I do not understand the additions of +1 in box_overlaps.pyx . I looked at the AVOD code and there they do not add +1. Maybe in Faster RCNN it is used because they work with pixels.
My interpretation of the effect (not certain):
As a result the current code should return higher IOU values or in other words the negative/positive thresholds should be effectively a little lower than 45/60. (which may be beneficial anyways..)
Hello Jeasine,
I do not understand the additions of +1 in box_overlaps.pyx . I looked at the AVOD code and there they do not add +1. Maybe in Faster RCNN it is used because they work with pixels.
box_area = ( (query_boxes[k, 2] - query_boxes[k, 0] + 1) (query_boxes[k, 3] - query_boxes[k, 1] + 1) ) ih = ( min(boxes[n, 3], query_boxes[k, 3]) - max(boxes[n, 1], query_boxes[k, 1]) + 1 ) ua = float( (boxes[n, 2] - boxes[n, 0] + 1) (boxes[n, 3] - boxes[n, 1] + 1) + box_area - iw * ih )
My interpretation of the effect (not certain): As a result the current code should return higher IOU values or in other words the negative/positive thresholds should be effectively a little lower than 45/60. (which may be beneficial anyways..)