Ubuntu 16.04 使用docker资料汇总与应用docker安装caffe并使用Classifier(ros kinetic+usb_cam+caffe)

前端之家收集整理的这篇文章主要介绍了Ubuntu 16.04 使用docker资料汇总与应用docker安装caffe并使用Classifier(ros kinetic+usb_cam+caffe)前端之家小编觉得挺不错的,现在分享给大家,也给大家做个参考。

Docker是开源的应用容器引擎。若想简单了解一下,可以参考百度百科词条Docker。好像只支持64位系统。

Docker官网:https://www.docker.com/

Docker — 从入门到实践:https://yeasy.gitbooks.io/docker_practice/content/

Pdf版下载:http://download.csdn.net/detail/zhangrelay/9743400

caffe官网:http://caffe.berkeleyvision.org/installation.html

caffe_docker:https://github.com/BVLC/caffe/tree/master/docker

然后参考这篇博客就可以了:http://blog.csdn.net/sysushui/article/details/54585788


看右图数据,准确识别出是磁罗盘(>0.8)

如: docker search caffe

$ docker search caffe
NAME                                  DESCRIPTION                                     STARS     OFFICIAL   AUTOMATED
kaixhin/caffe                         Ubuntu Core 14.04 + Caffe.                      33                   [OK]
kaixhin/cuda-caffe                    Ubuntu Core 14.04 + CUDA + Caffe.               30                   [OK]
neowaylabs/caffe-cpu                  Caffe cpu based on:  https://hub.docker.co...   4                    [OK]
kaixhin/caffe-deps                    `kaixhin/caffe` dependencies.                   1                    [OK]
mbartoli/caffe                        Caffe,cpu-only                                 1                    [OK]
drunkar/cuda-caffe-anaconda-chainer   cuda-caffe-anaconda-chainer                     1                    [OK]
kaixhin/cuda-caffe-deps               `kaixhin/cuda-caffe` dependencies.              0                    [OK]
mtngld/caffe-gpu                      Ubuntu + caffe (gpu ready)                      0                    [OK]
nitnelave/caffe                       Master branch of BVLC/caffe,on CentOS7 wi...   0                    [OK]
bvlc/caffe                            Official Caffe images                           0                    [OK]
ruimashita/caffe-gpu                  ubuntu 14.04 cuda 7 (NVIDIA driver version...   0                    [OK]
ruimashita/caffe-cpu-with-models      ubuntu 14.04 caffe  bvlc_reference_caffene...   0                    [OK]
elezar/caffe                          Caffe Docker Images                             0                    [OK]
ruimashita/caffe-gpu-with-models      ubuntu 14.04 cuda 7.0 caffe  bvlc_referenc...   0                    [OK]
floydhub/caffe                        Caffe docker image                              0                    [OK]
namikister/caffe                      Caffe with CUDA 8.0                             0                    [OK]
tingtinglu/caffe                      caffe                                           0                    [OK]
djpetti/caffe                         A simple container with Caffe,CUDA,and C...   0                    [OK]
flyingmouse/caffe                     Caffe is a deep learning framework made wi...   0                    [OK]
ruimashita/caffe-cpu                  ubuntu 14.04 caffe                              0                    [OK]
suyongsun/caffe-gpu                   Caffe image with gpu mode.                      0                    [OK]
haoyangz/caffe-cnn                    caffe-cnn                                       0                    [OK]
2breakfast/caffe-sshd                 installed sshd server on nvidia/caffe           0                    [OK]
chakkritte/docker-caffe               Docker caffe                                    0                    [OK]
ederrm/caffe                          Caffe http://caffe.berkeleyvision.org setup!    0                    [OK]
relaybot@relaybot-desktop:~$ 

选择安装即可,caffe安装cpu版本还是比较容易的。

安装完毕测试,这是在ros kinetic版本测试,和ros indigo一样。

具体请参考:

