Building 11_camera_object_identification

I am trying to follow the directions provided in the README file for 11_camera_object_identification and I got to step number 4. The instructions that I am trying to follow are:

#4. Build and run the sample with the following commands:

    $ cd 11_camera_object_identification
    $ make

But when I use make, the terminal gives me the following response:

ubuntu@tegra-ubuntu:~/tegra_multimedia_api/samples/11_camera_object_identification$ make
../Rules.mk:37: *** Please specify which ARM ABI platform you are compiling for.  Stop.

If I move on the the next step without heeding this warning, the terminal gives me this:

ubuntu@tegra-ubuntu:~/tegra_multimedia_api/samples/11_camera_object_identification$ ./camera_caffe -width 1920 -height 1080 \
> -lib opencv_consumer_lib/libopencv_consumer.so \
> -model $HOME/Work/caffe/caffe-master/models/bvlc_reference_caffenet/deploy.prototxt \
> -trained $HOME/Work/caffe/caffe-master/models/bvlc_reference_caffenet/
Error: CAFFE mean file missing!

Usage:./camera_caffe [options]

OPTIONS:
	-h,--help

	-width width                camera width, <1 -- 4096>
	-height height              camera height, <1 -- 4096>

	-lib library                image processing library

	-model model_file           CAFFE model file
	-trained trained_file       CAFFE trained file
	-mean mean_file             CAFFE mean file
	-label label_file           CAFFE label file
Error generated. camera_caffe_main.cpp, main:590 Fail to parse arguments.

How would I specify the ABI and how would I know what ABI to specify?

Hi PlatinumLuthier,
Please also refer to /home/ubuntu/tegra_multimedia_api/README to set up the environment.

And are you on r24.2.1? Do you download and build caffe?

Hi PlatinumLuthier,

Have this issue been clarified and resolved by your sides?
Any further suggestion required?

Thanks

I’m sorry for the delayed response, my semester started so I haven’t had as much time to fiddle around with it. I will look into this tonight and get back to you when I do that. As for downloading and building caffe, I followed the directions step by step in the readme file. I was under the impression that that was the process for building caffe.

As it turns out, it messed up because I somehow ran out of space on the module.

Hi,

I get the same error message. After flashing the latest Jetpack, I installed caffe, and also setup the environment variable as you mentioned earlier. Still after using ‘make’ :

ubuntu@tegra-ubuntu:~/tegra_multimedia_api/samples/11_camera_object_identification$ make
…/Rules.mk:37: *** Please specify which ARM ABI platform you are compiling for. Stop.

Hi rooz5002,
Please do the steps in /home/ubuntu/tegra_multimedia_api/README

To export environment variables
===============================

1. Export the ARM application binary interface based on the target
   platform with the following command:

        $ export TEGRA_ARMABI=aarch64-linux-gnu

2. Export the XDisplay with the following command:

        $ export DISPLAY=:0

(skip...)

6. For installation details, see the _installer folder.

To create the needed symbolic links
===================================

*  Create symbolic links with the following commands:

    $ cd /usr/lib/${TEGRA_ARMABI}
    $ sudo ln -sf tegra-egl/libEGL.so.1 libEGL.so
    $ sudo ln -sf tegra-egl/libGLESv2.so.2 libGLESv2.so
    $ sudo ln -sf libv4l2.so.0 libv4l2.so

I have tested 11_camera_object_identification . I have installed caffe, and also setup the environment variable as README. However,I met the failure like this.

F0501 15:35:06.339401 2336 pooling_layer.cu:212] Check failed: error == cudaSuccess (8 vs. 0) invalid device function
*** Check failure stack trace: ***

Who can help me?How to resolve it?

It looks like you have built both caffe and 11_camera_object_identification successfully and have issues in executing the app? Please share full log for reference.

