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1. To record mask to the archive (see Extra information overlay (Masks)), set Yes for the corresponding parameter (1).
   
2. If the camera supports multistreaming, select the stream for which detection is needed (2). 
3. 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.

4. Set the frame rate value for the detection tool to process per second (4). This value should be in the range [0.,016; 100]. 

5. Select the processor for the neural network – CPU, one of NVIDIA GPUs, or one of Intel GPUs (5, see Hardware requirements for neural analytics operation, General Information on Configuring Detection).

   Note
   title Attention!
   If you specify other processing resource than the CPU, this device will carry the most of computing load. However, the CPU will also be used to run the detection tool.

   
   

   Note
   title Attention!
   It may take several minutes to launch the algorithm on NVIDIA GPU after you apply the settings. You can use caching to speed up future launches (see see Configuring the acceleration of GPU-based neuroanalytics).

   
   

6. Select the segmenting neural network file (6). The following standard neural networks for different processor types are located in the C:\Program Files\Common Files\AxxonSoft\DetectorPack\NeuroSDK directory:

   poseEstimator_openvino.ann	Person-based privacy masking / CPU
   poseEstimator_original.ann	Person-based privacy masking / GPU
   poseEstimator_movidius.ann	Person-based privacy masking / IntelNCS

   Enter full path to a custom neural network file into this field. This is not required if you use standard neural networks which are selected automatically.

   Info
   title Note
   For correct neural network operation on Linux, place the corresponding file in the /opt/AxxonSoft/DetectorPack/NeuroSDK directory.

   
   

7. Set the minimum number of frames in which the detection tool should detect objects in order to trigger (7). The value should be in the range [1; 20].
8. Select Yes for all body parts that should be masked within FOV.
9. Click the Apply button.

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