Python SimpleBlobDetector.detect() is very slow with big images and can crash

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Hi!

I program in Python 3.X and use the simple blob detector to retreive their key points. This works very good. However when it comes to big images - like really big e.g. 16384x16384 pixels - processing takes really long. Here is the code:

    ...
    if blur_sigma > 0:
      img_blurred = cv2.GaussianBlur(img, (-1, -1), blur_sigma)
    else:
      img_blurred = img
    img_hsv = cv2.cvtColor(img_blurred, cv2.COLOR_BGR2HSV)
    img_filtered = cv2.inRange(img_hsv, tuple(lower_bounds), tuple(upper_bounds))

    ksize = 2 * morph_size + 1
    morph_element = cv2.getStructuringElement(morph_element, (ksize, ksize))
    img_morphed = cv2.morphologyEx(img_filtered,
                                   morph_operator,
                                   morph_element,
                                   borderType=cv2.BORDER_REFLECT)

    blob_params = cv2.SimpleBlobDetector_Params()
    blob_params.filterByInertia = False
    blob_params.minConvexity = 0.0
    blob_detector = cv2.SimpleBlobDetector_create(blob_params)
    key_points = blob_detector.detect(img_morphed)
    ...

Additionally it happened several times that in the last line, during execution, an assertion is thrown which directed me there:

cv2.error: D:\Build\OpenCV\opencv-3.2.0\modules\core\src\matrix.cpp:433: error: (-215) u != 0 in function cv::Mat::create

In there, an allocation fails.

So my questions are: 1) Is this kind of image size and edge case where the detection simply can no longer work with reasonable time? 2) Is the error also related to the image size? 3)Is there a way to improve detection with additonal steps beforehand?

Thanks!