self.loss_fcn = nn.BCEWithLogitsLoss(reduction='none') # must be nn.BCEWithLogitsLoss() self.alpha = alpha def forward(self, pred, true): loss = self.loss_fcn(pred, true) pred = flow.sigmoid(pred) # prob from logits # dx = [-1, 1] 当pred=1 true=0时(网络预测说这里有个obj...
一、make_roi_box_loss_evaluator()函数 box_head的计算loss相关操作在your_project/maskrcnn_benchmark/modeling/roi_heads/box_head/loss.py文件中,我们首先来看看make_roi_box_loss_evaluator()这个函数: defmake_roi_box_loss_evaluator(cfg):# 匹配器 用于给RPN输出给ROI_head部分的Proposals分配真实的标签m...
是因为计算距离和长度的时候需要开根号,这里加平方其实是减少开根号的运算步骤。 DIOU Loss具有以下特性: DIOU与IOU、GIOU一样具有尺度不变性; DIOU与GIOU一样在与目标框不重叠时,仍然可以为边界框提供移动方向; DIOU可以直接最小化两个目标框的距离,因此比GIOU Loss收敛快得多; DIOU在包含两个框水平/垂直方向...
定位损失box_loss:预测框与标定框之间的误差(GIoU),越小定位得越准; 分类损失cls_loss:计算锚框与对应的标定分类是否正确,越小分类得越准; 动态特征损失(dfl_loss):DFLLoss是一种用于回归预测框与目标框之间距离的损失函数。在计算损失时,目标框需要缩放到特征图尺度,即除以相应的stride,并与预测的边界框计算Cio...
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那么 x,y 的取值就是两个中心的偏移量和 cell 本身宽高的比值。...首先 Loss 要计算: 中心点的 Loss 宽高的 Loss 置信度的 Loss 目标类别的 Loss 前面讲到一张图片产生 49 个 cell,有些 cell 没有什么意义,因为它们不包含任何的 Object...这行 Loss 就是所有的存在目标的 cell 中所预测的 bbox ...
Fig. 2: A comparison between two single shot detection models: SSD and YOLO [5].Our SSD model adds several feature layers to the end of a base network, which predict the offsets to default boxes of different scales and aspect ratios and their associated confidences. SSD with a 300 × 30...
信度损失函数:针对分类,使用Cross Entropy Loss 5.PNG 针对offset的编码: 从上面不同特征图上的锚框图片中可以看出锚框的offset标识为 ,然而在计算LOSS的时候使用了如下转换: = , = , , (1) 其中(cx,cy,w,h)是ground truth的真实位置信息, 是锚框的真实位置信息 ...
状声在能料年状声在能料年RPN 中 reg loss,即 rpn_loss_bbox 层计算的 SOftmaX loss,用于 bounding box regressi
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