Usually, Mask-R-CNN outputs many bounding boxes to an image.
In your paper, the model use only ten bounding boxes for an image.
How did you choose ten bounding boxes? (confidence, the size of bbox, ...)
maskrcnn_bboxes
List of detected bounding boxes corresponding to the image. (x1,y1) refers to start vertex of the rectangle and (x2, y2) refers to end vertex of the rectangle
Usually, Mask-R-CNN outputs many bounding boxes to an image. In your paper, the model use only ten bounding boxes for an image. How did you choose ten bounding boxes? (confidence, the size of bbox, ...)
Thanks