ROS + Caffe 机器人操作系统框架和深度学习框架笔记 (機器人控制與人工智能)

http://www.jb51.cc/article/p-khhqywwx-nh.html


$ roscore
... logging to /home/relaybot/.ros/log/f214a97a-e0b1-11e6-833d-70f1a1ca7552/roslaunch-relaybot-desktop-32381.log
Checking log directory for disk usage. This may take awhile.
Press Ctrl-C to interrupt
Done checking log file disk usage. Usage is <1GB.

started roslaunch server http://relaybot-desktop:44408/
ros_comm version 1.12.6


SUMMARY
========

PARAMETERS
* /rosdistro: kinetic
* /rosversion: 1.12.6

NODES

auto-starting new master
process[master]: started with pid [32411]
ROS_MASTER_URI=http://relaybot-desktop:11311/

setting /run_id to f214a97a-e0b1-11e6-833d-70f1a1ca7552
process[rosout-1]: started with pid [32424]
started core service [/rosout]


$ rosrun uvc_camera uvc_camera_node
[ INFO] [1485096579.984543774]: using default calibration URL
[ INFO] [1485096579.984671839]: camera calibration URL: file:///home/relaybot/.ros/camera_info/camera.yaml
[ INFO] [1485096579.984939036]: Unable to open camera calibration file [/home/relaybot/.ros/camera_info/camera.yaml]
[ WARN] [1485096579.984987494]: Camera calibration file /home/relaybot/.ros/camera_info/camera.yaml not found.
opening /dev/video0
pixfmt 0 = 'YUYV' desc = 'YUYV 4:2:2'
discrete: 640x480: 1/30 1/15
discrete: 352x288: 1/30 1/15
discrete: 320x240: 1/30 1/15
discrete: 176x144: 1/30 1/15
discrete: 160x120: 1/30 1/15
discrete: 1280x800: 2/15
discrete: 1280x1024: 2/15
int (Brightness,id = 980900): -64 to 64 (1)
int (Contrast,id = 980901): 0 to 64 (1)
int (Saturation,id = 980902): 0 to 128 (1)
int (Hue,id = 980903): -40 to 40 (1)
bool (White Balance Temperature,Auto,id = 98090c): 0 to 1 (1)
int (Gamma,id = 980910): 72 to 500 (1)
menu (Power Line Frequency,id = 980918): 0 to 2 (1)
0: Disabled
1: 50 Hz
2: 60 Hz
int (Sharpness,id = 98091b): 0 to 6 (1)
int (Backlight Compensation,id = 98091c): 0 to 2 (1)
select timeout in grab
^Crelaybot@relaybot-desktop:~$ rosrun uvc_camera uvc_camera_node topic:=/camera/b/image_raw
[ INFO] [1485096761.665718381]: using default calibration URL
[ INFO] [1485096761.665859706]: camera calibration URL: file:///home/relaybot/.ros/camera_info/camera.yaml
[ INFO] [1485096761.665944994]: Unable to open camera calibration file [/home/relaybot/.ros/camera_info/camera.yaml]
[ WARN] [1485096761.665980436]: Camera calibration file /home/relaybot/.ros/camera_info/camera.yaml not found.
opening /dev/video0
pixfmt 0 = 'YUYV' desc = 'YUYV 4:2:2'
discrete: 640x480: 1/30 1/15
discrete: 352x288: 1/30 1/15
discrete: 320x240: 1/30 1/15
discrete: 176x144: 1/30 1/15
discrete: 160x120: 1/30 1/15
discrete: 1280x800: 2/15
discrete: 1280x1024: 2/15
int (Brightness,id = 98091c): 0 to 2 (1)
select timeout in grab

rosrun topic_tools transform /image_raw /camera/rgb/image_raw sensor_msgs/Image 'm'

$ rosrun ros_caffe ros_caffe_test

WARNING: Logging before InitGoogleLogging() is written to STDERR

I0122 23:02:21.915738 2968 upgrade_proto.cpp:67] Attempting to upgrade input file specified using deprecated input fields: /home/relaybot/Rob_Soft/caffe/src/ros_caffe/data/deploy.prototxt

I0122 23:02:21.915875 2968 upgrade_proto.cpp:70] Successfully upgraded file specified using deprecated input fields.

