python/path_to_maskrcnn_benchmark/tools/train_net.py--config-file"/path/to/config/file.yaml" 开始训练之后过不了几个iter就会出现所有的Loss为nan的现象,这是由于学习率过大引起的,自己调小就可以了。另外默认的版本是用的是warm up lr,所以开始的几个epoch可能和你设定的不一样,没关系~另外,配置参数...
1. 在训练过程中如果出现loss为nan的情况,或者出现错误 - RuntimeError: copy_if failed to synchronize: cudaErrorAssert: device-side assert triggered,请修改配置文件(.yaml)中的学习率(我训练fpn50和fpn101时将其改为了0.002)我的数据集只有一类物体,供大家参考。 我在训练完成时还碰到一个错误 TypeError: ...
CUDA out of menmory :首先引起该问题的原因最可能是batch_size太大,需要去defaults.py中手动修改,但是如果调到1了还是报错,那就是前面说的defaults.py中的MIN_SIZE_TRAIN ;MAX_SIZE_TRAIN...设置得太大,调小即可 loss NAN的错误,一般可以通过调小上面.yaml中的BASE_LR解决 几乎所有问题都可以在源工程的issues...
今年年初,Facebook AI研究院(FAIR)开源了 Detectron,业内最佳水平的目标检测平台。据介绍,该项目自 2016 年 7 月启动,构建于 Caffe2 之上,目前支持大量机器学习算法,其中包括 Mask R-CNN(何恺明的研究,ICCV 2017 最佳论文)和 Focal Loss for Dense Object Detection,(ICCV 2017最佳学生论文)。 本文以Airbus Ship...
error: Loss = nan 报错原因:Loss发散 解决办法: GPU的arch设置的不对 打开./lib/setup.py文件,找到第130行,将gpu的arch设置成与自己电脑相匹配的算力,这里举个例子,如果你用的是GTX1080,那么你的算力就是6.1,此时就需要将-arch=sm_52改成-arch=sm_61。
["ymax"]) # 进一步检查数据,有的标注信息中可能有w或h为0的情况,这样的数据会导致计算回归loss为nan if xmax <= xmin or ymax <= ymin: print("Warning: in '{}' xml, there are some bbox w/h <=0".format(xml_path)) continue boxes.append([xmin, ymin, xmax, ymax]) labels.append(...
Loss is nan, stopping training when training Mask-RCNN multi-class segmentation And this is the dataset code: classmaskrcnn_Dataset(torch.utils.data.Dataset):def__init__(self, root, transforms=None): self.root = root self.transforms = transforms# load all image files, sorti...
During training, the loss values are pretty unpredictable, bouncing between around 1 and 2 without ever reaching a steady decline where it seems like it's converging at all. I'm using these config values at the moment; they're the best I've been able to come up with while f...
9/500 [...] - ETA: 43:03 - loss: nan - rpn_class_loss: 0.4798 - rpn_bbox_loss: 0.5489 - mrcnn_class_loss: 1.1758 - mrcnn_bbox_loss: 0.4309 - mrcnn_mask_loss: 0.2511 As descreibe below, the total loss=nan, however the other 5 loss is not. I can't figure out why. ...
TrainingMaskLoss— Training cross-entropy loss for the mask segmentation branch at the end of each iteration. LearnRate— Learning rate at each iteration. ValidationLoss— Validation loss at each iteration. ValidationRPNLoss— Validation RPN loss at each iteration. ...