ubuntu@tegra-ubuntu:~$ export TEGRA_ARMABI=aarch64-linux-gnu
ubuntu@tegra-ubuntu:~$ export DISPLAY=:0
ubuntu@tegra-ubuntu:~$ cd /usr/lib/${TEGRA_ARMABI}
ubuntu@tegra-ubuntu:/usr/lib/aarch64-linux-gnu$ sudo ln -sf tegra-egl/libEGL.so.1 libEGL.so
[sudo] password for ubuntu: 
ubuntu@tegra-ubuntu:/usr/lib/aarch64-linux-gnu$ sudo ln -sf tegra-egl/libGLESv2.so.2 libGLESv2.so
ubuntu@tegra-ubuntu:/usr/lib/aarch64-linux-gnu$ sudo ln -sf libv4l2.so.0 libv4l2.so
ubuntu@tegra-ubuntu:/usr/lib/aarch64-linux-gnu$ cd
ubuntu@tegra-ubuntu:~$ cd tegra_multimedia_api/samples/11_camera_object_identification/
ubuntu@tegra-ubuntu:~/tegra_multimedia_api/samples/11_camera_object_identification$ make
make: Nothing to be done for 'all'.
ubuntu@tegra-ubuntu:~/tegra_multimedia_api/samples/11_camera_object_identification$ export LD_LIBRARY_PATH=$HOME/Work/caffe/caffe-master/build/lib:/usr/local/cu
da/lib64
ubuntu@tegra-ubuntu:~/tegra_multimedia_api/samples/11_camera_object_identification$ ./camera_caffe -width 1920 -height 1080 \
> -lib opencv_consumer_lib/libopencv_consumer.so \
> -model $HOME/Work/caffe/caffe-master/models/bvlc_reference_caffenet/deploy.prototxt \
> -trained $HOME/Work/caffe/caffe-master/models/bvlc_reference_caffenet/bvlc_reference_caffenet.caffemodel \
> -mean $HOME/Work/caffe/caffe-master/data/ilsvrc12/imagenet_mean.binaryproto \
> -label $HOME/Work/caffe/caffe-master/data/ilsvrc12/synset_words.txt
opencv_handler_open is called
opencv_set_config 0
Image width 1920
opencv_set_config 1
Image height 1080
opencv_set_config 2
CAFFE model file : 0x5c7200
opencv_set_config 3
CAFFE trained file : 0x5c6740
opencv_set_config 4
CAFFE mean file : 0x5c67e0
opencv_set_config 5
CAFFE label file : 0x5c6870
opencv_set_config 6
NvPclHwGetModuleData: Misc Driver v4l2_focuser_stub already exists. Avoiding duplicate drivers
Sensor_LoadModeModeType: mode 0: Failed to load pixeltype
Sensor_LoadModePixelPhase: mode 0: Failed to load pixeltype
Sensor_LoadModeModeType: mode 1: Failed to load pixeltype
Sensor_LoadModePixelPhase: mode 1: Failed to load pixeltype
Sensor_LoadModeModeType: mode 2: Failed to load pixeltype
Sensor_LoadModePixelPhase: mode 2: Failed to load pixeltype
PRODUCER: Creating output stream
PRODUCER: Launching consumer thread
Failed to query video capabilities: Bad address
libv4l2_nvvidconv (0):(765) (INFO) : Allocating (10) OUTPUT PLANE BUFFERS Layout=1
libv4l2_nvvidconv (0):(775) (INFO) : Allocating (10) CAPTURE PLANE BUFFERS Layout=0
create vidoe converter return true
CONSUMER: Waiting until producer is connected...
PRODUCER: Starting repeat capture requests.
CONSUMER: Producer has connected; continuing.
Sensor_GetV4LPixelType: pixel type 0x101 invalid
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WARNING: Logging before InitGoogleLogging() is written to STDERR
I0508 10:19:15.630271  8265 net.cpp:51] Initializing net from parameters: 
name: "CaffeNet"
state {
  phase: TEST
  level: 0
}
layer {
  name: "data"
  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"
}
I0508 10:19:15.634012  8265 layer_factory.hpp:77] Creating layer data
I0508 10:19:15.634155  8265 net.cpp:84] Creating Layer data
I0508 10:19:15.634223  8265 net.cpp:380] data -> data
I0508 10:19:15.650704  8265 net.cpp:122] Setting up data
I0508 10:19:15.650840  8265 net.cpp:129] Top shape: 10 3 227 227 (1545870)
I0508 10:19:15.650943  8265 net.cpp:137] Memory required for data: 6183480
I0508 10:19:15.651006  8265 layer_factory.hpp:77] Creating layer conv1
I0508 10:19:15.651124  8265 net.cpp:84] Creating Layer conv1
I0508 10:19:15.651183  8265 net.cpp:406] conv1 <- data
I0508 10:19:15.651257  8265 net.cpp:380] conv1 -> conv1
CONSUMER: acquireFd 1828717983 (1 frames)
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I0508 10:19:16.704816  8265 net.cpp:122] Setting up conv1
I0508 10:19:16.704903  8265 net.cpp:129] Top shape: 10 96 55 55 (2904000)
I0508 10:19:16.704954  8265 net.cpp:137] Memory required for data: 17799480
I0508 10:19:16.705088  8265 layer_factory.hpp:77] Creating layer relu1
I0508 10:19:16.705145  8265 net.cpp:84] Creating Layer relu1
I0508 10:19:16.705183  8265 net.cpp:406] relu1 <- conv1
I0508 10:19:16.705219  8265 net.cpp:367] relu1 -> conv1 (in-place)
I0508 10:19:16.706744  8265 net.cpp:122] Setting up relu1
I0508 10:19:16.706804  8265 net.cpp:129] Top shape: 10 96 55 55 (2904000)
I0508 10:19:16.706841  8265 net.cpp:137] Memory required for data: 29415480
I0508 10:19:16.706876  8265 layer_factory.hpp:77] Creating layer pool1
I0508 10:19:16.706923  8265 net.cpp:84] Creating Layer pool1
I0508 10:19:16.706955  8265 net.cpp:406] pool1 <- conv1
I0508 10:19:16.707000  8265 net.cpp:380] pool1 -> pool1
I0508 10:19:16.707350  8265 net.cpp:122] Setting up pool1
I0508 10:19:16.707401  8265 net.cpp:129] Top shape: 10 96 27 27 (699840)
I0508 10:19:16.707437  8265 net.cpp:137] Memory required for data: 32214840
I0508 10:19:16.707466  8265 layer_factory.hpp:77] Creating layer norm1
I0508 10:19:16.707537  8265 net.cpp:84] Creating Layer norm1
I0508 10:19:16.707571  8265 net.cpp:406] norm1 <- pool1
I0508 10:19:16.707607  8265 net.cpp:380] norm1 -> norm1
I0508 10:19:16.709095  8265 net.cpp:122] Setting up norm1
I0508 10:19:16.709161  8265 net.cpp:129] Top shape: 10 96 27 27 (699840)
I0508 10:19:16.709202  8265 net.cpp:137] Memory required for data: 35014200
I0508 10:19:16.709235  8265 layer_factory.hpp:77] Creating layer conv2
I0508 10:19:16.709285  8265 net.cpp:84] Creating Layer conv2
I0508 10:19:16.709326  8265 net.cpp:406] conv2 <- norm1
I0508 10:19:16.709363  8265 net.cpp:380] conv2 -> conv2
I0508 10:19:16.720489  8265 net.cpp:122] Setting up conv2
I0508 10:19:16.720574  8265 net.cpp:129] Top shape: 10 256 27 27 (1866240)
I0508 10:19:16.720623  8265 net.cpp:137] Memory required for data: 42479160
I0508 10:19:16.720681  8265 layer_factory.hpp:77] Creating layer relu2
I0508 10:19:16.720734  8265 net.cpp:84] Creating Layer relu2
I0508 10:19:16.720767  8265 net.cpp:406] relu2 <- conv2
I0508 10:19:16.720805  8265 net.cpp:367] relu2 -> conv2 (in-place)
I0508 10:19:16.722362  8265 net.cpp:122] Setting up relu2
I0508 10:19:16.722434  8265 net.cpp:129] Top shape: 10 256 27 27 (1866240)
I0508 10:19:16.722482  8265 net.cpp:137] Memory required for data: 49944120
I0508 10:19:16.722525  8265 layer_factory.hpp:77] Creating layer pool2
I0508 10:19:16.722625  8265 net.cpp:84] Creating Layer pool2
I0508 10:19:16.722661  8265 net.cpp:406] pool2 <- conv2
I0508 10:19:16.722705  8265 net.cpp:380] pool2 -> pool2
I0508 10:19:16.723040  8265 net.cpp:122] Setting up pool2
I0508 10:19:16.723114  8265 net.cpp:129] Top shape: 10 256 13 13 (432640)
I0508 10:19:16.723172  8265 net.cpp:137] Memory required for data: 51674680
I0508 10:19:16.723209  8265 layer_factory.hpp:77] Creating layer norm2
I0508 10:19:16.723321  8265 net.cpp:84] Creating Layer norm2
I0508 10:19:16.723466  8265 net.cpp:406] norm2 <- pool2
I0508 10:19:16.723618  8265 net.cpp:380] norm2 -> norm2
CONSUMER: acquireFd 1828718056 (1 frames)
I0508 10:19:16.725704  8265 net.cpp:122] Setting up norm2
I0508 10:19:16.725888  8265 net.cpp:129] Top shape: 10 256 13 13 (432640)
I0508 10:19:16.726023  8265 net.cpp:137] Memory required for data: 53405240
I0508 10:19:16.726150  8265 layer_factory.hpp:77] Creating layer conv3
I0508 10:19:16.726289  8265 net.cpp:84] Creating Layer conv3
I0508 10:19:16.726416  8265 net.cpp:406] conv3 <- norm2
I0508 10:19:16.726544  8265 net.cpp:380] conv3 -> conv3
CONSUMER: releaseFd 1828718056 (1 frames)
I0508 10:19:16.735821  8265 net.cpp:122] Setting up conv3
I0508 10:19:16.735894  8265 net.cpp:129] Top shape: 10 384 13 13 (648960)
I0508 10:19:16.735937  8265 net.cpp:137] Memory required for data: 56001080
I0508 10:19:16.735991  8265 layer_factory.hpp:77] Creating layer relu3
I0508 10:19:16.736034  8265 net.cpp:84] Creating Layer relu3
I0508 10:19:16.736065  8265 net.cpp:406] relu3 <- conv3
I0508 10:19:16.736099  8265 net.cpp:367] relu3 -> conv3 (in-place)
I0508 10:19:16.737752  8265 net.cpp:122] Setting up relu3
I0508 10:19:16.737813  8265 net.cpp:129] Top shape: 10 384 13 13 (648960)
I0508 10:19:16.737850  8265 net.cpp:137] Memory required for data: 58596920
I0508 10:19:16.737881  8265 layer_factory.hpp:77] Creating layer conv4
I0508 10:19:16.737926  8265 net.cpp:84] Creating Layer conv4
I0508 10:19:16.737954  8265 net.cpp:406] conv4 <- conv3
I0508 10:19:16.737989  8265 net.cpp:380] conv4 -> conv4
I0508 10:19:16.752305  8265 net.cpp:122] Setting up conv4
I0508 10:19:16.752384  8265 net.cpp:129] Top shape: 10 384 13 13 (648960)
I0508 10:19:16.752434  8265 net.cpp:137] Memory required for data: 61192760
I0508 10:19:16.752490  8265 layer_factory.hpp:77] Creating layer relu4
I0508 10:19:16.752537  8265 net.cpp:84] Creating Layer relu4
I0508 10:19:16.752573  8265 net.cpp:406] relu4 <- conv4
I0508 10:19:16.752614  8265 net.cpp:367] relu4 -> conv4 (in-place)
I0508 10:19:16.754343  8265 net.cpp:122] Setting up relu4
I0508 10:19:16.754406  8265 net.cpp:129] Top shape: 10 384 13 13 (648960)
I0508 10:19:16.754446  8265 net.cpp:137] Memory required for data: 63788600
I0508 10:19:16.754482  8265 layer_factory.hpp:77] Creating layer conv5
I0508 10:19:16.754528  8265 net.cpp:84] Creating Layer conv5
I0508 10:19:16.754564  8265 net.cpp:406] conv5 <- conv4
I0508 10:19:16.754603  8265 net.cpp:380] conv5 -> conv5
I0508 10:19:16.773831  8265 net.cpp:122] Setting up conv5
I0508 10:19:16.773906  8265 net.cpp:129] Top shape: 10 256 13 13 (432640)
I0508 10:19:16.773952  8265 net.cpp:137] Memory required for data: 65519160
I0508 10:19:16.774008  8265 layer_factory.hpp:77] Creating layer relu5
I0508 10:19:16.774054  8265 net.cpp:84] Creating Layer relu5
I0508 10:19:16.774086  8265 net.cpp:406] relu5 <- conv5
