {
                // road + sidewalk
                if (judgeHorizonPixels(resultImage, i, j, road, sidewalk)) {
                    resultImage.at<Vec4b>(i,j)=my_road_sidewalk;
                }
                // road + car
                else if (judgeHorizonPixels(resultImage, i, j, road, car)) {
                    resultImage.at<Vec4b>(i,j)=my_road_car;
                }
                // road + pole
                else if (judgeHorizonPixels(resultImage, i, j, road, pole)) {
                    resultImage.at<Vec4b>(i,j)=my_road_pole;
                }
                // road
                else if(image.at<Vec4b>(i,j)==road||image.at<Vec4b>(i+1,j)==road){
                    resultImage.at<Vec4b>(i,j)=my_road;
                }
                
                // building + pole
                else if (judgeHorizonPixels(resultImage, i, j, building, pole)) {
                    resultImage.at<Vec4b>(i,j)=my_building_pole;
                }
                // building + sidewalk
                else if (judgeHorizonPixels(resultImage, i, j, building, sidewalk)) {
                    resultImage.at<Vec4b>(i,j)=my_building_sidewalk;
                }
                // building + traffic sign
                else if (judgeHorizonPixels(resultImage, i, j, building, traffic_sign)) {
                    resultImage.at<Vec4b>(i,j)=my_building_traffic_sign;
                }
                // building + car
                else if (judgeHorizonPixels(resultImage, i, j, building, car)) {
                    resultImage.at<Vec4b>(i,j)=my_building_car;
                }
                // building + vegetation
                else if (judgeHorizonPixels(resultImage, i, j, building, vegetation)) {
                    resultImage.at<Vec4b>(i,j)=my_building_vegetation;
                }
                // building + sky
                else if (judgeHorizonPixels(resultImage, i, j, building, sky)) {
                    resultImage.at<Vec4b>(i,j)=my_building_sky;
                }
                // building + person
                else if (judgeHorizonPixels(resultImage, i, j, building, person)) {
                    resultImage.at<Vec4b>(i,j)=my_building_person;
                }
                // building
                else if(image.at<Vec4b>(i,j)==building||image.at<Vec4b>(i+1,j)==building){
                    resultImage.at<Vec4b>(i,j)=my_building;
                }
                
                // pole + car
                else if (judgeHorizonPixels(resultImage, i, j, pole, car)) {
                    resultImage.at<Vec4b>(i,j)=my_pole_car;
                }
                // pole + vegetation
                else if (judgeHorizonPixels(resultImage, i, j, pole, vegetation)) {
                    resultImage.at<Vec4b>(i,j)=my_pole_vegetation;
                }
                else{
                    resultImage.at<Vec4b>(i,j)=(Vec4b){0,0,0,255};
                }
            }
            //判断右边
            else if(j!=cols-1&&resultImage.at<Vec4b>(i,j)!=resultImage.at<Vec4b>(i,j+1))
            {
                // road + sidewalk
                if (judgeVerticalPixels(resultImage, i, j, road, sidewalk)) {
                    resultImage.at<Vec4b>(i,j)=my_road_sidewalk;
                }
                // road + car
                else if (judgeVerticalPixels(resultImage, i, j, road, car)) {
                    resultImage.at<Vec4b>(i,j)=my_road_car;
                }
                // road + pole
                else if (judgeVerticalPixels(resultImage, i, j, road, pole)) {
                    resultImage.at<Vec4b>(i,j)=my_road_pole;
                }
                // road
                else if(image.at<Vec4b>(i,j)==road||image.at<Vec4b>(i,j+1)==road){
                    resultImage.at<Vec4b>(i,j)=my_road;
                }
                
