OpenVINO16

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OpenVINO™ Toolkit for Linux on VirtualBox †

　OpenVINO™ツールキットの最新版「2021.3」を 「Core™ i7-6700」VirtualBox 上の ubuntu20.04 にインストールする。
　VirtualBox は USB デバイスを使用できるので、これまでの Hyper-V から移行することにする。（残念ながら同居はできない）

「OpenVINO™ Toolkit for Linux 2021.3」のインストール †

事前準備 †

• Virtual Box に ubuntu20.04.1 仮想マシンを構築
  
  • 仮想マシンを「新規」作成する。
    
    • ネットワーク設定で「ブリッジアダプター」を指定。
      
    • 「起動」ボタンを押しローカルのisoファイル「ubuntu-20.04.2-desktop-amd64.iso」を指定する。
      
    • ubuntu20.04 をインストールする。
      
• ubuntu基本設定
  
  • 言語サポート
    
  • 日本語(Mozc)
    
  • SSHサーバー・ネットツールをインストール
    

    sudo apt install openssh-server
    sudo apt install net-tools

  • vi 設定

    $ vi ~/.vimrc
    set nocompatible
    set backspace=indent,eol,start
    set expandtab
    set tabstop=4
    set shiftwidth=4
    set autoindent

  • sudo 付きでの vi 対応
    sudo 付きで vi を実行した場合は、root の設定が使用されるので、rootの .vimrcを ~/vimrc のシンボリックリンクにする。
    

    $ sudo ln -s ~/.vimrc /root/.vimrc
    $ sudo ls -la /root
    合計 24
    drwx------  4 root root 4096  3月 19 05:34 .
    drwxr-xr-x 21 root root 4096  3月 19 04:49 ..
    -rw-r--r--  1 root root  570  9月  9  2019 .bashrc
    drwx------  2 root root 4096  9月 26 09:13 .cache
    -rw-r--r--  1 root root  148  9月  9  2019 .profile
    lrwxrwxrwx  1 root root   15  3月 19 05:34 .vimrc -> /home/pi/.vimrc
    drwx------  3 root root 4096  3月 17 15:37 .vnc

OpenVINO™ Toolkit のダウンロード †

• ダウンロードファイル「l_openvino_toolkit_p_2021.3.394.tgz」を~/ダウンロードフォルダにコピーする。
  

OpenVINO™ Toolkit のインストール †

• 以下の手順詳細は OpenVINO™ Toolkit for Linux on VirtualBox 参照。
  

1. ダウンロードされたパッケージを解凍
   

   $ tar -xvzf l_openvino_toolkit_p_2021.3.394.tgz

2. 解凍したパッケージの中にあるインストーラを起動
   

   $ cd l_openvino_toolkit_p_2021.3.394
   $ sudo ./install_GUI.sh

3. 依存関係の外部パッケージをインストール

   $ cd /opt/intel/openvino_2021/install_dependencies
   $ sudo -E ./install_openvino_dependencies.sh

4. 環境変数の設定

   $ source /opt/intel/openvino_2021/bin/setupvars.sh
   [setupvars.sh] OpenVINO environment initialized

   シェルを起動時に自動的に環境変数を設定するため 「~/.bashrc」ファイルの最後に「source /opt/intel/openvino_2021/bin/setupvars.sh」の1行を追記する。
   
   
5. Model Optimizer の設定

   $ cd /opt/intel/openvino_2021/deployment_tools/model_optimizer/install_prerequisites
   $ sudo ./install_prerequisites.sh

6. Pytorch をインストール
   オフィシャルサイト PyTorch FROM RESEARCH TO PRODUCTION にアクセスして、インストールパラメータを取得する。
   

   pip3 install torch==1.8.0+cpu torchvision==0.9.0+cpu torchaudio==0.8.0 -f https://download.pytorch.org/whl/torch_stable.html

   $ pip3 install torch==1.8.1+cpu torchvision==0.9.1+cpu torchaudio==0.8.1 -f https://download.pytorch.org/whl/torch_stable.html

7. scipy をインストール
   

   $ pip3 install scipy

8. Neural Compute Stick 2 (NCS2) の設定
   

   $ sudo usermod -a -G users "$(whoami)"
   
   $ sudo cp /opt/intel/openvino_2021/inference_engine/external/97-myriad-usbboot.rules /etc/udev/rules.d/
   $ sudo udevadm control --reload-rules
   $ sudo udevadm trigger
   $ sudo ldconfig

   1. システムを再起動する。
      
   2. VirtualBox の USBデバイスで「Miriad...」をチェックしておく。
      
   3. 設定確認
      

      $ lsusb
      Bus 001 Device 002: ID 03e7:2485 Intel Movidius MyriadX
      Bus 001 Device 001: ID 1d6b:0002 Linux Foundation 2.0 root hub
      Bus 002 Device 002: ID 80ee:0021 VirtualBox USB Tablet
      Bus 002 Device 001: ID 1d6b:0001 Linux Foundation 1.1 root hub
      $ id mizutu
      uid=1000(mizutu) gid=1000(mizutu) groups=1000(mizutu),4(adm),24(cdrom),27(sudo),30(dip),46(plugdev),100(users),120(lpadmin),131(lxd),132(sambashare)

9. サンプルデモの実行１ demo_security_barrier_camera.sh
   

   $ cd /opt/intel/openvino_2021/deployment_tools/demo
   $ ./demo_security_barrier_camera.sh

10. サンプルデモの実行２ demo_squeezenet_download_convert_run.sh
    

    $ ./demo_squeezenet_download_convert_run.sh

11. サンプルデモの実行３ demo_benchmark_app.sh
    

    $ ./demo_benchmark_app.sh

12. 推論モデルファイル
    ここ からホームディレクトリにダウンロードして展開する。

    $ tar xvzf model_xxxxxxxx.tar.gz

    学習済みモデルの場所
    
    • ~/model/intel
    • ~/model/pubkic
13. OpenVINO™ ツールキット サンプルデモ ここ からホームディレクトリにダウンロードして展開する。

    $ tar xvzf Images_xxxxxxxx.tar.gz
    $ tar xvzf Videos_xxxxxxxx.tar.gz
    $ tar xvzf run_app_xxxxxxxx.tar.gz
    $ tar xvzf workspace_xxxxxxxx.tar.gz
    $ tar xvzf omz_demos_build_xxxxxxxx.tar.gz

14. デモ実行環境設定のシェルスクリプト
    シェルを起動時に自動的に環境変数を設定するため 「~/.bashrc」ファイルの最後に「source ~/omz_demos_build/omz_demos.sh」の1行を追記する。
    

OpenVINO™ Toolkit に付属するデモソフト †

「2021.3」に付属するデモソフト一覧)

Virtual Box で NCS2を使うために USBフィルターを追加する †

• 仮想マシンをシャットダウンする。
  
• VirtualBox Manager を開く。
  
• Open Settings -> USB (remove all usb from host)
• Check “Enable USB Controller”
• Check “USB 3.0 (xHCI) Controller”
• Add a new USB filter with Vendor ID: 03e7
• The other filter fields can be blank.
• Add a new USB filter with Vendor ID: 040e
• The other filter fields can be blank.