I0508 10:19:16.774122  8265 net.cpp:367] relu5 -> conv5 (in-place)
I0508 10:19:16.778875  8265 net.cpp:122] Setting up relu5
I0508 10:19:16.779027  8265 net.cpp:129] Top shape: 10 256 13 13 (432640)
I0508 10:19:16.779094  8265 net.cpp:137] Memory required for data: 67249720
I0508 10:19:16.779146  8265 layer_factory.hpp:77] Creating layer pool5
I0508 10:19:16.779227  8265 net.cpp:84] Creating Layer pool5
I0508 10:19:16.779284  8265 net.cpp:406] pool5 <- conv5
I0508 10:19:16.779352  8265 net.cpp:380] pool5 -> pool5
I0508 10:19:16.780225  8265 net.cpp:122] Setting up pool5
I0508 10:19:16.780346  8265 net.cpp:129] Top shape: 10 256 6 6 (92160)
I0508 10:19:16.780412  8265 net.cpp:137] Memory required for data: 67618360
I0508 10:19:16.780457  8265 layer_factory.hpp:77] Creating layer fc6
I0508 10:19:16.780567  8265 net.cpp:84] Creating Layer fc6
I0508 10:19:16.780632  8265 net.cpp:406] fc6 <- pool5
I0508 10:19:16.780683  8265 net.cpp:380] fc6 -> fc6
CONSUMER: acquireFd 1828718165 (1 frames)
CONSUMER: releaseFd 1828718165 (1 frames)
CONSUMER: acquireFd 1828718165 (1 frames)
CONSUMER: releaseFd 1828718165 (1 frames)
CONSUMER: acquireFd 1828718165 (1 frames)
CONSUMER: releaseFd 1828718165 (1 frames)
I0508 10:19:16.936663  8265 net.cpp:122] Setting up fc6
I0508 10:19:16.936749  8265 net.cpp:129] Top shape: 10 4096 (40960)
I0508 10:19:16.936789  8265 net.cpp:137] Memory required for data: 67782200
I0508 10:19:16.936839  8265 layer_factory.hpp:77] Creating layer relu6
I0508 10:19:16.936887  8265 net.cpp:84] Creating Layer relu6
I0508 10:19:16.936920  8265 net.cpp:406] relu6 <- fc6
I0508 10:19:16.936964  8265 net.cpp:367] relu6 -> fc6 (in-place)
I0508 10:19:16.941865  8265 net.cpp:122] Setting up relu6
I0508 10:19:16.941937  8265 net.cpp:129] Top shape: 10 4096 (40960)
I0508 10:19:16.941982  8265 net.cpp:137] Memory required for data: 67946040
I0508 10:19:16.942018  8265 layer_factory.hpp:77] Creating layer drop6
I0508 10:19:16.942067  8265 net.cpp:84] Creating Layer drop6
I0508 10:19:16.942101  8265 net.cpp:406] drop6 <- fc6
I0508 10:19:16.942138  8265 net.cpp:367] drop6 -> fc6 (in-place)
I0508 10:19:16.942410  8265 net.cpp:122] Setting up drop6
I0508 10:19:16.942456  8265 net.cpp:129] Top shape: 10 4096 (40960)
I0508 10:19:16.942495  8265 net.cpp:137] Memory required for data: 68109880
I0508 10:19:16.942528  8265 layer_factory.hpp:77] Creating layer fc7
I0508 10:19:16.942570  8265 net.cpp:84] Creating Layer fc7
I0508 10:19:16.942602  8265 net.cpp:406] fc7 <- fc6
I0508 10:19:16.942638  8265 net.cpp:380] fc7 -> fc7
CONSUMER: acquireFd 1828718340 (1 frames)
CONSUMER: releaseFd 1828718340 (1 frames)
I0508 10:19:17.012949  8265 net.cpp:122] Setting up fc7
I0508 10:19:17.013021  8265 net.cpp:129] Top shape: 10 4096 (40960)
I0508 10:19:17.013062  8265 net.cpp:137] Memory required for data: 68273720
I0508 10:19:17.013104  8265 layer_factory.hpp:77] Creating layer relu7
I0508 10:19:17.013146  8265 net.cpp:84] Creating Layer relu7
I0508 10:19:17.013177  8265 net.cpp:406] relu7 <- fc7
I0508 10:19:17.013211  8265 net.cpp:367] relu7 -> fc7 (in-place)
I0508 10:19:17.018929  8265 net.cpp:122] Setting up relu7
I0508 10:19:17.019006  8265 net.cpp:129] Top shape: 10 4096 (40960)
I0508 10:19:17.019047  8265 net.cpp:137] Memory required for data: 68437560
I0508 10:19:17.019078  8265 layer_factory.hpp:77] Creating layer drop7
I0508 10:19:17.019126  8265 net.cpp:84] Creating Layer drop7
I0508 10:19:17.019157  8265 net.cpp:406] drop7 <- fc7
I0508 10:19:17.019193  8265 net.cpp:367] drop7 -> fc7 (in-place)
I0508 10:19:17.019420  8265 net.cpp:122] Setting up drop7
I0508 10:19:17.019471  8265 net.cpp:129] Top shape: 10 4096 (40960)
I0508 10:19:17.019503  8265 net.cpp:137] Memory required for data: 68601400
I0508 10:19:17.019532  8265 layer_factory.hpp:77] Creating layer fc8
I0508 10:19:17.019569  8265 net.cpp:84] Creating Layer fc8
I0508 10:19:17.019598  8265 net.cpp:406] fc8 <- fc7
I0508 10:19:17.019630  8265 net.cpp:380] fc8 -> fc8
CONSUMER: acquireFd 1828718349 (1 frames)
CONSUMER: releaseFd 1828718349 (1 frames)
I0508 10:19:17.038238  8265 net.cpp:122] Setting up fc8
I0508 10:19:17.038308  8265 net.cpp:129] Top shape: 10 1000 (10000)
I0508 10:19:17.038355  8265 net.cpp:137] Memory required for data: 68641400
I0508 10:19:17.038408  8265 layer_factory.hpp:77] Creating layer prob
I0508 10:19:17.038456  8265 net.cpp:84] Creating Layer prob
I0508 10:19:17.038498  8265 net.cpp:406] prob <- fc8
I0508 10:19:17.038538  8265 net.cpp:380] prob -> prob
I0508 10:19:17.042289  8265 net.cpp:122] Setting up prob
I0508 10:19:17.042361  8265 net.cpp:129] Top shape: 10 1000 (10000)
I0508 10:19:17.042415  8265 net.cpp:137] Memory required for data: 68681400
I0508 10:19:17.042455  8265 net.cpp:200] prob does not need backward computation.
I0508 10:19:17.042522  8265 net.cpp:200] fc8 does not need backward computation.
I0508 10:19:17.042577  8265 net.cpp:200] drop7 does not need backward computation.
I0508 10:19:17.042623  8265 net.cpp:200] relu7 does not need backward computation.
I0508 10:19:17.042667  8265 net.cpp:200] fc7 does not need backward computation.
I0508 10:19:17.042708  8265 net.cpp:200] drop6 does not need backward computation.
I0508 10:19:17.042747  8265 net.cpp:200] relu6 does not need backward computation.
I0508 10:19:17.042784  8265 net.cpp:200] fc6 does not need backward computation.
I0508 10:19:17.042837  8265 net.cpp:200] pool5 does not need backward computation.
I0508 10:19:17.042881  8265 net.cpp:200] relu5 does not need backward computation.
I0508 10:19:17.042928  8265 net.cpp:200] conv5 does not need backward computation.
I0508 10:19:17.042975  8265 net.cpp:200] relu4 does not need backward computation.
I0508 10:19:17.043012  8265 net.cpp:200] conv4 does not need backward computation.
I0508 10:19:17.043040  8265 net.cpp:200] relu3 does not need backward computation.
I0508 10:19:17.043072  8265 net.cpp:200] conv3 does not need backward computation.
I0508 10:19:17.043107  8265 net.cpp:200] norm2 does not need backward computation.
I0508 10:19:17.043145  8265 net.cpp:200] pool2 does not need backward computation.
I0508 10:19:17.043181  8265 net.cpp:200] relu2 does not need backward computation.
I0508 10:19:17.043215  8265 net.cpp:200] conv2 does not need backward computation.
I0508 10:19:17.043246  8265 net.cpp:200] norm1 does not need backward computation.
I0508 10:19:17.043314  8265 net.cpp:200] pool1 does not need backward computation.
I0508 10:19:17.043355  8265 net.cpp:200] relu1 does not need backward computation.
I0508 10:19:17.043397  8265 net.cpp:200] conv1 does not need backward computation.
I0508 10:19:17.043432  8265 net.cpp:200] data does not need backward computation.
I0508 10:19:17.043464  8265 net.cpp:242] This network produces output prob
I0508 10:19:17.043556  8265 net.cpp:255] Network initialization done.
CONSUMER: acquireFd 1828718358 (1 frames)
CONSUMER: releaseFd 1828718358 (1 frames)
CONSUMER: acquireFd 1828718358 (1 frames)
CONSUMER: releaseFd 1828718358 (1 frames)
CONSUMER: acquireFd 1828718358 (1 frames)
CONSUMER: releaseFd 1828718358 (1 frames)
CONSUMER: acquireFd 1828718358 (1 frames)
CONSUMER: releaseFd 1828718358 (1 frames)
CONSUMER: acquireFd 1828718358 (1 frames)
CONSUMER: releaseFd 1828718358 (1 frames)
CONSUMER: acquireFd 1828718358 (1 frames)
CONSUMER: releaseFd 1828718358 (1 frames)
CONSUMER: acquireFd 1828718358 (1 frames)
I0508 10:19:17.448457  8265 upgrade_proto.cpp:44] Attempting to upgrade input file specified using deprecated transformation parameters: /home/ubuntu/Work/caffe/caffe-master/models/bvlc_reference_caffenet/bvlc_reference_caffenet.caffemodel
I0508 10:19:17.448554  8265 upgrade_proto.cpp:47] Successfully upgraded file specified using deprecated data transformation parameters.
W0508 10:19:17.448609  8265 upgrade_proto.cpp:49] Note that future Caffe releases will only support transform_param messages for transformation fields.
I0508 10:19:17.448642  8265 upgrade_proto.cpp:53] Attempting to upgrade input file specified using deprecated V1LayerParameter: /home/ubuntu/Work/caffe/caffe-master/models/bvlc_reference_caffenet/bvlc_reference_caffenet.caffemodel
CONSUMER: acquireFd 1828718359 (2 frames)
CONSUMER: releaseFd 1828718358 (2 frames)
CONSUMER: acquireFd 1828718358 (2 frames)
CONSUMER: acquireFd 1828718360 (3 frames)
CONSUMER: releaseFd 1828718359 (3 frames)
CONSUMER: acquireFd 1828718359 (3 frames)
CONSUMER: releaseFd 1828718358 (3 frames)
CONSUMER: acquireFd 1828718358 (3 frames)
CONSUMER: releaseFd 1828718360 (3 frames)
CONSUMER: acquireFd 1828718360 (3 frames)
CONSUMER: releaseFd 1828718359 (3 frames)
CONSUMER: acquireFd 1828718359 (3 frames)
CONSUMER: releaseFd 1828718358 (3 frames)
CONSUMER: acquireFd 1828718358 (3 frames)
CONSUMER: releaseFd 1828718360 (3 frames)
CONSUMER: acquireFd 1828718360 (3 frames)
CONSUMER: releaseFd 1828718359 (3 frames)
CONSUMER: acquireFd 1828718359 (3 frames)
I0508 10:19:18.141923  8265 upgrade_proto.cpp:61] Successfully upgraded file specified using deprecated V1LayerParameter
CONSUMER: releaseFd 1828718358 (3 frames)
CONSUMER: acquireFd 1828718358 (3 frames)
CONSUMER: releaseFd 1828718360 (3 frames)
CONSUMER: acquireFd 1828718360 (3 frames)
I0508 10:19:18.286593  8265 net.cpp:744] Ignoring source layer loss
CONSUMER: releaseFd 1828718359 (3 frames)
CONSUMER: acquireFd 1828718359 (3 frames)
CONSUMER: releaseFd 1828718358 (3 frames)
CONSUMER: acquireFd 1828718363 (3 frames)
To classify 
W0508 10:19:18.392797  8265 net.hpp:41] DEPRECATED: ForwardPrefilled() will be removed in a future version. Use Forward().
F0508 10:19:18.434018  8265 pooling_layer.cu:212] Check failed: error == cudaSuccess (8 vs. 0)  invalid device function
*** Check failure stack trace: ***
Aborted