                // building + pole
                else if (judgeVerticalPixels(resultImage, i, j, building, pole)) {
                    resultImage.at<Vec4b>(i,j)=my_building_pole;
                }
                // building + sidewalk
                else if (judgeVerticalPixels(resultImage, i, j, building, sidewalk)) {
                    resultImage.at<Vec4b>(i,j)=my_building_sidewalk;
                }
                // building + traffic sign
                else if (judgeVerticalPixels(resultImage, i, j, building, traffic_sign)) {
                    resultImage.at<Vec4b>(i,j)=my_building_traffic_sign;
                }
                // building + car
                else if (judgeVerticalPixels(resultImage, i, j, building, car)) {
                    resultImage.at<Vec4b>(i,j)=my_building_car;
                }
                // building + vegetation
                else if (judgeVerticalPixels(resultImage, i, j, building, vegetation)) {
                    resultImage.at<Vec4b>(i,j)=my_building_vegetation;
                }
                // building + sky
                else if (judgeVerticalPixels(resultImage, i, j, building, sky)) {
                    resultImage.at<Vec4b>(i,j)=my_building_sky;
                }
                // building + person
                else if (judgeVerticalPixels(resultImage, i, j, building, person)) {
                    resultImage.at<Vec4b>(i,j)=my_building_person;
                }
                // building
                else if(image.at<Vec4b>(i,j)==building||image.at<Vec4b>(i,j+1)==building){
                    resultImage.at<Vec4b>(i,j)=my_building;
                }
                
                // pole + car
                else if (judgeVerticalPixels(resultImage, i, j, pole, car)) {
                    resultImage.at<Vec4b>(i,j)=my_pole_car;
                }
                // pole + vegetation
                else if (judgeVerticalPixels(resultImage, i, j, pole, vegetation)) {
                    resultImage.at<Vec4b>(i,j)=my_pole_vegetation;
                }
                else{
                    resultImage.at<Vec4b>(i,j)=(Vec4b){0,0,0,255};
                }
            }else
            {
                resultImage.at<Vec4b>(i,j)=(Vec4b){0,0,0,255};
            }
        }
    }
    return resultImage;
}
int main(int argc, const char * argv[]) {
    
    Mat image=imread("/Users/gcf/Desktop/test.png",CV_LOAD_IMAGE_UNCHANGED);
    clock_t startTime,endTime;
    startTime = clock();
    Mat resultImage=detectEdge(image);
    endTime = clock();
    cout << "Totle Time : " <<(double)(endTime - startTime) / CLOCKS_PER_SEC << "s" << endl;
    imwrite("/Users/gcf/Desktop/22.png", resultImage);
    return 0;
}

image.png

Python代码

# 处理边缘
def edge_classifier(img):
    image2 = copy.deepcopy(img)
    rows = image2.shape[0]
    cols = image2.shape[1]
    # 遍历所有像素并设置像素值BGRA
    for i in xrange(rows):
        for j in xrange(cols):
            # 判断下边
            if i != rows - 1 and (image2[i, j] == image2[i + 1, j]).all() == False:
                # road + sidewalk
                if judge_horizon_pixels(image2, i, j, road, sidewalk):
                    image2[i, j] = my_road_sidewalk
                # road + car
                elif judge_horizon_pixels(image2, i, j, road, car):
                    image2[i, j] = my_road_car
                # road + pole
                elif judge_horizon_pixels(image2, i, j, road, pole):
                    image2[i, j] = my_road_pole
                # road
                elif (image2[i, j] == road).all() or (image2[i + 1, j] == road).all():
                    image2[i, j] = my_road

                # building + pole
                elif judge_horizon_pixels(image2, i, j, building, pole):
                    image2[i, j] = my_building_pole
                # building + sidewalk
                elif judge_horizon_pixels(image2, i, j, building, sidewalk):
                    image2[i, j] = my_building_sidewalk
                # building + traffic sign
                elif judge_horizon_pixels(image2, i, j, building, traffic_sign):
                    image2[i, j] = my_building_traffic_sign
                # building + car
                elif judge_horizon_pixels(image2, i, j, building, car):
                    image2[i, j] = my_building_car
                # building + vegetation
                elif judge_horizon_pixels(image2, i, j, building, vegetation):
                    image2[i, j] = my_building_vegetation
                # building + sky
                elif judge_horizon_pixels(image2, i, j, building, sky):
                    image2[i, j] = my_building_sky
                # building + person
                elif judge_horizon_pixels(image2, i, j, building, person):
                    image2[i, j] = my_building_person
                # building
                elif (image2[i, j] == building).all() or (image2[i + 1, j] == building).all():
                    image2[i, j] = my_building

