mmseg/models/decode_heads/enc_head.py
def losses(self, seg_logit, seg_label):
        """Compute segmentation and semantic encoding loss."""
        seg_logit, se_seg_logit = seg_logit
        loss = dict()
        loss.update(super(EncHead, self).losses(seg_logit, seg_label))
        se_loss = self.loss_se_decode(
            se_seg_logit,
            self._convert_to_onehot_labels(seg_label, self.num_classes))
        loss['loss_se'] = se_loss
        return loss
Compute segmentation and semantic encoding loss.
Compute segmentation and semantic encoding loss.
Compute segmentation and semantic encoding loss .
def losses(self, seg_logit, seg_label):
        seg_logit, se_seg_logit = seg_logit
        loss = dict()
        loss.update(super(EncHead, self).losses(seg_logit, seg_label))
        se_loss = self.loss_se_decode(
            se_seg_logit,
            self._convert_to_onehot_labels(seg_label, self.num_classes))
        loss['loss_se'] = se_loss
        return loss
def losses ( self , seg_logit , seg_label ) : seg_logit , se_seg_logit = seg_logit loss = dict ( ) loss . update ( super ( EncHead , self ) . losses ( seg_logit , seg_label ) ) se_loss = self . loss_se_decode ( se_seg_logit , self . _convert_to_onehot_labels ( seg_label , self . num_classes ) ) loss [ 'loss_se' ] = se_loss return loss
Compute segmentation and semantic encoding loss.
Compute segmentation and semantic encoding loss .
"""Compute segmentation and semantic encoding loss."""
self
seg_logit
seg_label