W0122 23:02:21.915894 2968 upgrade_proto.cpp:72] Note that future Caffe releases will only support input layers and not input fields.

I0122 23:02:21.916246 2968 net.cpp:53] Initializing net from parameters:

name: "CaffeNet"

state {

phase: TEST

level: 0

}

layer {

name: "input"

type: "Input"

top: "data"

input_param {

shape {

dim: 10

dim: 3

dim: 227

dim: 227

}

}

}

layer {

name: "conv1"

type: "Convolution"

bottom: "data"

top: "conv1"

convolution_param {

num_output: 96

kernel_size: 11

stride: 4

}

}

layer {

name: "relu1"

type: "ReLU"

bottom: "conv1"

top: "conv1"

}

layer {

name: "pool1"

type: "Pooling"

bottom: "conv1"

top: "pool1"

pooling_param {

pool: MAX

kernel_size: 3

stride: 2

}

}

layer {

name: "norm1"

type: "LRN"

bottom: "pool1"

top: "norm1"

lrn_param {

local_size: 5

alpha: 0.0001

beta: 0.75

}

}

layer {

name: "conv2"

type: "Convolution"

bottom: "norm1"

top: "conv2"

convolution_param {

num_output: 256

pad: 2

kernel_size: 5

group: 2

}

}

layer {

name: "relu2"

type: "ReLU"

bottom: "conv2"

top: "conv2"

}

layer {

name: "pool2"

type: "Pooling"

bottom: "conv2"

top: "pool2"

pooling_param {

pool: MAX

kernel_size: 3

stride: 2

}

}

layer {

name: "norm2"

type: "LRN"

bottom: "pool2"

top: "norm2"

lrn_param {

local_size: 5

alpha: 0.0001

beta: 0.75

}

}

layer {

name: "conv3"

type: "Convolution"

bottom: "norm2"

top: "conv3"

convolution_param {

num_output: 384

pad: 1

kernel_size: 3

}

}

layer {

name: "relu3"

type: "ReLU"

bottom: "conv3"

top: "conv3"

}

layer {

name: "conv4"

type: "Convolution"

bottom: "conv3"

top: "conv4"

convolution_param {

num_output: 384

pad: 1

kernel_size: 3

group: 2

}

}

layer {

name: "relu4"

type: "ReLU"

bottom: "conv4"

top: "conv4"

}

layer {

name: "conv5"

type: "Convolution"

bottom: "conv4"

top: "conv5"

convolution_param {

num_output: 256

pad: 1

kernel_size: 3

group: 2

}

}

layer {

name: "relu5"

type: "ReLU"

bottom: "conv5"

top: "conv5"

}

layer {

name: "pool5"

type: "Pooling"

bottom: "conv5"

top: "pool5"

pooling_param {

pool: MAX

kernel_size: 3

stride: 2

}

}

layer {

name: "fc6"

type: "InnerProduct"

bottom: "pool5"

top: "fc6"

inner_product_param {

num_output: 4096

}

}

layer {

name: "relu6"

type: "ReLU"

bottom: "fc6"

top: "fc6"

}

layer {

name: "drop6"

type: "Dropout"

bottom: "fc6"

top: "fc6"

dropout_param {

dropout_ratio: 0.5

}

}

layer {

name: "fc7"

type: "InnerProduct"

bottom: "fc6"

top: "fc7"

inner_product_param {

num_output: 4096

}

}

layer {

name: "relu7"

type: "ReLU"

bottom: "fc7"

top: "fc7"

}

layer {

name: "drop7"

type: "Dropout"

bottom: "fc7"

top: "fc7"

dropout_param {

dropout_ratio: 0.5

}

}

layer {

name: "fc8"

type: "InnerProduct"

bottom: "fc7"

top: "fc8"

inner_product_param {

num_output: 1000

}

}

layer {

name: "prob"

type: "Softmax"

bottom: "fc8"

top: "prob"

