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1. To record mask (body-based segmentation) to the archive (see Displaying information from a detection tool (mask)), select Yes in the corresponding parameter (1).
   
2. By default, metadata is not recorded to the database. To enable metadata recording, select Yes in the Record objects tracking parameter (2).

3. If the camera supports multistreaming, select the stream for which detection is needed (3). 

4. By default, the following neural networks are initialized: Classification neural network (equipment and PPE on the head) and Classification neural network (equipment and PPE on the body) according to the selected processing device (9). To initialize only one item of equipment, select the required classification neural network file (4). There must be a separate classification neural network to recognize equipment on each body segment. The standard classification neural networks for different processor types are located in the C:\Program Files\Common Files\Grundig\DetectorPack\NeuroSDK directory. You don't need to select the standard neural networks in this field, the system will automatically select the required one. If you use a custom neural network, specify the path to the file (4).

   Info
   title Note
   To ensure the correct operation of the neural network on Linux OS, the corresponding file must be located in the /opt/Grundig/DetectorPack/NeuroSDK directory.

5. Select a processing resource for decoding video streams (5). 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 (see General information on configuring detection).

6. Set the frame rate value for the detection tool to process per second (6). This value must be in the range [0.016; 100]. 

   Note
   title Attention!
   To apply detection in gateway mode (see Examples of configuring Equipment detection tool (PPE) for solving typical tasks), we recommend that you use the detection tool standard settings: 1 FPS and 3 frames for output (see step 10). To apply detection in continuous mode for busy scenes, set the delay to no less than 4 FPS, and the number of frames for output to no less than 6.

   
   

7. Set the minimum height and width of a person (7, 8) in the frame as a percentage of the frame height/width (0,15 = 15%). Objects which are smaller than the specified size will not be detected. The value must be in the range [0; 1].

8. Select the processor for the neural network—CPU, one of Nvidia GPUs or one of Intel GPUs (9, see Hardware requirements for neural analytics operation, 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 can use caching to speed up future launches (see Optimizing the operation of neural analytics on GPU). 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. If you select Intel HDDL, due to the features of the device, only the segmenting neural network will be processed on it, the CPU will be used to run the classification neural networks. Starting with Detector Pack 3.11, Intel HDDL and Intel NCS aren’t supported.

   
   

9. By default, the segmenting neural network is initialized according to the selected processing device (9). The standard segmenting neural networks for different processor types are located in the C:\Program Files\Common Files\Grundig\DetectorPack\NeuroSDK directory. You don't need to select the standard neural networks in this field, the system will automatically select the required one. If you use a custom neural network, specify the path to the file (10).

   Info

   title	Note

   To ensure the correct operation of the neural network in Linux OS, the corresponding file must be located in the /opt/Grundig/DetectorPack/NeuroSDK directory. 

10. Enable the Mask parameter to display body segments in the preview window (11).
11. Set the minimum number of frames containing people with no PPE for the tool to trigger (12). The value must be in the range [1; 20].

12. By default, each equipment element triggering occurs once during a continuous tracking of a person. You can set triggering to multiple by setting the One event per PPE element parameter to No (13).

    Info
    title Note
    Example. An individual not wearing a helmet appears in the FOV, puts on a helmet, then puts it off. If the One event per PPE element parameter is enabled, you will have one alarm event, otherwise two.

    
    

13. In the preview window, you can set the detection areas with the help of anchor points, much like privacy masks in Scene Analytics detection tools (see Setting General Zones for Scene analytics detection tools). By default, the entire FOV is a detection area.
14. Click the Apply button.

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