Deep learning 如何更改语义分段的填充?
我正在尝试对我的数据运行UNet,这是256x256分辨率的灰度图像。UNet正在将图像下采样为1×5×84×84(5是类别数)。我得到了以下错误:Deep learning 如何更改语义分段的填充?,deep-learning,caffe,pycaffe,matcaffe,caffe2,Deep Learning,Caffe,Pycaffe,Matcaffe,Caffe2,我正在尝试对我的数据运行UNet,这是256x256分辨率的灰度图像。UNet正在将图像下采样为1×5×84×84(5是类别数)。我得到了以下错误: 0501 02:16:17.345309 2433 net.cpp:400] loss -> loss I0501 02:16:17.345317 2433 layer_factory.hpp:77] Creating layer loss F0501 02:16:17.345377 2433 softmax_loss_layer.cp
0501 02:16:17.345309 2433 net.cpp:400] loss -> loss
I0501 02:16:17.345317 2433 layer_factory.hpp:77] Creating layer loss
F0501 02:16:17.345377 2433 softmax_loss_layer.cpp:47] Check failed: outer_num_ * inner_num_ == bottom[1]->count() (7056 vs. 65536) Number of labels must match number of predictions; e.g., if softmax axis == 1 and prediction shape is (N, C, H, W), label count (number of labels) must be N*H*W, with integer values in {0, 1, ..., C-1}.
*** Check failure stack trace: ***
@ 0x7f7d2c9575cd google::LogMessage::Fail()
@ 0x7f7d2c959433 google::LogMessage::SendToLog()
@ 0x7f7d2c95715b google::LogMessage::Flush()
@ 0x7f7d2c959e1e google::LogMessageFatal::~LogMessageFatal()
@ 0x7f7d2d02d4be caffe::SoftmaxWithLossLayer<>::Reshape()
@ 0x7f7d2d0c61df caffe::Net<>::Init()
@ 0x7f7d2d0c7a91 caffe::Net<>::Net()
@ 0x7f7d2d0e1a4a caffe::Solver<>::InitTrainNet()
@ 0x7f7d2d0e2db7 caffe::Solver<>::Init()
@ 0x7f7d2d0e315a caffe::Solver<>::Solver()
@ 0x7f7d2cf7b9f3 caffe::Creator_SGDSolver<>()
@ 0x40a6d8 train()
@ 0x4075a8 main
@ 0x7f7d2b40b830 __libc_start_main
@ 0x407d19 _start
@ (nil) (unknown)
0501 02:16:17.345309 2433 net.cpp:400]损失->损失
I0501 02:16:17.345317 2433 layer_factory.hpp:77]正在创建层丢失
F0501 02:16:17.345377 2433 softmax_loss_layer.cpp:47]检查失败:外部_num_*内部_num_==底部[1]->计数()(7056 vs.65536)标签数量必须与预测数量匹配;e、 例如,如果softmax轴==1且预测形状为(N,C,H,W),则标签计数(标签数量)必须为N*H*W,整数值在{0,1,…,C-1}中。
***检查故障堆栈跟踪:***
@0x7f7d2c9575cd谷歌::日志消息::失败()
@0x7f7d2c959433 google::LogMessage::SendToLog()
@0x7f7d2c95715b谷歌::日志消息::刷新()
@0x7f7d2c959e1e谷歌::LogMessageFatal::~LogMessageFatal()
@0x7f7d2d02d4be caffe::SoftmaxWithLossLayer::重塑()
@0x7f7d2d0c61df caffe::Net::Init()
@0x7f7d2d0c7a91 caffe::Net::Net()
@0x7f7d2d0e1a4a caffe::解算器::InitTrainNet()
@0x7f7d2d0e2db7 caffe::解算器::初始化()
@0x7f7d2d0e315a caffe::解算器::解算器()
@0x7f7d2cf7b9f3 caffe::创建者_SGDSolver()
@0x40a6d8列车()
@0x4075a8干管
@0x7f7d2b40b830自由启动主
@0x407d19_开始
@(无)(未知)
有人能告诉我如何设置填充值以获得输出预测中的输入大小吗?我不知道该如何更改,以及更改哪些层 谷歌搜索“接受域算术”@Shai非常感谢