I share the full log. I hope that you can help me solve the problem as soon as possible.

Hi ??,

Confirmed we can run “11_camera_object_identificaton” successfully on TX1/R24.2.1
Please check your camera is workable and run the command on Jetson board, not ssh.

Thanks!

Thank you very much!
I don’t know how to check my camera is workable and how to run the command on Jetson board.
Because I did run the command on Jetson board. I don’t know what is SSH.
I hope you can give me some tutorial material about TX1 camera.
I can successfully run “09_camera_capture”.

Were you compiling or logged in to the Jetson over the network? If so, then you were probably using ssh and certain parts of the environment may behave differently compared to logging in directly to the Jetson without networking. Whatever compiling or setup or testing you do the results may be more consistent and informing if not using a network login.

Hi,

We will investigate and update. Thanks!

Hi,

Thanks for your question.

Please add sm_53 architecture(for TX1) into Makefile.config.

diff --git a/Makefile b/Makefile
index 4d32416..ad173f8 100644
--- a/Makefile
+++ b/Makefile
@@ -178,7 +178,7 @@ ifneq ($(CPU_ONLY), 1)
        LIBRARIES := cudart cublas curand
 endif
 
-LIBRARIES += glog gflags protobuf boost_system boost_filesystem m hdf5_hl hdf5
+LIBRARIES += glog gflags protobuf boost_system boost_filesystem m hdf5_serial_hl hdf5_serial
 
 # handle IO dependencies
 USE_LEVELDB ?= 1
diff --git a/Makefile.config.example b/Makefile.config.example
index d552b38..4db1583 100644
--- a/Makefile.config.example
+++ b/Makefile.config.example
@@ -2,7 +2,7 @@
 # Contributions simplifying and improving our build system are welcome!
 
 # cuDNN acceleration switch (uncomment to build with cuDNN).
-# USE_CUDNN := 1
+USE_CUDNN := 1
 
 # CPU-only switch (uncomment to build without GPU support).
 # CPU_ONLY := 1
@@ -38,7 +38,7 @@ CUDA_ARCH := -gencode arch=compute_20,code=sm_20 \
                -gencode arch=compute_30,code=sm_30 \
                -gencode arch=compute_35,code=sm_35 \
                -gencode arch=compute_50,code=sm_50 \
-               -gencode arch=compute_52,code=sm_52 \
+               -gencode arch=compute_53,code=sm_53 \
                -gencode arch=compute_60,code=sm_60 \
                -gencode arch=compute_61,code=sm_61 \
                -gencode arch=compute_61,code=compute_61
@@ -91,7 +91,7 @@ PYTHON_LIB := /usr/lib
 # WITH_PYTHON_LAYER := 1
 
 # Whatever else you find you need goes here.
-INCLUDE_DIRS := $(PYTHON_INCLUDE) /usr/local/include
+INCLUDE_DIRS := $(PYTHON_INCLUDE) /usr/local/include /usr/include/hdf5/serial/
 LIBRARY_DIRS := $(PYTHON_LIB) /usr/local/lib /usr/lib
 
 # If Homebrew is installed at a non standard location (for example your home directory) and you use it for general dependencies
cp Makefile.config.example Makefile.config

We have verified sample “11_camera_object_identificaton” can work properly with this change.
Please give it a try and let us know the results.
Thanks.

Thank you very much! I have success in running 11_camera_object_identification.

Hello! so i just ran this sample and this was the output, can anyone please let me know whats wrong?

