README.md

Face Recognition demo with OpenVINO™ Toolkit

Demo Preparation

1. Install the OpenVINO™ toolkit

2. Create virtual python environment:

     mkvirtualenv fr --python=python3

3. Install dependencies:

     pip install -r requirements.txt

4. Initialize OpenVINO™ environment:

   source /opt/intel/computer_vision_sdk/bin/setupvars.sh

Deep Face Recognition

1. Set up the PATH_TO_GALLERY variable to point to the folder with gallery images (faces to be recognized):

   export PATH_TO_GALLERY=/path/to/gallery/with/images/
2. To use OpenVINO™ pretrained models, specify IR_MODELS_ROOT, otherwise modify the running command:

   export IR_MODELS_ROOT=$INTEL_OPENVINO_DIR/deployment_tools/intel_models/
3. If you are running from pure console, specify the PYTHONPATH variable:

   export PYTHONPATH=`pwd`:$PYTHONPATH
4. Run the 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 in the $INTEL_OPENVINO_DIR/inference_engine/lib/<system_name>/intel64/ folder, where the <system_name> is a name detected by OpenVINO™, for example, ubuntu_16.04 if you are running the demo under the Ubuntu 16.04 system. The folder with CPU extensions is already in LD_LIBRARY_PATH after initialization of the OpenVINO™ environment and can be omitted in the launch command.