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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 Displaying information from a detection tool (mask)), select Yes for in the corresponding parameter (1).
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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. By default, the following neural networks are used according to the selected processing device (8)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 required classification neural network file (34). There should   be a separate classification   neural network to recognize equipment on each body segment. The following standard classification neural networks for different processor types are located in the C:\Program Files\Common Files\AxxonSoft\DetectorPack\NeuroSDK directory:
   

   ppeHelmet(head)General_movidius.annClassification neural network (head) / IntelNCS ppeHelmet(head)General_openvino.annClassification neural network (head) / CPUppeHelmet(head)General_origin.annClassification neural network (head) / GPUppeSafetyVest(body)General_movidius.annClassification neural network (body) / IntelNCS ppeSafetyVest(body)General_openvino.annClassification neural network (body) / CPUppeSafetyVest(body)General_origin.annClassification neural network (body) / GPU

   . 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, it is necessary to specify the path to the file (34).

   Info
   title Note
   To ensure the correct operation of the neural network in 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!
   It may take several minutes to launch the algorithm on an NVIDIA GPU after you apply the settings. 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 CPU will also be used to run the detection tool will consume CPU as well. If you have Intel HDDL selected, it can host process only the segmenting neural networks. The CPU will handle process the classifying networks.

   
   

   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 Configuring the acceleration of GPU-based neuroanalytics).

   
   

9. By default, the Segmenting neural network (head, body) is used initialized according to the selected processing device (89). The following standard segmenting neural networks for different processor types are located in the C:\Program Files\Common Files\AxxonSoft\DetectorPack\NeuroSDK directory:
   

   ppeSegmentationByPose_movidius.annSegmenting neural network (head, body) / IntelNCS ppeSegmentationByPose_openvino.annSegmenting neural network (head, body)/ CPUppeSegmentationByPose_origin_onnx.annSegmenting neural network (head, body) / GPU

   . 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, it is necessary to specify the path to the file (910).
   

   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. Select Enable the Mask checkbox parameter to display body segments in the preview window (1011).Image Removed
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 the 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 is a detection zonearea.
14. Click the Apply button.

The Equipment detection tool (PPE) is now configured. 

The 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 the FOV.

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 RemovedImage Added
2. Vests:
   1. Yellow.
   2. Orange.
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