• アプリケーション実行例 (メガネ・帽子 バーチャル試着アプリケーション)
  NCS2 と Webカメラを接続して使用。
  
  

  $ cd ~/run_app/
  $ ./virtual_fitting_16.sh 0 cam
  [virtual_fitting_16.sh] virtual_Fitting.py (MYRIAD) Run !!
  itemidx.: 0
  program : virtual_fitting.py
  model1. : -m_dt /home/mizutu/model/intel/FP16/face-detection-retail-0005.xml
  model2. : -m_lm /home/mizutu/model/intel/FP16/landmarks-regression-retail-0009.xml
  device. : MYRIAD
  input.. : -i cam
  output. :
  
  ---  Virtual Fitting ---
  4.5.2-openvino
  OpenVINO inference_engine: 2.1.2021.3.0-2787-60059f2c755-releases/2021/3
  
  virtual_fitting.py:145: DeprecationWarning: 'inputs' property of IENetwork class is deprecated. To access DataPtrs user need to use 'input_data' property of InputInfoPtr objects which can be accessed by 'input_info' property.
    input_blob_face = next(iter(net_face.inputs))
   Virtual Fitting: Starting application...
     - Item File    :  ../../Images/parts/glass01.png
     - Image File   :  0
     - m_detect     :  /home/mizutu/model/intel/FP16/face-detection-retail-0005.xml
     - m_recognition:  /home/mizutu/model/intel/FP16/landmarks-regression-retail-0009.xml
     - Device       :  MYRIAD
     - Program Title:  y
     - Processed out:  non
  
   Finished.

   

Open Model Zoo Demos †

3D Human Pose Estimation Python* Demo †

デモの実行 †

#ref(): File not found: "omz01_s.jpg" at page "OpenVINO15/OMZdemo"

• 実行例「Ubuntu on VirtualBox Core™ i7-6700」

  $ cd ~/run_app/
  $ ./_human_pose_estimation_3d_demo.sh 
  [human_pose_estimation_3d_demo.sh] 'human_pose_estimation_3d_demo' Run !!

• 実行例「Ubuntu on VirtualBox Core™ i7-6700」+ NCS2

  $ cd ~/run_app/
  $ ./_human_pose_estimation_3d_demo_16.sh 
  [human_pose_estimation_3d_demo_16.sh] 'human_pose_estimation_3d_demo_16' Run !!

速度比較 †

Action Recognition Python* Demo †

デモの実行 †

• 実行例「Ubuntu on VirtualBox Core™ i7-6700」

  $ cd ~/run_app/
  $ ./_action_recognition.sh 
  [action_recognition_demo.sh] 'action_recognition_demo' Run !!
  Reading IR...
  Loading IR to the plugin...
  Reading IR...
  Loading IR to the plugin...
  To close the application, press 'CTRL+C' here or switch to the output window and press Esc or Q
  Frame 15: Safe driving - 85.45% -- 13.37ms
  Frame 16: Safe driving - 87.28% -- 29.62ms
      :
      :
  Frame 32: Safe driving - 96.67% -- 140.04ms
  Frame 33: Safe driving - 96.29% -- 141.38ms
  finishing <action_recognition_demo.steps.RenderStep object at 0x7f59125b0910>
  Data total: 2.77ms (+/-: 3.11) 361.50fps
  Data   own: 2.76ms (+/-: 3.11) 362.49fps
  Encoder total: 18.34ms (+/-: 5.95) 54.52fps
  Encoder   own: 18.33ms (+/-: 5.95) 54.55fps
  Decoder total: 88.19ms (+/-: 60.59) 11.34fps
  Decoder   own: 88.18ms (+/-: 60.59) 11.34fps
  Render total: 184.99ms (+/-: 96.08) 5.41fps
  Render   own: 182.94ms (+/-: 93.21) 5.47fps

• 実行例「Ubuntu on VirtualBox Core™ i7-6700」+ NCS2

  $ cd ~/run_app/
  $ ./_action_recognition_16.sh 
  [action_recognition_demo_16.sh] 'action_recognition_demo (NCS2)' Run !!
  Reading IR...
  Loading IR to the plugin...
  [Warning][VPU][Config] Deprecated option was used : VPU_HW_STAGES_OPTIMIZATION
  Reading IR...
  Loading IR to the plugin...
  To close the application, press 'CTRL+C' here or switch to the output window and press Esc or Q
  Frame 15: Safe driving - 84.79% -- 10.10ms
  Frame 16: Safe driving - 86.75% -- 13.23ms
      :
      :
  Frame 53: Safe driving - 63.68% -- 18.65ms
  Frame 54: Safe driving - 63.34% -- 18.99ms
  Frame 55: Safe driving - 64.52% -- 19.93ms
  finishing <action_recognition_demo.steps.RenderStep object at 0x7f2965b08af0>
  Data total: 5.79ms (+/-: 7.14) 172.66fps
  Data   own: 5.78ms (+/-: 7.13) 173.12fps
  Encoder total: 6.95ms (+/-: 5.41) 143.82fps
  Encoder   own: 6.90ms (+/-: 5.40) 144.87fps
  Decoder total: 10.24ms (+/-: 7.95) 97.65fps
  Decoder   own: 10.21ms (+/-: 7.95) 97.97fps
  Render total: 52.65ms (+/-: 86.55) 18.99fps
  Render   own: 52.09ms (+/-: 82.70) 19.20fps

速度比較 †

Object Detection Python* Demo †

デモの実行 †

• 実行例「Ubuntu on VirtualBox Core™ i7-6700」

  $ cd ~/run_app/
  $ ./_object_detection_python_demo.sh 
  [object_detection_demo.sh] 'object_detection_demo' Run !!
  [ INFO ] Initializing Inference Engine...
  [ INFO ] Loading network...
  [ INFO ] Reading network from IR...
  [ INFO ] Loading network to CPU plugin...
  [ INFO ] Starting inference...
  To close the application, press 'CTRL+C' here or switch to the output window and press ESC key
  Latency: 828.9 ms
  FPS: 1.1

• 実行例「Ubuntu on VirtualBox Core™ i7-6700」+ NCS2

  $ cd ~/run_app/
  $ ./_object_detection_python_demo_16.sh 
  [object_detection_demo/_16.sh] 'object_detection_demo (NCS2)' Run !!
  [ INFO ] Initializing Inference Engine...
  [ INFO ] Loading network...
  [ INFO ] Reading network from IR...
  [ INFO ] Loading network to MYRIAD plugin...
  [ INFO ] Starting inference...
  To close the application, press 'CTRL+C' here or switch to the output window and press ESC key
  Latency: 494.7 ms
  FPS: 1.9

速度比較 †

Human Pose Estimation Python* Demo †

デモの実行 †

• 実行例「Ubuntu on VirtualBox Core™ i7-6700」

  $ cd ~/run_app/
  $ ./_human_pose_estimation.sh 
  [human_pose_estimation_demo.sh] 'human_pose_estimation_demo' Run !!
  [ INFO ] Initializing Inference Engine...
  [ INFO ] Loading network...
  [ INFO ] Reading network from IR...
  [ INFO ] Reshape net to {'data': [1, 3, 256, 456]}
  [ INFO ] Loading network to CPU plugin...
  [ INFO ] Starting inference...
  To close the application, press 'CTRL+C' here or switch to the output window and press ESC key
  Latency: 170.2 ms
  FPS: 5.6

