One loss Anchor selection for Class tgt

[jaideep11061982]

hi
below is the code for loss
in this one while building classification
clas_mask = matches>=0

Class mask will have 1 for even the bg position of anchors .
As before this we add 1 to matches tensor which has -1,-1,-1 for background, 0 for class and -2 for ignore.
that way we are taking in from Pred tensor even those anchors that are predicting the background.
Similar is the case fo bbox tensor.
Can you please let me know the rational behind taking into the account bg detecting tensor.

def _one_loss(self, clas_pred, bbox_pred, clas_tgt, bbox_tgt):
        
        bbox_tgt, clas_tgt = self._unpad(bbox_tgt, clas_tgt)
    
        matches = match_anchors(self.anchors, bbox_tgt)
    
        bbox_mask = matches>=0
        if bbox_mask.sum() != 0:
            
            bbox_pred = bbox_pred[bbox_mask]
     
            bbox_tgt = bbox_tgt[matches[bbox_mask]]
       
            bb_loss = self.reg_loss(bbox_pred, bbox_to_activ(bbox_tgt, self.anchors[bbox_mask]))
            
        else: 
            bb_loss = 0.
     
        
        matches.add_(1)
        clas_tgt = clas_tgt + 1
     
        
       
        clas_mask = matches>=0
  
        clas_pred = clas_pred[clas_mask]
    
        clas_tgt = torch.cat([clas_tgt.new_zeros(1).long(), clas_tgt]) #make one hong vector [0,1]
     
        clas_tgt = clas_tgt[matches[clas_mask]]
     
        return bb_loss , self._focal_loss(clas_pred, clas_tgt)/torch.clamp(bbox_mask.sum(), min=1.)