}

I0122 23:02:21.916574 2968 layer_factory.hpp:77] Creating layer input

I0122 23:02:21.916613 2968 net.cpp:86] Creating Layer input

I0122 23:02:21.916638 2968 net.cpp:382] input -> data

I0122 23:02:21.931437 2968 net.cpp:124] Setting up input

I0122 23:02:21.939075 2968 net.cpp:131] Top shape: 10 3 227 227 (1545870)

I0122 23:02:21.939122 2968 net.cpp:139] Memory required for data: 6183480

I0122 23:02:21.939157 2968 layer_factory.hpp:77] Creating layer conv1

I0122 23:02:21.939210 2968 net.cpp:86] Creating Layer conv1

I0122 23:02:21.939235 2968 net.cpp:408] conv1 <- data

I0122 23:02:21.939278 2968 net.cpp:382] conv1 -> conv1

I0122 23:02:21.939563 2968 net.cpp:124] Setting up conv1

I0122 23:02:21.939604 2968 net.cpp:131] Top shape: 10 96 55 55 (2904000)

I0122 23:02:21.939618 2968 net.cpp:139] Memory required for data: 17799480

I0122 23:02:21.939685 2968 layer_factory.hpp:77] Creating layer relu1

I0122 23:02:21.939714 2968 net.cpp:86] Creating Layer relu1

I0122 23:02:21.939730 2968 net.cpp:408] relu1 <- conv1

I0122 23:02:21.939752 2968 net.cpp:369] relu1 -> conv1 (in-place)

I0122 23:02:21.939781 2968 net.cpp:124] Setting up relu1

I0122 23:02:21.939802 2968 net.cpp:131] Top shape: 10 96 55 55 (2904000)

I0122 23:02:21.939817 2968 net.cpp:139] Memory required for data: 29415480

I0122 23:02:21.939832 2968 layer_factory.hpp:77] Creating layer pool1

I0122 23:02:21.939857 2968 net.cpp:86] Creating Layer pool1

I0122 23:02:21.939868 2968 net.cpp:408] pool1 <- conv1

I0122 23:02:21.939887 2968 net.cpp:382] pool1 -> pool1

I0122 23:02:21.939947 2968 net.cpp:124] Setting up pool1

I0122 23:02:21.939967 2968 net.cpp:131] Top shape: 10 96 27 27 (699840)

I0122 23:02:21.939980 2968 net.cpp:139] Memory required for data: 32214840

I0122 23:02:21.939992 2968 layer_factory.hpp:77] Creating layer norm1

I0122 23:02:21.940014 2968 net.cpp:86] Creating Layer norm1

I0122 23:02:21.940027 2968 net.cpp:408] norm1 <- pool1

I0122 23:02:21.940045 2968 net.cpp:382] norm1 -> norm1

I0122 23:02:21.940075 2968 net.cpp:124] Setting up norm1

I0122 23:02:21.940093 2968 net.cpp:131] Top shape: 10 96 27 27 (699840)

I0122 23:02:21.940104 2968 net.cpp:139] Memory required for data: 35014200

I0122 23:02:21.940116 2968 layer_factory.hpp:77] Creating layer conv2

I0122 23:02:21.940137 2968 net.cpp:86] Creating Layer conv2

I0122 23:02:21.940152 2968 net.cpp:408] conv2 <- norm1

I0122 23:02:21.940171 2968 net.cpp:382] conv2 -> conv2

I0122 23:02:21.940996 2968 net.cpp:124] Setting up conv2

I0122 23:02:21.941033 2968 net.cpp:131] Top shape: 10 256 27 27 (1866240)

I0122 23:02:21.941045 2968 net.cpp:139] Memory required for data: 42479160

I0122 23:02:21.941121 2968 layer_factory.hpp:77] Creating layer relu2

I0122 23:02:21.941144 2968 net.cpp:86] Creating Layer relu2

I0122 23:02:21.941157 2968 net.cpp:408] relu2 <- conv2

I0122 23:02:21.941174 2968 net.cpp:369] relu2 -> conv2 (in-place)