• 実行例「Ubuntu on VirtualBox Core™ i7-6700」+ NCS2

  $ cd ~/run_app/
  $ ./_human_pose_estimation_16.sh 
  [human_pose_estimation_demo_16.sh] 'human_pose_estimation_demo (NCS2)' Run !!
  [ INFO ] Initializing Inference Engine...
  [ INFO ] Loading network...
  [ INFO ] Reading network from IR...
  [ INFO ] Reshape net to {'data': [1, 3, 256, 456]}
  [ INFO ] Loading network to MYRIAD plugin...
  [ INFO ] Starting inference...
  To close the application, press 'CTRL+C' here or switch to the output window and press ESC key
  Latency: 211.3 ms
  FPS: 4.6

速度比較 †

Gesture Recognition Python* Demo †

デモの実行 †

• 実行例「Ubuntu on VirtualBox Core™ i7-6700」

  $ cd ~/run_app/
  $ ./_gesture_recognition_demo.sh 
  [gesture_recognition_demo.sh] 'gesture_recognition_demo' Run !!
  
  Traceback (most recent call last):
    File "/usr/lib/python3.8/multiprocessing/queues.py", line 245, in _feed
      send_bytes(obj)
    File "/usr/lib/python3.8/multiprocessing/connection.py", line 200, in send_bytes
      self._send_bytes(m[offset:offset + size])
    File "/usr/lib/python3.8/multiprocessing/connection.py", line 405, in _send_bytes
      self._send(buf)
    File "/usr/lib/python3.8/multiprocessing/connection.py", line 368, in _send
      n = write(self._handle, buf)
  BrokenPipeError: [Errno 32] Broken pipe

速度比較 †

Handwritten Text Recognition Demo †

デモの実行 †

• 実行例「Ubuntu on VirtualBox Core™ i7-6700」

  $ cd ~/run_app/
  $ ./_handwritten_text_recognition_demo.sh 
  [handwritten_text_recognition_demo.sh] 'handwritten_text_recognition_demo' Run !!
  [ INFO ] Loading network
  [ INFO ] Preparing input/output blobs
  [ INFO ] Loading model to the plugin
  [ INFO ] Starting inference (1 iterations)
  ['菊池朋子']
  [ INFO ] Average throughput: 1194.643497467041 ms

• 実行例「Ubuntu on VirtualBox Core™ i7-6700」+ NCS2

  $ cd ~/run_app/
  $ ./_handwritten_text_recognition_demo_16.sh 
  [handwritten_text_recognition_demo_16.sh] 'handwritten_text_recognition_demo (NCS2)' Run !!
  [ INFO ] Loading network
  [ INFO ] Preparing input/output blobs
  [ INFO ] Loading model to the plugin
  [ INFO ] Starting inference (1 iterations)
  ['菊池朋子']
  [ INFO ] Average throughput: 913.844108581543 ms

速度比較 †

Text Detection C++ Demo †

デモの実行 †

• 実行例「Ubuntu on VirtualBox Core™ i7-6700」

  $ cd ~/run_app/
  $ ./_text_detection_demo.sh 
  [text_detection_demo.sh] 'text_detection_demo' Run !!
  InferenceEngine: 	API version ......... 2.1
  	Build ........... 2021.3.0-2787-60059f2c755-releases/2021/3
  [ INFO ] Parsing input parameters
  [ INFO ] Loading Inference Engine
  [ INFO ] Device info: 
  [ INFO ] 	CPU
  	MKLDNNPlugin version ......... 2.1
  	Build ........... 2021.3.0-2787-60059f2c755-releases/2021/3
  
  [ INFO ] Loading network files
  [ INFO ] Starting inference
  To close the application, press 'CTRL+C' here or switch to the output window and press ESC or Q
  text detection model inference (ms) (fps): 360.929 2.77063
  text detection postprocessing (ms) (fps): 98 10.2041
  
  text recognition model inference (ms) (fps): 26.3112 38.0066
  text recognition postprocessing (ms) (fps): 0.0191888 52113.8
  
  text crop (ms) (fps): 0.182423 5481.75

• 実行例「Ubuntu on VirtualBox Core™ i7-6700」+ NCS2

  $ cd ~/run_app/
  $ ./_text_detection_demo_16.sh 
  [text_detection_demo_16.sh] 'text_detection_demo (NCS2)' Run !!
  InferenceEngine: 	API version ......... 2.1
  	Build ........... 2021.3.0-2787-60059f2c755-releases/2021/3
  [ INFO ] Parsing input parameters
  [ INFO ] Loading Inference Engine
  [ INFO ] Device info: 
  [ INFO ] 	MYRIAD
  	myriadPlugin version ......... 2.1
  	Build ........... 2021.3.0-2787-60059f2c755-releases/2021/3
  
  [ INFO ] Loading network files
  [ INFO ] Starting inference
  To close the application, press 'CTRL+C' here or switch to the output window and press ESC or Q
  text detection model inference (ms) (fps): 654.625 1.52759
  text detection postprocessing (ms) (fps): 93.625 10.6809
  
  text recognition model inference (ms) (fps): 77.125 12.966
  text recognition postprocessing (ms) (fps): 0.02785 35906.6
  
  text crop (ms) (fps): 0.0734083 13622.4

速度比較 †

Crossroad Camera C++ Demo †

デモの実行 †

• 実行例「Ubuntu on VirtualBox Core™ i7-6700」

  $ cd ~/run_app/
  $ ./_crossroad_camera_demo.sh 
  [crossroad_camera_demo.sh] 'crossroad_camera_demo' Run !!
  InferenceEngine: 	API version ......... 2.1
  	Build ........... 2021.3.0-2787-60059f2c755-releases/2021/3
  [ INFO ] Parsing input parameters
  [ INFO ] Person Attributes Recognition detection DISABLED
  [ INFO ] Person Reidentification Retail detection DISABLED
  [ INFO ] Loading device CPU
  [ INFO ] 	CPU
  	MKLDNNPlugin version ......... 2.1
  	Build ........... 2021.3.0-2787-60059f2c755-releases/2021/3
  
  [ INFO ] Loading network files for PersonDetection
  [ INFO ] Batch size is forced to  1
  [ INFO ] Checking Person Detection inputs
  [ INFO ] Checking Person Detection outputs
  [ INFO ] Loading Person Detection model to the CPU device
  [ INFO ] Start inference 
  To close the application, press 'CTRL+C' here or switch to the output window and press ESC key
  [ INFO ] Total Inference time: 17497.5
  
  [ INFO ] Execution successful

• 実行例「Ubuntu on VirtualBox Core™ i7-6700」+ NCS2

  $ cd ~/run_app/
  $ ./_crossroad_camera_demo_16.sh 
  [crossroad_camera_demo_16.sh] 'crossroad_camera_demo (NCS2)' Run !!
  InferenceEngine: 	API version ......... 2.1
  	Build ........... 2021.3.0-2787-60059f2c755-releases/2021/3
  [ INFO ] Parsing input parameters
  [ INFO ] Person Attributes Recognition detection DISABLED
  [ INFO ] Person Reidentification Retail detection DISABLED
  [ INFO ] Loading device MYRIAD
  [ INFO ] 	MYRIAD
  	myriadPlugin version ......... 2.1
  	Build ........... 2021.3.0-2787-60059f2c755-releases/2021/3
  
