1、训练的时候出现box_loss、cls_loss、dfl_loss都为nan的情况,需要将训练的时候的参数进行修改,设置amp=False 2、修改之后训练的时候出现P、R、map值为NAN或者非常小,一般来说基于预训练模型来进行训练P、R、map的值都不会很低,如果出现0.0x这种一般是有点问题,这种情况可以尝试以下操作,需要到ultralytics/cfg...
这个问题就消失了。在ultralytics 8.0.26的环境中一切正常，然后我在8.0.30左右的环境中发现了NaN...
loss[1] += (proto * 0).sum() + (pred_masks * 0).sum() # inf sums may lead to nan loss loss[0] *= self.hyp.box # box gain loss[1] *= self.hyp.box # seg gain loss[2] *= self.hyp.cls # cls gain loss[3] *= self.hyp.dfl # dfl gain return loss.sum() * batch_...
It seems like you're attempting to replace the Binary Cross Entropy with Logits (BCEWithLogitsLoss) with Focal Loss. Based on the information you provided, your implementation appears to be correct. Regarding the classification loss value you're seeing (5.555e-05): This is not necessarily an ...
(left_loss + right_loss).mean(-1, keepdim=True)# 定义了一个用于计算边界框损失的模块classBboxLoss(nn.Module):"""Criterion class for computing training losses during training."""def__init__(self, reg_max=16):"""Initialize the BboxLoss module with regularization maximum and DFL settings....
Search before asking I have searched the YOLOv8 issues and discussions and found no similar questions. Question all loss is NAN and P/R/map is 0 when the user-defined data set GPU is trained! CUDA Change from 11.7 to 11.6 still can't tra...
Note: If during training you seenanvalues for avg (loss) field - then training goes wrong, but if nan is in some other lines - then training goes well. 6.程序中断之后继续训练 ./darknet detector train cfg/voc.data cfg/yolov3-voc.cfg backup/yolov3-voc.backup ...
表示左上角和右下角坐标 # `xywh` 表示中心点坐标和宽度、高度(YOLO格式) # `ltwh` 表示左上角坐标和宽度、高度(COCO格式) _formats = ["xyxy", "xywh", "ltwh"] # 导出的类名列表 __all__ = ("Bboxes",) # tuple or list # 定义边界框类 Bboxes class Bboxes: """ A class for ...
Search before asking I have searched the YOLOv8 issues and found no similar bug report. YOLOv8 Component Training Bug While Training the model in v8 with GPU all the losses becomes nan and all the evaluation metrics becomes zero. Under A...
bbox_format="xywh",# 边界框格式设置为(x, y, width, height)normalize=True,# 归一化图像像素值return_mask=self.use_segments,# 根据use_segments参数返回掩膜return_keypoint=self.use_keypoints,# 根据use_keypoints参数返回关键点batch_idx=True,# 返回带有批次索引的数据mask_ratio=hyp.mask_ratio,# 掩...