[code]opencv_handler_open is called
opencv_set_config 0
Image width 1920
opencv_set_config 1
Image height 1080
opencv_set_config 2
CAFFE model file : 0x5d2c20
opencv_set_config 3
CAFFE trained file : 0x5d1d20
opencv_set_config 4
CAFFE mean file : 0x5d1dc0
opencv_set_config 5
CAFFE label file : 0x5d1e50
opencv_set_config 6
PRODUCER: Creating output stream
PRODUCER: Launching consumer thread
Failed to query video capabilities: Inappropriate ioctl for device
libv4l2_nvvidconv (0):(761) (INFO) : Allocating (10) OUTPUT PLANE BUFFERS Layout=1
libv4l2_nvvidconv (0):(771) (INFO) : Allocating (10) CAPTURE PLANE BUFFERS Layout=0
create vidoe converter return true
CONSUMER: Waiting until producer is connected…
PRODUCER: Starting repeat capture requests.
CONSUMER: Producer has connected; continuing.
SCF: Error BadValue: not available (in src/services/gyro/SensorsManager.cpp, function initSensors(), line 278)
SCF: Error BadValue: not available (in src/services/gyro/SensorsManager.cpp, function initSensors(), line 278)
SCF: Error BadValue: not available (in src/services/gyro/SensorsManager.cpp, function initSensors(), line 278)
CONSUMER: acquireFd 1828717891 (1 frames)
CONSUMER: acquireFd 1828717892 (2 frames)
CONSUMER: releaseFd 1828717891 (2 frames)
SCF: Error BadValue: not available (in src/services/gyro/SensorsManager.cpp, function initSensors(), line 278)
SCF: Error BadValue: motionMonitorThread failure (in src/services/gyro/MotionMonitorService.cpp, function motionMonitorThread(), line 343)
CONSUMER: releaseFd 1828717892 (1 frames)
CONSUMER: acquireFd 1828717896 (1 frames)
WARNING: Logging before InitGoogleLogging() is written to STDERR
I0816 20:47:59.798387 21599 net.cpp:51] Initializing net from parameters:
name: “CaffeNet”
state {
phase: TEST
level: 0
}
layer {
name: “data”
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”
}
I0816 20:47:59.799242 21599 layer_factory.hpp:77] Creating layer data
I0816 20:47:59.799314 21599 net.cpp:84] Creating Layer data
I0816 20:47:59.799347 21599 net.cpp:380] data -> data
CONSUMER: releaseFd 1828717896 (1 frames)
CONSUMER: acquireFd 1828717892 (1 frames)
CONSUMER: releaseFd 1828717892 (1 frames)
CONSUMER: acquireFd 1828717892 (1 frames)
CONSUMER: releaseFd 1828717892 (1 frames)
CONSUMER: acquireFd 1828717892 (1 frames)
CONSUMER: releaseFd 1828717892 (1 frames)
CONSUMER: acquireFd 1828717892 (1 frames)
CONSUMER: releaseFd 1828717892 (1 frames)
CONSUMER: acquireFd 1828717892 (1 frames)
CONSUMER: releaseFd 1828717892 (1 frames)
CONSUMER: acquireFd 1828717892 (1 frames)
CONSUMER: releaseFd 1828717892 (1 frames)
CONSUMER: acquireFd 1828717892 (1 frames)
CONSUMER: releaseFd 1828717892 (1 frames)
CONSUMER: acquireFd 1828717897 (1 frames)
CONSUMER: releaseFd 1828717897 (1 frames)
CONSUMER: acquireFd 1828717897 (1 frames)
CONSUMER: releaseFd 1828717897 (1 frames)
CONSUMER: acquireFd 1828717897 (1 frames)
CONSUMER: releaseFd 1828717897 (1 frames)
CONSUMER: acquireFd 1828717897 (1 frames)
CONSUMER: releaseFd 1828717897 (1 frames)
CONSUMER: acquireFd 1828717897 (1 frames)
CONSUMER: releaseFd 1828717897 (1 frames)
CONSUMER: acquireFd 1828717897 (1 frames)
CONSUMER: releaseFd 1828717897 (1 frames)
CONSUMER: acquireFd 1828717897 (1 frames)
CONSUMER: releaseFd 1828717897 (1 frames)
CONSUMER: acquireFd 1828717897 (1 frames)
CONSUMER: releaseFd 1828717897 (1 frames)
CONSUMER: acquireFd 1828717897 (1 frames)
CONSUMER: releaseFd 1828717897 (1 frames)
CONSUMER: acquireFd 1828717897 (1 frames)
CONSUMER: releaseFd 1828717897 (1 frames)
CONSUMER: acquireFd 1828717897 (1 frames)
CONSUMER: releaseFd 1828717897 (1 frames)
CONSUMER: acquireFd 1828717897 (1 frames)
CONSUMER: releaseFd 1828717897 (1 frames)
CONSUMER: acquireFd 1828717897 (1 frames)
CONSUMER: releaseFd 1828717897 (1 frames)
CONSUMER: acquireFd 1828717897 (1 frames)
CONSUMER: releaseFd 1828717897 (1 frames)
CONSUMER: acquireFd 1828717897 (1 frames)
CONSUMER: releaseFd 1828717897 (1 frames)
CONSUMER: acquireFd 1828717897 (1 frames)
CONSUMER: releaseFd 1828717897 (1 frames)
CONSUMER: acquireFd 1828717897 (1 frames)
CONSUMER: releaseFd 1828717897 (1 frames)
CONSUMER: acquireFd 1828717897 (1 frames)
CONSUMER: releaseFd 1828717897 (1 frames)
CONSUMER: acquireFd 1828717897 (1 frames)
CONSUMER: releaseFd 1828717897 (1 frames)
CONSUMER: acquireFd 1828717906 (1 frames)
CONSUMER: releaseFd 1828717906 (1 frames)
CONSUMER: acquireFd 1828717897 (1 frames)
CONSUMER: releaseFd 1828717897 (1 frames)
CONSUMER: acquireFd 1828717906 (1 frames)
CONSUMER: releaseFd 1828717906 (1 frames)
CONSUMER: acquireFd 1828717897 (1 frames)
CONSUMER: acquireFd 1828717906 (2 frames)
CONSUMER: releaseFd 1828717897 (2 frames)
CONSUMER: acquireFd 1828717907 (2 frames)
CONSUMER: releaseFd 1828717906 (2 frames)
CONSUMER: acquireFd 1828717897 (2 frames)
CONSUMER: acquireFd 1828717906 (3 frames)
CONSUMER: releaseFd 1828717907 (3 frames)
CONSUMER: acquireFd 1828717907 (3 frames)
CONSUMER: releaseFd 1828717897 (3 frames)
CONSUMER: acquireFd 1828717897 (3 frames)
CONSUMER: releaseFd 1828717906 (3 frames)
CONSUMER: acquireFd 1828717906 (3 frames)
CONSUMER: releaseFd 1828717907 (3 frames)
CONSUMER: acquireFd 1828717907 (3 frames)
CONSUMER: releaseFd 1828717897 (3 frames)
CONSUMER: acquireFd 1828717897 (3 frames)
CONSUMER: releaseFd 1828717906 (3 frames)
CONSUMER: acquireFd 1828717906 (3 frames)
CONSUMER: releaseFd 1828717907 (3 frames)
CONSUMER: acquireFd 1828717907 (3 frames)
CONSUMER: releaseFd 1828717897 (3 frames)
CONSUMER: acquireFd 1828717897 (3 frames)
CONSUMER: releaseFd 1828717906 (3 frames)
CONSUMER: acquireFd 1828717906 (3 frames)
CONSUMER: releaseFd 1828717907 (3 frames)
CONSUMER: acquireFd 1828717907 (3 frames)
CONSUMER: releaseFd 1828717897 (3 frames)
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I0816 20:48:09.327061 21599 net.cpp:122] Setting up data
I0816 20:48:09.327183 21599 net.cpp:129] Top shape: 10 3 227 227 (1545870)
I0816 20:48:09.327272 21599 net.cpp:137] Memory required for data: 6183480
I0816 20:48:09.327337 21599 layer_factory.hpp:77] Creating layer conv1
I0816 20:48:09.327443 21599 net.cpp:84] Creating Layer conv1
I0816 20:48:09.327498 21599 net.cpp:406] conv1 <- data
I0816 20:48:09.327574 21599 net.cpp:380] conv1 -> conv1
CONSUMER: releaseFd 1828717906 (3 frames)
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I0816 20:48:10.115252 21599 net.cpp:122] Setting up conv1
I0816 20:48:10.115320 21599 net.cpp:129] Top shape: 10 96 55 55 (2904000)
I0816 20:48:10.115347 21599 net.cpp:137] Memory required for data: 17799480
I0816 20:48:10.115435 21599 layer_factory.hpp:77] Creating layer relu1
I0816 20:48:10.115468 21599 net.cpp:84] Creating Layer relu1
I0816 20:48:10.115484 21599 net.cpp:406] relu1 <- conv1
I0816 20:48:10.115504 21599 net.cpp:367] relu1 -> conv1 (in-place)
I0816 20:48:10.116950 21599 net.cpp:122] Setting up relu1
I0816 20:48:10.116986 21599 net.cpp:129] Top shape: 10 96 55 55 (2904000)
I0816 20:48:10.117007 21599 net.cpp:137] Memory required for data: 29415480
I0816 20:48:10.117024 21599 layer_factory.hpp:77] Creating layer pool1
I0816 20:48:10.117048 21599 net.cpp:84] Creating Layer pool1
I0816 20:48:10.117063 21599 net.cpp:406] pool1 <- conv1
I0816 20:48:10.117084 21599 net.cpp:380] pool1 -> pool1
I0816 20:48:10.117365 21599 net.cpp:122] Setting up pool1
I0816 20:48:10.117389 21599 net.cpp:129] Top shape: 10 96 27 27 (699840)
I0816 20:48:10.117408 21599 net.cpp:137] Memory required for data: 32214840
I0816 20:48:10.117421 21599 layer_factory.hpp:77] Creating layer norm1
I0816 20:48:10.117470 21599 net.cpp:84] Creating Layer norm1
I0816 20:48:10.117486 21599 net.cpp:406] norm1 <- pool1
I0816 20:48:10.117506 21599 net.cpp:380] norm1 -> norm1
CONSUMER: releaseFd 1828717897 (3 frames)
I0816 20:48:10.122020 21599 net.cpp:122] Setting up norm1
I0816 20:48:10.122081 21599 net.cpp:129] Top shape: 10 96 27 27 (699840)
I0816 20:48:10.122112 21599 net.cpp:137] Memory required for data: 35014200
I0816 20:48:10.122130 21599 layer_factory.hpp:77] Creating layer conv2
I0816 20:48:10.122169 21599 net.cpp:84] Creating Layer conv2
I0816 20:48:10.122187 21599 net.cpp:406] conv2 <- norm1
I0816 20:48:10.122212 21599 net.cpp:380] conv2 -> conv2
CONSUMER: acquireFd 1828717999 (3 frames)
I0816 20:48:10.136355 21599 net.cpp:122] Setting up conv2
I0816 20:48:10.136417 21599 net.cpp:129] Top shape: 10 256 27 27 (1866240)
I0816 20:48:10.136447 21599 net.cpp:137] Memory required for data: 42479160
I0816 20:48:10.136487 21599 layer_factory.hpp:77] Creating layer relu2
I0816 20:48:10.136528 21599 net.cpp:84] Creating Layer relu2
I0816 20:48:10.136548 21599 net.cpp:406] relu2 <- conv2
I0816 20:48:10.136571 21599 net.cpp:367] relu2 -> conv2 (in-place)
I0816 20:48:10.138237 21599 net.cpp:122] Setting up relu2
I0816 20:48:10.138284 21599 net.cpp:129] Top shape: 10 256 27 27 (1866240)
I0816 20:48:10.138316 21599 net.cpp:137] Memory required for data: 49944120
I0816 20:48:10.138340 21599 layer_factory.hpp:77] Creating layer pool2
I0816 20:48:10.138370 21599 net.cpp:84] Creating Layer pool2
I0816 20:48:10.138387 21599 net.cpp:406] pool2 <- conv2
I0816 20:48:10.138411 21599 net.cpp:380] pool2 -> pool2
I0816 20:48:10.138723 21599 net.cpp:122] Setting up pool2
I0816 20:48:10.138754 21599 net.cpp:129] Top shape: 10 256 13 13 (432640)
I0816 20:48:10.138773 21599 net.cpp:137] Memory required for data: 51674680
I0816 20:48:10.138789 21599 layer_factory.hpp:77] Creating layer norm2
I0816 20:48:10.138824 21599 net.cpp:84] Creating Layer norm2
I0816 20:48:10.138841 21599 net.cpp:406] norm2 <- pool2
I0816 20:48:10.138864 21599 net.cpp:380] norm2 -> norm2
I0816 20:48:10.140604 21599 net.cpp:122] Setting up norm2
I0816 20:48:10.140650 21599 net.cpp:129] Top shape: 10 256 13 13 (432640)
I0816 20:48:10.140672 21599 net.cpp:137] Memory required for data: 53405240
I0816 20:48:10.140688 21599 layer_factory.hpp:77] Creating layer conv3
I0816 20:48:10.140723 21599 net.cpp:84] Creating Layer conv3
I0816 20:48:10.140740 21599 net.cpp:406] conv3 <- norm2
I0816 20:48:10.140764 21599 net.cpp:380] conv3 -> conv3
I0816 20:48:10.152251 21599 net.cpp:122] Setting up conv3
I0816 20:48:10.152304 21599 net.cpp:129] Top shape: 10 384 13 13 (648960)
I0816 20:48:10.152330 21599 net.cpp:137] Memory required for data: 56001080
I0816 20:48:10.152371 21599 layer_factory.hpp:77] Creating layer relu3
I0816 20:48:10.152405 21599 net.cpp:84] Creating Layer relu3
I0816 20:48:10.152422 21599 net.cpp:406] relu3 <- conv3
I0816 20:48:10.152442 21599 net.cpp:367] relu3 -> conv3 (in-place)
I0816 20:48:10.154770 21599 net.cpp:122] Setting up relu3
I0816 20:48:10.154824 21599 net.cpp:129] Top shape: 10 384 13 13 (648960)
I0816 20:48:10.154855 21599 net.cpp:137] Memory required for data: 58596920
I0816 20:48:10.154876 21599 layer_factory.hpp:77] Creating layer conv4
I0816 20:48:10.154922 21599 net.cpp:84] Creating Layer conv4
I0816 20:48:10.154947 21599 net.cpp:406] conv4 <- conv3
I0816 20:48:10.154973 21599 net.cpp:380] conv4 -> conv4
I0816 20:48:10.170567 21599 net.cpp:122] Setting up conv4
I0816 20:48:10.170622 21599 net.cpp:129] Top shape: 10 384 13 13 (648960)
I0816 20:48:10.170647 21599 net.cpp:137] Memory required for data: 61192760
I0816 20:48:10.170680 21599 layer_factory.hpp:77] Creating layer relu4
I0816 20:48:10.170707 21599 net.cpp:84] Creating Layer relu4
I0816 20:48:10.170724 21599 net.cpp:406] relu4 <- conv4
I0816 20:48:10.170747 21599 net.cpp:367] relu4 -> conv4 (in-place)
I0816 20:48:10.172720 21599 net.cpp:122] Setting up relu4
I0816 20:48:10.172761 21599 net.cpp:129] Top shape: 10 384 13 13 (648960)