  [ INFO ] Loading network files for PersonDetection
  [ INFO ] Batch size is forced to  1
  [ INFO ] Checking Person Detection inputs
  [ INFO ] Checking Person Detection outputs
  [ INFO ] Loading Person Detection model to the MYRIAD device
  [ INFO ] Start inference 
  To close the application, press 'CTRL+C' here or switch to the output window and press ESC key
  [ INFO ] Total Inference time: 8970.92
  
  E: [global] [    812111] [crossroad_camer] XLink_sem_wait:94	 XLink_sem_inc(sem) method call failed with an error: -1
  E: [global] [    812111] [crossroad_camer] XLinkResetRemote:257	can't wait dispatcherClosedSem
  
  [ INFO ] Execution successful

速度比較 †

Human Pose Estimation C++ Demo †

デモの実行 †

• 実行例「Ubuntu on VirtualBox Core™ i7-6700」

  $ cd ~/run_app/
  $ ./_human_pose_estimation_demo.sh 
  [human_pose_estimation_demo.sh] 'human_pose_estimation_demo' Run !!
  [ INFO ] InferenceEngine: 	API version ......... 2.1
  	Build ........... 2021.3.0-2787-60059f2c755-releases/2021/3
  [ INFO ] Parsing input parameters
  [ INFO ] Reading input
  [ INFO ] Loading Inference Engine
  [ INFO ] Device info: 
  [ INFO ] 	CPU
  	MKLDNNPlugin version ......... 2.1
  	Build ........... 2021.3.0-2787-60059f2c755-releases/2021/3
  Loading network files
  [ INFO ] Batch size is forced to 1.
  [ INFO ] Loading model to the device
  
  [ INFO ] Metric reports:
  Latency: 382.1 ms
  FPS: 5.0
  [ INFO ] 
  
  [ INFO ] The execution has completed successfully

• 実行例「Ubuntu on VirtualBox Core™ i7-6700」+ NCS2

  $ cd ~/run_app/
  $ ./_human_pose_estimation_demo_16.sh 
  [ INFO ] InferenceEngine: 	API version ......... 2.1
  	Build ........... 2021.3.0-2787-60059f2c755-releases/2021/3
  [ INFO ] Parsing input parameters
  [ INFO ] Reading input
  [ INFO ] Loading Inference Engine
  [ INFO ] Device info: 
  [ INFO ] 	MYRIAD
  	myriadPlugin version ......... 2.1
  	Build ........... 2021.3.0-2787-60059f2c755-releases/2021/3
  Loading network files
  [ INFO ] Batch size is forced to 1.
  [ INFO ] Loading model to the device
  
  [ INFO ] Metric reports:
  Latency: 518.6 ms
  FPS: 9.5
  [ INFO ] 
  
  [ INFO ] The execution has completed successfully

速度比較 †

　※「2021.3」で変更あり。比較データ無し。

Object Detection C++ Demo †

デモの実行 †

• 実行例「Ubuntu on VirtualBox Core™ i7-6700」

  $ cd ~/run_app/
  $ ./_object_detection_demo.sh 
  [object_detection_demo.sh] 'object_detection_demo' Run !!
  [ INFO ] InferenceEngine: 	API version ......... 2.1
  	Build ........... 2021.3.0-2787-60059f2c755-releases/2021/3
  [ INFO ] Parsing input parameters
  [ INFO ] Reading input
  [ INFO ] Loading Inference Engine
  [ INFO ] Device info: 
  [ INFO ] 	CPU
  	MKLDNNPlugin version ......... 2.1
  	Build ........... 2021.3.0-2787-60059f2c755-releases/2021/3
  Loading network files
  [ INFO ] Batch size is forced to 1.
  [ INFO ] Checking that the inputs are as the demo expects
  [ INFO ] Checking that the outputs are as the demo expects
  [ INFO ] Loading model to the device
  
  [ INFO ] Metric reports:
  Latency: 78.2 ms
  FPS: 23.8
  [ INFO ] 
  
  [ INFO ] The execution has completed successfully

• 実行例「Ubuntu on VirtualBox Core™ i7-6700」+ NCS2

  $ cd ~/run_app/
  $ ./_object_detection_demo_16.sh 
  [object_detection_demo_16.sh] 'object_detection_demo (NCS2)' Run !!
  [ INFO ] InferenceEngine: 	API version ......... 2.1
  	Build ........... 2021.3.0-2787-60059f2c755-releases/2021/3
  [ INFO ] Parsing input parameters
  [ INFO ] Reading input
  [ INFO ] Loading Inference Engine
  [ INFO ] Device info: 
  [ INFO ] 	MYRIAD
  	myriadPlugin version ......... 2.1
  	Build ........... 2021.3.0-2787-60059f2c755-releases/2021/3
  Loading network files
  [ INFO ] Batch size is forced to 1.
  [ INFO ] Checking that the inputs are as the demo expects
  [ INFO ] Checking that the outputs are as the demo expects
  [ INFO ] Loading model to the device
  
  [ INFO ] Metric reports:
  Latency: 316.1 ms
  FPS: 15.6
  [ INFO ] 
  
  [ INFO ] The execution has completed successfully

速度比較 †

Smart Classroom C++ Demo †

デモの実行 †

• 実行例「Ubuntu on VirtualBox Core™ i7-6700」

  $ cd ~/run_app
  $ ./_smart_classroom_demo.sh
  [smart_classroom_demo.sh] 'smart_classroom_demo' Run !!
  [ INFO ] InferenceEngine: 	API version ......... 2.1
  	Build ........... 2021.3.0-2787-60059f2c755-releases/2021/3
  [ INFO ] Parsing input parameters
  [ INFO ] Loading Inference Engine
  [ INFO ] Device info: 
  [ INFO ] 	CPU
  	MKLDNNPlugin version ......... 2.1
  	Build ........... 2021.3.0-2787-60059f2c755-releases/2021/3
  
  [ WARNING ] Face recognition models are disabled!
  To close the application, press 'CTRL+C' here or switch to the output window and press ESC key
  
  [ INFO ] Mean FPS: 6.42783
  [ INFO ] Frames processed: 68
  
  [ INFO ] Execution successful

• 実行例「Ubuntu on VirtualBox Core™ i7-6700」+ NCS2

  $ cd ~/run_app
  $ ./_smart_classroom_demo_16.sh
  [smart_classroom_demo_16.sh] 'smart_classroom_demo (NCS2)' Run !!
  [ INFO ] InferenceEngine: 	API version ......... 2.1
  	Build ........... 2021.3.0-2787-60059f2c755-releases/2021/3
  [ INFO ] Parsing input parameters
  [ INFO ] Loading Inference Engine
  [ INFO ] Device info: 
  [ INFO ] 	MYRIAD
  	myriadPlugin version ......... 2.1
  	Build ........... 2021.3.0-2787-60059f2c755-releases/2021/3
  
  [ INFO ] 	CPU
  	MKLDNNPlugin version ......... 2.1
  	Build ........... 2021.3.0-2787-60059f2c755-releases/2021/3
  
