Documentation for Axxon One 1.0.

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Video stream and scene requirements for Equipment detection tool (PPE) operation

Objects image requirements for Equipment detection tool (PPE)

Hardware requirements for neural analytics operation

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

  1. To record mask (body-based segmentation) to archive select Yes for the corresponding parameter (1).

  2. If the camera supports multistreaming, select the stream for which detection is needed (2). 

  3. By default, the following neural networks are used according to the selected processing device (8): Classification neural network (head) and Classification neural network (body). To initialize only one item of equipment, select the required classification neural network file (3). 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.annClassification neural network (head) / IntelNCS 
    ppeHelmet(head)General_openvino.annClassification neural network (head) / CPU
    ppeHelmet(head)General_origin.annClassification neural network (head) / GPU
    ppeSafetyVest(body)General_movidius.annClassification neural network (body) / IntelNCS 
    ppeSafetyVest(body)General_openvino.annClassification neural network (body) / CPU
    ppeSafetyVest(body)General_origin.annClassification neural network (body) / GPU

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

    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. 

  4. Select a processing resource for decoding video streams (4). When you select a GPU, a stand-alone graphics card takes priority (when decoding with NVidia NVDEC chips). If there's no appropriate GPU, the decoding will use the Intel Quick Sync Video technology. Otherwise, CPU resources will be used for decoding.

  5. Set the frame rate value for the detection tool to process (5). This value should be in the range [0.016, 100]. 

    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 fps, and the number of frames to no less than 6.

  6. Set the minimum height and width of a person (6, 7) 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.

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

    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).

    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.

  8. By default, the Segmenting neural network (head, body) is used according to the selected processing device (8). The following 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) / CPU
    ppeSegmentationByPose_origin_onnx.annSegmenting neural network (head, body) / GPU

    If you use a custom neural network, it is necessary to specify the path to the file (9).

    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. 

  9. Select the Mask checkbox to display body segments in the preview window (10).

  10. Set the minimum number of frames containing people with no PPE for triggering the tool − Number of measurements in a row to trigger detection (11). The value should be within the range of 2 – 20.

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

    Note

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

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

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 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.
  2. Vests:
    1. Yellow.
    2. Orange.

Attention!

To ensure the correct reception of E-mail notifications (see E-mail notification) after the Equipment detection tool (PPE) is triggered, it is necessary to set up a separate macro command with an E-mail message for each item of equipment.

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