当γ设置为2时,对于模型预测为正例的样本也就是p>0.5的样本来说,如果样本越容易区分那么(1-p)的部分就会越小,相当于乘了一个系数很小的值使得Loss被缩小,也就是说对于那些比较容易区分的样本Loss会被抑制,同理对于那些比较难区分的样本Loss会被放大,这就是Focal Loss的核心:通过一个合适的函数来度量简单样本...
数据层面主要通过欠采样和过采样的方式来人为调节正负样本比例,模型层面主要是通过加权Loss,包括基于类别Loss、Focal Loss和GHM Loss三种加权Loss函数;最后讲了下其他解决样本不均衡的策略,可以通过调节阈值修改正负样本比例和利用半监督或自监督学习解决样本不均衡问题。需要说明下上面解决样本不均衡问题的策略不仅仅适用于...
importnumpyasnpimporttorchimporttorch.nnasnnimporttorch.nn.functionalasF# 支持多分类和二分类classFocalLoss(nn.Module):""" This is a implementation of Focal Loss with smooth label cross entropy supported which is proposed in 'Focal Loss for Dense Object Detection. (https://arxiv.org/abs/1708.020...
inputs,targets):ifself.logits:BCE_loss=F.binary_cross_entropy_with_logits(inputs,targets,reduce=False)else:BCE_loss=F.binary_cross_entropy(inputs,targets,reduce=False)pt=torch
Pytorch实现focal_loss多类别和⼆分类⽰例我就废话不多说了，直接上代码吧！import numpy as np import torch import torch.nn as nn import torch.nn.functional as F # ⽀持多分类和⼆分类 class FocalLoss(nn.Module):"""This is a implementation of Focal Loss with smooth label cross entropy ...
class FocalLoss(nn.Module): """ This is a implementation of Focal Loss with smooth label cross entropy supported which is proposed in 'Focal Loss for Dense Object Detection. (https://arxiv.org/abs/1708.02002)' Focal_Loss= -1*alpha*(1-pt)^gamma*log(pt) ...
class MultiFocalLoss(nn.Module): """ This is a implementation of Focal Loss with smoot...
class MultiFocalLoss(nn.Module): """ This is a implementation of Focal Loss with smoot...
An implementation of focal loss in pytorch meant to be understandable and easily swappable with nn.functional.cross_entropy and nn.CrossEntropyLoss - qiangw21/pytorch_focal_loss
1. Focal Loss 1.2 Focal Loss 定义 1.3. Focal Loss 例示 1.4. Focal Loss 求导 2. SoftmaxFocalLoss 求导 Focal Loss 损失函数: 3. Pytorch 实现 FocalLoss-PyTorch 代码语言:javascript 复制 importtorchimporttorch.nnasnnimporttorch.nn.functionalasFclassFocalLoss(nn.Module):def__init__(self,alpha=0.2...