def rotate_nms_cc(dets, thresh):
scores = dets[:, 5]
order = scores.argsort()[::-1].astype(np.int32) # highest->lowest
dets_corners = box_np_ops.center_to_corner_box2d(
dets[:, :2], dets[:, 2:4], dets[:, 4]
)
dets_standup = box_np_ops.corner_to_standup_nd(dets_corners)
standup_iou = box_np_ops.iou_jit(dets_standup, dets_standup, eps=0.0)
# print(dets_corners.shape, order.shape, standup_iou.shape)
return rotate_non_max_suppression_cpu(dets_corners, order, standup_iou, thresh)
def _compare(self, boxes1, boxes2):
"""Compute matrix of (negated) sq distances.
Args:
boxlist1: BoxList holding N boxes.
boxlist2: BoxList holding M boxes.
Returns:
A tensor with shape [N, M] representing negated pairwise squared distance.
"""
boxes1_bv = box_np_ops.rbbox2d_to_near_bbox(boxes1)
boxes2_bv = box_np_ops.rbbox2d_to_near_bbox(boxes2)
ret = box_np_ops.iou_jit(boxes1_bv, boxes2_bv, eps=0.0)
return ret
def rotate_weighted_nms_cc(box,
dets,
thresh,
iou_preds,
labels,
dirs,
anchors=None,
nms_cnt_thresh=2.6,
nms_sigma_dist_interval=(0, 20, 40, 60),
nms_sigma_square=(0.0009, 0.009, 0.1, 1),
suppressed_thresh=0.3,
):
scores = dets[:, 5]
dets_corners = box_np_ops.center_to_corner_box2d(
dets[:, :2], dets[:, 2:4], dets[:, 4]
)
dets_standup = box_np_ops.corner_to_standup_nd(dets_corners)
standup_iou = box_np_ops.iou_jit(dets_standup, dets_standup, eps=0.0)
if anchors is None:
centerness_c = 0
anchors = np.zeros((1,1))
else:
centerness_c = 1
result = IOU_weighted_rotate_non_max_suppression_cpu(box,
dets_corners,
standup_iou,
thresh,
scores,
iou_preds,
labels,
dirs,
anchors,
nms_cnt_thresh,
nms_sigma_dist_interval,
nms_sigma_square,
suppressed_thresh,
centerness_c)
return result
def rotate_weighted_nms_cc(
box,
dets,
thresh,
iou_preds,
labels,
dirs,
anchors=None,
):
scores = dets[:, 5]
order = scores.argsort()[::-1].astype(np.int32) # highest->lowest
dets_corners = box_np_ops.center_to_corner_box2d(dets[:, :2], dets[:, 2:4],
dets[:, 4])
dets_standup = box_np_ops.corner_to_standup_nd(dets_corners)
standup_iou = box_np_ops.iou_jit(dets_standup, dets_standup, eps=0.0)
result = IOU_weighted_rotate_non_max_suppression_cpu(
box, dets_corners, standup_iou, thresh, scores, iou_preds, labels,
dirs, anchors)
return result