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

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

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# 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

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#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

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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);

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# 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__)

Coderx7

#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
    """

Coderx7

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.

Table of Contents

• Install NVIDIA Graphics Driver via apt-get
• Install NVIDIA Graphics Driver via runfile
  • Remove Previous Installations (Important)
  • Download the Driver
  • Install Dependencies
  • Creat Blacklist for Nouveau Driver

• Stop lightdm/gdm/kdm

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#!/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

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/* Example of embedding Python in another program */
// to compile run:
//  gcc -o test $(python-config --cflags) test.c $(python-config --ldflags) && ./test

#include<stdio.h>
#include "Python.h"

void initxyzzy(void); /* Forward */

main(int argc, char **argv)