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Detection 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

  • MobileNet_SSD

Compile NCS graph.

cd /opt/movidius/ncappzoo/caffe/SSD_MobileNet
make

Launch object detection service.

roslaunch movidius_ncs_launch ncs_image.launch cnn_type:=mobilenetssd

Launch the example application on another console. For example,

roslaunch movidius_ncs_launch ncs_image_detection_example.launch demo_mode:=0 image_base_path:=<absolute-image-directory>
  • TinyYolo_V1

Compile NCS graph.

cd /opt/movidius/ncappzoo/caffe/TinyYolo
make

Launch object detection service.

roslaunch movidius_ncs_launch ncs_image.launch cnn_type:=tinyyolo_v1

Launch the example application on another console. For example,

roslaunch movidius_ncs_launch ncs_image_detection_example.launch demo_mode:=0 image_base_path:=<absolute-image-directory>

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 tinyyolo_v1 tinyyolo_v1 / mobilenetssd
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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