我一直在Python化一个C ++代码，我遇到了一种我有点陷入困境的情况。程序员使用goto语句来实现他的逻辑，因为Python中没有goto语句，因为我不想深入研究它的搞笑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);
...
他有一个名为“Jump”的标签，他去了。我们怎么能把这个Python化呢？因为我们已经处于for循环中，所以我有点想要引入更多循环。
提前致谢。
编辑：感谢贡献者，建议以下内容，但是这会陷入无限循环：
# 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语句和索引增加等同于continue指令（你几乎不需要在C / C ++程序中使用goto，而且绝对不是这里，原来的C ++代码是“模仿”continue，因为作者没有不知道它存在）：
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外读取：未定义的行为）
现在，您可以直接在python中转置它：您有两个选项：
你去索引（就像你的C ++代码那样）
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循环控制迭代。您只需告诉python使用continue跳转到下一次迭代，就像在“新”C ++代码中一样。
由于所有跳转似乎都以i ++开头，而jump是循环的开始，所以看起来Python continue语句很容易解决你的问题？
# 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)
...
我个人只是反转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我不能准确。请告诉我是否发生任何错误。