  [ WARNING ] Face recognition models are disabled!
  To close the application, press 'CTRL+C' here or switch to the output window and press ESC key
  
  [ INFO ] Mean FPS: 3.68177
  [ INFO ] Frames processed: 23
  
  E: [global] [    322767] [smart_classroom] XLink_sem_wait:94	 XLink_sem_inc(sem) method call failed with an error: -1
  E: [global] [    322767] [smart_classroom] XLinkResetRemote:257	can't wait dispatcherClosedSem
  
  [ INFO ] Execution successful

速度比較 †

Pedestrian Tracker C++ Demo †

デモの実行 †

• 実行例「Ubuntu on VirtualBox Core™ i7-6700」

  $ cd ~/run_app/
  $ ./_pedestrian_tracker_demo.sh 
  [pedestrian_tracker_demo.sh] 'pedestrian_tracker_demo' Run !!
  InferenceEngine: 	API version ......... 2.1
  	Build ........... 2021.3.0-2787-60059f2c755-releases/2021/3
  Loading device CPU
  	CPU
  	MKLDNNPlugin version ......... 2.1
  	Build ........... 2021.3.0-2787-60059f2c755-releases/2021/3
  
  To close the application, press 'CTRL+C' here or switch to the output window and press ESC key
  
  Execution successful

• 実行例「Ubuntu on VirtualBox Core™ i7-6700」+ NCS2

  $ cd ~/run_app/
  $ ./_pedestrian_tracker_demo_16.sh
  [pedestrian_tracker_demo_16.sh] 'pedestrian_tracker_demo (NCS2)' Run !!
  InferenceEngine: 	API version ......... 2.1
  	Build ........... 2021.3.0-2787-60059f2c755-releases/2021/3
  Loading device MYRIAD
  	MYRIAD
  	myriadPlugin version ......... 2.1
  	Build ........... 2021.3.0-2787-60059f2c755-releases/2021/3
  
  E: [global] [    454311] [pedestrian_trac] XLink_sem_wait:94	 XLink_sem_inc(sem) method call failed with an error: -1
  E: [global] [    454311] [pedestrian_trac] XLinkResetRemote:257	can't wait dispatcherClosedSem
  
  [ ERROR ] Failed to compile layer "736": Unsupported combination of indices in layer "736". Only across channel and full batch supported.

Super Resolution C++ Demo †

デモの実行 †

• 実行例「Ubuntu on VirtualBox Core™ i7-6700」

  $ cd ~/run_app/
  $ ./_super_resolution_demo.sh 
  [super_resolution_demo.sh] 'super_resolution_demo' Run !!
  [ INFO ] InferenceEngine: 	API version ......... 2.1
  	Build ........... 2021.3.0-2787-60059f2c755-releases/2021/3
  [ INFO ] Parsing input parameters
  [ INFO ] Files were added: 1
  [ INFO ]     /home/mizutu/Images/image-low.bmp
  [ INFO ] Loading Inference Engine
  [ INFO ] Device info: 
  [ INFO ] 	CPU
  	MKLDNNPlugin version ......... 2.1
  	Build ........... 2021.3.0-2787-60059f2c755-releases/2021/3
  
  [ INFO ] Loading network files
  [ INFO ] Preparing input blobs
  [ INFO ] Batch size is 1
  [ INFO ] Preparing output blobs
  [ INFO ] Loading model to the device
  [ INFO ] Create infer request
  To close the application, press 'CTRL+C' here or switch to the output window and press any key
  [ INFO ] Start inference
  [ INFO ] Output size [N,C,H,W]: 1, 3, 1080, 1920
  [ INFO ] Execution successful
  
  [ INFO ] This demo is an API example, for any performance measurements please use the dedicated benchmark_app tool from the openVINO toolkit

• 実行例「Ubuntu on VirtualBox Core™ i7-6700」+ NCS2

  $ cd ~/run_app/
  $ ./_super_resolution_demo_16.sh 
  [super_resolution_demo_16.sh] 'super_resolution_demo (NCS2)' Run !!
  [ INFO ] InferenceEngine: 	API version ......... 2.1
  	Build ........... 2021.3.0-2787-60059f2c755-releases/2021/3
  [ INFO ] Parsing input parameters
  [ INFO ] Files were added: 1
  [ INFO ]     /home/mizutu/Images/image-low.bmp
  [ INFO ] Loading Inference Engine
  [ INFO ] Device info: 
  [ INFO ] 	MYRIAD
  	myriadPlugin version ......... 2.1
  	Build ........... 2021.3.0-2787-60059f2c755-releases/2021/3
  
  [ INFO ] Loading network files
  [ INFO ] Preparing input blobs
  [ INFO ] Batch size is 1
  [ INFO ] Preparing output blobs
  [ INFO ] Loading model to the device
  [ INFO ] Create infer request
  To close the application, press 'CTRL+C' here or switch to the output window and press any key
  [ INFO ] Start inference
  [ INFO ] Output size [N,C,H,W]: 1, 3, 1080, 1920
  E: [global] [    553193] [super_resolutio] XLink_sem_wait:94	 XLink_sem_inc(sem) method call failed with an error: -1
  E: [global] [    553193] [super_resolutio] XLinkResetRemote:257	can't wait dispatcherClosedSem
  
  [ INFO ] Execution successful
  
  [ INFO ] This demo is an API example, for any performance measurements please use the dedicated benchmark_app tool from the openVINO toolkit

Single Human Pose Estimation Demo (top-down pipeline) †

デモの実行 †

• 実行例「Ubuntu on VirtualBox Core™ i7-6700」

  $ cd ~/run_app/
  $ ./_single_human_pose_estimation_demo.sh 
  [single_human_pose_estimation_demo.sh] 'single_human_pose_estimation_demo' Run !!

• 実行例「Ubuntu on VirtualBox Core™ i7-6700」+ NCS2

  $ cd ~/run_app/
  $ ./_single_human_pose_estimation_demo_16.sh 
  [single_human_pose_estimation_demo_16.sh] 'single_human_pose_estimation_demo (NCS2)' Run !!
  Killed

速度比較 †

Interactive Face Detection C++ Demo †

デモの実行 †

• 実行例「Ubuntu on VirtualBox Core™ i7-6700」

  $ cd ~/run_app/
  $ ./_interactive_face_detection_demo.sh 
  [interactive_face_detection_demo.sh] 'interactive_face_detection_demo' Run !!
  InferenceEngine: 	API version ......... 2.1
  	Build ........... 2021.3.0-2787-60059f2c755-releases/2021/3
  [ INFO ] Parsing input parameters
  [ INFO ] Loading device CPU
  [ INFO ] 	CPU
  	MKLDNNPlugin version ......... 2.1
  	Build ........... 2021.3.0-2787-60059f2c755-releases/2021/3
  
