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Classification for Image

This project supports multiple devices and multiple CNN models for classification. By default, maximum number of devices will be used in inference.
Please make sure you have already set up environment and installed this project correctly. You can refer to the following links for your interested models then.

1 CNN Models

2 Other Arguments


1 CNN Models

  • AlexNet

Compile NCS graph.

cd /opt/movidius/ncappzoo/caffe/AlexNet
make

Launch object classification service.

roslaunch movidius_ncs_launch ncs_image.launch cnn_type:=alexnet

Launch the example application on another console. For example,

roslaunch movidius_ncs_launch ncs_image_classification_example.launch demo_mode:=0
  • GoogleNet

Compile NCS graph.

cd /opt/movidius/ncappzoo/caffe/GoogleNet
make

Launch object classification service.

roslaunch movidius_ncs_launch ncs_image.launch cnn_type:=googlenet

Launch the example application on another console. For example,

roslaunch movidius_ncs_launch ncs_image_classification_example.launch demo_mode:=0
  • SqueezeNet

Compile NCS graph.

cd /opt/movidius/ncappzoo/caffe/SqueezeNet
make

Launch object classification service.

roslaunch movidius_ncs_launch ncs_image.launch cnn_type:=squeezenet

Launch the example application on another console. For example,

roslaunch movidius_ncs_launch ncs_image_classification_example.launch demo_mode:=0
  • Inception_V1

Compile NCS graph.

cd /opt/movidius/ncappzoo/tensorflow/inception_v1
make

Launch object classification service.

roslaunch movidius_ncs_launch ncs_image.launch cnn_type:=inception_v1

Launch the example application on another console. For example,

roslaunch movidius_ncs_launch ncs_image_classification_example.launch demo_mode:=0
  • Inception_V2

Compile NCS graph.

cd /opt/movidius/ncappzoo/tensorflow/inception_v2
make

Launch object classification service.

roslaunch movidius_ncs_launch ncs_image.launch cnn_type:=inception_v2

Launch the example application on another console. For example,

roslaunch movidius_ncs_launch ncs_image_classification_example.launch demo_mode:=0
  • Inception_V3

Compile NCS graph.

cd /opt/movidius/ncappzoo/tensorflow/inception_v3
make

Launch object classification service.

roslaunch movidius_ncs_launch ncs_image.launch cnn_type:=inception_v3

Launch the example application on another console. For example,

roslaunch movidius_ncs_launch ncs_image_classification_example.launch demo_mode:=0
  • Inception_V4

Compile NCS graph.

cd /opt/movidius/ncappzoo/tensorflow/inception_v4
make

Launch object classification service.

roslaunch movidius_ncs_launch ncs_image.launch cnn_type:=inception_v4

Launch the example application on another console. For example,

roslaunch movidius_ncs_launch ncs_image_classification_example.launch demo_mode:=0
  • MobileNet

Compile NCS graph.

cd /opt/movidius/ncappzoo/tensorflow/mobilenets
make

Launch object classification service.

roslaunch movidius_ncs_launch ncs_image.launch cnn_type:=mobilenet

Launch the example application on another console. For example,

roslaunch movidius_ncs_launch ncs_image_classification_example.launch demo_mode:=0

2 Other Arguments

Arguments Description Default Value Valid Values
device_index ncs device index 0 0~N-1(N is the maximum number of inserted NCS devices)
log_level ncs log level 0 0:Nothing / 1:Errors / 2:Verbose
cnn_type indicate different cnn models googlenet alexnet / googlenet / squeezenet / inception_v1 / inception_v2 / inception_v3 / inception_v4 / mobilenet
top_n the number of results to be shown, only valid for classification 3 0~5
demo_mode the display mode of processed results 0:sequentially output all results 1: display random results in infinite loop 0, 1
image_base_path directory of images to be inferred "/opt/movidius/ncappzoo/data/images/"
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