def _proposal_target_layer(self, rois, roi_scores):
if cfg.SUB_CATEGORY:
if cfg.DO_PARSING:
rois, roi_scores, labels, sub_labels, bbox_targets, bbox_inside_weights, bbox_outside_weights, mask_unit = \
proposal_target_layer(
rois, roi_scores, self._gt_boxes, self._num_classes, self._parsing_labels)
else:
rois, roi_scores, labels, sub_labels, bbox_targets, bbox_inside_weights, bbox_outside_weights = \
proposal_target_layer(
rois, roi_scores, self._gt_boxes, self._num_classes)
else:
if cfg.DO_PARSING:
rois, roi_scores, labels, bbox_targets, bbox_inside_weights, bbox_outside_weights, mask_unit = \
proposal_target_layer(
rois, roi_scores, self._gt_boxes, self._num_classes, self._parsing_labels)
else:
rois, roi_scores, labels, bbox_targets, bbox_inside_weights, bbox_outside_weights = \
proposal_target_layer(
rois, roi_scores, self._gt_boxes, self._num_classes)
if cfg.SUB_CATEGORY:
self._proposal_targets['sub_labels'] = sub_labels.long()
if cfg.DO_PARSING:
self._proposal_targets['mask_unit'] = mask_unit
self._proposal_targets['rois'] = rois
self._proposal_targets['labels'] = labels.long()
self._proposal_targets['bbox_targets'] = bbox_targets
self._proposal_targets['bbox_inside_weights'] = bbox_inside_weights
self._proposal_targets['bbox_outside_weights'] = bbox_outside_weights
for k in self._proposal_targets.keys():
self._score_summaries[k] = self._proposal_targets[k]
return rois, roi_scores
def _proposal_target_layer(self, rois, roi_scores):
rois, roi_scores, labels, bbox_targets, bbox_inside_weights, bbox_outside_weights = \
proposal_target_layer(rois, roi_scores, self._gt_boxes, self._num_classes)
self._proposal_targets['rois'] = rois
self._proposal_targets['labels'] = labels.long()
self._proposal_targets['bbox_targets'] = bbox_targets
self._proposal_targets['bbox_inside_weights'] = bbox_inside_weights
self._proposal_targets['bbox_outside_weights'] = bbox_outside_weights
for k in self._proposal_targets.keys():
self._score_summaries[k] = self._proposal_targets[k]
return rois, roi_scores
def _proposal_target_layer(self, rois, roi_scores):
rois, roi_scores, labels, bbox_targets, bbox_inside_weights, bbox_outside_weights = \
proposal_target_layer(
rois, roi_scores, self._gt_boxes, self._num_classes)
self._proposal_targets['rois'] = rois
self._proposal_targets['labels'] = labels.long()
self._proposal_targets['bbox_targets'] = bbox_targets
self._proposal_targets['bbox_inside_weights'] = bbox_inside_weights
self._proposal_targets['bbox_outside_weights'] = bbox_outside_weights
for k in self._proposal_targets.keys():
self._score_summaries[k] = self._proposal_targets[k]
return rois, roi_scores
def _proposal_target_layer(self, rois, roi_scores):
rois, roi_scores, labels, bbox_targets, bbox_inside_weights, bbox_outside_weights = \
proposal_target_layer(
rois, roi_scores, self._gt_boxes, self._num_classes)
self._proposal_targets['rois'] = Variable(
torch.from_numpy(rois).float().cuda())
self._proposal_targets['labels'] = Variable(
torch.from_numpy(labels).long().cuda())
self._proposal_targets['bbox_targets'] = Variable(
torch.from_numpy(bbox_targets).float().cuda())
self._proposal_targets['bbox_inside_weights'] = Variable(
torch.from_numpy(bbox_inside_weights).float().cuda())
self._proposal_targets['bbox_outside_weights'] = Variable(
torch.from_numpy(bbox_outside_weights).float().cuda())
for k in self._proposal_targets.keys():
self._score_summaries[k]['value'] = self._proposal_targets[k]
return rois, roi_scores
def _proposal_target_layer(self, rois, roi_scores):
rois, roi_scores, labels, bbox_targets, bbox_inside_weights, bbox_outside_weights = \
proposal_target_layer(
rois, roi_scores, self._gt_boxes, self._num_classes)
self.visualize_rois(rois.data.cpu().numpy()[:, 1:],
roi_scores.data.cpu().numpy(),
self._gt_boxes.data.cpu().numpy(), self.is_flipped,
self.img_name, self._im_info[1], self._im_info[2])
self._proposal_targets['rois'] = rois
self._proposal_targets['labels'] = labels.long()
self._proposal_targets['bbox_targets'] = bbox_targets
self._proposal_targets['bbox_inside_weights'] = bbox_inside_weights
self._proposal_targets['bbox_outside_weights'] = bbox_outside_weights
for k in self._proposal_targets.keys():
self._score_summaries[k] = self._proposal_targets[k]
return rois, roi_scores
def _proposal_target_layer(self, rois, roi_scores):
rois, roi_scores, labels, bbox_targets, bbox_inside_weights, bbox_outside_weights, depth_targets, rotation_targets, depth_inside_weights, depth_outside_weights = \
proposal_target_layer(rois, roi_scores, self._gt_boxes, self._num_classes) #fang fangpengfei add points_targets
self._proposal_targets['rois'] = rois
self._proposal_targets['labels'] = labels.long()
self._proposal_targets['bbox_targets'] = bbox_targets
self._proposal_targets['bbox_inside_weights'] = bbox_inside_weights
self._proposal_targets['bbox_outside_weights'] = bbox_outside_weights
self._proposal_targets['depth_targets'] = depth_targets
self._proposal_targets['rotation_targets'] = rotation_targets
self._proposal_targets['depth_inside_weights'] = depth_inside_weights
self._proposal_targets['depth_outside_weights'] = depth_outside_weights
for k in self._proposal_targets.keys():
self._score_summaries[k] = self._proposal_targets[k]
return rois, roi_scores
