caffe install

including 3.0 protobuf,glog,gflags IO libraries,, hdf5 leveldb snappy ,lmdb Pycaffe and Matcaffe interfaces have their own natural needs. For Python Caffe: Python 2.7 or Python 3.3+ , numpy (>= 1.7) boost-providedboost.python For MATLAB Caffe:matlab with the mex compiler. 1. Install various dependency packagesYum install-y gcc gcc-

Compiling the environmentVMWare Workstation PlayerUbuntu-15.10-desktop-amd64CPU 4700MQ, allocating 6 cores +4GB memory +80GB HDD to VMCompile stepThe main reference is Caffe official websiteHttp://caffe.berkeleyvision.org/install_apt.html1. Install the Basic Package sudo apt-get install Libprotobuf-dev libleveldb-dev libsnappy-dev libopencv-dev libhdf5-s

Transfer from website:http://blog.csdn.net/muyiyushan/article/details/705780771. Preparing the DataUsing the Dog/cat dataset, separate the train and Val folders under the training project root as the location where the training data and validation data are saved. Each of the train and Val folders has two folders: Dogs and cats, respectively, to save pictures of dog and cat. Dog and cat have 1000 training images and 400 test images respectively.Write a Python script file, Traverse train and Val t

Tags: markdown keyword root directory attribute read Process ALS sub folderConvert your own image data to Caffe required db (Leveldb/lmdb) fileAfter setting up the Caffe environment, we often need to train/test our image data, our image data often when the picture file, such as Jpg,jpeg,png, but in Caffe we need to use the type of data is Lmdb or LEVELDB, For exa

Math:yes4.3. Make compileMake-j8 for a long time, nearly 3 hours, but fortunately this compilation has no problem.sudo make install after compilingSudo/bin/bash-c ' echo '/usr/local/lib ' >/etc/ld.so.conf.d/opencv.conf ' change environment variablessudo ldconfig environment variable in effectReboot the system and restart the system after the CD to the build folder:sudo apt-get install Checkinstallsudo chec

This training main reference: http://blog.csdn.net/jesse_mx/article/details/65634482Thank jesse_mx, helped me a lot.Pit One "OpenCV not installed successfully":OpenCV not installed success will lead to a variety of inexplicable problems, such as: "No module named Cv2" problem.However, the correct solution to the OPENCV installation problem is not a smooth way. Here are the OpenCV installation methods, which have been summarized by several failures individually:Main references:Install and test Op

After the MATLAB path in the Makefile.config file is changed to the path of its own installation, using the command make Matcaffe always unsuccessful, rage sudo make cleam, the result of the cleanup solution succeeded. Details are as follows: My GCC version is 4.8.7,matlab version 2013b, just started with Matcaffe times wrong GCC version is too high, must use 4.4.x version, helpless, the Internet to find solutions: $sudo apt-get Install gcc-4.4 $sudo

Reprint please specify the source:Http://www.cnblogs.com/darkknightzh/p/5797526.htmlReference URL:Http://caffe.berkeleyvision.org/installation.html#prerequisites1. Required dependencies: Boost >= 1.55,cuda,blasCheck out which directory your cuda is installed in. Makefile.config default Cuda_dir: =/usr/local/cudaDependent libraries: Protobuf, Glog, GFlags, Hdf5. Installation:sudo install libgflags-devsudoinstall libgoogle-glog-devsudo

These problems are typically caused by graphics drivers or some incompatibilities with cuda versions. Workaround: 1. First switch to the terminal (Ctrl + Alt + f1~f6 corresponding tty1~tty6) login interface, enter user name and password login; 2.