I0122 23:02:21.941193 2968 net.cpp:124] Setting up relu2

I0122 23:02:21.941208 2968 net.cpp:131] Top shape: 10 256 27 27 (1866240)

I0122 23:02:21.941220 2968 net.cpp:139] Memory required for data: 49944120

I0122 23:02:21.941232 2968 layer_factory.hpp:77] Creating layer pool2

I0122 23:02:21.941248 2968 net.cpp:86] Creating Layer pool2

I0122 23:02:21.941259 2968 net.cpp:408] pool2 <- conv2

I0122 23:02:21.941275 2968 net.cpp:382] pool2 -> pool2

I0122 23:02:21.941301 2968 net.cpp:124] Setting up pool2

I0122 23:02:21.941316 2968 net.cpp:131] Top shape: 10 256 13 13 (432640)

I0122 23:02:21.941328 2968 net.cpp:139] Memory required for data: 51674680

I0122 23:02:21.941339 2968 layer_factory.hpp:77] Creating layer norm2

I0122 23:02:21.941360 2968 net.cpp:86] Creating Layer norm2

I0122 23:02:21.941372 2968 net.cpp:408] norm2 <- pool2

I0122 23:02:21.941390 2968 net.cpp:382] norm2 -> norm2

I0122 23:02:21.941411 2968 net.cpp:124] Setting up norm2

I0122 23:02:21.941426 2968 net.cpp:131] Top shape: 10 256 13 13 (432640)

I0122 23:02:21.941437 2968 net.cpp:139] Memory required for data: 53405240

I0122 23:02:21.941448 2968 layer_factory.hpp:77] Creating layer conv3

I0122 23:02:21.941468 2968 net.cpp:86] Creating Layer conv3

I0122 23:02:21.941478 2968 net.cpp:408] conv3 <- norm2

I0122 23:02:21.941495 2968 net.cpp:382] conv3 -> conv3

I0122 23:02:21.943603 2968 net.cpp:124] Setting up conv3

I0122 23:02:21.943662 2968 net.cpp:131] Top shape: 10 384 13 13 (648960)

I0122 23:02:21.943675 2968 net.cpp:139] Memory required for data: 56001080

I0122 23:02:21.943711 2968 layer_factory.hpp:77] Creating layer relu3

I0122 23:02:21.943733 2968 net.cpp:86] Creating Layer relu3

I0122 23:02:21.943747 2968 net.cpp:408] relu3 <- conv3

I0122 23:02:21.943765 2968 net.cpp:369] relu3 -> conv3 (in-place)

I0122 23:02:21.943786 2968 net.cpp:124] Setting up relu3

I0122 23:02:21.943801 2968 net.cpp:131] Top shape: 10 384 13 13 (648960)

I0122 23:02:21.943812 2968 net.cpp:139] Memory required for data: 58596920

I0122 23:02:21.943822 2968 layer_factory.hpp:77] Creating layer conv4

I0122 23:02:21.943848 2968 net.cpp:86] Creating Layer conv4

I0122 23:02:21.943861 2968 net.cpp:408] conv4 <- conv3

I0122 23:02:21.943881 2968 net.cpp:382] conv4 -> conv4

I0122 23:02:21.944964 2968 net.cpp:124] Setting up conv4

I0122 23:02:21.945030 2968 net.cpp:131] Top shape: 10 384 13 13 (648960)

I0122 23:02:21.945047 2968 net.cpp:139] Memory required for data: 61192760

I0122 23:02:21.945148 2968 layer_factory.hpp:77] Creating layer relu4

I0122 23:02:21.945188 2968 net.cpp:86] Creating Layer relu4

I0122 23:02:21.945206 2968 net.cpp:408] relu4 <- conv4

I0122 23:02:21.945230 2968 net.cpp:369] relu4 -> conv4 (in-place)

I0122 23:02:21.945258 2968 net.cpp:124] Setting up relu4

I0122 23:02:21.945277 2968 net.cpp:131] Top shape: 10 384 13 13 (648960)