I0816 20:48:10.172785 21599 net.cpp:137] Memory required for data: 63788600
I0816 20:48:10.172802 21599 layer_factory.hpp:77] Creating layer conv5
I0816 20:48:10.172838 21599 net.cpp:84] Creating Layer conv5
I0816 20:48:10.172855 21599 net.cpp:406] conv5 <- conv4
I0816 20:48:10.172881 21599 net.cpp:380] conv5 -> conv5
CONSUMER: releaseFd 1828717906 (3 frames)
CONSUMER: acquireFd 1828717906 (3 frames)
I0816 20:48:10.194640 21599 net.cpp:122] Setting up conv5
I0816 20:48:10.194697 21599 net.cpp:129] Top shape: 10 256 13 13 (432640)
I0816 20:48:10.194725 21599 net.cpp:137] Memory required for data: 65519160
I0816 20:48:10.194775 21599 layer_factory.hpp:77] Creating layer relu5
I0816 20:48:10.194810 21599 net.cpp:84] Creating Layer relu5
I0816 20:48:10.194831 21599 net.cpp:406] relu5 <- conv5
I0816 20:48:10.194861 21599 net.cpp:367] relu5 -> conv5 (in-place)
I0816 20:48:10.197455 21599 net.cpp:122] Setting up relu5
I0816 20:48:10.197510 21599 net.cpp:129] Top shape: 10 256 13 13 (432640)
I0816 20:48:10.197536 21599 net.cpp:137] Memory required for data: 67249720
I0816 20:48:10.197556 21599 layer_factory.hpp:77] Creating layer pool5
I0816 20:48:10.197587 21599 net.cpp:84] Creating Layer pool5
I0816 20:48:10.197607 21599 net.cpp:406] pool5 <- conv5
I0816 20:48:10.197628 21599 net.cpp:380] pool5 -> pool5
I0816 20:48:10.198024 21599 net.cpp:122] Setting up pool5
I0816 20:48:10.198057 21599 net.cpp:129] Top shape: 10 256 6 6 (92160)
I0816 20:48:10.198081 21599 net.cpp:137] Memory required for data: 67618360
I0816 20:48:10.198096 21599 layer_factory.hpp:77] Creating layer fc6
I0816 20:48:10.198130 21599 net.cpp:84] Creating Layer fc6
I0816 20:48:10.198148 21599 net.cpp:406] fc6 <- pool5
I0816 20:48:10.198168 21599 net.cpp:380] fc6 -> fc6
CONSUMER: releaseFd 1828717907 (3 frames)
CONSUMER: acquireFd 1828717907 (3 frames)
CONSUMER: releaseFd 1828717999 (3 frames)
CONSUMER: acquireFd 1828717999 (3 frames)
CONSUMER: releaseFd 1828717906 (3 frames)
I0816 20:48:10.340412 21599 net.cpp:122] Setting up fc6
I0816 20:48:10.340469 21599 net.cpp:129] Top shape: 10 4096 (40960)
I0816 20:48:10.340495 21599 net.cpp:137] Memory required for data: 67782200
I0816 20:48:10.340528 21599 layer_factory.hpp:77] Creating layer relu6
I0816 20:48:10.340557 21599 net.cpp:84] Creating Layer relu6
I0816 20:48:10.340576 21599 net.cpp:406] relu6 <- fc6
I0816 20:48:10.340605 21599 net.cpp:367] relu6 -> fc6 (in-place)
I0816 20:48:10.351158 21599 net.cpp:122] Setting up relu6
I0816 20:48:10.351210 21599 net.cpp:129] Top shape: 10 4096 (40960)
I0816 20:48:10.351235 21599 net.cpp:137] Memory required for data: 67946040
I0816 20:48:10.351251 21599 layer_factory.hpp:77] Creating layer drop6
I0816 20:48:10.351300 21599 net.cpp:84] Creating Layer drop6
I0816 20:48:10.351331 21599 net.cpp:406] drop6 <- fc6
I0816 20:48:10.351362 21599 net.cpp:367] drop6 -> fc6 (in-place)
I0816 20:48:10.351738 21599 net.cpp:122] Setting up drop6
I0816 20:48:10.351789 21599 net.cpp:129] Top shape: 10 4096 (40960)
I0816 20:48:10.351817 21599 net.cpp:137] Memory required for data: 68109880
I0816 20:48:10.351840 21599 layer_factory.hpp:77] Creating layer fc7
I0816 20:48:10.351879 21599 net.cpp:84] Creating Layer fc7
I0816 20:48:10.351907 21599 net.cpp:406] fc7 <- fc6
I0816 20:48:10.351943 21599 net.cpp:380] fc7 -> fc7
CONSUMER: acquireFd 1828717906 (3 frames)
CONSUMER: releaseFd 1828717907 (3 frames)
I0816 20:48:10.414032 21599 net.cpp:122] Setting up fc7
I0816 20:48:10.414088 21599 net.cpp:129] Top shape: 10 4096 (40960)
I0816 20:48:10.414115 21599 net.cpp:137] Memory required for data: 68273720
I0816 20:48:10.414150 21599 layer_factory.hpp:77] Creating layer relu7
I0816 20:48:10.414181 21599 net.cpp:84] Creating Layer relu7
I0816 20:48:10.414199 21599 net.cpp:406] relu7 <- fc7
I0816 20:48:10.414228 21599 net.cpp:367] relu7 -> fc7 (in-place)
CONSUMER: acquireFd 1828717907 (3 frames)
I0816 20:48:10.422852 21599 net.cpp:122] Setting up relu7
I0816 20:48:10.422912 21599 net.cpp:129] Top shape: 10 4096 (40960)
I0816 20:48:10.422937 21599 net.cpp:137] Memory required for data: 68437560
I0816 20:48:10.422956 21599 layer_factory.hpp:77] Creating layer drop7
I0816 20:48:10.422989 21599 net.cpp:84] Creating Layer drop7
I0816 20:48:10.423010 21599 net.cpp:406] drop7 <- fc7
I0816 20:48:10.423053 21599 net.cpp:367] drop7 -> fc7 (in-place)
I0816 20:48:10.423482 21599 net.cpp:122] Setting up drop7
I0816 20:48:10.423537 21599 net.cpp:129] Top shape: 10 4096 (40960)
I0816 20:48:10.423563 21599 net.cpp:137] Memory required for data: 68601400
I0816 20:48:10.423579 21599 layer_factory.hpp:77] Creating layer fc8
I0816 20:48:10.423606 21599 net.cpp:84] Creating Layer fc8
I0816 20:48:10.423643 21599 net.cpp:406] fc8 <- fc7
I0816 20:48:10.423671 21599 net.cpp:380] fc8 -> fc8
CONSUMER: releaseFd 1828717999 (3 frames)
I0816 20:48:10.445107 21599 net.cpp:122] Setting up fc8
I0816 20:48:10.445161 21599 net.cpp:129] Top shape: 10 1000 (10000)
I0816 20:48:10.445188 21599 net.cpp:137] Memory required for data: 68641400
I0816 20:48:10.445221 21599 layer_factory.hpp:77] Creating layer prob
I0816 20:48:10.445318 21599 net.cpp:84] Creating Layer prob
I0816 20:48:10.445339 21599 net.cpp:406] prob <- fc8
I0816 20:48:10.445497 21599 net.cpp:380] prob -> prob
CONSUMER: acquireFd 1828718202 (3 frames)
I0816 20:48:10.453233 21599 net.cpp:122] Setting up prob
I0816 20:48:10.453372 21599 net.cpp:129] Top shape: 10 1000 (10000)
I0816 20:48:10.453400 21599 net.cpp:137] Memory required for data: 68681400
I0816 20:48:10.453421 21599 net.cpp:200] prob does not need backward computation.
I0816 20:48:10.453461 21599 net.cpp:200] fc8 does not need backward computation.
I0816 20:48:10.453477 21599 net.cpp:200] drop7 does not need backward computation.
I0816 20:48:10.453492 21599 net.cpp:200] relu7 does not need backward computation.
I0816 20:48:10.453505 21599 net.cpp:200] fc7 does not need backward computation.
I0816 20:48:10.453519 21599 net.cpp:200] drop6 does not need backward computation.
I0816 20:48:10.453533 21599 net.cpp:200] relu6 does not need backward computation.
I0816 20:48:10.453547 21599 net.cpp:200] fc6 does not need backward computation.
I0816 20:48:10.453563 21599 net.cpp:200] pool5 does not need backward computation.
I0816 20:48:10.453578 21599 net.cpp:200] relu5 does not need backward computation.
I0816 20:48:10.453594 21599 net.cpp:200] conv5 does not need backward computation.
I0816 20:48:10.453609 21599 net.cpp:200] relu4 does not need backward computation.
I0816 20:48:10.453625 21599 net.cpp:200] conv4 does not need backward computation.
I0816 20:48:10.453687 21599 net.cpp:200] relu3 does not need backward computation.
I0816 20:48:10.453711 21599 net.cpp:200] conv3 does not need backward computation.
I0816 20:48:10.453728 21599 net.cpp:200] norm2 does not need backward computation.
I0816 20:48:10.453740 21599 net.cpp:200] pool2 does not need backward computation.
I0816 20:48:10.453794 21599 net.cpp:200] relu2 does not need backward computation.
I0816 20:48:10.453814 21599 net.cpp:200] conv2 does not need backward computation.
I0816 20:48:10.453825 21599 net.cpp:200] norm1 does not need backward computation.
I0816 20:48:10.453836 21599 net.cpp:200] pool1 does not need backward computation.
I0816 20:48:10.453891 21599 net.cpp:200] relu1 does not need backward computation.
I0816 20:48:10.453903 21599 net.cpp:200] conv1 does not need backward computation.
I0816 20:48:10.453913 21599 net.cpp:200] data does not need backward computation.
I0816 20:48:10.453923 21599 net.cpp:242] This network produces output prob
I0816 20:48:10.454028 21599 net.cpp:255] Network initialization done.
CONSUMER: releaseFd 1828717906 (3 frames)
CONSUMER: acquireFd 1828717906 (3 frames)
CONSUMER: releaseFd 1828717907 (3 frames)
CONSUMER: acquireFd 1828717907 (3 frames)
CONSUMER: releaseFd 1828718202 (3 frames)
CONSUMER: acquireFd 1828718202 (3 frames)
CONSUMER: releaseFd 1828717906 (3 frames)
CONSUMER: acquireFd 1828717906 (3 frames)
CONSUMER: releaseFd 1828717907 (3 frames)
CONSUMER: acquireFd 1828717907 (3 frames)
CONSUMER: releaseFd 1828718202 (3 frames)
CONSUMER: acquireFd 1828718202 (3 frames)
CONSUMER: releaseFd 1828717906 (3 frames)
CONSUMER: acquireFd 1828717906 (3 frames)
CONSUMER: releaseFd 1828717907 (3 frames)
CONSUMER: acquireFd 1828717907 (3 frames)
CONSUMER: releaseFd 1828718202 (3 frames)
CONSUMER: acquireFd 1828718202 (3 frames)
CONSUMER: releaseFd 1828717906 (3 frames)
CONSUMER: acquireFd 1828717906 (3 frames)
CONSUMER: releaseFd 1828717907 (3 frames)
CONSUMER: acquireFd 1828717907 (3 frames)
CONSUMER: releaseFd 1828718202 (3 frames)
CONSUMER: acquireFd 1828718202 (3 frames)
CONSUMER: releaseFd 1828717906 (3 frames)
CONSUMER: acquireFd 1828717906 (3 frames)
CONSUMER: releaseFd 1828717907 (3 frames)
CONSUMER: acquireFd 1828717907 (3 frames)
CONSUMER: releaseFd 1828718202 (3 frames)
CONSUMER: acquireFd 1828718202 (3 frames)
CONSUMER: releaseFd 1828717906 (3 frames)
CONSUMER: acquireFd 1828717906 (3 frames)
CONSUMER: releaseFd 1828717907 (3 frames)
CONSUMER: acquireFd 1828717907 (3 frames)
CONSUMER: releaseFd 1828718202 (3 frames)
CONSUMER: acquireFd 1828718202 (3 frames)
CONSUMER: releaseFd 1828717906 (3 frames)
CONSUMER: acquireFd 1828717906 (3 frames)
CONSUMER: releaseFd 1828717907 (3 frames)
I0816 20:48:11.454371 21599 upgrade_proto.cpp:44] Attempting to upgrade input file specified using deprecated transformation parameters: /home/ubuntu/Work/caffe/caffe-master/models/bvlc_reference_caffenet/bvlc_reference_caffenet.caffemodel
I0816 20:48:11.454444 21599 upgrade_proto.cpp:47] Successfully upgraded file specified using deprecated data transformation parameters.
W0816 20:48:11.454484 21599 upgrade_proto.cpp:49] Note that future Caffe releases will only support transform_param messages for transformation fields.
I0816 20:48:11.454500 21599 upgrade_proto.cpp:53] Attempting to upgrade input file specified using deprecated V1LayerParameter: /home/ubuntu/Work/caffe/caffe-master/models/bvlc_reference_caffenet/bvlc_reference_caffenet.caffemodel
CONSUMER: acquireFd 1828717907 (3 frames)
CONSUMER: releaseFd 1828718202 (3 frames)
CONSUMER: acquireFd 1828718202 (3 frames)
CONSUMER: releaseFd 1828717906 (3 frames)
CONSUMER: acquireFd 1828717906 (3 frames)
CONSUMER: releaseFd 1828717907 (3 frames)
CONSUMER: acquireFd 1828717907 (3 frames)
CONSUMER: releaseFd 1828718202 (3 frames)
CONSUMER: acquireFd 1828718202 (3 frames)
CONSUMER: releaseFd 1828717906 (3 frames)
CONSUMER: acquireFd 1828717906 (3 frames)
CONSUMER: releaseFd 1828717907 (3 frames)
CONSUMER: acquireFd 1828717907 (3 frames)
CONSUMER: releaseFd 1828718202 (3 frames)
CONSUMER: acquireFd 1828718202 (3 frames)
CONSUMER: releaseFd 1828717906 (3 frames)
CONSUMER: acquireFd 1828717906 (3 frames)
CONSUMER: releaseFd 1828717907 (3 frames)
CONSUMER: acquireFd 1828717907 (3 frames)
I0816 20:48:11.965185 21599 upgrade_proto.cpp:61] Successfully upgraded file specified using deprecated V1LayerParameter
CONSUMER: releaseFd 1828718202 (3 frames)
CONSUMER: acquireFd 1828718202 (3 frames)
I0816 20:48:12.082156 21599 net.cpp:744] Ignoring source layer loss
CONSUMER: releaseFd 1828717906 (3 frames)
To classify
CONSUMER: acquireFd 1828717906 (3 frames)
W0816 20:48:12.148085 21599 net.hpp:41] DEPRECATED: ForwardPrefilled() will be removed in a future version. Use Forward().
CONSUMER: releaseFd 1828717907 (3 frames)
CONSUMER: acquireFd 1828717888 (3 frames)
CONSUMER: releaseFd 1828718202 (3 frames)
CONSUMER: acquireFd 1828718202 (3 frames)
