caffe windows

This article refers to the following: Instant Recognition with CaffeExtracting Features Caffe Python feature Extraction Caffe Practice 4--Use Python to bulk extract Caffe Compute features--by banana melodyCaffe Exercise 3 Use the C + + function provided by Caffe to extract image features in batches--by banana melody

When using Caffe, we want to use our own data for training, and here's how to make your own data. All data production is based on imagenet.1. Data preparation, we need a train and valid folder, a train.txt and Val.txt (the location of the picture folder can be arbitrary, but the location of the two TXT files in the data/mydata/directory)The train and valid folders naturally store the images to be trained, and the data formats for Train.txt and Val.txt

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 install python-dev python-pip python-numpy gfortran2.然后创建 virtual --system-site-packages caffe-env,执行 source bin/activate,3.运行for req in $(cat requiremen

The MATLAB program in Caffe supports 4. 7 of GCC and UBUNTU14. 04 of the band's own GCC is 4. 8 so it will be wrong to compile. So we'll install GCC4 first. 7, installation method can be checked online, as if sudo apt-get install gcc-4.7 and there are two versions of GCC, so you need to set the default GCC version in the following way we will install the g++ also installed on the g++4.7, so we replace the following: CD /usr/binsudo mv gcc gcc.baksudo

Recent new contact depth learning starts with getting started: The new Installation Cuda,caffe installation process is simple, there are all over the Internet1: Disable the Nouveau driver before you install CudaPress CTRL+ALT+F1 to enter the command prompt to create a new blacklist file# sudo vi/etc/modprobe.d/blacklist-nouveau.confInputBlacklist nouveauoptions nouveau modset=0Save exit (: Wq)And then execute# sudo update-initramfs-uExecutive Lspci |

Official Installation ManualRemark: Using the system-Ubuntu 15.04 64-bit operating system (if the system is on a virtual machine, Ubuntu will not be able to enter the GUI after Cuda is installed)/**************************************************/Preparatory work: Cuda,openblas,boost, PROTOBUF,OPENCV, Python/**************************************************/Method One:Install Caffe Official Manual on Ubuntu system (the artifact was not seen on the fi

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

Caffe display all kinds of accuracy (including accuracy_layer source modification) This article mainly includes the following content: Caffe Show all kinds of accuracy containing Accuracy_layer source code modification prototxt File mode Two directly modify the Accuracy_layercpp source Accuracy_layercpp source code Accuracy_laye Rcpp Source Code Modification This blog is designed to teach you to train th

Recently, the problem of target detection based on Caffe needs to use Caffe to train a regression network to predict the position of object in the image (X1,y1,width,height). However, the existing Caffe version (Happynear version) only applies to two classification problem data set conversion, so it is necessary to modify the

Always wanted to use DL for their current research in Image retrieval, in fact, the boy in the previous blog deep Learning for content-based Image retrieval on the use of DL to do a search paper also did some research. As you can see, the DL is now very hot, but it does not seem to have much use for image retrieval. This sky just to sneak in, in Ubuntu12.04 Caffe, success, can only say configuration up really very egg pain. The following is their own

Pre-recordBecause it is in a long-time machine installed Caffe, the process is more complex, on the web said that the clean machine is relatively simple. If you can have a clean machine, you do not have to go through so many pits, I hope everyone good luck! Introduction here will not say, directly into the topic:Caffe Home http://caffe.berkeleyvision.org/GitHub Home Https://github.com/BVLC/caffeMachine configuration:[Email protected] build]# lsb_relea

Most layers in Caffe are written in C + +. But for the input of their own data to write the corresponding input layer, such as you want to go to the part of the image, you can not use Lmdb, or your label needs a special tag. This is the time to write an input layer in Python.As in FCN's voc_layers.py there are two classes:VocsegdatalayerSbddsegdatalayerContains: Setup,reshape,forward, Backward, Load_image, Load_label, respectively. No backward is requ

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 Install Libhdf5-serial-devBlas can use ATLAS,MKL or Openblas.

Installation steps for linux14.04 under CaffeOriginal address: Http://blog.csdn.net/xiaoyang19910623/article/details/52997481?locationNum=1fps=11. Download Caffe-master,:https://github.com/bvlc/caffe, download to downloads;2. Unpack the installation package to downloads;3. First install boost and OPENCV, because these two are larger, the command is:sudo apt-get install Libopencv-devsudo apt-get install Libb

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-serial-dev Protobuf-compilersudo apt-get install--no-install-recommends Libboost-all-dev

Finally Caffe compiled successfully, just compile let the weak slag busy two weeks.Important thing to say three times!Do not use ubuntu16.04! now CUDA does not support!Don't use ubuntu16.04!. now the Cuda does not support! Don't use ubuntu16.04!. now the Cuda does not support! Do not use cudnn7.0-v5! now Caffe do not support!Don't use cudnn7.0-v5!. now the Caffe

1. Create CMakeLists.txt: Cmake_minimum_required (VERSION 2.8) Project (cf_mnist) SET (cmake_cxx_flags_debug "$ENV {cxxflags}-o0-wall- G-ggdb ") #SET (cmake_cxx_flags_release" $ENV {cxxflags}-o3-wall ") find_package (Caffe) find_package ( OpenCV REQUIRED) include_directories (${caffe_include_dirs}) add_definitions (${caffe_definitions}) Add_executable (cf_mnist cf_mnist.cpp) target_link_libraries (Cf_mnist ${opencv_libs} ${Caffe_LIBRARIES})2. Ent

Caffe things really much, the data must be Lmdb or leveldb what to do, if the data is a picture, that with Caffe from the Convert_image.cpp on the line, but if not the picture, you have to write the program. I am not a computer professional, I can understand the source code, and then work hard and Baidu, but there is no very results, so Google, tasted "inside the matter does not decide to ask Baidu, foreign

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

Caffe is a deep learning library, believe in deep learning, not to use this library is to use Theano bar. The first step to using Caffe is to configure the Caffe environment. Here, I am mainly talking about how to configure the Caffe library in the Debian Linux environment. Because Python is easy to write programs, at