caffe windows

This issue is my installation of the official Caffe,windows version of the problem, the specific error prompted as follows: E:\nugetpackages\boost.1.59.0.0\lib\native\include\boost/format/alt_sstream_impl.hpp:error C2220: Warning is treated as error-no build " Object File (... \.. \src\caffe\util\math_functions.cpp) Check on the Internet, this problem is still

Follow the online tutorials to configure the Caffe environmentMake All-j8Finally appearedNon-virtual thunk to caffe::baseprefetchingdatalayerinternalthreadentry ()Finally a variety of search, Google, unexpectedly in http://discuss.cocos2d-x.org/t/error-non-virtual-thunk-to-cocos2d-cclayer-cctouchbegan/9061 in aAn answer was found in the answer because of a time-related problem in multiple classes of inherit

How to add a new type of layer in CaffeReference: https://github.com/BVLC/caffe/issues/684 ADD a class declaration for your layer to the appropriate one of COMMON_LAYERS.HPP,DATA_LAYERS.HPP, LOSS_LAYERS.HPP, neuro N_LAYERS.HPP, or VISION_LAYERS.HPP. Include an inline implementation of type and the *blobs () methods to specify BLOB number requirements. Omit THE*_GPU declarations If you ' ll is implementing CPU code. Implement your layer in layers

Sample Code for caffe feature Visualization Many readers read the previous two articles Summarize the research process of using caffe to run image data. Summary of deep learning practical experience 2-accuracy improved again, reaching 0.8. Then, I want to know how to implement feature visualization. To put it simply, it is to let the neural network spread forward once, then extract the feature values of a

Not much to say, experienced a lot of inexplicable errors finally installed, directly put the installation script:#!/bin/bash# installation should be aware that some libraries may fail to install and install Caffe and PROTOBUF related errors may need to re-make the ProtobufInstallCD/home/zw/Softwares #需要事先下载对应版本的cudasudoDpkg-i cuda-repo-ubuntu1604-8-0-local-ga2_8.0.61-1_amd64.debsudoapt-Get updatesudoApt-getInstallCUDACD/home/zw/git_home/#我存放git项目的目录g

Python to do deep learning caffe design CombatEssay background: In a lot of times, many of the early friends will ask me: I am from other languages transferred to the development of the program, there are some basic information to learn from us, your frame feel too big, I hope to have a gradual tutorial or video to learn just fine. For learning difficulties do not know how to improve themselves can be added: 1225462853 to communicate to get help, acce

previous: Own distorted understanding Some time ago with the MATLAB feature, after all, I am small white, matlab is the easiest for me to program (although, Daniel's structure is very good, I can only waste time complexity, alas ~ ~ ~), but the effect is still possible. Recently need to rewrite the code with Python, from yesterday day to this morning, I use Python features and MATLAB is not the same .... Oh, my God.... How could it be. The same structure, the same parameters, the same picture, h

Cifar10 training steps are as follows: (1) Open the terminal, apply the CD switch path, such as CD ~/caffe/data/cifar10, (2) Continue to execute the order./get_cifar10.sh, (3) After the successful download of the dataset, execute LS is visible to the downloaded data file, (4) Switch the path again to the CD ~/caffe/examples/cifar10 (5) Continue to execute the order./create_cifar10.sh The system does n

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 update-alternatives--INSTALL/USR/BIN/GCC gcc/

In fact, the installation of Caffe has been introduced very clearly, and there is no lack of introduction Caffe article, the reason for this is written because this is a Chinese version, and then I was in the lab server installation encountered a lot of problems, I think Up-and may encounter, so posted out Caffe Installation Guide under the Linux platform 1. S

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

Below for you to share a Python script to generate Caffe Train_list.txt method, with a good reference value, I hope to help you. Come and see it together. First give the code: Import Ospath = "/home/data//" path_exp = Os.path.expanduser (path) classes = [Int (p) for p in Os.listdir (PATH_EXP)]classes. Sort () # nrof_classes How many folders are there in a dataset, which means how many individuals, how many categories nrof_classes = Len (classes) coun

For example, now to add a vision layer, called Ly_layer: (generally named the first letter uppercase, the remaining lowercase.) ）1, which type of layer (a total of five species:common_layer, Data_layer, Loss_layer, Neuron_layer, Vision_layer ), open which HPP file (caffe-master/include/caffe/), open vision_layers.hpp here, and then add the definition of the layer yourself, or copy it directly Convolution_ L

Brief introductionCaffe is a friendly, easy-to-use, open-source deep learning platform, mainly used for image related processing, can support a variety of deep learning networks such as CNN.Based on Caffe, developers can easily and quickly develop a simple learning network for classification, positioning and other tasks, but also for scientific research, in its source code based on the modification, to achieve their own algorithm.The main purpose of t

1. PrefaceThe system used in this tutorial is Ubuntu 14.04 LTS 64-bit, using the Cuda version of 7.5, using the NVIDIA driver version of 352.If you are using Pascal architecture graphics, such as GTX1080 or new TTX, you must use a later driver and Cuda 8. This tutorial is not suitable for this situation, please do not try.Ubuntu releases the LTS version (the long-term support version) every two years, so the 16.04 LTS version has now been released. Given that many programs are not tested for com

First say nonsense: In the tutor's office 2 days + oneself at home Day finally completed Caffe configuration, (previous essay said every day update blog did not do but I really have in busy = =) The whole process out of countless, fortunately lucky enough configuration finished, while running cifar-10 train_ Full time to tidy up the whole process, and so the mentor's Titanx to be configured again.ENV:ALIENWARE17-R3, Ubuntu16.04 64-bit, NVIDIA Geforce

ippicv_linux_20151201.tgz this thing, 3.x version of the needPit two "compile Caffe":Caffe compilation requires a lot of dependent libraries, so the installation process of a variety of wonderful problems is normal. Here is the Caffe installation:Main reference URL: Reference site: http://blog.csdn.net/muzilinxi90/article/details/53673184　　Note:git clone https:/

STEP1: Installing homebrewIf there is a computer, temporarily do not install. However, if you still get an error after adding sudo to step2 (or any other situation that requires brew), you will need to reinstall homebrew. Enter the following command in the terminal:Ruby-e "$ (Curl-fssl https://raw.githubusercontent.com/Homebrew/install/master/intall)" to install.(reference URL: http://blog.csdn.net/yanzi1225627/article/details/42113661)STEP2: Installing CMakeAfter installing the homebrew, enter

Recently began to try deep learning things, brother recommended Caffe, began to try how to configure the Caffe to run the required environment.OK, get started.Find the Installation guide for Caffe official website: http://caffe.berkeleyvision.org/ Installation.html, really be installed in the pre-conditions scared a bit, a good lump, no way, installation needs, b

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