caffe machine learning

Https://github.com/beniz/deepdetectDeepdetect (http://www.deepdetect.com/) is a machine learning APIs and server written in C++11. It makes state of the "Art machine" learning easy-to-work with and integrate into existing applications.Deepdetect relies on external machine

Dump: LMDBE:\ machine learning 2\caffe data \caffe_root\caffe-master\build\x64\release>convert_imageset.exe e:/machine learning 2/caffe Data/caffe_root/

Main reference HTTPS://GITHUB.COM/WEILIU89/CAFFE/TREE/SSD get SSD code, download complete with a Caffe folder git clone https://github.com/weiliu89/caffe.git cd caffe git Checkout SSDGo to the downloaded Caffe directory and copy the configuration file CD Caffe CP Makefile.co

view the loss layer or the upper layer of the accuracy layer, modify the cover layer of the num_output can beThen you can start training, you need to know that training parameters are defined in both Solver.prototxt and Train_val.prototxt, and Batch_size defines how many data to train or test each time, Max_ ITER defines the maximum number of iterations, Test_iter defines the number of tests, in order to ensure that all data is tested Test_iter and the product of the test batch_size needs to be

Recently, in learning deep learning, the tool used is caffe, easier to use, not long-winded, first of all, said the configuration and compilation of the environment. the platform of the system is win10+matlab2014b+vs2013. Before starting, to install the Cuda driver, I use the Cuda 7.5 version (to sync with the version used inside the

NVIDIA DIGITS-2.0 + Ubuntu 14.04 + CUDA 7.0 + CuDNN 7.0 + Caffe 0.13.0 Environment configuration Introduction Digits Introduction Digits characteristics Resource information Description Digits installation Hardware and Software Environment Hardware environment Software Environment Operating system Installation Digits Pre-Installation preparation

HTTP due to network problems, so according to the code in the script, according to the Web site to download the compressed package, CP to the Mnist folder, using the decompression commands in the script to extract.Then, convert it to the LMDB database format./examples/mnist/create_mnist. SHThen train the network./examples/mnist/train_lenet. SHWhen you are training, you can see the loss and accuracy valuesYou can see that the final training accuracy is 0.9911.Completed successfully.Share only fo

Nvidia DIGITS Learning Notes (nvidia DIGITS-2.0 + Ubuntu 14.04 + CUDA 7.0 + CuDNN 7.0 + Caffe 0.13.0)Enjoyyl 2015-09-02 machine learning original linkNVIDIA DIGITS-2.0 + Ubuntu 14.04 + CUDA 7.0 + CuDNN 7.0 + Caffe 0.13.0 Environment configuration Introduction

Caffe is an efficient, deep learning framework. It can be executed either on the CPU or on the GPU.The following is an introduction to the Caffe configuration compilation process on Ubuntu without Cuda:1. Install the blas:$ sudo apt-get install Libatlas-base-dev2. Install dependencies: $ sudo apt-get install Libprotobuf-dev libleveldb-dev libsnappy-devlibopencv-d

Caffe is an efficient, deep learning framework. It can be executed either on the CPU or on the GPU.The following is an introduction to the Caffe configuration compilation process on Ubuntu without Cuda:1. Install the blas:$ sudo apt-get install Libatlas-base-dev2. Install dependencies: $ sudo apt-get install Libprotobuf-dev libleveldb-dev libsnappy-dev libopencv-

; CaffeAll caffe of the message are defined in $caffe/src/caffe/proto/caffe.proto. ExperimentIn the experiment, the main use of two protocol buffer:solver and model, respectively, define the Solver parameters (learning rate of what) and model structure (network structure).Tip: Freeze a layer does not participate in tra

Caffe Installation Guide-vomiting blood finishingObjective:It is easy to install Caffe on a Linux machine with a good system environment, but if the system itself is old and there is no GPU, the installation is too cumbersome and all has to be done from scratch, and this document is designed to cover as much of the pit as possible for installation.Steps:First, th

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

How to Train the Lenet network using Caffe + MNIST on Ubuntu 14.04 64-bit Machine How to Train the Lenet network using Caffe + MNIST on Ubuntu 14.04 64-bit Machine 1. Locate the terminal to the Caffe root directory; 2. Download and decompress the MNIST Database: $./data/m

The deep learning framework Caffe is compiled and installed in Ubuntu. The deep learning framework Caffe features expressive, fast, and modular. The following describes how to compile and install Caffe on Ubuntu.1. Prerequisites: CUDA is used for computing in GPU mode.

Recently participated in a recognized competition, the project involved in a number of categories, originally intended to a large category training a classification model, but this will be more troublesome, for the same image classification will be repeated calculation of the classification network convolutional layer, waste computing time and efficiency. Later found that multi-tasking learning in deep learning