我用的指令尝试了caffe安装,ubuntu安装命令sudo apt install caffe-cuda在错误的情况下根本无法工作。
Package caffe-cuda is not available, but is referred to by another package.
This may mean that the package is missing, has been obsoleted, or
is only available from another source
E: Package 'caffe-cuda' has no installation
当我试图在我的RHEL机器上编译caffe时,我有这样的错误:我确实遵循了这个链接的说明:,但它看起来不工作。有什么帮助吗?谢谢
$make all
CXX src/caffe/data_transformer.cpp
src/caffe/data_transformer.cpp:1:33: warning: opencv2/core/core.hpp: No such file or directory
src/caffe/data_transformer.cpp: In member function ‘void caffe::DataTransformer<Dtype>::T
我正在尝试在ubuntu17.10上安装
然而,当我执行make all时,我得到了以下错误:
./include/caffe/common.hpp(84): error: namespace "std" has no member "isnan"
./include/caffe/common.hpp(85): error: namespace "std" has no member "isinf"
2 errors detected in the compilation of "/tmp/tmpxft_0000492
我通过caffe使用自己的数据集训练网络,现在我想用C++编写一个分类代码。我的机器(linux)只与CPU一起工作!(我用GPU在虚拟机中训练网络)。
当我试图“包括”特定的Caffe头:#include <caffe/caffe.hpp>时,编译器会向我显示这个消息:fatal error: caffe/caffe.hpp: No such file or directory。
我试图将特定的caffe文件复制到/usr/lib/,但没有帮助。有什么建议吗?
我需要帮助在Ubuntu 14.04上建立Caffe (深度学习)。在运行命令sudo make all -j4之后,我得到如下报告:
In file included from /usr/local/include/google/protobuf/arena.h:48:0,
from .build_release/src/caffe/proto/caffe.pb.h:23,
from ./include/caffe/util/signal_handler.h:4,
from src/caff
Ubuntu 18.04 Python 2.7 我的问题是我无法在python中导入caffe模块,即使我已经安装了它。我认为这是一个路径/环境变量问题。 rivaldo4t@Rivaldo-OS3:~$ python
Python 2.7.15rc1 (default, Nov 12 2018, 14:31:15)
[GCC 7.3.0] on linux2
Type "help", "copyright", "credits" or "license" for more information.
>>>
我使用"conda install caffe“安装了caffe,但当我在终端中输入"import caffe”时,出现了以下错误:
Python 2.7.14 |Anaconda custom (64-bit)| (default, Oct 16 2017, 17:29:19)
[GCC 7.2.0] on linux2
Type "help", "copyright", "credits" or "license" for more information.
>>&
我正在尝试在Linux Ubuntu上运行。安装后,我在gpu中运行caffe,错误是
I0910 13:28:13.606891 10629 caffe.cpp:296] Use GPU with device ID 0
modprobe: ERROR: could not insert 'nvidia_352': No such device
F0910 13:28:13.728612 10629 common.cpp:142] Check failed: error == cudaSuccess (38 vs. 0) no CUDA-capable device is
我已经把cudnn和cuda安装在ubuntu里了,我
使所有的-j4
在caffe目录下,它通过得很好。但当我
做试验
它显示:
CXX src/caffe/test/test_im2col_layer.cpp
In file included from ./include/caffe/util/device_alternate.hpp:40:0,
from ./include/caffe/common.hpp:19,
from ./include/caffe/blob.hpp:8,
我正在尝试安装Caffe,但我遇到了这个令人沮丧的错误。当我运行make时,我得到以下结果:
CXX .build_release/src/caffe/proto/caffe.pb.cc
In file included from .build_release/src/caffe/proto/caffe.pb.cc:5:0:
.build_release/src/caffe/proto/caffe.pb.h:9:42: fatal error: google/protobuf/stubs/common.h: No such file or directory
compilation termi
嗨,我是linux的新手,我想让一个程序开始工作。
我按照以下指示行事:
Edit your ~/.bashrc file to set up the environment for the caffe U-Net software:
export PATH=$PATH:/home/unetuser/u-net/bin
export LD_LIBRARY_PATH=$LD_LIBRARY_PATH:/home/unetuser/u-net/lib
现在,所期望的bahviour是,当我运行caffe时,我得到了预期的输出,这确实和预期的一样工作。
然而,当我尝试:
ssh localhos
我正在为使卷积层和全连通层快速工作而进行一些优化。我需要预训练的Alex网模型的卷积核权重,以执行与实际图像的卷积。
我尝试通过编写一个简单的python代码来提取第一个卷积层的内核参数。
# Load the original network and extract the fully connected layers' parameters.
import caffe
import sys
f1=open('./testfile', 'w')
net = caffe.Net('models/bvlc_alexnet/deploy.p
我以非管理员身份开始在Linux上使用Caffe框架,Caffe是在我的帐户上安装的。我转到usr/local/caffe路径并开始运行./create_cifar10.sh.But的cifar10示例,我得到了这个错误:
./create_cifar10.sh: 12: ./create_cifar10.sh: ./build/examples/cifar10/convert_cifar_data.bin: not found
我已经检查了构建目录,那里有一个名为convert_cifar_data.bin的文件。我该怎么解决它呢?
我正在使用boost 1.66在Ubuntu17.04系统上安装caffe。我能够毫无问题地执行make all和make test:
me@icvr1:~/PackageDownloads/caffe$ make all
make: Nothing to be done for 'all'.
me@icvr1:~/PackageDownloads/caffe$ make test
make: Nothing to be done for 'test'.
然而,当我尝试make runtest时,我会得到以下错误:
me@icvr1:~/PackageDownl
我想在ubuntu上安装caffe,我已经安装了cudnn/cuda/anaconda/openCV。但是当我在caffe-master文件夹下make all -j4时,它显示
/usr/lib/x86_64-linux-gnu/libunwind.so.8: undefined reference to lzma_index_buffer_decode@XZ_5.0
/usr/lib/x86_64-linux-gnu/libunwind.so.8: undefined reference to lzma_index_size@XZ_5.0
/usr/lib/x86_64-linux-g