About bboxes_filter_overlap about seglink HOT 3 CLOSED

with tf.name_scope(scope, 'bboxes_filter', [labels, bboxes]):
    scores = bboxes_intersection(tf.constant([0, 0, 1, 1], bboxes.dtype),bboxes)
                
    mask = scores > threshold
    if assign_negative:
        labels = tf.where(mask, labels, -labels)
    else:
        labels = tf.boolean_mask(labels, mask)
        bboxes = tf.boolean_mask(bboxes, mask)
        scores = bboxes_intersection(tf.constant([0, 0, 1, 1], bboxes.dtype),bboxes)
        xs = tf.boolean_mask(xs, mask);
        ys = tf.boolean_mask(ys, mask);
    return labels, bboxes, xs, ys

with tf.name_scope(name, 'bboxes_intersection'):
    # Should be more efficient to first transpose.
    bboxes = tf.transpose(bboxes)
    bbox_ref = tf.transpose(bbox_ref)
    # Intersection bbox and volume.
    int_ymin = tf.maximum(bboxes[0], bbox_ref[0])
    int_xmin = tf.maximum(bboxes[1], bbox_ref[1])
    int_ymax = tf.minimum(bboxes[2], bbox_ref[2])
    int_xmax = tf.minimum(bboxes[3], bbox_ref[3])
    h = tf.maximum(int_ymax - int_ymin, 0.)
    w = tf.maximum(int_xmax - int_xmin, 0.)
    # Volumes.
    inter_vol = h * w
    bboxes_vol = (bboxes[2] - bboxes[0]) * (bboxes[3] - bboxes[1])
    scores = tfe_math.safe_divide(inter_vol, bboxes_vol, 'intersection')
    return scores