Caffe ConfigurationStep 1: Download: Cuda_8.0.44_windows.exe (https://developer.nvidia.com/cuda-toolkit-archive), Cudnn-8.0-windows7-x64-v5.0-ga.zip, Microsoft's Caffe (Https://github.com/Microsoft/caffe). According to the Computer Configuration and personal preferences to download the corresponding version, I GTX660 graphics, download Cuda 8.0 version and CUDNN

1.Cuda InstallationCuda is a GPU-accelerated computing platform from NVIDIAI installed here is cuda7.5, has been installed ignored, has not been installed here is the installation tutorial. It's very simple to install under Windows.Click on the Open link (my video card is 1080 now supports cuda8.0 so I'm under 8.0)2. download CUDNN (actually a compressed package) Note Now that 8.0 is out, I am under CUDNN V5 (May), the for CUDA 8.0 RCHttps://developer

These two days to help the doctor's office to install Caffe, it is said that this thing is a Chinese student in Berkeley, California, developed to train the neural network, Super Good, the world is used, but also open source for free. That is not very good outfit, said generally have to install more than three days, in fact, I probably also spent so much time, bu

Caffe An example of an issue that does not find the header file:/usr/local/include/caffe/blob.hpp:9:34:fatal error:caffe/proto/caffe.pb.h:no such file or directory#include "Caffe/proto/caffe.pb.h"Caffe cannot find the problem instance for the library file (the keyword has no member):Error: ' Class

. SHThe script automatically installs the dependencies, downloads the installation package, compiles and installs the OPENCV. The whole process is about half an hour.Note that there may be an error in the middleopencv-2.4. 9/MODULES/GPU/SRC/NVIDIA/CORE/NCVPIXELOPERATIONS.HPP (In anexplicit specialization Workaround in this: http://code.opencv.org/issues/3814 download ncvpixeloperations.hpp replace the files within the opencv2.4.9, and build again.6. Installing Additional DependenciesUbuntu14.0

1. Install the dependent environment first,% sudo apt-get install libprotobuf-dev libleveldb-dev libsnappy-dev libopencv-dev libhdf5-serial-dev libgflags-dev libgoogle-glog-dev liblmdb-dev protobuf-compiler libatlas-base-dev% sudo apt-get install --no-install-recommends libboost-all-dev% sudo apt-get

Original link: http://blog.csdn.net/yhl_leo/article/details/51371936 The second case of this blog post was encountered while compiling Caffe, which can be correctly executed when corrected: (Note that you can use make all-j16 depending on your computer) Sort out some of the compilation errors and workarounds that have recently been encountered with the Caffe project. 1 CuDNN CUDNN the latest version is V5

In Caffe, there are currently two ways to visualize the Prototxt format network structure : using Netscope online visualization to use the draw_net.py provided by Caffe In this paper, we will introduce the two methods of 1. Netscope: An online visualization tool for neural network architecture supporting Caffe Netscope is an online visual tool that supports the n

1. Preparatory work 1). Download the pre-trained model Http://cs.unc.edu/~wliu/projects/ParseNet/VGG_ILSVRC_16_layers_fc_reduced.caffemodel Put this file in the/home/software/caffe/models/vggnet/directory, if so, it is best to back up. 2). Download the VOC2007 data set wget Http://host.robots.ox.ac.uk/pascal/VOC/voc2012/VOCtrainval_11-May-2012.tar wget/http Host.robots.ox.ac.uk/pascal/voc/voc2007/voctrainval_06-nov-2007.tar wget http://host.robot

excellent deep learning open-source framework code learning, is also a good point of neural network learning. Here to organize and share is the use of a very wide range of deep learning framework Caffe, this is a set of the earliest originated in Berkeley deep Learning framework, widely used in the task of neural networks, a large number of paper experiments are done with it, And the domestic e-commerce and other Internet companies a large number of

This series of articles by the @yhl_leo produced, reproduced please indicate the source. Article Link: http://blog.csdn.net/yhl_leo/article/details/50961542 Spent a day, installed on the computer configuration of the Caffe deep learning framework, many of the online tutorials and guidance have expired, the middle of the time spent a bit, here the personal thought the simplest way to organize the following.version 1 Notebook: Think