caffe windows

"one, Ready." (In the blog "Two, compile" is not clear enough, and follow the process of the blog to compile, you will encounter some problems, specific issues described below.) ）2.2. Compiling(1) 1. Double-click the Caffe-windows-master/src/caffe/proto/extract_proto.bat batch file to generate three files: Caffe.pb.h, caffe.pb.cc, and Caffe_ pb2.py, the first tw

: ".. /.. /examples/cifar10/output_folders/cifar10_train_leveldb "Mean_file: ". /.. /examples/cifar10/mean.binaryproto "Source: ".. /.. /examples/cifar10/output_folders/cifar10_test_leveldb "and BACKEND:LEVELDB (there are two places!) ）Fifth Step:After you have changed two files, you can run Caffe to train, there are two ways, one is to write batch file bat, one is to run directly in vs2013First of all, create a text file under

This article describes how to use the well-trained model for image classification in MATLAB. Will take mnist as an example, the main use of Caffe-master\matlab\demo under the CLASSIFICATION_DEMO.M, can refer to my previous blog "Caffe-windows" Caffe-master CLASSFICATION_DEMO.M Ultra-Detailed analysis (http://blog.csdn.

This article describes in detail how to use Caffe to run their own image data for classification.1 first need to install the process see http://www.cnblogs.com/love6tao/p/5706830.html at the same time, according to the above tutorial, generated Caffe.exe2 Build your own data set. Divided into train and Val two datasets, this experiment for 2 classification tasks, one is to include the image of the car, one is not included in the car image, where train

When running the two examples of Caffe, our data comes from the Internet, which is a binary file that is downloaded directly.But most of us use raw picture data (such as. jpg. PNG, etc.), and then we'll look at how to convert the original image data into data that Caffe can run.1. Prepare picture data Caffe after the installation is complete, there will be four.

0. Recent Updates The contents of this blog are all obsolete and need to be installed by Caffe Windows version of the official tutorial (https://github.com/BVLC/caffe/tree/windows) directly. can also follow my GitHub (https://github.com/happynear/caffe-

After half a year, because of the needs of the paper, and re-start research Caffe. Thanks to the contribution of Niuzhiheng's GitHub great God, Caffe is already available under Windows. Reference to a lot of great God's blog, successfully configured in their own notebook Windows version of the

The format of the Convert.bat isConvert_imageset.exe position + Space +flags+ space + picture location + Space + The location of the list you generated + space + the location to save the DB format to be generatedIt is recommended to use absolute location!!!Example:D:/deeptools/caffe-windows-master/bin/convert_imageset.exe--shuffle--resize_height= --resize_width= d:/deeptools/

Description: Most of the masterpieces reproduced in Initialneil Caffe + vs2013 + OpenCV in Windows Tutorial (I) –setupPreparatory work:1. Download cuda7.5:https://developer.nvidia.com/cuda-downloads, the variable will be created automatically when the installation is complete cuda_path_v7_52. Download boost1.56:http://sourceforge.net/projects/boost/files/boost-binaries/1.56.0/, select boost_1_56_0- Msvc-12.

Consolidated Source: angle_cal 2016-12-19 17:32 624 ℃ 0 Reviews The BLVC version of Caffe-windows already supports visual Studio 2015, and the following configuration process is integrated with the experience of others and is validated to ensure effectiveness. Download Caffe-windows (BLVC): GitHubDownload good un

Windows Caffe in the GPU compilation processGeForce8800 gts512:cc=1.1CUDA6.5Question one:SRC/CAFFE/LAYERS/CONV_LAYER.CU: Error:too Few arguments in function callError in Conv_layer.cu:forward_gpu_gemm needs the argument Skip_im2col #1962Solve:https://github.com/BVLC/caffe/issues/1962As @liqing-ustc replied, just add "f

Basic EnvironmentIt is recommended to strictly follow the version-Windows 10-Visual Studio 2013-Matlab r2016b-Anaconda-CUDA 8.0.44-CuDNN V4 1. Installing Cuda 8.0After installation, the program automatically adds a CUDA_PATH environment variable: 2. Download CUDNNBefore downloading, you need to register a number on the developer online, simply fill in the basic material.The next is a compressed package, there is no way to install, the comp

http://blog.csdn.net/naaaa/article/details/52118437Tags: windowsvs2013caffecifar102016-08-04 15:33 1316 People read Comments (1) favorite reports Classification:CaffeCopyright NOTICE: This article for Bo Master original article, without Bo Master permission not reproduced.1. Download vs2013, installHttp://download.microsoft.com/download/0/7/5/0755898A-ED1B-4E11-BC04-6B9B7D82B1E4/VS2013_RTM_ULT_CHS.iso2. Download Caffe source code, unzipHttps://gith

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, VS2013 SP5 is a necessary version, according to H

Recently, the need to transplant faster-rcnn detect parts to the Android platform, to facilitate the deletion of code and debugging, the need for cross-platform compatibility to run under Windows, Windows debugging, With the Linux model definition proto and training good binary model, but the load model has not been successful, step-by-step solution is as follows: (1) Check the PROTOBUF version, are 2.5.0,

package. (I was placed under the D-Disk Caffe folder), note is 7.0, the actual I was under the CUDNN V5 (May,), the for CUDA 8.0 RC2. Unzip these two packages to get3. Open the Caffe-master folder, then see a Windows folder, then continue to open the Windows folder, see inside a CommonSettings.props.example file, copy

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

In the second year of Master's degree, he threw himself into the wave of deep learning. From the previous inertial navigation to this direction, everything starts from the beginning, here, only in this article to record their own way of playing strange.The initial idea is to get familiar with Caffe, considering the difficulty of getting started with the Ubuntu , so start with the basics in Windows. There is

appear after this file.3) Right-click the file to which you want to modify the extension, and then select the Rename option in the list.4) then enter the new extension, mouse click on the desktop blank place. Click the "Yes" button in the pop-up window.3. Open the file "Commonsetting.props", bold font for the modified content, the modified position should be opened in WordPad, the file's 第9-10 line, the following changes:truefalse4. Double-click "Caffe.sln" in the D:\

Recently contacted fine-grained classification, the classic method bilinear CNN used to bilinear layer, l2-normlize layer, SIGNED-SQRT layer, etc.These layers do not exist in the Caffe-windows already BVLC version of Caffe, you need to add the above layers to the Caffe project if you want to apply themHttps://github.co