yolo caffe

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

The specific installation process can refer to the official website of the installation, as well as some users to share some installation tutorials, tutorial one, tutorial two, tutorial three.I am here to record some of the problems I encountered during the installation process, as well as the workaround (not mentioned on the web), rather than the entire installation process. Because they are small white Linux, installation of Caffe spent a few days,

Draw on the http://blog.csdn.net/langb2014/article/details/50458520 of langb2014And the http://blog.csdn.net/liukailun09/article/details/51119052 of liukailun091. DataDownload: Data from langb2014 great God: Http://pan.baidu.com/s/1nuqlTnNData introduction: A total of 500 pictures, divided into buses, dinosaurs, elephants, flowers and horses five classes, each class 100. The numbers begin with 3,4,5,6,7, each of which is a category. Each category was selected for 20 tests and the remaining 80 fo

This paper introduces the preparation, transformation and the whole process of using SSD to train the data set in target detection. Contents include: 1, Data set preparation 1) Image callout 2) make VOC DataSet 3) Convert VOC data set to LMDB format 2, how to use SSD for training 3, use SSD to do test environment: Win7, compiled Caffe, Pytho N27, Python PIL (Pillow) module. Note: In Caffe