miamor / openvino_face_recognition

Creating a Gallery for Face Recognition

To recognize faces on a frame, the demo needs a gallery of reference images. Each image should contain a tight crop of face. You can create the gallery from an arbitrary list of images:

1. Put images containing tight crops of frontal-oriented faces to a separate empty folder. Each identity could have multiple images. Name images as id_name.0.png, id_name.1.png, ....
2. Run the create_list.py <path_to_folder_with_images> command to get a list of files and identities in .json format.

Running

Running the application with the -h option yields the following usage message:

./face_recognition -h
InferenceEngine:
    API version ............ <version>
    Build .................. <number>

face_recognition [OPTION]
Options:

    -h                             Print a usage message.
    -i '<path>'                    Required. Path to a video or image file. Default value is "cam" to work with camera.
    -m_fd '<path>'                 Required. Path to the Face Detection Retail model (.xml) file.
    -m_lm '<path>'                 Required. Path to the Facial Landmarks Regression Retail model (.xml) file.
    -m_reid '<path>'               Required. Path to the Face Reidentification Retail model (.xml) file.
    -l '<absolute_path>'           Optional. For CPU custom layers, if any. Absolute path to a shared library with the kernels implementation.
          Or
    -c '<absolute_path>'           Optional. For GPU custom kernels, if any. Absolute path to an .xml file with the kernels description.
    -d_fd '<device>'               Optional. Specify the target device for Face Detection Retail (CPU, GPU, FPGA, HDDL, MYRIAD, or HETERO).
    -d_lm '<device>'               Optional. Specify the target device for Landmarks Regression Retail (CPU, GPU, FPGA, HDDL, MYRIAD, or HETERO). 
    -d_reid '<device>'             Optional. Specify the target device for Face Reidentification Retail (CPU, GPU, FPGA, HDDL, MYRIAD, or HETERO). 
    -out_v  '<path>'               Optional. File to write output video with visualization to.
    -pc                            Optional. Enables per-layer performance statistics.
    -r                             Optional. Output Inference results as raw values.
    -t_fd                          Optional. Probability threshold for face detections.
    -inh_fd                        Optional. Input image height for face detector.
    -inw_fd                        Optional. Input image width for face detector.
    -exp_r_fd                      Optional. Expand ratio for bbox before face recognition.
    -t_reid                        Optional. Cosine distance threshold between two vectors for face reidentification.
    -fg                            Optional. Path to a faces gallery in .json format.
    -no_show                       Optional. Do not show processed video.
    -last_frame                    Optional. Last frame number to handle in demo. If negative, handle all input video.
    -crop_gallery                  Optional. Crop images during faces gallery creation.
    -t_reg_fd                      Optional. Probability threshold for face detections during database registration.
    -min_size_fr                   Optional. Minimum input size for faces during database registration.
    -ss_t                          Optional. Number of frames to smooth actions.
    -roi                           Optional. Enable roi

Running the application with the empty list of options yields the usage message given above and an error message.

To run the demo, you can use public or pre-trained models. To download the pre-trained models, use the OpenVINO Model Downloader or go to https://download.01.org/opencv/.

NOTE: Before running the demo with a trained model, make sure the model is converted to the Inference Engine format (*.xml + *.bin) using the Model Optimizer tool.

Example of a valid command line to run the application with pre-trained models for recognizing identities from faces_gallery:

./face_recognition  -m_fd <path_to_model>/face-detection-retail-0004.xml \
                    -m_reid <path_to_model>/face-reidentification-retail-0095.xml \
                    -m_lm <path_to_model>/landmarks-regression-retail-0009.xml \
                    -fg <path_to_faces_gallery.json> \
                    -i <path_to_video>
./face_recognition  -m_fd <path_to_model>/face-detection-retail-0004.xml \
                    -m_reid <path_to_model>/face-reidentification-retail-0095.xml \
                    -m_lm <path_to_model>/landmarks-regression-retail-0009.xml \
                    -fg <path_to_faces_gallery.json> \
                    -i <path_to_video> \
                    -roi