官法代码中：
def get_ground_truth(self, anchors, batched_gt_boxes, batched_valid_gt_box_number):
total_anchors = anchors.shape[0]
labels_cat_list = []
bbox_targets_list = []
for b_id in range(self.batch_size):
gt_boxes = batched_gt_boxes[b_id, : batched_valid_gt_box_number[b_id]]
overlaps = layers.get_iou(anchors, gt_boxes[:, :4])
argmax_overlaps = F.argmax(overlaps, axis=1)
max_overlaps = overlaps.ai[
F.linspace(0, total_anchors - 1, total_anchors).astype(np.int32),
argmax_overlaps,
]
labels = mge.tensor([-1]).broadcast(total_anchors)
labels = labels * (max_overlaps >= self.cfg.negative_thresh)
labels = labels * (max_overlaps < self.cfg.positive_thresh) + (
max_overlaps >= self.cfg.positive_thresh
)
bbox_targets = self.box_coder.encode(
anchors, gt_boxes.ai[argmax_overlaps, :4]
)
labels_cat = gt_boxes.ai[argmax_overlaps, 4]
labels_cat = labels_cat * (1.0 - F.less_equal(F.abs(labels), 1e-5))
ignore_mask = F.less_equal(F.abs(labels + 1), 1e-5)
labels_cat = labels_cat * (1 - ignore_mask) - ignore_mask
# assign low_quality boxes
if self.cfg.allow_low_quality:
gt_argmax_overlaps = F.argmax(overlaps, axis=0)
labels_cat = labels_cat.set_ai(gt_boxes[:, 4])[gt_argmax_overlaps]
matched_low_bbox_targets = self.box_coder.encode(
anchors.ai[gt_argmax_overlaps, :], gt_boxes[:, :4]
)
bbox_targets = bbox_targets.set_ai(matched_low_bbox_targets)[
gt_argmax_overlaps, :
]
labels_cat_list.append(F.add_axis(labels_cat, 0))
bbox_targets_list.append(F.add_axis(bbox_targets, 0))
return (
F.zero_grad(F.concat(labels_cat_list, axis=0)),
F.zero_grad(F.concat(bbox_targets_list, axis=0)),
)
想请教以下这两句该怎么理解呢，感激不尽
labels = labels * (max_overlaps >= self.cfg.negative_thresh)
labels = labels * (max_overlaps < self.cfg.positive_thresh) + (
max_overlaps >= self.cfg.positive_thresh
)