  [ INFO ] Loading network files for Face Detection
  [ INFO ] Batch size is set to 1
  [ INFO ] Checking Face Detection network inputs
  [ INFO ] Checking Face Detection network outputs
  [ INFO ] Loading Face Detection model to the CPU device
  [ INFO ] Loading network files for Age/Gender Recognition network
  [ INFO ] Batch size is set to 16 for Age/Gender Recognition network
  [ INFO ] Checking Age/Gender Recognition network inputs
  [ INFO ] Checking Age/Gender Recognition network outputs
  [ INFO ] Loading Age/Gender Recognition model to the CPU plugin
  [ INFO ] Loading network files for Head Pose Estimation network
  [ INFO ] Batch size is set to  16 for Head Pose Estimation network
  [ INFO ] Checking Head Pose Estimation network inputs
  [ INFO ] Checking Head Pose Estimation network outputs
  [ INFO ] Loading Head Pose Estimation model to the CPU plugin
  [ INFO ] Loading network files for Emotions Recognition
  [ INFO ] Batch size is set to 16 for Emotions Recognition
  [ INFO ] Checking Emotions Recognition network inputs
  [ INFO ] Checking Emotions Recognition network outputs
  [ INFO ] Loading Emotions Recognition model to the CPU plugin
  [ INFO ] Loading network files for Facial Landmarks Estimation
  [ INFO ] Batch size is set to  16 for Facial Landmarks Estimation network
  [ INFO ] Checking Facial Landmarks Estimation network inputs
  [ INFO ] Checking Facial Landmarks Estimation network outputs
  [ INFO ] Loading Facial Landmarks Estimation model to the CPU plugin
  [ INFO ] Loading network files for Antispoofing Classifier network
  [ INFO ] Batch size is set to 16 for Antispoofing Classifier network
  [ INFO ] Checking Antispoofing Classifier network inputs
  [ INFO ] Checking Antispoofing Classifier network outputs
  [ INFO ] Loading Antispoofing Classifier model to the CPU plugin
  To close the application, press 'CTRL+C' here or switch to the output window and press Q or Esc
  [ INFO ] Number of processed frames: 43
  [ INFO ] Total image throughput: 4.88887 fps
  
  [ INFO ] Execution successful

• 実行例「Ubuntu on VirtualBox Core™ i7-6700」+ NCS2

  $ cd ~/run_app/
  $ ./_interactive_face_detection_demo_16.sh 
  [interactive_face_detection_demo_16.sh] 'interactive_face_detection_demo (NCS2)' Run !!
  InferenceEngine: 	API version ......... 2.1
  	Build ........... 2021.3.0-2787-60059f2c755-releases/2021/3
  [ INFO ] Parsing input parameters
  [ INFO ] Loading device MYRIAD
  [ INFO ] 	MYRIAD
  	myriadPlugin version ......... 2.1
  	Build ........... 2021.3.0-2787-60059f2c755-releases/2021/3
  
  [ INFO ] Loading network files for Face Detection
  [ INFO ] Batch size is set to 1
  [ INFO ] Checking Face Detection network inputs
  [ INFO ] Checking Face Detection network outputs
  [ INFO ] Loading Face Detection model to the MYRIAD device
  [ INFO ] Loading network files for Age/Gender Recognition network
  [ INFO ] Batch size is set to 16 for Age/Gender Recognition network
  [ INFO ] Checking Age/Gender Recognition network inputs
  [ INFO ] Checking Age/Gender Recognition network outputs
  [ INFO ] Loading Age/Gender Recognition model to the MYRIAD plugin
  [ INFO ] Loading network files for Head Pose Estimation network
  [ INFO ] Batch size is set to  16 for Head Pose Estimation network
  [ INFO ] Checking Head Pose Estimation network inputs
  [ INFO ] Checking Head Pose Estimation network outputs
  [ INFO ] Loading Head Pose Estimation model to the MYRIAD plugin
  [ INFO ] Loading network files for Emotions Recognition
  [ INFO ] Batch size is set to 16 for Emotions Recognition
  [ INFO ] Checking Emotions Recognition network inputs
  [ INFO ] Checking Emotions Recognition network outputs
  [ INFO ] Loading Emotions Recognition model to the MYRIAD plugin
  [ INFO ] Loading network files for Facial Landmarks Estimation
  [ INFO ] Batch size is set to  16 for Facial Landmarks Estimation network
  [ INFO ] Checking Facial Landmarks Estimation network inputs
  [ INFO ] Checking Facial Landmarks Estimation network outputs
  [ INFO ] Loading Facial Landmarks Estimation model to the MYRIAD plugin
  [ INFO ] Loading network files for Antispoofing Classifier network
  [ INFO ] Batch size is set to 16 for Antispoofing Classifier network
  [ INFO ] Checking Antispoofing Classifier network inputs
  [ INFO ] Checking Antispoofing Classifier network outputs
  [ INFO ] Loading Antispoofing Classifier model to the MYRIAD plugin
  To close the application, press 'CTRL+C' here or switch to the output window and press Q or Esc
  [ INFO ] Number of processed frames: 16
  [ INFO ] Total image throughput: 2.38246 fps
  
  E: [global] [    987123] [interactive_fac] XLink_sem_wait:94	 XLink_sem_inc(sem) method call failed with an error: -1
  E: [global] [    987124] [interactive_fac] XLinkResetRemote:257	can't wait dispatcherClosedSem
  
  [ INFO ] Execution successful

速度比較 †

Gaze Estimation Demo †

デモの実行 †

• 実行例「Ubuntu on VirtualBox Core™ i7-6700」

  $ cd ~/run_app/
  $ ./_gaze_estimation_demo.sh 
  [gaze_estimation_demo.sh] 'gaze_estimation_demo' Run !!
  InferenceEngine: 	API version ......... 2.1
  	Build ........... 2021.3.0-2787-60059f2c755-releases/2021/3
  [ INFO ] Parsing input parameters
  [ INFO ] Loading device CPU
  [ INFO ] 	CPU
  	MKLDNNPlugin version ......... 2.1
  	Build ........... 2021.3.0-2787-60059f2c755-releases/2021/3
  
  
  [ INFO ] Execution successful

• 実行例「Ubuntu on VirtualBox Core™ i7-6700」+ NCS2

  $ cd ~/run_app/
  $ ./_gaze_estimation_demo_16.sh 
  [gaze_estimation_demo_16.sh] 'gaze_estimation_demo (NCS2)' Run !!
  InferenceEngine: 	API version ......... 2.1
  	Build ........... 2021.3.0-2787-60059f2c755-releases/2021/3
  [ INFO ] Parsing input parameters
  [ INFO ] Loading device MYRIAD
  [ INFO ] 	MYRIAD
  	myriadPlugin version ......... 2.1
  	Build ........... 2021.3.0-2787-60059f2c755-releases/2021/3
  
  [ INFO ] Loading device MYRIAD
  [ INFO ] 	MYRIAD
  	myriadPlugin version ......... 2.1
  	Build ........... 2021.3.0-2787-60059f2c755-releases/2021/3
  
  [ INFO ] Loading device MYRIAD
  [ INFO ] 	MYRIAD
  	myriadPlugin version ......... 2.1
  	Build ........... 2021.3.0-2787-60059f2c755-releases/2021/3
  
  [ INFO ] Loading device MYRIAD
  [ INFO ] 	MYRIAD
  	myriadPlugin version ......... 2.1
  	Build ........... 2021.3.0-2787-60059f2c755-releases/2021/3
  
  [ INFO ] Loading device MYRIAD
  [ INFO ] 	MYRIAD
  	myriadPlugin version ......... 2.1
  	Build ........... 2021.3.0-2787-60059f2c755-releases/2021/3
  
