Seyyed Hossein Hasanpour Coderx7

Caffe + Ubuntu 12.04 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
sudo apt-get install vim cmake git
sudo apt-get install libprotobuf-dev libleveldb-dev libsnappy-dev libopencv-dev libboost-all-dev libhdf5-serial-dev

In this article, I will share some of my experience on installing NVIDIA driver and CUDA on Linux OS. Here I mainly use Ubuntu as example. Comments for CentOS/Fedora are also provided as much as I can.

	layers {
	name: "conv1A"
	type: CONVOLUTION
	bottom: "data"
	top: "conv1A"
	blobs_lr: 1
	blobs_lr: 2
	weight_decay: 1
	weight_decay: 0
	convolution_param {

	#!/usr/bin/python
	# -- coding: utf-8 --

	# Author: Axel Angel, copyright 2015, license GPLv3.
	# added mean subtraction so that, the accuracy can be reported accurately just like caffe when doing a mean subtraction
	# Seyyed Hossein Hasan Pour
	# Coderx7@Gmail.com
	# 7/3/2016

	import sys

	# Typical setup to include TensorFlow.
	import tensorflow as tf

	# Make a queue of file names including all the JPEG images files in the relative
	# image directory.
	filename_queue = tf.train.string_input_producer(
	tf.train.match_filenames_once("./images/*.jpg"))

	# Read an entire image file which is required since they're JPEGs, if the images
	# are too large they could be split in advance to smaller files or use the Fixed

	#in the name of Allah, the most compassionate the most merciful
	#run this scrip under python2. python3 would work, but not prefectly. e.g. running this script and setting oversample to true in
	#net.predict([input_image], oversample=True) will cause a crash. but it works just fine under python2.

	import numpy as np
	import os, sys, getopt

	# Main path to your caffe installation
	caffe_root = '/path/to/your/caffe/'
	# Model prototxt file


	import argparse
	import time

	start_time=time.time();
	################## Argument Parsing #####################################
	parser=argparse.ArgumentParser();
	parser.add_argument('-s','--solver', default='', type=str); # if empty, solver is created, else read
	parser.add_argument('-res', '--resume_from', default='', type=str); #if not empty, resumes training from given file
	parser.add_argument('-ft', '--finetune_from', default='', type=str);

Seyyed Hossein Hasanpour Coderx7

Caffe + Ubuntu 12.04 64bit + CUDA 6.5 配置说明

1. 安装开发所需的依赖包

Table of Contents

Table of Contents

1. Install NVIDIA Graphics Driver via apt-get

	# Dinesh Jayaraman

	# Based on code by
	# Authors: Fabian Pedregosa <fabian.pedregosa@inria.fr>
	# Olivier Grisel <olivier.grisel@ensta.org>
	# Mathieu Blondel <mathieu@mblondel.org>
	# Gael Varoquaux
	# License: BSD 3 clause (C) INRIA 2011

	print(__doc__)

	#برای نمایش بلادرنگ نمودار ترینینگ و تست ما
	import numpy as np
	from matplotlib import pyplot as plt

	class LivePlotNotebook(object):
	"""
	Live plot using %matplotlib notebook in jupyter notebook
	original url : https://gist.github.com/wassname/04e77eb821447705b399e8e7a6d082ce
	"""