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Face Recognition demo with OpenVINO™ Toolkit

Demo Preparation

  1. Install OpenVINO Toolkit - Linux installation guide

  2. Create virtual python environment:

  mkvirtualenv fr --python=python3
  1. Install dependencies:
  pip install -r requirements.txt
  1. Initialize OpenVINO environment:
source /opt/intel/computer_vision_sdk/bin/setupvars.sh

Deep Face Recognition

  1. Set up PATH_TO_GALLERY variable to point to folder with gallery images (faces to be recognized):
export PATH_TO_GALLERY=/path/to/gallery/with/images/
  1. For using OpenVINO pretrained models, please specify IR_MODELS_ROOT, otherwise you need to modify running command.
export IR_MODELS_ROOT=$INTEL_CVSDK_DIR/deployment_tools/intel_models/
  1. If you are running from pure console, you need to specify PYTHONPATH variable:
export PYTHONPATH=`pwd`:$PYTHONPATH
  1. Run Face Recognition demo:
python demo/run_demo.py --path_to_gallery $PATH_TO_GALLERY --cam_id 0 \
  --fd_model $IR_MODELS_ROOT/face-detection-retail-0004/FP32/face-detection-retail-0004.xml \
  --fr_model $IR_MODELS_ROOT/face-reidentification-retail-0095/FP32/face-reidentification-retail-0095.xml  \
  --ld_model $IR_MODELS_ROOT/landmarks-regression-retail-0009/FP32/landmarks-regression-retail-0009.xml \
  -l libcpu_extension_avx2.so

Note: libcpu_extension_avx2.so is located at the $INTEL_CVSDK_DIR/inference_engine/lib/<system_name>/intel64/ folder. Here the <system_name> is a name detected by the OpenVINO. It can be for example ubuntu_16.04 if you are running the demo under Ubuntu 16.04 system. The folder with CPU extensions is already in LD_LIBRARY_PATH after initialization of the OpenVINO environment, that's why it can be omitted in the launch command.