I0122 23:02:21.945291 2968 net.cpp:139] Memory required for data: 63788600

I0122 23:02:21.945303 2968 layer_factory.hpp:77] Creating layer conv5

I0122 23:02:21.945334 2968 net.cpp:86] Creating Layer conv5

I0122 23:02:21.945353 2968 net.cpp:408] conv5 <- conv4

I0122 23:02:21.945376 2968 net.cpp:382] conv5 -> conv5

I0122 23:02:21.946549 2968 net.cpp:124] Setting up conv5

I0122 23:02:21.946606 2968 net.cpp:131] Top shape: 10 256 13 13 (432640)

I0122 23:02:21.946622 2968 net.cpp:139] Memory required for data: 65519160

I0122 23:02:21.946672 2968 layer_factory.hpp:77] Creating layer relu5

I0122 23:02:21.946698 2968 net.cpp:86] Creating Layer relu5

I0122 23:02:21.946717 2968 net.cpp:408] relu5 <- conv5

I0122 23:02:21.946743 2968 net.cpp:369] relu5 -> conv5 (in-place)

I0122 23:02:21.946771 2968 net.cpp:124] Setting up relu5

I0122 23:02:21.946792 2968 net.cpp:131] Top shape: 10 256 13 13 (432640)

I0122 23:02:21.946812 2968 net.cpp:139] Memory required for data: 67249720

I0122 23:02:21.946826 2968 layer_factory.hpp:77] Creating layer pool5

I0122 23:02:21.946848 2968 net.cpp:86] Creating Layer pool5

I0122 23:02:21.946864 2968 net.cpp:408] pool5 <- conv5

I0122 23:02:21.946885 2968 net.cpp:382] pool5 -> pool5

I0122 23:02:21.946935 2968 net.cpp:124] Setting up pool5

I0122 23:02:21.946971 2968 net.cpp:131] Top shape: 10 256 6 6 (92160)

I0122 23:02:21.946986 2968 net.cpp:139] Memory required for data: 67618360

I0122 23:02:21.947003 2968 layer_factory.hpp:77] Creating layer fc6

I0122 23:02:21.947028 2968 net.cpp:86] Creating Layer fc6

I0122 23:02:21.947044 2968 net.cpp:408] fc6 <- pool5

I0122 23:02:21.947065 2968 net.cpp:382] fc6 -> fc6

I0122 23:02:21.989847 2968 net.cpp:124] Setting up fc6

I0122 23:02:21.989913 2968 net.cpp:131] Top shape: 10 4096 (40960)

I0122 23:02:21.989919 2968 net.cpp:139] Memory required for data: 67782200

I0122 23:02:21.989943 2968 layer_factory.hpp:77] Creating layer relu6

I0122 23:02:21.989967 2968 net.cpp:86] Creating Layer relu6

I0122 23:02:21.989975 2968 net.cpp:408] relu6 <- fc6

I0122 23:02:21.989989 2968 net.cpp:369] relu6 -> fc6 (in-place)

I0122 23:02:21.990003 2968 net.cpp:124] Setting up relu6

I0122 23:02:21.990010 2968 net.cpp:131] Top shape: 10 4096 (40960)

I0122 23:02:21.990015 2968 net.cpp:139] Memory required for data: 67946040

I0122 23:02:21.990020 2968 layer_factory.hpp:77] Creating layer drop6

I0122 23:02:21.990031 2968 net.cpp:86] Creating Layer drop6

I0122 23:02:21.990036 2968 net.cpp:408] drop6 <- fc6

I0122 23:02:21.990043 2968 net.cpp:369] drop6 -> fc6 (in-place)

I0122 23:02:21.990067 2968 net.cpp:124] Setting up drop6

I0122 23:02:21.990074 2968 net.cpp:131] Top shape: 10 4096 (40960)