CONSUMER: releaseFd 1828717906 (3 frames)
CONSUMER: acquireFd 1828717906 (3 frames)
0.2795 - “n04592741 wing”
0.2348 - “n02788148 bannister, banister, balustrade, balusters, handrail”
0.0375 - “n11879895 rapeseed”
0.0262 - “n03337140 file, file cabinet, filing cabinet”
0.0244 - “n04501370 turnstile”
To classify
CONSUMER: releaseFd 1828717888 (3 frames)
CONSUMER: acquireFd 1828717888 (3 frames)
0.1877 - “n04501370 turnstile”
0.0637 - “n02788148 bannister, banister, balustrade, balusters, handrail”
0.0513 - “n03924679 photocopier”
0.0437 - “n02747177 ashcan, trash can, garbage can, wastebin, ash bin, ash-bin, ashbin, dustbin, trash barrel, trash bin”
0.0386 - “n04554684 washer, automatic washer, washing machine”
To classify
CONSUMER: releaseFd 1828718202 (3 frames)
CONSUMER: acquireFd 1828718202 (3 frames)
0.1874 - “n04501370 turnstile”
0.0649 - “n02788148 bannister, banister, balustrade, balusters, handrail”
0.0480 - “n03924679 photocopier”
0.0433 - “n02747177 ashcan, trash can, garbage can, wastebin, ash bin, ash-bin, ashbin, dustbin, trash barrel, trash bin”
0.0374 - “n04554684 washer, automatic washer, washing machine”
To classify
CONSUMER: releaseFd 1828717906 (3 frames)
CONSUMER: acquireFd 1828717906 (3 frames)
0.1827 - “n04501370 turnstile”
0.0645 - “n02788148 bannister, banister, balustrade, balusters, handrail”
0.0476 - “n03924679 photocopier”
0.0439 - “n02747177 ashcan, trash can, garbage can, wastebin, ash bin, ash-bin, ashbin, dustbin, trash barrel, trash bin”
0.0368 - “n04554684 washer, automatic washer, washing machine”
To classify
CONSUMER: releaseFd 1828717888 (3 frames)
CONSUMER: acquireFd 1828717888 (3 frames)
0.1726 - “n04501370 turnstile”
0.0642 - “n02788148 bannister, banister, balustrade, balusters, handrail”
0.0457 - “n02747177 ashcan, trash can, garbage can, wastebin, ash bin, ash-bin, ashbin, dustbin, trash barrel, trash bin”
0.0447 - “n03924679 photocopier”
0.0367 - “n04554684 washer, automatic washer, washing machine”
CONSUMER: releaseFd 1828718202 (3 frames)
To classify
CONSUMER: acquireFd 1828718202 (3 frames)
0.1640 - “n04501370 turnstile”
0.0655 - “n02788148 bannister, banister, balustrade, balusters, handrail”
0.0473 - “n02747177 ashcan, trash can, garbage can, wastebin, ash bin, ash-bin, ashbin, dustbin, trash barrel, trash bin”
0.0472 - “n03924679 photocopier”
0.0382 - “n04554684 washer, automatic washer, washing machine”
To classify
CONSUMER: releaseFd 1828717906 (3 frames)
CONSUMER: acquireFd 1828717906 (3 frames)
0.1747 - “n04501370 turnstile”
0.0639 - “n02788148 bannister, banister, balustrade, balusters, handrail”
0.0488 - “n03924679 photocopier”
0.0454 - “n02747177 ashcan, trash can, garbage can, wastebin, ash bin, ash-bin, ashbin, dustbin, trash barrel, trash bin”
0.0399 - “n04554684 washer, automatic washer, washing machine”
To classify
CONSUMER: releaseFd 1828717888 (3 frames)
CONSUMER: acquireFd 1828717888 (3 frames)
0.1722 - “n04501370 turnstile”
0.0619 - “n02788148 bannister, banister, balustrade, balusters, handrail”
0.0471 - “n03924679 photocopier”
0.0451 - “n02747177 ashcan, trash can, garbage can, wastebin, ash bin, ash-bin, ashbin, dustbin, trash barrel, trash bin”
0.0397 - “n04554684 washer, automatic washer, washing machine”
CONSUMER: releaseFd 1828718202 (3 frames)
To classify
CONSUMER: acquireFd 1828718202 (3 frames)
0.1762 - “n04501370 turnstile”
0.0656 - “n02788148 bannister, banister, balustrade, balusters, handrail”
0.0471 - “n03924679 photocopier”
0.0454 - “n02747177 ashcan, trash can, garbage can, wastebin, ash bin, ash-bin, ashbin, dustbin, trash barrel, trash bin”
0.0394 - “n04554684 washer, automatic washer, washing machine”
To classify
CONSUMER: releaseFd 1828717906 (3 frames)
CONSUMER: acquireFd 1828717906 (3 frames)
0.1758 - “n04501370 turnstile”
0.0652 - “n02788148 bannister, banister, balustrade, balusters, handrail”
0.0484 - “n03924679 photocopier”
0.0446 - “n02747177 ashcan, trash can, garbage can, wastebin, ash bin, ash-bin, ashbin, dustbin, trash barrel, trash bin”
0.0426 - “n04554684 washer, automatic washer, washing machine”
To classify
CONSUMER: releaseFd 1828717888 (3 frames)
CONSUMER: acquireFd 1828717888 (3 frames)
0.1760 - “n04501370 turnstile”
0.0664 - “n02788148 bannister, banister, balustrade, balusters, handrail”
0.0470 - “n03924679 photocopier”
0.0442 - “n02747177 ashcan, trash can, garbage can, wastebin, ash bin, ash-bin, ashbin, dustbin, trash barrel, trash bin”
0.0414 - “n04554684 washer, automatic washer, washing machine”
CONSUMER: releaseFd 1828718202 (3 frames)
To classify
CONSUMER: acquireFd 1828718202 (3 frames)
0.1743 - “n04501370 turnstile”
0.0631 - “n02788148 bannister, banister, balustrade, balusters, handrail”
0.0470 - “n03924679 photocopier”
0.0453 - “n02747177 ashcan, trash can, garbage can, wastebin, ash bin, ash-bin, ashbin, dustbin, trash barrel, trash bin”
0.0420 - “n04554684 washer, automatic washer, washing machine”
To classify
CONSUMER: releaseFd 1828717906 (3 frames)
CONSUMER: acquireFd 1828717906 (3 frames)
0.1766 - “n04501370 turnstile”
0.0642 - “n02788148 bannister, banister, balustrade, balusters, handrail”
0.0464 - “n03924679 photocopier”
0.0449 - “n02747177 ashcan, trash can, garbage can, wastebin, ash bin, ash-bin, ashbin, dustbin, trash barrel, trash bin”
0.0402 - “n04554684 washer, automatic washer, washing machine”
CONSUMER: releaseFd 1828717888 (3 frames)
To classify
CONSUMER: acquireFd 1828717888 (3 frames)
0.1740 - “n04501370 turnstile”
0.0646 - “n02788148 bannister, banister, balustrade, balusters, handrail”
0.0479 - “n03924679 photocopier”
0.0450 - “n02747177 ashcan, trash can, garbage can, wastebin, ash bin, ash-bin, ashbin, dustbin, trash barrel, trash bin”
0.0395 - “n04554684 washer, automatic washer, washing machine”
To classify
CONSUMER: releaseFd 1828718202 (3 frames)
CONSUMER: acquireFd 1828718202 (3 frames)
0.1694 - “n04501370 turnstile”
0.0650 - “n02788148 bannister, banister, balustrade, balusters, handrail”
0.0487 - “n03924679 photocopier”
0.0446 - “n02747177 ashcan, trash can, garbage can, wastebin, ash bin, ash-bin, ashbin, dustbin, trash barrel, trash bin”
0.0398 - “n04554684 washer, automatic washer, washing machine”
CONSUMER: releaseFd 1828717906 (3 frames)
To classify
CONSUMER: acquireFd 1828717906 (3 frames)
0.1776 - “n04501370 turnstile”
0.0647 - “n02788148 bannister, banister, balustrade, balusters, handrail”
0.0501 - “n03924679 photocopier”
0.0456 - “n02747177 ashcan, trash can, garbage can, wastebin, ash bin, ash-bin, ashbin, dustbin, trash barrel, trash bin”
0.0412 - “n04554684 washer, automatic washer, washing machine”
To classify
CONSUMER: releaseFd 1828717888 (3 frames)
CONSUMER: acquireFd 1828717888 (3 frames)
0.1740 - “n04501370 turnstile”
0.0643 - “n02788148 bannister, banister, balustrade, balusters, handrail”
0.0501 - “n03924679 photocopier”
0.0465 - “n02747177 ashcan, trash can, garbage can, wastebin, ash bin, ash-bin, ashbin, dustbin, trash barrel, trash bin”
0.0409 - “n04554684 washer, automatic washer, washing machine”
To classify
CONSUMER: releaseFd 1828718202 (3 frames)
CONSUMER: acquireFd 1828718202 (3 frames)
0.1728 - “n04501370 turnstile”
0.0643 - “n02788148 bannister, banister, balustrade, balusters, handrail”
0.0499 - “n03924679 photocopier”
0.0463 - “n02747177 ashcan, trash can, garbage can, wastebin, ash bin, ash-bin, ashbin, dustbin, trash barrel, trash bin”
0.0412 - “n04554684 washer, automatic washer, washing machine”
To classify
CONSUMER: releaseFd 1828717906 (3 frames)
0.1692 - “n04501370 turnstile”
0.0636 - “n02788148 bannister, banister, balustrade, balusters, handrail”
0.0487 - “n03924679 photocopier”
0.0476 - “n02747177 ashcan, trash can, garbage can, wastebin, ash bin, ash-bin, ashbin, dustbin, trash barrel, trash bin”
0.0406 - “n04554684 washer, automatic washer, washing machine”
CONSUMER: acquireFd 1828717906 (3 frames)
To classify
CONSUMER: releaseFd 1828717888 (3 frames)
CONSUMER: acquireFd 1828717888 (3 frames)
0.1626 - “n04501370 turnstile”
0.0625 - “n02788148 bannister, banister, balustrade, balusters, handrail”
0.0474 - “n02747177 ashcan, trash can, garbage can, wastebin, ash bin, ash-bin, ashbin, dustbin, trash barrel, trash bin”
0.0453 - “n03924679 photocopier”
0.0393 - “n04554684 washer, automatic washer, washing machine”
CONSUMER: releaseFd 1828718202 (3 frames)
To classify
CONSUMER: acquireFd 1828718202 (3 frames)
0.1603 - “n04501370 turnstile”
0.0613 - “n02788148 bannister, banister, balustrade, balusters, handrail”
0.0482 - “n02747177 ashcan, trash can, garbage can, wastebin, ash bin, ash-bin, ashbin, dustbin, trash barrel, trash bin”
0.0480 - “n03924679 photocopier”
0.0390 - “n04554684 washer, automatic washer, washing machine”
CONSUMER: releaseFd 1828717906 (3 frames)
To classify
CONSUMER: acquireFd 1828717906 (3 frames)
0.1614 - “n04501370 turnstile”
0.0621 - “n02788148 bannister, banister, balustrade, balusters, handrail”
0.0482 - “n03924679 photocopier”
0.0480 - “n02747177 ashcan, trash can, garbage can, wastebin, ash bin, ash-bin, ashbin, dustbin, trash barrel, trash bin”
0.0377 - “n04554684 washer, automatic washer, washing machine”
To classify
CONSUMER: releaseFd 1828717888 (3 frames)
CONSUMER: acquireFd 1828717888 (3 frames)
0.1635 - “n04501370 turnstile”
0.0625 - “n02788148 bannister, banister, balustrade, balusters, handrail”
0.0479 - “n03924679 photocopier”
0.0477 - “n02747177 ashcan, trash can, garbage can, wastebin, ash bin, ash-bin, ashbin, dustbin, trash barrel, trash bin”
0.0372 - “n04554684 washer, automatic washer, washing machine”
To classify
CONSUMER: releaseFd 1828718202 (3 frames)
0.1636 - “n04501370 turnstile”
0.0624 - “n02788148 bannister, banister, balustrade, balusters, handrail”
0.0471 - “n03924679 photocopier”
0.0467 - “n02747177 ashcan, trash can, garbage can, wastebin, ash bin, ash-bin, ashbin, dustbin, trash barrel, trash bin”
0.0375 - “n04554684 washer, automatic washer, washing machine”
CONSUMER: acquireFd 1828718202 (3 frames)
To classify
CONSUMER: releaseFd 1828717906 (3 frames)
CONSUMER: acquireFd 1828717906 (3 frames)
0.1576 - “n04501370 turnstile”
0.0631 - “n02788148 bannister, banister, balustrade, balusters, handrail”
0.0491 - “n03924679 photocopier”
0.0455 - “n02747177 ashcan, trash can, garbage can, wastebin, ash bin, ash-bin, ashbin, dustbin, trash barrel, trash bin”
0.0380 - “n04554684 washer, automatic washer, washing machine”
To classify
CONSUMER: releaseFd 1828717888 (3 frames)
CONSUMER: acquireFd 1828717888 (3 frames)
0.1576 - “n04501370 turnstile”
0.0624 - “n02788148 bannister, banister, balustrade, balusters, handrail”
0.0505 - “n03924679 photocopier”
0.0457 - “n02747177 ashcan, trash can, garbage can, wastebin, ash bin, ash-bin, ashbin, dustbin, trash barrel, trash bin”
0.0383 - “n04554684 washer, automatic washer, washing machine”
To classify
CONSUMER: releaseFd 1828718202 (3 frames)
CONSUMER: acquireFd 1828718202 (3 frames)
0.1608 - “n04501370 turnstile”
0.0634 - “n02788148 bannister, banister, balustrade, balusters, handrail”
0.0487 - “n03924679 photocopier”
0.0466 - “n02747177 ashcan, trash can, garbage can, wastebin, ash bin, ash-bin, ashbin, dustbin, trash barrel, trash bin”
0.0399 - “n04554684 washer, automatic washer, washing machine”
To classify
CONSUMER: releaseFd 1828717906 (3 frames)
CONSUMER: acquireFd 1828717906 (3 frames)
0.1617 - “n04501370 turnstile”
0.0635 - “n02788148 bannister, banister, balustrade, balusters, handrail”
0.0481 - “n02747177 ashcan, trash can, garbage can, wastebin, ash bin, ash-bin, ashbin, dustbin, trash barrel, trash bin”