  
  [ INFO ] Execution successful

速度比較] †

Security Barrier Camera C++ Demo †

デモの実行] †

• 実行例「Ubuntu Core™ i7-6700」

  $ cd ~/run_app/
  $ ./_security_barrier_camera_demo.sh 
  [security_barrier_camera_demo.sh] 'security_barrier_camera_demo' Run !!
  [ INFO ] InferenceEngine: 	API version ......... 2.1
  	Build ........... 2021.3.0-2787-60059f2c755-releases/2021/3
  [ INFO ] Files were added: 1
  [ INFO ]     /home/mizutu/Videos/car-detection.mp4
  [ INFO ] Loading device CPU
  [ INFO ] 	CPU
  	MKLDNNPlugin version ......... 2.1
  	Build ........... 2021.3.0-2787-60059f2c755-releases/2021/3
  
  [ INFO ] Loading detection model to the CPU plugin
  [ INFO ] Loading Vehicle Attribs model to the CPU plugin
  [ INFO ] Loading Licence Plate Recognition (LPR) model to the CPU plugin
  [ INFO ] Number of InferRequests: 1 (detection), 3 (classification), 3 (recognition)
  [ INFO ] 1 streams for CPU
  [ INFO ] Display resolution: 1920x1080
  [ INFO ] Number of allocated frames: 3
  [ INFO ] Resizable input with support of ROI crop and auto resize is disabled
  54.3FPS for (375 / 1) frames
  Detection InferRequests usage: 100.0%
  
  [ INFO ] Execution successful

• 実行例「Ubuntu on VirtualBox Core™ i7-6700」+ NCS2

  $ cd ~/run_app/
  $ ./_security_barrier_camera_demo_16.sh 
  mizutu@ubuntu-vbox2:~/run_app$ ./_security_barrier_camera_demo_16.sh
  [security_barrier_camera_demo_16.sh] 'security_barrier_camera_demo (NCS2)' Run !!
  [ INFO ] InferenceEngine: 	API version ......... 2.1
  	Build ........... 2021.3.0-2787-60059f2c755-releases/2021/3
  [ INFO ] Files were added: 1
  [ INFO ]     /home/mizutu/Videos/car-detection.mp4
  [ INFO ] Loading device MYRIAD
  [ INFO ] 	MYRIAD
  	myriadPlugin version ......... 2.1
  	Build ........... 2021.3.0-2787-60059f2c755-releases/2021/3
  
  [ INFO ] Loading detection model to the MYRIAD plugin
  [ INFO ] Loading Vehicle Attribs model to the MYRIAD plugin
  [ INFO ] Loading Licence Plate Recognition (LPR) model to the MYRIAD plugin
  [ INFO ] Number of InferRequests: 1 (detection), 3 (classification), 3 (recognition)
  [ INFO ] Display resolution: 1920x1080
  [ INFO ] Number of allocated frames: 3
  [ INFO ] Resizable input with support of ROI crop and auto resize is disabled
  33.0FPS for (375 / 1) frames
  Detection InferRequests usage: 100.0%
  
  E: [global] [    289604] [security_barrie] XLink_sem_wait:94	 XLink_sem_inc(sem) method call failed with an error: -1
  E: [global] [    289604] [security_barrie] XLinkResetRemote:257	can't wait dispatcherClosedSem
  
  [ INFO ] Execution successful

速度比較 †

Image Inpainting Python Demo †

デモの実行 †

• 実行例「Ubuntu Core™ i7-6700」

  $cd ~/run_app
  $ ./_image_inpainting_demo.sh
  [image_inpainting_demo.sh] 'image_inpainting_demo' Run !!

• 実行例「Ubuntu on VirtualBox Core™ i7-6700」+ NCS2

  $ cd ~/run_app/
  $ ./_image_inpainting_demo_16.sh
  [image_inpainting_demo_16.sh] 'image_inpainting_demo (NCS2)' Run !!
  E: [global] [    635158] [python3] XLink_sem_wait:94	 XLink_sem_inc(sem) method call failed with an error: -1
  E: [global] [    635158] [python3] XLinkResetRemote:257	can't wait dispatcherClosedSem

Colorization Python Demo †

デモの実行 †

• 実行例「Ubuntu Core™ i7-6700」

  $ cd ~/run_app
  $ ./_colorization_demo.sh
  [colorization_demo.sh] 'colorization_demo' Run !!

• 実行例「Ubuntu on VirtualBox Core™ i7-6700」+ NCS2

  $ cd ~/run_app/
  $ ./_colorization_demo_16.sh
  [colorization_demo_16.sh] 'colorization_demo (NCS2)' Run !!
  
  E: [global] [    657488] [python3] XLink_sem_wait:94	 XLink_sem_inc(sem) method call failed with an error: -1
  E: [global] [    657488] [python3] XLinkResetRemote:257	can't wait dispatcherClosedSem

Image Deblurring Python* Demo †

デモの実行 †

• 実行例「Ubuntu Core™ i7-6700」

  $ cd ~/run_app
  $ ./_deblurring_demo.sh
  [deblurring_demo.sh] 'deblurring_demo' Run !!
  [ INFO ] Initializing Inference Engine...
  [ INFO ] Loading network...
  [ INFO ] Reading network from IR...
  [ INFO ] Loading network to CPU plugin...
  [ INFO ] Starting inference...
  To close the application, press 'CTRL+C' here or switch to the output window and press ESC key
  Latency: 540.3 ms
  FPS: 1.8

• 実行例「Ubuntu on VirtualBox Core™ i7-6700」+ NCS2

  $ cd ~/run_app/
  $ ./_deblurring_demo_16.sh
  [deblurring_demo_16.sh] 'deblurring_demo (NCS2)' Run !!
  [ INFO ] Initializing Inference Engine...
  [ INFO ] Loading network...
  [ INFO ] Reading network from IR...
  [ INFO ] Loading network to MYRIAD plugin...
  [ INFO ] Starting inference...
  To close the application, press 'CTRL+C' here or switch to the output window and press ESC key
  Latency: 589.6 ms
  FPS: 1.6
  
  E: [global] [    797252] [python3] XLink_sem_wait:94	 XLink_sem_inc(sem) method call failed with an error: -1
  E: [global] [    797252] [python3] XLinkResetRemote:257	can't wait dispatcherClosedSem

Hello Query Device Python* Sample †

デモの実行 †

• 実行例「Ubuntu on VirtualBox Core™ i7-6700」+ NCS2

  $ cd ~/run_app/
  $ ./_hello_query_device.sh
  [hello_query_device.sh] 'hello_query_device' Run !!
  Available devices:
  [E:] [BSL] found 0 ioexpander device
  	Device: CPU
  	Metrics:
  		AVAILABLE_DEVICES: 
  		SUPPORTED_METRICS: AVAILABLE_DEVICES, SUPPORTED_METRICS, FULL_DEVICE_NAME, OPTIMIZATION_CAPABILITIES, SUPPORTED_CONFIG_KEYS, RANGE_FOR_ASYNC_INFER_REQUESTS, RANGE_FOR_STREAMS
  		FULL_DEVICE_NAME: Intel(R) Core(TM) i7-6700 CPU @ 3.40GHz
  		OPTIMIZATION_CAPABILITIES: FP32, FP16, INT8, BIN
  		SUPPORTED_CONFIG_KEYS: CPU_BIND_THREAD, CPU_THREADS_NUM, CPU_THROUGHPUT_STREAMS, DUMP_EXEC_GRAPH_AS_DOT, DYN_BATCH_ENABLED, DYN_BATCH_LIMIT, ENFORCE_BF16, EXCLUSIVE_ASYNC_REQUESTS, PERF_COUNT
  		RANGE_FOR_ASYNC_INFER_REQUESTS: 1, 1, 1
  		RANGE_FOR_STREAMS: 1, 1
  