I0122 23:02:21.990079 2968 net.cpp:139] Memory required for data: 68109880

I0122 23:02:21.990084 2968 layer_factory.hpp:77] Creating layer fc7

I0122 23:02:21.990094 2968 net.cpp:86] Creating Layer fc7

I0122 23:02:21.990099 2968 net.cpp:408] fc7 <- fc6

I0122 23:02:21.990111 2968 net.cpp:382] fc7 -> fc7

I0122 23:02:22.008998 2968 net.cpp:124] Setting up fc7

I0122 23:02:22.009058 2968 net.cpp:131] Top shape: 10 4096 (40960)

I0122 23:02:22.009106 2968 net.cpp:139] Memory required for data: 68273720

I0122 23:02:22.009145 2968 layer_factory.hpp:77] Creating layer relu7

I0122 23:02:22.009173 2968 net.cpp:86] Creating Layer relu7

I0122 23:02:22.009187 2968 net.cpp:408] relu7 <- fc7

I0122 23:02:22.009209 2968 net.cpp:369] relu7 -> fc7 (in-place)

I0122 23:02:22.009232 2968 net.cpp:124] Setting up relu7

I0122 23:02:22.009248 2968 net.cpp:131] Top shape: 10 4096 (40960)

I0122 23:02:22.009259 2968 net.cpp:139] Memory required for data: 68437560

I0122 23:02:22.009269 2968 layer_factory.hpp:77] Creating layer drop7

I0122 23:02:22.009286 2968 net.cpp:86] Creating Layer drop7

I0122 23:02:22.009299 2968 net.cpp:408] drop7 <- fc7

I0122 23:02:22.009322 2968 net.cpp:369] drop7 -> fc7 (in-place)

I0122 23:02:22.009346 2968 net.cpp:124] Setting up drop7

I0122 23:02:22.009362 2968 net.cpp:131] Top shape: 10 4096 (40960)

I0122 23:02:22.009371 2968 net.cpp:139] Memory required for data: 68601400

I0122 23:02:22.009382 2968 layer_factory.hpp:77] Creating layer fc8

I0122 23:02:22.009399 2968 net.cpp:86] Creating Layer fc8

I0122 23:02:22.009410 2968 net.cpp:408] fc8 <- fc7

I0122 23:02:22.009428 2968 net.cpp:382] fc8 -> fc8

I0122 23:02:22.017177 2968 net.cpp:124] Setting up fc8

I0122 23:02:22.017282 2968 net.cpp:131] Top shape: 10 1000 (10000)

I0122 23:02:22.017313 2968 net.cpp:139] Memory required for data: 68641400

I0122 23:02:22.017356 2968 layer_factory.hpp:77] Creating layer prob

I0122 23:02:22.017395 2968 net.cpp:86] Creating Layer prob

I0122 23:02:22.017411 2968 net.cpp:408] prob <- fc8

I0122 23:02:22.017433 2968 net.cpp:382] prob -> prob

I0122 23:02:22.017469 2968 net.cpp:124] Setting up prob

I0122 23:02:22.017491 2968 net.cpp:131] Top shape: 10 1000 (10000)

I0122 23:02:22.017504 2968 net.cpp:139] Memory required for data: 68681400

I0122 23:02:22.017516 2968 net.cpp:202] prob does not need backward computation.

I0122 23:02:22.017554 2968 net.cpp:202] fc8 does not need backward computation.

I0122 23:02:22.017566 2968 net.cpp:202] drop7 does not need backward computation.

I0122 23:02:22.017577 2968 net.cpp:202] relu7 does not need backward computation.

I0122 23:02:22.017588 2968 net.cpp:202] fc7 does not need backward computation.

I0122 23:02:22.017598 2968 net.cpp:202] drop6 does not need backward computation.

I0122 23:02:22.017609 2968 net.cpp:202] relu6 does not need backward computation.

I0122 23:02:22.017619 2968 net.cpp:202] fc6 does not need backward computation.

I0122 23:02:22.017630 2968 net.cpp:202] pool5 does not need backward computation.

I0122 23:02:22.017642 2968 net.cpp:202] relu5 does not need backward computation.

I0122 23:02:22.017652 2968 net.cpp:202] conv5 does not need backward computation.

I0122 23:02:22.017663 2968 net.cpp:202] relu4 does not need backward computation.

