Pythonizing C++ block with goto statement

The C++ code needs rework: the goto statement and index increase is equivalent to a continue instruction (you almost never need goto in a C/C++ program, and definitely not here, the original C++ code which is "emulating" continue because the author didn't know that it existed):

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

Note that now you don't need to increase manually the index, as continue skips to the next iteration, calling the ++j of your loop.

(the other issue of the incrementation+goto is that if the special case happens at the end of the array, then you can read outside the bounds of the array: undefined behaviour)

Now, you can transpose that directly in python: you have 2 options:

Either you go with indices (like your C++ code does)

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

or just iterate on elements (more pythonic, because it doesn't use indices):

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

In both cases, the for loop controls the iteration. You just tell python to skip to the next iteration with continue, just like in the "new" C++ code.

Since all the jumps seem to be preceeded by j++ and jump is the start of the loop, it would seem that the Python continue statement would solve your problem quite easily?

# 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)
    ...

I would personally just invert the if statement and execute the bottom half of the code conditionally as follows:

# 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)
        ...

Sure. I'd suggest this.

# 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)

Since I don't know the rest of the code I can't be much accurate. Please, tell me if any error occurs.