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To configure face the basic Face detection toolstool, do as followsthe following:

1. Select the Facial Recognition Face detection object. 
   

2. If you need to use this detection tool for real-time facial face recognition, set the corresponding parameter to Yes (1, see seeConfiguring real-time facial face recognition).

3. If you need to enable recording of record metadata, set select Yes in from the Record Objects objects tracking field  list (2).
4. If the camera supports multistreaming, select the stream for which detection is needed (3). For  For the correct operation of the Facial Recognition Face detection, it is recommended to use a High-quality video stream.
5. If you need to use this facial recognition face detection tool in real-time together with FaceCube Recognition Server (see Configuring FaceCube integration), set Yes in for the Real-time recognition on external servicefield parameter (4).

6. If you need to save age and gender information for each recognized captured face in the database, set select Yes in the corresponding field (1). .

   Info
   title Note
   The average error in age recognition is 5 years.

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7. If you use a bi-spherical XingYun lens, the detector will analyze two 180^° spherical images by default (see Configuring fisheye fish-eye cameras). This may decrease recognition quality. To dewarp the image before detection, set select Yes in for the Camera transform field parameter (2). This parameter is also relevant for other types of image transformation as well. 
8. Select a processing resource for decoding video streams (3). When you select a GPU, a stand-alone graphics card takes priority (when decoding with NVIDIA NVDEC chips). If there is no appropriate GPU, the decoding will use the Intel Quick Sync Video technology. Otherwise, CPU resources will be used for decoding.
9. Set the time (in milliseconds) between face search operations in a video frame in the Faсe Face detection period (msec)  field field (4). Acceptable values range : is [1, ; 10000]. Increasing this value decreases the Server load, but this can result in some faces being undetected. 
10. If you need plan to apply the masks detection tool, set Yes in for the Face mask detectionfield  parameter (5, see Configuring masks detectionMasks Detection).
11. In some cases, the detection tool may mistake other object for a face. To Select Yes in the Filter false alarms field (6) to filter out non-facial face objects, select Yes in the Filter false alarms field while calculating the vector model of a face and its recording into the metadata DB (6). If the filtering is on, false results will appear in the detection feed (see Facial Face recognition and search), but will be ignored during searches in the archive.

12. Analyzed framed are scaled down to a specified resolution (7, 1920 pixels on the longer side). This is how it works:

    1. If the longer side of the source image exceeds the value specified in the Frame size change field, it is divided by two.

    2. If the resulting resolution falls below the specified value, it is used further.

    3. If the resulting resolution still exceeds the specified limit, it is divided by two, etc.

       Info
       title Note
       For example, the source image resolution is 2048*1536, and the specified value is set to1000. In this case, the source resolution will be halved two times (down to 512*384), as after the first division, the number of pixels on the longer side exceeds the limit (1024 > 1000).

       
       

       Info
       title Note
       If detection is performed on a higher resolution stream and detection errors occur, it is recommended to reduce the compression.

       
       

13. Specify the minimum and maximum sizes of the captured faces as a percentage of the frame size (8). 

14. In the Minimum threshold of face authenticity field, set the minimum level of face recognition accuracy for the creation of a track (9). You can set any value by trial-and-error; no . No less than 90 is recommended. The higher the value is, the fewer faces are detected, while the recognition accuracy increases.

15. Select the processor for the face detection − CPU or NVIDIA GPU (10) (, see General Information on Configuring Detection). 
    

    Note
    title Attention!
    It may take several minutes to launch the algorithm on NVIDIA GPU after you apply the settings. You should use caching to speed up future launches (see Optimization of Face detection on GPU).

    
    

16. If you use FaceCube integration (see Configuring FaceCube integration), activate the Send face imageimages parameter (11).

17. Enter the time in milliseconds after which the face track is considered to be lost in the Track loss time field (12). Acceptable values range : is [1, ; 10000]. This parameter applies when a face moves in a frame and gets hidden behind an obstacle for some time. If this time is less than the set value, the face will be recognized as the same..

18. If necessary, fine-tune the detection tool (see Fine-tuning the Face detection tool).

19. In the preview window, set the rectangular area of the frame in which you want to perform face detectionSelect a rectangular area to be searched for faces in the preview window. To select the area, move the anchor points .
    

20. Click the Apply button.

Configuration of general parameters for Facial Recognition The basic Face detection tool is now completeconfigured.