用于学习记录

---

前言

---

一、SlideLoss

YOLO-FaceV2: A Scale and Occlusion Aware Face Detector

1.1 utils/loss.py

插入以下代码：

import math
class SlideLoss(nn.Module):def __init__(self, loss_fcn):super(SlideLoss, self).__init__()self.loss_fcn = loss_fcnself.reduction = loss_fcn.reductionself.loss_fcn.reduction = 'none'  # required to apply SL to each elementdef forward(self, pred, true, auto_iou=0.5):loss = self.loss_fcn(pred, true)if auto_iou < 0.2:auto_iou = 0.2b1 = true <= auto_iou - 0.1a1 = 1.0b2 = (true > (auto_iou - 0.1)) & (true < auto_iou)a2 = math.exp(1.0 - auto_iou)b3 = true >= auto_ioua3 = torch.exp(-(true - 1.0))modulating_weight = a1 * b1 + a2 * b2 + a3 * b3loss *= modulating_weightif self.reduction == 'mean':return loss.mean()elif self.reduction == 'sum':return loss.sum()else:  # 'none'return loss

修改 class ComputeLoss

        # Focal lossg = h['fl_gamma']  # focal loss gammaif g > 0:BCEcls, BCEobj = FocalLoss(BCEcls, g), FocalLoss(BCEobj, g)    # 添加以下代码：Slide_Loss = h['SlideLoss']if Slide_Loss > 0:BCEcls, BCEobj = SlideLoss(BCEcls), SlideLoss(BCEobj)

1.2 data/hyps/hyp.scratch-low.yaml

添加以下内容：

SlideLoss: 0.5

二、注意力机制 MultiSEAM

2.1 models/common.py

class Residual(nn.Module):def __init__(self, fn):super(Residual, self).__init__()self.fn = fndef forwar