(self, boxlists)
return target_lvls.to(torch.int64) - self.k_min
Arguments:
            boxlists (list[BoxList])
Arguments:
            boxlists (list[BoxList])
Arguments : boxlists ( list [ BoxList ] )
def __call__(self, boxlists):
        """
        Arguments:
            boxlists (list[BoxList])
        """
        # Compute level ids
        s = torch.sqrt(cat([boxlist.area() for boxlist in boxlists]))

        # Eqn.(1) in FPN paper
        target_lvls = torch.floor(self.lvl0 + torch.log2(s / self.s0 + self.eps))
        target_lvls = torch.clamp(target_lvls, min=self.k_min, max=self.k_max)
        return target_lvls.to(torch.int64) - self.k_min
def __call__ ( self , boxlists ) : # Compute level ids s = torch . sqrt ( cat ( [ boxlist . area ( ) for boxlist in boxlists ] ) ) # Eqn.(1) in FPN paper target_lvls = torch . floor ( self . lvl0 + torch . log2 ( s / self . s0 + self . eps ) ) target_lvls = torch . clamp ( target_lvls , min = self . k_min , max = self . k_max ) return target_lvls . to ( torch . int64 ) - self . k_min