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To set up configure the equipment Equipment detection tool (PPE), do the following:

1. To record mask (body-based segmentation) to the archive (see Extra information overlay (Masks)), select Yes for 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 (23). 

4. Select one or several files for the classifying neural network (3). There must be a separate classifying

   By default, the following neural networks are used according to the selected processing device (9): Classification neural network (head) and Classification neural network (body). To initialize only one item of equipment, select the required classification neural network file (4). There should be a separate classification neural network to recognize equipment on each body segment. The following classification neural networks for different processor types are located in the C:\Program Files\Common Files\AxxonSoft\DetectorPack\NeuroSDK directory:
   

   ppeHelmet(head)General_movidius.ann	Classification neural network (head) / IntelNCS
   ppeHelmet(head)General_openvino.ann	Classification neural network (head) / CPU
   ppeHelmet(head)General_origin.ann	Classification neural network (head) / GPU
   ppeSafetyVest(body)General_movidius.ann	Classification neural network (body) / IntelNCS
   ppeSafetyVest(body)General_openvino.ann	Classification neural network (body) / CPU
   ppeSafetyVest(body)General_origin.ann	Classification neural network (body) / GPU

   If you use a custom neural network, it is necessary to specify the path to the file (3).

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

   
   

5. Select a processing resource for decoding video streams (45). When you select a GPU, a stand-alone graphics card takes priority (when decoding with NVidia NVIDIA NVDEC chips). If there 's 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 (56). This value should 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 i.10). To apply detection in continuous mode for busy scenes, set the delay to no less than 4 fpsFPS, and the number of frames for output to no less than 6.

   
   

7. Set the minimum height and width of a person (67, 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 should be in the range [0; 1].

8. Select the processor for the neural network − CPU, one of GPUs, or Intel processors (89, see Hardware requirements for neural analytics operation).

   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. If you have Intel HDDL selected, it can process only the segmenting neural networks. The CPU will process the classifying networks.

   
   

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

   Note
   title Attention!
   If you specify other processing resource than the CPU, this device will carry the most of computing load. However, the detection tool will consume CPU as well. If you have Intel HDDL selected, it can host only the segmenting neural networks. The CPU will handle the classifying networks.

   Select the segmenting neural network file (9).

   Note
   title Attention!
   To access the neural network, contact technical support https://support.axxonsoft.com/.

   
   

9. By default, the Segmenting neural network (head, body) is used according to the selected processing device (9). The following segmenting neural networks for different processor types are located in the C:\Program Files\Common Files\AxxonSoft\DetectorPack\NeuroSDK directory:
   

   ppeSegmentationByPose_movidius.ann	Segmenting neural network (head, body) / IntelNCS
   ppeSegmentationByPose_openvino.ann	Segmenting neural network (head, body)/ CPU
   ppeSegmentationByPose_origin_onnx.ann	Segmenting neural network (head, body) / GPU

   If you use a custom neural network, it is necessary to 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 should be located in the /opt/AxxonSoft/DetectorPack/NeuroSDK directory.

   
   

10. Enable the Mask parameter Select the Mask checkbox to display body segments in the preview window (1011).
11. Set the minimum number of frames containing people with no PPE for triggering the tool − Number of measurements in a row to trigger detection (11to trigger (12). The value should be within in the range of 2 – 20 [1; 20].

12. By default, each equipment element 's triggering occurs once during a continuous tracking of a human objectperson. You can set triggering to multiple by setting the One Event event per Equipment ElementPPE element parameter to No (1213).

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

    
    

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

The Equipment detection tool (PPE) is now configured. 

The equipment Equipment detection tool (PPE) triggers an alarm when a person not wearing required equipment (PPE) on specified body parts, or wearing inappropriate equipment, appears in FoVthe FOV.
Image Modified
The Equipment detection tool (PPE) recognizes equipment of the following colors:

1. Helmets:
   1. Yellow.
   2. White.
   3. Blue.
   4. Green.
   5. Orange.
   6. Black.
   7. Red.
      Image Added
2. Vests:
   1. Yellow.
   2. Orange.
      Image Added

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