dongzhuoyao

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# Configuration
HOME_DIR=/home/[user]/
VERSION=3.1.0

# Installation
sudo apt-get update
sudo apt-get upgrade
sudo apt-get install -y build-essential cmake pkg-config
sudo apt-get install -y libjpeg8-dev libtiff5-dev libjasper-dev libpng12-dev
sudo apt-get install -y libavcodec-dev libavformat-dev libswscale-dev libv4l-dev

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#!/bin/bash

################################################################################
###                       OpenCV2 Installation Script                        ###
################################################################################
#            Source code at https://github.com/arthurbeggs/scripts             #
################################################################################
#                                                                              #
#     Feel free to copy and modify this file. Giving me credit for it is your  #
# choice, but please keep references to other people's work, which I don't     #

dongzhuoyao

Updated 4/11/2018

Here's my experience of installing the NVIDIA CUDA kit 9.0 on a fresh install of Ubuntu Desktop 16.04.4 LTS.

Table of Contents

• Install NVIDIA Graphics Driver via apt-get
• Install CUDA
• Install cuDNN

Table of contents generated with markdown-toc

dongzhuoyao

Felix Krull runs a PPA offering basically any version of Python (seriously, there is 2.3.7 build for vivid...) for many Ubuntu releases at

https://launchpad.net/~fkrull/+archive/ubuntu/deadsnakes

Do the usual:

sudo add-apt-repository ppa:fkrull/deadsnakes
sudo apt-get update
sudo apt-get install python3.5
It will not overwrite your existing python3.4 which is still symlinked as python3. If you want python3.5 to be the default python3, change the symlink

dongzhuoyao

local setting

PATH=$PATH:~/.local/bin
source /home/tao/.local/bin/virtualenvwrapper.sh
pip install virtualenvwrapper --user #make everything locally!!

vim, zsh is very hard to install locally without sudo permission.

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function [Dictionary,output] = KSVD(...
    Data,... % an nXN matrix that contins N signals (Y), each of dimension n.
    param)
% =========================================================================
%                          K-SVD algorithm
% =========================================================================
% The K-SVD algorithm finds a dictionary for linear representation of
% signals. Given a set of signals, it searches for the best dictionary that
% can sparsely represent each signal. Detailed discussion on the algorithm
% and possible applications can be found in "The K-SVD: An Algorithm for 

dongzhuoyao

"""
Multiclass SVMs (Crammer-Singer formulation).

A pure Python re-implementation of:

Large-scale Multiclass Support Vector Machine Training via Euclidean Projection onto the Simplex.
Mathieu Blondel, Akinori Fujino, and Naonori Ueda.
ICPR 2014.
http://www.mblondel.org/publications/mblondel-icpr2014.pdf
"""

dongzhuoyao

Theory of Building Caffe on OS X

Introduction

Our goal is to run python -c "import caffe" without crashing. For anyone who doesn't spend most of their time with build systems, getting to this point can be extremely difficult on OS X. Instead of providing a list of steps to follow, I'll try to epxlain why each step happens.

This page has OS X specific install instructions.

I assume:

dongzhuoyao

Caffe + Ubuntu 14.04 64bit + CUDA 6.5 配置说明

本步骤能实现用Intel核芯显卡来进行显示， 用NVIDIA GPU进行计算。

1. 安装开发所需的依赖包

安装开发所需要的一些基本包

sudo apt-get install build-essential  # basic requirement
sudo apt-get install libprotobuf-dev libleveldb-dev libsnappy-dev libopencv-dev libboost-all-dev libhdf5-serial-dev libgflags-dev libgoogle-glog-dev liblmdb-dev protobuf-compiler #required by caffe