                # pole + car
                elif judge_horizon_pixels(image2, i, j, pole, car):
                    image2[i, j] = my_pole_car
                # pole + vegetation
                elif judge_horizon_pixels(image2, i, j, pole, vegetation):
                    image2[i, j] = my_pole_vegetation
                else:
                    image2[i, j] = [0, 0, 0, 255]
            # 判断右边
            elif j != cols - 1 and (image2[i, j] == image2[i, j + 1]).all() == False:
                # road + sidewalk
                if judge_vertical_pixels(image2, i, j, road, sidewalk):
                    image2[i, j] = my_road_sidewalk
                # road + car
                elif judge_vertical_pixels(image2, i, j, road, car):
                    image2[i, j] = my_road_car
                # road + pole
                elif judge_vertical_pixels(image2, i, j, road, pole):
                    image2[i, j] = my_road_pole
                # road
                elif (image2[i, j] == road).all() or (image2[i, j + 1] == road).all():
                    image2[i, j] = my_road

                # building + pole
                elif judge_vertical_pixels(image2, i, j, building, pole):
                    image2[i, j] = my_building_pole
                # building + sidewalk
                elif judge_vertical_pixels(image2, i, j, building, sidewalk):
                    image2[i, j] = my_building_sidewalk
                # building + traffic sign
                elif judge_vertical_pixels(image2, i, j, building, traffic_sign):
                    image2[i, j] = my_building_traffic_sign
                # building + car
                elif judge_vertical_pixels(image2, i, j, building, car):
                    image2[i, j] = my_building_car
                # building + vegetation
                elif judge_vertical_pixels(image2, i, j, building, vegetation):
                    image2[i, j] = my_building_vegetation
                # building + sky
                elif judge_vertical_pixels(image2, i, j, building, sky):
                    image2[i, j] = my_building_sky
                # building + person
                elif judge_vertical_pixels(image2, i, j, building, person):
                    image2[i, j] = my_building_person
                # building
                elif (image2[i, j] == building).all() or (image2[i, j + 1] == building).all():
                    image2[i, j] = my_building

                # pole + car
                elif judge_vertical_pixels(image2, i, j, pole, car):
                    image2[i, j] = my_pole_car
                # pole + vegetation
                elif judge_vertical_pixels(image2, i, j, pole, vegetation):
                    image2[i, j] = my_pole_vegetation
                else:
                    image2[i, j] = [0, 0, 0, 255]
            else:
                image2[i, j] = [0, 0, 0, 255]
    return image2
# 只判断右下领域，值不同则保留当前值。RGBA
def detect_RGBA_edge():
    img = cv2.imread('//Users/gcf/Desktop/test.png',cv2.IMREAD_UNCHANGED)
    starttime = datetime.datetime.now()
    image2 = edge_classifier(img)
    endtime = datetime.datetime.now()
    print 'Totle Time : %ds'%(endtime-starttime).seconds
    cv2.imwrite('/Users/gcf/Desktop/11.png', image2)

image.png
image.png

总结

C++运行速度为0.25秒，而python需要足足23秒，有时更需要27秒，速度方面确实没有可比性，慢了两个数量级。为啥还那么多人用python呢？

• 其实很多python库都是用C或C++实现的，而当我们只关注上层极少数逻辑代码时，那么它的运行速度并没有想象中的那么慢。
• 从以上列子中很难看出python代码的简洁性，实际上python代码是非常简洁优雅的，花费少量时间写代码，运行时间可以通过并行GPU等手段优化，尤其在机器学习中，让我们有更多时间关注算法本身。