image_detection.md
April 2, 2018 ยท View on GitHub
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
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>
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/" |