用goto语句勾画C++块

Question

我一直在编写一个C++代码，我遇到了一种被困在其中的情况。程序员使用goto语句来实现他的逻辑，而且由于Python中没有goto语句，而且由于我不想钻研它的有趣的goto实现，所以我想知道我们是否可以以某种方式对以下块进行Python化：

// Loop over all detected circles of the input image
    for (int j = 0; j < circle_radius_vec.size(); ++j)
    {   
        Jump: 

        // Variables for ROI
        int roi_height_width = 0;
        int roi_corner_x = 0;
        int roi_corner_y = 0;

        Point center_now(roi_height_width/2, roi_height_width/2);

        // Load aktuellen center point
        center_now = center_vec[j];

        // Calculate ROI 
        roi_height_width = circle_radius_vec[j];
        roi_corner_x = center_now.x - roi_height_width/2;
        roi_corner_y = center_now.y - roi_height_width/2;   

        // If ROI is outside of image skip circle
        if(roi_corner_x < 0){j++; goto Jump;}
        if(roi_corner_y < 0){j++; goto Jump;}
        if((roi_corner_x+roi_height_width) > input_img.cols){j++; goto Jump;}
        if((roi_corner_y+roi_height_width) > input_img.rows){j++; goto Jump;}

        // Create ROI from input image
        Rect roi = Rect(roi_corner_x, roi_corner_y, roi_height_width, roi_height_width);
        Mat img_roi = input_img(roi);

        // Create HSV representation of ROI
        Mat hsv;
        cvtColor(img_roi, hsv, COLOR_BGR2HSV);
        ...

他有一个叫做“跳跃”的标签。我们怎么能把这幅画化为灰烬？由于我们已经处于for循环中，所以我有点不愿意引入更多的循环。

提前谢谢。

编辑：--感谢贡献者，提出了以下建议，但是这会陷入一个无限循环中：

# Loop over all detected circles of the input image
    for j in range(len(center_vec)):
        while True:
            # arrange the ROI
            # load the current center point
            center_now = center_vec[j] # take the center of ROI as the center of circle
            roi_height_width = int(round(circle_radius_vec[j])) # take the radius as height and width of the ROI
            roi_height_width = int(round(circle_radius_vec[j]))

            roi_corner_x = int(round(center_now[0] - roi_height_width / 2))
            roi_corner_y = int(round(center_now[1] - roi_height_width / 2))

            # If ROI is outside of image skip circle
            if roi_corner_x < 0:
                j += 1
                continue
            if roi_corner_y < 0:
                j += 1
                continue
            if roi_corner_x + roi_height_width > img.shape[1]:
                j += 1
                continue
            if roi_corner_y + roi_height_width > img.shape[0]:
                j += 1
                continue

        # create ROI from input image Rect
        roi = img[roi_corner_y:roi_corner_y+roi_height_width, roi_corner_x:roi_corner_x+roi_height_width]

        # Create HSV representation of ROI
        hsv = cv2.cvtColor(roi, cv2.COLOR_BGR2HSV)

Answer 1

C++代码需要重做：goto语句和索引的增加相当于continue指令(在C/C++程序中几乎不需要goto，这里绝对不需要原始的C++代码，因为作者不知道它的存在，所以它“模拟”了continue )：

for (int j = 0; j < circle_radius_vec.size(); ++j)
    {   
        ..
        // If ROI is outside of image skip circle
        if(roi_corner_x < 0){continue;}

注意，现在不需要手动增加索引，因为continue跳到下一个迭代，调用循环的++j。

( incrementation+goto的另一个问题是，如果特殊情况发生在数组的末尾，那么您可以在数组的边界之外读取:未定义的行为)

现在，您可以在python中直接转置:您有两个选项：

要么使用索引(就像C++代码那样)

for index in range(size):        
    ...
    if some_condition:
        continue

或者只是在元素上迭代(更多的pythonic元素，因为它不使用索引)：

for a in the_list:
    # a is the current element of the list, not the index
    ...
    if some_condition:
        continue

在这两种情况下，for循环控制迭代。您只需告诉python跳过使用continue的下一次迭代，就像在“新”C++代码中一样。

Answer 2

由于所有跳转似乎都是由j++预先执行的，而跳转是循环的开始，所以似乎Python语句可以很容易地解决您的问题？

# Loop over all detected circles of the input image
for in range(1, circle_radius_vec.size()):

    # Variables for ROI
    roi_height_width = 0
    roi_corner_x = 0
    roi_corner_y = 0

    Point center_now(roi_height_width/2, roi_height_width/2)

    # Load aktuellen center point
    center_now = center_vec[j]

    # Calculate ROI 
    roi_height_width = circle_radius_vec[j]
    roi_corner_x = center_now.x - roi_height_width/2
    roi_corner_y = center_now.y - roi_height_width/2   

    # If ROI is outside of image skip circle
    if roi_corner_x < 0 or roi_corner_y < 0 or roi_corner_x + roi_height_width > input_img.cols or roi_corner_y + roi_height_width > input_img.rows:
        continue

    # Create ROI from input image
    Rect roi = Rect(roi_corner_x, roi_corner_y, roi_height_width, roi_height_width)
    img_roi = input_img(roi)

    # Create HSV representation of ROI
    hsv()
    cvtColor(img_roi, hsv, COLOR_BGR2HSV)
    ...

我个人只需要反转if语句并有条件地执行代码的下半部分，如下所示：

# Loop over all detected circles of the input image
for in range(1, circle_radius_vec.size()):

    # Variables for ROI
    roi_height_width = 0
    roi_corner_x = 0
    roi_corner_y = 0

    Point center_now(roi_height_width/2, roi_height_width/2)

    # Load aktuellen center point
    center_now = center_vec[j]

    # Calculate ROI 
    roi_height_width = circle_radius_vec[j]
    roi_corner_x = center_now.x - roi_height_width/2
    roi_corner_y = center_now.y - roi_height_width/2   

    # If ROI is outside of image skip circle
    if roi_corner_x >= 0 and roi_corner_y >= 0 and roi_corner_x + roi_height_width <= input_img.cols and roi_corner_y + roi_height_width <= input_img.rows:


        # Create ROI from input image
        Rect roi = Rect(roi_corner_x, roi_corner_y, roi_height_width, roi_height_width)
        img_roi = input_img(roi)

        # Create HSV representation of ROI
        hsv()
        cvtColor(img_roi, hsv, COLOR_BGR2HSV)
        ...

Answer 3

好的。我建议你这么做。

# Loop over all detected circles ot the input image.
for j in range(len(circle_radius_vec)):
    # Variables for ROI.
    roi_height_width = 0
    roi_corner_x = 0
    roi_corner_y = 0

    # Calculate ROI 
    roi_height_width = circle_radius_vec[j]
    roi_corner_x = center_now.x - roi_height_width/2
    roi_corner_y = center_now.y - roi_height_width/2

    center_now = Point(roi_height_width/2, roi_height_width/2)

    # Load aktuellen center point.
    center_now = center_vec[j]

    # Calculate ROI.
    if roi_corner_x < 0:
        continue
    if roi_corner_y < 0:
        continue
    if roi_corner_x + roi_height_width > input_img.cols:
        continue


    # Create ROI from input image.
    roi = Rect(roi_corner_x, roi_corner_y, roi_height_width, roi_height_width)
    img_roi = input_img(roi)

    # Create HSV representation of ROI.
    hsv = None
    cvtColor(img_roi, hsv, COLOR_BGR2HSV)

因为我不知道剩下的代码，所以我不能说得很准确。请告诉我是否有任何错误发生。