PyTorch训练模型中 box_loss、obj_loss、cls_loss为nan的原因及解决方法 1. 整体流程 在理解“为什么使用PyTorch训练模型的box_loss、obj_loss、cls_loss都为nan”之前,我们需要了解整个训练过程的流程。下面是PyTorch训练模型的一般流程: 准备数据:首先我们需要准备训练数据,包括输入数据和对应的标签。 定义模型:然后...
解释:obj_loss(对象损失)在目标检测任务中用于衡量模型预测的对象存在性与真实情况之间的误差。它通常与模型判断一个区域是否包含目标对象的能力相关。 意义:通过最小化obj_loss,模型能够更好地区分图像中的前景和背景,提高目标检测的准确性。 cls_loss在分类任务中的角色: 解释:cls_loss(分类损失)在分类任务中用...
As the image shows below, there are disorders on the Y-axis of val/box_loss, val/obj_loss and val/cls_loss. And matplotlib output the following warning: Using categorical units to plot a list of strings that are all parsable as floats or dates. If these strings should be plotted as ...
conf_alpha * (class_loss + (obj_loss * keep).sum()) def conf_objectness_loss(self, conf_data, conf_t, batch_size, loc_p, loc_t, priors): """ Instead of using softmax, use class[0] to be p(obj) * p(IoU) as in YOLO....
❔Question Hi author, if I want to modify the loss function of the bounding box, do I modify the "GIOU" in the utils.py file (as shown below) and replace all of them with "CIOU"? or "DIOU"? Thanks. Additional context From line 409 to line...