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Caffe GNU error

*** Aborted at 1491880114 (unix time) try "date -d @1491880114" if you are using GNU date ***PC: @ 0x7fefd5f82cde (unknown)*** SIGSEGV (@0x0) received by PID 2769 (TID 0x7fefea08ca40) from PID 0;

2017-04-11 11:11:35

install opencv with linux

The following steps have been tested for Ubuntu 10.04 but should work with other distros as well.Required PackagesGCC 4.4.x or laterCMake 2.8.7 or higherGitGTK+2.x or higher, including headers

2017-04-09 09:21:17

Add sudo authority

12

2017-04-09 09:10:22

Caffe Layer Library

Convolution layer# convolutionlayer { name: "loss1/conv" type: "Convolution" bottom: "loss1/ave_pool" top: "loss1/conv" param { lr_mult: 1 decay_mult: 1 } param { lr_mult: 2

2017-03-14 15:22:33

Caffe Log Visualization

1.Record your train/test log as a log fileTOOLS=./build/tools GLOG_logtostderr=0 GLOG_log_dir=deepid/deepid2/Log/ \ $TOOLS/caffe train \ --solver=deepid/deepid2/deepid_solver.prototxt 2.Parse

2016-09-28 14:28:41

Caffe --- SyncedMemory

SyncedMemory类定义在syncedmem.hpp/cpp里, 主要负责caffe底层的内存管理.PS: Caffe的底层数据的切换(cpu模式和gpu模式),需要用到内存同步模块。其实个人觉得如果需要研究Blob,对于SyncedMemory的分析很重要内存分配与释放内存分配与释放由两个(不属于SyncedMemory类的)内联函数完成. 代码简单直观: 如果是CPU模式, 那么调用m

2016-07-25 09:59:49

Caffe --- blob code

两篇非常好的文章: http://blog.csdn.net/xizero00/article/details/50886829# http://www.cnblogs.com/yymn/articles/5341347.html

2016-07-23 13:02:21

Caffe Solver

Solver scaffolds the optimization bookkeeping and creates the training network for learning and test network(s) for evaluation. iteratively optimizes by calling forward / backward and updating p

2016-07-21 15:46:39

Blobs, Layers, and Nets: anatomy of a Caffe model

BlobsBlob作为Caffe的四大模块之一,负责完成CPU/GPU存储申请、同步和数据持久化映射。Caffe内部数据存储和通讯都是通过Blob来完成,Blob提供统一的存储操作接口,可用来保存训练数据、模型参数等。Blob 事实上是调用了SyncedMemory 类。SyncedMemory类封装了CPU/GPU内存申请、同步和释放等。所以SyncedMemory 完成了对内存的实际操作。

2016-07-21 15:39:26

Python learning

Packages are a way of structuring Python’s module namespace by using “dotted module names”

2016-07-21 11:57:15

Python layer

Fully Convolutional Networks for Semantic Segmentation 论文中公布的代码作为示例,解释python层该怎么写。 https://github.com/shelhamer/fcn.berkeleyvision.org First you have to build Caffe with WITH_PYTHON_LAYER option 1. R

2016-07-20 11:04:07

caffe net visualization

net.blobs.items() 存储了预测图片的网络中各层的feature map的数据。net.params.items()存储了训练结束后学习好的网络参数。vis_square 函数视觉化data,主要是进行数据归一化,data转换为plt可视化的square结构。plt.imshow(net.deprocess(‘data’, net.blobs[‘data’].data[4]))

2016-07-19 18:20:02

caffe net implement

#include <algorithm>#include <map>#include <set>#include <string>#include <utility>#include <vector>#include "caffe/common.hpp"#include "caffe/layer.hpp"#include "caffe/net.hpp"#include "caffe/

2016-07-19 17:28:31

caffe interface --- python

#include <Python.h> // NOLINT(build/include_alpha)// Produce deprecation warnings (needs to come before arrayobject.h inclusion).#define NPY_NO_DEPRECATED_API NPY_1_7_API_VERSION#include <boost/make_

2016-07-19 17:17:04

caffe interface --- matlab

本文首先介绍一些基础的入门知识,然后分析一个大型工程应用caffe_,从工程的视角分析,该如何设计好一个大型的交互接口。同时,找到matlab性能的瓶颈,正是我们需

2016-07-19 15:19:16

郑帅师兄的五年博士总结

这五年最重要的,是渐渐知道了怎么去做一件比较大的事情。说得很大,其实就一点,心要静下来。首先,心静下来才能钻进某个领域里认真做事。现在的社交媒体太多了,各类新闻也太多,每天忙于应付这些广泛却又浅薄的信号,或是忙着去评点别人,是没有办法做成一件事情的。就比如一个人要去旅游,按图索骥地走一圈著名的景点,并不会给自己新的体悟,最多只增些与人的谈资而已。真要体会大自然的美丽,那是一定要涉足别人达不到的地方,

2016-07-08 15:58:26

factor graph,potential function,Template models

factor是对于variables的某种combination的fitness。在BN中factor就是conditional probability distribution(CPD);但factor并不总对应着某种概率(当然也不一定取0~1),比如说在MRF中。和数据库table的操作类似,factor上的基本操作有factor product ,factor marginalization

2016-07-05 17:23:26

dense_CRF

/* Copyright (c) 2013, Philipp Krähenbühl All rights reserved. Redistribution and use in source and binary forms, with or without modification, are permitted provided that the followi

2016-06-30 10:44:32

deeplab script---python

import os,sys, subprocesssys.path.insert(0, os.getcwd()+'/python/my_script/')from tester import testerfrom trainer import trainerfrom crf_runner import crf_runner, grid_searchimport tools# MO

2016-06-01 07:53:21

deepLab

1.matio can't find HDF5 librarieschange file /densecrf/makefile as:g++ refine_pascal_v4/dense_inference.cpp util/Timer.h libDenseCRF.a$(CC) refine_pascal_v4/dense_inference.cpp -o prog_refine

2016-05-30 07:20:29

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