caffe install

　　0: Today is 20171114, this tutorial does not know when to be effective1: We installed the GPU version, so to install Cuda, this four platform compatible version is, cuda8+cudnn6. To the official website is the new version of CUDA8. Baidu Cloud: HTTP://PAN.BAIDU.COM/S/1PKKXS51,M2JL2: Because Caffe out of Anaconda installation because of the lack of some dependency error patterns, we use the anaconda to con

Ubuntu14.04+caffe+cuda Environment Building and training and testing of mnist data setsFirst, the installation of ubuntu14.04:　　Ubuntu installation is a very simple thing, here is a reference tutorial:Http://jingyan.baidu.com/article/76a7e409bea83efc3b6e1507.htmlSecond, the installation of Cuda:1, first download NVIDIA CUDA warehouse installation package (my is Ubuntu 14.04 64 bit, so download is ubuntu14.04 installation package, if you are 32 bit can

it is in line 74th of the configuration file boost_python3.lib .The solution is as follows:Check if you have the following files:ls /usr/lib/x86_64-linux-gnu/libboost_python-py34.soIf so, it means that the library file is already in our system, except the file name is different.cd /usr/lib/x86_64-linux-gnu/sudo ln -s libboost_python-py34.so libboost_python3.soRecompile to pass.TestAfter entering the Python interpreter environment, use the following command to test whether the installation was s

The full name of Caffe should be convolutional Architecture for Fast Feature embedding, which is a clear and efficient deep learning framework, which is open source, the core language is C + +, It supports command line, Python, and MATLAB interfaces, which can be run on the CPU or on the GPU. Its license is the BSD 2-clause.One reason why deep learning is popular is that it is able to learn from data autonomously to useful feature. Especially for

relatively simple, enter the Openblas download directoryMake make install target directory for prefix=2. Boost installationTo download the corresponding boost installation package, this article uses the Boost installation package version boost_1_59_0.tar.bz2, unzip it:Tar--bzip2-xf To access the Boost decompression directory, you can view the installation help by following these commands:./bootstrap.sh--helpinstallation command:./bootstrap.sh--prefi

Deploying Caffe under Windows 10 takes a lot of time to tune in, recording the key node for subsequent queries:First, install the software:1. Install Microsoft Virtual Studio 2013/matlab 2015a/cuda 7.5:Note that VS2013 needs to be installed first to facilitate Matlab to identify vs path, CUDA binding content; VS2013 first installation is required;Among them, VS20

with the unique display.After installation Be sure to test the driver and Cuda has not been installed successfully, there are many online tutorials, nvidia-smi command test drive, there is a test cuda do not remember.3. Install CUDNN, reference: http://blog.csdn.net/baidu_32173921/article/details/53510764http://blog.csdn.net/ai_smith/article/details/53000973http://blog.csdn.net/samylee/article/details/509226014. Now is the beginning to configure the

Tags: ipy pyc--pil using Python for NIS CTO dataCaffee installation Process1. Installing dependent Packages$ sudo apt-get install libprotobuf-dev libleveldb-dev libsnappy-dev libopencv-dev libhdf5-serial-dev protobuf-compiler$ sudo apt-get install --no-install-recommends libboost-all-dev$ sudo apt-get install libopenbl

Recommendation system and hardware combination: Ubuntu14.04+cuda 7.5 1, installation Cuda Install Caffe:git clone Https://github.com/BVLC/caffe Install the Caffe Dependency pack: http://caffe.berkeleyvision.org/ ->installation Instructions ->ubuntu Installation ->sudo apt-get Insta