Run_Samples_with_NCS2.md

Run Samples with Intel® Movidius™ Neural Compute Stick 2

In this lab, we will run the Classfication and Object Detection sample applications with NCS2.

1. Connect Intel® Movidius™ Neural Compute Stick to your development laptop

2. System check

Follow the instruction of Steps for Intel® Neural Compute Stick 2 from the Install Intel® Distribution of OpenVINO™ toolkit for Linux* to setup the USB rules for NCS2.

Then check if the device is visible with lsusb:

lsusb

You will see message like below:

Bus 002 Device 001: ID 1d6b:0003 Linux Foundation 3.0 root hub
Bus 001 Device 015: ID 03e7:2485 

Here ID 03e7:2485 without a description string is the Movidius device.

3. Run the sample application on Intel® Movidius™ Neural Compute Stick (NCS)

Set target hardware as Intel® Movidius™ NCS with -d MYRIAD, remember to use FP16 datatype for MYRIAD plugin.

Run Classification Sample Application with NCS2:

cd /opt/intel/openvino_2021/deployment_tools/inference_engine/samples/python/classification_sample_async

python3 classification_sample_async.py \
-m /opt/intel/workshop/Squeezenet/FP16/squeezenet1.1_fp16.xml \
-i /opt/intel/workshop/smart-video-workshop/Labs/daisy.jpg \
-d MYRIAD \
--labels /opt/intel/workshop/smart-video-workshop/Labs/squeezetnet_label.txt 

Run Object Detection Sample Application with NCS2:

cd /opt/intel/openvino_2021/deployment_tools/inference_engine/samples/python/object_detection_sample_ssd/

rm -f out.bmp

python3 object_detection_sample_ssd.py \
-m /opt/intel/workshop/Mobilenet-SSD-v1/FP16/mobilenet-ssd-v1-fp16.xml \
-i /opt/intel/workshop/smart-video-workshop/Labs/birds.jpg \
-d MYRIAD  

eog out.bmp

Further Reading

To learn more about MYRIAD plugin, pleae refer to MYRIAD Plugin session on OpenVINO documentation.