  	Default values for device configuration keys:
  		CPU_BIND_THREAD: YES
  		CPU_THREADS_NUM: 0
  		CPU_THROUGHPUT_STREAMS: 1
  		DUMP_EXEC_GRAPH_AS_DOT: 
  		DYN_BATCH_ENABLED: NO
  		DYN_BATCH_LIMIT: 0
  		ENFORCE_BF16: NO
  		EXCLUSIVE_ASYNC_REQUESTS: NO
  		PERF_COUNT: NO
  	Device: GNA
  	Metrics:
  		GNA_LIBRARY_FULL_VERSION: 2.0.0.1047
  		FULL_DEVICE_NAME: GNA_SW
  		OPTIMAL_NUMBER_OF_INFER_REQUESTS: 1
  		SUPPORTED_CONFIG_KEYS: EXCLUSIVE_ASYNC_REQUESTS, GNA_COMPACT_MODE, GNA_DEVICE_MODE, GNA_FIRMWARE_MODEL_IMAGE, GNA_FIRMWARE_MODEL_IMAGE_GENERATION, GNA_LIB_N_THREADS, GNA_PRECISION, GNA_PWL_UNIFORM_DESIGN, GNA_SCALE_FACTOR, GNA_SCALE_FACTOR_0, PERF_COUNT, SINGLE_THREAD
  		SUPPORTED_METRICS: GNA_LIBRARY_FULL_VERSION, FULL_DEVICE_NAME, OPTIMAL_NUMBER_OF_INFER_REQUESTS, SUPPORTED_CONFIG_KEYS, SUPPORTED_METRICS, AVAILABLE_DEVICES
  		AVAILABLE_DEVICES: GNA_SW
  
  	Default values for device configuration keys:
  		EXCLUSIVE_ASYNC_REQUESTS: NO
  		GNA_COMPACT_MODE: NO
  		GNA_DEVICE_MODE: GNA_SW_EXACT
  		GNA_FIRMWARE_MODEL_IMAGE: 
  		GNA_FIRMWARE_MODEL_IMAGE_GENERATION: 
  		GNA_LIB_N_THREADS: 1
  		GNA_PRECISION: I16
  		GNA_PWL_UNIFORM_DESIGN: NO
  		GNA_SCALE_FACTOR: 1.000000
  		GNA_SCALE_FACTOR_0: 1.000000
  		PERF_COUNT: NO
  		SINGLE_THREAD: YES
  	Device: MYRIAD
  	Metrics:
  		DEVICE_THERMAL: UNSUPPORTED TYPE
  		OPTIMIZATION_CAPABILITIES: FP16
  		RANGE_FOR_ASYNC_INFER_REQUESTS: 3, 6, 1
  		SUPPORTED_METRICS: DEVICE_THERMAL, OPTIMIZATION_CAPABILITIES, RANGE_FOR_ASYNC_INFER_REQUESTS, SUPPORTED_METRICS, SUPPORTED_CONFIG_KEYS, FULL_DEVICE_NAME, AVAILABLE_DEVICES
  		SUPPORTED_CONFIG_KEYS: DEVICE_ID, EXCLUSIVE_ASYNC_REQUESTS, LOG_LEVEL, VPU_MYRIAD_FORCE_RESET, VPU_MYRIAD_PLATFORM, VPU_CUSTOM_LAYERS, PERF_COUNT, VPU_PRINT_RECEIVE_TENSOR_TIME, CONFIG_FILE, VPU_HW_STAGES_OPTIMIZATION, MYRIAD_THROUGHPUT_STREAMS, MYRIAD_ENABLE_FORCE_RESET, MYRIAD_ENABLE_RECEIVING_TENSOR_TIME, MYRIAD_CUSTOM_LAYERS, MYRIAD_ENABLE_HW_ACCELERATION
  		FULL_DEVICE_NAME: Intel Movidius Myriad X VPU
  		AVAILABLE_DEVICES: 1.2-ma2480
  
  	Default values for device configuration keys:
  		DEVICE_ID: 
  		EXCLUSIVE_ASYNC_REQUESTS: NO
  		LOG_LEVEL: LOG_NONE
  		VPU_MYRIAD_FORCE_RESET: NO
  		VPU_MYRIAD_PLATFORM: 
  		VPU_CUSTOM_LAYERS: 
  		PERF_COUNT: NO
  		VPU_PRINT_RECEIVE_TENSOR_TIME: NO
  		CONFIG_FILE: 
  		VPU_HW_STAGES_OPTIMIZATION: YES
  		MYRIAD_THROUGHPUT_STREAMS: -1
  		MYRIAD_ENABLE_FORCE_RESET: NO
  		MYRIAD_ENABLE_RECEIVING_TENSOR_TIME: NO
  		MYRIAD_CUSTOM_LAYERS: 
  		MYRIAD_ENABLE_HW_ACCELERATION: YES

テスト環境 †

• Intel® NUC キット BXNUC10I5FNH
  
  • CPU Intel® Core™ i5-10210U CPU
    
  • OS Ubuntu20.04LTS
    
  • OpenVINO™ Toolkit for Linux 2021.2
    
  • OpenVINO™ Toolkit for Linux 2021.3
    

• HP EliteDesk 800 G2 SFF
  
  • CPU Intel® Core™ i7-6700 CPU @ 3.40GHz
    
  • OS Ubuntu20.04LTS (Hyper-V on Windows 10 Pro 64 bit)
    
  • OpenVINO™ Toolkit for Linux 2021.2
    
  • OpenVINO™ Toolkit for Linux 2021.3
    

• IntelR NUC キット BOXNUC7CJYH
  
  • CPU Intel® Celeron® J4005 Processor (4M Cache, up to 2.70 GHz)
    
  • OS Ubuntu20.04LTS
    
  • OpenVINO™ Toolkit for Linux 2021.2
    
  • OpenVINO™ Toolkit for Linux 2021.3
    

• Panasonic CF-B10BWJYS
  
  • CPU Intel® Core™ i7-6700 vPro CPU @ 2.60GHz
    
  • OS Ubuntu20.04LTS (Hyper-V on Windows 10 Pro 64 bit)
    
  • OpenVINO™ Toolkit for Linux 2021.2
    
  • OS Ubuntu20.04LTS (VirtualBox on Windows 10 Pro 64 bit)
    
  • OpenVINO™ Toolkit for Linux 2021.3
    

更新履歴 †

• 2021/05/18 初版
   

参考資料 †

• オフィシャルサイト
  • Intel® OpenVINO™ Toolkit Storage
    
  • Install Intel® Distribution of OpenVINO™ toolkit for Linux*「latest」
    
  • Get Started with OpenVINO™ Toolkit on Linux*
    
  • Open Model Zoo Demos「latest」