0.0472 - “n03924679 photocopier”
0.0393 - “n04554684 washer, automatic washer, washing machine”
To classify
CONSUMER: releaseFd 1828717888 (3 frames)
CONSUMER: acquireFd 1828717888 (3 frames)
0.1656 - “n04501370 turnstile”
0.0631 - “n02788148 bannister, banister, balustrade, balusters, handrail”
0.0478 - “n02747177 ashcan, trash can, garbage can, wastebin, ash bin, ash-bin, ashbin, dustbin, trash barrel, trash bin”
0.0471 - “n03924679 photocopier”
0.0363 - “n04554684 washer, automatic washer, washing machine”
To classify
CONSUMER: releaseFd 1828718202 (3 frames)
CONSUMER: acquireFd 1828718202 (3 frames)
0.1628 - “n04501370 turnstile”
0.0629 - “n02788148 bannister, banister, balustrade, balusters, handrail”
0.0484 - “n02747177 ashcan, trash can, garbage can, wastebin, ash bin, ash-bin, ashbin, dustbin, trash barrel, trash bin”
0.0462 - “n03924679 photocopier”
0.0360 - “n04554684 washer, automatic washer, washing machine”
To classify
CONSUMER: releaseFd 1828717906 (3 frames)
CONSUMER: acquireFd 1828717906 (3 frames)
0.1618 - “n04501370 turnstile”
0.0638 - “n02788148 bannister, banister, balustrade, balusters, handrail”
0.0494 - “n02747177 ashcan, trash can, garbage can, wastebin, ash bin, ash-bin, ashbin, dustbin, trash barrel, trash bin”
0.0468 - “n03924679 photocopier”
0.0364 - “n04554684 washer, automatic washer, washing machine”
To classify
CONSUMER: releaseFd 1828717888 (3 frames)
CONSUMER: acquireFd 1828717888 (3 frames)
0.1609 - “n04501370 turnstile”
0.0651 - “n02788148 bannister, banister, balustrade, balusters, handrail”
0.0487 - “n03924679 photocopier”
0.0478 - “n02747177 ashcan, trash can, garbage can, wastebin, ash bin, ash-bin, ashbin, dustbin, trash barrel, trash bin”
0.0353 - “n04554684 washer, automatic washer, washing machine”
To classify
CONSUMER: releaseFd 1828718202 (3 frames)
CONSUMER: acquireFd 1828718202 (3 frames)
0.1584 - “n04501370 turnstile”
0.0655 - “n02788148 bannister, banister, balustrade, balusters, handrail”
0.0481 - “n02747177 ashcan, trash can, garbage can, wastebin, ash bin, ash-bin, ashbin, dustbin, trash barrel, trash bin”
0.0452 - “n03924679 photocopier”
0.0330 - “n04554684 washer, automatic washer, washing machine”
To classify
CONSUMER: releaseFd 1828717906 (3 frames)
CONSUMER: acquireFd 1828717906 (3 frames)
0.1624 - “n04501370 turnstile”
0.0646 - “n02788148 bannister, banister, balustrade, balusters, handrail”
0.0483 - “n02747177 ashcan, trash can, garbage can, wastebin, ash bin, ash-bin, ashbin, dustbin, trash barrel, trash bin”
0.0466 - “n03924679 photocopier”
0.0342 - “n04554684 washer, automatic washer, washing machine”
CONSUMER: releaseFd 1828717888 (3 frames)
To classify
CONSUMER: acquireFd 1828717888 (3 frames)
0.1653 - “n04501370 turnstile”
0.0651 - “n02788148 bannister, banister, balustrade, balusters, handrail”
0.0489 - “n02747177 ashcan, trash can, garbage can, wastebin, ash bin, ash-bin, ashbin, dustbin, trash barrel, trash bin”
0.0462 - “n03924679 photocopier”
0.0352 - “n04554684 washer, automatic washer, washing machine”
To classify
CONSUMER: releaseFd 1828718202 (3 frames)
CONSUMER: acquireFd 1828718202 (3 frames)
0.1680 - “n04501370 turnstile”
0.0639 - “n02788148 bannister, banister, balustrade, balusters, handrail”
0.0486 - “n02747177 ashcan, trash can, garbage can, wastebin, ash bin, ash-bin, ashbin, dustbin, trash barrel, trash bin”
0.0449 - “n03924679 photocopier”
0.0351 - “n04554684 washer, automatic washer, washing machine”
To classify
CONSUMER: releaseFd 1828717906 (3 frames)
CONSUMER: acquireFd 1828717906 (3 frames)
0.1680 - “n04501370 turnstile”
0.0644 - “n02788148 bannister, banister, balustrade, balusters, handrail”
0.0489 - “n02747177 ashcan, trash can, garbage can, wastebin, ash bin, ash-bin, ashbin, dustbin, trash barrel, trash bin”
0.0444 - “n03924679 photocopier”
0.0373 - “n04554684 washer, automatic washer, washing machine”
To classify
CONSUMER: releaseFd 1828717888 (3 frames)
CONSUMER: acquireFd 1828717888 (3 frames)
0.1699 - “n04501370 turnstile”
0.0648 - “n02788148 bannister, banister, balustrade, balusters, handrail”
0.0481 - “n02747177 ashcan, trash can, garbage can, wastebin, ash bin, ash-bin, ashbin, dustbin, trash barrel, trash bin”
0.0441 - “n03924679 photocopier”
0.0382 - “n04554684 washer, automatic washer, washing machine”
To classify
CONSUMER: releaseFd 1828718202 (3 frames)
CONSUMER: acquireFd 1828718202 (3 frames)
0.1683 - “n04501370 turnstile”
0.0647 - “n02788148 bannister, banister, balustrade, balusters, handrail”
0.0483 - “n02747177 ashcan, trash can, garbage can, wastebin, ash bin, ash-bin, ashbin, dustbin, trash barrel, trash bin”
0.0418 - “n03924679 photocopier”
0.0375 - “n04554684 washer, automatic washer, washing machine”
To classify
CONSUMER: releaseFd 1828717906 (3 frames)
CONSUMER: acquireFd 1828717906 (3 frames)
0.1762 - “n04501370 turnstile”
0.0678 - “n02788148 bannister, banister, balustrade, balusters, handrail”
0.0502 - “n02747177 ashcan, trash can, garbage can, wastebin, ash bin, ash-bin, ashbin, dustbin, trash barrel, trash bin”
0.0433 - “n03924679 photocopier”
0.0348 - “n04554684 washer, automatic washer, washing machine”
CONSUMER: releaseFd 1828717888 (3 frames)
To classify
CONSUMER: acquireFd 1828717888 (3 frames)
0.1717 - “n04501370 turnstile”
0.0669 - “n02788148 bannister, banister, balustrade, balusters, handrail”
0.0496 - “n02747177 ashcan, trash can, garbage can, wastebin, ash bin, ash-bin, ashbin, dustbin, trash barrel, trash bin”
0.0436 - “n03924679 photocopier”
0.0363 - “n04554684 washer, automatic washer, washing machine”
To classify
CONSUMER: releaseFd 1828718202 (3 frames)
CONSUMER: acquireFd 1828718202 (3 frames)
0.1688 - “n04501370 turnstile”
0.0670 - “n02788148 bannister, banister, balustrade, balusters, handrail”
0.0499 - “n02747177 ashcan, trash can, garbage can, wastebin, ash bin, ash-bin, ashbin, dustbin, trash barrel, trash bin”
0.0428 - “n03924679 photocopier”
0.0343 - “n04554684 washer, automatic washer, washing machine”
To classify
CONSUMER: releaseFd 1828717906 (3 frames)
CONSUMER: acquireFd 1828717906 (3 frames)
0.1760 - “n04501370 turnstile”
0.0666 - “n02788148 bannister, banister, balustrade, balusters, handrail”
0.0500 - “n02747177 ashcan, trash can, garbage can, wastebin, ash bin, ash-bin, ashbin, dustbin, trash barrel, trash bin”
0.0445 - “n03924679 photocopier”
0.0358 - “n04554684 washer, automatic washer, washing machine”
To classify
CONSUMER: releaseFd 1828717888 (3 frames)
CONSUMER: acquireFd 1828717888 (3 frames)
0.1766 - “n04501370 turnstile”
0.0675 - “n02788148 bannister, banister, balustrade, balusters, handrail”
0.0504 - “n02747177 ashcan, trash can, garbage can, wastebin, ash bin, ash-bin, ashbin, dustbin, trash barrel, trash bin”
0.0443 - “n03924679 photocopier”
0.0344 - “n04554684 washer, automatic washer, washing machine”
To classify
CONSUMER: releaseFd 1828718202 (3 frames)
CONSUMER: acquireFd 1828718202 (3 frames)
0.1775 - “n04501370 turnstile”
0.0669 - “n02788148 bannister, banister, balustrade, balusters, handrail”
0.0493 - “n02747177 ashcan, trash can, garbage can, wastebin, ash bin, ash-bin, ashbin, dustbin, trash barrel, trash bin”
0.0429 - “n03924679 photocopier”
0.0352 - “n04554684 washer, automatic washer, washing machine”
CONSUMER: releaseFd 1828717906 (3 frames)
To classify
CONSUMER: acquireFd 1828717906 (3 frames)
0.1736 - “n04501370 turnstile”
0.0669 - “n02788148 bannister, banister, balustrade, balusters, handrail”
0.0491 - “n02747177 ashcan, trash can, garbage can, wastebin, ash bin, ash-bin, ashbin, dustbin, trash barrel, trash bin”
0.0426 - “n03924679 photocopier”
0.0358 - “n04554684 washer, automatic washer, washing machine”
To classify
CONSUMER: releaseFd 1828717888 (3 frames)
CONSUMER: acquireFd 1828717888 (3 frames)
0.1693 - “n04501370 turnstile”
0.0689 - “n02788148 bannister, banister, balustrade, balusters, handrail”
0.0473 - “n02747177 ashcan, trash can, garbage can, wastebin, ash bin, ash-bin, ashbin, dustbin, trash barrel, trash bin”
0.0415 - “n03924679 photocopier”
0.0354 - “n04554684 washer, automatic washer, washing machine”
To classify
CONSUMER: releaseFd 1828718202 (3 frames)
CONSUMER: acquireFd 1828718202 (3 frames)
0.1691 - “n04501370 turnstile”
0.0682 - “n02788148 bannister, banister, balustrade, balusters, handrail”
0.0479 - “n02747177 ashcan, trash can, garbage can, wastebin, ash bin, ash-bin, ashbin, dustbin, trash barrel, trash bin”
0.0392 - “n03924679 photocopier”
0.0365 - “n04554684 washer, automatic washer, washing machine”
To classify
CONSUMER: releaseFd 1828717906 (3 frames)
CONSUMER: acquireFd 1828717906 (3 frames)
0.1792 - “n04501370 turnstile”
0.0674 - “n02788148 bannister, banister, balustrade, balusters, handrail”
0.0481 - “n02747177 ashcan, trash can, garbage can, wastebin, ash bin, ash-bin, ashbin, dustbin, trash barrel, trash bin”
0.0416 - “n03924679 photocopier”
0.0367 - “n04554684 washer, automatic washer, washing machine”
To classify
CONSUMER: releaseFd 1828717888 (3 frames)
CONSUMER: acquireFd 1828717888 (3 frames)
0.1744 - “n04501370 turnstile”
0.0663 - “n02788148 bannister, banister, balustrade, balusters, handrail”
0.0492 - “n02747177 ashcan, trash can, garbage can, wastebin, ash bin, ash-bin, ashbin, dustbin, trash barrel, trash bin”
0.0427 - “n03924679 photocopier”
0.0369 - “n04554684 washer, automatic washer, washing machine”
To classify
CONSUMER: releaseFd 1828718202 (3 frames)
CONSUMER: acquireFd 1828718202 (3 frames)
0.1767 - “n04501370 turnstile”
0.0674 - “n02788148 bannister, banister, balustrade, balusters, handrail”
0.0512 - “n02747177 ashcan, trash can, garbage can, wastebin, ash bin, ash-bin, ashbin, dustbin, trash barrel, trash bin”
0.0410 - “n03924679 photocopier”
0.0356 - “n04554684 washer, automatic washer, washing machine”
To classify
CONSUMER: releaseFd 1828717906 (3 frames)
CONSUMER: acquireFd 1828717906 (3 frames)
0.1707 - “n04501370 turnstile”
0.0660 - “n02788148 bannister, banister, balustrade, balusters, handrail”
0.0519 - “n02747177 ashcan, trash can, garbage can, wastebin, ash bin, ash-bin, ashbin, dustbin, trash barrel, trash bin”
0.0402 - “n03924679 photocopier”
0.0363 - “n04554684 washer, automatic washer, washing machine”
To classify
CONSUMER: releaseFd 1828717888 (3 frames)
CONSUMER: acquireFd 1828717888 (3 frames)
0.1727 - “n04501370 turnstile”
0.0655 - “n02788148 bannister, banister, balustrade, balusters, handrail”
0.0492 - “n02747177 ashcan, trash can, garbage can, wastebin, ash bin, ash-bin, ashbin, dustbin, trash barrel, trash bin”
0.0432 - “n03924679 photocopier”
0.0373 - “n04554684 washer, automatic washer, washing machine”
To classify
CONSUMER: releaseFd 1828718202 (3 frames)
CONSUMER: acquireFd 1828718202 (3 frames)
0.1646 - “n04501370 turnstile”
0.0659 - “n02788148 bannister, banister, balustrade, balusters, handrail”
0.0482 - “n02747177 ashcan, trash can, garbage can, wastebin, ash bin, ash-bin, ashbin, dustbin, trash barrel, trash bin”
0.0414 - “n03924679 photocopier”
0.0357 - “n04554684 washer, automatic washer, washing machine”
To classify
CONSUMER: releaseFd 1828717906 (3 frames)
CONSUMER: acquireFd 182871

Hi Karlalopezsan,
Don’t see error in the log. What is the issue you are facing?

Hello DaneLLL!, I just wanted to know why i cant visually see whats going on in the sample, i just get all the code but no graphics at all. By the way I am using a remote desktop on my laptop to control the Jetson

Hi Karlalopezsan ,
Do you connect to TV via HDMI and set export ‘DISPLAY=:0’?