I0122 23:02:22.017674 2968 net.cpp:202] conv4 does not need backward computation.

I0122 23:02:22.017685 2968 net.cpp:202] relu3 does not need backward computation.

I0122 23:02:22.017696 2968 net.cpp:202] conv3 does not need backward computation.

I0122 23:02:22.017707 2968 net.cpp:202] norm2 does not need backward computation.

I0122 23:02:22.017720 2968 net.cpp:202] pool2 does not need backward computation.

I0122 23:02:22.017734 2968 net.cpp:202] relu2 does not need backward computation.

I0122 23:02:22.017746 2968 net.cpp:202] conv2 does not need backward computation.

I0122 23:02:22.017757 2968 net.cpp:202] norm1 does not need backward computation.

I0122 23:02:22.017770 2968 net.cpp:202] pool1 does not need backward computation.

I0122 23:02:22.017783 2968 net.cpp:202] relu1 does not need backward computation.

I0122 23:02:22.017796 2968 net.cpp:202] conv1 does not need backward computation.

I0122 23:02:22.017809 2968 net.cpp:202] input does not need backward computation.

I0122 23:02:22.017819 2968 net.cpp:244] This network produces output prob

I0122 23:02:22.017868 2968 net.cpp:257] Network initialization done.

I0122 23:02:22.196004 2968 upgrade_proto.cpp:44] Attempting to upgrade input file specified using deprecated transformation parameters: /home/relaybot/Rob_Soft/caffe/src/ros_caffe/data/bvlc_reference_caffenet.caffemodel

I0122 23:02:22.196061 2968 upgrade_proto.cpp:47] Successfully upgraded file specified using deprecated data transformation parameters.

W0122 23:02:22.196069 2968 upgrade_proto.cpp:49] Note that future Caffe releases will only support transform_param messages for transformation fields.

I0122 23:02:22.196074 2968 upgrade_proto.cpp:53] Attempting to upgrade input file specified using deprecated V1LayerParameter: /home/relaybot/Rob_Soft/caffe/src/ros_caffe/data/bvlc_reference_caffenet.caffemodel

I0122 23:02:22.506147 2968 upgrade_proto.cpp:61] Successfully upgraded file specified using deprecated V1LayerParameter

I0122 23:02:22.507925 2968 net.cpp:746] Ignoring source layer data

I0122 23:02:22.597734 2968 net.cpp:746] Ignoring source layer loss

W0122 23:02:22.716584 2968 net.hpp:41] DEPRECATED: ForwardPrefilled() will be removed in a future version. Use Forward().

Test default image under /data/cat.jpg


0.3134 - "n02123045 tabby,tabby cat"
0.2380 - "n02123159 tiger cat"
0.1235 - "n02124075 Egyptian cat"
0.1003 - "n02119022 red fox,Vulpes vulpes"
0.0715 - "n02127052 lynx,catamount"
W0122 23:07:35.308277 2968 net.hpp:41] DEPRECATED: ForwardPrefilled() will be removed in a future version. Use Forward().
W0122 23:12:52.805382 2968 net.hpp:41] DEPRECATED: ForwardPrefilled() will be removed in a future version. Use Forward().


$ rostopic list

/camera/rgb/image_raw
/camera_info
/image_raw
/image_raw/compressed
/image_raw/compressed/parameter_descriptions
/image_raw/compressed/parameter_updates
/image_raw/compressedDepth
/image_raw/compressedDepth/parameter_descriptions
/image_raw/compressedDepth/parameter_updates
/image_raw/theora
/image_raw/theora/parameter_descriptions
/image_raw/theora/parameter_updates
/rosout
/rosout_agg


$ rostopic echo /caffe_ret

---
data: [0.557911 - n04286575 spotlight,spot]
[0.115966 - n03729826 matchstick]
[0.0737537 - n02948072 candle,taper,wax light]
[0.040883 - n09472597 volcano]
[0.028961 - n03666591 lighter,light,igniter,ignitor]

---



$ rosrun rqt_graph rqt_graph




-End-

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