使用 goto 语句C++块进行 python化

Pythonizing C++ block with goto statement

本文关键字：python goto 语句 C++ 使用      更新时间：2023-10-16

我一直在对C++代码进行 Python 化，我遇到了一种我有点卡住的情况。程序员使用 goto 语句来实现他的逻辑，并且由于 Python 中没有 goto 语句，并且由于我不想深入研究它有趣的 goto 实现，我想知道我们是否可以以某种方式 Python 化以下块：

// 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，他去那里。我们如何将这个 Python 化？由于我们已经处于 for 循环中，因此我有点犹豫是否要引入更多循环。

提前谢谢。

编辑：感谢贡献者，提出了以下建议，但是这陷入了无限循环：

# 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)

C++代码需要返工：goto语句和索引增加相当于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++代码正在"模拟"continue，因为作者不知道它的存在(：

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

请注意，现在您不需要手动增加索引，因为continue会跳到下一次迭代，调用循环的++j。

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

现在，您可以直接在 python 中转置它：您有 2 个选项：

要么使用索引(就像你的C++代码一样(

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

或者只是迭代元素(更pythonic，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循环都控制迭代。你只需告诉python跳到下一次迭代continue，就像在"新"C++代码中一样。

由于所有的跳转似乎都以 j++ 开头，并且跳转是循环的开始，因此 Python 继续语句似乎很容易解决您的问题？

# 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)
...

我个人只会反转 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)
...

当然。 我会建议这个。

# 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)

由于我不知道其余的代码，所以我不能太准确。 如果发生任何错误，请告诉我。

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