def forward(self, im_data, im_info, gt_boxes=None, gt_ishard=None, dontcare_areas=None):
features, rois = self.rpn(im_data, im_info, gt_boxes, gt_ishard, dontcare_areas)
if self.training:
roi_data = self.proposal_target_layer(rois, gt_boxes, gt_ishard, dontcare_areas, self.n_classes)
rois = roi_data[0]
# roi pool
pooled_features = self.roi_pool(features, rois)
x = pooled_features.view(pooled_features.size()[0], -1)
# x = self.fc6(x)
# x = F.dropout(x, training=self.training)
# x = self.fc7(x)
# x = F.dropout(x, training=self.training)
x = self.fcs(x)
cls_score = self.score_fc(x)
cls_prob = F.softmax(cls_score)
bbox_pred = self.bbox_fc(x)
if self.training:
self.cross_entropy, self.loss_box = self.build_loss(cls_score, bbox_pred, roi_data)
return cls_prob, bbox_pred, rois
评论列表
文章目录